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Probit with Dependent Obervations

Author

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  • Poirier, Dale J.
  • Ruud, Paul A.

Abstract

Estimation of limited dependent variable models with dependent observations has received relatively little attention due to the computational complexity of the maximum likelihood estimator. We develop a computationally attractive and relatively efficient estimator for this case that utilises the orthogonality conditions. The resulting Generalized Conditional Moment (GCM) estimators can be applied with a known or an unknown disturbance covariance matrix. Although the paper considers only the probit model, the approach is easily generalized to other limited dependent variable models.
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Suggested Citation

  • Poirier, Dale J. & Ruud, Paul A., 1987. "Probit with Dependent Obervations," Department of Economics, Working Paper Series qt04f5m9t2, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
  • Handle: RePEc:cdl:econwp:qt04f5m9t2
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