EconPapers    
Economics at your fingertips  
 

Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models

Ying-Ying Lee

Papers from arXiv.org

Abstract: Partial mean with generated regressors arises in several econometric problems, such as the distribution of potential outcomes with continuous treatments and the quantile structural function in a nonseparable triangular model. This paper proposes a nonparametric estimator for the partial mean process, where the second step consists of a kernel regression on regressors that are estimated in the first step. The main contribution is a uniform expansion that characterizes in detail how the estimation error associated with the generated regressor affects the limiting distribution of the marginal integration estimator. The general results are illustrated with two examples: the generalized propensity score for a continuous treatment (Hirano and Imbens, 2004) and control variables in triangular models (Newey, Powell, and Vella, 1999; Imbens and Newey, 2009). An empirical application to the Job Corps program evaluation demonstrates the usefulness of the method.

Date: 2018-10
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://arxiv.org/pdf/1811.00157 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1811.00157

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().

 
Page updated 2019-01-31
Handle: RePEc:arx:papers:1811.00157