Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2021

• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021, "Forecasting with Shadow-Rate VARs," Working Papers, Federal Reserve Bank of Cleveland, number 21-09, Mar, DOI: 10.26509/frbc-wp-202109.
• James Mitchell & Martin Weale, 2021, "Censored Density Forecasts: Production and Evaluation," Working Papers, Federal Reserve Bank of Cleveland, number 21-12R, May, revised 16 Aug 2022, DOI: 10.26509/frbc-wp-202112r.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022, "Macroeconomic Forecasting in a Multi-country Context," Working Papers, Federal Reserve Bank of Cleveland, number 22-02, Feb, DOI: 10.26509/frbc-wp-202202.
• Chad Fulton & Kirstin Hubrich, 2021, "Forecasting US Inflation in Real Time," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2021-014, Mar, DOI: 10.17016/FEDS.2021.014.
• Dong Hwan Oh & Andrew J. Patton, 2021, "Better the Devil You Know: Improved Forecasts from Imperfect Models," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2021-071, Nov, DOI: 10.17016/FEDS.2021.071.
• Benjamin Gardner & Chiara Scotti & Clara Vega, 2021, "Words Speak as Loudly as Actions: Central Bank Communication and the Response of Equity Prices to Macroeconomic Announcements," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2021-074, Nov, DOI: 10.17016/FEDS.2021.074.
• Neil R. Ericsson, 2021, "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.), number 1311, Mar, DOI: 10.17016/IFDP.2021.1311.
• Danilo Cascaldi-Garcia & Thiago Revil T. Ferreira & Domenico Giannone & Michele Modugno, 2021, "Back to the Present: Learning about the Euro Area through a Now-casting Model," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.), number 1313, Mar, DOI: 10.17016/IFDP.2021.1313.
• Dario Caldara & Chiara Scotti & Molin Zhong, 2021, "Macroeconomic and Financial Risks: A Tale of Mean and Volatility," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.), number 1326, Aug, DOI: 10.17016/IFDP.2021.1326.
• Daniel Aaronson & Scott A. Brave & Michael Fogarty & Ezra Karger & Spencer D. Krane, 2021, "Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade," Working Paper Series, Federal Reserve Bank of Chicago, number WP-2021-05, Mar, revised 18 Jun 2021, DOI: 10.21033/wp-2021-05.
• Richard K. Crump & Stefano Eusepi & Domenico Giannone & Eric Qian & Argia M. Sbordone, 2021, "A Large Bayesian VAR of the United States Economy," Staff Reports, Federal Reserve Bank of New York, number 976, Aug.
• Richard Berner & Robert Engle & Hyeyoon Jung, 2021, "CRISK: Measuring the Climate Risk Exposure of the Financial System," Staff Reports, Federal Reserve Bank of New York, number 977, Sep.
• Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2021, "Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models," Working Papers, Federal Reserve Bank of Philadelphia, number 21-21, Jun, DOI: 10.21799/frbp.wp.2021.21.
• Bogdan Ion Boldea & Costin Radu Boldea, 2021, "A quasi-cyclical regressive model of the pandemic impact on Romanian e-market," Journal of Financial Studies, Institute of Financial Studies, volume 11, issue 6, pages 46-56, December.
• Tsukhlo Sergey, 2021, "Russian industrial sector in 2020: (based on surveys’ findings)," Published Papers, Gaidar Institute for Economic Policy, number ppaper-2021-1125, revised 2021.
• Barinova Vera & Zemtsov Tsepan & Tsareva Yulia, 2021, "Small and medium business amid coronacrisis," Published Papers, Gaidar Institute for Economic Policy, number ppaper-2021-1130, revised 2021.
• Zubarev Andrey & Rybak Konstantin, 2021, "GDP Nowcasting: Dynamic Factor Model vs. Official Forecasts
  [Наукастинг Ввп: Динамическая Факторная Модель И Официальные Прогнозы]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 34-40, December.
• Polbin Andrey & Fokin Nikita, 2021, "Employment in Russia in 2020: a Controversial Recovery
  [Занятость В России В 2020 Г.: Противоречивое Восстановление]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 4, pages 74-76, April.
• Zubarev Andrey & Rybak Konstantin, 2021, "Наукастинг Ввп: Динамическая Факторная Модель И Официальные Прогнозы," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 34-40, December.
• Polbin Andrey & Fokin Nikita, 2021, "Занятость В России В 2020 Г.: Противоречивое Восстановление," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 4, pages 74-76, April.
• Chad Fulton & Kirstin Hubrich, 2021, "Forecasting US Inflation in Real Time," Econometrics, MDPI, volume 9, issue 4, pages 1-20, October.
• Simon Liebermann & Jung-Sup Um & YoungSeok Hwang & Stephan Schlüter, 2021, "Performance Evaluation of Neural Network-Based Short-Term Solar Irradiation Forecasts," Energies, MDPI, volume 14, issue 11, pages 1-21, May.
• Arkadiusz Jędrzejewski & Grzegorz Marcjasz & Rafał Weron, 2021, "Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO," Energies, MDPI, volume 14, issue 11, pages 1-17, June.
• Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2021, "Modeling Electricity Price and Quantity Uncertainty: An Application for Hedging with Forward Contracts," Energies, MDPI, volume 14, issue 11, pages 1-26, June.
• Rangan Gupta & Christian Pierdzioch, 2021, "Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers," Energies, MDPI, volume 14, issue 14, pages 1-15, July.
• Rangan Gupta & Christian Pierdzioch & Wing-Keung Wong, 2021, "A Note on Forecasting the Historical Realized Variance of Oil-Price Movements: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios," Energies, MDPI, volume 14, issue 20, pages 1-12, October.
• Rangan Gupta & Christian Pierdzioch, 2021, "Climate Risks and the Realized Volatility Oil and Gas Prices: Results of an Out-of-Sample Forecasting Experiment," Energies, MDPI, volume 14, issue 23, pages 1-18, December.
• Dean Fantazzini & Julia Pushchelenko & Alexey Mironenkov & Alexey Kurbatskii, 2021, "Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg," Forecasting, MDPI, volume 3, issue 4, pages 1-30, October.
• Dean Fantazzini & Raffaella Calabrese, 2021, "Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure," JRFM, MDPI, volume 14, issue 11, pages 1-23, October.
• Nadiia Shapovalenko, 2021, "A BVAR Model for Forecasting Ukrainian Inflation," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 05-2021, Mar.
• Anastasiya Ivanova & Alona Shmygel & Ihor Lubchuk, 2021, "The Growth-at-Risk (GaR) Framework: Implication For Ukraine," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 10-2021, Jul.
• Vasco J.Gabriel & Luis F. Martins & Anthoulla Phella, 2021, "Modelling Low-Frequency Covariability of Paleoclimatic Data," Working Papers, Business School - Economics, University of Glasgow, number 2022_17, Dec.
• 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, University of Graz, Department of Economics, number 2021-01, Jan.
• Hans Manner & Gabriel Rodriguez & Florian St ckler, 2021, "A changepoint analysis of exchange rate and commodity price risks for Latin American stock markets," Graz Economics Papers, University of Graz, Department of Economics, number 2021-14, Dec.
• Guoyou Yue, 2021, "Forecasting the Logistics Demand of Guangxi Beibu Gulf Port," GATR Journals, Global Academy of Training and Research (GATR) Enterprise, number gjbssr587, Mar, DOI: https://doi.org/10.35609/gjbssr.202.
• Neil R. Ericsson, 2021, "Dynamic Econometrics in Action: A Biography of David F. Hendry," Working Papers, The George Washington University, The Center for Economic Research, number 2021-001, Mar.
• Eiji Goto & Jan P.A.M. Jacobs & Tara M. Sinclair & Simon van Norden, 2021, "Employment Reconciliation and Nowcasting," Working Papers, The George Washington University, The Center for Economic Research, number 2021-007, Dec.
• Jean-David Fermanian & Dominique Guegan, 2021, "Fair learning with bagging," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers), HAL, number halshs-03500906, Nov.
• Jamal Bouoiyour & Refk Selmi, 2021, "The financial costs of terrorism: evidence from Germany," Post-Print, HAL, number hal-02108636, DOI: 10.25428/1824-2979/202101-87-104.
• 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, number hal-03103717, Jan, DOI: 10.1007/978-3-030-54252-8_9.
• Christina Christou & Rangan Gupta & Fredj Jawadi, 2021, "Does inequality help in forecasting equity premium in a panel of G7 countries?," Post-Print, HAL, number hal-04478772, Jul, DOI: 10.1016/j.najef.2021.101456.
• Elizaveta Golovanova & Andrey Zubarev, 2021, "Forecasting Aggregate Retail Sales with Google Trends," Post-Print, HAL, number hal-05250233, Dec, DOI: 10.31477/rjmf.202104.50.
• Jean-David Fermanian & Dominique Guegan, 2021, "Fair learning with bagging," Post-Print, HAL, number halshs-03500906, Nov.
• Antoine Auberger, 2021, "Vote, popularity, economic conditions and French legislative elections
  [Vote, popularité, conditions économiques et élections législatives françaises]," Working Papers, HAL, number hal-03480853, Dec.
• Vanella, Patrizio & Rodriguez Gonzalez, Miguel & Wilke, Christina B., 2021, "The Impact of Population Aging on the German Statutory Pension Insurance - A Probabilistic Approach," Hannover Economic Papers (HEP), Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, number dp-688, Jul.
• Fink Simonsen, Nicolai & Kjær, Trine, 2021, "New Evidence of Health State Dependent Utility of Consumption: A combined survey and register study," DaCHE discussion papers, University of Southern Denmark, Dache - Danish Centre for Health Economics, number 2021:2, Jun, DOI: 10.21996/2c7w-0m41.
• Liudmila Kitrar & Tamara Lipkind, 2021, "Assessment Of GDP Growth After The Corona Crisis Using The Results Of Business And Consumer Surveys," HSE Working papers, National Research University Higher School of Economics, number WP BRP 118/STI/2021.
• Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2021, "Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility," Discussion paper series, Hitotsubashi Institute for Advanced Study, Hitotsubashi University, number HIAS-E-104, Jan.
