Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2024

• Etienne Briand & Massimiliano Marcellino & Dalibor Stevanovic, 2024, "Inflation, Attention and Expectations," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 24-05, Dec, revised Dec 2024.
• Antoine Poulin-Moore & Kerem Tuzcuoglu, 2024, "Forecasting Recessions in Canada: An Autoregressive Probit Model Approach," Staff Working Papers, Bank of Canada, number 24-10, Mar, DOI: 10.34989/swp-2024-10.
• Tony Chernis & Gary Koop & Emily Tallman & Mike West, 2024, "Decision Synthesis in Monetary Policy," Staff Working Papers, Bank of Canada, number 24-30, Aug, DOI: 10.34989/swp-2024-30.
• Pablo Garcia & Pascal Jacquinot & Crt Lenarcic & Kostas Mavromatis & Niki Papadopoulou & Edgar Silgado-Gómez, 2024, "Green Transition in the euro area: Domestic and global factors," BCL working papers, Central Bank of Luxembourg, number 190, Sep.
• Furkan TURKOGLU & Eda GOCECEK & Yavuz YUMRUKUZ, 2024, "Predictive Abilities of Machine Learning and Deep Learning Approaches for Exchange Rate Prediction," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, volume 18, issue 2, pages 186-210.
• Todd E. Clark & Gergely Ganics & Elmar Mertens, 2024, "Constructing fan charts from the ragged edge of SPF forecasts," Working Papers, Banco de España, number 2429, Sep, DOI: https://doi.org/10.53479/37597.
• Alicia Aguilar & Ricardo Gimeno, 2024, "Discrete Probability Forecasts: What to expect when you are expecting a monetary policy decision," Working Papers, Banco de España, number 2438, Oct, DOI: https://doi.org/10.53479/37893.
• Francesco Braggiotti & Nicola Chiarini & Giulio Dondi & Luciano Lavecchia & Valeria Lionetti & Juri Marcucci & Riccardo Russo, 2024, "Predicting buildings' EPC in Italy: a machine learning based-approach," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 850, Jun.
• Davide Delle Monache & Claudia Pacella, 2024, "The drivers of inflation dynamics in Italy over the period 2021-2023," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 873, Oct.
• Donato Ceci & Orest Prifti & Andrea Silvestrini, 2024, "Nowcasting Italian GDP growth: a Factor MIDAS approach," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1446, Mar.
• Andrea Gazzani & Fabrizio Venditti & Giovanni Veronese, 2024, "Oil price shocks in real time," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1448, Mar.
• Simon Freyaldenhoven & Christian B. Hansen & Jorge Pérez Pérez & Jesse M. Shapiro & Constantino Carreto, 2024, "Policy Effect Estimation and Visualization in Linear Panel Event-Study Designs: Introducing the xtevent Package," Working Papers, Banco de México, number 2024-09, Aug.
• Lenin Arango-Castillo & Francisco J. Martínez-Ramírez & María José Orraca, 2024, "Univariate Measures of Persistence: A Comparative Analysis," Working Papers, Banco de México, number 2024-11, Sep.
• Magnus Saß, 2024, "Detecting excessive credit growth: An approach based on structural counterfactuals," Berlin School of Economics Discussion Papers, Berlin School of Economics, number 0046, Aug, DOI: 10.48462/opus4-5591.
• Gary Cornwall & Marina Gindelsky, 2024, "Nowcasting Distributional National Accounts for the United States: A Machine Learning Approach," BEA Papers, Bureau of Economic Analysis, number 0130, Sep.
• Pınar Karadayı Ataş, 2024, "A Novel Hybrid Regression Model for Banking Loss Estimation," Bingol University Journal of Economics and Administrative Sciences, Bingol University, Faculty of Economics and Administrative Sciences, volume 8, issue 1, pages 91-105, June, DOI: https://doi.org/10.33399/biibfad.13.
• Ilia Chapyshev & Ansel Shaidullin, 2024, "Study of the Problem of Interoperability of the Bank of Russia's Digital Currency," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 1, pages 104-126, March.
• Anastasiia Pankratova, 2024, "Forecasting Key Macroeconomic Indicators Using DMA and DMS Methods," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 1, pages 32-52, March.
• Urmat Dzhunkeev, 2024, "Forecasting Inflation in Russia Using Gradient Boosting and Neural Networks," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 1, pages 53-76, March.
• Anastasia Mogilat & Oleg Kryzhanovskiy & Zhanna Shuvalova & Yaroslav Murashov, 2024, "DYFARUS: Dynamic Factor Model to Forecast GDP by Output Using Input-Output Tables," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 2, pages 3-25, June.
• Yury Perevyshin, 2024, "Analysts' Inflation Expectations vs Univariate Models of Inflation Forecasting in the Russian Economy," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 2, pages 54-76, June.
• Rodion Latypov & Elena Akhmedova & Egor Postolit & Marina Mikitchuk, 2024, "Bottom-up Inflation Forecasting Using Machine Learning Methods," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 3, pages 23-44, September.
• Alexandra Bozhechkova & Urmat Dzhunkeev, 2024, "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 3, pages 45-69, September.
• Oguzhan Cepni & Rangan Gupta & Wenting Liao & Jun Ma, 2024, "Climate risks and forecastability of the weekly state‐level economic conditions of the United States," International Review of Finance, International Review of Finance Ltd., volume 24, issue 1, pages 154-162, March, DOI: 10.1111/irfi.12431.
• Leona Han Chen & Yijie Fei & Jun Yu, 2024, "Multivariate Stochastic Volatility Models based on Generalized Fisher Transformation," Working Papers, University of Macau, Faculty of Business Administration, number 202419, Oct.
