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LUKE KEELE - Penn State University

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” Geographic Boundaries as Regression Discontinuities”
07 November 2013 from 4:00 PM to 5:00 PM
201 Thomas Bldg.
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Social scientists often turn to natural experiments to draw causal inferences with observational data.  Recently, the regression discontinuity design (RD) has become one popular type of natural experiment given its relatively weak assumptions. We study a special type of regression discontinuity design where the discontinuity in treatment assignment is geographic. In this design, which we call the Geographic Regression Discontinuity (GRD) design, a geographic or administrative boundary splits units into treated and control areas, and analysts make the case that the division into treated and control areas occurs in an as-if random fashion.  We show how this design is equivalent to a standard RD with two cutoffs, but we also clarify several methodological differences that arise in geographical contexts. We also offer a method for estimation for geographically-located treatment effects that can also be used to validate the identification assumptions using observable pre-treatment characteristics.