Working Paper Number
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.
UMass Amherst Open Access Policy
Basu, Deepankar, "Bias of OLS Estimators due to Exclusion of Relevant Variables and Inclusion of Irrelevant Variables" (2018). UMass Amherst Economics Working Papers. 256.
Retrieved from https://scholarworks.umass.edu/econ_workingpaper/256