Research classified by Journal of Economic Literature (JEL) codes

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

2019

• Alacevich, Caterina & Nicodemo, Catia, 2019, "Immigration and Work-Related Injuries: Evidence from Italian Administrative Data," IZA Discussion Papers, IZA Network @ LISER, number 12510, Jul.
• Bruno, Randolph Luca & Douarin, Elodie & Korosteleva, Julia & Radosevic, Slavo, 2019, "Determinants of Productivity Gap in the European Union: A Multilevel Perspective," IZA Discussion Papers, IZA Network @ LISER, number 12542, Aug.
• Harold D. Chiang, 2019, "Many Average Partial Effects: with an Application to Text Regression," 2019 Papers, Job Market Papers, number pch1836, Oct.
• Rituparna Sen & Manavathi Subramaniam, 2019, "Stylized Facts of the Indian Stock Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, volume 26, issue 4, pages 479-493, December, DOI: 10.1007/s10690-019-09275-3.
• Oscar Claveria & Enric Monte & Salvador Torra, 2019, "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, volume 46, issue 2, pages 205-227, May, DOI: 10.1007/s10663-017-9395-1.
• Qing Luo & Daniel A. Griffith & Huayi Wu, 2019, "Spatial autocorrelation for massive spatial data: verification of efficiency and statistical power asymptotics," Journal of Geographical Systems, Springer, volume 21, issue 2, pages 237-269, June, DOI: 10.1007/s10109-019-00293-3.
• Kim Kaivanto & Peng Zhang, 2019, "Popular Music, Sentiment, and Noise Trading," Working Papers, Lancaster University Management School, Economics Department, number 279326509.
• Christophe HURLIN & Christophe PERIGNON, 2019, "Machine Learning et nouvelles sources de données pour le scoring de crédit," LEO Working Papers / DR LEO, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans, number 2739.
• Andrea Bastianin, 2019, "Robust measures of skewness and kurtosis for macroeconomic and financial time series," Working Papers, University of Milano-Bicocca, Department of Economics, number 408, May, revised 06 May 2019.
• Tamás Sikos T. & Csaba József Kovács, 2019, "The Silver Generation as Potential Purchasing Power in Budapest: a Case Study," Theory Methodology Practice (TMP), Faculty of Economics, University of Miskolc, volume 15, issue 02, pages 53-63.
• Priyanga Dilini Talagala & Rob J Hyndman & Kate Smith-Miles, 2019, "Anomaly Detection in High Dimensional Data," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 20/19.
• Bo Zhang & Jiti Gao & Guangming Pan & Yanrong Yang, 2019, "Spiked Eigenvalues of High-Dimensional Separable Sample Covariance Matrices," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 31/19.
• Hannes Mueller & Christopher Rauh, 2019, "The hard problem of prediction for conflict prevention," Cahiers de recherche, Universite de Montreal, Departement de sciences economiques, number 2019-02, Apr.
• Hannes Mueller & Christopher Rauh, 2019, "The Hard Problem of Prediction for Conflict Prevention," Cahiers de recherche, Centre interuniversitaire de recherche en économie quantitative, CIREQ, number 02-2019, Apr.
• Paweł Macias & Damian Stelmasiak, 2019, "Food inflation nowcasting with web scraped data," NBP Working Papers, Narodowy Bank Polski, number 302.
• Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2021, "From Transaction Data to Economic Statistics: Constructing Real-Time, High-Frequency, Geographic Measures of Consumer Spending," NBER Chapters, National Bureau of Economic Research, Inc, "Big Data for Twenty-First-Century Economic Statistics".
• Jeffrey C. Chen & Abe Dunn & Kyle Hood & Alexander Driessen & Andrea Batch, 2019, "Off to the Races: A Comparison of Machine Learning and Alternative Data for Predicting Economic Indicators," NBER Chapters, National Bureau of Economic Research, Inc, "Big Data for Twenty-First-Century Economic Statistics".
• Rishab Guha & Serena Ng, 2019, "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, National Bureau of Economic Research, Inc, "Big Data for Twenty-First-Century Economic Statistics".
• Rebecca J. Hutchinson, 2019, "Improving Retail Trade Data Products Using Alternative Data Sources," NBER Chapters, National Bureau of Economic Research, Inc, "Big Data for Twenty-First-Century Economic Statistics".
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019, "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, National Bureau of Economic Research, Inc, "Big Data for Twenty-First-Century Economic Statistics".
• Arthur Turrell & Bradley Speigner & Jyldyz Djumalieva & David Copple & James Thurgood, 2019, "Transforming Naturally Occurring Text Data into Economic Statistics: The Case of Online Job Vacancy Postings," NBER Chapters, National Bureau of Economic Research, Inc, "Big Data for Twenty-First-Century Economic Statistics".
• John Cuffe & Sudip Bhattacharjee & Ugochukwu Etudo & Justin C. Smith & Nevada Basdeo & Nathaniel Burbank & Shawn R. Roberts, 2019, "Using Public Data to Generate Industrial Classification Codes," NBER Chapters, National Bureau of Economic Research, Inc, "Big Data for Twenty-First-Century Economic Statistics".
