FORECASTING AGRICULTURAL COMMODITY PRICES WITH LIMITED DATA SETS

Andrew Eliel Jacque

No 10998, Graduate Research Master's Degree Plan B Papers from Michigan State University, Department of Agricultural, Food, and Resource Economics

Abstract: Many developing countries wish to, but do not publish forecasts of commodity prices.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.

Keywords: Demand; and; Price; Analysis (search for similar items in EconPapers)
Pages: 157
Date: 1991
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/10998/files/pb91ja01.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:midagr:10998

DOI: 10.22004/ag.econ.10998

Access Statistics for this paper

More papers in Graduate Research Master's Degree Plan B Papers from Michigan State University, Department of Agricultural, Food, and Resource Economics Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().