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Decline of Europe. The Governance Indicators Tale Please cite 'Can a Civilisation Know Its Own Institutional Decline?', with Roberto Martínez

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This paper asks if current indicators of low trust and moral decay in Europe can be better traced to facts than similar perceptions on record from the Western Roman Empire during its decline. The answer is provided by complementing individual-level analysis of corruption survey data with national-level data, using three novel fact-based indicators. The findings provide a general validation of public perception by more objective indicators. Most individuals seem to report what they observe and experience, uninfluenced by media or social status, so these negative perceptions are likely to reflect the overall practices that people observe as well as the integrity policy framework. The paper argues that public perception does not need direct evidence to have objective evidence, and indirect indicators offer sufficient grounds for the perception of corruption and decaying standards. Nevertheless, the chapter also shows that objectivity is uneven across respondents of a survey.
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Decline of Europe. The Governance Indicators Tale
Alina Mungiu-Pippidi and Roberto Martinez Barranco Kukutschka
1
Please cite
‘Can a Civilisation Know Its Own Institutional Decline?’, with Roberto Martínez
Barranco Kukutschka, In: Helmut K. Anheier, Matthias Haber, and Mark A. Kayser
(eds.), Governance Indicators: Approaches, Progress, Promise, Oxford: Oxford
University Press, 2018, pp. 71-102
https://www.oxfordscholarship.com/view/10.1093/oso/9780198817062.001.0001/oso-
9780198817062-chapter-4
This paper is an earlier rough version.
10147 words
I. The perceived institutional decay
Starting with the financial crisis of 2008-2009, an increasing number of observers
have warned that the Western civilization, whose superiority over the rest of the
world had been explained previously by a vast literature, has de facto entered a
stage of decay, or degeneration, or demise, in short, its final decline. Titles like
“Are we the next Rome?” (41 million entries on Google by mid-2017) or “After the
European Union” (50 million entries) have therefore multiplied, simultaneously
with the business as usual literature, which still makes plans for global
1
Based on Kukutschka, R. M. B., & Mungiu-Pippidi, A. (2017). Crony capitalism in the European Union. Subjective
or objective?. Working Paper no 48. March 2017. Berlin: European Research Centre for Anticorruption and State-
Building (ERCAS).
2
governance under Western leadership or an ever deeper and successful European
Union. The new doom and gloom literature features equally top economists like
Niall Ferguson who has earlier excelled at the business of explaining why the West
is better than the rest, financiers like George Soros who has made the most to
change the Rest on a Western model, and even thinkers like Francis Fukuyama,
who has been branded for eternity by their earlier belief that the West managed
to impose liberal capitalist democracy as the only acceptable universal model. The
commonality of these approaches lies in the primacy of the political explanation
versus the economical one the decay is attributed to ‘institutional’ reasons, as
the economists call it. In other words, what seems to be failing is what Baron de
Montesquieu would have called ‘moeurs’, Machiavelli would have called ‘virtue,
and Cicero moral duties. The West, which has conquered the world due to its
superior ‘inclusive institutions’, as Acemoglu and Robinson call them, is now
losing on both these institutions and the social fabric which generated them in
the first place, with rising inequality, distrust in government and the election of
populists like Donald Trump or Theresa May, who espouse a completely different
set of values than the one that we identify as Western universalism.
We do not ask, of course, in this chapter, if the Western civilization, and in
particular the European one, which is set apart by its common political
institutions in the form of the European Union, is declining or ‘degenerating’ due
to moral causes. We ask instead the epistemological question- could such a
decline due to corrupt institutions be observed and known by its
contemporaries? Are our instruments, as social scientists, better in any way than
the intellectual archeological tools used by historians when trying to decipher the
decline of the Roman Empire due to corruption? In the latter endeavor, for
instance, historian Ramsay MacMullen, in the Corruption and the Decline of Rome
(MacMullen 1988) tried to assess with scarce statistical ‘hard’ evidence what the
extent and scale of corruption was and what was its weight in the process of
Roman decline and fall. Given that most testimonials are tendentious and
therefore unreliable (also contradictory to a dazzling extent- in each and every
period of the Roman Republic and Empire we seem to have had simultaneously
some thinkers who explained the superiority of Roman institutions and others
3
who deplored their degeneration and warned of the imminent demise), the most
objective historian cannot but struggle with an evidence based diagnosis.
MacMullen concludes that by the fourth and fifth centuries corruption had
become the norm in Rome: no longer abuse of a system, but an alternative
system in itself. The evidence is, of course, incomplete, but the explanation is
tempting: ‘ghost’ legions can, of course, explain why a defense which had held
well the previous centuries no longer seemed to exist and function, although
similar on paper, and the indicator of Rome’s demise become its mere conquest
by barbarians. Similarly, the cohorts of refugees and migrants besieging European
Union by land and sea indicates its failure to stabilize neighborhood and secure its
borders, in other words it might indicate a breakup of the European order. And
what about the failure to collect sufficient taxes to pay for defense, is this not also
a traditional indicator of a civilization’s decline, currently being observed for EU,
after having been a classic explanation for the Western Roman Empire failure
(Cooper 2011)?
The presumed failure mechanism has corruption at its core, of course, not
corruption in the narrow sense of individual monetary inducement, but
corruption defined as the generalized deviation of rulers and elites from public
welfare goals to seek their narrow profit and self preservation. As Fukuyama puts
it: “Because Americans distrust government, they are generally unwilling to
delegate to it the authority to make decisions, as happens in other democracies.
… The government then doesn’t perform well, which confirms people’s lack of
trust in it. [ A major obstacle ] … stands in the way of reversing the trend toward
decay. Many political actors in the United States recognize that the system isn’t
working well but nonetheless have strong interests in keeping things as they are.
Neither political party has an incentive to cut itself off from access to interest -
group money, and the interest groups don’t want a system in which money won’t
buy influence”. (Fukuyama 2014: 17-18). And Ferguson approves: the West has
entered what Adam Smith called “the stationary state” in the Wealth of Nations,
whereby “a corrupt and monopolistic elite exploits the system of law and
administration to their own advantage” (Ferguson 2014: 9). In this regard,
traditional distinctions of the type of West versus the Rest have started to matter
4
less and less, as the assumption that market based liberal democracies would
become the template regime following the demise of Communism proved
misplaced, the focus of indicators on nation states missed most of the negative
effects of globalization (Heywood 2017:45), and the global trends across the
world proved not so ‘global’, with some of the world being required to or actually
converging with what used to be the Western governance standards, while the
West itself was backsliding on them (Ferguson, 2014: 19).
