_____ 1. The difference between the population regression function and the sample regression function is that:

*a. *Economists know the population regression function; they have to estimate the sample regression function.

*b. *The sample regression function is used to make inferences about the population regression function.

*c. *The sample regression function is constructed with data in deviation form; the population regression function uses data in levels form.

*d. *The population regression function is constructed with data in deviation form; the sample regression function uses data in levels form.

_____ 2. Which of the following is **not **listed as a reason for the inclusion of the error in the regression equation?

*a. *The error term captures the effects of the omitted variables.

*b. *The error term captures the effects of measurement errors.

*c. *The error term is necessary because *X* is assumed to be random.

*d. *None of the above; all were mentioned as reasons to include the error.

_____ 3. Suppose that a regression study reveals that Y= 50.00 + 0.90*X*; *R ^{2}*= 0.80. Which of the following best describes these results?

*a. *About 80% of the variation in *Y* is accounted for by *X, *and a 1% change in *X* will result in a 0.90% change in *Y*.

*b. *About 80% of the variation in *Y* is accounted for by *X*, and a 1-unit change in *X* will result in a 0.90-unit change in *Y*.

*c. *There is an 80% chance that *Y* will equal 140 if *X* = 100.

*d. *There is an 80% chance that *Y* will equal 50.90% if *X* increases by 1%.

_____ 4. Suppose that a regression study reveals that Y-hat* _{ }*= 50 + 0.9

then Y-hat=

* a.* 230 *b. *180

*c. *184 *d.* 144

_____ 5. The parameter estimates ß_{0}-hat and ß_{1}-hat are found by:

*a. *minimizing the sum of the regression residuals.

*b.* minimizing the sum of the squared regression residuals.

*c.* minimizing the sum of the squared population errors.

*d.* None of the above.

* *

_____ 6. Suppose you hypothesize ß_{1 }> 0. Your simple regression using 60 observations reveals that ß_{1}-hat = 0.21 and SE(ß_{1}-hat) = 0.11. What can you conclude about the relationship between *X* and *Y*?

*a. *A 1-unit change in *X* results in a 0.21 unit change in *Y*.

*b. *A 1% change in *X* results in 0.21% change in *Y*.

*c. *There is no statistically significant relationship between *X* and *Y*.

*d. *Both *a. *and *b.*

_____ 7. Suppose you hypothesize ß_{1 }< 0. Your simple regression using 60 observations reveal that ß_{1}-hat = 0.21 and SE(ß_{1}-hat) = 0.11. What can you conclude about the relationship between *X* and *Y*?

*a. *A 1-unit change in *X* results in a -0.21 unit change in *Y*.

*b. *A 1% change in *X* results in -0.21% change in *Y*.

*c. *There is no statistically significant relationship between *X* and *Y*.

*d. *Both *a. *and *b.*

_____ 8. Suppose an ANOVA printout from a simple regression (one independent variable) model yields the following: ESS = 600, RSS = 200, n = 20. What is the *F*-statistic?

*a. * 600 = 54

200/18

*b. * 600/2 = 27

200/18

*c. * 600/2 = 30

200/20

*d. * None of the above.

* *

_____ 9. Let Y= ß_{0 }+ ß_{1}*X*+ *E. *Suppose that ß_{1}-hat = 0.5, *X*-bar = 1 and *Y*-bar = 2. What is the elasticity of Y with respect to *X*?

*a. *0.25

*b. *1.0

*c. *2.0

*d. *Not enough information

_____ 10. If the error terms are correlated with the independent variable(s) in a regression model, the parameter estimates will be:

*a. *Inefficient.

*b. *Biased.

*c. *Biased and inefficient.

*d. *Unbiased and efficient, but the *t*-ratios will be unreliable.

_____ 11. The result of a multiple regression estimating the consumption as a function of income, wealth, and interest rates indicated that the estimated coefficients on wealth and income were not significantly different from zero yet the coefficient on interest rates was significant and the adjusted *R ^{2}* exceeded 0.97. Based on this information, one should conclude that:

*a. *Only interest rates play a major role in the determination of consumption.

*b. *Interest rates, while important, probably capture an extraneous force in the economy and should not be included in the model.

*c. *A high degree of collinearity between income and wealth may be making it difficult to estimate the individual effects of each of these variables.

*d. *Interest rates and wealth are both important determinants of consumption, but the high degree of collinearity between the two variables leads to an inflated standard error on the coefficient on wealth.

_____ 12. When would you use a semi-log model?

*a. *If it has a higher *R ^{2 }*than alternative model specifications.

*b. *When the effect of *X* on *Y* depends on the level of *X* as well as the change in *X*.

*c. *When the model is inherently non-linear.

*d. *When the model has an additive error instead of a multiplicative error.

_____ 13. If the equation Y= ß_{0 }+ ß_{1}*X _{1 }*+ ß

*a. *A 1-unit change in *X _{2 }*would be expected to change

*b. *The expected value of *Y* would be ß_{0 }if *X _{1 }+ X_{2 }+ X_{3 }= *0

*c. *A 1% change in *X _{3 }*would be expected to change

*d. *All of the above.

* *

*Questions 14 and 15 require the following information.*

A double-log model used to estimate the effects of income (I), the price level (P), and interest rates (R) on the demand for money (M) yielded the following estimated equation:

*ln(M-hat) = ln(*ß_{0}*) + *0.85*ln(I) + *1.05*ln(P) – *0.10*ln(R) *

_____ 14. According to this equation, assuming all else remains constant, if income rises by:

*a. *1 unit, money demand will rise by 0.85 units.

*b. *1%, money demand will increase by 1.05 units.

*c. *10%, money demand will rise by 0.85%.

*d. *10%, money demand will rise by 8.50%.

_____ 15. According to this equation, if the price level doubled and all else remained constant, more money demand would:

*a. *Rise by 2.10%.

*b. *Approximately double.

*c. *Increase by 210%.

*d. *Increase by 210 units.

_____ 16. Consider the reciprocal model, *Y* = ß_{0 }+ ß_{1}*X ^{-1}*.

*a. *If ß_{1 }is positive, the value of *Y* decreases at a decreasing rate as *X* increases.

*b. *The marginal effect of *X* on *Y* is given by -ß_{1 }*(X ^{-2}).*

*c. *The elasticity is given by -ß_{1 }*(XY) ^{ -2}.*

*d. *All of the above.

* *

_____ 17. When is it **inappropriate** to use the Durbin-Watson table to check for autocorrelation?

*a. *When the estimated model contains a lagged dependent variable.

*b. *When autocorrelation is definitely first-order autocorrelation

*c. *When the estimated model has the correct signs, good *t*-ratios, and a high *R ^{2}*

*d. *Both *a *and *b*.

_____ 18. Which of the following typically occurs after correcting for autocorrelation?

*a. *Both the *t*-ratios and *R ^{2 }*fall.

*b. *Both the *t*-ratios and *R ^{2 }*rise.

*c. *The fitted values track the actual values better than before correction.

*d. *Both *a* and *c.*

Subject | Business |

Due By (Pacific Time) | 04/22/2015 04:00 pm |

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