When there are omitted variables in the regression, which are determinants of the dependent variable, then...?

When there are omitted variables in the regression, they can lead to biased or misleading results, as they are determinants of the dependent variable. Omitted variable bias occurs when a variable that is correlated with the independent variable and the dependent variable, has been omitted from the regression model. This bias can either lead to an underestimate (downward bias) or an overestimate (upward bias) of the estimated relationship between the independent variable and the dependent variable. Omitted variable bias can be avoided by making sure all the relevant factors affecting the dependent variable are taken into account when constructing the regression model.

The OLS estimator is biased if the omitted variable is correlated with the included variable