Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2025

• Aguilar, Pablo & Vázquez, Jesús, 2025, "Multi-period Euler-equation learning and term structure," Economic Modelling, Elsevier, volume 153, issue C, DOI: 10.1016/j.econmod.2025.107346.
• Papenfuß, Patric & Schischke, Amelie & Rathgeber, Andreas, 2025, "Factors of predictive power for metal commodities," The North American Journal of Economics and Finance, Elsevier, volume 76, issue C, DOI: 10.1016/j.najef.2024.102309.
• Fernandez-Perez, Adrián & Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2025, "Examining the transmission of credit and liquidity risks: A network analysis for EMU sovereign debt markets," The North American Journal of Economics and Finance, Elsevier, volume 77, issue C, DOI: 10.1016/j.najef.2025.102407.
• Hu, Genhua & Ma, Xiaoqing & Zhu, Tingting, 2025, "Forecasting volatility of China’s crude oil futures based on hybrid ML-HAR-RV models," The North American Journal of Economics and Finance, Elsevier, volume 78, issue C, DOI: 10.1016/j.najef.2025.102428.
• Clements, Adam & Otero, Jesús, 2025, "Forecasting retail fuel prices with spatial interdependencies," Economics Letters, Elsevier, volume 247, issue C, DOI: 10.1016/j.econlet.2024.112128.
• Younker, James, 2025, "Calculating effective degrees of freedom for forecast combinations and ensemble models," Economics Letters, Elsevier, volume 247, issue C, DOI: 10.1016/j.econlet.2024.112137.
• Marcellino, Massimiliano & Pfarrhofer, Michael, 2025, "Nonparametric mixed frequency monitoring macro-at-risk," Economics Letters, Elsevier, volume 255, issue C, DOI: 10.1016/j.econlet.2025.112498.
• Seiler, Pascal, 2025, "Measuring economic sentiment from open-ended survey comments using large language models," Economics Letters, Elsevier, volume 256, issue C, DOI: 10.1016/j.econlet.2025.112622.
• Chen, Minghui & Hanauer, Matthias X. & Kalsbach, Tobias, 2025, "Model complexity and the performance of global versus regional models," Economics Letters, Elsevier, volume 257, issue C, DOI: 10.1016/j.econlet.2025.112641.
• Ghirelli, Corinna & Pérez, Javier J. & Santabárbara, Daniel, 2025, "Forecast errors and the sacrifice ratio of monetary policy in the euro area," Economics Letters, Elsevier, volume 257, issue C, DOI: 10.1016/j.econlet.2025.112678.
• Tu, Yundong & Zheng, Jinsha, 2025, "Consistent model selection for factor-augmented regression within hierarchical factor structures," Economics Letters, Elsevier, volume 257, issue C, DOI: 10.1016/j.econlet.2025.112697.
• Gonçalves, Sílvia & McCracken, Michael W. & Yao, Yongxu, 2025, "Bootstrapping out-of-sample predictability tests with real-time data," Journal of Econometrics, Elsevier, volume 247, issue C, DOI: 10.1016/j.jeconom.2024.105916.
• Paap, Richard & Franses, Philip Hans, 2025, "Shrinkage estimators for periodic autoregressions," Journal of Econometrics, Elsevier, volume 247, issue C, DOI: 10.1016/j.jeconom.2024.105937.
• Czellar, Veronika & Garcia, René & Le Grand, François, 2025, "Uncovering asset market participation from household consumption and income," Journal of Econometrics, Elsevier, volume 248, issue C, DOI: 10.1016/j.jeconom.2024.105867.
• Ding, Yi & Engle, Robert & Li, Yingying & Zheng, Xinghua, 2025, "Multiplicative factor model for volatility," Journal of Econometrics, Elsevier, volume 249, issue PB, DOI: 10.1016/j.jeconom.2025.105959.
• Lin, Tzu-Chi & Liu, Chu-An, 2025, "Model averaging prediction for possibly nonstationary autoregressions," Journal of Econometrics, Elsevier, volume 249, issue PB, DOI: 10.1016/j.jeconom.2025.105994.
• Tu, Yundong & Wang, Siwei, 2025, "Quantile prediction with factor-augmented regression: Structural instability and model uncertainty," Journal of Econometrics, Elsevier, volume 249, issue PB, DOI: 10.1016/j.jeconom.2025.105999.
• Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2025, "Bayesian neural networks for macroeconomic analysis," Journal of Econometrics, Elsevier, volume 249, issue PC, DOI: 10.1016/j.jeconom.2024.105843.
• Ahrens, Maximilian & Erdemlioglu, Deniz & McMahon, Michael & Neely, Christopher J. & Yang, Xiye, 2025, "Mind your language: Market responses to central bank speeches," Journal of Econometrics, Elsevier, volume 249, issue PC, DOI: 10.1016/j.jeconom.2024.105921.
• Haghighi, Maryam & Joseph, Andreas & Kapetanios, George & Kurz, Christopher & Lenza, Michele & Marcucci, Juri, 2025, "Machine Learning for Economic Policy," Journal of Econometrics, Elsevier, volume 249, issue PC, DOI: 10.1016/j.jeconom.2025.105970.
• Chen, Han & Fei, Yijie & Yu, Jun, 2025, "Multivariate stochastic volatility models based on generalized Fisher transformation," Journal of Econometrics, Elsevier, volume 251, issue C, DOI: 10.1016/j.jeconom.2025.106041.
• Chen, Yi-Ting & Liu, Chu-An & Su, Jiun-Hua, 2025, "Bregman model averaging for forecast combination," Journal of Econometrics, Elsevier, volume 251, issue C, DOI: 10.1016/j.jeconom.2025.106076.
