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

2021

• Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
• George-Marios Angeletos & Zhen Huo, 2021. "Myopia and Anchoring," American Economic Review, American Economic Association, vol. 111(4), pages 1166-1200, April.
• Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO," WORking papers in Management Science (WORMS) WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Weronika Nitka & Tomasz Serafin & Dimitrios Sotiros, 2021. "Forecasting Electricity Prices: Autoregressive Hybrid Nearest Neighbors (ARHNN) method," WORking papers in Management Science (WORMS) WORMS/21/06, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Kin G. Olivares & Cristian Challu & Grzegorz Marcjasz & Rafal Weron & Artur Dubrawski, 2021. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," WORking papers in Management Science (WORMS) WORMS/21/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Константин Орлов // Konstantin Orlov, 2021. "Построение большой байесовской авторегрессионной модели для Казахстана // Building a Large Bayesian Vector Autoregression Model for Kazakhstan," Working Papers #2021-1, National Bank of Kazakhstan.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanovic, Dalibor, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers 15867, C.E.P.R. Discussion Papers.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers 2021s-09, CIRANO.
• Fiaschi, Davide & Tealdi, Cristina, 2021. "A General Methodology to Measure Labour Market Dynamics," IZA Discussion Papers 14254, Institute of Labor Economics (IZA).
  • Davide Fiaschi & Cristina Tealdi, 2021. "A general methodology to measure labour market dynamics," Papers 2104.01097, arXiv.org.
• Martina Makarieva, 2021. "Yield curve modelling and forecasting in an undeveloped financial market: The case of Bulgaria," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 61-83,84-10.
• Tatjana Dahlhaus & Julia Schaumburg & Tatevik Sekhposyan, 2021. "Networking the Yield Curve: Implications for Monetary Policy," Staff Working Papers 21-4, Bank of Canada.
• Corinna Ghirelli & María Gil & Samuel Hurtado & Alberto Urtasun, 2021. "Relación entre las medidas de contención de la pandemia, la movilidad y la actividad económica," Occasional Papers 2109, Banco de España;Occasional Papers Homepage.
• Corinna Ghirelli & María Gil & Samuel Hurtado & Alberto Urtasun, 2021. "The relationship between pandemic containment measures, mobility and economic activity," Occasional Papers 2109, Banco de España;Occasional Papers Homepage.
• Valentina Aprigliano & Guerino Ardizzi & Alessia Cassetta & Alessandro Cavallero & Simone Emiliozzi & Alessandro Gambini & Nazzareno Renzi & Roberta Zizza, 2021. "Exploiting payments to track Italian economic activity: the experience at Banca d’Italia," Questioni di Economia e Finanza (Occasional Papers) 609, Bank of Italy, Economic Research and International Relations Area.
• Cristina Angelico & Juri Marcucci & Marcello Miccoli & Filippo Quarta, 2021. "Can we measure inflation expectations using Twitter?," Temi di discussione (Economic working papers) 1318, Bank of Italy, Economic Research and International Relations Area.
• De Polis, Andrea & Delle Monache, Davide & Petrella, Ivan, 2020. "Modeling and Forecasting Macroeconomic Downside Risk," CEPR Discussion Papers 15109, C.E.P.R. Discussion Papers.
  • Delle Monache, Davide & De Polis, Andrea & Petrella, Ivan, 2021. "Modeling and forecasting macroeconomic downside risk," Temi di discussione (Economic working papers) 1324, Bank of Italy, Economic Research and International Relations Area.
  • Delle-Monache, Davide & De-Polis, Andrea & Petrella, Ivan, 2020. "Modelling and Forecasting Macroeconomic Downside Risk," EMF Research Papers 34, Economic Modelling and Forecasting Group.
• Rojas-Bernal, Alejandro & Villamizar-Villegas, Mauricio, 2021. "Pricing the exotic: Path-dependent American options with stochastic barriers," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(1).
  • Alejandro Rojas-Bernal & Mauricio Villamizar-Villegas, 2021. "Pricing the exotic: Path-dependent American options with stochastic barriers," Borradores de Economia 1156, Banco de la Republica de Colombia.
• Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
• J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
  • J. James Reade & Carl Singleton & Alasdair Brown, 2019. "Evaluating Strange Forecasts: The Curious Case of Football Match Scorelines," Economics Discussion Papers em-dp2019-18, Department of Economics, University of Reading.
• Joseph, Andreas & Kalamara, Eleni & Kapetanios, George & Potjagailo, Galina, 2021. "Forecasting UK inflation bottom up," Bank of England working papers 915, Bank of England.
• Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2021. "The bias and efficiency of the ECB inflation projections: a State dependent analysis," Research Discussion Papers 7/2021, Bank of Finland.
• Takuji Kawamoto & Takashi Nakazawa & Yui Kishaba & Kohei Matsumura & Jouchi Nakajima, 2021. "Supplementary Paper Series for the "Assessment" (2): Estimating Effects of Expansionary Monetary Policy since the Introduction of Quantitative and Qualitative Monetary Easing (QQE) Using the," Bank of Japan Working Paper Series 21-E-4, Bank of Japan.
• Mueller, Hannes Felix & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
  • Mueller, H. & Rauh, C., 2021. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2103, Faculty of Economics, University of Cambridge.
  • Hannes Mueller & Christopher Rauh, 2021. "The Hard Problem of Prediction for Conflict Prevention," Working Papers 1244, Barcelona Graduate School of Economics.
  • 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.
  • Hannes Mueller & Christopher Rauh, 2019. "The Hard Problem of Prediction for Conflict Prevention," Cahiers de recherche 02-2019, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  • Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
• Ding, Y., 2021. "Augmented Real-Time GARCH: A Joint Model for Returns, Volatility and Volatility of Volatility," Cambridge Working Papers in Economics 2112, Faculty of Economics, University of Cambridge.
• Olatunji Abdul Shobande & Oladimeji Tomiwa Shodipe, 2021. "Monetary Policy Interdependency in Fisher Effect: A Comparative Evidence," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(1), pages 203-226.
• Carlos Castro-Iragorri & Juan Felipe Peña & Cristhian Rodríguez, 2021. "A Segmented and Observable Yield Curve for Colombia," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(2), pages 179-200.
• Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
  • Felix Haase & Matthias Neuenkirch, 2021. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," CESifo Working Paper Series 8828, CESifo.
  • Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Working Paper Series 2020-03, University of Trier, Research Group Quantitative Finance and Risk Analysis.
• Florian Huber & Gary Koop & Luca Onorante & Michael Pfarrhofer & Josef Schreiner, 2020. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Papers 2008.12706, arXiv.org, revised Dec 2020.
  • Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Working Paper Series 2510, European Central Bank.
  • Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Working Papers 2021-01, Joint Research Centre, European Commission (Ispra site).
• Ferrari, Massimo & Le Mezo, Helena, 2021. "Text-based recession probabilities," Working Paper Series 2516, European Central Bank.
• Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
• 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.
  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021. "Economic predictions with big data: the illusion of sparsity," Working Paper Series 2542, European Central Bank.
  • 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.
  • 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.
• Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
• Dimitrios Kartsonakis Mademlis & Nikolaos Dritsakis, 2021. "Volatility Forecasting using Hybrid GARCH Neural Network Models: The Case of the Italian Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 11(1), pages 49-60.
• Ernie Hendrawaty & Rialdi Azhar & Fajrin Satria Dwi Kesumah & Sari Indah Oktanti Sembiring & Mega Metalia, 2021. "Modelling and Forecasting Crude Oil Prices during COVID-19 Pandemic," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 149-154.
• Santiago Gallón & Jorge Barrientos, 2021. "Forecasting the Colombian Electricity Spot Price under a Functional Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 67-74.
• Hasan, Mudassar & Arif, Muhammad & Naeem, Muhammad Abubakr & Ngo, Quang-Thanh & Taghizadeh–Hesary, Farhad, 2021. "Time-frequency connectedness between Asian electricity sectors," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 208-224.
• Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2021. "Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility," Discussion paper series HIAS-E-104, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
• Ozana Nadoveza Jelić & Rafael Ravnik, 2021. "Introducing Policy Analysis Croatian MAcroecoNometric Model (PACMAN)," Surveys 41, The Croatian National Bank, Croatia.
• Luigi Longo & Massimo Riccaboni & Armando Rungi, 2021. "A Neural Network Ensemble Approach for GDP Forecasting," Working Papers 02/2021, IMT Institute for Advanced Studies Lucca, revised Mar 2021.
• Crespo-Cuaresma, Jesus & Fortin, Ines & Hlouskova, Jaroslava & Obersteiner, Michael, 2021. "Regime-dependent commodity price dynamics: A predictive analysis," IHS Working Paper Series 28, Institute for Advanced Studies.
• David Conaly Martínez Vázquez & Christian Bucio Pacheco & Alejandra Cabello Rosales, 2021. "Proyección Markoviana para 2020 y 2021 de las Calificaciones Corporativas en México," 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. 16(1), pages 1-21, Enero - M.
• Gustavo Cabrera González & Adrián de León Arias, 2021. "Dinámica anticipada del PIB trimestral en México ante shocks negativos derivados de factores debidos a la crisis sanitaria del covid-19," 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. 16(1), pages 1-15, Enero - M.
