Degree Programmes
Final Year Project Cover Sheet
Please complete the form (in capital letters) and attach it securely to the front of your assignment
before submitting your assignment.
Student ID: …..0348585………………………………………………
Title of Your Award: …FINAL YEAR PROJECT …………
Name of Supervisor: …DR YAMUNAH VAICONDAM………………………………………
Module Code:
P
R
J
6
0
1
0
4
Research Project Title: Impacts of Foreign Direct Investment, Inflation, Export of Goods and
Services, and Imports of Goods and Services on Standard of Living in Malaysia
Due Date & Time: …28 JUNE 2023, 2PM……………………………
I have read and understood the Degree Programmes Regulations on cheating, plagiarism, and collusion. I declare
that this piece of work is my own and does not contain any unacknowledged work from any other sources.
I authorise the University to test any work submitted by me, using text comparison software, for instances of
plagiarism. I understand this will involve the University or its contractor copying my work and storing it on a
database to be used in future to test work submitted by others.
Note: The attachment of this statement on any electronically submitted assignments will be deemed to have the same
authority as a signed statement.
Signed: DENIS
Date: 28 JUNE 2023
Impacts of Foreign Direct Investment, Inflation, Export of Goods and Services, and
Imports of Goods and Services on Standard of Living in Malaysia
Denis Sim Li Teik
Bachelor of Business (Hons) Finance & Economics
Taylor’s Business School
Taylor’s University
Appendix I
FINAL YEAR PROJECT SUBMISSION CHECKLIST
(this check-list should be placed after the project cover page)
Dear Students,
1. Have you uploaded the soft copy of your project paper (with reference list,
questionnaire/ list of secondary data & SPSS/Eviews/Excel output)to Turnitin?
Yes
/
No
2. Have you generated the full Turnitin similarity report and attached that to your project paper?
Yes
When:
3. Please make sure you have included the following documents before submitting your project
papers:
No.
1.
2.
3.
4.
5.
6.
7.
8.
9.
Documents (according to sequence)
Please ‘√’ if your
project paper has
the document
Cover page
Title page
Statement of Authorship
Table of Contents
Abstract
Chapter 1 to 5
Reference list
Questionnaire/list of secondary data
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/
/
/
/
/
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10.
SPSS/Eviews/Excel
research output; supporting documents for
qualititative research
Three copies of Supervisor and Student Meeting Record (signed)
11.
12.
13.
Research Ethics Check-list (signed)
Full Turnitin similarity report
Supervisor Review Record (signed)
/
/
/
Student’s Signature: denis
Date: 28 JUNE 2023
Student Name: Denis Sim Li Teik
Student ID: 0348585
Programme: Bachelor of Business (Hons) Finance & Economics
Module Code: PRJ60104
/
Acknowledgement
I would like to express my deepest gratitude towards Dr Yamunah Vaicondam for being my
supervisor and guiding me through so many obstacles throughout my final year project journey.
Without her, it will truly be impossible for me to accomplish my final-year project
Lastly, I want to show appreciation to my friends and family for being considerate of me
throughout these past few months while I was overcoming major hurdles in my life.
Statement of Authorship
I, Denis Sim Li Teik, hereby declare that this study is based on my original work except for
quotations and citations, which have been duly acknowledged. I also declare that it has not been
previously or concurrently submitted elsewhere in any other institutions or any other degree of
qualification.
Word Count: ( 9600 words)
Signature: denis
Date: 28 JUNE 2023
Table of Contents
Appendix I ............................................................................................................................................................3
3.
Please make sure you have included the following documents before submitting your project papers:
3
Abstract................................................................................................................................. 7
Abstract
The intention of this research is to investigate the relationship between the determinants of standard of
living in Malaysia which are foreign direct investment, inflation rate, exports of goods and services and
imports of goods and services. The approach that has been selected to run the regression model is
Ordinary Least Squares and the output data will be produced with EViews. There is a total of 32
observations in this research and the period ranges from 1990 to 2021. To interpret and analyse the data,
several methods such as correlation analysis, descriptive statistics analysis and multiple regression
analysis were employed. Diagnostic tests such as heteroskedasticity test, serial correlation test and
normality test were carried out to test the quality of the regression model. The relationship between all
four of the independent variables with the dependent variable is significant at 1% significance level and
the expected signs were aligned with the hypothesized signs from the literature review. Recommendations
for policymakers in developing countries who are striving to reach Malaysia’s high standard of living will
be to divert more resources to the four identified independent variables in future policies.
Chapter 1
1.1 Research Title
Impacts of Foreign Direct Investment, Inflation, Export of Goods and Services, and Imports of Goods and
Services on Standard of Living in Malaysia.
1.2 Background of Research
The standard of living is among the many critical economic issues policymakers are actively trying to
improve when implementing economic policies. Living standards pose a significant challenge to
developing countries due to various factors hindering well-being and socioeconomic progress. Limited
access to necessities, income inequality, and inadequate social infrastructure are among the key issues
faced by these nations. The Covid-19 pandemic has worsened the standard of living crises in many
developing countries and the average household income in developing countries has experienced an 8% to
87% fall in income (Egger et al., 2021). Living standards dropped significantly as food insecurity became
a common theme during the pandemic (Egger et al., 2021).
A primary concern is the prevalence of poverty and extreme poverty. According to the World Bank,
around 9.2% of the global population lived in extreme poverty in 2020, struggling to meet their most
basic needs (World Bank, 2020). Insufficient income prevents individuals from accessing proper nutrition,
healthcare, education, and housing, leading to a diminished standard of living. Over 2.5 billion of the total
human population live on a budget of 2 USD per day (GiveWell, n.d.) which means many of them can
barely afford basic necessities and have to live under very bad living conditions.
The indicator selected to measure standard of living is the human development index (HDI). HDI measures
3 key dimensions of human development which are life expectancy, education, and decent standard of living
(UNDP, n.d). HDI measures all the essential elements of standard of living thus it will be used as an
indicator of the standard of living in Malaysia over the years. Throughout the rest of this research, both the
word standard of living and human development index are going to be used interchangeably but they
ultimately are referring to the same thing.
Income inequality compounds the problem, as it restricts opportunities and perpetuates disparities. The
United Nations Development Programme (UNDP) emphasizes that unequal distribution of wealth and
resources can impede social mobility and hinder overall development (UNDP, n.d). Marginalized
populations are particularly affected, with limited access to education, healthcare, and essential services.
Inadequate social infrastructure further exacerbates the challenges. Insufficient investment in healthcare
systems results in limited access to quality medical services, contributing to higher mortality rates and
increased vulnerability to diseases. The World Health Organization (WHO) highlights that many
developing countries struggle to provide essential health services to their populations (WHO, 2017).
Similarly, a lack of educational opportunities restricts human capital development, hindering
socioeconomic progress and reducing prospects for individuals and communities.
Addressing the problem requires comprehensive efforts. It entails implementing policies and initiatives
aimed at poverty alleviation, equitable economic growth, and investment in social infrastructure.
Collaboration between international stakeholders, development assistance, and domestic reforms are
crucial in improving developing countries' living standards.
1.3 Problem statement
The standard of living can be used as an indicator of the quality of life, economic growth, human
development, and social stability in a country (UNDP, n.d) which are all the macroeconomic goals of
policymakers in a country. Thus, the goal of many economic policies implemented by policymakers is to
improve a country's overall standard of living.
Global poverty rates are at a concerningly high level, especially in developing nations such as the SubSaharan African nations (GiveWell, n.d.). Based on data estimates, over 1.4 billion of the total human
population live under a daily budget of 1.25 USD and over 2.5 billion survive off an amount lesser than 2
USD a day (GiveWell, n.d.). Living on such a tight budget means that the majority of the income is spent
on necessities such as food which leaves very little amount left for productive assets such as a phone or
bicycle. In developing nations like Mexico and Indonesia, tap water and toilet systems which are deemed
necessities in the present day, were not available for a concerning number of households (GiveWell, n.d.).
During the Covid-19 pandemic, developing nations were hit the hardest as their already weak healthcare
systems were being overwhelmed by the increasing cases of infections (OECD, 2020) which means many
of the infected are not getting appropriate treatments for their disease. Pre-existing food and security
issues in developing nations have also been exacerbated because of the pandemic (OECD, 2020). From
the evidence provided, it is evident that the standard of living in many developing nations is at
concerningly low levels and needs to be addressed by policymakers.
Malaysia on the other hand, has managed to secure the position of 62 out of 191 countries in terms of
standard of living with an impressive HDI score of 0.803 which is high enough for the nation to be
classified under the “very high human development” category (Khalid, 2022) despite being a developing
nation. Within a generation, Malaysia has achieved great feats such as improving the nation’s standard of
living, reducing the poverty rate from 7.6 percent to 5.6 percent in 3 years, and transitioning into an
upper-middle-income nation from a low-income nation (UNSDG, 2021). During the Covid-19 pandemic,
the Malaysian government was able to implement effective policies to protect the vulnerable and offer
accessible healthcare that is on par with developed countries (UNSDG, 2021).
Therefore, this study aims to uncover the reasons behind Malaysia’s high standard of living despite being
a developing country. The results of this study may provide answers to the standard of living crises faced
by other fellow developing nations. This study done by (Hitam & Borhan, 2012) explored a similar topic
however the researchers focused on the deterioration in the environment due to FDI and GDP growth
rather than indicators of standard of living such as human development index (HDI) in Malaysia. Thus,
the main intention of this research will cover areas that are not covered in the study by looking into
factors that are affecting the standard of living in Malaysia and once the factors with strong correlation to
the standard of living in Malaysia are identified, policymakers in other developing nations can implement
effective policies by targeting the relevant variables that have contributed to Malaysia’s high standard of
living to improve the standard of living and reduce poverty rates in their nation.
