Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2026

• Carlos Montes-Galdón & Joan Paredes & Elias Wolf, 2026, "A robust approach to tilting: parametric relative entropy," Working and Discussion Papers, Research Department, National Bank of Slovakia, number WP 2/2026, Feb.
• Garratt Anthony & Petrella Ivan & Zhang Yunyi, 2026, "The Predictive Content of U.S. Energy Information Administration Oil Market Forecasts," Working papers, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino, number 104, Mar.
• Yachou Najlae & Abahman Omar & Hakimi Khalid, 2026, "Designing an LSTM-Based Model for Financial Asset Forecasting Using Machine Learning," Central European Economic Journal, Sciendo, volume 13, issue 60, pages 1-23, DOI: 10.2478/ceej-2026-0001.
• Harold Glenn A. Valera & Cymon Kayle Lubangco & Mark J. Holmes, 2026, "Does repeated cross-section data help explain consumer inflation expectations revisions?," Working Papers in Economics, University of Waikato, number 26/03, Feb.
• Evangelos E. Ioannidis & Sofia‐Eirini Nikolakakou, 2026, "Modeling and Forecasting Stochastic Seasonality: Are Seasonal Autoregressive Integrated Moving Average Models Always the Best Choice?," Journal of Forecasting, John Wiley & Sons, Ltd., volume 45, issue 1, pages 316-334, January, DOI: 10.1002/for.70034.
• Verona, Fabio, 2026, "Forecasting inflation: The sum of the cycles outperforms the whole," Bank of Finland Research Discussion Papers, Bank of Finland, number 1/2026.
• Fausch, Jürg & Frigg, Moreno & Ruenzi, Stefan & Weigert, Florian, 2026, "Machine learning mutual fund flows," CFR Working Papers, University of Cologne, Centre for Financial Research (CFR), number 26-03.
• Dallari, Pietro & Gattini, Luca, 2026, "How severe are European regulatory stress test scenarios? A probabilistic calibration for the euro area," EIB Working Papers, European Investment Bank (EIB), number 2026/01, DOI: 10.2867/0689043.
• Guest, Oliver & Steenkamp, Daan, 2026, "Is the rand at fair value?," EconStor Research Reports, ZBW - Leibniz Information Centre for Economics, number 336005.
• Heinisch, Katja & van Norden, Simon & Wildi, Marc, 2026, "Smooth and persistent forecasts of German GDP: Balancing accuracy and stability," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 1/2026, DOI: 10.18717/dp99kr-7336.
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Schult, Christoph & Zeddies, Götz, 2026, "Einhaltung der EU-Fiskalregeln erfordert umfangreiche Konsolidierung: Mittelfristige Projektion der gesamtwirtschaftlichen Entwicklung und der öffentlichen Finanzen in Deutschland," IWH Policy Notes, Halle Institute for Economic Research (IWH), number 1/2026, DOI: 10.18717/pnb1fm-ja32.
• Kerim Keskin, 2026, "A game theory approach to football predictions," Public Choice, Springer, volume 206, issue 1, pages 241-261, January, DOI: 10.1007/s11127-025-01317-x.
• Ewa Dziwok & Witold Szczepaniak, 2026, "Systemic risk and climate change: a joint impact of transition and physical climate risks on the Polish banking sector," Bank i Kredyt, Narodowy Bank Polski, volume 57, issue 1, pages 105-134.
• Ming Gu & David Hirshleifer & Siew Hong Teoh & Shijia Wu, 2026, "GIFfluence: A Visual Approach to Investor Sentiment and the Stock Market," NBER Working Papers, National Bureau of Economic Research, Inc, number 34636, Jan.
• Joshua S. Gans, 2026, "Optimal Use of Preferences in Artificial Intelligence Algorithms," NBER Working Papers, National Bureau of Economic Research, Inc, number 34780, Jan.
• Lauren Cohen & Yiwen Lu & Quoc H. Nguyen, 2026, "Mimicking Finance," NBER Working Papers, National Bureau of Economic Research, Inc, number 34849, Feb.
• Kurt G. Lunsford & Kenneth D. West, 2026, "An Empirical Evaluation of Some Long-Horizon Macroeconomic Forecasts," NBER Working Papers, National Bureau of Economic Research, Inc, number 34904, Feb.
• Lauren Cohen & Bo Li, 2026, "The Micro-Geography of Persuasion: Randomized Peer Exposure and Legislative Outcomes," NBER Working Papers, National Bureau of Economic Research, Inc, number 34925, Mar.
• Takashi Miyahara & Laura Betschka, 2026, "Can the Sahm rule indicator signal recession in OECD countries?," OECD Statistics Working Papers, OECD Publishing, number 2026/01, Mar.
• Wojciech Starosta, 2026, "Calibrating credit risk parameters for climate stress testing," Risk Management, Palgrave Macmillan, volume 28, issue 1, pages 1-24, February, DOI: 10.1057/s41283-025-00189-1.
• Bahaa Aly, Tarek, 2026, "Global Economic Cycles Unveiled: A Hybrid TCN-HMM Approach for Regime Dynamics Across Eight Nations," MPRA Paper, University Library of Munich, Germany, number 127574, Jan.
• Kahambwe, Christ & Aidini, Christian & E.Loemba, Alexandre, 2026, "Intelligence artificielle et transformation de la relation croissance –emploi : une relecture empirique de la loi d’okun
  [Artificial Intelligence and the transformation of the growth–employment nexus: an empirical reappraisal of okun’s law]," MPRA Paper, University Library of Munich, Germany, number 127930, Jan, revised 2026.
• Giovanni Bonaccolto & Massimiliano Caporin & Oguzhan Cepni & Rangan Gupta, 2026, "Forecasting Realized Volatility of State-Level Stock Markets of the United States: The Role of Sentiment," Working Papers, University of Pretoria, Department of Economics, number 202603, Feb.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2026, "Credit Standards: A New Predictor of U.S. Stock Market Realized Volatility," Working Papers, University of Pretoria, Department of Economics, number 202607, Mar.
• Yang Yu & Yaping Gong & DooHwan Won & Atif Jahanger, 2026, "Regional Disparities in Drivers and Peaking Pathways of CO2 Emissions: Insights from Scenario Planning," Politická ekonomie, Prague University of Economics and Business, volume 2026, issue 1, pages 170-197, DOI: 10.18267/j.polek.1484.
• Luz Judith Rodríguez Esparza & Dolly Anabel Ortiz Lazcano, 2026, "A stochastic model to analyze the dynamics of poverty and social mobility in Mexico," EconoQuantum, Revista de Economia y Finanzas, Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas, Departamento de Metodos Cuantitativos y Maestria en Economia., volume 23, issue 1, pages 25-48, January-J.
