I derive the dynamic full Laurent model to estimate economic models that assume a dynamic process. The application in this paper is to use the dynamic full Laurent to estimate a system of dynamic asset demand equations. The main results are that the dynamic full Laurent rejects its static version and the estimated elasticities are variable over time. Results from a Monte Carlo analysis, using a dynamic data-generating process, show that the prediction errors from the dynamic full Laurent are much smaller than those from the static version. Thus when the data are generated by a dynamic process, inferences from the static full Laurent model can be severely biased.
