Estimating the rational expectations model of speculative storage: A Monte Carlo comparison of three simulation estimators
The non-negativity constraint on inventories imposed on the rational expectations theory of speculative storage implies that the conditional mean and variance of commodity prices are non-linear in lagged prices and have a kink at a threshold point. In this paper, the structural parameters of this model are estimated using three simulation-based estimators. In a Monte Carlo experiment, the finite sample properties of the simulated methods of moments estimator of Duffie and Singleton (1993, Econometrica 61 (4), 929–952) the indirect inference estimator of Gourieroux et al. (1993, Journal of Applied Economterics 8, S85–S118) and the efficient method of moments estimator of Gallant and Tauchen (1996, Econometric Theory 12, 657–681) are assessed. Exploiting the invariant distribution implied by the theory allows us to evaluate the error induced by simulations. Our results show that the estimators differ in their sensitivity to the sample size, the number of simulations, choice of auxiliary models, and computation demands. For some estimators, the test for overidentifying restrictions exhibit significant size distortions in small samples. Overall, while the simulation estimators have small bias, they are less efficient than pseudo-maximum likelihood (PMLE). Hence for the small sample sizes considered, the simulation estimators are still inferior to the PMLE estimates in a mean-squared sense.
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