• Mara Giua & Francesca Micocci & Giulia Valeria Sonzogno, 2026, "Enhancing Implementation SuccessinCohesion Policy. A Machine Learning Approach," Departmental Working Papers of Economics - University 'Roma Tre', Department of Economics - University Roma Tre, number 0289, Mar.
• Dimitris Anastasiou & Apostolos Katsafados & Christos Tzomakas, 2026, "Banks’ stock price crash risk prediction with textual analysis: a machine learning approach," Annals of Operations Research, Springer, volume 357, issue 1, pages 89-111, February, DOI: 10.1007/s10479-025-06567-y.
• Philippe Bertrand & Jean-luc Prigent, 2026, "On the performance of factor investing: an analysis based on constant mix and buy-and-hold strategies," Annals of Operations Research, Springer, volume 357, issue 1, pages 531-563, February, DOI: 10.1007/s10479-025-06644-2.
• Xiaoqing Luo, 2026, "When simplicity fails: forecasting Mainland Chinese tourist arrivals in Macao during structural breaks with a hybrid economic-search model," Asia-Pacific Journal of Regional Science, Springer, volume 10, issue 1, pages 1-31, March, DOI: 10.1007/s41685-026-00419-8.
• Vaibhav Gagneja & Mayank Gupta & Sanjay Batish & Poonam Saini & Sudesh Rani, 2026, "ES-LSTM: a hybrid model for accurate time series forecasting in financial markets," Digital Finance, Springer, volume 8, issue 1, pages 1-21, March, DOI: 10.1007/s42521-025-00173-0.
• Christos Tzomakas, 2026, "Monetary policy transmission and the yield curve: the role of external market factors against the backdrop of Brexit," Empirical Economics, Springer, volume 70, issue 1, pages 1-42, January, DOI: 10.1007/s00181-025-02874-2.
• Alena Skolkova, 2026, "Model averaging with ridge regularization," Empirical Economics, Springer, volume 70, issue 2, pages 1-19, February, DOI: 10.1007/s00181-025-02866-2.
• Elliot Beck & Michael Wolf, 2026, "Forecasting inflation with the hedged random forest," Empirical Economics, Springer, volume 70, issue 2, pages 1-36, February, DOI: 10.1007/s00181-025-02879-x.
• Visa Kuntze & Henri Nyberg & Samuel Rauhala, 2026, "Similarity-based path forecasting of US recession periods," Empirical Economics, Springer, volume 70, issue 3, pages 1-18, March, DOI: 10.1007/s00181-026-02893-7.
• Arthur Jonath & Fred Khorasani & John O’Connell, 2026, "The consumer-to-producer temperature gradient predicts leading indicators: a new economic measurement based on physical principles and cause and effect," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 12, issue 1, pages 1-24, December, DOI: 10.1186/s40854-025-00805-9.
• Radmir Mishelevich Leushuis & Nicolai Petkov, 2026, "Advances in forecasting realized volatility: a review of methodologies," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 12, issue 1, pages 1-29, December, DOI: 10.1186/s40854-025-00809-5.
• Hugo Gobato Souto & Amir Moradi, 2026, "Enhancing financial risk management: a novel multivariate neural network approach for realized covariance matrix prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 12, issue 1, pages 1-26, December, DOI: 10.1186/s40854-025-00816-6.
• Afees A. Salisu & Abeeb O. Olaniran, 2026, "Energy market uncertainty and economic conditions at the global and U.S. State levels," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 50, issue 1, pages 1-51, December, DOI: 10.1007/s12197-025-09739-5.
• Elie Bouri & Rangan Gupta & Asingamaanda Liphadzi & Christian Pierdzioch, 2026, "Forecasting the volatility of stock returns in the G7 countries over centuries: the role of climate risks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 50, issue 1, pages 1-32, December, DOI: 10.1007/s12197-026-09751-3.
• Tu DQ Le & Son H Tran & Thanh Ngo & Hung D Bui, 2026, "Forecasting Vietnam Inflation Using Machine Learning Approaches: A Comprehensive Analysis," Advances in Decision Sciences, Asia University, Taiwan, volume 30, issue 1, pages 136-185.
• Jose Rizal & Nur Afandi & Gusman Juliadi & Indah Wahyuliani & Cinta Rizki Oktarina, 2026, "Forecasting the Appearance Frequency of Rafflesia arnoldii in Bengkulu, Indonesia, Using Discrete-valued Time Series Modeling," Advances in Decision Sciences, Asia University, Taiwan, volume 30, issue 2, pages 39-67, March.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2026, "Asymmetric Roles of Macroeconomic Variables in the Real Exchange Rate: Insights from U.S.-Korea Data," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2026-01, Jan.
• Casoli, Chiara & Lucchetti, Riccardo, 2026, "A rotated Dynamic Factor Model for the yield curve: squeezing out information when it matters," FEEM Working Papers, Fondazione Eni Enrico Mattei (FEEM), number 388985, Jan, DOI: 10.22004/ag.econ.388985.
• Katarzyna Chec & Bartosz Uniejewski & Rafal Weron, 2026, "From biased point forecasts of electricity demand to accurate predictive distributions: Using LASSO and GAMLSS," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/26/01.
• Cansu Çilingir Kara, 2026, "The Impact of R&D Intensity and Financial Slack on Company Performance: An Analysis of Companies with the Highest R&D Expenditure in Türkiye," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 10, issue 4, pages 1366-1381, DOI: 10.30784/epfad.1666691.
• Chiara Casoli & Riccardo Lucchetti, 2026, "A rotated Dynamic Factor Model for the yield curve: squeezing out information when it matters," Working Papers, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali, number 503, Jan.
• Ахмет Алишер // Alisher Akhmet, 2026, "Прогнозирование ВВП Казахстана на основе динамической факторной модели с регуляризацией // Forecasting Kazakhstan’s GDP Based on a Dynamic Factor Model with Regularization," Working Papers, National Bank of Kazakhstan, number #2026-1.
• Niko Hauzenberger Massimiliano Marcellino Michael Pfarrhofer Anna Stelzer, 2026, "Direct Gaussian Process Predictive Regressions with Mixed Frequency Data," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 26265.
• Guanglan Zhou & Ziyi Wu, 2026, "A resilient model for trade volume forecasting under economic uncertainty: Addressing challenges in the global supply chain," E&M Economics and Management, Technical University of Liberec, Faculty of Economics, volume 29, issue 1, pages 207-224, March, DOI: 10.15240/tul/001/2026-1-013.
