Corruption Perceptions Index

Map showing countries and territories according to the Corruption Perception Index, 2023, in ascending order:
  Score higher than 89
  Score equal to or between 80 and 89
  Score equal to or between 70 and 79
  Score equal to or between 60 and 69
  Score equal to or between 50 and 59
  Score equal to or between 40 and 49
  Score equal to or between 30 and 39
  Score equal to or between 20 and 29
  Score equal to or between 10 and 19
  Score less than 10
  Data unavailable

The Corruption Perceptions Index (CPI) is an index that ranks countries "by their perceived levels of public sector[1] corruption, as determined by expert assessments and opinion surveys."[2] The CPI generally defines corruption as an "abuse of entrusted power for private gain".[3]: 2  The index is published annually by the non-governmental organisation Transparency International since 1995.[4]

The 2023 CPI, published in January 2024, currently ranks 180 countries "on a scale from 100 (very clean) to 0 (highly corrupt)" based on the situation between 1 May 2022 and 30 April 2023. Denmark, Finland, New Zealand, Norway, Singapore, and Sweden are perceived as the least corrupt nations in the world, ranking consistently high among international financial transparency, while the most apparently corrupt are Syria, South Sudan, and Venezuela (scoring 13), as well as Somalia (scoring 11).[5]

Although the CPI is currently the most widely used indicator of corruption globally, it is worth emphasizing that there are some limitations. First, the CPI does not distinguish between individual types of corruption (some are not even included in the index) and people's perceptions do not necessarily correspond to the actual level of corruption. To get a more comprehensive picture, the CPI should be used alongside other assessments. Furthermore, the CPI is better suited for analyzing long-term trends, as perceptions tend to change slowly.[6]

Methods

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The following paragraph describes the methodology for calculating the index, which has been used to calculate the index since 2012, when the methodology was modified to allow comparison over time. The index is calculated in four steps: selection of source data, rescaling source data, aggregating the rescaled data and then reporting a measure for uncertainty.[3]: 7 

Selection of source data

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The goal of the data selection is to capture expert and business leader assessments of various public sector corruption practices. This includes bribery, misuse of public funds, abuse of public office for personal gain, nepotism in civil service, and state capture. Since 2012 CPI takes into account 13 different surveys and assessments[7] from 12 different institutions.[3]: 1  The institutions are:

Countries need to be evaluated by at least three sources to appear in the CPI.[3]: 7  The CPI measures perception of corruption due to the difficulty of measuring absolute levels of corruption.[8] Transparency International commissioned the University of Passau's Johann Graf Lambsdorff to produce the CPI.[9] Early CPIs used public opinion surveys.[3]: 7 

Rescaling source data

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In order for all data to be aggregated into the CPI index, it is first necessary to carry out standardization during which all data points are converted to a scale of 0-100. Here, 0 represents the most corruption and 100 signifies the least. Indices originally measuring corruption inversely (higher values for higher corruption) are multiplied by -1 to align with the 0-100 scale.

In the next step, the mean and standard deviation for each data source based on data from the baseline year are calculated (the "impute" command of the STATA statistical software package is used to replace missing values). Subsequently, a standardized z score is calculated with an average centered around 0 and a standard deviation of 1 for each source from each country. Finally, these scores are converted back to a 0-100 scale with a mean of approximately 45 and a standard deviation of 20. Scores below 0 are set to 0, and scores exceeding 100 are capped at 100. This ensures consistent comparability across years since 2012.

Aggregating the rescaled data

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The resulting CPI index for each country is calculated as a simple average of all its rescaled scores that are available for the given country, while at least three data sources must be available in order to calculate the index. The imputed data is used only for standardization and is not used as a score to calculate the index.

Reporting a measure for uncertainty

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The CPI score is accompanied by a standard error and confidence interval. This reflects the variation present within the data sources used for a particular country or territory.

Validity

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A study published in 2002 found a "very strong significant correlation" between the Corruption Perceptions Index and two other proxies for corruption: black market activity and an overabundance of regulation.[10]

All three metrics also had a highly significant correlation with the real gross domestic product per capita (RGDP/Cap); the Corruption Perceptions Index correlation with RGDP/Cap was the strongest, explaining over three-quarters of the variance.[10] (Note that a lower rating on this scale reflects greater corruption so that countries with higher RGDPs generally had less corruption.)