• Michela Giorcelli & Nicola Lacetera & Astrid Marinoni, 2019, "How Does Scientific Progress Affect Cultural Changes? A Digital Text Analysis," NBER Working Papers, National Bureau of Economic Research, Inc, number 25429, Jan.
• Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2019, "Taming the Factor Zoo: A Test of New Factors," NBER Working Papers, National Bureau of Economic Research, Inc, number 25481, Jan.
• Arthur Turrell & Bradley J. Speigner & Jyldyz Djumalieva & David Copple & James Thurgood, 2019, "Transforming Naturally Occurring Text Data Into Economic Statistics: The Case of Online Job Vacancy Postings," NBER Working Papers, National Bureau of Economic Research, Inc, number 25837, May.
• Jon Kleinberg & Sendhil Mullainathan, 2019, "Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability," NBER Working Papers, National Bureau of Economic Research, Inc, number 25854, May.
• Rishab Guha & Serena Ng, 2019, "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Working Papers, National Bureau of Economic Research, Inc, number 25899, May.
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019, "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Working Papers, National Bureau of Economic Research, Inc, number 26033, Jul.
• Stefania Albanesi & Domonkos F. Vamossy, 2019, "Predicting Consumer Default: A Deep Learning Approach," NBER Working Papers, National Bureau of Economic Research, Inc, number 26165, Aug.
• Sendhil Mullainathan & Ziad Obermeyer, 2019, "Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care," NBER Working Papers, National Bureau of Economic Research, Inc, number 26168, Aug.
• Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019, "Predicting Returns With Text Data," NBER Working Papers, National Bureau of Economic Research, Inc, number 26186, Aug.
• Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2019, "From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending," NBER Working Papers, National Bureau of Economic Research, Inc, number 26253, Sep.
• Fernando M. Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019, "Are Small Farms Really more Productive than Large Farms?," NBER Working Papers, National Bureau of Economic Research, Inc, number 26331, Sep.
• Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019, "Demand Analysis with Many Prices," NBER Working Papers, National Bureau of Economic Research, Inc, number 26424, Nov.
• Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019, "Text Selection," NBER Working Papers, National Bureau of Economic Research, Inc, number 26517, Nov.
• Joshua Angrist & Brigham Frandsen, 2019, "Machine Labor," NBER Working Papers, National Bureau of Economic Research, Inc, number 26584, Dec.
• Ulrich K. Müller & James H. Stock & Mark W. Watson, 2019, "An Econometric Model of International Long-run Growth Dynamics," NBER Working Papers, National Bureau of Economic Research, Inc, number 26593, Dec.
• Jens Mehrhoff, 2019, "Introduction – The Value Chain of Scanner and Web Scraped Data," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 509, pages 5-11, DOI: https://doi.org/10.24187/ecostat.20.
• Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019, "Nowcasting GDP using machine learning algorithms: A real-time assessment," Reserve Bank of New Zealand Discussion Paper Series, Reserve Bank of New Zealand, number DP2019/03, Nov.
• Seán Kennedy, 2019, "The potential of tax microdata for tax policy," OECD Taxation Working Papers, OECD Publishing, number 45, Sep, DOI: 10.1787/d2283b8e-en.
• Arnaud Pincet & Shu Okabe & Martin Pawelczyk, 2019, "Linking Aid to the Sustainable Development Goals – a machine learning approach," OECD Development Co-operation Working Papers, OECD Publishing, number 52, Feb, DOI: 10.1787/4bdaeb8c-en.
• Nathan, Max & Rosso, Anna, 2019, "Innovative Events," SocArXiv, Center for Open Science, number t3jrq, Mar, DOI: 10.31219/osf.io/t3jrq.
• Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2019, "Identification of Global and Local Shocks in International Financial Markets via General Dynamic Factor Models," Journal of Financial Econometrics, Oxford University Press, volume 17, issue 3, pages 462-494.
• Simona Vasilica Oprea & Adela Bâra, 2019, "Big Data Solutions for Efficient Operation of Microgrids," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 1, pages 266-271, August.
• Simona-Vasilica Oprea & Adela Bâra & Dan PreoÈ›escu, 2019, "NoSQL Data Storage and Clustering Large Volume of Data from Smart Metering Systems with Impact on Electricity Consumption Peak and Tariff Settings," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 2, pages 327-333, December.
• Mora Rodríguez, Jhon James & González Terán, Ángela María, 2019, "Progresos educativos intergeneracionales: un análisis para Colombia || Intergenerational educational progress: an analysis for Colombia," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, volume 28, issue 1, pages 143-159, December.
• Joanna Olbrys, 2019, "Intra-market commonality in liquidity: new evidence from the Polish stock exchange," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, volume 14, issue 2, pages 251-275, June, DOI: 10.24136/eq.2019.012.
• Dhruv Grover & Sebastian Bauhoff & Jed Friedman, 2019, "Using supervised learning to select audit targets in performance-based financing in health: An example from Zambia," PLOS ONE, Public Library of Science, volume 14, issue 1, pages 1-13, January, DOI: 10.1371/journal.pone.0211262.
• Alifatussaadah, Ardiana & Primariesty, Anindya Diva & Soleh, Agus Mohamad & Andriansyah, Andriansyah, 2019, "Nowcasting Indonesia's GDP Growth: Are Fiscal Data Useful?," MPRA Paper, University Library of Munich, Germany, number 105252, Aug.
