Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2021

• Martin Iseringhausen, 2021, "A time-varying skewness model for Growth-at-Risk," Working Papers, European Stability Mechanism, number 49, Jun.
• Clements, Adam & Vasnev, Andrey, 2021, "Forecast combination puzzle in the HAR model," Working Papers, University of Sydney Business School, Discipline of Business Analytics, number BAWP-2021-01, Feb.
• Magnus, Jan & Vasnev, Andrey, 2021, "On the uncertainty of a combined forecast: The critical role of correlation," Working Papers, University of Sydney Business School, Discipline of Business Analytics, number BAWP-2022-01, Dec.
• Hanjo Odendaal, 2021, "A machine learning approach to domain specific dictionary generation. An economic time series framework," Working Papers, Stellenbosch University, Department of Economics, number 06/2021.
• Constantin Bürgi & Tara M. Sinclair, 2021, "What does forecaster disagreement tell us about the state of the economy?," Applied Economics Letters, Taylor & Francis Journals, volume 28, issue 1, pages 49-53, January, DOI: 10.1080/13504851.2020.1730751.
• 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, volume 28, issue 21, pages 1889-1897, December, DOI: 10.1080/13504851.2020.1854658.
• Antonio Rodríguez Andrés & Voxi Heinrich S. Amavilah & Abraham Otero, 2021, "Evaluation of technology clubs by clustering: a cautionary note," Applied Economics, Taylor & Francis Journals, volume 53, issue 52, pages 5989-6001, November, DOI: 10.1080/00036846.2021.1934393.
• Tommaso Proietti, 2021, "Predictability, real time estimation, and the formulation of unobserved components models," Econometric Reviews, Taylor & Francis Journals, volume 40, issue 5, pages 433-454, April, DOI: 10.1080/07474938.2020.1793508.
• Antoine A. Djogbenou, 2021, "Model selection in factor-augmented regressions with estimated factors," Econometric Reviews, Taylor & Francis Journals, volume 40, issue 5, pages 470-503, April, DOI: 10.1080/07474938.2020.1808371.
• 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, volume 39, issue 1, pages 307-324, January, DOI: 10.1080/07350015.2019.1660175.
• 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, volume 39, issue 4, pages 1054-1065, October, DOI: 10.1080/07350015.2020.1763805.
• Selcuk Gul & Abdullah Kazdal, 2021, "Nowcasting and Short-term Forecasting Turkish GDP: Factor-MIDAS Approach," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 2111.
• Ioannis Sitzimis, 2021, "An Optimal Forecasting Method of Passenger Traffic in Greek Coastal Shipping," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, volume 14, issue 3, pages 72-87, December.
• 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, Tinbergen Institute, number 21-016/III, Feb.
• 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, Tinbergen Institute, number 21-053/III, Jun.
• Yongchen Zhao, 2021, "Uncertainty and Disagreement of Inflation Expectations: Evidence from Household-Level Qualitative Survey Responses," Working Papers, Towson University, Department of Economics, number 2021-03, Dec, revised Dec 2021.
• K. Peren Arin & Kevin Devereux & Mieszko Mazur, 2021, "Taxes and Firm Investment," Working Papers, School of Economics, University College Dublin, number 202102, Jan.
• Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2021, "Efficient Combined Estimation under Structural Breaks," Working Papers, University of California at Riverside, Department of Economics, number 202101, Jan.
• 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, DOI: 10.26531/vnbu2021.251.02.
• 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, volume 55, issue 1, pages 27-37, DOI: http://dx.doi.org/10.17576/JEM-2021.
• Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021, "Evaluating forecast performance with state dependence," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1800, Jul.
• 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, Department of Economics, University of Venice "Ca' Foscari", number 2021:03.
• Jitender, 2021, "Value-at-Risk Estimation of Equity Market Risk in India," Acta Universitatis Sapientiae, Economics and Business, Sciendo, volume 9, issue 1, pages 1-24, September, DOI: 10.2478/auseb-2021-0001.
• Kaczmarczyk Paweł, 2021, "Econometric Modelling of Compound Cyclicality of using Telecommunication Services," Econometrics. Advances in Applied Data Analysis, Sciendo, volume 25, issue 2, pages 27-45, June, DOI: 10.15611/eada.2021.2.03.
