Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2026

• Choi, Insu & Lim, Soyeong & Kim, Seoyeon & Choi, Yeona & Han, Subin & Kim, Woo Chang, 2026, "Metric-based technical indicators for yield forecasting," Pacific-Basin Finance Journal, Elsevier, volume 98, issue C, DOI: 10.1016/j.pacfin.2026.103169.
• 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.
• Caporin, Massimiliano & Gupta, Rangan & Subramaniam, Sowmya & Torrent, Hudson S., 2026, "Supply Constraints and Conditional Distribution Predictability of Inflation and its Volatility: A Nonparametric Mixed-Frequency Causality-in-Quantiles Approach," Research in Economics, Elsevier, volume 80, issue 2, DOI: 10.1016/j.rie.2026.101128.
• 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.
• Bargman, Daniil, 2026, "Latent variable modelling by supervised diffusion," International Review of Economics & Finance, Elsevier, volume 106, issue C, DOI: 10.1016/j.iref.2026.104972.
• Fasanya, Ismail O. & Oyewole, Oluwatomisin J. & Saleh Al-Faryan, Mamdouh Abdulaziz, 2026, "The inflation-energy nexus in OPEC: A nonlinear forecasting perspective," International Review of Economics & Finance, Elsevier, volume 107, issue C, DOI: 10.1016/j.iref.2026.105096.
• Khadivar, Hamed & Davis, Frederick & Khadivar, Ameneh & Stetsyuk, Ivan, 2026, "Predicting takeover rumor accuracy with machine learning," International Review of Economics & Finance, Elsevier, volume 108, issue C, DOI: 10.1016/j.iref.2026.105204.
• Barasal Morales, Adriano, 2026, "Climate calm? Long-run temperature signals and volatility in EU carbon futures," International Review of Economics & Finance, Elsevier, volume 108, issue C, DOI: 10.1016/j.iref.2026.105221.
• Chen, Ying & Peng, Liang & Sheng, Jiliang, 2026, "Predictability of climate policy uncertainty index," International Review of Economics & Finance, Elsevier, volume 108, issue C, DOI: 10.1016/j.iref.2026.105293.
• 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.
• Sun, Hao & Zhu, Xiaoqian & Li, Jianping, 2026, "Revealing corporate accounting fraud: From the perspective of individual investors," Research in International Business and Finance, Elsevier, volume 86, issue C, DOI: 10.1016/j.ribaf.2026.103385.
• Bao, Guanhao & Cui, Baisheng, 2026, "Research on the impact of U.S. monetary policy uncertainty on international oil price forecasting: A deep learning approach based on frequency domain decomposition," Research in International Business and Finance, Elsevier, volume 87, issue C, DOI: 10.1016/j.ribaf.2026.103391.
• Aslam, Adnan & Brahmana, Rayenda Khresna, 2026, "The dynamic relationship among private and public markets and its most important features," Research in International Business and Finance, Elsevier, volume 89, issue C, DOI: 10.1016/j.ribaf.2026.103490.
• Fontana, Stefania & Guccio, Calogero & Pignataro, Giacomo & Vidoli, Francesco, 2026, "Better politicians, fewer deaths? Local resilience in overcoming the pandemic crisis in Italy," Social Science & Medicine, Elsevier, volume 398, issue C, DOI: 10.1016/j.socscimed.2026.119198.
• 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.
• Hilde C. Bjornland & Nicolas Hardy & Dimitris Korobilis, 2026, "Forecasting Oil Prices Across the Distribution: A Quantile VAR Approach," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2026-39, May.
• Slawomir Bukowski & Joanna Bukowska & Jacek Woloszyn & Agnieszka Molga, 2026, "Forecasting the EUR/PLN Exchange RateUsing Classical and Artificial Intelligence Methods:An Empirical Comparison of ARIMA, XGBoost, LSTMand Hybrid Models on NBP Data 2015-2026," European Research Studies Journal, European Research Studies Journal, volume 0, issue 2, pages 295-317.
• Anna Gembalska-Kwiecien, 2026, "Attempted Development of a Methodology to Support Project Implementation Risk Management in a Manufacturing Enterprise," European Research Studies Journal, European Research Studies Journal, volume 0, issue 2, pages 57-66.
• Eduard Gracia, 2026, "Follow the median: revisiting bubbles and cycles," UB School of Economics Working Papers, University of Barcelona School of Economics, number 2026/497.
• 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.
