Guido W Imbens

Biographic Data

ID1471513
NAMEGuido W Imbens
GIVEN NAMESGuido W
FAMILY NAMEImbens
SIGNATUREIMBENS G W
AFFILIATIONSStanford University
ORCID0000-0002-4846-7326
VERIFIEDYes
TOTAL WORKS50
TOTAL CITATIONS176
AUTHOR COUNT50
EDITOR COUNT0
FIRST PUBLICATION YEAR1994
LATEST PUBLICATION YEAR2025
H-INDEX3

  • Comparing Experimental and Nonexperimental Methods: What Lessons Have We Learned Four Decades after LaLonde (1986)

    Open AccessGuido W Imbens, Yiqing XuARTICLEThe Journal of Economic…2025

    In 1986, Robert LaLonde published an article comparing nonexperimental estimates to experimental benchmarks (LaLonde 1986). He concluded that the nonexperimental methods at the time could not systematically replicate experimental benchmarks, casting doubt on their credibility. Following LaLonde's critical assessment, there have been significant methodological advances and practical changes, including (1) an emphasis on the unconfoundedness assump…

  • A Design-Based Perspective on Synthetic Control Methods

    Open AccessLea Bottmer, Guido W Imbens et al.ARTICLEJournal of Business and Economic…2024

    Since their introduction by Abadie and Gardeazabal, Synthetic Control (SC) methods have quickly become one of the leading methods for estimating causal effects in observational studies in settings with panel data.Formal discussions often motivate SC methods by the assumption that the potential outcomes were generated by a factor model.Here we study SC methods from a design-based perspective, assuming a model for the selection of the treated unit(…

  • When Should You Adjust Standard Errors for Clustering?

    Open AccessAlberto Abadie, Susan Athey et al.ARTICLEThe Quarterly Journal of Economics2022

    Clustered standard errors, with clusters defined by factors such as geography, are widespread in empirical research in economics and many other disciplines. Formally, clustered standard errors adjust for the correlations induced by sampling the outcome variable from a data-generating process with unobserved cluster-level components. However, the standard econometric framework for clustering leaves important questions unanswered: (i) Why do we adj…

  • Design-based analysis in Difference-In-Differences settings with staggered adoption

    Open AccessSusan Athey, Guido W ImbensARTICLEJournal of Econometrics2022

  • Synthetic Difference-in-Differences

    Dmitry Arkhangelsky, Susan Athey et al.ARTICLEAmerican Economic Review2021

    We present a new estimator for causal effects with panel data that builds on insights behind the widely used difference-in-differences and synthetic control methods. Relative to these methods we find, both theoretically and empirically, that this “synthetic difference-in-differences” estimator has desirable robustness properties, and that it performs well in settings where the conventional estimators are commonly used in practice. We study the as…

  • Statistical Significance,p-Values, and the Reporting of Uncertainty

    Open AccessGuido W ImbensARTICLEThe Journal of Economic…2021Cited by: 12References: 9

    The use of statistical significance and p-values has become a matter of substantial controversy in various fields using statistical methods. This has gone as far as some journals banning the use of indicators for statistical significance, or even any reports of p-values, and, in one case, any mention of confidence intervals. I discuss three of the issues that have led to these often-heated debates. First, I argue that in many cases, p-values and …

  • Identification and Efficiency Bounds for the Average Match Function Under Conditionally Exogenous Matching

    Bryan S Graham, Guido W Imbens et al.ARTICLEJournal of Business and Economic…2020

    Consider two heterogenous populations of agents who, when matched, jointly produce an output, Y. For example, teachers and classrooms of students together produce achievement, parents raise children, whose life outcomes vary in adulthood, assembly plant managers and workers produce a certain number of cars per month, and lieutenants and their platoons vary in unit effectiveness. Let W∈W={w1,...,wJ} and X∈X={x1,...,xK} denote agent types in the tw…

  • External Validity in Fuzzy Regression Discontinuity Designs

    Marinho Bertanha, Guido W ImbensARTICLEJournal of Business and Economic…2020

    Fuzzy regression discontinuity designs identify the local average treatment effect (LATE) for the subpopulation of compliers, and with forcing variable equal to the threshold. We develop methods that assess the external validity of LATE to other compliance groups at the threshold, and allow for identification away from the threshold. Specifically, we focus on the equality of outcome distributions between treated compliers and always-takers, and b…

  • Machine Learning Methods That Economists Should Know About

    Susan Athey, Guido W ImbensARTICLEAnnual Review of Economics2019

    We discuss the relevance of the recent machine learning (ML) literature for economics and econometrics. First we discuss the differences in goals, methods, and settings between the ML literature and the traditional econometrics and statistics literatures. Then we discuss some specific methods from the ML literature that we view as important for empirical researchers in economics. These include supervised learning methods for regression and classi…

  • Optimized Regression Discontinuity Designs

    Guido W Imbens, Guido Imbens et al.ARTICLEThe Review of Economics and…2019

    The increasing popularity of regression discontinuity methods for causal inference in observational studies has led to a proliferation of different estimating strategies, most of which involve first fitting nonparametric regression models on both sides of a treatment assignment boundary and then reporting plug-in estimates for the effect of interest. In applications, however, it is often difficult to tune the nonparametric regressions in a way th…

  • Understanding and misunderstanding randomized controlled trials: A commentary on Deaton and Cartwright

    Open AccessGuido W Imbens, Guido ImbensARTICLESocial Science & Medicine2018

  • When Should You Adjust Standard Errors for Clustering?

