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The Corruption Perceptions Index (CPI) is an index that scores and ranks countries by their perceived levels of public sector corruption, as assessed by experts and business executives. The CPI generally defines corruption as an "abuse of entrusted power for private gain". The index is published annually by the non-governmental organisation Transparency International since 1995.

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).

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.

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.

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 takes into account 13 different surveys and assessments from 12 different institutions. The institutions are:

• African Development Bank (based in Côte d'Ivoire)
• Bertelsmann Foundation (based in Germany)
• Economist Intelligence Unit (based in the UK)
• Freedom House (based in the US)
• Global Insight (based in the US)
• International Institute for Management Development (based in Switzerland)
• Political and Economic Risk Consultancy (based in Hong Kong)
• The PRS Group, Inc. (based in the US)
• World Bank
• World Economic Forum
• World Justice Project (based in the US)

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

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.

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. (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."

Phenomena and Indices Related to the CPI

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, as well as an increase in GDP growth of 1.7% for every unit increase in a country's CPI score. 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" 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 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.

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.

CPI and Some Other Phenomena and Indices

Thesis The Relationship Between Corruption And Income Inequality: A Crossnational Study, 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 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" 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 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:

• 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".

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."

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.

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.

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.

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.

Ranking over Time

As stated by Transparency International in 2024, 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

2020–2023

Corruption Perceptions Index table:

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

2012–2019

Corruption Perceptions Index table:

