HS221
Assignment 4
HS221 – Economics
Assignment – 4
Done By:
Krishnaveni Unnikrishnan - 2006321
Manali Naik - 2004222
Shivika Sharma - 2004235
Shlok Desai – 2003324
1.
a)
The table below shows the number of years that data is available for each country in the
category ‘Final consumption expenditure’.
S.
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Country
Number of years of GDP data
Afghanistan
50
Albania
50
Algeria
50
Andorra
50
Angola
50
Anguilla
50
Antigua and Barbuda
50
Argentina
50
Armenia
30
Aruba
50
Australia
50
Austria
50
Azerbaijan
30
Bahamas
50
Bahrain
50
Bangladesh
50
Barbados
50
Belarus
30
Belgium
50
Belize
50
Benin
50
Bermuda
50
Bhutan
50
Bolivia (Plurinational State of)
50
Bosnia and Herzegovina
30
Botswana
50
Brazil
50
British Virgin Islands
50
Brunei Darussalam
50
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Assignment 4
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
Bulgaria
50
Burkina Faso
50
Burundi
50
Cabo Verde
50
Cambodia
50
Cameroon
50
Canada
50
Cayman Islands
50
Central African Republic
50
Chad
50
Chile
50
China
50
China, Hong Kong SAR
50
China, Macao SAR
50
Colombia
50
Comoros
50
Congo
50
Cook Islands
50
Costa Rica
50
Côte d'Ivoire
50
Croatia
30
Cuba
50
Curaçao
15
Cyprus
50
Czechia
30
Czechoslovakia (Former)
21
D.P.R. of Korea
50
D.R. of the Congo
50
Denmark
50
Djibouti
50
Dominica
50
Dominican Republic
50
Ecuador
50
Egypt
50
El Salvador
50
Equatorial Guinea
50
Eritrea
30
Estonia
30
Eswatini
50
Ethiopia
30
Ethiopia (Former)
24
Fiji
50
Finland
50
Former Netherlands Antilles
43
France
50
French Polynesia
50
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Assignment 4
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
Gabon
50
Gambia
50
Georgia
30
Germany
50
Ghana
50
Greece
50
Greenland
50
Grenada
50
Guatemala
50
Guinea
50
Guinea-Bissau
50
Guyana
50
Haiti
50
Honduras
50
Hungary
50
Iceland
50
India
50
Indonesia
50
Iran (Islamic Republic of)
50
Iraq
50
Ireland
50
Israel
50
Italy
50
Jamaica
50
Japan
50
Jordan
50
Kazakhstan
30
Kenya
50
Kiribati
50
Kosovo
30
Kuwait
50
Kyrgyzstan
30
Lao People's DR
50
Latvia
30
Lebanon
50
Lesotho
50
Liberia
50
Libya
50
Liechtenstein
50
Lithuania
30
Luxembourg
50
Madagascar
50
Malawi
50
Malaysia
50
Maldives
50
Mali
50
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Assignment 4
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
Malta
50
Marshall Islands
50
Mauritania
50
Mauritius
50
Mexico
50
Micronesia (FS of)
50
Monaco
50
Mongolia
50
Montenegro
30
Montserrat
50
Morocco
50
Mozambique
50
Myanmar
50
Namibia
50
Nauru
50
Nepal
50
Netherlands
50
New Caledonia
50
New Zealand
50
Nicaragua
50
Niger
50
Nigeria
50
North Macedonia
30
Norway
50
Oman
50
Pakistan
50
Palau
50
Panama
50
Papua New Guinea
50
Paraguay
50
Peru
50
Philippines
50
Poland
50
Portugal
50
Puerto Rico
50
Qatar
50
Republic of Korea
50
Republic of Moldova
30
Romania
50
Russian Federation
30
Rwanda
50
Saint Kitts and Nevis
50
Saint Lucia
50
Samoa
50
San Marino
50
Sao Tome and Principe
50
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Assignment 4
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
Saudi Arabia
50
Senegal
50
Serbia
30
Seychelles
50
Sierra Leone
50
Singapore
50
Sint Maarten (Dutch part)
15
Slovakia
30
Slovenia
30
Solomon Islands
50
Somalia
50
South Africa
50
South Sudan
12
Spain
50
Sri Lanka
50
St. Vincent and the Grenadines
50
State of Palestine
50
Sudan
12
Sudan (Former)
41
Suriname
50
Sweden
50
Switzerland
50
Syrian Arab Republic
50
Tajikistan
30
Thailand
50
Timor-Leste
30
Togo
50
Tonga
50
Trinidad and Tobago
50
Tunisia
50
Turkey
50
Turkmenistan
30
Turks and Caicos Islands
50
Tuvalu
50
U.R. of Tanzania: Mainland
50
Uganda
50
Ukraine
30
United Arab Emirates
50
United Kingdom
50
United States
50
Uruguay
50
USSR (Former)
21
Uzbekistan
30
Vanuatu
50
Venezuela (Bolivarian Republic
of)
50
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Assignment 4
213
214
215
216
217
218
219
220
Viet Nam
50
Yemen
31
Yemen Arab Republic (Former)
21
Yemen Democratic (Former)
21
Yugoslavia (Former)
21
Zambia
50
Zanzibar
30
Zimbabwe
50
b)
179 out of 220 countries have data for the entire period (1970 to 2019). Yes, missing data
can prove to be a serious issue in ensuing analysis. It is important to note that almost 20+
years of data is missing for most of these countries. This implies there will be a considerable
difference in the plots of countries with missing data. It will reduce the representativeness of
such countries for the years in which data is unavailable. This in turn will reduce the
statistical power of our analysis.