• 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, volume 25, issue 3, pages 21-41, September, DOI: 10.15611/eada.2021.3.02.
• 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, volume 18, issue 1, pages 70-81, June, DOI: 10.2478/jec-2021-0006.
• Wang Guan-Yuan, 2021, "The Brand Effect: A Case Study in Taiwan Second-Hand Smartphone Market," Journal of Social and Economic Statistics, Sciendo, volume 10, issue 1-2, pages 30-42, December, DOI: 10.2478/jses-2021-0003.
• 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, volume 29, issue 2, pages 52-70, June, DOI: 10.2478/remav-2021-0013.
• 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, volume 16, issue 2, pages 43-52, December, DOI: 10.2478/jeb-2021-0013.
• Dawid Siwicki, 2021, "The Application of Machine Learning Algorithms for Spatial Analysis: Predicting of Real Estate Prices in Warsaw," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-05.
• Mateusz Buczyński & Marcin Chlebus, 2021, "GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-08.
• Michał Woźniak & Marcin Chlebus, 2021, "HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-10.
• Szymon Lis & Marcin Chlebus, 2021, "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-11.
• Piotr Borowski & Marcin Chlebus, 2021, "Machine learning in the prediction of flat horse racing results in Poland," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-13.
• Kamil Korzeń & Robert Ślepaczuk, 2021, "Enhanced Index Replication Based on Smart Beta and Tail-Risk Asset Allocation," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-18.
• Michał Lewandowski & Marcin Chlebus, 2021, "Predicting football outcomes from Spanish league using machine learning models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-22.
• Jan Grudniewicz & Robert Ślepaczuk, 2021, "Application of machine learning in quantitative investment strategies on global stock markets," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-23.
• Nguyen Vo & Robert Ślepaczuk, 2021, "Applying Hybrid ARIMA-SGARCH in Algorithmic Investment Strategies on S&P500 Index," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-25.
• Sergio Castellano Gómez & Robert Ślepaczuk, 2021, "Robust optimisation in algorithmic investment strategies," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-27.
• Aleksander Schiffers & Marcin Chlebus, 2021, "The effectiveness of Value-at-Risk models in various volatility regimes," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-28.
• Stefan Jestl & Robert Stehrer, 2021, "EU Employment Dynamics: The Pandemic Years and Beyond," wiiw Research Reports, The Vienna Institute for International Economic Studies, wiiw, number 457, Nov.
• Vadim Kufenko & Klaus Prettner, 2021, "Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators," Department of Economics Working Papers, Vienna University of Economics and Business, Department of Economics, number wuwp316, Sep.
• 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, WU Vienna University of Economics and Business, number 316, Sep.
• Reinhard Ellwanger, Stephen Snudden, 2021, "Predictability of Aggregated Time Series," LCERPA Working Papers, Laurier Centre for Economic Research and Policy Analysis, number bm0127.
• 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., volume 26, issue 1, pages 153-170, January, DOI: 10.1002/ijfe.1782.
• Jörg Breitung & Malte Knüppel, 2021, "How far can we forecast? Statistical tests of the predictive content," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 36, issue 4, pages 369-392, June, DOI: 10.1002/jae.2817.
• 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., volume 36, issue 5, pages 495-516, August, DOI: 10.1002/jae.2828.
• Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021, "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 36, issue 5, pages 517-543, August, DOI: 10.1002/jae.2810.
• Till Weigt & Bernd Wilfling, 2021, "An approach to increasing forecast‐combination accuracy through VAR error modeling," Journal of Forecasting, John Wiley & Sons, Ltd., volume 40, issue 4, pages 686-699, July, DOI: 10.1002/for.2733.
• Ricardo Crisóstomo, 2021, "Estimating real‐world probabilities: A forward‐looking behavioral framework," Journal of Futures Markets, John Wiley & Sons, Ltd., volume 41, issue 11, pages 1797-1823, November, DOI: 10.1002/fut.22248.
• 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, volume 53, issue 5, pages 1005-1046, August, DOI: 10.1111/jmcb.12771.
• John B. Donaldson & Rajnish Mehra, 2021, "Average crossing time: An alternative characterization of mean aversion and reversion," Quantitative Economics, Econometric Society, volume 12, issue 3, pages 903-944, July, DOI: 10.3982/QE1560.
