Data/hora: 08/06/2024 18:40:19

Provedor de dados: | 31
País: | United States
Título: | MELE: MAXIMUM ENTROPY LEUVEN ESTIMATORS
Autores: | Paris,   Quirino.
Data: | 2001-08-15
Ano: | 2001
Palavras-chave: | Multicollinearity; Mean squared error; Ordinary least squares; Generalized maximum entropy; Research Methods/ Statistical Methods; C2.
Resumo: | Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls of their own. The ridge estimator is not generally accepted as a vital alternative to the ordinary least-squares (OLS) estimator because it depends upon unknown parameters. The generalized maximum entropy (GME) estimator of Golan, Judge and Miller depends upon subjective exogenous information that affects the estimated parameters in an unpredictable way.  This paper presents novel maximum entropy estimators inspired by the theory of light that do not depend upon any additional information. Monte Carlo experiments show that they are not affected by any level of multicollinearity and dominate OLS uniformly. The Leuven estimators are consistent and asymptotically normal.
Tipo: | Working or Discussion Paper
Idioma: | Inglês

Identificador:

3425

http://purl.umn.edu/11991

Editor: | AgEcon Search

Relação:

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

Working Paper 01-003

Formato:

34

application/pdf