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Panel Data Dynamics and Measurement Errors: GMM Bias, IV Validity and Model Fit – A Monte Carlo Study

Author

Listed:
  • Biørn, Erik

    (Dept. of Economics, University of Oslo)

  • Han, Xuehui

    (Fudan University)

Abstract

An autoregressive fixed effects panel data equation in error-ridden endogenous and exogenous variables, with finite memory of disturbances, latent regressors and measurement errors is considered. Finite sample properties of GMM estimators are explored by Monte Carlo (MC) simulations. Two kinds of estimators are compared with respect to bias, instrument (IV) validity and model fit: equation in differences/IVs levels, equation in levels/IVs in differences. We discuss the impact on estimators’ bias and other properties of their distributions of changes in the signal-noise variance ratio, the length of the signal and noise memory, the strength of autocorrelation, the size of the IV set, and the panel length. Finally, some practical guidelines are provided.

Suggested Citation

  • Biørn, Erik & Han, Xuehui, 2012. "Panel Data Dynamics and Measurement Errors: GMM Bias, IV Validity and Model Fit – A Monte Carlo Study," Memorandum 27/2012, Oslo University, Department of Economics.
    • Handle: RePEc:hhs:osloec:2012_027
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    References listed on IDEAS

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    More about this item

    Keywords

    Panel data; Measurement error; ARMA model; GMM; Signal-noise ratio; Error memory; IV validity; Monte Carlo simulation; Finite sample bias;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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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