• Rodrigo A. Morales Fernández Rafaelly & Roberto J. Santillán-Salgado, 2021. "Oil price effect on sectoral stock returns: A conditional covariance and correlation approach for Mexico," 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. 16(1), pages 1-15, Enero - M.
• David Conaly Martínez Vázquez & Christian Bucio Pacheco & Alejandra Cabello Rosales, 2021. "Proyección Markoviana para 2020 y 2021 de las Calificaciones Corporativas en México," 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. 16(1), pages 1-21, Enero - M.
• Paolo Riccardo Morganti, 2021. "Extreme Value Theory and Auction Models," 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. 16(2), pages 1-15, Abril - J.
• Paolo Riccardo Morganti, 2021. "Extreme Value Theory and Auction Models," 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. 16(2), pages 1-15, Abril - J.
• Emerson Abraham Jackson, 2021. "Forecasting COVID-19 Daily Contraction in Sierra Leone with Implications for Policy Formulation," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 8(1), pages 29-43, January.
• Sergio Navarro Palacios, 2021. "Limitaciones de las metodologías basadas en opiniones de expertos. El caso de la automatización del empleo," Working Papers. Serie EC 2021-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
• Davide Fiaschi & Cristina Tealdi, 2021. "A general methodology to measure labour market dynamics," Papers 2104.01097, arXiv.org.
  • Fiaschi, Davide & Tealdi, Cristina, 2021. "A General Methodology to Measure Labour Market Dynamics," IZA Discussion Papers 14254, Institute of Labor Economics (IZA).
• Rabia Özdemir & Münevver Turanlı, 2021. "Comparison of machine learning classification algorithms for purchasing forecast," JOURNAL OF LIFE ECONOMICS, Rating Academy, vol. 8(1), pages .59-68, January.
• Florian Huber & Gary Koop & Luca Onorante & Michael Pfarrhofer & Josef Schreiner, 2020. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Papers 2008.12706, arXiv.org, revised Dec 2020.
  • Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Working Papers 2021-01, Joint Research Centre, European Commission (Ispra site).
  • Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Working Paper Series 2510, European Central Bank.
• Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2021. "Efficient Combined Estimation under Structural Breaks," Working Papers 202101, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2021. "Efficient Combined Estimation under Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202107, University of Kansas, Department of Economics, revised Jan 2021.
• Luiz Renato Lima & Lucas Lúcio Godeiro & Mohammed Mohsin, 2021. "Time-Varying Dictionary and the Predictive Power of FED Minutes," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 149-181, January.
• Indranil Ghosh & Manas K. Sanyal & R. K. Jana, 2021. "Co-movement and Dynamic Correlation of Financial and Energy Markets: An Integrated Framework of Nonlinear Dynamics, Wavelet Analysis and DCC-GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 503-527, February.
• Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
• Alfred Michael Dockery & Mark N. Harris & Nicholas Holyoak & Ranjodh B. Singh, 2021. "A methodology for projecting sparse populations and its application to remote Indigenous communities," Journal of Geographical Systems, Springer, vol. 23(1), pages 37-61, January.
• Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2021. "High-Frequency Volatility Forecasting of US Housing Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 62(2), pages 283-317, February.
  • 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.
• Boriss Siliverstovs, 2021. "Gauging the Effect of Influential Observations on Measures of Relative Forecast Accuracy in a Post-COVID-19 Era: Application to Nowcasting Euro Area GDP Growth," Working Papers 2021/01, Latvijas Banka.
• Yoonseok Lee & Donggyu Sul, 2021. "Depth-Weighted Forecast Combination: Application to COVID-19 Cases," Center for Policy Research Working Papers 238, Center for Policy Research, Maxwell School, Syracuse University.
• Kadir Özen & Dilem Yıldırım, 2021. "Application of Bagging in Day-Ahead Electricity Price Forecasting and Factor Augmentation," ERC Working Papers 2101, ERC - Economic Research Center, Middle East Technical University, revised Apr 2021.
• Andres Algaba & Samuel Borms & Kris Boudt & Brecht Verbeken, 2021. "Daily news sentiment and monthly surveys: A mixed–frequency dynamic factor model for nowcasting consumer confidence," Working Paper Research 396, National Bank of Belgium.
• Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2021. "Smooth Robust Multi-Horizon Forecasts," Economics Papers 2021-W01, Economics Group, Nuffield College, University of Oxford.
• Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2020. "Smooth Robust Multi-Horizon Forecasts," Working Papers 2020-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2021. "Smooth Robust Multi-Horizon Forecasts," Economics Papers 2021-W01, Economics Group, Nuffield College, University of Oxford.
• Gerhard Fenz & Helmut Stix, 2021. "Monitoring the economy in real time with the weekly OeNB GDP indicator: background, experience and outlook," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/20-Q1/, pages 17-40.
• Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021. "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, vol. 96(C), pages 445-454.
• Frömmel, Michael & Midiliç, Murat, 2021. "Daily currency interventions in an emerging market: Incorporating reserve accumulation to the reaction function," Economic Modelling, Elsevier, vol. 97(C), pages 461-476.
• Mora-Valencia, Andrés & Rodríguez-Raga, Santiago & Vanegas, Esteban, 2021. "Skew index: Descriptive analysis, predictive power, and short-term forecast," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
• Ouyang, Zi-sheng & Yang, Xi-te & Lai, Yongzeng, 2021. "Systemic financial risk early warning of financial market in China using Attention-LSTM model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
• Lyu, Yifei & Nie, Jun & Yang, Shu-Kuei X., 2021. "Forecasting US economic growth in downturns using cross-country data," Economics Letters, Elsevier, vol. 198(C).
• Aguilar, Pablo & Ghirelli, Corinna & Pacce, Matías & Urtasun, Alberto, 2021. "Can news help measure economic sentiment? An application in COVID-19 times," Economics Letters, Elsevier, vol. 199(C).
  • Pablo Aguilar & Corinna Ghirelli & Matías Pacce & Alberto Urtasun, 2020. "Can news help measure economic sentiment? An application in COVID-19 times," Working Papers 2027, Banco de España.
• Qiu, Yue, 2021. "Complete subset least squares support vector regression," Economics Letters, Elsevier, vol. 200(C).
• Li, Yiyun & Law, Keith K.F., 2021. "Systematic risk in pairs trading and dynamic parameterization," Economics Letters, Elsevier, vol. 202(C).
• Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
  • 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.
• Korolev, Ivan, 2021. "Identification and estimation of the SEIRD epidemic model for COVID-19," Journal of Econometrics, Elsevier, vol. 220(1), pages 63-85.
• Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
• Pathak, Parag A. & Shi, Peng, 2021. "How well do structural demand models work? Counterfactual predictions in school choice," Journal of Econometrics, Elsevier, vol. 222(1), pages 161-195.
• Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
  • Matteo Mogliani & Anna Simoni, 2019. "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers 1903.08025, arXiv.org, revised Jun 2020.
  • Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
  • Matteo Mogliani, 2019. "Bayesian MIDAS penalized regressions: estimation, selection, and prediction," Working papers 713, Banque de France.
• Vázquez, Jesús & Aguilar, Pablo, 2021. "Adaptive learning with term structure information," European Economic Review, Elsevier, vol. 134(C).
• Eckert, Florian & Hyndman, Rob J. & Panagiotelis, Anastasios, 2021. "Forecasting Swiss exports using Bayesian forecast reconciliation," European Journal of Operational Research, Elsevier, vol. 291(2), pages 693-710.
  • 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.
• Chiang, I-Hsuan Ethan & Liao, Yin & Zhou, Qing, 2021. "Modeling the cross-section of stock returns using sensible models in a model pool," Journal of Empirical Finance, Elsevier, vol. 60(C), pages 56-73.
• Baum, Christopher F. & Zerilli, Paola & Chen, Liyuan, 2021. "Stochastic volatility, jumps and leverage in energy and stock markets: Evidence from high frequency data," Energy Economics, Elsevier, vol. 93(C).
  • 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.
• Dai, Zhifeng & Zhou, Huiting & Kang, Jie & Wen, Fenghua, 2021. "The skewness of oil price returns and equity premium predictability," Energy Economics, Elsevier, vol. 94(C).
• Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(C).
  • 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.
• Bennedsen, Mikkel & Hillebrand, Eric & Koopman, Siem Jan, 2021. "Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors," Energy Economics, Elsevier, vol. 96(C).
• Bouri, Elie & Demirer, Riza & Gupta, Rangan & Wohar, Mark E., 2021. "Gold, platinum and the predictability of bond risk premia," Finance Research Letters, Elsevier, vol. 38(C).
  • 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.
• Chen, Wen & Minney, Aaron & Toscas, Peter & Koo, Bonsoo & Zhu, Zili & Pantelous, Athanasios A., 2021. "Personalised drawdown strategies and partial annuitisation to mitigate longevity risk," Finance Research Letters, Elsevier, vol. 39(C).
• Hoang, Khoa & Cannavan, Damien & Huang, Ronghong & Peng, Xiaowen, 2021. "Predicting stock returns with implied cost of capital: A partial least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
• Knill, April M. & Lee, Bong Soo & Ang, James, 2021. "Leveling of the playing field and corporate financing patterns around the world," Global Finance Journal, Elsevier, vol. 47(C).
• Battiston, Pietro & Gamba, Simona, 2021. "COVID-19: R0 is lower where outbreak is larger," Health Policy, Elsevier, vol. 125(2), pages 141-147.
  • 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.
