Forecasting Organic Food Prices: Emerging Methods for Testing and Evaluating Conditional Predictive Ability
| dc.creator | Gubanova, Tatiana | |
| dc.creator | Lohr, Luanne | |
| dc.creator | Park, Timothy A. | |
| dc.date | 2017-04-01T19:39:25Z | |
| dc.date.accessioned | 2026-07-09T03:26:22Z | |
| dc.description | Organic farmers, wholesalers, and retailers need 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. A seasonal autoregressive method is recommended for all planning horizons. The role of better price forecasts for the agents who deal in less common organic produce is highlighted. A confirmation for the claim that the organic produce industry needs better farmgate price forecasts to grow is provided. | |
| dc.identifier | doi:10.22004/ag.econ.19045 | |
| dc.identifier | https://ageconsearch.umn.edu/record/19045/files/cp05gu01.pdf | |
| dc.identifier | http://ageconsearch.umn.edu/record/19045 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/532575 | |
| dc.language | eng | |
| dc.publisher | ||
| dc.source | http://ageconsearch.umn.edu/record/19045 | |
| dc.title | Forecasting Organic Food Prices: Emerging Methods for Testing and Evaluating Conditional Predictive Ability | |
| dc.type | Text |