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Susan AtheyThe Economics of Technology Professor, Stanford University Graduate School of BusinessPatvirtintas el. paštas stanford.edu
Josh AngristMITPatvirtintas el. paštas mit.edu
Alberto AbadieProfessor of Economics, MITPatvirtintas el. paštas mit.edu
Donald B RubinYCMS Tsinghua; Senior Research Fellow at Fox / Temple U, Emeritus at Harvard UPatvirtintas el. paštas temple.edu
Jeffrey M. WooldridgeUniversity Distinguished Professor of Economics, Michigan State UniversityPatvirtintas el. paštas msu.edu
V. Joseph HotzDuke UniversityPatvirtintas el. paštas econ.duke.edu
Keisuke HiranoProfessor of Economics, Pennsylvania State UniversityPatvirtintas el. paštas psu.edu
Stefan WagerGraduate School of Business, Stanford UniversityPatvirtintas el. paštas stanford.edu
Thomas LemieuxProfessor of Economics, University of British ColumbiaPatvirtintas el. paštas ubc.ca
Whitney NeweyProfessor of Economics, MITPatvirtintas el. paštas mit.edu
Richard K. CrumpFederal Reserve Bank of New YorkPatvirtintas el. paštas ny.frb.org
Andrew GelmanProfessor of Statistics and Political Science, Columbia UniversityPatvirtintas el. paštas stat.columbia.edu
Michal KolesárPrinceton UniversityPatvirtintas el. paštas princeton.edu
David M. DrukkerSam Houston State UniversityPatvirtintas el. paštas shsu.edu
Bryan S GrahamProfessor of Economics, University of California - BerkeleyPatvirtintas el. paštas econ.berkeley.edu
Richard SpadyResearch Professor of Economics, Johns Hopkins UniversityPatvirtintas el. paštas jhu.edu
Bruce SacerdoteDartmouth CollegePatvirtintas el. paštas dartmouth.edu
Paul Goldsmith-PinkhamYale School of ManagementPatvirtintas el. paštas yale.edu
Alan KruegerPrinceton UniversityPatvirtintas el. paštas princeton.edu

Stebėti

guido imbens

Stanford University

Patvirtintas el. paštas stanford.edu

causal inference econometrics


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Identification of causal effects using instrumental variables JD Angrist, GW Imbens, DB Rubin Journal of the American statistical Association 91 (434), 444-455, 1996	8230	1996
Identification and estimation of local average treatment effects J Angrist, G Imbens National Bureau of Economic Research, 1995	6961	1995
Recent developments in the econometrics of program evaluation GW Imbens, JM Wooldridge Journal of economic literature 47 (1), 5-86, 2009	6880	2009
Causal inference in statistics, social, and biomedical sciences GW Imbens, DB Rubin Cambridge university press, 2015	6828	2015
Regression discontinuity designs: A guide to practice GW Imbens, T Lemieux Journal of econometrics 142 (2), 615-635, 2008	5798	2008
Nonparametric estimation of average treatment effects under exogeneity: A review GW Imbens Review of Economics and statistics 86 (1), 4-29, 2004	4367	2004
Large sample properties of matching estimators for average treatment effects A Abadie, GW Imbens econometrica 74 (1), 235-267, 2006	3739	2006
Efficient estimation of average treatment effects using the estimated propensity score K Hirano, GW Imbens, G Ridder Econometrica 71 (4), 1161-1189, 2003	3477	2003
When should you adjust standard errors for clustering? A Abadie, S Athey, GW Imbens, JM Wooldridge The Quarterly Journal of Economics 138 (1), 1-35, 2023	3454	2023
Optimal bandwidth choice for the regression discontinuity estimator G Imbens, K Kalyanaraman The Review of economic studies 79 (3), 933-959, 2012	3417	2012
Redefine statistical significance DJ Benjamin, JO Berger, M Johannesson, BA Nosek, EJ Wagenmakers, ... Nature human behaviour 2 (1), 6-10, 2018	3059	2018
Bias-corrected matching estimators for average treatment effects A Abadie, GW Imbens Journal of Business & Economic Statistics 29 (1), 1-11, 2011	2582*	2011
The role of the propensity score in estimating dose-response functions GW Imbens Biometrika 87 (3), 706-710, 2000	2459	2000
Why high-order polynomials should not be used in regression discontinuity designs A Gelman, G Imbens Journal of Business & Economic Statistics 37 (3), 447-456, 2019	2245	2019
Recursive partitioning for heterogeneous causal effects S Athey, G Imbens Proceedings of the National Academy of Sciences 113 (27), 7353-7360, 2016	2189	2016
The state of applied econometrics: Causality and policy evaluation S Athey, GW Imbens Journal of Economic perspectives 31 (2), 3-32, 2017	1840	2017
Two-stage least squares estimation of average causal effects in models with variable treatment intensity JD Angrist, GW Imbens Journal of the American statistical Association 90 (430), 431-442, 1995	1788	1995
Implementing matching estimators for average treatment effects in Stata A Abadie, D Drukker, JL Herr, GW Imbens The stata journal 4 (3), 290-311, 2004	1758	2004
Identification and inference in nonlinear difference‐in‐differences models S Athey, GW Imbens Econometrica 74 (2), 431-497, 2006	1744	2006
Estimation of causal effects using propensity score weighting: An application to data on right heart catheterization K Hirano, GW Imbens Health Services and Outcomes research methodology 2, 259-278, 2001	1501	2001

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