Unlike historians, we are packed with governance indicators, statistics and public
opinion polls. Yet, very much like them, we seem to be doing a rather poor job in
using them to discern the deeper trends of our governance and their roots. For
instance, how could American scholars have been so surprised by the election of
Donald Trump when public opinion polls had been showing for a while a nearly
general discontent with American elites, democracy and capitalism? In the past
decade, the percentage of U.S. adults who see corruption as pervasive has never
been less than a majority in Gallup polls, at the peak reaching 75% who saw
widespread government corruption
2
. During elections, Reuters/Ipsos polled more
than 10,000 Americans who had already cast their ballots and found that 72
percent agreed that "the American economy is rigged to advantage the rich and
powerful.", and 75 percent felt that "America needs a strong leader to take the
country back from the rich and powerful." The trust failure seems to be complete,
with an additional 68 percent distrusting "traditional parties and politicians and
76 percent believing that "the mainstream media is more interested in making
money than telling the truth.
3
" In the EU also, except for the countries in
Northern Europe, the feeling that the ruling governing elites collude with business
interests to favor special interests versus merit have been endorsed by majorities
for some years now (Mungiu-Pippidi et al. 2016). If public opinion is an indicator
to go by, there is clearly a picture of moral decay strongly emerging from both the
traditional Western civilization shores of the Atlantic.
2
http://www.gallup.com/poll/185759/widespread-government-corruption.aspx
3
http://www.reuters.com/article/us-usa-election-poll-mood-idUSKBN1332NC
5
But are such perceptions accurate, or do they reflect the general pessimism in times
of austerity, uncertainty and growing inequality? How much can we trust public
opinion governance indicators, versus expert surveys and fact based indicators,
when available? This paper attempts to give an answer by analyzing how much of
the widespread perceptions of corruption, state capture and government
favouritism in the EU are based on facts, and how much on other factors. Despite
imperfect data, we attempt to establish the merit of popular claims by both
drawing on objective data and by deconstructing perceptions. Our sources are
therefore based on subjective data (the 397 Eurobarometer survey fully dedicated
to corruption conceived as governance norm) and the objective indicators
generated in recent research on good governance and corruption (mostly ours,
funded by EU). Our objective data sources are based on the European Tender
Database (TED), the Foreign Corrupt Practices Litigations data and a collection of
other sources including the World Bank Public Accountability Mechanisms data, the
Ease of Doing Business Index and the Open Budget Index, among others.
The European Union is ideally suited for this test and such deconstruction of
governance perceptions. The EU has long provided the modernity benchmark for
the rest of the world and its historical capitalism was the model for the theory of
rationalization of governance through inner-worldly asceticism, mostly Protestant
Ethics (Weber 1968). Institutional decay, of course, as our authors cited above
suggest, means a relapse into the non-modern, limited access order based on
particularism - treating individuals or businesses by virtue of their status and
connection to power rather than on a universal and impersonal basis (Parsons
1997; Mungiu-Pippidi 2006) - so it would be hardly conceivable to find it in the
European Union. Furthermore, no other continent has sufficient variation in
government effectiveness and corruption control across countries, while
simultaneously enjoying (with the most open data and best statistics in the world)
a common market and a rule of law based polity. Countries have common relevant
legislation upholding a market based on fair competition and merit, such as the
competition acquis, (articles 101 to 109 of the Treaty on the Functioning of the
European Union, TFEU, see European Union 2016) with a national enforcement
agency partly subordinated to Brussels. The European treaty and secondary
6
legislation is mindful of cartels, collusion and other anti-competitive practices,
under article 101 of the TFEU; market dominance, or potential abuse of firms'
dominant market positions (under article 102 TFEU); and also of government
favouritism, for instance prohibiting state aid, direct or indirect (TFEU article 107).
Directive 2014/24/EU of the European Parliament and of the Council of 26 February
2014 on public procurement, which replaced Directive 2004/18/EC, states that:
The award of public contracts by or on behalf of Member States’ authorities
has to comply with the principles of the Treaty on the Functioning of the
European Union (TFEU), and in particular the free movement of goods,
freedom of establishment and the freedom to provide services, as well as the
principles deriving from, such as equal treatment, non-discrimination,
mutual recognition, proportionality and transparency. (European Union
2014).
By choosing the EU for this test, we therefore have the advantage to control for
formal institutions, as competition law and most of the procurement regulations
are similar across 28 member states. While keeping US in the discussion would have
been tempting, it is practically impossible to control for all these elements across
the entire West.
II. Perceived institutional decay
The dedicated survey of DG Home, and its correspondent, a business survey,
seemed to descend directly from the Roman chronicle of Mac Mullen, showing that
bad governance has pervasively become norm. The general sample showed that
three in four Europeans (73%) believed that bribery and connections were the
easiest way to obtain public services in their respective countries. Two out of three
also thought that corruption was an intrinsic part of the business culture in their
country (66% of respondents), while three of five Europeans identified political
connections as the best way to succeed in business (58%). Except for the countries
in Northern Europe (Denmark, Finland and Sweden), negative perceptions
regarding the integrity of the public and private sectors in the European Union
seem to be widespread (see Table 1). The Survey on Business Attitudes’ towards
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Corruption also shows France and Germany, EU’s ‘motor’ countries on the wrong
side of the norm. In Germany, over half of businesses in the sample believed that
procurement deals in Germany are either inside deals or pre-arranged as a rule. A
similar percentage declared that favouritism towards friends and family was
widespread in the German business community. Likewise, 50% of French
businesses complained that favouritism of one’s family is widespread in the public
sector (and 52% found it in the business sector), 42% reported tax evasion and VAT
fraud as very common, and 37% considered that the practice of granting favors to
businesses in exchange for campaign contributions is rife. In the estimate of
nepotism, French businessmen ranked France between Romania and Bulgaria, no
less, so the 2017 Fillon affair and the revelation that only first degree relatives on
the public payroll of French MPs are a fifth or more should not have come as a
surprise.
[Figure 1 about here]
These figures are closely correlated with public trust in government, Parliament
and EU institutions (over 70%, with the correlation between business political
connections and trust in national Parliament at 91%, see Mungiu-Pippidi 2016). If
52%
64% 72%
78% 87% 92%
25% 32% 40%
76% 83% 90%
0%
20%
40%
60%
80%
100%
Political connections
are the only way to
succeed in business
Corruption is part of
business culture Bribes and connections
are the easiest way to
obtain a public service
% of respondents that agree
with the statement
Western Europe Southern Europe Northern Europe Eastern Europe
8
public trust figures have long been monitored by governments and pollsters alike,
the monitoring of governance and corruption trends is of more recent date and of a
less regular character. For this reason there is no time series on corruption
perception in EU28 to match the trust data for the past decade, only occasional
surveys like the one cited. There are, however, year based expert indicators that
are widely used in the anti-corruption literature, i.e. the World Bank’s Control of
Corruption (CoC), Transparency International’s Corruption Perception Index (CPI)
and the World Economic Forum Government Favouritism. These former two
measurements are statistical aggregates of country expert assessments (they use
nearly the same sources) and they are available for all EU28 countries since 1998.
