Corruption Realities Index 2010

The most famous corruption indicator is Transparency International’s Corruption Perceptions Index. Its only problem is that the perceptions of their self-appointed experts have nothing to do with reality!

As I explained in previous posts on this blog, it suffers from numerous flaws. Part of it has to do with its questionable methodology: using changing mixes of different surveys to gauge a fluid, opaque-by-definition social phenomenon. Another is its reliance on its appeal to authority, the theory being that “experts” in business and think-tanks know more about corruption relative to anyone else. Countries with more regulations are systematically prejudged, as are those facing hostile media environments such as Russia or Venezuela. Above all, the CPI doesn’t pass the face validity test – in other words, many of its results are frankly ludicrous. Is it truly plausible that Russia (2.1) is as corrupt as failed states like Zimbabwe (2.4) or D.R. Congo (2.0), or that Italy (3.9) is more corrupt than Saudi Arabia (4.7) which is a feudalistic monarchy!?

This suggests that we urgently need another, more objective index. Thus I present the Corruption Realities Index (CRI)!

Unlike my previous attempt at this, the Karlin Corruption Index – which was rightly critiqued for being no less subjective than the CPI (though I do believe it was more accurate) – this time round I am drawing on real world data. In particular, there are three corruption indices that aren’t as well known as the CPI, but far more useful.

One of them is Transparency International’s less well-known Global Corruption Barometer. Every year, they poll respondents on the following question: “In the past 12 months have you or anyone living in your household paid a bribe?” The answers hint at the prevalence of corruption in everyday life, as experienced by a sample of normal people, and as such they almost certainly offer a better picture than the perceptions of experts who are prone to the narrative fallacy and are unduly influenced by the ideological biases of the international business media (e.g. op-eds in The Economist or the WSJ). A good example is the reputational fallout Russia experienced in the wake of the prosecution of Mikhail Khodorkovsky, which saw its CPI retreat despite the lack of any noticeable increase in corruption on the ground.

Another key resource is the Global Integrity Report, which evaluates countries on their “actually existing” Legal Frameworks and Actual Implementation on issues such as “the transparency of the public procurement process, media freedom, asset disclosure requirements, and conflicts of interest regulations.” This involves line by line examination of the laws in question, and the “de facto realities of practical implementation.” Crucially, the assessments are blindly reviewed by a panel of peer reviewers and outside experts, which is an important antidote to bias.

Finally, there is the International Budget Partnership, which – believe it or not – assesses budget transparency and accountability. It compiles an Open Budget Index on the basis of factors such as budget documents availability, and the effectiveness of oversight by legislatures and supreme audit institutions. People who think of Eastern Europe as a black hole of government corruption will be surprised to learn that it is the best performing region after the developed world, while the Middle East, China, and sub-Saharan Africa are distinguished by their opacity.

Data from all three sources – to the extent that it is available – is amalgamated and fed through a formula to produce the Corruption Realities Index.

GCB is the percentage of people saying they or their households paid a bribe in the past 12 months from 2010 data. GILF is the Global Integrity Legal Framework score. GIAI is the Global Integrity Actual Implementation score. Most Global Integrity data is from 2007-2010. OBI is the Open Budget Index score from 2010 data. The CRI is the Corruption Realities Index. More details are given at the bottom of the table.

