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

2022

• Christian Gourieroux & Joann Jasiak, 2022. "Long Run Predictions," Annals of Economics and Statistics, GENES, issue 145, pages 75-90.
• Paul Beaudry & Tim Willems, 2022. "On the Macroeconomic Consequences of Over-Optimism," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(1), pages 38-59, January.
  • Paul Beaudry & Tim Willems, 2018. "On the Macroeconomic Consequences of Over-Optimism," NBER Working Papers 24685, National Bureau of Economic Research, Inc.
  • Tim Willems & Paul Beaudry, 2018. "On the Macroeconomic Consequences of Over-Optimism," IMF Working Papers 2018/122, International Monetary Fund.
• Ilya V. Naumov & Sergey S. Krasnykh & Yulia S. Otmakhova, 2022. "Scenario forecasting of the socio-economic consequences of the COVID-19 pandemic in Russian regions," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 8(1), pages 5-20.
• Nuno Goncalves, 2022. "Most probable or more prudent? Analysing CFP's macroeconomic projections, 2015-2019," CFP Occasional Papers 02/2022, Portuguese Public Finance Council.
• Lafond, François & Farmer, J. Doyne & Mungo, Luca & Astudillo-Estévez, Pablo, 2022. "Reconstructing production networks using machine learning," INET Oxford Working Papers 2022-02, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
• Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," CEPR Discussion Papers 17111, C.E.P.R. Discussion Papers.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," Papers 2201.05556, arXiv.org.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," Working Papers hal-03573080, HAL.
• Fiaschi, Davide & Tealdi, Cristina, 2022. "Scarring Effects of the COVID-19 Pandemic on the Italian Labour Market," IZA Discussion Papers 15102, Institute of Labor Economics (IZA).
  • Davide Fiaschi & Cristina Tealdi, 2022. "Scarring effects of the COVID-19 pandemic on the Italian labour market," Papers 2202.13317, arXiv.org.
• Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022. "Forecasting US Inflation Using Bayesian Nonparametric Models," Working Papers 22-05, Federal Reserve Bank of Cleveland.
  • Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022. "Forecasting US Inflation Using Bayesian Nonparametric Models," Papers 2202.13793, arXiv.org.
• Francis X. Diebold & Glenn D. Rudebusch & Maximilian Gobel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," PIER Working Paper Archive 22-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Francis X. Diebold & Glenn D. Rudebusch & Maximilian Goebel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," Papers 2203.04040, arXiv.org.
• Tony Chernis & Taylor Webley, 2022. "Nowcasting Canadian GDP with Density Combinations," Discussion Papers 2022-12, Bank of Canada.
• Hossein Hosseini & Craig Johnston & Craig Logan & Miguel Molico & Xiangjin Shen & Marie-Christine Tremblay, 2022. "Assessing Climate-Related Financial Risk: Guide to Implementation of Methods," Technical Reports 120, Bank of Canada.
• James Chapman & Ajit Desai, 2022. "Macroeconomic Predictions Using Payments Data and Machine Learning," Staff Working Papers 22-10, Bank of Canada.
• Celal OZTURK & Cemal IBIS, 2022. "Behavioral Modelling of Non-Maturing and Time Deposits in Liquidity Risk Management," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 16(1), pages 1-26.
• Donato Ceci & Andrea Silvestrini, 2022. "Nowcasting the state of the Italian economy: the role of financial markets," Temi di discussione (Economic working papers) 1362, Bank of Italy, Economic Research and International Relations Area.
• Youssef Ulgazi & Paul Vertier, 2022. "Forecasting Inflation in France: an Update of MAPI," Working papers 869, Banque de France.
• Ana Aguilar & María Diego-Fernández & Rocio Elizondo & Jessica Roldán-Peña, 2022. "Term premium dynamics and its determinants: the Mexican case," BIS Working Papers 993, Bank for International Settlements.
• Aleksei Kipriyanov, 2022. "Comparison of Models for Growth-at-Risk Forecasting," Russian Journal of Money and Finance, Bank of Russia, vol. 81(1), pages 23-45, March.
• Sergey Ivashchenko, 2022. "Dynamic Stochastic General Equilibrium Model with Multiple Trends and Structural Breaks," Russian Journal of Money and Finance, Bank of Russia, vol. 81(1), pages 46-72, March.
• Urmat Dzhunkeev, 2022. "Forecasting Unemployment in Russia Using Machine Learning Methods," Russian Journal of Money and Finance, Bank of Russia, vol. 81(1), pages 73-87, March.
• Fulvia Pennoni & Francesco Bartolucci & Gianfranco Forte & Ferdinando Ametrano, 2022. "Exploring the dependencies among main cryptocurrency log‐returns: A hidden Markov model," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(1), February.
  • 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.
• Shang Han Lin & Zhang Xibin, 2022. "Bayesian bandwidth estimation for local linear fitting in nonparametric regression models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 55-71, February.
• Segnon Mawuli & Wilfling Bernd & Lau Chi Keung & Gupta Rangan, 2022. "Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 73-98, February.
  • Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are Multifractal Processes Suited to Forecasting Electricity Price Volatility? Evidence from Australian Intraday Data," Working Papers 201739, University of Pretoria, Department of Economics.
  • Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data," CQE Working Papers 6117, Center for Quantitative Economics (CQE), University of Muenster.
• Pesaran, M. H. & Pick, A. & Timmermann, A., 2022. "Forecasting with panel data: estimation uncertainty versus parameter heterogeneity," Cambridge Working Papers in Economics 2219, Faculty of Economics, University of Cambridge.
• Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Cambridge Working Papers in Economics 2220, Faculty of Economics, University of Cambridge.
• Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Janeway Institute Working Papers 2209, Faculty of Economics, University of Cambridge.
• Congressional Budget Office, 2022. "The Accuracy of CBO’s Budget Projections for Fiscal Year 2021," Reports 57614, Congressional Budget Office.
• Congressional Budget Office, 2022. "A Markov-Switching Model of the Unemployment Rate: Working Paper 2022-05," Working Papers 57582, Congressional Budget Office.
• U. Devrim Demirel & James Otterson, 2022. "Quantifying the Uncertainty of Long-Term Economic Projections: Working Paper 2022-07," Working Papers 57711, Congressional Budget Office.
• Xu, Yongdeng, 2022. "Exponential High-Frequency-Based-Volatility (EHEAVY) Models," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
• Blazsek, Szabolcs & Escribano, Álvaro, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
• Lukas Boer, 2022. "Steigende Metallpreise als mögliches Hindernis der Energiewende," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 89(4), pages 47-55.
• Chahad, Mohammed & Hofmann-Drahonsky, Anna-Camilla & Page, Adrian & Tirpák, Marcel & Meunier, Baptiste, 2022. "What explains recent errors in the inflation projections of Eurosystem and ECB staff?," Economic Bulletin Boxes, European Central Bank, vol. 3.
• Andrey V. Polbin & Andrey V. Shumilov, 2022. "Об Использовании Моделей Панельных Данных Для Прогнозирования Темпов Роста Отраслей Российской Обрабатывающей Промышленности," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 2, pages 15-19, February.
• Conlon, Thomas & Cotter, John & Eyiah-Donkor, Emmanuel, 2022. "The illusion of oil return predictability: The choice of data matters!," Journal of Banking & Finance, Elsevier, vol. 134(C).
  • Thomas Conlon & John Cotter & Emmanuel Eyiah-Donkor, 2022. "The illusion of oil return predictability: The choice of data matters!," Post-Print hal-03519860, HAL.
• Jardet Caroline & Meunier Baptiste, 2020. "Nowcasting World GDP Growth with High-Frequency Data," Working papers 788, Banque de France.
  • Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
• Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," CEPR Discussion Papers 17111, C.E.P.R. Discussion Papers.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," Working Papers hal-03573080, HAL.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," Papers 2201.05556, arXiv.org.
• Gergõ Tóth & Zoltán Elekes & Adam Whittle & Changjun Lee & Dieter F. Kogler, 2022. "Technology network structure conditions the economic resilience of regions," CERS-IE WORKING PAPERS 2202, Institute of Economics, Centre for Economic and Regional Studies.
• Morita, Hiroshi, 2022. "Forecasting GDP growth using stock returns in Japan: A factor-augmented MIDAS approach," Discussion paper series HIAS-E-118, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
• Montserrat Reyna Miranda & Ricardo Massa Roldán & Vicente Gómez Salcido, 2022. "Neuro-wavelet Model for price prediction in high-frequency data in the Mexican Stock market," 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. 17(1), pages 1-23, Enero - M.
• Davide Fiaschi & Cristina Tealdi, 2022. "Scarring effects of the COVID-19 pandemic on the Italian labour market," Papers 2202.13317, arXiv.org.
  • Fiaschi, Davide & Tealdi, Cristina, 2022. "Scarring Effects of the COVID-19 Pandemic on the Italian Labour Market," IZA Discussion Papers 15102, Institute of Labor Economics (IZA).
• Immervoll, Herwig & Hyee, Raphaela & Fernandez, Rodrigo & Lee, Jongmi, 2022. "How Reliable Are Social Safety Nets? Value and Accessibility in Situations of Acute Economic Need," IZA Discussion Papers 15232, Institute of Labor Economics (IZA).
• Foltas Alexander, 2022. "Testing Investment Forecast Efficiency with Forecasting Narratives," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 242(2), pages 191-222, April.
• Fabian Baier & Peter Berster & Marc Gelhausen, 2022. "Global cargo gravitation model: airports matter for forecasts," International Economics and Economic Policy, Springer, vol. 19(1), pages 219-238, February.
• Chris Charalambous & Spiros H. Martzoukos & Zenon Taoushianis, 2022. "Estimating corporate bankruptcy forecasting models by maximizing discriminatory power," Review of Quantitative Finance and Accounting, Springer, vol. 58(1), pages 297-328, January.
• Ludmila Fadejeva & Boriss Siliverstovs & Karlis Vilerts & Anete Brinke, 2022. "Consumer Spending in the Covid-19 Pandemic: Evidence from Card Transactions in Latvia," Discussion Papers 2022/01, Latvijas Banka.
• Andreas Marcus Gohs, 2022. "Forecasting Market Diffusion of Innovative Battery-Electric and Conventional Vehicles in Germany under Model Uncertainty," MAGKS Papers on Economics 202209, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Tino Berger & Christian Ochsner, 2022. "Tracking the German Business Cycle," MAGKS Papers on Economics 202212, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Makram El-Shagi & Yizhuang Zheng, 2022. "Money Demand in China: A Meta Study," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 58(1), pages 145-163, January.
  • Makram El-Shagi & Yizhuang Zheng, 2017. "Money Demand in China: A Meta-Study," CFDS Discussion Paper Series 2017/3, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
• Andras Viktor Szabo, 2022. "Credit Risk Modelling of Mortgage Loans in the Supervisory Stress Test of the Magyar Nemzeti Bank," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 21(1), pages 56-94.
• Bianca Reichert & Adriano Mendonça Souza, 2022. "Can the Heston Model Forecast Energy Generation? A Systematic Literature Review," International Journal of Energy Economics and Policy, Econjournals, vol. 12(1), pages 289-295.
• Ambya Ambya & Lies Maria Hamzah, 2022. "Indonesian Coal Exports: Dynamic Panel Analysis Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 12(1), pages 390-395.
• Nikodinoska, Dragana & Käso, Mathias & Müsgens, Felix, 2022. "Solar and wind power generation forecasts using elastic net in time-varying forecast combinations," Applied Energy, Elsevier, vol. 306(PA).
• Wichitaksorn, Nuttanan, 2022. "Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach," Journal of Asian Economics, Elsevier, vol. 78(C).
• Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
  • Luigi Longo & Massimo Riccaboni & Armando Rungi, 2021. "A Neural Network Ensemble Approach for GDP Forecasting," Working Papers 02/2021, IMT School for Advanced Studies Lucca, revised Mar 2021.
• Tsuchiya, Yoichi, 2022. "Evaluating the European Central Bank’s uncertainty forecasts," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 321-330.
• Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
• Jang, Hyuna & Kim, Jong-Min & Noh, Hohsuk, 2022. "Vine copula Granger causality in mean," Economic Modelling, Elsevier, vol. 109(C).
• Yang, Yanlin & Hu, Xuemei & Jiang, Huifeng, 2022. "Group penalized logistic regressions predict up and down trends for stock prices," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
• Salisu, Afees A. & Gupta, Rangan & Pierdzioch, Christian, 2022. "Predictability of tail risks of Canada and the U.S. Over a Century: The role of spillovers and oil tail Risks☆," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
• Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
• Bognanni, Mark, 2022. "Comment on “Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors”," Journal of Econometrics, Elsevier, vol. 227(2), pages 498-505.
• Angelico, Cristina & Marcucci, Juri & Miccoli, Marcello & Quarta, Filippo, 2022. "Can we measure inflation expectations using Twitter?," Journal of Econometrics, Elsevier, vol. 228(2), pages 259-277.
• Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
• Zhang, Han & Guo, Bin & Liu, Lanbiao, 2022. "The time-varying bond risk premia in China," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 51-76.
• Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2022. "Forecasting natural gas consumption using Bagging and modified regularization techniques," Energy Economics, Elsevier, vol. 106(C).
• Pincheira-Brown, Pablo & Bentancor, Andrea & Hardy, Nicolás & Jarsun, Nabil, 2022. "Forecasting fuel prices with the Chilean exchange rate: Going beyond the commodity currency hypothesis," Energy Economics, Elsevier, vol. 106(C).
• Mahler, Valentin & Girard, Robin & Kariniotakis, Georges, 2022. "Data-driven structural modeling of electricity price dynamics," Energy Economics, Elsevier, vol. 107(C).
• Ren, Xiaohang & Duan, Kun & Tao, Lizhu & Shi, Yukun & Yan, Cheng, 2022. "Carbon prices forecasting in quantiles," Energy Economics, Elsevier, vol. 108(C).
• Salisu, Afees A. & Gupta, Rangan & Demirer, Riza, 2022. "Global financial cycle and the predictability of oil market volatility: Evidence from a GARCH-MIDAS model," Energy Economics, Elsevier, vol. 108(C).
  • Afees A. Salisu & Rangan Gupta & Riza Demirer, 2021. "Global Financial Cycle and the Predictability of Oil Market Volatility: Evidence from a GARCH-MIDAS Model," Working Papers 202121, University of Pretoria, Department of Economics.
• Li, Xiafei & Liang, Chao & Chen, Zhonglu & Umar, Muhammad, 2022. "Forecasting crude oil volatility with uncertainty indicators: New evidence," Energy Economics, Elsevier, vol. 108(C).
• Luo, Keyu & Guo, Qiang & Li, Xiafei, 2022. "Can the return connectedness indices from grey energy to natural gas help to forecast the natural gas returns?," Energy Economics, Elsevier, vol. 109(C).
• Salisu, Afees A. & Olaniran, Abeeb & Tchankam, Jean Paul, 2022. "Oil tail risk and the tail risk of the US Dollar exchange rates," Energy Economics, Elsevier, vol. 109(C).
• Umar, Zaghum & Aharon, David Y. & Esparcia, Carlos & AlWahedi, Wafa, 2022. "Spillovers between sovereign yield curve components and oil price shocks," Energy Economics, Elsevier, vol. 109(C).
• Kertlly de Medeiros, Rennan & da Nóbrega Besarria, Cássio & Pitta de Jesus, Diego & Phillipe de Albuquerquemello, Vinicius, 2022. "Forecasting oil prices: New approaches," Energy, Elsevier, vol. 238(PC).
• Kuang, Wei, 2022. "The economic value of high-frequency data in equity-oil hedge," Energy, Elsevier, vol. 239(PA).
• Resce, Giuliano & Vaquero-Pineiro, Cristina, 2022. "Predicting Agri-food Quality across Space: A Machine Learning Model for the Acknowledgment of Geographical Indications," Economics & Statistics Discussion Papers esdp22082, University of Molise, Department of Economics.
• Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Papers 2012.11649, arXiv.org, revised Jan 2021.
  • Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2022. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," NBER Working Papers 29635, National Bureau of Economic Research, Inc.
  • Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone In?ation and Real Interest Rates," PIER Working Paper Archive 21-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
• Richard B. Freeman, 2022. "Planning for the “Expected Unexpected”: Work and Retirement in the U.S. After the COVID-19 Pandemic Shock," NBER Working Papers 29653, National Bureau of Economic Research, Inc.
• Petar Rangelov, 2022. "Application of Simulation-based Approach for Determining the Value of Companies Operating in an Environment of Uncertainty," Ikonomiceski i Sotsialni Alternativi, University of National and World Economy, Sofia, Bulgaria, issue 1, pages 111-131, March.
• Grégoire Tallard & Marcel Adenäuer & Koen Deconinck & Gaëlle Gouarin, 2022. "Potential impact of dietary changes on the triple challenge facing food systems: Three stylised scenarios," OECD Food, Agriculture and Fisheries Papers 173, OECD Publishing.
• Francis X. Diebold & Maximilian Gobel, 2022. "A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting," PIER Working Paper Archive 22-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Francis X. Diebold & Glenn D. Rudebusch & Maximilian Goebel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," Papers 2203.04040, arXiv.org.
  • Francis X. Diebold & Glenn D. Rudebusch & Maximilian Gobel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," PIER Working Paper Archive 22-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Weshah Razzak, 2021. "The Ownership of Oil, Democracy, and Iraq's Past, Present and Future," Discussion Papers 2102, School of Economics and Finance, Massey University, New Zealand.
  • Razzak, Weshah, 2022. "The Ownership of Oil, Democracy, and Iraq’s Past, Present, and Future," MPRA Paper 111417, University Library of Munich, Germany.
• Pincheira, Pablo & Hardy, Nicolas, 2022. "Correlation Based Tests of Predictability," MPRA Paper 112014, University Library of Munich, Germany.
• Arikha, Dahlia, 2022. "Strategi Pembangunan Ekonomi Islam M. Umer Chapra [The Strategy of Islamic Economic Development in Perspective of M. Umer Chapra]," MPRA Paper 112257, University Library of Munich, Germany, revised 28 Feb 2022.
• G.K., Chetan Kumar & K.B., Rangappa & S., Suchitra, 2022. "Analyzing the Impact of Companies’ Investment on Skill Upgradation in Improving their Resilience amidst COVID-19," MPRA Paper 112425, University Library of Munich, Germany.
• Naimoli, Antonio, 2022. "The information content of sentiment indices for forecasting Value at Risk and Expected Shortfall in equity markets," MPRA Paper 112588, University Library of Munich, Germany.
• Lehmann, Robert & Wikman, Ida, 2022. "Quarterly GDP Estimates for the German States," MPRA Paper 112642, University Library of Munich, Germany.
• Li, Chenxing, 2022. "A multivariate GARCH model with an infinite hidden Markov mixture," MPRA Paper 112792, University Library of Munich, Germany.
• Christina Anderl & Guglielmo Maria Caporale, 2022. "Forecasting Inflation with a Zero Lower Bound or Negative Interest Rates: Evidence from Point and Density Forecasts," CESifo Working Paper Series 9687, CESifo.
• M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2022. "Forecasting With Panel Data: Estimation Uncertainty Versus Parameter Heterogeneity," CESifo Working Paper Series 9690, CESifo.
• Didier Sornette & Florian Ulmann & Alexander Wehrli, 2022. "On the Directional Destabilizing Feedback Effects of Option Hedging," Swiss Finance Institute Research Paper Series 22-34, Swiss Finance Institute.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021. "Macroeconomic Forecasting in a Multi-country Context," Working Papers 22-02, Federal Reserve Bank of Cleveland.
  • Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
• Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," Papers 2201.05556, arXiv.org.
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," CEPR Discussion Papers 17111, C.E.P.R. Discussion Papers.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," Working Papers hal-03573080, HAL.
• Pesaran, M Hashem & Pick, Andreas & Timmermann, Allan, 2022. "Forecasting with panel data: estimation uncertainty versus parameter heterogeneity," CEPR Discussion Papers 17123, C.E.P.R. Discussion Papers.
• Inoue, Atsushi & Rossi, Barbara & Wang, Yiru, 2022. "Local Projections in Unstable Environments: How Effective is Fiscal Policy?," CEPR Discussion Papers 17134, C.E.P.R. Discussion Papers.
• Verena Monschang & Bernd Wilfling, 2022. "A procedure for upgrading linear-convex combination forecasts with an application to volatility prediction," CQE Working Papers 9722, Center for Quantitative Economics (CQE), University of Muenster.
• Alanya-Beltran, Willy, 2022. "Modelling stock returns volatility with dynamic conditional score models and random shifts," Finance Research Letters, Elsevier, vol. 45(C).
• Sheng, Xin & Gupta, Rangan & Salisu, Afees A. & Bouri, Elie, 2022. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Finance Research Letters, Elsevier, vol. 45(C).
  • Xin Sheng & Rangan Gupta & Afees A. Salisu & Elie Bouri, 2021. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Working Papers 202101, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Tchankam, Jean Paul, 2022. "US Stock return predictability with high dimensional models," Finance Research Letters, Elsevier, vol. 45(C).
• Kutuk, Yasin & Barokas, Lina, 2022. "Multivariate CDS risk premium prediction with SOTA RNNs on MI[N]T countries," Finance Research Letters, Elsevier, vol. 45(C).
• Duan, Yuejiao & Goodell, John W. & Li, Haoran & Li, Xinming, 2022. "Assessing machine learning for forecasting economic risk: Evidence from an expanded Chinese financial information set," Finance Research Letters, Elsevier, vol. 46(PA).
• Nonejad, Nima, 2022. "Forecasting crude oil price volatility out-of-sample using news-based geopolitical risk index: What forms of nonlinearity help improve forecast accuracy the most?," Finance Research Letters, Elsevier, vol. 46(PA).
• Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš, 2022. "YOLO trading: Riding with the herd during the GameStop episode," Finance Research Letters, Elsevier, vol. 46(PA).
  • 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.
• Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2022. "Oil tail risks and the forecastability of the realized variance of oil-price: Evidence from over 150 years of data," Finance Research Letters, Elsevier, vol. 46(PB).
  • Afees A. Salisu & Christian Pierdzioch & Rangan Gupta, 2021. "Oil Tail Risks and the Forecastability of the Realized Variance of Oil-Price: Evidence from Over 150 Years of Data," Working Papers 202146, University of Pretoria, Department of Economics.
• Zhang, Dan & Farnoosh, Arash & Lantz, Frédéric, 2022. "Does something change in the oil market with the COVID-19 crisis?," International Economics, Elsevier, vol. 169(C), pages 252-268.
• Martin, Gael M. & Loaiza-Maya, Rubén & Maneesoonthorn, Worapree & Frazier, David T. & Ramírez-Hassan, Andrés, 2022. "Optimal probabilistic forecasts: When do they work?," International Journal of Forecasting, Elsevier, vol. 38(1), pages 384-406.
  • Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
  • Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
• Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2022. "Forecasting realized volatility of agricultural commodities," International Journal of Forecasting, Elsevier, vol. 38(1), pages 74-96.
  • Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2019. "Forecasting Realized Volatility of Agricultural Commodities," MPRA Paper 96267, University Library of Munich, Germany.
• Lahiri, Kajal & Yang, Cheng, 2022. "Boosting tax revenues with mixed-frequency data in the aftermath of COVID-19: The case of New York," International Journal of Forecasting, Elsevier, vol. 38(2), pages 545-566.
  • Kajal Lahiri & Cheng Yang, 2021. "Boosting Tax Revenues with Mixed-Frequency Data in the Aftermath of Covid-19: The Case of New York," CESifo Working Paper Series 9365, CESifo.
• Conlon, Thomas & Cotter, John & Eyiah-Donkor, Emmanuel, 2022. "The illusion of oil return predictability: The choice of data matters!," Journal of Banking & Finance, Elsevier, vol. 134(C).
  • Thomas Conlon & John Cotter & Emmanuel Eyiah-Donkor, 2022. "The illusion of oil return predictability: The choice of data matters!," Post-Print hal-03519860, HAL.
• Caporin, Massimiliano & Costola, Michele & Garibal, Jean-Charles & Maillet, Bertrand, 2022. "Systemic risk and severe economic downturns: A targeted and sparse analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
• Huang, Rong & Pilbeam, Keith & Pouliot, William, 2022. "Are macroeconomic forecasters optimists or pessimists? A reassessment of survey based forecasts," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 706-724.
• Obaid, Khaled & Pukthuanthong, Kuntara, 2022. "A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news," Journal of Financial Economics, Elsevier, vol. 144(1), pages 273-297.
• Kishor, N. Kundan & Marfatia, Hardik A. & Nam, Gooan & Rizi, Majid Haghani, 2022. "The local employment effect of house prices: Evidence from U.S. States," Journal of Housing Economics, Elsevier, vol. 55(C).
• Degiannakis, Stavros & Filis, George, 2022. "Oil price volatility forecasts: What do investors need to know?," Journal of International Money and Finance, Elsevier, vol. 123(C).
  • Degiannakis, Stavros & Filis, George, 2019. "Oil price volatility forecasts: What do investors need to know?," MPRA Paper 94445, University Library of Munich, Germany.
• Stolbov, Mikhail & Shchepeleva, Maria, 2022. "Modeling global real economic activity: Evidence from variable selection across quantiles," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
• Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
• Salisu, Afees A. & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil prices over 150 years: The role of tail risks," Resources Policy, Elsevier, vol. 75(C).
  • Afees A. Salisu & Rangan Gupta & Qiang Ji, 2021. "Forecasting Oil Price over 150 Years: The Role of Tail Risks," Working Papers 202120, University of Pretoria, Department of Economics.
• Yan, Xiang & Bai, Jiancheng & Li, Xiafei & Chen, Zhonglu, 2022. "Can dimensional reduction technology make better use of the information of uncertainty indices when predicting volatility of Chinese crude oil futures?," Resources Policy, Elsevier, vol. 75(C).
• Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
  • Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," Working Papers 202133, University of Pretoria, Department of Economics.
  • Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," GRU Working Paper Series GRU_2021_017, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
• Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2022. "A babel of web-searches: Googling unemployment during the pandemic," Labour Economics, Elsevier, vol. 74(C).
• Maples, Chellie H. & Hagerman, Amy D. & Lambert, Dayton M., 2022. "Ex-ante effects of the 2018 Agricultural Improvement Act’s grassland initiative," Land Use Policy, Elsevier, vol. 116(C).
• Umar, Zaghum & Yousaf, Imran & Gubareva, Mariya & Vo, Xuan Vinh, 2022. "Spillover and risk transmission between the term structure of the US interest rates and Islamic equities," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
• Bui, Quynh & Ślepaczuk, Robert, 2022. "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
• Ahmed, Walid M.A., 2022. "On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 135-151.
• Cerqua, Augusto & Letta, Marco, 2022. "Local inequalities of the COVID-19 crisis," Regional Science and Urban Economics, Elsevier, vol. 92(C).
  • Cerqua, Augusto & Letta, Marco, 2021. "Local inequalities of the COVID-19 crisis," GLO Discussion Paper Series 875, Global Labor Organization (GLO).
• Islam, Md. Monirul & Irfan, Muhammad & Shahbaz, Muhammad & Vo, Xuan Vinh, 2022. "Renewable and non-renewable energy consumption in Bangladesh: The relative influencing profiles of economic factors, urbanization, physical infrastructure and institutional quality," Renewable Energy, Elsevier, vol. 184(C), pages 1130-1149.
• Salisu, Afees A. & Cuñado, Juncal & Gupta, Rangan, 2022. "Geopolitical risks and historical exchange rate volatility of the BRICS," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 179-190.
  • Afees A. Salisu & Juncal Cunado & Rangan Gupta, 2020. "Geopolitical Risks and Historical Exchange Rate Volatility of the BRICS," Working Papers 2020105, University of Pretoria, Department of Economics.
• Umar, Zaghum & Riaz, Yasir & Aharon, David Y., 2022. "Network connectedness dynamics of the yield curve of G7 countries," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 275-288.
• Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022. "Semi-nonparametric risk assessment with cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
• Liu Yang & Kajal Lahiri & Adrian Pagan, 2022. "Getting the ROC into Sync," CAMA Working Papers 2022-01, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Calonaci, Fabio & Kapetanios, George & Price, Simon, 2022. "Stock returns predictability with unstable predictors," Essex Finance Centre Working Papers 32331, University of Essex, Essex Business School.
  • Fabio Calonaci & George Kapetanios & Simon Price, 2022. "Stock returns predictability with unstable predictors," CAMA Working Papers 2022-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Ferrara, Laurent & Karadimitropoulou, Aikaterini & Triantafyllou, Athanasios, 2021. "Commodity price uncertainty comovement: Does it matter for global economic growth?," Essex Finance Centre Working Papers 30945, University of Essex, Essex Business School.
  • Laurent Ferrara & Aikaterini Karadimitropoulou & Athanasios Triantafyllou, 2022. "Commodity price uncertainty comovement: Does it matter for global economic growth?," CAMA Working Papers 2022-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Mawuli Segnon & Rangan Gupta & Bernd Wilfling, 2022. "Forecasting Stock Market Volatility with Regime-Switching GARCH-MIDAS: The Role of Geopolitical Risks," Working Papers 202203, University of Pretoria, Department of Economics.
• Oguzhan Cepni & Rangan Gupta & Daniel Pienaar & Christian Pierdzioch, 2022. "Forecasting the Realized Variance of Oil-Price Returns Using Machine-Learning: Is there a Role for U.S. State-Level Uncertainty?," Working Papers 202205, University of Pretoria, Department of Economics.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Climate Risks and Realized Volatility of Major Commodity Currency Exchange Rates," Working Papers 202210, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Elie Bouri, 2022. "Testing the Forecasting Power of Global Economic Conditions for the Volatility of International REITs using a GARCH-MIDAS Approach," Working Papers 202211, University of Pretoria, Department of Economics.
• Elie Bouri & Christina Christou & Rangan Gupta, 2022. "Forecasting Returns of Major Cryptocurrencies: Evidence from Regime-Switching Factor Models," Working Papers 202213, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2022. "Do Economic Conditions of U.S. States Predict the Realized Volatility of Oil-Price Returns? A Quantile Machine-Learning Approach," Working Papers 202216, University of Pretoria, Department of Economics.
• Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022. "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Working Papers 202217, University of Pretoria, Department of Economics.
• Amaro, Raphael & Pinho, Carlos & Madaleno, Mara, 2022. "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 77-101.
• Zubarev, Andrei & Kirillova, Maria, 2022. "Modeling COVID-19 spread in the Russian Federation using global VAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 117-138.
• Mihaela Simionescu & Mihaela-Daniela Vornicescu (Niculescu), 2022. "The Impact of the European Economic Integration on Sustainable Development in the EU New Member States," Bulgarian Economic Papers bep-2022-02, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, revised Jan 2022.
• Christian Hepenstrick & Jason Blunier, 2022. "What were they thinking? Estimating the quarterly forecasts underlying annual growth projections," Working Papers 2022-05, Swiss National Bank.
• Gabriel Lyrio de Oliveira & Andre Luis Squarize Chagas, Denise Leyi Li, 2022. "Public Sector Procurements and Reference Prices Estimation with Small Samples in Brazil," Working Papers, Department of Economics 2022_02, University of São Paulo (FEA-USP).
• Yuting Chen & Don Bredin & Valerio Potì & Roman Matkovskyy, 2022. "COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic," Digital Finance, Springer, vol. 4(1), pages 17-61, March.
• Helmut Wasserbacher & Martin Spindler, 2022. "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, vol. 4(1), pages 63-88, March.
• Lixiong Yang, 2022. "Threshold mixed data sampling (TMIDAS) regression models with an application to GDP forecast errors," Empirical Economics, Springer, vol. 62(2), pages 533-551, February.
• Julián Andrada-Félix & Adrian Fernandez-Perez & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2022. "Time connectedness of fear," Empirical Economics, Springer, vol. 62(3), pages 905-931, March.
  • Julián Andrada-Félixa & Adrian Fernandez-Perez & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2018. "“Time connectedness of fear”," IREA Working Papers 201818, University of Barcelona, Research Institute of Applied Economics, revised Sep 2018.
• Julia Kielmann & Hans Manner & Aleksey Min, 2022. "Stock market returns and oil price shocks: A CoVaR analysis based on dynamic vine copula models," Empirical Economics, Springer, vol. 62(4), pages 1543-1574, April.
• Chao Liang & Yin Liao & Feng Ma & Bo Zhu, 2022. "United States Oil Fund volatility prediction: the roles of leverage effect and jumps," Empirical Economics, Springer, vol. 62(5), pages 2239-2262, May.
• Şirin Özlem & Omer Faruk Tan, 2022. "Predicting cash holdings using supervised machine learning algorithms," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-19, December.
• Eva O. Arceo-Gomez & Raymundo M. Campos-Vazquez & Raquel Y. Badillo & Sergio Lopez-Araiza, 2022. "Gender stereotypes in job advertisements: What do they imply for the gender salary gap?," Journal of Labor Research, Springer, vol. 43(1), pages 65-102, March.
• Richard J. Arend, 2022. "Balancing the perceptions of NK modelling with critical insights," Journal of Innovation and Entrepreneurship, Springer, vol. 11(1), pages 1-15, December.
• Stephanie Glaser & Robert C. Jung & Karsten Schweikert, 2022. "Spatial panel count data: modeling and forecasting of urban crimes," Journal in Spatial Econometrics, Springer, vol. 3(1), pages 1-29, December.
• Jakob A. Dambon & Stefan S. Fahrländer & Saira Karlen & Manuel Lehner & Jaron Schlesinger & Fabio Sigrist & Anna Zimmermann, 2022. "Examining the vintage effect in hedonic pricing using spatially varying coefficients models: a case study of single-family houses in the Canton of Zurich," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 158(1), pages 1-14, December.
• Siddhartha Pradeep, 2022. "Role of monetary policy on CO2 emissions in India," SN Business & Economics, Springer, vol. 2(1), pages 1-33, January.
• Mar Delgado-Téllez & Esther Gordo & Iván Kataryniuk & Javier J. Pérez, 2022. "The decline in public investment: ``social dominance’’ or too-rigid fiscal rules?," Applied Economics, Taylor & Francis Journals, vol. 54(10), pages 1123-1136, February.
  • Mar Delgado-Téllez & Esther Gordo & Iván Kataryniuk & Javier J. Pérez, 2020. "The decline in public investment: “social dominance” or too-rigid fiscal rules?," Working Papers 2025, Banco de España.
• Ioannis Sitzimis, 2022. "An Optimal Forecasting Method of Passenger Traffic in Greek Coastal Shipping," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 14(3), pages 72-87, January.
• Fabio Calonaci & George Kapetanios & Simon Price, 2022. "Stock returns predictability with unstable predictors," CAMA Working Papers 2022-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Calonaci, Fabio & Kapetanios, George & Price, Simon, 2022. "Stock returns predictability with unstable predictors," Essex Finance Centre Working Papers 32331, University of Essex, Essex Business School.
• Ina Hajdini, 2022. "Mis-specified Forecasts and Myopia in an Estimated New Keynesian Model," Working Papers 22-03, Federal Reserve Bank of Cleveland.
• Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022. "Forecasting US Inflation Using Bayesian Nonparametric Models," Papers 2202.13793, arXiv.org.
  • Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022. "Forecasting US Inflation Using Bayesian Nonparametric Models," Working Papers 22-05, Federal Reserve Bank of Cleveland.
• Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates," Working Papers 22-06, Federal Reserve Bank of Cleveland.
• James Mitchell & Aubrey Poon & Dan Zhu, 2022. "Constructing Density Forecasts from Quantile Regressions: Multimodality in Macro-Financial Dynamics," Working Papers 22-12, Federal Reserve Bank of Cleveland.
• Michael Clements & Robert W. Rich & Joseph Tracy, 2022. "Surveys of Professionals," Working Papers 22-13, Federal Reserve Bank of Cleveland.
• Amy Y. Guisinger & Michael W. McCracken & Michael T. Owyang, 2022. "Reconsidering the Fed’s Forecasting Advantage," Working Papers 2022-001, Federal Reserve Bank of St. Louis, revised 02 Jan 2022.
• Andrey Yu. Nevela & Victor A. Lapshin, 2022. "Model Risk and Basic Approaches to its Estimation on Example of Market Risk Models," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 127006, Russia, issue 2, pages 91-112, April.
• Andrey V. Polbin & Andrey V. Shumilov, 2022. "Forecasting Output Growth of Russian Manufacturing Industries Using Panel Data Models [Об Использовании Моделей Панельных Данных Для Прогнозирования Темпов Роста Отраслей Российской Обрабатывающей ," Russian Economic Development, Gaidar Institute for Economic Policy, issue 2, pages 15-19, February.
• Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman van Dijk, 2022. "A Flexible Predictive Density Combination Model for Large Financial Data Sets in Regular and Crisis Periods," Tinbergen Institute Discussion Papers 22-013/III, Tinbergen Institute.
• Aman Ullah & Tao Wang & Weixin Yao, 2022. "Nonlinear Modal Regression for Dependent Data with Application for Predicting COVID-19," Working Papers 202207, University of California at Riverside, Department of Economics.
• Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2021. "Optimal Forecast under Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202207, University of Kansas, Department of Economics, revised Feb 2022.
  • Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Optimal Forecast under Structural Breaks," Working Papers 202208, University of California at Riverside, Department of Economics.
• Todd H. Kuethe & Brady Brewer & Chad Fiechter, 2022. "Loss Aversion in Farmland Price Expectations," Land Economics, University of Wisconsin Press, vol. 98(1), pages 98-114.
• Srhoj Stjepan, 2022. "Can we predict high growth firms with financial ratios?," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 18(1), pages 66-73, March.
• Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2022. "A moving average heterogeneous autoregressive model for forecasting the realized volatility of the US stock market: Evidence from over a century of data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 384-400, January.
  • 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.
• Mehmet Balcilar & Edmond Berisha & Oğuzhan Çepni & Rangan Gupta, 2022. "The predictive power of the term spread on inequality in the United Kingdom: An empirical analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1979-1988, April.
  • 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.
• Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022. "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
  • S. Delle Chiaie & L. Ferrara & D. Giannone, 2017. "Common Factors of Commodity Prices," Working papers 645, Banque de France.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common Factors of Commodity Prices," CEPR Discussion Papers 12767, C.E.P.R. Discussion Papers.
  • Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2017. "Common factors of commodity prices," Working Paper Series 2112, European Central Bank.
• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2022. "An automated prior robustness analysis in Bayesian model comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 583-602, April.
  • Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "An automated prior robustness analysis in Bayesian model comparison," CAMA Working Papers 2019-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Michael P. Clements, 2022. "Individual forecaster perceptions of the persistence of shocks to GDP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 640-656, April.
  • Michael P. Clements, 2020. "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance icma-dp2020-02, Henley Business School, University of Reading.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Forecasting realized volatility of international REITs: The role of realized skewness and realized kurtosis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 303-315, March.
  • Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of International REITs: The Role of Realized Skewness and Realized Kurtosis," Working Papers 202114, University of Pretoria, Department of Economics.
• Barbara Jarmulska, 2022. "Random forest versus logit models: Which offers better early warning of fiscal stress?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 455-490, April.
  • Jarmulska, Barbara, 2020. "Random forest versus logit models: which offers better early warning of fiscal stress?," Working Paper Series 2408, European Central Bank.
• Lucija Benko & Karlo Krstanović & Luka Sovulj, 2022. "Procjena učinaka pandemije koronavirusa na turističke dolaske i noćenja u Republici Hrvatskoj te na vrijednost CROBEXturist indeksa Zagrebačke burze," EFZG Working Papers Series 2201, Faculty of Economics and Business, University of Zagreb.
• Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2022. "Addressing COVID-19 outliers in BVARs with stochastic volatility," Discussion Papers 13/2022, Deutsche Bundesbank.
• Hauber, Philipp, 2022. "Real-time nowcasting with sparse factor models," EconStor Preprints 251551, ZBW - Leibniz Information Centre for Economics.
• Duan, Fang, 2022. "Forecasting risk measures based on structural breaks in the correlation matrix," Ruhr Economic Papers 945, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

2021

• Garg, Karan, 2021. "Machines and Markets : Assessing the Impact of Algorithmic Trading on Financial Market Efficiency," Warwick-Monash Economics Student Papers 11, Warwick Monash Economics Student Papers.
• Aldott, Zoltan, 2021. "Predicting Specialty Coffee Auction Prices Using Machine Learning," Warwick-Monash Economics Student Papers 15, Warwick Monash Economics Student Papers.
• Gan-Ochir Doojav & Davaasukh Damdinjav, 2021. "Policy-Driven Boom and Bust in the Housing Market: Evidence from Mongolia," Surface Review and Letters (SRL), World Scientific Publishing Co. Pte. Ltd., vol. 38(02), pages 279-317.
  • 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., vol. 38(02), pages 279-317, September.
  • 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.
• 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., vol. 38(02), pages 279-317, September.
  • Gan-Ochir Doojav & Davaasukh Damdinjav, 2021. "Policy-Driven Boom and Bust in the Housing Market: Evidence from Mongolia," Surface Review and Letters (SRL), World Scientific Publishing Co. Pte. Ltd., vol. 38(02), pages 279-317.
  • 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.
• Laura Coroneo & Fabrizio Iacone, 2021. "Testing for equal predictive accuracy with strong dependence," Discussion Papers 21/03, Department of Economics, University of York.
• Laura Coroneo, & Fabrizio Iacone, & Giancarlo Manzi, & Silvia Salini, 2021. "Predicting the COVID-19 epidemic: is a regional approach preferable?," Discussion Papers 21/06, Department of Economics, University of York.
• Moench, Emanuel & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
  • Mönch, Emanuel & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," Discussion Papers 25/2021, Deutsche Bundesbank.
• Marta Bañbura & Danilo Leiva-León & Jan-Oliver Menz, 2021. "Do inflation expectations improve model-based inflation Forecasts?," Working Papers 2138, Banco de España.
  • Bańbura, Marta & Leiva-León, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Discussion Papers 48/2021, Deutsche Bundesbank.
  • Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
• 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.
• 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.
• Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš, 2022. "YOLO trading: Riding with the herd during the GameStop episode," Finance Research Letters, Elsevier, vol. 46(PA).
  • 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.
• Hauber, Philipp, 2021. "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints 251469, 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, December.
• Hügle, Dominik, 2021. "The decision to enrol in higher education," Discussion Papers 2021/8, Free University Berlin, School of Business & Economics.
• Cerqua, Augusto & Letta, Marco, 2022. "Local inequalities of the COVID-19 crisis," Regional Science and Urban Economics, Elsevier, vol. 92(C).
  • Cerqua, Augusto & Letta, Marco, 2021. "Local inequalities of the COVID-19 crisis," GLO Discussion Paper Series 875, Global Labor Organization (GLO).
• 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 Kiel).
• 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).
• Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Working Papers EPRG2110, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • 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 158, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
  • Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising temperatures, falling ratings: The effect of climate change on sovereign creditworthiness," CAMA Working Papers 2021-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Klusak, P. & Agarwala, M. & Burke, M. & Kraemer, M. & Mohaddes, K., 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Cambridge Working Papers in Economics 2127, Faculty of Economics, University of Cambridge.
• Wei Li & Florentina Paraschiv & Georgios Sermpinis, 2021. "A Data-driven Explainable Case-based Reasoning Approach for Financial Risk Detection," Papers 2107.08808, arXiv.org.
  • Li, Wei & Paraschiv, Florentina & Sermpinis, Georgios, 2021. "A data-driven explainable case-based reasoning approach for financial risk detection," IRTG 1792 Discussion Papers 2021-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Glas, Alexander & Heinisch, Katja, 2021. "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers 7/2021, Halle Institute for Economic Research (IWH).
• 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), vol. 9(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 921, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Kremer, Manfred & Chavleishvili, Sulkhan, 2021. "Measuring Systemic Financial Stress and its Impact on the Macroeconomy," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242346, Verein für Socialpolitik / German Economic Association.
• 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.
• Chaido Dritsaki & Dimitrios Niklis & Pavlos Stamatiou, 2021. "Oil Consumption Forecasting using ARIMA Models: An Empirical Study for Greece," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 214-224.
• Mohamed Defaf & Mohamed Tkiouat, 2021. "A Review on Prospective Energy Models: The Moroccan Case," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 14-23.
• Saring Suhendro & Mega Matalia & Sari Indah Oktanti Sembiring, 2021. "Public Sector Policy of Estimating Model for Renewable Energy," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 609-613.
• Bharat Kumar Meher & Iqbal Thonse Hawaldar & Mathew Thomas Gil & Deebom Zorle Dum, 2021. "Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 489-502.
