ETC2410/ETC5241 Introductory Econometrics Group Assignment 2 S2, 2024-25

ETC2410/ETC5241 Assignment 2

Instructions

1. The assignment must be electronically submitted by 4:30pm Australian Daylight Sav-ings Time, on Friday, 18 October 2024.
2. The file needs to be uploaded in PDF format by only one member of each group.
3. After Step 2, all members of the group must click the "Submit Assignment" button onMoodle and accept the University’s submission statement. 
   This step is essential, soplease make sure that you do this.
4. When instructed to do so, you must report your results in equation form, with stan-dard errors reported in parentheses below the parameter estimates. Screen shots ofEViews (or any other statistical package) output are not acceptable. For example, the estimated regression equation below is reported in equation form with standard errorsreported in parentheses below the estimated coeffcients:\UNDER5M R = 7
5. 459(7.607) −0.004(0.001)GDP P C5. The assignment must be typed. Please use Times New Roman font size 12.
6. Please attach a number to any equation or diagram that you refer to when answeringthe assignment questions.
7. Unless otherwise instructed, all hypothesis tests should be conducted at the 5% signif-icance level.
8. If an assignment is submitted late a penalty of 5% point deduction per 24hrs lateapplies.
9. If you are applying for special consideration for circumstances that may make youunable to engage in group work or to adhere to strict deadlines, please let Akankshaknow as early as possible, so that alternative arrangements can be made in time.
10. A penalty of up to 10% will be imposed for failure to comply with the instructions above

Peer Evaluation Surveys

Each group member will be required to complete an anonymous peer evaluation survey. The survey will be conducted via the FeedBack Fruits app. You will find the link to the app under the assignment submission link on Moodle. You will be asked to rate your group members’participation and effort. The aim of the survey is to identify and address any days functional 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 n0equal 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 n1equal the number of (C) votes that Arsene receives from his teammates. A (C) vote means that in the opinion of his teammates Arsene has contributedless 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’smark for the assignment is

max{0,1−0.4n0−0.15n1} × GMIf 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 giveneveryone 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 completethe survey on time. 

It is important to communicate clearly with your group members andmake sure that everyone understands what is expected from them.

ETC2410/ETC5241 Questions

Question 1 (32 marks)

The data for Question 1 is contained in HPRICE1.csv. The file contains 88 observations on 10 variables out of which the following are the most relevant for answering the questions below:

• price: house price, 1000s
• assess: assessed value, 1000s
• bdrms: number of bedrooms
• lotsize: size of lot in square feet
• sqrft: size of house in square feet
• colonial: =1 if home is colonial style, 0 otherwiseConsider the linear regression modelprice =β0+β1lotsize +β2sqrf t +β3bdrms +β4colonial +u(1)1

(a) Estimate the linear regression equation. Report the estimated equation in equationform with the estimated coefficients and standard errors to three decimal places. (4marks)
(b) Write down the definition of homoske dasticity and heteroskedasticity in the context of the regression equation given in (1). (4 marks)1
(c) Do you think that the error term in equation (1) may be homoskedastic or heteroskedas-tic? Briefly explain your reasoning. (4 marks)1
(d) Perform the Breusch-Pagan test of the null hypothesis that the conditional variance of the error term is homoskedastic against the alternative that the variance varies acrosshouses. Specify any auxiliary regressions that you estimate in answering the question.State the null and alternative hypotheses in terms of restrictions on relevant parame-ters, specify the form and distribution of the test statistic under the null, the samplevalue and critical value of the test statistic, your decision rule and your conclusion. (8marks)1
(e) Perform the standard White test of the null hypothesis that the conditional varianceof the error term is homoskedastic against the alternative that it is a smooth functionof the regressors. Specify any auxiliary regressions that you estimate in answeringthe question. State the null and alternative hypotheses in terms of restrictions onrelevant parameters, specify the form and distribution of the test statistic under the null, the sample value and critical value of the test statistic, your decision rule andyour conclusion. (8 marks)1
(f) Obtain the heteroske dasticity-robust standard errors for the equation estimated in part1(a) and discuss any important differences with the usual standard errors. (4 marks)

Question 2 (28 marks)

The file ‘FISH.csv’ contains 97 daily price and quantity observations on fish prices at a FishMarket in Melbourne. The dataset contains a total of 20 variables out of which the following are the most relevant for answering the questions below.

• mon = 1 if Monday
• tues = 1 if Tuesday
• wed = 1 if Wednesday
• thurs = 1 if Thursday
• wave2 = average of maximum wave heights of past 1 & 2 days
• wave3 = average of maximum wave heights of past 3 & 4 days
• log(avgprc) = log of average fish price
• t= time trendUse this dataset to answer the following questions.

2(a) Estimate a linear regression of log(avgprc) on the daily dummy variables, with Fridayas the base, along with a linear time trend. Also add the variables wave2 and wave3,which are measures of wave heights over the past several days to this regression. Report the estimated equation along with the usual standard errors. (4 marks)
2(b) Are wave2 and wave3 individually significant? Describe a mechanism by which stormyseas would increase the price of fish. (4 marks)
2(c) Plot the correlogram of the OLS residuals from the regression in 2(a). What does the information in the correlogram suggest with regards to the behavior of the error termin the model? Briefly discuss your findings. (4 marks)
2(d) Perform a Breusch-Godfrey test of the null hypothesis that there is no third-order au-tocorrelation in the error term. Specify any auxiliary regressions that you estimatein answering the question. State the null and alternative hypotheses in terms of re-strictions on relevant parameters, specify the form and distribution of the test statisticunder the null, the sample value and critical value of the test statistic, your decision rule and your conclusion. (8 marks)
2(e) Correct the standard errors for the model estimated in Question 2(a) for serial correla-tion of order three. Report the results of this regression with the new standard errors.Compare the results obtained with the usual OLS standard errors to the results withthe HAC standard errors. (4 marks)
2(f) Use the model estimated in Question 2(e) to comment on whether there is evidencethat price varies systematically within a week? Explain your reasoning (4 marks)