Corruption Perceptions Index

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The Corruption Perceptions Index (CPI) is an index published annually by Transparency International, a German registered association, since 1995.[1] It scores and ranks countries by their perceived levels of public sector[2] corruption, as assessed by experts and business executives.[3] The CPI generally defines corruption as an "abuse of entrusted power for private gain".[4]Template:Rp

From 1995 to 2011, the index was scored on a scale of 10 to 0. Since 2012, the Corruption Perceptions Index has been ranked on a scale from 100 (very clean) to 0 (highly corrupt).

Of the 182 countries ranked in the 2025 CPI, published in February 2026, the top scorers included Denmark (89), Finland (88), and Singapore (84), while those perceived as the most corrupt included South Sudan (9), Somalia (9), and Venezuela (10).[5]

Although widely used as a key indicator of corruption, the CPI does not capture all forms of corruption. Perceptions about corruption may differ from actual levels of corruption and the index focuses solely on the public sector. For a more comprehensive picture, the CPI should be used alongside other assessments.[6]

Methods

The CPI methodology, revised in 2012, enables consistent comparison of corruption perceptions across countries and years. It involves four stages: selecting data sources, rescaling them to a uniform 0–100 scale, aggregating the results, and estimating uncertainty.[4]Template:Rp

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.[4]Template:Rp The institutions are:

Countries need to be evaluated by at least three sources to appear in the CPI.[4]Template:Rp The CPI measures the 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.[4]Template:Rp

Rescaling source data

In order for all data to be aggregated into the CPI, 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 score 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.

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,[10] as well as an increase in GDP growth of 1.7% for every unit increase in a country's CPI score.[11] 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"[12] 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[13] 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.[14]

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.[15]

Other phenomena and indices

A Georgetown University master's thesis The Relationship Between Corruption And Income Inequality: A Crossnational Study,[16] 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[17] 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"[18] 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[19] 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.

Criticism

The CPI has received significant criticism related to its conceptual and methodological limitations, and bias towards developed countries.

According to political scientist Dan Hough, three flaws in the index include:[20]

  • 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.
  • Measuring perception of corruption, rather than corruption itself, may reinforce 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 Volkswagen emissions scandal are not counted as corrupt actions.

While criticizing the Index for its limited usefulness in measuring corruption, Hough says it "helps to keep the fight against corruption on the agendas of policymakers and the global commentariat".[20] He has added that the Index is "still generally regarded as a decent place to start" and says the Index results are not too dissimilar from other indexes of corruption and integrity, such as the Global Corruption Index, the Freedom from Corruption Index, the Index of Public Integrity and the World Bank's index of quality of governance.[21][22]

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 Foreign Policy article, Alex Cobham argues that the CPI reflects an elite bias in popular perceptions of corruption, potentially contributing to a vicious cycle and 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] He noted that "many of the staff and chapters" at Transparency International, "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 that he was "no longer available for doing the Corruption Perceptions Index."[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.[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.[28]

Scoring

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As stated by Transparency International in the 2023 Corruption Perceptions Index,[29] the level of corruption was stagnating at the global level. Only 28 of the 180 countries measured by the CPI at that time had improved their corruption levels over the last twelve years, and 34 countries had significantly worsened. No significant change was recorded for 118 countries. Moreover, according to Transparency International, over 80 percent of the population lived in countries whose CPI score was lower than the global average of 43, and thus corruption remained a problem that affected the majority of people globally.

Among the states with the most significant score decline in the 2023 CPI were authoritarian states such as Venezuela, as well as established democracies that had been rated high for a long time, such as Sweden (decrease of 7, 2023 score 82) or Great Britain (decrease 3, 2023 score 71). Other countries experiencing sharp declines included Sri Lanka, Mongolia, Gabon, Guatemala, and Turkey. In contrast, the most significant improvements in the 2023 CPI score over the preceding twelve years were recorded by Uzbekistan, Tanzania, Ukraine, Ivory Coast, the Dominican Republic and Kuwait.

