Explanation:
Omitted variable bias occurs when a model unnecessarily excludes one or more variables that are significant determinants of the dependent variable and are correlated with one or more of the other included independent variables. Omitted variable bias leads to an over- or under-estimation of the regression parameters (intercept and the coefficients).
Key points:
Why other options are incorrect:
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A financial analyst wishes to come up with Ordinary Least Squares Estimation (OLS) regression model to analyze the financial performance of a company. However, the analyst is aware that some of the explanatory variables might be excluded (and hence omitted variable bias). What is the cause of omitted variables bias?
A
Omitted variable bias happens when the omitted variable is independent of the included independent variables but is not a determinant of the dependent variable.
B
Omitted variable bias occurs when the omitted variable is correlated with all of the included independent variables and is a determinant of the dependent variable.
C
Omitted variable bias occurs when the omitted variable is independent of the included independent variables and is a determinant of the dependent variable.
D
Omitted variable bias occurs when the omitted variable is correlated with at least one of the included independent variables and is a determinant of the dependent variable.