Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2024

• Deschermeier, Philipp, 2024, "IW-Bevölkerungsprognose: Eine Datengrundlage zur Gestaltung der Herausforderungen des demografischen Wandels auf Basis des Zensus 2022
  [IW population forecast 2024 - Essential data for meeting the ," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, volume 51, issue 3, pages 67-87, DOI: 10.2373/1864-810X.24-03-04.
• Foltas, Alexander, 2024, "Inefficient forecast narratives: A BERT-based approach," Working Papers, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin, number 45, DOI: 10.18452/29133.
• Wolf, Elias & Montes-Galdón, Carlos & Paredes, Joan, 2024, "Conditional density forecasting: a tempered importance sampling approach," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges, Verein für Socialpolitik / German Economic Association, number 302442.

2023

• Samuel F. Onipede & Nafiu A. Bashir & Jamaladeen Abubakar, 2023, "Small open economies and external shocks: an application of Bayesian global vector autoregression model," Quality & Quantity: International Journal of Methodology, Springer, volume 57, issue 2, pages 1673-1699, April, DOI: 10.1007/s11135-022-01423-8.
• Afees A. Salisu & Abdulsalam Abidemi Sikiru & Philip C. Omoke, 2023, "COVID-19 pandemic and financial innovations," Quality & Quantity: International Journal of Methodology, Springer, volume 57, issue 4, pages 3885-3904, August, DOI: 10.1007/s11135-022-01540-4.
• Matthias Breuer & Harm H. Schütt, 2023, "Accounting for uncertainty: an application of Bayesian methods to accruals models," Review of Accounting Studies, Springer, volume 28, issue 2, pages 726-768, June, DOI: 10.1007/s11142-021-09654-0.
• Krzysztof Rusek & Agnieszka Kleszcz & Albert Cabellos-Aparicio, 2023, "Bayesian inference of spatial and temporal relations in AI patents for EU countries," Scientometrics, Springer;Akadémiai Kiadó, volume 128, issue 6, pages 3313-3335, June, DOI: 10.1007/s11192-023-04699-1.
• Sylvia Kaufmann, 2023, "Covid-19 outbreak and beyond: a retrospect on the information content of short-time workers for GDP now- and forecasting," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 159, issue 1, pages 1-10, December, DOI: 10.1186/s41937-023-00106-x.
• Stavros Degiannakis, 2023, "The D-model for GDP nowcasting," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 159, issue 1, pages 1-33, December, DOI: 10.1186/s41937-023-00109-8.
• Peter Kugler & George Sheldon, 2023, "A monthly leading indicator of Swiss GDP growth based on Okun’s law," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 159, issue 1, pages 1-14, December, DOI: 10.1186/s41937-023-00115-w.
• Emmanuel O. Akande & Elijah O. Akanni & Oyedamola F. Taiwo & Jeremiah D. Joshua & Abel Anthony, 2023, "Predicting inflation component drivers in Nigeria: a stacked ensemble approach," SN Business & Economics, Springer, volume 3, issue 1, pages 1-32, January, DOI: 10.1007/s43546-022-00384-2.
• Pami Dua & Rajiv Ranjan & Deepika Goel, 2023, "Forecasting the INR/USD Exchange Rate: A BVAR Framework," Springer Books, Springer, chapter 0, in: Pami Dua, "Macroeconometric Methods", DOI: 10.1007/978-981-19-7592-9_8.
• Timothy Neal, 2023, "The Importance of External Weather Effects in Projecting the Economic Impacts of Climate Change," Discussion Papers, School of Economics, The University of New South Wales, number 2023-09, Jun.
• Clements, Adam & Vasnev, Andrey L., 2023, "Combining simple multivariate HAR-like models for portfolio construction," Working Papers, University of Sydney Business School, Discipline of Business Analytics, number BAWP-2023-03, Nov.
• Kajal Lahiri & Junyan Zhang & Yongchen Zhao, 2023, "Inefficiency in social security trust funds forecasts," Applied Economics Letters, Taylor & Francis Journals, volume 30, issue 10, pages 1353-1357, June, DOI: 10.1080/13504851.2022.2053649.
• Jiqian Wang & Rangan Gupta & Oğuzhan Çepni & Feng Ma, 2023, "Forecasting international REITs volatility: the role of oil-price uncertainty," The European Journal of Finance, Taylor & Francis Journals, volume 29, issue 14, pages 1579-1597, September, DOI: 10.1080/1351847X.2022.2137422.
• Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2023, "Investor Confidence and Forecastability of US Stock Market Realized Volatility: Evidence from Machine Learning," Journal of Behavioral Finance, Taylor & Francis Journals, volume 24, issue 1, pages 111-122, January, DOI: 10.1080/15427560.2021.1949719.
• Monica Billio & Roberto Casarin & Matteo Iacopini & Sylvia Kaufmann, 2023, "Bayesian Dynamic Tensor Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 41, issue 2, pages 429-439, April, DOI: 10.1080/07350015.2022.2032721.
• Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2023, "Quantifying Time-Varying Forecast Uncertainty and Risk for the Real Price of Oil," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 41, issue 2, pages 523-537, April, DOI: 10.1080/07350015.2022.2039159.
• Laurent Ferrara & Anna Simoni, 2023, "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 41, issue 4, pages 1188-1202, October, DOI: 10.1080/07350015.2022.2116025.
• Zhongchen Song & Tom Coupé, 2023, "Predicting Chinese consumption series with Baidu," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, volume 21, issue 3, pages 429-463, July, DOI: 10.1080/14765284.2022.2161175.
• Constantin Rudolf Salomo Bürgi, 2023, "How to deal with missing observations in surveys of professional forecasters," Journal of Applied Economics, Taylor & Francis Journals, volume 26, issue 1, pages 2185975-218, December, DOI: 10.1080/15140326.2023.2185975.
• Anna Gloria Billé & Alessio Tomelleri & Francesco Ravazzolo, 2023, "Forecasting regional GDPs: a comparison with spatial dynamic panel data models," Spatial Economic Analysis, Taylor & Francis Journals, volume 18, issue 4, pages 530-551, October, DOI: 10.1080/17421772.2023.2199034.
