科学研究

首都经济贸易大学国际经济管理学院教授。主要研究方向为高维因子分析，交互效应面板模型，时间序列分析，空间计量经济学等。目前已在Journal of Econometrics: Economic Letters, Journal of Business and Economic Statistics等国际知名经济学期刊发表SSCI论文10余篇，并多次应邀作为上述知名经济类期刊的匿名审稿人。

This paper introduces a spatial panel quantile model with unobserved heterogeneity. The proposed model is capable of capturing high-dimensional cross-sectional dependence and allows heterogeneous regression coefficients. A new procedure is proposed to estimate the model parameters. We establish the asymptotic theory of the estimated parameters under the large-$N$ and large-$T$ scenario. We prove that the widely-used Bai and Ng's information criterion can consistently estimate the dimension of interactive fixed effects. Monte Carlo simulations document the satisfactory performance of the proposed method. We apply our model to study the quantile co-movement structure of the U.S. stock market by taking into account the input-output linkages as firms are connected through the input-output production network.

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