Research classified by Journal of Economic Literature (JEL) codes

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

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, Paradigm, 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, Paradigm, 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, Paradigm, 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.
• 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, undated, "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, 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, 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 & 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 & 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 & Risk Management, Athenaeum University of Bucharest, volume 59, issue 3, pages 23-33, September.
• Dănuţ-Octavian SIMION & Emilia VASILE, 2020, "Models Of Classes For Economic Objects In Applications," Internal Auditing & Risk Management, Athenaeum University of Bucharest, volume 59, issue 3, pages 9-22, September.
• Emilia VASILE & Dănuţ-Octavian SIMION, 2020, "Polymorphism Of Classes And Reference Of Instances Distribution For Economic Objects In Applications," Internal Auditing & 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, "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 | 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.
• Hanjo Odendaal & Monique Reid & Johann F. Kirsten, 2020, "Media‐Based Sentiment Indices as an Alternative Measure of Consumer Confidence," South African Journal of Economics, Economic Society of South Africa, volume 88, issue 4, pages 409-434, December, DOI: 10.1111/saje.12261.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020, "News media vs. FRED-MD for macroeconomic forecasting," Working Paper, Norges Bank, number 2020/14, Oct.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020, "News media vs. FRED-MD for macroeconomic forecasting," Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School, number No 08/2020, Oct.
• Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2020, "Making text count: economic forecasting using newspaper text," Bank of England Staff Working Paper series, Bank of England, number 865, May.
• Hyeongwoo Kim & Soohyon Kim, 2020, "Common Factor Augmented Forecasting Models for the US Dollar-Korean Won Exchange Rate," Working Papers, Economic Research Institute, Bank of Korea, number 2020-5, Feb.
• 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.
• Ahmed, R. & Pesaran, M. H., 2020, "Regional Heterogeneity and U.S. Presidential Elections," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2092, Oct.
• Markus Heinrich & Magnus Reif, 2020, "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series, CESifo, number 8054.
• 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.
• Rashad Ahmed & M. Hashem Pesaran, 2020, "Regional Heterogeneity and U.S. Presidential Elections," CESifo Working Paper Series, CESifo, number 8615.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020, "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series, CESifo, number 8639.
• Michael Allan Ribers & Hannes Ullrich, 2020, "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," CESifo Working Paper Series, CESifo, number 8702.
• Magnus Reif, 2020, "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87, September.
• 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.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2020, "Macroeconomic Data Transformations Matter," CIRANO Working Papers, CIRANO, number 2020s-42, Aug.
• Kevin Moran & Dalibor Stevanovic & Adam Abdel Kader Touré, 2020, "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," CIRANO Working Papers, CIRANO, number 2020s-47, Sep.
• Feng, Guanhao & Giglio, Stefano & Xiu, Dacheng, 2020, "Taming the Factor Zoo: A Test of New Factors," CEPR Discussion Papers, Centre for Economic Policy Research, number 14266, Jan.
• Mark Trede & Michael Zimmermann, 2020, "Regional labour migration - Stylized facts for Germany," CQE Working Papers, Center for Quantitative Economics (CQE), University of Muenster, number 9320, Sep.
• Franchi, Massimo & Paruolo, Paolo, 2020, "Cointegration In Functional Autoregressive Processes," Econometric Theory, Cambridge University Press, volume 36, issue 5, pages 803-839, October.
• Antonia Grohmann & Steffen Herbold & Friederike Lenel, 2020, "Repayment under Flexible Loan Contracts: Evidence from Tanzania," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1884.
• Michael Allan Ribers & Hannes Ullrich, 2020, "Machine Predictions and Human Decisions with Variation in Payoffs and Skills," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1911.
• Laurent Ferrara & Anna Simoni, 2020, "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers, University of Paris Nanterre, EconomiX, number 2020-11.
• Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2020, "The long-run information effect of central bank communication," Working Paper Series, European Central Bank, number 2363, Jan.
• Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2020, "The simpler the better: measuring financial conditions for monetary policy and financial stability," Working Paper Series, European Central Bank, number 2451, Aug.
• Ferrari Minesso, Massimo & Pagliari, Maria Sole & Kurcz, Frederik, 2020, "Do words hurt more than actions? The impact of trade tensions on financial markets," Working Paper Series, European Central Bank, number 2490, Nov.
• Schönheit, David & Weinhold, Richard & Dierstein, Constantin, 2020, "The impact of different strategies for generation shift keys (GSKs) on the flow-based market coupling domain: A model-based analysis of Central Western Europe," Applied Energy, Elsevier, volume 258, issue C, DOI: 10.1016/j.apenergy.2019.114067.
• Milusheva, Sveta, 2020, "Managing the spread of disease with mobile phone data," Journal of Development Economics, Elsevier, volume 147, issue C, DOI: 10.1016/j.jdeveco.2020.102559.