• Benjamin Monnery & Fran ois-Charles Wolff, 2023, "Is participatory democracy in line with social protest ? Evidence from the French Yellow Vests movement," TEPP Working Paper, TEPP, number 2023-07.
• Daan Opschoor & Dick van Dijk, 2023, "Slow Expectation-Maximization Convergence in Low-Noise Dynamic Factor Models," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 23-018/III, Apr.
• Francisco Blasques & Siem Jan Koopman & Gabriele Mingoli, 2023, "Observation-Driven filters for Time- Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 23-065/III, Oct, revised 01 Mar 2024.
• Gabriel Mathy & Yongchen Zhao, 2023, "Could Diffusion Indexes Have Forecasted the Great Depression?," Working Papers, Towson University, Department of Economics, number 2023-05, Sep, revised Sep 2023.
• Yongchen Zhao, 2023, "Uncertainty of Household Inflation Expectations: Reconciling Point and Density Forecasts," Working Papers, Towson University, Department of Economics, number 2023-09, Dec, revised Dec 2023.
• Travis J. Berge, 2023, "Time-Varying Uncertainty of the Federal Reserve's Output Gap Estimate," The Review of Economics and Statistics, MIT Press, volume 105, issue 5, pages 1191-1206, September, DOI: 10.1162/rest_a_01102.
• Abir HASSAN & Mahbubul Md. ALAM & Azmaine FAEIQUE, 2023, "Forecasting Monthly Inflation in Bangladesh: A Seasonal Autoregressive Moving Average (SARIMA) Approach," Journal of Economics and Financial Analysis, Tripal Publishing House, volume 7, issue 2, pages 25-43, DOI: 10.1991/jefa.v7i2.a61.
• Marco Del Negro & Marc P. Giannoni & Christina Patterson, 2023, "The Forward Guidance Puzzle," Journal of Political Economy Macroeconomics, University of Chicago Press, volume 1, issue 1, pages 43-79, DOI: 10.1086/724214.
• Jianghao Chu & Tae-Hwy Lee & Aman Ullah, 2023, "Asymmetric AdaBoost for High-dimensional Maximum Score Regression," Working Papers, University of California at Riverside, Department of Economics, number 202306, Aug.
• Tae-Hwy Lee & Tao Wang, 2023, "Estimation and Testing of Forecast Rationality with Many Moments," Working Papers, University of California at Riverside, Department of Economics, number 202307, Sep.
• Tae-Hwy Lee & Ekaterina Seregina & Yaojue Xu, 2023, "Elicitability and Encompassing for Volatility Forecasts by Bregman Functions," Working Papers, University of California at Riverside, Department of Economics, number 202311, Sep.
• Vladimir M. Markovic & Nikola Radivojevic & Tatjana Ivanovic & Slobodan Radisic & Nenad Novakovic, 2023, "The quantum harmonic oscillator expected shortfall model," Estudios de Economia, University of Chile, Department of Economics, volume 50, issue 2 Year 20, pages 233-261, December.
• Mihnea Constantinescu, 2023, "Sparse Warcasting," Working Papers, National Bank of Ukraine, number 01/2023, Jun.
• Alejo Estavillo & Gabriela Mordecki, 2023, "Nowcasting del PIB para Uruguay en base a un modelo de ecuaciones puente," Documentos de Trabajo (working papers), Instituto de Economía - IECON, number 23-26, Dec.
• Dietrich, Stephan & Malerba, Daniele & Gassmann, Franziska, 2023, "Predicting social assistance beneficiaries," MERIT Working Papers, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT), number 2023-007, Mar.
• Jaromir Hurnik & Vatcharin Sirimaneetham, 2023, "A long-term approach for analysing public debt sustainability: a case study of Mongolia," MPDD Working Paper Series, United Nations Economic and Social Commission for Asia and the Pacific (ESCAP), number WP/23/02, Dec.
• Lis Szymon & Chlebus Marcin, 2023, "Combining forecasts? Keep it simple," Central European Economic Journal, Sciendo, volume 10, issue 57, pages 343-370, January, DOI: 10.2478/ceej-2023-0020.
• Sabek Amine, 2023, "Unveiling the diverse efficacy of artificial neural networks and logistic regression: A comparative analysis in predicting financial distress," Croatian Review of Economic, Business and Social Statistics, Sciendo, volume 9, issue 1, pages 16-32, July, DOI: 10.2478/crebss-2023-0002.
• Berezka Kateryna & Kovalchuk Olha, 2023, "The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates," Econometrics. Advances in Applied Data Analysis, Sciendo, volume 27, issue 1, pages 1-16, March, DOI: 10.15611/eada.2023.1.01.
• Souto Hugo Gobato & Moradi Amir, 2023, "Forecasting realized volatility through financial turbulence and neural networks," Economics and Business Review, Sciendo, volume 9, issue 2, pages 133-159, April, DOI: 10.18559/ebr.2023.2.737.
• Mishra Akshay Kumar & Kumar Rahul & Bal Debi Prasad, 2023, "ESG Volatility Prediction Using GARCH and LSTM Models," Financial Internet Quarterly (formerly e-Finanse), Sciendo, volume 19, issue 4, pages 97-114, December, DOI: 10.2478/fiqf-2023-0029.
• Vasilev Julian & Sulova Snezhana, 2023, "An Approach for the In-Depth Data Analysis of the Marine Traffic of Independent Nearby Ports," Folia Oeconomica Stetinensia, Sciendo, volume 23, issue 2, pages 402-426, December, DOI: 10.2478/foli-2023-0038.
• Suleiman Ahmad Abubakar & Othman Mahmod & Daud Hanita & Abdullah Mohd Lazim & Kadir Evizal Abdul & Kane Ibrahim Lawal & Husin Abdullah, 2023, "Forecasting the Volatility of Real Residential Property Prices in Malaysia: A Comparison of Garch Models," Real Estate Management and Valuation, Sciendo, volume 31, issue 3, pages 20-31, September, DOI: 10.2478/remav-2023-0018.
