Identification and decompositions in probit and logit models
| Autor: | Ronald L. Oaxaca, SeEun Jung, Chung Choe |
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| Rok vydání: | 2019 |
| Předmět: |
Statistics and Probability
Economics and Econometrics 05 social sciences Logit Ordered probit Probit Multivariate probit model Mathematics (miscellaneous) Mixed logit Probit model 0502 economics and business Statistics Econometrics Multinomial probit 050207 economics Latent variable model Social Sciences (miscellaneous) 050205 econometrics Mathematics |
| Zdroj: | Empirical Economics. 59:1479-1492 |
| ISSN: | 1435-8921 0377-7332 |
| Popis: | Probit and logit models typically require a normalization on the error variance for model identification. This paper shows that in the context of sample mean probability decompositions, error variance normalizations preclude estimation of the effects of group differences in the latent variable model parameters. An empirical example is provided for a model in which the error variances are identified. This identification allows the effects of group differences in the latent variable model parameters to be estimated. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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