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The Corruption Situation
Corruption is notoriously difficult to measure. One reason is that what people understand by the term varies somewhat not only across cultures but even among individuals and groups within the same culture. However, there are other factors. Most crimes have victims who can and often do report illegal actions to the authorities. Corruption is different. Some forms, notably so-called social corruption - such as various forms of favouritism (nepotism, cronyism, etc.) and arguably gift-giving - are not illegal in most jurisdictions. Indeed, in some Asian countries, such as Indonesia and Laos, nepotism is not necessarily illicit; within the dominant culture, someone promoted to high office who did not then promote members of his or her family would be seen by many citizens, at least in the past, as disloyal and behaving improperly. Other forms, mainly of economic corruption, either do not involve anyone other than the corrupt official (e.g. embezzlement) or involve bilateral collusion. In the former case, corrupt officials do not generally report themselves, whereas in the latter, someone who has paid a bribe to avoid a fine or improperly secure a building permit is unlikely to report the fact that they paid a corrupt official, since they might then have to pay the fine or lose their permit.
Given this, official legal statistics on corruption - the number of cases reported; the number investigated; the number of prosecutions; the number of convictions; sentences meted out - have limited value. While they can tell us, for instance, that the ratio of convictions to prosecutions is higher in country A than in country B, or that sentences for similar crimes appear to be much harsher in country B than in country A, they tell us little about the actual scale of corruption in either state.
Because of this problem with official legal statistics, analysts have devised various alternative methods for assessing the scale of corruption in any given state. The first and still most popular is to mount perceptual and attitudinal surveys, of which the best known is Transparency International’s (TI’s) Corruption Perceptions Index (CPI); this has appeared annually since 1995. The methodology changed somewhat in 2012, since when, according to TI itself, it is legitimate to compare one year’s findings with another’s.3 Unfortunately, TI warns against comparing one year’s results with another’s for pre-2012 CPIs. However, here, in line with the practice of many analysts, pre-2012 data are cited as well as the most recent results, faute de mieux; those uneasy about reading the results as time-series data can at least compare country scores in any given year.
Since 2012, the CPI has been scaled 0-100, whereby the lower the score, the more corrupt a country is perceived to be; the CPIs through 2011 were scaled 0-10, with the directionality being the same (i.e. less corrupt countries had higher scores). In Table 4.1, pre-2012 scores have been presented according to the new scaling to make comparison easier. Moreover, the scores in the earliest CPIs were given to two decimal places; again for the sake of easy comparability, these have been rounded here to one decimal place before removing the decimal point.
Table 4.1 reveals that, with the exceptions of 2003, when it was significantly better than Georgia, and 2005, when it was just marginally better than Georgia, Russia has consistently been seen as the most corrupt
Table 4.1 CPI (perceptions-based) corruption scores 1997-2015
Note: Empty cells = no data.
Source: Transparency International website, http://www.transparency.org/research/cpi/overview. Accessed 28 November 2015 and 20 March 2016.
of the four countries analysed here, and by quite a margin. Second, Russia does appear to have improved significantly towards the end of President Medvedev’s term (in office 2008-2012), and has apparently been essentially in a steady state since Putin returned to the presidency in 2012. A third point is that Georgia has improved significantly since 2003, a point explored later in this chapter. Finally, while Bulgaria had improved just 2 years before its admission to the EU in comparison with the year 2000, Romania had not; its score in both years was almost identical. On the other hand, Bulgaria was perceived to have actually become more corrupt within three years of joining the EU, though it has since improved somewhat; this said, it has been treading water in recent years. Romania appears to have steadily improved (the drop between 2012 and 2014 is marginal), and has pulled away from Bulgaria in the most recent (2015) CPI.
It must be acknowledged that perceptions may not reflect the actual corruption situation, although it is impossible to determine exactly what the latter is in any country. Moreover, perceptions are a form of reality anyway, since we all make decisions based on them. Nevertheless, partly in response to criticisms of its perceptions indices, TI has since 2003 also published a Global Corruption Barometer (GCB) that includes responses to a question designed to measure citizens’ actual experiences of corruption. Table 4.2 shows the responses to the question ‘In the past 12 months, have you or has anyone living in your household paid a bribe in any form?’ (in more recent GCBs, this has become more precise, by specifying eight to nine agencies, though an aggregate figure for each country is still available).
