Corruption Perceptions Index 2003
The CPI 2003 Score
relates to perceptions of the degree of corruption as seen by business people, academics and risk analysts, and ranges between 10 (highly clean) and 0 (highly corrupt). A total of 15 surveys were used from nine independent institutions, and at least three surveys were required for a country to be included in the CPI.Go to:
National IQ differences - likely causesGo to:
Other success factors for nations and individuals|
CPI |
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Countries - listed in order from least to most corrupt in 2003, as perceived by others |
Corruption Perception Index 2003 from:http://www.transparency.org/ cpi/2003/cpi2003.en.html |
GDP/ capita 2002 with Purchasing Power Parity from:http://www.worldfactsandfigures.com/ gdp_country_desc.php |
Average IQ in the nation from:http://www.rlynn.co.uk/pages/ article_intelligence/t4.htm |
Degree of Development |
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|
Finland |
9.7 |
26,200 |
97 |
Developed |
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|
Iceland |
9.6 |
25,000 |
98 |
Developed |
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|
New Zealand |
9.5 |
20,200 |
100 |
Developed |
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|
Denmark |
9.5 |
29,000 |
98 |
Developed |
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|
Singapore |
9.4 |
24,000 |
100 |
Developed |
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|
Sweden |
9.3 |
25,700 |
101 |
Developed |
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|
Netherlands |
8.9 |
26,900 |
102 |
Developed |
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|
Australia |
8.8 |
27,000 |
98 |
Developed |
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|
Switzerland |
8.8 |
31,700 |
101 |
Developed |
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|
Norway |
8.8 |
31,800 |
98 |
Developed |
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|
United Kingdom |
8.7 |
25,700 |
100 |
Developed |
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|
Canada |
8.7 |
29,400 |
97 |
Developed |
||||
|
Luxembourg |
8.7 |
44,000 |
101 |
Developed |
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|
Hong Kong |
8.0 |
26,000 |
107 |
Developed |
||||
|
Austria |
8.0 |
27,700 |
102 |
Developed |
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|
Germany |
7.7 |
26,600 |
102 |
Developed |
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|
Belgium |
7.6 |
29,000 |
100 |
Developed |
||||
|
Ireland |
7.5 |
30,500 |
93 |
Developed |
||||
|
United States |
7.5 |
37,600 |
98 |
Developed |
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|
Chile |
7.4 |
10,000 |
93 |
Developed |
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|
Israel |
7.0 |
19,000 |
94 |
Developed |
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|
Japan |
7.0 |
28,000 |
105 |
Developed |
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|
Spain |
6.9 |
20,700 |
99 |
Developed |
||||
|
France |
6.9 |
25700 |
98 |
Developed |
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|
Portugal |
6.6 |
18,000 |
95 |
Developed |
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|
Oman |
6.3 |
8,200 |
83 |
Developing |
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|
Bahrain |
6.1 |
14,000 |
83 |
Developed |
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|
Cyprus |
6.1 |
15,000 |
92 |
Developed |
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|
Botswana |
5.7 |
9,500 |
72 |
Developing |
||||
|
Taiwan |
5.7 |
18,000 |
104 |
Developed |
||||
|
Qatar |
5.6 |
21,500 |
78 |
Developed |
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|
Uruguay |
5.5 |
7,600 |
96 |
Developing |
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|
Estonia |
5.5 |
10,900 |
97 |
Developed |
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|
Kuwait |
5.3 |
15,000 |
83 |
Developed |
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|
Italy |
5.3 |
25,000 |
102 |
Developed |
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|
Malaysia |
5.2 |
9,300 |
92 |
Developing |
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|
United Arab Emirates |
5.2 |
22,000 |
83 |
Developed |
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|
Tunisia |
4.9 |
6,500 |
84 |
Developing |
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|
Hungary |
4.8 |
13,300 |
99 |
Developed |
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|
Namibia |
4.7 |
6,900 |
72 |
Developing |
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|
Lithuania |
4.7 |
8,400 |
97 |
Developing |
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|
Cuba |
4.6 |
2,300 |
85 |
Underdeveloped |
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|
Jordan |
4.6 |
4,300 |
87 |
Developing |
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|
Trinidad and Tobago |
4.6 |
9,500 |
80 |
Developing |
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|
Belize |
4.5 |
4,900 |
83 |
Developing |
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|
Saudi Arabia |
4.5 |
10,500 |
83 |
Developed |
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|
South Africa |
4.4 |
10,000 |
72 |
Developed |
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|
Mauritius |
4.4 |
11,000 |
81 |
Developed |
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|
Costa Rica |
4.3 |
