Endogeneity

Endogeneity, in econometrics and statistics, describes a situation where an explanatory variable in a model is correlated with the error term. This correlation undermines the assumption of independence, leading to biased and inconsistent estimates of the model's parameters. Essentially, the 'cause' (explanatory variable) is influenced by the 'effect' (the error term or unobserved factors), violating the assumption of exogenous variables. Sources of Endogeneity can include omitted variables, simultaneity (feedback loops), and measurement error. Addressing Endogeneity is critical for drawing valid causal inferences.

Endogeneity meaning with examples

• 1. Studying the impact of education on income, Endogeneity arises if innate ability (unobserved) affects both education attainment and future earnings. This means the error term incorporates ability and is correlated with education, thus biasing the estimated effect of education on income. Researchers use instrumental variables, such as distance to the nearest school to fix this issue.
• 2. Consider the relationship between advertising spending and sales. Endogeneity exists because companies often increase advertising when sales are already high, creating a feedback loop. A model might incorrectly suggest that advertising *causes* increased sales, while sales are actually driving advertising decisions. The relationship must be corrected.
• 3. Examining the effect of exercise on health. If healthier individuals are more likely to exercise, there is Endogeneity because the unobserved health status (in the error term) influences both exercise levels and measured health outcomes. Instrumental variables might be used or fixed effects techniques may be used.
• 4. A study looking at the effect of government spending on economic growth faces endogeneity. High economic growth might lead to increased government spending (tax revenues), creating simultaneity and biasing the estimated impact of government spending. Careful techniques such as IV's or the lagged effects model can provide valid answers.
• 5. Assessing the effect of inflation on unemployment presents Endogeneity if expectations of future unemployment influence inflation, potentially violating model assumptions. Additionally, the error term incorporates omitted variables, such as productivity shocks. Advanced methods are required to disentangle these complex, interwoven relationships.