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Fixed and Random Effects in Classical and Bayesian Regression

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  • Silvio R. Rendon

Abstract

This paper proposes a common and tractable framework for analyzing different definitions of fixed and random effects in a constant-slope variable-intercept model. It is shown that, regardless of whether effects (i) are treated as parameters or as an error term, (ii) are estimated in different stages of a hierarchical model, or whether (iii) correlation between effects and regressor is allowed, when the same information on effects is introduced into all estimation methods, the resulting slope estimator is also the same across methods. If different methods produce different results, is is ultimately because different information is being used for each method.
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Suggested Citation

  • Silvio R. Rendon, 2013. "Fixed and Random Effects in Classical and Bayesian Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(3), pages 460-476, June.
    • Handle: RePEc:bla:obuest:v:75:y:2013:i:3:p:460-476
    DOI: 10.1111/obes.2013.75.issue-3
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    Cited by:

    1. Huth, K.B.S. & van der Wal, J. & Zavlis, O. & Luigjes, J. & Lakerveld, J. & Galenkamp, H. & Lok, A. & Stronks, K. & Bockting, C.L. & Marsman, M. & Goudriaan, A.E. & van Holst, R.J., 2025. "Individual and neighborhood determinants of depressive symptoms in ethnic minorities in the urban HELIUS sample: a multi-level network perspective," Social Science & Medicine, Elsevier, vol. 381(C).
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    4. Baltagi, Badi H. & Bresson, Georges & Chaturvedi, Anoop & Lacroix, Guy, 2018. "Robust linear static panel data models using ε-contamination," Journal of Econometrics, Elsevier, vol. 202(1), pages 108-123.
    5. Laia Maynou & Bruce Morley & Mercedes Monfort & Javier Ordóñez, 2020. "House price convergence Across Europe," Working Papers 2020/07, Economics Department, Universitat Jaume I, Castellón (Spain).
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    10. Laia Maynou & Marc Saez & Jordi Bacaria & Guillem Lopez-Casasnovas, 2015. "Health inequalities in the European Union: an empirical analysis of the dynamics of regional differences," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(5), pages 543-559, June.
    11. Jaeho Kim & Le Wang, 2019. "Hidden group patterns in democracy developments: Bayesian inference for grouped heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 1016-1028, September.
    12. Burda, Martin & Harding, Matthew & Hausman, Jerry, 2012. "A Poisson mixture model of discrete choice," Journal of Econometrics, Elsevier, vol. 166(2), pages 184-203.
    13. Han, Xiaoyi & Hsieh, Chih-Sheng & Lee, Lung-fei, 2017. "Estimation and model selection of higher-order spatial autoregressive model: An efficient Bayesian approach," Regional Science and Urban Economics, Elsevier, vol. 63(C), pages 97-120.
    14. Baltagi, Badi H. & Bresson, Georges & Chaturvedi, Anoop & Lacroix, Guy, 2014. "Robust linear static panel data models using epsilon-contamination," MPRA Paper 59896, University Library of Munich, Germany.
    15. Rammer, Christian, 2023. "Measuring process innovation output in firms: Cost reduction versus quality improvement," Technovation, Elsevier, vol. 124(C).
    16. Chih‐Sheng Hsieh & Lung‐Fei Lee & Vincent Boucher, 2020. "Specification and estimation of network formation and network interaction models with the exponential probability distribution," Quantitative Economics, Econometric Society, vol. 11(4), pages 1349-1390, November.
    17. Shobande, Olatunji A., 2023. "Rethinking social change: Does the permanent and transitory effects of electricity and solid fuel use predict health outcome in Africa?," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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