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BUS700 ASSIGNMENT Term 1 2020 BUS700 ECONOMICS T XXXXXXXXXX – Individual Assignment, Due 11.59 pm Friday Week XXXXXXXXXXMay 2020) Page 1 SUBJECT CODE & NAME: BUS700 ECONOMICS (PG) Due Date: 11.59 PM,...

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BUS700 ASSIGNMENT Term 1 2020
BUS700 ECONOMICS T XXXXXXXXXX – Individual Assignment, Due 11.59 pm Friday Week XXXXXXXXXXMay 2020) Page 1
SUBJECT CODE & NAME: BUS700 ECONOMICS (PG)
Due Date: 11.59 PM, FRIDAY WEEK XXXXXXXXXXMay 2020)
Section Details
Assessment N: Assessment 3

Assessment type: Research Report: 1500 – 2000 words report - Individual assessment
Assessment purpose: To enable students to research, critically analyse and evaluate the impact of the external sector on macroeconomic
performance of Australia and its policy implications. This assessment contributes to Learning Outcomes b, c, and d.
Assessment topic: Evaluation of the performance of net exports in Australia
Task details: Students will complete a research-based analysis and evaluation of Australia’s macroeconomic performance for the period
1990 to 2017. The response needs to be developed into a professionally presented report. Students will follow the following
procedure:
(1) Obtain data on real GDP, exchange rate, net exports (exports – imports), and the cash rate (interest rate). Then using
graphs and statistical summaries, discuss the relationships between the following variables:
a. Growth of net exports as a share of real GDP and the exchange rate
. Growth of net exports as a share of real GDP and the cash rate

(2) Conduct a simple regression analysis to investigate factors that influence the growth of net exports as a share of real GDP
in Australia.
(3) Given the insights gained from (1)–(2), discuss how macroeconomic policies, particularly monetary policies, would
contribute to improvement of net export growth as a share of real GDP in Australia?
Students need to support their analysis with a minimum of 10 academic journal articles plus the text. Students aiming for a
Credit or higher grade will need to use more sources. Articles should be relevant and recent. Non-academic journal sources
may also be used, but relevance and validity should be clarified with the lecture
tutor.
BUS700 ASSIGNMENT Term 1 2020
BUS700 ECONOMICS T XXXXXXXXXX – Individual Assignment, Due 11.59 pm Friday Week XXXXXXXXXXMay 2020) Page 2
Report format: 1500 – 2000 words report in Word.doc or .docx. Title page, executive summary, table of contents,
appropriate headings and sub-headings, recommendations/findings/conclusions, in-text referencing and reference list
(Harvard – Anglia style), attachments if relevant. Single spaced, font Cali
i 11pt.

Recommended sources of data are:
• www.abs.gov.au
• www.
a.gov.au
• www.imf.org
• www.worldbank.org.
• http:
datatopics.worldbank.org/world-development-indicators/
However, data may also be obtained from other credible sources. Also, recommended readings for government policies
include:
• Statement on Monetary Policy of the Reserve Bank of Australia for insights of monetary policies in Australia.
https:
www.
a.gov.au/publications/smp/
• Budget documents for insights of fiscal policies in Australia.
https:
www.budget.gov.au/2018-19/content/documents.html
1. This assignment is individual assessment.
2. Name and ID number of student must be clearly printed on the Assignment Cover Sheet.
3. Students must follow an appropriate format explained below. Not following appropriate format will cause a loss of some
marks.
• All analytical contents must be clearly typed and printed. Hand-written report will NOT be accepted.
• Appropriate heading or sub-title of each section must be typed and used.
• You must analyse, explain and show how and why you draw your conclusion.
• You must also draw and include appropriate and relevant graphs and tables together in your explanation. Draw them
using Microsoft Power Point/Word/Excel, NOT hand-drawn.
4. Plagiarism (copying the paper from other person) is a serious violation of copy right. It will be penalised and attract a very
heavy loss of marks – “Fail”. Make sure you do not show your work to other person(s). Both who show the work and who
copy the work will lose their marks heavily and fail in the assessment.
5. Only ONE COPY of the research paper is required to be submitted.
6. Make sure that you read and check everything in the research paper before submission, once completed.
http:
www.abs.gov.au
http:
www.
a.gov.au
http:
www.imf.org
http:
www.worldbank.org
http:
datatopics.worldbank.org/world-development-indicators
https:
www.
a.gov.au/publications/smp
https:
www.budget.gov.au/2018-19/content/documents.html
BUS700 ASSIGNMENT Term 1 2020
BUS700 ECONOMICS T XXXXXXXXXX – Individual Assignment, Due 11.59 pm Friday Week XXXXXXXXXXMay 2020) Page 3
• Knowledge and understanding of topic XXXXXXXXXX%
• Critical thinking, analysis and evaluation XXXXXXXXXX%
• Reading and Research XXXXXXXXXX20%
• Written presentation XXXXXXXXXX20%
• Identifying examples, both historical and
cu
ent, and make policy recommendations
improvement XXXXXXXXXX20%
Total mark will be scaled to a mark out of 20. A full Marking Ru
ic is provided below and also available in Moodle.