• Rocío Clara A. Mora-Quiñones & Antonio José Orozco-Gallo & Dora Alicia Mora-Pérez, 2026, "Sentiment and Uncertainty Indices from economic news in Colombia," Borradores de Economia, Banco de la Republica de Colombia, number 1340, Jan, DOI: 10.32468/be.1340.
• Renato Vassallo & Margherita Philipp & Christopher Rauh & Hannes Mueller & Laura Mayoral, 2026, "Semantic Similarity Measures in Newspaper Text for Detecting and Predicting Disruptive Institutional Events," Working Papers, Barcelona School of Economics, number 1555, Jan.
• Danila Ovechkin, 2026, "Estimation and forecasting with a Nonlinear Phillips Curve based on heterogeneous sensitivity between economic activity and CPI components," Bank of Russia Working Paper Series, Bank of Russia, number wps161, Jan.
• Oguzhan Cepni & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2026, "Political Geography and Stock Market Volatility: The Role of Political Alignment Across Sentiment Regimes," Scottish Journal of Political Economy, Scottish Economic Society, volume 73, issue 1, February, DOI: 10.1111/sjpe.70028.
• Tom Doan, 2026, "MATHESONSTAVREVEL2013: RATS programs to replicate Matheson-Stavrev(2013) non-linear state-space model," Statistical Software Components, Boston College Department of Economics, number RTJ00054, revised .
• Panagiotis Delis & Georgios Kontogeorgos, 2026, "Outlier-robust evaluation of fixed-event macroeconomic survey expectations," Working Papers, Bank of Greece, number 356, Jan, DOI: 10.52903/wp2026356.
• Nonejad Nima, 2026, "Out-of-Sample Density Prediction of the End-of-Month Price of Crude Oil and the U.S. Economic Policy Uncertainty Index," Journal of Time Series Econometrics, De Gruyter, volume 18, issue 1, pages 1-47, DOI: 10.1515/jtse-2025-0007.
• Mayoral, L. & Mueller, H. & Philipp, M. & Rauh, C. & Vassallo, R., 2026, "Semantic Similarity Measures in Newspaper Text for Detecting and Predicting Disruptive Institutional Events," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2609, Jan.
• Congressional Budget Office, 2026, "The Accuracy of CBO's Budget Projections for Fiscal Year 2025," Reports, Congressional Budget Office, number 61916, Jan.
• Uluc Aysun & Melanie Guldi, 2026, "Revisiting exchange rate predictability: Can machine learning with theoretical filtering outperform canonical models?," Working Papers, University of Central Florida, Department of Economics, number 2026-01, Jan.
• Eraslan, Sercan & Fabbri, Andrea & Saiz, Lorena, 2026, "Short-term forecasting of euro area economic activity in an uncertain world," Economic Bulletin Articles, European Central Bank, volume 8.
• Montes-Galdón, Carlos & Paredes, Joan & Wolf, Elias, 2026, "A robust approach to tilting: parametric relative entropy," Working Paper Series, European Central Bank, number 3200, Mar.
• Mahler, Daniel Gerszon & Schoch, Marta & Lakner, Christoph & Nguyen, Minh Cong, 2026, "A parsimonious approach to predicting income distributions," Journal of Development Economics, Elsevier, volume 180, issue C, DOI: 10.1016/j.jdeveco.2025.103695.
• Chironna, Gianpiero & Orlando, Giuseppe, 2026, "Predicting bank defaults in Italy: A comparative analysis of conventional and machine learning approaches," Economic Analysis and Policy, Elsevier, volume 89, issue C, pages 788-833, DOI: 10.1016/j.eap.2025.12.002.
• Shah, Sayar Ahmad & Garg, Bhavesh, 2026, "Dynamics of exchange rate pass-through: The role of pricing strategies and economic shocks," Economic Modelling, Elsevier, volume 154, issue C, DOI: 10.1016/j.econmod.2025.107353.
• Guerzoni, Marco & Riso, Luigi & Zoia, M. Grazia, 2026, "Extreme weather events as the main driver of electricity price volatility in Italy: A GARCH-MIDAS approach with machine learning-based variable selection," The North American Journal of Economics and Finance, Elsevier, volume 81, issue C, DOI: 10.1016/j.najef.2025.102512.
• Aslam, Adnan & Brahmana, Rayenda Khresna, 2026, "Systemic spillovers in high-growth private market sectors: determinants and portfolio implications," The North American Journal of Economics and Finance, Elsevier, volume 82, issue C, DOI: 10.1016/j.najef.2025.102579.
• Caldeira, João F. & Cordeiro, Werley C., 2026, "Decomposing nominal and real yield curves and inflation forecasting: Evidence from Brazil," Economics Letters, Elsevier, volume 258, issue C, DOI: 10.1016/j.econlet.2025.112712.
• Goulet Coulombe, Philippe & Klieber, Karin, 2026, "An adaptive moving average for macroeconomic monitoring," Economics Letters, Elsevier, volume 259, issue C, DOI: 10.1016/j.econlet.2025.112773.
• Quinlan, Rory & Pinheiro, Roberto, 2026, "BLS payroll revisions: Forecasting recessions," Economics Letters, Elsevier, volume 261, issue C, DOI: 10.1016/j.econlet.2026.112859.
• Patton, Andrew J. & Zhang, Haozhe, 2026, "Bespoke realized volatility: Tailored measures of risk for volatility prediction," Journal of Econometrics, Elsevier, volume 254, issue PA, DOI: 10.1016/j.jeconom.2025.106122.
• Garcia, Pablo & Jacquinot, Pascal & Lenarčič, Črt & Mavromatis, Kostas & Papadopoulou, Niki & Silgado-Gómez, Edgar, 2026, "Green transition in the euro area: Domestic and global factors," European Economic Review, Elsevier, volume 182, issue C, DOI: 10.1016/j.euroecorev.2025.105206.
• Nam, Kyungsik & Seo, Won-Ki, 2026, "Nonlinear temperature sensitivity of residential electricity demand: Evidence from a distributional regression approach," Energy Economics, Elsevier, volume 153, issue C, DOI: 10.1016/j.eneco.2025.109076.
• Ghelasi, Paul & Ziel, Florian, 2026, "A data-driven merit order: Learning a fundamental electricity price model," Energy Economics, Elsevier, volume 154, issue C, DOI: 10.1016/j.eneco.2025.109114.
• Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2026, "The predictive content of U.S. Energy Information Administration oil market forecasts," Energy Economics, Elsevier, volume 156, issue C, DOI: 10.1016/j.eneco.2026.109214.
• Yu, Deshui & Tang, Jiachen & Zhou, Mingtao, 2026, "Trade policy uncertainty and stock returns: A tale of two periods," International Review of Financial Analysis, Elsevier, volume 109, issue C, DOI: 10.1016/j.irfa.2025.104789.