Alex Cobham of the Center for Global Development reported in 2013 that "many of the staff and chapters" at Transparency International, the publisher of the Corruption Perceptions Index, "protest internally" over concerns about the index. The original creator of the index, Johann Graf Lambsdorff, withdrew from work on the index in 2009, stating "In 1995 I invented the Corruption Perceptions Index and have orchestrated it ever since, putting TI on the spotlight of international attention. In August 2009 I have informed Cobus de Swardt, managing director of TI, that I am no longer available for doing the Corruption Perceptions Index."[11]

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CPI and Economic Growth

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Research papers published in 2007 and 2008 examined the economic consequences of corruption perception, as defined by the CPI. The researchers found a correlation between a higher CPI and higher long-term economic growth,[12] as well as an increase in GDP growth of 1.7% for every unit increase in a country's CPI score.[13] Also shown was a power-law dependence linking higher CPI score to higher rates of foreign investment in a country.

The research article The investigation of the relationship between corruption perception index and GDP in the cake of the Balkans[14] from 2020 confirms the positive co-integration relationship in Balkan countries between CPI and GDP and calculates the affecting rate of CDI GDP as 0.34. Moreover, the direction of causality between CDI and GDP was identified from CDI to GDP and, according to this, the hypothesis that CDI is the cause of GDP was accepted.

Working paper Corruption and economic growth: New empirical evidence[15] from 2019 emphasizes that many previous studies used the CPI for their analysis before 2012 (when the index was difficult to compare over time) and therefore may be biased. At the same time, it presents new empirical evidence based on data for 175 over the period 2012-2018. The results show that corruption is negatively associated with economic growth (Real per capita GDP decreased by around 17% in the long-run when the reversed CPI increased by one standard deviation).

CPI and Justice

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As reported by Transparency International, there is a correlation between the absence of discrimination and a better CPI score. That indicates that in countries with high corruption, equal treatment before the law is not guaranteed and there is more space for discrimination against specific groups.[16]

It seems that the country's justice system is an important protector of the country against corruption, and conversely, a high level of corruption can undermine the effectiveness of the justice system.Furthermore, as noted by the United Nations Office on Drugs and Crime (UNODC), justice systems around the world are overburdened with large caseloads, chronically underfunded and in need of more financial and human resources to properly fulfill their mandates. This, in combination with increasing outside interference, pressures and efforts to undermine judicial independence, results in the inability of justice systems to control corruption. The latest edition of the World Justice Project's Rule of Law Index, which shows that in the past year, justice systems in most countries exhibited signs of deterioration, including increasing delays and lower levels of accessibility and affordability, also serves as evidence of the urgency of the situation. Conversely, because corruption implies disproportionate favoring of some groups or individuals over others, it prevents people from accessing justice. For example, a person may rely on personal contacts to change a statutory process.

As shown in the Corruption Perception Index 2023, there is also a positive relationship between corruption and impunity. Countries with higher levels of corruption are less likely to sanction public officials for failing to adhere to existing rules and fulfilled their responsibilities. A positive relationship was also shown between corruption and access to justice.[17]

CPI and Some Other Phenomena and Indices

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Thesis The Relationship Between Corruption And Income Inequality: A Ccrossnational Study,[18] published in 2013, investigates the connection between corruption and income inequality on a global scale. The study's key finding is a robust positive association between income inequality (measured by the Gini coefficient) and corruption (measured by the CPI).

A study from 2001[19] shows that the more affected by corruption, the worse a country's environmental performance. Measuring national environmental performance according to 67 variables, the closest match is with the 2000 TI Corruption Perceptions Index, which revealed a 0.75 correlation with the ranking of environmental performance.

A 2022 study titled "Statistical Analyses on the Correlation Perception Index and Some Other Indices in Nigeria"[20] investigated the relationship between the Corruption Perception Index in Nigeria and other relevant indices. These other indices included the Human Development Index (HDI), Global Peace Index (GPI), and Global Hunger Index (GHI). The result from the analysis carried out on the standardized data set shows that a positive linear relationship exists among all the variable considered except for CPI and GPI holding HDI and GHI constant which indicates a negative linear relationship between them.

A study investigating the relationship between public governance and the Corruption Perception Index[21] found that aspects of public administration like voice and accountability, political stability, and rule of law significantly influence how corrupt a country is perceived to be. This suggests that strong governance practices can be effective in reducing corruption.

