Estimating Partially Conditional Quantile Treatment Effects

Zongwu Cai, Ying Fang, Ming Lin and Shengfang Tang
Additional contact information
Zongwu Cai: Department of Economics, The University of Kansas, Lawrence, KS 66045, USA
Ying Fang: The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, Fujian 361005, China and Department of Statistics, School of Economics, Xiamen University, Xiamen, Fujian 361005, China
Ming Lin: The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, Fujian 361005, China and Department of Statistics, School of Economics, Xiamen University, Xiamen, Fujian 361005, China
Shengfang Tang: Department of Statistics, School of Economics, Xiamen University, Xiamen, Fujian 361005, China

No 202103, WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS from University of Kansas, Department of Economics

Abstract: This paper proposes a new model, termed as the partially conditional quantile treatment effect model, to characterize the heterogeneity of treatment effect conditional on some predetermined variable(s). We show that this partially conditional quantile treatment effect is identified under the assumption of selection on observables, which leads to a semiparametric estimation procedure in two steps: first, parametric estimation of the propensity score function and then, nonparametric estimation of conditional quantile treatment effects. Under some regularity conditions, the consistency and asymptotic normality of the proposed semiparametric estimator are derived. Furthermore, the finite sample performance of the proposed method is illustrated through Monte Carlo experiments. Finally, we apply our methods to estimate the quantile treatment effects of a first-time mother’s smoking during the pregnancy on the baby’s weight as a function of the mother’s age, and our empirical results show substantial heterogeneity across different mother’s ages with a significant negative effect of smoking on infant birth weight across all mother’s ages and quantiles considered.

Keywords: Conditional quantile treatment effect; Heterogeneity; Propensity score; Semiparametric estimation; Treatment effect on treated (search for similar items in EconPapers)
JEL-codes: C13 C14 C21 C54 (search for similar items in EconPapers)
Date: 2021-01, Revised 2021-01
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www2.ku.edu/~kuwpaper/2021Papers/202103.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 500 Can't connect to www2.ku.edu:80 (A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond.)

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:kan:wpaper:202103

Access Statistics for this paper

More papers in WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS from University of Kansas, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Professor Zongwu Cai ().