Chapter 3 and 4 econometrics TB Questions || All Correct.
In the equation,
y=β0+β1x1+β2x2+u
β2 is a(n) _____.
a. independent variable
b. dependent variable
c. slope parameter
d. intercept parameter correct answers C
Consider the following regression equation:
y=β1+β2x1+β2x2+u
. What does β1 imply?
a. β1 measures the ceteris paribus effect of x1 on x2
b. β1 measures the ceteris paribus effect of y on x1
c. β1 measures the ceteris paribus effect of x1 on y.
d. β1 measures the ceteris paribus effect of x1 on u correct answers C
3. If the explained sum of squares is 35 and the total sum of squares is 49, what is
the residual sum of squares?
a. 10
b. 12
c. 18
d. 14 correct answers D.
4. Which of the following is true of R2?
a. R2 is also called the standard error of regression.
b. A low R2 indicates that the Ordinary Least Squares line fits the data well.
c. R2 usually decreases with an increase in the number of independent variables in a
regression.
d. R2 shows what percentage of the total variation in the dependent variable, Y, is
explained by the explanatory variables. correct answers D.
The value of R2 always _____.
a. lies below 0
b. lies above 1
c. lies between 0 and 1
d. lies between 1 and 1.5 correct answers C.
6. If an independent variable in a multiple linear regression model is an exact linear
combination of other independent variables, the model suffers from the problem of
_____.
a. perfect collinearity
b. homoskedasticity
c. heteroskedasticty
d. omitted variable bias correct answers A.
, 7. The assumption that there are no exact linear relationships among the
independent variables in a multiple linear regression model fails if _____, where n is
the sample size and k is the number of parameters.
a. n>2
b. n=k+1
c. n>k
d. n<k+1 correct answers D.
8. Exclusion of a relevant variable from a multiple linear regression model leads to
the problem of _____.
a. misspecification of the model
b. multicollinearity
c. perfect collinearity
d. homoskedasticity correct answers A.
9. Suppose the variable x2 has been omitted from the following regression equation,
y=β0+β1x1+β2x2+u. ~β1 is the estimator obtained when x2 is omitted from the equation. The
bias in ~ β1 is positive if _____.
a. β2 >0 and x 1 and x 2 are positively correlated
b. β2 <0 and x 1 and x 2 are positively correlated
c. β2 >0 and x 1 and x 2 are negatively correlated
d. β2 = 0 and x 1 and x 2 are negatively correlated correct answers A.
10. Suppose the variable x2 has been omitted from the following regression
equation,
y=β0+β1x1+β2x2+u.~β1 is the estimator obtained when x2 is omitted from the equation. The
bias in ~β1 is negative if _____.
a. β2>0 and x 1 and x 2 are positively correlated
b.β2<0 and x 1 and x 2 are positively correlated
c.β2=0 and x 1 and x 2 are negatively correlated
d.β2=0 and x 1 and x 2 are negatively correlated correct answers B.
11. Suppose the variable x2 has been omitted from the following regression
equation, y=β0+β1x1+β2x2+u. ~β1 is the estimator obtained when x2 is omitted
from the equation. If E(~β1) >β1,~β1
is said to _____.
a. have an upward bias
b. have a downward bias
c. be unbiased
d. be biased toward zero correct answers A.
12. High (but not perfect) correlation between two or more independent variables is
called _____.
a. heteroskedasticty
b. homoskedasticty
In the equation,
y=β0+β1x1+β2x2+u
β2 is a(n) _____.
a. independent variable
b. dependent variable
c. slope parameter
d. intercept parameter correct answers C
Consider the following regression equation:
y=β1+β2x1+β2x2+u
. What does β1 imply?
a. β1 measures the ceteris paribus effect of x1 on x2
b. β1 measures the ceteris paribus effect of y on x1
c. β1 measures the ceteris paribus effect of x1 on y.
d. β1 measures the ceteris paribus effect of x1 on u correct answers C
3. If the explained sum of squares is 35 and the total sum of squares is 49, what is
the residual sum of squares?
a. 10
b. 12
c. 18
d. 14 correct answers D.
4. Which of the following is true of R2?
a. R2 is also called the standard error of regression.
b. A low R2 indicates that the Ordinary Least Squares line fits the data well.
c. R2 usually decreases with an increase in the number of independent variables in a
regression.
d. R2 shows what percentage of the total variation in the dependent variable, Y, is
explained by the explanatory variables. correct answers D.
The value of R2 always _____.
a. lies below 0
b. lies above 1
c. lies between 0 and 1
d. lies between 1 and 1.5 correct answers C.
6. If an independent variable in a multiple linear regression model is an exact linear
combination of other independent variables, the model suffers from the problem of
_____.
a. perfect collinearity
b. homoskedasticity
c. heteroskedasticty
d. omitted variable bias correct answers A.
, 7. The assumption that there are no exact linear relationships among the
independent variables in a multiple linear regression model fails if _____, where n is
the sample size and k is the number of parameters.
a. n>2
b. n=k+1
c. n>k
d. n<k+1 correct answers D.
8. Exclusion of a relevant variable from a multiple linear regression model leads to
the problem of _____.
a. misspecification of the model
b. multicollinearity
c. perfect collinearity
d. homoskedasticity correct answers A.
9. Suppose the variable x2 has been omitted from the following regression equation,
y=β0+β1x1+β2x2+u. ~β1 is the estimator obtained when x2 is omitted from the equation. The
bias in ~ β1 is positive if _____.
a. β2 >0 and x 1 and x 2 are positively correlated
b. β2 <0 and x 1 and x 2 are positively correlated
c. β2 >0 and x 1 and x 2 are negatively correlated
d. β2 = 0 and x 1 and x 2 are negatively correlated correct answers A.
10. Suppose the variable x2 has been omitted from the following regression
equation,
y=β0+β1x1+β2x2+u.~β1 is the estimator obtained when x2 is omitted from the equation. The
bias in ~β1 is negative if _____.
a. β2>0 and x 1 and x 2 are positively correlated
b.β2<0 and x 1 and x 2 are positively correlated
c.β2=0 and x 1 and x 2 are negatively correlated
d.β2=0 and x 1 and x 2 are negatively correlated correct answers B.
11. Suppose the variable x2 has been omitted from the following regression
equation, y=β0+β1x1+β2x2+u. ~β1 is the estimator obtained when x2 is omitted
from the equation. If E(~β1) >β1,~β1
is said to _____.
a. have an upward bias
b. have a downward bias
c. be unbiased
d. be biased toward zero correct answers A.
12. High (but not perfect) correlation between two or more independent variables is
called _____.
a. heteroskedasticty
b. homoskedasticty