• Zhou, Fan & Guo, Wenjing, 2026, "Time-varying network structure and volatility prediction in the cryptocurrency market," Finance Research Letters, Elsevier, volume 87, issue C, DOI: 10.1016/j.frl.2025.109028.
• Benmoussa, Amor Aniss & Ellwanger, Reinhard & Snudden, Stephen, 2026, "Carpe diem: Can daily oil prices improve model-based forecasts of the real price of crude oil?," International Journal of Forecasting, Elsevier, volume 42, issue 1, pages 281-295, DOI: 10.1016/j.ijforecast.2025.02.009.
• Bürgi, Constantin & Ortiz, Julio L., 2026, "Overreaction through anchoring," International Journal of Forecasting, Elsevier, volume 42, issue 2, pages 512-526, DOI: 10.1016/j.ijforecast.2025.08.002.
• Bolivar, Osmar, 2026, "High-frequency inflation forecasting: A two-step machine learning methodology," Latin American Journal of Central Banking (previously Monetaria), Elsevier, volume 7, issue 1, DOI: 10.1016/j.latcb.2025.100172.
• Gemmi, Luca & Valchev, Rosen, 2026, "Biased surveys," Journal of Monetary Economics, Elsevier, volume 157, issue C, DOI: 10.1016/j.jmoneco.2025.103868.
• Hubrich, Kirstin & Schüler, Yves & Waggoner, Daniel, 2026, "Financial shocks and leverage of financial institutions: When do they matter?," Journal of Monetary Economics, Elsevier, volume 158, issue C, DOI: 10.1016/j.jmoneco.2026.103900.
• Bonato, Matteo & Demirer, Riza & Gupta, Rangan & Olaniran, Abeeb, 2026, "Does mining activity drive crash risks in bitcoin?," The Quarterly Review of Economics and Finance, Elsevier, volume 105, issue C, DOI: 10.1016/j.qref.2025.102082.
• Salisu, Afees A. & Gupta, Rangan & Cepni, Oguzhan, 2026, "Housing market variables and predictability of state-level stock market volatility of the United States: Fundamentals versus sentiments in a mixed-frequency framework," The Quarterly Review of Economics and Finance, Elsevier, volume 105, issue C, DOI: 10.1016/j.qref.2025.102087.
• Mati, Sagiru & Usman, Abdullahi G. & Ismael, Goran Yousif & Babuga, Umar Tijjani & Nadarajah, Saralees & Masoud, Serag & Uzun Ozsahin, Dilber & Abba, Sani I., 2026, "Explainable support vector regression coupled with quantum firefly optimisation algorithm for carbon emission prediction in West Africa: The role of socioeconomic, energy, and environmental factors," Renewable Energy, Elsevier, volume 256, issue PE, DOI: 10.1016/j.renene.2025.124298.
• Migliavacca, Milena & Anwer, Zaheer & Fandella, Paola, 2026, "Geopolitical risk and stock market volatility: The case of US weapon and non-weapon firms," Research in International Business and Finance, Elsevier, volume 81, issue C, DOI: 10.1016/j.ribaf.2025.103195.
• Mei, Dexiang & Li, Xiaotao, 2026, "Forecasting of Chinese stock price using a hybrid neural network model," Research in International Business and Finance, Elsevier, volume 82, issue C, DOI: 10.1016/j.ribaf.2025.103232.
• Hamida, Amal Ben & de Peretti, Christian & Belkacem, Lotfi, 2026, "Benford’s law and intraday microstructure anomalies: Forecasting market movements with high-frequency data," Research in International Business and Finance, Elsevier, volume 84, issue C, DOI: 10.1016/j.ribaf.2026.103302.
• Yilin Xiao & Jamie L. Cross, 2026, "Regularized Random Subspace Regressions," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2026-13, Feb.
• Chiara Casoli & Riccardo Lucchetti, 2026, "A rotated Dynamic Factor Model for the yield curve: squeezing out information when it matters," Working Papers, Fondazione Eni Enrico Mattei, number 2026.03, Jan.
• Gary Koop & Stuart McIntyre & James Mitchell & Ping Wu, 2026, "Incorporating Micro Data into Macro Models Using Pseudo VARs," Working Papers, Federal Reserve Bank of Cleveland, number 26-04, Feb, DOI: 10.26509/frbc-wp-202604.
• Dobrislav Dobrev & Pawel J. Szerszén, 2026, "Missing Data Substitution for Enhanced Robust Filtering and Forecasting in State-Space Models," Working Papers, The George Washington University, The Center for Economic Research, number 2026-004, Mar.
• Drin, Svitlana & Zhuravlova, Anastasiia, 2026, "Real-Time Nowcasting of Kyiv’s Regional GRP Using Google Trends and Mixed-Frequency Data," Working Papers, Örebro University, School of Business, number 2026:1, Jan.
• Giménez-Nadal, José Ignacio & Molina, José Alberto & Velilla, Jorge, 2026, "Who Shirks at Work? An Application of Machine Learning to Time Use Data," IZA Discussion Papers, IZA Network @ LISER, number 18432, Mar.

2025

• Luo, Jiawen & Chen, Zhenbiao & Cheng, Mingmian, 2025, "Forecasting realized betas using predictors indicating structural breaks and asymmetric risk effects," Journal of Empirical Finance, Elsevier, volume 80, issue C, DOI: 10.1016/j.jempfin.2024.101575.
• Luo, Jiawen & Cepni, Oguzhan & Demirer, Riza & Gupta, Rangan, 2025, "Forecasting multivariate volatilities with exogenous predictors: An application to industry diversification strategies," Journal of Empirical Finance, Elsevier, volume 81, issue C, DOI: 10.1016/j.jempfin.2025.101595.
• Zhang, Tao & Tang, Ke & Liu, Taoxiong & Jiang, Tingfeng, 2025, "High frequency online inflation and term structure of interest rates: Evidence from China," Journal of Empirical Finance, Elsevier, volume 83, issue C, DOI: 10.1016/j.jempfin.2025.101626.
• Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan & Li, Yan, 2025, "On the profitability of influential carry-trade strategies: Data-snooping bias and post-publication performance," Journal of Empirical Finance, Elsevier, volume 83, issue C, DOI: 10.1016/j.jempfin.2025.101640.
• Yuan, Ying & Qu, Yong & Wang, Tianyang, 2025, "Predicting risk premiums: A constraint-based model," Journal of Empirical Finance, Elsevier, volume 83, issue C, DOI: 10.1016/j.jempfin.2025.101647.