• Sun, Yixiao, 2025, "Support vector decision making," Journal of Econometrics, Elsevier, volume 251, issue C, DOI: 10.1016/j.jeconom.2025.106087.
• Wróblewska, Justyna, 2025, "Bayesian analysis of seasonally cointegrated VAR models," Econometrics and Statistics, Elsevier, volume 35, issue C, pages 55-70, DOI: 10.1016/j.ecosta.2023.02.002.
• 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.

2024

• Do, Quang Hung, 2024, "Predicting Efficiency of Commercial Banks in Vietnam: A DEA and Machine Learning Approach," Advances in Decision Sciences, Asia University, Taiwan, volume 28, issue 4, pages 120-143.
• Nguyen Anh Phong & Phan Huy Tam & Ngo Phu Thanh, 2024, "Identifying Fraudulent Financial Reports: Verification Between the M-Score Model and the Auditor’s Opinion," Advances in Decision Sciences, Asia University, Taiwan, volume 28, issue 4, pages 23-45.
• Hyeongwoo Kim & Jisoo Son, 2024, "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2024-01, Feb.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2024, "Predictive Power of U.S. Macroeconomic Factors for the Dollar/Won Real Exchange Rate," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2024-02, Feb.
• Sedat Çerez & Abdullah Kürşat Merter & Yavuz Selim Balcıoğlu & Gökhan Özer, 2024, "Evaluation of Annual Reports by Text Analysis: An Application in Bist100 Index," Journal of Finance Letters (Maliye ve Finans Yazıları), Maliye ve Finans Yazıları Yayıncılık Ltd. Şti., volume 39, issue 121, pages 175-188, April, DOI: https://doi.org/10.33203/mfy.133848.
• Rodney Duffett & Rodica Milena Zaharia & Tudor Edu & Raluca Constantinescu & Costel Negricea, 2024, "Exploring the Antecedents of Artificial Intelligence Products’ Usage. The Case of Business Students," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, volume 26, issue 65, pages 106-106, February.
• Khulood Mohammed BaLashwar & Yuosuf Khalid Al-Hamar & Seyed-Ali Sadegh-Zadeh, 2024, "Optimizing Bank Stability Through MSME Loan Securitization: A Predictive and Prescriptive Analytics Approach," The African Finance Journal, Africagrowth Institute, volume 26, issue 2, pages 58-79.
• Bastianin, Andrea & Mirto, Elisabetta & Qin, Yan & Rossini, Luca, , "What drives the European carbon market? Macroeconomic factors and forecasts," FEEM Working Papers, Fondazione Eni Enrico Mattei (FEEM), number 339740, DOI: 10.22004/ag.econ.339740.
• Tomasz Serafin & Rafal Weron, 2024, "Loss functions in regression models: Impact on profits and risk in day-ahead electricity trading," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/24/03.
• Katarzyna Chec & Bartosz Uniejewski & Rafal Weron, 2024, "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/24/04.
• İbrahim Tutar & Özge Orbey, 2024, "Start-up Değerlemesi: Yeni bir Yöntem Önerisi," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 9, issue 3, pages 549-574, DOI: 10.30784/epfad.1475685.
• Lucian MIRESCU & Ana-Maria Camelia POPESCU, 2024, "Analysis And Forecast Of The Employees In The Public And Private Health Systems In Romania," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, volume 0, issue 1, pages 113-138, May.
• Liudmyla DOROKHOVA & Silvia BELOEVA & Nataliya VENELINOVA & Oleksandr DOROKHOV, 2024, "Consumer service modeling: the study of buyer’s queues in pharmacies," Access Journal, Access Press Publishing House, volume 5, issue 3, pages 511-525, July, DOI: 10.46656/access.2024.5.3(8).
• Evgeny V. Balatsky, Natalia A. Ekimova, 2024, "Identification of Economies of Scale in Regional-Industrial Production Complexes of Russia: Theoretical Foundations and Econometric Estimates," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, volume 23, issue 2, pages 394-421, DOI: https://doi.org/10.15826/vestnik.20.
• Elena G. Shershneva, Min Zhou Hao, 2024, "Russian Banks Financial Stability Loss Diagnostic: Multidimensional Logit-Model Approach," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, volume 23, issue 2, pages 476-498, DOI: https://doi.org/10.15826/vestnik.20.
• Algieri, Bernardina & Iania, Leonardo & Leccadito, Arturo, 2024, "Looking ahead: Forecasting total energy carbon dioxide emissions," LIDAM Reprints LFIN, Université catholique de Louvain, Louvain Finance (LFIN), number 2024007, Jan, DOI: https://doi.org/10.1016/j.cesys.202.
• Gabriel P. Mathy & Yongchen Zhao, 2024, "Could Diffusion Indexes Have Forecasted the Great Recession?," Working Papers, American University, Department of Economics, number 2024-03.
• Ozge Camalan & Sahika Gokmen & Sibel Atan, 2024, "Using Advanced Machine Learning Techniques to Predict the Sales Volume of Non-Fungible Tokens," World Journal of Applied Economics, WERI-World Economic Research Institute, volume 10, issue 1, pages 17-27, June, DOI: 10.22440/wjae.10.1.2.
• Merve Kılınç Yılmaz & Yusuf Şahin & Kenan Oğuzhan Oruç, 2024, "Price Forecasting of Feed Raw Materials Used in Dairy Farming: A Methodological Comparison," Alphanumeric Journal, Bahadir Fatih Yildirim, volume 12, issue 3, pages 249-280, December, DOI: https://doi.org/10.17093/alphanumer.
• Құратова Ақбөпе // Kuratova Akbope & Ускенбаев Азат // Uskenbayev Azat, 2024, "Подходы К Оценке Устойчивости Внешнего Сектора Казахстана," Working Papers, National Bank of Kazakhstan, number #2024-9.
