Regression Discontinuity Designs in Economics

Дизайны регрессионной прерывности в экономике
David S. Lee, Thomas Lemieux
2009-02-01

RD estimationcausal inferenceempirical economicsquasi-experimental designregression discontinuity designs
This paper provides an introduction and "user guide" to Regression Discontinuity (RD) designs for empirical researchers. It presents the basic theory behind the research design, details when RD is likely to be valid or invalid given economic incentives, explains why it is considered a "quasi-experimental" design, and summarizes different ways (with their advantages and disadvantages) of estimating RD designs and the limitations of interpreting these estimates. Concepts are discussed using examples drawn from the growing body of empirical research using RD.
1
Economic incentives can determine whether the assumptions required for RD identification hold, affecting the design’s credibility.
2
It explains the theoretical foundations of RD designs and the conditions under which they are likely to be valid or invalid.
3
RD designs are characterized as quasi-experimental because treatment assignment changes discontinuously at a known threshold.
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The paper provides an introductory user guide to regression discontinuity designs for empirical economic research.
5
The paper reviews alternative estimation approaches, their advantages and disadvantages, and limitations in interpreting RD estimates.

Regression discontinuity designs in economic empirical research

The theoretical validity, quasi-experimental interpretation, estimation methods, and limitations of regression discontinuity designs

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2009-02-01
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David S. Lee
Thomas Lemieux
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