ESTIMATION OF UNKNOWN PARAMETERS IN SYSTEM DYNAMICS MODELS USING THE METHOD OF SIMULATED MOMENTS

In principle the Method of Simulated Moments (MSM) combines simulation-based methods (e.g. Monte Carlo methods) with non-parametric statistical estimations techniques such as General Method of Mo-ments (GMM). The MSM is useful when there are empirical data related to the behavior of different enti-ties. Different statistical moments (e.g. mean, variance, correlation, etc.) of empirical data can be matched against the moments of model-generated data in order to estimate some structural parameters of the mod-el. In this paper, we introduce the MSM as a non-parametric method of estimating the parameters of dy-namic models. The major value of the MSM for estimating dynamic models is in its flexibility to be used with any type of data, including cross-sectional data and time series data.