2) --3)
a)--b)
The line charts given below represent the value of the four components of GDP for India and China.
Components of GDP, India (billion 2015 US$)
1800B
1600B
1400B
1200B
1000B
800B
600B
400B
200B
0B
-200B
-400B
General government final consumption expenditure
Gross capital formation
Household consumption expenditure (including Non-profit institutions serving households)
Net Exports
Fig: India’s GDP components in the time period 1970–2019.
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Assignment 4
Components of GDP, China (billion 2015 US $)
7000B
6000B
5000B
4000B
3000B
2000B
1000B
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
-1000B
1970
0B
General government final consumption expenditure
Gross capital formation
Household consumption expenditure (including Non-profit institutions serving households)
Net Exports
Fig: China’s GDP components in the time period 1970–2019.
c)
It is expected that consumption expenditure and gross capital formation will increase
together as they feed off each other. Higher the consumption of capital goods, higher would
be its production, and vice versa.
If the consumption expenditure and gross capital formation decrease, government
consumption expenditure and net exports is expected to rise as government will have to
provide more subsidies to support consumers and producers. The imports will reduce and in
turn net exports will increase.
So, we expect consumption expenditure and gross capital formation to move together and
government expenditure and net exports to move together. Household consumption
expenditure and government consumption expenditure will move opposite each other.
This hypothesis is true for China and India up until 2007-08, the consumption expenditure
and capital formation seem to grow hand in hand. After 2011, consumption and capital
formation settle back in China. While in India, the consumption graph seems to increase
perpetually, even though there are peaks and valleys in capital formation. China’s net
exports plummeted in the global financial crisis, but this didn’t affect the other components
of GDP.
d)
India:
There was an economic growth in 1980’s due to a string of measures taken by the
government under the sixth five-year plan. This meant the removal of price controls,
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Assignment 4
initiation of fiscal reforms, a revamp of the public sector, reductions in import duties, and
de-licensing of the domestic industry. These reforms helped the country get freedom from
the tough bureaucratic system and opened the doors for more opportunities and foreign
financial inflows. Moreover, it led to a boom in stock markets in 1990-91. The Indian stock
market scam in 1992 changed the whole liquidity market and led to a market crash of nearly
13% in one day. India was less impacted by the global economic crisis 2007-08 because the
exports accounted for just 15% of the GDP. In 2016 Prime Minister Narendra Modi declared
that Rs 500 and Rs 1,000 notes would not be legal tender. The announcement shook the
country, almost everyone from a small vendor to a high-profile businessman was affected.
Sensex crashed due to the government’s move to withdraw notes of higher denominations.
Just months after demonetisation, the Rajya Sabha passed a crucial bill on Goods and
Services Tax (GST). However, at that time, the plots didn't react much and remained mostly
flat on the upper side.
China:
The key events that brought about changes in China’s economy were the introduction of
various reforms like marketisation and decentralisation to stimulate economic growth in the
late 70’s, implementation of second wave of reforms in the 90’s, entry in WTO in 2001 and
the global economic crisis. There was a shift in government policies in favour of labourintensive manufacturing industries rather than capital-intensive heavy industries. This was
fruitful for the economy as abundance of labour was optimised to give China an advantage
in manufacturing. Owing to this an accelerated growth of net exports is seen, which is the
key driver of economy there. The rapid economic growth has allowed all three components
to increase simultaneously. The decentralization and the declining role of state-owned
enterprises have contributed to the decreasing relative size of government expenditure.
e)
4.
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Assignment 4
a)
See spreadsheet
b)
c)
The proportion of spending has seen an overall decrease over time when it comes to
household consumption for both India and China. The blue line indicates the same in both
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Assignment 4
the charts. Proportion of general government final consumption expenditure has seen a very
slight rise from the year 1970 to 2000 in both countries while it has remained somewhat
constant after that. The trend can be visualised by observing the orange line on the charts.
d)
Compared to the charts in Question 3, the charts we see in Question 4 show a clearer
picture of how every component of GDP actually varied with the GDP. The minute peaks and
troughs observed in the charts of this question are absent in the ones in the previous
question which only shows the gradual trend of only the component and not the trend with
respect to GDP. This is where we have an advantage at a glance.
5.
a)
See spreadsheet.
b)
c)
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Assignment 4
With respect to the household consumption, the developed countries (Austria, Belgium and
Denmark) spend moderately compared to the countries in economic transition (Albania,
Montenegro and Kazakhstan) and the developing countries (India, China and Mexico) which
spend more, overall. The proportion of the general government final consumption
expenditure with respect to GDP is greater than 0.5 for both the developed and developing
countries but less than that of the countries in economic transition, on the whole.
6.
a)
The GDP per capita is a useful measure of material wellbeing for the following reasons:
1. It is not just a raw number like GDP but takes into account the population of the
nation too and how well-off each member might ideally be.
2. Once you know the GDP and the population count, the GDP per capita is easy to
calculate and draw conclusions.
3. Knowing the cost of goods in a market and whether the average individual in the
population can afford it if they want is an ideally good measure of material
wellbeing. GDP per capita can help there.
Listed below are some limitations of GDP per capita as a measure of material well-being:
1. Household work is not accounted for because no monetary value has been
recognized for it.
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Assignment 4
2. Sustainability is overlooked in the sense that we count the profit from activities
that give us certain resources like wood from trees but we fail to estimate the
damage it may cause to our environment in the future.
3. It tells us how well-off each individual must ideally be, while in reality the
distribution of material wellbeing that GDP per capita measures, varies significantly
across a population.
b)
Taking into account the contents of the articles, GDP per capita seems to be an acceptable
measure of material wellbeing but may not necessarily imply overall wellbeing. It can
measure how well we are doing in terms of economic transactions we successfully carry out,
but it cannot at a particular point in time measure how well we are actually doing. While it
can measure "commodities" it overlooks "capabilities", as is written in the article.