Assessments

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The Index’s methodology was criticized in the past.[22]

According to political scientist Dan Hough, three flaws in the Index include:[23]

  • Corruption is too complex a concept to be captured by a single score. For instance, the nature of corruption in rural Kansas will be different from that in the city administration of New York, yet the Index measures them in the same way.
  • By measuring perceptions of corruption, as opposed to corruption itself, the Index may simply be reinforcing existing stereotypes and cliches.
  • The Index only measures public sector corruption, ignoring the private sector. This, for instance, means the well-publicized Libor scandal, Odebrecht case and the VW emissions scandal are not counted as corrupt actions.

Media outlets frequently use the raw numbers as a yardstick for government performance, without clarifying what the numbers mean. The local Transparency International chapter in Bangladesh disowned the index results after a change in methodology caused the country's scores to increase; media reported it as an "improvement".[24]

In a 2013 article in Foreign Policy, Alex Cobham suggested that CPI should be dropped for the good of Transparency International. It argues that the CPI embeds a powerful and misleading elite bias in popular perceptions of corruption, potentially contributing to a vicious cycle and at the same time incentivizing inappropriate policy responses. Cobham writes, "the index corrupts perceptions to the extent that it's hard to see a justification for its continuing publication."[25]

Recent econometric analyses that have exploited the existence of natural experiments on the level of corruption and compared the CPI with other subjective indicators have found that, while not perfect, the CPI is argued to be broadly consistent with one-dimensional measures of corruption.[26]

In the United States, many lawyers advise international businesses to consult the CPI when attempting to measure the risk of Foreign Corrupt Practices Act violations in different nations. This practice has been criticized by the Minnesota Journal of International Law, which wrote that since the CPI may be subject to perceptual biases it therefore should not be considered by lawyers to be a measure of actual national corruption risk.[27]

Transparency International also publishes the Global Corruption Barometer, which ranks countries by corruption levels using direct surveys instead of perceived expert opinions, which has been under criticism for substantial bias from the powerful elite.[25]

Transparency International has warned that a country with a clean CPI score may still be linked to corruption internationally. For example, while Sweden had the 3rd best CPI score in 2015, one of its state-owned companies, TeliaSonera, was facing allegations of bribery in Uzbekistan.[28]

Ranking over Time

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As stated by Transparency International in 2024,[29] the level of corruption stagnates at the global level. Only 28 of the 180 countries measured by the CPI index have improved their corruption levels over the last twelve years, and 34 countries have significantly worsened. No significant change was recorded for 118 countries. Moreover, according to Transparency International, over 80 percent of the population lives in countries whose CPI index is lower than the global average of 43, and thus corruption remains a problem that affects the majority of people globally.

Among the states with the most significant decline in the CPI are authoritarian states such as Venezuela, as well as established democracies that have been rated high for a long time, such as Sweden (decrease of 7, the current score 82) or Great Britain (decrease 3, current score 71). Other countries experiencing sharp declines include Sri Lanka, Mongolia, Gabon, Guatemala, and Turkey. In contrast, the most significant improvements in the CPI score over the last twelve years were recorded by Uzbekistan, Tanzania, Ukraine, Côte d'Ivoire, the Dominican Republic and Kuwait.

Legend

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Scores Perceived as less corrupt Perceived as more corrupt
99–90 89–80 79–70 69–60 59–50 49–40 39–30 29–20 19–10 9–0

2020–2023

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Corruption Perceptions Index table:[30]