1.4 Research Objective
RO1 : To determine the relationship between foreign direct investment and human development index in
Malaysia.
RO2 : To determine the relationship between inflation rate and human development index in Malaysia.
RO3 : To determine the relationship between exports of goods and services and human development index
in Malaysia.
RO4 : To determine the relationship between imports of goods and services and human development index
in Malaysia.
1.5 Research Questions
1. How does foreign direct investment affect human development index in Malaysia?
2. How does inflation affect human development index in Malaysia?
3. How does exports of goods and services affect human development index in Malaysia?
4. How does imports of goods and services affect human development index in Malaysia?
1.6 Scope of Study
The scope of this research aims to investigate the relationships between the independent variables which
are foreign direct investment, inflation, exports of goods and services, imports of goods and services, and
the dependent variable, standard of living within the period of 1990 to 2021. The reason for the selection
of this period is to investigate the long-term trends and changes in the standard of living in Malaysia over
time. The first ever HDI report was released in 1990 by UNDP thus the data used for this research will
begin from 1990 until the latest HDI report that was released in 2021. Over the years from 1990 to 2021,
Malaysia has experienced many structural changes in its economy. From 1986 to 1998, export-oriented
industrialization thrived in Malaysia due to the Plaza Accord of 1985 agreement that reduced Japan’s
competitiveness when it came to trade (Krinstitute, 2018). This made Malaysia an attractive spot for
overseas investment which has allowed industrial sectors such as electronics, chemical, and palm oil
products to flourish (Krinstitute, 2018). From 1998 to the current date, Malaysia has weathered many
economic crises such as the Asian and Global Financial Crisis and the Covid-19 pandemic (Krinstitute,
2018). The economy has also gone through deindustrialization by slowly shifting over to the services
sector (Krinstitute, 2018). Thus, the selected period will allow this study to understand the impacts these
economic events had on the nation and what are the variables that has helped Malaysia maintain its high
standard of living over the years.
1.7 Significance of Study
The intention of this study is to investigate the relationship between several economic indicators and the
standard of living in Malaysia. Despite being a developing nation, Malaysia has achieved a high standard
of living which is a rare phenomenon as many other developing nations are suffering from low standard of
living with many of its citizens living in extreme poverty. This research aims to use Malaysia’s success
story as an example to provide insights to other developing nations regarding the factors influencing the
standard of living in Malaysia. Once policymakers have identified and understood the areas that are directly
related to the standard of living in Malaysia, policymakers can focus on improving those areas to drive the
standard of living of their own nation. Another reason is targeting resources, when policymakers understand
which factors affect the standard of living the most they can target more of their resources towards that
certain factor. After policymakers have successfully raised the standard of living in their own nation, several
other macroeconomic goals will also be achieved such as economic growth as these goals are directly
related to each other.
1.8 Organisation of Thesis
This thesis will consist of 5 chapters. The first chapter will cover the research background, problem
statement, research objectives, research questions, scope of studies and significance of study. In Chapter 2,
the study will provide definitions, establish a theoretical framework, and construct hypotheses. Additionally,
a thorough literature review will be conducted to examine the dependent and independent variables. Chapter
3 will present the research design approach, including the selection of the population and sampling
technique, the method of data collection, and the chosen data analysis method. The outcomes of the data
analysis and empirical research will be displayed in Chapter 4. Finally, Chapter 5 will present the overall
research findings, discuss any study limitations, explore policy implications, and provide recommendations
for future research.
Chapter 2
2.0 Introduction
In this chapter, literature reviews will be done on the chosen theories relevant to the topic of standard of
living. This chapter will contain the definitions of the chosen independent variables and dependent variables,
relationships between the variables, literature reviews of past journal articles, and the research framework.
2.1 Theories
There are many theories related to standard of living however for this study, only three of those theories
have been selected. The theories selected for this research are the human capital theory, neoclassical growth
theory, and comparative advantage theory.
2.2 Human Capital Theory
The human capital theory states that investments in education, training, and healthcare can enhance an
individual's productivity and earning potential, ultimately leading to an improved standard of living (WSM,
n.d.). According to this theory, individuals with higher levels of human capital tend to have access to better
job opportunities, higher wages, and improved living conditions.
According to a study done by (Almendarez, 2013), it is stated that education is a fundamental piece in the
advancement of every society. High levels of education are necessary to promote economic growth and
development in an economy. It is also a proven fact that education helps citizens develop the core skills
needed for production activities thus creating the necessary human resources for the purpose of economic
and social transformation (Almendarez, 2013) which will then increase the standard of living in the society.
This study also looked at the human capital development in the Caribbean, the standard of living in the
Caribbean is very poor as 55 million people in the region are suffering from malnutrition and this is mainly
caused by the lack of emphasis placed on the education system (Almendarez, 2013). High unemployment
rates, high poverty rates, and low productivity in the labor force were the result of the low human capital
development in the region. The author also concluded that the lack of investment in the education system
in the in Caribbean has caused many social problems such as violence, crime and exploitation of young
women which are all detrimental to the standard of living in the society (Almendarez, 2013).
The standard of living is measured with the human development index, and in one of its measures of
dimensions is education. According to this research by (Almendarez, 2013), the researchers emphasize
education being an economic good as the human capital theory deems formal education as necessary in
order to increase productivity and boost economic growth within the economy. Another research
(Mengesha & Singh, 2022) has discovered that government expenditure on education, health and capital
education has shown a significant and positive relationship with improving the human development index
of a country. Countries that place heavy emphasis on the human capital theory by investing in areas such
as education also have higher standard of living as reflected in their high human development index scores
as compared to less developed countries (Akinyemi & Abiddin, 2013).
2.3 Comparative Advantage Theory
Comparative advantage is an economic principle that refers to the ability of a country, individual, or
entity to produce goods or services at a lower opportunity cost compared to others (CFI, 2019). It is a
concept developed by economist David Ricardo in the early 19th century and is based on the theory of
international trade (CFI, 2019). According to this theory, countries should focus on producing goods and
services in which they have a comparative advantage and trade with other nations. Through trade,
countries can access a wider range of goods and increase overall consumption, leading to an improved
standard of living.
The author (Schumacher, 2013) discussed the theory of comparative advantage and how it encouraged
international trade in the eyes of many economists. In this study, it is stated that international trade is one
of the biggest blessings in the world of economics and the very theory that gave life to the whole concept
was the comparative advantage theory as nations started trading goods and services, they have a
comparative advantage in with each other, so everyone benefits without having to specialize in areas that
will carry high levels of opportunity costs (Schumacher, 2013). The theory of comparative advantage
emphasizes the importance for developing nations to engage in international trade as many of them possess
comparative advantages in sectors such as agriculture which will help the nations maximize economic
welfare and ultimately translate into a higher standard of living.
Another study by (Kabadayi, 2013) discussed how comparative advantage can open opportunities for
developing countries to increase human development in their country and raise standard of living. By
specializing in areas that they possess a comparative advantage in they can experience economies of scale
(Kabadayi, 2013) which will decrease the cost of their exports thus making them much more competitive
in the global economy. This will increase exports in the nation and fuel economic growth. As for countries
with limited resources, they might have comparative advantages in other sectors such as human resources,
technology, or services (Nainggolan et al., 2021). For these countries, their main aim could be to develop
human resources further in their country (Nainggolan et al., 2021) and export their services to other
countries.
2.4 Neoclassical Growth Theory
The neoclassical growth theory otherwise known as the neoclassical growth model is an economic theory
that seeks to explain long-run economic growth with three economic variables which are labour, capital and
technology (CFI, 2022). Solow-Swan Growth Model is the most widely adopted version of this theory (CFI,
2022). The theory suggests that increasing the level of capital per worker will lead to higher levels of output
and productivity, which can improve the standard of living in an economy.
According to this study (Prescott, 1988), the neoclassical growth theory was first introduced in 1957 when
Robert Solow used this theory to evaluate the growth in the U.S. economy. From his findings, technological
advancement in the nation accounted for four-fifth of the growth in output per worker and another one-fifth
of the growth in output per worker was caused by an increase in the tangible capital per worker (Prescott,
1988). Thus, to sustain long-term economic growth to improve the standard of living, policymakers should
focus on policies to promote technological advancement and increase the number of capital in the economy.
Another study by (Hussain et al., 2010) further supports the claims of the neoclassical growth theory that
capital accumulation results in higher levels of human development in the economy. According to the study,
exports play a huge role in the economic growth of a nation, and investing in technological development
and accumulating more capital, can lead to lower cost of production (Hussain et al., 2010) which will
increase efficiency in the manufacturing processes and may result in higher levels of exports in the country.
2.5 Definition of Variables
2.5.1 Human Development Index
Human Development Index (HDI) is an indicator used to measure the key achievements in human
development (UNDP, n.d). These dimensions are life expectancy, quality of education and decent
standard of living (UNDP, n.d). The concept of the standard of living is distinct from other indicators of
quality of life (Amadeo, 2022). While quality of life encompasses intangible aspects like relationships,
freedom, and satisfaction, measures attempting to assess the overall quality of life also consider the
material standard of living (Amadeo, 2022). The standard of living specifically centres on the evaluation
of the value of goods and services produced and consumed, adopting a narrower perspective.
