Which of the following statements is true when the dependent variable, y 0?
A)Taking log of a variable often expands its range.
B)Models using log(y) as the dependent variable will satisfy CLM assumptions more closely than models using the level of y.
C)Taking log of variables make OLS estimates more sensitive to extreme values.
D)Taking logarithmic form of variables make the slope coefficients more responsive to rescaling.

Question

Which of the following statements is true when the dependent variable, y > 0?
A)Taking log of a variable often expands its range.
B)Models using log(y) as the dependent variable will satisfy CLM assumptions more closely than models using the level of y.
C)Taking log of variables make OLS estimates more sensitive to extreme values.
D)Taking logarithmic form of variables make the slope coefficients more responsive to rescaling.

Quizplus · Accepted Answer

When the dependent variable, y > 0, taking the logarithmic form of the variable (i.e. using log(y) as the dependent variable) will satisfy CLM assumptions more closely than using the level of y. This is because taking the logarithm of a variable can reduce the impact of outliers and make the distribution more symmetric, which can help meet the assumptions of normality and constant variance in the error term. Additionally, taking the logarithmic form can stabilize the variance of the residuals and make the model more interpretable, as the slope coefficients in log form reflect the percent change in y for a one-unit increase in the independent variable. However, taking the logarithmic form can make the OLS estimates more sensitive to extreme values, as well as expand the range of the variable.

Which of the Following Statements Is True When the Dependent