Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2024

• Berrisch, Jonathan & Ziel, Florian, 2024, "Multivariate probabilistic CRPS learning with an application to day-ahead electricity prices," International Journal of Forecasting, Elsevier, volume 40, issue 4, pages 1568-1586, DOI: 10.1016/j.ijforecast.2024.01.005.
• Gibbs, Christopher G. & Vasnev, Andrey L., 2024, "Conditionally optimal weights and forward-looking approaches to combining forecasts," International Journal of Forecasting, Elsevier, volume 40, issue 4, pages 1734-1751, DOI: 10.1016/j.ijforecast.2024.03.002.
• Fritzsch, Simon & Timphus, Maike & Weiß, Gregor, 2024, "Marginals versus copulas: Which account for more model risk in multivariate risk forecasting?," Journal of Banking & Finance, Elsevier, volume 158, issue C, DOI: 10.1016/j.jbankfin.2023.107035.
• Cheng, Hang & Guo, Hui & Shi, Yongdong, 2024, "Multifactor conditional equity premium model: Evidence from China's stock market," Journal of Banking & Finance, Elsevier, volume 161, issue C, DOI: 10.1016/j.jbankfin.2024.107117.
• Cao, Cong, 2024, "How to better predict the effect of urban traffic and weather on air pollution? Norwegian evidence from machine learning approaches," Journal of Economic Behavior & Organization, Elsevier, volume 221, issue C, pages 544-569, DOI: 10.1016/j.jebo.2024.03.018.
• Zhang, Li & Liang, Chao & Huynh, Luu Duc Toan & Wang, Lu & Damette, Olivier, 2024, "Measuring the impact of climate risk on renewable energy stock volatility: A case study of G20 economies," Journal of Economic Behavior & Organization, Elsevier, volume 223, issue C, pages 168-184, DOI: 10.1016/j.jebo.2024.05.005.
• Clements, Michael P., 2024, "Survey expectations and adjustments for multiple testing," Journal of Economic Behavior & Organization, Elsevier, volume 224, issue C, pages 338-354, DOI: 10.1016/j.jebo.2024.06.009.
• Qiu, Yajie & Deschamps, Bruno & Liu, Xiaoquan, 2024, "Uncertainty and macroeconomic forecasts: Evidence from survey data," Journal of Economic Behavior & Organization, Elsevier, volume 224, issue C, pages 463-480, DOI: 10.1016/j.jebo.2024.06.008.
• Xiao, Wei, 2024, "Initial anchors and limited information in learning-to-forecast experiments," Journal of Economic Behavior & Organization, Elsevier, volume 225, issue C, pages 192-227, DOI: 10.1016/j.jebo.2024.06.038.
• Chen, Heng & Li, Xu & Pei, Guangyu & Xin, Qian, 2024, "Heterogeneous overreaction in expectation formation: Evidence and theory," Journal of Economic Theory, Elsevier, volume 218, issue C, DOI: 10.1016/j.jet.2024.105839.
• Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan & Li, Yan, 2024, "The out-of-sample performance of carry trades," Journal of International Money and Finance, Elsevier, volume 143, issue C, DOI: 10.1016/j.jimonfin.2024.103042.
• Hecq, Alain & Issler, João Victor & Voisin, Elisa, 2024, "A short term credibility index for central banks under inflation targeting: An application to Brazil," Journal of International Money and Finance, Elsevier, volume 143, issue C, DOI: 10.1016/j.jimonfin.2024.103057.
• Bei, Zeyun & Lin, Juan & Zhou, Yinggang, 2024, "No safe haven, only diversification and contagion — Intraday evidence around the COVID-19 pandemic," Journal of International Money and Finance, Elsevier, volume 143, issue C, DOI: 10.1016/j.jimonfin.2024.103069.
• Conlon, Thomas & Cotter, John & Eyiah-Donkor, Emmanuel, 2024, "Forecasting the price of oil: A cautionary note," Journal of Commodity Markets, Elsevier, volume 33, issue C, DOI: 10.1016/j.jcomm.2023.100378.
• Lazar, Emese & Pan, Jingqi & Wang, Shixuan, 2024, "On the estimation of Value-at-Risk and Expected Shortfall at extreme levels," Journal of Commodity Markets, Elsevier, volume 34, issue C, DOI: 10.1016/j.jcomm.2024.100391.
• Ma, Tian & Li, Ganghui & Zhang, Huajing, 2024, "Stock return predictability using economic narrative: Evidence from energy sectors," Journal of Commodity Markets, Elsevier, volume 35, issue C, DOI: 10.1016/j.jcomm.2024.100418.
• Li, Kaixin & Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie, 2024, "Forecasting crude oil returns with oil-related industry ESG indices," Journal of Commodity Markets, Elsevier, volume 36, issue C, DOI: 10.1016/j.jcomm.2024.100444.
• Cavicchioli, Maddalena, 2024, "A matrix unified framework for deriving various impulse responses in Markov switching VAR: Evidence from oil and gas markets," The Journal of Economic Asymmetries, Elsevier, volume 29, issue C, DOI: 10.1016/j.jeca.2023.e00349.
• Alves, Renan Santos & Palma, Andreza A., 2024, "The effectiveness of fiscal policy in Brazil through the MIDAS Lens," Journal of Policy Modeling, Elsevier, volume 46, issue 1, pages 113-128, DOI: 10.1016/j.jpolmod.2023.10.004.
• Sen, Abhibasu & Dutta Choudhury, Karabi, 2024, "Forecasting the Crude Oil prices for last four decades using deep learning approach," Resources Policy, Elsevier, volume 88, issue C, DOI: 10.1016/j.resourpol.2023.104438.
• Simionescu, Mihaela & Cifuentes-Faura, Javier, 2024, "The digital economy and energy poverty in Central and Eastern Europe," Utilities Policy, Elsevier, volume 91, issue C, DOI: 10.1016/j.jup.2024.101841.
• Bolivar, Osmar, 2024, "GDP nowcasting: A machine learning and remote sensing data-based approach for Bolivia," Latin American Journal of Central Banking (previously Monetaria), Elsevier, volume 5, issue 3, DOI: 10.1016/j.latcb.2024.100126.
• Durand, Luigi & Fornero, Jorge Alberto, 2024, "Estimating the output gap in times of COVID-19," Latin American Journal of Central Banking (previously Monetaria), Elsevier, volume 5, issue 4, DOI: 10.1016/j.latcb.2024.100129.
• Han, Zhao, 2024, "Asymmetric information and misaligned inflation expectations," Journal of Monetary Economics, Elsevier, volume 143, issue C, DOI: 10.1016/j.jmoneco.2023.10.010.
