Juarez, Miguel A. and Steel, Mark F. J. (2006): NonGaussian dynamic Bayesian modelling for panel data.

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Abstract
A first order autoregressive nonGaussian 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.
Item Type:  MPRA Paper 

Original Title:  NonGaussian dynamic Bayesian modelling for panel data 
Language:  English 
Keywords:  autoregressive modelling; growth convergence; individual effects; labour earnings; prior elicitation; posterior existence; skewed distributions 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C11  Bayesian Analysis: General C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C23  Panel Data Models ; Spatiotemporal Models 
Item ID:  450 
Depositing User:  Miguel A. Juarez 
Date Deposited:  15. Oct 2006 
Last Modified:  20. Feb 2013 02:33 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/450 