Psychological surveys could say something totally different from what GDP per capita might
say about how well we are doing. So it would be only appropriate to not mix this measure of
material wellbeing with overall wellbeing.
4.2
1.
The indicators mentioned can never be completely dependable because there is always a
shortcoming while obtaining those readings. We can evaluate how significant they are in
determining the measure of the dimension ‘a decent standard of living’.
 The life expectancy of a person is dependent multiple factors, such as quality of life,
healthcare and even access to documentation for maintaining proper records.
 Expected and mean years of schooling do not tell us about the quality of education, or
the job quality expected after said education has been given. Thus, it is redundant in
estimating the quality of life.
 Life expectancy can be affected by genetic factors, working environment, access to
medical equipment and so on. Hence, it is not very dependable.
 GNI (and its variants) is comparatively better and more dependable. Since this is more
accurate than GDP, and money is usually associated with a decent living standard, it is
widely used.
2.
The tables given on page 2 of the technical notes are as follows:
12
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Assignment 4
We have been given the formula:-
According to the above table, the values (minimum and maximum) are justified. The
difference between them is an indicator of the variance of that resource between the more
and less fortunate people of the country.
If we put the given values in the formula, we get the following results:
Dimension
Health
Education
Standard of living
Index
0.846154
0.792778
0.116903
This allows us to compare the different indicators to each other after being normalized.
3.
a)
This is the Dimension index for Health.
Country
Minimum
Maximum
Mean
Dimension Index
Norway
Ireland
Switzerland
Hong Kong, China (SAR)
Iceland
20
20
20
20
20
85
85
85
85
85
82.4
82.3
83.8
84.9
83.0
0.96
0.958615385
0.981230769
0.997846154
0.969076923
Germany
20
85
81.3
0.943538462
Sweden
20
85
82.8
0.966153846
Australia
20
85
83.4
0.976
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Assignment 4
Netherlands
20
85
82.3
0.958153846
Denmark
20
85
80.9
0.936923077
Finland
20
85
81.9
0.952461538
Singapore
20
85
83.6
0.978769231
United Kingdom
20
85
81.3
0.943384615
Belgium
20
85
81.6
0.948153846
New Zealand
20
85
82.3
0.958307692
Canada
20
85
82.4
0.960461538
United States
20
85
78.9
0.905538462
Austria
20
85
81.5
0.946769231
Israel
20
85
83.0
0.968769231
Japan
20
85
84.6
0.994307692
Liechtenstein
20
85
80.7
0.933384615
Slovenia
20
85
81.3
0.943384615
Korea (Republic of)
20
85
83.0
0.969692308
Luxembourg
20
85
82.3
0.957692308
Spain
20
85
83.6
0.978
France
20
85
82.7
0.964
Czechia
20
85
79.4
0.913538462
Malta
20
85
82.5
0.962
Estonia
20
85
78.8
0.903846154
Italy
20
85
83.5
0.977076923
United Arab Emirates
20
85
78.0
0.891846154
Greece
20
85
82.2
0.957538462
Cyprus
20
85
81.0
0.938153846
Lithuania
20
85
75.9
0.860461538
Poland
20
85
78.7
0.903538462
Andorra
20
85
81.9
0.952461538
Latvia
20
85
75.3
0.850615385
Portugal
20
85
82.1
0.954615385
Slovakia
20
85
77.5
0.885230769
Hungary
20
85
76.9
0.875076923
Saudi Arabia
20
85
75.1
0.848153846
Bahrain
20
85
77.3
0.881384615
Chile
20
85
80.2
0.925846154
Croatia
20
85
78.5
0.899846154
Qatar
20
85
80.2
0.926615385
Argentina
20
85
76.7
0.871846154
Brunei Darussalam
20
85
75.9
0.859384615
Montenegro
20
85
76.9
0.875076923
Romania
20
85
76.1
0.862307692
Palau
20
85
73.9
0.829692308
Kazakhstan
20
85
73.6
0.824615385
Russian Federation
20
85
72.6
0.808923077
Belarus
20
85
74.8
0.842923077
Turkey
20
85
77.7
0.887538462
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Assignment 4
Uruguay
20
85
77.9
0.890923077
Bulgaria
20
85
75.1
0.846923077
Panama
20
85
78.5
0.900153846
Bahamas
20
85
73.9
0.829538462
Barbados
20
85
79.2
0.910615385
Oman
20
85
77.9
0.890153846
Georgia
20
85
73.8
0.827230769
Costa Rica
20
85
80.3
0.927384615
Malaysia
20
85
76.2
0.864
Kuwait
20
85
75.5
0.853692308
Serbia
20
85
76.0
0.861538462
Mauritius
20
85
75.0
0.846
Seychelles
20
85
73.4
0.821538462
Trinidad and Tobago
20
85
73.5
0.823230769
Albania
20
85
78.6
0.901076923
Cuba
20
85
