Research classified by Journal of Economic Literature (JEL) codes

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Top JEL
/ C: Mathematical and Quantitative Methods
/ / C5: Econometric Modeling
/ / / C53: Forecasting and Prediction Models; Simulation Methods

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This JEL code is mentioned in the following RePEc Biblio entries:

1. > Econometrics > Forecasting

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This topic is covered by the following reading lists:

1. SOEP based publications
2. Socio-Economics of Innovation

2023

• Mihail Yanchev, 2023. "Uncertainty - Definition and Classification for the Task of Economic Forecasting," Bulgarian Economic Papers bep-2023-03, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, revised Mar 2023.
• Laura Felber & Simon Beyeler, 2023. "Nowcasting economic activity using transaction payments data," Working Papers 2023-01, Swiss National Bank.
• Christoph Hanck & Martin C. Arnold, 2023. "Hierarchical Bayes modelling of penalty conversion rates of Bundesliga players," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 177-204, March.
• Georgios Fatouros & Georgios Makridis & Dimitrios Kotios & John Soldatos & Michael Filippakis & Dimosthenis Kyriazis, 2023. "DeepVaR: a framework for portfolio risk assessment leveraging probabilistic deep neural networks," Digital Finance, Springer, vol. 5(1), pages 29-56, March.
• Brian Colgan, 2023. "EU-SILC and the potential for synthetic panel estimates," Empirical Economics, Springer, vol. 64(3), pages 1247-1280, March.
• Fumio Hayashi & Yuta Tachi, 2023. "Nowcasting Japan’s GDP," Empirical Economics, Springer, vol. 64(4), pages 1699-1735, April.
• Jan Niederreiter, 2023. "Broadening Economics in the Era of Artificial Intelligence and Experimental Evidence," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(1), pages 265-294, March.
• Paul M. Torrens, 2023. "Agent models of customer journeys on retail high streets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(1), pages 87-128, January.
• Zouheir Mighri & Raouf Jaziri, 2023. "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 41-97, March.
• Rudrani Bhattacharya & Bornali Bhandari & Sudipto Mundle, 2023. "Nowcasting India’s Quarterly GDP Growth: A Factor-Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 213-234, March.
• 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, vol. 57(2), pages 1673-1699, April.
• Matthias Breuer & Harm H. Schütt, 2023. "Accounting for uncertainty: an application of Bayesian methods to accruals models," Review of Accounting Studies, Springer, vol. 28(2), pages 726-768, June.
• 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, vol. 128(6), pages 3313-3335, June.
• 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, vol. 159(1), pages 1-10, December.
• Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-33, December.
• 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, vol. 3(1), pages 1-32, January.
• Pami Dua & Rajiv Ranjan & Deepika Goel, 2023. "Forecasting the INR/USD Exchange Rate: A BVAR Framework," Springer Books, in: Pami Dua (ed.), Macroeconometric Methods, chapter 0, pages 183-224, Springer.
• 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, vol. 24(1), pages 111-122, January.
  • Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2021. "Investor Confidence and Forecastability of US Stock Market Realized Volatility : Evidence from Machine Learning," Working Papers 202118, University of Pretoria, Department of Economics.
• Daan Opschoor & Dick van Dijk, 2023. "Slow Expectation-Maximization Convergence in Low-Noise Dynamic Factor Models," Tinbergen Institute Discussion Papers 23-018/III, Tinbergen Institute.
• Dietrich, Stephan & Malerba, Daniele & Gassmann, Franziska, 2023. "Predicting social assistance beneficiaries," MERIT Working Papers 2023-007, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
• 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 2023-05, Faculty of Economic Sciences, University of Warsaw.
• Konrad Lewszyk & Piotr Wójcik, 2023. "Modelling Subjective Attractiveness," Working Papers 2023-06, Faculty of Economic Sciences, University of Warsaw.
• Pablo Guerróon‐Quintana & Molin Zhong, 2023. "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 295-320, April.
  • Pablo Guerrón-Quintana & Molin Zhong, 2017. "Macroeconomic Forecasting in Times of Crises," Finance and Economics Discussion Series 2017-018, Board of Governors of the Federal Reserve System (U.S.).
• 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., vol. 42(2), pages 331-346, March.
  • William Barnett & Sohee Park, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202120, University of Kansas, Department of Economics, revised Oct 2021.
  • Barnett, William & Park, Sohee, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," MPRA Paper 110298, University Library of Munich, Germany.
• 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., vol. 42(3), pages 514-529, April.
  • Stephen G. Hall & George S. Tavlas & Yongli Wang, 2022. "Forecasting Inflation: The Use of Dynamic Factor Analysis and Nonlinear Combinations," Discussion Papers 22-12, Department of Economics, University of Birmingham.
  • Stephen G. Hall & George S. Tavlas & Yongli Wang, 2023. "Forecasting inflation: the use of dynamic factor analysis and nonlinear combinations," Working Papers 314, Bank of Greece.
• Carlos Cañizares Martínez & Gabe J. de Bondt & Arne Gieseck, 2023. "Forecasting housing investment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 543-565, April.
  • Martínez, Carlos Cañizares & de Bondt, Gabe & Gieseck, Arne, 2023. "Forecasting housing investment," Working Paper Series 2807, European Central Bank.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2023. "Forecasting with a panel Tobit model," Quantitative Economics, Econometric Society, vol. 14(1), pages 117-159, January.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," NBER Working Papers 26569, National Bureau of Economic Research, Inc.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2021. "Forecasting with a Panel Tobit Model," Papers 2110.14117, arXiv.org, revised Jul 2022.
• 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., vol. 18(01), pages 1-16, March.
• 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., vol. 18(01), pages 1-37, March.
• 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., vol. 18(02), pages 1-51, June.
• 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., vol. 10(01), pages 1-14, March.
• 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., vol. 10(02), pages 1-54, June.
• 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., vol. 68(02), pages 319-353.
• Frank, Johannes, 2023. "Forecasting realized volatility in turbulent times using temporal fusion transformers," FAU Discussion Papers in Economics 03/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
• Hyeongwoo Kim & Jisoo Son, 2023. "Forecasting Net Charge-Off Rates of Large U.S. Bank Holding Companies using Macroeconomic Latent Factors," Auburn Economics Working Paper Series auwp2023-02, Department of Economics, Auburn University.
• Petra E. Todd & Kenneth I. Wolpin, 2023. "The Best of Both Worlds: Combining Randomized Controlled Trials with Structural Modeling," Journal of Economic Literature, American Economic Association, vol. 61(1), pages 41-85, March.
• Sanjay Kumar SINGH & Shivendra Sanjay SINGH & Vijay Lakshmi SINGH, 2023. "Predicting Adoption of Next Generation Digital Technology Utilizing the Adoption-Diffusion Model Fit: The Case of Mobile Payments Interface in an Emerging Economy," Access Journal, Access Press Publishing House, vol. 4(1), pages 130-148, October.
• Aysun Kapucugil Ikiz & Gizem Halil Utma, 2023. "Combined Forecasts of Intermittent Demand for Stock-keeping Units (SKUs)," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 9(1), pages 1-31, June.
• Gonzalo, Jesús & Pitarakis, Jean-Yves, 2020. "Out of sample predictability in predictive regressions with many predictor candidates," UC3M Working papers. Economics 31554, Universidad Carlos III de Madrid. Departamento de Economía.
  • Jesus Gonzalo & Jean-Yves Pitarakis, 2023. "Out of Sample Predictability in Predictive Regressions with Many Predictor Candidates," Papers 2302.02866, arXiv.org.
• Marta Crispino & Vincenzo Mariani, 2023. "A tool to nowcast tourist overnight stays with payment data and complementary indicators," Questioni di Economia e Finanza (Occasional Papers) 746, Bank of Italy, Economic Research and International Relations Area.
• Juan Pablo Cote-Barón & Karen L. Pulido-Mahecha & Nicol Valeria Rodríguez-Rodríguez & Carlos D. Rojas-Martínez, 2023. "El ISAE: Un Indicador para Monitorear la Actividad Económica Colombiana en Alta Frecuencia," Borradores de Economia 1225, Banco de la Republica de Colombia.
• Konstantin Boss & Andre Groeger & Tobias Heidland & Finja Krueger & Conghan Zheng, 2023. "Forecasting Bilateral Refugee Flows with High-dimensional Data and Machine Learning Techniques," Working Papers 1387, Barcelona School of Economics.
• Anton Votinov & Samvel Lazaryan & Yulia Polshchikova, 2023. "The Impact of the Cross-Sectoral Economic Structure on the Properties of DSGE Models," Russian Journal of Money and Finance, Bank of Russia, vol. 82(1), pages 32-54, March.
• Christina Anderl & Guglielmo Maria Caporale, 2023. "Forecasting inflation with a zero lower bound or negative interest rates: Evidence from point and density forecasts," Manchester School, University of Manchester, vol. 91(3), pages 171-232, June.
  • Christina Anderl & Guglielmo Maria Caporale, 2022. "Forecasting Inflation with a Zero Lower Bound or Negative Interest Rates: Evidence from Point and Density Forecasts," CESifo Working Paper Series 9687, CESifo.
• 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., vol. 42(3), pages 514-529, April.
  • Stephen G. Hall & George S. Tavlas & Yongli Wang, 2022. "Forecasting Inflation: The Use of Dynamic Factor Analysis and Nonlinear Combinations," Discussion Papers 22-12, Department of Economics, University of Birmingham.
  • Stephen G. Hall & George S. Tavlas & Yongli Wang, 2023. "Forecasting inflation: the use of dynamic factor analysis and nonlinear combinations," Working Papers 314, Bank of Greece.
• Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Working Papers 317, Bank of Greece.
• Stavros Degiannakis & George Filis & Grigorios Siourounis & Lorenzo Trapani, 2023. "Superkurtosis," Working Papers 318, Bank of Greece.
• Liu-Evans Gareth, 2023. "Improving the Estimation and Predictions of Small Time Series Models," Journal of Time Series Econometrics, De Gruyter, vol. 15(1), pages 1-26, January.
• Doojav Gan-Ochir & Luvsannyam Davaajargal, 2023. "Forecasting Inflation in Mongolia: A Dynamic Model Averaging Approach," Journal of Time Series Econometrics, De Gruyter, vol. 15(1), pages 27-48, January.
  • Doojav, Gan-Ochir & Luvsannyam, Davaajargal, 2017. "Forecasting inflation in Mongolia: A dynamic model averaging approach," MPRA Paper 102602, University Library of Munich, Germany.
• Abbara Omar & Zevallos Mauricio, 2023. "Estimation and forecasting of long memory stochastic volatility models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(1), pages 1-24, February.
• Martina Jakob & Sebastian Heinrich, 2023. "Measuring Human Capital with Social Media Data and Machine Learning," University of Bern Social Sciences Working Papers 46, University of Bern, Department of Social Sciences.
• Congressional Budget Office, 2023. "The Accuracy of CBO’s Budget Projections for Fiscal Year 2022," Reports 58603, Congressional Budget Office.
• Congressional Budget Office, 2023. "An Evaluation of CBO’s Projections of Outlays From 1984 to 2021," Reports 58613, Congressional Budget Office.
• Constantin Bürgi, 2023. "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series 10203, CESifo.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Globalization Institute Working Papers 394, Federal Reserve Bank of Dallas, revised 18 Jan 2023.
  • Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," CESifo Working Paper Series 10223, CESifo.
• Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  • Robert Lehmann & Ida Wikman, 2023. "Quarterly GDP Estimates for the German States: New Data for Business Cycle Analyses and Long-Run Dynamics," CESifo Working Paper Series 10280, CESifo.
  • Lehmann, Robert & Wikman, Ida, 2022. "Quarterly GDP Estimates for the German States," MPRA Paper 112642, University Library of Munich, Germany.
• Robert Lehmann, 2023. "READ-GER: Introducing German Real-Time Regional Accounts Data for Revision Analysis and Nowcasting," CESifo Working Paper Series 10315, CESifo.
• Kajal Lahiri & Cheng Yang, 2023. "ROC and PRC Approaches to Evaluate Recession Forecasts," CESifo Working Paper Series 10449, CESifo.
• Mohana Mondal & Michael P. Cameron & Jacques Poot, 2023. "Towards a Dynamic Spatial Microsimulation Model for Projecting Auckland’s Spatial Distribution of Ethnic Groups," CReAM Discussion Paper Series 2303, Centre for Research and Analysis of Migration (CReAM), Department of Economics, University College London.
• Christopher E.S. WARBURTON & Jared PEMBERTON, 2023. "Volatile Financial Conditions, Asset Prices, and Investment Decisions: Analysis of daily data of DJIA and S&P500, from January to April of 2022," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 23(1), pages 101-124.
• Germann, Maximilian & Kusmierczyk, Piotr & Puyo, Christelle, 2023. "Results of the 2022 climate risk stress test of the Eurosystem balance sheet," Economic Bulletin Boxes, European Central Bank, vol. 2.
• Burban, Valentin & Schupp, Fabian, 2023. "Backcasting real interest rates and inflation expectations – combining market-based measures with historical data for related variables," Economic Bulletin Boxes, European Central Bank, vol. 2.
• Warne, Anders, 2023. "DSGE model forecasting: rational expectations vs. adaptive learning," Working Paper Series 2768, European Central Bank.
• Carlos Cañizares Martínez & Gabe J. de Bondt & Arne Gieseck, 2023. "Forecasting housing investment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 543-565, April.
  • Martínez, Carlos Cañizares & de Bondt, Gabe & Gieseck, Arne, 2023. "Forecasting housing investment," Working Paper Series 2807, European Central Bank.
• Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
• Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
• Mungo, Luca & Lafond, François & Astudillo-Estévez, Pablo & Farmer, J. Doyne, 2023. "Reconstructing production networks using machine learning," Journal of Economic Dynamics and Control, Elsevier, vol. 148(C).
  • Lafond, François & Farmer, J. Doyne & Mungo, Luca & Astudillo-Estévez, Pablo, 2022. "Reconstructing production networks using machine learning," INET Oxford Working Papers 2022-02, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, revised Jan 2023.
• Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023. "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
• Shintani, Mototsugu & Ueda, Kozo, 2023. "Identifying the source of information rigidities in the expectations formation process," Journal of Economic Dynamics and Control, Elsevier, vol. 150(C).
  • Mototsugu Shintani & Kozo Ueda, 2021. "Identifying the source of information rigidities in the expectations formation process," CAMA Working Papers 2021-48, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Mototsugu Shintani & Kozo Ueda, 2021. "Identifying the Source of Information Rigidities in the Expectations Formation Process," CARF F-Series CARF-F-516, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
• Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
• Arango-Castillo, Lenin & Orraca, María José & Molina, G. Stefano, 2023. "The global component of headline and core inflation in emerging market economies and its ability to improve forecasting performance," Economic Modelling, Elsevier, vol. 120(C).
• Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2023. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Economic Modelling, Elsevier, vol. 120(C).
• Ojeda-Joya, Jair & Romero, José Vicente, 2023. "Global uncertainty shocks and exchange-rate expectations in Latin America," Economic Modelling, Elsevier, vol. 120(C).
• Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
• Yu, Dan & Chen, Chuang & Wang, Yudong & Zhang, Yaojie, 2023. "Hedging pressure momentum and the predictability of oil futures returns," Economic Modelling, Elsevier, vol. 121(C).
• Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
• Zhao, Shangwei & Xie, Tian & Ai, Xin & Yang, Guangren & Zhang, Xinyu, 2023. "Correcting sample selection bias with model averaging for consumer demand forecasting," Economic Modelling, Elsevier, vol. 123(C).
• Yan, Wan-Lin, 2023. "Stock index futures price prediction using feature selection and deep learning," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
• Li, Houjian & Zhou, Deheng & Hu, Jiayu & Li, Junwen & Su, Mengying & Guo, Lili, 2023. "Forecasting the realized volatility of Energy Stock Market: A multimodel comparison," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
• Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2023. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Journal of Econometrics, Elsevier, vol. 232(1), pages 52-69.
  • Florian Huber & Gary Koop & Luca Onorante & Michael Pfarrhofer & Josef Schreiner, 2020. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Papers 2008.12706, arXiv.org, revised Dec 2020.
  • Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Working Papers 2021-01, Joint Research Centre, European Commission.
  • Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Working Paper Series 2510, European Central Bank.
• Hounyo, Ulrich & Lahiri, Kajal, 2023. "Estimating the variance of a combined forecast: Bootstrap-based approach," Journal of Econometrics, Elsevier, vol. 232(2), pages 445-468.
• Ding, Yashuang (Dexter), 2023. "A simple joint model for returns, volatility and volatility of volatility," Journal of Econometrics, Elsevier, vol. 232(2), pages 521-543.
• Blasques, F. & Francq, Christian & Laurent, Sébastien, 2023. "Quasi score-driven models," Journal of Econometrics, Elsevier, vol. 234(1), pages 251-275.
• Lippi, Marco & Deistler, Manfred & Anderson, Brian, 2023. "High-Dimensional Dynamic Factor Models: A Selective Survey and Lines of Future Research," Econometrics and Statistics, Elsevier, vol. 26(C), pages 3-16.
• Zakharenko, Roman, 2023. "Pricing shared vehicles," Economics of Transportation, Elsevier, vol. 33(C).
• Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
  • Samad Sarferaz & Andreas Dibiasi, 2020. "Measuring Macroeconomic Uncertainty: A Cross-Country Analysis," KOF Working papers 20-479, KOF Swiss Economic Institute, ETH Zurich.
• Khalfaoui, Rabeh & Hammoudeh, Shawkat & Rehman, Mohd Ziaur, 2023. "Spillovers and connectedness among BRICS stock markets, cryptocurrencies, and uncertainty: Evidence from the quantile vector autoregression network," Emerging Markets Review, Elsevier, vol. 54(C).
• Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
• Nonejad, Nima, 2023. "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 91-122.
• Ferrer Fernández, María & Henry, Ólan & Pybis, Sam & Stamatogiannis, Michalis P., 2023. "Can we forecast better in periods of low uncertainty? The role of technical indicators," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 1-12.
• Degiannakis, Stavros & Filis, George, 2023. "Oil price assumptions for macroeconomic policy," Energy Economics, Elsevier, vol. 117(C).
  • Degiannakis, Stavros & Filis, George, 2020. "Oil price assumptions for macroeconomic policy," MPRA Paper 100705, University Library of Munich, Germany.
• Blazsek, Szabolcs & Escribano, Alvaro, 2023. "Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts," Energy Economics, Elsevier, vol. 118(C).
  • Blazsek, Szabolcs & Escribano, Álvaro, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
• Galarneau-Vincent, Rémi & Gauthier, Geneviève & Godin, Frédéric, 2023. "Foreseeing the worst: Forecasting electricity DART spikes," Energy Economics, Elsevier, vol. 119(C).
• Qu, Hui & Li, Guo, 2023. "Multi-perspective investor attention and oil futures volatility forecasting," Energy Economics, Elsevier, vol. 119(C).
• Li, Jingpeng & Umar, Muhammad & Huo, Jiale, 2023. "The spillover effect between Chinese crude oil futures market and Chinese green energy stock market," Energy Economics, Elsevier, vol. 119(C).
• Sohag, Kazi & Hassan, M. Kabir & Bakhteyev, Stepan & Mariev, Oleg, 2023. "Do green and dirty investments hedge each other?," Energy Economics, Elsevier, vol. 120(C).
• Grothe, Oliver & Kächele, Fabian & Krüger, Fabian, 2023. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Energy Economics, Elsevier, vol. 120(C).
• Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2023. "Asymmetry and interdependence when evaluating U.S. Energy Information Administration forecasts," Energy Economics, Elsevier, vol. 121(C).
• Panarello, Demetrio & Gatto, Andrea, 2023. "Decarbonising Europe – EU citizens’ perception of renewable energy transition amidst the European Green Deal," Energy Policy, Elsevier, vol. 172(C).
• Zhang, Yaojie & He, Mengxi & Wen, Danyan & Wang, Yudong, 2023. "Forecasting crude oil price returns: Can nonlinearity help?," Energy, Elsevier, vol. 262(PB).
• Kuang, Wei, 2023. "The equity-oil hedge: A comparison between volatility and alternative risk frameworks," Energy, Elsevier, vol. 271(C).
• Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
• Zhang, Ning & Su, Xiaoman & Qi, Shuyuan, 2023. "An empirical investigation of multiperiod tail risk forecasting models," International Review of Financial Analysis, Elsevier, vol. 86(C).
• Ghosh, Indranil & Alfaro-Cortés, Esteban & Gámez, Matías & García-Rubio, Noelia, 2023. "Prediction and interpretation of daily NFT and DeFi prices dynamics: Inspection through ensemble machine learning & XAI," International Review of Financial Analysis, Elsevier, vol. 87(C).
• Citterio, Alberto & King, Timothy, 2023. "The role of Environmental, Social, and Governance (ESG) in predicting bank financial distress," Finance Research Letters, Elsevier, vol. 51(C).
• Ghosh, Indranil & Alfaro-Cortés, Esteban & Gámez, Matías & García, Noelia, 2023. "Do travel uncertainty and invasion rhetoric spur Metaverse financial asset? – Gauging the role of media influence," Finance Research Letters, Elsevier, vol. 51(C).
• Yamani, Ehab, 2023. "The informational role of fund flow in the profitable predictability of mutual funds," Finance Research Letters, Elsevier, vol. 51(C).
• Díaz-Mendoza, Ana Carmen & Pardo, Ángel, 2023. "Water and traditional asset classes," Finance Research Letters, Elsevier, vol. 52(C).
• Cheng, Tingting & Jiang, Shan & Zhao, Albert Bo & Jia, Zhimin, 2023. "Complete subset averaging methods in corporate bond return prediction," Finance Research Letters, Elsevier, vol. 54(C).
