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Assessment Answers : Corporate Accounting Management ACC3MAC

Assessment Answers : Corporate Accounting Management ACC3MAC

INTEGRATED
ACCOUNTING PROJECT
[ACC3MAC]
NAME OF THE STUDENT:
STUDENT ID:
Introduction and strategy
 Founded in 1924 is identifie …

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INTEGRATED
ACCOUNTING PROJECT
[ACC3MAC]
NAME OF THE STUDENT:
STUDENT ID:
Introduction and strategy
 Founded in 1924 is identified as one of the largest supermarket chains based in Australia
since 2019
 Specializes in dealing with items such as packaged food, meat, fruit and vegetables
 Woolworth also specialises in providing items such as baby supplies, stationery,
household product, health product and beauty products
 Main strategy followed by Woolworths can be directly identified in form of offer, growth
and efficiency
Last 3 year key performance indicator
under strategic pillar – Sustainability
Pillar
EMISSIONS FROM FACILITIES (t CO2e) (2019 -2021)
SCOPE 1 SCOPE 2 SCOPE 3 TOTAL
ALH 29,931 1,86,669 25,997 2,42,597
BIG W 10,672 1,05,209 19,962 1,35,844
BWS 5,916 45,887 6,604 58,407
Corporate 1,600 27,600 3,967 33,168
Dan Murphy’s 5,162 62,615 8,403 76,181
FABCOT 121 6,664 735 7,519
Logistics 253 89,231 20,616 1,10,101
New Zealand 28,926 30,133 19,685 78,744
Supermarkets and Metro 3,15,455 13,56,624 2,61,217 19,33,296
Grand Total 3,98,036 19,10,632 3,67,186 26,75,857
Last 3 year key performance indicator
under strategic pillar – Sustainability
Pillar
TRANSPORT EMISSIONS BY USE (t CO2e) (2019 -2021)
END USE AUSTRALIA NEW ZEALAND
Business travel 2,942 2,744
Home delivery 24,411 3,389
Logistics 3rd party road 1,76,997 23,247
Trolley collection 17,839 0
Last 3 year key performance indicator
under strategic pillar – Workplace
Pillars
FEMALE REPRESENTATION BY EMPLOYMENT CATEGORY 1 (2019 -2021)
Executives 30.60%
Senior Managers 37.91%
Managers 42.57%
Office support 55.63%
Technicians and trades 12.66%
Sales 59.22%
Other 18.55%
Last 3 year key performance indicator
under strategic pillar – Workplace
Pillars
WORKFORCE AND TURNOVER (2019 -2021)
Headcount by business unit
GROUP FEMALE MALE TOTAL
ALH (Venue & Support) 6,322 4,976 11,298
BIG W 12,089 5,479 17,568
Endeavour Drinks 6,785 9,982 16,767
Food Group 87,470 65,837 1,53,307
Statewide Independent Wholesalers 30 376 406
Group Support 2,867 7,854 10,721
Total 1,15,563 94,504 2,10,067
Analysis of the Results – EMISSIONS
FROM FACILITIES (t CO2e) (2019 – 2021)
0 500,000 1,000,000 1,500,000 2,000,000 2,500,000
ALH
BIG W
BWS
Corporate
Dan Murphy’s
FABCOT
Logistics
New Zealand
Supermarkets and Metro
EMISSIONS FROM FACILITIES (t CO2e) (2019 -2021)
TOTAL SCOPE 3 SCOPE 2 SCOPE 1
Analysis of the Results – TRANSPORT
EMISSIONS BY USE (t CO2e) (2019 –
2021)
0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
Business travel
Home delivery
Logistics 3rd party road
Trolley collection
TRANSPORT EMISSIONS BY USE (t CO2e) (2019 -2021)
NEW ZEALAND AUSTRALIA
Analysis of the Results – FEMALE
REPRESENTATION BY EMPLOYMENT
CATEGORY 1 (2019 – 2021)
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00%
Executives
Senior Managers
Managers
Office support
Technicians and trades
Sales
Other
FEMALE REPRESENTATION BY EMPLOYMENT CATEGORY 1 (2019 -2021)
Analysis of the Results – WORKFORCE
AND TURNOVER (2019 – 2021)
0 50,000 100,000 150,000 200,000 250,000
ALH (Venue & Support)
BIG W
Endeavour Drinks
Food Group
Statewide Independent Wholesalers
Group Support
Total
WORKFORCE AND TURNOVER (2019 -2021)
TOTAL MALE FEMALE
Accounting Standard having the biggest
impact on the financial results of the
company
 The relevant accounting standard having the most significant impact on
wools worth can be identified with Corporations Act 2001 (Cth ) as issued
by Code of Conduct APES 110
 The financial statements of Woolworth are also complied with the IFRS
standard which also has a considerable impact on the financials of the
company
 The corporations act is applicable for Woolworth while preparing the deed
of cross guarantee
 The IFRS standard is applicable for Margins including gross profit, CODB
and EBIT, Closing inventory days, Average inventory days and Free cash
flow after equity related financing activities excluding dividends
Sustainability goals integrated into
strategy of the company
 Woolworth has integrated the sustainability goals as per the strategy such
as strategy set by adhering to 17 global goals of United Nations in 2015 .
 The adherence to the relevant SDG can be depicted with compliance to
decent work and economic growth (SDG 8)
 Woolworth also adheres to the relevance of sustainability goals set by the
UN as reduced inequalities (SDG 10 ), no poverty (SDG 1 ) and decent work
on economic growth (SDG 8).
 Integration of the sustainability goals is seen with Life on land (SDG 12 ),
responsible consumption (SDG 15 ) and production and Life on land (SDG
15 ).
UN goals the company is trying to
achieve and progressing towards the
same
 The UN Goal it is trying to achieve can be directly inferred in form of
arranging desktop review of range of information resources
 Similarly, it is also looking forward to engaging external and internal
stakeholders based on UN 2030 SDG
 The third priority can be clearly depicted in form of emphasizing on
material issues for present opportunities/ risks evaluated in longer time
horizons
 The internal validation set by the senior leaders on board also plays a vital
role in UN 2030 Sustainable Development Goals
Executive remuneration practice of
the company
 The executive remuneration practice of the group directly relies on
monitoring the culture of the company, overseeing the consequence of
succession planning and remuneration frameworks
 As per the review of remuneration framework, we are able to identify how
STI scorecard will evolve to a new broader measure – Severity Rate
 The executive KMP remuneration comprises of short -term incentive, long –
term incentive, remuneration framework changes for 22 and terms of
executive KMP agreements
 The non -executive directors remuneration includes aggregate annual pool
fee of $4,000 ,000
Risk associated with the incentive
system of the company and mitigation
for the same
 Difficulty in management of composition arrangements
 Issues associated with proper alignment of incentive compensation with
both companies risk appetite and strategic objectives
 Development of current incentives with consideration of appropriate risk
appetite and risk profile
 Designing of relevant internal control to resolve excessive risk taking ability
and retaining necessary talent
Technologies adopted by the
company to help achieve the
strategic goals from 2020
 Technologies for addressing relevant climate change issues, water
conservation issues and packaging
 Relying on micro automation technology
 Introduced technology for reducing the congestion in floors during the
covid 19 pandemic
Thank You
References
 Grootboom, V. (2018 ). University of KwaZulu -Natal students’ perceptions of green branding at Woolworths (Doctoral dissertation) .
 HAO, T., & HOWE, T. C. (2018 ). VALUING SUSTAINABILITY TO CREATE VALUE : A BUSINESS PERSPECTIVE .
 Kabi , T. (2021 ). Sustainability in consumer marketing . Marketing to South African consumers . Cape Town : UCT Liberty Institute of strategic marketing & UCT Libraries . http ://doi . org/ 10 .15641 /0-7992 -2548 -5.
 Kasanagottu , S., & Bhattacharya, S. (2018 ). A Review of Metro, Target, & Woolworths Global Business Strategy . International Journal of Mechanical Engineering and Technology, 9(7).
 Maroun , W., & Atkins, J. (2018 , March) . The emancipatory potential of extinction accounting : Exploring current practice in integrated reports . In Accounting Forum (Vol . 42 , No . 1, pp . 102 -118 ). No longer published by Elsevier .
 Naidoo, M., & Gasparatos , A. (2018 ). Corporate environmental sustainability in the retail sector : Drivers, strategies and performance measurement . Journal of Cleaner Production, 203 , 125 -142 .
 Van der Haer , L. (2019 ). The race to sustainable retail trade : An exploration of brand personality within the South African context (Doctoral dissertation, The IIE) .
 Woolworthsgroup .com .au . (2022 a). Retrieved 14 May 2022 , from https ://www .woolworthsgroup .com .au/icms_docs/ 195984 _annual -report -2021 .pdf
 Woolworthsgroup .com .au . (2022 b). Sustainability Reports – Woolworths Group . (2022 ). Retrieved 14 May 2022 , from https ://www .woolworthsgroup .com .au/page/investors/our -performance/reports/Reports/CR_Reports
 Woolworthsgroup .com .au . (2022 c). About Us – Woolworths Group . (2022 ). Retrieved 14 May 2022 , from https ://www .woolworthsgroup .com .au/page/about -us

Assignment Answers : Principles of Economics ECON1011

Assignment Answers : Principles of Economics ECON1011

1
Principles of Economics
Student’s Name
Institutional Affiliation
2
Principles of Economics
Question …

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1
Principles of Economics
Student’s Name
Institutional Affiliation
2
Principles of Economics
Question 1: Fuel excised tax
a) In Australia, an excise tax is a duty on particular products manufactured in
Australia, and some of these commodities include tobacco, alcohol, and fuel. These types of
taxes are paid by the business and indirectly raise the price for consumers. Excise tax can be
paid by percentage or cost per unit of a com modity (Australian Government, 2021). An
excise tax per litre of Petroleum before 2022 -23 was 44.2 cents before it was halved to 22.1
cents per litre. Two of the main reasons to impose an excise tax on Petroleum in Australia
are: to generate revue and, sec ond, to recover from those that use roads the cost they put on
society.
b) Figure 1: change in consumer surplus, producer surplus, total surplus, price and total
quantity
3
From the above figure, in the Australian economy before the budget announcement of
reducing excise tax on Petroleum, consumer surplus was represented by triangle A, and pr oducer
surplus was triangle B. T he total surplus was A+B. The price before the announcement was P*,
and Petroleum demanded was Q*. However, following the announcements th at halved excises
duty on Petroleum, the demand curve and supply curve shifted to the right. Therefore, the new
consumers’ surplus increased from A to A1, the producer surplus increased from B to B1, and the
total surplus also increased. The price of Petro leum reduced from P* to P1, and the quantity of
Petroleum demanded increased from Q* to Q1 holding other factors constant.
C. E ffect of cutting tax on Petroleum
4
Yes, from a theoretical perspective, the federal Government’s cut in excise tax will have
an effect on the rising Inflation. The move will further increase Inflation. Cutting taxes on
products is an example of expansionary fiscal policy, which encourages people to buy more
Petroleum. When Government encourages consumption, there will be more mone y in supply,
leading to an increase in Inflation (Truger, 2015).
Question 2: Inflation
i. O’Neill, Ralph and Smith (2017) define Inflation as the decline in the purchasing
power of money evidenced in a general increase in prices of commodities in an economy o r
simply defined as an increase in the prices of goods and services in an economy. In Australia,
the major groups of goods and services included in the Consumer Price Index (CPI) basket
fall into the eleven groups: Education, Food and non -alcoholic beverag es, Health, Transport,
Housing, Communication, Recreation and culture, Alcohol and tobacco, Furnishings,
household equipment and services , Clothing and footwear, and Insurance and financial
services (Australian Bureau of Statistics, 2020).
ii. Major drivers of CPI changes
Figure 2
5
From figure 2 above, the major drivers of CPI changes and their contribution to price rises over
the January – March quarter of 2022 are education with a change of 4.5 from the previous
quarter, followed closely by transport at 4.2, then housing follows at a distance with 2.7. Health
had 2.3 . Clothing and footwear had the least with -0.6.
Question 3: Macroeconomic variables in the 2022 -23 Federal Budget
Regarding growth, the Government has predicted growth for 2022 -23 to increase f rom
3.75% to 4.25%. The GDP growth will remain unchanged at 3.5%. The unemployment was
predicted to fall by 3.75 % by June 2023 from 4.25%. Also , the wages and Inflation have been
revised upwards. There is optimism about the near -term growth, but wages and Inflation will
6
also increase. The Government has postponed its $US55/tonne iron ore price supposition to the
September quarter of 2022. Currently, the iron ore stands at approximately $US135/tonne, and it
is expec ted to generate more revenues (Australian Government Department of Education, Skills
and Employment, 2022).
The Government has set up $12 billion that is committed to supporting the National
Skills Agreement in states and territories for a period of five years. The Australian Government
has set $3.7 billion for the 2022 -23 Budget in addition to $8.3 billion for the National Skills and
Workforce Development Specific Purpose Payment. Once the NSA is approved, it will change
the approach of all government sup port to vocational education and training to ensure higher
national consistency and increase the transparency of investment decisions. In the next five
years, NSA can deliver approximately 800000 extra training places (Australian Government
Department of E ducation, Skills and Employment, 2022).
Question 4: Automotive fuel and owner -occupied new dwellings’ prices affect the CPI of
Australia
The CPI of the March 2022 quarter shows that there is Inflation. Inflation has increased
by 2.1% in the quarter and 5 .1% throughout the year. Automotive fuel was the leading
contributor to the quarterly CPI rise, an 11% increase in the quarter and an increase of 35%
annual up to March. Compared to mid -2020, the fuel prices in March were 62% higher. Offset
was predicted i n the June quarter with a short fuel excise reduction. Similarly, there was an
increase in the new dwellings purchases by owner -occupies by 5.7% from the last quarter, the
largest in quarter since 2000 (Rumbens & Malouf, 2022) . The rise was significantly c ontributed
by persistent shortages of supplies like a shortage in labor and a rise in freight costs.
7
Other contributors significantly added to CPI in this quarter. They included tertiary
education, which rose by 6.3% in the quarter, reflecting the effect of updated student
contribution fees and bands. Also, a strong jump was experienced in the food, rising by 2.8%.
The beef recorded a 7.6%, vegetables had 6.6%, and fruits had a 4.9% quarterly increase. The
increase in the costs of food was largely contrib uted by a higher cost of inputs coupled with
Covid -19 interference in the latest months (Rumbens & Malouf, 2022). Therefore, there is a
problem of Inflation in Australia, although not as bad as in other parts of the world. In other parts
of the world, Inflation is as high as 40% annually. For instance, in the U.S, there has been the
largest increase in the prices since the early 1980s, recording a j ump of 8.5% over the year to
March 2022. The main contributor to the prices in the U.S is the high costs of fuel due to the war
in Ukraine that has interfered with supply chains.
8
References
Australian Bureau of Statistics. (2020). Consumer Price Index, Australia methodology. Retrieved
from https://www.abs.gov.au/methodologies/consumer -price -index -australia –
methodology/mar -2020
Australian Government (2021). Excise duties. https://business.gov.au/finance/taxation/excise –
duties
Australian Government Department of Education, Skills and Employment. (2022). Budget 2022 –
23. Re trieved from https://www.dese.gov.au/about -us/corpor ate -reporting/budget/2022 –
23 –
budget#:~:text=Under%20this%20measure%2C%20the%20Australian,Workforce%20De
velopment%20Specific%20Purpose%20Payment .
O’Neill, R., Ralph, J., & Smith, P. A. (2017). What Is Inflation?. In Inflation (pp. 21 -43).
Palgrave Macmillan, Cham.
Rumbens, D. & Malouf, A. (2022). The CPI – Australia’s inflation problem confirmed; over to
you, RBA. Retrieved from https://www2.deloitte.com/au/en/blog/economics –
blog/2022/cpi -australias -inflation -problem -confirmed.html
Truger, A. (2015). The Fiscal Compact, cyclical adjustment and the remaining leeway for
expansionary fiscal policies in the Euro Area. Panoeconomicus , 62 (2), 157 -175.

