Research classified by Journal of Economic Literature (JEL) codes

1. Nowcasting
2. Bayesian Vector autoregressions (BVARs)
3. Dynamic Factor Models

2021

• Smeekes, Stephan & Wijler, Etienne, 2021, "An automated approach towards sparse single-equation cointegration modelling," Journal of Econometrics, Elsevier, volume 221, issue 1, pages 247-276, DOI: 10.1016/j.jeconom.2020.07.021.
• Yang, Xinxin & Zheng, Xinghua & Chen, Jiaqi, 2021, "Testing high-dimensional covariance matrices under the elliptical distribution and beyond," Journal of Econometrics, Elsevier, volume 221, issue 2, pages 409-423, DOI: 10.1016/j.jeconom.2020.05.017.
• Kapetanios, G. & Pesaran, M.H. & Reese, S., 2021, "Detection of units with pervasive effects in large panel data models," Journal of Econometrics, Elsevier, volume 221, issue 2, pages 510-541, DOI: 10.1016/j.jeconom.2020.05.001.
• Ding, Yi & Li, Yingying & Zheng, Xinghua, 2021, "High dimensional minimum variance portfolio estimation under statistical factor models," Journal of Econometrics, Elsevier, volume 222, issue 1, pages 502-515, DOI: 10.1016/j.jeconom.2020.07.013.
• Jin, Sainan & Miao, Ke & Su, Liangjun, 2021, "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, volume 222, issue 1, pages 745-777, DOI: 10.1016/j.jeconom.2020.08.002.
• Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021, "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, volume 225, issue 1, pages 2-26, DOI: 10.1016/j.jeconom.2021.03.012.
• Di Iorio, Francesca & Fachin, Stefano, 2021, "Evaluating restricted common factor models for non-stationary data," Econometrics and Statistics, Elsevier, volume 17, issue C, pages 64-75, DOI: 10.1016/j.ecosta.2020.10.004.
• Cavallari, Lilia & Romano, Simone & Naticchioni, Paolo, 2021, "The original sin: Firms’ dynamics and the life-cycle consequences of economic conditions at birth," European Economic Review, Elsevier, volume 138, issue C, DOI: 10.1016/j.euroecorev.2021.103844.
• Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021, "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, volume 63, issue C, pages 252-269, DOI: 10.1016/j.jempfin.2021.07.009.
• Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021, "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, volume 102, issue C, DOI: 10.1016/j.eneco.2021.105494.
• Bennedsen, Mikkel & Hillebrand, Eric & Koopman, Siem Jan, 2021, "Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors," Energy Economics, Elsevier, volume 96, issue C, DOI: 10.1016/j.eneco.2021.105118.
• Nam, Kyungsik, 2021, "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, volume 96, issue C, DOI: 10.1016/j.eneco.2021.105123.
• Strauss, Ilan & Yang, Jangho, 2021, "Slowing investment rates in developing economies: Evidence from a Bayesian hierarchical model," International Review of Financial Analysis, Elsevier, volume 77, issue C, DOI: 10.1016/j.irfa.2021.101843.
• Shynkevich, Andrei, 2021, "Bitcoin arbitrage," Finance Research Letters, Elsevier, volume 40, issue C, DOI: 10.1016/j.frl.2020.101698.
• Joo, Young C. & Park, Sung Y., 2021, "Optimal portfolio selection using a simple double-shrinkage selection rule," Finance Research Letters, Elsevier, volume 43, issue C, DOI: 10.1016/j.frl.2021.102019.
• Avanzi, Benjamin & Taylor, Greg & Wang, Melantha & Wong, Bernard, 2021, "SynthETIC: An individual insurance claim simulator with feature control," Insurance: Mathematics and Economics, Elsevier, volume 100, issue C, pages 296-308, DOI: 10.1016/j.insmatheco.2021.06.004.
• Avanzi, Benjamin & Taylor, Greg & Wong, Bernard & Yang, Xinda, 2021, "On the modelling of multivariate counts with Cox processes and dependent shot noise intensities," Insurance: Mathematics and Economics, Elsevier, volume 99, issue C, pages 9-24, DOI: 10.1016/j.insmatheco.2021.01.002.
• Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021, "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, volume 37, issue 1, pages 360-377, DOI: 10.1016/j.ijforecast.2020.06.006.
• Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021, "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, volume 37, issue 2, pages 941-948, DOI: 10.1016/j.ijforecast.2020.10.005.
• Chan, Joshua C.C., 2021, "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, volume 37, issue 3, pages 1212-1226, DOI: 10.1016/j.ijforecast.2021.01.002.
• Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021, "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, volume 37, issue 4, pages 1338-1354, DOI: 10.1016/j.ijforecast.2021.05.005.
• Hillen, Judith & Fedoseeva, Svetlana, 2021, "E-commerce and the end of price rigidity?," Journal of Business Research, Elsevier, volume 125, issue C, pages 63-73, DOI: 10.1016/j.jbusres.2020.11.052.