• Buonanno, Paolo & Puca, Marcello, 2021. "Using newspaper obituaries to “nowcast” daily mortality: Evidence from the Italian COVID-19 hot-spots," Health Policy, Elsevier, vol. 125(4), pages 535-540.
• Mammen, Enno & Martínez-Miranda, María Dolores & Nielsen, Jens Perch & Vogt, Michael, 2021. "Calendar effect and in-sample forecasting," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 31-52.
• Urom, Christian & Ndubuisi, Gideon & Ozor, Jude, 2021. "Economic activity, and financial and commodity markets’ shocks: An analysis of implied volatility indexes," International Economics, Elsevier, vol. 165(C), pages 51-66.
• Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021. "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, vol. 37(1), pages 360-377.
  • 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.
• Daniele Bianchi & Matthias Büchner & Andrea Tamoni & Stijn Van Nieuwerburgh, 2021. "Bond Risk Premiums with Machine Learning," Review of Financial Studies, Society for Financial Studies, vol. 34(2), pages 1046-1089.
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  • 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.
• Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," Working Papers 2021-02, Federal Reserve Bank of Cleveland.
• Robert W. Rich & Joseph Tracy, 2021. "All Forecasters Are Not the Same: Time-Varying Predictive Ability across Forecast Environments," Working Papers 202106, Federal Reserve Bank of Cleveland.
• Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," Working Papers 202108, Federal Reserve Bank of Cleveland.
• Nadiia Shapovalenko, 2021. "A BVAR Model for Forecasting Ukrainian Inflation," IHEID Working Papers 05-2021, Economics Section, The Graduate Institute of International Studies.
• Julia Kielmann & Hans Manner & Aleksey Min, 2021. "Stock Market Returns and Oil Price Shocks: A CoVaR Analysis based on Dynamic Vine Copula Models," Graz Economics Papers 2021-01, University of Graz, Department of Economics.
• Guoyou Yue, 2021. "Forecasting the Logistics Demand of Guangxi Beibu Gulf Port," GATR Journals gjbssr587, Global Academy of Training and Research (GATR) Enterprise.
• Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," Working Papers 2021-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• Marcel Aloy & Floris Laly & Sébastien Laurent & Christelle Lecourt, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," Dynamic Modeling and Econometrics in Economics and Finance, in: Gilles Dufrénot & Takashi Matsuki (ed.), Recent Econometric Techniques for Macroeconomic and Financial Data, pages 229-264, Springer.
  • Marcel Aloy & Floris Laly & Sébastien Laurent & Christelle Lecourt, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," Post-Print hal-03103717, HAL.
• Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.
• Lyócsa, Štefan & Baumöhl, Eduard & Vŷrost, Tomáš, 2021. "YOLO trading: Riding with the herd during the GameStop episode," EconStor Preprints 230679, ZBW - Leibniz Information Centre for Economics.
• Bubalo, Branko, 2021. "Airport Capacity and Performance in Europe - A study of transport economics, service quality and sustainability," EconStor Theses, ZBW - Leibniz Information Centre for Economics, number 229442.
• Hügle, Dominik, 2021. "The decision to enrol in higher education," Discussion Papers 2021/8, Free University Berlin, School of Business & Economics.
• Stamer, Vincent, 2021. "Thinking outside the container: A machine learning approach to forecasting trade flows," Kiel Working Papers 2179, Kiel Institute for the World Economy (IfW).
• Milivojevic, Lazar & Tatar, Balint, 2021. "Fixed exchange rate - a friend or foe of labor cost adjustments?," IMFS Working Paper Series 152, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).

2020

• 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.
• Andrea Bucci, 2020. "Cholesky–ANN models for predicting multivariate realized volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 865-876, September.
  • Bucci, Andrea, 2019. "Cholesky-ANN models for predicting multivariate realized volatility," MPRA Paper 95137, University Library of Munich, Germany.
• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2020. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 934-943, September.
  • 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.
• Elie Bouri & Riza Demirer & Rangan Gupta & Xiaojin Sun, 2020. "The predictability of stock market volatility in emerging economies: Relative roles of local, regional, and global business cycles," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 957-965, September.
  • 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 Güney & M. Yilmaz, 2020. "Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 966-985, September.
  • 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.
• Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
• Galvao, Ana Beatriz & Mitchell, James, 2020. "Real-Time Perceptions of Historical GDP Data Uncertainty," EMF Research Papers 35, Economic Modelling and Forecasting Group.
• Clements, Michael P. & Galvao, Ana Beatriz, 2020. "Density Forecasting with BVAR Models under Macroeconomic Data Uncertainty," EMF Research Papers 36, Economic Modelling and Forecasting Group.
• Galvao, Ana Beatriz & Owyang, Michael, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," EMF Research Papers 38, 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.
• Berta, Paolo & Lovaglio, Pietro Giorgio & Paruolo, Paolo & Verzillo, Stefano, 2020. "Real Time Forecasting of Covid-19 Intensive Care Units demand," Working Papers 2020-08, Joint Research Centre, European Commission (Ispra site).
  • Berta, P. & Lovaglio, P.G. & Paruolo, P. & Verzillo, S., 2020. "Real Time Forecasting of Covid-19 Intensive Care Units demand," Health, Econometrics and Data Group (HEDG) Working Papers 20/16, HEDG, c/o Department of Economics, University of York.
• Perone, G., 2020. "Comparison of ARIMA, ETS, NNAR and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy," Health, Econometrics and Data Group (HEDG) Working Papers 20/18, HEDG, c/o Department of Economics, University of York.
• Sriubaite, I. & Harris, A. & Jones, A.M. & Gabbe, B., 2020. "Economic Consequences of Road Traffic Injuries. Application of the Super Learner algorithm," Health, Econometrics and Data Group (HEDG) Working Papers 20/20, HEDG, c/o Department of Economics, University of York.
• Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2020. "Testing the predictive accuracy of COVID-19 forecasts," Discussion Papers 20/10, 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.
  • 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.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Sciences Po publications 06/2020, Sciences Po.
• Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.
• Opiła, Janusz, 2020. "Employing of Extended Characteristic Surface Model for Forecasting of Demand in Tourism," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020, pages 60-73, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
• 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.
• Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
• Dieckelmann, Daniel, 2020. "Cross-border lending and the international transmission of banking crises," Discussion Papers 2020/13, Free University Berlin, School of Business & Economics.
• Fischer, Benjamin & Hügle, Dominik, 2020. "The private and fiscal returns to higher education: A simulation approach for a young German cohort," Discussion Papers 2020/21, Free University Berlin, School of Business & Economics.
• Hügle, Dominik, 2020. "Higher education funding in Germany: A distributional lifetime perspective," Discussion Papers 2021/1, Free University Berlin, School of Business & Economics.
• 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.
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Wieschemeyer, Matthias & Zeddies, Götz, 2020. "Hohes öffentliches Defizit nicht nur wegen Corona: Mittelfristige Handlungsmöglichkeiten für den Staat," Konjunktur aktuell, Halle Institute for Economic Research (IWH), vol. 8(4), pages 150-161.
• Reh, Laura & Krüger, Fabian & Liesenfeld, Roman, 2020. "Predicting the global minimum variance portfolio," Working Paper Series in Economics 141, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
• Foltas, Alexander, 2020. "Testing investment forecast efficiency with textual data," Working Papers 19, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Foltas, Alexander & Pierdzioch, Christian, 2020. "On the efficiency of German growth forecasts: An empirical analysis using quantile random forests," Working Papers 21, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Foltas, Alexander & Pierdzioch, Christian, 2020. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Working Papers 22, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Müller, Karsten, 2020. "German forecasters' narratives: How informative are German business cycle forecast reports?," Working Papers 23, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Behrens, Christoph, 2020. "German trade forecasts since 1970: An evaluation using the panel dimension," Working Papers 26, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• 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.
• Berislav Žmuk & Hrvoje Jošiæ, 2020. "Forecasting stock market indices using machine learning algorithms," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 18(4), pages 471-489.
• Simon C Smith & George Bulkley & David S Leslie, 2020. "Equity Premium Forecasts with an Unknown Number of Structural Breaks [Tests for Parameter Instability and Structural Change with Unknown Change Point]," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(1), pages 59-94.
• Johanna F Ziegel & Fabian Krüger & Alexander Jordan & Fernando Fasciati, 2020. "Robust Forecast Evaluation of Expected Shortfall [Designing Realized Kernels to Measure the Ex Post Variation of Equity Prices in the Presence of Noise]," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(1), pages 95-120.
• Fabrizio Cipollini & Giampiero M Gallo & Alessandro Palandri, 2020. "Realized Variance Modeling: Decoupling Forecasting from Estimation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(3), pages 532-555.
  • Fabrizio Cipollini & Giampiero M Gallo & Alessandro Palandri, 0. "Realized Variance Modeling: Decoupling Forecasting from Estimation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(3), pages 532-555.
  • 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".
• Axel Bücher & Peter N Posch & Philipp Schmidtke, 2020. "Using the Extremal Index for Value-at-Risk Backtesting," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(3), pages 556-584.
• Elena Andreou & Patrick Gagliardini & Eric Ghysels & Mirco Rubin, 2020. "Mixed-Frequency Macro–Finance Factor Models: Theory and Applications," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(3), pages 585-628.
• 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," Economics and Business Letters, Oviedo University Press, vol. 9(3), pages 167-177.
  • 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.
