Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2024

• Baruník Jozef & Fišer Pavel, 2024, "Co-Jumping of Treasury Yield Curve Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 28, issue 3, pages 481-506, DOI: 10.1515/snde-2022-0091.
• Ayala Astrid & Blazsek Szabolcs & Licht Adrian, 2024, "Volatility Forecasting Using Quasi-Score-Driven Models with an Application to the Coronavirus Pandemic Period," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 28, issue 5, pages 785-805, DOI: 10.1515/snde-2022-0085.
• Pesaran, M. H. & Smith, R. P., 2024, "High-Dimensional Forecasting with Known Knowns and Known Unknowns," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2406, Feb.
• Agarwala, M. & Burke, M. & Doherty-Bigara, J. & Klusak, P. & Mohaddes, K., 2024, "Climate Change and Sovereign Risk: A Regional Analysis for the Caribbean," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2420, Apr.
• Pesaran, M. H. & Song, H., 2024, "Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2464, Oct.
• Burke, M. & Agarwala, M. & Klusak, P. & Mohaddes, K., 2024, "Climate Policy and Sovereign Debt: The Impact of Transition Scenarios on Sovereign Creditworthiness," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2470, Dec.
• Congressional Budget Office, 2024, "An Evaluation of CBO’s Projections of Deficits and Debt From 1984 to 2023," Reports, Congressional Budget Office, number 60664, Dec.
• M. Hashem Pesaran & Ron P. Smith, 2024, "High-Dimensional Forecasting with Known Knowns and Known Unknowns," CESifo Working Paper Series, CESifo, number 10931.
• Alexandros Botsis & Christoph Görtz & Plutarchos Sakellaris, 2024, "Quantifying Qualitative Survey Data with Panel Data Structure," CESifo Working Paper Series, CESifo, number 11013.
• Hannes Ullrich & Jonas Hannane & Christian Peukert & Luis Aguiar & Tomaso Duso, 2024, "Returns to Data: Evidence from Web Tracking," CESifo Working Paper Series, CESifo, number 11240.
• Thorsten Drautzburg & Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Dick Oosthuizen, 2024, "Filtering with Limited Information," CESifo Working Paper Series, CESifo, number 11243.
• M. Hashem Pesaran & Hayun Song, 2024, "Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call," CESifo Working Paper Series, CESifo, number 11415.
• Stefan Sauer & Klaus Wohlrabe, 2024, "What Is Behind the ifo Business Climate? Evidence from a Meta-Survey," CESifo Working Paper Series, CESifo, number 11482.
• Mariia Okuneva & Philipp Hauber & Kai Carstensen & Jasper Bär, 2024, "Nowcasting German GDP with Text Data," CESifo Working Paper Series, CESifo, number 11587.
• Katharina Wedel, 2024, "Improving Educational Outcomes: Analyses of Interventions and Public Opinion," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 105, April.
• Markus Leippold & Michal Svaton, 2024, "Scheduling Processes and Inference of Scheduled Events From Price Data," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-12, Jan.
• Soros Chitsiripanich & Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2024, "Smoothing Out Momentum and Reversal," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-47, Sep.
• Yicheng Wang & Didier Sornette & Ke Wu & Sandro Claudio Lera, 2024, "Dynamic Influence Networks Self-Organize Towards Sub-Critical Financial Instabilities," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-77, Oct.
• V. Candila & O. Cepni & G. Gallo & R. Gupta, 2024, "Influence of Local and Global Economic Policy Uncertainty on the volatility of US state-level equity returns: Evidence from a GARCH-MIDAS approach with Shrinkage and Cluster Analysis," Working Paper CRENoS, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia, number 202414.
• S. Borgioli & G. Gallo & C. .Ongari, 2024, "Financial Returns, Sentiment and Market Volatility: a Dynamic Assessment," Working Paper CRENoS, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia, number 202415.
• Omar Castillo Nuñez, 2024, "Incidencia de las lluvias y del precio en la oferta de leche cruda en los departamentos de Córdoba y Sucre, Colombia," Ensayos de Economía, Universidad Nacional de Colombia Sede Medellín, number 21226, Sep.
• Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2024, "Specification Choices in Quantile Regression for Empirical Macroeconomics," CEPR Discussion Papers, Centre for Economic Policy Research, number 18901, Mar.
• Marcellino, Massimiliano & Pfarrhofer, Michael, 2024, "Bayesian nonparametric methods for macroeconomic forecasting," CEPR Discussion Papers, Centre for Economic Policy Research, number 18970, Apr.
• Baumeister, Christiane & Huber, Florian & Marcellino, Massimiliano, 2024, "Risky Oil: It's All in the Tails," CEPR Discussion Papers, Centre for Economic Policy Research, number 19129, Jun.
• Kwon, Alexander & Maliar, Lilia, 2024, "Predicting Retirement and Social Security Claiming Decisions using Machine Learning," CEPR Discussion Papers, Centre for Economic Policy Research, number 19198, Jul.
• Ullrich, Hannes & Hannane, Jonas & Peukert, Christian & Aguiar, Luis & Duso, Tomaso, 2024, "Returns to Data: Evidence from Web Tracking," CEPR Discussion Papers, Centre for Economic Policy Research, number 19266, Jul.
• Drautzburg, Thorsten & Fernández-Villaverde, Jesús & Guerron, Pablo & Oosthuizen, Dick, 2024, "Filtering with Limited Information," CEPR Discussion Papers, Centre for Economic Policy Research, number 19270, Jul.
• Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2024, "Bayesian Neural Networks for Macroeconomic Analysis," CEPR Discussion Papers, Centre for Economic Policy Research, number 19381, Aug.
• Bassetti, Federico & Casarin, Roberto & Del Negro, Marco, 2024, "A Bayesian Approach for Inference on Probabilistic Surveys," CEPR Discussion Papers, Centre for Economic Policy Research, number 19426, Sep.
• Furno, Francesco & Giannone, Domenico, 2024, "Nowcasting Recession Risk," CEPR Discussion Papers, Centre for Economic Policy Research, number 19483, Sep.
• Calvo, Richard & Pons, Vincent & Shapiro, Jesse, 2024, "Pitfalls of Demographic Forecasts of US Elections," CEPR Discussion Papers, Centre for Economic Policy Research, number 19564, Oct.