# Nation or Territory 2023[5] 2022[31] 2021[32] 2020[33]
Score  Δ[i] Score  Δ[i] Score  Δ[i] Score  Δ[i]
1  Denmark
90
Steady
90
Steady
88
Steady
88
Steady
2  Finland
87
Steady
87
Decrease 1
88
Increase 2
85
Steady
3  New Zealand
85
Decrease 1
87
Decrease 1
88
Steady
88
Steady
4  Norway
84
Steady
84
Steady
85
Increase 3
84
Steady
5  Singapore
83
Steady
83
Decrease 1
85
Decrease 1
85
Increase 1
6  Sweden
82
Decrease 1
83
Decrease 1
85
Decrease 1
85
Increase 1
7   Switzerland
82
Increase 1
82
Steady
84
Decrease 4
85
Increase 1
8  Netherlands
79
Steady
80
Steady
82
Steady
82
Steady
9  Germany
78
Steady
79
Increase 1
80
Decrease 1
80
Steady
10  Luxembourg
78
Increase 1
77
Decrease 1
81
Steady
80
Steady
11  Ireland
77
Decrease 1
77
Increase 3
74
Increase 7
72
Decrease 2
12  Canada
76
Increase 2
74
Decrease 1
75
Decrease 2
77
Increase 1
13  Estonia
76
Increase 2
74
Decrease 1
74
Increase 4
75
Increase 1
14  Australia
75
Decrease 1
75
Increase 5
73
Decrease 7
77
Increase 1
15  Hong Kong
75
Decrease 2
76
Steady
76
Decrease 1
77
Increase 5
16  Belgium
73
Increase 2
73
Steady
73
Decrease 3
76
Increase 2
17  Japan
73
Increase 2
73
Steady
73
Increase 1
74
Increase 1
18  Uruguay
73
Decrease 2
74
Increase 4
73
Increase 3
71
Steady
19  Iceland
72
Decrease 5
74
Decrease 1
74
Increase 4
75
Decrease 6
20  Austria
71
Increase 2
71
Decrease 9
74
Increase 2
76
Decrease 3
21  France
71
Increase 1
72
Increase 1
71
Increase 1
69
Steady
22  Seychelles
71
Increase 3
70
Steady
70
Increase 4
66
Steady
23  United Kingdom
71
Decrease 2
73
Decrease 7
78
Steady
77
Increase 1
24  Barbados
69
Increase 5
65
Steady
65
Steady
64
Increase 1
25  United States
69
Steady
69
Increase 3
67
Decrease 2
67
Decrease 2
26  Bhutan
68
Decrease 1
68
Steady
68
Decrease 1
68
Increase 1
27  United Arab Emirates
68
Increase 1
67
Decrease 3
69
Decrease 3
71
Steady
28  Taiwan
67
Decrease 3
68
Steady
68
Increase 3
65
Steady
29  Chile
66
Decrease 2
67
Steady
67
Decrease 2
67
Increase 1
30  Bahamas
64
Steady
64
Steady
64
Steady
63
Decrease 1
30  Cape Verde
64
Increase 5
60
Increase 4
58
Increase 2
58
Steady
32  South Korea
63
Decrease 1
63
Increase 1
62
Increase 1
61
Increase 6
33  Israel
62
Decrease 2
63
Increase 5
59
Decrease 1
60
Steady
34  Lithuania
61
Decrease 1
62
Increase 1
61
Increase 1
60
Steady
34  Portugal
61
Decrease 1
62
Decrease 1
62
Increase 1
61
Decrease 3
36  Latvia
60
Increase 3
59
Decrease 3
59
Increase 6
57
Increase 2
36  Saint Vincent and the Grenadines
60
Decrease 1
60
Increase 1
59
Increase 4
59
Decrease 1
36  Spain
60
Decrease 1
60
Decrease 1
61
Decrease 2
62
Decrease 2
 Brunei Darussalam
60
Steady
39  Botswana
59
Decrease 4
60
Increase 10
55
Decrease 10
60
Decrease 1
40  Qatar
58
Steady
58
Decrease 9
63
Decrease 1
63
Steady
41  Czechia
57
Steady
56
Increase 8
54
Steady
54
Decrease 5
42  Dominica
56
Increase
55
Steady
55
Increase 3
55
Steady
42  Italy
56
Decrease 1
56
Increase 1
56
Increase 10
53
Decrease 1
42  Slovenia
56
Decrease 1
56
Steady
57
Decrease 6
60
Steady
45  Costa Rica
55
Increase 3
54
Decrease 9
58
Increase 3
57
Increase 2
45  Saint Lucia
55
Steady
55
