Department of Economics and Business Economics

Optimal bandwidth selection for nonparametric conditional distribution and quantile functions

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  • Qi Li, Texas A and M University, United States
  • J. Lin, National University of Singapore
  • ,
  • J.S. Racine
We propose a data-driven least-square cross-validation method to optimally select smoothing parameters for the nonparametric estimation of conditional cumulative distribution functions and conditional quantile functions. We allow for general multivariate covariates that can be continuous, categorical, or a mix of either. We provide asymptotic analysis, examine finite-sample properties via Monte Carlo simulation, and consider an application involving testing for first-order stochastic dominance of children's health conditional on parental education and income. This article has supplementary materials online.
Original languageEnglish
JournalJournal of Business and Economic Statistics
Pages (from-to)57-65
Number of pages9
Publication statusPublished - 1 Jan 2013

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