• Thu, Le Ha & Leon-Gonzalez, Roberto, 2021. "Forecasting macroeconomic variables in emerging economies," Journal of Asian Economics, Elsevier, vol. 77(C).
• Gelfer, Sacha, 2021. "Evaluating the forecasting power of an open-economy DSGE model when estimated in a data-Rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
• 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.
• Gangopadhyay, Kausik & Mondal, Debasis, 2021. "Productivity, relative sectoral prices, and total factor productivity: Theory and evidence," Economic Modelling, Elsevier, vol. 100(C).
• Busetti, Fabio & Caivano, Michele & Delle Monache, Davide & Pacella, Claudia, 2021. "The time-varying risk of Italian GDP," Economic Modelling, Elsevier, vol. 101(C).
  • Fabio Busetti & Michele Caivano & Davide Delle Monache & Claudia Pacella, 2020. "The time-varying risk of Italian GDP," Temi di discussione (Economic working papers) 1288, Bank of Italy, Economic Research and International Relations Area.
• Belomestny, Denis & Krymova, Ekaterina & Polbin, Andrey, 2021. "Bayesian TVP-VARX models with time invariant long-run multipliers," Economic Modelling, Elsevier, vol. 101(C).
• Lehrer, Steven & Xie, Tian & Zhang, Xinyu, 2021. "Social media sentiment, model uncertainty, and volatility forecasting," Economic Modelling, Elsevier, vol. 102(C).
• Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
• Lucey, Brian & Ren, Boru, 2021. "Does news tone help forecast oil?," Economic Modelling, Elsevier, vol. 104(C).
• Cross, Jamie L. & Hou, Chenghan & Trinh, Kelly, 2021. "Returns, volatility and the cryptocurrency bubble of 2017–18," Economic Modelling, Elsevier, vol. 104(C).
• Casarin, Roberto & Costantini, Mauro & Paradiso, Antonio, 2021. "On the role of dependence in sticky price and sticky information Phillips curve: Modelling and forecasting," Economic Modelling, Elsevier, vol. 105(C).
• 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).
• Lin, Yu & Yan, Yan & Xu, Jiali & Liao, Ying & Ma, Feng, 2021. "Forecasting stock index price using the CEEMDAN-LSTM model," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
• Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021. "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
• Pérez-Rodríguez, Jorge V. & Andrada-Félix, Julián & Rachinger, Heiko, 2021. "Testing the forward volatility unbiasedness hypothesis in exchange rates under long-range dependence," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
• Christou, Christina & Gupta, Rangan & Jawadi, Fredj, 2021. "Does inequality help in forecasting equity premium in a panel of G7 countries?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
  • Christina Christou & Rangan Gupta & Fredj Jawadi, 2017. "Does Inequality Help in Forecasting Equity Premium in a Panel of G7 Countries?," Working Papers 201720, University of Pretoria, Department of Economics.
• Shu, Min & Song, Ruiqiang & Zhu, Wei, 2021. "The ‘COVID’ crash of the 2020 U.S. Stock market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
• Kim, Jong-Min & Kim, Dong H. & Jung, Hojin, 2021. "Applications of machine learning for corporate bond yield spread forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 58(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).
• Fang, Ming & Taylor, Stephen, 2021. "A machine learning based asset pricing factor model comparison on anomaly portfolios," Economics Letters, Elsevier, vol. 204(C).
• Ardia, David & Bluteau, Keven & Kassem, Alaa, 2021. "A century of Economic Policy Uncertainty through the French–Canadian lens," Economics Letters, Elsevier, vol. 205(C).
  • David Ardia & Keven Bluteau & Alaa Kassem, 2021. "A Century of Economic Policy Uncertainty Through the French-Canadian Lens," Papers 2106.05240, arXiv.org, revised Oct 2021.
• Du, Zaichao & Pei, Pei, 2021. "A simple and robust counterfactual impact evaluation," Economics Letters, Elsevier, vol. 207(C).
• Karmakar, Sayar & Demirer, Riza & Gupta, Rangan, 2021. "Bitcoin mining activity and volatility dynamics in the power market," Economics Letters, Elsevier, vol. 209(C).
  • Sayar Karmakar & Riza Demirer & Rangan Gupta, 2021. "Bitcoin Mining Activity and Volatility Dynamics in the Power Market," Working Papers 202166, University of Pretoria, Department of Economics.
• Hayashi, Fumio & Tachi, Yuta, 2021. "The nowcast revision analysis extended," Economics Letters, Elsevier, vol. 209(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.
• Sun, Yuying & Hong, Yongmiao & Lee, Tae-Hwy & Wang, Shouyang & Zhang, Xinyu, 2021. "Time-varying model averaging," Journal of Econometrics, Elsevier, vol. 222(2), pages 974-992.
  • Yongmiao Hong & Tae-Hwy Lee & Yuying Sun & Shouyang Wang & Xinyu Zhang, 2017. "Time-varying Model Averaging," Working Papers 202001, University of California at Riverside, Department of Economics.
• Liao, Jun & Zou, Guohua & Gao, Yan & Zhang, Xinyu, 2021. "Model averaging prediction for time series models with a diverging number of parameters," Journal of Econometrics, Elsevier, vol. 223(1), pages 190-221.
• Su, Jiun-Hua, 2021. "Model selection in utility-maximizing binary prediction," Journal of Econometrics, Elsevier, vol. 223(1), pages 96-124.
• Ahsan, Md. Nazmul & Dufour, Jean-Marie, 2021. "Simple estimators and inference for higher-order stochastic volatility models," Journal of Econometrics, Elsevier, vol. 224(1), pages 181-197.
• Andersen, Torben G. & Varneskov, Rasmus T., 2021. "Consistent inference for predictive regressions in persistent economic systems," Journal of Econometrics, Elsevier, vol. 224(1), pages 215-244.
  • Torben G. Andersen & Rasmus T. Varneskov, 2021. "Consistent Inference for Predictive Regressions in Persistent Economic Systems," NBER Working Papers 28568, National Bureau of Economic Research, Inc.
• Hecq, Alain & Voisin, Elisa, 2021. "Forecasting bubbles with mixed causal-noncausal autoregressive models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 29-45.
  • Voisin, Elisa & Hecq, Alain, 2019. "Forecasting bubbles with mixed causal-noncausal autoregressive models," MPRA Paper 92734, University Library of Munich, Germany.
• Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
• 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.
• Qiu, Yue & Wang, Zongrun & Xie, Tian & Zhang, Xinyu, 2021. "Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 179-201.
• Cheng, Mingmian & Swanson, Norman R. & Yang, Xiye, 2021. "Forecasting volatility using double shrinkage methods," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 46-61.
• Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
  • Alessandro Giovannelli & Daniele Massacci & Stefano Soccorsi, 2020. "Forecasting Stock Returns with Large Dimensional Factor Models," Working Papers 305661169, Lancaster University Management School, Economics Department.
• Han, Yang & Jiao, Anqi & Ma, Jun, 2021. "The predictive power of Nelson–Siegel factor loadings for the real economy," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 95-127.
• Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021. "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, vol. 100(C).
• Lyócsa, Štefan & Todorova, Neda, 2021. "What drives volatility of the U.S. oil and gas firms?," Energy Economics, Elsevier, vol. 100(C).
• Patra, Saswat, 2021. "Revisiting value-at-risk and expected shortfall in oil markets under structural breaks: The role of fat-tailed distributions," Energy Economics, Elsevier, vol. 101(C).
• Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
  • Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner P. Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Yihao Lin, 2021. "Machine Learning and Oil Price Point and Density Forecasting," Working Papers Series 544, Central Bank of Brazil, Research Department.
• Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
• Nonejad, Nima, 2021. "Predicting the return on the spot price of crude oil out-of-sample by conditioning on news-based uncertainty measures: Some new empirical results," Energy Economics, Elsevier, vol. 104(C).
• Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian, 2021. "Do oil-price shocks predict the realized variance of U.S. REITs?," Energy Economics, Elsevier, vol. 104(C).
  • Matteo Bonato & Rangan Gupta & Christian Pierdzioch, 2020. "Do Oil-Price Shocks Predict the Realized Variance of U.S. REITs?," Working Papers 2020100, University of Pretoria, Department of Economics.
• 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).
  • Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2019. "Modeling, Forecasting, and Nowcasting U.S. CO2 Emissions Using Many Macroeconomic Predictors," CREATES Research Papers 2019-21, Department of Economics and Business Economics, Aarhus University.
• He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
• Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
• Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2021. "Geopolitical risk and forecastability of tail risk in the oil market: Evidence from over a century of monthly data," Energy, Elsevier, vol. 235(C).
  • Afees A. Salisu & Christian Pierdzioch & Rangan Gupta, 2021. "Geopolitical Risk and Forecastability of Tail Risk in the Oil Market: Evidence from Over a Century of Monthly Data," Working Papers 202122, University of Pretoria, Department of Economics.
• Ma, Feng & Wang, Ruoxin & Lu, Xinjie & Wahab, M.I.M., 2021. "A comprehensive look at stock return predictability by oil prices using economic constraint approaches," International Review of Financial Analysis, Elsevier, vol. 78(C).
• Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2021. "VCRIX — A volatility index for crypto-currencies," International Review of Financial Analysis, Elsevier, vol. 78(C).
  • Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
  • Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," Working Papers 202133, University of Pretoria, Department of Economics.
  • Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," GRU Working Paper Series GRU_2021_017, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
• Sarlin, Peter & von Schweinitz, Gregor, 2021. "Optimizing Policymakers’ Loss Functions In Crisis Prediction: Before, Within Or After?," Macroeconomic Dynamics, Cambridge University Press, vol. 25(1), pages 100-123, January.
  • Sarlin, Peter & von Schweinitz, Gregor, 2015. "Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?," IWH Discussion Papers 6/2015, Halle Institute for Economic Research (IWH).
  • Sarlin, Peter & von Schweinitz, Gregor, 2017. "Optimizing policymakers' loss functions in crisis prediction: before, within or after?," Working Paper Series 2025, European Central Bank.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, Cambridge University Press, vol. 256, pages 71-109, April.
  • 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?," CIRANO Working Papers 2021s-09, CIRANO.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
• Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Cowles Foundation Discussion Papers 2312, Cowles Foundation for Research in Economics, Yale University.
• Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Cowles Foundation Discussion Papers 2312, Cowles Foundation for Research in Economics, Yale University, revised Mar 2022.
• Mr. Andrea Pescatori & Lukas Boer & Martin Stuermer, 2021. "Energy Transition Metals," IMF Working Papers 2021/243, International Monetary Fund.
  • Lukas Boer & Andrea Pescatori & Martin Stuermer, 2021. "Energy Transition Metals," Discussion Papers of DIW Berlin 1976, DIW Berlin, German Institute for Economic Research.
  • Boer, Lukas & Pescatori, Andrea & Stuermer, Martin, 2021. "Energy Transition Metals," MPRA Paper 110364, University Library of Munich, Germany.
• Bastien Lextrait, 2021. "Scaling up SME's credit scoring scope with LightGBM," EconomiX Working Papers 2021-25, University of Paris Nanterre, EconomiX.
• Hirschbühl, Dominik & Onorante, Luca & Saiz, Lorena, 2021. "Using machine learning and big data to analyse the business cycle," Economic Bulletin Articles, European Central Bank, vol. 5.
• Alogoskoufis, Spyros & Dunz, Nepomuk & Emambakhsh, Tina & Hennig, Tristan & Kaijser, Michiel & Kouratzoglou, Charalampos & Muñoz, Manuel A. & Parisi, Laura & Salleo, Carmelo, 2021. "ECB’s economy-wide climate stress test," Occasional Paper Series 281, European Central Bank.
• 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.
• Le Mezo, Helena & Ferrari, Massimo, 2021. "Text-based recession probabilities," Working Paper Series 2516, European Central Bank.
• Tatjana Dahlhaus & Julia Schaumburg & Tatevik Sekhposyan, 2021. "Networking the Yield Curve: Implications for Monetary Policy," Staff Working Papers 21-4, Bank of Canada.
  • Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
• Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
  • 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.
• Bobeica, Elena & Hartwig, Benny, 2021. "The COVID-19 shock and challenges for time series models," Working Paper Series 2558, European Central Bank.
• Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
• Consolo, Agostino & Foroni, Claudia & Hernández, Catalina Martínez, 2021. "A mixed frequency BVAR for the euro area labour market," Working Paper Series 2601, European Central Bank.
• Pablo Garcia & Pascal Jacquinot & Crt Lenarcic & Matija Lozej & Kostas Mavromatis, 2021. "Global models for a global pandemic: the impact of COVID-19 on small euro area economies," BCL working papers 156, Central Bank of Luxembourg.
  • Garcia, Pablo & Jacquinot, Pascal & Lenarčič, Črt & Lozej, Matija & Mavromatis, Kostas, 2021. "Global models for a global pandemic: the impact of COVID-19 on small euro area economies," Working Paper Series 2603, European Central Bank.
• Bańbura, Marta & Leiva-León, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Discussion Papers 48/2021, Deutsche Bundesbank.
  • Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
  • Marta Bañbura & Danilo Leiva-León & Jan-Oliver Menz, 2021. "Do inflation expectations improve model-based inflation Forecasts?," Working Papers 2138, Banco de España.
• Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kang, Miao & Kapadia, Sujit & Simsek, Özgür, 2020. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Bank of England working papers 848, Bank of England.
  • Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kapadia, Sujit & Şimşek, Özgür, 2021. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Working Paper Series 2614, European Central Bank.
• Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, 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.
• David E. Allen & Michael McAleer, 2021. "Predicting COVID-19 Cases and Deaths in the USA from Tests and State Populations," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(2), pages 1-27, June.
• Martin M. Andreasen & Giovanni Caggiano & Efrem Castelnuovo & Giovanni Pellegrino, 2021. "Why Does Risk Matter More in Recessions than in Expansions?," "Marco Fanno" Working Papers 0275, Dipartimento di Scienze Economiche "Marco Fanno".
  • Martin M. Andreasen & Giovanni Caggiano & Efrem Castelnuovo & Giovanni Pellegrino, 2021. "Why Does Risk Matter More in Recessions than in Expansions?," Economics Working Papers 2021-12, Department of Economics and Business Economics, Aarhus University.
  • Andreasen, Martin M. & Caggiano, Giovanni & Castelnuovo, Efrem & Pellegrino, Giovanni, 2021. "Why does risk matter more in recessions than in expansions?," Research Discussion Papers 13/2021, Bank of Finland.
  • Martin M. Andreasen & Giovanni Caggiano & Efrem Castelnuovo & Giovanni Pellegrino, 2021. "Why does risk matter more in recessions than in expansions?," CAMA Working Papers 2021-83, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Martin M. Andreasen & Giovanni Caggiano & Efrem Castelnuovo & Giovanni Pellegrino, 2021. "Why Does Risk Matter More in Recessions than in Expansions?," CESifo Working Paper Series 9328, CESifo.
  • Martin M. Andreasen & Giovanni Caggiano & Efrem Castelnuovo & Giovanni Pellegrino, 2021. "Why Does Risk Matter More in Recessions than in Expansions?," Monash Economics Working Papers 2021-11, Monash University, Department of Economics.
• 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.
• Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.
• Mikkel Bennedsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2021. "Inference and forecasting for continuous-time integer-valued trawl processes and their use in financial economics," CREATES Research Papers 2021-12, Department of Economics and Business Economics, Aarhus University.
• Ulrich Hounyo & Kajal Lahiri, 2021. "Estimating the Variance of a Combined Forecast: Bootstrap-Based Approach," CREATES Research Papers 2021-14, Department of Economics and Business Economics, Aarhus University.
• Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2021. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2021-03, Department of Economics, Auburn University.
• Ivan Korolev, 2021. "How Could Russia Have Developed without the Revolution of 1917?," Annals of Economics and Statistics, GENES, issue 144, pages 75-112.
• George-Marios Angeletos & Zhen Huo, 2021. "Myopia and Anchoring," American Economic Review, American Economic Association, vol. 111(4), pages 1166-1200, April.
  • George-Marios Angeletos & Zhen Huo, 2018. "Myopia and Anchoring," NBER Working Papers 24545, National Bureau of Economic Research, Inc.
• Alexandre N. Kohlhas & Ansgar Walther, 2021. "Asymmetric Attention," American Economic Review, American Economic Association, vol. 111(9), pages 2879-2925, September.
• Barbara Rossi, 2021. "Forecasting in the Presence of Instabilities: How We Know Whether Models Predict Well and How to Improve Them," Journal of Economic Literature, American Economic Association, vol. 59(4), pages 1135-1190, December.
• Vesna Karadzic & Bojan Pejovic, 2021. "Inflation Forecasting in the Western Balkans and EU: A Comparison of Holt-Winters, ARIMA and NNAR Models," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(57), pages 517-517.
• Nigel E.N. Chitambo & Darren Lee & Sure Mataramvura, 2021. "A Hybrid Neural Network GARCH Approach to Forecasting Zimbabwean Inflation Volatility," The African Finance Journal, Africagrowth Institute, vol. 23(1), pages 56-73.
• Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
• 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, vol. 14(11), pages 1-17, June.
  • 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.
• Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafal Weron, 2021. "Erratum to 'Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark' [Appl. Energy 293 (2021) 116983]," WORking papers in Management Science (WORMS) WORMS/21/12, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• David E. Allen & Michael McAleer, 2021. "Predicting COVID-19 Cases and Deaths in the USA from Tests and State Populations," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(2), pages 1-27, June.
  • David E. Allen & Michael McAleer, 2021. "Predicting COVID-19 Cases and Deaths in the USA from Tests and State Populations," International Association of Decision Sciences, Asia University, Taiwan, vol. 25(2), pages 1-27, June.
• 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.
  • Aloy, Marcel & Laly, Floris & Laurent, Sébastien & Lecourt, Christelle, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," LIDAM Reprints LFIN 2021021, Université catholique de Louvain, Louvain Finance (LFIN).
• Nurdaulet Abilov & Aizhan Bolatbayeva, 2021. "Nowcasting GDP growth in Russia with an incomplete dataset: A factor model approach," NAC Analytica Working Paper 18, NAC Analytica, Nazarbayev University, revised Feb 2022.
• Asta Ndongo & Ibrahima Thione Diop, 2021. "Economic and Monetary Integration in ECOWAS Countries: A Panel VAR Approach to Identify Macroeconomic Shocks," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 7(2), pages 61-87, December.
• Игсатов О.Р. // Igsatov О.R., 2021. "Анализ эффективности процентного канала в Казахстане // Analyzing effectiveness of the interest rate channel in Kazakhstan," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue 1, pages 4-14.
• 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 & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, Cambridge University Press, vol. 256, pages 71-109, April.
  • 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.
• David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin & Bonsoo Koo, 2021. "Loss-Based Variational Bayes Prediction," Monash Econometrics and Business Statistics Working Papers 8/21, Monash University, Department of Econometrics and Business Statistics.
  • David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin & Bonsoo Koo, 2021. "Loss-Based Variational Bayes Prediction," Papers 2104.14054, arXiv.org, revised May 2022.
• Ardia, David & Bluteau, Keven & Kassem, Alaa, 2021. "A century of Economic Policy Uncertainty through the French–Canadian lens," Economics Letters, Elsevier, vol. 205(C).
  • David Ardia & Keven Bluteau & Alaa Kassem, 2021. "A Century of Economic Policy Uncertainty Through the French-Canadian Lens," Papers 2106.05240, arXiv.org, revised Oct 2021.
• Fiaschi, Davide & Tealdi, Cristina, 2021. "Young People between Education and the Labour Market during the COVID-19 Pandemic in Italy," IZA Discussion Papers 14479, Institute of Labor Economics (IZA).
  • Davide Fiaschi & Cristina Tealdi, 2021. "Young people between education and the labour market during the COVID-19 pandemic in Italy," Papers 2106.08296, arXiv.org.
• Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
  • Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Papers 2107.02512, arXiv.org.
• Li, Wei & Paraschiv, Florentina & Sermpinis, Georgios, 2021. "A data-driven explainable case-based reasoning approach for financial risk detection," IRTG 1792 Discussion Papers 2021-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  • Wei Li & Florentina Paraschiv & Georgios Sermpinis, 2021. "A Data-driven Explainable Case-based Reasoning Approach for Financial Risk Detection," Papers 2107.08808, arXiv.org.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2021. "Forecasting with a Panel Tobit Model," Papers 2110.14117, arXiv.org.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," NBER Working Papers 26569, National Bureau of Economic Research, Inc.
• Sabyasachi Kar & Amaani Bashir & Mayank Jain, 2021. "New Approaches to Forecasting Growth and Inflation: Big Data and Machine Learning," IEG Working Papers 446, Institute of Economic Growth.
• Massimo Guidolin & Davide La Cara & Massimiliano Marcellino, 2021. "Boosting the Forecasting Power of Conditional Heteroskedasticity Models to Account for Covid-19 Outbreaks," BAFFI CAREFIN Working Papers 21169, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• 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.
• Francois-Michel Boire & Thibaut Duprey & Alexander Ueberfeldt, 2021. "Shaping the future: Policy shocks and the GDP growth distribution," Staff Working Papers 21-24, Bank of Canada.
• Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
  • Tatjana Dahlhaus & Julia Schaumburg & Tatevik Sekhposyan, 2021. "Networking the Yield Curve: Implications for Monetary Policy," Staff Working Papers 21-4, Bank of Canada.
• Ugochi Emenogu & Cars Hommes & Mikael Khan, 2021. "Detecting exuberance in house prices across Canadian cities," Staff Analytical Notes 2021-9, Bank of Canada.
• Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
  • Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner P. Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Yihao Lin, 2021. "Machine Learning and Oil Price Point and Density Forecasting," Working Papers Series 544, Central Bank of Brazil, Research Department.
• Garcia, Pablo & Jacquinot, Pascal & Lenarčič, Črt & Lozej, Matija & Mavromatis, Kostas, 2021. "Global models for a global pandemic: the impact of COVID-19 on small euro area economies," Working Paper Series 2603, European Central Bank.
  • Pablo Garcia & Pascal Jacquinot & Crt Lenarcic & Matija Lozej & Kostas Mavromatis, 2021. "Global models for a global pandemic: the impact of COVID-19 on small euro area economies," BCL working papers 156, Central Bank of Luxembourg.
• Emilio Blanco & Laura D’Amato & Fiorella Dogliolo & Lorena Garegnani, 2021. "Nowcast of Macroeconomic Aggregates in Argentina: Comparing the Predictive Capacity of Different Models," BCRA Working Paper Series 202190, Central Bank of Argentina, Economic Research Department.
• Pablo Aguilar, 2021. "La recuperación del consumo en 2021: un análisis a partir de las expectativas de los consumidores," Boletín Económico, Banco de España, issue 3/2021, pages 1-10.
• Pablo Aguilar, 2021. "Consumption recovery in 2021: an analysis drawing on consumer expectations," Economic Bulletin, Banco de España, issue 3/2021, pages 1-9.
• 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.
• 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.
• Erik Andres-Escayola & Juan Carlos Berganza & Rodolfo Campos & Luis Molina, 2021. "A BVAR toolkit to assess macrofinancial risks in Brazil and Mexico," Occasional Papers 2114, Banco de España.
• Bańbura, Marta & Leiva-León, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Discussion Papers 48/2021, Deutsche Bundesbank.
  • Marta Bañbura & Danilo Leiva-León & Jan-Oliver Menz, 2021. "Do inflation expectations improve model-based inflation Forecasts?," Working Papers 2138, Banco de España.
  • Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
• 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.
• Maria Ludovica Drudi & Stefano Nobili, 2021. "A liquidity risk early warning indicator for Italian banks: a machine learning approach," Temi di discussione (Economic working papers) 1337, Bank of Italy, Economic Research and International Relations Area.
• Raúl Ibarra-Ramírez, 2021. "The Yield Curve as a Predictor of Economic Activity in Mexico: The Role of the Term Premium," Working Papers 2021-07, Banco de México.
• Enrique Bátiz-Zuk Enrique & Abdulkadir Mohamed & Fátima Sánchez-Cajal, 2021. "Exploring the sources of loan default clustering using survival analysis with frailty," Working Papers 2021-14, Banco de México.
• Rangel González Erick & Irving Llamosas-Rosas, 2021. "Observing the Evolution of the Informal Sector from Space: A Municipal Approach 2013-2020," Working Papers 2021-18, Banco de México.
• 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.
• Franky Juliano Galeano-Ramírez & Nicolás Martínez-Cortés & Carlos D. Rojas-Martínez, 2021. "Nowcasting Colombian Economic Activity: DFM and Factor-MIDAS approaches," Borradores de Economia 1168, Banco de la Republica de Colombia.
• Juan C. Méndez-Vizcaíno & Alexander Guarin & César Anzola-Bravo & Anderson Grajales-Olarte, 2021. "Characterizing and Communicating the Balance of Risks of Macroeconomic Forecasts: A Predictive Density Approach for Colombia," Borradores de Economia 1178, Banco de la Republica de Colombia.
• Marcela De Castro-Valderrama & Santiago Forero-Alvarado & Nicolás Moreno-Arias & Sara Naranjo-Saldarriaga, 2021. "Unraveling the Exogenous Forces Behind Analysts’ Macroeconomic Forecasts," Borradores de Economia 1184, Banco de la Republica de Colombia.
• Ana María Iregui-Bohórquez & César Anzola-Bravo & Luisa Fernanda Ballén-Rubio & Valeria Bejarano-Salcedo & Eliana González-Molano & Anderson Grajales-Olarte & Alexander Guarín-López & María Alejandra , 2021. "¿Qué nos dicen las encuestas sobre la formación de expectativas de inflación?," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República - ESPE, issue 100, pages 1-95, September.
  • Ana María Iregui-Bohórquez & César Anzola-Bravo & Luisa Fernanda Ballén-Rubio & Valeria Bejarano-Salcedo & Eliana González-Molano & Anderson Grajales-Olarte & Alexander Guarín-López & María Alejandra , 2021. "¿Qué nos dicen las encuestas sobre la formación de expectativas de inflación?," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, issue 100, pages 1-95, September.
• Andrejs Bessonovs & Olegs Krasnopjorovs, 2021. "Short-term inflation projections model and its assessment in Latvia," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 21(2), pages 184-204.
  • Andrejs Bessonovs & Olegs Krasnopjorovs, 2020. "Short-Term Inflation Projections Model and Its Assessment in Latvia," Working Papers 2020/01, Latvijas Banka.
• Ksenia Mayorova & Nikita Fokin, 2021. "Nowcasting Growth Rates of Russia’s Export and Import by Commodity Group," Russian Journal of Money and Finance, Bank of Russia, vol. 80(3), pages 34-48, September.
• Roman Tikhonov & Aleksey Masyutin & Vadim Anpilogov, 2021. "The Relationship Between the Financial Performance of Banks and the Quality of Credit Scoring Models," Russian Journal of Money and Finance, Bank of Russia, vol. 80(2), pages 76-95, June.
• Elizaveta Golovanova & Andrey Zubarev, 2021. "Forecasting Aggregate Retail Sales with Google Trends," Russian Journal of Money and Finance, Bank of Russia, vol. 80(4), pages 50-73, December.
• 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.
• Tommaso Proietti & Alessandro Giovannelli, 2021. "Nowcasting monthly GDP with big data: A model averaging approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 683-706, April.
  • 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.
• Valentina Aprigliano & Danilo Liberati, 2021. "Using Credit Variables to Date Business Cycle and to Estimate the Probabilities of Recession in Real Time," Manchester School, University of Manchester, vol. 89(S1), pages 76-96, September.
  • Valentina Aprigliano & Danilo Liberati, 2019. "Using credit variables to date business cycle and to estimate the probabilities of recession in real time," Temi di discussione (Economic working papers) 1229, Bank of Italy, Economic Research and International Relations Area.
• Anibal Emiliano Da Silva Neto & Jesús Gonzalo & Jean‐Yves Pitarakis, 2021. "Uncovering Regimes in Out of Sample Forecast Errors from Predictive Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 713-741, June.
  • Da Silva Neto, Anibal Emiliano & Gonzalo, Jesús & Pitarakis, Jean-Yves, 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.
• Fabio Busetti & Michele Caivano & Davide Delle Monache, 2021. "Domestic and Global Determinants of Inflation: Evidence from Expectile Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 982-1001, August.
  • Fabio Busetti & Michele Caivano & Davide Delle Monache, 2019. "Domestic and global determinants of inflation: evidence from expectile regression," Temi di discussione (Economic working papers) 1225, Bank of Italy, Economic Research and International Relations Area.
• 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.
• Eleonora Granziera & Pirkka Jalasjoki & Maritta Paloviita, 2021. "The Bias and Efficiency of the ECB Inflation Projections: a State Dependent Analysis," Working Paper 2021/1, Norges Bank.
• 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 21-053/III, Tinbergen Institute.
  • Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
  • Knut Are Aastveit & Jamie Cross & Herman K. Djik, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Papers No 03/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
  • Knut Are Aastveit & Jamie Cross & Herman K. Djik, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Papers No 03/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • 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 21-053/III, Tinbergen Institute.
• Joseph, Andreas & Kalamara, Eleni & Kapetanios, George & Potjagailo, Galina, 2021. "Forecasting UK inflation bottom up," Bank of England working papers 915, Bank of England.
• Anesti, Nikoleta & Kalamara, Eleni & Kapetanios, George, 2021. "Forecasting UK GDP growth with large survey panels," Bank of England working papers 923, 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.
• Manuel M. F. Martins & Fabio Verona, 2021. "Inflation Dynamics and Forecast: Frequency Matters," CEF.UP Working Papers 2101, Universidade do Porto, Faculdade de Economia do Porto.
  • Martins, Manuel M. F. & Verona, Fabio, 2021. "Inflation dynamics and forecast : frequency matters," Research Discussion Papers 8/2021, Bank of Finland.
• Oren Barkan & Jonathan Benchimol & Itamar Caspi & Eliya Cohen & Allon Hammer & Noam Koenigstein, 2020. "Forecasting CPI Inflation Components with Hierarchical Recurrent Neural Networks," Papers 2011.07920, arXiv.org, revised Feb 2022.
  • Oren Barkan & Jonathan Benchimol & Itamar Caspi & Allon Hammer & Noam Koenigstein, 2021. "Forecasting CPI Inflation Components with Hierarchical Recurrent Neural Network," Bank of Israel Working Papers 2021.06, Bank of Israel.
• 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.
• Takuji Kawamoto & Jouchi Nakajima & Tomoaki Mikami, 2021. "Supplementary Paper Series for the "Assessment" (3): Inflation-Overshooting Commitment:An Analysis Using a Macroeconomic Model," Bank of Japan Working Paper Series 21-E-9, Bank of Japan.
• Jouchi Nakajima & Hiroaki Yamagata & Tatsushi Okuda & Shinnosuke Katsuki & Takeshi Shinohara, 2021. "Extracting Firms' Short-Term Inflation Expectations from the Economy Watchers Survey Using Text Analysis," Bank of Japan Working Paper Series 21-E-12, Bank of Japan.
• Becker William & Paruolo Paolo & Saltelli Andrea, 2021. "Variable Selection in Regression Models Using Global Sensitivity Analysis," Journal of Time Series Econometrics, De Gruyter, vol. 13(2), pages 187-233, July.
• Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
  • Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Lahiri Kajal & Yang Liu, 2021. "Construction of leading economic index for recession prediction using vine copulas," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(4), pages 193-212, September.
• Maurin Baillif & Matthieu de Lapparent & Evanthia Kazagli, 2021. "A Hybrid Approach to Real Estate Price Definition: A Case Study in Western Switzerland," Revue économique, Presses de Sciences-Po, vol. 72(6), pages 1055-1077.
• 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.
• Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Working Papers EPRG2110, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • Klusak, P. & Agarwala, M. & Burke, M. & Kraemer, M. & Mohaddes, K., 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Cambridge Working Papers in Economics 2127, Faculty of Economics, University of Cambridge.
  • 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 158, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
  • Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising temperatures, falling ratings: The effect of climate change on sovereign creditworthiness," CAMA Working Papers 2021-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Ding, Y., 2021. "Conditional Heteroskedasticity in the Volatility of Asset Returns," Cambridge Working Papers in Economics 2179, Faculty of Economics, University of Cambridge.
• Ding, Y., 2021. "Conditional Heteroskedasticity in the Volatility of Asset Returns," Janeway Institute Working Papers 2111, 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.
• Nenad Milojević & Srdjan Redzepagic, 2021. "Prospects of Artificial Intelligence and Machine Learning Application in Banking Risk Management," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(3), pages 41-57.
• Congressional Budget Office, 2021. "CBO’s Economic Forecasting Record: 2021 Update," Reports 57579, Congressional Budget Office.
• 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).
• Dario Sansone & Anna Zhu, 2020. "Using Machine Learning to Create an Early Warning System for Welfare Recipients," Papers 2011.12057, arXiv.org, revised May 2021.
  • Sansone, Dario & Zhu, Anna, 2021. "Using Machine Learning to Create an Early Warning System for Welfare Recipients," IZA Discussion Papers 14377, Institute of Labor Economics (IZA).
• Davide Fiaschi & Cristina Tealdi, 2021. "Young people between education and the labour market during the COVID-19 pandemic in Italy," Papers 2106.08296, arXiv.org.
  • Fiaschi, Davide & Tealdi, Cristina, 2021. "Young People between Education and the Labour Market during the COVID-19 Pandemic in Italy," IZA Discussion Papers 14479, Institute of Labor Economics (IZA).
• Rabia Özdemir & Münevver Turanlı, 2021. "Comparison of machine learning classification algorithms for purchasing forecast," JOURNAL OF LIFE ECONOMICS, Holistence Publications, 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.
  • 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.
• Barnett, William & Park, Sohee, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," MPRA Paper 110298, University Library of Munich, Germany.
  • William Barnett & Sohee Park, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202120, University of Kansas, Department of Economics, revised Oct 2021.
• Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2021. "Optimal Forecast under Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202207, University of Kansas, Department of Economics, revised Feb 2022.
  • Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Optimal Forecast under Structural Breaks," Working Papers 202208, University of California at Riverside, Department of Economics.
• Kartikay Gupta & Niladri Chatterjee, 2021. "Stocks Recommendation from Large Datasets Using Important Company and Economic Indicators," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 667-689, December.
• 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.
• Athanasios Tsadiras & Maria Pempetzoglou & Iosif Viktoratos, 2021. "Making Predictions of Global Warming Impacts Using a Semantic Web Tool that Simulates Fuzzy Cognitive Maps," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 715-745, October.
• 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.
• Eduard Baitinger & Samuel Flegel, 2021. "The better turbulence index? Forecasting adverse financial markets regimes with persistent homology," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 277-308, September.
• 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.
• Niall Newsham & Francisco Rowe, 2021. "Projecting the demographic impact of Syrian migration in a rapidly ageing society, Germany," Journal of Geographical Systems, Springer, vol. 23(2), pages 231-261, April.
• 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.
• Qingjing Zhang & Taufiq Choudhry & Jing-Ming Kuo & Xiaoquan Liu, 2021. "Does liquidity drive stock market returns? The role of investor risk aversion," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 929-958, October.
• Cem Cakmakli & Verda Ozturk, 2021. "Economic Value of Modeling the Joint Distribution of Returns and Volatility: Leverage Timing," Koç University-TUSIAD Economic Research Forum Working Papers 2110, Koc University-TUSIAD Economic Research Forum.
• Alexander Correa, 2021. "Forecasting Tourist Arrivals to Colombia from Google Trends Search Criteria," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 95, pages 105-134, July-Dece.
• Jamal Bouoiyour, Refk Selmi, 2021. "The financial costs of terrorism: evidence from Germany," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 18(1), pages 87-104, June.
• Muhammad Ejaz & Javed Iqbal, 2021. "Estimation and Forecasting of Industrial Production Index," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 26(1), pages 1-30, Jan-June.
  • Muhammad Ejaz & Javed Iqbal, 2019. "Estimation and Forecasting of Industrial Production Index," SBP Working Paper Series 103, State Bank of Pakistan, Research Department.
• 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.
• Andreï Kostyrka & Dmitry Igorevich Malakhov,, 2021. "The good, the bad, and the asymmetric: Evidence from a new conditional density model," DEM Discussion Paper Series 21-09, Department of Economics at the University of Luxembourg.
• Gani Ramadani & Magdalena Petrovska & Vesna Bucevska, 2021. "Evaluation of mixed frequency approaches for tracking near-term economic developments in North Macedonia," Working Papers 2021-03, National Bank of the Republic of North Macedonia.
• Martin Baumgaertner & Johannes Zahner, 2021. "Whatever it takes to understand a central banker - Embedding their words using neural networks," MAGKS Papers on Economics 202130, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Erik Heilmann & Janosch Henze & Heike Wetzel, 2021. "Machine learning in energy forecasts with an application to high frequency electricity consumption data," MAGKS Papers on Economics 202135, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Weshah Razzak, 2021. "The Ownership of Oil, Democracy, and Iraq's Past, Present and Future," Discussion Papers 2102, School of Economics and Finance, Massey University, New Zealand.
  • Razzak, Weshah, 2022. "The Ownership of Oil, Democracy, and Iraq’s Past, Present, and Future," MPRA Paper 111417, University Library of Munich, Germany.
• 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.
• 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.
• Simon Liebermann & Jung-Sup Um & YoungSeok Hwang & Stephan Schlüter, 2021. "Performance Evaluation of Neural Network-Based Short-Term Solar Irradiation Forecasts," Energies, MDPI, vol. 14(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, vol. 14(11), pages 1-17, June.
  • 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.
• Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2021. "Modeling Electricity Price and Quantity Uncertainty: An Application for Hedging with Forward Contracts," Energies, MDPI, vol. 14(11), pages 1-26, June.
  • 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.
• Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers," Energies, MDPI, vol. 14(14), pages 1-15, July.
  • Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers," Working Papers 202135, University of Pretoria, Department of Economics.
• 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, vol. 14(20), pages 1-12, October.
  • 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," Working Papers 202158, University of Pretoria, Department of Economics.
• 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, vol. 14(23), pages 1-18, December.
  • Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and the Realized Volatility Oil and Gas Prices: Results of an Out-of-Sample Forecasting Experiment," Working Papers 202175, University of Pretoria, Department of Economics.
• 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, vol. 3(4), pages 1-30, October.
  • Fantazzini, Dean & Pushchelenko, Julia & Mironenkov, Alexey & Kurbatskii, Alexey, 2021. "Forecasting internal migration in Russia using Google Trends: Evidence from Moscow and Saint Petersburg," MPRA Paper 110452, University Library of Munich, Germany.
• Dean Fantazzini & Raffaella Calabrese, 2021. "Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure," JRFM, MDPI, vol. 14(11), pages 1-23, October.
  • Fantazzini, Dean & Calabrese, Raffaella, 2021. "Crypto-exchanges and Credit Risk: Modelling and Forecasting the Probability of Closure," MPRA Paper 110391, University Library of Munich, Germany.
• Nadiia Shapovalenko, 2021. "A BVAR Model for Forecasting Ukrainian Inflation," IHEID Working Papers 05-2021, Economics Section, The Graduate Institute of International Studies.
• Anastasiya Ivanova & Alona Shmygel & Ihor Lubchuk, 2021. "The Growth-at-Risk (GaR) Framework: Implication For Ukraine," IHEID Working Papers 10-2021, 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.
• Hans Manner & Gabriel Rodriguez & Florian Stöckler, 2021. "A changepoint analysis of exchange rate and commodity price risks for Latin American stock markets," Graz Economics Papers 2021-14, 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.
• Eiji Goto & Jan P.A.M. Jacobs & Tara M. Sinclair & Simon van Norden, 2021. "Employment Reconciliation and Nowcasting," Working Papers 2021-007, 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.
  • Aloy, Marcel & Laly, Floris & Laurent, Sébastien & Lecourt, Christelle, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," LIDAM Reprints LFIN 2021021, Université catholique de Louvain, Louvain Finance (LFIN).
  • 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.
• Antoine Auberger, 2021. "Vote, popularity, economic conditions and French legislative elections [Vote, popularité, conditions économiques et élections législatives françaises]," Working Papers hal-03480853, HAL.
• 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) dp-688, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
• Fink Simonsen, Nicolai & Kjær, Trine, 2021. "New Evidence of Health State Dependent Utility of Consumption: A combined survey and register study," DaCHE discussion papers 2021:2, University of Southern Denmark, Dache - Danish Centre for Health Economics.
• 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.
• 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, vol. 0(2), pages 83-92, June.
• Collischon, Matthias, 2021. "Identifying supervisory or managerial status in administrative records," IAB-Discussion Paper 202120, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
• Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
  • Luigi Longo & Massimo Riccaboni & Armando Rungi, 2021. "A Neural Network Ensemble Approach for GDP Forecasting," Working Papers 02/2021, IMT School for Advanced Studies Lucca, revised Mar 2021.
• Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Papers 2107.02512, arXiv.org.
  • Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 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.
• Fortin, Ines & Hlouskova, Jaroslava & Soegner, Leopold, 2021. "Financial instability and economic activity," IHS Working Paper Series 36, Institute for Advanced Studies.
• Eda Gülşen & Hakan Kara, 2021. "Policy Performance and the Behavior of Inflation Expectations," International Journal of Central Banking, International Journal of Central Banking, vol. 17(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, vol. 17(71), pages 1-41, December.
  • Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2015. "Real-Time Forecasting and Scenario Analysis using a Large Mixed-Frequency Bayesian VAR," Working Papers 2015-030, Federal Reserve Bank of St. Louis, revised 10 Apr 2020.
• Jaumotte, Florence & Liu, Weifeng & McKibbin, Warwick, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," CEPR Discussion Papers 16553, C.E.P.R. Discussion Papers.
  • Weifeng Liu & Warwick J. McKibbin & Ms. Florence Jaumotte, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," IMF Working Papers 2021/195, International Monetary Fund.
  • Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021. "Mitigating climate change: Growth-friendly policies to achieve net zero emissions by 2050," CAMA Working Papers 2021-75, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Lukas Boer & Andrea Pescatori & Martin Stuermer, 2021. "Energy Transition Metals," Discussion Papers of DIW Berlin 1976, DIW Berlin, German Institute for Economic Research.
  • Mr. Andrea Pescatori & Lukas Boer & Martin Stuermer, 2021. "Energy Transition Metals," IMF Working Papers 2021/243, International Monetary Fund.
  • Boer, Lukas & Pescatori, Andrea & Stuermer, Martin, 2021. "Energy Transition Metals," MPRA Paper 110364, University Library of Munich, Germany.
• 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.
• 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, vol. 16(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, vol. 16(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, vol. 16(TNEA), pages 1-18, Septiembr.
• Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2020. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Working Paper series 20-27, Rimini Centre for Economic Analysis.
  • 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 21-016/III, Tinbergen Institute.
• Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
  • 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 21-053/III, Tinbergen Institute.
  • Knut Are Aastveit & Jamie Cross & Herman K. Djik, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Papers No 03/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Yongchen Zhao, 2021. "Uncertainty and Disagreement of Inflation Expectations: Evidence from Household-Level Qualitative Survey Responses," Working Papers 2021-03, Towson University, Department of Economics, revised Dec 2021.
• K. Peren Arin & Kevin Devereux & Mieszko Mazur, 2021. "Taxes and firm investment," CAMA Working Papers 2021-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • K. Peren Arin & Kevin Devereux & Mieszko Mazur, 2021. "Taxes and Firm Investment," Working Papers 202102, School of Economics, University College Dublin.
• 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.
  • 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.
• Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating forecast performance with state dependence," Economics Working Papers 1800, Department of Economics and Business, Universitat Pompeu Fabra.
• Monica Billio & Roberto Casarin & Enrica De Cian & Malcolm Mistry & Anthony Osuntuyi, 2020. "The impact of Climate on Economic and Financial Cycles: A Markov-switching Panel Approach," Papers 2012.14693, arXiv.org.
  • 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 2021:03, Department of Economics, University of Venice "Ca' Foscari".
• Jitender, 2021. "Value-at-Risk Estimation of Equity Market Risk in India," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 9(1), pages 1-24, September.
• Kaczmarczyk Paweł, 2021. "Econometric Modelling of Compound Cyclicality of using Telecommunication Services," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 25(2), pages 27-45, June.
• 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, Sciendo, vol. 25(3), pages 21-41, September.
• 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, Sciendo, vol. 18(1), pages 70-81, June.
• Wang Guan-Yuan, 2021. "The Brand Effect: A Case Study in Taiwan Second-Hand Smartfhone Market," Journal of Social and Economic Statistics, Sciendo, vol. 10(1-2), pages 30-42, December.
