Juarez, Miguel A. and Steel, Mark F. J. (2006): Modelbased Clustering of nonGaussian Panel Data.

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Abstract
In this paper we propose a modelbased method to cluster units within a panel. The underlying model is autoregressive and nonGaussian, allowing for both skewness and fat tails, and the units are clustered according to their dynamic behaviour and equilibrium level. Inference is addressed from a Bayesian perspective and model comparison is conducted using the formal tool of Bayes factors. Particular attention is paid to prior elicitation and posterior propriety. We suggest priors that require little subjective input from the user and possess hierarchical structures that enhance the robustness of the inference. Two examples illustrate the methodology: one analyses economic growth of OECD countries and the second one investigates employment growth of Spanish manufacturing firms
Item Type:  MPRA Paper 

Institution:  University of Warwick 
Original Title:  Modelbased Clustering of nonGaussian Panel Data 
Language:  English 
Keywords:  autoregressive modelling; employment growth; GDP growth convergence; hierarchical prior; model comparison; posterior propriety; skewness 
Subjects:  C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C23  Panel Data Models ; Spatiotemporal Models C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C11  Bayesian Analysis: General 
Item ID:  880 
Depositing User:  Miguel A. Juarez 
Date Deposited:  21 Nov 2006 
Last Modified:  28 Sep 2019 04:36 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/880 