Forecasting Organic Food Prices: Testing and Evaluating Conditional Predictive Ability

dc.creatorPark, Timothy A.
dc.creatorGubanova, Tatiana
dc.creatorLohr, Luanne
dc.creatorEscalante, Cesar L.
dc.date2017-04-01T19:18:36Z
dc.date.accessioned2026-07-09T03:27:42Z
dc.descriptionOrganic farmers, wholesalers, and retailers need reliable price forecasts to improve their decision- making practices. This paper presents a methodology and protocol to select the best-performing method from several time and frequency domain candidates. Weekly farmgate prices for organic fresh produce are used. Forecasting methods are evaluated on the basis of an aggregate accuracy measure and several out-of-sample predictive ability tests. Combining forecasts to improve on individual forecasts is investigated.
dc.identifierdoi:10.22004/ag.econ.19412
dc.identifierhttps://ageconsearch.umn.edu/record/19412/files/sp05pa06.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/19412
dc.identifier.urihttp://hdl.handle.net/123456789/532942
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/19412
dc.titleForecasting Organic Food Prices: Testing and Evaluating Conditional Predictive Ability
dc.typeText

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