• De Polis, Andrea & Melosi, Leonardo & Petrella, Ivan, 2024, "The Taming of the Skew: Asymmetric Inflation Risk and Monetary Policy," CEPR Discussion Papers, Centre for Economic Policy Research, number 19760, Dec.
• Blazsek, Szabolcs & Escribano, Álvaro & Kristof, Erzsebet, 2024, "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics, Universidad Carlos III de Madrid. Departamento de Economía, number 39546, Jan.
• Barrio Castro, Tomás del & Escribano, Álvaro & Sibbertsen, Philipp, 2024, "Modeling and Forecasting the Long Memory of Cyclical Trends in Paleoclimate Data," UC3M Working papers. Economics, Universidad Carlos III de Madrid. Departamento de Economía, number 43987, Jun.
• Julen Iglesias Tejedor, 2024, "Creación de una cartera de inversión que venza la inflación atendiendo a criterios ESG gestionada mediante machine learning," Revista de Economía y Finanzas (REyF), Asociación Cuadernos de Economía, volume 2, issue 5, pages 79-100, Mayo.
• Javier Teo Sanz Ortega, 2024, "El mercado bursátil español: BME Growth frente al IBEX," Revista de Economía y Finanzas (REyF), Asociación Cuadernos de Economía, volume 2, issue 6, pages 185-198, Septiembr.
• Janny Núñez-Almonte & Alfredo Grau-Grau & Inmaculada Bel-Oms, 2024, "Sustainability, sustainable finance, good governance codes. A new perspective," Revista de Economía y Finanzas (REyF), Asociación Cuadernos de Economía, volume 2, issue 6, pages 199-214, Septiembr.
• Pesaran, M. Hashem & Smith, Ron P., 2024, "High-Dimensional Forecasting With Known Knowns And Known Unknowns," National Institute Economic Review, National Institute of Economic and Social Research, volume 267, issue , pages 1-25, February.
• Issam BOUSALAM & Ahmed KHATTAB & Yahya SALMI, 2024, "Explicative determinants of real exchange rate volatility in Morocco: An econometric approach," Turkish Economic Review, EconSciences Journals, volume 11, issue 3-4, pages 88-101, November.
• Hannes Ullrich & Jonas Hannane & Christian Peukert & Luis Aguiar & Tomaso Duso, 2024, "Returns to Data: Evidence from Web Tracking," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 2091.
• Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024, "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers, DNB, number 806, Mar.
• Pablo Garcia & Pascal Jacquinot & ÄŒrt LenarÄ iÄ & Kostas Mavromatis & Niki Papadopoulou & Niki Papadopoulou, 2024, "Green Transition in the Euro Area: Domestic and Global Factors," Working Papers, DNB, number 816, Oct.
• Dorinth van Dijk & Mick van Rooijen & Jasper de Winter, 2024, "DFROG: A nowcasting model for GDP growth," Working Papers, DNB, number 819, Nov.
• Chahad, Mohammed & Hofmann-Drahonsky, Anna-Camilla & Krause, Willi & Landau, Bettina & Sigwalt, Antoine, 2024, "The empirical performance of ECB/Eurosystem staff inflation projections since 2000," Economic Bulletin Articles, European Central Bank, volume 5.
• Chahad, Mohammed & Martínez Hernández, Catalina & Page, Adrian & Hofmann-Drahonsky, Anna-Camilla, 2024, "An update on the accuracy of recent Eurosystem/ECB staff projections for short-term inflation," Economic Bulletin Boxes, European Central Bank, volume 2.
• Page, Adrian, 2024, "The performance of Eurosystem/ECB staff projections for economic growth since the COVID-19 pandemic," Economic Bulletin Boxes, European Central Bank, volume 7.
• Ciccarelli, Matteo & Darracq Pariès, Matthieu & Priftis, Romanos & Angelini, Elena & Bańbura, Marta & Bokan, Nikola & Fagan, Gabriel & Gumiel, José Emilio & Kornprobst, Antoine & Lalik, Magdalena & Mo, 2024, "ECB macroeconometric models for forecasting and policy analysis," Occasional Paper Series, European Central Bank, number 344, Mar.
• Cappelletti, Giuseppe & Dimitrov, Ivan & Naruševičius, Laurynas & Le Grand, Catherine & Nunes, André & Podlogar, Jure & Röhm, Nicola & Ter Steege, Lucas, 2024, "2023 macroprudential stress test of the euro area banking system," Occasional Paper Series, European Central Bank, number 347, May.
• Allayioti, Anastasia & Venditti, Fabrizio, 2024, "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series, European Central Bank, number 2901, Feb.
• Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2024, "Nowcasting consumer price inflation using high-frequency scanner data: evidence from Germany," Working Paper Series, European Central Bank, number 2930, Apr.
• Darracq Pariès, Matthieu & Kornprobst, Antoine & Priftis, Romanos, 2024, "Monetary policy strategies to navigate post-pandemic inflation: an assessment using the ECB’s New Area-Wide Model," Working Paper Series, European Central Bank, number 2935, Apr.
• Borgioli, Stefano & Gallo, Giampiero M. & Ongari, Chiara, 2024, "Financial returns, sentiment and market volatility. A dynamic assessment," Working Paper Series, European Central Bank, number 2999, Nov.
• Linzenich, Jan & Meunier, Baptiste, 2024, "Nowcasting Made Easier: a toolbox for economists," Working Paper Series, European Central Bank, number 3004, Dec.
• Siphat Lim & Edman Flores & Casey Barnett, 2024, "Analyzing the Effectiveness of a System of Equation Model in Comparison to Single Equation Models for Predicting General Price Level in Cambodia," International Journal of Economics and Financial Issues, Econjournals, volume 14, issue 5, pages 156-166, September.
• Aarti Mehta Sharma & Saina Baby & Varsha Raghu, 2024, "Forecasting High Speed Diesel Demand in India with Econometric and Machine Learning Methods," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 1, pages 496-506, January.
• Wamiliana Wamiliana & Edwin Russel & Iskandar Ali Alam & Widiarti Widiarti & Tuti Hairani & Mustofa Usman, 2024, "Modeling and Forecasting Closing Prices of some Coal Mining Companies in Indonesia by Using the VAR(3)-BEKK GARCH(1,1) Model," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 1, pages 579-591, January.
