n-prediction of generalized heteroscedastic transformation regression models

Songnian Chen and Hanghui Zhang

Journal of Econometrics, 2020, vol. 215, issue 2, 305-340

Abstract: Chen (2010) and Khan (2001) consider quantile regression estimation subject to general transformation that permits general heteroscedasticity, but the resulting conditional quantile predictors converge at rates slower than the parametric rate. In this paper, we consider the estimation of a general transformation model subject to a multiplicative form of heteroscedasticity. Our estimators for the finite dimensional parameters, the transformation function and the resulting conditional quantile predictor all converge at the parametric rate. Monte Carlo simulation experiments show that our estimators and conditional quantile predictor perform well in finite samples.

Keywords: Generalized transformation regression model; Heteroscedasticity; n-prediction (search for similar items in EconPapers)
JEL-codes: C14 C24 C51 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:215:y:2020:i:2:p:305-340

DOI: 10.1016/j.jeconom.2019.09.003

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