TRUNCATED REGRESSION IN EMPIRICAL ESTIMATION
Thomas Marsh and
Ron Mittelhammer ()
No 36391, 2000 Annual Meeting, June 29-July 1, 2000, Vancouver, British Columbia from Western Agricultural Economics Association
In 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.
Keywords: doubly truncated samples; Bayesian regression; maximum entropy; wheat-by-class; Research Methods/ Statistical Methods (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:waeava:36391
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