Data/hora: 06/06/2024 11:47:34

Provedor de dados: | 31
País: | United States
Título: | A Minimum Power Divergence Class of CDFs and Estimators for Binary Choice Models
Autores: | Mittelhammer,   Ronald C.; Judge,   George G.
Data: | 2008-07-08
Ano: | 2008
Palavras-chave: | Binary choice models and estimators; Conditional moment equations; Squared error loss; Cressie-Read statistic; Information theoretic methods; Minimum power divergence; Research Methods/ Statistical Methods.
Resumo: | The Cressie-Read (CR) family of power divergence measures is used to identify a new class of statistical models and estimators for competing explanations of the data in binary choice models. A large flexible class of cumulative distribution functions and associated probability density functions emerge that subsumes the conventional logit model, and forms the basis for a large set of estimation alternatives to traditional logit and probit methods. Asymptotic properties of estimators are identified, and sampling experiments are used to provide a basis for gauging the finite sample performance of the estimators in this new class of statistical models.
Tipo: | Working or Discussion Paper
Idioma: | Inglês
Identificador: | http://purl.umn.edu/37759

Relação:

University of California, Berkeley&gt;Department of Agricultural and Resource Economics&gt;CUDARE Working Papers

CUDARE Working Papers

1059

Formato: | 31