Updating the economic vulnerability index

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Version 4
UPDATING AND AUGMENTING THE ECONOMIC
VULNERABILITY INDEX1
Lino Briguglio2 and Waldemar Galea3
1. INTRODUCTION
The economic vulnerability index (EcVI)4 was initially developed to explain the seeming
contradiction that a country can be economically vulnerable and yet register a relatively high
GDP per capita.5 Many versions of the index were produced, principally by Briguglio (1992,
1993, 1995, 1997), the Commonwealth Secretariat6 and Crowards (1998 and 1999). The
general conclusion that emerged from these studies is the small island developing states, as a
group, tend to be more economically vulnerable than other groups of countries.7
The characteristics of small island developing states (SIDS) are well documented (see for
example, Briguglio, 1995), and include limited ability to exploit economies of scale; lack of
natural resource endowments and a high import content (especially of strategic imports such as
food and fuel). Other characteristics relate to limitations of diversification possibilities;
dependence on a narrow range of exports; limitations on the extent to which domestic
competition policy can be applied; inability to influence international prices; and in the case of
1 This study is being published as an Occasional Paper by the Islands ands Small States Institute of the
University of Malta. It is for discussion only and is not to be quoted at this stage without the prior
permission of the authors.
2 Head and Professor, Economics Department, University of Malta.
3 When this paper was written, Waldemar Galea was a fourth year student of economics, who wrote a
thesis on economic vulnerability under the supervision of Professor Lino Briguglio
4 The term EcVI is being used not to be confused with EVI the term used for the Environmental
Vulnerability Index.
5 The idea of constructing the vulnerability index first occurred to Lino Briguglio during a conference held
in Malta in 1985 on the economic development of small countries, where it was shown that many fragile
economies were registering relatively high GDP per capita. The index was actually developed in the run-up
of the Barbados Global Conference on the Sustainable Development of Small Island Developing States, as
a tool to draw the attention of the international community to the vulnerability of SIDS. When the General
Assembly, at its 47th session, resolved to convene this SIDS Global Conference (A/Res/47/189 of 10 March
1993), which was subsequently held in Barbados in April 1994, the Vulnerability Index featured
prominently in the Programme of Action (BPoA) for the Sustainable Development of Small Island
Developing States (A/CONF.167/9). The BPoA was endorsed by the General Assembly in 1994 in its
resolution 49/122 of 19 December 1994, with Paragraphs 113 and 114 calling for the development of a
vulnerability index for small island developing States.
6 See Atkins et al (1998 and 2001), Easter (1998) Chander (1996) and Wells (1997). All Economic
Vulnerability Indices which has been produced so far arrive at the conclusion that small states (most of
which are SIDS) are among the most vulnerable countries.
7 An expert group meeting held at the United Nations Headquarters in December 1997, after reviewing the
vulnerability indices produced until then, also concluded that SIDS, tend to more vulnerable, as a group,
than other groups of countries.

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island states, high international transport costs and uncertainties of industrial supplies due to
insularity and remoteness.
Small size also creates problems associated with public administration, the most important of
which is probably the small manpower resource base from which to draw experienced and
efficient administrators. Another problem is that many government functions tend to be very
expensive per capita when the population is small, due to the fact that certain expenses are not
divisible in proportion to the number of users.
2. ECONOMIC VULNERABILITY AND RESILIENCE
There are features which lead to inherent economic vulnerability of SIDS. Such vulnerability
arises from the fact that the economies of SIDS are, to a large extent, shaped by forces outside
their control, mostly due to their high degrees of economic openness and export concentration,
and high dependence on strategic imports.
Although economic vulnerability poses serious constraints, many SIDS have managed to attain
relatively high GDP per capita, possibly because they have taken steps to build up resilience in
order to cope with and withstand their inherent vulnerability. Thus economic vulnerability need
not necessarily lead to poverty or underdevelopment. However economic backwardness may be
associated with limited ability to build economic resilience.
Recently, there has been considerable debate on building resilience in SIDS.8 This issue is
important because it carries the message that these states should not be complacent in the
face of their inherent vulnerability. In other words they should adopt measures, possibly
supported by the international community, to strengthen their economic, environmental and
social resilience.
In addition, the discussion on resilience sheds light as to why a number of vulnerable SIDS
have managed to achieve a notable level of economic development in spite of their economic
vulnerability. Reference is made here to the “Singapore Paradox” where an inherently
economically vulnerable small state has managed to cope with its vulnerability through
deliberate economic development policies.
8 See proceedings of the “Global Roundtable on Vulnerability and Small Island Developing States:
Exploring Mechanisms for Partnerships”, Montego Bay, Jamaica, 9-10 May, 2002, particularly the papers
Witter, Briguglio, and Bhuglah (2002) and UWICED (2002).