2025 scores

Below are the scores for each country in the Corruption Perceptions Index for 2025. The scores reflect a country's transparency (i.e., the opposite of corruption).[5]

Legend

Scores Perceived as less corrupt Perceived as more corrupt
since 2012 100–90 89–80 79–70 69–60 59–50 49–40 39–30 29–20 19–10 9–0

Template:Sticky header

2025 scores
# Nation or Territory Score  Rank

Change

1 File:Flag of Denmark.svg Denmark 89
2 File:Flag of Finland.svg Finland 88
3 File:Flag of Singapore.svg Singapore 84
4 File:Flag of New Zealand.svg New Zealand 81
4 File:Flag of Norway.svg Norway 81 +1
6 File:Flag of Sweden.svg Sweden 80 +2
6 File:Flag of Switzerland (Pantone).svg  Switzerland 80 -1
8 File:Flag of Luxembourg.svg Luxembourg 78 -3
8 File:Flag of the Netherlands.svg Netherlands 78 +1
10 File:Flag of Germany.svg Germany 77 +5
10 File:Flag of Iceland.svg Iceland 77
12 Australia Australia 76 -2
12 File:Flag of Estonia.svg Estonia 76 +1
12 File:Flag of Hong Kong.svg Hong Kong 76 +5
12 File:Flag of Ireland.svg Ireland 76 -2
16 File:Flag of Canada (Pantone).svg Canada 75 -1
17 File:Flag of Uruguay.svg Uruguay 73 -4
18 File:Flag of Bhutan.svg Bhutan 71
18 File:Flag of Japan.svg Japan 71 +2
20 File:Flag of the United Kingdom (1-2).svg United Kingdom 70
21 File:Flag of Austria.svg Austria 69 +4
21 File:Flag of Belgium (civil).svg Belgium 69 +1
21 File:Flag of the United Arab Emirates.svg United Arab Emirates 69 +2
24 File:Flag of Barbados.svg Barbados 68 -1
24 File:Flag of Seychelles.svg Seychelles 68 -6
24 File:Flag of the Republic of China.svg Taiwan 68 +1
27 File:Flag of France.svg France 66 -2
28 File:Flag of Lithuania.svg Lithuania 65 +4
29 File:Flag of the Bahamas.svg Bahamas 64 -1
29 File:Flag of the United States.svg United States 64 -1
31 File:Flag of Brunei.svg Brunei Darussalam 63
31 File:Flag of Chile.svg Chile 63 +1
31 File:Flag of Saint Vincent and the Grenadines.svg Saint Vincent and the Grenadines 63 +1
31 File:Flag of South Korea.svg South Korea 63 -1
35 File:Flag of Cape Verde.svg Cape Verde 62
35 File:Flag of Israel.svg Israel 62 -5
37 File:Flag of Dominica.svg Dominica 60 -1
37 File:Flag of Latvia.svg Latvia 60 +1
39 File:Flag of the Czech Republic.svg Czech Republic 59 +7
39 File:Flag of Saint Lucia.svg Saint Lucia 59 -1
41 File:Flag of Botswana.svg Botswana 58 +2
41 File:Flag of Qatar.svg Qatar 58 -3
41 File:Flag of Rwanda.svg Rwanda 58 +2
41 File:Flag of Slovenia.svg Slovenia 58 -5
45 File:Flag of Saudi Arabia.svg Saudi Arabia 57 -4
46 File:Flag of Costa Rica.svg Costa Rica 56 -4
46 File:Flag of Grenada.svg Grenada 56
46 File:Flag of Portugal (official).svg Portugal 56 -3
49 File:Flag of Cyprus.svg Cyprus 55 -3
49 File:Flag of Fiji.svg Fiji 55 +1
49 File:Flag of Spain.svg Spain 55 -3
52 File:Flag of Italy.svg Italy 53
53 File:Flag of Poland.svg Poland 52 +1
54 File:Flag of Malaysia.svg Malaysia 52 +3
54 File:Flag of Oman.svg Oman 52 -4
56 File:Flag of Bahrain.svg Bahrain 50 -6
56 Template:Country data Georgia 50 -3
56 File:Flag of Greece.svg Greece 50 +3
56 File:Flag of Jordan.svg Jordan 50 +3
60 File:Flag of Malta.svg Malta 49 +5
61 File:Flag of Mauritius.svg Mauritius 48 -5
61 File:Flag of Slovakia.svg Slovakia 48 -2
63 File:Flag of Croatia.svg Croatia 47
63 File:Flag of Vanuatu.svg Vanuatu 47 -6
65 File:Flag of Armenia.svg Armenia 46 -2
65 File:Flag of Kuwait.svg Kuwait 46
65 File:Flag of Montenegro.svg Montenegro 46
65 File:Flag of Namibia.svg Namibia 46 -6
65 File:Flag of Senegal.svg Senegal 46 +4
70 File:Flag of Benin.svg Benin 45 -1
70 File:Flag of Romania.svg Romania 45 -5
70 File:Flag of São Tomé and Príncipe.svg São Tomé and Príncipe 45 -1
73 File:Flag of Jamaica.svg Jamaica 44
73 File:Flag of the Solomon Islands.svg Solomon Islands 44 +3
73 File:Flag of East Timor.svg Timor-Leste 44
76 File:Flag of the People's Republic of China.svg China 43
76 File:Flag of Ghana.svg Ghana 43 +4
76 File:Flag of Côte d'Ivoire.svg Ivory Coast 43 -7
76 File:Flag of Kosovo.svg Kosovo 43 -3
80 File:Flag of Moldova.svg Moldova 42 -4
81 File:Flag of South Africa.svg South Africa 41 +1
81 File:Flag of Trinidad and Tobago.svg Trinidad and Tobago 41 +1
81 File:Flag of Vietnam.svg Vietnam 41 +7
84 File:Flag of Bulgaria.svg Bulgaria 40 -8
84 File:Flag of Burkina Faso.svg Burkina Faso 40 -2
84 File:Flag of Cuba.svg Cuba 40 -2
84 File:Flag of Guyana.svg Guyana 40 +8
84 File:Flag of Hungary.svg Hungary 40 -2