Government Favouritism comes out of a business expert survey carried our yearly
by World Economic Forum for the Global Competitiveness report.
The observance of these scores returns some interesting observations. First, expert
scores of national corruption/particularism tend to be very stable across time
because achieving change which is agreed on across different sources is quite
difficult. This is why the CoC indicator, which unlike the CPI can be compared across
years, is very resistant to change (Mungiu-Pippidi et al. 2016). Countries such as
Italy, Spain and Greece, for instance, show no statistically significant change
between 1996 and 2013. However, following the EU financial crisis these countries
(and Cyprus) registered some worsening of their scores within the confidence
error, but this could be a result of the crisis making some experts reassess the
governance quality and retrospectively prime corruption as a cause of the
economic crisis. Among the newer EU members, only Croatia, Estonia and Latvia
show some significant progress in the last decade, while headline-making Romania
has changed only within its confidence error margin.
The EU28 shows a great variation of governance quality in the CPI/COC: While
Sweden, Denmark, Finland, Netherlands and UK rank among the best performers
in the continent and worldwide, thus embodying the idea of Western Europe as
good governance benchmark, Southern and the Eastern European countries lag
behind, with Romania and Bulgaria at the bottom closely followed by Greece and
Italy. The big performer in the EU28, however, is Estonia, who has surpassed all
Southern European countries and France over the last twenty years, partly due to
9
Western European decline, but partly to its own exceptional progress. As the
European Union enlarged, receiving countries such as Romania and Bulgaria which
by all standards were “developing” and not developed, a new, more visible sort of
corruption appeared. This consisted of a large spectrum of symptoms, from
informal payments to poorly paid doctors or clerks to top-level undue profit owing
to unregulated conflict of interest. The new member countries’ corruption
captured most of the attention (and sanctions) of the European Union after the
2004-2006 enlargement. The ratings show many anomalies, though. CPI 2017 ranks
Qatar better than Spain and Rwanda, where there is no pluralism, better than
Romania and Bulgaria. Government favouritism, ranked 1 to 7, with Sweden best
(less favouritism), shows a poor European average (under 4), confirming the critical
judgment of businesspeople.
But all these remain inherently subjective. A critical businessman may compare
Germany with his father’s generation standards, and not with standards in sub-
Saharan Africa. Majorities complaining of corruption in the former and latter
countries might not be comparable. At least the governments always claim that
perception is not reliable, and is sometimes worsened by efforts to redress
corruption. About here we would need a third set of indicators, fact based, to check
against public opinion and expert scores. Corruption and favouritism are not
however easily traceable in statistics, either because they are hidden, or because
they are not collected, being surrounded by public hypocrisy. Most governments
prefer to single them out as individual deviations instead of monitoring them as
practices, through consumer surveys or other means.
To answer this challenge, the EU FP7 ANTICORRP project developed direct and
indirect measurements of governance quality at policy or sector level, based mostly
on facts, not perceptions. The universe of observations is given by all the
transactions that a government agency, a sector or indeed a state engages in (from
regulation to spending). The measurement efforts at sector level aim at
establishing the prevalence of favouritism, in other words at measuring how many
of these transactions are “as they should be”, according to regulations and the
norm of ethical universalism (treating citizens and businesses equally and
impersonally). Alternatively, at national level (but also sub-national) one can design
10
an indirect measurement based on factors enabling a good control of corruption,
so statistically associated with less corrupt outcomes and/or processes (The Index
for Public Integrity, see Mungiu-Pippidi and Dadasov 2016). This approach results
from a definition of governance conceptualized holistically as a set of formal and
informal institutions determining who gets what from the allocation of public
resources in any given society. This allows for the majority of government
transactions (or exchanges) to be placed on a continuum particularism-ethical
universalism in any country where information can be collected. The direct
measurement approach has to determine if government transactions are of a
universal or particular nature and what are the rules of the game in the allocation
of public resources. The indirect measurement approach further looks at what
institutional arrangements determine the respective rules of the game in order to
know how they can ne changed. This approach has important theoretical and
practical advantages, as it allows more sensitivity towards change in governance
and the impact of various policies. An outcome based definition of ‘state capture’
can be derived from here as the situation when significant numbers of government
transactions (the threshold is debatable 50 per cent is the simplest to establish as
majority norm, although of course very high) are particular, and a definition of
‘government favouritism as the administrative behavior by which such a
preferential distributional outcome is reached. Such distributive behavior, both
through its processes and its outcomes, is observable, and therefore likely to
greatly influence public opinion.
1.
The data needed for the direct measurement of corrupt practices can be collected
and analyzed from a variety of sources, such as public procurement allocations and
their degree of competitiveness and correctness, the distribution of subsidies, state
loans and tax exemptions, the distribution of subnational cash transfers, the public
and private employment practices (how much merit based versus nepotistic?), the
financial and interest disclosures of public officials, some private market indicators
at company and sector level (favorite companies versus average companies profit,
turnout from competitive versus non-competitive contracts, market concentration.
11
An illustrative dataset, summing up over 6000 public construction contracts (all
over one million euros) over seven years in Romania can be observed in Table 1
(data obtained by scrapping from public sources). Romania is of interest because it
has the most intense judicial anticorruption in the world presently, comparable
probably only to Brazil (18 ministers jailed in the past five years, and one former
PM). It also presents a puzzle as its progress does not manage to evade from the
margin of confidence error in CoC. The table presents a few indicators achieved by
crosstabulation of procurement success. Although only open forms of favouritism
can be traced, such as single bidding (just one competitor), capture of an agency
(over 50% of allocation to one private contractor) and awards to politically
connected companies (as identified in financial disclosures or by donations to
parties), in the interval of seven years observed (the timing corresponds with
Romania’s own ‘mani pulite’, with eighteen ministers jailed for corruption in the
interval, and several mayors), overt particular allocations decreased only by a fifth.
There is no way of knowing if they were not replaced with more insidious and hard
to trace connections. The decrease was mostly on behalf of openly non-competitive
tenders, due to intense media, civil society and EU pressure. The construction
sector represents the highest expenditure within procurement and Romania has
been for many years EU’s number one per capita spender for public works, as well
as a leading procurer amongst EU-28 (Doroftei 2016)
4
. Table 1 shows a time series
of particularism indicators in Romanian public procurement during intensive
judicial anti-corruption, 2007-2013, resulting in a decrease by a fifth of problematic
transactions, from the majority (52%), to ”only” 42% by contracts value. This
actually shows some effort to catch up with EU governance benchmarks, so
convergence, rather than decay, seems to be the norm here.