	Country	GCB /%	GILF /100	GIAI /100	OBI /100	CRI
1	Denmark	0				10.0
2	UK	1			87	9.1
3	Norway	1			83	9.0
4	Korea, South	2	96	82	71	8.7
5	Finland	2				8.6
6	Netherlands	2				8.6
7	Switzerland	2				8.6
8	Germany*†	2	83	83	67	8.4
9	Portugal*†	3	86	86	58	8.3
10	Iceland	3				8.3
11	Australia*†	2	78	78		8.2
12	Israel*†	4	83	83		8.2
13	USA	5	90	78	82	8.1
14	Slovenia	4			68	8.1
15	New Zealand	4			90	8.0
16	Ireland	4				8.0
17	Brazil	4	85	66	71	7.9
18	Spain	5	84	74	63	7.8
19	Canada	4	90	61		7.8
20	Hong Kong	5				7.8
21	Georgia	3	86	58	55	7.8
22	Bulgaria	8	97	73	56	7.7
23	Croatia	5			57	7.7
24	France	7	87	68	87	7.7
25	Japan	9	91	76		7.7
26	Argentina	12	97	77	56	7.5
27	Taiwan	7				7.4
28	Latvia	15	93	76		7.3
29	Italy	13	84	71	58	7.1
30	Poland	15	86	71	64	7.0
31	Singapore	9				7.0
32	Austria	9				7.0
33	Czech Republic	14	84	64	62	6.9
34	Peru	22	93	70	65	6.7
35	Chile	21	87	66	72	6.6
36	Indonesia	18	92	56	51	6.6
37	FYR Macedonia	21	90	65	49	6.5
38	Vanuatu	16	84	55		6.5
39	Fiji	12	64	64		6.5
40	Kosovo	16	78	60		6.5
41	Romania	28	95	64	59	6.3
42	Armenia*	22	72	72		6.3
43	China	9	76	43	13	6.2
44	Hungary	24	83	62		6.2
45	Serbia	17	80	44	54	6.2
46	Russia	26	90	54	60	6.1
47	Colombia	24	89	49	61	6.1
48	Philippines	16	84	31	55	6.0
49	Malaysia	9	57	37	39	6.0
50	Luxembourg	16				6.0
51	Papua New Guinea*	26	69	69	57	6.0
52	Bosnia & Herzegovina	23	90	39	44	5.8
53	Thailand	23	79	50	42	5.8
54	Venezuela	20	84	39	34	5.8
55	Lithuania	34	85	63		5.8
56	Mexico	31	83	59	52	5.8
57	Greece	18				5.8
58	Moldova	37	89	59		5.7
59	Solomon Islands	20	63	52		5.6
60	Belarus	27	81	48		5.6
61	Turkey	33	75	57	57	5.5
62	Bolivia	30	78	56	13	5.3
63	Ghana	37	78	51	54	5.3
64	Ukraine	34	77	39	62	5.2
65	India	54	86	55	67	5.0
66	Pakistan	49	91	47	38	4.9
67	El Salvador	31			37	4.8
68	Azerbaijan	47	88	40	43	4.8
69	Lebanon	34	65	39	32	4.7
70	Mongolia	48	70	43	60	4.6
71	Kenya	45	62	45	49	4.5
72	Palestine	51	73	41		4.3
73	Sierra Leone	71	79	58		4.2
74	Zambia	42			36	4.1
75	Senegal*	56	65	65	3	4.0
76	Uganda	86	99	45	55	4.0
77	Nigeria	63	73	44	18	3.8
78	Vietnam	44	56	28	14	3.7
79	Cameroon	54	69	39	2	3.6
80	Iraq	56	75	32	0	3.4
81	Liberia	89	64	43	40	3.1
82	Afghanistan	61			21	2.8
83	Cambodia	84	58	30	15	2.6

* The Global Integrity scores for Legal Framework and Actual Implementation were given as one averaged figure, so bear in mind that
† Global Integrity scores were collected for 2006 or earlier, so may no longer be up to date.
The CRI for countries in italics was generated on the basis of only one piece of data, the percentage of people saying they or someone in their household paid a bribe in the last year. As such, their CRI has a high margin of error.

Formulas

For countries with all four data points. (10-sqrt(GCB))*5 + (GILF + GIAI)/5 + sqrt(OBI) = CRI, with the GCB/GILF/GIAI/OBI weighted 50-20-20-10.
For countries with no OBI. (10-sqrt(GCB))*5 + (GILF + GIAI)/4 = CRI, with the GCB/GILF/GIAI weighted 50-25-25.
For countries with no Global Integrity data. (10-sqrt(GCB))*7.5 + sqrt(OBI)*2.5 = CRI, with the GCB/OBI weighted 75-25.
For countries with only GCB. (10-sqrt(GCB))*10, with the GCB being the only weight by definition.

Needless to say, the accuracy of any CRI score increases with the amount of data it is based on.

I did not bother including any country that doesn’t have polling data on the prevalence of bribery over the past year, as it is an indispensable indicator. One can only hope that the Global Corruption Barometer will expand its coverage in the coming years, as the CRI depends so much on its data.

One major group of countries that isn’t assessed here, because of a lack of data, are the Gulf monarchies. If we make the (rather generous?) assumption than only 5% of their households pay a bribe in any given year, then based on the UAE’s and Kuwait’s Global Integrity scores and Saudi Arabia’s OBI, these countries will have the following CRI: Kuwait (6.2), UAE (6.7), Saudi Arabia (4.0).

This is but the beginning. I hope to search out more sources of data like the GCB, and keep expanding the Corruption Realities Index in the years ahead.

EDIT 05/26/2011: Note that there are going to be substantial internal variations for corruption within a country, as different regions will have varyingly corrupt bureaucracies and police forces. To take the example of Russia, for instance, a recent FOM poll indicates that the frequency of requests for bribes ranged from, say, 7% in Omsk oblast, to 31% in St.-Petersburg. This would translate into CRI scores of 7.3 and 5.9, respectively.