Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2019

• Simplice A. Asongu & Joseph Nnanna, 2019, "Foreign aid, instability and governance in Africa," Research Africa Network Working Papers, Research Africa Network (RAN), number 19/022, Jan.
• Hyeongwoo Kim & Kyunghwan Ko, 2019, "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2019-03, Apr.
• Sarthak Behera & Hyeongwoo Kim, 2019, "Forecasting Dollar Real Exchange Rates and the Role of Real Activity Factors," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2019-04, Oct.
• Simplice A. Asongu & Joseph Nnanna, 2019, "Foreign aid, instability and governance in Africa," CEREDEC Working Papers, Centre de Recherche pour le Développement Economique (CEREDEC), number 19/022, Jan.
• T. Bazhenov & D. Fantazzini, 2019, "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," Russian Journal of Industrial Economics, MISIS, volume 12, issue 1, DOI: 10.17073/2072-1633-2019-1-79-88.
• Ali Babikir & Mohammed Elamin Hassan & Henry Mwambi, 2019, "Asymmetry, Fat-tail and Autoregressive Conditional Density in Daily Stocks Return Data," Annals of Economics and Statistics, GENES, issue 135, pages 57-68, DOI: 10.15609/annaeconstat2009.135.0057.
• Lukas Kremens & Ian Martin, 2019, "The Quanto Theory of Exchange Rates," American Economic Review, American Economic Association, volume 109, issue 3, pages 810-843, March.
• Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2019, "Vulnerable Growth," American Economic Review, American Economic Association, volume 109, issue 4, pages 1263-1289, April.
• Daniel J. Wilson, 2019, "Clearing the Fog: The Predictive Power of Weather for Employment Reports and Their Asset Price Responses," American Economic Review: Insights, American Economic Association, volume 1, issue 3, pages 373-388, December.
• Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2019, "The Impact of Big Data on Firm Performance: An Empirical Investigation," AEA Papers and Proceedings, American Economic Association, volume 109, pages 33-37, May.
• Cristiana Chiriac & Laura Daniela RoÈ™ca, 2019, "Automotive Industry Video-Commercials – A Pluralistic Research Based on an Eye-Tracking Experiment," Journal of Emerging Trends in Marketing and Management, The Bucharest University of Economic Studies, volume 1, issue 1, pages 327-336, November.
• Simplice A. Asongu & Joseph Nnanna, 2019, "Foreign aid, instability and governance in Africa," Working Papers of the African Governance and Development Institute., African Governance and Development Institute., number 19/022, Jan.
• Tomasz Serafin & Bartosz Uniejewski & Rafal Weron, 2019, "Averaging predictive distributions across calibration windows for day-ahead electricity price forecasting," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/19/08, Jun, revised 06 Jul 2019.
• Nuno Goncalves & Domingos Seward, 2019, "Forecasting unemployment in Portugal: A labour market flows approach," CFP Working Papers, Portuguese Public Finance Council, number 01/2019, Nov.
• Chermat Tahar & Bouaichaoui Youcef, 2019, "A Predictive Study of Electricity Consumption Fluctuations Using the Autoregressive-Moving-Average Models: Wilaya of Medea as a Case Study (2011-2017)," Management & Economics Research Journal, Faculty of Economics, Commercial and Management Sciences, Ziane Achour University of Djelfa, volume 1, issue 1, pages 190-211, March, DOI: 10.48100/merj.v1i1.23.
• Anindya Banerjee & Victor Bystrov & Paul Mizen, 2019, "Structural Factor Analysis of Interest Rate Pass Through in Four Large Euro Area Economies," Lodz Economics Working Papers, University of Lodz, Faculty of Economics and Sociology, number 1/2019, May.
• Жузбаев А.М. // Zhuzbayev A.M. & Орлов К.В. // Orlov K.V., 2019, "Использование квартальной прогностической модели и сателлитных моделей в системе анализа и прогнозирования НБ РК // Use of the quarterly predictive model and satellite models in the analysis and forec," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue special, pages 3-14.
• Орлов Константин // Orlov Konstantin, 2019, "Оценка и анализ эффективности применения динамической факторной модели для оценивания и прогнозирования ВВП на примере Казахстан // Evaluation and analysis of the effectiveness of the use of a dynamic," Working Papers, National Bank of Kazakhstan, number #2019-4.
• Adolfo Rodríguez-Vargas, 2019, "Univariate Forecasts for Costa Rican Inflation With Stochastic Volatility and GARCH Effects," Documentos de Trabajo, Banco Central de Costa Rica, number 1604, Jul.
• Alonso Alfaro-Ureña & Aarón Mora-Meléndez, 2019, "The Information Rigidities and Rationality of Costa Rican Inflation Expectations," Documentos de Trabajo, Banco Central de Costa Rica, number 1705, Jul.
