Title: Checking the Adequacy of Quantile Regression Models
Speaker: Xiaojun Song, PKU
Xiaojun Song is an associate professor and PhD supervisor in the Department of Business Statistics and Econometrics, Guanghua School of Management, Peking University, and has a PhD in economics from Carlos III University, Madrid, Spain. His main research interests are theoretical econometrics, including non-parametric/semi-parametric methods, hypothesis testing and self-help methods, and applications of econometrics. His papers have been published in international journals such as Econometric Theory, Journal of Applied Econometrics, Journal of Business & Economic Statistics and Journal of Econometrics. Since January 2020, he has been the associate editor of Economic Modelling.
Absract: We propose a new class of tests to evaluate the correct specification of quantile regression models over a continuum of quantiles. A cumulative sum (cusum) process is established by using all components in the gradient of the check function, which is further modified by (1) replacing the weighting functions with dimension reduction ability, and (2) incorporating an orthogonal projection onto the tangent space of nuisance parameters in order to eliminate the uncertainty of preliminary parameter estimation. Besides, this projection is also able to facilitate an attractive multiplier bootstrap procedure for the computation of critical values. We then introduce several Cramer-von Mises-type test statistics with convenient closed-form expressions. The asymptotic properties of the proposed test statistics are investigated under the null, the alternative, and a sequence of local alternatives converging to the null at the \'n rate, respectively. Simulation studies show that our tests have good finite sample performance. A real data example is also introduced to illustrate the usefulness of our tests in practice.
Time: 16:30-17:30, Tuesday, Sep 6, 2022
Venue: Tencent Meeting ID: 375 8612 5504
