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Economics and Finance
USA
2026

D-Index & Metrics

Economics and Finance

D-Index
101
Citations
106713
World Ranking
97
National Ranking
76

Research.com Recognitions

  • 2026 - Research.com Economics and Finance in United States Leader Award
  • 2025 - Research.com Economics and Finance in United States Leader Award
  • 2024 - Research.com Economics and Finance in United States Leader Award
  • 2020 - Fellow of the American Statistical Association (ASA)
  • 2017 - Royal Netherlands Academy of Arts and Sciences
  • 2009 - Fellow of the American Academy of Arts and Sciences
  • 2001 - Fellows of the Econometric Society
  • 1995 - Fellow of Alfred P. Sloan Foundation

Overview

Guido W. Imbens is affiliated with Stanford University in the United States. Their research primarily focuses on fields within Mathematics, with notable contributions to Statistics and Probability, Economics and Econometrics, Management Science and Operations Research, Sociology and Political Science, and Artificial Intelligence. The main topics covered in their work include Advanced Causal Inference Techniques, Statistical Methods and Inference, Statistical Methods and Bayesian Inference, Economic Policies and Impacts, Statistical Methods in Clinical Trials, Spatial and Panel Data Analysis, and Income, Poverty, and Inequality.

Some of their recent papers include:

  • Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics, 2020, Journal of Economic Literature
  • Statistical Significance, p-Values, and the Reporting of Uncertainty, 2021, The Journal of Economic Perspectives

Other notable publications associated with their research network, although not directly authored by them, are:

  • Sampling-Based versus Design-Based Uncertainty in Regression Analysis, 2020, Econometrica
  • Design-based analysis in Difference-In-Differences settings with staggered adoption, 2021, Journal of Econometrics
  • Synthetic Difference-in-Differences Estimation, 2023, SSRN Electronic Journal

Frequent co-authors working with Guido W. Imbens include:

  • Susan Athey
  • Dmitry Arkhangelsky
  • Jann Spiess
  • Alberto Abadie
  • James M. McQueen

Their work has been published regularly in influential venues such as:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Journal of Econometrics
  • Econometrica
  • The Journal of Economic Perspectives

Guido W. Imbens has received several awards throughout their career, including:

  • Fellow of the American Statistical Association (ASA), 2020
  • Royal Netherlands Academy of Arts and Sciences, 2017
  • Fellow of the American Academy of Arts and Sciences, 2009
  • Fellows of the Econometric Society, 2001
  • Fellow of Alfred P. Sloan Foundation, 1995

Best Publications

  • Identification and Estimation of Local Average Treatment Effects

    Joshua D. Angrist;Guido W. Imbens

  • Identification of Causal Effects Using Instrumental Variables

    Joshua D. Angrist;Guido W. Imbens;Donald B. Rubin

  • Recent developments in the econometrics of program evaluation

    Guido W. Imbens;Jeffrey M. Wooldridge

  • Regression Discontinuity Designs: A Guide to Practice

    Guido W. Imbens;Thomas Lemieux

  • Identification and Estimation of Local Average Treatment Effects

    Joshua D. Angrist;Joshua D. Angrist;Joshua D. Angrist;Guido W. Imbens

  • Identification and Estimation of Local Average Treatment Effects

    Guido W. Imbens;Joshua D. Angrist

  • Nonparametric Estimation of Average Treatment Effects under Exogeneity: A Review

    Guido W. Imbens

  • Large Sample Properties of Matching Estimators for Average Treatment Effects

    Alberto Abadie;Guido W. Imbens

  • Optimal Bandwidth Choice for the Regression Discontinuity Estimator

    Guido Imbens;Karthik Kalyanaraman

  • Efficient estimation of average treatment effects using the estimated propensity score

    Keisuke Hirano;Guido W. Imbens;Geert Ridder

  • Redefine statistical significance

    Daniel J. Benjamin;James O. Berger;Magnus Johannesson;Magnus Johannesson;Brian A. Nosek;Brian A. Nosek

  • Causal Inference for Statistics, Social, and Biomedical Sciences

    Guido W. Imbens;Donald B. Rubin

  • Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs

    Andrew Gelman;Guido Imbens

  • Bias-Corrected Matching Estimators for Average Treatment Effects

    Alberto Abadie;Guido W. Imbens

  • Implementing matching estimators for average treatment effects in Stata

    Alberto Abadie;David M. Drukker;Jane Leber Herr;Guido W. Imbens

  • Identification and Inference in Nonlinear Difference-in-Differences Models

    Susan Athey;Guido W. Imbens

  • Recursive partitioning for heterogeneous causal effects

    Susan Athey;Guido Imbens

  • On the Failure of the Bootstrap for Matching Estimators

    Alberto Abadie;Guido W. Imbens

  • The Propensity Score with Continuous Treatments

    Keisuke Hirano;Guido W. Imbens

  • Estimation of Causal Effects using Propensity Score Weighting: An Application to Data on Right Heart Catheterization

    Keisuke Hirano;Guido W. Imbens

  • Two-Stage Least Squares Estimation of Average Causal Effects in Models with Variable Treatment Intensity

    Joshua D. Angrist;Guido W. Imbens

  • Identification of Causal Effects Using Instrumental Variables

    Joshua Angrist;Guido Imbens;D.B. Rubin

  • Evolution and Rationality Some Recent Game-Theoretic Results. Identification and Estimation of Local Average Treatment Effects

    Guido Imbens

Frequent Co-Authors

Susan Athey
Susan Athey Stanford University
V. Joseph Hotz
V. Joseph Hotz Duke University
Geert Ridder
Geert Ridder University of Southern California
Gary Chamberlain
Gary Chamberlain Harvard University
Raj Chetty
Raj Chetty Harvard University
Brian A. Nosek
Brian A. Nosek Center for Open Science
Thomas Lemieux
Thomas Lemieux University of British Columbia
David Cesarini
David Cesarini New York University
Thomas D. Cook
Thomas D. Cook University of Wisconsin–Madison

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