• Douglas Laxton & Asya Kostanyan & Akaki Liqokeli & Gevorg Minasyan & Tamta Sopromadze & Armen Nurbekyan, 2019, "Mind the Gaps! Financial-Cycle Output Gaps and Monetary-Policy-Relevant Output Gaps," Working Papers, Central Bank of Armenia, number 19, Dec.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019, "lassopack: Model selection and prediction with regularized regression in Stata," Papers, arXiv.org, number 1901.05397, Jan.
• Matteo Mogliani & Anna Simoni, 2019, "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers, arXiv.org, number 1903.08025, Mar, revised Jun 2020.
• Ali Habibnia & Esfandiar Maasoumi, 2019, "Forecasting in Big Data Environments: an Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet)," Papers, arXiv.org, number 1904.11145, Apr.
• Jozef Barunik & Pavel Fiser, 2019, "Co-jumping of Treasury Yield Curve Rates," Papers, arXiv.org, number 1905.01541, May.
• Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019, "Testing Forecast Rationality for Measures of Central Tendency," Papers, arXiv.org, number 1910.12545, Oct, revised Jul 2024.
• Alain Hecq & Elisa Voisin, 2019, "Predicting crashes in oil prices during the COVID-19 pandemic with mixed causal-noncausal models," Papers, arXiv.org, number 1911.10916, Nov, revised May 2022.
• Junjie Hu & Wolfgang Karl Hardle & Weiyu Kuo, 2019, "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," Papers, arXiv.org, number 1912.05228, Dec, revised Dec 2021.
• Francis X. Diebold & Glenn D. Rudebusch, 2019, "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers, arXiv.org, number 1912.10774, Dec, revised Jul 2021.
• Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2019, "Focused Bayesian Prediction," Papers, arXiv.org, number 1912.12571, Dec, revised Aug 2020.
• Roland Fuess & Massimo Guidolin & Christian Koeppel, 2019, "Sentiment Risk Premia in the Cross-Section of Global Equity and Currency Returns," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 19116.
• Ekaterina Tzvetanova, 2019, "Adaptation of the Altman’s Corporate Insolvency Prediction Model – The Bulgarian Case," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 125-142.
• Hartl, Tobias & Weigand, Roland, 2019, "Multivariate Fractional Components Analysis," University of Regensburg Working Papers in Business, Economics and Management Information Systems, University of Regensburg, Department of Economics, number 38283.
• Dany Brouillette & Marie-Noëlle Robitaille & Laurence Savoie-Chabot & Pierre St-Amant & Bassirou Gueye & Elise Martin, 2019, "The Trend Unemployment Rate in Canada: Searching for the Unobservable," Staff Working Papers, Bank of Canada, number 19-13, Mar, DOI: 10.34989/swp-2019-13.
• Gergely Ganics & Eva Ortega, 2019, "Las previsiones macroeconómicas del Banco de España a la luz de un modelo econométrico," Boletín Económico, Banco de España, issue SEP.
• Gergely Ganics & Eva Ortega, 2019, "Banco de España macroeconomic projections: comparison with an econometric model," Economic Bulletin, Banco de España, issue SEP.
• Luis Julián Álvarez, 2019, "El índice de precios de consumo: usos y posibles vías de mejora," Occasional Papers, Banco de España, number 1910, May.
• Mar Delgado-Téllez & Enrique Moral-Benito & Javier J. Pérez, 2019, "Outsourcing and public expenditure: an aggregate perspective with regional data," Working Papers, Banco de España, number 1939, Nov.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019, "From fixed-event to fixed-horizon density forecasts: obtaining measures of multi-horizon uncertainty from survey density forecasts," Working Papers, Banco de España, number 1947, Dec.
• Gergely Ganics & Florens Odendahl, 2019, "Bayesian VAR forecasts, survey information and structural change in the euro area," Working Papers, Banco de España, number 1948, Dec.
• Franecsca Carta, 2019, "Timely indicators for labour income inequality," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 503, Jul.
• Angela Capolongo & Claudia Pacella, 2019, "Forecasting inflation in the euro area: countries matter!," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1224, Jun.
• Fabio Busetti & Michele Caivano & Davide Delle Monache, 2019, "Domestic and global determinants of inflation: evidence from expectile regression," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1225, Jun.
• Valentina Aprigliano & Danilo Liberati, 2019, "Using credit variables to date business cycle and to estimate the probabilities of recession in real time," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1229, Jul.
• Francisco Lasso-Valderrama & Héctor M. Zárate-Solano, 2019, "Forecasting the Colombian Unemployment Rate Using Labour Force Flows," Borradores de Economia, Banco de la Republica de Colombia, number 1073, May, DOI: 10.32468/be.1073.
