Case Name: memoTo: Who is your primary audience for this memo/decision? From: An Ethical Accountant in the Finance Department CC: Is there anyone else you need to include or inform with this memo? Date: Today’s Date Re: Email Subject Line The body of the email (memo) goes here. Please separate the sections/elements of the memo into separate paragraphs, paying attention to structure. Is This My Place? ...Speaking “UP” (A)1 Ben was pleased when he was hired out of college, with an accounting degree, to manage the internal and external reporting for a non-profit organization whose work he respected. The organization collected donations of medical supplies from U.S. producers and shipped them to developing countries where the need was great and where they had partnerships with service providers on the ground. It was a small, thinly-staffed office and that also appealed to Ben. He knew their small size was the reason he had the opportunity to take on so much responsibility so quickly, and he approved of the thin operating expenses. The more efficient their operations, the greater the services they could provide to the individuals who most needed them. However, shortly after starting work, he began to see the downside of the organization’s thin staffing. The Executive Director was over-worked and stressed. Although by nature a micro-manager, necessity dictated that she delegate everything she could to her staff. And he quickly began to recognize that the organization had no formal system for monitoring the value of donated supplies for tax purposes. They relied on donors who might feel pressures from their own organizations to inflate the values. Ben struggled with several questions at first: shouldn’t he just trust the donors? After all, they were engaging in corporate philanthropy. And how much did it really matter? The point was to get the supplies to those who needed them overseas. He didn’t want to do anything that would discourage the donations. And he felt confident his Executive Director was aware of the conflict but just didn’t see it as a priority. In fact, when instructing staff on what she needed from them with regard to reporting, she often commented that she wasn’t interested in “data,” but rather focused on relationships and real world impacts. Wouldn’t she know better than he did how to prioritize this issue? And where was the organization’s accountant on this question? On the other hand, as time went on, Ben became quite certain that some of their donors were deceiving the IRS, and that he – and his organization – were enabling that deception. He knew he didn’t want to be part of that. And although he was young, he was a cocky sort. In fact, it had been his outspoken identification of an accounting error during his interview that had secured him the job in the first place, despite his relative youth. Of course, that error was simply a mistake and had had no ethical implications. What should he say, to whom, when.

1. Case Name:
memoTo:
Who is your primary audience for this memo/decision?
From:
An Ethical Accountant in the Finance Department
CC:
Is there anyone else you need to include or inform with this
memo?
Date:
Today’s Date
Re:
Email Subject Line
The body of the email (memo) goes here. Please separate the
sections/elements of the memo into separate paragraphs, paying
attention to structure.
Is This My Place? ...Speaking “UP” (A)1
Ben was pleased when he was hired out of college, with an
accounting degree, to manage the internal and external reporting
for a non-profit organization whose work he respected. The
organization collected donations of medical supplies from U.S.
producers and shipped them to developing countries where the
need was great and where they had partnerships with service
providers on the ground.
It was a small, thinly-staffed office and that also appealed to
Ben. He knew their small size was the reason he had the
opportunity to take on so much responsibility so quickly, and he

2. approved of the thin operating expenses. The more efficient
their operations, the greater the services they could provide to
the individuals who most needed them.
However, shortly after starting work, he began to see the
downside of the organization’s thin staffing. The Executive
Director was over-worked and stressed. Although by nature a
micro-manager, necessity dictated that she delegate everything
she could to her staff. And he quickly began to recognize that
the organization had no formal system for monitoring the value
of donated supplies for tax purposes. They relied on donors who
might feel pressures from their own organizations to inflate the
values.
Ben struggled with several questions at first: shouldn’t he just
trust the donors? After all, they were engaging in corporate
philanthropy. And how much did it really matter? The point was
to get the supplies to those who needed them overseas. He
didn’t want to do anything that would discourage the donations.
And he felt confident his Executive Director was aware of the
conflict but just didn’t see it as a priority. In fact, when
instructing staff on what she needed from them with regard to
reporting, she often commented that she wasn’t interested in
“data,” but rather focused on relationships and real world
impacts. Wouldn’t she know better than he did how to prioritize
this issue? And where was the organization’s accountant on this
question?
On the other hand, as time went on, Ben became quite certain
that some of their donors were deceiving the IRS, and that he –
and his organization – were enabling that deception. He knew
he didn’t want to be part of that.
And although he was young, he was a cocky sort. In fact, it had
been his outspoken identification of an accounting error during
his interview that had secured him the job in the first place,
despite his relative youth. Of course, that error was simply a
mistake and had had no ethical implications.
What should he say, to whom, when and how?

