In an economic model
, parameters or variables are said to be endogenous
when they are predicted by other variables in the model.
For example, in a simple supply and demand model, when predicting the quantity demanded, the price is endogenous because consumers change their demand in response to the price. In contrast, a change in consumer tastes or preferences would be an exogenous change on the demand curve. In this case, the price variable is said to have total endogeneity once the demand and supply curves are known.
In econometrics the problem of endogeneity occurs when the independent variable is correlated with the error term in a regression model. This implies that the regression coefficient in an OLS regression is biased. There are many methods of overcoming this, including instrumental variable regression and Heckman selection correction.
In time series
The endogeneity problem is particularly relevant in the context of time series
analysis of causal
processes. It is common for some factors within a causal system to be dependent for their value in period n
on the values of other factors in the causal system in period n-1
. Suppose that the level of pest infestation is independent of all other factors within a given period, but is influenced by the level of rainfall and fertilizer in the preceding period. In this instance it would be correct to say that infestation is exogenous
within the period, but endogenous