• María Fernanda Meneses-González & Javier Eliecer Pirateque-Niño & Santiago David Segovia-Baquero, 2019, "Indicadores de alerta temprana para el sector corporativo privado colombiano," Borradores de Economia, Banco de la Republica de Colombia, number 1084, Jul, DOI: 10.32468/be.1084.
• Carlos León, 2019, "Detecting anomalous payments networks: A dimensionality reduction approach," Borradores de Economia, Banco de la Republica de Colombia, number 1098, Dec, DOI: https://doi.org/10.32468/be.1098.
• Matteo Mogliani, 2019, "Bayesian MIDAS penalized regressions: estimation, selection, and prediction," Working papers, Banque de France, number 713.
• Laurent Ferrara & Anna Simoni, 2019, "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers, Banque de France, number 717.
• Gergely Ganics & Florens Odendahl, 2019, "Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area," Working papers, Banque de France, number 733.
• Yiru Wang & Barbara Rossi, 2019, "VAR-Based Granger-Causality Test in the Presence of Instabilities," Working Papers, Barcelona School of Economics, number 1083, Apr.
• Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019, "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, Bank for International Settlements, in: Bank for International Settlements, "The use of big data analytics and artificial intelligence in central banking".
• María Gil & Javier J. Pérez & Alberto Urtasun, 2019, "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," IFC Bulletins chapters, Bank for International Settlements, in: Bank for International Settlements, "The use of big data analytics and artificial intelligence in central banking".
• Burcu Erik & Marco Jacopo Lombardi & Dubravko Mihaljek & Hyun Song Shin, 2019, "Financial conditions and purchasing managers' indices: exploring the links," BIS Quarterly Review, Bank for International Settlements, September.
• Michael Brei & Claudio Borio, 2019, "Bank intermediation activity in a low interest rate environment," BIS Working Papers, Bank for International Settlements, number 807, Aug.
• Heiner Mikosch & Laura Solanko, 2019, "Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data," Russian Journal of Money and Finance, Bank of Russia, volume 78, issue 1, pages 19-35, March, DOI: 10.31477/rjmf.201901.19.
• Konstantin Styrin, 2019, "Forecasting Inflation in Russia Using Dynamic Model Averaging," Russian Journal of Money and Finance, Bank of Russia, volume 78, issue 1, pages 3-18, March, DOI: 10.31477/rjmf.201901.03.
• Nikita Fokin & Andrey Polbin, 2019, "Forecasting Russia's Key Macroeconomic Indicators with the VAR-LASSO Model," Russian Journal of Money and Finance, Bank of Russia, volume 78, issue 2, pages 67-93, June, DOI: 10.31477/rjmf.201901.67.
• Denis Shibitov & Mariam Mamedli, 2019, "The finer points of model comparison in machine learning: forecasting based on russian banks’ data," Bank of Russia Working Paper Series, Bank of Russia, number wps43, Aug.
• Sergei Seleznev, 2019, "Truncated priors for tempered hierarchical Dirichlet process vector autoregression," Bank of Russia Working Paper Series, Bank of Russia, number wps47, Oct.
• Ramis Khabibullin, 2019, "What measures of real economic activity slack are helpful for forecasting Russian inflation?," Bank of Russia Working Paper Series, Bank of Russia, number wps50, Oct.
• Katja Heinisch & Rolf Scheufele, 2019, "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, volume 20, issue 4, pages 170-200, November, DOI: 10.1111/geer.12163.
• Dario Sansone, 2019, "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, volume 81, issue 2, pages 456-485, April, DOI: 10.1111/obes.12277.
• André K. Anundsen, 2019, "Detecting Imbalances in House Prices: What Goes Up Must Come Down?," Scandinavian Journal of Economics, Wiley Blackwell, volume 121, issue 4, pages 1587-1619, October, DOI: 10.1111/sjoe.12349.
• Stavros Degiannakis & George Filis, 2019, "Forecasting European economic policy uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, volume 66, issue 1, pages 94-114, February, DOI: 10.1111/sjpe.12174.
• Laurent Ferrara & Clément Marsilli, 2019, "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, volume 42, issue 3, pages 846-875, March, DOI: 10.1111/twec.12708.
• Juan Carlos Carlo Santos, 2019, "Pronósticos del PIB mediante modelos de factores dinámicos," Revista de Análisis del BCB, Banco Central de Bolivia, volume 30, issue 1, pages 125-174, January -.
• Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019, "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper, Norges Bank, number 2019/2, Jan.
• Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019, "News-driven inflation expectations and information rigidities," Working Paper, Norges Bank, number 2019/5, Feb.
• Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman K. van Dijk, 2019, "Partially Censored Posterior for robust and efficient risk evaluation," Working Paper, Norges Bank, number 2019/12, Aug.
• Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019, "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School, number No 01/2019, Jan.
• Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019, "News-driven inflation expectations and information rigidities," Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School, number No 03/2019, Apr.
