Quantile Selection Models with an Application to Understanding Changes in Wage Inequality

Manuel Arellano and Stéphane Bonhomme

Abstract: We propose a method to correct for sample selection in quantile regression models. Selection is modelled via the cumulative distribution function, or copula, of the percentile error in the outcome equation and the error in the participation decision. Copula parameters are estimated by minimizing a method-of-moments criterion. Given these parameter estimates, the percentile levels of the outcome are re-adjusted to correct for selection, and quantile parameters are estimated by minimizing a rotated "check" function. We apply the method to correct wage percentiles for selection into employment, using data for the UK for the period 1978-2000. We also extend the method to account for the presence of equilibrium effects when performing counterfactual exercises.

Keywords: Quantiles; sample selection; copula; wage inequality; gender wage gap. (search for similar items in EconPapers)
JEL-codes: C13 J31 (search for similar items in EconPapers)
Date: 2016-12
New Economics Papers: this item is included in nep-lma
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Related works:
Journal Article: Quantile Selection Models With an Application to Understanding Changes in Wage Inequality (2017)
Working Paper: Quantile selection models: with an application to understanding changes in wage inequality (2015)
Working Paper: Quantile selection models: with an application to understanding changes in wage inequality (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:cmf:wpaper:wp2016_1610

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