To decide whether $Y_i = \beta_0 + \beta_1 X_i + u_i$ or $ln(Y_i) = \beta_0 + \beta_1 X_i + u_i$ fits the data better, you can:
a. consult the $R^2$.
b. check if the estimates are significant.
c. run an F-test.
d. use the adjusted $R^2$.
e. All of the above.
f. None of the above.
QUESTION 13
In the model $Y_i = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + \beta_3 (X_1 \times X_2) + u_i$, the expected effect on Y of a change of 3 units in $X_1$ is:
a. $\beta_1 + \beta_3 X_2$.
b. $3\beta_1$.
c. $\beta_1 + \beta_3$.
d. $3\beta_1 + 3\beta_3 X_2$.
e. All of the above.
f. None of the above.
QUESTION 14
Let $X_1$ be a continuous variable, and let $D_i$ be a binary variable. An example of an interaction term between two independent, continuous variables is:
a. $Y_i = \beta_0 + \beta_1 X_i + \beta_2 D_i + \beta_3 (X_i \times D_i) + u_i$.
b. $Y_i = \beta_0 + \beta_1 X_{1i} + \beta_2 X_{2i} + u_i$.
c. $Y_i = \beta_0 + \beta_1 D_{1i} + \beta_2 D_{2i} + \beta_3 (D_{1i} \times D_{2i}) + u_i$.
d. $Y_i = \beta_0 + \beta_1 X_{1i} + \beta_2 X_{2i} + \beta_3 (X_{1i} \times D_{2i}) + u_i$.
e. All of the above.
f. None of the above.
QUESTION 15
Which of the following are properties of the logarithm function:
a. $ln(1/x) = -ln(x)$.
b. $ln(ax) = ln(a) + ln(x)$.
c. $ln(a/x) = ln(a) - ln(x)$.
d. $ln(x^a) = aln(x)$.
e. All of the above.
f. None of the above.