Data/hora: 10/06/2024 17:59:35

Provedor de dados: | 31
País: | United States
Título: | FORECASTING LIMITED DEPENDENT VARIABLES:  BETTER STATISTICS FOR BETTER STEAKS
Autores: | Lusk,   Jayson L.; Norwood,   F. Bailey; Brorsen,   B. Wade.
Data: | 2003-12-29
Ano: | 2003
Palavras-chave: | Research Methods/ Statistical Methods.
Resumo: | Little research has been conducted on evaluating out-of-sample forecasts of limited dependent variables.  This study describes the large and small sample properties of two forecast evaluation techniques for limited dependent variables: receiver-operator curves and out-of-sample-log-likelihood functions.  The methods are shown to provide identical model rankings in large samples and similar rankings in small samples.  The likelihood function method is slightly better at detecting forecast accuracy in small samples, while receiver-operator curves are better at comparing forecasts across different data.  By improving forecasts of fed-cattle quality grades, the forecast evaluation methods are shown to increase cattle marketing revenues by $2.59/head.
Tipo: | Conference Paper or Presentation
Idioma: | Inglês

Identificador:

11793

http://purl.umn.edu/34612

Editor: | AgEcon Search

Relação:

Southern Agricultural Economics Association&gt;2004 Annual Meeting, February 14-18, 2004, Tulsa, Oklahoma

Selected Paper

Formato:

20

application/pdf