The Pitfalls Of Multiple Dummy Variables In A Regression

Abstract

This study reports long-been-neglected pitfalls when using multiple dummy variables in a regression model. We conduct simulation analysis to explain the mathematical meaning of a product term of two dummy variables, and find that the interaction dummy term indicates only the extra contribution, not the additive contribution of two dummies. The results suggest that testing and estimating interaction effects of dummy variables are not meaningful, and that dummy variable techniques should be handled carefully when introducing two or more dummies in a multiple regression model.