Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2023

• Ivan Stankevich, 2023, "Application of Markov-Switching MIDAS models to nowcasting of GDP and its components," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 70, pages 122-143.
• Hasan Yosefizadeh & Farzaneh Khalili & Kamran Nadri, 2023, "Investigating the Effects of Taxation on the Profit of Bank Deposits on Inflation and GDP of Iran's Economy in the Form of a Dynamic General Equilibrium Model (DSGE)," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, volume 10, issue 1, pages 59-88.
• Reza Etemadpur & Sakine Owjimehr, 2023, "Evaluating the Role of Banking Facilities Distortions in the Impact of Macroeconomic Shocks within the Framework of a Dynamic Stochastic General Equilibrium Model: A Case Study of Iran," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, volume 10, issue 2, pages 145-182.
• Astafyeva, Ekaterina (Астафьева, Екатерина) & Turuntseva, Marina (Турунцева, Марина), 2023, "Analysis of the possibilities of improving the quality of forecasting prices for certain types of raw materials using the simplest methods of combining individual forecasts
  [Анализ Возможностей Пов," Working Papers, Russian Presidential Academy of National Economy and Public Administration, number w20220271, Oct.
• Perevyshin, Yuriy (Перевышин, Юрий) & Trunin, Pavel (Трунин, Павел), 2023, "Inflation expectations accuracy in russian economy
  [Точность Инфляционных Ожиданий В Российской Экономике]," Working Papers, Russian Presidential Academy of National Economy and Public Administration, number w202332.
• Perevyshin, Yuriy (Перевышин, Юрий) & Kolyadenko, Pavel (Коляденко, Павел), 2023, "Do inflation expectations improve model-based inflation forecasts in russian economy?
  [Помогают Ли Инфляционные Ожидания Прогнозировать Инфляцию В Российской Экономике?]," Working Papers, Russian Presidential Academy of National Economy and Public Administration, number w202333.
• Vedev, Aleksei (Ведев, Алексей) & Silchuk, Aleksandra (Сильчук, Александра) & Eremkin, Vladimir (Еремкин, Владимир) & Tuzov, Konstantin (Тузов, Константин) & Kovaleva, Maria (Ковалева, Мария), 2023, "Forecast of medium-term dynamics of socio-economic development of the Russian Federation under sanctions pressure, assessment of the effectiveness of implemented economic support measures and risk man," Working Papers, Russian Presidential Academy of National Economy and Public Administration, number w202374.
• Mihaela Simionescu, 2023, "Globalization And Pollution In Central And Eastern European Eu Countries," Romanian Journal of Regional Science, Romanian Regional Science Association, volume 17, issue 1, pages 66-82, June.
• Imran Khan & Darshita Fulara Gunwant, 2023, "Is the remittance inflow to the Turkish economy sustainable? A glimpse of the future through the lens of the past," Review of Applied Socio-Economic Research, Pro Global Science Association, volume 25, issue 1, pages 34-51, June.
• Dominic Quint & Fabrizio Venditti, 2023, "The Influence of OPEC+ on Oil Prices: A Quantitative Assessment," The Energy Journal, , volume 44, issue 5, pages 173-186, September, DOI: 10.5547/01956574.44.4.dqui.
• Ari Hyytinen & Petri Rouvinen & Mika Pajarinen & Joosua Virtanen, 2023, "Ex Ante Predictability of Rapid Growth: A Design Science Approach," Entrepreneurship Theory and Practice, , volume 47, issue 6, pages 2465-2493, November, DOI: 10.1177/10422587221128268.
• Mihail Yanchev, 2023, "Uncertainty - Definition and Classification for the Task of Economic Forecasting," Bulgarian Economic Papers, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, number bep-2023-03, Mar, revised Mar 2023.
• Laura Felber & Simon Beyeler, 2023, "Nowcasting economic activity using transaction payments data," Working Papers, Swiss National Bank, number 2023-01.
• Marie-Catherine Bieri, 2023, "Assessing economic sentiment with newspaper text indices: evidence from Switzerland," Working Papers, Swiss National Bank, number 2023-07.
• Joao Felix & Michel Alexandre & Gilberto Tadeu Lima, 2023, "Applying Machine Learning Algorithms to Predict the Size of the Informal Economy," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2023_10, Aug, revised 11 Sep 2023.
• Joao Vitor Matos Goncalves & Michel Alexandre & Gilberto Tadeu Lima, 2023, "ARIMA and LSTM: A Comparative Analysis of Financial Time Series Forecasting," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2023_13, Nov.
• Shyam Kumar Basnet & Ranjan Kumar Ghosh & Mattias Eriksson & Carl-Johan Lagerkvist, 2023, "The distortion in the EU feed market due to import constraints on genetically modified soy," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), volume 11, issue 1, pages 1-26, December, DOI: 10.1186/s40100-023-00290-7.
• Christoph Hanck & Martin C. Arnold, 2023, "Hierarchical Bayes modelling of penalty conversion rates of Bundesliga players," AStA Advances in Statistical Analysis, Springer;German Statistical Society, volume 107, issue 1, pages 177-204, March, DOI: 10.1007/s10182-021-00420-w.
• Konstantinos N. Konstantakis & Panagiotis T. Cheilas & Ioannis G. Melissaropoulos & Panos Xidonas & Panayotis G. Michaelides, 2023, "Supply chains and fake news: a novel input–output neural network approach for the US food sector," Annals of Operations Research, Springer, volume 327, issue 2, pages 779-794, August, DOI: 10.1007/s10479-022-04817-x.
• Georgios Fatouros & Georgios Makridis & Dimitrios Kotios & John Soldatos & Michael Filippakis & Dimosthenis Kyriazis, 2023, "DeepVaR: a framework for portfolio risk assessment leveraging probabilistic deep neural networks," Digital Finance, Springer, volume 5, issue 1, pages 29-56, March, DOI: 10.1007/s42521-022-00050-0.