A number of observations can be made on the basis of Table 4.2. First, Bulgaria appears to be considerably less prone to bribery than Romania, even though they are often treated as basically very similar, including by
Table 4.2 GCB (bribery experience) percentages 2004-2013
Source: Transparency International website, http://www.transparency.org/ research/gcb/overview. Accessed 28 November 2015 (the latest GCB results are to be released region by region late-2015 to mid-2016, but were still unavailable for Central and Eastern Europe as ofmid-March 2016).
the EU, in terms of the overall corruption situation. Second, there is no clear pattern for Bulgaria in terms of pre-accession or post-accession to the EU; an apparent improvement in the first 2 years of membership was seemingly followed by an increase in bribe paying. In the case of Romania, it appears that the situation may have significantly improved shortly after the country joined the EU, but to have been volatile since then. Third, while Russia’s scores are also volatile, they are invariably high. Finally, the ‘star performer’ among our four selected countries is again Georgia.
While some maintain that experiential responses, such as those included in the GCB, are more useful than perceptual ones, they have at least one major drawback, viz. that experiential questions of the general public are very unlikely to detect high-level (grand) corruption. In addition to the CPI, one of the few methods that can help us to gauge the latter is state capture assessment. According to one recent analysis, which is based partly on World Bank governance indicators, Bulgaria and Romania are both examples of states with a high degree of ‘corporate state capture’ in which ‘public power is exercised primarily for private gain’ (Innes 2014, p. 88).4
Another potential indicator of the corruption situation is the business community’s direct perceptions of the situation as reflected in the World Economic Forum’s annual (since 2004) Global Competitiveness Report (GCR). This provides results of four questions of direct relevance here. The first asks businesspeople to rank-order 155 variables (e.g. access to financing; inflation; tax rates; inefficient government bureaucracy;
Table 4.3 The most problematic factors for doing business: ranking of corruption
Sources: Schwab and Porter (2006, 2008); Schwab (2009, 2011, 2014, 2015).
corruption) in terms of how problematic these factors are for doing business. The results of this are shown in Table 4.3.
Table 4.3 demonstrates clearly that corruption is and has long been a very significant problem for businesspeople in Bulgaria - where it actually became worse shortly after joining the EU - and Russia; that it became much less of a problem in Romania between 2006 and 2008 (i.e. from just before to just after accession to the EU), then gradually became more of a problem, but has very recently become slightly less of one relative to other factors; and that it is considered ever less of an issue, and a relatively marginal one, for Georgian businesspeople.
The second GCR response of relevance here relates to the business community’s perception of the seriousness of the problem of the diversion of public funds to private interests because of corruption. This is scaled 1 (very common) to 7 (never occurs), so that the lower the figure, the more significant the problem is perceived to be.
In Table 4.4, the score is in many ways more revealing than the rank, since it provides a picture of the situation within a given country, rather than one of how that country is faring relative to other countries. Bulgaria’s scores since 2008 suggest that this form of corruption did reduce somewhat for several years after the country became an EU member-state, but that this Balkan state may now be backsliding. Moreover, with the exception of 2011 (when Russia was the worst), Bulgaria is perceived to have been the worst country of our four in terms of this particular form of corruption, though Russia joined it in this questionable position in 2015. Romania’s situation appears to have deteriorated significantly between 2009 and 2011, but then to have more or less stabilised, though it is still not as good as it was in 2008 and 2009. Contrary to what might be expected given both President Medvedev’s anti-corruption campaign and President Putin’s lukewarm approach to
Table 4.4 Diversion of public funds6
Notes: Ranks are global - 2006 N= 125; 2008 N = 134; 2009 N = 133; 2011 N = 142; 2014 N = 144; 2015 N = 140.
Sources: Schwab and Porter (2006, p. 405, 2008, p. 366); Schwab (2009, p 348, 2011, p. 392, 2014, p. 408, 2015, pp. 125, 177, 305 and 307).
