Economic Modelling

Economic Modelling Meaning

The meaning of economic modeling is related to the meaning of scientific modeling. Sciences, in general, try to understand the occurring phenomena. From physics to political science, scientists try to reduce uncertainty and chaos with rules and models.

But what is a model exactly? Models are a simpler version of reality. They paint a picture for us to understand extremely complex things. On the other hand, economics is rather different from natural sciences. Economics can’t observe the phenomena happening in a petri dish like biologists do. Furthermore, the lack of controlled experiments and obscurity in causality between events happening in the social world impedes experiments in economics to an extent. Therefore, this lack of options while conducting experiments substituted with modeling in economics.

While doing this, since reality is extremely complex and chaotic, they assume some rules before constructing a model. These assumptions generally reduce the complexity of reality.

For example, physicists time to time, assume a vacuum for these models, and economists assume that agents are rational and have complete information about the market. We know that this is not real. We are all aware that air exists, and we are not living in a vacuum, as we all know that economic agents may make irrational decisions. Nonetheless, they are useful for various reasons.

Economic models are specific types of models that are especially focused on what is happening in economies. They represent reality with different types of methods, such as graphical representations or mathematical equation sets.

Nonetheless, since economies and societies are extremely complex systems, economic models vary, and their methodologies change. They all have different approaches and characteristics to answer different questions.

Types of Economic Models

In this section, we will go over the widely used general types of economic models. As mentioned before, economic models come in different methodologies, and their implications vary since the reality that they are trying to discover is different. The most commonly used economic models can be given as visual economic models, mathematical economic models, and economic simulations.

Types of Economic Models: Visual Economic Models

The visual economic models are maybe the most common ones in textbooks. If you go to a bookstore and grab an economics book, you will see dozens of graphs and charts. Visual economic models are relatively simple and easy to understand. They are trying to grasp the events that are happening in reality with various charts and graphs.

The most well-known visual economic models are perhaps the IS-LM curves, aggregate demand and supply graphs, utility curves, factor markets charts, and production-possibility frontier.

Let’s summarize the production possibility frontier to answer the question of why we classify it as a visual economic model.

In Figure 1 below, we can see probably the first graph in every contemporary economics textbook - the production possibility frontier or the product-possibility curve.

Fig. 1 - Production Possibility Frontier

This curve represents the possible production amounts for both goods, x and y. Nonetheless, we are not going to examine the model itself but rather its aspects. This model assumes that there exist two goods in the economy. But in reality, we can see many goods in any economy, and most of the time, there exists a complex relationship between goods and our budget. This model simplifies reality and gives us a clear explanation by an abstraction.

Another well-known example of visual economic models is the representation of the relationships between agents in an economy via charts of the factor markets.

Fig. 2- Relationships in Factor Markets

This type of chart is an example of visual economic modeling. We know that, in reality, the relationships in economies are rather complex than this chart. Nonetheless, this type of modeling helps us understand and develop policies to an extent.

On the other hand, the scope of the visual economic models is relatively limited. Therefore, economics heavily depends on mathematical models to overcome the limitations of visual economic models.

Types of Economic Models: Mathematical Economic Models

Mathematical economic models are developed to overcome the restrictions of visual economic models. They generally follow the rules of algebra and calculus. While following these rules, mathematical models try to explain the relationships between variables. Nonetheless, these models can be extremely abstract, and even the most basic models contain a significant amount of variables and their interactions.One famous mathematical economic model is the Solow-Swan Model, generally known as Solow Growth Model.

Solow Growth Model tries to model the economic growth of a country in the long run. It is constructed over different assumptions, such as an economy containing just a single good or a lack of international trade. We can denote the production function of the Solow Growth Model as follows:

\(Y(t) = K(t)^\alpha H(t)^\beta (A(t)L(t))^{1-\alpha-\beta}\)

Here we denote the production function with \(Y\), capital with \(K\), human capital with \(H\), labor with \(L\), and technology with \(A\). Nonetheless, our main goal here isn’t to dive deep into the Solow Growth Model but rather show that it contains lots of variables.

