@article{71810b51ef614bb9a9b6dcdfc5eb82bc,
title = "Nonstationary nonlinear quantile regression",
abstract = "This study examines estimation and inference based on quantile regression for parametric nonlinear models with an integrated time series covariate. We first derive the limiting distribution of the nonlinear quantile regression estimator and then consider testing for parameter restrictions, when the regression function is specified as an asymptotically homogeneous function. We also study linear-in-parameter regression models when the regression function is given by integrable regression functions as well as asymptotically homogeneous regression functions. We, furthermore, propose a fully modified estimator to reduce the bias in the original estimator under a certain set of conditions. Finally, simulation studies show that the estimators behave well, especially when the regression error term has a fat-tailed distribution.",
keywords = "Integrated time series, nonlinear regression model, quantile regression",
author = "Yoshimasa Uematsu",
note = "Funding Information: The author thanks the Editor, two referees, Toshio Honda, Eiji Kurozumi, Tae-Hwan Kim, Chirok Han, Mototsugu Shintani, Jana Jurecˇkov{\'a}, and all the participants at the workshop at Hitotsubashi University, the Sogang–Hitotsubashi Conference on Econometrics at Sogang University, and the 2012 Asian Meeting of the Econometric Society at the University of Delhi for their helpful suggestions. The author acknowledges financial supports from a Grant-in-Aid for JSPS Fellows, 26-1905. Funding Information: The author thanks the Editor, two referees, Toshio Honda, Eiji Kurozumi, Tae-Hwan Kim, Chirok Han, Mototsugu Shintani, Jana Jure?kov?, and all the participants at the workshop at Hitotsubashi University, the Sogang?Hitotsubashi Conference on Econometrics at Sogang University, and the 2012 Asian Meeting of the Econometric Society at the University of Delhi for their helpful suggestions. The author acknowledges financial supports from a Grant-in-Aid for JSPS Fellows, 26-1905. Publisher Copyright: {\textcopyright} 2017, {\textcopyright} 2017 Taylor & Francis Group, LLC.",
year = "2019",
month = apr,
day = "21",
doi = "10.1080/07474938.2017.1308056",
language = "English",
volume = "38",
pages = "386--416",
journal = "Econometric Reviews",
issn = "0747-4938",
publisher = "Taylor and Francis Ltd.",
number = "4",
}