Econometric simulation is relatively a new technique that has been used in the management sciences as a complement to more conventional methods of analysis such as budgeting and linear programming. For simulating any system, an artificial environment is created in such a way that it resembles the real world. The output of a simulation is a set of system performance variables associated with each set of policies or strategies. The agricultural sector is influenced by a wide range of continuously changing forces. The agricultural economy can be characterized to remain constantly in disequilibrium. For this single reason itself, the non-optimization feature of simulation renders this approach as a desirable method of analysis.
But the foremost requirement of the use of simulation technique is to test the validity of the model developed for simulation or prediction purposes. Simulation is basically a computer assisted method of operating a model of a real economic system. The simulation technique permits the analysis of a large economic system through a series of sets of functional relationships. The simulation technique allows the researcher to investigate the influence of different sectors on the overall economic system. Simulation provides the modeler with a kind of ‘data laboratory’. It generates as much data as required according to the objectives of any investigation. Experiments that could be otherwise too costly or completely impossible to perform on the real economic system can be conducted on a computer simulation model of the system. Various simulation experiments were performed on all the commodity sub-models as well as on the aggregate level model assuming various exogenous changes of interest in each case. A number of alternative policies were simulated in order to provide policy makers, scientists and others with information about the likely consequences of alternative policy changes. For this purpose, we will use ‘static simulation’ to simulate the endogenous variable-es of the entire Agro-Economic Model of Punjab in order to evaluate various policy alternatives for crop enterprises separately, and when crop sub-models will be integrated with the macro level model of the Agricultural Sector of the State.
KEYWORDS: simulation, linear programming, economic system, livestock
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