• Gazzani, Andrea & Venditti, Fabrizio & Veronese, Giovanni, 2024, "Oil price shocks in real time," Journal of Monetary Economics, Elsevier, volume 144, issue C, DOI: 10.1016/j.jmoneco.2023.12.005.
• López-Salido, David & Loria, Francesca, 2024, "Inflation at risk," Journal of Monetary Economics, Elsevier, volume 145, issue S, DOI: 10.1016/j.jmoneco.2024.103570.
• Tong, Bin & Diao, Xundi & Li, Xiaoping, 2024, "Forecasting VaRs via hybrid EVT with normal and non-normal filters: A comparative analysis from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, volume 83, issue C, DOI: 10.1016/j.pacfin.2024.102271.
• Pan, Ging-Ginq & Shiu, Yung-Ming & Wu, Tu-Cheng, 2024, "Extrapolation and option-implied kurtosis in volatility forecasting," Pacific-Basin Finance Journal, Elsevier, volume 84, issue C, DOI: 10.1016/j.pacfin.2024.102286.
• Lu, Yao & Zhao, Zhihui & Tian, Yuan & Zhan, Minghua, 2024, "How does the economic structure break change the forecast effect of money and credit on output? Evidence based on machine learning algorithms," Pacific-Basin Finance Journal, Elsevier, volume 84, issue C, DOI: 10.1016/j.pacfin.2024.102325.
• Huang, Xiaowei & He, Chenyu & Zhang, Man, 2024, "Economic policy uncertainty and capital flows' tail risk in China," Pacific-Basin Finance Journal, Elsevier, volume 85, issue C, DOI: 10.1016/j.pacfin.2024.102370.
• Huynh, Tran & Uebelmesser, Silke, 2024, "Early warning models for systemic banking crises: Can political indicators improve prediction?," European Journal of Political Economy, Elsevier, volume 81, issue C, DOI: 10.1016/j.ejpoleco.2023.102484.
• Christensen, Peter & Francisco, Paul & Myers, Erica & Shao, Hansen & Souza, Mateus, 2024, "Energy efficiency can deliver for climate policy: Evidence from machine learning-based targeting," Journal of Public Economics, Elsevier, volume 234, issue C, DOI: 10.1016/j.jpubeco.2024.105098.
• Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Bouri, Elie, 2024, "Energy-related uncertainty and international stock market volatility," The Quarterly Review of Economics and Finance, Elsevier, volume 95, issue C, pages 280-293, DOI: 10.1016/j.qref.2024.04.005.
• Wang, Lu & Wang, Xing & Liang, Chao, 2024, "Natural gas volatility prediction via a novel combination of GARCH-MIDAS and one-class SVM," The Quarterly Review of Economics and Finance, Elsevier, volume 98, issue C, DOI: 10.1016/j.qref.2024.101927.
• du Plessis, Emile, 2024, "Reading between the lines: Quantitative text analysis of banking crises," Research in Economics, Elsevier, volume 78, issue 4, DOI: 10.1016/j.rie.2024.101000.
• Mati, Sagiru & Baita, Abubakar Jamilu & Ismael, Goran Yousif & Abdullahi, Salisu Garba & Samour, Ahmed & Ozsahin, Dilber Uzun, 2024, "Enhancing CO2 emissions prediction in Africa: A novel approach integrating enviroeconomic factors and nature-inspired neural network in the presence of unit root," Renewable Energy, Elsevier, volume 237, issue PA, DOI: 10.1016/j.renene.2024.121561.
• Westphal, Igor, 2024, "The effects of reducing renewable power intermittency through portfolio diversification," Renewable and Sustainable Energy Reviews, Elsevier, volume 197, issue C, DOI: 10.1016/j.rser.2024.114415.
• Manner, Hans & Rodríguez, Gabriel & Stöckler, Florian, 2024, "A changepoint analysis of exchange rate and commodity price risks for Latin American stock markets," International Review of Economics & Finance, Elsevier, volume 89, issue PA, pages 1385-1403, DOI: 10.1016/j.iref.2023.08.021.
• Guo, Yanfeng & Zhao, Huanyu, 2024, "Volatility spillovers between oil and coal prices and its implications for energy portfolio management in China," International Review of Economics & Finance, Elsevier, volume 89, issue PB, pages 446-457, DOI: 10.1016/j.iref.2023.10.004.
• Luo, Tao & Sun, Huaping & Zhang, Lixia & Bai, Jiancheng, 2024, "Do the dynamics of macroeconomic attention drive the yen/dollar exchange market volatility?," International Review of Economics & Finance, Elsevier, volume 89, issue PB, pages 597-611, DOI: 10.1016/j.iref.2023.09.012.
• Li, Xiaodan & Gong, Xue & Ge, Futing & Huang, Jingjing, 2024, "Forecasting stock volatility using pseudo-out-of-sample information," International Review of Economics & Finance, Elsevier, volume 90, issue C, pages 123-135, DOI: 10.1016/j.iref.2023.11.014.
• Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024, "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, volume 93, issue PB, pages 673-711, DOI: 10.1016/j.iref.2024.05.008.
• Peng, Lijuan & Liang, Chao & Yang, Baoying & Wang, Lu, 2024, "Crude oil volatility forecasting: Insights from a novel time-varying parameter GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, volume 94, issue C, DOI: 10.1016/j.iref.2024.103413.
• Patra, Saswat, 2024, "An empirical analysis of the volume-volatility nexus in crude oil markets under structural breaks: Implications for forecasting," International Review of Economics & Finance, Elsevier, volume 94, issue C, DOI: 10.1016/j.iref.2024.103434.
• He, Mengxi & Wen, Danyan & Xing, Lu & Zhang, Yaojie, 2024, "Industry volatility concentration and the predictability of aggregate stock market volatility," International Review of Economics & Finance, Elsevier, volume 95, issue C, DOI: 10.1016/j.iref.2024.103488.
• Zhang, Xincheng & Wu, Shaojiang, 2024, "Natural resources and sustainable development: Evidence from the dynamic correlation between crude oil and gold market," International Review of Economics & Finance, Elsevier, volume 96, issue PB, DOI: 10.1016/j.iref.2024.103665.
• Semenov, Andrei, 2024, "Overreaction and underreaction to new information and the directional forecast of exchange rates," International Review of Economics & Finance, Elsevier, volume 96, issue PC, DOI: 10.1016/j.iref.2024.103676.
• Li, Zhe & Liang, Shuguang & Pan, Xianyou & Pang, Meng, 2024, "Credit risk prediction based on loan profit: Evidence from Chinese SMEs," Research in International Business and Finance, Elsevier, volume 67, issue PA, DOI: 10.1016/j.ribaf.2023.102155.