Such indicators may look work intensive and difficult to compare across
countries. But as procurement and spending are increasingly digitalized, and even
France adopted some public version of financial disclosure for officials the data can
increasingly be found, scrapped and patterns observed. Fact based evolution or
4
For more indicators and a description of this methodology see Mungiu-Pippidi, A. (editor) (2015). Government
Favouritism in Europe: The ANTICORRP Project: Anti-corruption Report. Barbara Budrich Publishers.
12
lack of evolution from one year to another can easily be traced using such
indicators.
Table 1. The decline of particularism in Romania during the anti-corruption
campaign (2007-2015)
2007
2008
2009
2010
2011
2012
2013
2007-2013
change
VALUE CONTRACTS
Single bidder1
30,8%
24,1%
21,6%
26,4%
22,4%
12,9%
8,4%
↓↓
Political connection2
23,4%
31,3%
20,3%
16,4%
19,7%
16,5%
13,6%
Agency capture3
18,5%
11,8%
17,3%
20,9%
21,7%
9,3%
18,6%
Total particularism
51,7%
52,9%
43,9%
53,0%
49,1%
34,0%
39,4%
Number
CONTRACTS
2007
2008
2009
2010
2011
2012
2013
Single bidder
30,1%
27,6%
20,3%
24,0%
24,2%
17,6%
12,2%
↓↓
Political connection
22,7%
21,5%
19,9%
19,3%
19,7%
17,7%
17,3%
Agency capture
9,4%
8,5%
8,3%
7,4%
8,1%
7,5%
5,9%
13
Total particularism
47,7%
45,3%
41,1%
42,7%
43,5%
37,2%
33,1%
Legend: Time series of particularism indicators in Romanian public procurement during intensive judicial
anticorruption, 2007-2013, resulting in a decrease by a fifth of problematic transactions; ↓ indicates small
change; ↓↓ indicates change over 10%; ↔ indicates no significant change.
Source: Romanian Academic Society, www.sar.org.ro.
[1] Single bidding. i.e. only one bid is submitted to a tender on a competitive market.
[2] Political connection. Allocation to a company with political connections (politician shareholder, board
member or party donor company, according to digital interest disclosures or donation reports)
[3] Agency capture. Public agency awards 51% contracts or value of total contracts to one bidder.
Unlike other areas of public sector, procurement is extensively regulated precisely
to avoid rents and discriminative treatment of companies (Mungiu-Pippidi et al.
2016). Why the indicators presented here are not openly breaking rules, the
resulted outcomes are corrupt. A company politically connected has higher chances
of winning more tenders both from national and EU budget, for instance. Agency
capture is abnormal if framework contracts are deducted, as it is the case with the
Romanian data, and indicate the existence of favourite companies which extract
rents versus regular kickbacks: several such cases have been meanwhile tried.
Single bidding, i.e. only one bid is submitted to a tender on a competitive market,
indicates the expectations of the market that the winner is already known. In
frequently results in above market price contracts and corrupt rents. Clean single
bidding is exceptionally possible for very specialized areas or restricted markets,
but at the high contract values reported in the EU Tender Electronic Database it
should be exceptional, as all tenders above four million Euros are supposed to be
competitive.
The data presented in table 2 shows regional averages and some selected
countries, confirming that trends can be opposite in the developing versus the
developed Europe. Slovakia evolves, while Portugal, Spain and Cyprus involve, for
instance, which seems at first sight to match perceptions from public opinion
surveys. The data shows that some Southern and Eastern countries also have a high
proportion of “favourite companies” which bid alone in many public tenders and
win regularly a gross share of public funds. On the other end of the spectrum, we
see countries where competition over public funds is usually the case and
14
‘dedicated’ tenders practically do not exist. UK and Ireland, for instance, have less
than 5% of single bidding. Also Netherlands, Luxembourg and the Nordic countries
show consistently low numbers of single bidding situations. The other Western
European countries lie below the European average with 8% to 16% of public
procurement being assigned to single bidders (see Table 2).
Table 2 Percentage of single bidder contracts in public procurement (2009-2013)
2009
2010
2011
2012
2013
EU and regional averages
19%
20%
20%
21%
21%
Central & Eastern
29%
31%
29%
26%
25%
Romania
25%
23%
19%
19%
25%
Slovak Republic
61%
58%
48%
33%
12%
Northern
5%
6%
7%
7%
7%
Southern
21%
23%
25%
26%
29%
Cyprus
29%
28%
26%
33%
43%
Greece
13%
35%
16%
28%
31%
Portugal
11%
8%
12%
16%
25%
15
Spain
12%
14%
18%
18%
20%
Western
8%
8%
8%
8%
10%
United Kingdom
3%
3%
3%
4%
4%
Source: EU's Tenders Electronic Daily, data released by DG GROW of the European Commission,
available under: http://ted.europa.eu/TED/main/HomePage.do.
Note: Table shows the proportion of public procurement as part of the total amount of contracts.
Numbers are aggregated based on the number of contracts.
The indirect public integrity indicator draws on the last twenty-five years of
empirical evidence on causes of good governance, and can be better described
through a model of control of corruption as an equilibrium between opportunities
(or resources) for corruption such as natural resources, unconditional aid, lack of
transparency, administrative discretion and obstacles to trade, and constraints,
such as legal (an autonomous judiciary and audit) and normative (oversight on
government exercised by the media and civil society)
i
. Not only has each element
high explanatory power on corruption, but the statistical interactions between
resources and constraints, between red tape and independence of judiciary,
between transparency in any form (fiscal, existence of freedom of information
legislation, financial disclosures) and civil society activism or press freedom are
highly significant. Using this model, we designed a parsimonious composite index
for public integrity based on policy determinants of control of corruption (Mungiu-
Pippidi et al. 2016; Mungiu-Pippidi and Dadasov 2016)
5
. Table 3 shows a breakdown
of this governance index across EU countries and regions. The institutional
5
This index was developed for the Dutch EU presidency for EU 28 (Mungiu-Pippidi et al. 2016), then an updated
version was created for over 100 countries. Available on www.integrity-index.org.
16
differences across EU are as expected, with the Northern countries doing well
above EU average, and the Southern and new member countries well under. But
the trend for the first two years the index could be computed, and which
corresponds with the research period of the EB special surveys (2013, 2014) are
quite diverse, showing minor backsliding for some developed countries and some
scattered progress across others, in particular Greece, Latvia, Lithuania, Slovakia,
Ireland and Romania, a sign of some crisis related reforms. The index does not
show at first sight indications of some dramatic institutional decay, and it correlates
at over 90 per cent with expert corruption scores CoC and CPI.
Table 3. EU-28 by strength of integrity framework (2014)
Index of
public
Integrity
Red
Tape
Trade
Barriers
Auditing
Standards
Judicial
Independe
nce
E-Gov.
Services
E-Gov.