The Allocation of Investment Capital- MN2565

The Allocation of Investment Capital- MN2565

ONLINE EXAM INSTRUCTIONS
• Type your answers in an MS Word or Excel file where possible. Fully handwritten answers
are not permitted. …

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ONLINE EXAM INSTRUCTIONS
• Type your answers in an MS Word or Excel file where possible. Fully handwritten answers
are not permitted.
• The total word limit for this paper is: 3000. Examiners will not continue marking past this
limit. • Fill in the online exam submission cover sheet and include it as the first page of
your answers .
Page 2 MN -2565 (May/June 2022)
SECTION A – Answer ALL Questions – Multiple Choice [5 marks each]
FOR EACH QUESTION IN SECTION A, INDICATE CLEARLY WHICH OF THE FOUR
OPTIONS YOU CONSIDER TO BE THE ANSWER, AND PROVIDE A BRIEF
WRITTEN EXPLANATION JUSTIFYING YOUR CHOICE.
1. What is the effect of an increase in the income tax rate on the equilibrium price of an
inferior good?
A. The equilibrium price will go up.
B. The equilibrium price will go down.
C. The equilibrium price will stay the same.
D. The equilibrium price may go up or down.
2. If market demand gets more elastic, this means that the market demand curve A.
gets steeper.
B. gets flatter.
C. shifts to the right.
D. shifts to the left.
3. Analyse a consumer’s choice of consumption bundle, and compare two consumption
bundles X and Y. X is located on the budget line, and Y is located below the budget line .
Based on this information, which of the following can you say with certainty?
A. The consumer prefers X over Y.
B. The consumer prefers Y over X.
C. You do not know whether the consumer prefers X or Y.
D. X is the consumer’s optimal consumption bundl e.
4. Your firm operates in a perfectly competitive market. The market price is above both your
firm’s average total cost and your firm’s marginal cost at the quantity that your firm is
currently producing. Which of the following is true?
A. Your firm ru ns a loss and could reduce this loss by producing a larger quantity.
B. Your firm runs a loss and could reduce this loss by producing a smaller quantity.
C. Your firm makes a positive economic profit but could make more profit by
producing a larger quantity.
D. Your firm makes a positive economic profit but could make more profit by producing
a smaller quantity.
Turn Over
MN -2565 (May/June 2022) Page 3
5. In the table below, you can find the willingness to pay for each extra unit of a good, along
with the marginal cost of producing that extra unit of the good. The maximum possible
total surplus is
Unit First Second Third Fourth Fifth
(Marginal)
Willingness to pay
40 35 32 30 28
Marginal
Cost
20 24 28 32 36
A. 12
B. 28
C. 32
D. 35
6. In the table below, you can find the willingness to pay for each extra unit of a good, along
with a monopolist’s marginal revenue and marginal cost of producing that extra unit of
the good. The deadweight loss due to the inefficient market structure is
Unit First Second Third Fourth Fifth
(Marginal)
Willingness to pay
40 35 32 30 28
Marginal
Cost
20 24 28 32 36
Marginal
Revenue
40 30 26 24 20
A. 2
B. 4
C. 6
D. 11
Page 4 MN -2565 (May/June 2022)
7. Assume the below table includes all transactions in a country that produces potatoes and
imports Ketchup. The country’s GDP is
Item Price Quantity
Potatoes (domestic consumption) 1 500
Potatoes (export) 1 500
Ketchup (imported; domestic consumption ) 2 100
A. 700
B. 800
C. 1,000
D. 1,200
8. In a country where apples are produced and exported but not consumed, a change in the
price of apples will affect
A. the CPI but not the GDP deflator.
B. the GDP deflator but not the CPI.
C. both the CPI and the GDP deflator.
D. neither the CPI nor the GDP deflator.
9. Structural unemployment occurs because
A. it takes time for workers to search for the jobs that best suit their tastes and skill s.
B. minimum wage laws force the wages to remain above their equilibrium levels. C.
some people are economically inactive.
D. the number of jobs available in some labour markets is insufficient to provide a job
for everyone who wants one.
10.In th e Solow model of economic growth, a country with a higher rate of capital
depreciation will, ceteris paribus, have a steady -state equilibrium with A. lower output
per worker.
B. higher capital to labour ratio.
C. the same capital to labour ratio.
D. more investment.
Turn Over
MN -2565 (May/June 2022) Page 5 SECTION B – Answer ONE Question ONLY
Question B1
A central bank carries out a contractionary open market operation.
(a) What precisely does the central bank do in such an event?
[10 marks]
(b) Use the Theory of Liquidity Preference and the AD/AS model to analyse the short -run effects
of this policy on GDP and the price level in the economy.
[20 marks]
(c) Another way of achieving the same thing as in an open market operation is to change the banks’
refinancing rate. Explain carefully in which direction this rate would have to change in order
to achieve the same effect as the aforementioned contractionary open market operation, and
how the banks’ reaction to this change brings about this effect .
[20 marks]
[50 marks total]
Question B2
The government announces a cut in the income tax rate.
(a) Explain the multiplier effect by analysing how a typical consumer would react to this
tax cut and which other decisions this reaction would trigger in the economy. [15 marks]
Answer
The two principal tools of fiscal policy are expenditure of government and tax rates.
Governments can borrow money to fund public infrastructure such as bridges and highways,
or they can give money back to taxpayers in the form of lower tax rates or tax refunds.
In either instance, there is an increase in total quantity of money in the system. This translates
to more demand for products and services, as well as higher production to supply that need.
More hiring is required as output rises, resulting in more money to spend on products and
services.
The multiplier effect can be said to be any fac tor which is greater than one except in rare
circumstances. That is, the quantity of money injected into the economy by the government
will be exceeded by the amount of income it generates.
If the multiplier impact is 3, each dollar of stimulus will result in a $3 rise in total revenue.
Increased consumption and expenditure by consumers and companies are inextricably linked
to government stimulus funds. More things are purchased by consumers. Businesses expand,
invest, and recruit additional employees. The GDP (gross domestic product) is increasing.
Fiscal policy therefore has a multiplier impact
Further, reduction in tax shall increase the consumption in the economy which shall boost
the growth of GDP also the said action shall result in income of the peop le and thus tax
revenue of the government shall increase on account of increased expenditure.
The cut in tax shall trigger production and supply decisions on account of increase in personal
disposable income, inflation decisions and monetary auit
(b) Use t he AD/AS model to analyse the short -run effects of this policy on GDP and the price level
in the economy.
[15 marks]
Ans b
The cut in tax rate shall increase the consumption and shall cause the AD curve to shift to
the right. At this new equilibrium it is expected that the real GDP shall rise and the
unemployment shall fall as the economy has not yet reached the full level of employment
and any rise in the price level remains muted. The diagrammatic presentation is as under:
Thus, price is expected t o rise and unemployment shall fall in the short run.
(b) What are the long -run effects of the tax cut?
Answer
A higher marginal tax rate can discourage work, saving, investment and form of innovation,
while at the same time a tax preference can also affect the economic resources allocation. At
the same time tax cuts can slow the long run growth in economy by an increase in deficits.
The long run tax policy is dependant not only on the incentive effect but also their deficit
effect.
1. Tax incentive: Taxes can have effect on both demand and supply factors. A reduction
in margin al rate of tax on wages and salaries can bring lower skilled worker on board.
Low tax rate on dividend and interest gain can also foster saving and also force
domestic company to invest in own country rather than in foreign country.
But at the same time reduction can have negative supply effects, if a worker’s income
after tax cut increases than may people may choose to work less and take leisure more.
The “income effect “ pushes against the “substitution effect “in which low rate of tax
increases the financial reward of working.
Tax regulations can potentially skew the allocation of investment capital. For example,
our existing tax structure encourages housing over other sorts of investment. This
disparity is likely to lead to excessive housing investment, lowering economic
production and social welfare.
2. Deficits in Budget: At the same time cut in tax also w long run economic growth by an
increase in budget deficits. When an econ omy is operating near potential, the finance
of government by divulging few capitals that could have gone into private form of
investment or borrowing through foreign investors.
The long -run impacts of tax policy are thus determined by both their incentive and
budgetary implications. If the marginal tax rates are reduced by government on
individual incomes, for example, the long -term implications might be favourable or
negative, depending on whether the enhanced savings and investment benefits offset
the po tential drag from higher deficits.
On basis of above it can conclude that, cut in tax boost the economy by putting more money
into circulation process. At the same time deficit is also increased if the same is not offset by
spending cuts. As a result of this, a cut in tax improves the economy in the short term, but at
the same time if they lead to an increase in federal debt, economy will be depressed in long
run period of time.
[20 marks]
[50 marks total]
End of Paper

Task Solutions on Globalisation Of Footwear Product: SO4705

Task Solutions on Globalisation Of Footwear Product: SO4705

Running head: GLOBALISATION OF FOOTWEAR PRODUCT
GLOBALISATION OF FOOTWEAR PRODUCT
Name of Student
Name of University
Author notes
2 GLOBALISATION …

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Running head: GLOBALISATION OF FOOTWEAR PRODUCT
GLOBALISATION OF FOOTWEAR PRODUCT
Name of Student
Name of University
Author notes
2 GLOBALISATION OF FOOTWEAR PRODUCT
Introduction
After globalization, the global economy has become independent and its culture,
population has also evolved significantly. Due to the effect of globalization, different
companies have been able to gain competitive advantage while others have been able to
reduce their operating costs and expenses to significant extent. Globalization has created job
opportunities in different sectors across the globe and have revolutionized the cross-border
flow of different products and footwear product is not an exception to this. In recent
timeframe, globalization in the footwear industry has created significant number of
implications and searched for cheap labor within the industry (Findlay, Mavromaras & Wei,
2021). For footwear products, it has been evident that the labor costs have became cheaper
and the same has affected on labor market negatively. Further, it has been also evident that
due to the globalization, role of labor market for footwear products have changed and various
macroeconomic factors articulated in the global supply chain. Different sets of barriers
related to the exchange rates; trade barriers have also affected the footwear industry
significantly. Post globalization, ithas been evident that the supply chains and trade routes of
footwear industry has evolved and there have been various forces affecting the production,
distribution as well as the use of the footwear products. In the following section of the essay,
the evolution of the footwear product in light of globalization will be explained. Afterwards,
the main forces behind globalization and implications for globalization of footwear products
will be analyzed based on different set of arguments. Finally, the forces behind the
production, distribution and use of shoe products will be understood and denoted in the
analysis.
3 GLOBALISATION OF FOOTWEAR PRODUCT
Discussion
The evolution of the footwear product in light of globalization
In the developing countries, globalization has been affected heavily on the footwear
industry. It has been prevalent that multinational companies are taking advantage of the
manufacturing factories and are looking for cheap labor. In the recent timeframe, it has been
evident that the footwear industry has experiencing significant number of changes. Being
trader of labor inventive product within the industry, it has been evident that the developing
countries are displacing industrialized countries as traders (Wang & Song, 2019). In the
footwear industry, it has been evident that the developing countries are accumulating
competitive weights. In weight of the industrialized structure of developing countries, it has
been evident that the Western economies are controlling the industrial value chains globally
and in locations in low-cost economies.
With reference to the traditional theory, also known as Stolper Samuelson theorem, it
has been evident that the changes in the piece of skilled labor post the globalization have
significantly improvised the footwear industry (Basco etal 2020). Further, the theorem
denotes that the there is atraditional link between the trade, changes to the wages structure
which has also made the transition process seamless. Despite of the fact, many researches
have denoted issues related to finding sufficient amount of evidence related to the reduction
in the price of footwear product that has significantly reduced after the globalization. Based
on the analysis, it has been also evident that within the footwear industry, the need of both
skilled and unskilled workers is different and it may significantly cause fluctuations in the
price of footwear products (Chemirbayeva, Malgarayeva & Azamatova, 2020). With that
being said, it can be noted that after the globalization period, the demand and competition of
4 GLOBALISATION OF FOOTWEAR PRODUCT
footwear product has significantly increased which forced companies to reduce the prices of
their shoe products significantly and has made changes to the import and exports.
After the globalization, the revolution of footwear product has become apparent and it
evident that the import penetration and export intensity has become more prominent after the
globalization. With the increase in import penetration, it has been also apparent that the
export intensity has also increased significantly which in turn created employment in the
footwear industry. Arguers denote that despite of the increase in the employment, the
production of footwears has significantly fell which has affected the footwear industry to
significant extent. Despite of the fact, it is evident that the footwear production has largely
shifted to the developing countries after the globalization which has overall increased the
supply at less cost. After globalization, it has been evident that the export of footwear has
increased to significant extent and exports has grown at arapid rate which signifies that the
footwear industry has perceived asignificant amount of growth post globalization.
The main forces behind globalization for footwear product
For the footwear products, the primary forces behind globalization which made
gradual changes to the economy are denoted below.
Advancement of technology
Before globalization, technological improvement was not in sight and it was not
contributing positively towards the footwear industry. It has been evident that the
improvement in technology remains one of the key factors behind globalization and
improvement in telecommunication and information technology within the industry has
improved communication between key stakeholders within the industry. Further, it has been
also apparent that increase in technology has brought significant amount of improvement
within the economic activities of acountry (Lund, Manyika & Spence, 2019). As aresult, it
5 GLOBALISATION OF FOOTWEAR PRODUCT
has been apparent that global footwear industry has been able to perceive growth with the
advancement of technology.
Besides, it has been also evident that the advancement of technology and improved
communication within the footwear industry has also facilitated seamless exchange of
products and services in different geographic location.
Reduction of cross border trade barriers
Cross border trade barriers were among one of the most significant issues affecting
the footwear product significantly. The movement of products and services across the border
were restricted and there were various tariffs and quotas on the products and services that is
imported to the country. There were also frequent regulatory changes that has created chaos
within the global business environment significantly. ithas been evident that the cross-border
barriers also limit the international business activities to significant extent. Despite of the fact,
ithas been evident that there were gradual relief within the cross-border trade restrictions that
made government to improve growth of the economy.
Increase in consumer demand
Increase in consumer demand also acts as one of the primary drivers that facilitates
globalization. As per the recent forms of research, ithas been evident that in recent timeframe,
there has been increase in the level of income and standard of living that has affected towards
the increase in demand of customers in the footwear industry as well as other industry. After
globalization, customers are now well known about the products and services available in
different countries as well as recognizes the association of different organizations with
foreign players that has been allowed in meeting the need of domestic market
(Adulyanukosol & Silpcharu, 2020).
High competition
6 GLOBALISATION OF FOOTWEAR PRODUCT
High competition is also among one of the most important drivers of globalization.
Within the organizational environment, it has been evident afootwear business significantly
strives to gain competitive advantage within the market. After globalization it has been
evident that the competition in the domestic market has increased significantly which further
has affected the ability of the organization to improve their potential and expand their market
share significantly. Further, it has been also evident that the export footwear product within
the foreign market is higher and the prices of products and services are also higher. With the
help of mergers and acquisitions, it has been evident that organization has been able to
improve existing condition within the footwear industry.
Implications for globalization of footwear products
Within the footwear industry, globalization has brought various implications which
needs to be evaluated in order to understand the impact of globalization in footwear products.
The increase in consumption of footwear product towards the ecological cycle has been
affected significantly. With effect to the increase in demand for footwear product with
globalization, it has been apparent that production of goods has stressed the environment
significantly. With essence to globalization, researchers have also denoted that transportation
of raw materials and footwears have increased significantly which affected the environment
significantly and increased pollution level massively. Further, the foreign trade has brought
various concerns such as water pollution, landscape intrusion as well as noise pollution.
Globalization has also affected on the cultural diversity and has exploited the
consumer confidence towards certain footwear products. It has been also apparent that the
societal values have also become affected which led to loss in traditions and values. It has
been also prevalent that globalization is beneficial for the wealthy part of the society who
knows global trends within the footwear industry (Dewi etal 2020). Poor consumers who
7 GLOBALISATION OF FOOTWEAR PRODUCT
have know sense about the footwear and can be scammed and therefore affecting the society
negatively. Further, it has been also apparent that in light of globalization, advertisement for
footwear products has been also apparent which can be correct or incorrect depending on the
situation. Hence the footwear businesses can have tough situation to control the problems
related to advertising.
As per the view of the non-economists and public, it has been apparent that the
negative effect related to the globalization can significantly outweigh the advantages within
the footwear industry ithas been evident that trading in less wealthy countries became riskier
as compared to the developing countries. Further, the scene of employment has also changed
post globalization which showed that despite of increase in demand for workers in the
footwear industry post globalization, workers are not getting paid enough which is aserious
concern.
Along with footwear products, other domestic products can become endangered post
globalization due to the absolute advantage of other countries within the footwear industry.
Another significant implication is the overuse of natural resources to meet the higher demand
in the production of possessions (Gavranovi ć,2018). Price instability can become one of the
most significant concerns affecting the overseas industry of footwear products. Due to the
increase in competition, price instability occurs and affects the footwear industry as awhole.
After globalization, currency fluctuations are also occurring within the economy which is
making the economic condition worse and affecting price level as well.
The forces behind the production, distribution and use of shoe products
During the production process, land, labor, capital and entrepreneurship are the
primary forces that is affecting the shoe products. Land is used to begin the operations and
processes of the industry and is one of the most significant forces behind the production
8 GLOBALISATION OF FOOTWEAR PRODUCT
process. Labor is also one of the most crucial factors without which the business cannot be
able to improve over time. Within the footwear business, having skilled labor will allow
businesses to attain growth while businesses can increase their value to significant extent.
Skilled workers are known as human capital and they are paid with more wages as they bring
value to the organization. Capital is the flow of money within the business and is aprimary
driver of value within the organization (G ürbüz, 2018). An organization will have to
distinguish the personal as well as private capital in favor of its production. If there is
economic contraction while the business is suffering losses, businesses will have to reduce its
capital expenditures to earn profits.
Within the distribution process, the business will have to evaluate perishability of the
product, technical aspects, divisibility of the product as well as legal aspects of the product.
Footwear product are not perishable hence the use of direct channels is nor preferable
however, with advanced transportation facility, footwear products can be distributed towards
its customers. Further, itis also evident that different technical aspects related to the footwear
product is also needed to be evaluated to make sure that the customers are satisfied.
Forces that affect the use of shoes of consumers includes the price of shoe, its
availability, brand value and so on. It has been apparent from recent source of research that
after globalization, cross border trades were more transient which improved the availability
of both branded and non-branded shoe products. It has been also apparent that the sale of mid
ranged shoes is higher as compared to high ranged shoes. As per local shoe industry analysis
domestic shoes became less appealing in terms of stylishness and diversity than imported
footwear (Meraviglia, 2018). In terms of shoe performance, the study discovered that local
leather shoes were more durable but less ergonomic than their imported counterparts. As a
result, customers who were exposed to criteria other than durability chose domestic shoes,
while those addressed to ergonomics preferred international shoes. In terms of pricing, the
9 GLOBALISATION OF FOOTWEAR PRODUCT
survey revealed that local leather shoes were less expensive than international shoes. As a
result, the domestic leather shoe ruled the shoe preferences of the majority of price-conscious
consumers.
In acompetitive and rapidly changing world, product acceptability by customers is a
critical problem that must not be overlooked for any commercial operation to be profitable.
Consumers nowadays regard each commodity as abundle of qualities with variable abilities
of delivering the advantages to meet this need and desire while looking for a product to
satisfy their need and want. Despite the fact that consumer preferences differ by product,
style, quality, and pricing are all desirable characteristics in ashoe. Furthermore, customers
differed by demographic component; age in terms of the product qualities they consider most
important and the value they denote on each attribute.
Conclusion
On aconcluding note, it can be evident from the above analysis that the revolution of
footwear products has been visible since globalization, and it is clear that import penetration
and export intensity have become more significant since globalization. With growing import
penetration, it is also clear that export intensity has expanded dramatically, creating jobs in
the footwear business. Cross-border trade obstacles were among the most serious concerns
facing the footwear industry. The flow of goods and services over the border was limited, and
different levies and quotas were imposed on goods and services brought into the nation.
There were also regular regulatory changes, which dramatically disrupted the global
corporate landscape. Globalization has also had an impact on cultural diversity as well as has
abused customer trust in some footwear items. It is also clear that society ideals have been
impacted, resulting in the erosion of traditions and culture. It has also been established that
globalization benefits the rich segment of society that is aware of global trends in the
10 GLOBALISATION OF FOOTWEAR PRODUCT
footwear sector. Other indigenous goods, in addition to footwear, may become endangered as
aresult of globalization due to other nations’ absolute superiority in the footwear business.
Another key impact is the exploitation of natural resources to fulfil the increased desire for
goods. Price volatility may become one of the most serious issues impacting the international
footwear business.
11 GLOBALISATION OF FOOTWEAR PRODUCT
References
Adulyanukosol, A., & Silpcharu, T. (2020). Footwear design strategies for the Thai footwear
industry to be excellent in the world market. Journal of Open Innovation: Technology,
Market, and Complexity ,6(1), 5.
Basco, S., Li égey, M., Mestieri, M., & Smagghue, G. (2020). The Heterogeneous Effects of
Trade across Occupations: A Test of the Stolper-Samuelson Theorem.
Chemirbayeva, M., Malgarayeva, Z., & Azamatova, A. (2020). Economic strategy of
diversification of enterprise activities under conditions of globalization. Entrepreneurship
and Sustainability Issues ,8(2), 1083.
Dewi, M. U., Mekaniwati, A., Nurendah, Y., Cakranegara, P., & Arief, A. S. (2020).
Globalization challenges of micro small and medium enterprises. Eur. J. Mol. Clin.
Med ,7(11), 1909-1915.
Findlay, C., Mavromaras, K., & Wei, Z. (2021). Economic consequences of globalisation: the
Australian framework for reforms. this volume ,26-56.
Gavranovi ć,A. (2018). How to deal with new challenges? Economic, technological and
social aspects of the textile and clothing industry. Textile & Leather Review ,1(1), 29-33.
Gürbüz, E. (2018). Theory of new product development and its applications. Marketing ,57-
75.
Lund, S., Manyika, J., & Spence, M. (2019). The Global Economy’s Next Winners: What It
Takes to Thrive in the Automation Age. Foreign Aff. ,98 ,121.
Meraviglia, L. (2018). Technology and counterfeiting in the fashion industry: Friends or
foes?. Business Horizons ,61 (3), 467-475.
12 GLOBALISATION OF FOOTWEAR PRODUCT
Wang, Q., & Song, X. (2019). Indias coal footprint in the globalized world: evolution and
drivers. Journal of Cleaner Production ,230 ,286-301.