• Todd E. Clark & Florian Huber & Gary Koop, 2026, "A Nonparametric Approach to Augmenting a Bayesian VAR with Nonlinear Factors," Working Papers, Federal Reserve Bank of Cleveland, number 26-14, Jun, DOI: 10.26509/frbc-wp-202614.
• Kevin J. Lansing & Adam Hale Shapiro, 2026, "Measuring Inflation Shock Momentum," Working Paper Series, Federal Reserve Bank of San Francisco, number 2026-10, Apr, DOI: 10.24148/wp2026-10.
• Vera Barinova & Margarita Gvozdeva, 2026, "The role of SMEs in the development of tourism in Russia," Published Papers, Gaidar Institute for Economic Policy, number ppaper-2026-1619, revised 2026.
• Elena Villalobos & Adolfo de Unánue T. & Fernanda Sobrino & David Aké & Stephany Cisneros & Jorge Lecona & Alejandra Matadamaz, 2026, "Toward Reducing Unproductive Container Moves: Predicting Service Requirements and Dwell Times," Working Paper Series of the School of Government and Public Transformation, School of Governement and Public Transformation, number 31, Apr.
• Adolfo De Unánue & Fernanda Sobrino, 2026, "Machine Learning as Performative Materialist Practice: Thirteen Theses on the Epistemology, Methodology, and Politics of Applied ML," Working Paper Series of the School of Government and Public Transformation, School of Governement and Public Transformation, number 34, May.
• Dobrislav Dobrev & Pawel J. Szerszen, 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.
• Rahma Mzouri & Abdelkrim Kandrouch, 2026, "Business failure: a literature review
  [Défaillance des entreprises : revue de littérature]," Post-Print, HAL, number hal-05527901, Feb, DOI: 10.5281/zenodo.18614550.
• Laurent Ferrara & Aikaterini Karadimitropoulou & Athanasios Triantafyllou, 2026, "Commodity price uncertainty comovement: Does it matter for global economic growth?," Post-Print, HAL, number hal-05607366, Jul, DOI: 10.1016/j.euroecorev.2026.105339.
• Emmanouil Sofianos & Thierry Betti & Theophilos Papadimitriou & Amélie Barbier-Gauchard & Periklis Gogas, 2026, "Using DSGE and Machine Learning to Forecast Public Debt for France," Post-Print, HAL, number hal-05620169, Mar, DOI: 10.1002/for.70144.
• G Barone-Adesi & M Bonollo & V Damato & F Luce, 2026, "Risk Governance Through Long-Term Risk Modelling: An Enhanced Filtered Historical Simulation Approach for Financial Institutions," Working Papers, HAL, number hal-05487195, Jan.
• Safira, Dinda Ayu & Kuswanto, Heri & Ahsan, Muhammad & Sibbertsen, Philipp, 2026, "A Majorization-Minimization gLASSO Framework for SETAR Models: Theory, Simulation, and Application to PM2.5 Data," Hannover Economic Papers (HEP), Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, number dp-746, May.
• 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.
• Andrew B. Martinez & Alexander D. Schibuola & David Beckworth, 2026, "The Reliability of the Nominal GDP Expectations Gap," International Journal of Central Banking, International Journal of Central Banking, volume 22, issue 2, pages 525-557, April.
• Yusuke Oh & Mototsugu Shintani, 2026, "Forecasting Recessions Using Machine Learning on Text Data and Mixed-Frequency Predictors," IMES Discussion Paper Series, Institute for Monetary and Economic Studies, Bank of Japan, number 26-E-07, Mar.
• Bogdan Mirea & Giani-Ionel Gradinaru, 2026, "Ethics and bias in AI: a potential challenge to fair economic progress," Romanian Journal of Economics, Institute of National Economy, volume 62, issue 1(71), pages 99-110, June.
• 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

• Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2025, "Density forecasts of inflation: A quantile regression forest approach," European Economic Review, Elsevier, volume 178, issue C, DOI: 10.1016/j.euroecorev.2025.105079.
• Ellington, Michael & Kalli, Maria, 2025, "Predictive distributions and the market return: The role of market illiquidity," European Journal of Operational Research, Elsevier, volume 323, issue 1, pages 309-322, DOI: 10.1016/j.ejor.2025.01.006.
• 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.
• Bårdsen, Gunnar & Nymoen, Ragnar, 2025, "Dynamic time series modelling and forecasting of COVID-19 in Norway," International Journal of Forecasting, Elsevier, volume 41, issue 1, pages 251-269, DOI: 10.1016/j.ijforecast.2024.05.004.
