CEPII, Recherche et Expertise sur l'economie mondiale
The Role of Storage in Commodity Markets: Indirect Inference Based on Grains Data

Christophe Gouel
Nicolas Legrand

 Highlights :
  • Understanding the drivers of commodity prices dynamics is crucial. Unfortunately the central economic model for representing commodity prices, the competitive storage model, is not yet empirically validated.
  • In this work, we develop a rich storage model with four demand and supply shocks, elastic supply, and longrun trends and estimate it structurally on a caloric aggregate of the four most important grains.
  • Our estimated model is consistent with most of the moments in the data, validating the empirical relevance of the storage model.
  • The estimated model shows that speculative storage while crucial cannot explain alone the persistence of grain price. It explains 42% of the price autocorrelation, the rest being accounted for by the price trend, the persistence of demand shocks, and the presence of news shocks about production.

 Abstract :
Understanding commodity prices dynamics is of crucial importance for assessing the persistence of cost-push costs or for countries dependent on commodity exports. Unfortunately, despite decades of research, the workhorse theoretical model in the field, the rational expectations storage model, is yet to be empirically validated. This paper provides the first full empirical test of the storage model. We first build a new storage model featuring a supply response, long-run demand and cost trends, and four structural shocks. We then develop a flexible empirical approach which relies on the indirect inference method and exploits the joint dynamics of prices and quantities unlike previous estimations which only use price information. The information contained in quantities is essential to relax restrictive identifying assumptions and empirically assess the overall consistency of the model's new features. Finally, we carry out a structural estimation on the aggregate index of the world most important staple food products: maize, rice, soybeans, and wheat. The results show that our extended storage model is consistent with most of the moments in the data, including the high price autocorrelation of which up to 42% can be explained by the transfer of inventories over time. They also show that, although for these commodities supply shocks are the main drivers of market dynamics, over the past 60 years all price spikes have been associated with large positive demand shocks.

 Keywords : Commodity Price Dynamics | Indirect Inference | Monte Carlo Analysis | Storage

 JEL : C51, C52, Q11
CEPII Working Paper
N°2022-04, July 2022

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