Nonparametric Tests for Conditional Quantile Independence with Duration Outcomes

Sungwon Lee () and Joon H. Ro ()
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Sungwon Lee: Department of Economics, Sogang University, Seoul
Joon H. Ro: A.B. Freeman School of Business, Tulane University

No 2013, Working Papers from Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy)

Abstract: It is common for empirical studies to specify models with many covariates to eliminate the omitted variable bias, even if some of them are potentially irrelevant. In the case where models are nonparametrically specified, such a practice results in the curse of dimensionality. Therefore, it is important in nonparametric models to drop irrelevant variables and consider a small number of covariates to improve the precision of estimation. This paper develops nonparametric significance tests for censored quantile regression models with duration outcomes. The null hypothesis is characterized by a conditional moment restriction. We adopt the integrated conditional moment (ICM) approach, which was developed by Bierens (1982); Bierens (1990), to construct test statistics. The testing procedure does not require to estimate the alternative models. Two test statistics are considered: one is the Kolmogorov-Smirnov type statistic and the other is the Cramer-von-Mises type statistic. These test statistics are functionals of a stochastic process which converges weakly to centered Gaussian process. The test has non-trivial power against local alternatives at the parametric rate. A subsampling procedure is proposed to obtain critical values.

Keywords: Conditional quantile independence; nonparametric tests; duration outcomes; integrated conditional moment; empirical processes (search for similar items in EconPapers)
JEL-codes: C12 C14 C41 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2020
New Economics Papers: this item is included in nep-ecm and nep-ore
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