A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model
This paper uses information theoretic methods to introduce a new class of probability distributions and estimators for competing explanations of the data in the binary choice model. No explicit parameterization of the function connecting the data to the Bernoulli probabilities is stated in the sp...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Econometric Research Association
2009-04-01
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| Series: | International Econometric Review |
| Online Access: | http://www.era.org.tr/makaleler/6010030.pdf |
| _version_ | 1797923463681277952 |
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| author | Ron Mittelhammer George Judge |
| author_facet | Ron Mittelhammer George Judge |
| author_sort | Ron Mittelhammer |
| collection | DOAJ |
| description | This paper uses information theoretic methods to introduce a new class of probability
distributions and estimators for competing explanations of the data in the binary choice
model. No explicit parameterization of the function connecting the data to the Bernoulli
probabilities is stated in the specification of the statistical model. A large class of
probability density functions emerges including the conventional logit model. The new
class of statistical models and estimators requires minimal a priori model structure and
non-sample information, and provides a range of model and estimator extensions. An
empirical example is included to reflect the applicability of these methods. |
| first_indexed | 2024-04-10T14:46:41Z |
| format | Article |
| id | doaj.art-38c9e732328c47879420fdaf3b4848c0 |
| institution | Directory Open Access Journal |
| issn | 1308-8793 1308-8815 |
| language | English |
| last_indexed | 2024-04-10T14:46:41Z |
| publishDate | 2009-04-01 |
| publisher | Econometric Research Association |
| record_format | Article |
| series | International Econometric Review |
| spelling | doaj.art-38c9e732328c47879420fdaf3b4848c02023-02-15T16:07:51ZengEconometric Research AssociationInternational Econometric Review1308-87931308-88152009-04-01113349A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice ModelRon Mittelhammer0George Judge1Regents Professor of Economic Sciences and Statistics, Washington State UniversityUniversity of CaliforniaThis paper uses information theoretic methods to introduce a new class of probability distributions and estimators for competing explanations of the data in the binary choice model. No explicit parameterization of the function connecting the data to the Bernoulli probabilities is stated in the specification of the statistical model. A large class of probability density functions emerges including the conventional logit model. The new class of statistical models and estimators requires minimal a priori model structure and non-sample information, and provides a range of model and estimator extensions. An empirical example is included to reflect the applicability of these methods.http://www.era.org.tr/makaleler/6010030.pdf |
| spellingShingle | Ron Mittelhammer George Judge A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model International Econometric Review |
| title | A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model |
| title_full | A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model |
| title_fullStr | A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model |
| title_full_unstemmed | A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model |
| title_short | A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model |
| title_sort | minimum power divergence class of cdfs and estimators for the binary choice model |
| url | http://www.era.org.tr/makaleler/6010030.pdf |
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