• 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.
• Roberto Pinheiro & Rory G. Quinlan, 2025, "BLS Payroll Revisions: Forecasting Recessions," Working Papers, Federal Reserve Bank of Cleveland, number 25-26, Dec, DOI: 10.26509/frbc-wp-202526.
• Jesus Cañas & Emily Kerr & Diego Morales-Burnett, 2025, "Texas Service Sector Outlook Survey: Survey Methodology, Performance and Forecast Accuracy," Working Papers, Federal Reserve Bank of Dallas, number 2532, Aug, DOI: 10.24149/wp2532.
• Dobrislav Dobrev & Pawel J. Szerszen, 2025, "Missing Data Substitution for Enhanced Robust Filtering and Forecasting in Linear State-Space Models," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2025-001, Jan, DOI: 10.17016/FEDS.2025.001.
• Robin Braun & George Kapetanios & Massimiliano Marcellino, 2025, "Nonparametric Time Varying IV-SVARs: Estimation and Inference," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2025-004, Jan, DOI: 10.17016/FEDS.2025.004.
• Tobias Adrian & Domenico Giannone & Matteo Luciani & Mike West, 2025, "Scenario Synthesis and Macroeconomic Risk," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2025-036, May, DOI: 10.17016/FEDS.2025.036.
• Leland D. Crane & Akhil Karra & Paul E. Soto, 2025, "Total Recall? Evaluating the Macroeconomic Knowledge of Large Language Models," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2025-044, Jun, DOI: 10.17016/FEDS.2025.044.
• Hyung Joo Kim & Dong Hwan Oh, 2025, "Local Estimation for Option Pricing: Improving Forecasts with Market State Information," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2025-076, Aug, DOI: 10.17016/FEDS.2025.076.
• Daniel O. Beltran & Julio L. Ortiz, 2025, "Core Inflation in the Advanced Economies: A Regional Perspective," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.), number 1421, Sep, DOI: 10.17016/IFDP.2025.1421.
• Scott A. Brave & Ben Henken & Ezra Karger, 2025, "Blending Traditional and Alternative Labor Market Data with CHURN," Chicago Fed Letter, Federal Reserve Bank of Chicago, volume 506, June.
• Silvia Goncalves & Michael W. McCracken & Yongxu Yao, 2025, "Out-of-Sample Inference with Annual Benchmark Revisions," Working Papers, Federal Reserve Bank of St. Louis, number 2025-020, Sep, DOI: 10.20955/wp.2025.020.
• Richard K. Crump & Nikolay Gospodinov, 2025, "How Uncertain Is the Estimated Probability of a Future Recession?," Liberty Street Economics, Federal Reserve Bank of New York, number 20250529, May.
• Hannah O’Keeffe & Katerina Petrova, 2025, "Component-Based Dynamic Factor Nowcast Model," Staff Reports, Federal Reserve Bank of New York, number 1152, Apr, DOI: 10.59576/sr.1152.
• Rahul Billakanti & Minchul Shin, 2025, "At-Risk Transformation for U.S. Recession Prediction," Working Papers, Federal Reserve Bank of Philadelphia, number 25-34, Oct, DOI: 10.21799/frbp.wp.2025.34.
• Mitchell Berlin & SungJe Byun & Pablo D'Erasmo & Edison Yu, 2025, "Measuring Climate Transition Risk at the Regional Level with an Application to Community Banks," Working Papers, Federal Reserve Bank of Philadelphia, number 25-11, Mar, DOI: 10.21799/frbp.wp.2025.11.
• Vera Barinova & Margarita Gvozdeva & Stepan Zemtsov & Poilov N, 2025, "The impact of sanctions on small technology companies in Russia," Published Papers, Gaidar Institute for Economic Policy, number ppaper-2025-1412, revised 2025.
• Dean Fantazzini, 2025, "Detecting Stablecoin Failure with Simple Thresholds and Panel Binary Models: The Pivotal Role of Lagged Market Capitalization and Volatility," Forecasting, MDPI, volume 7, issue 4, pages 1-47, November.
• Said Magomedov & Dean Fantazzini, 2025, "Modeling and Forecasting the Probability of Crypto-Exchange Closures: A Forecast Combination Approach," JRFM, MDPI, volume 18, issue 2, pages 1-20, January.
• Shakhzod Abdullaevich Makhmudov, 2025, "Forecasting Banking System Liquidity Using Payment System Data in Uzbekistan," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 05-2025, Feb, revised 17 Feb 2025.