#	Nation or Territory	2019		2018		2017		2016		2015		2014		2013		2012
		Score	Δ	Score	Δ	Score	Δ	Score	Δ	Score	Δ	Score	Δ	Score	Δ	Score
1	New Zealand	87	1	87	1	89		90		91	1	91	1	91		90
1	Denmark	87		88	1	88	1	90		91		92		91		90
3	Finland	86		85		85		89		90		89		89	2	90
4	Sweden	85	1	85	3	84	2	88		89		87	1	89	1	88
4	Singapore	85	1	85	3	84	1	84		85		84	2	86		87
4	Switzerland	85	1	85		85	2	86	1	86	1	86	2	85	1	86
7	Norway	84		84	4	85	3	85	1	88		86		86	2	85
8	Netherlands	82		82		82		83	1	84	1	83		83	1	84
9	Germany	80	2	80	1	81	2	81	1	81	1	79		78	1	79
9	Luxembourg	80		81	1	82	2	81	3	85	2	82	2	80	1	80
11	Iceland	78	3	76	1	77	1	78	1	79	1	79		78	1	82
12	United Kingdom	77	1	80	3	82	2	81	1	81	3	78		76	3	74
12	Canada	77	3	81	1	82	1	82	1	83		81	1	81		84
12	Austria	77	2	76	2	75	1	75	1	76	7	72	3	69	1	69
12	Australia	77	1	77		77		79		79	2	80	2	81	2	85
16	Hong Kong	76	2	76	1	77	2	77	3	75	1	74	2	75	1	77
17	Belgium	75		75	1	75	1	77		77		76		75	1	75
18	Estonia	74		73	3	71	1	70	1	70	4	69	1	68	4	64
18	Ireland	74		73	1	74		73	1	75	1	74	4	72	4	69
20	Japan	73	2	73	2	73		72	2	75	3	76	3	74	1	74
21	United Arab Emirates	71	2	70	2	71	3	66	1	70	3	70		69	1	68
21	Uruguay	71	2	70		70	2	71		74		73	2	73	1	72
23	United States	69	1	71	6	75	2	74	2	76	1	74	2	73		73
23	France	69	2	72	2	70		69		70	4	69	5	71		71
25	Bhutan	68		68	1	67	1	65		65	3	65	1	63	2	63
26	Chile	67	1	67	1	67	2	66	1	70	2	73	1	71	2	72
27	Seychelles	66	1	66	8	60	4			55	4	55	3	54	4	52
28	Taiwan	65	3	63	2	63	2	61		62	5	61		61	1	61
29	Bahamas	64		65	1	65	4	66				71	2	71		71
30	Barbados	62	5	68		68	6	61	14			74	2	75		76
30	Portugal	62		64	1	63		62	1	64	3	63	2	62		63
30	Spain	62	11	58	1	57	1	58	4	58	1	60	2	59	10	65
30	Qatar	62	3	62	4	63	2	61	9	71	5	69	1	68	1	68
34	Botswana	61		61		61	1	60	6	63	2	63	1	64		65
35	Brunei Darussalam	60	4	63	1	62	9	58	3					60	8	55
35	Lithuania	60	3	59		59		59	2	59	4	58	3	57	5	54
35	Israel	60	1	61	2	62	4	64	4	61	6	60	2	61	3	60
35	Slovenia	60	1	60	2	61	3	61	3	60	6	58	3	57	6	61
39	Saint Vincent and the Grenadines	59	2	58	1	58	5	60				62	2	62	3	62
39	South Korea	59	6	57	6	54	1	53	9	54	1	55	2	55	1	56
41	Cape Verde	58	4	57	3	55	10	59	2	55	3	57	2	58		60
41	Poland	58	5	60		60	7	62		63	7	61	2	60	3	58
41	Cyprus	58	3	59	4	57	5	55	15	61	1	63		63	2	66
44	Costa Rica	56	4	56	10	59	3	58	1	55	8	54	1	53	1	54
44	Georgia	56	3	58	5	56	2	57	4	52	3	52	4	49	4	52
44	Latvia	56	3	58	1	58	4	57	6	56	6	55	5	53	5	49
44	Czech Republic	56	6	59	4	57	5	55	9	56	15	51	4	48	3	49
48	Saint Lucia	55	2	55	2	55	13	60	11			71	2	71		71
48	Dominica	55	3	57	3	57	4	59	2			58	1	58		58
50	Malta	54	1	54	5	56	1	55	13	60	10	55	1	56	2	57
51	Malaysia	53	10	47	1	47	7	49	1	50	3	52	2	50	1	49
51	Grenada	53	2	52	1	52	6	56
51	Rwanda	53	3	56		55	2	54	7	54	12	49	6	53	1	53
51	Saudi Arabia	53	7	49	1	49	5	46	14	52	7	49	8	46	3	44
51	Italy	53	2	52	1	50	6	47	1	44	8	43		43	3	42
56	Oman	52	3	52	15	44	4	45	4	45	4	45	3	47		47
56	Namibia	52	4	53	1	51		52	8	53	10	49	2	48	1	48
56	Mauritius	52		51	2	50	4	54	5	53	3	54	4	52	9	57
59	Slovakia	50	2	50	3	50		51	4	51	4	50	7	47	1	46
60	Jordan	48	2	49	1	48	2	48	12	53	10	49	11	45	8	48
60	Greece	48	7	45	8	48	10	44	11	46	11	43	11	40	14	36
