Econometrics Ketevani Kapanadze
Problem Set 1
a) Multiple choice questions
1. If the total sum of squares (SST) in a regression equation is 81, and the residual sum of
squares (SSR) is 25, what is the explained sum of squares (SSE)?
a. 64
b. 56
c. 32
d. 18
2. If the residual sum of squares (SSR) in a regression analysis is 66 and the total sum of
squares (SST) is equal to 90, what is the value of the R-squared?
a. 0.73
b. 0.55
c. 0.27
d. 1.2
3. The significance level of a test is:
a. the probability of rejecting the null hypothesis when it is false.
b. one minus the probability of rejecting the null hypothesis when it is false.
c. the probability of rejecting the null hypothesis when it is true.
d. one minus the probability of rejecting the null hypothesis when it is true.
4. Which of the following is true of heteroskedasticity?
a. Heteroskedasticty causes inconsistency in the Ordinary Least Squares estimators.
b. Population R2 is affected by the presence of heteroskedasticty.
c. The Ordinary Least Square estimators are not the best linear unbiased estimators if
heteroskedasticity is present.
d. It is not possible to obtain F statistics that are robust to heteroskedasticity of an
unknown form.
5. Which of the following tests helps in the detection of heteroskedasticity?
a. The Breusch-Pagan test
b. The Breusch-Godfrey test
c. The Durbin-Watson test
d. The Chow test
Econometrics Ketevani Kapanadze
6. The OLS residuals in the multiple regression model
a. cannot be calculated because there is more than one explanatory variable.
b. can be calculated by subtracting the fitted values from the actual values.
c. are zero because the predicted values are another name for forecasted values.
d. are typically the same as the population regression function errors.
7. To decide whether the slope coefficient is large or small,
a. you should analyze the economic importance of a given increase in X.
b. the slope coefficient must be larger than one.
c. the slope coefficient must be statistically significant.
d. you should change the scale of the X variable if the coefficient appears to be too small.
8. An estimator ˆY of the population value Y is more efficient when compared to another
estimator Y , if:
a. E( ˆY ) > E( Y ).
b. it has a smaller variance.
c. its c.d.f. is flatter than that of the other estimator.
d. both estimators are unbiased, and var( ˆY ) < var( Y ).
9. Which of the following is true of the OLS t statistics?
a. The heteroskedasticity-robust t statistics are justified only if the sample size is large.
b. The heteroskedasticty-robust t statistics are justified only if the sample size is small.
c. The usual t statistics do not have exact t distributions if the sample size is large.
d. In the presence of homoskedasticity, the usual t statistics do not have exact t distributions if the
sample size is small.
10. 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.
Econometrics Ketevani Kapanadze
d. If bank credit increases by 1%, gdp increases by log(0.527)%, the level of FDI remaining
constant.
11. 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.
12. 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.
13. 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
14. The following simple model is used to determine the annual savings of an individual on the
basis of his annual income and education.
Savings = β0+∂0 Edu + β1Inc+u
The variable ‘Edu’ takes a value of 1 if the person is educated and the variable ‘Inc’ measures
the income of the individual.
If ∂0 > 0, _____.
a. uneducated people have higher savings than those who are educated
b. educated people have higher savings than those who are not educated
c. individuals with lower income have higher savings
d. individual with lower income have higher savings
Econometrics Ketevani Kapanadze
15. The income of an individual in Brno depends on her ethnicity and several other factors
which can be measured quantitatively. If there are 5 ethnic groups in Brno, how many dummy
variables should be included in the regression equation for income determination in Brno?
a. 1
b. 5
c. 6
d. 4