Transcript Cooruption measurement in Bulgaria and SEEurope

Study to examine the links between
corruption and organised crime
Tihomir Bezlov and Philip Gounev
Center for the Study of Democracy
Blagoevgrad, 28 February 2013
Content
• Goals and objectives
• Methodology
• Organised crime and corruption
• Institutional perspectives
• Market perspectives
• Member state perspectives
• Case studies
• Recommendations
Objectives
• Take stock of existing studies on the link
• Identify the factors that bring about the use of corruption
by organised crime within the public and private sectors
• provide a framework for future assessment of the trends in
the how corruption is used by organised crime
• provide a framework for future assessment of the
effectiveness of the various preventive and repressive
measures
Scope: defining ‘organised crime’
Data analysis
Data sources
Research methods
156 interviews
(law-enforcement, judiciary,
private sector, academics,
journalists, anti-corruption
authorities)
Semi-structured
interviews
Institutions
:
-Police
-Judiciary
-Customs
-Political
Illegal
Markets:
-Cigarettes
-THB
-Car-theft
-Extortion
Literature
review
Statistical
data:
105
indicators /
indexes
6 country studies
(FR, NL, EL, BG, IT, ES)
Private
sector
MS
clusters
Cluster /
neural
network
analysis
Defining the link
Social
stratification
Immigration
Culture /
informal social
relations
Business
culture
Political
history
Institutional
setup
Institutional
effectiveness
Type of
illegal
market
Economic
factors
Use of
corruption
by OC
Grey
economy
Corruptionand
andGDP
Corruption
300.0
250.0
200.0
150.0
100.0
50.0
0.0
-50.0
IR
NL AT SE DK UK BE
FI
DE FR ES
GDP PPP per capita
IT
EL
SI
CY CZ MT PT SK EE HU LT
Corr Control
Bribes
LV
PL RO BG
Statistical evidence: country clusters
Statistical evidence: country clusters
Cluster 1:
Denmark,
Finland,
Sweden
Cluster 4:
Estonia,
Latvia,
Lithuania,
Portugal
Cluster 2:
Austrian,
Belgium,
Germany, Ireland,
Luxembourg,
Slovenia, Spain,
UK
Weak link b/w
corruption & OC
Cluster 5:
Czech Republic,
Cyprus, Greece,
Hungary, Malta,
Slovakia
Cluster 3:
France
Cluster 6:
Italy
Cluster 7:
Bulgaria,
Poland,
Romania
Strong link b/w
corruption & OC
Issues with statistical evidence and clusters
• Unreliable data (no index on ‘organised crime’)
• Data on corruption measures primarily perceptions / petty
corruption
• No explanations to describe the nature of the relationship
• (many factors are not / are difficult to measure statistically)
• Difficult clustering (unclear boundaries between clusters;
single-country clusters)
Institutions and corruption
•
•
•
•
•
Police
Judiciary
Political corruption
Customs administration and tax administration
Other institutions (depending on OC activity)
• Museums (antiquities market)
• Ministries of agriculture / forest services (illegal logging)
• Ministries of economy / trade (arms trafficking)
Institutions and corruption
Anti-corruption
unit
Anti-corruption
measures
Institutional setup
(powers)
Regional specifics
(pressures)
Culture / informal
social relations
General level of
corruption in
country
Use of
corruption
by OC to
target
institutions
Economic factors
(salaries)
Size / types of
criminal market
Institutions and corruption
Police
corruption
Judicial
corruption
Illegal market / OC activity and corruption
Volume of trade /
infrastructure
Type of illegal
market
Effectiveness of
lawenforcement
Regional
specifics
(pressures)
Culture /
informal social
relations
Government
policies (taxes,
illegality)
Anti-corruption
measures
Use of
corruptio
n by OC
Economic
factors
(salaries)
Grey
economy
Police corruption
Immigration &
OC
Internal affairs
unit s
Economic
factors
(salaries)
Regional
specifics
(pressures)
Culture /
informal social
relations
General level of
corruption
(judicial / political
corruption)
Anti-corruption
measures
Use of
corruption
by OC to
target
police
Policies on
illegal markets
Size / types
of criminal
market
Police corruption
Type
Grid
Group
Description
MS observed
Donkeys
Strong
Weak
work characterised by both isolations and
subordination: individual deviance of lower
level officer
All EU
Hawks
(rotten
apples)
Weak
Weak
a lot of freedom, distance from organisation,
individual deviance (example: higher rank
officers or officers working on highly
confidential material)
FR, ES, UK,
IT, SL, SE, NL,
AU, BE, EI,
DE
Wolves
Strong
Strong
strong group identity creates a subculture
that facilitates organised deviance; group
protection against external controls
FR, ES, IT,
RO, CZ, BG,
PT
Vultures
Weak
Strong
freedom to aggressively seek exploitable
situations, using the cover offered by the
group
BG, EL, RO,
CZ, LT, LA,
CY, PO
Trafficking in human beings and corruption
Recruitment
• Law firms –
arranged
marriages;
• Work/travel
agencies
Transport
• Border
Police
• Counselor
services visa
applications
Exploitation
• Police
officers –
protection
and noninterference
• Local
authorities –
licensing of
premises,
prostitutes
Laundering
• Stores,
transport
companies,
• Financial:
change
bureaus;
• Car-dealers
Further information
www.csd.bg
http://ec.europa.eu/homeaffairs/doc_centre/crime/docs/study_on_links_between_organised_cri
me_and_corruption_en.pdf
Tihomir Bezlov
[email protected]
Philip Gounev
[email protected]