• Brian Colgan, 2023, "EU-SILC and the potential for synthetic panel estimates," Empirical Economics, Springer, volume 64, issue 3, pages 1247-1280, March, DOI: 10.1007/s00181-022-02277-7.
• Fumio Hayashi & Yuta Tachi, 2023, "Nowcasting Japan’s GDP," Empirical Economics, Springer, volume 64, issue 4, pages 1699-1735, April, DOI: 10.1007/s00181-022-02301-w.
• Jiawen Xu & Pierre Perron, 2023, "Forecasting in the presence of in-sample and out-of-sample breaks," Empirical Economics, Springer, volume 64, issue 6, pages 3001-3035, June, DOI: 10.1007/s00181-022-02346-x.
• Ayman Mnasri & Zouhair Mrabet & Mouyad Alsamara, 2023, "A new quadratic asymmetric error correction model: does size matter?," Empirical Economics, Springer, volume 65, issue 1, pages 33-64, July, DOI: 10.1007/s00181-022-02323-4.
• Rodrigo Mulero & Alfredo Garcia-Hiernaux, 2023, "Forecasting unemployment with Google Trends: age, gender and digital divide," Empirical Economics, Springer, volume 65, issue 2, pages 587-605, August, DOI: 10.1007/s00181-022-02347-w.
• Hwee Kwan Chow & Yijie Fei & Daniel Han, 2023, "Forecasting GDP with many predictors in a small open economy: forecast or information pooling?," Empirical Economics, Springer, volume 65, issue 2, pages 805-829, August, DOI: 10.1007/s00181-022-02356-9.
• Jie Cheng, 2023, "Modelling and forecasting risk dependence and portfolio VaR for cryptocurrencies," Empirical Economics, Springer, volume 65, issue 2, pages 899-924, August, DOI: 10.1007/s00181-023-02360-7.
• Kajal Lahiri & Cheng Yang, 2023, "A tale of two recession-derivative indicators," Empirical Economics, Springer, volume 65, issue 2, pages 925-947, August, DOI: 10.1007/s00181-023-02361-6.
• Weijia Peng & Chun Yao, 2023, "Sector-level equity returns predictability with machine learning and market contagion measure," Empirical Economics, Springer, volume 65, issue 4, pages 1761-1798, October, DOI: 10.1007/s00181-023-02404-y.
• Anna Kiziltan & Mustafa Kiziltan & Shihomi Ara Aksoy & Merih Aydınalp Köksal & Ş. Elçin Tekeli & Nilhan Duran & S. Yeşer Aslanoğlu & Fatma Öztürk & Nazan Özyürek & Pervin Doğan & Ağça Gül Yılmaz & Can, 2023, "Cost–benefit analysis of road-transport policy options to combat air pollution in Turkey," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, volume 25, issue 10, pages 10765-10798, October, DOI: 10.1007/s10668-022-02504-2.
• India Flint & Jasmina Medjedovic & Ewa Drogon O’Flaherty & Elena Alvarez-Baron & Karthinathan Thangavelu & Natasa Savic & Aurelie Meunier & Louise Longworth, 2023, "Mapping analysis to predict SF-6D utilities from health outcomes in people with focal epilepsy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), volume 24, issue 7, pages 1061-1072, September, DOI: 10.1007/s10198-022-01519-w.
• Tiago E. Pratas & Filipe R. Ramos & Lihki Rubio, 2023, "Forecasting bitcoin volatility: exploring the potential of deep learning," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, volume 13, issue 2, pages 285-305, June, DOI: 10.1007/s40822-023-00232-0.
• James Yae & Yang Luo, 2023, "Robust monitoring machine: a machine learning solution for out-of-sample R $$^2$$ 2 -hacking in return predictability monitoring," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 9, issue 1, pages 1-28, December, DOI: 10.1186/s40854-023-00497-z.
• Sacchidananda Mukherjee & Rudrani Bhattacharya, 2023, "Revenue forecasting of corporate income tax (CIT) in India," Indian Economic Review, Springer, volume 58, issue 2, pages 329-349, December, DOI: 10.1007/s41775-023-00203-x.
• Sacchidananda Mukherjee & Rudrani Bhattacharya, 2023, "Correction to: Revenue forecasting of corporate income tax (CIT) in India," Indian Economic Review, Springer, volume 58, issue 2, pages 465-466, December, DOI: 10.1007/s41775-024-00208-0.
• Jan Niederreiter, 2023, "Broadening Economics in the Era of Artificial Intelligence and Experimental Evidence," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), volume 9, issue 1, pages 265-294, March, DOI: 10.1007/s40797-021-00171-2.
• Giorgio Gnecco & Sara Landi & Massimo Riccaboni, 2023, "Can Machines Learn Creativity Needs? An Approach Based on Matrix Completion," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), volume 9, issue 3, pages 1111-1151, November, DOI: 10.1007/s40797-022-00200-8.
• Christian Lohmann & Steffen Möllenhoff & Thorsten Ohliger, 2023, "Nonlinear relationships in bankruptcy prediction and their effect on the profitability of bankruptcy prediction models," Journal of Business Economics, Springer, volume 93, issue 9, pages 1661-1690, November, DOI: 10.1007/s11573-022-01130-8.
• Tobias Götze & Marc Gürtler & Eileen Witowski, 2023, "Forecasting accuracy of machine learning and linear regression: evidence from the secondary CAT bond market," Journal of Business Economics, Springer, volume 93, issue 9, pages 1629-1660, November, DOI: 10.1007/s11573-023-01138-8.
• Kajal Lahiri & Cheng Yang, 2023, "ROC and PRC Approaches to Evaluate Recession Forecasts," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 19, issue 2, pages 119-148, September, DOI: 10.1007/s41549-023-00082-4.
• Satoshi Urasawa, 2023, "The Usefulness of High-Frequency Alternative Data to Obtain Nowcasts for Japan’s GDP: Evidence from Credit Card Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 19, issue 2, pages 191-211, September, DOI: 10.1007/s41549-023-00085-1.