2.5.2 Foreign Direct Investment
Foreign Direct Investment (FDI) refers to the investment made by an individual, company, or entity from
one country into business interests located in another country. It involves the direct ownership or control of
assets, such as the establishment of subsidiaries, branches, or the acquisition of shares in a foreign company
(Duce and España, 2003).
2.5.3 Inflation
Inflation refers to an increase in prices that leads to a decrease in the value of money over time (Oner, 2010).
This decline in purchasing power is typically measured by observing the average price increase of a specific
set of goods and services during a given period (Oner, 2010). The percentage increase in prices signifies
that the same amount of currency can buy fewer goods and services compared to previous periods. It is
important to note that inflation stands in contrast to deflation, where prices decrease, resulting in an increase
in purchasing power.
2.5.4 Export of Goods and Services
Exports of goods and services refer to the sale or transfer of domestically produced goods, services, and
intangible assets from one country to another (He and Zhang, 2010). It represents the economic value of
products and services that are sent out of a country's borders to be consumed or used by individuals,
businesses, or governments in foreign nations (He and Zhang, 2010). Exports play a vital role in a country's
economy as they contribute to economic growth, job creation, and the generation of foreign exchange.
When a country exports goods and services, it earns revenue from abroad, which can be used to pay for
imports, invest in domestic industries, or strengthen the national currency.
2.5.5 Imports of Goods and Services
Imports of goods and services refer to the total value of goods and services that was received from overseas,
in other words, it refers to inflow of goods and services into the domestic economy from foreign businesses,
individuals or governments (World Bank, n.d).
2.6 Literature Review of Variables
2.6.1 Foreign Direct Investment
In a research by (Agusty & Damayanti, 2015), the relationship between foreign direct investment and
human development index which is the indicator for standard of living was explored. According to the
researchers, due to the lack of capital in developing countries, they will usually require assistance from
other countries in the form of foreign direct investment. The researchers have found a strong positive
correlation between foreign direct investment and human development index (Agusty & Damayanti, 2015)
which means that capital inflow from overseas will encourage human welfare and development as
investments from overseas will create new jobs in the economy. New jobs will help increase the income of
the households thus increasing their spending power which will result in a higher standard of living.
Another study by (Tamer, 2013), also looked at the relationship between foreign direct investment and
human development index but this time in Africa. In Africa, foreign direct investment is one of the largest
foreign funds used to fuel development in many African countries. This study has looked at the effects of
foreign direct investment on human development index in low-income, lower-middle, upper-middle, and
high-income African countries. This study has discovered that there is a strong positive correlation between
FDI and HDI in the lower-middle, upper-middle, and high-income African countries whereas in low-income
countries, the relationship between FDI and HDI remains ambiguous (Tamer, 2013) thus, to encourage
development, FDI is crucial to drive development in African countries except for low-income African
countries.
In this study by (Thi Hong Vinh et al., 2017), the researchers state that foreign direct investment plays a
significant role when it comes to improving the economic performance and social development of a country
however, it can also cause income inequality amongst the citizens as most of the time the rich are the ones
who benefit from foreign direct investment. The outcome of the research has concluded that foreign direct
investment did increase income inequality in Asian countries, however, it has also reduced inequality in
education (Thi Hong Vinh et al., 2017). In terms of higher institutional quality, it has improved human
development and political situations. According to another study by (Lehnert et al., 2013), similar results
have been achieved as the research have also discovered a positive relationship between foreign direct
investment and welfare development in over 175 countries.
Hypothesis Formed:
H1: There is a positive relationship between foreign direct investment and human development index
2.6.2 Inflation Rate
In this study by (Cahyanti & Fevriera, 2020), the relationship between inflation and HDI in Central Java is
investigated. Central Java is a province in Indonesia with a high HDI which prompted this study to
investigate factors contributing to the high HDI. This study uses the least square dummy variable model to
uncover the different constants in each regency and city in Central Java. The hypotheses of this study state
that inflation has a positive correlation with HDI in Central Java and indeed the hypotheses were proven to
be true (Cahyanti & Fevriera, 2020). The research has concluded that inflation has a positive relationship
with HDI in all the Central Java cities as an increase in inflation could increase productivity in the economy
by making households work harder to meet the increasing price levels in commodities which will increase
their purchasing power thus leading to higher standard of living (Cahyanti & Fevriera, 2020).
However, another study explored the relationship between inflation and HDI in Nigeria as the nation is
suffering from a low standard of living with over 91 million Nigerians living in extreme poverty (Peter et
al., 2022). The researchers stated that a high inflation rate is often a common theme in developing countries
whereas developed nations often have a low inflation rate. This causes a low standard of living in
developing nations while developed nations enjoy a higher standard of living. From the findings of the
research, it is revealed that inflation and standard of living have a strong negative correlation with each
other (Peter et al., 2022). The coefficient of inflation has a value of -0.034 whilst the P-value is at 0.017. In
other words, an increase in inflation by 1 unit causes the standard of living to fall by 0.034 in Nigeria (Peter
et al., 2022).
Hypothesis Formed:
H1: There is a negative relationship between the inflation rate and human development index
2.6.3 Exports of Goods and Services
The relationship between exports of goods and services and HDI in Indonesia was investigated in this study
by (Sari, 2022). In this study, exports along with two other variables were measured using the Regional
GDP (RGDP) as the indicator. The RGDP is then tested as an independent variable of HDI using the
secondary panel data of 34 Indonesian provinces with the Fixed Effect Model estimation technique. The
export of non-oil and gas exports were used to measure the exports from the selected provinces. Exports
along with the other two variables have been revealed to have positive correlations with RGDP per capita
and thus exports are indirectly positively correlated with HDI using RGDP per capita as the intervening
variable (Sari, 2022).
In 2016, another study done by (Hamdan, 2016), used the Eviews panel data approach to evaluate the effects
of exports on economic growth which is indirectly related to the standard of living in 17 Arab countries.
The researchers stated that exports play a vital part in the economic growth of a nation as it is an important
source of foreign income and higher levels of exports also create more employment opportunities in the
local economy. By engaging in international trade, there is a higher incentive for technological development
and greater utilization of capital to increase the competitiveness of the exported goods and services which
will all contribute to economic growth in a nation. The result of the research has concluded that exports
along with several other variables have a positive correlation with the economic growth in Arab countries
(Hamdan, 2016) and thus policymakers in Arab countries should focus on industrialization to increase the
levels of exports in their nation. An increase in economic growth will lead to a higher standard of living as
households will have more disposable income to spend on goods and services in the economy.
Hypothesis Formed:
H1: There is a positive relationship between exports of goods and services and human development index
2.6.4 Imports of Goods and Services
Import vulnerability is a topic that is explored in this study by (Veninga & Ihle, 2018). Wheat is a staple
ingredient in the Egyptian diet, and it is heavily subsidized by the Egyptian government. The local demand
for wheat in Egypt is extremely high since it is heavily subsidized by the government. The availability of
this ingredient has made this ingredient a necessity good in the nation and this increases their dependency
on imported wheat from other nations. Egypt’s dependency on wheat import has made them vulnerable to
price increments or supply challenges that may disrupt the inflow of imported wheat and threaten the
nation’s food security. The research has shown a strong negative correlation between imported wheat and
the standard of living in Egypt (Veninga & Ihle, 2018). Due to the nation’s dependency on imported wheat,
Egypt faces severe food insecurity and in 2013, Egypt’s HDI has fallen from 0.682 to 0.518 as many
Egyptians did not have access to basic necessities such as wheat (Veninga & Ihle, 2018).
According to a piece of recent news in Malaysia, the nation is facing a standard of living crisis as the rate
of import continues to rise (Yunus, 2022). Due to Malaysia’s dependency on imported goods, the cost of
living has increased significantly as the Malaysian Ringgit weakens against the United States Dollar which
has increased the costs of imported essential items (Yunus, 2022). The Ukraine-Russia war has also
contributed to the imported inflationary heat as the costs of chicken feed have gone up due to the war (Yunus,
2022) which has translated into higher prices for chicken meats. With the hike in price, many might not be
able to afford chicken which is considered to be a staple in the Malaysian diet thus affecting the standard
of living in the country.
Hypothesis Formed:
H1: There is a negative relationship between imports of goods and services and human development index
2.6.5 Research Framework
Fig 1 Research Framework
Chapter 3
3.0 Introduction
This chapter will contain the research approach, population and sampling technique, hypotheses of the study,
data collection, and data analysis of the study. The utilized in this research is going to be extracted from
world bank data. The software used to run the regression model in this study will be EViews.
3.1 Research Approach
This research will adopt a quantitative approach to collect and analyze numerical data and ultimately
understand the patterns, relationships, and trends between the variables. The reason for the selection of the
quantitative approach is due to the nature of the variables. Data for variables like FDI, inflation, exports of
goods and services and imports of goods and services must be extracted from a reliable database such as
world bank in order to reflect a truthful representation of the data. A large sample size will be used in this
research thus the quantitative approach will help to generalize the findings and allow statistical techniques
to be used to analyze data, uncover patterns, and test hypotheses. Statistical analysis allows for the
identification of relationships, trends, and correlations between variables, providing a deeper understanding
of the research topic. Thus, this research will also adopt the positivism concept while focusing on
objectivity to reduce the possibilities of biases by focusing on numerical data rather than subjective
interpretations.
3.2 Population and Sampling Technique
The human development index is a measurement of human development across countries, allowing for
comparisons and rankings based on various dimensions such as health, education, and income (Roser, 2014).
