Testing for Autocorrelation in Dynamic Random Effects Models

نویسنده

  • MANUEL ARELLANO
چکیده

This article develops tests of covariance restrictions after estimating by three-stage least squares a dynamic random effects model from panel data. The asymptotic distribution of covariance matrix estimates under non-normality is obtained. It is shown how minimum chi-square tests for interesting covariance restrictions can be calculated from a generalised linear regression involving the sample autocovariances and dummy variables. Asymptotic efficiency exploiting covariance restrictions can also be attained using a GLS estimator.

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تاریخ انتشار 2007