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2.1 Some definitions
It is important to define terms at this stage, because there is a certain degree of confusion as
to what constitute economic vulnerability.
Economic vulnerability
For the purpose of this paper, the term “economic vulnerability” refers to inherent, permanent
or quasi-permanent features of a country which render that country exposed to a very high
degree to economic forces outside its control.
It should be noted here, that economic vulnerability can also be policy-induced and therefore
not inherent or permanent. For the purpose of this paper, policy induced vulnerability is being
treated as the obverse of “resilience” in the sense that countries adopting policies which
exacerbate their inherent vulnerability, render themselves less resilient.
Economic resilience
The term “economic resilience” as used in this paper, refers to a country’s ability to
economically cope with or withstand its inherent vulnerability, as a result of some deliberate
policy. As is the case of vulnerability, resilience may also be inherent or nurtured. The inherent
aspect of resilience may be considered as the obverse of vulnerability, in the sense that
countries that inherently lack economic resilience are economically vulnerable. Nurtured
resilience on the other hand, is that which can be developed and managed, often as a result of
deliberate policy.
Four Possible Scenarios
On the basis of these definitions, we can therefore consider 4 possible scenarios with regard to
vulnerability and resilience as follows:
Countries that adopt
policies to withstand
vulnerability
Countries that adopt
polices that
exacerbate
vulnerability
Inherently vulnerable
countries
The “self-made”
scenario
Worst case scenario
Inherently resilient
countries
Best case scenario
The “prodigal son”
scenario

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This method of defining vulnerability in terms of inherent features and resilience in terms of
policy measures has a number of advantages, including:
(1) the vulnerability measurement would refer to features on which a state has little or not
control and therefore cannot be attributed to bad governance. In other words, a country with
high inherent vulnerability score cannot be blamed that is has self-inflicted vulnerability.
(2) The resilience component would refer to what a country can do. In this regard, the
international donor community can be a source of support to enable vulnerable countries build
up their resilience.
2. What constitutes economic vulnerability?
The principal variables which have been used as components of the EcVI in the context of SIDS
are (a) economic openness, (b) export concentration (c) peripherality and (d) dependence on
strategic imports.
Economic openness
Economic openness captures the degree to which a state is susceptible to economic conditions
in the rest of the world. It is often measured as the ratio of exports or imports, or an average
of both, as a percentage of GDP. In the computation which follows, the openness index takes
an average of imports and exports.
Dependence on a narrow range of exports
The range of exports captures the extent to which a country lacks export diversification, a
condition exacerbating the degree of economic openness. This is usually measured by the
export concentration index devised by UNCTAD, which only covers merchandise. Briguglio
(1997) argued that export concentration can also be observed in the trade in services,
especially in tourism and financial services, and he devised a concentration index with services
exports included. In the computation which follows, the concentration index covers goods and
services.
Peripherality
Peripherality is associated with insularity and remoteness, leading to high transport costs and
marginalization from main commercial centres. This again exacerbates the problem of high
dependence on international trade. The problem with the peripherality variable is that it cannot