78.8
0.904615385
Iran (Islamic Republic of)
20
85
76.7
0.872
Sri Lanka
20
85
77.0
0.876615385
Bosnia and Herzegovina
20
85
77.4
0.883076923
Grenada
20
85
72.4
0.806153846
Mexico
20
85
75.1
0.846923077
Saint Kitts and Nevis
20
85
74.8
0.842461538
Ukraine
20
85
72.1
0.801076923
Antigua and Barbuda
20
85
77.0
0.877230769
Peru
20
85
76.7
0.872923077
Thailand
20
85
77.2
0.879230769
Armenia
20
85
75.1
0.847538462
North Macedonia
20
85
75.8
0.858461538
Colombia
20
85
77.3
0.881384615
Brazil
20
85
75.9
0.859692308
China
20
85
76.9
0.875538462
Ecuador
20
85
77.0
0.877076923
Saint Lucia
20
85
76.2
0.864615385
Azerbaijan
20
85
73.0
0.815538462
Dominican Republic
20
85
74.1
0.832
Moldova (Republic of)
20
85
71.9
0.798461538
Algeria
20
85
76.9
0.875076923
Lebanon
20
85
78.9
0.906615385
Fiji
20
85
67.4
0.729846154
Dominica
20
85
78.2
0.895538462
Maldives
20
85
78.9
0.906461538
Tunisia
20
85
76.7
0.872307692
Saint Vincent and the
Grenadines
Suriname
20
85
72.5
0.808153846
20
85
71.7
0.795076923
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Assignment 4
Mongolia
20
85
69.9
0.767230769
Botswana
20
85
69.6
0.762923077
Jamaica
20
85
74.5
0.838153846
Jordan
20
85
74.5
0.838923077
Paraguay
20
85
74.3
0.834615385
Tonga
20
85
70.9
0.783230769
Libya
20
85
72.9
0.814
Uzbekistan
20
85
71.7
0.795846154
Bolivia (Plurinational State of)
20
85
71.5
0.792461538
Indonesia
20
85
71.7
0.795692308
Philippines
20
85
71.2
0.788153846
Belize
20
85
74.6
0.840307692
Samoa
20
85
73.3
0.820307692
Turkmenistan
20
85
68.2
0.741384615
Venezuela (Bolivarian
Republic of)
South Africa
20
85
72.1
0.800923077
20
85
64.1
0.678923077
Palestine, State of
20
85
74.1
0.831538462
Egypt
20
85
72.0
0.799846154
Marshall Islands
20
85
74.1
0.832461538
Viet Nam
20
85
75.4
0.852307692
Gabon
20
85
66.5
0.714923077
Kyrgyzstan
20
85
71.5
0.791538462
Morocco
20
85
76.7
0.872
Guyana
20
85
69.9
0.767846154
Iraq
20
85
70.6
0.778461538
El Salvador
20
85
73.3
0.820307692
Tajikistan
20
85
71.1
0.786153846
Cabo Verde
20
85
73.0
0.815076923
Guatemala
20
85
74.3
0.835384615
Nicaragua
20
85
74.5
0.838307692
Bhutan
20
85
71.8
0.796615385
Namibia
20
85
63.7
0.672461538
India
20
85
69.7
0.764
Honduras
20
85
75.3
0.850307692
Bangladesh
20
85
72.6
0.809076923
Kiribati
20
85
68.4
0.744153846
Sao Tome and Principe
20
85
70.4
0.775230769
Micronesia (Federated States
of)
Lao People's Democratic
Republic
Eswatini (Kingdom of)
20
85
67.9
0.736615385
20
85
67.9
0.737230769
20
85
60.2
0.618307692
Ghana
20
85
64.1
0.678
Vanuatu
20
85
70.5
0.776461538
Timor-Leste
20
85
69.5
0.761538462
16
HS221
Assignment 4
Nepal
20
85
70.8
0.781230769
Kenya
20
85
66.7
0.718461538
Cambodia
20
85
69.8
0.766461538
Equatorial Guinea
20
85
58.7
0.596
Zambia
20
85
63.9
0.675230769
Myanmar
20
85
67.1
0.725076923
Angola
20
85
61.2
0.633076923
Congo
20
85
64.6
0.685692308
Zimbabwe
20
85
61.5
0.638307692
Solomon Islands
20
85
73.0
0.815384615
Syrian Arab Republic
20
85
72.7
0.810769231
Cameroon
20
85
59.3
0.604461538
Pakistan
20
85
67.3
0.727230769
Papua New Guinea
20
85
64.5
0.684615385
Comoros
20
85
64.3
0.681846154
Mauritania
20
85
64.9
0.691230769
Benin
20
85
61.8
0.642615385
Uganda
20
85
63.4
0.667230769
Rwanda
20
85
69.0
0.754153846
Nigeria
20
85
54.7
0.533692308
Côte d'Ivoire
20
85
57.8
0.581230769
Tanzania (United Republic of)
20
85
65.5
0.699384615
Madagascar
20
85
67.0
0.723692308
Lesotho
20
85
54.3
0.528153846
Djibouti
20
85
67.1
0.724769231
Togo
20
85
61.0
0.631384615
Senegal
20
85
67.9
0.737538462
Afghanistan
20
85
64.8
0.689692308
Haiti
20
85
64.0
0.676923077
Sudan
20
85
65.3
0.697076923
Gambia
20
85
62.1
0.646923077
Ethiopia
20
85
66.6
0.716923077
Malawi
20
85
64.3
0.680923077
Congo (Democratic Republic
of the)
Guinea-Bissau
20
85
60.7
0.625846154
20
85
58.3
0.589538462
Liberia
20
85
64.1
0.678461538
Guinea
20
85
61.6
0.64
Yemen
20
85
66.1
0.709692308
Eritrea
20
85
66.3
0.712615385
Mozambique
20
85
60.9
0.628461538
Burkina Faso
20
85
61.6
0.639692308
Sierra Leone
20
85
54.7
0.533846154
Mali
20
85
59.3
0.604769231
Burundi
20
85
61.6
0.639692308
17
HS221
Assignment 4
South Sudan
20
85
57.9
0.582307692
Chad
20
85
54.2
0.526769231
Central African Republic
20
85
53.3
0.512
Niger
20
85
62.4
0.652615385
Korea (Democratic People's
Rep. of)
Monaco
20
85
72.3
0.804153846
20
85
..
