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ARCH models for multi-period forecast uncertainty-a reality check using a panel of density forecasts

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  • Lahiri, Kajal
  • Liu, Fushang

Abstract

We develop a theoretical framework to compare forecast uncertainty estimated from time series models to those available from survey density forecasts. The sum of the average variance of individual densities and the disagreement, which is the same as the variance of the aggregate density, is shown to approximate the predictive uncertainty from well specified time series models when the variance of the aggregate shocks is relatively small compared to that of the idiosyncratic shocks. We argue that due to grouping error problems, compositional effects of the panel, and other complications, the uncertainty measure has to be estimated from individual densities. Despite numerous reservations on the credibility of time series based measures of forecast uncertainty, we found that during normal times the uncertainty estimates based on ARCH models simulate the subjective survey measure remarkably well. However, during times of regime change and structural break, the two estimates do not overlap. We suggest ways to improve the time series measures during periods when forecast errors are apt to be large. The disagreement series is a good indicator of such periods.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 21693.

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Date of creation: 2005
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Handle: RePEc:pra:mprapa:21693

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Related research

Keywords: Inflation; Survey of Professional Forecasters; GARCH; Real time data.;

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References

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Citations

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Cited by:
  1. Kajal Lahiri & Xuguang Sheng, 2008. "Measuring Forecast Uncertainty by Disagreement: The Missing Link," Ifo Working Paper Series Ifo Working Paper No. 60, Ifo Institute for Economic Research at the University of Munich.
  2. Christian Grimme & Steffen Henzel & Elisabeth Wieland, 2011. "Inflation uncertainty revisited: A proposal for robust measurement," Ifo Working Paper Series Ifo Working Paper No. 111, Ifo Institute for Economic Research at the University of Munich.
  3. Fushang Liu & Kajal Lahiri, 2006. "Modelling multi-period inflation uncertainty using a panel of density forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1199-1219.

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