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Estimation methods in panel data models with observed and unobserved components: a Monte Carlo study

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  • Castagnetti, Carolina
  • Rossi, Eduardo

Abstract

Recently some new techniques have been proposed for the estimation of the slope coefficients in presence of unobserved components. Though, the presence of common observed and unobserved factors is neither considered or the estimation of their impacts is not taken into account. In this work a range of estimators is surveyed and their finite-sample properties are examined by means of Monte Carlo experiments. We consider both the properties of estimators for the individual specific components and for the observed common effects.

Suggested Citation

  • Castagnetti, Carolina & Rossi, Eduardo, 2008. "Estimation methods in panel data models with observed and unobserved components: a Monte Carlo study," MPRA Paper 26196, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:26196
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    File URL: https://mpra.ub.uni-muenchen.de/26196/1/MPRA_paper_26196.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    factor error structure; principal component; common regressors; cross-section dependence; large panels; Monte Carlo simulations.;

    JEL classification:

    • 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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