Quantile Regression Under Misspecification: With an Application to the US Wage Structure

Working Paper: NBER ID: w10428

Authors: Joshua Angrist; Victor Chernozhukov; Iván Fernández-Val

Abstract: Quantile regression(QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean square error linear approximation to the conditional expectation function even when the linear model is misspecified. Empirical research using quantile regression with discrete covariates suggests that QR may have a similar property, but the exact nature of the linear approximation has remained elusive. In this paper, we show that QR can be interpreted as minimizing a weighted mean-squared error loss function for specification error. The weighting function is an average density of the dependent variable near the true conditional quantile. The weighted least squares interpretation of QR is used to derive an omitted variables bias formula and a partial quantile correlation concept, similar to the relationship between partial correlation and OLS. We also derive general asymptotic results for QR processes allowing for misspecification of the conditional quantile function, extending earlier results from a single quantile to the entire process. The approximation properties of QR are illustrated through an analysis of the wage structure and residual inequality in US Census data for 1980, 1990, and 2000. The results suggest continued residual inequality growth in the 1990s, primarily in the upper half of the wage distribution and for college graduates.

Keywords: No keywords provided

JEL Codes: J31; C13; C14


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
Quantile Regression (QR) (C21)Conditional Quantile Function (CQF) (C46)
Quantile Regression (QR) (C21)Wage Distribution (J31)
Quantile Regression (QR) (C21)Residual Inequality (I24)
Quantile Regression (QR) (C21)Changes in Wage Distribution Over Time (J31)
Quantile Regression (QR) (C21)Evolution of Conditional Wage Distribution (J31)
Changes in Upper Half of Wage Distribution (D39)Growth of Withingroup Inequality (1990-2000) (D31)

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