• Brettschneider, Julia & Burro, Giovanni & Henderson, Vicky, 2021, "Wide framing disposition effect: An empirical study," Journal of Economic Behavior & Organization, Elsevier, volume 185, issue C, pages 330-347, DOI: 10.1016/j.jebo.2021.03.003.
• Painter, Marcus & Qiu, Tian, 2021, "Political beliefs affect compliance with government mandates," Journal of Economic Behavior & Organization, Elsevier, volume 185, issue C, pages 688-701, DOI: 10.1016/j.jebo.2021.03.019.
• Godzinski, Alexandre & Suarez Castillo, Milena, 2021, "Disentangling the effects of air pollutants with many instruments," Journal of Environmental Economics and Management, Elsevier, volume 109, issue C, DOI: 10.1016/j.jeem.2021.102489.
• Hirche, Martin & Farris, Paul W. & Greenacre, Luke & Quan, Yiran & Wei, Susan, 2021, "Predicting Under- and Overperforming SKUs within the Distribution–Market Share Relationship," Journal of Retailing, Elsevier, volume 97, issue 4, pages 697-714, DOI: 10.1016/j.jretai.2021.04.002.
• Martins, Pedro S., 2021, "Working to get fired? Unemployment benefits and employment duration," Journal of Policy Modeling, Elsevier, volume 43, issue 5, pages 1016-1030, DOI: 10.1016/j.jpolmod.2021.03.004.
• Turrell, Arthur & Speigner, Bradley & Copple, David & Djumalieva, Jyldyz & Thurgood, James, 2021, "Is the UK’s productivity puzzle mostly driven by occupational mismatch? An analysis using big data on job vacancies," Labour Economics, Elsevier, volume 71, issue C, DOI: 10.1016/j.labeco.2021.102013.
• Brownlees, Christian & Hans, Christina & Nualart, Eulalia, 2021, "Bank credit risk networks: Evidence from the Eurozone," Journal of Monetary Economics, Elsevier, volume 117, issue C, pages 585-599, DOI: 10.1016/j.jmoneco.2020.03.014.
• Tissaoui, Kais & Zaghdoudi, Taha, 2021, "Dynamic connectedness between the U.S. financial market and Euro-Asian financial markets: Testing transmission of uncertainty through spatial regressions models," The Quarterly Review of Economics and Finance, Elsevier, volume 81, issue C, pages 481-492, DOI: 10.1016/j.qref.2020.10.020.
• Garciga, Christian & Verbrugge, Randal, 2021, "Robust covariance matrix estimation and identification of unusual data points: New tools," Research in Economics, Elsevier, volume 75, issue 2, pages 176-202, DOI: 10.1016/j.rie.2021.03.001.
• Roshen Fernando & Weifeng Liu & Warwick J McKibbin, 2021, "Global economic impacts of climate shocks, climate policy and changes in climate risk assessment," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2021-37, Apr.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021, "Tracking weekly state-level economic conditions," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2021-55, Jul.
• Hanol Lee & Jong-Wha Lee, 2021, "Why East Asian students perform better in mathematics than their peers: An investigation using a machine learning approach," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2021-66, Jul.
• Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021, "Mitigating climate change: Growth-friendly policies to achieve net zero emissions by 2050," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2021-75, Aug.
• Jieyi Kang & David Reiner, 2021, "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Working Papers, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge, number EPRG2112, May.
• Jieyi Kang & David Reiner, 2021, "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Working Papers, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge, number EPRG2113, May.
• Jieyi Kang & David Reiner, 2021, "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Working Papers, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge, number EPRG2114, May.
• Krzysztof Marcjan & Lucjan Gucma & Kotkowska Diana, 2021, "The Collision Risk Management Method for Ships Navigating on Coastal Waters Based on Ship Domain and Near-Miss Concept," European Research Studies Journal, European Research Studies Journal, volume 0, issue 4 - Part , pages 127-146.
• Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021, "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers, European Xtramile Centre of African Studies (EXCAS), number 21/074, Jan.
• Lenka Nechvatalova, 2021, "Multi-Horizon Equity Returns Predictability via Machine Learning," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2021/02, Feb, revised Feb 2021.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022, "Macroeconomic Forecasting in a Multi-country Context," Working Papers, Federal Reserve Bank of Cleveland, number 22-02, Feb, DOI: 10.26509/frbc-wp-202202.
• Hie Joo Ahn & Matteo Luciani, 2021, "Relative prices and pure inflation since the mid-1990s," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2021-069, Oct, DOI: 10.17016/FEDS.2021.069.
• Simon Freyaldenhoven, 2021, "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers, Federal Reserve Bank of Philadelphia, number 21-15, Apr, DOI: 10.21799/frbp.wp.2021.15.
• Massimo Franchi & Paolo Paruolo, 2021, "Cointegration, Root Functions and Minimal Bases," Econometrics, MDPI, volume 9, issue 3, pages 1-27, August.
• 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, volume 3, issue 4, pages 1-30, October.
• Joelle Noailly; Laura Nowzohour; Matthias van den Heuvel, 2021, "Heard the News? Environmental Policy and Clean Investments," CIES Research Paper series, Centre for International Environmental Studies, The Graduate Institute, number 70-2021, Nov.