3. Discussion Questions
What are the main arguments Ben is trying to counter? That is,
what are the reasons and rationalizations you need to address?
What’s at stake for the key parties, including those with whom
Ben disagrees?
What levers/arguments can Ben use to influence those with
whom he disagrees?
What is Ben’s most powerful and persuasive response to the
reasons and rationalizations he needs to address?
2
Running Head: COMPARING FACTORS THAT LEAD TO
UNDERDEVELOPMENT 1
COMPARING FACTORS THAT LEAD TO
UNDERDEVELOPMENT 2
Comparing Factors that Lead to Underdevelopment

4. Name
Institution Affiliation
Date
Overview
Fundamentally, every nation wishes to experience economic,
social, and political progress to ensure a better life for its
citizens. They can achieve this through the implementation of
several appropriate developmental reforms and policies.
Moreover, countries are usually categorized as either developed
or undeveloped. Developed countries refer to nations with
efficient health care, numerous educational opportunities, good
governance, high expectancy, more job opportunities, and high
standards of living among others (Frank, 2018). On the other
hand, less developed nations comprise states with inadequate
health care, few educational opportunities, low average life
expectancy, a small number of job opportunities, few
recreational facilities, poor economic growth, a low standard of
living and impoverished life, among others. Nevertheless, less
developed countries tend to share the factors that hinder their
development. Therefore, this study aims to analyze the factors
that are common in two less developed countries (LDCs) as far
as their development is concerned.
LCDs to Compare and Assess
The selected less developed nations to compare and assess in
this assignment include Kenya and Malaysia. Kenya is a state in
Eastern Africa with Nairobi as its capital city. It covers an area
of 581,308km² and boarders countries such as Uganda, Ethiopia,
Tanzania, Somalia, and South Sudan. The national language of
Kenya is Swahili although English is also recognized as the
official language. Additionally, it comprises various ethnic
groups that include the entire population of about 49 million
people. Moreover, the total Gross Domestic Product (GDP) and
per capita income of Kenya is $175.659 billion and $3,657
respectively. On the other hand, Malaysia is a state in Southeast
Asia which borders Singapore, Thailand, Indonesia, and
Vietnam. Kaula Lambur is the capital city of Malaysia and

5. Malay is the national language of this nation. It has a total area
of 330,803 kilometers per square and a population of about 32
million people. The country’s GDP and per capita income are
41.002 trillion and $30,858 respectively.
Besides, Kenya and Malaysia were selected for comparison
since they attained independence in almost the same time,
therefore comparing the two nations will be interesting to
establish the strides these countries have made towards
development since independence. Another reason for selecting
Kenya and Malaysia was that comparing a nation from Asia and
Africa will give an overview of the development status of the
two continents since the countries will act as samples. Finally,
Kenya and Malaysia share as well as differs in many things;
thus there is enough information to support the research.
Comparing Factors that Lead to Underdevelopment
Governmental Corruption
Corruption and bribery are one of the primary factors that
contribute to the underdevelopment of nations. According to
Asongu (2013), corruption refers to a situation where an
individual bribes another person to receive particular favors.
Such a situation tends to result in underdevelopment because
the national resources of a country can remain in the hands of a
few selfish people, thus putting the majority to a miserable life.
Through corruption, government officers can involve in
embezzling the national resources which can put development to
a standstill (Chelliah, 2012). Besides, Kenya and Malaysia share
as well as differs in various ways regarding governmental
corruption as a factor that has contributed to their
underdevelopment. According to recent data by Transparency
International’s Corruption Perception Index, Kenya and
Malaysia are ranked 143rd and 62nd out of 180 nations
respectively. The ranking indicates that there is an existence of
corruption in these nations that have played a role in hindering
development.

