Introduction to Econometrics (ECO2008)

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Introduction to Econometrics (ECO2008):

Group Project 1 Instructions

Academic Year: 2018–19

Instructions and Regulations


Please inform me of your project group (or if you are working alone) as soon

as possible. The maximum group size is 4. DO NOT ASK ME IF YOUR


from your group needs to send me an email (a.fernihough@qub.ac.uk)

containing your name(s), student number(s), and email address(es). Once you

inform me of your group I will designate your group with a country to study.

Group members do not need to be in the same tutorial class.


Each project will be completed and submitted on TurnitinUK before 5:00pm

on the 22nd of February 2019 at the latest.

Formatting Instructions

The project should be typed in 12 point font size, double spaced, on A4 paper,

and should not exceed 1,500 words length (excluding graphs, tables, equations,

and bibliographical references). This word count is an upper limit. The whole

project, everything included but excluding the cover page, must not exceed 15

pages (5% deducted for each additional page). Again this is an upper limit.

Every page should have the page number printed in the middle at the bottom.


The project should contain a cover page (not numbered) with the following



Full name(s) and degree(s)

Email address(es)

Student ID number(s)

Each project should have a References section if works are cited. Each

answer must have the same number as the corresponding question and must

be presented in the same order as in the project. Clearly label all tables and

graphs which must be reported in the main text and not in an appendix.

Make sure each graph’s axes are clearly labeled. Do not include graphs or

tables on which you do not comment in the report. Marks will be deducted

for a messy presentation of results. See Fernihough’s golden rules for further



If you need to refer to any results established in another person’s work, clearly

indicate the reference to that work by writing down the family name(s) of the

author(s) and the year of publication—for example, Fernihough (2015). Make

sure that you indicate the full reference to the work in the References part of

your project. Use the Harvard referencing scheme.

Project Submission

All written assignments will be submitted using TurnitinUK. Note the “UK”

bit, saying you could not get this to work because you submitted to Turnitin

rather than TurnitinUK is not a valid excuse. Make sure you or one person

from your group sets up an account and sees how this works at least a week

prior to the due date. That way you will not get stuck on the day you have

to submit the assignment. Only one person from each group is required to

submit a project.

This is an online submission system that checks for plagiarism. The class

is called “Introduction to Econometrics 2019”, the class id is: 4043253, and the

enrollment key is 3381795. If you need help with TurnitinUK please use the

following link for the FAQs for Queen’s students:


Late Submission Penalties

Assessed work submitted after the deadline will be penalised at the rate of 5% of the

total marks available for each working day late up to a maximum of five working days,

after which a mark of zero shall be awarded, i.e., day one is 100% - 5%; day two is

100% -10%; day three is 100% - 15%, etc. Where the assessed work element accounts

for a certain proportion of the module mark, the 5% penalty will apply to the assessed

element mark only and not to the overall module mark. Exemptions shall be granted

only if there are exceptional circumstances, and where the student has made a case in

writing to the School Office within three working days of the deadline for submission

or where a concession has been agreed on the grounds of a student’s disability. A list of

guidelines on acceptable exceptional circumstances is contained in the Guidelines for

Schools on Exceptional Circumstances. Extensions to deadlines shall be proportionate

to the impact of the exceptional circumstances.

The above passage is taken from: Study Regulations for Undergraduate

Programmes Section 1.3.11.

Late Submission Exemptions

Evidence of exceptional circumstances must be submitted to the relevant School Office

on the appropriate form within three working days of returning to study or, in the

case of emergencies which arose during examinations, by the published deadline. If

a student knows they are going to miss an assignment deadline or an examination

because of exceptional circumstances, they should inform the relevant School Office

in advance by telephone or email/letter of their enforced absence, either personally or,

if this is not possible, via someone on their behalf. School Exceptional Circumstances

Committees are not obliged to consider any medical certificate or evidence of exceptional

circumstances presented after the published deadline (see 1.4.43). The exception to this

is where a concession has been agreed on the grounds of a student’s disability (see also


The above passage is taken from: Study Regulations for Undergraduate

Programmes Section 1.3.12.

Plagiarism, Duplication, Collusion and Fabrication

Carrying out, and writing up the project must be exclusively the work of each

group. Plagiarism, duplication, collusion (between groups rather than within

groups) and fabrication is of concern to the university and your work should

conform to the requirements of academic integrity. Please read the “Procedures

for Dealing with Academic Offences” stated by the university.


TurnitinUK will be used to detect plagiarism. All suspect assignments will

be reported without exception.

Fernihough’s Golden Rules

Part of this project will be assessed on the project formatting and how neat

and tidy your report is. In addition to the formatting and other instructions

outlined in the above I suggest you obey the following rules when writing your

project up.

1. Justify the text in MS Word (not align right), or whatever word processor

you use.

2. Label all tables and figures appropriately. Table 1, Table 2, Figure 1, and

so on.

3. Tables are tables, not figures, so label them correctly.

4. Don’t repeat the question in your text. It’s a waste of space.

5. Double space text.

6. Don’t use any weird font type. Ariel, Times New Roman, and Calibri are


7. Don’t tell me what you did. For example, “I turned on my PC and loaded

Excel. After having a cup of tea I opened the data file and began to work,

and so on”.