• Konrad Raczkowski & Jarosław Klepacki, 2024, "Typologia metod prognozowania kursu walutowego," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 3, pages 350-366.
• Alberto Vindas-Quesada & Carlos Brenes-Soto & Adriana Sandí-Esquivel & Susan Jiménez-Montero, 2024, "Univariate inflation forecasts in Costa Rica: model evaluation and selection," Notas Técnicas, Banco Central de Costa Rica, number 2405, Oct.
• Inna S. Lola & Dmitry G. Asoskov, 2024, "Potential of business uncertainty indicators in forecasting economic activity: The case of Russia," Russian Journal of Economics, ARPHA Platform, volume 10, issue 4, pages 351-364, December, DOI: 10.32609/j.ruje.10.113578.
• Anna A. Maigur, 2024, "Machine learning algorithms for predicting unemployment duration in Russia," Russian Journal of Economics, ARPHA Platform, volume 10, issue 4, pages 365-384, December, DOI: 10.32609/j.ruje.10.128611.
• Takaaki Koike & Cathy W. S. Chen & Edward M. H. Lin, 2024, "Forecasting and Backtesting Gradient Allocations of Expected Shortfall," Papers, arXiv.org, number 2401.11701, Jan, revised Jun 2024.
• M. Hashem Pesaran & Ron P. Smith, 2024, "High-dimensional forecasting with known knowns and known unknowns," Papers, arXiv.org, number 2401.14582, Jan, revised Apr 2024.
• Davide Fiaschi & Cristina Tealdi, 2024, "Let's roll back! The challenging task of regulating temporary contracts," Papers, arXiv.org, number 2401.17971, Jan.
• Andrea Bastianin & Elisabetta Mirto & Yan Qin & Luca Rossini, 2024, "What drives the European carbon market? Macroeconomic factors and forecasts," Papers, arXiv.org, number 2402.04828, Feb, revised Feb 2024.
• Arnaud Dufays & Aristide Houndetoungan & Alain Coen, 2024, "Selective linear segmentation for detecting relevant parameter changes," Papers, arXiv.org, number 2402.05329, Feb.
• Jeff Dominitz & Charles F. Manski, 2024, "Comprehensive OOS Evaluation of Predictive Algorithms with Statistical Decision Theory," Papers, arXiv.org, number 2403.11016, Mar, revised Apr 2025.
• Bartosz Bieganowski & Robert Slepaczuk, 2024, "Supervised Autoencoder MLP for Financial Time Series Forecasting," Papers, arXiv.org, number 2404.01866, Apr, revised Jun 2024.
• Arkadiusz Lipiecki & Bartosz Uniejewski & Rafa{l} Weron, 2024, "Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression," Papers, arXiv.org, number 2404.02270, Apr, revised Oct 2024.
• M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2024, "Forecasting with panel data: Estimation uncertainty versus parameter heterogeneity," Papers, arXiv.org, number 2404.11198, Apr, revised Jan 2026.
• Tony Chernis & Gary Koop & Emily Tallman & Mike West, 2024, "Decision synthesis in monetary policy," Papers, arXiv.org, number 2406.03321, Jun, revised Feb 2025.
• Kamil Kashif & Robert 'Slepaczuk, 2024, "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Papers, arXiv.org, number 2406.18206, Jun.
• Maciej Wysocki & Robert 'Slepaczuk, 2024, "Construction and Hedging of Equity Index Options Portfolios," Papers, arXiv.org, number 2407.13908, Jul.
• Jannik Kreye & Philipp Sibbertsen, 2024, "Testing for a Forecast Accuracy Breakdown under Long Memory," Papers, arXiv.org, number 2409.07087, Sep.
• Laura Coroneo & Fabrizio Iacone, 2024, "Testing for equal predictive accuracy with strong dependence," Papers, arXiv.org, number 2409.12662, Sep.
• Matteo Mogliani & Florens Odendahl, 2024, "Density forecast transformations," Papers, arXiv.org, number 2412.06092, Dec.
• Kemal Kirtac & Guido Germano, 2024, "Sentiment trading with large language models," Papers, arXiv.org, number 2412.19245, Dec.
• Conrad, Christian & Lahiri, Kajal, 2024, "Heterogeneous Expectations among Professional Forecasters," Working Papers, University of Heidelberg, Department of Economics, number 0754, Oct.
• Xiao Li & Wenjun Xue & Kaimeng Zhang, 2024, "The Predictive Power of Monetary Policy on International Stock Market Returns-Evidence From TV-ARMAX Model," Asian Economics Letters, Asia-Pacific Applied Economics Association, volume 5, issue 2, pages 1-8, DOI: 2024/06/28.
• Xiaohang Ren & Kang Yuan & Lizhu Tao & Cheng Yan, 2024, "Carbon Prices Forecasting Using Group Information," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, volume 4, issue 4, pages 1-6, DOI: 2024/07/09.
• Massimiliano MARCELLINO & Michael PFARRHOFER, 2024, "Bayesian nonparametric methods for macroeconomic forecasting," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 24224.
• Monia Magnani, 2024, "Does Macroeconomic Predictability Enhance the Economic Value of Hedge Funds to Risk-Averse Investors?," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 24232.
• Etienne Briand & Massimiliano Marcellino & Dalibor Stevanovic, 2024, "Inflation, Attention and Expectations," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 24-05, Dec, revised Dec 2024.
• Antoine Poulin-Moore & Kerem Tuzcuoglu, 2024, "Forecasting Recessions in Canada: An Autoregressive Probit Model Approach," Staff Working Papers, Bank of Canada, number 24-10, Mar, DOI: 10.34989/swp-2024-10.
