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Unformatted text preview: Practice Multiple Choice Questions 1. Which of the following is NOT generally included in the study of econometrics? a.) using economic data to estimate relationships b.) testing economic hypotheses c.) predicting economic outcomes d.) developing new economic relationships. Ans: d 2. Why is a random error term included in an econometric model? a.) because many economic models have not been well developed yet and need to allow for inaccuracies b.) because some people are irrational c.) because there is intrinsic uncertainty in any economic activity due to individual decision making d.) because most estimating techniques are not well suited to work with a deterministic model. Ans: c 3. If you use a times series data set with 20 years worth of data to estimate a distributed lag model of order 1, how many observations will you have for estimation? a.) 21 b.) 20 c.) 19 d.) 18 Ans: c 4. A data set that has observations on one entity at multiple points in time is classified as a). time series data b.) cross‐section data c.) panel data d.) flow data Ans: a 5. The expected value of a random variable is a.) the probability weighted mean b.) a measure of central tendency of the pdf c.) average value that occurs in many repeated trial of an experiment d.) all of the above Ans: d 6. Which of the following statements about the standard normal distribution is NOT true? a.) =0 , 2 = 1 b.) it can be used to find probability intervals for any normal distribution c.) it is symmetric d.) it is derived from repeated sampling of naturally occurring phenomena Ans: d 7. In an economic model that uses income to predict monthly expenditures on entertainment, what is the dependent variable? a.) income b.) monthly expenditures on entertainment c.) income elasticity d.) demand for entertainment Ans: b 8. Which of the following is NOT an assumption of the Simple Linear Regression Model? a.) The value of y, for each value of x, is y = 1 + 2x + e b.)The variance of the random error e is var(e)= 2 c.) The covariance between any pair of random errors ei and ej is zero d.) The parameter estimate of 1 is unbiased. Ans: d 9. The OLS estimators for 1 and 2 are formulas derived by minimizing _____________. a.) the sum of the error terms or residuals b.) the sum of the squared residuals c.) the slope of the regression line d.) the fit of the regression line to the observed data. Ans: b 10. You estimate a simple linear regression model using a sample of 62 observations and obtain the following results (estimated standard errors in parentheses below coefficient estimates): y = 97.25 + 33.74 *x (3.86) (9.42) What are the endpoints of the interval estimator for 2 with a 95% interval estimate? a.) (14.90, 52.58) b.) (24.32, 43.16) c.) (‐3.58, 3.58) d.) (30.16,37.32) Ans: a 11. Which of the following is not a component of a hypothesis test? a.) null hypothesis b.) goodness‐of‐fit c.) test statistic d.) rejection region Ans: b 12. For which alternative hypothesis do you reject H0 if t≤t (,N‐2)? a.) k = c b.) k ≠ c c.) k > c d.) k< c Ans: d 13. How should k in the general multiple regression model be interpreted? a.) The number of units of change in the expected value of y for a 1 unit increase in xk when all remaining variables are unchanged b.) the magnitude by which xk varies in the model c.) the amount of variation in y explained by xk in the model d.) the number of variables used in the model. Ans: a 14. What statistical test allows joint hypotheses to be tested? a.) Breusch‐Pagan Test b.) t‐test c.) Gauss‐Markov d.) F‐test Ans: d 15. When performing an F‐test, if the null hypothesis is H0: 2 = 3 = 0 what is the alternative hypothesis? a.) 2 ≠0 and 3≠0 b.) 2 ≠0 or 3≠0 c.) (2 ≠0 and 3=0) or (2 =0 and 3≠0) d.) (2 <0 and 3>0) or (2 >0 and 3<0) Ans: b 16. Which of the following measures is NOT used to evaluate model specification? a.) adj R2 b.) Akiake Information Criterion (AIC) c.) Bayesian Information Criterion (BIC) d.) Jarque‐Bera Test Ans: d 17. Using the notation ARDL(p,q) what does p represent? a.) the number of lagged dependent variables included as explanatory variables b.) the number of lagged explanatory variables included c.) the frequency of the time series d.) the degree or integration in the error term Ans: a 18. Which of the following terms is NOT commonly used to refer to an indicator variable? a.) dummy b.) binary c.) dichotomous d.) digital Ans; d
19. Heteroskedasticity is a violation of which assumption of the MR model?
a.) The values of each xik are not random and are not exact linear functions of the other explanatory
b.) var(yi.) = var(ei) = 2 c.) E(yi) = 1 + 2xi2 + 3xi3 + ……. + kxik E(ei) = 0 d.) cov(yi, yj) = cov(ei, ej) = 0; (i≠j) Ans: b
20. What are the consequences of using least squares when heteroskedasticity is present?
a.) no consequences, coefficient estimates are still unbiased
b.) confidence intervals and hypothesis testing are inaccurate due to inflated standard errors
c.) all coefficient estimates are biased for variables correlated with the error term
d.) it requires very large sample sizes to get efficient estimates
21. Which test for heteroskedasticity should you use if you suspect different variances of the error term for different groups of observations? a.) White test b.) Lagrange Multiplier test c.) Goldfeld‐Quandt test d.) Chow Test Ans: c 22. The LM (Lagrange Multiplier) test generates a test statistic N * R2 ~2(S‐1). To what does the S in
this distribution refer?
a.) the number of explanatory variables in the auxiliary regression
b.) the number of explanatory variables in the initial model
c.) N-K—the degrees of freedom in econometric model of interest
d.) the statistical significance level chosen for the LM test
Ans: a 23. Which of the following is an example of an autoregressive distributed lag model? a.) yt = f(xt, xt‐1, xt‐2…….) b.) yt = f(yt‐1, xt, xt‐1, xt‐2…) c.) yt = f(xt, x2t, x3t) d.) yt = f(xt) + g(et‐1) Ans: b 24. When using the LM test for serial correlation, what is the null hypothesis? a.) it depends on the model specification b.) no serial correlation is present c.) statistically significant serial correlation with the first lag d.) statistically significant serial correlation with unspecified lag Ans: b 25. Using the notation ARDL(p, q) what does p represent? a.) the number of lagged dependent variables included as explanatory variables b.) the number of lagged explanatory variables included c.) the frequency of the time series d.) the degree or integration in the error term Ans: a ...
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- Statistical hypothesis testing, explanatory variables