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Panel data analysis with heterogeneous dynamics

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  • Okui, Ryo
  • Yanagi, Takahide

Abstract

This paper proposes a model-free approach to analyze panel data with heterogeneous dynamic structures across observational units. We first compute the sample mean, autocovariances, and autocorrelations for each unit, and then estimate the parameters of interest based on their empirical distributions. We then investigate the asymptotic properties of our estimators using double asymptotics and propose split-panel jackknife bias correction and inference based on the cross-sectional bootstrap. We illustrate the usefulness of our procedures by studying the deviation dynamics of the law of one price. Monte Carlo simulations confirm that the proposed bias correction is effective and yields valid inference in small samples.

Suggested Citation

  • Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
    • Handle: RePEc:eee:econom:v:212:y:2019:i:2:p:451-475
    DOI: 10.1016/j.jeconom.2019.04.036
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    Cited by:

    1. Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
    2. Artūras Juodis & Simas Kučinskas, 2023. "Quantifying noise in survey expectations," Quantitative Economics, Econometric Society, vol. 14(2), pages 609-650, May.
    3. Ryo Okui & Takahide Yanagi, 2020. "Kernel estimation for panel data with heterogeneous dynamics," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 156-175.
    4. Jochmans, Koen & Weidner, Martin, 2024. "Inference On A Distribution From Noisy Draws," Econometric Theory, Cambridge University Press, vol. 40(1), pages 60-97, February.
    5. Ivan Fernandez-Val & Wayne Yuan Gao & Yuan Liao & Francis Vella, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," Papers 2202.04154, arXiv.org, revised Jan 2023.
    6. Yazgan, M. Ege & Yilmazkuday, Hakan, 2011. "Price-level convergence: New evidence from U.S. cities," Economics Letters, Elsevier, vol. 110(2), pages 76-78, February.
    7. St'ephane Bonhomme & Martin Weidner, 2019. "Posterior Average Effects," Papers 1906.06360, arXiv.org, revised Sep 2021.
    8. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    9. Ryo Okui, 2017. "Misspecification in Dynamic Panel Data Models and Model-Free Inferences," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 283-304, September.
    10. Hoskins, Stephen & Johnston, David W. & Kunz, Johannes S. & Shields, Michael A. & Staub, Kevin E., 2024. "Heterogeneity in the Persistence of Health: Evidence from a Monthly Micro Panel," IZA Discussion Papers 17023, Institute of Labor Economics (IZA).
    11. Laurent Barras & Patrick Gagliardini & Olivier Scaillet, 2022. "Skill, Scale, and Value Creation in the Mutual Fund Industry," Journal of Finance, American Finance Association, vol. 77(1), pages 601-638, February.

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    More about this item

    Keywords

    Panel data; Heterogeneity; Functional central limit theorem; Jackknife; Bootstrap;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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