北京师范大学经济与工商管理学院
 
 
 

12.23金融系Seminar:Fixed-effects dynamic spatial panel data models and impulse response analysis
发布日期: 2016-12-19  浏览次数:

时        间:2016年12月23日(周五)上午10:00-11:30。
地        点:后主楼16层1620
讲座语言:中文
主  讲  人:李鲲鹏   首都经贸国民经济管理学院副院长
主  持  人:李    锐   北京师范大学经管学院教授

主讲人简介
        李鲲鹏,清华经管2011年博士,哥伦比亚大学经济系访问学者,首都经贸国民经济管理学院副院长,研究领域是计量经济学和应用经济学。SSCI/SCI已检索论文10篇,其中,在国际顶级期刊Annals of Statistics上已发表论文1篇,Econometrica上的论文即将发表;在Review of Economics and Statistics,Journal of Econometrics 等国际一流期刊上发表论文5篇。已主持国家自然科学基金项目2项。获2016年中国经济学优秀博士论文奖。担任Journal of Econometrics等6个国际期刊的匿名评审人。

【Abstract】
Real data often have complicated correlations over cross section and time. Such correlations are of particular interests in empirical studies. This paper considers using high order spatial lags and high order time lags to model complicated correlations over cross section and time. We propose to use the quasi maximum likelihood (QML) method to estimate the model. We establish the asymptotic theory of the quasi maximum likelihood estimator (QMLE), including the consistency and limiting distribution, under large N and large T setup, where N denotes the number of individuals and T the number of time periods. We investigate the problem of estimating impulse response functions and the associated (1-a)-confidence intervals. Average direct, indirect and total impacts are defined along the same spirits of LeSage and Pace (2009) under the dynamic spatial panel data setup. The estimation and inferential theory for the three impacts are studied. Model selection issue is also considered. Monte Carlo simulations confirm our theoretical results and show that the QMLE after bias correction has good finite sample performance.

Key Words: Dynamic spatial models; Panel data models; Quasi maximum likelihood estimation; Impulse response analysis; Confidence intervals; Model selection.

 

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