科学研究

Professor Qi Li is a tenured chair professor at Texas A&M University in the United States. His main research field is econometrics. He has made significant contributions to theoretical econometrics, and his main contributions include econometric model testing and nonparametric/semiparametric model estimation. Since 1991, Professor Li has published more than 150 papers on international journals of economics and statistics, including Econometrica, Review of Economics and Statistics, Journal of Economic Theory, Journal of Econometrics, Economtric Theory, Journal of the American Statistical Association, Annals of Statistics, and Journal of Multivariate Analysis, etc. His book "Nonparametric Econometrics" has become a standard textbook in the field of nonparametric econometrics. In the past few years, he has also served as an editor or associate editor of several academic journals such as Journal of Econometrics, Econometric Theory, Econometrics Journal, Econometric Reviews, Economics Letters, Journal of Nonparametric Statistics, etc.

This paper considers a varying-coefficient spatial dynamic panel data model with fixed effects. We show that a conventional kernel-based nonparametric instrumental variable approach poses a weak IV problem. We propose a robust modified estimator that overcomes this identification problem and derive its asymptotic theory. We also extend our analysis to a partially linear varying-coefficient specification and establish the asymptotic normality results for both finite and infinite dimensional parameter estimators. Simulation results show that our proposed methods work well in finite samples. We apply the partially linear varying-coefficient model to study how the sales of a liquor producer respond to those of neighboring competitors in China. We find significant spatial dependence among liquor markets and show that the spatial effect varies with competition intensity.