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be measured directly by taking the number of kilometres from a main commercial centre, or
from the nearest island or from the nearest continent. In the case of certain islands, a
relatively large proportion of international trade is directed to and from their ex-colonizing
powers, even though other centres of commercial activity could be more proximate. In other
words measuring remoteness by taking distance in kilometres may convey the wrong sort of
information regarding insularity and remoteness, for economic purposes. Two variables which
may reflect the effects of remoteness are (1) the ratio of FOB/CIF factors and (2) the ratio of
transport and freight costs to imports. In the computation which follows, the second ration was
used, since it has been considered to be more meaningful.
Dependence on strategic imports
This variable is intended to measure the extent to which a country’s viability depends on
imports. There are obvious vulnerability connotations when a country depends heavily on
imported energy and industrial supplies for production and on imported food for consumption.
Various indices have been used for this purpose. Briguglio (1997) suggested that this variable
can be measured as average imports of commercial energy as a percentage of domestic energy
production, and this is the index used in the computation presented below.
2.3 Standardising the components
The summation of the variables making up the composite index poses sum problems.9 The
approach taken by Briguglio and Cowards is to standardise the observations, as follows:
i. Subtract the minimum value of a range of observations of a given variable from each
observed value.
ii. Subtract the minimum value from the maximum value of the same range of observations.
iii. Divide the result of (i) by the result of (ii).
iv. Repeat this procedure for all observations of variable X.
The formula for standardising a given observation in an array of observed values for a given
variable is therefore:
(Xi – Min X) / (Max X – Min X)
Where:
Xi is an observed value in an array of observed values for a given variable.
Max X is the highest value in the same array.
Min X is the lowest value in the same array.
9 See Briguglio (1995) and (1997).

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The range of standardised values of variable X will this be between 0 and 1.10
3. UPDATED COMPUTATION OF THE VULNERABILITY INDEX
Below, we present an updated computation of the EcVI, building on Briguglio (1995) and
Briguglio (1997). The results again confirm that SIDS, when compared to other groups of
countries tend to:
• be more exposed to international trade
• have higher export concentration indices
• are more dependent on strategic imports, and
• have relatively higher transport costs than other groups of countries.
These tendencies are shown in Figures 1. The diagrams show the relationships11 between the
variables just described and population size.12
Figure 1: Population Size and Economic Vulnerability Features
Openness Index
0
20
40
60
80
100
120
140
160
34567891011121314
Concentrat ion Index
0
20
40
60
80
100
35791113
10 The Commonwealth Secretariat opted for a different approach, which is based on the Least Square
Method, essentially leading to summing the different components of the index using varying weights,
represented by the estimated coefficients on the individual components.
11 In all cases, the relationship is statistically significantly different from zero
12 SIDS generally have a small population. In the diagram, a population of about 1 million is represented
by a value of 7 on the horizontal axis. Log values of the population are used to compress the population
values, which range from a few thousand to more than 1 billion.

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Energy Dependence
0
2
4
6
8
10
12
14
34567891011121314
Transport Cost s
0
5
10
15
20
25
30
35
40
34567891011121314
These four variables were averaged out, to compute a composite EcVI, and the results obtained
are shown in Figure 2 based on the data shown in Appendix 1.
The results indicate that there is negative relationship13 between population size and economic
vulnerability, as measured by the variables described above.
Fig. 2. The Economic Vulnerability Index (117 Countries)
Openness + Concentration + Energy dependence + Transport costs
0.0
0.2
0.4
0.6
0.8
1.0
1.2
35791113
Table 1 shows the vulnerability scores classified by population size, where it is clear that smaller
countries tend to have higher vulnerability scores than larger ones. This tendency is true for
developed as well as for developing countries.
13 Again here the relationships in statistically significant at the 95% level.

