Oracle Efficient Estimation of Heterogeneous Dynamic Panel Data Models with Interactive Fixed Effects

被引:0
|
作者
Cao, Yiqiu [1 ]
Jin, Sainan [1 ,2 ]
Lu, Xun [3 ]
Su, Liangjun [1 ,4 ]
机构
[1] Tsinghua Univ, Sch Econ & Management, Beijing, Peoples R China
[2] Tsinghua Univ, Sch Social Sci, Beijing, Peoples R China
[3] Chinese Univ Hong Kong, Dept Econ, Shatin, Hong Kong, Peoples R China
[4] Tsinghua Univ, Sch Econ & Management, Beijing 100084, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Cross-sectional dependence; Dynamic panel; Heterogeneity; Minimum wage; principal component analysis; MINIMUM-WAGE; INFERENCE; NUMBER; EMPLOYMENT; REGRESSION;
D O I
10.1080/07350015.2023.2294124
中图分类号
F [经济];
学科分类号
02 ;
摘要
We propose a two-step procedure to estimate a heterogeneous dynamic panel data model with interactive fixed effects. We establish the asymptotic properties of the estimators and show that the final estimator is oracle efficient. We also propose a specification test for the null hypothesis of homogeneous slopes and study the asymptotic properties of the test statistic under both local and global alternatives. Simulations demonstrate the fine performance of the estimator and test statistic. The new estimation and inference methods are applied to study the heterogeneous effects of minimum wage on employment across different counties in the United States. Our dynamic model suggests that the changes of employment range from about-1% to 1% when the minimum wage increases by 1%.
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页码:1169 / 1184
页数:16
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