Working paper

Bayesian Estimation of the Storage Model using Information on Quantities

Christophe Gouel, and Nicolas Legrand


This paper presents a new strategy to estimate the rational expectations storage model. It uses information on prices and quantities – consumption and production – in contrast to previous approaches which use only prices. This additional information allows us to estimate a model with elastic supply, and to identify parameters such as supply and demand elasticities, which are left unidentified when using prices alone. The estimation relies on the Bayesian methods popularized in the literature on the estimation of DSGE models. It is carried out on a market representing the caloric aggregate of the four basic staples – maize, rice, soybeans, and wheat – from 1961 to 2006. The results show that to be consistent with the observed volatility of consumption, production, and price, elasticities have to be in the lower ranges of the elasticities in the literature, a result consistent with recent instrumental variable estimations on the same sample.


Commodity price dynamics; storage; Bayesian inference;

JEL codes

  • C51: Model Construction and Estimation
  • C52: Model Evaluation, Validation, and Selection
  • Q11: Aggregate Supply and Demand Analysis • Prices


Christophe Gouel, and Nicolas Legrand, Bayesian Estimation of the Storage Model using Information on Quantities, TSE Working Paper, n. 17-776, March 2017.

See also

Published in

TSE Working Paper, n. 17-776, March 2017