• Tony Chernis & Gary Koop & Emily Tallman & Mike West, 2024, "Decision Synthesis in Monetary Policy," Staff Working Papers, Bank of Canada, number 24-30, Aug, DOI: 10.34989/swp-2024-30.
• Pablo Garcia & Pascal Jacquinot & Crt Lenarcic & Kostas Mavromatis & Niki Papadopoulou & Edgar Silgado-Gómez, 2024, "Green Transition in the euro area: Domestic and global factors," BCL working papers, Central Bank of Luxembourg, number 190, Sep.
• Furkan TURKOGLU & Eda GOCECEK & Yavuz YUMRUKUZ, 2024, "Predictive Abilities of Machine Learning and Deep Learning Approaches for Exchange Rate Prediction," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, volume 18, issue 2, pages 186-210.
• Todd E. Clark & Gergely Ganics & Elmar Mertens, 2024, "Constructing fan charts from the ragged edge of SPF forecasts," Working Papers, Banco de España, number 2429, Sep, DOI: https://doi.org/10.53479/37597.
• Alicia Aguilar & Ricardo Gimeno, 2024, "Discrete Probability Forecasts: What to expect when you are expecting a monetary policy decision," Working Papers, Banco de España, number 2438, Oct, DOI: https://doi.org/10.53479/37893.
• Francesco Braggiotti & Nicola Chiarini & Giulio Dondi & Luciano Lavecchia & Valeria Lionetti & Juri Marcucci & Riccardo Russo, 2024, "Predicting buildings' EPC in Italy: a machine learning based-approach," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 850, Jun.
• Davide Delle Monache & Claudia Pacella, 2024, "The drivers of inflation dynamics in Italy over the period 2021-2023," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 873, Oct.
• Donato Ceci & Orest Prifti & Andrea Silvestrini, 2024, "Nowcasting Italian GDP growth: a Factor MIDAS approach," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1446, Mar.
• Andrea Gazzani & Fabrizio Venditti & Giovanni Veronese, 2024, "Oil price shocks in real time," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1448, Mar.
• Simon Freyaldenhoven & Christian B. Hansen & Jorge Pérez Pérez & Jesse M. Shapiro & Constantino Carreto, 2024, "Policy Effect Estimation and Visualization in Linear Panel Event-Study Designs: Introducing the xtevent Package," Working Papers, Banco de México, number 2024-09, Aug.
• Lenin Arango-Castillo & Francisco J. Martínez-Ramírez & María José Orraca, 2024, "Univariate Measures of Persistence: A Comparative Analysis," Working Papers, Banco de México, number 2024-11, Sep.
• Magnus Saß, 2024, "Detecting excessive credit growth: An approach based on structural counterfactuals," Berlin School of Economics Discussion Papers, Berlin School of Economics, number 0046, Aug, DOI: 10.48462/opus4-5591.
• Gary Cornwall & Marina Gindelsky, 2024, "Nowcasting Distributional National Accounts for the United States: A Machine Learning Approach," BEA Papers, Bureau of Economic Analysis, number 0130, Sep.
• Pınar Karadayı Ataş, 2024, "A Novel Hybrid Regression Model for Banking Loss Estimation," Bingol University Journal of Economics and Administrative Sciences, Bingol University, Faculty of Economics and Administrative Sciences, volume 8, issue 1, pages 91-105, June, DOI: https://doi.org/10.33399/biibfad.13.
• Ilia Chapyshev & Ansel Shaidullin, 2024, "Study of the Problem of Interoperability of the Bank of Russia's Digital Currency," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 1, pages 104-126, March.
• Anastasiia Pankratova, 2024, "Forecasting Key Macroeconomic Indicators Using DMA and DMS Methods," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 1, pages 32-52, March.
• Urmat Dzhunkeev, 2024, "Forecasting Inflation in Russia Using Gradient Boosting and Neural Networks," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 1, pages 53-76, March.
• Anastasia Mogilat & Oleg Kryzhanovskiy & Zhanna Shuvalova & Yaroslav Murashov, 2024, "DYFARUS: Dynamic Factor Model to Forecast GDP by Output Using Input-Output Tables," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 2, pages 3-25, June.
• Yury Perevyshin, 2024, "Analysts' Inflation Expectations vs Univariate Models of Inflation Forecasting in the Russian Economy," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 2, pages 54-76, June.
• Rodion Latypov & Elena Akhmedova & Egor Postolit & Marina Mikitchuk, 2024, "Bottom-up Inflation Forecasting Using Machine Learning Methods," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 3, pages 23-44, September.
• Alexandra Bozhechkova & Urmat Dzhunkeev, 2024, "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 3, pages 45-69, September.
• Oguzhan Cepni & Rangan Gupta & Wenting Liao & Jun Ma, 2024, "Climate risks and forecastability of the weekly state‐level economic conditions of the United States," International Review of Finance, International Review of Finance Ltd., volume 24, issue 1, pages 154-162, March, DOI: 10.1111/irfi.12431.
• Leona Han Chen & Yijie Fei & Jun Yu, 2024, "Multivariate Stochastic Volatility Models based on Generalized Fisher Transformation," Working Papers, University of Macau, Faculty of Business Administration, number 202419, Oct.
• Fernando Eguren-Martin & Sevim Kösem & Guido Maia & Andrej Sokol, 2024, "Targeted financial conditions indices and growth-at-risk," Bank of England working papers, Bank of England, number 1084, Aug.
• Mehrabani Ali & Parsaeian Shahnaz & Ullah Aman, 2024, "Shrinkage Estimation and Forecasting in Dynamic Regression Models Under Structural Instability," Journal of Econometric Methods, De Gruyter, volume 13, issue 2, pages 251-279, DOI: 10.1515/jem-2023-0036.