8. Never copy and paste a screenshot. Edit your tables as instructed and

make them tidy.

9. Make sure your tables are consistent, i.e. things are on the right lines and

they are easy to read and interpret.

10. Put your labels at the top of each table and figure. For example, “Table 1:

Summary Statistics” should be at the top of the table.

11. Don’t pad your analysis out to meet the max word/page counts. These

counts are set as upper limits.

12. Pay attention to the number of decimal places you use when quoting a

number. More is not better.



This project requires you to work with annual data from the OECD on the

money-supply growth-inflation relationship over the period 1988–2017. This

relationship refers to the empirical regularity that connects money-supply growth

and output. In the literature researchers tend to fit the following bivariate linear

regression model:

In f lationt = b0 + b1MoneySupplyGrowtht + et,

and find that there is an positive relationship between the two (b1 > 0), thus

confirming that some degree of monetary neutrality exists.

The project data file is an Excel file called “oecd_data.xlsx”. This file consists

of one worksheet with four columns indicating the Country (using an

isocode id), the year in which the measurement is taken, alongside a measures

of the country’s inflation rate (annual % growth in the CPI) and an index of

broad money supply (M3). You can read more about these measures at the

following two links:



The project datafile is “messy” because I have scrambled these data. Before

commencing your analysis you will need to carefully sort these data so that all

of your country values are together and in the correct chronological order. In

the following questions I will refer to “your country” as the one you have been

allocated by me.

This assignment will be marked out of 100. The marks listed below provide

a rough indication of how much effort your should allot to that particular part.

(a) Create a table showing the average inflation rate for your country in the

periods 1988–2002, and 2003–2017 alongside the average inflation rate for

all countries in these two time periods (by for all countries I mean: what

is the average inflation rate for every country in this sample excluding the

one you have been allocated for these two periods?). This table should

consist of four sample mean estimates. Briefly describe the performance

of your country relative to the full sample. Do you see any issue in

pooling the inflation numbers for different counties? (5 Marks)

From now on all questions require you to work with the data from your

country only.


(b) Create a table that reports the sample mean, standard deviation, and

standard error for the inflation rate variable for your country for the following

three time periods 1988–2002, 2003–2017, and 1988–2017. Explain

why the standard error is different to the standard deviation and also

why you might expect the standard errors to be smaller in a larger sample.

(5 Marks)

(c) Construct and interpret a 95% confidence interval around the mean of the

inflation rate variable from part (b) over the period 1988–2017. (5 Marks)

(d) Motivate, perform, and interpret a hypothesis test that examines whether

the means of the inflation rate variable were equal during the periods

1988–2002 and 2003–2017. (10 Marks)

(e) In the next part you will need to create a money supply growth variable.

For example, say in 2015, the money supply index variable is 100 and this

figure was 97 in 2014, this means that money supply growth in 2015 was:

MoneySupplyGrowth2015 = 100

100 􀀀 97


= 3.092784% (1)

around 3.1 per cent. The easiest way to generate this variable is to create

the data in a column alongside the M3 index and use the following


MoneySupplyGrowtht = 100

MoneySupplyGrowtht 􀀀 MoneySupplyGrowtht􀀀1




Once you create this variable, produce a scatter plot (X-Y graph) showing

the relationship between the inflation rate (y-axis) and money supply

growth (x-axis) over the entire sample period (1989–2017, you will see

why 1988 cannot be included). Does this figure suggest monetary neutrality?

(10 Marks)

(f) Estimate, report and interpret the intercept (b0) and slope (b1) coefficients

of the following bivariate linear regression model over the entire sample


In f lationt = b0 + b1MoneySupplyGrowtht + et,

where In f lationt and MoneySupplyGrowtht are the same variables used

for the plot in part (e). (10 Marks)

(g) Use the linear equation from part (f) to calculate the RSS, TSS, and ESS.

Report and interpret the R2 statistic. (15 Marks)


(h) Report and interpret the standard error of the estimated slope coefficient


1. (10 Marks)

(i) Did the 2008 financial crisis change the relationship between the money

supply and inflation in your country? (15 Marks)

(j) Presentation. Marks will be allocated on the basis on the presentation

of your report. Make it neat and tidy and obey all of the instructions

outlined in the above. (15 Marks)

Hints and Tips

(a) Show some, but not all workings. You will need to be judicious. For

example, when performing a hypothesis test you may wish to show me

how the test statistic was calculated but do not need to show me how

all of the associated components (like standard errors and sample means

etc.) were calculated.

(b) Construct and interpret means, tell me how you did the calculation and

then tell me what it means. If you say what the numbers are but don’t

tell me what they mean that is not interpreting.

(c) We have covered a number of hypothesis tests in class. “Motivate” means

telling me why you chose this particular one over the alternatives.

(d) Interpret, in the context of the linear regression model, primarily means

that you tell me what the slope coefficient is doing. For example, the

slope coefficient is 2, then this implies ¶y/¶x = 2 so a one-unit increase

in x is associated with a 2 unit increase in y.




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