Table 4.5 Irregular payments and bribes7
Notes: Ranks are global - 2011 N = 142; 2014 N = 144; 2015 N = 140. Sources: Schwab (2011, p. 394, 2014, p. 410, 2015, pp. 125, 177, 305, 307).
corruption (see ensuing sections), the situation in Russia apparently worsened between 2008 and 2011, but then seems to have marginally improved again. Finally, this type of corruption is apparently much less of a problem in Georgia than in any of the other three states.
The third set of responses from the GCR (Table 4.5) concerns bribe payments to state officials by the private sector; once again the scaling is between 1 (very common) and 7 (never occurs).
Unfortunately, this question was not asked until the 2010-2011 GCR, so that we have a less comprehensive picture than for the previous question. However, this time, Russia emerges as the worst of our four countries - and Georgia as once again easily the best performer (i.e. where bribery seems to be less of a problem). On this variable, Bulgaria appears to have improved quite significantly between 2011 and 2014, whereas Romania headed in the opposite direction, albeit only marginally so. Sadly, both countries’ scores declined again in 2015.
The final GCR question cited here may relate to economic (bribery) and social corruption, since the motives for favouritism can be both economic incentive and ‘mateship’ (i.e. privileging people one knows) or nepotism. Yet again, the scaling for Table 4.6 is 1 (always shows favouritism) to 7 (never shows favouritism).
This time, the Bulgarian results are broadly in line with the trend identified in Table 4.4, but somewhat at odds with those in Table 4.5. There has apparently been little change in Romania since joining the EU, though its scores are marginally better than in the year before accession. The Russian situation seems to have deteriorated between 2008 and 2011, but - as with the results in Tables 4.4 and 4.5 - to have begun to improve again lately. As by now would be expected, Georgia again consistently comes ‘top of the class’.
Table 4.6 Favouritism in decisions of government officials8
Notes: Ranks are global - 2006 N= 125; 2008 N = 134; 2009 N = 133; 2011 N = 142; 2014 N = 144; 2015 N = 140.
Sources: Schwab and Porter (2006, p. 408, 2008, p. 369); Schwab (2009, p. 351, 2011, p. 396, 2014, p. 412, 2015, pp. 125, 177, 305, 307).
Table 4.7 Enterprise perceptions and experiences of corruption
A = Percentage of firms identifying corruption as a problem of doing business.
B = Percentage of firms reporting unofficial payments (‘bribe tax’, ‘graft index’ in 2011); unfortunately, the methodology used in BEEPS 2008 was slightly different from that in 2005 on this variable, and then again in 2011, so that the figures are not directly comparable over time (Knack and Kisunko 2011, p. 23); however, the methodology was the same in any given year across states, so that cross-polity comparison for any given year in the above table is valid.
Empty cells = no data.
Sources: 2002—Fries et al. (2003, p. 25); Holmes (2010, pp. 37-38).
One final business-related survey source that can throw more light on the corruption situation in our four countries are the European Bank for Reconstruction and Development (EBRD)-World Bank Business Environment and Enterprise Performance Surveys (BEEPS) that have been conducted in 2002, 2005, 2008 and 2011. Table 4.7 summarises some key findings of relevance to us.
According to BEEPS data (B) in Table 4.7, the number of firms paying bribes substantially declined in all four countries between 2002 and 2008, and then again in Georgia, Romania and Russia in 2011; the percentage increased in Bulgaria in 2011 compared with 2008, but was still considerably lower than in 2002 and 2005. However, most of these data are at odds with the perceptual data (A), which suggested that, in 2008, a higher percentage of firms identified corruption as a problem of doing business than had done so in 2005 in three of our four states; Georgia was the only exception to this. Such a mismatch may simply endorse the notion that there are ‘lies, damned lies, and statistics’. Alternatively, it may be in line with the findings of researchers who have compared perceptual and experiential data on corruption and discovered that they are often at odds with each other for various reasons (e.g. Treisman 2007, p. 212; Mishler and Rose 2008; Rose and Mishler 2010; Donchev and Ujhelyi 2014).11
Let us now delve a little deeper into the corruption situation in the two EU member-states selected for particular attention in this chapter.