• Ozana Nadoveza Jelić & Rafael Ravnik, 2021, "Introducing Policy Analysis Croatian MAcroecoNometric Model (PACMAN)," Surveys, The Croatian National Bank, Croatia, number 41, Feb.
• Toleu PANIYAZ & Kargash ZHANPEIISSOVA & Oralbay KABUL & Aigul AMANTAYEVA, 2021, "Strategic Priorities Of The National Policy Of The Republic Of Kazakhstan On The Development Of Regions," Regional Science Inquiry, Hellenic Association of Regional Scientists, volume 0, issue 2, pages 83-92, June.
• Collischon, Matthias, 2021, "Identifying supervisory or managerial status in administrative records," IAB-Discussion Paper, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], number 202120, Dec.
• Luigi Longo & Massimo Riccaboni & Armando Rungi, 2021, "A Neural Network Ensemble Approach for GDP Forecasting," Working Papers, IMT School for Advanced Studies Lucca, number 02/2021, Mar, revised Mar 2021.
• Francesca Micocci & Armando Rungi, 2021, "Predicting Exporters with Machine Learning," Working Papers, IMT School for Advanced Studies Lucca, number 03/2021, Jul, revised Jul 2021.
• Afees A. Salisu & Abdulsalam Abidemi Sikiru, 2021, "Palm Oil Price–Exchange Rate Nexus in Indonesia and Malaysia," Bulletin of Monetary Economics and Banking, Bank Indonesia, volume 24, issue 2, pages 169-180, June, DOI: https://doi.org/10.21098/bemp.v24i2.
• Crespo-Cuaresma, Jesus & Fortin, Ines & Hlouskova, Jaroslava & Obersteiner, Michael, 2021, "Regime-dependent commodity price dynamics: A predictive analysis," IHS Working Paper Series, Institute for Advanced Studies, number 28, Jan.
• Fortin, Ines & Hlouskova, Jaroslava & Soegner, Leopold, 2021, "Financial instability and economic activity," IHS Working Paper Series, Institute for Advanced Studies, number 36, Nov.
• Eda Gülşen & Hakan Kara, 2021, "Policy Performance and the Behavior of Inflation Expectations," International Journal of Central Banking, International Journal of Central Banking, volume 17, issue 70, pages 1-46, October.
• Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2021, "Real-Time Forecasting and Scenario Analysis Using a Large Mixed-Frequency Bayesian VAR," International Journal of Central Banking, International Journal of Central Banking, volume 17, issue 71, pages 1-41, December.
• Ms. Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021, "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," IMF Working Papers, International Monetary Fund, number 2021/195, Jul.
• Lukas Boer & Mr. Andrea Pescatori & Martin Stuermer, 2021, "Energy Transition Metals," IMF Working Papers, International Monetary Fund, number 2021/243, Oct.
• Mr. Yan Carriere-Swallow & José Marzluf, 2021, "Macrofinancial Causes of Optimism in Growth Forecasts," IMF Working Papers, International Monetary Fund, number 2021/275, Nov.
• 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, volume 16, issue 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, volume 16, issue 1, pages 1-15, 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, volume 16, issue 2, pages 1-15, Abril - J.
• Maria del Carmen Gomez-Rios & Dora Carmen Galvez-Cruz, 2021, "Simulation of Levelized Costs of Electricity Considering Externalities," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 16, issue 4, pages 1-23, Octubre -.
• Adrián F. Rossignolo, 2021, "The New Standardised Approach as a Credible Fallback," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 16, issue TNEA, pages 1-27, Septiembr.
• Guillermo Benavides, 2021, "Asymmetric Volatility Relevance in Risk Management: An Empirical Analysis using Stock Index Futures," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 16, issue TNEA, pages 1-18, Septiembr.
• 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, Springer, in: Gilles Dufrénot & Takashi Matsuki, "Recent Econometric Techniques for Macroeconomic and Financial Data", DOI: 10.1007/978-3-030-54252-8_9.
• Alain Kabundi & Asithandile Mbelu, 2021, "Estimating a time-varying financial conditions index for South Africa," Empirical Economics, Springer, volume 60, issue 4, pages 1817-1844, April, DOI: 10.1007/s00181-020-01844-0.
• Yongchen Zhao, 2021, "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, volume 61, issue 1, pages 173-199, July, DOI: 10.1007/s00181-020-01864-w.
• Jack Fosten & Daniel Gutknecht, 2021, "Horizon confidence sets," Empirical Economics, Springer, volume 61, issue 2, pages 667-692, August, DOI: 10.1007/s00181-020-01891-7.
• Serdar Neslihanoglu & Stelios Bekiros & John McColl & Duncan Lee, 2021, "Multivariate time-varying parameter modelling for stock markets," Empirical Economics, Springer, volume 61, issue 2, pages 947-972, August, DOI: 10.1007/s00181-020-01896-2.
• Georges Tsafack & James Cataldo, 2021, "Backtesting and estimation error: value-at-risk overviolation rate," Empirical Economics, Springer, volume 61, issue 3, pages 1351-1396, September, DOI: 10.1007/s00181-020-01905-4.
• Edmond Berisha & David Gabauer & Rangan Gupta & Chi Keung Marco Lau, 2021, "Time-varying influence of household debt on inequality in United Kingdom," Empirical Economics, Springer, volume 61, issue 4, pages 1917-1933, October, DOI: 10.1007/s00181-020-01940-1.