• Ciocîrlan Cecilia & Zwak-Cantoriu Maria-Cristina & Stancea Andreea & Plăcintă Dimitrie-Daniel, 2023, "European Macroeconomic Dynamics on Financial Markets and Economic Policy: A Cross Country Study for Spillover Effects," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, volume 68, issue 3, pages 40-63, December, DOI: 10.2478/subboec-2023-0014.
• Leo Krippner, 2023, "Estimating and Applying Autoregression Models Via Their Eigensystem Representation," Working Papers in Economics, University of Waikato, number 23/09, Dec.
• Maudud Hassan Uzzal & Robert Ślepaczuk, 2023, "The performance of time series forecasting based on classical and machine learning methods for S&P 500 index," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-05.
• Konrad Lewszyk & Piotr Wójcik, 2023, "Modelling Subjective Attractiveness," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-06.
• Karol Chojnacki & Robert Ślepaczuk, 2023, "This study compares well-known tools of technical analysis (Moving Average Crossover MAC) with Machine Learning based strategies (LSTM and XGBoost) and Ensembled Machine Learning Strategies (LSTM ense," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-15.
• Damian Ślusarczyk & Robert Ślepaczuk, 2023, "Optimal Markowitz Portfolio Using Returns Forecasted with Time Series and Machine Learning Models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-17.
• Paweł Jakubowski & Robert Ślepaczuk & Franciszek Windorbski, 2023, "REnsembling ARIMAX Model in Algorithmic Investment Strategies on Commodities Market," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-20.
• Jakub Michańków & Paweł Sakowski & Robert Ślepaczuk, 2023, "Mean Absolute Directional Loss as a New Loss Function for Machine Learning Problems in Algorithmic Investment Strategies," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-23.
• Jakub Michańków & Paweł Sakowski & Robert Ślepaczuk, 2023, "Hedging Properties of Algorithmic Investment Strategies using Long Short-Term Memory and Time Series models for Equity Indices," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-25.
• Sahil Teymurzade & Robert Ślepaczuk, 2023, "Predicting DJIA, NASDAQ and NYSE index prices using ARIMA and VAR models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-27.
• Amor Aniss Benmoussa, Reinhard Ellwanger, Stephen Snudden, 2023, "Carpe Diem: Can daily oil prices improve model-based forecasts of the real price of crude oil?," LCERPA Working Papers, Laurier Centre for Economic Research and Policy Analysis, number bm0141, Dec.
• Reinhard Ellwanger, Stephen Snudden, Lenin Arango-Castillo, 2023, "Seize the Last Day: Period-End-Point Sampling for Forecasts of Temporally Aggregated Data," LCERPA Working Papers, Laurier Centre for Economic Research and Policy Analysis, number bm0142, Dec.
• Gary Koop & Dimitris Korobilis, 2023, "Bayesian Dynamic Variable Selection In High Dimensions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, volume 64, issue 3, pages 1047-1074, August, DOI: 10.1111/iere.12623.
• Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023, "Tail Forecasting With Multivariate Bayesian Additive Regression Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, volume 64, issue 3, pages 979-1022, August, DOI: 10.1111/iere.12619.
• Pablo Guerróon‐Quintana & Molin Zhong, 2023, "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 38, issue 3, pages 295-320, April, DOI: 10.1002/jae.2951.
• James Mitchell & Martin Weale, 2023, "Censored density forecasts: Production and evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 38, issue 5, pages 714-734, August, DOI: 10.1002/jae.2972.
• Eiji Goto & Jan P.A.M. Jacobs & Tara M. Sinclair & Simon van Norden, 2023, "Employment reconciliation and nowcasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 38, issue 7, pages 1007-1017, November, DOI: 10.1002/jae.2995.
• William A. Barnett & Sohee Park, 2023, "Forecasting inflation and output growth with credit‐card‐augmented Divisia monetary aggregates," Journal of Forecasting, John Wiley & Sons, Ltd., volume 42, issue 2, pages 331-346, March, DOI: 10.1002/for.2910.
• Stephen G. Hall & George S. Tavlas & Yongli Wang, 2023, "Forecasting inflation: The use of dynamic factor analysis and nonlinear combinations," Journal of Forecasting, John Wiley & Sons, Ltd., volume 42, issue 3, pages 514-529, April, DOI: 10.1002/for.2948.
• Carlos Cañizares Martínez & Gabe J. de Bondt & Arne Gieseck, 2023, "Forecasting housing investment," Journal of Forecasting, John Wiley & Sons, Ltd., volume 42, issue 3, pages 543-565, April, DOI: 10.1002/for.2946.
• Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023, "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., volume 42, issue 4, pages 785-801, July, DOI: 10.1002/for.2914.
• Donato Ceci & Andrea Silvestrini, 2023, "Nowcasting the state of the Italian economy: The role of financial markets," Journal of Forecasting, John Wiley & Sons, Ltd., volume 42, issue 7, pages 1569-1593, November, DOI: 10.1002/for.2958.
• Afees A. Salisu & Riza Demirer & Rangan Gupta, 2023, "Policy uncertainty and stock market volatility revisited: The predictive role of signal quality," Journal of Forecasting, John Wiley & Sons, Ltd., volume 42, issue 8, pages 2307-2321, December, DOI: 10.1002/for.3016.
• Stavros Degiannakis & George Filis & Grigorios Siourounis & Lorenzo Trapani, 2023, "Superkurtosis," Journal of Money, Credit and Banking, Blackwell Publishing, volume 55, issue 8, pages 2061-2091, December, DOI: 10.1111/jmcb.12988.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2023, "Forecasting with a panel Tobit model," Quantitative Economics, Econometric Society, volume 14, issue 1, pages 117-159, January, DOI: 10.3982/QE1505.
• Szydlo, Jan, 2023, "Forecasting Credit Dynamics : VAR, VECM or modern Factor-Augmented VAR approach?," Warwick-Monash Economics Student Papers, Warwick Monash Economics Student Papers, number 63.
• Christian Pierdzioch & Sebastian Rohloff & Roland Von Campe, 2023, "On the Predictive Value of the (Shadow) Real Interest Rate for the Realized Volatility of Gold-Price Returns," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., volume 18, issue 01, pages 1-16, March, DOI: 10.1142/S2010495222410019.