6. For instance, Kenya has had a series of corruption cases and
scandals where substantial public resources have been lost. In
the 1990’s, Kenya witnessed the greatest corruption scandal in
its history where about $850 million was lost through the
Central Bank of Kenya in a corruption deal known as
“Goldenberg Scandal” (Daily Nation, 2012). It was estimated
that Kenya lost about 10% of its GDP through this deal
something that has negatively impacted its development. There
have also been other corruption cases such as the “NYS
Scandal” of 2016 where the government lost about $7.6 million.
Similarly, Malaysia has also experienced several corruption
cases that have slowed its development. For instance, in 2009,
Malaysian government lost almost $4.5 billion in the 1MDB
Scandal where the money that was meant to establish an
economic hub went to the pockets of individuals including the
former Prime Minister, Najib Razak (Promchertchoo, 2018).
Recent studies have indicated that the current corruption cases
are the main reason why Malaysia dropped from 55th in 2016 to
65th position in 2017 in the corruption perception index (The
Strait Times, 2018). Nevertheless, although corruption is one of
the factors leading to underdevelopment in both Kenya and
Malaysia, the bribery level in Kenya is comparably higher than
Malaysian. Also, Malaysia has better systems to deal with
corruption cases than Kenya. For instance, currently, the
government has managed to recover about $700 million from
the lost $4.5 billion in the 1MDB scandal.
Internal and External Conflicts
Both internal and external conflicts can result in
underdevelopment of a nation because the nation will focus
more on resolving the dispute rather than enhancing economic
development (Chelliah, 2012). Also, during these times, the
state can use a lot of national resources in trying to settle the
feuds. Besides, both Kenya and Malaysia have had a series of

7. internal and external conflicts that have significantly impacted
their development. For example, in 2007, Kenya witnessed its
worst domestic disputes in the post-election violence where
nearly 1500 people lost their lives and property worth billions
got destroyed. Schools, roads, hospitals, and other vital
institutions were destroyed something that significantly
contributed to Kenya’s underdevelopment. Also, Kenya has
suffered from external attacks mainly from the militia group
known as Al-Shabaab that originates in Somalia.
In 2013, Al-Shabaab attacked the Westgate Shopping Mall in
Kenya’s capital city something that greatly scarred away
investors, thus negatively impacting the development of this
nation. Similarly, Malaysia has also had various internal
conflicts such as the 2001 ethnic clashes between the Malays
and ethnic Indians which affected growth negatively (BBC
News, 2018). Although Malaysia has not experienced major
external conflicts in recent years, its constant dispute with its
neighbors such as Indonesia is also affecting development
adversely. Moreover, between the two countries, Kenya’s
growth seems to be profoundly affected by both internal and
external conflicts compared to Malaysia. The ethnic wars are
still present as well as the Al-Shabaab menace which is
continuing to affect the economic and social development of
Kenya.
Ethnic, Racial or Tribal Disparities
Ethnic, racial, and tribal disparities also comprise one of the
primary factors that result in underdevelopment in many
nations. Kenya and Malaysia are not an exception. Ethnic and
tribal inequalities have been a severe problem to Kenya since
independence. People are divided across ethnic and tribal lines,
and this has been evident in all of Kenyan’s general election
where people tend to vote for leaders based on their tribes.
Kenya comprises more than 44 tribes that find it challenging to
live along with each other. Current studies have revealed that

8. dominant tribes in Kenya including the Kikuyu and Luo own
and control the most significant percentage of the countries
resources. Individuals from these tribes also hold various
critical positions in the government something that has
intensified corruption and nepotism in the public service. In
essence, when the nation is divided along ethnic and tribal
lines, development is adversely affected because the dominant
tribe tends to control as well as own a more significant share of
resources (Bauer, 2013). Only a few areas can experience
development, but the most significant part of the nation will
have poor roads, ill-equipped schools and hospitals, and high
unemployment rates among others. Because of ethnic and tribal
disparities, Kenya has been experiencing these things which
have surprised its development since only a section of the
citizens can share the nation’s resources as well as access
development opportunities.
On the other hand, although not at a high intensity like Kenya,
Malaysia has also been witnessing particular ethnic and racial
disparities that have impacted its development. For instance,
most Malays discriminate the ethnic Indians something that has
slowed growth in areas where with the Indians. The ethnic
Indians are discriminated in employment, infrastructure
development, and even health care among others a situation that
tends to affect the overall development of the nation adversely.
Additionally, most Malays racially discriminate foreign workers
who at times bring in new development ideas, therefore slowing
the progress of the country.
Unfair Judicial Systems
The judicial system of Kenya has also played a significant role
in the underdevelopment of the nation. Usually, the legal system
must ensure that all economic crimes are punished and stolen
assets recovered to enhance development. However, in Kenya,
the judicial system has not been doing enough to support
growth. For instance, the money stolen in “Golden bag” and
“NYS” scandals have not yet been recovered until today (Daily

