Quantile Regression Estimates of Confidence Intervals for WASDE Price Forecasts

This study uses quantile regressions to estimate historical forecast error distributions for WASDE forecasts of corn, soybean, and wheat prices, and then compute confidence limits for the forecasts based on the empirical distributions. Quantile regressions with fit errors expressed as a function of...

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Main Authors: Olga Isengildina-Massa, Scott H. Irwin, Darrel L. Good
Format: Article
Language:English
Published: Western Agricultural Economics Association 2010-12-01
Series:Journal of Agricultural and Resource Economics
Subjects:
Online Access:https://ageconsearch.umn.edu/record/99120
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author Olga Isengildina-Massa
Scott H. Irwin
Darrel L. Good
author_facet Olga Isengildina-Massa
Scott H. Irwin
Darrel L. Good
author_sort Olga Isengildina-Massa
collection DOAJ
description This study uses quantile regressions to estimate historical forecast error distributions for WASDE forecasts of corn, soybean, and wheat prices, and then compute confidence limits for the forecasts based on the empirical distributions. Quantile regressions with fit errors expressed as a function of forecast lead time are consistent with theoretical forecast variance expressions while avoiding assumptions of normality and optimality. Based on out-of-sample accuracy tests over 1995/96Ð2006/07, quantile regression methods produced intervals consistent with the target confidence level. Overall, this study demonstrates that empirical approaches may be used to construct accurate confidence intervals for WASDE corn, soybean, and wheat price forecasts.
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spelling doaj.art-5ff282b12d02492f95f1a414634060c92022-12-22T01:42:13ZengWestern Agricultural Economics AssociationJournal of Agricultural and Resource Economics1068-55022327-82852010-12-0135354556710.22004/ag.econ.9912099120Quantile Regression Estimates of Confidence Intervals for WASDE Price ForecastsOlga Isengildina-MassaScott H. IrwinDarrel L. GoodThis study uses quantile regressions to estimate historical forecast error distributions for WASDE forecasts of corn, soybean, and wheat prices, and then compute confidence limits for the forecasts based on the empirical distributions. Quantile regressions with fit errors expressed as a function of forecast lead time are consistent with theoretical forecast variance expressions while avoiding assumptions of normality and optimality. Based on out-of-sample accuracy tests over 1995/96Ð2006/07, quantile regression methods produced intervals consistent with the target confidence level. Overall, this study demonstrates that empirical approaches may be used to construct accurate confidence intervals for WASDE corn, soybean, and wheat price forecasts.https://ageconsearch.umn.edu/record/99120commodityevaluating forecastsgovernment forecastingjudgmental forecastingprediction intervalsprice forecasting
spellingShingle Olga Isengildina-Massa
Scott H. Irwin
Darrel L. Good
Quantile Regression Estimates of Confidence Intervals for WASDE Price Forecasts
Journal of Agricultural and Resource Economics
commodity
evaluating forecasts
government forecasting
judgmental forecasting
prediction intervals
price forecasting
title Quantile Regression Estimates of Confidence Intervals for WASDE Price Forecasts
title_full Quantile Regression Estimates of Confidence Intervals for WASDE Price Forecasts
title_fullStr Quantile Regression Estimates of Confidence Intervals for WASDE Price Forecasts
title_full_unstemmed Quantile Regression Estimates of Confidence Intervals for WASDE Price Forecasts
title_short Quantile Regression Estimates of Confidence Intervals for WASDE Price Forecasts
title_sort quantile regression estimates of confidence intervals for wasde price forecasts
topic commodity
evaluating forecasts
government forecasting
judgmental forecasting
prediction intervals
price forecasting
url https://ageconsearch.umn.edu/record/99120
work_keys_str_mv AT olgaisengildinamassa quantileregressionestimatesofconfidenceintervalsforwasdepriceforecasts
AT scotthirwin quantileregressionestimatesofconfidenceintervalsforwasdepriceforecasts
AT darrellgood quantileregressionestimatesofconfidenceintervalsforwasdepriceforecasts