• Garg, Karan, 2021, "Machines and Markets : Assessing the Impact of Algorithmic Trading on Financial Market Efficiency," Warwick-Monash Economics Student Papers, Warwick Monash Economics Student Papers, number 11.
• Aldott, Zoltan, 2021, "Predicting Specialty Coffee Auction Prices Using Machine Learning," Warwick-Monash Economics Student Papers, Warwick Monash Economics Student Papers, number 15.
• 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., volume 38, issue 02, pages 279-317, September, DOI: 10.1142/S0116110521500050.
• 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., volume 38, issue 02, pages 237-277, September, DOI: 10.1142/S0116110521500104.
• Laura Coroneo & Fabrizio Iacone, 2021, "Testing for equal predictive accuracy with strong dependence," Discussion Papers, Department of Economics, University of York, number 21/03, May.
• Laura Coroneo, & Fabrizio Iacone, & Giancarlo Manzi, & Silvia Salini, 2021, "Predicting the COVID-19 epidemic: is a regional approach preferable?," Discussion Papers, Department of Economics, University of York, number 21/06, Sep.
• 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, Bank of Finland, number 7/2021.
• Martins, Manuel Mota Freitas & Verona, Fabio, 2021, "Inflation dynamics and forecast: Frequency matters," Bank of Finland Research Discussion Papers, Bank of Finland, number 8/2021.
• Mönch, Emanuel & Stein, Tobias, 2021, "Equity premium predictability over the business cycle," Discussion Papers, Deutsche Bundesbank, number 25/2021.
• Bańbura, Marta & Leiva-León, Danilo & Menz, Jan-Oliver, 2021, "Do inflation expectations improve model-based inflation forecasts?," Discussion Papers, Deutsche Bundesbank, number 48/2021.
• Memmel, Christoph & Roling, Christoph, 2021, "Risks in domestic banks' corporate lending business," Technical Papers, Deutsche Bundesbank, number 08/2021.
• Memmel, Christoph & Roling, Christoph, 2021, "Risiken im Unternehmenskreditgeschäft inländischer Banken
  [Risks in domestic banks' corporate lending business]," Technical Papers, Deutsche Bundesbank, number 08/2021.
• Falter, Alexander & Kleemann, Michael & Strobel, Lena & Wilke, Hannes, 2021, "Stress testing market risk of German financial intermediaries," Technical Papers, Deutsche Bundesbank, number 11/2021.
• Kukacka, Jiri & Sacht, Stephen, 2021, "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2021-01.
• 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, issue forthcomi.
• Lyócsa, Štefan & Baumöhl, Eduard & Vŷrost, Tomáš, 2021, "YOLO trading: Riding with the herd during the GameStop episode," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 230679.
• Hauber, Philipp, 2021, "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 251469.
• 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, DOI: 10.25592/uhhfdm.8630.
• Hügle, Dominik, 2021, "The decision to enrol in higher education," Discussion Papers, Free University Berlin, School of Business & Economics, number 2021/8, DOI: 10.17169/refubium-29947.
• Cerqua, Augusto & Letta, Marco, 2021, "Local inequalities of the COVID-19 crisis," GLO Discussion Paper Series, Global Labor Organization (GLO), number 875.
• Stamer, Vincent, 2021, "Thinking outside the container: A machine learning approach to forecasting trade flows," Kiel Working Papers, Kiel Institute for the World Economy (IfW Kiel), number 2179.
• Milivojevic, Lazar & Tatar, Balint, 2021, "Fixed exchange rate - a friend or foe of labor cost adjustments?," IMFS Working Paper Series, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), number 152.
• 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, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), number 158.
• Li, Wei & Paraschiv, Florentina & Sermpinis, Georgios, 2021, "A data-driven explainable case-based reasoning approach for financial risk detection," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2021-010.
• Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021, "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2021-020.
• Glas, Alexander & Heinisch, Katja, 2021, "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 7/2021.
• 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), volume 9, issue 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, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 921, DOI: 10.4419/96973067.
• Kremer, Manfred & Chavleishvili, Sulkhan, 2021, "Measuring Systemic Financial Stress and its Impact on the Macroeconomy," VfS Annual Conference 2021 (Virtual Conference): Climate Economics, Verein für Socialpolitik / German Economic Association, number 242346.