• 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.
• Cevallos-Valdiviezo, Holger & Rodríguez-Cristiansen, Ariana & Valdiviezo-Valenzuela, Patricia & Arévalo-Avecillas, Danny & Padilla-Lozano, Carmen, 2020. "Predicción del nivel de cosecha de camarón blanco: el caso de una pequeña camaronera en la parroquia Tenguel del cantón Guayaquil, Ecuador || Prediction of white shrimp harvest: the case of a small sh," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 30(1), pages 227-257, December.
• Harris Ntantanis & Lawrence Pohlman, 2020. "Market implied GDP," Journal of Asset Management, Palgrave Macmillan, vol. 21(7), pages 636-646, December.
• Andrés Berenguer & Luis Gandarias & Álvaro Arévalo, 2020. "Singular spectrum analysis for modelling the hard-to-model risk factors," Risk Management, Palgrave Macmillan, vol. 22(3), pages 178-191, September.
• Wittwer, Glyn & Anderson, Kym, 2020. "A Model of Global Beverage Markets," Journal of Wine Economics, Cambridge University Press, vol. 15(3), pages 330-354, August.
  • Anderson, Kym & Wittwer, Glyn, 2020. "A Model of Global Beverage Markets," CEPR Discussion Papers 14387, C.E.P.R. Discussion Papers.
  • Glyn Wittwer & Kym Anderson, 2020. "A model of global beverage markets," Departmental Working Papers 2020-05, The Australian National University, Arndt-Corden Department of Economics.
  • 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.
• Roberto S. Mariano & Suleyman Ozmucur, 2020. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)Abstract: We study how the separation of time and risk preferences ," PIER Working Paper Archive 20-029, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Robust Forecasting," Papers 2011.03153, arXiv.org, revised Dec 2020.
  • Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Robust Forecasting," PIER Working Paper Archive 20-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," Working Papers 20-26, Federal Reserve Bank of Philadelphia.
  • Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Tadeusz Kufel, 2020. "ARIMA-based forecasting of the dynamics of confirmed Covid-19 cases for selected European countries," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 15(2), pages 181-204, June.
• Michael Hanias & Stefanos Tsakonas & Lykourgos Magafas & Eleftherios I. Thalassinos & Loukas Zachilas, 2020. "Deterministic chaos and forecasting in Amazon’s share prices," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 15(2), pages 253-273, June.
• 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.
• 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.
  • 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.
• 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.
  • Razzak, Weshah, 2020. "The Dynamic of COVID-19 New Infections under Different Stringent Policies," MPRA Paper 100451, University Library of Munich, Germany.
  • Weshah Razzak, 2020. "The Dynamic of COVID-19 New Infections under Different Stringent Policies," EERI Research Paper Series EERI RP 2020/07, Economics and Econometrics Research Institute (EERI), Brussels.
• 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.
• Juan R. Hernández, 2020. "Covered Interest Parity: A Stochastic Volatility Approach to Estimate the Neutral Band," Working Papers 2020-02, Banco de México.
  • Hernández, Juan R., 2020. "Covered Interest Parity: A Stochastic Volatility Approach to Estimate the Neutral Band," MPRA Paper 100744, University Library of Munich, Germany.
• Bas B. Bakker & Manuk Ghazanchyan & Alex Ho & Vibha Nanda, 2020. "The Lack of Convergence of Latin-America Compared with CESEE: Is Low Investment to Blame?," IMF Working Papers 2020/098, International Monetary Fund.
  • Bakker, Bas & Ghazanchyan, Manuk & Ho, Alex & Nanda, Vibha, 2020. "The Lack of Convergence of Latin-America Compared with CESEE: Is Low Investment to Blame?," MPRA Paper 101287, University Library of Munich, Germany.
• Ahumada, Hildegart & Espina, Santos & Navajas, Fernando H., 2020. "COVID-19 with uncertain phases: estimation issues with an illustration for Argentina," MPRA Paper 101466, University Library of Munich, Germany.
• Van, Germinal, 2020. "Property Rights and Economic Growth in Africa: An Econometric Analysis," MPRA Paper 101681, University Library of Munich, Germany.
• Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
• Sucarrat, Genaro, 2020. "Identification of Volatility Proxies as Expectations of Squared Financial Return," MPRA Paper 101953, University Library of Munich, Germany.
• Yang, Bill Huajian & Yang, Jenny & Yang, Haoji, 2020. "Modeling Portfolio Loss by Interval Distributions," MPRA Paper 102219, University Library of Munich, Germany.
• Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
  • Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," MPRA Paper 102315, University Library of Munich, Germany.
• Fantazzini, Dean, 2020. "Discussing copulas with Sergey Aivazian: a memoir," MPRA Paper 102317, University Library of Munich, Germany.
• Polterovich, Victor & Denisova, Irina & Shakleina, Marina & Bogatova, Irina & Vartanov, Sergey & Turdyeva, Natalya & Chubarova, Tatiana, 2020. "Социально-Экономические Детерминанты Болезни Паркинсона Для Развитых И Развивающихся Стран [Socioeconomic determinants of Parkinson's disease for developed and developing countries]," MPRA Paper 103126, University Library of Munich, Germany.
• Van, Germinal G., 2020. "Modeling and Forecasting Economic Growth in Sub-Saharan Africa in the Post-Covid Era," MPRA Paper 103153, University Library of Munich, Germany.
• Dimitrakopoulos, Stefanos & Tsionas, Mike G. & Aknouche, Abdelhakim, 2020. "Ordinal-response models for irregularly spaced transactions: A forecasting exercise," MPRA Paper 103250, University Library of Munich, Germany, revised 01 Oct 2020.
• Poblete-Cazenave, Miguel & Pachauri, Shonali, 2020. "A simulation-based estimation model of household electricity demand and appliance ownership," MPRA Paper 103403, University Library of Munich, Germany.
• Fokin, Nikita & Haritonova, Marina, 2020. "Сравнительный Анализ Прогнозных Моделей Российского Ввп В Условиях Наличия Структурных Сдвигов [Comparative analysis of the forecasting models for Russia’s GDP under the structural breaks]," MPRA Paper 103412, University Library of Munich, Germany.
• Dean Fantazzini & Nikita Kolodin, 2020. "Does the Hashrate Affect the Bitcoin Price?," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 13(11), pages 1-29, October.
  • Fantazzini, Dean & Kolodin, Nikita, 2020. "Does the hashrate affect the bitcoin price?," MPRA Paper 103812, University Library of Munich, Germany.
• Soh, Ann-Ni, 2020. "A Review on the Leading Indicator Approach towards Economic Forecasting," MPRA Paper 103854, University Library of Munich, Germany.
• Sinha, Pankaj & Verma, Aniket & Shah, Purav & Singh, Jahnavi & Panwar, Utkarsh, 2020. "Prediction for the 2020 United States Presidential Election using Linear Regression Model," MPRA Paper 103890, University Library of Munich, Germany, revised 20 Oct 2020.
• Cerqua, Augusto & Letta, Marco, 2020. "Local economies amidst the COVID-19 crisis in Italy: a tale of diverging trajectories," MPRA Paper 104404, University Library of Munich, Germany.
• Victor Olkhov, 2020. "Business Cycles as Collective Risk Fluctuations," Papers 2012.04506, arXiv.org.
  • Olkhov, Victor, 2020. "Business Cycles as Collective Risk Fluctuations," MPRA Paper 104598, University Library of Munich, Germany.
• Li, Chenxing & Maheu, John M, 2020. "A Multivariate GARCH-Jump Mixture Model," MPRA Paper 104770, University Library of Munich, Germany.
• Pincheira, Pablo & Hardy, Nicolas, 2020. "The Mean Squared Prediction Error Paradox: A summary," MPRA Paper 105020, University Library of Munich, Germany.
• Fajar, Muhammad & Prasetyo, Octavia Rizky & Nonalisa, Septiarida & Wahyudi, Wahyudi, 2020. "Forecasting unemployment rate in the time of COVID-19 pandemic using Google trends data (case of Indonesia)," MPRA Paper 105042, University Library of Munich, Germany, revised 30 Nov 2020.
• Pincheira, Pablo & Jarsun, Nabil, 2020. "Summary of the Paper Entitled: Forecasting Fuel Prices with the Chilean Exchange Rate," MPRA Paper 105056, University Library of Munich, Germany.
• Olalude, Gbenga Adelekan & Olayinka, Hammed Abiola & Ankeli, Uchechi Constance, 2020. "Modelling and forecasting inflation rate in Nigeria using ARIMA models," MPRA Paper 105342, University Library of Munich, Germany, revised Dec 2020.
• Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2020. "On an integer-valued stochastic intensity model for time series of counts," MPRA Paper 105406, University Library of Munich, Germany.
• Pennoni, Fulvia & Bartolucci, Francesco & Forte, Gianfranco & Ametrano, Ferdinando, 2020. "Exploring the dependencies among main cryptocurrency log-returns: A hidden Markov model," MPRA Paper 106150, University Library of Munich, Germany.
• Андрей Захариев & Стефан Проданов & Николай Здравков, 2020. "Управленски Финансов Модел На Застрахователен Брокер В България - Методически И Приложни Аспекти," Electronic magazine "Dialogue", D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, issue 2 Year 20, pages 1-31.
• 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, 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.
  • 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, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org.
