tailieunhanh - An expert system for national economy model simulations

There are some fundamental economic uncertainties. We cannot forecast economic events with a very high scientific precision. It is very clear that there does not exist a unique "general" model, which can yield all answers to a wide range of macroeconomic issues. Therefore, we use several different kinds of models on segments of the macroeconomic problem. | Yugoslav Journal of Operations Research 12 (2002), Number 2, 247-269 AN EXPERT SYSTEM FOR NATIONAL ECONOMY MODEL SIMULATIONS Lazo ROLJI] Fulbright Fellow, DuPree College of Management Georgia Institute of Technology, Atlanta, Georgia Faculty of Economics, University of Banja Luka Banja Luka, Republic of Srpska Abstract: There are some fundamental economic uncertainties. We cannot forecast economic events with a very high scientific precision. It is very clear that there does not exist a unique "general" model, which can yield all answers to a wide range of macroeconomic issues. Therefore, we use several different kinds of models on segments of the macroeconomic problem. Different models can distinguish/solve economy desegregation, time series analysis and other subfactors involved in macroeconomic problem solving. A major issue becomes finding a meaningful method to link these econometric models. Macroeconomic models were linked through development of an Expert System for National Economy Model Simulations (ESNEMS). ESNEMS consists of five parts: (1) small-scale short-term national econometric model, (2) Methodology of Interactive Nonlinear Goal Programming (MINGP), (3) data-base of historical macro-economic aggregates, (4) software interface for interactive communications between a model and a decision maker, and (5) software for solving problems. ESNEMS was developed to model the optimum macro-economic policy of a developing country (SFRY-formerly Yugoslavia). Most econometric models are very complex. Optimizing of the economic policy is typically defined as a nonlinear goal programming problem. To solve/optimize these models, a new methodology, MINGP, was developed as a part of ESNEMS. MINGP is methodologically based on linear goal programming and feasible directions method. Using Euler's Homogeneous Function Theorem, MINGP linearizes nonlinear homogeneous functions. The highest priorities in minimizing the objective function are the growth of gross domestic .