Identification in Nonlinear Difference in Difference Models with Multivalued Treatment Outcomes
36 Pages Posted: 5 Nov 2011
Date Written: November 4, 2011
Abstract
We study the conditions to directly identify the joint distribution of outcomes for the treated group in absence of any treatment, avoiding to make assumptions that allow identify each counterfactual marginal distribution. Our starting point is Athey & Imbens (2006)'s Changes-In-Changes Model, but we generalize it letting the treatment also affect the distribution of unobservables even within each group (e.g. treated and untreated). We show that under a reasonable set of assumptions we can identify sharp bound for the counterfactual joint distribution of outcome variables. Moreover, we show identification power increases for copulas from the Archimedean family.
Keywords: treatment effect, identification, nonlinear difference in difference, copulas
JEL Classification: C14, C31, C46
Suggested Citation: Suggested Citation
Do you have negative results from your research you’d like to share?
Recommended Papers
-
Trends in U.S. Wage Inequality: Re-Assessing the Revisionists
By David H. Autor, Lawrence F. Katz, ...
-
Trends in U.S. Wage Inequality: Re-Assessing the Revisionists
By David H. Autor, Lawrence F. Katz, ...
-
Skill Biased Technological Change and Rising Wage Inequality: Some Problems and Puzzles
By David Card and John E. Dinardo
-
The Polarization of the U.S. Labor Market
By David H. Autor, Lawrence F. Katz, ...
-
Rising Wage Inequality: The Role of Composition and Prices
By David H. Autor, Lawrence F. Katz, ...
-
Rising Wage Inequality: The Role of Composition and Prices
By David H. Autor, Lawrence F. Katz, ...
-
Changes in the Labor Supply Behavior of Married Women: 1980-2000
By Francine D. Blau and Lawrence M. Kahn
-
Revisiting the German Wage Structure
By Christian Dustmann, Johannes Ludsteck, ...
-
Quantile Regression Under Misspecification, with an Application to the U.S. Wage Structure
By Joshua D. Angrist, Victor Chernozhukov, ...