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Multidimensional Parameter Heterogeneity in Panel Data Models

Timothy Neal ()

No 2016-15, Discussion Papers from School of Economics, The University of New South Wales

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.

Keywords: Panel Data; parameter heterogeneity; dynamic panels; estimation (search for similar items in EconPapers)
JEL-codes: C13 C22 C23 C33 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2016-10
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http://research.economics.unsw.edu.au/RePEc/papers/2016-15.pdf (application/pdf)

Related works:
Working Paper: Multidimensional Parameter Heterogeneity in Panel Data Models (2018) Downloads
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