Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices

Kjartan Kloster Osmundsen, Tore Kleppe (), Roman Liesenfeld and Atle Oglend
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Kjartan Kloster Osmundsen: Department of Mathematics and Physics, University of Stavanger, 4036 Stavanger, Norway
Roman Liesenfeld: Institute of Econometrics and Statistics, University of Cologne, Albertus-Magnus-Platz, 50937 Cologne, Germany
Atle Oglend: Department of Safety, Economics and Planning, University of Stavanger, 4036 Stavanger, Norway

Econometrics, 2021, vol. 9, issue 4, 1-24

Abstract: 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. For a Bayesian posterior analysis of the SSM, which is nonlinear in the latent states, we used a Markov chain Monte Carlo algorithm based on the particle marginal Metropolis–Hastings approach. An empirical application to four commodity markets showed 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 typically larger under the stochastic trend SSM.

Keywords: commodity price dynamics; Bayesian posterior analysis; particle marginal Metropolis–Hastings; state-space model (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2021
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