• Kbiri, Mohammed Alaoui & Ghassan, Hassan Belkacem, 2019, "Model reduction in dynamical VAR systems," MPRA Paper, University Library of Munich, Germany, number 122971, revised 2020.
• Yang, Bill Huajian, 2019, "Monotonic Estimation for the Survival Probability over a Risk-Rated Portfolio by Discrete-Time Hazard Rate Models," MPRA Paper, University Library of Munich, Germany, number 93398, Mar.
• Yang, Bill Huajian, 2019, "Monotonic Estimation for Probability Distribution and Multivariate Risk Scales by Constrained Minimum Generalized Cross-Entropy," MPRA Paper, University Library of Munich, Germany, number 93400, Mar.
• Maas, Benedikt, 2019, "Short-term forecasting of the US unemployment rate," MPRA Paper, University Library of Munich, Germany, number 94066, Apr.
• Genge, Ewa & Bartolucci, Francesco, 2019, "Are attitudes towards immigration changing in Europe? An analysis based on bidimensional latent class IRT models," MPRA Paper, University Library of Munich, Germany, number 94672, Jun.
• Loermann, Julius & Maas, Benedikt, 2019, "Nowcasting US GDP with artificial neural networks," MPRA Paper, University Library of Munich, Germany, number 95459, May.
• Indaco, Agustín, 2019, "From Twitter to GDP: Estimating Economic Activity From Social Media," MPRA Paper, University Library of Munich, Germany, number 95885, Mar.
• Korobilis, Dimitris, 2019, "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper, University Library of Munich, Germany, number 96079, Sep.
• Maas, Benedikt, 2019, "Nowcasting and forecasting US recessions: Evidence from the Super Learner," MPRA Paper, University Library of Munich, Germany, number 96408, Sep.
• Rahmati, Mohammad Hossein & Tavakoli, Amirhossein & Vesal, Mohammad, 2019, "What do one hundred million transactions tell us about demand elasticity of gasoline?," MPRA Paper, University Library of Munich, Germany, number 97858, Mar.
• Oguzhan Cepni & Selcuk Gul & Rangan Gupta, 2019, "Local Currency Bond Risk Premia of Emerging Markets: The Role of Local and Global Factors," Working Papers, University of Pretoria, Department of Economics, number 201901, Jan.
• Oguzhan Cepni & Rangan Gupta & I. Ethem Guney & M. Hasan Yilmaz, 2019, "Forecasting Local Currency Bond Risk Premia of Emerging Markets: The Role of Cross-Country Macro-Financial Linkages," Working Papers, University of Pretoria, Department of Economics, number 201957, Jul.
• Paweł Lula & Anna Kovaleva & Renata Oczkowska & Małgorzata Tyrańska & Sylwia Wiśniewska, 2019, "Bipartite Competency Schemas on Polish Labor Market," Central European Business Review, Prague University of Economics and Business, volume 2019, issue 4, pages 1-25, DOI: 10.18267/j.cebr.222.
• Pavel Jasek & Lenka Vrana & Lucie Sperkova & Zdenek Smutny & Marek Kobulsky, 2019, "Predictive Performance of Customer Lifetime Value Models in E-Commerce and the Use of Non-Financial Data," Prague Economic Papers, Prague University of Economics and Business, volume 2019, issue 6, pages 648-669, DOI: 10.18267/j.pep.714.
• Fernando Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019, "Are Small Farms Really more Productive than Large Farms?," 2019 Meeting Papers, Society for Economic Dynamics, number 1230.
• Gerhard Längst & Jürgen Elsner & Anastasia Berzhanin, 2019, "Data Quality Imperatives for Data Migration Initiatives: A Guide for Data Practicioners," Journal of Financial Transformation, Capco Institute, volume 50, pages 118-125.
• Michael Pfarrhofer, 2019, "Measuring international uncertainty using global vector autoregressions with drifting parameters," Working Papers in Economics, University of Salzburg, number 2019-3, Aug.
• Liangjun Su & Ke Miao & Sainan Jin, 2019, "On Factor Models with Random Missing: EM Estimation, Inference, and Cross Validation," Economics and Statistics Working Papers, Singapore Management University, School of Economics, number 4-2019, Jan.
• Syed Badruddoza & Modhurima Amin & Jill McCluskey, 2019, "Assessing the Importance of an Attribute in a Demand SystemStructural Model versus Machine Learning," Working Papers, School of Economic Sciences, Washington State University, number 2019-5, Dec.
• Paolo Andreini & Donato Ceci, 2019, "A Horse Race in High Dimensional Space," CEIS Research Paper, Tor Vergata University, CEIS, number 452, Feb, revised 14 Feb 2019.
• Massimo Franchi & Paolo Paruolo, 2019, "Cointegration, root functions and minimal bases," DSS Empirical Economics and Econometrics Working Papers Series, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome, number 2019/2, Dec.
• Fernando Aragon, Diego Restuccia, Juan Pablo Rud & Diego Restuccia & Juan Pablo Rud, 2019, "Are small farms really more productive than large farms?," Discussion Papers, Department of Economics, Simon Fraser University, number dp19-05, Sep.
• Benjamin Anderegg & Didier Sornette & Florian Ulmann, 2019, "Quantification of feedback effects in FX options markets," Working Papers, Swiss National Bank, number 2019-03.