• 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, Sciendo, vol. 29(2), pages 52-70, June.
• 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, Sciendo, vol. 16(2), pages 43-52, December.
• Dawid Siwicki, 2021. "The Application of Machine Learning Algorithms for Spatial Analysis: Predicting of Real Estate Prices in Warsaw," Working Papers 2021-05, Faculty of Economic Sciences, University of Warsaw.
• Mateusz Buczyński & Marcin Chlebus, 2021. "GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks," Working Papers 2021-08, Faculty of Economic Sciences, University of Warsaw.
• Michał Woźniak & Marcin Chlebus, 2021. "HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation," Working Papers 2021-10, Faculty of Economic Sciences, University of Warsaw.
• Szymon Lis & Marcin Chlebus, 2021. "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers 2021-11, Faculty of Economic Sciences, University of Warsaw.
• Piotr Borowski & Marcin Chlebus, 2021. "Machine learning in the prediction of flat horse racing results in Poland," Working Papers 2021-13, Faculty of Economic Sciences, University of Warsaw.
• Stefan Jestl & Robert Stehrer, 2021. "EU Employment Dynamics: The Pandemic Years and Beyond," wiiw Research Reports 457, The Vienna Institute for International Economic Studies, wiiw.
• 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 316, WU Vienna University of Economics and Business.
  • Vadim Kufenko & Klaus Prettner, 2021. "Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators," Department of Economics Working Papers wuwp316, Vienna University of Economics and Business, Department of Economics.
• Vadim Kufenko & Klaus Prettner, 2021. "Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators," Department of Economics Working Papers wuwp316, Vienna University of Economics and Business, Department of Economics.
  • 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 316, WU Vienna University of Economics and Business.
• Reinhard Ellwanger, Stephen Snudden, 2021. "Predictability of Aggregated Time Series," LCERPA Working Papers bm0127, Laurier Centre for Economic Research and Policy Analysis.
• 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., vol. 26(1), pages 153-170, January.
  • 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.
• 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., vol. 36(5), pages 495-516, August.
  • Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," Working Papers 20-27, Federal Reserve Bank of Cleveland.
• Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
  • Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2019. "Focused Bayesian Prediction," Papers 1912.12571, arXiv.org, revised Aug 2020.
  • Ruben Loaiza-Maya & Gael M Martin & David T. Frazier, 2020. "Focused Bayesian Prediction," Monash Econometrics and Business Statistics Working Papers 1/20, Monash University, Department of Econometrics and Business Statistics.
• Till Weigt & Bernd Wilfling, 2021. "An approach to increasing forecast‐combination accuracy through VAR error modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 686-699, July.
  • Till Weigt & Bernd Wilfling, 2018. "An approach to increasing forecast-combination accuracy through VAR error modeling," CQE Working Papers 6818, Center for Quantitative Economics (CQE), University of Muenster.
• 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, vol. 53(5), pages 1005-1046, August.
  • Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
  • Benjamin K Johannsen & Elmar Mertens, 2018. "A time series model of interest rates with the effective lower bound," BIS Working Papers 715, Bank for International Settlements.
• John B. Donaldson & Rajnish Mehra, 2021. "Average crossing time: An alternative characterization of mean aversion and reversion," Quantitative Economics, Econometric Society, vol. 12(3), pages 903-944, July.
  • 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.
• 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).
• Nonejad, Nima, 2021. "Predicting equity premium by conditioning on macroeconomic variables: A prediction selection strategy using the price of crude oil," Finance Research Letters, Elsevier, vol. 41(C).
• Ly, Kim Tien, 2021. "A COVID-19 forecasting system using adaptive neuro-fuzzy inference," Finance Research Letters, Elsevier, vol. 41(C).
• Chatziantoniou, Ioannis & Degiannakis, Stavros & Delis, Panagiotis & Filis, George, 2021. "Forecasting oil price volatility using spillover effects from uncertainty indices," Finance Research Letters, Elsevier, vol. 42(C).
• Bouri, Elie & Gupta, Rangan & Majumdar, Anandamayee & Subramaniam, Sowmya, 2021. "Time-varying risk aversion and forecastability of the US term structure of interest rates," Finance Research Letters, Elsevier, vol. 42(C).
  • Elie Bouri & Rangan Gupta & Anandamayee Majumdar & Sowmya Subramaniam, 2020. "Time-Varying Risk Aversion and Forecastability of the US Term Structure of Interest Rates," Working Papers 202098, University of Pretoria, Department of Economics.
• Bouri, Elie & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021. "Forecasting power of infectious diseases-related uncertainty for gold realized variance," Finance Research Letters, Elsevier, vol. 42(C).
• Guidolin, Massimo & Pedio, Manuela, 2021. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," Finance Research Letters, Elsevier, vol. 42(C).
  • Massimo Guidolin & Manuela Pedio, 2020. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," BAFFI CAREFIN Working Papers 20145, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Umar, Zaghum & Riaz, Yasir & Zaremba, Adam, 2021. "Patterns of Spillover in Energy, Agricultural, and Metal Markets: A Connectedness Analysis for Years 1780-2020," Finance Research Letters, Elsevier, vol. 43(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.
• Avanzi, Benjamin & Taylor, Greg & Wang, Melantha & Wong, Bernard, 2021. "SynthETIC: An individual insurance claim simulator with feature control," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 296-308.
• Maciak, Matúš & Okhrin, Ostap & Pešta, Michal, 2021. "Infinitely stochastic micro reserving," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 30-58.
• Taylor, Greg, 2021. "A special Tweedie sub-family with application to loss reserving prediction error," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 262-288.
• 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.
• Bravo, Jorge M. & Ayuso, Mercedes & Holzmann, Robert & Palmer, Edward, 2021. "Addressing the life expectancy gap in pension policy," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 200-221.
• Avanzi, Benjamin & Taylor, Greg & Wong, Bernard & Yang, Xinda, 2021. "On the modelling of multivariate counts with Cox processes and dependent shot noise intensities," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 9-24.
• 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.
• Bessler, Wolfgang & Taushanov, Georgi & Wolff, Dominik, 2021. "Optimal asset allocation strategies for international equity portfolios: A comparison of country versus industry optimization," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
• Sermpinis, Georgios & Hassanniakalager, Arman & Stasinakis, Charalampos & Psaradellis, Ioannis, 2021. "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
• Breen, John David & Hu, Liang, 2021. "The predictive content of oil price and volatility: New evidence on exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
• 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.
• Cipollini, Fabrizio & Gallo, Giampiero M. & Otranto, Edoardo, 2021. "Realized volatility forecasting: Robustness to measurement errors," International Journal of Forecasting, Elsevier, vol. 37(1), pages 44-57.
  • Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
• Costantini, Mauro & Kunst, Robert M., 2021. "On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation," International Journal of Forecasting, Elsevier, vol. 37(2), pages 445-460.
  • Costantini, Mauro & Kunst, Robert M., 2018. "On Using Predictive-ability Tests in the Selection of Time-series Prediction Models: A Monte Carlo Evaluation," Economics Series 341, Institute for Advanced Studies.
• Clements, Michael P., 2021. "Do survey joiners and leavers differ from regular participants? The US SPF GDP growth and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 37(2), pages 634-646.
  • Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, University of Reading.
• Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
  • Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR forecasts, survey information and structural change in the euro area," Working Papers 1948, Banco de España.
  • Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area," Working papers 733, Banque de France.
• Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
  • Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
• Brave, Scott A. & Gascon, Charles & Kluender, William & Walstrum, Thomas, 2021. "Predicting benchmarked US state employment data in real time," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1261-1275.
  • 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.
  • Scott Brave & Charles S. 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.
• Blasques, Francisco & Hoogerkamp, Meindert Heres & Koopman, Siem Jan & van de Werve, Ilka, 2021. "Dynamic factor models with clustered loadings: Forecasting education flows using unemployment data," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1426-1441.
  • 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.
• Chikamatsu, Kyosuke & Hirakata, Naohisa & Kido, Yosuke & Otaka, Kazuki, 2021. "Mixed-frequency approaches to nowcasting GDP: An application to Japan," Japan and the World Economy, Elsevier, vol. 57(C).
• Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
• Sopitpongstorn, Nithi & Silvapulle, Param & Gao, Jiti & Fenech, Jean-Pierre, 2021. "Local logit regression for loan recovery rate," Journal of Banking & Finance, Elsevier, vol. 126(C).
• Clements, Adam & Preve, Daniel P.A., 2021. "A Practical Guide to harnessing the HAR volatility model," Journal of Banking & Finance, Elsevier, vol. 133(C).
  • A Clements & D Preve, 2019. "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series 120, National Centre for Econometric Research.
• Jang, Tae-Seok & Sacht, Stephen, 2021. "Forecast heuristics, consumer expectations, and New-Keynesian macroeconomics: A Horse race," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 493-511.
  • Jang, Tae-Seok & Sacht, Stephen, 2018. "Forecast heuristics, consumer expectations, and new-Keynesian macroeconomics: A horse race," Economics Working Papers 2018-09, Christian-Albrechts-University of Kiel, Department of Economics.
• Antulov-Fantulin, Nino & Lagravinese, Raffaele & Resce, Giuliano, 2021. "Predicting bankruptcy of local government: A machine learning approach," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 681-699.
• Noussair, Charles N. & Popescu, Andreea Victoria, 2021. "Comovement and return predictability in asset markets: An experiment with two Lucas trees," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 671-687.
• Iregui, Ana María & Núñez, Héctor M. & Otero, Jesús, 2021. "Testing the efficiency of inflation and exchange rate forecast revisions in a changing economic environment," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 290-314.
• Huisman, Ronald & Van der Sar, Nico L. & Zwinkels, Remco C.J., 2021. "Volatility expectations and disagreement," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 379-393.
• Makarewicz, Tomasz, 2021. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 626-673.
• Al Mabsali, Yousuf Khamis & Hayward, Robert & Eliwa, Yasser, 2021. "Managerial tools used to meet or beat analyst forecasts: Evidence from the UK," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 43(C).
• 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).
  • John G. Fernald & Eric Hsu & Mark M. Spiegel, 2019. "Is China Fudging Its GDP Figures? Evidence from Trading Partner Data," Working Paper Series 2019-19, Federal Reserve Bank of San Francisco.
• Fernald, John G. & Hsu, Eric & Spiegel, Mark M., 2021. "Reprint: Is China fudging its GDP figures? Evidence from trading partner data," Journal of International Money and Finance, Elsevier, vol. 114(C).
• Biolsi, Christopher, 2021. "Labor productivity forecasts based on a Beveridge–Nelson filter: Is there statistical evidence for a slowdown?," Journal of Macroeconomics, Elsevier, vol. 69(C).
• Pozo, Veronica F. & Bachmeier, Lance J. & Schroeder, Ted C., 2021. "Are there price asymmetries in the U.S. beef market?," Journal of Commodity Markets, Elsevier, vol. 21(C).
• Nonejad, Nima, 2021. "The price of crude oil and (conditional) out-of-sample predictability of world industrial production," Journal of Commodity Markets, Elsevier, vol. 23(C).
• Wolters, Jannik & Huchzermeier, Arnd, 2021. "Joint In-Season and Out-of-Season Promotion Demand Forecasting in a Retail Environment," Journal of Retailing, Elsevier, vol. 97(4), pages 726-745.
• Mishra, Shekhar & Mishra, Sibanjan, 2021. "Are Indian sectoral indices oil shock prone? An empirical evaluation," Resources Policy, Elsevier, vol. 70(C).
• Pincheira, Pablo & Hardy, Nicolás, 2021. "Forecasting aluminum prices with commodity currencies," Resources Policy, Elsevier, vol. 73(C).
  • Pincheira, Pablo & Hardy, Nicolás, 2019. "Forecasting Aluminum Prices with Commodity Currencies," MPRA Paper 97005, University Library of Munich, Germany.
• Dai, Zhifeng & Kang, Jie & Hu, Yangli, 2021. "Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index," Resources Policy, Elsevier, vol. 74(C).
• Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2021. "Common factors and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 74(C).
• 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.
• Larsen, Vegard H. & Thorsrud, Leif Anders & Zhulanova, Julia, 2021. "News-driven inflation expectations and information rigidities," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 507-520.
  • Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Paper 2019/5, Norges Bank.
  • Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Papers No 03/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Antolín-Díaz, Juan & Petrella, Ivan & Rubio-Ramírez, Juan F., 2021. "Structural scenario analysis with SVARs," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 798-815.
  • Antolin-Diaz, Juan & Petrella, Ivan & Rubio-Ramírez, Juan Francisco, 2018. "Structural Scenario Analysis with SVARs," CEPR Discussion Papers 12579, C.E.P.R. Discussion Papers.
  • Antolin-Diaz, Juan & Petrella, Ivan & Rubio-Ramirez, Juan F., 2020. "Structural Scenario Analysis with SVARs," EMF Research Papers 32, Economic Modelling and Forecasting Group.
• Brownlees, Christian & Souza, André B.M., 2021. "Backtesting global Growth-at-Risk," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 312-330.
• Tang, Wenjin & Ding, Saijie & Chen, Hao, 2021. "Economic uncertainty and its spillover networks: Evidence from the Asia-Pacific countries," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
• Umar, Zaghum & Yousaf, Imran & Aharon, David Y., 2021. "The relationship between yield curve components and equity sectorial indices: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
• Pamp, Oliver & Lebacher, Michael & Thurner, Paul W. & Ziegler, Eva, 2021. "Explaining destinations and volumes of international arms transfers: A novel network Heckman selection model," European Journal of Political Economy, Elsevier, vol. 69(C).
• Jiang, Minqi & Liu, Jiapeng & Zhang, Lu, 2021. "An extended regularized Kalman filter based on Genetic Algorithm: Application to dynamic asset pricing models," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 28-44.
• Fassas, Athanasios P. & Siriopoulos, Costas, 2021. "Implied volatility indices – A review," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 303-329.
• Borgards, Oliver & Czudaj, Robert L., 2021. "Features of overreactions in the cryptocurrency market," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 31-48.
• Chaikumbung, Mayula, 2021. "Institutions and consumer preferences for renewable energy: A meta-regression analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
• Andreana, Gianmarco & Gualini, Andrea & Martini, Gianmaria & Porta, Flavio & Scotti, Davide, 2021. "The disruptive impact of COVID-19 on air transportation: An ITS econometric analysis," Research in Transportation Economics, Elsevier, vol. 90(C).
• Plíhal, Tomáš & Lyócsa, Štefan, 2021. "Modeling realized volatility of the EUR/USD exchange rate: Does implied volatility really matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 811-829.
• Chen, Shun & Ge, Lei, 2021. "A learning-based strategy for portfolio selection," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 936-942.
• Zhou, Xuemei & Liu, Qiang & Guo, Shuxin, 2021. "Do overnight returns explain firm-specific investor sentiment in China?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 451-477.
• Bloise, Francesco & Tancioni, Massimiliano, 2021. "Predicting the spread of COVID-19 in Italy using machine learning: Do socio-economic factors matter?," Structural Change and Economic Dynamics, Elsevier, vol. 56(C), pages 310-329.
• Balcilar, Mehmet & Berisha, Edmond & Gupta, Rangan & Pierdzioch, Christian, 2021. "Time-varying evidence of predictability of financial stress in the United States over a century: The role of inequality," Structural Change and Economic Dynamics, Elsevier, vol. 57(C), pages 87-92.
  • Mehmet Balcilar & Edmond Berisha & Rangan Gupta & Christian Pierdzioch, 2020. "Time-Varying Evidence of Predictability of Financial Stress in the United States over a Century: The Role of Inequality," Working Papers 202054, University of Pretoria, Department of Economics.
• Akaev, Askar & Devezas, Tessaleno & Ichkitidze, Yuri & Sarygulov, Askar, 2021. "Forecasting the labor intensity and labor income share for G7 countries in the digital age," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
• Chen, Ji & Huang, Jiayan & Su, Weihua & Štreimikienė, Dalia & Baležentis, Tomas, 2021. "The challenges of COVID-19 control policies for sustainable development of business: Evidence from service industries," Technology in Society, Elsevier, vol. 66(C).
• Gutiérrez-Romero, Roxana & Ahamed, Mostak, 2021. "COVID-19 response needs to broaden financial inclusion to curb the rise in poverty," World Development, Elsevier, vol. 138(C).
• K. Peren Arin & Kevin Devereux & Mieszko Mazur, 2021. "Taxes and Firm Investment," Working Papers 202102, School of Economics, University College Dublin.
  • K. Peren Arin & Kevin Devereux & Mieszko Mazur, 2021. "Taxes and firm investment," CAMA Working Papers 2021-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Hilde Christiane Bjørnland & Roberto Casarin & Marco Lorusso & Francesco Ravazzolo, 2020. "Oil and Fiscal Policy Regimes," Working Papers No 11/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjørnland & Roberto Casarin & Marco Lorusso & Francesco Ravazzolo, 2021. "Oil and fiscal policy regimes," CAMA Working Papers 2021-10, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Working Papers EPRG2110, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising temperatures, falling ratings: The effect of climate change on sovereign creditworthiness," CAMA Working Papers 2021-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • 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 158, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
  • Klusak, P. & Agarwala, M. & Burke, M. & Kraemer, M. & Mohaddes, K., 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Cambridge Working Papers in Economics 2127, Faculty of Economics, University of Cambridge.
• Fernando, Roshen & Liu, Weifeng & McKibbin, Warwick, 2021. "Global Economic Impacts of Climate Shocks, Climate Policy and Changes in Climate Risk Assessment," CEPR Discussion Papers 16154, C.E.P.R. Discussion Papers.
  • Roshen Fernando & Weifeng Liu & Warwick J McKibbin, 2021. "Global economic impacts of climate shocks, climate policy and changes in climate risk assessment," CAMA Working Papers 2021-37, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Mototsugu Shintani & Kozo Ueda, 2021. "Identifying the Source of Information Rigidities in the Expectations Formation Process," CARF F-Series CARF-F-516, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  • Mototsugu Shintani & Kozo Ueda, 2021. "Identifying the source of information rigidities in the expectations formation process," CAMA Working Papers 2021-48, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• 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.
  • Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2021. "Testing the predictive accuracy of COVID-19 forecasts," CAMA Working Papers 2021-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Hanol Lee & Jong-Wha Lee, 2021. "Why East Asian students perform better in mathematics than their peers: An investigation using a machine learning approach," CAMA Working Papers 2021-66, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Jaumotte, Florence & Liu, Weifeng & McKibbin, Warwick, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," CEPR Discussion Papers 16553, C.E.P.R. Discussion Papers.
  • Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021. "Mitigating climate change: Growth-friendly policies to achieve net zero emissions by 2050," CAMA Working Papers 2021-75, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Weifeng Liu & Warwick J. McKibbin & Ms. Florence Jaumotte, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," IMF Working Papers 2021/195, International Monetary Fund.
• Tino Berger & Paul David Boll & James Morley & Benjamin Wong, 2021. "Cyclical signals from the labor market," CAMA Working Papers 2021-91, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Stephen Walker, 2021. "Critique of an Article on Machine Learning in the Detection of Accounting Fraud," Econ Journal Watch, Econ Journal Watch, vol. 18(1), pages 1-61–70, March.
• Yang Bao & Bin Ke & Bin Li & Y. Julia Yu & Jie Zhang, 2021. "A Response to "Critique of an Article on Machine Learning in the Detection of Accounting Fraud"," Econ Journal Watch, Econ Journal Watch, vol. 18(1), pages 1-71–78, March.
• Stephen Walker, 2021. "Rejoinder to the Critique of an Article on Machine Learning in the Detection of Accounting Fraud," Econ Journal Watch, Econ Journal Watch, vol. 18(2), pages 230–234-2, September.
• Daniel Goller & Michael C. Knaus & Michael Lechner & Gabriel Okasa, 2021. "Predicting match outcomes in football by an Ordered Forest estimator," Chapters, in: Ruud H. Koning & Stefan Kesenne (ed.), A Modern Guide to Sports Economics, chapter 22, pages 335-355, Edward Elgar Publishing.
  • Goller, Daniel & Knaus, Michael C. & Lechner, Michael & Okasa, Gabriel, 2018. "Predicting Match Outcomes in Football by an Ordered Forest Estimator," Economics Working Paper Series 1811, University of St. Gallen, School of Economics and Political Science.
• Jean-David Fermanian & Dominique Guégan, 2021. "Fair learning with bagging," Documents de travail du Centre d'Economie de la Sorbonne 21034, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• George Athanasopoulos & Nikolaos Kourentzes, 2021. "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers 10/21, Monash University, Department of Econometrics and Business Statistics.
• Bodha Hannadige, Sium & Gao, Jiti & Silvapulle, Mervyn & Silvapulle, Param, 2021. "Time Series Forecasting using a Mixture of Stationary and Nonstationary Predictors," MPRA Paper 108669, University Library of Munich, Germany, revised 30 Apr 2021.
  • Sium Bodha Hannadige & Jiti Gao & Mervyn J Silvapulle & Param Silvapulle, 2021. "Time Series Forecasting Using a Mixture of Stationary and Nonstationary Predictors," Monash Econometrics and Business Statistics Working Papers 6/21, Monash University, Department of Econometrics and Business Statistics.
• David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin & Bonsoo Koo, 2021. "Loss-Based Variational Bayes Prediction," Papers 2104.14054, arXiv.org, revised May 2022.
  • David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin & Bonsoo Koo, 2021. "Loss-Based Variational Bayes Prediction," Monash Econometrics and Business Statistics Working Papers 8/21, Monash University, Department of Econometrics and Business Statistics.
• 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.
• Anirban Basu & Noah Hammarlund & Sara Khor & Aasthaa Bansal, 2021. "Understanding Algorithmic Discrimination in Health Economics Through the Lens of Measurement Errors," NBER Working Papers 29413, National Bureau of Economic Research, Inc.
• Ali Hortaçsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," NBER Working Papers 29508, National Bureau of Economic Research, Inc.
• 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, 2021. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," NBER Working Papers 29535, National Bureau of Economic Research, Inc.
  • Schorfheide, Frank & Song, Dongo, 2021. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," CEPR Discussion Papers 16760, C.E.P.R. Discussion Papers.
  • 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.
• Rudrani Bhattacharya & Bornali Bhandari & Sudipto Mundle, 2021. "Nowcasting India's Quarterly GDP Growth: A Factor Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)," NCAER Working Papers 130, National Council of Applied Economic Research.
• Novikova, T. & Tsyplakov, A., 2021. "Social policy development based on a combination of agent-oriented and inter-industrial approaches," Journal of the New Economic Association, New Economic Association, vol. 52(4), pages 12-36.
• Ali Hortaçsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Working Papers 21-09, NET Institute.
• Bhattacharya, Rudrani & Bhandari, Bornali & Mundle, Sudipto, 2021. "Nowcasting India's Quarterly GDP Growth: A Factor Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)," Working Papers 21/357, National Institute of Public Finance and Policy.
• 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.
• Victor Yotzov, 2021. "Commodity Market Structure and Risk Factor Analysis in Bulgaria," Godishnik na UNSS, University of National and World Economy, Sofia, Bulgaria, issue 2, pages 1-53–73, December.
• Iva Raycheva, 2021. "Child Poverty among European Countries and Bulgaria’s Place among Them. Statistical Analysis of Convergence," Ikonomiceski i Sotsialni Alternativi, University of National and World Economy, Sofia, Bulgaria, issue 3, pages 37-51, September.
• Kensuke Tanaka, 2021. "Forecasting developing Asian economies during normal times and large external shocks: Approaches and challenges," OECD Development Centre Working Papers 345, OECD Publishing.
• 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.
• Lidia Vesa & Marcel Ioan Boloş & Claudia Diana Sabău-Popa, 2021. "Inventory Decision In Vuca World Using Economic Logic Quantity," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 251-267, July.
• Ionuţ Gavriş & Valentin Toader, 2021. "The Probability Of Uncertainty: Romania’S Growth Perspectives," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 71-81, July.
• Rachel R. Cheti & Bahati Ilembo, 2021. "Vector Autoregressive Approach After First Differencing: A Time Series Analysis Of Inflation And Its Determinants In Tanzania," Oradea Journal of Business and Economics, University of Oradea, Faculty of Economics, vol. 6(2), pages 43-56, September.
• Michael Cai & Marco Del & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2021. "Online estimation of DSGE models," Econometrics Journal, Royal Economic Society, vol. 24(1), pages 33-58.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," PIER Working Paper Archive 19-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Michael D. Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," NBER Working Papers 26826, National Bureau of Economic Research, Inc.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Staff Reports 893, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Liberty Street Economics 20190821, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," Finance and Economics Discussion Series 2020-023, Board of Governors of the Federal Reserve System (U.S.).
• Fred Liu & Lars Stentoft, 2021. "Regulatory Capital and Incentives for Risk Model Choice under Basel 3 [Procyclical Leverage and Value-at-Risk]," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(1), pages 53-96.
• Apaar Sadhwani & Kay Giesecke & Justin Sirignano, 2021. "Deep Learning for Mortgage Risk [The Subprime Virus]," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(2), pages 313-368.
• Giuseppe Buccheri & Fulvio Corsi, 2021. "HARK the SHARK: Realized Volatility Modeling with Measurement Errors and Nonlinear Dependencies," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(4), pages 614-649.
• Daniele Bianchi & Matthias Büchner & Andrea Tamoni, 2021. "Bond Risk Premiums with Machine Learning [Quadratic term structure models: Theory and evidence]," Review of Financial Studies, Society for Financial Studies, vol. 34(2), pages 1046-1089.
• Romero Martínez, Mariano & Carmona Ibáñez, Pedro & Pozuelo Campillo, José, 2021. "Utilidad del Deep Learning en la predicción del fracaso empresarial en el ámbito europeo || The usefulness of Deep Learning in the prediction of business failure at the European level," 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. 32(1), pages 392-414, December.
• Wolfgang Bessler & Georgi Taushanov & Dominik Wolff, 2021. "Factor investing and asset allocation strategies: a comparison of factor versus sector optimization," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 488-506, October.
• János Varga & Jan in ’t Veld, 2021. "The Impact of the EU Cohesion Policy Spending: A Model-Based Assessment," Studies in Economic Transition, in: Michael Landesmann & István P. Székely (ed.), Does EU Membership Facilitate Convergence? The Experience of the EU's Eastern Enlargement - Volume II, chapter 0, pages 89-112, Palgrave Macmillan.
• Alessandro Bitetto & Paola Cerchiello & Stefano Filomeni & Alessandra Tanda & Barbara Tarantino, 2021. "Machine Learning and Credit Risk: Empirical Evidence from SMEs," DEM Working Papers Series 201, University of Pavia, Department of Economics and Management.
• Alessandro Bitetto & Stefano Filomeni & Michele Modina, 2021. "Understanding corporate default using Random Forest: The role of accounting and market information," DEM Working Papers Series 205, University of Pavia, Department of Economics and Management.
• Mario Papik & Lenka Papikova, 2021. "Application of selected data mining techniques in unintentional accounting error detection," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 16(1), pages 185-201, March.
• Martins, Manuel M. F. & Verona, Fabio, 2021. "Inflation dynamics and forecast : frequency matters," Research Discussion Papers 8/2021, Bank of Finland.
  • Manuel M. F. Martins & Fabio Verona, 2021. "Inflation Dynamics and Forecast: Frequency Matters," CEF.UP Working Papers 2101, Universidade do Porto, Faculdade de Economia do Porto.
• Valerio Mendoza, Octasiano Miguel & Borsi, Mihály Tamás & Comim, Flavio, 2022. "Human capital dynamics in China: Evidence from a club convergence approach," Journal of Asian Economics, Elsevier, vol. 79(C).
  • Valerio Mendoza, Octasiano & Borsi, Mihály Tamás & Comim, Flavio, 2021. "Human capital dynamics in China: Evidence from a club convergence approach," MPRA Paper 105200, University Library of Munich, Germany.
• Pincheira, Pablo & Hardy, Nicolas, 2021. "The Mean Squared Prediction Error Paradox," MPRA Paper 107403, University Library of Munich, Germany.
• VINTU, Denis, 2021. "GDP Modelling and Forecasting Using ARIMA. An Empirical Assessment for Innovative Economy Formation," MPRA Paper 107603, University Library of Munich, Germany, revised 11 Feb 2021.
• Pincheira, Pablo & Hardy, Nicolas & Bentancor, Andrea & Henriquez, Cristóbal & Tapia, Ignacio, 2021. "Forecasting Base Metal Prices with an International Stock Index," MPRA Paper 107828, University Library of Munich, Germany.
• Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
  • Ofori, Isaac K, 2021. "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper 108622, University Library of Munich, Germany.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers 21/044, Research Africa Network (RAN).
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers of the African Governance and Development Institute. 21/044, African Governance and Development Institute..
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers 21/044, European Xtramile Centre of African Studies (EXCAS).
• Youssef, Jamile & Ishker, Nermeen & Fakhreddine, Nour, 2021. "GDP Forecast of the Biggest GCC Economies Using ARIMA," MPRA Paper 108912, University Library of Munich, Germany.
• Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Using Deep Learning Neural Networks to Predict the Knowledge Economy Index for Developing and Emerging Economies," MPRA Paper 109137, University Library of Munich, Germany.
• Antonio Rodríguez Andrés & Voxi Heinrich S. Amavilah & Abraham Otero, 2021. "Evaluation of technology clubs by clustering: a cautionary note," Applied Economics, Taylor & Francis Journals, vol. 53(52), pages 5989-6001, November.
  • Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Evaluation of technology clubs by clustering: A cautionary note," MPRA Paper 109138, University Library of Munich, Germany.
• Kindop, Igor, 2021. "Ubiquitous multimodality in mixed causal-noncausal processes," MPRA Paper 109594, University Library of Munich, Germany, revised 04 Sep 2021.
• Kadanga, Mayo Takémsi Norris & Togbenu, Fo-Kossi Edem, 2021. "Modélisation et prévision du nombre d’infections au coronavirus au Togo: une approche par un modèle ARIMA avec le logiciel R [Modeling and forecasting the number of coronavirus infections in Togo: ," MPRA Paper 109893, University Library of Munich, Germany.
• Ahamuefula E. Ogbonna & Olusanya E. Olubusoye, 2021. "Tail Risks and Stock Return Predictability - Evidence From Asia-Pacific," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(3), pages 1-6.
  • Ogbonna, Ahamuefula & Olubusoye, Olusanya E, 2021. "Tail Risks and Stock Return Predictability: Evidence From Asia-Pacific," MPRA Paper 109922, University Library of Munich, Germany.
• Adekunle, Wasiu & Bekoe, William & Badmus, Sheriff & Anagun, Michael & Alimi, Wasiu, 2021. "Nexus Between Fiscal Discipline And The Budget Process In Africa: Evidence From Nigeria," MPRA Paper 110061, University Library of Munich, Germany.
• William Barnett & Sohee Park, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202120, University of Kansas, Department of Economics, revised Oct 2021.
  • Barnett, William & Park, Sohee, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," MPRA Paper 110298, University Library of Munich, Germany.
• Mr. Andrea Pescatori & Lukas Boer & Martin Stuermer, 2021. "Energy Transition Metals," IMF Working Papers 2021/243, International Monetary Fund.
  • Boer, Lukas & Pescatori, Andrea & Stuermer, Martin, 2021. "Energy Transition Metals," MPRA Paper 110364, University Library of Munich, Germany.
  • Lukas Boer & Andrea Pescatori & Martin Stuermer, 2021. "Energy Transition Metals," Discussion Papers of DIW Berlin 1976, DIW Berlin, German Institute for Economic Research.
• Dean Fantazzini & Raffaella Calabrese, 2021. "Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure," JRFM, MDPI, vol. 14(11), pages 1-23, October.
  • Fantazzini, Dean & Calabrese, Raffaella, 2021. "Crypto-exchanges and Credit Risk: Modelling and Forecasting the Probability of Closure," MPRA Paper 110391, University Library of Munich, Germany.
• 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, vol. 3(4), pages 1-30, October.
  • Fantazzini, Dean & Pushchelenko, Julia & Mironenkov, Alexey & Kurbatskii, Alexey, 2021. "Forecasting internal migration in Russia using Google Trends: Evidence from Moscow and Saint Petersburg," MPRA Paper 110452, University Library of Munich, Germany.
• Bhadury, Soumya & Ghosh, Saurabh & Gopalakrishnan, Pawan, 2021. "In quest for policy 'silver bullets' towards triggering a v-shaped recovery," MPRA Paper 110905, University Library of Munich, Germany.
• Degiannakis, Stavros, 2021. "Stock market as a nowcasting indicator for real investment," MPRA Paper 110914, University Library of Munich, Germany.
• Mestiri, Sami, 2021. "Modelling the volatility of Bitcoin returns using Nonparametric GARCH models," MPRA Paper 111116, University Library of Munich, Germany.
• Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
  • Korobilis, Dimitris & Shimizu, Kenichi, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," MPRA Paper 111631, University Library of Munich, Germany.
  • Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Paper series 22-02, Rimini Centre for Economic Analysis.
  • Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Papers 2112.11751, arXiv.org.
• G.K., Chetan Kumar & K.B., Rangappa & S., Suchitra, 2021. "Analyzing Interlinkages between Financial and Real Estate Sector in the aftermath of COVID-19's Second wave: An Econometric Approach using VECM model," MPRA Paper 112440, University Library of Munich, Germany.
• Filip Stanek, 2021. "Optimal Out-of-Sample Forecast Evaluation under Stationarity," CERGE-EI Working Papers wp712, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
• 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.
• Simon Blöthner & Mario Larch, 2021. "Economic Determinants of Regional Trade Agreements Revisited Using Machine Learning," CESifo Working Paper Series 9233, CESifo.
• Lahiri, Kajal & Yang, Cheng, 2022. "Boosting tax revenues with mixed-frequency data in the aftermath of COVID-19: The case of New York," International Journal of Forecasting, Elsevier, vol. 38(2), pages 545-566.
  • Kajal Lahiri & Cheng Yang, 2021. "Boosting Tax Revenues with Mixed-Frequency Data in the Aftermath of Covid-19: The Case of New York," CESifo Working Paper Series 9365, CESifo.
• Jorge Miguel Bravo & Mercedes Ayuso & Robert Holzmann & Edward Palmer, 2021. "Intergenerational Actuarial Fairness when Longevity Increases: Amending the Retirement Age," CESifo Working Paper Series 9408, CESifo.
• Kajal Lahiri & Junyan Zhang & Yongchen Zhao, 2021. "Inefficiency in Social Security Trust Funds Forecasts," CESifo Working Paper Series 9415, CESifo.
• Mototsugu Shintani & Kozo Ueda, 2021. "Identifying the source of information rigidities in the expectations formation process," CAMA Working Papers 2021-48, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Mototsugu Shintani & Kozo Ueda, 2021. "Identifying the Source of Information Rigidities in the Expectations Formation Process," CARF F-Series CARF-F-516, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
• Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2021. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Swiss Finance Institute Research Paper Series 21-09, Swiss Finance Institute.
• Matteo Garzoli & Alberto Plazzi & Rossen I. Valkanov, 2021. "Backcasting, Nowcasting, and Forecasting Residential Repeat-Sales Returns: Big Data meets Mixed Frequency," Swiss Finance Institute Research Paper Series 21-21, Swiss Finance Institute.
• David Solo & Didier Sornette & Florian Ulmann, 2021. "Dynamical Internal Cost of Capital Driven by Cash Flow Growth," Swiss Finance Institute Research Paper Series 21-24, Swiss Finance Institute.
• Alexander Wehrli & Didier Sornette, 2021. "Excess financial volatility explained by endogenous excitations revealed by EM calibrations of a generalized Hawkes point process," Swiss Finance Institute Research Paper Series 21-35, Swiss Finance Institute.
• Eric Jondeau & Alexandre Pauli, 2021. "Disasters, Large Drawdowns, and Long-term Asset Management," Swiss Finance Institute Research Paper Series 21-37, Swiss Finance Institute.
• Pawel Polak & Urban Ulrych, 2021. "Dynamic Currency Hedging with Ambiguity," Swiss Finance Institute Research Paper Series 21-60, Swiss Finance Institute.
• Dongshuai Zhao, CFA & Didier Sornette, 2021. "Bubbles for Fama from Sornette," Swiss Finance Institute Research Paper Series 21-94, Swiss Finance Institute.
• Damir Filipović & Amir Khalilzadeh, 2021. "Machine Learning for Predicting Stock Return Volatility," Swiss Finance Institute Research Paper Series 21-95, Swiss Finance Institute.
• Hugo Couture & Dalibor Stevanovic, 2021. "Analyse du marché du travail à l’aide des données de Google Trends," CIRANO Project Reports 2021rp-15, CIRANO.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, Cambridge University Press, vol. 256, pages 71-109, April.
  • 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?," CIRANO Working Papers 2021s-09, CIRANO.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
• Miroslav Plasil, 2021. "Designing Macro-Financial Scenarios: The New CNB Framework and Satellite Models for Property Prices and Credit," Research and Policy Notes 2021/01, Czech National Bank.
• Michal Franta & Jan Libich, 2021. "Holding the Economy by the Tail: Analysis of Short- and Long-run Macroeconomic Risks," Working Papers 2021/3, Czech National Bank.
• Ricardo Crisóstomo, 2021. "Estimación de probabilidades representativas del mundo real: importancia de los sesgos conductuales," CNMV Documentos de Trabajo CNMV Documentos de Trabaj, CNMV- Comisión Nacional del Mercado de Valores - Departamento de Estudios y Estadísticas.
• Javier Ojea-Ferreiro, 2021. "Deconstrucción del riesgo sistémico: Un método de prueba de resistencia inversa," CNMV Documentos de Trabajo CNMV Documentos de Trabaj, CNMV- Comisión Nacional del Mercado de Valores - Departamento de Estudios y Estadísticas.
• Ricardo Cris'ostomo, 2020. "Estimating real-world probabilities: A forward-looking behavioral framework," Papers 2012.09041, arXiv.org, revised Jan 2021.
  • Ricardo Crisóstomo, 2021. "Estimating real word probabilities: a forward-looking behavioral framework," CNMV Working Papers CNMV Working Papers no. 7, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
• Javier Ojea-Ferreiro, 2021. "Deconstructing systemic risk: A reverse stress testing approach," CNMV Working Papers CNMV Working Papers no. 7, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
• Castro-Iragorri, C & Ramírez, J, 2021. "Forecasting Dynamic Term Structure Models with Autoencoders," Documentos de Trabajo 019431, Universidad del Rosario.
• Ana María Iregui-Bohórquez & César Anzola-Bravo & Luisa Fernanda Ballén-Rubio & Valeria Bejarano-Salcedo & Eliana González-Molano & Anderson Grajales-Olarte & Alexander Guarín-López & María Alejandra , 2021. "¿Qué nos dicen las encuestas sobre la formación de expectativas de inflación?," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, issue 100, pages 1-95, September.
  • Ana María Iregui-Bohórquez & César Anzola-Bravo & Luisa Fernanda Ballén-Rubio & Valeria Bejarano-Salcedo & Eliana González-Molano & Anderson Grajales-Olarte & Alexander Guarín-López & María Alejandra , 2021. "¿Qué nos dicen las encuestas sobre la formación de expectativas de inflación?," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República - ESPE, issue 100, pages 1-95, September.
• Katherine Coronel-Pangol & Gustavo Flores-Sánchez & Jorge Campoverde-Campoverde & Armando Romero-Galarza, 2021. "Aproximación predictiva al riesgo crediticio comercial en empresas alimenticias ecuatorianas," Estudios Gerenciales, Universidad Icesi, vol. 37(160), pages 413-424, August.
• Correa, Alexander, 2021. "Prediciendo la llegada de turistas a Colombia a partir de los criterios de Google Trends," Revista Lecturas de Economía, Universidad de Antioquia - CIE, issue No. 95, pages 105-134, July.
• Benchimol, Jonathan & Bounader, Lahcen, 2018. "Optimal monetary policy under bounded rationality," Research Discussion Papers 9/2018, Bank of Finland.
  • Benchimol, Jonathan & Bounader, Lahcen, 2021. "Optimal Monetary Policy Under Bounded Rationality," Dynare Working Papers 67, CEPREMAP.
  • Jonathan Benchimol & Lahcen Bounader, 2018. "Optimal Monetary Policy Under Bounded Rationality," Globalization Institute Working Papers 336, Federal Reserve Bank of Dallas.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy Under Bounded Rationality," IMF Working Papers 2019/166, International Monetary Fund.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy under Bounded Rationality," Bank of Israel Working Papers 2019.07, Bank of Israel.
• Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2020. "Nowcasting with large Bayesian vector autoregressions," Working Paper Series 2453, European Central Bank.
  • Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, Cambridge University Press, vol. 256, pages 71-109, April.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
  • 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?," CIRANO Working Papers 2021s-09, CIRANO.
• Charles Engel & Steve Pak Yeung Wu, 2021. "Forecasting the U.S. Dollar in the 21st Century," NBER Working Papers 28447, National Bureau of Economic Research, Inc.
  • Engel, Charles M & Wu, Steve Pak Yeung, 2021. "Forecasting the U.S. Dollar in the 21st Century," CEPR Discussion Papers 15915, C.E.P.R. Discussion Papers.
• Timmermann, Allan & Zhu, Yinchu, 2021. "Conditional Rotation Between Forecasting Models," CEPR Discussion Papers 15917, 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 21-02R, Federal Reserve Bank of Cleveland, revised 09 Aug 2021.
  • 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.
• Roshen Fernando & Weifeng Liu & Warwick J McKibbin, 2021. "Global economic impacts of climate shocks, climate policy and changes in climate risk assessment," CAMA Working Papers 2021-37, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Fernando, Roshen & Liu, Weifeng & McKibbin, Warwick, 2021. "Global Economic Impacts of Climate Shocks, Climate Policy and Changes in Climate Risk Assessment," CEPR Discussion Papers 16154, C.E.P.R. Discussion Papers.
• Mönch, Emanuel & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," Discussion Papers 25/2021, Deutsche Bundesbank.
  • Moench, Emanuel & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
• Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2021. "Nowcasting Tail Risk to Economic Activity at a Weekly Frequency," CEPR Discussion Papers 16496, C.E.P.R. Discussion Papers.
• Weifeng Liu & Warwick J. McKibbin & Ms. Florence Jaumotte, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," IMF Working Papers 2021/195, International Monetary Fund.
  • Jaumotte, Florence & Liu, Weifeng & McKibbin, Warwick, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," CEPR Discussion Papers 16553, C.E.P.R. Discussion Papers.
  • Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021. "Mitigating climate change: Growth-friendly policies to achieve net zero emissions by 2050," CAMA Working Papers 2021-75, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Juan Antolín-Díaz & Ivan Petrella & Juan F. Rubio-Ramírez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," Working Papers 2021-14, FEDEA.
  • Antolin-Diaz, Juan & Petrella, Ivan & Rubio-Ramírez, Juan Francisco, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," CEPR Discussion Papers 16613, C.E.P.R. Discussion Papers.
  • Juan Antolin-Diaz & Ivan Petrella & Juan F. Rubio-Ramirez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," FRB Atlanta Working Paper 2021-25, Federal Reserve Bank of Atlanta.
• Broer, Tobias & Kohlhas, Alexandre & Mitman, Kurt & Schlafmann, Kathrin, 2021. "On the Possibility of Krusell-Smith Equilibria," CEPR Discussion Papers 16667, C.E.P.R. Discussion Papers.
• 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.
  • Schorfheide, Frank & Song, Dongo, 2021. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," CEPR Discussion Papers 16760, C.E.P.R. Discussion Papers.
  • 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.
  • Frank Schorfheide & Dongho Song, 2021. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," NBER Working Papers 29535, National Bureau of Economic Research, Inc.
• Nikolai Dokuchaev, 2021. "On statistical indistinguishability of complete and incomplete market models," Studies in Economics and Finance, Emerald Group Publishing, vol. 38(1), pages 114-125, January.
• Ramiro Bautista Espinosa & Diana Terrazas Santamaría, 2021. "La viabilidad de invertir en almacenamiento de energía solar en México: un enfoque de opciones reales," Serie documentos de trabajo del Centro de Estudios Económicos 2021-09, El Colegio de México, Centro de Estudios Económicos.
• Klusak, P. & Agarwala, M. & Burke, M. & Kraemer, M. & Mohaddes, K., 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Cambridge Working Papers in Economics 2127, Faculty of Economics, University of Cambridge.
  • Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Working Papers EPRG2110, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • 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 158, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
  • Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising temperatures, falling ratings: The effect of climate change on sovereign creditworthiness," CAMA Working Papers 2021-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Yose Rizal Damuri & Prabaning Tyas & Haryo Aswicahyono & Lionel Priyadi & Stella Kusumawardhani & Ega Kurnia Yazid, 2021. "Tracking the Ups and Downs in Indonesia’s Economic Activity During COVID-19 Using Mobility Index: Evidence from Provinces in Java and Bali," Working Papers DP-2021-18, Economic Research Institute for ASEAN and East Asia (ERIA).
• Zoumpoulidis Vassilios, 2021. "The Relationship between Taxation Levels and Economic Growth in Greece: Comparison with Selected Countries," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(2), pages 321-343.
• Halina Swieboda & Mateusz Kuczabski & Ryszard Szpyra & Tomasz Zawadzki & Tomasz Walecki & Pawel Stobiecki, 2021. "Social Control in the Face of Digital Propaganda," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 1057-1069.
• Ilona Urych, 2021. "The Use of Models for the Diagnosis of Defence Potential in the Strategic Management of Activities by Civilians to Strengthen National Security," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 830-840.
• Joanna Kowalik, 2021. "The “UMO” as an Example of Scientific Project Implementation," European Research Studies Journal, European Research Studies Journal, vol. 0(2B), pages 1055-1068.
• Tomasz Lukaszewski, 2021. "Buildings Thermal Retrofit Investement under ESCO Formula - A Case Study from Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(2B), pages 1081-1093.
• Michal Gostkowski & Tomasz Rokicki, 2021. "Forecasting the Unemployment Rate: Application of Selected Prediction Methods," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 985-1000.
• Vladislavas Kutut & Natalija Lepkova & Sabina Zrobek, 2021. "Immovable Cultural Heritage Usage Modes: Theoretical Approach," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 1136-1151.
• Joanna Holub-Iwan, 2021. "Management Information Systems of Public Health Behaviors based on Evidence in Medicine and Health Management," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 623-643.
• Katarzyna Puszko, 2021. "Effectivity of Leadership," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 644-663.
• Katarzyna Puszko, 2021. "Denotation of Leadership Efficiency," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 664-676.
• Pawel Rymarczyk & Piotr Bednarczuk & Ryszard Nowak & Tomasz Cieplak, 2021. "Methods of Analyzing Consumer Behavior Based on Multi-Source Data," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 335-345.
• Pawel Rymarczyk & Piotr Golabek & Sylwia Skrzypek - Ahmed & Magdalena Rzemieniak, 2021. "Profiling and Segmenting Clients with the Use of Machine Learning Algorithms," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 513-522.
• Lukasz Golabek & Konrad Gauda & Krzysztof Zuk & Edward Kozlowski, 2021. "Identification of the Demand Curve and Forecasts in Subsequent Periods Using the Metropolis-Hastings Algorithm," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 523-533.
• Ferrara, Laurent & Karadimitropoulou, Aikaterini & Triantafyllou, Athanasios, 2021. "Commodity price uncertainty comovement: Does it matter for global economic growth?," Essex Finance Centre Working Papers 30945, University of Essex, Essex Business School.
  • Laurent Ferrara & Aikaterini Karadimitropoulou & Athanasios Triantafyllou, 2022. "Commodity price uncertainty comovement: Does it matter for global economic growth?," CAMA Working Papers 2022-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
• Poghosyan, Karen & Poghosyan, Ruben, 2021. "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 28-46.
  • Karen Poghosyan & Ruben Poghosyan, 2021. "On the Applicability of Dynamic Factor Models for Forecasting Real GDP Growth in Armenia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 71(1), pages 52-79, June.
• Michal Kuchta, 2021. "Scenario Generation for IFRS9 Purposes using a Bayesian MS-VAR Model," Working Papers IES 2021/10, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2021.
• Barbora Malinska, 2021. "Forecasting Sovereign Bond Realized Volatility Using Time-Varying Coefficients Model," Working Papers IES 2021/19, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jun 2021.
• Anna Gloria Billé & Alessio Tomelleri & Francesco Ravazzolo, 2021. "Forecasting Regional GDPs: a Comparison with Spatial Dynamic Panel Data Models," FBK-IRVAPP Working Papers 2021-02, Research Institute for the Evaluation of Public Policies (IRVAPP), Bruno Kessler Foundation.
• Antolin-Diaz, Juan & Petrella, Ivan & Rubio-Ramírez, Juan Francisco, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," CEPR Discussion Papers 16613, C.E.P.R. Discussion Papers.
  • Juan Antolín-Díaz & Ivan Petrella & Juan F. Rubio-Ramírez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," Working Papers 2021-14, FEDEA.
  • Juan Antolin-Diaz & Ivan Petrella & Juan F. Rubio-Ramirez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," FRB Atlanta Working Paper 2021-25, Federal Reserve Bank of Atlanta.
• Antolin-Diaz, Juan & Petrella, Ivan & Rubio-Ramírez, Juan Francisco, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," CEPR Discussion Papers 16613, C.E.P.R. Discussion Papers.
  • Juan Antolin-Diaz & Ivan Petrella & Juan F. Rubio-Ramirez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," FRB Atlanta Working Paper 2021-25, Federal Reserve Bank of Atlanta.
  • Juan Antolín-Díaz & Ivan Petrella & Juan F. Rubio-Ramírez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," Working Papers 2021-14, FEDEA.
• 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 21-02R, Federal Reserve Bank of Cleveland, revised 09 Aug 2021.
• Robert W. Rich & Joseph Tracy, 2021. "All Forecasters Are Not the Same: Time-Varying Predictive Ability across Forecast Environments," Working Papers 21-06, 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 21-08, Federal Reserve Bank of Cleveland.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
• James Mitchell & Martin Weale, 2021. "Censored Density Forecasts: Production and Evaluation," Working Papers 21-12, Federal Reserve Bank of Cleveland.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021. "Macroeconomic Forecasting in a Multi-country Context," Working Papers 22-02, Federal Reserve Bank of Cleveland.
  • Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
• Chad Fulton & Kirstin Hubrich, 2021. "Forecasting US Inflation in Real Time," Finance and Economics Discussion Series 2021-014, Board of Governors of the Federal Reserve System (U.S.).
• Dong Hwan Oh & Andrew J. Patton, 2021. "Better the Devil You Know: Improved Forecasts from Imperfect Models," Finance and Economics Discussion Series 2021-071, Board of Governors of the Federal Reserve System (U.S.).
• 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 2021-074, Board of Governors of the Federal Reserve System (U.S.).
• Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
• 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 1313, Board of Governors of the Federal Reserve System (U.S.).
• Dario Caldara & Chiara Scotti & Molin Zhong, 2021. "Macroeconomic and Financial Risks: A Tale of Mean and Volatility," International Finance Discussion Papers 1326, Board of Governors of the Federal Reserve System (U.S.).
• 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 WP-2021-05, Federal Reserve Bank of Chicago, revised 18 Jun 2021.
• Richard K. Crump & Stefano Eusepi & Domenico Giannone & Eric Qian & Argia M. Sbordone, 2021. "A Large Bayesian VAR of the United States Economy," Staff Reports 976, Federal Reserve Bank of New York.
• Richard Berner & Robert Engle & Hyeyoon Jung, 2021. "Climate Stress Testing," Staff Reports 977, Federal Reserve Bank of New York.
• Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models," Working Papers 21-21, Federal Reserve Bank of Philadelphia.
• 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, vol. 11(6), pages 46-56, December.
• Tsukhlo Sergey, 2021. "Russian industrial sector in 2020: (based on surveys’ findings)," Published Papers ppaper-2021-1125, Gaidar Institute for Economic Policy, revised 2021.
• Barinova Vera & Zemtsov Tsepan & Tsareva Yulia, 2021. "Small and medium business amid coronacrisis," Published Papers ppaper-2021-1130, Gaidar Institute for Economic Policy, 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.
• Sheng, Xin & Gupta, Rangan & Salisu, Afees A. & Bouri, Elie, 2022. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Finance Research Letters, Elsevier, vol. 45(C).
  • Xin Sheng & Rangan Gupta & Afees A. Salisu & Elie Bouri, 2021. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Working Papers 202101, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna & Mark E. Wohar, 2021. "Uncertainty and Predictability of Real Housing Returns in the United Kingdom: A Regional Analysis," Working Papers 202102, University of Pretoria, Department of Economics.
• Afees A. Salisu & Umar Bida Ndako & Rangan Gupta, 2021. "Forecasting US Output Growth with Large Information Sets," Working Papers 202103, University of Pretoria, Department of Economics.
• Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
• Riza Demirer & Rangan Gupta & He Li & Yu You, 2021. "Financial Vulnerability and Volatility in Emerging Stock Markets: Evidence from GARCH-MIDAS Models," Working Papers 202112, University of Pretoria, Department of Economics.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Forecasting realized volatility of international REITs: The role of realized skewness and realized kurtosis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 303-315, March.
  • Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of International REITs: The Role of Realized Skewness and Realized Kurtosis," Working Papers 202114, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil prices over 150 years: The role of tail risks," Resources Policy, Elsevier, vol. 75(C).
  • Afees A. Salisu & Rangan Gupta & Qiang Ji, 2021. "Forecasting Oil Price over 150 Years: The Role of Tail Risks," Working Papers 202120, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Gupta, Rangan & Demirer, Riza, 2022. "Global financial cycle and the predictability of oil market volatility: Evidence from a GARCH-MIDAS model," Energy Economics, Elsevier, vol. 108(C).
  • Afees A. Salisu & Rangan Gupta & Riza Demirer, 2021. "Global Financial Cycle and the Predictability of Oil Market Volatility: Evidence from a GARCH-MIDAS Model," Working Papers 202121, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2021. "Geopolitical risk and forecastability of tail risk in the oil market: Evidence from over a century of monthly data," Energy, Elsevier, vol. 235(C).
  • Afees A. Salisu & Christian Pierdzioch & Rangan Gupta, 2021. "Geopolitical Risk and Forecastability of Tail Risk in the Oil Market: Evidence from Over a Century of Monthly Data," Working Papers 202122, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Christian Pierdzioch, 2021. "Predictability of Tail Risks of Canada and the U.S. Over a Century: The Role of Spillovers and Oil Tail Risks," Working Papers 202127, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
  • Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," GRU Working Paper Series GRU_2021_017, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
  • Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," Working Papers 202133, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers," Energies, MDPI, vol. 14(14), pages 1-15, July.
  • Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers," Working Papers 202135, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty, Spillovers, and Forecasts of the Realized Variance of Gold Returns," Working Papers 202137, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta, 2021. "Commodity Prices and Forecastability of South African Stock Returns Over a Century: Sentiments versus Fundamentals," Working Papers 202144, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2022. "Oil tail risks and the forecastability of the realized variance of oil-price: Evidence from over 150 years of data," Finance Research Letters, Elsevier, vol. 46(PB).
  • Afees A. Salisu & Christian Pierdzioch & Rangan Gupta, 2021. "Oil Tail Risks and the Forecastability of the Realized Variance of Oil-Price: Evidence from Over 150 Years of Data," Working Papers 202146, University of Pretoria, Department of Economics.
• Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & David Gabauer, 2021. "Forecasting Stock-Market Tail Risk and Connectedness in Advanced Economies Over a Century: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios," Working Papers 202161, University of Pretoria, Department of Economics.
• Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & Renee van Eyden, 2021. "Climate Risks and U.S. Stock-Market Tail Risks: A Forecasting Experiment Using over a Century of Data," Working Papers 202165, University of Pretoria, Department of Economics.
• Karmakar, Sayar & Demirer, Riza & Gupta, Rangan, 2021. "Bitcoin mining activity and volatility dynamics in the power market," Economics Letters, Elsevier, vol. 209(C).
  • Sayar Karmakar & Riza Demirer & Rangan Gupta, 2021. "Bitcoin Mining Activity and Volatility Dynamics in the Power Market," Working Papers 202166, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and Forecastability of the Realized Volatility of Gold and Other Metal Prices," Working Papers 202172, University of Pretoria, Department of Economics.
• Jiqian Wang & Rangan Gupta & Oguzhan Cepni & Feng Ma, 2021. "Forecasting International REITs Volatility: The Role of Oil-Price Uncertainty," Working Papers 202173, University of Pretoria, Department of Economics.
• 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, vol. 14(23), pages 1-18, December.
  • Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and the Realized Volatility Oil and Gas Prices: Results of an Out-of-Sample Forecasting Experiment," Working Papers 202175, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Realized Variance of Oil-Price Returns: A Disaggregated Analysis of the Role of Uncertainty and Geopolitical Risk," Working Papers 202176, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risk and the Volatility of Agricultural Commodity Price Fluctuations: A Forecasting Experiment," Working Papers 202177, University of Pretoria, Department of Economics.
• Ruipeng Liu & Rangan Gupta & Elie Bouri, 2021. "Conventional and Unconventional Monetary Policy Rate Uncertainty and Stock Market Volatility: A Forecasting Perspective," Working Papers 202178, University of Pretoria, Department of Economics.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2021. "El Nino, La Nina, and Forecastability of the Realized Variance of Agricultural Commodity Prices: Evidence from a Machine Learning Approach," Working Papers 202179, University of Pretoria, Department of Economics.
• Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and Forecasting Stock-Market Returns in Advanced Economies Over a Century," Working Papers 202183, University of Pretoria, Department of Economics.
• Paulina Ziembińska, 2021. "Quality of Tests of Expectation Formation for Revised Data," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(4), pages 405-453, December.
• Bhumjai Tangsawasdirat & Suranan Tanpoonkiat & Burasakorn Tangsatchanan, 2021. "Credit Risk Database: Credit Scoring Models for Thai SMEs," PIER Discussion Papers 168, Puey Ungphakorn Institute for Economic Research.
• Eliud Silva & Corey Sparks, 2021. "Hierarchical forecasts of Diabetes mortality in Mexico by marginalization and sex to establish resource allocation," EconoQuantum, Revista de Economia y Finanzas, Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas, Departamento de Metodos Cuantitativos y Maestria en Economia., vol. 18(2), pages 82-98, Julio-Dic.
• Luke Hartigan & Michelle Wright, 2021. "Financial Conditions and Downside Risk to Economic Activity in Australia," RBA Research Discussion Papers rdp2021-03, Reserve Bank of Australia.
• Pérez Forero, Fernando, 2021. "Predicción de variables macroeconómicas en el Perú a través un modelo BVAR con media cambiante en el tiempo," Working Papers 2021-001, Banco Central de Reserva del Perú.
• Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.
• Anna Gloria Billé & Angelica Gianfreda & Filippo Del Grosso & Francesco Ravazzolo, 2021. "Forecasting Electricity Prices with Expert, Linear and Non-Linear Models," Working Paper series 21-20, Rimini Centre for Economic Analysis.
• Uddin, Gazi Salah & Tang, Ou & Sahamkhadam, Maziar & Taghizadeh-Hesary, Farhad & Yahya, Muhammad & Cerin, Pontus & Rehme, Jakob, 2021. "Analysis of Forecasting Models in an Electricity Market under Volatility," ADBI Working Papers 1212, Asian Development Bank Institute.
• Karen Poghosyan & Ruben Poghosyan, 2021. "On the Applicability of Dynamic Factor Models for Forecasting Real GDP Growth in Armenia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 71(1), pages 52-79, June.
  • Poghosyan, Karen & Poghosyan, Ruben, 2021. "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 28-46.
• Garafutdinov, Robert, 2021. "Influence of some ARFIMA model parameters on the accuracy of financial time series forecasting," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 62, pages 85-100.
• Fokin, Nikita, 2021. "The importance of modeling structural breaks in forecasting Russian GDP," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 5-29.
• ERİLLİ, Necati Alp, 2021. "Use of Trimean in Theil-Sen Regression Analysis," Bulletin of Economic Theory and Analysis, BETA Journals, vol. 6(1), pages 15-26, June.
• Kocak, Necmettin Alpay, 2021. "Analysis of Relationship between the Consumer and Producer Prices in Turkey using Alternative Estimation Methods (Türkiye'de Tüketici ve Üretici Fiyatları Arasındaki İlişkinin Alternatif Tahmin Yöntem," Business and Economics Research Journal, Uludag University, Faculty of Economics and Administrative Sciences, vol. 12(1), pages 33-47, January.
• Adli, Kaveh A. & Sener, Ugur, 2021. "Forecasting of the U.S. Steel Prices with LVAR and VEC Models," Business and Economics Research Journal, Uludag University, Faculty of Economics and Administrative Sciences, vol. 12(3), pages 509-522, July.
• de Lucio, Juan, 2021. "Estimación adelantada del crecimiento regional mediante redes neuronales LSTM," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 49, pages 45-64.
• Mendoza-González, Miguel Ángel, 2021. "Apertura comercial, choques productivos y externalidades con ciclos espacio-tiempo en el crecimiento económico por entidad federativa en México, 1980-2018," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 50, pages 105-124.
• Bhaghoe, Sailesh & Ooft, Gavin, 2021. "Nowcasting Quarterly GDP Growth in Suriname with Factor-MIDAS and Mixed-Frequency VAR Models," Studies in Applied Economics 176, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
• Rao, Anitha & Wiendling, Mark & Ridgeway, Paul & Kennedy, Liz & Eyre, Harris A. & Pinho, Paulo, 2021. "Bridging the Gap Between Medicine and Insurance: How to Leverage Data, Artificial Intelligence, and Neuroinformatics for Insurance and Financial Risk Management," Journal of Financial Transformation, Capco Institute, vol. 54, pages 142-147.
• Sadeghpour, Solmaz & Heidari, Hassan & Mohseni Zenozi, Seyyed Jamaleddin, 2021. "Study the effect of the monetary and financial shocks in the real sector of Iran's economy with considering of gharz-al -hasanah deposits in the context of a DSGE model," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 8(1), pages 89-114, June.
• Chow, Hwee Kwan & Han, Daniel, 2021. "Forecast Pooling or Information Pooling During Crises? MIDAS Forecasting of GDP in a Small Open Economy," Economics and Statistics Working Papers 6-2021, Singapore Management University, School of Economics.
• Weiwei ZHANG & Tiezhu SUN & Yechi MA & Zilong WANG, 2021. "New Evidence on the Information Content of Implied Volatility of S&P 500: Model-Free versus Model-Based," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 109-121, December.
• Fatemeh SALIMIANRAD & Vali BORIMNEJAD & Sahar DEHYUORI, 2021. "Investigating the Relationship between Natural Capital and Sustainable Economic Growth using the General Equilibrium Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 120-139, June.
• Kirill Dragun & Kris Boudt & Orimar Sauri & Steven Vanduffel, 2021. "Beta-Adjusted Covariance Estimation," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1010, Ghent University, Faculty of Economics and Business Administration.
• George Varghese & Vinodh Madhavan, 2021. "Nonlinearity in Global Crude Oil Benchmarks: Disentangling the Effect of Time Aggregation," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 20(3), pages 290-307, December.
• Tomas Havranek & Ayaz Zeynalov, 2021. "Forecasting tourist arrivals: Google Trends meets mixed-frequency data," Tourism Economics, , vol. 27(1), pages 129-148, February.
  • Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
• Wojciech Charemza & Michal Lewandowski & Lukasz Wozny, 2021. "Efficiency in rewarding academic journal publications. The case of Poland," Working Papers 2021-062, Warsaw School of Economics, Collegium of Economic Analysis.
• Alejandro Rodriguez Arana, 2021. "La expansion de Covid-19 en Mexico en 2020: un enfoque desde la econometria de series de tiempo," Sobre México. Revista de Economía, Sobre México. Temas en economía, vol. 1(3), pages 34-66.
• F. Benedetto & L. Mastroeni & P. Vellucci, 2021. "Modeling the flow of information between financial time-series by an entropy-based approach," Annals of Operations Research, Springer, vol. 299(1), pages 1235-1252, April.
• Chrysovalantis Gaganis & Panagiota Papadimitri & Menelaos Tasiou, 2021. "A multicriteria decision support tool for modelling bank credit ratings," Annals of Operations Research, Springer, vol. 306(1), pages 27-56, November.
• Eric Séverin & David Veganzones, 2021. "Can earnings management information improve bankruptcy prediction models?," Annals of Operations Research, Springer, vol. 306(1), pages 247-272, November.
• Yuzhi Cai & Thanaset Chevapatrakul & Danilo V. Mascia, 2021. "How is price explosivity triggered in the cryptocurrency markets?," Annals of Operations Research, Springer, vol. 307(1), pages 37-51, December.
• Christos Agiakloglou & Apostolos Tsimpanos, 2021. "Evaluating information criteria for selecting spatial processes," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 66(3), pages 677-697, June.
• David Volkmann, 2021. "Explaining S&P500 option returns: an implied risk-adjusted approach," 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. 29(2), pages 665-685, June.
• Michal Mešťan & Ivan Králik & Matej Žofaj & Nikola Karkošiaková & Audrius Kabašinskas, 2021. "Projections of pension benefits in supplementary pension saving scheme in Slovakia," 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. 29(2), pages 687-712, June.
• Gianna Figá-Talamanca & Sergio Focardi & Marco Patacca, 2021. "Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 863-882, December.
• Paolo Angelis & Roberto Marchis & Mario Marino & Antonio Luciano Martire & Immacolata Oliva, 2021. "Betting on bitcoin: a profitable trading between directional and shielding strategies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 883-903, December.
• Prilly Oktoviany & Robert Knobloch & Ralf Korn, 2021. "A machine learning-based price state prediction model for agricultural commodities using external factors," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1063-1085, December.
• 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.
  • Aloy, Marcel & Laly, Floris & Laurent, Sébastien & Lecourt, Christelle, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," LIDAM Reprints LFIN 2021021, Université catholique de Louvain, Louvain Finance (LFIN).
• Alain Kabundi & Asithandile Mbelu, 2021. "Estimating a time-varying financial conditions index for South Africa," Empirical Economics, Springer, vol. 60(4), pages 1817-1844, April.
  • Alain Kabundi & Asi Mbelu, 2017. "Estimating a timevarying financial conditions index for South Africa," Working Papers 8008, South African Reserve Bank.
• Yongchen Zhao, 2021. "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
• Jack Fosten & Daniel Gutknecht, 2021. "Horizon confidence sets," Empirical Economics, Springer, vol. 61(2), pages 667-692, August.
• Serdar Neslihanoglu & Stelios Bekiros & John McColl & Duncan Lee, 2021. "Multivariate time-varying parameter modelling for stock markets," Empirical Economics, Springer, vol. 61(2), pages 947-972, August.
• Georges Tsafack & James Cataldo, 2021. "Backtesting and estimation error: value-at-risk overviolation rate," Empirical Economics, Springer, vol. 61(3), pages 1351-1396, September.
• 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, vol. 61(4), pages 1917-1933, October.
  • Edmond Berisha & David Gabauer & Rangan Gupta & Chi Keung Marco Lau, 2020. "Time-Varying Influence of Household Debt on Inequality in United Kingdom," Working Papers 202017, University of Pretoria, Department of Economics.
• Nima Nonejad, 2021. "Crude oil price point forecasts of the Norwegian GDP growth rate," Empirical Economics, Springer, vol. 61(5), pages 2913-2930, November.
• 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, vol. 48(3), pages 463-504, September.
• 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, vol. 7(1), pages 1-25, December.
• 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, vol. 91(9), pages 1469-1497, November.
• 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), vol. 17(3), pages 263-291, December.
• Pelin Akyol & Kala Krishna & Jinwen Wang, 2021. "Taking PISA Seriously: How Accurate are Low-Stakes Exams?," Journal of Labor Research, Springer, vol. 42(2), pages 184-243, June.
  • Ş. Pelin Akyol & Kala Krishna & Jinwen Wang, 2018. "Taking PISA Seriously: How Accurate are Low Stakes Exams?," NBER Working Papers 24930, National Bureau of Economic Research, Inc.
• 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), vol. 72(1), pages 133-166, July.
• Annalisa Cristini & Piero Ferri, 2021. "Nonlinear models of the Phillips curve," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1129-1155, September.
• 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), vol. 19(1), pages 363-381, December.
• 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), vol. 19(1), pages 383-400, December.
• 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), vol. 19(1), pages 419-441, December.
• 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, vol. 14(2), pages 111-128, August.
• Ricarda B. Bouncken & Yixin Qiu & Noemi Sinkovics & Wolfgang Kürsten, 2021. "Qualitative research: extending the range with flexible pattern matching," Review of Managerial Science, Springer, vol. 15(2), pages 251-273, February.
• Rosina O. Weber & Kedma B. Duarte, 2021. "Data-driven artificial intelligence to automate researcher assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3265-3281, April.
• 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, vol. 12(3), pages 329-349, September.
• 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, vol. 12(4), pages 687-708, December.
• 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, vol. 11(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, vol. 11(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 948, Statistics Norway, Research Department.
• Pål Boug & Håvard Hungnes & Takamitsu Kurita, 2021. "The empirical modelling of house prices and debt revisited. A policy-oriented perspective," Discussion Papers 967, Statistics Norway, Research Department.
• Martin Iseringhausen, 2021. "A time-varying skewness model for Growth-at-Risk," Working Papers 49, European Stability Mechanism.
• Hanjo Odendaal, 2021. "A machine learning approach to domain specific dictionary generation. An economic time series framework," Working Papers 06/2021, Stellenbosch University, Department of Economics.
• Constantin Bürgi & Tara M. Sinclair, 2021. "What does forecaster disagreement tell us about the state of the economy?," Applied Economics Letters, Taylor & Francis Journals, vol. 28(1), pages 49-53, January.
  • Constantin Bürgi & Tara M. Sinclair, 2020. "What Does Forecaster Disagreement Tell Us about the State of the Economy?," Working Papers 2020-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• 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, vol. 28(21), pages 1889-1897, December.
  • Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2020. "A Note on Oil Price Shocks and the Forecastability of Gold Realized Volatility," Working Papers 202010, University of Pretoria, Department of Economics.
• Antonio Rodríguez Andrés & Voxi Heinrich S. Amavilah & Abraham Otero, 2021. "Evaluation of technology clubs by clustering: a cautionary note," Applied Economics, Taylor & Francis Journals, vol. 53(52), pages 5989-6001, November.
  • Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Evaluation of technology clubs by clustering: A cautionary note," MPRA Paper 109138, University Library of Munich, Germany.
• Tommaso Proietti, 2021. "Predictability, real time estimation, and the formulation of unobserved components models," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 433-454, April.
  • Tommaso Proietti, 2019. "Predictability, Real Time Estimation, and the Formulation of Unobserved Components Models," CEIS Research Paper 455, Tor Vergata University, CEIS, revised 22 Mar 2019.
• Antoine A. Djogbenou, 2021. "Model selection in factor-augmented regressions with estimated factors," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 470-503, April.
  • Antoine A. Djogbenou, 2017. "Model Selection In Factor-augmented Regressions With Estimated Factors," Working Paper 1391, Economics Department, Queen's University.
• 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.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections — IV models," Working Papers 1841, Banco de España.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence Intervals for Bias and Size Distortion in IV and Local Projections–IV Models," Working Papers 1077, Barcelona Graduate School of Economics.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections–IV models," Economics Working Papers 1640, Department of Economics and Business, Universitat Pompeu Fabra.
• 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, vol. 39(4), pages 1054-1065, October.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," CEPR Discussion Papers 14107, C.E.P.R. Discussion Papers.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers) 1296, Bank of Italy, Economic Research and International Relations Area.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," EMF Research Papers 29, Economic Modelling and Forecasting Group.
  • Delle Monache, Davide & Venditti, Fabrizio & Petrella, Ivan, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Working Paper Series 2369, European Central Bank.
• Selcuk Gul & Abdullah Kazdal, 2021. "Nowcasting and Short-term Forecasting Turkish GDP: Factor-MIDAS Approach," Working Papers 2111, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Ioannis Sitzimis, 2021. "An Optimal Forecasting Method of Passenger Traffic in Greek Coastal Shipping," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 14(3), pages 72-87, December.

2020

• 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.
• Martínez Vázquez, David Conaly & Pérez Avila, Héctor, 2020. "Proyección Markoviana de riesgos hidrometeorológicos para el cálculo actuarial en México al 2020 / Markovian projection of hydrometeorological risks for actuarial calculation in Mexico up to 2020," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 10(2), pages 163-194, julio-dic.
• 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).
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Post-Print hal-03403017, HAL.
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Working Papers hal-03403073, HAL.
• Reichlin, Lucrezia & Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial variables as predictors of real growth vulnerability," Discussion Papers 05/2020, Deutsche Bundesbank.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," 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.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Working Papers hal-03403077, HAL.
  • 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).
• 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 1-4.
  • 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.
• Aitor Erce & Xu Jiang & Diana Zigraiova, 2020. "Quantifying Risks to Sovereign Market Access: Methods and Challenges," Globalization Institute Working Papers 377, Federal Reserve Bank of Dallas.
  • Diana Žigraiová & Aitor Erce & Xu Jiang, 2020. "Quantifying risks to sovereign market access: Methods and challenges," Working Papers 42, European Stability Mechanism.
• Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, 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.
• R. Erasmus & H. Hollander, 2020. "A Forward Guidance Indicator For The South African Reserve Bank: Implementing A Text Analysis Algorithm," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 44(3), pages 41-72, December.
  • 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.
• 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.
  • Hossein Hassani & Mohammad Reza Yeganegi & Juncal Cunado & Rangan Gupta, 2018. "Forecasting Interest Rate Volatility of the United Kingdom: Evidence from over 150 Years of Data," Working Papers 201873, University of Pretoria, Department of Economics.
• 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.
  • Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Papers No 01/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
• Joshua C. C. Chan, 2020. "Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
  • Joshua C.C. Chan, 2015. "Large Bayesian VARs: A flexible Kronecker error covariance structure," CAMA Working Papers 2015-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• 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.
  • Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
• Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2020. "Markov-Switching Three-Pass Regression Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 285-302, April.
  • Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-switching three-pass regression filter," Working Papers 1748, Banco de España.
  • Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-Switching Three-Pass Regression Filter," Staff Working Papers 17-13, Bank of Canada.
• 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.
  • Bormann, Carsten & Schienle, Melanie, 2019. "Detecting structural differences in tail dependence of financial time series," Working Paper Series in Economics 122, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
• Georges Dionne & Xiaozhou Zhou, 2020. "The dynamics of ex-ante weighted spread: an empirical analysis," Quantitative Finance, Taylor & Francis Journals, vol. 20(4), pages 593-617, April.
  • Dionne, Georges & Zhou, Xiaozhou, 2016. "The Dynamics of Ex-ante Weighted Spread: An Empirical Analysis," Working Papers 16-4, HEC Montreal, Canada Research Chair in Risk Management, revised 04 Nov 2019.
• R. Erasmus & H. Hollander, 2020. "A Forward Guidance Indicator For The South African Reserve Bank: Implementing A Text Analysis Algorithm," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 44(3), pages 41-72, December.
  • 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.
• 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.
• 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.
• Laura Liu, 2018. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," Papers 1805.04178, arXiv.org, revised Oct 2021.
  • Laura Liu, 2020. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," CAEPR Working Papers 2020-003, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
  • Laura Liu, 2018. "Density Forecasts in Panel Data Models : A Semiparametric Bayesian Perspective," Finance and Economics Discussion Series 2018-036, Board of Governors of the Federal Reserve System (U.S.).
• Oscar Claveria & Ivana Lolic & Enric Monte & Salvador Torra & Petar Soric, 2020. "“Economic determinants of employment sentiment: A socio-demographic analysis for the euro area”," AQR Working Papers 2012001, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2020.
  • Oscar Claveria & Ivana Lolic & Enric Monte & Petar Soric, 2020. "Economic determinants of employment sentiment: A socio-demographic analysis for the euro area," IREA Working Papers 202001, University of Barcelona, Research Institute of Applied Economics, revised Jan 2020.
• Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," 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.
• Zidong An & Joao Tovar Jalles, 2020. "On the performance of US fiscal forecasts: government vs. private information," Journal of Economic Studies, Emerald Group Publishing, vol. 48(2), pages 367-391, June.
  • Zidong An & João Tovar Jalles, 2020. "On the Performance of US Fiscal Forecasts: Government vs. Private Information," Working Papers REM 2020/0130, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
• Kaiser, Ulrich & Kuhn, Johan Moritz, 2020. "Value of Publicly Available, Textual and Non-textuThe al Information for Startup Performance Prediction," IZA Discussion Papers 13029, Institute of Labor Economics (IZA).
• Wilde, Joshua & Chen, Wei & Lohmann, Sophie, 2020. "COVID-19 and the Future of US Fertility: What Can We Learn from Google?," SocArXiv 2bgqs, Center for Open Science.
  • Wilde, Joshua & Chen, Wei & Lohmann, Sophie, 2020. "COVID-19 and the Future of US Fertility: What Can We Learn from Google?," IZA Discussion Papers 13776, Institute of Labor Economics (IZA).
  • Joshua Wilde & Wei Chen & Sophie Lohmann, 2020. "COVID-19 and the future of US fertility: what can we learn from Google?," MPIDR Working Papers WP-2020-034, Max Planck Institute for Demographic Research, Rostock, Germany.
• Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2020. "Googling Unemployment During the Pandemic: Inference and Nowcast Using Search Data," Working Papers 2020-04, Joint Research Centre, European Commission.
• 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.
  • 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.
• Mawuli Segnon & Stelios Bekiros, 2020. "Forecasting volatility in bitcoin market," Annals of Finance, Springer, vol. 16(3), pages 435-462, September.
• Murat Midiliç, 2020. "Estimation of STAR–GARCH Models with Iteratively Weighted Least Squares," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 87-117, January.
• Stefan Palan & Jürgen Huber & Larissa Senninger, 2020. "Aggregation mechanisms for crowd predictions," Experimental Economics, Springer;Economic Science Association, vol. 23(3), pages 788-814, September.
  • Stefan Palan & Jürgen Huber & Larissa Senninger, 2019. "Aggregation Mechanisms for Crowd Predictions," Working Paper Series, Social and Economic Sciences 2019-01, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
• Bernard Fingleton, 2020. "Italexit, is it another Brexit?," Journal of Geographical Systems, Springer, vol. 22(1), pages 77-104, January.
• Takafumi Kato, 2020. "Likelihood-based strategies for estimating unknown parameters and predicting missing data in the simultaneous autoregressive model," Journal of Geographical Systems, Springer, vol. 22(1), pages 143-176, January.
• Frank J. Fabozzi & Iason Kynigakis & Ekaterini Panopoulou & Radu S. Tunaru, 2020. "Detecting Bubbles in the US and UK Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 60(4), pages 469-513, May.
• Robina Iqbal & Ghulam Sorwar & Rose Baker & Taufiq Choudhry, 2020. "Multiday expected shortfall under generalized t distributions: evidence from global stock market," Review of Quantitative Finance and Accounting, Springer, vol. 55(3), pages 803-825, October.
• Jan Alexander Fischer & Philipp Pohl & Dietmar Ratz, 2020. "A machine learning approach to univariate time series forecasting of quarterly earnings," Review of Quantitative Finance and Accounting, Springer, vol. 55(4), pages 1163-1179, November.
• Cem Cakmakli & Hamza Demircan, 2020. "Using Survey Information for Improving the Density Nowcasting of US GDP with a Focus on Predictive Performance during Covid-19 Pandemic," Koç University-TUSIAD Economic Research Forum Working Papers 2016, Koc University-TUSIAD Economic Research Forum.
• Eda Gulsen & Hakan Kara, 2020. "Formation of inflation expectations: Does macroeconomic and policy environment matter?," Koç University-TUSIAD Economic Research Forum Working Papers 2017, Koc University-TUSIAD Economic Research Forum.
• Daniel Wochner, 2020. "Dynamic Factor Trees and Forests – A Theory-led Machine Learning Framework for Non-Linear and State-Dependent Short-Term U.S. GDP Growth Predictions," KOF Working papers 20-472, KOF Swiss Economic Institute, ETH Zurich.
• Samad Sarferaz & Andreas Dibiasi, 2020. "Measuring Macroeconomic Uncertainty: A Cross-Country Analysis," KOF Working papers 20-479, KOF Swiss Economic Institute, ETH Zurich.
• Florian Eckert & Philipp Kronenberg & Heiner Mikosch & Stefan Neuwirth, 2020. "Tracking Economic Activity With Alternative High-Frequency Data," KOF Working papers 20-488, KOF Swiss Economic Institute, ETH Zurich.
• Boros, Péter, 2020. "A hitelminősítői bejelentések fertőző hatásai és a hitelértékelési kiigazítás [Rating migration, credit risk contagion and Credit Valuation Adjustment]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 140-163.
• Christian Estmann & Bjoern Bo Soerensen & Benno Ndulu & John Rand, 2020. "Merchandise export diversification strategy for Tanzania - promoting inclusive growth, economic complexity and structural change," DERG working paper series 20-02, University of Copenhagen. Department of Economics. Development Economics Research Group (DERG).
• Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
  • Alessandro Giovannelli & Daniele Massacci & Stefano Soccorsi, 2020. "Forecasting Stock Returns with Large Dimensional Factor Models," Working Papers 305661169, Lancaster University Management School, Economics Department.
• Elena Ivona DUMITRESCU & Sullivan HUE & Christophe HURLIN & Sessi TOKPAVI, 2020. "Machine Learning or Econometrics for Credit Scoring: Let’s Get the Best of Both Worlds," LEO Working Papers / DR LEO 2839, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Elena Dumitrescu & Sullivan Hué & Christophe Hurlin & Sessi Tokpavi, 2021. "Machine Learning or Econometrics for Credit Scoring: Let's Get the Best of Both Worlds," Working Papers hal-02507499, HAL.
• Tomas Reichenbachas, 2020. "Assessing the impact of macroprudential measures: The case of the LTV limit in Lithuania," Bank of Lithuania Working Paper Series 80, Bank of Lithuania.
• Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
  • Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model An application to the German business cycle," Munich Reprints in Economics 84736, University of Munich, Department of Economics.
  • Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," CESifo Working Paper Series 6457, CESifo.
• Andrejs Bessonovs & Olegs Krasnopjorovs, 2021. "Short-term inflation projections model and its assessment in Latvia," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 21(2), pages 184-204.
  • Andrejs Bessonovs & Olegs Krasnopjorovs, 2020. "Short-Term Inflation Projections Model and Its Assessment in Latvia," Working Papers 2020/01, Latvijas Banka.
• Vahidin Jeleskovic & Mirko Meloni & Zahid Irshad Younas, 2020. "Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations," MAGKS Papers on Economics 202034, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• 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.
  • 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.
• Sadeghzadeh Yazdi, Ali & Abounoori, Esmaiel & Erfani, Alireza, 2020. "Forecasting Liquidity at Risk of a Private Bank Using the Parametric Approach (in Persian)," Journal of Monetary and Banking Research (فصلنامه پژوهش‌های پولی-بانکی), Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(44), pages 261-296, August.
• Sohrabi, Babak & Khalili Jafarabad, Ahmad & Hadizadeh, Ardalan, 2020. "Forecasting Stock Price Movements Based on Opinion Mining and Sentiment Analysis: An Application of Support Vector Machine and Twitter Data," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 15(3), pages 235-251, July.
• Ji Hyung Lee & Youngki Shin, 2020. "Complete Subset Averaging for Quantile Regressions," Papers 2003.03299, arXiv.org, revised Jul 2021.
  • Ji Hyung Lee & Youngki Shin, 2020. "Complete Subset Averaging for Quantile Regressions," Department of Economics Working Papers 2020-03, McMaster University.
• Evžen Kočenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Eastern European Economics, Taylor & Francis Journals, vol. 58(3), pages 197-220, May.
  • Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
  • Evzen Kocenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Working Papers IES 2020/5, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2020.
• Alexander Glas & Matthias Hartmann, 2020. "Uncertainty measures from partially rounded probabilistic forecast surveys," Working Papers 427, University of Milano-Bicocca, Department of Economics, revised Jan 2020.
• Pietro Battiston & Simona Gamba & Alessandro Santoro, 2020. "Optimizing Tax Administration Policies with Machine Learning," Working Papers 436, University of Milano-Bicocca, Department of Economics, revised Mar 2020.
• 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: $R_0$ is lower where outbreak is larger," Papers 2004.07827, arXiv.org.
  • Pietro Battiston & Simona Gamba, 2020. "COVID-19: R0 is lower where outbreak is larger," Working Papers 438, University of Milano-Bicocca, Department of Economics, revised Apr 2020.
• Escribano Saez, Alvaro & Wang, Dandan, 2020. "Forecasting gasoline prices with mixed random forest error correction models," UC3M Working papers. Economics 30557, Universidad Carlos III de Madrid. Departamento de Economía.
• Gonzalo, Jesús & Pitarakis, Jean-Yves, 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.
• Anibal Emiliano Da Silva Neto & Jesús Gonzalo & Jean‐Yves Pitarakis, 2021. "Uncovering Regimes in Out of Sample Forecast Errors from Predictive Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 713-741, June.
  • Da Silva Neto, Anibal Emiliano & Gonzalo, Jesús & Pitarakis, Jean-Yves, 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.
• Nieto Delfin, Maria Rosa & Ruiz Ortega, Esther, 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.
• Carlomagno Real, Guillermo & Espasa, Antoni, 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.
• Casas Villalba, Maria Isabel & Mao, Xiuping & Lopes Moreira Da Veiga, María Helena, 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.
  • Bekaert, Geert & Panayotov, George, 2019. "Good Carry, Bad Carry," CEPR Discussion Papers 13463, C.E.P.R. Discussion Papers.
  • Geert Bekaert & George Panayotov, 2019. "Good Carry, Bad Carry," NBER Working Papers 25420, National Bureau of Economic Research, Inc.
• 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.
  • 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.
• Galvão, Ana Beatriz & Lopresto, Marta, 2020. "Real-Time Probabilistic Nowcasts Of Uk Quarterly Gdp Growth Using A Mixed-Frequency Bottom-Up Approach," National Institute Economic Review, Cambridge University Press, vol. 254, pages 1-11, November.
  • Ana Beatriz Galvão & Marta Lopresto, 2020. "Real-time Probabilistic Nowcasts of UK Quarterly GDP Growth using a Mixed-Frequency Bottom-up Approach," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-06, Economic Statistics Centre of Excellence (ESCoE).
• 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.
• 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, revised Jun 2021.
• 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.
• Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
• Bańbura, Marta & Saiz, Lorena, 2020. "Short-term forecasting of euro area economic activity at the ECB," Economic Bulletin Articles, European Central Bank, vol. 2.
• 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, vol. 39(4), pages 1054-1065, October.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," CEPR Discussion Papers 14107, C.E.P.R. Discussion Papers.
  • Delle Monache, Davide & Venditti, Fabrizio & Petrella, Ivan, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Working Paper Series 2369, European Central Bank.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers) 1296, Bank of Italy, Economic Research and International Relations Area.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," EMF Research Papers 29, Economic Modelling and Forecasting Group.
• Meyler, Aidan, 2020. "Forecast performance in the ECB SPF: ability or chance?," Working Paper Series 2371, European Central Bank.
• McAdam, Peter & Warne, Anders, 2020. "Density forecast combinations: the real-time dimension," Working Paper Series 2378, European Central Bank.
• Barbara Jarmulska, 2022. "Random forest versus logit models: Which offers better early warning of fiscal stress?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 455-490, April.
  • Jarmulska, Barbara, 2020. "Random forest versus logit models: which offers better early warning of fiscal stress?," Working Paper Series 2408, European Central Bank.
• De Santis, Roberto A. & Van der Veken, Wouter, 2020. "Forecasting macroeconomic risk in real time: Great and Covid-19 Recessions," Working Paper Series 2436, European Central Bank.
• Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2020. "Nowcasting with large Bayesian vector autoregressions," Working Paper Series 2453, European Central Bank.
  • Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
• Quint, Dominic & Venditti, Fabrizio, 2020. "The influence of OPEC+ on oil prices: a quantitative assessment," Working Paper Series 2467, European Central Bank.
• Foroni, Claudia & Marcellino, Massimiliano & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
  • 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.
  • Claudia Foroni & Massimiliano Marcellino & Dalibor Stevanovic, 2020. "Forecasting the Covid-19 Recession and Recovery: Lessons from the Financial Crisis," CIRANO Working Papers 2020s-32, CIRANO.
• Falconio, Andrea & Manganelli, Simone, 2020. "Financial conditions, business cycle fluctuations and growth at risk," Working Paper Series 2470, European Central Bank.
