Statistical Inference for Computable General Equilibrium Models, with Application to a Model of the Moroccan Economy

We study the problem of measuring the uncertainty of computable general equilibrium (CGE) (or RBC)-type model simulations associated with parameter uncertainty. We describe two approaches for building conŽ dence sets on model endogenous variables. The Ž rst uses a standard Wald-type statistic. The second approach assumes that a conŽ dence set (sampling or Baycsian) is available for the free parameters, from which conŽ dence sets are derived by a projection technique. The latter has two advantages: Ž rst, conŽ dence set validity is not affected by model nonlinearities; second, we can easily build simultaneous conŽ dence intervals for an unlimited number of variables. We study conditions under which these conŽ dence sets take the form of intervals and show how they can be implemented using standard methods for solving CGEmodels. We present an application to a CGE model of the Moroccan economy to study the effects of policy-induced increases of transfers from Moroccan expatriates.