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Table 1: Vulnerability score classified by Population Size
Population
(millions)
Number
of Countries
Vulnerability
Score
0-1 17 .492
1-2 6 .359
2-5 21 .323
5-20 35 .237
20 – 50 17 .184
50 - 100 11 .182
100 – 200 6 .177
200+ 4 .089
Total 117
Table 2 shows the vulnerability score, classified by category of countries. It can be seen that
SIDS register the highest vulnerability score. Other small developing states (OSDS) also register
high scores. Large developing states (LDS), on the other hand, register relatively low
vulnerability scores. The smallest scores as registered by large advanced states (LAS). Of
interest, is that small advanced states (SAS) also register higher scores than LDS.
Table 2: Vulnerability scores classified by Different Categories of Countries
Category Number
of Countries
Vulnerability
Score
SIDS 19 .470
OSDS 20 .354
LDS 56 .220
SAS 5 .258
LAS 17 .148
Total 117
4. ECONOMIC RESILIENCE
There are many factors that could strengthen economic resilience of vulnerable countries,
including:
 improving the competitiveness of the economy
 building a sound macroeconomic environment
 improving governance
 diversifying the economy to reduce excessive reliance on a narrow range of
exports14
 strengthening the transport and communications infrastructure
14 This, however, is not an easy task since there are major constraints with regard to diversification in
small states, principally because this could lead to excessive fragmentation and loss of efficiency.

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It would be useful to construct a resilience index, to complement the EcVI, and to assess the
degree to which economically vulnerable countries, as a group or individually, are moving ahead
or otherwise, in coping with or withstanding economic vulnerability.
Such an index could also be useful for SIDS to identify their weak points with regard to
resilience-building and serve as a monitoring tool in this regard.
Such a resilience index does not exist, and in its absence, we propose that a proxy indicator
could be GDP per capita. This variable may capture a country’s ex-post material success or
otherwise to cope with its inherent vulnerability.15
Although we have not tested the relationship between the resilience factors outlined above and
GDP per capita index, we are assuming that they are closely related.16 GDP per capita is an
attractive index as it is readily available, and can be adjusted for purchasing power standards.
Figure 3 shows that there is no correlation between size and GDP per capita. On average,
however, SIDS register a higher GDP per capita than larger developing countries. This average
however masks many variations, as there some SIDS with a very GDP per capita.
Figure 3. GDP PER CAPITA
We have constructed an index, which combines the EcVI with the GDP per capita index
(standing for economic resilience component, on the basis of data given in Appendix 1), calling
it EVIAR (Economic Vulnerability Index Augmented by Resilience). This result is shown
graphically in Figure 4, which is based on the data given in Appendix 1.
15 This is not a new idea. Briguglio(1995) used this approach to construct the VADI (Vulnerability Adjusted
Development Index). Atkins et al (2001) used total GDP as a form of resilience index.
16 This calls for further study on this issue. A priori, it is plausible to assume that sound macroeconomic
management, economic competitiveness and good governance are indeed correlated with GDP per capita.

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Figure 3. The EcVI (Blue line) and the EVIAR (Red line)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
35791113
The figure reproduces the EcVI, so as to compare it with the EVIAR. It can be seen that the
gradient of the EVIAR is lower than that of the EcVI. This results from the fact that many
vulnerable states have a relatively high GDP per capita.
For example, Singapore ranks 7th on the EcVI, but because it has a high GDP per capita, it
ranks 54th in the EVIAR out of 117 countries. Similarly Malta ranks 5th on the EcVI and 17th
on the EVIAR. This is true of SIDS with a relatively high GDP per capita.
As argued earlier, vulnerability need not result in poverty. There are inherently vulnerable small
states which have adopted policies to withstand their vulnerability. As stated, this suggests that
vulnerable states should not accept their condition as a
fait accompli
as it is possible to build
up resilience to cope with inherent vulnerability.
This fact that some SIDS have strengthened their resilience to withstand vulnerability would
seem to be paradoxical, as SIDS are likely to have very limited resources to build economic
resilience. In reality, these SIDS may have been able to register high GDP per capita in the past
partly due to a number of “props” they enjoyed, including preferential trade arrangements,
attractive incentive packages to attract FDI17, and development assistance from the former
colonising powers. However, contrary to some other states, these SIDS would seem to have
17 SIDS have a number of inherent disadvantages, related to transport course and limited manpower
base, and the incentive package was probable necessary to attract FDI. There is the danger that with the
WTO rules, this tendency could be reversed.