• Klaus Abberger & Michael Graff & Oliver Müller & Boriss Siliverstovs, 2023, "Imputing Monthly Values for Quarterly Time Series: An Application Performed with Swiss Business Cycle Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 19, issue 3, pages 241-273, November, DOI: 10.1007/s41549-023-00088-y.
• Saulius Jokubaitis & Dmitrij Celov, 2023, "Business Cycle Synchronization in the EU: A Regional-Sectoral Look through Soft-Clustering and Wavelet Decomposition," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 19, issue 3, pages 311-371, November, DOI: 10.1007/s41549-023-00090-4.
• Javier Sánchez García & Salvador Cruz Rambaud, 2023, "Volatility spillovers between oil and financial markets during economic and financial crises: A dynamic approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 47, issue 4, pages 1018-1040, December, DOI: 10.1007/s12197-023-09634-x.
• Mihaela Simionescu & Nicolas Schneider, 2023, "Monetary shocks and production network in the G7 countries," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), volume 12, issue 1, pages 1-32, December, DOI: 10.1186/s40008-023-00313-y.
• Paul M. Torrens, 2023, "Agent models of customer journeys on retail high streets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, volume 18, issue 1, pages 87-128, January, DOI: 10.1007/s11403-022-00350-z.
• Mustafa Yurtsever, 2023, "Unemployment rate forecasting: LSTM-GRU hybrid approach," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), volume 57, issue 1, pages 1-9, December, DOI: 10.1186/s12651-023-00345-8.
• Zouheir Mighri & Raouf Jaziri, 2023, "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 21, issue 1, pages 41-97, March, DOI: 10.1007/s40953-022-00331-w.
• Rudrani Bhattacharya & Bornali Bhandari & Sudipto Mundle, 2023, "Nowcasting India’s Quarterly GDP Growth: A Factor-Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 21, issue 1, pages 213-234, March, DOI: 10.1007/s40953-022-00335-6.
• Hyeongwoo Kim & Jisoo Son, 2023, "Forecasting Net Charge-Off Rates of Large U.S. Bank Holding Companies using Macroeconomic Latent Factors," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2023-02, Feb.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2023, "Superior Predictability of American Factors of the Dollar/Won Real Exchange Rate," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2023-05, Jun.
• Hyeongwoo Kim & Jisoo Son, 2023, "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2023-06, Jul.
• Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2023, "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," American Economic Journal: Macroeconomics, American Economic Association, volume 15, issue 3, pages 355-387, July, DOI: 10.1257/mac.20200068.
• Petra E. Todd & Kenneth I. Wolpin, 2023, "The Best of Both Worlds: Combining Randomized Controlled Trials with Structural Modeling," Journal of Economic Literature, American Economic Association, volume 61, issue 1, pages 41-85, March, DOI: 10.1257/jel.20211652.
• Dorel Mihai Paraschiv & Narciz Balasoiu & Souhir Ben-Amor & Raul Cristian Bag, 2023, "Hybridising Neurofuzzy Model the Seasonal Autoregressive Models for Electricity Price Forecasting on Germany’s Spot Market," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, volume 25, issue 63, pages 463-463, April.
• Stanislav Zabojník & Dusan Steinhauser & Viktoria Pestova, 2023, "EU Decarbonisation: Do EU Electricity Costs Harm Export Competitiveness?," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, volume 25, issue 63, pages 522-522, April.
• Alexandra-Nicoleta Ciucu (Durnoi) & Cosmin Alexandru Teodorescu & Vanesa Madalina Vargas & Corina Ioanas, 2023, "Analysing EU Countries Digital Progress Towards Sustainable Development Goals," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, volume 25, issue S17, pages 987-987, November.
• Grzegorz Marcjasz & Tomasz Serafin & Rafal Weron, 2023, "Trading on short-term path forecasts of intraday electricity prices. Part II -- Distributional Deep Neural Networks," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/23/01.
• Cem Çakmaklı & Anıl Divar Çakmaklı & Han Özsöylev, 2023, "Getiri Dağılımı Tahmininin Ekonomik Değeri," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 8, issue 1, pages 40-58, DOI: 10.30784/epfad.1252574.
• Sanjay Kumar SINGH & Shivendra Sanjay SINGH & Vijay Lakshmi SINGH, 2023, "Predicting Adoption of Next Generation Digital Technology Utilizing the Adoption-Diffusion Model Fit: The Case of Mobile Payments Interface in an Emerging Economy," Access Journal, Access Press Publishing House, volume 4, issue 1, pages 130-148, October, DOI: 10.46656/access.2023.4.1(10).
• Aysun Kapucugil Ikiz & Gizem Halil Utma, 2023, "Combined Forecasts of Intermittent Demand for Stock-keeping Units (SKUs)," World Journal of Applied Economics, WERI-World Economic Research Institute, volume 9, issue 1, pages 1-31, June, DOI: 10.22440/wjae.9.1.1.
• Pavithra Manivannan & Geetika Palta & Susan Thomas & Bhargavi Zaveri-Shah, 2023, "Evaluating courts from a litigant's perspective: A project report," Working Papers, xKDR, number 29, Dec.
• Esteban Méndez-Chacón, 2023, "Cash Demand Forecast Models for Costa Rica," Documentos de Trabajo, Banco Central de Costa Rica, number 2301, May.
• Jesus Gonzalo & Jean-Yves Pitarakis, 2023, "Out of Sample Predictability in Predictive Regressions with Many Predictor Candidates," Papers, arXiv.org, number 2302.02866, Feb, revised Oct 2023.
• Florian Huber & Gary Koop, 2023, "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers, arXiv.org, number 2305.16827, May.
• Ali Lashgari, 2023, "Harnessing the Potential of Volatility: Advancing GDP Prediction," Papers, arXiv.org, number 2307.05391, Jun.
