Model Economic Models

In economics, a model is a hypothesis embodied by a set of relationships between a dependent variable, the cause, (x-axis) and an independent variable, the effect, (y-axis) variables. As household income increases, household expenditure increases is a hypothesis where the direct variable, which in this case is the extra income, is causing the indirect variable, the extra spending. The use of such models in economics is known as econometrics.

Economic models, which can contain many dependent variables in the explanation of a single independent variable, are thus used as a simplified framework designed to illustrate a complex process which would be otherwise impossible to examine. Another example would be in the case of the circular flow of income model. This simplifies the entirety of economic activity (as recorded by Gross Domestic Product) in a national economy as a sum of household consumption, investment, government expenditure, and net exports. This simplification allows economists to examine particular independent variables for economic growth and get at least a sense of the broader picture despite concerns about a lack of a sterile environment, ethical objections and the dispute over the existence of universal laws of human behaviour. Evaluating policies such as Brexit or nationalisation with this model allows economists to push government to making the correct polices to maximise economic growth.

This complexity can be attributed to the diversity of factors that determine economic activity; these factors include: individual and cooperative decision processes, resource limitations, environmental and geographical constraints and institutional and legal requirements. Indeed, this list is ever growing as more and more Economists identify more and more variables that impact models. The quality of economic thought and the awareness of what to include impacts the quality of the model. Increasingly models that reflect economic growth across countries are having to add increasingly more accurate definitions of “human capital” as machines replace basic human labour like mining and assembling goods.

The need to simplify to test theories is simultaneously the greatest strength and weakness of modelling. For one Economists therefore must make a reasoned choice of which variables and which relationships between these variables are relevant. Failing to account for important variables in models, perhaps due to a desire not to examine something that goes against the Economists’ political beliefs, will reduce the ability for models to explain economic phenomena. It would be of little value not to include measures of household income when discussing household expenditure because the Economist does not believe it is an important factor.

Assumptions are also very important in constructing models given that Economists assume the importance of variables and how they interact before they test them. Economists test the relationship between household income and expenditure, and not individual income and expenditure. The assumption that a household is essentially the same as a collection individuals is an assumption, which could on inspection invalidate the accuracy and usefulness of the model. If on closer inspection the expenditure of only the wage earner changed with a change in income, if would be inaccurate to say the whole expenditure of everyone in the household changes.