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used these “props” well, to such an extent that such external support may no longer be
needed.
The findings in this paper suggests also that SIDS which currently register relatively low GDP
per capita, and are therefore vulnerable and poor, merit special attention and support by the
donor community, to enable them to strengthen their resilience sustainably.
CONCLUDING CONSIDERATIONS
A number of considerations emerge from the findings presented in this paper.
1. The updated Economic Vulnerability Index produced above has confirmed that SIDS, as a
group, tend to be more economically vulnerable than other groups of countries.
2. Many SIDS are coping well with their inherent vulnerability, possibly due to the wise
governance practices and sound economic management they have adopted in the past.
3. Building of economic resilience to cope with and withstand economic vulnerability should
take centre stage in the sustainable development strategy of vulnerable states, particularly
those SIDS with a low GNP per capita.
4. Towards this end, the donor community may consider stepping up their assistance to SIDS,
so as to enable them to sustainably accelerate their resilience-building.
5. In addition, international organisations may consider granting special treatment to such
states. The WTO in particular should give serious thought to the possibility of allowing a
longer transition period than normal for SIDS, with regard to removal of trade preferences
and dismantling of incentive packages to attract FDI.
REFERENCES
Atkins, J., Mazzi S and Easter, C. (2001),
Small States: A Composite Vulnerability Index
In: Peretz D., Faruqi R and Eliawony J., (eds), Small States in the Global Economy
Commonwealth Secretariat Publication pg 53-92.
Atkins, J., Mazzi S and Ramlogan, C. (1998),
A Study on the Vulnerability of Developing
and Island States: A Composite Index
Issued by the Commonwealth Secretariat, August 1998.

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Briguglio, L. (1992),
Preliminary Study on the Construction of an Index for Ranking Countries
According to their Economic Vulnerability,
UNCTAD/LDC/Misc.4 1992.
Briguglio, L. (1993),
The Economic Vulnerabilities of Small Island Developing States
Study commissioned by CARICOM for the Regional Technical Meeting of the Global Conference
on the Sustainable Development of Small Island Developing States, Port of Spain,
Trinidad and Tobago, July 1993.
Briguglio, L. (1995),
Small Island States and their Economic Vulnerabilities
World
Development Vol.23(9), 1615-1632.
Briguglio, L. (1997),
Alternative Economic Vulnerability Indices for Developing
Countries
,
Report prepared for the Expert Group on Vulnerability Index, United Nations Department
of Economic and Social Affairs-UN(DESA), December 1997.
Briguglio, L. (2002),
The Economic Vulnerability of Small Island Developing States
In:
Sustainable Development for Island Societies: Taiwan and the World, Asia-Pacific
Research Program w/SARCS Secretariat Publication, Taiwan, December 2002
Chander, R. (1996),
Measurement of the Vulnerability of Small States
Report prepared for the
Commonwealth Secretariat, April 1996.
Crowards, T and Coultier, W. (1998),
Economic Vulnerability in the Developing World with
Special Reference to the Caribbean,
Caribbean Development Bank.
Crowards, T. (1999),
An Economic Vulnerability Index , with Special Reference to the
Caribbean: Alternative Methodologies and Provisional Results
, Caribbean Development
Bank, March 1999.
Easter, Christopher D. (1998),
Small States and Development: A Composite Index of
Vulnerability,
Small States: Economic Review and Basic Statistics, Commonwealth
Secretariat, December 1998.
University of the West Indies Centre for Environment and Development (2002)
“Vulnerability and Small Island States,”, UNDP Policy Journal, Vol. 1 (2002).
Wells, J. (1996),
Composite Vulnerability Index: A Preliminary Report
, Commonwealth
Secretariat, London.
Wells, J. (1997),
Composite Vulnerability Index: A Revised Report,
Commonwealth
Secretariat, London.
Witter, M., Briguglio, L. and Bhuglah, A (2002). “Measuring and Managing the Economic
Vulnerability of Small Island Developing States” (
http://www.undp.org/capacity21/docs/Econ-Vulnerability-Paper.doc ).