• Bańbura, Marta & Bobeica, Elena, 2020. "Does the Phillips curve help to forecast euro area inflation?," Working Paper Series 2471, European Central Bank.
• Venditti, Fabrizio & Veronese, Giovanni, 2020. "Global financial markets and oil price shocks in real time," Working Paper Series 2472, European Central Bank.
• Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
• Chia-Cheng Chen & Chun-Hung Chen & Ting-Yin Liu, 2020. "Investment Performance of Machine Learning: Analysis of S&P 500 Index," International Journal of Economics and Financial Issues, Econjournals, vol. 10(1), pages 59-66.
• Hatice Erkekoglu & Aweng Peter Majok Garang & Adire Simon Deng, 2020. "Modeling and Forecasting USD/UGX Volatility through GARCH Family Models: Evidence from Gaussian, T and GED Distributions," International Journal of Economics and Financial Issues, Econjournals, vol. 10(2), pages 268-281.
• Rim Ammar Lamouchi, 2020. "Long Memory and Stock Market Efficiency: Case of Saudi Arabia," International Journal of Economics and Financial Issues, Econjournals, vol. 10(3), pages 29-34.
• Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
  • 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.
• Ana B. Galvão & Michael T. Owyang, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," Working Papers 2020-028, Federal Reserve Bank of St. Louis, revised 12 Oct 2021.
  • 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.
  • 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.
  • Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2021. "Testing the predictive accuracy of COVID-19 forecasts," CAMA Working Papers 2021-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• 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," Working Papers hal-03403077, HAL.
  • 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 and Book Chapters, 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.
• Seuffert, Stefan, 2020. "German Pension Simulation: Arbeitspapier zur Methodik eines anwartschaftsbasierten Projektionsmodells der gesetzlichen Rentenversicherung," FZG Discussion Papers 73, University of Freiburg, Research Center for Generational Contracts (FZG).
• Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jun 2021.
  • Dimitriadis, Timo & Patton, Andrew J. & Schmidt, Patrick W., 2020. "Testing forecast rationality for measures of central tendency," Hohenheim Discussion Papers in Business, Economics and Social Sciences 12-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
• Brighton, Henry, 2020. "Statistical foundations of ecological rationality," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), 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.
• Rialdi Azhar & Fajrin Satria Dwi Kesumah & Ambya Ambya & Febryan Kusuma Wisnu & Edwin Russel, 2020. "Application of Short-term Forecasting Models for Energy Entity Stock Price (Study on Indika Energi Tbk, JII)," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 294-301.
• Aderibigbe Israel Adekitan & Odunayo Salau, 2020. "The Significance of Stock Management to Jet Fuel Supply using Partial Least Squares," International Journal of Energy Economics and Policy, Econjournals, vol. 10(3), pages 389-395.
• Melina Dritsaki & Chaido Dritsaki, 2020. "Forecasting European Union CO2 Emissions Using Autoregressive Integrated Moving Average-autoregressive Conditional Heteroscedasticity Models," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 411-423.
• Sameer Al-Dahidi & Salah Al-Nazer & Osama Ayadi & Shuruq Shawish & Nahed Omran, 2020. "Analysis of the Effects of Cell Temperature on the Predictability of the Solar Photovoltaic Power Production," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 208-219.
• Toto Gunarto & Rialdi Azhar & Novita Tresiana & Supriyanto Supriyanto & Ayi Ahadiat, 2020. "Accurate Estimated Model of Volatility Crude Oil Price," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 228-233.
• Ambya Ambya & Toto Gunarto & Ernie Hendrawaty & Fajrin Satria Dwi Kesumah & Febryan Kusuma Wisnu, 2020. "Future Natural Gas Price Forecasting Model and Its Policy Implication," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 64-70.
• Heo, Wookjae & Lee, Jae Min & Park, Narang & Grable, John E., 2020. "Using Artificial Neural Network techniques to improve the description and prediction of household financial ratios," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
• Uddin, Ajim & Yu, Dantong, 2020. "Latent factor model for asset pricing," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
• Li, Jinjing & Wang, Xinmei & Xu, Jing & Yuan, Chang, 2020. "The role of public pensions in income inequality among elderly households in China 1988–2013," China Economic Review, Elsevier, vol. 61(C).
  • Li, Jinjing & Wang, Xinmei & Yuan, Chang & Xu, Jing, 2018. "The Role of Public Pensions in Income Inequality among Elderly Households in China 1988–2013," CIS Discussion paper series 674, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
• Yan, Ruzhen & Yue, Ding & Chen, Xudong & Wu, Xu, 2020. "Non-linear characterization and trend identification of liquidity in China's new OTC stock market based on multifractal detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
• Yuan, Ying & Zhang, Tonghui, 2020. "Forecasting stock market in high and low volatility periods: a modified multifractal volatility approach," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
• Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
  • Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2019. "Exploiting ergodicity in forecasts of corporate profitability," BERG Working Paper Series 147, Bamberg University, Bamberg Economic Research Group.
• Dur, Ayşe & Martínez García, Enrique, 2020. "Mind the gap!—A monetarist view of the open-economy Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
  • Ayse Dur & Enrique Martinez-Garcia, 2020. "Mind the Gap!—A Monetarist View of the Open-Economy Phillips Curve," Globalization Institute Working Papers 392, Federal Reserve Bank of Dallas.
• Pham, Manh Cuong & Anderson, Heather Margot & Duong, Huu Nhan & Lajbcygier, Paul, 2020. "The effects of trade size and market depth on immediate price impact in a limit order book market," Journal of Economic Dynamics and Control, Elsevier, vol. 120(C).
• Li, Hong, 2020. "Volatility spillovers across European stock markets under the uncertainty of Brexit," Economic Modelling, Elsevier, vol. 84(C), pages 1-12.
• Wang, Yajing & Liang, Fang & Wang, Tianyi & Huang, Zhuo, 2020. "Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market," Economic Modelling, Elsevier, vol. 87(C), pages 148-157.
• McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
  • Stephen McKnight & Alexander Mihailov & Kerry Patterson & Fabio Rumler, 2014. "The Predictive Performance of Fundamental Inflation Concepts: An Application to the Euro Area and the United States," Economics Discussion Papers em-dp2014-03, Department of Economics, University of Reading.
  • Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
• Jahn, Malte, 2020. "Artificial neural network regression models in a panel setting: Predicting economic growth," Economic Modelling, Elsevier, vol. 91(C), pages 148-154.
• Qiu, Yue, 2020. "Forecasting the Consumer Confidence Index with tree-based MIDAS regressions," Economic Modelling, Elsevier, vol. 91(C), pages 247-256.
• Benchimol, Jonathan & El-Shagi, Makram, 2020. "Forecast performance in times terrorism," Economic Modelling, Elsevier, vol. 91(C), pages 386-402.
  • Jonathan Benchimol & Makram El-Shagi, 2017. "Forecast Performance in Times of Terrorism," CFDS Discussion Paper Series 2017/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
  • Jonathan Benchimol & Makram El-Shagi, 2020. "Forecast Performance in Times of Terrorism," Globalization Institute Working Papers 390, Federal Reserve Bank of Dallas.
  • Jonathan Benchimol & Makram El-Shagi, 2019. "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers 2019.08, Bank of Israel.
  • Jonathan Benchimol & Makram El-Shagi, 2020. "Forecast performance in times of terrorism," Post-Print halshs-03248938, HAL.
• Xu, Yahua & Xiao, Jun & Zhang, Liguo, 2020. "Global predictive power of the upside and downside variances of the U.S. equity market," Economic Modelling, Elsevier, vol. 93(C), pages 605-619.
• Liang, Chao & Ma, Feng & Li, Ziyang & Li, Yan, 2020. "Which types of commodity price information are more useful for predicting US stock market volatility?," Economic Modelling, Elsevier, vol. 93(C), pages 642-650.
• Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
• Díaz-Mendoza, Ana-Carmen & Pardo, Angel, 2020. "Holidays, weekends and range-based volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
• Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
• Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2020. "Improving the realized GARCH’s volatility forecast for Bitcoin with jump-robust estimators," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
• Dai, Zhifeng & Zhou, Huiting & Wen, Fenghua & He, Shaoyi, 2020. "Efficient predictability of stock return volatility: The role of stock market implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
• Choe, Geon Ho & Choi, So Eun & Jang, Hyun Jin, 2020. "Assessment of time-varying systemic risk in credit default swap indices: Simultaneity and contagiousness," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
• Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
• Gupta, Rangan & Sun, Xiaojin, 2020. "Forecasting economic policy uncertainty of BRIC countries using Bayesian VARs," Economics Letters, Elsevier, vol. 186(C).
• Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2020. "Computationally efficient inference in large Bayesian mixed frequency VARs," Economics Letters, Elsevier, vol. 191(C).
  • Deborah Gefang & Gary Koop & Aubrey Poon, "undated". "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Discussion Papers in Economics 20/02, Division of Economics, School of Business, University of Leicester.
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
• Lahiri, Kajal & Zhao, Yongchen, 2020. "The Nordhaus test with many zeros," Economics Letters, Elsevier, vol. 193(C).
  • Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," Working Papers 2020-05, Towson University, Department of Economics, revised Jun 2020.
  • Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," CESifo Working Paper Series 8350, CESifo.
• Huh, Sungjun & Kim, Insu, 2020. "Growth forecast revisions over business cycles: Evidence from the Survey of Professional Forecasters," Economics Letters, Elsevier, vol. 196(C).
• Nonejad, Nima, 2020. "An observation regarding Hamilton’s recent criticisms of Kilian’s global real economic activity index," Economics Letters, Elsevier, vol. 196(C).
• Tu, Yundong & Wang, Siwei, 2020. "Jackknife model averaging for expectile regressions in increasing dimension," Economics Letters, Elsevier, vol. 197(C).
• Holt, Matthew T. & Teräsvirta, Timo, 2020. "Global hemispheric temperatures and co-shifting: A vector shifting-mean autoregressive analysis," Journal of Econometrics, Elsevier, vol. 214(1), pages 198-215.
  • Matthew T. Holt & Timo Teräsvirta, 2017. "Global Hemispheric Temperatures and Co–Shifting: A Vector Shifting–Mean Autoregressive Analysis," CREATES Research Papers 2017-05, Department of Economics and Business Economics, Aarhus University.
• Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
• Arcidiacono, Peter & Miller, Robert A., 2020. "Identifying dynamic discrete choice models off short panels," Journal of Econometrics, Elsevier, vol. 215(2), pages 473-485.
• Borowska, Agnieszka & Hoogerheide, Lennart & Koopman, Siem Jan & van Dijk, Herman K., 2020. "Partially censored posterior for robust and efficient risk evaluation," Journal of Econometrics, Elsevier, vol. 217(2), pages 335-355.
  • Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
  • Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman K. van Dijk, 2019. "Partially Censored Posterior for robust and efficient risk evaluation," Working Paper 2019/12, Norges Bank.
• Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
• Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
• Gonçalves, Sílvia & Perron, Benoit, 2020. "Bootstrapping factor models with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 218(2), pages 476-495.
  • Sílvia GONÇALVES & Benoit PERRON, 2018. "Bootstrapping Factor Models With Cross Sectional Dependence," Cahiers de recherche 10-2018, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  • GONÇALVES, Sílvia & PERRON, Benoit, 2018. "Bootstrapping factor models with cross sectional dependence," Cahiers de recherche 2018-07, Universite de Montreal, Departement de sciences economiques.
• Nevrla, Matěj, 2020. "Systemic risk in European financial and energy sectors: Dynamic factor copula approach," Economic Systems, Elsevier, vol. 44(4).
• Chu, Amanda M.Y. & Lv, Zhihui & Wagner, Niklas F. & Wong, Wing-Keung, 2020. "Linear and nonlinear growth determinants: The case of Mongolia and its connection to China," Emerging Markets Review, Elsevier, vol. 43(C).
  • Chu, Amanda M.Y. & Lv, Zhihui & Wagner, Niklas F. & Wong, Wing-Keung, 2020. "Linear and Nonlinear Growth Determinants: The Case of Mongolia and its Connection to China," MPRA Paper 99185, University Library of Munich, Germany.
• Nguyen, Linh Hoang & Chevapatrakul, Thanaset & Yao, Kai, 2020. "Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 333-355.
• 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.
  • Tong Fang & Tae-Hwy Lee & Zhi Su, 2020. "Predicting the Long-term Stock Market Volatility: A GARCH-MIDAS Model with Variable Selection," Working Papers 202009, University of California at Riverside, Department of Economics.
• Reschenhofer, Erhard & Mangat, Manveer Kaur & Stark, Thomas, 2020. "Volatility forecasts, proxies and loss functions," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 133-153.
• Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
• Bissoondoyal-Bheenick, Emawtee & Brooks, Robert & Do, Hung Xuan & Smyth, Russell, 2020. "Exploiting the heteroskedasticity in measurement error to improve volatility predictions in oil and biofuel feedstock markets," Energy Economics, Elsevier, vol. 86(C).
• Lu, Quanying & Li, Yuze & Chai, Jian & Wang, Shouyang, 2020. "Crude oil price analysis and forecasting: A perspective of “new triangle”," Energy Economics, Elsevier, vol. 87(C).
• Wang, Jiqian & Huang, Yisu & Ma, Feng & Chevallier, Julien, 2020. "Does high-frequency crude oil futures data contain useful information for predicting volatility in the US stock market? New evidence," Energy Economics, Elsevier, vol. 91(C).
• Trespalacios, Alfredo & Cortés, Lina M. & Perote, Javier, 2020. "Uncertainty in electricity markets from a semi-nonparametric approach," Energy Policy, Elsevier, vol. 137(C).
  • Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2019. "Uncertainty in Electricity Markets from a seminonparametric Approach," Documentos de Trabajo CIEF 017304, Universidad EAFIT.
• Belbute, José M. & Pereira, Alfredo M., 2020. "Reference forecasts for CO2 emissions from fossil-fuel combustion and cement production in Portugal," Energy Policy, Elsevier, vol. 144(C).
  • José M. Belbute & Alfredo M. Pereira, 2019. "Reference Forecasts for CO2 Emissions from Fossil-Fuel Combustion and Cement Production in Portugal," GEE Papers 00126, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Aug 2019.
• Jasiński, Tomasz, 2020. "Use of new variables based on air temperature for forecasting day-ahead spot electricity prices using deep neural networks: A new approach," Energy, Elsevier, vol. 213(C).
• Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
• Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
• Fang, Tong & Su, Zhi & Yin, Libo, 2020. "Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility," International Review of Financial Analysis, Elsevier, vol. 71(C).
• Alejandra Lelo-de-Larrea, 2020. "Forecast Comparison of the Term Structure of Interest Rates of Mexico for Different Specifications of the Affine Model," Working Papers 2020-01, 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.
  • Juan R. Hernández, 2020. "Covered Interest Parity: A Stochastic Volatility Approach to Estimate the Neutral Band," Working Papers 2020-02, Banco de México.
• Guillermo Benavides, 2020. "Asymmetric Volatility Effects in Risk Management: An Empirical Analysis using a Stock Index Futures," Working Papers 2020-10, Banco de México.
• Ana Aguilar-Argaez & María Diego-Fernández & Rocío Elizondo & Jessica Roldán-Peña, 2020. "Term Premium Dynamics and its Determinants: The Mexican Case," Working Papers 2020-18, Banco de México.
• Valeria Bejarano-Salcedo & Juan Manuel Julio-Román & Edgar Caicedo-García & Julián Alonso Cárdenas-Cárdenas, 2020. "Entendiendo, Modelando y Pronosticando el Efecto de “El Niño” Sobre los Precios de los Alimentos: El Caso Colombiano," Borradores de Economia 1102, Banco de la Republica de Colombia.
• Julián Alonso Cárdenas-Cárdenas & Edgar Caicedo-García & Eliana R. González Molano, 2020. "Estimación de la variación del precio de los alimentos con modelos de frecuencias mixtas," Borradores de Economia 1109, Banco de la Republica de Colombia.
• Sergio Restrepo-Ángel & Hernán Rincón-Castro & Juan J. Ospina-Tejeiro, 2020. "Multiplicadores de los impuestos y del gasto público en Colombia: aproximaciones SVAR y proyecciones locales," Borradores de Economia 1114, Banco de la Republica de Colombia.
• Jardet Caroline & Meunier Baptiste, 2020. "Nowcasting World GDP Growth with High-Frequency Data," Working papers 788, Banque de France.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: obtaining measures of multi-horizon uncertainty from survey density forecasts," Working Papers 1947, Banco de España.
  • Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2020. "From Fixed-Event to Fixed-Horizon Density Forecasts: Obtaining Measures of Multi-Horizon Uncertainty from Survey Density Forecasts," Working Papers 1142, Barcelona Graduate School of Economics.
  • Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
  • Ganics, Gergely & Rossi, Barbara & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Forecasts," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
• 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.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Papers 1158, Barcelona Graduate School of Economics.
  • Hoesch, Lukas & Rossi, Barbara & Sekhposyan, Tatevik, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," CEPR Discussion Papers 14456, C.E.P.R. Discussion Papers.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the information channel of monetary policy disappeared? Revisiting the empirical evidence," Economics Working Papers 1701, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
• Baranowski Paweł & Korczak Karol & Zając Jarosław, 2020. "Forecasting Cinema Attendance at the Movie Show Level: Evidence from Poland," Business Systems Research, Sciendo, vol. 11(1), pages 73-88, March.
• Ferencek Aljaž & Kofjač Davorin & Škraba Andrej & Sašek Blaž & Borštnar Mirjana Kljajić, 2020. "Deep Learning Predictive Models for Terminal Call Rate Prediction during the Warranty Period," Business Systems Research, Sciendo, vol. 11(2), pages 36-50, October.
• Mikhail Gareev, 2020. "Use of Machine Learning Methods to Forecast Investment in Russia," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 35-56, March.
• Evgeny Pavlov, 2020. "Forecasting Inflation in Russia Using Neural Networks," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 57-73, March.
• Vladimir Boyko & Nadezhda Kislyak & Mikhail Nikitin & Oleg Oborin, 2020. "Methods for Estimating the Gross Regional Product Leading Indicator," Russian Journal of Money and Finance, Bank of Russia, vol. 79(3), pages 3-29, September.
• Aleksey Ponomarenko & Svetlana Popova & Andrey Sinyakov & Natalia Turdyeva & Dmitry Chernyadyev, 2020. "Assessing the Consequences of the Pandemic for the Russian Economy Through an Input-Output Model," Russian Journal of Money and Finance, Bank of Russia, vol. 79(4), pages 3-17, December.
• Michael Brei & Claudio Borio & Leonardo Gambacorta, 2020. "Bank intermediation activity in a low‐interest‐rate environment," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 49(2), July.
  • Borio, Claudio & Brei, Michael & Gambacorta, Leonardo, 2019. "Bank intermediation activity in a low interest rate environment," CEPR Discussion Papers 13980, C.E.P.R. Discussion Papers.
  • Michael Brei & Claudio Borio, 2019. "Bank intermediation activity in a low interest rate environment," BIS Working Papers 807, Bank for International Settlements.
  • Michael Brei & Claudio Borio & Leonardo Gambacorta, 2020. "Bank intermediation activity in a low‐interest‐rate environment," Post-Print hal-02985986, HAL.
• 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.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020. "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 285-310, April.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh K. Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Papers No 8/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017. "Do central banks respond timely to developments in the global economy?," CAMA Working Papers 2017-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Paper 2016/19, Norges Bank.
• Ferdinand Dreher & Johannes Gräb & Thomas Kostka, 2020. "From carry trades to curvy trades," The World Economy, Wiley Blackwell, vol. 43(3), pages 758-780, March.
  • Dreher, Ferdinand & Gräb, Johannes & Kostka, Thomas, 2018. "From carry trades to curvy trades," Working Paper Series 2149, European Central Bank.
• BRAILA Alexandru & TOACA Zinovia, 2020. "Identification Of The Production Function By The Form Of The Marginal Characteristics, The Marginal Substitution Rate, The Elasticities And The Cost Function," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 72(3), pages 8-18, November.
• Jonnathan R. Cáceres Santos, 2020. "Modelos de Machine Learning para el análisis y pronóstico de la situación financiera de bancos – Caso boliviano," Revista de Análisis del BCB, Banco Central de Bolivia, vol. 33(1), pages 69-91, July - De.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Paper 2020/14, Norges Bank.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Papers No 08/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
• Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate Risk and Commodity Currencies," Working Papers No 10/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate risk and commodity currencies," Working Paper 2020/18, Norges Bank.
  • Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate Risk and Commodity Currencies," CESifo Working Paper Series 8788, CESifo.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Papers No 08/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Paper 2020/14, Norges Bank.
• Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate risk and commodity currencies," Working Paper 2020/18, Norges Bank.
  • Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate Risk and Commodity Currencies," Working Papers No 10/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate Risk and Commodity Currencies," CESifo Working Paper Series 8788, CESifo.
• Hilde Christiane Bjørnland & Roberto Casarin & Marco Lorusso & Francesco Ravazzolo, 2020. "Oil and Fiscal Policy Regimes," Working Papers No 11/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjørnland & Roberto Casarin & Marco Lorusso & Francesco Ravazzolo, 2021. "Oil and fiscal policy regimes," CAMA Working Papers 2021-10, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kang, Miao & Kapadia, Sujit & Simsek, Özgür, 2020. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Bank of England working papers 848, Bank of England.
  • Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kapadia, Sujit & Şimşek, Özgür, 2021. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Working Paper Series 2614, European Central Bank.
• 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.
  • 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.
• Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2020. "Do Expert Experience and Characteristics Affect Inflation Forecasts?," CFDS Discussion Paper Series 2020/6, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
  • Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2020. "Do Expert Experience and Characteristics Affect Inflation Forecasts?," Bank of Israel Working Papers 2020.11, Bank of Israel.
• Hyeongwoo Kim & Soohyon Kim, 2020. "Common Factor Augmented Forecasting Models for the US Dollar-Korean Won Exchange Rate," Working Papers 2020-5, Economic Research Institute, Bank of Korea.
• Nam Gang Lee, 2020. "Vulnerable Growth: A Revisit," Working Papers 2020-22, Economic Research Institute, Bank of Korea.
• Pierdzioch Christian & Gupta Rangan, 2020. "Uncertainty and Forecasts of U.S. Recessions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-20, September.
  • Christian Pierdzioch & Rangan Gupta, 2017. "Uncertainty and Forecasts of U.S. Recessions," Working Papers 201732, University of Pretoria, Department of Economics.
• Funke Michael & Loermann Julius & Moessner Richhild, 2020. "The discontinuation of the EUR/CHF minimum exchange rate: information from option-implied break probabilities," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(3), pages 63-79, June.
• Rutzer, Christian & Niggli, Matthias & Weder, Rolf, 2020. "Estimating the Green Potential of Occupations: A New Approach Applied to the U.S. Labor Market," Working papers 2020/03, Faculty of Business and Economics - University of Basel.
• Lake, A., 2020. "Optimal Feasible Expectations in Economics and Finance," Cambridge Working Papers in Economics 20105, Faculty of Economics, University of Cambridge.
• Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
• 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., 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, 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.
  • 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.
• Rashad Ahmed & M. Hashem Pesaran, 2020. "Regional Heterogeneity and U.S. Presidential Elections," CESifo Working Paper Series 8615, CESifo.
  • Ahmed, R. & Pesaran, M. H., 2020. "Regional Heterogeneity and U.S. Presidential Elections," Cambridge Working Papers in Economics 2092, Faculty of Economics, University of Cambridge.
• Ba Chu & Shafiullah Qureshi, 2020. "Predicting the COVID-19 Pandemic in Canada and the US," Carleton Economic Papers 20-05, Carleton University, Department of Economics, revised 30 Jul 2020.
• Congressional Budget Office, 2020. "The Accuracy of CBO’s Budget Projections for Fiscal Year 2020," Reports 56885, Congressional Budget Office.
• 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.
  • Carlo Pizzinelli & Konstantinos Theodoridis & Francesco Zanetti, 2020. "State dependence in labour market fluctuations," Working Papers 47, European Stability Mechanism.
  • 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.
• Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
  • Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Domenico Sartore, 2018. "A scoring rule for factor and autoregressive models under misspecification," Working Papers 2018:18, Department of Economics, University of Venice "Ca' Foscari".
• Daniel Borup & Bent Jesper Christensen & Nicolaj N{o}rgaard Muhlbach & Mikkel Slot Nielsen, 2020. "Targeting predictors in random forest regression," Papers 2004.01411, arXiv.org, revised Nov 2020.
  • Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
• Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2020. "A statistical model of the global carbon budget," CREATES Research Papers 2020-18, Department of Economics and Business Economics, Aarhus University.
• Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2020. "Forecasting the US Dollar-Korean Won Exchange Rate: A Factor-Augmented Model Approach," Auburn Economics Working Paper Series auwp2020-02, Department of Economics, Auburn University.
• 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.
  • 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.
  • Anderson, Kym & Wittwer, Glyn, 2020. "A Model of Global Beverage Markets," CEPR Discussion Papers 14387, C.E.P.R. Discussion Papers.
• Teboho Jeremiah Mosikari & Joel Hinaunye Eita, 2020. "Modelling Asymmetric Relationship between Exports and Growth in a Developing Economy: Evidence from Namibia," Economic Development and Well-being Research Group Working Paper Series edwrg-02-2020, University of Johannesburg, College of Business and Economics, revised 2020.
• Pedro Bordalo & Nicola Gennaioli & Yueran Ma & Andrei Shleifer, 2020. "Overreaction in Macroeconomic Expectations," American Economic Review, American Economic Association, vol. 110(9), pages 2748-2782, September.
  • Pedro Bordalo & Nicola Gennaioli & Yueran Ma & Andrei Shleifer, 2018. "Over-reaction in Macroeconomic Expectations," NBER Working Papers 24932, National Bureau of Economic Research, Inc.
• Raffaella Giacomini & Vasiliki Skreta & Javier Turen, 2020. "Heterogeneity, Inattention, and Bayesian Updates," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(1), pages 282-309, January.
• Stefano DellaVigna & Nicholas Otis & Eva Vivalt, 2020. "Forecasting the Results of Experiments: Piloting an Elicitation Strategy," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 75-79, May.
  • Stefano DellaVigna & Nicholas Otis & Eva Vivalt, 2020. "Forecasting the Results of Experiments: Piloting an Elicitation Strategy," NBER Working Papers 26716, National Bureau of Economic Research, Inc.
• Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020. "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers 4304, Asociación Argentina de Economía Política.
• J. Daniel Aromí & Martín Llada, 2020. "Forecasting inflation with twitter," Asociación Argentina de Economía Política: Working Papers 4308, Asociación Argentina de Economía Política.
• Emilio Blanco & Laura D’Amato & Fiorella Dogliolo & Lorena Garegnani, 2020. "Nowcasting Macroeconomic Aggregates in Argentina: Comparing the predictive ability of different models," Asociación Argentina de Economía Política: Working Papers 4335, Asociación Argentina de Economía Política.
• 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.
• Tamar Mdivnishvili & Shalva Mkhatrishvili & Davit Tutberidze, 2020. "Cash Flow at Risk Assessment for the Banking Sector of Georgia," NBG Working Papers 03/2020, National Bank of Georgia.
• Olivier DAMETTE & Claude DIEBOLT & Stephane GOUTTE & Umberto TRIACCA, 2020. "Cliometrics of Climate Change: A Natural Experiment on the Little Ice Age," Working Papers of BETA 2020-20, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
  • Olivier Damette & Claude Diebolt & Stephane Goutte & Umberto Triacca, 2020. "Cliometrics of Climate Change: A Natural Experiment on the Little Ice Age," Working Papers 02-20, Association Française de Cliométrie (AFC).
• Enrico D’Elia & Francesca Faedda & Giacomo Giannone, 2020. "Un modello statistico per il monitoraggio delle entrate tributarie (MoME)," Working Papers wp2020-5, Ministry of Economy and Finance, Department of Finance.
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, vol. 13(7), pages 1-16, April.
  • Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2020. "Beating the naive: Combining LASSO with naive intraday electricity price forecasts," WORking papers in Management Science (WORMS) WORMS/20/01, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices," Energies, MDPI, vol. 13(14), pages 1-19, July.
  • Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Tao Hong & Pierre Pinson & Yi Wang & Rafal Weron & Dazhi Yang & Hamidreza Zareipour, 2020. "Energy forecasting: A review and outlook," WORking papers in Management Science (WORMS) WORMS/20/08, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Tomasz Serafin & Grzegorz Marcjasz & Rafal Weron, 2020. "Trading on short-term path forecasts of intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/17, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore & Wing-Keung Wong, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
  • Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore & Wing-Keung Wong, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," International Association of Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
  • Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Domenico Sartore, 2018. "A scoring rule for factor and autoregressive models under misspecification," Working Papers 2018:18, Department of Economics, University of Venice "Ca' Foscari".
• Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020. "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series 2020-04, Monash University, SoDa Laboratories.
• Oscar Claveria & Ivana Lolic & Enric Monte & Petar Soric, 2020. "Economic determinants of employment sentiment: A socio-demographic analysis for the euro area," IREA Working Papers 202001, University of Barcelona, Research Institute of Applied Economics, revised Jan 2020.
  • Oscar Claveria & Ivana Lolic & Enric Monte & Salvador Torra & Petar Soric, 2020. "“Economic determinants of employment sentiment: A socio-demographic analysis for the euro area”," AQR Working Papers 2012001, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2020.
• Ji Hyung Lee & Youngki Shin, 2020. "Complete Subset Averaging for Quantile Regressions," Department of Economics Working Papers 2020-03, McMaster University.
  • Ji Hyung Lee & Youngki Shin, 2020. "Complete Subset Averaging for Quantile Regressions," Papers 2003.03299, arXiv.org, revised Jul 2021.
• Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
  • Daniel Borup & Bent Jesper Christensen & Nicolaj N{o}rgaard Muhlbach & Mikkel Slot Nielsen, 2020. "Targeting predictors in random forest regression," Papers 2004.01411, arXiv.org, revised Nov 2020.
• Pietro Battiston & Simona Gamba, 2020. "COVID-19: R0 is lower where outbreak is larger," Working Papers 438, University of Milano-Bicocca, Department of Economics, revised Apr 2020.
  • Pietro Battiston & Simona Gamba, 2020. "COVID-19: $R_0$ is lower where outbreak is larger," Papers 2004.07827, arXiv.org.
• Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019_07, Business School - Economics, University of Glasgow.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
• Fabrizio Cipollini & Giampiero Gallo & Alessandro Palandri, 2020. "A Dynamic Conditional Approach to Portfolio Weights Forecasting," Econometrics Working Papers Archive 2020_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  • Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
• Andreas Dibiasi & Samad Sarferaz, 2020. "Measuring Macroeconomic Uncertainty: The Labor Channel of Uncertainty from a Cross-Country Perspective," Papers 2006.09007, arXiv.org, revised Dec 2020.
• Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2020. "A Model of the Fed's View on Inflation," Papers 2006.14110, arXiv.org.
  • Thomas Hasenzagl & Fillipo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of the FED's view on inflation," Working Papers hal-03458456, HAL.
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2018. "A Model of the Fed's View on Inflation," CEPR Discussion Papers 12564, C.E.P.R. Discussion Papers.
  • Thomas Hasenzagl & Fillipo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of the FED's view on inflation," Sciences Po publications 03, Sciences Po.
  • Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of FED'S view on inflation," Documents de Travail de l'OFCE 2018-03, Observatoire Francais des Conjonctures Economiques (OFCE).
  • Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," Economic Research Papers 269087, University of Warwick - Department of Economics.
• 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," Papers 2007.00273, arXiv.org, revised Jun 2021.
  • 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," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
• Dalibor Stevanovic & Stéphane Surprenant & Philippe Goulet Coulombe, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
• 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.
  • 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.
• Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," CERGE-EI Working Papers wp677, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  • Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," Papers 2009.03394, arXiv.org, revised Jul 2021.
• Martin, Gael M. & Loaiza-Maya, Rubén & Maneesoonthorn, Worapree & Frazier, David T. & Ramírez-Hassan, Andrés, 2022. "Optimal probabilistic forecasts: When do they work?," International Journal of Forecasting, Elsevier, vol. 38(1), pages 384-406.
  • Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
  • Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
• 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.
  • Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Robust Forecasting," Papers 2011.03153, arXiv.org, revised Dec 2020.
• Oren Barkan & Jonathan Benchimol & Itamar Caspi & Eliya Cohen & Allon Hammer & Noam Koenigstein, 2020. "Forecasting CPI Inflation Components with Hierarchical Recurrent Neural Networks," Papers 2011.07920, arXiv.org, revised Feb 2022.
  • Oren Barkan & Jonathan Benchimol & Itamar Caspi & Allon Hammer & Noam Koenigstein, 2021. "Forecasting CPI Inflation Components with Hierarchical Recurrent Neural Network," Bank of Israel Working Papers 2021.06, Bank of Israel.
• Dario Sansone & Anna Zhu, 2020. "Using Machine Learning to Create an Early Warning System for Welfare Recipients," Papers 2011.12057, arXiv.org, revised May 2021.
  • Sansone, Dario & Zhu, Anna, 2021. "Using Machine Learning to Create an Early Warning System for Welfare Recipients," IZA Discussion Papers 14377, Institute of Labor Economics (IZA).
• Olkhov, Victor, 2020. "Business Cycles as Collective Risk Fluctuations," MPRA Paper 104598, University Library of Munich, Germany.
  • Victor Olkhov, 2020. "Business Cycles as Collective Risk Fluctuations," Papers 2012.04506, arXiv.org.
• Ricardo Cris'ostomo, 2020. "Estimating real-world probabilities: A forward-looking behavioral framework," Papers 2012.09041, arXiv.org, revised Jan 2021.
  • Ricardo Crisóstomo, 2021. "Estimating real word probabilities: a forward-looking behavioral framework," CNMV Working Papers CNMV Working Papers no. 7, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
• Monica Billio & Roberto Casarin & Enrica De Cian & Malcolm Mistry & Anthony Osuntuyi, 2020. "The impact of Climate on Economic and Financial Cycles: A Markov-switching Panel Approach," Papers 2012.14693, arXiv.org.
  • 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 2021:03, Department of Economics, University of Venice "Ca' Foscari".
• Fatemi Ardestani, Seyed Farshad & Barakchian, Seyed Mahdi & Shokoohian, Hamideh, 2020. "Short-term Forecast of Hourly Electricity Demand in Iran Using a Forecast Combination Method (in Persian)," The Journal of Planning and Budgeting (فصلنامه برنامه ریزی و بودجه), Institute for Management and Planning studies, vol. 24(4), pages 57-73, February.
• Guidolin, Massimo & Pedio, Manuela, 2021. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," Finance Research Letters, Elsevier, vol. 42(C).
  • Massimo Guidolin & Manuela Pedio, 2020. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," BAFFI CAREFIN Working Papers 20145, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Massimo Guidolin & Alexei Orlov, 2020. "Are Unconventional Monetary Policies a Priced Risk Factor for Hedge Fund Strategies?," BAFFI CAREFIN Working Papers 20146, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Olga Palamarchuk, 2020. "The Use Of Fuzzy Logic While Modeling The Creditworthiness Of Legal Entities," Green, Blue & Digital Economy Journal, Publishing house "Baltija Publishing", vol. 1(2).
• Olga Palamarchuk, 2020. "The Use Of Fuzzy Logic While Modeling The Creditworthiness Of Legal Entities," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 1(2).
• Nataliya Vnukova & Sergii Kavun & Oleh Kolodiziev & Svitlana Achkasova & Daria Hontar, 2020. "Indicators-Markers for Assessment of Probability of Insurance Companies Relatedness in Implementation of Risk-Oriented Approach," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 151-173.
• Anton Gerunov, 2020. "Classification algorithms for modeling economic choice," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 45-67.
• Ionut Laurentiu Gavris & Valentin Toader, 2020. "Romania’S Long-Term Growth Perspectives," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
• Jinyue Dong, 2020. "Modelo de predicción de la inflación en China [China | Forecasting modeling for China\'s inflation]," Working Papers 20/05, BBVA Bank, Economic Research Department.
• Félix Lores & Pep Ruiz & Angie Suárez & Alfonso Ugarte, 2020. "España | Modelo de precios de la vivienda. Una perspectiva regional [Spain | Model for housing prices. A regional perspective]," Working Papers 20/12, BBVA Bank, Economic Research Department.
• Amor Aniss Benmoussa & Reinhard Ellwanger & Stephen Snudden, 2020. "The New Benchmark for Forecasts of the Real Price of Crude Oil," Staff Working Papers 20-39, Bank of Canada.
• Necmettin Alpay KOCAK, 2020. "Are CBRT’s Monetary Policy Statements Affected by ECB and FED Statements?," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 14(2), pages 205-226.
• Banco de España, 2020. "Escenarios macroeconómicos de referencia para la economía española tras el Covid-19," Boletín Económico, Banco de España, issue 2/2020, pages 1-35.
• Pablo Aguilar, 2020. "La persistencia de la inflación en el área del euro: el papel de las expectativas," Boletín Económico, Banco de España, issue 4/2020, pages 1-11.
• Banco de España, 2020. "Reference macroeconomic scenarios for the Spanish economy after Covid-19," Economic Bulletin, Banco de España, issue 2/2020, pages 1-32.
• Pablo Aguilar, 2020. "Inflation persistence in the euro area: the role of expectations," Economic Bulletin, Banco de España, issue 4/2020, pages 1-10.
• Eduardo Gutiérrez & Enrique Moral-Benito, 2020. "Medidas de contención, evolución del empleo y propagación del Covid-19 en los municipios españoles," Occasional Papers 2022, Banco de España.
• Eduardo Gutiérrez & Enrique Moral-Benito, 2020. "Containment measures, employment and the spread of COVID-19 in Spanish municipalities," Occasional Papers 2022, Banco de España.
• Mar Delgado-Téllez & Esther Gordo & Iván Kataryniuk & Javier J. Pérez, 2022. "The decline in public investment: ``social dominance’’ or too-rigid fiscal rules?," Applied Economics, Taylor & Francis Journals, vol. 54(10), pages 1123-1136, February.
  • Mar Delgado-Téllez & Esther Gordo & Iván Kataryniuk & Javier J. Pérez, 2020. "The decline in public investment: “social dominance” or too-rigid fiscal rules?," Working Papers 2025, Banco de España.
• 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.
• Andrés Alonso & José Manuel Carbó, 2020. "Machine learning in credit risk: measuring the dilemma between prediction and supervisory cost," Working Papers 2032, Banco de España.
• Nélida Díaz Sobrino & Corinna Ghirelli & Samuel Hurtado & Javier J. Pérez & Alberto Urtasun, 2020. "The narrative about the economy as a shadow forecast: an analysis using Banco de España quarterly reports," Working Papers 2042, Banco de España.
• Ivan Faiella & Alessandro Mistretta, 2020. "Energy costs and competitiveness in Europe," Temi di discussione (Economic working papers) 1259, Bank of Italy, Economic Research and International Relations Area.
• Busetti, Fabio & Caivano, Michele & Delle Monache, Davide & Pacella, Claudia, 2021. "The time-varying risk of Italian GDP," Economic Modelling, Elsevier, vol. 101(C).
  • Fabio Busetti & Michele Caivano & Davide Delle Monache & Claudia Pacella, 2020. "The time-varying risk of Italian GDP," Temi di discussione (Economic working papers) 1288, Bank of Italy, Economic Research and International Relations Area.
• 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, vol. 39(4), pages 1054-1065, October.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," CEPR Discussion Papers 14107, C.E.P.R. Discussion Papers.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers) 1296, Bank of Italy, Economic Research and International Relations Area.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," EMF Research Papers 29, Economic Modelling and Forecasting Group.
  • Delle Monache, Davide & Venditti, Fabrizio & Petrella, Ivan, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Working Paper Series 2369, European Central Bank.
• Jackson, Emerson Abraham, 2020. "Understanding SLL / US$ exchange rate dynamics in Sierra Leone using Box-Jenkins ARIMA approach," MPRA Paper 97965, University Library of Munich, Germany, revised 03 Jan 2020.
• Cerulli, Giovanni, 2020. "A Super-Learning Machine for Predicting Economic Outcomes," MPRA Paper 99111, University Library of Munich, Germany.
• Adeniyi, Isaac Adeola & Yahya, Waheed Babatunde, 2020. "Bayesian Generalized Linear Mixed Effects Models Using Normal-Independent Distributions: Formulation and Applications," MPRA Paper 99165, University Library of Munich, Germany.
• Chu, Amanda M.Y. & Lv, Zhihui & Wagner, Niklas F. & Wong, Wing-Keung, 2020. "Linear and nonlinear growth determinants: The case of Mongolia and its connection to China," Emerging Markets Review, Elsevier, vol. 43(C).
  • Chu, Amanda M.Y. & Lv, Zhihui & Wagner, Niklas F. & Wong, Wing-Keung, 2020. "Linear and Nonlinear Growth Determinants: The Case of Mongolia and its Connection to China," MPRA Paper 99185, University Library of Munich, Germany.
• Laliotis, Ioannis, 2020. "The Covid-19 pandemic in Greece," MPRA Paper 99754, University Library of Munich, Germany.
• Matthew W Clance & Riza Demirer & Rangan Gupta & Clement Kweku Kyei, 2020. "Predicting firm-level volatility in the United States: the role of monetary policy uncertainty," 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.
• 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, vol. 28(21), pages 1889-1897, December.
  • Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2020. "A Note on Oil Price Shocks and the Forecastability of Gold Realized Volatility," Working Papers 202010, University of Pretoria, Department of Economics.
• Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian, 2021. "Do oil-price shocks predict the realized variance of U.S. REITs?," Energy Economics, Elsevier, vol. 104(C).
  • Matteo Bonato & Rangan Gupta & Christian Pierdzioch, 2020. "Do Oil-Price Shocks Predict the Realized Variance of U.S. REITs?," Working Papers 2020100, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Cuñado, Juncal & Gupta, Rangan, 2022. "Geopolitical risks and historical exchange rate volatility of the BRICS," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 179-190.
  • Afees A. Salisu & Juncal Cunado & Rangan Gupta, 2020. "Geopolitical Risks and Historical Exchange Rate Volatility of the BRICS," Working Papers 2020105, University of Pretoria, Department of Economics.
• 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, vol. 61(4), pages 1917-1933, October.
  • Edmond Berisha & David Gabauer & Rangan Gupta & Chi Keung Marco Lau, 2020. "Time-Varying Influence of Household Debt on Inequality in United Kingdom," Working Papers 202017, University of Pretoria, Department of Economics.
• Edmond Berisha & David Gabauer & Rangan Gupta & Jacobus Nel, 2020. "Time-Varying Predictability of Financial Stress on Inequality in United Kingdom," Working Papers 202030, University of Pretoria, Department of Economics.
• Christos Bouras & Christina Christou & Rangan Gupta & Keagile Lesame, 2020. "Forecasting State- and MSA-Level Housing Returns of the US: The Role of Mortgage Default Risks," Working Papers 202037, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Gupta, Rangan & Bouri, Elie & Ji, Qiang, 2020. "The role of global economic conditions in forecasting gold market volatility: Evidence from a GARCH-MIDAS approach," Research in International Business and Finance, Elsevier, vol. 54(C).
  • Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2020. "The Role of Global Economic Conditions in Forecasting Gold Market Volatility: Evidence from a GARCH-MIDAS Approach," Working Papers 202043, University of Pretoria, Department of Economics.
• Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian & Shahzad, Syed Jawad Hussain, 2020. "The predictive power of oil price shocks on realized volatility of oil: A note," Resources Policy, Elsevier, vol. 69(C).
  • Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2020. "The Predictive Power of Oil Price Shocks on Realized Volatility of Oil: A Note," Working Papers 202044, University of Pretoria, Department of Economics.
• Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Forecasting Power of Infectious Diseases-Related Uncertainty for Gold Realized Volatility," Working Papers 202049, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Riza Demirer, 2020. "A Note on Uncertainty due to Infectious Diseases and Output Growth of the United States: A Mixed-Frequency Forecasting Experiment," Working Papers 202050, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2020. "Forecasting Oil Volatility Using a GARCH-MIDAS Approach: The Role of Global Economic Conditions," Working Papers 202051, University of Pretoria, Department of Economics.
• Balcilar, Mehmet & Berisha, Edmond & Gupta, Rangan & Pierdzioch, Christian, 2021. "Time-varying evidence of predictability of financial stress in the United States over a century: The role of inequality," Structural Change and Economic Dynamics, Elsevier, vol. 57(C), pages 87-92.