• Hager Ben Romdhane, 2021, "Nowcasting in Tunisia using large datasets and mixed frequency models," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 11-2021, Jun.
• Tetiana Yukhymenko, 2021, "Role of the Media in the Inflation Expectation Formation Process," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 13-2021, Jun.
• Christophe Hurlin & Christophe Perignon & Sébastien Saurin, 2021, "The Fairness of Credit Scoring Models," Working Papers, HAL, number hal-03501452, May, DOI: 10.2139/ssrn.3785882.
• Hansson, Magnus, 2021, "Evolution of topics in central bank speech communication," Working Papers in Economics, University of Gothenburg, Department of Economics, number 811, Oct.
• Amberg, Niklas & Jansson, Thomas & Klein, Mathias & Rogantini Picco, Anna, 2021, "Five Facts about the Distributional Income Effects of Monetary Policy," Working Paper Series, Sveriges Riksbank (Central Bank of Sweden), number 403, May.
• Camino González Vasco & María Jesús Delgado Rodríguez & Sonia de Lucas Santos, 2021, "Segmentation of Potential Fraud Taxpayers and Characterization in Personal Income Tax Using Data Mining Techniques," Hacienda Pública Española / Review of Public Economics, IEF, volume 239, issue 4, pages 127-157, November.
• Hartl, Tobias & Hutter, Christian & Weber, Enzo, 2021, "Matching for three: big data evidence on search activity of workers, firms, and employment service," IAB-Discussion Paper, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], number 202101, Jan.
• Hutter, Christian, 2021, "Cyclicality of labour market search: a new big data Approach," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], volume 55, issue , pages 1-001, DOI: 10.1186/s12651-020-00283-9.
• Francesca Micocci & Armando Rungi, 2021, "Predicting Exporters with Machine Learning," Working Papers, IMT School for Advanced Studies Lucca, number 03/2021, Jul, revised Jul 2021.
• Ms. Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021, "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," IMF Working Papers, International Monetary Fund, number 2021/195, Jul.
• Narges Ahani & Tommy Andersson & Alessandro Martinello & Alexander Teytelboym & Andrew C. Trapp, 2021, "Placement Optimization in Refugee Resettlement," Operations Research, INFORMS, volume 69, issue 5, pages 1468-1486, September, DOI: 10.1287/opre.2020.2093.
• Oscar Claveria & Enric Monte & Salvador Torra, 2021, ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202103, Feb, revised Feb 2021.
• Sarracino, Francesco & Greyling, Talita & O'Connor, Kelsey J. & Peroni, Chiara & Rossouw, Stephanie, 2021, "A Year of Pandemic: Levels, Changes and Validity of Well-Being Data from Twitter. Evidence from Ten Countries," IZA Discussion Papers, IZA Network @ LISER, number 14903, Nov.
• Luiz Renato Lima & Lucas Lúcio Godeiro & Mohammed Mohsin, 2021, "Time-Varying Dictionary and the Predictive Power of FED Minutes," Computational Economics, Springer;Society for Computational Economics, volume 57, issue 1, pages 149-181, January, DOI: 10.1007/s10614-020-10039-9.
• Zhan Gao & Zhentao Shi, 2021, "Implementing Convex Optimization in R: Two Econometric Examples," Computational Economics, Springer;Society for Computational Economics, volume 58, issue 4, pages 1127-1135, December, DOI: 10.1007/s10614-020-09995-z.
• Dani Arribas-Bel & Mark Green & Francisco Rowe & Alex Singleton, 2021, "Open data products-A framework for creating valuable analysis ready data," Journal of Geographical Systems, Springer, volume 23, issue 4, pages 497-514, October, DOI: 10.1007/s10109-021-00363-5.
• Robert Donnelly & Francisco J.R. Ruiz & David Blei & Susan Athey, 2021, "Counterfactual inference for consumer choice across many product categories," Quantitative Marketing and Economics (QME), Springer, volume 19, issue 3, pages 369-407, December, DOI: 10.1007/s11129-021-09241-2.
• Pradeep K. Chintagunta, 2021, "Comments on “Counterfactual Inference for Consumer Choice Across Many Product Categories”," Quantitative Marketing and Economics (QME), Springer, volume 19, issue 3, pages 411-415, December, DOI: 10.1007/s11129-021-09243-0.
• Robert Donnelly & Francisco J. R. Ruiz & David Blei & Susan Athey, 2021, "Correction to: Counterfactual inference for consumer choice across many product categories," Quantitative Marketing and Economics (QME), Springer, volume 19, issue 3, pages 409-409, December, DOI: 10.1007/s11129-021-09245-y.
• Timothy Holt & Mitsuru Igami & Simon Scheidegger, 2021, "Detecting Edgeworth Cycles," Cahiers de Recherches Economiques du Département d'économie, Université de Lausanne, Faculté des HEC, Département d’économie, number 21.16, Nov.
• Christophe HURLIN & Christophe PERIGNON & Sébastien SAURIN, 2021, "The Fairness of Credit Scoring Models," LEO Working Papers / DR LEO, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans, number 2912.
