Econometric 4-5-6-7-8

Question 1 of 26

1

Binary variables

Select one of the following:

are generally used to control for outliers in your sample.
can take on more than two values.
exclude certain individuals from your sample.
can take on only two values.

Explanation

Question 2 of 26

1

In the simple linear regression model, the regression slope

Select one of the following:

indicates by how many percent Y increases, given a one percent increase in X.
when multiplied with the explanatory variable will give you the predicted Y.
indicates by how many units Y increases, given a one unit increase in X.
represents the elasticity of Y on X.

Explanation

Question 3 of 26

1

In which of the following relationships does the intercept have a real-world interpretation?

Select one of the following:

the relationship between the change in the unemployment rate and the growth rate of real GDP (“Okun’s Law”)
the demand for coffee and its price
test scores and class-size
weight and height of individuals

Explanation

Question 4 of 26

1

The OLS residuals, ˆi u , are sample counterparts of the population

Select one of the following:

regression function slope
errors
regression function’s predicted values
regression function intercept

Explanation

Question 5 of 26

1

Changing the units of measurement, e.g. measuring test scores in 100s, will do all of the following EXCEPT for changing the

Select one of the following:

residuals
numerical value of the slope estimate
interpretation of the effect that a change in X has on the change in Y
numerical value of the intercept

Explanation

Question 6 of 26

1

To decide whether the slope coefficient indicates a “large” effect of X on Y, you look at the

Select one of the following:

size of the slope coefficient
regression R2
economic importance implied by the slope coefficient
value of the intercept

Explanation

Question 7 of 26

1

The t-statistic is calculated by dividing

Select one of the following:

the OLS estimator by its standard error.
the slope by the standard deviation of the explanatory variable.
the estimator minus its hypothesized value by the standard error of the
estimator.
the slope by 1.96.

Explanation

Question 8 of 26

1

A binary variable is often called a

Select one of the following:

dummy variable
dependent variable
residual
power of a test

Explanation

Question 9 of 26

1

If the errors are heteroskedastic, then

Select one of the following:

OLS is BLUE
WLS is BLUE if the conditional variance of the errors is known up to a constant factor of proportionality
LAD is BLUE if the conditional variance of the errors is known up to a constant factor of proportionality
OLS is efficient

Explanation

Question 10 of 26

1

Using the textbook example of 420 California school districts and the regression of test scores on the student-teacher ratio, you find that the standard error on the slope coefficient is 0.51 when using the heteroskedasticity robust formula, while it is 0.48 when employing the homoskedasticity only formula. When calculating the t-statistic, the recommended procedure is to

Select one of the following:

use the homoskedasticity only formula because the t-statistic becomes larger
first test for homoskedasticity of the errors and then make a decision
use the heteroskedasticity robust formula
make a decision depending on how much different the estimate of the slope is under the two procedures

Explanation

Question 11 of 26

1

Using 143 observations, assume that you had estimated a simple regression function and that your estimate for the slope was 0.04, with a standard error of 0.01. You want to test whether or not the estimate is statistically significant. Which of the following decisions is the only correct one:

Select one of the following:

you decide that the coefficient is small and hence most likely is zero in the population
the slope is statistically significant since it is four standard errors away from zero
the response of Y given a change in X must be economically important since it is statistically significant
since the slope is very small, so must be the regression R2(square).

Explanation

Question 12 of 26

1

In the multiple regression model, the adjusted R2, R2

Select one of the following:

cannot be negative.
will never be greater than the regression R2(square).
equals the square of the correlation coefficient r.
cannot decrease when an additional explanatory variable is added.

Explanation

Question 13 of 26

1

If you had a two regressor regression model, then omitting one variable which is relevant

Select one of the following:

will have no effect on the coefficient of the included variable if the correlation between the excluded and the included variable is negative.
will always bias the coefficient of the included variable upwards.
can result in a negative value for the coefficient of the included variable, even though the coefficient will have a significant positive effect on Y if the omitted variable were included.
makes the sum of the product between the included variable and the residuals different from 0.

