Econometric models

The task of econometric models is to map the course of economic processes on the basis of quantified values. The aim is to calculate the conceivable consequences of external influences (market trends, political, legal and economic developments, etc.) on companies, other institutions or even entire economies: forecast calculations, forecast calculations (in the sense of extrapolations), scenarios, optimization calculations and simulations are therefore the focus of econometrics Calculations.
The development of such a model is based on a combination of mathematical, statistical and economic theoretical knowledge and leads to a mathematical model (e.g. company models).

Econometric activities require a system of hypotheses with regard to the object of investigation. At the beginning of econometric analyzes, possible cause-effect relationships must be identified. Therefore, the variables relevant to the equations must first be selected. The next step is to determine the mathematical form of the functions (linear / non-linear).

They are single or multiple equation models with a problem-specific different number of explanatory variables. The models for mapping socio-technical systems, such as those represented by companies, are basically of a stochastic nature (there are practically no deterministic relationships).

A variable relationship therefore consists of a function that includes all the variables relevant to the explanation, as well as a random variable (residual size) that maps the remaining random factors.
Furthermore, the coefficients (elasticities, multipliers) of the equations have to be integrated. These are quantified using estimates (observations, empirical values). In one-equation models, this is done using the least squares method (regression analysis), the maximum likelihood method and the generalized least squares method.

In multi-equation models, individual equation estimation methods (estimation of the functions one after the other) and system estimation methods (simultaneous estimation) are used depending on the level of knowledge about the coefficients.
Then the model assumptions and the parameters must be checked for their significance and relevance in the course of tests. The following series of tests must be carried out:

⦁ autocorrelation test (regarding intertemporal independence of the random variable),
⦁ heteroscedasticity test (with regard to the premise of constant variance of the random variable),
⦁ Structural constancy test (regarding the stability of the regression coefficients),
⦁ Significance tests of the coefficients.

The possible uses of econometric models are very diverse. They are used in particular for demand, production and cost analyzes, business cycle and growth models and economic forecasts.

Bislang ist es den Modellen aber nicht gelungen, die in sie gesetzten Erwartungen zu erfüllen. Dies ist wohl insb. darin begründet, dass die gedankliche Vereinfachung sowie die Beschränkung auf quantifizierbare Größen einen unvollkommenen Level of information bewirken.

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