• Angela Capolongo & Claudia Pacella, 2021, "Forecasting inflation in the euro area: countries matter!," Empirical Economics, Springer, volume 61, issue 5, pages 2477-2499, November, DOI: 10.1007/s00181-020-01959-4.
• Nima Nonejad, 2021, "Crude oil price point forecasts of the Norwegian GDP growth rate," Empirical Economics, Springer, volume 61, issue 5, pages 2913-2930, November, DOI: 10.1007/s00181-020-01964-7.
• Ahmet Akca & Ethem Çanakoğlu, 2021, "Adaptive stochastic risk estimation of firm operating profit," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, volume 48, issue 3, pages 463-504, September, DOI: 10.1007/s40812-021-00184-z.
• David Y. Aharon & Zaghum Umar & Xuan Vinh Vo, 2021, "Dynamic spillovers between the term structure of interest rates, bitcoin, and safe-haven currencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 7, issue 1, pages 1-25, December, DOI: 10.1186/s40854-021-00274-w.
• Christian Stummer & Lars Lüpke & Markus Günther, 2021, "Beaming market simulation to the future by combining agent-based modeling with scenario analysis," Journal of Business Economics, Springer, volume 91, issue 9, pages 1469-1497, November, DOI: 10.1007/s11573-021-01046-9.
• Martin Pažický, 2021, "Predicting Recessions in Germany Using the German and the US Yield Curve," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 17, issue 3, pages 263-291, December, DOI: 10.1007/s41549-021-00061-7.
• Pelin Akyol & Kala Krishna & Jinwen Wang, 2021, "Taking PISA Seriously: How Accurate are Low-Stakes Exams?," Journal of Labor Research, Springer, volume 42, issue 2, pages 184-243, June, DOI: 10.1007/s12122-021-09317-8.
• Filippo Massari, 2021, "Price probabilities: a class of Bayesian and non-Bayesian prediction rules," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), volume 72, issue 1, pages 133-166, July, DOI: 10.1007/s00199-020-01270-4.
• Annalisa Cristini & Piero Ferri, 2021, "Nonlinear models of the Phillips curve," Journal of Evolutionary Economics, Springer, volume 31, issue 4, pages 1129-1155, September, DOI: 10.1007/s00191-021-00736-5.
• Ali Habibnia & Esfandiar Maasoumi, 2021, "Forecasting in Big Data Environments: An Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 19, issue 1, pages 363-381, December, DOI: 10.1007/s40953-021-00275-7.
• Roberto S. Mariano & Suleyman Ozmucur, 2021, "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 19, issue 1, pages 383-400, December, DOI: 10.1007/s40953-021-00276-6.
• Subhash C. Sharma & Anil K. Bera, 2021, "Estimation of Random Components and Prediction in One and Two-Way Error Component Regression Models," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 19, issue 1, pages 419-441, December, DOI: 10.1007/s40953-021-00278-4.
• Guilherme Lindenmeyer & Pedro Pablo Skorin & Hudson da Silva Torrent, 2021, "Using boosting for forecasting electric energy consumption during a recession: a case study for the Brazilian State Rio Grande do Sul," Letters in Spatial and Resource Sciences, Springer, volume 14, issue 2, pages 111-128, August, DOI: 10.1007/s12076-021-00268-3.
• Ricarda B. Bouncken & Yixin Qiu & Noemi Sinkovics & Wolfgang Kürsten, 2021, "Qualitative research: extending the range with flexible pattern matching," Review of Managerial Science, Springer, volume 15, issue 2, pages 251-273, February, DOI: 10.1007/s11846-021-00451-2.
• Rosina O. Weber & Kedma B. Duarte, 2021, "Data-driven artificial intelligence to automate researcher assessment," Scientometrics, Springer;Akadémiai Kiadó, volume 126, issue 4, pages 3265-3281, April, DOI: 10.1007/s11192-020-03859-x.
• Rodrigo Mulero & Alfredo García-Hiernaux, 2021, "Forecasting Spanish unemployment with Google Trends and dimension reduction techniques," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, volume 12, issue 3, pages 329-349, September, DOI: 10.1007/s13209-021-00231-x.
• Ángel Cuevas & Ramiro Ledo & Enrique M. Quilis, 2021, "Seasonal adjustment of the Spanish sales daily data," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, volume 12, issue 4, pages 687-708, December, DOI: 10.1007/s13209-021-00251-7.
• Javier Ojea-Ferreiro, 2021, "Deconstructing Systemic Risk: A Reverse Stress Testing Approach," Springer Books, Springer, in: Marco Corazza & Manfred Gilli & Cira Perna & Claudio Pizzi & Marilena Sibillo, "Mathematical and Statistical Methods for Actuarial Sciences and Finance", DOI: 10.1007/978-3-030-78965-7_54.
• Raad Mozib Lalon & PhD & Nusrat Jahan, 2021, "Predicting Economic Performance of Bangladesh using Autoregressive Integrated Moving Average (ARIMA) model," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 11, issue 2, pages 1-5.
