Poor identification and estimation problems in panel data models with random effects and autocorrelated errors
AbstractA dramatically large number of corner solutions occur when estimating by (Gaussian) maximum likelihood a simple model for panel data with random effects and autocorrelated errors. This can invalidate results of applications to panel data with a short time dimension, even in a correctly specified model. We explain this unpleasant effect (usually underestimated, almost ignored in the literature) showing that the expected log-likelihood is nearly flat, thus rising problems of poor identification.
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Bibliographic InfoPaper provided by University of Verona, Department of Economics in its series Working Papers with number 53.
Date of creation: Jan 2009
Date of revision:
panel data; maximum likelihood; identification.;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
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