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Stein-like Shrinkage Estimation of Panel Data Models with Common Correlated Effects

In: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A

Author

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  • Bai Huang
  • Tae-Hwy Lee
  • Aman Ullah

Abstract

This chapter examines the asymptotic properties of the Stein-type shrinkage combined (averaging) estimation of panel data models. We introduce a combined estimation when the fixed effects (FE) estimator is inconsistent due to endogeneity arising from the correlated common effects in the regression error and regressors. In this case, the FE estimator and the CCEP estimator of Pesaran (2006) are combined. This can be viewed as the panel data model version of the shrinkage to combine the OLS and 2SLS estimators as the CCEP estimator is a 2SLS or control function estimator that controls for the endogeneity arising from the correlated common effects. The asymptotic theory, Monte Carlo simulation, and empirical applications are presented. According to our calculation of the asymptotic risk, the Stein-like shrinkage estimator is more efficient estimation than the CCEP estimator.

Suggested Citation

  • Bai Huang & Tae-Hwy Lee & Aman Ullah, 2019. "Stein-like Shrinkage Estimation of Panel Data Models with Common Correlated Effects," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 249-274, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-90532019000040a011
    DOI: 10.1108/S0731-90532019000040A011
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    More about this item

    Keywords

    Endogeneity; panel data; fixed effect; common correlated effects; shrinkage; model averaging; local asymptotics; Hausman test; C13; C33; C52;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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