• Schnaubelt, Matthias & Fischer, Thomas G. & Krauss, Christopher, 2020, "Separating the signal from the noise – Financial machine learning for Twitter," Journal of Economic Dynamics and Control, Elsevier, volume 114, issue C, DOI: 10.1016/j.jedc.2020.103895.
• Pham, Manh Cuong & Anderson, Heather Margot & Duong, Huu Nhan & Lajbcygier, Paul, 2020, "The effects of trade size and market depth on immediate price impact in a limit order book market," Journal of Economic Dynamics and Control, Elsevier, volume 120, issue C, DOI: 10.1016/j.jedc.2020.103992.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020, "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, volume 88, issue C, pages 341-355, DOI: 10.1016/j.econmod.2019.09.046.
• Arata, Linda & Fabrizi, Enrico & Sckokai, Paolo, 2020, "A worldwide analysis of trend in crop yields and yield variability: Evidence from FAO data," Economic Modelling, Elsevier, volume 90, issue C, pages 190-208, DOI: 10.1016/j.econmod.2020.05.006.
• Álvarez de Toledo, Pablo & Núñez, Fernando & Usabiaga, Carlos, 2020, "Matching in segmented labor markets: An analytical proposal based on high-dimensional contingency tables," Economic Modelling, Elsevier, volume 93, issue C, pages 175-186, DOI: 10.1016/j.econmod.2020.07.019.
• Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020, "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, volume 93, issue C, pages 576-585, DOI: 10.1016/j.econmod.2020.09.015.
• Sant’Anna, Leonardo Riegel & Caldeira, João Frois & Filomena, Tiago Pascoal, 2020, "Lasso-based index tracking and statistical arbitrage long-short strategies," The North American Journal of Economics and Finance, Elsevier, volume 51, issue C, DOI: 10.1016/j.najef.2019.101055.
• Gupta, Rangan & Sun, Xiaojin, 2020, "Forecasting economic policy uncertainty of BRIC countries using Bayesian VARs," Economics Letters, Elsevier, volume 186, issue C, DOI: 10.1016/j.econlet.2019.108677.
• Wei, Jie & Chen, Hui, 2020, "Determining the number of factors in approximate factor models by twice K-fold cross validation," Economics Letters, Elsevier, volume 191, issue C, DOI: 10.1016/j.econlet.2020.109149.
• Wei, Jie & Zhang, Yonghui, 2020, "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, volume 193, issue C, DOI: 10.1016/j.econlet.2020.109337.
• Fan, Yanqin & Han, Fang & Li, Wei & Zhou, Xiao-Hua, 2020, "On rank estimators in increasing dimensions," Journal of Econometrics, Elsevier, volume 214, issue 2, pages 379-412, DOI: 10.1016/j.jeconom.2019.08.003.
• 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.
• Huang, Danyang & Wang, Feifei & Zhu, Xuening & Wang, Hansheng, 2020, "Two-mode network autoregressive model for large-scale networks," Journal of Econometrics, Elsevier, volume 216, issue 1, pages 203-219, DOI: 10.1016/j.jeconom.2020.01.014.
• Chan, N.H. & Cheung, Simon K.C. & Wong, Samuel P.S., 2020, "Inference for the degree distributions of preferential attachment networks with zero-degree nodes," Journal of Econometrics, Elsevier, volume 216, issue 1, pages 220-234, DOI: 10.1016/j.jeconom.2020.01.015.
• Vogt, Michael & Linton, Oliver, 2020, "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, volume 216, issue 1, pages 305-325, DOI: 10.1016/j.jeconom.2020.01.020.
• Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020, "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, volume 216, issue 1, pages 86-105, DOI: 10.1016/j.jeconom.2020.01.007.
• Hafner, Christian M. & Linton, Oliver B. & Tang, Haihan, 2020, "Estimation of a multiplicative correlation structure in the large dimensional case," Journal of Econometrics, Elsevier, volume 217, issue 2, pages 431-470, DOI: 10.1016/j.jeconom.2019.12.012.
• Galbraith, John W. & Zinde-Walsh, Victoria, 2020, "Simple and reliable estimators of coefficients of interest in a model with high-dimensional confounding effects," Journal of Econometrics, Elsevier, volume 218, issue 2, pages 609-632, DOI: 10.1016/j.jeconom.2020.04.031.
• Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020, "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, volume 219, issue 1, pages 171-200, DOI: 10.1016/j.jeconom.2020.04.043.
• 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.
• Reschenhofer, Erhard & Mangat, Manveer Kaur & Stark, Thomas, 2020, "Volatility forecasts, proxies and loss functions," Journal of Empirical Finance, Elsevier, volume 59, issue C, pages 133-153, DOI: 10.1016/j.jempfin.2020.09.006.
• Evangelista, Rui & Ramalho, Esmeralda A. & Andrade e Silva, João, 2020, "On the use of hedonic regression models to measure the effect of energy efficiency on residential property transaction prices: Evidence for Portugal and selected data issues," Energy Economics, Elsevier, volume 86, issue C, DOI: 10.1016/j.eneco.2020.104699.
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