• Bharat Kumar Meher & Abhishek Anand & Sunil Kumar & Ramona Birau & Manohar Sing, 2024, "Effectiveness of Random Forest Model in Predicting Stock Prices of Solar Energy Companies in India," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 2, pages 426-434, March.
• Anggi Putri Kurniadi & Hasdi Aimon & Zamroni Salim & Ragimun Ragimun & Adang Sonjaya & Sigit Setiawan & Viktor Siagian & Lokot Zein Nasution & R Nurhidajat & Mutaqin Mutaqin & Joko Sabtohadi, 2024, "Analysis of Existing and Forecasting for Coal and Solar Energy Consumption on Climate Change in Asia Pacific: New Evidence for Sustainable Development Goals," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 4, pages 352-359, July.
• Herry Kartika Gandhi & Ispány Márton, 2024, "Multi-step Natural Gas Price Forecasting using Ensemble Empirical Mode Decomposition and Long Short-Term Memory Hybrid Model," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 4, pages 590-598, July.
• Hatem Brik & Jihene El Ouakdi, 2024, "Interplay of Volatility and Geopolitical Tensions in Clean Energy Markets: A Comprehensive GARCH-LSTM Forecasting Approach," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 4, pages 92-107, July.
• Wellcome Peujio Jiotsop-Foze & Adrián Hernández-del-Valle & Francisco Venegas-Martínez, 2024, "Transforming Mexico’s Electric Load Infrastructure: A Quantile Transformer Network Deep Learning Approach, 2019-2020," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 5, pages 527-533, September.
• Massimiliano Caporin & Muhammad Shahbaz & Bekhzod Kuziboev & Manzura Masharipova & Sherali Allaberganov & Samariddin Makhmudov, 2024, "Environmental Kuznets Curve for Extended Brics Economies: Do Women Governance and Water Stress Matter?," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 6, pages 174-183, November.
• Abdikani Yusuf Abdulle & Idiris Sid Ali Mohamed, 2024, "The Environmental Impact of Trade Openness on CO2 Emissions: Empirical Evidence from Somalia," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 6, pages 353-364, November.
• Zhang, Huajing & Jiang, Fuwei & Liu, Yumin, 2024, "Extrapolative beliefs and return predictability: Evidence from China," Journal of Behavioral and Experimental Finance, Elsevier, volume 43, issue C, DOI: 10.1016/j.jbef.2024.100957.
• Yacoubou Djima, Ismael & Kilic, Talip, 2024, "Attenuating measurement errors in agricultural productivity analysis by combining objective and self-reported survey data," Journal of Development Economics, Elsevier, volume 168, issue C, DOI: 10.1016/j.jdeveco.2023.103249.
• Botsis, Alexandros & Görtz, Christoph & Sakellaris, Plutarchos, 2024, "Quantifying qualitative survey data with panel data," Journal of Economic Dynamics and Control, Elsevier, volume 167, issue C, DOI: 10.1016/j.jedc.2024.104929.
• Lux, Thomas, 2024, "Lack of identification of parameters in a simple behavioral macroeconomic model," Journal of Economic Dynamics and Control, Elsevier, volume 168, issue C, DOI: 10.1016/j.jedc.2024.104972.
• Delogu, Marco & Lagravinese, Raffaele & Paolini, Dimitri & Resce, Giuliano, 2024, "Predicting dropout from higher education: Evidence from Italy," Economic Modelling, Elsevier, volume 130, issue C, DOI: 10.1016/j.econmod.2023.106583.
• Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024, "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, volume 135, issue C, DOI: 10.1016/j.econmod.2024.106706.
• Granados, Camilo & Parra-Amado, Daniel, 2024, "Estimating the output gap after COVID: How to address unprecedented macroeconomic variations," Economic Modelling, Elsevier, volume 135, issue C, DOI: 10.1016/j.econmod.2024.106711.
• Song, Yuping & Huang, Jiefei & Zhang, Qichao & Xu, Yang, 2024, "Heterogeneity effect of positive and negative jumps on the realized volatility: Evidence from China," Economic Modelling, Elsevier, volume 136, issue C, DOI: 10.1016/j.econmod.2024.106745.
• Arbués, Ignacio & Matilla-García, Mariano, 2024, "Multibenchmark reality checks," Economic Modelling, Elsevier, volume 140, issue C, DOI: 10.1016/j.econmod.2024.106848.
• Conigliani, Caterina & Costantini, Valeria & Paglialunga, Elena & Tancredi, Andrea, 2024, "Forecasting the climate-conflict risk in Africa along climate-related scenarios and multiple socio-economic drivers," Economic Modelling, Elsevier, volume 141, issue C, DOI: 10.1016/j.econmod.2024.106911.
• Dufera, Tamirat Temesgen, 2024, "Fractional Brownian motion in option pricing and dynamic delta hedging: Experimental simulations," The North American Journal of Economics and Finance, Elsevier, volume 69, issue PB, DOI: 10.1016/j.najef.2023.102017.
• Li, Xiaowei & Wu, Zhengyu & Zhang, Hao & Zhang, Lu, 2024, "Risk-neutral skewness and stock market returns: A time-series analysis," The North American Journal of Economics and Finance, Elsevier, volume 70, issue C, DOI: 10.1016/j.najef.2023.102040.
• Wang, Jia & Wang, Xinyi & Wang, Xu, 2024, "International oil shocks and the volatility forecasting of Chinese stock market based on machine learning combination models," The North American Journal of Economics and Finance, Elsevier, volume 70, issue C, DOI: 10.1016/j.najef.2023.102065.
• Herrera, Rodrigo & Piña, Marco, 2024, "Market risk modeling with option-implied covariances and score-driven dynamics," The North American Journal of Economics and Finance, Elsevier, volume 72, issue C, DOI: 10.1016/j.najef.2024.102136.
• Bufalo, Michele & Ceci, Claudia & Orlando, Giuseppe, 2024, "Addressing the financial impact of natural disasters in the era of climate change," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102152.
• Maki, Daiki, 2024, "Evaluation of volatility spillovers for asymmetric realized covariance," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102177.