Decrease 3
56
Increase 3
56
Increase 3
47  Poland
54
Decrease 2
55
Decrease 3
56
Increase 3
56
Decrease 4
47  Slovakia
54
Increase 2
53
Increase 7
52
Increase 4
49
Decrease 1
49  Cyprus
53
Increase 2
52
Increase 1
53
Decrease 10
57
Decrease 1
49  Georgia
53
Decrease 8
56
Increase 4
55
Steady
56
Decrease 1
49  Grenada
53
Increase 2
52
Increase 1
53
Steady
53
Decrease 1
49  Rwanda
53
Increase 5
51
Decrease 2
53
Decrease 3
54
Increase 2
53  Fiji
52
Decrease 4
53
Decrease 4
55
Increase 10
53  Saudi Arabia
52
Increase 1
51
Decrease 2
53
Steady
53
Decrease 1
55  Malta
51
Decrease 1
51
Decrease 5
54
Increase 3
53
Decrease 2
55  Mauritius
51
Increase 2
50
Decrease 8
54
Increase 3
53
Increase 4
57  Croatia
50
Steady
50
Increase 6
47
Steady
47
Steady
57  Malaysia
50
Increase 4
47
Increase 1
48
Decrease 5
51
Decrease 6
59  Greece
49
Decrease 8
52
Increase 7
49
Increase 1
50
Increase 1
59  Namibia
49
Steady
49
Decrease 1
49
Decrease 1
51
Decrease 1
61  Vanuatu
48
Decrease 1
48
Increase 6
45
Increase 9
43
Decrease 11
62  Armenia
47
Increase 1
46
Decrease 5
49
Increase 2
49
Increase 17
63  Kuwait
46
Increase 14
42
Decrease 4
43
Increase 5
42
Increase 7
63  Jordan
46
Decrease 2
47
Decrease 3
49
Increase 2
49
Steady
63  Montenegro
46
Increase 2
45
Decrease 1
46
Increase 3
45
Decrease 1
63  Romania
46
Steady
46
Increase 3
45
Increase 3
44
Increase 1
67  Bulgaria
45
Increase 5
43
Increase 6
42
Decrease 9
44
Increase 5
67  São Tomé and Príncipe
45
Decrease 2
45
Increase 1
45
Decrease 3
47
Increase 1
69  Jamaica
44
Steady
44
Increase 1
44
Decrease 1
44
Increase 5
70  Ghana
43
Increase 2
43
Increase 1
43
Increase 2
43
Increase 5
70  Benin
43
Increase 2
43
Increase 6
42
Increase 5
41
Decrease 3
70  Oman
43
Decrease 1
44
Decrease 13
52
Decrease 7
54
Increase 7
70  Senegal
43
Increase 2
43
Increase 1
43
Decrease 6
45
Decrease 1
70  Solomon Islands
43
Increase 7
42
Decrease 4
43
Increase 5
42
Decrease 1
70  Timor-Leste
43
Increase 7
42
Increase 5
41
Increase 4
40
Increase 7
76  Bahrain
42
Decrease 7
44
Increase 9
42
Steady
42
Decrease 1
76  China
42
Decrease 11
45
Increase 1
45
Increase 12
42
Increase 2
76  Cuba
42
Decrease 11
45
Decrease 1
46
Decrease 1
47
Decrease 3
76  Hungary
42
Increase 1
42
Decrease 4
43
Decrease 4
44
Increase 1
76  Moldova
42
Increase 15
39
Increase 14
36
Increase 10
34
Increase 5
76  North Macedonia
42
Increase 9
40
Increase 2
39
Increase 24
35
Decrease 5
76  Trinidad and Tobago
42
Increase 1
42
Increase 5
41
Increase 4
40
Decrease 1
83  Burkina Faso
41
Decrease 6
42
Increase 1
42
Increase 8
40
Decrease 1
83  Kosovo
41
Increase 1
41
Increase 3
39
Increase 17
36
Decrease 3
83  South Africa
41
Decrease 11
43
Decrease 2
44
Decrease 1
44
Increase 1
83  Vietnam
41
Decrease 6
42
Increase 10
39
Increase 17
36
Decrease 8
87  Colombia
40
Increase 4
39
Decrease 4
39
Increase 5
39
Increase 4
87  Guyana
40
Decrease 2
40
Increase 2
39
Decrease 4
41
Increase 2
87  Ivory Coast
40
Increase 12
37
Increase 6
36
Decrease 1
36
Increase 2
87  Suriname
40
Decrease 2
40
Increase 2
39
Increase 7
38
Decrease 24
87  Tanzania
40
Increase 7
38
Decrease 7