84 Template:Country data North Macedonia 40 +4
84 File:Flag of Tanzania.svg Tanzania 40 -2
91 File:Flag of Albania.svg Albania 39 -11
91 File:Flag of India.svg India 39 +5
91 File:Flag of Maldives.svg Maldives 39 +5
91 File:Flag of Morocco.svg Morocco 39 +8
91 File:Flag of Tunisia.svg Tunisia 39 +1
96 File:Flag of Ethiopia.svg Ethiopia 38 +3
96 File:Flag of Kazakhstan.svg Kazakhstan 38 -8
96 File:Flag of Suriname.svg Suriname 38 -8
99 File:Flag of Colombia.svg Colombia 37 -7
99 File:Flag of the Dominican Republic.svg Dominican Republic 37 +5
99 File:Flag of The Gambia.svg Gambia 37 -3
99 File:Flag of Lesotho.svg Lesotho 37
99 File:Flag of Zambia.svg Zambia 37 -7
104 File:Flag of Argentina.svg Argentina 36 -5
104 File:Flag of Belize.svg Belize 36
104 File:Flag of Ukraine.svg Ukraine 36 +1
107 File:Flag of Brazil.svg Brazil 35
107 File:Flag of Sri Lanka.svg Sri Lanka 35 +14
109 File:Flag of Algeria.svg Algeria 34 -2
109 File:Flag of Bosnia and Herzegovina.svg Bosnia and Herzegovina 34 +5
109 File:Flag of Indonesia.svg Indonesia 34 -10
109 File:Flag of Laos.svg Laos 34 +5
109 File:Flag of Malawi.svg Malawi 34 -2
109 File:Flag of Nepal.svg   Nepal 34 -2
109 File:Flag of Sierra Leone.svg Sierra Leone 34 +5
116 File:Flag of Ecuador.svg Ecuador 33 +5
116 File:Flag of Panama.svg Panama 33 -2
116 File:Flag of Serbia.svg Serbia 33 -11
116 File:Flag of Thailand.svg Thailand 33 -9
120 File:Flag of Angola.svg Angola 32 +1
120 File:Flag of El Salvador.svg El Salvador 32 +10
120 File:Flag of the Philippines.svg Philippines 32 -6
120 File:Flag of Togo (3-2).svg Togo 32 +1
124 File:Flag of Belarus.svg Belarus 31 -10
124 File:Flag of Djibouti.svg Djibouti 31 +3
124 File:Flag of Mongolia.svg Mongolia 31 -10
124 File:Flag of Niger.svg Niger 31 -17
124 File:Flag of Turkey.svg Turkey 31 -17
124 File:Flag of Uzbekistan.svg Uzbekistan 31 -3
130 File:Flag of Azerbaijan.svg Azerbaijan 30 +24
130 File:Flag of Egypt.svg Egypt 30
130 File:Flag of Kenya.svg Kenya 30 -9
130 File:Flag of Mauritania.svg Mauritania 30
130 File:Flag of Peru.svg Peru 30 -3
135 File:Flag of Gabon.svg Gabon 29
136 File:Flag of Bolivia.svg Bolivia 28 -3
136 File:Flag of Iraq.svg Iraq 28 +4
136 File:Flag of Liberia.svg Liberia 28 -1
136 File:Flag of Mali.svg Mali 28 -1
136 File:Flag of Pakistan.svg Pakistan 28 -1
141 File:Flag of Mexico.svg Mexico 27 -1
142 File:Flag of Cameroon.svg Cameroon 26 -2
142 File:Flag of Guatemala.svg Guatemala 26 +4
142 File:Flag of Guinea.svg Guinea 26 -9
142 File:Flag of Kyrgyzstan.svg Kyrgyzstan 26 +4
142 File:Flag of Nigeria.svg Nigeria 26 -2
142 File:Flag of Papua New Guinea.svg Papua New Guinea 26 -15
148 File:Flag of Madagascar.svg Madagascar 25 -8
148 File:Flag of Uganda.svg Uganda 25 -8
150 File:Flag of Bangladesh.svg Bangladesh 24 +1
150 File:Flag of the Central African Republic.svg Central African Republic 24 -1
150 File:Flag of Paraguay.svg Paraguay 24 -1
153 File:Flag of the Republic of the Congo.svg Congo 23 -2
153 File:Flag of Eswatini.svg Eswatini 23 -18
153 File:Flag of Iran.svg Iran 23 -2
153 File:Flag of Lebanon.svg Lebanon 23 +1
157 File:Flag of Chad.svg Chad 22 +1
157 File:Flag of Honduras (1949–2022, 2026–present).svg Honduras 22 -3
157 File:Flag of Russia.svg Russia 22 -3
157 File:Flag of Zimbabwe.svg Zimbabwe 22 +1
161 File:Flag of Guinea-Bissau.svg Guinea-Bissau 21 -3
161 File:Flag of Mozambique.svg Mozambique 21 -15
163 File:Flag of Cambodia.svg Cambodia 20 -5
163 File:Flag of the Comoros.svg Comoros 20 -5
163 File:Flag of the Democratic Republic of the Congo.svg Democratic Republic of the Congo 20
166 File:Flag of Tajikistan.svg Tajikistan 19 -2
167 File:Flag of Burundi.svg Burundi 17 -2
167 File:Flag of Turkmenistan.svg Turkmenistan 17 -2
169 File:Flag of the Taliban.svg Afghanistan 16 -4
169 File:Flag of Haiti.svg Haiti 16 -1
169 File:Flag of Myanmar.svg Myanmar 16 -1
172 File:Flag of Equatorial Guinea.svg Equatorial Guinea 15 +1
172 File:Flag of North Korea (March 2026-).svg North Korea 15 -2
172 File:Flag of Syria (2025-).svg Syria 15 +5
175 File:Flag of Nicaragua.svg Nicaragua 14 -3
175 File:Flag of Sudan.svg Sudan 14 -5
177 File:Flag of Eritrea.svg Eritrea 13 -4
177 File:Flag of Libya.svg Libya 13 -4
177 File:Flag of Yemen.svg Yemen 13 -4
180 File:Flag of Venezuela.svg Venezuela 10 -2
181 File:Flag of Somalia.svg Somalia 9 -2
181 File:Flag of South Sudan.svg South Sudan 9 -1


