Panel data analysis with heterogeneous dynamics

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...

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Bibliographic Details
Published in:Journal of econometrics 2019-10, Vol.212 (2), p.451-475
Main Authors: Okui, Ryo, Yanagi, Takahide
Format: Article
Language:English
Subjects:
Asymptotic methods
Bias
Bootstrap
Bootstrap method
Correlation analysis
Deviation
Econometrics
Functional central limit theorem
Heterogeneity
Jackknife
Longitudinal studies
Panel data
Usefulness
Variances
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Summary: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.
ISSN:0304-4076
1872-6895
DOI:10.1016/j.jeconom.2019.04.036