9. Nation, 2012). Also, most of the courts and judges in Kenya
tend to receive bribes, thus making verdicts in favor of the
economic criminals. Such situations have significantly hindered
development since the nation’s resources are stolen, and nothing
is done. The money could have been used in improving
infrastructure, creating employment, improving health care
among others which are usually the indicators of development.
The Anti-Corruption Commission (EACC) is also not doing its
work efficiently.
Moreover, Malaysia has also witnessed several inefficiencies in
its judicial system that has been a threat to the development of
the country. For example, the Anti-Corruption Commission and
other investigative agencies could find Najib Razak (former
prime minister) guilty in the 1MBD scandal where the
government lost a lot of money. Nevertheless, the judicial
system of Kenya is less efficient than Malaysian. Also,
Malaysia has implemented various reforms that have refined its
legal framework to support development.
Shaky Financial Systems
The financial systems of both Kenya and Malaysia have also
hindered the development of these nations. The Central Bank of
both these nations has involved in specific financial scandals
that have cost the countries dearly. For example, the Central
Bank of Kenya played a massive role in the Golden bag scandal
in the 1990’s where most of its employees were part of the
crime. Also, when the Malaysian government lost $4.5 billion in
the 1MBD scandal, the Central Bank did not adequately track
the individual accounts of persons involved in the crime.
Therefore, the inefficient financial systems of these two nations
mostly hinder their development.
Conclusion
In summary, many factors can hinder the development of a
nation including governmental corruption, internal and external
conflicts, ethnic, racial or tribal disparities, unfair judicial
systems, and shaky financial systems among others. The

10. research has revealed that Kenya and Malaysia share particular
factors that have hindered their development. Overall, the
factors analyzed seem to be more frequent and prevalent in
Kenya than Malaysia. As such, the Kenyan government should
implement appropriate development reforms and policies to
enhance the growth of the nation.
References
Asongu, S. A. (2013). Fighting corruption in Africa: do existing
corruption-control levels matter?. International Journal of
Development Issues, 12(1), 36-52.
Bauer, P. (2013). Economic analysis and policy in
underdeveloped countries. Routledge.
BBC News (2018). Malaysia profile – Timeline. Retrieved from
https://www.bbc.com/news/world-asia-pacific-15391762
Chelliah, R. J. (2012). Fiscal policy in underdeveloped
countries: with special reference to India. Routledge.
Daily Nation (2012). How Goldenberg scandal was hatched and
executed. Retrieved from https://www.nation.co.ke/news/How-
Goldenberg-scandal-was-hatched-and-executed-/1056-1628532-
8k2yos/index.html
Frank, A. G. (2018). The development of underdevelopment.
In Promise of development (pp. 111-123). Routledge.
Promchertchoo, P. (2018). Najib, 1MDB and billions of dollars:
A look back at one of Malaysia’s biggest corruption scandals.
Retrieved from
https://www.channelnewsasia.com/news/asia/najib-1mdb-
malaysia-corruption-scandal-10255114
The Strait Times (2018). Malaysia drops to 62nd position in
2017, its worst, in corruption perceptions index. Retrieved from
https://www.straitstimes.com/asia/se-asia/malaysia-drops-to-
62nd-position-in-2017-its-worst-in-corruption-perceptions-
index

11. Country classification
Data sources, country classifications and aggregation
methodology
The statistical annex contains a set of data that the World
Economic Situation and Prospects
(WESP) employs to delineate trends in various dimensions of
the world economy.
Data sources
The annex was prepared by the Development Policy and
Analysis Division (DPAD) of the
Department of Economic and Social Affairs of the United
Nations Secretariat (UN/DESA).
It is based on information obtained from the Statistics Division
and the Population Division
of UN/DESA, as well as from the five United Nations regional
commissions, the United Na-
tions Conference on Trade and Development (UNCTAD), the
United Nations World Tour-
ism Organization (UNWTO), the International Monetary Fund
(IMF), the World Bank,
the Organization for Economic Cooperation and Development
(OECD), and national and
private sources. Estimates for the most recent years were made
by DPAD in consultation
with the regional commissions, UNCTAD, UNWTO and
participants in Project LINK,
an international collaborative research group for econometric
modelling coordinated jointly
by DPAD and the University of Toronto. Forecasts for 2014 and
2015 are primarily based
on the World Economic Forecasting Model of DPAD, with

