Abstract Details
|
Activity Number:
|
503
|
|
Type:
|
Invited
|
|
Date/Time:
|
Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
Business and Economic Statistics Section
|
| Abstract - #307686 |
|
Title:
|
Using Local Randomization to Analyze Regression Discontinuity Designs
|
|
Author(s):
|
Adam Sales*+ and Ben B. Hansen
|
|
Companies:
|
University of Michigan and University of Michigan
|
|
Keywords:
|
|
|
Abstract:
|
Identification in regression discontinuity designs (RDDs) stems from "local randomization" of treatment assignment in a window around the threshold. However, conventional practice does not directly choose or assess such a window. We present techniques that use covariates to weaken the relevant local randomization assumptions, along with strengthened tests of the new assumptions. The resulting method furnishes inferences on averages of treatment effects across the chosen window, as opposed to within infinitesimal neighborhoods of a threshold. We demonstrate it on the dataset from Lindo, et al. (2008), evaluating the effect of undergraduate academic probation on future academic performance.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2013 program
|
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.