• Yu-Min Lian & Chia-Hsuan Li & Yi-Hsuan Wei, 2021, "Machine Learning and Time Series Models for VNQ Market Predictions," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 11, issue 5, pages 1-2.
• Rebecca F. Gleditsch & Adrian F. Rogne & Astri Syse & Michael Thomas, 2021, "The accuracy of Statistics Norway’s national population projections," Discussion Papers, Statistics Norway, Research Department, number 948, Mar.
• Pål Boug & Håvard Hungnes & Takamitsu Kurita, 2021, "The empirical modelling of house prices and debt revisited. A policy-oriented perspective," Discussion Papers, Statistics Norway, Research Department, number 967, Nov.
• Martin Iseringhausen, 2021, "A time-varying skewness model for Growth-at-Risk," Working Papers, European Stability Mechanism, number 49, Jun.
• Clements, Adam & Vasnev, Andrey, 2021, "Forecast combination puzzle in the HAR model," Working Papers, University of Sydney Business School, Discipline of Business Analytics, number BAWP-2021-01, Feb.
• Magnus, Jan & Vasnev, Andrey, 2021, "On the uncertainty of a combined forecast: The critical role of correlation," Working Papers, University of Sydney Business School, Discipline of Business Analytics, number BAWP-2022-01, Dec.
• Hanjo Odendaal, 2021, "A machine learning approach to domain specific dictionary generation. An economic time series framework," Working Papers, Stellenbosch University, Department of Economics, number 06/2021.
• Constantin Bürgi & Tara M. Sinclair, 2021, "What does forecaster disagreement tell us about the state of the economy?," Applied Economics Letters, Taylor & Francis Journals, volume 28, issue 1, pages 49-53, January, DOI: 10.1080/13504851.2020.1730751.
• Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2021, "A note on oil price shocks and the forecastability of gold realized volatility," Applied Economics Letters, Taylor & Francis Journals, volume 28, issue 21, pages 1889-1897, December, DOI: 10.1080/13504851.2020.1854658.
• Antonio Rodríguez Andrés & Voxi Heinrich S. Amavilah & Abraham Otero, 2021, "Evaluation of technology clubs by clustering: a cautionary note," Applied Economics, Taylor & Francis Journals, volume 53, issue 52, pages 5989-6001, November, DOI: 10.1080/00036846.2021.1934393.
• Tommaso Proietti, 2021, "Predictability, real time estimation, and the formulation of unobserved components models," Econometric Reviews, Taylor & Francis Journals, volume 40, issue 5, pages 433-454, April, DOI: 10.1080/07474938.2020.1793508.
• Antoine A. Djogbenou, 2021, "Model selection in factor-augmented regressions with estimated factors," Econometric Reviews, Taylor & Francis Journals, volume 40, issue 5, pages 470-503, April, DOI: 10.1080/07474938.2020.1808371.
• 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, volume 39, issue 1, pages 307-324, January, DOI: 10.1080/07350015.2019.1660175.
• Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2021, "Price Dividend Ratio and Long-Run Stock Returns: A Score-Driven State Space Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 39, issue 4, pages 1054-1065, October, DOI: 10.1080/07350015.2020.1763805.
• Selcuk Gul & Abdullah Kazdal, 2021, "Nowcasting and Short-term Forecasting Turkish GDP: Factor-MIDAS Approach," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 2111.
• Ioannis Sitzimis, 2021, "An Optimal Forecasting Method of Passenger Traffic in Greek Coastal Shipping," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, volume 14, issue 3, pages 72-87, December.
• Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2021, "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 21-016/III, Feb.
• Knut Are Aastveit & Jamie Cross & Herman K. van Dijk, 2021, "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 21-053/III, Jun.
• Yongchen Zhao, 2021, "Uncertainty and Disagreement of Inflation Expectations: Evidence from Household-Level Qualitative Survey Responses," Working Papers, Towson University, Department of Economics, number 2021-03, Dec, revised Dec 2021.
• K. Peren Arin & Kevin Devereux & Mieszko Mazur, 2021, "Taxes and Firm Investment," Working Papers, School of Economics, University College Dublin, number 202102, Jan.
• Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2021, "Efficient Combined Estimation under Structural Breaks," Working Papers, University of California at Riverside, Department of Economics, number 202101, Jan.
• Nadiia Shapovalenko, 2021, "A BVAR Model for Forecasting Ukrainian Inflation and GDP," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 251, pages 14-36, DOI: 10.26531/vnbu2021.251.02.
• Mubarok, Faizul & Al Arif, Mohammad Nur Rianto, 2021, "Pandemic Attack and Islamic Stocks Index: A Cross Country Analysis," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, volume 55, issue 1, pages 27-37, DOI: http://dx.doi.org/10.17576/JEM-2021.
• Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021, "Evaluating forecast performance with state dependence," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1800, Jul.
• Monica Billio & Roberto Casarin & Enrica De Cian & Malcolm Mistry & Anthony Osuntuyi, 2021, "The Impact of Climate on Economic and Financial Cycles: A Markov-switching Panel Approach," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2021:03.
• Jitender, 2021, "Value-at-Risk Estimation of Equity Market Risk in India," Acta Universitatis Sapientiae, Economics and Business, Paradigm, volume 9, issue 1, pages 1-24, September, DOI: 10.2478/auseb-2021-0001.