• Joel Suss & Henry Treitel, 2019, "Predicting bank distress in the UK with machine learning," Bank of England working papers, Bank of England, number 831, Oct.
• Jonathan Benchimol & Lahcen Bounader, 2019, "Optimal Monetary Policy under Bounded Rationality," Bank of Israel Working Papers, Bank of Israel, number 2019.07, Jul.
• Jonathan Benchimol & Makram El-Shagi, 2019, "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers, Bank of Israel, number 2019.08, Jul.
• Bruno Deschamps & Christos Ioannidis & Kook Ka, 2019, "High-Frequency Credit Spread Information and Macroeconomic Forecast Revision," Working Papers, Economic Research Institute, Bank of Korea, number 2019-17, May.
• Rahul Roy & Santhakumar Shijin, 2019, "The nexus of anomalies-stock returns-asset pricing models: The international evidence," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, volume 19, issue 1, pages 1-14, March.
• 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, Boston University - Department of Economics, number dp-328, Feb.
• Fugazza Carolina, 2019, "Anatomy of Non-Employment Risk," The B.E. Journal of Economic Analysis & Policy, De Gruyter, volume 19, issue 3, pages 1-19, July, DOI: 10.1515/bejeap-2018-0070.
• Heinisch Katja & Scheufele Rolf, 2019, "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, volume 20, issue 4, pages 170-200, December, DOI: 10.1111/geer.12163.
• Bruttel Oliver & Baumann Arne & Dütsch Matthias, 2019, "Beschäftigungseffekte des gesetzlichen Mindestlohns: Prognosen und empirische Befunde," Perspektiven der Wirtschaftspolitik, De Gruyter, volume 20, issue 3, pages 237-253, September, DOI: 10.1515/pwp-2018-0035.
• Olimpia NEAGU, 2019, "Digital Divide Gap Convergence Across European Union: The Role Of Urbanisation," Contemporary Economy Journal, Constantin Brancoveanu University, volume 4, issue 1, pages 43-48.
• Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019, "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen, number BEMPS59, Feb.
• Ahmed, M. F. & Satchell, S, 2019, "Some Dynamic and Steady-State Properties of Threshold Autoregressions with Applications to Stationarity and Local Explosivity," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 1923, Mar.
• 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, Faculty of Economics, University of Cambridge, number 1929, Mar.
• Miroslav Klucik, 2019, "Tracking the Course of the Economy (Nowcasting of basic macroeconomic indicators of Slovakia)," Working Papers, Council for Budget Responsibility, number Working Paper No. 1/2019, Jan.
• de Bondt, Gabe & Gieseck, Arne & Herrero, Pablo & Zekaite, Zivile, 2019, "Disaggregate income and wealth effects in the largest euro area countries," Research Technical Papers, Central Bank of Ireland, number 15/RT/19, Dec.
• Congressional Budget Office, 2019, "An Evaluation of CBO’s Past Deficit and Debt Projections," Reports, Congressional Budget Office, number 55234, Sep.
• Congressional Budget Office, 2019, "CBO’s Economic Forecasting Record: 2019 Update," Reports, Congressional Budget Office, number 55505, Oct.
• Congressional Budget Office, 2019, "The Accuracy of CBO’s Baseline Estimates for Fiscal Year 2019," Reports, Congressional Budget Office, number 55927, Dec.
• Hylke Vandenbussche & William Connell & Wouter Simons, 2019, "Global Value Chains, Trade Shocks and Jobs: An Application to Brexit," CESifo Working Paper Series, CESifo, number 7473.
• Domenico Delli Gatti & Jakob Grazzini, 2019, "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series, CESifo, number 7894.
• Paul Schneider, 2019, "A Theory of Scenario Generation," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-17, Mar.
• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019, "A Flexible Regime Switching Model for Asset Returns," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-27, May, revised May 2019.
• Rebecca Westphal & Didier Sornette, 2019, "Market Impact and Performance of Arbitrageurs of Financial Bubbles in An Agent-Based Model," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-29, Jun.
• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019, "A Non-Elliptical Orthogonal GARCH Model for Portfolio Selection under Transaction Costs," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-51, Sep.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019, "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers, CIRANO, number 2019s-22, Oct.
• Mateo Dulce Rubio, 2019, "Predicting criminal behavior with L√©vy flights using real data from Bogot√°," Documentos CEDE, Universidad de los Andes, Facultad de Economía, CEDE, number 17198, Feb.
• Alfredo Trespalacios & Lina M. Cort�s & Javier Perote, 2019, "Uncertainty in Electricity Markets from a seminonparametric Approach," Documentos de Trabajo de Valor Público, Universidad EAFIT, number 17304, Jun.