Users
Change
IPI
2014-
2012
EU Average
5.71
6.33
5.86
5.90
5.00
5.76
5.45
0.29
Central &
Eastern
4.27
5.31
3.86
3.86
3.76
4.38
4.46
0.40
Bulgaria
2.38
2.75
3.20
1.15
3.83
1.00
2.38
-0.06
Croatia
2.64
4.04
1.00
2.87
1.26
3.69
3.00
0.18
Czech
Republic
3.22
1.14
2.88
4.36
3.97
2.58
4.38
0.46
Estonia
7.83
9.98
9.24
8.12
6.45
7.31
5.88
0.05
Hungary
4.84
7.25
1.13
4.72
5.25
4.80
5.88
0.17
Latvia
5.93
7.71
5.30
4.65
4.94
6.47
6.50
1.26
17
Index of
public
Integrity
Red
Tape
Trade
Barriers
Auditing
Standards
Judicial
Independe
nce
E-Gov.
Services
E-Gov.
Users
Change
IPI
2014-
2012
EU Average
5.71
6.33
5.86
5.90
5.00
5.76
5.45
0.29
Lithuania
5.78
8.59
6.37
3.90
3.84
7.12
4.88
0.97
Poland
3.71
2.44
4.13
4.86
3.84
4.62
2.38
0.15
Romania
2.60
2.70
3.68
3.51
1.27
3.41
1.00
0.77
Slovak
Republic
3.84
3.21
3.25
1.00
5.26
3.97
6.38
0.93
Slovenia
4.19
8.61
2.25
3.28
1.40
3.23
6.38
-0.44
Northern
8.60
9.50
8.45
9.36
8.02
6.60
9.71
-0.09
Denmark
8.49
9.52
9.24
9.89
6.30
6.01
10.00
-0.09
Finland
8.88
9.67
6.92
10.00
10.00
7.31
9.38
0.22
Sweden
8.44
9.31
9.18
8.20
7.75
6.47
9.75
-0.39
Southern
4.74
5.09
5.11
4.62
3.43
5.70
4.48
0.43
Cyprus
4.77
4.46
5.60
5.60
4.16
3.78
5.00
-0.28
Greece
4.34
7.18
3.44
3.92
1.51
5.36
4.63
1.49
Italy
4.12
5.59
5.08
3.67
1.00
7.03
2.38
0.63
Malta
4.39
1.00
4.11
5.91
7.77
2.95
4.63
-0.30
Portugal
5.71
8.87
5.38
5.66
4.03
5.73
4.63
0.69
Spain
5.09
3.43
7.06
2.97
2.13
9.35
5.63
0.34
Western
7.35
7.49
8.19
8.36
6.76
7.38
5.94
0.17
Austria
6.50
3.60
7.75
7.09
6.91
7.03
6.63
0.14
Belgium
7.16
9.72
7.43
8.12
6.13
6.20
5.38
0.46
France
7.89
9.05
9.44
6.66
6.33
10.00
5.88
0.38
18
Index of
public
Integrity
Red
Tape
Trade
Barriers
Auditing
Standards
Judicial
Independe
nce
E-Gov.
Services
E-Gov.
Users
Change
IPI
2014-
2012
EU Average
5.71
6.33
5.86
5.90
5.00
5.76
5.45
0.29
Germany
6.60
4.37
7.61
8.57
6.57
6.10
6.38
-0.18
Ireland
7.39
9.71
10.00
9.39
3.67
6.20
5.38
0.89
Luxembourg
6.87
5.34
7.11
8.81
9.06
5.55
5.38
-0.2
Netherlands
8.66
10.00
8.17
9.00
7.99
9.16
7.63
-0.03
United
Kingdom
7.74
8.13
7.99
9.23
7.45
8.79
4.88
-0.14
Source: Ease of Doing Business Index (Administrative Burden; Trade Openness), Global
Competitiveness Report (Auditing Standards, Judicial Independence), UN E-Government survey
2012 (E-Gov Services), Internet World Stats (E-Gov Users); own calculation. Republished from
Mungiu-Pippidi et al. 2016.
19
A third indicator of interest developed in recent years is the Public Administration
Corruption Index (PACI), developed by Escressa and Picci (2015). PACI combines
litigation data from Foreign Corrupt Practices Act, on the presumption that as
companies’ law suits against bribery can be filled in American courts, not the
country where the alleged offense took place, it would capture the variation of
extorted bribes across countries, therefore the quality of national governance. The
official judicial statistics is only weighted by the amount of foreign business going
to a country.
III. How evidence-based are governance perception indicators?
The macro picture
These recently published objective indicators are all contemporary with the period
of time that we look at in this chapter- after the economic crisis. Additionally, three
of them- single bidding across EU 28, IPI and PACI exist for all EU 28 countries, so
we can test our subjective indicators against them. But their greatest limitation is
obvious: they are still quite recent, so it will take some years until longer time series
exist if, indeed, enough investment is made in publishing such data in open
format. But presently they offer us, for a moment in time, a rare opportunity
unavailable to historians, to test representative fact-based data (not archeological
remains) against representative subjective data. We will try to make the most of it,
being aware in the same time of the limitations of all our sets of data- subjective,
general and expert, and fact-based
From our subjective data, we select the perceptions of Europeans regarding the
extent of corruption, particularism and political favouritism using the following
Eurobarometer questions:
Extent of perceived corruption is based on the question QB5 “How
widespread do you think the problem of corruption is in the country?”
and with answers ranging from 1 (very widespread) to 5 (there is no
corruption in the country).
Favouritism in the public sector was taken from the answers to the
20
question QB15.10 “Do you agree or disagree with the following
statement: bribery and the use of connections is often the easiest way
to obtain certain public services in our country”, which are coded from
1 (totally agree) to 4 (totally disagree).
Favouritism in the private sector was extracted from the question
QB15.4 “Corruption is part of the business culture in the country”. The
possible answers also range from 1 (totally agree) to 4 (totally
disagree).
Political favouritism was measured through the answers to question
QB15.13, which follow the same coding as the previous two variables.
This item in the survey asks whether political connections are the only
way to succeed in business.
Aside the objective indicators, we sought of also using the experience with public
sector reflected in the survey, although this is still subjective. These are the
following:
Self-reported experience with bribing (individual level) was extracted
from the Eurobaorometer 397 QB9b question, worded as follows:
Thinking about these contacts in the past 12 months has anyone in
(OUR COUNTRY) asked you or expected you to pay a bribe for his or her
services?” This is generally used in what is called ‘victimization; surveys
(see Seligson 2006)
Individual assessment of public procurement as being corrupt. This
measure was also extracted from the Eurobarometer results. The
original question QB7 is phrased as follows: “In (OUR COUNTRY), do you
think that the giving and taking of bribes and the abuse of power for
personal gain are widespread among any of the following?” and one of
the possible answers involves officials awarding public tenders.
