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
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)
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Persistent link: https://EconPapers.repec.org/RePEc:cns:cnscwp:201805
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