**INSTANT DOWNLOAD WITH ANSWERS**

#### Principles of Econometrics 4th Edition by R. Carter Hill -Test Bank

File: Ch06, Chapter 6, Further Inference in the Multiple Regression Model Multiple Choice

- The following model has been estimated using a dataset with 4854 observations.

SS | df | MS | |||||||

Regression | 919587.543 | 4 | 229896.9 | ||||||

Error | 2590390.62 | 121 | 534.2113 | ||||||

Variable | b | Std. Error | t | P>|t| | |||||

x2 | -0.0126355 | 0.005519 | -2.28937 | 0.022 | |||||

x3 | 0.5957923 | 0.014482 | 41.13934 | 0.000 | |||||

x4 | 1.124589 | 0.877192 | 1.282032 | 0.200 | |||||

x5 | 0.3237421 | 0.060709 | 5.332661 | 0.000 | |||||

Constant | 8.86016 | 1.766116 | 5.016749 | 0.000 | |||||

Calculate the F-statistic to test **H _{0}: **

**b**

_{2}**=**

**b**

_{3}**=-**

**b**

_{4}**=**

**b**

_{5}**= 0**a.) 430.35b.) .2620c.) 76.80d.) 2.8169 Ans: aLevel: DifficultSection: 6.1

- The critical value for a given p-value in the F-distribution depends on the degrees of freedom in the numerator and denominator. How do you find the degrees of freedom in the numerator?

a.) It is the number of observations minus the number of coefficients estimated (N-K)b.) It is the number of hypotheses being tested simultaneously (J)c.) It is the number of coefficients being estimated (K)d.) It is the number of observations minus the number of hypotheses tested (N-J) Ans: bLevel: ModerateSection: 6.1

- The critical value for a given p-value in the F-distribution depends on the degrees of freedom in the numerator and denominator. How do you find the degrees of freedom in the denominator?

a.) It is the number of observations minus the number of coefficients estimated (N-K)b.) It is the number of hypotheses being tested simultaneously (J)c.) It is the number of coefficients being estimated (K)d.) It is the number of observations minus the number of hypotheses tested (N-J) Ans: aLevel: ModerateSection: 6.1

- When performing an F-test, if the null hypothesis is
**H**_{0}:**b**_{2}**=****b**_{3}**= 0**what is the alternative hypothesis?

a.) b_{2} ≠0 and b_{3}≠0b.) b_{2} ≠0 or b_{3}≠0c.) (b_{2} ≠0 and b_{3}=0) or (b_{2} =0 and b_{3}≠0)d.) (b_{2} <0 and b_{3}>0) or (b_{2} >0 and b_{3}<0) Ans: bLevel: ModerateSection: 6.1

- The F
_{(1,218)}distribution is equivalent to what distribution?

a.) N (1,218)b.) F_{(2, 114)}c.) t_{(218)}d.) c^{2}_{(2,114)} Ans: cLevel: ModerateSection: 6.1

- What statistical test allows joint hypotheses to be tested?

a.) Breusch-Pagan Testb.) t-testc.) Gauss-Markovd.) F-test Ans: dLevel: EasySection: 6.1

- If your computer printout includes an F-statistic and p-value for the overall model, how should you interpret the p-value?

a.) the probability that all of the coefficients are actually equal to zerob.) the probability that all of the coefficients other than the intercept are actually zero and we would observe the estimated resultsc.) the probability that the model is completely invalidd.) the probability that the model is incorrectly specified Ans: bLevel: ModerateSection: 6.1

- Why should
__good__non-sample information be incorporated into an econometric model via restricted least squares?

a.) it reduces the variance of estimated coefficients without introducing biasb.) it allows more precise hypotheses testing to be donec.) it reduces the degrees of freedom in the denominator of an F-testd.) It reduces the probability of rejecting a true null hypothesis Ans: aLevel: ModerateSection: 6.2

- How does omitting a relevant variable from a regression model affect the estimated coefficient of other variables in the model?

a.) they are biased downward and have smaller standard errorsb.) they are biased upward and have larger standard errorsc.) they are biased and the bias can be negative or positived.) they are unbiased but have larger standard errors Ans: c.Level: ModerateSection: 6.3

