Stochastic simulations on the Romanian macroeconomic model

The paper presents the methodology for attaching probability distribution or intervals of variation to point forecasts. This methodology might prove significant for countries that have suffered deep structural transformations in their not very distant past. For these models, stability is more difficult to be achieved, because some coefficients lack accuracy of estimation, and this is not visible until intervals of variation are constructed. Forecasts consist traditionally in sets of values of key economic indicators, with no information regarding the associated uncertainty. Our assessment is that policy makers would benefit if they would be given probabilities as well as values, and the methodology of stochastic simulation, presented in this paper quantifies the uncertainty of the coefficients of the behavioural equations, on a reduced version of the Romanian Market Economy Model. In our paper we present the advantages of applying stochastic simulation on macromodels of emerging market economies, both from a cognitive and practical perspective. On one hand, researchers have an instrument to check the operational properties of a given model, and subsequently improve them, and, on the other hand, policy makers by incorporating the uncertainty into the decisional mechanism, have additional information which would help them in efficiently defining and promoting their targets.