Regression–Discontinuity Analysis: A Survey of Recent Developments in Economics
TLDR
The authors provides a discussion of recent developments related to the applicability of the regression discontinuity design in economics, such as identification and estimation methods, as well as a number of sensitivity and validity tests of importance in empirical application.Abstract:
. This paper provides a discussion of recent developments related to the applicability of the regression discontinuity design in economics. It reviews econometric issues, such as identification and estimation methods, as well as a number of sensitivity and validity tests of importance in empirical application.read more
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Regression Discontinuity Designs in Economics
TL;DR: In this article, the authors provide an introduction and user guide to regression discontinuity (RD) design for empirical researchers, including the basic theory behind RD design, details when RD is likely to be valid or invalid given economic incentives.
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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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Evolution and Rationality Some Recent Game-Theoretic Results. Identification and Estimation of Local Average Treatment Effects
TL;DR: In this paper, the authors investigated conditions sufficient for identification of average treatment effects using instrumental variables and showed that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect.
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Regression discontinuity designs in economics
David S. Lee,Thomas Lemieux +1 more
TL;DR: In this paper, the authors provide an introduction and user guide to regression discontinuity (RD) designs for empirical researchers, and discuss the advantages and disadvantages of estimating RD designs and the limitations of interpreting these estimates.
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Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs
TL;DR: Calonico et al. as mentioned in this paper proposed new theory-based, more robust confidence interval estimators for average treatment effects at the cutoff in sharp regression discontinuity (RD), sharp kink, fuzzy RD, and fuzzy kink RD designs.
References
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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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Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme
TL;DR: This paper decompose the conventional measure of evaluation bias into several components and find that bias due to selection on unobservables, commonly called selection bias in econometrics, is empirically less important than other components, although it is still a sizeable fraction of the estimated programme impact.
Book
Local polynomial modelling and its applications
Jianqing Fan,Irène Gijbels +1 more
TL;DR: Applications of Local Polynomial Modeling in Nonlinear Time Series and Automatic Determination of Model Complexity and Framework for Local polynomial regression.
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Evolution and Rationality Some Recent Game-Theoretic Results. Identification and Estimation of Local Average Treatment Effects
TL;DR: In this paper, the authors investigated conditions sufficient for identification of average treatment effects using instrumental variables and showed that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect.