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 equ ilibrium (CGE) (or RBC)-type model simulations associated with parameter un certainty. We describe two approaches for building confidence sets on model endogenous variables. The first uses a standard Wald-type statistic. The s econd approach assumes that a confidence set (sampling or Bayesian) is avai lable for the free parameters, from which confidence sets are derived by a projection technique. The latter has two advantages: first, confidence set validity is not affected by model nonlinearities; second, we can easily bui ld simultaneous confidence intervals for an unlimited number of variables. We study conditions under which these confidence sets take the form of inte rvals and show how they can be implemented using standard methods for solvi ng CGE models. We present an application to a CGE model of the Moroccan eco nomy to study the effects of policy-induced increases of transfers from Mor occan expatriates.