• Zhang, Han & Xiong, Xiong & Guo, Bin, 2025, "The stock return predictability of treasury bond yield in China," Journal of Empirical Finance, Elsevier, volume 84, issue C, DOI: 10.1016/j.jempfin.2025.101654.
• Agakishiev, Ilyas & Härdle, Wolfgang Karl & Kopa, Milos & Kozmik, Karel & Petukhina, Alla, 2025, "Multivariate probabilistic forecasting of electricity prices with trading applications," Energy Economics, Elsevier, volume 141, issue C, DOI: 10.1016/j.eneco.2024.108008.
• Ellwanger, Reinhard, 2025, "The tail risk premium in the oil market," Energy Economics, Elsevier, volume 141, issue C, DOI: 10.1016/j.eneco.2024.108041.
• Wang, Zhengzhong & Wei, Yunjie & Wang, Shouyang, 2025, "Forecasting the carbon price of China's national carbon market: A novel dynamic interval-valued framework," Energy Economics, Elsevier, volume 141, issue C, DOI: 10.1016/j.eneco.2024.108107.
• Motegi, Kaiji & Hamori, Shigeyuki, 2025, "Conditional threshold effects of stock market volatility on crude oil market volatility," Energy Economics, Elsevier, volume 143, issue C, DOI: 10.1016/j.eneco.2025.108189.
• Forgetta, Anthony & Godin, Frédéric & Augustyniak, Maciej, 2025, "Distributional forecasting of electricity DART spreads with a covariate-dependent mixture model," Energy Economics, Elsevier, volume 144, issue C, DOI: 10.1016/j.eneco.2025.108332.
• Castro, Tomas del Barrio & Escribano, Alvaro & Sibbertsen, Philipp, 2025, "Modeling and forecasting the long memory of Cyclical Trends in paleoclimate data," Energy Economics, Elsevier, volume 147, issue C, DOI: 10.1016/j.eneco.2025.108520.
• Wu, Bangzheng, 2025, "The global supply pressure and oil supply–demand shocks: A time-scale and quantile analysis," Energy Economics, Elsevier, volume 147, issue C, DOI: 10.1016/j.eneco.2025.108555.
• Delis, Panagiotis & Degiannakis, Stavros & Filis, George, 2025, "Navigating crude oil volatility forecasts: Assessing the contribution of geopolitical risk," Energy Economics, Elsevier, volume 148, issue C, DOI: 10.1016/j.eneco.2025.108594.
• Serafin, Tomasz & Weron, Rafał, 2025, "Loss functions in regression models: Impact on profits and risk in day-ahead electricity trading," Energy Economics, Elsevier, volume 148, issue C, DOI: 10.1016/j.eneco.2025.108596.
• Candila, Vincenzo & Petrella, Lea & Andreani, Mila, 2025, "Mixed-frequency Quantile Regression Forests for Value-at-Risk forecasting," Energy Economics, Elsevier, volume 149, issue C, DOI: 10.1016/j.eneco.2025.108706.
• Koechlin, Guillaume & Bovera, Filippo & Secchi, Piercesare, 2025, "Strategic bidding in pay-as-bid power reserve markets: A machine learning approach," Energy Economics, Elsevier, volume 150, issue C, DOI: 10.1016/j.eneco.2025.108780.
• Das, Debojyoti & Saurav, Sumit & Dutta, Anupam, 2025, "Modelling for insight: Does oil price uncertainty have directional predictability for travel and leisure firms?," Energy Economics, Elsevier, volume 151, issue C, DOI: 10.1016/j.eneco.2025.108887.
• Hanus, Luboš & Baruník, Jozef, 2025, "Learning the probability distributions of day-ahead electricity prices," Energy Economics, Elsevier, volume 152, issue C, DOI: 10.1016/j.eneco.2025.108988.
• Wen, Danyan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2025, "Forecasting gasoline prices using oil prices: New evidence based on the rocket and feather hypothesis," Energy, Elsevier, volume 335, issue C, DOI: 10.1016/j.energy.2025.138115.
• Yan, Lili & Kellard, Neil M. & Lambercy, Lyudmyla, 2025, "Multivariate range-based EGARCH models," International Review of Financial Analysis, Elsevier, volume 100, issue C, DOI: 10.1016/j.irfa.2025.103983.
• Chen, Sihan & Ming, Lei & Yang, Haoxi & Yang, Shenggang, 2025, "Iterated Dynamic Model Averaging and application to inflation forecasting," International Review of Financial Analysis, Elsevier, volume 102, issue C, DOI: 10.1016/j.irfa.2025.104095.
• Liu, Yanchen & Yi, Siyu & Li, Sitong & Chen, Gengxuan, 2025, "Asymmetric impacts of energy market-related uncertainty on clean energy stock volatility: The role of extreme shocks," International Review of Financial Analysis, Elsevier, volume 103, issue C, DOI: 10.1016/j.irfa.2025.104206.
• Wang, Jiqian & Chen, Chuang & Dai, Xingyu, 2025, "News topic attention and crude oil price predictability," International Review of Financial Analysis, Elsevier, volume 108, issue PA, DOI: 10.1016/j.irfa.2025.104696.
• Zhao, Dongshuai & Wang, Zhongli & Schweizer-Gamborino, Florian & Sornette, Didier, 2025, "Polytope Fraud Theory," International Review of Financial Analysis, Elsevier, volume 97, issue C, DOI: 10.1016/j.irfa.2024.103734.
• Zhang, Yaojie & He, Mengxi & Wang, Yudong & Wen, Danyan, 2025, "Model specification for volatility forecasting benchmark," International Review of Financial Analysis, Elsevier, volume 97, issue C, DOI: 10.1016/j.irfa.2024.103850.
• Hu, Nan & Yin, Xuebao & Yao, Yuhang, 2025, "A novel HAR-type realized volatility forecasting model using graph neural network," International Review of Financial Analysis, Elsevier, volume 98, issue C, DOI: 10.1016/j.irfa.2024.103881.
• Blazsek, Szabolcs & Kong, Dejun & Shadoff, Samantha R., 2025, "Within-regime volatility dynamics for observable- and Markov-switching score-driven models," Finance Research Letters, Elsevier, volume 73, issue C, DOI: 10.1016/j.frl.2024.106631.
• Li, Sitong & Chen, Huangen & Chen, Gengxuan, 2025, "The US-China tension and fossil fuel energy price volatility relationship," Finance Research Letters, Elsevier, volume 74, issue C, DOI: 10.1016/j.frl.2024.106707.
• Hu, Wendi & Shao, Chujian & Zhang, Wenyu, 2025, "Predicting U.S. bank failures and stress testing with machine learning algorithms," Finance Research Letters, Elsevier, volume 75, issue C, DOI: 10.1016/j.frl.2025.106802.