39
Increase 7
38
Increase 2
87  Tunisia
40
Decrease 2
40
Decrease 15
44
Decrease 1
44
Increase 5
93  Kazakhstan
39
Increase 8
36
Increase 1
37
Decrease 8
38
Increase 19
93  India
39
Decrease 8
40
Steady
40
Increase 1
40
Decrease 6
93  Lesotho
39
Increase 6
37
Decrease 3
38
Decrease 13
41
Increase 2
93  Maldives
39
Decrease 8
40
Steady
40
Decrease 10
43
Increase 55
97  Morocco
38
Decrease 3
38
Decrease 7
39
Decrease 1
40
Decrease 6
98  Argentina
37
Decrease 4
38
Increase 2
38
Decrease 18
42
Decrease 12
98  Albania
37
Increase 3
36
Increase 9
35
Decrease 6
36
Increase 2
98  Belarus
37
Decrease 7
39
Decrease 9
41
Decrease 19
47
Increase 3
98  Ethiopia
37
Decrease 4
38
Decrease 7
39
Increase 7
38
Increase 2
98  Gambia
37
Increase 12
34
Decrease 8
37
Steady
37
Decrease 6
98  Zambia
37
Increase 18
33
Increase 1
33
Steady
33
Decrease 4
104  Algeria
36
Increase 12
33
Increase 1
33
Decrease 13
36
Increase 2
104  Brazil
36
Decrease 10
38
Increase 2
38
Decrease 2
38
Increase 12
104  Serbia
36
Decrease 3
36
Decrease 5
38
Decrease 2
38
Decrease 3
104  Ukraine
36
Increase 12
33
Increase 6
32
Decrease 5
33
Increase 9
108  Bosnia and Herzegovina
35
Increase 2
34
Steady
35
Increase 1
35
Decrease 10
108  Dominican Republic
35
Increase 15
32
Increase 5
30
Increase 9
28
Steady
108  Egypt
35
Increase 22
30
Decrease 13
33
Steady
33
Decrease 11
108    Nepal
35
Increase 2
34
Increase 7
33
Steady
33
Decrease 4
108  Panama
35
Decrease 7
36
Increase 4
36
Increase 6
35
Decrease 10
108  Sierra Leone
35
Increase 2
34
Increase 5
34
Increase 2
33
Increase 2
108  Thailand
35
Decrease 7
36
Increase 9
35
Decrease 6
36
Decrease 3
115  Ecuador
34
Decrease 14
36
Increase 4
36
Decrease 13
39
Increase 1
115  Indonesia
34
Decrease 5
34
Decrease 14
38
Increase 6
37
Decrease 17
115  Malawi
34
Decrease 5
34
Steady
35
Increase 19
30
Decrease 6
115  Philippines
34
Increase 1
33
Increase 1
33
Decrease 2
34
Decrease 2
115  Sri Lanka
34
Decrease 14
36
Increase 1
37
Decrease 8
38
Decrease 1
115  Turkey
34
Decrease 14
36
Decrease 5
38
Decrease 10
40
Increase 5
121  Angola
33
Decrease 5
33
Increase 20
29
Increase 6
27
Increase 4
121  Mongolia
33
Decrease 5
33
Decrease 6
35
Increase 1
35
Decrease 5
121  Peru
33
Decrease 20
36
Increase 4
36
Decrease 11
38
Increase 7
121  Uzbekistan
33
Increase 5
31
Increase 14
28
Increase 6
26
Increase 7
125  Niger
32
Decrease 2
32
Increase 1
31
Decrease 1
32
Decrease 3
126  El Salvador
31
Decrease 10
33
Decrease 1
34
Decrease 11
36
Increase 9
126  Kenya
31
Decrease 3
32
Increase 5
30
Decrease 4
31
Increase 13
126  Mexico
31
Steady
31
Decrease 2
31
Steady
31
Increase 6
126  Togo
31
Increase 4
30
Decrease 2
30
Increase 6
29
Decrease 4
130  Djibouti
30
Steady
30
Decrease 2
30
Increase 14
27
Decrease 16
130  Eswatini
30
Steady
30
Decrease 8
32
Decrease 5
33
Decrease 4
130  Mauritania
30
Steady
30
Increase 10
28
Decrease 6
29
Increase 3
133  Bolivia
29
Decrease 7
31
Increase 2
30
Decrease 4
31
Decrease 1
133  Pakistan
29
Increase 7
27
Steady
28
Decrease 16
31
Decrease 4
133  Papua New Guinea
29
Decrease 3
30
Decrease 6
31
Increase 18
27
Decrease 5
