Journal article
Is the minimum chi-square estimator the winner in logit regression?
Journal of econometrics, Vol.61(2), pp.345-366
04/01/1994
DOI: 10.1016/0304-4076(94)90089-2
Abstract
Amemiya (1980) showed that the bias-corrected maximum likelihood estimator has a smaller n
-order MSE matrix than minimum chi-square in a general logit model. In this paper the exact MSE is calculated for both estimators for Berkson's (1995) examples. The bias-corrected maximum likelihood has a smaller exact MSE provided that Berkson's 2n-rule is used in the calculation of the exact results. The margin by which the exact MSE of minimum chi-square exceeds that of bias-corrected maximum likelihood is small, and hence there may be no practical advantage in using the latter estimator. © 1994.
Details
- Title: Subtitle
- Is the minimum chi-square estimator the winner in logit regression?
- Creators
- Gordon A. Hughes - World BankN. E. Savin - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of econometrics, Vol.61(2), pp.345-366
- DOI
- 10.1016/0304-4076(94)90089-2
- ISSN
- 0304-4076
- eISSN
- 1872-6895
- Number of pages
- 22
- Grant note
- USDA-Forest Servtce PSW-86-0012CA / Department of Economics
- Language
- English
- Date published
- 04/01/1994
- Academic Unit
- Economics
- Record Identifier
- 9984963210002771
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