报告人：朱浣君助理教授 厦门大学
报告题目：Testing for a Structural Break in Dynamic Panel Data Models with Common Factors
时 间：2017年5月1日(星期一) 15:00 ~ 16:00
地 点：旗山校区理工北楼601报告厅
主 办：数学与计算机科学学院,福建省分析数学及应用重点实验室
参加对象：相关专业教师和学生
报告摘要：This paper develops a method for testing for the presence of a single structural break in panel data models with unobserved heterogeneity represented by a factor error structure. The common factor approach is an appealing way to capture the e?ect of unobserved variables, such as skills and innate ability in studies of returns to education, common shocks and cross-sectional dependence in models of economic growth, law enforcement acts and public attitudes towards crime in statistical modelling of criminal behaviour. Ignoring these variables may result in inconsistent parameter estimates and invalid inferences. We focus on the case where the time frequency of the data may be yearly and thereby the number of time series observations is small, even if the sample covers a rather long period of time. We develop a Distance type statistic based on a Method of Moments estimator that allows for unobserved common factors. Existing structural break tests proposed in the literature are not valid under these circumstances. The asymptotic properties of the test statistic are established for both known and unknown breakpoints. In our simulation study, the method performed well, both in terms of size and power, as well as in terms of successfully locating the time at which the break occurred. The method is illustrated using data from a large sample of banking institutions, providing empirical evidence on the well-known Gibrat’s‘Law’.
专家简介：澳大利亚Monash大学统计学博士，厦门大学经济学院统计系助理教授。
