First-stage analysis for instrumental-variables quantile regression

• Autores: Javier Alejo, Antonio F. Galvao, Gabriel Montes Rojas
• Localización: The Stata journal, ISSN 1536-867X, Vol. 24, Nº. 2, 2024, págs. 273-286
• Idioma: inglés
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• Resumen

  • In this article, we develop a first-stage linear regression command, fsivqreg, for an instrumental-variables quantile regression (QR) model. The quan- tile first stage is analogous to the least-squares case, that is, a linear projection of the endogenous variables on the instruments and other exogenous covariates, with the difference that the QR case is a weighted projection. The weights are given by the conditional density function of the innovation term in the QR structural model, at a given quantile. An empirical application illustrates its implementation.