• Yoshiaki Ogura & Ryo Okui & Yukiko Umeno Saito, 2019, "Network-motivated Lending Decisions: A Rationale for Forbearance," Working Paper Series, Institute of Economic Research, Seoul National University, number no127, Oct.
• James P. LeSage & Daniel Hendrikz, 2019, "Large Bayesian vector autoregressive forecasting for regions: A comparison of methods based on alternative disturbance structures," The Annals of Regional Science, Springer;Western Regional Science Association, volume 62, issue 3, pages 563-599, June, DOI: 10.1007/s00168-019-00908-z.
• Petra Burdejová & Wolfgang K. Härdle, 2019, "Dynamic semi-parametric factor model for functional expectiles," Computational Statistics, Springer, volume 34, issue 2, pages 489-502, June, DOI: 10.1007/s00180-019-00883-1.
• Peter N. Posch & Daniel Ullmann & Dominik Wied, 2019, "Detecting structural changes in large portfolios," Empirical Economics, Springer, volume 56, issue 4, pages 1341-1357, April, DOI: 10.1007/s00181-017-1392-5.
• Qing Wang & Dan Zhao, 2019, "Penalization methods with group-wise sparsity: econometric applications to eBay Motors online auctions," Empirical Economics, Springer, volume 57, issue 2, pages 683-704, August, DOI: 10.1007/s00181-018-1460-5.
• Ard Reijer & Andreas Johansson, 2019, "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, volume 57, issue 4, pages 1351-1373, October, DOI: 10.1007/s00181-018-1500-1.
• Tomáš Gajdošík, 2019, "Big Data Analytics in Smart Tourism Destinations. A New Tool for Destination Management Organizations?," Springer Proceedings in Business and Economics, Springer, chapter 0, in: Vicky Katsoni & Marival Segarra-Oña, "Smart Tourism as a Driver for Culture and Sustainability", DOI: 10.1007/978-3-030-03910-3_2.
• Athanasios Koutras & Ioannis A. Nikas & Alkiviadis Panagopoulos, 2019, "Towards Developing Smart Cities: Evidence from GIS Analysis on Tourists’ Behavior Using Social Network Data in the City of Athens," Springer Proceedings in Business and Economics, Springer, chapter 0, in: Vicky Katsoni & Marival Segarra-Oña, "Smart Tourism as a Driver for Culture and Sustainability", DOI: 10.1007/978-3-030-03910-3_28.
• Daria Maltseva & Vladimir Batagelj, 2019, "Social network analysis as a field of invasions: bibliographic approach to study SNA development," Scientometrics, Springer;Akadémiai Kiadó, volume 121, issue 2, pages 1085-1128, November, DOI: 10.1007/s11192-019-03193-x.
• Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019, "Effectiveness of policy and regulation in European sovereign credit risk markets: a network analysis," ESRB Working Paper Series, European Systemic Risk Board, number 90, Mar.
• Randolph Luca Bruno & Elodie Douarin & Julia Korosteleva & Slavo Radosevic, 2019, "Determinants of Productivity Gap in the European Union: A Multilevel Perspective," LEM Papers Series, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy, number 2019/25, Aug.
• Rachida Ouysse, 2019, "Constrained principal components estimation of large approximate factor models," Discussion Papers, School of Economics, The University of New South Wales, number 2017-12a, Dec.
• Chloé van Biljon & Cobus Burger, 2019, "The period effect: the effect of menstruation on absenteeism of school girls in Limpopo," Working Papers, Stellenbosch University, Department of Economics, number 20/2019.
• Simon Beyeler & Sylvia Kaufmann, 2019, "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers, Swiss National Bank, Study Center Gerzensee, number 16.08R, Mar.
• Massimo Franchi & Paolo Paruolo, 2019, "A general inversion theorem for cointegration," Econometric Reviews, Taylor & Francis Journals, volume 38, issue 10, pages 1176-1201, November, DOI: 10.1080/07474938.2018.1536100.
• Yacine Aït-Sahalia & Dacheng Xiu, 2019, "Principal Component Analysis of High-Frequency Data," Journal of the American Statistical Association, Taylor & Francis Journals, volume 114, issue 525, pages 287-303, January, DOI: 10.1080/01621459.2017.1401542.
• Matias Quiroz & Robert Kohn & Mattias Villani & Minh-Ngoc Tran, 2019, "Speeding Up MCMC by Efficient Data Subsampling," Journal of the American Statistical Association, Taylor & Francis Journals, volume 114, issue 526, pages 831-843, April, DOI: 10.1080/01621459.2018.1448827.
• Alexander N. Bogin & William M. Doerner, 2019, "Property Renovations and Their Impact on House Price Index Construction," Journal of Real Estate Research, Taylor & Francis Journals, volume 41, issue 2, pages 249-284, April, DOI: 10.1080/10835547.2019.12091526.
• Prüfer, Jens & Prüfer, Patricia, 2019, "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Discussion Paper, Tilburg University, Center for Economic Research, number 2019-005.
• Prüfer, Jens & Prüfer, Patricia, 2019, "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Other publications TiSEM, Tilburg University, School of Economics and Management, number 83a4ca9e-c0cd-4786-ac8c-9.
• Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2019, "Are Small Farms Really more Productive than Large Farms?," Working Papers, University of Toronto, Department of Economics, number tecipa-647, Sep.
• Gabriela Mordecki & Ronald Miranda, 2019, "Real Exchange Rate Volatility and Exports: A Study for Four Selected Commodity Exporting Countries," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, volume 66, issue 4, pages 411-437.
• Chiara Elena Dalla & Menon Martina & Perali Federico, 2019, "An Integrated Database to Measure Living Standards," Journal of Official Statistics, Sciendo, volume 35, issue 3, pages 531-576, September, DOI: 10.2478/jos-2019-0023.
• Koen Jochmans & Martin Weidner, 2019, "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, volume 87, issue 5, pages 1543-1560, September, DOI: 10.3982/ECTA14605.
• Timo Bettendorf, 2019, "Spillover effects of credit default risk in the euro area and the effects on the Euro: A GVAR approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., volume 24, issue 1, pages 296-312, January, DOI: 10.1002/ijfe.1663.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019, "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 34, issue 7, pages 1027-1049, November, DOI: 10.1002/jae.2722.
• Hauber, Philipp & Schumacher, Christian & Zhang, Jiachun, 2019, "A flexible state-space model with lagged states and lagged dependent variables: Simulation smoothing," Discussion Papers, Deutsche Bundesbank, number 15/2019.
• Krstić, Živko & Seljan, Sanja & Zoroja, Jovana, 2019, "Visualization of Big Data Text Analytics in Financial Industry: A Case Study of Topic Extraction for Italian Banks," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2019), Rovinj, Croatia, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019".
• Dragota, Victor & Pele, Daniel Traian & Yaseen, Hanaan, 2019, "Dividend payout ratio follows a Tweedie distribution: International evidence," Economics Discussion Papers, Kiel Institute for the World Economy, number 2019-41.
• Doanh Khanh Nguyen & Van Ngoc Thi Pham & Heo, Yoon, 2019, "Impact of institutional and cultural distance on ASEAN's trade efficiency," Economics Discussion Papers, Kiel Institute for the World Economy, number 2019-57.
• Dragotă, Victor & Pele, Daniel Traian & Yaseen, Hanaan, 2019, "Dividend payout ratio follows a Tweedie distribution: International evidence," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy, volume 13, pages 1-35, DOI: 10.5018/economics-ejournal.ja.2019-.
• Hinz, Julian & Stammann, Amrei & Wanner, Joschka, 2019, "Persistent zeros: The extensive margin of trade," Kiel Working Papers, Kiel Institute for the World Economy, number 2139.
• Härdle, Wolfgang Karl & Schulz, Rainer & Xie, Taojun, 2019, "Cooling Measures and Housing Wealth: Evidence from Singapore," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-001.
• Qian, Ya & Tu, Jun & Härdle, Wolfgang Karl, 2019, "Information Arrival, News Sentiment, Volatilities and Jumps of Intraday Returns," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-002.
• Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019, "Effectiveness of policy and regulation in European sovereign credit risk markets: A network analysis," Working Paper Series in Economics, Karlsruhe Institute of Technology (KIT), Department of Economics and Management, number 125, DOI: 10.5445/IR/1000092476.
• Bertsche, Dominik & Brüggemann, Ralf & Kascha, Christian, 2019, "Directed Graph and Variable Selection in Large Vector Autoregressive Models," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy, Verein für Socialpolitik / German Economic Association, number 203656.

2018

• Ogerta Elezaj & Dhimitri Tole, 2018, "Big Data: Potential, Challenges, And Implications In Official Statistics," CBU International Conference Proceedings, ISE Research Institute, volume 6, issue 0, pages 95-99, September, DOI: 10.12955/cbup.v6.1139.
• Riccardo Borghi & Eric Hillebrand & Jakob Mikkelsen & Giovanni Urga, 2018, "The dynamics of factor loadings in the cross-section of returns," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2018-38, Dec.
• Djogbenou, Antoine A., 2018, "Comovements in the Real Activity of Developed and Emerging Economies: A Test of Global versus Specific International Factors," Queen's Economics Department Working Papers, Queen's University - Department of Economics, number 274718, Apr, DOI: 10.22004/ag.econ.274718.
• Rui Pedro Brito & Helder Sebastião & Pedro Godinho, 2018, "On the Gains of Using High Frequency Data in Portfolio Selection," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, volume 65, issue 4, pages 365-383, December.
• Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018, "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers, Aix-Marseille School of Economics, France, number 1844, Dec.
• Jan Vavřina & Lubor Lacina, 2018, "Profitability of foodstuff processing companies in V4 countries during the 2008-2012 economic crisis," Society and Economy, Akadémiai Kiadó, Hungary, volume 40, issue 2, pages 245-270, June.
• Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018, "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, volume 10, issue 1, pages 615-643, August, DOI: 10.1146/annurev-economics-080217-05.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018, "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 201801, Jan, revised Jan 2018.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018, "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 201803, Apr, revised Jun 2018.
• Christoph Breunig & Enno Mammen & Anna Simoni, 2018, "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers, arXiv.org, number 1806.00666, Jun, revised Aug 2020.