This means the sample population for the HDI consists of countries from different regions, income levels,
and development stages. However, in this study, only the human development index report of Malaysia has
been selected. Therefore, the target population for this research is the citizens from all income levels,
development stages, and regions of Malaysia as the standard of living in Malaysia applies to all the citizens
residing within the country.
The sampling technique adopted in this research is purposive sampling which is a sampling technique that
allows the researcher to select participants who possess specific characteristics or expertise relevant to the
research objectives (BRM, n.d). This technique is commonly used in qualitative research or when
researchers want to focus on specific traits or attributes. In the case of this research, every Malaysian citizen
is purposefully selected as the sample population as the aim of this research is to investigate the standard
of living in Malaysia which is relevant to every Malaysian.
3.3 Hypothesis
Below are the constructed hypothesis tests:
H0: The relationship between foreign direct investment and human development index in Malaysia is not
significant.
H1: The relationship between foreign direct investment and human development index in Malaysia is
significant.
H0: The relationship between inflation rate and human development index in Malaysia is not significant.
H1: The relationship between inflation rate and human development index in Malaysia is significant.
H0: The relationship between exports of goods and services and human development index in Malaysia is
not significant.
H1: The relationship between exports of goods and services and human development index in Malaysia is
significant.
H0: The relationship between imports of goods and services and human development index in Malaysia is
not significant.
H1: The relationship between imports of goods and services and human development index in Malaysia is
significant.
3.4 Data Collection
Data for foreign direct investment, inflation rate, exports of goods and services, and imports of goods and
services in Malaysia will be extracted from world bank data from the period of 1990 to 2021 with a total
sample size of 32 observations. Data for standard of living will be taken from the human development index
report released by the United Nations Development Programme on their website and similarly to the other
variables, there will be 32 observations. Once the data has been collected, the software called EViews will
be used to run the regression model, test the hypothesis, and reveal the relationship between the independent
and dependent variables.
3.5 Formulation of Variables
Table 1.1 Formulation of Variables
Variable
Description
HDI
Human
Index
Unit of Measure
Development HDI
(Standard
of
Source
UNDP
Human
Development Reports
Living)
FDI
Foreign
Direct % of GDP
World Bank Data
Investment
INFLATION
Inflation Rate
Annual % change in World Bank Data
average cost of living
EXPORT
Exports of Goods and % of GDP
World Bank Data
Services
IMPORT
Imports of Goods and % of GDP
World Bank Data
Services
3.6 Data Analysis
The regression analysis technique employed in this study is Ordinary Least Square (OLS), OLS is one of
the commonly used techniques in multiple regression to calculate the coefficients of the independent
variables and determine the relationship between the independent and dependent variables (Gulve, 2020).
The OLS method aims to minimize the sum of squared residuals, which involves calculating the squared
distance between each data point and the regression line derived from the given data (Gulve, 2020). These
squared errors are then summed together to provide an overall measure of the deviation from the regression
line (Gulve, 2020). After the output of the regression model has been obtained from EViews using the
ordinary least square method, several tests such as heteroskedasticity test, serial correlation test and
normality test will be performed using EViews to assess the quality of the regression model. This study will
also analyse the descriptive statistics, correlation test, and quality of regression model using the R-Square
value. The results of the regression model will also be interpreted together with the coefficients of the
independent variable to reveal the relationship between the independent and dependent variables and to test
the constructed hypothesis of the research.
3.6.1 Descriptive Analysis
Descriptive statistics in research refers to the analysis and summary of data using various statistical
measures and techniques to provide a clear and concise description of the data (Trochim, n.d). It involves
organizing, summarizing, and presenting data in a meaningful way to gain insights and understand patterns
or characteristics of the dataset. Descriptive statistics are used to describe and summarize the main features
of the data, such as central tendency, variability, distribution, and relationships between variables (Bhandari,
2023). These statistics help researchers and analysts to explore and understand the data, identify trends,
detect outliers, and communicate key findings effectively.
3.6.2 Correlation Analysis
According to (Lindley, 1990), correlation is used as a tool to identify and evaluate the relationship between
two variables. In a regression model, one model must be dependent on the other variable thus there will be
a dependent variable and an independent variable in a regression model. In correlation analysis, a coefficient
value of 0 indicates that there is no relationship between the variables (Lindley, 1990). Typically, when the
coefficient value is below 0.6, the correlation between the independent variable and dependent variable is
generally regarded as weak. On the other hand, if the coefficient value exceeds 0.6, the correlation is
commonly considered strong. (BMJ, 2020)
3.6.3 Diagnostic Test
3.6.3.1 Heteroskedasticity Test
Heteroskedasticity refers to a situation where the residuals of the regression are scattered unequally causing
the variance of the residual to be unequal (CFI, 2023). In a regression analysis, the idea of homoskedasticity
which refers to a constant variance of the error terms is normally assumed as part of the 7 classical
assumptions of ordinary least squares (Indeed, 2022). Detecting heteroskedasticity can be done by
examining residual plots or conducting formal statistical tests, such as the White test or the Breusch-Pagan
test. If heteroskedasticity is detected, the validity and reliability of the results could be questioned.
3.6.3.2 Serial Correlation Test
One of the basic assumptions of ordinary least squares is that the error terms are independent of each other
and when this assumption is broken, serial correlation occurs (Durbin & Watson, 1992). Serial correlation
refers to the correlation or relationship between consecutive or lagged observations within a time series
data (CFI, 2023). To detect serial correlation, several methods such as the Durbin-Watson test and BreuschGodfrey test can be used. If serial correlation were to be detected, then there might be biased parameters
estimates which will lead to inaccurate results and invalid hypothesis tests.
3.6.3.3 Normality Test
The normality test refers to a test that determines whether the drawn sample of data is from a normally
distributed population (OriginLab, n.d). According to this study by (Rani Das, 2016), in all the commonly
used statistical methods, it is assumed that the data are drawn from a normally distributed population. This
includes statistical methods such as linear and when the data deviates from normality, the reliability of the
results will be impacted as it goes against the assumption that data are collected from a normally distributed
population.
3.7 Regression Analysis
Expected Multiple Regression Model:
HDIt= β0 + β1(FDIt) - β2(INFLATIONt)+β3(EXPORTt) + β4(IMPORTt) + 𝜺t
Where:
HDI = Human Development Index
β0 = Intercept
β0, β1, β2, β3, β4 = Coefficient or slope value
FDI = Foreign Direct Investment
INFLATION = Inflation rate
EXPORT = Exports of goods and services
IMPORT = Imports of goods and services
𝜀t = Error term
Linear regression analysis refers to a technique that is used to determine the relationship between an
independent variable and the dependent variables whereas multiple regression refers to a technique that
determines the relationship between multiple independent variables and one dependent variable (Indeed,
2022) which is the method employed in this research. With reference to the literature review in Chapter 2,
the expected signs that have been developed for foreign direct investment is a positive sign as foreign direct
investment can improve economic growth which will lead to higher standard of living. The expected sign
for inflation rate is negative as an increase in inflation rate will increase the cost of living thus making it
harder for many households to afford basic necessities which will be detrimental to the standard of living.
The expected sign for exports of goods and services is positive as higher levels of exports promote
productivity in the economy which will lead to higher income and a higher standard of living. Lastly, the
expected sign for imports of goods and services is negative as higher levels of imports could mean a
dependency on imported goods and services which means the standard of living in a country could be
threatened if inflow of imported necessities is disrupted.
Chapter 4
4.1 Eviews Results (Multiple Regression Model)
Fig 2 Multiple Regression Model
Dependent Variable: HDI
Method: Least Squares
Date: 06/26/23 Time: 22:24
Sample: 1990 2021
Included observations: 32
Variable
Coefficient
Std. Error
t-Statistic
Prob.
FDI
INFLATION
EXPORT
IMPORT
C
5.04E-12
-0.011418
0.002357
-0.004060
0.842249
1.32E-12
0.003366
0.000528
0.000809
0.037318
3.806171
-3.391728
4.460579
-5.018441
22.56934
0.0007
0.0022
0.0001
0.0000
0.0000
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.821602
0.795173
0.023804
0.015299
76.92529
31.08681
0.000000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
0.739219
0.052596
-4.495331
-4.266310
-4.419417
0.969007
Estimated Human Development Index Model:
Human Development Index = 0.842249 + 5.04E-12FDIt – 0.011418INFLATIONt +
0.002357EXPORTt – 0.004060IMPORTt + 𝜺t
The typical significance level value for a hypothesis test is 0.1, 0.05 and 0.01 (Yale, n.d). If the P-value is
less than the significance level then that means the hypothesis test is statistically significant. The P-value
for FDI, Inflation, exports of goods and services, and imports of goods and services are 0.0007, 0.0022,
0.0001, and 0.0000 respectively. The P-value of these variables should be compared against the
significance level of 0.01 as they are closest to the value. All of four of the independent variables are
significant at 1% significance level as all of their P-value are lesser than 0.01. Thus, we reject the null
hypothesis and the relationship between all of the four independent variables and the dependent variable
is significant.
4.1.1 Quality Evaluation of Regression Equation
R-Squared is an indicator that indicates the proportion of the variance in a dependent variable that is
explained by the independent variables in the regression model (Taylor, 2020). R-Squared measures how
well-suited the data are for the regression model (Taylor, 2020). An R-Squared value that is close to 1
means more of the variation in the dependent variable is explained by the independent variables (JMP,
n.d). Thus, R-squared can be used as an evaluation tool to evaluate the performance of the regression
model.