  • Mehmet Balcilar & Edmond Berisha & Rangan Gupta & Christian Pierdzioch, 2020. "Time-Varying Evidence of Predictability of Financial Stress in the United States over a Century: The Role of Inequality," Working Papers 202054, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
• 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.
• Xin Sheng & Rangan Gupta & Qiang Ji, 2020. "Forecasting Charge-Off Rates with a Panel Tobit Model: The Role of Uncertainty," Working Papers 202092, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch & Afees A. Salisu, 2020. "Oil-Price Uncertainty and the U.K. Unemployment Rate: A Forecasting Experiment with Random Forests Using 150 Years of Data," Working Papers 202095, University of Pretoria, Department of Economics.
• Bouri, Elie & Gupta, Rangan & Majumdar, Anandamayee & Subramaniam, Sowmya, 2021. "Time-varying risk aversion and forecastability of the US term structure of interest rates," Finance Research Letters, Elsevier, vol. 42(C).
  • Elie Bouri & Rangan Gupta & Anandamayee Majumdar & Sowmya Subramaniam, 2020. "Time-Varying Risk Aversion and Forecastability of the US Term Structure of Interest Rates," Working Papers 202098, University of Pretoria, Department of Economics.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2020. "Uncertainty due to Infectious Diseases and Forecastability of the Realized Variance of US REITs: A Note," Working Papers 202099, University of Pretoria, Department of Economics.
• Tomáš Jeøábek, 2020. "The Efficiency of GARCH Models in Realizing Value at Risk Estimates," ACTA VSFS, University of Finance and Administration, vol. 14(1), pages 32-50.
• António Rua & Carlos Melo Gouveia & Nuno Lourenço, 2020. "Forecasting tourism with targeted predictors in a data-rich environment," Working Papers w202005, Banco de Portugal, Economics and Research Department.
• Nuttanan Wichitaksorn, 2020. "Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach," PIER Discussion Papers 146, Puey Ungphakorn Institute for Economic Research.
• Steven F. Lehrer & Tian Xie, 2018. "The Bigger Picture: Combining Econometrics with Analytics Improve Forecasts of Movie Success," NBER Working Papers 24755, National Bureau of Economic Research, Inc.
  • Steven Lehrer & Tian Xie, 2020. "The Bigger Picture: Combining Econometrics with Analytics Improve Forecasts of Movie Success," Working Paper 1449, Economics Department, Queen's University.
• Ramona Serrano Bautista & Leovardo Mata Mata, 2020. "A conditional heteroscedastic VaR approach with alternative distributions," EconoQuantum, Revista de Economia y Finanzas, Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas, Departamento de Metodos Cuantitativos y Maestria en Economia., vol. 17(2), pages 81-98, Julio-Dic.
• Castellares, Renzo & Cornejo, Gerson, 2020. "A Leading Indicator for Employment using Big Data," Working Papers 2020-009, Banco Central de Reserva del Perú.
• J. James Reade & Carl Singleton & Leighton Vaughan Williams, 2020. "Betting markets for English Premier League results and scorelines: evaluating a forecasting model," Economics Discussion Papers em-dp2020-03, Department of Economics, University of Reading.
• Andrew Clark, 2020. "A Pound Centric look at the Pound vs. Krona Exchange Rate Movement from 1844 to 1965," Economics Discussion Papers em-dp2020-22, Department of Economics, University of Reading.
• Clements, Michael P., 2021. "Do survey joiners and leavers differ from regular participants? The US SPF GDP growth and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 37(2), pages 634-646.
  • Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, University of Reading.
• Michael P. Clements, 2022. "Individual forecaster perceptions of the persistence of shocks to GDP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 640-656, April.
  • Michael P. Clements, 2020. "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance icma-dp2020-02, Henley Business School, University of Reading.
• Bejarano-Salcedo, Valeria & Cárdenas-Cárdenas, Julián Alonso & Julio-Román, Juan Manuel & Caicedo-García, Edgar, 2020. "Entendiendo, Modelando y Pronosticando los efectos de "El Niño" sobre los precios de los alimentos: el caso colombiano," Working papers 50, Red Investigadores de Economía.
• Avela, Aleksi & Lehmus, Markku, 2020. "It’s in the News: Developing a Real Time Index for Economic Uncertainty Based on Finnish News Titles," ETLA Working Papers 84, The Research Institute of the Finnish Economy.
• Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Papers 2020_21, Business School - Economics, University of Glasgow.
  • Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Paper series 20-09, Rimini Centre for Economic Analysis.
• Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2020. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Working Paper series 20-27, Rimini Centre for Economic Analysis.
  • 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 21-016/III, Tinbergen Institute.
• Balagula, Yuri, 2020. "Forecasting daily spot prices in the Russian electricity market with the ARFIMA model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 89-101.
• 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.
• Petrova, Diana & Trunin, Pavel, 2020. "Revealing the mood of economic agents based on search queries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 71-87.
• Stankevich, Ivan, 2020. "Comparison of macroeconomic indicators nowcasting methods: Russian GDP case," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 113-127.
• Lozinskaia, Agata & Redkina, Anastasiia & Shenkman, Evgeniia, 2020. "Electricity consumption forecasting for integrated power system with seasonal patterns," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 60, pages 5-25.
• 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.
• 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.
• Balázs Páger & Zsuzsanna Zsibók, 2020. "Regionalizing National-Level Growth Projections In The Visegrad Countries €“ The Issue Of Ex-Post Rescaling," Romanian Journal of Regional Science, Romanian Regional Science Association, vol. 14(1), pages 1-23, JUNE.
• Balazs Pager & Zsuzsanna Zsibókb, 2020. "Regionalizing National-Level Growth Projections in the Visegrad Countries – The Issue Of Ex-Post Rescaling," Romanian Journal of Regional Science, Romanian Regional Science Association, vol. 14(1), pages 1-24, JUNE.
• Tommaso Proietti & Alessandro Giovannelli, 2021. "Nowcasting monthly GDP with big data: A model averaging approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 683-706, April.
  • 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.
• Sobreira, Nuno & Louro, Rui, 2020. "Evaluation of volatility models for forecasting Value-at-Risk and Expected Shortfall in the Portuguese stock market," Finance Research Letters, Elsevier, vol. 32(C).
• 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.
• 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, University of Reading.
• Aslan, Aylin & Sensoy, Ahmet, 2020. "Intraday efficiency-frequency nexus in the cryptocurrency markets," Finance Research Letters, Elsevier, vol. 35(C).
• Pincheira-Brown, Pablo & Neumann, Federico, 2020. "Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile," Finance Research Letters, Elsevier, vol. 37(C).
  • Pincheira, Pablo & Neumann, Federico, 2018. "Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile," MPRA Paper 90432, University Library of Munich, Germany.
• Çepni, Oğuzhan & Guney, I. Ethem & Gupta, Rangan & Wohar, Mark E., 2020. "The role of an aligned investor sentiment index in predicting bond risk premia of the U.S," Journal of Financial Markets, Elsevier, vol. 51(C).
• Kupiec, Paul H., 2020. "Policy uncertainty and bank stress testing," Journal of Financial Stability, Elsevier, vol. 51(C).
  • Paul H. Kupiec, 2019. "Policy uncertainty and bank stress testing," AEI Economics Working Papers 1022739, American Enterprise Institute.
• Cupido, Kyran & Jevtić, Petar & Paez, Antonio, 2020. "Spatial patterns of mortality in the United States: A spatial filtering approach," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 28-38.
• Andrada-Félix, Julián & Fernandez-Perez, Adrian & Sosvilla-Rivero, Simón, 2020. "Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
  • Julián Andrada-Félix & Adrian Fernandez-Perez & Simón Sosvilla-Rivero, 2019. "“Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities”," IREA Working Papers 201912, University of Barcelona, Research Institute of Applied Economics, revised Jul 2019.
• Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
  • Ellis W. Tallman & Saeed Zaman, 2018. "Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy," Working Papers (Old Series) 1809, Federal Reserve Bank of Cleveland.
• Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2020. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 466-479.
  • Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2018. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," HSC Research Reports HSC/18/05, Hugo Steinhaus Center, Wroclaw University of Technology.
• Maheu, John M. & Song, Yong & Yang, Qiao, 2020. "Oil price shocks and economic growth: The volatility link," International Journal of Forecasting, Elsevier, vol. 36(2), pages 570-587.
  • John M. Maheu & Yong Song & Qiao Yang, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," Working Paper series 18-03, Rimini Centre for Economic Analysis.
  • Maheu, John M & Yang, Qiao & Song, Yong, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83779, University Library of Munich, Germany.
  • Maheu, John M & Song, Yong & Yang, Qiao, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83999, University Library of Munich, Germany.
• Niesert, Robin F. & Oorschot, Jochem A. & Veldhuisen, Christian P. & Brons, Kester & Lange, Rutger-Jan, 2020. "Can Google search data help predict macroeconomic series?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1163-1172.
  • Robin Niesert & Jochem Oorschot & Chris Veldhuisen & Kester Brons & Rutger-Jan Lange, "undated". "Can Google Search Data Help Predict Macroeconomic Series?," Tinbergen Institute Discussion Papers 19-021/III, Tinbergen Institute.
• Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
  • Monokroussos, George, 2015. "Nowcasting in Real Time Using Popularity Priors," MPRA Paper 68594, University Library of Munich, Germany.
  • George Monokroussos & Yongchen Zhao, 2020. "Nowcasting in Real Time Using Popularity Priors," Working Papers 2020-01, Towson University, Department of Economics, revised Feb 2020.
• Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
  • Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," CESifo Working Paper Series 6457, CESifo.
  • Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
  • Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2019. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model," Jena Economic Research Papers 2019-006, Friedrich-Schiller-University Jena.
• Chernis, Tony & Cheung, Calista & Velasco, Gabriella, 2020. "A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth," International Journal of Forecasting, Elsevier, vol. 36(3), pages 851-872.
  • Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
• Colombo, Emilio & Pelagatti, Matteo, 2020. "Statistical learning and exchange rate forecasting," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1260-1289.
  • Emilio Colombo & Matteo Pelagatti, 2019. "Statistical Learning and Exchange Rate Forecasting," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo dis1901, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS).
• Zhang, Bo & Chan, Joshua C.C. & Cross, Jamie L., 2020. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1318-1328.
  • Bo Zhang & Joshua C.C. Chan & Jamie L. Cross, 2018. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," CAMA Working Papers 2018-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Jones, Jacob T. & Sinclair, Tara M. & Stekler, Herman O., 2020. "A textual analysis of Bank of England growth forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1478-1487.
  • Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018. "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers 2018-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised May 2019.
• Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Pricing individual stock options using both stock and market index information," Journal of Banking & Finance, Elsevier, vol. 111(C).
• Bengtsson, Elias & Grothe, Magdalena & Lepers, Etienne, 2020. "Home, safe home: Cross-country monitoring framework for vulnerabilities in the residential real estate sector," Journal of Banking & Finance, Elsevier, vol. 112(C).
  • Bengtsson, Elias & Grothe, Magdalena & Lepers, Etienne, 2017. "Home, safe home: cross-country monitoring framework for vulnerabilities in the residential real estate sector," Working Paper Series 2096, European Central Bank.
• Das, Prashant & Füss, Roland & Hanle, Benjamin & Russ, Isabel Nina, 2020. "The cross-over effect of irrational sentiments in housing, commercial property, and stock markets," Journal of Banking & Finance, Elsevier, vol. 114(C).
• Moura, Guilherme V. & Santos, André A.P. & Ruiz, Esther, 2020. "Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 118(C).
• Hüttner, Amelie & Scherer, Matthias & Gräler, Benedikt, 2020. "Geostatistical modeling of dependent credit spreads: Estimation of large covariance matrices and imputation of missing data," Journal of Banking & Finance, Elsevier, vol. 118(C).
• Westphal, Rebecca & Sornette, Didier, 2020. "Market impact and performance of arbitrageurs of financial bubbles in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 1-23.
• Delli Gatti, Domenico & Grazzini, Jakob, 2020. "Rising to the challenge: Bayesian estimation and forecasting techniques for macroeconomic Agent Based Models," Journal of Economic Behavior & Organization, Elsevier, vol. 178(C), pages 875-902.
  • Domenico Delli Gatti & Jakob Grazzini, 2019. "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series 7894, CESifo.
• 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).
• Kaiser, Ulrich & Kuhn, Johan M., 2020. "The value of publicly available, textual and non-textual information for startup performance prediction," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
• Arunanondchai, Panit & Sukcharoen, Kunlapath & Leatham, David J., 2020. "Dealing with tail risk in energy commodity markets: Futures contracts versus exchange-traded funds," Journal of Commodity Markets, Elsevier, vol. 20(C).
• Nonejad, Nima, 2020. "A comprehensive empirical analysis of the predictive impact of the price of crude oil on aggregate equity return volatility," Journal of Commodity Markets, Elsevier, vol. 20(C).
• Ogbuabor, Jonathan E. & Anthony-Orji, Onyinye I. & Manasseh, Charles O. & Orji, Anthony, 2020. "Measuring the dynamics of COMESA output connectedness with the global economy," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
• Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
• Virbickaitė, Audronė & Frey, Christoph & Macedo, Demian N., 2020. "Bayesian sequential stock return prediction through copulas," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
• Coda Moscarola, Flavia & Colombino, Ugo & Figari, Francesco & Locatelli, Marilena, 2020. "Shifting taxes away from labour enhances equity and fiscal efficiency," Journal of Policy Modeling, Elsevier, vol. 42(2), pages 367-384.
• Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian & Shahzad, Syed Jawad Hussain, 2020. "The predictive power of oil price shocks on realized volatility of oil: A note," Resources Policy, Elsevier, vol. 69(C).
  • Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2020. "The Predictive Power of Oil Price Shocks on Realized Volatility of Oil: A Note," Working Papers 202044, University of Pretoria, Department of Economics.
• León, Carlos, 2020. "Detecting anomalous payments networks: A dimensionality-reduction approach," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
  • Carlos León, 2019. "Detecting anomalous payments networks: A dimensionality reduction approach," Borradores de Economia 1098, Banco de la Republica de Colombia.
• Rodríguez-Vargas, Adolfo, 2020. "Forecasting Costa Rican inflation with machine learning methods," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
• Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2020. "Crisis transmission: Visualizing vulnerability," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
  • Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2019. "Crisis transmission: visualizing vulnerability," Working Papers 2019-07, University of Tasmania, Tasmanian School of Business and Economics.
• Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
• Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2020. "Why are some Chinese firms failing in the US capital markets? A machine learning approach," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
• Jian, Zhihong & Li, Xupei & Zhu, Zhican, 2020. "Sequential forecasting of downside extreme risk during overnight and daytime: Evidence from the Chinese Stock Market☆," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
• McGurk, Zachary, 2020. "US real estate inflation prediction: Exchange rates and net foreign assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 53-66.
• Christou, Christina & Gupta, Rangan, 2020. "Forecasting equity premium in a panel of OECD countries: The role of economic policy uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 243-248.
  • Christina Christou & Rangan Gupta, 2016. "Forecasting Equity Premium in a Panel of OECD Countries: The Role of Economic Policy Uncertainty," Working Papers 201622, University of Pretoria, Department of Economics.
• Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Heterogeneous market hypothesis approach for modeling unbiased extreme value volatility estimator in presence of leverage effect: An individual stock level study with economic significance analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 271-285.
• 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.
• Arvanitopoulos, T. & Agnolucci, P., 2020. "The long-term effect of renewable electricity on employment in the United Kingdom," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
• Hicks, Robert L. & Holland, Daniel S. & Kuriyama, Peter T. & Schnier, Kurt E., 2020. "Choice sets for spatial discrete choice models in data rich environments," Resource and Energy Economics, Elsevier, vol. 60(C).
• Kim, Young Min & Lee, Seojin, 2020. "Exchange rate predictability: A variable selection perspective," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 117-134.
• Bonollo, Michele & Di Persio, Luca & Oliva, Immacolata, 2020. "A quantization approach to the counterparty credit exposure estimation," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 335-356.
• Salisu, Afees A. & Gupta, Rangan & Bouri, Elie & Ji, Qiang, 2020. "The role of global economic conditions in forecasting gold market volatility: Evidence from a GARCH-MIDAS approach," Research in International Business and Finance, Elsevier, vol. 54(C).
  • Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2020. "The Role of Global Economic Conditions in Forecasting Gold Market Volatility: Evidence from a GARCH-MIDAS Approach," Working Papers 202043, University of Pretoria, Department of Economics.
• 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, University of Reading.
• Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
• Manickavasagam, Jeevananthan & Visalakshmi, S. & Apergis, Nicholas, 2020. "A novel hybrid approach to forecast crude oil futures using intraday data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
• Nasir, Muhammad Ali, 2020. "Forecasting inflation under uncertainty: The forgotten dog and the frisbee," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
• 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.
  • 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.
  • Razzak, Weshah, 2020. "The Dynamic of COVID-19 New Infections under Different Stringent Policies," MPRA Paper 100451, University Library of Munich, Germany.
• Patrick J. Coe & Shaun P. Vahey, 2020. "Financial conditions and the risks to economic growth in the United States since 1875," CAMA Working Papers 2020-36, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• 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.
  • 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.
  • 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.
• Marek Kwas & Alessia Paccagnini & Michal Rubaszek, 2020. "Common factors and the dynamics of cereal prices. A forecasting perspective," CAMA Working Papers 2020-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Laurent Ferrara & Joseph Yapi, 2020. "Measuring exchange rate risks during periods of uncertainty," CAMA Working Papers 2020-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," Working Papers 2020-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Aug 2020.
  • William D. Larson & Tara M. Sinclair, 2020. "Nowcasting unemployment insurance claims in the time of COVID-19," CAMA Working Papers 2020-63, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," FHFA Staff Working Papers 20-02, Federal Housing Finance Agency.
• Bo Zhang & Bao H. Nguyen, 2020. "Real-time forecasting of the Australian macroeconomy using flexible Bayesian VARs," CAMA Working Papers 2020-91, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Gandy, Axel & Veraart, Luitgard A. M., 2021. "Compound poisson models for weighted networks with applications in finance," LSE Research Online Documents on Economics 104185, London School of Economics and Political Science, LSE Library.
• J Reade & C Singleton & L Vaughan Williams, 2020. "Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model," Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
• Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices," Energies, MDPI, vol. 13(14), pages 1-19, July.
  • Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, vol. 13(7), pages 1-16, April.
  • Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2020. "Beating the naive: Combining LASSO with naive intraday electricity price forecasts," WORking papers in Management Science (WORMS) WORMS/20/01, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Dean Fantazzini & Nikita Kolodin, 2020. "Does the Hashrate Affect the Bitcoin Price?," JRFM, MDPI, 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.
• Philip Hans Franses & Max Welz, 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," JRFM, MDPI, vol. 13(3), pages 1-8, March.
  • Franses, Ph.H.B.F. & Welz, M., 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," Econometric Institute Research Papers EI-1687, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Ruben Fotso, 2020. "Evaluation of indirect effects of place-based science-industry transfer policies: Case of French Technological Research Institutes," Working Papers 2031, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
• Ruben Fotso, 2020. "Evaluation of the effectiveness of technological platforms as a technology transfer tool: the impact of French Technological Research Institutes on the socio-economic performance of SMEs," Working Papers 2032, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
• Gary Koop & Dimitris Korobilis, 2018. "Bayesian dynamic variable selection in high dimensions," Papers 1809.03031, arXiv.org, revised May 2020.
  • 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.
• Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Paper series 20-09, Rimini Centre for Economic Analysis.
  • Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Papers 2020_21, Business School - Economics, University of Glasgow.
• Adrien LAGARDE & Luc DOYEN & Joachim CLAUDET & Olivier THEBAUD, 2020. "Ecological-economic resilience of a fished coral reef through stochastic multi-species MSY," Bordeaux Economics Working Papers 2020-11, Bordeaux School of Economics (BSE).
• Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Short-Term Exuberance and long-term stability: A simultaneous optimization of stock return predictions for short and long horizons," Graz Economics Papers 2020-20, University of Graz, Department of Economics.
• Constantin Bürgi & Tara M. Sinclair, 2021. "What does forecaster disagreement tell us about the state of the economy?," Applied Economics Letters, Taylor & Francis Journals, vol. 28(1), pages 49-53, January.
  • Constantin Bürgi & Tara M. Sinclair, 2020. "What Does Forecaster Disagreement Tell Us about the State of the Economy?," Working Papers 2020-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," FHFA Staff Working Papers 20-02, Federal Housing Finance Agency.
  • William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," Working Papers 2020-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Aug 2020.
  • William D. Larson & Tara M. Sinclair, 2020. "Nowcasting unemployment insurance claims in the time of COVID-19," CAMA Working Papers 2020-63, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Constantin Bürgi, 2020. "Expectation Formation and the Persistence of Shocks," Working Papers 2020-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Sep 2020.
• Natsuki Arai, 2020. "The FOMC’s New Individual Economic Projections and Macroeconomic Theories," Working Papers 2020-007, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• 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.
• Philip ME Garboden, 2019. "Sources and Types of Big Data for Macroeconomic Forecasting," Working Papers 2019-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
• Peter Fuleky, 2020. "Nowcasting the Trajectory of the COVID-19 Recovery," Working Papers 2020-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
• Peter Fuleky, 2020. "Nowcasting the Trajectory of the COVID-19 Recovery," Working Papers 202022, University of Hawaii at Manoa, Department of Economics.
• Michael Brei & Claudio Borio & Leonardo Gambacorta, 2020. "Bank intermediation activity in a low‐interest‐rate environment," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 49(2), July.
  • Michael Brei & Claudio Borio, 2019. "Bank intermediation activity in a low interest rate environment," BIS Working Papers 807, Bank for International Settlements.
  • Michael Brei & Claudio Borio & Leonardo Gambacorta, 2020. "Bank intermediation activity in a low‐interest‐rate environment," Post-Print hal-02985986, HAL.
  • Borio, Claudio & Brei, Michael & Gambacorta, Leonardo, 2019. "Bank intermediation activity in a low interest rate environment," CEPR Discussion Papers 13980, C.E.P.R. Discussion Papers.
• 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.
• Benchimol, Jonathan & El-Shagi, Makram, 2020. "Forecast performance in times terrorism," Economic Modelling, Elsevier, vol. 91(C), pages 386-402.
  • Jonathan Benchimol & Makram El-Shagi, 2017. "Forecast Performance in Times of Terrorism," CFDS Discussion Paper Series 2017/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
  • Jonathan Benchimol & Makram El-Shagi, 2020. "Forecast performance in times of terrorism," Post-Print halshs-03248938, HAL.
  • Jonathan Benchimol & Makram El-Shagi, 2020. "Forecast Performance in Times of Terrorism," Globalization Institute Working Papers 390, Federal Reserve Bank of Dallas.
  • Jonathan Benchimol & Makram El-Shagi, 2019. "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers 2019.08, Bank of Israel.
• Elena Ivona DUMITRESCU & Sullivan HUE & Christophe HURLIN & Sessi TOKPAVI, 2020. "Machine Learning or Econometrics for Credit Scoring: Let’s Get the Best of Both Worlds," LEO Working Papers / DR LEO 2839, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Elena Dumitrescu & Sullivan Hué & Christophe Hurlin & Sessi Tokpavi, 2021. "Machine Learning or Econometrics for Credit Scoring: Let's Get the Best of Both Worlds," Working Papers hal-02507499, HAL.
• Olivier Damette & Claude Diebolt & Stephane Goutte & Umberto Triacca, 2020. "Cliometrics of Climate Change," Working Papers hal-03215675, HAL.
• 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," Working Papers hal-03403077, HAL.
  • 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.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Sciences Po publications 06/2020, Sciences Po.
• Steffen Q. Mueller & Patrick Ring & Maria Schmidt, 2019. "Forecasting economic decisions under risk: The predictive importance of choice-process data," Working Papers 066, Chair for Economic Policy, University of Hamburg.
  • Steffen Q. Mueller & Patrick Ring & Maria Fischer, 2020. "Excited and aroused: The predictive importance of simple choice process metrics," Working Papers 067, Chair for Economic Policy, University of Hamburg.
• William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," Working Papers 2020-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Aug 2020.
  • William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," FHFA Staff Working Papers 20-02, Federal Housing Finance Agency.
  • William D. Larson & Tara M. Sinclair, 2020. "Nowcasting unemployment insurance claims in the time of COVID-19," CAMA Working Papers 2020-63, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Gregory Chernov, 2020. "How to Learn to Defeat Noisy Robot in Rock-Paper-Scissors Game: An Exploratory Study," HSE Economic Journal, National Research University Higher School of Economics, vol. 24(4), pages 503-538.
• Dauth, Wolfgang & Eppelsheimer, Johann, 2020. "Preparing the sample of integrated labour market biographies (SIAB) for scientific analysis," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 54(1), pages 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.
  • 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.
  • 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 1-4.
• Falco J. Bargagli-Dtoffi & Massimo Riccaboni & Armando Rungi, 2020. "Machine Learning for Zombie Hunting. Firms Failures and Financial Constraints," Working Papers 01/2020, IMT School for Advanced Studies Lucca, revised Jun 2020.
• Thomas Lustenberger & Enzo Rossi, 2020. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," International Journal of Central Banking, International Journal of Central Banking, vol. 16(2), pages 153-201, March.
  • Thomas Lustenberger & Enzo Rossi, 2017. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," Working Papers 2017-12, Swiss National Bank.
  • Lustenberger, Thomas & Rossi, Enzo, 2018. "Does Central Bank Transparency and Communication Affect Financial and Macroeconomic Forecasts?," Working papers 2018/06, Faculty of Business and Economics - University of Basel.
• Toshiaki Ogawa & Masato Ubukata & Toshiaki Watanabe, 2020. "Stock Return Predictability and Variance Risk Premia around the ZLB," IMES Discussion Paper Series 20-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
• 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.
  • 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 20/98, 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.
  • Mr. Manuk Ghazanchyan & Vibha Nanda & Alex Ho & Mr. Bas B. Bakker, 2020. "The Lack of Convergence of Latin-America Compared with CESEE: Is Low Investment to Blame?," IMF Working Papers 2020/098, International Monetary Fund.
• Rey Francisco Ayala Castrejon & Christian Bucio Pacheco, 2020. "Modelo ARIMA aplicado al tipo de cambio peso-dólar en el periodo 2016-2017 mediante ventanas temporales deslizantes," 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. 15(3), pages 331-354, Julio - S.
• Sergio Lagunas Puls & Miguel Angel Oropeza Tagle & Juan Bautista Boggio Vázquez, 2020. "Energy Consumption in North America: Visualization and Pyramidal Perspective," 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. 15(4), pages 709-723, Octubre -.
• Xavier Estupinan & Mohit Sharma & Sargam Gupta & Bharti Birla, 2020. "Impact of COVID-19 pandemic on labour supply and gross value added in India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2020-022, Indira Gandhi Institute of Development Research, Mumbai, India.
• Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2020. "A New Index of Housing Sentiment," Management Science, INFORMS, vol. 66(4), pages 1563-1583, April.
  • Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2016. "A New Index of Housing Sentiment," CREATES Research Papers 2016-32, Department of Economics and Business Economics, Aarhus University.
• Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
• Blasques, Francisco & Hoogerkamp, Meindert Heres & Koopman, Siem Jan & van de Werve, Ilka, 2021. "Dynamic factor models with clustered loadings: Forecasting education flows using unemployment data," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1426-1441.
  • 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.
  • Noussair, C.N. & Popescu, Andreea Victoria, 2020. "Contagion and Return Predictability in Asset Markets : An Experiment with Two Lucas Trees," Discussion Paper 2020-014, Tilburg University, Center for Economic Research.
• Kohei Maehashi & Mototsugu Shintani, 2020. "Macroeconomic Forecasting Using Factor Models and Machine Learning: An Application to Japan," CIRJE F-Series CIRJE-F-1146, CIRJE, Faculty of Economics, University of Tokyo.
• Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
  • Monokroussos, George, 2015. "Nowcasting in Real Time Using Popularity Priors," MPRA Paper 68594, University Library of Munich, Germany.
  • George Monokroussos & Yongchen Zhao, 2020. "Nowcasting in Real Time Using Popularity Priors," Working Papers 2020-01, Towson University, Department of Economics, revised Feb 2020.
• Lahiri, Kajal & Zhao, Yongchen, 2020. "The Nordhaus test with many zeros," Economics Letters, Elsevier, vol. 193(C).
  • Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," CESifo Working Paper Series 8350, CESifo.
  • Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," Working Papers 2020-05, Towson University, Department of Economics, revised Jun 2020.
• Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 2017-026, Federal Reserve Bank of St. Louis.
  • Todd E Clark & Michael W McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," BIS Working Papers 667, Bank for International Settlements.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 17-15R, Federal Reserve Bank of Cleveland.
  • Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers (Old Series) 1715, Federal Reserve Bank of Cleveland.
• 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.
• 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.
  • 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," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "lassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, Institute of Labor Economics (IZA).
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
• Benedikt Janzen & Doina Radulescu, 0. "Electricity Use as a Real-Time Indicator of the Economic Burden of the COVID-19-Related Lockdown: Evidence from Switzerland," CESifo Economic Studies, CESifo, vol. 66(4), pages 303-321.
  • 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.
  • Benedikt Janzen & Doina Radulescu, 2020. "Electricity Use as a Real Time Indicator of the Economic Burden of the COVID-19-Related Lockdown: Evidence from Switzerland," Diskussionsschriften dp2010, Universitaet Bern, Departement Volkswirtschaft.
• 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.
  • Tong Fang & Tae-Hwy Lee & Zhi Su, 2020. "Predicting the Long-term Stock Market Volatility: A GARCH-MIDAS Model with Variable Selection," Working Papers 202009, University of California at Riverside, Department of Economics.
• 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).
  • Olivier DAMETTE & Claude DIEBOLT & Stephane GOUTTE & Umberto TRIACCA, 2020. "Cliometrics of Climate Change: A Natural Experiment on the Little Ice Age," Working Papers of BETA 2020-20, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
• 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.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the information channel of monetary policy disappeared? Revisiting the empirical evidence," Economics Working Papers 1701, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
  • Hoesch, Lukas & Rossi, Barbara & Sekhposyan, Tatevik, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," CEPR Discussion Papers 14456, C.E.P.R. Discussion Papers.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Papers 1158, Barcelona Graduate School of Economics.
• Breitenstein, Miriam & Anke, Carl-Philipp & Nguyen, Duc Khuong & Walther, Thomas, 2019. "Stranded Asset Risk and Political Uncertainty: The Impact of the Coal Phase-out on the German Coal Industry," MPRA Paper 101763, University Library of Munich, Germany.
  • Miriam Breitenstein & Carl-Philipp Anke & Duc Khuong Nguyen & T. Walther, 2020. "Stranded Asset Risk and Political Uncertainty: The Impact of the Coal Phase-out on the German Coal Industry," Working Papers 2002, Utrecht School of Economics.
• 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).
  • Jonas Striaukas & Martin Schumacher & Harald Binder & Matthias Weber, 2020. "Network-Constrained Covariate Coefficient and Connection Sign Estimation," Working Papers on Finance 2001, University of St. Gallen, School of Finance.
  • Matthias Weber & Jonas Striaukas & Martin Schumacher & Harald Binder, 2018. "Network constrained covariate coefficient and connection sign estimation," Bank of Lithuania Discussion Paper Series 8, Bank of Lithuania.
• 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.
• Hans R. ISAKSON & Mark D. ECKER & Lee KENNEDY, 2020. "Principles For Calculating Avm Performance Metrics," The Valuation Journal, National Association of Romanian Valuers, vol. 16(2), pages 38-69.
• 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.
• 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.
• Rządkowski Grzegorz & Sobczak Lidia, 2020. "A Generalized Logistic Function and Its Applications," Foundations of Management, Sciendo, vol. 12(1), pages 85-92, 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, 2017. "Forecasting with Dynamic Panel Data Models," Papers 1709.10193, arXiv.org.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2018. "Forecasting with Dynamic Panel Data Models," NBER Working Papers 25102, National Bureau of Economic Research, Inc.
• 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.
  • Carlo Pizzinelli & Konstantinos Theodoridis & Francesco Zanetti, 2020. "State dependence in labour market fluctuations," Working Papers 47, European Stability Mechanism.
• 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," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," Working Paper Series 44, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
• 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.
• Cindy S. H. Wang & Shui Ki Wan, 2020. "A VAR Approach to Forecasting Multivariate Long Memory Processes Subject to Structural Breaks," Advances in Econometrics, in: Tong Li & M. Hashem Pesaran & Dek Terrell (ed.), Essays in Honor of Cheng Hsiao, volume 41, pages 105-141, Emerald Publishing Ltd.
• Hardik Marfatia, 2020. "Evaluating the forecasting power of foreign Country's income growth: a global analysis," Journal of Economic Studies, Emerald Group Publishing, vol. 47(5), pages 1071-1092, April.
• Rahul Roy & Santhakumar Shijin, 2020. "The nexus of asset pricing, volatility and the business cycle," Journal of Economic Studies, Emerald Group Publishing, vol. 48(1), pages 79-101, May.
• Zidong An & Joao Tovar Jalles, 2020. "On the performance of US fiscal forecasts: government vs. private information," Journal of Economic Studies, Emerald Group Publishing, vol. 48(2), pages 367-391, June.
  • Zidong An & João Tovar Jalles, 2020. "On the Performance of US Fiscal Forecasts: Government vs. Private Information," Working Papers REM 2020/0130, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
• Philip Hans Franses & Max Welz, 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," JRFM, MDPI, vol. 13(3), pages 1-8, March.
  • Franses, Ph.H.B.F. & Welz, M., 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," Econometric Institute Research Papers EI-1687, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Franses, Ph.H.B.F., 2020. "An introduction to time-varying lag autoregression," Econometric Institute Research Papers EI2020-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Raymundo M. Campos Vázquez & Sergio E. López-Araiza B., 2020. "Grandes datos, Google y desempleo/Big Data, Google and Unemployment," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 35(1), pages 125-151.
• Francisco Corona & Jesús López-Pérez, 2020. "Una evaluación econométrica de la retropolación de la actividad económica estatal de México," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 35(2), pages 193-212.
• Oscar de J. Gálvez-Soriano, 2020. "Nowcasting Mexico's quarterly GDP using factor models and bridge equations," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 35(2), pages 213-265.
• Baris Yalin Uzunlu & Syed Muzammil Hussain, 2020. "Employing Machine Learning Algorithms to build Trading Strategies with higher than Risk-Free Returns," International Econometric Review (IER), Econometric Research Association, vol. 12(2), pages 112-138, September.
• My-Linh Thi Nguyen, 2020. "The Hedonic Pricing Model Applied to the Housing Market," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(3), pages 416-428.
• Ioannis N. Kallianiotis & Karen Bianchi & Augustine C. Arize & John Malindretos & Ikechukwu Ndu, 2020. "Financial Assets, Expected Return and Risk, Speculation, Uncertainty, and Exchange Rate Determination," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 3-30.
• Mariusz Doszyn, 2020. "Accuracy of Intermittent Demand Forecasting Systems in the Enterprise," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 912-930.
• Bartlomiej H. Toszek, 2020. "Innovative Arrangements of Waste Management Environment Strategy: The Case of London," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 1024-1032.
• Mariusz Doszyn, 2020. "Biasedness of Forecasts Errors for Intermittent Demand Data," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 1113-1127.
• Anna Warchlewska & Krzysztof Waliszewski, 2020. "Who uses Robo-Advisors? The Polish Case," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 97-114.
• Tomasz Zawadzki & Tomasz Walecki & Halina Swieboda & Ryszard Szpyra & M.Kuczabski & P.Stobiecki, 2020. "Introduction to Methods of Modelling Information Wars as a 21st Century Threat," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 1011-1026.
• Katarzyna Witczynska, 2020. "The Impact of the Electronic Commerce Market in the Supply Chain during COVID-19 Pandemic in Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 648-658.
• Krzysztof Waliszewski & Anna Warchlewska, 2020. "Socio-Demographic Factors Determining Expectation Experienced while Using Modern Technologies in Personal Financial Management (PFM and robo-advice): A Polish Case," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 893-904.
• Evžen Kočenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Eastern European Economics, Taylor & Francis Journals, vol. 58(3), pages 197-220, May.
  • Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
  • Evzen Kocenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Working Papers IES 2020/5, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2020.
• 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," Post-Print hal-03403017, HAL.
  • 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).
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Sciences Po publications 04/2020, Sciences Po.
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Working Papers hal-03403073, HAL.
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Sciences Po publications info:hdl:2441/2q9catktmn9, Sciences Po.
• Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Sciences Po publications 06/2020, Sciences Po.
  • 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).
  • 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," Working Papers hal-03403077, HAL.
  • Reichlin, Lucrezia & Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial variables as predictors of real growth vulnerability," Discussion Papers 05/2020, Deutsche Bundesbank.
• Bo Zhao, 2020. "Forecasting the New England States’ Tax Revenues in the Time of the COVID-19 Pandemic," Current Policy Perspectives 88356, Federal Reserve Bank of Boston.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," Working Papers 20-02R, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
• Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
• 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., vol. 36(5), pages 495-516, August.
  • Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," Working Papers 20-27, 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.
  • Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
• Diana Žigraiová & Aitor Erce & Xu Jiang, 2020. "Quantifying risks to sovereign market access: Methods and challenges," Working Papers 42, European Stability Mechanism.
  • Aitor Erce & Xu Jiang & Diana Zigraiova, 2020. "Quantifying Risks to Sovereign Market Access: Methods and Challenges," Globalization Institute Working Papers 377, Federal Reserve Bank of Dallas.
• Enrique Martinez-Garcia & Efthymios Pavlidis & Kostas Vasilopoulos, 2020. "exuber: Recursive Right-Tailed Unit Root Testing with R," Globalization Institute Working Papers 383, Federal Reserve Bank of Dallas, revised 19 Oct 2021.
• Benchimol, Jonathan & El-Shagi, Makram, 2020. "Forecast performance in times terrorism," Economic Modelling, Elsevier, vol. 91(C), pages 386-402.
  • Jonathan Benchimol & Makram El-Shagi, 2017. "Forecast Performance in Times of Terrorism," CFDS Discussion Paper Series 2017/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
  • Jonathan Benchimol & Makram El-Shagi, 2020. "Forecast Performance in Times of Terrorism," Globalization Institute Working Papers 390, Federal Reserve Bank of Dallas.
  • Jonathan Benchimol & Makram El-Shagi, 2019. "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers 2019.08, Bank of Israel.
  • Jonathan Benchimol & Makram El-Shagi, 2020. "Forecast performance in times of terrorism," Post-Print halshs-03248938, HAL.
• Dur, Ayşe & Martínez García, Enrique, 2020. "Mind the gap!—A monetarist view of the open-economy Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
  • Ayse Dur & Enrique Martinez-Garcia, 2020. "Mind the Gap!—A Monetarist View of the Open-Economy Phillips Curve," Globalization Institute Working Papers 392, Federal Reserve Bank of Dallas.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks," CESifo Working Paper Series 8475, CESifo.
  • Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks," Globalization Institute Working Papers 394, Federal Reserve Bank of Dallas, revised 17 Apr 2021.
• Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," PIER Working Paper Archive 20-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Working Paper Series 2020-02, Federal Reserve Bank of San Francisco.
  • Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," NBER Working Papers 28228, National Bureau of Economic Research, Inc.
  • Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers 1912.10774, arXiv.org, revised Jul 2021.
• Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the information channel of monetary policy disappeared? Revisiting the empirical evidence," Economics Working Papers 1701, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
  • 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.
  • Hoesch, Lukas & Rossi, Barbara & Sekhposyan, Tatevik, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," CEPR Discussion Papers 14456, C.E.P.R. Discussion Papers.
  • Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Papers 1158, Barcelona Graduate School of Economics.
• Christopher A. Hollrah & Steven A. Sharpe & Nitish R. Sinha, 2020. "The Power of Narratives in Economic Forecasts," Finance and Economics Discussion Series 2020-001, Board of Governors of the Federal Reserve System (U.S.).
• Travis J. Berge, 2020. "Time-varying Uncertainty of the Federal Reserve’s Output Gap Estimate," Finance and Economics Discussion Series 2020-012r1, Board of Governors of the Federal Reserve System (U.S.), revised 14 Apr 2021.
• Michael Cai & Marco Del & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2021. "Online estimation of DSGE models," Econometrics Journal, Royal Economic Society, vol. 24(1), pages 33-58.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Liberty Street Economics 20190821, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," Finance and Economics Discussion Series 2020-023, Board of Governors of the Federal Reserve System (U.S.).
  • Michael D. Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," NBER Working Papers 26826, National Bureau of Economic Research, Inc.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Staff Reports 893, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," PIER Working Paper Archive 19-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2020. "Tracking Labor Market Developments during the COVID-19 Pandemic: A Preliminary Assessment," Finance and Economics Discussion Series 2020-030, Board of Governors of the Federal Reserve System (U.S.).
• Michael Puglia & Adam Tucker, 2020. "Machine Learning, the Treasury Yield Curve and Recession Forecasting," Finance and Economics Discussion Series 2020-038, Board of Governors of the Federal Reserve System (U.S.).
• Elena Afanasyeva, 2020. "Can Forecast Errors Predict Financial Crises? Exploring the Properties of a New Multivariate Credit Gap," Finance and Economics Discussion Series 2020-045, Board of Governors of the Federal Reserve System (U.S.).
• Hie Joo Ahn & Yun Liu & Yeonwoo Rho, 2020. "Revealing Cluster Structures Based on Mixed Sampling Frequencies," Finance and Economics Discussion Series 2020-082, Board of Governors of the Federal Reserve System (U.S.).
• Andrew C. Chang & Trace J. Levinson, 2020. "Raiders of the Lost High-Frequency Forecasts: New Data and Evidence on the Efficiency of the Fed's Forecasting," Finance and Economics Discussion Series 2020-090, Board of Governors of the Federal Reserve System (U.S.).
• , 2020. "Looking down the road with ALEX: Forecasting U.S. GDP," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue 447, pages 1-5, October.
• Daniel Aaronson & Scott A. Brave & R. Andrew Butters & Daniel Sacks & Boyoung Seo, 2020. "Using the Eye of the Storm to Predict the Wave of Covid-19 UI Claims," Working Paper Series WP-2020-10, Federal Reserve Bank of Chicago, revised 16 Apr 2020.
  • Daniel Aaronson & Scott A. Brave & R. Andrew Butters & Daniel W. Sacks & Boyoung Seo, 2020. "Using the Eye of the Storm to Predict the Wave of Covid-19 UI Claims," Working Paper Series WP 2020-10, Federal Reserve Bank of Chicago.
• Scott A. Brave & R. Andrew Butters & Michael Fogarty, 2020. "The perils of working with Big Data and a SMALL framework you can use to avoid them," Working Paper Series WP-2020-35, Federal Reserve Bank of Chicago, revised 02 Mar 2020.
• Daniel Aaronson & Scott A. Brave & R. Andrew Butters & Daniel W. Sacks & Boyoung Seo, 2020. "Using the Eye of the Storm to Predict the Wave of Covid-19 UI Claims," Working Paper Series WP 2020-10, Federal Reserve Bank of Chicago.
  • Daniel Aaronson & Scott A. Brave & R. Andrew Butters & Daniel Sacks & Boyoung Seo, 2020. "Using the Eye of the Storm to Predict the Wave of Covid-19 UI Claims," Working Paper Series WP-2020-10, Federal Reserve Bank of Chicago, revised 16 Apr 2020.
• , 2020. "Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data," Research Working Paper RWP 20-09, Federal Reserve Bank of Kansas City.
• Galvao, Ana Beatriz & Owyang, Michael, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," EMF Research Papers 38, Economic Modelling and Forecasting Group.
  • Ana B. Galvão & Michael T. Owyang, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," Working Papers 2020-028, Federal Reserve Bank of St. Louis, revised Apr 2022.
• Michael W. McCracken, 2020. "Tests of Conditional Predictive Ability: Existence, Size, and Power," Working Papers 2020-050, Federal Reserve Bank of St. Louis.
• Daniel J. Lewis & Karel Mertens & James H. Stock, 2020. "Monitoring Real Activity in Real Time: The Weekly Economic Index," Liberty Street Economics 20200330b, Federal Reserve Bank of New York.
• Dean Croushore & Stephanie M. Wilshusen, 2020. "Forecasting Consumption Spending Using Credit Bureau Data," Working Papers 20-22, 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.
