Working Paper: NBER ID: w14723
Authors: David S. Lee; Thomas Lemieux
Abstract: 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.
Keywords: No keywords provided
JEL Codes: C1; H0; I0; J0
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| assignment variable (C78) | treatment effect (C22) |
| local randomization (C90) | treatment effects (C22) |
| merit award assignment (M52) | difference in outcomes (I14) |
| continuity of baseline characteristics (C22) | validity of RD design (C90) |
| RD designs (O32) | credible causal estimates (C51) |
| variation in treatment status near cutoff (C24) | treatment effect identification (C22) |