Measuring forecast uncertainty by disagreement: The missing link
Kajal Lahiri, Xuguang Simon Sheng
Abstract
Open-access reader
Kajal Lahiri, Xuguang Simon Sheng
Abstract
Open-access reader
Abstract Using a standard decomposition of forecast errors into common and idiosyncratic shocks, we show that aggregate forecast uncertainty can be expressed as the disagreement among the forecasters plus the perceived variability of future aggregate shocks. Thus the reliability of disagreement as a proxy for uncertainty will be determined by the stability of the forecasting environment and the length of the forecast horizon. Using density forecasts from the Survey of Professional Forecasters, we find direct evidence in support of our hypothesis. Our results support the use of GARCH‐type models, rather than the ex post squared errors in consensus forecasts, to estimate the ex ante variability of aggregate shocks as a component of aggregate uncertainty. Copyright © 2010 John Wiley & Sons, Ltd.
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Abstract Using a standard decomposition of forecast errors into common and idiosyncratic shocks, we show that aggregate forecast uncertainty can be expressed as the disagreement among the forecasters plus the perceived variability of future aggregate shocks. Thus the reliability of disagreement as a proxy for uncertainty will be determined by the stability of the forecasting environment and the length of the forecast horizon. Using density forecasts from the Survey of Professional Forecasters, we find direct evidence in support of our hypothesis. Our results support the use of GARCH‐type models, rather than the ex post squared errors in consensus forecasts, to estimate the ex ante variability of aggregate shocks as a component of aggregate uncertainty. Copyright © 2010 John Wiley & Sons, Ltd.
Key concepts: Econometrics, Proxy (statistics), Aggregate (composite), Survey of Professional Forecasters, Economics, Ex-ante, Consensus forecast, Reliability (semiconductor)