In the natural sciences, a laboratory experiment can isolate various elements and their movements. There is no equivalent in the discipline of economics. The employment of model building is an attempt to produce a laboratory where controlled experiments can be conducted.
The idea of having such a laboratory is very appealing to economists and politicians. Once the model is built and endorsed as a good replica of the economy, politicians can evaluate the outcomes of various policies.
This, it is argued, enhances the efficiency of government policies and thus leads to a better and more prosperous economy.
It is also suggested that the model can serve as a referee in assessing the validity of various economic ideas. The other purpose of a model is to provide an indication regarding the future.
By means of mathematical and statistical methods, a model builder establishes relationships between various economic variables.
For example, personal consumer outlays are related to personal disposable income and interest rates, while fixed capital spending is explained by the past stock of capital, interest rates, and economic activity. A collection of such various estimated relations—i.e., equations—constitutes an econometric model.
A comparison of the goodness of fit of the dynamic simulation versus the actual data is an important criterion in assessing the reliability of a model. (In a static simulation, the equations of the model are solved using actual lagged variables. In a dynamic simulation, the equations are solved by employing calculated from the model-lagged variables).
The final test of the model is its response to a policy variable change, such as an increase in taxes or a rise in government outlays. By means of a qualitative assessment, a model builder decides whether the response is reasonable or not. Once the model is successfully constructed, it is ready to be used.
Is the mathematical method valid in economics?
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