• Gupta, Rangan & Nel, Jacobus & Salisu, Afees A. & Ji, Qiang, 2023. "Predictability of economic slowdowns in advanced countries over eight centuries: The role of climate risks," Finance Research Letters, Elsevier, vol. 54(C).
• Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and realized volatility of major commodity currency exchange rates," Journal of Financial Markets, Elsevier, vol. 62(C).
  • Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Climate Risks and Realized Volatility of Major Commodity Currency Exchange Rates," Working Papers 202210, University of Pretoria, Department of Economics.
• Engel, Charles & Wu, Steve Pak Yeung, 2023. "Forecasting the U.S. Dollar in the 21st Century," Journal of International Economics, Elsevier, vol. 141(C).
  • Wu, Steve Pak Yeung, 2021. "Forecasting the U.S. Dollar in the 21st Century," CEPR Discussion Papers 15915, C.E.P.R. Discussion Papers.
  • Charles Engel & Steve Pak Yeung Wu, 2021. "Forecasting the U.S. Dollar in the 21st Century," NBER Working Papers 28447, National Bureau of Economic Research, Inc.
• Dang, Ou & Feng, Mingbin & Hardy, Mary R., 2023. "Two-stage nested simulation of tail risk measurement: A likelihood ratio approach," Insurance: Mathematics and Economics, Elsevier, vol. 108(C), pages 1-24.
• Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
• Fortin, Alain-Philippe & Simonato, Jean-Guy & Dionne, Georges, 2023. "Forecasting expected shortfall: Should we use a multivariate model for stock market factors?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 314-331.
  • Fortin, Alain-Philippe & Simonato, Jean-Guy & Dionne, Georges, 2018. "Forecasting Expected Shortfall: Should we use a Multivariate Model for Stock Market Factors?," Working Papers 18-4, HEC Montreal, Canada Research Chair in Risk Management, revised 25 Jun 2021.
• Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
  • Bańbura, Marta & Bobeica, Elena, 2020. "Does the Phillips curve help to forecast euro area inflation?," Working Paper Series 2471, European Central Bank.
• Haase, Felix & Neuenkirch, Matthias, 2023. "Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US," International Journal of Forecasting, Elsevier, vol. 39(2), pages 587-605.
  • Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Working Paper Series 2020-03, University of Trier, Research Group Quantitative Finance and Risk Analysis.
  • Felix Haase & Matthias Neuenkirch, 2021. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," CESifo Working Paper Series 8828, CESifo.
  • Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
• Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023. "Testing the predictive accuracy of COVID-19 forecasts," International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
  • Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2020. "Testing the predictive accuracy of COVID-19 forecasts," Discussion Papers 20/10, Department of Economics, University of York.
  • Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2021. "Testing the predictive accuracy of COVID-19 forecasts," CAMA Working Papers 2021-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Olivares, Kin G. & Challu, Cristian & Marcjasz, Grzegorz & Weron, Rafał & Dubrawski, Artur, 2023. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," International Journal of Forecasting, Elsevier, vol. 39(2), pages 884-900.
  • Kin G. Olivares & Cristian Challu & Grzegorz Marcjasz & Rafal Weron & Artur Dubrawski, 2021. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," WORking papers in Management Science (WORMS) WORMS/21/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Krivorotov, George, 2023. "Machine learning-based profit modeling for credit card underwriting - implications for credit risk," Journal of Banking & Finance, Elsevier, vol. 149(C).
• Arai, Natsuki, 2023. "The FOMC’s new individual economic projections and macroeconomic theories," Journal of Banking & Finance, Elsevier, vol. 151(C).
• Lohmann, Christian & Möllenhoff, Steffen, 2023. "Dark premonitions: Pre-bankruptcy investor attention and behavior," Journal of Banking & Finance, Elsevier, vol. 151(C).
• Hall, Stephen G. & Tavlas, George S. & Wang, Yongli, 2023. "Drivers and spillover effects of inflation: The United States, the euro area, and the United Kingdom☆," Journal of International Money and Finance, Elsevier, vol. 131(C).
• Tafuro, Andrea, 2023. "Labour market rigidity and expansionary austerity," Journal of Macroeconomics, Elsevier, vol. 75(C).
• Demirel, Ufuk Devrim & Otterson, James, 2023. "Quantifying the uncertainty of long-term macroeconomic projections," Journal of Macroeconomics, Elsevier, vol. 75(C).
• Salisu, Afees A. & Adediran, Idris & Omoke, Philip C. & Tchankam, Jean Paul, 2023. "Gold and tail risks," Resources Policy, Elsevier, vol. 80(C).
• Swamy, Vighneswara & Lagesh, M.A., 2023. "Does happy Twitter forecast gold price?," Resources Policy, Elsevier, vol. 81(C).
• Fasanya, Ismail O. & Oyewole, Oluwatomisin J., 2023. "On the connection between international REITs and oil markets: The role of economic policy uncertainty," Resources Policy, Elsevier, vol. 81(C).
• Salisu, Afees A. & Ndako, Umar B. & Vo, Xuan Vinh, 2023. "Transition risk, physical risk, and the realized volatility of oil and natural gas prices," Resources Policy, Elsevier, vol. 81(C).
• Andres–Escayola, Erik & Berganza, Juan Carlos & Campos, Rodolfo G. & Molina, Luis, 2023. "A BVAR toolkit to assess macrofinancial risks in Brazil and Mexico," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(1).
  • Erik Andres-Escayola & Juan Carlos Berganza & Rodolfo Campos & Luis Molina, 2021. "A BVAR toolkit to assess macrofinancial risks in Brazil and Mexico," Occasional Papers 2114, Banco de España.
• Belhadj, Besma, 2023. "New fuzzy multiple regressions for the instantaneous and panel data “The determinants of Poverty in the Countries MENA”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
• Cronin, David & McInerney, Niall, 2023. "Official fiscal forecasts in EU member states under the European Semester and Fiscal Compact – An empirical assessment," European Journal of Political Economy, Elsevier, vol. 76(C).
• Demirer, Riza & Gupta, Rangan & Salisu, Afees A. & van Eyden, Reneé, 2023. "Firm-level business uncertainty and the predictability of the aggregate U.S. stock market volatility during the COVID-19 pandemic," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 295-302.
  • Riza Demirer & Rangan Gupta & Afees A. Salisu & Renee van Eyden, 2021. "Firm-level Business Uncertainty and the Predictability of the Aggregate U.S. Stock Market Volatility during the COVID-19 Pandemic," Working Papers 202157, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Gupta, Rangan & Bouri, Elie, 2023. "Testing the forecasting power of global economic conditions for the volatility of international REITs using a GARCH-MIDAS approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 303-314.
  • Afees A. Salisu & Rangan Gupta & Elie Bouri, 2022. "Testing the Forecasting Power of Global Economic Conditions for the Volatility of International REITs using a GARCH-MIDAS Approach," Working Papers 202211, University of Pretoria, Department of Economics.
• Zhang, Li & Wang, Lu & Peng, Lijuan & Luo, Keyu, 2023. "Measuring the response of clean energy stock price volatility to extreme shocks," Renewable Energy, Elsevier, vol. 206(C), pages 1289-1300.
• Yao, Youfu & Hong, Yun, 2023. "Can comment letters impact excess cash holdings? Evidence from China," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 900-922.
• Hong, Yanran & Yu, Jize & Su, Yuquan & Wang, Lu, 2023. "Southern oscillation: Great value of its trends for forecasting crude oil spot price volatility," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 358-368.
• Chen, Zhonglu & Zhang, Li & Weng, Chen, 2023. "Does climate policy uncertainty affect Chinese stock market volatility?," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 369-381.
• Liu, Xiaoqun & Zhang, Yuchen & Tian, Mengqiao & Chao, Youcong, 2023. "Financial distress and jump tail risk: Evidence from China's listed companies," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 316-336.
• Li, Xiafei & Guo, Qiang & Liang, Chao & Umar, Muhammad, 2023. "Forecasting gold volatility with geopolitical risk indices," Research in International Business and Finance, Elsevier, vol. 64(C).
• Liu, Yujun & Li, Zhongfei & Nekhili, Ramzi & Sultan, Jahangir, 2023. "Forecasting cryptocurrency returns with machine learning," Research in International Business and Finance, Elsevier, vol. 64(C).
• González, Marta Ramos & Ureña, Antonio Partal & Fernández-Aguado, Pilar Gómez, 2023. "Forecasting for regulatory credit loss derived from the COVID-19 pandemic: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 64(C).
• Mitze, Timo & Makkonen, Teemu, 2023. "Can large-scale RDI funding stimulate post-crisis recovery growth? Evidence for Finland during COVID-19," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
• Zhang, Ning & Gong, Yujing & Xue, Xiaohan, 2023. "Less disagreement, better forecasts: adjusted risk measures in the energy futures market," LSE Research Online Documents on Economics 118451, London School of Economics and Political Science, LSE Library.
• Alain Hecq & Elisa Voisin, 2023. "Predicting Crashes in Oil Prices During The Covid-19 Pandemic with Mixed Causal-Noncausal Models," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 209-233, Emerald Group Publishing Limited.
  • Alain Hecq & Elisa Voisin, 2019. "Predicting crashes in oil prices during the COVID-19 pandemic with mixed causal-noncausal models," Papers 1911.10916, arXiv.org, revised May 2022.
• Yoonseok Lee & Donggyu Sul, 2023. "Depth-weighted Forecast Combination: Application to COVID-19 Cases," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 235-260, Emerald Group Publishing Limited.
• Soumya Bhadury & Satadru Das & Saurabh Ghosh & Pawan Gopalakrishnan, 2023. "Impact of crude prices shock on GDP growth: using a linear, nonlinear and extreme value framework," Indian Growth and Development Review, Emerald Group Publishing Limited, vol. 16(1), pages 91-103, March.
• Mariusz Pyra, 2023. "A Scenario Analysis for the Decarbonisation Process in Poland’s Road Transport Sector," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 411-432.
• Gary Koop & Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon & Ping Wu, 2023. "Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting," Working Papers 23-09, Federal Reserve Bank of Cleveland.
• Bennett Schmanski & Chiara Scotti & Clara Vega, 2023. "Fed Communication, News, Twitter, and Echo Chambers," Finance and Economics Discussion Series 2023-036, Board of Governors of the Federal Reserve System (U.S.).
• Mary Chen & Matthew DeHaven & Isabel Kitschelt & Seung Jung Lee & Martin Sicilian, 2023. "Identifying Financial Crises Using Machine Learning on Textual Data," International Finance Discussion Papers 1374, Board of Governors of the Federal Reserve System (U.S.).
• Maximilian Ahrens & Deniz Erdemlioglu & Michael McMahon & Christopher J. Neely & Xiye Yang, 2023. "Mind Your Language: Market Responses to Central Bank Speeches," Working Papers 2023-013, Federal Reserve Bank of St. Louis.
• Thorsten Drautzburg, 2023. "A Structural Approach to Combining External and DSGE Model Forecasts," Working Papers 23-10, Federal Reserve Bank of Philadelphia.
• Boris I. Alekhin, 2023. "Interregional Differences in Inflation through the Prism of Ackley’s Theory," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 127006, Russia, issue 1, pages 8-25, February.
• Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2023. "Climate Risks and Forecasting Stock Market Returns in Advanced Economies over a Century," Mathematics, MDPI, vol. 11(9), pages 1-21, April.
  • Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and Forecasting Stock-Market Returns in Advanced Economies Over a Century," Working Papers 202183, University of Pretoria, Department of Economics.
• John B. Guerard & Dimitrios D. Thomakos & Foteini Kyriazi & Konstantinos Mamais, 2023. "On the Predictability of the DJIA and S&P500 Indices," Working Papers 2023-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• Watanabe, Toshiaki & Nakajima, Jouchi, 2023. "High-frequency realized stochastic volatility model," Discussion paper series HIAS-E-127, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
• Saurabh Ghosh & Abhishek Ranjan, 2023. "A Machine Learning Approach To Gdp Nowcasting: An Emerging Market Experience," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 26(Special I), pages 33-54.
• Maiti,Dibyendu & Khari,Bhavna, 2023. "Digitalisation, Governance and the Informal Sector," IDE Discussion Papers 898, Institute of Developing Economies, Japan External Trade Organization(JETRO).
• Haowen Bao & Zongwu Cai & Yuying Sun, 2023. "Penalized Model Averaging for High Dimensional Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202302, University of Kansas, Department of Economics, revised Jan 2023.
• Ruzhen Yan & Ding Yue & Xu Wu & Wei Gao, 2023. "Multiscale Multifractal Detrended Fluctuation Analysis and Trend Identification of Liquidity in the China's Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 487-511, February.
• Yushu Li & Hyunjoo Kim Karlsson, 2023. "Investigating the Asymmetric Behavior of Oil Price Volatility Using Support Vector Regression," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1765-1790, April.
• Jan G. De Gooijer, 2023. "Penalized Averaging of Quantile Forecasts from GARCH Models with Many Exogenous Predictors," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 407-424, June.
• Gert Bijnens & Shyngys Karimov & Jozef Konings, 2023. "Does Automatic Wage Indexation Destroy Jobs? A Machine Learning Approach," De Economist, Springer, vol. 171(1), pages 85-117, March.
• 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, vol. 50(2), pages 481-521, May.
• Ying Fan & Abdullah Yavas, 2023. "Price Dynamics in Public and Private Commercial Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 67(1), pages 150-190, July.
• Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in the 21st Century: A Modern Review," Papers 2212.03471, arXiv.org.
  • 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 1/23, Monash University, Department of Econometrics and Business Statistics.
• 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 30852, National Bureau of Economic Research, Inc.
• Gunnar BÃ¥rdsen & Ragnar Nymoen, 2023. "Dynamic time series modelling and forecasting of COVID-19 in Norway," Working Paper Series 19623, Department of Economics, Norwegian University of Science and Technology.
• Seok Young Hong & Ingmar Nolte & Stephen J Taylor & Xiaolu Zhao, 2023. "Volatility Estimation and Forecasts Based on Price Durations [Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 21(1), pages 106-144.
• Massimo Ferrari Minesso & Laura Lebastard & Helena Mezo, 2023. "Text-Based Recession Probabilities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 415-438, June.
• Yan Carrière-Swallow & José Marzluf, 2023. "Macrofinancial Causes of Optimism in Growth Forecasts," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 509-537, June.
• Karamanis, Dimitrios & Kechrinioti, Alexandra, 2023. "The Greek-Turkish rivalry: A Bayesian VAR approach," MPRA Paper 116827, University Library of Munich, Germany.
• Mohajan, Devajit & Mohajan, Haradhan, 2023. "Sensitivity Analysis between Lagrange Multipliers and Consumer Budget: Utility Maximization Case," MPRA Paper 116907, University Library of Munich, Germany, revised 19 Feb 2023.
• Andrianady, Josué R., 2023. "Comparing Econometric Models for Forecasting GDP in Madagascar," MPRA Paper 116911, University Library of Munich, Germany.
• Andrianady, Josué R., 2023. "Crunching the Numbers: A Comparison of Econometric Models for GDP Forecasting in Madagascar," MPRA Paper 116916, University Library of Munich, Germany.
• Mohajan, Devajit & Mohajan, Haradhan, 2023. "Sensitivity Analysis for Utility Maximization: A Study on Lagrange Multipliers and Commodity Coupons," MPRA Paper 117077, University Library of Munich, Germany, 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 117103, University Library of Munich, Germany.
• Mohajan, Devajit & Mohajan, Haradhan, 2023. "Sensitivity Analysis of Inputs of an Organization: A Profit Maximization Exploration," MPRA Paper 117121, University Library of Munich, Germany, revised 12 Mar 2023.
• Fantazzini, Dean, 2023. "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models," MPRA Paper 117141, University Library of Munich, Germany.
• Gutierrez-Lythgoe, Antonio, 2023. "Autoempleo y Machine Learning: Una aplicación para España [Self-employment and Machine Learning: An application for Spain]," MPRA Paper 117275, University Library of Munich, Germany.
• Mohajan, Devajit & Mohajan, Haradhan, 2023. "Mathematical Model for Nonlinear Budget Constraint: Economic Activities on Increased Budget," MPRA Paper 117299, University Library of Munich, Germany, 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 117324, University Library of Munich, Germany, revised 27 Mar 2023.
• Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2023. "Drivers of Realized Volatility for South Africa (and the BRIC Countries): Fundamentals versus Sentiment," Working Papers 202303, University of Pretoria, Department of Economics.
• Afees A. Salisu & Riza Demirer & Rangan Gupta, 2023. "Technological Shocks and Stock Market Volatility Over a Century: A GARCH-MIDAS Approach," Working Papers 202308, University of Pretoria, Department of Economics.
• 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 202311, University of Pretoria, Department of Economics.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2023. "Forecasting the Realized Volatility of Agricultural Commodity Prices: Does Sentiment Matter?," Working Papers 202316, University of Pretoria, Department of Economics.
• Srecko Devjak, 2023. "Corporate Liquidity in Coronacrisis: Experience of Serbian Economy," Central European Business Review, Prague University of Economics and Business, vol. 2023(1), pages 1-20.
• Michael P. Clements & Shixuan Wang, 2023. "Do Professional Forecasters' Phillips Curves Incorporate the Beliefs of Others?," Economics Discussion Papers em-dp2023-05, Department of Economics, University of Reading.

2022

• Liang, Chao & Umar, Muhammad & Ma, Feng & Huynh, Toan L.D., 2022. "Climate policy uncertainty and world renewable energy index volatility forecasting," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
• Liu Yang & Kajal Lahiri & Adrian Pagans, 2022. "Getting the ROC into Sync," CAMA Working Papers 2022-01, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• James Morley & Trung Duc Tran & Benjamin Wong, 2022. "A Simple Correction for Misspecification in Trend-Cycle Decompositions with an Application to Estimating r," CAMA Working Papers 2022-02, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Calonaci, Fabio & Kapetanios, George & Price, Simon, 2022. "Stock returns predictability with unstable predictors," Essex Finance Centre Working Papers 32331, University of Essex, Essex Business School.
  • Fabio Calonaci & George Kapetanios & Simon Price, 2022. "Stock returns predictability with unstable predictors," CAMA Working Papers 2022-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Ferrara, Laurent & Karadimitropoulou, Aikaterini & Triantafyllou, Athanasios, 2021. "Commodity price uncertainty comovement: Does it matter for global economic growth?," Essex Finance Centre Working Papers 30945, University of Essex, Essex Business School.
  • Laurent Ferrara & Aikaterini Karadimitropoulou & Athanasios Triantafyllou, 2022. "Commodity price uncertainty comovement: Does it matter for global economic growth?," CAMA Working Papers 2022-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Stephen Jarvis & Olivier Deschenes & Akshaya Jha, 2022. "The Private and External Costs of Germany’s Nuclear Phase-Out [“How Effective Was the UK Carbon Tax?—A Machine Learning Approach to Policy Evaluation.”]," Journal of the European Economic Association, European Economic Association, vol. 20(3), pages 1311-1346.
  • Stephen Jarvis & Olivier Deschenes & Akshaya Jha, 2019. "The Private and External Costs of Germany's Nuclear Phase-Out," NBER Working Papers 26598, National Bureau of Economic Research, Inc.
  • Jarvis, Stephen & Deschenes, Olivier & Jha, Akshaya, 2022. "The private and external costs of Germany’s nuclear phase-out," LSE Research Online Documents on Economics 113634, London School of Economics and Political Science, LSE Library.
• Ekaterina Oparina & Caspar Kaiser & Niccolo Gentile & Alexandre Tkatchenko & Andrew E. Clark & Jan-Emmanuel De Neve & Conchita D'Ambrosio, 2022. "Human wellbeing and machine learning," CEP Discussion Papers dp1863, Centre for Economic Performance, LSE.
  • Oparina, Ekaterina & Kaiser, Caspar & Gentile, Niccoló & Tkatchenko, Alexandre & Clark, Andrew E. & De Neve, Jan-Emmanuel & D'Ambrosio, Conchita, 2022. "Human wellbeing and machine learning," LSE Research Online Documents on Economics 117955, London School of Economics and Political Science, LSE Library.
  • Kaiser, Caspar & Oparina, Ekaterina & Gentile, Niccolò & Tkatchenko, Alexandre & Clark, Andrew E. & De Neve, Jan-Emmanuel & D’Ambrosio, Conchita, 2022. "Human Wellbeing and Machine Learning," INET Oxford Working Papers 2022-11, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
  • Ekaterina Oparina & Caspar Kaiser & Niccol`o Gentile & Alexandre Tkatchenko & Andrew E. Clark & Jan-Emmanuel De Neve & Conchita D'Ambrosio, 2022. "Human Wellbeing and Machine Learning," Papers 2206.00574, arXiv.org.
• Stephen Walker, 2022. "Erroneous Erratum to Accounting Fraud Article," Econ Journal Watch, Econ Journal Watch, vol. 19(2), pages 190–203-1, September.
• Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2022. "Smooth Robust Multi-Horizon Forecasts," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 143-165, Emerald Group Publishing Limited.
  • Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2020. "Smooth Robust Multi-Horizon Forecasts," Working Papers 2020-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2021. "Smooth Robust Multi-Horizon Forecasts," Economics Papers 2021-W01, Economics Group, Nuffield College, University of Oxford.
• Luca Nocciola, 2022. "Finite Sample Forecast Properties and Window Length Under Breaks in Cointegrated Systems," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 167-196, Emerald Group Publishing Limited.
  • Luca Nocciola, "undated". "Finite sample forecast properties and window length under breaks in cointegrated systems," Discussion Papers 19/07, University of Nottingham, Granger Centre for Time Series Econometrics.
• Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
• Xuan Liu & G. Cornelis van Kooten & Eric Martin Gerbrandt & Jun Duan, 2022. "Prospects for weather-indexed insurance for blueberry growers," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 83(2), pages 333-351, December.
• Davide Fiaschi & Cristina Tealdi, 2022. "Young people between education and the labour market during the COVID-19 pandemic in Italy," International Journal of Manpower, Emerald Group Publishing Limited, vol. 43(7), pages 1719-1757, July.
• Davide Fiaschi & Cristina Tealdi, 2022. "Young people between education and the labour market during the COVID-19 pandemic in Italy," International Journal of Manpower, Emerald Group Publishing Limited, vol. 43(7), pages 1719-1757, July.
  • Davide Fiaschi & Cristina Tealdi, 2021. "Young people between education and the labour market during the COVID-19 pandemic in Italy," Papers 2106.08296, arXiv.org.
  • Fiaschi, Davide & Tealdi, Cristina, 2021. "Young People between Education and the Labour Market during the COVID-19 Pandemic in Italy," IZA Discussion Papers 14479, Institute of Labor Economics (IZA).
• Fariq Rahadiyan Chalik & Taufik Faturohman & William A. Barnett & Bruno S. Sergi, 2022. "Customer Satisfaction of E-wallet User: An Adoption of Information System Success Model," International Symposia in Economic Theory and Econometrics, in: Quantitative Analysis of Social and Financial Market Development, volume 30, pages 61-83, Emerald Group Publishing Limited.
• Fariq Rahadiyan Chalik & Taufik Faturohman, 2022. "Customer Satisfaction of E-wallet User: An Adoption of Information System Success Model," International Symposia in Economic Theory and Econometrics, in: Quantitative Analysis of Social and Financial Market Development, volume 30, pages 61-83, Emerald Group Publishing Limited.
• Thi Thu Ha Nguyen & Salma Ibrahim & George Giannopoulos, 2022. "Detecting earnings management: a comparison of accrual and real earnings manipulation models," Journal of Applied Accounting Research, Emerald Group Publishing Limited, vol. 24(2), pages 344-379, August.
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• Urmat K. Dzhunkeev & Yury N. Perevyshin & Pavel V. Trunin & Maria I. Chembulatova, 2022. "Global Economic Development: Worsening Forecasts [Развитие Мировой Экономики: Ухудшение Прогнозов]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 9, pages 4-14, September.
• Urmat K. Dzhunkeev & Yury N. Perevyshin & Pavel V. Trunin & Maria I. Chembulatova, 2022. "Social and Economic Situation in G20 Countries: Outlooks are Getting Worse [Социально-Экономическое Положение В Странах G20: Прогнозы Ухудшаются]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 10, pages 4-12, October.
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• Morita, Hiroshi, 2022. "Forecasting GDP growth using stock returns in Japan: A factor-augmented MIDAS approach," Discussion paper series HIAS-E-118, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
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• Tsvetan Tsvetanov, 2022. "Tax Holidays and the Heterogeneous Pass-Through of Gasoline Taxes," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202219, University of Kansas, Department of Economics.
• Sanjay Kumar Rout & Hrushikesh Mallick, 2022. "Sovereign Bond Market Shock Spillover Over Different Maturities: A Journey from Normal to Covid-19 Period," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(4), pages 697-734, December.
• Michele Catalano & Emilia Pezzolla, 2022. "Global natural projections," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 49(4), pages 949-990, November.
• Ivan Faiella & Alessandro Mistretta, 2022. "The Net Zero Challenge for Firms’ Competitiveness," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(1), pages 85-113, September.
• Fabian Baier & Peter Berster & Marc Gelhausen, 2022. "Global cargo gravitation model: airports matter for forecasts," International Economics and Economic Policy, Springer, vol. 19(1), pages 219-238, February.
• E. Ezzahid & Z. Firano & J. Ennouhi & A. Laaroussi & A. Serghini Anbari, 2022. "Countries’ readiness to deal with large-scale crises: analysis, measure, and World classification," Policy Sciences, Springer;Society of Policy Sciences, vol. 55(3), pages 555-572, September.
• Chris Charalambous & Spiros H. Martzoukos & Zenon Taoushianis, 2022. "Estimating corporate bankruptcy forecasting models by maximizing discriminatory power," Review of Quantitative Finance and Accounting, Springer, vol. 58(1), pages 297-328, January.
• Yang Pang & Shimeng Shi & Yukun Shi & Yang Zhao, 2022. "A nonlinear dynamic approach to cash flow forecasting," Review of Quantitative Finance and Accounting, Springer, vol. 59(1), pages 205-237, July.
• Ludmila Fadejeva & Boriss Siliverstovs & Karlis Vilerts & Anete Brinke, 2022. "Consumer Spending in the Covid-19 Pandemic: Evidence from Card Transactions in Latvia," Discussion Papers 2022/01, Latvijas Banka.
• Andreas Marcus Gohs, 2022. "Forecasting Market Diffusion of Innovative Battery-Electric and Conventional Vehicles in Germany under Model Uncertainty," MAGKS Papers on Economics 202209, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Tino Berger & Christian Ochsner, 2022. "Tracking the German Business Cycle," MAGKS Papers on Economics 202212, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Daniel Stempel & Johannes Zahner, 2022. "DSGE Models and Machine Learning: An Application to Monetary Policy in the Euro Area," MAGKS Papers on Economics 202232, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Nico Peter Benjamin Wehrle, 2022. "The Cost of Renewable Electricity and Energy Storage in Germany," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 8(1), pages 19-41.
• Makram El-Shagi & Yizhuang Zheng, 2022. "Money Demand in China: A Meta Study," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 58(1), pages 145-163, January.
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• Rueben Ellul & Germano Ruisi, 2022. "Nowcasting the Maltese economy with a dynamic factor model," CBM Working Papers WP/02/2022, Central Bank of Malta.
• Andras Viktor Szabo, 2022. "Credit Risk Modelling of Mortgage Loans in the Supervisory Stress Test of the Magyar Nemzeti Bank," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 21(1), pages 56-94.
• Laszlo Bokor, 2022. "Climate Stress Test of the Hungarian Banking System," MNB Occasional Papers 2022/147, Magyar Nemzeti Bank (Central Bank of Hungary).
• Resce, Giuliano & Vaquero-Pineiro, Cristina, 2022. "Predicting Agri-food Quality across Space: A Machine Learning Model for the Acknowledgment of Geographical Indications," Economics & Statistics Discussion Papers esdp22082, University of Molise, Department of Economics.
• Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Papers 2012.11649, arXiv.org, revised Jun 2022.
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  • Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone In?ation and Real Interest Rates," PIER Working Paper Archive 21-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
• Richard B. Freeman, 2022. "Planning for the “Expected Unexpected”: Work and Retirement in the U.S. After the COVID-19 Pandemic Shock," NBER Working Papers 29653, National Bureau of Economic Research, Inc.
• Sara B. Heller & Benjamin Jakubowski & Zubin Jelveh & Max Kapustin, 2022. "Machine Learning Can Predict Shooting Victimization Well Enough to Help Prevent It," NBER Working Papers 30170, National Bureau of Economic Research, Inc.
• Edward E. Leamer, 2022. "A New Way of Forecasting Recessions," NBER Working Papers 30247, National Bureau of Economic Research, Inc.
• Yacine Aït-Sahalia & Jianqing Fan & Lirong Xue & Yifeng Zhou, 2022. "How and When are High-Frequency Stock Returns Predictable?," NBER Working Papers 30366, National Bureau of Economic Research, Inc.
• Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using hierarchical aggregation constraints to nowcast regional economic aggregates," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-04, Economic Statistics Centre of Excellence (ESCoE).
• Martin Weale & Paul Labonne, 2022. "Nowcasting in the presence of large measurement errors and revisions," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-05, Economic Statistics Centre of Excellence (ESCoE).
• Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
• George Kapetanios & Fotis Papailias, 2022. "Real Time Indicators During the COVID-19 Pandemic Individual Predictors & Selection," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-15, Economic Statistics Centre of Excellence (ESCoE).
• George Kapetanios & Fotis Papailias, 2022. "An Evaluation Framework for Targeted Indicators Aggregates vs. Disaggregates," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-17, Economic Statistics Centre of Excellence (ESCoE).
• George Kapetanios & Fotis Papailias, 2022. "A Quality Assessment Framework for Maintaining & Publishing New Indicators," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-18, Economic Statistics Centre of Excellence (ESCoE).
• Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Agency Forecasts," MPRA Paper 114325, University Library of Munich, Germany.
  • Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Agency Forecasts," National Institute of Economic and Social Research (NIESR) Discussion Papers 541, National Institute of Economic and Social Research.
• Mihaela Simionescu, 2022. "Macroeconomic Challenges for Life Insurance Market in the Baltic States," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 4, pages 647-660, December.
• Petar Rangelov, 2022. "Application of Simulation-based Approach for Determining the Value of Companies Operating in an Environment of Uncertainty," Ikonomiceski i Sotsialni Alternativi, University of National and World Economy, Sofia, Bulgaria, issue 1, pages 111-131, March.
• Andrew Binning, 2022. "An Efficient Application of the Extended Path Algorithm in Matlab with Examples," Treasury Working Paper Series 22/02, New Zealand Treasury.
• Grégoire Tallard & Marcel Adenäuer & Koen Deconinck & Gaëlle Gouarin, 2022. "Potential impact of dietary changes on the triple challenge facing food systems: Three stylised scenarios," OECD Food, Agriculture and Fisheries Papers 173, OECD Publishing.
• Stephen Jarvis & Olivier Deschenes & Akshaya Jha, 2022. "The Private and External Costs of Germany’s Nuclear Phase-Out [“How Effective Was the UK Carbon Tax?—A Machine Learning Approach to Policy Evaluation.”]," Journal of the European Economic Association, European Economic Association, vol. 20(3), pages 1311-1346.
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• Hannes Mueller & Christopher Rauh, 2022. "The Hard Problem of Prediction for Conflict Prevention [The World Uncertainty Index]," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2440-2467.
  • Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
  • Hannes Mueller & Christopher Rauh, 2021. "The Hard Problem of Prediction for Conflict Prevention," Working Papers 1244, Barcelona School of Economics.
  • Mueller, H. & Rauh, C., 2021. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2103, Faculty of Economics, University of Cambridge.
  • Mueller, H. & Rauh, C., 2020. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2015, Faculty of Economics, University of Cambridge.
  • Hannes Mueller & Christopher Rauh, 2019. "The Hard Problem of Prediction for Conflict Prevention," Cahiers de recherche 02-2019, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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• Richard Gerlach & Chao Wang, 2022. "Bayesian Semi-Parametric Realized Conditional Autoregressive Expectile Models for Tail Risk Forecasting [On the Estimation of Production Frontiers: Maximum Likelihood Estimation of the Parameters o," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 20(1), pages 105-138.
• Diaa Noureldin, 2022. "Volatility Prediction Using a Realized-Measure-Based Component Model [Modelling Volatility by Variance Decomposition]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 20(1), pages 76-104.
• Tim Bollerslev, 2022. "Realized Semi(co)variation: Signs That All Volatilities are Not Created Equal [Vulnerable Growth]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 20(2), pages 219-252.
• Young Min Kim & Kyu Ho Kang, 2022. "Bayesian Inference of Multivariate Regression Models with Endogenous Markov Regime-Switching Parameters [“Bayes Inference via Gibbs Sampling of Autoregressive Time-Series Subject to Markov Mean and," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 20(3), pages 391-436.
• Sebastian Bayer & Timo Dimitriadis, 2022. "Regression-Based Expected Shortfall Backtesting [Backtesting Expected Shortfall]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 20(3), pages 437-471.
• Rogier Quaedvlieg & Peter Schotman, 2022. "Hedging Long-Term Liabilities [Pricing the Term Structure with Linear Regressions]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 20(3), pages 505-538.
• Gianluca De Nard, 2022. "Oops! I Shrunk the Sample Covariance Matrix Again: Blockbuster Meets Shrinkage [Eigenvalue Ratio Test for the Number of Factors]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 20(4), pages 569-611.
• Yushuang Jiang & Emese Lazar, 2022. "Forecasting VIX Using Filtered Historical Simulation [A GARCH Option Pricing Model with Filtered Historical Simulation]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 20(4), pages 655-680.
• Arnaud Dufays & Elysee Aristide Houndetoungan & Alain Coën, 2022. "Selective Linear Segmentation for Detecting Relevant Parameter Changes [Risks and Portfolio Decisions Involving Hedge Funds]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 20(4), pages 762-805.
• Mikkel Bennedsen & Asger Lunde & Mikko S Pakkanen, 2022. "Decoupling the Short- and Long-Term Behavior of Stochastic Volatility [Multifactor Approximation of Rough Volatility Models]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 20(5), pages 961-1006.
• Martínez Vargas, Agustín María & Edilson Hernández, Marcos & Velásquez Cerón, Omar, 2022. "Evaluación de las decisiones financieras operacionales que generan flujo de caja en las MIPYMES [Evaluation of Operational Financial Decisions that Generate Cash Flow in Msmes]," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 34(1), pages 60-82, December.
• Philippe Dupuy & Jean-Charles Garibal, 2022. "Cross-dispersion bias-adjusted ESG rankings," Journal of Asset Management, Palgrave Macmillan, vol. 23(7), pages 631-643, December.
• Walid Mansour & Hechem Ajmi & Karima Saci, 2022. "Regulatory policies in the global Islamic banking sector in the outbreak of COVID-19 pandemic," Journal of Banking Regulation, Palgrave Macmillan, vol. 23(3), pages 265-287, September.
• Diebold, Francis X. & Göbel, Maximilian, 2022. "A benchmark model for fixed-target Arctic sea ice forecasting," Economics Letters, Elsevier, vol. 215(C).
  • Francis X. Diebold & Maximilian Gobel, 2021. "A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting," Papers 2101.10359, arXiv.org, revised Jan 2022.
  • Francis X. Diebold & Maximilian Gobel, 2022. "A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting," PIER Working Paper Archive 22-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Francis X. Diebold & Glenn D. Rudebusch & Maximilian Goebel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," Papers 2203.04040, arXiv.org, revised Nov 2022.
  • Francis X. Diebold & Glenn D. Rudebusch & Maximilian Gobel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," PIER Working Paper Archive 22-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Francis X. Diebold & Glenn D. Rudebusch & Maximilian Göbel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," NBER Working Papers 30732, National Bureau of Economic Research, Inc.
• Francis X. Diebold & Maximilian Goebel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice: Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," Papers 2206.10721, arXiv.org.
  • Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice:Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," PIER Working Paper Archive 22-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Katarina Kramarova & Lucia Svabova & Barbora Gabrikova, 2022. "Impacts of the Covid-19 crisis on unemployment in Slovakia: a statistically created counterfactual approach using the time series analysis," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(2), pages 343-389, June.
• Andrea Kolková & Petr Rozehnal, 2022. "Hybrid demand forecasting models: pre-pandemic and pandemic use studies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(3), pages 699-725, September.
• Beata Gavurova & Sylvia Jencova & Radovan Bacik & Marta Miskufova & Stanislav Letkovsky, 2022. "Artificial intelligence in predicting the bankruptcy of non-financial corporations," Oeconomia Copernicana, Institute of Economic Research, vol. 13(4), pages 1215-1251, December.
• Syed Ateeb Akhter Shah & Muhammad Ishtiaq & Sumbal Qureshi & Kaneez Fatima, 2022. "Inflation Forecasting for Pakistan in a Data-rich Environment (Article)," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 61(4), pages 643-658.
• Sonan Memon, 2022. "Inflation in Pakistan: High-Frequency Estimation and Forecasting," PIDE-Working Papers 2022:12, Pakistan Institute of Development Economics.
• Weshah Razzak, 2021. "The Ownership of Oil, Democracy, and Iraq's Past, Present and Future," Discussion Papers 2102, School of Economics and Finance, Massey University, New Zealand.
  • Razzak, Weshah, 2022. "The Ownership of Oil, Democracy, and Iraq’s Past, Present, and Future," MPRA Paper 111417, University Library of Munich, Germany.
• Pincheira, Pablo & Hardy, Nicolas, 2022. "Correlation Based Tests of Predictability," MPRA Paper 112014, University Library of Munich, Germany.
• Arikha, Dahlia, 2022. "Strategi Pembangunan Ekonomi Islam M. Umer Chapra [The Strategy of Islamic Economic Development in Perspective of M. Umer Chapra]," MPRA Paper 112257, University Library of Munich, Germany, revised 28 Feb 2022.
• G.K., Chetan Kumar & K.B., Rangappa & S., Suchitra, 2022. "Analyzing the Impact of Companies’ Investment on Skill Upgradation in Improving their Resilience amidst COVID-19," MPRA Paper 112425, University Library of Munich, Germany.
• Naimoli, Antonio, 2022. "The information content of sentiment indices for forecasting Value at Risk and Expected Shortfall in equity markets," MPRA Paper 112588, University Library of Munich, Germany.
• Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  • Lehmann, Robert & Wikman, Ida, 2022. "Quarterly GDP Estimates for the German States," MPRA Paper 112642, University Library of Munich, Germany.
  • Robert Lehmann & Ida Wikman, 2023. "Quarterly GDP Estimates for the German States: New Data for Business Cycle Analyses and Long-Run Dynamics," CESifo Working Paper Series 10280, CESifo.
• Li, Chenxing, 2022. "A multivariate GARCH model with an infinite hidden Markov mixture," MPRA Paper 112792, University Library of Munich, Germany.
• Dean Fantazzini, 2022. "Crypto-Coins and Credit Risk: Modelling and Forecasting Their Probability of Death," JRFM, MDPI, vol. 15(7), pages 1-34, July.
  • Fantazzini, Dean, 2022. "Crypto Coins and Credit Risk: Modelling and Forecasting their Probability of Death," MPRA Paper 113744, University Library of Munich, Germany.
• Anastasiou, Dimitris & Drakos, Konstantinos & Kapopoulos, Panayotis, 2022. "Predicting international tourist arrivals in Greece with a novel sector-specific business leading indicator," MPRA Paper 113860, University Library of Munich, Germany.
• G.K., Chetan Kumar & K.B., Rangappa & S., Suchitra, 2022. "Normative analysis of the impact of Covid-19 on prominent sectors of Indian economy by using ARCH Model," MPRA Paper 114027, University Library of Munich, Germany.
• Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Agency Forecasts," National Institute of Economic and Social Research (NIESR) Discussion Papers 541, National Institute of Economic and Social Research.
  • Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Agency Forecasts," MPRA Paper 114325, University Library of Munich, Germany.
• Cengiz, Doruk & Tekgüç, Hasan, 2022. "Counterfactual Reconciliation: Incorporating Aggregation Constraints For More Accurate Causal Effect Estimates," MPRA Paper 114478, University Library of Munich, Germany.
• Silva Lopes, Artur, 2022. "Feels Like Going Backwards: Assessing Income Convergence with a Long-Run Forecasting Approach," MPRA Paper 114488, University Library of Munich, Germany.
• Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
• Yang, Zixiu & Fantazzini, Dean, 2022. "Using crypto assets pricing methods to build technical oscillators for short-term bitcoin trading," MPRA Paper 115508, University Library of Munich, Germany.
• Mohajan, Devajit & Mohajan, Haradhan, 2022. "Importance of Total Coupon in Utility Maximization: A Sensitivity Analysis," MPRA Paper 115553, University Library of Munich, Germany, revised 17 Sep 2022.
• Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2023. "Asymmetry and interdependence when evaluating U.S. Energy Information Administration forecasts," Energy Economics, Elsevier, vol. 121(C).
  • Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Administration Forecasts," MPRA Paper 115559, University Library of Munich, Germany.
• Mohajan, Devajit & Mohajan, Haradhan, 2022. "Utility Maximization Analysis of an Organization: A Mathematical Economic Procedure," MPRA Paper 115791, University Library of Munich, Germany, revised 15 Oct 2022.
• Mohajan, Devajit & Mohajan, Haradhan, 2022. "Utility maximization analysis of an emerging firm: a bordered Hessian approach," MPRA Paper 115838, University Library of Munich, Germany, revised 25 Sep 2022.
• Mohajan, Devajit & Mohajan, Haradhan, 2022. "Mathematical Analysis of SEIR Model to Prevent COVID-19 Pandemic," MPRA Paper 115858, University Library of Munich, Germany, revised 25 Aug 2022.
• Mohajan, Devajit & Mohajan, Haradhan, 2022. "Sensitivity Analysis between Lagrange Multipliers and Consumer Coupon: Utility Maximization Perspective," MPRA Paper 116022, University Library of Munich, Germany, revised 16 Sep 2022.
• Jadidzadeh, Ali, 2022. "An Application of Smooth Transition Regression Models to Homeless Research," MPRA Paper 116356, University Library of Munich, Germany.
• Mohajan, Devajit & Mohajan, Haradhan, 2022. "Sensitivity Analysis between Commodity and Budget: Utility Maximization Case," MPRA Paper 116495, University Library of Munich, Germany, revised 20 Dec 2022.
• Mawuli Segnon & Rangan Gupta & Bernd Wilfling, 2022. "Forecasting Stock Market Volatility with Regime-Switching GARCH-MIDAS: The Role of Geopolitical Risks," Working Papers 202203, University of Pretoria, Department of Economics.
• Çepni, Oğuzhan & Gupta, Rangan & Pienaar, Daniel & Pierdzioch, Christian, 2022. "Forecasting the realized variance of oil-price returns using machine learning: Is there a role for U.S. state-level uncertainty?," Energy Economics, Elsevier, vol. 114(C).
  • Oguzhan Cepni & Rangan Gupta & Daniel Pienaar & Christian Pierdzioch, 2022. "Forecasting the Realized Variance of Oil-Price Returns Using Machine-Learning: Is there a Role for U.S. State-Level Uncertainty?," Working Papers 202205, University of Pretoria, Department of Economics.
• Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and realized volatility of major commodity currency exchange rates," Journal of Financial Markets, Elsevier, vol. 62(C).
  • Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Climate Risks and Realized Volatility of Major Commodity Currency Exchange Rates," Working Papers 202210, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Gupta, Rangan & Bouri, Elie, 2023. "Testing the forecasting power of global economic conditions for the volatility of international REITs using a GARCH-MIDAS approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 303-314.
  • Afees A. Salisu & Rangan Gupta & Elie Bouri, 2022. "Testing the Forecasting Power of Global Economic Conditions for the Volatility of International REITs using a GARCH-MIDAS Approach," Working Papers 202211, University of Pretoria, Department of Economics.
• Bouri, Elie & Christou, Christina & Gupta, Rangan, 2022. "Forecasting returns of major cryptocurrencies: Evidence from regime-switching factor models," Finance Research Letters, Elsevier, vol. 49(C).
  • Elie Bouri & Christina Christou & Rangan Gupta, 2022. "Forecasting Returns of Major Cryptocurrencies: Evidence from Regime-Switching Factor Models," Working Papers 202213, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2022. "Do Economic Conditions of U.S. States Predict the Realized Volatility of Oil-Price Returns? A Quantile Machine-Learning Approach," Working Papers 202216, University of Pretoria, Department of Economics.
• Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022. "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Energies, MDPI, vol. 15(22), pages 1-26, November.
  • Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022. "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Working Papers 202217, University of Pretoria, Department of Economics.
• David Gabauer & Rangan Gupta & Sayar Karmakar & Joshua Nielsen, 2022. "Stock Market Bubbles and the Forecastability of Gold Returns (and Volatility)," Working Papers 202228, University of Pretoria, Department of Economics.
• Elie Bouri & Rangan Gupta & Luca Rossini, 2022. "The Role of the Monthly ENSO in Forecasting the Daily Baltic Dry Index," Working Papers 202229, University of Pretoria, Department of Economics.
• Afees A. Salisu & Riza Demirer & Rangan Gupta, 2022. "Policy Uncertainty and Stock Market Volatility Revisited: The Predictive Role of Signal Quality," Working Papers 202232, University of Pretoria, Department of Economics.
• Rangan Gupta & Xiaojin Sun, 2022. "Time-Varying Parameter Four-Equation DSGE Model," Working Papers 202234, University of Pretoria, Department of Economics.
• Rangan Gupta & Jacobus Nel & Afees A. Salisu & Qiang Ji, 2022. "Predictability of Economic Slowdowns in Advanced Countries over Eight Centuries: The Role of Climate Risks," Working Papers 202237, University of Pretoria, Department of Economics.
• Hardik A. Marfatia & Rangan Gupta & Goodness C. Aye & Christian Pierdzioch, 2022. "Forecasting More than Three Centuries of Economic Growth of the United Kingdom: The Role of Climate Risks," Working Papers 202238, University of Pretoria, Department of Economics.
• Sayar Karmakar & Rangan Gupta & Oguzhan Cepni & Lavinia Rognone, 2022. "Climate Risks and Predictability of the Trading Volume of Gold: Evidence from an INGARCH Model," Working Papers 202241, University of Pretoria, Department of Economics.
• Jacobus Nel & Rangan Gupta & Mark E. Wohar & Christian Pierdzioch, 2022. "Climate Risks and Predictability of Commodity Returns and Volatility: Evidence from Over 750 Years of Data," Working Papers 202242, University of Pretoria, Department of Economics.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Climate Risks and State-Level Stock-Market Realized Volatility," Working Papers 202246, University of Pretoria, Department of Economics.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Business Applications and State-Level Stock Market Realized Volatility: A Forecasting Experiment," Working Papers 202247, University of Pretoria, Department of Economics.
• Oguzhan Cepni & Rangan Gupta & Wenting Liao & Jun Ma, 2022. "Climate Risks and Forecastability of the Weekly State-Level Economic Conditions of the United States," Working Papers 202251, University of Pretoria, Department of Economics.
• Oguzhan Cepni & Christina Christou & Rangan Gupta, 2022. "Forecasting National Recessions of the United States with State-Level Climate Risks: Evidence from Model Averaging in Markov-Switching Models," Working Papers 202252, University of Pretoria, Department of Economics.
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• Pawan Kumar Singh & Anushka Chouhan & Rajiv Kumar Bhatt & Ravi Kiran & Ansari Saleh Ahmar, 2022. "Implementation of the SutteARIMA method to predict short-term cases of stock market and COVID-19 pandemic in USA," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2023-2033, August.
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• Kishor, N. Kundan & Marfatia, Hardik A. & Nam, Gooan & Rizi, Majid Haghani, 2022. "The local employment effect of house prices: Evidence from U.S. States," Journal of Housing Economics, Elsevier, vol. 55(C).
• Degiannakis, Stavros & Filis, George, 2022. "Oil price volatility forecasts: What do investors need to know?," Journal of International Money and Finance, Elsevier, vol. 123(C).
  • Degiannakis, Stavros & Filis, George, 2019. "Oil price volatility forecasts: What do investors need to know?," MPRA Paper 94445, University Library of Munich, Germany.
• Casabianca, Elizabeth Jane & Catalano, Michele & Forni, Lorenzo & Giarda, Elena & Passeri, Simone, 2022. "A machine learning approach to rank the determinants of banking crises over time and across countries," Journal of International Money and Finance, Elsevier, vol. 129(C).
  • Elizabeth Jane Casabianca & Michele Catalano & Lorenzo Forni & Elena Giarda & Simone Passeri, 2019. "An Early Warning System for banking crises: From regression-based analysis to machine learning techniques," "Marco Fanno" Working Papers 0235, Dipartimento di Scienze Economiche "Marco Fanno".
• Dai, Peng-Fei & Xiong, Xiong & Duc Huynh, Toan Luu & Wang, Jiqiang, 2022. "The impact of economic policy uncertainties on the volatility of European carbon market," Journal of Commodity Markets, Elsevier, vol. 26(C).
• Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2022. "Common factors and the dynamics of cereal prices. A forecasting perspective," Journal of Commodity Markets, Elsevier, vol. 28(C).
  • Marek Kwas & Alessia Paccagnini & Michal Rubaszek, 2020. "Common factors and the dynamics of cereal prices. A forecasting perspective," CAMA Working Papers 2020-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Alfeus, Mesias & Nikitopoulos, Christina Sklibosios, 2022. "Forecasting volatility in commodity markets with long-memory models," Journal of Commodity Markets, Elsevier, vol. 28(C).
• Stolbov, Mikhail & Shchepeleva, Maria, 2022. "Modeling global real economic activity: Evidence from variable selection across quantiles," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
• Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
• Salisu, Afees A. & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil prices over 150 years: The role of tail risks," Resources Policy, Elsevier, vol. 75(C).
  • Afees A. Salisu & Rangan Gupta & Qiang Ji, 2021. "Forecasting Oil Price over 150 Years: The Role of Tail Risks," Working Papers 202120, University of Pretoria, Department of Economics.
• Yan, Xiang & Bai, Jiancheng & Li, Xiafei & Chen, Zhonglu, 2022. "Can dimensional reduction technology make better use of the information of uncertainty indices when predicting volatility of Chinese crude oil futures?," Resources Policy, Elsevier, vol. 75(C).
• Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
  • Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," GRU Working Paper Series GRU_2021_017, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
  • Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," Working Papers 202133, University of Pretoria, Department of Economics.
• Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
• Gupta, Rangan & Pierdzioch, Christian & Salisu, Afees A., 2022. "Oil-price uncertainty and the U.K. unemployment rate: A forecasting experiment with random forests using 150 years of data," Resources Policy, Elsevier, vol. 77(C).
  • Rangan Gupta & Christian Pierdzioch & Afees A. Salisu, 2020. "Oil-Price Uncertainty and the U.K. Unemployment Rate: A Forecasting Experiment with Random Forests Using 150 Years of Data," Working Papers 202095, University of Pretoria, Department of Economics.
• Hong, Yanran & Wang, Lu & Liang, Chao & Umar, Muhammad, 2022. "Impact of financial instability on international crude oil volatility: New sight from a regime-switching framework," Resources Policy, Elsevier, vol. 77(C).
• Gupta, Rangan & Pierdzioch, Christian, 2022. "Climate risks and forecastability of the realized volatility of gold and other metal prices," Resources Policy, Elsevier, vol. 77(C).
  • Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and Forecastability of the Realized Volatility of Gold and Other Metal Prices," Working Papers 202172, University of Pretoria, Department of Economics.
• Mei, Dexiang & Zhao, Chenchen & Luo, Qin & Li, Yan, 2022. "Forecasting the Chinese low-carbon index volatility," Resources Policy, Elsevier, vol. 77(C).
• Lin, Yu & Liao, Qidong & Lin, Zixiao & Tan, Bin & Yu, Yuanyuan, 2022. "A novel hybrid model integrating modified ensemble empirical mode decomposition and LSTM neural network for multi-step precious metal prices prediction," Resources Policy, Elsevier, vol. 78(C).
• Kakade, Kshitij & Jain, Ishan & Mishra, Aswini Kumar, 2022. "Value-at-Risk forecasting: A hybrid ensemble learning GARCH-LSTM based approach," Resources Policy, Elsevier, vol. 78(C).
• Liu, Guangqiang & Zeng, Qing & Lei, Juan, 2022. "Dynamic risks from climate policy uncertainty: A case study for the natural gas market," Resources Policy, Elsevier, vol. 79(C).
• Zhao, Jing, 2022. "Exploring the influence of the main factors on the crude oil price volatility: An analysis based on GARCH-MIDAS model with Lasso approach," Resources Policy, Elsevier, vol. 79(C).
• Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market volatility: A newspaper-based predictor regarding petroleum market volatility," Resources Policy, Elsevier, vol. 79(C).
• Khezri, Mohsen & Heshmati, Almas & Ghazal, Reza & Khodaei, Mehdi, 2022. "Non-resource revenues and the resource curse in different institutional structures: The DIGNAR-MTFF model," Resources Policy, Elsevier, vol. 79(C).
• Xu, Yongan & Li, Ming & Yan, Wen & Bai, Jiancheng, 2022. "Predictability of the renewable energy market returns: The informational gains from the climate policy uncertainty," Resources Policy, Elsevier, vol. 79(C).
• Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2022. "A babel of web-searches: Googling unemployment during the pandemic," Labour Economics, Elsevier, vol. 74(C).
• Restrepo-Ángel, Sergio & Rincón-Castro, Hernán & Ospina-Tejeiro, Juan J., 2022. "Multipliers of taxes and public spending in Colombia: SVAR and local projections approaches," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 3(3).
• Maples, Chellie H. & Hagerman, Amy D. & Lambert, Dayton M., 2022. "Ex-ante effects of the 2018 Agricultural Improvement Act’s grassland initiative," Land Use Policy, Elsevier, vol. 116(C).
• Umar, Zaghum & Yousaf, Imran & Gubareva, Mariya & Vo, Xuan Vinh, 2022. "Spillover and risk transmission between the term structure of the US interest rates and Islamic equities," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
• Yao, Haixiang & Xia, Shenghao & Liu, Hao, 2022. "Six-factor asset pricing and portfolio investment via deep learning: Evidence from Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
• Bui, Quynh & Ślepaczuk, Robert, 2022. "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
• Li, Wei-Zhen & Zhai, Jin-Rui & Jiang, Zhi-Qiang & Wang, Gang-Jin & Zhou, Wei-Xing, 2022. "Predicting tail events in a RIA-EVT-Copula framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
• Ahmed, Walid M.A., 2022. "On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 135-151.
• Su, Zhi & Liu, Peng & Fang, Tong, 2022. "Uncertainty matters in US financial information spillovers: Evidence from a directed acyclic graph approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 229-242.
• Fasanya, Ismail O. & Oyewole, Oluwatomisin J. & Oliyide, Johnson A., 2022. "Investors' sentiments and the dynamic connectedness between cryptocurrency and precious metals markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 347-364.
• Cerqua, Augusto & Letta, Marco, 2022. "Local inequalities of the COVID-19 crisis," Regional Science and Urban Economics, Elsevier, vol. 92(C).
  • Cerqua, Augusto & Letta, Marco, 2021. "Local inequalities of the COVID-19 crisis," GLO Discussion Paper Series 875, Global Labor Organization (GLO).
• Islam, Md. Monirul & Irfan, Muhammad & Shahbaz, Muhammad & Vo, Xuan Vinh, 2022. "Renewable and non-renewable energy consumption in Bangladesh: The relative influencing profiles of economic factors, urbanization, physical infrastructure and institutional quality," Renewable Energy, Elsevier, vol. 184(C), pages 1130-1149.
• Salisu, Afees A. & Cuñado, Juncal & Gupta, Rangan, 2022. "Geopolitical risks and historical exchange rate volatility of the BRICS," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 179-190.
  • Afees A. Salisu & Juncal Cunado & Rangan Gupta, 2020. "Geopolitical Risks and Historical Exchange Rate Volatility of the BRICS," Working Papers 2020105, University of Pretoria, Department of Economics.
• Umar, Zaghum & Riaz, Yasir & Aharon, David Y., 2022. "Network connectedness dynamics of the yield curve of G7 countries," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 275-288.
• Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je & Gau, Yin-Feng, 2022. "Risk-return trade-off in the Australian Securities Exchange: Accounting for overnight effects, realized higher moments, long-run relations, and fractional cointegration," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 384-401.
• Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022. "Semi-nonparametric risk assessment with cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
• Kristóf, Tamás & Virág, Miklós, 2022. "EU-27 bank failure prediction with C5.0 decision trees and deep learning neural networks," Research in International Business and Finance, Elsevier, vol. 61(C).
• Wang, Yaqi & Wang, Chunfeng & Sensoy, Ahmet & Yao, Shouyu & Cheng, Feiyang, 2022. "Can investors’ informed trading predict cryptocurrency returns? Evidence from machine learning," Research in International Business and Finance, Elsevier, vol. 62(C).
• Su, Yuandong & Lu, Xinjie & Zeng, Qing & Huang, Dengshi, 2022. "Good air quality and stock market returns," Research in International Business and Finance, Elsevier, vol. 62(C).
• Tripathy, Naliniprava, 2022. "Long memory and volatility persistence across BRICS stock markets," Research in International Business and Finance, Elsevier, vol. 63(C).
• Naimoli, Antonio, 2022. "Modelling the persistence of Covid-19 positivity rate in Italy," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).

2021

• David E. Allen & Michael McAleer, 2021. "Predicting COVID-19 Cases and Deaths in the USA from Tests and State Populations," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(2), pages 1-27, June.
• Martin M. Andreasen & Giovanni Caggiano & Efrem Castelnuovo & Giovanni Pellegrino, 2021. "Why Does Risk Matter More in Recessions than in Expansions?," "Marco Fanno" Working Papers 0275, Dipartimento di Scienze Economiche "Marco Fanno".
  • Martin M. Andreasen & Giovanni Caggiano & Efrem Castelnuovo & Giovanni Pellegrino, 2021. "Why Does Risk Matter More in Recessions than in Expansions?," Economics Working Papers 2021-12, Department of Economics and Business Economics, Aarhus University.
  • Martin M. Andreasen & Giovanni Caggiano & Efrem Castelnuovo & Giovanni Pellegrino, 2021. "Why does risk matter more in recessions than in expansions?," CAMA Working Papers 2021-83, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Martin M. Andreasen & Giovanni Caggiano & Efrem Castelnuovo & Giovanni Pellegrino, 2021. "Why Does Risk Matter More in Recessions than in Expansions?," CESifo Working Paper Series 9328, CESifo.
  • Andreasen, Martin Møller & Caggiano, Giovanni & Castelnuovo, Efrem & Pellegrino, Giovanni, 2021. "Why does risk matter more in recessions than in expansions?," Bank of Finland Research Discussion Papers 13/2021, Bank of Finland.
  • Martin M. Andreasen & Giovanni Caggiano & Efrem Castelnuovo & Giovanni Pellegrino, 2021. "Why Does Risk Matter More in Recessions than in Expansions?," Monash Economics Working Papers 2021-11, Monash University, Department of Economics.
• Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
• Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.
• Mikkel Bennedsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2021. "Inference and forecasting for continuous-time integer-valued trawl processes and their use in financial economics," CREATES Research Papers 2021-12, Department of Economics and Business Economics, Aarhus University.
• Ulrich Hounyo & Kajal Lahiri, 2021. "Estimating the Variance of a Combined Forecast: Bootstrap-Based Approach," CREATES Research Papers 2021-14, Department of Economics and Business Economics, Aarhus University.
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2021. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2021-03, Department of Economics, Auburn University.
  • Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2022. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2022-03, Department of Economics, Auburn University.
• Ivan Korolev, 2021. "How Could Russia Have Developed without the Revolution of 1917?," Annals of Economics and Statistics, GENES, issue 144, pages 75-112.
• George-Marios Angeletos & Zhen Huo, 2021. "Myopia and Anchoring," American Economic Review, American Economic Association, vol. 111(4), pages 1166-1200, April.
  • George-Marios Angeletos & Zhen Huo, 2018. "Myopia and Anchoring," NBER Working Papers 24545, National Bureau of Economic Research, Inc.
• Alexandre N. Kohlhas & Ansgar Walther, 2021. "Asymmetric Attention," American Economic Review, American Economic Association, vol. 111(9), pages 2879-2925, September.
• Barbara Rossi, 2021. "Forecasting in the Presence of Instabilities: How We Know Whether Models Predict Well and How to Improve Them," Journal of Economic Literature, American Economic Association, vol. 59(4), pages 1135-1190, December.
• María Paula Bonel & Daniel J. Aromí, 2021. "Assessing GDP forecasts from autoregressive models: the impact of model complexity and training dataset," Asociación Argentina de Economía Política: Working Papers 4440, Asociación Argentina de Economía Política.
• Pacheco & Riquelme, 2021. "¿Cómo se siente el presidente?," Asociación Argentina de Economía Política: Working Papers 4500, Asociación Argentina de Economía Política.
• Vesna Karadzic & Bojan Pejovic, 2021. "Inflation Forecasting in the Western Balkans and EU: A Comparison of Holt-Winters, ARIMA and NNAR Models," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(57), pages 517-517.
• Nigel E.N. Chitambo & Darren Lee & Sure Mataramvura, 2021. "A Hybrid Neural Network GARCH Approach to Forecasting Zimbabwean Inflation Volatility," The African Finance Journal, Africagrowth Institute, vol. 23(1), pages 56-73.
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
• Arkadiusz Jędrzejewski & Grzegorz Marcjasz & Rafał Weron, 2021. "Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO," Energies, MDPI, vol. 14(11), pages 1-17, June.
  • Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO," WORking papers in Management Science (WORMS) WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Weronika Nitka & Tomasz Serafin & Dimitrios Sotiros, 2021. "Forecasting Electricity Prices: Autoregressive Hybrid Nearest Neighbors (ARHNN) method," WORking papers in Management Science (WORMS) WORMS/21/06, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Olivares, Kin G. & Challu, Cristian & Marcjasz, Grzegorz & Weron, Rafał & Dubrawski, Artur, 2023. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," International Journal of Forecasting, Elsevier, vol. 39(2), pages 884-900.
  • Kin G. Olivares & Cristian Challu & Grzegorz Marcjasz & Rafal Weron & Artur Dubrawski, 2021. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," WORking papers in Management Science (WORMS) WORMS/21/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafal Weron, 2021. "Erratum to 'Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark' [Appl. Energy 293 (2021) 116983]," WORking papers in Management Science (WORMS) WORMS/21/12, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• David E. Allen & Michael McAleer, 2021. "Predicting COVID-19 Cases and Deaths in the USA from Tests and State Populations," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(2), pages 1-27, June.
  • David E. Allen & Michael McAleer, 2021. "Predicting COVID-19 Cases and Deaths in the USA from Tests and State Populations," International Association of Decision Sciences, Asia University, Taiwan, vol. 25(2), pages 1-27, June.
• Marcel Aloy & Floris Laly & Sébastien Laurent & Christelle Lecourt, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," Dynamic Modeling and Econometrics in Economics and Finance, in: Gilles Dufrénot & Takashi Matsuki (ed.), Recent Econometric Techniques for Macroeconomic and Financial Data, pages 229-264, Springer.
  • Marcel Aloy & Floris Laly & Sébastien Laurent & Christelle Lecourt, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," Post-Print hal-03103717, HAL.
  • Aloy, Marcel & Laly, Floris & Laurent, Sébastien & Lecourt, Christelle, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," LIDAM Reprints LFIN 2021021, Université catholique de Louvain, Louvain Finance (LFIN).
• Nurdaulet Abilov & Aizhan Bolatbayeva, 2021. "Nowcasting GDP growth in Russia with an incomplete dataset: A factor model approach," NAC Analytica Working Paper 18, NAC Analytica, Nazarbayev University, revised Feb 2022.
• Asta Ndongo & Ibrahima Thione Diop, 2021. "Economic and Monetary Integration in ECOWAS Countries: A Panel VAR Approach to Identify Macroeconomic Shocks," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 7(2), pages 61-87, December.
• Игсатов О.Р. // Igsatov О.R., 2021. "Анализ эффективности процентного канала в Казахстане // Analyzing effectiveness of the interest rate channel in Kazakhstan," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue 1, pages 4-14.
• Константин Орлов // Konstantin Orlov, 2021. "Построение большой байесовской авторегрессионной модели для Казахстана // Building a Large Bayesian Vector Autoregression Model for Kazakhstan," Working Papers #2021-1, National Bank of Kazakhstan.