• Niango Ange Joseph Yapi, 2020. "Exchange rate predictive densities and currency risks: A quantile regression approach," EconomiX Working Papers 2020-16, University of Paris Nanterre, EconomiX.
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• Maria Morena Rivera, 2020. "Estimación de Demanda de Milanesas de Cerdo y estudio de viabilidad financiera del proyecto: “Elaboración y comercialización de milanesas de cerdo para Piamontesa SA”," Asociación Argentina de Economía Política: Working Papers 4398, Asociación Argentina de Economía Política.
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• Hardik A. Marfatia & Christophe Andre & Rangan Gupta, 2020. "Predicting Housing Market Sentiment: The Role of Financial, Macroeconomic and Real Estate Uncertainties," Working Papers 202061, University of Pretoria, Department of Economics.
• Afees A. Salisu & Juncal Cunado & Kazeem Isah & Rangan Gupta, 2020. "Oil Price and Exchange Rate Behaviour of the BRICS for Over a Century," Working Papers 202064, University of Pretoria, Department of Economics.
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• Nuttanan Wichitaksorn, 2020. "Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach," PIER Discussion Papers 146, Puey Ungphakorn Institute for Economic Research, revised Dec 2020.
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• Kocak, Necmettin Alpay, 2020. "Analysis of the Relationship between Household and Real Sector Expectations in Turkey (Türkiye’de Hanehalkı ve Reel Sektör Beklentileri Arasındaki İlişkinin Analizi)," Business and Economics Research Journal, Uludag University, Faculty of Economics and Administrative Sciences, vol. 11(4), pages 989-1000, October.
• Bilodeau, Yann, 2020. "Deep limit order book events dynamics," Working Papers 20-4, HEC Montreal, Canada Research Chair in Risk Management.
• Hoseeini Ebrahimabad, S.A & Jahangiri, Kh & Ghaemi Asl, M & Heydari, H, 2020. "Investigation of the volatility spillover effect and dynamic conditional correlations in Tehran Stock Exchange using wavelet-based Bayesian conditional variance heteroscedasticity," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 7(1), pages 149-184, May.
• Eghbali, Leila & Ranjpour, Reza & Sadeghi, Seyed Kamal, 2020. "Granger Causality Analysis of Energy Consumption and Value Added in Industrial Sub-Sectors of Iran: A Bootstrap Panel Approach," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 7(3), pages 99-130, October.
• 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.
• J-C Gerlach & Dongshuai Zhao, CFA & Didier Sornette, 2020. "Forecasting Financial Crashes: A Dynamic Risk Management Approach," Swiss Finance Institute Research Paper Series 20-103, Swiss Finance Institute.
• Roberto Molinari & Gaetan Bakalli & Stéphane Guerrier & Cesare Miglioli & Samuel Orso & O. Scaillet, 2020. "Swag: A Wrapper Method for Sparse Learning," Swiss Finance Institute Research Paper Series 20-49, Swiss Finance Institute.
• Rebecca Westphal & Didier Sornette, 2020. "How market intervention can prevent bubbles and crashes," Swiss Finance Institute Research Paper Series 20-74, Swiss Finance Institute.
• Marc-Aurèle Divernois, 2020. "A Deep Learning Approach to Estimate Forward Default Intensities," Swiss Finance Institute Research Paper Series 20-79, Swiss Finance Institute.
• J-C Gerlach & Jerome L Kreuser & Didier Sornette, 2020. "Crash-sensitive Kelly Strategy built on a modified Kreuser-Sornette bubble model tested over three decades of twenty equity indices," Swiss Finance Institute Research Paper Series 20-85, Swiss Finance Institute.
• Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: lessons from the financial crisis," Working Paper Series 2468, European Central Bank.
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• Kevin Moran & Dalibor Stevanovic & Adam Abdel Kader Touré, 2020. "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," CIRANO Working Papers 2020s-47, CIRANO.
• Milan Szabo, 2020. "Growth-at-Risk: Bayesian Approach," Working Papers 2020/3, Czech National Bank.
• Frantisek Brazdik & Tibor Hledik & Zuzana Humplova & Iva Martonosi & Karel Musil & Jakub Rysanek & Tomas Sestorad & Jaromir Tonner & Stanislav Tvrz & Jan Zacek, 2020. "The g3+ Model: An Upgrade of the Czech National Bank's Core Forecasting Framework," Working Papers 2020/7, Czech National Bank.
• 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.
• Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2020. "Modeling electricity price and quantity uncertainty: An application for hedging with forward contracts," Documentos de Trabajo CIEF 018186, Universidad EAFIT.
• Henry Caicedo-Asprilla *, 2020. "La producción del conocimiento de las regiones competitivas: una aproximación basada en modelos de variables latentes," Estudios Gerenciales, Universidad Icesi, vol. 36(155), pages 177-192, June.
• Paola Mariell Brens Ortega, 2020. "An Econometric Analysis of a Calibrated Macroeconomic Model for the Dominican Republic: A Closer Look into Monetary Policy," Documentos de Trabajo LACEA 018253, The Latin American and Caribbean Economic Association - LACEA.
• Rodríguez, Aldo, 2020. "Estimación Bayesiana de un Modelo de Economía Abierta con Sector Bancario," Dynare Working Papers 52, CEPREMAP.
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• Reichlin, Lucrezia & Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial variables as predictors of real growth vulnerability," Discussion Papers 05/2020, Deutsche Bundesbank.
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• Wittwer, Glyn & Anderson, Kym, 2020. "A Model of Global Beverage Markets," Journal of Wine Economics, Cambridge University Press, vol. 15(3), pages 330-354, August.
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  • 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.
• 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.
• Viral V. Acharya & Soumya Bhadury & Jay Surti, 2020. "Financial Vulnerability and Risks to Growth in Emerging Markets," NBER Working Papers 27411, National Bureau of Economic Research, Inc.
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• Delle-Monache, Davide & De-Polis, Andrea & Petrella, Ivan, 2020. "Modelling and Forecasting Macroeconomic Downside Risk," EMF Research Papers 34, Economic Modelling and Forecasting Group.
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• Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: lessons from the financial crisis," Working Paper Series 2468, European Central Bank.
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• Odendahl, Florens & Rossi, Barbara & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
• Wang, Dandan & Escribano Saez, Alvaro, 2020. "Forecasting gasoline prices with mixed random forest error correction models," UC3M Working papers. Economics 30557, Universidad Carlos III de Madrid. Departamento de Economía.
• Pitarakis, Jean-Yves & Gonzalo, Jesús, 2020. "Out of sample predictability in predictive regressions with many predictor candidates," UC3M Working papers. Economics 31554, Universidad Carlos III de Madrid. Departamento de Economía.
• Pitarakis, Jean-Yves & Gonzalo, Jesús & Da Silva Neto, Anibal Emiliano, 2020. "Uncovering regimes in out of sample forecast errors from predictive regressions," UC3M Working papers. Economics 31555, Universidad Carlos III de Madrid. Departamento de Economía.
• 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.
• Espasa Terrades, Antoni & Carlomagno Real, Guillermo, 2020. "Discovering general and sectorial trends in a large set of time series," DES - Working Papers. Statistics and Econometrics. WS 30899, Universidad Carlos III de Madrid. Departamento de Estadística.
• Lopes Moreira Da Veiga, María Helena & Mao, Xiuping & Casas Villalba, Maria Isabel, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, 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.
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• Wittwer, Glyn & Anderson, Kym, 2020. "A Model of Global Beverage Markets," Journal of Wine Economics, Cambridge University Press, vol. 15(3), pages 330-354, August.
  • Anderson, Kym & Wittwer, Glyn, 2020. "A Model of Global Beverage Markets," CEPR Discussion Papers 14387, C.E.P.R. Discussion Papers.
  • 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.
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• Todd Henry & Peter C.B. Phillips, 2020. "Forecasting Economic Activity Using the Yield Curve: Quasi-Real-Time Applications for New Zealand, Australia and the US," Cowles Foundation Discussion Papers 2259, Cowles Foundation for Research in Economics, Yale University.
• Hossein Hassani & Mohammad Reza Yeganegi & Juncal Cuñado & Rangan Gupta, 2020. "Forecasting interest rate volatility of the United Kingdom: evidence from over 150 years of data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(6), pages 1128-1143, April.
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• Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
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• Christian Conrad & Melanie Schienle, 2020. "Testing for an Omitted Multiplicative Long-Term Component in GARCH Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 229-242, April.
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• Carsten Bormann & Melanie Schienle, 2020. "Detecting Structural Differences in Tail Dependence of Financial Time Series," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 380-392, April.
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• 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.
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• 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.
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• Islam, Raisul & Volkov, Vladimir, 2020. "Contagion or interdependence? Comparing signed and unsigned spillovers," Working Papers 2020-05, University of Tasmania, Tasmanian School of Business and Economics.
• Islam, Raisul & Volkov, Vladimir, 2020. "Calm before the storm: an early warning approach before and during the COVID-19 crisis," Working Papers 2020-09, University of Tasmania, Tasmanian School of Business and Economics.
• Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
• 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.
• Mahmut Gunay, 2020. "Nowcasting Turkish GDP Growth with Targeted Predictors: Fill in the Blanks," Working Papers 2006, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 08 Jan 2021.
• Francisco Blasques & Meindert Heres Hoogerkamp & Siem Jan Koopman & Ilka van de Werve, 2020. "Dynamic Factor Models with Clustered Loadings: Forecasting Education Flows using Unemployment Data," Tinbergen Institute Discussion Papers 20-078/III, Tinbergen Institute, revised 21 Jan 2021.