• Marc S. Paolella & PaweÅ‚ Polak, 2023, "Density and Risk Prediction with Non-Gaussian COMFORT Models," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., volume 18, issue 01, pages 1-37, March, DOI: 10.1142/S2010495222500336.
• Francisca Mendonça Souza & Claudia Aline de Souza Ramser & Adriano Mendonça Souza & Claudimar Pereira da Veiga, 2023, "Spillover Effects in the Presence of Structural Breaks, Persistence and Conditioned Heteroscedasticity," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., volume 18, issue 02, pages 1-51, June, DOI: 10.1142/S2010495222500348.
• Fazlul Miah, 2023, "News And Information Rigidity: Further Evidence From Gdp Growth Forecasts," Global Economy Journal (GEJ), World Scientific Publishing Co. Pte. Ltd., volume 23, issue 01n04, pages 1-21, December, DOI: 10.1142/S2194565924500039.
• Mohamad Hassan Shahrour & Mostafa Dekmak, 2023, "Intelligent stock prediction: A neural network approach," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., volume 10, issue 01, pages 1-14, March, DOI: 10.1142/S2424786322500165.
• Bolin Lei & Yuping Song, 2023, "The impact of contagion effects of media reports, investors’ sentiment and attention on the stock market based on HAR-RV model," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., volume 10, issue 02, pages 1-54, June, DOI: 10.1142/S242478632350010X.
• Sanjeev Kadam & Anshul Agrawal & Aryan Bajaj & Rachit Agarwal & Rameesha Kalra & Jaymin Shah, 2023, "Predicting Crude Oil Future Price Using Traditional and Artificial Intelligence-Based Model: Comparative Analysis," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., volume 14, issue 03, pages 1-15, October, DOI: 10.1142/S179399332350014X.
• Alexander Correa, 2023, "Predicting Business Bankruptcy in Colombian SMEs: A Machine Learning Approach," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., volume 14, issue 03, pages 1-21, October, DOI: 10.1142/S1793993323500278.
• Benedict Foo & Deng Yao Koh & Juan Pang Tan & Wenjie Wang, 2023, "FORECASTING SINGAPORE’s ECONOMY USING STATISTICAL LEARNING AND FACTOR MODELS," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., volume 68, issue 02, pages 319-353, DOI: 10.1142/S0217590822500655.
• Qu Feng & Shihao Zhou, 2023, "Electricity Market Liberalization And Efficiency: Evidence From Singapore," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., volume 68, issue 03, pages 651-669, June, DOI: 10.1142/S0217590822500667.
• Young Bin Ahn & Yoichi Tsuchiya, 2023, "Directional Accuracy Of Singapore’S Macroeconomic Forecasts," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., volume 68, issue 05, pages 1569-1583, September, DOI: 10.1142/S0217590819500541.
• Arabinda Basistha & Richard Startz, 2023, "Measuring Persistent Global Economic Factors with Output, Commodity Price, and Commodity Currency Data," Working Papers, Department of Economics, West Virginia University, number 23-05, Oct.
• Xin Jing & Jin Seo Cho, 2023, "Forecasting the Confirmed COVID-19 Cases Using Modal Regression," Working papers, Yonsei University, Yonsei Economics Research Institute, number 2023rwp-217, Jun.
• Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023, "Shadow-rate VARs," Discussion Papers, Deutsche Bundesbank, number 14/2023.
• Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2023, "Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany," Discussion Papers, Deutsche Bundesbank, number 34/2023.
• Barkan, Oren & Benchimol, Jonathan & Caspi, Itamar & Cohen, Eliya & Hammer, Allon & Koenigstein, Noam, 2023, "Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 39, issue 3, pages 1145-1162, DOI: 10.1016/j.ijforecast.2022.04.009.
• Stempel, Daniel & Zahner, Johannes, 2023, "Whose inflation rates matter most? A DSGE model and machine learning approach to monetary policy in the Euro area," IMFS Working Paper Series, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), number 188.
• Baumgärtner, Martin & Zahner, Johannes, 2023, "Whatever it takes to understand a central banker: Embedding their words using neural networks," IMFS Working Paper Series, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), number 194.
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Sardone, Alessandro & Schult, Christoph & Schultz, Birgit & Zeddies, Götz, 2023, "Grüne Transformation und Schuldenbremse: Implikationen zusätzlicher Investitionen für öffentliche Finanzen und privaten Konsum," Konjunktur aktuell, Halle Institute for Economic Research (IWH), volume 11, issue 4, pages 141-159.
• Frank, Johannes, 2023, "Forecasting realized volatility in turbulent times using temporal fusion transformers," FAU Discussion Papers in Economics, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, number 03/2023.
• Born, Benjamin & Enders, Zeno & Menkhoff, Manuel & Müller, Gernot J. & Niemann, Knut, 2023, "Firm expectations and news: Micro v macro," Working Papers, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin, number 43, DOI: 10.18452/26901.
• Billio, Monica & Casarin, Roberto & Costola, Michele & Veggente, Veronica, 2023, "Learning from experts: Energy efficiency in residential buildings," SAFE Working Paper Series, Leibniz Institute for Financial Research SAFE, number 403, DOI: 10.2139/ssrn.4596682.
• Ganics, Gergely & Mertens, Elmar & Clark, Todd E., 2023, "What Is the Predictive Value of SPF Point and Density Forecasts?," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage", Verein für Socialpolitik / German Economic Association, number 277622.
• Stempel, Daniel & Zahner, Johannes, 2023, "Whose Inflation Rates Matter Most? A DSGE Model and Machine Learning Approach to Monetary Policy in the Euro Area," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage", Verein für Socialpolitik / German Economic Association, number 277627.
• Holtemöller, Oliver & Kozyrev, Boris, 2023, "Forecasting Economic Activity with a Neural Network in Uncertain Times: Monte Carlo Evidence and Application to German GDP," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage", Verein für Socialpolitik / German Economic Association, number 277688.
• Strunz, Franziska & Gödl, Maximilian, 2023, "An Evaluation of Professional Forecasts for the German Economy," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage", Verein für Socialpolitik / German Economic Association, number 277707.