- How does including an irrelevant variable in a regression model affect the estimated coefficient of other variables in the model?

a.) they are biased downward and have smaller standard errorsb.) they are biased upward and have larger standard errorsc.) they are biased and the bias can be negative or positived.) they are unbiased but have larger standard errors Ans: dLevel: ModerateSection: 6.3

- Which of the following measures is NOT used to evaluate model specification?

a.) adj R^{2}b.) Akiake Information Criterion (AIC)c.) Bayesian Information Criterion (BIC)d.) Jarque-Bera Test Ans: dLevel: EasySection: 6.3

- When are R
^{2}and adjusted R^{2}equal?

a.) when the model is correctly specifiedb.) when K = 1c.) when the error terms are normally distributedd.) when an unrestricted model is estimated Ans: bLevel: ModerateSection: 6.3

- You estimate 4 different specifications of an econometric model by adding a variable each time and get the following results

R^{2} |
adj R^{2} |
AIC | ||

Model A | 0.3458 | 0.3285 | 22.56 | |

Model B | 0.3689 | 0.3394 | 22.37 | |

Model C | 0.4256 | 0.3916 | 21.21 | |

Model D | 0.4299 | 0.3911 | 21.79 | |

Which model appears to be correctly specified?a.)Ab.)Bc.)Cd.)D Ans: CLevel: ModerateSection: 6.3

- If you reject the null hypothesis when performing a RESET test, what should you conclude?

a.) at least one of the original coefficients is not equal to zerob.) the original model is incorrectly specified and can be improved uponc.) relevant variable are omitted and the coefficient estimates of included variables are biasedd.) an incorrect functional form was used Ans: b (the misspecification does not have to be an omitted variable)Level: Moderate/DifficultSection: 6.3

- When collinear variables are included in an econometric model coefficient estimates are

a.) biased downward and have smaller standard errorsb.) biased upward and have larger standard errorsc.) biased and the bias can be negative or positived.) unbiased but have larger standard errors Ans: dLevel: ModerateSection: 6.4

- When a set of variables with exact collinearity is included in an econometric model coefficient estimates are

a.) undefinedb.) unbiasedc.) biased upwardd.) biased, but the direction is unclear Ans: aLevel: EasySection: 6.4

- If your regression results show a high R
^{2}, adj R^{2}, and a significant F-test, but low t values for the coefficients, what is the most likely cause?

a.) omitted relevant variablesb.) irrelevant variables includedc.) collinearityd.) heteroskedasiticity Ans: cLevel: EasySection: 6.4

- Running auxillary regressions where each explanatory variable is estimated as a function of eth remaining explanatory variables can help detect

a.) omitted relevant variablesb.) irrelevant variables includedc.) collinearityd.) heteroskedasiticity Ans: cLevel: ModerateSection: 6.4

- Why is the variance of the forecast y larger than the variance of the expected value of y?

a.) the estimated forecast variance includes an estimate of ŝ^{2}b.) the estimated forecast variance includes weighted covariance terms of all paired variablesc.) the Gauss-Markov theorem does not apply to forecast of a single observationd.) the expected value of confidence intervals rely on the standard normal distribution while forecast use a t distribution. Ans: aLevel: DifficultSection: 6.5Short Answer

- For what does RESET test?

Ans: Model misspecificationLevel: ModerateSection: 6.3

- When two or more variables move together in systematic ways they are said to be ________________?

Ans: CollinearLevel: EasySection: 6.4 File: Ch07, Chapter 7, Using Indicator Variables Multiple Choice

- Which of the following terms is NOT commonly used to refer to an indicator variable?

a.) dummyb.) binaryc.) dichotomousd.) digital Ans; dLevel: EasySection: 7.1

- Which of the following wage premia is modeled with an indicator variable that shifts the intercept?

