期刊
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
卷 39, 期 1, 页码 294-306出版社
AMER STATISTICAL ASSOC
DOI: 10.1080/07350015.2019.1654879
关键词
Common correlated effects; Dynamic panel bias; Factor augmented regression; Multifactor error structure
资金
- Ghent University
- Hercules Foundation
- Economy, Science, and Innovation Department of the Flemish Government
- Ghent University BOF research fund
- Research Foundation Flanders (FWO)
- National Bank of Belgium
This article extends the common correlated effects pooled (CCEP) estimator to homogenous dynamic panels and develops a bias-corrected estimator that is consistent for a large number of cross-sectional units. Monte Carlo experiments demonstrate strong improvements in terms of bias and variance in the correction.
This article extends the common correlated effects pooled (CCEP) estimator to homogenous dynamic panels. In this setting, CCEP suffers from a large bias when the time span (T) of the dataset is fixed. We develop a bias-corrected CCEP estimator that is consistent as the number of cross-sectional units (N) tends to infinity, for T fixed or growing large, provided that the specification is augmented with a sufficient number of cross-sectional averages, and lags thereof. Monte Carlo experiments show that the correction offers strong improvements in terms of bias and variance. We apply our approach to estimate the dynamic impact of temperature shocks on aggregate output growth.
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