Blogroll

Jumat, 09 Maret 2012

Index Persepsi Korupsi 2003


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 causes
Go to: Other success factors for nations and individuals


CPI


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
Finland
9.7
26,200
97
Developed
Iceland
9.6
25,000
98
Developed
New Zealand
9.5
20,200
100
Developed
Denmark
9.5
29,000
98
Developed
Singapore
9.4
24,000
100
Developed
Sweden
9.3
25,700
101
Developed
Netherlands
8.9
26,900
102
Developed
Australia
8.8
27,000
98
Developed
Switzerland
8.8
31,700
101
Developed
Norway
8.8
31,800
98
Developed
United Kingdom
8.7
25,700
100
Developed
Canada
8.7
29,400
97
Developed
Luxembourg
8.7
44,000
101
Developed
Hong Kong
8.0
26,000
107
Developed
Austria
8.0
27,700
102
Developed
Germany
7.7
26,600
102
Developed
Belgium
7.6
29,000
100
Developed
Ireland
7.5
30,500
93
Developed
United States
7.5
37,600
98
Developed
Chile
7.4
10,000
93
Developed
Israel
7.0
19,000
94
Developed
Japan
7.0
28,000
105
Developed
Spain
6.9
20,700
99
Developed
France
6.9
25700
98
Developed
Portugal
6.6
18,000
95
Developed
Oman
6.3
8,200
83
Developing
Bahrain
6.1
14,000
83
Developed
Cyprus
6.1
15,000
92
Developed
Botswana
5.7
9,500
72
Developing
Taiwan
5.7
18,000
104
Developed
Qatar
5.6
21,500
78
Developed
Uruguay
5.5
7,600
96
Developing
Estonia
5.5
10,900
97
Developed
Kuwait
5.3
15,000
83
Developed
Italy
5.3
25,000
102
Developed
Malaysia
5.2
9,300
92
Developing
United Arab Emirates
5.2
22,000
83
Developed
Tunisia
4.9
6,500
84
Developing
Hungary
4.8
13,300
99
Developed
Namibia
4.7
6,900
72
Developing
Lithuania
4.7
8,400
97
Developing
Cuba
4.6
2,300
85
Underdeveloped
Jordan
4.6
4,300
87
Developing
Trinidad and Tobago
4.6
9,500
80
Developing
Belize
4.5
4,900
83
Developing
Saudi Arabia
4.5
10,500
83
Developed
South Africa
4.4
10,000
72
Developed
Mauritius
4.4
11,000
81
Developed
Costa Rica
4.3
8,500
91
Developing
Greece
4.3
19,000
92
Developed
Korea, South
4.3
19,400
106
Developed
Belarus
4.2
8,000
96
Developing
Bulgaria
3.9
6,600
93
Developing
Brazil
3.9
7,600
87
Developing
Czech Republic
3.9
15,300
97
Developed
Jamaica
3.8
3,900
72
Developing
Latvia
3.8
8,300
97
Developing
El Salvador
3.7
4,700
84
Developing
Peru
3.7
4,800
90
Developing
Colombia
3.7
6,500
88
Developing
Croatia
3.7
8,800
90
Developing
Slovakia
3.7
12,200
96
Developed
Mexico
3.6
9,000
87
Developing
Poland
3.6
9,500
99
Developing
Syria
3.4
3,500
87
Underdeveloped
Sri Lanka
3.4
3,700
81
Underdeveloped
China
3.4
4,400
100
Developing
Panama
3.4
6,000
84
Developing
Ghana
3.3
2,100
71
Underdeveloped
Egypt
3.3
3,900
83
Developing
Morocco
3.3
3,900
85
Developing
Dominican Republic
3.3
6,100
84
Developing
Thailand
3.3
6,900
91
Developing
Senegal
3.2
1,500
64
Underdeveloped
Turkey
3.1
6,900
90
Developing
Mali
3.0
860
68
Underdeveloped
Armenia
3.0
3,800
93
Developing
Lebanon
3.0
5,400
86
Developing
Iran
3.0
7,000
84
Developing
Malawi
2.8
670
71
Underdeveloped
India
2.8
2,540
81
Underdeveloped
Romania
2.8
7,000
94
Developing
Mozambique
2.7
1,000
72
Underdeveloped
Russia
2.7
9,300
96
Developing
Madagascar
2.6
760
79
Underdeveloped
Yemen
2.6
840
83
Underdeveloped
Nicaragua
2.6
2,500
84
Underdeveloped
Algeria
2.6
5,300
84
Developing
Tanzania
2.5
630
72
Underdeveloped
Ethiopia
2.5
750
63
Underdeveloped
Zambia
2.5
890
77
Underdeveloped
Gambia
2.5
1,800
64
Underdeveloped
Pakistan
2.5
2,000
81
Underdeveloped
Philippines
2.5
4,200
86
Developing
Albania
2.5
4,500
90
Developing
Argentina
2.5
10,200
96
Developed
Vietnam
2.4
2,250
96
Underdeveloped
Uzbekistan
2.4
2,500
87
Underdeveloped
Moldova
2.4
2,500
95
Underdeveloped
Guatemala
2.4
3,700
79
Underdeveloped
Venezuela
2.4
5,500
88
Developing
Kazakhstan
2.4
6,300
93
Developing
Sudan
2.3
1,420
72
Underdeveloped
Zimbabwe
2.3
2,400
66
Underdeveloped
Bolivia
2.3
2,500
85
Underdeveloped
Honduras
2.3
2,600
84
Underdeveloped
Ukraine
2.3
4,500
96
Developing
Macedonia
2.3
5,000
93
Developing
Sierra Leone
2.2
550
64
Underdeveloped
Uganda
2.2
1,260
73
Underdeveloped
Iraq
2.2
2,400
87
Underdeveloped
Ecuador
2.2
3,100
80
Underdeveloped
Cote d'Ivoire
2.1
1,500
71
Underdeveloped
Papua New Guinea
2.1
2,300
84
Underdeveloped
Kyrgyzstan
2.1
2,800
87
Underdeveloped
Libya
2.1
7,400
84
Developing
Kenya
1.9
1,020
72
Underdeveloped
Indonesia
1.9
2,900
89
Underdeveloped
Tajikistan
1.8
1,250
87
Underdeveloped
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
Paraguay
1.6
4,200
85
Developing
Haiti
1.5
1,700
72
Underdeveloped
Nigeria
1.4
875
67
Underdeveloped
Bangladesh
1.3
1,700
81
Underdeveloped
Albania
?
4500
90
Underdeveloped
Palestine: Gaza
West Bank
?
?
600
800
87 (Jordan)
87 (Jordan)
Underdeveloped
Underdeveloped
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.

IQ to GDPCorrupt to GDPIQ to Corrupt
GDP
0.5847804
0.723046008
0.557679697
Log GDP
0.5888812
0.709619697





Developing Countries Correlation Coefficients
If integrity is medium, IQ takes equal importance to integrity.

IQ to GDPCorrupt to GDPIQ to Corrupt
GDP
0.6096047
0.574192128
0.206513484
Log GDP
0.6863854
0.612479943





Underdeveloped Countries Correlation Coefficients
If integrity is low, IQ takes a great importance towards GDP.

IQ to GDPCorrupt to GDPIQ 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 competitiveness
Go to: Happiness of various nations
Diposting oleh di

Tidak ada komentar:

Posting Komentar

Langganan: Posting Komentar (Atom)