Map showing countries and territories according to the Corruption Perception Index, 2024, in ascending order:
  Score equal to or between 90 and 100
  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 equal to or between 0 and 9
  Data unavailable

The Corruption Perceptions Index (CPI) is an index that scores and ranks countries by their perceived levels of public sector[1] corruption, as assessed by experts and business executives.[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 2024 CPI, published in Febraury 2025, currently ranks 180 countries "on a scale from 100 (very clean) to 0 (highly corrupt)" based on the situation between 1 May 2023 and 30 April 2024. Denmark, Finland, Singapore, New Zealand, Luxembourg, Norway, Switzerland and Sweden, (all scoring above 80 over the last four years), are perceived as the least corrupt nations in the world — ranking consistently high among international financial transparency — while the most apparently corrupt is South Sudan (scoring 8), along with Somalia (9) and Venezuela (10).[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

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

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 has taken 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

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

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

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

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]

CPI and economic growth

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 Case 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 CPI GDP as 0.34. Moreover, the direction of causality between CPI and GDP was identified from CPI to GDP and, according to this, the hypothesis that CPI is the cause of GDP was accepted.

The 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

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 fulfill their responsibilities. A positive relationship was also shown between corruption and access to justice.[17]

Other phenomena and indices

Thesis The Relationship Between Corruption And Income Inequality: A Crossnational 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 of Corruption 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

According to political scientist Dan Hough, three flaws in the Index include:[22]

  • 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".[23]

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."[24]

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.[25]

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.[26]

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.[24]

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.[27]

Scoring

As stated by Transparency International in 2024,[28] 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, Ivory Coast, the Dominican Republic and Kuwait.

Legend

Scores Perceived as less corrupt Perceived as more corrupt
since 2012 99–90 89–80 79–70 69–60 59–50 49–40 39–30 29–20 19–10 9–0
1995–2011 10–9 8.99–8 7.99–7 6.99–6 5.99–5 4.99–4 3.99–3 2.99–2 1.99–1 0.99–0

Corruption Perceptions Index table 2024:[29]

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

Transnational corruption in states with high CPI scores

The advanced economies of Northern and Western Europe, North America, and Asia and the Pacific tend to top the rankings over the long term. This means that these countries are perceived as having a low level of corruption in the public sector. These nations also generally have well-functioning judicial systems, a strong rule of law, and political stability – all factors that contribute to perceptions of clean governance. However, while these top-ranked countries have strong domestic institutions, their commitment to fighting corruption appears to be weak when it comes to their own financial systems and regulations affecting the international environment.[30] The CPI doesn't capture transnational corruption, so corrupt foreign business practices by companies from these countries don't affect their CPI scores. The example of the Netherlands highlights this issue. Despite a high CPI score, the Netherlands has a poor record of prosecuting companies that bribe foreign officials to win contracts, as seen in the Nigerian oil bribery case.[31]

The report Exporting Corruption 2022,[32] which assesses foreign bribery enforcement in 43 of the 44 signatories to the OECD Anti-Bribery Convention, as well as China, ZAO Hong Kong, India and Singapore, reinforces this concern. It found a significant decline in foreign bribery enforcement, only two out of 47 countries are now in active enforcement category. Other key findings were that no country is exempt from bribery by its nationals and related money laundering. Moreover, according to the report weaknesses remain in legal frameworks and enforcement systems are not adequately disclosed by most countries information on enforcement, victim compensation is rare and international cooperation is increasing still faces significant obstacles. This calls for a more comprehensive approach to tackling corruption, addressing both domestic and international aspects.

See also

Footnotes

  1. ^ Change in Rank (not Score).