-
Nauru
20
85
..
-
San Marino
20
85
..
-
Somalia
20
85
57.4
0.575384615
Tuvalu
20
85
..
-
Very high human
development
High human development
20
85
79.6
0.916787506
20
85
75.3
0.851007334
Medium human development
20
85
69.3
0.758454896
Low human development
20
85
61.4
0.637571244
Developing countries
20
85
71.3
0.788970552
Arab States
20
85
72.1
0.801262619
East Asia and the Pacific
20
85
75.4
0.853067087
Europe and Central Asia
20
85
74.4
0.837049865
Latin America and the
Caribbean
South Asia
20
85
75.6
0.855018408
20
85
69.9
0.768436135
Sub-Saharan Africa
20
85
61.5
0.639094732
Least developed countries
20
85
65.3
0.697625081
Small island developing states
20
85
72.0
0.800070808
Organization for Economic
Co-operation and
Development
World
20
85
80.4
0.928495748
20
85
72.8
0.811576402
Regions
A3)
b)
This is the index value for education.
Country
Index value
Norway
Ireland
Switzerland
0.9
0.9
0.9
18
HS221
Assignment 4
Hong Kong, China (SAR)
Iceland
Germany
Sweden
Australia
Netherlands
Denmark
Finland
Singapore
United Kingdom
Belgium
New Zealand
Canada
United States
Austria
Israel
Japan
Liechtenstein
Slovenia
Korea (Republic of)
Luxembourg
Spain
France
Czechia
Malta
Estonia
Italy
United Arab Emirates
Greece
Cyprus
Lithuania
Poland
Andorra
Latvia
Portugal
Slovakia
Hungary
Saudi Arabia
Bahrain
Chile
Croatia
Qatar
Argentina
Brunei Darussalam
Montenegro
Romania
0.9
1.0
0.9
1.0
1.0
0.9
0.9
1.0
0.8
0.9
1.0
0.9
0.9
0.9
0.9
0.9
0.9
0.8
0.9
0.9
0.8
0.8
0.8
0.9
0.8
0.9
0.8
0.8
0.8
0.8
0.9
0.9
0.7
0.9
0.8
0.8
0.8
0.8
0.8
0.8
0.8
0.7
0.9
0.7
0.8
0.8
19
HS221
Assignment 4
Palau
Kazakhstan
Russian Federation
Belarus
Turkey
Uruguay
Bulgaria
Panama
Bahamas
Barbados
Oman
Georgia
Costa Rica
Malaysia
Kuwait
Serbia
Mauritius
Seychelles
Trinidad and Tobago
Albania
Cuba
Iran (Islamic Republic of)
Sri Lanka
Bosnia and Herzegovina
Grenada
Mexico
Saint Kitts and Nevis
Ukraine
Antigua and Barbuda
Peru
Thailand
Armenia
North Macedonia
Colombia
Brazil
China
Ecuador
Saint Lucia
Azerbaijan
Dominican Republic
Moldova (Republic of)
Algeria
Lebanon
Fiji
Dominica
0.9
0.8
0.8
0.8
0.7
0.8
0.8
0.7
0.7
0.8
0.7
0.9
0.7
0.7
0.6
0.8
0.7
0.0
0.7
0.7
0.7
0.8
0.8
0.7
0.7
0.8
0.7
0.7
0.8
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.6
0.8
0.6
20
HS221
Assignment 4
Maldives
Tunisia
Saint Vincent and the Grenadines
Suriname
Mongolia
Botswana
Jamaica
Jordan
Paraguay
Tonga
Libya
Uzbekistan
Bolivia (Plurinational State of)
Indonesia
Philippines
Belize
Samoa
Turkmenistan
Venezuela (Bolivarian Republic of)
South Africa
Palestine, State of
Egypt
Marshall Islands
Viet Nam
Gabon
Kyrgyzstan
Morocco
Guyana
Iraq
El Salvador
Tajikistan
Cabo Verde
Guatemala
Nicaragua
Bhutan
Namibia
India
Honduras
Bangladesh
Kiribati
Sao Tome and Principe
Micronesia (Federated States of)
Lao People's Democratic Republic
Eswatini (Kingdom of)
Ghana
0.6
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.6
0.8
0.6
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.6
0.7
0.6
0.7
0.0
0.7
0.6
0.6
0.6
0.6
0.7
0.6
0.5
0.6
0.5
0.6
0.6
0.5
0.5
0.6
0.6
0.6
0.5
0.6
0.6
21
HS221
Assignment 4
Vanuatu
Timor-Leste
Nepal
Kenya
Cambodia
Equatorial Guinea
Zambia
Myanmar
Angola
Congo
Zimbabwe
Solomon Islands
Syrian Arab Republic
Cameroon
Pakistan
Papua New Guinea
Comoros
Mauritania
Benin
Uganda
Rwanda
Nigeria
Côte d'Ivoire
Tanzania (United Republic of)
Madagascar
Lesotho
Djibouti
Togo
Senegal
Afghanistan
Haiti
Sudan
Gambia
Ethiopia
Malawi
Congo (Democratic Republic of the)
Guinea-Bissau
Liberia
Guinea
Yemen
Eritrea
Mozambique
Burkina Faso
Sierra Leone
Mali
0.6
0.5
0.5
0.5
0.5
0.5
0.6
0.5
0.5
0.5
0.6
0.5
0.4
0.5
0.4
0.4
0.5
0.0
0.4
0.5
0.5
0.5
0.5
0.5
0.4
0.5
0.5
0.3
0.5
0.3
0.4
0.5
0.3
0.4
0.3
0.5
0.5
0.4
0.4
0.4
0.4
0.3
0.4
0.3
0.4
0.3
22
HS221
Assignment 4
Burundi
South Sudan
Chad
Central African Republic
Niger
0.4
0.3
0.3
0.4
0.2
Human development groups
Very high human development
High human development
Medium human development
Low human development
0.0
0.9
0.7
0.5
0.4
0.0
0.6
0.0
0.0
0.6
0.6
0.8
0.7
0.5
0.5
0.0
0.4
0.6
0.0
Developing countries
Regions
Arab States
East Asia and the Pacific
Europe and Central Asia
Latin America and the Caribbean
South Asia
Sub-Saharan Africa
Least developed countries
Small island developing states
Organisation for Economic Co-operation
and Development
0.9
A3)
c) This is the dimension index value for decent standard of living.
