ECONOMETRICS FINAL EXAM 2025/2026 WITH
100% ACCURATE ANSWERS
1. What is one of the key assumptions of the Gauss-Markov theorem that is
violated by the linear probability model?
The assumption of no exact linear relationship among independent
variables.
The assumption that none of the independent variables are
constants.
The assumption of constant variance of the error term.
The assumption of zero conditional mean of the error term.
2. Which of the following is an example of time series data?
Starting salaries of recent business graduates at Penn State
University
The sale prices of townhouses sold last year
The monthly sales of cars at a dealership in 2018
Results of market research testing consumer preferences for soda
3. In a regression model, if an explanatory variable is found to be correlated
with the error term, what implication does this have for the model's
estimates?
The estimates may be biased and inconsistent.
The estimates will only be affected if the variable is dependent.
The estimates will be unaffected by the correlation.
,The estimates will be perfectly accurate.
,4. In a regression analysis, if a researcher identifies a variable that affects the
dependent variable but is correlated with other independent variables,
what should the researcher consider doing?
Remove the variable from the analysis entirely.
Assume the variable has no effect on the dependent variable.
Reassess the model specification to determine if the variable
should be included or if multicollinearity needs to be addressed.
Include the variable without any changes to the model.
5. What is the effect of heteroskedasticity on the population R-squared?
It decreases the population R-squared.
It increases the population R-squared.
It makes the population R-squared unreliable.
It does not affect the population R-squared.
6. What is a common challenge faced by labor economists when estimating
returns to education using non-experimental data?
Experience, another factor that also affects wage, is generally
difficult to measure.
Wage is often reported unreliably and inaccurately.
Education level in non-experimental data is probably dependent
on other omitted factors that also affect wage.
In a non-experimental setting, education level is often difficult to
measure.
, 7. Describe the implications of the normality assumption for the population
error term in regression analysis.
The normality assumption indicates that the population error term
is independent of the explanatory variables and follows a normal
distribution with a mean of zero.
The normality assumption suggests that the population error term is
dependent on the explanatory variables and has a mean of one.
The normality assumption implies that the population error term can
take any value without a specific distribution.
The normality assumption means that the population error term is
dependent on the explanatory variables and has a mean of zero.
8. In a regression analysis, if you find that the error terms are not normally
distributed, what steps can you take to ensure the reliability of the
estimated coefficients?
Ignore the non-normality of error terms and proceed with the
analysis.
Use only linear regression techniques without adjustments.
Consider using robust standard errors or transforming the data.
Change the dependent variable to ensure normality.
9. Why do labor economists often find it difficult to estimate the ceteris
paribus return to education, in terms of wage, using non-experimental
data?
Education level in non-experimental data is probably dependent
on other omitted factors that also affect wage.
In a non-experimental setting, education level is often difficult to
measure.
100% ACCURATE ANSWERS
1. What is one of the key assumptions of the Gauss-Markov theorem that is
violated by the linear probability model?
The assumption of no exact linear relationship among independent
variables.
The assumption that none of the independent variables are
constants.
The assumption of constant variance of the error term.
The assumption of zero conditional mean of the error term.
2. Which of the following is an example of time series data?
Starting salaries of recent business graduates at Penn State
University
The sale prices of townhouses sold last year
The monthly sales of cars at a dealership in 2018
Results of market research testing consumer preferences for soda
3. In a regression model, if an explanatory variable is found to be correlated
with the error term, what implication does this have for the model's
estimates?
The estimates may be biased and inconsistent.
The estimates will only be affected if the variable is dependent.
The estimates will be unaffected by the correlation.
,The estimates will be perfectly accurate.
,4. In a regression analysis, if a researcher identifies a variable that affects the
dependent variable but is correlated with other independent variables,
what should the researcher consider doing?
Remove the variable from the analysis entirely.
Assume the variable has no effect on the dependent variable.
Reassess the model specification to determine if the variable
should be included or if multicollinearity needs to be addressed.
Include the variable without any changes to the model.
5. What is the effect of heteroskedasticity on the population R-squared?
It decreases the population R-squared.
It increases the population R-squared.
It makes the population R-squared unreliable.
It does not affect the population R-squared.
6. What is a common challenge faced by labor economists when estimating
returns to education using non-experimental data?
Experience, another factor that also affects wage, is generally
difficult to measure.
Wage is often reported unreliably and inaccurately.
Education level in non-experimental data is probably dependent
on other omitted factors that also affect wage.
In a non-experimental setting, education level is often difficult to
measure.
, 7. Describe the implications of the normality assumption for the population
error term in regression analysis.
The normality assumption indicates that the population error term
is independent of the explanatory variables and follows a normal
distribution with a mean of zero.
The normality assumption suggests that the population error term is
dependent on the explanatory variables and has a mean of one.
The normality assumption implies that the population error term can
take any value without a specific distribution.
The normality assumption means that the population error term is
dependent on the explanatory variables and has a mean of zero.
8. In a regression analysis, if you find that the error terms are not normally
distributed, what steps can you take to ensure the reliability of the
estimated coefficients?
Ignore the non-normality of error terms and proceed with the
analysis.
Use only linear regression techniques without adjustments.
Consider using robust standard errors or transforming the data.
Change the dependent variable to ensure normality.
9. Why do labor economists often find it difficult to estimate the ceteris
paribus return to education, in terms of wage, using non-experimental
data?
Education level in non-experimental data is probably dependent
on other omitted factors that also affect wage.
In a non-experimental setting, education level is often difficult to
measure.
