Financial Risk Manager Part 1
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- In the realm of financial analysis, ordinary least squares (OLS) estimation is a widely used technique to understand the behavior of financial variables. A financial analyst must carefully select appropriate regressors to include in the OLS model to ensure accurate results. Omitted variable bias occurs in this context. Can you explain the specific conditions under which omitted variable bias arises?
- In the realm of financial analysis, ordinary least squares (OLS) estimation is a widely used technique to understand the behavior of financial variables. A financial analyst must carefully select appropriate regressors to include in the OLS model to ensure accurate results. Omitted variable bias occurs in this context. Can you explain the specific conditions under which omitted variable bias arises?
Explanation:
Omitted variable bias occurs when a model improperly omits one or more variables that are critical determinants of the dependent variable and are correlated with one or more of the other included independent variables. This bias results in an over- or under-estimation of the regression parameters. The correct answer is A, as it accurately describes the scenario where the omitted variable is both a determinant of the dependent variable and correlated with an included regressor, leading to the bias. Options B, C, and D are incorrect because they either misrepresent the relationship between the omitted variable and the determinant of the dependent variable or incorrectly suggest that the omitted variable is not correlated with any included regressors.