• Diebold, Francis X. & Göbel, Maximilian, 2022. "A benchmark model for fixed-target Arctic sea ice forecasting," Economics Letters, Elsevier, vol. 215(C).
  • Francis X. Diebold & Maximilian Gobel, 2021. "A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting," Papers 2101.10359, arXiv.org, revised Jan 2022.
  • Francis X. Diebold & Maximilian Gobel, 2022. "A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting," PIER Working Paper Archive 22-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, Cambridge University Press, vol. 256, pages 71-109, April.
  • Stevanovic, Dalibor & Goulet Coulombe, Philippe, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers 15867, C.E.P.R. Discussion Papers.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Working Papers 21-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers 2021s-09, CIRANO.
• Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
  • Michael Pfarrhofer, 2021. "Modeling tail risks of inflation using unobserved component quantile regressions," Papers 2103.03632, arXiv.org, revised Oct 2021.
• Fiaschi, Davide & Tealdi, Cristina, 2021. "A General Methodology to Measure Labour Market Dynamics," IZA Discussion Papers 14254, Institute of Labor Economics (IZA).
  • Davide Fiaschi & Cristina Tealdi, 2021. "A general methodology to measure labour market dynamics," Papers 2104.01097, arXiv.org.
• David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin & Bonsoo Koo, 2021. "Loss-Based Variational Bayes Prediction," Monash Econometrics and Business Statistics Working Papers 8/21, Monash University, Department of Econometrics and Business Statistics.
  • David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin & Bonsoo Koo, 2021. "Loss-Based Variational Bayes Prediction," Papers 2104.14054, arXiv.org, revised May 2022.
• Ardia, David & Bluteau, Keven & Kassem, Alaa, 2021. "A century of Economic Policy Uncertainty through the French–Canadian lens," Economics Letters, Elsevier, vol. 205(C).
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• Davide Fiaschi & Cristina Tealdi, 2022. "Young people between education and the labour market during the COVID-19 pandemic in Italy," International Journal of Manpower, Emerald Group Publishing Limited, vol. 43(7), pages 1719-1757, July.
  • Fiaschi, Davide & Tealdi, Cristina, 2021. "Young People between Education and the Labour Market during the COVID-19 Pandemic in Italy," IZA Discussion Papers 14479, Institute of Labor Economics (IZA).
  • Davide Fiaschi & Cristina Tealdi, 2021. "Young people between education and the labour market during the COVID-19 pandemic in Italy," Papers 2106.08296, arXiv.org.
• Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
  • Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Papers 2107.02512, arXiv.org, revised Sep 2022.
• Li, Wei & Paraschiv, Florentina & Sermpinis, Georgios, 2021. "A data-driven explainable case-based reasoning approach for financial risk detection," IRTG 1792 Discussion Papers 2021-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  • Wei Li & Florentina Paraschiv & Georgios Sermpinis, 2021. "A Data-driven Explainable Case-based Reasoning Approach for Financial Risk Detection," Papers 2107.08808, arXiv.org.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2023. "Forecasting with a panel Tobit model," Quantitative Economics, Econometric Society, vol. 14(1), pages 117-159, January.
  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
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  • Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," NBER Working Papers 26569, National Bureau of Economic Research, Inc.
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• Massimo Guidolin & Davide La Cara & Massimiliano Marcellino, 2021. "Boosting the Forecasting Power of Conditional Heteroskedasticity Models to Account for Covid-19 Outbreaks," BAFFI CAREFIN Working Papers 21169, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
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• Ibarra-Ramírez Raúl, 2021. "The Yield Curve as a Predictor of Economic Activity in Mexico: The Role of the Term Premium," Working Papers 2021-07, Banco de México.
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• Rangel González Erick & Llamosas-Rosas Irving, 2021. "Observing the Evolution of the Informal Sector from Space: A Municipal Approach 2013-2020," Working Papers 2021-18, Banco de México.
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• Elizaveta Golovanova & Andrey Zubarev, 2021. "Forecasting Aggregate Retail Sales with Google Trends," Russian Journal of Money and Finance, Bank of Russia, vol. 80(4), pages 50-73, December.
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• J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
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• Ding, Y., 2021. "Conditional Heteroskedasticity in the Volatility of Asset Returns," Cambridge Working Papers in Economics 2179, Faculty of Economics, University of Cambridge.
• Ding, Y., 2021. "Conditional Heteroskedasticity in the Volatility of Asset Returns," Janeway Institute Working Papers 2111, Faculty of Economics, University of Cambridge.
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• Joanna Holub-Iwan, 2021. "Management Information Systems of Public Health Behaviors based on Evidence in Medicine and Health Management," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 623-643.
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• Fink Simonsen, Nicolai & Kjær, Trine, 2021. "New Evidence of Health State Dependent Utility of Consumption: A combined survey and register study," DaCHE discussion papers 2021:2, University of Southern Denmark, Dache - Danish Centre for Health Economics.
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• Paolo Riccardo Morganti, 2021. "Extreme Value Theory and Auction Models," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(2), pages 1-15, Abril - J.
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• Guillermo Benavides, 2021. "Asymmetric Volatility Relevance in Risk Management: An Empirical Analysis using Stock Index Futures," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(TNEA), pages 1-18, Septiembr.
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• 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., vol. 42(2), pages 331-346, March.
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• Athanasios Tsadiras & Maria Pempetzoglou & Iosif Viktoratos, 2021. "Making Predictions of Global Warming Impacts Using a Semantic Web Tool that Simulates Fuzzy Cognitive Maps," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 715-745, October.
• Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
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• Cem Cakmakli & Verda Ozturk, 2021. "Economic Value of Modeling the Joint Distribution of Returns and Volatility: Leverage Timing," Koç University-TUSIAD Economic Research Forum Working Papers 2110, Koc University-TUSIAD Economic Research Forum.
• Magdalena Cornejo, 2021. "Forecasting crop yields through climate variables using mixed frequency data. The case of Argentine soybeans," Económica, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 67, pages 93-106, January-D.
• Alexander Correa, 2021. "Forecasting Tourist Arrivals to Colombia from Google Trends Search Criteria," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 95, pages 105-134, July-Dece.
• Jamal Bouoiyour, Refk Selmi, 2021. "The financial costs of terrorism: evidence from Germany," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 18(1), pages 87-104, June.
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• David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin & Bonsoo Koo, 2021. "Loss-Based Variational Bayes Prediction," Papers 2104.14054, arXiv.org, revised May 2022.
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• Andres Algaba & Samuel Borms & Kris Boudt & Brecht Verbeken, 2021. "Daily news sentiment and monthly surveys: A mixed–frequency dynamic factor model for nowcasting consumer confidence," Working Paper Research 396, National Bank of Belgium.
• Sylwia Radomska, 2021. "Prognozowanie indeksu WIG20 za pomocą sieci neuronowych NARX i metody SVM," Bank i Kredyt, Narodowy Bank Polski, vol. 52(5), pages 457-472.
• Anirban Basu & Noah Hammarlund & Sara Khor & Aasthaa Bansal, 2021. "Understanding Algorithmic Discrimination in Health Economics Through the Lens of Measurement Errors," NBER Working Papers 29413, National Bureau of Economic Research, Inc.
• Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Cowles Foundation Discussion Papers 2312, Cowles Foundation for Research in Economics, Yale University.
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• Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," Working Papers 20-26, Federal Reserve Bank of Philadelphia.
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• Bhattacharya, Rudrani & Bhandari, Bornali & Mundle, Sudipto, 2021. "Nowcasting India's Quarterly GDP Growth: A Factor Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)," Working Papers 21/357, National Institute of Public Finance and Policy.
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• Novikova, T. & Tsyplakov, A., 2021. "Social policy development based on a combination of agent-oriented and inter-industrial approaches," Journal of the New Economic Association, New Economic Association, vol. 52(4), pages 12-36.
• Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Cowles Foundation Discussion Papers 2312, Cowles Foundation for Research in Economics, Yale University.
  • Ali Hortaçsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Working Papers 21-09, NET Institute.
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  • Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Cowles Foundation Discussion Papers 2312R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2022.
• Bhattacharya, Rudrani & Bhandari, Bornali & Mundle, Sudipto, 2021. "Nowcasting India's Quarterly GDP Growth: A Factor Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)," Working Papers 21/357, National Institute of Public Finance and Policy.
• George Kapetanios & Fotis Papailias, 2021. "UK Economic Conditions during the Pandemic: Assessing the Economy using ONS Faster Indicators," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2021-10, Economic Statistics Centre of Excellence (ESCoE).
• Alexandros Botsis & Christoph Görtz & Plutarchos Sakellaris, 2020. "Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts," CESifo Working Paper Series 8148, CESifo.
  • Alex Botsis & Christoph Gortz & Plutarchos Sakellaris, 2021. "Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2021-14, Economic Statistics Centre of Excellence (ESCoE).
• Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2021. "Smooth Robust Multi-Horizon Forecasts," Economics Papers 2021-W01, Economics Group, Nuffield College, University of Oxford.
• Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2022. "Smooth Robust Multi-Horizon Forecasts," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 143-165, Emerald Group Publishing Limited.
  • Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2020. "Smooth Robust Multi-Horizon Forecasts," Working Papers 2020-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
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• Victor Yotzov, 2021. "Commodity Market Structure and Risk Factor Analysis in Bulgaria," Godishnik na UNSS, University of National and World Economy, Sofia, Bulgaria, issue 2, pages 1-53–73, December.
• Iva Raycheva, 2021. "Child Poverty among European Countries and Bulgaria’s Place among Them. Statistical Analysis of Convergence," Ikonomiceski i Sotsialni Alternativi, University of National and World Economy, Sofia, Bulgaria, issue 3, pages 37-51, September.
• Kensuke Tanaka, 2021. "Forecasting developing Asian economies during normal times and large external shocks: Approaches and challenges," OECD Development Centre Working Papers 345, OECD Publishing.
• Gerhard Fenz & Helmut Stix, 2021. "Monitoring the economy in real time with the weekly OeNB GDP indicator: background, experience and outlook," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 20/Q4-21/, pages 17-40.
• Gerhard Fenz & Helmut Stix, 2021. "Monitoring the economy in real time with the weekly OeNB GDP indicator: background, experience and outlook," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/20-Q1/, pages 17-40.
• Lidia Vesa & Marcel Ioan Boloş & Claudia Diana Sabău-Popa, 2021. "Inventory Decision In Vuca World Using Economic Logic Quantity," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 251-267, July.
• Ionuţ Gavriş & Valentin Toader, 2021. "The Probability Of Uncertainty: Romania’S Growth Perspectives," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 71-81, July.
• Rachel R. Cheti & Bahati Ilembo, 2021. "Vector Autoregressive Approach After First Differencing: A Time Series Analysis Of Inflation And Its Determinants In Tanzania," Oradea Journal of Business and Economics, University of Oradea, Faculty of Economics, vol. 6(2), pages 43-56, September.
• Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2021. "Online estimation of DSGE models," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 33-58.
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  • Michael D. Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," NBER Working Papers 26826, National Bureau of Economic Research, Inc.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Staff Reports 893, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Liberty Street Economics 20190821, Federal Reserve Bank of New York.
  • Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," Finance and Economics Discussion Series 2020-023, Board of Governors of the Federal Reserve System (U.S.).
• Fred Liu & Lars Stentoft, 2021. "Regulatory Capital and Incentives for Risk Model Choice under Basel 3 [Procyclical Leverage and Value-at-Risk]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(1), pages 53-96.
• Apaar Sadhwani & Kay Giesecke & Justin Sirignano, 2021. "Deep Learning for Mortgage Risk [The Subprime Virus]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(2), pages 313-368.
• Giuseppe Buccheri & Fulvio Corsi, 2021. "HARK the SHARK: Realized Volatility Modeling with Measurement Errors and Nonlinear Dependencies," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(4), pages 614-649.
• Giorgio Calzolari & Roxana Halbleib & Aygul Zagidullina, 2021. "A Latent Factor Model for Forecasting Realized Variances [Stock Returns and Volatility: Pricing the Short-Run and Long-Run Components of Market Risk]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(5), pages 860-909.
• Steven Lehrer & Tian Xie & Tao Zeng, 2021. "Does High-Frequency Social Media Data Improve Forecasts of Low-Frequency Consumer Confidence Measures? [Regression Models with Mixed Sampling Frequencies]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(5), pages 910-933.
  • Steven F. Lehrer & Tian Xie & Tao Zeng, 2019. "Does High Frequency Social Media Data Improve Forecasts of Low Frequency Consumer Confidence Measures?," NBER Working Papers 26505, National Bureau of Economic Research, Inc.
• Daniele Bianchi & Matthias Büchner & Andrea Tamoni, 2021. "Bond Risk Premiums with Machine Learning [Quadratic term structure models: Theory and evidence]," Review of Financial Studies, Society for Financial Studies, vol. 34(2), pages 1046-1089.
• Romero Martínez, Mariano & Carmona Ibáñez, Pedro & Pozuelo Campillo, José, 2021. "Utilidad del Deep Learning en la predicción del fracaso empresarial en el ámbito europeo || The usefulness of Deep Learning in the prediction of business failure at the European level," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 32(1), pages 392-414, December.
• Wolfgang Bessler & Georgi Taushanov & Dominik Wolff, 2021. "Factor investing and asset allocation strategies: a comparison of factor versus sector optimization," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 488-506, October.
• János Varga & Jan in ’t Veld, 2021. "The Impact of the EU Cohesion Policy Spending: A Model-Based Assessment," Studies in Economic Transition, in: Michael Landesmann & István P. Székely (ed.), Does EU Membership Facilitate Convergence? The Experience of the EU's Eastern Enlargement - Volume II, chapter 0, pages 89-112, Palgrave Macmillan.
• Alessandro Bitetto & Paola Cerchiello & Stefano Filomeni & Alessandra Tanda & Barbara Tarantino, 2021. "Machine Learning and Credit Risk: Empirical Evidence from SMEs," DEM Working Papers Series 201, University of Pavia, Department of Economics and Management.
• Alessandro Bitetto & Stefano Filomeni & Michele Modina, 2021. "Understanding corporate default using Random Forest: The role of accounting and market information," DEM Working Papers Series 205, University of Pavia, Department of Economics and Management.
• Mario Papik & Lenka Papikova, 2021. "Application of selected data mining techniques in unintentional accounting error detection," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 16(1), pages 185-201, March.
• Krzysztof Waliszewski & Anna Warchlewska, 2021. "Comparative analysis of Poland and selected countries in terms of household financial behaviour during the COVID-19 pandemic," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 16(3), pages 577-615, September.
• Andrea Kolková & Aleksandr Kljuènikov, 2021. "Demand forecasting: an alternative approach based on technical indicator Pbands," Oeconomia Copernicana, Institute of Economic Research, vol. 12(4), pages 1063-1094, December.
• Martins, Manuel Mota Freitas & Verona, Fabio, 2021. "Inflation dynamics and forecast: Frequency matters," Bank of Finland Research Discussion Papers 8/2021, Bank of Finland.
  • Manuel M. F. Martins & Fabio Verona, 2021. "Inflation Dynamics and Forecast: Frequency Matters," CEF.UP Working Papers 2101, Universidade do Porto, Faculdade de Economia do Porto.
• Valerio Mendoza, Octasiano Miguel & Borsi, Mihály Tamás & Comim, Flavio, 2022. "Human capital dynamics in China: Evidence from a club convergence approach," Journal of Asian Economics, Elsevier, vol. 79(C).
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• Pincheira, Pablo & Hardy, Nicolas, 2021. "The Mean Squared Prediction Error Paradox," MPRA Paper 107403, University Library of Munich, Germany.
• VINTU, Denis, 2021. "GDP Modelling and Forecasting Using ARIMA. An Empirical Assessment for Innovative Economy Formation," MPRA Paper 107603, University Library of Munich, Germany, revised 11 Feb 2021.
• Pincheira, Pablo & Hardy, Nicolas & Bentancor, Andrea & Henriquez, Cristóbal & Tapia, Ignacio, 2021. "Forecasting Base Metal Prices with an International Stock Index," MPRA Paper 107828, University Library of Munich, Germany.
• Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
  • Ofori, Isaac K, 2021. "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper 108622, University Library of Munich, Germany.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers 21/044, Research Africa Network (RAN).
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers of the African Governance and Development Institute. 21/044, African Governance and Development Institute..
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• Youssef, Jamile & Ishker, Nermeen & Fakhreddine, Nour, 2021. "GDP Forecast of the Biggest GCC Economies Using ARIMA," MPRA Paper 108912, University Library of Munich, Germany.
• Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Using Deep Learning Neural Networks to Predict the Knowledge Economy Index for Developing and Emerging Economies," MPRA Paper 109137, University Library of Munich, Germany.
• Antonio Rodríguez Andrés & Voxi Heinrich S. Amavilah & Abraham Otero, 2021. "Evaluation of technology clubs by clustering: a cautionary note," Applied Economics, Taylor & Francis Journals, vol. 53(52), pages 5989-6001, November.
  • Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Evaluation of technology clubs by clustering: A cautionary note," MPRA Paper 109138, University Library of Munich, Germany.
• Kindop, Igor, 2021. "Ubiquitous multimodality in mixed causal-noncausal processes," MPRA Paper 109594, University Library of Munich, Germany, revised 04 Sep 2021.
• Kadanga, Mayo Takémsi Norris & Togbenu, Fo-Kossi Edem, 2021. "Modélisation et prévision du nombre d’infections au coronavirus au Togo: une approche par un modèle ARIMA avec le logiciel R [Modeling and forecasting the number of coronavirus infections in Togo: ," MPRA Paper 109893, University Library of Munich, Germany.
• Ahamuefula E. Ogbonna & Olusanya E. Olubusoye, 2021. "Tail Risks and Stock Return Predictability - Evidence From Asia-Pacific," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(3), pages 1-6.
  • Ogbonna, Ahamuefula & Olubusoye, Olusanya E, 2021. "Tail Risks and Stock Return Predictability: Evidence From Asia-Pacific," MPRA Paper 109922, University Library of Munich, Germany.
• Adekunle, Wasiu & Bekoe, William & Badmus, Sheriff & Anagun, Michael & Alimi, Wasiu, 2021. "Nexus Between Fiscal Discipline And The Budget Process In Africa: Evidence From Nigeria," MPRA Paper 110061, University Library of Munich, Germany.
• 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., vol. 42(2), pages 331-346, March.
  • William Barnett & Sohee Park, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202120, University of Kansas, Department of Economics, revised Oct 2021.
  • Barnett, William & Park, Sohee, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," MPRA Paper 110298, University Library of Munich, Germany.
• Lukas Boer & Andrea Pescatori & Martin Stuermer, 2021. "Energy Transition Metals," Discussion Papers of DIW Berlin 1976, DIW Berlin, German Institute for Economic Research.
  • Boer, Lukas & Pescatori, Andrea & Stuermer, Martin, 2021. "Energy Transition Metals," MPRA Paper 110364, University Library of Munich, Germany.
  • Lukas Boer & Mr. Andrea Pescatori & Martin Stuermer, 2021. "Energy Transition Metals," IMF Working Papers 2021/243, International Monetary Fund.
• Dean Fantazzini & Raffaella Calabrese, 2021. "Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure," JRFM, MDPI, vol. 14(11), pages 1, October.
  • Fantazzini, Dean & Calabrese, Raffaella, 2021. "Crypto-exchanges and Credit Risk: Modelling and Forecasting the Probability of Closure," MPRA Paper 110391, University Library of Munich, Germany.
• Dean Fantazzini & Julia Pushchelenko & Alexey Mironenkov & Alexey Kurbatskii, 2021. "Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg," Forecasting, MDPI, vol. 3(4), pages 1-30, October.
  • Fantazzini, Dean & Pushchelenko, Julia & Mironenkov, Alexey & Kurbatskii, Alexey, 2021. "Forecasting internal migration in Russia using Google Trends: Evidence from Moscow and Saint Petersburg," MPRA Paper 110452, University Library of Munich, Germany.
• Bhadury, Soumya & Ghosh, Saurabh & Gopalakrishnan, Pawan, 2021. "In quest for policy 'silver bullets' towards triggering a v-shaped recovery," MPRA Paper 110905, University Library of Munich, Germany.
• Stavros Degiannakis, 2022. "Stock market as a nowcasting indicator for real investment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 911-919, August.
  • Degiannakis, Stavros, 2021. "Stock market as a nowcasting indicator for real investment," MPRA Paper 110914, University Library of Munich, Germany.
• Mestiri, Sami, 2021. "Modelling the volatility of Bitcoin returns using Nonparametric GARCH models," MPRA Paper 111116, University Library of Munich, Germany.
• Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Foundations and Trends(R) in Econometrics, now publishers, vol. 11(4), pages 230-354, June.
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  • Korobilis, Dimitris & Shimizu, Kenichi, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," MPRA Paper 111631, University Library of Munich, Germany.
  • Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Paper series 22-02, Rimini Centre for Economic Analysis.
  • Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Papers 2112.11751, arXiv.org.
• G.K., Chetan Kumar & K.B., Rangappa & S., Suchitra, 2021. "Analyzing Interlinkages between Financial and Real Estate Sector in the aftermath of COVID-19's Second wave: An Econometric Approach using VECM model," MPRA Paper 112440, University Library of Munich, Germany.
• Abdullah, Muhammad & Gul, Zarro & Waseem, Faiza & Islam, Tanweer, 2021. "The State of Pakistan’s Economy and the Ineffectiveness of Monetary Policy," MPRA Paper 112678, University Library of Munich, Germany.
• Bradrania, Reza & Pirayesh Neghab, Davood, 2021. "State-dependent asset allocation using neural networks," MPRA Paper 115254, University Library of Munich, Germany.
• Sheng, Xin & Gupta, Rangan & Salisu, Afees A. & Bouri, Elie, 2022. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Finance Research Letters, Elsevier, vol. 45(C).