Country
Norway
Ireland
Switzerland
Hong Kong, China (SAR)
Iceland
Germany
Sweden
Australia
Netherlands
Denmark
Finland
Singapore
Index value
0.98182
0.98602
0.98826
0.97363
0.95227
0.95401
0.95179
0.93285
0.96041
0.96289
0.93419
1.02441
23
HS221
Assignment 4
United Kingdom
Belgium
New Zealand
Canada
United States
Austria
Israel
Japan
Liechtenstein
Slovenia
Korea (Republic of)
Luxembourg
Spain
France
Czechia
Malta
Estonia
Italy
United Arab Emirates
Greece
Cyprus
Lithuania
Poland
Andorra
Latvia
Portugal
Slovakia
Hungary
Saudi Arabia
Bahrain
Chile
Croatia
Qatar
Argentina
Brunei Darussalam
Montenegro
Romania
Palau
Kazakhstan
Russian Federation
Belarus
Turkey
Uruguay
Bulgaria
Panama
Bahamas
0.92639
0.94492
0.90803
0.93424
0.97563
0.95640
0.90575
0.91573
1.08428
0.89761
0.91612
0.99532
0.90868
0.92996
0.89773
0.90335
0.88921
0.91518
0.98400
0.86237
0.89812
0.88828
0.86955
0.95587
0.86300
0.88035
0.87187
0.86814
0.93099
0.91428
0.82316
0.85154
1.03155
0.80907
0.97596
0.81056
0.85904
0.79509
0.82051
0.84088
0.78894
0.84954
0.80082
0.82357
0.85935
0.87937
24
HS221
Assignment 4
Barbados
Oman
Georgia
Costa Rica
Malaysia
Kuwait
Serbia
Mauritius
Seychelles
Trinidad and Tobago
Albania
Cuba
Iran (Islamic Republic of)
Sri Lanka
Bosnia and Herzegovina
Grenada
Mexico
Saint Kitts and Nevis
Ukraine
Antigua and Barbuda
Peru
Thailand
Armenia
North Macedonia
Colombia
Brazil
China
Ecuador
Saint Lucia
Azerbaijan
Dominican Republic
Moldova (Republic of)
Algeria
Lebanon
Fiji
Dominica
Maldives
Tunisia
Saint Vincent and the Grenadines
Suriname
Mongolia
Botswana
Jamaica
Jordan
Paraguay
0.75624
0.83965
0.75102
0.78845
0.84863
0.96270
0.77749
0.83565
-0.69564
0.84513
0.84131
0.74645
0.67322
0.72870
0.73183
0.75559
0.76321
0.79386
0.83427
0.73776
0.80696
0.72632
0.78258
0.74532
0.76535
0.74921
0.74927
0.76718
0.71064
0.75296
0.74411
0.78095
0.74279
0.71240
0.75337
0.73537
0.72171
0.77945
0.70177
0.72786
0.74992
0.70780
0.77071
0.68499
0.69348
0.72597
25
HS221
Assignment 4
Tonga
Libya
Uzbekistan
Bolivia (Plurinational State of)
Indonesia
Philippines
Belize
Samoa
Turkmenistan
Venezuela (Bolivarian Republic of)
South Africa
Palestine, State of
Egypt
Marshall Islands
Viet Nam
Gabon
0.62738
0.76366
0.64479
0.67204
0.71621
0.69224
0.62779
0.62605
0.75596
0.64272
0.72480
0.62863
0.71630
0.59211
0.65082
0.74570
Kyrgyzstan
Morocco
Guyana
Iraq
El Salvador
Tajikistan
Cabo Verde
Guatemala
Nicaragua
Bhutan
Namibia
India
Honduras
Bangladesh
Kiribati
Sao Tome and Principe
Micronesia (Federated States of)
Lao People's Democratic Republic
Eswatini (Kingdom of)
Ghana
Vanuatu
Timor-Leste
Nepal
Kenya
Cambodia
Equatorial Guinea
Zambia
Myanmar
Angola
0.58678
0.64951
0.68717
0.70727
0.66856
0.55546
0.64217
0.67098
0.59927
0.70650
0.68559
0.63472
0.59998
0.59021
0.56673
0.55541
0.55657
0.65043
0.66039
0.59885
0.51896
0.57301
0.53518
0.56616
0.56625
0.74586
0.52933
0.58974
0.62107
26
HS221
Assignment 4
Congo
Zimbabwe
Solomon Islands
Syrian Arab Republic
Cameroon
Pakistan
Papua New Guinea
Comoros
0.50756
0.49592
0.47054
0.54186
0.54051
0.59109
0.56819
0.51870
Mauritania
Benin
Uganda
Rwanda
Nigeria
Côte d'Ivoire
Tanzania (United Republic of)
Madagascar
Lesotho
Djibouti
Togo
Senegal
Afghanistan
Haiti
Sudan
Gambia
Ethiopia
Malawi
Congo (Democratic Republic of the)
Guinea-Bissau
Liberia
Guinea
Yemen
Eritrea
Mozambique
Burkina Faso
Sierra Leone
Mali
Burundi
South Sudan
Chad
Central African Republic
Niger
0.59495
0.52606
0.46156
0.46382
0.58820
0.59299
0.49215
0.41846
0.52117
0.61044
0.41904
0.52860
0.46892
0.42875
0.55061
0.46470
0.46737
0.35297
0.35698
0.45222
0.38254
0.48039
0.41822
0.50300
0.38157
0.46224
0.42509
0.47157
0.30515
0.45277
0.41454
0.34676
0.37547
Regions
Arab States
East Asia and the Pacific
0.92137
0.74919
0.62229
27
HS221
Assignment 4
Europe and Central Asia
Latin America and the Caribbean
South Asia
Sub-Saharan Africa
0.50035
Least developed countries
Small island developing states
0.75556
0.75394
0.78392
0.70420
Organisation for Economic Co-operation and
Development
0.75498
4.