• Yousaf, Imran & Arfaoui, Nadia & Gubareva, Mariya, 2024, "Spillovers and hedging effectiveness between oil and US equity sectors: Evidence from the COVID pre- and post-vaccination phases," Research in International Business and Finance, Elsevier, volume 69, issue C, DOI: 10.1016/j.ribaf.2023.102204.
• Pan, Zhigang & Bai, Zhihong & Xing, Xiaochao & Wang, Zhufeng, 2024, "US inflation and global commodity prices: Asymmetric interdependence," Research in International Business and Finance, Elsevier, volume 69, issue C, DOI: 10.1016/j.ribaf.2024.102245.
• Lohmann, Christian & Ohliger, Thorsten, 2024, "Predicting the cure of a defaulted company: Nonlinear relationships between loan-related variables and the cure probability," Research in International Business and Finance, Elsevier, volume 70, issue PB, DOI: 10.1016/j.ribaf.2024.102395.
• Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2024, "Financial stress and realized volatility: The case of agricultural commodities," Research in International Business and Finance, Elsevier, volume 71, issue C, DOI: 10.1016/j.ribaf.2024.102442.
• Belhadj, Besma, 2024, "Fuzzy multiple regressions for Cross-Section and Panel data," Socio-Economic Planning Sciences, Elsevier, volume 91, issue C, DOI: 10.1016/j.seps.2023.101761.
• Citterio, Alberto, 2024, "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, volume 92, issue C, DOI: 10.1016/j.seps.2024.101818.
• Battiston, Pietro & Gamba, Simona & Santoro, Alessandro, 2024, "Machine learning and the optimization of prediction-based policies," Technological Forecasting and Social Change, Elsevier, volume 199, issue C, DOI: 10.1016/j.techfore.2023.123080.
• Ghosh, Indranil & Jana, Rabin K., 2024, "Clean energy stock price forecasting and response to macroeconomic variables: A novel framework using Facebook's Prophet, NeuralProphet and explainable AI," Technological Forecasting and Social Change, Elsevier, volume 200, issue C, DOI: 10.1016/j.techfore.2023.123148.
• Yang, Jinyu & Dong, Dayong & Liang, Chao, 2024, "Climate policy uncertainty and the U.S. economic cycle," Technological Forecasting and Social Change, Elsevier, volume 202, issue C, DOI: 10.1016/j.techfore.2024.123344.
• Zhang, Xincheng, 2024, "Country-level energy-related uncertainties and stock market returns: Insights from the U.S. and China," Technological Forecasting and Social Change, Elsevier, volume 204, issue C, DOI: 10.1016/j.techfore.2024.123437.
• Saâdaoui, Foued & Rabbouch, Hana, 2024, "Financial forecasting improvement with LSTM-ARFIMA hybrid models and non-Gaussian distributions," Technological Forecasting and Social Change, Elsevier, volume 206, issue C, DOI: 10.1016/j.techfore.2024.123539.
• Lamperti, Fabio, 2024, "Unlocking machine learning for social sciences: The case for identifying Industry 4.0 adoption across business restructuring events," Technological Forecasting and Social Change, Elsevier, volume 207, issue C, DOI: 10.1016/j.techfore.2024.123627.
• Alexandros Botsis & Christoph Gortz & Plutarchos Sakellaris, 2024, "Quantifying Qualitative Survey Data with Panel Data Structure," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-21, Mar.
• Matthew Agarwala & Matt Burke & Jennifer Doherty-Bigara & Patrycja Klusak & Kamiar Mohaddes, 2024, "Climate Change and Sovereign Risk: A Regional Analysis for the Caribbean," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-26, Apr.
• Roshen Fernando, 2024, "Global Economic Impacts of Physical Climate Risks on Agriculture and Energy," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-37, Jun.
• Roshen Fernando, 2024, "Impact of Physical Climate Risks on Financial Assets," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-38, Jun.
• Roshen Fernando & Warwick McKibbin, 2024, "Global Economic Impacts of Antimicrobial Resistance," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-41, Jun.
• Leo Krippner, 2024, "Applications of Vector Autoregressions in Their Scalar Autoregressive Component Form," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-71, Dec.
• Matt Burke & Matthew Agarwala & Patrycja Klusak & Kamiar Mohaddes, 2024, "Climate Policy and Sovereign Debt: The Impact of Transition Scenarios on Sovereign Creditworthiness," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-73, Dec.
• Kirtac, Kemal & Germano, Guido, 2024, "Sentiment trading with large language models," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 122592, Apr.
• Kumar, Utkarsh & Ahmad, Wasim & Uddin, Gazi Salah, 2024, "Bayesian Markov switching model for BRICS currencies' exchange rates," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 122816, Sep.
• Simionescu, Mihaela & Schneider, Nicolas & Gavurova, Beata, 2024, "A Bayesian vector-autoregressive application with time-varying parameters on the monetary shocks-production network nexus," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 125580, Sep.
• Massimiliano Marcellino & Michael Pfarrhofer, 2024, "Bayesian nonparametric methods for macroeconomic forecasting," Chapters, Edward Elgar Publishing, chapter 5, in: Michael P. Clements & Ana Beatriz Galvão, "Handbook of Research Methods and Applications in Macroeconomic Forecasting".
• Francesco Furno & Domenico Giannone, 2024, "Nowcasting recession risk," Chapters, Edward Elgar Publishing, chapter 7, in: Michael P. Clements & Ana Beatriz Galvão, "Handbook of Research Methods and Applications in Macroeconomic Forecasting".
• Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2024, "Lessons from nowcasting GDP across the world," Chapters, Edward Elgar Publishing, chapter 8, in: Michael P. Clements & Ana Beatriz Galvão, "Handbook of Research Methods and Applications in Macroeconomic Forecasting".
• Christine Amsler & Robert James & Artem Prokhorov & Peter Schmidt, 2024, "Improving Predictions of Technical Inefficiency," Advances in Econometrics, Emerald Group Publishing Limited, "Essays in Honor of Subal Kumbhakar", DOI: 10.1108/S0731-905320240000046011.
• Kwame Asiam Addey & John Baptist D. Jatoe, 2024, "Implications of crop yield distributions for multiperil crop insurance rating in Ghana: a lasso model application," Agricultural Finance Review, Emerald Group Publishing Limited, volume 84, issue 2/3, pages 246-265, August, DOI: 10.1108/AFR-05-2024-0078.