• Conrad, Christian & Lahiri, Kajal, 2023, "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 23-062.
• Janßen, Rebecca & Ribar, Matthew K., 2023, "In vi(vi)no veritas? Expertise, review accuracy and reputation inflation," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 23-075.
• Iva Tolic Mandic & Sanja Tisma & Daniela Angelina Jelincic & Damir Demonja, 2023, "Smart Solutions for Sustainable Tourism Pearls: How to Live Between Culture and Tourism in Dubrovnik," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 21, issue 3, pages 272-296.
• Gert Bijnens & Shyngys Karimov & Jozef Konings, 2023, "Does Automatic Wage Indexation Destroy Jobs? A Machine Learning Approach," De Economist, Springer, volume 171, issue 1, pages 85-117, March, DOI: 10.1007/s10645-023-09418-y.
• Ines Fortin & Jaroslava Hlouskova & Leopold Sögner, 2023, "Financial and economic uncertainties and their effects on the economy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, volume 50, issue 2, pages 481-521, May, DOI: 10.1007/s10663-023-09570-3.
• Ying Fan & Abdullah Yavas, 2023, "Price Dynamics in Public and Private Commercial Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, volume 67, issue 1, pages 150-190, July, DOI: 10.1007/s11146-020-09773-6.
• Benjamin Monnery & François-Charles Wolff, 2023, "Is participatory democracy in line with social protest? Evidence from the French Yellow Vests movement," Public Choice, Springer, volume 197, issue 1, pages 283-309, October, DOI: 10.1007/s11127-023-01105-5.
• Maxim Ulrich & Lukas Zimmer & Constantin Merbecks, 2023, "Implied volatility surfaces: a comprehensive analysis using half a billion option prices," Review of Derivatives Research, Springer, volume 26, issue 2, pages 135-169, October, DOI: 10.1007/s11147-023-09195-5.
• Noora Alzayed & Rasol Eskandari & Hassan Yazdifar, 2023, "Bank failure prediction: corporate governance and financial indicators," Review of Quantitative Finance and Accounting, Springer, volume 61, issue 2, pages 601-631, August, DOI: 10.1007/s11156-023-01158-z.
• Misik, Sándor, 2023, "Korrelációbecslés a forintpiacon
  [Correlation forecasting on the Hungarian forint market]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), volume 0, issue 7, pages 772-794, DOI: 10.18414/KSZ.2023.7-8.772.
• Kristóf, Tamás & Márton, András & Fiáth, Attila, 2023, "Állami energiavállalatok pénzügyi teljesítménye Magyarországon a koronavírus-járvány előtt és alatt
  [Financial performance of publicly owned energy companies in Hungary before and during the COVID ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), volume 0, issue 10, pages 1057-1076, DOI: 10.18414/KSZ.2023.10.1057.
• Chaoyi Chen & Yiguo Sun & Yao Rao, 2023, "Threshold MIDAS Forecasting of Inflation Rate," Working Papers, University of Liverpool, Department of Economics, number 202314, Jul.
• Lorena Skufi & Adam Geršl, 2023, "Using Macrofinancial Models to Simulate Macroeconomic Developments During the COVID-19 Pandemic: The Case of Albania," Eastern European Economics, Taylor & Francis Journals, volume 61, issue 5, pages 517-553, September, DOI: 10.1080/00128775.2023.2215229.
• Gabor Szigel & Boldizsar Istvan Gyurus, 2023, "Are Default Rate Time Series Stationary? A Practical Approach for Banking Experts," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), volume 22, issue 4, pages 107-135.
• Viola Monostoriné Grolmusz, 2023, "Optimal Forecast Combination Under Asymmetric Loss and Regime-Switching," MNB Working Papers, Magyar Nemzeti Bank (Central Bank of Hungary), number 2023/3.
• Viola Monostoriné Grolmusz, 2023, "Recovering Stock Analysts’ Loss Functions from Buy/Sell Recommendations," MNB Working Papers, Magyar Nemzeti Bank (Central Bank of Hungary), number 2023/4.
• Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023, "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 1/23.
• Chaya Weerasinghe & Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2023, "ABC-based Forecasting in State Space Models," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 12/23.
• George Athanasopoulos & Rob J Hyndman & Raffaele Mattera, 2023, "Improving out-of-sample Forecasts of Stock Price Indexes with Forecast Reconciliation and Clustering," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 17/23.
• David T. Frazier & Ryan Covey & Gael M. Martin & Donald S. Poskitt, 2023, "Solving the Forecast Combination Puzzle," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 18/23.
• Heather Anderson & Jiti Gao & Farshid Vahid & Wei Wei & Yang Yang, 2023, "Does Climate Sensitivity Differ Across Regions?," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 7/23.
• George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Anastasios Panagiotelis, 2023, "Forecast Reconciliation: A Review," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 8/23.
• Kris Boud & Arno De Block & Geert Langenus & Peter Reusens, 2023, "Nowcasting GDP through the lens of economic states," Working Paper Research, National Bank of Belgium, number 445, Dec.
• Monica P. Bhatt & Sara B. Heller & Max Kapustin & Marianne Bertrand & Christopher Blattman, 2023, "Predicting and Preventing Gun Violence: An Experimental Evaluation of READI Chicago," NBER Working Papers, National Bureau of Economic Research, Inc, number 30852, Jan.
• Menzie D. Chinn & Baptiste Meunier & Sebastian Stumpner, 2023, "Nowcasting World Trade with Machine Learning: a Three-Step Approach," NBER Working Papers, National Bureau of Economic Research, Inc, number 31419, Jun.
• Luca Gemmi & Rosen Valchev, 2023, "Biased Surveys," NBER Working Papers, National Bureau of Economic Research, Inc, number 31607, Aug.
• Bryan T. Kelly & Semyon Malamud & Mohammad Pourmohammadi & Fabio Trojani, 2023, "Universal Portfolio Shrinkage," NBER Working Papers, National Bureau of Economic Research, Inc, number 32004, Dec.