• Noussair, C.N. & Popescu, Andreea Victoria, 2020. "Contagion and Return Predictability in Asset Markets : An Experiment with Two Lucas Trees," Other publications TiSEM f29687f7-d02c-4fad-98c2-0, Tilburg University, School of Economics and Management.
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• Maehashi, Kohei & Shintani, Mototsugu, 2020. "Macroeconomic forecasting using factor models and machine learning: an application to Japan," Journal of the Japanese and International Economies, Elsevier, vol. 58(C).
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• Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
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• Lahiri, Kajal & Zhao, Yongchen, 2020. "The Nordhaus test with many zeros," Economics Letters, Elsevier, vol. 193(C).
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• 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.
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• Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
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• Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Working Paper Series 2020-03, University of Trier, Research Group Quantitative Finance and Risk Analysis.
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• 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.
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• Benedikt Janzen & Doina Maria Radulescu, 2020. "Electricity Use as a Real Time Indicator of the Economic Burden of the Covid-19-Related Lockdown: Evidence from Switzerland," CESifo Working Paper Series 8363, CESifo.
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• Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020. "Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
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• Dmytro Krukovets, 2020. "Data Science Opportunities at Central Banks: Overview," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 249, pages 13-24.
• 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).
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• Juan Equiza-Goñi, 2020. "WP02/20 Datos de mortalidad diarios durante la crisis del COVID-19: una propuesta de mejora," Faculty Working Papers 01/20, School of Economics and Business Administration, University of Navarra.
• 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.
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• WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," LIDAM Discussion Papers CORE 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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• Mesias Alfeus & Christina Sklibosios Nikitopoulos, 2020. "Forecasting Commodity Markets Volatility: HAR or Rough?," Research Paper Series 415, Quantitative Finance Research Centre, University of Technology, Sydney.
• Christina Sklibosios Nikitopoulos & Alice Thomas & Jianxin Wang, 2020. "The Economic Impact of Volatility Persistence on Energy Markets," Research Paper Series 417, Quantitative Finance Research Centre, University of Technology, Sydney.
• Hristina Vasileva, 2020. "Application Of Logistic Regressionin Assessing The Credit Risk Of Smes," Economic Science, education and the real economy: Development and interactions in the digital age, Publishing house Science and Economics Varna, issue 1, pages 334-345.
• Žmuk Berislav & Kovač Matej, 2020. "Ornstein-Uhlenbeck process and GARCH model for temperature forecasting in weather derivatives valuation," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 27-42, May.
• Oesterreich Maciej, 2020. "On the Method of Identification of Atypical Observations in Time Series," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(2), pages 1-16, June.
• Krzciuk Małgorzata K., 2020. "On Empirical Best Linear Unbiased Predictor Under a Linear Mixed Model with Correlated Random Effects," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(2), pages 17-29, June.
• Jaworski Stanisław, 2020. "A Few Remarks on the Stochastic Structure of the Unemployment Rate in Poland by Gender," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(2), pages 41-52, June.
• Gürsakal Necmi & Yilmaz Fırat Melih & Uğurlu Erginbay, 2020. "Finding Opportunity Windows in Time Series Data Using the Sliding Window Technique: the Case of Stock Exchanges," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(3), pages 1-19, September.
• Wójcik Filip & Górnik Michał, 2020. "Improvement of E-Commerce Recommendation Systems with Deep Hybrid Collaborative Filtering with Content: A Case Study," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(3), pages 37-50, September.
• Zanka Mikhail, 2020. "A Comparison of Variables Selection Methods and their Sequential Application: A Case Study of the Bankruptcy of Polish Companies," Folia Oeconomica Stetinensia, Sciendo, vol. 20(1), pages 531-543, June.
• Wodecki Andrzej, 2020. "The Reserve Price Optimization for Publishers on Real-Time Bidding on-Line Marketplaces with Time-Series Forecasting," Foundations of Management, Sciendo, vol. 12(1), pages 167-180, January.
• Moro Matheus Fernando & Weise Andreas Dittmar & Bornia Antonio Cezar, 2020. "Model Hybrid for Sales Forecast for the Housing Market of São Paulo," Real Estate Management and Valuation, Sciendo, vol. 28(3), pages 45-64, September.
• Ngozi E. Egbuna (PhD) & Maimuna John-Sowe & Santigie M. Kargbo (PhD) & Ibrahima Diallo & Sani Bawa (PhD) & Isatou Mendy, 2020. "When Will Normalcy Return? Exploring The Novel Covid-19 Spread In The West African Monetary Zone," West African Journal of Monetary and Economic Integration, West African Monetary Institute, vol. 20(1b), pages 1-22, June.
• 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.
• Maciej Wysocki & Robert Ślepaczuk, 2020. "Artificial Neural Networks Performance in WIG20 Index Options Pricing," Working Papers 2020-19, Faculty of Economic Sciences, University of Warsaw.
• Mateusz Kijewski & Robert Ślepaczuk, 2020. "Predicting prices of S&P500 index using classical methods and recurrent neural networks," Working Papers 2020-27, Faculty of Economic Sciences, University of Warsaw.
• Karol Kielak & Robert Ślepaczuk, 2020. "Value-at-risk — the comparison of state-of-the-art models on various assets," Working Papers 2020-28, Faculty of Economic Sciences, University of Warsaw.
• Mateusz Heba & Marcin Chlebus, 2020. "Impact of using industry benchmark financial ratios on performance of bankruptcy prediction logistic regression model," Working Papers 2020-30, Faculty of Economic Sciences, University of Warsaw.
• Bartłomiej Bollin & Robert Ślepaczuk, 2020. "Variance Gamma Model in Hedging Vanilla and Exotic Options," Working Papers 2020-31, Faculty of Economic Sciences, University of Warsaw.
• Robert Ślepaczuk & Igor Wabik, 2020. "The impact of the results of football matches on the stock prices of soccer clubs," Working Papers 2020-35, Faculty of Economic Sciences, University of Warsaw.
• Quynh Bui & Robert Ślepaczuk, 2020. "Applying Hurst Exponent in Pair Trading Strategies," Working Papers 2020-39, Faculty of Economic Sciences, University of Warsaw.
• Stefan Jestl & Roman Römisch, 2020. "On the Economic Effects of a Reallocation of EU Cohesion Policy Expenditures," wiiw Working Papers 183, The Vienna Institute for International Economic Studies, wiiw.
• Capek, Jan & Crespo Cuaresma, Jesus & Hauzenberger, Niko & Reichel, Vlastimil, 2020. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Paper Series 305, WU Vienna University of Economics and Business.
  • Jan Capek & Jesus Crespo Cuaresma & Niko Hauzenberger & Vlastimil Reichel, 2020. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Papers wuwp305, Vienna University of Economics and Business, Department of Economics.
• Jan Capek & Jesus Crespo Cuaresma & Niko Hauzenberger & Vlastimil Reichel, 2020. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Papers wuwp305, Vienna University of Economics and Business, Department of Economics.
  • Capek, Jan & Crespo Cuaresma, Jesus & Hauzenberger, Niko & Reichel, Vlastimil, 2020. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Paper Series 305, WU Vienna University of Economics and Business.
• 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.
• Michael W. McCracken, 2020. "Diverging Tests of Equal Predictive Ability," Econometrica, Econometric Society, vol. 88(4), pages 1753-1754, July.
  • Michael W. McCracken, 2019. "Diverging Tests of Equal Predictive Ability," Working Papers 2019-018, Federal Reserve Bank of St. Louis, revised 09 Mar 2020.
• Carlo Pizzinelli & Konstantinos Theodoridis & Francesco Zanetti, 2020. "State Dependence In Labor Market Fluctuations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(3), pages 1027-1072, August.
  • 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.
  • Francesco Zanetti & Carlo Pizzinelli & Konstantinos Theodoridis, 2020. "State Dependence in Labor Market Fluctuations," Economics Series Working Papers 902, University of Oxford, Department of Economics.
• Gloria Gonzalez‐Rivera & Yun Luo & Esther Ruiz, 2020. "Prediction regions for interval‐valued time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 373-390, June.
  • 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.
• Jonas Dovern & Hans Manner, 2020. "Order‐invariant tests for proper calibration of multivariate density forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 440-456, June.
  • Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
  • 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.
• Joshua C. C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2020. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 692-711, September.
  • 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.
• 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.
• Dalia STREIMIKIENE & Rizwan Raheem AHMED & Saghir Pervaiz GHAURI & Muhammad AQIL & Justas STREIMIKIS, 2020. "Forecasting and the Causal Relationship of Sectorial Energy Consumptions and GDP of Pakistan by using AR, ARIMA, and Toda-Yamamoto Wald Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 131-148, July.
• Krzysztof DRACHAL, 2020. "Forecasting the Inflation Rate in Poland and U.S. Using Dynamic Model Averaging (DMA) and Google Queries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 18-34, July.
• Costas Siriopoulos & Maria Skaperda, 2020. "Investing in mutual funds: are you paying for performance or for the ties of the manager?," Bulletin of Applied Economics, Risk Market Journals, vol. 7(2), pages 153-164.
• 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.