2020

• Tomasz Brzęczek, 2020, "Optimisation of product portfolio sales and their risk subject to product width and diversity," Review of Managerial Science, Springer, volume 14, issue 5, pages 1009-1027, October, DOI: 10.1007/s11846-018-0315-y.
• Marc Burri & Daniel Kaufmann, 2020, "A daily fever curve for the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 156, issue 1, pages 1-11, December, DOI: 10.1186/s41937-020-00051-z.
• Francesca Carta, 2020, "Timely Indicators for Inequality and Poverty Using the Italian Labour Force Survey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, volume 149, issue 1, pages 41-65, May, DOI: 10.1007/s11205-019-02238-1.
• Thieß Petersen & Martina Lizarazo López & Serguei Kaniovski & Thomas Url, 2020, "Makroökonomische Folgen der demografischen Alterung
  [Macroeconomic Consequences of Demographic Ageing: Simulations Until 2050]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, volume 100, issue 12, pages 958-963, December, DOI: 10.1007/s10273-020-2804-2.
• Håvard Hungnes, 2020, "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers, Statistics Norway, Research Department, number 931, May.
• Håvard Hungnes, 2020, "Predicting the exchange rate path. The importance of using up-to-date observations in the forecasts," Discussion Papers, Statistics Norway, Research Department, number 934, Jun.
• Marina Y. Anokhina & Rakhat Abdrakhmanov & Yelena Evgenevna Gridneva & Milton Arrieta-López & Nuray Romanovna Dzhalilova & Abel Meza-Godoy, 2020, "Formation of the competitive potential of the agricultural territories," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, volume 7, issue 3, pages 1921-1936, March, DOI: 10.9770/jesi.2020.7.3(32).
• Diana Žigraiová & Aitor Erce & Xu Jiang, 2020, "Quantifying risks to sovereign market access: Methods and challenges," Working Papers, European Stability Mechanism, number 42, Jan.
• Edward Knotek & Saeed Zaman, 2020, "Real-time density nowcasts of US inflation: a model-combination approach," Working Papers, University of Strathclyde Business School, Department of Economics, number 2015, Oct.
• Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2020, "Higher Moment Constraints for Predictive Density Combinations," Working Papers, University of Sydney Business School, Discipline of Business Analytics, number BAWP-2020-01, May.
• Ruan Erasmus & Hylton Hollander, 2020, "A Forward Guidance Indicator For The South African Reserve Bank: Implementing A Text Analysis Algorithm," Working Papers, Stellenbosch University, Department of Economics, number 04/2020.
• Philip Hans Franses, 2020, "IMA(1,1) as a new benchmark for forecast evaluation," Applied Economics Letters, Taylor & Francis Journals, volume 27, issue 17, pages 1419-1423, October, DOI: 10.1080/13504851.2019.1686115.
• Steffen Q. Mueller, 2020, "Pre- and within-season attendance forecasting in Major League Baseball: a random forest approach," Applied Economics, Taylor & Francis Journals, volume 52, issue 41, pages 4512-4528, September, DOI: 10.1080/00036846.2020.1736502.
• Oğuzhan Çepni & Rangan Gupta & Mark E. Wohar, 2020, "The role of real estate uncertainty in predicting US home sales growth: evidence from a quantiles-based Bayesian model averaging approach," Applied Economics, Taylor & Francis Journals, volume 52, issue 5, pages 528-536, January, DOI: 10.1080/00036846.2019.1654082.
• Hossein Hassani & Mohammad Reza Yeganegi & Juncal Cuñado & Rangan Gupta, 2020, "Forecasting interest rate volatility of the United Kingdom: evidence from over 150 years of data," Journal of Applied Statistics, Taylor & Francis Journals, volume 47, issue 6, pages 1128-1143, April, DOI: 10.1080/02664763.2019.1666093.
• Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020, "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, volume 115, issue 531, pages 1092-1110, July, DOI: 10.1080/01621459.2019.1660171.
• Joshua C. C. Chan, 2020, "Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 38, issue 1, pages 68-79, January, DOI: 10.1080/07350015.2018.1451336.
• Christian Conrad & Melanie Schienle, 2020, "Testing for an Omitted Multiplicative Long-Term Component in GARCH Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 38, issue 2, pages 229-242, April, DOI: 10.1080/07350015.2018.1482759.
• Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2020, "Markov-Switching Three-Pass Regression Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 38, issue 2, pages 285-302, April, DOI: 10.1080/07350015.2018.1497508.