• Rasstrigin, M. & Kitaev, A. & Pleshackova, E., 2023, "Forecasting spending on orphan diseases to maintain the long-run financial sustainability of healthcare system," Journal of the New Economic Association, New Economic Association, volume 59, issue 2, pages 120-141, DOI: 10.31737/22212264_2023_2_120-141.
• Mirko Ðukic, Iva Krsmanovic, Miodrag Petkovic & Mirko Ðukic & Iva Krsmanovic & Miodrag Petkovic, 2023, "Nowcasting inflation using prices from the web," Working Papers Bulletin, National Bank of Serbia, number 16, Mar.
• Gunnar BÃ¥rdsen & Ragnar Nymoen, 2023, "Dynamic time series modelling and forecasting of COVID-19 in Norway," Working Paper Series, Department of Economics, Norwegian University of Science and Technology, number 19623, May.
• Oana Chindris-Vasioiu, 2023, "The RDI System in Romania as Compared to Other Member States of The European Union," Global Economic Observer, "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences;Institute for World Economy of the Romanian Academy, volume 11, issue 1, pages 32-39, May.
• Marion Devaux & Alexandra Aldea & Aliénor Lerouge & Marina Dorfmuller Ciampi & Michele Cecchini, 2023, "Évaluation du programme national de lutte contre le tabagisme en France," OECD Health Working Papers, OECD Publishing, number 155, Jun, DOI: 10.1787/b656e9ac-fr.
• Annabelle Mourougane & Polina Knutsson & Rodrigo Pazos & Julia Schmidt & Francesco Palermo, 2023, "Nowcasting trade in value added indicators," OECD Statistics Working Papers, OECD Publishing, number 2023/03, Sep, DOI: 10.1787/00f8aff7-en.
• Kitti Fodor, 2023, "Decision Tree Or Logistic Regression - Which Basic Model Is Better?," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, volume 32, issue 2, pages 67-75, December.
• Ramaharo, Franck Maminirina & Rasolofomanana, Gerzhino H, 2023, "Nowcasting Madagascar's real GDP using machine learning algorithms," AfricArxiv, Center for Open Science, number vpuac, Dec, DOI: 10.31219/osf.io/vpuac.
• Bhatt, Monica & Heller, Sara & Kapustin, Max & Bertrand, Marianne & Blattman, Christopher, 2023, "Predicting and Preventing Gun Violence: An Experimental Evaluation of READI Chicago," SocArXiv, Center for Open Science, number dks29, Jan, DOI: 10.31219/osf.io/dks29.
• Kibrom A Abay & Nishant Yonzan & Sikandra Kurdi & Kibrom Tafere, 2023, "Revisiting Poverty Trends and the Role of Social Protection Systems in Africa during the COVID-19 Pandemic," Journal of African Economies, Centre for the Study of African Economies, volume 32, issue Supplemen, pages 44-68.
• Seok Young Hong & Ingmar Nolte & Stephen J Taylor & Xiaolu Zhao, 2023, "Volatility Estimation and Forecasts Based on Price Durations," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 1, pages 106-144.
• Sander Barendse & Erik Kole & Dick van Dijk, 2023, "Backtesting Value-at-Risk and Expected Shortfall in the Presence of Estimation Error," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 2, pages 528-568.
• Shenyi Pan & Harry Joe & Guofu Li, 2023, "Conditional Inferences Based on Vine Copulas with Applications to Credit Spread Data of Corporate Bonds," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 3, pages 714-741.
• Uwe Hassler & Marc-Oliver Pohle, 2023, "Forecasting under Long Memory," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 3, pages 742-778.
• Tobias Hartl & Roland Jucknewitz, 2023, "Multivariate Fractional Components Analysis," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 3, pages 880-914.
• Razvan Pascalau & Ryan Poirier, 2023, "Increasing the information content of realized volatility forecasts," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 4, pages 1064-1098.
• Eleftheria Kafousaki & Stavros Degiannakis, 2023, "Forecasting VIX: the illusion of forecast evaluation criteria," Economics and Business Letters, Oviedo University Press, volume 12, issue 3, pages 231-240.
• Faten Ben Bouheni & Manish Tewari, 2023, "Common risk factors and risk–return trade-off for REITs and treasuries," Journal of Asset Management, Palgrave Macmillan, volume 24, issue 5, pages 374-395, September, DOI: 10.1057/s41260-023-00309-0.
• Massimo Ferrari Minesso & Laura Lebastard & Helena Mezo, 2023, "Text-Based Recession Probabilities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, volume 71, issue 2, pages 415-438, June, DOI: 10.1057/s41308-022-00177-5.
• Yan Carrière-Swallow & José Marzluf, 2023, "Macrofinancial Causes of Optimism in Growth Forecasts," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, volume 71, issue 2, pages 509-537, June, DOI: 10.1057/s41308-022-00187-3.
• Egidio Palmieri & Enrico Fioravante Geretto, 2023, "From Theory to Practice: Discussion and Managerial Implications," Palgrave Macmillan Studies in Banking and Financial Institutions, Palgrave Macmillan, chapter 0, "Adapting to Change", DOI: 10.1007/978-3-031-50265-1_5.
• Hyungsik Roger Moon & Frank Schorfheide & Boyuan Zhang, 2023, "Bayesian Estimation of Panel Models under Potentially Sparse Heterogeneity," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 23-017, Oct.
• Vancsura, László & Bareith, Tibor, 2023, "Analysis of the performance of predictive models during Covid-19 and the Russian-Ukrainian war," Public Finance Quarterly, Corvinus University of Budapest, volume 69, issue 2, pages 118-132, DOI: https://doi.org/10.35551/PFQ_2023_2.
• Karamanis, Dimitrios & Kechrinioti, Alexandra, 2023, "The Greek-Turkish rivalry: A Bayesian VAR approach," MPRA Paper, University Library of Munich, Germany, number 116827, Mar.
• Mohajan, Devajit & Mohajan, Haradhan, 2023, "Sensitivity Analysis between Lagrange Multipliers and Consumer Budget: Utility Maximization Case," MPRA Paper, University Library of Munich, Germany, number 116907, Feb, revised 19 Feb 2023.
