Download Econ415_tst_test1_part1_winter2010

Economics 415
Econometrics
Midterm Exam: Part 1
40 Points
Professor Thornton
Winter 2010
Write the letter corresponding to the best answer on the answer sheet provided for part 1.
1. Suppose the objective of your empirical study is to use the money supply to predict the inflation rate.
Which of the following questions is of little or no concern to you in using this relationship to make a
prediction?
a. Does the money supply have a causal effect on the inflation rate?
b. Does the money supply account for a relatively large amount of the variation in the inflation
rate?
c. Is the relationship between the money supply and inflation a stable relationship?
d. Both b and c.
2. Suppose the objective of your empirical study is to explain the relationship between the dependent
variable wage and explanatory variables education and IQ. Specifically, you want to determine whether
education or IQ has the biggest effect on the wage. The wage is measured in dollars per hour. Education
is measured in years of education. IQ is measured in IQ points. You estimate the marginal effect of an
additional year of education is $1.50. The marginal effect of an additional IQ point is $1.47. Given this
information, which of the following is a valid conclusion?
a. Education has the biggest effect on the wage.
b. IQ has the biggest effect on the wage.
c. From a statistical point of view, education and IQ have the same effect on the wage since the
difference between them is very small.
d. These estimates of marginal effect cannot be used to determine whether education or IQ
has the biggest effect on the wage.
3. You want to determine if health insurance coverage has a causal effect on health in the U.S.
population. When designing an empirical study to analyze this relationship, which of the following
possibilities must you account for?
a. Confounding variables
b. Reverse causation
c. Chance
d. All of the above.
4. Which of the following is a qualitative variable?
a. Income
b. Gender
c. IQ
d. Education
5. You have a sample of data on two variables: amount of beef purchased per month measured in pounds,
and the price per pound of beef measured in dollars. You want to determine which variable has more
dispersion in the sample. Which of the following is the best measure to use?
a. Mean
b. Variance
c. Standard deviation
d. Coefficient of variation
6. A statistical model describes:
a. a data generation process.
b. quantifiable characteristics of a sample.
c. known and observable population parameters.
d. All of the above.
7. A random variable:
a. is a variable that can take a finite number of values on a given interval.
b. is a variable that can take an infinite number of values on a given interval.
c. is a variable whose value is uncertain.
d. is a variable that indicates the presence or absence of a characteristic of a unit in a sample.
8. Which of the following is not involved in specifying a statistical model?
a. Choosing dependent and explanatory variables.
b. Getting to know the dependent and explanatory variables by calculating descriptive statistics.
c. Choosing a functional form.
d. Making assumptions about the error term.
9. The simple classical linear regression model makes the assumption that that error term has mean zero.
This implies:
a. There errors for any two units in the sample are uncorrelated.
b. The error term and the explanatory variable are uncorrelated.
c. The error term has a constant variance.
d. The error term has a normal distribution.
10. You specify a simple classical linear regression model. The dependent variable is a measure of the
health status for the tth state in the U.S. The explanatory variable is a measure of medical care spending
per capita for the tth state. Consider the following argument: States with healthy populations spend less
on medical care than states with unhealthy populations. If this argument is valid, then which of the
following assumptions of the simple classical linear regression model will not be valid?
a. The error term is not correlated with the explanatory variable.
b. The error term has constant variance.
c. The errors are independent.
d. The error term has a normal distribution.
11. You are interested in explaining the relationship between the dependent variable annual household
food expenditure and the explanatory variable annual household income. Suppose that in the population
of households the amount of dispersion in food expenditure increases as household income increases.
This is an example of:
a. reverse causation.
b. confounding variable.
c. heteroscedasticity.
d. autocorrelation.
12. You specify a simple classical linear regression model to analyze the relationship between the
dependent variable health and the explanatory variable income. Health economics studies find evidence
that individuals with more education tend to have better health. Labor economics studies find that
individuals with more education tend to have higher incomes. Given this information, which of the
following would you expect?
a. The error term will be positively correlated with income.
b. The error term will be negatively correlated with income.
c. The error term will have non-constant variance.
d. The errors for the different households will be correlated.
13. The standard error of an estimator (also called the standard error of the estimate) is:
a. The standard deviation of the error term in a statistical model.
b. The standard deviation of the probability distribution of the dependent variable in the model
for which the estimator is being used.
c. The standard deviation of the sampling distribution of the estimator.
d. None of the above.
14. Which of the following describes the behavior of an estimator that has the property of consistency?
a. The estimator will be unbiased and have minimum variance for any size sample.
b. If the estimator is biased, the bias will be smaller the larger the sample size.
c. The larger the sample size the smaller the variance of the estimator, and therefore the more
more reliable the estimator.
d. Both b and c.
15. If an estimator is unbiased, then:
a. for any given sample it will produce an estimate that is equal to the true value of the
population parameter being estimated.
b. in a very large number of samples it will produce an average estimate that equals the true
value of the population parameter, so on average it is correct.
c. in the class of efficient estimators it has the smallest bias.
d. it does not discriminate between different types of parameters it can be used to estimate.
16. If an estimator is efficient, then:
a. it has the smallest variance in the class of unbiased estimators.
b. as the sample size increases the variance must decrease.
c. as the sample size increases the bias must decrease.
d. Both b and c.
17. The level of significance of a statistical test is:
a. The probability that the effect observed in a sample is the result of chance.
b. The probability that the effect observed in a sample is a real effect.
c. The probability of rejecting the null hypothesis when it is true.
d. The probability of accepting the null hypothesis when it is false.
18. You are analyzing the relationship between the hourly wage rate and years of education. You
hypothesize that education has no effect on the wage in the population of working age adults. You obtain
a sample from the population and estimate that the marginal effect of education is $1.25. Based on this
information, which of the following is a valid conclusion?
a. Education has an effect on the wage in the population.
b. Education does not have an effect on the wage in the population.
c. The positive marginal effect of $1.25 observed in the sample is biased upward.
d. The positive marginal effect of $1.25 observed in the sample may either be a real effect or the
result of chance (sampling error/estimation error).
19. You are using a simple classical linear regression model and the OLS estimator to analyze the
relationship between the hourly wage rate and years of education. Why can’t you use the Z-statistic,
which has a standard normal distribution, as your test statistic to test the null hypothesis that the marginal
effect of education on the wage is 1.00?
a. The Z-statistic has a mean of zero.
b. The Z-statistic has a variance and standard deviation of 1.
c. The true standard error of the estimator of the marginal effect of education is unknown and
unobservable.
d. Both a and b.
20. You are using a simple classical linear regression model and the OLS estimator to analyze the
relationship between the hourly wage rate and years of education. You have reason to believe your error
term has non- constant variance. Which of the following would you expect to be the consequence of this
situation?
a. Your study will not be internally valid because your estimate of the effect of education will be
biased.
b. Your study will not be internally valid because your standard error of the estimate of the
effect of education will be incorrect, and therefore any inferences you make or hypotheses
you test may be incorrect.
c. Your study will be internally valid but not externally valid, because it will not generalize to the
population in which you are interested.
d. Your study will be both internally and externally valid, because non-constant error variance
does not affect the validity of your conclusions.