• Siddhartha S. Bora & Ani L. Katchova, 2024, "Multi-step commodity forecasts using deep learning," Agricultural Finance Review, Emerald Group Publishing Limited, volume 84, issue 4/5, pages 269-296, September, DOI: 10.1108/AFR-08-2023-0105.
• Bingzi Jin & Xiaojie Xu, 2024, "Predicting wholesale edible oil prices through Gaussian process regressions tuned with Bayesian optimization and cross-validation," Asian Journal of Economics and Banking, Emerald Group Publishing Limited, volume 9, issue 1, pages 64-82, December, DOI: 10.1108/AJEB-06-2024-0070.
• Ehsanul Hassan & Muhammad Awais-E-Yazdan & Ramona Birau & Peter Wanke & Yong Aaron Tan, 2024, "Predicting financial distress in non-financial sector of Pakistan using PCA and logit," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, volume 17, issue 3, pages 485-508, June, DOI: 10.1108/IMEFM-10-2023-0404.
• Vighneswara Swamy & Vijayakumar Narayanamurthy, 2024, "Are private banks more sensitive to changes in reserve requirements? Evidence from an emerging market," Journal of Economics, Finance and Administrative Science, Emerald Group Publishing Limited, volume 30, issue 59, pages 79-115, December, DOI: 10.1108/JEFAS-11-2022-0261.
• Souhir Amri Amamou & Mouna Ben Daoud & Saoussen Aguir Bargaoui, 2024, "Green bonds forecasting: evidence from pre-crisis, Covid-19 and Russian–Ukrainian crisis frameworks," Journal of Economic Studies, Emerald Group Publishing Limited, volume 52, issue 1, pages 179-193, June, DOI: 10.1108/JES-01-2024-0061.
• Dinci J. Penzin & Kazeem O. Isah & Afees A. Salisu, 2024, "Climate change-stock return volatility nexus in advanced economies: the role of technology shocks," Journal of Economic Studies, Emerald Group Publishing Limited, volume 52, issue 1, pages 119-135, May, DOI: 10.1108/JES-08-2023-0419.
• Luan Thanh Le & Trang Xuan-Thi-Thu, 2024, "Discovering supply chain operation towards sustainability using machine learning and DES techniques: a case study in Vietnam seafood," Maritime Business Review, Emerald Group Publishing Limited, volume 9, issue 3, pages 243-262, July, DOI: 10.1108/MABR-10-2023-0074.
• A. Szepeluk & D. Tomczyszyn & A. Cyburt, 2024, "Application of Technical Analysis Stochastic Oscillator for Early Detection of Epidemiological Changes Based on Covid-19 Data in Poland," European Research Studies Journal, European Research Studies Journal, volume 0, issue 3, pages 1069-1082.
• Oksana Kiforenko & Iwona Szczepaniak, 2024, "The War’s Impact on Ukraine’s Agricultural Production – Projections Vs. Real Data," European Research Studies Journal, European Research Studies Journal, volume 0, issue 3, pages 241-269.
• Bartosz Przysucha & Piotr Bednarczuk & Wlodzimierz Martyniuk & Ewa Golec & Michal Jasienski & Damian Pliszczuk, 2024, "Monte Carlo Simulation as a Demand Forecasting Tool," European Research Studies Journal, European Research Studies Journal, volume 0, issue Special A, pages 103-113.
• Pawel Rymarczyk & Cezary Figura & Lukasz Wojciechowski & Kamila Cwik & Piotr Stalinski, 2024, "Evaluating the Effectiveness of Advertising Campaigns in the Fast-Food Industry Using an Analytical Engine," European Research Studies Journal, European Research Studies Journal, volume 0, issue Special A, pages 126-136.
• Pawel Olszewski & Leszek Gil & Natalia Rak & Tomasz Wolowiec & Michal Jasienski, 2024, "Construction of Regression Models Predicting Lead Times and Classification Models," European Research Studies Journal, European Research Studies Journal, volume 0, issue Special A, pages 179-189.
• Krzysztof Krol & Pawel Kaleta & Dariusz Kasperek & Sylwia Skrzypek-Ahmed & Emanuel Jozefacki & Agnieszka Chmielowska-Marmucka, 2024, "Analysis System for Logistics and Production Processes: A Methodological Approach to Signal Analysis for Forecasting," European Research Studies Journal, European Research Studies Journal, volume 0, issue Special A, pages 59-71.
• Tomasz Smutek & Jan Sikora & Sylwester Bogacki & Marek Rutkowski & Dariusz Wozniak, 2024, "Use of Autoencoder and One-Hot Encoding for Customer Segmentation," European Research Studies Journal, European Research Studies Journal, volume 0, issue Special A, pages 72-82.
• Boris Fisera & Filip Ostrihon, 2024, "Constructing Prediction Regions for Exchange Rate Path Forecasts: The Potential of Calibration," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, volume 74, issue 4, pages 432-472, October.
• Jiri Kukacka & Erik Zila, 2024, "Wealth, Cost, and Misperception: Empirical Estimation of Three Interaction Channels in a Financial-Macroeconomic Agent-Based Model," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2024/22, May, revised May 2024.
• Andrea Bastianin & Elisabetta Mirto & Yan Qin & Luca Rossini, 2024, "What drives the European carbon market? Macroeconomic factors and forecasts," Working Papers, Fondazione Eni Enrico Mattei, number 2024.02, Feb.
• Daniel Borup & Philippe Goulet Coulombe & Erik Christian Montes Schütte & David E. Rapach & Sander Schwenk-Nebbe, 2024, "The Anatomy of Out-of-Sample Forecasting Accuracy," FRB Atlanta Working Paper, Federal Reserve Bank of Atlanta, number 2022-16b, Feb, DOI: 10.29338/wp2022-16b.
• Edward S. Knotek & Saeed Zaman, 2024, "Nowcasting Inflation," Working Papers, Federal Reserve Bank of Cleveland, number 24-06, Mar, DOI: 10.26509/frbc-wp-202406.
• Ina Hajdini & Andre Kurmann, 2024, "Predictable Forecast Errors in Full-Information Rational Expectations Models with Regime Shifts," Working Papers, Federal Reserve Bank of Cleveland, number 24-08, Apr, DOI: 10.26509/frbc-wp-202408.
• Todd E. Clark & Gergely Ganics & Elmar Mertens, 2024, "Constructing Fan Charts from the Ragged Edge of SPF Forecasts," Working Papers, Federal Reserve Bank of Cleveland, number 22-36R, Aug, DOI: 10.26509/frbc-wp-202236r.
• Michael Clements & Robert W. Rich & Joseph Tracy, 2024, "An Investigation into the Uncertainty Revision Process of Professional Forecasters," Working Papers, Federal Reserve Bank of Cleveland, number 24-19, Sep, DOI: 10.26509/frbc-wp-202419.