• Zhan Gao & Zhentao Shi, 2018, "Implementing Convex Optimization in R: Two Econometric Examples," Papers, arXiv.org, number 1806.10423, Jun, revised Aug 2019.
• Matthew Harding & Carlos Lamarche, 2018, "A Panel Quantile Approach to Attrition Bias in Big Data: Evidence from a Randomized Experiment," Papers, arXiv.org, number 1808.03364, Aug.
• Stephan Smeekes & Etienne Wijler, 2018, "An Automated Approach Towards Sparse Single-Equation Cointegration Modelling," Papers, arXiv.org, number 1809.08889, Sep, revised Jul 2020.
• Eoghan O'Neill & Melvyn Weeks, 2018, "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Papers, arXiv.org, number 1810.09179, Oct, revised Oct 2019.
• Harold D. Chiang, 2018, "Many Average Partial Effects: with An Application to Text Regression," Papers, arXiv.org, number 1812.09397, Dec, revised Jan 2022.
• Emilia VASILE & Danut-Octavian SIMION & George CALOTA, 2018, "Propositional calculation for expert systems in economics," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 50, issue 2, pages 9-19, June.
• Danut-Octavian SIMION & Emilia VASILE, 2018, "Usage of informational systems in economic applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 51, issue 3, pages 9-23, September.
• Emilia VASILE, 2018, "The Strategy Of Improving Informational Systems Through Economic Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 52, issue 4, pages 9-21, December.
• Dario Buono & George Kapetanios & Massimiliano Marcellino & Gianluigi Mazzi & Fotis Papailias, 2018, "Big Data Econometrics: Now Casting and Early Estimates," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 1882.
• Heather L.R. Tierney & Jiyoon Kim & Zafar Nazarov, 2018, "The Effects of Temporal Aggregation on Search Engine Data," Review of Economics & Finance, Better Advances Press, Canada, volume 12, pages 57-71, May.
• Hicham Ganga & Javier Alonso & Vincenzo Spiezia & Jan Tscheke, 2018, "Patterns of domestic and cross-border e-commerce in Spain: A gravitational model approach," Working Papers, BBVA Bank, Economic Research Department, number 18/18, Dec.
• Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2018, "Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?," Staff Working Papers, Bank of Canada, number 18-12, DOI: 10.34989/swp-2018-12.
• Narayan Bulusu & Pierre Guérin, 2018, "What Drives Interbank Loans? Evidence from Canada," Staff Working Papers, Bank of Canada, number 18-5, DOI: 10.34989/swp-2018-5.
• Sandra García-Uribe, 2018, "Multidimensional media slant: complementarities in news reporting by US newspapers," Working Papers, Banco de España, number 1817, Jun.
• Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018, "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, volume 56, issue 1, pages 114-137, January, DOI: 10.1111/ecin.12364.
• José M. Cordero & Víctor Cristóbal & Daniel Santín, 2018, "Causal Inference On Education Policies: A Survey Of Empirical Studies Using Pisa, Timss And Pirls," Journal of Economic Surveys, Wiley Blackwell, volume 32, issue 3, pages 878-915, July, DOI: 10.1111/joes.12217.
• Vegard H. Larsen & Leif Anders Thorsrud, 2018, "Business cycle narratives," Working Paper, Norges Bank, number 2018/3, Feb.
• Shakeeb Khan & Denis Nekipelov & Justin Rao, 2018, "Measuring the Return to Online Advertising: Estimation and Inference of Endogenous Treatment Effects," Boston College Working Papers in Economics, Boston College Department of Economics, number 946, Feb.
• Matei Demetrescu & Sinem Hacioglu Hoke, 2018, "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers, Bank of England, number 723, May.
• Arthur Turrell & Bradley Speigner & Jyldyz Djumalieva & David Copple & James Thurgood, 2018, "Using job vacancies to understand the effects of labour market mismatch on UK output and productivity," Bank of England working papers, Bank of England, number 737, Jul.
• Arthur Turrell & James Thurgood & Jyldyz Djumalieva & David Copple & Bradley Speigner, 2018, "Using online job vacancies to understand the UK labour market from the bottom-up," Bank of England working papers, Bank of England, number 742, Jul.
• Vladimir Lazarov & Marc Hinterschweiger, 2018, "Determinants of distress in the UK owner-occupier and buy-to-let mortgage markets," Bank of England working papers, Bank of England, number 760, Oct.
• Nikoleta Anesti & Ana Galvão & Silvia Miranda-Agrippino, 2018, "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers, Bank of England, number 764, Nov.
• Wucherpfennig, Julian & Kachi, Aya & Bormann, Nils-Christian & Hunziker, Philipp, 2018, "Estimating Interdependence Across Space, Time and Outcomes in Binary Choice Models Using Pseudo Maximum Likelihood Estimators," Working papers, Faculty of Business and Economics - University of Basel, number 2018/11.
• Anna Gloria Billé & Leopoldo Catania, 2018, "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen, number BEMPS55, Sep.
• Guo, P. & Lam, J. & Li, V., 2018, "A novel machine learning approach for identifying the drivers of domestic electricity users’ price responsiveness," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 1844, Aug.
• O'Neill, E. & Weeks, M., 2018, "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 1865, Oct.
• Hafner, C. & Linton, O. & Tang, H., 2018, "Estimation of a Multiplicative Correlation Structure in the Large Dimensional Case," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 1878, Sep.