• Prüser Jan, 2024, "Forecasting the Risk of Cryptocurrencies: Comparison and Combination of GARCH and Stochastic Volatility Models," Journal of Time Series Econometrics, De Gruyter, volume 16, issue 2, pages 83-108, DOI: 10.1515/jtse-2023-0039.
• Mohamed Riyath Mohamed Ismail & Aldabbous Nagham, 2024, "Long-Run Volatility Memory Dynamics and Inter-Market Linkages in GCC Equity Markets: Application of DCC-FIGARCH Models," Review of Middle East Economics and Finance, De Gruyter, volume 20, issue 3, pages 299-329, DOI: 10.1515/rmeef-2024-0018.
• Chernis Tony, 2024, "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 28, issue 2, pages 293-317, April, DOI: 10.1515/snde-2022-0108.
• Baruník Jozef & Fišer Pavel, 2024, "Co-Jumping of Treasury Yield Curve Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 28, issue 3, pages 481-506, DOI: 10.1515/snde-2022-0091.
• Ayala Astrid & Blazsek Szabolcs & Licht Adrian, 2024, "Volatility Forecasting Using Quasi-Score-Driven Models with an Application to the Coronavirus Pandemic Period," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 28, issue 5, pages 785-805, DOI: 10.1515/snde-2022-0085.
• Pesaran, M. H. & Smith, R. P., 2024, "High-Dimensional Forecasting with Known Knowns and Known Unknowns," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2406, Feb.
• Agarwala, M. & Burke, M. & Doherty-Bigara, J. & Klusak, P. & Mohaddes, K., 2024, "Climate Change and Sovereign Risk: A Regional Analysis for the Caribbean," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2420, Apr.
• Pesaran, M. H. & Song, H., 2024, "Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2464, Oct.
• Burke, M. & Agarwala, M. & Klusak, P. & Mohaddes, K., 2024, "Climate Policy and Sovereign Debt: The Impact of Transition Scenarios on Sovereign Creditworthiness," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2470, Dec.
• Congressional Budget Office, 2024, "An Evaluation of CBO’s Projections of Deficits and Debt From 1984 to 2023," Reports, Congressional Budget Office, number 60664, Dec.
• M. Hashem Pesaran & Ron P. Smith, 2024, "High-Dimensional Forecasting with Known Knowns and Known Unknowns," CESifo Working Paper Series, CESifo, number 10931.
• Alexandros Botsis & Christoph Görtz & Plutarchos Sakellaris, 2024, "Quantifying Qualitative Survey Data with Panel Data Structure," CESifo Working Paper Series, CESifo, number 11013.
• Hannes Ullrich & Jonas Hannane & Christian Peukert & Luis Aguiar & Tomaso Duso, 2024, "Returns to Data: Evidence from Web Tracking," CESifo Working Paper Series, CESifo, number 11240.
• Thorsten Drautzburg & Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Dick Oosthuizen, 2024, "Filtering with Limited Information," CESifo Working Paper Series, CESifo, number 11243.
• M. Hashem Pesaran & Hayun Song, 2024, "Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call," CESifo Working Paper Series, CESifo, number 11415.
• Stefan Sauer & Klaus Wohlrabe, 2024, "What Is Behind the ifo Business Climate? Evidence from a Meta-Survey," CESifo Working Paper Series, CESifo, number 11482.
• Mariia Okuneva & Philipp Hauber & Kai Carstensen & Jasper Bär, 2024, "Nowcasting German GDP with Text Data," CESifo Working Paper Series, CESifo, number 11587.
• Katharina Wedel, 2024, "Improving Educational Outcomes: Analyses of Interventions and Public Opinion," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 105.
• Markus Leippold & Michal Svaton, 2024, "Scheduling Processes and Inference of Scheduled Events From Price Data," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-12, Jan.
• Soros Chitsiripanich & Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2024, "Smoothing Out Momentum and Reversal," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-47, Sep.
• Yicheng Wang & Didier Sornette & Ke Wu & Sandro Claudio Lera, 2024, "Dynamic Influence Networks Self-Organize Towards Sub-Critical Financial Instabilities," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-77, Oct.
• V. Candila & O. Cepni & G. M. Gallo & R. Gupta, 2024, "Influence of Local and Global Economic Policy Uncertainty on the volatility of US state-level equity returns: Evidence from a GARCH-MIDAS approach with Shrinkage and Cluster Analysis," Working Paper CRENoS, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia, number 202414.
• G.M. Gallo & C.Ongari & S. Borgioli, 2024, "Financial Returns, Sentiment and Market Volatility: a Dynamic Assessment," Working Paper CRENoS, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia, number 202415.
• Omar Castillo Nuñez, 2024, "Incidencia de las lluvias y del precio en la oferta de leche cruda en los departamentos de Córdoba y Sucre, Colombia," Ensayos de Economía, Universidad Nacional de Colombia Sede Medellín, number 21226, Sep.
• Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2024, "Specification Choices in Quantile Regression for Empirical Macroeconomics," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18901, Mar.
• Marcellino, Massimiliano & Pfarrhofer, Michael, 2024, "Bayesian nonparametric methods for macroeconomic forecasting," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18970, Apr.
• Baumeister, Christiane & Huber, Florian & Marcellino, Massimiliano, 2024, "Risky Oil: It's All in the Tails," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19129, Jun.
• Kwon, Alexander & Maliar, Lilia, 2024, "Predicting Retirement and Social Security Claiming Decisions using Machine Learning," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19198, Jul.
• Ullrich, Hannes & Hannane, Jonas & Peukert, Christian & Aguiar, Luis & Duso, Tomaso, 2024, "Returns to Data: Evidence from Web Tracking," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19266, Jul.
• Drautzburg, Thorsten & Fernández-Villaverde, Jesús & Guerron, Pablo & Oosthuizen, Dick, 2024, "Filtering with Limited Information," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19270, Jul.