List by region

The following table lists the average CPI score for each region since 2012. Template:Static row numbersTemplate:Sticky-headerTemplate:Sort-underTemplate:Table alignment

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.[31] 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.[32]

The report Exporting Corruption 2022,[33] 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 but still faces significant obstacles. This calls for a more comprehensive approach to tackling corruption, addressing both domestic and international aspects.

See also

References

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  27. ^ Page Module:Citation/CS1/styles.css has no content.Campbell, Stuart (2013). "Perception is Not Reality: The FCPA, Brazil, and the Mismeasurement of Corruption" (PDF). Minnesota Journal of International Law. 22 (1). Rochester, NY: 247–282. SSRN 2210019.
  28. ^ Page Module:Citation/CS1/styles.css has no content."2015 Corruptions Perceptions Index – Explore the results". Transparency.org. 27 January 2016. Retrieved 5 January 2023.
  29. ^ Page Module:Citation/CS1/styles.css has no content."CPI 2023: Highlights and insights – News". Transparency.org. 30 January 2024. Retrieved 29 April 2024.
  30. ^ Bahamas and Barbados were not scored this year, lowering the regional average.
  31. ^ Page Module:Citation/CS1/styles.css has no content."CPI 2023: Trouble at the top – News". Transparency.org. 30 January 2024. Retrieved 29 April 2024.
  32. ^ Page Module:Citation/CS1/styles.css has no content."Nigeria oil bribery case: Netherlands and US must reopen…". Transparency.org. 22 May 2023. Retrieved 29 April 2024.
  33. ^ Dell, G., & McDevitt, A. (2022). Exporting Corruption 2022: Assessing Enforcement of the OECD Anti-Bribery Convention. In www.transparency.org (Template:ISBN). Transparency International.

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