• Carsten Bormann & Melanie Schienle, 2020, "Detecting Structural Differences in Tail Dependence of Financial Time Series," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 38, issue 2, pages 380-392, April, DOI: 10.1080/07350015.2018.1506343.
• Georges Dionne & Xiaozhou Zhou, 2020, "The dynamics of ex-ante weighted spread: an empirical analysis," Quantitative Finance, Taylor & Francis Journals, volume 20, issue 4, pages 593-617, April, DOI: 10.1080/14697688.2019.1690160.
• 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, volume 44, issue 3, pages 41-72, December, DOI: 10.1080/03796205.2020.1919424.
• 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, volume 34, issue 1, pages 136-150, January, DOI: 10.1080/08853908.2019.1687056.
• Islam, Raisul & Volkov, Vladimir, 2020, "Contagion or interdependence? Comparing signed and unsigned spillovers," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2020-05.
• Islam, Raisul & Volkov, Vladimir, 2020, "Calm before the storm: an early warning approach before and during the COVID-19 crisis," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2020-09.
• Zhang, Bo & Nguyen, Bao H., 2020, "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2020-12.
• Mahmut Gunay, 2020, "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 2002.
• Mahmut Gunay, 2020, "Nowcasting Turkish GDP Growth with Targeted Predictors: Fill in the Blanks," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 2006.
• Rutger Jan Lange, 2020, "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 20-052/III, Aug, revised 19 May 2021.
• Francisco Blasques & Meindert Heres Hoogerkamp & Siem Jan Koopman & Ilka van de Werve, 2020, "Dynamic Factor Models with Clustered Loadings: Forecasting Education Flows using Unemployment Data," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 20-078/III, Nov, revised 21 Jan 2021.
• Noussair, C.N. & Popescu, Andreea Victoria, 2020, "Contagion and Return Predictability in Asset Markets : An Experiment with Two Lucas Trees," Discussion Paper, Tilburg University, Center for Economic Research, number 2020-014.
• Kohei Maehashi & Mototsugu Shintani, 2020, "Macroeconomic Forecasting Using Factor Models and Machine Learning: An Application to Japan," CIRJE F-Series, CIRJE, Faculty of Economics, University of Tokyo, number CIRJE-F-1146, Mar.
• George Monokroussos & Yongchen Zhao, 2020, "Nowcasting in Real Time Using Popularity Priors," Working Papers, Towson University, Department of Economics, number 2020-01, Feb, revised Feb 2020.
• Kajal Lahiri & Yongchen Zhao, 2020, "The Nordhaus Test with Many Zeros," Working Papers, Towson University, Department of Economics, number 2020-05, Jun, revised Jun 2020.
• 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, volume 102, issue 1, pages 17-33, March.
• Jonathan M.V. Davis & Sara B. Heller, 2020, "Rethinking the Benefits of Youth Employment Programs: The Heterogeneous Effects of Summer Jobs," The Review of Economics and Statistics, MIT Press, volume 102, issue 4, pages 664-677, October.
• 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, volume 4, issue 2, pages 63-99, DOI: 10.1991/jefa.v4i2.a37.
• 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, University of Trier, Research Group Quantitative Finance and Risk Analysis, number 2020-03.
• 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, University of Trier, Department of Economics, number 2020-01.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020, "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LLC, volume 20, issue 1, pages 176-235, March, DOI: 10.1177/1536867X20909697.
• Benedikt Janzen & Doina Radulescu, 2020, "Electricity Use as a Real Time Indicator of the Economic Burden of the COVID-19-Related Lockdown: Evidence from Switzerland," Diskussionsschriften, Universitaet Bern, Departement Volkswirtschaft, number dp2010, Jun.
• Tong Fang & Tae-Hwy Lee & Zhi Su, 2020, "Predicting the Long-term Stock Market Volatility: A GARCH-MIDAS Model with Variable Selection," Working Papers, University of California at Riverside, Department of Economics, number 202009, May.
• 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, DOI: 10.26531/vnbu2020.249.02.
• 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, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg, number 2020-20.
• Juan Equiza-Goñi, 2020, "WP02/20 Datos de mortalidad diarios durante la crisis del COVID-19: una propuesta de mejora," Faculty Working Papers, School of Economics and Business Administration, University of Navarra, number 01/20, Mar.
• Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020, "Has the information channel of monetary policy disappeared? Revisiting the empirical evidence," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1701, Feb, revised Jul 2021.
• Miriam Breitenstein & Carl-Philipp Anke & Duc Khuong Nguyen & T. Walther, 2020, "Stranded Asset Risk and Political Uncertainty: The Impact of the Coal Phase-out on the German Coal Industry," Working Papers, Utrecht School of Economics, number 2002.
• Jonas Striaukas & Martin Schumacher & Harald Binder & Matthias Weber, 2020, "Network-Constrained Covariate Coefficient and Connection Sign Estimation," Working Papers on Finance, University of St. Gallen, School of Finance, number 2001, Jan.
• Mesias Alfeus & Christina Sklibosios Nikitopoulos, 2020, "Forecasting Commodity Markets Volatility: HAR or Rough?," Research Paper Series, Quantitative Finance Research Centre, University of Technology, Sydney, number 415, Dec.
• Christina Sklibosios Nikitopoulos & Alice Thomas & Jianxin Wang, 2020, "The Economic Impact of Volatility Persistence on Energy Markets," Research Paper Series, Quantitative Finance Research Centre, University of Technology, Sydney, number 417, Dec.
• Hans R. ISAKSON & Mark D. ECKER & Lee KENNEDY, 2020, "Principles For Calculating Avm Performance Metrics," The Valuation Journal, The National Association of Authorized Romanian Valuers, volume 16, issue 2, pages 38-69.
• 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", volume 24, issue 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.
• Žmuk Berislav & Kovač Matej, 2020, "Ornstein-Uhlenbeck process and GARCH model for temperature forecasting in weather derivatives valuation," Croatian Review of Economic, Business and Social Statistics, Sciendo, volume 6, issue 1, pages 27-42, May, DOI: 10.2478/crebss-2020-0003.
• Oesterreich Maciej, 2020, "On the Method of Identification of Atypical Observations in Time Series," Econometrics. Advances in Applied Data Analysis, Sciendo, volume 24, issue 2, pages 1-16, June, DOI: 10.15611/eada.2020.2.01.
• Krzciuk Małgorzata K., 2020, "On Empirical Best Linear Unbiased Predictor Under a Linear Mixed Model with Correlated Random Effects," Econometrics. Advances in Applied Data Analysis, Sciendo, volume 24, issue 2, pages 17-29, June, DOI: 10.15611/eada.2020.2.02.
• Jaworski Stanisław, 2020, "A Few Remarks on the Stochastic Structure of the Unemployment Rate in Poland by Gender," Econometrics. Advances in Applied Data Analysis, Sciendo, volume 24, issue 2, pages 41-52, June, DOI: 10.15611/eada.2020.2.04.
• Gürsakal Necmi & Yilmaz Fırat Melih & Uğurlu Erginbay, 2020, "Finding Opportunity Windows in Time Series Data Using the Sliding Window Technique: the Case of Stock Exchanges," Econometrics. Advances in Applied Data Analysis, Sciendo, volume 24, issue 3, pages 1-19, September, DOI: 10.15611/eada.2020.3.01.
• Wójcik Filip & Górnik Michał, 2020, "Improvement of E-Commerce Recommendation Systems with Deep Hybrid Collaborative Filtering with Content: A Case Study," Econometrics. Advances in Applied Data Analysis, Sciendo, volume 24, issue 3, pages 37-50, September, DOI: 10.15611/eada.2020.3.03.
• Zanka Mikhail, 2020, "A Comparison of Variables Selection Methods and their Sequential Application: A Case Study of the Bankruptcy of Polish Companies," Folia Oeconomica Stetinensia, Sciendo, volume 20, issue 1, pages 531-543, June, DOI: 10.2478/foli-2020-0031.
• Wodecki Andrzej, 2020, "The Reserve Price Optimization for Publishers on Real-Time Bidding on-Line Marketplaces with Time-Series Forecasting," Foundations of Management, Sciendo, volume 12, issue 1, pages 167-180, January, DOI: 10.2478/fman-2020-0013.
• Rządkowski Grzegorz & Sobczak Lidia, 2020, "A Generalized Logistic Function and Its Applications," Foundations of Management, Sciendo, volume 12, issue 1, pages 85-92, January, DOI: 10.2478/fman-2020-0007.