8,500 |
91 |
Developing |
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|
Greece |
4.3 |
19,000 |
92 |
Developed |
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|
Korea, South |
4.3 |
19,400 |
106 |
Developed |
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|
Belarus |
4.2 |
8,000 |
96 |
Developing |
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|
Bulgaria |
3.9 |
6,600 |
93 |
Developing |
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|
Brazil |
3.9 |
7,600 |
87 |
Developing |
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|
Czech Republic |
3.9 |
15,300 |
97 |
Developed |
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|
Jamaica |
3.8 |
3,900 |
72 |
Developing |
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|
Latvia |
3.8 |
8,300 |
97 |
Developing |
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|
El Salvador |
3.7 |
4,700 |
84 |
Developing |
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|
Peru |
3.7 |
4,800 |
90 |
Developing |
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|
Colombia |
3.7 |
6,500 |
88 |
Developing |
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|
Croatia |
3.7 |
8,800 |
90 |
Developing |
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|
Slovakia |
3.7 |
12,200 |
96 |
Developed |
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|
Mexico |
3.6 |
9,000 |
87 |
Developing |
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|
Poland |
3.6 |
9,500 |
99 |
Developing |
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|
Syria |
3.4 |
3,500 |
87 |
Underdeveloped |
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|
Sri Lanka |
3.4 |
3,700 |
81 |
Underdeveloped |
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|
China |
3.4 |
4,400 |
100 |
Developing |
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|
Panama |
3.4 |
6,000 |
84 |
Developing |
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|
Ghana |
3.3 |
2,100 |
71 |
Underdeveloped |
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|
Egypt |
3.3 |
3,900 |
83 |
Developing |
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|
Morocco |
3.3 |
3,900 |
85 |
Developing |
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|
Dominican Republic |
3.3 |
6,100 |
84 |
Developing |
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|
Thailand |
3.3 |
6,900 |
91 |
Developing |
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|
Senegal |
3.2 |
1,500 |
64 |
Underdeveloped |
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|
Turkey |
3.1 |
6,900 |
90 |
Developing |
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|
Mali |
3.0 |
860 |
68 |
Underdeveloped |
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|
Armenia |
3.0 |
3,800 |
93 |
Developing |
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|
Lebanon |
3.0 |
5,400 |
86 |
Developing |
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|
Iran |
3.0 |
7,000 |
84 |
Developing |
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|
Malawi |
2.8 |
670 |
71 |
Underdeveloped |
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|
India |
2.8 |
2,540 |
81 |
Underdeveloped |
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|
Romania |
2.8 |
7,000 |
94 |
Developing |
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|
Mozambique |
2.7 |
1,000 |
72 |
Underdeveloped |
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|
Russia |
2.7 |
9,300 |
96 |
Developing |
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|
Madagascar |
2.6 |
760 |
79 |
Underdeveloped |
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|
Yemen |
2.6 |
840 |
83 |
Underdeveloped |
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|
Nicaragua |
2.6 |
2,500 |
84 |
Underdeveloped |
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|
Algeria |
2.6 |
5,300 |
84 |
Developing |
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|
Tanzania |
2.5 |
630 |
72 |
Underdeveloped |
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|
Ethiopia |
2.5 |
750 |
63 |
Underdeveloped |
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|
Zambia |
2.5 |
890 |
77 |
Underdeveloped |
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|
Gambia |
2.5 |
1,800 |
64 |
Underdeveloped |
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|
Pakistan |
2.5 |
2,000 |
81 |
Underdeveloped |
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|
Philippines |
2.5 |
4,200 |
86 |
Developing |
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|
Albania |
2.5 |
4,500 |
90 |
Developing |
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|
Argentina |
2.5 |
10,200 |
96 |
Developed |
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|
Vietnam |
2.4 |
2,250 |
96 |
Underdeveloped |
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|
Uzbekistan |
2.4 |
2,500 |
87 |
Underdeveloped |
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|
Moldova |
2.4 |
2,500 |
95 |
Underdeveloped |
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|
Guatemala |
2.4 |
3,700 |
79 |
Underdeveloped |
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|
Venezuela |
2.4 |
5,500 |
88 |
Developing |
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|
Kazakhstan |
2.4 |
6,300 |
93 |
Developing |
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|
Sudan |
2.3 |
1,420 |
72 |
Underdeveloped |
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|
