Modeling heterogeneous treatment effects in the presence of endogeneity

Giacomo Benini and Stefan Sperlich

Econometric Reviews, 2022, vol. 41, issue 3, 359-372

Abstract: An inappropriate handling of cross-sectional heterogeneity renders estimates of causal effects inaccurate and uninformative. The present paper discusses how the direct modeling of cross-sectional differences via semiparametric models represents a useful bridge between a statistical approach, where the conditional distribution of the dependent variable returns any value of the outcome given any value of the explanatory variables, and an econometric analysis, where functions and parameters have direct policy implications. The explicit modeling of heterogeneity across different groups improves the quality of the estimates, mitigates their dependence upon the chosen instrumental variable, diminishes the self-selection problem, and fosters the acquisition of useful information for the entire sample.

Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/07474938.2021.1927548 (text/html)
Access to full text is restricted to subscribers.

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:taf:emetrv:v:41:y:2022:i:3:p:359-372

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/LECR20

DOI: 10.1080/07474938.2021.1927548

Access Statistics for this article

Econometric Reviews is currently edited by Dr. Essie Maasoumi

More articles in Econometric Reviews from Taylor & Francis Journals
Bibliographic data for series maintained by ().