Assignment Answers of The Colon Adenocarcinoma- BIOL122

Assignment Answers of The Colon Adenocarcinoma- BIOL122

Running head: COLON ADENOCARCINOMA
COLON ADENOCARCINOMA
Name of the Student
Name of the University
Author Note
1 COLON ADEN …

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Running head: COLON ADENOCARCINOMA
COLON ADENOCARCINOMA
Name of the Student
Name of the University
Author Note
1 COLON ADENOCARCINOMA
Answe r 1
a) The intestina l wall is made up of multip le layers . The four layers from the lume n
outwards include s submucosa l layers, mucosal layer, serosa layer and muscula r laye r.
The muscular layer is made of up of 2 layers of smooth muscle includ ing the oute r
layer, inner layer, circular and longitud ina l layer. The structure of large intestine
consists of three parts such as the colon, rectum and anal . The large intestine consists
of digestive tissue layer named lamina propria. It is stated that the three parts of the
large intestine helps in absorbing electrolyte s and water, producing or absorb ing
vitamins and forming feces. The three differe nt layers of the large intestine where the
adenocarcino ma occurs includes allowing the contraction of the longitud ina l musc le ,
providing proper blood supply and helping in absor ption. (Nasef & Mehta, 2020).
b) The five major risk of developing colon adenocarcino ma includes age, family histo ry
of Lynch syndrome, history of cancer, infla mma tory bowel disease and unhealthy diet.
The six ways which is usually considered by the healthc are professiona ls for impro v in g
the knowledge and lowering the chances of developing cancer includes early scree ning
process such as imaging tests , recommend ing healthy diet, mainta ining regula r
exercise, lowering alcohol or smoking consumptio n and providi ng diet or nutritio n a l
counselling (Sawicki et al., 2021) .
Answe r 2
a) It is stated that the mutatio n in the POLD1 and POLE genes are associated with the
increased risk of colorectal or colon cancer. The family history with such muta tio n
results in increases the risk of developing cancers and polyps with MAP, AFAP, FAO
and lynch syndrome. Pan et al., (2022) stated that tumors with mutp53 and wild typ e
2 COLON ADENOCARCINOMA
p53 is common among the patient with colon cancer . It is also stated that mutatio n in
the non -GOF and mutp53 is associated with less surviva l of the patient.
b) It is stated that the metastasis of colorectal cancer spreads in the early stage when the
tumour is found to break from the origin and travels with the help of lymph and blood
to the various parts of the bo dy includ ing the lung, brain and liver where the new tumo r
cells is found to settle and increasing the spread of cancer (Kamal et al. ,
2019) . Riihima rk i et al., (2016) stated that metastasis spread in the colon and recta l
cancer is found to be challenging and the study highlighted the fact that the most
common area of rectal cancer metastasis into the thoracic organ includ ing the nervo us
system and less frequency is observed within the peritoneum. The study also
highlighted the fact that within the perito neum signet ring adenocarcino ma and
mucino us it is mostly mitic ide. The pattern of metastasis is found to differ from colo n
and rectal cancer. The metastasis occurs in Stage IVA where the cancer is characterize d
by the spread from one organ to another. Th e most common site of metastasis occurs
in the liver, lungs, spinal cord and bones (Munro et al., 2018) .
Answe r 3
Chemotherapy helps in eradicating the cell by splitting into two and prevents the
chance of multip licatio n which is essential to reduce the metastasis in cancer (Fields et al. ,
2019) . The chemo drugs are found to attack the cells by divid ing it quickly. The chemothe ra p y
which is usually used for the patient suffering from colon adenocarcino ma includes adjuva nt
chemotherap y which is usually pr ovided after the surgery in order to kill the cancer cell whic h
might escape from the main colon and it also helps in lowering the chance of cancer spread
(Manjelie vsk a ia et al., 2017) . The neoadjuvant chemotherap y is usually given before the
3 COLON ADENOCARCINOMA
surgery and h elps in shrink ing the cancer cell. The other chemotherap y include s syste mic
chemotherap y, hepatic artery infusio n and regional chemotherap y (Body et al., 2021) .
4 COLON ADENOCARCINOMA
References
Body, A., Prenen, H., Latham, S., Lam, M., Tipping -S mith, S., Raghunath, A., & S egelov, E.
(2021). The role of neoadjuvant chemotherapy in locally advanced colo n
cancer. Cancer Management and Research , 13 , 2567. doi: 10.2147/CMAR.S262870
Fields, A. C., Lu, P., Goldb erg, J., Irani, J., Bleday, R., & Melnitc ho uk, N. (2019). The role of
adjuvant chemotherapy in stage II and III mucino us colon cancer. Journal of surgical
oncology , 120 (7), 1190 -1200. https://doi.org/10.1002/jso.2 57 05
Kamal, Y., Schmit, S. L., Hoehn, H. J., Amos, C. I., & Frost, H. R. (2019). Transcripto mic
differe nces between primary colorectal adenocarcino mas and distant metastases reve a l
metastatic colorectal cancer subtypes. Cancer research , 79 (16), 4227 -4241.
https://doi.org/10.1158/0008 -54 72. CAN -18 -3 94 5
Manjelie vska ia, J., Brown, D., McGlynn, K. A., Anderson, W., Shriver, C. D., & Zhu, K.
(2017). Chemotherapy use and surviva l among young and middle -aged patients with
colon cancer. JAMA surgery , 152 (5), 452 -459. doi:10.1001/ja masurg.2016.5050
Munro, M. J., Wickremesekera, S. K., Peng, L., Tan, S. T., & Itinteang, T. (2018). Cancer ste m
cells in colorectal cance r: a review. Journal of clinical pathology , 71 (2), 110 -116.
http://dx.doi.org/10.1136/jclinpath -201 7 -204 73 9
Nasef, N. A., & Mehta, S. (2020). Role of infla mmatio n in pathophysio lo gy of colonic disea se :
An update. International journal of molecular sciences , 21 (13), 4748.
https://doi.org/10.3390/ijms2 11 347 48
Pan, M., Jiang, C., Tse, P., Achacoso, N., Alexeeff, S., Solorzano, A. V., . .. & Habel, L. A.
(2022). TP53 Gain -of-Func tio n and Non –Gain -of-Functio n Mutations Are
Differe ntia lly Associated With Sidedness -Dependent Prognosis in Metasta tic
5 COLON ADENOCARCINOMA
Colorectal Cancer. Journal of Clinical Oncology , 40 (2), 171 -179.
DOI: 10.1200/JCO.21.0201 4
Riihimäk i, M., Hemmink i, A., Sundquist, J., & Hemmink i, K. (2016). Patterns of metastasis in
colon and rectal cancer. Scientific reports , 6, 29765. https://do i.org/10.1038/srep2 9 7 6 5
Sawicki, T., Ruszkowska, M., Daniele wic z, A., Niedźwiedzk a, E., Arłukowic z, T., &
Przybyłowic z, K. E. (2021). A review of colorectal cancer in terms of epidemio lo g y,
risk factors, development, symptoms and diagnosis. Cancers , 13 (9), 2025.
https://doi.org/10.3390/ca nce r s1 309 20 25

Real Estate Prices Constantly On The Rise- BE937

Real Estate Prices Constantly On The Rise- BE937

Running head: ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE
WORLD?
Are real estate prices constantly on the r …