• Kurt Graden Lunsford & Kenneth D. West, 2024, "An Empirical Evaluation of Some Long-Horizon Macroeconomic Forecasts," Working Papers, Federal Reserve Bank of Cleveland, number 24-20, Sep, DOI: 10.26509/frbc-wp-202420.
• Hana Braitsch & James Mitchell & Taylor Shiroff, 2024, "Practice Makes Perfect: Learning Effects with Household Point and Density Forecasts of Inflation," Working Papers, Federal Reserve Bank of Cleveland, number 24-25, Nov, DOI: 10.26509/frbc-wp-202425.
• Jesus Cañas & Aparna Jayashankar & Emily Kerr & Diego Morales-Burnett, 2024, "Texas Manufacturing Outlook Survey: Survey Methodology, Performance and Forecast Accuracy," Working Papers, Federal Reserve Bank of Dallas, number 2402, Mar, DOI: 10.24149/wp2402.
• Mohammad R. Jahan-Parvar & Charles Knipp & Pawel J. Szerszen, 2024, "Trend-Cycle Decomposition and Forecasting Using Bayesian Multivariate Unobserved Components," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2024-100, Dec, DOI: 10.17016/FEDS.2024.100.
• Miguel Faria-e-Castro & Fernando Leibovici, 2024, "Artificial Intelligence and Inflation Forecasts," Review, Federal Reserve Bank of St. Louis, volume 106, issue 12, pages 1-14, November, DOI: 10.20955/r.2024.12.
• Sergey V. Arzhenovskiy, 2024, "Forecasting GDP Dynamics Based on the Bank of Russia’s Enterprise Monitoring Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 31-44, February, DOI: 10.31107/2075-1990-2024-1-31-44.
• Ștefan Rusu & Marcel Ioan Boloș & Marius Leordeanu, 2024, "Comparative analysis of regression models for stock price prediction: Linear, support vector, polynomial, and LASSO," Journal of Financial Studies, Institute of Financial Studies, volume 9, issue 17, pages 143-156, November, DOI: 10.55654/JFS.2024.9.17.09.
• Konstantinos Kofidis & Cătălina Lucia Cocianu, 2024, "Comparative analysis of RF, SVR with Gaussian kernel and LSTM for predicting loan defaults," Journal of Financial Studies, Institute of Financial Studies, volume 9, issue 17, pages 91-106, November, DOI: 10.55654/JFS.2024.9.17.06.
• Vera Barinova & Margarita Gvozdeva & Stepan Zemtsov, 2024, "Small and medium-sized enterprises in Russia in the context of sanctions," Published Papers, Gaidar Institute for Economic Policy, number ppaper-2024-1330, revised 2024.
• Rangan Gupta & Anandamayee Majumdar & Christian Pierdzioch & Onur Polat, 2024, "Climate Risks and Real Gold Returns over 750 Years," Forecasting, MDPI, volume 6, issue 4, pages 1-16, October.
• Prodosh Eugene Simlai, 2024, "Risk Characterization of Firms with ESG Attributes Using a Supervised Machine Learning Method," JRFM, MDPI, volume 17, issue 5, pages 1-9, May.
• Dean Fantazzini, 2024, "Adaptive Conformal Inference for Computing Market Risk Measures: An Analysis with Four Thousand Crypto-Assets," JRFM, MDPI, volume 17, issue 6, pages 1-44, June.
• Rangan Gupta & Christian Pierdzioch, 2024, "Multi-Task Forecasting of the Realized Volatilities of Agricultural Commodity Prices," Mathematics, MDPI, volume 12, issue 18, pages 1-26, September.
• Muhammad Akmal Farouqi & Gigih Fitrianto, 2024, "Systemic Effects on Intersectoral Linkages: Framework and Analysis," Gadjah Mada Economics Working Paper Series, Department of Economics, Faculty of Economics and Business, Universitas Gadjah Mada, number 202403001, Mar.
• Matias Quiroz & Laleh Tafakori & Hans Manner, 2024, "Forecasting Realized Covariances Using HAR-Type Models," Graz Economics Papers, University of Graz, Department of Economics, number 2024-20, Dec.
• Tobias Eibinger & Karl W. Steininger & Hans Manner, 2024, "The Development of Austrian Greenhouse Gas Emissions since 2021," Graz Economics Papers, University of Graz, Department of Economics, number 2024-23, Dec.
• Gary Cornwall & Marina Gindelsky, 2024, "House Prices, Debt Burdens, and the Heterogeneous Effects of Mortgage Rate Shocks," Working Papers, The George Washington University, The Center for Economic Research, number 2024-003, Sep.
• Dr. Marc Ingo Wolter & Florian Bernardt & Jannik Daßler & Saskia Reuschel & Dr. Britta Stöver, 2024, "Klimafolgen und Anpassung – 2024," GWS Research Report Series, GWS - Institute of Economic Structures Research, number 24-2.
• Abdelaati Daouia & Simone A. Padoan & Gilles Stupfler, 2024, "Extreme expectile estimation for short-tailed data," Post-Print, HAL, number hal-04672516, DOI: 10.1016/j.jeconom.2024.105770.
• Rafael Branco & Alexandre Rubesam & Mauricio Zevallos, 2024, "Forecasting realized volatility: Does anything beat linear models?," Post-Print, HAL, number hal-04835657, Sep, DOI: 10.1016/j.jempfin.2024.101524.
• Amal Ben Hamida & Christian de Peretti & Lotfi Belkacem, 2024, "The link between abnormal numbers and price movements of financial securities: How does Benford’s law predict stock returns?," Post-Print, HAL, number hal-04875454, Oct, DOI: 10.1016/j.irfa.2024.103517.
• Michele Lenza & Inès Moutachaker & Joan Paredes, 2024, "Density forecasts of inflation: a quantile regression forest approach
  [Prévisions de densité de l'inflation : une approche par forêt de régressions quantile]," Working Papers, HAL, number hal-05329662, Jun.
• Kreye, Tom Jannik & Sibbertsen, Philipp, 2024, "Testing for a Forecast Accuracy Breakdown under Long Memory," Hannover Economic Papers (HEP), Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, number dp-729, Nov.
• Tea Šestanović, 2024, "A Comprehensive Approach To Bitcoin Forecasting Using Neural Networks," Ekonomski pregled, Hrvatsko društvo ekonomista (Croatian Society of Economists), volume 75, issue 1, pages 62-85, DOI: 10.32910/ep.75.1.3.
• Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024, "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers, Norwegian School of Economics, Department of Business and Management Science, number 2024/1, Jan.
