What is an exogenous variable? (with photos)

The supply and demand for home computers can be used as an example of an exogenous variable.

An exogenous variable is a factor that is outside a given economic model. It often has an impact on the outcome of the model or the outcome of certain situations, but it is usually not a determining factor in its own right and changes to the model usually do not affect it. These variables are sometimes called independent variables as opposed to dependent or endogenous variables, which are usually explained by the mathematical relationships in the model. While endogenous variables can be manipulated, exogenous variables are often uncontrollable. The concept can be a bit confusing to understand on a purely theoretical level, but economists and social scientists tend to think a lot about this sort of thing and how they play out in different scenarios about sales and profit margins, broad tax policies and changes in the international landscape. Market.

Why and how the variable is used

Exogenous variables are outside the normal economy, which can affect the economic model, although the model does not.

Economic models are often very complicated, and one of the ways researchers break them down is to identify and name all the different pieces. Most models have to do with money. Changes in exchange rates are an example; global impacts of natural disasters, the introduction of new products and fluctuations in wage earnings and employment rates are also possibilities. In these and other situations, some things will change and be impacted and other things will remain virtually unaffected. Economists often refer to these “things” as “variables,” and those that are not directly affected by a major change are typically considered exogenous.

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An exogenous variable can impact the supply and demand curves.

Exogenous variables are not always crucial to economic research, but they can give academics and practitioners a better and more complete view of the impacts of any change, whether real or imagined. Even though these factors usually don’t change, they still matter. They are often useful when measuring things like the overall health of an economy or the stability of a market in general.

Basic Economic Model

One way to better understand this type of variable is to look at a basic economic model, such as supply and demand for a particular item. In the basic version of this model, changes in the amount of money a consumer has to spend on the product may affect the amount of demand for the item, but the demand curve does not usually influence the consumer’s income. In this particular case, the consumer’s income – or how much the consumer has to spend at the beginning – is an exogenous variable.

Imagining that the good in question is a home computer can help to make this example even clearer. There is a certain level of demand for home computers around the world and manufacturers sell a variety of computers at certain prices to meet this demand. Dependent variables here include the price of computers and the number of machines produced. Consumer income is exogenous; how much money the consumer has to spend on the computer is not part of the equation at all. Likewise, this factor can affect the graph as it alters the supply and demand curves and therefore shifts the equilibrium level of price and quantity.

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It is important to note here that a given variable can be endogenous to one model, but exogenous to another. There may be cases where the consumer’s income is essential. Much depends on the circumstances and general objectives of the study or dataset.

Measurement error accounting

Another example of this type of variable is measurement error, which is the difference between the actual value of a quantity and the value measured experimentally. Some measurement error is generally considered a given in most models. It is generally considered exogenous because it does not really change the results and in fact is often considered a stagnant and inevitable consideration.

path analysis

Path analysis, which is the study of causality, causality, and correlation between different variables, is also important. This type of analysis investigates the interrelationship of exogenous factors and how they impact endogenous factors. These influences can be direct or indirect and are usually portrayed through structural equation modeling. Structural equation models are built by summing the contributions of all independent variables to a specific result.

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