• Sanford, Anthony, 2024, "Information content of option prices: Comparing analyst forecasts to option-based forecasts," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102197.
• Ren, Tingting & Li, Shaofang & Zhang, Siying, 2024, "Stock market extreme risk prediction based on machine learning: Evidence from the American market," The North American Journal of Economics and Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.najef.2024.102241.
• Yang, Qu & Yu, Yuanyuan & Dai, Dongsheng & He, Qian & Lin, Yu, 2024, "Can hybrid model improve the forecasting performance of stock price index amid COVID-19? Contextual evidence from the MEEMD-LSTM-MLP approach," The North American Journal of Economics and Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.najef.2024.102252.
• Zhao, Yongchen, 2024, "Uncertainty of household inflation expectations: Reconciling point and density forecasts," Economics Letters, Elsevier, volume 234, issue C, DOI: 10.1016/j.econlet.2023.111486.
• Drautzburg, Thorsten, 2024, "A structural approach to combining external and DSGE model forecasts," Economics Letters, Elsevier, volume 235, issue C, DOI: 10.1016/j.econlet.2024.111538.
• Doan, Bao & Jayasuriya, Dulani & Lee, John B. & Reeves, Jonathan J., 2024, "Cryptocurrency systematic risk dynamics," Economics Letters, Elsevier, volume 241, issue C, DOI: 10.1016/j.econlet.2024.111788.
• Kunaschk, Max, 2024, "Enriching administrative data using survey data and machine learning techniques," Economics Letters, Elsevier, volume 243, issue C, DOI: 10.1016/j.econlet.2024.111924.
• Harel, Arie & Harpaz, Giora, 2024, "Why stock analysts may make wrong predictions?," Economics Letters, Elsevier, volume 244, issue C, DOI: 10.1016/j.econlet.2024.111956.
• Telg, Sean, 2024, "Time aggregation of mixed causal–noncausal models," Economics Letters, Elsevier, volume 244, issue C, DOI: 10.1016/j.econlet.2024.112019.
• Arai, Natsuki & Iizuka, Nobuo & Yamamoto, Yohei, 2024, "The efficiency of the Japanese government’s revenue projections," Economics Letters, Elsevier, volume 244, issue C, DOI: 10.1016/j.econlet.2024.112035.
• Lange, Rutger-Jan, 2024, "Bellman filtering and smoothing for state–space models," Journal of Econometrics, Elsevier, volume 238, issue 2, DOI: 10.1016/j.jeconom.2023.105632.
• Reuvers, Hanno & Wijler, Etienne, 2024, "Sparse generalized Yule–Walker estimation for large spatio-temporal autoregressions with an application to NO2 satellite data," Journal of Econometrics, Elsevier, volume 239, issue 1, DOI: 10.1016/j.jeconom.2023.105520.
• Diebold, Francis X. & Rudebusch, Glenn D. & Göbel, Maximilian & Goulet Coulombe, Philippe & Zhang, Boyuan, 2024, "Reprint of: When will Arctic sea ice disappear? Projections of area, extent, thickness, and volume," Journal of Econometrics, Elsevier, volume 239, issue 1, DOI: 10.1016/j.jeconom.2023.105645.
• Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024, "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, volume 240, issue 1, DOI: 10.1016/j.jeconom.2024.105693.
• Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2024, "Predictive ability tests with possibly overlapping models," Journal of Econometrics, Elsevier, volume 241, issue 1, DOI: 10.1016/j.jeconom.2024.105716.
• Daouia, Abdelaati & Padoan, Simone A. & Stupfler, Gilles, 2024, "Extreme expectile estimation for short-tailed data," Journal of Econometrics, Elsevier, volume 241, issue 2, DOI: 10.1016/j.jeconom.2024.105770.
• Oh, Dong Hwan & Patton, Andrew J., 2024, "Better the devil you know: Improved forecasts from imperfect models," Journal of Econometrics, Elsevier, volume 242, issue 1, DOI: 10.1016/j.jeconom.2024.105767.
• Mei, Ziwei & Shi, Zhentao, 2024, "On LASSO for high dimensional predictive regression," Journal of Econometrics, Elsevier, volume 242, issue 2, DOI: 10.1016/j.jeconom.2024.105809.
• Brownlees, Christian & Llorens-Terrazas, Jordi, 2024, "Empirical risk minimization for time series: Nonparametric performance bounds for prediction," Journal of Econometrics, Elsevier, volume 244, issue 1, DOI: 10.1016/j.jeconom.2024.105849.
• Inoue, Atsushi & Rossi, Barbara & Wang, Yiru, 2024, "Local projections in unstable environments," Journal of Econometrics, Elsevier, volume 244, issue 2, DOI: 10.1016/j.jeconom.2024.105726.
• Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2024, "Reprint of: Out-of-sample tests for conditional quantile coverage: An application to Growth-at-Risk," Journal of Econometrics, Elsevier, volume 244, issue 2, DOI: 10.1016/j.jeconom.2024.105746.
• Huo, Shutong & Feng, Derek & Gill, Thomas M. & Chen, Xi, 2024, "Childhood Circumstances and Health of American and Chinese Older Adults: A Machine Learning Evaluation of Inequality of Opportunity in Health," IZA Discussion Papers, IZA Network @ LISER, number 16764, Jan.
• Fiaschi, Davide & Tealdi, Cristina, 2024, "Let's Roll Back! The Challenging Task of Regulating Temporary Contracts," IZA Discussion Papers, IZA Network @ LISER, number 16777, Jan.
• Kumar, Pradeep & Nicodemo, Catia & Oreffice, Sonia & Quintana-Domeque, Climent, 2024, "Machine Learning and Multiple Abortions," IZA Discussion Papers, IZA Network @ LISER, number 17046, Jun.
• Hyee, Raphaela & Immervoll, Herwig & Fernandez, Rodrigo & Lee, Jongmi & Handscomb, Karl, 2024, "How Reliable Are Social Safety Nets in Situations of Acute Economic Need? Extended Estimates for 14 OECD Countries," IZA Discussion Papers, IZA Network @ LISER, number 17477, Nov.