  • Schorfheide, Frank & Song, Dongo, 2021. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," CEPR Discussion Papers 16760, C.E.P.R. Discussion Papers.
  • 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, 2021. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," NBER Working Papers 29535, National Bureau of Economic Research, Inc.
• Ryan Cumings-Menon & Minchul Shin, 2020. "Probability Forecast Combination via Entropy Regularized Wasserstein Distance," Working Papers 20-31/R, Federal Reserve Bank of Philadelphia.
• Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
  • Fabrizio Cipollini & Giampiero Gallo & Alessandro Palandri, 2020. "A Dynamic Conditional Approach to Portfolio Weights Forecasting," Econometrics Working Papers Archive 2020_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
• Ludovic Dobbelaere & Igor Lebrun, 2020. "WP 05-20 - Évaluation de la précision des prévisions à court terme et des perspectives à moyen terme du BFP - Une mise à jour des Working Papers 12-17 et 13-17 [WP 05-20 - Evaluatie van de nauwkeur," Working Papers 2005, Federal Planning Bureau, Belgium.
• Lucian Liviu Albu & Radu Lupu, 2020. "Anomaly detection in stock market indices with neural networks," Journal of Financial Studies, Institute of Financial Studies, vol. 9(5), pages 10-23, November.
• Tsukhlo Sergey, 2020. "Russian industrial sector in 2019: (based on surveys’ findings)," Published Papers ppaper-2020-1047, Gaidar Institute for Economic Policy, revised 2020.
• Barinova Vera & Zemtsov Tsepan & Tsareva Yulia, 2020. "Small and medium-sized entrepreneurship in Russia and regions in 2019–2020," Published Papers ppaper-2020-1052, Gaidar Institute for Economic Policy, revised 2020.
• Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
  • Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2019. "Focused Bayesian Prediction," Papers 1912.12571, arXiv.org, revised Aug 2020.
  • Ruben Loaiza-Maya & Gael M Martin & David T. Frazier, 2020. "Focused Bayesian Prediction," Monash Econometrics and Business Statistics Working Papers 1/20, Monash University, Department of Econometrics and Business Statistics.
• Natalia Bailey & Zvi Hochman & Yufeng Mao & Mervyn J. Silvapulle & Param Silvapulle, 2020. "Statistical Modelling and Forecast Evaluation of the Impact of Extreme Temperatures on Wheat Crops in North Western Victoria," Monash Econometrics and Business Statistics Working Papers 18/20, Monash University, Department of Econometrics and Business Statistics.
• Sium Bodha Hannadige & Jiti Gao & Mervyn J. Silvapulle & Param Silvapulle, 2020. "Forecasting a Nonstationary Time Series with a Mixture of Stationary and Nonstationary Factors as Predictors," Monash Econometrics and Business Statistics Working Papers 19/20, Monash University, Department of Econometrics and Business Statistics.
• George Athanasopoulos & Nikolaos Kourentzes, 2020. "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers 2/20, Monash University, Department of Econometrics and Business Statistics.
• Martin, Gael M. & Loaiza-Maya, Rubén & Maneesoonthorn, Worapree & Frazier, David T. & Ramírez-Hassan, Andrés, 2022. "Optimal probabilistic forecasts: When do they work?," International Journal of Forecasting, Elsevier, vol. 38(1), pages 384-406.
  • Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
  • Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
• Michael Cai & Marco Del & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2021. "Online estimation of DSGE models," Econometrics Journal, Royal Economic Society, vol. 24(1), pages 33-58.
  • Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," PIER Working Paper Archive 19-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Michael D. Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," NBER Working Papers 26826, National Bureau of Economic Research, Inc.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Staff Reports 893, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Liberty Street Economics 20190821, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," Finance and Economics Discussion Series 2020-023, Board of Governors of the Federal Reserve System (U.S.).
• 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.
• Jacob Boudoukh & Ronen Israel & Matthew P. Richardson, 2020. "Biases in Long-Horizon Predictive Regressions," NBER Working Papers 27410, National Bureau of Economic Research, Inc.
• Acharya, Viral V. & Bhadury, Soumya & Surti, Jay, 2020. "Financial Vulnerability and Risks to Growth in Emerging Markets," CEPR Discussion Papers 14962, 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.
• Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," PIER Working Paper Archive 20-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," NBER Working Papers 28228, National Bureau of Economic Research, Inc.
  • Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers 1912.10774, arXiv.org, revised Jul 2021.
  • Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Working Paper Series 2020-02, Federal Reserve Bank of San Francisco.
• Anton A. Gerunov, 2020. "Machine Learning Algorithms For Forecasting Asset Prices: An Application To The Housing Market," Economics and Management, Faculty of Economics, SOUTH-WEST UNIVERSITY "NEOFIT RILSKI", BLAGOEVGRAD, vol. 17(1), pages 27-42.
• Branimir Cvitko Cicvarić, 2020. "Volatility of Cryptocurrencies," Notitia - journal for economic, business and social issues, Notitia Ltd., vol. 1(6), pages 13-23, December.
• Bhattacharya, Rudrani & Kapoor, Mrigankshi, 2020. "Forecasting Consumer Price Index Inflation in India: Vector Error Correction Mechanism Vs. Dynamic Factor Model Approach for Non-Stationary Time Series," Working Papers 20/323, National Institute of Public Finance and Policy.
• Mukherjee, Sacchidananda, 2020. "Pandemic and GST Revenue: An Assessment for Union and States," Working Papers 20/327, National Institute of Public Finance and Policy.
• Vianney Costemalle, 2020. "Bayesian Probabilistic Population Projections for France," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 520-521, pages 29-47.
• Galvão, Ana Beatriz & Lopresto, Marta, 2020. "Real-Time Probabilistic Nowcasts Of Uk Quarterly Gdp Growth Using A Mixed-Frequency Bottom-Up Approach," National Institute Economic Review, Cambridge University Press, vol. 254, pages 1-11, November.
  • Ana Beatriz Galvão & Marta Lopresto, 2020. "Real-time Probabilistic Nowcasts of UK Quarterly GDP Growth using a Mixed-Frequency Bottom-up Approach," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-06, Economic Statistics Centre of Excellence (ESCoE).
• Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2020. "Computationally efficient inference in large Bayesian mixed frequency VARs," Economics Letters, Elsevier, vol. 191(C).
  • Deborah Gefang & Gary Koop & Aubrey Poon, "undated". "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Discussion Papers in Economics 20/02, Division of Economics, School of Business, University of Leicester.
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
• Nicolas Woloszko, 2020. "Adaptive Trees: a new approach to economic forecasting," OECD Economics Department Working Papers 1593, OECD Publishing.
• Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.
• Raphaela Hyee & Herwig Immervoll & Rodrigo Fernandez & Jongmi Lee, 2020. "How reliable are social safety nets?: Value and accessibility in situations of acute economic need," OECD Social, Employment and Migration Working Papers 252, OECD Publishing.
• Jan Sebo & Daniela Dankova & Ivan Kralik, 2020. "Projecting A Life-Cycle Income - A Simulation Model For The Slovak Pension Benefit Statement," OLSZTYN ECONOMIC JOURNAL, University of Warmia and Mazury in Olsztyn, Faculty of Economic Sciences, vol. 15(4), pages 271-284, December.
• Wilde, Joshua & Chen, Wei & Lohmann, Sophie, 2020. "COVID-19 and the Future of US Fertility: What Can We Learn from Google?," IZA Discussion Papers 13776, Institute of Labor Economics (IZA).
  • Wilde, Joshua & Chen, Wei & Lohmann, Sophie, 2020. "COVID-19 and the Future of US Fertility: What Can We Learn from Google?," SocArXiv 2bgqs, Center for Open Science.
  • Joshua Wilde & Wei Chen & Sophie Lohmann, 2020. "COVID-19 and the future of US fertility: what can we learn from Google?," MPIDR Working Papers WP-2020-034, Max Planck Institute for Demographic Research, Rostock, Germany.
• 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.
  • Schorfheide, Frank & Song, Dongo, 2021. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," CEPR Discussion Papers 16760, C.E.P.R. Discussion Papers.
  • 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.
  • Frank Schorfheide & Dongho Song, 2021. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," NBER Working Papers 29535, National Bureau of Economic Research, Inc.
• 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.
• Angelo Gabrielle Santos, 2020. "Forecasting Residential electricity demand in the Philippines using an Error Correction Model," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 57(1), pages 121-151, June.
• 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, 2018. "Bayesian dynamic variable selection in high dimensions," Papers 1809.03031, arXiv.org, revised May 2020.
  • Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
  • Gary Koop & Dimitris Korobilis, 2020. "Bayesian dynamic variable selection in high dimensions," Working Papers 2020_11, Business School - Economics, University of Glasgow.
• 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.
  • 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," Discussion Papers 2007, School of Economics and Finance, Massey University, New Zealand.
• 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.
• Mr. Manuk Ghazanchyan & Vibha Nanda & Alex Ho & Mr. Bas B. Bakker, 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?," JRFM, MDPI, 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.
• Fulvia Pennoni & Francesco Bartolucci & Gianfranco Forte & Ferdinando Ametrano, 2022. "Exploring the dependencies among main cryptocurrency log‐returns: A hidden Markov model," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(1), February.
  • 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.
• Tinoco, Marcos, 2020. "Modelando la volatilidad del diferencial TED: Una evaluación de pronósticos de modelos con heterocedasticidad condicional [Modeling the volatility of the TED spread: An assessment of model forecast," MPRA Paper 108086, University Library of Munich, Germany.
• Maiorova, Ksenia & Fokin, Nikita, 2020. "Наукастинг Темпов Роста Стоимостных Объемов Экспорта И Импорта По Товарным Группам [Nowcasting the growth rates of the export and import by commodity groups]," MPRA Paper 109557, University Library of Munich, Germany.
• Nguyen, Phong Thanh, 2020. "Application Machine Learning in Construction Management," MPRA Paper 109899, University Library of Munich, Germany, revised 01 Aug 2021.
• Vîntu, Denis, 2020. "Relegating - The GDP Structural Modelling Strategy, The Dynamics in Time-Series Data: Short-Run Shocks, Disequilibrium Shocks and Innovative Shocks to Nuisance," MPRA Paper 112857, University Library of Munich, Germany, revised 30 Sep 2020.
• Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," Papers 2009.03394, arXiv.org, revised Jul 2021.
  • Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," CERGE-EI Working Papers wp677, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
• Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
• Alexandros Botsis & Christoph Görtz & Plutarchos Sakellaris, 2020. "Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts," CESifo Working Paper Series 8148, CESifo.
• Lahiri, Kajal & Zhao, Yongchen, 2020. "The Nordhaus test with many zeros," Economics Letters, Elsevier, vol. 193(C).
  • Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," Working Papers 2020-05, Towson University, Department of Economics, revised Jun 2020.
  • Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," CESifo Working Paper Series 8350, CESifo.
• Benedikt Janzen & Doina Radulescu, 0. "Electricity Use as a Real-Time Indicator of the Economic Burden of the COVID-19-Related Lockdown: Evidence from Switzerland," CESifo Economic Studies, CESifo, vol. 66(4), pages 303-321.
  • Benedikt Janzen & Doina Radulescu, 2020. "Electricity Use as a Real Time Indicator of the Economic Burden of the COVID-19-Related Lockdown: Evidence from Switzerland," Diskussionsschriften dp2010, Universitaet Bern, Departement Volkswirtschaft.
  • 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.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks," Globalization Institute Working Papers 394, Federal Reserve Bank of Dallas, revised 17 Apr 2021.
  • Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks," CESifo Working Paper Series 8475, CESifo.
• Constantin Bürgi & Nisan Gorgulu, 2020. "Social Distancing and the Economic Impact of Covid-19 in the United States," CESifo Working Paper Series 8577, CESifo.
• Ahmed, R. & Pesaran, M. H., 2020. "Regional Heterogeneity and U.S. Presidential Elections," Cambridge Working Papers in Economics 2092, Faculty of Economics, University of Cambridge.
  • Rashad Ahmed & M. Hashem Pesaran, 2020. "Regional Heterogeneity and U.S. Presidential Elections," CESifo Working Paper Series 8615, CESifo.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Paper 2020/14, Norges Bank.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Papers No 08/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate risk and commodity currencies," Working Paper 2020/18, Norges Bank.
  • Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate Risk and Commodity Currencies," CESifo Working Paper Series 8788, CESifo.
  • Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate Risk and Commodity Currencies," Working Papers No 10/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87, March.
• 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.
  • Claudia Foroni & Massimiliano Marcellino & Dalibor Stevanovic, 2020. "Forecasting the Covid-19 Recession and Recovery: Lessons from the Financial Crisis," CIRANO Working Papers 2020s-32, CIRANO.
  • Foroni, Claudia & Marcellino, Massimiliano & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
• Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022. "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 379-405, February.
  • 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, 2021. "Modeling Electricity Price and Quantity Uncertainty: An Application for Hedging with Forward Contracts," Energies, MDPI, vol. 14(11), pages 1-26, June.
  • 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.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
  • Ganics, Gergely & Rossi, Barbara & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Forecasts," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
  • Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: obtaining measures of multi-horizon uncertainty from survey density forecasts," Working Papers 1947, Banco de España.
  • Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2020. "From Fixed-Event to Fixed-Horizon Density Forecasts: Obtaining Measures of Multi-Horizon Uncertainty from Survey Density Forecasts," Working Papers 1142, Barcelona Graduate School of Economics.
• 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.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Working Papers hal-03403077, HAL.
  • 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).
• 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.
  • 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.
  • 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.
• 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.
  • Acharya, Viral V. & Bhadury, Soumya & Surti, Jay, 2020. "Financial Vulnerability and Risks to Growth in Emerging Markets," CEPR Discussion Papers 14962, C.E.P.R. Discussion Papers.
• Hsu, Po-Hsuan & Taylor, Mark P & Wang, Zigan, 2020. "The Out-of-Sample Performance of Carry Trades," CEPR Discussion Papers 15052, C.E.P.R. Discussion Papers.
• Delle-Monache, Davide & De-Polis, Andrea & Petrella, Ivan, 2020. "Modelling and Forecasting Macroeconomic Downside Risk," EMF Research Papers 34, Economic Modelling and Forecasting Group.
  • 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.
  • 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.
• 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.
  • Foroni, Claudia & Marcellino, Massimiliano & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
  • Claudia Foroni & Massimiliano Marcellino & Dalibor Stevanovic, 2020. "Forecasting the Covid-19 Recession and Recovery: Lessons from the Financial Crisis," CIRANO Working Papers 2020s-32, CIRANO.
• Odendahl, Florens & Rossi, Barbara & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.

2019

• Hylke Vandenbussche & William Connell & Wouter Simons, 2019. "Global Value Chains, Trade Shocks and Jobs: An Application to Brexit," CESifo Working Paper Series 7473, CESifo.
• Delli Gatti, Domenico & Grazzini, Jakob, 2020. "Rising to the challenge: Bayesian estimation and forecasting techniques for macroeconomic Agent Based Models," Journal of Economic Behavior & Organization, Elsevier, vol. 178(C), pages 875-902.
  • Domenico Delli Gatti & Jakob Grazzini, 2019. "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series 7894, CESifo.
• Paul Schneider, 2019. "A Theory of Scenario Generation," Swiss Finance Institute Research Paper Series 19-17, Swiss Finance Institute.
• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019. "A Flexible Regime Switching Model for Asset Returns," Swiss Finance Institute Research Paper Series 19-27, Swiss Finance Institute, revised May 2019.
• Rebecca Westphal & Didier Sornette, 2019. "Market Impact and Performance of Arbitrageurs of Financial Bubbles in An Agent-Based Model," Swiss Finance Institute Research Paper Series 19-29, Swiss Finance Institute.
• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019. "A Non-Elliptical Orthogonal GARCH Model for Portfolio Selection under Transaction Costs," Swiss Finance Institute Research Paper Series 19-51, Swiss Finance Institute.
• Dalibor Stevanovic & Stéphane Surprenant & Philippe Goulet Coulombe, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
• Mateo Dulce Rubio, 2019. "Predicting criminal behavior with Lévy flights using real data from Bogotá," Documentos CEDE 017198, Universidad de los Andes - CEDE.
• Trespalacios, Alfredo & Cortés, Lina M. & Perote, Javier, 2020. "Uncertainty in electricity markets from a semi-nonparametric approach," Energy Policy, Elsevier, vol. 137(C).
  • Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2019. "Uncertainty in Electricity Markets from a seminonparametric Approach," Documentos de Trabajo CIEF 017304, Universidad EAFIT.
• Luis Sánchez & Karina Caballero, 2019. "La curva de Kuznets ambiental y su relación con el cambio climático en América Latina y el Caribe: un análisis de cointegración con panel, 1980-2015," Revista de Economía del Rosario, Universidad del Rosario, vol. 22(1), pages 101-142, June.
• Juan Pablo Alfonso Zorro, 2019. "Efectos de las variaciones del IPC en las decisiones financieras," Econógrafos - Escuela de Economía 017329, Universidad Nacional de Colombia -FCE - CID.
• Pérez García, Jorge Iván & Lopera Castaño, Mauricio & Vásquez Bedoya, Fredy Alonso, 2019. "Una breve aplicación a la predicción de la fragilidad de empresas colombianas, mediante el uso de modelos estadísticos," Borradores Departamento de Economía 017525, Universidad de Antioquia - CIE.
• José Manuel Leguizamón Tiusabá & José Manuel Leguizamón Tiusabá, 2019. "Estímulos tributarios y hotelería en Colombia," Revista Economía y Región, Universidad Tecnológica de Bolívar, vol. 13(1), pages 177-198, June.
• Mateo Dulce Rubio, 2019. "Predicting criminal behavior with Levy flights using real data from Bogota," Documentos de Trabajo Quantil 017347, Quantil.
• Bekaert, Geert & Panayotov, George, 2020. "Good Carry, Bad Carry," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(4), pages 1063-1094, June.
  • Geert Bekaert & George Panayotov, 2019. "Good Carry, Bad Carry," NBER Working Papers 25420, National Bureau of Economic Research, Inc.
  • Bekaert, Geert & Panayotov, George, 2019. "Good Carry, Bad Carry," CEPR Discussion Papers 13463, C.E.P.R. Discussion Papers.
• Arash Aloosh & Geert Bekaert, 2019. "Currency Factors," NBER Working Papers 25449, National Bureau of Economic Research, Inc.
  • Aloosh, Arash & Bekaert, Geert, 2019. "Currency Factors," CEPR Discussion Papers 13464, C.E.P.R. Discussion Papers.
• Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2018. "The global component of inflation volatility," Temi di discussione (Economic working papers) 1170, Bank of Italy, Economic Research and International Relations Area.
  • Carriero, Andrea & Corsello, Francesco & Marcellino, Massimiliano, 2019. "The Global Component of Inflation Volatility," CEPR Discussion Papers 13470, C.E.P.R. Discussion Papers.
• 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.
  • 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.
• 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, 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.
  • 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.
  • 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.
• Michael Brei & Claudio Borio & Leonardo Gambacorta, 2020. "Bank intermediation activity in a low‐interest‐rate environment," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 49(2), July.
  • Michael Brei & Claudio Borio, 2019. "Bank intermediation activity in a low interest rate environment," BIS Working Papers 807, Bank for International Settlements.
  • Borio, Claudio & Brei, Michael & Gambacorta, Leonardo, 2019. "Bank intermediation activity in a low interest rate environment," CEPR Discussion Papers 13980, C.E.P.R. Discussion Papers.
  • Michael Brei & Claudio Borio & Leonardo Gambacorta, 2020. "Bank intermediation activity in a low‐interest‐rate environment," Post-Print hal-02985986, HAL.
• 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, vol. 39(4), pages 1054-1065, October.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," EMF Research Papers 29, Economic Modelling and Forecasting Group.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," CEPR Discussion Papers 14107, C.E.P.R. Discussion Papers.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers) 1296, Bank of Italy, Economic Research and International Relations Area.
  • Delle Monache, Davide & Venditti, Fabrizio & Petrella, Ivan, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Working Paper Series 2369, European Central Bank.
• Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.
• Bunjira Makond & Mayuening Eso, 2019. "Predictive Models for Classifying the Outcomes of Violence Case Study for Thailand’s Deep South," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(3), pages 56-92, September.
• Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
• Søren Kjærgaard & Yunus Emre Ergemen & Malene Kallestrup-Lamb & Jim Oeppen & Rune Lindahl-Jacobsen, 2019. "Forecasting Causes of Death using Compositional Data Analysis: the Case of Cancer Deaths," CREATES Research Papers 2019-07, Department of Economics and Business Economics, Aarhus University.
• Søren Kjærgaard & Yunus Emre Ergemen & Marie-Pier Bergeron Boucher & Jim Oeppen & Malene Kallestrup-Lamb, 2019. "Longevity forecasting by socio-economic groups using compositional data analysis," CREATES Research Papers 2019-08, Department of Economics and Business Economics, Aarhus University.
• Daniel Borup & Erik Christian Montes Schütte, 2019. "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers 2019-13, Department of Economics and Business Economics, Aarhus University.
• Kristoffer Pons Bertelsen, 2019. "Comparing Tests for Identification of Bubbles," CREATES Research Papers 2019-16, Department of Economics and Business Economics, Aarhus University.
• Malene Kallestrup-Lamb & Søren Kjærgaard & Carsten P. T. Rosenskjold, 2019. "Insight into Stagnating Life Expectancy: Analysing Cause of Death Patterns across Socio-economic Groups," CREATES Research Papers 2019-20, Department of Economics and Business Economics, Aarhus University.
• 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).
  • Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2019. "Modeling, Forecasting, and Nowcasting U.S. CO2 Emissions Using Many Macroeconomic Predictors," CREATES Research Papers 2019-21, Department of Economics and Business Economics, Aarhus University.
• Asongu, Simplice & Nnanna, Joseph, 2019. "Foreign aid, instability and governance in Africa," MPRA Paper 101087, University Library of Munich, Germany.
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Research Africa Network Working Papers 19/022, Research Africa Network (RAN).
  • Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Foreign aid, instability and governance in Africa," Working Papers 19/022, European Xtramile Centre of African Studies (EXCAS).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Working Papers of the African Governance and Development Institute. 19/022, African Governance and Development Institute..
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," CEREDEC Working Papers 19/022, Centre de Recherche pour le Développement Economique (CEREDEC).
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Sarthak Behera & Hyeongwoo Kim, 2019. "Forecasting Dollar Real Exchange Rates and the Role of Real Activity Factors," Auburn Economics Working Paper Series auwp2019-04, Department of Economics, Auburn University.
• Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Working Papers of the African Governance and Development Institute. 19/022, African Governance and Development Institute..
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," CEREDEC Working Papers 19/022, Centre de Recherche pour le Développement Economique (CEREDEC).
  • Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Foreign aid, instability and governance in Africa," Working Papers 19/022, European Xtramile Centre of African Studies (EXCAS).
  • Asongu, Simplice & Nnanna, Joseph, 2019. "Foreign aid, instability and governance in Africa," MPRA Paper 101087, University Library of Munich, Germany.
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Research Africa Network Working Papers 19/022, Research Africa Network (RAN).
• T. Bazhenov & D. Fantazzini, 2019. "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," Russian Journal of Industrial Economics, MISiS.
  • Bazhenov, Timofey & Fantazzini, Dean, 2019. "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," MPRA Paper 93544, University Library of Munich, Germany.
• Ali Babikir & Mohammed Elamin Hassan & Henry Mwambi, 2019. "Asymmetry, Fat-tail and Autoregressive Conditional Density in Daily Stocks Return Data," Annals of Economics and Statistics, GENES, issue 135, pages 57-68.
• Lukas Kremens & Ian Martin, 2019. "The Quanto Theory of Exchange Rates," American Economic Review, American Economic Association, vol. 109(3), pages 810-843, March.
  • Kremens, Lukas & Martin, Ian, 2017. "The Quanto Theory of Exchange Rates," CEPR Discussion Papers 11970, C.E.P.R. Discussion Papers.
  • Kremens, Lukas & Martin, Ian, 2019. "The quanto theory of exchange rates," LSE Research Online Documents on Economics 89839, London School of Economics and Political Science, LSE Library.
• Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2019. "Vulnerable Growth," American Economic Review, American Economic Association, vol. 109(4), pages 1263-1289, April.
  • Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2016. "Vulnerable growth," Staff Reports 794, Federal Reserve Bank of New York.
  • Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2018. "Vulnerable Growth," Liberty Street Economics 20180409, Federal Reserve Bank of New York.
  • Nina Boyarchenko & Domenico Giannone & Tobias Adrian, 2017. "Vulnerable Growth," 2017 Meeting Papers 1317, Society for Economic Dynamics.
  • Adrian, Tobias & Boyarchenko, Nina & Giannone, Domenico, 2016. "Vulnerable Growth," CEPR Discussion Papers 11583, C.E.P.R. Discussion Papers.
• Daniel J. Wilson, 2019. "Clearing the Fog: The Predictive Power of Weather for Employment Reports and Their Asset Price Responses," American Economic Review: Insights, American Economic Association, vol. 1(3), pages 373-388, December.
  • Daniel J. Wilson, 2017. "Clearing the Fog: The Predictive Power of Weather for Employment Reports and their Asset Price Responses," Working Paper Series 2017-13, Federal Reserve Bank of San Francisco.
• Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2019. "The Impact of Big Data on Firm Performance: An Empirical Investigation," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 33-37, May.
  • Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2018. "The Impact of Big Data on Firm Performance: An Empirical Investigation," NBER Working Papers 24334, National Bureau of Economic Research, Inc.
• 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, vol. 1(1), pages 327-336, November.
• Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Research Africa Network Working Papers 19/022, Research Africa Network (RAN).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," Working Papers of the African Governance and Development Institute. 19/022, African Governance and Development Institute..
  • Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Foreign aid, instability and governance in Africa," Working Papers 19/022, European Xtramile Centre of African Studies (EXCAS).
  • Simplice A. Asongu & Joseph Nnanna, 2019. "Foreign aid, instability and governance in Africa," CEREDEC Working Papers 19/022, Centre de Recherche pour le Développement Economique (CEREDEC).
  • Asongu, Simplice & Nnanna, Joseph, 2019. "Foreign aid, instability and governance in Africa," MPRA Paper 101087, University Library of Munich, Germany.
• Tomasz Serafin & Bartosz Uniejewski & Rafał Weron, 2019. "Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 12(13), pages 1-12, July.
  • Tomasz Serafin & Bartosz Uniejewski & Rafal Weron, 2019. "Averaging predictive distributions across calibration windows for day-ahead electricity price forecasting," WORking papers in Management Science (WORMS) WORMS/19/08, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, revised 06 Jul 2019.
• Bunjira Makond & Mayuening Eso, 2019. "Predictive Models for Classifying the Outcomes of Violence Case Study for Thailand’s Deep South," International Association of Decision Sciences, Asia University, Taiwan, vol. 23(3), pages 56-92, September.
• Nuno Goncalves & Domingos Seward, 2019. "Forecasting unemployment in Portugal: A labour market flows approach," CFP Working Papers 01/2019, Portuguese Public Finance Council.
• 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, vol. 1(1), pages 190-211, March.
• Anindya Banerjee & Victor Bystrov & Paul Mizen, 2017. "Structural Factor Analysis of Interest Rate Pass Through In Four Large Euro Area Economies," Working Papers in Economics 17/07, University of Canterbury, Department of Economics and Finance.
  • Anindya Banerjee & Victor Bystrov & Paul Mizen, 2019. "Structural Factor Analysis of Interest Rate Pass Through in Four Large Euro Area Economies," Lodz Economics Working Papers 1/2019, University of Lodz, Faculty of Economics and Sociology.
• 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 #2019-4, National Bank of Kazakhstan.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "lassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, Institute of Labor Economics (IZA).
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
• 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, 2019. "Bayesian MIDAS penalized regressions: estimation, selection, and prediction," Working papers 713, Banque de France.
  • Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
  • Matteo Mogliani & Anna Simoni, 2019. "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers 1903.08025, arXiv.org, revised Jun 2020.
• 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), vol. 19(1), pages 363-381, December.
  • Ali Habibnia & Esfandiar Maasoumi, 2019. "Forecasting in Big Data Environments: an Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet)," Papers 1904.11145, arXiv.org.
• Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jun 2021.
  • Dimitriadis, Timo & Patton, Andrew J. & Schmidt, Patrick W., 2020. "Testing forecast rationality for measures of central tendency," Hohenheim Discussion Papers in Business, Economics and Social Sciences 12-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
• Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  • Junjie Hu & Wolfgang Karl Hardle & Weiyu Kuo, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," Papers 1912.05228, arXiv.org, revised Dec 2021.
• Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," PIER Working Paper Archive 20-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers 1912.10774, arXiv.org, revised Jul 2021.
  • Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Working Paper Series 2020-02, Federal Reserve Bank of San Francisco.
  • Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," NBER Working Papers 28228, National Bureau of Economic Research, Inc.
• Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
  • Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2019. "Focused Bayesian Prediction," Papers 1912.12571, arXiv.org, revised Aug 2020.
  • Ruben Loaiza-Maya & Gael M Martin & David T. Frazier, 2020. "Focused Bayesian Prediction," Monash Econometrics and Business Statistics Working Papers 1/20, Monash University, Department of Econometrics and Business Statistics.
• Minjae Park & Mi Lim Lee & Jinpyo Lee, 2019. "Predicting Stock Market Indices Using Classification Tools," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 9(2), pages 243-256, February.
• Roland Fuess & Massimo Guidolin & Christian Koeppel, 2019. "Sentiment Risk Premia in the Cross-Section of Global Equity and Currency Returns," BAFFI CAREFIN Working Papers 19116, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Ekaterina Tzvetanova, 2019. "Adaptation of the Altman’s Corporate Insolvency Prediction Model – The Bulgarian Case," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 125-142.
• Tobias Hartl & Roland Weigand, 2018. "Multivariate Fractional Components Analysis," Papers 1812.09149, arXiv.org, revised Jan 2019.
  • Hartl, Tobias & Weigand, Roland, 2019. "Multivariate Fractional Components Analysis," University of Regensburg Working Papers in Business, Economics and Management Information Systems 38283, University of Regensburg, Department of Economics.
• Dany Brouillette & Marie-Noëlle Robitaille & Laurence Savoie-Chabot & Pierre St-Amant & Bassirou Gueye & Elise Martin, 2019. "The Trend Unemployment Rate in Canada: Searching for the Unobservable," Staff Working Papers 19-13, Bank of Canada.
• 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, pages 1-9.
• Gergely Ganics & Eva Ortega, 2019. "Banco de España macroeconomic projections: comparison with an econometric model," Economic Bulletin, Banco de España, issue SEP, pages 1-9.
• Luis Julián Álvarez, 2019. "El índice de precios de consumo: usos y posibles vías de mejora," Occasional Papers 1910, Banco de España.
• Mar Delgado-Téllez & Enrique Moral-Benito & Javier J. Pérez, 2019. "Outsourcing and public expenditure: an aggregate perspective with regional data," Working Papers 1939, Banco de España.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
  • Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: obtaining measures of multi-horizon uncertainty from survey density forecasts," Working Papers 1947, Banco de España.
  • Ganics, Gergely & Rossi, Barbara & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Forecasts," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
  • Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2020. "From Fixed-Event to Fixed-Horizon Density Forecasts: Obtaining Measures of Multi-Horizon Uncertainty from Survey Density Forecasts," Working Papers 1142, Barcelona Graduate School of Economics.
• Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
  • Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area," Working papers 733, Banque de France.
  • Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR forecasts, survey information and structural change in the euro area," Working Papers 1948, Banco de España.
• Franecsca Carta, 2019. "Timely indicators for labour income inequality," Questioni di Economia e Finanza (Occasional Papers) 503, Bank of Italy, Economic Research and International Relations Area.
• Angela Capolongo & Claudia Pacella, 2019. "Forecasting inflation in the euro area: countries matter!," Temi di discussione (Economic working papers) 1224, Bank of Italy, Economic Research and International Relations Area.
• Fabio Busetti & Michele Caivano & Davide Delle Monache, 2021. "Domestic and Global Determinants of Inflation: Evidence from Expectile Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 982-1001, August.
  • Fabio Busetti & Michele Caivano & Davide Delle Monache, 2019. "Domestic and global determinants of inflation: evidence from expectile regression," Temi di discussione (Economic working papers) 1225, Bank of Italy, Economic Research and International Relations Area.
• Valentina Aprigliano & Danilo Liberati, 2021. "Using Credit Variables to Date Business Cycle and to Estimate the Probabilities of Recession in Real Time," Manchester School, University of Manchester, vol. 89(S1), pages 76-96, September.
  • Valentina Aprigliano & Danilo Liberati, 2019. "Using credit variables to date business cycle and to estimate the probabilities of recession in real time," Temi di discussione (Economic working papers) 1229, Bank of Italy, Economic Research and International Relations Area.
• Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • 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, revised Jun 2021.
  • 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.
• 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.
  • González-Rivera, Gloria & Luo, Yun & Ruiz Ortega, Esther, 2019. "Prediction regions for interval-valued time series," DES - Working Papers. Statistics and Econometrics. WS 29054, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2019. "Prediction Regions for Interval-valued Time Series," Working Papers 201921, University of California at Riverside, Department of Economics.
• Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
• Guillaume MAROIS & Patrick SABOURIN & Alain BÉLANGER, 2019. "Forecasting Human Capital of EU Member Countries Accounting for Sociocultural Determinants," JODE - Journal of Demographic Economics, Cambridge University Press, vol. 85(3), pages 231-269, September.
• 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, vol. 42(119), pages 189-206, Mayo.
• Ibrahim D. Raheem & Kazeem Isah, 2019. "The Jolly Ride of International Reserves and Commodity Prices: Evidence from Predictive Models," Working Papers 063, Centre for Econometric and Allied Research, University of Ibadan.
• Elias A. Udeaja & Kazeem Isah, 2019. "Revisiting the accuracy of inflation forecasts in Nigeria: the oil price –exchange rate perspectives," Working Papers 065, Centre for Econometric and Allied Research, University of Ibadan.
• Fries, Sébastien & Zakoian, Jean-Michel, 2019. "Mixed Causal-Noncausal Ar Processes And The Modelling Of Explosive Bubbles," Econometric Theory, Cambridge University Press, vol. 35(6), pages 1234-1270, December.
  • Fries, Sébastien & Zakoian, Jean-Michel, 2017. "Mixed Causal-Noncausal AR Processes and the Modelling of Explosive Bubbles," MPRA Paper 81345, University Library of Munich, Germany.
• Voon, Derby & Fogarty, James, 2019. "A Note on Forecasting Alcohol Demand," Journal of Wine Economics, Cambridge University Press, vol. 14(2), pages 208-213, May.
• Barnett, William A. & Su, Liting, 2019. "Risk Adjustment Of The Credit-Card Augmented Divisia Monetary Aggregates," Macroeconomic Dynamics, Cambridge University Press, vol. 23(S1), pages 90-114, September.
  • Barnett, William & Su, Liting, 2016. "Risk Adjustment of the Credit-Card Augmented Divisia Monetary Aggregates," Studies in Applied Economics 67, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
  • William Barnett & Liting Su, 2016. "Risk Adjustment of the Credit-Card Augmented Divisia Monetary Aggregates," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201606, University of Kansas, Department of Economics, revised Aug 2016.
  • Barnett, William & Su, Liting, 2016. "Risk adjustment of the credit-card augmented Divisia monetary aggregates," MPRA Paper 73248, University Library of Munich, Germany.
• Colombo, Emilio & Pelagatti, Matteo, 2020. "Statistical learning and exchange rate forecasting," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1260-1289.
  • Emilio Colombo & Matteo Pelagatti, 2019. "Statistical Learning and Exchange Rate Forecasting," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo dis1901, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS).
• Konstantin A. Kholodilin & Claus Michelsen, 2019. "High Risk of a Housing Bubble in Germany and Most OECD Countries," DIW Weekly Report, DIW Berlin, German Institute for Economic Research, vol. 9(32), pages 265-273.
• Konstantin A. Kholodilin & Claus Michelsen, 2019. "Das Risiko einer Immobilienpreisblase ist in Deutschland sowie in den meisten OECD-Ländern hoch," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 86(32), pages 547-555.
• Niels Gilbert, 2019. "Euro area sovereign risk spillovers before and after the ECB's OMT announcement," DNB Working Papers 636, Netherlands Central Bank, Research Department.
• Page, Adrian & Lambrias, Kyriacos, 2019. "The performance of the Eurosystem/ECB staff macroeconomic projections since the financial crisis," Economic Bulletin Articles, European Central Bank, vol. 8.
• Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1658-1668.
  • Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: a multi-country BVAR benchmark for the Eurosystem projections," Working Paper Series 2227, European Central Bank.
• Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
• Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
• Chavleishvili, Sulkhan & Manganelli, Simone, 2019. "Forecasting and stress testing with quantile vector autoregression," Working Paper Series 2330, European Central Bank.
• de Bondt, Gabe & Gieseck, Arne & Herrero, Pablo & Zekaite, Zivile, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Research Technical Papers 15/RT/19, Central Bank of Ireland.
  • de Bondt, Gabe & Gieseck, Arne & Zekaite, Zivile & Herrero, Pablo, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Working Paper Series 2343, European Central Bank.
• Yao Thibaut Kpegli & Bator Anne, 2019. "Poisson-model Analysis of Power Alternation in Africa," International Journal of Economics and Financial Issues, Econjournals, vol. 9(1), pages 116-120.
  • Yao T. Kpegli & Anne Bator, 2019. "Poisson-model Analysis of Power Alternation in Africa," Post-Print halshs-02900779, HAL.
• Chin-Sheng Huang & Yi-Sheng Liu, 2019. "Machine Learning on Stock Price Movement Forecast: The Sample of the Taiwan Stock Exchange," International Journal of Economics and Financial Issues, Econjournals, vol. 9(2), pages 189-201.
• Mariem Talbi & Amel Ben Halima, 2019. "Global Contagion of Investor Sentiment during the US Subprime Crisis: The Case of the USA and the Region of Latin America," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 163-174.
• Arindam Banerjee, 2019. "Forecasting of India VIX as a Measure of Sentiment," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 268-276.
• Chia-Cheng Chen & Yisheng Liu & Ting-Hsin Hsu, 2019. "An Analysis on Investment Performance of Machine Learning: An Empirical Examination on Taiwan Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 1-10.
• Nájera Salmerón, Jorge Alberto, 2019. "Relaciones en el comportamiento de los precios de las criptomonedas: un análisis econométrico a través de modelos VAR y VEC / Relationship in the Cryptocurrencies Price Behavior: An Econometric Analys," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 9(1), pages 33-61, enero-jun.
• Cristófoli, María Elizabeth & García Fronti, Javier, 2019. "Macroeconomic Reverse Stress Testing: An Early-Warning System for Spanish Banking Regulators. Analysis Based on the 2008 Global Financial Crisis / Prueba de resistencia inversa Macroeconómica: una pru," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 9(2), pages 181-204, julio-dic.
• Zeineb Affes & Rania Hentati-Kaffel, 2019. "Forecast bankruptcy using a blend of clustering and MARS model: case of US banks," Annals of Operations Research, Springer, vol. 281(1), pages 27-64, October.
• James P. LeSage & Daniel Hendrikz, 2019. "Large Bayesian vector autoregressive forecasting for regions: A comparison of methods based on alternative disturbance structures," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 563-599, June.
• Henryk Gurgul & Łukasz Lach, 2019. "On approximating the accelerator part in dynamic input–output models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(1), pages 219-239, March.
• Asmerilda Hitaj & Lorenzo Mercuri & Edit Rroji, 2019. "Lévy CARMA models for shocks in mortality," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 205-227, June.
• Jonathan Haynes & Daniel Schmitt & Lukas Grimm, 2019. "Estimating stochastic volatility: the rough side to equity returns," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 449-469, December.
• Bahar Şen Doğan & Murat Midiliç, 2019. "Forecasting Turkish real GDP growth in a data-rich environment," Empirical Economics, Springer, vol. 56(1), pages 367-395, January.
• Silvija Vlah Jerić & Mihovil Anđelinović, 2019. "Evaluating Croatian stock index forecasts," Empirical Economics, Springer, vol. 56(4), pages 1325-1339, April.
• Natalia Ponomareva & Jeffrey Sheen & Ben Zhe Wang, 2019. "The common component of bilateral US exchange rates: to what is it related?," Empirical Economics, Springer, vol. 56(4), pages 1251-1268, April.
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019. "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, vol. 57(3), pages 923-955, September.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2016. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," MPRA Paper 76308, University Library of Munich, Germany.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," ETA: Economic Theory and Applications 253725, Fondazione Eni Enrico Mattei (FEEM).
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2018. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Papers 1804.08315, arXiv.org.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Working Papers 2017.06, Fondazione Eni Enrico Mattei.
• Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.
• Cees Diks & Cars Hommes & Juanxi Wang, 2019. "Critical slowing down as an early warning signal for financial crises?," Empirical Economics, Springer, vol. 57(4), pages 1201-1228, October.
  • Diks, C.G.H. & Hommes, C.H. & Wang, J., 2015. "Critical Slowing Down as Early Warning Signals for Financial Crises?," CeNDEF Working Papers 15-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
• Paul Lehmann & Jos Sijm & Erik Gawel & Sebastian Strunz & Unnada Chewpreecha & Jean-Francois Mercure & Hector Pollitt, 2019. "Addressing multiple externalities from electricity generation: a case for EU renewable energy policy beyond 2020?," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 21(2), pages 255-283, April.
• Antonio Fabio Forgione & Carlo Migliardo, 2019. "An empirical analysis of the impact of trade credit on bank debt restructuring," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 36(2), pages 415-438, July.
• Carlos Uribe-Teran & Santiago Mosquera, 2019. "Structural factors, global shocks and sovereign debt credit ratings," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(1), pages 104-126, January.
• Claveria, Oscar, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 53(1), pages 1-3.
  • Oscar Claveria, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-10, December.
• Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 433-446, June.
  • Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Post-Print hal-02155402, HAL.
• Balasubramaniam Meghanadh & Lagesh Aravalath & Bhupesh Joshi & Raghunathan Sathiamoorthy & Manish Kumar, 2019. "Imputation of Missing Values in the Fundamental Data: Using MICE Framework," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(3), pages 459-475, September.
• Rómulo A. Chumacero, 2019. "Skills versus Luck: Bolivia and its recent Bonanza," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 28(1), pages 1-27, December.
• Grant Allan & Gary Koop & Stuart McIntyre & Paul Smith, 2019. "Nowcasting Using Mixed Frequency Methods: An Application to the Scottish Economy," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 12-45, September.
• Aloisio Campelo & Ataman Ozyildirim & Jing Sima-Friedman & Paulo Picchetti & Sarah Piassi Machado Lima, 2019. "Coincident and Leading Indicators for Brazilian Cycles," Societies and Political Orders in Transition, in: Sergey Smirnov & Ataman Ozyildirim & Paulo Picchetti (ed.), Business Cycles in BRICS, pages 315-329, Springer.
• Paulo Picchetti, 2019. "A Bayesian Approach to Predicting Cycles Using Composite Indicators," Societies and Political Orders in Transition, in: Sergey Smirnov & Ataman Ozyildirim & Paulo Picchetti (ed.), Business Cycles in BRICS, pages 337-345, Springer.
• Atish Kumar Dash & Ataman Ozyildirim & Jing Sima-Friedman, 2019. "An Application of the Indicator Approach to Developing Coincident and Leading Economic Indexes for India," Societies and Political Orders in Transition, in: Sergey Smirnov & Ataman Ozyildirim & Paulo Picchetti (ed.), Business Cycles in BRICS, pages 377-392, Springer.
• João A. Bastos, 2019. "Forecasting the capacity of mobile networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(2), pages 231-242, October.
  • Bastos, João A., 2019. "Forecasting the capacity of mobile networks," MPRA Paper 92727, University Library of Munich, Germany.
• Moussa Wajdi, 2019. "The dynamic relationship between stock index and exchange rate: Evidence for Tunis," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 8(1), pages 1-4.
• Moussa Wajdi, 2019. "On the co-movements among Stock prices and exchange rates cointegration: a VAR/VECM approach," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 8(1), pages 1-5.
• Jaka Sriyana, 2019. "What drives economic growth sustainability? Evidence from Indonesia," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(2), pages 906-918, December.
• Milan Vyskrabka & Stanislav Tvrz & Martin Zeleznik, 2019. "PreMISE: DSGE Model of the Slovak Economy Integrated in a Monetary Union," Working and Discussion Papers WP 8/2019, Research Department, National Bank of Slovakia.