• Rządkowski Grzegorz & Sobczak Lidia, 2020, "A Generalized Logistic Function and Its Applications," Foundations of Management, Sciendo, volume 12, issue 1, pages 85-92, January, DOI: 10.2478/fman-2020-0007.
• Moro Matheus Fernando & Weise Andreas Dittmar & Bornia Antonio Cezar, 2020, "Model Hybrid for Sales Forecast for the Housing Market of São Paulo," Real Estate Management and Valuation, Sciendo, volume 28, issue 3, pages 45-64, September, DOI: 10.1515/remav-2020-0023.
• Ngozi E. Egbuna (PhD) & Maimuna John-Sowe & Santigie M. Kargbo (PhD) & Ibrahima Diallo & Sani Bawa (PhD) & Isatou Mendy, 2020, "When Will Normalcy Return? Exploring The Novel Covid-19 Spread In The West African Monetary Zone," West African Journal of Monetary and Economic Integration, West African Monetary Institute, volume 20, issue 1b, pages 1-22, June.
• Mateusz Buczyński & Marcin Chlebus, 2020, "Size does matter. A study on the required window size for optimal quality market risk models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-09.
• Maciej Wysocki & Robert Ślepaczuk, 2020, "Artificial Neural Networks Performance in WIG20 Index Options Pricing," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-19.
• Mateusz Kijewski & Robert Ślepaczuk, 2020, "Predicting prices of S&P500 index using classical methods and recurrent neural networks," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-27.
• Karol Kielak & Robert Ślepaczuk, 2020, "Value-at-risk — the comparison of state-of-the-art models on various assets," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-28.
• Mateusz Heba & Marcin Chlebus, 2020, "Impact of using industry benchmark financial ratios on performance of bankruptcy prediction logistic regression model," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-30.
• Bartłomiej Bollin & Robert Ślepaczuk, 2020, "Variance Gamma Model in Hedging Vanilla and Exotic Options," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-31.
• Robert Ślepaczuk & Igor Wabik, 2020, "The impact of the results of football matches on the stock prices of soccer clubs," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-35.
• Quynh Bui & Robert Ślepaczuk, 2020, "Applying Hurst Exponent in Pair Trading Strategies," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-39.
• Christian Glocker & Serguei Kaniovski, 2020, "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers, WIFO, number 614, Oct.
• Stefan Jestl & Roman Römisch, 2020, "On the Economic Effects of a Reallocation of EU Cohesion Policy Expenditures," wiiw Working Papers, The Vienna Institute for International Economic Studies, wiiw, number 183, Aug.
• Jan Capek & Jesus Crespo Cuaresma & Niko Hauzenberger & Vlastimil Reichel, 2020, "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Papers, Vienna University of Economics and Business, Department of Economics, number wuwp305, Nov.
• Capek, Jan & Crespo Cuaresma, Jesus & Hauzenberger, Niko & Reichel, Vlastimil, 2020, "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Paper Series, WU Vienna University of Economics and Business, number 305, Nov.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2020, "Forecasting With Dynamic Panel Data Models," Econometrica, Econometric Society, volume 88, issue 1, pages 171-201, January, DOI: 10.3982/ECTA14952.
• Michael W. McCracken, 2020, "Diverging Tests of Equal Predictive Ability," Econometrica, Econometric Society, volume 88, issue 4, pages 1753-1754, July, DOI: 10.3982/ECTA17523.
• Carlo Pizzinelli & Konstantinos Theodoridis & Francesco Zanetti, 2020, "State Dependence In Labor Market Fluctuations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, volume 61, issue 3, pages 1027-1072, August, DOI: 10.1111/iere.12448.
• Gloria Gonzalez‐Rivera & Yun Luo & Esther Ruiz, 2020, "Prediction regions for interval‐valued time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 35, issue 4, pages 373-390, June, DOI: 10.1002/jae.2754.
• Jonas Dovern & Hans Manner, 2020, "Order‐invariant tests for proper calibration of multivariate density forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 35, issue 4, pages 440-456, June, DOI: 10.1002/jae.2755.
• Joshua C. C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2020, "Composite likelihood methods for large Bayesian VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 35, issue 6, pages 692-711, September, DOI: 10.1002/jae.2793.
