Peer Evaluation Surveys:
Each group member will be required to complete an anonymous peer evaluation survey. The survey will be done via the TeamMates app which will email you a unique link to the survey (to your Monash student email address). You will be asked to rate your group members’ participation and effort (not their intelligence!). The aim of the survey is to identify and address any dysfunctional groups as early as possible. The survey will also be used to adjust your assignment marks in the following manner:
• Consider hypothetical student called Arsene:
– Let n0 equal the number of (D) votes that Arsene receives from his teammates. A (D) indicates that in the opinion of his teammates Arsene has contributed nothing to the completion of the assignment.
– Let n1 equal the number of (C) votes that Arsene receives from his teammates. A (C) vote means that in the opinion of his teammates Arsene has contributed less than it was agreed by the group that he would contribute.
– Let GM equal Arsene’s group submission mark. If n0 + n1 ≥ 2, then Arsene’s mark for the assignment is
max {0, 1 − 0.4n0 − 0.15n1} × GM.
If n0 + n1 < 2, then Arsene’s mark for the assignment will be equal to the GM .
• If you fail to complete the survey by the deadline, we will assume that you have given everyone else in your group a (B) and that you have given yourself a (D).
Failure to complete the survey by the deadline will result in a loss of marks, so please complete the survey on time. It is important to communicate clearly with your group members and make sure that everyone understands what is expected from them.
Data description
The purpose of this assignment is to investigate the influence of various factors on the birthrate across states in the United States of America. The file ‘data A1.csv’ contains observations on the following variables for 50 states:
Variable Code Description
state Name of the state
birth Birth rate (in births per woman) in the state age Median age in the state
region Indicates whether the state is in the North, West, South, or East of the USA.
There are various ways to transform the variable region into the dummy variables north, east, and south in Eviews. For instance, @recode() or @expand() can be used. Please consult the Eviews documentation for details.
Question 1 (20 marks) Assume that
E(birth|age, north, east, south) = β0 + β1age + β2north + β3east + β4south. (1)
1(a) Estimate the linear regression equation associated with (1) by OLS. Report the estimated equation in equation form with the estimated coefficients and standard errors to three decimal places. Place the Eviews output in an Appendix. (4 marks)
1(b) Interpret βˆ1. (2 marks)
1(c) Test the individual significance of the regressor age. State the null and alternative hypotheses, the form and sampling distribution of your test statistic under the null, the sample and critical value of your test statistic, your decision rule and your conclusion. (6 marks)
1(d) Do your results provide conclusive evidence that states are likely to have a higher birth rate when they are located in the North of the US instead of the South? Briefly explain. (2 marks)
1(e) Report the 95% confidence interval for β2. (2 marks)
1(f) Use the confidence interval to determine whether or not βˆ2 is statistically significant at the 5% significance level. (2 marks)
1(g) Based on the reported p-values, are any of the regressors individually insignificant at the 1% sig- nificance level? Briefly explain. (2 marks)
Question 2 (20 marks)
2(a) Test the joint significance of the regressors in (1). Conduct the test at the 5% significance level. State the null and alternative hypotheses, the form and sampling distribution of your test statistic under the null, the sample and critical values of your test statistic, your decision rule and your conclusion. (6 marks)
2(b) Test the joint significance of the regressors north, east, and south in (1). Conduct the test at the 5% significance level. Specify the unrestricted and restricted models. State the null and alternative hypotheses, the form and sampling distribution of your test statistic under the null, the sample and critical values of your test statistic, your decision rule and your conclusion. (8 marks)
2(c) Interpret and discuss the size of the R-squared of the estimated equation associated with (1). (2 marks)
2(d) Use the R-squared and sum of squared errors in the Eviews output for (1) to calculate the total sum of squares. (2 marks)
2(e) Suppose we can add an extra regressor that measures the number of marriages in each state to the linear regression implied by (1). Would you expect the R-squared to increase or decrease? Briefly explain. (2 marks)
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