Explanation

Question 14 of 26

1

Under the least squares assumptions for the multiple regression problem (zero conditional mean for the error term, all Xi and Yi being i.i.d., all Xi and ui having finite fourth moments, no perfect multicollinearity), the OLS estimators for the slopes and intercept

Select one of the following:

have an exact normal distribution for n > 25.
are BLUE.
have a normal distribution in small samples as long as the errors are homoskedastic.
are unbiased and consistent.

Explanation

Question 15 of 26

1

The following OLS assumption is most likely violated by omitted variables bias:

Select one of the following:

there is heteroskedasticity

Explanation

Question 16 of 26

1

The dummy variable trap is an example of

Select one of the following:

imperfect multicollinearity
something that is of theoretical interest only
perfect multicollinearity
something that does not happen to university or college students

Explanation

Question 17 of 26

1

Imperfect multicollinearity

Select one of the following:

is not relevant to the field of economics and business administration
only occurs in the study of finance
means that the least squares estimator of the slope is biased
means that two or more of the regressors are highly correlated

Explanation

Question 18 of 26

1

Consider the multiple regression model with two regressors X1 and X2, where both variables are determinants of the dependent variable. You first regress Y on X1 only and find no relationship. However when regressing Y on X1 and X2, the slope coefficient 1ˆ changes by a large amount. This suggests that your first regression suffers from

Select one of the following:

heteroskedasticity
perfect multicollinearity
omitted variable bias
dummy variable trap

Explanation

Question 19 of 26

1

Imperfect multicollinearity

Select one of the following:

implies that it will be difficult to estimate precisely one or more of the partial effects using the data at hand
violates one of the four Least Squares assumptions in the multiple regression model
means that you cannot estimate the effect of at least one of the Xs on Y
suggests that a standard spreadsheet program does not have enough power to estimate the
multiple regression model

Explanation

Question 20 of 26

1

When testing joint hypothesis, you should

Select one of the following:

use t-statistics for each hypothesis and reject the null hypothesis is all of the restrictions fail
use the F-statistic and reject all the hypothesis if the statistic exceeds the critical value
use t-statistics for each hypothesis and reject the null hypothesis once the statistic exceeds the critical value for a single hypothesis
use the F-statistics and reject at least one of the hypothesis if the statistic exceeds the critical value

Explanation

Question 21 of 26

1

In the multiple regression model, the t-statistic for testing that the slope is significantly different from zero is calculated

Select one of the following:

by dividing the estimate by its standard error.
from the square root of the F-statistic.
by multiplying the p-value by 1.96.
using the adjusted R2(square) and the confidence interval.

Explanation

Question 22 of 26

1

If you wanted to test, using a 5% significance level, whether or not a specific slope coefficient is equal to one, then you should

Select one of the following:

subtract 1 from the estimated coefficient, divide the difference by the standard error, and check if the resulting ratio is larger than 1.96.
add and subtract 1.96 from the slope and check if that interval includes 1.
see if the slope coefficient is between 0.95 and 1.05.
check if the adjusted R2 is close to 1.

Explanation

Question 23 of 26

1

When there are two coefficients, the resulting confidence sets are

Select one of the following:

rectangles
ellipses
squares
trapezoids

Explanation

Question 24 of 26

1

The homoskedasticity-only F-statistic and the heteroskedasticity-robust F-statistic typically are

Select one of the following:

the same
different
related by a linear function
a multiple of each other (the heteroskedasticity-robust F-statistic is 1.96 times the homoskedasticity-only F-statistic)

Explanation

Question 25 of 26

1

A nonlinear function

Select one of the following:

makes little sense, because variables in the real world are related linearly.
can be adequately described by a straight line between the dependent variable and one of the explanatory variables.
is a concept that only applies to the case of a single or two explanatory variables since you cannot draw a line in four dimensions.
is a function with a slope that is not constant.

Explanation

Question 26 of 26

1

The best way to interpret polynomial regressions is to

Select one of the following:

take a derivative of Y with respect to the relevant X.
plot the estimated regression function and to calculate the estimated effect on Y associated with a change in X for one or more values of X.
look at the t-statistics for the relevant coefficients.
analyze the standard error of estimated effect.

	Created by aykutwashere almost 11 years ago