Research classified by Journal of Economic Literature (JEL) codes

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Top JEL
/ C: Mathematical and Quantitative Methods
/ / C5: Econometric Modeling
/ / / C53: Forecasting and Prediction Models; Simulation Methods

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This JEL code is mentioned in the following RePEc Biblio entries:

1. > Econometrics > Forecasting

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This topic is covered by the following reading lists:

1. SOEP based publications
2. Socio-Economics of Innovation

2020

• Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2020. "Forecasting the US Dollar-Korean Won Exchange Rate: A Factor-Augmented Model Approach," Auburn Economics Working Paper Series auwp2020-02, Department of Economics, Auburn University.
• Glyn Wittwer & Kym Anderson, 2020. "A Model of Global Beverage Markets," Wine Economics Research Centre Working Papers 2019-05, University of Adelaide, Wine Economics Research Centre.
• Raffaella Giacomini & Vasiliki Skreta & Javier Turen, 2020. "Heterogeneity, Inattention, and Bayesian Updates," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(1), pages 282-309, January.
• Stefano DellaVigna & Nicholas Otis & Eva Vivalt, 2020. "Forecasting the Results of Experiments: Piloting an Elicitation Strategy," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 75-79, May.
• Olivier DAMETTE & Claude DIEBOLT & Stephane GOUTTE & Umberto TRIACCA, 2020. "Cliometrics of Climate Change: A Natural Experiment on the Little Ice Age," Working Papers of BETA 2020-20, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
  • Olivier Damette & Claude Diebolt & Stephane Goutte & Umberto Triacca, 2020. "Cliometrics of Climate Change: A Natural Experiment on the Little Ice Age," Working Papers 02-20, Association Française de Cliométrie (AFC).
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, Open Access Journal, vol. 13(7), pages 1-16, April.
  • Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2020. "Beating the naive: Combining LASSO with naive intraday electricity price forecasts," WORking papers in Management Science (WORMS) WORMS/20/01, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Tao Hong & Pierre Pinson & Yi Wang & Rafal Weron & Dazhi Yang & Hamidreza Zareipour, 2020. "Energy forecasting: A review and outlook," WORking papers in Management Science (WORMS) WORMS/20/08, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Oscar Claveria & Ivana Lolic & Enric Monte & Petar Soric, 2020. "Economic determinants of employment sentiment: A socio-demographic analysis for the euro area," IREA Working Papers 202001, University of Barcelona, Research Institute of Applied Economics, revised Jan 2020.
  • Oscar Claveria & Ivana Lolic & Enric Monte & Salvador Torra & Petar Soric, 2020. "“Economic determinants of employment sentiment: A socio-demographic analysis for the euro area”," AQR Working Papers 2012001, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2020.
• Pietro Battiston & Simona Gamba, 2020. "COVID-19: R0 is lower where outbreak is larger," Working Papers 438, University of Milano-Bicocca, Department of Economics, revised Apr 2020.
  • Pietro Battiston & Simona Gamba, 2020. "COVID-19: $R_0$ is lower where outbreak is larger," Papers 2004.07827, arXiv.org.
• Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019-07, Business School - Economics, University of Glasgow.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
• Nataliya Vnukova & Sergii Kavun & Oleh Kolodiziev & Svitlana Achkasova & Daria Hontar, 2020. "Indicators-Markers for Assessment of Probability of Insurance Companies Relatedness in Implementation of Risk-Oriented Approach," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 151-173.
• Anton Gerunov, 2020. "Classification algorithms for modeling economic choice," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 45-67.
• Jinyue Dong, 2020. "Modelo de predicción de la inflación en China
  [China | Forecasting modeling for China\'s inflation]," Working Papers 20/05, BBVA Bank, Economic Research Department.
• Ivan Faiella & Alessandro Mistretta, 2020. "Energy costs and competitiveness in Europe," Temi di discussione (Economic working papers) 1259, Bank of Italy, Economic Research and International Relations Area.
• Valeria Bejarano-Salcedo & Juan Manuel Julio-Román & Edgar Caicedo-García & Julián Alonso Cárdenas-Cárdenas, 2020. "Entendiendo, Modelando y Pronosticando el Efecto de “El Niño” Sobre los Precios de los Alimentos: El Caso Colombiano," Borradores de Economia 1102, Banco de la Republica de Colombia.
• Julián Alonso Cárdenas-Cárdenas & Edgar Caicedo-García & Eliana R. González Molano, 2020. "Estimación de la variación del precio de los alimentos con modelos de frecuencias mixtas," Borradores de Economia 1109, Banco de la Republica de Colombia.
• Sergio Restrepo-Ángel & Hernán Rincón-Castro & Juan J. Ospina-Tejeiro, 2020. "Multiplicadores de los impuestos y del gasto público en Colombia: aproximaciones SVAR y proyecciones locales," Borradores de Economia 1114, Banco de la Republica de Colombia.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
  • Gegerly Ganics & Barbara Rossi & Tatevik Sekhposyan, 2020. "From Fixed-Event to Fixed-Horizon Density Forecasts: Obtaining Measures of Multi-Horizon Uncertainty from Survey Density Forecasts," Working Papers 1142, Barcelona Graduate School of Economics.
  • Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: obtaining measures of multi-horizon uncertainty from survey density forecasts," Working Papers 1947, Banco de España;Working Papers Homepage.
• Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Paper Series 2020-08, Federal Reserve Bank of San Francisco, revised 27 Feb 2020.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Papers 1158, Barcelona Graduate School of Economics.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the information channel of monetary policy disappeared? Revisiting the empirical evidence," Economics Working Papers 1701, Department of Economics and Business, Universitat Pompeu Fabra.
• Baranowski Paweł & Korczak Karol & Zając Jarosław, 2020. "Forecasting Cinema Attendance at the Movie Show Level: Evidence from Poland," Business Systems Research, Sciendo, vol. 11(1), pages 73-88, March.
• Mikhail Gareev, 2020. "Use of Machine Learning Methods to Forecast Investment in Russia," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 35-56, March.
• Evgeny Pavlov, 2020. "Forecasting Inflation in Russia Using Neural Networks," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 57-73, March.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020. "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 285-310, April.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh K. Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Papers No 8/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017. "Do central banks respond timely to developments in the global economy?," CAMA Working Papers 2017-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Paper 2016/19, Norges Bank.
• Ferdinand Dreher & Johannes Gräb & Thomas Kostka, 2020. "From carry trades to curvy trades," The World Economy, Wiley Blackwell, vol. 43(3), pages 758-780, March.
  • Dreher, Ferdinand & Gräb, Johannes & Kostka, Thomas, 2018. "From carry trades to curvy trades," Working Paper Series 2149, European Central Bank.
• Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kang, Miao & Kapadia, Sujit & Simsek, Özgür, 2020. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Bank of England working papers 848, Bank of England.
• Martins, Manuel M. F. & Verona, Fabio, 2020. "Forecasting inflation with the New Keynesian Phillips curve : Frequency matters," Research Discussion Papers 4/2020, Bank of Finland.
• Hyeongwoo Kim & Soohyon Kim, 2020. "Common Factor Augmented Forecasting Models for the US Dollar-Korean Won Exchange Rate," Working Papers 2020-5, Economic Research Institute, Bank of Korea.
• Rutzer, Christian & Niggli, Matthias & Weder, Rolf, 2020. "Estimating the Green Potential of Occupations: A New Approach Applied to the U.S. Labor Market," Working papers 2020/03, Faculty of Business and Economics - University of Basel.
• Mueller, H. & Rauh, C., 2020. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2015, Faculty of Economics, University of Cambridge.
• Francesco Zanetti & Carlo Pizzinelli & Konstantinos Theodoridis, 2020. "State Dependence in Labor Market Fluctuations," Economics Series Working Papers 902, University of Oxford, Department of Economics.
  • Pizzinelli, Carlo & Theodoridis, Konstantinos & Zanetti, Francesco, 2020. "State Dependence in Labor Market Fluctuations," Cardiff Economics Working Papers E2020/2, Cardiff University, Cardiff Business School, Economics Section.
• Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo Group Munich.
• Alexandros Botsis & Christoph Görtz & Plutarchos Sakellaris, 2020. "Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts," CESifo Working Paper Series 8148, CESifo Group Munich.
• Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87, April.
• Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
• Bańbura, Marta & Saiz, Lorena, 2020. "Short-term forecasting of euro area economic activity at the ECB," Economic Bulletin Articles, European Central Bank, vol. 2.
• Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," EMF Research Papers 29, Economic Modelling and Forecasting Group.
  • Delle Monache, Davide & Venditti, Fabrizio & Petrella, Ivan, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Working Paper Series 2369, European Central Bank.
• Meyler, Aidan, 2020. "Forecast performance in the ECB SPF: ability or chance?," Working Paper Series 2371, European Central Bank.
• McAdam, Peter & Warne, Anders, 2020. "Density forecast combinations: the real-time dimension," Working Paper Series 2378, European Central Bank.
• Jarmulska, Barbara, 2020. "Random forest versus logit models: which offers better early warning of fiscal stress?," Working Paper Series 2408, European Central Bank.
• Chia-Cheng Chen & Chun-Hung Chen & Ting-Yin Liu, 2020. "Investment Performance of Machine Learning: Analysis of S&P 500 Index," International Journal of Economics and Financial Issues, Econjournals, vol. 10(1), pages 59-66.
• Hatice Erkekoglu & Aweng Peter Majok Garang & Adire Simon Deng, 2020. "Modeling and Forecasting USD/UGX Volatility through GARCH Family Models: Evidence from Gaussian, T and GED Distributions," International Journal of Economics and Financial Issues, Econjournals, vol. 10(2), pages 268-281.
• Rialdi Azhar & Fajrin Satria Dwi Kesumah & Ambya Ambya & Febryan Kusuma Wisnu & Edwin Russel, 2020. "Application of Short-term Forecasting Models for Energy Entity Stock Price (Study on Indika Energi Tbk, JII)," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 294-301.
• Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
  • Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2019. "Exploiting ergodicity in forecasts of corporate profitability," BERG Working Paper Series 147, Bamberg University, Bamberg Economic Research Group.
• Li, Hong, 2020. "Volatility spillovers across European stock markets under the uncertainty of Brexit," Economic Modelling, Elsevier, vol. 84(C), pages 1-12.
• Wang, Yajing & Liang, Fang & Wang, Tianyi & Huang, Zhuo, 2020. "Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market," Economic Modelling, Elsevier, vol. 87(C), pages 148-157.
• McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
• Díaz-Mendoza, Ana-Carmen & Pardo, Angel, 2020. "Holidays, weekends and range-based volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
• Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
• Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2020. "Improving the realized GARCH’s volatility forecast for Bitcoin with jump-robust estimators," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
• Dai, Zhifeng & Zhou, Huiting & Wen, Fenghua & He, Shaoyi, 2020. "Efficient predictability of stock return volatility: The role of stock market implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
• Gupta, Rangan & Sun, Xiaojin, 2020. "Forecasting economic policy uncertainty of BRIC countries using Bayesian VARs," Economics Letters, Elsevier, vol. 186(C).
• Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2020. "Computationally efficient inference in large Bayesian mixed frequency VARs," Economics Letters, Elsevier, vol. 191(C).
• Murat Midiliç, 2020. "Estimation of STAR–GARCH Models with Iteratively Weighted Least Squares," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 87-117, January.
• Bernard Fingleton, 2020. "Italexit, is it another Brexit?," Journal of Geographical Systems, Springer, vol. 22(1), pages 77-104, January.
• Takafumi Kato, 2020. "Likelihood-based strategies for estimating unknown parameters and predicting missing data in the simultaneous autoregressive model," Journal of Geographical Systems, Springer, vol. 22(1), pages 143-176, January.
• Frank J. Fabozzi & Iason Kynigakis & Ekaterini Panopoulou & Radu S. Tunaru, 2020. "Detecting Bubbles in the US and UK Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 60(4), pages 469-513, May.
• Andrejs Bessonovs & Olegs Krasnopjorovs, 2020. "Short-Term Inflation Projections Model and Its Assessment in Latvia," Working Papers 2020/01, Latvijas Banka.
• Weshah Razzak, 2020. "The Dynamic of COVID-19 New Infections under Different Stringent Policies," Discussion Papers 2007, School of Economics and Finance, Massey University, New Zealand.
• Ji Hyung Lee & Youngki Shin, 2020. "Complete Subset Averaging for Quantile Regressions," Department of Economics Working Papers 2020-03, McMaster University.
• Evžen KoÄ enda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Eastern European Economics, Taylor & Francis Journals, vol. 58(3), pages 197-220, May.
  • Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
  • Evzen Kocenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Working Papers IES 2020/5, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2020.
• Alexander Glas & Matthias Hartmann, 2020. "Uncertainty measures from partially rounded probabilistic forecast surveys," Working Papers 427, University of Milano-Bicocca, Department of Economics, revised Jan 2020.
• Pietro Battiston & Simona Gamba & Alessandro Santoro, 2020. "Optimizing Tax Administration Policies with Machine Learning," Working Papers 436, University of Milano-Bicocca, Department of Economics, revised Mar 2020.
• Pietro Battiston & Simona Gamba, 2020. "COVID-19: $R_0$ is lower where outbreak is larger," Papers 2004.07827, arXiv.org.
  • Pietro Battiston & Simona Gamba, 2020. "COVID-19: R0 is lower where outbreak is larger," Working Papers 438, University of Milano-Bicocca, Department of Economics, revised Apr 2020.
• Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2019. "Focused Bayesian Prediction," Papers 1912.12571, arXiv.org.
  • Ruben Loaiza-Maya & Gael M Martin & David T. Frazier, 2020. "Focused Bayesian Prediction," Monash Econometrics and Business Statistics Working Papers 1/20, Monash University, Department of Econometrics and Business Statistics.
• Natalia Bailey & Zvi Hochman & Yufeng Mao & Mervyn J. Silvapulle & Param Silvapulle, 2020. "Statistical Modelling and Forecast Evaluation of the Impact of Extreme Temperatures on Wheat Crops in North Western Victoria," Monash Econometrics and Business Statistics Working Papers 18/20, Monash University, Department of Econometrics and Business Statistics.
• Sium Bodha Hannadige & Jiti Gao & Mervyn J. Silvapulle & Param Silvapulle, 2020. "Forecasting a Nonstationary Time Series with a Mixture of Stationary and Nonstationary Factors as Predictors," Monash Econometrics and Business Statistics Working Papers 19/20, Monash University, Department of Econometrics and Business Statistics.
• George Athanasopoulos & Nikolaos Kourentzes, 2020. "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers 2/20, Monash University, Department of Econometrics and Business Statistics.
• Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," PIER Working Paper Archive 19-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Michael D. Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," NBER Working Papers 26826, National Bureau of Economic Research, Inc.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Staff Reports 893, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Liberty Street Economics 20190821, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," Finance and Economics Discussion Series 2020-023, Board of Governors of the Federal Reserve System (U.S.).
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Panel Forecasts of Country-Level Covid-19 Infections," NBER Working Papers 27248, National Bureau of Economic Research, Inc.
• Nicolas Woloszko, 2020. "Adaptive Trees: a new approach to economic forecasting," OECD Economics Department Working Papers 1593, OECD Publishing.
• Sander Barendse & Andrew J. Patton, 2020. "Comparing Predictive Accuracy in the Presence of a Loss Function Shape Parameter," Economics Series Working Papers 909, University of Oxford, Department of Economics.
• Erika Onuferova & Veronika Cabinova & Tunde Dzurov Vargova, 2020. "Analysis of modern methods for increasing and managing the financial prosperity of businesses in the context of performance: a case study of the tourism sector in Slovakia," Oeconomia Copernicana, Institute of Economic Research, vol. 11(1), pages 95-116, March.
• Manuel M. F. Martins & Fabio Verona, 2020. "Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters," CEF.UP Working Papers 2001, Universidade do Porto, Faculdade de Economia do Porto.
• Gary Koop & Dimitris Korobilis, 2020. "Bayesian dynamic variable selection in high dimensions," Working Papers 2020_11, Business School - Economics, University of Glasgow.
  • Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
• Razzak, Weshah, 2020. "The Dynamic of COVID-19 New Infections under Different Stringent Policies," MPRA Paper 100451, University Library of Munich, Germany.
• González Laxe, Fernando & Da Rocha Alvarez, Jose Maria & Armesto Pina, José Francisco & Sanchez-Fernandez, Patricio & Lago-Peñas, Santiago, 2020. "Economía de Galicia tras el COVID-19: prospectiva de escenarios
  [Economy of Galicia after COVID-covid-19: prospective forecastings]," MPRA Paper 100483, University Library of Munich, Germany, revised May 2020.
• Degiannakis, Stavros & Filis, George, 2020. "Oil price assumptions for macroeconomic policy," MPRA Paper 100705, University Library of Munich, Germany.
• Holt, Matthew T. & Teräsvirta, Timo, 2020. "Global hemispheric temperatures and co-shifting: A vector shifting-mean autoregressive analysis," Journal of Econometrics, Elsevier, vol. 214(1), pages 198-215.
  • Matthew T. Holt & Timo Teräsvirta, 2017. "Global Hemispheric Temperatures and Co–Shifting: A Vector Shifting–Mean Autoregressive Analysis," CREATES Research Papers 2017-05, Department of Economics and Business Economics, Aarhus University.
• Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
• Arcidiacono, Peter & Miller, Robert A., 2020. "Identifying dynamic discrete choice models off short panels," Journal of Econometrics, Elsevier, vol. 215(2), pages 473-485.
• Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
• Bissoondoyal-Bheenick, Emawtee & Brooks, Robert & Do, Hung Xuan & Smyth, Russell, 2020. "Exploiting the heteroskedasticity in measurement error to improve volatility predictions in oil and biofuel feedstock markets," Energy Economics, Elsevier, vol. 86(C).
• Trespalacios, Alfredo & Cortés, Lina M. & Perote, Javier, 2020. "Uncertainty in electricity markets from a semi-nonparametric approach," Energy Policy, Elsevier, vol. 137(C).
  • Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2019. "Uncertainty in Electricity Markets from a seminonparametric Approach," Documentos de Trabajo CIEF 017304, Universidad EAFIT.
• Sobreira, Nuno & Louro, Rui, 2020. "Evaluation of volatility models for forecasting Value-at-Risk and Expected Shortfall in the Portuguese stock market," Finance Research Letters, Elsevier, vol. 32(C).
• Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2020. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 466-479.
  • Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2018. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," HSC Research Reports HSC/18/05, Hugo Steinhaus Center, Wroclaw University of Technology.
• Maheu, John M. & Song, Yong & Yang, Qiao, 2020. "Oil price shocks and economic growth: The volatility link," International Journal of Forecasting, Elsevier, vol. 36(2), pages 570-587.
  • John M. Maheu & Yong Song & Qiao Yang, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," Working Paper series 18-03, Rimini Centre for Economic Analysis.
  • Maheu, John M & Yang, Qiao & Song, Yong, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83779, University Library of Munich, Germany.
  • Maheu, John M & Song, Yong & Yang, Qiao, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83999, University Library of Munich, Germany.
• Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Pricing individual stock options using both stock and market index information," Journal of Banking & Finance, Elsevier, vol. 111(C).
• Bengtsson, Elias & Grothe, Magdalena & Lepers, Etienne, 2020. "Home, safe home: Cross-country monitoring framework for vulnerabilities in the residential real estate sector," Journal of Banking & Finance, Elsevier, vol. 112(C).
• Das, Prashant & Füss, Roland & Hanle, Benjamin & Russ, Isabel Nina, 2020. "The cross-over effect of irrational sentiments in housing, commercial property, and stock markets," Journal of Banking & Finance, Elsevier, vol. 114(C).
• Westphal, Rebecca & Sornette, Didier, 2020. "Market impact and performance of arbitrageurs of financial bubbles in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 1-23.
• Ogbuabor, Jonathan E. & Anthony-Orji, Onyinye I. & Manasseh, Charles O. & Orji, Anthony, 2020. "Measuring the dynamics of COMESA output connectedness with the global economy," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
• Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
• Coda Moscarola, Flavia & Colombino, Ugo & Figari, Francesco & Locatelli, Marilena, 2020. "Shifting taxes away from labour enhances equity and fiscal efficiency," Journal of Policy Modeling, Elsevier, vol. 42(2), pages 367-384.
• Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2020. "Crisis transmission: Visualizing vulnerability," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
• Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
• McGurk, Zachary, 2020. "US real estate inflation prediction: Exchange rates and net foreign assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 53-66.
• Hicks, Robert L. & Holland, Daniel S. & Kuriyama, Peter T. & Schnier, Kurt E., 2020. "Choice sets for spatial discrete choice models in data rich environments," Resource and Energy Economics, Elsevier, vol. 60(C).
• Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
• Jackson, Emerson Abraham, 2020. "Understanding SLL / US$ exchange rate dynamics in Sierra Leone using Box-Jenkins ARIMA approach," MPRA Paper 97965, University Library of Munich, Germany, revised 03 Jan 2020.
• Cerulli, Giovanni, 2020. "A Super-Learning Machine for Predicting Economic Outcomes," MPRA Paper 99111, University Library of Munich, Germany.
• Adeniyi, Isaac Adeola & Yahya, Waheed Babatunde, 2020. "Bayesian Generalized Linear Mixed Effects Models Using Normal-Independent Distributions: Formulation and Applications," MPRA Paper 99165, University Library of Munich, Germany.
• Chu, Amanda M.Y. & Lv, Zhihui & Wagner, Niklas F. & Wong, Wing-Keung, 2020. "Linear and Nonlinear Growth Determinants: The Case of Mongolia and its Connection to China," MPRA Paper 99185, University Library of Munich, Germany.
• Laliotis, Ioannis, 2020. "The Covid-19 pandemic in Greece," MPRA Paper 99754, University Library of Munich, Germany.
• Matthew W. Clance & Riza Demirer & Rangan Gupta & Clement Kweku Kyei, 2020. "Predicting Firm-Level Volatility in the United States: The Role of Monetary Policy Uncertainty," Working Papers 202007, University of Pretoria, Department of Economics.
• Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2020. "A Note on Oil Price Shocks and the Forecastability of Gold Realized Volatility," Working Papers 202010, University of Pretoria, Department of Economics.
• Edmond Berisha & David Gabauer & Rangan Gupta & Chi Keung Marco Lau, 2020. "Time-Varying Influence of Household Debt on Inequality in United Kingdom," Working Papers 202017, University of Pretoria, Department of Economics.
• Edmond Berisha & David Gabauer & Rangan Gupta & Jacobus Nel, 2020. "Time-Varying Predictability of Financial Stress on Inequality in United Kingdom," Working Papers 202030, University of Pretoria, Department of Economics.
• Christos Bouras & Christina Christou & Rangan Gupta & Keagile Lesame, 2020. "Forecasting State- and MSA-Level Housing Returns of the US: The Role of Mortgage Default Risks," Working Papers 202037, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Elie Bouri, 2020. "The Role of Global Economic Conditions in Forecasting Gold Market Volatility: Evidence from a GARCH-MIDAS Approach," Working Papers 202043, University of Pretoria, Department of Economics.
• Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2020. "The Predictive Power of Oil Price Shocks on Realized Volatility of Oil: A Note," Working Papers 202044, University of Pretoria, Department of Economics.
• Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Forecasting Power of Infectious Diseases-Related Uncertainty for Gold Realized Volatility," Working Papers 202049, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Riza Demirer, 2020. "A Note on Uncertainty due to Infectious Diseases and Output Growth of the United States: A Mixed-Frequency Forecasting Experiment," Working Papers 202050, University of Pretoria, Department of Economics.
• Tomáš Jeøábek, 2020. "The Efficiency of GARCH Models in Realizing Value at Risk Estimates," ACTA VSFS, University of Finance and Administration, vol. 14(1), pages 32-50.
• António Rua & Carlos Melo Gouveia & Nuno Lourenço, 2020. "Forecasting tourism with targeted predictors in a data-rich environment," Working Papers w202005, Banco de Portugal, Economics and Research Department.
• J. James Reade & Carl Singleton & Leighton Vaughan Williams, 2020. "Betting markets for English Premier League results and scorelines: evaluating a simple forecasting model," Economics & Management Discussion Papers em-dp2020-03, Henley Business School, Reading University.
• Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, Reading University.
• Michael P. Clements, 2020. "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance icma-dp2020-02, Henley Business School, Reading University.
• Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Paper series 20-09, Rimini Centre for Economic Analysis.
• Balagula, Yuri, 2020. "Forecasting daily spot prices in the Russian electricity market with the ARFIMA model," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 57, pages 89-101.
• Qiu, Yue & Xie, Tian & Yu, Jun, 2020. "Forecast combinations in machine learning," Economics and Statistics Working Papers 13-2020, Singapore Management University, School of Economics.
• Nikola RADIVOJEVIĆ & Luka FILIPOVI & Тomislav D. BRZAKOVIĆ, 2020. "A New Semiparametric Mirrored Historical Simulation Value-At-Risk Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-21, March.
• Tommaso Proietti & Alessandro Giovannelli, 2020. "Nowcasting Monthly GDP with Big Data: a Model Averaging Approach," CEIS Research Paper 482, Tor Vergata University, CEIS, revised 12 May 2020.
• Alessandro Giovannelli & Tommaso Proietti & Ambra Citton & Ottavio Ricchi & Cristian Tegami & Cristina Tinti, 2020. "Nowcasting GDP and its Components in a Data-rich Environment: the Merits of the Indirect Approach," CEIS Research Paper 489, Tor Vergata University, CEIS, revised 30 May 2020.
• Robert Wrathall & Rod Falvey & Gulasekaran Rajaguru, 2020. "Do (Australian) jockeys have hot hands?," Australian Journal of Management, Australian School of Business, vol. 45(2), pages 223-239, May.
• Andreas Psimopoulos, 2020. "Forecasting Economic Recessions Using Machine Learning:An Empirical Study in Six Countries," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 18(1), pages 40-99.
• Bernard Fingleton, 2020. "Exploring Brexit with dynamic spatial panel models: some possible outcomes for employment across the EU regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 455-491, April.
• Joanna Bruzda, 2020. "Multistep quantile forecasts for supply chain and logistics operations: bootstrapping, the GARCH model and quantile regression based approaches," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 309-336, March.
• Rangan Gupta & Hylton Hollander & Rudi Steinbach, 2020. "Forecasting output growth using a DSGE-based decomposition of the South African yield curve," Empirical Economics, Springer, vol. 58(1), pages 351-378, January.
  • Rangan Gupta & Hylton Hollander & Rudi Steinbach, 2015. "Forecasting Output Growth using a DSGE-Based Decomposition of the South African Yield Curve," Working Papers 201567, University of Pretoria, Department of Economics.
• Nima Nonejad, 2020. "Does the price of crude oil help predict the conditional distribution of aggregate equity return?," Empirical Economics, Springer, vol. 58(1), pages 313-349, January.
• Christian Glocker & Philipp Wegmueller, 2020. "Business cycle dating and forecasting with real-time Swiss GDP data," Empirical Economics, Springer, vol. 58(1), pages 73-105, January.
  • Christian Glocker & Philipp Wegmüller, 2017. "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers 542, WIFO.
• M. Chudý & S. Karmakar & W. B. Wu, 2020. "Long-term prediction intervals of economic time series," Empirical Economics, Springer, vol. 58(1), pages 191-222, January.
• Boriss Siliverstovs, 2020. "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
  • Boriss Siliverstovs, 2019. "Assessing Nowcast Accuracy of US GDP Growth in Real Time: The Role of Booms and Busts," Working Papers 2019/01, Latvijas Banka.
• Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
• Gabe Jacob de Bondt & Arne Gieseck & Zivile Zekaite, 2020. "Thick modelling income and wealth effects: a forecast application to euro area private consumption," Empirical Economics, Springer, vol. 58(1), pages 257-286, January.
• Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.
• João C. Claudio & Katja Heinisch & Oliver Holtemöller, 2020. "Nowcasting East German GDP growth: a MIDAS approach," Empirical Economics, Springer, vol. 58(1), pages 29-54, January.
  • Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
• Ines Fortin & Sebastian P. Koch & Klaus Weyerstrass, 2020. "Evaluation of economic forecasts for Austria," Empirical Economics, Springer, vol. 58(1), pages 107-137, January.
• Christian Pierdzioch & Marian Risse, 2020. "Forecasting precious metal returns with multivariate random forests," Empirical Economics, Springer, vol. 58(3), pages 1167-1184, March.
• Kyle E. Binder & Mohsen Pourahmadi & James W. Mjelde, 2020. "The role of temporal dependence in factor selection and forecasting oil prices," Empirical Economics, Springer, vol. 58(3), pages 1185-1223, March.
• Aitor Ciarreta & Peru Muniain & Ainhoa Zarraga, 2020. "Realized volatility and jump testing in the Japanese electricity spot market," Empirical Economics, Springer, vol. 58(3), pages 1143-1166, March.
• Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
• Dean Fantazzini & Stephan Zimin, 2020. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 19-69, March.
  • Fantazzini, Dean & Zimin, Stephan, 2019. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," MPRA Paper 95988, University Library of Munich, Germany.
• Unn Lindholm & Marcus Mossfeldt & Pär Stockhammar, 2020. "Forecasting inflation in Sweden," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(1), pages 39-68, April.
• Maurizio Bovi, 2020. "A time-varying expectations formation mechanism," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(1), pages 69-103, April.
  • Bovi, Maurizio, 2019. "A Time-Varying Expectations Formation Mechanism," MPRA Paper 97624, University Library of Munich, Germany.
• Maren Hein & Peter Kurz & Winfried J. Steiner, 2020. "Analyzing the capabilities of the HB logit model for choice-based conjoint analysis: a simulation study," Journal of Business Economics, Springer, vol. 90(1), pages 1-36, February.
• Christian Lohmann & Thorsten Ohliger, 2020. "Bankruptcy prediction and the discriminatory power of annual reports: empirical evidence from financially distressed German companies," Journal of Business Economics, Springer, vol. 90(1), pages 137-172, February.
• Moses Tule & Afees Salisu & Charles Chiemeke, 2020. "Improving Nigeria’s Inflation Forecast with Oil Price: The Role of Estimators," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(1), pages 191-229, March.
• Marina Y. Anokhina & Rakhat Abdrakhmanov & Yelena Evgenevna Gridneva & Milton Arrieta-López & Nuray Romanovna Dzhalilova & Abel Meza-Godoy, 2020. "Formation of the competitive potential of the agricultural territories," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(3), pages 1921-1936, March.
• Ruan Erasmus & Hylton Hollander, 2020. "A Forward Guidance Indicator For The South African Reserve Bank: Implementing A Text Analysis Algorithm," Working Papers 04/2020, Stellenbosch University, Department of Economics.
• Ramiro Losada & Ricardo Laborda, 2020. "Non-alternative collective investment schemes, connectedness and systemic risk," CNMV Working Papers CNMV Working Papers no. 7, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
• Rodríguez, Aldo, 2020. "Estimación Bayesiana de un Modelo de Economía Abierta con Sector Bancario," Dynare Working Papers 52, CEPREMAP.
• Hasenzagl, Thomas & Reichlin, Lucrezia & Ricco, Giovanni, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," CEPR Discussion Papers 14322, C.E.P.R. Discussion Papers.
• Anderson, Kym & Wittwer, Glyn, 2020. "A Model of Global Beverage Markets," CEPR Discussion Papers 14387, C.E.P.R. Discussion Papers.
• Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2020. "Panel Forecasts of Country-Level Covid-19 Infectionsliu," CEPR Discussion Papers 14790, C.E.P.R. Discussion Papers.
• Ruiz Ortega, Esther & Nieto Delfin, Maria Rosa, 2020. "Direct versus iterated multi-period Value at Risk," DES - Working Papers. Statistics and Econometrics. WS 30349, Universidad Carlos III de Madrid. Departamento de Estadística.
• Bekaert, Geert & Panayotov, George, 2020. "Good Carry, Bad Carry," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(4), pages 1063-1094, June.
  • Bekaert, Geert & Panayotov, George, 2019. "Good Carry, Bad Carry," CEPR Discussion Papers 13463, C.E.P.R. Discussion Papers.
  • Geert Bekaert & George Panayotov, 2019. "Good Carry, Bad Carry," NBER Working Papers 25420, National Bureau of Economic Research, Inc.
• Philip Hans Franses & Max Welz, 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 13(3), pages 1-8, March.
  • Franses, Ph.H.B.F. & Welz, M., 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," Econometric Institute Research Papers EI-1687, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Franses, Ph.H.B.F., 2020. "An introduction to time-varying lag autoregression," Econometric Institute Research Papers EI2020-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Raymundo M. Campos Vázquez & Sergio E. López-Araiza B., 2020. "Grandes datos, Google y desempleo/Big Data, Google and Unemployment," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 35(1), pages 125-151.
• Evžen KoÄ enda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Eastern European Economics, Taylor & Francis Journals, vol. 58(3), pages 197-220, May.
  • Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
  • Evzen Kocenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Working Papers IES 2020/5, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2020.
• Bruno Ducoudré & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Documents de Travail de l'OFCE 2020-04, Observatoire Francais des Conjonctures Economiques (OFCE).
• Reichlin, Lucrezia & Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial variables as predictors of real growth vulnerability," Discussion Papers 05/2020, Deutsche Bundesbank.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Documents de Travail de l'OFCE 2020-06, Observatoire Francais des Conjonctures Economiques (OFCE).
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," Working Papers 202002, Federal Reserve Bank of Cleveland.
• Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 202013, Federal Reserve Bank of Cleveland.
• Aitor Erce & Xu Jiang & Diana Zigraiova, 2020. "Quantifying Risks to Sovereign Market Access: Methods and Challenges," Globalization Institute Working Papers 377, Federal Reserve Bank of Dallas, revised 10 Feb 2020.
• Enrique Martínez-García & Efthymios Pavlidis & Kostas Vasilopoulos, 2020. "exuber: Recursive Right-Tailed Unit Root Testing with R," Globalization Institute Working Papers 383, Federal Reserve Bank of Dallas.
• Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers 1912.10774, arXiv.org.
  • Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Working Paper Series 2020-02, Federal Reserve Bank of San Francisco, revised 11 Jan 2020.
  • Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," PIER Working Paper Archive 20-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the information channel of monetary policy disappeared? Revisiting the empirical evidence," Economics Working Papers 1701, Department of Economics and Business, Universitat Pompeu Fabra.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Paper Series 2020-08, Federal Reserve Bank of San Francisco, revised 27 Feb 2020.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Papers 1158, Barcelona Graduate School of Economics.
• Christopher A. Hollrah & Steven A. Sharpe & Nitish R. Sinha, 2020. "The Power of Narratives in Economic Forecasts," Finance and Economics Discussion Series 2020-001, Board of Governors of the Federal Reserve System (U.S.).
• Travis J. Berge, 2020. "Time-varying Uncertainty of the Federal Reserve’s Output Gap Estimate," Finance and Economics Discussion Series 2020-012, Board of Governors of the Federal Reserve System (U.S.).
• Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Liberty Street Economics 20190821, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," Finance and Economics Discussion Series 2020-023, Board of Governors of the Federal Reserve System (U.S.).
  • Michael D. Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," NBER Working Papers 26826, National Bureau of Economic Research, Inc.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Staff Reports 893, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," PIER Working Paper Archive 19-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Tomaz Cajner & Leland Crane & Ryan Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2020. "Tracking Labor Market Developments during the COVID-19 Pandemic: A Preliminary Assessment," Finance and Economics Discussion Series 2020-030, Board of Governors of the Federal Reserve System (U.S.).
• Michael Puglia & Adam Tucker, 2020. "Machine Learning, the Treasury Yield Curve and Recession Forecasting," Finance and Economics Discussion Series 2020-038, Board of Governors of the Federal Reserve System (U.S.).
• Daniel Aaronson & Scott A. Brave & R. Andrew Butters & Daniel W. Sacks & Boyoung Seo, 2020. "Using the Eye of the Storm to Predict the Wave of Covid-19 UI Claims," Working Paper Series WP 2020-10, Federal Reserve Bank of Chicago, revised 07 Apr 2020.
• Daniel J. Lewis & Karel Mertens & James H. Stock, 2020. "Monitoring Real Activity in Real Time: The Weekly Economic Index," Liberty Street Economics 20200330b, Federal Reserve Bank of New York.
• Fabrizio Cipollini & Giampiero Gallo & Alessandro Palandri, 2020. "A Dynamic Conditional Approach to Portfolio Weights Forecasting," Econometrics Working Papers Archive 2020_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
• OÄŸuzhan Çepni & Rangan Gupta & Mark E. Wohar, 2020. "The role of real estate uncertainty in predicting US home sales growth: evidence from a quantiles-based Bayesian model averaging approach," Applied Economics, Taylor & Francis Journals, vol. 52(5), pages 528-536, January.
  • Oguzhan Cepni & Rangan Gupta & Mark E. Wohar, 2019. "The Role of Real Estate Uncertainty in Predicting US Home Sales Growth: Evidence from a Quantiles-Based Bayesian Model Averaging Approach," Working Papers 201936, University of Pretoria, Department of Economics.
• Joshua C. C. Chan, 2020. "Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
  • Joshua C.C. Chan, 2015. "Large Bayesian VARs: A flexible Kronecker error covariance structure," CAMA Working Papers 2015-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2020. "Markov-Switching Three-Pass Regression Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 285-302, April.
  • Pierre Guerin & Danilo Leiva-Leon & Massimiliano Marcellino, 2016. "Markov-Switching Three-Pass Regression Filter," Working Papers 591, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  • Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-Switching Three-Pass Regression Filter," Staff Working Papers 17-13, Bank of Canada.
  • Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-switching three-pass regression filter," Working Papers 1748, Banco de España;Working Papers Homepage.
• Georges Dionne & Xiaozhou Zhou, 2020. "The dynamics of ex-ante weighted spread: an empirical analysis," Quantitative Finance, Taylor & Francis Journals, vol. 20(4), pages 593-617, April.
  • Dionne, Georges & Zhou, Xiaozhou, 2016. "The Dynamics of Ex-ante Weighted Spread: An Empirical Analysis," Working Papers 16-4, HEC Montreal, Canada Research Chair in Risk Management, revised 04 Nov 2019.
• Troy Lorde & Antonio Alleyne & Roger Hosein & Mu Yifei, 2020. "Should the Caribbean Look to the East? An Assessment of Caribbean Export Potential," The International Trade Journal, Taylor & Francis Journals, vol. 34(1), pages 136-150, January.
  • Lorde, Troy & Alleyne, Antonio & Hosein, Roger & Yifei, Mu, 2019. "Should the Caribbean Look to the East? An Assessment of Caribbean Export Potential," MPRA Paper 96641, University Library of Munich, Germany.
• Mahmut Gunay, 2020. "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers 2002, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Noussair, C.N. & Popescu, Andreea Victoria, 2020. "Contagion and Return Predictability in Asset Markets : An Experiment with Two Lucas Trees," Discussion Paper 2020-014, Tilburg University, Center for Economic Research.
• Monokroussos, George, 2015. "Nowcasting in Real Time Using Popularity Priors," MPRA Paper 68594, University Library of Munich, Germany.
  • George Monokroussos & Yongchen Zhao, 2020. "Nowcasting in Real Time Using Popularity Priors," Working Papers 2020-01, Towson University, Department of Economics, revised Feb 2020.
• Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 2017-026, Federal Reserve Bank of St. Louis.
  • Todd E Clark & Michael W McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," BIS Working Papers 667, Bank for International Settlements.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 171501, Federal Reserve Bank of Cleveland, revised 08 May 2018.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers (Old Series) 1715, Federal Reserve Bank of Cleveland, revised 25 Sep 2017.
• Felix Haase & Matthias Neuenkirch, 2020. "Forecasting Stock Market Recessions in the US: Predictive Modeling using Different Identification Approaches," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "Iassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, Institute of Labor Economics (IZA).
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
• Tong Fang & Tae-Hwy Lee & Zhi Su, 2020. "Predicting the Long-term Stock Market Volatility: A GARCH-MIDAS Model with Variable Selection," Working Papers 202009, University of California at Riverside, Department of Economics.
• Olivier Damette & Claude Diebolt & Stephane Goutte & Umberto Triacca, 2020. "Cliometrics of Climate Change: A Natural Experiment on the Little Ice Age," Working Papers 02-20, Association Française de Cliométrie (AFC).
  • Olivier DAMETTE & Claude DIEBOLT & Stephane GOUTTE & Umberto TRIACCA, 2020. "Cliometrics of Climate Change: A Natural Experiment on the Little Ice Age," Working Papers of BETA 2020-20, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
• Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Paper Series 2020-08, Federal Reserve Bank of San Francisco, revised 27 Feb 2020.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the information channel of monetary policy disappeared? Revisiting the empirical evidence," Economics Working Papers 1701, Department of Economics and Business, Universitat Pompeu Fabra.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Papers 1158, Barcelona Graduate School of Economics.
• WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," CORE Discussion Papers 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Jonas Striaukas & Martin Schumacher & Harald Binder & Matthias Weber, 2020. "Network-Constrained Covariate Coefficient and Connection Sign Estimation," Working Papers on Finance 2001, University of St. Gallen, School of Finance.
  • Matthias Weber & Jonas Striaukas & Martin Schumacher & Harald Binder, 2018. "Network constrained covariate coefficient and connection sign estimation," Bank of Lithuania Discussion Paper Series 8, Bank of Lithuania.
• Mateusz Buczyński & Marcin Chlebus, 2020. "Size does matter. A study on the required window size for optimal quality market risk models," Working Papers 2020-09, Faculty of Economic Sciences, University of Warsaw.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Forecasting With Dynamic Panel Data Models," Econometrica, Econometric Society, vol. 88(1), pages 171-201, January.
  • Laura Liu & Hyungsik Moon & Frank Schorfheide, 2016. "Forecasting with Dynamic Panel Data Models," PIER Working Paper Archive 16-022, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 21 Dec 2016.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2018. "Forecasting with Dynamic Panel Data Models," NBER Working Papers 25102, National Bureau of Economic Research, Inc.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2017. "Forecasting with Dynamic Panel Data Models," Papers 1709.10193, arXiv.org.
• Duc Khuong Nguyen & Thomas Walther, 2020. "Modeling and forecasting commodity market volatility with long‐term economic and financial variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 126-142, March.
  • Nguyen, Duc Khuong & Walther, Thomas, 2017. "Modeling and forecasting commodity market volatility with long-term economic and financial variables," MPRA Paper 84464, University Library of Munich, Germany, revised Jan 2018.
  • Thomas Walther & Duc Khuong Nguyen, 2018. "Modeling and Forecasting Commodity Market Volatility with Long-term Economic and Financial Variables," Working Papers on Finance 1824, University of St. Gallen, School of Finance.
• Benedikt Maas, 2020. "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
  • Maas, Benedikt, 2019. "Short-term forecasting of the US unemployment rate," MPRA Paper 94066, University Library of Munich, Germany.
• Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
• Gaetano Perone, 2020. "An ARIMA model to forecast the spread and the final size of COVID-2019 epidemic in Italy," Health, Econometrics and Data Group (HEDG) Working Papers 20/07, HEDG, c/o Department of Economics, University of York.
• Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Documents de Travail de l'OFCE 2020-06, Observatoire Francais des Conjonctures Economiques (OFCE).
  • Reichlin, Lucrezia & Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial variables as predictors of real growth vulnerability," Discussion Papers 05/2020, Deutsche Bundesbank.
• Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.
• Sallam, Walid & Ahmed, Osama, 2020. "The socio-economic assessment to evaluate the potentiality of developing the rural community in Upper Egypt," EconStor Open Access Articles, ZBW - Leibniz Information Centre for Economics, pages 143-165.
• Brighton, Henry, 2020. "Statistical foundations of ecological rationality," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 14, pages 1-32.
• Bluhm, Benjamin & Cutura, Jannic, 2020. "Econometrics at scale: Spark up big data in economics," SAFE Working Paper Series 266, Leibniz Institute for Financial Research SAFE.
• Grammig, Joachim & Hanenberg, Constantin & Schlag, Christian & Sönksen, Jantje, 2020. "Diverging roads: Theory-based vs. machine learning-implied stock risk premia," University of Tübingen Working Papers in Business and Economics 130, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
• Kaiser, Ulrich & Kuhn, Johan M., 2020. "The value of publicly available, textual and non-textual information for startup performance prediction," ZEW Discussion Papers 20-012, ZEW - Leibniz Centre for European Economic Research.
• Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
  • Gary Koop & Dimitris Korobilis, 2020. "Bayesian dynamic variable selection in high dimensions," Working Papers 2020_11, Business School - Economics, University of Glasgow.
• Constantin Bürgi & Tara M. Sinclair, 2020. "What Does Forecaster Disagreement Tell Us about the State of the Economy?," Working Papers 2020-001, The George Washington University, Department of Economics, Research Program on Forecasting.
• Elena Dumitrescu & Sullivan Hué & Christophe Hurlin & Sessi Tokpavi, 2020. "Machine Learning or Econometrics for Credit Scoring: Let's Get the Best of Both Worlds ," Working Papers hal-02507499, HAL.
• Thomas Lustenberger & Enzo Rossi, 2020. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," International Journal of Central Banking, International Journal of Central Banking, vol. 16(2), pages 153-201, March.
  • Thomas Lustenberger & Enzo Rossi, 2017. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," Working Papers 2017-12, Swiss National Bank.
  • Lustenberger, Thomas & Rossi, Enzo, 2018. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," Working papers 2018/06, Faculty of Business and Economics - University of Basel.
• Oscar Claveria & Ivana Lolic & Enric Monte & Salvador Torra & Petar Soric, 2020. "“Economic determinants of employment sentiment: A socio-demographic analysis for the euro area”," AQR Working Papers 2012001, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2020.
  • Oscar Claveria & Ivana Lolic & Enric Monte & Petar Soric, 2020. "Economic determinants of employment sentiment: A socio-demographic analysis for the euro area," IREA Working Papers 202001, University of Barcelona, Research Institute of Applied Economics, revised Jan 2020.
• Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," IRENE Working Papers 20-05, IRENE Institute of Economic Research.
• Zidong An & João Tovar Jalles, 2020. "On the Performance of US Fiscal Forecasts: Government vs. Private Information," Working Papers REM 2020/0130, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
• Kaiser, Ulrich & Kuhn, Johan Moritz, 2020. "The Value of Publicly Available, Textual and Non-textual Information for Startup Performance Prediction," IZA Discussion Papers 13029, Institute of Labor Economics (IZA).

2019

• Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
• Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2019. "Machine Learning for Forecasting Excess Stock Returns – The Five-Year-View," Graz Economics Papers 2019-06, University of Graz, Department of Economics.
• Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional variance forecasts for long-term stock returns," Graz Economics Papers 2019-08, University of Graz, Department of Economics.
• Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, Department of Economics, Research Program on Forecasting.
• Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
• Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.
  • Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print halshs-02418967, HAL.
  • Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print hal-02105203, HAL.
• Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 433-446, June.
  • Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Post-Print hal-02155402, HAL.
• Brei, Michael & Moreno, Ramon, 2019. "Reserve requirements and capital flows in Latin America," Journal of International Money and Finance, Elsevier, vol. 99(C).
  • Michael Brei & Ramon Moreno, 2018. "Reserve requirements and capital flows in Latin America," BIS Working Papers 741, Bank for International Settlements.
  • Michael Brei & Ramon Moreno, 2019. "Reserve requirements and capital flows in Latin America," Post-Print hal-02504212, HAL.
• Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.
  • Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print hal-02105203, HAL.
  • Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print halshs-02418967, HAL.
• Steffen Q. Mueller & Patrick Ring & Maria Schmidt, 2019. "Forecasting economic decisions under risk: The predictive importance of choice-process data," Working Papers 066, Chair for Economic Policy, University of Hamburg.
• Reslow, André, 2019. "Inefficient Use of Competitors'Forecasts?," Working Paper Series 380, Sveriges Riksbank (Central Bank of Sweden).
• Reslow, André, 2019. "Inefficient Use of Competitors’ Forecasts?," Working Paper Series 2019:9, Uppsala University, Department of Economics.
• Alex Borodin & Victoria Pyatanova & Anton Yashin, 2019. "Bankruptcy Predictions for Air Carriers: Global Market," HSE Economic Journal, National Research University Higher School of Economics, vol. 23(3), pages 418-443.
• Morita, Hiroshi, 2019. "Forecasting Public Investment Using Daily Stock Returns," Discussion paper series HIAS-E-88, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
• SYAHRIL & Raja MASBAR & M. Shabri Abd. MAJID & Sofyan SYAHNUR, 2019. "Does Indonesia As The World Largest Palm Oil Producing Country Determine The World Crude Palm Oil Price Volatility?," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(2), pages 93-104, June.
• Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private Financing of Long‑Term Care: Income, Savings and Reverse Mortgages," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 507-508, pages 5-24.
  • Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private financing of long-term care: income, savings and reverse mortgages," Erudite Working Paper 2019-14, Erudite.
  • Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private financing of long-term care: income, savings and reverse mortgages," Working Papers 14, French Institute for Demographic Studies.
• Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2019. "Mixed-Frequency Models for Tracking Short-Term Economic Developments in Switzerland," International Journal of Central Banking, International Journal of Central Banking, vol. 15(2), pages 151-178, June.
  • Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2017. "Mixed-frequency models for tracking short-term economic developments in Switzerland," Working Papers 2017-02, Swiss National Bank.
• Valentina Aprigliano & Guerino Ardizzi & Libero Monteforte, 2019. "Using Payment System Data to Forecast Economic Activity," International Journal of Central Banking, International Journal of Central Banking, vol. 15(4), pages 55-80, October.
• Benchimol, Jonathan & Bounader, Lahcen, 2018. "Optimal monetary policy under bounded rationality," Research Discussion Papers 9/2018, Bank of Finland.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy Under Bounded Rationality," IMF Working Papers 19/166, International Monetary Fund.
  • Jonathan Benchimol & Lahcen Bounader, 2018. "Optimal Monetary Policy Under Bounded Rationality," Globalization Institute Working Papers 336, Federal Reserve Bank of Dallas, revised 01 Jan 2018.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy under Bounded Rationality," Bank of Israel Working Papers 2019.07, Bank of Israel.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," NBER Working Papers 26569, National Bureau of Economic Research, Inc.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "Iassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, Institute of Labor Economics (IZA).
• Emmanuel Antwi & Emmanuel Numapau Gyamfi & Kwabena A. Kyei, 2019. "Modeling And Forecasting Ghana’s Inflation Rate Under Threshold Models," Journal of Developing Areas, Tennessee State University, College of Business, vol. 53(3), pages 93-105, Summer.
• Nyoni, Thabani, 2019. "Is the United States of America (USA) really being made great again? witty insights from the Box-Jenkins ARIMA approach," MPRA Paper 91353, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Modeling and forecasting population in Bangladesh: a Box-Jenkins ARIMA approach," MPRA Paper 91394, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Where is Kenya being headed to? Empirical evidence from the Box-Jenkins ARIMA approach," MPRA Paper 91395, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Is Nigeria's economy progressing or backsliding? Implications from ARIMA models," MPRA Paper 91396, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Time series modeling and forecasting of the consumer price index in Japan," MPRA Paper 92409, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Forecasting UK consumer price index using Box-Jenkins ARIMA models," MPRA Paper 92410, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Forecasting consumer price index in Norway: An application of Box-Jenkins ARIMA models," MPRA Paper 92411, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Forecasting Australian CPI using ARIMA models," MPRA Paper 92412, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Predicting CPI in Singapore: An application of the Box-Jenkins methodology," MPRA Paper 92413, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Time series modeling and forecasting of the consumer price index in Belgium," MPRA Paper 92414, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Understanding CPI dynamics in Canada," MPRA Paper 92415, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Predicting CPI in France," MPRA Paper 92416, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Forecasting CPI in Sweden," MPRA Paper 92418, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Predicting CPI in Panama," MPRA Paper 92419, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Modeling and forecasting CPI in Myanmar: An application of ARIMA models," MPRA Paper 92420, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Analyzing CPI dynamics in Italy," MPRA Paper 92421, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Predicting consumer price index in Saudi Arabia," MPRA Paper 92422, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Modeling and forecasting CPI in Mauritius," MPRA Paper 92423, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Can Algeria be the first African country to outsmart the Malthusian population trap? Insights from the ARIMA approach," MPRA Paper 92425, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Prediction of Inflation in Algeria using ARIMA models," MPRA Paper 92426, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Understanding inflation trends in Israel: A univariate approach," MPRA Paper 92427, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Modeling and forecasting inflation in Lesotho using Box-Jenkins ARIMA models," MPRA Paper 92428, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Modeling and forecasting inflation in Philippines using ARIMA models," MPRA Paper 92429, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Predicting inflation in Senegal: An ARMA approach," MPRA Paper 92431, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Predicting inflation in Sri Lanka using ARMA models," MPRA Paper 92432, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Forecasting total population in Yemen using Box-Jenkins ARIMA models," MPRA Paper 92433, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "A Box-Jenkins ARIMA approach to the population question in Pakistan: A reliable prognosis," MPRA Paper 92434, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Where is Eritrea going in terms of population growth? Insights from the ARIMA approach," MPRA Paper 92435, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Predicting total population in India: A Box-Jenkins ARIMA approach," MPRA Paper 92436, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Forecasting the population of Brazil using the Box-Jenkins ARIMA approach," MPRA Paper 92437, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "What will be China's population in 2050? Evidence from the Box-Jenkins approach," MPRA Paper 92439, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Addressing the population question in Mexico: A Box-Jenkins ARIMA approach," MPRA Paper 92440, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Is South Africa the South Africa we all desire? Insights from the Box-Jenkins ARIMA approach," MPRA Paper 92441, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "ARIMA modeling and forecasting of Consumer Price Index (CPI) in Germany," MPRA Paper 92442, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Forecasting inflation in Burkina Faso using ARMA models," MPRA Paper 92443, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Modeling and forecasting inflation in Burundi using ARIMA models," MPRA Paper 92444, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "ARIMA modeling and forecasting of inflation in Egypt (1960-2017)," MPRA Paper 92446, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Understanding inflation trends in Finland: A univariate approach," MPRA Paper 92448, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Inflation dynamics in Jamaica: Evidence from the ARMA methodology," MPRA Paper 92449, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Inflation dynamics in Niger unlocked: An ARMA approach," MPRA Paper 92450, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Understanding inflation patterns in Thailand: An ARMA approach," MPRA Paper 92451, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Predicting inflation in the Kingdom of Bahrain using ARIMA models," MPRA Paper 92452, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Modeling and forecasting CPI in Iran: A univariate analysis," MPRA Paper 92454, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Uncovering inflation dynamics in Morocco: An ARIMA approach," MPRA Paper 92455, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Box-Jenkins ARIMA approach to predicting total population in Russia," MPRA Paper 92456, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Somalia population dynamics versus the Malthusian population trap: What does the ARIMA approach tell us?," MPRA Paper 92457, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Modeling and forecasting inflation in Tanzania using ARIMA models," MPRA Paper 92458, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Will the United States of America (USA) be a beneficiary of the Alburg (1998) and Becker et al (1999) prophecies? Recent insights from the Box-Jenkins ARIMA approach," MPRA Paper 92459, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Understanding inflation dynamics in the United States of America (USA): A univariate approach," MPRA Paper 92460, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Modeling and forecasting remittances in Bangladesh using the Box-Jenkins ARIMA methodology," MPRA Paper 92463, University Library of Munich, Germany.
• João A. Bastos, 2019. "Forecasting the capacity of mobile networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(2), pages 231-242, October.
  • Bastos, João A., 2019. "Forecasting the capacity of mobile networks," MPRA Paper 92727, University Library of Munich, Germany.
• Voisin, Elisa & Hecq, Alain, 2019. "Forecasting bubbles with mixed causal-noncausal autoregressive models," MPRA Paper 92734, University Library of Munich, Germany.
• Bonino-Gayoso, Nicolás & García-Hiernaux, Alfredo, 2019. "TF-MIDAS: a new mixed-frequency model to forecast macroeconomic variables," MPRA Paper 93366, University Library of Munich, Germany.
• Yang, Bill Huajian, 2019. "Monotonic Estimation for the Survival Probability over a Risk-Rated Portfolio by Discrete-Time Hazard Rate Models," MPRA Paper 93398, University Library of Munich, Germany.
• Yang, Bill Huajian, 2019. "Monotonic Estimation for Probability Distribution and Multivariate Risk Scales by Constrained Minimum Generalized Cross-Entropy," MPRA Paper 93400, University Library of Munich, Germany.
• T. Bazhenov & D. Fantazzini, 2019. "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," Russian Journal of Industrial Economics, MISiS.
  • Bazhenov, Timofey & Fantazzini, Dean, 2019. "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," MPRA Paper 93544, University Library of Munich, Germany.
• Yang, Bill Huajian & Wu, Biao & Cui, Kaijie & Du, Zunwei & Fei, Glenn, 2019. "IFRS9 Expected Credit Loss Estimation: Advanced Models for Estimating Portfolio Loss and Weighting Scenario Losses," MPRA Paper 93634, University Library of Munich, Germany.
• Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," MPRA Paper 93802, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "What will be Botswana's population in 2050? Evidence from the Box-Jenkins approach," MPRA Paper 93977, University Library of Munich, Germany.
• Nyoni, Thabani & Mutongi, Chipo, 2019. "Can Afghanistan be a victim of the Malthusian population trap? what does the ARIMA approach tell us?," MPRA Paper 93978, University Library of Munich, Germany.
• Nyoni, Thabani & Mutongi, Chipo & Nyoni, Munyaradzi & Hamadziripi, Oscar Hapanyengwi, 2019. "Understanding inflation dynamics in the Kingdom of Eswatini: a univariate approach," MPRA Paper 93979, University Library of Munich, Germany.
• Nyoni, Thabani & Mutongi, Chipo, 2019. "Modeling and forecasting inflation in The Gambia: an ARMA approach," MPRA Paper 93980, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "Demystifying inflation dynamics in Rwanda: an ARMA approach," MPRA Paper 93982, University Library of Munich, Germany.
• Nyoni, Thabani & Mutongi, Chipo, 2019. "Prediction of total population in Togo using ARIMA models," MPRA Paper 93983, University Library of Munich, Germany.
• Nyoni, Thabani & Mutongi, Chipo, 2019. "Modeling and forecasting carbon dioxide emissions in China using Autoregressive Integrated Moving Average (ARIMA) models," MPRA Paper 93984, University Library of Munich, Germany.
• Nyoni, Thabani & Mutongi, Chipo & Munyaradzi, Nyoni, 2019. "Population dynamics in Gambia: an ARIMA approach," MPRA Paper 93985, University Library of Munich, Germany.
• Nyoni, Thabani & Muchingami, Lovemore, 2019. "Foreign Direct Investment (FDI) dynamics in India: what do ARIMA models tell us?," MPRA Paper 93986, University Library of Munich, Germany.
