The State of Applied Econometrics: Causality and Policy Evaluation
Susan Athey,Guido W. Imbens +1 more
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In this paper, the authors discuss recent developments in econometrics that they view as important for empirical researchers working on policy evaluation questions, focusing on three main areas, where in each case they highlight recommendations for applied work.Abstract:
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, where in each case we highlight 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 interpretation of regression methods. Second, we discuss various forms of supplementary analyses to make the identification strategies more credible. These include placebo analyses as well as sensitivity and robustness analyses. Third, we discuss recent advances in machine learning methods for causal effects. These advances include methods to adjust for differences between treated and control units in high-dimensional settings, and methods for identifying and estimating heterogeneous treatment effects.read more
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References
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Journal ArticleDOI
The central role of the propensity score in observational studies for causal effects
TL;DR: The authors discusses the central role of propensity scores and balancing scores in the analysis of observational studies and shows that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates.
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Identification of Endogenous Social Effects: The Reflection Problem
TL;DR: The authors examined the reflection problem that arises when a researcher observing the distribution of behaviour in a population tries to infer whether the average behaviour in some group influences the behaviour of the individuals that comprise the group.
Journal ArticleDOI
Identification of Causal Effects Using Instrumental Variables
TL;DR: It is shown that the instrumental variables (IV) estimand can be embedded within the Rubin Causal Model (RCM) and that under some simple and easily interpretable assumptions, the IV estimand is the average causal effect for a subgroup of units, the compliers.
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Recent developments in the econometrics of program evaluation
TL;DR: In the last two decades, much research has been done on the econometric and statistical analysis of such causal effects as discussed by the authors, which has reached a level of maturity that makes it an important tool in many areas of empirical research in economics, including labor economics, public finance, development economics, industrial organization, and other areas in empirical microeconomics.
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The Economic Costs of Conflict: A Case Study of the Basque Country
TL;DR: In this paper, the authors investigated the economic effects of conflict, using the terrorist conflict in the Basque Country as a case study, and found that after the outbreak of terrorism in the late 1960's, per capita GDP in the basque country declined about 10 percentage points relative to a synthetic control region without terrorism.