Using the following formula:
We get the calculated value od HDI. This can be compared to the given value of HDI. We can
observe that they are similar.
Country
Calculated HDI
Given HDI
Norway
Ireland
Switzerland
0.95764
0.96197
0.95550
0.957
0.955
0.955
Hong Kong, China (SAR)
0.94896
0.949
Iceland
0.95904
0.949
Germany
0.94694
0.947
Sweden
0.95912
0.945
Australia
0.98008
0.944
Netherlands
0.94850
0.944
Denmark
0.94830
0.940
Finland
0.95089
0.938
Singapore
0.94594
0.938
United Kingdom
0.93239
0.932
Belgium
0.94801
0.931
New Zealand
0.93831
0.931
Canada
0.92929
0.929
United States
0.92649
0.926
Austria
0.92187
0.922
Israel
0.91863
0.919
Japan
0.91863
0.919
Liechtenstein
0.94426
0.919
Slovenia
0.91682
0.917
Korea (Republic of)
0.91592
0.916
Luxembourg
0.91603
0.916
28
HS221
Assignment 4
Spain
0.90392
0.904
France
0.90146
0.901
Czechia
0.90048
0.900
Malta
0.89497
0.895
Estonia
0.89172
0.892
Italy
0.89170
0.892
United Arab Emirates
0.88957
0.890
Greece
0.88841
0.888
Cyprus
0.88658
0.887
Lithuania
0.88212
0.882
Poland
0.88040
0.880
Andorra
0.86848
0.868
Latvia
0.86559
0.866
Portugal
0.86424
0.864
Slovakia
0.86049
0.860
Hungary
0.85444
0.854
Saudi Arabia
0.85410
0.854
Bahrain
0.85249
0.852
Chile
0.85134
0.851
Croatia
0.85111
0.851
Qatar
0.85709
0.848
Argentina
0.84491
0.845
Brunei Darussalam
0.83825
0.838
Montenegro
0.82891
0.829
Romania
0.82757
0.828
Palau
0.82629
0.826
Kazakhstan
0.82510
0.825
Russian Federation
0.82422
0.824
Belarus
0.82296
0.823
Turkey
0.82006
0.820
Uruguay
0.81730
0.817
Bulgaria
0.81603
0.816
Panama
0.81500
0.815
Bahamas
0.81406
0.814
Barbados
0.81369
0.814
Oman
0.81276
0.813
Georgia
0.81210
0.812
Costa Rica
0.80976
0.810
Malaysia
0.81034
0.810
Kuwait
0.80648
0.806
Serbia
0.80628
0.806
Mauritius
0.80440
0.804
Seychelles
0.79589
0.796
Trinidad and Tobago
0.79585
0.796
Albania
0.79478
0.795
29
HS221
Assignment 4
Cuba
0.78348
0.783
Iran (Islamic Republic of)
0.78332
0.783
Sri Lanka
0.78234
0.782
Bosnia and Herzegovina
0.77977
0.780
Grenada
0.77945
0.779
Mexico
0.77903
0.779
Saint Kitts and Nevis
0.77929
0.779
Ukraine
0.77860
0.779
Antigua and Barbuda
0.77774
0.778
Peru
0.77691
0.777
Thailand
0.77713
0.777
Armenia
0.77600
0.776
North Macedonia
0.77353
0.774
Colombia
0.76660
0.767
Brazil
0.76470
0.765
China
0.76139
0.761
Ecuador
0.75935
0.759
Saint Lucia
0.75932
0.759
Azerbaijan
0.75553
0.756
Dominican Republic
0.75633
0.756
Moldova (Republic of)
0.74977
0.750
Algeria
0.74821
0.748
Lebanon
0.74447
0.744
Fiji
0.74297
0.743
Dominica
0.74181
0.742
Maldives
0.73973
0.740
Tunisia
0.73958
0.740
Saint Vincent and the Grenadines
0.73836
0.738
Suriname
0.73833
0.738
Mongolia
0.73672
0.737
Botswana
0.73511
0.735
Jamaica
0.73424
0.734
Jordan
0.72927
0.729
Paraguay
0.72830
0.728
Tonga
0.72479
0.725
Libya
0.72395
0.724
Uzbekistan
0.72039
0.720
Bolivia (Plurinational State of)
0.71800
0.718
Indonesia
0.71825
0.718
Philippines
0.71797
0.718
Belize
0.71572
0.716
Samoa
0.71539
0.715
Turkmenistan
0.71540
0.715
Venezuela (Bolivarian Republic of)
0.71146
0.711
South Africa
0.70906
0.709
Palestine, State of
0.70768
0.708
30
HS221
Assignment 4
Egypt
0.70744
0.707
Marshall Islands
0.70372
0.704
Viet Nam
0.70433
0.704
Gabon
0.70254
0.703
Kyrgyzstan
0.69742
0.697
Morocco
0.68576
0.686
Guyana
0.68175
0.682
Iraq
0.67433
0.674
El Salvador
0.67267
0.673
Tajikistan
0.66772
0.668
Cabo Verde
0.66525
0.665
Guatemala
0.66279
0.663
Nicaragua
0.66011
0.660
Bhutan
0.65374
0.654
Namibia
0.64570
0.646
India
0.64545
0.645
Honduras
0.63359
0.634
Bangladesh
0.63234
0.632
Kiribati
0.63038
0.630
Sao Tome and Principe
0.62499
0.625
Micronesia (Federated States of)
0.61988
0.620
Lao People's Democratic Republic
0.61346
0.613
Eswatini (Kingdom of)
0.61058
0.611
Ghana
0.61126
0.611
Vanuatu
0.60933
0.609
Timor-Leste
0.60610
0.606
Nepal
0.60187
0.602
Kenya
0.60104
0.601
Cambodia
0.59448
0.594
Equatorial Guinea
0.59230
0.592
Zambia
0.58399
0.584
Myanmar
0.58334
0.583
Angola
0.58131
0.581
Congo
0.57385
0.574
Zimbabwe
0.57061
0.571