• Kaczmarczyk Paweł, 2021, "Econometric Modelling of Compound Cyclicality of using Telecommunication Services," Econometrics. Advances in Applied Data Analysis, Paradigm, volume 25, issue 2, pages 27-45, June, DOI: 10.15611/eada.2021.2.03.
• Chi Yeong Nain & Chi Orson, 2021, "Modeling and Forecasting of Monthly Global Price of Bananas Using Seasonal Arima and Multilayer Perceptron Neural Network," Econometrics. Advances in Applied Data Analysis, Paradigm, volume 25, issue 3, pages 21-41, September, DOI: 10.15611/eada.2021.3.02.
• Lauraéus Theresa & Kaivo-oja Jari & Knudsen Mikkel S. & Kuokkanen Kimmo, 2021, "Market Structure analysis with Herfindahl-Hirchman Index and Lauraéus-Kaivo-Oja Indices in the Global Cobotics Markets," Economics and Culture, Paradigm, volume 18, issue 1, pages 70-81, June, DOI: 10.2478/jec-2021-0006.
• Wang Guan-Yuan, 2021, "The Brand Effect: A Case Study in Taiwan Second-Hand Smartphone Market," Journal of Social and Economic Statistics, Paradigm, volume 10, issue 1-2, pages 30-42, December, DOI: 10.2478/jses-2021-0003.
• Ataguba Joseph Obaje, 2021, "Synthesis of Short-Cut DCF Appraisal and Spreadsheet Iteration of Freehold Rental Growth Rates Across Specific Valuation Epochs," Real Estate Management and Valuation, Paradigm, volume 29, issue 2, pages 52-70, June, DOI: 10.2478/remav-2021-0013.
• Ramadani Gani & Petrovska Magdalena & Bucevska Vesna, 2021, "Evaluation of Mixed Frequency Approaches for Tracking Near-Term Economic Developments in North Macedonia," South East European Journal of Economics and Business, Paradigm, volume 16, issue 2, pages 43-52, December, DOI: 10.2478/jeb-2021-0013.
• Dawid Siwicki, 2021, "The Application of Machine Learning Algorithms for Spatial Analysis: Predicting of Real Estate Prices in Warsaw," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-05.
• Mateusz Buczyński & Marcin Chlebus, 2021, "GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-08.
• Michał Woźniak & Marcin Chlebus, 2021, "HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-10.
• Szymon Lis & Marcin Chlebus, 2021, "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-11.
• Piotr Borowski & Marcin Chlebus, 2021, "Machine learning in the prediction of flat horse racing results in Poland," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-13.
• Kamil Korzeń & Robert Ślepaczuk, 2021, "Enhanced Index Replication Based on Smart Beta and Tail-Risk Asset Allocation," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-18.
• Michał Lewandowski & Marcin Chlebus, 2021, "Predicting football outcomes from Spanish league using machine learning models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-22.
• Jan Grudniewicz & Robert Ślepaczuk, 2021, "Application of machine learning in quantitative investment strategies on global stock markets," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-23.
• Nguyen Vo & Robert Ślepaczuk, 2021, "Applying Hybrid ARIMA-SGARCH in Algorithmic Investment Strategies on S&P500 Index," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-25.
• Sergio Castellano Gómez & Robert Ślepaczuk, 2021, "Robust optimisation in algorithmic investment strategies," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-27.
• Aleksander Schiffers & Marcin Chlebus, 2021, "The effectiveness of Value-at-Risk models in various volatility regimes," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-28.
• Stefan Jestl & Robert Stehrer, 2021, "EU Employment Dynamics: The Pandemic Years and Beyond," wiiw Research Reports, The Vienna Institute for International Economic Studies, wiiw, number 457, Nov.
• Vadim Kufenko & Klaus Prettner, 2021, "Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators," Department of Economics Working Papers, Vienna University of Economics and Business, Department of Economics, number wuwp316, Sep.
• Kufenko, Vadim & Prettner, Klaus, 2021, "Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators," Department of Economics Working Paper Series, WU Vienna University of Economics and Business, number 316, Sep.
• Reinhard Ellwanger, Stephen Snudden, 2021, "Predictability of Aggregated Time Series," LCERPA Working Papers, Laurier Centre for Economic Research and Policy Analysis, number bm0127.
• Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2021, "Dynamic return and volatility spillovers among S&P 500, crude oil, and gold," International Journal of Finance & Economics, John Wiley & Sons, Ltd., volume 26, issue 1, pages 153-170, January, DOI: 10.1002/ijfe.1782.
• Jörg Breitung & Malte Knüppel, 2021, "How far can we forecast? Statistical tests of the predictive content," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 36, issue 4, pages 369-392, June, DOI: 10.1002/jae.2817.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021, "No‐arbitrage priors, drifting volatilities, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 36, issue 5, pages 495-516, August, DOI: 10.1002/jae.2828.
• Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021, "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 36, issue 5, pages 517-543, August, DOI: 10.1002/jae.2810.
• Till Weigt & Bernd Wilfling, 2021, "An approach to increasing forecast‐combination accuracy through VAR error modeling," Journal of Forecasting, John Wiley & Sons, Ltd., volume 40, issue 4, pages 686-699, July, DOI: 10.1002/for.2733.
