Truncated Regression In Empirical Estimation
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.
|Date of creation:||2000|
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- Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119, July.
- Geweke, John, 1989. "Exact predictive densities for linear models with arch disturbances," Journal of Econometrics, Elsevier, vol. 40(1), pages 63-86, January.
- Alice Nakamura & Masao Nakamura, 1983. "Part-Time and Full-Time Work Behaviour of Married Women: A Model with a Doubly Truncated Dependent Variable," Canadian Journal of Economics, Canadian Economics Association, vol. 16(2), pages 229-57, May.
- Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
- Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January.
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