• Nyoni, Thabani & Muchingami, Lovemore, 2019. "Modeling and forecasting Botswana's Growth Domestic Product (GDP) per capita," MPRA Paper 93987, University Library of Munich, Germany.
• Benedikt Maas, 2020. "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
  • Maas, Benedikt, 2019. "Short-term forecasting of the US unemployment rate," MPRA Paper 94066, University Library of Munich, Germany.
• Shah, Syed Sibghatullah, 2019. "On Trust Dynamics of Economic Growth," MPRA Paper 94095, University Library of Munich, Germany, revised 30 May 2019.
• Jair N. Ojeda-Joya, 2014. "A Consumption-Based Approach to Exchange Rate Predictability," BORRADORES DE ECONOMIA 012339, BANCO DE LA REPÚBLICA.
  • Ojeda-Joya, Jair, 2019. "A consumption-based approach to exchange rate predictability," MPRA Paper 94231, University Library of Munich, Germany.
  • Jair N. Ojeda-Joya, 2014. "A Consumption-Based Approach to Exchange Rate Predictability," Borradores de Economia 857, Banco de la Republica de Colombia.
• Degiannakis, Stavros & Filis, George, 2019. "Oil price volatility forecasts: What do investors need to know?," MPRA Paper 94445, University Library of Munich, Germany.
• Dmitriy, Skrypnik & Marina, Shakleina, 2019. "Counter sanctions and well-being population of Russia: econometric analyses," MPRA Paper 94478, University Library of Munich, Germany.
• Pourghorban, Mojtaba & Mamipour, Siab, 2019. "Day-ahead electricity price forecasting with emphasis on its volatility in Iran (GARCH combined with ARIMA models)," MPRA Paper 94826, University Library of Munich, Germany.
• Bucci, Andrea, 2019. "Cholesky-ANN models for predicting multivariate realized volatility," MPRA Paper 95137, University Library of Munich, Germany.
• Quaas, Georg, 2019. "Ferndiagnose des RWI-Konjunkturmodells
  [Remote diagnosis of the RWI business cycle model]," MPRA Paper 95292, University Library of Munich, Germany.
• Bucci, Andrea, 2019. "Realized Volatility Forecasting with Neural Networks," MPRA Paper 95443, University Library of Munich, Germany.
• Loermann, Julius & Maas, Benedikt, 2019. "Nowcasting US GDP with artificial neural networks," MPRA Paper 95459, University Library of Munich, Germany.
• Indaco, Agustín, 2019. "From Twitter to GDP: Estimating Economic Activity From Social Media," MPRA Paper 95885, University Library of Munich, Germany.
• Chakraborty, Lekha & Chakraborty, Pinaki & Shrestha, Ruzel, 2019. "Budget Credibility of Subnational Governments: Analyzing the Fiscal Forecasting Errors of 28 States in India," MPRA Paper 95921, University Library of Munich, Germany.
• Dean Fantazzini & Stephan Zimin, 2020. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 19-69, March.
  • Fantazzini, Dean & Zimin, Stephan, 2019. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," MPRA Paper 95988, University Library of Munich, Germany.
• Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 55, pages 5-31.
  • Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," MPRA Paper 95992, University Library of Munich, Germany.
• Bhadury, Soumya & Ghosh, Saurabh & Kumar, Pankaj, 2019. "Nowcasting GDP Growth Using a Coincident Economic Indicator for India," MPRA Paper 96007, University Library of Munich, Germany.
• Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019-07, Business School - Economics, University of Glasgow.
• Chatziantoniou, Ioannis & Degiannakis, Stavros & Delis, Panagiotis & Filis, George, 2019. "Can spillover effects provide forecasting gains? The case of oil price volatility," MPRA Paper 96266, University Library of Munich, Germany.
• Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2019. "Forecasting Realized Volatility of Agricultural Commodities," MPRA Paper 96267, University Library of Munich, Germany.
• Stavros Degiannakis & George Filis, 2019. "Forecasting European economic policy uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 94-114, February.
  • Stavros Degiannakis & George Filis, 2018. "Forecasting European Economic Policy Uncertainty," BAFES Working Papers BAFES15, Department of Accounting, Finance & Economic, Bournemouth University.
  • Degiannakis, Stavros & Filis, George, 2019. "Forecasting European Economic Policy Uncertainty," MPRA Paper 96268, University Library of Munich, Germany.
• Maas, Benedikt, 2019. "Nowcasting and forecasting US recessions: Evidence from the Super Learner," MPRA Paper 96408, University Library of Munich, Germany.
• Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," Energy Economics, Elsevier, vol. 81(C), pages 639-649.
  • Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," MPRA Paper 96446, University Library of Munich, Germany.
• Valdivia Coria, Joab Dan & Valdivia Coria, Daney David, 2019. "Construcción de una Bolivia artificial: Efectos de la Política Económica desde 2006
  [Construction of an artificial Bolivia: Effects of the Economic Policy since 2006]," MPRA Paper 96626, University Library of Munich, Germany.
• Troy Lorde & Antonio Alleyne & Roger Hosein & Mu Yifei, 2020. "Should the Caribbean Look to the East? An Assessment of Caribbean Export Potential," The International Trade Journal, Taylor & Francis Journals, vol. 34(1), pages 136-150, January.
  • Lorde, Troy & Alleyne, Antonio & Hosein, Roger & Yifei, Mu, 2019. "Should the Caribbean Look to the East? An Assessment of Caribbean Export Potential," MPRA Paper 96641, University Library of Munich, Germany.
• Jackson, Emerson Abraham & Tamuke, Edmund & Jabbie, Mohamed, 2019. "Disaggregated Short-Term Inflation Forecast (STIF) for Monetary Policy Decision in Sierra Leone," MPRA Paper 96735, University Library of Munich, Germany, revised 26 Nov 2019.
• Nyoni, Thabani, 2019. "The population question in Zimbabwe: reliable projections from the Box – Jenkins ARIMA approach," MPRA Paper 96791, University Library of Munich, Germany.
• Jackson, Emerson Abraham & Tamuke, Edmund, 2019. "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," MPRA Paper 96845, University Library of Munich, Germany, revised 23 Dec 2019.
• Gharsallah, Sofian & Sucarrat, Genaro, 2019. "Hvor presise er prognosene i Nasjonalbudsjettet?
  [How precise are the forecasts of the Norwegian national budget?]," MPRA Paper 96850, University Library of Munich, Germany.
• Mullat, Joseph, 2019. "The Financing Dilemma Supporting a Project," MPRA Paper 96879, University Library of Munich, Germany.
• Nyoni, Thabani, 2019. "An ARIMA analysis of the Indian Rupee/USD exchange rate in India," MPRA Paper 96908, University Library of Munich, Germany.
• Pincheira, Pablo & Hardy, Nicolás, 2019. "Forecasting Aluminum Prices with Commodity Currencies," MPRA Paper 97005, University Library of Munich, Germany.
• Aknouche, Abdelhakim & Francq, Christian, 2019. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," MPRA Paper 97382, University Library of Munich, Germany.
• Maurizio Bovi, 2020. "A time-varying expectations formation mechanism," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(1), pages 69-103, April.
  • Bovi, Maurizio, 2019. "A Time-Varying Expectations Formation Mechanism," MPRA Paper 97624, University Library of Munich, Germany.
• Pincheira, Pablo & Hernández, Ana María, 2019. "Forecasting Unemployment Rates with International Factors," MPRA Paper 97855, University Library of Munich, Germany.
• Emara, Noha & Ma, Jinpeng, 2019. "An Analysis of the Seasonal Cycle and the Business Cycle," MPRA Paper 99310, University Library of Munich, Germany.
• Oguzhan Cepni & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2019. "Time-Varying Risk Aversion and the Predictability of Bond Premia," Working Papers 201906, University of Pretoria, Department of Economics.
• Joao F. Caldeira & Rangan Gupta & Tahir Suleman & Hudson S. Torrent, 2019. "Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis," Working Papers 201911, University of Pretoria, Department of Economics.
• Oguzhan Cepni & Rangan Gupta & Mark E. Wohar, 2019. "Variants of Consumption-Wealth Ratios and Predictability of U.S. Government Bond Risk Premia: Old is still Gold," Working Papers 201912, University of Pretoria, Department of Economics.
• Oguzhan Cepni & Rangan Gupta & Mark E. Wohar, 2019. "The Role of Real Estate Uncertainty in Predicting US Home Sales Growth: Evidence from a Quantiles-Based Bayesian Model Averaging Approach," Working Papers 201936, University of Pretoria, Department of Economics.
• Elie Bouri & Riza Demirer & Rangan Gupta & Xiaojin Sun, 2019. "The Predictability of Stock Market Volatility in Emerging Economies: Relative Roles of Local, Regional and Global Business Cycles," Working Papers 201938, University of Pretoria, Department of Economics.
• Oguzhan Cepni & Rangan Gupta & I. Ethem Guney & M. Hasan Yilmaz, 2019. "Forecasting Local Currency Bond Risk Premia of Emerging Markets: The Role of Cross-Country Macro-Financial Linkages," Working Papers 201957, University of Pretoria, Department of Economics.
• Rangan Gupta & Xiaojin Sun, 2019. "Forecasting Economic Policy Uncertainty of BRIC Countries Using Bayesian VARs," Working Papers 201961, University of Pretoria, Department of Economics.
• Elie Bouri & Riza Demirer & Rangan Gupta & Mark E. Wohar, 2019. "Gold, Platinum and the Predictability of Bond Risk Premia," Working Papers 201967, University of Pretoria, Department of Economics.
• Oguzhan Cepni & I. Ethem Guney & Rangan Gupta & Mark E. Wohar, 2019. "The Role of an Aligned Investor Sentiment Index in Predicting Bond Risk Premia of the United States," Working Papers 201973, University of Pretoria, Department of Economics.
• Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2019. "High-Frequency Volatility Forecasting of US Housing Markets," Working Papers 201977, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2019. "A Moving Average Heterogeneous Autoregressive Model for Forecasting the Realized Volatility of the US Stock Market: Evidence from Over a Century of Data," Working Papers 201978, University of Pretoria, Department of Economics.
• Vasilios Plakandaras & Elie Bouri & Rangan Gupta, 2019. "Forecasting Bitcoin Returns: Is there a Role for the U.S. – China Trade War?," Working Papers 201980, University of Pretoria, Department of Economics.
• Mehmet Balcilar & Edmond Berisha & Oguzhan Cepni & Rangan Gupta, 2019. "The Predictive Power of the Term Spread on Inequality in the United Kingdom: An Empirical Analysis," Working Papers 201981, University of Pretoria, Department of Economics.
• Miroslav Navratil & Andrea Kolkova, 2019. "Decomposition and Forecasting Time Series in the Business Economy Using Prophet Forecasting Model," Central European Business Review, University of Economics, Prague, vol. 2019(4), pages 26-39.
• Pavel Jasek & Lenka Vrana & Lucie Sperkova & Zdenek Smutny & Marek Kobulsky, 2019. "Predictive Performance of Customer Lifetime Value Models in E-Commerce and the Use of Non-Financial Data," Prague Economic Papers, University of Economics, Prague, vol. 2019(6), pages 648-669.
• Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
  • António Rua & Hossein Hassani & Emmanuel Sirimal Silva & Dimitrios Thomakos, 2019. "Monthly Forecasting of GDP with Mixed Frequency Multivariate Singular Spectrum Analysis," Working Papers w201913, Banco de Portugal, Economics and Research Department.
• Alessio Volpicella, 2019. "SVARs Identification through Bounds on the Forecast Error Variance," Working Papers 890, Queen Mary University of London, School of Economics and Finance.
• A Clements & D Preve, 2019. "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series 120, National Centre for Econometric Research.
• Alexander Ballantyne & Tom Cusbert & Richard Evans & Rochelle Guttmann & Jonathan Hambur & Adam Hamilton & Elizabeth Kendall & Rachael McCririck & Gabriela Nodari & Daniel Rees, 2019. "MARTIN Has Its Place: A Macroeconometric Model of the Australian Economy," RBA Research Discussion Papers rdp2019-07, Reserve Bank of Australia.
• Carl Singleton & J. James Reade & Alsdair Brown, 2018. "Going with your Gut: The (In)accuracy of Forecast Revisions in a Football Score Prediction Game," Working Papers 2018-006, The George Washington University, Department of Economics, Research Program on Forecasting.
  • Carl Singleton & J. James Reade & Alasdair Brown, 2019. "Going with your gut: the (in)accuracy of forecast revisions in a football score prediction game," Economics & Management Discussion Papers em-dp2019-05, Henley Business School, Reading University.
• Guy Elaad & J. James Reade & Carl Singleton, 2019. "Information, prices and efficiency in an online betting market," Economics & Management Discussion Papers em-dp2019-10, Henley Business School, Reading University.
• J. James Reade & Carl Singleton & Alasdair Brown, 2019. "Evaluating Strange Forecasts: The Curious Case of Football Match Scorelines," Economics & Management Discussion Papers em-dp2019-18, Henley Business School, Reading University.
• Sacha Gelfer, 2019. "Data-Rich DSGE Model Forecasts of the Great Recession and its Recovery," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 32, pages 18-41, April.
  • Sacha Gelfer, 2019. "Code and data files for "Data-Rich DSGE Model Forecasts of the Great Recession and its Recovery"," Computer Codes 18-269, Review of Economic Dynamics.
• Sacha Gelfer, 2019. "Data-Rich DSGE Model Forecasts of the Great Recession and its Recovery," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 32, pages 18-41, April.
  • Sacha Gelfer, 2019. "Code and data files for "Data-Rich DSGE Model Forecasts of the Great Recession and its Recovery"," Computer Codes 18-269, Review of Economic Dynamics.
• Thomas R. Cook & Aaron Smalter Hall, 2017. "Macroeconomic Indicator Forecasting with Deep Neural Networks," Research Working Paper RWP 17-11, Federal Reserve Bank of Kansas City, revised 04 Sep 2017.
  • Thomas Cook, 2019. "Macroeconomic Indicator Forecasting with Deep Neural Networks," 2019 Meeting Papers 402, Society for Economic Dynamics.
• Melo, Luis F. & Loaiza, Rubén A. & Villamizar-Villegas, Mauricio, 2016. "Bayesian combination for inflation forecasts: The effects of a prior based on central banks’ estimates," Economic Systems, Elsevier, vol. 40(3), pages 387-397.
  • Luis F. Melo Velandia & Rubén A. Loaiza Maya & Mauricio Villamizar-Villegas, 2014. "Bayesian Combination for Inflation Forecasts: The Effects of a Prior Based on Central Banks’ Estimates," BORRADORES DE ECONOMIA 012323, BANCO DE LA REPÚBLICA.
  • Melo-Velandia, Luis Fernando & Loaiza, Rubén & Villamizar-Villegas, Mauricio, 2019. "Bayesian Combination for Inflation Forecasts: The Effects of a Prior Based on Central Banks’ Estimates," Working papers 8, Red Investigadores de Economía.
  • Luis F. Melo Velandia & Rubén A. Loaiza Maya & Mauricio Villamizar-Villegas, 2014. "Bayesian Combination for Inflation Forecasts: The Effects of a Prior Based on Central Banks’ Estimates," Borradores de Economia 853, Banco de la Republica de Colombia.
• Juan José Echavarría & Iader Giraldo & Fernando Jaramillo, 2019. "Cadenas globales de valor, crecimiento y protección arancelaria en Colombia," Borradores de Economia 1080, Banco de la Republica de Colombia.
  • Echavarría, Juan José & Giraldo, Iader & Jaramillo, Fernando, 2019. "Cadenas globales de valor, crecimiento y protección arancelaria en Colombia," Working papers 9, Red Investigadores de Economía.
• Sen Gupta, Abhijit & Iyer, Tara, 2019. "Quarterly Forecasting Model for India’s Economic Growth: Bayesian Vector Autoregression Approach," ADB Economics Working Paper Series 573, Asian Development Bank.
• Iyer , Tara & Sen Gupta, Abhijit, 2019. "Nowcasting Economic Growth in India: The Role of Rainfall," ADB Economics Working Paper Series 593, Asian Development Bank.
• Moiseev, Nikita & Volodin, Andrei, 2019. "Increasing the accuracy of macroeconomic time series forecast by incorporating functional and correlational dependencies between them," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 53, pages 119-137.
• Gorlin, Yury & Kartseva, Marina & Lyashok, Victor, 2019. "The impact of the retirement age increase on the poverty level of the Russian population: Microsimulation analysis," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 54, pages 26-50.
• Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 55, pages 5-31.
  • Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," MPRA Paper 95992, University Library of Munich, Germany.
• Dionne, Georges & Zhou, Xiaozhou, 2019. "Information Environments and High Price Impact Trades: Implication for Volatility and Price Efficiency," Working Papers 19-3, HEC Montreal, Canada Research Chair in Risk Management, revised 04 Nov 2019.
• Niels Gilbert, 2019. "Euro area sovereign risk spillovers before and after the ECB's OMT announcement," DNB Working Papers 636, Netherlands Central Bank, Research Department.
• Page, Adrian & Lambrias, Kyriacos, 2019. "The performance of the Eurosystem/ECB staff macroeconomic projections since the financial crisis," Economic Bulletin Articles, European Central Bank, vol. 8.
• Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1658-1668.
  • Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: a multi-country BVAR benchmark for the Eurosystem projections," Working Paper Series 2227, European Central Bank.
• Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
• Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
• Chavleishvili, Sulkhan & Manganelli, Simone, 2019. "Forecasting and stress testing with quantile vector autoregression," Working Paper Series 2330, European Central Bank.
• de Bondt, Gabe & Gieseck, Arne & Herrero, Pablo & Zekaite, Zivile, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Research Technical Papers 15/RT/19, Central Bank of Ireland.
  • de Bondt, Gabe & Gieseck, Arne & Zekaite, Zivile & Herrero, Pablo, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Working Paper Series 2343, European Central Bank.
• Yao Thibaut Kpegli & Bator Anne, 2019. "Poisson-model Analysis of Power Alternation in Africa," International Journal of Economics and Financial Issues, Econjournals, vol. 9(1), pages 116-120.
• Chin-Sheng Huang & Yi-Sheng Liu, 2019. "Machine Learning on Stock Price Movement Forecast: The Sample of the Taiwan Stock Exchange," International Journal of Economics and Financial Issues, Econjournals, vol. 9(2), pages 189-201.
• Mariem Talbi & Amel Ben Halima, 2019. "Global Contagion of Investor Sentiment during the US Subprime Crisis: The Case of the USA and the Region of Latin America," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 163-174.
• Arindam Banerjee, 2019. "Forecasting of India VIX as a Measure of Sentiment," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 268-276.
• Chia-Cheng Chen & Yisheng Liu & Ting-Hsin Hsu, 2019. "An Analysis on Investment Performance of Machine Learning: An Empirical Examination on Taiwan Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 1-10.
• Ademola Abdulkareem & E. J. Okoroafor & Ayokunle Awelewa & Aderibigbe Adekitan, 2019. "Pseudo-Inverse Matrix Model for Estimating Long-Term Annual Peak Electricity Demand: The Covenant University’s Experience," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 103-109.
• Warsono Warsono & Edwin Russel & Wamiliana Wamiliana & Widiarti Widiarti & Mustofa Usman, 2019. "Modeling and Forecasting by the Vector Autoregressive Moving Average Model for Export of Coal and Oil Data (Case Study from Indonesia over the Years 2002-2017)," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 240-247.
• Lucheroni, Carlo & Boland, John & Ragno, Costantino, 2019. "Scenario generation and probabilistic forecasting analysis of spatio-temporal wind speed series with multivariate autoregressive volatility models," Applied Energy, Elsevier, vol. 239(C), pages 1226-1241.
• Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019. "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, vol. 60(C), pages 45-68.
• Guo, Jing & Zhang, Zhengyu, 2019. "Does renaming promote economic development? New evidence from a city-renaming reform experiment in China," China Economic Review, Elsevier, vol. 57(C).
• McKenzie, David & Sansone, Dario, 2019. "Predicting entrepreneurial success is hard: Evidence from a business plan competition in Nigeria," Journal of Development Economics, Elsevier, vol. 141(C).
• Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
  • Wilko Bolt & Maria Demertzis & Cees Diks & Cars Hommes & Marco van der Leij, 2014. "Identifying Booms and Busts in House Prices under Heterogeneous Expectations," Tinbergen Institute Discussion Papers 14-157/II, Tinbergen Institute.
  • Bolt, W. & Demertzis, D. & Diks, C.G.H. & Van der Leij, M.J., 2014. "Identifying Booms and Busts in House Prices under Heterogeneous Expectations," CeNDEF Working Papers 14-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  • Wilko Bolt & Maria Demertzis & Cees Diks & Cars Hommes & Marco van der Leij, 2014. "Identifying Booms and Busts in House Prices under Heterogeneous Expectations," European Economy - Economic Papers 2008 - 2015 540, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
  • Wilko Bolt & Maria Demertzis & Cees Diks & Cars Hommes & Marco van der Leij, 2014. "Identifying booms and busts in house prices under heterogeneous expectations," DNB Working Papers 450, Netherlands Central Bank, Research Department.
• Kapetanios, George & Masolo, Riccardo M. & Petrova, Katerina & Waldron, Matthew, 2019. "A time-varying parameter structural model of the UK economy," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.
  • Petrova, Katerina & Kapetanios, George & Masolo, Riccardo & Waldron, Matthew, 2017. "A time varying parameter structural model of the UK economy," Bank of England working papers 677, Bank of England.
• Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
• Zhang, Han & Fan, Xiaoyun & Guo, Bin & Zhang, Wei, 2019. "Reexamining time-varying bond risk premia in the post-financial crisis era," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
• Plachel, Lukas, 2019. "A unified model for regularized and robust portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
• Kolidakis, Stylianos & Botzoris, George & Profillidis, Vassilios & Lemonakis, Panagiotis, 2019. "Road traffic forecasting — A hybrid approach combining Artificial Neural Network with Singular Spectrum Analysis," Economic Analysis and Policy, Elsevier, vol. 64(C), pages 159-171.
• Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
• Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019. "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, vol. 78(C), pages 32-39.
• El-Shagi, Makram, 2019. "Rationality tests in the presence of instabilities in finite samples," Economic Modelling, Elsevier, vol. 79(C), pages 242-246.
• González-Astudillo, Manuel & Baquero, Daniel, 2019. "A nowcasting model for Ecuador: Implementing a time-varying mean output growth," Economic Modelling, Elsevier, vol. 82(C), pages 250-263.
• Tissaoui, Kais & Azibi, Jamel, 2019. "International implied volatility risk indexes and Saudi stock return-volatility predictabilities," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 65-84.
• Salisu, Afees A. & Isah, Kazeem & Akanni, Lateef O., 2019. "Improving the predictability of stock returns with Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 857-867.
• Nonejad, Nima, 2019. "Forecasting aggregate equity return volatility using crude oil price volatility: The role of nonlinearities and asymmetries," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
• Paccagnini, Alessia, 2019. "Did financial factors matter during the Great Recession?," Economics Letters, Elsevier, vol. 174(C), pages 26-30.
• Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient matrix approach for classical inference in state space models," Economics Letters, Elsevier, vol. 181(C), pages 22-27.
  • Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient Matrix Approach for Classical Inference in State Space Models," EMF Research Papers 19, Economic Modelling and Forecasting Group.
• Uddin, Gazi Salah & Gençay, Ramazan & Bekiros, Stelios & Sahamkhadam, Maziar, 2019. "Enhancing the predictability of crude oil markets with hybrid wavelet approaches," Economics Letters, Elsevier, vol. 182(C), pages 50-54.
• Cuesta, Jose & Chagalj, Cristian, 2019. "Measuring poverty with administrative data in data deprived contexts: The case of Nicaragua," Economics Letters, Elsevier, vol. 183(C), pages 1-1.
• Gozgor, Giray & Lau, Chi Keung Marco & Sheng, Xin & Yarovaya, Larisa, 2019. "The role of uncertainty measures on the returns of gold," Economics Letters, Elsevier, vol. 185(C).
• Bunjira Makond & Mayuening Eso, 2019. "Predictive Models for Classifying the Outcomes of Violence Case Study for Thailand’s Deep South," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(3), pages 56-92, September.
• Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
• Søren Kjærgaard & Yunus Emre Ergemen & Malene Kallestrup-Lamb & Jim Oeppen & Rune Lindahl-Jacobsen, 2019. "Forecasting Causes of Death using Compositional Data Analysis: the Case of Cancer Deaths," CREATES Research Papers 2019-07, Department of Economics and Business Economics, Aarhus University.
• Søren Kjærgaard & Yunus Emre Ergemen & Marie-Pier Bergeron Boucher & Jim Oeppen & Malene Kallestrup-Lamb, 2019. "Longevity forecasting by socio-economic groups using compositional data analysis," CREATES Research Papers 2019-08, Department of Economics and Business Economics, Aarhus University.
• Daniel Borup & Erik Christian Montes Schütte, 2019. "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers 2019-13, Department of Economics and Business Economics, Aarhus University.
• Kristoffer Pons Bertelsen, 2019. "Comparing Tests for Identification of Bubbles," CREATES Research Papers 2019-16, Department of Economics and Business Economics, Aarhus University.
• Malene Kallestrup-Lamb & Søren Kjærgaard & Carsten P. T. Rosenskjold, 2019. "Insight into Stagnating Life Expectancy: Analysing Cause of Death Patterns across Socio-economic Groups," CREATES Research Papers 2019-20, Department of Economics and Business Economics, Aarhus University.
• Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2019. "Modeling, Forecasting, and Nowcasting U.S. CO2 Emissions Using Many Macroeconomic Predictors," CREATES Research Papers 2019-21, Department of Economics and Business Economics, Aarhus University.
• Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," CEREDEC Working Papers 19/022, Centre de Recherche pour le Développement Economique (CEREDEC).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Research Africa Network Working Papers 19/022, Research Africa Network (RAN).
  • Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Foreign aid, instability and governance in Africa," Working Papers 19/022, European Xtramile Centre of African Studies (EXCAS).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Working Papers of the African Governance and Development Institute. 19/022, African Governance and Development Institute..
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Sarthak Behera & Hyeongwoo Kim, 2019. "Forecasting Dollar Real Exchange Rates and the Role of Real Activity Factors," Auburn Economics Working Paper Series auwp2019-04, Department of Economics, Auburn University.
• Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Research Africa Network Working Papers 19/022, Research Africa Network (RAN).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," CEREDEC Working Papers 19/022, Centre de Recherche pour le Développement Economique (CEREDEC).
  • Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Foreign aid, instability and governance in Africa," Working Papers 19/022, European Xtramile Centre of African Studies (EXCAS).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Working Papers of the African Governance and Development Institute. 19/022, African Governance and Development Institute..
• T. Bazhenov & D. Fantazzini, 2019. "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," Russian Journal of Industrial Economics, MISiS.
  • Bazhenov, Timofey & Fantazzini, Dean, 2019. "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," MPRA Paper 93544, University Library of Munich, Germany.
• Ali Babikir & Mohammed Elamin Hassan & Henry Mwambi, 2019. "Asymmetry, Fat-tail and Autoregressive Conditional Density in Daily Stocks Return Data," Annals of Economics and Statistics, GENES, issue 135, pages 57-68.
• Lukas Kremens & Ian Martin, 2019. "The Quanto Theory of Exchange Rates," American Economic Review, American Economic Association, vol. 109(3), pages 810-843, March.
  • Kremens, Lukas & Martin, Ian, 2017. "The Quanto Theory of Exchange Rates," CEPR Discussion Papers 11970, C.E.P.R. Discussion Papers.
  • Kremens, Lukas & Martin, Ian, 2019. "The quanto theory of exchange rates," LSE Research Online Documents on Economics 89839, London School of Economics and Political Science, LSE Library.
• Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2019. "Vulnerable Growth," American Economic Review, American Economic Association, vol. 109(4), pages 1263-1289, April.
  • Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2016. "Vulnerable growth," Staff Reports 794, Federal Reserve Bank of New York, revised 01 Nov 2017.
  • Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2018. "Vulnerable Growth," Liberty Street Economics 20180409, Federal Reserve Bank of New York.
  • Nina Boyarchenko & Domenico Giannone & Tobias Adrian, 2017. "Vulnerable Growth," 2017 Meeting Papers 1317, Society for Economic Dynamics.
  • Adrian, Tobias & Boyarchenko, Nina & Giannone, Domenico, 2016. "Vulnerable Growth," CEPR Discussion Papers 11583, C.E.P.R. Discussion Papers.
• Daniel J. Wilson, 2019. "Clearing the Fog: The Predictive Power of Weather for Employment Reports and Their Asset Price Responses," American Economic Review: Insights, American Economic Association, vol. 1(3), pages 373-388, December.
  • Daniel J. Wilson, 2017. "Clearing the Fog: The Predictive Power of Weather for Employment Reports and their Asset Price Responses," Working Paper Series 2017-13, Federal Reserve Bank of San Francisco, revised 14 Jun 2017.
• Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2019. "The Impact of Big Data on Firm Performance: An Empirical Investigation," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 33-37, May.
  • Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2018. "The Impact of Big Data on Firm Performance: An Empirical Investigation," NBER Working Papers 24334, National Bureau of Economic Research, Inc.
• Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Research Africa Network Working Papers 19/022, Research Africa Network (RAN).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Working Papers of the African Governance and Development Institute. 19/022, African Governance and Development Institute..
  • Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Foreign aid, instability and governance in Africa," Working Papers 19/022, European Xtramile Centre of African Studies (EXCAS).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," CEREDEC Working Papers 19/022, Centre de Recherche pour le Développement Economique (CEREDEC).
• Tomasz Serafin & Bartosz Uniejewski & Rafał Weron, 2019. "Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, Open Access Journal, vol. 12(13), pages 1-12, July.
  • Tomasz Serafin & Bartosz Uniejewski & Rafal Weron, 2019. "Averaging predictive distributions across calibration windows for day-ahead electricity price forecasting," WORking papers in Management Science (WORMS) WORMS/19/08, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, revised 06 Jul 2019.
• Anindya Banerjee & Victor Bystrov & Paul Mizen, 2017. "Structural Factor Analysis of Interest Rate Pass Through In Four Large Euro Area Economies," Working Papers in Economics 17/07, University of Canterbury, Department of Economics and Finance.
  • Anindya Banerjee & Victor Bystrov & Paul Mizen, 2019. "Structural Factor Analysis of Interest Rate Pass Through in Four Large Euro Area Economies," Lodz Economics Working Papers 1/2019, University of Lodz, Faculty of Economics and Sociology.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "Iassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, Institute of Labor Economics (IZA).
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
• Matteo Mogliani, 2019. "Bayesian MIDAS penalized regressions: estimation, selection, and prediction," Working papers 713, Banque de France.
  • Matteo Mogliani & Anna Simoni, 2019. "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers 1903.08025, arXiv.org, revised Jan 2020.
• Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," PIER Working Paper Archive 20-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers 1912.10774, arXiv.org.
  • Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Working Paper Series 2020-02, Federal Reserve Bank of San Francisco, revised 11 Jan 2020.
• Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2019. "Focused Bayesian Prediction," Papers 1912.12571, arXiv.org.
  • Ruben Loaiza-Maya & Gael M Martin & David T. Frazier, 2020. "Focused Bayesian Prediction," Monash Econometrics and Business Statistics Working Papers 1/20, Monash University, Department of Econometrics and Business Statistics.
• Minjae Park & Mi Lim Lee & Jinpyo Lee, 2019. "Predicting Stock Market Indices Using Classification Tools," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 9(2), pages 243-256, February.
• Roland Füss & Massimo Guidolin & Christian Koeppel, 2019. "Sentiment Risk Premia In The Cross-Section of Global Equity," Working Papers on Finance 1913, University of St. Gallen, School of Finance, revised May 2020.
  • Roland Fuess & Massimo Guidolin & Christian Koeppel, 2019. "Sentiment Risk Premia in the Cross-Section of Global Equity and Currency Returns," BAFFI CAREFIN Working Papers 19116, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Ekaterina Tzvetanova, 2019. "Adaptation of the Altman’s Corporate Insolvency Prediction Model – The Bulgarian Case," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 125-142.
• Tobias Hartl & Roland Weigand, 2018. "Multivariate Fractional Components Analysis," Papers 1812.09149, arXiv.org, revised Jan 2019.
  • Hartl, Tobias & Weigand, Roland, 2019. "Multivariate Fractional Components Analysis," University of Regensburg Working Papers in Business, Economics and Management Information Systems 38283, University of Regensburg, Department of Economics.
• Dany Brouillette & Marie-Noëlle Robitaille & Laurence Savoie-Chabot & Pierre St-Amant & Bassirou Gueye & Elise Martin, 2019. "The Trend Unemployment Rate in Canada: Searching for the Unobservable," Staff Working Papers 19-13, Bank of Canada.
• Luis Julián Álvarez, 2019. "El índice de precios de consumo: usos y posibles vías de mejora," Occasional Papers 1910, Banco de España;Occasional Papers Homepage.
• Mar Delgado-Téllez & Enrique Moral-Benito & Javier J. Pérez, 2019. "Outsourcing and public expenditure: an aggregate perspective with regional data," Working Papers 1939, Banco de España;Working Papers Homepage.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
  • Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: obtaining measures of multi-horizon uncertainty from survey density forecasts," Working Papers 1947, Banco de España;Working Papers Homepage.
  • Gegerly Ganics & Barbara Rossi & Tatevik Sekhposyan, 2020. "From Fixed-Event to Fixed-Horizon Density Forecasts: Obtaining Measures of Multi-Horizon Uncertainty from Survey Density Forecasts," Working Papers 1142, Barcelona Graduate School of Economics.
• Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area," Working papers 733, Banque de France.
  • Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR forecasts, survey information and structural change in the euro area," Working Papers 1948, Banco de España;Working Papers Homepage.
• Franecsca Carta, 2019. "Timely indicators for labour income inequality," Questioni di Economia e Finanza (Occasional Papers) 503, Bank of Italy, Economic Research and International Relations Area.
• Angela Capolongo & Claudia Pacella, 2019. "Forecasting inflation in the euro area: countries matter!," Temi di discussione (Economic working papers) 1224, Bank of Italy, Economic Research and International Relations Area.
• Fabio Busetti & Michele Caivano & Davide Delle Monache, 2019. "Domestic and global determinants of inflation: evidence from expectile regression," Temi di discussione (Economic working papers) 1225, Bank of Italy, Economic Research and International Relations Area.
• Valentina Aprigliano & Danilo Liberati, 2019. "Using credit variables to date business cycle and to estimate the probabilities of recession in real time," Temi di discussione (Economic working papers) 1229, Bank of Italy, Economic Research and International Relations Area.
• Francisco Lasso-Valderrama & Héctor M. Zárate-Solano, 2019. "Forecasting the Colombian Unemployment Rate Using Labour Force Flows," Borradores de Economia 1073, Banco de la Republica de Colombia.
• María Fernanda Meneses-González & Javier Eliecer Pirateque-Niño & Santiago David Segovia-Baquero, 2019. "Indicadores de alerta temprana para el sector corporativo privado colombiano," Borradores de Economia 1084, Banco de la Republica de Colombia.
• Carlos León, 2019. "Detecting anomalous payments networks: A dimensionality reduction approach," Borradores de Economia 1098, Banco de la Republica de Colombia.
• Matteo Mogliani & Anna Simoni, 2019. "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers 1903.08025, arXiv.org, revised Jan 2020.
  • Matteo Mogliani, 2019. "Bayesian MIDAS penalized regressions: estimation, selection, and prediction," Working papers 713, Banque de France.
• Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
• Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR forecasts, survey information and structural change in the euro area," Working Papers 1948, Banco de España;Working Papers Homepage.
  • Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area," Working papers 733, Banque de France.
• Yiru Wang & Barbara Rossi, 2019. "VAR-based Granger-causality test in the presence of instabilities," Economics Working Papers 1642, Department of Economics and Business, Universitat Pompeu Fabra.
  • Yiru Wang & Barbara Rossi, 2019. "VAR-Based Granger-Causality Test in the Presence of Instabilities," Working Papers 1083, Barcelona Graduate School of Economics.
• Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• María Gil & Javier J. Pérez & Alberto Urtasun, 2019. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • María Gil & Javier J. Pérez & A. Jesús Sánchez & Alberto Urtasun, 2018. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," Working Papers 1842, Banco de España;Working Papers Homepage.
• Burcu Erik & Marco Jacopo Lombardi & Dubravko Mihaljek & Hyun Song Shin, 2019. "Financial conditions and purchasing managers' indices: exploring the links," BIS Quarterly Review, Bank for International Settlements, September.
• Borio, Claudio & Brei, Michael & Gambacorta, Leonardo, 2019. "Bank intermediation activity in a low interest rate environment," CEPR Discussion Papers 13980, C.E.P.R. Discussion Papers.
  • Michael Brei & Claudio Borio, 2019. "Bank intermediation activity in a low interest rate environment," BIS Working Papers 807, Bank for International Settlements.
• Heiner Mikosch & Laura Solanko, 2019. "Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 19-35, March.
• Konstantin Styrin, 2019. "Forecasting Inflation in Russia Using Dynamic Model Averaging," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 3-18, March.
• Nikita Fokin & Andrey Polbin, 2019. "Forecasting Russia's Key Macroeconomic Indicators with the VAR-LASSO Model," Russian Journal of Money and Finance, Bank of Russia, vol. 78(2), pages 67-93, June.
• Denis Shibitov & Mariam Mamedli, 2019. "The finer points of model comparison in machine learning: forecasting based on russian banks’ data," Bank of Russia Working Paper Series wps43, Bank of Russia.
• Sergei Seleznev, 2019. "Truncated priors for tempered hierarchical Dirichlet process vector autoregression," Bank of Russia Working Paper Series wps47, Bank of Russia.
• Ramis Khabibullin, 2019. "What measures of real economic activity slack are helpful for forecasting Russian inflation?," Bank of Russia Working Paper Series wps50, Bank of Russia.
• Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
  • Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
• Dario Sansone, 2019. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(2), pages 456-485, April.
  • Dario Sansone, 2017. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Working Papers gueconwpa~17-17-09, Georgetown University, Department of Economics.
• Stavros Degiannakis & George Filis, 2019. "Forecasting European economic policy uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 94-114, February.
  • Stavros Degiannakis & George Filis, 2018. "Forecasting European Economic Policy Uncertainty," BAFES Working Papers BAFES15, Department of Accounting, Finance & Economic, Bournemouth University.
  • Degiannakis, Stavros & Filis, George, 2019. "Forecasting European Economic Policy Uncertainty," MPRA Paper 96268, University Library of Munich, Germany.
• Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.
  • L. Ferrara & C. Marsilli, 2014. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Working papers 515, Banque de France.
  • Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Post-Print hal-01636761, HAL.
• JACKSON Emerson Abraham & TAMUKE Edmund & JABBIE Mohamed, 2019. "Disaggregated Short-Term Inflation Forecast (Stif) For Monetary Policy Decision In Sierra Leone," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 71(3), pages 31-53, November.
  • Jackson, Emerson Abraham & Tamuke, Edmund & Jabbie, Mohamed, 2019. "Disaggregated Short-Term Inflation Forecast (STIF) for Monetary Policy Decision in Sierra Leone," MPRA Paper 96735, University Library of Munich, Germany, revised 26 Nov 2019.
• Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Papers No 01/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
• Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Papers No 03/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Paper 2019/5, Norges Bank.
• Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
  • Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman K. van Dijk, 2019. "Partially Censored Posterior for robust and efficient risk evaluation," Working Paper 2019/12, Norges Bank.
• Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
  • Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Papers No 01/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Paper 2019/5, Norges Bank.
  • Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Papers No 03/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Suss, Joel & Treitel, Henry, 2019. "Predicting bank distress in the UK with machine learning," Bank of England working papers 831, Bank of England.
• Stanisławska, Ewa & Paloviita, Maritta & Łyziak, Tomasz, 2019. "Assessing reliability of aggregated inflation views in the European Commission consumer survey," Research Discussion Papers 10/2019, Bank of Finland.
• Benchimol, Jonathan & Bounader, Lahcen, 2018. "Optimal monetary policy under bounded rationality," Research Discussion Papers 9/2018, Bank of Finland.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy under Bounded Rationality," Bank of Israel Working Papers 2019.07, Bank of Israel.
  • Jonathan Benchimol & Lahcen Bounader, 2018. "Optimal Monetary Policy Under Bounded Rationality," Globalization Institute Working Papers 336, Federal Reserve Bank of Dallas, revised 01 Jan 2018.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy Under Bounded Rationality," IMF Working Papers 19/166, International Monetary Fund.
• Jonathan Benchimol & Makram El-Shagi, 2017. "Forecast Performance in Times of Terrorism," CFDS Discussion Paper Series 2017/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
  • Jonathan Benchimol & Makram El-Shagi, 2019. "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers 2019.08, Bank of Israel.
• Bruno Deschamps & Christos Ioannidis & Kook Ka, 2019. "High-Frequency Credit Spread Information and Macroeconomic Forecast Revision," Working Papers 2019-17, Economic Research Institute, Bank of Korea.
• Rahul Roy & Santhakumar Shijin, 2019. "The nexus of anomalies-stock returns-asset pricing models: The international evidence," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 19(1), pages 1-14, March.
• Fugazza Carolina, 2019. "Anatomy of Non-Employment Risk," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 19(3), pages 1-19, July.
• Bruttel Oliver & Baumann Arne & Dütsch Matthias, 2019. "Beschäftigungseffekte des gesetzlichen Mindestlohns: Prognosen und empirische Befunde," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 20(3), pages 237-253, September.
• Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
• Ahmed, M. F.. & Satchell, S, 2019. "Some Dynamic and Steady-State Properties of Threshold Autoregressions with Applications to Stationarity and Local Explosivity," Cambridge Working Papers in Economics 1923, Faculty of Economics, University of Cambridge.
• Yang Han & Victor OK Li & Jacqueline CK Lam & Michael Pollitt, 2019. "How BLUE is the Sky? Estimating the Air Quality Data in Beijing During the Blue Sky Day Period (2008-2012) by the Bayesian LSTM Approach," Working Papers EPRG1912, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • Han, Y. & Li, V. & Lam, J. & Pollitt, M., 2019. "How BLUE is the Sky? Estimating the Air Quality Data in Beijing During the Blue Sky Day Period (2008-2012) by the Bayesian LSTM Approach," Cambridge Working Papers in Economics 1929, Faculty of Economics, University of Cambridge.
• Miroslav Klucik, 2019. "Tracking the Course of the Economy (Nowcasting of basic macroeconomic indicators of Slovakia)," Working Papers Working Paper No. 1/2019, Council for Budget Responsibility.
• de Bondt, Gabe & Gieseck, Arne & Zekaite, Zivile & Herrero, Pablo, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Working Paper Series 2343, European Central Bank.
  • de Bondt, Gabe & Gieseck, Arne & Herrero, Pablo & Zekaite, Zivile, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Research Technical Papers 15/RT/19, Central Bank of Ireland.
• Congressional Budget Office, 2019. "An Evaluation of CBO’s Past Deficit and Debt Projections," Reports 55234, Congressional Budget Office.
• Congressional Budget Office, 2019. "CBO’s Economic Forecasting Record: 2019 Update," Reports 55505, Congressional Budget Office.
• Congressional Budget Office, 2019. "The Accuracy of CBO’s Baseline Estimates for Fiscal Year 2019," Reports 55927, Congressional Budget Office.
• Hylke Vandenbussche & William Connell & Wouter Simons, 2019. "Global Value Chains, Trade Shocks and Jobs: An Application to Brexit," CESifo Working Paper Series 7473, CESifo Group Munich.
• Domenico Delli Gatti & Jakob Grazzini, 2019. "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series 7894, CESifo Group Munich.
• Paul Schneider, 2019. "A Theory of Scenario Generation," Swiss Finance Institute Research Paper Series 19-17, Swiss Finance Institute.
• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019. "A Flexible Regime Switching Model for Asset Returns," Swiss Finance Institute Research Paper Series 19-27, Swiss Finance Institute, revised May 2019.
• Rebecca Westphal & Didier Sornette, 2019. "Market Impact and Performance of Arbitrageurs of Financial Bubbles in An Agent-Based Model," Swiss Finance Institute Research Paper Series 19-29, Swiss Finance Institute.
• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019. "A Non-Elliptical Orthogonal GARCH Model for Portfolio Selection under Transaction Costs," Swiss Finance Institute Research Paper Series 19-51, Swiss Finance Institute.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
• Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
• Rossi, Barbara & Sekhposyan, Tatevik, 2019. "Alternative tests for correct specification of conditional predictive densities," Journal of Econometrics, Elsevier, vol. 208(2), pages 638-657.
  • Barbara Rossi & Tatevik Sekhposyan, 2014. "Alternative tests for correct specification of conditional predictive densities," Economics Working Papers 1416, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2017.
  • Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona Graduate School of Economics.
• Liao, Jun & Zong, Xianpeng & Zhang, Xinyu & Zou, Guohua, 2019. "Model averaging based on leave-subject-out cross-validation for vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(1), pages 35-60.
• Boot, Tom & Nibbering, Didier, 2019. "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
• Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 2016_09, Business School - Economics, University of Glasgow.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103R, Brandeis University, Department of Economics and International Businesss School, revised Apr 2016.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Businesss School.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2017. "Bayesian Compressed Vector Autoregressions," Working Paper series 17-32, Rimini Centre for Economic Analysis.
• McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
• Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
  • Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
• Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.
• Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Adaptive hierarchical priors for high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 212(1), pages 241-271.
  • Dimitris Korobilis & Davide Pettenuzzo, 2017. "Adaptive Hierarchical Priors for High-Dimensional Vector Autoregessions," Working Papers 115, Brandeis University, Department of Economics and International Businesss School.
  • Dimitris Korobilis & Davide Pettenuzzo, 2018. "Adaptive Hierarchical Priors for High-Dimensional Vector Autoregressions," Working Paper series 18-21, Rimini Centre for Economic Analysis.
• Giessing, Alexander & He, Xuming, 2019. "On the predictive risk in misspecified quantile regression," Journal of Econometrics, Elsevier, vol. 213(1), pages 235-260.
• Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
• Sutton, Maxwell & Vasnev, Andrey L. & Gerlach, Richard, 2019. "Mixed interval realized variance: A robust estimator of stock price volatility," Econometrics and Statistics, Elsevier, vol. 11(C), pages 43-62.
• Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.
• Ghysels, Eric & Qian, Hang, 2019. "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, vol. 9(C), pages 1-16.
• Al-Sadoon, Majid M., 2019. "Testing subspace Granger causality," Econometrics and Statistics, Elsevier, vol. 9(C), pages 42-61.
  • Majid M. Al-Sadoon, 2015. "Testing subspace Granger causality," Economics Working Papers 1495, Department of Economics and Business, Universitat Pompeu Fabra.
  • Majid M. Al-Sadoon, 2016. "Testing Subspace Granger Causality," Working Papers 850, Barcelona Graduate School of Economics.
• Trucíos, Carlos & Hotta, Luiz K. & Valls Pereira, Pedro L., 2019. "On the robustness of the principal volatility components," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 201-219.
  • Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
• Díaz-Hernández, Adán & Constantinou, Nick, 2019. "A multiple regime extension to the Heston–Nandi GARCH(1,1) model," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 162-180.
• Panopoulou, Ekaterini & Souropanis, Ioannis, 2019. "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 197-221.
• Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
• Westerlund, Joakim & Sharma, Susan Sunila, 2019. "Panel evidence on the ability of oil returns to predict stock returns in the G7 area," Energy Economics, Elsevier, vol. 77(C), pages 3-12.
• Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
• Chen, Rongda & Xu, Jianjun, 2019. "Forecasting volatility and correlation between oil and gold prices using a novel multivariate GAS model," Energy Economics, Elsevier, vol. 78(C), pages 379-391.
• Cheng, Fangzheng & Li, Tian & Wei, Yi-ming & Fan, Tijun, 2019. "The VEC-NAR model for short-term forecasting of oil prices," Energy Economics, Elsevier, vol. 78(C), pages 656-667.
• Jiao, Ying & Ma, Chunhua & Scotti, Simone & Sgarra, Carlo, 2019. "A branching process approach to power markets," Energy Economics, Elsevier, vol. 79(C), pages 144-156.
• Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting: Part II — Probabilistic forecasting," Energy Economics, Elsevier, vol. 79(C), pages 171-182.
  • Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2017. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting," HSC Research Reports HSC/17/02, Hugo Steinhaus Center, Wroclaw University of Technology.
• Maryniak, Paweł & Trück, Stefan & Weron, Rafał, 2019. "Carbon pricing and electricity markets — The case of the Australian Clean Energy Bill," Energy Economics, Elsevier, vol. 79(C), pages 45-58.
• Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
• Kostrzewski, Maciej & Kostrzewska, Jadwiga, 2019. "Probabilistic electricity price forecasting with Bayesian stochastic volatility models," Energy Economics, Elsevier, vol. 80(C), pages 610-620.
• Beyca, Omer Faruk & Ervural, Beyzanur Cayir & Tatoglu, Ekrem & Ozuyar, Pinar Gokcin & Zaim, Selim, 2019. "Using machine learning tools for forecasting natural gas consumption in the province of Istanbul," Energy Economics, Elsevier, vol. 80(C), pages 937-949.
• Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
• Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," Energy Economics, Elsevier, vol. 81(C), pages 639-649.
  • Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," MPRA Paper 96446, University Library of Munich, Germany.
• Liu, Jingzhen & Kemp, Alexander, 2019. "Forecasting the sign of U.S. oil and gas industry stock index excess returns employing macroeconomic variables," Energy Economics, Elsevier, vol. 81(C), pages 672-686.
• Dahl, Christian M. & Effraimidis, Georgios & Pedersen, Mikkel H., 2019. "Nonparametric wind power forecasting under fixed and random censoring," Energy Economics, Elsevier, vol. 84(C).
• Caloia, Francesco Giuseppe & Cipollini, Andrea & Muzzioli, Silvia, 2019. "How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study," Energy Economics, Elsevier, vol. 84(C).
• Khalifa, Ahmed & Caporin, Massimiliano & Di Fonzo, Tommaso, 2019. "Scenario-based forecast for the electricity demand in Qatar and the role of energy efficiency improvements," Energy Policy, Elsevier, vol. 127(C), pages 155-164.
• Baldoni, Edoardo & Coderoni, Silvia & D'Orazio, Marco & Di Giuseppe, Elisa & Esposti, Roberto, 2019. "The role of economic and policy variables in energy-efficient retrofitting assessment. A stochastic Life Cycle Costing methodology," Energy Policy, Elsevier, vol. 129(C), pages 1207-1219.
• Maluf de Lima, Lilian & Piedade Bacchi, Mirian Rumenos, 2019. "Assessing the impact of Brazilian economic growth on demand for electricity," Energy, Elsevier, vol. 172(C), pages 861-873.
• Moral-Carcedo, Julián & Pérez-García, Julián, 2019. "Time of day effects of temperature and daylight on short term electricity load," Energy, Elsevier, vol. 174(C), pages 169-183.
• Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019. "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 1-9.
• Bleher, Johannes & Dimpfl, Thomas, 2019. "Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 147-159.
• Tissaoui, Kais, 2019. "Forecasting implied volatility risk indexes: International evidence using Hammerstein-ARX approach," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 232-249.
• Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
• Sensoy, Ahmet, 2019. "The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies," Finance Research Letters, Elsevier, vol. 28(C), pages 68-73.
• Aslanidis, Nektarios & Christiansen, Charlotte & Cipollini, Andrea, 2019. "Predicting bond betas using macro-finance variables," Finance Research Letters, Elsevier, vol. 29(C), pages 193-199.
  • Nektarios Aslanidis & Charlotte Christiansen & Andrea Cipollini, 2017. "Predicting Bond Betas using Macro-Finance Variables," CREATES Research Papers 2017-01, Department of Economics and Business Economics, Aarhus University.
  • Aslanidis, Nektarios, & Christiansen, Charlotte & Cipollini, Andrea & Bons -- Models matemàtics, 2018. "Predicting Bond Betas using Macro-Finance Variables," Working Papers 2072/306546, Universitat Rovira i Virgili, Department of Economics.
• Gupta, Rangan & Pierdzioch, Christian & Vivian, Andrew J. & Wohar, Mark E., 2019. "The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests," Finance Research Letters, Elsevier, vol. 29(C), pages 315-322.
  • Rangan Gupta & Christian Pierdzioch & Andrew J. Vivian & Mark E. Wohar, 2018. "The Predictive Value of Inequality Measures for Stock Returns: An Analysis of Long-Span UK Data Using Quantile Random Forests," Working Papers 201809, University of Pretoria, Department of Economics.
• Troster, Victor & Tiwari, Aviral Kumar & Shahbaz, Muhammad & Macedo, Demian Nicolás, 2019. "Bitcoin returns and risk: A general GARCH and GAS analysis," Finance Research Letters, Elsevier, vol. 30(C), pages 187-193.
• Lei, Likun & Shang, Yue & Chen, Yongfei & Wei, Yu, 2019. "Does the financial crisis change the economic risk perception of crude oil traders? A MIDAS quantile regression approach," Finance Research Letters, Elsevier, vol. 30(C), pages 341-351.
• Chevapatrakul, Thanaset & Mascia, Danilo V., 2019. "Detecting overreaction in the Bitcoin market: A quantile autoregression approach," Finance Research Letters, Elsevier, vol. 30(C), pages 371-377.
• Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019. "Does machine learning help us predict banking crises?," Journal of Financial Stability, Elsevier, vol. 45(C).
• Inoue, Atsushi & Rossi, Barbara, 2019. "The effects of conventional and unconventional monetary policy on exchange rates," Journal of International Economics, Elsevier, vol. 118(C), pages 419-447.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Chapters, in: NBER International Seminar on Macroeconomics 2018, pages 419-447, National Bureau of Economic Research, Inc.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Working Papers 25021, National Bureau of Economic Research, Inc.
  • Atsushi Inoue & Barbara Rossi, 2018. "The effects of conventional and unconventional monetary policy on exchange rates," Economics Working Papers 1639, Department of Economics and Business, Universitat Pompeu Fabra.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," Working Papers 1078, Barcelona Graduate School of Economics.
• Guibert, Quentin & Lopez, Olivier & Piette, Pierrick, 2019. "Forecasting mortality rate improvements with a high-dimensional VAR," Insurance: Mathematics and Economics, Elsevier, vol. 88(C), pages 255-272.
• Ponomareva, Natalia & Sheen, Jeffrey & Wang, Ben Zhe, 2019. "Forecasting exchange rates using principal components," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
• Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
  • Götz, Thomas B. & Knetsch, Thomas A., 2017. "Google data in bridge equation models for German GDP," Discussion Papers 18/2017, Deutsche Bundesbank.
• Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
  • Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
• Frazier, David T. & Maneesoonthorn, Worapree & Martin, Gael M. & McCabe, Brendan P.M., 2019. "Approximate Bayesian forecasting," International Journal of Forecasting, Elsevier, vol. 35(2), pages 521-539.
  • David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Brendan P.M. McCabe, 2018. "Approximate Bayesian forecasting," Monash Econometrics and Business Statistics Working Papers 2/18, Monash University, Department of Econometrics and Business Statistics.
• McAdam, Peter & Warne, Anders, 2019. "Euro area real-time density forecasting with financial or labor market frictions," International Journal of Forecasting, Elsevier, vol. 35(2), pages 580-600.
  • McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
• Panagiotelis, Anastasios & Athanasopoulos, George & Hyndman, Rob J. & Jiang, Bin & Vahid, Farshid, 2019. "Macroeconomic forecasting for Australia using a large number of predictors," International Journal of Forecasting, Elsevier, vol. 35(2), pages 616-633.
  • Bin Jiang & George Athanasopoulos & Rob J Hyndman & Anastasios Panagiotelis & Farshid Vahid, 2017. "Macroeconomic forecasting for Australia using a large number of predictors," Monash Econometrics and Business Statistics Working Papers 2/17, Monash University, Department of Econometrics and Business Statistics.
• Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
  • António Rua & Hossein Hassani & Emmanuel Sirimal Silva & Dimitrios Thomakos, 2019. "Monthly Forecasting of GDP with Mixed Frequency Multivariate Singular Spectrum Analysis," Working Papers w201913, Banco de Portugal, Economics and Research Department.
• Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1533-1547.
  • Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2018. "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," HSC Research Reports HSC/18/07, Hugo Steinhaus Center, Wroclaw University of Technology.
• Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
  • Granziera, Eleonora & Sekhposyan, Tatevik, 2018. "Predicting relative forecasting performance : An empirical investigation," Research Discussion Papers 23/2018, Bank of Finland.
• Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1658-1668.
  • Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: a multi-country BVAR benchmark for the Eurosystem projections," Working Paper Series 2227, European Central Bank.
• Knotek, Edward S. & Zaman, Saeed, 2019. "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1708-1724.
  • Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland, revised 17 Mar 2017.
• Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
  • Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
• Thiele, Stephen, 2019. "Detecting underestimates of risk in VaR models," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 12-20.
• Lazar, Emese & Zhang, Ning, 2019. "Model risk of expected shortfall," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 74-93.
• Gupta, Jairaj & Chaudhry, Sajid, 2019. "Mind the tail, or risk to fail," Journal of Business Research, Elsevier, vol. 99(C), pages 167-185.
• Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
• Fan, Ying & Yang, Zan & Yavas, Abdullah, 2019. "Understanding real estate price dynamics: The case of housing prices in five major cities of China✰," Journal of Housing Economics, Elsevier, vol. 43(C), pages 37-55.
• Auer, Simone, 2019. "Monetary policy shocks and foreign investment income: Evidence from a large Bayesian VAR," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 142-166.
  • Simone Auer, 2014. "Monetary policy shocks and foreign investment income: evidence from a large Bayesian VAR," Globalization Institute Working Papers 170, Federal Reserve Bank of Dallas.
  • Simone Auer, 2014. "Monetary Policy Shocks and Foreign Investment Income: Evidence from a large Bayesian VAR," Working Papers 2014-02, Swiss National Bank.
• Chen, Jian & Jiang, Fuwei & Xue, Shuyu & Yao, Jiaquan, 2019. "The world predictive power of U.S. equity market skewness risk," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 210-227.
• Xu, Zhongxiang & Chevapatrakul, Thanaset & Li, Xiafei, 2019. "Return asymmetry and the cross section of stock returns," Journal of International Money and Finance, Elsevier, vol. 97(C), pages 93-110.
• Brei, Michael & Moreno, Ramon, 2019. "Reserve requirements and capital flows in Latin America," Journal of International Money and Finance, Elsevier, vol. 99(C).
  • Michael Brei & Ramon Moreno, 2018. "Reserve requirements and capital flows in Latin America," BIS Working Papers 741, Bank for International Settlements.
  • Michael Brei & Ramon Moreno, 2019. "Reserve requirements and capital flows in Latin America," Post-Print hal-02504212, HAL.
• Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
• Hwang, Youngjin, 2019. "Forecasting recessions with time-varying models," Journal of Macroeconomics, Elsevier, vol. 62(C).
• Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.
  • Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print halshs-02418967, HAL.
  • Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print hal-02105203, HAL.
• Afik, Zvika & Katz, Hagai, 2019. "Reconsidering the philanthropic foundation minimum payout policy under a “new normal”," Journal of Policy Modeling, Elsevier, vol. 41(2), pages 219-233.
• Álvarez, Luis J. & Sánchez, Isabel, 2019. "Inflation projections for monetary policy decision making," Journal of Policy Modeling, Elsevier, vol. 41(4), pages 568-585.
• Salmanzadeh-Meydani, N. & Fatemi Ghomi, S.M.T., 2019. "The causal relationship among electricity consumption, economic growth and capital stock in Iran," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1230-1256.
• Pincheira Brown, Pablo & Hardy, Nicolás, 2019. "Forecasting base metal prices with the Chilean exchange rate," Resources Policy, Elsevier, vol. 62(C), pages 256-281.
• Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
• Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
• Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2019. "Forecasting the KOSPI200 spot volatility using various volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 156-166.
• Radivojević, Nikola & Cvijanović, Drago & Sekulic, Dejan & Pavlovic, Dejana & Jovic, Srdjan & Maksimović, Goran, 2019. "Econometric model of non-performing loans determinants," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 481-488.
• Demos, G. & Sornette, D., 2019. "Comparing nested data sets and objectively determining financial bubbles’ inceptions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 661-675.
• Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
• Xiao, Binqing & Yang, Ye & Peng, Xuerong & Fang, Libing, 2019. "Measuring the connectedness of European electricity markets using the network topology of variance decompositions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
• Isah, Kazeem O. & Raheem, Ibrahim D., 2019. "The hidden predictive power of cryptocurrencies and QE: Evidence from US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
• Ivo da Rocha Lima Filho, Roberto, 2019. "Does PPI lead CPI IN Brazil?," International Journal of Production Economics, Elsevier, vol. 214(C), pages 73-79.
• Simlai, Prodosh, 2019. "Subprime credit, idiosyncratic risk, and foreclosures," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 175-189.
• Fingleton, Bernard & Szumilo, Nikodem, 2019. "Simulating the impact of transport infrastructure investment on wages: A dynamic spatial panel model approach," Regional Science and Urban Economics, Elsevier, vol. 75(C), pages 148-164.
  • Fingleton, Bernard & Szumilo, Nikodem, 2019. "Simulating the impact of transport infrastructure investment on wages: a dynamic spatial panel model approach," LSE Research Online Documents on Economics 100014, London School of Economics and Political Science, LSE Library.
• Croonenbroeck, Carsten & Stadtmann, Georg, 2019. "Renewable generation forecast studies – Review and good practice guidance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 312-322.
• Balcilar, Mehmet & Gupta, Rangan & Kim, Won Joong & Kyei, Clement, 2019. "The role of economic policy uncertainties in predicting stock returns and their volatility for Hong Kong, Malaysia and South Korea," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 150-163.
• Chevapatrakul, Thanaset & Xu, Zhongxiang & Yao, Kai, 2019. "The impact of tail risk on stock market returns: The role of market sentiment," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 289-301.
• Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
• Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & Maasoumi, Esfandiar & McAleer, Michael & Pérez-Amaral, Teodosio, 2019. "Choosing expected shortfall over VaR in Basel III using stochastic dominance," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 95-113.
  • Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Esfandiar Maasoumi & Michel McAleer & Teodosio Pérez-Amaral, 2015. "Choosing Expected Shortfall over VaR in Basel III Using Stochastic Dominance," Tinbergen Institute Discussion Papers 15-133/III, Tinbergen Institute.
  • Chang, C-L. & Jiménez-Martín, J.A. & Maasoumi, E. & McAleer, M.J., 2015. "Choosing Expected Shortfall over VaR in Basel III Using Stochastic Dominance," Econometric Institute Research Papers EI2015-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Plakandaras, Vasilios & Gogas, Periklis & Papadimitriou, Theophilos & Gupta, Rangan, 2019. "A re-evaluation of the term spread as a leading indicator," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 476-492.
• Śmiech, Sławomir & Papież, Monika & Dąbrowski, Marek A., 2019. "How important are different aspects of uncertainty in driving industrial production in the CEE countries?," Research in International Business and Finance, Elsevier, vol. 50(C), pages 252-266.
• Landini, S. & Uberti, M. & Casellina, S., 2019. "Credit risk migration rates modelling as open systems II: A simulation model and IFRS9-baseline principles," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 175-189.
• Plakandaras, Vasilios & Papadimitriou, Theophilos & Gogas, Periklis, 2019. "Forecasting transportation demand for the U.S. market," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 195-214.
• Aytaç PEKMEZCÄ° & Nevin Güler DÄ°NCER & Öznur İŞÇİGÃœNERÄ°, 2019. "Comparison Of The Performance Of Fuzzy Time Series Methods Based On Clustering In The Econometric Time Series Estimation," JOURNAL OF LIFE ECONOMICS, Rating Academy, vol. 6(3), pages 307-320, July.
• Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
  • Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2019. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model," Jena Economic Research Papers 2019-006, Friedrich-Schiller-University Jena.
• Zied Ftiti & Fredj Jawadi, 2019. "Forecasting Inflation Uncertainty in the United States and Euro Area," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 455-476, June.
• Elettra Agliardi & Thomas Alexopoulos & Christian Cech, 2019. "On the Relationship Between GHGs and Global Temperature Anomalies: Multi-level Rolling Analysis and Copula Calibration," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(1), pages 109-133, January.
• Marzia De Donno & Riccardo Donati & Gino Favero & Paola Modesti, 2019. "Risk estimation for short-term financial data through pooling of stable fits," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(4), pages 447-470, December.
• Heather L. R. Tierney, 2019. "Forecasting with the Nonparametric Exclusion-from-Core Inflation Persistence Model Using Real-Time Data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 39-63, February.
• Riadh Abed & Amna Zardoub, 2019. "On the co-movements among gold and other financial markets: a multivariate time-varying asymmetric approach," International Economics and Economic Policy, Springer, vol. 16(4), pages 701-719, October.
• Sabrina Backs & Markus Günther & Christian Stummer, 2019. "Stimulating academic patenting in a university ecosystem: an agent-based simulation approach," The Journal of Technology Transfer, Springer, vol. 44(2), pages 434-461, April.
• Phillip A. Cartwright & Natalija Riabko, 2019. "Do spot food commodity and oil prices predict futures prices?," Review of Quantitative Finance and Accounting, Springer, vol. 53(1), pages 153-194, July.
• Mihaela Simionescu & Maria-Simona Naros, 2019. "Sustainable Development and the Insertion of Higher Educated Unemployed People on Romanian Labour Market," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 5(1), pages 12-16, March.
• Mirela Catalina Turkes, 2019. "The Evolution of Fertility over the Life Course. A Comparative Study between Romania and Turkey," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 5(1), pages 95-105, March.
• Florian Eckert & Rob J Hyndman & Anastasios Panagiotelis, 2019. "Forecasting Swiss Exports Using Bayesian Forecast Reconciliation," Monash Econometrics and Business Statistics Working Papers 14/19, Monash University, Department of Econometrics and Business Statistics.
  • Florian Eckert & Rob Hyndman & Anastasios Panagiotelis, 2019. "Forecasting Swiss Exports using Bayesian Forecast Reconciliation," KOF Working papers 19-457, KOF Swiss Economic Institute, ETH Zurich.
• Tóth, Tamás & Kulin, Ferenc, 2019. "A megújuló energia részarányának modellezése 2020-as kitekintéssel
  [Modelling the proportion of renewable energy with an outlook up to 2020]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(10), pages 1073-1092.
• Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-07, Economic Statistics Centre of Excellence (ESCoE).
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Discussion Papers in Economics 19/05, Division of Economics, School of Business, University of Leicester.
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Laurynas Narusevicius & Tomas Ramanauskas & Laura Gudauskaitė & Tomas Reichenbachas, 2019. "Lithuanian house price index: modelling and forecasting," Bank of Lithuania Occasional Paper Series 28, Bank of Lithuania.
• Egle Jakucionyte & Swapnil Singh, 2019. "Mortgage Foreclosure Risk After the Great Recession," Bank of Lithuania Working Paper Series 69, Bank of Lithuania.
• P.N. Brusov & T.V. Filatova & N.P. Orekhova & V.L. Kulik & I. Weil, 2019. "Ratings of The Investment Projects of Arbitrary Durations: New Methodology," Journal of Reviews on Global Economics, Lifescience Global, vol. 8, pages 437-448.
• Boriss Siliverstovs, 2020. "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
  • Boriss Siliverstovs, 2019. "Assessing Nowcast Accuracy of US GDP Growth in Real Time: The Role of Booms and Busts," Working Papers 2019/01, Latvijas Banka.
• Daniel Gros & Roberto Musmeci, 2019. "Preparing for the next MFF: Where did the money go in the past?," Working Papers LuissLab 19147, Dipartimento di Economia e Finanza, LUISS Guido Carli.
• José M. Belbute & Alfredo M. Pereira, 2019. "Reference Forecasts for CO2 Emissions from Fossil-Fuel Combustion and Cement Production in Portugal," GEE Papers 00126, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Aug 2019.
• José M. Belbute & Alfredo Marvão Pereira, 2019. "ARFIMA Reference Forecasts for Worldwide CO2 Emissions and the National Dimension of the Policy Efforts to Meet IPCC Targets," GEE Papers 0125, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Aug 2019.
• José M. Belbute & Alfredo M. Pereira, 2019. "ARFIMA Reference Forecasts for Worldwide CO2 Emissions and the Need for Large and Frontloaded Decarbonization Policies," GEE Papers 0135, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Oct 2019.
• Kristen M. Altenburger & Daniel E. Ho, 2019. "When Algorithms Import Private Bias into Public Enforcement: The Promise and Limitations ofStatistical Debiasing Solutions," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 175(1), pages 98-122.
• Sándor Karajz, 2019. "Multi-Agent-Based Macroeconomic Modelling," Theory Methodology Practice (TMP), Faculty of Economics, University of Miskolc, vol. 15(01), pages 19-24.
• Florian Eckert & Rob Hyndman & Anastasios Panagiotelis, 2019. "Forecasting Swiss Exports using Bayesian Forecast Reconciliation," KOF Working papers 19-457, KOF Swiss Economic Institute, ETH Zurich.
  • Florian Eckert & Rob J Hyndman & Anastasios Panagiotelis, 2019. "Forecasting Swiss Exports Using Bayesian Forecast Reconciliation," Monash Econometrics and Business Statistics Working Papers 14/19, Monash University, Department of Econometrics and Business Statistics.
• Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global temperatures and greenhouse gases - a common features approach," Working Papers 2019-07-15, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
  • Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global Temperatures and Greenhouse Gases: A Common Features Approach," Monash Econometrics and Business Statistics Working Papers 23/19, Monash University, Department of Econometrics and Business Statistics.
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for 21st Century Economic Statistics, National Bureau of Economic Research, Inc.
  • Tomaz Cajner & Leland Crane & Ryan Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," Finance and Economics Discussion Series 2019-065, Board of Governors of the Federal Reserve System (U.S.).
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Working Papers 26033, National Bureau of Economic Research, Inc.
• Bekaert, Geert & Panayotov, George, 2020. "Good Carry, Bad Carry," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(4), pages 1063-1094, June.
  • Bekaert, Geert & Panayotov, George, 2019. "Good Carry, Bad Carry," CEPR Discussion Papers 13463, C.E.P.R. Discussion Papers.
  • Geert Bekaert & George Panayotov, 2019. "Good Carry, Bad Carry," NBER Working Papers 25420, National Bureau of Economic Research, Inc.
• Aloosh, Arash & Bekaert, Geert, 2019. "Currency Factors," CEPR Discussion Papers 13464, C.E.P.R. Discussion Papers.
  • Arash Aloosh & Geert Bekaert, 2019. "Currency Factors," NBER Working Papers 25449, National Bureau of Economic Research, Inc.
• John B. Donaldson & Rajnish Mehra, 2019. "Average Crossing Time: An Alternative Characterization of Mean Aversion and Reversion," NBER Working Papers 25519, National Bureau of Economic Research, Inc.
• Samuel Bazzi & Robert A. Blair & Christopher Blattman & Oeindrila Dube & Matthew Gudgeon & Richard Merton Peck, 2019. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," NBER Working Papers 25980, National Bureau of Economic Research, Inc.
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for 21st Century Economic Statistics, National Bureau of Economic Research, Inc.
  • Tomaz Cajner & Leland Crane & Ryan Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," Finance and Economics Discussion Series 2019-065, Board of Governors of the Federal Reserve System (U.S.).
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Working Papers 26033, National Bureau of Economic Research, Inc.
• Sruthi Davuluri & René García Franceschini & Christopher R. Knittel & Chikara Onda & Kelly Roache, 2019. "Machine Learning for Solar Accessibility: Implications for Low-Income Solar Expansion and Profitability," NBER Working Papers 26178, National Bureau of Economic Research, Inc.
• Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019. "Predicting Returns With Text Data," NBER Working Papers 26186, National Bureau of Economic Research, Inc.
• Antoine Arnoud & Fatih Guvenen & Tatjana Kleineberg, 2019. "Benchmarking Global Optimizers," NBER Working Papers 26340, National Bureau of Economic Research, Inc.
• Christopher R. Knittel & Samuel Stolper, 2019. "Using Machine Learning to Target Treatment: The Case of Household Energy Use," NBER Working Papers 26531, National Bureau of Economic Research, Inc.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," NBER Working Papers 26569, National Bureau of Economic Research, Inc.
• Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth, 2019. "Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis," Foundations and Trends(R) in Econometrics, now publishers, vol. 10(1-2), pages 1-144, January.
• Shreshtha, Ruzel & Chakraborty, Lekha S, 2019. "Practising Subnational Public Finance in an Emerging Economy: Fiscal Marksmanship in Kerala," MPRA Paper 93367, University Library of Munich, Germany.
  • Shrestha, Ruzel & Chakraborty, Lekha, 2019. "Practising Subnational Public Finance in an Emerging Economy: Fiscal Marksmanship in Kerala," Working Papers 19/261, National Institute of Public Finance and Policy.
• Chakraborty, Lekha & Chakraborty, Pinaki & Shrestha, Ruzel, 2019. "Budget Credibility of Subnational Governments: Analyzing the Fiscal Forecasting Errors of 28 States in India," Working Papers 19/280, National Institute of Public Finance and Policy.
• Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private Financing of Long‑Term Care: Income, Savings and Reverse Mortgages," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 507-508, pages 5-24.
  • Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private financing of long-term care: income, savings and reverse mortgages," Erudite Working Paper 2019-14, Erudite.
  • Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private financing of long-term care: income, savings and reverse mortgages," Working Papers 14, French Institute for Demographic Studies.
• Jérôme Wittwer, 2019. "Comment – Is Self‑Insurance for Long‑Term Care Risk a Solution?," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 507-508, pages 25-30.
• François Legendre, 2019. "The Emergence and Consolidation of Microsimulation Methods in France," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 510-511-5, pages 201-217.
• Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Discussion Papers in Economics 19/05, Division of Economics, School of Business, University of Leicester.
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-07, Economic Statistics Centre of Excellence (ESCoE).
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Galvao, Ana Beatriz & Mitchell, James, 2019. "Measuring Data Uncertainty : An Application using the Bank of England’s “Fan Charts” for Historical GDP Growth," EMF Research Papers 24, Economic Modelling and Forecasting Group.
  • Ana Beatriz Galvao & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
• Luca Lorenzoni & Alberto Marino & David Morgan & Chris James, 2019. "Health Spending Projections to 2030: New results based on a revised OECD methodology," OECD Health Working Papers 110, OECD Publishing.
• Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
• Nosakhare Liberty Arodoye & John Norense Izevbigie, 2019. "Sectoral Composition And Tax Revenue Performance In Ecowas Countries," Oradea Journal of Business and Economics, University of Oradea, Faculty of Economics, vol. 4(2), pages 45-55, September.
• Mikhail Anufriev & Cars Hommes & Tomasz Makarewicz, 2019. "Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments," Journal of the European Economic Association, European Economic Association, vol. 17(5), pages 1538-1584.
  • Mikhail Anufriev & Cars Hommes & Tomasz Makarewicz, 2015. "Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments," Working Paper Series 29, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
  • Anufriev, M. & Hommes, C.H. & Makarewicz, T.A., 2015. "Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments," CeNDEF Working Papers 15-07, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
• Kevin Sheppard & Wen Xu, 2019. "Factor High-Frequency-Based Volatility (HEAVY) Models," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 17(1), pages 33-65.
• Gong Cheng & Javier Diaz-Cassou & Aitor Erce, 2019. "The macroeconomic effects of official debt restructuring: evidence from the Paris Club," Oxford Economic Papers, Oxford University Press, vol. 71(2), pages 344-363.
  • Gong Cheng & Javier Diaz-Cassou & Aitor Erce, 2016. "The Macroeconomic Effects of Official Debt Restructuring: Evidence from the Paris Club," Working Papers 21, European Stability Mechanism, revised 24 Apr 2017.
• Dominik Wolff & Ulrich Neugebauer, 2019. "Tree-based machine learning approaches for equity market predictions," Journal of Asset Management, Palgrave Macmillan, vol. 20(4), pages 273-288, July.
• Mauricio Zevallos, 2019. "Una nota sobre el pronóstico del riesgo diario de volatilidad en el mercado de valores peruano utilizando retornos intradía," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 42(84), pages 94-101.
• Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Liberty Street Economics 20190821, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," PIER Working Paper Archive 19-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Michael D. Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," NBER Working Papers 26826, National Bureau of Economic Research, Inc.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Staff Reports 893, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," Finance and Economics Discussion Series 2020-023, Board of Governors of the Federal Reserve System (U.S.).
• Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," PIER Working Paper Archive 19-021, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers 1912.10774, arXiv.org.
  • Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," PIER Working Paper Archive 20-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Working Paper Series 2020-02, Federal Reserve Bank of San Francisco, revised 11 Jan 2020.
• Maria Kovacova & Tomas Kliestik & Katarina Valaskova & Pavol Durana & Zuzana Juhaszova, 2019. "Systematic review of variables applied in bankruptcy prediction models of Visegrad group countries," Oeconomia Copernicana, Institute of Economic Research, vol. 10(4), pages 743-772, December.
• Raul V. Fabella & Geoffrey Ducanes, 2019. "Power Industry Disruptors and Prospects of the Electricity Demand in the Greater Metro-Manila Area," UP School of Economics Discussion Papers 201901, University of the Philippines School of Economics.
• Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient matrix approach for classical inference in state space models," Economics Letters, Elsevier, vol. 181(C), pages 22-27.
  • Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient Matrix Approach for Classical Inference in State Space Models," EMF Research Papers 19, Economic Modelling and Forecasting Group.
• Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2018. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-14, Economic Statistics Centre of Excellence (ESCoE).
  • Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
• Ana Beatriz Galvao & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
  • Galvao, Ana Beatriz & Mitchell, James, 2019. "Measuring Data Uncertainty : An Application using the Bank of England’s “Fan Charts” for Historical GDP Growth," EMF Research Papers 24, Economic Modelling and Forecasting Group.
• Juvenal, Luciana & Petrella, Ivan, 2019. "Not all Terms of Trade Shocks are Alike," EMF Research Papers 25, Economic Modelling and Forecasting Group.
• Mitchell, James & Weale, Martin, 2019. "Forecasting with Unknown Unknowns: Censoring and Fat Tails on the Bank of England's Monetary Policy Committee," EMF Research Papers 27, Economic Modelling and Forecasting Group.
• Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
  • Katarzyna Maciejowska & Rafal Weron, 2019. "Electricity price forecasting," HSC Research Reports HSC/19/01, Hugo Steinhaus Center, Wroclaw University of Technology.
• Bartosz Uniejewski & Rafal Weron, 2019. "Regularized Quantile Regression Averaging for probabilistic electricity price forecasting," HSC Research Reports HSC/19/04, Hugo Steinhaus Center, Wroclaw University of Technology.
• Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemyslaw Zaleski & Rafal Weron, 2019. "Balancing RES generation: Profitability of an energy trader," HSC Research Reports HSC/19/07, Hugo Steinhaus Center, Wroclaw University of Technology.
• Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019. "Enhancing load, wind and solar generation forecasts in day-ahead forecasting of spot and intraday electricity prices," HSC Research Reports HSC/19/08, Hugo Steinhaus Center, Wroclaw University of Technology.
• Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global Temperatures and Greenhouse Gases: A Common Features Approach," Monash Econometrics and Business Statistics Working Papers 23/19, Monash University, Department of Econometrics and Business Statistics.
  • Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global temperatures and greenhouse gases - a common features approach," Working Papers 2019-07-15, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
• Alberto Caruso & Laura Coroneo, 2019. "Predicting interest rates in real-time," Discussion Papers 19/18, Department of Economics, University of York.
• Makarewicz, Tomasz, 2019. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," BERG Working Paper Series 141, Bamberg University, Bamberg Economic Research Group.
• Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
  • Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2019. "Exploiting ergodicity in forecasts of corporate profitability," BERG Working Paper Series 147, Bamberg University, Bamberg Economic Research Group.
• Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
  • Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
• Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
• Jackson, Emerson Abraham & Tamuke, Edmund, 2019. "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," EconStor Preprints 202547, ZBW - Leibniz Information Centre for Economics.
• Strohsal, Till & Wolf, Elias, 2019. "Data revisions to German national accounts: Are initial releases good nowcasts?," Discussion Papers 2019/11, Free University Berlin, School of Business & Economics.
• Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019. "Metcalfe's law and herding behaviour in the cryptocurrencies market," Economics Discussion Papers 2019-16, Kiel Institute for the World Economy (IfW).
• Bolgorian, Meysam, 2019. "Can a cusp catastrophe model describe the effect of sanctions on exchange rates?," Economics Discussion Papers 2019-2, Kiel Institute for the World Economy (IfW).
• Thompson, Erica L. & Smith, Leonard A., 2019. "Escape from model-land," Economics Discussion Papers 2019-23, Kiel Institute for the World Economy (IfW).
• Brighton, Henry, 2019. "Beyond quantified ignorance: Rebuilding rationality without the bias bias," Economics Discussion Papers 2019-25, Kiel Institute for the World Economy (IfW).
• Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019. "Metcalfe's law and log-period power laws in the cryptocurrencies market," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 13, pages 1-26.
• Thompson, Erica L. & Smith, Leonard A., 2019. "Escape from model-land," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 13, pages 1-17.
• Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019. "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers 18/2019, Halle Institute for Economic Research (IWH).
• Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers 48/2018, Deutsche Bundesbank.
  • Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," IWH Discussion Papers 2/2019, Halle Institute for Economic Research (IWH).
• João C. Claudio & Katja Heinisch & Oliver Holtemöller, 2020. "Nowcasting East German GDP growth: a MIDAS approach," Empirical Economics, Springer, vol. 58(1), pages 29-54, January.
  • Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
• Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Business Engineering.
• Bormann, Carsten & Schienle, Melanie, 2019. "Detecting structural differences in tail dependence of financial time series," Working Paper Series in Economics 122, Karlsruhe Institute of Technology (KIT), Department of Economics and Business Engineering.
• Ansgar Belke & Jens Klose, 2019. "Forecasting ECB Policy Rates with Different Monetary Policy Rules," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(3), pages 238-252, June.
  • Ansgar Belke & Jens Klose, 2019. "Forecasting ECB Policy Rates with Different Monetary Policy Rules," ROME Working Papers 201906, ROME Network.
  • Belke, Ansgar & Klose, Jens, 2019. "Forecasting ECB policy rates with different monetary policy rules," Ruhr Economic Papers 815, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Döhrn, Roland, 2019. "Comparing forecast accuracy in small samples," Ruhr Economic Papers 833, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Hinterlang, Natascha, 2019. "Predicting Monetary Policy Using Artificial Neural Networks," Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203503, Verein für Socialpolitik / German Economic Association.
• Axenbeck, Janna & Breithaupt, Patrick, 2019. "Web-based innovation indicators: Which firm website characteristics relate to firm-level innovation activity?," ZEW Discussion Papers 19-063, ZEW - Leibniz Centre for European Economic Research.
• Oliver Merz & Raphael Flepp & Egon Franck, 2019. "Sonic Thunder vs Brian the Snail : Fast-sounding racehorse names and prediction accuracy in betting exchange markets," Working Papers 384, University of Zurich, Department of Business Administration (IBW).
• Leo Krippner, 2019. "Will the real eigensystem VAR please stand up? A univariate primer," CAMA Working Papers 2019-01, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-07, Economic Statistics Centre of Excellence (ESCoE).
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Discussion Papers in Economics 19/05, Division of Economics, School of Business, University of Leicester.
• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "An automated prior robustness analysis in Bayesian model comparison," CAMA Working Papers 2019-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," CAMA Working Papers 2019-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Fingleton, Bernard & Szumilo, Nikodem, 2019. "Simulating the impact of transport infrastructure investment on wages: A dynamic spatial panel model approach," Regional Science and Urban Economics, Elsevier, vol. 75(C), pages 148-164.
  • Fingleton, Bernard & Szumilo, Nikodem, 2019. "Simulating the impact of transport infrastructure investment on wages: a dynamic spatial panel model approach," LSE Research Online Documents on Economics 100014, London School of Economics and Political Science, LSE Library.
• Franses, Ph.H.B.F. & Welz, M., 2018. "Evaluating heterogeneous forecasts for vintages of macroeconomic variables," Econometric Institute Research Papers EI2018-47, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Franses, Ph.H.B.F., 2019. "IMA(1,1) as a new benchmark for forecast evaluation," Econometric Institute Research Papers EI2019-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Franses, Ph.H.B.F., 2019. "Professional Forecasters and January," Econometric Institute Research Papers EI2019-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Bhaghoe, S. & Ooft, G. & Franses, Ph.H.B.F., 2019. "Estimates of quarterly GDP growth using MIDAS regressions," Econometric Institute Research Papers EI2019-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Han, Y. & Li, V. & Lam, J. & Pollitt, M., 2019. "How BLUE is the Sky? Estimating the Air Quality Data in Beijing During the Blue Sky Day Period (2008-2012) by the Bayesian LSTM Approach," Cambridge Working Papers in Economics 1929, Faculty of Economics, University of Cambridge.
  • Yang Han & Victor OK Li & Jacqueline CK Lam & Michael Pollitt, 2019. "How BLUE is the Sky? Estimating the Air Quality Data in Beijing During the Blue Sky Day Period (2008-2012) by the Bayesian LSTM Approach," Working Papers EPRG1912, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
• Muhammad Jahanzeb Malik & Muhammad Nadim Hanif, 2019. "Learning from Errors While Forecasting Inflation: A Case for Intercept Correction," International Econometric Review (IER), Econometric Research Association, vol. 11(1), pages 24-38, April.
• Zümre Özdemir Güler & Mehmet Akif Bakýr, 2019. "Performance of Methods Determining Structural Break in Linear Regression Models," International Econometric Review (IER), Econometric Research Association, vol. 11(2), pages 70-83, September.
• O.N. Dmitriev & S.V. Novikov, 2019. "Optimizing the Economic Information Transparency Level of High-Tech Enterprises in the Post-Industrial Globalized Economy," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(3), pages 25-56.
• Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private Financing of Long‑Term Care: Income, Savings and Reverse Mortgages," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 507-508, pages 5-24.
  • Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private financing of long-term care: income, savings and reverse mortgages," Working Papers 14, French Institute for Demographic Studies.
  • Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private financing of long-term care: income, savings and reverse mortgages," Erudite Working Paper 2019-14, Erudite.
• Werner Roeger & Janos Varga & Jan in 't Veld & Lukas Vogel, 2019. "A Model-Based Assessment of the Distributional Impact of Structural Reforms," European Economy - Discussion Papers 2015 - 091, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
• Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Working Papers of the African Governance and Development Institute. 19/022, African Governance and Development Institute..
  • Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Foreign aid, instability and governance in Africa," Working Papers 19/022, European Xtramile Centre of African Studies (EXCAS).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," CEREDEC Working Papers 19/022, Centre de Recherche pour le Développement Economique (CEREDEC).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Research Africa Network Working Papers 19/022, Research Africa Network (RAN).
• Ansgar Belke & Jens Klose, 2019. "Forecasting ECB Policy Rates with Different Monetary Policy Rules," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(3), pages 238-252, June.
  • Ansgar Belke & Jens Klose, 2019. "Forecasting ECB Policy Rates with Different Monetary Policy Rules," ROME Working Papers 201906, ROME Network.
  • Belke, Ansgar & Klose, Jens, 2019. "Forecasting ECB policy rates with different monetary policy rules," Ruhr Economic Papers 815, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Joseph E. Stiglitz, 2019. "An Agenda for Reforming Economic Theory," Frontiers of Economics in China, Higher Education Press, vol. 14(2), pages 149-167, June.
• Charles B. Perkins & J. Christina Wang, 2019. "How Magic a Bullet Is Machine Learning for Credit Analysis? An Exploration with FinTech Lending Data," Working Papers 19-16, Federal Reserve Bank of Boston, revised 14 Oct 2019.
• Rodrigo Hizmeri & Marwan Izzeldin & Anthony Murphy & Mike G. Tsionas, 2019. "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers 1902, Federal Reserve Bank of Dallas.
• John G. Fernald & Eric Hsu & Mark M. Spiegel, 2019. "Is China Fudging Its GDP Figures? Evidence from Trading Partner Data," Working Paper Series 2019-19, Federal Reserve Bank of San Francisco, revised 04 Sep 2019.
• Travis J. Berge & Andrew C. Chang & Nitish R. Sinha, 2019. "Evaluating the Conditionality of Judgmental Forecasts," Finance and Economics Discussion Series 2019-002, Board of Governors of the Federal Reserve System (U.S.).
• Francesca Loria & Christian Matthes & Donghai Zhang, 2019. "Assessing Macroeconomic Tail Risk," Working Paper 19-10, Federal Reserve Bank of Richmond.
  • Francesca Loria & Christian Matthes & Donghai Zhang, 2019. "Assessing Macroeconomic Tail Risk," Finance and Economics Discussion Series 2019-026, Board of Governors of the Federal Reserve System (U.S.).
• Pablo Cuba‐Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019. "Likelihood evaluation of models with occasionally binding constraints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1073-1085, November.
  • Pablo Cuba-Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019. "Likelihood Evaluation of Models with Occasionally Binding Constraints," Finance and Economics Discussion Series 2019-028, Board of Governors of the Federal Reserve System (U.S.).
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for 21st Century Economic Statistics, National Bureau of Economic Research, Inc.
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Working Papers 26033, National Bureau of Economic Research, Inc.
  • Tomaz Cajner & Leland Crane & Ryan Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," Finance and Economics Discussion Series 2019-065, Board of Governors of the Federal Reserve System (U.S.).
• Tyler Pike & Horacio Sapriza & Thomas Zimmermann, 2019. "Bottom-up Leading Macroeconomic Indicators: An Application to Non-Financial Corporate Defaults using Machine Learning," Finance and Economics Discussion Series 2019-070, Board of Governors of the Federal Reserve System (U.S.).
• Gary S. Anderson & Alena Audzeyeva, 2019. "A Coherent Framework for Predicting Emerging Market Credit Spreads with Support Vector Regression," Finance and Economics Discussion Series 2019-074, Board of Governors of the Federal Reserve System (U.S.).
• John H. Rogers & Jiawen Xu, 2019. "How Well Does Economic Uncertainty Forecast Economic Activity?," Finance and Economics Discussion Series 2019-085, Board of Governors of the Federal Reserve System (U.S.).
• Lewis Gaul & Jonathan Jones & Pinar Uysal, 2019. "Forecasting High-Risk Composite CAMELS Ratings," International Finance Discussion Papers 1252, Board of Governors of the Federal Reserve System (U.S.).
• Scott A. Brave & Charles S. Gascon & William Kluender & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Real Time," Working Papers 2019-037, Federal Reserve Bank of St. Louis, revised 29 Nov 2019.
  • Scott Brave & Charles Gascon & William Kluender & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Realtime," Working Paper Series WP 2019-11, Federal Reserve Bank of Chicago.
• Michael W. McCracken, 2019. "Tests of Conditional Predictive Ability: Some Simulation Evidence," Working Papers 2019-11, Federal Reserve Bank of St. Louis, revised 01 Mar 2019.
• Michael W. McCracken, 2019. "Diverging Tests of Equal Predictive Ability," Working Papers 2019-018, Federal Reserve Bank of St. Louis, revised 09 Mar 2020.
• Michael W. McCracken & Joseph McGillicuddy & Michael T. Owyang, 2019. "Binary Conditional Forecasts," Working Papers 2019-29, Federal Reserve Bank of St. Louis.
• Scott Brave & Charles Gascon & William Kluender & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Realtime," Working Paper Series WP 2019-11, Federal Reserve Bank of Chicago.
  • Scott A. Brave & Charles S. Gascon & William Kluender & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Real Time," Working Papers 2019-037, Federal Reserve Bank of St. Louis, revised 29 Nov 2019.
• Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," PIER Working Paper Archive 19-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Michael D. Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," NBER Working Papers 26826, National Bureau of Economic Research, Inc.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Staff Reports 893, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Liberty Street Economics 20190821, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," Finance and Economics Discussion Series 2020-023, Board of Governors of the Federal Reserve System (U.S.).
• Francesca Loria & Christian Matthes & Donghai Zhang, 2019. "Assessing Macroeconomic Tail Risk," Finance and Economics Discussion Series 2019-026, Board of Governors of the Federal Reserve System (U.S.).
  • Francesca Loria & Christian Matthes & Donghai Zhang, 2019. "Assessing Macroeconomic Tail Risk," Working Paper 19-10, Federal Reserve Bank of Richmond.
• Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
• Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2019. "Realized variance modeling: decoupling forecasting from estimation," Econometrics Working Papers Archive 2019_05, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
• Gijs Dekkers & Ekaterina Tarantchenko & Karel Van den Bosch, 2019. "Working Paper 03-19 - Medium-term projection for Belgium of the at-risk-of-poverty and social exclusion indicators based on EU-SILC
  [Working Paper 03-19 - Prévisions à moyen terme des indicateurs ," Working Papers 1903, Federal Planning Bureau, Belgium.
• Andrey A. Kozlov & Andrey V. Vlasov, 2019. "Cryptoeconomics: Pilot Study on Investments in ICO Startups Using Neural Networks," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 127006, Russia, issue 1, pages 76-87, February.
• Roman S. Leukhin, 2019. "Short-Term Fiscal Projections Using Forecast Combination Approach," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 127006, Russia, issue 3, pages 9-21, June.
• Nataliya G. Filatova, 2019. "Improving the Credit Rating of Loan Recipients Implementing Long-Term Investment Projects," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 127006, Russia, issue 4, pages 102-115, August.
• Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Khromov Mikhail & Tsukhlo Sergey & Kaukin Andrey & Abramov Alexander & Miller Evgenia & Lavrischeva A. & Zhemkova A., 2019. "Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-economic Development," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 2, pages 1-26, January.
• Khromov Mikhail & Tsukhlo Sergey & Florinskaya Yulia & Mkrtchian Nikita & Dobrolyubova E. & Yuzhakov V. & Mkrtchyan N., 2019. "Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-economic Development," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 5, pages 1-18, April.
• Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Khromov Mikhail & Tsukhlo Sergey & Kaukin Andrey & Abramov Alexander & Miller Evgenia & Lavrischeva A. & Zhemkova A., 2019. "Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-economic Development," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 2, pages 1-25, February.
• Khromov Mikhail & Tsukhlo Sergey & Florinskaya Yulia & Mkrtchian Nikita & Dobrolyubova E. & Yuzhakov V., 2019. "Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-economic Development," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 6, pages 1-17, April.
• Tsukhlo Sergey, 2019. "Russian industrial sector in 2018: slowdown of exiting from stagnation of 2012–2016 (on business surveys’ findings)," Published Papers ppaper-2019-969, Gaidar Institute for Economic Policy, revised 2019.
• Barinova Vera & Zemtsov Tsepan & Tsareva Yulia, 2019. "Government support of small and medium sized entrepreneurship in Russia," Published Papers ppaper-2019-977, Gaidar Institute for Economic Policy, revised 2019.
• Meri Papavangjeli, 2019. "Forecasting the Albanian short-term inflation through a Bayesian VAR model," IHEID Working Papers 16-2019, Economics Section, The Graduate Institute of International Studies, revised 09 Oct 2019.
• DRITSAKIS, Nikolaos & KLAZOGLOU, Paraskevi, 2019. "Time Series Analysis using ARIMA Models: An Approach to Forecasting Health Expenditure in USA," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 72(1), pages 77-106.
• Dritsaki, Chaido, 2019. "Modeling the Volatility of Exchange Rate Currency using GARCH Model," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 72(2), pages 209-230.
• Javidi Abdollahzadeh Aval, Narges & Assad Zadeh, Ahmad & Shahmorad, Sedaghat, 2019. "A Comparative Study of the Efficiency of Ponzi Vs. No-Ponzi Economic System Based on Agent-Based Modeling," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 6(3), pages 73-102, October.
• Novkovska, Blagica & Dumicic, Ksenija, 2019. "Ordering Goods And Services Online In South East European Countries: Comparison By Cluster Analysis," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 10(2), pages 163-173.
• A. ISLAS & Víctor M. GUERRERO & Eliud SILVA, 2019. "Forecasting Remittances to Mexico with a Multi-State Markov-Switching Model Applied to the Trend with Controlled Smoothness," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 38-56, March.
• Wojciech CHAREMZA & Carlos DÍAZ & Svetlana MAKAROVA, 2019. "Conditional Term Structure of Inflation Forecast Uncertainty: The Copula Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-18, March.
  • Wojciech Charemza & Carlos Díaz & Svetlana Makarova, 2015. "Conditional Term Structure of Inflation Forecast Uncertainty: The Copula Approach," Discussion Papers in Economics 15/07, Division of Economics, School of Business, University of Leicester.
• Dimitar EFTIMOSKI, 2019. "Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 32-53, June.
• Xianning WANG & Jingrong DONG & Zhi XIAO & Guanjie HE, 2019. "A novel spatial mixed frequency forecasting model with application to Chinese regional GDP," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 54-77, June.
• Gheorghe RUXANDA & Sorin OPINCARIU & Stefan IONESCU, 2019. "Modelling Non-Stationary Financial Time Series with Input Warped Student T-Processes," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 51-61, September.
• Yuchen PAN & Zhi XIAO & Xianning WANG & Daoli YANG, 2019. "A Multi-Indicator Multi-Output Mixed Frequency Sampling Approach for Stock Index Forecasting," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 100-123, December.
• Wali ULLAH, 2019. "The Role of No-Arbitrage Restriction in Term Structure Model in the Context of an Emerging Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 44-66, December.
• Ansgar Belke & Jens Klose, 2019. "Forecasting ECB Policy Rates with Different Monetary Policy Rules," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(3), pages 238-252, June.
  • Belke, Ansgar & Klose, Jens, 2019. "Forecasting ECB policy rates with different monetary policy rules," Ruhr Economic Papers 815, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  • Ansgar Belke & Jens Klose, 2019. "Forecasting ECB Policy Rates with Different Monetary Policy Rules," ROME Working Papers 201906, ROME Network.
• Julia Mortera & A. Philip Dawid, 2019. "Probability Forecasts and Prediction Markets," Departmental Working Papers of Economics - University 'Roma Tre' 0250, Department of Economics - University Roma Tre.
• Paolo Andreini & Donato Ceci, 2019. "A Horse Race in High Dimensional Space," CEIS Research Paper 452, Tor Vergata University, CEIS, revised 14 Feb 2019.
• Tommaso Proietti, 2019. "Predictability, Real Time Estimation, and the Formulation of Unobserved Components Models," CEIS Research Paper 455, Tor Vergata University, CEIS, revised 22 Mar 2019.
• Emilio Zanetti Chini, 2019. "Strategic judgment: its game-theoretic foundations,its econometric elicitation," Working Papers 190, University of Rome La Sapienza, Department of Public Economics.
• Muhammad Ejaz & Javed Iqbal, 2019. "Estimation and Forecasting of Industrial Production Index," SBP Working Paper Series 103, State Bank of Pakistan, Research Department.
• Nájera Salmerón, Jorge Alberto, 2019. "Relaciones en el comportamiento de los precios de las criptomonedas: un análisis econométrico a través de modelos VAR y VEC / Relationship in the Cryptocurrencies Price Behavior: An Econometric Analys," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 9(1), pages 33-61, enero-jun.
• Cristófoli, María Elizabeth & García Fronti, Javier, 2019. "Macroeconomic Reverse Stress Testing: An Early-Warning System for Spanish Banking Regulators. Analysis Based on the 2008 Global Financial Crisis / Prueba de resistencia inversa Macroeconómica: una pru," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 9(2), pages 181-204, julio-dic.
• Zeineb Affes & Rania Hentati-Kaffel, 2019. "Forecast bankruptcy using a blend of clustering and MARS model: case of US banks," Annals of Operations Research, Springer, vol. 281(1), pages 27-64, October.
• James P. LeSage & Daniel Hendrikz, 2019. "Large Bayesian vector autoregressive forecasting for regions: A comparison of methods based on alternative disturbance structures," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 563-599, June.
• Henryk Gurgul & Łukasz Lach, 2019. "On approximating the accelerator part in dynamic input–output models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(1), pages 219-239, March.
• Asmerilda Hitaj & Lorenzo Mercuri & Edit Rroji, 2019. "Lévy CARMA models for shocks in mortality," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 205-227, June.
• Jonathan Haynes & Daniel Schmitt & Lukas Grimm, 2019. "Estimating stochastic volatility: the rough side to equity returns," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 449-469, December.
• Bahar Şen Doğan & Murat Midiliç, 2019. "Forecasting Turkish real GDP growth in a data-rich environment," Empirical Economics, Springer, vol. 56(1), pages 367-395, January.
• Silvija Vlah Jerić & Mihovil Anđelinović, 2019. "Evaluating Croatian stock index forecasts," Empirical Economics, Springer, vol. 56(4), pages 1325-1339, April.
• Natalia Ponomareva & Jeffrey Sheen & Ben Zhe Wang, 2019. "The common component of bilateral US exchange rates: to what is it related?," Empirical Economics, Springer, vol. 56(4), pages 1251-1268, April.
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019. "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, vol. 57(3), pages 923-955, September.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2016. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," MPRA Paper 76308, University Library of Munich, Germany.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," ETA: Economic Theory and Applications 253725, Fondazione Eni Enrico Mattei (FEEM).
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2018. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Papers 1804.08315, arXiv.org.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Working Papers 2017.06, Fondazione Eni Enrico Mattei.
• Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.
• Cees Diks & Cars Hommes & Juanxi Wang, 2019. "Critical slowing down as an early warning signal for financial crises?," Empirical Economics, Springer, vol. 57(4), pages 1201-1228, October.
  • Diks, C.G.H. & Hommes, C.H. & Wang, J., 2015. "Critical Slowing Down as Early Warning Signals for Financial Crises?," CeNDEF Working Papers 15-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
• Paul Lehmann & Jos Sijm & Erik Gawel & Sebastian Strunz & Unnada Chewpreecha & Jean-Francois Mercure & Hector Pollitt, 2019. "Addressing multiple externalities from electricity generation: a case for EU renewable energy policy beyond 2020?," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 21(2), pages 255-283, April.
• Antonio Fabio Forgione & Carlo Migliardo, 2019. "An empirical analysis of the impact of trade credit on bank debt restructuring," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 36(2), pages 415-438, July.
• Carlos Uribe-Teran & Santiago Mosquera, 2019. "Structural factors, global shocks and sovereign debt credit ratings," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(1), pages 104-126, January.
• Oscar Claveria, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-10, December.
• Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 433-446, June.
  • Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Post-Print hal-02155402, HAL.
• Balasubramaniam Meghanadh & Lagesh Aravalath & Bhupesh Joshi & Raghunathan Sathiamoorthy & Manish Kumar, 2019. "Imputation of Missing Values in the Fundamental Data: Using MICE Framework," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(3), pages 459-475, September.
• Rómulo A. Chumacero, 2019. "Skills versus Luck: Bolivia and its recent Bonanza," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 28(1), pages 1-27, December.
• Grant Allan & Gary Koop & Stuart McIntyre & Paul Smith, 2019. "Nowcasting Using Mixed Frequency Methods: An Application to the Scottish Economy," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 12-45, September.
• João A. Bastos, 2019. "Forecasting the capacity of mobile networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(2), pages 231-242, October.
  • Bastos, João A., 2019. "Forecasting the capacity of mobile networks," MPRA Paper 92727, University Library of Munich, Germany.
• Moussa Wajdi, 2019. "The dynamic relationship between stock index and exchange rate: Evidence for Tunis," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 8(1), pages 1-4.
• Moussa Wajdi, 2019. "On the co-movements among Stock prices and exchange rates cointegration: a VAR/VECM approach," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 8(1), pages 1-5.
• Jaka Sriyana, 2019. "What drives economic growth sustainability? Evidence from Indonesia," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(2), pages 906-918, December.
• Milan Vyskrabka & Stanislav Tvrz & Martin Zeleznik, 2019. "PreMISE: DSGE Model of the Slovak Economy Integrated in a Monetary Union," Working and Discussion Papers WP 8/2019, Research Department, National Bank of Slovakia.
• Rachida Ouysse, 2019. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12a, School of Economics, The University of New South Wales.
• Lisa-Cheree Martin, 2019. "Machine Learning vs Traditional Forecasting Methods: An Application to South African GDP," Working Papers 12/2019, Stellenbosch University, Department of Economics.
• Mateo Dulce Rubio, 2019. "Predicting criminal behavior with Lévy flights using real data from Bogotá," Documentos CEDE 017198, Universidad de los Andes - CEDE.
• Trespalacios, Alfredo & Cortés, Lina M. & Perote, Javier, 2020. "Uncertainty in electricity markets from a semi-nonparametric approach," Energy Policy, Elsevier, vol. 137(C).
  • Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2019. "Uncertainty in Electricity Markets from a seminonparametric Approach," Documentos de Trabajo CIEF 017304, Universidad EAFIT.
• Luis Sánchez & Karina Caballero, 2019. "La curva de Kuznets ambiental y su relación con el cambio climático en América Latina y el Caribe: un análisis de cointegración con panel, 1980-2015," Revista de Economía del Rosario, Universidad del Rosario, vol. 22(1), pages 101-142, June.
• Juan Pablo Alfonso Zorro, 2019. "Efectos de las variaciones del IPC en las decisiones financieras," Econógrafos - Escuela de Economía 017329, Universidad Nacional de Colombia -FCE - CID.
• Pérez García, Jorge Iván & Lopera Castaño, Mauricio & Vásquez Bedoya, Fredy Alonso, 2019. "Una breve aplicación a la predicción de la fragilidad de empresas colombianas, mediante el uso de modelos estadísticos," Borradores Departamento de Economía 017525, Universidad de Antioquia - CIE.
• Mateo Dulce Rubio, 2019. "Predicting criminal behavior with Levy flights using real data from Bogota," Documentos de Trabajo Quantil 017347, Quantil.
• Bekaert, Geert & Panayotov, George, 2020. "Good Carry, Bad Carry," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(4), pages 1063-1094, June.
  • Geert Bekaert & George Panayotov, 2019. "Good Carry, Bad Carry," NBER Working Papers 25420, National Bureau of Economic Research, Inc.
  • Bekaert, Geert & Panayotov, George, 2019. "Good Carry, Bad Carry," CEPR Discussion Papers 13463, C.E.P.R. Discussion Papers.
• Arash Aloosh & Geert Bekaert, 2019. "Currency Factors," NBER Working Papers 25449, National Bureau of Economic Research, Inc.
  • Aloosh, Arash & Bekaert, Geert, 2019. "Currency Factors," CEPR Discussion Papers 13464, C.E.P.R. Discussion Papers.
• Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2018. "The global component of inflation volatility," Temi di discussione (Economic working papers) 1170, Bank of Italy, Economic Research and International Relations Area.
  • Carriero, Andrea & Corsello, Francesco & Marcellino, Massimiliano, 2019. "The Global Component of Inflation Volatility," CEPR Discussion Papers 13470, C.E.P.R. Discussion Papers.
• Bazzi, Samuel & Blair, Robert & Blattman, Christopher & Dube, Oeindrila & Gudgeon, Matthew & Peck, Richard, 2019. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," CEPR Discussion Papers 13829, C.E.P.R. Discussion Papers.
• Michael Brei & Claudio Borio, 2019. "Bank intermediation activity in a low interest rate environment," BIS Working Papers 807, Bank for International Settlements.
  • Borio, Claudio & Brei, Michael & Gambacorta, Leonardo, 2019. "Bank intermediation activity in a low interest rate environment," CEPR Discussion Papers 13980, C.E.P.R. Discussion Papers.
• Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," CEPR Discussion Papers 14107, C.E.P.R. Discussion Papers.
• Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.
• Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
• Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2018. "Prediction Regions for Interval-valued Time Series," Working Papers 201817, University of California at Riverside, Department of Economics.
  • Ruiz Ortega, Esther & Luo, Yun & González-Rivera, Gloria, 2019. "Prediction regions for interval-valued time series," DES - Working Papers. Statistics and Econometrics. WS 29054, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2019. "Prediction Regions for Interval-valued Time Series," Working Papers 201921, University of California at Riverside, Department of Economics.
• Moura, Guilherme V. & Ruiz, Esther & Santos, André A. P., 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
• Guillaume MAROIS & Patrick SABOURIN & Alain BÉLANGER, 2019. "Forecasting Human Capital of EU Member Countries Accounting for Sociocultural Determinants," JODE - Journal of Demographic Economics, Cambridge University Press, vol. 85(3), pages 231-269, September.
• Ibrahim D. Raheem & Kazeem Isah, 2019. "The Jolly Ride of International Reserves and Commodity Prices: Evidence from Predictive Models," Working Papers 063, Centre for Econometric and Allied Research, University of Ibadan.
• Elias A. Udeaja & Kazeem Isah, 2019. "Revisiting the accuracy of inflation forecasts in Nigeria: the oil price –exchange rate perspectives," Working Papers 065, Centre for Econometric and Allied Research, University of Ibadan.
• Fries, Sébastien & Zakoian, Jean-Michel, 2019. "Mixed Causal-Noncausal Ar Processes And The Modelling Of Explosive Bubbles," Econometric Theory, Cambridge University Press, vol. 35(6), pages 1234-1270, December.
  • Fries, Sébastien & Zakoian, Jean-Michel, 2017. "Mixed Causal-Noncausal AR Processes and the Modelling of Explosive Bubbles," MPRA Paper 81345, University Library of Munich, Germany.
• Voon, Derby & Fogarty, James, 2019. "A Note on Forecasting Alcohol Demand," Journal of Wine Economics, Cambridge University Press, vol. 14(2), pages 208-213, May.
• Barnett, William A. & Su, Liting, 2019. "Risk Adjustment Of The Credit-Card Augmented Divisia Monetary Aggregates," Macroeconomic Dynamics, Cambridge University Press, vol. 23(S1), pages 90-114, September.
  • Barnett, William & Su, Liting, 2016. "Risk adjustment of the credit-card augmented Divisia monetary aggregates," MPRA Paper 73248, University Library of Munich, Germany.
  • William Barnett & Liting Su, 2016. "Risk Adjustment of the Credit-Card Augmented Divisia Monetary Aggregates," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201606, University of Kansas, Department of Economics, revised Aug 2016.
• Emilio Colombo & Matteo Pelagatti, 2019. "Statistical Learning and Exchange Rate Forecasting," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo dis1901, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS).
• Konstantin A. Kholodilin & Claus Michelsen, 2019. "High Risk of a Housing Bubble in Germany and Most OECD Countries," DIW Weekly Report, DIW Berlin, German Institute for Economic Research, vol. 9(32), pages 265-273.
• Konstantin A. Kholodilin & Claus Michelsen, 2019. "Das Risiko einer Immobilienpreisblase ist in Deutschland sowie in den meisten OECD-Ländern hoch," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 86(32), pages 547-555.
• Diego Winkelried & Javier Torres, 2019. "Economic mobility along the business cycle. The case of Peru," Applied Economics, Taylor & Francis Journals, vol. 51(18), pages 1894-1906, April.
  • Diego Winkelried & Javier Torres, 2017. "Economic mobility along the business cycle. The case of Peru," Working Papers 2017-115, Peruvian Economic Association.
• Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2019. "Is there a role for uncertainty in forecasting output growth in OECD countries? Evidence from a time-varying parameter-panel vector autoregressive model," Applied Economics, Taylor & Francis Journals, vol. 51(33), pages 3624-3631, July.
  • Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2018. "Is There a Role for Uncertainty in Forecasting Output Growth in OECD Countries? Evidence from a Time Varying Parameter-Panel Vector Autoregressive Model," Working Papers 201823, University of Pretoria, Department of Economics.
• Florian Huber & Martin Feldkircher, 2019. "Adaptive Shrinkage in Bayesian Vector Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 27-39, January.
  • Florian Huber & Martin Feldkircher, 2016. "Adaptive shrinkage in Bayesian vector autoregressive models," Department of Economics Working Papers wuwp221, Vienna University of Economics and Business, Department of Economics.
  • Feldkircher, Martin & Huber, Florian, 2016. "Adaptive Shrinkage in Bayesian Vector Autoregressive Models," Department of Economics Working Paper Series 221, WU Vienna University of Economics and Business.
• James Mitchell & Donald Robertson & Stephen Wright, 2019. "R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 681-695, October.
  • Stephen Wright & James Mitchell & Donald Robertson, 2018. "R2 bounds for predictive models: what univariate properties tell us about multivariate predictability," Birkbeck Working Papers in Economics and Finance 1804, Birkbeck, Department of Economics, Mathematics & Statistics.
• Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2019. "Crisis transmission: visualizing vulnerability," Working Papers 2019-07, University of Tasmania, Tasmanian School of Business and Economics.
• Eda Gulsen & Hakan Kara, 2019. "Measuring inflation uncertainty in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 19(2), pages 33-43.
  • Eda Gulsen & Hakan Kara, 2019. "Measuring Inflation Uncertainty in Turkey," Working Papers 1912, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Eda Gulsen & Hakan Kara, 2019. "Measuring inflation uncertainty in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 19(2), pages 33-43.
  • Eda Gulsen & Hakan Kara, 2019. "Measuring Inflation Uncertainty in Turkey," Working Papers 1912, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Mehmet Selman Colak & Ibrahim Ethem Guney & Ahmet Senol & Muhammed Hasan Yilmaz, 2019. "Monitoring and Forecasting Cyclical Dynamics in Bank Credits: Evidence from Turkish Banking Sector," Working Papers 1929, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman K. van Dijk, 2019. "Partially Censored Posterior for robust and efficient risk evaluation," Working Paper 2019/12, Norges Bank.
  • Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
• Sander Barendse & Erik Kole & Dick van Dijk, 2019. "Backtesting Value-at-Risk and Expected Shortfall in the Presence of Estimation Error," Tinbergen Institute Discussion Papers 19-058/III, Tinbergen Institute.
• Heikki Kauppi, 2019. "Recession Prediction with OptimalUse of Leading Indicators," Discussion Papers 125, Aboa Centre for Economics.
• Regis Barnichon & Christian Brownlees, 2019. "Impulse Response Estimation by Smooth Local Projections," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 522-530, July.
  • Barnichon, Régis & Brownlees, Christian, 2016. "Impulse Response Estimation By Smooth Local Projections," CEPR Discussion Papers 11726, C.E.P.R. Discussion Papers.
• Audrone Virbickaite & Christoph Frey & Demian N. Macedo, 2019. "Sequential Stock Return Prediction Through Copulas," DEA Working Papers 91, Universitat de les Illes Balears, Departament d'Economía Aplicada.
• Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2018. "Prediction Regions for Interval-valued Time Series," Working Papers 201817, University of California at Riverside, Department of Economics.
  • Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2019. "Prediction Regions for Interval-valued Time Series," Working Papers 201921, University of California at Riverside, Department of Economics.
  • Ruiz Ortega, Esther & Luo, Yun & González-Rivera, Gloria, 2019. "Prediction regions for interval-valued time series," DES - Working Papers. Statistics and Econometrics. WS 29054, Universidad Carlos III de Madrid. Departamento de Estadística.
• Eva Boj & M. Mercè Claramunt & Anna Castañer & Teresa Costa & Oriol Roch, 2019. "Economic Indicators for automobile claim frequencies," Estudios de Economia, University of Chile, Department of Economics, vol. 46(2), pages 245-271, December.
• Dmytro Krukovets & Olesia Verchenko, 2019. "Short-Run Forecasting of Core Inflation in Ukraine: a Combined ARMA Approach," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 248, pages 11-20.
• Anton Grui & Artem Vdovychenko, 2019. "Quarterly Projection Model for Ukraine," Working Papers 03/2019, National Bank of Ukraine.
• Mohammad Ghaderi & Milosz Kadzinsky, 2019. "Accounting for structural patterns in construction of value functions: a convex optimization approach," Economics Working Papers 1634, Department of Economics and Business, Universitat Pompeu Fabra.
• Yiru Wang & Barbara Rossi, 2019. "VAR-Based Granger-Causality Test in the Presence of Instabilities," Working Papers 1083, Barcelona Graduate School of Economics.
  • Yiru Wang & Barbara Rossi, 2019. "VAR-based Granger-causality test in the presence of instabilities," Economics Working Papers 1642, Department of Economics and Business, Universitat Pompeu Fabra.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: obtaining measures of multi-horizon uncertainty from survey density forecasts," Working Papers 1947, Banco de España;Working Papers Homepage.
  • Gegerly Ganics & Barbara Rossi & Tatevik Sekhposyan, 2020. "From Fixed-Event to Fixed-Horizon Density Forecasts: Obtaining Measures of Multi-Horizon Uncertainty from Survey Density Forecasts," Working Papers 1142, Barcelona Graduate School of Economics.
  • Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
• Do Van Thanh, 2019. "Macro-Econometric Model For Medium-Term Socio-Economic Development Planning In Vietnam. Part 1: Structure Of The Model," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(1), pages 121-136.
• Valery Zh. Dubrovsky & Ekaterina M. Ivanova & Natalia V. Chuprakova, 2019. "Problems of assessing defence contractors’ efficiency," Journal of New Economy, Ural State University of Economics, vol. 20(5), pages 92-107, December.
• Roland Fuess & Massimo Guidolin & Christian Koeppel, 2019. "Sentiment Risk Premia in the Cross-Section of Global Equity and Currency Returns," BAFFI CAREFIN Working Papers 19116, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
  • Roland Füss & Massimo Guidolin & Christian Koeppel, 2019. "Sentiment Risk Premia In The Cross-Section of Global Equity," Working Papers on Finance 1913, University of St. Gallen, School of Finance, revised May 2020.