60	Cuba	48	1	47	1	47	2	47	4	47	7	46		46	5	48
63	Croatia	47	3	48	3	49	2	49	5	51	11	48	4	48	5	46
64	São Tomé and Príncipe	46		46		46	2	46	4	42	10	42	4	42		42
64	Vanuatu	46		46	7	43
66	Argentina	45	19	40		39	10	36	11	32	1	34	1	34	4	35
66	Montenegro	45	1	45	3	46		45	3	44	15	42	9	44	8	41
66	Senegal	45	1	45	1	45	2	45	3	44	8	43	8	41	17	36
66	Belarus	45	4	44	2	44	11	40	27	32	13	31	4	29		31
70	Hungary	44	6	46	2	45	9	48	7	51	2	54	1	54	1	55
70	South Africa	44	3	43	2	43	7	45	3	44	6	44	5	42	3	43
70	Romania	44	9	47	2	48	2	48	1	46	11	43		43	3	44
70	Suriname	44	3	43	4	41	13	45	24	36	12	36	6	36	6	37
74	Jamaica	43	4	44	2	44	15	39	14	41	16	38	2	38		38
74	Tunisia	43	1	43	1	42	1	41	1	38	3	40	2	41	2	41
74	Bulgaria	43	3	42	6	43	4	41	6	41		43	8	41	2	41
77	Bahrain	42	22	36	4	36	33	43	20	51	5	49	2	48	4	51
77	Solomon Islands	42	7	44	15	39	13	42
77	Armenia	42	28	35	2	35	6	33	18	35	1	37		36	11	34
80	Ghana	41	2	41	3	40	11	43	14	47	5	48	2	46	1	45
80	Morocco	41	7	43	8	40	9	37	2	36	8	39	11	37	3	37
80	India	41	2	41	3	40	2	40	3	38	9	38	9	36		36
80	China	41	7	39	10	41	2	40	4	37	17	36	20	40		39
80	Benin	41	5	40		39	10	36	12	37	3	39	14	36		36
85	Guyana	40	8	37	2	38	17	34	11	29	5	30	12	27	3	28
85	Trinidad and Tobago	40	7	41	1	41	24	35	29	39	13	38	2	38	3	39
85	Indonesia	40	4	38	7	37	6	37	2	36	19	34	7	32	4	32
85	Burkina Faso	40	7	41	4	42	2	42	4	38	9	38	2	38		38
85	Lesotho	40	7	41	4	42	9	39	22	44	6	49		49	9	45
85	Kuwait	40	7	41	7	39	10	41	20	49	12	44	2	43	3	44
91	Serbia	39	4	39	10	41	5	42	1	40	7	41	6	42	8	39
91	Turkey	39	13	41	3	40	6	41	9	42	2	45	11	50	1	49
93	Sri Lanka	38	4	38	2	38	4	36	12	37	2	38	6	37	12	40
93	Ecuador	38	21	34	3	32	3	31	14	32	4	33	8	35	16	32
93	Timor-Leste	38	12	35	14	38	10	35	22	28	10	28	14	30	6	33
96	Ethiopia	37	18	34	7	35	1	34	6	33	8	33	1	33	2	33
96	Vietnam	37	21	33	10	35	6	33	2	31	8	31	3	31	7	31
96	Gambia	37	3	37	37	30	15	26	22	28	3	29	1	28	22	34
96	Colombia	37	3	36	3	37	6	37	7	37	11	37		36		36
96	Tanzania	37	3	36	4	36	13	32	1	30	2	31	8	33	9	35
101	Kosovo	36	8	37	8	39	10	36	7	33	8	33	1	33	6	34
101	Thailand	36	2	36	3	37	5	35	25	38	9	38	17	35	14	37
101	Peru	36	4	35	9	37	5	35	13	36	3	38	2	38		38
101	Panama	36	8	37	3	37	9	38	15	39	22	37	8	35	19	38
101	Bosnia and Herzegovina	36	12	38	2	38	8	39	7	38	4	39	8	42		42
106	Brazil	35	1	35	9	37	17	40	3	38	7	43	3	42	3	43
106	Mongolia	35	13	37	10	36	16	38	15	39	8	39	3	38	11	36
106	Albania	35	7	36	8	38	8	39	5	36	22	33	6	31	3	33
106	Egypt	35	1	35	12	32	9	34	20	36	6	37	20	32	4	32
106	Algeria	35	1	35	7	33	4	34	20	36	12	36	6	36	11	34
106	Ivory Coast	35	1	35	2	36	5	34	2	32	9	32	21	27		29
106	North Macedonia	35	13	37	14	35	17	37	24	42	2	45	3	44		43
113	Kazakhstan	34	11	31	2	31	9	29	8	28	3	29	14	26	7	28
113	Nepal	34	11	31	2	31	9	29	1	27	4	29	10	31	23	27
113	Philippines	34	14	36	12	34	10	35	6	35	10	38	9	36	11	34
113	Zambia	34	8	35	9	37	9	38	11	38	9	38	2	38	5	37
113	Eswatini	34	24	38	4	39	16					43	13	39		37
113	El Salvador	34	8	35	7	33	17	36	23	39	8	39	3	38		38
119	Sierra Leone	33	10	30	1	30	7	30	4	29		31		30	4	31
120	Moldova	32	3	33	5	31	1	30	21	33	1	35	1	35	8	36
120	Niger	32	6	34	2	33	11	35	3	34	5	35	3	34	7	33