• Soroosh Soofi-Siavash & Emanuel Moench, 2021, "What Moves Treasury Yields?," Bank of Lithuania Working Paper Series, Bank of Lithuania, number 88, Mar.
• François Gardes, 2021, "Biases on variances estimated on large data-sets," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 21022, Mar.
• François Gardes, 2021, "Endogenous Prices in a Riemannian Geometry Framework," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 21026, Jul.
• George Athanasopoulos & Nikolaos Kourentzes, 2021, "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 10/21.
• Sevvandi Kandanaarachchi & Rob J Hyndman, 2021, "Leave-one-out Kernel Density Estimates for Outlier Detection," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 2/21.
• Sayani Gupta & Rob J Hyndman & Dianne Cook, 2021, "Detecting Distributional Differences between Temporal Granularities for Exploratory Time Series Analysis," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 20/21.
• Fan Cheng & Rob J Hyndman & Anastasios Panagiotelis, 2021, "Manifold Learning with Approximate Nearest Neighbors," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 3/21.
• 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, National Bank of Belgium, number 396, Feb.
• Stefano Giglio & Yuan Liao & Dacheng Xiu, 2021, "Thousands of Alpha Tests," NBER Chapters, National Bureau of Economic Research, Inc, "Big Data: Long-Term Implications for Financial Markets and Firms".
• Mark Braverman & Sylvain Chassang, 2021, "Data-Driven Incentive Alignment in Capitation Schemes," NBER Working Papers, National Bureau of Economic Research, Inc, number 28429, Feb.
• Gabriel E. Kreindler & Yuhei Miyauchi, 2021, "Measuring Commuting and Economic Activity inside Cities with Cell Phone Records," NBER Working Papers, National Bureau of Economic Research, Inc, number 28516, Feb.
• Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021, "Tracking Weekly State-Level Economic Conditions," NBER Working Papers, National Bureau of Economic Research, Inc, number 29003, Jul.
• Allen Hu & Song Ma, 2021, "Persuading Investors: A Video-Based Study," NBER Working Papers, National Bureau of Economic Research, Inc, number 29048, Jul.
• Emily Aiken & Suzanne Bellue & Dean Karlan & Christopher R. Udry & Joshua Blumenstock, 2021, "Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance," NBER Working Papers, National Bureau of Economic Research, Inc, number 29070, Jul.
• Jens Ludwig & Sendhil Mullainathan, 2021, "Fragile Algorithms and Fallible Decision-Makers: Lessons from the Justice System," NBER Working Papers, National Bureau of Economic Research, Inc, number 29267, Sep.
• Galina Manahilova, 2021, "Identifying Surrogation Using Business Analysis," Economics and Management, Faculty of Economics, SOUTH-WEST UNIVERSITY "NEOFIT RILSKI", BLAGOEVGRAD, volume 18, issue 1, pages 90-95, DOI: 10.37708/em.swu.v18i1.7.
• J. Boussard & R. Lee, 2020, "Competition, Profit Share and Concentration," Documents de Travail de l'Insee - INSEE Working Papers, Institut National de la Statistique et des Etudes Economiques, number g2020-04.
• A. Godzinski & M. Suarez Castillo, 2021, "Disentangling the effects of air pollutants with many instruments," Documents de Travail de l'Insee - INSEE Working Papers, Institut National de la Statistique et des Etudes Economiques, number g2021-04.
• Vasil Marchev, 2021, "Self-Perfecting Model for Managing Individualized Investment Portfolios," Ikonomiceski i Sotsialni Alternativi, University of National and World Economy, Sofia, Bulgaria, issue 4, pages 86-97, December.
• Julie Lassébie & Luca Marcolin & Marieke Vandeweyer & Benjamin Vignal, 2021, "Speaking the same language: A machine learning approach to classify skills in Burning Glass Technologies data," OECD Social, Employment and Migration Working Papers, OECD Publishing, number 263, Nov, DOI: 10.1787/adb03746-en.
• Şeuleanu Dragoş, 2021, "The Communication Dimension of the Business Model Applied to the ELI-NP Project," Revista OEconomica, Romanian Society for Economic Science, Revista OEconomica, issue 02, June.
• Torben Andersen & Ilya Archakov & Leon Grund & Nikolaus Hautsch & Yifan Li & Sergey Nasekin & Ingmar Nolte & Manh Cuong Pham & Stephen Taylor & Viktor Todorov, 2021, "A Descriptive Study of High-Frequency Trade and Quote Option Data
  [Stealth Trading in Options Markets]," Journal of Financial Econometrics, Oxford University Press, volume 19, issue 1, pages 128-177.
• Apaar Sadhwani & Kay Giesecke & Justin Sirignano, 2021, "Deep Learning for Mortgage Risk
  [The Subprime Virus]," Journal of Financial Econometrics, Oxford University Press, volume 19, issue 2, pages 313-368.
• P Gagliardini & C Gourieroux & M Rubin, 2021, "Positional Portfolio Management," Journal of Financial Econometrics, Oxford University Press, volume 19, issue 4, pages 650-706.