• TORI Athina & GJECI Ardit & KUFO Andromahi, 2024, "Emerging from the Storm: Forecasting Bank Loan Quality in the Aftermath of COVID-19," European Journal of Interdisciplinary Studies, Bucharest Economic Academy, issue 01, March.
• Ali Mehrabani & Shahnaz Parsaeian & Aman Ullah, 2024, "Shrinkage Estimation and Forecasting in Dynamic Regression Models under Structural Instability," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 202410, Aug.
• Zongwu Cai & Gunawan & Yuying Sun, 2024, "A New Nonparametric Combination Forecasting with Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 202412, Sep, revised Sep 2024.
• Peter J. Zeitsch, 2024, "Convertible Bond Arbitrage Smart Beta," Computational Economics, Springer;Society for Computational Economics, volume 63, issue 1, pages 159-192, January, DOI: 10.1007/s10614-022-10335-6.
• Dibyendu Maiti & Naveen Kumar & Debajit Jha & Soumyadipta Sarkar, 2024, "Post-COVID Recovery and Long-Run Forecasting of Indian GDP with Factor-Augmented Error Correction Model (FECM)," Computational Economics, Springer;Society for Computational Economics, volume 63, issue 3, pages 1095-1120, March, DOI: 10.1007/s10614-023-10414-2.
• Pierre Rostan & Alexandra Rostan & John Wall, 2024, "Measuring the Resilience to the Covid-19 Pandemic of Eurozone Economies with Their 2050 Forecasts," Computational Economics, Springer;Society for Computational Economics, volume 63, issue 3, pages 1137-1157, March, DOI: 10.1007/s10614-023-10425-z.
• Helong Li & Guanglong Xu & Qin Huang & Rubin Ruan & Weiguo Zhang, 2024, "COVID-19 Impact on Stock Markets: A Multiscale Event Analysis Perspective," Computational Economics, Springer;Society for Computational Economics, volume 63, issue 3, pages 1191-1212, March, DOI: 10.1007/s10614-023-10448-6.
• Yamin Ahmad & Adam Check & Ming Chien Lo, 2024, "Unit Roots in Macroeconomic Time Series: A Comparison of Classical, Bayesian and Machine Learning Approaches," Computational Economics, Springer;Society for Computational Economics, volume 63, issue 6, pages 2139-2173, June, DOI: 10.1007/s10614-023-10397-0.
• Efstathios Polyzos & Costas Siriopoulos, 2024, "Autoregressive Random Forests: Machine Learning and Lag Selection for Financial Research," Computational Economics, Springer;Society for Computational Economics, volume 64, issue 1, pages 225-262, July, DOI: 10.1007/s10614-023-10429-9.
• Aparna Gupta & Vipula Rawte & Mohammed J. Zaki, 2024, "Predicting Firm Financial Performance from SEC Filing Changes Using Automatically Generated Dictionary," Computational Economics, Springer;Society for Computational Economics, volume 64, issue 1, pages 307-334, July, DOI: 10.1007/s10614-023-10443-x.
• Rebecca Westphal & Didier Sornette, 2024, "How Market Intervention can Prevent Bubbles and Crashes: An Agent Based Modelling Approach," Computational Economics, Springer;Society for Computational Economics, volume 64, issue 3, pages 1315-1356, September, DOI: 10.1007/s10614-023-10462-8.
• Maolin Cheng & Bin Liu, 2024, "Quarterly Data Forecasting Method Based on Extended Grey GM(2, 1, Σsin) Model and Its Application in China’s Quarterly GDP Forecasting," Computational Economics, Springer;Society for Computational Economics, volume 64, issue 4, pages 2385-2412, October, DOI: 10.1007/s10614-023-10518-9.
• Shun Chen & Lingling Guo & Lei Ge, 2024, "Increasing the Hong Kong Stock Market Predictability: A Temporal Convolutional Network Approach," Computational Economics, Springer;Society for Computational Economics, volume 64, issue 5, pages 2853-2878, November, DOI: 10.1007/s10614-024-10547-y.
• Aykut Ekinci & Safa Sen, 2024, "Forecasting Bank Failure in the U.S.: A Cost-Sensitive Approach," Computational Economics, Springer;Society for Computational Economics, volume 64, issue 6, pages 3161-3179, December, DOI: 10.1007/s10614-023-10537-6.
• Jie Cheng, 2024, "Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context," Computational Economics, Springer;Society for Computational Economics, volume 64, issue 6, pages 3617-3643, December, DOI: 10.1007/s10614-024-10571-y.
• Andrea Baldin & Trine Bille & Raghava Rao Mukkamala & Ravi Vatrapu, 2024, "The impact of social media activities on theater demand," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, volume 48, issue 2, pages 199-220, June, DOI: 10.1007/s10824-023-09480-z.
• Batuhan Kilic & Onur Can Bayrak & Fatih Gülgen & Mert Gurturk & Perihan Abay, 2024, "Unveiling the impact of machine learning algorithms on the quality of online geocoding services: a case study using COVID-19 data," Journal of Geographical Systems, Springer, volume 26, issue 4, pages 601-622, October, DOI: 10.1007/s10109-023-00435-8.
• Michael Allan Ribers & Hannes Ullrich, 2024, "Complementarities between algorithmic and human decision-making: The case of antibiotic prescribing," Quantitative Marketing and Economics (QME), Springer, volume 22, issue 4, pages 445-483, December, DOI: 10.1007/s11129-024-09284-1.
• Alessandro Bitetto & Paola Cerchiello & Stefano Filomeni & Alessandra Tanda & Barbara Tarantino, 2024, "Can we trust machine learning to predict the credit risk of small businesses?," Review of Quantitative Finance and Accounting, Springer, volume 63, issue 3, pages 925-954, October, DOI: 10.1007/s11156-024-01278-0.
• Chuxuan Xiao & Winifred Huang & David P. Newton, 2024, "Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models," Review of Quantitative Finance and Accounting, Springer, volume 63, issue 3, pages 979-1006, October, DOI: 10.1007/s11156-024-01279-z.
• Afees A. Salisu & Rangan Gupta & Oguzhan Cepni & Petre Caraiani, 2024, "Oil shocks and state-level stock market volatility of the United States: a GARCH-MIDAS approach," Review of Quantitative Finance and Accounting, Springer, volume 63, issue 4, pages 1473-1510, November, DOI: 10.1007/s11156-024-01295-z.
