Machine Learning: An Applied Econometric Approach
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Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:
- Sam Watson’s journal round-up for 12th June 2017
by Sam Watson in The Academic Health Economists' Blog on 2017-06-12 16:00:00
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Isil Erel & Léa H. Stern & Chenhao Tan & Michael S. Weisbach, 2018. "Selecting Directors Using Machine Learning," NBER Working Papers 24435, National Bureau of Economic Research, Inc.
- Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
- Lionel Roger, 2018. "Blinded by the light? Heterogeneity in the luminosity-growth nexus and the African growth miracle," Discussion Papers 2018-04, University of Nottingham, CREDIT.
- Michael Knaus & Michael Lechner & Anthony Strittmatter, 2017.
"Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach,"
1709.10279, arXiv.org, revised May 2018.
- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," Economics Working Paper Series 1711, University of St. Gallen, School of Economics and Political Science.
- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," CEPR Discussion Papers 12224, C.E.P.R. Discussion Papers.
- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," IZA Discussion Papers 10961, Institute for the Study of Labor (IZA).
- repec:kap:poprpr:v:37:y:2018:i:1:d:10.1007_s11113-017-9450-4 is not listed on IDEAS
- Jens Ludwig & Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning Tests for Effects on Multiple Outcomes," Papers 1707.01473, arXiv.org.
- Paolo Brunori & Paul Hufe & Daniel Gerszon Mahler, 2017.
"The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees,"
Working Papers - Economics
wp2017_18.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
- Brunori,Paolo & Hufe,Paul & Mahler,Daniel Gerszon, 2018. "The roots of inequality : estimating inequality of opportunity from regression trees," Policy Research Working Paper Series 8349, The World Bank.
- Paolo Brunori & Paul Hufe & Gerszon Daniel Mahler, 2018. "The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees," ifo Working Paper Series 252, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
- Carlos León & Fabio Ortega, 2018. "Nowcasting economic activity with electronic payments data: A predictive modeling approach," Borradores de Economia 1037, Banco de la Republica de Colombia.
- Andersson, Tommy & Ehlers, Lars & Martinello, Alessandro, 2018. "Dynamic Refugee Matching," Working Papers 2018:7, Lund University, Department of Economics.
- repec:nbr:nberch:14009 is not listed on IDEAS
- Fritz Schiltz & Chiara Masci & Tommaso Agasisti & Daniel Horn, 2017. "Using Machine Learning To Model Interaction Effects In Education: A Graphical Approach," Budapest Working Papers on the Labour Market 1704, Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences.
- John Gathergood & Neale Mahoney & Neil Stewart & Joerg Weber, 2017. "How Do Individuals Repay Their Debt? The Balance-Matching Heuristic," NBER Working Papers 24161, National Bureau of Economic Research, Inc.
- Monica Andini & Emanuele Ciani & Guido de Blasio & Alessio D'Ignazio & Viola Salvestrini, 2017. "Targeting policy-compliers with machine learning: an application to a tax rebate programme in Italy," Temi di discussione (Economic working papers) 1158, Bank of Italy, Economic Research and International Relations Area.
- Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018. "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers 9/2018, Bank of Finland, Institute for Economies in Transition.
- repec:bis:bisifc:46-26 is not listed on IDEAS
- Ajay Agrawal & John McHale & Alexander Oettl, 2018.
"Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth,"
NBER Chapters,in: The Economics of Artificial Intelligence: An Agenda
National Bureau of Economic Research, Inc.
- Ajay Agrawal & John McHale & Alex Oettl, 2018. "Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth," NBER Working Papers 24541, National Bureau of Economic Research, Inc.
- 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 18-12, Bank of Canada.
- Potnuru Kishen Suraj & Ankesh Gupta & Makkunda Sharma & Sourabh Bikash Paul & Subhashis Banerjee, 2017. "On monitoring development using high resolution satellite images," Papers 1712.02282, arXiv.org, revised Dec 2017.
More about this item
- C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
- C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
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