Panel Regression with Unobserved Classes
AbstractWe 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.
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Bibliographic InfoPaper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 353.
Length: 19 pages
Date of creation: 24 Jan 2000
Date of revision:
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Panel data; Bayesian statistics;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
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