Our preliminary test refers to checking the connection between self-reported
experience with bribing and corruption perception. This is sometimes reported in
literature as ‘perception-experience gap’, although bribe solicitation is only a part
of the experience with corruption and the alignment of a fragment with the whole
21
should be questioned from the start. Scholars have already investigated the gap
between the perception of corruption and experience (see Abramo 2008; Donchev
and Ujhelyi, 2009; Rose and Mishler, 2010; Charron 2015). We find that people who
report having been solicited a bribe are significantly more inclined to perceive
higher levels of particularism in the public and private sector than non-bribe payers,
even in complex regression multivariate models (ordered probit model, see Table
5). Also, when explaining separately the most critical group (which selects the
option with most corruption on all three dependents) we find that experience with
bribery is a highly significant predictor, with all demographic controls.
90% of bribe payers agree that corruption is part of business culture, while only
72% of those who did not pay a bribe share this belief. 93% of bribe payers agree
that bribery and connections are the easiest way to obtain a public service in the
EU, compared to just 79% of non-bribe payers. Out of these 20,000 respondents,
however, 94% report not having paid any bribes over the previous 12 months and
only 6% of the whole sample report having some experience with corruption.
Bribery seems on the most part confined to some poor post-communist countries,
but it is quite an exceptional practice in the rest of Europe. The question therefore
remains on what experiences the non-bribers ground their perceptions. We
attempt to answer by correlating subjective and objective factors at country level,
as well as across our public opinion survey and expert estimates, and we find
impressive consistency throughout, as follows:
Consistency between Eurobarometer perceptions of crony capitalism
and expert surveys that measure government favouritism, from WEF
and World Bank (all correlations are at over 80 per cent)
Consistency across Eurobarometer perceptions of public and private
particularism and extent of corruption- despite common talk of petty
versus grand corruption, these perceptions seem to measure a
governance order which is internally consistent, and rules of the game
which cut across areas of experience, direct (as with bribing) and
indirect (other observable phenomena), giving further justification to
our particularism-universalism continuum.
22
Consistency across subjective indicators and objective indicators. The
Eurobarometer perceptions of particularism correlate at 80 per cent
with the Index of public integrity, at around 60 per cent with single
bidding and at around 50 per cent with PACI. The objective indexes, in
particular IPI and single bidding also strongly correlate with expert
scores from World Bank and WEF (over 70 per cent). As the public
opinion data and the fact-based indicators are completely separately
generated, their high consistency can only mean that facts of
particularism that we measure are also observable by ordinary citizens,
as well as by experts and considered as corrupt. Non-competitive
tenders, impartiality of the judiciary and regulation, and favouritism in
government spending are all observable phenomena.
On top of such simple bivariate correlations, we ran a series of multivariate linear
regressions, comparing across fact-based determinants, expert scores and socio-
economic (contextual) variables that are often used in corruption literature. Here,
we preferred not to combine the different types of indicators or include the
contextual variables as controls in the models due to obvious endogeneity
problems, as governance rules of game are captured by most corruption and
development indicators. Instead, we simply used life expectancy as a development
control.
23
Table 4. Explaining country-level perceptions of corruption
24
The results in Table 4 (also see Appendix for figures) show that citizens’ perceptions
are closely related to what scholars have been able to objectively measure through
different methods from the objective reality of the country’s governance regime in
both the public and private sector. The explanatory power of the IPI, the PACI index
and the single bidding indicators remains high and statistically significant, even
when using life expectancy as a development control: the IPI explains between 61
and 66% of the variation in our perception-based variables, single bidding captures
between 35 and 48% of the variation and the PACI index, despite showing the
weakest explanatory power with values between 19 and 34%, remains statistically
significant. In none of these cases does the development control turn out to be
statistically significant, or affect the significance of our objective indicators.
Experience of bribery explains between 21 and 26% of the variation in corruption
perceptions (see detailed results in Appendix), so well below IPI and single bidding,
showing that observable phenomena might matter more than direct experience.
Finally, the socio-economic indicators have the lowest explanatory power. Out of
the five variables chosen to capture the national context, only two appear to be
statistically significant across all three dependent variables: secondary education
attainment and government investment in gross fixed capital formation both have
a negative effect on perceptions of corruption and particularism. The percentage
of people with completed tertiary education and the total government
expenditure, a measurement often used to capture the size of government, on the
other hand, do not show a statistically significant effect. However, the perceptions
of corruption are mostly shaped by the percentage of people with secondary
school. Additionally, it is not the overall level of government spending, or the “size
of government” that people consider when assessing the level of corruption in their
countries. Rather, citizens seem to take cues from the particular ways in which the
government budget is spent. This is in line with previous research showing that
universalistic spending in areas such as health and education is often associated
with less corruption, whereas spending in construction, for example, tends to be
perceived as more corrupt (Tanzi and Davoodi 1998). The other factors often cited
in the literature as possible sources of bias for perceptions, such as inequality, level
of education and size of government (Inglehart 1999; Jong-Song and Khagram
25
2005; Rothstein and Uslaner 2005), show even lower explanatory power and in
some cases, they are not even statistically significant at national level.
IV. Mediators of individual perceptions
Having accomplished the first round of tests, and having shown that there are
indeed strong and statistically significant relationships between the citizens’
perceptions and objective measurements of corruption and particularism at
national level, we will now attempt to shed some light on the determinants of these
individual perceptions.
Despite the salience of these theories in corruption studies, the first piece of
evidence suggesting that socio-economic variables might have less importance in
driving the popular perceptions of corruption and particularism in the EU Member
States can already be found in Table 4. As mentioned before, tertiary education
enrolment and total government expenditure as a share of GDP are not statistically
significant. Inequality, however, does show a positive and statistically significant
relationship when regressed against two of our perception-based dependent
variables: higher values of the GINI coefficient are indeed related to higher
perceptions of corruption and the need for connections to succeed in business. The
explanatory power of this indicator (20-30%) and its statistical significance is still
lower than that of two of our objective measurements and only comparable to our
weakest one, i.e. the PACI index. This is worth exploring further, however, as it
might be that for some individuals, their perceptions might indeed be less
grounded in evidence and more in their personal situation.
To provide further evidence on this, we will now proceed to dissect these
perceptions at the individual level. For evidence-based mechanisms of corruption,
we use three variables: assessment of procurement, experience with bribing and
perceived political favouritism. Seeing that in the Eurobarometer survey, politicians
are blamed far more for corruption than civil servants (Mungiu-Pippidi et al. 2016),
we will test political favouritism, the hypothesis that political connections provide
the shortcut to success. Based on the results obtained in the previous section and
considering the limited presence of bribery in the EU, we thus presume that
26
particularism is attributed foremost to political connections, rather than other types
of undue influence, and we use this survey question on political favouritism
alongside victimization.