• Hauzenberger , Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2024, "Bayesian Neural Networks for Macroeconomic Analysis," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19381, Aug.
• Bassetti, Federico & Casarin, Roberto & Del Negro, Marco, 2024, "A Bayesian Approach for Inference on Probabilistic Surveys," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19426, Sep.
• Blazsek, Szabolcs & Escribano, Álvaro & Kristof, Erzsebet, 2024, "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics, Universidad Carlos III de Madrid. Departamento de Economía, number 39546, Jan.
• Barrio Castro, Tomás del & Escribano, Álvaro & Sibbertsen, Philipp, 2024, "Modeling and Forecasting the Long Memory of Cyclical Trends in Paleoclimate Data," UC3M Working papers. Economics, Universidad Carlos III de Madrid. Departamento de Economía, number 43987, Jun.
• Julen Iglesias Tejedor, 2024, "Creación de una cartera de inversión que venza la inflación atendiendo a criterios ESG gestionada mediante machine learning," Revista de Economía y Finanzas (REyF), Asociación Cuadernos de Economía, volume 2, issue 5, pages 79-100, Mayo.
• Javier Teo Sanz Ortega, 2024, "El mercado bursátil español: BME Growth frente al IBEX," Revista de Economía y Finanzas (REyF), Asociación Cuadernos de Economía, volume 2, issue 6, pages 185-198, Septiembr.
• Janny Núñez-Almonte & Alfredo Grau-Grau & Inmaculada Bel-Oms, 2024, "Sustainability, sustainable finance, good governance codes. A new perspective," Revista de Economía y Finanzas (REyF), Asociación Cuadernos de Economía, volume 2, issue 6, pages 199-214, Septiembr.
• Pesaran, M. Hashem & Smith, Ron P., 2024, "High-Dimensional Forecasting With Known Knowns And Known Unknowns," National Institute Economic Review, National Institute of Economic and Social Research, volume 267, issue , pages 1-25, February.
• Issam BOUSALAM & Ahmed KHATTAB & Yahya SALMI, 2024, "Explicative determinants of real exchange rate volatility in Morocco: An econometric approach," Turkish Economic Review, EconSciences Journals, volume 11, issue 3-4, pages 88-101, November.
• Hannes Ullrich & Jonas Hannane & Christian Peukert & Luis Aguiar & Tomaso Duso, 2024, "Returns to Data: Evidence from Web Tracking," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 2091.
• Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024, "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers, DNB, number 806, Mar.
• Pablo Garcia & Pascal Jacquinot & ÄŒrt LenarÄ iÄ & Kostas Mavromatis & Niki Papadopoulou & Niki Papadopoulou, 2024, "Green Transition in the Euro Area: Domestic and Global Factors," Working Papers, DNB, number 816, Oct.
• Dorinth van Dijk & Mick van Rooijen & Jasper de Winter, 2024, "DFROG: A nowcasting model for GDP growth," Working Papers, DNB, number 819, Nov.
• Chahad, Mohammed & Hofmann-Drahonsky, Anna-Camilla & Krause, Willi & Landau, Bettina & Sigwalt, Antoine, 2024, "The empirical performance of ECB/Eurosystem staff inflation projections since 2000," Economic Bulletin Articles, European Central Bank, volume 5.
• Chahad, Mohammed & Martínez Hernández, Catalina & Page, Adrian & Hofmann-Drahonsky, Anna-Camilla, 2024, "An update on the accuracy of recent Eurosystem/ECB staff projections for short-term inflation," Economic Bulletin Boxes, European Central Bank, volume 2.
• Page, Adrian, 2024, "The performance of Eurosystem/ECB staff projections for economic growth since the COVID-19 pandemic," Economic Bulletin Boxes, European Central Bank, volume 7.
• Ciccarelli, Matteo & Darracq Pariès, Matthieu & Priftis, Romanos & Angelini, Elena & Bańbura, Marta & Bokan, Nikola & Fagan, Gabriel & Gumiel, José Emilio & Kornprobst, Antoine & Lalik, Magdalena & Mo, 2024, "ECB macroeconometric models for forecasting and policy analysis," Occasional Paper Series, European Central Bank, number 344, Mar.
• Cappelletti, Giuseppe & Dimitrov, Ivan & Naruševičius, Laurynas & Le Grand, Catherine & Nunes, André & Podlogar, Jure & Röhm, Nicola & Ter Steege, Lucas, 2024, "2023 macroprudential stress test of the euro area banking system," Occasional Paper Series, European Central Bank, number 347, May.
• Allayioti, Anastasia & Venditti, Fabrizio, 2024, "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series, European Central Bank, number 2901, Feb.
• Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2024, "Nowcasting consumer price inflation using high-frequency scanner data: evidence from Germany," Working Paper Series, European Central Bank, number 2930, Apr.
• Darracq Pariès, Matthieu & Kornprobst, Antoine & Priftis, Romanos, 2024, "Monetary policy strategies to navigate post-pandemic inflation: an assessment using the ECB’s New Area-Wide Model," Working Paper Series, European Central Bank, number 2935, Apr.
• Borgioli, Stefano & Gallo, Giampiero M. & Ongari, Chiara, 2024, "Financial returns, sentiment and market volatility. A dynamic assessment," Working Paper Series, European Central Bank, number 2999, Nov.
• Linzenich, Jan & Meunier, Baptiste, 2024, "Nowcasting Made Easier: a toolbox for economists," Working Paper Series, European Central Bank, number 3004, Dec.
• Siphat Lim & Edman Flores & Casey Barnett, 2024, "Analyzing the Effectiveness of a System of Equation Model in Comparison to Single Equation Models for Predicting General Price Level in Cambodia," International Journal of Economics and Financial Issues, Econjournals, volume 14, issue 5, pages 156-166, September.
