Bias of OLS Estimators due to Exclusion of Relevant Variables and Inclusion of Irrelevant Variables

Authors

Deepankar Basu, Department of Economics, University of MassachusettsFollow

Working Paper Number

2018-19

Publication Date

2018

Abstract

In this paper I discuss three issues related to bias of OLS estimators in a general multivariate setting. First, I discuss the bias that arises from omitting relevant variables. I offer a geometric interpretation of such bias and derive sufficient conditions in terms of sign restrictions that allows us to determine the direction of bias. Second, I show that inclusion of some omitted variables will not necessarily reduce the magnitude of OVB as long as some others remain omitted. Third, I show that inclusion of irrelevant variables in a model with omitted variables can also have an impact on the bias of OLS estimators. I use the running example of a simple wage regression to illustrate my arguments.

DOI

https://doi.org/10.7275/13409887

License

UMass Amherst Open Access Policy

Recommended Citation

Basu, Deepankar, "Bias of OLS Estimators due to Exclusion of Relevant Variables and Inclusion of Irrelevant Variables" (2018). UMass Amherst Economics Working Papers. 256.
https://doi.org/10.7275/13409887