• 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]," Journal of Financial Econometrics, Oxford University Press, volume 19, issue 5, pages 860-909.
• Marcus Buckmann & Andy Haldane & Anne-Caroline Hüser, 2021, "Comparing minds and machines: implications for financial stability," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, volume 37, issue 3, pages 479-508.
• Stefano Giglio & Yuan Liao & Dacheng Xiu & Wei Jiang, 2021, "Thousands of Alpha Tests
  [The performance of hedge funds: Risk, return, and incentives]," The Review of Financial Studies, Society for Financial Studies, volume 34, issue 7, pages 3456-3496.
• Claudiu-Catalin Munteanu & Adina Cristea, 2021, "A Methodological Approach for the Journey through Real-Time Marketing: From Customer Journey Analytics to Personalization Engines," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 2, pages 849-855, December.
• Alessandro Bitetto & Paola Cerchiello & Charilaos Mertzanis, 2021, "A data-driven approach to measuring epidemiological susceptibility risk around the world," DEM Working Papers Series, University of Pavia, Department of Economics and Management, number 200, Feb.
• Marco Vega & Erick Lahura & Hilary Coronado, 2021, "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Documentos de Trabajo / Working Papers, Departamento de Economía - Pontificia Universidad Católica del Perú, number 2021-497, DOI: 10.18800/2079-8474.0497.
• Julian Hinz & Amrei Stammann & Joschka Wanner, 2021, "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," CEPA Discussion Papers, Center for Economic Policy Analysis, number 36, Jul, DOI: 10.25932/publishup-51191.
• Kollár, Aladár, 2021, "Betting models using AI: a review on ANN, SVM, and Markov chain," MPRA Paper, University Library of Munich, Germany, number 106821, Mar.
• Ofori, Isaac K, 2021, "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper, University Library of Munich, Germany, number 108622.
• 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, University Library of Munich, Germany, number 110452.
• Ando, Tomohiro & Bai, Jushan, 2021, "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper, University Library of Munich, Germany, number 111431, Dec.
• Korobilis, Dimitris & Shimizu, Kenichi, 2021, "Bayesian Approaches to Shrinkage and Sparse Estimation," MPRA Paper, University Library of Munich, Germany, number 111631, Dec.
• Kombarov, Sayan, 2021, "Action in Economics: Mathematical Derivation of Laws of Economics from the Principle of Least Action in Physics," MPRA Paper, University Library of Munich, Germany, number 112474, Aug.
• Bradrania, Reza & Pirayesh Neghab, Davood, 2021, "State-dependent asset allocation using neural networks," MPRA Paper, University Library of Munich, Germany, number 115254, Feb.
• Christiane Baumeister & Danilo Leiva-Leon & Eric Sims, 2021, "Tracking Weekly State-Level Economic Conditions," Working Papers, University of Pretoria, Department of Economics, number 202151, Jul.
• Mark Braverman & Sylvain Chassang, 2021, "Data-Driven Incentive Alignment in Capitation Schemes," Working Papers, Princeton University, Department of Economics, Center for Economic Policy Studies., number 282, Feb.
• Yuhei Miyauchi & Kentaro Nakajima & Stephen J. Redding, 2021, "Consumption Access and Agglomeration: Evidence from Smartphone Data," Working Papers, Princeton University, Department of Economics, Center for Economic Policy Studies., number 287, Jun.
• Bhumjai Tangsawasdirat & Suranan Tanpoonkiat & Burasakorn Tangsatchanan, 2021, "Credit Risk Database: Credit Scoring Models for Thai SMEs," PIER Discussion Papers, Puey Ungphakorn Institute for Economic Research, number 168, Nov.
• Giulio Marini, 2021, "Joining the European Union as an advantage in science performativity. A quasi-experimental study," DoQSS Working Papers, Quantitative Social Science - UCL Social Research Institute, University College London, number 21-09, Apr.
• Luke Hartigan & Michelle Wright, 2021, "Financial Conditions and Downside Risk to Economic Activity in Australia," RBA Research Discussion Papers, Reserve Bank of Australia, number rdp2021-03, Mar, DOI: 10.47688/rdp2021-03.
• Coronado, Hilary & Lahura, Erick & Vega, Marco, 2021, "¿Qué tan rígidos son los precios en línea? Evidencia para el Perú usando Big Data," Revista Moneda, Banco Central de Reserva del Perú, issue 188, pages 30-33.
• Karen Poghosyan & Ruben Poghosyan, 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), volume 61, pages 28-46.
• Denise Desjardins & Georges Dionne & Yang Lu, 2021, "Hierarchical random effects model for insurance pricing of vehicles belonging to a fleet," Working Papers, HEC Montreal, Canada Research Chair in Risk Management, number 21-2, Feb.
• Roselyn Dimingo & John W. Muteba Mwamba & Lumengo Bonga-Bonga, 2021, "Prediction of Stock Market Direction: Application of Machine Learning Models," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, volume 74, issue 4, pages 499-536.