12. support from Project LINK.
Data presented in WESP may differ from those published by
other organizations for
a series of reasons, including differences in timing, sample
composition and aggregation
methods. Historical data may differ from those in previous
editions of WESP because of
updating and changes in the availability of data for individual
countries.
Country classifications
For analytical purposes, WESP classifies all countries of the
world into one of three broad
categories: developed economies, economies in transition and
developing economies. The
composition of these groupings, specified in tables A, B and C,
is intended to reflect basic
economic country conditions. Several countries (in particular
the economies in transition)
have characteristics that could place them in more than one
category; however, for purposes
of analysis, the groupings have been made mutually exclusive.
Within each broad category,
some subgroups are defined based either on geographical
location or on ad hoc criteria, such
as the subgroup of “major developed economies”, which is
based on the membership of the
Group of Seven. Geographical regions for developing
economies are as follows: Africa, East
Asia, South Asia, Western Asia, and Latin America and the
Caribbean.1
1 Names and composition of geographical areas follow those
specified in the statistical paper entitled
“Standard country or area codes for statistical use”

13. (ST/ESA/STAT/SER.M/49/Rev. 4).
144 World Economic Situation and Prospects 2014
In parts of the analysis, a distinction is made between fuel
exporters and fuel
importers from among the economies in transition and the
developing countries. An
economy is classified as a fuel exporter if the share of fuel
exports in its total merchandise
exports is greater than 20 per cent and the level of fuel exports
is at least 20 per cent
higher than that of the country’s fuel imports. This criterion is
drawn from the share
of fuel exports in the total value of world merchandise trade.
Fuels include coal, oil and
natural gas (table D).
For other parts of the analysis, countries have been classified by
their level of devel-
opment as measured by per capita gross national income (GNI).
Accordingly, countries
have been grouped as high-income, upper middle income, lower
middle income and
low-income (table E). To maintain compatibility with similar
classifications used else-
where, the threshold levels of GNI per capita are those
established by the World Bank.
Countries with less than $1,035 GNI per capita are classified as
low-income countries,
those with between $1,036 and $4,085 as lower middle income
countries, those with
between $4,086 and $12,615 as upper middle income countries,
and those with incomes

14. of more than $12,615 as high-income countries. GNI per capita
in dollar terms is esti-
mated using the World Bank Atlas method,2 and the
classification in table E is based on
data for 2012.
The list of the least developed countries (LDCs) is decided upon
by the United
Nations Economic and Social Council and, ultimately, by the
General Assembly, on the
basis of recommendations made by the Committee for
Development Policy. The basic
criteria for inclusion require that certain thresholds be met with
regard to per capita GNI,
a human assets index and an economic vulnerability index.3 As
at 29 November 2013,
there were 49 LDCs (table F).
WESP also makes reference to the group of heavily indebted
poor countries (HIPCs),
which are considered by the World Bank and IMF as part of
their debt-relief initiative
(the Enhanced HIPC Initiative).4 In September 2013, there were
39 HIPCs (see table G).
Aggregation methodology
Aggregate data are either sums or weighted averages of
individual country data. Unless
otherwise indicated, multi-year averages of growth rates are
expressed as compound an-
nual percentage rates of change. The convention followed is to
omit the base year in a
multi-year growth rate. For example, the 10-year average
growth rate for the decade of
the 2000s would be identified as the average annual growth rate
for the period from 2001