• Raffaella Giacomini & Sokbae Lee & Silvia Sarpietro, 2023, "Individual Shrinkage for Random Effects," Papers, arXiv.org, number 2308.01596, Aug, revised Jul 2025.
• David T. Frazier & Ryan Covey & Gael M. Martin & Donald Poskitt, 2023, "Solving the Forecast Combination Puzzle," Papers, arXiv.org, number 2308.05263, Aug.
• Denis Koshelev & Alexey Ponomarenko & Sergei Seleznev, 2023, "Amortized neural networks for agent-based model forecasting," Papers, arXiv.org, number 2308.05753, Aug.
• Kejin Wu & Sayar Karmakar & Rangan Gupta, 2023, "GARCHX-NoVaS: A Model-free Approach to Incorporate Exogenous Variables," Papers, arXiv.org, number 2308.13346, Aug, revised Sep 2024.
• Victor Olkhov, 2023, "Economic Complexity Limits Accuracy of Price Probability Predictions by Gaussian Distributions," Papers, arXiv.org, number 2309.02447, Aug, revised Apr 2024.
• Tae-Hwy Lee & Tao Wang, 2023, "Estimation and Testing of Forecast Rationality with Many Moments," Papers, arXiv.org, number 2309.09481, Sep, revised Jul 2025.
• Jakub Micha'nk'ow & Pawe{l} Sakowski & Robert 'Slepaczuk, 2023, "Mean Absolute Directional Loss as a New Loss Function for Machine Learning Problems in Algorithmic Investment Strategies," Papers, arXiv.org, number 2309.10546, Sep.
• Jakub Micha'nk'ow & Pawe{l} Sakowski & Robert 'Slepaczuk, 2023, "Hedging Properties of Algorithmic Investment Strategies using Long Short-Term Memory and Time Series models for Equity Indices," Papers, arXiv.org, number 2309.15640, Sep.
• Jozef Barunik & Lubos Hanus, 2023, "Learning the Probability Distributions of Day-Ahead Electricity Prices," Papers, arXiv.org, number 2310.02867, Oct, revised Jul 2025.
• Hyungsik Roger Moon & Frank Schorfheide & Boyuan Zhang, 2023, "Bayesian Estimation of Panel Models under Potentially Sparse Heterogeneity," Papers, arXiv.org, number 2310.13785, Oct, revised Feb 2024.
• Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023, "Predictive Density Combination Using a Tree-Based Synthesis Function," Papers, arXiv.org, number 2311.12671, Nov.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023, "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Papers, arXiv.org, number 2312.15494, Dec, revised Jul 2024.
• Franck Ramaharo & Gerzhino Rasolofomanana, 2023, "Nowcasting Madagascar's real GDP using machine learning algorithms," Papers, arXiv.org, number 2401.10255, Dec.
• Adrian NICOLAU, 2023, "The Impact Of Ai On Internal Audit And Accounting Practices," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 67, issue 2, pages 38-56, May.
• Alahverdi, Atefe & Daei-Karimzadeh, Saeed & Ghobadi, Sara, 2023, "Forecasting the Trend of Macroeconomic Variables in Terms of Financial Conditions Index in Iran: TVP-FAVAR Approach (in Persian)," The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی Ùˆ بودجه), Institute for Management and Planning studies, volume 28, issue 3, pages 161-185, December.
• Silvija Vlah Jeric, 2023, "Analysis Of The Financial Performance Of Machine Learning Models For Predicting The Direction Of Changes In Cee And See Stock Market Indices With Different Classification Evaluation Metrics," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, volume 32, issue 2, pages 533-545, december, DOI: 10.17818/EMIP/2023/2.12.
• Taofeek O. AYINDE & Farouq A. ADEYEMI, 2023, "Global Evidence of Oil Supply Shocks and Climate Risk a GARCH-MIDAS Approach," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, volume 4, issue 2, pages 1-7, DOI: 2023/06/13.
• Volodymyr Mozharovskyi & Oleksiy Solomytskyi, 2023, "Assessment And Forecasting Method Of State Stability," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", volume 9, issue 2, DOI: 10.30525/2256-0742/2023-9-2-157-163.
• Johan Brannlund & Helen Lao & Maureen MacIsaac & Jing Yang, 2023, "Predicting Changes in Canadian Housing Markets with Machine Learning," Discussion Papers, Bank of Canada, number 2023-21, Sep, DOI: 10.34989/sdp-2023-21.
• Donald Coletti, 2023, "A Blueprint for the Fourth Generation of Bank of Canada Projection and Policy Analysis Models," Discussion Papers, Bank of Canada, number 2023-23, Oct, DOI: 10.34989/sdp-2023-23.
• Tony Chernis, 2023, "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Staff Working Papers, Bank of Canada, number 23-45, Aug, DOI: 10.34989/swp-2023-45.
• Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023, "Predictive Density Combination Using a Tree-Based Synthesis Function," Staff Working Papers, Bank of Canada, number 23-61, Dec, DOI: 10.34989/swp-2023-61.
• Tomás Marinozzi, 2023, "Forecasting Inflation in Argentina: A Probabilistic Approach," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, volume 1, issue 81, pages 81-110, May.
• Mercedes de Luis & Emilio Rodríguez & Diego Torres, 2023, "Machine learning applied to active fixed-income portfolio management: a Lasso logit approach," Working Papers, Banco de España, number 2324, Sep, DOI: https://doi.org/10.53479/33560.
• Marta Crispino & Vincenzo Mariani, 2023, "A tool to nowcast tourist overnight stays with payment data and complementary indicators," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 746, Feb.
• Salgado Alfredo & Trujillo Alejandro, 2023, "Growth at Risk and Uncertainty: Evidence from Mexico," Working Papers, Banco de México, number 2023-08, Sep.
• Juan Pablo Cote-Barón & Karen L. Pulido-Mahecha & Nicol Valeria Rodríguez-Rodríguez & Carlos D. Rojas-Martínez, 2023, "El ISAE: Un Indicador para Monitorear la Actividad Económica Colombiana en Alta Frecuencia," Borradores de Economia, Banco de la Republica de Colombia, number 1225, Mar, DOI: 10.32468/be.1225.