• Markos Farag & Chahir Zaki, 2021, "On the Determinants of Trade in Natural Gas: A Political Economy Approach," EWI Working Papers, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI), number 2021-8, Nov.
• Anitha Rao & Mark Wiendling & Paul Ridgeway & Liz Kennedy & Harris A. Eyre & Paulo Pinho, 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, volume 54, pages 142-147.
• Hwee Kwan Chow & Daniel Han, 2021, "Forecast Pooling or Information Pooling During Crises? MIDAS Forecasting of GDP in a Small Open Economy," Economics and Statistics Working Papers, Singapore Management University, School of Economics, number 6-2021, Jul.
• Huaiwen ZHANG & Adnan Khurshid & Xinyu WANG & Alina Mirela BĂLTĂŢEANU, 2021, "Corporate Financial Risk Assessment and Role of Big Data; New Perspective Using Fuzzy Analytic Hierarchy Process," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 2, pages 181-199, June.
• Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021, "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium, Ghent University, Faculty of Economics and Business Administration, number 21/1028, Sep.
• Wojciech Charemza & Michał Lewandowski & Łukasz Woźny, 2021, "Efficiency in rewarding academic journal publications. The case of Poland," KAE Working Papers, Warsaw School of Economics, Collegium of Economic Analysis, number 2021-062, Feb, DOI: 10.33119/kaewps2021062.
• Paolo Nicola Barbieri & Beatrice Bonini, 2021, "Political orientation and adherence to social distancing during the COVID-19 pandemic in Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, volume 38, issue 2, pages 483-504, July, DOI: 10.1007/s40888-021-00224-w.
• Christopher Helm & Tim A. Herberger & Marcel Tyrell, 2021, "Demand dynamics across secondary German Book markets: an information aggregation and synthetization approach," Information Systems and e-Business Management, Springer, volume 19, issue 2, pages 567-596, June, DOI: 10.1007/s10257-021-00512-9.
• Faustino Prieto & José María Sarabia & Enrique Calderín-Ojeda, 2021, "The nonlinear distribution of employment across municipalities," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, volume 16, issue 2, pages 287-307, April, DOI: 10.1007/s11403-020-00294-2.
• Christian Hutter, 2021, "Cyclicality of labour market search: a new big data approach," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), volume 55, issue 1, pages 1-16, December, DOI: 10.1186/s12651-020-00283-9.
• 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), volume 19, issue 1, pages 383-400, December, DOI: 10.1007/s40953-021-00276-6.
• Iasonas Papafotikas & Dimitrios Folinas, 2021, "Sentiment Analysis: Relationship Between Customer Sentiment and Online Customer Ratings for Price Comparison Engines. An Empirical Study," Springer Proceedings in Business and Economics, Springer, in: Alexandra Horobet & Lucian Belascu & Persefoni Polychronidou & Anastasios Karasavvoglou, "Global, Regional and Local Perspectives on the Economies of Southeastern Europe", DOI: 10.1007/978-3-030-57953-1_16.
• Fu-Hsiang Kuo, 2021, "An Investigation of the Operational Efficiency of School Management through Innovative Teaching via Digital Mobile E-learning: DEA and Data mining Methodology," Advances in Management and Applied Economics, SCIENPRESS Ltd, volume 11, issue 1, pages 1-1.
• Chris van Wyk, 2021, "Learner flow through patterns in the Western Cape using CEMIS datasets from 2007 to 2019: A longitudinal cohort analysis," Working Papers, Stellenbosch University, Department of Economics, number 01/2021.
• 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.
• 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.
• Dimitris Korobilis, 2021, "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 39, issue 2, pages 493-504, March, DOI: 10.1080/07350015.2019.1677472.
• Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021, "Expecting the unexpected: economic growth under stress," Working Papers, University of California at Riverside, Department of Economics, number 202106, Mar.
• Guillermo Cabanillas-Jiménez, 2021, "Testing the Permanent Income Hypothesis using the Spanish Christmas Lottery," Studies in Economics, School of Economics, University of Kent, number 2104, Mar.
• Dylan Brewer & Alyssa Carlson, 2021, "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers, Department of Economics, University of Missouri, number 2102.
• Dylan Brewer & Alyssa Carlson, 2021, "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers, Department of Economics, University of Missouri, number 2114, Sep.
• Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021, "Longing for which home: Evidence from global aspirations to stay, return or migrate onwards," MERIT Working Papers, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT), number 2021-035, Sep.
• Jankowiak Maciej, 2021, "The EU Member States’ national healthcare systems compared using the single synthetic index," Economics and Business Review, Sciendo, volume 7, issue 2, pages 37-49, June, DOI: 10.18559/ebr.2021.2.4.
• Poláček Lukáš & Vavřina Jan & Polák Josef, 2021, "Current Challenges of Social Responsibility Best Practise in Foodstuff Production and Distribution Chain: Focus on Cee Countries," Management Theory and Studies for Rural Business and Infrastructure Development, Sciendo, volume 43, issue 4, pages 442-456, December, DOI: 10.15544/mts.2021.40.
