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Title
Cited by
Cited by
Year
Identification of causal effects using instrumental variables
JD Angrist, GW Imbens, DB Rubin
Journal of the American statistical Association 91 (434), 444-455, 1996
82061996
Identification and estimation of local average treatment effects
J Angrist, G Imbens
National Bureau of Economic Research, 1995
69461995
Recent developments in the econometrics of program evaluation
GW Imbens, JM Wooldridge
Journal of economic literature 47 (1), 5-86, 2009
68822009
Causal inference in statistics, social, and biomedical sciences
GW Imbens, DB Rubin
Cambridge university press, 2015
67292015
Regression discontinuity designs: A guide to practice
GW Imbens, T Lemieux
Journal of econometrics 142 (2), 615-635, 2008
58072008
Nonparametric estimation of average treatment effects under exogeneity: A review
GW Imbens
Review of Economics and statistics 86 (1), 4-29, 2004
43722004
Large sample properties of matching estimators for average treatment effects
A Abadie, GW Imbens
econometrica 74 (1), 235-267, 2006
37392006
Efficient estimation of average treatment effects using the estimated propensity score
K Hirano, GW Imbens, G Ridder
Econometrica 71 (4), 1161-1189, 2003
34712003
Optimal bandwidth choice for the regression discontinuity estimator
G Imbens, K Kalyanaraman
The Review of economic studies 79 (3), 933-959, 2012
34132012
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
33952023
Redefine statistical significance
DJ Benjamin, JO Berger, M Johannesson, BA Nosek, EJ Wagenmakers, ...
Nature human behaviour 2 (1), 6-10, 2018
30002018
Bias-corrected matching estimators for average treatment effects
A Abadie, GW Imbens
Journal of Business & Economic Statistics 29 (1), 1-11, 2011
2737*2011
The role of the propensity score in estimating dose-response functions
GW Imbens
Biometrika 87 (3), 706-710, 2000
24592000
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
22462019
Recursive partitioning for heterogeneous causal effects
S Athey, G Imbens
Proceedings of the National Academy of Sciences 113 (27), 7353-7360, 2016
21592016
The state of applied econometrics: Causality and policy evaluation
S Athey, GW Imbens
Journal of Economic perspectives 31 (2), 3-32, 2017
18302017
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
17771995
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
17752004
Identification and inference in nonlinear difference‐in‐differences models
S Athey, GW Imbens
Econometrica 74 (2), 431-497, 2006
17372006
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
15052001
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Articles 1–20