Modelling Time-Varying Heterogeneity in Panel Data as Regime-Switching

Andrea Beccarini and Bernd Kempa

Annals of Economics and Statistics, 2023, issue 151, 81-120

Abstract: This article proposes a new method for analysing panel data based on modelling heterogeneity of individuals or entities as a regime-switching process. There are several advantages to this approach. Firstly, it enables modelling not only heterogeneity, but also "similarity" among entities. Secondly, it permits disentangling the individual observed and unobserved effects, which in classic panel data analysis must be merged. Thirdly, it does not need to specify whether or not the unobserved individual effects are correlated with some regressors - hence it does not require a distinction between fixed effect or random effect estimators. Fourthly, it allows the unobserved individual effects to be time-varying, although they do not necessarily have to be a function of time. Fifthly, the determinants of the unobserved individual effects can be specified and their importance estimated. The theoretical properties of the proposed estimators are outlined and the importance of the underlying assumptions are verified through simulations. An empirical application based on interest rate differentials is also proposed.

Keywords: Panel Data Analysis; Regime-Switching Model; EM-Algorithm; Interest Rate Differentials (search for similar items in EconPapers)
JEL-codes: C32 C33 F31 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:adr:anecst:y:2023:i:151:p:81-120

DOI: 10.2307/48744151

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