Fig. 3 - Solow Growth Model

For example, Figure 3 shows Solow Growth Model, an increase in technology will change the slope of the required investment line in a positive way. In addition to that, the model states that an increase in the potential output can only exist with respect to an increase in the technology of the country.

Solow Growth Model is a relatively simple model. Contemporary economic models may contain pages of equations or applications related to the concept of probability. Therefore, for calculating these types of extremely complex systems, we generally use economic simulation models or economic simulations.

Types of Economic Models: Economic Simulations

As mentioned before, contemporary economic models are generally investigated with computers while using economic simulations. They are highly complex dynamic systems. Therefore, computation becomes necessary. Economists are generally aware of the mechanics of the system that they are constructing. They set the rules and let the machines do the mathematical part. For example, if we want to develop a Solow Growth Model with international trade and multiple goods, a computational approach would be suitable.

Uses of Economic Models

Economic models can be used for many reasons. Economists and politicians continuously share ideas about agenda-setting. As mentioned before, economic models are used for a better understanding of reality.

Economic Modelling Example

We gave lots of examples of economic models. Nonetheless, it is better to dive deep and understand the structure of one economic model in detail. It is better to start with the basics. Thus here, we are focusing on the supply and demand model.

As we have said before, all models start with assumptions, and the supply and demand model is no exception. First, we assume that markets are perfectly competitive. Why are we assuming that? First of all, to simplify the reality of monopolies. Since there exist many buyers and sellers, monopolies don’t exist. Both firms and consumers must be price takers. This guarantees that firms are selling according to the price. Finally, we must assume that information is available and easy to access for both sides. If consumers don’t know what they are getting, the price can be altered for more profits by the firms.

Now, after establishing our basic assumptions, we can go and elaborate from here. We know that there exists a good. Let’s call this good \(x\) and the price of this good as \(P_x\). We know that there exists some demand for this good. We can demonstrate the amount of demand with \(Q_d\) and the amount of supply with \(Q_s\). We are assuming that if the price is lower, then the demand will be higher.

Thus, we can say that total demand is a function of price. Therefore, we can say the following:

\(Q_d = \alpha P + \beta \)

where \(\alpha\) is demand’s relationship with price and \(\beta\) is a constant.

Fig. 4 - Supply and Demand Graph in the Factor Market

In real life, this relationship may be too complicated. Nonetheless, this doesn’t mean that we can’t simplify. Since we know that deals can only be made where the supply is equal to the demand, we can find the equilibrium price for this good in this market.

While constructing this model, first, we set some assumptions, and after that, we decided what to analyze and simplified the reality. After that, we used our knowledge and created a general model for application over reality. Nonetheless, we should keep in mind that this model has limitations. In reality, markets are nearly never completely competitive, and information is not as fluid or widespread as we assumed. This is not just a problem for this specific model. In general, all models have limitations. If we understand a model’s limitations, the model will be more helpful for future applications.

Limitations of Economic Models

As in all models, economic models contain some limitations too.

Famous British statistician George E. P. Pox said the following:

This is rather an important argument. As we have mentioned before, models may be extremely useful for improving our understanding of phenomena. Nonetheless, all models have limitations, and some may contain flaws.

Do you remember what we did while constructing our extremely simple model? We started with assumptions. False assumptions may lead to false results. They may inherently sound within the borders of the model. Nonetheless, they can’t explain the reality if they are not constructed with realistic assumptions.

After constructing assumptions for a model, we simplified the reality. Social systems are extremely complex and chaotic. Therefore for calculating and chasing what is necessary, we eliminate some conditions and simplify reality. On the other hand, oversimplification can lead us to unrealistic solutions. We should carefully analyze the things that we are not considering in the equations.

Following the simplification step, a mathematical relationship is created. Mathematics is a big part of economic modeling. Thus, economic models should follow mathematical logic in a rigorous manner. Finally, all models should be falsifiable. This is crucial for it to be scientific. This means that we should be able to argue against the model if we have the proof.