Further controls are needed. We therefore included basic controls for gender, type
of community (urban or rural) and income (proxied by capacity to pay monthly
bills). Furthermore, due to the uneven geographic distribution, we will add a
control based on a simple cultural-geographic hypothesis: that all other things
being equal, individuals residing in Northern Europe will perceive less corruption
than those in the remaining three regions (Western, Southern and the Eastern
Europe) see Rothstein and Uslaner (2005) on the Scandinavian exception.
To test the above, we rely on the following questions from the survey:
For perceived inequality, we use the respondents’ self-assessment of
their stand in society as an indicator of subjective social status, but
also their inability to pay bills as an objective indicator of hardship.
For media exposure, as media is often denounced as worsening
corruption perception (Misher and Rose 2010; Rizzica and Tonnello
2015). We use Internet consumption; given that the Internet has
evolved into a main source of news and information for many people,
we use this as a way to indirectly test for media exposure.
A simple look at the breakdown of citizens’ perceptions of corruption and
particularism in the public and the private sector by social class and availability of
internet access reveals some fascinating results. First, for all three dependent
variables, people with regular access to the internet are less likely to believe that
corruption and particularism are defining trends of their countries’ governance
regimes. This still means that where six Internet intensive consumers see
corruption, seven or more complain of it from people with less Internet access and
usage, depending of the question. The difference is consistent across all our
dependent variables. The biggest difference between these two groups is with
regards to the importance of political connections to succeed in business: while
three quarters of respondents without internet access believe that this is a
27
problem, only 63% of respondents with access to the internet share this same
opinion.
Figure 2. Perceptions of corruption and particularism by social class.
28
The inequality hypothesis, therefore the perception of belonging to an
underprivileged social class might increase the likelihood of seeing the governance
regime as rigged or designed to favor others, is illustrated in Figure 2. These results
also show some interesting features. Firstly, the hypothesis seems to be generally
true: respondents who identify themselves as belonging to a lower social class do
exhibit higher perceptions of corruption and particularism. This group includes the
highest proportion of respondents who believe that political connections are the
only way to succeed in business, that corruption is part of the business culture and
that bribes and connections are the easiest way to obtain public services. Yet again,
while the differences between groups are statistically significant, we still have
majorities which agree with the vision of the underprivileged class in the other
groups as well. The biggest disparity between the perception of the lowest and
highest social class is when it comes to the importance of political connections to
succeed in business: 75% of the poorest respondents think this is true, while only
half of the richest respondents hold the same opinion. It is interesting to see,
however, that there is almost a consensus regarding corruption in the private
sector. Eight out of ten respondents believe that corruption is part of the business
culture and seven out of ten respondents from the middle and upper classes
believe the same.
To gain more insights we also conducted an individual-level order probit analysis of
the responses (see Table 5). We used three different models to explain each one
of our dependent variables:
The first model tries to explain different perceptions of corruption only
through socio-economic variables often found in the literature, i.e. the type
of residential community, the level of education, income and gender. This
model also includes our hypotheses regarding internet access and social
class.
The second model incorporates three corruption “red flags” that are related
to experiences or possible sources of information that a person can access
to estimate the overall level of corruption, i.e their direct experience of
bribery, assessment of how difficult it is to succeed in business by merit only
29
(without the use of political connections) and the assessment of whether
public tenders are corrupt. This last variable was included for two main
reasons: firstly, public procurement can be a source of objective cues on
which people can base their perceptions of corruption: if a highway, an
airport or a hospital is being built, but is never finished or its quality is
disputed, an individual might attribute this to corruption. Secondly, our
country-level regressions in Table 4 show that there is a remarkable overlap
between non-competitive tenders awarded by the government and the
people’s perception of corruption. This evidence also suggests that people
do not simply make up their assessments of corruption or particularism
based on their personal situation or their satisfaction with government, but
that they rely on some cues, and procurement with public contract disbursal
is one of the most visible areas of government.
Finally, the third model includes regional dummy variables to account for the
geographical-cultural control.
The explanatory power of personal factors such as income, education or gender is
weaker than that of people’s more direct encounters with corruption in the form
of either bribery, expectation of the need for connections to succeed in business,
or identification of corrupt public tenders. While the socio-economic factors show
an adjusted R square of only two to three percent (see models 1,4 and 7), including
encounters with corruption as explanatory variables increases the value of this
measurement to a range of 14 to 16% (see models 2,5 and 8). Moreover, the
corruption variables remain significant across all three dependent variables, while
the statistical significance of the socio-economic indicators varies greatly: gender
and the type of community where respondents live are only significant when
explaining overall corruption perceptions, but they have no statistically significant
effect when explaining the perceptions of crony capitalism (corruption is part of
the business culture in this country) or particularism in the public sector (bribery
and connections are the easiest way to get a public service).
30
Table 5. Ordered Probit models of explaining individual corruption perceptions.
31
The statistical models also confirm the descriptive evidence linking the frequency of internet access to lower
perceptions of corruption, crony capitalism and particularism. The statistical significance of internet access,
however, disappears once we introduce the control for regional dummies. The self-assessed level in society, as well
as the objective level of income (measured through the difficulty to pay bills every month), on the other hand,
remain statistically significant even when we introduce the regional controls (see models 3, 6 and 9).
Although the number of respondents who have a direct experience with bribery across the EU is limited, we
consistently find that it is a significant determinant in shaping people’s perceptions. Alongside this direct kind of
experience, though, the most powerful explanatory variables are the beliefs that public tenders are corrupt - and
in particular, that political favouritism (political connections) is responsible for business success. Perceptions of
governance thus draw on a larger pool of experiences with business and government, subjectively interpreted, but
observation based, where the distortion by media does not seem not to be significant.
Can we tell apart the most from the least subjective respondents in the sample? We can. The percentage of
people who self-identify as low class in the survey is 27%. When looking at how the group who perceive high
corruption is formed, 30% come from the lowest group, 49% from the middle category and 22 from the highest,
with the poor are slightly over-represented in this group and the rich slightly underrepresented. It’s also worth
noting that these values remain unchanged across our 3 dependent variables (particularism in the public sector,
particularism in the private sector and overall perception of corruption). When conducting the same exercise with
the difficulty of paying bills, we see that 15% of respondents have difficulties paying bills most of the time. Almost
a quarter of the participants (24%) find it hard to pay their bills from time to time and a majority (57%) almost
never or never experience this problem. In this case, the composition of the group perceiving high levels of
corruption and particularism are slightly different from the demographic breakdown, but the numbers also
remain largely consistent across our dependent variables: 17% have difficulties paying bills most of the time, 31%
32
have the same problem from time to time and the remaining 52% belong to those that can always or almost
always pay their bills (see Table 6). In other words, the noise due to inequality and poverty is no more
than a fifth of the sample, and at least three quarters of respondents perceive corruption independent of
their own material situation.
Table 6. Breakdown of high perception of corruption by difficulty to pay bills.