136  Gabon
28
Steady
29
Decrease 12
31
Increase 5
30
Decrease 6
136  Laos
28
Decrease 10
31
Increase 2
30
Increase 6
29
Decrease 4
136  Mali
28
Increase 1
28
Decrease 1
29
Decrease 7
30
Increase 1
136  Paraguay
28
Increase 1
28
Decrease 9
30
Increase 9
28
Steady
140  Cameroon
27
Increase 2
26
Increase 2
27
Increase 5
25
Increase 4
141  Guinea
26
Increase 6
25
Increase 3
25
Decrease 13
28
Decrease 7
141  Kyrgyzstan
26
Decrease 1
27
Increase 4
27
Decrease 20
31
Increase 2
141  Russia
26
Decrease 4
28
Decrease 1
29
Decrease 7
30
Increase 8
141  Uganda
26
Increase 1
26
Increase 2
27
Decrease 2
27
Decrease 5
145  Liberia
25
Decrease 3
26
Decrease 6
29
Increase 1
28
Steady
145  Madagascar
25
Decrease 3
26
Increase 5
26
Increase 2
25
Increase 9
145  Mozambique
25
Decrease 3
26
Increase 5
26
Increase 2
25
Decrease 3
145  Nigeria
25
Increase 5
24
Increase 4
24
Decrease 5
25
Decrease 3
149  Bangladesh
24
Decrease 2
25
Steady
26
Decrease 1
26
Steady
149  Central African Republic
24
Increase 1
24
Increase 4
24
Decrease 8
26
Increase 7
149  Iran
24
Decrease 2
25
Increase 3
25
Decrease 1
25
Decrease 3
149  Lebanon
24
Increase 1
24
Increase 4
24
Decrease 5
25
Decrease 12
149  Zimbabwe
24
Increase 8
23
Steady
23
Steady
24
Increase 1
154  Azerbaijan
23
Increase 3
23
Decrease 29
30
Increase 1
30
Decrease 3
154  Guatemala
23
Decrease 4
24
Steady
25
Decrease 1
25
Decrease 3
154  Honduras
23
Increase 3
23
Steady
23
Steady
24
Decrease 11
154  Iraq
23
Increase 3
23
Steady
23
Increase 3
21
Increase 2
158  Cambodia
22
Decrease 8
24
Increase 7
23
Increase 3
21
Increase 2
158  Congo
22
Increase 6
21
Decrease 2
21
Increase 3
19
Steady
158  Guinea-Bissau
22
Increase 6
21
Decrease 2
21
Increase 3
19
Increase 3
161  Eritrea
21
Increase 1
22
Decrease 1
22
Decrease 1
21
Steady
162  Afghanistan
20
Decrease 12
24
Increase 24
16
Decrease 9
19
Increase 8
162  Burundi
20
Increase 9
17
Decrease 2
19
Decrease 4
19
Steady
162  Chad
20
Increase 5
19
Decrease 3
20
Decrease 4
21
Increase 2
162  Comoros
20
Increase 5
19
Decrease 3
20
Decrease 4
21
Decrease 7
162  Democratic Republic of the Congo
20
Increase 4
20
Increase 3
19
Increase 1
18
Decrease 2
162  Myanmar
20
Decrease 5
23
Decrease 17
28
Decrease 3
28
Decrease 7
162  Sudan
20
Steady
22
Increase 2
20
Increase 10
16
Decrease 1
162  Tajikistan
20
Decrease 12
24
Steady
25
Decrease 1
25
Increase 4
170  Libya
18
Increase 1
17
Increase 1
17
Increase 1
17
Decrease 5
170  Turkmenistan
18
Decrease 3
19
Increase 2
19
Decrease 4
19
Steady
172  Equatorial Guinea
17
Decrease 1
17
Increase 1
17
Increase 2
16
Decrease 1
172  Haiti
17
Decrease 1
17
Decrease 7
20
Increase 6
18
Decrease 2
172  Nicaragua
17
Decrease 5
19
Decrease 3
20
Decrease 5
22
Increase 2
172  North Korea
17
Decrease 1
17
Increase 3
16
Decrease 4
18
Increase 2
176  Yemen
16
Steady
16
Decrease 2
16
Increase 2
15
Increase 1
177  Venezuela
13
Steady
14
Steady
14
Decrease 1
15
Decrease 3
177  South Sudan
13
Increase 1
13
Increase 2
11
Decrease 1
12
Steady
177  Syria
13
Increase 1
13
Steady
13
Steady
14
Steady
180  Somalia
11
Steady
12
Decrease 2
13
Increase 1
12
Increase 1