  • Xin Sheng & Rangan Gupta & Afees A. Salisu & Elie Bouri, 2021. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Working Papers 202101, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna & Mark E. Wohar, 2022. "Uncertainty and predictability of real housing returns in the United Kingdom: A regional analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1525-1556, November.
  • Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna & Mark E. Wohar, 2021. "Uncertainty and Predictability of Real Housing Returns in the United Kingdom: A Regional Analysis," Working Papers 202102, University of Pretoria, Department of Economics.
• Afees A. Salisu & Umar Bida Ndako & Rangan Gupta, 2021. "Forecasting US Output Growth with Large Information Sets," Working Papers 202103, University of Pretoria, Department of Economics.
• Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
• Riza Demirer & Rangan Gupta & He Li & Yu You, 2021. "Financial Vulnerability and Volatility in Emerging Stock Markets: Evidence from GARCH-MIDAS Models," Working Papers 202112, University of Pretoria, Department of Economics.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Forecasting realized volatility of international REITs: The role of realized skewness and realized kurtosis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 303-315, March.
  • Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of International REITs: The Role of Realized Skewness and Realized Kurtosis," Working Papers 202114, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil prices over 150 years: The role of tail risks," Resources Policy, Elsevier, vol. 75(C).
  • Afees A. Salisu & Rangan Gupta & Qiang Ji, 2021. "Forecasting Oil Price over 150 Years: The Role of Tail Risks," Working Papers 202120, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Gupta, Rangan & Demirer, Riza, 2022. "Global financial cycle and the predictability of oil market volatility: Evidence from a GARCH-MIDAS model," Energy Economics, Elsevier, vol. 108(C).
  • Afees A. Salisu & Rangan Gupta & Riza Demirer, 2021. "Global Financial Cycle and the Predictability of Oil Market Volatility: Evidence from a GARCH-MIDAS Model," Working Papers 202121, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2021. "Geopolitical risk and forecastability of tail risk in the oil market: Evidence from over a century of monthly data," Energy, Elsevier, vol. 235(C).
  • Afees A. Salisu & Christian Pierdzioch & Rangan Gupta, 2021. "Geopolitical Risk and Forecastability of Tail Risk in the Oil Market: Evidence from Over a Century of Monthly Data," Working Papers 202122, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta & Christian Pierdzioch, 2021. "Predictability of Tail Risks of Canada and the U.S. Over a Century: The Role of Spillovers and Oil Tail Risks," Working Papers 202127, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
  • Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," GRU Working Paper Series GRU_2021_017, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
  • Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," Working Papers 202133, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers," Energies, MDPI, vol. 14(14), pages 1-15, July.
  • Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers," Working Papers 202135, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty, Spillovers, and Forecasts of the Realized Variance of Gold Returns," Working Papers 202137, University of Pretoria, Department of Economics.
• Afees A. Salisu & Rangan Gupta, 2021. "Commodity Prices and Forecastability of South African Stock Returns Over a Century: Sentiments versus Fundamentals," Working Papers 202144, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2022. "Oil tail risks and the forecastability of the realized variance of oil-price: Evidence from over 150 years of data," Finance Research Letters, Elsevier, vol. 46(PB).
  • Afees A. Salisu & Christian Pierdzioch & Rangan Gupta, 2021. "Oil Tail Risks and the Forecastability of the Realized Variance of Oil-Price: Evidence from Over 150 Years of Data," Working Papers 202146, University of Pretoria, Department of Economics.
• Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan & Gabauer, David, 2022. "Forecasting stock-market tail risk and connectedness in advanced economies over a century: The role of gold-to-silver and gold-to-platinum price ratios," International Review of Financial Analysis, Elsevier, vol. 83(C).
  • Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & David Gabauer, 2021. "Forecasting Stock-Market Tail Risk and Connectedness in Advanced Economies Over a Century: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios," Working Papers 202161, University of Pretoria, Department of Economics.
• Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & Renee van Eyden, 2021. "Climate Risks and U.S. Stock-Market Tail Risks: A Forecasting Experiment Using over a Century of Data," Working Papers 202165, University of Pretoria, Department of Economics.
• Karmakar, Sayar & Demirer, Riza & Gupta, Rangan, 2021. "Bitcoin mining activity and volatility dynamics in the power market," Economics Letters, Elsevier, vol. 209(C).
  • Sayar Karmakar & Riza Demirer & Rangan Gupta, 2021. "Bitcoin Mining Activity and Volatility Dynamics in the Power Market," Working Papers 202166, University of Pretoria, Department of Economics.
• Gupta, Rangan & Pierdzioch, Christian, 2022. "Climate risks and forecastability of the realized volatility of gold and other metal prices," Resources Policy, Elsevier, vol. 77(C).
  • Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and Forecastability of the Realized Volatility of Gold and Other Metal Prices," Working Papers 202172, University of Pretoria, Department of Economics.
• Jiqian Wang & Rangan Gupta & Oguzhan Cepni & Feng Ma, 2021. "Forecasting International REITs Volatility: The Role of Oil-Price Uncertainty," Working Papers 202173, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and the Realized Volatility Oil and Gas Prices: Results of an Out-of-Sample Forecasting Experiment," Energies, MDPI, vol. 14(23), pages 1, December.
  • Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and the Realized Volatility Oil and Gas Prices: Results of an Out-of-Sample Forecasting Experiment," Working Papers 202175, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Realized Variance of Oil-Price Returns: A Disaggregated Analysis of the Role of Uncertainty and Geopolitical Risk," Working Papers 202176, University of Pretoria, Department of Economics.
• Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risk and the Volatility of Agricultural Commodity Price Fluctuations: A Forecasting Experiment," Working Papers 202177, University of Pretoria, Department of Economics.
• Ruipeng Liu & Rangan Gupta & Elie Bouri, 2021. "Conventional and Unconventional Monetary Policy Rate Uncertainty and Stock Market Volatility: A Forecasting Perspective," Working Papers 202178, University of Pretoria, Department of Economics.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2021. "El Nino, La Nina, and Forecastability of the Realized Variance of Agricultural Commodity Prices: Evidence from a Machine Learning Approach," Working Papers 202179, University of Pretoria, Department of Economics.
• Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2023. "Climate Risks and Forecasting Stock Market Returns in Advanced Economies over a Century," Mathematics, MDPI, vol. 11(9), pages 1-21, April.
  • Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and Forecasting Stock-Market Returns in Advanced Economies Over a Century," Working Papers 202183, University of Pretoria, Department of Economics.
• Paulina Ziembińska, 2021. "Quality of Tests of Expectation Formation for Revised Data," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(4), pages 405-453, December.
• Bhumjai Tangsawasdirat & Suranan Tanpoonkiat & Burasakorn Tangsatchanan, 2021. "Credit Risk Database: Credit Scoring Models for Thai SMEs," PIER Discussion Papers 168, Puey Ungphakorn Institute for Economic Research.
• Eliud Silva & Corey Sparks, 2021. "Hierarchical forecasts of Diabetes mortality in Mexico by marginalization and sex to establish resource allocation," EconoQuantum, Revista de Economia y Finanzas, Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas, Departamento de Metodos Cuantitativos y Maestria en Economia., vol. 18(2), pages 82-98, Julio-Dic.
• Luke Hartigan & Michelle Wright, 2021. "Financial Conditions and Downside Risk to Economic Activity in Australia," RBA Research Discussion Papers rdp2021-03, Reserve Bank of Australia.
• Pérez Forero, Fernando, 2021. "Predicción de variables macroeconómicas en el Perú a través un modelo BVAR con media cambiante en el tiempo," Working Papers 2021-001, Banco Central de Reserva del Perú.
• Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.
• Anna Gloria Billé & Angelica Gianfreda & Filippo Del Grosso & Francesco Ravazzolo, 2021. "Forecasting Electricity Prices with Expert, Linear and Non-Linear Models," Working Paper series 21-20, Rimini Centre for Economic Analysis.
• Uddin, Gazi Salah & Tang, Ou & Sahamkhadam, Maziar & Taghizadeh-Hesary, Farhad & Yahya, Muhammad & Cerin, Pontus & Rehme, Jakob, 2021. "Analysis of Forecasting Models in an Electricity Market under Volatility," ADBI Working Papers 1212, Asian Development Bank Institute.
• Karen Poghosyan & Ruben Poghosyan, 2021. "On the Applicability of Dynamic Factor Models for Forecasting Real GDP Growth in Armenia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 71(1), pages 52-79, June.
  • Poghosyan, Karen & Poghosyan, Ruben, 2021. "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 28-46.
• Garafutdinov, Robert, 2021. "Influence of some ARFIMA model parameters on the accuracy of financial time series forecasting," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 62, pages 85-100.
• Fokin, Nikita, 2021. "The importance of modeling structural breaks in forecasting Russian GDP," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 5-29.
• ERİLLİ, Necati Alp, 2021. "Use of Trimean in Theil-Sen Regression Analysis," Bulletin of Economic Theory and Analysis, BETA Journals, vol. 6(1), pages 15-26, June.
• Kocak, Necmettin Alpay, 2021. "Analysis of Relationship between the Consumer and Producer Prices in Turkey using Alternative Estimation Methods (Türkiye'de Tüketici ve Üretici Fiyatları Arasındaki İlişkinin Alternatif Tahmin Yöntem," Business and Economics Research Journal, Uludag University, Faculty of Economics and Administrative Sciences, vol. 12(1), pages 33-47, January.
• Adli, Kaveh A. & Sener, Ugur, 2021. "Forecasting of the U.S. Steel Prices with LVAR and VEC Models," Business and Economics Research Journal, Uludag University, Faculty of Economics and Administrative Sciences, vol. 12(3), pages 509-522, July.
• de Lucio, Juan, 2021. "Estimación adelantada del crecimiento regional mediante redes neuronales LSTM," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 49, pages 45-64.
• Mendoza-González, Miguel Ángel, 2021. "Apertura comercial, choques productivos y externalidades con ciclos espacio-tiempo en el crecimiento económico por entidad federativa en México, 1980-2018," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 50, pages 105-124.
• Bhaghoe, Sailesh & Ooft, Gavin, 2021. "Nowcasting Quarterly GDP Growth in Suriname with Factor-MIDAS and Mixed-Frequency VAR Models," Studies in Applied Economics 176, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
• Rao, Anitha & Wiendling, Mark & Ridgeway, Paul & Kennedy, Liz & Eyre, Harris A. & Pinho, Paulo, 2021. "Bridging the Gap Between Medicine and Insurance: How to Leverage Data, Artificial Intelligence, and Neuroinformatics for Insurance and Financial Risk Management," Journal of Financial Transformation, Capco Institute, vol. 54, pages 142-147.
• Hong, Sung Wook & Min, Seong-hwan, 2021. "Market Analysis of Key Manufacturing Segments Using News Data," Research Papers 21/8, Korea Institute for Industrial Economics and Trade.
• Sadeghpour, Solmaz & Heidari, Hassan & Mohseni Zenozi, Seyyed Jamaleddin, 2021. "Study the effect of the monetary and financial shocks in the real sector of Iran's economy with considering of gharz-al -hasanah deposits in the context of a DSGE model," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 8(1), pages 89-114, June.
• Chow, Hwee Kwan & Han, Daniel, 2021. "Forecast Pooling or Information Pooling During Crises? MIDAS Forecasting of GDP in a Small Open Economy," Economics and Statistics Working Papers 6-2021, Singapore Management University, School of Economics.
• Weiwei ZHANG & Tiezhu SUN & Yechi MA & Zilong WANG, 2021. "New Evidence on the Information Content of Implied Volatility of S&P 500: Model-Free versus Model-Based," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 109-121, December.
• Fatemeh SALIMIANRAD & Vali BORIMNEJAD & Sahar DEHYUORI, 2021. "Investigating the Relationship between Natural Capital and Sustainable Economic Growth using the General Equilibrium Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 120-139, June.
• Kirill Dragun & Kris Boudt & Orimar Sauri & Steven Vanduffel, 2021. "Beta-Adjusted Covariance Estimation," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1010, Ghent University, Faculty of Economics and Business Administration.
• George Varghese & Vinodh Madhavan, 2021. "Nonlinearity in Global Crude Oil Benchmarks: Disentangling the Effect of Time Aggregation," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 20(3), pages 290-307, December.
• Tomas Havranek & Ayaz Zeynalov, 2021. "Forecasting tourist arrivals: Google Trends meets mixed-frequency data," Tourism Economics, , vol. 27(1), pages 129-148, February.
  • Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
• Reyes Zárate, Francisco J & León López, Iván, 2021. "Estimaciones de riesgo ajustadas por distribución: una aplicación para portafolios de inversión integrados por activos nacionales / Distribution-Adjusted Risk Estimates: An Application to Domestic Ass," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 11(2), pages 117-146, julio-dic.
• Wojciech Charemza & Michal Lewandowski & Lukasz Wozny, 2021. "Efficiency in rewarding academic journal publications. The case of Poland," Working Papers 2021-062, Warsaw School of Economics, Collegium of Economic Analysis.
• Alejandro Rodriguez Arana, 2021. "La expansion de Covid-19 en Mexico en 2020: un enfoque desde la econometria de series de tiempo," Sobre México. Revista de Economía, Sobre México. Temas en economía, vol. 1(3), pages 34-66.
• F. Benedetto & L. Mastroeni & P. Vellucci, 2021. "Modeling the flow of information between financial time-series by an entropy-based approach," Annals of Operations Research, Springer, vol. 299(1), pages 1235-1252, April.
• Chrysovalantis Gaganis & Panagiota Papadimitri & Menelaos Tasiou, 2021. "A multicriteria decision support tool for modelling bank credit ratings," Annals of Operations Research, Springer, vol. 306(1), pages 27-56, November.
• Eric Séverin & David Veganzones, 2021. "Can earnings management information improve bankruptcy prediction models?," Annals of Operations Research, Springer, vol. 306(1), pages 247-272, November.
• Yuzhi Cai & Thanaset Chevapatrakul & Danilo V. Mascia, 2021. "How is price explosivity triggered in the cryptocurrency markets?," Annals of Operations Research, Springer, vol. 307(1), pages 37-51, December.
• Christos Agiakloglou & Apostolos Tsimpanos, 2021. "Evaluating information criteria for selecting spatial processes," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 66(3), pages 677-697, June.
• David Volkmann, 2021. "Explaining S&P500 option returns: an implied risk-adjusted approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 665-685, June.
• Michal Mešťan & Ivan Králik & Matej Žofaj & Nikola Karkošiaková & Audrius Kabašinskas, 2021. "Projections of pension benefits in supplementary pension saving scheme in Slovakia," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 687-712, June.
• Gianna Figá-Talamanca & Sergio Focardi & Marco Patacca, 2021. "Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 863-882, December.
• Paolo Angelis & Roberto Marchis & Mario Marino & Antonio Luciano Martire & Immacolata Oliva, 2021. "Betting on bitcoin: a profitable trading between directional and shielding strategies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 883-903, December.
• Prilly Oktoviany & Robert Knobloch & Ralf Korn, 2021. "A machine learning-based price state prediction model for agricultural commodities using external factors," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1063-1085, December.
• Marcel Aloy & Floris Laly & Sébastien Laurent & Christelle Lecourt, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," Dynamic Modeling and Econometrics in Economics and Finance, in: Gilles Dufrénot & Takashi Matsuki (ed.), Recent Econometric Techniques for Macroeconomic and Financial Data, pages 229-264, Springer.
  • Aloy, Marcel & Laly, Floris & Laurent, Sébastien & Lecourt, Christelle, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," LIDAM Reprints LFIN 2021021, Université catholique de Louvain, Louvain Finance (LFIN).
  • Marcel Aloy & Floris Laly & Sébastien Laurent & Christelle Lecourt, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," Post-Print hal-03103717, HAL.
• Alain Kabundi & Asithandile Mbelu, 2021. "Estimating a time-varying financial conditions index for South Africa," Empirical Economics, Springer, vol. 60(4), pages 1817-1844, April.
  • Alain Kabundi & Asi Mbelu, 2017. "Estimating a timevarying financial conditions index for South Africa," Working Papers 8008, South African Reserve Bank.
• Yongchen Zhao, 2021. "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
• Jack Fosten & Daniel Gutknecht, 2021. "Horizon confidence sets," Empirical Economics, Springer, vol. 61(2), pages 667-692, August.
• Serdar Neslihanoglu & Stelios Bekiros & John McColl & Duncan Lee, 2021. "Multivariate time-varying parameter modelling for stock markets," Empirical Economics, Springer, vol. 61(2), pages 947-972, August.
• Georges Tsafack & James Cataldo, 2021. "Backtesting and estimation error: value-at-risk overviolation rate," Empirical Economics, Springer, vol. 61(3), pages 1351-1396, September.
• Edmond Berisha & David Gabauer & Rangan Gupta & Chi Keung Marco Lau, 2021. "Time-varying influence of household debt on inequality in United Kingdom," Empirical Economics, Springer, vol. 61(4), pages 1917-1933, October.
  • Edmond Berisha & David Gabauer & Rangan Gupta & Chi Keung Marco Lau, 2020. "Time-Varying Influence of Household Debt on Inequality in United Kingdom," Working Papers 202017, University of Pretoria, Department of Economics.
• Angela Capolongo & Claudia Pacella, 2021. "Forecasting inflation in the euro area: countries matter!," Empirical Economics, Springer, vol. 61(5), pages 2477-2499, November.
  • Angela Capolongo & Claudia Pacella, 2019. "Forecasting inflation in the euro area: countries matter!," Temi di discussione (Economic working papers) 1224, Bank of Italy, Economic Research and International Relations Area.
• Nima Nonejad, 2021. "Crude oil price point forecasts of the Norwegian GDP growth rate," Empirical Economics, Springer, vol. 61(5), pages 2913-2930, November.
• Ahmet Akca & Ethem Çanakoğlu, 2021. "Adaptive stochastic risk estimation of firm operating profit," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 48(3), pages 463-504, September.
• David Y. Aharon & Zaghum Umar & Xuan Vinh Vo, 2021. "Dynamic spillovers between the term structure of interest rates, bitcoin, and safe-haven currencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-25, December.
• Christian Stummer & Lars Lüpke & Markus Günther, 2021. "Beaming market simulation to the future by combining agent-based modeling with scenario analysis," Journal of Business Economics, Springer, vol. 91(9), pages 1469-1497, November.
• Martin Pažický, 2021. "Predicting Recessions in Germany Using the German and the US Yield Curve," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 263-291, December.
• Pelin Akyol & Kala Krishna & Jinwen Wang, 2021. "Taking PISA Seriously: How Accurate are Low-Stakes Exams?," Journal of Labor Research, Springer, vol. 42(2), pages 184-243, June.
  • Ş. Pelin Akyol & Kala Krishna & Jinwen Wang, 2018. "Taking PISA Seriously: How Accurate are Low Stakes Exams?," NBER Working Papers 24930, National Bureau of Economic Research, Inc.
• Filippo Massari, 2021. "Price probabilities: a class of Bayesian and non-Bayesian prediction rules," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(1), pages 133-166, July.
• Annalisa Cristini & Piero Ferri, 2021. "Nonlinear models of the Phillips curve," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1129-1155, September.
• Ali Habibnia & Esfandiar Maasoumi, 2021. "Forecasting in Big Data Environments: An Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 363-381, December.
  • Ali Habibnia & Esfandiar Maasoumi, 2019. "Forecasting in Big Data Environments: an Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet)," Papers 1904.11145, arXiv.org.
• Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
• Subhash C. Sharma & Anil K. Bera, 2021. "Estimation of Random Components and Prediction in One and Two-Way Error Component Regression Models," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 419-441, December.
• Guilherme Lindenmeyer & Pedro Pablo Skorin & Hudson da Silva Torrent, 2021. "Using boosting for forecasting electric energy consumption during a recession: a case study for the Brazilian State Rio Grande do Sul," Letters in Spatial and Resource Sciences, Springer, vol. 14(2), pages 111-128, August.
• Ricarda B. Bouncken & Yixin Qiu & Noemi Sinkovics & Wolfgang Kürsten, 2021. "Qualitative research: extending the range with flexible pattern matching," Review of Managerial Science, Springer, vol. 15(2), pages 251-273, February.
• Rosina O. Weber & Kedma B. Duarte, 2021. "Data-driven artificial intelligence to automate researcher assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3265-3281, April.
• Rodrigo Mulero & Alfredo García-Hiernaux, 2021. "Forecasting Spanish unemployment with Google Trends and dimension reduction techniques," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(3), pages 329-349, September.
• Ángel Cuevas & Ramiro Ledo & Enrique M. Quilis, 2021. "Seasonal adjustment of the Spanish sales daily data," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(4), pages 687-708, December.
• Javier Ojea-Ferreiro, 2021. "Deconstructing Systemic Risk: A Reverse Stress Testing Approach," Springer Books, in: Marco Corazza & Manfred Gilli & Cira Perna & Claudio Pizzi & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 369-375, Springer.
  • Javier Ojea-Ferreiro, 2021. "Deconstructing systemic risk: A reverse stress testing approach," CNMV Working Papers CNMV Working Papers no. 7, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
• Raad Mozib Lalon & PhD & Nusrat Jahan, 2021. "Predicting Economic Performance of Bangladesh using Autoregressive Integrated Moving Average (ARIMA) model," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 11(2), pages 1-5.
• Yu-Min Lian & Chia-Hsuan Li & Yi-Hsuan Wei, 2021. "Machine Learning and Time Series Models for VNQ Market Predictions," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 11(5), pages 1-2.
• Rebecca F. Gleditsch & Adrian F. Rogne & Astri Syse & Michael Thomas, 2021. "The accuracy of Statistics Norway’s national population projections," Discussion Papers 948, Statistics Norway, Research Department.