On the other hand, adjusted R-Squared another indicator used to assess the quality of the regression
model can be utilised to show whether the quality of the regression model has improved or not when an
additional variable is added (CFI, 2020), unlike R-Squared which fails to do so.
From the Eviews results above, it is revealed that the R-Squared and adjusted R-Squared values are
0.821602 and 0.795173 respectively. The R-Squared value of 0.821602 indicates that 82.1602% of the
variation in the dependent variable is explained by the independent variables which are foreign direct
investments, inflation rate, exports of goods and services and imports of goods and services, with the
remainder 17.8398% being explained by other variables. The high R-Squared value indicates that the
independent variables are a good fit for the regression model.
4.2 Descriptive Statistics
Fig 3 Descriptive Statistics
Date: 06/26/23 Time: 22:44
Sample: 1990 2021
HDI
FDI
INFLATION
EXPORT
IMPORT
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
0.739219
0.735500
0.810000
0.640000
0.052596
-0.273722
1.917255
6.70E+09
5.11E+09
1.86E+10
1.15E+08
4.25E+09
0.838021
3.372346
2.537144
2.547452
5.440782
-1.138702
1.441785
-0.073806
3.075901
89.58671
88.04054
121.3114
61.59922
18.50944
0.240666
1.689989
78.57259
78.09446
100.5971
55.22934
13.93999
-0.070038
1.562499
Jarque-Bera
Probability
1.962707
0.374803
3.930343
0.140132
0.036733
0.981801
2.597077
0.272930
2.781374
0.248904
Sum
23.65500
2.14E+11
81.18862
2866.775
2514.323
4.2.1 Mean
As shown by the descriptive data from 1990 to 2021, the average human development index in Malaysia
was at 0.74 while the independent variables, foreign direct investment averaged at 6.7 billion USD,
inflation rate on average is 2.54%, average exports of goods and services is 89.59% of the Gross
Domestic Product (GDP) and imports of goods and services on average is at 78.57% of the GDP.
4.2.2 Median
In terms of median, 50% of the human development index in Malaysia is either higher than or lower than
0.74. As for the independent variable, 50% of the foreign direct investment is either higher than or lower
than 5.11 billion USD, 50% of the Inflation rate is either higher than or lower than 2.55%, 50% of the
exports of goods and services is either higher or lower than 88.04% of the GDP and 50% of the imports of
goods and services is either higher or lower than 78.09% of the GDP.
4.2.3 Maximum and Minimum
Throughout the period of 1990 to 2021, the highest-recorded human development index is 0.81 while the
lowest ever recorded is 0.64. In terms of independent variables, the highest-recorded foreign direct
investment is 18.6 billion USD while the lowest ever recorded is 115 million USD, the highest-recorded
inflation rate is 5.44% while the lowest-recorded inflation rate is -1.14%, the highest-recorded exports of
goods and services is 121.31% of the GDP while the lowest-recorded is 61.60% of the GDP, the highestrecorded imports of goods and services is 100.60% of the GDP while the lowest-recorded imports of
goods and services is 55.23% of the GDP.
4.2.4 Skewness and Kurtosis
Skewness assesses the degree of how symmetrical the distribution of the variable is. The general
guideline used to assess the skewness of a data distribution is a range from -1 to +1 which is considered to
be the best range (SmartPLS. n.d.). The skewness indicated by the table above range from -0.274 to
+0.838 which is the most desirable range according to the guideline.
Kurtosis on the other hand measures how peaked the data distribution is. If the kurtosis value is more than
+2 then the data distribution is too peaked whereas if the data is less than -2 then the data distribution is
too flat (SmartPLS. n.d.). Human development index, exports of goods and services, and imports of goods
and services has a kurtosis value of 1.917, 1.690, and 1.562 respectively which is lesser than +2 meaning
they are still within the normal range. Foreign direct investment and inflation on the other hand have a
kurtosis value of 3.372 and 3.076 respectively which means their data distribution is outside the normal
range and is too peaked.
4.3 Heteroskedasticity Test
Fig 4 Heteroskedasticity results
Heteroskedasticity Test: Breusch-Pagan-Godfrey
Null hypothesis: Homoskedasticity
F-statistic
Obs*R-squared
Scaled explained SS
2.120431
7.649437
8.660973
Prob. F(4,27)
Prob. Chi-Square(4)
Prob. Chi-Square(4)
0.1058
0.1053
0.0702
Test Equation:
Dependent Variable: RESID^2
Method: Least Squares
Date: 06/27/23 Time: 00:05
Sample: 1990 2021
Included observations: 32
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
FDI
INFLATION
EXPORT
IMPORT
0.002791
-7.06E-14
0.000205
-1.87E-05
-8.75E-06
0.001269
4.50E-14
0.000115
1.80E-05
2.75E-05
2.198379
-1.568998
1.793819
-1.038972
-0.317918
0.0367
0.1283
0.0840
0.3080
0.7530
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.239045
0.126311
0.000810
1.77E-05
185.1133
2.120431
0.105777
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
0.000478
0.000866
-11.25708
-11.02806
-11.18117
1.808988
The Breusch-Pagan-Godfrey test was selected to test for heteroskedasticity in the regression model. A
general rule of thumb is that if the observed Chi-Square value is more than the significance level of 5%,
then heteroskedasticity does not exist or in other words, homoskedasticity exists. The observed ChiSquare value in the table above is 0.1053 which is more than 0.05 or the significance level of 5% thus,
heteroskedasticity does not exist.
4.4 Serial Correlation Test
Fig 5 Serial correlation results
Breusch-Godfrey Serial Correlation LM Test:
Null hypothesis: No serial correlation at up to 2 lags
F-statistic
Obs*R-squared
2.582159
5.478598
Prob. F(2,25)
Prob. Chi-Square(2)
0.0956
0.0646
Test Equation:
Dependent Variable: RESID
Method: Least Squares
Date: 06/27/23 Time: 00:41
Sample: 1990 2021
Included observations: 32
Presample missing value lagged residuals set to zero.
Variable
Coefficient
Std. Error
t-Statistic
Prob.
FDI
INFLATION
EXPORT
IMPORT
C
RESID(-1)
RESID(-2)
-1.68E-13
0.002519
-0.000207
0.000274
-0.008529
0.413898
0.109917
1.28E-12
0.003420
0.000511
0.000775
0.035666
0.208410
0.212737
-0.131038
0.736631
-0.404675
0.353682
-0.239148
1.985978
0.516679
0.8968
0.4682
0.6892
0.7265
0.8129
0.0581
0.6099
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.171206
-0.027704
0.022521
0.012680
79.92983
0.860720
0.536778
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
-1.05E-16
0.022215
-4.558115
-4.237485
-4.451835
1.586951
The Breusch-Godfrey serial correlation LM Test is employed to test for serial correlation otherwise
known as autocorrelation in the regression model. If the probability of Chi-Square is more than the
significance level of 5% then serial correlation does not exist. From the test results above, it is observed
that the probability of Chi-Square in this regression model is 0.0646 which is higher than 0.05 or the
significance level of 5%, hence serial correlation does not exist in this regression model and the variables
are independent from each other.
4.5 Normality Test
Fig 6 Normality Results
12
Series: Residuals
Sample 1990 2021
Observations 32
10
8
6
4
2
0
-0.06
-0.04
-0.02
0.00
0.02
0.04
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
-1.05e-16
0.003367
0.051080
-0.065619
0.022215
-0.591365
4.180824
Jarque-Bera
Probability
3.724257
0.155342
0.06
Using the normality test we are able to test whether the data in the regression model is normally
distributed or not. The general guideline to test whether the data is normally distributed is to gauge
the probability, if the probability exceeds 5% then the data in the regression model is normally
distributed (Feldman, 2018). The probability in this regression model is at 15.53% which exceeds 5%,
meaning the data in this regression model is normally distributed.
4.6 Conclusion
To conclude this chapter, data used for the regression output was extracted from World Bank Data from
the year 1990 to 2021. After running several tests, this regression model proven to be free of serial
correlation, heteroskedasticity, and the data are normally distributed. This aligns with the basic
assumptions of the Ordinary Least Squared method as errors are independent from each other,
uncorrelated, normally distributed and a linear relationship exists between the dependent and independent
variable (Malik, 2018). Having met all these assumptions, this regression model is considered to be a
suitable model.
5.1 Interpretation of Regression Output Results
5.1.1 Intercept Value
β0 = -0.842249
The intercept value of this regression model is -0.842249 which indicates that when all the independent
variables which are foreign direct investment, inflation rate, exports of goods and services and imports of
goods and services were to be zero, the human development index in Malaysia will be -0.842249 units.
5.1.2 Relationship Between Foreign Direct Investment and Human Development Index
β1(FDIt) = 5.04E-12FDIt
The slope value of 5.04E-12 indicates that if foreign direct investment (FDI) were to increase by 1 unit,
human development index (HDI) in Malaysia will increase by 5.04E-12 units holding other variables
constant. The p-value of 0.0007 indicates that FDI is significant at 1% significance level which means the
relationship between FDI and HDI is significant. In general, the correlation between the independent
variable and dependent variable is considered to be weak if the coefficient value is lesser than 0.6 and strong
when the coefficient value is higher than 0.6 (BMJ, 2020). The coefficient value of 5.04E-12 indicates a
positive weak correlation between FDI and HDI in Malaysia. This relationship between foreign direct
investment and human development index can be further supported by this study by (Almozaini, n.d). In
this study, the researcher claims that many countries can experience improvements to their human
development index from inflows of foreign direct investment through channels such as economic growth
which will increase employment opportunities in the economy, which further supports the positive
relationship between HDI and FDI.
