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Bias-corrected common correlated effects pooled estimation in dynamic panels

Ignace De Vos (UGent) and Gerdie Everaert (UGent)
(2021) JOURNAL OF BUSINESS & ECONOMIC STATISTICS. 39(1). p.294-306
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Abstract
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.
Keywords
Factor augmented regression, dynamic panel bias, Common Correlated Effects, Multifactor error structure, Statistics, Common correlated effects, Dynamic panel bias, Factor augmented regression, Multifactor error structure, CROSS-SECTIONAL DEPENDENCE, DATA MODELS, ADJUSTMENT, REGRESSION, Probability and Uncertainty, Economics and Econometrics, Statistics and Probability, Social Sciences (miscellaneous)

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MLA
De Vos, Ignace, and Gerdie Everaert. “Bias-Corrected Common Correlated Effects Pooled Estimation in Dynamic Panels.” JOURNAL OF BUSINESS & ECONOMIC STATISTICS, vol. 39, no. 1, 2021, pp. 294–306, doi:10.1080/07350015.2019.1654879.
APA
De Vos, I., & Everaert, G. (2021). Bias-corrected common correlated effects pooled estimation in dynamic panels. JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 39(1), 294–306. https://doi.org/10.1080/07350015.2019.1654879
Chicago author-date
De Vos, Ignace, and Gerdie Everaert. 2021. “Bias-Corrected Common Correlated Effects Pooled Estimation in Dynamic Panels.” JOURNAL OF BUSINESS & ECONOMIC STATISTICS 39 (1): 294–306. https://doi.org/10.1080/07350015.2019.1654879.
Chicago author-date (all authors)
De Vos, Ignace, and Gerdie Everaert. 2021. “Bias-Corrected Common Correlated Effects Pooled Estimation in Dynamic Panels.” JOURNAL OF BUSINESS & ECONOMIC STATISTICS 39 (1): 294–306. doi:10.1080/07350015.2019.1654879.
Vancouver
1.
De Vos I, Everaert G. Bias-corrected common correlated effects pooled estimation in dynamic panels. JOURNAL OF BUSINESS & ECONOMIC STATISTICS. 2021;39(1):294–306.
IEEE
[1]
I. De Vos and G. Everaert, “Bias-corrected common correlated effects pooled estimation in dynamic panels,” JOURNAL OF BUSINESS & ECONOMIC STATISTICS, vol. 39, no. 1, pp. 294–306, 2021.
@article{8626934,
  abstract     = {{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.}},
  author       = {{De Vos, Ignace and Everaert, Gerdie}},
  issn         = {{0735-0015}},
  journal      = {{JOURNAL OF BUSINESS & ECONOMIC STATISTICS}},
  keywords     = {{Factor augmented regression,dynamic panel bias,Common Correlated Effects,Multifactor error structure,Statistics,Common correlated effects,Dynamic panel bias,Factor augmented regression,Multifactor error structure,CROSS-SECTIONAL DEPENDENCE,DATA MODELS,ADJUSTMENT,REGRESSION,Probability and Uncertainty,Economics and Econometrics,Statistics and Probability,Social Sciences (miscellaneous)}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{294--306}},
  title        = {{Bias-corrected common correlated effects pooled estimation in dynamic panels}},
  url          = {{http://doi.org/10.1080/07350015.2019.1654879}},
  volume       = {{39}},
  year         = {{2021}},
}
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