A SIMPLE NONPARAMETRIC APPROACH FOR ESTIMATION AND INFERENCE OF CONDITIONAL QUANTILE FUNCTIONS Academic Article uri icon

abstract

  • In this paper, we present a new nonparametric method for estimating a conditional quantile function and develop its weak convergence theory. The proposed estimator is computationally easy to implement and automatically ensures quantile monotonicity by construction. For inference, we propose to use a residual bootstrap method. Our Monte Carlo simulations show that this new estimator compares well with the check-function-based estimator in terms of estimation mean squared error. The bootstrap confidence bands yield adequate coverage probabilities. An empirical example uses a dataset of Canadian high school graduate earnings, illustrating the usefulness of the proposed method in applications.

published proceedings

  • ECONOMETRIC THEORY

author list (cited authors)

  • Fang, Z., Li, Q. i., & Yan, K. X.

citation count

  • 1

complete list of authors

  • Fang, Zheng||Li, Qi||Yan, Karen X

publication date

  • April 2023