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Estimation of heterogeneous panels with systematic slope variations

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  • Breitung, Jörg
  • Salish, Nazarii

Abstract

We analyse estimation procedures for the panel data models with heterogeneous slopes. Specifically we take into account a possible dependence between regressors and heterogeneous slope coefficients, which is referred to as systematic variation. It is shown that under relevant forms of systematic slope variations (i) the pooled OLS estimator is severely biased, (ii) Swamy’s GLS estimator is inconsistent if the number of time periods T is fixed, whereas (iii) the mean-group estimator always provides consistent estimators at the risk of high variances. Following Mundlak (1978) we propose an augmentated regression which results in a simple and robust version of the pooled estimator. The latter approach avoids the risk of large standard errors of the mean-group estimator, whenever T is small. We also propose two test statistics for systematic slope variation using the Lagrange multiplier and Hausman principles. We derive their asymptotic properties and provide a local power analysis of both test statistics. Monte Carlo experiments corroborate our theoretical findings and show that for all combinations of N and T the Mundlak-type GLS estimator outperform all other estimators.

Suggested Citation

  • Breitung, Jörg & Salish, Nazarii, 2021. "Estimation of heterogeneous panels with systematic slope variations," Journal of Econometrics, Elsevier, vol. 220(2), pages 399-415.
    • Handle: RePEc:eee:econom:v:220:y:2021:i:2:p:399-415
    DOI: 10.1016/j.jeconom.2020.04.007
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    More about this item

    Keywords

    Panel data; Random effects; Slope heterogeneity;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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