Potentials and Limitations of Econometric Forecast and Simulation Models

Formal methods and models have become an integrated part of social sciences and in particular of economics. The availability of empirical data and the data processing capacity of computers have indeed created demand for quantitative analysis which in former times had been done mostly in a qualitative manner. In this paper I give an overview about different approaches to modelling and empirically analysing economies starting from early approaches of the Cowles type which were first discussed in the 50’s. I also treat large scale models which have been developped in the 60’s and 70’s and which were and still are used mainly for forecasting. However during the last two decades two types of quantitative models have become important which are drastically differerent in their approaches compared to econometric models: One is the “Real Business Cycle” (RBC) approach which is based mainly on macroeconomic theory and the other is the “Computational General Equilibrium (CGE) approach which starts from microeconomics. I shortly describe some recent developments in economics which were at least partly responsible for these two new classes of models which could be characterized as empirical models without data1 since there is no longer need for a large sample, i.e. a long time series. For economies which have undergone a radical change such as most Eastern-European countries this is the only way to anlyse formally the new structure of the economy and to forecast the future development although equilibrium models in particular may be not the most adequate way of describing the present structure of these economies.