17 Marginal Effects
Marginal effects play a fundamental role in interpreting regression models, particularly when analyzing the impact of explanatory variables on an outcome variable. These effects provide a precise measure of how a small change in an independent variable influences the dependent variable.
The concept of a marginal effect is closely linked to derivatives in calculus. In simple linear models, marginal effects correspond directly to the estimated regression coefficients. However, in nonlinear models, computing marginal effects requires careful consideration, often involving either analytical differentiation or numerical approximation.
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