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A Monte Carlo comparison of parametric and nonparametric quantile regressions

Insik Min and Inchul Kim

Applied Economics Letters, 2004, vol. 11, issue 2, 71-74

Abstract: This study compares parametric and nonparametric quantile regression methods using Monte Carlo simulations. Simulation results indicate that the nonparametric quantile regression approach is more appropriate, particularly when the underlying model is nonlinear or the error term follows a non-normal distribution.

Date: 2004
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