Truncated Regression In Empirical Estimation
AbstractIn this paper we illustrate the use of alternative truncated regression estimators for the general linear model. These include variations of maximum likelihood, Bayesian, and maximum entropy estimators in which the error distributions are doubly truncated. To evaluate the performance of the estimators (e.g., efficiency) for a range of sample sizes, Monte Carlo sampling experiments are performed. We then apply each estimator to a factor demand equation for wheat-by-class.
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Bibliographic InfoPaper provided by Western Agricultural Economics Association in its series 2000 Annual Meeting, June 29-July 1, 2000, Vancouver, British Columbia with number 36391.
Date of creation: 2000
Date of revision:
doubly truncated samples; Bayesian regression; maximum entropy; wheat-by-class; Research Methods/ Statistical Methods;
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