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Economic Models

by Jackson B

Have you ever taken the time to consider just how “real” an economic model really is? If not, you may be missing out on one of the most important keys to understanding economic activity. In order to truly understand economic models, you need to ask yourself what does a model represent in the terms of how it relates to reality. Unfortunately, too many economists have devoted their time to developing models instead of explaining to people how they actually work in the real world.

An economic model, essentially, is a simplified version of the real world that allows us to see, understand, and determine how economic activity will affect the economy over time. The purpose of such a model is first to take a more complex, but essential, real world situation and pare it down into its most basic components. Next, the model will attempt to create a chemical/mechanical/electricity/human interaction process (CMEH) to understand how the economic growth or response to economic stimulus will occur. Economic models also typically provide inputs (the goods and services that are being produced or purchased) for future economic growth or contraction, as well as future potential shocks to the economy from various events or conditions. Finally, the model will project the effects of any intervention/policy changes on the economy at the end of the CMEH.

There are two broad categories of economic models: fundamental economic models and numerical, economic models. In fundamental economic models, such as the Taylor Model of Purchasing, Production and Marketing or the Chicago Board of Trade Model, there is only a focus on how markets function in the short term, namely as a result of initial price levels. Long term theories such as Say’s Law and economic history are ignored. In numerical economic models, by contrast, there is more emphasis on analyzing the relationship between economic variables over extended time frames and the resulting behavior of the market.

Circular flow economic models, on the other hand, assume that price changes cause the production or consumption elasticity of demand and supply. The output price, for instance, is thought to be elastic when the economy needs more of something, but firms respond by lowering production if they get a rise in the price. This leads to an increase in employment as firms seek to match output to input cost, which, in turn, causes the economy to expand. The circular flow mechanism then goes on. As long as the equilibrium is maintained, this is how economics operates.

Many economists, however, disagree with this view. Most economic models developed by modern economists depend on empirical methods to support their predictions and assumptions about the economy. If these assumptions are wrong, the models cannot explain the real economic data. Hence, the data sets analyzed in these models are usually unable to tell researchers what the economic situation actually is. Instead, most empirical economic models form the basis of the models’ predictive power and reliability.

However, it is important to realize that the failure of these economic models to capture the key features of real economic behavior means that the forecasts made by these models are not always reliable. There are three main limitations to what can be deduced from these models. First, it is possible that economic indicators are correlated with each other and the economy cannot be analyzed in a pure fashion. Second, there may be extraneous influences that cloud the true economic picture. For instance, pollution and other disturbances in the market may throw off the accuracy of these economic models. Finally, the time series data analyzed may simply be too short for the usefulness of these models.

Still, there are a number of ways to circumvent these limitations. Using multiple regression analysis, economists have been able to create economic models that can take into account the effects of both primary and secondary variables. This allows the economists to statistically test the assumptions of the models. In addition, the models can be constructed on a much smaller scale compared to those used in the empirical verification process mentioned above.

To summarize, there are many limitations associated with the analysis of economic data. However, the existence of complex economic relationships allows the modeling of these relationships to be very accurate and provide a rich source of information for economic researchers and policy makers. Economic theories are developed using these equations and observations to create a framework for economic science. This framework then becomes a key part of how people analyze the financial markets.