• Narum, Benjamin S. & Berentsen, Geir D., 2024, "Joint Forecasting of Salmon Lice and Treatment Interventions in Aquaculture Operations," Discussion Papers, Norwegian School of Economics, Department of Business and Management Science, number 2024/7, May.
• Shchestyuk, Nataliya & Tyshchenkob, Sergii, 2024, "Subdiffusive option price model with Inverse Gaussian subordinator," Working Papers, Örebro University, School of Business, number 2024:1, Jan.
• Pettersson, Nicklas & Kelemen, Katalin, 2024, "Yet another case of Nordic exceptionalism?: A quantitative approach to an intra-Nordic and an international comparison of supreme courts’ constitutional reasoning," Working Papers, Örebro University, School of Business, number 2024:7, Aug.
• Bårdsen, Gunnar & Nymoen, Ragnar, 2024, "U.S. wage-price dynamics, before, during and after COVID-19, through the lens of an empirical econometric model," Memorandum, Oslo University, Department of Economics, number 1/2024, Jun.
• Kim Karlsson, Hyunjoo & Li, Yushu, 2024, "Investigation of Swedish krona exchange rate volatility by APARCH-Support Vector Regression," Working Papers in Economics and Statistics, Linnaeus University, School of Business and Economics, Department of Economics and Statistics, number 10/2024, Jun.
• HARA, Naoko & YAMAMOTO, Yohei, 2024, "Testing and Quantifying Economic Resilience," Discussion paper series, Hitotsubashi Institute for Advanced Study, Hitotsubashi University, number HIAS-E-142, Nov.
• Alison Baulos & Jorge Luis Garcia & James J. Heckman, 2024, "Perry Preschool at 50: What Lessons Should Be Drawn and Which Criticisms Ignored?," Working Papers, Human Capital and Economic Opportunity Working Group, number 2024-019, Nov.
• Berg, Gerard J. van den & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2024, "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," IAB-Discussion Paper, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], number 202403, Feb, DOI: 10.48720/IAB.DP.2403.
• Bjarni G. Einarsson, 2024, "Online Monitoring of Policy Optimality," Economics, Department of Economics, Central bank of Iceland, number wp95, Apr.
• Agarwala, Matthew & Burke, Matt & Doherty-Bigara, Jennifer & Klusak, Patrycja & Mohaddes, Kamiar, 2024, "Climate Change and Sovereign Risk: A Regional Analysis for the Caribbean," IDB Publications (Working Papers), Inter-American Development Bank, number 13478, Apr, DOI: http://dx.doi.org/10.18235/0012885.
• Benítez, Miguel & Parrado, Eric, 2024, "Mirror, Mirror on the Wall: Which Jobs Will AI Replace After All?: A New Index of Occupational Exposure," IDB Publications (Working Papers), Inter-American Development Bank, number 13696, Aug, DOI: http://dx.doi.org/10.18235/0013125.
• Kaustubh & Soumya Bhadury & Saurabh Ghosh, 2024, "Reinvigorating GVA Nowcasting in the Post-pandemic Period: A Case Study for India," Bulletin of Monetary Economics and Banking, Bank Indonesia, volume 27, issue Spesial I, pages 95-130, February, DOI: https://doi.org/10.59091/2460-9196..
• Gabriel, Stefan & Kunst, Robert M., 2024, "Cointegrated portfolios and volatility modeling in the cryptocurrency market," IHS Working Paper Series, Institute for Advanced Studies, number 52, Mar.
• Cullen S. Hendrix, 2024, "The El Nino Southern Oscillation and Geopolitical Risk," Working Paper Series, Peterson Institute for International Economics, number WP24-14, May.
• Mahir Binici & Samuele Centorrino & Serhan Cevik & Gyowon Gwon, 2024, "Here Comes the Change: The Role of Global and Domestic Factors in Post-Pandemic Inflation in Europe," International Journal of Central Banking, International Journal of Central Banking, volume 20, issue 2, pages 237-290, April.
• Frank Schorfheide & Dongho Song, 2024, "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," International Journal of Central Banking, International Journal of Central Banking, volume 20, issue 4, pages 275-320, October.
• Ferdinand Fichtner & Heike Joebges, 2024, "Stock market returns and GDP growth," IMK Studies, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute, number 90-2024.
• Adrián F. Rossignolo, 2024, "Basel IV and the structural relationship between SA and IMA," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 19, issue 2, pages 1-37, Abril - J.
• Erwis Melchor Pérez & Moisés Emmanuel Ramírez Guzmán & Araceli Hernández Jiménez & Agustín Santiago Alvarado, 2024, "Predicción del riesgo crediticio a microfinanciera usando aprendizaje computacional," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 19, issue 4, pages 1-16, Octubre -.
• Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024, "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202402, Feb, revised Feb 2024.
• Adrián Fernandez-Perez & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2025, "Examining the transmission of credit and liquidity risks: A network analysis for EMU sovereign debt markets," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202504, Jan.
• Huo, Shutong & Feng, Derek & Gill, Thomas M. & Chen, Xi, 2024, "Childhood Circumstances and Health of American and Chinese Older Adults: A Machine Learning Evaluation of Inequality of Opportunity in Health," IZA Discussion Papers, IZA Network @ LISER, number 16764, Jan.
• Fiaschi, Davide & Tealdi, Cristina, 2024, "Let's Roll Back! The Challenging Task of Regulating Temporary Contracts," IZA Discussion Papers, IZA Network @ LISER, number 16777, Jan.
• Kumar, Pradeep & Nicodemo, Catia & Oreffice, Sonia & Quintana-Domeque, Climent, 2024, "Machine Learning and Multiple Abortions," IZA Discussion Papers, IZA Network @ LISER, number 17046, Jun.
• Hyee, Raphaela & Immervoll, Herwig & Fernandez, Rodrigo & Lee, Jongmi & Handscomb, Karl, 2024, "How Reliable Are Social Safety Nets in Situations of Acute Economic Need? Extended Estimates for 14 OECD Countries," IZA Discussion Papers, IZA Network @ LISER, number 17477, Nov.
• Michal Franta & Jan Libich, 2024, "Holding the economy by the tail: analysis of short- and long-run macroeconomic risks," Empirical Economics, Springer, volume 66, issue 4, pages 1443-1489, April, DOI: 10.1007/s00181-023-02514-7.
• Zhikai Zhang & Yaojie Zhang & Yudong Wang, 2024, "Forecasting the equity premium using weighted regressions: Does the jump variation help?," Empirical Economics, Springer, volume 66, issue 5, pages 2049-2082, May, DOI: 10.1007/s00181-023-02521-8.