• Marco Corazza & Giovanni Fasano & Riccardo Gusso & Raffaele Pesenti, 2019. "A comparison among Reinforcement Learning algorithms in financial trading systems," Working Papers 2019:33, Department of Economics, University of Venice "Ca' Foscari".
• Mariana Kaneva, 2019. "Broadband and e-Commerce in the Balkans - Econometric Analysis," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, vol. 8(2), pages 100-109, August.
• Szubzda Filip & Chlebus Marcin, 2019. "Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions," Central European Economic Journal, Sciendo, vol. 6(53), pages 70-85, January.
• Čižmešija Mirjana & Lukač Zrinka & Novoselec Tomislav, 2019. "Nonlinear optimisation approach to proposing novel Croatian Industrial Confidence Indicator," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 5(2), pages 17-26, December.
• Kvainickas Tomas Sovijus & Stankevičienė Jelena, 2019. "Regional Limitations of Stock Indices Prediction Models Based on Macroeconomic Variables," Economics and Culture, Sciendo, vol. 16(2), pages 5-20, December.
• Pelinescu Elena & Simionescu Mihaela, 2019. "Higher Education Policies and Employability of University Graduates in the EU-28," Journal of Intercultural Management, Sciendo, vol. 11(3), pages 105-133, September.
• Bălan Mariana, 2019. "Particularities of the Recent Evolution of Higher Education in Romania. Analysis and Forecasts," Journal of Intercultural Management, Sciendo, vol. 11(3), pages 87-104, September.
• Simionescu Mihaela & Naroș Maria-Simona, 2019. "The Unemployment of Highly Educated People in Romania. A Panel VAR Approach," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 29(3), pages 20-37, September.
• Mateusz Buczyński & Marcin Chlebus, 2019. "Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states," Working Papers 2019-12, Faculty of Economic Sciences, University of Warsaw.
• Michael W. McCracken & Joseph T. McGillicuddy, 2019. "An empirical investigation of direct and iterated multistep conditional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 181-204, March.
  • Michael W. McCracken & Joseph McGillicuddy, 2017. "An Empirical Investigation of Direct and Iterated Multistep Conditional Forecasts," Working Papers 2017-40, Federal Reserve Bank of St. Louis, revised 01 Nov 2017.
• Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2019. "Real‐time forecast combinations for the oil price," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 456-462, April.
  • Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2018. "Real-time forecast combinations for the oil price," CAMA Working Papers 2018-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Anthony Garratt & Shaun P. Vahey & Ynuyi Zhang, 2018. "Real-time Forecast Combinations for the Oil Price," National Institute of Economic and Social Research (NIESR) Discussion Papers 494, National Institute of Economic and Social Research.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.
  • Kapetanios, George & Marcellino, Massimiliano & Venditti, Fabrizio, 2016. "Large Time-Varying Parameter VARs: A Non-Parametric Approach," CEPR Discussion Papers 11560, C.E.P.R. Discussion Papers.
  • George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
• Pablo Cuba‐Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019. "Likelihood evaluation of models with occasionally binding constraints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1073-1085, November.
  • Pablo Cuba-Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019. "Likelihood Evaluation of Models with Occasionally Binding Constraints," Finance and Economics Discussion Series 2019-028, Board of Governors of the Federal Reserve System (U.S.).
• Philip Hans Franses, 2019. "Model‐based forecast adjustment: With an illustration to inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(2), pages 73-80, March.
  • Franses, Ph.H.B.F., 2018. "Model-based forecast adjustment; with an illustration to inflation," Econometric Institute Research Papers EI2018-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Libero Monteforte & Valentina Raponi, 2019. "Short‐term forecasts of economic activity: Are fortnightly factors useful?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 207-221, April.
  • Libero Monteforte & Valentina Raponi, 2018. "Short term forecasts of economic activity: are fortnightly factors useful?," Temi di discussione (Economic working papers) 1177, Bank of Italy, Economic Research and International Relations Area.
• João H. Gonçalves Mazzeu & Helena Veiga & Massimo B. Mariti, 2019. "Modeling and forecasting the oil volatility index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(8), pages 773-787, December.
  • Mariti, Massimo B. & Gonçalves Mazzeu, Joao Henrique & Lopes Moreira Da Veiga, María Helena, 2017. "Modeling and forecasting the oil volatility index," DES - Working Papers. Statistics and Econometrics. WS 25985, Universidad Carlos III de Madrid. Departamento de Estadística.

2018

• Stephen Bazen & Jean-Marie Cardebat, 2018. "Forecasting Bordeaux wine prices using state-space methods," Applied Economics, Taylor & Francis Journals, vol. 50(47), pages 5110-5121, October.
• Tomasz Woźniak, 2018. "Granger-causal analysis of GARCH models: A Bayesian approach," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 325-346, April.
  • Tomasz Wozniak, 2015. "Granger-causal analysis of GARCH models: a Bayesian approach," Department of Economics - Working Papers Series 1194, The University of Melbourne.
• Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch & Mark E. Wohar, 2018. "Terror attacks and stock-market fluctuations: evidence based on a nonparametric causality-in-quantiles test for the G7 countries," The European Journal of Finance, Taylor & Francis Journals, vol. 24(4), pages 333-346, March.
  • Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch & Mark Wohar, 2016. "Terror Attacks and Stock-Market Fluctuations: Evidence Based on a Nonparametric Causality-in-Quantiles Test for the G7 Countries," Working Papers 201608, University of Pretoria, Department of Economics.
• Carlos A. Medel, 2018. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," International Economic Journal, Taylor & Francis Journals, vol. 32(3), pages 331-371, July.
  • Medel, Carlos A., 2015. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," MPRA Paper 67081, University Library of Munich, Germany.
  • Carlos Medel, 2016. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," Working Papers Central Bank of Chile 785, Central Bank of Chile.
• Christian Pierdzioch & Monique B. Reid & Rangan Gupta, 2018. "On the directional accuracy of inflation forecasts: evidence from South African survey data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(5), pages 884-900, April.
  • Christian Pierdzioch & Monique B. Reid & Rangan Gupta, 2014. "On the Directional Accuracy of Inflation Forecasts: Evidence from South African Survey Data," Working Papers 201463, University of Pretoria, Department of Economics.
  • Christian Pierdzioch & Monique B. Reid & Rangan Gupta, 2014. "On the Directional Accuracy of Inflation Forecasts: Evidence from South African Survey Data," Working Papers 24/2014, Stellenbosch University, Department of Economics.
• Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2018. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 675-685, April.
  • Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2015. "Bayesian nonparametric calibration and combination of predictive distributions," Working Paper 2015/03, Norges Bank.
  • Roberto Casarin & Federico Bassetti & Francesco Ravazzolo, 2015. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Working Papers 2015:04, Department of Economics, University of Venice "Ca' Foscari".
• Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
  • Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an Uncertain Economic Environment," Tinbergen Institute Discussion Papers 14-152/III, Tinbergen Institute.
  • Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an uncertain economic environment," Working Paper 2014/17, Norges Bank.
• Rasmus T. Varneskov & Pierre Perron, 2018. "Combining long memory and level shifts in modelling and forecasting the volatility of asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 18(3), pages 371-393, March.
  • Rasmus Tangsgaard Varneskov & Pierre Perron, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," CREATES Research Papers 2011-26, Department of Economics and Business Economics, Aarhus University.
  • Rasmus T. Varneskov & Pierre Perron, 2017. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2017-006, Boston University - Department of Economics.
  • Rasmus T. Varneskov & Pierre Perron, 2015. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series wp2015-015, Boston University - Department of Economics.
  • Pierre Perron & Rasmus T. Varneskov, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2011-050, Boston University - Department of Economics.
• Thomas Brenner & Marco Capasso & Matthias Duschl & Koen Frenken & Tania Treibich, 2018. "Causal relations between knowledge-intensive business services and regional employment growth," Regional Studies, Taylor & Francis Journals, vol. 52(2), pages 172-183, February.
  • Brenner T. & Capasso M. & Duschl M. & Frenken K. & Treibich T.G., 2015. "Causal relations between knowledge-intensive business services and regional employment growth," Research Memorandum 029, Maastricht University, Graduate School of Business and Economics (GSBE).
  • Thomas Brenner & Marco Capasso & Matthias Duschl & Koen Frenken & Tania Treibich, 2015. "Causal Relations between Knowledge-Intensive Business Services and Regional Employment Growth," Papers in Evolutionary Economic Geography (PEEG) 1534, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Oct 2015.
  • Thomas Brenner & Marco Capasso & Matthias Duschl & Koen Frenken & Tania Treibich, 2015. "Causal Relations between Knowledge-Intensive Business Services and Regional Employment Growth," LEM Papers Series 2015/27, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  • Thomas Brenner & Marco Capasso & Matthias Duschl & Koen Frenken & Tania Treibich, 2015. "Causal Relations between Knowledge-Intensive Business Services and Regional Employment Growth," Working Papers on Innovation and Space 2015-04, Philipps University Marburg, Department of Geography.
• Tian, Jing & Goodwin, Thomas, 2018. "An unobserved component modeling approach to evaluate multi-horizon forecasts," Working Papers 2018-04, University of Tasmania, Tasmanian School of Business and Economics.
• Mahmut Gunay, 2018. "Forecasting industrial production and inflation in Turkey with factor models," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(4), pages 149-161.
  • Mahmut Gunay, 2018. "Forecasting Industrial Production and Inflation in Turkey with Factor Models," Working Papers 1805, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Mahmut Gunay, 2018. "Forecasting industrial production and inflation in Turkey with factor models," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(4), pages 149-161.
  • Mahmut Gunay, 2018. "Forecasting Industrial Production and Inflation in Turkey with Factor Models," Working Papers 1805, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Nikolaos Arnis, 2018. "Predicting Corporate Bankruptcy: A Cross-Sectoral Empirical Study - The Case of Greece," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Eastern Macedonia and Thrace Institute of Technology (EMATTECH), Kavala, Greece, vol. 11(3), pages 31-56, December.
• P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
• Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.
• Mengheng Li & Siem Jan (S.J.) Koopman, 2018. "Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction," Tinbergen Institute Discussion Papers 18-027/III, Tinbergen Institute.
• Florian Peters & Simas Kucinskas, 2018. "Measuring Biases in Expectation Formation," Tinbergen Institute Discussion Papers 18-058/IV, Tinbergen Institute.
• Prüfer, Jens & Prüfer, Patricia, 2018. "Data Science for Institutional and Organizational Economics," Discussion Paper 2018-011, Tilburg University, Tilburg Law and Economic Center.
  • Prüfer, Jens & Prüfer, Patricia, 2018. "Data Science for Institutional and Organizational Economics," Discussion Paper 2018-016, Tilburg University, Center for Economic Research.
• Prüfer, Jens & Prüfer, Patricia, 2018. "Data Science for Institutional and Organizational Economics," Discussion Paper 2018-016, Tilburg University, Center for Economic Research.
  • Prüfer, Jens & Prüfer, Patricia, 2018. "Data Science for Institutional and Organizational Economics," Discussion Paper 2018-011, Tilburg University, Tilburg Law and Economic Center.
• Heikki Kauppi & Timo Virtanen, 2018. "Boosting Non-linear Predictabilityof Macroeconomic Time SeriesComplexity and benefit take-up: Empirical evidence from the Finnish homecare allowance," Discussion Papers 124, Aboa Centre for Economics.
• Giacomo Caterini, 2018. "Classifying Firms with Text Mining," DEM Working Papers 2018/09, Department of Economics and Management.
• Carlo Fezzi & Luca Mosetti, 2018. "Size matters: Estimation sample length and electricity price forecasting accuracy," DEM Working Papers 2018/10, Department of Economics and Management.
• Carolina Fugazza, 2018. "Anatomy of Unemployment Risk," Working papers 048, Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
• Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2018. "Prediction Regions for Interval-valued Time Series," Working Papers 201817, University of California at Riverside, Department of Economics.
  • Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2019. "Prediction Regions for Interval-valued Time Series," Working Papers 201921, University of California at Riverside, Department of Economics.
  • Ruiz Ortega, Esther & Luo, Yun & González-Rivera, Gloria, 2019. "Prediction regions for interval-valued time series," DES - Working Papers. Statistics and Econometrics. WS 29054, Universidad Carlos III de Madrid. Departamento de Estadística.
• Tae-Hwy Lee & Jianghao Chu & Aman Ullah, 2018. "Variable Selection in Sparse Semiparametric Single Index Models," Working Papers 201908, University of California at Riverside, Department of Economics.
• Tae-Hwy Lee & Yundong Tu, 2018. "Forecasting Using Supervised Factor Models," Working Papers 201909, University of California at Riverside, Department of Economics.
• Alula Nerea, 2018. "The Impact of Illicit Financial Flow on Economic Growth of Ethiopia," Working Papers 2018107, University of Ferrara, Department of Economics.
• Francis Bismans, 2018. "Is the South African economy likely to fall back into recession in 2018-2019?," Working Papers of BETA 2018-33, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
• J. Isaac Miller & Kyungsik Nam, 2019. "Dating Hiatuses: A Statistical Model of the Recent Slowdown in Global Warming – and the Next One," Working Papers 1903, Department of Economics, University of Missouri.
• Inoue, Atsushi & Rossi, Barbara, 2019. "The effects of conventional and unconventional monetary policy on exchange rates," Journal of International Economics, Elsevier, vol. 118(C), pages 419-447.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Chapters, in: NBER International Seminar on Macroeconomics 2018, pages 419-447, National Bureau of Economic Research, Inc.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Working Papers 25021, National Bureau of Economic Research, Inc.
  • Atsushi Inoue & Barbara Rossi, 2018. "The effects of conventional and unconventional monetary policy on exchange rates," Economics Working Papers 1639, Department of Economics and Business, Universitat Pompeu Fabra.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," Working Papers 1078, Barcelona Graduate School of Economics.
• Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections — IV models," Working Papers 1841, Banco de España;Working Papers Homepage.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections–IV models," Economics Working Papers 1640, Department of Economics and Business, Universitat Pompeu Fabra.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence Intervals for Bias and Size Distortion in IV and Local Projections–IV Models," Working Papers 1077, Barcelona Graduate School of Economics.
• Galina A. Timofeeva & Yana A. Bozhalkina, 2018. "Dependence of a Loan Portfolio Structure on a Cut-Off Level in a Scoring Model," Journal of New Economy, Ural State University of Economics, vol. 19(2), pages 24-35, April.
• Aslanidis, Nektarios & Christiansen, Charlotte & Cipollini, Andrea, 2019. "Predicting bond betas using macro-finance variables," Finance Research Letters, Elsevier, vol. 29(C), pages 193-199.
  • Nektarios Aslanidis & Charlotte Christiansen & Andrea Cipollini, 2017. "Predicting Bond Betas using Macro-Finance Variables," CREATES Research Papers 2017-01, Department of Economics and Business Economics, Aarhus University.
  • Aslanidis, Nektarios, & Christiansen, Charlotte & Cipollini, Andrea & Bons -- Models matemàtics, 2018. "Predicting Bond Betas using Macro-Finance Variables," Working Papers 2072/306546, Universitat Rovira i Virgili, Department of Economics.
• Goller, Daniel & Knaus, Michael C. & Lechner, Michael & Okasa, Gabriel, 2018. "Predicting Match Outcomes in Football by an Ordered Forest Estimator," Economics Working Paper Series 1811, University of St. Gallen, School of Economics and Political Science.
• Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," Working Paper Series 44, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
• Mengheng Li & Marcel Scharth, 2018. "Leverage, asymmetry and heavy tails in the high-dimensional factor stochastic volatility model," Working Paper Series 49, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
• Monica Billio & Roberto Casarin & Sylvia Kaufmann & Matteo Iacopini, 2018. "Bayesian Dynamic Tensor Regression," Working Papers 2018:13, Department of Economics, University of Venice "Ca' Foscari".
• Monica Billio & Roberto Casarin & Matteo Iacopini, 2018. "Bayesian Markov Switching Tensor Regression for Time-varying Networks," Working Papers 2018:14, Department of Economics, University of Venice "Ca' Foscari".
• Matteo Iacopini & Dominique Guégan, 2018. "Nonparametric Forecasting of Multivariate Probability Density Functions," Working Papers 2018:15, Department of Economics, University of Venice "Ca' Foscari".
• Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Domenico Sartore, 2018. "A scoring rule for factor and autoregressive models under misspecification," Working Papers 2018:18, Department of Economics, University of Venice "Ca' Foscari".
• Mariana Kaneva, 2018. "Telecommunications in the Balkans - Retrospective Statistical Analysis," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, vol. 7(2), pages 163-174, November.
• Gulay Emrah, 2018. "Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition," Scientific Annals of Economics and Business, Sciendo, vol. 65(2), pages 159-169, June.
• Ginanneschi Marco & Piu Pietro, 2018. "The Role of e-Commerce in the Success of Low-cost Carriers," Scientific Annals of Economics and Business, Sciendo, vol. 65(4), pages 407-425, December.
• Husáková Martina, 2018. "Use of the Multi-Agent Paradigm in Sustainable Tourism," Czech Journal of Tourism, Sciendo, vol. 7(1), pages 5-24, June.
• Zekić-Sušac Marijana & Scitovski Rudolf & Has Adela, 2018. "Cluster analysis and artificial neural networks in predicting energy efficiency of public buildings as a cost-saving approach," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 4(2), pages 57-66, November.
• Siekelova Anna & Kliestik Tomas & Adamko Peter, 2018. "Predictive Ability of Chosen Bankruptcy Models: A Case Study of Slovak Republic," Economics and Culture, Sciendo, vol. 15(1), pages 105-114, June.
• Zawada Marcin & Szajt Marek, 2018. "Application of Statistical and Econometric Tools in The Analysis of Air Pollution Level on The Example of Czestochowa," Folia Oeconomica Stetinensia, Sciendo, vol. 18(2), pages 144-158, December.
• Kaczmarczyk Paweł, 2018. "Neural Network Application to Support Regression Model in Forecasting Single-Sectional Demand for Telecommunications Services," Folia Oeconomica Stetinensia, Sciendo, vol. 18(2), pages 159-177, December.
• Simionescu Mihaela, 2018. "The Impact of European Economic Integration on Migration in the European Union," HOLISTICA – Journal of Business and Public Administration, Sciendo, vol. 9(1), pages 23-34, May.
• Ene Andreea Bianca, 2018. "Distance Education in Romanian Higher Education," HOLISTICA – Journal of Business and Public Administration, Sciendo, vol. 9(1), pages 65-70, May.
• Devjak Srečko, 2018. "Modeling of Cash Flows from Nonperforming Loans in a Commercial Bank," Naše gospodarstvo/Our economy, Sciendo, vol. 64(4), pages 3-9, December.
• Weigand Roland & Wanger Susanne & Zapf Ines, 2018. "Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany," Journal of Official Statistics, Sciendo, vol. 34(1), pages 265-301, March.
  • Weigand, Roland & Wanger, Susanne & Zapf, Ines, 2015. "Factor structural time series models for official statistics with an application to hours worked in Germany," IAB Discussion Paper 201522, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
• Simionescu Mihaela, 2018. "What Drives Economic Growth in Some CEE Countries?," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 28(1), pages 46-56, March.
• Florea Nicoleta Valentina & Tănăsescu Dorina Antoneta & Duică Anişoara, 2018. "Enabling Customer-Centricity and Relationship Management using Net Promoter Score," Valahian Journal of Economic Studies, Sciendo, vol. 9(2), pages 115-126, November.
• Shehu U.R. Aliyu & Nafiu B. Abdulsalam & Sani Bawa, 2018. "Testing For Financial Spillovers In Calm And Turbulent Periods," West African Journal of Monetary and Economic Integration, West African Monetary Institute, vol. 18(2), pages 1-27, December.
• Martin Feldkircher & Florian Huber & Gregor Kastner, 2017. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Papers 1711.00564, arXiv.org, revised Nov 2017.
  • Martin Feldkircher & Florian Huber & Gregor Kastner, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Papers wuwp260, Vienna University of Economics and Business, Department of Economics.
  • Feldkircher, Martin & Huber, Florian & Kastner, Gregor, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Paper Series 260, WU Vienna University of Economics and Business.
• Martin Feldkircher & Florian Huber & Gregor Kastner, 2017. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Papers 1711.00564, arXiv.org, revised Nov 2017.
  • Feldkircher, Martin & Huber, Florian & Kastner, Gregor, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Paper Series 260, WU Vienna University of Economics and Business.
  • Martin Feldkircher & Florian Huber & Gregor Kastner, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Papers wuwp260, Vienna University of Economics and Business, Department of Economics.
• Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2018. "On The Sources Of Uncertainty In Exchange Rate Predictability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(1), pages 329-357, February.
  • Byrne, Joseph P & Korobilis, Dimitris & Ribeiro, Pinho J, 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," MPRA Paper 58956, University Library of Munich, Germany.
  • Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," Working Papers 2014_16, Business School - Economics, University of Glasgow.
  • Byrne, Joseph P. & Korobilis, Dimitris & Ribeiro, Pinho J., 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," SIRE Discussion Papers 2015-24, Scottish Institute for Research in Economics (SIRE).
• John M. Maheu & Yong Song, 2018. "An efficient Bayesian approach to multiple structural change in multivariate time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(2), pages 251-270, March.
  • Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
• Carlos Díaz, 2018. "Extracting information shocks from the Bank of England inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(3), pages 316-326, April.
  • Carlos Diaz Vela, 2016. "Extracting the Information Shocks from the Bank of England Inflation Density Forecasts," Discussion Papers in Economics 16/13, Division of Economics, School of Business, University of Leicester.
• Ricardo Crisóstomo & Lorena Couso, 2018. "Financial density forecasts: A comprehensive comparison of risk‐neutral and historical schemes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 589-603, August.
  • Ricardo Crisóstomo & Lorena Couso, 2017. "Financial density forecasts: A comprehensive comparison of risk-neutral and historical schemes," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
  • Ricardo Crisostomo & Lorena Couso, 2018. "Financial density forecasts: A comprehensive comparison of risk-neutral and historical schemes," Papers 1801.08007, arXiv.org, revised May 2018.
• Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018. "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 705-719, November.
  • Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2017. "The Role of Economic Uncertainty in Forecasting Exchange Rate Returns and Realized Volatility: Evidence from Quantile Predictive Regressions," Working Papers 201774, University of Pretoria, Department of Economics.
• Marek Jarociński & Michele Lenza, 2018. "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
  • Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
• Thomas F. Coleman & Alex LaPlante & Alexey Rubtsov, 2018. "Analysis of the SRISK measure and its application to the Canadian banking and insurance industries," Annals of Finance, Springer, vol. 14(4), pages 547-570, November.
• Susanne Maidorn, 2018. "Is there a trade-off between procyclicality and revisions in EC trend TFP estimations?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(1), pages 59-82, February.
• Jurij Weinblat, 2018. "Forecasting European high-growth Firms - A Random Forest Approach," Journal of Industry, Competition and Trade, Springer, vol. 18(3), pages 253-294, September.
• Felix Brinkmann & Olaf Korn, 2018. "Risk-adjusted option-implied moments," Review of Derivatives Research, Springer, vol. 21(2), pages 149-173, July.
• Yu-Sheng Lai, 2018. "Dynamic hedging with futures: a copula-based GARCH model with high-frequency data," Review of Derivatives Research, Springer, vol. 21(3), pages 307-329, October.
• Iris Bergmann & Wolfgang Schultze, 2018. "Accounting based valuation: a simultaneous equations model for forecasting earnings to proxy for ‘other information’," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 1057-1091, May.
• Peter Grundke & Kamil Pliszka, 2018. "A macroeconomic reverse stress test," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 1093-1130, May.
  • Grundke, Peter & Pliszka, Kamil, 2015. "A macroeconomic reverse stress test," Discussion Papers 30/2015, Deutsche Bundesbank.
• Heiner Mikosch & Laura Solanko, 2018. "Should one follow movements in the oil price or in money supply? Forecasting quarterly GDP growth in Russia with higher†frequency indicators," KOF Working papers 18-438, KOF Swiss Economic Institute, ETH Zurich.
• Boros, Péter, 2018. "A hitelértékelési kiigazítás tőketartalékolásának új szabályozása
  [New regulation of the Credit Valuation Adjustment for capital reserves]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 161-184.
• Evžen KoÄ enda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Eastern European Economics, Taylor & Francis Journals, vol. 58(3), pages 197-220, May.
  • Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
  • Evzen Kocenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Working Papers IES 2020/5, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2020.
• WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," CORE Discussion Papers 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Jonas Striaukas & Martin Schumacher & Harald Binder & Matthias Weber, 2020. "Network-Constrained Covariate Coefficient and Connection Sign Estimation," Working Papers on Finance 2001, University of St. Gallen, School of Finance.
  • Matthias Weber & Jonas Striaukas & Martin Schumacher & Harald Binder, 2018. "Network constrained covariate coefficient and connection sign estimation," Bank of Lithuania Discussion Paper Series 8, Bank of Lithuania.
• Julius Stakenas, 2018. "Slicing up inflation: analysis and forecasting of Lithuanian inflation components," Bank of Lithuania Working Paper Series 56, Bank of Lithuania.
• Urbschat, Florian, 2018. "The Good, the Bad, and the Ugly: Impact of Negative Interest Rates and QE on the Profitability and Risk-Taking of 1600 German Banks," Discussion Papers in Economics 56535, University of Munich, Department of Economics.
• Rostan, Pierre & Rostan, Alexandra, 2018. "Forecasting Spanish GDPs with Spectral Analysis /Previsiones del PIB español con análisis espectral," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 217-234, Enero.
• Danica Unevska-Andonova, 2018. "Inflation Decomposition Model: Application to Macedonian inflation," Working Papers 2018-06, National Bank of the Republic of North Macedonia.
• Evžen KoÄ enda & Karen Poghosyan, 2018. "Export Sophistication: A Dynamic Panel Data Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(12), pages 2799-2814, September.
  • Karen Poghosyan & Evžen Kočenda, 2016. "Determinants of export sophistication: Evidence from Monte Carlo simulations," Working Papers 360, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).
  • Evzen Kocenda & Karen Poghosyan, 2017. "Export sophistication: A dynamic panel data approach," KIER Working Papers 980 Classification-C52; C, Kyoto University, Institute of Economic Research.
  • Evzen Kocenda & Karen Poghosyan, 2017. "Export sophistication: A dynamic panel data approach," Working Papers 1, Central Bank of the Republic of Armenia.
• Hatice Gökçe Karasoy Can & ÇaÄŸlar Yüncüler, 2018. "The Explanatory Power and the Forecast Performance of Consumer Confidence Indices for Private Consumption Growth in Turkey," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(9), pages 2136-2152, July.
  • Hatice Gokce Karasoy & Caglar Yunculer, 2015. "The Explanatory Power and the Forecast Performance of Consumer Confidence Indices for Private Consumption Growth in Turkey," Working Papers 1519, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Renáta Géczi-Papp, 2018. "Presentation and Testing of the Creeping Trend with Harmonic Weights Method in the Light of Sovereign CDS Prices," Theory Methodology Practice (TMP), Faculty of Economics, University of Miskolc, vol. 14(02), pages 25-37.
• Ian Borg & Germano Ruisi, 2018. "Forecasting using Bayesian VARs: A Benchmark for STREAM," CBM Working Papers WP/04/2018, Central Bank of Malta.
• György Inzelt & Zsuzsa Szentes-Markhot & Gábor Budai, 2018. "Monitoring of Banks’ Risks Related to the Funding of Financial Enterprises," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 17(4), pages 112-139.
• Francesco Caloia & Andrea Cipollini & Silvia Muzzioli, 2018. "On the financial connectedness of the commodity market: a replication of the Diebold and Yilmaz (2012) study," Department of Economics 0131, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
• Di Bonaventura, Luca & Forni, Mario & Pattarin, Francesco, 2018. "The Forcasting Performance of Dynamic Factor Models with Vintage Data," CEPR Discussion Papers 13034, C.E.P.R. Discussion Papers.
  • Luca Di Bonaventura & Mario Forni & Francesco Pattarin, 2018. "The Forecasting Performance of Dynamic Factor Models with Vintage Data," Center for Economic Research (RECent) 138, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
  • Luca Di Bonaventura & Mario Forni & Francesco Pattarin, 2018. "The Forecasting Performance of Dynamic Factor Models with Vintage Data," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0070, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
• Di Bonaventura, Luca & Forni, Mario & Pattarin, Francesco, 2018. "The Forcasting Performance of Dynamic Factor Models with Vintage Data," CEPR Discussion Papers 13034, C.E.P.R. Discussion Papers.
  • Luca Di Bonaventura & Mario Forni & Francesco Pattarin, 2018. "The Forecasting Performance of Dynamic Factor Models with Vintage Data," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0070, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
  • Luca Di Bonaventura & Mario Forni & Francesco Pattarin, 2018. "The Forecasting Performance of Dynamic Factor Models with Vintage Data," Center for Economic Research (RECent) 138, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
• Seika Akemura & Daizo Kojima, 2018. "Japan’s Long-Term Care Cost Projections: Comparison with the European Commission Ageing Report," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 14(4), pages 541-562, July.
• Dominique Guégan & Matteo Iacopini, 2018. "Nonparameteric forecasting of multivariate probability density functions," Documents de travail du Centre d'Economie de la Sorbonne 18012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Jørgen Vitting Andersen & Philippe de Peretti, 2018. "New method to detect convergence in simple multi-period market games with infinite large strategy spaces," Documents de travail du Centre d'Economie de la Sorbonne 18038, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Frazier, David T. & Maneesoonthorn, Worapree & Martin, Gael M. & McCabe, Brendan P.M., 2019. "Approximate Bayesian forecasting," International Journal of Forecasting, Elsevier, vol. 35(2), pages 521-539.
  • David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Brendan P.M. McCabe, 2018. "Approximate Bayesian forecasting," Monash Econometrics and Business Statistics Working Papers 2/18, Monash University, Department of Econometrics and Business Statistics.
• Sílvia GONÇALVES & Benoit PERRON, 2018. "Bootstrapping Factor Models With Cross Sectional Dependence," Cahiers de recherche 10-2018, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
• Eric Ghysels & Leonardo Iania & Jonas Striaukas, 2018. "Quantile-based Inflation Risk Models," Working Paper Research 349, National Bank of Belgium.
• Inoue, Atsushi & Rossi, Barbara, 2019. "The effects of conventional and unconventional monetary policy on exchange rates," Journal of International Economics, Elsevier, vol. 118(C), pages 419-447.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Chapters, in: NBER International Seminar on Macroeconomics 2018, pages 419-447, National Bureau of Economic Research, Inc.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Working Papers 25021, National Bureau of Economic Research, Inc.
  • Atsushi Inoue & Barbara Rossi, 2018. "The effects of conventional and unconventional monetary policy on exchange rates," Economics Working Papers 1639, Department of Economics and Business, Universitat Pompeu Fabra.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," Working Papers 1078, Barcelona Graduate School of Economics.
• Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2019. "The Impact of Big Data on Firm Performance: An Empirical Investigation," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 33-37, May.
  • Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2018. "The Impact of Big Data on Firm Performance: An Empirical Investigation," NBER Working Papers 24334, National Bureau of Economic Research, Inc.
• Steven F. Lehrer & Tian Xie, 2018. "The Bigger Picture: Combining Econometrics with Analytics Improve Forecasts of Movie Success," NBER Working Papers 24755, National Bureau of Economic Research, Inc.
• Ş. Pelin Akyol & Kala Krishna & Jinwen Wang, 2018. "Taking PISA Seriously: How Accurate are Low Stakes Exams?," NBER Working Papers 24930, National Bureau of Economic Research, Inc.
• Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially Egalitarian Lasso and its Derivatives," PIER Working Paper Archive 18-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 17 Aug 2018.
  • Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and its Derivatives," NBER Working Papers 24967, National Bureau of Economic Research, Inc.
• Inoue, Atsushi & Rossi, Barbara, 2019. "The effects of conventional and unconventional monetary policy on exchange rates," Journal of International Economics, Elsevier, vol. 118(C), pages 419-447.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Chapters, in: NBER International Seminar on Macroeconomics 2018, pages 419-447, National Bureau of Economic Research, Inc.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," Working Papers 1078, Barcelona Graduate School of Economics.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Working Papers 25021, National Bureau of Economic Research, Inc.
  • Atsushi Inoue & Barbara Rossi, 2018. "The effects of conventional and unconventional monetary policy on exchange rates," Economics Working Papers 1639, Department of Economics and Business, Universitat Pompeu Fabra.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Forecasting With Dynamic Panel Data Models," Econometrica, Econometric Society, vol. 88(1), pages 171-201, January.
  • Laura Liu & Hyungsik Moon & Frank Schorfheide, 2016. "Forecasting with Dynamic Panel Data Models," PIER Working Paper Archive 16-022, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 21 Dec 2016.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2018. "Forecasting with Dynamic Panel Data Models," NBER Working Papers 25102, National Bureau of Economic Research, Inc.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2017. "Forecasting with Dynamic Panel Data Models," Papers 1709.10193, arXiv.org.
• Nadia Boussaha & Faycal Hamdi & Saïd Souam, 2018. "Multivariate Periodic Stochastic Volatility Models: Applications to Algerian dinar exchange rates and oil prices modeling," EconomiX Working Papers 2018-14, University of Paris Nanterre, EconomiX.
• Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
  • S. Delle Chiaie & L. Ferrara & D. Giannone, 2017. "Common Factors of Commodity Prices," Working papers 645, Banque de France.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common Factors of Commodity Prices," CEPR Discussion Papers 12767, C.E.P.R. Discussion Papers.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2017. "Common factors of commodity prices," Working Paper Series 2112, European Central Bank.
• Nymand-Andersen, Per & Pantelidis, Emmanouil, 2018. "Google econometrics: nowcasting euro area car sales and big data quality requirements," Statistics Paper Series 30, European Central Bank.
• Gräb, Johannes & Kostka, Thomas, 2018. "Predicting risk premia in short-term interest rates and exchange rates," Working Paper Series 2131, European Central Bank.
• McAdam, Peter & Warne, Anders, 2019. "Euro area real-time density forecasting with financial or labor market frictions," International Journal of Forecasting, Elsevier, vol. 35(2), pages 580-600.
  • McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
• Ferdinand Dreher & Johannes Gräb & Thomas Kostka, 2020. "From carry trades to curvy trades," The World Economy, Wiley Blackwell, vol. 43(3), pages 758-780, March.
  • Dreher, Ferdinand & Gräb, Johannes & Kostka, Thomas, 2018. "From carry trades to curvy trades," Working Paper Series 2149, European Central Bank.
• Hahn, Elke & Zekaite, Zivile & de Bondt, Gabe, 2018. "ALICE: A new inflation monitoring tool," Working Paper Series 2175, European Central Bank.
• Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018. "Mixed frequency models with MA components," Discussion Papers 02/2018, Deutsche Bundesbank.
  • Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018. "Mixed frequency models with MA components," Working Paper Series 2206, European Central Bank.
• Nikolaos Dritsakis & Paraskevi Klazoglou, 2018. "Forecasting Unemployment Rates in USA using Box-Jenkins Methodology," International Journal of Economics and Financial Issues, Econjournals, vol. 8(1), pages 9-20.
• Onder Buberkoku, 2018. "Examining the Value-at-risk Performance of Fractionally Integrated GARCH Models: Evidence from Energy Commodities," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 36-50.
• Zouheir Ahmed Mighri & Majid Ibrahim Al Saggaf, 2018. "Gold - Silver Nexus: A Threshold Cointegration Approach," International Journal of Economics and Financial Issues, Econjournals, vol. 8(5), pages 210-219.
• Jorge Barrientos Marin & Elkin Tabares Orozco & Esteban Velilla, 2018. "Forecasting electricity price in Colombia: A comparison between Neural Network, ARMA process and Hybrid Models," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 97-106.
• Jean Gaston Tamba & Salomé Ndjakomo Essiane & Emmanuel Flavian Sapnken & Francis Djanna Koffi & Jean Luc Nsouandélé & Bozidar Soldo & Donatien Njomo, 2018. "Forecasting Natural Gas: A Literature Survey," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 216-249.
• Sallahuddin Hassan, 2018. "Dynamic Impact of Energy Consumption, Private Investment and Financial Development on Environmental Pollutions: Evidence from Malaysia," International Journal of Energy Economics and Policy, Econjournals, vol. 8(4), pages 63-69.
• Kunlapath Sukcharoen & David Leatham, 2018. "Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method," International Journal of Energy Economics and Policy, Econjournals, vol. 8(5), pages 193-201.
• Blagrave, Patrick & Vesperoni, Esteban, 2018. "The implications of China’s slowdown for international trade," Journal of Asian Economics, Elsevier, vol. 56(C), pages 36-47.
• Kabukçuoğlu, Ayşe & Martínez-García, Enrique, 2018. "Inflation as a global phenomenon—Some implications for inflation modeling and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 46-73.
  • Ayse Kabukcuoglu & Enrique Martínez-García, 2015. "Inflation as a Global Phenomenon—Some Implications for Policy Analysis and Forecasting," Koç University-TUSIAD Economic Research Forum Working Papers 1520, Koc University-TUSIAD Economic Research Forum.
  • Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "Inflation as a global phenomenon - some implications for policy analysis and forecasting," Globalization Institute Working Papers 261, Federal Reserve Bank of Dallas, revised 01 Jan 2016.
• Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2018. "Model Complexity and Out-of-Sample Performance: Evidence from S&P 500 Index Returns," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 1-29.
• Berger, Theo & Gençay, Ramazan, 2018. "Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 30-46.
• Dellas, Harris & Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2018. "The macroeconomic and fiscal implications of inflation forecast errors," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 203-217.
• Nalban, Valeriu, 2018. "Forecasting with DSGE models: What frictions are important?," Economic Modelling, Elsevier, vol. 68(C), pages 190-204.
• Salisu, Afees A. & Isah, Kazeem O., 2018. "Predicting US inflation: Evidence from a new approach," Economic Modelling, Elsevier, vol. 71(C), pages 134-158.
  • Afees A. Salisu & Kazeem Isah, 2017. "Predicting US Inflation: Evidence from a New Approach," Working Papers 039, Centre for Econometric and Allied Research, University of Ibadan.
  • Afees A. Salisu & Kazeem Isah, 2017. "Predicting US CPI-Inflation in the presence of asymmetries, persistence, endogeneity, and conditional heteroscedasticity," Working Papers 026, Centre for Econometric and Allied Research, University of Ibadan.
• Burney, Nadeem A. & Mohaddes, Kamiar & Alawadhi, Ahmad & Al-Musallam, Marwa, 2018. "The dynamics and determinants of Kuwait's long-run economic growth," Economic Modelling, Elsevier, vol. 71(C), pages 289-304.
• Behrens, Christoph & Pierdzioch, Christian & Risse, Marian, 2018. "Testing the optimality of inflation forecasts under flexible loss with random forests," Economic Modelling, Elsevier, vol. 72(C), pages 270-277.
• Ma, Feng & Liu, Jing & Wahab, M.I.M. & Zhang, Yaojie, 2018. "Forecasting the aggregate oil price volatility in a data-rich environment," Economic Modelling, Elsevier, vol. 72(C), pages 320-332.
• Chaudhuri, Kausik & Sen, Rituparna & Tan, Zheng, 2018. "Testing extreme dependence in financial time series," Economic Modelling, Elsevier, vol. 73(C), pages 378-394.
• Salisu, Afees A. & Ndako, Umar B., 2018. "Modelling stock price–exchange rate nexus in OECD countries: A new perspective," Economic Modelling, Elsevier, vol. 74(C), pages 105-123.
  • Afees A. Salisu & Umar B. Ndako, 2017. "Modelling stock price-exchange rate nexus in OECD countries - A new perspective," Working Papers 038, Centre for Econometric and Allied Research, University of Ibadan.
• Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2018. "Forecasting the prices of crude oil using the predictor, economic and combined constraints," Economic Modelling, Elsevier, vol. 75(C), pages 237-245.
• Jian, Zhihong & Deng, Pingjun & Zhu, Zhican, 2018. "High-dimensional covariance forecasting based on principal component analysis of high-frequency data," Economic Modelling, Elsevier, vol. 75(C), pages 422-431.
• Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
• Ong, Sheue Li & Sato, Kiyotaka, 2018. "Regional or global shock? A global VAR analysis of Asian economic and financial integration," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 232-248.
• Papanikolaou, Nikolaos I., 2018. "A dual early warning model of bank distress," Economics Letters, Elsevier, vol. 162(C), pages 127-130.
  • Nikolaos I. Papanikolaou, 2017. "A Dual Early Warning Model of Bank Distress," BAFES Working Papers BAFES11, Department of Accounting, Finance & Economic, Bournemouth University.
• Feng, Pan & Qian, Junhui, 2018. "Forecasting the yield curve using a dynamic natural cubic spline model," Economics Letters, Elsevier, vol. 168(C), pages 73-76.
• González-Fernández, Marcos & González-Velasco, Carmen, 2018. "Can Google econometrics predict unemployment? Evidence from Spain," Economics Letters, Elsevier, vol. 170(C), pages 42-45.
• Pedro Gajardo & Luc Doyen, 2018. "Viability standards and multi-criteria maximin," Cahiers du GREThA (2007-2019) 2018-04, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
• Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2018. "Choice of Benchmark When Forecasting Long-term Stock Returns," Graz Economics Papers 2018-08, University of Graz, Department of Economics.
• Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo Group Munich.
  • Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," Graz Economics Papers 2018-09, University of Graz, Department of Economics.
• Gabriel Mathy & Christian Roatta, 2018. "Forecasting the 1937-1938 Recession: Quantifying Contemporary Newspaper Forecasts," Working Papers 2018-004, The George Washington University, Department of Economics, Research Program on Forecasting.
• Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018. "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers 2018-005, The George Washington University, Department of Economics, Research Program on Forecasting, revised May 2019.
• Carl Singleton & J. James Reade & Alsdair Brown, 2018. "Going with your Gut: The (In)accuracy of Forecast Revisions in a Football Score Prediction Game," Working Papers 2018-006, The George Washington University, Department of Economics, Research Program on Forecasting.
  • Carl Singleton & J. James Reade & Alasdair Brown, 2019. "Going with your gut: the (in)accuracy of forecast revisions in a football score prediction game," Economics & Management Discussion Papers em-dp2019-05, Henley Business School, Reading University.
• Stephen Bazen & Jean-Marie Cardebat, 2018. "Forecasting Bordeaux wine prices using state-space methods," Post-Print hal-01867216, HAL.
• Darolles, Serge & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Journal of Econometrics, Elsevier, vol. 204(2), pages 223-247.
  • Darolles, Serges & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," MPRA Paper 83988, University Library of Munich, Germany.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-01980815, HAL.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," AMSE Working Papers 1845, Aix-Marseille School of Economics, France.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," Working Papers halshs-01944656, HAL.
• Darolles, Serge & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Journal of Econometrics, Elsevier, vol. 204(2), pages 223-247.
  • Darolles, Serges & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," MPRA Paper 83988, University Library of Munich, Germany.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," Working Papers halshs-01944656, HAL.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," AMSE Working Papers 1845, Aix-Marseille School of Economics, France.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-01980815, HAL.
• Vanella, Patrizio & Deschermeier, Philipp, 2018. "A Principal Component Simulation of Age-Specific Fertility - Impacts of Family and Social Policy on Reproductive Behavior in Germany," Hannover Economic Papers (HEP) dp-630, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
• Vanella, Patrizio & Deschermeier, Philipp, 2018. "A Probabilistic Cohort-Component Model for Population Forecasting - The Case of Germany," Hannover Economic Papers (HEP) dp-638, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
• Steffen Q. Mueller, 2018. "Pre- and within-season attendance forecasting in Major League Baseball: A random forest approach," Working Papers 065, Chair for Economic Policy, University of Hamburg.
• Mirjana Čižmešija & Zrinka Orlović, 2018. "Consumer Confidence Indicator As A Leading Indicator Of Changes In Retail Trade Turnover," Ekonomski pregled, Hrvatsko društvo ekonomista (Croatian Society of Economists), vol. 69(1), pages 3-19.
• Lindholm, Unn & Mossfeldt, Marcus & Stockhammar, Pär, 2018. "Forecasting Inflation in Sweden," Working Papers 152, National Institute of Economic Research.
• George Borshchevskiy, 2018. "Improvement of Evaluation Approaches of the Russian Public Programs," HSE Economic Journal, National Research University Higher School of Economics, vol. 22(1), pages 110-134.
• Igor Gurkov & Evgeniy Morgunov & Zokirzhon Saidov & Alexander Arshavsky, 2018. "Perspectives of Manufacturing Subsidiaries of Foreign Companies in Russia: Frontier, Faubourg or Sticks?," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 12(2), pages 24-35.
• Ricardo Seidl da Fonseca & Alex Pinheiro Veloso, 2018. "The Practice and Future of Financing Science, Technology, and Innovation," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 12(2), pages 6-22.
• Timofei Nestik, 2018. "The Psychological Aspects of Corporate Foresight," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 12(2), pages 78-90.
• Evgeniy M. Ozhegov & Alina Ozhegova, 2018. "Segmentation of Theatre Audiences: A Latent Class Approach for Combined Data," HSE Working papers WP BRP 198/EC/2018, National Research University Higher School of Economics.
• Evgeniy M. Ozhegov & Daria Teterina, 2018. "The Ensemble Method For Censored Demand Prediction," HSE Working papers WP BRP 200/EC/2018, National Research University Higher School of Economics.
• Li, Jinjing & Wang, Xinmei & Yuan, Chang & Xu, Jing, 2018. "The Role of Public Pensions in Income Inequality among Elderly Households in China 1988–2013," CIS Discussion paper series 674, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
• Xu, Jing & Wang, Xinmei, 2018. "Working Longer in China: Implicit Tax or Subsidy?," CIS Discussion paper series 675, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
• Gómez Aguirre, Maximiliano & Garegnani, Lorena, 2020. "Forecasting Inflation in Argentina," IDB Publications (Working Papers) 8940, Inter-American Development Bank.
• Libonatti, Luis, 2020. "MIDAS Modeling for Core Inflation Forecasting," IDB Publications (Working Papers) 9035, Inter-American Development Bank.
• Hurtarte-Aguilar, Guisela & Valle-Samayoa, Héctor Augusto & Ortiz-Cardona, Edson Roger & Catalán-Herrera, Juan Carlos & Arriaza-Herrera, Juan Carlos & Gutiérrez-Morales, José & Castillo-Maldonado, Car, 2020. "Evaluation of Inflation Forecasting Models in Guatemala," IDB Publications (Working Papers) 9054, Inter-American Development Bank.
• Saiful Anwar & A.M Hasan Ali, 2018. "ANNs-BASED EARLY WARNING SYSTEM FOR INDONESIAN ISLAMIC BANKS," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 20(3), pages 1-18, January.
• Tarsidin & Idham & Robbi Nur Rakhman, 2018. "Nowcasting Household Consumption And Investment In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 20(3), pages 1-30, January.
• Profita Sumunar Luthfiana & Nasrudin, 2018. "Disaggregation And Forecasting Of The Monthly Indonesian Gross Domestic Product (Gdp)," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 20(4), pages 1-28, April.
• Luigi Grossi & Fany Nan, 2018. "The influence of renewables on electricity price forecasting: a robust approach," Working Papers 2018/10, Institut d'Economia de Barcelona (IEB).
• Costantini, Mauro & Kunst, Robert M., 2018. "On Using Predictive-ability Tests in the Selection of Time-series Prediction Models: A Monte Carlo Evaluation," Economics Series 341, Institute for Advanced Studies.
• Michael Dotsey & Shigeru Fujita & Tom Stark, 2018. "Do Phillips Curves Conditionally Help to Forecast Inflation?," International Journal of Central Banking, International Journal of Central Banking, vol. 14(4), pages 43-92, September.
• Cathal O'Donoghue & Gijs Dekkers, 2018. "Increasing the Impact of Dynamic Microsimulation Modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 61-96.
• Abbygail Jaccard & Lise Retat & Martin Brown & Laura Webber & Zaid Chalabi, 2018. "Global Sensitivity Analysis of a Model Simulating an Individual’s Health State through Their Lifetime," International Journal of Microsimulation, International Microsimulation Association, vol. 11(3), pages 100-121.
• Abbygail Jaccard & Lise Retat & Martin Brown & Laura Webber & Zaid Chalabi, 2018. "Global Sensitivity Analysis of a Model Simulating an Individual’s Health State through Their Lifetime APPENDIX," International Journal of Microsimulation, International Microsimulation Association, vol. 11(3), pages 122-133.
• Rupendra N Shrestha & Deborah Schofield & Melanie J B Zeppel & Michelle M Cunich & Robert Tanton & Simon J Kelly & Lennert Veerman & Megan E Passey, 2018. "Care&WorkMOD: An Australian Microsimulation Model Projecting the Economic Impacts of Early Retirement in Informal Carers," International Journal of Microsimulation, International Microsimulation Association, vol. 11(3), pages 78-99.
• Luis Manuel León Anaya & Víctor Manuel Landassuri Moreno & Héctor Rafael Orozco Aguirre & Maricela Quintana López, 2018. "Predicción del IPC mexicano combinando modelos econométricos e inteligencia artificial," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 13(4), pages 603-629, Octubre-D.
• Achim Zeileis & Christoph Leitner & Kurt Hornik, 2018. "Probabilistic forecasts for the 2018 FIFA World Cup based on the bookmaker consensus model," Working Papers 2018-09, Faculty of Economics and Statistics, University of Innsbruck.
• Thorsten Simon & Georg J. Mayr & Nikolaus Umlauf & Achim Zeileis, 2018. "Lightning Prediction Using Model Output Statistics," Working Papers 2018-14, Faculty of Economics and Statistics, University of Innsbruck.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A regional perspective on the accuracy of machine learning forecasts of tourism demand based on data characteristics”," AQR Working Papers 201802, University of Barcelona, Regional Quantitative Analysis Group, revised Apr 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A regional perspective on the accuracy of machine learning forecasts of tourism demand based on data characteristics”," IREA Working Papers 201805, University of Barcelona, Research Institute of Applied Economics, revised Mar 2018.
• Oscar Claveria, 2018. "“A new metric of consensus for Likert scales”," AQR Working Papers 201810, University of Barcelona, Regional Quantitative Analysis Group, revised Oct 2018.
  • Oscar Claveria, 2018. "“A new metric of consensus for Likert scales”," IREA Working Papers 201821, University of Barcelona, Research Institute of Applied Economics, revised Oct 2018.
• Antonio Cappiello, 2018. "Mediation: economic concepts and some examples of rational framework for legal professionals," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - Italian Review of Economics, Demography and Statistics, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 72(2), pages 149-158, April-Jun.
• Stefania Pozzuoli, 2018. "L'evoluzione del credito alle società non finanziarie e alle famiglie: un'analisi empririca per l'Italia," Working Papers 2, Department of the Treasury, Ministry of the Economy and of Finance.
• Dr. Brijesh Kumar Agarwal & Anamica Bansal, 2018. "An Analytical Study of Marketing Mix of Selected Brands of Vegetable Oil in Northern India," Journal of Commerce and Trade, Society for Advanced Management Studies, vol. 13(1), pages 118-123, April.
• Maheu, John M. & Song, Yong & Yang, Qiao, 2020. "Oil price shocks and economic growth: The volatility link," International Journal of Forecasting, Elsevier, vol. 36(2), pages 570-587.
  • John M. Maheu & Yong Song & Qiao Yang, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," Working Paper series 18-03, Rimini Centre for Economic Analysis.
  • Maheu, John M & Yang, Qiao & Song, Yong, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83779, University Library of Munich, Germany.
  • Maheu, John M & Song, Yong & Yang, Qiao, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83999, University Library of Munich, Germany.
• Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018. "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper 83893, University Library of Munich, Germany.
• GRITLI, Mohamed Ilyes, 2018. "Quel avenir du dinar tunisien face à l'euro ? Prévision avec le modèle ARIMA
  [What future of the Tunisian dinar against the euro? Prediction with the ARIMA model]," MPRA Paper 83937, University Library of Munich, Germany.
• Ghouse, Ghulam & Khan, Saud Ahmed & Rehman, Atiq Ur, 2018. "ARDL model as a remedy for spurious regression: problems, performance and prospectus," MPRA Paper 83973, University Library of Munich, Germany.
• Maheu, John M. & Song, Yong & Yang, Qiao, 2020. "Oil price shocks and economic growth: The volatility link," International Journal of Forecasting, Elsevier, vol. 36(2), pages 570-587.
  • John M. Maheu & Yong Song & Qiao Yang, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," Working Paper series 18-03, Rimini Centre for Economic Analysis.
  • Maheu, John M & Song, Yong & Yang, Qiao, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83999, University Library of Munich, Germany.
  • Maheu, John M & Yang, Qiao & Song, Yong, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83779, University Library of Munich, Germany.
• Sabaj, Ernil & Kahveci, Mustafa, 2018. "Forecasting tax revenues in an emerging economy: The case of Albania," MPRA Paper 84404, University Library of Munich, Germany.
• Corradini, Riccardo, 2018. "A set of state space models at an high disaggregation level to forecast Italian Industrial Production," MPRA Paper 84558, University Library of Munich, Germany, revised 12 Feb 2018.
• Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2018. "Does a financial accelerator improve forecasts during financial crises?: Evidence from Japan with Prediction Pool Methods," MPRA Paper 85523, University Library of Munich, Germany.
• Lee, David, 2018. "Pricing Financial Derivatives Subject to Counterparty Risk and Credit Value Adjustment," MPRA Paper 85575, University Library of Munich, Germany.
• EMERSON Abraham Jackson, 2018. "Comparison Between Static And Dynamic Forecast In Autoregressive Integrated Moving Average For Seasonally Adjusted Headline Consumer Price Index," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 70(1), pages 53-65, August.
  • Jackson, Emerson Abraham, 2018. "Comparison between Static and Dynamic Forecast in Autoregressive Integrated Moving Average for Seasonally Adjusted Headline Consumer Price Index," MPRA Paper 86180, University Library of Munich, Germany, revised 12 Apr 2018.
• Check, Adam J. & Nolan, Anna K. & Schipper, Tyler C., 2018. "Forecasting GDP: Do Revisions Matter?," MPRA Paper 86194, University Library of Munich, Germany.
• Fingleton, Bernard, 2018. "Exploring Brexit with dynamic spatial panel models : some possible outcomes for employment across the EU regions," MPRA Paper 86553, University Library of Munich, Germany.
• Raputsoane, Leroi, 2018. "Quantifying economic recovery from the recent global financial crisis," MPRA Paper 87410, University Library of Munich, Germany.
• Brkic, Sabina & Hodzic, Migdat & Dzanic, Enis, 2018. "Soft Data Modeling via Type 2 Fuzzy Distributions for Corporate Credit Risk Assessment in Commercial Banking," MPRA Paper 87652, University Library of Munich, Germany.
• Korobilis, Dimitris & Koop, Gary, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," Essex Finance Centre Working Papers 22665, University of Essex, Essex Business School.
  • Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
  • Gary Koop & Dimitris Korobilis, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," Working Paper series 18-31, Rimini Centre for Economic Analysis.
• Spelta, Alessandro & Pecora, Nicolò & Flori, Andrea & Pammolli, Fabio, 2018. "Transition drivers and crisis signaling in stock markets," MPRA Paper 88127, University Library of Munich, Germany.
• Kapur, Muneesh, 2018. "Macroeconomic Policies and Transmission Dynamics in India," MPRA Paper 88566, University Library of Munich, Germany.
• Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
• Nyoni, Thabani, 2018. "Modeling and Forecasting Naira / USD Exchange Rate In Nigeria: a Box - Jenkins ARIMA approach," MPRA Paper 88622, University Library of Munich, Germany, revised 19 Aug 2018.
• Pincheira, Pablo & Hardy, Nicolas, 2018. "The predictive relationship between exchange rate expectations and base metal prices," MPRA Paper 89423, University Library of Munich, Germany.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Asante Gyamerah, Samuel & Ngare, Philip & Ikpe, Dennis, 2018. "A Levy Regime-Switching Temperature Dynamics Model for Weather Derivatives," MPRA Paper 89680, University Library of Munich, Germany, revised 10 Jul 2018.
• bailek, Alexandra, 2018. "Economic Impact Analysis of Hospital Readmission Rate and Service Quality Using Machine Learning," MPRA Paper 89875, University Library of Munich, Germany.
• Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
• Pincheira, Pablo & Neumann, Federico, 2018. "Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile," MPRA Paper 90432, University Library of Munich, Germany.
• Nyoni, Thabani & Nathaniel, Solomon Prince, 2018. "Modeling rates of inflation in Nigeria: an application of ARMA, ARIMA and GARCH models," MPRA Paper 91351, University Library of Munich, Germany.
• Aliyu, Shehu Usman Rano & Aminu, Abubakar Wambai, 2018. "Economic regimes and stock market performance in Nigeria: Evidence from regime switching model," MPRA Paper 91430, University Library of Munich, Germany, revised 03 Oct 2018.
• Spiliotis, Evangelos & Petropoulos, Fotios & Kourentzes, Nikolaos & Assimakopoulos, Vassilios, 2018. "Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption," MPRA Paper 91762, University Library of Munich, Germany.
• Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018. "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper 94289, University Library of Munich, Germany.
• Fries, Sébastien, 2018. "Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds," MPRA Paper 97353, University Library of Munich, Germany, revised Nov 2019.
• Gupta, Rangan & Pierdzioch, Christian & Vivian, Andrew J. & Wohar, Mark E., 2019. "The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests," Finance Research Letters, Elsevier, vol. 29(C), pages 315-322.
  • Rangan Gupta & Christian Pierdzioch & Andrew J. Vivian & Mark E. Wohar, 2018. "The Predictive Value of Inequality Measures for Stock Returns: An Analysis of Long-Span UK Data Using Quantile Random Forests," Working Papers 201809, University of Pretoria, Department of Economics.
• Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2018. "Is There a Role for Uncertainty in Forecasting Output Growth in OECD Countries? Evidence from a Time Varying Parameter-Panel Vector Autoregressive Model," Working Papers 201823, University of Pretoria, Department of Economics.
• Goodness Aye, 2018. "Causality between Economic Policy Uncertainty and Real Housing Returns in Emerging Economies: A Cross-Sample Validation Approach," Working Papers 201827, University of Pretoria, Department of Economics.
• Rangan Gupta, 2018. "Manager Sentiment and Stock Market Volatility," Working Papers 201853, University of Pretoria, Department of Economics.
• Rangan Gupta & Chi Keung Marco Lau & Wendy Nyakabawo, 2018. "Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment," Working Papers 201866, University of Pretoria, Department of Economics.