• P. K. Viswanathan & Suresh Srinivasan & N. Hariharan, 2020. "Predicting Financial Health of Banks for Investor Guidance Using Machine Learning Algorithms," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 19(2), pages 226-261, August.
• Mar Delgado-Téllez & Javier J. Pérez, 2020. "Institutional and Economic Determinants of Regional Public Debt in Spain," Public Finance Review, , vol. 48(2), pages 212-249, March.
  • 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.
• Yu. Beketnova M. & Ю. Бекетнова М., 2020. "Синтез социально-экономических карт и визуализация девиантной деятельности объектов финансового мониторинга // Synthesis of Socio-Economic Maps and Visualization of Deviant Activity Measures of Financ," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 24(4), pages 6-17.
• Yu. Beketnova M. & Ю. Бекетнова М., 2020. "Анализ возможностей автоматизации выявления недобросовестных микрофинансовых организаций на основе методов машинного обучения // Analysis of Possibilities to Automate Detection of Unscrupulous Microfi," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 24(6), pages 38-50.
• 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.
• Henry Nasses & Rodrigo De Losso, 2020. "Behavior Biases in Macroeconomic Forecasting," Working Papers, Department of Economics 2020_23, University of São Paulo (FEA-USP).
• Ducoudré, Bruno & Hubert, Paul & Tabarly, Guilhem, 2020. "The state-dependence of output revisions," Economics Letters, Elsevier, vol. 192(C).
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Sciences Po publications info:hdl:2441/2q9catktmn9, Sciences Po.
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Sciences Po publications 04/2020, Sciences Po.
  • 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).
• 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).
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Sciences Po publications 06/2020, Sciences Po.
  • 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.
  • Reichlin, Lucrezia & Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial variables as predictors of real growth vulnerability," Discussion Papers 05/2020, Deutsche Bundesbank.
• 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.
  • 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.
• 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.
• Theophilos Papadimitriou & Periklis Gogas & Athanasios Fotios Athanasiou, 2020. "Forecasting S&P 500 spikes: an SVM approach," Digital Finance, Springer, vol. 2(3), pages 241-258, December.
• 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.
• João F. Caldeira, 2020. "Investigating the expectation hypothesis and the risk premium dynamics: new evidence for Brazil," Empirical Economics, Springer, vol. 59(1), pages 395-412, July.
• Holger Stichnoth, 2020. "Short-run fertility effects of parental leave benefits: evidence from a structural model," Empirical Economics, Springer, vol. 59(1), pages 143-168, July.
  • Stichnoth, Holger, 2014. "Short-run fertility effects of parental leave benefits: Evidence from a structural model," ZEW Discussion Papers 14-069, ZEW - Leibniz Centre for European Economic Research.
• Marcos Álvarez-Díaz, 2020. "Is it possible to accurately forecast the evolution of Brent crude oil prices? An answer based on parametric and nonparametric forecasting methods," Empirical Economics, Springer, vol. 59(3), pages 1285-1305, September.
• Yana Petrova, 2020. "On cointegration between the insurance market and economic activity," Empirical Economics, Springer, vol. 59(3), pages 1127-1138, September.
• Wali Ullah, 2020. "The arbitrage-free generalized Nelson–Siegel term structure model: Does a good in-sample fit imply better out-of-sample forecasts?," Empirical Economics, Springer, vol. 59(3), pages 1243-1284, September.
• Kenneth R. Szulczyk & Changyong Zhang, 2020. "Switching-regime regression for modeling and predicting a stock market return," Empirical Economics, Springer, vol. 59(5), pages 2385-2403, November.
• Marián Vávra, 2020. "Assessing distributional properties of forecast errors for fan-chart modelling," Empirical Economics, Springer, vol. 59(6), pages 2841-2858, December.
  • Marian Vavra, 2018. "Assessing Distributional Properties of Forecast Errors," Working and Discussion Papers WP 3/2018, Research Department, National Bank of Slovakia.
• Lixiong Yang, 2020. "State-dependent biases and the quality of China’s preliminary GDP announcements," Empirical Economics, Springer, vol. 59(6), pages 2663-2687, December.
• 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.
• Maud H. Korte & Gertjan S. Verhoeven & Arianne M. J. Elissen & Silke F. Metzelthin & Dirk Ruwaard & Misja C. Mikkers, 2020. "Using machine learning to assess the predictive potential of standardized nursing data for home healthcare case-mix classification," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(8), pages 1121-1129, November.
• 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.
• Yongchen Zhao, 2020. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 77-97, November.
• Kristian Jönsson, 2020. "Machine Learning and Nowcasts of Swedish GDP," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 123-134, November.
• Saakshi & Sohini Sahu & Siddhartha Chattopadhyay, 2020. "Epidemiology of inflation expectations and internet search: an analysis for India," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 649-671, July.
  • Jha, Saakshi & Sahu, Sohini & Chattopadhyay, Siddhartha, 2019. "Epidemiology of Inflation Expectations and Internet Search- An Analysis for India," MPRA Paper 92666, University Library of Munich, Germany.
• Hutter, Christian, 2020. "A new indicator for nowcasting employment subject to social security contributions in Germany," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 54(1), pages .4(1-10).
  • Christian Hutter, 2020. "A new indicator for nowcasting employment subject to social security contributions in Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 54(1), pages 1-10, December.
• 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.
• Dilip Kumar, 2020. "Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 587-610, September.
• Laura Casula & Guglielmo D’Amico & Giovanni Masala & Filippo Petroni, 2020. "Performance estimation of photovoltaic energy production," Letters in Spatial and Resource Sciences, Springer, vol. 13(3), pages 267-285, December.
• Tomasz Brzęczek, 2020. "Optimisation of product portfolio sales and their risk subject to product width and diversity," Review of Managerial Science, Springer, vol. 14(5), pages 1009-1027, October.
• Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-11, December.
  • Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," IRENE Working Papers 20-05, IRENE Institute of Economic Research.
• Francesca Carta, 2020. "Timely Indicators for Inequality and Poverty Using the Italian Labour Force Survey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(1), pages 41-65, May.
• Thieß Petersen & Martina Lizarazo López & Serguei Kaniovski & Thomas Url, 2020. "Makroökonomische Folgen der demografischen Alterung [Macroeconomic Consequences of Demographic Ageing: Simulations Until 2050]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 100(12), pages 958-963, December.
• Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
• Håvard Hungnes, 2020. "Predicting the exchange rate path. The importance of using up-to-date observations in the forecasts," Discussion Papers 934, Statistics Norway, Research Department.
• 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.
• Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 202031, Federal Reserve Bank of Cleveland.
  • Edward Knotek & Saeed Zaman, 2020. "Real-time density nowcasts of US inflation: a model-combination approach," Working Papers 2015, University of Strathclyde Business School, Department of Economics.
• Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
  • Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2020. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2020-01, University of Sydney Business School, Discipline of Business Analytics.
  • Laurent Pauwels & Peter Radchenko & Andrey L. Vasnev, 2020. "Higher moment constraints for predictive density combination," CAMA Working Papers 2020-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• 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.
• Philip Hans Franses, 2020. "IMA(1,1) as a new benchmark for forecast evaluation," Applied Economics Letters, Taylor & Francis Journals, vol. 27(17), pages 1419-1423, October.
  • 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.
• Steffen Q. Mueller, 2020. "Pre- and within-season attendance forecasting in Major League Baseball: a random forest approach," Applied Economics, Taylor & Francis Journals, vol. 52(41), pages 4512-4528, September.
  • 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.
• Oğuzhan 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.

2019

• 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.
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• 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.
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• 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.
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• 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.
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• Doojav, Gan-Ochir & Damdinjav, Davaasukh, 2019. "The policy-driven boom and bust in the housing market: Evidence from Mongolia," MPRA Paper 102933, University Library of Munich, Germany, revised 2019.
• Mukherjee, Paramita & Coondoo, Dipankor & Lahiri, Poulomi, 2019. "Forecasting Hourly Prices in Indian Spot Electricity Market," MPRA Paper 103161, University Library of Munich, Germany.
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• 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.
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• 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.
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• 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.
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• 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.
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• Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
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• 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.
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• Pincheira Brown, Pablo & Hardy, Nicolás, 2019. "Forecasting base metal prices with the Chilean exchange rate," Resources Policy, Elsevier, vol. 62(C), pages 256-281.
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• 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.
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• 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.
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• 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.
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• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2020. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 934-943, September.
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• 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.
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• 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.
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• 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.
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• 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.
• 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.
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• 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.
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• Sándor Karajz, 2019. "Multi-Agent-Based Macroeconomic Modelling," Theory Methodology Practice (TMP), Faculty of Economics, University of Miskolc, vol. 15(01), pages 19-24.
• Eckert, Florian & Hyndman, Rob J. & Panagiotelis, Anastasios, 2021. "Forecasting Swiss exports using Bayesian forecast reconciliation," European Journal of Operational Research, Elsevier, vol. 291(2), pages 693-710.
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• 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.
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• Mueller, Hannes Felix & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
  • Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
  • Hannes Mueller & Christopher Rauh, 2021. "The Hard Problem of Prediction for Conflict Prevention," Working Papers 1244, Barcelona Graduate School of Economics.
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• Mueller, Hannes Felix & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
  • Hannes Mueller & Christopher Rauh, 2021. "The Hard Problem of Prediction for Conflict Prevention," Working Papers 1244, Barcelona Graduate School of Economics.