• Luis Sánchez & Karina Caballero, 2019, "La curva de Kuznets ambiental y su relación con el cambio climático en América Latina y el Caribe: un análisis de cointegración con panel, 1980-2015," Revista de Economía del Rosario, Universidad del Rosario, volume 22, issue 1, pages 101-142.
• Juan Pablo Alfonso Zorro, 2019, "Efectos de las variaciones del IPC en las decisiones financieras," Econógrafos, Escuela de Economía, Universidad Nacional de Colombia, FCE, CID, number 17329, Jul.
• Jorge Iván Pérez García & Mauricio Lopera Casta�o & Fredy Alonso V�squez Bedoya, 2019, "Una breve aplicación a la predicción de la fragilidad de empresas colombianas, mediante el uso de modelos estadísticos," Borradores Departamento de Economía, Universidad de Antioquia, CIE, number 17525, Sep.
• José Manuel Leguizamón Tiusabá, 2019, "Estímulos tributarios y hotelería en Colombia," Revista Economía y Región, Universidad Tecnológica de Bolívar, volume 13, issue 1, pages 177-198.
• Mateo Dulce Rubio, 2019, "Predicting criminal behavior with Levy flights using real data from Bogota," Documentos de Trabajo, Quantil, number 17347, Apr.
• Bekaert, Geert & Panayotov, George, 2019, "Good Carry, Bad Carry," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13463, Jan.
• Bekaert, Geert & Aloosh, Arash, 2019, "Currency Factors," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13464, Jan.
• Marcellino, Massimiliano & Carriero, Andrea & Corsello, Francesco, 2019, "The Global Component of Inflation Volatility," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13470, Jan.
• Mueller, Hannes & Rauh, Christopher, 2019, "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13748, May.
• Blattman, Christopher & Dube, Oeindrila & Bazzi, Samuel & Gudgeon, Matthew & Peck, Richard & Blair, Robert, 2019, "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13829, Jun.
• Gambacorta, Leonardo & Brei, Michael & Borio, Claudio, 2019, "Bank intermediation activity in a low interest rate environment," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13980, Sep.
• Petrella, Ivan & Delle Monache, Davide & Venditti, Fabrizio, 2019, "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 14107, Nov.
• Mawuli Segnon & Stelios Bekiros, 2019, "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers, Center for Quantitative Economics (CQE), University of Muenster, number 7919, Mar.
• Laurent Ferrara & Anna Simoni, 2019, "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers, Center for Research in Economics and Statistics, number 2019-04, Feb.
• González-Rivera, Gloria & Luo, Yun & Ruiz Ortega, Esther, 2019, "Prediction regions for interval-valued time series," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 29054, Oct.
• Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019, "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 29291, Nov.
• Guillaume MAROIS & Patrick SABOURIN & Alain BÉLANGER, 2019, "Forecasting Human Capital of EU Member Countries Accounting for Sociocultural Determinants," JODE - Journal of Demographic Economics, Cambridge University Press, volume 85, issue 3, pages 231-269, September, DOI: 10.1017/dem.2019.4.
• Damià Rey Miró & Pedro V. Piffaut, 2019, "Índice de Calidad Financiera (iCF)," Cuadernos de Economía - Spanish Journal of Economics and Finance, Asociación Cuadernos de Economía, volume 42, issue 119, pages 189-206, Mayo.
• Fuwei Jiang & Joshua Lee & Xiumin Martin & Guofu Zhou, 2019, "Manager sentiment and stock returns," CEMA Working Papers, China Economics and Management Academy, Central University of Finance and Economics, number 677.
• Ibrahim D. Raheem & Kazeem Isah, 2019, "The Jolly Ride of International Reserves and Commodity Prices: Evidence from Predictive Models," Working Papers, Centre for Econometric and Allied Research, University of Ibadan, number 063, Mar.
• Elias A. Udeaja & Kazeem Isah, 2019, "Revisiting the accuracy of inflation forecasts in Nigeria: the oil price –exchange rate perspectives," Working Papers, Centre for Econometric and Allied Research, University of Ibadan, number 065, Apr.
• Fries, Sébastien & Zakoian, Jean-Michel, 2019, "Mixed Causal-Noncausal Ar Processes And The Modelling Of Explosive Bubbles," Econometric Theory, Cambridge University Press, volume 35, issue 6, pages 1234-1270, December.
• Voon, Derby & Fogarty, James, 2019, "A Note on Forecasting Alcohol Demand," Journal of Wine Economics, Cambridge University Press, volume 14, issue 2, pages 208-213, May.
• Barnett, William A. & Su, Liting, 2019, "Risk Adjustment Of The Credit-Card Augmented Divisia Monetary Aggregates," Macroeconomic Dynamics, Cambridge University Press, volume 23, issue S1, pages 90-114, September.
• Adelajda MATUKA, 2019, "Bank credit to the private sector: VECM approach for Albania," Journal of Economics and Political Economy, EconSciences Journals, volume 6, issue 2, pages 159-171, June.
