Practical Regression: Introduction to Endogeneity: Omitted Variable Bias
This is the fourth in a series of lecture notes which, if tied together into a textbook, might be entitled “Practical Regression.” The purpose of the notes is to supplement the theoretical content of most statistics texts with practical advice based on nearly three decades of experience of the author, combined with over one hundred years of experience of colleagues who have offered guidance. As the title “Practical Regression” suggests, these notes are a guide to performing regression in practice.
This technical note introduces the concept of endogeneity bias with specific coverage of omitted variable bias. Students who read this note will understand why omitting key predictors can sometimes bias the coefficients of included variables. The note illustrates omitted variable bias by means of an extended example and offers practical advice for model building that balances the desire for parsimony developed in a previous note with the need to limit omitted variable bias.
Dranove, David. Practical Regression: Introduction to Endogeneity: Omitted Variable Bias. Case 7-112-004 (KEL638).