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Running head: ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE
WORLD?
Are real estate prices constantly on the rise in the world?
By Name of the Studen t
Tutor Name
1
ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE WORLD?
Table of Conte nts
Introd uc tio n ………………………….. ………………………….. ………………………….. ………………………….. 2
Litera ture Re vie w ………………………….. ………………………….. ………………………….. ………………….. 4
Inc rease in prope rty price in Ma la ysia ………………………….. ………………………….. ………………….. 4
Inc rease in prope rty price in C hina ………………………….. ………………………….. ………………………. 5
Inc rease in prope rty price in Japa n ………………………….. ………………………….. ………………………. 7
Re fe re nces ………………………….. ………………………….. ………………………….. ………………………….. .. 9
2
ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE WORLD?
Introductio n
The rising property price in Malaysia is evident in form of surge in the house price and
monitoring the relevant developments. The proportion of the annual price growth is evident in
form increase by 48.2% (Trofimo v and Xuan 2018 ). In this regard, it is im portant to note ho w
the property price has increased from 16.1% in the fourth quarter of 2020 to 48.2% in the third
quarter of 48.2 (Razali et al. 2018 ). The rationale for rise in the property price in Malaysia is
mainly evident because of rise in the constructio n materials by 20% which led to a furthe r
increase in the house price by 10% (Rachmawati et al. 2019 ; Yap and Ng 2018 ). On a Simila r
note, the Ave rage home prices in China is seen to increase by 0.1% since January 2021 in more
than 70 major cities. Along with this, the product market increased as a result of considera tio n
of heavily -indebted players in market such as China Evergrande Group . Moreover , the avera ge
prices of new housing in four largest cities namely Shenzhe n , Guangzho u and Shanghai also
increased by 0.6% in January 2021 (Chari et al. 2021 ). In addition to this, on an average the
home prices in China are seen to further increase by 1.5% on a year on year from March 2022.
The minima l rise in the property price can be seen to be evident in form of increase in the
property prices amidst COVID -19 pandemic (Zhang Qiao and Yeh 2022 ).
On a similar note, the increase in the property price in Ja pan can be also identified with
an increase of 6.9% during the Q3 2021. This is further seen to be evident with yoy increase of
2.4% in 2017, 2.1% in 2018, 0.5% in 2019 and 3% in 2020 (Law 2021 ). The factors drivin g
the property prices in Japan can be further identified in form of 3.4% yoy as on Feb 2021. This
is referred with a 3.8% increase in comparison to the previous month. Similarly , the yoy growth
can be identified with a growth rate of 1.3% . Moreover, as on 2021, the land prices increase d
on an average by 0.6% in 2021 from 0.5% in 2020 (Suzuki et al. 2022 ).
The purpose of this research is to investigate the rise in the real estate price on a consta nt
basis. In this regard, some of the main excerpts of the research relates to answering the rele va nt
question of increase in the overall price in the property from 2019 -2022 in China, Japan and
3
ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE WORLD?
Malaysia. It is worth noting that the research has considered increase in the property price s
particularl y in the rising world. The main aim of the study aims to answer the relevant questio n
of the rationale for such an increase in the property price. The motive of conducting the stud y
can be directly identified with knowing the factors which affected the pro perty prices in the
selected countries. Therefore , the main rationale of conducting the study is seen with
identifying the different types of the macro -economic factors which has influe nced the price s
of the property as the country tried to recover from th e COVID hit situatio n.
Re se arch Scope
The direct scope of the research can be seen in form of knowing about the changes in
real estate prices in Malaysia, Japan and China. In this aspect, the research scope has dire c tly
identified several macro -economic f actors impacting the property prices in the aforementio ne d
countries. The scope of the research has also considered various external and unforeseen facto rs
such as COVID – 19 pandemic.
Re se arch Obje ctive
ï‚· To know about the macro -economic factors impacting the rise in real estate prices in
Malaysia
ï‚· To know about the macro -economic factors impacting the rise in real estate prices in
China
ï‚· To know about the macro -economic factors impacting the rise in real estate prices in
Japan
Re se arch Que stion
ï‚· What are the main macro -economic factors impacting the rise in real estate prices in
Malaysia?
4
ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE WORLD?
ï‚· What are the main macroeconomic factors impacting the rise in real estate prices in
China?
ï‚· What are the main macroeconomic factors impacting the rise in real estate prices in
Japan?
Lite rature Re vie w
Incre ase in prope rty price in M alaysia
As per the review existing literature, we are able to identify how there has been a
constant increase in the prices of the property in Malaysia due to the attributes such as
population demand and supply, housing price as per the location, neighbourhood, physic a l
characteris tic s, accessibility, developer, cost of materia l and land and income. In this manne r,
we are directly able to identify how the re has been several changes in the prices. Based on the
literature of populatio n demand and supply, the increase in the income and populatio n ma y
significa ntly influe nce the housing demand (Aris 2018; Pinjama n and Kogid 2020) . The
relevant changes in the quantity in the housing demand has been further considered with
significa nt changes associated with income growth, household format io n rate and popula tio n
growth. Therefore, the overall trend in the housing price is depicted with an increasing trend .
Furthermore, the pertinent changes in the housing demand may also impact the housing sup p ly
which further affect the prices of the houses. As a result of the investiga te d population increa s e
from 1.66m from 2013f to of 1.75 millio n in 2020f, the price of the household is also depicte d
to rise to a considerable level (Dwaikat and Ali 2018 ).
The housi ng price based on location is seen to change with availab ility of the
development projects and location of the projects in form of the accessibility of the facilit ie s
such as schools, healthcare, child care facilitie s and other social facilities . Based on the loca tio n
facilities, the annual percentage growth in the household is investiga te d to grow significa n t ly .
5
ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE WORLD?
As per the neighbo urhood factor, the housing price in Malaysia is seen to depend on rele va nt
form of the factors such as environme nt and neighbourhood characteristics (Hanafi et al. 2018) .
Moreover, as a result of the depiction of the house being in good neighbo urhood, the
environme nt quality characteristic s along with availab ility of green space area has been seen
to have a considerable impact the prices of the property in Malaysia. Similarly, the physic a l
characteristic s may also influe nce the price of the houses as a result of presence of any specia l
design (Kiong and Aralas 2019 ). The common form of structural attribute pertaining to the
property is seen with size of the living areas and built -up areas. The accessibility of such as
easing the reach of the services, destinatio ns and ease of reaching goods may further affect the
prope rty prices in Malaysia in considerable manner. In addition to this, the experts of the
relevant literature have further revealed that one of the main reasons of surging property price s
in Malaysia is also due to Government cutting down on the premiums of t he construc tio n
developers through which the constructio n cost is able to be reduced to a great extent. Howeve r,
the developer needs to in turn pay higher premiums on the constructio n which is the n
transferred to the buyers of the house (Trofimo v and CD Xu an 2018 ).
The cost of the materia l and land is responsible for driving the property price to an
extent of 3 – 5% . Furthermore, the transportation also increases the prices of the property in
Malaysia by 10 -20%. The formulatio n of the relevant relationship between the income and
house price has increased the prices of the property to a tune of CAGR 8.1% (Razali et al.
2018 ). As per the role of the Government, the fulfilme nt of the housing is seen as a majo r
objective pertaining to the nationa l development. This has been focused as the main action as
a result of the increasing housing pric es (Rachmawati et al . 2019 ).
Incre ase in prope rty price in China
The present literature has focused on accommodating monetary policy during the
financ ia l crisis associated with the risks related to the property bubble associated with infla t in g
6
ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE WORLD?
the price of the property. As a result of the ea rly evidence of the literature we are further able
to identify that the dramatic increase in the housing prices in China came up with severa l
questions on housing bubble of China especially related to affordability price -to-rent and price –
to-income ratio (Orlik 2020) . Moreover, the signific a nt rise in the consumptio n patter n is also
responsible for increasing the prices of the property (Wen et al. 2018 ). It is also worth no ting
how interna l the impact of overall property prices is seen to be largely dependent on financ ia l
system of differe nt share of well pertaining to the households. In this aspect, the property pric e
index of China significa ntly increased in nomina l terms. Therefore, the result of deflated CPI
infla tio n and prices of real estate, th e consumptio n significa ntly increased as on 2020 (Gua n
and Peiser 2018) .
As a result of such an increase in the consumptio n, the property price in both Beijin g
and Shangha i followed an increasing trend. Some of the existing literature review referring to
the past trend of increasing property price in China and related with interesting case of
Hangzho u which is the capital of Zhejiang Province (Versal, Balytska and Erastov 2021) . It is
worth noting how in 2015 in Hangzho u the property prices increased as a result of housin g
reform in 1998 . Moreover, the existing literature suggests how in China direct impact of
increasing property prices can be also seen in form of constructio n of rail transit. In this regard ,
the rail transit is conducive for facilita ting s uperior means of alternative transportatio n, there b y
reducing the overall traffic pressure. However, as a result of increased accessibility the nearb y
property prices significa ntly inflate s. Traditio na lly, prior studies have used property marke t
data to bu ild hedonistic price models for empirica l study. In theory, a property may be
considered of as a heterogeneous good, with its price determined by a number of distinc t
characteristic s such as location, neighbo urhood, and structure. As a key extrinsic amenit y,
metropolita n rail transit plays an important role in property buyers’ decision -mak ing process
(Wen et al. 2018 ; Quinn and Turner 2021) .
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ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE WORLD?
The advantages of transport facilities and services are, of course, reflected in ho me
prices. Benjamin and Sirmans investigated railway in Washingto n, D.C., and discovered tha t
every 0.1 mile nearer to the nearest station increased the rental value of an apartment by 2.5
percent. As per Hess and Almeida, each foot of length decreased leads in a $2.31 rise in ho me
valu e. Typically, ease of access is measured by the straight -line range between the estate and
the rail transit station. These investiga tio ns directly applied the distance variable into
investigate d models to produce price elasticity, quasi, or margina l price for traffic access, and
then analysed the rail transit’s average capitalizatio n impact. In most circumsta nces, this
method will suffice to meet the requirements of the research (Li, Wang and Liu 2022 ).
Incre ase in prope rty price in Japan
As per the existi ng literature, we are able to discern how the asset bubbles have forme d
a unique combinatio n of psychologic a l factors for differe nt economic and cultura l
developments. In this aspect, it is worth noting how for a long time, there have been no large
financ i a l firm bankruptcy in Japan, and such instances of property price increase were kept
low. However, it is worth noting how in 2009 itself, the country experienced a sudden rise in
the prices of the property as a result of GFC impact (Versal, Balytska and Er astov 2021; Wo lf
and Takeuchi 2022) . Due to such an effect, the average price of its regions but into the house s
situated in Xihu District was seen to undergo a considerable rise in experienc ing highe st
average of property prices. moreover, the investiga ti o n of further increase in property prices in
Japan can be further identified with the funding considered as are the safe haven for individ ua ls
with higher average consumer spending. Due to such phenomena, the overall property price s
are always considered t o be on the higher side (Charoenwong, Morck and Wiwattanakan ta n g
2019 ). Moreover, the market attractiveness is ensured by following stable economic and
politica l fundame nta ls. However, in the recent times these factors have been seen to be
disrupted as a result of social disruptio n and COVID -19 pandemic around the globe. The
8
ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE WORLD?
governme nt of Japan was expected to continue to expand with real GDP reaching up to 3.2%.
Despite such predictions, the Galway and along with the shortage of conductors, the dema nd
in in the residentia l property sale increase d both in Osaka and Tokyo (Run gsk unroc h, Ya ng
and Kaewunruen 2020 ).
The relevant literature has investigated how in Tokyo the selling of total number of
existing condominiums substantia lly increased by 10.8% to 37,113 units in the first few months
of 2021 . On a similar note, in Osaka the selling of the existing condominiums substantia l ly
increased by 6% y -o-y to 15,822 units in Jan -Nov 2021 (Globalpropertyguid e.co m 2022 ). A
similar trend and was identified with increase in the land sales despite of rise in the property
price. This was mainly evident as a result of increased demand (Shima moto 2019 ). In additio n
to this, it is worth noting how the authorised starting price of housing properties reached up to
788,091 units during the first 11 months of 2021 which is again seen as an incre ase of 5.1% in
comparison to the previous year. However, despite of these reasons, historic increase in the
Omicron variant is seen as the main reason behind increasing property prices in Japan in the
recent times (Ltd. 2022 ). As a result of review of the existing literature, we are able to identify
a direct correlatio n in the increase in the property prices of Japan, China and Malaysia .
Moreover, the increase in the property price as a result of asset bubble is also a direct co rrela tio n
between Japan and China (Su et al. 2018) .
9
ARE REAL ESTATE PRICES CONSTANTLY ON THE RISE IN THE WORLD?
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Assessment Answers of Gender Pay Gap in Australia: ECON1030

Assessment Answers of Gender Pay Gap in Australia: ECON1030

RMIT Classification: Trusted
Exploring the gender pay gap in Australia
Executive Summary
The main aim of the present study was to investigate the g …