  • Mueller, H. & Rauh, C., 2021. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2103, Faculty of Economics, University of Cambridge.
  • 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.
  • Hannes Mueller & Christopher Rauh, 2019. "The Hard Problem of Prediction for Conflict Prevention," Cahiers de recherche 02-2019, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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• Krystian Jaworski, 2019. "Sentiment-induced regime switching in density forecasts of emerging markets’ exchange rates. Calibrated simulation trumps estimated autoregression," Bank i Kredyt, Narodowy Bank Polski, vol. 50(1), pages 83-106.
• Marcin Pełka, 2019. "Symbolic decision stumps in individual credit scoring," Bank i Kredyt, Narodowy Bank Polski, vol. 50(6), pages 513-528.
• 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 Twenty-First Century Economic Statistics, National Bureau of Economic Research, Inc.
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  • 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.
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• Aloosh, Arash & Bekaert, Geert, 2019. "Currency Factors," CEPR Discussion Papers 13464, C.E.P.R. Discussion Papers.
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• 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 Peck, 2019. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series dp-328, Boston University - Department of Economics.
  • 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.
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  • 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.
• 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 Twenty-First 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.
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• Andrzej JARYNOWSKI, 2019. "Cost-Effectiveness Analysis For Hpv Mitigation Strategies In The Republic Of Moldova Based On Infectious Disease Modelling," ECONOMY AND SOCIOLOGY: Theoretical and Scientifical Journal, Socionet;Complexul Editorial "INCE", issue 2, pages 50-64.
• 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.
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• 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.
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• 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.
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• 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," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
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• 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.
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• 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.
• Samuel Bazzi & Robert A. Blair & Christopher Blattman & Oeindrila Dube & Matthew Gudgeon & Richard Peck, 2019. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series dp-328, Boston University - Department of Economics.
  • Bazzi, Samuel & Blair, Robert & Blattman, Chris & Dube, Oeindrila & Gudgeon, Matthew & Peck, Richard, 2019. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," SocArXiv bkrn8, Center for Open Science.
  • 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.
  • 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.
• 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.
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• 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.
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• Ruijun Bu & Rodrigo Hizmeri & Marwan Izzeldin & Anthony Murphy & Mike G. Tsionas, 2019. "The Contribution of Jump Activity and Sign to Forecasting Stock Price Volatility," Working Papers 1902, Federal Reserve Bank of Dallas, revised 17 Nov 2020.
• Fernald, John G. & Hsu, Eric & Spiegel, Mark M., 2021. "Is China fudging its GDP figures? Evidence from trading partner data," Journal of International Money and Finance, Elsevier, vol. 110(C).
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• 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.
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• 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.
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• 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 Twenty-First 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 11 Mar 2021.
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• Michael W. McCracken, 2019. "Tests of Conditional Predictive Ability: Some Simulation Evidence," Working Papers 2019-11, Federal Reserve Bank of St. Louis.
• Michael W. McCracken, 2020. "Diverging Tests of Equal Predictive Ability," Econometrica, Econometric Society, vol. 88(4), pages 1753-1754, July.
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• Michael W. McCracken & Joseph McGillicuddy & Michael T. Owyang, 2019. "Binary Conditional Forecasts," Working Papers 2019-029, Federal Reserve Bank of St. Louis, revised Apr 2021.
• 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.
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• 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.
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• 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.).
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• Fabrizio Cipollini & Giampiero M Gallo & Alessandro Palandri, 2020. "Realized Variance Modeling: Decoupling Forecasting from Estimation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(3), pages 532-555.
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• 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 d," 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.
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• 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.
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• Nyoni, Thabani, 2019. "Time series modeling and forecasting of the consumer price index in Japan," MPRA Paper 92409, University Library of Munich, Germany.
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• 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.
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• 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.
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• 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.
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• 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.
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• Nyoni, Thabani, 2019. "Modeling and forecasting remittances in Bangladesh using the Box-Jenkins ARIMA methodology," MPRA Paper 92463, University Library of Munich, Germany.
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• 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," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
  • 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.
• Andrea Bucci, 2020. "Cholesky–ANN models for predicting multivariate realized volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 865-876, September.
  • 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.
• Andrea Bucci, 2020. "Realized Volatility Forecasting with Neural Networks," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(3), pages 502-531.
  • Andrea Bucci, 0. "Realized Volatility Forecasting with Neural Networks," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(3), pages 502-531.
  • 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, 2020. "From twitter to GDP: Estimating economic activity from social media," Regional Science and Urban Economics, Elsevier, vol. 85(C).
  • 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," Working Papers 19/280, 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," 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, Russian Presidential Academy of National Economy and Public Administration (RANEPA), 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.
• Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
  • 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, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • 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 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," EconStor Preprints 202547, ZBW - Leibniz Information Centre for Economics.
  • 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.
• Çepni, Oğguzhan & Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian, 2020. "Time-varying risk aversion and the predictability of bond premia," Finance Research Letters, Elsevier, vol. 34(C).
  • 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.
• Oğuzhan 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.
• Elie Bouri & Riza Demirer & Rangan Gupta & Xiaojin Sun, 2020. "The predictability of stock market volatility in emerging economies: Relative roles of local, regional, and global business cycles," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 957-965, September.
  • 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 Güney & M. Yilmaz, 2020. "Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 966-985, September.
  • 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.
• Bouri, Elie & Demirer, Riza & Gupta, Rangan & Wohar, Mark E., 2021. "Gold, platinum and the predictability of bond risk premia," Finance Research Letters, Elsevier, vol. 38(C).
  • 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, 2021. "High-Frequency Volatility Forecasting of US Housing Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 62(2), pages 283-317, February.
  • 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, Prague University of Economics and Business, 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, Prague University of Economics and Business, vol. 2019(6), pages 648-669.
• Maciej Kostrzewski, 2019. "The Bayesian Methods of Jump Detection: The Example of Gas and EUA Contract Prices," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(2), pages 107-131, June.
• 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 M. Rees, 2020. "MARTIN Has Its Place: A Macroeconometric Model of the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 225-251, September.
  • 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.
• Singleton, Carl & Reade, J. James & Brown, Alasdair, 2020. "Going with your gut: The (In)accuracy of forecast revisions in a football score prediction game," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 89(C).
  • 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, H. O. Stekler 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 Discussion Papers em-dp2019-05, Department of Economics, Reading University.
• Elaad, Guy & Reade, J. James & Singleton, Carl, 2020. "Information, prices and efficiency in an online betting market," Finance Research Letters, Elsevier, vol. 35(C).
  • Guy Elaad & J. James Reade & Carl Singleton, 2019. "Information, prices and efficiency in an online betting market," Economics Discussion Papers em-dp2019-10, Department of Economics, Reading University.
• J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
  • J. James Reade & Carl Singleton & Alasdair Brown, 2019. "Evaluating Strange Forecasts: The Curious Case of Football Match Scorelines," Economics Discussion Papers em-dp2019-18, Department of Economics, 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.
• Broer, Tobias & Kohlhas, Alexandre, 2018. "Forecaster (Mis-)Behavior," CEPR Discussion Papers 12898, C.E.P.R. Discussion Papers.
  • Alexandre Kohlhas & Tobias Broer, 2019. "Forecaster (Mis-)Behavior," 2019 Meeting Papers 1171, Society for 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.
  • 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, Russian Presidential Academy of National Economy and Public Administration (RANEPA), 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, Russian Presidential Academy of National Economy and Public Administration (RANEPA), 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, Russian Presidential Academy of National Economy and Public Administration (RANEPA), 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.
• 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.

2018

• 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 Sciencess, 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.
• Adam J. Check & Anna K Nolan & Tyler C. Schipper, 2019. "Forecasting GDP Growth using Disaggregated GDP Revisions," Economics Bulletin, AccessEcon, vol. 39(4), pages 2580-2588.
  • Check, Adam J. & Nolan, Anna K. & Schipper, Tyler C., 2018. "Forecasting GDP: Do Revisions Matter?," MPRA Paper 86194, University Library of Munich, Germany.
• 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.
  • 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.
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• 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).
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• 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.
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• 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.
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• Tony Chernis & Rodrigo Sekkel, 2018. "Nowcasting Canadian Economic Activity in an Uncertain Environment," Discussion Papers 18-9, Bank of Canada.
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• 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.
• Fiorella Dogliolo, 2018. "Investment Nowcasting. A Real-Time Estimate with High Frequency Indicators," BCRA Working Paper Series 201878, Central Bank of Argentina, Economic Research Department.
• Lorena Garegnani & Mauricio Gómez Aguirre, 2018. "Forecasting Inflation in Argentina," BCRA Working Paper Series 201879, Central Bank of Argentina, Economic Research Department.
• Mar Delgado-Téllez & Javier J. Pérez, 2020. "Institutional and Economic Determinants of Regional Public Debt in Spain," Public Finance Review, , vol. 48(2), pages 212-249, March.
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• Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2021. "Confidence Intervals for Bias and Size Distortion in IV and Local Projections-IV Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 307-324, January.
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• 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.
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• 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.
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• 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.
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• Oscar de Jesús Gálvez-Soriano, 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.
• 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.
• 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.
• Marcel, Bräutigam & Michel, Dacorogna & Marie, Kratz, 2018. "Predicting risk with risk measures : an empirical study," ESSEC Working Papers WP1803, ESSEC Research Center, ESSEC Business School.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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