• Huawei Niu & Tianyu Liu, 2024, "Forecasting the volatility of European Union allowance futures with macroeconomic variables using the GJR-GARCH-MIDAS model," Empirical Economics, Springer, volume 67, issue 1, pages 75-96, July, DOI: 10.1007/s00181-023-02551-2.
• Robert Lehmann, 2024, "A real-time regional accounts database for Germany with applications to GDP revisions and nowcasting," Empirical Economics, Springer, volume 67, issue 2, pages 817-838, August, DOI: 10.1007/s00181-024-02566-3.
• Nima Nonejad, 2024, "Point forecasts of the price of crude oil: an attempt to “beat” the end-of-month random-walk benchmark," Empirical Economics, Springer, volume 67, issue 4, pages 1497-1539, October, DOI: 10.1007/s00181-024-02599-8.
• Fameliti Stavroula & Skintzi Vasiliki, 2024, "Macroeconomic attention and commodity market volatility," Empirical Economics, Springer, volume 67, issue 5, pages 1967-2007, November, DOI: 10.1007/s00181-024-02613-z.
• Yasmeen Bayaa & Mahmoud Qadan, 2024, "Interest rate uncertainty and the shape of the yield curve of U.S. treasury bonds," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, volume 14, issue 4, pages 981-1003, December, DOI: 10.1007/s40822-024-00278-8.
• Aktham Maghyereh & Salem Adel Ziadat, 2024, "Pattern and determinants of tail-risk transmission between cryptocurrency markets: new evidence from recent crisis episodes," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 10, issue 1, pages 1-34, December, DOI: 10.1186/s40854-023-00592-1.
• Xiaozhen Jing & Dezhong Xu & Bin Li & Tarlok Singh, 2024, "Does the U.S. extreme indicator matter in stock markets? International evidence," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 10, issue 1, pages 1-27, December, DOI: 10.1186/s40854-024-00610-w.
• Blanco-Oliver Antonio & Lara-Rubio Juan & Irimia-Diéguez Ana & Liébana-Cabanillas Francisco, 2024, "Examining user behavior with machine learning for effective mobile peer-to-peer payment adoption," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 10, issue 1, pages 1-30, December, DOI: 10.1186/s40854-024-00625-3.
• Malvina Marchese & María Dolores Martínez-Miranda & Jens Perch Nielsen & Michael Scholz, 2024, "Robustifying and simplifying high-dimensional regression with applications to yearly stock return and telematics data," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 10, issue 1, pages 1-16, December, DOI: 10.1186/s40854-024-00657-9.
• Fred Espen Benth & Carlo Sgarra, 2024, "A Barndorff-Nielsen and Shephard model with leverage in Hilbert space for commodity forward markets," Finance and Stochastics, Springer, volume 28, issue 4, pages 1035-1076, October, DOI: 10.1007/s00780-024-00546-0.
• Ioannis Sitzimis, 2024, "Forecasting methods in Greek coastal shipping: The case of Southwest Crete," Future Business Journal, Springer, volume 10, issue 1, pages 1-16, December, DOI: 10.1186/s43093-024-00352-2.
• Leila Hedhili Zaier & Khaled Mokni & Ahdi Noomen Ajmi, 2024, "Causality relationships between climate policy uncertainty, renewable energy stocks, and oil prices: a mixed-frequency causality analysis," Future Business Journal, Springer, volume 10, issue 1, pages 1-11, December, DOI: 10.1186/s43093-024-00399-1.
• Sandra Dreher & Sebastian Eichfelder & Felix Noth, 2024, "Does IFRS information on tax loss carryforwards and negative performance improve predictions of earnings and cash flows?," Journal of Business Economics, Springer, volume 94, issue 1, pages 1-39, January, DOI: 10.1007/s11573-023-01147-7.
• J. Peter Leo Deepak & Yavana Rani Subramanian & J. Josephine Lalitha & K. Vidhya, 2024, "Optimum Level of Currency Reserves: Investigation and Forecasting of Indian Rupee Using ARIMA Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 20, issue 1, pages 137-150, August, DOI: 10.1007/s41549-023-00091-3.
• Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024, "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 20, issue 3, pages 339-366, November, DOI: 10.1007/s41549-025-00106-1.
• Jörg Döpke & Tim Köhler & Lars Tegtmeier, 2024, "Are they worth it? – An evaluation of predictions for NBA ‘Fantasy Sports’," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 48, issue 1, pages 142-165, March, DOI: 10.1007/s12197-023-09646-7.
• Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2024, "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from the Lasso Regularization and Inferential Techniques," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), volume 15, issue 1, pages 144-179, March, DOI: 10.1007/s13132-022-01055-1.
• Dervis Kirikkaleli & Fusun Celebi Boz & Melike Torun, 2024, "Do Economic and Financial Stabilities Matter for Political Stability in Estonia?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), volume 15, issue 3, pages 15202-15217, September, DOI: 10.1007/s13132-023-01662-6.
• Filip Lubinski, 2024, "Book review. J. Doyne Farmer, Making Sense of Chaos. A Better Economics for a Better World, Penguin (2024), pp. 364," Journal of Evolutionary Economics, Springer, volume 34, issue 4, pages 1013-1017, December, DOI: 10.1007/s00191-024-00876-4.
• Agnieszka Orwat-Acedańska, 2024, "Accuracy of small area mortality prediction methods: evidence from Poland," Journal of Population Research, Springer, volume 41, issue 1, pages 1-20, March, DOI: 10.1007/s12546-023-09326-7.
• Gavin Ooft & Sailesh Bhaghoe & Philip Hans Franses, 2024, "Forecasting Annual Inflation Using Weekly Money Supply," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 22, issue 1, pages 25-43, March, DOI: 10.1007/s40953-023-00376-5.
• Kristian Jönsson, 2024, "Neighbor Weighting and Distance Metrics in Nearest Neighbor Nowcasting of Swedish GDP," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 22, issue 4, pages 1077-1089, December, DOI: 10.1007/s40953-024-00400-2.
• Seyed Farshid Ghorashi & Maziyar Bahri & Atousa Goodarzi, 2024, "Developing and comparing machine learning approaches for predicting insurance penetration rates based on each country," Letters in Spatial and Resource Sciences, Springer, volume 17, issue 1, pages 1-29, December, DOI: 10.1007/s12076-024-00387-7.
• Claudia Ceci & Michele Bufalo & Giuseppe Orlando, 2024, "Modelling the industrial production of electric and gas utilities through the $$CIR^3$$ C I R 3 model," Mathematics and Financial Economics, Springer, number 1, June, DOI: 10.1007/s11579-023-00350-y.