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APPENDIX 1
Log of
Population
Vulnerability
index
Standardised
GDP per
capita
Standardised EVIAR
ST KITTS AND NEVIS 3.689 0.685 0.827 0.756
DOMINICA 4.295 0.588 0.920 0.754
SEYCHELLES 4.382 1.000 0.837 0.919
GRENADA 4.536 0.645 0.909 0.777
ST VINCENT & GRENADINES 4.700 0.647 0.934 0.790
ST LUCIA 5.011 0.765 0.901 0.833
BELIZE 5.494 0.588 0.937 0.762
BARBADOS 5.598 0.549 0.796 0.672
MALDIVES 5.611 0.948 0.956 0.952
ICELAND 5.623 0.465 0.310 0.387
MALTA 5.958 0.765 0.790 0.778
SURINAME 6.024 0.724 0.963 0.844
CAPE VERDE 6.052 0.950 0.972 0.961
LUXEMBOURG 6.072 0.471 0.000 0.235
CYPRUS 6.625 0.643 0.917 0.780
GUYANA 6.646 0.605 0.982 0.793
MAURITIUS 7.068 0.484 0.915 0.699
TRINIDAD AND TOBAGO 7.147 0.408 0.893 0.651
GAMBIA 7.182 0.708 0.995 0.851
ESTONIA 7.247 0.695 0.918 0.807
SLOVENIA 7.594 0.235 0.781 0.508
MACEDONIA, FYR 7.601 0.296 0.963 0.629
KUWAIT 7.654 0.560 0.675 0.617
MAURITANIA 7.762 0.725 0.992 0.858
OMAN 7.796 0.413 0.846 0.630
LATVIA 7.798 0.550 0.886 0.718
JAMAICA 7.861 0.706 0.935 0.820
PANAMA 7.935 0.640 0.923 0.782
CONGO REPUBLIC OF 7.984 0.654 0.983 0.819
URUGUAY 8.106 0.221 0.857 0.539
ALBANIA 8.149 0.263 0.980 0.622
COSTA RICA 8.202 0.334 0.906 0.620
MOLDOVA 8.202 0.794 0.994 0.894
LITHUANIA 8.212 0.357 0.521 0.439
IRELAND 8.229 0.284 0.494 0.389
ARMENIA 8.242 0.531 0.991 0.761
NEW ZEALAND 8.245 0.245 0.682 0.464
SINGAPORE 8.294 0.743 0.528 0.635
NORWAY 8.403 0.416 0.214 0.315
CROATIA 8.407 0.368 0.899 0.633
TOGO 8.407 0.704 0.995 0.850
PAPUA NEW GUINEA 8.445 0.389 0.985 0.687
KYRGYZ REPUBLIC 8.483 0.526 0.996 0.761
NICARAGUA 8.504 0.442 0.988 0.715
FINLAND 8.550 0.219 0.444 0.332
DENMARK 8.580 0.311 0.277 0.294
PARAGUAY 8.587 0.227 0.968 0.598