Preview text

RMIT Classification: Trusted
Exploring the gender pay gap in Australia
Executive Summary
The main aim of the present study was to investigate the gender pay gap in Australia between
male and female full time workers. Data revealed that full time male Australian workers
earned more than the full time female workers on a weekly basis. It was found that male
workers with similar educational qualification as female received earned more. Also, male
workers with similar level of skills as female earned more. This gave reason to believe that
male workers were earning more than female irrespective of the level of educational
qualification or the skills. Data also revealed that male workers had higher years of
experience as compared to females. There was asignificant difference in weekly earning by
male and female full time workers in Australia with male workers earning more than female
workers.
Introduction
Gender pay gap refers to the difference in earning by male and female workers
working under the exact same circumstances. Women are usually observed to be underpaid
compared to men (Bishu and Alkadry 2017) .This becomes amatter of concern as itis unfair
when on particular group of employees are paid less than another group even though they are
equal in terms of skills, productivity and commitment to the organization. One specific
reason for the prevalence of gender pay gap in organizations is fewer women representatives
in higher management in any organization (Chamberlain 2016) .Another explanation is that
women select to care for their children and families, so they naturally wind up in part-time
occupations with lower pay and less possibilities for advancement (Miller and Vagins 2018) .
Companies that want to improve gender diversity throughout their business should evaluate
gender bias, such as gender pay gaps, that may be rooted in their culture. Corporations can
make use of various of actions to effectively decrease the gender wage gap in their workplace.
Gender pay gap is one of the major economic issues in Australia. The existence of
gender pay gap impedes the growth of the economy. Prevalence of gender pay gap
demotivates employees and also hampers the performance of female employees. The present
study puts emphasis on the gender pay gap in Australian full time male and female workers.
A data of 1099 full time Australian workers (Male =672, Female =427) was obtained from
the survey of Household, Income and Labour Dynamics in Australia(HILDA), 2019. The
study aimed to make data driven decisions and conclusions about the gender pay gap in
Australia. The analysis included descriptive as well as inferential statistical approach. The
analysis of the data have been discussed in the following section in thorough details. The
findings from this study can help employers understand the gender pay gap in clear and
concise way through data driven information and help them take actions necessary to cope
with the problem and come up with solutions to the problem
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RMIT Classification: Trusted
Analysis
1. Summary statistical findings for male weekly earning
Table 1shows the descriptive statistical findings for male Australian workers in the
sample. Summary statistics mainly included measures of center and measures of spread.
Measures of center include mean, median and mode and measures of spread included sample
variance, standard deviation, range.
Table 1:Descriptive summary for male weekly earnings
Male earnings
Mean 1787.29
Standard Error 44.18
Median 1500
Mode 1000
Standard Deviation 1145.20
Sample Variance 1311472.36
1stQuartile 1049
3rdQuartile 2100
Range 10301
Minimum 276
Maximum 10577
Sum 1201059
Count 672
2. Summary statistical findings for female weekly earning
Table 2shows the descriptive statistical findings for male Australian workers in the
sample.
Table 2:Descriptive summary for male weekly earnings
Female earnings
Mean 1439.96
Standard Error 34.79
Median 1250
Mode 1000
Standard Deviation 718.98
Sample Variance 516935.18
1stQuartile 959
3rdQuartile 1750
Range 6049
Minimum 51
Maximum 6100
Sum 614864
Count 427
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RMIT Classification: Trusted
3. Discussion based on the summary statistical findings
Data revealed that on an average amale worker in Australia earned AU$ 1787.29 in a
week. Average is the sum of observations in the sample divided by the total number of male
workers (Kaliyadan and Kulkarni 2019) .The median weekly earning by the male workers in
Australia was found to be AU$ 1500. Median is that observation in adata which occurs in the
middle when the data has been arranged in either increasing or decreasing order (Conner and
Johnson 2017) .It was indicated that half of the male workers in the sample earned equal to or
higher than AU$ 1500 per week and the other half earned equal to or less than AU$ 1500 per
week. The modal weekly earning by the male Australian worker was AU$ 1000. Mode is that
observation in adata which has highest number of occurrences in the data (Holcomb 2016) .
In other words, majority of the male workers in the sample earned AU$ 1000 on aweekly
basis. The sample variance of male weekly earnings was 1311472.36 .The standard deviation
was AU$ 1145.2. The standard deviation is actually the squared root of the sample variance
(George and Mallery 2018) .Standard deviation shows how much the weekly earning by the
male workers were deviated from the mean weekly earning. The standard deviation was quite
high indicating alarge deviation in the sample observations about the mean weekly earning
by male workers (Sarka 2021) .According to the data, the maximum weekly earning by male
worker in Australia was AU$ 10577. The minimum weekly earning by the workers in the
sample was AU$ 276. The range of weekly earning by the male workers in the sample was
AU$ 10301. In simple terms range is the difference between the maximum and minimum
observation in adata (Kaur, Stoltzfus and Yellapu 2018) .The first quartile for weekly wage
earned by male workers in the sample was AU$ 1049. This indicated that one quarter of the
male workers in the sample earned less than AU$ 1049. The third quartile for male weekly
earnings was AU$ 2100. This indicated that one quarter of the male workers in the sample
earned more than AU$ 2100 every week.
From the data itwas found that on an average afemale worker in Australia earned
AU$ 1439.96 in aweek which was less than what male workers in the sample earned on an
average on aweekly basis. The median weekly earning by the female workers in Australia
was found to be AU$ 1500. It was indicated that half of the female workers in the sample
earned equivalent to or higher than AU$ 1250 per week and the other half earned equivalent
to or less than AU$ 1250 per week. The modal weekly earning by the female Australian
worker was AU$ 1000. In other words, majority of the female workers in the sample earned
AU$ 1000 on aper week. The sample variance of female weekly earnings was 516935.18 .
The standard deviation was AU$ 718.98. The standard deviation was quite high indicating a
large deviation in the sample observations about the mean weekly earning by female workers.
The standard deviation of female weekly income about the mean was less than that of the
male weekly incomes about its mean indicating less deviation in the sample observations of
female weekly earning about the mean as compared to the male weekly earnings. According
to the data, the maximum weekly earning by female worker in Australia was AU$ 6100. The
minimum weekly earning by the workers in the sample was AU$ 51. The range of weekly
earning by the female workers in the sample was AU$ 6049. The range of weekly earning by
male workers in the sample was more than that of the female workers. The first quartile for
weekly wage earned by female workers in the sample was AU$ 959. This indicated that one
quarter of the female workers in the sample earned less than AU$ 959. The third quartile for
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RMIT Classification: Trusted
female weekly earnings was AU$ 1750. This indicated that one quarter of the female workers
in the sample earned more than AU$ 1750 every week.
4. Distributions of earnings by male and female workers in Australia
To get aclear picture of how the distribution of weekly earnings by male and female
workers in Australia looked like two separate histograms were produced each showing the
distribution for male and female weekly earnings respectively.
Figure 1:Histogram showing the distribution of weekly earnings by male workers
From figure 1itwas noted that the distribution of weekly earning by Australian male
workers was unimodal. Majority of the Australian male workers earned between AU$ 1012
and AU$ 1748. The distribution was skewed towards the right. Right skewness of the
distribution indicated that the majority of the male workers had lower weekly income as
compared to those with very high weekly earnings. There were very few workers with
exceptionally high incomes (weekly earnings above AU$ 9105) among the sample of male
workers.
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RMIT Classification: Trusted
Figure 2:Histogram showing the distribution of weekly earnings by male workers
From figure 2itwas observed that the distribution of weekly earning by Australian
female workers was unimodal. Majority of the Australian female workers earned between
AU$ 915 and AU$ 1347. The distribution was skewed towards the right. Right skewness of
the distribution indicated that the majority of the female workers had lower weekly income as
compared to those with very high weekly earnings. There were very few workers with
exceptionally high incomes (weekly earnings above AU$ 5668) among the sample of female
workers.
By comparing the two distributions itwas observed that what majority of the male
workers in Australia earned was much more than what the female workers earned on weekly
basis. The minimum income of male workers started from AU$ 276 while the minimum
income of female workers started from AU$ 51.
5. Differences in labour market characteristics
Table 3:Male and female numbers based on educational qualification
Educational Attainment Male Female
Bachelor’s degree or higher 209 197
Lower than degree qualification 463 230
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RMIT Classification: Trusted
Figure 3:Pie chart showing the percentage distribution for male workers according to
the educational qualification
Figure 4:Pie chart showing the percentage distribution for male workers according to
the educational qualification
Data revealed that about 31 % of the Australian male workers in the sample had a
bachelor ’sdegree or higher educational qualification. In the case of female workers, itwas
observed that 46 % of them had adegree equivalent of Bachelor ’sdegree or higher. The
percentage of female workers with higher educational qualifications was higher than that of
the male workers in Australia. About 69 % of the male workers in the sample had educational
qualification lower than degree level while in the case of female workers 54 % had lower
than degree level qualification.
Table 4:Male and female numbers based on skills
Skills Male Female
Highly Skilled 256 148
Not highly skilled 416 279
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RMIT Classification: Trusted
Figure 5:Pie chart showing the percentage distribution for male workers according to
the level of skills
Figure 6:Pie chart showing the percentage distribution for female workers according to
the level of skills
38 % of the male workers were highly skilled and on the other hand 35 % of the
female workers were observed to be highly skilled. About 62 % of the male workers and
65 % of the female workers in the sample were not highly skilled.
Thus, majority of both male and female workers were not highly skilled and not
qualified above degree level.
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RMIT Classification: Trusted
Figure 7:Bar chart showing the average years of experience by male and female
workers
From figure 7itwas observed that male workers had higher years of experience than
female full time workers. On an average male workers had 12.8 years of experience and
female workers had 10.56 years of experience.
6. Differences in weekly earnings between male and female with similar labour market
attributes
Table 5shows the summary statistics of weekly earnings by male and female
Australian workers with educational qualification equivalent to degree or higher.
Table 5:Summary statistics of weekly income by male and female with bachelor ’s
degree or higher educational qualification
Male Female
Mean 2301.35 1761.90
Standard Error 97.54 56.85
Median 1918 1666
Mode 1000 1750
Standard Deviation 1410.17 797.88
Sample Variance 1988580.56 636614.24
Kurtosis 9.23 8.70
Skewness 2.42 2.37
Range 10301 5500
Minimum 276 600
Maximum 10577 6100
Sum 480982 347095
Count 209 197
On an average, male workers with degree or higher level of education earned
AU$ 2301.35 (SD =1410.17) per week. On the other hand, women workers with same
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RMIT Classification: Trusted
educational qualification in Australia earned AU$ 1761.90 (SD =797.88) which was less
than what their male counterparts earned every week. The median weekly earning by male
workers with degree or higher level of educational qualification was AU$ 1918. On the other
hand, the median of weekly earning by female Australian workers was AU$ 1666. Majority
of the male workers with degree or higher level of educational qualification earned AU$ 1000
per week. Majority of female workers on the other had with similar educational qualifications
earned AU$ 1750.
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RMIT Classification: Trusted
Table 6:Summary statistics of weekly income by male and female with less than degree
level qualification
Male Female
Mean 1555.24 1164.21
Standard Error 42.49 33.05
Median 1343 1050
Mode 1000 1000
Standard Deviation 914.31 501.23
Sample Variance 835958.11 251227.25
Kurtosis 21.96 8.81
Skewness 3.53 2.23
Range 9833 4025
Minimum 350 51
Maximum 10183 4076
Sum 720077 267769
Count 463 230
On an average, male workers with educational qualification lower than degree level
earned AU$ 1555.24 (SD =914.31) per week. On the other hand, women workers with same
educational qualification in Australia earned AU$ 1164.21 (SD =501.23 )which was less than
what their male counterparts earned every week. The median weekly earning by male
workers with lower than degree level educational qualification was AU$ 1343. On the other
hand, the median of weekly earning by female Australian workers was AU$ 1050 .Majority of
the male workers with lower than degree level of educational qualification earned AU$ 1000
per week. Majority of female workers on the other with similar educational qualifications
earned was also AU$ 1000.
Table 7:Summary statistics of weekly income by highly skilled male and female
workers
Male Female
Mean 2177.86 1673.50
Standard Error 84.60 65.70
Median 1839.5 1476.5
Mode 1151 1000
Standard Deviation 1353.67 799.24
Sample Variance 1832421.67 638787.26
Kurtosis 9.23 1.97
Skewness 2.36 1.32
Range 10301 4373
Minimum 276 230
Maximum 10577 4603
Sum 557531 247678
Count 256 148
On an average, male workers with highly competent skill sets earned AU$ 2177.86
(SD =1353.67 )per week. On the other hand, women workers with similar skill sets in
10
RMIT Classification: Trusted
Australia earned AU$ 1673.50 (SD =799.24 )which was less than what their male
counterparts earned every week. The median weekly earning by highly skilled male
Australian workers was AU$ 1839.5. On the other hand, the median of weekly earning by
female Australian workers with no high skills was AU$ 1476.5. Majority of the male workers
with no high skills earned AU$ 1151 per week. Majority of female workers on the other with
similar level of skills earned AU$ 1000 per week.
Table 8:Summary statistics of weekly income by not highly highly skilled male and
female workers
Male Female
Mean 1546.94 1316.08
Standard Error 45.00 38.33
Median 1343 1150
Mode 1000 1150
Standard Deviation 917.89 640.25
Sample Variance 842527.11 409924.17
Kurtosis 25.82 21.26
Skewness 3.91 3.45
Range 9709 6049
Minimum 474 51
Maximum 10183 6100
Sum 643528 367186
Count 416 279
On an average, male workers with no high level skill sets earned AU$ 1546.94 (SD =
917.89 )per week. On the other hand, women workers with similar skill sets in Australia
earned AU$ 1316.08 (SD =640.25 )which was less than what their male counterparts earned
every week. The median weekly earning by not highly skilled male Australian workers was
AU$ 1343. On the other hand, the median of weekly earning by female Australian workers
with no high skills was AU$ 1150. Majority of the male workers with no high skills earned
AU$ 1000 per week. Majority of female workers on the other with similar level of skills
earned AU$ 1150.
The summary statistics indicate that irrespective of educational qualification or level
of skills male workers in Australia earned more than what female workers in Australia earned
on aweekly basis.
7. Confidence interval for male and female weekly earnings (Step by step computation)
By assuming that the male and female weekly earnings observed in the sample were
normally distributed the 95 % confidence interval for the male and female full time workers
in Australia were computed.
For male
Average point estimate for male weekly earnings (x̄)=AU$ 1787.89
Standard deviation (s) =AU$ 1145.20
Number of observations (n) =672
11
RMIT Classification: Trusted
Degrees of freedom (df) =671
t(α/2,df) =t(0.025, 671) =1.9635
Margin of error (M.E) =t(0.025, 671) ×(s /√n) =1.9635 ×(1145.2 /√672) =86.74
95 % upper confidence =x̄+M.E =1787.89 +86.74 =1874.03.
95 % lower confidence =x̄-M.E =1787.89 -86.74 =1700.55.
One can be 95 % confident that the weekly earning by the true population of male
workers of Australia lies between AU$ 1700.55 and AU$ 1874.03.
For female
Average point estimate for male weekly earnings (x̄)=AU$ 1439.96
Standard deviation (s) =AU$ 718.98
Number of observations (n) =427
Degrees of freedom (df) =426
t(α/2,df) =t(0.025, 426) =1.9655
Margin of error (M.E) =t(0.025, 426) ×(s /√n) =1.9655 ×(718.98 /√427) =68.39
95 % upper confidence =x̄+M.E =1439.96 +68.39 =1508.35.
95 % lower confidence =x̄-M.E =1439.96 -68.39 =1371.57.
One can be 95 % confident that the weekly earning by the true population of female
workers of Australia lies between AU$ 1508.35 and AU$ 1371.57.
8. Gender pay gap in 2007 and 2019
According to the government the gender pay gap between male and female workers in
Australia in the year 2007 was AU$ 400. The current data from 2019 revealed that the true
highest possible difference between earning by male and female worker in Australia with
95 % confidence can be AU$ 365.68 and the true lowest possible difference between earning
by male and female worker in Australia with 95 % confidence can be AU$ 328.97. Thus,
compared the gender gap in weekly earning by male and female work force of Australia in
2007, the gap in 2019 was reduced.
9. Hypothesis testing regarding population mean of female full time workers in
Australia
According to aclaim by media report full time female workers in Australia earned
AU$ 1500 in the year 2019. To verify the claim ahypothesis test was performed using aone
–sample t–test (Gerald 2018) .
12
RMIT Classification: Trusted
Figure 8:Bar chart showing the sample weekly earnings and hypothesized weekly
earning of female workers
From the figure itcan be observed that the hypothesized mean weekly earning by full
time female workers of Australia was higher than the sample mean.
The null and alternate hypothesis are as follows –
H0:The true population mean weekly earning by full time Australian female workers was not
different from AU$ 1500
H1:The true population mean weekly earning by full time Australian female workers was
significantly different from AU$ 1500
Level of significance (α)=0.05
Degrees of freedom =426
Decision rule: The null hypothesis shall be rejected if the computed t–statistic is greater than
+1.97 or less than –1.97.
Sample mean (x̄)=AU$ 1439.46
Hypothesized population mean (µ)=AU$ 1500
Sample standard deviation (s) =AU$ 718.98
t–statistic =(x̄-µ)/(s /√n) =(1439.46 –1500) /(718.98/ √427) =-1.73
p–value =0.085 (From the standard normal table)
The computed t–statistic was neither less than –1.97 nor greater than +1.97. The p–
value associated with the test statistic was less greater than the level of significance 0.05.
Thus, according to the decision rule we do not have sufficient evidence to reject the null
hypothesis.
Hence, the claim that the true average weekly earnings by full time female workers in
Australia was AU$ 1500 was true.
13
RMIT Classification: Trusted
A probable error in this case might be failing to reject the null hypothesis even though
itmight be not actually true. This is atype II error in hypothesis tests.
10. Confirming the significance in difference in weekly earnings between male and
female workers
An independent sample t-test was performed to confirm whether the difference in
mean weekly earning between male and female population was statistically significant. For
this itwas assumed that the observed weekly earnings by both groups were normally
distributed. Also, the variance in earnings by male and female are not different.
Table 9:T-test two-sample
Male earnings Female Earning
Mean 1787.29 1439.96
Variance 1311472.36 516935.18
Observations 672 427
Pooled Variance 1002928.29
Hypothesized Mean Difference 0
df 1097
tStat 5.60
P(T

Project Work Answers- Effect is the Over Valuation :FNCE2390

Project Work Answers- Effect is the Over Valuation :FNCE2390

1
Student’s Name:
Admission Number:
Lecture
Course:
2
Part A
Ariely was the only one in the study to rid himself of hepatitis C because he w …