• Nicolas Hardy & Dimitris Korobilis, 2025, "Learning from crises: A new class of time-varying parameter VARs with observable adaptation," Working Papers, Business School - Economics, University of Glasgow, number 2025_12, Dec.
• Luke P. Jackson & Katarina Juselius & Andrew B. Martinez & Felix Pretis, 2025, "Modelling the dependence between recent changes in polar ice sheets: Implications for global sea-level projections," Working Papers, The George Washington University, The Center for Economic Research, number 2025-002, Apr.
• Natsuki Arai & Shian Chang, 2025, "Dispersion of FOMC Policymakers: Evidence from Individual Economic Projections with Identities," Working Papers, The George Washington University, The Center for Economic Research, number 2025-003, Apr.
• Andrew B. Martinez & Alexander D. Schibuola & David Beckworth, 2025, "The Reliability of the Nominal GDP Expectations Gap," Working Papers, The George Washington University, The Center for Economic Research, number 2025-004, Jun.
• Emmanouil Sofianos & Christos Alexakis & Periklis Gogas & Theophilos Papadimitriou, 2025, "Machine learning forecasting in the macroeconomic environment: the case of the US output gap," Post-Print, HAL, number hal-04885268, Jan, DOI: 10.1007/s10644-024-09849-w.
• Veronika Czellar & René Garcia & François Le Grand, 2025, "Uncovering asset market participation from household consumption and income," Post-Print, HAL, number hal-04977635, Mar, DOI: 10.1016/j.jeconom.2024.105867.
• Ally Manengu Manengu, 2025, "Analysis Of The Non-Linear Effects Of The Volatile Exchange Rate On Inflation In The Democratic Republic Of Congo From 1970 To 2022
  [Analyse Des Effets Non-Lineaires De La Volatilite Du Taux De Change Sur L'Inflation En Republique Democratique Du ," Post-Print, HAL, number hal-05083768, May.
• Amélie Barbier-Gauchard & Emmanouil Sofianos, 2025, "Forecasting Public Debt in the Euro Area Using Machine Learning: Decision Tools for Financial Markets," Post-Print, HAL, number hal-05459979, Oct, DOI: 10.1007/s10614-025-11106-9.
• Angelo Leogrande & Nicola Magaletti & Valeria Notarnicola & Mauro Di Molfetta & Stefano Mariani, 2025, "Data-Driven Welding Quality Assessment: Leveraging IoT and Machine Learning in Industrial Practice," Working Papers, HAL, number hal-05043506, Apr.
• Nicola Magaletti & Giancarlo Caponio & Angelo Amodio & Valeria Notarnicola & Mauro Di Molfetta & Angelo Leogrande, 2025, "A Decision-Support Model for Managing Outbound Logistics: Forecasting, Simulation, and Real-Time Operational Control," Working Papers, HAL, number hal-05385826, Nov.
• Frédérique Bec & François Courtoy & Philipp Mohl & Frederic Opitz, 2025, "The Stochastic Simulations of the Commission's Debt Sustainability Analysis: A Refined Approach
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• Josip Arnerić & Matteo Moćan, 2025, "Bayesov pristup logističkoj regresiji za predviđanje stečaja trgovačkih društava u uvjetima neizvjesnosti," Ekonomski pregled, Hrvatsko društvo ekonomista (Croatian Society of Economists), volume 76, issue 1, pages 15-34, DOI: 10.32910/ep.76.1.2.
• Enerstvedt, Vegard, 2025, "The Cost of Weather: Modeling Weather Delay in Bulk Shipping," Discussion Papers, Norwegian School of Economics, Department of Business and Management Science, number 2025/4, Feb.
• Aase, Knut K., 2025, "Optimal risk sharing with translation invariant recursive utility for jump-diffusions," Discussion Papers, Norwegian School of Economics, Department of Business and Management Science, number 2025/5, Feb.
• Karlsson, Sune & Mazur, Stepan & Raftab, Mariya, 2025, "Identifying Useful Indicators for Nowcasting GDP in Sweden," Working Papers, Örebro University, School of Business, number 2025:4, Feb.
• Ferreira Batista Martins, Igor & Virbickaitè, Audronè & Nguyen, Hoang & Freitas Lopes, Hedibert, 2025, "Volume-driven time-of-day effects in intraday volatility models," Working Papers, Örebro University, School of Business, number 2025:14, Nov.
• Celani, Alessandro & Pedini, Luca, 2025, "Moderate Time-Varying Parameter VARs," Working Papers, Örebro University, School of Business, number 2025:16, Dec.