• Julius N. ANYU & William G. DZEKASHU, 2019, "China’s enterprises in Africa: Market entry strategies, implications for capacity building, and corporate social responsibility," Journal of Economics and Political Economy, EconSciences Journals, volume 6, issue 2, pages 172-180, June.
• Brian MICALLEF, 2019, "Measuring the effects of structural reforms in Malta," Journal of Economics and Political Economy, EconSciences Journals, volume 6, issue 4, pages 344-367, December.
• Liaqat Ali CHANDIO & Amir Ahmed KHUHRO, 2019, "The US-Pakistan relationship in South Asia, 2001-2012: A case study of Afghanistan," Journal of Economics and Political Economy, EconSciences Journals, volume 6, issue 4, pages 383-391, December.
• Emilio Colombo & Matteo Pelagatti, 2019, "Statistical Learning and Exchange Rate Forecasting," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS), number dis1901.
• Konstantin A. Kholodilin & Claus Michelsen, 2019, "High Risk of a Housing Bubble in Germany and Most OECD Countries," DIW Weekly Report, DIW Berlin, German Institute for Economic Research, volume 9, issue 32, pages 265-273.
• Konstantin A. Kholodilin & Claus Michelsen, 2019, "Das Risiko einer Immobilienpreisblase ist in Deutschland sowie in den meisten OECD-Ländern hoch," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, volume 86, issue 32, pages 547-555.
• Page, Adrian & Lambrias, Kyriacos, 2019, "The performance of the Eurosystem/ECB staff macroeconomic projections since the financial crisis," Economic Bulletin Articles, European Central Bank, volume 8.
• Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019, "Mind the gap: a multi-country BVAR benchmark for the Eurosystem projections," Working Paper Series, European Central Bank, number 2227, Jan.
• Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019, "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series, European Central Bank, number 2250, Mar.
• Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019, "An analysis of the Eurosystem/ECB projections," Working Paper Series, European Central Bank, number 2291, Jun.
• Chavleishvili, Sulkhan & Manganelli, Simone, 2019, "Forecasting and stress testing with quantile vector autoregression," Working Paper Series, European Central Bank, number 2330, Nov.
• de Bondt, Gabe & Gieseck, Arne & Zekaite, Zivile & Herrero, Pablo, 2019, "Disaggregate income and wealth effects in the largest euro area countries," Working Paper Series, European Central Bank, number 2343, Dec.
• Yao Thibaut Kpegli & Bator Anne, 2019, "Poisson-model Analysis of Power Alternation in Africa," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 1, pages 116-120.
• Chin-Sheng Huang & Yi-Sheng Liu, 2019, "Machine Learning on Stock Price Movement Forecast: The Sample of the Taiwan Stock Exchange," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 2, pages 189-201.
• Mariem Talbi & Amel Ben Halima, 2019, "Global Contagion of Investor Sentiment during the US Subprime Crisis: The Case of the USA and the Region of Latin America," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 3, pages 163-174.
• Arindam Banerjee, 2019, "Forecasting of India VIX as a Measure of Sentiment," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 3, pages 268-276.
• Chia-Cheng Chen & Yisheng Liu & Ting-Hsin Hsu, 2019, "An Analysis on Investment Performance of Machine Learning: An Empirical Examination on Taiwan Stock Market," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 4, pages 1-10.
• Ademola Abdulkareem & E. J. Okoroafor & Ayokunle Awelewa & Aderibigbe Adekitan, 2019, "Pseudo-Inverse Matrix Model for Estimating Long-Term Annual Peak Electricity Demand: The Covenant University s Experience," International Journal of Energy Economics and Policy, Econjournals, volume 9, issue 4, pages 103-109.
• Warsono Warsono & Edwin Russel & Wamiliana Wamiliana & Widiarti Widiarti & Mustofa Usman, 2019, "Modeling and Forecasting by the Vector Autoregressive Moving Average Model for Export of Coal and Oil Data (Case Study from Indonesia over the Years 2002-2017)," International Journal of Energy Economics and Policy, Econjournals, volume 9, issue 4, pages 240-247.
• Lucheroni, Carlo & Boland, John & Ragno, Costantino, 2019, "Scenario generation and probabilistic forecasting analysis of spatio-temporal wind speed series with multivariate autoregressive volatility models," Applied Energy, Elsevier, volume 239, issue C, pages 1226-1241, DOI: 10.1016/j.apenergy.2019.02.015.
• Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019, "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, volume 60, issue C, pages 45-68, DOI: 10.1016/j.asieco.2018.10.005.
• Guo, Jing & Zhang, Zhengyu, 2019, "Does renaming promote economic development? New evidence from a city-renaming reform experiment in China," China Economic Review, Elsevier, volume 57, issue C, DOI: 10.1016/j.chieco.2019.101344.
