Financial Risk Manager Part 1
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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?
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NNikitesh
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.
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:
- Correlation requirement: The omitted variable must be correlated with at least one included independent variable
- Determinant requirement: The omitted variable must be a determinant of the dependent variable
- Bias mechanism: When both conditions are met, the estimated coefficients for the included variables become biased because they partially capture the effect of the omitted variable
- Direction of bias: The bias can be positive or negative depending on the correlation structure
Why other options are incorrect:
- Option A: Incorrect because if the omitted variable is independent of included variables, no bias occurs even if it's not a determinant
- Option B: Too restrictive - correlation with ALL included variables is not necessary; correlation with at least one is sufficient
- Option C: Incorrect because independence from included variables means no correlation, so no bias occurs even if it's a determinant
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