• Liu, Zhenya & You, Rongyu & Zhan, Yaosong, 2025, "Modeling GDP with a continuous-time finance approach," Finance Research Letters, Elsevier, volume 76, issue C, DOI: 10.1016/j.frl.2025.106971.
• Ellwanger, Reinhard & Snudden, Stephen, 2025, "Putting VAR forecasts of the real price of crude oil to the test," Finance Research Letters, Elsevier, volume 77, issue C, DOI: 10.1016/j.frl.2025.106940.
• Polat, Onur & Somani, Dhanashree & Gupta, Rangan & Karmakar, Sayar, 2025, "Shortages and machine-learning forecasting of oil returns volatility: 1900–2024," Finance Research Letters, Elsevier, volume 79, issue C, DOI: 10.1016/j.frl.2025.107334.
• Li, Chenxing & Yang, Qiao, 2025, "An infinite hidden Markov model with GARCH for short-term interest rates," Finance Research Letters, Elsevier, volume 80, issue C, DOI: 10.1016/j.frl.2025.107294.
• Wu, Bangzheng, 2025, "Sino-American relations and gold market volatility," Finance Research Letters, Elsevier, volume 80, issue C, DOI: 10.1016/j.frl.2025.107379.
• Awartani, Basel & Maghyereh, Aktham, 2025, "The value of cross market volatility in improving the forecast accuracy of risk in the gold, the dollar and the oil futures markets," Finance Research Letters, Elsevier, volume 83, issue C, DOI: 10.1016/j.frl.2025.107668.
• Lu, Zhichao & Xu, Yuhong & Zhang, Yue & Zhao, Xinyao, 2025, "Is it difficult to predict the price movements of high-volatility assets," Finance Research Letters, Elsevier, volume 85, issue PB, DOI: 10.1016/j.frl.2025.107980.
• Koutmos, Dimitrios & Gunay, Samet & Payne, James E., 2025, "Market expectations and the holding behaviors of bitcoin whales, dolphins, and minnows," Finance Research Letters, Elsevier, volume 86, issue PE, DOI: 10.1016/j.frl.2025.108590.
• Somani, Dhanashree & Gupta, Rangan & Karmakar, Sayar & Plakandaras, Vasilios, 2025, "Supply bottlenecks and machine learning forecasting of international stock market volatility," Finance Research Letters, Elsevier, volume 86, issue PG, DOI: 10.1016/j.frl.2025.108931.
• Oliveira, Lucas M. & Alencar, Airlane P., 2025, "When timing matters: Regime-dependent delays in exchange rate fundamentals," Finance Research Letters, Elsevier, volume 86, issue PG, DOI: 10.1016/j.frl.2025.108941.
• Liu, Dan, 2025, "Seeing is believing: Forecasting oil market returns with artificial intelligence-powered visual climate change perception," Global Finance Journal, Elsevier, volume 68, issue C, DOI: 10.1016/j.gfj.2025.101174.
• Yuan, Ying & Qu, Yong & Qiao, Sijia, 2025, "Equity premium prediction: A constraint-based predictor decomposition approach," Global Finance Journal, Elsevier, volume 68, issue C, DOI: 10.1016/j.gfj.2025.101199.
• Levich, Sergej & Knust, Lucas, 2025, "Discriminative meets generative: Automated information retrieval from unstructured corporate documents via (large) language models," International Journal of Accounting Information Systems, Elsevier, volume 56, issue C, DOI: 10.1016/j.accinf.2025.100750.
• Barone, Guglielmo & Letta, Marco, 2025, "Unlevel playing field? Machine learning meets state aid regulation," International Journal of Industrial Organization, Elsevier, volume 101, issue C, DOI: 10.1016/j.ijindorg.2025.103175.
• Baumgärtner, Martin & Zahner, Johannes, 2025, "Whatever it takes to understand a central banker — Embedding their words using neural networks," Journal of International Economics, Elsevier, volume 157, issue C, DOI: 10.1016/j.jinteco.2025.104101.
• Chen, Ze & Li, Hong & Mao, Yu & Zhou, Kenneth Q., 2025, "Learning from COVID-19: A catastrophe mortality bond solution in the post-pandemic era," Insurance: Mathematics and Economics, Elsevier, volume 123, issue C, DOI: 10.1016/j.insmatheco.2025.103113.
• Koike, Takaaki & Chen, Cathy W.S. & Lin, Edward M.H., 2025, "Forecasting and backtesting gradient allocations of expected shortfall," Insurance: Mathematics and Economics, Elsevier, volume 124, issue C, DOI: 10.1016/j.insmatheco.2025.103130.
• Ahn, Jae Youn & Jeong, Himchan & Lu, Yang & Wüthrich, Mario V., 2025, "An observation-driven state-space count model for experience rating," Insurance: Mathematics and Economics, Elsevier, volume 125, issue C, DOI: 10.1016/j.insmatheco.2025.103149.
• Caporin, Massimiliano & Caraiani, Petre & Cepni, Oguzhan & Gupta, Rangan, 2025, "Predicting the conditional distribution of US stock market systemic Stress: The role of climate risks," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 101, issue C, DOI: 10.1016/j.intfin.2025.102156.
• M’bakob, Gilles Brice & Mandeng ma Ntamack, Jules & Mfouapon, Georges Kriyoss, 2025, "Anticipated psychological spreads: Cryptocurrencies’ hidden short-term monitors and implications for price forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 104, issue C, DOI: 10.1016/j.intfin.2025.102224.
• Coroneo, Laura & Iacone, Fabrizio, 2025, "Testing for equal predictive accuracy with strong dependence," International Journal of Forecasting, Elsevier, volume 41, issue 3, pages 1073-1092, DOI: 10.1016/j.ijforecast.2024.11.003.
• Sokol, Andrej, 2025, "Fan charts 2.0: Flexible forecast distributions with expert judgement," International Journal of Forecasting, Elsevier, volume 41, issue 3, pages 1148-1164, DOI: 10.1016/j.ijforecast.2024.11.009.
• Samartzis, Panagiotis, 2025, "Predicting the relative performance among financial assets: A comparative analysis of different approaches," International Journal of Forecasting, Elsevier, volume 41, issue 4, pages 1428-1449, DOI: 10.1016/j.ijforecast.2024.12.008.
• Degiannakis, Stavros & Kafousaki, Eleftheria, 2025, "Disaggregating VIX," International Journal of Forecasting, Elsevier, volume 41, issue 4, pages 1559-1588, DOI: 10.1016/j.ijforecast.2025.01.007.