• Csizmadia, Péter & Kosztyán, Zsolt Tibor & Fehérvölgyi, Beáta & Hausz, Frigyes, 2024, "Intézményi koncentráció és az innovációs hálózatok vizsgálata
  [Institutional concentration and innovation networks]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), volume 0, issue 12, pages 1351-1380, DOI: 10.18414/KSZ.2024.12.1351.
• Chin Kuo-Hsuan & Lau Chi Ho, 2024, "Inflation Forecast Combination: Evidence from Taiwan," Review of Economics, De Gruyter, volume 75, issue 3, pages 215-231, DOI: 10.1515/roe-2024-0054.
• Bachmann Ronald & Boockmann Bernhard & Vonnahme Christina & Wiemann Jan Simon, 2024, "Internationale Dateninnovationen: Potenziale für die deutsche Arbeitsmarkt- und Sozialpolitik," Zeitschrift für Wirtschaftspolitik, De Gruyter, volume 73, issue 1, pages 1-23, May, DOI: 10.1515/zfwp-2024-2001.
• Paulo Barbosa & João Cortes & João Amador, 2024, "Distance to Export: A Machine Learning Approach with Portuguese Firms," GEE Papers, Gabinete de Estratégia e Estudos, Ministério da Economia, number 182, Jul, revised Jul 2024.
• David Cronin & Niall McInerney, 2024, "Institutional Quality and Official Budgetary Forecast Performance in EU Member States," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, volume 80, issue 2, pages 165-192, DOI: 10.1628/fa-2024-0005.
• Caravaggio, Nicola & Resce, Giuliano & Idola Francesca, Spanò, 2024, "Is Local Taxation Predictable? A Machine Learning Approach," Economics & Statistics Discussion Papers, University of Molise, Department of Economics, number esdp24098, Sep.
• Tomasz Piotr Kostyra, 2024, "Forecasting the yield curve for Poland with the PCA and machine learning," Bank i Kredyt, Narodowy Bank Polski, volume 55, issue 4, pages 459-478.
• Jeff Dominitz & Charles F. Manski, 2024, "Comprehensive OOS Evaluation of Predictive Algorithms with Statistical Decision Theory," NBER Working Papers, National Bureau of Economic Research, Inc, number 32269, Mar.
• Christiane Baumeister & Florian Huber & Massimiliano Marcellino, 2024, "Risky Oil: It's All in the Tails," NBER Working Papers, National Bureau of Economic Research, Inc, number 32524, May.
• Thorsten Drautzburg & Jesús Fernández-Villaverde & Pablo A. Guerrón-Quintana & Dick Oosthuizen, 2024, "Filtering with Limited Information," NBER Working Papers, National Bureau of Economic Research, Inc, number 32754, Jul.
• Alison W. Baulos & Jorge Luis García & James J. Heckman, 2024, "Perry Preschool at 50: What Lessons Should Be Drawn and Which Criticisms Ignored?," NBER Working Papers, National Bureau of Economic Research, Inc, number 32972, Sep.
• Richard Calvo & Vincent Pons & Jesse M. Shapiro, 2024, "Pitfalls of Demographic Forecasts of US Elections," NBER Working Papers, National Bureau of Economic Research, Inc, number 33016, Oct.
• Ruslan Goyenko & Bryan T. Kelly & Tobias J. Moskowitz & Yinan Su & Chao Zhang, 2024, "Trading Volume Alpha," NBER Working Papers, National Bureau of Economic Research, Inc, number 33037, Oct.
• Iva Glišic, 2024, "A comparison of using MIDAS and LSTM models for GDP nowcasting," Working Papers Bulletin, National Bank of Serbia, number 22, Mar.
• A. Bourgeois & B. Favetto, 2024, "Construction d’intervalles de confiance et relecture du passe avec le modèle Mesange," Documents de Travail de l'Insee - INSEE Working Papers, Institut National de la Statistique et des Etudes Economiques, number 2024-07.
• M. Lenza & I. Moutachaker & I. Moutachaker, 2024, "Density forecasts of inflation : a quantile regression forest approach," Documents de Travail de l'Insee - INSEE Working Papers, Institut National de la Statistique et des Etudes Economiques, number 2024-12.
• A. Quartier-La-Tente, 2024, "Utilisation de modèles de regression à coefficients variant dans le temps pour la prevision conjoncturelle," Documents de Travail de l'Insee - INSEE Working Papers, Institut National de la Statistique et des Etudes Economiques, number 2024-16.
• Lagesh Meethale Aravalath & Subhendu Dutta, 2024, "Forecasting World Food Price Volatility: Performance of the GARCH Model with Different Distributions Assumptions," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 1, pages 120-141, March.
• Tsvetan Tsvetkov, 2024, "An Innovative Approach for Vulnerability Assessment of a Nuclear Facility’s Physical Protection System," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 4, pages 829-845, December.
• Raphaela Hyee & Herwig Immervoll & Rodrigo Fernández & Jongmi Lee & Karl Handscomb, 2024, "How reliable are social safety nets in situations of acute economic need?: Extended estimates for 14 OECD countries," OECD Social, Employment and Migration Working Papers, OECD Publishing, number 317, Dec, DOI: 10.1787/568bb35b-en.
• Fabrice Murtin & Max Salomon-Ermel, 2024, "Nowcasting subjective well-being with Google Trends: A meta-learning approach," OECD Papers on Well-being and Inequalities, OECD Publishing, number 27, Jun, DOI: 10.1787/cbdfb5d9-en.
• Petra Greso & Karin Klieber, 2024, "The role of inflation subcomponents: applying maximally forward-looking core inflation to euro area countries," OeNB Bulletin, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/2024-1, pages 1-22.
• Petra Greso & Karin Klieber, 2024, "The role of inflation subcomponents: applying maximally forward-looking core inflation to euro area countries," OeNB Bulletin, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/24-1, pages 1-22.
• Friedrich Fritzer, 2024, "The instability of leading indicators in forecasting Austrian inflation: lessons from the COVID-19 pandemic and the energy crisis," OeNB Bulletin, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/24-1, pages 1-18.