• Julián Alonso Cárdenas-Cárdenas & Deicy J. Cristiano-Botia & Nicolás Martínez-Cortés, 2023, "Colombian inflation forecast using Long Short-Term Memory approach," Borradores de Economia, Banco de la Republica de Colombia, number 1241, Jun, DOI: 10.32468/be.1241.
• Camilo Granados & Daniel Parra-Amado, 2023, "Estimating the Output Gap After COVID: How to Address Unprecedented Macroeconomic Variations," Borradores de Economia, Banco de la Republica de Colombia, number 1249, Sep, DOI: 10.32468/be.1249.
• Andrey Duván Rincón-Torres & Andrés Felipe Salas-Avila & Juan Manuel Julio-Román, 2023, "Inflation Expectations: Rationality, Disagreement and the Role of the Loss Function in Colombia," Borradores de Economia, Banco de la Republica de Colombia, number 1262, Dec, DOI: 10.32468/be.1262.
• Menzie Chinn & Baptiste Meunier & Sebastian Stumpner, 2023, "Nowcasting World Trade with Machine Learning: a Three-Step Approach," Working papers, Banque de France, number 917.
• Olivier de Bandt & Jean-Charles Bricongne & Julien Denes & Alexandre Dhenin & Annabelle De Gaye & Pierre-Antoine Robert, 2023, "Using the Press to Construct a New Indicator of Inflation Perceptions in France," Working papers, Banque de France, number 921.
• Konstantin Boss & Finja Krueger & Conghan Zheng & Tobias Heidland & Andre Groeger, 2023, "Forecasting Bilateral Refugee Flows with High-dimensional Data and Machine Learning Techniques," Working Papers, Barcelona School of Economics, number 1387, Mar.
• Jonathan Chassot & Michael Creel, 2023, "Constructing Efficient Simulated Moments Using Temporal Convolutional Networks," Working Papers, Barcelona School of Economics, number 1412, Nov.
• Koresh Galil & Ami Hauptman & Rosit Levy Rosenboim, 2023, "Prediction of Corporate Credit Ratings with Machine Learning: Simple Interpretative Models," Working Papers, Ben-Gurion University of the Negev, Department of Economics, number 2308.
• Alexandros Botsis & Christoph Gortz & Plutarchos Sakellaris, 2023, "Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts," Discussion Papers, Department of Economics, University of Birmingham, number 23-06, Jul.
• Anton Votinov & Samvel Lazaryan & Yulia Polshchikova, 2023, "The Impact of the Cross-Sectoral Economic Structure on the Properties of DSGE Models," Russian Journal of Money and Finance, Bank of Russia, volume 82, issue 1, pages 32-54, March.
• Anastasia Petaykina, 2023, "Estimation of Sensitivity of Russian Household Consumption to Permanent and Transitory Income Shocks Using Kalman Filter," Russian Journal of Money and Finance, Bank of Russia, volume 82, issue 3, pages 110-127, September.
• Artur Sharafutdinov, 2023, "Forecasting Russian GDP, Inflation, Interest Rate, and Exchange Rate Using DSGE-VAR Model," Russian Journal of Money and Finance, Bank of Russia, volume 82, issue 3, pages 62-86, September.
• Viacheslav Kramkov, 2023, "Does CPI disaggregation improve inflation forecast accuracy?," Bank of Russia Working Paper Series, Bank of Russia, number wps112, Mar.
• Denis Koshelev & Alexey Ponomarenko & Sergei Seleznev, 2023, "Amortized Neural Networks for Agent-Based Model Forecasting," Bank of Russia Working Paper Series, Bank of Russia, number wps115, Jul.
• Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & Reneé van Eyden, 2023, "Climate risks and U.S. stock‐market tail risks: A forecasting experiment using over a century of data," International Review of Finance, International Review of Finance Ltd., volume 23, issue 2, pages 228-244, June, DOI: 10.1111/irfi.12397.
• Christina Anderl & Guglielmo Maria Caporale, 2023, "Forecasting inflation with a zero lower bound or negative interest rates: Evidence from point and density forecasts," Manchester School, University of Manchester, volume 91, issue 3, pages 171-232, June, DOI: 10.1111/manc.12434.
• Ana Beatriz Galvão & James Mitchell, 2023, "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, volume 85, issue 3, pages 457-481, June, DOI: 10.1111/obes.12542.
• Hai‐Anh H. Dang & Peter F. Lanjouw, 2023, "Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross Sections," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, volume 85, issue 3, pages 599-622, June, DOI: 10.1111/obes.12539.
• Dario Sansone & Anna Zhu, 2023, "Using Machine Learning to Create an Early Warning System for Welfare Recipients," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, volume 85, issue 5, pages 959-992, October, DOI: 10.1111/obes.12550.
• COJOCARIU Irina-Cristina, 2023, "Analysis Of Sports Performances Using Machine Learning And Statistical Models - A General Analysis Of The Literature," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, volume 75, issue 2, pages 34-39, June, DOI: 10.56043/reveco-2023-0013.
• David Kohns & Galina Potjagailo, 2023, "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers, Bank of England, number 1025, Jun.
• Stephen G. Hall & George S. Tavlas & Yongli Wang, 2023, "Forecasting inflation: the use of dynamic factor analysis and nonlinear combinations," Working Papers, Bank of Greece, number 314, Feb, DOI: 10.52903/wp2023314.
• Stavros Degiannakis, 2023, "The D-model for GDP nowcasting," Working Papers, Bank of Greece, number 317, Apr.
• Stavros Degiannakis & George Filis & Grigorios Siourounis & Lorenzo Trapani, 2023, "Superkurtosis," Working Papers, Bank of Greece, number 318, Apr.