15. to 2010.
WESP utilizes exchange-rate conversions of national data in
order to aggregate
output of individual countries into regional and global totals.
The growth of output in
each group of countries is calculated from the sum of gross
domestic product (GDP)
of individual countries measured at 2005 prices and exchange
rates. Data for GDP in
2 See http://data.worldbank.org/about/country-classifications.
3 Handbook on the Least Developed Country Category:
Inclusion, Graduation and Special Support Measures
(United Nations publication, Sales No. E.07.II.A.9). Available
from http://www.un.org/esa/analysis/
devplan/cdppublications/2008cdphandbook.pdf.
4 IMF, Debt Relief Under the Heavily Indebted Poor Countries
(HIPC) Initiative Available from
http://www.imf.org/external/np/exr/facts/pdf/hipc.pdf
145Country classification
2005 in national currencies were converted into dollars (with
selected adjustments) and
extended forwards and backwards in time using changes in real
GDP for each country.
This method supplies a reasonable set of aggregate growth rates
for a period of about 15
years, centred on 2005.
The exchange-rate based method differs from the one mainly

16. applied by the IMF
and the World Bank for their estimates of world and regional
economic growth, which is
based on purchasing power parity (PPP) weights. Over the past
two decades, the growth
of world gross product (WGP) on the basis of the exchange-rate
based approach has been
below that based on PPP weights. This is because developing
countries, in the aggregate,
have seen significantly higher economic growth than the rest of
the world in the 1990s
and 2000s and the share in WGP of these countries is larger
under PPP measurements
than under market exchange rates.
Table A
Developed economies
Europe
Other countries
Major developed
economies (G7)European Union New EU member States Other
Europe
EU-15
Austria
Belgium
Denmark
Finland
France

17. Germany
Greece
Ireland
Italy
Luxembourg
Netherlands
Portugal
Spain
Sweden
United Kingdom
Bulgaria
Croatia
Cyprus
Czech Republic
Estonia
Hungary
Latvia
Lithuania

18. Malta
Poland
Romania
Slovakia
Slovenia
Iceland
Norway
Switzerland
Australia
Canada
Japan
New Zealand
United States
Canada
Japan
France
Germany
Italy

19. United Kingdom
United States
Table B
Economies in transition
South-Eastern Europe Commonwealth of Independent States and
Georgiaa
Albania
Bosnia and Herzegovina
Montenegro
Serbia
The former Yugoslav Republic
of Macedonia
Armenia
Azerbaijan
Belarus
Georgiaa
Kazakhstan
Kyrgyzstan
Republic of Moldova

20. Russian Federation
Tajikistan
Turkmenistan
Ukraine
Uzbekistan
a Georgia officially left the
Commonwealth of Independent
States on 18 August 2009.
However, its performance is
discussed in the context of this
group of countries for reasons
of geographic proximity
and similarities in economic
structure.
146 World Economic Situation and Prospects 2014
Table C
Developing economies by regiona
Africa Asia
Latin America
and the Caribbean
North Africa Southern Africa East Asia Caribbean
Algeria

21. Egypt
Libyab
Mauritania
Morocco
Sudan
Tunisia
Angola
Botswana
Lesotho
Malawi
Mauritius
Mozambique
Namibia
South Africa
Zambia
Zimbabwe
Brunei Darussalam
China

22. Hong Kong SARc
Indonesia
Malaysia
Myanmar
Papua New Guinea
Philippines
Republic of Korea
Singapore
Taiwan Province of China
Thailand
Viet Nam
Barbados
Cuba
Dominican Republic
Guyana
Haiti
Jamaica
Trinidad and Tobago

23. Central Africa Mexico and Central America
Cameroon
Central African Republic
Chad
Congo
Equatorial Guinea
Gabon
Sao Tome and Prinicipe
Costa Rica
El Salvador
Guatemala
Honduras
Mexico
Nicaragua
Panama
West Africa
Benin
Burkina Faso

24. Cabo Verde
Côte d’Ivoire
Gambia
Ghana
Guinea
Guinea-Bissau
Liberia
Mali
Niger
Nigeria
Senegal
Sierra Leone
Togo
South Asia
Bangladesh
India
Iran (Islamic Republic of)
Nepal

25. Pakistan
Sri Lanka
East Africa South America
Burundi
Comoros
Democratic Republic
of the Congo
Djibouti
Eritrea
Ethiopia
Kenya
Madagascar
Rwanda
Somalia
Uganda
United Republic
of Tanzania
Argentina
Bolivia (Plurinational
State of)

26. Brazil
Chile
Colombia
Ecuador
Paraguay
Peru
Uruguay
Venezuela (Bolivarian
Republic of)
Western Asia
Bahrain
Iraq
Israel
Jordan
Kuwait
Lebanon
Oman
Qatar