• Aarti Mehta Sharma & Saina Baby & Varsha Raghu, 2024, "Forecasting High Speed Diesel Demand in India with Econometric and Machine Learning Methods," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 1, pages 496-506, January.
• Wamiliana Wamiliana & Edwin Russel & Iskandar Ali Alam & Widiarti Widiarti & Tuti Hairani & Mustofa Usman, 2024, "Modeling and Forecasting Closing Prices of some Coal Mining Companies in Indonesia by Using the VAR(3)-BEKK GARCH(1,1) Model," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 1, pages 579-591, January.
• Bharat Kumar Meher & Abhishek Anand & Sunil Kumar & Ramona Birau & Manohar Sing, 2024, "Effectiveness of Random Forest Model in Predicting Stock Prices of Solar Energy Companies in India," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 2, pages 426-434, March.
• Anggi Putri Kurniadi & Hasdi Aimon & Zamroni Salim & Ragimun Ragimun & Adang Sonjaya & Sigit Setiawan & Viktor Siagian & Lokot Zein Nasution & R Nurhidajat & Mutaqin Mutaqin & Joko Sabtohadi, 2024, "Analysis of Existing and Forecasting for Coal and Solar Energy Consumption on Climate Change in Asia Pacific: New Evidence for Sustainable Development Goals," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 4, pages 352-359, July.
• Herry Kartika Gandhi & Ispány Márton, 2024, "Multi-step Natural Gas Price Forecasting using Ensemble Empirical Mode Decomposition and Long Short-Term Memory Hybrid Model," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 4, pages 590-598, July.
• Hatem Brik & Jihene El Ouakdi, 2024, "Interplay of Volatility and Geopolitical Tensions in Clean Energy Markets: A Comprehensive GARCH-LSTM Forecasting Approach," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 4, pages 92-107, July.
• Wellcome Peujio Jiotsop-Foze & Adrián Hernández-del-Valle & Francisco Venegas-Martínez, 2024, "Transforming Mexico’s Electric Load Infrastructure: A Quantile Transformer Network Deep Learning Approach, 2019-2020," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 5, pages 527-533, September.
• Massimiliano Caporin & Muhammad Shahbaz & Bekhzod Kuziboev & Manzura Masharipova & Sherali Allaberganov & Samariddin Makhmudov, 2024, "Environmental Kuznets Curve for Extended Brics Economies: Do Women Governance and Water Stress Matter?," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 6, pages 174-183, November.
• Abdikani Yusuf Abdulle & Idiris Sid Ali Mohamed, 2024, "The Environmental Impact of Trade Openness on CO2 Emissions: Empirical Evidence from Somalia," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 6, pages 353-364, November.
• Zhang, Huajing & Jiang, Fuwei & Liu, Yumin, 2024, "Extrapolative beliefs and return predictability: Evidence from China," Journal of Behavioral and Experimental Finance, Elsevier, volume 43, issue C, DOI: 10.1016/j.jbef.2024.100957.
• Yacoubou Djima, Ismael & Kilic, Talip, 2024, "Attenuating measurement errors in agricultural productivity analysis by combining objective and self-reported survey data," Journal of Development Economics, Elsevier, volume 168, issue C, DOI: 10.1016/j.jdeveco.2023.103249.
• Botsis, Alexandros & Görtz, Christoph & Sakellaris, Plutarchos, 2024, "Quantifying qualitative survey data with panel data," Journal of Economic Dynamics and Control, Elsevier, volume 167, issue C, DOI: 10.1016/j.jedc.2024.104929.
• Lux, Thomas, 2024, "Lack of identification of parameters in a simple behavioral macroeconomic model," Journal of Economic Dynamics and Control, Elsevier, volume 168, issue C, DOI: 10.1016/j.jedc.2024.104972.
• Delogu, Marco & Lagravinese, Raffaele & Paolini, Dimitri & Resce, Giuliano, 2024, "Predicting dropout from higher education: Evidence from Italy," Economic Modelling, Elsevier, volume 130, issue C, DOI: 10.1016/j.econmod.2023.106583.
• Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024, "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, volume 135, issue C, DOI: 10.1016/j.econmod.2024.106706.
• Granados, Camilo & Parra-Amado, Daniel, 2024, "Estimating the output gap after COVID: How to address unprecedented macroeconomic variations," Economic Modelling, Elsevier, volume 135, issue C, DOI: 10.1016/j.econmod.2024.106711.
• Song, Yuping & Huang, Jiefei & Zhang, Qichao & Xu, Yang, 2024, "Heterogeneity effect of positive and negative jumps on the realized volatility: Evidence from China," Economic Modelling, Elsevier, volume 136, issue C, DOI: 10.1016/j.econmod.2024.106745.
• Arbués, Ignacio & Matilla-García, Mariano, 2024, "Multibenchmark reality checks," Economic Modelling, Elsevier, volume 140, issue C, DOI: 10.1016/j.econmod.2024.106848.
• Conigliani, Caterina & Costantini, Valeria & Paglialunga, Elena & Tancredi, Andrea, 2024, "Forecasting the climate-conflict risk in Africa along climate-related scenarios and multiple socio-economic drivers," Economic Modelling, Elsevier, volume 141, issue C, DOI: 10.1016/j.econmod.2024.106911.
• Dufera, Tamirat Temesgen, 2024, "Fractional Brownian motion in option pricing and dynamic delta hedging: Experimental simulations," The North American Journal of Economics and Finance, Elsevier, volume 69, issue PB, DOI: 10.1016/j.najef.2023.102017.
