期刊
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
卷 111, 期 516, 页码 1804-1819出版社
AMER STATISTICAL ASSOC
DOI: 10.1080/01621459.2015.1119696
关键词
Change point; Interactive fixed effects; LASSO; Panel data; Penalized estimation; Principal component analysis
资金
- Singapore Ministry of Education for Academic Research Fund (AcRF) under the Tier 2 grant [MOE2012-T2-2-021]
- Lee Kong Chian Fund for Excellence
In this article, we consider estimation of common structural breaks in panel data models with unobservable interactive fixed effects. We introduce a penalized principal component (PPC) estimation procedure with an adaptive group fused LASSO to detect the multiple structural breaks in the models. Under some mild conditions, we show that with probability approaching one the proposed method can correctly determine the unknown number of breaks and consistently estimate the common break dates. Furthermore, we estimate the regression coefficients through the post-LASSO method and establish the asymptotic distribution theory for the resulting estimators. The developed methodology and theory are applicable to the case of dynamic panel data models. Simulation results demonstrate that the proposed method works well in finite samples with low false detection probability when there is no structural break and high probability of correctly estimating the break numbers when the structural breaks exist. We finally apply our method to study the environmental Kuznets curve for 74 countries over 40 years and detect two breaks in the data. Supplementary materials for this article are available online.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据