• Giorgio Gnecco & Sara Landi & Massimo Riccaboni, 2024, "The emergence of social soft skill needs in the post COVID-19 era," Quality & Quantity: International Journal of Methodology, Springer, volume 58, issue 1, pages 647-680, February, DOI: 10.1007/s11135-023-01659-y.
• Afees Salisu & Sulaiman Salisu & Subair Salisu, 2024, "A news-based economic policy uncertainty index for Nigeria," Quality & Quantity: International Journal of Methodology, Springer, volume 58, issue 5, pages 4987-5002, October, DOI: 10.1007/s11135-024-01886-x.
• Chris Reimann, 2024, "Predicting financial crises: an evaluation of machine learning algorithms and model explainability for early warning systems," Review of Evolutionary Political Economy, Springer, volume 5, issue 1, pages 51-83, June, DOI: 10.1007/s43253-024-00114-4.
• Diego Fresoli, 2024, "Spanish GDP short-term point and density forecasting using a mixed-frequency dynamic factor model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, volume 15, issue 2, pages 145-177, June, DOI: 10.1007/s13209-024-00297-3.
• Philipp Wegmueller & Christian Glocker, 2024, "Capturing Swiss economic confidence," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 160, issue 1, pages 1-17, December, DOI: 10.1186/s41937-024-00120-7.
• Riadh Trabelsi, 2024, "Sources of macroeconomic fluctuations in Tunisia: a structural VAR approach," SN Business & Economics, Springer, volume 4, issue 10, pages 1-28, October, DOI: 10.1007/s43546-024-00717-3.
• M’bakob Gilles Brice & Mandeng ma Ntamack Jules, 2024, "Influence of psychological exchange rates (PER) on forex price formation: theory, empirical, and experimental evidence," SN Business & Economics, Springer, volume 4, issue 9, pages 1-53, September, DOI: 10.1007/s43546-024-00698-3.
• Kazım Berk Küçüklerli & Veysel Ulusoy, 2024, "Sentiment-Driven Exchange Rate Forecasting: Integrating Twitter Analysis with Economic Indicators," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 14, issue 3, pages 1-4.
• Pål Boug & Håvard Hungnes & Takamitsu Kurita, 2024, "Getting Back on Track. Forecasting After Extreme Observations," Discussion Papers, Statistics Norway, Research Department, number 1018, Dec.
• Joana Katina & Joana Katina & Igor Katin & Igor Katin & Vera Komarova, 2024, "Cryptocurrency price forecasting: a comparative analysis of autoregressive and recurrent neural network models," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, volume 11, issue 4, pages 425-436, June, DOI: 10.9770/jesi.2024.11.4(26).
• Givi Bedianashvili & Murman Tsartsidze & Nino Mikeladze & Zviad Gabroshvili, 2024, "Human capital and economic growth under modern globalization," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, volume 12, issue 1, pages 268-289, September, DOI: 10.9770/jesi.2024.12.1(19).
• Yasin Mimir & Lorenzo Ricci, 2024, "Financial imbalances and macroeconomic tail risks: A structural regime-switching investigation," Working Papers, European Stability Mechanism, number 64, Nov, revised 15 Nov 2024.
• Luke Hartigan & Tom Rosewall, 2024, "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," Working Papers, University of Sydney, School of Economics, number 2024-15, Jul.
• Monica Billio & Roberto Casarin & Matteo Iacopini, 2024, "Bayesian Markov-Switching Tensor Regression for Time-Varying Networks," Journal of the American Statistical Association, Taylor & Francis Journals, volume 119, issue 545, pages 109-121, January, DOI: 10.1080/01621459.2022.2102502.
• Liu Yang & Kajal Lahiri & Adrian Pagan, 2024, "Getting the ROC into Sync," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 42, issue 1, pages 109-121, January, DOI: 10.1080/07350015.2022.2154778.
• James Morley & Trung Duc Tran & Benjamin Wong, 2024, "A Simple Correction for Misspecification in Trend-Cycle Decompositions with an Application to Estimating r," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 42, issue 2, pages 665-680, April, DOI: 10.1080/07350015.2023.2221974.
• Davide Delle Monache & Andrea De Polis & Ivan Petrella, 2024, "Modeling and Forecasting Macroeconomic Downside Risk," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 42, issue 3, pages 1010-1025, July, DOI: 10.1080/07350015.2023.2277171.
• David Ardia & Arnaud Dufays & Carlos Ordás Criado, 2024, "Linking Frequentist and Bayesian Change-Point Methods," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 42, issue 4, pages 1155-1168, October, DOI: 10.1080/07350015.2023.2293166.
• Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2024, "Investigating Growth-at-Risk Using a Multicountry Nonparametric Quantile Factor Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 42, issue 4, pages 1302-1317, October, DOI: 10.1080/07350015.2024.2310020.
• Raffaele Mattera & George Athanasopoulos & Rob Hyndman, 2024, "Improving out-of-sample forecasts of stock price indexes with forecast reconciliation and clustering," Quantitative Finance, Taylor & Francis Journals, volume 24, issue 11, pages 1641-1667, November, DOI: 10.1080/14697688.2024.2412687.
• Mihaela Simionescu & Nicolas Schneider & Beata Gavurova, 2024, "A Bayesian vector-autoregressive application with time-varying parameters on the monetary shocks–production network nexus," Journal of Applied Economics, Taylor & Francis Journals, volume 27, issue 1, pages 2395114-239, December, DOI: 10.1080/15140326.2024.2395114.
• Salih Zeki Atilgan & Tarik Aydogdu & Mehmet Selman Colak & Muhammed Hasan Yilmaz, 2024, "Anticipating Credit Developments with Regularization and Shrinkage Methods: Evidence for Turkish Banking Industry," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 2402.
• Anne Opschoor & Dewi Peerlings & Luca Rossini & Andre Lucas, 2024, "Density Forecasting for Electricity Prices under Tail Heterogeneity with the t-Riesz Distribution," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 24-049/III, Jul.
• Gabriele Mingoli, 2024, "Modeling Common Bubbles: A Mixed Causal Non-Causal Dynamic Factor Model," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 24-072/III, Nov.
• Pierluigi Vallarino, 2024, "Dynamic kernel models," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 24-082/III, Dec.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024, "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, volume 106, issue 5, pages 1403-1417, September, DOI: 10.1162/rest_a_01213.
• Felix Haase, 2024, "Sum-of-the-Parts Revised: Economic Regimes and Flexible Probabilities," Research Papers in Economics, University of Trier, Department of Economics, number 2024-10.