Particularism in
the private
sector is
widespread
Particularism in
the public sector
is widespread
Corruption is
widespread
Difficulties
paying bills
Most of the
time
17.5%
17.1%
17.5%
From time
to time
30.9%
30.7%
31.0%
Almost
never/never
51.6%
52.2%
51.6%
V. Conclusions
33
We have started by asking if our indicators of low trust and moral decay in the third decade of the third millennium
can in any way be better verified than similar perceptions on record from the Western Roman Empire in the fourth
century A.D. Our individual level analysis complements the national level one, leading to three brief conclusions with
serious policy implications:
The first finding is the main contribution to the question and offers a general validation of public perception by more
objective indicators, which is a premiere (it generally works the other way around). In most EU countries people
perceive that government is a source of business favouritism and unable to uphold merit as the main source of
advancement. Most individuals seem to report what they observe and experience, uninfluenced by media or social
status, so these negative perceptions are likely to reflect the overall practices, as well as the integrity policy
framework. We do not have one objective measure to capture all forms and varieties of corruption, but triangulating
from three sources we find enough evidence to argue that there is an objective basis to the widespread feelings that
institutions of European capitalism and democracy have fallen below the standards that they espouse. In other
words, in the countries where we have a perception of institutional decay some objective grounds exist which should
be a source of policy concern. We show at country level, but are not able to provide cross country comparative data
yet, that digital procurement could provide us with time series of public resource allocation allowing tracing change
across years. Had this paper been about comparing one given country with the Roman Empire we are confident that
using such methods and data we would be able to give more ample validation to people’s perception- to the extent
that all perceptions are objectively grounded.
Our second finding, however, is a qualification as it shows that a more subjective group exists within the majority of
Europeans perceiving institutional decay, a minority who feels the most economically disadvantaged, between a
fifth and a quarter on the average, but with great variation within countries, which blames politicians and politics
disproportionately and which turns against the political system. The feeling of being cheated on the part of this
objectively disadvantaged group requires a policy if they are not to be left prey to radical populist movements. As
34
we have seen with Brexit and the election of Donald Trump, pocket groups that lose out because of globalization
develop anti-status and anti-elite narratives and attitudes, which may play a large role in turning a popular vote
against the system. Anticorruption apart, these groups need some better targeted policies to adjust to new realities
in the labour or housing markets.
Finally, it may be worth noting that Scandinavia alone, of all Europe, seems to have succeeded in successfully
addressing both problems, inequality and corruption, although other countries, such as the UK or the Netherlands,
seem to have high integrity capitalism and public sector both. The policy implication is that some sort of optimal mix
might exist between addressing social alienation to avoid people blaming it on political corruption, and controlling
corruption itself. While the main response should be directed to what people consider corruption addressing
government favouritism, the fairness and integrity of taxation, public tenders and public services, as well as
perceived privileges of the political elite - a successful dual approach on the lines suggested here should be sought
for the particular European model. This ideal mix might come close to what Emmanuel Macron is already trying in
France- combining deeper reforms with the removal of very visible forms of favouritism, like nepotism in the
Parliament, to offer a redress alternative solution of perceived institutional decay to the anti-system one promoted
by populists.
35
Appendix
Perception of Private Corruption
Perception of Public Corruption
Political Favoritism
INDEPENDENT
VARIABLES
(β1)
β1
(IV)
β 2
(LifeExp)
Constant
N
R-
squared
Adj. R-
squared
β1
(IV)
β 2
(LifeExp)
Constant
N
R-
squared
Adj. R-
squared
β1 (IV)
Fact-based
(objective)
corruption
indicators
Single bidding
in Public
Procurement
(2009-2013)
1.15***
0.00
51.62
26
0.41
0.35
1.02**
-0.97
137.13*
26
0.35
0.29
1.22***
(0.401)
(0.763)
(64.526)
(0.415)
(0.915)
(76.142)
(0.377)
Index of Public
Integrity
-8.02***
0.44
83.86
28
0.66
0.63
-8.10***
-0.18
139.56*
28
0.61
0.58
-7.67***
(1.391)
(0.749)
(57.233)
(1.582)
(0.936)
(72.153)
(1.517)
Public
Administration
Corruption
Index
0.04**
-0.81
131.52
25
0.23
0.16
0.04*
-1.27
173.83
25
0.25
0.18
0.05***
(0.020)
(1.228)
(99.334)
(0.023)
(1.281)
(102.992)
(0.015)
Subjective
corruption
indicators
WEF
Government
Favoritism
-
18.24***
0.38
105.36***
26
0.76
0.74
-
19.64***
0.15
135.31***
26
0.72
0.70
-17.47***
(2.128)
(0.437)
(32.752)
(3.011)
(0.597)
(45.180)
(2.344)
WGI Control of
Corruption
-7.18***
2.12**
-59.05
28
0.79
0.78
-7.73***
1.80*
-24.30
28
0.81
0.79
-6.75***
(1.014)
(0.792)
(58.910)
(1.168)
(0.890)
(66.496)
(1.055)
National
context
Corruption
experience
(paid a bribe in
the past 12
months)
2.11**
0.84
-3.93
28
0.21
0.15
2.00**
0.06
64.8
28
0.22
0.16
1.97**
(0.91)
(1.30)
(106.25)
(0.92)
(1.45)
(119.19)
(0.87)
-0.05
-1.98**
234.53***
28
0.09
0.02
0.02
-2.64***
288.12***
28
0.13
0.06
-0.08
36
Tertiary
Education
enrollment
(0.271)
(0.912)
(72.968)
(0.310)
(0.903)
(74.306)
(0.224)
Secondary
Education
attainment
among 24-64
year olds
-0.44**
-3.04***
350.76***
28
0.17
0.10
-0.74***
-4.40***
488.21***
28
0.32
0.26
-0.45*
(0.213)
(1.044)
(91.768)
(0.218)
(0.964)
(86.179)
(0.250)
General
government
gross fixed
capital
formation
-
11.10***
-3.98***
429.50***
28
0.30
0.24
-10.74**
-4.56***
480.33***
28
0.29
0.24
-8.76*
(3.831)
(1.108)
(96.874)
(4.204)
(1.199)
(105.046)
(4.404)
Total
government
expenditure (%
of GDP)
-0.68
-0.96
181.83**
28
0.14
0.07
-0.58
-1.76
246.62***
28
0.16
0.09
-0.33
(0.708)
(1.262)
(79.462)
(0.801)
(1.322)
(80.587)
(0.668)
GINI
coefficients
(2013)
1.91
-1.20
112.28
28
0.21
0.15
2.09*
-1.77*
158.27
28
0.25
0.19
2.47**
(1.147)
(1.041)
(107.154)
(1.144)
(0.983)
(101.017)
(1.056)
Robust
standard errors
in parentheses
*** p<0.01, **
p<0.05, *
p<0.10
37
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i
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