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Answer: Omitted variable bias occurs when the omitted variable is correlated with the included regressor and is a determinant of the dependent variable.
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. It is a common issue in regression analysis where the exclusion of relevant variables can lead to inaccurate and misleading conclusions. The correct selection of factors to include in an ordinary least squares estimation is therefore critical to the accuracy of the result.
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In the context of ordinary least squares (OLS) estimation in regression analysis, provide a detailed explanation of the circumstances that lead to omitted variable bias. Additionally, explain how the careful selection of factors to include in the model affects the precision and accuracy of the estimated outcomes.
A
Omitted variable bias occurs when the omitted variable is correlated with the included regressor and is a determinant of the dependent variable.
B
Omitted variable bias occurs when the omitted variable is correlated with the included regressor but is not a determinant of the dependent variable.
C
Omitted variable bias occurs when the omitted variable is independent of the included regressor and is a determinant of the dependent variable.
D
Omitted variable bias occurs when the omitted variable is independent of the included regressor but is not a determinant of the dependent variable