a.) heightb.) genderc.) educationd.) weight Ans: bLevel: EasySection: 7.1

- The following Mincer equation has been used to estimate wages:

ln (*Y*) = ln (*Y*_{o}) + b_{2}*EDU* + b_{3}*EXPER* + b_{4 }*EXPER*^{2} + *e*where *Y* is income, *Y*_{0} is income of someone with no education or experience, *EDU* is years of education and *EXPER* is experience in the field. If you suspect males earn higher wages than females and that the wage difference increases with education how would you adjust the econometric model to estimate wages?a.) include a binary variable for gender, *MALE*b.) include an interaction term equal to *MALE* EXPER*c.) include an indicator variable for *MALE* and one for *FEMALE*d.) include a binary variable for *MALE* and an interaction term equal to *MALE * EXPER** *Ans: dLevel: ModerateSection: 7.1

- The Chow test is a specific application of a(n)

a.) z-testb.) c^{2} testc.) F-testd.) t-test Ans: cLevel: EasySection 7.2

- A large company is accused of gender discrimination in wages. The following model has been estimated from the company’s human resource information

**ln( WAGE) = 1.439 + .0834 EDU + .0512 EXPER + .1932 MALE**

**Where WAGE is hourly wage, EDU is years of education, EXPER is years of relevant experience, and MALE indicates the employee is male. How much more do men at the firm earn, on average?a.) $1.21 per hour more than femalesb.) 19.32% more than femalesc.) $19.32 per hourd.) $19,320 more per year than females Ans: bLevel: ModerateSection: 7.3[highlighted term should have a “hat” over]**

- . A large company is accused of gender discrimination in wages. The following model has been estimated from the company’s human resource information

**ln( WAGE) = 1.439 + .0834 EDU + .0512 EXPER + .1932 MALE**

**Where WAGE is hourly wage, EDU is years of education, EXPER is years of relevant experience, and MALE indicates the employee is male. What hypothesis would you test to determine if the discrimination claim is valid?a.) H**

_{0}:b

_{MALE}= 0 ; H

_{1}: b

_{MALE}≥ 0b.) H

_{0}:b

_{MALE}= b

_{EDU}= b

_{EXPER }= 0 ; H

_{1}: b

_{MALE}≠ 0 and b

_{EDU}≠ 0 and b

_{EXPER }≠ 0c.) H

_{0}:b

_{MALE}= b

_{EDU}= b

_{EXPER }= 0 ; H

_{1}: b

_{MALE}≠ 0 or b

_{EDU}≠ 0 or b

_{EXPER }≠ 0d.) H

_{0}:b

_{MALE}≤ b

_{EDU}or b

_{MALE }≤ b

_{EXPER }; H

_{1}: b

_{MALE}> b

_{EDU}or b

_{MALE }> b

_{EXPER}Ans: aLevel: ModerateSection: 7.3[highlighted term should have a “hat” over]

- When you have a multiple regression model with a binary dependent variable it is a __________.

a.) dichotomous modelb.) Bernoulli modelc.) Linear Probability modeld.) prediction model Ans: cLevel: EasySection: 7.4

- The following economic model predicts whether a voter will vote for an incumbent school board member

*INCUMBENT* = b_{1} + b_{2} *MALE* + b_{3 }*PARTY* + b_{4 }*MARRIED *+ b_{5 }*KIDS *where*INCUMBENT* = 1 if the voter votes for them, 0 otherwise,*MALE* = 1 if the voter is a male,*PARTY* indicates the voter is registered with the same political party as the incumbent,*MARRIED *= 1 for married voters, 0 otherwise, and*KIDS *is the number of school age kids living with the voter.What is the probability that a married female without kids who is not registered with a political party will vote for the incumbent?a.) b_{1} + b_{4}b.) b_{1}c.) b_{1 }+ b_{2} + b_{3 }+ b_{5}d.) b_{2} + b_{3} + b_{5} Ans: aLevel: ModerateSection: 7.4

- The following economic model predicts whether a voter will vote for an incumbent school board member

*INCUMBENT* = b_{1} + b_{2} *MALE* + b_{3 }*PARTY* + b_{4 }*MARRIED *+ b_{5 }*KIDS *where*INCUMBENT* = 1 if the voter votes for them, 0 otherwise,*MALE* = 1 if the voter is a male,*PARTY* indicates the voter is registered with the same political party as the incumbent,*MARRIED *= 1 for married voters, 0 otherwise, and*KIDS *is the number of school age kids living in the voter’s house.How should we interpret b_{4}?a.) the likelihood the incumbent candidate is marriedb.) the percentage of married voters who vote for the incumbentc.) the probability a married person is registered to voted.) the difference in probability a married voter will vote for the incumbent as opposed to an unmarried voter Ans: dLevel: ModerateSection: 7.4

