Quantile Regression Methods of Estimating Confidence Intervals for WASDE Price Forecasts

Olga Isengildina-Massa, Scott Irwin and Darrel L. Good
Authors registered in the RePEc Author Service: Olga Isengildina Massa

No 6409, 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida from American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association)

Abstract: This paper explores the use of quantile regression for estimation of empirical confidence limits for WASDE forecasts of corn, soybean, and wheat prices. Quantile regressions for corn, soybean, and wheat forecast errors over 1980/81 through 2006/07 were specified as a function of forecast lead time. Estimated coefficients were used to calculate forecast intervals for 2007/08. The quantile regression approach to calculating forecast intervals was evaluated based on out-of-sample performance. The accuracy of the empirical confidence intervals was not statistically different from the target level about 87% of the time prior to harvest and 91% of the time after harvest.

Keywords: Demand; and; Price; Analysis (search for similar items in EconPapers)
Pages: 35
Date: 2008
New Economics Papers: this item is included in nep-ecm and nep-for
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea08:6409

DOI: 10.22004/ag.econ.6409

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