Economics Research Institute Study Paper
Utah State University Department of Economics
Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact the Institutional Repository Librarian at email@example.com.
The introduction of generalized autoregressive conditional heteroscedastic (GARCH) modelling techniques to agricultural price analysis represents an important advancement, both because commodity prices often exhibit volatility clustering and because explicit estimation of conditional second moments is desirable where price risk influences production and marketing behavior. However, agricultural economists may be borrowing too freely from the macro econometrics literature in applying parsimonious GARCH models to commodity price series. Using monthly data from Madagascar, this paper demonstrates the value of introducing structural regressors to the conditional variance equation of GARCH models of commodity prices. The extended GARCH model is shown to exhibit superior out-of-sample forecasting accuracy.
Barrett, Christopher B., "Is There a Structural Component to Commodity Price Volatility Clustering?" (1995). Economic Research Institute Study Papers. Paper 55.