• Andrianady, Josué R., 2023, "Comparing Econometric Models for Forecasting GDP in Madagascar," MPRA Paper, University Library of Munich, Germany, number 116911.
• Andrianady, Josué R., 2023, "Crunching the Numbers: A Comparison of Econometric Models for GDP Forecasting in Madagascar," MPRA Paper, University Library of Munich, Germany, number 116916.
• Mohajan, Devajit & Mohajan, Haradhan, 2023, "Sensitivity Analysis for Utility Maximization: A Study on Lagrange Multipliers and Commodity Coupons," MPRA Paper, University Library of Munich, Germany, number 117077, Jan, revised 06 Jan 2023.
• Gutierrez-Lythgoe, Antonio, 2023, "Movilidad urbana sostenible: Predicción de demanda con Inteligencia Artificial
  [Sustainable Urban Mobility: Demand Prediction with Artificial Intelligence]," MPRA Paper, University Library of Munich, Germany, number 117103, Apr.
• Mohajan, Devajit & Mohajan, Haradhan, 2023, "Sensitivity Analysis of Inputs of an Organization: A Profit Maximization Exploration," MPRA Paper, University Library of Munich, Germany, number 117121, Mar, revised 12 Mar 2023.
• Fantazzini, Dean, 2023, "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models," MPRA Paper, University Library of Munich, Germany, number 117141.
• Gutierrez-Lythgoe, Antonio, 2023, "Autoempleo y Machine Learning: Una aplicación para España
  [Self-employment and Machine Learning: An application for Spain]," MPRA Paper, University Library of Munich, Germany, number 117275, May.
• Mohajan, Devajit & Mohajan, Haradhan, 2023, "Mathematical Model for Nonlinear Budget Constraint: Economic Activities on Increased Budget," MPRA Paper, University Library of Munich, Germany, number 117299, Mar, revised 17 Mar 2023.
• Mohajan, Devajit & Mohajan, Haradhan, 2023, "A Study on Nonlinear Budget Constraint of a Local Industrial Firm of Bangladesh: A Profit Maximization Investigation," MPRA Paper, University Library of Munich, Germany, number 117324, Mar, revised 27 Mar 2023.
• Mohajan, Devajit & Mohajan, Haradhan, 2023, "Economic Investigation of Lagrange Multiplier if Cost of Inputs and Budget Size of a Firm Increase: A Profit Maximization Endeavor," MPRA Paper, University Library of Munich, Germany, number 117993, May, revised 07 May 2023.
• Mohajan, Devajit & Mohajan, Haradhan, 2023, "Effects of Various Inputs for Increased Interest Rate of Capital: A Nonlinear Budget Constraint Consideration," MPRA Paper, University Library of Munich, Germany, number 118134, May, revised 06 May 2023.
• Mohajan, Devajit & Mohajan, Haradhan, 2023, "An Economical Study When Cost of Irregular Raw Materials of an Industry Increases for Nonlinear Budget Constraint," MPRA Paper, University Library of Munich, Germany, number 118176, May, revised 05 May 2023.
• Arnold, Rob, 2023, "Uniform Confidence/Certainty Estimation," MPRA Paper, University Library of Munich, Germany, number 118234, Aug.
• Mohajan, Devajit, 2023, "Ponderal Index: An Important Anthropometric Indicator for Physical Growth," MPRA Paper, University Library of Munich, Germany, number 118334, Feb, revised 13 Feb 2023.
• Olkhov, Victor, 2023, "Economic complexity limits accuracy of price probability predictions by gaussian distributions," MPRA Paper, University Library of Munich, Germany, number 118373, Aug.
• Fantazzini, Dean & Xiao, Yufeng, 2023, "Detecting Pump-and-Dumps with Crypto-Assets: Dealing with Imbalanced Datasets and Insiders’ Anticipated Purchases," MPRA Paper, University Library of Munich, Germany, number 118435.
• Lee, David, 2023, "Default Forecasting and Credit Valuation Adjustment," MPRA Paper, University Library of Munich, Germany, number 118578, Sep.
• Polbin, Andrey & Shumilov, Andrei, 2023, "Прогнозирование Инфляции В России С Помощью Tvp-Модели С Байесовским Сжатием Параметров
  [Forecasting inflation in Russia using a TVP model with Bayesian shrinkage]," MPRA Paper, University Library of Munich, Germany, number 118650.
• Josué, ANDRIANADY & M. Randriamifidy, Fitiavana & H. P. Ranaivoson, Michel & Miora Steffanie, Thierry, 2023, "Econometric Analysis and Forecasting of Madagascar’s Economy: An ARIMAX Approach," MPRA Paper, University Library of Munich, Germany, number 118763.
• Mohajan, Devajit, 2023, "Mathematical Analysis of an Industry When Cost of Principal Raw Materials Increase: A Nonlinear Budget Constraint Attempt," MPRA Paper, University Library of Munich, Germany, number 118933, Jun.
• Elshin, Leonid & Mikhalevich, Polina, 2023, "Транснациональные Цепочки Поставок И Их Роль В Формировании Добавленной Стоимости Региона (На Примере Республики Татарстан)
  [Transnational supply chains and their role in creating value added in th," MPRA Paper, University Library of Munich, Germany, number 118969, Jun.
• Ardia, David & Dufays, Arnaud & Ordás Criado, Carlos, 2023, "Linking Frequentist and Bayesian Change-Point Methods," MPRA Paper, University Library of Munich, Germany, number 119486, Dec.
• Liu, Jia & Maheu, John M & Song, Yong, 2023, "Identification and Forecasting of Bull and Bear Markets using Multivariate Returns," MPRA Paper, University Library of Munich, Germany, number 119515.
• Aknouche, Abdelhakim & Gouveia, Sonia & Scotto, Manuel, 2023, "Random multiplication versus random sum: auto-regressive-like models with integer-valued random inputs," MPRA Paper, University Library of Munich, Germany, number 119518, Dec, revised 18 Dec 2023.
• Salisu, Afees & Salisu, Sulaiman & Salisu, Subair, 2023, "A news-based economic policy uncertainty index for Nigeria," MPRA Paper, University Library of Munich, Germany, number 119539, Apr, revised 13 Aug 2023.