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SLOVAK REPUBLIC 8.594 0.273 0.917 0.595
ISRAEL 8.719 0.339 0.617 0.478
EL SALVADOR 8.725 0.277 0.956 0.617
HONDURAS 8.753 0.409 0.982 0.696
JORDAN 8.762 0.555 0.974 0.764
HONG KONG 8.796 0.546 0.443 0.494
SWITZERLAND 8.873 0.136 0.191 0.164
AZERBAIJAN 8.980 0.447 0.990 0.718
AUSTRIA 8.999 0.166 0.430 0.298
BOLIVIA 9.005 0.229 0.979 0.604
SWEDEN 9.089 0.159 0.390 0.274
SENEGAL 9.136 0.355 0.991 0.673
TUNISIA 9.154 0.326 0.954 0.640
PORTUGAL 9.206 0.185 0.753 0.469
HUNGARY 9.217 0.225 0.895 0.560
BELARUS 9.218 0.488 0.977 0.733
NIGER 9.220 0.484 0.999 0.741
BELGIUM 9.233 0.294 0.458 0.376
CZECH REPUBLIC 9.238 0.236 0.881 0.559
GREECE 9.247 0.501 0.737 0.619
GUATEMALA 9.314 0.211 0.963 0.587
ECUADOR 9.426 0.345 0.973 0.659
CAMEROON 9.527 0.304 0.987 0.646
KAZAKHSTAN 9.614 0.327 0.973 0.650
CHILE 9.617 0.290 0.887 0.588
MADAGASCAR 9.649 0.356 0.997 0.676
NETHERLANDS 9.668 0.279 0.444 0.361
COTE D'IVOIRE 9.669 0.401 0.987 0.694
YEMEN, REPUBLIC OF 9.780 0.526 0.994 0.760
GHANA 9.782 0.420 0.994 0.707
AUSTRALIA 9.850 0.141 0.545 0.343
SRI LANKA 9.855 0.318 0.983 0.650
UGANDA 9.881 0.457 0.995 0.726
NEPAL 10.015 0.250 0.997 0.624
ROMANIA 10.020 0.158 0.964 0.561
MALAYSIA 10.031 0.449 0.921 0.685
VENEZUELA 10.074 0.356 0.898 0.627
PERU 10.136 0.186 0.953 0.570
MOROCCO 10.249 0.208 0.974 0.591
SUDAN 10.302 0.260 0.994 0.627
KENYA 10.309 0.391 0.994 0.693
CANADA 10.326 0.089 0.504 0.297
TANZANIA 10.443 0.368 0.997 0.682
ARGENTINA 10.507 0.077 0.821 0.449
POLAND 10.562 0.134 0.909 0.522
SPAIN 10.582 0.192 0.670 0.431
COLOMBIA 10.635 0.194 0.954 0.574
SOUTH AFRICA 10.668 0.113 0.933 0.523
KOREA 10.755 0.225 0.812 0.518
ITALY 10.962 0.062 0.547 0.305
FRANCE 10.984 0.099 0.460 0.279
UNITED KINGDOM 10.992 0.081 0.447 0.264

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ETHIOPIA 11.000 0.543 1.000 0.771
THAILAND 11.030 0.278 0.958 0.618
EGYPT 11.045 0.504 0.970 0.737
IRAN, ISLAMIC REP 11.047 0.389 0.905 0.647
TURKEY 11.083 0.140 0.934 0.537
PHILIPPINES 11.231 0.371 0.981 0.676
GERMANY 11.316 0.076 0.436 0.256
MEXICO 11.496 0.035 0.887 0.461
NIGERIA 11.620 0.518 0.992 0.755
JAPAN 11.749 0.081 0.211 0.146
PAKISTAN 11.809 0.267 0.992 0.630
BANGLADESH 11.810 0.240 0.995 0.617
RUSSIA 11.890 0.184 0.965 0.575
BRAZIL 12.013 0.001 0.917 0.459
INDONESIA 12.243 0.133 0.988 0.561
UNITED STATES 12.516 0.046 0.221 0.134
INDIA 13.794 0.154 0.992 0.573
CHINA, P.R.: MAINLAND 14.051 0.000 0.984 0.492