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Estimating Dynamic Random Effects Models from Panel Data Covering Short Time Periods
Alok Bhargava
J. D. Sargan
Abstract
This paper advocates the use of simultaneous equations estimators (especially LIML) to estimate dynamic random effects models from panel data. The methods are found to perform quite satisfactorily in Monte Carlo experiments. The LIML procedures are also extended to the case where some of the regressors are correlated with the effects and a theorem on identification is proved. Finally, the Michigan Panel is used for some illustrations.
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