• Ricardo Crisóstomo, 2021, "Estimating real‐world probabilities: A forward‐looking behavioral framework," Journal of Futures Markets, John Wiley & Sons, Ltd., volume 41, issue 11, pages 1797-1823, November, DOI: 10.1002/fut.22248.
• Benjamin K. Johannsen & Elmar Mertens, 2021, "A Time‐Series Model of Interest Rates with the Effective Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, volume 53, issue 5, pages 1005-1046, August, DOI: 10.1111/jmcb.12771.
• John B. Donaldson & Rajnish Mehra, 2021, "Average crossing time: An alternative characterization of mean aversion and reversion," Quantitative Economics, Econometric Society, volume 12, issue 3, pages 903-944, July, DOI: 10.3982/QE1560.
• Garg, Karan, 2021, "Machines and Markets : Assessing the Impact of Algorithmic Trading on Financial Market Efficiency," Warwick-Monash Economics Student Papers, Warwick Monash Economics Student Papers, number 11.
• Aldott, Zoltan, 2021, "Predicting Specialty Coffee Auction Prices Using Machine Learning," Warwick-Monash Economics Student Papers, Warwick Monash Economics Student Papers, number 15.
• Gan-Ochir Doojav & Davaasukh Damdinjav, 2021, "Policy-Driven Boom and Bust in the Housing Market: Evidence from Mongolia," Asian Development Review (ADR), World Scientific Publishing Co. Pte. Ltd., volume 38, issue 02, pages 279-317, September, DOI: 10.1142/S0116110521500050.
• Soumya Bhadury & Saurabh Ghosh & Pankaj Kumar, 2021, "Constructing a Coincident Economic Indicator for India: How Well Does It Track Gross Domestic Product?," Asian Development Review (ADR), World Scientific Publishing Co. Pte. Ltd., volume 38, issue 02, pages 237-277, September, DOI: 10.1142/S0116110521500104.
• Laura Coroneo & Fabrizio Iacone, 2021, "Testing for equal predictive accuracy with strong dependence," Discussion Papers, Department of Economics, University of York, number 21/03, May.
• Laura Coroneo, & Fabrizio Iacone, & Giancarlo Manzi, & Silvia Salini, 2021, "Predicting the COVID-19 epidemic: is a regional approach preferable?," Discussion Papers, Department of Economics, University of York, number 21/06, Sep.
• Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2021, "The bias and efficiency of the ECB inflation projections: A state dependent analysis," Bank of Finland Research Discussion Papers, Bank of Finland, number 7/2021.
• Martins, Manuel Mota Freitas & Verona, Fabio, 2021, "Inflation dynamics and forecast: Frequency matters," Bank of Finland Research Discussion Papers, Bank of Finland, number 8/2021.
• Mönch, Emanuel & Stein, Tobias, 2021, "Equity premium predictability over the business cycle," Discussion Papers, Deutsche Bundesbank, number 25/2021.
• Bańbura, Marta & Leiva-León, Danilo & Menz, Jan-Oliver, 2021, "Do inflation expectations improve model-based inflation forecasts?," Discussion Papers, Deutsche Bundesbank, number 48/2021.
• Memmel, Christoph & Roling, Christoph, 2021, "Risks in domestic banks' corporate lending business," Technical Papers, Deutsche Bundesbank, number 08/2021.
• Memmel, Christoph & Roling, Christoph, 2021, "Risiken im Unternehmenskreditgeschäft inländischer Banken
  [Risks in domestic banks' corporate lending business]," Technical Papers, Deutsche Bundesbank, number 08/2021.
• Falter, Alexander & Kleemann, Michael & Strobel, Lena & Wilke, Hannes, 2021, "Stress testing market risk of German financial intermediaries," Technical Papers, Deutsche Bundesbank, number 11/2021.
• Kukacka, Jiri & Sacht, Stephen, 2021, "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2021-01.
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021, "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
• Lyócsa, Štefan & Baumöhl, Eduard & Vŷrost, Tomáš, 2021, "YOLO trading: Riding with the herd during the GameStop episode," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 230679.
• Hauber, Philipp, 2021, "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 251469.
• 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, DOI: 10.25592/uhhfdm.8630.
• Hügle, Dominik, 2021, "The decision to enrol in higher education," Discussion Papers, Free University Berlin, School of Business & Economics, number 2021/8, DOI: 10.17169/refubium-29947.
• Cerqua, Augusto & Letta, Marco, 2021, "Local inequalities of the COVID-19 crisis," GLO Discussion Paper Series, Global Labor Organization (GLO), number 875.
• Stamer, Vincent, 2021, "Thinking outside the container: A machine learning approach to forecasting trade flows," Kiel Working Papers, Kiel Institute for the World Economy, number 2179.
• Milivojevic, Lazar & Tatar, Balint, 2021, "Fixed exchange rate - a friend or foe of labor cost adjustments?," IMFS Working Paper Series, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), number 152.
• Agarwala, Matthew & Burke, Matt & Klusak, Patrycja & Kraemer, Moritz & Mohaddes, Kamiar, 2021, "Rising temperatures, falling ratings: The effect of climate change on sovereign creditworthiness," IMFS Working Paper Series, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), number 158.