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1
Student’s Name:
Admission Number:
Lecture
Course:
2
Part A
Ariely was the only one in the study to rid himself of hepatitis C because he was the
only one in the procedure which used to take the interferon as per the doctor’s prescription.
The other individuals in the study had skipped the medication many times due to the
unfriendliness involved when taking the medication. He could get through the unpleasantness
because he had away of making the approach more bearable by watching movies.
Low to moderate performance-based bonuses can help (Saleem et al., 2021). This is
because when the level of the bonus is very high, itis likely to take over too much
consciousness and thereby dumbfound the worker’s mind with thoughts about the bonus. This
can cause stress and, after that, decrease the worker’s grade of productivity.
According to Ariely, big bonuses hurt worker productivity because over-motivation
can cause the workers to perform worse with the interest of outdoing themselves by over-
stressing themselves. Paying large bonuses to the workers is unlikely to improve their
creativity, which will lower their productivity. This is because financial incentives don’t
operate simply on the capacity of the result from our thinking.
We perform when in private than in public because, in the private sector, we receive
more opportunities for the advancement of the job since the decision is based on our
performance (Stulz, 2020). On the other hand, in the public sector, we tend to enjoy more
work stability because itis not amust for our organizations to meet the pressures in the
market.
The IKEA effect is the over-valuation resulting from labor. More effort results in
greater valuation and appreciation. It holds because the struggle we offer into substance does
not just change the item. Instead, itchanges us and the way we evaluate that object. In
addition, our over-valuation of what we make goes so deep that we make assumptions that
other people share our biased perspectives. It is also stated that when we cannot finish
3
something into which we have offered huge effort, we don’t feel very much adhered to it.
Lastly, more significant labor leads to great love.
Not- invented here, bias is the attraction to one’s ideas. It goes with the principle that
“if I(or we) didn’t invent it, itis not worth much.” It holds because, nonetheless, of what we
make, be itanew mathematical theorem, atoy box, or anew source of electricity, much of
the most important to us is what we have created. Provided we create it, we have atendency
to feel that itis more important and valuable than similar ideas from other individuals. Like
many other aspects of our curious and exciting nature, we should recall that our
predisposition to put more value on what we create is amixed bag of evil or good.
Idiosyncratic fit is when the consumers believe that they have arelative advantage for
an option that is often, though not always (Huffman, 2018).
The power of saying sorry is that itcompletely counteracts the effect of annoyance. It
is stated that apologies often work, even if itis temporary. Before you agree it’s alright for
you to begin acting like afool and saying sorry instantly after you irritate somebody, aword
of attention is essential (Nair, 2020). For instance, since they expected the people who were
annoyed to be less possibly to give back the extra cash, which was the case as per the results,
the amount of cash brought back in the condition of apology was similar to when people were
not annoyed at all.
The downside of adaptation is that we forget to consider that life continues when we
are predicting. Other negative and positive activities will influence our sense of well-being in
days. We expect to remain distressed for many years if things do not go as we hope (Issahaku
et al., 2021). But our grief and unhappiness do not understand how we are flexible
extraordinarily. For instance, you might hope that taking abreak from aboring or irritating
experience will be best for you, but having abreak will decrease your adaptation ability,
making the experience worse whenever you go back.
4
The upside of adaptation is slowing down pleasure. For instance, acouch that is new
may please an individual for several days, but don’t purchase your television until after the
thrill of the couch has worn out. But if you are struggling with economic cutbacks
(Rosengren, 2021). When decreasing consumption, you should move to asmaller apartment,
cut back on expensive coffee and give up cable television. In this case, the pain at the start
will be more significant, and the total quantity of distress will be lower with time.
Part B
Why we don’t learn from our mistakes better
We did earlier for the assumption of individuals not learning from their mistakes
while repeating the mistakes. Lack of self-control and procrastination is the first reason we
keep repeating the same mistakes. When we lack self-control, we are likely to lose focus
when making investment decisions such as spending rather than saving or changing our
portfolios more frequently (Edmondson, 2018). Complete flexibility cannot make you avoid
the mistakes, but rather when you can have your deadline, itwill help. Being at ease is
essential, as demonstrated by Ariely, as itcan help avoid the previous mistakes made.
Precommitments can also be helpful. Individuals usually value the short-term much more
than the long-term and find itdifficult to make tough decisions.
The other reason we don’t learn from our mistakes better is relativity, where
individuals rarely choose things in absolute terms. People are always interested in the things
around them compared to others. Further, the endowment effect is another reason we fail to
learn better from our mistakes. Individuals tend to value what they have and undervalue what
they don’t have. When investing, the endowment effect may cause an individual to continue
using assets that have no sense for their portfolio and assume new investment opportunities.
Why we are so resistant to testing our ways of doing things
5
One reason is that we have many irrational tendencies. Petriglieri et al., (2019)
reported that people always tend to keep things how they are. The change is painful and
challenging. Therefore, we would not change something if we could assist it. Individuals
prefer not to take any action and live with their condition, however harmful itis. Making
regular choices is hard enough.
On the other hand, making decisions that are not reversible is more complicated. For
instance, we think hard and long about choosing acareer or purchasing ahouse because we
do not have enough information about the future. Therefore, making huge, essential, life-
changing decisions is challenging because we all tend to be susceptible to various decision
biases.
The reason is that we are mostly not aware of how irrationalities affect us. This shows
that we lack acomplete understanding of things that drive our behavior. This gives
companies, policymakers, and individuals the reason to doubt their feelings. Suppose we
keep going with our common wisdom and gut or doing what is most habitual or easiest
simply because things are supposed to be done in that same way. In that case, we are likely to
continue making mistakes that lead to alot of effort, time, money, and heartbreak going down
the same initial ways.
Why do we need so much meaning at work?
Even less meaning can make us go along way (Brock & Hansen, 2018).
Organizations should impart asense of meaning to their workers if they want to produce.
This should be through allowing workers to have asensibility of fulfillment and
acknowledging ajob well done, not just through the vision statements. At the end of itall,
such factors can significantly influence productivity and satisfaction.
Why are the economic models so wrong?
6
The economic models of labor are so wrong because they generally treat working
women and men as if they are rats in amaze. They assume the work to be annoying; thus, all
the individual wants is to get food using the little effort possible and rest for most of the time.
Why we are so seduced by numbers and put off by qualitative things in finance and
economics
In chapter two of irrationality, the simplest economic perspective is that individuals
will regularly choose to increase their bonus while decreasing their effort. Regarding this
economic perspective, spending anything such as intensity is said to be acost, and therefore it
doesn’t make sense that an individual would do that voluntarily. The results of building bionic
legs discovered that if you take people who love something and place them in ameaningful
working condition, the joy they get from the event will be the basic driver in dictating their
effort level. If you take the same people with similar initial desires and passion and place
them in working conditions that are meaningless, you will likely execute any internal joy they
can get from the event.
Why intelligent people are easily fooled
This is because intelligent people tend to overweight new events or information
without considering the objective probabilities of these events in the long run. This can make
them get fooled easily. Availability bias is essential for the financial business, as memories of
recent business events or news can make investors believe rationally that the same event is
more likely to happen again without looking at its objective probability. As aresult,
intelligent individuals can decide to buy into bubbles or sell into bear businesses.
Smart people also tend to overreact to the news of events recently (Skagerlund et al.,
2018). They will make decisions based on what has occurred without looking at its effects
shortly. The availability bias affects the marketing decisions that an individual is likely to
7
make based on the recent headlines or events while expecting such events to be more instant
than they are. In this case, they will end up easily fooled.
Why do we create models that people cannot follow?
This is because most economic models lie on several assumptions which are not
entirely realistic. For instance, agents are assumed to contain perfect data, while markets are
most of the time assumed to clear without resistance. We assume that people can do these
calculations because economists cannot isolate the individual variables in the real world; thus,
they design amodel with some constancy.
Why do we assume we are rational?
We assume that we are rational because consumers aim to maximize their wants and
needs or utility (Modgil & D’Agostino, 2020). Since maximizing utility is an element of
rationality, its main focus is on how individuals attain their objectives by making rational
decisions. We, therefore, assume that we are so rational.
Part C
The behavior in the default setting (system 1) will acknowledge the mind’s
unconscious default setting. Thinking this way tends to be so easy and automatic that itdoes
not have to be achoice. In this case, my default setting will be how Iwill jump the line and
get served fast since Iam so tired. This will be my behavior because itis the first thing that
will ring my mind. After all, Iwill be at the Centre, and everyone else will be in my way.
Thus, everything will be about me. Wallace thinks that instead of doing all these, we should
be empathetic with others by assuming that we are in front of others rather than them being
behind us (Pitari, 2018). By doing this, you are going to make yourself generally happy and
more connected to people. You can also try to make the situation so dull to be best now that
you are many in the line of the store and most probably people are tired of waiting.
8
Drollinger, (2018) reported that doing this will enable you to establish social
connections with other individuals. By understanding what individuals are feeling and
thinking, one can appropriately respond to social situations. Studies have demonstrated that
social connections are essential for psychological and physical well-being. It can also help an
individual to learn to control their own emotions. This can enable you to manage what you
are feeling. It can also enhance helping behaviors. You are not the only one who will help
others, but other individuals will help you whenever they come across empathy.
9
References
Blanchflower, D. G., & Bryson, A. (2021). The economics of walking about and predicting
unemployment (No. w29172). National Bureau of Economic Research.
Brock, W. A., & Hansen, L. P. (2018). Wrestling with uncertainty in climate economic
models. University of Chicago, Becker Friedman Institute for Economics Working
Paper ,(2019-71).
Drollinger, T. (2018). Using active empathetic listening to build relationships with major-gift
donors. Journal of Nonprofit & Public Sector Marketing ,30 (1), 37-51.
Edmondson, A. C. (2018). The fearless organization: Creating psychological safety in the
workplace for learning, innovation, and growth .John Wiley & Sons.
Gabaix, X., & Koijen, R. S. (2021). In search of the origins of financial fluctuations: The
inelastic markets hypothesis (No. w28967). National Bureau of Economic Research.
Huffman, M. (2018). A Look at Behavioral Antitrust from 2018. CPI Antitrust Chronicle
(Jan. 2019) .
Issahaku, G., Abdul-Rahaman, A., & Amikuzuno, J. (2021). Climate change adaptation
strategies, farm performance and poverty reduction among smallholder farming
households in Ghana. Climate and Development ,13 (8), 736-747.
Modgil, S., & D’Agostino, M. (2020). A fully rational account of structured argumentation
under resource bounds. In Proceedings of the Twenty-Ninth International Joint
Conference on Artificial Intelligence Main track. (pp. 1841-1847). International Joint
Conferences on Artificial Intelligence.
Nair, D. (2020). Emotional labor and the power of international bureaucrats. International
Studies Quarterly ,64 (3), 573-587.
10
Petriglieri, G., Ashford, S. J., & Wrzesniewski, A. (2019). Agony and ecstasy in the gig
economy: Cultivating holding environments for precarious and personalized work
identities. Administrative Science Quarterly ,64 (1), 124-170.
Pitari, P. (2018). Consciousness According to David Foster Wallace. Revue francaise detudes
americaines ,(4), 185-198.
Rosengren, L. (2021). 10 Capturing adaptation opportunities. The catalytic effects of DFI
investment –gender equality, climate action and the harmonisation of impact
standards ,70.
Saleem, S., Feng, Y., & Luqman, A. (2021). Excessive SNS use at work, technological
conflicts and employee performance: A social-cognitive-behavioral
perspective. Technology in Society ,65 ,101584.
Skagerlund, K., Lind, T., Str ömb äck, C., Tingh ög, G., & Västfj äll, D. (2018). Financial
literacy and the role of numeracy –How individuals’ attitude and affinity with numbers
influence financial literacy. Journal of behavioral and experimental economics ,74 ,
18-25.
Stulz, R. M. (2020). Public versus private equity. Oxford Review of Economic Policy ,36 (2),
275-290.
Wang, H., He, F., Peng, Z., Shao, T., Yang, Y. L., Zhou, K., & Hogg, D. (2021).
Understanding the robustness of skeleton-based action recognition under adversarial
attack. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern
Recognition (pp. 14656-14665).

Assessment Solutions-Information in the Market : ACFI5078

Assessment Solutions-Information in the Market : ACFI5078

Running head: BEHAVIORAL FINANCE
BEHAVIORAL FINANCE
Name of the Student:
Name of the University:
Author Note:
1 BEHAVIORAL FINANCE
Empirical evid …

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Running head: BEHAVIORAL FINANCE
BEHAVIORAL FINANCE
Name of the Student:
Name of the University:
Author Note:
1 BEHAVIORAL FINANCE
Empirical evidence for and against over-reaction and under-reaction
As per the Bayes law which considers investors to be arational being which makes
informed and timely decision based on collection and processing of all the available
information in the market. However, the same is not true and not applicable as investors are
rather emotional being which are impacted by significant biases which effect the decision-
making power of the investor (Kapoor and Prosad 2017) .This report aims to highlight the
overreaction bias which is present among the investors. The overreaction hypothesis suggests
that the investors ’reaction to aparticular news of event is phenomenal high which is not in
line with the impact of the news or event. This reaction highlights that the investors prefer
and put additional importance to any new set of information while putting lower weights to
older set of information. The reaction of the investors to information has been observed in the
past by the excessive volatility in the price of the securities and the earnings price anomaly
which is present in the markets (Fakhry 2016) .The volatility in excess in the price of the
securities had been observed in the past was based on the relationship between the earnings
quality and the dividend payment by acompany. The investors tend to prefer and give more
importance to current earnings of the company while providing lower weights to the dividend
paying power of the company. Thus, when acompany which had good/bad earnings in the
past generates bad/good earnings the market overreacts leading to fall/rise in the price of the
shares of the company (kumari Nuthalapati 2022) .Similarly, this pattern can also be justified
in the earnings price anomaly. As acompany which had aseries of bad years, investors tend
to have anegative outlook for the company but if the same company posts positive earnings,
itleads to an overreaction in the market. Thus, the overreaction of the market can be used as a
predictive force to determine the price movements of astock. If aprice which systematically
increases over time can be expected to fall and hence allow the investors to devise atrading
strategy which would generate exponential returns. The magnitude of the price movements in
2 BEHAVIORAL FINANCE
the past can be used to determine the price movements intensity as when the movement in
price is highly volatile then the subsequent price movement would also be volatile. This is an
effect which is against the weak form of efficient markets and hence allows the investors to
generate returns from the market. As per the research of de Bondt and thaler the overreaction
hypothesis in the markets holds true for the stock prices (Pokavattana, Sethjinda and
Tangjitprom 2019) .It has been observed over the sample period that in every 36 months the
over reaction is predictive and the markets tend to present this anomaly. It has been observed
over aportfolio losers and winners, the loser ’sportfolio tends to provide areturn which is
above the market return. In addition, it is also observed the risk for the loser portfolio stocks
tends to decline due to the overreaction hypothesis. The winner portfolio on an average have
led to ageneration of lower returns from the market by almost 5% while also leading to an
increase in the risk of the portfolio. The analysis concludes with two outcomes holding the
overreaction hypothesis to be true while also leading to an effect where this particular
phenomenon is occurring during the month of January. The January effect of tax loss
harvesting is considered as one of the fundamental anomalies which is leading to the
overreaction hypothesis. The loser portfolio tends to lose value in the month of October
November and areaction of January effect leads to ageneration of returns. The overreaction
hypothesis has aseasonality factor in its pattern where it occurs at agiven started period of
time which is in every 36 months and also occurs during the month of January. The
overreaction hypothesis is still visible currently in the Ukrainian stock markets where the
market had overreacted with a panic selling with the fall in price (Gens 2020) .The same
market is expected to overreact with an increase in the price in the short run. A similar event
took place during the initiation of the covid 19 pandemic where the global markets had fallen
due to the increase in the uncertainty in the markets. This was followed by asubsequent over
reaction in the market where the price of all the stocks increased exponentially in the short
3 BEHAVIORAL FINANCE
run and also leading to an all-time new high for the index (Antony 2020) .Overreaction
hypothesis holds true in the behavioural finance and also in the real markets and investors
have the opportunity to generate exponential returns based on this hypothesis in the markets.
Reference
Antony, A., 2020. Behavioral finance and portfolio management: Review of theory and
literature. Journal of Public Affairs ,20 (2), p.e1996.
Fakhry, B., 2016. A literature review of behavioural finance. Journal of Economics
Library ,3(3), pp.458-465.
Gens, D., 2020. Behavioral Finance for the Individual Investor.
Kapoor, S. and Prosad, J.M., 2017. Behavioural finance: A review. Procedia computer
science ,122 ,pp.50-54.
kumari Nuthalapati, S., (2022) analysis of cluster based corporate behaviour finance.
Pokavattana, N., Sethjinda, T. and Tangjitprom, N., 2019. The over-reaction effect in the
stock exchange of Thailand: An empirical study. Journal of Community Development
Research (Humanities and Social Sciences) ,12 (3), pp.92-106.

Task Solutions – Calendar Effect On Stock Market Returns FBLT043

Task Solutions – Calendar Effect On Stock Market Returns FBLT043

1
Calendar effects in financial markets
Name
Course professor
Course code
Date of submission
Calendar effect on stock market returns 2
Abstract …

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1
Calendar effects in financial markets
Name
Course professor
Course code
Date of submission
Calendar effect on stock market returns 2
Abstract
The study pertains to the examination of the European stock market within day and
months performance focus on the stock indexed in the period between 2004 and 2017. The study
will evaluate and discus the model specification and also evaluate the previous literatures with
the aim of proposing and justifying simple specification model which would be used to show
different types of calendar effect. With the understanding that the return sourced from investment
in stock is usually not normally distributed, residual of linear regression are subject to variant
over time and auto correlated then the study will utilize the statistically robust estimation
methodology that include the GARCH modeling and bootstrapping modeling. Even if the return
will be, lower in the month of September and august there should be no string evidence of across
the board calendar effect in such asituation and thus the most favorable evidence will be sourced
from country specific. The study will use the rolling window regression that will discover the
specific calendar effect that is linked to aspecific country over the study or analysis period with
the aim of verifying the doubt on the economic significance due to calendar effect.
Contents
Abstract ……………………………………………………………………………………………………………. 2
Chapter 1; Introduction ………………………………………………………………………………………….. 4
1.1 Relevance of the study ………………………………………………………………………………….. 5
Chapter 2: Literature Review ………………………………………………………………………………….. 7
2.1. The day of the week effect ……………………………………………………………………………. 7
2.2. The month of the year effect …………………………………………………………………………. 8
2.3 Research gap ……………………………………………………………………………………………… 10
Calendar effect on stock market returns 3
Chapter 3; Study methodology ……………………………………………………………………………… 11
3.1 Research type …………………………………………………………………………………………….. 11
3.2 Data ………………………………………………………………………………………………………….. 12
3.2.1 S&P 500 ……………………………………………………………………………………………… 12
3.2.2 Nasdaq-100 …………………………………………………………………………………………. 12
3.2.3 Euronext 100 index ………………………………………………………………………………. 13
Chapter 4; Study result ……………………………………………………………………………………….. 14
4.1 General stock return ……………………………………………………………………………………. 16
4.2 End of the month and beginning of the month high return effect ……………………… 18
4.3 The weekend effect …………………………………………………………………………………….. 20
4.4 January and July effect ……………………………………………………………………………….. 23
Chapter 5: Discussion ………………………………………………………………………………………….. 26
5.1 End of the month and beginning of the month high return effect ……………………… 26
5.2 The weekend effect …………………………………………………………………………………….. 27
5.3 January and July effect ……………………………………………………………………………….. 28
Chapter 6: Conclusion …………………………………………………………………………………………. 29
6.1 Recommendation ……………………………………………………………………………………….. 29
Reference ……………………………………………………………………………………………………….. 30
Appendix ……………………………………………………………………………………………………………. 32
Days of the month effect …………………………………………………………………………………… 32
Days of the week effect ……………………………………………………………………………………. 33
Months of the year effect ………………………………………………………………………………….. 33
Calendar effect on stock market returns 4
Chapter 1; Introduction
Calendar effect is defined as the changes in the market price or the market indexes caused
by the effect of particular days or month ion the year. The effect of the calendar on price affect
the more volatile product in the market such as the stock, the currency exchange rate as well as
some consumer product especially in the entertainment sector. Example during festive season is
highly likely for the entertainment cost to increase such effect also occur in the stock market
according to various previous theories highlighted by previous researchers. Investor has stated
that it is ineffective to invest in the stock market in particular days of the year or months due to
the effect such days have to the price of the stock. Such days have been expressed by the
researchers in the past include the October effect, the Monday effect and January affect
Halloween. Challenger effect is generally associated with the gross effect of the period or days in
ayear to the stock price in the stock market.
Previous studies have recorded existence of calendar effect in the stock market that tend
to be higher on specific calendar period and low in certain period in an year. This was caused by
high correlation rate between certain period of the year and days in ayear where certain events
occur thus affecting the stock market prices. Such effect include the weekend effect where the
Monday return has been observed to be lower than other days of the week due to low prices in
the stock market with Friday having higher return as more people would invest in Friday and
expect return on Monday. There has been significance evidence that January effect occur where
there is higher daily return in the month. In conjunction to this there are holiday effect where
certain holiday experience higher return to investment in stock while the same is opposite in
other holidays.
Calendar effect on stock market returns 5
The study will exclusively evaluate the days of the week and month of the year and how
they affect the stock market in relation to the price of stock. To achieve this, the study will use
the European stock market to evaluate the effect. The study will contribute to the information
gathered by the previous literature thus clarifying the issues in the subject matter pertaining to
the return on the stock investment. The study will achieve the study objective by starting with the
evaluation of the previous literature highlighted by other researchers. The study will highlight the
finding of other researchers with evaluation of the shortcoming of the research work in the past.
The aim is to understand the previous highlighted model so that the study can identify its
weakness and thus propose effective measured which would improve the model. The study will
progress to identification of non-normality, time-dependent variance of the residuals of linear
regressions, autocorrelation in stock market returns and apply appropriate statistical
methodologies to tackle these problems using the GARCH model using the statistical robustness
in the result. The study has examined the time stability in the most significant calendar effect in
the period of study the study will evaluate the seventeen countries in the same economic region
such that the study will gather sufficient information to aid the study make aconclusion in the
study. Comparison of the different countries ’outcome to the study will give the study authority
to develop auniversal model that can be used across different economic region to predict event
of calendar effect to stock market return.
1.1 Relevance of the study
While investing in stock market it is primary to understand the effect of such day on the
general performance stock market. Understanding how such days affect the return to investment
could lead to understanding which day to best invest in the stock market and thus generate
Calendar effect on stock market returns 6
maximum profit or reduce investment risk. The study of calendar effect is relevant in the
financial economics because some calendar effects are consistent with the efficient market
hypothesis. When the data collection is effective in stock market, then the return observed on
Monday can be expected to be three times better than the weeks days return. There are three
calendar days between the between the day which the market was closed and the day when
market will be opened. It is expected that the demand of each individual day is expressed in the
day when the stock market will be opened. However, because information slow is negligible in
the weekend then the return on Monday should be at least more than the other days of the weeks.
However according to the European stock market none of this hypothesis is consistent or holds.
In fact, the return on Monday is usually lower than that of other days of the weeks. This is the
same case for different months that are expected to have higher rate of return due to the
perception of higher trading. Such theories have been explained to be non-existing in the ideal
stock market and thus they are just hypothesis that have been rejected by the current and past
data. Due such evidence, there is no such view or effect that January has high return rate than the
other months of the year due to high influx of good new. These means that the calendar effect
will remain as odd with both the hypothesis stated below.
ï‚· Existence of efficiency in the market
ï‚· Existence of investor rational behavior
The study on calendar effect on the stock market is consistent with the manager interest
to understand the strategies that they would employ to remain profitable in the market. This
means that the information created by the study will be relevant to the financial adviser, fund and
investment manager as well as professional investor.
Calendar effect on stock market returns 7
Chapter 2: Literature Review
In the past researcher have valuated the phenomenon of seasonality and times affecting
the price movement of stock market. the regularities are known as the calendar effect to the stock
market. Some of the past studies on calendar effect involve study of the week effect and the
month effect. Additionally there have been studies that have valuated the behavior of daily return
after the holiday and the behavior of the return on the first day of the month. Such study
provided crucial information on the outcome of the studies and what development is needed to
contribute to the studies.
2.1. The day of the week effect
Study carried out by cross (1973) portrayed how weekend effect affects the stock prices.
He used the United States stock market to evaluate how the weekend affects the prices of the
stock and share in the Monday as the stock market is opened. The researcher evaluated using the
regression and correlation statistical test and discovered negative return over the weekend. The
result of the study was consistent with the study that was conducted by keim and stambaugh
(1984) which concluded that the return were negative averagely post the weekend. The study
stated that the weekend effect has been causing the stock market to have low return due to low
turnout and little information spread and availability. In 1984, rogalski used the ftest OLS
regression as well as ttest to evaluate the Monday effect and observed that it causes negative
return but will alow significance level. A study carried out by Chang 2000 and Kamara in 2002
stated that the validity of the weekend effect was insignificant to approve of the outcome of the
Monday effect. A study by Condoyanni et al. (1987) and Chang, et al. (1993) evaluated the
United States stock market and other non-united states countries such as japan Australia,
Calendar effect on stock market returns 8
Singapore, UK, Canada and other countries in the European countries and found out that the
negatives effect was averagely negative and statistically significant. The issue on the Monday
effect and the weekend effect has caused both positive and negative result among the researchers
with both high validity and low validity of both positive and negative result. In the recent times,
there have been low research papers to explain such effect in the resent period using recent data.
The fact that different results are observed by different researchers cause need for more
evaluation of the present literatures and research works. Sullivan, Timmermann and White (2010)
used the nontraditional approach to boots strap procedure and concluded that calendar effect has
no significant statistical significance. Rubinstein (2001), Mabberly and Waggoner (2000),
Schwert (2001), Steeley (2001), Kohers et al. (2004) and Hui (2005) conducted an international
study which show that the market becomes weaker especially for developing market. A study
carried out to understand the week effect in stock market return in fifteen European countries and
discovered corroborative evidence in seven markets while the rest the outcome was
insignificance. The study discovered anegative return on the Tuesdays and in some countries,
the use of differentiated model detected week effect. Due to this, the study concluded that
majority of the 21 emerging stock market are not affected by the calendar effect on the stock
market investment return. Overall, there is mixed evidence on day of the week effects, as more
recent studies, using more advanced statistical procedures, have cast some doubt on the favorable
evidence from the initial studies.
2.2. The month of the year effect
The month effect is defined as the effect of the stock market return due to the month of
the year. Some months due to the events occurring in the month, they may have ahigher return
Calendar effect on stock market returns 9
or alow return. Additionally due to the social perspective of investing, amonth may have more
investment return due to stock increase in the prices. According to various researchers, there
exist the January effects where the investor is expected to have ahigher return during the month
of January. Researchers explain that this is the period when most company has produced their
financial performance of the previous financial year and their projection of the coming year is
realized. For long-term investment ion the stock, this is the right time for investment according
to the previous studies, as it will facilitate. Apart from the January effect, other months have
been reported also to affect the return of the investor. studies conducted by Brown et al. (1983),
Dyl (1977) and Rozeff and Kinney (1976) whose purpose was the analysis of the united states
stock market to understand or identify existence of high return in January observed asignificance
higher return in January than other months of the year. A previous study conducted by Gultekin
and Gultekin (1983) used the non-parametric approach as well as parametric test to evaluate the
month effect to the stock market return. The study observed positive return and even higher
return in January compared to the other months of the year. The study-evaluated stock market
from 15 countries to have asignificant value that could be used as areferenced conclusion.
A study conducted by Keim (1983) related the January effected to the small firm effect
and anumber of international studies discovered that small firm achieved larger return rate than
the larger firm did during the month of January. The reason as explained by the research was the
fact that most small firm produce their end year report during the year of December and this
information is used by investor to verify their investment into the small firms. The result of this
study were confirmed by other studies that followed by Aggarwal, Rao and Hiraki, 1990.
January effect is explained to be caused largely by the behavior of the price of the small firm.
Additionally the tax loss-selling hypothesis that was proposed in 1983 by brown who explain
Calendar effect on stock market returns 10
that the selling pressure at the end of the year depresses the price that rebound back during the
month of January. When the UK market was used to study the month effect, the researcher
discovered April effect for small firms and January effect for larger firms.
A study conducted by H0 in 1995 evaluated 12 stock market sources fromjapan, austrlai,
Korea, New Zealand, Thailand, Singapore, U and the united states of America. The study
observed that there was corroborative of the January effect that affected the return of the stock
higher than other month. The study observed with a high level of confidence at 96%. In the
recent year a study conducted by Tonchev and Kim (2004) and Haugen and Jorion (1996)
discovered areal empirical finding which was similar to the previous studies. The study however
observed that the April effect existed in several nations with lower level of return in December
and July.
2.3 Research gap
In the previous study as evaluated in the study above there have been mixed
understanding of week, day and the month effect to the stock market return. There have not been
consistent understanding how such period and season within ayear affect the productivity of the
stock market and thus without adefinitive model to highlight what the investor or manager need
to understand pertaining calendar effect on the stock return the investment decision may be
Confucius. The study has come to conclusion from the previous literature that there is need to
have one study which is consistently with the current data or more recent data. Such amodel will
be used in making decision on investment. Such a model will either refute or verify the past
studies. To ensure that the study has a high confidences level the study will collect a large
Calendar effect on stock market returns 11
enough sample consolidated from different countries stock market but especially the United
Kingdom.
Chapter 3; Study methodology
The methodology is asystematic and theoretical analysis of the method that is applied at
afield of study. This section will cover the approach with which the study used to collect the
data, conduct data analysis and latter present the study outcome or make a conclusion of the
study. The study will include primary stock performance historical data sourced from financial
website such as yahoo finance. The study will conducted aquantitative study that will rely on
financial data on different types of stock over time to make conclusion. This means that the study
will collect data from financial website on the stock performance over time since 2004 to 2017.
This data will be evaluated and the outcome will be used to make the decision pertaining to the
3.1 Research type
With the identification of research approach that will be used in the study as quantitative,
the study will adopt the research type that will aid in realization of the quantitative research
approach. The study will use the experimental research style to actualize the research approach
selected to the study. This research type will involve creative research and experimental; while
developing the model to the study. The study will seek to identify the cause and effect of the
calendar effect on the return to stock market. The study will evaluate the independent variable
against the dependent variable to understand how the dependent variable is affected by the
independent variable. The dependent variable in this case is return in the stock market while the
independent variable is the calendar days like the days of the week, weeks in amonth or the
Calendar effect on stock market returns 12
month in ayear. Understanding of the relationship will aid in understanding when to invest best
and when to liquidation of the stock. The information and relationship as well as the model that
will be developed by the study will be relevant to investor and fund manager while deciding
when to invest and how to take advantage of the stock market.
3.2 Data
3.2.1 S&P 500
The aim of the study is to evaluate calendar effect on the stock market return. Previous
studies have observed the weekend effect, the end of the month and beginning of the month
effect as well as January effect as well as July effect on the stock market return. The study aim at
conducting an analysis of the New York stock market based on S&P 500 stock. In order to obtain
high confidence interval that will be significant in developing the conclusion of the study the
study will conduct analysis of the stock market starting 2010 to the present data. The study has
made 3118 observation from the S&P 500 indexes stock prices. The S&P 500 has been selected
because it contains 500 stock companies from the United States stock market in all industries.
With the understanding of the stock market from the S&P 500 perspective, it means that the
study would be evaluating the whole economy. The study has made such analysis with the
understanding that the S&P 500 indexes selected would represent the outcome of the whole
industry and multiple countries because the index is not limited to the United States companies
but international well performing companies. This means that the study will be considered all
industries globally.
3.2.2 Nasdaq-100
Calendar effect on stock market returns 13
The study second sample data was sourced from yahoo finance on the Nasdaq data.
Nasdaq is astock index which contain all high capitalization company in the New York stock
market. Unlike the S&P 500 that contains a variety of companies from different industries,
Nasdaq has high capitalization company which mostly are within the technology and innovation
industry. The index also has high capitalization real estate, health, and Medicine Company. This
means that the index is characterized of high return companies. the Nasdac index was selected
because S&P 500 do not majorly carry the lead companies in the economy but a variety of
companies which are selected to represent certain industries because on their high performance.
The reason why this index was included in the study as it would give the perspective of calendar
effect from the large companies and high capitalization end.
3.2.3 Euronext 100 index
From the fact that the study is expected to evaluate the calendar effect globally the study
would need to integrate the European countries stock market in the study. Due to this need the
study utilized the Euronext 100 index which is an index of 100 European companies. This index
is referred to ablue chip index of the pan European exchange. It houses largest and the most
liquid stock which are traded in the Euronext. The requirement of the index is that each stock
must trade more than 20% of the issued shares over the period of arolling year of analysis. The
index will be reviewed quarterly in the size and liquidity analysis of the investment universe. The
index will represent the calendar effect in the form of the European countries and European stock
market called Euronext. The study made observation of the stiock since janual third 2005 with
observation of more than 4455 observation during this period.
Calendar effect on stock market returns 14
Chapter 4; Study result
The study highlight that the stock and indexes daily return will be calculated as:
Rt=ln(p t/pt-1)
The rt represent the daily return of the stock market index and the term pt represent the stock
index at the date tlisted. While making observation the study emphasized on using the trading
days of the week and month. All the three index belong to two stock market which have trading
days as five in aweek. Thus, the study made only five days in aweek. The days of the week are
labeled 1-6 while the months of the year are labeled 1-12 and the days in amonth are labeled 1-
23 depending on the trading days in month
When the stock market is closed on aweekday then the daily return will not be calculated
for the day the stock market is closed as well as the following day after the closure of the stock
market. These mean that the two day will be skipped while making the observation. Generally,
all the daily return will be computed with a strategic lag of one calendar day except from
Monday that has alag of three calendar days. The study made more than 3118 observation from
the European countries stock both United Kingdom company stocks as well as the Poland stocks.
The study will use descriptive statistic to analyses the outcome of the data analyzing and the
information gathered from the study.
The study will utilize the secondary data that will be sourced from yahoo finance for the
s&p 500 indexes since 2010 to 2022. The data will be used to evaluate the existence of calendar
effect on the stock market. The study made atotal of 3115observation and understanding such a
trend-required assistance of data analysis and use of e-view to understand the data. The index
Calendar effect on stock market returns 15
comprises the 500 top performance and high capitalization companies in the United States and
beyond. The reason why this index is selected the fact that the index comprise of companies
from all industries. The study made 3118 observation on the data. There is need to understand
that stock market are open in five days in aweek because on weekend the stock market does not
open then there is missing data for Saturday and Sunday of the 52 weeks in ayear. Ion the study
