Probit with Dependent Observations
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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|Date of creation:||01 Mar 1987|
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