Semiparametric Estimation of Correlated Random Coefficient Models without Instrumental Variables

Samuele Centorrino; Aman Ullah; Jing Xue

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arXiv · 1911.06857

Semiparametric Estimation of Correlated Random Coefficient Models without Instrumental Variables

Samuele Centorrino·Aman Ullah·Jing Xue

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Abstract

We study a linear random coefficient model where slope parameters may be correlated with some continuous covariates. Such a model specification may occur in empirical research, for instance, when quantifying the effect of a continuous treatment observed at two time periods. We show one can carry identification and estimation without instruments. We propose a semiparametric estimator of average partial effects and of average treatment effects on the treated. We showcase the small sample properties of our estimator in an extensive simulation study. Among other things, we reveal that it compares favorably with a control function estimator. We conclude with an application to the effect of malaria eradication on economic development in Colombia.

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BibTeX RIS

Samuele Centorrino, Aman Ullah, Jing Xue. 2019-11-15. Semiparametric Estimation of Correlated Random Coefficient Models without Instrumental Variables. https://arxiv.org/abs/1911.06857

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