• George Kapetanios & M. Hashem Pesaran & Simon Reese, 2018, "A Residual-based Threshold Method for Detection of Units that are Too Big to Fail in Large Factor Models," CESifo Working Paper Series, CESifo, number 7401.
• Magnus Reif, 2018, "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 265.
• Markus Heinrich & Magnus Reif, 2018, "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 273.
• Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018, "Uncertain Kingdom: Nowcasting GDP and its Revisions," Discussion Papers, Centre for Macroeconomics (CFM), number 1824, Aug.
• Dhruv Grover & Sebastian Bauhoff & Jed Friedman, 2018, "Using Supervised Learning to Select Audit Targets in Performance-Based Financing in Health: An Example from Zambia," Working Papers, Center for Global Development, number 481, Apr.
• J-C Gerlach & Guilherme Demos & Didier Sornette, 2018, "Dissection of Bitcoin's Multiscale Bubble History," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 18-30, Apr.
• Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018, "Empirical Asset Pricing via Machine Learning," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 18-71, Nov.
• Ricardo Hausmann & Julian Hinz & Muhammed A. Yildirim, 2018, "Measuring Venezuelan Emigration with Twitter," CID Working Papers, Center for International Development at Harvard University, number 342, May.
• Martin Gurtler, 2018, "What Influences Private Investment? The Case of the Czech Republic," Working Papers, Czech National Bank, Research and Statistics Department, number 2018/14, Dec.
• J Gallego & G Rivero & J.D. MartÔøΩnez, 2018, "Preventing rather than Punishing: An Early Warning Model of Malfeasance in Public Procurement," Documentos de Trabajo, Universidad del Rosario, number 16724, Sep.
• Eduardo Rosas Rojas & M�nica C. Mimbrera Delgado, 2018, "Inflación y volatilidad cambiaria en México (1969-2017)," Ensayos de Economía, Universidad Nacional de Colombia Sede Medellín, number 17297, Jul.
• Henry Sebastián Rangel Quinonez & Gabriel Y��ez Canal, 2018, "Clasificación por capitales de una muestra de microempresarios del Área Metropolitana de Bucaramanga a partir del Análisis de Correspondencia Múltiple," Ensayos de Economía, Universidad Nacional de Colombia Sede Medellín, number 17302, Jul.
• Eduardo Rosas Rojas & Teresa L�pez Gonz�lez, 2018, "Inflación e incertidumbre inflacionaria: la postura del Banco de México, 1969-2017," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, volume 10, issue 2, pages 349-372.
• WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018, "Network constrained covariate coefficient and connection sign estimation," LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE), number 2018018, Jun.
• Giannone, Domenico & Tambalotti, Andrea & Sbordone, Argia & Bok, Brandyn & Caratelli, Daniele, 2018, "Macroeconomic Nowcasting and Forecasting with Big Data," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 12589, Jan.
• Gonzalo Villa-Cox & Everardo Quezada & Joseph Aguilar-Bohorquez & Ivanna Valverde-Bajana & Paul Vera-Gilces, 2018, "Diseño experimental para la entrada de una firma en un mercado monopolístico con efectos de red: caso de estudio con estudiantes de pregrado en un rol empresarial," Cuadernos de Economía - Spanish Journal of Economics and Finance, Asociación Cuadernos de Economía, volume 41, issue 115, pages 130-139, Enero.
• Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2018, "Modelling And Estimating Individual And Firm Effects With Count Panel Data," ASTIN Bulletin, Cambridge University Press, volume 48, issue 3, pages 1049-1078, September.
• Bruce Headey & Gert G. Wagner, 2018, "Alternative Values-Based ‘Recipes’ for Life Satisfaction: German Results with an Australian Replication," SOEPpapers on Multidisciplinary Panel Data Research, DIW Berlin, The German Socio-Economic Panel (SOEP), number 982.
• Maximilian Schäfer & Geza Sapi & Szabolcs Lorincz, 2018, "The Effect of Big Data on Recommendation Quality: The Example of Internet Search," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1730.
• Fornaro, Paolo & Luomaranta, Henri, 2018, "Aggregate fluctuations and the effect of large corporations: Evidence from Finnish monthly data," Economic Modelling, Elsevier, volume 70, issue C, pages 245-258, DOI: 10.1016/j.econmod.2017.11.012.
• Jones, Benjamin A., 2018, "Forest-attacking Invasive Species and Infant Health: Evidence From the Invasive Emerald Ash Borer," Ecological Economics, Elsevier, volume 154, issue C, pages 282-293, DOI: 10.1016/j.ecolecon.2018.08.010.
• Xiang, Jingjie & Li, Kunpeng & Cui, Guowei, 2018, "A note on the asymptotic properties of least squares estimation in high dimensional constrained factor models," Economics Letters, Elsevier, volume 171, issue C, pages 144-148, DOI: 10.1016/j.econlet.2018.07.029.
• Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018, "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, volume 204, issue 1, pages 54-65, DOI: 10.1016/j.jeconom.2018.01.002.
• Corradi, Valentina & Silvapulle, Mervyn J. & Swanson, Norman R., 2018, "Testing for jumps and jump intensity path dependence," Journal of Econometrics, Elsevier, volume 204, issue 2, pages 248-267, DOI: 10.1016/j.jeconom.2018.02.004.
