A first-stage test for instrumental variables quantile regression

Javier Alejo, Antonio Galvao and Gabriel Montes-Rojas ()

No 4304, Asociación Argentina de Economía Política: Working Papers from Asociación Argentina de Economía Política

Abstract: This paper develops inference procedures to evaluate the validity of instruments in instrumental variables (IV) quantile regression (QR) models. We first derive a first-stage regression for the IVQR model, analogue to the least squares case, which is a weighted least-squares regression. The weights are given by the density function of the conditional distribution of the innovation term in the QR structural model, conditional on the exogenous covariates and the nstruments. The first-stage regression is a natural framework to evaluate the instruments since we can test for their statistical significance. In the QR case, the instruments could be relevant at some quantiles but not for others or at the mean. Monte Carlo finite sample experiments show that the tests work as expected in terms of empirical size and power. Two applications illustrate that checking for the statistical significance of the instruments at di↵erent quantiles is important.

Keywords: quantile regression; instrumental variables; first-stage (search for similar items in EconPapers)
JEL-codes: C13 C14 C21 C51 C53 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2020-11
New Economics Papers: this item is included in nep-ecm and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:aep:anales:4304

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