27. Saudi Arabia
Syrian Arab Repuplic
Turkey
United Arab Emirates
Yemen
a Economies systematically
monitored by the Global
Economic Monitoring Unit
of DPAD.
b The name of the Libyan
Arab Jamahiriya was officially
changed to Libya on 16
September 2011.
c Special Administrative
Region of China.
147Country classification
Table D
Fuel-exporting countries
Economies
in transition
Developing countries

28. Latin America
and the Caribbean Africa East Asia South Asia Western Asia
Azerbaijan
Kazakhstan
Russian
Federation
Turkmenistan
Uzbekistan
Bolivia
(Plurinational
State of)
Colombia
Ecuador
Trinidad
and Tobago
Venezuela
(Bolivarian
Republic of)
Algeria
Angola
Cameroon

29. Chad
Congo
Côte d’Ivoire
Egypt
Equatorial
Guinea
Gabon
Libya
Nigeria
Sudan
Brunei
Darussalam
Indonesia
Viet Nam
Iran (Islamic
Republic of)
Bahrain
Iraq
Kuwait
Oman

30. Qatar
Saudi Arabia
United Arab
Emirates
Yemen
148 World Economic Situation and Prospects 2014
Table E
Economies by per capita GNI in 2012a
High-income Upper middle income Lower middle income Low-
income
Australia
Austria
Bahrain
Barbados
Belgium
Brunei
Darussalam
Canada
Chileb

31. Croatia
Cyprus
Czech
Republic
Denmark
Equatorial
Guinea
Estonia
Finland
France
Germany
Greece
Hong Kong
SARd
Iceland
Ireland
Israel
Italy
Japan

32. Kuwait
Latviab
Lithuaniab
Luxembourg
Malta
Netherlands
New Zealand
Norway
Oman
Poland
Portugal
Qatar
Republic
of Korea
Russian Federationb
Saudi Arabia
Singapore
Slovak
Republic

33. Slovenia
Spain
Sweden
Switzerland
Taiwan Province
of China
Trinidad and
Tobago
United Arab
Emirates
United Kingdom
United States
Uruguayb
Albaniab
Algeria
Angola
Argentina
Azerbaijan
Belarus
Bosnia and

34. Herzegovina
Botswana
Brazil
Bulgaria
China
Colombia
Costa Rica
Cuba
Dominican
Republic
Ecuador
Gabon
Hungaryc
Iran, Islamic
Republic
Iraqb
Jamaica
Jordan
Kazakhstan

35. Lebanon
Libya
Malaysia
Mauritius
Mexico
Montenegro
Namibia
Panama
Peru
Romania
Serbia
South Africa
Thailand
The former
Yugoslav
Republc of
Macedonia
Tunisia
Turkey
Turkmenistan

36. Venezuela, RB
Armenia
Bolivia
Cameroon
Cape Verde
Congo
Côte d’Ivoire
Djibouti
Egypt
El Salvador
Georgia
Ghana
Guatemala
Guyana
Honduras
India
Indonesia
Lesotho

37. Mauritaniab
Moldova
Morocco
Nicaragua
Nigeria
Pakistan
Papua New Guinea
Paraguay
Philippines
São Tomé and
Principe
Senegal
Sri Lanka
Sudan
Syrian Arab Republic
Ukraine
Uzbekistan
Vietnam

38. Yemen, Rep.
Zambia
Bangladesh
Benin
Burkina Faso
Burundi
Central African
Republic
Chad
Comoros
Democratic Republic
of the Congo
Eritrea
Ethiopia
Gambia, The
Guinea
Guinea-Bissau
Haiti
Kenya

39. Kyrgyz Republic
Liberia
Madagascar
Malawi
Mali
Mozambique
Myanmar
Nepal
Niger
Rwanda
Sierra Leone
Somalia
Tajikistan
Tanzania
Togo
Uganda
Zimbabwe
a Economies systematically monitored for the World Economic
Situation and Prospects report and included in the United

