Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices

We propose a state-space model (SSM) for commodity prices that combines the competitive storage model with a stochastic trend. This approach fits into the economic rationality of storage decisions, and adds to previous deterministic trend specifications of the storage model. Parameters are estimated using a particle Markov chain Monte Carlo procedure. Empirical application to four commodity markets shows that the stochastic trend SSM is favored over deterministic trend specifications. The stochastic trend SSM identifies structural parameters that differ from those for deterministic trend specifications. In particular, the estimated price elasticities of demand are significantly larger under the stochastic trend SSM.

Keywords: Commodity price dynamics, Bayesian posterior analysis, Particle marginal Metropolis Hastings, State-space model

JEL Classification: C11, C22, C32, C51, C52, C53, C58, Q02

Suggested Citation: Suggested Citation

Kloster Osmundsen, Kjartan and Kleppe, Tore Selland and Liesenfeld, Roman and Oglend, Atle, Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices (January 12, 2020). Available at SSRN: https://ssrn.com/abstract=3518402 or http://dx.doi.org/10.2139/ssrn.3518402