• Christian Pierdzioch & Rangan Gupta & Hossein Hassani & Emmanuel Silva, 2018. "Forecasting Changes of Economic Inequality: A Boosting Approach," Working Papers 201868, University of Pretoria, Department of Economics.
• Hossein Hassani & Mohammad Reza Yeganegi & Juncal Cunado & Rangan Gupta, 2018. "Forecasting Interest Rate Volatility of the United Kingdom: Evidence from over 150 Years of Data," Working Papers 201873, University of Pretoria, Department of Economics.
• Milan Bašta, 2018. "Time series forecasting with a prior wavelet-based denoising step," Acta Oeconomica Pragensia, University of Economics, Prague, vol. 2018(1), pages 5-24.
• Michal Kováč, 2018. "Approaches to stress testing for regulatory purposes by institutions using the IRBA method
  [Konstrukce stres testu pro regulatorní účely modelem VEC]," Český finanční a účetní časopis, University of Economics, Prague, vol. 2018(2), pages 43-59.
• Michal Kováč, 2018. "Comparison of stress testing models for regulatory purposes by institutions using the IRBA method
  [Porovnání stres test modelů pro regulatorní účely institucí využívajících IRBA metodu]," Český finanční a účetní časopis, University of Economics, Prague, vol. 2018(3), pages 41-56.
• Madalina Ecaterina Popescu & Victor Dragotă, 2018. "What Do Post-Communist Countries Have in Common When Predicting Financial Distress?," Prague Economic Papers, University of Economics, Prague, vol. 2018(6), pages 637-653.
• Matúš Mihalovič, 2018. "Využitie skóringových modelov pri predikcii defaultu ekonomických subjektov v Slovenskej republike
  [Applicability of Scoring Models in Firms' Default Prediction. The Case of Slovakia]," Politická ekonomie, University of Economics, Prague, vol. 2018(6), pages 689-708.
• Alasdair Brown & James Reade & Leighton Vaughan Williams, 2018. "Prediction Markets and Poll Releases: When Are Prices Most Informative?," Economics & Management Discussion Papers em-dp2018-02, Henley Business School, Reading University.
• Anttonen, Jetro, 2018. "Nowcasting the Unemployment Rate in the EU with Seasonal BVAR and Google Search Data," ETLA Working Papers 62, The Research Institute of the Finnish Economy.
• Maheu, John M. & Song, Yong & Yang, Qiao, 2020. "Oil price shocks and economic growth: The volatility link," International Journal of Forecasting, Elsevier, vol. 36(2), pages 570-587.
  • Maheu, John M & Song, Yong & Yang, Qiao, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83999, University Library of Munich, Germany.
  • John M. Maheu & Yong Song & Qiao Yang, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," Working Paper series 18-03, Rimini Centre for Economic Analysis.
  • Maheu, John M & Yang, Qiao & Song, Yong, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83779, University Library of Munich, Germany.
• Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Adaptive hierarchical priors for high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 212(1), pages 241-271.
  • Dimitris Korobilis & Davide Pettenuzzo, 2017. "Adaptive Hierarchical Priors for High-Dimensional Vector Autoregessions," Working Papers 115, Brandeis University, Department of Economics and International Businesss School.
  • Dimitris Korobilis & Davide Pettenuzzo, 2018. "Adaptive Hierarchical Priors for High-Dimensional Vector Autoregressions," Working Paper series 18-21, Rimini Centre for Economic Analysis.
• Korobilis, Dimitris & Koop, Gary, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," Essex Finance Centre Working Papers 22665, University of Essex, Essex Business School.
  • Gary Koop & Dimitris Korobilis, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," Working Paper series 18-31, Rimini Centre for Economic Analysis.
  • Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
• Fortin, Alain-Philippe & Simonato, Jean-Guy & Dionne, Georges, 2018. "Forecasting Expected Shortfall: Should we use a Multivariate Model for Stock Market Factors?," Working Papers 18-4, HEC Montreal, Canada Research Chair in Risk Management, revised 04 Dec 2019.
• Dias, Gustavo Fruet & Kapetanios, George, 2018. "Estimation and forecasting in vector autoregressive moving average models for rich datasets," Journal of Econometrics, Elsevier, vol. 202(1), pages 75-91.
• Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
• Kalli, Maria & Griffin, Jim E., 2018. "Bayesian nonparametric vector autoregressive models," Journal of Econometrics, Elsevier, vol. 203(2), pages 267-282.
• Darolles, Serge & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Journal of Econometrics, Elsevier, vol. 204(2), pages 223-247.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," Working Papers halshs-01944656, HAL.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," AMSE Working Papers 1845, Aix-Marseille School of Economics, France.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-01980815, HAL.
  • Darolles, Serges & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," MPRA Paper 83988, University Library of Munich, Germany.
• Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
  • Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers CWP50/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Marczak, Martyna & Proietti, Tommaso & Grassi, Stefano, 2018. "A data-cleaning augmented Kalman filter for robust estimation of state space models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 107-123.
  • Marczak, Martyna & Proietti, Tommaso & Grassi, Stefano, 2015. "A data-cleaning augmented Kalman filter for robust estimation of state space models," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
  • Martyna Marczak & Tommaso Proietti & Stefano Grassi, 2016. "A Data–Cleaning Augmented Kalman Filter for Robust Estimation of State Space Models," CEIS Research Paper 374, Tor Vergata University, CEIS, revised 31 Mar 2016.
• Breitung, Jörg & Schreiber, Sven, 2018. "Assessing causality and delay within a frequency band," Econometrics and Statistics, Elsevier, vol. 6(C), pages 57-73.
  • Jörg Breitung & Sven Schreiber, 2016. "Assessing Causality and Delay within a Frequency Band," IMK Working Paper 165-2016, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
• Kapetanios, George & Price, Simon & Young, Garry, 2018. "A UK financial conditions index using targeted data reduction: Forecasting and structural identification," Econometrics and Statistics, Elsevier, vol. 7(C), pages 1-17.
  • George Kapetanios & Simon Price & Garry Young, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," CAMA Working Papers 2017-58, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kapetanios, G & Price, SG & Young, G, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," Essex Finance Centre Working Papers 20328, University of Essex, Essex Business School.
  • Kapetanios, George & Price, Simon & Young, Garry, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," Bank of England working papers 699, Bank of England.
• Bayer, Sebastian, 2018. "Combining Value-at-Risk forecasts using penalized quantile regressions," Econometrics and Statistics, Elsevier, vol. 8(C), pages 56-77.
• Sarrias, Mauricio & Daziano, Ricardo A., 2018. "Individual-specific point and interval conditional estimates of latent class logit parameters," Journal of choice modelling, Elsevier, vol. 27(C), pages 50-61.
• Ahmad, Wasim & Mishra, Anil V. & Daly, Kevin J., 2018. "Financial connectedness of BRICS and global sovereign bond markets," Emerging Markets Review, Elsevier, vol. 37(C), pages 1-16.
• Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018. "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 111-129.
• Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
• Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the term structure of option implied volatility: The power of an adaptive method," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 157-177.
• Zhu, Bangzhu & Ye, Shunxin & Wang, Ping & He, Kaijian & Zhang, Tao & Wei, Yi-Ming, 2018. "A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting," Energy Economics, Elsevier, vol. 70(C), pages 143-157.
• Wang, Delu & Wang, Yadong & Song, Xuefeng & Liu, Yun, 2018. "Coal overcapacity in China: Multiscale analysis and prediction," Energy Economics, Elsevier, vol. 70(C), pages 244-257.
• Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
  • Afees A. Salisu & Idris Ademuyiwa & Kazeem Isah, 2017. "Revisiting the forecasting accuracy of Phillips curve: the role of oil price," Working Papers 022, Centre for Econometric and Allied Research, University of Ibadan.
• Özmen, Ayşe & Yılmaz, Yavuz & Weber, Gerhard-Wilhelm, 2018. "Natural gas consumption forecast with MARS and CMARS models for residential users," Energy Economics, Elsevier, vol. 70(C), pages 357-381.
• Ziel, Florian & Weron, Rafał, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Energy Economics, Elsevier, vol. 70(C), pages 396-420.
  • Florian Ziel & Rafal Weron, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Papers 1805.06649, arXiv.org.
• Zhang, Yaojie & Ma, Feng & Shi, Benshan & Huang, Dengshi, 2018. "Forecasting the prices of crude oil: An iterated combination approach," Energy Economics, Elsevier, vol. 70(C), pages 472-483.
• Presno, María José & Landajo, Manuel & Fernández González, Paula, 2018. "Stochastic convergence in per capita CO2 emissions. An approach from nonlinear stationarity analysis," Energy Economics, Elsevier, vol. 70(C), pages 563-581.
• Chai, Jian & Xing, Li-Min & Zhou, Xiao-Yang & Zhang, Zhe George & Li, Jie-Xun, 2018. "Forecasting the WTI crude oil price by a hybrid-refined method," Energy Economics, Elsevier, vol. 71(C), pages 114-127.
• Wang, Minggang & Tian, Lixin & Zhou, Peng, 2018. "A novel approach for oil price forecasting based on data fluctuation network," Energy Economics, Elsevier, vol. 71(C), pages 201-212.
• Sephton, Peter & Mann, Janelle, 2018. "Gold and crude oil prices after the great moderation," Energy Economics, Elsevier, vol. 71(C), pages 273-281.
• Pan, Zhiyuan & Wang, Qing & Wang, Yudong & Yang, Li, 2018. "Forecasting U.S. real GDP using oil prices: A time-varying parameter MIDAS model," Energy Economics, Elsevier, vol. 72(C), pages 177-187.
• Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
• Cheng, Fangzheng & Fan, Tijun & Fan, Dandan & Li, Shanling, 2018. "The prediction of oil price turning points with log-periodic power law and multi-population genetic algorithm," Energy Economics, Elsevier, vol. 72(C), pages 341-355.
• Hahn, Warren J. & DiLellio, James A. & Dyer, James S., 2018. "Risk premia in commodity price forecasts and their impact on valuation," Energy Economics, Elsevier, vol. 72(C), pages 393-403.
• Uddin, Gazi Salah & Rahman, Md Lutfur & Shahzad, Syed Jawad Hussain & Rehman, Mobeen Ur, 2018. "Supply and demand driven oil price changes and their non-linear impact on precious metal returns: A Markov regime switching approach," Energy Economics, Elsevier, vol. 73(C), pages 108-121.
• Jiao, Lei & Liao, Yin & Zhou, Qing, 2018. "Predicting carbon market risk using information from macroeconomic fundamentals," Energy Economics, Elsevier, vol. 73(C), pages 212-227.
• Drachal, Krzysztof, 2018. "Comparison between Bayesian and information-theoretic model averaging: Fossil fuels prices example," Energy Economics, Elsevier, vol. 74(C), pages 208-251.
• Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
• Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018. "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, vol. 74(C), pages 628-643.
• Smith, Michael Stanley & Shively, Thomas S., 2018. "Econometric modeling of regional electricity spot prices in the Australian market," Energy Economics, Elsevier, vol. 74(C), pages 886-903.
• Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
• Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
• Poblete-Cazenave, Miguel & Pachauri, Shonali, 2018. "A structural model of cooking fuel choices in developing countries," Energy Economics, Elsevier, vol. 75(C), pages 449-463.
• Prakash Ranjan, Ravi & Bhattachharyya, Malay, 2018. "Does investor attention to energy stocks exhibit power law?," Energy Economics, Elsevier, vol. 75(C), pages 573-582.
• Funk, Christoph, 2018. "Forecasting the real price of oil - Time-variation and forecast combination," Energy Economics, Elsevier, vol. 76(C), pages 288-302.
• Degiannakis, Stavros & Filis, George, 2018. "Forecasting oil prices: High-frequency financial data are indeed useful," Energy Economics, Elsevier, vol. 76(C), pages 388-402.
• Zhang, Jin & Li, Pujiang & Zhao, Guochang, 2018. "Is power generation really the gold measure of the Chinese economy? A conceptual and empirical assessment," Energy Policy, Elsevier, vol. 121(C), pages 211-216.
• Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.
• de Albuquerquemello, Vinícius Phillipe & de Medeiros, Rennan Kertlly & da Nóbrega Besarria, Cássio & Maia, Sinézio Fernandes, 2018. "Forecasting crude oil price: Does exist an optimal econometric model?," Energy, Elsevier, vol. 155(C), pages 578-591.
• Elamin, Niematallah & Fukushige, Mototsugu, 2018. "Modeling and forecasting hourly electricity demand by SARIMAX with interactions," Energy, Elsevier, vol. 165(PB), pages 257-268.
  • Niematallah Elamin & Mototsugu Fukushige, 2017. "Modeling and Forecasting Hourly Electricity Demand by SARIMAX with Interactions," Discussion Papers in Economics and Business 17-28, Osaka University, Graduate School of Economics.
• Antonakakis, Nikolaos & Chang, Tsangyao & Cunado, Juncal & Gupta, Rangan, 2018. "The relationship between commodity markets and commodity mutual funds: A wavelet-based analysis," Finance Research Letters, Elsevier, vol. 24(C), pages 1-9.
  • Nikolaos Antonakakis & Tsangyao Chang & Juncal Cunado & Rangan Gupta, 2016. "The Relationship between Commodity Markets and Commodity Mutual Funds: A Wavelet-Based Analysis," Working Papers 201619, University of Pretoria, Department of Economics.
• Gupta, Rangan & Mwamba, John W. Muteba & Wohar, Mark E., 2018. "The role of partisan conflict in forecasting the U.S. equity premium: A nonparametric approach," Finance Research Letters, Elsevier, vol. 25(C), pages 131-136.
  • Rangan Gupta & John W. Muteba Mwamba & Mark E. Wohar, 2016. "The Role of Partisan Conflict in Forecasting the U.S. Equity Premium: A Nonparametric Approach," Working Papers 201686, University of Pretoria, Department of Economics.
• Ping, Yuan & Li, Rui, 2018. "Forecasting realized volatility based on the truncated two-scales realized volatility estimator (TTSRV): Evidence from China's stock market," Finance Research Letters, Elsevier, vol. 25(C), pages 222-229.
• van der Merwe, C.J. & Heyman, D. & de Wet, T., 2018. "Approximating risk-free curves in sparse data environments," Finance Research Letters, Elsevier, vol. 26(C), pages 112-118.
• Kim, Donghan & Kim, Jun Sik & Seo, Sung Won, 2018. "What options to trade and when: Evidence from seasoned equity offerings," Journal of Financial Markets, Elsevier, vol. 37(C), pages 70-96.
• Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
  • Jozef Barunik & Lukas Vacha, 2016. "Do co-jumps impact correlations in currency markets?," Papers 1602.05489, arXiv.org, revised Oct 2017.
• Lin, Qi, 2018. "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, vol. 38(C), pages 103-123.
• Baltas, Nick & Karyampas, Dimitrios, 2018. "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, vol. 38(C), pages 83-102.
• Papanikolaou, Nikolaos I., 2018. "To be bailed out or to be left to fail? A dynamic competing risks hazard analysis," Journal of Financial Stability, Elsevier, vol. 34(C), pages 61-85.
  • Nikolaos I. Papanikolaou, 2017. "To Be Bailed Out or To Be Left to Fail? A Dynamic Competing Risks Hazard Analysis," BAFES Working Papers BAFES12, Department of Accounting, Finance & Economic, Bournemouth University.
• Kupiec, Paul H., 2018. "On the accuracy of alternative approaches for calibrating bank stress test models," Journal of Financial Stability, Elsevier, vol. 38(C), pages 132-146.
• Jåstad, Eirik Ogner & Mustapha, Walid Fayez & Bolkesjø, Torjus Folsland & Trømborg, Erik & Solberg, Birger, 2018. "Modelling of uncertainty in the economic development of the Norwegian forest sector," Journal of Forest Economics, Elsevier, vol. 32(C), pages 106-115.
• Bruszas, Sandy & Kaschützke, Barbara & Maurer, Raimond & Siegelin, Ivonne, 2018. "Unisex pricing of German participating life annuities—Boon or bane for customer and insurance company?," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 230-245.
• Börger, Matthias & Schupp, Johannes, 2018. "Modeling trend processes in parametric mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 369-380.
• Doan, Bao & Papageorgiou, Nicolas & Reeves, Jonathan J. & Sherris, Michael, 2018. "Portfolio management with targeted constant market volatility," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 134-147.
• Franses, Philip Hans & Janssens, Eva, 2018. "Inflation in Africa, 1960–2015," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 261-292.
• Knüppel, Malte, 2018. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," International Journal of Forecasting, Elsevier, vol. 34(1), pages 105-116.
  • Knüppel, Malte, 2014. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," Discussion Papers 40/2014, Deutsche Bundesbank.
• Clements, Michael P., 2018. "Are macroeconomic density forecasts informative?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 181-198.
  • Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, Reading University.
• Smeekes, Stephan & Wijler, Etienne, 2018. "Macroeconomic forecasting using penalized regression methods," International Journal of Forecasting, Elsevier, vol. 34(3), pages 408-430.
  • Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
• Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
  • Claudia Foroni & Pierre Guérin & Massimiliano Marcellino, 2015. "Using low frequency information for predicting high frequency variables," Working Paper 2015/13, Norges Bank.
• Berge, Travis J., 2018. "Understanding survey-based inflation expectations," International Journal of Forecasting, Elsevier, vol. 34(4), pages 788-801.
  • Travis J. Berge, 2017. "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series 2017-046, Board of Governors of the Federal Reserve System (U.S.).
• Herrera, R. & Clements, A.E., 2018. "Point process models for extreme returns: Harnessing implied volatility," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 161-175.
  • R Herrera & Adam Clements, 2015. "Point process models for extreme returns: Harnessing implied volatility," NCER Working Paper Series 104, National Centre for Econometric Research.
• Grigoli, Francesco & Mansilla, Mario & Saldías, Martín, 2018. "Macro-financial linkages and heterogeneous non-performing loans projections: An application to Ecuador," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 130-141.
  • Francesco Grigoli & Mario Mansilla & Martín Saldías, 2016. "Macro-Financial Linkages and Heterogeneous Non-Performing Loans Projections; An Application to Ecuador," IMF Working Papers 16/236, International Monetary Fund.
• Badarinza, Cristian & Ramadorai, Tarun, 2018. "Home away from home? Foreign demand and London house prices," Journal of Financial Economics, Elsevier, vol. 130(3), pages 532-555.
• Foroni, Claudia & Ravazzolo, Francesco & Sadaba, Barbara, 2018. "Assessing the predictive ability of sovereign default risk on exchange rate returns," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 242-264.
  • Claudia Foroni & Francesco Ravazzolo & Barbara Sadaba, 2017. "Assessing the Predictive Ability of Sovereign Default Risk on Exchange Rate Returns," Staff Working Papers 17-19, Bank of Canada.
• Amat, Christophe & Michalski, Tomasz & Stoltz, Gilles, 2018. "Fundamentals and exchange rate forecastability with simple machine learning methods," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 1-24.
  • Christophe Amat & Tomasz Michalski & Gilles Stoltz, 2018. "Fundamentals and exchange rate forecastability with simple machine learning methods," Working Papers halshs-01003914, HAL.
• Ismailov, Adilzhan & Rossi, Barbara, 2018. "Uncertainty and deviations from uncovered interest rate parity," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 242-259.
• Proaño, Christian R. & Tarassow, Artur, 2018. "Evaluating the predicting power of ordered probit models for multiple business cycle phases in the U.S. and Japan," Journal of the Japanese and International Economies, Elsevier, vol. 50(C), pages 60-71.
  • Christian R. Proaño & Artur Tarassow, 2017. "Evaluating the predicting power of ordered probit models for multiple business cycle phases in the U.S. and Japan," IMK Working Paper 188-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
• Debnath, Deepayan & Babu, Suresh & Ghosh, Parijat & Helmar, Michael, 2018. "The impact of India’s food security policy on domestic and international rice market," Journal of Policy Modeling, Elsevier, vol. 40(2), pages 265-283.
• Chen, Junyi & Kibriya, Shahriar & Bessler, David & Price, Edwin, 2018. "The relationship between conflict events and commodity prices in Sudan," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 663-684.
• Bonato, Matteo & Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian, 2018. "Gold futures returns and realized moments: A forecasting experiment using a quantile-boosting approach," Resources Policy, Elsevier, vol. 57(C), pages 196-212.
  • Matteo Bonato & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2016. "Gold Futures Returns and Realized Moments: A Forecasting Experiment Using a Quantile-Boosting Approach," Working Papers 201645, University of Pretoria, Department of Economics.
• Pan, Zhiyuan & Liu, Li, 2018. "Forecasting stock return volatility: A comparison between the roles of short-term and long-term leverage effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 168-180.
• Fang, Libing & Xiao, Binqing & Yu, Honghai & You, Qixing, 2018. "A stable systemic risk ranking in China’s banking sector: Based on principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1997-2009.
• Duan, Yinying & Chen, Wang & Zeng, Qing & Liu, Zhicao, 2018. "Leverage effect, economic policy uncertainty and realized volatility with regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 148-154.
• Chen, Yanhui & Zhang, Chuan & He, Kaijian & Zheng, Aibing, 2018. "Multi-step-ahead crude oil price forecasting using a hybrid grey wave model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 98-110.
• Bonaccolto, G. & Caporin, M. & Gupta, R., 2018. "The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 446-469.
  • Giovanni Bonaccolto & Massimiliano Caporin & Rangan Gupta, 2015. "The Dynamic Impact of Uncertainty in Causing and Forecasting the Distribution of Oil Returns and Risk," Working Papers 201564, University of Pretoria, Department of Economics.
• Hassani, Hossein & Silva, Emmanuel Sirimal & Gupta, Rangan & Das, Sonali, 2018. "Predicting global temperature anomaly: A definitive investigation using an ensemble of twelve competing forecasting models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 121-139.
  • Hossein Hassani & Emmanuel Sirimal Silva & Rangan Gupta & Sonali Das, 2015. "Predicting Global Temperature Anomaly: A Definitive Investigation Using an Ensemble of Twelve Competing Forecasting Models," Working Papers 201561, University of Pretoria, Department of Economics.
• He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2018. "Forecasting exchange rate using Variational Mode Decomposition and entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 15-25.
• Hong, Hui & Chen, Naiwei & O’Brien, Fergal & Ryan, James, 2018. "Stock return predictability and model instability: Evidence from mainland China and Hong Kong," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 132-142.
• Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
  • Jakub Nowotarski & Rafal Weron, 2016. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," HSC Research Reports HSC/16/07, Hugo Steinhaus Center, Wroclaw University of Technology.
• Skjerpen, Terje & Storrøsten, Halvor Briseid & Rosendahl, Knut Einar & Osmundsen, Petter, 2018. "Modelling and forecasting rig rates on the Norwegian Continental Shelf," Resource and Energy Economics, Elsevier, vol. 53(C), pages 220-239.
  • Terje Skjerpen & Halvor Briseid Storrøsten & Knut Einar Rosendahl & Petter Osmundsen, 2015. "Modelling and forecasting rig rates on the Norwegian Continental Shelf," Discussion Papers 832, Statistics Norway, Research Department.
• Zhu, Min & Chen, Rui & Du, Ke & Wang, You-Gan, 2018. "Dividend growth and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 125-137.
• Ari, Ali & Cergibozan, Raif, 2018. "Currency crises in Turkey: An empirical assessment," Research in International Business and Finance, Elsevier, vol. 46(C), pages 281-293.
• Stahl, Dale O., 2018. "Assessing the forecast performance of models of choice," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 73(C), pages 86-92.
• Deaton, Angus & Cartwright, Nancy, 2018. "Understanding and misunderstanding randomized controlled trials," Social Science & Medicine, Elsevier, vol. 210(C), pages 2-21.
  • Angus Deaton & Nancy Cartwright, 2016. "Understanding and Misunderstanding Randomized Controlled Trials," Working Papers august_25.pdf, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies..
  • Angus Deaton & Nancy Cartwright, 2017. "Understanding and misunderstanding randomized controlled trials," Working Papers 2017-10, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing..
  • Angus Deaton & Nancy Cartwright, 2016. "Understanding and Misunderstanding Randomized Controlled Trials," NBER Working Papers 22595, National Bureau of Economic Research, Inc.
• Gurgul, Henryk & Lach, Łukasz, 2018. "On using dynamic IO models with layers of techniques to measure value added in global value chains," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 155-170.
• Lafond, François & Bailey, Aimee Gotway & Bakker, Jan David & Rebois, Dylan & Zadourian, Rubina & McSharry, Patrick & Farmer, J. Doyne, 2018. "How well do experience curves predict technological progress? A method for making distributional forecasts," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 104-117.
  • Franc{c}ois Lafond & Aimee Gotway Bailey & Jan David Bakker & Dylan Rebois & Rubina Zadourian & Patrick McSharry & J. Doyne Farmer, 2017. "How well do experience curves predict technological progress? A method for making distributional forecasts," Papers 1703.05979, arXiv.org, revised Sep 2017.
• Philip Hans Franses, 2018. "Prediction Intervals For Expert-Adjusted Forecasts," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 308-320, December.
• Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," DEM Working Papers Series 145, University of Pavia, Department of Economics and Management.
  • Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
  • Emilio Zanetti Chini, 2018. "Forecasters’ utility and forecast coherence," CREATES Research Papers 2018-23, Department of Economics and Business Economics, Aarhus University.
• Torben G. Andersen & Rasmus T. Varneskov, 2018. "Consistent Inference for Predictive Regressions in Persistent VAR Economies," CREATES Research Papers 2018-09, Department of Economics and Business Economics, Aarhus University.
• Isabel Casas & Xiuping Mao & Helena Veiga, 2018. "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers 2018-10, Department of Economics and Business Economics, Aarhus University.
• Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," DEM Working Papers Series 145, University of Pavia, Department of Economics and Management.
  • Emilio Zanetti Chini, 2018. "Forecasters’ utility and forecast coherence," CREATES Research Papers 2018-23, Department of Economics and Business Economics, Aarhus University.
  • Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
• Erik Christian Montes Schütte, 2018. "In Search of a Job: Forecasting Employment Growth in the US using Google Trends," CREATES Research Papers 2018-25, Department of Economics and Business Economics, Aarhus University.
• Sebastian Ankargren & Måns Unosson & Yukai Yang, 2018. "A mixed-frequency Bayesian vector autoregression with a steady-state prior," CREATES Research Papers 2018-32, Department of Economics and Business Economics, Aarhus University.
• James Barth & Sunghoon Joo & Hyeongwoo Kim & Kang Bok Lee & Stevan Maglic & Xuan Shen, 2018. "Forecasting Net Charge-Off Rates of Banks: A PLS Approach," Auburn Economics Working Paper Series auwp2018-03, Department of Economics, Auburn University.
• Jackson, Emerson Abraham & Sillah, Abdulai & Tamuke, Edmund, 2018. "Modelling Monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins Methodology," EconStor Open Access Articles, ZBW - Leibniz Information Centre for Economics, pages 51-56.
  • Emerson Abraham Jackson & Edmond Tamuke & Abdulai Sillah, 2018. "Modelling Monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins Methodology," International Journal of Sciences, Office ijSciences, vol. 7(01), pages 51-56, January.
• Rahul Deb & Mallesh M. Pai & Maher Said, 2018. "Evaluating Strategic Forecasters," American Economic Review, American Economic Association, vol. 108(10), pages 3057-3103, October.
  • Rahul Deb & Mallesh Pai & Maher Said, 2017. "Evaluating Strategic Forecasters," Working Papers tecipa-578, University of Toronto, Department of Economics.
  • Rahul Deb & Mallesh M. Pai & Maher Said, 2018. "Evaluating Strategic Forecasters," Working Papers 18-23, New York University, Leonard N. Stern School of Business, Department of Economics.
  • Rahul Deb & Mallesh M. Pai & Maher Said, 2017. "Evaluating Strategic Forecasters," Working Papers 17-02, New York University, Leonard N. Stern School of Business, Department of Economics.
• Edward L. Glaeser & Hyunjin Kim & Michael Luca, 2018. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 77-82, May.
• Jaka Sriyana, 2018. "Inflationary effects of fiscal and monetary policies in Indonesia," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(3), pages 674-688, June.
  • Sriyana, Jaka, 2018. "Inflationary effects of fiscal and monetary policies in Indonesia," Business and Economic Horizons (BEH), Prague Development Center (PRADEC), vol. 14(3), June.
• Hanna Tarasova, 2018. "Scientific and methodical approach to adaptive diversification of industrial enterprise development under crisis conditions," Virtual Economics, The London Academy of Science and Business, vol. 1(1), pages 42-52, October.
• Darolles, Serge & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Journal of Econometrics, Elsevier, vol. 204(2), pages 223-247.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," Working Papers halshs-01944656, HAL.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," AMSE Working Papers 1845, Aix-Marseille School of Economics, France.
  • Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-01980815, HAL.
  • Darolles, Serges & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," MPRA Paper 83988, University Library of Munich, Germany.
• Mioara POPESCU, 2018. "Data Mining For Analysing Trends And Customer Behaviour Via Internet Searches," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(20), pages 1-7.
• Milind Tiwari, 2018. "Shell Companies – Identification of an Instrument Used for Illicit Purposes: A Pitch," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 17(4), pages 685-692, December.
• Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
• Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
  • Bok, Brandyn & Caratelli, Daniele & Giannone, Domenico & Sbordone, Argia & Tambalotti, Andrea, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," CEPR Discussion Papers 12589, C.E.P.R. Discussion Papers.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A regional perspective on the accuracy of machine learning forecasts of tourism demand based on data characteristics”," IREA Working Papers 201805, University of Barcelona, Research Institute of Applied Economics, revised Mar 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A regional perspective on the accuracy of machine learning forecasts of tourism demand based on data characteristics”," AQR Working Papers 201802, University of Barcelona, Regional Quantitative Analysis Group, revised Apr 2018.
• Oscar Claveria, 2018. "“A new metric of consensus for Likert scales”," IREA Working Papers 201821, University of Barcelona, Research Institute of Applied Economics, revised Oct 2018.
  • Oscar Claveria, 2018. "“A new metric of consensus for Likert scales”," AQR Working Papers 201810, University of Barcelona, Regional Quantitative Analysis Group, revised Oct 2018.
• Ricardo Crisóstomo & Lorena Couso, 2018. "Financial density forecasts: A comprehensive comparison of risk‐neutral and historical schemes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 589-603, August.
  • Ricardo Crisóstomo & Lorena Couso, 2017. "Financial density forecasts: A comprehensive comparison of risk-neutral and historical schemes," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
  • Ricardo Crisostomo & Lorena Couso, 2018. "Financial density forecasts: A comprehensive comparison of risk-neutral and historical schemes," Papers 1801.08007, arXiv.org, revised May 2018.
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019. "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, vol. 57(3), pages 923-955, September.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2011. "Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria," Working Papers 20110301, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2018. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Papers 1804.08315, arXiv.org.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," ETA: Economic Theory and Applications 253725, Fondazione Eni Enrico Mattei (FEEM).
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Working Papers 2017.06, Fondazione Eni Enrico Mattei.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2016. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," MPRA Paper 76308, University Library of Munich, Germany.
• Laura Liu, 2018. "Density Forecasts in Panel Data Models : A Semiparametric Bayesian Perspective," Finance and Economics Discussion Series 2018-036, Board of Governors of the Federal Reserve System (U.S.).
  • Laura Liu, 2018. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," Papers 1805.04178, arXiv.org, revised Feb 2020.
• Ziel, Florian & Weron, Rafał, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Energy Economics, Elsevier, vol. 70(C), pages 396-420.
  • Florian Ziel & Rafal Weron, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Papers 1805.06649, arXiv.org.
• Ray Fair, 2018. "Information Content of DSGE Forecasts," Papers 1808.02910, arXiv.org.
• Carol Alexander & Emese Lazar & Silvia Stanescu, 2010. "Analytic Moments for GARCH Processes," ICMA Centre Discussion Papers in Finance icma-dp2011-07, Henley Business School, Reading University, revised Apr 2011.
  • Carol Alexander & Emese Lazar & Silvia Stanescu, 2018. "Analytic Moments for GARCH Processes," Papers 1808.09666, arXiv.org, revised Sep 2018.
• Tobias Hartl & Roland Weigand, 2018. "Multivariate Fractional Components Analysis," Papers 1812.09149, arXiv.org, revised Jan 2019.
  • Hartl, Tobias & Weigand, Roland, 2019. "Multivariate Fractional Components Analysis," University of Regensburg Working Papers in Business, Economics and Management Information Systems 38283, University of Regensburg, Department of Economics.
• Hamna Nasir & Sadaf Majeed & Abdul Aleem, 2018. "Does Financial Development Leads Economic Growth? Evidence from Emerging Asian Markets," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 8(5), pages 599-617, May.
• Matt Lutey & Mohammad Kabir Hassan & Dave Rayome, 2018. "An Application of Can Slim Investing in the Dow Jones Benchmark," Asian Journal of Economic Modelling, Asian Economic and Social Society, vol. 6(3), pages 274-286, September.
• Renáta Myšková & Petr Hájek & Vladimír Olej, 2018. "Predicting Abnormal Stock Return Volatility Using Textual Analysis of News ? A Meta-Learning Approach," The Audit Financiar journal, Chamber of Financial Auditors of Romania, vol. 20(47), pages 185-185, February.
• Dario Buono & George Kapetanios & Massimiliano Marcellino & Gianluigi Mazzi & Fotis Papailias, 2018. "Big Data Econometrics: Now Casting and Early Estimates," BAFFI CAREFIN Working Papers 1882, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Massimo Guidolin & Alexei Orlov, 2018. "Can Investors Benefit from Hedge Fund Strategies? Utility-Based, Out-of-Sample Evidence," BAFFI CAREFIN Working Papers 1890, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
  • Massimo Guidolin & Alexei G. Orlov, 2018. "Can Investors Benefit from Hedge Fund Strategies? Utility-Based, Out-of-Sample Evidence," BAFFI CAREFIN Working Papers 1887, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Massimo Guidolin & Andrea Ricci, 2018. "Arbitrage Risk and Investor Sentiment as Causes of Persistent Mispricing: the European Evidence," BAFFI CAREFIN Working Papers 1889, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
  • Massimo Guidolin & Andrea Ricci, 2018. "Arbitrage Risk and Investor Sentiment as Causes of Persistent Mispricing: the European Evidence," BAFFI CAREFIN Working Papers 1888, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Massimo Guidolin & Andrea Ricci, 2018. "Arbitrage Risk and Investor Sentiment as Causes of Persistent Mispricing: the European Evidence," BAFFI CAREFIN Working Papers 1888, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
  • Massimo Guidolin & Andrea Ricci, 2018. "Arbitrage Risk and Investor Sentiment as Causes of Persistent Mispricing: the European Evidence," BAFFI CAREFIN Working Papers 1889, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Massimo Guidolin & Alexei G. Orlov, 2018. "Can Investors Benefit from Hedge Fund Strategies? Utility-Based, Out-of-Sample Evidence," BAFFI CAREFIN Working Papers 1887, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
  • Massimo Guidolin & Alexei Orlov, 2018. "Can Investors Benefit from Hedge Fund Strategies? Utility-Based, Out-of-Sample Evidence," BAFFI CAREFIN Working Papers 1890, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Nataliya Bondarchuk & Lesya Vasiljeva, 2018. "Impact Of Operating Costs On Economic Phenomena And The Possibility Of Their Optimization At Processors," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 4(2).
• Olha Kaut & Dmytro Kozenkov & Valentyna Lebedieva, 2018. "Organizational And Methodological Aspects Of Management Of Economic Consequences Of Technical Risks," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 4(3).
• Stavros Degiannakis & George Filis, 2019. "Forecasting European economic policy uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 94-114, February.
  • Stavros Degiannakis & George Filis, 2018. "Forecasting European Economic Policy Uncertainty," BAFES Working Papers BAFES15, Department of Accounting, Finance & Economic, Bournemouth University.
  • Degiannakis, Stavros & Filis, George, 2019. "Forecasting European Economic Policy Uncertainty," MPRA Paper 96268, University Library of Munich, Germany.
• Antonio Stasi & Francesco Diotallevi & Andrea Marchini & Gianluca Nardone, 2018. "Italian Extra-Virgin Olive Oil: Impact on Demand on Being Market Leaders, Private Labels or Small Producers," Review of Economics & Finance, Better Advances Press, Canada, vol. 13, pages 39-54, August.
• James Mitchell & Donald Robertson & Stephen Wright, 2019. "R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 681-695, October.
  • Stephen Wright & James Mitchell & Donald Robertson, 2018. "R2 bounds for predictive models: what univariate properties tell us about multivariate predictability," Birkbeck Working Papers in Economics and Finance 1804, Birkbeck, Department of Economics, Mathematics & Statistics.
• Tony Chernis & Rodrigo Sekkel, 2018. "Nowcasting Canadian Economic Activity in an Uncertain Environment," Discussion Papers 18-9, Bank of Canada.
• Lise Pichette & Marie-Noëlle Robitaille & Mohanad Salameh & Pierre St-Amant, 2018. "Dismiss the Gap? A Real-Time Assessment of the Usefulness of Canadian Output Gaps in Forecasting Inflation," Staff Working Papers 18-10, Bank of Canada.
• Luis Uzeda, 2016. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," ANU Working Papers in Economics and Econometrics 2016-632, Australian National University, College of Business and Economics, School of Economics.
  • Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
• Patrick Rizzetto, 2018. "GDP by Industry in Real Time: Are Revisions Well Behaved?," Staff Analytical Notes 2018-40, Bank of Canada.
• Mar Delgado-Téllez & Javier J. Pérez, 2018. "Institutional and economic determinants of regional public debt in Spain," Occasional Papers 1807, Banco de España;Occasional Papers Homepage.
• Pablo Aguilar & Jesús Vázquez, 2018. "Term structure and real-time learning," Working Papers 1803, Banco de España;Working Papers Homepage.
• Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections–IV models," Economics Working Papers 1640, Department of Economics and Business, Universitat Pompeu Fabra.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections — IV models," Working Papers 1841, Banco de España;Working Papers Homepage.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence Intervals for Bias and Size Distortion in IV and Local Projections–IV Models," Working Papers 1077, Barcelona Graduate School of Economics.
• María Gil & Javier J. Pérez & Alberto Urtasun, 2019. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • María Gil & Javier J. Pérez & A. Jesús Sánchez & Alberto Urtasun, 2018. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," Working Papers 1842, Banco de España;Working Papers Homepage.
• Simone Emiliozzi & Elisa Guglielminetti & Michele Loberto, 2018. "Forecasting house prices in Italy," Questioni di Economia e Finanza (Occasional Papers) 463, Bank of Italy, Economic Research and International Relations Area.
• Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2018. "The global component of inflation volatility," Temi di discussione (Economic working papers) 1170, Bank of Italy, Economic Research and International Relations Area.
  • Carriero, Andrea & Corsello, Francesco & Marcellino, Massimiliano, 2019. "The Global Component of Inflation Volatility," CEPR Discussion Papers 13470, C.E.P.R. Discussion Papers.
• Libero Monteforte & Valentina Raponi, 2019. "Short‐term forecasts of economic activity: Are fortnightly factors useful?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 207-221, April.
  • Libero Monteforte & Valentina Raponi, 2018. "Short term forecasts of economic activity: are fortnightly factors useful?," Temi di discussione (Economic working papers) 1177, Bank of Italy, Economic Research and International Relations Area.
• Gálvez-Soriano Oscar de Jesús, 2018. "Nowcasting Mexican GDP using Factor Models and Bridge Equations," Working Papers 2018-06, Banco de México.
• Carlos León & Fabio Ortega, 2018. "Nowcasting Economic Activity with Electronic Payments Data: A Predictive Modeling Approach," Revista de Economía del Rosario, Universidad del Rosario, vol. 21(2), pages 381-407, December.
  • Carlos León & Fabio Ortega, 2018. "Nowcasting economic activity with electronic payments data: A predictive modeling approach," Borradores de Economia 1037, Banco de la Republica de Colombia.
• S. Béreau & V. Faubert & K. Schmidt, 2018. "Explaining and Forecasting Euro Area Inflation: the Role of Domestic and Global Factors," Working papers 663, Banque de France.
• José García-Montalvo & Omiros Papaspiliopoulos & Timothée Stumpf-Fétizon, 2018. "Bayesian Forecasting of Electoral Outcomes with new Parties' Competition," Working Papers 1065, Barcelona Graduate School of Economics.
• Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections — IV models," Working Papers 1841, Banco de España;Working Papers Homepage.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence Intervals for Bias and Size Distortion in IV and Local Projections–IV Models," Working Papers 1077, Barcelona Graduate School of Economics.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections–IV models," Economics Working Papers 1640, Department of Economics and Business, Universitat Pompeu Fabra.
• Inoue, Atsushi & Rossi, Barbara, 2019. "The effects of conventional and unconventional monetary policy on exchange rates," Journal of International Economics, Elsevier, vol. 118(C), pages 419-447.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Chapters, in: NBER International Seminar on Macroeconomics 2018, pages 419-447, National Bureau of Economic Research, Inc.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Working Papers 25021, National Bureau of Economic Research, Inc.
  • Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," Working Papers 1078, Barcelona Graduate School of Economics.
  • Atsushi Inoue & Barbara Rossi, 2018. "The effects of conventional and unconventional monetary policy on exchange rates," Economics Working Papers 1639, Department of Economics and Business, Universitat Pompeu Fabra.
• Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
  • Benjamin K Johannsen & Elmar Mertens, 2018. "A time series model of interest rates with the effective lower bound," BIS Working Papers 715, Bank for International Settlements.
• Brei, Michael & Moreno, Ramon, 2019. "Reserve requirements and capital flows in Latin America," Journal of International Money and Finance, Elsevier, vol. 99(C).
  • Michael Brei & Ramon Moreno, 2018. "Reserve requirements and capital flows in Latin America," BIS Working Papers 741, Bank for International Settlements.
  • Michael Brei & Ramon Moreno, 2019. "Reserve requirements and capital flows in Latin America," Post-Print hal-02504212, HAL.
• Erzsebet Eva Nagy & Veronika Tengely, 2018. "External and Domestic Drivers of Inflation: The Case Study of Hungary," Russian Journal of Money and Finance, Bank of Russia, vol. 77(3), pages 49-64, September.
• Mikhail Mamonov & Renat Akhmetov & Vera Pankova & Oleg Solntsev & Anna Pestova & Artem Deshko, 2018. "Identification of Financial Sector Optimal Depth and Structure from the Perspective of Economic Growth, Macroeconomic and Financial Stability," Russian Journal of Money and Finance, Bank of Russia, vol. 77(3), pages 89-123, September.
• Ivan Baybuza, 2018. "Inflation Forecasting Using Machine Learning Methods," Russian Journal of Money and Finance, Bank of Russia, vol. 77(4), pages 42-59, December.
• Ramis Khabibullin & Alexey Ponomarenko & Sergei Seleznev, 2018. "Forecasting the implications of foreign exchange reserve accumulation with an agent-based model," Bank of Russia Working Paper Series wps37, Bank of Russia.
• Konstantin Styrin, 2018. "Forecasting inflation in Russia by Dynamic Model Averaging," Bank of Russia Working Paper Series wps39, Bank of Russia.
• Angela Abbate & Massimiliano Marcellino, 2018. "Point, interval and density forecasts of exchange rates with time varying parameter models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(1), pages 155-179, January.
  • Abbate, Angela & Marcellino, Massimiliano, 2016. "Point, interval and density forecasts of exchange rates with time-varying parameter models," CEPR Discussion Papers 11559, C.E.P.R. Discussion Papers.
  • Abbate, Angela & Marcellino, Massimiliano, 2016. "Point, interval and density forecasts of exchange rates with time-varying parameter models," Discussion Papers 19/2016, Deutsche Bundesbank.
• Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
  • Giampiero M. Gallo & Edoardo Otranto, 2017. "Combining Sharp and Smooth Transitions in Volatility Dynamics: a Fuzzy Regime Approach," Econometrics Working Papers Archive 2017_05, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
• Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 953-965, November.
  • Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," PIER Working Paper Archive 18-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Aug 2018.
• Daniela Bragoli & Jack Fosten, 2018. "Nowcasting Indian GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 259-282, April.
  • Daniela Bragoli & Jack Fosten, 2016. "Nowcasting Indian GDP," University of East Anglia School of Economics Working Paper Series 2016-06, School of Economics, University of East Anglia, Norwich, UK..
• Laura Bisio & Filippo Moauro, 2018. "Temporal disaggregation by dynamic regressions: Recent developments in Italian quarterly national accounts," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 471-494, November.
  • Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.
• Christopher F Baum & Paola Zerilli & Liyuan Chen, 2018. "Stochastic volatility, jumps and leverage in energy and stock markets: evidence from high frequency data," Boston College Working Papers in Economics 952, Boston College Department of Economics, revised 29 May 2019.
• Nyman, Rickard & Kapadia, Sujit & Tuckett, David & Gregory, David & Ormerod, Paul & Smith, Robert, 2018. "News and narratives in financial systems: exploiting big data for systemic risk assessment," Bank of England working papers 704, Bank of England.
• Chiu,Ching-Wai & Hayes, Simon & Kapetanios, George & Theodoridis, Konstantinos, 2018. "A New Approach for Detecting Shifts in Forecast Accuracy," Cardiff Economics Working Papers E2018/24, Cardiff University, Cardiff Business School, Economics Section.
  • Chiu, Ching-Wai (Jeremy) & hayes, simon & kapetanios, george & Theodoridis, Konstantinos, 2018. "A new approach for detecting shifts in forecast accuracy," Bank of England working papers 721, Bank of England.
• Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
  • Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
• Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: Nowcasting GDP and its Revisions," Discussion Papers 1824, Centre for Macroeconomics (CFM).
  • Anesti, Nikoleta & Galvão, Ana & Miranda-Agrippino, Silvia, 2018. "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers 764, Bank of England, revised 31 Jan 2020.
  • Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
• Jonathan Benchimol & Lahcen Bounader, 2018. "Optimal Monetary Policy Under Bounded Rationality," Globalization Institute Working Papers 336, Federal Reserve Bank of Dallas, revised 01 Jan 2018.
  • Benchimol, Jonathan & Bounader, Lahcen, 2018. "Optimal monetary policy under bounded rationality," Research Discussion Papers 9/2018, Bank of Finland.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy Under Bounded Rationality," IMF Working Papers 19/166, International Monetary Fund.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy under Bounded Rationality," Bank of Israel Working Papers 2019.07, Bank of Israel.
• Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
  • Granziera, Eleonora & Sekhposyan, Tatevik, 2018. "Predicting relative forecasting performance : An empirical investigation," Research Discussion Papers 23/2018, Bank of Finland.
• Kyosuke Chikamatsu, Naohisa Hirakata, Yosuke Kido, Kazuki Otaka, 2018. "Nowcasting Japanese GDPs," Bank of Japan Working Paper Series 18-E-18, Bank of Japan.
• Bulut Levent & Dogan Can, 2018. "Google Trends and Structural Exchange Rate Models for Turkish Lira–US Dollar Exchange Rate," Review of Middle East Economics and Finance, De Gruyter, vol. 14(2), pages 1-12, August.
• Wang Cindy Shin-Huei & Hafner Christian M., 2018. "A simple solution of the spurious regression problem," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(3), pages 1-14, June.
• Nicoleta Valentina FLOREA & Anisoara DUICA, 2018. "Improving Relationship With Customers By Reducing Complaints - Using Modelling And Pareto Diagram," Contemporary Economy Journal, Constantin Brancoveanu University, vol. 3(1), pages 79-87.
• Thomas Lustenberger & Enzo Rossi, 2020. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," International Journal of Central Banking, International Journal of Central Banking, vol. 16(2), pages 153-201, March.
  • Thomas Lustenberger & Enzo Rossi, 2017. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," Working Papers 2017-12, Swiss National Bank.
  • Lustenberger, Thomas & Rossi, Enzo, 2018. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," Working papers 2018/06, Faculty of Business and Economics - University of Basel.
• Kuhlmey, Florian & Minke, Matthias, 2018. "Estimating Survival Times Using Swiss Hospital Data," Working papers 2018/14, Faculty of Business and Economics - University of Basel.
• Angelica Gianfreda & Derek Bunn, 2018. "A Stochastic Latent Moment Model for Electricity Price Formation," BEMPS - Bozen Economics & Management Paper Series BEMPS46, Faculty of Economics and Management at the Free University of Bozen.
• Matus Kubik & Pavol Majher, 2018. "Budgetary Traffic Lights," Discussion Papers Discussion Paper No. 2/20, Council for Budget Responsibility.
• Peter G. Dunne, 2019. "Positive Liquidity Spillovers from Sovereign Bond-Backed Securities," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(2), pages 1-25, April.
  • Dunne, Peter G., 2018. "Positive liquidity spillovers from sovereign bond-backed securities," ESRB Working Paper Series 67, European Systemic Risk Board.
  • Dunne, Peter G., 2018. "Positive Liquidity Spillovers from Sovereign Bond-Backed Securities," Research Technical Papers 5/RT/18, Central Bank of Ireland.
• Congressional Budget Office, 2018. "The Accuracy of CBO’s Outlay Projections for Fiscal Year 2017," Reports 53923, Congressional Budget Office.
• Congressional Budget Office, 2018. "The Accuracy of CBO's Baseline Estimates for Fiscal Year 2018," Reports 54872, Congressional Budget Office.
• Chiu, Ching-Wai (Jeremy) & hayes, simon & kapetanios, george & Theodoridis, Konstantinos, 2018. "A new approach for detecting shifts in forecast accuracy," Bank of England working papers 721, Bank of England.
  • Chiu,Ching-Wai & Hayes, Simon & Kapetanios, George & Theodoridis, Konstantinos, 2018. "A New Approach for Detecting Shifts in Forecast Accuracy," Cardiff Economics Working Papers E2018/24, Cardiff University, Cardiff Business School, Economics Section.
• Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo Group Munich.
• Cristina Sattarhoff & Marc Gronwald, 2018. "How to Measure Financial Market Efficiency? A Multifractality-Based Quantitative Approach with an Application to the European Carbon Market," CESifo Working Paper Series 7102, CESifo Group Munich.
• Florian Urbschat, 2018. "The Good, the Bad, and the Ugly: Impact of Negative Interest Rates and QE on the Profitability and Risk-Taking of 1600 German Banks," CESifo Working Paper Series 7358, CESifo Group Munich.
• Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Anesti, Nikoleta & Galvão, Ana & Miranda-Agrippino, Silvia, 2018. "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers 764, Bank of England, revised 31 Jan 2020.
  • Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: Nowcasting GDP and its Revisions," Discussion Papers 1824, Centre for Macroeconomics (CFM).
  • Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
• Spencer Wheatley & Didier Sornette & Tobias Huber & Max Reppen & Robert N. Gantner, 2018. "Are Bitcoin Bubbles Predictable? Combining a Generalized Metcalfe's Law and the LPPLS Model," Swiss Finance Institute Research Paper Series 18-22, Swiss Finance Institute, revised Mar 2018.
• Jerome L Kreuser & Didier Sornette, 2018. "Bitcoin Bubble Trouble," Swiss Finance Institute Research Paper Series 18-24, Swiss Finance Institute, revised Jun 2018.
• J-C Gerlach & Guilherme Demos & Didier Sornette, 2018. "Dissection of Bitcoin's Multiscale Bubble History," Swiss Finance Institute Research Paper Series 18-30, Swiss Finance Institute.
• Feng Zhou & Zhang Qun & Didier Sornette & Liu Jiang, 2018. "Cascading Logistic Regression Onto Gradient Boosted Decision Trees to Predict Stock Market Changes Using Technical Analysis," Swiss Finance Institute Research Paper Series 18-50, Swiss Finance Institute, revised Aug 2018.
• Michael Mayer & Steven C. Bourassa & Martin Hoesli & Donato Flavio Scognamiglio, 2018. "Estimation and Updating Methods for Hedonic Valuation," Swiss Finance Institute Research Paper Series 18-76, Swiss Finance Institute.
• Tomas Adam & Filip Novotny, 2018. "Assessing the External Demand of the Czech Economy: Nowcasting Foreign GDP Using Bridge Equations," Working Papers 2018/18, Czech National Bank.
• Gallego, J & Rivero, G & Martínez, J.D., 2018. "Preventing rather than Punishing: An Early Warning Model of Malfeasance in Public Procurement," Documentos de Trabajo 016724, Universidad del Rosario.
• Carlos León & Fabio Ortega, 2018. "Nowcasting Economic Activity with Electronic Payments Data: A Predictive Modeling Approach," Revista de Economía del Rosario, Universidad del Rosario, vol. 21(2), pages 381-407, December.
  • Carlos León & Fabio Ortega, 2018. "Nowcasting economic activity with electronic payments data: A predictive modeling approach," Borradores de Economia 1037, Banco de la Republica de Colombia.
• Astrid Martínez Ortiz, 2018. "Estudio sobre el impacto de la actividad petrolera en las regiones productoras de Colombia. Caracterización departamental Santander," Cuadernos de Fedesarrollo 016813, Fedesarrollo.
• Matthias Weber & Jonas Striaukas & Martin Schumacher & Harald Binder, 2018. "Network constrained covariate coefficient and connection sign estimation," Bank of Lithuania Discussion Paper Series 8, Bank of Lithuania.
  • WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," CORE Discussion Papers 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Jonas Striaukas & Martin Schumacher & Harald Binder & Matthias Weber, 2020. "Network-Constrained Covariate Coefficient and Connection Sign Estimation," Working Papers on Finance 2001, University of St. Gallen, School of Finance.
• Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2018. "A Model of the Fed's View on Inflation," CEPR Discussion Papers 12564, C.E.P.R. Discussion Papers.
  • Thomas Hasenzagl & Fillipo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of the FED's view on inflation," Sciences Po publications 03, Sciences Po.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of FED'S view on inflation," Documents de Travail de l'OFCE 2018-03, Observatoire Francais des Conjonctures Economiques (OFCE).
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," Economic Research Papers 269087, University of Warwick - Department of Economics.
• Antolin-Diaz, Juan & Petrella, Ivan & Rubio-Ramírez, Juan Francisco, 2018. "Structural Scenario Analysis with SVARs," CEPR Discussion Papers 12579, C.E.P.R. Discussion Papers.
• Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
  • Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017. "Macroeconomic nowcasting and forecasting with big data," Staff Reports 830, Federal Reserve Bank of New York.
  • Bok, Brandyn & Caratelli, Daniele & Giannone, Domenico & Sbordone, Argia & Tambalotti, Andrea, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," CEPR Discussion Papers 12589, C.E.P.R. Discussion Papers.
• Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
  • Bollerslev, Tim & Hood, Benjamin & Huss, John & Pedersen, Lasse Heje, 2018. "Risk Everywhere: Modeling and Managing Volatility," CEPR Discussion Papers 12687, C.E.P.R. Discussion Papers.
• Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
  • S. Delle Chiaie & L. Ferrara & D. Giannone, 2017. "Common Factors of Commodity Prices," Working papers 645, Banque de France.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common Factors of Commodity Prices," CEPR Discussion Papers 12767, C.E.P.R. Discussion Papers.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2017. "Common factors of commodity prices," Working Paper Series 2112, European Central Bank.
• Broer, Tobias & Kohlhas, Alexandre, 2018. "Forecaster (Mis-)Behavior," CEPR Discussion Papers 12898, C.E.P.R. Discussion Papers.
• Luca Di Bonaventura & Mario Forni & Francesco Pattarin, 2018. "The Forecasting Performance of Dynamic Factor Models with Vintage Data," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0070, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
  • Di Bonaventura, Luca & Forni, Mario & Pattarin, Francesco, 2018. "The Forcasting Performance of Dynamic Factor Models with Vintage Data," CEPR Discussion Papers 13034, C.E.P.R. Discussion Papers.
  • Luca Di Bonaventura & Mario Forni & Francesco Pattarin, 2018. "The Forecasting Performance of Dynamic Factor Models with Vintage Data," Center for Economic Research (RECent) 138, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
• Till Weigt & Bernd Wilfling, 2018. "An approach to increasing forecast-combination accuracy through VAR error modeling," CQE Working Papers 6818, Center for Quantitative Economics (CQE), University of Muenster.
• Moses Tule & Afees A. Salisu & Charles Chimeke, 2018. "You are what you eat: The role of oil price in Nigeria inflation forecast," Working Papers 040, Centre for Econometric and Allied Research, University of Ibadan.
• Afees A. Salisu & Raymond Swaray & Idris Adediran, 2018. "Improving the predictability of commodity prices in US inflation: The role of coffee price," Working Papers 041, Centre for Econometric and Allied Research, University of Ibadan.
• Afees A. Salisu & Lateef O. Akanni & Ahamuefula Ephraim Ogbonna, 2018. "Forecasting CO2 emissions: Does the choice of estimator matter?," Working Papers 045, Centre for Econometric and Allied Research, University of Ibadan.
• Afees A. Salisu & Ahamuefula Ephraim Ogbonna & Paul Adeoye Omosebi, 2018. "Does the choice of estimator matter for forecasting? A revisit," Working Papers 053, Centre for Econometric and Allied Research, University of Ibadan.
• Afees A. Salisu & Kazeem Isah & Lateef O. Akanni, 2018. "Predicting the stock prices of G7 countries with Bitcoin prices," Working Papers 054, Centre for Econometric and Allied Research, University of Ibadan.
• Kazeem Isah & Ibrahim D. Raheem, 2018. "The Hidden Predictive Power of Cryptocurrencies: Evidence from US Stock Market," Working Papers 056, Centre for Econometric and Allied Research, University of Ibadan.
• Afees A. Salisu & Ibrahim D. Raheem, 2018. "A new procedure for pre-testing the distribution properties of Stock returns," Working Papers 057, Centre for Econometric and Allied Research, University of Ibadan.
• Afees A. Salisu & Idris Adediran, 2018. "Testing for time-varying stochastic volatility in Bitcoin returns," Working Papers 060, Centre for Econometric and Allied Research, University of Ibadan.
• Afees A. Salisu & Ahamuefula Ephraim Ogbonna, 2018. "Does time-variation matter in the stochastic volatility components for G7 stock returns," Working Papers 062, Centre for Econometric and Allied Research, University of Ibadan.
• Ray C. Fair, 2018. "Information Content of DSGE Forecasts," Cowles Foundation Discussion Papers 2140, Cowles Foundation for Research in Economics, Yale University.
• Pavel Vidal & Gilberto Ramírez & Lya Paola Sierra, 2018. "¿Por qué el Valle del Cauca ha crecido más que el promedio nacional? Un análisis regional de los ciclos y los choques económicos," Working Papers 33, Faculty of Economics and Management, Pontificia Universidad Javeriana Cali.
• Martin Bruns & Malte Rieth & Ben Schumann, 2018. "Berücksichtigung des Teufelskreises zwischen Banken und Staaten verbessert Prognose von Kreditrisiken," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 85(12), pages 253-260.
• Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2018. "International transmissions of aggregate macroeconomic uncertainty in small open economies: An empirical approach," CAMA Working Papers 2018-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Joshua C.C. Chan & Liana Jacobi & Dan Zhu, 2018. "How sensitive are VAR forecasts to prior hyperparameters? An automated sensitivity analysis," CAMA Working Papers 2018-25, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," Working Paper Series 44, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
  • Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Bo Zhang & Joshua C.C. Chan & Jamie L. Cross, 2018. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," CAMA Working Papers 2018-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2019. "Real‐time forecast combinations for the oil price," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 456-462, April.
  • Anthony Garratt & Shaun P. Vahey & Ynuyi Zhang, 2018. "Real-time Forecast Combinations for the Oil Price," National Institute of Economic and Social Research (NIESR) Discussion Papers 494, National Institute of Economic and Social Research.
  • Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2018. "Real-time forecast combinations for the oil price," CAMA Working Papers 2018-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: Nowcasting GDP and its Revisions," Discussion Papers 1824, Centre for Macroeconomics (CFM).
  • Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
  • Anesti, Nikoleta & Galvão, Ana & Miranda-Agrippino, Silvia, 2018. "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers 764, Bank of England, revised 31 Jan 2020.
• Paule Vianez, Jessica & Granado Sánchez, Manuel & Coca Pérez, José Luis, 2018. "Método Bootstrap para el cálculo de provisiones técnicas por siniestros," Cuadernos de Gestión, Universidad del País Vasco - Instituto de Economía Aplicada a la Empresa (IEAE).
• Philip Hans Franses, 2019. "Model‐based forecast adjustment: With an illustration to inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(2), pages 73-80, March.
  • Franses, Ph.H.B.F., 2018. "Model-based forecast adjustment; with an illustration to inflation," Econometric Institute Research Papers EI2018-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2018. "Dynamic return and volatility spillovers among S&P 500, crude oil and gold," Working Papers 15-46, Eastern Mediterranean University, Department of Economics.
• George A. Dyer & Alan Hernández-Solano & Pablo Meza-Pale & Héctor Robles-Berlanga & Antonio Yúnez-Naude, 2018. "Mexican agriculture and policy under NAFTA," Serie documentos de trabajo del Centro de Estudios Económicos 2018-04, El Colegio de México, Centro de Estudios Económicos.
• Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
• Carlos A. Rodríguez, 2018. "Fuentes de las fluctuaciones macroeconómicas en Puerto Rico\Sources of macroeconomic fluctuations in Puerto Rico," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 33(2), pages 219-252.
• R.G. Akhmadeev & O.A. Bykanova & N.V. Philippova & I.V. Vashchekina & T.B. Turishcheva, 2018. "Macroeconomic Indicators and their Impact on the Foreign Debt Burden: The Case of BRICS Countries," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(2), pages 68-82.
• M. Kruk & A. Semenov & A. Cherepovitsyn & A. Nikulina, 2018. "Environmental and Economic Damage from the Development of Oil and Gas Fields in the Arctic Shelf of the Russian Federation," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 423-433.
• Josep Lluís Raymond & Dolors Cotrina & Àlex Costa & Enric Puig & Vittorio Galletto & Sandra Aguilera & Marc Fíguls, 2018. "GDP estimation for Barcelona and the Barcelona Metropolitan Area. Methodological improvement in the estimation of productivity dynamics with wage information," IERMB Working Paper in economics 1801, Institut d'Estudis Regionals i Metropolitans de Barcelona.
• Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
  • Korobilis, Dimitris & Koop, Gary, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," Essex Finance Centre Working Papers 22665, University of Essex, Essex Business School.
  • Gary Koop & Dimitris Korobilis, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," Working Paper series 18-31, Rimini Centre for Economic Analysis.
• Gustavo Félix Verduzco. & David Castro Lugo. & Gilberto Aboites Manrique., 2018. "Nuevas barreras comerciales de EU a las importaciones automotrices y posibles efectos en el empleo regional," Economía: teoría y práctica, Universidad Autónoma Metropolitana, México, vol. 0(2), pages 125-176, Agosto.
• Natalya Gennadievna Dzhurka, 2018. "Spatial Concentration of Industrial Production in Russia: Testing the Home Market Effectûíêà," Spatial Economics=Prostranstvennaya Ekonomika, Economic Research Institute, Far Eastern Branch, Russian Academy of Sciences (Khabarovsk, Russia), issue 3, pages 19-42.
• Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," Economic Research Papers 269087, University of Warwick - Department of Economics.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of FED'S view on inflation," Documents de Travail de l'OFCE 2018-03, Observatoire Francais des Conjonctures Economiques (OFCE).
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2018. "A Model of the Fed's View on Inflation," CEPR Discussion Papers 12564, C.E.P.R. Discussion Papers.
  • Thomas Hasenzagl & Fillipo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of the FED's view on inflation," Sciences Po publications 03, Sciences Po.
• Trucíos, Carlos & Hotta, Luiz K. & Valls Pereira, Pedro L., 2019. "On the robustness of the principal volatility components," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 201-219.
  • Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
• Ellis W. Tallman & Saeed Zaman, 2018. "Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy," Working Papers (Old Series) 1809, Federal Reserve Bank of Cleveland, revised 22 Jun 2018.
• Benchimol, Jonathan & Bounader, Lahcen, 2018. "Optimal monetary policy under bounded rationality," Research Discussion Papers 9/2018, Bank of Finland.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy Under Bounded Rationality," IMF Working Papers 19/166, International Monetary Fund.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy under Bounded Rationality," Bank of Israel Working Papers 2019.07, Bank of Israel.
  • Jonathan Benchimol & Lahcen Bounader, 2018. "Optimal Monetary Policy Under Bounded Rationality," Globalization Institute Working Papers 336, Federal Reserve Bank of Dallas, revised 01 Jan 2018.
• Tomaz Cajner & Leland Crane & Ryan Decker & Adrian Hamins-Puertolas & Christopher J. Kurz & Tyler Radler, 2018. "Using Payroll Processor Microdata to Measure Aggregate Labor Market Activity," Finance and Economics Discussion Series 2018-005, Board of Governors of the Federal Reserve System (U.S.).
• Andrew C. Chang, 2018. "The Fed's Asymmetric Forecast Errors," Finance and Economics Discussion Series 2018-026, Board of Governors of the Federal Reserve System (U.S.).
• Laura Liu, 2018. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," Papers 1805.04178, arXiv.org, revised Feb 2020.
  • Laura Liu, 2018. "Density Forecasts in Panel Data Models : A Semiparametric Bayesian Perspective," Finance and Economics Discussion Series 2018-036, Board of Governors of the Federal Reserve System (U.S.).
• Daniel Baquero & Manuel Gonzalez-Astudillo, 2018. "A Nowcasting Model for the Growth Rate of Real GDP of Ecuador : Implementing a Time-Varying Intercept," Finance and Economics Discussion Series 2018-044, Board of Governors of the Federal Reserve System (U.S.).
• Jun Nie & Amy Oksol, 2018. "Forecasting Current-Quarter U.S.Exports Using Satellite Data," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 5-24.
• Aaron Smalter Hall, 2018. "Machine Learning Approaches to Macroeconomic Forecasting," Economic Review, Federal Reserve Bank of Kansas City, issue Q IV, pages 63-81.
• Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
  • Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
  • Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic Predictions with Big Data: The Illusion of Sparsity," Liberty Street Economics 20180521, Federal Reserve Bank of New York.
• Eyyüp Ensari ŞAHİN, 2018. "Crypto Money Bitcoin: Price Estimation with ARIMA and Artificial Neural Networks," Fiscaoeconomia, Tubitak Ulakbim JournalPark (Dergipark), issue 3.
• Samvel S. Lazaryan & Nikita E. German, 2018. "Forecasting Current GDP Dynamics With Google Search Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 127006, Russia, issue 6, pages 83-94, December.
• Cornel Coca Constantinescu & Ion Stanciu & Iulian Panait, 2018. "Impact study of telematics auto insurance," Scientific Papers 0010, Institute of Financial Studies.
• Knobel Alexander & Firanchuk Alexander & Tsukhlo Sergey & Uzun Vasily & Tishchenko Tatiana, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 10, pages 1-24, May.
• Trunin Pavel & Tsukhlo Sergey & Kiyutsevskaya Anna & Poliakova Aleksandra & Polbin Andrei, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 12, pages 1-18, June.
• Trunin Pavel & Khromov Mikhail & Lyashok Viktor & Kiyutsevskaya Anna & Gadiy Ludmila & Sherbustanova Maria, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 17, pages 1-18, October.
• Avraamova Elena & Loginov Dmitry & Khromov Mikhail & Tsukhlo Sergey & Kaukin Andrey & Miller Evgenia & Khudko Elizaveta, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 19, pages 1-20, November.
• Sinelnikov-Murylev Sergey & Drobyshevsky Sergey & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Khromov Mikhail & Tsukhlo Sergey & Khasanova Ramilya, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 2, pages 1-27, February.
• Khromov Mikhail & Tsukhlo Sergey & Uzun Vasily & Zubarevich Natalia, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 21, pages 1-20, December.
• Avraamova Elena & Loginov Dmitry & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Firanchuk Alexander & Khromov Mikhail & Tsukhlo Sergey, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 4, pages 1-27, March.
• Bobylev Yuri & Khromov Mikhail & Tsukhlo Sergey & Khasanova Ramilya & Tretiakova Elena & Osmakov Vasiliy, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 6, pages 1-25, March.
• Knobel Alexander & Firanchuk Alexander & Tsukhlo Sergey & Uzun Vasily & Tishchenko Tatiana, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 10, pages 1-23, May.
• Trunin Pavel & Tsukhlo Sergey & Kiyutsevskaya Anna & Poliakova Aleksandra & Polbin Andrei, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 1-18, June.
• Trunin Pavel & Khromov Mikhail & Lyashok Viktor & Kiyutsevskaya Anna & Gadiy Ludmila & Sherbustanova Maria, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 17, pages 1-16, October.
• Sinelnikov-Murylev Sergey & Drobyshevsky Sergey & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Khromov Mikhail & Tsukhlo Sergey & Khasanova Ramilya, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 2, pages 1-27, February.
• Khromov Mikhail & Tsukhlo Sergey & Uzun Vasily & Zubarevich Natalia, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 21, pages 1-17, December.
• Avraamova Elena & Loginov Dmitry & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Firanchuk Alexander & Khromov Mikhail & Tsukhlo Sergey, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 4, pages 1-27, March.
• Bobylev Yuri & Tsukhlo Sergey & Khasanova Ramilya & Tretiakova Elena & Osmakov Vasiliy, 2018. "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 6, pages 1-20, March.
• Tsukhlo Sergey, 2018. "Russian industrial enterprises in 2017 (on business surveys’ findings)," Published Papers ppaper-2018-307, Gaidar Institute for Economic Policy, revised 2018.
• Barinova Vera & Zemtsov Tsepan & Tsareva Yulia, 2018. "Small and medium-sized enterprises in 2016–2017," Published Papers ppaper-2018-312, Gaidar Institute for Economic Policy, revised 2018.
• Soumya Bhadury & Sanjib Pohit & Robert C. M. Beyer, 2018. "A New Approach to Nowcasting Indian Gross Value Added," NCAER Working Papers 115, National Council of Applied Economic Research.
• Erika Vanessa Alves da Silva & Nathália da Silva Oliveira & Roberto Tatiwa Ferreira & Cristiano da Costa da Silva, 2018. "Média móvel e a Curva de Phillips: previsões para a taxa de inflação em uma amostra de países desenvolvidos e em desenvolvimento [Moving Average and the Phillips Curve: forecasts for the inflation rat," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), vol. 28(2), pages 499-521, May-Augus.
• Chakraborty, Lekha & Sinha, Darshy, 2018. "Has Fiscal Rule changed the Fiscal Marksmanship of Union Government?," Working Papers 18/234, National Institute of Public Finance and Policy.
• Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018. "Nowcasting GDP Growth by Reading the Newspapers," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 505-506, pages 17-33.
• François Robin, 2018. "Use of Google Trends Data in Banque de France Monthly Retail Trade Surveys," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 505-506, pages 35-63.
• Pete Richardson, 2018. "Nowcasting and the Use of Big Data in Short-Term Macroeconomic Forecasting: A Critical Review," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 505-506, pages 65-87.
• Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK regional nowcasting using a mixed frequency vector autoregressive model," Working Papers 1805, University of Strathclyde Business School, Department of Economics.
  • Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-07, Economic Statistics Centre of Excellence (ESCoE).
• George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
• Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2018. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-14, Economic Statistics Centre of Excellence (ESCoE).
  • Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
• Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2019. "Real‐time forecast combinations for the oil price," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 456-462, April.
  • Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2018. "Real-time forecast combinations for the oil price," CAMA Working Papers 2018-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Anthony Garratt & Shaun P. Vahey & Ynuyi Zhang, 2018. "Real-time Forecast Combinations for the Oil Price," National Institute of Economic and Social Research (NIESR) Discussion Papers 494, National Institute of Economic and Social Research.
• Aleksandra Riedl & Julia Wörz, 2018. "A simple approach to nowcasting GDP growth in CESEE economies," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/18, pages 56-74.
• Tommaso Proietti & Alessandro Giovannelli, 2018. "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, vol. 105(4), pages 783-795.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers 2017-20, Department of Economics and Business Economics, Aarhus University.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CEIS Research Paper 410, Tor Vergata University, CEIS, revised 19 Jul 2017.
• Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 16(1), pages 1-33.
  • Caio Almeida & Axel Simonsen & José Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.
• Piotr Kokoszka & Hong Miao & Matthew Reimherr & Bahaeddine Taoufik, 2018. "Dynamic Functional Regression with Application to the Cross-section of Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 16(3), pages 461-485.
• Martin M Andreasen & Jesús Fernández-Villaverde & Juan F Rubio-Ramírez, 2018. "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications," Review of Economic Studies, Oxford University Press, vol. 85(1), pages 1-49.
  • Martin M. Andreasen & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2013. "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications," CREATES Research Papers 2013-12, Department of Economics and Business Economics, Aarhus University.
  • Andreasen, Martin M. & Fernández-Villaverde, Jesús & Rubio-Ramírez, Juan Francisco, 2013. "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications," CEPR Discussion Papers 9442, C.E.P.R. Discussion Papers.
  • Martin M. Andreasen & Jesús Fernández-Villaverde & Juan Rubio-Ramírez, 2013. "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications," NBER Working Papers 18983, National Bureau of Economic Research, Inc.
  • Martin M. Andreasen & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2016. "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications," Working Papers 2016-07, FEDEA.
• Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
  • Bollerslev, Tim & Hood, Benjamin & Huss, John & Pedersen, Lasse Heje, 2018. "Risk Everywhere: Modeling and Managing Volatility," CEPR Discussion Papers 12687, C.E.P.R. Discussion Papers.
• Vintu Denis & Negotei Ioana-Alina, 2018. "Analysis of Financial Stability: The Construction of a New Composite Financial Stability Index for Euro Area," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 264-270, July.
• Max Schreder, 2018. "Volatility forecasting in practice: exploratory evidence from European hedge funds," Journal of Asset Management, Palgrave Macmillan, vol. 19(4), pages 245-258, July.
• Emilio Zanetti Chini, 2018. "Forecasters’ utility and forecast coherence," CREATES Research Papers 2018-23, Department of Economics and Business Economics, Aarhus University.
  • Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," DEM Working Papers Series 145, University of Pavia, Department of Economics and Management.
  • Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
• Santiago Javier Fucci & Martín Grandes, 2018. "Inflación y crecimiento a largo plazo: ¿malas predicciones, buenos modelos?," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 41(82), pages 83-123.
• Sriyana, Jaka, 2018. "Inflationary effects of fiscal and monetary policies in Indonesia," Business and Economic Horizons (BEH), Prague Development Center (PRADEC), vol. 14(3), June.
  • Jaka Sriyana, 2018. "Inflationary effects of fiscal and monetary policies in Indonesia," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(3), pages 674-688, June.
• Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 953-965, November.
  • Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," PIER Working Paper Archive 18-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Aug 2018.
• Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and its Derivatives," NBER Working Papers 24967, National Bureau of Economic Research, Inc.
  • Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially Egalitarian Lasso and its Derivatives," PIER Working Paper Archive 18-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 17 Aug 2018.
• Marcin Chlebus, 2018. "One-day-ahead forecast of state of turbulence based on today's economic situation," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 13(3), pages 357-389, September.
• Panna Miskolczi, 2018. "Comparison of Risk Calculation Based on Historical Simulation and the Copula Function," Public Finance Quarterly, State Audit Office of Hungary, vol. 63(1), pages 80-95.
• Bartosz Uniejewski & Rafał Weron, 2018. "Efficient Forecasting of Electricity Spot Prices with Expert and LASSO Models," Energies, MDPI, Open Access Journal, vol. 11(8), pages 1-26, August.
  • Bartosz Uniejewski & Rafal Weron, 2018. "Efficient forecasting of electricity spot prices with expert and LASSO models," HSC Research Reports HSC/18/02, Hugo Steinhaus Center, Wroclaw University of Technology.
• Katarzyna Hubicka & Grzegorz Marcjasz & Rafal Weron, 2018. "A note on averaging day-ahead electricity price forecasts across calibration windows," HSC Research Reports HSC/18/03, Hugo Steinhaus Center, Wroclaw University of Technology.
• Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2020. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 466-479.
  • Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2018. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," HSC Research Reports HSC/18/05, Hugo Steinhaus Center, Wroclaw University of Technology.
• Grzegorz Marcjasz & Tomasz Serafin & Rafał Weron, 2018. "Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, Open Access Journal, vol. 11(9), pages 1-20, September.
  • Grzegorz Marcjasz & Tomasz Serafin & Rafal Weron, 2018. "Selection of calibration windows for day-ahead electricity price forecasting," HSC Research Reports HSC/18/06, Hugo Steinhaus Center, Wroclaw University of Technology.
• Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1533-1547.
  • Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2018. "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," HSC Research Reports HSC/18/07, Hugo Steinhaus Center, Wroclaw University of Technology.
• Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
  • Katarzyna Maciejowska & Rafal Weron, 2019. "Electricity price forecasting," HSC Research Reports HSC/19/01, Hugo Steinhaus Center, Wroclaw University of Technology.
• Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018. "Mixed frequency models with MA components," Working Paper Series 2206, European Central Bank.
  • Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018. "Mixed frequency models with MA components," Discussion Papers 02/2018, Deutsche Bundesbank.
• Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
• Kurz-Kim, Jeong-Ryeol, 2018. "A note on the predictive power of survey data in nowcasting euro area GDP," Discussion Papers 10/2018, Deutsche Bundesbank.
• Gerke, Rafael & Giesen, Sebastian & Kienzler, Daniel, 2018. "Uncertainty about QE effects when an interest rate peg is anticipated," Discussion Papers 12/2018, Deutsche Bundesbank.
• Pinkwart, Nicolas, 2018. "Short-term forecasting economic activity in Germany: A supply and demand side system of bridge equations," Discussion Papers 36/2018, Deutsche Bundesbank.
• Götz, Thomas B. & Hauzenberger, Klemens, 2018. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," Discussion Papers 40/2018, Deutsche Bundesbank.
• Ollech, Daniel, 2018. "Seasonal adjustment of daily time series," Discussion Papers 41/2018, Deutsche Bundesbank.
• Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers 48/2018, Deutsche Bundesbank.
  • Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," IWH Discussion Papers 2/2019, Halle Institute for Economic Research (IWH).
• Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
  • Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
• Jang, Tae-Seok & Sacht, Stephen, 2018. "Forecast heuristics, consumer expectations, and new-Keynesian macroeconomics: A horse race," Economics Working Papers 2018-09, Christian-Albrechts-University of Kiel, Department of Economics.
• Jang, Tae-Seok & Sacht, Stephen, 2018. "Macroeconomic dynamics under bounded rationality: On the impact of consumers' forecast heuristics," Economics Working Papers 2018-10, Christian-Albrechts-University of Kiel, Department of Economics.
• Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
• Kašćelan, Ljiljana & Lazović, Vujica & Đuričković, Tamara & Rondović Biljana, 2018. "Analysis of the Diffusion of E-services in Public Sector Using the Decision Tree Method," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2018), Split, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Split, Croatia, 6-8 September 2018, pages 38-48, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
• Opiła, Janusz, 2018. "Visualization in a Knowledge Transfer Process," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2018), Split, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Split, Croatia, 6-8 September 2018, pages 485-493, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
• Emerson Abraham Jackson & Edmond Tamuke & Abdulai Sillah, 2018. "Modelling Monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins Methodology," International Journal of Sciences, Office ijSciences, vol. 7(01), pages 51-56, January.
  • Jackson, Emerson Abraham & Sillah, Abdulai & Tamuke, Edmund, 2018. "Modelling Monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins Methodology," EconStor Open Access Articles, ZBW - Leibniz Information Centre for Economics, pages 51-56.
• Heinisch, Katja & Lindner, Axel, 2018. "For how long do IMF forecasts of world economic growth stay up-to-date?," EconStor Open Access Articles, ZBW - Leibniz Information Centre for Economics, pages 1-6.
• Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
• Jahn, Malte, 2018. "Artificial neural network regression models: Predicting GDP growth," HWWI Research Papers 185, Hamburg Institute of International Economics (HWWI).
• Coupé, Tom, 2018. "Replicating "Predicting the present with Google trends" by Hyunyoung Choi and Hal Varian (The Economic Record, 2012)," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 12, pages 1-8.
  • Coupé, Tom, 2017. "Replicating "Predicting the present with Google trends" by Hyunyoung Choi and Hal Varian (The Economic Record, 2012)," Economics Discussion Papers 2017-76, Kiel Institute for the World Economy (IfW).
• Holtemöller, Oliver & Schult, Christoph, 2018. "Expectation formation, financial frictions, and forecasting performance of dynamic stochastic general equilibrium models," IWH Discussion Papers 15/2018, Halle Institute for Economic Research (IWH).
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Wieschemeyer, Matthias & Zeddies, Götz, 2018. "Mittelfristprojektion des IWH: Wirtschaftsentwicklung und Öffentliche Finanzen 2018 bis 2025," Konjunktur aktuell, Halle Institute for Economic Research (IWH), vol. 6(4), pages 105-114.
• Pablo Duarte & Bernd Süssmuth, 2018. "Implementing an Approximate Dynamic Factor Model to Nowcast GDP Using Sensitivity Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 127-141, April.
  • Duarte, Pablo & Süßmuth, Bernd, 2018. "Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis," Working Papers 152, University of Leipzig, Faculty of Economics and Management Science.
• Wei-Bin Zhang, 2018. "A Growth Theory Based on Walrasian General Equilibrium, Solow-Uzawa Growth, and Heckscher-Ohlin Trade Theories," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 16(3-B), pages 452-464.
• Berislav Žmuk & Ksenija Dumièiæ & Irena Paliæ, 2018. "Forecasting Labour Productivity in the European Union Member States: Is Labour Productivity Changing as Expected?," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 16(3-B), pages 504-523.
• AMATO, Amedeo, 2018. "Some International Financial Contributions: Empirical Results and Policy Implications," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 71(2), pages 1-1.
• Moosa, Imad A. & Vaz, John, 2018. "Direct and Indirect Forecasting of Cross Exchange Rates," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 71(2), pages 173-190.
• Awel, Yesuf M., 2018. "Forecasting GDP Growth: Application of Autoregressive Integrated Moving Average Model," Empirical Economic Review, University of Management and Technology, Lahore, vol. 1(2), pages 1-16.
• Gueddoudj, Sabbah, 2018. "Financial Variables as Predictive Indicators of the Luxembourg GDP Growth," Empirical Economic Review, University of Management and Technology, Lahore, vol. 1(2), pages 49-62.
• Aghayan, Behnoosh Sadat & Bahrami, Javid & Jahangard, Esfandiar, 2018. "Forecasting Iran's Economy Inflation with DSGE-VAR Model (Theory and Technique)," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 5(2), pages 149-176, August.
• Wali ULLAH & Khadija Malik BARI, 2018. "The Term Structure of Government Bond Yields in an Emerging Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-28, September.
• Mircea BAHNA & Cosmin-Octavian CEPOI & Bogdan Andrei DUMITRESCU & Virgil DAMIAN, 2018. "Estimating the Price Impact of Market Orders on the Bucharest Stock Exchange," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 120-133, December.
• Sinelnikova-Muryleva, Elena V. (Синельникова-Мурылева, Елена) & Gorshkova, Taisija G. (Горшкова, Таисия) & Makeeva, Natalja V. (Макеева, Наталья), 2018. "Default forecasting in the Russian banking sector
  [Прогнозирование Дефолтов В Российском Банковском Секторе]," Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 2, pages 8-27, April.
• Angelica BÃCESCU-CÃRBUNARU, 2018. "Global Demographic Pressures and Management of Natural Resources – Foresights about the Future of Mankind," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 19(1), pages 40-53, March.
• Luca Brugnolini, 2018. "About Local Projection Impulse Response Function Reliability," CEIS Research Paper 440, Tor Vergata University, CEIS, revised 09 Jun 2018.
• Thomas Conefrey & Gerard O'Reilly & Graeme Walsh, 2018. "Modelling External Shocks in a Small Open Economy: The Case of Ireland," National Institute Economic Review, National Institute of Economic and Social Research, vol. 244(1), pages 56-63, May.
• Shahzad Ahmad & Waqas Ahmed & Ehsan Choudhri & Farooq Pasha & Abdullah Tahir, 2018. "A Model for Forecasting and Policy Analysis in Pakistan: The Role of Government and External Sectors," SBP Working Paper Series 95, State Bank of Pakistan, Research Department.
• Fida Hussain & Kalim Hayder & Muhammad Rehman, 2018. "Nowcasting LSM Growth in Pakistan," SBP Working Paper Series 98, State Bank of Pakistan, Research Department.
• Krzysztof Echaust, 2018. "Conditional VaR using GARCH-EVT approach with optimal tail selection," Proceedings of Economics and Finance Conferences 6910151, International Institute of Social and Economic Sciences.
• Michal Mares & Martin Slany, 2018. "Early Warning Indicator of financial crises for V4 Countries," Proceedings of Economics and Finance Conferences 6910382, International Institute of Social and Economic Sciences.
• Łukasz Lipiński & Michał Bernardelli, 2018. "Anonimowość w Internecie – identyfikacja płci użytkowników na podstawie historii odwiedzanych stron internetowych," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 53, pages 147-162.
• Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," Economic Research Papers 269087, University of Warwick - Department of Economics.
  • Thomas Hasenzagl & Fillipo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of the FED's view on inflation," Sciences Po publications 03, Sciences Po.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of FED'S view on inflation," Documents de Travail de l'OFCE 2018-03, Observatoire Francais des Conjonctures Economiques (OFCE).
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2018. "A Model of the Fed's View on Inflation," CEPR Discussion Papers 12564, C.E.P.R. Discussion Papers.
• A. M. Angulo & J. Mur & F. J. Trívez, 2018. "Measuring resilience to economic shocks: an application to Spain," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(2), pages 349-373, March.
• Masato Yamazaki & Atsushi Koike & Yoshinori Sone, 2018. "A Heuristic Approach to the Estimation of Key Parameters for a Monthly, Recursive, Dynamic CGE Model," Economics of Disasters and Climate Change, Springer, vol. 2(3), pages 283-301, October.
• Wen-Hsien Liu & Shu-Shih Weng, 2018. "On predicting the semiconductor industry cycle: a Bayesian model averaging approach," Empirical Economics, Springer, vol. 54(2), pages 673-703, March.
• Fabio Bacchini & Maria Elena Bontempi & Roberto Golinelli & Cecilia Jona-Lasinio, 2018. "Short- and long-run heterogeneous investment dynamics," Empirical Economics, Springer, vol. 54(2), pages 343-378, March.
• Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
  • Katja Drechsel & Rolf Scheufele, 2012. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," Working Papers 2012-16, Swiss National Bank.
  • Drechsel, Katja & Scheufele, Rolf, 2013. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," IWH Discussion Papers 7/2013, Halle Institute for Economic Research (IWH).
• Sami Ben Jabeur & Youssef Fahmi, 2018. "Forecasting financial distress for French firms: a comparative study," Empirical Economics, Springer, vol. 54(3), pages 1173-1186, May.
• Angelos T. Vouldis & Dimitrios P. Louzis, 2018. "Leading indicators of non-performing loans in Greece: the information content of macro-, micro- and bank-specific variables," Empirical Economics, Springer, vol. 54(3), pages 1187-1214, May.
• Inske Pirschel & Maik H. Wolters, 2018. "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, vol. 55(2), pages 573-596, September.
• Matteo Luciani & Madhavi Pundit & Arief Ramayandi & Giovanni Veronese, 2018. "Nowcasting Indonesia," Empirical Economics, Springer, vol. 55(2), pages 597-619, September.
  • Luciani, Matteo & Pundit, Madhavi & Ramayandi, Arief & Veronese , Giovanni, 2015. "Nowcasting Indonesia," ADB Economics Working Paper Series 471, Asian Development Bank.
  • Matteo Luciani & Madhavi Pundit & Arief Ramayandi & Giovanni Veronese, 2015. "Nowcasting Indonesia," Finance and Economics Discussion Series 2015-100, Board of Governors of the Federal Reserve System (U.S.), revised 09 Nov 2015.
• Konstantin A. Kholodilin & Claus Michelsen & Dirk Ulbricht, 2018. "Speculative price bubbles in urban housing markets," Empirical Economics, Springer, vol. 55(4), pages 1957-1983, December.
• C. Orsenigo & C. Vercellis, 2018. "Anthropogenic influence on global warming for effective cost-benefit analysis: a machine learning perspective," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 45(3), pages 425-442, September.
• Manhal Ali & Reza Salehnejad & Mohaimen Mansur, 2018. "Hospital heterogeneity: what drives the quality of health care," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(3), pages 385-408, April.
• Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
• Fritz Breuss, 2018. "Would DSGE Models Have Predicted the Great Recession in Austria?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 105-126, April.
• Pablo Duarte & Bernd Süssmuth, 2018. "Implementing an Approximate Dynamic Factor Model to Nowcast GDP Using Sensitivity Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 127-141, April.
  • Duarte, Pablo & Süßmuth, Bernd, 2018. "Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis," Working Papers 152, University of Leipzig, Faculty of Economics and Management Science.
• Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.
  • Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
• KhasadYahu ZarBabal & Jocelyn Evans, 2018. "Does wall street affect main street? examining potential spillovers from investor stock market sentiment to personal consumption expenditures," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 293-314, April.
• Vugar Ahmadov & Salman Huseynov & Shaig Adigozalov & Fuad Mammadov & Vugar Rahimov, 2018. "Forecasting inflation in post-oil boom years: A case for regime switches?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 369-385, April.
• Muhammad Aamir Khan & Naseeb Zada & Kakali Mukhopadhyay, 2018. "Economic implications of the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) on Pakistan: a CGE approach," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-20, December.
• M. L. Bertotti & G. Modanese, 2018. "Mathematical models describing the effects of different tax evasion behaviors," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(2), pages 351-363, July.
• David Court & Benjamin Gillen & Jordi McKenzie & Charles R. Plott, 2018. "Two information aggregation mechanisms for predicting the opening weekend box office revenues of films: Boxoffice Prophecy and Guess of Guesses," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(1), pages 25-54, January.
  • David Court & Benjamin Gillen & Jordi McKenzie & Charles Plott, 2015. "Two Information Aggregation Mechanisms for Predicting the Opening Weekend Box Office Revenues of Films: Boxoffice Prophecy and Guess of Guesses," Natural Field Experiments 00541, The Field Experiments Website.
• Bo Carlsson & Gunnar Eliasson & Karolin Sjöö, 2018. "The Swedish industrial support program of the 1970s revisited," Journal of Evolutionary Economics, Springer, vol. 28(4), pages 805-835, September.
• Sangeeta Das & Dipankor Coondoo, 2018. "Is PMI Useful in Quarterly GDP Growth Forecasts for India? An Exploratory Note," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(1), pages 199-207, December.
• Dilip Kumar, 2018. "Modeling and Forecasting Unbiased Extreme Value Volatility Estimator in Presence of Leverage Effect," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 313-335, June.
• Zouheir Mighri, 2018. "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 427-473, June.
• Carlos Cuerpo & Ángel Cuevas & Enrique M. Quilis, 2018. "Estimating output gap: a beauty contest approach," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(3), pages 275-304, August.
• Leif Jacobs & Lara Quack, 2018. "Das Ende der Dieselsubvention: Verteilungseffekte einer CO2-basierten Energiesteuerreform
  [The End of the Diesel Subsidy: Distributional Effects of a CO2-based Energy Tax Reform]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 98(8), pages 578-586, August.
• Djahoué Mangblé Gérald, 2018. "Estimating and Forecasting West Africa Stock Market Volatility Using Asymmetric GARCH Models," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 8(6), pages 1-4.
• Emeka Nkoro & Aham Kelvin Uko, 2018. "A Small-Size Macroeconometric Model for Nigerian Economy," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(2), pages 1-4.
• Peter G. Dunne, 2019. "Positive Liquidity Spillovers from Sovereign Bond-Backed Securities," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(2), pages 1-25, April.
  • Dunne, Peter G., 2018. "Positive Liquidity Spillovers from Sovereign Bond-Backed Securities," Research Technical Papers 5/RT/18, Central Bank of Ireland.
  • Dunne, Peter G., 2018. "Positive liquidity spillovers from sovereign bond-backed securities," ESRB Working Paper Series 67, European Systemic Risk Board.
• Nick Jagger, 2018. "A Co-Evolutionary, Long-Term, MacroEconomic Forecast for the UK Using Demographic Projections," SPRU Working Paper Series 2018-20, SPRU - Science Policy Research Unit, University of Sussex Business School.
• Håvard Hungnes, 2018. "Encompassing tests for evaluating multi-step system forecasts invariant to linear transformations," Discussion Papers 871, Statistics Norway, Research Department.
• Nico Keilman & Dinh Q. Pham & Astri Syse, 2018. "Mortality shifts and mortality compression. The case of Norway, 1900-2060," Discussion Papers 884, Statistics Norway, Research Department.
• Rahul Deb & Mallesh M. Pai & Maher Said, 2018. "Evaluating Strategic Forecasters," American Economic Review, American Economic Association, vol. 108(10), pages 3057-3103, October.
  • Rahul Deb & Mallesh Pai & Maher Said, 2017. "Evaluating Strategic Forecasters," Working Papers tecipa-578, University of Toronto, Department of Economics.
  • Rahul Deb & Mallesh M. Pai & Maher Said, 2018. "Evaluating Strategic Forecasters," Working Papers 18-23, New York University, Leonard N. Stern School of Business, Department of Economics.
  • Rahul Deb & Mallesh M. Pai & Maher Said, 2017. "Evaluating Strategic Forecasters," Working Papers 17-02, New York University, Leonard N. Stern School of Business, Department of Economics.
• Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-07, Economic Statistics Centre of Excellence (ESCoE).
  • Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK regional nowcasting using a mixed frequency vector autoregressive model," Working Papers 1805, University of Strathclyde Business School, Department of Economics.
• Marian Vavra, 2018. "Assessing Distributional Properties of Forecast Errors," Working and Discussion Papers WP 3/2018, Research Department, National Bank of Slovakia.
• Yuzhi Cai & Guodong Li, 2018. "A novel approach to modelling the distribution of financial returns," Working Papers 2018-22, Swansea University, School of Management.

2017

• Behrad-Amin, Mehdi & Zamanian , Gholamreza & Esfandiari , Marziyeh, 2017. "The Impact of Oil Shocks on Foreign Trade in Iran: The Role of Inflation Targeting Policy," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 4(1), pages 1-28, May.
• Emilian DOBRESCU, 2017. "Modelling an Emergent Economy and Parameter Instability Problem," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-28, June.
• Emrah ALTUN & Morad ALIZADEH & Gamze OZEL & Hüseyin TATLIDIL & Najmieh MAKSAYI, 2017. "Forecasting Value-At-Risk With Two-Step Method: Garch-Exponentiated Odd Log-Logistic Normal Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 97-115, December.
• Akaev, Askar A. (Акаев, Аскар) & Sarygulov, Askar I. (Сарыгулов, Аскар) & Sokolov, Valentin N. (Соколов, Валентин), 2017. "On the Possibility of Dynamic Optimization of Output by Changing the Level of Income Inequality
  [О Динамической Оптимизации Роста Ввп Путем Изменения Уровня Неравенства Доходов]," Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 6, pages 8-23, December.
• Randall W. Jackson, 2017. "Computing Coal Dependent Employment Estimates," Working Papers Technical Document 2017-0, Regional Research Institute, West Virginia University.
• Madalina-Gabriela ANGHEL & Ana CARP & Marian SFETCU & Stefan Gabriel DUMBRAVA, 2017. "Econometric Model For Analyzing The Influence Of Factors On Final Consumption," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(10), pages 123-131, October.
• Madalina-Gabriela ANGHEL & Constantin ANGHELACHE & Georgiana NITA & Gyorgy BODO, 2017. "The Main Concepts Of The Eqcm Model And Data-Based Dvar Systems," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(7), pages 132-140, July.
• Constantin ANGHELACHE & Madalina-Gabriela ANGHEL & Zoica NICOLA & Radu STOICA, 2017. "Correction Of Equilibrum And Autoregressive Models Used In The Macroeconomic Forecast," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(7), pages 92-104, July.
• Julia Mortera & A. Philip Dawid, 2017. "A Note on Prediction Markets," Departmental Working Papers of Economics - University 'Roma Tre' 0215, Department of Economics - University Roma Tre.
• Loretta Mastroeni & Pierluigi Vellucci, 2017. "“Chaos” In Energy And Commodity Markets: A Controversial Matter," Departmental Working Papers of Economics - University 'Roma Tre' 0218, Department of Economics - University Roma Tre.
• Davide De Gaetano, 2017. "Forecasting With Garch Models Under Structural Breaks: An Approach Based On Combinations Across Estimation Windows," Departmental Working Papers of Economics - University 'Roma Tre' 0219, Department of Economics - University Roma Tre.
• Vincenzo Atella & Federico Belotti & Ludovico Carrino & Andrea Piano Mortari, 2017. "The future of Long Term Care in Europe. An investigation using a dynamic microsimulation model," CEIS Research Paper 405, Tor Vergata University, CEIS, revised 08 May 2017.
• Tommaso Proietti & Alessandro Giovannelli, 2018. "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, vol. 105(4), pages 783-795.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers 2017-20, Department of Economics and Business Economics, Aarhus University.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CEIS Research Paper 410, Tor Vergata University, CEIS, revised 19 Jul 2017.
• Tommaso Proietti & Niels Haldrup & Oskar Knapik, 2017. "Spikes and memory in (Nord Pool) electricity price spot prices," CREATES Research Papers 2017-39, Department of Economics and Business Economics, Aarhus University.
  • Tommaso Proietti & Niels Haldrup & Oskar Knapik, 2017. "Spikes and memory in (Nord Pool) electricity price spot prices," CEIS Research Paper 422, Tor Vergata University, CEIS, revised 18 Dec 2017.
• Qing Zhou & Robert Faff, 2017. "The complementary role of cross-sectional and time-series information in forecasting stock returns," Australian Journal of Management, Australian School of Business, vol. 42(1), pages 113-139, February.
• Aviral Kumar Tiwari & Phouphet Kyophilavong, 2017. "Exchange Rates and International Reserves in India," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 18(1), pages 76-93, March.
• Santos, André Alves Portela & Ferreira, Alexandre R., 2017. "On the choice of covariance specifications for portfolio selection problems," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(1), May.
  • R. Ferreira, Alexandre & A. P. Santos, Andre, 2016. "On the choice of covariance specifications for portfolio selection problems," MPRA Paper 73259, University Library of Munich, Germany.
• Fida Hussain & Asif Mahmood, 2017. "Predicting Output Growth and Inflation in Pakistan: The Role of Yield Spread," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 13, pages 53-76.
• Fida Hussain & Asif Mahmood, 2017. "Predicting Inflation and Output in Pakistan: The Role of Yield Spread," SBP Working Paper Series 93, State Bank of Pakistan, Research Department.
• Jiri Prochazka & Matej Camaj, 2017. "Modelling the number of road accidents of uninsured drivers and their severity," Proceedings of International Academic Conferences 5408040, International Institute of Social and Economic Sciences.
• Taku Yamamoto & Hiroaki Chigira, 2017. "Forecasting Mortality: Some Recent Developments," Proceedings of International Academic Conferences 5808110, International Institute of Social and Economic Sciences.
• Michał Chojnowski & Piotr Dybka, 2017. "Is Exchange Rate Moody? Forecasting Exchange Rate with Google Trends Data," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(1), pages 1-21, June.
• Giovanni De Luca & Giampiero M. Gallo & Danilo Carità, 2017. "Evaluating Combined Forecasts for Realized Volatility Using Asymmetric Loss Functions," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(2), pages 99-111, December.
• Waldemar Florczak, 2017. "Wpływ starzejącego się społeczeństwa na długookresowy wzrost gospodarczy Polski do roku 2050," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 5, pages 73-104.
• Mihaela Simionescu, 2017. "Bayesian Forecast Intervals for Inflation and Unemployment Rate in Romania," Bulgarian Economic Papers (www.bep.bg) bep-2017-06, St Kliment Ohridski University of Sofia, Faculty of Economics and Business Administration / Center for Economic Theories and Policies, revised May 2017.
• Elena Pelinescu & Mihaela Simionescu, 2017. "The Effects of the Recent Economic and Financial Crisis on the Romanian Economy," Working papers 15, Research Association for Interdisciplinary Studies.
• Mihaela Simionescu & Mirel Daniel Simionescu, 2017. "The Connection between Foreign Direct Investment and Unemployment Rate in the United States," Working papers 18, Research Association for Interdisciplinary Studies.
• Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2019. "Mixed-Frequency Models for Tracking Short-Term Economic Developments in Switzerland," International Journal of Central Banking, International Journal of Central Banking, vol. 15(2), pages 151-178, June.
  • Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2017. "Mixed-frequency models for tracking short-term economic developments in Switzerland," Working Papers 2017-02, Swiss National Bank.
• Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.
  • Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
• Thomas Lustenberger & Enzo Rossi, 2020. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," International Journal of Central Banking, International Journal of Central Banking, vol. 16(2), pages 153-201, March.
  • Thomas Lustenberger & Enzo Rossi, 2017. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," Working Papers 2017-12, Swiss National Bank.
  • Lustenberger, Thomas & Rossi, Enzo, 2018. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," Working papers 2018/06, Faculty of Business and Economics - University of Basel.
• Éric Heyer & Xavier Timbeau, 2017. "Chômage, déficit, dette publique. Quelles marges pour les cinq prochaines années ?," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(2), pages 135-155.
  • Eric Heyer & Xavier Timbeau, 2017. "Chômage, déficit, dette publique: Quelles marges pour les cinq prochaines années ?," Sciences Po publications info:hdl:2441/302li69kth8, Sciences Po.
• Xin Li & Kyung-Min Nam, 2017. "One country, two “urban” systems: focusing on bimodality in China’s city-size distribution," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 59(2), pages 427-452, September.
• Ricardo Buettner, 2017. "Predicting user behavior in electronic markets based on personality-mining in large online social networks," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 247-265, August.
• Eric. W. K. See-To & Yang Yang, 2017. "Market sentiment dispersion and its effects on stock return and volatility," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 283-296, August.
• Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
  • Amendola, Alessandra & Candila, Vincenzo & Scognamillo, Antonio, 2015. "On the influence of the U.S. monetary policy on the crude oil price volatility," 2015 Fourth Congress, June 11-12, 2015, Ancona, Italy 207860, Italian Association of Agricultural and Applied Economics (AIEAA).
• Harri Pönkä, 2017. "Predicting the direction of US stock markets using industry returns," Empirical Economics, Springer, vol. 52(4), pages 1451-1480, June.
  • Pönkä, Harri, 2014. "Predicting the direction of US stock markets using industry returns," MPRA Paper 62942, University Library of Munich, Germany.
• Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017. "The role of indicator selection in nowcasting euro-area GDP in pseudo-real time," Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
  • A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
• Constantin Bürgi & Tara M. Sinclair, 2017. "A nonparametric approach to identifying a subset of forecasters that outperforms the simple average," Empirical Economics, Springer, vol. 53(1), pages 101-115, August.
  • Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, Research Program on Forecasting.
• Malte Knüppel & Guido Schultefrankenfeld, 2017. "Interest rate assumptions and predictive accuracy of central bank forecasts," Empirical Economics, Springer, vol. 53(1), pages 195-215, August.
  • Knüppel, Malte & Schultefrankenfeld, Guido, 2013. "The Empirical (Ir)Relevance of the Interest Rate Assumption for Central Bank Forecasts," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 80042, Verein für Socialpolitik / German Economic Association.
  • Knüppel, Malte & Schultefrankenfeld, Guido, 2013. "The empirical (ir)relevance of the interest rate assumption for central bank forecasts," Discussion Papers 11/2013, Deutsche Bundesbank.
• Fabian Krüger, 2017. "Survey-based forecast distributions for Euro Area growth and inflation: ensembles versus histograms," Empirical Economics, Springer, vol. 53(1), pages 235-246, August.
• Graham Elliott, 2017. "Forecast combination when outcomes are difficult to predict," Empirical Economics, Springer, vol. 53(1), pages 7-20, August.
• Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
  • Tony Chernis & Rodrigo Sekkel, 2017. "A Dynamic Factor Model for Nowcasting Canadian GDP Growth," Staff Working Papers 17-2, Bank of Canada.
• Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.
• Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2017. "The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method," Empirical Economics, Springer, vol. 53(3), pages 879-889, November.
  • Mehmet Balcilar & Rangan Gupta & STELIOS BEKIROS, 2015. "The Role Of News-Based Uncertainty Indices In Predicting Oil Markets: A Hybrid Nonparametric Quantile Causality Method," Working Papers 15-02, Eastern Mediterranean University, Department of Economics.
  • Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2015. "The Role of News-Based Uncertainty Indices in Predicting Oil Markets: A Hybrid Nonparametric Quantile Causality Method," Working Papers 201522, University of Pretoria, Department of Economics.
• Vladimir Vovk, 2017. "The role of measurability in game-theoretic probability," Finance and Stochastics, Springer, vol. 21(3), pages 719-739, July.
• Sebastian Voigt & Oliver Hinz, 2017. "Assessing the economic effects of server launches in free-to-play MMO games," Journal of Business Economics, Springer, vol. 87(4), pages 421-464, May.
  • Voigt, Sebastian & Hinz, Oliver, 2016. "Assessing the Economic Effects of Server Launches in Free-to-Play MMO Games," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 84846, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Sami Oinonen & Maritta Paloviita, 2017. "How Informative are Aggregated Inflation Expectations? Evidence from the ECB Survey of Professional Forecasters," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(2), pages 139-163, November.
  • Oinonen, Sami & Paloviita, Maritta, 2016. "How informative are aggregated inflation expectations? Evidence from the ECB Survey of Professional Forecasters," Research Discussion Papers 15/2016, Bank of Finland.
• Amit K. Sinha & Philip A. Horvath & Robert C. Scott, 2017. "The real miss-specification in the forward rate premium puzzle," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(3), pages 463-473, July.
• Beatriz Vaz de Melo Mendes & Victor Bello Accioly, 2017. "Improving (E)GARCH forecasts with robust realized range measures: Evidence from international markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(4), pages 631-658, October.
• Naoya Sueishi & Arihiro Yoshimura, 2017. "Focused Information Criterion for Series Estimation in Partially Linear Models," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 352-363, September.
  • Naoya Sueishi & Arihiro Yoshimura, 2017. "Focused Information Criterion for Series Estimation in Partially Linear Models," The Japanese Economic Review, Springer, vol. 68(3), pages 352-363, September.
  • Naoya Sueishi & Arihiro Yoshimura, 2014. "Focused Information Criterion for Series Estimation in Partially Linear Models," Discussion papers e-14-001, Graduate School of Economics Project Center, Kyoto University.
• Christopher G. Gibbs, 2017. "Forecast combination, non-linear dynamics, and the macroeconomy," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 63(3), pages 653-686, March.
  • Christopher Gibbs, 2015. "Forecast Combination, Non-linear Dynamics, and the Macroeconomy," Discussion Papers 2015-05, School of Economics, The University of New South Wales.
• Cars Hommes & Tomasz Makarewicz & Domenico Massaro & Tom Smits, 2017. "Genetic algorithm learning in a New Keynesian macroeconomic setup," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1133-1155, November.
  • Hommes, C.H. & Makarewicz, T.A. & Massaro, D. & Smits, T., 2015. "Genetic Algorithm Learning in a New Keynesian Macroeconomic Setup," CeNDEF Working Papers 15-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
• Francisco Corona & Graciela González-Farías & Pedro Orraca, 2017. "A dynamic factor model for the Mexican economy: are common trends useful when predicting economic activity?," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 26(1), pages 1-35, December.
• Robert Lehmann & Klaus Wohlrabe, 2017. "Boosting and regional economic forecasting: the case of Germany," Letters in Spatial and Resource Sciences, Springer, vol. 10(2), pages 161-175, July.
  • Lehmann, Robert & Wohlrabe, Klaus, 2015. "The role of component-wise boosting for regional economic forecasting," MPRA Paper 68186, University Library of Munich, Germany, revised 03 Dec 2015.
  • Lehmann, Robert & Wohlrabe, Klaus, 2017. "Boosting and regional economic forecasting: the case of Germany," Munich Reprints in Economics 49919, University of Munich, Department of Economics.
  • Robert Lehmann & Klaus Wohlrabe, 2016. "Boosting and Regional Economic Forecasting: The Case of Germany," CESifo Working Paper Series 6157, CESifo Group Munich.
• Mikael Collan & Jyrki Savolainen & Pasi Luukka, 2017. "Investigating the effect of price process selection on the value of a metal mining asset portfolio," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 30(2), pages 107-115, July.
• Iñaki Bildosola & Pilar Gonzalez & Paz Moral, 2017. "An approach for modelling and forecasting research activity related to an emerging technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 557-572, July.
• Wali Ullah, 2017. "Term structure forecasting in affine framework with time-varying volatility," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(3), pages 453-483, August.
• Bogdan Batrinca & Christian W. Hesse & Philip C. Treleaven, 2017. "Developing a Volume Forecasting Model," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(1), pages 1-1.
• Bing Li, 2017. "Network Evolution of the Chinese Stock Market: A Study based on the CSI 300 Index," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(3), pages 1-5.
• Petrus Strydom, 2017. "Macro economic cycle effect on mortgage and personal loan default rates," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(6), pages 1-1.
• Bogdan Batrinca & Christian W. Hesse & Philip C. Treleaven, 2017. "Developing a Volume Forecasting Model," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 0, pages 1-1.
• Brian Stacey, 2017. "A Standardized Treatment of Binary Similarity Measures with an Introduction to k-Vector Percentage Normalized Similarity," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 6(1), pages 1-3.
  • Stacey, Brian, 2016. "A Standardized Treatment of Binary Similarity Measures with an Introduction to k-Vector Percentage Normalized Similarity," MPRA Paper 72815, University Library of Munich, Germany.
• Christian Brownlees & Robert F. Engle, 2017. "SRISK: A Conditional Capital Shortfall Measure of Systemic Risk," Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 48-79.
  • Brownlees, Christian & Engle, Robert F., 2017. "SRISK: a conditional capital shortfall measure of systemic risk," ESRB Working Paper Series 37, European Systemic Risk Board.
• Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
  • Bucci, Andrea, 2017. "Forecasting realized volatility: a review," MPRA Paper 83232, University Library of Munich, Germany.
• Anthony Mouraud, 2017. "Innovative time series forecasting: auto regressive moving average vs deep networks," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 4(3), pages 282-293, March.
• Rahul Deb & Mallesh M. Pai & Maher Said, 2018. "Evaluating Strategic Forecasters," American Economic Review, American Economic Association, vol. 108(10), pages 3057-3103, October.
  • Rahul Deb & Mallesh Pai & Maher Said, 2017. "Evaluating Strategic Forecasters," Working Papers tecipa-578, University of Toronto, Department of Economics.
  • Rahul Deb & Mallesh M. Pai & Maher Said, 2018. "Evaluating Strategic Forecasters," Working Papers 18-23, New York University, Leonard N. Stern School of Business, Department of Economics.
  • Rahul Deb & Mallesh M. Pai & Maher Said, 2017. "Evaluating Strategic Forecasters," Working Papers 17-02, New York University, Leonard N. Stern School of Business, Department of Economics.
• Christopher G. Gibbs & Andrey L. Vasnev, 2017. "Conditionally Optimal Weights and Forward-Looking Approaches to Combining Forecasts," Discussion Papers 2017-10, School of Economics, The University of New South Wales.
• Rachida Ouysse, 2017. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12, School of Economics, The University of New South Wales.
• R. Lehmann & K. Wohlrabe, 2017. "Experts, firms, consumers or even hard data? Forecasting employment in Germany," Applied Economics Letters, Taylor & Francis Journals, vol. 24(4), pages 279-283, February.
  • Lehmann, Robert & Wohlrabe, Klaus, 2016. "Experts, firms, consumers or even hard data? Forecasting employment in Germany," MPRA Paper 69611, University Library of Munich, Germany.
• Jari Hännikäinen, 2017. "The shadow rate as a predictor of real activity and inflation: evidence from a data-rich environment," Applied Economics Letters, Taylor & Francis Journals, vol. 24(8), pages 527-535, May.
  • Hännikäinen Jari, 2016. "The shadow rate as a predictor of real activity and inflation: Evidence from a data-rich environment," Working Papers 1606, Tampere University, School of Management and Business, Economics.
  • Hännikäinen, Jari, 2016. "The shadow rate as a predictor of real activity and inflation: Evidence from a data-rich environment," MPRA Paper 71432, University Library of Munich, Germany.
• Timo Teräsvirta, 2017. "Sir Clive Granger's contributions to nonlinear time series and econometrics," CREATES Research Papers 2017-04, Department of Economics and Business Economics, Aarhus University.
• Holt, Matthew T. & Teräsvirta, Timo, 2020. "Global hemispheric temperatures and co-shifting: A vector shifting-mean autoregressive analysis," Journal of Econometrics, Elsevier, vol. 214(1), pages 198-215.
  • Matthew T. Holt & Timo Teräsvirta, 2017. "Global Hemispheric Temperatures and Co–Shifting: A Vector Shifting–Mean Autoregressive Analysis," CREATES Research Papers 2017-05, Department of Economics and Business Economics, Aarhus University.
• Wegener, Christoph & Kruse, Robinson & Basse, Tobias, 2019. "The walking debt crisis," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 382-402.
  • Tobias Basse & Robinson Kruse & Christoph Wegener, 2017. "The Walking Debt Crisis," CREATES Research Papers 2017-06, Department of Economics and Business Economics, Aarhus University.
• Oskar Knapik, 2017. "Modeling and forecasting electricity price jumps in the Nord Pool power market," CREATES Research Papers 2017-07, Department of Economics and Business Economics, Aarhus University.
• Malene Kallestrup-Lamb & Carsten P.T. Rosenskjold, 2017. "Insight into the Female Longevity Puzzle: Using Register Data to Analyse Mortality and Cause of Death Behaviour Across Socio-economic Groups," CREATES Research Papers 2017-08, Department of Economics and Business Economics, Aarhus University.
• Daniel Borup & Martin Thyrsgaard, 2017. "Statistical tests for equal predictive ability across multiple forecasting methods," CREATES Research Papers 2017-19, Department of Economics and Business Economics, Aarhus University.
• Tommaso Proietti & Alessandro Giovannelli, 2018. "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, vol. 105(4), pages 783-795.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CEIS Research Paper 410, Tor Vergata University, CEIS, revised 19 Jul 2017.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers 2017-20, Department of Economics and Business Economics, Aarhus University.
• Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Decoupling the short- and long-term behavior of stochastic volatility," CREATES Research Papers 2017-26, Department of Economics and Business Economics, Aarhus University.
• Tommaso Proietti & Niels Haldrup & Oskar Knapik, 2017. "Spikes and memory in (Nord Pool) electricity price spot prices," CEIS Research Paper 422, Tor Vergata University, CEIS, revised 18 Dec 2017.
  • Tommaso Proietti & Niels Haldrup & Oskar Knapik, 2017. "Spikes and memory in (Nord Pool) electricity price spot prices," CREATES Research Papers 2017-39, Department of Economics and Business Economics, Aarhus University.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Mihaela Simionescu & Yuriy Bilan & Grzegorz Mentel, 2017. "Economic Effects of Migration from Poland to the UK," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 19(46), pages 757-757, August.
• Jana Fabianová & Jaroslava Janeková & Daniela Onofrejová, 2017. "Cost Analysis of Poor Quality Using a Software Simulation," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 19(44), pages 181-181, February.
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2011. "Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria," Working Papers 20110301, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," ET: Economic Theory 253725, Fondazione Eni Enrico Mattei (FEEM).
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2018. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Papers 1804.08315, arXiv.org.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Working Papers 2017.06, Fondazione Eni Enrico Mattei.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2016. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," MPRA Paper 76308, University Library of Munich, Germany.
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019. "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, vol. 57(3), pages 923-955, September.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2011. "Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria," Working Papers 20110301, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2018. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Papers 1804.08315, arXiv.org.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," ETA: Economic Theory and Applications 253725, Fondazione Eni Enrico Mattei (FEEM).
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Working Papers 2017.06, Fondazione Eni Enrico Mattei.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2016. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," MPRA Paper 76308, University Library of Munich, Germany.
• Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2018. "A Model of the Fed's View on Inflation," CEPR Discussion Papers 12564, C.E.P.R. Discussion Papers.
  • Thomas Hasenzagl & Fillipo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of the FED's view on inflation," Sciences Po publications 03, Sciences Po.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of FED'S view on inflation," Documents de Travail de l'OFCE 2018-03, Observatoire Francais des Conjonctures Economiques (OFCE).
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," Economic Research Papers 269087, University of Warwick - Department of Economics.
• Nimet Melis Esenyel & Melda Akın, 2017. "Comparing Accuracy Performance of ELM, ARMA and ARMA-GARCH Model In Predicting Exchange Rate Return," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 5(1), pages 1-14, June.
• Tuncay Özcan, 2017. "Application of Seasonal and Multivariable Grey Prediction Models for Short-Term Load Forecasting," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 5(2), pages 329-338, December.
• Jonathan H. Wright, 2017. "Forward-Looking Estimates of Interest-Rate Distributions," Annual Review of Financial Economics, Annual Reviews, vol. 9(1), pages 333-351, November.