120	Pakistan	32	3	33		32	1	32	1	30	9	29	1	28	12	27
123	Malawi	31	3	32	2	31	2	31	9	31	1	33	19	37	3	37
123	Bolivia	31	9	29	20	33	1	33	15	34	5	35	3	34	1	34
123	Gabon	31	1	31	7	32	16	35	3	34	4	37	12	34	4	35
126	Djibouti	30	2	31	2	31	1	30	25	34	9	34	13	36		36
126	Kyrgyzstan	30	6	29	3	29	1	28	13	28	13	27	14	24	4	24
126	Azerbaijan	30	26	25	30	31	1	30	4	29	7	29	1	28	12	27
126	Ukraine	30	6	32	10	30	1	29	1	27	12	26	2	25		26
130	Laos	29	2	29	3	29	12	30	16	25	6	25	5	26	20	21
130	Guinea	29	8	28	10	27	6	27	3	25	6	25	5	24	4	24
130	Myanmar	29	2	29	2	30	6	28	11	22	9	21	1	21	15	15
130	Mexico	29	8	28	3	29	12	30	12	31	8	35	3	34	1	34
130	Maldives	29	6	31	12	33	17	36
130	Mali	29	10	32	2	31	6	32	21	35	20	32	12	28	22	34
130	Togo	29	1	30	12	32	1	32	10	32	20	29	3	29	5	30
137	Russia	28	1	28	3	29	4	29	12	29	17	27	9	28	6	28
137	Papua New Guinea	28	1	28	3	29	1	28	3	25	6	25	1	25	6	25
137	Mauritania	28	7	27	1	28	1	27	31	31	13	30	5	30	4	31
137	Liberia	28	17	32	2	31	32	37	7	37	11	37	11	38	8	41
137	Lebanon	28	1	28	5	28	7	28	13	28	13	27	9	28	1	30
137	Kenya	28	7	27	1	28	2	26	6	25	6	25	9	27	3	27
137	Uganda	28	12	26	2	26		25	12	25	3	26	2	26	10	29
137	Paraguay	28	5	29	3	29	12	30	7	27	20	24		24		25
137	Dominican Republic	28	8	30	6	29	15	31	18	33	13	32	8	29	5	32
146	Nigeria	26	2	27	4	27	12	28		26		27	8	25	5	27
146	Mozambique	26	12	23	5	25	11	27	31	31	8	31		30	4	31
146	Guatemala	26	2	27	1	28	7	28	13	28	8	32	8	29	10	33
146	Iran	26	8	28	8	30	1	29	1	27	6	27	8	25	11	28
146	Angola	26	19	19	2	19	3	18	1	15	2	19	8	23	4	22
146	Bangladesh	26	3	26	6	28	2	26	6	25	6	25	9	27	8	26
146	Honduras	26	14	29	3	29	12	30	12	31	15	29	14	26	7	28
153	Cameroon	25	1	25	1	25	8	26	15	27	6	27	8	25		26
153	Central African Republic	25	4	26	7	23	3	20	14	24	5	24	6	25		26
153	Uzbekistan	25	5	23	1	22	1	21	3	19	13	18	2	17	2	17
153	Tajikistan	25	1	25	9	21	10	25	15	26	16	23	2	22	3	22
153	Comoros	25	9	27	4	27	5	24	17	26	6	26	15	28	6	28
158	Zimbabwe	24	2	22	3	22	3	22	4	21	6	21	1	21	6	20
158	Madagascar	24	6	25	3	24	10	26	22	28	10	28	6	28	9	32
160	Eritrea	23	3	24	8	20	1	18	10	18	12	18	6	20	10	25
161	Nicaragua	22	9	25	1	26	6	26	15	27	3	28	6	28	3	29
162	Chad	20	3	19		20	6	20	12	22	7	22	9	19	2	19
162	Cambodia	20	1	20		21	5	21	6	21	6	21	4	20	3	22
162	Iraq	20	6	18	1	18	3	17	5	16	9	16	1	16	2	18
165	Turkmenistan	19	4	20	6	19	13	22		18	15	17	1	17	2	17
165	Republic of the Congo	19		19	4	21	2	20	13	23	6	23	2	22		26
165	Burundi	19	5	17	13	22	2	20	9	21	9	20	2	21	8	19
168	Haiti	18	7	20	4	22	2	20	1	17	3	19	2	19	2	19
168	Democratic Republic of the Congo	18	7	20		21	5	21	9	22	7	22		22	6	21
168	Libya	18	2	17	1	17	1	14	9	16	5	18	6	15	12	21
168	Guinea Bissau	18	4	16	1	17	3	16	10	17	3	19	2	19		25
172	North Korea	17	4	14	5	17	3	12	7	8	7	8	1	8		8
173	Sudan	16	1	16	3	16	5	14	5	12	8	11	1	11	1	13
173	Afghanistan	16	1	16	5	15	8	15	3	11	6	12	3	8	1	8
173	Equatorial Guinea	16	1	16	1	17	8							19		20
173	Venezuela	16	5	18	1	18	3	17	8	17	3	19	1	20	5	19
177	Yemen	15	1	14	1	16	5	14	16	18	7	19	6	18	11	23
178	Syria	13		13		14	5	13	19	18	5	20	9	17	24	26
179	South Sudan	12	1	13	1	12	4	11	12	15	8	15	2	14
180	Somalia	9		10		9	4	10	9	8	7	8	1	8	1	8