Submission
equirements details:
Due Date: 11.59 pm, Friday Week XXXXXXXXXXMay 2020)

Student will upload ONLY ONE SOFT COPY to Moodle by the due date.


BUS700 Learning Activity XXXXXXXXXX1
BUS700 ECONOMICS T319, DUE: 11:59 P.M. FRIDAY WEEK 10
Learning Activity Towards Preparation of Assignment
This activity will help you complete your assignment. KOI Economics and Statistics department uses
EXCEL often to undertake data analysis, as such, this activity introduces you to two useful functions of
EXCEL: regression analysis and graphs. Part I introduces how to use Excel for regression analysis; Part
II is about how to use Excel for graphs, and Part III contains recommended Youtube videos about using
Excel for regression analysis and interpretation of results. PLEASE NOTE THAT THE INFORMATION
CONTAINED IN THIS ACTIVITY IS A GUIDE FOR YOU TO COMPLETE THE ASSIGNMENT. IT SHOULD BE
USED AS A GUIDE TO THOSE WHO ARE UNFAMILIAR WITH REGRESSION ANALYSIS AND GRAPHS.
Part I: Regression Analysis
The first thing to do is to collect data on some variables and, then, specify a regression model. The
table below (2.3. Example 1) shows the values of the factors that influence the average demand for
energy bars: average income per person, tariff on energy bars imported, number of stores selling
energy bars. The dependent variable (Y) is demand for energy; and the independent/explanatory
variables (X) are income (X1); Tariff rate (X2); and number of stores (X3).
1.2 Multiple Regression Model
Y = α + β1X1 +β2X2 +β3X3 + β4X4 + ϵt XXXXXXXXXX1)
Demand = ( β1*Income)+ ( β2*Tariff)+ ( β3*No of Stores) + ϵt
The slope/coefficient/parameter (β1, β2 etc.) should be interpreted as the impact (effect) of the
explanatory variables (variable 1, variable 2 etc.) on the dependent variable.
1.3 Multiple Log-Linear Regression Model

LnY = α + β1lnX1 +β2lnX2 +β3lnX3 + β4lnX4 + ϵt XXXXXXXXXX2)
ln (Demand) = β1* ln (Income) + β2*ln (Tariff) + β3* ln (No of Stores) + ϵt
The slope/coefficient/parameter (β1, β2 etc.) should be interpreted as the percentage of the
dependent variable in response to percentage change in of the explanatory variable (variable 1,
variable 2 etc.) or the elasticity of the dependent variable with respect to the explanatory variable.
NOTE: WE CANNOT TAKE LN OF NEGATIVE NUMBERS.

* ONLY REGRESSION RESULTS, Tables and graphs are to be inserted in the body or essay. Place
aw data in the appendix.


BUS700 Learning Activity XXXXXXXXXX2


Part II: Regression Process - Excel

2.1: Installing/Activating Data Analysis tool in Excel

1. Open Excel, then
2. Go to File, then click on
3. Options. In left-hand side of Options dialog Box,
4. Add-ins, then on the bottom of right-hand side, Excel Add-ins appears in front of Manage
5. Click on Go, then in Add-ins dialog box, select
6. Analysis ToolPak, the click on
7. Ok, to return to Excel Worksheet.
8. On the Menu Bar, Click on Data, then see
9. Data
Answered Same Day May 18, 2021