• Binz, Oliver & Schipper, Katherine & Standridge, Kevin R., 2025, "Estimating profitability decomposition frameworks via machine learning: Implications for earnings forecasting and financial statement analysis," Journal of Accounting and Economics, Elsevier, volume 80, issue 2, DOI: 10.1016/j.jacceco.2025.101805.
• Feng, Guanhao & He, Xin & Wang, Yanchu & Wu, Chunchi, 2025, "Predicting individual corporate bond returns," Journal of Banking & Finance, Elsevier, volume 171, issue C, DOI: 10.1016/j.jbankfin.2024.107372.
• Amendola, Marco & Pereira, Marcelo C., 2025, "State-dependent impulse responses in agent-based models: A new methodology and an economic application," Journal of Economic Behavior & Organization, Elsevier, volume 229, issue C, DOI: 10.1016/j.jebo.2024.106811.
• Nutarelli, Federico & Edet, Samuel & Gnecco, Giorgio & Riccaboni, Massimo, 2025, "Predicting the technological complexity of global cities based on unsupervised and supervised machine learning methods," Journal of Economic Behavior & Organization, Elsevier, volume 234, issue C, DOI: 10.1016/j.jebo.2025.107011.
• Gerotto, Luca & Paradiso, Antonio & Pellizzari, Paolo, 2025, "A tale of inattentiveness and the loss function: A model for household-level macroeconomic expectations," Journal of Economic Behavior & Organization, Elsevier, volume 236, issue C, DOI: 10.1016/j.jebo.2025.107076.
• Clements, Michael P., 2025, "Inconsistent survey histograms and point forecasts revisited," Journal of Economic Behavior & Organization, Elsevier, volume 236, issue C, DOI: 10.1016/j.jebo.2025.107097.
• Qiu, Yajie & Deschamps, Bruno, 2025, "Peer influence in macroeconomic predictions," Journal of Economic Behavior & Organization, Elsevier, volume 236, issue C, DOI: 10.1016/j.jebo.2025.107129.
• Jung, Hyeyoon & Engle, Robert F. & Berner, Richard, 2025, "CRISK: Measuring the climate risk exposure of the financial system," Journal of Financial Economics, Elsevier, volume 171, issue C, DOI: 10.1016/j.jfineco.2025.104076.
• Drake, Keith M. & McGuire, Thomas G., 2025, "Using stock price movements to estimate the harm from collusive drug patent litigation settlements," Journal of Health Economics, Elsevier, volume 103, issue C, DOI: 10.1016/j.jhealeco.2025.103054.
• Mertzanis, Charilaos & Kampouris, Ilias & Samitas, Aristeidis, 2025, "Climate change and U.S. Corporate bond market activity: A machine learning approach," Journal of International Money and Finance, Elsevier, volume 151, issue C, DOI: 10.1016/j.jimonfin.2024.103259.
• Chȩć, Katarzyna & Uniejewski, Bartosz & Weron, Rafał, 2025, "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Journal of Commodity Markets, Elsevier, volume 37, issue C, DOI: 10.1016/j.jcomm.2024.100449.
• Santos, Augusto Seabra & Almeida, Alexandre Nunes, 2025, "Do different speculation strategies cause distinct impacts on the volatility of the live cattle futures in Brazil?," Journal of Commodity Markets, Elsevier, volume 37, issue C, DOI: 10.1016/j.jcomm.2025.100458.
• Iregui, Ana María & Núñez, Héctor M. & Otero, Jesús, 2025, "Testing the efficiency of oil price forecast revisions in times of COVID-19 and the Russia–Ukraine conflict," Journal of Commodity Markets, Elsevier, volume 40, issue C, DOI: 10.1016/j.jcomm.2025.100513.
• Li, Shuaibing & Ma, Yong, 2025, "News-based equity market uncertainty aligned: An informative predictor for gold market volatility," Journal of Commodity Markets, Elsevier, volume 40, issue C, DOI: 10.1016/j.jcomm.2025.100522.
• Awijen, Haithem & Ben Zaied, Younes & Ben Jabeur, Sami, 2025, "Mobilizing FDI in natural resources in the post-COP28 era: Spatial drivers, natural capital, and sustainability dynamics," Resources Policy, Elsevier, volume 107, issue C, DOI: 10.1016/j.resourpol.2025.105638.
• Kohlhas, Alexandre N. & Robertson, Donald, 2025, "Cautious expectations," Journal of Monetary Economics, Elsevier, volume 155, issue S, DOI: 10.1016/j.jmoneco.2025.103759.
• Adam, Klaus & Kuang, Pei & Xie, Shihan, 2025, "Overconfidence in private information explains biases in professional forecasts," Journal of Monetary Economics, Elsevier, volume 155, issue S, DOI: 10.1016/j.jmoneco.2025.103839.
• Shi, Qi, 2025, "Technical indicators and aggregate stock returns: An updated look," Journal of Multinational Financial Management, Elsevier, volume 77, issue C, DOI: 10.1016/j.mulfin.2025.100898.
• Kampouris, Ilias & Mertzanis, Charilaos & Samitas, Aristeidis, 2025, "Natural disaster shocks and commodity market volatility: A machine learning approach," Pacific-Basin Finance Journal, Elsevier, volume 90, issue C, DOI: 10.1016/j.pacfin.2024.102618.
• Li, Xiao-Xin & Xie, Chi & Wang, Gang-Jin & Zhu, You & Li, Zhao-Chen & Zhang, Zhi-Yu, 2025, "Enhancing stock market return predictability by using a novel autoencoder-based aggregate EPU index," Pacific-Basin Finance Journal, Elsevier, volume 93, issue C, DOI: 10.1016/j.pacfin.2025.102873.
• Cordeiro, Werley & Caldeira, João F. & Moura, Guilherme V., 2025, "Forecasting the Brazilian yield curve using macroeconomics expectations and time-varying volatility," The Quarterly Review of Economics and Finance, Elsevier, volume 104, issue C, DOI: 10.1016/j.qref.2025.102072.
• Ohikhuare, Obaika M. & Oyewole, Oluwatomisin J., 2025, "Asymmetric connectedness among the G7 REITs market: How important are oil returns, climate policy uncertainty, and geopolitical risks?," Research in Economics, Elsevier, volume 79, issue 2, DOI: 10.1016/j.rie.2025.101043.
• Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2025, "Forecasting realised volatility using regime-switching models," International Review of Economics & Finance, Elsevier, volume 101, issue C, DOI: 10.1016/j.iref.2025.104171.