• Rachida Ouysse, 2017. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12, School of Economics, The University of New South Wales.
  • Rachida Ouysse, 2019. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12a, School of Economics, The University of New South Wales.
• 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.
  • 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.
  • 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.
• Lisa-Cheree Martin, 2019. "Machine Learning vs Traditional Forecasting Methods: An Application to South African GDP," Working Papers 12/2019, Stellenbosch University, Department of Economics.
• Diego Winkelried & Javier Torres, 2019. "Economic mobility along the business cycle. The case of Peru," Applied Economics, Taylor & Francis Journals, vol. 51(18), pages 1894-1906, April.
  • Diego Winkelried & Javier Torres, 2017. "Economic mobility along the business cycle. The case of Peru," Working Papers 2017-115, Peruvian Economic Association.
• Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2019. "Is there a role for uncertainty in forecasting output growth in OECD countries? Evidence from a time-varying parameter-panel vector autoregressive model," Applied Economics, Taylor & Francis Journals, vol. 51(33), pages 3624-3631, July.
  • Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2018. "Is There a Role for Uncertainty in Forecasting Output Growth in OECD Countries? Evidence from a Time Varying Parameter-Panel Vector Autoregressive Model," Working Papers 201823, University of Pretoria, Department of Economics.
• Florian Huber & Martin Feldkircher, 2019. "Adaptive Shrinkage in Bayesian Vector Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 27-39, January.
  • Florian Huber & Martin Feldkircher, 2016. "Adaptive shrinkage in Bayesian vector autoregressive models," Department of Economics Working Papers wuwp221, Vienna University of Economics and Business, Department of Economics.
  • Feldkircher, Martin & Huber, Florian, 2016. "Adaptive Shrinkage in Bayesian Vector Autoregressive Models," Department of Economics Working Paper Series 221, WU Vienna University of Economics and Business.
• James Mitchell & Donald Robertson & Stephen Wright, 2019. "R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 681-695, October.
  • Stephen Wright & James Mitchell & Donald Robertson, 2018. "R2 bounds for predictive models: what univariate properties tell us about multivariate predictability," Birkbeck Working Papers in Economics and Finance 1804, Birkbeck, Department of Economics, Mathematics & Statistics.
• Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.
  • Ying Chen & Wolfgang K. Härdle & Wee Song Chua, 2016. "Forecasting Limit Order Book Liquidity Supply-Demand Curves with Functional AutoRegressive Dynamics," SFB 649 Discussion Papers SFB649DP2016-025, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2020. "Crisis transmission: Visualizing vulnerability," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
  • Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2019. "Crisis transmission: visualizing vulnerability," Working Papers 2019-07, University of Tasmania, Tasmanian School of Business and Economics.
• Eda Gulsen & Hakan Kara, 2019. "Measuring inflation uncertainty in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 19(2), pages 33-43.
  • Eda Gulsen & Hakan Kara, 2019. "Measuring Inflation Uncertainty in Turkey," Working Papers 1912, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Eda Gulsen & Hakan Kara, 2019. "Measuring inflation uncertainty in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 19(2), pages 33-43.
  • Eda Gulsen & Hakan Kara, 2019. "Measuring Inflation Uncertainty in Turkey," Working Papers 1912, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Mehmet Selman Colak & Ibrahim Ethem Guney & Ahmet Senol & Muhammed Hasan Yilmaz, 2019. "Monitoring and Forecasting Cyclical Dynamics in Bank Credits: Evidence from Turkish Banking Sector," Working Papers 1929, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," NBER Working Papers 26569, National Bureau of Economic Research, Inc.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2021. "Forecasting with a Panel Tobit Model," Papers 2110.14117, arXiv.org.
• Andrada-Félix, Julián & Fernandez-Perez, Adrian & Sosvilla-Rivero, Simón, 2020. "Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
  • Julián Andrada-Félix & Adrian Fernandez-Perez & Simón Sosvilla-Rivero, 2019. "“Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities”," IREA Working Papers 201912, University of Barcelona, Research Institute of Applied Economics, revised Jul 2019.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "lassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, Institute of Labor Economics (IZA).
• Emmanuel Antwi & Emmanuel Numapau Gyamfi & Kwabena A. Kyei, 2019. "Modeling And Forecasting Ghana’s Inflation Rate Under Threshold Models," Journal of Developing Areas, Tennessee State University, College of Business, vol. 53(3), pages 93-105, Summer.
• Aytaç PEKMEZCÄ° & Nevin Güler DÄ°NCER & Öznur İŞÇİGÃœNERÄ°, 2019. "Comparison Of The Performance Of Fuzzy Time Series Methods Based On Clustering In The Econometric Time Series Estimation," JOURNAL OF LIFE ECONOMICS, Holistence Publications, vol. 6(3), pages 307-320, July.
• Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
  • Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
  • Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2019. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model," Jena Economic Research Papers 2019-006, Friedrich-Schiller-University Jena.
  • Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," CESifo Working Paper Series 6457, CESifo.
• Zied Ftiti & Fredj Jawadi, 2019. "Forecasting Inflation Uncertainty in the United States and Euro Area," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 455-476, June.
• Elettra Agliardi & Thomas Alexopoulos & Christian Cech, 2019. "On the Relationship Between GHGs and Global Temperature Anomalies: Multi-level Rolling Analysis and Copula Calibration," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(1), pages 109-133, January.
  • Elettra Agliardi & Thomas Alexopoulos & Christian Cech, 2017. "On the relationship between GHGs and Global Temperature Anomalies: Multi-level rolling analysis and Copula calibration," Working Paper series 17-05, Rimini Centre for Economic Analysis.
• Marzia De Donno & Riccardo Donati & Gino Favero & Paola Modesti, 2019. "Risk estimation for short-term financial data through pooling of stable fits," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(4), pages 447-470, December.
• Heather L. R. Tierney, 2019. "Forecasting with the Nonparametric Exclusion-from-Core Inflation Persistence Model Using Real-Time Data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 39-63, February.
• Riadh Abed & Amna Zardoub, 2019. "On the co-movements among gold and other financial markets: a multivariate time-varying asymmetric approach," International Economics and Economic Policy, Springer, vol. 16(4), pages 701-719, October.
• Sabrina Backs & Markus Günther & Christian Stummer, 2019. "Stimulating academic patenting in a university ecosystem: an agent-based simulation approach," The Journal of Technology Transfer, Springer, vol. 44(2), pages 434-461, April.
• Phillip A. Cartwright & Natalija Riabko, 2019. "Do spot food commodity and oil prices predict futures prices?," Review of Quantitative Finance and Accounting, Springer, vol. 53(1), pages 153-194, July.
• Mihaela Simionescu & Maria-Simona Naros, 2019. "Sustainable Development and the Insertion of Higher Educated Unemployed People on Romanian Labour Market," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 5(1), pages 12-16, March.
• Mirela Catalina Turkes, 2019. "The Evolution of Fertility over the Life Course. A Comparative Study between Romania and Turkey," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 5(1), pages 95-105, March.
• Florian Eckert & Rob J Hyndman & Anastasios Panagiotelis, 2019. "Forecasting Swiss Exports using Bayesian Forecast Reconciliation," KOF Working papers 19-457, KOF Swiss Economic Institute, ETH Zurich.
• Tóth, Tamás & Kulin, Ferenc, 2019. "A megújuló energia részarányának modellezése 2020-as kitekintéssel [Modelling the proportion of renewable energy with an outlook up to 2020]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(10), pages 1073-1092.
• Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-07, Economic Statistics Centre of Excellence (ESCoE).
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Discussion Papers in Economics 19/05, Division of Economics, School of Business, University of Leicester.
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Laurynas Narusevicius & Tomas Ramanauskas & Laura Gudauskaitė & Tomas Reichenbachas, 2019. "Lithuanian house price index: modelling and forecasting," Bank of Lithuania Occasional Paper Series 28, Bank of Lithuania.
• Egle Jakucionyte & Swapnil Singh, 2019. "Mortgage Foreclosure Risk After the Great Recession," Bank of Lithuania Working Paper Series 69, Bank of Lithuania.
• P.N. Brusov & T.V. Filatova & N.P. Orekhova & V.L. Kulik & I. Weil, 2019. "Ratings of The Investment Projects of Arbitrary Durations: New Methodology," Journal of Reviews on Global Economics, Lifescience Global, vol. 8, pages 437-448.
• Boriss Siliverstovs, 2020. "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
  • Boriss Siliverstovs, 2019. "Assessing Nowcast Accuracy of US GDP Growth in Real Time: The Role of Booms and Busts," Working Papers 2019/01, Latvijas Banka.
• Daniel Gros & Roberto Musmeci, 2019. "Preparing for the next MFF: Where did the money go in the past?," Working Papers LuissLab 19147, Dipartimento di Economia e Finanza, LUISS Guido Carli.
• Belbute, José M. & Pereira, Alfredo M., 2020. "Reference forecasts for CO2 emissions from fossil-fuel combustion and cement production in Portugal," Energy Policy, Elsevier, vol. 144(C).
  • José M. Belbute & Alfredo M. Pereira, 2019. "Reference Forecasts for CO2 Emissions from Fossil-Fuel Combustion and Cement Production in Portugal," GEE Papers 00126, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Aug 2019.
• José M. Belbute & Alfredo Marvão Pereira, 2019. "ARFIMA Reference Forecasts for Worldwide CO2 Emissions and the National Dimension of the Policy Efforts to Meet IPCC Targets," GEE Papers 0125, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Aug 2019.
• José M. Belbute & Alfredo M. Pereira, 2019. "ARFIMA Reference Forecasts for Worldwide CO2 Emissions and the Need for Large and Frontloaded Decarbonization Policies," GEE Papers 0135, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Oct 2019.
• Ewert Kleynhans & Clive Coetzee, 2021. "Regional Business Confidence as Early Indicator of Regional Economic Growth," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 19(1 (Spring), pages 27-48.
• Kristen M. Altenburger & Daniel E. Ho, 2019. "When Algorithms Import Private Bias into Public Enforcement: The Promise and Limitations ofStatistical Debiasing Solutions," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 175(1), pages 98-122.
• Sándor Karajz, 2019. "Multi-Agent-Based Macroeconomic Modelling," Theory Methodology Practice (TMP), Faculty of Economics, University of Miskolc, vol. 15(01), pages 19-24.
• Francisco Lasso-Valderrama & Héctor M. Zárate-Solano, 2019. "Forecasting the Colombian Unemployment Rate Using Labour Force Flows," Borradores de Economia 1073, Banco de la Republica de Colombia.
• María Fernanda Meneses-González & Javier Eliecer Pirateque-Niño & Santiago David Segovia-Baquero, 2019. "Indicadores de alerta temprana para el sector corporativo privado colombiano," Borradores de Economia 1084, Banco de la Republica de Colombia.
• León, Carlos, 2020. "Detecting anomalous payments networks: A dimensionality-reduction approach," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
  • Carlos León, 2019. "Detecting anomalous payments networks: A dimensionality reduction approach," Borradores de Economia 1098, Banco de la Republica de Colombia.
• 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.
• Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • 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, revised Jun 2021.
  • 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.
• Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
  • Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR forecasts, survey information and structural change in the euro area," Working Papers 1948, Banco de España.
  • Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area," Working papers 733, Banque de France.
• Yiru Wang & Barbara Rossi, 2019. "VAR-based Granger-causality test in the presence of instabilities," Economics Working Papers 1642, Department of Economics and Business, Universitat Pompeu Fabra.
  • Barbara Rossi & Yiru Wang, 2019. "VAR-Based Granger-Causality Test in the Presence of Instabilities," Working Papers 1083, Barcelona Graduate School of Economics.
• Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• María Gil & Javier J. Pérez & Alberto Urtasun, 2019. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • María Gil & Javier J. Pérez & A. Jesús Sánchez & Alberto Urtasun, 2018. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," Working Papers 1842, Banco de España.
• 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 & Leonardo Gambacorta, 2020. "Bank intermediation activity in a low‐interest‐rate environment," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 49(2), July.
  • Borio, Claudio & Brei, Michael & Gambacorta, Leonardo, 2019. "Bank intermediation activity in a low interest rate environment," CEPR Discussion Papers 13980, C.E.P.R. Discussion Papers.
  • Michael Brei & Claudio Borio, 2019. "Bank intermediation activity in a low interest rate environment," BIS Working Papers 807, Bank for International Settlements.
  • Michael Brei & Claudio Borio & Leonardo Gambacorta, 2020. "Bank intermediation activity in a low‐interest‐rate environment," Post-Print hal-02985986, HAL.
• Heiner Mikosch & Laura Solanko, 2019. "Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 19-35, March.
• Konstantin Styrin, 2019. "Forecasting Inflation in Russia Using Dynamic Model Averaging," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 3-18, March.
• Nikita Fokin & Andrey Polbin, 2019. "Forecasting Russia's Key Macroeconomic Indicators with the VAR-LASSO Model," Russian Journal of Money and Finance, Bank of Russia, vol. 78(2), pages 67-93, June.
• Denis Shibitov & Mariam Mamedli, 2019. "The finer points of model comparison in machine learning: forecasting based on russian banks’ data," Bank of Russia Working Paper Series wps43, Bank of Russia.
• Sergei Seleznev, 2019. "Truncated priors for tempered hierarchical Dirichlet process vector autoregression," Bank of Russia Working Paper Series wps47, Bank of Russia.
• Ramis Khabibullin, 2019. "What measures of real economic activity slack are helpful for forecasting Russian inflation?," Bank of Russia Working Paper Series wps50, Bank of Russia.
• 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, vol. 20(4), pages 170-200, December.
  • Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
  • Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
• Dario Sansone, 2019. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(2), pages 456-485, April.
  • Dario Sansone, 2017. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Working Papers gueconwpa~17-17-09, Georgetown University, Department of Economics.
• André K. Anundsen, 2019. "Detecting Imbalances in House Prices: What Goes Up Must Come Down?," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(4), pages 1587-1619, October.
  • André K. Anundsen, 2016. "Detecting imbalances in house prices: What goes up must come down?," Working Paper 2016/11, Norges Bank.
• Stavros Degiannakis & George Filis, 2019. "Forecasting European economic policy uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 94-114, February.
  • Stavros Degiannakis & George Filis, 2018. "Forecasting European Economic Policy Uncertainty," BAFES Working Papers BAFES15, Department of Accounting, Finance & Economic, Bournemouth University.
  • Degiannakis, Stavros & Filis, George, 2019. "Forecasting European Economic Policy Uncertainty," MPRA Paper 96268, University Library of Munich, Germany.
• Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.
  • L. Ferrara & C. Marsilli, 2014. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Working papers 515, Banque de France.
  • Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Post-Print hal-01636761, HAL.
• JACKSON Emerson Abraham & TAMUKE Edmund & JABBIE Mohamed, 2019. "Disaggregated Short-Term Inflation Forecast (Stif) For Monetary Policy Decision In Sierra Leone," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 71(3), pages 31-53, November.
  • Jackson, Emerson Abraham & Tamuke, Edmund & Jabbie, Mohamed, 2019. "Disaggregated Short-Term Inflation Forecast (STIF) for Monetary Policy Decision in Sierra Leone," MPRA Paper 96735, University Library of Munich, Germany, revised 26 Nov 2019.
• Juan Carlos Carlo Santos, 2019. "Pronósticos del PIB mediante modelos de factores dinámicos," Revista de Análisis del BCB, Banco Central de Bolivia, vol. 30(1), pages 125-174, January -.
• 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.
  • Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Papers No 01/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
• Larsen, Vegard H. & Thorsrud, Leif Anders & Zhulanova, Julia, 2021. "News-driven inflation expectations and information rigidities," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 507-520.
  • Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Papers No 03/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Paper 2019/5, Norges Bank.
• Borowska, Agnieszka & Hoogerheide, Lennart & Koopman, Siem Jan & van Dijk, Herman K., 2020. "Partially censored posterior for robust and efficient risk evaluation," Journal of Econometrics, Elsevier, vol. 217(2), pages 335-355.
  • Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
  • Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman K. van Dijk, 2019. "Partially Censored Posterior for robust and efficient risk evaluation," Working Paper 2019/12, Norges Bank.
• Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
  • Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
  • Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Papers No 01/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Larsen, Vegard H. & Thorsrud, Leif Anders & Zhulanova, Julia, 2021. "News-driven inflation expectations and information rigidities," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 507-520.
  • Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Paper 2019/5, Norges Bank.
  • Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Papers No 03/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Suss, Joel & Treitel, Henry, 2019. "Predicting bank distress in the UK with machine learning," Bank of England working papers 831, Bank of England.
• Stanisławska, Ewa & Paloviita, Maritta & Łyziak, Tomasz, 2019. "Assessing reliability of aggregated inflation views in the European Commission consumer survey," Research Discussion Papers 10/2019, Bank of Finland.
• Benchimol, Jonathan & Bounader, Lahcen, 2018. "Optimal monetary policy under bounded rationality," Research Discussion Papers 9/2018, Bank of Finland.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy under Bounded Rationality," Bank of Israel Working Papers 2019.07, Bank of Israel.
  • Benchimol, Jonathan & Bounader, Lahcen, 2021. "Optimal Monetary Policy Under Bounded Rationality," Dynare Working Papers 67, CEPREMAP.
  • Jonathan Benchimol & Lahcen Bounader, 2018. "Optimal Monetary Policy Under Bounded Rationality," Globalization Institute Working Papers 336, Federal Reserve Bank of Dallas.
  • Jonathan Benchimol & Lahcen Bounader, 2019. "Optimal Monetary Policy Under Bounded Rationality," IMF Working Papers 2019/166, International Monetary Fund.
• Benchimol, Jonathan & El-Shagi, Makram, 2020. "Forecast performance in times terrorism," Economic Modelling, Elsevier, vol. 91(C), pages 386-402.
  • Jonathan Benchimol & Makram El-Shagi, 2017. "Forecast Performance in Times of Terrorism," CFDS Discussion Paper Series 2017/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
  • Jonathan Benchimol & Makram El-Shagi, 2020. "Forecast performance in times of terrorism," Post-Print halshs-03248938, HAL.
  • Jonathan Benchimol & Makram El-Shagi, 2020. "Forecast Performance in Times of Terrorism," Globalization Institute Working Papers 390, Federal Reserve Bank of Dallas.
  • Jonathan Benchimol & Makram El-Shagi, 2019. "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers 2019.08, Bank of Israel.
• Bruno Deschamps & Christos Ioannidis & Kook Ka, 2019. "High-Frequency Credit Spread Information and Macroeconomic Forecast Revision," Working Papers 2019-17, Economic Research Institute, Bank of Korea.
• Rahul Roy & Santhakumar Shijin, 2019. "The nexus of anomalies-stock returns-asset pricing models: The international evidence," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 19(1), pages 1-14, March.
• 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.
  • 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.
• Fugazza Carolina, 2019. "Anatomy of Non-Employment Risk," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 19(3), pages 1-19, July.
• Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
  • Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
  • Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
• Bruttel Oliver & Baumann Arne & Dütsch Matthias, 2019. "Beschäftigungseffekte des gesetzlichen Mindestlohns: Prognosen und empirische Befunde," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 20(3), pages 237-253, September.
• Bruttel Oliver & Baumann Arne & Dütsch Matthias, 2019. "Beschäftigungseffekte des gesetzlichen Mindestlohns: Prognosen und empirische Befunde," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 20(3), pages 237-253, September.
• Olimpia NEAGU, 2019. "Digital Divide Gap Convergence Across European Union: The Role Of Urbanisation," Contemporary Economy Journal, Constantin Brancoveanu University, vol. 4(1), pages 43-48.
• Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
• Ahmed, M. F.. & Satchell, S, 2019. "Some Dynamic and Steady-State Properties of Threshold Autoregressions with Applications to Stationarity and Local Explosivity," Cambridge Working Papers in Economics 1923, Faculty of Economics, University of Cambridge.
• Yang Han & Victor OK Li & Jacqueline CK Lam & Michael Pollitt, 2019. "How BLUE is the Sky? Estimating the Air Quality Data in Beijing During the Blue Sky Day Period (2008-2012) by the Bayesian LSTM Approach," Working Papers EPRG1912, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • Han, Y. & Li, V. & Lam, J. & Pollitt, M., 2019. "How BLUE is the Sky? Estimating the Air Quality Data in Beijing During the Blue Sky Day Period (2008-2012) by the Bayesian LSTM Approach," Cambridge Working Papers in Economics 1929, Faculty of Economics, University of Cambridge.
• Miroslav Klucik, 2019. "Tracking the Course of the Economy (Nowcasting of basic macroeconomic indicators of Slovakia)," Working Papers Working Paper No. 1/2019, Council for Budget Responsibility.
• de Bondt, Gabe & Gieseck, Arne & Zekaite, Zivile & Herrero, Pablo, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Working Paper Series 2343, European Central Bank.
  • de Bondt, Gabe & Gieseck, Arne & Herrero, Pablo & Zekaite, Zivile, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Research Technical Papers 15/RT/19, Central Bank of Ireland.
• Congressional Budget Office, 2019. "An Evaluation of CBO’s Past Deficit and Debt Projections," Reports 55234, Congressional Budget Office.
• Congressional Budget Office, 2019. "CBO’s Economic Forecasting Record: 2019 Update," Reports 55505, Congressional Budget Office.
• Congressional Budget Office, 2019. "The Accuracy of CBO’s Baseline Estimates for Fiscal Year 2019," Reports 55927, Congressional Budget Office.
• Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient matrix approach for classical inference in state space models," Economics Letters, Elsevier, vol. 181(C), pages 22-27.
  • Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient Matrix Approach for Classical Inference in State Space Models," EMF Research Papers 19, Economic Modelling and Forecasting Group.
• Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2018. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-14, Economic Statistics Centre of Excellence (ESCoE).
  • Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
• Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
  • Galvao, Ana Beatriz & Mitchell, James, 2019. "Measuring Data Uncertainty : An Application using the Bank of England’s “Fan Charts” for Historical GDP Growth," EMF Research Papers 24, Economic Modelling and Forecasting Group.
• Juvenal, Luciana & Petrella, Ivan, 2019. "Not all Terms of Trade Shocks are Alike," EMF Research Papers 25, Economic Modelling and Forecasting Group.
• Mitchell, James & Weale, Martin, 2019. "Forecasting with Unknown Unknowns: Censoring and Fat Tails on the Bank of England's Monetary Policy Committee," EMF Research Papers 27, Economic Modelling and Forecasting Group.
• Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
  • Katarzyna Maciejowska & Rafal Weron, 2019. "Electricity price forecasting," HSC Research Reports HSC/19/01, Hugo Steinhaus Center, Wroclaw University of Technology.
• 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.
• Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemyslaw Zaleski & Rafal Weron, 2019. "Balancing RES generation: Profitability of an energy trader," HSC Research Reports HSC/19/07, Hugo Steinhaus Center, Wroclaw University of Technology.
• Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019. "Enhancing load, wind and solar generation forecasts in day-ahead forecasting of spot and intraday electricity prices," HSC Research Reports HSC/19/08, Hugo Steinhaus Center, Wroclaw University of Technology.
• Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global Temperatures and Greenhouse Gases: A Common Features Approach," Monash Econometrics and Business Statistics Working Papers 23/19, Monash University, Department of Econometrics and Business Statistics.
  • Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global temperatures and greenhouse gases - a common features approach," Working Papers 2019-07-15, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
• Alberto Caruso & Laura Coroneo, 2019. "Predicting interest rates in real-time," Discussion Papers 19/18, Department of Economics, University of York.
• Makarewicz, Tomasz, 2019. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," BERG Working Paper Series 141, Bamberg University, Bamberg Economic Research Group.
• Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
  • Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2019. "Exploiting ergodicity in forecasts of corporate profitability," BERG Working Paper Series 147, Bamberg University, Bamberg Economic Research Group.
• Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
  • Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
• Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
• Jackson, Emerson Abraham & Tamuke, Edmund, 2019. "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," MPRA Paper 96845, University Library of Munich, Germany, revised 23 Dec 2019.
  • Jackson, Emerson Abraham & Tamuke, Edmund, 2019. "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," EconStor Preprints 202547, ZBW - Leibniz Information Centre for Economics.
• Strohsal, Till & Wolf, Elias, 2019. "Data revisions to German national accounts: Are initial releases good nowcasts?," Discussion Papers 2019/11, Free University Berlin, School of Business & Economics.
• Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019. "Metcalfe's law and herding behaviour in the cryptocurrencies market," Economics Discussion Papers 2019-16, Kiel Institute for the World Economy (IfW Kiel).
• Bolgorian, Meysam, 2019. "Can a cusp catastrophe model describe the effect of sanctions on exchange rates?," Economics Discussion Papers 2019-2, Kiel Institute for the World Economy (IfW Kiel).
• Thompson, Erica L. & Smith, Leonard A., 2019. "Escape from model-land," Economics Discussion Papers 2019-23, Kiel Institute for the World Economy (IfW Kiel).
• Brighton, Henry, 2019. "Beyond quantified ignorance: Rebuilding rationality without the bias bias," Economics Discussion Papers 2019-25, Kiel Institute for the World Economy (IfW Kiel).
• Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019. "Metcalfe's law and log-period power laws in the cryptocurrencies market," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-26.
• Thompson, Erica L. & Smith, Leonard A., 2019. "Escape from model-land," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-17.
• Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019. "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers 2019-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Michael Kostmann & Wolfgang K. Härdle, 2019. "Forecasting in Blockchain-Based Local Energy Markets," Energies, MDPI, vol. 12(14), pages 1-27, July.
  • Kostmann, Michael & Härdle, Wolfgang Karl, 2019. "Forecasting in Blockchain-based Local Energy Markets," IRTG 1792 Discussion Papers 2019-014, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Pele, Daniel Traian & Wesselhöfft, Niels & Härdle, Wolfgang Karl & Kolossiatis, Michalis & Yatracos, Yannis, 2019. "Phenotypic convergence of cryptocurrencies," IRTG 1792 Discussion Papers 2019-018, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Junjie Hu & Wolfgang Karl Hardle & Weiyu Kuo, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," Papers 1912.05228, arXiv.org, revised Dec 2021.
  • Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2021. "VCRIX — A volatility index for crypto-currencies," International Review of Financial Analysis, Elsevier, vol. 78(C).
  • Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019. "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers 18/2019, Halle Institute for Economic Research (IWH).
• Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers 48/2018, Deutsche Bundesbank.
  • Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," IWH Discussion Papers 2/2019, Halle Institute for Economic Research (IWH).
• João C. Claudio & Katja Heinisch & Oliver Holtemöller, 2020. "Nowcasting East German GDP growth: a MIDAS approach," Empirical Economics, Springer, vol. 58(1), pages 29-54, January.
  • Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
• 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.
  • Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
• 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.
  • Bormann, Carsten & Schienle, Melanie, 2019. "Detecting structural differences in tail dependence of financial time series," Working Paper Series in Economics 122, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
• Behrens, Christoph, 2019. "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers 9, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Ansgar Belke & Jens Klose, 2019. "Forecasting ECB Policy Rates with Different Monetary Policy Rules," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(3), pages 238-252, June.
  • Ansgar Belke & Jens Klose, 2019. "Forecasting ECB Policy Rates with Different Monetary Policy Rules," ROME Working Papers 201906, ROME Network.
  • Belke, Ansgar & Klose, Jens, 2019. "Forecasting ECB policy rates with different monetary policy rules," Ruhr Economic Papers 815, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Döhrn, Roland, 2019. "Comparing forecast accuracy in small samples," Ruhr Economic Papers 833, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Hinterlang, Natascha, 2019. "Predicting Monetary Policy Using Artificial Neural Networks," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203503, Verein für Socialpolitik / German Economic Association.
• Axenbeck, Janna & Breithaupt, Patrick, 2019. "Web-based innovation indicators: Which firm website characteristics relate to firm-level innovation activity?," ZEW Discussion Papers 19-063, ZEW - Leibniz Centre for European Economic Research.
• Merz, Oliver & Flepp, Raphael & Franck, Egon, 2021. "Sonic Thunder vs. Brian the Snail: Are people affected by uninformative racehorse names?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
  • Oliver Merz & Raphael Flepp & Egon Franck, 2020. "Sonic Thunder vs. Brian the Snail : Are people affected by uninformative racehorse names?," Working Papers 384, University of Zurich, Department of Business Administration (IBW).
• Ademola Abdulkareem & E. J. Okoroafor & Ayokunle Awelewa & Aderibigbe Adekitan, 2019. "Pseudo-Inverse Matrix Model for Estimating Long-Term Annual Peak Electricity Demand: The Covenant University’s Experience," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 103-109.
• Warsono Warsono & Edwin Russel & Wamiliana Wamiliana & Widiarti Widiarti & Mustofa Usman, 2019. "Modeling and Forecasting by the Vector Autoregressive Moving Average Model for Export of Coal and Oil Data (Case Study from Indonesia over the Years 2002-2017)," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 240-247.
• Lucheroni, Carlo & Boland, John & Ragno, Costantino, 2019. "Scenario generation and probabilistic forecasting analysis of spatio-temporal wind speed series with multivariate autoregressive volatility models," Applied Energy, Elsevier, vol. 239(C), pages 1226-1241.
• Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019. "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, vol. 60(C), pages 45-68.
• Guo, Jing & Zhang, Zhengyu, 2019. "Does renaming promote economic development? New evidence from a city-renaming reform experiment in China," China Economic Review, Elsevier, vol. 57(C).
• McKenzie, David & Sansone, Dario, 2019. "Predicting entrepreneurial success is hard: Evidence from a business plan competition in Nigeria," Journal of Development Economics, Elsevier, vol. 141(C).
• Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
  • Wilko Bolt & Maria Demertzis & Cees Diks & Cars Hommes & Marco van der Leij, 2014. "Identifying booms and busts in house prices under heterogeneous expectations," DNB Working Papers 450, Netherlands Central Bank, Research Department.
  • Bolt, W. & Demertzis, D. & Diks, C.G.H. & Van der Leij, M.J., 2014. "Identifying Booms and Busts in House Prices under Heterogeneous Expectations," CeNDEF Working Papers 14-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  • Wilko Bolt & Maria Demertzis & Cees Diks & Cars Hommes & Marco van der Leij, 2014. "Identifying Booms and Busts in House Prices under Heterogeneous Expectations," European Economy - Economic Papers 2008 - 2015 540, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
  • Wilko Bolt & Maria Demertzis & Cees Diks & Cars Hommes & Marco van der Leij, 2014. "Identifying Booms and Busts in House Prices under Heterogeneous Expectations," Tinbergen Institute Discussion Papers 14-157/II, Tinbergen Institute.
• Kapetanios, George & Masolo, Riccardo M. & Petrova, Katerina & Waldron, Matthew, 2019. "A time-varying parameter structural model of the UK economy," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.
  • Petrova, Katerina & Kapetanios, George & Masolo, Riccardo & Waldron, Matthew, 2017. "A time varying parameter structural model of the UK economy," Bank of England working papers 677, Bank of England.
• Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
• Zhang, Han & Fan, Xiaoyun & Guo, Bin & Zhang, Wei, 2019. "Reexamining time-varying bond risk premia in the post-financial crisis era," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
• Plachel, Lukas, 2019. "A unified model for regularized and robust portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
• Kolidakis, Stylianos & Botzoris, George & Profillidis, Vassilios & Lemonakis, Panagiotis, 2019. "Road traffic forecasting — A hybrid approach combining Artificial Neural Network with Singular Spectrum Analysis," Economic Analysis and Policy, Elsevier, vol. 64(C), pages 159-171.
• Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
• Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019. "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, vol. 78(C), pages 32-39.
• El-Shagi, Makram, 2019. "Rationality tests in the presence of instabilities in finite samples," Economic Modelling, Elsevier, vol. 79(C), pages 242-246.
• González-Astudillo, Manuel & Baquero, Daniel, 2019. "A nowcasting model for Ecuador: Implementing a time-varying mean output growth," Economic Modelling, Elsevier, vol. 82(C), pages 250-263.
• Tissaoui, Kais & Azibi, Jamel, 2019. "International implied volatility risk indexes and Saudi stock return-volatility predictabilities," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 65-84.
• Salisu, Afees A. & Isah, Kazeem & Akanni, Lateef O., 2019. "Improving the predictability of stock returns with Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 857-867.
• Nonejad, Nima, 2019. "Forecasting aggregate equity return volatility using crude oil price volatility: The role of nonlinearities and asymmetries," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
• Paccagnini, Alessia, 2019. "Did financial factors matter during the Great Recession?," Economics Letters, Elsevier, vol. 174(C), pages 26-30.
• Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient matrix approach for classical inference in state space models," Economics Letters, Elsevier, vol. 181(C), pages 22-27.
  • Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient Matrix Approach for Classical Inference in State Space Models," EMF Research Papers 19, Economic Modelling and Forecasting Group.
• Uddin, Gazi Salah & Gençay, Ramazan & Bekiros, Stelios & Sahamkhadam, Maziar, 2019. "Enhancing the predictability of crude oil markets with hybrid wavelet approaches," Economics Letters, Elsevier, vol. 182(C), pages 50-54.
• Cuesta, Jose & Chagalj, Cristian, 2019. "Measuring poverty with administrative data in data deprived contexts: The case of Nicaragua," Economics Letters, Elsevier, vol. 183(C), pages 1-1.
• Gozgor, Giray & Lau, Chi Keung Marco & Sheng, Xin & Yarovaya, Larisa, 2019. "The role of uncertainty measures on the returns of gold," Economics Letters, Elsevier, vol. 185(C).
• Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
• Rossi, Barbara & Sekhposyan, Tatevik, 2019. "Alternative tests for correct specification of conditional predictive densities," Journal of Econometrics, Elsevier, vol. 208(2), pages 638-657.
  • Barbara Rossi & Tatevik Sekhposyan, 2014. "Alternative tests for correct specification of conditional predictive densities," Economics Working Papers 1416, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2017.
  • Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona Graduate School of Economics.
• Liao, Jun & Zong, Xianpeng & Zhang, Xinyu & Zou, Guohua, 2019. "Model averaging based on leave-subject-out cross-validation for vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(1), pages 35-60.
• Boot, Tom & Nibbering, Didier, 2019. "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
• Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Businesss School.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 2016_09, Business School - Economics, University of Glasgow.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103R, Brandeis University, Department of Economics and International Businesss School, revised Apr 2016.
  • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2017. "Bayesian Compressed Vector Autoregressions," Working Paper series 17-32, Rimini Centre for Economic Analysis.
• McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
• Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
  • Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
• Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.
• Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Adaptive hierarchical priors for high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 212(1), pages 241-271.
  • Dimitris Korobilis & Davide Pettenuzzo, 2017. "Adaptive Hierarchical Priors for High-Dimensional Vector Autoregessions," Working Papers 115, Brandeis University, Department of Economics and International Businesss School.
  • Dimitris Korobilis & Davide Pettenuzzo, 2018. "Adaptive Hierarchical Priors for High-Dimensional Vector Autoregressions," Working Paper series 18-21, Rimini Centre for Economic Analysis.
• Giessing, Alexander & He, Xuming, 2019. "On the predictive risk in misspecified quantile regression," Journal of Econometrics, Elsevier, vol. 213(1), pages 235-260.
• Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
• Sutton, Maxwell & Vasnev, Andrey L. & Gerlach, Richard, 2019. "Mixed interval realized variance: A robust estimator of stock price volatility," Econometrics and Statistics, Elsevier, vol. 11(C), pages 43-62.
• Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.
• Ghysels, Eric & Qian, Hang, 2019. "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, vol. 9(C), pages 1-16.
• Al-Sadoon, Majid M., 2019. "Testing subspace Granger causality," Econometrics and Statistics, Elsevier, vol. 9(C), pages 42-61.
  • Majid M. Al-Sadoon, 2015. "Testing subspace Granger causality," Economics Working Papers 1495, Department of Economics and Business, Universitat Pompeu Fabra.
  • Majid M. Al-Sadoon, 2016. "Testing Subspace Granger Causality," Working Papers 850, Barcelona Graduate School of Economics.
• Trucíos, Carlos & Hotta, Luiz K. & Valls Pereira, Pedro L., 2019. "On the robustness of the principal volatility components," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 201-219.
  • Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
• Díaz-Hernández, Adán & Constantinou, Nick, 2019. "A multiple regime extension to the Heston–Nandi GARCH(1,1) model," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 162-180.
• Panopoulou, Ekaterini & Souropanis, Ioannis, 2019. "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 197-221.
• Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
• Westerlund, Joakim & Sharma, Susan Sunila, 2019. "Panel evidence on the ability of oil returns to predict stock returns in the G7 area," Energy Economics, Elsevier, vol. 77(C), pages 3-12.
• Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
• Chen, Rongda & Xu, Jianjun, 2019. "Forecasting volatility and correlation between oil and gold prices using a novel multivariate GAS model," Energy Economics, Elsevier, vol. 78(C), pages 379-391.
• Cheng, Fangzheng & Li, Tian & Wei, Yi-ming & Fan, Tijun, 2019. "The VEC-NAR model for short-term forecasting of oil prices," Energy Economics, Elsevier, vol. 78(C), pages 656-667.
• Jiao, Ying & Ma, Chunhua & Scotti, Simone & Sgarra, Carlo, 2019. "A branching process approach to power markets," Energy Economics, Elsevier, vol. 79(C), pages 144-156.
• Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting: Part II — Probabilistic forecasting," Energy Economics, Elsevier, vol. 79(C), pages 171-182.
  • Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2017. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting," HSC Research Reports HSC/17/02, Hugo Steinhaus Center, Wroclaw University of Technology.
• Maryniak, Paweł & Trück, Stefan & Weron, Rafał, 2019. "Carbon pricing and electricity markets — The case of the Australian Clean Energy Bill," Energy Economics, Elsevier, vol. 79(C), pages 45-58.
• Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
• Kostrzewski, Maciej & Kostrzewska, Jadwiga, 2019. "Probabilistic electricity price forecasting with Bayesian stochastic volatility models," Energy Economics, Elsevier, vol. 80(C), pages 610-620.
• Beyca, Omer Faruk & Ervural, Beyzanur Cayir & Tatoglu, Ekrem & Ozuyar, Pinar Gokcin & Zaim, Selim, 2019. "Using machine learning tools for forecasting natural gas consumption in the province of Istanbul," Energy Economics, Elsevier, vol. 80(C), pages 937-949.
• Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
• Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," Energy Economics, Elsevier, vol. 81(C), pages 639-649.
  • Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," MPRA Paper 96446, University Library of Munich, Germany.
• Liu, Jingzhen & Kemp, Alexander, 2019. "Forecasting the sign of U.S. oil and gas industry stock index excess returns employing macroeconomic variables," Energy Economics, Elsevier, vol. 81(C), pages 672-686.
• Dahl, Christian M. & Effraimidis, Georgios & Pedersen, Mikkel H., 2019. "Nonparametric wind power forecasting under fixed and random censoring," Energy Economics, Elsevier, vol. 84(C).
• Caloia, Francesco Giuseppe & Cipollini, Andrea & Muzzioli, Silvia, 2019. "How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study," Energy Economics, Elsevier, vol. 84(C).
• Khalifa, Ahmed & Caporin, Massimiliano & Di Fonzo, Tommaso, 2019. "Scenario-based forecast for the electricity demand in Qatar and the role of energy efficiency improvements," Energy Policy, Elsevier, vol. 127(C), pages 155-164.
• Baldoni, Edoardo & Coderoni, Silvia & D'Orazio, Marco & Di Giuseppe, Elisa & Esposti, Roberto, 2019. "The role of economic and policy variables in energy-efficient retrofitting assessment. A stochastic Life Cycle Costing methodology," Energy Policy, Elsevier, vol. 129(C), pages 1207-1219.
• Maluf de Lima, Lilian & Piedade Bacchi, Mirian Rumenos, 2019. "Assessing the impact of Brazilian economic growth on demand for electricity," Energy, Elsevier, vol. 172(C), pages 861-873.
• Moral-Carcedo, Julián & Pérez-García, Julián, 2019. "Time of day effects of temperature and daylight on short term electricity load," Energy, Elsevier, vol. 174(C), pages 169-183.
• Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019. "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 1-9.
• Bleher, Johannes & Dimpfl, Thomas, 2019. "Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 147-159.
• Tissaoui, Kais, 2019. "Forecasting implied volatility risk indexes: International evidence using Hammerstein-ARX approach," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 232-249.
• Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
• 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.
• Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global temperatures and greenhouse gases - a common features approach," Working Papers 2019-07-15, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
  • Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global Temperatures and Greenhouse Gases: A Common Features Approach," Monash Econometrics and Business Statistics Working Papers 23/19, Monash University, Department of Econometrics and Business Statistics.
• 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.
  • 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.
• 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.
  • 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.
  • Mueller, Hannes Felix & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
• 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.
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," Finance and Economics Discussion Series 2019-065, Board of Governors of the Federal Reserve System (U.S.).
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Working Papers 26033, National Bureau of Economic Research, Inc.
• Bekaert, Geert & Panayotov, George, 2020. "Good Carry, Bad Carry," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(4), pages 1063-1094, June.
  • Bekaert, Geert & Panayotov, George, 2019. "Good Carry, Bad Carry," CEPR Discussion Papers 13463, C.E.P.R. Discussion Papers.
  • Geert Bekaert & George Panayotov, 2019. "Good Carry, Bad Carry," NBER Working Papers 25420, National Bureau of Economic Research, Inc.
• Aloosh, Arash & Bekaert, Geert, 2019. "Currency Factors," CEPR Discussion Papers 13464, C.E.P.R. Discussion Papers.
  • Arash Aloosh & Geert Bekaert, 2019. "Currency Factors," NBER Working Papers 25449, National Bureau of Economic Research, Inc.
• John B. Donaldson & Rajnish Mehra, 2021. "Average crossing time: An alternative characterization of mean aversion and reversion," Quantitative Economics, Econometric Society, vol. 12(3), pages 903-944, July.
  • 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.
  • 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.
• 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 J. Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," Finance and Economics Discussion Series 2019-065, Board of Governors of the Federal Reserve System (U.S.).
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Working Papers 26033, National Bureau of Economic Research, Inc.
• Sruthi Davuluri & René García Franceschini & Christopher R. Knittel & Chikara Onda & Kelly Roache, 2019. "Machine Learning for Solar Accessibility: Implications for Low-Income Solar Expansion and Profitability," NBER Working Papers 26178, National Bureau of Economic Research, Inc.
• Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019. "Predicting Returns With Text Data," NBER Working Papers 26186, National Bureau of Economic Research, Inc.
• Antoine Arnoud & Fatih Guvenen & Tatjana Kleineberg, 2019. "Benchmarking Global Optimizers," NBER Working Papers 26340, National Bureau of Economic Research, Inc.
• Christopher R. Knittel & Samuel Stolper, 2019. "Using Machine Learning to Target Treatment: The Case of Household Energy Use," NBER Working Papers 26531, National Bureau of Economic Research, Inc.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," NBER Working Papers 26569, National Bureau of Economic Research, Inc.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2021. "Forecasting with a Panel Tobit Model," Papers 2110.14117, arXiv.org.
• 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.
  • Shrestha, Ruzel & Chakraborty, Lekha, 2019. "Practising Subnational Public Finance in an Emerging Economy: Fiscal Marksmanship in Kerala," Working Papers 19/261, National Institute of Public Finance and Policy.
• Chakraborty, Lekha & Chakraborty, Pinaki & Shrestha, Ruzel, 2019. "Budget Credibility of Subnational Governments: Analyzing the Fiscal Forecasting Errors of 28 States in India," MPRA Paper 95921, 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.
• Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private Financing of Long‑Term Care: Income, Savings and Reverse Mortgages," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 507-508, pages 5-24.
  • Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private financing of long-term care: income, savings and reverse mortgages," Erudite Working Paper 2019-14, Erudite.
  • Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private financing of long-term care: income, savings and reverse mortgages," Working Papers 14, French Institute for Demographic Studies.
• Jérôme Wittwer, 2019. "Comment – Is Self‑Insurance for Long‑Term Care Risk a Solution?," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 507-508, pages 25-30.
• François Legendre, 2019. "The Emergence and Consolidation of Microsimulation Methods in France," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 510-511-5, pages 201-217.
• Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-07, Economic Statistics Centre of Excellence (ESCoE).
  • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Discussion Papers in Economics 19/05, Division of Economics, School of Business, University of Leicester.
• Galvao, Ana Beatriz & Mitchell, James, 2019. "Measuring Data Uncertainty : An Application using the Bank of England’s “Fan Charts” for Historical GDP Growth," EMF Research Papers 24, Economic Modelling and Forecasting Group.
  • Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (E