The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
Activity Number:
|
269
|
Type:
|
Invited
|
Date/Time:
|
Tuesday, July 31, 2012 : 8:30 AM to 10:20 AM
|
Sponsor:
|
JBES-Journal of Business & Economic Statistics
|
Abstract - #306862 |
Title:
|
Estimation of Treatment Effects with High-Dimensional Controls
|
Author(s):
|
Alexandre Belloni*+ and Victor Chernozhukov and Christian Hansen
|
Companies:
|
Duke University and Massachusetts Institute of Technology and The University of Chicago
|
Address:
|
Fuqua School of Business, Durham, NC, 27708,
|
Keywords:
|
|
Abstract:
|
We propose methods for inference on the effect of a treatment on a scalar outcome in the presence of very many controls. Our setting is a partially linear regression model containing the treatment/policy variable and a large number p of controls or series terms. We allow p to be much larger than the sample size n but impose that only s < n controls or series terms whose identities are unknown are needed to approximate the regression function accurately. The latter condition makes it possible to estimate the entire regression function as well as the treatment effect by selecting approximately the right set of controls. We develop estimation and inference methods for the average treatment effect in this setting, proposing a novel "post-double-selection" method that provides attractive inferential and estimation properties. In our analysis, we expressly allow for imperfect selection of the controls and account for the impact of selection errors on estimation and inference. In order to cover typical applications in economics, we present methods that allow for non-Gaussian and heteroskedastic disturbances. We illustrate the use of the developed methods with numerical simulations and an application to the effect of abortion on crime rates.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 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.