• Pål Boug & Håvard Hungnes & Takamitsu Kurita, 2021. "The empirical modelling of house prices and debt revisited. A policy-oriented perspective," Discussion Papers 967, Statistics Norway, Research Department.
• Martin Iseringhausen, 2021. "A time-varying skewness model for Growth-at-Risk," Working Papers 49, European Stability Mechanism.
• Clements, Adam & Vasnev, Andrey, 2021. "Forecast combination puzzle in the HAR model," Working Papers BAWP-2021-01, University of Sydney Business School, Discipline of Business Analytics.
• Magnus, Jan & Vasnev, Andrey, 2021. "On the uncertainty of a combined forecast: The critical role of correlation," Working Papers BAWP-2022-01, University of Sydney Business School, Discipline of Business Analytics.
• Hanjo Odendaal, 2021. "A machine learning approach to domain specific dictionary generation. An economic time series framework," Working Papers 06/2021, Stellenbosch University, Department of Economics.
• Constantin Bürgi & Tara M. Sinclair, 2021. "What does forecaster disagreement tell us about the state of the economy?," Applied Economics Letters, Taylor & Francis Journals, vol. 28(1), pages 49-53, January.
  • Constantin Bürgi & Tara M. Sinclair, 2020. "What Does Forecaster Disagreement Tell Us about the State of the Economy?," Working Papers 2020-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2021. "A note on oil price shocks and the forecastability of gold realized volatility," Applied Economics Letters, Taylor & Francis Journals, vol. 28(21), pages 1889-1897, December.
  • Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2020. "A Note on Oil Price Shocks and the Forecastability of Gold Realized Volatility," Working Papers 202010, University of Pretoria, Department of Economics.
• Antonio Rodríguez Andrés & Voxi Heinrich S. Amavilah & Abraham Otero, 2021. "Evaluation of technology clubs by clustering: a cautionary note," Applied Economics, Taylor & Francis Journals, vol. 53(52), pages 5989-6001, November.
  • Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Evaluation of technology clubs by clustering: A cautionary note," MPRA Paper 109138, University Library of Munich, Germany.
• Tommaso Proietti, 2021. "Predictability, real time estimation, and the formulation of unobserved components models," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 433-454, April.
  • Tommaso Proietti, 2019. "Predictability, Real Time Estimation, and the Formulation of Unobserved Components Models," CEIS Research Paper 455, Tor Vergata University, CEIS, revised 22 Mar 2019.
• Antoine A. Djogbenou, 2021. "Model selection in factor-augmented regressions with estimated factors," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 470-503, April.
  • Antoine A. Djogbenou, 2017. "Model Selection In Factor-augmented Regressions With Estimated Factors," Working Paper 1391, Economics Department, Queen's University.
• Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2021. "Confidence Intervals for Bias and Size Distortion in IV and Local Projections-IV Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 307-324, January.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections — IV models," Working Papers 1841, Banco de España.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence Intervals for Bias and Size Distortion in IV and Local Projections–IV Models," Working Papers 1077, Barcelona School of Economics.
  • Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections–IV models," Economics Working Papers 1640, Department of Economics and Business, Universitat Pompeu Fabra.
• Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2021. "Price Dividend Ratio and Long-Run Stock Returns: A Score-Driven State Space Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1054-1065, October.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," CEPR Discussion Papers 14107, C.E.P.R. Discussion Papers.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers) 1296, Bank of Italy, Economic Research and International Relations Area.
  • Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," EMF Research Papers 29, Economic Modelling and Forecasting Group.
  • Delle Monache, Davide & Venditti, Fabrizio & Petrella, Ivan, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Working Paper Series 2369, European Central Bank.
• Selcuk Gul & Abdullah Kazdal, 2021. "Nowcasting and Short-term Forecasting Turkish GDP: Factor-MIDAS Approach," Working Papers 2111, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Ioannis Sitzimis, 2021. "An Optimal Forecasting Method of Passenger Traffic in Greek Coastal Shipping," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 14(3), pages 72-87, December.
• Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2020. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Working Paper series 20-27, Rimini Centre for Economic Analysis.
  • Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2021. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Tinbergen Institute Discussion Papers 21-016/III, Tinbergen Institute.
• Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
  • Knut Are Aastveit & Jamie Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Tinbergen Institute Discussion Papers 21-053/III, Tinbergen Institute.
  • Knut Are Aastveit & Jamie Cross & Herman K. Djik, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Papers No 03/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Yongchen Zhao, 2021. "Uncertainty and Disagreement of Inflation Expectations: Evidence from Household-Level Qualitative Survey Responses," Working Papers 2021-03, Towson University, Department of Economics, revised Dec 2021.
• K. Peren Arin & Kevin Devereux & Mieszko Mazur, 2021. "Taxes and firm investment," CAMA Working Papers 2021-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • K. Peren Arin & Kevin Devereux & Mieszko Mazur, 2021. "Taxes and Firm Investment," Working Papers 202102, School of Economics, University College Dublin.
• Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2021. "Efficient Combined Estimation under Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202107, University of Kansas, Department of Economics.
  • Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2021. "Efficient Combined Estimation under Structural Breaks," Working Papers 202101, University of California at Riverside, Department of Economics.
• Nadiia Shapovalenko, 2021. "A BVAR Model for Forecasting Ukrainian Inflation and GDP," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 251, pages 14-36.
• Mubarok, Faizul & Al Arif, Mohammad Nur Rianto, 2021. "Pandemic Attack and Islamic Stocks Index: A Cross Country Analysis," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 55(1), pages 27-37.
• Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
  • Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating forecast performance with state dependence," Economics Working Papers 1800, Department of Economics and Business, Universitat Pompeu Fabra.
• Monica Billio & Roberto Casarin & Enrica De Cian & Malcolm Mistry & Anthony Osuntuyi, 2020. "The impact of Climate on Economic and Financial Cycles: A Markov-switching Panel Approach," Papers 2012.14693, arXiv.org.
  • Monica Billio & Roberto Casarin & Enrica De Cian & Malcolm Mistry & Anthony Osuntuyi, 2021. "The Impact of Climate on Economic and Financial Cycles: A Markov-switching Panel Approach," Working Papers 2021:03, Department of Economics, University of Venice "Ca' Foscari".
• Jitender, 2021. "Value-at-Risk Estimation of Equity Market Risk in India," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 9(1), pages 1-24, September.
• Kaczmarczyk Paweł, 2021. "Econometric Modelling of Compound Cyclicality of using Telecommunication Services," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 25(2), pages 27-45, June.
• Chi Yeong Nain & Chi Orson, 2021. "Modeling and Forecasting of Monthly Global Price of Bananas Using Seasonal Arima and Multilayer Perceptron Neural Network," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 25(3), pages 21-41, September.
• Lauraéus Theresa & Kaivo-oja Jari & Knudsen Mikkel S. & Kuokkanen Kimmo, 2021. "Market Structure analysis with Herfindahl-Hirchman Index and Lauraéus-Kaivo-Oja Indices in the Global Cobotics Markets," Economics and Culture, Sciendo, vol. 18(1), pages 70-81, June.
• Wang Guan-Yuan, 2021. "The Brand Effect: A Case Study in Taiwan Second-Hand Smartfhone Market," Journal of Social and Economic Statistics, Sciendo, vol. 10(1-2), pages 30-42, December.
• Ataguba Joseph Obaje, 2021. "Synthesis of Short-Cut DCF Appraisal and Spreadsheet Iteration of Freehold Rental Growth Rates Across Specific Valuation Epochs," Real Estate Management and Valuation, Sciendo, vol. 29(2), pages 52-70, June.
• Ramadani Gani & Petrovska Magdalena & Bucevska Vesna, 2021. "Evaluation of Mixed Frequency Approaches for Tracking Near-Term Economic Developments in North Macedonia," South East European Journal of Economics and Business, Sciendo, vol. 16(2), pages 43-52, December.
• Dawid Siwicki, 2021. "The Application of Machine Learning Algorithms for Spatial Analysis: Predicting of Real Estate Prices in Warsaw," Working Papers 2021-05, Faculty of Economic Sciences, University of Warsaw.
• Mateusz Buczyński & Marcin Chlebus, 2021. "GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks," Working Papers 2021-08, Faculty of Economic Sciences, University of Warsaw.
• Michał Woźniak & Marcin Chlebus, 2021. "HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation," Working Papers 2021-10, Faculty of Economic Sciences, University of Warsaw.
• Szymon Lis & Marcin Chlebus, 2021. "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers 2021-11, Faculty of Economic Sciences, University of Warsaw.
• Piotr Borowski & Marcin Chlebus, 2021. "Machine learning in the prediction of flat horse racing results in Poland," Working Papers 2021-13, Faculty of Economic Sciences, University of Warsaw.
• Kamil Korzeń & Robert Ślepaczuk, 2021. "Enhanced Index Replication Based on Smart Beta and Tail-Risk Asset Allocation," Working Papers 2021-18, Faculty of Economic Sciences, University of Warsaw.
• Michał Lewandowski & Marcin Chlebus, 2021. "Predicting football outcomes from Spanish league using machine learning models," Working Papers 2021-22, Faculty of Economic Sciences, University of Warsaw.
• Jan Grudniewicz & Robert Ślepaczuk, 2021. "Application of machine learning in quantitative investment strategies on global stock markets," Working Papers 2021-23, Faculty of Economic Sciences, University of Warsaw.
• Nguyen Vo & Robert Ślepaczuk, 2021. "Applying Hybrid ARIMA-SGARCH in Algorithmic Investment Strategies on S&P500 Index," Working Papers 2021-25, Faculty of Economic Sciences, University of Warsaw.
• Sergio Castellano Gómez & Robert Ślepaczuk, 2021. "Robust optimisation in algorithmic investment strategies," Working Papers 2021-27, Faculty of Economic Sciences, University of Warsaw.
• Aleksander Schiffers & Marcin Chlebus, 2021. "The effectiveness of Value-at-Risk models in various volatility regimes," Working Papers 2021-28, Faculty of Economic Sciences, University of Warsaw.
• Stefan Jestl & Robert Stehrer, 2021. "EU Employment Dynamics: The Pandemic Years and Beyond," wiiw Research Reports 457, The Vienna Institute for International Economic Studies, wiiw.
• Kufenko, Vadim & Prettner, Klaus, 2021. "Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators," Department of Economics Working Paper Series 316, WU Vienna University of Economics and Business.
  • Vadim Kufenko & Klaus Prettner, 2021. "Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators," Department of Economics Working Papers wuwp316, Vienna University of Economics and Business, Department of Economics.
• Vadim Kufenko & Klaus Prettner, 2021. "Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators," Department of Economics Working Papers wuwp316, Vienna University of Economics and Business, Department of Economics.
  • Kufenko, Vadim & Prettner, Klaus, 2021. "Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators," Department of Economics Working Paper Series 316, WU Vienna University of Economics and Business.
• Reinhard Ellwanger, Stephen Snudden, 2021. "Predictability of Aggregated Time Series," LCERPA Working Papers bm0127, Laurier Centre for Economic Research and Policy Analysis.
• Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2021. "Dynamic return and volatility spillovers among S&P 500, crude oil, and gold," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 153-170, January.
  • Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2018. "Dynamic return and volatility spillovers among S&P 500, crude oil and gold," Working Papers 15-46, Eastern Mediterranean University, Department of Economics.
• Jörg Breitung & Malte Knüppel, 2021. "How far can we forecast? Statistical tests of the predictive content," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 369-392, June.
  • Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021. "No‐arbitrage priors, drifting volatilities, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 495-516, August.
  • Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," Working Papers 20-27, Federal Reserve Bank of Cleveland.
• Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
  • Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2019. "Focused Bayesian Prediction," Papers 1912.12571, arXiv.org, revised Aug 2020.
  • Ruben Loaiza-Maya & Gael M Martin & David T. Frazier, 2020. "Focused Bayesian Prediction," Monash Econometrics and Business Statistics Working Papers 1/20, Monash University, Department of Econometrics and Business Statistics.
• Till Weigt & Bernd Wilfling, 2021. "An approach to increasing forecast‐combination accuracy through VAR error modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 686-699, July.
  • Till Weigt & Bernd Wilfling, 2018. "An approach to increasing forecast-combination accuracy through VAR error modeling," CQE Working Papers 6818, Center for Quantitative Economics (CQE), University of Muenster.
• Ricardo Crisóstomo, 2021. "Estimating real‐world probabilities: A forward‐looking behavioral framework," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1797-1823, November.
  • Ricardo Cris'ostomo, 2020. "Estimating real-world probabilities: A forward-looking behavioral framework," Papers 2012.09041, arXiv.org, revised Jan 2021.
  • Ricardo Crisóstomo, 2021. "Estimating real word probabilities: a forward-looking behavioral framework," CNMV Working Papers CNMV Working Papers no. 7, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
• Benjamin K. Johannsen & Elmar Mertens, 2021. "A Time‐Series Model of Interest Rates with the Effective Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(5), pages 1005-1046, August.
  • Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
  • Benjamin K Johannsen & Elmar Mertens, 2018. "A time series model of interest rates with the effective lower bound," BIS Working Papers 715, Bank for International Settlements.
• John B. Donaldson & Rajnish Mehra, 2021. "Average crossing time: An alternative characterization of mean aversion and reversion," Quantitative Economics, Econometric Society, vol. 12(3), pages 903-944, July.
  • John B. Donaldson & Rajnish Mehra, 2019. "Average Crossing Time: An Alternative Characterization of Mean Aversion and Reversion," NBER Working Papers 25519, National Bureau of Economic Research, Inc.
• Garg, Karan, 2021. "Machines and Markets : Assessing the Impact of Algorithmic Trading on Financial Market Efficiency," Warwick-Monash Economics Student Papers 11, Warwick Monash Economics Student Papers.
• Aldott, Zoltan, 2021. "Predicting Specialty Coffee Auction Prices Using Machine Learning," Warwick-Monash Economics Student Papers 15, Warwick Monash Economics Student Papers.
• Gan-Ochir Doojav & Davaasukh Damdinjav, 2021. "Policy-Driven Boom and Bust in the Housing Market: Evidence from Mongolia," Asian Development Review (ADR), World Scientific Publishing Co. Pte. Ltd., vol. 38(02), pages 279-317, September.
  • Doojav, Gan-Ochir & Damdinjav, Davaasukh, 2019. "The policy-driven boom and bust in the housing market: Evidence from Mongolia," MPRA Paper 102933, University Library of Munich, Germany, revised 2019.
• Soumya Bhadury & Saurabh Ghosh & Pankaj Kumar, 2021. "Constructing a Coincident Economic Indicator for India: How Well Does It Track Gross Domestic Product?," Asian Development Review (ADR), World Scientific Publishing Co. Pte. Ltd., vol. 38(02), pages 237-277, September.
• Gan-Ochir Doojav & Davaasukh Damdinjav, 2021. "Policy-Driven Boom and Bust in the Housing Market: Evidence from Mongolia," Asian Development Review (ADR), World Scientific Publishing Co. Pte. Ltd., vol. 38(02), pages 279-317, September.
  • Gan-Ochir Doojav & Davaasukh Damdinjav, 2021. "Policy-Driven Boom and Bust in the Housing Market: Evidence from Mongolia," Surface Review and Letters (SRL), World Scientific Publishing Co. Pte. Ltd., vol. 38(02), pages 279-317.
  • Doojav, Gan-Ochir & Damdinjav, Davaasukh, 2019. "The policy-driven boom and bust in the housing market: Evidence from Mongolia," MPRA Paper 102933, University Library of Munich, Germany, revised 2019.
• Soumya Bhadury & Saurabh Ghosh & Pankaj Kumar, 2021. "Constructing a Coincident Economic Indicator for India: How Well Does It Track Gross Domestic Product?," Asian Development Review (ADR), World Scientific Publishing Co. Pte. Ltd., vol. 38(02), pages 237-277, September.
  • Soumya Bhadury & Saurabh Ghosh & Pankaj Kumar, 2021. "Constructing a Coincident Economic Indicator for India: How Well Does It Track Gross Domestic Product?," Surface Review and Letters (SRL), World Scientific Publishing Co. Pte. Ltd., vol. 38(02), pages 237-277.
• Laura Coroneo & Fabrizio Iacone, 2021. "Testing for equal predictive accuracy with strong dependence," Discussion Papers 21/03, Department of Economics, University of York.
• Laura Coroneo, & Fabrizio Iacone, & Giancarlo Manzi, & Silvia Salini, 2021. "Predicting the COVID-19 epidemic: is a regional approach preferable?," Discussion Papers 21/06, Department of Economics, University of York.
• Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2021. "The bias and efficiency of the ECB inflation projections: A state dependent analysis," Bank of Finland Research Discussion Papers 7/2021, Bank of Finland.
• Manuel M. F. Martins & Fabio Verona, 2021. "Inflation Dynamics and Forecast: Frequency Matters," CEF.UP Working Papers 2101, Universidade do Porto, Faculdade de Economia do Porto.
  • Martins, Manuel Mota Freitas & Verona, Fabio, 2021. "Inflation dynamics and forecast: Frequency matters," Bank of Finland Research Discussion Papers 8/2021, Bank of Finland.
• , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
  • Mönch, Emanuel & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," Discussion Papers 25/2021, Deutsche Bundesbank.
• Marta Bañbura & Danilo Leiva-León & Jan-Oliver Menz, 2021. "Do inflation expectations improve model-based inflation Forecasts?," Working Papers 2138, Banco de España.
  • Bańbura, Marta & Leiva-León, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Discussion Papers 48/2021, Deutsche Bundesbank.
  • Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
• Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
• Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš, 2022. "YOLO trading: Riding with the herd during the GameStop episode," Finance Research Letters, Elsevier, vol. 46(PA).
  • Lyócsa, Štefan & Baumöhl, Eduard & Vŷrost, Tomáš, 2021. "YOLO trading: Riding with the herd during the GameStop episode," EconStor Preprints 230679, ZBW - Leibniz Information Centre for Economics.
• Hauber, Philipp, 2021. "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints 251469, ZBW - Leibniz Information Centre for Economics.
• Bubalo, Branko, 2021. "Airport Capacity and Performance in Europe - A study of transport economics, service quality and sustainability," EconStor Theses, ZBW - Leibniz Information Centre for Economics, number 229442.
• Hügle, Dominik, 2021. "The decision to enrol in higher education," Discussion Papers 2021/8, Free University Berlin, School of Business & Economics.
• Cerqua, Augusto & Letta, Marco, 2022. "Local inequalities of the COVID-19 crisis," Regional Science and Urban Economics, Elsevier, vol. 92(C).
  • Cerqua, Augusto & Letta, Marco, 2021. "Local inequalities of the COVID-19 crisis," GLO Discussion Paper Series 875, Global Labor Organization (GLO).
• Stamer, Vincent, 2021. "Thinking outside the container: A machine learning approach to forecasting trade flows," Kiel Working Papers 2179, Kiel Institute for the World Economy (IfW Kiel).
• Milivojevic, Lazar & Tatar, Balint, 2021. "Fixed exchange rate - a friend or foe of labor cost adjustments?," IMFS Working Paper Series 152, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
• Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Working Papers EPRG2110, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • Agarwala, Matthew & Burke, Matt & Klusak, Patrycja & Kraemer, Moritz & Mohaddes, Kamiar, 2021. "Rising temperatures, falling ratings: The effect of climate change on sovereign creditworthiness," IMFS Working Paper Series 158, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
  • Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising temperatures, falling ratings: The effect of climate change on sovereign creditworthiness," CAMA Working Papers 2021-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Klusak, P. & Agarwala, M. & Burke, M. & Kraemer, M. & Mohaddes, K., 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Cambridge Working Papers in Economics 2127, Faculty of Economics, University of Cambridge.
• Wei Li & Florentina Paraschiv & Georgios Sermpinis, 2021. "A Data-driven Explainable Case-based Reasoning Approach for Financial Risk Detection," Papers 2107.08808, arXiv.org.
  • Li, Wei & Paraschiv, Florentina & Sermpinis, Georgios, 2021. "A data-driven explainable case-based reasoning approach for financial risk detection," IRTG 1792 Discussion Papers 2021-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Glas, Alexander & Heinisch, Katja, 2021. "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers 7/2021, Halle Institute for Economic Research (IWH).
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Zeddies, Götz, 2021. "Investitionen, Auslastungsgrad und Öffentliche Finanzen in der mittleren Frist: Implikationen des Zweiten Nachtragshaushalts 2021," Konjunktur aktuell, Halle Institute for Economic Research (IWH), vol. 9(4), pages 141-148.
• Blagov, Boris & Müller, Henrik & Jentsch, Carsten & Schmidt, Torsten, 2021. "The investment narrative: Improving private investment forecasts with media data," Ruhr Economic Papers 921, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Kremer, Manfred & Chavleishvili, Sulkhan, 2021. "Measuring Systemic Financial Stress and its Impact on the Macroeconomy," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242346, Verein für Socialpolitik / German Economic Association.

2020

• Andreas Psimopoulos, 2020. "Forecasting Economic Recessions Using Machine Learning:An Empirical Study in Six Countries," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 18(1), pages 40-99.
• Martínez Vázquez, David Conaly & Pérez Avila, Héctor, 2020. "Proyección Markoviana de riesgos hidrometeorológicos para el cálculo actuarial en México al 2020 / Markovian projection of hydrometeorological risks for actuarial calculation in Mexico up to 2020," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 10(2), pages 163-194, julio-dic.
• Henry Nasses & Rodrigo De Losso, 2020. "Behavior Biases in Macroeconomic Forecasting," Working Papers, Department of Economics 2020_23, University of São Paulo (FEA-USP).