H1: The relationship between Foreign Direct Investment and Human Development Index in Malaysia is
significant
5.1.3 Relationship Between Inflation Rate and Human Development Index
β2(INFLATIONt) = –0.011418INFLATIONt
The slope value of -0.011418 indicates that if inflation rate were to increase by 1 unit, human development
index will decrease by 0.011418 units holding other variables constant. The p-value of 0.0022 indicates that
inflation rate is significant at 1% significance level, meaning the relationship between inflation rate and
human development index is significant. The coefficient value of -0.011418 also indicates that there is a
weak negative correlation between inflation rate and human development index in Malaysia. This result
makes sense as an increase in inflation rate means a higher cost of living and with a higher cost of living,
purchasing powers of households will decrease (Hicks, 2023). For lower-income households, this may
prevent them from buying basic necessities such as food (Hicks, 2023) which will ultimately result in a
lower standard of living in the economy.
H1: The relationship between Inflation Rate and Human Development Index in Malaysia is significant
5.1.4 Relationship between Exports of Goods and Services and Human Development Index
β2(EXPORTt) = 0.002357EXPORTt
The slope value of 0.002357 indicates that if exports of goods and services were to increase by 1 unit,
human development index will increase by 0.002357 units holding other variables constant. The p-value of
0.0001 indicates that exports of goods and services are significant at 1% significance level, meaning the
relationship between exports of goods and services and human development index is significant. The
coefficient value of 0.002357 also indicates that there is a weak positive correlation between exports of
goods and services and human development index in Malaysia. According to an article, developing
countries benefits from growing their economy by increasing their levels of exports (Ungerer et al., 2022).
Exporting goods and services allows the economy to become more productive which will result in higher
GDP per capita (Ungerer et al., 2022) and ultimately increases the standard of living as the households in
the economy get richer and are able to afford a higher quality of life.
H1: The relationship between Exports of Goods and Services and Human Development Index in Malaysia
is significant
5.1.5 Relationship between Imports of Goods and Services and Human Development Index
β4(IMPORTt) = –0.004060IMPORTt
The slope value of -0.004060 indicates that if imports of goods and services were to increase by 1 unit,
human development index will decrease by 0.004060 units holding other variables constant. The p-value
of 0.0000 indicates that imports of goods and services are significant at 1% significance level, meaning the
relationship between imports of goods and services and human development index is significant. The
coefficient value of -0.004060 also indicates that there is a weak negative correlation between imports of
goods and services and human development index in Malaysia. The results imply that dependency on
imported goods and services could be detrimental to the standard of living in the economy as relying on
imported basic necessities such as food could threaten the food security of the country if the inflow of
imported goods is disrupted similar to what Egypt faced when the nation experienced food insecurity when
their inflow of imported wheat got disrupted (Veninga & Ihle, 2018).
H1: The relationship between Imports of Goods and Services and Human Development Index in Malaysia
is significant.
Table 2 Hypothesis Results
Hypothesis Developed
Results
H0: The relationship between Foreign Direct Rejected
Investment and Human Development Index in
Malaysia is not significant.
H1: The relationship between Foreign Direct Accepted
Investment and Human Development Index in
Malaysia is significant.
H0: The relationship between Inflation Rate and Rejected
Human Development Index in Malaysia is not
significant.
H1: The relationship between Inflation Rate and Accepted
Human Development Index in Malaysia is
significant.
H0: The relationship between Exports of Goods Rejected
and Services and Human Development Index in
Malaysia is not significant.
H1: The relationship between Exports of Goods Accepted
and Services and Human Development Index in
Malaysia is significant.
H0: The relationship between Imports of Goods Rejected
and Services and Human Development Index in
Malaysia is not significant.
H1: The relationship between Imports of Goods Accepted
and Services and Human Development Index in
Malaysia is significant.
5.2 Recommendations Based on Results
From the results produced in Chapter 4, the relationships between the independent variables and the
dependent variable have become clearer. It is evident that the relationship between all the independent
variables which are foreign direct investment, inflation rate, exports of goods and services, imports of goods
and services, and the dependent variable, human development index is significant. In other words, there
exists a relationship between all the independent variables and human development index in Malaysia.
Now that four of the variables behind Malaysia’s high standard of living have been revealed, policymakers
from other developing nations can divert more of their attention toward these four variables in their future
policies. Firstly, policymakers can encourage more inflow of foreign direct investment into their country
by offering financial incentives such as tax deductions, cheaper insurance, or even lower interest rates for
loans to foreign investors (Mariadoss, n.d) which will increase their competitiveness as a host country for
foreign investments as compared to other countries. Diverting more funds towards the investment of
infrastructures such as highways, efficient energy sources, and other transportation channels can also attract
more foreign direct investments (Mariadoss, n.d) as these infrastructures will aid in cost reductions in many
of the processes of a company. As foreign direct investment is crucial to fuel economic development and
improve standard of living in developing countries as mentioned in the literature review.
Secondly, policymakers in developing nations should investigate policies to control the inflation rates in
their local economy. From this research, it has been revealed that high inflation rates can be detrimental to
the standard of living in the economy thus if the inflation rate in the economy ever goes past the threshold,
the policymakers can deploy contractionary fiscal policies such as a tax hike which will help control the
domestic demands in the local economy (Dubey, 2022) and reduce the inflationary gap caused by
overwhelming domestic demand. In terms of contractionary monetary policy, policymakers can also
decrease the money supply in the economy which will then cause demand for goods and services to reduce
thus resulting in price level reductions (Dubey, 2022).
Thirdly, it has been discussed above that exports of goods and services are crucial for developing nations
to expand their economy and raise the standard of living. According to a study, policymakers should first
identify which goods or services their country are specializing in and once these goods or services have
been identified, invest in programs to help domestic firms to engage in research and development for their
products which gives them a competitive edge in the global economy (Katz & Istrate, 2011). These
programs can be carried out in the form of grants, any domestic company that are interested in expanding
their export capacity by training programs, marketing strategies or any other related strategies should be
eligible for a state grant by the government to encourage higher levels of exports like what the Washington
state carried out in 2010 (Katz & Istrate, 2011).
Lastly, dependency on imports could cause crises such as food insecurity as discussed in the literature
review. Policymakers could reduce dependency on imports by subsidizing domestic businesses which will
reduce the prices of goods and services (CFI, 2019) thus increasing the demand for domestic products and
also helping domestic businesses to grow so they can compete with foreign competitors. Another method
is to impose tariffs on imported goods and services so they are less price competitive which will reduce the
domestic demand for them (CFI, 2019), this will encourage more domestic firms to enter the market which
will increase the domestic supply for many necessary goods and avoid dependency on imports which can
be detrimental to the standard of living in an economy.
5.3 Limitations of Research and Recommendations for Future Research
Standard of living has been the concern of many policymakers and economists throughout the years and it
is a very complex topic with a lot of variables affecting it. This research only covers four of those
variables which is not sufficient when planning an extensive long-term plan to curb low standards of
living in developing countries. The regression technique used in this research is Ordinary Least Squares
which may not be the most accurate regression technique amongst the other alternatives as a large amount
of data is required in order to generate a reliable result and outliers in the data may affect the accuracy of
the result (IBNET, n.d.).
For future research regarding the topic, here are some recommendations to tackle the limitations faced in
this study. Firstly, more variables can be included in the research as there are many more variables such as
literacy rate, healthcare expenditure and access to electricity that can affect the standard of living in a
country. Secondly, another regression analysis technique can be employed in future research as there are
many more regression analysis techniques that may be more suitable for research like this when data over
time on the same country is collected such as panel data analysis.
5.4 Conclusion
Malaysia has consistently secured a high position in UNDP’s ranking for standard of living despite being a
developing nation. This research investigated the variables behind Malaysia’s high standard of living so
other developing nations can divert more attention towards these variables contributing to Malaysia’s high
standard of living in their future policies. This study has concluded that foreign direct invest and exports of
goods and services have a positive relationship with human development index in Malaysia while inflation
and imports of goods and services have a negative relationship with human development index in Malaysia.
Policymakers should consider various strategies to accommodate all of these variables in their future
policies in order to increase their standard of living in their country.
6.0 Appendices
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Appendix 2: Secondary Data
Years
HDI
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
0.64
0.648
0.656
0.663
0.671
0.679
0.689
0.7
0.703
0.709
0.721
0.722
0.724
0.732
0.735
0.732
0.736
0.747
0.756
FDI
2332455289
3998448522
5183358086
5005642760
4341800916
4178239335
5078414948
5136514576
2163401816
3895263158
3787631579
553947368.4
3192894737
3218947368
4376052632
3924786635
7690731246
9071369835
7572512432
Inflation
2.61780105
4.35833333
4.7672283
3.53658537
3.72497055
3.4505751
3.48855946
2.6625146
5.270342
2.7445613
1.53474024
1.41678473
1.80787246
1.08967633
1.42127116
2.97507093
3.60923564
2.02735318
5.44078221
Export
74.4661197
77.8255528
75.98386
78.9202876
89.1507769
94.0891704
91.5761512
93.289448
115.743725
121.311394
119.809709
110.402491
108.305303
106.943446
115.373338
112.898977
112.185481
106.168275
99.4995772
Import
72.4221328
81.4858944
74.6273609
79.0201749
90.7541658
98.0240299
90.1908313
92.3756632
93.7484775
96.2595257
100.59708
92.9621447
91.0509299
87.2516829
95.0009282
90.9556678
90.391666
86.2972315
77.1687475
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
0.762
0.769
0.773
0.78
0.785
0.792
0.797
0.803
0.805
0.807
0.81
0.806
0.803
114664434.6
10885801852
15119439204
8895774251
11296279514
10619431583
9857162112
13470089921
9368469823
8304480742
9154921685
4058769679
18595649824
0.58330841
1.62285236
3.17447092
1.66357102
2.10501231
3.14299051
2.1043898
2.0905666
3.87120116
0.88470916
0.66289187
-1.1387022
2.47710241
91.4167919
86.9302951
85.2554421
79.2999139
75.629041
73.7934986
69.4486809
66.7754129
70.011732
68.55494
65.2777282
61.5992243
68.8388945
71.1421786
71.0144698
69.6822425
68.5418408
67.0919504
64.5187326
61.9213707
60.1235659
63.1434588
61.8476129
57.7507804
55.2293371
61.7308972
Appendix 3: EViews Output
Dependent Variable: HDI
Method: Least Squares
Date: 06/26/23 Time: 22:24
Sample: 1990 2021
Included observations: 32
Variable
Coefficient
Std. Error
t-Statistic
Prob.