Solution

Suraj answered on May 19 2021
146 Votes
Regression Analysis for GDP of Australia
Introduction : It is a problem of linear regression technique in which we are using the data of gdp of Australia for the year 1990 – 2017 . In this problem we discuss two types of regression which are multiple linear regression and multiple log linear regression . so for this task we follow the instruction as follow .
Data Collection : The first task in any statistical technique is to have the data and cleaning of the data . As clearly mentioned in the assignment that from where we have to pick the data , so we are following the same procedure and extract the data of net export of the Australia from the year , 1990 – 2017 as mentioned . we pick the relevant data from the given link. The link from where we pick the data is as follow :
http:
datatopics.worldbank.org/world-development-indicators/
data of the GDP is given as follow :
     Yea
    Cost Rate
     Exchange Rate
     Net Export
     1989
    1990
    1991
    1992
    1993
    1994
    1995
    1996
    1997
    1998
    1999
    2000
    2001
    2002
    2003
    2004
    2005
    2006
    2007
    2008
    2009
    2010
    2011
    2012
    2013
    2014
    2015
    2016
    2017
        1.0651
    1.0509
    1.0579
    1.0209
    0.9217
    0.8994
    0.9725
    0.9950
    1.0233
    0.8811
    0.8127
    0.8234
    0.7130
    0.6993
    0.7896
    0.9714
    1.0437
    1.0507
    1.1203
    1.3241
    1.0613
    1.3229
    1.4897
    1.5881
    1.4847
    1.3334
    1.2265
    1.0563
    1.0894
        0.7659
    0.7542
    0.7752
    0.7684
    0.7058
    0.7008
    0.728
    0.7793
    0.7865
    0.6634
    0.6293
    0.6055
    0.489
    0.5316
    0.5036
    0.7589
    0.7719
    0.7159
    0.807
    0.918
    0.6873
    0.9159
    1.0334
    1.0402
    1.0426
    0.9221
    0.7634
    0.9094
    0.8650
        299.268
    310.777
    325.310
    324.879
    311.544
    322.212
    367.216
    400.303
    434.568
    398.899
    388.608
    415.223
    378.376
    394.649
    466.488
    612.490
    693.408
    746.054
    853.100
    1053.996
    927.805
    1146.138
    1396.650
    1546.152
    1576.184
    1467.484
    1351.694
    1208.847
    1330.136

Now our fist task is to visualize the kind of relationship between the variables . for this we plot the scatter plot technique to show the kind of relation .
Scatter plot between the net export and the cost rate :
Scatter plot between the net export and the exchange rate :
Exchange rate For year 1989 – 2017
Cost rate For year 1989 – 2017
Conclusion from the above diagrams as follow :
In the first scatter plot , plotted between the Net Export rate as a dependent variable and the cost rate we see that there is some relationship between the two variables and it is a kind of negative relationship . In the second plot , between the Net Export rate as a dependent variable and the exchange rate we see there is some relationship between the two variables and it is a kind of negative relationship. So it means with the increase of one variable the second variable is decreases . we can measure the relationship between any two variables mathematically by calculating the co
elation coefficient between them.
Making the desired model :
Introduction : - The main advantage or use of Regression Analysis technique is to make predictions of interest . For this we have to calculate various coefficients like the intercept term and the slope , as mentioned in the assignment we can use the MS – Excel for making the model .
A Regression model is look like as follow :
Y = α + β1X1 + β2X2 + _ _ _ _ _ + βnXn + €
Where € is a e
or term and we assume that it is normally distributes with mean 0 and variance , and α is a intercept term and β1 , β2 , β3 , _ _ _ _ _ _ _ , βn are the slope terms in the model , in our model we have only two independent variables
Main : Now in our problem we have to build a model of the Net GDP of the Australia and the independent variables are the exchange rate and the cost rate of the GDP of the Australia form year 1990 to 2017 , for this the calculations are given .
The output of the model from excel is given as follow :
    SUMMARY OUTPUT
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    Regression Statistics
    
    
    
    
    
    
    
    Multiple R
    0.824172
    
    
    
    
    
    
    
    R Square
    0.67926
    
    
    
    
    
    
    
    Adjusted R Square
    0.654588
    
    
    
    
    
    
    
    Standard E
o
    264.7182
    
    
    
    
    
    
    
    Observations
    29
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    ANOVA
    
    
    
    
    
    
    
    
     
    df
    SS
    MS
    F
    Significance F
    
    
    
    Regression
    2
    3858547
    1929274
    27.53128
    3.8E-07
    
    
    
    Residual
    26
    1821968
    70075.7
    
    
    
    
    
    Total
    28
    5680516
     
     
     
    
    
    
    
    
    
    
    
    
    
    
    
     
    Coefficients
    Standard E
o
    t Stat
    P-value
    Lower...
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