• NAKAJIMA, Jouchi, 2025, "Time-varying Local Projections with Stochastic Volatility," Discussion Paper Series, Institute of Economic Research, Hitotsubashi University, number 761, Mar.
• Kostiantyn Zatvornytskyi, 2025, "The Role of Financial Forecasting in the Formation of Optimal Loan Portfolios of Ukrainian Banks," Oblik i finansi, Institute of Accounting and Finance, issue 1, pages 40-48, March, DOI: 10.33146/2307-9878-2025-1(107)-40-4.
• Afees A. Salisu & Dinci J. Penzin & Yinka S. Hammed, 2025, "Health Crisis and Currency Risk: Fresh Evidence from New Data Sets," Bulletin of Monetary Economics and Banking, Bank Indonesia, volume 28, issue 1, pages 1-14, April, DOI: https://doi.org/10.59091/2460-9196..
• Roshen Fernando & Warwick J. McKibbin, 2025, "Global economic impacts of antimicrobial resistance," Working Paper Series, Peterson Institute for International Economics, number WP25-12, Jun.
• Todd E. Clark & Matthew V. Gordon & Saeed Zaman, 2025, "Forecasting Core Inflation and Its Goods, Housing, and Supercore Components," International Journal of Central Banking, International Journal of Central Banking, volume 21, issue 4, pages 351-403, October.
• Mr. Tobias Adrian & Domenico Giannone & Matteo Luciani & Mike West, 2025, "Scenario Synthesis and Macroeconomic Risk," IMF Working Papers, International Monetary Fund, number 2025/105, May.
• Samuele Centorrino & Antonia Diakantoni & Alexander Keck & Michele Ruta & Monika Sztajerowska & Yuting Wei, 2025, "Measuring Global Trade Policy Activity," IMF Working Papers, International Monetary Fund, number 2025/220, Oct.
• Mateo Ljubisic, 2025, "Guiding through uncertainty: nowcasting the GDP of Croatia," Public Sector Economics, Institute of Public Finance, volume 49, issue 2, pages 185-211, DOI: 10.3326/pse.49.2.1.
• Budría, Santiago & Fermé, Eduardo & Freitas, Diogo Nuno, 2025, "Toward Proactive Policy Design: Identifying 'To-Be' Energy-Poor Households Using Shap for Early Intervention," IZA Discussion Papers, IZA Network @ LISER, number 17669, Feb.
• Gorodnichenko, Yuriy & Vasudevan, Vittal, 2025, "Macroeconomic Expectations in a War," IZA Discussion Papers, IZA Network @ LISER, number 18017, Jul.
• Priscila Espinosa & Priscila Espinosa & Maria Teresa Balaguer-Coll & José Manuel Pavía & Emili Tortosa-Ausina, 2025, "Urban economic resilience after climate disasters: A regional recovery forecasting framework for the Valencia floods," Working Papers, Economics Department, Universitat Jaume I, Castellón (Spain), number 2025/10.
• Hyder Ali & Salma Naz, 2025, "Out-of-sample equity premium prediction: A voting approach to forecast combination," Annals of Finance, Springer, volume 21, issue 3, pages 243-281, September, DOI: 10.1007/s10436-025-00466-9.
• Fei Su & Feifan Wang & Yahua Xu, 2025, "Economic Policy Uncertainty and Volatility Spillovers Among International Stock Market Indices During the COVID-19 Outbreak," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, volume 32, issue 1, pages 237-266, March, DOI: 10.1007/s10690-024-09452-z.
• João Felix & Michel Alexandre & Gilberto Tadeu Lima, 2025, "Applying Machine Learning Algorithms to Predict the Size of the Informal Economy," Computational Economics, Springer;Society for Computational Economics, volume 65, issue 3, pages 1169-1189, March, DOI: 10.1007/s10614-024-10593-6.
• Emile du Plessis, 2025, "Can Text-Based Statistical Models Reveal Impending Banking Crises?," Computational Economics, Springer;Society for Computational Economics, volume 65, issue 3, pages 1265-1298, March, DOI: 10.1007/s10614-024-10594-5.
• Havisha Jahajeeah & Aslam A. E. F. Saib, 2025, "Greymodels: A Shiny Package for Grey Forecasting Models in R," Computational Economics, Springer;Society for Computational Economics, volume 65, issue 3, pages 1549-1565, March, DOI: 10.1007/s10614-024-10610-8.