• Poláček Lukáš & Vavřina Jan & Polák Josef, 2021, "Current Challenges of Social Responsibility Best Practise in Foodstuff Production and Distribution Chain: Focus on Cee Countries," Management Theory and Studies for Rural Business and Infrastructure Development, Sciendo, volume 43, issue 4, pages 442-456, December, DOI: 10.15544/mtsrbid-2021-40.
• 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.
• 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.
• Maaz Khan & Faheem Aslam & Paulo Ferreira, 2021, "Extreme Value Theory and COVID-19 Pandemic: Evidence from India," Economic Research Guardian, Mutascu Publishing, volume 11, issue 1, pages 2-10, June.
• Mrestyal Khan & Maaz Khan, 2021, "Cryptomarket Volatility in Times of COVID-19 Pandemic: Application of GARCH Models," Economic Research Guardian, Mutascu Publishing, volume 11, issue 2, pages 170-181, December.
• Stefan Ederer & Stefan Humer & Stefan Jestl & Emanuel List, 2020, "Distributional National Accounts (DINA) with Household Survey Data. Methodology and Results for European Countries," WIFO Working Papers, WIFO, number 599, Apr.
• Peter C. B. Phillips & Zhentao Shi, 2021, "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, volume 62, issue 2, pages 521-570, May, DOI: 10.1111/iere.12495.
• Ricketts, Simon, 2021, "Do Political Actors Engage in Strategic Deception on Social Media?," Warwick-Monash Economics Student Papers, Warwick Monash Economics Student Papers, number 16.
• Hauber, Philipp & Schumacher, Christian, 2021, "Precision-based sampling with missing observations: A factor model application," Discussion Papers, Deutsche Bundesbank, number 11/2021.
• Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2021, "The simpler, the better: Measuring financial conditions for monetary policy and financial stability," EIB Working Papers, European Investment Bank (EIB), number 2021/10, DOI: 10.2867/149278.
• 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.
• Ofori, Isaac Kwesi, 2021, "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 235482.
• 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.
• Sarracino, Francesco & Greyling, Talita & O'Connor , Kelsey & Peroni, Chiara & Rossouw, Stephanie, 2021, "A year of pandemic: levels, changes and validity of well-being data from Twitter. Evidence from ten countries," GLO Discussion Paper Series, Global Labor Organization (GLO), number 831.
• Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021, "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," GLO Discussion Paper Series, Global Labor Organization (GLO), number 930.
• Dörr, Julian Oliver & Kinne, Jan & Lenz, David & Licht, Georg & Winker, Peter, 2021, "An integrated data framework for policy guidance in times of dynamic economic shocks," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 21-062.

2020

• Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020, "Targeting predictors in random forest regression," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2020-03, May.
• 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, Department of Economics and Business Economics, Aarhus University, number 2020-19, Dec.
• 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, Department of Economics, Auburn University, number auwp2020-02, May.
• Maryam Farboodi & Laura Veldkamp, 2020, "Long-Run Growth of Financial Data Technology," American Economic Review, American Economic Association, volume 110, issue 8, pages 2485-2523, August, DOI: 10.1257/aer.20171349.
• Janet Currie & Henrik Kleven & Esmée Zwiers, 2020, "Technology and Big Data Are Changing Economics: Mining Text to Track Methods," AEA Papers and Proceedings, American Economic Association, volume 110, pages 42-48, May, DOI: 10.1257/pandp.20201058.
• Viorelia LUNGU, 2020, "Some Notes on the Geopolitics and Geo-economics of Russia’s Post-Soviet Neocolonialism in Central Asia," Eastern European Journal for Regional Studies (EEJRS), Center for Studies in European Integration (CSEI), Academy of Economic Studies of Moldova (ASEM), volume 6, issue 1, pages 87-101, June.
• Edson Zambon Monte & Felipe Fantin Almeida, 2020, "Interrelationships Between The Stock Returns Of Brazilian Companies That Make Up The Sãƒo Paulo Stock Exchange Index," Revista de Economia Mackenzie (REM), Mackenzie Presbyterian University, Social and Applied Sciences Center, volume 17, issue 1, pages 115-145, January-J, DOI: 105935/1808-2785/rem.v17n1p.115-145.
• Castelli, Chiara & Parenti, Angela, , "Commuting in Europe: An Inter-regional Analysis on its Determinants and Spatial Effects," 2030 Agenda, Fondazione Eni Enrico Mattei (FEEM), number 307985, DOI: 10.22004/ag.econ.307985.
• Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020, "Modeling Joint Lives within Families," AMSE Working Papers, Aix-Marseille School of Economics, France, number 2021, Jun.
• Klaus Ackermann & Alexey Chernikov & Nandini Anantharama & Miethy Zaman & Paul A Raschky, 2020, "Object Recognition for Economic Development from Daytime Satellite Imagery," SoDa Laboratories Working Paper Series, Monash University, SoDa Laboratories, number 2020-02, Sep.
• Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020, "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series, Monash University, SoDa Laboratories, number 2020-04, Oct.
