To Fit: The model to the data. To Detect: Any multicollinearity in the data.

Question

Want to see the full answer?

Answer 1

Question

Chapter 12, Problem 12.170ACI

a.

To determine

To Fit: The model to the data.

To Detect: Any multicollinearity in the data.

b.

To determine

To Explain: That a second-order model may be more appropriate for predicting household food consumption.

c.

To determine

To comment: The assumption of constant error variance.

d.

To determine

To Identify: The outliers in the data.

e.

To determine

To Explain: The assumption of normal errors appears to be reasonably satisfied.

Expert Solution & Answer

Want to see the full answer?

Check out a sample textbook solution

See solution

Students have asked these similar questions

1. A study published in 1993 used US state panel data to investigate the relationshipbetween minimum wage and the employment of teenagers. The sample period was1977 to 1989 for all 50 states. The author estimated a model of the following type:ln(Eit) = β0 + β1ln(Mit/Wit) + γ2D2i + ... + γnD50i + δ2B2t + ... + δTB13t + uitwhere E is the employment to population ratio of teenagers, M is the nominalminimum wage, and W is average hourly earnings in manufacturing. In addition,other explanatory variables, such as the adult unemployment rate, the teenagepopulation share, and the teenage enrollment rate in school, were included.(a) Name some of the factors that might be picked up by time and state fixedeffects(b) The author decided to use eight regional dummy variables instead of the 49state dummy variables. What is the implicit assumption made by the author?Could you test for its validity? How?(c) The results, using time and region fixed effects only, were as follows:ˆ ln(EIT ) =…

The following regression was run using a sample of 587 women living in Kenya. The variable goats is the number of goats the woman owns and grant is whether the woman received $ 500 in cash (in local currency equivalent) two years ago from the charity GiveDirectly, or not. The charity gives grants randomly to poor people in Kenya, of $ 500. goats = 6.42 +0.80 grant R2=0.35 1. What is the estimated coefficient for grant? What does it mean, in words? (Be specific, referring to numbers.) 2. Suppose one woman in the sample, Wangari, did not receive a grant. What is her predicted number of goats? Please do fast ASAP fast

Comment on why there exists a trade-off between variance and bias of of OLS estimators when considering the choice of including a particular explanatory variable in your underlying model. Please keep your answer precise.

Answer 2

Question

Chapter 12, Problem 12.170ACI

a.

To determine

To Fit: The model to the data.

To Detect: Any multicollinearity in the data.

b.

To determine

To Explain: That a second-order model may be more appropriate for predicting household food consumption.

c.

To determine

To comment: The assumption of constant error variance.

d.

To determine

To Identify: The outliers in the data.

e.

To determine

To Explain: The assumption of normal errors appears to be reasonably satisfied.

Expert Solution & Answer

Want to see the full answer?

Check out a sample textbook solution

See solution

Answer 3

Question

Chapter 12, Problem 12.170ACI

a.

To determine

To Fit: The model to the data.

To Detect: Any multicollinearity in the data.

b.

To determine

To Explain: That a second-order model may be more appropriate for predicting household food consumption.

c.

To determine

To comment: The assumption of constant error variance.

d.

To determine

To Identify: The outliers in the data.

e.

To determine

To Explain: The assumption of normal errors appears to be reasonably satisfied.

Expert Solution & Answer

Want to see the full answer?

Check out a sample textbook solution

See solution

Answer 4

Question

Chapter 12, Problem 12.170ACI

a.

To determine

To Fit: The model to the data.

To Detect: Any multicollinearity in the data.

b.

To determine

To Explain: That a second-order model may be more appropriate for predicting household food consumption.

c.

To determine

To comment: The assumption of constant error variance.

d.

To determine

To Identify: The outliers in the data.

e.

To determine

To Explain: The assumption of normal errors appears to be reasonably satisfied.

Expert Solution & Answer

Want to see the full answer?

Check out a sample textbook solution

See solution

Answer 5

Chapter 12, Problem 12.170ACI

a.

To determine

To Fit: The model to the data.

To Detect: Any multicollinearity in the data.

b.

To determine

To Explain: That a second-order model may be more appropriate for predicting household food consumption.

c.

To determine

To comment: The assumption of constant error variance.

d.

To determine

To Identify: The outliers in the data.

e.

To determine

To Explain: The assumption of normal errors appears to be reasonably satisfied.

Answer 6

Chapter 12, Problem 12.170ACI

a.

To determine

To Fit: The model to the data.

To Detect: Any multicollinearity in the data.

Answer 7

Chapter 12, Problem 12.170ACI

a.

To determine

To Fit: The model to the data.

To Detect: Any multicollinearity in the data.

Answer 8

b.

To determine

To Explain: That a second-order model may be more appropriate for predicting household food consumption.

Answer 9

b.

To determine

To Explain: That a second-order model may be more appropriate for predicting household food consumption.

Answer 10

c.

To determine

To comment: The assumption of constant error variance.

Answer 11

c.

To determine

To comment: The assumption of constant error variance.

Answer 12

d.

To determine

To Identify: The outliers in the data.

Answer 13

d.

To determine

To Identify: The outliers in the data.

Answer 14

e.

To determine

To Explain: The assumption of normal errors appears to be reasonably satisfied.

Answer 15

e.

To determine

To Explain: The assumption of normal errors appears to be reasonably satisfied.

Answer 16

Expert Solution & Answer

Answer 17

Expert Solution & Answer

Answer 18

Want to see the full answer?

Check out a sample textbook solution

See solution

Answer 19

Ch. 12.3 - Write a first-order model relating E(y) to a. two...Ch. 12.3 - Minitab was used to fit the model E(y) = (0 + 1x1...Ch. 12.3 - Suppose you fit the multiple regression model y =0...Ch. 12.3 - Suppose you fit the first-order multiple...Ch. 12.3 - Prob. 12.5LM Ch. 12.3 - Prob. 12.6LM Ch. 12.3 - Prob. 12.7LM Ch. 12.3 - If the analysis of variance F-test leads to the...Ch. 12.3 - Ambiance of 5-star hotels. Although invisible and...Ch. 12.3 - Forecasting movie revenues with Twitter. Refer to...

To Fit: The model to the data. To Detect: Any multicollinearity in the data.

Solution Summary: The author explains that a second-order model may be more appropriate for predicting household food consumption.

Concept explainers

Videos

To Fit: The model to the data.

To Detect: Any multicollinearity in the data.

To Explain: That a second-order model may be more appropriate for predicting household food consumption.

To comment: The assumption of constant error variance.

To Identify: The outliers in the data.

To Explain: The assumption of normal errors appears to be reasonably satisfied.

Want to see the full answer?

Chapter 12 Solutions