References

  1. ^ "Corruption Perception Index". transparency.org. Retrieved 28 January 2020.
  2. ^ "Corruption Perceptions Index: Frequently Asked Questions". Transparency International. 2024. Archived from the original on 3 June 2024. Retrieved 20 July 2024.
  3. ^ a b c d e Corruption Perceptions Index 2010: Long Methodological Brief (PDF) (Report). Transparency International. Retrieved 30 March 2024.
  4. ^ "1995 – CPI". Transparency.org. Retrieved 7 July 2022.
  5. ^ "CPI 2024". Transparency International. Retrieved 14 February 2025.{{cite web}}: CS1 maint: url-status (link)
  6. ^ Andy McDevitt. (2016). How-to guide for corruption assessment tools (2nd edition). U4 operated by Transparency International.
  7. ^ Transparency International. "Corruption Perceptions Index 2022: Full Source Description". Corruption Perceptions Index: 1.
  8. ^ Transparency International (2010). "Frequently asked questions (FAQs)". Corruption Perceptions Index 2010. Transparency International. Archived from the original on 2 September 2011. Retrieved 24 August 2011.
  9. ^ "Frequently Asked Questions: TI Corruption Perceptions Index (CPI 2005)". Retrieved 22 November 2005.
  10. ^ a b Wilhelm, Paul G. (2002). "International Validation of the Corruption Perceptions Index: Implications for Business Ethics and Entrepreneurship Education". Journal of Business Ethics. 35 (3). Springer Netherlands: 177–189. doi:10.1023/A:1013882225402. S2CID 151245049.
  11. ^ Cobham, Alex (23 July 2013). "Corrupting Perceptions: Why Transparency International's Flagship Corruption Index Falls Short". cgdev.org.
  12. ^ Shao, J.; Ivanov, P. C.; Podobnik, B.; Stanley, H. E. (2007). "Quantitative relations between corruption and economic factors". The European Physical Journal B. 56 (2): 157. arXiv:0705.0161. Bibcode:2007EPJB...56..157S. doi:10.1140/epjb/e2007-00098-2. S2CID 2357298.
  13. ^ Podobnik, B.; Shao, J.; Njavro, D.; Ivanov, P. C.; Stanley, H. E. (2008). "Influence of corruption on economic growth rate and foreign investment". The European Physical Journal B. 63 (4): 547. arXiv:0710.1995. Bibcode:2008EPJB...63..547P. doi:10.1140/epjb/e2008-00210-2. S2CID 3038265.
  14. ^ Göktürk, E.; Yalçınkaya, H. S. (2020). "The investigation of relationship between Corruption Perception Index and GDP in the case of the Balkans". International Journal of Management Economics and Business. 16 (4). doi:10.17130/ijmeb.853535.
  15. ^ Gründler, Klaus; Potrafke, Niklas (2019). "Corruption and Economic Growth: New Empirical Evidence" (PDF). European Journal of Political Economy. 60: 101810. doi:10.1016/j.ejpoleco.2019.08.001. hdl:10419/207207.
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  18. ^ Mehen, M. (2013). The Relationship between Corruption and Income Inequality: A Crossnational Study (PDF) (Thesis). Faculty of the Graduate School of Arts and Sciences of Georgetown University.
  19. ^ ""Strongest correlation" between corruption and poor environmental…". Transparency.org. 25 January 2001. Retrieved 29 April 2024.
  20. ^ Onyeogulu, T; Ogoke, U.P. (29 January 2023). "Statistical Analyses on the Correlation of Corruption Perception Index and Some Other Indices in Nigeria". Scientia Africana. 21 (3): 37–48. doi:10.4314/sa.v21i3.3.
  21. ^ Koeswayo, P. S.; Handoyo, S.; Abdul Hasyir, D (2024). "Investigating the Relationship between Public Governance and the Corruption Perception Index". Cogent Social Sciences. 10 (1). doi:10.1080/23311886.2024.2342513.
  22. ^ Hough, Dan (27 January 2016). "Here's this year's (flawed) Corruption Perception Index. Those flaws are useful". The Washington Post. ISSN 0190-8286. Retrieved 27 January 2016.
  23. ^ Werve, Jonathan (23 September 2008). "TI's Index: Local Chapter Not Having It". Global Integrity. Archived from the original on 14 May 2013.
  24. ^ a b Cobham, Alex (22 July 2013). "Corrupting Perceptions". Foreign Policy. Archived from the original on 4 December 2014. Retrieved 6 March 2017.
  25. ^ Hamilton, Alexander (2017). "Can We Measure the Power of the Grabbing Hand? A Comparative Analysis of Different Indicators of Corruption" (PDF). World Bank Policy Research Working Paper Series.
  26. ^ Campbell, Stuart (2013). "Perception is Not Reality: The FCPA, Brazil, and the Mismeasurement of Corruption". Minnesota Journal of International Law. 22 (1). Rochester, NY: Elsevier: 247–282. SSRN 2210019.
  27. ^ "2015 Corruptions Perceptions Index - Explore the results". Transparency.org. 27 January 2016. Retrieved 5 January 2023.
  28. ^ "CPI 2023: Highlights and insights - News". Transparency.org. 30 January 2024. Retrieved 29 April 2024.
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  31. ^ "Nigeria oil bribery case: Netherlands and US must reopen…". Transparency.org. 22 May 2023. Retrieved 29 April 2024.
  32. ^ Dell, G., & McDevitt, A. (2022). Exporting Corruption 2022: Assessing Enforcement of the OECD Anti-Bribery Convention. In www.transparency.org (No. 978-3-96076-228–7). Transparency International.
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