• Ramaharo, Franck M. & Rasolofomanana, Gerzhino H., 2023, "Nowcasting Madagascar's real GDP using machine learning algorithms," MPRA Paper, University Library of Munich, Germany, number 119574, Dec.
• Andriantomanga, Zo, 2023, "The role of survey-based expectations in real-time forecasting of US inflation," MPRA Paper, University Library of Munich, Germany, number 119904, Nov.
• Pal, Hemendra, 2023, "The Impact of Russia-Ukraine conflict on Global Commodity Brent Crude Prices," MPRA Paper, University Library of Munich, Germany, number 124770, Aug, revised 02 Oct 2024.
• Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2023, "Drivers of Realized Volatility for South Africa (and the BRIC Countries): Fundamentals versus Sentiment," Working Papers, University of Pretoria, Department of Economics, number 202303, Feb.
• Afees A. Salisu & Riza Demirer & Rangan Gupta, 2023, "Technological Shocks and Stock Market Volatility Over a Century: A GARCH-MIDAS Approach," Working Papers, University of Pretoria, Department of Economics, number 202308, Apr.
• Rangan Gupta & Yuvana Jaichand & Christian Pierdzioch & Renee van Eyden, 2023, "Realized Stock-Market Volatility of the United States and the Presidential Approval Rating," Working Papers, University of Pretoria, Department of Economics, number 202311, May.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2023, "Forecasting the Realized Volatility of Agricultural Commodity Prices: Does Sentiment Matter?," Working Papers, University of Pretoria, Department of Economics, number 202316, May.
• Rangan Gupta & Qiang Ji & Christian Pierdzioch & Vasilios Plakandaras, 2023, "Forecasting the Conditional Distribution of Realized Volatility of Oil Price Returns: The Role of Skewness over 1859 to 2023," Working Papers, University of Pretoria, Department of Economics, number 202318, Jun.
• Rangan Gupta & Savanah Hall & Christian Pierdzioch, 2023, "Realized Stock Market Volatility of the United States: The Role of Employee Sentiment," Working Papers, University of Pretoria, Department of Economics, number 202319, Jul.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2023, "Financial Stress and Realized Volatility: The Case of Agricultural Commodities," Working Papers, University of Pretoria, Department of Economics, number 202320, Jul.
• Afees A. Salisu & Wenting Liao & Rangan Gupta & Oguzhan Cepni, 2023, "Economic Conditions and Predictability of US Stock Returns Volatility: Local Factor versus National Factor in a GARCH-MIDAS Model," Working Papers, University of Pretoria, Department of Economics, number 202323, Aug.
• Rangan Gupta & Joshua Nielsen & Christian Pierdzioch, 2023, "Stock Market Bubbles and the Realized Volatility of Oil Price Returns," Working Papers, University of Pretoria, Department of Economics, number 202325, Aug.
• Kejin Wu & Sayar Karmakar & Rangan Gupta & Christian Pierdzioch, 2023, "Climate Risks and Stock Market Volatility Over a Century in an Emerging Market Economy: The Case of South Africa," Working Papers, University of Pretoria, Department of Economics, number 202326, Sep.
• Afees A. Salisu & Rangan Gupta & Oguzhan Cepni & Petre Caraiani, 2023, "Oil Shocks and State-Level Stock Market Volatility of the United States: A GARCH-MIDAS Approach," Working Papers, University of Pretoria, Department of Economics, number 202327, Sep.
• Ryan Shackleton & Sonali Das & Rangan Gupta, 2023, "Comparing Risk Profiles of International Stock Markets as Functional Data: COVID-19 versus the Global Financial Crisis," Working Papers, University of Pretoria, Department of Economics, number 202328, Sep.
• Santino Del Fava & Rangan Gupta & Christian Pierdzioch & Lavinia Rognone, 2023, "Forecasting International Financial Stress: The Role of Climate Risks," Working Papers, University of Pretoria, Department of Economics, number 202329, Sep.
• Afees A. Salisu & Rangan Gupta & Oguzhan Cepni, 2023, "Housing Market Variables and Predictability of State-Level Stock Market Volatility of the United States: Evidence from a GARCH-MIDAS Approach," Working Papers, University of Pretoria, Department of Economics, number 202330, Sep.
• Afees A. Salisu & Ahamuefula E. Ogbonna & Rangan Gupta & Elie Bouri, 2023, "Energy-Related Uncertainty and International Stock Market Volatility," Working Papers, University of Pretoria, Department of Economics, number 202336, Dec.
• Matteo Foglia & Vasilios Plakandaras & Rangan Gupta & Elie Bouri, 2023, "Multi-Layer Spillovers between Volatility and Skewness in International Stock Markets Over a Century of Data: The Role of Disaster Risks," Working Papers, University of Pretoria, Department of Economics, number 202337, Dec.
• Ruipeng Liu & Mawuli Segnon & Oguzhan Cepni & Rangan Gupta, 2023, "Forecasting Volatility of Commodity, Currency, and Stock Markets: Evidence from Markov Switching Multifractal Models," Working Papers, University of Pretoria, Department of Economics, number 202340, Dec.
• Srecko Devjak, 2023, "Corporate Liquidity in Coronacrisis: Experience of Serbian Economy," Central European Business Review, Prague University of Economics and Business, volume 2023, issue 1, pages 1-20, DOI: 10.18267/j.cebr.311.
• İsmail Cakmak & Selcen Öztürk, 2023, "Analysing Impact of Economic Crises on Sector Profits with a New Approach," Prague Economic Papers, Prague University of Economics and Business, volume 2023, issue 3, pages 225-245, DOI: 10.18267/j.pep.827.
• António Rua & Nuno Lourenço & João Quelhas, 2023, "Navigating with a compass: Charting the course of underlying inflation," Working Papers, Banco de Portugal, Economics and Research Department, number w202317.
• Michael P. Clements & Shixuan Wang, 2023, "Do Professional Forecasters' Phillips Curves Incorporate the Beliefs of Others?," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2023-05, Feb.
• Stepan Gogolev & Evgeniy Ozhegov, 2023, "Asymmetric loss function in product-level sales forecasting: An empirical comparison," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 70, pages 109-121.