EconPapers    
Economics at your fingertips  
 

Efficiency of Average Treatment Effect Estimation When the True Propensity Is Parametric

Kyoo il Kim ()
Additional contact information
Kyoo il Kim: Department of Economics, Michigan State University, 486 W. Circle Dr., East Lansing, MI 48824, USA

Econometrics, 2019, vol. 7, issue 2, 1-13

Abstract: It is well known that efficient estimation of average treatment effects can be obtained by the method of inverse propensity score weighting, using the estimated propensity score, even when the true one is known. When the true propensity score is unknown but parametric, it is conjectured from the literature that we still need nonparametric propensity score estimation to achieve the efficiency. We formalize this argument and further identify the source of the efficiency loss arising from parametric estimation of the propensity score. We also provide an intuition of why this overfitting is necessary. Our finding suggests that, even when we know that the true propensity score belongs to a parametric class, we still need to estimate the propensity score by a nonparametric method in applications.

Keywords: average treatment effect; efficiency bound; propensity score; sieve MLE (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://www.mdpi.com/2225-1146/7/2/25/pdf (application/pdf)
https://www.mdpi.com/2225-1146/7/2/25/ (text/html)

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:gam:jecnmx:v:7:y:2019:i:2:p:25-:d:236151

Access Statistics for this article

Econometrics is currently edited by Prof. Dr. Kerry Patterson

More articles in Econometrics from MDPI, Open Access Journal
Bibliographic data for series maintained by XML Conversion Team ().

 
Page updated 2019-06-22
Handle: RePEc:gam:jecnmx:v:7:y:2019:i:2:p:25-:d:236151