• Zacharias Bragoudakis & Ioannis Krompas, 2023, "Greek GDP forecasting using Bayesian multivariate models," Working Papers, Bank of Greece, number 321, Jun, DOI: 10.52903/wp2023321.
• Stavros Degiannakis & Eleftheria Kafousaki, 2023, "Forecasting VIX: The illusion of forecast evaluation criteria," Working Papers, Bank of Greece, number 322, Jun, DOI: 10.52903/wp2022322.
• Liu-Evans Gareth, 2023, "Improving the Estimation and Predictions of Small Time Series Models," Journal of Time Series Econometrics, De Gruyter, volume 15, issue 1, pages 1-26, January, DOI: 10.1515/jtse-2021-0051.
• Doojav Gan-Ochir & Luvsannyam Davaajargal, 2023, "Forecasting Inflation in Mongolia: A Dynamic Model Averaging Approach," Journal of Time Series Econometrics, De Gruyter, volume 15, issue 1, pages 27-48, January, DOI: 10.1515/jtse-2020-0021.
• Abbara Omar & Zevallos Mauricio, 2023, "Estimation and forecasting of long memory stochastic volatility models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 27, issue 1, pages 1-24, February, DOI: 10.1515/snde-2020-0106.
• Martina Jakob & Sebastian Heinrich, 2023, "Measuring Human Capital with Social Media Data and Machine Learning," University of Bern Social Sciences Working Papers, University of Bern, Department of Social Sciences, number 46, May.
• Carole Bonnet & Sandrine Juin & Anne Laferrère, 2023, "Financer la perte d'autonomie : la piste des prêts viagers hypothécaires et de l'assurance obligatoire," Revue d'économie financière, Association d'économie financière, volume 0, issue 4, pages 217-233.
• Congressional Budget Office, 2023, "The Accuracy of CBO’s Budget Projections for Fiscal Year 2022," Reports, Congressional Budget Office, number 58603, Jan.
• Congressional Budget Office, 2023, "An Evaluation of CBO’s Projections of Outlays From 1984 to 2021," Reports, Congressional Budget Office, number 58613, Apr.
• Congressional Budget Office, 2023, "CBO’s Economic Forecasting Record: 2023 Update," Reports, Congressional Budget Office, number 59078, Jun.
• Congressional Budget Office, 2023, "The Accuracy of CBO’s Budget Projections for Fiscal Year 2023," Reports, Congressional Budget Office, number 59682, Dec.
• Byoung Hark Yoo, 2023, "Conditional Forecasting With a Bayesian Vector Autoregression: Working Paper 2023-08," Working Papers, Congressional Budget Office, number 59629, Nov.
• Constantin Bürgi, 2023, "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series, CESifo, number 10203.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023, "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," CESifo Working Paper Series, CESifo, number 10223.
• Robert Lehmann & Ida Wikman, 2023, "Quarterly GDP Estimates for the German States: New Data for Business Cycle Analyses and Long-Run Dynamics," CESifo Working Paper Series, CESifo, number 10280.
• Robert Lehmann, 2023, "READ-GER: Introducing German Real-Time Regional Accounts Data for Revision Analysis and Nowcasting," CESifo Working Paper Series, CESifo, number 10315.
• Kajal Lahiri & Cheng Yang, 2023, "ROC and PRC Approaches to Evaluate Recession Forecasts," CESifo Working Paper Series, CESifo, number 10449.
• Friederike Fourné & Robert Lehmann, 2023, "From Shopping to Statistics: Tracking and Nowcasting Private Consumption Expenditures in Real-Time," CESifo Working Paper Series, CESifo, number 10764.
• Sören Blomquist, 2023, "Evaluating the Discrete Choice and BN Methods to Estimate Labor Supply Functions," CESifo Working Paper Series, CESifo, number 10827.
• Benjamin Born & Zeno Enders & Manuel Menkhoff & Gernot J. Müller & Knut Niemann, 2023, "Firm Expectations and News: Micro v Macro," ifo Working Paper Series, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 400.
• Charles Kenny & Zack Gehan, 2023, "Scenarios for Future Global Growth to 2050," Working Papers, Center for Global Development, number 634, Mar.
• Bryan Kelly & Semyon Malamud & Mohammad Pourmohammadi & Fabio Trojani, 2023, "Universal Portfolio Shrinkage," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 23-119, Dec.
• Markus Leippold & Hanlin Yang, 2023, "Mixed-Frequency Predictive Regressions with Parameter Learning," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 23-39, Mar, revised Jun 2023.
• Michal Andrle & Jan Bruha, 2023, "A Sparse Kalman Filter: A Non-Recursive Approach," Working Papers, Czech National Bank, Research and Statistics Department, number 2023/13, Nov.
• Miguel Sebastiano Chalup Calmotti & Luis Fernando Escobar Caba, 2023, "Efectos macroeconómicos de la política fiscal durante la crisis del Covid-19: evidencia de Bolivia a nivel regional," Revista de Economía del Rosario, Universidad del Rosario, volume 26, issue 1, pages 1-39.
• Seydyss Garay Rodríguez & Pavel Vidal-Alejandro & Julieth Cerón-Ordoñez, 2023, "El monitoreo del sector de la construcción en el Valle del Cauca," Apuntes del Cenes, Universidad Pedagógica y Tecnológica de Colombia, volume 42, issue 75, pages 237-271.
• Oscar López-Solís & Alexander Fernando Haro Sarango & Ana Córdova-Pacheco & Juan Pérez-Briceño, 2023, "El teorema Modigliani-Miller: un análisis desde la estructura de capital mediante modelos Data Mining en pymes del sector comercio," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, volume 15, issue 1, pages 45-66.
• Emile Cammeraat & Brinn Hekkelman & Pim Kastelein & Suzanne Vissers, 2023, "Predictability and (co-)incidence of labor and health shocks," CPB Discussion Paper, CPB Netherlands Bureau for Economic Policy Analysis, number 453, Dec, DOI: 10.34932/n1bs-qm11.
