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Provedor de dados:  AgEcon
País:  United States
Título:  FORECASTING AGRICULTURAL COMMODITY PRICES WITH LIMITED DATA SETS
Autores:  Jacque, Andrew Eliel
Data:  2003-06-10
Ano:  1991
Palavras-chave:  Demand and Price Analysis
Resumo:  Many developing countries wish to, but do not publish forecasts of commodity prices. One difficulty often cited is the length (shortness) of the data series. This study tried to determine whether this was a valid reason. Price data for two commodities in a specific country, where the problem is acknowledged were utilized in a case study approach. Existing models were evaluated for applicability to the data series. The identified models were estimated with estimation data and then while keeping the model parameters constant, prices were forecasted in the out-of-sample period. The error associated with the forecast of each model was calculated and the relationship between quantity of data and model accuracy evaluated. The error values of all the models were high. The results of the analyses were inconclusive in terms of the study objectives.
Tipo:  Thesis or Dissertation
Idioma:  Inglês
Identificador:  9525

http://purl.umn.edu/10998
Editor:  AgEcon Search
Relação:  Michigan State University>Department of Agricultural Economics>Graduate Research Master's Degree Plan B Papers
Graduate Research Master's Degree Plan B Papers
Formato:  157

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