• Ducoudré, Bruno & Hubert, Paul & Tabarly, Guilhem, 2020. "The state-dependence of output revisions," Economics Letters, Elsevier, vol. 192(C).
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Post-Print hal-03403017, HAL.
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Sciences Po publications 04/2020, Sciences Po.
  • Bruno Ducoudré & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Documents de Travail de l'OFCE 2020-04, Observatoire Francais des Conjonctures Economiques (OFCE).
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," SciencePo Working papers Main hal-03403073, HAL.
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Working Papers hal-03403073, HAL.
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Sciences Po publications info:hdl:2441/2q9catktmn9, Sciences Po.
  • Bruno Ducoudre & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," SciencePo Working papers Main hal-03403017, HAL.
• Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Documents de Travail de l'OFCE 2020-06, Observatoire Francais des Conjonctures Economiques (OFCE).
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Sciences Po publications 06/2020, Sciences Po.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," SciencePo Working papers Main hal-03403077, HAL.
  • Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," CEPR Discussion Papers 14322, C.E.P.R. Discussion Papers.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Working Papers hal-03403077, HAL.
  • Reichlin, Lucrezia & Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial variables as predictors of real growth vulnerability," Discussion Papers 05/2020, Deutsche Bundesbank.
• Bernard Fingleton, 2020. "Exploring Brexit with dynamic spatial panel models: some possible outcomes for employment across the EU regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 455-491, April.
  • Fingleton, Bernard, 2018. "Exploring Brexit with dynamic spatial panel models : some possible outcomes for employment across the EU regions," MPRA Paper 86553, University Library of Munich, Germany.
• Joanna Bruzda, 2020. "Multistep quantile forecasts for supply chain and logistics operations: bootstrapping, the GARCH model and quantile regression based approaches," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 309-336, March.
• Theophilos Papadimitriou & Periklis Gogas & Athanasios Fotios Athanasiou, 2020. "Forecasting S&P 500 spikes: an SVM approach," Digital Finance, Springer, vol. 2(3), pages 241-258, December.
• Rangan Gupta & Hylton Hollander & Rudi Steinbach, 2020. "Forecasting output growth using a DSGE-based decomposition of the South African yield curve," Empirical Economics, Springer, vol. 58(1), pages 351-378, January.
  • Rangan Gupta & Hylton Hollander & Rudi Steinbach, 2015. "Forecasting Output Growth using a DSGE-Based Decomposition of the South African Yield Curve," Working Papers 201567, University of Pretoria, Department of Economics.
• Nima Nonejad, 2020. "Does the price of crude oil help predict the conditional distribution of aggregate equity return?," Empirical Economics, Springer, vol. 58(1), pages 313-349, January.
• Christian Glocker & Philipp Wegmueller, 2020. "Business cycle dating and forecasting with real-time Swiss GDP data," Empirical Economics, Springer, vol. 58(1), pages 73-105, January.
  • Christian Glocker & Philipp Wegmüller, 2017. "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers 542, WIFO.
• M. Chudý & S. Karmakar & W. B. Wu, 2020. "Long-term prediction intervals of economic time series," Empirical Economics, Springer, vol. 58(1), pages 191-222, January.
• Boriss Siliverstovs, 2020. "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
  • Boriss Siliverstovs, 2019. "Assessing Nowcast Accuracy of US GDP Growth in Real Time: The Role of Booms and Busts," Working Papers 2019/01, Latvijas Banka.
• Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
• Gabe Jacob de Bondt & Arne Gieseck & Zivile Zekaite, 2020. "Thick modelling income and wealth effects: a forecast application to euro area private consumption," Empirical Economics, Springer, vol. 58(1), pages 257-286, January.
• Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.
• João C. Claudio & Katja Heinisch & Oliver Holtemöller, 2020. "Nowcasting East German GDP growth: a MIDAS approach," Empirical Economics, Springer, vol. 58(1), pages 29-54, January.
  • Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
• Ines Fortin & Sebastian P. Koch & Klaus Weyerstrass, 2020. "Evaluation of economic forecasts for Austria," Empirical Economics, Springer, vol. 58(1), pages 107-137, January.
• Christian Pierdzioch & Marian Risse, 2020. "Forecasting precious metal returns with multivariate random forests," Empirical Economics, Springer, vol. 58(3), pages 1167-1184, March.
• Kyle E. Binder & Mohsen Pourahmadi & James W. Mjelde, 2020. "The role of temporal dependence in factor selection and forecasting oil prices," Empirical Economics, Springer, vol. 58(3), pages 1185-1223, March.
• Aitor Ciarreta & Peru Muniain & Ainhoa Zarraga, 2020. "Realized volatility and jump testing in the Japanese electricity spot market," Empirical Economics, Springer, vol. 58(3), pages 1143-1166, March.
• Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
• João F. Caldeira, 2020. "Investigating the expectation hypothesis and the risk premium dynamics: new evidence for Brazil," Empirical Economics, Springer, vol. 59(1), pages 395-412, July.
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• Hutter, Christian, 2020. "A new indicator for nowcasting employment subject to social security contributions in Germany," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 54(1), pages 1-4.
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• Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
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• R. Erasmus & H. Hollander, 2020. "A Forward Guidance Indicator For The South African Reserve Bank: Implementing A Text Analysis Algorithm," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 44(3), pages 41-72, December.
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• R. Erasmus & H. Hollander, 2020. "A Forward Guidance Indicator For The South African Reserve Bank: Implementing A Text Analysis Algorithm," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 44(3), pages 41-72, December.
  • Ruan Erasmus & Hylton Hollander, 2020. "A Forward Guidance Indicator For The South African Reserve Bank: Implementing A Text Analysis Algorithm," Working Papers 04/2020, Stellenbosch University, Department of Economics.
• Troy Lorde & Antonio Alleyne & Roger Hosein & Mu Yifei, 2020. "Should the Caribbean Look to the East? An Assessment of Caribbean Export Potential," The International Trade Journal, Taylor & Francis Journals, vol. 34(1), pages 136-150, January.
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• Islam, Raisul & Volkov, Vladimir, 2020. "Contagion or interdependence? Comparing signed and unsigned spillovers," Working Papers 2020-05, University of Tasmania, Tasmanian School of Business and Economics.
• Islam, Raisul & Volkov, Vladimir, 2020. "Calm before the storm: an early warning approach before and during the COVID-19 crisis," Working Papers 2020-09, University of Tasmania, Tasmanian School of Business and Economics.
• Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
• Mahmut Gunay, 2020. "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers 2002, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Mahmut Gunay, 2020. "Nowcasting Turkish GDP Growth with Targeted Predictors: Fill in the Blanks," Working Papers 2006, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
• Blasques, Francisco & Hoogerkamp, Meindert Heres & Koopman, Siem Jan & van de Werve, Ilka, 2021. "Dynamic factor models with clustered loadings: Forecasting education flows using unemployment data," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1426-1441.
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• Noussair, C.N. & Popescu, Andreea Victoria, 2020. "Contagion and Return Predictability in Asset Markets : An Experiment with Two Lucas Trees," Discussion Paper 2020-014, Tilburg University, Center for Economic Research.
• Kohei Maehashi & Mototsugu Shintani, 2020. "Macroeconomic Forecasting Using Factor Models and Machine Learning: An Application to Japan," CIRJE F-Series CIRJE-F-1146, CIRJE, Faculty of Economics, University of Tokyo.
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• Lahiri, Kajal & Zhao, Yongchen, 2020. "The Nordhaus test with many zeros," Economics Letters, Elsevier, vol. 193(C).
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• Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
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• Michael Safo OFORI & Abel FUMEY & Edward NKETIAH-AMPONSAH, 2020. "Forecasting Value Added Tax Revenue in Ghana," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 4(2), pages 63-99.
• Haase, Felix & Neuenkirch, Matthias, 2023. "Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US," International Journal of Forecasting, Elsevier, vol. 39(2), pages 587-605.
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• Haase, Felix & Neuenkirch, Matthias, 2023. "Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US," International Journal of Forecasting, Elsevier, vol. 39(2), pages 587-605.
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  • Felix Haase & Matthias Neuenkirch, 2021. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," CESifo Working Paper Series 8828, CESifo.
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• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
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• Benedikt Janzen & Doina Radulescu, 0. "Electricity Use as a Real-Time Indicator of the Economic Burden of the COVID-19-Related Lockdown: Evidence from Switzerland," CESifo Economic Studies, CESifo, vol. 66(4), pages 303-321.
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• Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020. "Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
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• Dmytro Krukovets, 2020. "Data Science Opportunities at Central Banks: Overview," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 249, pages 13-24.
• Olivier Damette & Claude Diebolt & Stephane Goutte & Umberto Triacca, 2020. "Cliometrics of Climate Change: A Natural Experiment on the Little Ice Age," Working Papers 02-20, Association Française de Cliométrie (AFC).
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• Juan Equiza-Goñi, 2020. "WP02/20 Datos de mortalidad diarios durante la crisis del COVID-19: una propuesta de mejora," Faculty Working Papers 01/20, School of Economics and Business Administration, University of Navarra.
• Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Paper Series 2020-08, Federal Reserve Bank of San Francisco.
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• Breitenstein, Miriam & Anke, Carl-Philipp & Nguyen, Duc Khuong & Walther, Thomas, 2019. "Stranded Asset Risk and Political Uncertainty: The Impact of the Coal Phase-out on the German Coal Industry," MPRA Paper 101763, University Library of Munich, Germany.
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• WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," LIDAM Discussion Papers CORE 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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• Mesias Alfeus & Christina Sklibosios Nikitopoulos, 2020. "Forecasting Commodity Markets Volatility: HAR or Rough?," Research Paper Series 415, Quantitative Finance Research Centre, University of Technology, Sydney.
• Christina Sklibosios Nikitopoulos & Alice Thomas & Jianxin Wang, 2020. "The Economic Impact of Volatility Persistence on Energy Markets," Research Paper Series 417, Quantitative Finance Research Centre, University of Technology, Sydney.
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• SAHIN, Emrah & GUNGOR, Selim & KARACA, Suleyman Serdar, 2020. "Empirical Analysis Of The Relationship Between Purchasing Managers Index And Bist Industrial Index Under Structural Breaks," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 24(3), pages 6-22, September.
• Hristina Vasileva, 2020. "Application Of Logistic Regressionin Assessing The Credit Risk Of Smes," Economic Science, education and the real economy: Development and interactions in the digital age, Publishing house Science and Economics Varna, issue 1, pages 334-345.
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• Wodecki Andrzej, 2020. "The Reserve Price Optimization for Publishers on Real-Time Bidding on-Line Marketplaces with Time-Series Forecasting," Foundations of Management, Sciendo, vol. 12(1), pages 167-180, January.
• Wodecki Andrzej, 2020. "The Reserve Price Optimization for Publishers on Real-Time Bidding on-Line Marketplaces with Time-Series Forecasting," Foundations of Management, Sciendo, vol. 12(1), pages 167-180, January.
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• Gloria Gonzalez‐Rivera & Yun Luo & Esther Ruiz, 2020. "Prediction regions for interval‐valued time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 373-390, June.
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• Jonas Dovern & Hans Manner, 2020. "Order‐invariant tests for proper calibration of multivariate density forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 440-456, June.
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• Duc Khuong Nguyen & Thomas Walther, 2020. "Modeling and forecasting commodity market volatility with long‐term economic and financial variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 126-142, March.
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• Benedikt Maas, 2020. "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
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• Andrea Bucci, 2020. "Cholesky–ANN models for predicting multivariate realized volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 865-876, September.
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• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2020. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 934-943, September.
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• Elie Bouri & Riza Demirer & Rangan Gupta & Xiaojin Sun, 2020. "The predictability of stock market volatility in emerging economies: Relative roles of local, regional, and global business cycles," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 957-965, September.
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• Oguzhan Cepni & Rangan Gupta & I. Ethem Güney & M. Yilmaz, 2020. "Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 966-985, September.
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• Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
  • Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
• Galvao, Ana Beatriz & Mitchell, James, 2020. "Real-Time Perceptions of Historical GDP Data Uncertainty," EMF Research Papers 35, Economic Modelling and Forecasting Group.
• Clements, Michael P. & Galvao, Ana Beatriz, 2020. "Density Forecasting with BVAR Models under Macroeconomic Data Uncertainty," EMF Research Papers 36, Economic Modelling and Forecasting Group.
• Ana B. Galvão & Michael T. Owyang, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," Working Papers 2020-028, Federal Reserve Bank of St. Louis, revised Apr 2022.
  • Galvao, Ana Beatriz & Owyang, Michael, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," EMF Research Papers 38, Economic Modelling and Forecasting Group.
• Gaetano Perone, 2020. "An ARIMA model to forecast the spread and the final size of COVID-2019 epidemic in Italy," Health, Econometrics and Data Group (HEDG) Working Papers 20/07, HEDG, c/o Department of Economics, University of York.
• Berta, Paolo & Lovaglio, Pietro Giorgio & Paruolo, Paolo & Verzillo, Stefano, 2020. "Real Time Forecasting of Covid-19 Intensive Care Units demand," Working Papers 2020-08, Joint Research Centre, European Commission.
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• Perone, G., 2020. "Comparison of ARIMA, ETS, NNAR and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy," Health, Econometrics and Data Group (HEDG) Working Papers 20/18, HEDG, c/o Department of Economics, University of York.
• Sriubaite, I. & Harris, A. & Jones, A.M. & Gabbe, B., 2020. "Economic Consequences of Road Traffic Injuries. Application of the Super Learner algorithm," Health, Econometrics and Data Group (HEDG) Working Papers 20/20, HEDG, c/o Department of Economics, University of York.
• Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023. "Testing the predictive accuracy of COVID-19 forecasts," International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
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• Manuel M. F. Martins & Fabio Verona, 2020. "Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters," CEF.UP Working Papers 2001, Universidade do Porto, Faculdade de Economia do Porto.
  • Martins, Manuel Mota Freitas & Verona, Fabio, 2020. "Forecasting inflation with the New Keynesian Phillips curve: Frequency matters," Bank of Finland Research Discussion Papers 4/2020, Bank of Finland.
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  • Reichlin, Lucrezia & Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial variables as predictors of real growth vulnerability," Discussion Papers 05/2020, Deutsche Bundesbank.
  • Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," CEPR Discussion Papers 14322, C.E.P.R. Discussion Papers.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Working Papers hal-03403077, HAL.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Sciences Po publications 06/2020, Sciences Po.
  • Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," SciencePo Working papers Main hal-03403077, HAL.
• Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.
• Opiła, Janusz, 2020. "Employing of Extended Characteristic Surface Model for Forecasting of Demand in Tourism," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020, pages 60-73, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
• Sallam, Walid & Ahmed, Osama, 2020. "The socio-economic assessment to evaluate the potentiality of developing the rural community in Upper Egypt," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 143-165.
• Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
• Dieckelmann, Daniel, 2020. "Cross-border lending and the international transmission of banking crises," Discussion Papers 2020/13, Free University Berlin, School of Business & Economics.
• Fischer, Benjamin & Hügle, Dominik, 2020. "The private and fiscal returns to higher education: A simulation approach for a young German cohort," Discussion Papers 2020/21, Free University Berlin, School of Business & Economics.
• Hügle, Dominik, 2020. "Higher education funding in Germany: A distributional lifetime perspective," Discussion Papers 2021/1, Free University Berlin, School of Business & Economics.
• Seuffert, Stefan, 2020. "German Pension Simulation: Arbeitspapier zur Methodik eines anwartschaftsbasierten Projektionsmodells der gesetzlichen Rentenversicherung," FZG Discussion Papers 73, University of Freiburg, Research Center for Generational Contracts (FZG).
• Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jun 2021.
  • Dimitriadis, Timo & Patton, Andrew J. & Schmidt, Patrick W., 2020. "Testing forecast rationality for measures of central tendency," Hohenheim Discussion Papers in Business, Economics and Social Sciences 12-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
• Brighton, Henry, 2020. "Statistical foundations of ecological rationality," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-32.
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Wieschemeyer, Matthias & Zeddies, Götz, 2020. "Hohes öffentliches Defizit nicht nur wegen Corona: Mittelfristige Handlungsmöglichkeiten für den Staat," Konjunktur aktuell, Halle Institute for Economic Research (IWH), vol. 8(4), pages 150-161.
• Reh, Laura & Krüger, Fabian & Liesenfeld, Roman, 2020. "Predicting the global minimum variance portfolio," Working Paper Series in Economics 141, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
• Foltas, Alexander, 2020. "Testing investment forecast efficiency with textual data," Working Papers 19, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Foltas, Alexander & Pierdzioch, Christian, 2020. "On the efficiency of German growth forecasts: An empirical analysis using quantile random forests," Working Papers 21, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Alexander Foltas & Christian Pierdzioch, 2022. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Applied Economics Letters, Taylor & Francis Journals, vol. 29(10), pages 867-872, June.
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• Müller, Karsten, 2020. "German forecasters' narratives: How informative are German business cycle forecast reports?," Working Papers 23, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Behrens, Christoph, 2020. "German trade forecasts since 1970: An evaluation using the panel dimension," Working Papers 26, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Bluhm, Benjamin & Cutura, Jannic, 2020. "Econometrics at scale: Spark up big data in economics," SAFE Working Paper Series 266, Leibniz Institute for Financial Research SAFE.
• Grammig, Joachim & Hanenberg, Constantin & Schlag, Christian & Sönksen, Jantje, 2020. "Diverging roads: Theory-based vs. machine learning-implied stock risk premia," University of Tübingen Working Papers in Business and Economics 130, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
• Kaiser, Ulrich & Kuhn, Johan M., 2020. "The value of publicly available, textual and non-textual information for startup performance prediction," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
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• Berislav Žmuk & Hrvoje Jošiæ, 2020. "Forecasting stock market indices using machine learning algorithms," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 18(4), pages 471-489.
• Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
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• Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2020. "A statistical model of the global carbon budget," CREATES Research Papers 2020-18, Department of Economics and Business Economics, Aarhus University.
• Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2020. "Forecasting the US Dollar-Korean Won Exchange Rate: A Factor-Augmented Model Approach," Auburn Economics Working Paper Series auwp2020-02, Department of Economics, Auburn University.
• Wittwer, Glyn & Anderson, Kym, 2020. "A Model of Global Beverage Markets," Journal of Wine Economics, Cambridge University Press, vol. 15(3), pages 330-354, August.
  • Glyn Wittwer & Kym Anderson, 2020. "A model of global beverage markets," Departmental Working Papers 2020-05, The Australian National University, Arndt-Corden Department of Economics.
  • Glyn Wittwer & Kym Anderson, 2020. "A Model of Global Beverage Markets," Wine Economics Research Centre Working Papers 2019-05, University of Adelaide, Wine Economics Research Centre.
  • Wittwer, Glyn, 2020. "A Model of Global Beverage Markets," CEPR Discussion Papers 14387, C.E.P.R. Discussion Papers.
• Teboho Jeremiah Mosikari & Joel Hinaunye Eita, 2020. "Modelling Asymmetric Relationship between Exports and Growth in a Developing Economy: Evidence from Namibia," Economic Development and Well-being Research Group Working Paper Series edwrg-02-2020, University of Johannesburg, College of Business and Economics, revised 2020.
• Pedro Bordalo & Nicola Gennaioli & Yueran Ma & Andrei Shleifer, 2020. "Overreaction in Macroeconomic Expectations," American Economic Review, American Economic Association, vol. 110(9), pages 2748-2782, September.
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• Raffaella Giacomini & Vasiliki Skreta & Javier Turen, 2020. "Heterogeneity, Inattention, and Bayesian Updates," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(1), pages 282-309, January.
• Stefano DellaVigna & Nicholas Otis & Eva Vivalt, 2020. "Forecasting the Results of Experiments: Piloting an Elicitation Strategy," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 75-79, May.
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• Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020. "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers 4304, Asociación Argentina de Economía Política.
• J. Daniel Aromí & Martín Llada, 2020. "Forecasting inflation with twitter," Asociación Argentina de Economía Política: Working Papers 4308, Asociación Argentina de Economía Política.
• Emilio Blanco & Laura D’Amato & Fiorella Dogliolo & Lorena Garegnani, 2020. "Nowcasting Macroeconomic Aggregates in Argentina: Comparing the predictive ability of different models," Asociación Argentina de Economía Política: Working Papers 4335, Asociación Argentina de Economía Política.
• Maria Morena Rivera, 2020. "Estimación de Demanda de Milanesas de Cerdo y estudio de viabilidad financiera del proyecto: “Elaboración y comercialización de milanesas de cerdo para Piamontesa SA”," Asociación Argentina de Economía Política: Working Papers 4398, Asociación Argentina de Economía Política.
• Tamar Mdivnishvili & Shalva Mkhatrishvili & Davit Tutberidze, 2020. "Cash Flow at Risk Assessment for the Banking Sector of Georgia," NBG Working Papers 03/2020, National Bank of Georgia.
• Olivier DAMETTE & Claude DIEBOLT & Stephane GOUTTE & Umberto TRIACCA, 2020. "Cliometrics of Climate Change: A Natural Experiment on the Little Ice Age," Working Papers of BETA 2020-20, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
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• Enrico D’Elia & Francesca Faedda & Giacomo Giannone, 2020. "Un modello statistico per il monitoraggio delle entrate tributarie (MoME)," Working Papers wp2020-5, Ministry of Economy and Finance, Department of Finance.
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, vol. 13(7), pages 1-16, April.
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• Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices," Energies, MDPI, vol. 13(14), pages 1-19, July.
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• Tao Hong & Pierre Pinson & Yi Wang & Rafal Weron & Dazhi Yang & Hamidreza Zareipour, 2020. "Energy forecasting: A review and outlook," WORking papers in Management Science (WORMS) WORMS/20/08, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
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  • Domenico Dell