• 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., volume 39, issue 2, pages 126-142, March, DOI: 10.1002/for.2617.
• Benedikt Maas, 2020, "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., volume 39, issue 3, pages 394-411, April, DOI: 10.1002/for.2630.
• Andrea Bucci, 2020, "Cholesky–ANN models for predicting multivariate realized volatility," Journal of Forecasting, John Wiley & Sons, Ltd., volume 39, issue 6, pages 865-876, September, DOI: 10.1002/for.2664.
• 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., volume 39, issue 6, pages 934-943, September, DOI: 10.1002/for.2660.
• 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., volume 39, issue 6, pages 957-965, September, DOI: 10.1002/for.2672.
• 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., volume 39, issue 6, pages 966-985, September, DOI: 10.1002/for.2669.
• 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, HEDG, c/o Department of Economics, University of York, number 20/07, Apr.
• Berta, P. & Lovaglio, P.G. & Paruolo, P. & Verzillo, S., 2020, "Real Time Forecasting of Covid-19 Intensive Care Units demand," Health, Econometrics and Data Group (HEDG) Working Papers, HEDG, c/o Department of Economics, University of York, number 20/16, Aug.
• 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, HEDG, c/o Department of Economics, University of York, number 20/18, Nov.
• 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, HEDG, c/o Department of Economics, University of York, number 20/20, Nov.
• Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2020, "Testing the predictive accuracy of COVID-19 forecasts," Discussion Papers, Department of Economics, University of York, number 20/10, Oct.
• Martins, Manuel Mota Freitas & Verona, Fabio, 2020, "Forecasting inflation with the New Keynesian Phillips curve: Frequency matters," Bank of Finland Research Discussion Papers, Bank of Finland, number 4/2020.
• Reichlin, Lucrezia & Ricco, Giovanni & Hasenzagl, Thomas, 2020, "Financial variables as predictors of real growth vulnerability," Discussion Papers, Deutsche Bundesbank, number 05/2020.
• Eraslan, Sercan & Nöller, Marvin, 2020, "Recession probabilities falling from the STARs," Discussion Papers, Deutsche Bundesbank, number 08/2020.
• 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, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020".
• 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, volume 8, issue 2, pages 143-165.
• Benchimol, Jonathan & El-Shagi, Makram, 2020, "Forecast performance in times of terrorism," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 91, pages 386-402.
• Heinrich, Markus, 2020, "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 219312.
• Dieckelmann, Daniel, 2020, "Cross-border lending and the international transmission of banking crises," Discussion Papers, Free University Berlin, School of Business & Economics, number 2020/13, DOI: 10.17169/refubium-27524.
• Fischer, Benjamin & Hügle, Dominik, 2020, "The private and fiscal returns to higher education: A simulation approach for a young German cohort," Discussion Papers, Free University Berlin, School of Business & Economics, number 2020/21, DOI: 10.17169/refubium-28847.
• Hügle, Dominik, 2020, "Higher education funding in Germany: A distributional lifetime perspective," Discussion Papers, Free University Berlin, School of Business & Economics, number 2021/1, DOI: 10.17169/refubium-28932.
• Seuffert, Stefan, 2020, "German Pension Simulation: Arbeitspapier zur Methodik eines anwartschaftsbasierten Projektionsmodells der gesetzlichen Rentenversicherung," FZG Discussion Papers, University of Freiburg, Research Center for Generational Contracts (FZG), number 73.
• 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, University of Hohenheim, Faculty of Business, Economics and Social Sciences, number 12-2020.
• 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), volume 14, pages 1-32, DOI: 10.5018/economics-ejournal.ja.2020-.
• 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), volume 8, issue 4, pages 150-161.
• Reh, Laura & Krüger, Fabian & Liesenfeld, Roman, 2020, "Predicting the global minimum variance portfolio," Working Paper Series in Economics, Karlsruhe Institute of Technology (KIT), Department of Economics and Management, number 141, DOI: 10.5445/IR/1000122441.
• Foltas, Alexander, 2020, "Testing investment forecast efficiency with textual data," Working Papers, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin, number 19, DOI: 10.18452/21651.
• Foltas, Alexander & Pierdzioch, Christian, 2020, "On the efficiency of German growth forecasts: An empirical analysis using quantile random forests," Working Papers, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin, number 21, DOI: 10.18452/21910.