Solomon Islands
0.56668
0.567
Syrian Arab Republic
0.56742
0.567
Cameroon
0.56313
0.563
Pakistan
0.55692
0.557
Papua New Guinea
0.55465
0.555
Comoros
0.55434
0.554
Mauritania
0.54614
0.546
Benin
0.54466
0.545
Uganda
0.54400
0.544
31
HS221
Assignment 4
Rwanda
0.54311
0.543
Nigeria
0.53903
0.539
Côte d'Ivoire
0.53839
0.538
Tanzania (United Republic of)
0.52855
0.529
Madagascar
0.52796
0.528
Lesotho
0.52719
0.527
Djibouti
0.52406
0.524
Togo
0.51518
0.515
Senegal
0.51215
0.512
Afghanistan
0.51145
0.511
Haiti
0.50956
0.510
Sudan
0.50954
0.510
Gambia
0.49606
0.496
Ethiopia
0.48520
0.485
Malawi
0.48338
0.483
Congo (Democratic Republic of the)
0.48019
0.480
Guinea-Bissau
0.47963
0.480
Liberia
0.48007
0.480
Guinea
0.47737
0.477
Yemen
0.47020
0.470
Eritrea
0.45857
0.459
Mozambique
0.45588
0.456
Burkina Faso
0.45205
0.452
Sierra Leone
0.45165
0.452
Mali
0.43352
0.434
Burundi
0.43341
0.433
South Sudan
0.43263
0.433
Chad
0.39780
0.398
Central African Republic
0.39720
0.397
Niger
0.39372
0.394
Human development groups
0.00000
Very high human development
0.89831
0.898
High human development
0.75296
0.753
Medium human development
0.63056
0.631
Low human development
0.51309
0.513
Developing countries
0.68939
0.689
Arab States
0.70505
0.705
East Asia and the Pacific
0.74664
0.747
Europe and Central Asia
0.79065
0.791
Latin America and the Caribbean
0.76616
0.766
South Asia
0.64081
0.641
Sub-Saharan Africa
0.54746
0.547
Regions
32
HS221
Assignment 4
0.00000
Least developed countries
0.53802
0.538
Small island developing states
0.73181
0.728
Organisation for Economic Co-operation and
Development
0.90025
World
0.73685
0.900
0.737
7.
(a)
(b)
The graph clearly shows some pattern between the two quantities i.e., GDP per capita rank
and HDI rank. This implies that in addition to income, GDP is also linked with health and
education factors due to its correlation with HDI rank.
(c)
There are many possible criterions to define a ‘high’ GDP per capita but due to lack of
further information and for the sake of simplicity, let us consider it to be the GDP per capita
that lies above the middle-valued rank. Therefore, the required table becomes:
Low
GDP per Capita
High
HDI
Low
Chad
Liberia
Sudan
Libya
Turkmenistan
Botswana
High
Cuba
Armenia
Georgia
Norway
Switzerland
Singapore
33
HS221
Assignment 4
(d)
GDP per capita measures the well-being of a person solely on their economic output (or the
income earned) whereas HDI additionally measures the well-being of a person in terms of
income (natural log), health and education. Thus, one big difference is that, in the words of
GDP, the well-being is directly proportional to income earned whereas in HDI terms, all we
can say is that the well-being increases with an increase in income (might have a further
diminishing or increasing effect).
8.
(a)
Weaknesses:
HDI fails to capture the short-term advancements in the society. Furthermore, it
doesn’t consider gender and other inequality related issues.
Strengths:
As mentioned in the answer for Q7(d), HDI is a better measure of well-being as it
considers education as well as health factors other than income unlike GDP per
capita.
(b)
Other possible measures:
 Mental health measures:
Often mental health is disregarded from ‘mainstream health issues’.
This can result in people becoming lethargic in the long run and
hence unproductive along with a degraded well-being.
 Unemployment measures:
Due to the increasing human population, there is an increasing
struggle to be employed and this affects a wide range of people.
 Social and Gender discrimination issues:
Often being as qualified is not sufficient as many inappropriate
social norms exclude a certain section of the society from
participating in certain economic activities which leads to their
degraded well-being.
 Advancements in innovation and research:
An increase in technological advancements in any field leads to
making peoples’ lives easier and thereby an increase d well-being.
34