• Ștefan RUSU & Marcel BOLOȘ, 2024, "Machine Learning Clustering In Financial Markets: A Literature Review," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, volume 33, issue 1, pages 330-336, July.
• Ke-Li Xu & Junjie Guo, 2024, "A New Test for Multiple Predictive Regression," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 1, pages 119-156.
• Luca Vincenzo Ballestra & Enzo D’Innocenzo & Andrea Guizzardi, 2024, "Score-Driven Modeling with Jumps: An Application to S&P500 Returns and Options," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 2, pages 375-406.
• Chao Zhang & Yihuang Zhang & Mihai Cucuringu & Zhongmin Qian, 2024, "Volatility Forecasting with Machine Learning and Intraday Commonality," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 2, pages 492-530.
• Donggyu Kim & Minseog Oh & Xinyu Song & Yazhen Wang, 2024, "Factor Overnight GARCH-Itô Models," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 5, pages 1209-1235.
• Jesús Gil Jaime & Jose Olmo, 2024, "Measuring and Testing Systemic Risk from the Cross-Section of Stock Returns†," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 5, pages 1503-1531.
• Monica P Bhatt & Sara B Heller & Max Kapustin & Marianne Bertrand & Christopher Blattman, 2024, "Predicting and Preventing Gun Violence: An Experimental Evaluation of READI Chicago," The Quarterly Journal of Economics, President and Fellows of Harvard College, volume 139, issue 1, pages 1-56.
• Sebastian Denk & Gunter Löffler, 2024, "Predicting the Equity Premium with Combination Forecasts: A Reappraisal," The Review of Asset Pricing Studies, Society for Financial Studies, volume 14, issue 4, pages 545-577.
• Yufeng Han & Ai He & David E Rapach & Guofu Zhou, 2024, "Cross-sectional expected returns: new Fama–MacBeth regressions in the era of machine learning," Review of Finance, European Finance Association, volume 28, issue 6, pages 1807-1831.
• Vipul Kumar Singh & Pawan Kumar, 2024, "Effectiveness of deterministic option pricing models: new evidence from Nifty and Bank Nifty Index options," Journal of Asset Management, Palgrave Macmillan, volume 25, issue 2, pages 172-189, March, DOI: 10.1057/s41260-024-00348-1.
• Sakai Ando & Taehoon Kim, 2024, "Systematizing Macroframework Forecasting: High-Dimensional Conditional Forecasting with Accounting Identities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, volume 72, issue 4, pages 1386-1410, December, DOI: 10.1057/s41308-023-00225-8.
• Manuel Monge, 2024, "Trends and persistence in global olive oil prices after COVID-19," Journal of Revenue and Pricing Management, Palgrave Macmillan, volume 23, issue 5, pages 481-488, October, DOI: 10.1057/s41272-024-00481-x.
• Thorsten Drautzburg & Jesus Fernandez-Villaverde & Pablo Guerron-Quintana & Dick Oosthuizen, 2024, "Filtering with Limited Information," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 24-016, Jul.
• Maria S. Mavillonio, 2024, "Textual Representation of Business Plans and Firm Success," Discussion Papers, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy, number 2024/308, May.
• Caterina Giannetti & Maria Saveria Mavillonio, 2024, "Crowdfunding Success: Human Insights vs Algorithmic Textual Extraction," Discussion Papers, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy, number 2024/315, Nov.
• Silva Lopes, Artur, 2024, "Assessing Income Convergence with a Long-Run Forecasting Approach: Some New Results," MPRA Paper, University Library of Munich, Germany, number 120143, Feb, revised Jun 2022.
• Polbin, Andrey & Shumilov, Andrei, 2024, "Прогнозирование Основных Российских Макроэкономических Показателей С Помощью Tvp-Модели С Байесовским Сжатием Параметров
  [Forecasting key Russian macroeconomic variables using a TVP model with Bayesian shrinkage]," MPRA Paper, University Library of Munich, Germany, number 120170.
• Frank, Luis, 2024, "Proyección del Consumo Privado de Argentina por medio de un Modelo de Corrección de Errores
  [Projection of Argentina's Private Consumption through an Error Correction Model]," MPRA Paper, University Library of Munich, Germany, number 121181, Jun.
• Fantazzini, Dean, 2024, "Adaptive Conformal Inference for computing Market Risk Measures: an Analysis with Four Thousands Crypto-Assets," MPRA Paper, University Library of Munich, Germany, number 121214.
• Foutzopoulos, Giorgos & Pandis, Nikolaos & Tsagris, Michail, 2024, "Predicting full retirement attainment of NBA players," MPRA Paper, University Library of Munich, Germany, number 121540, Jul.
• Mahmood, Asif & Ali, Ringchan, 2024, "A Measure of Financial Conditions for Pakistan," MPRA Paper, University Library of Munich, Germany, number 121952, Sep.
• Yang, Linge, 2024, "Shaping the USDA Agriculture Innovation Agenda: Addressing Agricultural Nonpoint Source Pollution from A Point Source Perspective," MPRA Paper, University Library of Munich, Germany, number 122265, Oct.
• Cherkashin, Alexander & Sakhadzhi, Vladislav & Guliev, Ruslan & Bolshunova, Elena, 2024, "Practical Methods for Predicting Customer Retention," MPRA Paper, University Library of Munich, Germany, number 122400, Oct.
• Черкашин, Александр & Сахаджи, Владислав & Гулиев, Руслан & Большунова, Елена, 2024, "Практические Методы Прогнозирования Сохранения Клиентской Базы (Перевод На Русский Язык)
  [Practical Methods for Predicting Customer Retention]," MPRA Paper, University Library of Munich, Germany, number 122483, Oct.
• Elshin, Leonid & Mikhalevich, Polina & Mingulov, Almaz, 2024, "Эмпирическая Оценка Влияния Экспортно-Импортных Операций На Экономический Рост Регионов Рф В Условиях Внешнего Давления
  [Empirical assessment of the impact of export-import operations on the economic growth of the regions of the Russian Federation," MPRA Paper, University Library of Munich, Germany, number 122704, Sep.
