Oracle Efficient Estimation of Heterogeneous Dynamic Panel Data Models with Interactive Fixed Effects
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作者:
Cao, Yiqiu
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机构:
Tsinghua Univ, Sch Econ & Management, Beijing, Peoples R ChinaTsinghua Univ, Sch Econ & Management, Beijing, Peoples R China
Cao, Yiqiu
[1
]
Jin, Sainan
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机构:
Tsinghua Univ, Sch Econ & Management, Beijing, Peoples R China
Tsinghua Univ, Sch Social Sci, Beijing, Peoples R ChinaTsinghua Univ, Sch Econ & Management, Beijing, Peoples R China
Jin, Sainan
[1
,2
]
Lu, Xun
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机构:
Chinese Univ Hong Kong, Dept Econ, Shatin, Hong Kong, Peoples R ChinaTsinghua Univ, Sch Econ & Management, Beijing, Peoples R China
Lu, Xun
[3
]
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机构:
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
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%.
机构:
NYU, Dept Econ, New York, NY 10012 USA
Tsinghua Univ, SEM, Beijing 100084, Peoples R China
Cent Univ Finance & Econ, CEMA, Beijing, Peoples R ChinaNYU, Dept Econ, New York, NY 10012 USA