there are two variables, which is the dependent viable that in this case is the stock return and the
independent variable that in this case is the days, weeks and months in ayear. The study will
evaluate the effect of the independent variable on the dependent variable. The study will use the
model below that will investigate the January effect as well as the weekend effect to the stock
return.
Rt=βo+β1Dt+β2Dt+β3Dt+β4Dt+εt
Rt = a+ x1M 1+ x2M 2+ x3M 3+ x4M 4+ x5M 5+ x6M 6+ x7M 7+ x8M 8+ x9M 9+ x10M 10 + x11M 11
+εt
In the above mode D show the days of the week which are five in the week while m represent the
month in ayear which are 12 in number. RT represents the stock return. The study will utilize
the anova, ttest and the regression model to evaluate he relationship between dependent and
independent factor and also the hypothesis highlighted above. The daily return of the index
selected as s& p 500 will be calculated using the formula rt= ln (
)in this case Irepresent
index value. see the attached tables
Calendar effect on stock market returns 16
4.1 General stock return
The study observed 3114 observation on the data pertaining to the return of the index s&p500 in
the New York stock market. The stock was selected to be used to observe on the weekend effect,
the Friday effect, and month and week effect all known as Calendar effect on the stock market
return
Over years, the S&P 500 company stock price has been consistently increasing in the price due
to the increase in the demand of the stock in the stock market. as the primary index in the new
york stock market which represent all the industry in the economy as it has stock from all
industry the result of the index are reliable in forging aconclusion on the calendar effect. When
evaluating the general return of the stock the following table is developed
Factor s&P 500 Return Percentage return
mean 0.89588764 0.046%
standard deviation 27.89618821 1.098%
Calendar effect on stock market returns 17
variance 0.000121
The average return from the stock is 0.046% with astandard deviation of 1.098% and variance of
0.000121. The standard deviation shows the risk that an investor would be indulging by deciding
to invest in the stock. The rates of the standard deviation suggest that this is anon-risk or low
risk asset and this is the reason why the stock price is high. The instances when the stock has
hade decline in the price thus loss to the invest is the occasion when there was economic
recession and decline in economy.
Nasdaq price Return Percentage return
average return 4708.02 2.360826 0.000555
standard dev 3783.565 87.81824 0.013872
variance 14315367 7712.044 0.000192
The average return from the stock is 0.055% with astandard deviation of 1.08% and variance of
0.000192. The standard deviation shows the risk that an investor would be indulging by deciding
to invest in the stock. The rates of the standard deviation suggest that this is anon-risk or low
risk asset and this is the reason why the stock price is high. The instances when the stock has
hade decline in the price thus loss to the invest is the occasion when there was economic
recession and decline in economy.
Euronext 100 price Return Percentage return
average return 869.7135357 45.78344854 0.05085389
standard dev 198.1587502 133.04833 0.140172412
variance 39266.8903 17701.85811 0.019648305
Calendar effect on stock market returns 18
The average return from the stock is 0.05085 with astandard deviation of 0.14075 and variance
of 0.019648. The standard deviation shows the risk that an investor would be indulging by
deciding to invest in the stock. The rates of the standard deviation suggest that this is anon-risk
or low risk asset and this is the reason why the stock price is high. The instances when the stock
has hade decline in the price thus loss to the invest is the occasion when there was economic
recession and decline in economy.
4.2 End of the month and beginning of the month high return effect
The study utilized regression analysis to evaluate the relationship between the days of the
month to their return. The regression analysis tool is used to find the relationship between the
independent and depend variable. Due such it was used to evaluate the relationship between the
days of the week as the independent variable and the stock return as the dependent variable. The
study would evaluate the extent with which the days of the month affect the return. The table is s
Regression Statistics
Multiple R 0.331955
R Square 0.110194
Adjusted R Square -0.06777
Standard Error 5.814862
Observations 19
The study observed that the average trading days in amonth is 19 for the Euronext and Nasdaq
while S&P 500 average trading days was 23 days. However, 19 were selected as it was the
modal trade days. The multiple R is the correlation coefficient that shows the linear relationship
between the dependent and independent variable. It value is 0.331955 which shows avery low
overall relationship between the days of the month and the return in the day. This mean that the
Calendar effect on stock market returns 19
day of the week has little to do with the return or rather the influence of the days of the month on
the return of the stock is low.
The R2shows the coefficient of determinant that will explain how many points fall on the
regression line. In this case, 11.02% mean that the variation of the yvalues around the mean will
be shown by the x-value. This means that 11% is the value fit for the model. The adjusted R2will
adjust the number of terms in the model. The standard error of regression is the estimate of the
error µ standard deviation that is quite different from standard error. The standard error in the
regression is specific according to the coefficient evaluated. When the coefficient is huge
compared to the standard error then the coefficient will be zero.
ANOVA
df SS MS F
Significance
F
Regression 3 62.81 20.94 0.62 0.61
Residual 15 507.19 33.81
Total 18 570
The sum of the squared is 62.81 for the regression and 507.19 for the residual the regression
degrees of freedom is 20.94 shown by the regression ms and aresidual of 33.81. The result for
the ftest is 0.62 for the null hypothesis with asignificance pvalue associated with the regression
being 61%. Due to the ftest above the null hypothesis is rejected. The null hypotheses dictate
that the days of the month affect or influence the return to the stock market.
Coefficients Standard
Error
tStat P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept 16.3 9.1 1.8 0.1 -3.1 35.7 -3.1 35.7
S&P 500 -2627.1 2207.9 -1.2 0.3 -7333.2 2078.9 -7333.2 2078.9
NASDAQ 1293.4 2231.7 0.6 0.6 -3463.4 6050.3 -3463.4 6050.3
EURONEXT -112.3 175.3 -0.6 0.5 -486.0 261.4 -486.0 261.4
Calendar effect on stock market returns 20
The coefficient represent sthe average expected change with response to the variable assuming
the independent variable. The coefficient show s the relationship between the dependent and
independent variable in the study. From the first outcome of the study, the study has established
that there is no much relationship between the independent and the dependent variable through
the low multiple R values in the study. Additionally the null hypothesis has been rejected in
favor of the alternative hypothesis. However ,the coefficient show sdifferent result all together.
Two of the index S&P 500 and the Euronex t100 has negative coefficient with high standard
error, Negative coefficient show negative relationship. However ,the NASDAQ shows high
positive relationship with ahigh margin of error. The entire study outcome has ahigh significant
interval of
The p-value shows the significance of the coefficient or the relationship forged by the regression
analysis. The study with high p value has a hig h significance level and thus it is statistically
significant. Inorder to accept the study outcome the significance interval should be below 0.05.
the p-value which is less than 0.05 shows at 5% confidence interval the dependent variable is
statistically significance. Because the significance level is too large at 10%, 30%, 60% and 50%
then the independent variable is insignificant to the retur n of the stock and thus the null
hypothesis will be rejected in favor of the alternative hypothesis. The study found no significant
proof that the day of the month has any influence on the return on stock.
4.3 The weekend effect
The study utilized regression analysis to evaluate the relationship between the days of the
week to their return in the stock market. The regression analysis tool is used to find the
relationship between the independent and depend variable. Due such it was used to evaluate the
Calendar effect on stock market returns 21
relationship between the days of the week as the independent variable and the stock return as the
dependent variable. The study would evaluate the extent with which the days of the month affect
the return.
Regression Statistics
Multiple R 0.999249
R Square 0.998498
Adjusted R Square 0.993993
Standard Error 0.12255
Observations 5
The study observed that the average trading days in aweek is 5 due to the fact that during the
weekend globally the stock market is closed and only open on Monday the following week. In
the analysis, 2represent the second day of the week that is Monday while 6represent Friday the
sixth day of the week. The multiple R is the correlation coefficient that shows the linear
relationship between the dependent and independent variable. It value is 0.9999 which shows a
very high overall relationship between the days of the month and the return in the day. It mean
that the day of the week has alot to do with the return or rather the influence of the days of the
week on the return of the stock is high.
The R2shows the coefficient of determinant that will explain how many points fall on the
regression line. In this case, 99.84% mean that the variation of the yvalues around the mean will
be shown by the x-value. This means that 99.94% is the value fit for the model. The adjusted R2
will adjust the number of terms in the model. The standard error of regression is the estimate of
the error µ standard deviation that is quite different from standard error. The standard error in the
regression is specific according to the coefficient evaluated. In this case, the stand error of the
study is 12.25% that is within the margin of acceptable error due to the standard deviation.
Calendar effect on stock market returns 22
ANOVA df SS MS F Significance F
Regression 3 9.984981582 3.32832719 221.6164 0.04933
Residual 1 0.015018418 0.01501842
Total 4 10
The sum of the squared is 9.984 for the regression and 0.015 for the residual the regression
degrees of freedom is 3.32832 shown by the regression ms and aresidual of 0.015. The result for
the f test is 221.6 for the null hypothesis with a significance p value associated with the
regression. Due to the ftest above the null hypothesis is accepted. The null hypotheses dictate
that the days of the week affect or influence the return to the stock market.
Coefficient Standard Error tStat P-value Lower 95% Upper 95 Lower 95% Upper 95
Intercept -16.94 2.18 -7.76 0.05 -44.68 10.79 -44.68 10.79
S&P 500 496.47 340.46 1.46 0.04 -3829.43 4822.38 -3829.43 4822.38
Nasdaq -2720.08 235.94 -11.5 0.03 -5717.97 277.81 -5717.97 277.81
Euronext 437.18 42.53 10.28 0.03 -103.24 977.61 -103.24 977.61
The coefficient represent sthe average expected change with response to the variable assuming
the independent variable. The coefficient show s the relationship between the dependent and
independent variable in the study. From the first outcome of the study, the study has established
that there is much relationship between the independent and the dependent variable through the
high multiple R-values in the study. Additionally the null hypothesis his accepted with rejection
of the alternative hypothesis. However ,the coefficient show sdifferent result all together. Two of
the index S&P 500 and the Euronex t100 has high coefficient with low standard error, positive
coefficient show positive relationship. However ,the NASDAQ shows high negative relationship
with ahigh margin of error. The entire study outcome has ahigh significant interval of 96%
The p-value shows the significance of the coefficient or the relationship forged by the regression
analysis. The study with high p value has a hig h significance level and thus it is statistically
significant. Inorder to accept the study outcome the significance interval should be below 0.05.
Calendar effect on stock market returns 23
the p-value which is less than 0.05 shows at 5% confidence interval the dependent variable is
statistically significance. Because the significance level is too large at 5%, 4%, 3% and 3% then
the independent variable is significant to the retur nof the stock and thus the null hypothesis will
accepted while the alternative hypothesis will be rejected. The study found significant proof that
the day of the week has any influence on the return on stock.
4.4 January and July effect
The study utilized regression analysis to evaluate the relationship between the months of
the year to their return in the stock market. The regression analysis tool is used to find the
relationship between the independent and depend variable. Due such it was used to evaluate the
relationship between the months of the year as the independent variable and the stock return as
the dependent variable. The study would evaluate the extent with which the month of the year
affects the return.
Regression Statistics
Multiple R 0.536543
R Square 0.287878
Adjusted R Square 0.020832
Standard Error 3.567798
Observations 12
The study observed that the average trading months in a year is 12 month of the year. Each
month has been represented or coded with its specific defining number. One represents January
the first month of the year while 12 represent December the last month of the year. The multiple
R is the correlation coefficient that shows the linear relationship between the dependent and
independent variable. It value is 53% which shows avery high overall relationship between the
Calendar effect on stock market returns 24
months of the month and the return in the day. It means that the day of the year has alot to do
with the return or rather the influence of the months of the year on the return of the stock is high.
The R2shows the coefficient of determinant that will explain how many points fall on the
regression line. In this case, 28.78% mean that the variation of the yvalues around the mean will
be shown by the x-value. This means that 28.74% is the value fit for the model. The adjusted R2
will adjust the number of terms in the model. The standard error of regression is the estimate of
the error µ standard deviation that is quite different from standard error. The standard error in the
regression is specific according to the coefficient evaluated. In this case, the stand error of the
study is 356.77%% that is within the margin of acceptable error due to the standard deviation.
ANOVA df SS MS F Significance F
Regression 3 41.16656393 13.722188 1.07801 0.411666
Residual 8 101.8334361 12.7291795
Total 11 143
The sum of the squared is 41.166for the regression and 101.83 for the residual the regression
degrees of freedom is 13.722 shown by the regression ms and aresidual of 123.73. The result for
the f test is 1.078 for the null hypothesis with a significance p value associated with the
regression. Due to the ftest above the null hypothesis is accepted. The null hypotheses dictate
that the months of the year affect or influence the return to the stock market.
Coefficients Standard Error tStat P-value Lower 95% Upper 95% Lower 95% Upper 95%
Intercept -37.11 28.39 -1.31 0.05 -102.59 28.36 -102.59 28.36
s&p 500 883.87 2420.15 0.37 0.04 -4697.00 6464.75 -4697.00 6464.75
nasdaq 427.83 2763.26 0.15 0.04 -5944.27 6799.93 -5944.27 6799.93
euronext 844.63 564.23 1.50 0.04 -456.48 2145.74 -456.48 2145.74
The coefficient represent sthe average expected change with response to the variable assuming
the independent variable. The coefficient show s the relationship between the dependent and
Calendar effect on stock market returns 25
independent variable in the study. From the first outcome of the study, the study has established
that there is much relationship between the independent and the dependent variable through the
high multiple R-values in the study. Additionally the null hypothesis his accepted with rejection
of the alternative hypothesis. However ,the coefficient show sdifferent result all together. Two of
the index S&P 500, NASDAQ and the Euronex t100 has high coefficient with low standard error,
positive coefficient show positive relationship. The entire study outcome has ahigh significant
interval of 96%
The p-value shows the significance of the coefficient or the relationship forged by the regression
analysis. The study with high p value has a hig h significance level and thus it is statistically
significant. Inorder to accept the study outcome the significance interval should be below 0.05.
The p-value that is less than 0.05 shows at 5% confidence interval the dependent variable is
statistically significance. Because the significance level is too large at 5%, 4%, 3% and 3% then ,
the independent variable is significant to the retur nof the stock and thus the null hypothesis will
accepted while the alternative hypothesis will be rejected. The study found significant proof that
the month of the year has any influence on the return on stock.
Calendar effect on stock market returns 26
Chapter 5: Discussion
5.1 End of the month and beginning of the month high return effect
From the graph above, it is evident that for all the three indexes the beginning of the
month is slightly higher return. For nasdaq and the s&p 500 indexes the beginning month start on
ahigh return to the stock investment and from there is falls or raised accordingly to the factors of
the market. However the result is inconclusive because the highest for the nasdaq and the s&p
500 is between the month in the period between 11 and 12. Conversely the lowest is just about
the same period between the period of 13- 15. This days is inconsistent and random because
during the peak of high performance for nasdaq and the s&p 500 it was the peak for low
performance for Euronext. This man that the data that would predict the extent of the days of the
month effect to the stock market return are inconclusive and thus as the regression analysis did
not find sufficient information to conclude that the days of the month have any effect on the
return in the stock market .
Calendar effect on stock market returns 27
5.2 The weekend effect
The weekend effect state that after the weekend the stock market usually have high return due to
the nun trading days of Saturday and Sunday. The weekend affect also dictate that in the Friday
the return is reduced as more people seek to go to weekend with their asset and only liquidate
them during the new week on Monday.
The chart above concurs with the outcome of the regression analysis that during the beginning of
the new week the return has always been high for the entire stock index. This is aclear proof of
the weekend effect as shown by the regression analysis. The chart above also shows that there is
low return in the end of the week on Friday. The literature has explained that the perception of
the population and stock trader is that Friday for conservation thus lowering the demand and
supply in the stock market while on Monday is liquidation. This mean that strategically the
investor should seek to buy stock during the course of the week especially on Wednesday when
the stock prices are at the lowest while liquidate the stock while the price is highest on Monday.
Calendar effect on stock market returns 28
5.3 January and July effect
The monthly effect on the stock return dictates high return in the stock market during
certain months of the year. The narrative follow that in certain months of the year the stock
market is active with high demand rates and low supply especially when closing the first quarter,
second quarter and thirds quarter. Some researchers have explained high return on January and
July while others strictly negate this theory. The study has observed positive relationship
between the month of the year and the return meaning there are some months in the year with
high return than others. The study will evaluate such phenomena using the graph trend of the
return.
From the graph above it is common that the three index move in the same trend showing
consistency in the stock market. All the stock open the year with low return shown by low stock
return in January. This is consistent in the entire three indexes. This dispute the previous
literature that during January there is high return compared to other months. The study hover has
seen high return consistent in the entire three index in the month of April, July and October. The
Calendar effect on stock market returns 29
study has also observed low return in the months of January, March, May and August. This can
act as direction with which the investor should take while investing and yielding high results.
The study also clearly observe that the return and loss are consecutive meaning in the event that
the stock is lowering itwill certainly increase its return on the following and upcoming month.
Chapter 6: Conclusion
In conclusion, the study has observed with certain amount of stock return observation that the
return of the stock market can be influenced by the month of the year and the days of the week.
The study has observed low return in the month of January, March, may, august and September.
There was presence of high return for all indexes in the months of April, July, comber and
December. The study literature explains the calendar effect is caused by the investor perception
of the return as well as the internal reporting period of the company. This month ’swhen the
companies have been observed to have high return are the months when the companies make
report of their development and annual earning. The study has observed that the days of the
month do not affect the return. However the days of week has much effect on the return as
Monday had abnormally high return while the Wednesday has very low prices.
6.1 Recommendation
This information should be effective in the investment decision as the investor should seek to
buy the stock when the price is lowest and liquidate them when the prices is high to gain
maximum return possible. The study would however recommend further study to evaluate how
this information can be used effectively in line with other predictors of the stock price such that
the investment risk can be reduced or strategic investment can be ascertained
Calendar effect on stock market returns 30
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Appendix
Days of the month effect
DAYS OF THE MONTH S&P 500/100 NASDAQ/100 EURONET
1 0.167525791 0.203714439 0.054782
2 0.063370029 0.074580556 0.054505
3 0.158963259 0.059794978 0.059705
4 0.052194396 0.024841654 0.054066
5 0.021757865 -0.036977626 0.037247
6 0.016554617 0.013225882 0.055024
7 0.151413516 0.089143077 0.040052
8 -0.090633731 -0.073679499 0.052024
9 -0.030343983 0.127741577 0.054464
10 0.099361515 0.076627989 0.05867
11 0.122439877 0.081926586 0.054961
12 0.216525861 0.249181379 0.037809
Calendar effect on stock market returns 33
13 -0.099949363 -0.120450786 0.057276
14 -0.120776254 -0.130853019 0.03907
15 -0.025546828 0.058342993 0.054134
16 -0.04481949 0.104538155 0.055358
17 0.053666614 0.043570516 0.059688
18 0.069422002 0.077070351 0.055627
19 0.09985362 0.035453304 0.038709
20 0.082211243
21 0.075204962
22 -0.148402892
23 0.070057664
Days of the week effect
DAYS OF THE WEEK S&P 500/100 NASDAQ/100 EURONET
2 0.118367381 0.144049234 0.051007
3 0.048936762 0.091118531 0.050567
4 0.023061575 0.033342394 0.049919
5 0.034678679 -0.004466657 0.049433
6 0.009710663 0.019214624 0.053568
Months of the year effect
MONTHS OF THE YEAR S&P 500/100 NASDAQ/100 EURONET
1 0.022035994 -0.003499694 0.04668
2 0.06583427 0.010770567 0.051774
3 0.018347422 0.076357799 0.051095
4 0.087409726 0.119970043 0.050651
5 -0.059472724 0.009556518 0.052131
6 0.067149705 0.030874717 0.04913
7 0.100863581 0.149729215 0.049895
8 -0.017934057 0.051410517 0.05018
9 -0.009979238 -0.002910632 0.050502
10 0.118358231 0.084810203 0.054496
11 0.10140578 0.050721392 0.050677
12 0.064509637 0.087973117 0.053217