• Diego Winkelried & Javier Torres, 2017. "Economic mobility along the business cycle. The case of Peru," Working Papers 2017-115, Peruvian Economic Association.
• Evžen KoÄ enda & Karen Poghosyan, 2018. "Export Sophistication: A Dynamic Panel Data Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(12), pages 2799-2814, September.
  • Karen Poghosyan & Evžen Kočenda, 2016. "Determinants of export sophistication: Evidence from Monte Carlo simulations," Working Papers 360, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).
  • Evzen Kocenda & Karen Poghosyan, 2017. "Export sophistication: A dynamic panel data approach," Working Papers 1, Central Bank of the Republic of Armenia.
  • Evzen Kocenda & Karen Poghosyan, 2017. "Export sophistication: A dynamic panel data approach," KIER Working Papers 980 Classification-C52; C, Kyoto University, Institute of Economic Research.
• Evzen Kocenda & Karen Poghosyan, 2017. "Export sophistication: A dynamic panel data approach," Working Papers 980, Central Bank of the Republic of Armenia.
• Lafond, François & Bailey, Aimee Gotway & Bakker, Jan David & Rebois, Dylan & Zadourian, Rubina & McSharry, Patrick & Farmer, J. Doyne, 2018. "How well do experience curves predict technological progress? A method for making distributional forecasts," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 104-117.
  • Franc{c}ois Lafond & Aimee Gotway Bailey & Jan David Bakker & Dylan Rebois & Rubina Zadourian & Patrick McSharry & J. Doyne Farmer, 2017. "How well do experience curves predict technological progress? A method for making distributional forecasts," Papers 1703.05979, arXiv.org, revised Sep 2017.
• Ormos Mihály & Timotity Dusán, 2017. "The Case of “Less is More”: Modelling Risk-Preference with Expected Downside Risk," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 17(2), pages 1-14, June.
  • Mihaly Ormos & Dusan Timotity, 2017. "The case of 'Less is more': Modelling risk-preference with Expected Downside Risk," Papers 1704.05332, arXiv.org.
• Plakandaras, Vasilios & Gupta, Rangan & Gogas, Periklis & Papadimitriou, Theophilos, 2015. "Forecasting the U.S. real house price index," Economic Modelling, Elsevier, vol. 45(C), pages 259-267.
  • Vasilios Plakandaras & Rangan Gupta & Periklis Gogas & Theophilos Papadimitriou, 2014. "Forecasting the U.S. Real House Price Index," Working Papers 201418, University of Pretoria, Department of Economics.
  • Vasilios Plakandaras & Rangan Gupta & Periklis Gogas & Theophilos Papadimitriou, 2017. "Forecasting the U.S. Real House Price Index," Papers 1707.04868, arXiv.org.
  • Plakandaras, Vasilios & Gupta, Rangan & Papadimitriou, Theophilos & Gogas, Periklis, 2014. "Forecasting the U.S. Real House Price Index," DUTH Research Papers in Economics 10-2014, Democritus University of Thrace, Department of Economics.
  • Vasilios Plakandaras & Rangan Gupta & Periklis Gogas & Theophilos Papadimitriou, 2014. "Forecasting the U.S. Real House Price Index," Working Paper series 30_14, Rimini Centre for Economic Analysis.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Forecasting With Dynamic Panel Data Models," Econometrica, Econometric Society, vol. 88(1), pages 171-201, January.
  • Laura Liu & Hyungsik Moon & Frank Schorfheide, 2016. "Forecasting with Dynamic Panel Data Models," PIER Working Paper Archive 16-022, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 21 Dec 2016.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2017. "Forecasting with Dynamic Panel Data Models," Papers 1709.10193, arXiv.org.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2018. "Forecasting with Dynamic Panel Data Models," NBER Working Papers 25102, National Bureau of Economic Research, Inc.
• Beutner, Eric & Heinemann, Alexander & Smeekes, Stephan, 2017. "A Justification of Conditional Confidence Intervals," Research Memorandum 023, Maastricht University, Graduate School of Business and Economics (GSBE).
  • Eric Beutner & Alexander Heinemann & Stephan Smeekes, 2017. "A Justification of Conditional Confidence Intervals," Papers 1710.00643, arXiv.org, revised Jan 2019.
• Martin Feldkircher & Florian Huber & Gregor Kastner, 2017. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Papers 1711.00564, arXiv.org, revised Nov 2017.
  • Feldkircher, Martin & Huber, Florian & Kastner, Gregor, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Paper Series 260, WU Vienna University of Economics and Business.
  • Martin Feldkircher & Florian Huber & Gregor Kastner, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Papers wuwp260, Vienna University of Economics and Business, Department of Economics.
• Mihaela SIMIONESCU, 2017. "The Efficiency Of Fertilizers And Minimum Tiilage Method In The Agricultural Production In Romania," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 46(2), pages 76-84, June.
• Doina PRODAN-PALADE, 2017. "Bankruptcy risk prediction models based on artificial neural networks," The Audit Financiar journal, Chamber of Financial Auditors of Romania, vol. 15(147), pages 418-418.
• Anastasiia Koliesnichenko, 2017. "Theoretical Aspects Of The Predictional Instrumentation For Application In The State Regulation Of The Participants Relationships In The Electricity Market," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 3(2).
• Papanikolaou, Nikolaos I., 2018. "A dual early warning model of bank distress," Economics Letters, Elsevier, vol. 162(C), pages 127-130.
  • Nikolaos I. Papanikolaou, 2017. "A Dual Early Warning Model of Bank Distress," BAFES Working Papers BAFES11, Department of Accounting, Finance & Economic, Bournemouth University.
• Papanikolaou, Nikolaos I., 2018. "To be bailed out or to be left to fail? A dynamic competing risks hazard analysis," Journal of Financial Stability, Elsevier, vol. 34(C), pages 61-85.
  • Nikolaos I. Papanikolaou, 2017. "To Be Bailed Out or To Be Left to Fail? A Dynamic Competing Risks Hazard Analysis," BAFES Working Papers BAFES12, Department of Accounting, Finance & Economic, Bournemouth University.
• Lidiya Guryanova & Tamara Klebanova & Tetiana Trunova, 2017. "Modeling the Financial Strategy of the Enterprise in an Unstable Environment," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 91-109.
• Lise Pichette & Marie-Noëlle Robitaille, 2017. "Assessing the Business Outlook Survey Indicator Using Real-Time Data," Discussion Papers 17-5, Bank of Canada.
• David Xiao Chen & Philippe Muller & Hawa Wagué, 2017. "Multilateral Development Bank Credit Rating Methodology: Overcoming the Challenges in Assessing Relative Credit Risk in Highly Rated Institutions Based on Public Data," Discussion Papers 17-6, Bank of Canada.
• Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
• Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2020. "Markov-Switching Three-Pass Regression Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 285-302, April.
  • Pierre Guerin & Danilo Leiva-Leon & Massimiliano Marcellino, 2016. "Markov-Switching Three-Pass Regression Filter," Working Papers 591, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  • Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-Switching Three-Pass Regression Filter," Staff Working Papers 17-13, Bank of Canada.
  • Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-switching three-pass regression filter," Working Papers 1748, Banco de España;Working Papers Homepage.
• Foroni, Claudia & Ravazzolo, Francesco & Sadaba, Barbara, 2018. "Assessing the predictive ability of sovereign default risk on exchange rate returns," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 242-264.
  • Claudia Foroni & Francesco Ravazzolo & Barbara Sadaba, 2017. "Assessing the Predictive Ability of Sovereign Default Risk on Exchange Rate Returns," Staff Working Papers 17-19, Bank of Canada.
• Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
  • Tony Chernis & Rodrigo Sekkel, 2017. "A Dynamic Factor Model for Nowcasting Canadian GDP Growth," Staff Working Papers 17-2, Bank of Canada.
• Reinhard Ellwanger, 2017. "On the Tail Risk Premium in the Oil Market," Staff Working Papers 17-46, Bank of Canada.
• Pinar KAYA & Bulent GULOGLU, 2017. "Modeling and Forecasting the Markets Volatility and VaR Dynamics of Commodity," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 11(1), pages 9-49.
• Luis J. Álvarez & Isabel Sánchez, 2017. "A suite of inflation forecasting models," Occasional Papers 1703, Banco de España;Occasional Papers Homepage.
• Guérin, Pierre & Leiva-Leon, Danilo, 2017. "Model averaging in Markov-switching models: Predicting national recessions with regional data," Economics Letters, Elsevier, vol. 157(C), pages 45-49.
  • Guérin, Pierre & Leiva-Leon, Danilo, 2014. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," MPRA Paper 59361, University Library of Munich, Germany.
  • Pierre Guérin & Danilo Leiva-Leon, 2017. "Model averaging in markov-switching models: predicting national recessions with regional data," Working Papers 1727, Banco de España;Working Papers Homepage.
  • Pierre Guérin & Danilo Leiva-Leon, 2015. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," Staff Working Papers 15-24, Bank of Canada.
• Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2020. "Markov-Switching Three-Pass Regression Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 285-302, April.
  • Pierre Guerin & Danilo Leiva-Leon & Massimiliano Marcellino, 2016. "Markov-Switching Three-Pass Regression Filter," Working Papers 591, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  • Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-switching three-pass regression filter," Working Papers 1748, Banco de España;Working Papers Homepage.
  • Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-Switching Three-Pass Regression Filter," Staff Working Papers 17-13, Bank of Canada.
• Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España;Working Papers Homepage.
• Valentina Aprigliano & Guerino Ardizzi & Libero Monteforte, 2017. "Using the payment system data to forecast the Italian GDP," Temi di discussione (Economic working papers) 1098, Bank of Italy, Economic Research and International Relations Area.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.
  • Kapetanios, George & Marcellino, Massimiliano & Venditti, Fabrizio, 2016. "Large Time-Varying Parameter VARs: A Non-Parametric Approach," CEPR Discussion Papers 11560, C.E.P.R. Discussion Papers.
  • George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
• Raul Ibarra & Luis M. Gomez-Zamudio, 2017. "Are Daily Financial Data Useful for Forecasting GDP? Evidence from Mexico," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 173-203, April.
  • Gómez-Zamudio Luis M. & Ibarra-Ramírez Raúl, 2017. "Are daily financial data useful for forecasting GDP? Evidence from Mexico," Working Papers 2017-17, Banco de México.
• Juan Manuel Julio & Javier Guillermo Gómez & Manuel Dario Hernández, 2017. "La Inflación de los Precios Rígidos en Colombia," Borradores de Economia 1007, Banco de la Republica de Colombia.
• Muhammad Shahzad Ijaz & Ahmed Imran Hunjra & Rauf I Azam, 2017. "Forewarning Bankruptcy: An Indigenous Model for Pakistan," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 9(4), pages 259-286, December.
• L. De Charsonville & F. Ferrière & C. Jardet, 2017. "MAPI: Model for Analysis and Projection of Inflation in France," Working papers 637, Banque de France.
• Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2017. "Common factors of commodity prices," Working Paper Series 2112, European Central Bank.
  • S. Delle Chiaie & L. Ferrara & D. Giannone, 2017. "Common Factors of Commodity Prices," Working papers 645, Banque de France.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common Factors of Commodity Prices," CEPR Discussion Papers 12767, C.E.P.R. Discussion Papers.
• Benjamin Beckers & Konstantin A. Kholodilin & Dirk Ulbricht, 2017. "Reading between the Lines: Using Media to Improve German Inflation Forecasts," Discussion Papers of DIW Berlin 1665, DIW Berlin, German Institute for Economic Research.
• Roy Verbaan & Wilko Bolt & Carin van der Cruijsen, 2017. "Using debit card payments data for nowcasting Dutch household consumption," DNB Working Papers 571, Netherlands Central Bank, Research Department.
• Chevillon, Guillaume, 2017. "Robustness of Multistep Forecasts and Predictive Regressions at Intermediate and Long Horizons," ESSEC Working Papers WP1710, ESSEC Research Center, ESSEC Business School.
• Strasser, Georg, 2017. "What determines the impact of macroeconomic news on asset markets?," Research Bulletin, European Central Bank, vol. 37.
• Sousa, João & Falagiarda, Matteo, 2017. "Forecasting euro area inflation using targeted predictors: is money coming back?," Working Paper Series 2015, European Central Bank.
• Sarlin, Peter & von Schweinitz, Gregor, 2015. "Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?," IWH Discussion Papers 6/2015, Halle Institute for Economic Research (IWH).
  • Sarlin, Peter & von Schweinitz, Gregor, 2017. "Optimizing policymakers' loss functions in crisis prediction: before, within or after?," Working Paper Series 2025, European Central Bank.
• Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
  • S. Delle Chiaie & L. Ferrara & D. Giannone, 2017. "Common Factors of Commodity Prices," Working papers 645, Banque de France.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common Factors of Commodity Prices," CEPR Discussion Papers 12767, C.E.P.R. Discussion Papers.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2017. "Common factors of commodity prices," Working Paper Series 2112, European Central Bank.
• Maryam Hosseinzadeh & Saeed Daei-Karimzadeh, 2017. "Investigate the Effect of Exchange Rate Volatility on the Demand for Life Insurance in Iran," International Journal of Economics and Financial Issues, Econjournals, vol. 7(2), pages 166-174.
• Khalil Abbasi Museloo & Shaker Abartavi, 2017. "Incorrect Pricing Impact on Investment and the Capital Structure of Companies with Financial Constraints," International Journal of Economics and Financial Issues, Econjournals, vol. 7(2), pages 319-324.
• Mehdi Behrad-Amin & Gholamreza Zamanian & Marzie Esfandiari, 2017. "The Effect of Oil Shocks on Foreign Trade under Inflation and Exchange Rate Targeting Policies (In the Form of a Dynamic Stochastic General Equilibrium Model for Iran)," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 342-351.
• Abbas Taleb Bidokhti & Ali Akbar Esmailpour, 2017. "Examining the Effect of Social and Intellectual Value on Organizational Performance Based on the Balanced Evaluation Method and Structural Equations in the Iranian Oil Terminals Company," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 404-410.
• Ghazi Al-Assaf, 2017. "An Early Warning System for Currency Crisis: A Comparative Study for the Case of Jordan and Egypt," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 43-50.
• Shahram Fattahi & Kiomars Sohaili & Hamed Monkaresi & Fatemeh Mehrabi, 2017. "Modelling and Forecasting Recessions in Oil-exporting Countries: The Case of Iran," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 569-574.
• Morteza Doosti Seyyed Shekari & Babak Jamshidinavid, 2017. "Study of Information Asymmetry Effect on Price Synchronism in Tehran Stock Exchange," International Journal of Economics and Financial Issues, Econjournals, vol. 7(4), pages 343-346.
• Daniel Toth & Lenka Kucírková, 2017. "Macroeconomic Prognosis of Employment in the Czech Republic," International Journal of Economics and Financial Issues, Econjournals, vol. 7(4), pages 730-736.
• Songul Cinaroglu, 2017. "A Fresh Look at Out-of-Pocket Health Expenditures after More than a Decade Health Reform Experience in Turkey: A Data Mining Application," International Journal of Economics and Financial Issues, Econjournals, vol. 7(5), pages 33-40.
• Lana V. L. Costa-Silva & Vinicio S. Almeida & Felipe M. Pimenta & Giovanna T. Segantini, 2017. "Time Span does Matter for Offshore Wind Plant Allocation with Modern Portfolio Theory," International Journal of Energy Economics and Policy, Econjournals, vol. 7(3), pages 188-193.
• Hassan Mehrmanesh & Seyed Rahim Safavi Mirmahalleh, 2017. "Examining the Relationship between Supply Chain Relationships and Practice of Distributors (Case Study: NoshinCo)," International Review of Management and Marketing, Econjournals, vol. 7(2), pages 67-70.
• Neda Sharifi Asadi Malafe & Masoud Ahmadi & Fahime Baei, 2017. "The Relationship between Demographic Characteristics with Information and Communication Technology and Empowerment in General Organizations (Case Study: Sari Municipality)," International Review of Management and Marketing, Econjournals, vol. 7(2), pages 71-75.
• Rasool Sarihi Asfestani & Mehraban Hadi Peykani & Akbar Eetebaryan, 2017. "Design and Presentation of Professional Ethics Criteria and Indicators for the Promotion of Political Accountability within Iranian’s Government Organizations (Case Study: National Chief Executive Dev," International Review of Management and Marketing, Econjournals, vol. 7(2), pages 226-232.
• Hassan Mehrmanesh & Seyed Rahim Safavi Mirmahalleh, 2017. "Studying the Relationship among Character, Phantasm and Environment with Customers’ Loyalty in Iran’s Hotel Industry (Case Study: Hotels of Ardabil)," International Review of Management and Marketing, Econjournals, vol. 7(2), pages 233-236.
• Mahdi Rezapour & Mehraban Hadi Peykani, 2017. "Compare Customer Satisfaction with the Quality of E-banking Services among State, Private and Altered Banks in Isfahan," International Review of Management and Marketing, Econjournals, vol. 7(2), pages 237-243.
• Fahime Baei & Masoud Ahmadi & Neda Sharifi Asadi Malafeh & Abbasali Baee, 2017. "The Relationship between Manager’s Strategic Intelligence and Organization Development in Governmental Agencies in Iran (Case Study: Office of Cooperatives Labor and Social Welfare)," International Review of Management and Marketing, Econjournals, vol. 7(2), pages 244-249.
• Azade Aryana & Reza Ameri Siyahouei & Tahereh Mahmoudi, 2017. "Investigating the Relationship between Employee Empowerment and the Development of an Entrepreneurial Culture at Fatemieh Technical and Vocational University of Bandar Abbas," International Review of Management and Marketing, Econjournals, vol. 7(2), pages 250-255.
• Cantore, Cristiano & Ferroni, Filippo & León-Ledesma, Miguel A., 2017. "The dynamics of hours worked and technology," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 67-82.
  • Cristiano Cantore & Filippo Ferroni & Miguel A. León-Ledesma, 2012. "The dynamics of hours worked and technology," Working Papers 1238, Banco de España;Working Papers Homepage.
• Wei, Yu & Cao, Yang, 2017. "Forecasting house prices using dynamic model averaging approach: Evidence from China," Economic Modelling, Elsevier, vol. 61(C), pages 147-155.
• Paret, Anne-Charlotte, 2017. "Debt sustainability in emerging market countries: Some policy guidelines from a fan-chart approach," Economic Modelling, Elsevier, vol. 63(C), pages 26-45.
  • Anne-Charlotte Paret, 2017. "Debt sustainability in emerging market countries: Some policy guidelines from a fan-chart approach," Post-Print hal-01590005, HAL.
• Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
  • Mogliani, M. & Brunhes-Lesage, V. & Darné, O. & Pluyaud, B., 2014. "New estimate of the MIBA forecasting model. Modeling first-release GDP using the Banque de France's Monthly Business Survey and the “blocking” approach," Working papers 473, Banque de France.
• Doumpos, Michael & Hasan, Iftekhar & Pasiouras, Fotios, 2017. "Bank overall financial strength: Islamic versus conventional banks," Economic Modelling, Elsevier, vol. 64(C), pages 513-523.
• Jiang, Yu & Guo, Yongji & Zhang, Yihao, 2017. "Forecasting China's GDP growth using dynamic factors and mixed-frequency data," Economic Modelling, Elsevier, vol. 66(C), pages 132-138.
• Pop, Raluca-Elena, 2017. "A small-scale DSGE-VAR model for the Romanian economy," Economic Modelling, Elsevier, vol. 67(C), pages 1-9.
• Siliverstovs, Boriss, 2017. "Dissecting models' forecasting performance," Economic Modelling, Elsevier, vol. 67(C), pages 294-299.
  • Boriss Siliverstovs, 2015. "Dissecting Models' Forecasting Performance," KOF Working papers 15-397, KOF Swiss Economic Institute, ETH Zurich.
• Zhang, Heng-Guo & Su, Chi-Wei & Song, Yan & Qiu, Shuqi & Xiao, Ran & Su, Fei, 2017. "Calculating Value-at-Risk for high-dimensional time series using a nonlinear random mapping model," Economic Modelling, Elsevier, vol. 67(C), pages 355-367.
• Chen, Cathy W.S. & Wang, Zona & Sriboonchitta, Songsak & Lee, Sangyeol, 2017. "Pair trading based on quantile forecasting of smooth transition GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 38-55.
• Li, Leon, 2017. "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 116-135.
• Jung, Alexander, 2017. "Forecasting broad money velocity," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 421-432.
• Ng, Kok Haur & Peiris, Shelton & Chan, Jennifer So-kuen & Allen, David & Ng, Kooi Huat, 2017. "Efficient modelling and forecasting with range based volatility models and its application," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 448-460.
• Ñíguez, Trino-Manuel & Perote, Javier, 2017. "Moments expansion densities for quantifying financial risk," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 53-69.
• Xie, Tian, 2017. "Heteroscedasticity-robust model screening: A useful toolkit for model averaging in big data analytics," Economics Letters, Elsevier, vol. 151(C), pages 119-122.
• Bürgi, Constantin, 2017. "Bias, rationality and asymmetric loss functions," Economics Letters, Elsevier, vol. 154(C), pages 113-116.
• Guérin, Pierre & Leiva-Leon, Danilo, 2017. "Model averaging in Markov-switching models: Predicting national recessions with regional data," Economics Letters, Elsevier, vol. 157(C), pages 45-49.
  • Guérin, Pierre & Leiva-Leon, Danilo, 2014. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," MPRA Paper 59361, University Library of Munich, Germany.
  • Pierre Guérin & Danilo Leiva-Leon, 2017. "Model averaging in markov-switching models: predicting national recessions with regional data," Working Papers 1727, Banco de España;Working Papers Homepage.
  • Pierre Guérin & Danilo Leiva-Leon, 2015. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," Staff Working Papers 15-24, Bank of Canada.
• Fosten, Jack, 2017. "Confidence intervals in regressions with estimated factors and idiosyncratic components," Economics Letters, Elsevier, vol. 157(C), pages 71-74.
• Zhang, Keyi & Gençay, Ramazan & Ege Yazgan, M., 2017. "Application of wavelet decomposition in time-series forecasting," Economics Letters, Elsevier, vol. 158(C), pages 41-46.
• Sensoy, Ahmet & Fabozzi, Frank J. & Eraslan, Veysel, 2017. "Predictability dynamics of emerging sovereign CDS markets," Economics Letters, Elsevier, vol. 161(C), pages 5-9.
• Colin O’hare & Youwei Li, 2017. "Modelling mortality: are we heading in the right direction?," Applied Economics, Taylor & Francis Journals, vol. 49(2), pages 170-187, January.
  • O'Hare, Colin & Li, Youwei, 2016. "Modelling mortality: Are we heading in the right direction?," MPRA Paper 71392, University Library of Munich, Germany.
• Stavros Degiannakis & George Filis & George Palaiodimos, 2017. "Investments and uncertainty revisited: the case of the US economy," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4521-4529, September.
  • Degiannakis, Stavros & Filis, George & Palaiodimos, George, 2015. "Investments and uncertainty revisited: The case of the US economy," MPRA Paper 72083, University Library of Munich, Germany.
• Mardi Dungey & Jan P.A.M. Jacobs & Jing Tian, 2017. "Forecasting output gaps in the G-7 countries: the role of correlated innovations and structural breaks," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4554-4566, September.
  • Dungey, Mardi & Jacobs, Jan P.A.M. & Tian, Jing, 2016. "Forecasting output gaps in the G-7 countries: The role of correlated Innovations and structural breaks," Working Papers 2016-04, University of Tasmania, Tasmanian School of Business and Economics.
• Philip Hans Franses & Rianne Legerstee & Richard Paap, 2017. "Estimating loss functions of experts," Applied Economics, Taylor & Francis Journals, vol. 49(4), pages 386-396, January.
  • Franses, Ph.H.B.F. & Legerstee, R. & Paap, R., 2011. "Estimating Loss Functions of Experts," Econometric Institute Research Papers EI2011-42, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Philip Hans Franses & Rianne Legerstee & Richard Paap, 2011. "Estimating Loss Functions of Experts," Tinbergen Institute Discussion Papers 11-177/4, Tinbergen Institute.
• Colin O’hare & Youwei Li, 2017. "Models of mortality rates – analysing the residuals," Applied Economics, Taylor & Francis Journals, vol. 49(52), pages 5309-5323, November.
• Francis X. Diebold & Minchul Shin, 2017. "Assessing point forecast accuracy by stochastic error distance," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 588-598, October.
  • Francis X. Diebold & Minchul Shin, 2014. "Assessing Point Forecast Accuracy by Stochastic Error Distance," PIER Working Paper Archive 14-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Francis X. Diebold & Minchul Shin, 2016. "Assessing Point Forecast Accuracy by Stochastic Error Distance," NBER Working Papers 22516, National Bureau of Economic Research, Inc.
• Manabu Asai & Michael McAleer, 2017. "The impact of jumps and leverage in forecasting covolatility," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 638-650, October.
  • Manabu Asai & Michael McAleer, 2015. "The Impact of Jumps and Leverage in Forecasting Co-Volatility," Documentos de Trabajo del ICAE 2015-02, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Manabu Asai & Michael McAleer, 2015. "The Impact of Jumps and Leverage in Forecasting Co-Volatility," Tinbergen Institute Discussion Papers 15-018/III, Tinbergen Institute.
  • Asai, M. & McAleer, M.J., 2015. "The Impact of Jumps and Leverage in Forecasting Co-Volatility," Econometric Institute Research Papers EI 2015-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Sotirios Bersimis & Stavros Degiannakis & Dimitrios Georgakellos, 2017. "Real-time monitoring of carbon monoxide using value-at-risk measure and control charting," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 89-108, January.
  • Bersimis, Sotirios & Degiannakis, Stavros & Georgakellos, Dimitrios, 2015. "Real Time Monitoring of Carbon Monoxide Using Value-at-Risk Measure and Control Charting," MPRA Paper 65865, University Library of Munich, Germany.
• Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2017. "Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 110-129, January.
  • Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2013. "Macroeconomic factors strike back: A Bayesian change-point model of time-varying risk exposures and premia in the U.S. cross-section," Working Paper 2013/19, Norges Bank.
  • Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2015. "Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section," Working Papers 550, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
• Joshua C. C. Chan, 2017. "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
  • Joshua C.C. Chan, 2015. "The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling," CAMA Working Papers 2015-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017. "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 162-182, April.
  • Bauwens, Luc & Carpantier, Jean-François & Dufays, Arnaud, 2015. "Autoregressive moving average infinite hidden markov-switching models," CORE Discussion Papers 2015007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Luc BAUWENS & Jean-François CARPENTIER & Arnaud DUFAYS, 2017. "Autoregressive moving average infinite hidden Markov-switching models," CORE Discussion Papers RP 2836, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017. "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Post-Print hal-01795051, HAL.
• Davide Pettenuzzo & Allan Timmermann, 2017. "Forecasting Macroeconomic Variables Under Model Instability," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 183-201, April.
  • Pettenuzzo, Davide & Timmermann, Allan G, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
• Michael P. Clements, 2017. "Assessing Macro Uncertainty in Real-Time When Data Are Subject To Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 420-433, July.
  • Michael P. Clements, 2015. "Assessing Macro Uncertainty In Real-Time When Data Are Subject To Revision," ICMA Centre Discussion Papers in Finance icma-dp2015-02, Henley Business School, Reading University.
• Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017. "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 470-485, July.
  • Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers No 8/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Krüger, Fabian & Clark, Todd E. & Ravazzolo, Francesco, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113077, Verein für Socialpolitik / German Economic Association.
  • Todd E. Clark & Fabian Krueger & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers (Old Series) 1439, Federal Reserve Bank of Cleveland, revised 07 Jan 2015.
• Christian Menden & Christian R. Proaño, 2017. "Dissecting the financial cycle with dynamic factor models," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1965-1994, December.
  • Christian Menden & Christian R. Proaño, 2017. "Dissecting the financial cycle with dynamic factor models," IMK Working Paper 183-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
• G. Demos & D. Sornette, 2017. "Birth or burst of financial bubbles: which one is easier to diagnose?," Quantitative Finance, Taylor & Francis Journals, vol. 17(5), pages 657-675, May.
  • Guilherme DEMOS & Qunzhi ZHANG & Didier SORNETTE, 2015. "Birth or Burst of Financial Bubbles: Which One is Easier to Diagnose?," Swiss Finance Institute Research Paper Series 15-57, Swiss Finance Institute.
• V. Filimonov & G. Demos & D. Sornette, 2017. "Modified profile likelihood inference and interval forecast of the burst of financial bubbles," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1167-1186, August.
  • Vladimir Filimonov & Guilherme Demos & Didier Sornette, 2016. "Modified Profile Likelihood Inference and Interval Forecast of the Burst of Financial Bubbles," Papers 1602.08258, arXiv.org.
  • Vladimir Filimonov & Guilherme Demos & Didier Sornette, 2016. "Modified Profile Likelihood Inference and Interval Forecast of the Burst of Financial Bubbles," Swiss Finance Institute Research Paper Series 16-12, Swiss Finance Institute.
• Goodwin, Thomas & Tian, Jing, 2017. "A state space approach to evaluate multi-horizon forecasts," Working Papers 2017-15, University of Tasmania, Tasmanian School of Business and Economics.
• Kurmas Akdogan, 2017. "Mean-Reversion in Unprocessed Food Prices," Working Papers 1703, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Ferhat Camlica & Didem Gunes & Etkin Ozen, 2017. "A Financial Connectedness Analysis for Turkey," Working Papers 1719, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(11), pages 1141-1152, November.
  • Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Documentos de Trabajo del ICAE 2017-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Manabu Asai & Michael McAleer, 2017. "Forecasting the Volatility of Nikkei 225 Futures," Tinbergen Institute Discussion Papers 17-017/III, Tinbergen Institute.
  • Asai, M. & McAleer, M.J., 2017. "Forecasting the Volatility of Nikkei 225 Futures," Econometric Institute Research Papers TI 2017-017/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Tom Boot & Andreas Pick, 2017. "A near optimal test for structural breaks when forecasting under square error loss," Tinbergen Institute Discussion Papers 17-039/III, Tinbergen Institute.
• Carlos León & José Fernando Moreno & Jorge Cely, 2016. "Whose Balance Sheet is this? Neural Networks for Banks’ Pattern Recognition," Borradores de Economia 959, Banco de la Republica de Colombia.
  • Leon Rincon, Carlos & Moreno, José Fernando & Cely, Jorge, 2017. "Whose Balance Sheet is this? Neural Networks for Banks' Pattern Recognition," Discussion Paper 2017-009, Tilburg University, Center for Economic Research.
• Steven Lehrer & Tian Xie, 2017. "Box Office Buzz: Does Social Media Data Steal the Show from Model Uncertainty When Forecasting for Hollywood?," The Review of Economics and Statistics, MIT Press, vol. 99(5), pages 749-755, December.
  • Steven Lehrer & Tian Xie, 2016. "Box Office Buzz: Does Social Media Data Steal the Show from Model Uncertainty When Forecasting for Hollywood?," NBER Working Papers 22959, National Bureau of Economic Research, Inc.
• Gianni Amisano & John Geweke, 2017. "Prediction Using Several Macroeconomic Models," The Review of Economics and Statistics, MIT Press, vol. 99(5), pages 912-925, December.
  • Amisano, Gianni & Geweke, John, 2013. "Prediction using several macroeconomic models," Working Paper Series 1537, European Central Bank.
• Victor De Oliveira, 2017. "Geostatistical Binary Data: Models, Properties And Connections," Working Papers 0151mss, College of Business, University of Texas at San Antonio.
• Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(11), pages 1141-1152, November.
  • Manabu Asai & Michael McAleer, 2017. "Forecasting the Volatility of Nikkei 225 Futures," Tinbergen Institute Discussion Papers 17-017/III, Tinbergen Institute.
  • Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Documentos de Trabajo del ICAE 2017-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Asai, M. & McAleer, M.J., 2017. "Forecasting the Volatility of Nikkei 225 Futures," Econometric Institute Research Papers TI 2017-017/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Roberta Cardani & Alessia Paccagnini & Stelios D. Bekiros, 2017. "The Effectiveness of Forward Guidance in an Estimated DSGE Model for the Euro Area: the Role of Expectations," Working Papers 201701, School of Economics, University College Dublin.
• Michael Spagat & Neil Johnson & Stijn van Weezel, 2017. "David Versus Goliath: Fundamental Patterns and Predictions in Modern Wars and Terrorist Campaigns," Working Papers 201721, School of Economics, University College Dublin.
• Umi Mahmudah, 2017. "Predicting unemployment rates in Indonesia," Economic Journal of Emerging Markets, Universitas Islam Indonesia, Department of Economics, vol. 9(1), pages 20-28, April.
• Anton Grui & Roman Lysenko, 2017. "Nowcasting Ukraine's GDP Using a Factor-Augmented VAR (FAVAR) Model," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 242, pages 5-13.
• Teresa de J. Vargas Vega & Zeus S. Hernández Veleros & Eleazar Villegas González, 2017. "Economic growth and financial development: Evidence from three countries in North America," Economía, Instituto de Investigaciones Económicas y Sociales (IIES). Facultad de Ciencias Económicas y Sociales. Universidad de Los Andes. Mérida, Venezuela, vol. 42(43), pages 11-50, January-j.
• Lorenzo Ricci, 2017. "Essays on tail risk in macroeconomics and finance: measurement and forecasting," ULB Institutional Repository 2013/242122, ULB -- Universite Libre de Bruxelles.
• Eric Beutner & Alexander Heinemann & Stephan Smeekes, 2017. "A Justification of Conditional Confidence Intervals," Papers 1710.00643, arXiv.org, revised Jan 2019.
  • Beutner, Eric & Heinemann, Alexander & Smeekes, Stephan, 2017. "A Justification of Conditional Confidence Intervals," Research Memorandum 023, Maastricht University, Graduate School of Business and Economics (GSBE).
• A. Ason Okoruwa, 2017. "Regression Analysis of Property Productivity Index and Value," The Valuation Journal, National Association of Romanian Valuers, vol. 12(1), pages 58-93.
• Chlebus Marcin, 2017. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Central European Economic Journal, Sciendo, vol. 3(50), pages 01-25, December.
  • Marcin Chlebus, 2016. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Working Papers 2016-06, Faculty of Economic Sciences, University of Warsaw.
• Popescu Mioara, 2017. "Modelling prediction of unemployment statistics using web technologies," HOLISTICA – Journal of Business and Public Administration, Sciendo, vol. 8(3), pages 55-60, December.
• Mateusz Buczyński & Marcin Chlebus, 2017. "Is CAViaR model really so good in Value at Risk forecasting? Evidence from evaluation of a quality of Value-at-Risk forecasts obtained based on the: GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH(," Working Papers 2017-29, Faculty of Economic Sciences, University of Warsaw.
• McKenzie, David J. & Sansone, Dario, 2017. "Man vs. Machine in Predicting Successful Entrepreneurs: Evidence from a Business Plan Competition in Nigeria," CEPR Discussion Papers 12523, C.E.P.R. Discussion Papers.
  • Mckenzie,David J. & Sansone,Dario & Mckenzie,David J. & Sansone,Dario, 2017. "Man vs. machine in predicting successful entrepreneurs : evidence from a business plan competition in Nigeria," Policy Research Working Paper Series 8271, The World Bank.
• Christian Glocker & Philipp Wegmueller, 2020. "Business cycle dating and forecasting with real-time Swiss GDP data," Empirical Economics, Springer, vol. 58(1), pages 73-105, January.
  • Christian Glocker & Philipp Wegmüller, 2017. "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers 542, WIFO.
• Huber, Florian & Zörner, Thomas, 2017. "Threshold cointegration and adaptive shrinkage," Department of Economics Working Paper Series 250, WU Vienna University of Economics and Business.
  • Florian Huber & Thomas Zörner, 2017. "Threshold cointegration and adaptive shrinkage," Department of Economics Working Papers wuwp250, Vienna University of Economics and Business, Department of Economics.
• Florian Huber & Thomas Zörner, 2017. "Threshold cointegration and adaptive shrinkage," Department of Economics Working Papers wuwp250, Vienna University of Economics and Business, Department of Economics.
  • Huber, Florian & Zörner, Thomas, 2017. "Threshold cointegration and adaptive shrinkage," Department of Economics Working Paper Series 250, WU Vienna University of Economics and Business.
• Bruno Lanz & Simon Dietz & Timothy Swanson, 2017. "Global Population Growth, Technology, And Malthusian Constraints: A Quantitative Growth Theoretic Perspective," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58, pages 973-1006, August.
  • Bruno Lanz & Simon Dietz & Tim Swanson, 2014. "Global Population Growth, Technology and Malthusian Constraints: A Quantitative Growth Theoretic Perspective," CIES Research Paper series 25-2014, Centre for International Environmental Studies, The Graduate Institute, revised 01 May 2016.
  • Lanz, Bruno & Dietz, Simon & Swanson, Tim, 2017. "Global population growth, technology and Malthusian constraints: a quantitative growth theoretic perspective," LSE Research Online Documents on Economics 66496, London School of Economics and Political Science, LSE Library.
  • Bruno Lanz & Simon Dietz & Tim Swanson, 2016. "Global Population Growth, Technology and Malthusian Constraints: A Quantitative Growth Theoretic Perspective," IHEID Working Papers 04-2016, Economics Section, The Graduate Institute of International Studies, revised 18 May 2016.
  • Bruno Lanz & Simon Dietz & Tim Swanson, 2015. "Global Population Growth, Technology, and Malthusian Constraints: A Quantitative Growth Theoretic Perspective," EcoMod2015 8380, EcoMod.
  • Bruno Lanz & Simon Dietz & Tim Swanson, 2016. "Global population growth, technology and Malthusian constraints: A quantitative growth theoretic perspective," IRENE Working Papers 16-05, IRENE Institute of Economic Research.
  • Bruno Lanz & Simon Diet & Tim Swanson, 2014. "Global population growth, technology, and Malthusian constraints: a quantitative growth theoretic perspective," GRI Working Papers 161, Grantham Research Institute on Climate Change and the Environment.
• Anders Warne & Günter Coenen & Kai Christoffel, 2017. "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 103-119, January.
  • Warne, Anders & Coenen, Günter & Christoffel, Kai, 2014. "Marginalized predictive likelihood comparisons of linear Gaussian state-space models with applications to DSGE, DSGEVAR, and VAR models," CFS Working Paper Series 478, Center for Financial Studies (CFS).
• Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
  • Kole, H.J.W.G. & van Dijk, D.J.C., 2013. "How to Identify and Forecast Bull and Bear Markets?," ERIM Report Series Research in Management ERS-2013-016-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
• Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2017. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 275-295, March.
  • Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K, 2015. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," CEPR Discussion Papers 10362, C.E.P.R. Discussion Papers.
  • Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2015. "Inside the crystal ball: New approaches to predicting the gasoline price at the pump," CFS Working Paper Series 500, Center for Financial Studies (CFS).
• Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2017. "Euromind‐ D : A Density Estimate of Monthly Gross Domestic Product for the Euro Area," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 683-703, April.
  • Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CREATES Research Papers 2015-12, Department of Economics and Business Economics, Aarhus University.
  • Proietti, Tommaso & Marczak, Martyna & Mazzi, Gianluigi, 2015. "EuroMInd-D: A density estimate of monthly gross domestic product for the euro area," Hohenheim Discussion Papers in Business, Economics and Social Sciences 03-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
  • Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CEIS Research Paper 340, Tor Vergata University, CEIS, revised 10 Apr 2015.
• Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
  • Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
  • Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Papers No 3/2014, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2017. "Have Standard VARS Remained Stable Since the Crisis?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 931-951, August.
  • Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2014. "Have standard VARs remained stable since the crisis?," Working Paper 2014/13, Norges Bank.
  • Aastveit, Knut Are & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2016. "Have Standard VARs Remained Stable Since the Crisis?," CEPR Discussion Papers 11558, C.E.P.R. Discussion Papers.
  • Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2014. "Have Standard VARs Remained Stable since the Crisis?," Working Papers (Old Series) 1411, Federal Reserve Bank of Cleveland, revised 18 Sep 2014.
• Jack Fosten, 2017. "Model selection with estimated factors and idiosyncratic components," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1087-1106, September.
  • Jack Fosten, 2016. "Model selection with factors and variables," University of East Anglia School of Economics Working Paper Series 2016-07, School of Economics, University of East Anglia, Norwich, UK..
• Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017. "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 109-121, March.
  • Periklis Gogas & Theophilos Papadimitriou & Vasilios Plakandaras & Rangan Gupta, 2015. "The Informational Content of the Term-Spread in Forecasting the U.S. Inflation Rate: A Nonlinear Approach," Working Papers 201548, University of Pretoria, Department of Economics.
  • Gogas, Periklis & Papadimitriou, Theophilos & Plakandaras, Vasilios & Gupta, Rangan, 2019. "The Informational Content of the Term-Spread in Forecasting the U.S. Inflation Rate: A Nonlinear Approach," DUTH Research Papers in Economics 3-2016, Democritus University of Thrace, Department of Economics.
• Dirk Ulbricht & Konstantin A. Kholodilin & Tobias Thomas, 2017. "Do Media Data Help to Predict German Industrial Production?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 483-496, August.
  • Konstantin A. Kholodilin & Tobias Thomas & Dirk Ulbricht, 2014. "Do Media Data Help to Predict German Industrial Production?," Discussion Papers of DIW Berlin 1393, DIW Berlin, German Institute for Economic Research.
  • Kholodilin, Konstantin A. & Thomas, Tobias & Ulbricht, Dirk, 2014. "Do media data help to predict German industrial production?," DICE Discussion Papers 149, University of Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
• Kirstin Hubrich & Frauke Skudelny, 2017. "Forecast Combination for Euro Area Inflation: A Cure in Times of Crisis?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 515-540, August.
  • Kirstin Hubrich & Frauke Skudelny, 2016. "Forecast Combination for Euro Area Inflation - A Cure in Times of Crisis?," Finance and Economics Discussion Series 2016-104, Board of Governors of the Federal Reserve System (U.S.).
  • Hubrich, Kirstin & Skudelny, Frauke, 2016. "Forecast combination for euro area inflation: a cure in times of crisis?," Working Paper Series 1972, European Central Bank.
• Rangan Gupta & Eric Olson & Mark E. Wohar, 2017. "Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(6), pages 640-650, September.
  • Rangan Gupta & Eric Olson & Mark E. Wohar, 2015. "Forecasting Key US Macroeconomic Variables with a Factor-Augmented Qual VAR," Working Papers 201585, University of Pretoria, Department of Economics.
• Michael K Andersson & Ted Aranki & André Reslow, 2017. "Adjusting for information content when comparing forecast performance," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 784-794, November.
  • Andersson, Michael K. & Aranki, Ted & Reslow, André, 2016. "Adjusting for Information Content when Comparing Forecast Performance," Working Paper Series 328, Sveriges Riksbank (Central Bank of Sweden).
• Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(11), pages 1141-1152, November.
  • Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Documentos de Trabajo del ICAE 2017-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Asai, M. & McAleer, M.J., 2017. "Forecasting the Volatility of Nikkei 225 Futures," Econometric Institute Research Papers TI 2017-017/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Manabu Asai & Michael McAleer, 2017. "Forecasting the Volatility of Nikkei 225 Futures," Tinbergen Institute Discussion Papers 17-017/III, Tinbergen Institute.
• Edward S. Knotek Ii & Saeed Zaman, 2017. "Nowcasting U.S. Headline and Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 931-968, August.
  • Edward S. Knotek & Saeed Zaman, 2014. "Nowcasting U.S. Headline and Core Inflation," Working Papers (Old Series) 1403, Federal Reserve Bank of Cleveland, revised 01 May 2014.
• Jose Cuesta & Gabriel Lara Ibarra, 2017. "Comparing Cross-Survey Micro Imputation and Macro Projection Techniques: Poverty in Post Revolution Tunisia," Journal of Income Distribution, Ad libros publications inc., vol. 25(1), pages 1-30, March.
• Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017. "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 29-62, February.
• William Barnett & Liting Su, 2017. "Financial Firm Production Of Inside Monetary And Credit Card Services: An Aggregation Theoretic Approach1," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201707, University of Kansas, Department of Economics, revised Oct 2017.
• Mihály Ormos & Dusán Timotity, 2017. "Expected downside risk and asset prices: characteristics of emerging and developed European markets," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(3), pages 529-546, August.
• Francesca Rondina, 2017. "An Econometric Learning Approach to Approximate Expectations in Empirical Macro Models," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 23(4), pages 437-438, November.
• Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2017. "On exchange-rate movements and gold-price fluctuations: evidence for gold-producing countries from a nonparametric causality-in-quantiles test," International Economics and Economic Policy, Springer, vol. 14(4), pages 691-700, October.
  • Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2015. "On Exchange-Rate Movements and Gold-Price Fluctuations: Evidence for Gold-Producing Countries from a Nonparametric Causality-in-Quantiles Test," Working Papers 201598, University of Pretoria, Department of Economics.
• Esteban Fernández-Vázquez & Blanca Moreno, 2017. "Entropy Econometrics for combining regional economic forecasts: A Data-Weighted Prior Estimator," Journal of Geographical Systems, Springer, vol. 19(4), pages 349-370, October.
• Rangan Gupta & Anandamayee Majumdar & Mark E. Wohar, 2017. "The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence From a Quantile Predictive Regression Approach," Open Economies Review, Springer, vol. 28(1), pages 47-59, February.
  • Rangan Gupta & Anandamayee Majumdar & Mark Wohar, 2016. "The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence from a Quantile Predictive Regression Approach," Working Papers 201612, University of Pretoria, Department of Economics.
• Niels D. Gilbert & Jasper F.M. Jong, 2017. "Do European fiscal rules induce a bias in fiscal forecasts? Evidence from the Stability and Growth Pact," Public Choice, Springer, vol. 170(1), pages 1-32, January.
• Jing Xu & Michelle Hallack & Miguel Vazquez, 2017. "Applying a third party access model for China’s gas pipeline network: an independent pipeline operator and congestion rent transfer," Journal of Regulatory Economics, Springer, vol. 51(1), pages 72-97, February.
• Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017. "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 949-971, November.
• Chulwoo Han & Frank C. Park & Jangkoo Kang, 2017. "A geometric treatment of time-varying volatilities," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 1121-1141, November.
• Byeongdeuk Jang & Young Se Kim, 2017. "Driving Forces of Inflation Expectations," Korean Economic Review, Korean Economic Association, vol. 33, pages 207-237.
• Mihaela Simionescu, 2017. "The Impact Of Immigrants On The UK Economy," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 9(2), pages 31-46, June.
• Mirel-Daniel Simionescu, 2017. "Determinants of Foreign Direct Investments in Bulgaria and Romania in the Context of Recent Economic Crisis," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 3(1), pages 68-72, March.
• Iulian Lolea, 2017. "Where did the GARCH Models Perform Best in Terms of Volatility Forecasting? Equity vs. Commodities Markets," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 3(3), pages 79-86, September.
• Ayse Kabukcuoglu & Enrique Martínez-García & Mehmet A. Soytas, 2017. "Exploring the Nexus Between Inflation and Globalization Under Inflation Targeting Through the Lens of New Zealand’s Experience," Globalization Institute Working Papers 308, Federal Reserve Bank of Dallas, revised 01 Mar 2017.
  • Ayse Kabukcuoglu & Enrique Martínez-García & Mehmet Ali Soytas, 2017. "Exploring the Nexus between Inflation and Globalization under Inflation Targeting through the Lens of New Zealand’s Experience," Koç University-TUSIAD Economic Research Forum Working Papers 1709, Koc University-TUSIAD Economic Research Forum.
• Florian Chatagny & Christian Stettler, 2017. "Fiscal Fore casting in a Federal Country: Does Space Matter?," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 11(4), pages 51-60, December.
• Virág, Miklós & Nyitrai, Tamás, 2017. "Magyar vállalkozások felszámolásának előrejelzése pénzügyi mutatóik idősorai alapján
  [Predicting the liquidation of Hungarian firms using a time series of their financial ratios]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 305-324.
• Ouael EL JEBARI & Abdelati HAKMAOUI, 2017. "Modeling persistence of volatility in the Moroccan exchange market using a fractionally integrated EGARCH," Turkish Economic Review, KSP Journals, vol. 4(4), pages 388-399, December.
• Ron W. NIELSEN, 2017. "Application of differential equations in projecting growth trajectories," Journal of Economics Bibliography, KSP Journals, vol. 4(3), pages 203-221, September.
• Evžen KoÄ enda & Karen Poghosyan, 2018. "Export Sophistication: A Dynamic Panel Data Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(12), pages 2799-2814, September.
  • Karen Poghosyan & Evžen Kočenda, 2016. "Determinants of export sophistication: Evidence from Monte Carlo simulations," Working Papers 360, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).
  • Evzen Kocenda & Karen Poghosyan, 2017. "Export sophistication: A dynamic panel data approach," KIER Working Papers 980 Classification-C52; C, Kyoto University, Institute of Economic Research.
  • Evzen Kocenda & Karen Poghosyan, 2017. "Export sophistication: A dynamic panel data approach," Working Papers 1, Central Bank of the Republic of Armenia.
• Marisol Valencia Cárdenas & Juan Gabriel Vanegas López & Juan Carlos Correa Morales & Jorge Aníbal Restrepo Morales, 2017. "Comparing forecasts for tourism dynamics in Medellín, Colombia," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 86, pages 199-230, Enero - J.
• Anh Dinh Minh Nguyen, 2017. "U.K. Monetary Policy under Inflation Targeting," Bank of Lithuania Working Paper Series 41, Bank of Lithuania.
• Michael McAleer & Xiao-Guang Yue, 2017. "Prediction of Gas Concentration Based on the Opposite Degree Algorithm," Journal of Reviews on Global Economics, Lifescience Global, vol. 6, pages 154-162.
  • Yue, X-G. & Gao, R. & McAleer, M.J., 2016. "Prediction of Gas Concentration Based on the Opposite Degree Algorithm," Econometric Institute Research Papers EI2016-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Xiao-Guang Yue & Rui Gao & Michael McAleer, 2016. "Prediction of Gas Concentration Based on the Opposite Degree Algorithm," Documentos de Trabajo del ICAE 2016-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Xiao-Guang Yue & Rui Gao & Michael McAleer, 2016. "Prediction of Gas Concentration based on the Opposite Degree Algorithm," Tinbergen Institute Discussion Papers 16-027/III, Tinbergen Institute.
• Aumnad Phdungsilp, 2017. "Projections of Energy Use and Carbon Emissions for Bangkok,Thailand," Journal of Reviews on Global Economics, Lifescience Global, vol. 6, pages 248-257.
• Narongdech Keeratipranon & Phatcharasak Phawanaphinyo, 2017. "Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution," Journal of Reviews on Global Economics, Lifescience Global, vol. 6, pages 269-278.
• Robert Lehmann & Klaus Wohlrabe, 2017. "Boosting and regional economic forecasting: the case of Germany," Letters in Spatial and Resource Sciences, Springer, vol. 10(2), pages 161-175, July.
  • Robert Lehmann & Klaus Wohlrabe, 2016. "Boosting and Regional Economic Forecasting: The Case of Germany," CESifo Working Paper Series 6157, CESifo Group Munich.
  • Lehmann, Robert & Wohlrabe, Klaus, 2017. "Boosting and regional economic forecasting: the case of Germany," Munich Reprints in Economics 49919, University of Munich, Department of Economics.
• Pulido Sanroman, Antonio, 2017. "La predicción en Economía: Posibilidades y limitaciones/Prediction in Economics: Possibilities and Limitations," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 35, pages 215-228, Mayo.
• Parra Márquez, Juan Carlos, 2017. "Análisis del comportamiento del Modelo de Crecimiento de Gompertz en la predicción del crecimiento de la economía de Argentina, Bolivia, Chile y Perú/Study of Economic Growth of four Latin American Ec," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 35, pages 443-464, Mayo.
• López Menéndez, Ana Jesús & Pérez Suárez, Rigoberto, 2017. "Forecasting Performance and Information Measures. Revisiting the M-Competition /Evaluación de Predicciones y Medidas de Información. Reexamen de la M-Competición," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 35, pages 299-314, Mayo.
• Benchimol, Andrés, 2017. "Proyección de mortalidad en España mediante mixturas de modelos y análisis del impacto económico del riesgo de longevidad /Mortality Projection in Spain through Mixtures of Models and Analysis of the ," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 35, pages 341-366, Mayo.
• López, Ana M. & Flores, Mario A. & Sánchez, Juan I., 2017. "Modelos de series temporales aplicados a la predicción del tráfico aeroportuario español de pasajeros: Un enfoque agregado y desagregado/Forecasting of Spanish Passenger Air Traffic Based on Time Seri," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 35, pages 395-418, Mayo.
• Magdalena Petrovska & Gani Ramadani & Nikola Naumovski & Biljana Jovanovic, 2017. "Forecasting Macedonian Inflation: Evaluation of different models for short-term forecasting," Working Papers 2017-06, National Bank of the Republic of North Macedonia.
• Mohammad Reza Farzanegan & Mai Hassan, 2017. "The Impact of Economic Globalization on the Shadow Economy in Egypt," CESifo Working Paper Series 6424, CESifo Group Munich.
  • Mohammad Reza Farzanegan & Mai Hassan, 2017. "The impact of economic globalization on the shadow economy in Egypt," MAGKS Papers on Economics 201718, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Radim Farana & Cyril Klimeš & Bogdan Walek, 2017. "System Modelling and Decision Making System Based on Fuzzy Expert System," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 3(2), pages 118-122, December.
• Aleksandra HaÅ‚ka & Jacek KotÅ‚owski, 2017. "Global or Domestic? Which Shocks Drive Inflation in European Small Open Economies?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(8), pages 1812-1835, August.
  • Aleksandra Hałka & Jacek Kotłowski, 2016. "Global or domestic? Which shocks drive inflation in European small open economies?," NBP Working Papers 232, Narodowy Bank Polski, Economic Research Department.
• Christoph Anders & Max Groneck, 2017. "The Optimal Portfolio of PAYG Benefits and Funded Pensions in Germany," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 73(3), pages 255-291, September.
• Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01442618, HAL.
  • Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Documents de travail du Centre d'Economie de la Sorbonne 17006, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Armagan Tuna Aktuna-Gunes & Okay Gunes, 2017. "Time Use Elasticity of Substitution Estimates Conditional on Working Time Available," Documents de travail du Centre d'Economie de la Sorbonne 17016, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Antoine Kornprobst, 2017. "Winning Investment Strategies Based on Financial Crisis Indicators," Documents de travail du Centre d'Economie de la Sorbonne 17039, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Jørgen Vitting Andersen & Philippe de Peretti, 2017. "New method to detect convergence in simple multi-period market games," Documents de travail du Centre d'Economie de la Sorbonne 17058, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• David T. Frazier & Gael M. Martin & Christian P. Robert & Judith Rousseau, 2017. "Asymptotic properties of approximate Bayesian computation," Monash Econometrics and Business Statistics Working Papers 12/17, Monash University, Department of Econometrics and Business Statistics.
• Nithi Sopitpongstorn & Param Silvapulle & Jiti Gao, 2017. "Local logit regression for recovery rate," Monash Econometrics and Business Statistics Working Papers 19/17, Monash University, Department of Econometrics and Business Statistics.
• Panagiotelis, Anastasios & Athanasopoulos, George & Hyndman, Rob J. & Jiang, Bin & Vahid, Farshid, 2019. "Macroeconomic forecasting for Australia using a large number of predictors," International Journal of Forecasting, Elsevier, vol. 35(2), pages 616-633.
  • Bin Jiang & George Athanasopoulos & Rob J Hyndman & Anastasios Panagiotelis & Farshid Vahid, 2017. "Macroeconomic forecasting for Australia using a large number of predictors," Monash Econometrics and Business Statistics Working Papers 2/17, Monash University, Department of Econometrics and Business Statistics.
• Souhaib Ben Taieb & James W. Taylor & Rob J. Hyndman, 2017. "Coherent Probabilistic Forecasts for Hierarchical Time Series," Monash Econometrics and Business Statistics Working Papers 3/17, Monash University, Department of Econometrics and Business Statistics.
• David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
• Raïsa Basselier & David de Antonio Liedo & Geert Langenus,, 2017. "Nowcasting real economic activity in the euro area : Assessing the impact of qualitative surveys," Working Paper Research 331, National Bank of Belgium.
• Alessia Paccagnini, 2017. "Forecasting with FAVAR: macroeconomic versus financial factors," NBP Working Papers 256, Narodowy Bank Polski, Economic Research Department.
• Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski, Economic Research Department.
• Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
• Ulrich K. Müller & Mark W. Watson, 2017. "Long-Run Covariability," NBER Working Papers 23186, National Bureau of Economic Research, Inc.
• Jonathan M.V. Davis & Sara B. Heller, 2017. "Rethinking the Benefits of Youth Employment Programs: The Heterogeneous Effects of Summer Jobs," NBER Working Papers 23443, National Bureau of Economic Research, Inc.
• Andrés F. Barrientos & Alexander Bolton & Tom Balmat & Jerome P. Reiter & John M. de Figueiredo & Ashwin Machanavajjhala & Yan Chen & Charles Kneifel & Mark DeLong, 2017. "A Framework for Sharing Confidential Research Data, Applied to Investigating Differential Pay by Race in the U. S. Government," NBER Working Papers 23534, National Bureau of Economic Research, Inc.
• Yuriy Gorodnichenko & Byoungchan Lee, 2017. "A Note on Variance Decomposition with Local Projections," NBER Working Papers 23998, National Bureau of Economic Research, Inc.
• Galvão, Ana Beatriz, 2017. "Data revisions and DSGE models," Journal of Econometrics, Elsevier, vol. 196(1), pages 215-232.
  • Galvao, Ana Beatriz, 2016. "Data Revisions and DSGE Models," EMF Research Papers 11, Economic Modelling and Forecasting Group.
• Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
  • Atsushi Inoue & Lu Jin & Barbara Rossi, 2014. "Rolling Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," Working Papers 768, Barcelona Graduate School of Economics.
  • Atsushi Inoue & Lu Jin & Barbara Rossi, 2014. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Economics Working Papers 1435, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 2016.
• Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
• Engle, Robert & Roussellet, Guillaume & Siriwardane, Emil, 2017. "Scenario generation for long run interest rate risk assessment," Journal of Econometrics, Elsevier, vol. 201(2), pages 333-347.
• Amador-Torres, J. Sebastián, 2017. "Finance-neutral potential output: An evaluation in an emerging market monetary policy context," Economic Systems, Elsevier, vol. 41(3), pages 389-407.
  • J. Sebastián Amador-Torres, 2016. "Finance neutral potential output: an evaluation on an emerging market monetary policy context," Borradores de Economia 958, Banco de la Republica de Colombia.
