Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research

1998/01/01 by Moshe Buchinsky · 1,459 citations
Decision Sciences · Mathematics · Medicine · #Advanced Statistical Methods and Models #Bayesian multivariate linear regression #Computer science #Cross-sectional regression #Econometrics #Economics #Empirical research #Guideline #Mathematics #Medicine #Probabilistic and Robust Engineering Design #Quantile #Quantile regression #Regression analysis #Statistical Methods and Inference #Statistics

paper · doi:10.2307/146316

published in The Journal of Human Resources 33(1), 88 (University of Wisconsin Press)

openalex publication_date 1998/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

This paper provides a guideline for the practical use of the semi-parametric technique of quantile regression, concentrating on cross-section applications. It summarizes the most important issues in quantile regression applications and fills some gaps in the literature. The paper (a) presents several alternative estimators for the covariance matrix of the quantile regression estimates; (b) reviews the results for a sequence of quantile regression estimates; and (c) discusses testing procedures for homoskedasticity and symmetry of the error distribution. The various results in the literature are incorporated into the generalized method of moments frame-work. The paper also provides an empirical example using data from the Current Population Survey, raising several important issues relevant to empirical applications of quantile regression. The paper concludes with an extension to the censored quantile regression model.

Citations

• Large Sample Properties of Generalized Method of Moments Estimators

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