The State of Applied Econometrics: Causality and Policy Evaluation

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 strate...

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Bibliographic Details
Published in:The Journal of economic perspectives 2017-04, Vol.31 (2), p.3-32
Main Authors: Athey, Susan, Imbens, Guido W.
Format: Article
Language:English
Subjects:
Analytical estimating
Causality
Discontinuity
Econometrics
Economic models
Economic theory
Estimation methods
Estimators
Inference
Machine learning
Modeling
Observational research
Observational studies
Program evaluation
Robustness
Symposium: Recent Ideas in Econometrics
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Summary: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 interpretation of regression methods. Second, we discuss various forms of supplementary analyses, including placebo analyses as well as sensitivity and robustness analyses, intended to make the identification strategies more credible. Third, we discuss some implications of recent advances in machine learning methods for causal effects, including methods to adjust for differences between treated and control units in high-dimensional settings, and methods for identifying and estimating heterogenous treatment effects.
ISSN:0895-3309
1944-7965
DOI:10.1257/jep.31.2.3