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Estimation of short dynamic panels in the presence of cross-sectional dependence and dynamic eterogeneity

Author

Listed:
  • Gilhooly, Robert

    (Monetary Policy Committee Unit, Bank of England)

  • Weale, Martin

    (Monetary Policy Committee Unit, Bank of England)

  • Wieladek, Tomasz

    (Monetary Policy Committee Unit, Bank of England)

Abstract

We propose a Bayesian approach to dynamic panel estimation in the presence of cross-sectional dependence and dynamic heterogeneity which is suitable for inference in short panels, unlike alternative estimators. Monte Carlo simulations indicate that our estimator produces less bias, and a lower root mean squared error, than existing estimators. The method is illustrated by estimating a panel VAR on sector level data for labour productivity and hours worked growth for Canada, Germany, France, Italy, the UK and the US from 1992 Q1 to 2011 Q3. We use historical decompositions to examine the determinants of recent output growth in each country. This exercise demonstrates that failure to take cross-sectional dependence into account leads to highly misleading results.

Suggested Citation

  • Gilhooly, Robert & Weale, Martin & Wieladek, Tomasz, 2015. "Estimation of short dynamic panels in the presence of cross-sectional dependence and dynamic eterogeneity," Discussion Papers 38, Monetary Policy Committee Unit, Bank of England.
    • Handle: RePEc:mpc:wpaper:0038
    as

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    File URL: https://www.bankofengland.co.uk/-/media/boe/files/external-mpc-discussion-paper/2013/estimation-of-short-dynamic-panels-in-the-presence
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    References listed on IDEAS

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    More about this item

    Keywords

    Bayesian dynamic panel estimator; dynamic heterogeneity; cross-sectional dependence; labour productivity.;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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