Zimbabwe |
2.3 |
2,400 |
66 |
Underdeveloped |
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|
Bolivia |
2.3 |
2,500 |
85 |
Underdeveloped |
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|
Honduras |
2.3 |
2,600 |
84 |
Underdeveloped |
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|
Ukraine |
2.3 |
4,500 |
96 |
Developing |
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|
Macedonia |
2.3 |
5,000 |
93 |
Developing |
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|
Sierra Leone |
2.2 |
550 |
64 |
Underdeveloped |
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|
Uganda |
2.2 |
1,260 |
73 |
Underdeveloped |
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|
Iraq |
2.2 |
2,400 |
87 |
Underdeveloped |
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|
Ecuador |
2.2 |
3,100 |
80 |
Underdeveloped |
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|
Cote d'Ivoire |
2.1 |
1,500 |
71 |
Underdeveloped |
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|
Papua New Guinea |
2.1 |
2,300 |
84 |
Underdeveloped |
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|
Kyrgyzstan |
2.1 |
2,800 |
87 |
Underdeveloped |
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|
Libya |
2.1 |
7,400 |
84 |
Developing |
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|
Kenya |
1.9 |
1,020 |
72 |
Underdeveloped |
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|
Indonesia |
1.9 |
2,900 |
89 |
Underdeveloped |
||||
|
Tajikistan |
1.8 |
1,250 |
87 |
Underdeveloped |
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|
Angola |
1.8 |
1,600 |
69 |
Underdeveloped |
||||
|
Cameroon |
1.8 |
1,700 |
70 |
Underdeveloped |
||||
|
Georgia |
1.8 |
3,100 |
93 |
Underdeveloped |
||||
|
Azerbaijan |
1.8 |
3,500 |
87 |
Underdeveloped |
||||
|
Myanmar |
1.6 |
1,660 |
86 |
Underdeveloped |
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|
Paraguay |
1.6 |
4,200 |
85 |
Developing |
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|
1.5 |
1,700 |
72 |
Underdeveloped |
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|
1.4 |
875 |
67 |
Underdeveloped |
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|
Bangladesh |
1.3 |
1,700 |
81 |
Underdeveloped |
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|
? |
4500 |
90 |
Underdeveloped |
|||||
|
? ? |
600 800 |
87 (Jordan) 87 (Jordan) |
Underdeveloped Underdeveloped |
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The last three areas have very high corruption. They are noteworthy because the corruption and income of their neighboring countries is significantly different. These
differences fuel the ongoing despair and violence in these regions.This chart and correlations on this page were done by Parhatsathid (Ted) Napatalung of Thailand. Questions on this page should be sent to Ted at parhat@yahoo.com . Click for Ted's basic
analysis of the causes of corruption or details of how corruption hurts Nigeria. Or click to read his comments on what the numbers on this page mean. Low corruption (high 1st column scores above) shows a very high 0.89 correlation to income, while the correlation of IQ to income is a bit lower at 0.67.For another interesting contribution by Professor Ted to this website, see
The Apprentice TV show and SQ skills|
Developed Countries Correlation Coefficients If integrity is already high, improvement in integrity takes an even greater importance. |
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|
IQ to GDP |
Corrupt to GDP |
IQ to Corrupt |
|
|
GDP |
0.5847804 |
0.723046008 |
0.557679697 |
|
Log GDP |
0.5888812 |
0.709619697 |
|
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Developing Countries Correlation Coefficients If integrity is medium, IQ takes equal importance to integrity. |
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|
IQ to GDP |
Corrupt to GDP |
IQ to Corrupt |
|
|
GDP |
0.6096047 |
0.574192128 |
0.206513484 |
|
Log GDP |
0.6863854 |
0.612479943 |
|
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Underdeveloped Countries Correlation Coefficients If integrity is low, IQ takes a great importance towards GDP. |
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|
IQ to GDP |
Corrupt to GDP |
IQ to Corrupt |
|
|
GDP |
0.6031906 |
0.232614825 |
0.149918456 |
|
Log GDP |
0.6901287 |
0.167734259 |
|
Also on this topic:
Corruption, Income Distribution, and Growth from http://ideas.repec.org/a/bla/ecopol/v12y2000i2p155-182.html This paper uses an encompassing framework developed by Murphy et al. (1991, 1993) to study corruption and how it affects income distribution and growth. We find that (1) corruption affects income distribution in an inverted U-shaped way, (2) corruption alone also explains a large proportion of the Gini differential across developing and industrial countries, and (3) after correcting for measurement errors, corruption seems to retard economic growth. But the effect is far less pronounced than the one found in Mauro (1995). Moreover, corruption alone explains little of the continental growth differentials. In countries where the asset distribution is less equal, corruption is associated with a smaller increase in income inequality and a larger drop in growth rates.Go to:
Nation rankings on business competitivenessGo to:
Happiness of various nationsComments to:
VanSloan@yahoo.comRead the
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