• Fernando Eguren-Martin & Sevim Kösem & Guido Maia & Andrej Sokol, 2024, "Targeted financial conditions indices and growth-at-risk," Bank of England working papers, Bank of England, number 1084, Aug.
• Mehrabani Ali & Parsaeian Shahnaz & Ullah Aman, 2024, "Shrinkage Estimation and Forecasting in Dynamic Regression Models Under Structural Instability," Journal of Econometric Methods, De Gruyter, volume 13, issue 2, pages 251-279, DOI: 10.1515/jem-2023-0036.
• Prüser Jan, 2024, "Forecasting the Risk of Cryptocurrencies: Comparison and Combination of GARCH and Stochastic Volatility Models," Journal of Time Series Econometrics, De Gruyter, volume 16, issue 2, pages 83-108, DOI: 10.1515/jtse-2023-0039.
• Mohamed Riyath Mohamed Ismail & Aldabbous Nagham, 2024, "Long-Run Volatility Memory Dynamics and Inter-Market Linkages in GCC Equity Markets: Application of DCC-FIGARCH Models," Review of Middle East Economics and Finance, De Gruyter, volume 20, issue 3, pages 299-329, DOI: 10.1515/rmeef-2024-0018.
• Chernis Tony, 2024, "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 28, issue 2, pages 293-317, April, DOI: 10.1515/snde-2022-0108.
• 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.
• Agarwala, M. & Burke, M. & Doherty-Bigara, J. & Klusak, P. & Mohaddes, K., 2024, "Climate Change and Sovereign Risk: A Regional Analysis for the Caribbean," Janeway Institute Working Papers, Faculty of Economics, University of Cambridge, number 2414, Apr.
• Burke, M. & Agarwala, M. & Klusak, P. & Mohaddes, K., 2024, "Climate Policy and Sovereign Debt: The Impact of Transition Scenarios on Sovereign Creditworthiness," Janeway Institute Working Papers, Faculty of Economics, University of Cambridge, number 2430, 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.
• 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. M. 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.
• G.M. Gallo & C.Ongari & S. Borgioli, 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, C.E.P.R. Discussion Papers, number 18901, Mar.
• Marcellino, Massimiliano & Pfarrhofer, Michael, 2024, "Bayesian nonparametric methods for macroeconomic forecasting," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18970, Apr.
• Baumeister, Christiane & Huber, Florian & Marcellino, Massimiliano, 2024, "Risky Oil: It's All in the Tails," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19129, Jun.
• Kwon, Alexander & Maliar, Lilia, 2024, "Predicting Retirement and Social Security Claiming Decisions using Machine Learning," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19198, Jul.
• Ullrich, Hannes & Hannane, Jonas & Peukert, Christian & Aguiar, Luis & Duso, Tomaso, 2024, "Returns to Data: Evidence from Web Tracking," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19266, Jul.
• Drautzburg, Thorsten & Fernández-Villaverde, Jesús & Guerron, Pablo & Oosthuizen, Dick, 2024, "Filtering with Limited Information," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19270, Jul.
• Hauzenberger , Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2024, "Bayesian Neural Networks for Macroeconomic Analysis," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19381, Aug.
• Bassetti, Federico & Casarin, Roberto & Del Negro, Marco, 2024, "A Bayesian Approach for Inference on Probabilistic Surveys," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19426, Sep.
• 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.
• Vu, Patrick, 2024, "Why are replication rates so low?," Journal of Econometrics, Elsevier, volume 245, issue 1, DOI: 10.1016/j.jeconom.2024.105868.
• Chudik, Alexander & Pesaran, M. Hashem & Sharifvaghefi, Mahrad, 2024, "Variable selection in high dimensional linear regressions with parameter instability," Journal of Econometrics, Elsevier, volume 246, issue 1, DOI: 10.1016/j.jeconom.2024.105900.
• Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2024, "Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility," Econometrics and Statistics, Elsevier, volume 32, issue C, pages 34-56, DOI: 10.1016/j.ecosta.2021.08.002.
• Berlin, Mitchell & Byun, Sung Je & D'Erasmo, Pablo & Yu, Edison, 2024, "Measuring climate transition risk at the regional level with an application to community banks," European Economic Review, Elsevier, volume 170, issue C, DOI: 10.1016/j.euroecorev.2024.104834.
• Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2024, "Labour at risk," European Economic Review, Elsevier, volume 170, issue C, DOI: 10.1016/j.euroecorev.2024.104849.
• Montorsi, Carlotta & Fusco, Alessio & Van Kerm, Philippe & Bordas, Stéphane P.A., 2024, "Predicting depression in old age: Combining life course data with machine learning," Economics & Human Biology, Elsevier, volume 52, issue C, DOI: 10.1016/j.ehb.2023.101331.
• Coqueret, Guillaume & Deguest, Romain, 2024, "Unexpected opportunities in misspecified predictive regressions," European Journal of Operational Research, Elsevier, volume 318, issue 2, pages 686-700, DOI: 10.1016/j.ejor.2024.05.044.
• Hernández, Juan R. & Ventosa-Santaulària, Daniel & Valencia, J. Eduardo, 2024, "Global supply chain inflationary pressures and monetary policy in Mexico," Emerging Markets Review, Elsevier, volume 58, issue C, DOI: 10.1016/j.ememar.2023.101089.
• Lo, Gaye-Del & Marcelin, Isaac & Bassène, Théophile & Lo, Assane, 2024, "Connectedness and risk spillovers among sub-Saharan Africa and MENA equity markets," Emerging Markets Review, Elsevier, volume 63, issue C, DOI: 10.1016/j.ememar.2024.101193.
• 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.
• 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.
• 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 Baye," 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 econom," 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 Conte," 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 econo," 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 t," 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.