    Alberto Abadie, Susan Athey et al.REPORTNational Bureau of Economic…2017

    In empirical work in economics it is common to report standard errors that account for clustering of units.Typically, the motivation given for the clustering adjustments is that unobserved components in outcomes for units within clusters are correlated.However, because correlation may occur across more than one dimension, this motivation makes it difficult to justify why researchers use clustering in some dimensions, such as geographic, but not o…

  • The State of Applied Econometrics: Causality and Policy Evaluation

    Open AccessSusan Athey, Guido W ImbensARTICLEThe Journal of Economic…2017Cited by: 58References: 90

    In this paper, we discuss recent developments in econometrics that we view as important for empirical researchers working on policy evaluation questions. We focus on three main areas, in each case, highlighting recommendations for applied work. First, we discuss new research on identification strategies in program evaluation, with particular focus on synthetic control methods, regression discontinuity, external validity, and the causal interpreta…

  • Redefine statistical significance

    Open AccessDaniel J Benjamin, James O Berger et al.ARTICLENature Human Behaviour2017Cited by: 106References: 14

  • Matching on the Estimated Propensity Score

    Open AccessAlberto Abadie, Guido W ImbensARTICLEEconometrica2016

    Propensity score matching estimators (Rosenbaum and Rubin (1983)) are widely used in evaluation research to estimate average treatment effects. In this article, we derive the large sample distribution of propensity score matching estimators. Our derivations take into account that the propensity score is itself estimated in a first step, prior to matching. We prove that first step estimation of the propensity score affects the large sample distrib…

  • Recursive partitioning for heterogeneous causal effects

    Open AccessSusan Athey, Guido W Imbens et al.ARTICLEProceedings of the National…2016

    In this paper we propose methods for estimating heterogeneity in causal effects in experimental and observational studies and for conducting hypothesis tests about the magnitude of differences in treatment effects across subsets of the population. We provide a data-driven approach to partition the data into subpopulations that differ in the magnitude of their treatment effects. The approach enables the construction of valid confidence intervals f…

  • Robust Standard Errors in Small Samples: Some Practical Advice

    Guido W Imbens, Michal KolesárARTICLEThe Review of Economics and…2016

    We study the properties of heteroskedasticity-robust confidence intervals for regression parameters. We show that confidence intervals based on a degrees-of-freedom correction suggested by Bell and McCaffrey (2002) are a natural extension of a principled approach to the Behrens-Fisher problem. We suggest a further improvement for the case with clustering. We show that these standard errors can lead to substantial improvements in coverage rates ev…

  • Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction

    Guido W Imbens, Donald B RubinBOOKCausal Inference in Statistics,…2015

    Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime.…

  • Matching Methods in Practice: Three Examples

    Guido W ImbensARTICLEThe Journal of Human Resources2015

    There is a large theoretical literature on methods for estimating causal effects under unconfoundedness, exogeneity, or selection-on-observables type assumptions using matching or propensity score methods. Much of this literature is highly technical and has not made inroads into empirical practice where many researchers continue to use simple methods such as ordinary least squares regression even in settings where those methods do not have attrac…

  • Identification and Inference With Many Invalid Instruments

    Michal Kolesár, Raj Chetty et al.ARTICLEJournal of Business and Economic…2015

    We study estimation and inference in settings where the interest is in the effect of a potentially endogenous regressor on some outcome. To address the endogeneity, we exploit the presence of additional variables. Like conventional instrumental variables, these variables are correlated with the endogenous regressor. However, unlike conventional instrumental variables, they also have direct effects on the outcome, and thus are “invalid” instrument…

  • Promoting Transparency in Social Science Research

    Open AccessEdward Miguel, Colin F Camerer et al.ARTICLEScience2014

    Social scientists should adopt higher transparency standards to improve the quality and credibility of research.

  • Social Networks and the Identification of Peer Effects

    Paul Goldsmith-Pinkham, Guido W ImbensARTICLEJournal of Business and Economic…2013

    There is a large and growing literature on peer effects in economics. In the current article, we focus on a Manski-type linear-in-means model that has proved to be popular in empirical work. We critically examine some aspects of the statistical model that may be restrictive in empirical analyses. Specifically, we focus on three aspects. First, we examine the endogeneity of the network or peer groups. Second, we investigate simultaneously alternat…

  • Optimal Bandwidth Choice for the Regression Discontinuity Estimator

    Open AccessGuido W Imbens, G Imbens et al.ARTICLEThe Review of Economic Studies2012

    We investigate the choice of the bandwidth for the regression discontinuity estimator. We focus on estimation by local linear regression, which was shown to have attractive properties (Porter, J. 2003, “Estimation in the Regression Discontinuity Model” (unpublished, Department of Economics, University of Wisconsin, Madison)). We derive the asymptotically optimal bandwidth under squared error loss. This optimal bandwidth depends on unknown functio…

  • Bias-Corrected Matching Estimators for Average Treatment Effects

    Alberto Abadie, Guido W ImbensARTICLEJournal of Business and Economic…2011

    In Abadie and Imbens (2006), it was shown that simple nearest-neighbor matching estimators include a conditional bias term that converges to zero at a rate that may be slower than N1/2. As a result, matching estimators are not N1/2-consistent in general. In this article, we propose a bias correction that renders matching estimators N1/2-consistent and asymptotically normal. To demonstrate the methods proposed in this article, we apply them to the…

  • Better Late Than Nothing: Some Comments on Deaton (2009) and Heckman and Urzua (2009)

    Guido W ImbensARTICLEJournal of Economic Literature2010

    Two recent papers, Deaton (2009) and Heckman and Urzua (2009), argue against what they see as an excessive and inappropriate use of experimental and quasi-experimental methods in empirical work in economics in the last decade. They specifically question the increased use of instrumental variables and natural experiments in labor economics and of randomized experiments in development economics. In these comments, I will make the case that this mov…