• Oscar Claveria & Ivana Lolic & Enric Monte & Salvador Torra & Petar Soric, 2020, "“Economic determinants of employment sentiment: A socio-demographic analysis for the euro area”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 2012001, Jan, revised Jan 2020.
• Daniel Borup & Bent Jesper Christensen & Nicolaj N{o}rgaard Muhlbach & Mikkel Slot Nielsen, 2020, "Targeting predictors in random forest regression," Papers, arXiv.org, number 2004.01411, Apr, revised Nov 2020.
• Dimitris Korobilis, 2020, "High-dimensional macroeconomic forecasting using message passing algorithms," Papers, arXiv.org, number 2004.11485, Apr.
• Julian Hinz & Amrei Stammann & Joschka Wanner, 2020, "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," Papers, arXiv.org, number 2004.12655, Apr, revised Jul 2021.
• Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020, "Modeling Joint Lives within Families," Papers, arXiv.org, number 2006.08446, Jun.
• Laurent Ferrara & Anna Simoni, 2020, "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers, arXiv.org, number 2007.00273, Jul, revised Sep 2022.
• Robert Adamek & Stephan Smeekes & Ines Wilms, 2020, "Lasso Inference for High-Dimensional Time Series," Papers, arXiv.org, number 2007.10952, Jul, revised Sep 2022.
• Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020, "Deep Dynamic Factor Models," Papers, arXiv.org, number 2007.11887, Jul, revised May 2023.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020, "Macroeconomic Data Transformations Matter," Papers, arXiv.org, number 2008.01714, Aug, revised Mar 2021.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020, "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers, arXiv.org, number 2008.12477, Aug.
• Klaus Ackermann & Alexey Chernikov & Nandini Anantharama & Miethy Zaman & Paul A Raschky, 2020, "Object Recognition for Economic Development from Daytime Satellite Imagery," Papers, arXiv.org, number 2009.05455, Sep.
• Tae-Hwy Lee & Ekaterina Seregina, 2020, "Optimal Portfolio Using Factor Graphical Lasso," Papers, arXiv.org, number 2011.00435, Nov, revised Apr 2023.
• David Kohns & Arnab Bhattacharjee, 2020, "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers, arXiv.org, number 2011.00938, Nov, revised May 2022.
• Tae-Hwy Lee & Ekaterina Seregina, 2020, "Learning from Forecast Errors: A New Approach to Forecast Combinations," Papers, arXiv.org, number 2011.02077, Nov, revised May 2021.
• Michael Allan Ribers & Hannes Ullrich, 2020, "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," Papers, arXiv.org, number 2011.11017, Nov.
• Catalin DUMITRESCU, 2020, "Financial Stability Of Economic Agencies In Conditions Of Economic Crisis," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 57, issue 1, pages 22-33, March.
• Cătălin DUMITRESCU & Matei DUMITRESCU, 2020, "Virtual Currency And Global Business - The New Trend In The Net-Economy," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 58, issue 2, pages 22-32, June.
• Robert HELLVIG & Cătălin DUMITRESCU & Matei DUMITRESCU, 2020, "Management Of Cybercrime In The Financial Field - Perspectives To Combat The Phenomenon," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 59, issue 3, pages 23-33, September.
• DănuÅ£-Octavian SIMION & Emilia VASILE, 2020, "Models Of Classes For Economic Objects In Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 59, issue 3, pages 9-22, September.
• Emilia VASILE & DănuÅ£-Octavian SIMION, 2020, "Polymorphism Of Classes And Reference Of Instances Distribution For Economic Objects In Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 60, issue 4, pages 9-21, December.
• Gail Pacheco & Alexander Plum, 2020, "When there is no way up: Reconsidering low-paid jobs as stepping stones," Working Papers, Auckland University of Technology, Department of Economics, number 2020-08, Jul.
• Cristina Caprara & Daniele Vergari, 2020, "Credit risk analysis and lending decisions: new Machine Learning techniques," BANCARIA, Bancaria Editrice, volume 1, pages 49-53, January.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020, "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 20-01, Apr, revised Aug 2020.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020, "Macroeconomic Data Transformations Matter," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 20-17, Aug, revised Mar 2021.
• Kevin Moran & Dalibor Stevanovic & Adam Kader Toure, 2020, "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 20-18, Sep, revised Dec 2020.
• Luis Antonio Espinosa & Juan José Li Ng, 2020, "El riesgo del sargazo para la economía y turismo de Quintana Roo y México
  [The risk of sargassum to the economy and tourism of Quintana Roo and Mexico]," Working Papers, BBVA Bank, Economic Research Department, number 20/02, Feb.
• Ali Batuhan Barlas & Seda Guler Mert & Alvaro Ortiz & Tomasa Rodrigo, 2020, "Global | Inversión en tiempo real y alta definición: Un enfoque Big Data
  [Global | Investment in Real Time and High Definition: A Big Data Approach]," Working Papers, BBVA Bank, Economic Research Department, number 20/13, Oct.
• Eddie Gerba & Danilo Leiva-Leon, 2020, "Macro-financial interactions in a changing world," Working Papers, Banco de España, number 2018, Jul.