Reducing Bias in a Matching Estimation of Endogenous Treatment Effect

A. Di Pino, Maria Gabriella Campolo () and Edoardo Otranto

Working Paper CRENoS from Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia

Abstract: The traditional matching methods for the estimation of treatment parameters are often affected by selectivity bias due to the endogenous joint influence of latent factors on the assignment to treatment and on the outcome, especially in a cross-sectional framework. In this study, we show that the influence of unobserved factors involves a cross-correlation between the endogenous components of propensity scores and causal effects. A correction for the effects of this correlation on matching results leads to a reduction of bias. A Monte Carlo experiment and an empirical application using the LaLonde's experimental data set support this finding.

Keywords: endogenous component of propensity scores; endogenous treatment; propensity score matching; State-Space Model (search for similar items in EconPapers)
Date: 2018
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://crenos.unica.it/crenos/node/7124
https://crenos.unica.it/crenos/sites/default/files/wp-18-05.pdf (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:cns:cnscwp:201805

Access Statistics for this paper

More papers in Working Paper CRENoS from Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia Contact information at EDIRC.
Bibliographic data for series maintained by CRENoS ().