• Lam, Clifford & Feng, Phoenix, 2018, "A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data," Journal of Econometrics, Elsevier, volume 206, issue 1, pages 226-257, DOI: 10.1016/j.jeconom.2018.06.001.
• Chen, Le-Yu & Lee, Sokbae, 2018, "Best subset binary prediction," Journal of Econometrics, Elsevier, volume 206, issue 1, pages 39-56, DOI: 10.1016/j.jeconom.2018.05.001.
• Jåstad, Eirik Ogner & Mustapha, Walid Fayez & Bolkesjø, Torjus Folsland & Trømborg, Erik & Solberg, Birger, 2018, "Modelling of uncertainty in the economic development of the Norwegian forest sector," Journal of Forest Economics, Elsevier, volume 32, issue C, pages 106-115, DOI: 10.1016/j.jfe.2018.04.005.
• Hofmarcher, Paul & Crespo Cuaresma, Jesus & Grün, Bettina & Humer, Stefan & Moser, Mathias, 2018, "Bivariate jointness measures in Bayesian Model Averaging: Solving the conundrum," Journal of Macroeconomics, Elsevier, volume 57, issue C, pages 150-165, DOI: 10.1016/j.jmacro.2018.05.005.
• Kareem, Olayinka Idowu, 2018, "The determinants of large-scale land investments in Africa," Land Use Policy, Elsevier, volume 75, issue C, pages 180-190, DOI: 10.1016/j.landusepol.2018.03.039.
• Whitaker, Stephan D., 2018, "Big Data versus a survey," The Quarterly Review of Economics and Finance, Elsevier, volume 67, issue C, pages 285-296, DOI: 10.1016/j.qref.2017.07.011.
• Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018, "Nowcasting New Zealand GDP Using Machine Learning Algorithms," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2018-47, Sep.
• Brian Micallef, 2018, "Constructing an index to examine house price misalignment with fundamentals in Malta," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, volume 11, issue 2, pages 315-334, January, DOI: 10.1108/IJHMA-11-2017-0099.
• Franses, Ph.H.B.F. & Wiemann, T., 2018, "Intertemporal Similarity of Economic Time Series," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI2018-30, Aug.
• Peiyang Guo & Jacqueline CK Lam & Victor OK Li, 2018, "A novel machine learning approach for identifying the drivers of domestic electricity users' price responsiveness," Working Papers, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge, number EPRG 1824, Aug.
• Jan Janku & Zuzana Kucerova, 2018, "Successful Crowdfunding Campaigns: The Role of Project Specifics, Competition and Founders’ Experience," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, volume 68, issue 4, pages 351-373, September.
• Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018, "On the robustness of the principal volatility components," Textos para discussão, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil), number 474, Mar.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018, "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1803, Mar, DOI: 10.26509/frbc-wp-201803.
• Jack DeWaard & Janna Johnson & Stephan D. Whitaker, 2018, "Internal Migration in the United States: A Comparative Assessment of the Utility of the Consumer Credit Panel," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1804, Mar, DOI: 10.26509/frbc-wp-201804.
• Christopher L. Foote & Lara Loewenstein & Paul S. Willen, 2018, "Technological Innovation in Mortgage Underwriting and the Growth in Credit: 1985-2015," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1816, Dec, DOI: 10.26509/frbc-wp-201816.
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz & Tyler Radler, 2018, "Using Payroll Processor Microdata to Measure Aggregate Labor Market Activity," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2018-005, Jan, DOI: 10.17016/FEDS.2018.005.
• Gregory J. Cohen & Melanie Friedrichs & Kamran Gupta & William Hayes & Seung Jung Lee & W. Blake Marsh & Nathan Mislang & Maya Shaton & Martin Sicilian, 2018, "The U.S. Syndicated Loan Market : Matching Data," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2018-085, Dec, DOI: 10.17016/FEDS.2018.085.
• Gregory J. Cohen & Melanie Friedrichs & Kamran Gupta & William Hayes & Seung Jung Lee & W. Blake Marsh & Nathan Mislang & Maya Shaton & Martin Sicilian, 2018, "The U.S. Syndicated Loan Market: Matching Data," Research Working Paper, Federal Reserve Bank of Kansas City, number RWP 18-9, Dec, DOI: 10.18651/RWP2018-09.
• Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018, "Economic predictions with big data: the illusion of sparsity," Staff Reports, Federal Reserve Bank of New York, number 847, Apr.
• Niels Framroze Møller & Laura Mørch Andersen & Lars Gårn Hansen & Carsten Lynge Jensen, 2018, "Can pecuniary and environmental incentives via SMS messaging make households adjust their intra-day electricity demand to a fluctuating production?," IFRO Working Paper, University of Copenhagen, Department of Food and Resource Economics, number 2018/06, May.
• Ricardo Hausmann & Julian Hinz & Muhammed A. Yildirim, 2018, "Measuring Venezuelan Emigration with Twitter," Growth Lab Working Papers, Harvard's Growth Lab, number 113, May.
• Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018, "Generating univariate fractional integration within a large VAR(1)," Post-Print, HAL, number hal-01980783, DOI: 10.1016/j.jeconom.2018.01.002.