2010–2019

edit

Corruption Perceptions Index table:[30]

# Nation or Territory 2019[34] 2018[35] 2017[36] 2016[37] 2015[38] 2014[39] 2013[40] 2012[41] 2011[42] 2010[43]
Score  Δ[i] Score  Δ[i] Score  Δ[i] Score  Δ[i] Score  Δ[i] Score  Δ[i] Score  Δ[i] Score  Δ[i] Score  Δ[i] Score  Δ[i]
1  New Zealand
87
Steady
87
Decrease 2
89
Decrease 1
90
Decrease 1
91
Steady
91
Steady
91
Increase 1
90
1  Denmark
87
Decrease 1
88
Steady
88
Decrease 2
90
Decrease 1
91
Decrease 1
92
Increase 1
91
Increase 1
90
3  Finland
86
Increase 1
85
Steady
85
Decrease 4
89
Decrease 1
90
Increase 1
89
Steady
89
Decrease 1
90
4  Sweden
85
Steady
85
Increase 1
84
Decrease 4
88
Decrease 1
89
Increase 2
87
Decrease 2
89
Increase 1
88
4  Singapore
85
Steady
85
Increase 1
84
Steady
84
Decrease 1
85
Increase 1
84
Decrease 2
86
Decrease 1
87
4   Switzerland
85
Steady
85
Steady
85
Decrease 1
86
Steady
86
Steady
86
Increase 1
85
Decrease 1
86
7  Norway
84
Steady
84
Decrease 1
85
Steady
85
Decrease 2
87
Increase 1
86
Steady
86
Increase 1
85
8  Netherlands
82
Steady
82
Steady
82
Decrease 1
83
Decrease 4
87
Increase 4
83
Steady
83
Decrease 1
84
9  Germany
80
Steady
80
Decrease 1
81
Steady
81
Steady
81
Increase 2
79
Increase 1
78
Decrease 1
79
9  Luxembourg
80
Decrease 1
81
Decrease 1
82
Increase 1
81
Steady
81
Decrease 1
82
Increase 2
80
Steady
80
11  Iceland
78
Increase 2
76
Decrease 1
77
Decrease 1
78
Decrease 1
79
Steady
79
Increase 1
78
Decrease 4
82
12  United Kingdom
77
Decrease 3
80
Decrease 2
82
Increase 1
81
Steady
81
Increase 3
78
Increase 2
76
Increase 2
74
12  Canada
77
Decrease 4
81
Decrease 1
82
Steady
82
Decrease 1
83
Increase 2
81
Steady
81
Decrease 3
84
12  Austria
77
Increase 1
76
Increase 1
75
Steady
75
Decrease 1
76
Increase 4
72
Increase 3
69
Steady
69
12  Australia
77
Steady
77
Steady
77
Decrease 2
79
Steady
79
Decrease 1
80
Decrease 1
81
Decrease 4
85
16  Hong Kong
76
Steady
76
Decrease 1
77
Steady
77
Increase 2
75
Increase 1
74
Decrease 1
75
Decrease 2
77
17  Belgium
75
Steady
75
Steady
75
Decrease 2
77
Steady
77
Increase 1
76
Increase 1
75
Steady
75
18  Estonia
74
Increase 1
73
Increase 2
71
Increase 1
70
Steady
70
Increase 1
69
Increase 1
68
Increase 4
64
18  Ireland
74
Increase 1
73
Decrease 1
74
Increase 1
73
Decrease 2
75
Increase 1
74
Increase 2
72
Increase 3
69
20  Japan
73
Steady
73
Steady
73
Increase 1
72
Decrease 3
75
Decrease 1
76
Increase 2
74
Steady
74
21  United Arab Emirates
71
Increase 1
70
Decrease 1
71
Increase 5
66
Decrease 4
70
Steady
70
Increase 1
69
Increase 1
68
21  Uruguay
71
Increase 1
70
Steady
70
Decrease 1
71
Decrease 3
74
Increase 1
73
Steady
73
Increase 1
72
23  United States
69
Decrease 2
71
Decrease 4
75
Increase 1
74
Decrease 2
76
Increase 2
74
Increase 1
73
Steady
73
23  France
69
Decrease 3
72
Increase 2
70
Increase 1
69
Decrease 1
70
Increase 1
69
Decrease 2
71
Steady
71
25  Bhutan
68
Steady
68
Increase 1
67
Increase 2
65
Steady
65
Steady
65
Increase 2
63
Steady
63
26  Chile
67
Steady
67
Steady
67
Increase 1
66
Decrease 4
70
Decrease 3
73
Increase 2
71
Decrease 1
72
27  Seychelles
66
Steady
66
Increase 6