FDI
INFLATION
EXPORT
IMPORT
C
5.04E-12
-0.011418
0.002357
-0.004060
0.842249
1.32E-12
0.003366
0.000528
0.000809
0.037318
3.806171
-3.391728
4.460579
-5.018441
22.56934
0.0007
0.0022
0.0001
0.0000
0.0000
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.821602
0.795173
0.023804
0.015299
76.92529
31.08681
0.000000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
0.739219
0.052596
-4.495331
-4.266310
-4.419417
0.969007
Date: 06/26/23 Time: 22:44
Sample: 1990 2021
HDI
FDI
INFLATION
EXPORT
IMPORT
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
0.739219
0.735500
0.810000
0.640000
0.052596
-0.273722
1.917255
6.70E+09
5.11E+09
1.86E+10
1.15E+08
4.25E+09
0.838021
3.372346
2.537144
2.547452
5.440782
-1.138702
1.441785
-0.073806
3.075901
89.58671
88.04054
121.3114
61.59922
18.50944
0.240666
1.689989
78.57259
78.09446
100.5971
55.22934
13.93999
-0.070038
1.562499
Jarque-Bera
Probability
1.962707
0.374803
3.930343
0.140132
0.036733
0.981801
2.597077
0.272930
2.781374
0.248904
Sum
23.65500
2.14E+11
81.18862
2866.775
2514.323
Heteroskedasticity Test: Breusch-Pagan-Godfrey
Null hypothesis: Homoskedasticity
F-statistic
Obs*R-squared
Scaled explained SS
2.120431
7.649437
8.660973
Prob. F(4,27)
Prob. Chi-Square(4)
Prob. Chi-Square(4)
0.1058
0.1053
0.0702
Test Equation:
Dependent Variable: RESID^2
Method: Least Squares
Date: 06/27/23 Time: 00:05
Sample: 1990 2021
Included observations: 32
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
FDI
INFLATION
EXPORT
IMPORT
0.002791
-7.06E-14
0.000205
-1.87E-05
-8.75E-06
0.001269
4.50E-14
0.000115
1.80E-05
2.75E-05
2.198379
-1.568998
1.793819
-1.038972
-0.317918
0.0367
0.1283
0.0840
0.3080
0.7530
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.239045
0.126311
0.000810
1.77E-05
185.1133
2.120431
0.105777
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
0.000478
0.000866
-11.25708
-11.02806
-11.18117
1.808988
Breusch-Godfrey Serial Correlation LM Test:
Null hypothesis: No serial correlation at up to 2 lags
F-statistic
Obs*R-squared
2.582159
5.478598
Prob. F(2,25)
Prob. Chi-Square(2)
0.0956
0.0646
Test Equation:
Dependent Variable: RESID
Method: Least Squares
Date: 06/27/23 Time: 00:41
Sample: 1990 2021
Included observations: 32
Presample missing value lagged residuals set to zero.
Variable
Coefficient
Std. Error
t-Statistic
Prob.
FDI
INFLATION
EXPORT
IMPORT
C
RESID(-1)
RESID(-2)
-1.68E-13
0.002519
-0.000207
0.000274
-0.008529
0.413898
0.109917
1.28E-12
0.003420
0.000511
0.000775
0.035666
0.208410
0.212737
-0.131038
0.736631
-0.404675
0.353682
-0.239148
1.985978
0.516679
0.8968
0.4682
0.6892
0.7265
0.8129
0.0581
0.6099
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.171206
-0.027704
0.022521
0.012680
79.92983
0.860720
0.536778
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
-1.05E-16
0.022215
-4.558115
-4.237485
-4.451835
1.586951
12
Series: Residuals
Sample 1990 2021
Observations 32
10
8
6
4
2
0
-0.06
-0.04
-0.02
0.00
0.02
0.04
0.06
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
-1.05e-16
0.003367
0.051080
-0.065619
0.022215
-0.591365
4.180824
Jarque-Bera
Probability
3.724257
0.155342
Appendix 4: Supervisor and Student Meeting Record
Appendix B
SUPERVISOR – STUDENT MEETING RECORD
Student Name: Denis Sim Li Teik
Programme: Bachelor of Business (Honours) Finance and Economics
Module Code: PRJ60104
Supervisor Name: Yamunah Vaicondam
Day/Date/Time and Duration of meeting: Wednesday, 5/3/2023, 12pm-1pm
Purpose of meeting: Seeking advice regarding research topic and approach to carry out the
research
Key issues discussed:
We discussed the format and flow of the assignment. We also discussed some appropriate
alternatives for my research topic and how I should choose my variables for the research.
Agreed action and deadline:
Come up with an appropriate draft that encompasses all of the points that were discussed during
the session. Due date was a week after the session
Signature of the Student:
denis
Date:
6/28/2023
Signature of the Supervisor:
Date:
Appendix B
SUPERVISOR – STUDENT MEETING RECORD
Student Name: Denis Sim Li Teik
Programme: Bachelor of Business (Honours) Finance and Economics
Module Code: PRJ60104
Supervisor Name: Yamunah Vaicondam
Day/Date/Time and Duration of meeting: Thursday, 5/18/2023, 12pm-1pm
Purpose of meeting: Draft evaluation for topic 1 and 3
Key issues discussed:
Going over my draft for topic 1 to 3 and identifying the areas that needs adjustments. The scope
of study and problem statement wasn’t clear enough.
Agreed action and deadline:
Make the relevant adjustments to the above-mentioned areas and revert back in 5 days.
Signature of the Student:
denis
Date:
6/28/2023
Signature of the Supervisor:
Date:
Appendix B
SUPERVISOR – STUDENT MEETING RECORD
Student Name: Denis Sim Li Teik
Programme: Bachelor of Business (Honours) Finance and Economics
Module Code: PRJ60104
Supervisor Name: Yamunah Vaicondam
Day/Date/Time and Duration of meeting: Thursday, 6/22/2023, 12pm-1pm
Purpose of meeting: Seeking guidance for problems encounters with regression output
results
Key issues discussed:
Going over the problems that was faced in my output which are heteroskedasticity, low RSquared and unexpected signs
Agreed action and deadline:
Include more independent variables and test the regression output again. Due in 3 days from
session.
Signature of the Student:
denis
Date:
6/28/2023
Signature of the Supervisor:
Date:
Appendix 5: Research Ethics
Appendix H
Research Ethics Check-list
Please complete this check-list before executing your research. A copy of the signed and dated
Research Ethics Check-list must be submitted togetherwith the Project as appendix.
Student Name
Student I.D.
Programme
Module Code
Supervisor Name
Research Project Title
No.
Denis Sim Li Teik
0348585
Bachelor of Business (Hons) Finance & Economics
PRJ60104
Dr Yamunah Vaicondam
Impacts of Foreign Direct Investment, Inflation, Export of Goods and
Services, and Imports of Goods and Services on Standard of Living in
Malaysia
Check-list
Yes (please explain briefly)
No
/
1.
Will you be collecting primary data from
human subjects?
2.
Will you be involving respondents who are
children or vulnerable adults?
Will the data collection process cause
anxiety/stress to respondents?
Will you be going to collect any data that
is of a sensitive and/or confidential
naturefrom your respondents?
Will you be safeguarding the anonymity of
your respondents and assure
the
confidentiality of data collected?
Will there be any kind of risks to you, to
/
the respondents or to the University that
may result from conducting this research?
Will you
be
collecting
data from organisation/s?
Do you foresee any ethical issues that may
arise from your research?
the respondents or to the University
thatmay result from conducting this
research?
Will you be collecting data from
organisation/s?
/
Do you foresee any ethical issues that
mayarise from your research?
/
3.
4.
5.
6.
7.
8.
7.
8.
/
/
/
/
/
/
/
/
Student’s signature: denis
Supervisor’s Signature:
Appendix 6: Turnitin Report
Date: 28 June 2023
Date:
Appendix 7: Supervisor Review Record
Appendix J
SUPERVISOR REVIEW RECORD
Student Name: Denis Sim Li Teik
Student ID: 0348585
Programme: Bachelor of Business (Hons) Finance & Economics
Module Code: PJR60104
I hereby confirm that I have progressively reviewed all the chapters of the above students FYP.