• Li, Xiaowei & Wu, Zhengyu & Zhang, Hao & Zhang, Lu, 2024, "Risk-neutral skewness and stock market returns: A time-series analysis," The North American Journal of Economics and Finance, Elsevier, volume 70, issue C, DOI: 10.1016/j.najef.2023.102040.
• Wang, Jia & Wang, Xinyi & Wang, Xu, 2024, "International oil shocks and the volatility forecasting of Chinese stock market based on machine learning combination models," The North American Journal of Economics and Finance, Elsevier, volume 70, issue C, DOI: 10.1016/j.najef.2023.102065.
• Herrera, Rodrigo & Piña, Marco, 2024, "Market risk modeling with option-implied covariances and score-driven dynamics," The North American Journal of Economics and Finance, Elsevier, volume 72, issue C, DOI: 10.1016/j.najef.2024.102136.
• Bufalo, Michele & Ceci, Claudia & Orlando, Giuseppe, 2024, "Addressing the financial impact of natural disasters in the era of climate change," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102152.
• Maki, Daiki, 2024, "Evaluation of volatility spillovers for asymmetric realized covariance," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102177.
• Sanford, Anthony, 2024, "Information content of option prices: Comparing analyst forecasts to option-based forecasts," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102197.
• Ren, Tingting & Li, Shaofang & Zhang, Siying, 2024, "Stock market extreme risk prediction based on machine learning: Evidence from the American market," The North American Journal of Economics and Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.najef.2024.102241.
• Yang, Qu & Yu, Yuanyuan & Dai, Dongsheng & He, Qian & Lin, Yu, 2024, "Can hybrid model improve the forecasting performance of stock price index amid COVID-19? Contextual evidence from the MEEMD-LSTM-MLP approach," The North American Journal of Economics and Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.najef.2024.102252.
• Zhao, Yongchen, 2024, "Uncertainty of household inflation expectations: Reconciling point and density forecasts," Economics Letters, Elsevier, volume 234, issue C, DOI: 10.1016/j.econlet.2023.111486.
• Drautzburg, Thorsten, 2024, "A structural approach to combining external and DSGE model forecasts," Economics Letters, Elsevier, volume 235, issue C, DOI: 10.1016/j.econlet.2024.111538.
• Doan, Bao & Jayasuriya, Dulani & Lee, John B. & Reeves, Jonathan J., 2024, "Cryptocurrency systematic risk dynamics," Economics Letters, Elsevier, volume 241, issue C, DOI: 10.1016/j.econlet.2024.111788.
• Kunaschk, Max, 2024, "Enriching administrative data using survey data and machine learning techniques," Economics Letters, Elsevier, volume 243, issue C, DOI: 10.1016/j.econlet.2024.111924.
• Harel, Arie & Harpaz, Giora, 2024, "Why stock analysts may make wrong predictions?," Economics Letters, Elsevier, volume 244, issue C, DOI: 10.1016/j.econlet.2024.111956.
• Telg, Sean, 2024, "Time aggregation of mixed causal–noncausal models," Economics Letters, Elsevier, volume 244, issue C, DOI: 10.1016/j.econlet.2024.112019.
• Arai, Natsuki & Iizuka, Nobuo & Yamamoto, Yohei, 2024, "The efficiency of the Japanese government’s revenue projections," Economics Letters, Elsevier, volume 244, issue C, DOI: 10.1016/j.econlet.2024.112035.
• Lange, Rutger-Jan, 2024, "Bellman filtering and smoothing for state–space models," Journal of Econometrics, Elsevier, volume 238, issue 2, DOI: 10.1016/j.jeconom.2023.105632.
• Reuvers, Hanno & Wijler, Etienne, 2024, "Sparse generalized Yule–Walker estimation for large spatio-temporal autoregressions with an application to NO2 satellite data," Journal of Econometrics, Elsevier, volume 239, issue 1, DOI: 10.1016/j.jeconom.2023.105520.
• Diebold, Francis X. & Rudebusch, Glenn D. & Göbel, Maximilian & Goulet Coulombe, Philippe & Zhang, Boyuan, 2024, "Reprint of: When will Arctic sea ice disappear? Projections of area, extent, thickness, and volume," Journal of Econometrics, Elsevier, volume 239, issue 1, DOI: 10.1016/j.jeconom.2023.105645.
• Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024, "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, volume 240, issue 1, DOI: 10.1016/j.jeconom.2024.105693.
• Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2024, "Predictive ability tests with possibly overlapping models," Journal of Econometrics, Elsevier, volume 241, issue 1, DOI: 10.1016/j.jeconom.2024.105716.
• Daouia, Abdelaati & Padoan, Simone A. & Stupfler, Gilles, 2024, "Extreme expectile estimation for short-tailed data," Journal of Econometrics, Elsevier, volume 241, issue 2, DOI: 10.1016/j.jeconom.2024.105770.
• Oh, Dong Hwan & Patton, Andrew J., 2024, "Better the devil you know: Improved forecasts from imperfect models," Journal of Econometrics, Elsevier, volume 242, issue 1, DOI: 10.1016/j.jeconom.2024.105767.
• Mei, Ziwei & Shi, Zhentao, 2024, "On LASSO for high dimensional predictive regression," Journal of Econometrics, Elsevier, volume 242, issue 2, DOI: 10.1016/j.jeconom.2024.105809.
• Brownlees, Christian & Llorens-Terrazas, Jordi, 2024, "Empirical risk minimization for time series: Nonparametric performance bounds for prediction," Journal of Econometrics, Elsevier, volume 244, issue 1, DOI: 10.1016/j.jeconom.2024.105849.
• Inoue, Atsushi & Rossi, Barbara & Wang, Yiru, 2024, "Local projections in unstable environments," Journal of Econometrics, Elsevier, volume 244, issue 2, DOI: 10.1016/j.jeconom.2024.105726.