• McKenzie, David & Sansone, Dario, 2019, "Predicting entrepreneurial success is hard: Evidence from a business plan competition in Nigeria," Journal of Development Economics, Elsevier, volume 141, issue C, DOI: 10.1016/j.jdeveco.2019.07.002.
• Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019, "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, volume 103, issue C, pages 234-259, DOI: 10.1016/j.jedc.2019.04.003.
• Kapetanios, George & Masolo, Riccardo M. & Petrova, Katerina & Waldron, Matthew, 2019, "A time-varying parameter structural model of the UK economy," Journal of Economic Dynamics and Control, Elsevier, volume 106, issue C, pages 1-1, DOI: 10.1016/j.jedc.2019.05.012.
• Fiszeder, Piotr & Fałdziński, Marcin, 2019, "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, volume 108, issue C, DOI: 10.1016/j.jedc.2019.103736.
• Zhang, Han & Fan, Xiaoyun & Guo, Bin & Zhang, Wei, 2019, "Reexamining time-varying bond risk premia in the post-financial crisis era," Journal of Economic Dynamics and Control, Elsevier, volume 109, issue C, DOI: 10.1016/j.jedc.2019.103777.
• Plachel, Lukas, 2019, "A unified model for regularized and robust portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, volume 109, issue C, DOI: 10.1016/j.jedc.2019.103779.
• Kolidakis, Stylianos & Botzoris, George & Profillidis, Vassilios & Lemonakis, Panagiotis, 2019, "Road traffic forecasting — A hybrid approach combining Artificial Neural Network with Singular Spectrum Analysis," Economic Analysis and Policy, Elsevier, volume 64, issue C, pages 159-171, DOI: 10.1016/j.eap.2019.08.002.
• Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019, "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, volume 76, issue C, pages 319-329, DOI: 10.1016/j.econmod.2018.08.009.
• Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019, "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, volume 78, issue C, pages 32-39, DOI: 10.1016/j.econmod.2018.09.014.
• El-Shagi, Makram, 2019, "Rationality tests in the presence of instabilities in finite samples," Economic Modelling, Elsevier, volume 79, issue C, pages 242-246, DOI: 10.1016/j.econmod.2018.11.011.
• González-Astudillo, Manuel & Baquero, Daniel, 2019, "A nowcasting model for Ecuador: Implementing a time-varying mean output growth," Economic Modelling, Elsevier, volume 82, issue C, pages 250-263, DOI: 10.1016/j.econmod.2019.01.010.
• Tissaoui, Kais & Azibi, Jamel, 2019, "International implied volatility risk indexes and Saudi stock return-volatility predictabilities," The North American Journal of Economics and Finance, Elsevier, volume 47, issue C, pages 65-84, DOI: 10.1016/j.najef.2018.11.016.
• Salisu, Afees A. & Isah, Kazeem & Akanni, Lateef O., 2019, "Improving the predictability of stock returns with Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, volume 48, issue C, pages 857-867, DOI: 10.1016/j.najef.2018.08.010.
• Nonejad, Nima, 2019, "Forecasting aggregate equity return volatility using crude oil price volatility: The role of nonlinearities and asymmetries," The North American Journal of Economics and Finance, Elsevier, volume 50, issue C, DOI: 10.1016/j.najef.2019.101022.
• Paccagnini, Alessia, 2019, "Did financial factors matter during the Great Recession?," Economics Letters, Elsevier, volume 174, issue C, pages 26-30, DOI: 10.1016/j.econlet.2018.10.005.
• Delle Monache, Davide & Petrella, Ivan, 2019, "Efficient matrix approach for classical inference in state space models," Economics Letters, Elsevier, volume 181, issue C, pages 22-27, DOI: 10.1016/j.econlet.2019.04.012.
• Uddin, Gazi Salah & Gençay, Ramazan & Bekiros, Stelios & Sahamkhadam, Maziar, 2019, "Enhancing the predictability of crude oil markets with hybrid wavelet approaches," Economics Letters, Elsevier, volume 182, issue C, pages 50-54, DOI: 10.1016/j.econlet.2019.05.041.
• Cuesta, Jose & Chagalj, Cristian, 2019, "Measuring poverty with administrative data in data deprived contexts: The case of Nicaragua," Economics Letters, Elsevier, volume 183, issue C, pages 1-1, DOI: 10.1016/j.econlet.2019.108573.
• Gozgor, Giray & Lau, Chi Keung Marco & Sheng, Xin & Yarovaya, Larisa, 2019, "The role of uncertainty measures on the returns of gold," Economics Letters, Elsevier, volume 185, issue C, DOI: 10.1016/j.econlet.2019.108680.