• Elshin, Leonid & Mingulov, Almaz & Mikhalevich, Polina, 2024, "Оценка Перспектив Устойчивого Развития Регионов Рф В Условиях Ограничения Экспортно-Импортных Операций С Кнр
  [Assessment of the Prospects for Sustainable Development of Russian Regions in the Context of Restricted Export-Import Operations with Chi," MPRA Paper, University Library of Munich, Germany, number 122705, Sep.
• Elshin, Leonid & Mingulov, Almaz & Mikhalevich, Polina, 2024, "Потенциал Замедления Экономики Регионов В Условиях Локализации Внешнеэкономической Деятельности С Кнр
  [Potential for a slowdown in regional economies in the context of localization of foreign economic activity with China]," MPRA Paper, University Library of Munich, Germany, number 122706, Sep.
• Elshin, Leonid & Mikhalevich, Polina & Mingulov, Almaz, 2024, "Прогностическая Оценка Устойчивого Развития Импортозависимых Секторов Экономики Региона В Условиях Внешнего Давления
  [Forecast assessment of sustainable development of import-dependent sectors of the regional economy under external pressure]," MPRA Paper, University Library of Munich, Germany, number 122707, Sep.
• Katsafados, Apostolos G. & Leledakis, George N. & Panagiotou, Nikolaos P. & Pyrgiotakis, Emmanouil G., 2024, "Can central bankers’ talk predict bank stock returns? A machine learning approach," MPRA Paper, University Library of Munich, Germany, number 122899, Oct.
• Korobova, Elena & Fantazzini, Dean, 2024, "Stablecoins and credit risk: when do they stop being stable?," MPRA Paper, University Library of Munich, Germany, number 122951.
• Rodriguez, A.E. & Kucsma, Kristen, 2024, "On the Use of the Bass Model for Forecasting Pecuniary Damages: a Reappraisal," MPRA Paper, University Library of Munich, Germany, number 124948, Nov.
• Korobilis, Dimitris & Schroeder, Maximilian, 2024, "Probabilistic Quantile Factor Analysis," MPRA Paper, University Library of Munich, Germany, number 128773, Aug.
• Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024, "Forecasting Growth-at-Risk of the United States: Housing Price versus Housing Sentiment or Attention," Working Papers, University of Pretoria, Department of Economics, number 202401, Jan.
• Massimiliano Caporin & Petre Caraiani & Oguzhan Cepni & Rangan Gupta, 2024, "Predicting the Conditional Distribution of US Stock Market Systemic Stress: The Role of Climate Risks," Working Papers, University of Pretoria, Department of Economics, number 202407, Mar.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024, "Forecasting Realized US Stock Market Volatility: Is there a Role for Economic Policy Uncertainty?," Working Papers, University of Pretoria, Department of Economics, number 202408, Mar.
• Afees A. Salisu & Ahamuefula E.Oghonna & Rangan Gupta & Oguzhan Cepni, 2024, "Energy Market Uncertainties and US State-Level Stock Market Volatility: A GARCH-MIDAS Approach," Working Papers, University of Pretoria, Department of Economics, number 202409, Mar.
• Bruno Tag Sales & Hudson Da Silva Torrent & Rangan Gupta, 2024, "Forecasting Real Housing Price Returns of the United States using Machine Learning: The Role of Climate Risks," Working Papers, University of Pretoria, Department of Economics, number 202412, Mar.
• Oguzhan Cepni & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2024, "Political Geography and Stock Market Volatility: The Role of Political Alignment across Sentiment Regimes," Working Papers, University of Pretoria, Department of Economics, number 202414, Mar.
• Matteo Foglia & Vasilios Plakandaras & Rangan Gupta & Qiang Ji, 2024, "Long-Span Multi-Layer Spillovers between Moments of Advanced Equity Markets: The Role of Climate Risks," Working Papers, University of Pretoria, Department of Economics, number 202415, Apr.
• Afees A. Salisu & Ahamuefula E. Ogbonna & Rangan Gupta & Qiang Ji, 2024, "Energy Market Uncertainties and Exchange Rate Volatility: A GARCH-MIDAS Approach," Working Papers, University of Pretoria, Department of Economics, number 202418, Apr.
• Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2024, "Climate Risks and Forecastability of US Inflation: Evidence from Dynamic Quantile Model Averaging," Working Papers, University of Pretoria, Department of Economics, number 202420, May.
• Thanoj K. Muddana & Komal S.R. Bhimireddy & Anandamayee Majumdar & Rangan Gupta, 2024, "Forecasting Gold Returns Volatility Over 1258-2023: The Role of Moments," Working Papers, University of Pretoria, Department of Economics, number 202421, May.
• Rangan Gupta & Christian Pierdzioch, 2024, "Multi-Task Forecasting of the Realized Volatilities of Agricultural Commodity Prices," Working Papers, University of Pretoria, Department of Economics, number 202423, Jun.
• Elie Bouri & Rangan Gupta & Asingamaanda Liphadzi & Christian Pierdzioch, 2024, "Forecasting Stock Returns Volatility of the G7 Over Centuries: The Role of Climate Risks," Working Papers, University of Pretoria, Department of Economics, number 202424, Jun.
• Kejin Wu & Sayar Karmakar & Rangan Gupta, 2024, "GARCHX-NoVaS: A Model-Free Approach to Incorporate Exogenous Variables," Working Papers, University of Pretoria, Department of Economics, number 202425, Jun.
• Rangan Gupta & Christian Pierdzioch & Aviral K. Tiwari, 2024, "Gasoline Prices and Presidential Approval Ratings of the United States," Working Papers, University of Pretoria, Department of Economics, number 202427, Jun.
• Rangan Gupta & Christian Pierdzioch, 2024, "Climate Policy Uncertainty and Financial Stress: Evidence for China," Working Papers, University of Pretoria, Department of Economics, number 202428, Jun.
• Afees A. Salisu & Ahamuefula E. Ogbonna & Rangan Gupta, 2024, "Geopolitical Risks and Oil Returns Volatility: A GARCH-MIDAS Approach," Working Papers, University of Pretoria, Department of Economics, number 202429, Jun.
• Afees A. Salisu & Ahamuefula E. Ogbonna & Rangan Gupta & Sisa Shiba, 2024, "Energy Market Uncertainties and Gold Return Volatility: A GARCH-MIDAS Approach," Working Papers, University of Pretoria, Department of Economics, number 202431, Jul.