Supervisor’s Name: Dr Yamunah Vaicondam
Supervisor’s Signature:
Date:
Appendix 8: Marking Rubrics and Markers comment page
Appendix K
Marking rubrics
Rubrics for Assessment Task (100%):
Sub-Attributes
TCG2b_2b.1:
Flexibility and
divergent
thinking
(10%)
%
10%
TCG2b_2b.4:
Analyze and
synthesize the
evidence
(10%)
10%
TCG2b_2b:5: Justify
and theorize your
position
(perspective/thesis/h
ypothesis) (20%)
20%
Outstanding (9-10)
Integrate literature
information from
multiple
perspectives and is
able to
shift readily
from one
perspective to
another
Select and use
journal articles or
current research
papers from
sources with
enough
interpretation to
develop a
comprehensive
analysis or
synthesis
Mastering (7-8)
Explore literature
information from
multiple
perspectives
Developing (5-6)
Generate
literature
information
from few
perspectives
Beginning (0-4)
Provide literature
information from a
singleperspective
Analyse the issue with
the most relevant
journal articlesor
current research
papers, and evaluate it
with some
evidence and
logical reasoning
acknowledged
Analyse the issue
with somerelevant
journal articles or
current research
papers, and
evaluate it with
little
evidence and
simplistic
logical
reasoning
Analyse the issue
with little journal
articles or current
research papers,
evidence and
logical reasoning
Articulate a detailed
positionand the
reasoning behind
research hypothesis
or themes and
develop a reasonable
and well thought-out
conclusion/solution.
Fully recognizes
biases andmultiple
points of view
Articulate a position
and the basic
reasoning behind
research hypothesis or
themes and develops a
reasonable and well
thought-out
conclusion/solution.
Adequately
recognizes biases or
multiple points of
view
Articulate a position
and the basic
reasoning behind
research hypothesis
or themesand
develops a
reasonable and well
thought-out
conclusion/solution.
Partially recognises
biases or multiple
points of view
Does not articulate
a clear position and
fails tosupport all
research
hypothesis/themes
or justify a
conclusion/
solution. Does not
recognise biases or
multiple points of
view
TCG3_3.1: Deliver
content with
consideration of
audience, purpose,
and context
surrounding the
task, both orally
and in written
form as well as any
other appropriate
forms(10%)
10%
Deliver compelling
content which
demonstrates a
thorough
understanding of
appropriate research
context,audience and
purpose, in written
forms
Deliver a central
content which
demonstrates a
thorough
understanding of
appropriate research
context,audience and
purpose, in written
forms
Deliver basic
content which
demonstrates a
basic understanding
of appropriate
research context,
audience and
purpose, in written
forms
Deliver superficial
content which
demonstrates a
lacked of
understanding of
appropriate
research context,
audience and
purpose, in written
forms
TCG3_3.2: Demonstrate
disciplinaryconvention and
display organisation (10%)
10
%
Demonstrate
detailed attention
and successful
execution of a wide
range ofconventions
particular to a
specific research
topic including
organization,
content,
presentation
formatting and style
TCG3_3.4: Use supporting
evidence(20%)
20
%
Uses a variety of
supportingevidence
(quantitative data
or interview
transcripts), making
appropriate
reference to
information or
analysis that
significantly
supports the points
being made
TCG6_4.1:
Demonstrate selfdirected learning
(5%)
5%
TCG6_4.2: Demonstrate
self-inquiryin learning (5%)
5%
Demonstrate
autonomy anda
continued
commitment to
project paper and
learn
independently, in a
consistent manner,
using a variety of
self-directed
learning activities
Explore research
topics in-depth,
yielding a rich
awareness and/or
little- known
information
indicating intense
interest, initiative
and effort in the
subject
Demonstrate
competent
attention and
execution of awide
range of
conventions
particular to a
specific research
topic including
organization,
content,
presentation
formatting and
style
Uses adequate
supporting
evidence
(quantitative data
or interview
transcripts),
making
appropriate
reference to
information or
analysis that
supports the
points being made
Demonstrate
adequate attention
and execution of a
wide range of
conventions
particular to a
specific research
topic including
organization,
content,
presentation
formatting and
style
Demonstrate little
attention and
execution ofa
wide range of
conventions
particular to a
specific research
topic including
organization,
content,
presentation
formatting and style
Uses adequate, but
sometimes irrelevant,
supporting evidence
(quantitative data or
interview transcripts),
makingadequate, but
sometimes
inappropriate,
reference to
information or
analysis that supports
the points being
made
Demonstrate
autonomy and a
continued
commitment to
project paper and
learn
independently, at
various occasions,
using a variety of
self-directed
learning activities
Explore research
topics in depth,
yielding insight
and/or information
indicating interest,
initiativeand effort
in the subject
Demonstrate
commitment to
project paper and
learn independently
using a varietyof selfdirected learning
activities
Uses little or
irrelevant
supporting
evidence
(quantitative
data or
interview
transcripts),
with little
reference to
information or
analysisthat
supports the
pointsbeing
made
Demonstrate
limited
commitment to
projectpaper
and learn
independently
using a variety
of self-directed
learning
activities
Explore research
topics with some
evidence of depth,
providing occasional
insight and/or
information
indicatingmild
interest, initiative
and effort in the
subject
Explore research
topics ata surface
level, providing
little insight
and/or
information
beyond the very
basic facts
indicating low
interest, initiative
and effort in the
subject
TCG8_8.4: Function
effectively and
constructively in a global
environment and in a
variety of contemporary
global contexts (5%).
5%
TCG8_8.5: Demonstrate a
knowledge and respect of
ethics andethical
standards (5%).
5%
Apply knowledge
and skills to
implement
sophisticated,
appropriate, and
workable solutions
to address complex
global problems
using
interdisciplinary
perspectives
independently
Maintain a high
level of ethical
integrity by always
prioritizing ethical
values over selfinterest. Be aware
of ethical concerns
and research bias.
Plan and evaluate
more complex
solutions to global
challenges that are
appropriate to their
contextsusing
multiple disciplinary
perspectives (such
as cultural,
historical, and
scientific)
Formulate practical
yet elementary
solutions to global
challenges that use at
least two disciplinary
perspectives (such as
cultural,historical,
and scientific).
Define global
challenges in basic
ways, including a
limited number of
perspectives and
solutions.
Commit to ethical
integrity by
sometimes
prioritizing ethical
values over selfinterest. Be aware
of ethicalconcerns
and research bias.
Consider ethical
integrity over selfinterest occasionally
when facing ethical
dilemmas. Be aware
of ethical concerns
and research bias.
Prioritize selfinterest over
ethical integrity
when facing
ethical
dilemmas. Be
aware ofethical
concerns and
research bias.
Appendix L
Marker’s Comments
Final Year Project Marking Report
(Please attach this report to scoring rubric)
Supervisor’s report ( ) 2nd marker’s report ( ) 3rd markers report ( )
Student’s name
Student’s I.D. No.
Research Topic
Denis Sim Li Teik
0348585
Impacts of Foreign Direct Investment, Inflation,
Export of Goods and Services, and Imports of
Goods and Services on Standard of Living in
Malaysia.
Programme (please circle)
BA / IB / HRM / IBM / MKT / AF / FE /
BF
Module Code
PJR60104
Marker’s name (please circle) Dr.
/ Mr / Ms
Marks awarded
Final Project Marks
(after 2ndmarking)*
*To be completed by supervisor when mark difference is more than5 marks:
Comments given by supervisor after the discussion with 2nd marker
(1) Need 3rd marking
Yes
No
Please notify students the final year project grade, NOT the marks. Students will be provided a copy of the Project
Paper Scoring Rubric (with additional comments) after the Business School has finalised the final year project
grades.
Marker’s Comments
( ) 1st Marker
( ) 2nd Marker
3rd Marker ( )
Introduction
Literature Review
Research Methodology
Result & Discussion
Conclusion & Recommendations
Format
Marks
Grade
Marker’ Name
Marker’s Signature
Date:
Grading Standard for Taylor’s University
(for marker’s reference only)
Grade Marks
Grade
Points
Definition
A
80100
4.00
Excellent
A-
75-79
3.67
Very Good
B+
70-74
3.33
Good
B
65-69
3.00
B-
60-64
2.67
C+
55-59
2.33
C
50-54
2.00
D+
47-49
1.67
D
44-46
1.33
D-
40-43
1.00
F
0-39
WD
-
Pass
Marginal Fail
0.
0
0
Fail
-
Withdra
wn
Description
Evidence of original thinking; demonstrated outstanding
capacity to analyse and synthesise; outstanding grasp of
subject matter; evidence of extensive knowledge base.
Evidence of grasp of subject matter, critical capacity and
analytical ability; understanding of relevant issues; evidence
of familiarity with the literature.
Evidence of grasp of subject matter, critical capacity and
analytical ability; reasonable understanding of relevant issues;
evidence of familiarity with the literature.
Evidence of some understanding of the subject matter; ability
to develop solutions to simple problems; benefiting from
his/her university experience.
Evidence of minimally acceptable familiarity with subject matter,
critical and analytical skills.
Insufficient evidence of understanding of the subject matter; weakness
in critical and analytical skills; limited or irrelevant use of the
literature.
Withdrawn from a module before census date, typically mid semester.
[please refer to Description 1 below]
F(W)
0
0.
0
0
Fail
IN
-
-
Incomp
lete
P
-
-
Pass
Withdrawn from a module after census date, typically mid semester.
[please refer to Description 2 below]
An interim notation given for a module where a student has not
completed certain requirements with valid reason or it is not possible to
finalise the grade by the published deadline.
Given for satisfactory completion of practicum
(Valid as of 2 April, 2013 and subject to change without
notice)