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Moment Conditions for Dynamic Panel Data Models with Multiplicative Individual Effects in the Conditional Variance

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  • Costas Meghir
  • Frank Windmeijer

Abstract

Moment conditions are derived for dynamic linear panel data models with linear individual specific effects in the mean and multiplicative individual effects in the conditional ARCH type variance function. The relation and correlation between the linear and multiplicative effects are unrestrained. Moment conditions are derived for non-autocorrelated error processes, MA(q) processes, and for models that allow for time varying parameters on both the linear mean effects and multiplicative variance effects. The small sample performance of a GMM estimator is investigated in a Monte Carlo simulation study.

Suggested Citation

  • Costas Meghir & Frank Windmeijer, 1999. "Moment Conditions for Dynamic Panel Data Models with Multiplicative Individual Effects in the Conditional Variance," Annals of Economics and Statistics, GENES, issue 55-56, pages 317-330.
    • Handle: RePEc:adr:anecst:y:1999:i:55-56:p:317-330
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    References listed on IDEAS

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    1. Wooldridge, Jeffrey M., 1997. "Multiplicative Panel Data Models Without the Strict Exogeneity Assumption," Econometric Theory, Cambridge University Press, vol. 13(5), pages 667-678, October.
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    5. repec:cup:etheor:v:13:y:1997:i:5:p:667-78 is not listed on IDEAS
    6. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    7. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    8. Chamberlain, Gary, 1992. "Sequential Moment Restrictions in Panel Data: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 20-26, January.
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    Cited by:

    1. Costas Meghir & Luigi Pistaferri, 2004. "Income Variance Dynamics and Heterogeneity," Econometrica, Econometric Society, vol. 72(1), pages 1-32, January.
    2. L. Hospido, 2012. "Modelling heterogeneity and dynamics in the volatility of individual wages," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(3), pages 386-414, April.
    3. Botosaru, Irene, 2023. "Time-varying unobserved heterogeneity in earnings shocks," Journal of Econometrics, Elsevier, vol. 235(2), pages 1378-1393.
    4. Lee, Yoon-Jin, 2014. "Testing a linear dynamic panel data model against nonlinear alternatives," Journal of Econometrics, Elsevier, vol. 178(P1), pages 146-166.
    5. Irene Botosaru, 2017. "Identifying Distributions in a Panel Model with Heteroskedasticity: An Application to Earnings Volatility," Discussion Papers dp17-11, Department of Economics, Simon Fraser University.
    6. Chihwa Kao & Yongmiao Hong, 2004. "Detecting Neglected Nonlinearity in Dynamic Panel Data with Time-Varying Conditional Heteroskedasticity," Econometric Society 2004 Far Eastern Meetings 753, Econometric Society.

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    More about this item

    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

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