Bell, A. and Jones, K. (2014) Explaining Fixed Effects: Random Effects modelling of Time-Series Cross-Sectional and Panel Data. Political Science Research and Methods, 3 (1). 133 - 153. ISSN 2049-8470
Abstract
This article challenges Fixed Effects (FE) modelling as the ‘default’ for time-series-cross-sectional and panel data. Understanding different within- and between-effects is crucial when choosing modelling strategies. The downside of Random Effects (RE) modelling – correlated lower-level covariates and higher-level residuals – is omitted-variable bias, solvable with Mundlak’s (1978a) formulation. Consequently, RE can provide everything FE promises and more, as confirmed by Monte-Carlo simulations, which additionally show problems with Plümper and Troeger’s FE Vector Decomposition method when data are unbalanced. As well as incorporating time-invariant variables, RE models are readily extendable, with random coefficients, cross-level interactions, and complex variance functions. We argue not simply for technical solutions to endogeneity, but the substantive importance of context/heterogeneity, modelled using RE. The implications extend beyond political science, to all multilevel datasets. However, omitted variables could still bias estimated higher-level variable effects; as with any model, care is required in interpretation.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The European Political Science Association 2014. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 27 Oct 2015 14:36 |
Last Modified: | 23 Jun 2023 21:52 |
Published Version: | https://doi.org/10.1017/psrm.2014.7 |
Status: | Published |
Publisher: | Cambridge University Press |
Refereed: | Yes |
Identification Number: | 10.1017/psrm.2014.7 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:89757 |