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Panel Regression with Unobserved Classes

Mickael Salabasis () and Mattias Villani
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Mickael Salabasis: UC AB, Postal: Analyssektionen, SE-117 88 Stockholm, Sweden

Authors registered in the RePEc Author Service: Mickael Bäckman ()

No 353, SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics

Abstract: We propose a panel regression model with a predetermined and fixed number of classes, where each class is defined by its parameters, but any reference as to which group any observation belongs to is absent. The classes or groups are rationalized by a willingness to attribute some of the observed heterogeneity on a higher level than the individual. The estimation procedures have a distinct Bayesian flavor, relying on the Gibbs sampler for parameter estimation, a method proven effective in situations with missing or latent variables.

Keywords: Panel data; Bayesian statistics (search for similar items in EconPapers)
JEL-codes: C11 C33 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2000-01-24
New Economics Papers: this item is included in nep-ecm
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