- Treatment effects are
*best*estimated using data from

a.) randomized, controlled experiments.b.) subjects that have already undergone the risky treatment.c.) people most in need of the treatments.d.) natural or quasi-experiments. Ans: aLevel: EasySection: 7.5

- Randomized, controlled experiments are needed to accurately measure treatment effects without

a.) the expense of having to treat everyone.b.) the risk of discrimination bias.c.) exposing everyone to untested treatments.d.) selection bias. Ans: dLevel: ModerateSection: 7.5

- When certain characteristics cause a person to choose to be in a treatment group, selection bias can be overcome by using

a.) conditional randomization and fixed effects.b.) difference in differences estimation.c.) larger sample sizes.d.) quasi-experiments. Ans: aLevel: DifficultSection: 7.5

- Treatment effects can be estimated from natural or quasi-experiments using which estimator?

a.) Restricted least squaresb.) Difference-in-differences estimatorc.) Fixed effectsd.) Quasi-Likelihood Ans: bLevel: ModerateSection: 7.5

- Which of the following variables is not necessary in order to estimate treatment effects using difference-in-differences?

a.) a treatment/control indicatorb.) pre-treatment / post-treatment indicatorc.) treatment group * treatment time interaction termd.) post-treatment performance Ans: cLevel: ModerateSection: 7.5

- Estimating treatment effects using difference-in-differences requires what kind of data?

a.) aggregate measures over timeb.) time-series data spanning the treatment lengthc.) paired, panel datad.) cross-section spanning the treated population Ans: cLevel: EasySection: 7.5

- What benefit is gained by estimating treatment effects with fixed effects using panel data?

a.) it controls for unobserved, individual characteristicsb.) it controls for changes in individuals over timec.) it allows the treatment effect to vary with the length of treatmentd.) it “fixes” the treatment to the same time for each individual Ans: aLevel: ModerateSection: 7.5

- The following economic model predicts whether a voter will vote for an incumbent school board member

*INCUMBENT* = b_{1} + b_{2} *MALE* + b_{3 }*PARTY* + b_{4 }*MARRIED *+ b_{5 }*KIDS *where*INCUMBENT* = 1 if the voter votes for them, 0 otherwise,*MALE* = 1 if the voter is a male,*PARTY* indicates the voter is registered with the same political party as the incumbent,*MARRIED *= 1 for married voters, 0 otherwise, and*KIDS *is the number of school age kids living in the voter’s house. If you hypothesize males and females might have a different willingness to vote for a candidate registered with a different political party, which variable should you add to the economic model to allow you to test the hypothesis?a.) MALE * PARTYb.) MALE * MARRIEDc.) MARRIED * KIDSd.) MARRIED * PARTY Ans: aLevel: EasySection: 7.2

- The following economic model predicts whether a voter will vote for an incumbent school board member

*INCUMBENT* = b_{1} + b_{2} *MALE* + b_{3 }*PARTY* + b_{4 }*MARRIED *+ b_{5 }*KIDS *where*INCUMBENT* = 1 if the voter votes for them, 0 otherwise.*MALE* = 1 if the voter is a male.*PARTY* indicates the voter is registered with the same political party as the incumbent.*MARRIED *= 1 for married voters, 0 otherwise.*KIDS *is the number of school age kids living in the voter’s house. If you believe marriage affects male and female voters differently, which variable should you add to the economic model to allow you to test the hypothesis?a.) MALE * PARTYb.) MALE * MARRIEDc.) MARRIED * KIDSd.) MARRIED * PARTY Ans: bLevel: EasySection: 7.2

- If you perform a Chow test to compare two regressions and reject the null hypothesis, what should you conclude?

a.) there is not sufficient evidence that the regressions are significantly differentb.) the regression equations are statistically differentc.) the regression equations are equivalentd.) it depends on how you set up the null hypothesis Ans: aLevel: ModerateSection: 7.2