• Roesel, Felix, 2017. "The causal effect of wrong-hand drive vehicles on road safety," Economics of Transportation, Elsevier, vol. 11, pages 15-22.
  • Roesel, Felix, 2017. "The causal effect of wrong-hand drive vehicles on road safety," CEPIE Working Papers 15/17, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
• Huber, Peter & Oberhofer, Harald & Pfaffermayr, Michael, 2017. "Who creates jobs? Econometric modeling and evidence for Austrian firm level data," European Economic Review, Elsevier, vol. 91(C), pages 57-71.
  • Huber, Peter & Oberhofer, Harald & Pfaffermayr, Michael, 2015. "Who Creates Jobs? Econometric Modeling and Evidence for Austrian Firm Level Data," Department of Economics Working Paper Series 205, WU Vienna University of Economics and Business.
  • Peter Huber & Harald Oberhofer & Michael Pfaffermayr, 2015. "Who Creates Jobs? Econometric Modeling and Evidence for Austrian Firm Level Data," Department of Economics Working Papers wuwp205, Vienna University of Economics and Business, Department of Economics.
• Meinen, Philipp & Roehe, Oke, 2017. "On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area," European Economic Review, Elsevier, vol. 92(C), pages 161-179.
  • Meinen, Philipp & Röhe, Oke, 2016. "On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area," Discussion Papers 48/2016, Deutsche Bundesbank.
• Harris, Richard D.F. & Stoja, Evarist & Tan, Linzhi, 2017. "The dynamic Black–Litterman approach to asset allocation," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1085-1096.
  • Harris, Richard D F & Stoja, Evarist & Tan, Linzhi, 2016. "The dynamic Black-Litterman approach to asset allocation," Bank of England working papers 596, Bank of England.
• Athanasopoulos, George & Hyndman, Rob J. & Kourentzes, Nikolaos & Petropoulos, Fotios, 2017. "Forecasting with temporal hierarchies," European Journal of Operational Research, Elsevier, vol. 262(1), pages 60-74.
  • George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Fotios Petropoulos, 2015. "Forecasting with Temporal Hierarchies," Monash Econometrics and Business Statistics Working Papers 16/15, Monash University, Department of Econometrics and Business Statistics.
  • Athanasopoulos, George & Hyndman, Rob J. & Kourentzes, Nikolaos & Petropoulos, Fotios, 2015. "Forecasting with Temporal Hierarchies," MPRA Paper 66362, University Library of Munich, Germany.
• Guarin, Alexander & Lozano, Ignacio, 2017. "Credit funding and banking fragility: A forecasting model for emerging economies," Emerging Markets Review, Elsevier, vol. 32(C), pages 168-189.
• Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2017. "Relation between higher order comoments and dependence structure of equity portfolio," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 101-120.
• Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
• Fries, Christian P. & Nigbur, Tobias & Seeger, Norman, 2017. "Displaced relative changes in historical simulation: Application to risk measures of interest rates with phases of negative rates," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 175-198.
• Anatolyev, Stanislav & Gospodinov, Nikolay & Jamali, Ibrahim & Liu, Xiaochun, 2017. "Foreign exchange predictability and the carry trade: A decomposition approach," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 199-211.
• Han, Xing & Li, Youwei, 2017. "Can investor sentiment be a momentum time-series predictor? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 212-239.
  • Han, Xing & Li, Youwei, 2016. "Can Investor Sentiment Be a Momentum Time-Series Predictor? Evidence from China," RIEI Working Papers 2016-07, Xi'an Jiaotong-Liverpool University, Research Institute for Economic Integration, revised 12 Jan 2017.
• Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
• Gupta, Rangan & Kotzé, Kevin, 2017. "The role of oil prices in the forecasts of South African interest rates: A Bayesian approach," Energy Economics, Elsevier, vol. 61(C), pages 270-278.
  • Rangan Gupta & Kevin Kotze, 2015. "The Role of Oil Prices in the Forecasts of South African Interest Rates: A Bayesian Approach," Working Papers 201531, University of Pretoria, Department of Economics.
  • Rangan Gupta & Kevin Kotze, 2016. "The Role of Oil Prices in the Forecasts of South African Interest Rates: A Bayesian Approach," School of Economics Macroeconomic Discussion Paper Series 2016-01, School of Economics, University of Cape Town.
• Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
  • Rangan Gupta & Mark E. Wohar, 2015. "Forecasting Oil and Stock Returns with a Qual VAR using over 150 Years of Data," Working Papers 201589, University of Pretoria, Department of Economics.
• Bennedsen, Mikkel, 2017. "A rough multi-factor model of electricity spot prices," Energy Economics, Elsevier, vol. 63(C), pages 301-313.
• Bataille, Chris & Melton, Noel, 2017. "Energy efficiency and economic growth: A retrospective CGE analysis for Canada from 2002 to 2012," Energy Economics, Elsevier, vol. 64(C), pages 118-130.
• Pinheiro Neto, Daywes & Domingues, Elder Geraldo & Coimbra, António Paulo & de Almeida, Aníbal Traça & Alves, Aylton José & Calixto, Wesley Pacheco, 2017. "Portfolio optimization of renewable energy assets: Hydro, wind, and photovoltaic energy in the regulated market in Brazil," Energy Economics, Elsevier, vol. 64(C), pages 238-250.
• Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
• Zhang, Lei & Li, Yaoyu, 2017. "Regime-switching based vehicle-to-building operation against electricity price spikes," Energy Economics, Elsevier, vol. 66(C), pages 1-8.
• Campos, I. & Cortazar, G. & Reyes, T., 2017. "Modeling and predicting oil VIX: Internet search volume versus traditional mariables," Energy Economics, Elsevier, vol. 66(C), pages 194-204.
• Mirakyan, Atom & Meyer-Renschhausen, Martin & Koch, Andreas, 2017. "Composite forecasting approach, application for next-day electricity price forecasting," Energy Economics, Elsevier, vol. 66(C), pages 228-237.
• Wang, Yudong & Liu, Li & Wu, Chongfeng, 2017. "Forecasting the real prices of crude oil using forecast combinations over time-varying parameter models," Energy Economics, Elsevier, vol. 66(C), pages 337-348.
• Taylor, Nick, 2017. "Timing strategy performance in the crude oil futures market," Energy Economics, Elsevier, vol. 66(C), pages 480-492.
• Sukcharoen, Kunlapath & Leatham, David J., 2017. "Hedging downside risk of oil refineries: A vine copula approach," Energy Economics, Elsevier, vol. 66(C), pages 493-507.
• Lyu, Yongjian & Wang, Peng & Wei, Yu & Ke, Rui, 2017. "Forecasting the VaR of crude oil market: Do alternative distributions help?," Energy Economics, Elsevier, vol. 66(C), pages 523-534.
• Han, Liyan & Lv, Qiuna & Yin, Libo, 2017. "Can investor attention predict oil prices?," Energy Economics, Elsevier, vol. 66(C), pages 547-558.
• Zhao, Yang & Li, Jianping & Yu, Lean, 2017. "A deep learning ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 66(C), pages 9-16.
• Ma, Feng & Wahab, M.I.M. & Huang, Dengshi & Xu, Weiju, 2017. "Forecasting the realized volatility of the oil futures market: A regime switching approach," Energy Economics, Elsevier, vol. 67(C), pages 136-145.
• Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
• Miao, Hong & Ramchander, Sanjay & Wang, Tianyang & Yang, Dongxiao, 2017. "Influential factors in crude oil price forecasting," Energy Economics, Elsevier, vol. 68(C), pages 77-88.
• Croonenbroeck, Carsten & Hüttel, Silke, 2017. "Quantifying the economic efficiency impact of inaccurate renewable energy price forecasts," Energy, Elsevier, vol. 134(C), pages 767-774.
• Alexopoulos, Thomas A., 2017. "The growing importance of natural gas as a predictor for retail electricity prices in US," Energy, Elsevier, vol. 137(C), pages 219-233.
• Moral-Carcedo, Julián & Pérez-García, Julián, 2017. "Integrating long-term economic scenarios into peak load forecasting: An application to Spain," Energy, Elsevier, vol. 140(P1), pages 682-695.
• Degiannakis, Stavros & Potamia, Artemis, 2017. "Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: Inter-day versus intra-day data," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 176-190.
  • Degiannakis, Stavros & Potamia, Artemis, 2016. "Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: inter-day versus intra-day data," MPRA Paper 74670, University Library of Munich, Germany.
• Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2017. "Predictability and diversification benefits of investing in commodity and currency futures," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 52-66.
• Tunaru, Radu & Zheng, Teng, 2017. "Parameter estimation risk in asset pricing and risk management: A Bayesian approach," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 80-93.
• Svec, Jiri & Katrak, Xerxis, 2017. "Forecasting volatility with interacting multiple models," Finance Research Letters, Elsevier, vol. 20(C), pages 245-252.
• Chen, Cathy W.S. & Lin, Tsai-Yu, 2017. "Nonparametric tolerance limits for pair trading," Finance Research Letters, Elsevier, vol. 21(C), pages 1-9.
• Kinateder, Harald & Hofstetter, Benedikt & Wagner, Niklas, 2017. "Do liquidity variables improve out-of-sample prediction of sovereign spreads during crisis periods?," Finance Research Letters, Elsevier, vol. 21(C), pages 144-150.
• Klein, Tony & Walther, Thomas, 2017. "Fast fractional differencing in modeling long memory of conditional variance for high-frequency data," Finance Research Letters, Elsevier, vol. 22(C), pages 274-279.
• Demirer, Riza & Pierdzioch, Christian & Zhang, Huacheng, 2017. "On the short-term predictability of stock returns: A quantile boosting approach," Finance Research Letters, Elsevier, vol. 22(C), pages 35-41.
• Mendes, Beatriz Vaz de Melo & Lavrado, Rafael Coelho, 2017. "Implementing and testing the Maximum Drawdown at Risk," Finance Research Letters, Elsevier, vol. 22(C), pages 95-100.
• Lyócsa, Štefan & Molnár, Peter, 2017. "The effect of non-trading days on volatility forecasts in equity markets," Finance Research Letters, Elsevier, vol. 23(C), pages 39-49.
• Dawood, Mary & Horsewood, Nicholas & Strobel, Frank, 2017. "Predicting sovereign debt crises: An Early Warning System approach," Journal of Financial Stability, Elsevier, vol. 28(C), pages 16-28.
• Abbassi, Puriya & Brownlees, Christian & Hans, Christina & Podlich, Natalia, 2017. "Credit risk interconnectedness: What does the market really know?," Journal of Financial Stability, Elsevier, vol. 29(C), pages 1-12.
  • Abbassi, Puriya & Brownlees, Christian & Hans, Christina & Podlich, Natalia, 2016. "Credit risk interconnectedness: What does the market really know?," Discussion Papers 09/2016, Deutsche Bundesbank.
• Kolo, Horst & Tzanova, Polia, 2017. "Forecasting the German forest products trade: A vector error correction model," Journal of Forest Economics, Elsevier, vol. 26(C), pages 30-45.
• Ince, Onur & Molodtsova, Tanya, 2017. "Rationality and forecasting accuracy of exchange rate expectations: Evidence from survey-based forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 47(C), pages 131-151.
• Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
• Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
  • Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Papers No 1/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Paper 2015/05, Norges Bank.
  • Hilde C. Bjornland & Francesco Ravazzolo & Leif Anders Thorsrud, 2016. "Forecasting GDP with global components. This time is different," CAMA Working Papers 2016-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Kang, Yanfei & Hyndman, Rob J. & Smith-Miles, Kate, 2017. "Visualising forecasting algorithm performance using time series instance spaces," International Journal of Forecasting, Elsevier, vol. 33(2), pages 345-358.
  • Yanfei Kang & Rob J. Hyndman & Kate Smith-Miles, 2016. "Visualising forecasting Algorithm Performance using Time Series Instance Spaces," Monash Econometrics and Business Statistics Working Papers 10/16, Monash University, Department of Econometrics and Business Statistics.
• Hendry, David F. & Martinez, Andrew B., 2017. "Evaluating multi-step system forecasts with relatively few forecast-error observations," International Journal of Forecasting, Elsevier, vol. 33(2), pages 359-372.
  • David Hendry & Andrew B. Martinez, 2016. "Evaluating Multi-Step System Forecasts with Relatively Few Forecast-Error Observations," Economics Series Working Papers 784, University of Oxford, Department of Economics.
• Tallman, Ellis W. & Zaman, Saeed, 2017. "Forecasting inflation: Phillips curve effects on services price measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 442-457.
  • Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland, revised 14 Oct 2015.
• Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
  • Delle Monache, Davide & Petrella, Ivan, 2016. "Adaptive Models and Heavy Tails with an Application to Inflation Forecasting," EMF Research Papers 13, Economic Modelling and Forecasting Group.
  • Davide Delle Monache & Ivan Petrella, 2016. "Adaptive models and heavy tails with an application to inflation forecasting," BCAM Working Papers 1603, Birkbeck Centre for Applied Macroeconomics.
  • Delle Monache, Davide & Petrella, Ivan, 2016. "Adaptive models and heavy tails with an application to inflation forecasting," MPRA Paper 75424, University Library of Munich, Germany.
• Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
  • Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice: An Interview with David F. Hendry," Working Papers 2016-012, The George Washington University, Department of Economics, Research Program on Forecasting.
  • Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice : An Interview with David F. Hendry," International Finance Discussion Papers 1184, Board of Governors of the Federal Reserve System (U.S.).
• Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
  • Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, Department of Economics, Research Program on Forecasting.
  • Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.), revised 06 Jan 2017.
• Rua, António, 2017. "A wavelet-based multivariate multiscale approach for forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 581-590.
  • António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
• Hännikäinen, Jari, 2017. "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1044-1064.
  • Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
  • Jari Hännikäinen, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," Working Papers 1603, Tampere University, School of Management and Business, Economics.
• Sbrana, Giacomo & Silvestrini, Andrea & Venditti, Fabrizio, 2017. "Short-term inflation forecasting: The M.E.T.A. approach," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1065-1081.
  • Giacomo Sbrana & Andrea Silvestrini & Fabrizio Venditti, 2015. "Short term inflation forecasting: the M.E.T.A. approach," Temi di discussione (Economic working papers) 1016, Bank of Italy, Economic Research and International Relations Area.
• Döpke, Jörg & Fritsche, Ulrich & Pierdzioch, Christian, 2017. "Predicting recessions with boosted regression trees," International Journal of Forecasting, Elsevier, vol. 33(4), pages 745-759.
  • Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions With Boosted Regression Trees," Working Papers 2015-004, The George Washington University, Department of Economics, Research Program on Forecasting.
• Taylor, Nick, 2017. "Realised variance forecasting under Box-Cox transformations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 770-785.
• Bragoli, Daniela & Modugno, Michele, 2017. "A now-casting model for Canada: Do U.S. variables matter?," International Journal of Forecasting, Elsevier, vol. 33(4), pages 786-800.
  • Daniela Bragoli & Michele Modugno, 2016. "A Nowcasting Model for Canada: Do U.S. Variables Matter?," Finance and Economics Discussion Series 2016-036, Board of Governors of the Federal Reserve System (U.S.).
• D’Amuri, Francesco & Marcucci, Juri, 2017. "The predictive power of Google searches in forecasting US unemployment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 801-816.
  • Francesco D'Amuri & Juri Marcucci, 2012. "The predictive power of Google searches in forecasting unemployment," Temi di discussione (Economic working papers) 891, Bank of Italy, Economic Research and International Relations Area.
• Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
  • Tatjana Dahlhaus & Justin-Damien Guénette & Garima Vasishtha, 2015. "Nowcasting BRIC+M in Real Time," Staff Working Papers 15-38, Bank of Canada.
• Kolev, Gueorgui I. & Karapandza, Rasa, 2017. "Out-of-sample equity premium predictability and sample split–invariant inference," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 188-201.
• Bella, Giovanni & Mattana, Paolo & Venturi, Beatrice, 2017. "Shilnikov chaos in the Lucas model of endogenous growth," Journal of Economic Theory, Elsevier, vol. 172(C), pages 451-477.
• Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017. "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 183-203.
• Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
  • Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
• David, Benjamin, 2017. "Computer technology and probable job destructions in Japan: An evaluation," Journal of the Japanese and International Economies, Elsevier, vol. 43(C), pages 77-87.
• Fanelli, Luca & Sorge, Marco M., 2017. "Indeterminate forecast accuracy under indeterminacy," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 57-70.
• Aepli, Matthias D. & Füss, Roland & Henriksen, Tom Erik S. & Paraschiv, Florentina, 2017. "Modeling the multivariate dynamic dependence structure of commodity futures portfolios," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 66-87.
• Ekici, Oya & Nemlioğlu, Karun, 2017. "Emerging economies’ short-term private external debt as evidence of economic crisis," Journal of Policy Modeling, Elsevier, vol. 39(2), pages 232-246.
• Atashbar, Tohid & Arani, Abbas Assari & Antoun, Joseph & Bossert, Thomas, 2017. "Health reform policy-making: Fiscal sustainability matters (The case of Iran’s PresidentCare)," Journal of Policy Modeling, Elsevier, vol. 39(6), pages 1086-1101.
• Gilbert, Thomas & Scotti, Chiara & Strasser, Georg & Vega, Clara, 2017. "Is the intrinsic value of a macroeconomic news announcement related to its asset price impact?," Journal of Monetary Economics, Elsevier, vol. 92(C), pages 78-95.
• Mei, Dexiang & Liu, Jing & Ma, Feng & Chen, Wang, 2017. "Forecasting stock market volatility: Do realized skewness and kurtosis help?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 153-159.
• Cortés, Lina M. & Mora-Valencia, Andrés & Perote, Javier, 2017. "Measuring firm size distribution with semi-nonparametric densities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 485(C), pages 35-47.
  • Lina Cortés & Andrés Mora-Valencia & Javier Perote, 2017. "Measuring firm size distribution with semi-nonparametric densities," Documentos de Trabajo CIEF 015300, Universidad EAFIT.
• Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian & Wohar, Mark E., 2017. "Do terror attacks predict gold returns? Evidence from a quantile-predictive-regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 276-284.
  • Rangan Gupta & Anandamayee Majumdar & Christian Pierdzioch & Mark Wohar, 2016. "Do Terror Attacks Predict Gold Returns? Evidence from a Quantile-Predictive-Regression Approach," Working Papers 201626, University of Pretoria, Department of Economics.
• Christou, Christina & Gupta, Rangan & Hassapis, Christis, 2017. "Does economic policy uncertainty forecast real housing returns in a panel of OECD countries? A Bayesian approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 50-60.
  • Christina Christou & Rangan Gupta & Christis Hassapis, 2016. "Does Economic Policy Uncertainty Forecast Real Housing Returns in a Panel of OECD Countries? A Bayesian Approach," Working Papers 201637, University of Pretoria, Department of Economics.
• Balcilar, Mehmet & Gupta, Rangan & Sousa, Ricardo M. & Wohar, Mark E., 2017. "Do cay and cayMS predict stock and housing returns? Evidence from a nonparametric causality test," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 269-279.
• Suh, Sangwon, 2017. "Sudden stops of capital flows to emerging markets: A new prediction approach," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 289-308.
• Chen, Nan-Kuang & Chen, Shiu-Sheng & Chou, Yu-Hsi, 2017. "Further evidence on bear market predictability: The role of the external finance premium," International Review of Economics & Finance, Elsevier, vol. 50(C), pages 106-121.
  • Chen, Nan-Kuang & Chen, Shiu-Sheng & Chou, Yu-Hsi, 2013. "Further evidence on bear market predictability: The role of the external finance premium," MPRA Paper 49093, University Library of Munich, Germany.
• Park, Hail & Shin, Yongcheol, 2017. "Exploring international linkages using generalised connectedness measures: The case of Korea," International Review of Economics & Finance, Elsevier, vol. 50(C), pages 49-64.
• Caraiani, Petre, 2017. "Evaluating exchange rate forecasts along time and frequency," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 60-81.
• Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
  • Buncic, Daniel & Tischhauser, Martin, 2015. "Macroeconomic Factors and Equity Premium Predictability," Economics Working Paper Series 1522, University of St. Gallen, School of Economics and Political Science.
• Jalles, João Tovar, 2017. "On the rationality and efficiency of inflation forecasts: Evidence from advanced and emerging market economies," Research in International Business and Finance, Elsevier, vol. 40(C), pages 175-189.
• Walther, Thomas & Klein, Tony & Thu, Hien Pham & Piontek, Krzysztof, 2017. "True or spurious long memory in European non-EMU currencies," Research in International Business and Finance, Elsevier, vol. 40(C), pages 217-230.
• Maggi, Bernardo, 2017. "A technology-based countries-interaction dynamic model for the study of European growth and stability: Were there the conditions for convergence?," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 275-288.
• Jason Allen, 2017. "Loan pricing, stress testing and capital allocation," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 60(2), pages 39-64.
• Sonia de Lucas Santos & María Jesús Delgado Rodríguez, 2017. "Contribution of economic theory to the cyclical crisis: State of art in historical perspective," Economia Coyuntural,Revista de temas de perspectivas y coyuntura, Instituto de Investigaciones Economicas y Sociales 'Jose Ortiz Mercado' (IIES-JOM), Facultad de Ciencias Economicas, Administrativas y Financieras, Universidad Autonoma Gabriel Rene Moreno, vol. 2(3), pages 1-50.
• Adrien Lagarde & Abdoul Ahad-Cissé & Sophie Gourguet & Olivier Le Pape & Olivier Thébaud & Nathalie Caill-Milly & Gilles Morandeau & Claire Macher & Luc Doyen, 2017. "How MMEY mitigates bio-economic impacts of climate change on mixed fisheries," Cahiers du GREThA (2007-2019) 2017-22, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
• Sri Hapsari Wijayanti, 2017. "The Canvas Model as a Strategy for Improving Financial Profits: A Casey Study of Online Businesses in Indonesia," GATR Journals jber148, Global Academy of Training and Research (GATR) Enterprise.
• Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
  • Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.), revised 06 Jan 2017.
  • Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, Department of Economics, Research Program on Forecasting.
• Lionel Fontagné & Jean Fouré, 2017. "La politique commerciale au service de la politique climatique," La Lettre du CEPII, CEPII research center, issue 373.
  • Lionel Fontagné & Jean Fouré, 2017. "La politique commerciale au service de la politique climatique," Post-Print hal-01459839, HAL.
  • Lionel Fontagné & Jean Fouré, 2017. "La politique commerciale au service de la politique climatique," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01459839, HAL.
• Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Documents de travail du Centre d'Economie de la Sorbonne 17006, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01442618, HAL.
• Lionel Fontagné & Jean Fouré, 2017. "La politique commerciale au service de la politique climatique," La Lettre du CEPII, CEPII research center, issue 373.
  • Lionel Fontagné & Jean Fouré, 2017. "La politique commerciale au service de la politique climatique," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01459839, HAL.
  • Lionel Fontagné & Jean Fouré, 2017. "La politique commerciale au service de la politique climatique," Post-Print hal-01459839, HAL.
• Paret, Anne-Charlotte, 2017. "Debt sustainability in emerging market countries: Some policy guidelines from a fan-chart approach," Economic Modelling, Elsevier, vol. 63(C), pages 26-45.
  • Anne-Charlotte Paret, 2017. "Debt sustainability in emerging market countries: Some policy guidelines from a fan-chart approach," Post-Print hal-01590005, HAL.
• Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.
  • L. Ferrara & C. Marsilli, 2014. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Working papers 515, Banque de France.
  • Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Post-Print hal-01636761, HAL.
• Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017. "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 162-182, April.
  • Bauwens, Luc & Carpantier, Jean-François & Dufays, Arnaud, 2015. "Autoregressive moving average infinite hidden markov-switching models," CORE Discussion Papers 2015007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017. "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Post-Print hal-01795051, HAL.
  • Luc BAUWENS & Jean-François CARPENTIER & Arnaud DUFAYS, 2017. "Autoregressive moving average infinite hidden Markov-switching models," CORE Discussion Papers RP 2836, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
• Vanella, Patrizio, 2017. "Stochastische Prognose demografischer Komponenten auf Basis der Hauptkomponentenanalyse," Hannover Economic Papers (HEP) dp-597, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
• Vanella, Patrizio & Deschermeier, Philipp, 2017. "Ein stochastisches Prognosemodell internationaler Migration in Deutschland," Hannover Economic Papers (HEP) dp-605, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
• Vanella, Patrizio, 2017. "Age- and Sex-Specific Fertility in Germany until the Year 2040 - The Impact of International Migration," Hannover Economic Papers (HEP) dp-606, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
• Franziska K. Kruse & Wolfgang Maennig, 2017. "The future development of world records," Working Papers 061, Chair for Economic Policy, University of Hamburg.
• Przemyslaw Zbierowski, 2017. "The Aspirations of New Technology-Based Firms in CEE and CIS Countries," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 11(3), pages 50-60.
• Olga Obraztsova & Tatiana Poliakova & Ekaterina Popovskaya, 2017. "The Choice of Funding Sources for Start-Ups in a Transitional Economy: The Ability to Predict in a National Context," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 11(3), pages 71-81.
• Victoria Golikova & Boris Kuznetsov, 2017. "Suboptimal Size: Factors Preventing the Growth of Russian Small and Medium-Sized Enterprises," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 11(3), pages 83-93.
• Evgeniy M. Ozhegov & Alina Ozhegova, 2017. "Regression Tree Model for Analysis of Demand with Heterogeneity and Censorship," HSE Working papers WP BRP 174/EC/2017, National Research University Higher School of Economics.
• Takeuchi-Nogimori, Asuka, 2017. "An Empirical Analysis of Nikkei 225 Options Using Realized GARCH Models," Economic Review, Hitotsubashi University, vol. 68(2), pages 97-113, April.
• Violeta DUTA, 2017. "Analysis and Modeling of NYSE Arca Oil & Gas Stock Index Returns," Hyperion Economic Journal, Faculty of Economic Sciences, Hyperion University of Bucharest, Romania, vol. 5(4), pages 48-62, December.
• Wagner Piazza Gaglianone & Waldyr Dutra Areosa, 2016. "Financial Conditions Indicators for Brazil," Working Papers Series 435, Central Bank of Brazil, Research Department.
  • Gaglianone, Wagner Piazza & Dutra Areosa, Waldyr, 2017. "Financial Conditions Indicator for Brazil," IDB Publications (Working Papers) 8488, Inter-American Development Bank.
• Benito Muela, Sonia & López Martín, Carmen & Arguedas Sanz, Raquel, 2017. "An Application Of Extreme Value Theory In Estimating Liquidity Risk," European Research on Management and Business Economics (ERMBE), Academia Europea de Dirección y Economía de la Empresa (AEDEM), vol. 23(3), pages 157-164.
• G.C. Imanov & H.S.Alieva & R.A.Yusifzadeh, 2017. "Financial Stability In Azerbaijan: The Application Of Fuzzy Approach," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 19(3), pages 1-16, January.
• Valentina Aprigliano & Claudia Foroni & Massimiliano Marcellino & Gianluigi Mazzi & Fabrizio Venditti, 2017. "A daily indicator of economic growth for the euro area," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 7(1/2), pages 43-63.
  • Valentina Aprigliano & Claudia Foroni & Massimiliano Marcellino & Gianluigi Mazzi & Fabrizio Venditti, 2016. "A daily indicator of economic growth for the euro area," Working Papers 570, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
• Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
  • Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers CWP50/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Michael Ehrmann & Damjan Pfajfar & Emiliano Santoro, 2017. "Consumers' Attitudes and Their Inflation Expectations," International Journal of Central Banking, International Journal of Central Banking, vol. 13(1), pages 225-259, February.
  • Michael Ehrmann & Damjan Pfajfar & Emilianio Santoro, 2015. "Consumers' Attitudes and Their Inflation Expectations," Finance and Economics Discussion Series 2015-15, Board of Governors of the Federal Reserve System (U.S.), revised 10 Mar 2015.
• Stavroula A Chrysanthopoulou, 2017. "MILC: A Microsimulation Model of the Natural History of Lung Cancer," International Journal of Microsimulation, International Microsimulation Association, vol. 10(3), pages 5-26.
• Christian Menden & Christian R. Proaño, 2017. "Dissecting the financial cycle with dynamic factor models," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1965-1994, December.
  • Christian Menden & Christian R. Proaño, 2017. "Dissecting the financial cycle with dynamic factor models," IMK Working Paper 183-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
• Proaño, Christian R. & Tarassow, Artur, 2018. "Evaluating the predicting power of ordered probit models for multiple business cycle phases in the U.S. and Japan," Journal of the Japanese and International Economies, Elsevier, vol. 50(C), pages 60-71.
  • Christian R. Proaño & Artur Tarassow, 2017. "Evaluating the predicting power of ordered probit models for multiple business cycle phases in the U.S. and Japan," IMK Working Paper 188-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
• Thorsten Simon & Peter Fabsic & Georg J. Mayr & Nikolaus Umlauf & Achim Zeileis, 2017. "Probabilistic forecasting of thunderstorms in the Eastern Alps," Working Papers 2017-25, Faculty of Economics and Statistics, University of Innsbruck.
• José A. Álvarez-Jareño & Elena Badal-Valero & José Manuel Pavía, 2017. "Using machine learning for financial fraud detection in the accounts of companies investigated for money laundering," Working Papers 2017/07, Economics Department, Universitat Jaume I, Castellón (Spain).
• Dr. Sudeshna Ghosh, 2017. "Forecasting Exports of Tea from India : Application of Arima Model," Journal of Commerce and Trade, Society for Advanced Management Studies, vol. 12(2), pages 116-129, October.
• Bernard Njindan Iyke & Sin-Yu Ho, 2017. "Monetary uncertainty and the demand for money in Ghana," Journal of Developing Areas, Tennessee State University, College of Business, vol. 51(4), pages 1-15, October-D.
• Fizzah Malik & Fangjun Wang & Muhammad Akram Naseem, 2017. "Econometric estimation of banking stocks," Journal of Developing Areas, Tennessee State University, College of Business, vol. 51(4), pages 207-237, October-D.
• Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
• Cobb, Marcus P A, 2017. "Joint Forecast Combination of Macroeconomic Aggregates and Their Components," MPRA Paper 76556, University Library of Munich, Germany.
• Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.
• Pincheira, Pablo, 2017. "A Power Booster Factor for Out-of-Sample Tests of Predictability," MPRA Paper 77027, University Library of Munich, Germany.
• Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP
  [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
  • Tóth, Peter, 2017. "Nowcasting Slovak GDP by a Small Dynamic Factor Model," MPRA Paper 77245, University Library of Munich, Germany.
• BLINOV, Sergey, 2017. "Использование Взаимосвязи Между Ввп И Денежной Массой Для Экономического Прогнозирования
  [Economic Forecasting Based on the Relationship between GDP and Real Money Supply]," MPRA Paper 77475, University Library of Munich, Germany.
• Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil prices," MPRA Paper 77531, University Library of Munich, Germany.
• Carlos Medel, 2017. "Forecasting Chilean inflation with the hybrid new keynesian Phillips curve: globalisation, combination, and accuracy," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 20(3), pages 004-050, December.
  • Carlos Medel, 2016. "Forecasting Chilean Inflation with the Hybrid New Keynesian Phillips Curve: Globalisation, Combination, and Accuracy," Working Papers Central Bank of Chile 791, Central Bank of Chile.
  • Medel, Carlos A., 2017. "Forecasting Chilean Inflation with the Hybrid New Keynesian Phillips Curve: Globalisation, Combination, and Accuracy," MPRA Paper 78439, University Library of Munich, Germany.
• BLINOV, Sergey, 2017. "Economic Forecasting Based on the Relationship between GDP and Real Money Supply," MPRA Paper 78717, University Library of Munich, Germany.
• John M. Maheu & Yong Song, 2018. "An efficient Bayesian approach to multiple structural change in multivariate time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(2), pages 251-270, March.
  • Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
• Pyzhov, Vladislav & Pyzhov, Stanislav, 2017. "Comparison of methods of data mining techniques for the predictive accuracy," MPRA Paper 79326, University Library of Munich, Germany.
• Polman, Fabian M. & Krijgsman, Cees & Dajani, Karma & Hemminga, Marcus A., 2017. "Modelling a Dutch Pension Fund’s Capital Requirement for Longevity Risk," MPRA Paper 79438, University Library of Munich, Germany.
• Davis, Brent, 2017. "“Negative Political Advertising: It’s All in the Timing”," MPRA Paper 79449, University Library of Munich, Germany.
• Bhatt, Vipul & Kishor, Kundan & Marfatia, Hardik, 2017. "Estimating excess sensitivity and habit persistence in consumption using Greenbook forecast as an instrument," MPRA Paper 79748, University Library of Munich, Germany.
• Yang, Bill Huajian, 2017. "Smoothing Algorithms by Constrained Maximum Likelihood," MPRA Paper 79911, University Library of Munich, Germany.
• Yang, Bill Huajian, 2017. "Forward Ordinal Probability Models for Point-in-Time Probability of Default Term Structure," MPRA Paper 79934, University Library of Munich, Germany.
• Laura Bisio & Filippo Moauro, 2018. "Temporal disaggregation by dynamic regressions: Recent developments in Italian quarterly national accounts," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 471-494, November.
  • Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.
• Lindblad, Annika, 2017. "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper 80266, University Library of Munich, Germany.
• Kuusela, Annika & Hännikäinen, Jari, 2017. "What do the shadow rates tell us about future inflation?," MPRA Paper 80542, University Library of Munich, Germany.
• Yang, Bill Huajian, 2017. "Point-in-Time PD Term Structure Models with Loan Credit Quality as a Component," MPRA Paper 80641, University Library of Munich, Germany.
• Nelimarkka, Jaakko, 2017. "Evidence on News Shocks under Information Deficiency," MPRA Paper 80850, University Library of Munich, Germany.
• Fries, Sébastien & Zakoian, Jean-Michel, 2019. "Mixed Causal-Noncausal Ar Processes And The Modelling Of Explosive Bubbles," Econometric Theory, Cambridge University Press, vol. 35(6), pages 1234-1270, December.
  • Fries, Sébastien & Zakoian, Jean-Michel, 2017. "Mixed Causal-Noncausal AR Processes and the Modelling of Explosive Bubbles," MPRA Paper 81345, University Library of Munich, Germany.
• Cobb, Marcus P A, 2017. "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper 81585, University Library of Munich, Germany.
• Raihan, Tasneem, 2017. "Performance of Markov-Switching GARCH Model Forecasting Inflation Uncertainty," MPRA Paper 82343, University Library of Munich, Germany.
• Svetunkov, Ivan & Boylan, John Edward, 2017. "Multiplicative state-space models for intermittent time series," MPRA Paper 82487, University Library of Munich, Germany.
• Hegadekatti, Kartik & S G, Yatish, 2017. "The Programmable Economy: Envisaging an Entire Planned Economic System as a Single Computer through Blockchain Networks," MPRA Paper 82831, University Library of Munich, Germany, revised 16 May 2017.
• Hassett, Kevin & Zhong, Weifeng, 2017. "On the Observational Implications of Knightian Uncertainty," MPRA Paper 82998, University Library of Munich, Germany.
• Brkic, Sabina & Hodzic, Migdat & Dzanic, Enis, 2017. "Fuzzy Logic Model of Soft Data Analysis for Corporate Client Credit Risk Assessment in Commercial Banking," MPRA Paper 83028, University Library of Munich, Germany, revised Nov 2017.
• Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
  • Bucci, Andrea, 2017. "Forecasting realized volatility: a review," MPRA Paper 83232, University Library of Munich, Germany.
• Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
• Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzan, Alfred G., 2017. "Assessing the 2016 U.S. Presidential Election Popular Vote Forecasts," MPRA Paper 83282, University Library of Munich, Germany.
• Lee, Seohyun, 2017. "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper 83617, University Library of Munich, Germany.
• Chhorn, Theara & Chaiboonsri, Chukiat, 2017. "Modelling and Forecasting Tourist Arrivals to Cambodia: An Application of ARIMA-GARCH Approach," MPRA Paper 83942, University Library of Munich, Germany, revised 27 Dec 2017.
• Tonnerre, Antoine, 2017. "Merger Simulations in the American Airline Industry," MPRA Paper 84395, University Library of Munich, Germany.
• Duc Khuong Nguyen & Thomas Walther, 2020. "Modeling and forecasting commodity market volatility with long‐term economic and financial variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 126-142, March.
  • Nguyen, Duc Khuong & Walther, Thomas, 2017. "Modeling and forecasting commodity market volatility with long-term economic and financial variables," MPRA Paper 84464, University Library of Munich, Germany, revised Jan 2018.
  • Thomas Walther & Duc Khuong Nguyen, 2018. "Modeling and Forecasting Commodity Market Volatility with Long-term Economic and Financial Variables," Working Papers on Finance 1824, University of St. Gallen, School of Finance.
• Li, Longqing, 2017. "A Comparative Study of GARCH and EVT Model in Modeling Value-at-Risk," MPRA Paper 85645, University Library of Munich, Germany.
• MacDonald, Stephen & Ash, Mark & Cooke, Bryce, 2017. "The Evolution of Inefficiency in USDA’s Forecasts of U.S. and World Soybean Markets," MPRA Paper 87545, University Library of Munich, Germany.
• Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
  • Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
• Christina Christou & Rangan Gupta & Fredj Jawadi, 2017. "Does Inequality Help in Forecasting Equity Premium in a Panel of G7 Countries?," Working Papers 201720, University of Pretoria, Department of Economics.
• Christian Pierdzioch & Rangan Gupta, 2017. "Uncertainty and Forecasts of U.S. Recessions," Working Papers 201732, University of Pretoria, Department of Economics.
• Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data," CQE Working Papers 6117, Center for Quantitative Economics (CQE), University of Muenster.
  • Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are Multifractal Processes Suited to Forecasting Electricity Price Volatility? Evidence from Australian Intraday Data," Working Papers 201739, University of Pretoria, Department of Economics.
• Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018. "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 705-719, November.
  • Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2017. "The Role of Economic Uncertainty in Forecasting Exchange Rate Returns and Realized Volatility: Evidence from Quantile Predictive Regressions," Working Papers 201774, University of Pretoria, Department of Economics.
• Milan Fičura, 2017. "Forecasting Stock Market Realized Variance with Echo State Neural Networks," European Financial and Accounting Journal, University of Economics, Prague, vol. 2017(3), pages 145-155.
• Nikola Radivojevic & Jelena Jovovic, 2017. "Examining of Determinants of Non-Performing Loans," Prague Economic Papers, University of Economics, Prague, vol. 2017(3), pages 300-316.
• Martina Miskolczi & Jitka Langhamrová, 2017. "Využití metody vícestavové demografie při analýze trhu práce
  [Utilization of Multistate Demography Method at the Labour Market Analysis]," Politická ekonomie, University of Economics, Prague, vol. 2017(1), pages 82-95.
• Jan Vlachý, 2017. "Analýza daňových systémů středoevropských zemí pomocí statistické simulace
  [An Analysis of Central European Tax Systems Using Statistical Simulation]," Politická ekonomie, University of Economics, Prague, vol. 2017(4), pages 410-423.
• Deaton, Angus & Cartwright, Nancy, 2018. "Understanding and misunderstanding randomized controlled trials," Social Science & Medicine, Elsevier, vol. 210(C), pages 2-21.
  • Angus Deaton & Nancy Cartwright, 2016. "Understanding and Misunderstanding Randomized Controlled Trials," Working Papers august_25.pdf, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies..
  • Angus Deaton & Nancy Cartwright, 2017. "Understanding and misunderstanding randomized controlled trials," Working Papers 2017-10, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing..
  • Angus Deaton & Nancy Cartwright, 2016. "Understanding and Misunderstanding Randomized Controlled Trials," NBER Working Papers 22595, National Bureau of Economic Research, Inc.
• Antoine A. Djogbenou, 2017. "Model Selection In Factor-augmented Regressions With Estimated Factors," Working Paper 1391, Economics Department, Queen's University.
• David L. Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series 2017-020, Board of Governors of the Federal Reserve System (U.S.), revised 24 Feb 2017.
  • David Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors: The Federal Reserve's Approach," RBA Research Discussion Papers rdp2017-01, Reserve Bank of Australia.
• Michael P Clements & Ana Beatriz Galvao, 2017. "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance icma-dp2017-01, Henley Business School, Reading University.
• Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
  • Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Online Appendix to "Financial conditions and density forecasts for US output and inflation"," Online Appendices 14-103, Review of Economic Dynamics.
• Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
  • Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Code and data files for "Financial conditions and density forecasts for US output and inflation"," Computer Codes 14-103, Review of Economic Dynamics.
• Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
  • Piergiorgio Alessandri & Haroon Mumtaz, 2013. "Financial conditions and density forecasts for US Output and inflation," Joint Research Papers 4, Centre for Central Banking Studies, Bank of England.
  • Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial conditions and density forecasts for US output and inflation," CReMFi Discussion Papers 1, CReMFi, School of Economics and Finance, QMUL.
  • Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Online Appendix to "Financial conditions and density forecasts for US output and inflation"," Online Appendices 14-103, Review of Economic Dynamics.
  • Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial Conditions and Density Forecasts for US Output and Inflation," Working Papers 715, Queen Mary University of London, School of Economics and Finance.
  • Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial Conditions and Density Forecasts for US Output and Inflation," Working Papers 715, Queen Mary University of London, School of Economics and Finance.
  • Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Code and data files for "Financial conditions and density forecasts for US output and inflation"," Computer Codes 14-103, Review of Economic Dynamics.
• Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2019. "Vulnerable Growth," American Economic Review, American Economic Association, vol. 109(4), pages 1263-1289, April.
  • Adrian, Tobias & Boyarchenko, Nina & Giannone, Domenico, 2016. "Vulnerable Growth," CEPR Discussion Papers 11583, C.E.P.R. Discussion Papers.
  • Nina Boyarchenko & Domenico Giannone & Tobias Adrian, 2017. "Vulnerable Growth," 2017 Meeting Papers 1317, Society for Economic Dynamics.
  • Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2018. "Vulnerable Growth," Liberty Street Economics 20180409, Federal Reserve Bank of New York.
• Simon M. Potter & Giorgio Topa & Wilbert van den Klaauv, 2017. "The Advantages of Probabilistic Survey Questions," Review of Economic Analysis, Rimini Centre for Economic Analysis, vol. 9(1), pages 1-32, June.
• Gustavo Rodríguez & Jorge Dávalos, 2017. "El Potencial de Comercio del Acuerdo Trans-Pacífico para el Perú, un enfoque Gravitacional (The Trans-Pacific Partnership Agreement (TPP) Trade Potential for Peru, a Gravity Model Approach)," Revista Internacional de Gestión del Conocimiento y la Tecnología (GECONTEC), Revista Internacional de Gestión del Conocimiento y la Tecnología (GECONTEC), vol. 5(2), pages 93-107, December.
• Fornaro, Paolo & Luomaranta, Henri & Saarinen, Lauri, 2017. "Nowcasting Finnish Turnover Indexes Using Firm-Level Data," ETLA Working Papers 46, The Research Institute of the Finnish Economy.
• Elettra Agliardi & Thomas Alexopoulos & Christian Cech, 2017. "On the relationship between GHGs and Global Temperature Anomalies: Multi-level rolling analysis and Copula calibration," Working Paper series 17-05, Rimini Centre for Economic Analysis.
• Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Businesss School.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2017. "Bayesian Compressed Vector Autoregressions," Working Paper series 17-32, Rimini Centre for Economic Analysis.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 2016_09, Business School - Economics, University of Glasgow.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103R, Brandeis University, Department of Economics and International Businesss School, revised Apr 2016.
• Fossati, Sebastian, 2017. "Testing for State-Dependent Predictive Ability," Working Papers 2017-9, University of Alberta, Department of Economics.
• Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2017. "Everything you always wanted to know about bitcoin modelling but were afraid to ask. Part 2," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 45, pages 5-28.
• Aganin, Artem, 2017. "Forecast comparison of volatility models on Russian stock market," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 48, pages 63-84.
• Makarov, Valerii & Bakhtizin, Albert & Sushko, Elena & Ageeva, Alina, 2017. "Simulation of the socio-economic system of the Eurasian continent using the agent-based models," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 48, pages 122-139.
• Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," Economic Research Papers 269087, University of Warwick - Department of Economics.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of FED'S view on inflation," Documents de Travail de l'OFCE 2018-03, Observatoire Francais des Conjonctures Economiques (OFCE).
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2018. "A Model of the Fed's View on Inflation," CEPR Discussion Papers 12564, C.E.P.R. Discussion Papers.
  • Thomas Hasenzagl & Fillipo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of the FED's view on inflation," Sciences Po publications 03, Sciences Po.
• Bartosz Uniejewski & Rafal Weron & Florian Ziel, 2017. "Variance stabilizing transformations for electricity spot price forecasting," HSC Research Reports HSC/17/01, Hugo Steinhaus Center, Wroclaw University of Technology.
• Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting: Part II — Probabilistic forecasting," Energy Economics, Elsevier, vol. 79(C), pages 171-182.
  • Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2017. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting," HSC Research Reports HSC/17/02, Hugo Steinhaus Center, Wroclaw University of Technology.
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2017. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Neural network models," HSC Research Reports HSC/17/03, Hugo Steinhaus Center, Wroclaw University of Technology.
• Dreher, Sandra & Eichfelder, Sebastian & Noth, Felix, 2017. "Predicting earnings and cash flows: The information content of losses and tax loss carryforwards," arqus Discussion Papers in Quantitative Tax Research 224, arqus - Arbeitskreis Quantitative Steuerlehre.
• Menden, Christian & Proaño, Christian R., 2017. "Dissecting the financial cycle with dynamic factor models," BERG Working Paper Series 126, Bamberg University, Bamberg Economic Research Group.
• Itkonen, Juha & Juvonen, Petteri, 2017. "Nowcasting the Finnish economy with a large Bayesian vector autoregressive model," BoF Economics Review 6/2017, Bank of Finland.
• Bettendorf, Timo & Bursian, Dirk, 2017. "Chow-Lin ×N: How adding a panel dimension can improve accuracy," Economics Letters, Elsevier, vol. 157(C), pages 5-9.
  • Bettendorf, Timo & Bursian, Dirk, 2017. "Chow-Lin x N: How adding a panel dimension can improve accuracy," Discussion Papers 12/2017, Deutsche Bundesbank.
• Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
  • Götz, Thomas B. & Knetsch, Thomas A., 2017. "Google data in bridge equation models for German GDP," Discussion Papers 18/2017, Deutsche Bundesbank.
• Mokinski, Frieder, 2017. "A severity function approach to scenario selection," Discussion Papers 34/2017, Deutsche Bundesbank.
• Jang, Tae-Seok & Sacht, Stephen, 2017. "Modeling consumer confidence and its role for expectation formation: A horse race," Economics Working Papers 2017-04, Christian-Albrechts-University of Kiel, Department of Economics.
• Simionescu, Mihaela, 2017. "The Influence of Brexit on the Foreign Direct Investment Projects and Inflows in the United Kingdom," GLO Discussion Paper Series 68, Global Labor Organization (GLO).
• Simionescu, Mihaela, 2017. "Prediction intervals for inflation and unemployment rate in Romania. A Bayesian approach," GLO Discussion Paper Series 82, Global Labor Organization (GLO).
• Doll, Jens & Rosenthal, Beatrice & Volkenand, Jonas & Hamella, Sandra, 2017. "Nowcasting des deutschen BIP," Weidener Diskussionspapiere 59, University of Applied Sciences Amberg-Weiden (OTH).
• Coupé, Tom, 2018. "Replicating "Predicting the present with Google trends" by Hyunyoung Choi and Hal Varian (The Economic Record, 2012)," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 12, pages 1-8.
  • Coupé, Tom, 2017. "Replicating "Predicting the present with Google trends" by Hyunyoung Choi and Hal Varian (The Economic Record, 2012)," Economics Discussion Papers 2017-76, Kiel Institute for the World Economy (IfW).
• Dreher, Sandra & Eichfelder, Sebastian & Noth, Felix, 2017. "Predicting earnings and cash flows: The information content of losses and tax loss carryforwards," IWH Discussion Papers 30/2017, Halle Institute for Economic Research (IWH).
• Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
  • Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
• Bershadskyy, Dmitri & Brautzsch, Hans-Ulrich & Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Wieschemeyer, Matthias & Zeddies, Götz, 2017. "Die mittelfristige wirtschaftliche Entwicklung in Deutschland für die Jahre 2017 bis 2022 und finanzpolitische Optionen einer neuen Bundesregierung," Konjunktur aktuell, Halle Institute for Economic Research (IWH), vol. 5(5), pages 138-145.
• Deschermeier, Philipp, 2017. "Bevölkerungsentwicklung in den deutschen Bundesländern bis 2035," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, vol. 44(3), pages 63-80.
• Haskamp, Ulrich, 2017. "Forecasting exchange rates: The time-varying relationship between exchange rates and Taylor rule fundamentals," Ruhr Economic Papers 704, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Haskamp, Ulrich, 2017. "Improving the forecasts of European regional banks' profitability with machine learning algorithms," Ruhr Economic Papers 705, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Prüser, Jan, 2017. "Forecasting US inflation using Markov dimension switching," Ruhr Economic Papers 710, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Roesel, Felix, 2017. "The causal effect of wrong-hand drive vehicles on road safety," Economics of Transportation, Elsevier, vol. 11, pages 15-22.
  • Roesel, Felix, 2017. "The causal effect of wrong-hand drive vehicles on road safety," CEPIE Working Papers 15/17, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
• Conrad, Christian, 2017. "When does information on forecast variance improve the performance of a combined forecast?," Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168200, Verein für Socialpolitik / German Economic Association.
• Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," CESifo Working Paper Series 6457, CESifo Group Munich.
  • Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
  • Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2019. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model," Jena Economic Research Papers 2019-006, Friedrich-Schiller-University Jena.
• Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
  • Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
• Ksenija Dumicic & Berislav Zmuk & Anita Ceh Casni, 2017. "Evaluating forecasting models for unemployment rates by gender in selected european countries," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 15(1), pages 16-35.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020. "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 285-310, April.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh K. Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Papers No 8/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017. "Do central banks respond timely to developments in the global economy?," CAMA Working Papers 2017-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Paper 2016/19, Norges Bank.
• Kapetanios, George & Price, Simon & Young, Garry, 2018. "A UK financial conditions index using targeted data reduction: Forecasting and structural identification," Econometrics and Statistics, Elsevier, vol. 7(C), pages 1-17.
  • Kapetanios, George & Price, Simon & Young, Garry, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," Bank of England working papers 699, Bank of England.
  • George Kapetanios & Simon Price & Garry Young, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," CAMA Working Papers 2017-58, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kapetanios, G & Price, SG & Young, G, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," Essex Finance Centre Working Papers 20328, University of Essex, Essex Business School.
• Thomas Goodwin & Jing Tian, 2017. "A state space approach to evaluate multi-horizon forecasts," CAMA Working Papers 2017-67, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Beili Zhu, 2017. "Forecasting the real price of oil under alternative specifications of constant and time-varying volatility," CAMA Working Papers 2017-71, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Dassios, Angelos & Zhao, Hongbiao, 2017. "Efficient simulation of clustering jumps with CIR intensity," LSE Research Online Documents on Economics 74205, London School of Economics and Political Science, LSE Library.
• Worawuth Kongsilp & Cesario Mateus, 2017. "Volatility risk and stock return predictability on global financial crises," China Finance Review International, Emerald Group Publishing, vol. 7(1), pages 33-66, February.
• Dilip Kumar & Srinivasan Maheswaran, 2017. "Value-at-risk and expected shortfall using the unbiased extreme value volatility estimator," Studies in Economics and Finance, Emerald Group Publishing, vol. 34(4), pages 506-526, October.
• Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(11), pages 1141-1152, November.
  • Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Documentos de Trabajo del ICAE 2017-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Asai, M. & McAleer, M.J., 2017. "Forecasting the Volatility of Nikkei 225 Futures," Econometric Institute Research Papers TI 2017-017/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Manabu Asai & Michael McAleer, 2017. "Forecasting the Volatility of Nikkei 225 Futures," Tinbergen Institute Discussion Papers 17-017/III, Tinbergen Institute.
• Rocío Elizondo, 2017. "Pronósticos de la estructura temporal de las tasas de interés en México con base en un modelo afín," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 32(2), pages 213-253.
• Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
• Kapetanios, George & Price, Simon & Young, Garry, 2018. "A UK financial conditions index using targeted data reduction: Forecasting and structural identification," Econometrics and Statistics, Elsevier, vol. 7(C), pages 1-17.
  • Kapetanios, George & Price, Simon & Young, Garry, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," Bank of England working papers 699, Bank of England.
  • Kapetanios, G & Price, SG & Young, G, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," Essex Finance Centre Working Papers 20328, University of Essex, Essex Business School.
  • George Kapetanios & Simon Price & Garry Young, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," CAMA Working Papers 2017-58, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Dorin JULA & Nicolae Marius JULA, 2017. "Mixed Sampling Panel Data Model for Regional Job Vacancies Forecasting," Eco-Economics Review, Ecological University of Bucharest, Economics Faculty and Ecology and Environmental Protection Faculty, vol. 3(1), pages 3-20, June.
• Caterina Astarita & Gaetano D'Adamo, 2017. "Inequality and Structural Reforms: Methodological Concerns and Lessons from Policy," European Economy - Discussion Papers 2015 - 071, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
• Matan Mayer & Martin Bechthold, 2017. "Development of policy metrics for circularity assessment in building assemblies," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2017(1-2), pages 57-84.
• Matej Nevrla, 2017. "Systemic Risk in the European Financial and Energy Sector: Dynamic Factor Copula Approach," Working Papers IES 2017/11, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2017.
• Jonathan Benchimol & Makram El-Shagi, 2017. "Forecast Performance in Times of Terrorism," CFDS Discussion Paper Series 2017/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
  • Jonathan Benchimol & Makram El-Shagi, 2019. "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers 2019.08, Bank of Israel.
• Makram El-Shagi & Yizhuang Zheng, 2017. "Money Demand in China: A Meta-Study," CFDS Discussion Paper Series 2017/3, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019. "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, vol. 57(3), pages 923-955, September.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2011. "Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria," Working Papers 20110301, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Working Papers 2017.06, Fondazione Eni Enrico Mattei.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2018. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Papers 1804.08315, arXiv.org.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," ETA: Economic Theory and Applications 253725, Fondazione Eni Enrico Mattei (FEEM).
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2016. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," MPRA Paper 76308, University Library of Munich, Germany.
• Hovick Shahnazarian & Martin Solberger & Erik Spånberg, 2017. "Forecasting and Analysing Corporate Tax Revenues in Sweden Using Bayesian VAR Models," Finnish Economic Papers, Finnish Economic Association, vol. 28(1), pages 50-74, Autumn.
• Michelle L. Barnes & Giovanni P. Olivei, 2017. "Financial variables and macroeconomic forecast errors," Working Papers 17-17, Federal Reserve Bank of Boston, revised 31 Oct 2017.
• Knotek, Edward S. & Zaman, Saeed, 2019. "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1708-1724.
  • Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland, revised 17 Mar 2017.
• Christian Garciga & Edward S. Knotek, 2017. "Forecasting GDP Growth with NIPA Aggregates," Working Papers (Old Series) 1708, Federal Reserve Bank of Cleveland, revised 19 May 2017.
• Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 2017-026, Federal Reserve Bank of St. Louis.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers (Old Series) 1715, Federal Reserve Bank of Cleveland, revised 25 Sep 2017.
  • Todd E Clark & Michael W McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," BIS Working Papers 667, Bank for International Settlements.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 171501, Federal Reserve Bank of Cleveland, revised 08 May 2018.
• Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland, revised 02 Nov 2017.
• Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 2017-026, Federal Reserve Bank of St. Louis.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 201715R, Federal Reserve Bank of Cleveland.
  • Todd E Clark & Michael W McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," BIS Working Papers 667, Bank for International Settlements.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers (Old Series) 1715, Federal Reserve Bank of Cleveland, revised 25 Sep 2017.
• Ayse Kabukcuoglu & Enrique Martínez-García & Mehmet Ali Soytas, 2017. "Exploring the Nexus between Inflation and Globalization under Inflation Targeting through the Lens of New Zealand’s Experience," Koç University-TUSIAD Economic Research Forum Working Papers 1709, Koc University-TUSIAD Economic Research Forum.
  • Ayse Kabukcuoglu & Enrique Martínez-García & Mehmet A. Soytas, 2017. "Exploring the Nexus Between Inflation and Globalization Under Inflation Targeting Through the Lens of New Zealand’s Experience," Globalization Institute Working Papers 308, Federal Reserve Bank of Dallas, revised 01 Mar 2017.
• Alessandro Barbarino & Efstathia Bura, 2017. "A Unified Framework for Dimension Reduction in Forecasting," Finance and Economics Discussion Series 2017-004, Board of Governors of the Federal Reserve System (U.S.).
• Christopher A. Hollrah & Steven A. Sharpe & Nitish R. Sinha, 2017. "What's the Story? A New Perspective on the Value of Economic Forecasts," Finance and Economics Discussion Series 2017-107, Board of Governors of the Federal Reserve System (U.S.), revised 20 Aug 2018.
• Pablo Guerron-Quintana & Molin Zhong, 2017. "Macroeconomic Forecasting in Times of Crises," Finance and Economics Discussion Series 2017-018, Board of Governors of the Federal Reserve System (U.S.), revised 31 Jan 2017.
• David Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors: The Federal Reserve's Approach," RBA Research Discussion Papers rdp2017-01, Reserve Bank of Australia.
  • David L. Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series 2017-020, Board of Governors of the Federal Reserve System (U.S.), revised 24 Feb 2017.
• Berge, Travis J., 2018. "Understanding survey-based inflation expectations," International Journal of Forecasting, Elsevier, vol. 34(4), pages 788-801.
  • Travis J. Berge, 2017. "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series 2017-046, Board of Governors of the Federal Reserve System (U.S.).
• Todd Prono, 2017. "Regular Variation of Popular GARCH Processes Allowing for Distributional Asymmetry," Finance and Economics Discussion Series 2017-095, Board of Governors of the Federal Reserve System (U.S.).
• Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
  • Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, Department of Economics, Research Program on Forecasting.
  • Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.), revised 06 Jan 2017.
• Thomas R. Cook & Aaron Smalter Hall, 2017. "Macroeconomic Indicator Forecasting with Deep Neural Networks," Research Working Paper RWP 17-11, Federal Reserve Bank of Kansas City, revised 04 Sep 2017.
  • Thomas Cook, 2019. "Macroeconomic Indicator Forecasting with Deep Neural Networks," 2019 Meeting Papers 402, Society for Economic Dynamics.
• Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers (Old Series) 1715, Federal Reserve Bank of Cleveland, revised 25 Sep 2017.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 2017-026, Federal Reserve Bank of St. Louis.
  • Todd E Clark & Michael W McCracken & Elmar Mertens, 2017. "