Chapter 6
1. A change in the unit of measurement of the dependent variable in a model does not lead to a change
in:
a. the standard error of the regression.
b. the sum of squared residuals of the regression.
c. the goodness-of–fit of the regression.
d. the confidence intervals of the regression.
2. Changing the unit of measurement of any independent variable, where log of the dependent variable
appears in the regression:
a. affects only the intercept coefficient.
b. affects only the slope coefficient.
c. affects both the slope and intercept coefficients.
d. affects neither the slope nor the intercept coefficient.
3. A variable is standardized in the sample:
a. by multiplying by its mean.
b. by subtracting off its mean and multiplying by its standard deviation.
c. by subtracting off its mean and dividing by its standard deviation.
d. by multiplying by its standard deviation.
4. Standardized coefficients are also referred to as:
a. beta coefficients.
b. y coefficients.
c. alpha coefficients.
d. j coefficients.
5. If a regression equation has only one explanatory variable, say x1, its standardized coefficient must lie
in the range:
a. -2 to 0.
b. -1 to 1.
c. 0 to 1.
d. 0 to 2.
6. In the following equation, gdp refers to gross domestic product, and FDI refers to foreign direct
investment.
log(gdp) = 2.65 + 0.527log(bankcredit) + 0.222FDI
(0.13) (0.022) (0.017)
Which of the following statements is then true?
a. If gdp increases by 1%, bank credit increases by 0.527%, the level of FDI remaining constant.
b. If bank credit increases by 1%, gdp increases by 0.527%, the level of FDI remaining constant.
c. If gdp increases by 1%, bank credit increases by log(0.527)%, the level of FDI remaining constant.
d. If bank credit increases by 1%, gdp increases by log(0.527)%, the level of FDI remaining constant.
7. In the following equation, gdp refers to gross domestic product, and FDI refers to foreign direct
investment.
log(gdp) = 2.65 + 0.527log(bankcredit) + 0.222FDI
(0.13) (0.022) (0.017)
Which of the following statements is then true?
a. If FDI increases by 1%, gdp increases by approximately 22.2%, the amount of bank credit remaining
constant.
b. If FDI increases by 1%, gdp increases by approximately 26.5%, the amount of bank credit remaining
constant.
c. If FDI increases by 1%, gdp increases by approximately 24.8%, the amount of bank credit remaining
constant.
d. If FDI increases by 1%, gdp increases by approximately 52.7%, the amount of bank credit remaining
constant.
8. 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.
9. Which of the following correctly identifies a limitation of logarithmic transformation of variables?
a. Taking log of variables make OLS estimates more sensitive to extreme values in comparison to
variables taken in level.
b. Logarithmic transformations cannot be used if a variable takes on zero or negative values.
c. Logarithmic transformations of variables are likely to lead to heteroskedasticity.
d. Taking log of a variable often expands its range which can cause inefficient estimates.
10. Which of the following models is used quite often to capture decreasing or increasing marginal
effects of a variable?
a. Models with logarithmic functions
b. Models with quadratic functions
c. Models with variables in level
d. Models with interaction terms
11. Which of the following correctly represents the equation for adjusted R2?
a. 𝑅
̅2 = 1 – [SSR/(n –1)]/[SST/(n+1)]
b. 𝑅
̅2 = 1 – [SSR/(n –k – 1)]/[SST/(n+1)]
c. 𝑅
̅2 = 1 – [SSR/(n –k – 1)]/[SST/(n – 1)]
d. 𝑅
̅2 = 1 – [SSR]/[SST/(n – 1)]
12. Which of the following correctly identifies an advantage of using adjusted R2 over R2?
a. Adjusted R2 corrects the bias in R2.
b. Adjusted R2 is easier to calculate than R2.
c. The penalty of adding new independent variables is better understood through adjusted R2 than R2.
d. The adjusted R2 can be calculated for models having logarithmic functions while R2 cannot be
calculated for such models.
13. Two equations form a nonnested model when:
a. one is logarithmic and the other is quadratic.
b. neither equation is a special case of the other.
c. each equation has the same independent variables.
d. there is only one independent variable in both equations.
14. A predicted value of a dependent variable:
a. represents the difference between the expected value of the dependent variable and its actual value.
b. is always equal to the actual value of the dependent variable.
c. is independent of explanatory variables and can be estimated on the basis of the residual error term
only.
d. represents the expected value of the dependent variable given particular values for the explanatory
variables.
15. Residual analysis refers to the process of:
a. examining individual observations to see whether the actual value of a dependent variable differs
from the predicted value.
b. calculating the squared sum of residuals to draw inferences for the consistency of estimates.
c. transforming models with variables in level to logarithmic functions so as to understand the effect of
percentage changes in the independent variable on the dependent variable.
d. sampling and collection of data in such a way to minimize the squared sum of residuals.
16. Beta coefficients are always greater than standardized coefficients.
17. If a new independent variable is added to a regression equation, the adjusted R2 increases only if the
absolute value of the t statistic of the new variable is greater than one.
18. F statistic can be used to test nonnested models.
19. Predictions of a dependent variable are subject to sampling variation.
20. To make predictions of logarithmic dependent variables, they first have to be converted to their level
forms.