• Kim, Donggyu & Fan, Jianqing, 2019, "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, volume 208, issue 2, pages 395-417, DOI: 10.1016/j.jeconom.2018.10.003.
• Rossi, Barbara & Sekhposyan, Tatevik, 2019, "Alternative tests for correct specification of conditional predictive densities," Journal of Econometrics, Elsevier, volume 208, issue 2, pages 638-657, DOI: 10.1016/j.jeconom.2018.07.008.
• Liao, Jun & Zong, Xianpeng & Zhang, Xinyu & Zou, Guohua, 2019, "Model averaging based on leave-subject-out cross-validation for vector autoregressions," Journal of Econometrics, Elsevier, volume 209, issue 1, pages 35-60, DOI: 10.1016/j.jeconom.2018.10.007.
• Boot, Tom & Nibbering, Didier, 2019, "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, volume 209, issue 2, pages 391-406, DOI: 10.1016/j.jeconom.2019.01.009.
• Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019, "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 135-154, DOI: 10.1016/j.jeconom.2018.11.009.
• McAlinn, Kenichiro & West, Mike, 2019, "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 155-169, DOI: 10.1016/j.jeconom.2018.11.010.
• Kastner, Gregor, 2019, "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 98-115, DOI: 10.1016/j.jeconom.2018.11.007.
• Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019, "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, volume 212, issue 1, pages 137-154, DOI: 10.1016/j.jeconom.2019.04.024.
• Korobilis, Dimitris & Pettenuzzo, Davide, 2019, "Adaptive hierarchical priors for high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, volume 212, issue 1, pages 241-271, DOI: 10.1016/j.jeconom.2019.04.029.
• Giessing, Alexander & He, Xuming, 2019, "On the predictive risk in misspecified quantile regression," Journal of Econometrics, Elsevier, volume 213, issue 1, pages 235-260, DOI: 10.1016/j.jeconom.2019.04.013.
• Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019, "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, volume 213, issue 2, pages 493-515, DOI: 10.1016/j.jeconom.2019.07.002.
• Sutton, Maxwell & Vasnev, Andrey L. & Gerlach, Richard, 2019, "Mixed interval realized variance: A robust estimator of stock price volatility," Econometrics and Statistics, Elsevier, volume 11, issue C, pages 43-62, DOI: 10.1016/j.ecosta.2018.06.001.
• Leippold, Markus & Yang, Hanlin, 2019, "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, volume 12, issue C, pages 25-41, DOI: 10.1016/j.ecosta.2019.07.001.
• Ghysels, Eric & Qian, Hang, 2019, "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, volume 9, issue C, pages 1-16, DOI: 10.1016/j.ecosta.2018.02.001.
• Al-Sadoon, Majid M., 2019, "Testing subspace Granger causality," Econometrics and Statistics, Elsevier, volume 9, issue C, pages 42-61, DOI: 10.1016/j.ecosta.2017.08.003.

2018

• Philip Hans Franses, 2018, "Prediction Intervals For Expert-Adjusted Forecasts," Advances in Decision Sciences, Asia University, Taiwan, volume 22, issue 1, pages 308-320, December.
• Emilio Zanetti Chini, 2018, "Forecaster’s utility and forecasts coherence," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2018-01, Jan.
• Torben G. Andersen & Rasmus T. Varneskov, 2018, "Consistent Inference for Predictive Regressions in Persistent VAR Economies," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2018-09, Feb.
• Isabel Casas & Xiuping Mao & Helena Veiga, 2018, "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2018-10, Mar.
• Emilio Zanetti Chini, 2018, "Forecasters’ utility and forecast coherence," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2018-23, Aug.
• Erik Christian Montes Schütte, 2018, "In Search of a Job: Forecasting Employment Growth in the US using Google Trends," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2018-25, Aug.
• Sebastian Ankargren & Måns Unosson & Yukai Yang, 2018, "A mixed-frequency Bayesian vector autoregression with a steady-state prior," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2018-32, Dec.
• James Barth & Sunghoon Joo & Hyeongwoo Kim & Kang Bok Lee & Stevan Maglic & Xuan Shen, 2018, "Forecasting Net Charge-Off Rates of Banks: A PLS Approach," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2018-03, Apr.
• Emerson Abraham Jackson & Edmond Tamuke & Abdulai Sillah, 2018, "Modelling Monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins Methodology," International Journal of Sciences, Office ijSciences, volume 7, issue 01, pages 51-56, January, DOI: 10.18483/ijSci.1507.
• Rahul Deb & Mallesh M. Pai & Maher Said, 2018, "Evaluating Strategic Forecasters," American Economic Review, American Economic Association, volume 108, issue 10, pages 3057-3103, October.
• Edward L. Glaeser & Hyunjin Kim & Michael Luca, 2018, "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change," AEA Papers and Proceedings, American Economic Association, volume 108, pages 77-82, May.