• Li, Wei & Paraschiv, Florentina & Sermpinis, Georgios, 2021, "A data-driven explainable case-based reasoning approach for financial risk detection," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2021-010.
• Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021, "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2021-020.
• Glas, Alexander & Heinisch, Katja, 2021, "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 7/2021.
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Zeddies, Götz, 2021, "Investitionen, Auslastungsgrad und Öffentliche Finanzen in der mittleren Frist: Implikationen des Zweiten Nachtragshaushalts 2021," Konjunktur aktuell, Halle Institute for Economic Research (IWH), volume 9, issue 4, pages 141-148.
• Blagov, Boris & Müller, Henrik & Jentsch, Carsten & Schmidt, Torsten, 2021, "The investment narrative: Improving private investment forecasts with media data," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 921, DOI: 10.4419/96973067.
• Kremer, Manfred & Chavleishvili, Sulkhan, 2021, "Measuring Systemic Financial Stress and its Impact on the Macroeconomy," VfS Annual Conference 2021 (Virtual Conference): Climate Economics, Verein für Socialpolitik / German Economic Association, number 242346.

2020

• Rangan Gupta & Hylton Hollander & Rudi Steinbach, 2020, "Forecasting output growth using a DSGE-based decomposition of the South African yield curve," Empirical Economics, Springer, volume 58, issue 1, pages 351-378, January, DOI: 10.1007/s00181-018-1607-4.
• Nima Nonejad, 2020, "Does the price of crude oil help predict the conditional distribution of aggregate equity return?," Empirical Economics, Springer, volume 58, issue 1, pages 313-349, January, DOI: 10.1007/s00181-019-01643-2.
• Christian Glocker & Philipp Wegmueller, 2020, "Business cycle dating and forecasting with real-time Swiss GDP data," Empirical Economics, Springer, volume 58, issue 1, pages 73-105, January, DOI: 10.1007/s00181-019-01666-9.
• M. Chudý & S. Karmakar & W. B. Wu, 2020, "Long-term prediction intervals of economic time series," Empirical Economics, Springer, volume 58, issue 1, pages 191-222, January, DOI: 10.1007/s00181-019-01689-2.
• Boriss Siliverstovs, 2020, "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, volume 58, issue 1, pages 7-27, January, DOI: 10.1007/s00181-019-01704-6.
• Marcus P. A. Cobb, 2020, "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, volume 58, issue 1, pages 287-312, January, DOI: 10.1007/s00181-019-01720-6.
• 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, volume 58, issue 1, pages 257-286, January, DOI: 10.1007/s00181-019-01738-w.
• Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020, "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, volume 58, issue 1, pages 139-167, January, DOI: 10.1007/s00181-019-01788-0.
• João C. Claudio & Katja Heinisch & Oliver Holtemöller, 2020, "Nowcasting East German GDP growth: a MIDAS approach," Empirical Economics, Springer, volume 58, issue 1, pages 29-54, January, DOI: 10.1007/s00181-019-01810-5.
• Ines Fortin & Sebastian P. Koch & Klaus Weyerstrass, 2020, "Evaluation of economic forecasts for Austria," Empirical Economics, Springer, volume 58, issue 1, pages 107-137, January, DOI: 10.1007/s00181-019-01814-1.
• Christian Pierdzioch & Marian Risse, 2020, "Forecasting precious metal returns with multivariate random forests," Empirical Economics, Springer, volume 58, issue 3, pages 1167-1184, March, DOI: 10.1007/s00181-018-1558-9.
• Kyle E. Binder & Mohsen Pourahmadi & James W. Mjelde, 2020, "The role of temporal dependence in factor selection and forecasting oil prices," Empirical Economics, Springer, volume 58, issue 3, pages 1185-1223, March, DOI: 10.1007/s00181-018-1574-9.
• Aitor Ciarreta & Peru Muniain & Ainhoa Zarraga, 2020, "Realized volatility and jump testing in the Japanese electricity spot market," Empirical Economics, Springer, volume 58, issue 3, pages 1143-1166, March, DOI: 10.1007/s00181-018-1577-6.
• Rodrigo Herrera & Adam Clements, 2020, "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, volume 58, issue 4, pages 1575-1601, April, DOI: 10.1007/s00181-018-1600-y.
• João F. Caldeira, 2020, "Investigating the expectation hypothesis and the risk premium dynamics: new evidence for Brazil," Empirical Economics, Springer, volume 59, issue 1, pages 395-412, July, DOI: 10.1007/s00181-019-01629-0.
• Holger Stichnoth, 2020, "Short-run fertility effects of parental leave benefits: evidence from a structural model," Empirical Economics, Springer, volume 59, issue 1, pages 143-168, July, DOI: 10.1007/s00181-019-01673-w.
• 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, volume 59, issue 3, pages 1285-1305, September, DOI: 10.1007/s00181-019-01665-w.
• Yana Petrova, 2020, "On cointegration between the insurance market and economic activity," Empirical Economics, Springer, volume 59, issue 3, pages 1127-1138, September, DOI: 10.1007/s00181-019-01669-6.