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Non-Gaussian dynamic Bayesian modelling for panel data

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Author Info
Juarez, Miguel A.
Steel, Mark F. J.

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Abstract

A first order autoregressive non-Gaussian model for analysing panel data is proposed. The main feature is that the model is able to accommodate fat tails and also skewness, thus allowing for outliers and asymmetries. The modelling approach is to gain sufficient flexibility, without sacrificing interpretability and computational ease. The model incorporates individual effects and we pay specific attention to the elicitation of the prior. As the prior structure chosen is not proper, we derive conditions for the existence of the posterior. By considering a model with individual dynamic parameters we are also able to formally test whether the dynamic behaviour is common to all units in the panel. The methodology is illustrated with two applications involving earnings data and one on growth of countries.

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File URL: http://mpra.ub.uni-muenchen.de/450/
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 450.

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Date of creation: Jul 2006
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Handle: RePEc:pra:mprapa:450

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Related research
Keywords: autoregressive modelling growth convergence individual effects labour earnings prior elicitation posterior existence skewed distributions

Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data

This paper has been announced in the following NEP Reports:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    Other versions:
  2. Fern ndez, Carmen & Steel, Mark F.J., 2000. "Bayesian Regression Analysis With Scale Mixtures Of Normals," Econometric Theory, Cambridge University Press, vol. 16(01), pages 80-101, February. [Downloadable!]
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    Other versions:
  4. Lee, Michael, et al, 1998. "Growth Convergence: Some Panel Data Evidence," Applied Economics, Taylor and Francis Journals, vol. 30(7), pages 907-12, July. [Downloadable!] (restricted)
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    Other versions:
  11. Liu, Lon-Mu & Tiao, George C., 1980. "Random coefficient first-order autoregressive models," Journal of Econometrics, Elsevier, vol. 13(3), pages 305-325, August. [Downloadable!] (restricted)
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  13. Keisuke Hirano, 2002. "Semiparametric Bayesian Inference in Autoregressive Panel Data Models," Econometrica, Econometric Society, vol. 70(2), pages 781-799, March. [Downloadable!] (restricted)
  14. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July. [Downloadable!] (restricted)
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  19. Tsung-Wu Ho, 2006. "Income Thresholds And Growth Convergence: A Panel Data Approach," Manchester School, University of Manchester, vol. 74(2), pages 170-189, 03. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Juarez, Miguel A. & Steel, Mark F. J., 2006. "Model-based Clustering of non-Gaussian Panel Data," MPRA Paper 880, University Library of Munich, Germany. [Downloadable!]
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