• Ahrens, Maximilian & Erdemlioglu, Deniz & Mcmahon, Michael & Neely, Christopher J & Yang, Xiye, 2023, "Mind Your Language: Market Responses to Central Bank Speeches," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18191, Jun.
• Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano, 2023, "Forecasting US Inflation Using Bayesian Nonparametric Models," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18244, Jun.
• Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023, "Density forecasts of inflation: a quantile regression forest approach," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18298, Jul.
• Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2023, "Labour at risk," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18432, Sep.
• Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano & Pfarrhofer, Michael, 2023, "Investigating Growth-at-Risk Using a Multicountry Non-parametric Quantile Factor Model," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18549, Oct.
• Moon, Hyungsik Roger & Schorfheide, Frank & Zhang, Boyuan, 2023, "Bayesian Estimation of Panel Models under Potentially Sparse Heterogeneity," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18560, Oct.
• Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023, "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers, Center for Quantitative Economics (CQE), University of Muenster, number 10523, Jun.
• Verena Monschang & Mark Trede & Bernd Wilfling, 2023, "Multi-horizon uniform superior predictive ability revisited: A size-exploiting and consistent test," CQE Working Papers, Center for Quantitative Economics (CQE), University of Muenster, number 10623, Nov.
• Mohana Mondal & Michael P. Cameron & Jacques Poot, 2023, "Towards a Dynamic Spatial Microsimulation Model for Projecting Auckland’s Spatial Distribution of Ethnic Groups," RFBerlin Discussion Paper Series, ROCKWOOL Foundation Berlin (RFBerlin), number 2303, Feb.
• Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2023, "Deep Dynamic Factor Models," Working Papers, Center for Research in Economics and Statistics, number 2023-08, May.
• Gerard J. van den Berg & Max Kunaschk & Julia Lang & Gesine Stephan & Arne Uhlendorf, 2023, "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," Working Papers, Center for Research in Economics and Statistics, number 2023-09, Aug.
• Marín Díazaraque, Juan Miguel & Lopes Moreira da Veiga, María Helena, 2023, "Shock-triggered asymmetric response stochastic volatility," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 36569, Feb.
• González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023, "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 37968, Jul.
• Simon SCHNÜRCH & Torsten KLEINOW & Andreas WAGNER, 2023, "Accounting for COVID-19-type shocks in mortality modeling: a comparative study," JODE - Journal of Demographic Economics, Cambridge University Press, volume 89, issue 3, pages 483-512, September, DOI: 10.1017/dem.2023.9.
• Kamil Dawid Grzebien & María Jesús Segovia-Vargas, 2023, "Predicción del riesgo de impago en los préstamos P2P," Revista de Economía y Finanzas (REyF), Asociación Cuadernos de Economía, volume 1, issue 2, pages 175-188, Mayo.
• Michael Sampson, 2023, "Learning About New Eras," Annals of Economics and Finance, Society for AEF, volume 24, issue 1, pages 1-12, May.
• Lee, Ji Hyung & Shin, Youngki, 2023, "Complete Subset Averaging For Quantile Regressions," Econometric Theory, Cambridge University Press, volume 39, issue 1, pages 146-188, February.
• Micocci, Francesca & Rungi, Armando, 2023, "Predicting Exporters with Machine Learning," World Trade Review, Cambridge University Press, volume 22, issue 5, pages 584-607, December.
• Sailesh BHAGHOE & Gavin OOFT, 2023, "Nowcasting quarterly GDP growth in Suriname with factor-MIDAS and mixed-frequency VAR models," Journal of Economics and Political Economy, EconSciences Journals, volume 10, issue 1, pages 1-18, March.
• Pablo Garcia & Pascal Jacquinot & ÄŒrt LenarÄ iÄ & Matija Lozej & Kostas Mavromatis, 2023, "Global models for a global pandemic: the impact of COVID-19 on small euro area economies," Working Papers, DNB, number 782, Jun.
• Benjamin Monnery & François-Charles Wolff, 2023, "Is participatory democracy in line with social protest? Evidence from the French Yellow Vests movement," EconomiX Working Papers, University of Paris Nanterre, EconomiX, number 2023-23.
• Christopher E.S. WARBURTON & Jared PEMBERTON, 2023, "Volatile Financial Conditions, Asset Prices, and Investment Decisions: Analysis of daily data of DJIA and S&P500, from January to April of 2022," Applied Econometrics and International Development, Euro-American Association of Economic Development, volume 23, issue 1, pages 101-124.
• Germann, Maximilian & Kusmierczyk, Piotr & Puyo, Christelle, 2023, "Results of the 2022 climate risk stress test of the Eurosystem balance sheet," Economic Bulletin Boxes, European Central Bank, volume 2.
• Burban, Valentin & Schupp, Fabian, 2023, "Backcasting real interest rates and inflation expectations – combining market-based measures with historical data for related variables," Economic Bulletin Boxes, European Central Bank, volume 2.
• Emambakhsh, Tina & Fuchs, Maximilian & Kördel, Simon & Kouratzoglou, Charalampos & Lelli, Chiara & Pizzeghello, Riccardo & Salleo, Carmelo & Spaggiari, Martina, 2023, "The Road to Paris: stress testing the transition towards a net-zero economy," Occasional Paper Series, European Central Bank, number 328, Sep.
• Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023, "Forecasting euro area inflation with machine-learning models," Research Bulletin, European Central Bank, volume 112.
• Warne, Anders, 2023, "DSGE model forecasting: rational expectations vs. adaptive learning," Working Paper Series, European Central Bank, number 2768, Jan.
• Martínez, Carlos Cañizares & de Bondt, Gabe & Gieseck, Arne, 2023, "Forecasting housing investment," Working Paper Series, European Central Bank, number 2807, Apr.
• Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023, "Nowcasting employment in the euro area," Working Paper Series, European Central Bank, number 2815, May.
• Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023, "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series, European Central Bank, number 2830, Jul.
• Chinn, Menzie D. & Meunier, Baptiste & Stumpner, Sebastian, 2023, "Nowcasting world trade with machine learning: a three-step approach," Working Paper Series, European Central Bank, number 2836, Aug.
• Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2023, "Labour at risk," Working Paper Series, European Central Bank, number 2840, Aug.
• Chavleishvili, Sulkhan & Kremer, Manfred, 2023, "Measuring systemic financial stress and its risks for growth," Working Paper Series, European Central Bank, number 2842, Aug.
• Khondokar Jilhajj, 2023, "Forecasting Lending Interest Rate and Deposit Interest Rate of Bangladesh Using the Autoregressive Integrated Moving Average Model," International Journal of Economics and Financial Issues, Econjournals, volume 13, issue 3, pages 169-177, May.
• William Djamfa Mbiakop & Hlalefang Khobai & Djomo Choumbou Raoul Fani, 2023, "Response of Agriculture Production to Change of Foreign Direct Investment and Public Agriculture Expenditure in South Africa: A Monte Carlo Simulation Analysis," International Journal of Economics and Financial Issues, Econjournals, volume 13, issue 6, pages 1-7, November.
• Amine Mounir, 2023, "Crude Oil Price Movements between Fundamental and Uncertainty: Evidence from Frequency Causality Tests," International Journal of Energy Economics and Policy, Econjournals, volume 13, issue 3, pages 428-433, May.
• Mustofa Usman & M. Komarudin & Nurhanurawati Nurhanurawati & Edwin Russel & Ahmad Sidiq & Warsono Warsono & F. A.M Elfaki, 2023, "Dynamic Modeling and Analysis of Some Energy Companies of Indonesia Over the Year 2018 to 2022 By Using VAR(p)-CCC GARCH(r,s) Model: -," International Journal of Energy Economics and Policy, Econjournals, volume 13, issue 4, pages 542-554, July.
• Samuel John Parreno, 2023, "Forecasting the Total Non-coincidental Monthly System Peak Demand in the Philippines: A Comparison of Seasonal Autoregressive Integrated Moving Average Models and Artificial Neural Networks," International Journal of Energy Economics and Policy, Econjournals, volume 13, issue 5, pages 544-552, September.
• Abdulrazak Nur Mohamed & Idiris Sid Ali Mohamed, 2023, "Precious Metals and Oil Price Dynamics," International Journal of Energy Economics and Policy, Econjournals, volume 13, issue 6, pages 119-128, November.
• Hamdy Ahmad Aly Alhendawy & Mohammed Galal Abdallah Mostafa & Mohamed Ibrahim Elgohari & Ibrahim Abdalla Abdelraouf Mohamed & Nabil Medhat Arafat Mahmoud & Mohamed Ahmed Mohamed Mater, 2023, "Determinants of Renewable Energy Production in Egypt New Approach: Machine Learning Algorithms," International Journal of Energy Economics and Policy, Econjournals, volume 13, issue 6, pages 679-689, November.
• Kukacka, Jiri & Sacht, Stephen, 2023, "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, volume 146, issue C, DOI: 10.1016/j.jedc.2022.104585.
• Mungo, Luca & Lafond, François & Astudillo-Estévez, Pablo & Farmer, J. Doyne, 2023, "Reconstructing production networks using machine learning," Journal of Economic Dynamics and Control, Elsevier, volume 148, issue C, DOI: 10.1016/j.jedc.2023.104607.
• Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023, "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, volume 149, issue C, DOI: 10.1016/j.jedc.2023.104636.
• Shintani, Mototsugu & Ueda, Kozo, 2023, "Identifying the source of information rigidities in the expectations formation process," Journal of Economic Dynamics and Control, Elsevier, volume 150, issue C, DOI: 10.1016/j.jedc.2023.104653.
• Ahn, Hie Joo, 2023, "Duration structure of unemployment hazards and the trend unemployment rate," Journal of Economic Dynamics and Control, Elsevier, volume 151, issue C, DOI: 10.1016/j.jedc.2023.104664.
• Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023, "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, volume 157, issue C, DOI: 10.1016/j.jedc.2023.104762.
• Tsuchiya, Yoichi, 2023, "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, volume 77, issue C, pages 64-84, DOI: 10.1016/j.eap.2022.10.017.
• Kawamoto, Takuji & Nakazawa, Takashi & Kishaba, Yui & Matsumura, Kohei & Nakajima, Jouchi, 2023, "Estimating the macroeconomic effects of Japan’s expansionary monetary policy under Quantitative and Qualitative Monetary Easing during 2013–2020," Economic Analysis and Policy, Elsevier, volume 78, issue C, pages 208-224, DOI: 10.1016/j.eap.2023.03.007.
• Sen, Anindya & Baker, John David & Zhang, Qihuang & Agarwal, Rishav Raj & Lam, Jean-Paul, 2023, "Do more stringent policies reduce daily COVID-19 case counts? Evidence from Canadian provinces," Economic Analysis and Policy, Elsevier, volume 78, issue C, pages 225-242, DOI: 10.1016/j.eap.2023.03.006.
• Shah, Sayar Ahmad & Garg, Bhavesh, 2023, "Identifying efficient policy mix under different targeting regimes: A tale of two crises," Economic Analysis and Policy, Elsevier, volume 78, issue C, pages 975-994, DOI: 10.1016/j.eap.2023.04.019.
• Zhang, Li & Li, Yan & Yu, Sixin & Wang, Lu, 2023, "Risk transmission of El Niño-induced climate change to regional Green Economy Index," Economic Analysis and Policy, Elsevier, volume 79, issue C, pages 860-872, DOI: 10.1016/j.eap.2023.07.006.
• Peng, Lijuan & Pan, Zhigang & Liang, Chao & Umar, Muhammad, 2023, "Exchange rate volatility predictability: A new insight from climate policy uncertainty," Economic Analysis and Policy, Elsevier, volume 80, issue C, pages 688-700, DOI: 10.1016/j.eap.2023.09.017.