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Multidimensional Parameter Heterogeneity in Panel Data Models

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  • Timothy Neal

    (School of Economics, UNSW Business School, UNSW)

Abstract

This article introduces an approach to estimation for static or dynamic panel data models that feature intercept and slope heterogeneity across individuals and over time. It is able to estimate each individual observation coefficient as well as the average coefficient over the sample, and allows for correlation between the heterogeneity and the regressors. Asymptotic theory establishes the consistency and asymptotic normality of the estimates as N and T jointly go to infinity. Finally, Monte Carlo simulations demonstrate that the estimator performs well in environments where fixed effects and mean group estimators are inconsistent and severely biased.

Suggested Citation

  • Timothy Neal, 2016. "Multidimensional Parameter Heterogeneity in Panel Data Models," Discussion Papers 2016-15, School of Economics, The University of New South Wales.
    • Handle: RePEc:swe:wpaper:2016-15
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    File URL: http://research.economics.unsw.edu.au/RePEc/papers/2016-15.pdf
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    References listed on IDEAS

    as
    1. Hsiao, C. & Pesaran, M.H., 2004. "‘Random Coefficient Panel Data Models’," Cambridge Working Papers in Economics 0434, Faculty of Economics, University of Cambridge.
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    6. Hsiao, Cheng, 1975. "Some Estimation Methods for a Random Coefficient Model," Econometrica, Econometric Society, vol. 43(2), pages 305-325, March.
    7. Degui Li & Jia Chen & Jiti Gao, 2011. "Non‐parametric time‐varying coefficient panel data models with fixed effects," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 387-408, October.
    8. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    9. Timothy Neal & Michael Keane, 2018. "The Impact of Climate Change on U.S. Agriculture: The Roles of Adaptation Techniques and Emissions Reductions," Discussion Papers 2018-08, School of Economics, The University of New South Wales.
    10. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
    11. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    12. Harding, Matthew & Lamarche, Carlos, 2011. "Least squares estimation of a panel data model with multifactor error structure and endogenous covariates," Economics Letters, Elsevier, vol. 111(3), pages 197-199, June.
    13. Pesaran, M. Hashem, 2015. "Time Series and Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780198759980.
    14. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    15. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.
    16. Mesters, G. & Koopman, S.J., 2014. "Generalized dynamic panel data models with random effects for cross-section and time," Journal of Econometrics, Elsevier, vol. 180(2), pages 127-140.
    17. Cooley, Thomas F & Prescott, Edward C, 1976. "Estimation in the Presence of Stochastic Parameter Variation," Econometrica, Econometric Society, vol. 44(1), pages 167-184, January.
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    19. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
    20. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    21. 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.
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    Cited by:

    1. Michael Keane & Timothy Neal, 2017. "The Impact of Climate Change on U.S. Agriculture: New Evidence on the Role of Heterogeneity and Adaptation," Economics Papers 2017-W03, Economics Group, Nuffield College, University of Oxford.
    2. Timothy Neal & Michael Keane, 2018. "The Impact of Climate Change on U.S. Agriculture: The Roles of Adaptation Techniques and Emissions Reductions," Discussion Papers 2018-08, School of Economics, The University of New South Wales.

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    More about this item

    Keywords

    Panel Data; parameter heterogeneity; dynamic panels; estimation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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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