40. Nations’ global economic forecast.
b Indicates the country has been shifted upward by one category
from previous year’s classification.
c Indicates the country has been shifted downward by one
category from previous year’s classification.
d Special Administrative Region of China.
149Country classification
Table F
Least developed countries (as of November 2013)
Africa East Asia South Asia Western Asia
Latin America
& the Caribbean
Angola
Benin
Burkina Faso
Burundi
Central African Republic
Chad
Comoros
Democratic Republic of the
Congo
Djibouti
Equatorial Guinea
Eritrea
Ethiopia
Gambia
Guinea
Guinea-Bissau
Lesotho

41. Liberia
Madagascar
Malawi
Mali
Mauritania
Mozambique
Niger
Rwanda
Sao Tome and Principe
Senegal
Sierra Leone
Somalia
South Sudana
Sudan
Togo
Uganda
United Republic
of Tanzania
Zambia
Cambodiaa
Kiribatia
Lao People’s
Democratic
Republica
Myanmar
Samoaa, b
Solomon
Islandsa

42. Timor Lestea
Tuvalua
Vanuatua
Afghanistana
Bangladesh
Bhutana
Nepal
Yemen Haiti
a Not included in the WESP discussion because of insufficient
data.
b Samoa will graduate from the list of the least developed
countries in January 2014.
Table G
Heavily indebted poor countries (as of September 2013)
Post-completion point HIPCsa Interim HIPCsb Pre-decision
point HIPCsc
Afghanistan
Benin
Bolivia
Burkina Faso
Burundi
Cameroon
Central African Republic
Congo
Côte D’Ivoire

43. Democratic Republic of the Congo
Ethiopia
Gambia
Ghana
Guinea
Guinea-Bissau
Guyana
Haiti
Honduras
Liberia
Madagascar
Malawi
Mali
Mauritania
Mozambique
Nicaragua
Niger
Rwanda
Sao Tome and Principe
Senegal
Sierra Leone
Togo
Uganda
United Republic of Tanzania
Zambia
Chad
Comoros
Eritrea
Somalia
Sudan
a Countries that have qualified for irrevocable debt relief under
the HIPC Initiative.

44. b Countries that have qualified for assistance under the HIPC
Initiative (that is to say, have reached decision point), but have
not yet reached completion point.
c Countries that are potentially eligible and may wish to avail
themselves of the HIPC Initiative or the Multilateral Debt
Relief Initiative (MDRI).
150 World Economic Situation and Prospects 2014
Table H
Small island developing States
United Nations members
Non-UN Members/Associate Members
of the Regional Commissions
Antigua and Barbuda
Bahamas
Bahrain
Barbados
Belize
Cabo Verde
Comoros
Cuba
Dominica

45. Dominican Republic
Federated States of
Micronesia
Fiji
Grenada
Guinea-Bissau
Guyana
Haiti
Jamaica
Kiribati
Maldives
Marshall Islands
Mauritius
Nauru
Palau
Papua New Guinea
Saint Kitts and Nevis
Saint. Lucia
Saint Vincent and the

46. Grenadines
Samoa
São Tomé and Príncipe
Seychelles
Singapore
Solomon Islands
Suriname
Timor-Leste
Tonga
Trinidad and Tobago
Tuvalu
Vanuatu
American Samoa
Anguilla
Aruba
Bermuda
British Virgin Islands
Cayman Islands

47. Commonwealth of Northern
Marianas
Cook Islands
Curacao
French Polynesia
Guadeloupe
Guam
Martinique
Montserrat
New Caledonia
Niue
Puerto Rico
Turks and Caicos Islands
U.S. Virgin Islands
Table I
Landlocked developing countries
Landlocked developing countries
Afghanistan
Armenia

48. Azerbaijan
Bhutan
Bolivia (Plurinational State of)
Botswana
Burkina Faso
Burundi
Central African Republic
Chad
Ethiopia
Kazakhstan
Kyrgystan
Lao People’s Democratic
Republic
Lesotho
Malawi
American Samoa
Anguilla
Aruba
Bermuda

49. British Virgin Islands
Cayman Islands
Commonwealth of Northern
Marianas
Cook Islands
Curacao
French Polynesia
Mali
Republic of Moldova
Mongolia
Nepal
Niger
Paraguay
Rwanda
South Sudan
Swaziland
Tajikistan
The former Yugoslav Republic
of Macedonia

50. Turkmenistan
Uganda
Uzbekistan
Zambia
Zimbabwe