The centering of explanatory variables about their sample averages before creating quadratics or interactions forces the coefficient on the levels to be average partial effects.

Question

The centering of explanatory variables about their sample averages before creating quadratics or interactions forces the coefficient on the levels to be average partial effects.​

Quizplus · Accepted Answer

Centering explanatory variables around their sample means before creating quadratics or interactions ensures that the coefficient on the level variables represents the average partial effect. This is because by centering the variables, the intercept of the regression model represents the expected outcome when all variables are at their sample means, and the level coefficients represent the average effect of a one-unit change in the original variable.

The Centering of Explanatory Variables About Their Sample Averages Before