description- – This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of the coefficients in the truncated regression model. The distribution of the errors is unknown and permits general forms of unknown heteroscedasticity. Also provided is an instrumental variables based two stage least squares estimator for this model, which can be used when the errors are correlated with some regressors. Estimation is based on a 'special' regressor as in Lewbel (2000). Our limiting distributions include a new result regarding asymptotic trimming for root-n convegence of density weighed extremum estimators.
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