• Foglia, Matteo & Plakandaras, Vasilios & Gupta, Rangan & Bouri, Elie, 2025, "Rare disasters and multilayer spillovers between volatility and skewness in international stock markets over a century of data: The role of geopolitical risk," International Review of Economics & Finance, Elsevier, volume 101, issue C, DOI: 10.1016/j.iref.2025.104183.
• Ardakani, Omid M., 2025, "Informational efficiency and rational bubbles," International Review of Economics & Finance, Elsevier, volume 103, issue C, DOI: 10.1016/j.iref.2025.104486.
• Li, Lin & Li, Guoping, 2025, "Information rigidity: Comparing average and individual forecasts of analysts of Chinese A-Share listed companies," International Review of Economics & Finance, Elsevier, volume 104, issue C, DOI: 10.1016/j.iref.2025.104732.
• Dolaeva, Aishat & Beliaeva, Uliana & Grigoriev, Dmitry & Semenov, Alexander & Rysz, Maciej, 2025, "Analyzing and forecasting P/E ratios using investor sentiment in panel data regression and LSTM models," International Review of Economics & Finance, Elsevier, volume 98, issue C, DOI: 10.1016/j.iref.2025.103840.
• Kumar, Satish & Rao, Amar & Dhochak, Monika, 2025, "Hybrid ML models for volatility prediction in financial risk management," International Review of Economics & Finance, Elsevier, volume 98, issue C, DOI: 10.1016/j.iref.2025.103915.
• Foglia, Matteo & Plakandaras, Vasilios & Gupta, Rangan & Ji, Qiang, 2025, "Long-span multi-layer spillovers between moments of advanced equity markets: The role of climate risks," Research in International Business and Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.ribaf.2024.102667.
• Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2025, "Volatility forecasting and volatility-timing strategies: A machine learning approach," Research in International Business and Finance, Elsevier, volume 75, issue C, DOI: 10.1016/j.ribaf.2024.102723.
• Chen, Rui & Jiang, Haiqi & Guo, Tingyu & Fan, Chenyou, 2025, "Can Large Language Models forecast carbon price movements? Evidence from Chinese carbon markets," Research in International Business and Finance, Elsevier, volume 77, issue PB, DOI: 10.1016/j.ribaf.2025.102951.
• Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2025, "Measuring the impact of climate transition risk on the systemic risk: A multivariate quantile-located ES approach," Research in International Business and Finance, Elsevier, volume 80, issue C, DOI: 10.1016/j.ribaf.2025.103127.
• Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Bouri, Elie, 2025, "Forecasting spot and futures price volatility of agricultural commodities: The role of climate-related migration uncertainty," Research in International Business and Finance, Elsevier, volume 80, issue C, DOI: 10.1016/j.ribaf.2025.103133.
• Salinas, Julián & Zhang, Jianhua, 2025, "Unveiling structural change determinants: A machine learning approach to long-term dynamics," Socio-Economic Planning Sciences, Elsevier, volume 101, issue C, DOI: 10.1016/j.seps.2025.102290.
• Maiti, Dibyendu & Khari, Bhavna, 2025, "Digitalisation, e-Governance and the informal sector," Structural Change and Economic Dynamics, Elsevier, volume 75, issue C, pages 451-463, DOI: 10.1016/j.strueco.2025.08.007.
• Papík, Mário & Papíková, Lenka, 2025, "The possibilities of using AutoML in bankruptcy prediction: Case of Slovakia," Technological Forecasting and Social Change, Elsevier, volume 215, issue C, DOI: 10.1016/j.techfore.2025.124098.
• Thomas Persson, 2025, "Machine Learning Methods," Journal of Economics and Econometrics, Economics and Econometrics Society, volume 68, issue 2, pages 106-129.
• Weifeng Larry Liu & Warwick J. McKibbin, 2025, "Long-Term Projections of the World Economy," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2025-31, May.
• Mohammad Mahabub Alam, 2025, "The Effects of Macroeconomic Shocks and Uncertainty on Bangladesh's Fiscal Sustainability," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2025-33, Jun.
• Ghosh, Anisha & Julliard, Christian & Taylor, Alex. P, 2025, "An information-theoretic asset pricing model," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 126155, Jan.
• Briola, Antonio & Bartolucci, Silvia & Aste, Tomaso, 2025, "HLOB–Information persistence and structure in limit order books," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 126623, Mar.
• Koukorinis, Andreas & Peters, Gareth W. & Germano, Guido, 2025, "Generative-discriminative machine learning models for high-frequency financial regime classification," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 128016, Jun.
• Briola, Antonio & Bartolucci, Silvia & Aste, Tomaso, 2025, "Deep limit order book forecasting: a microstructural guide," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 128950, Jul.
• Paker, Meredith & Stephenson, Judy & Wallis, Patrick, 2025, "Predictive modeling the past," Economic History Working Papers, London School of Economics and Political Science, Department of Economic History, number 128852, Jun.
• Pornpawee Supsermpol & Van Nam Huynh & Suttipong Thajchayapong & Nathridee Suppakitjarak & Navee Chiadamrong, 2025, "Predicting post-IPO financial performance: a hybrid approach using logistic regression and decision trees," Journal of Asian Business and Economic Studies, Emerald Group Publishing Limited, volume 32, issue 1, pages 52-65, February, DOI: 10.1108/JABES-06-2024-0292.
• Bergin, Adele & Low, Hailey & Millard, Stephen & Verma, Akhilesh Kumar, 2025, "A macro-model of the Northern Ireland Economy," Papers, Economic and Social Research Institute (ESRI), number WP796.
• Frédérique Bec & François Courtoy & Philipp Mohl & Frederic Opitz, 2025, "The Stochastic Simulations of the Commission’s Debt Sustainability Analysis: A Refined Approach," European Economy - Discussion Papers, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission, number 226, Sep.
• Alessandro Stringhi & Sara Gil-Gallen & Andrea Albertazzi, 2025, "The Enemy of my Enemy," Working Papers, Fondazione Eni Enrico Mattei, number 2025.03, Jan.
• Andrea Bastianin & Xiao Li & Luqman Shamsudin, 2025, "Forecasting the Volatility of Energy Transition Metals," Working Papers, Fondazione Eni Enrico Mattei, number 2025.04, Jan.
• Monica Bonacina & Romolo Consigna Tokong, 2025, "Is Italy on Track? A Data-Driven Forecast for Road Transport Decarbonisation by 2030," Working Papers, Fondazione Eni Enrico Mattei, number 2025.19, Sep.
• Nikolay Gospodinov & Esfandiar Massoumi, 2025, "On Model Aggregation and Forecast Combination," FRB Atlanta Working Paper, Federal Reserve Bank of Atlanta, number 2025-12, Oct, DOI: 10.29338/wp2025-12.