Research classified by Journal of Economic Literature (JEL) codes

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

2021

• 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 & Michal Lewandowski & Lukasz Wozny, 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.
• 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.
• Nélida Díaz Sobrino & Corinna Ghirelli & Samuel Hurtado & Javier J. Pérez & Alberto Urtasun, 2020, "The narrative about the economy as a shadow forecast: an analysis using Banco de España quarterly reports," Working Papers, Banco de España, number 2042, Dec.
• Bradley Shapiro & Günter J. Hitsch & Anna Tuchman, 2020, "Generalizable and Robust TV Advertising Effects," Working Papers, Becker Friedman Institute for Research In Economics, number 2020-111.
• Caroline Jardet & Baptiste Meunier, 2020, "Nowcasting World GDP Growth with High-Frequency Data," Working papers, Banque de France, number 788.
• Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020, "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Discussion Papers, Department of Economics, University of Birmingham, number 20-03, Feb.
• Daniel Levy & Tamir Mayer & Alon Raviv, 2020, "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers, Bar-Ilan University, Department of Economics, number 2020-01, Jan.
• Filipp Ulyankin, 2020, "Forecasting Russian Macroeconomic Indicators Based on Information from News and Search Queries," Russian Journal of Money and Finance, Bank of Russia, volume 79, issue 4, pages 75-97, December, DOI: 10.31477/rjmf.202004.75.
• Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020, "Taming the Factor Zoo: A Test of New Factors," Journal of Finance, American Finance Association, volume 75, issue 3, pages 1327-1370, June, DOI: 10.1111/jofi.12883.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020, "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, volume 82, issue 2, pages 285-310, April, DOI: 10.1111/obes.12335.
• Jaqueson K. Galimberti, 2020, "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, volume 82, issue 4, pages 697-722, August, DOI: 10.1111/obes.12361.
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• Andreas Gulyas & Krzysztof Pytka, 2020, "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," CRC TR 224 Discussion Paper Series, University of Bonn and University of Mannheim, Germany, number crctr224_2020_131v2, May.
• Cristea, R. G., 2020, "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 20108, Nov.
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• Jonas Klos & Tim Krieger & Sven Stöwhase, 2020, "Measuring Intra-Generational Redistribution in PAYG Pension Schemes," CESifo Working Paper Series, CESifo, number 8200.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020, "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks," CESifo Working Paper Series, CESifo, number 8475.
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• Roberto Molinari & Gaetan Bakalli & Stéphane Guerrier & Cesare Miglioli & Samuel Orso & O. Scaillet, 2020, "Swag: A Wrapper Method for Sparse Learning," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 20-49, Jun.
• David Ardia & Laurent Barras & Patrick Gagliardini & Olivier Scaillet, 2020, "Is it Alpha or Beta? Decomposing Hedge Fund Returns When Models are Misspecified," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 20-82, Sep, revised May 2023.
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• Cai, T. Tony & Hu, Jianchang & Li, Yingying & Zheng, Xinghua, 2020, "High-dimensional minimum variance portfolio estimation based on high-frequency data," Journal of Econometrics, Elsevier, volume 214, issue 2, pages 482-494, DOI: 10.1016/j.jeconom.2019.04.039.
• Li, Z. Merrick & Laeven, Roger J.A. & Vellekoop, Michel H., 2020, "Dependent microstructure noise and integrated volatility estimation from high-frequency data," Journal of Econometrics, Elsevier, volume 215, issue 2, pages 536-558, DOI: 10.1016/j.jeconom.2019.10.004.
• Zhu, Xuening & Huang, Danyang & Pan, Rui & Wang, Hansheng, 2020, "Multivariate spatial autoregressive model for large scale social networks," Journal of Econometrics, Elsevier, volume 215, issue 2, pages 591-606, DOI: 10.1016/j.jeconom.2018.11.018.
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• Nevrla, Matěj, 2020, "Systemic risk in European financial and energy sectors: Dynamic factor copula approach," Economic Systems, Elsevier, volume 44, issue 4, DOI: 10.1016/j.ecosys.2020.100820.
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• DePaula, Guilherme, 2020, "The distributional effect of climate change on agriculture: Evidence from a Ricardian quantile analysis of Brazilian census data," Journal of Environmental Economics and Management, Elsevier, volume 104, issue C, DOI: 10.1016/j.jeem.2020.102378.
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• Samaratunge, Ramanie & Kumara, Ajantha Sisira & Abeysekera, Lakmal, 2020, "Breaking the Perverse Health-debt Cycle in Sri Lanka: Policy Options," Journal of Policy Modeling, Elsevier, volume 42, issue 3, pages 728-745, DOI: 10.1016/j.jpolmod.2020.01.003.
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• Tino Berger & James Morley & Benjamin Wong, 2020, "Nowcasting the Output Gap," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2020-78, Aug.
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• Nguyen Khanh Doanh & Linh Tuan Truong & Yoon Heo, 2020, "Impact of institutional and cultural distances on ASEAN's trade efficiency," Journal of Economic Studies, Emerald Group Publishing Limited, volume 49, issue 1, pages 77-94, December, DOI: 10.1108/JES-07-2020-0343.
• Luisa Mendonça & Alan De Genaro, 2020, "Detection and analysis of occurrences of spoofing in the Brazilian capital market," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, volume 28, issue 3, pages 369-408, March, DOI: 10.1108/JFRC-07-2019-0092.
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