ECOM20001 Introductory Econometrics 计量经济学导论代写

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ECOM20001 Introductory Econometrics 计量经济学导论代写

Assignment 1 Ecom20001 Sem 2

Assignment 1

This assignment is evaluated for a total of 34 marks. It is worth 10% of your final

mark. No late assignments will be accepted if for some reason you cannot submit on time

please submit an application for special consideration to have the weight for this assignment

put on your final examination. Please use the LMS page for this subject to submit it. This is

an individual project each person is expected to do their own assignment. It is due by

11:30pm on Thursday 14th September.

The first is a question taken from a previous year’s final examination and you should

prepare an answer in the same manner you would on an exam – without using a computer for

computations. The second and third questions require that you use EViews.

Please limit your total response to no more than the equivalent to 10 A4 pages. You

may cut and paste the Eviews output in your file. (Nb. This is what we mean when we say

“Report the results”). In most cases any figures will probably need to be reduced in size. Any

equations can be done using the equation editor in Word.

Question 1 (10 marks)

The true regression between x and y in the population is given by

0 1 i i i

y x e     

where

ECOM20001 Introductory Econometrics 计量经济学导论代写

2   and

3.   Suppose the values of x in the sample of 5 observations are

1,2,3,4,5.The values of the actual errors drawn at random from a normal population with

zero mean and unit variance are:

e 1 = .464 e 2 = .137 e 3 = 2.455 e 4 = -0.323 e 5 = -0.068

(i) Show that the observed 5 values of y are as given in the Table below (2 marks)

5.464

8.137

13.455

13.677

16.932

(ii) Use the least squares formulas to estimate the regression coefficients. Show your

working. (2 marks)

(iii) Use this data to calculate the estimated error variance and show your working.

(2 marks)

(iv) Using this data calculate the standard error of the estimated slope coefficient and

show your working. (2 marks)

(v) Carry out a test for the existence of a relationship between x and y. (2 marks)

Assignment 1 Ecom20001 Sem 2

Question 2 (12 marks)

The Executive Express Café (the café) was founded in semester 2 of 2009 and is run by

volunteer undergraduate business students. Since its inception, the café has been operating on

a semester by semester basis. The café purchases drinks and food at wholesale prices and

then sells the goods primarily to students but also academics and other University staff at

reasonable prices. Lunch is by far the most popular meal, and the most popular items are

pizza and sandwiches. Normal hours for the café are from 8 a.m. to 3 p.m. As sales have

grown, managing the supply chain and keeping waste under control have become more

difficult.

Managers do not have a clear picture as to what the pattern of sales is. Is there more or

less sold on certain days and is there a weekly cycle? This information could be useful in

purchasing so that there is less chance of running out. On the other hand, having slow sales of

particular items on specific days of the week could help the managers buy fewer items to

limit the number of items that expire and are wasted. Also, having a better understanding of

the fluctuations in sales between days of the week would be useful for staffing purposes so

that long customer queues can be avoided.

The managers have made available two time series of the most popular items in the file

cafe.wf1. The data on the two series cover 60 days, Monday through Friday that the café was

open in semester 2, 2015.The two series are:

pizza: number of pizza slices sold per day

sandw: number of sandwiches sold per day

The two other series in the file are

dayofweek: Day of the week (Monday through Friday)

week: The week of the semester (1 through 12)

They would like you to analyze this data by answering the following questions:

(i) Create a time series plot of each series. Do you observe any patterns in these plots?

(4 marks)

Hint: use Line&Symbol/Basic graph. That is, the Eviews graph options should look

like:

(ii) Present a time series plot of each series by day of the week (2 marks)

Hint: use Line&Symbol/categorical graph with dayofweek as the within graph factor

and choose raw data as the graph data option. That is, the Eviews graph options

should look like:

Assignment 1 Ecom20001 Sem 2

(iii) Present a time series plot of each series that shows the mean amount purchased by the

week of the semester. (2 marks)

(Hint: use Line&Symbol/categorical graph with week as the within graph factor and choose

means as the graph data option).

(iv) Based on the graphs you produced in (ii) and (iii) write a paragraph (6 or 7 sentences)

giving advice to the managers about the fluctuations in their sales by day of week and week

of semester? (4 marks)

Question 3 (12 marks)

You have been asked to study the trade-off between time spent sleeping and working

and to look at other factors affecting sleep including years of education and age. The data are

in the file sleep.wf1 and the variables are defined as

sleep – measured in minutes per week

totwrk – measured in minutes per week

educ – years of education

age – measured in years.

(i) Estimate a relationship between sleep and totwrk and also include years of

education and age as explanatory variables. Report your results (that is, include a

copy of the Eviews regression output). (1 mark)

(ii) Suppose an individual is currently working 35 hours per week. If they were to

work 40 hours per week by how many minutes is sleep predicted to fall? Is this a

large trade-off. (3 marks)

(iii) Would you say totwrk, educ and age explain much of the variation in sleep?

(1 mark)

Assignment 1 Ecom20001 Sem 2

(iv) Re-estimate the equation in (i) but now also include the squared totwrk variable.

Report your results. (1 mark)

(v) Test for the existence of a nonlinear relationship between totwrk and sleep.

(2 marks)

(vi) Now using the model estimated in (iv), if an individual is currently working 35

hours per week and if they were to work 40 hours per week by how many minutes

is sleep predicted to fall? How does the result compare to that obtained in (ii)

above? (3 marks)

(vii) Which model do you prefer? The model estimated in (i) or the model estimated in

(iv)? Justify your answer. (1 mark)

ECOM20001 Introductory Econometrics 计量经济学导论代写