Empirical commodity storage model: the challenge of matching data and theory

Abstract

The ability of the standard commodity storage model to replicate annual price serial correlation is a controversial issue. Calendar year averages of prices induce spurious smoothing of price spikes, a fact that has been surprisingly overlooked in several empirical estimations of the annual commodity storage model for agricultural commodities. We present the application of a maximum likelihood estimator of the storage model for maize prices, correcting for the spurious smoothing. We find, for this data set, serious differences in magnitudes of interest.