The hidden rules and open secrets of corporate governance. Preliminary results and research plan of European Interlocking directorates. By Elisa Bello, Sergios Lenis, Johan Koskinen, Moses Boudourides, Ning Gao and Martin Everett

1. The
hidden
rules
and
open
secrets
of
corporate
governance.
Preliminary
results
and
research
plan
of
European
Interlocking
directorates.
Elisa
Bello*1,
Sergios
Lenis1,
Johan
Koskinen1,
Moses
Boudourides2,
Ning
Gao1
and
Mar<n
Evere>1
1University
of
Manchester
2University
of
Patras
The
Mitchell
Centre
for
Social
Network
Analysis

2. A
board
of
directors
is
a
body
of
members,
either
elected
or
appointed,
who
supervise
and
manage
the
ac<vi<es
of
an
organiza<on.
-­‐ In
small
private
companies,
the
directors
and
execu<ve
managers
are
normally
the
same
people.
-­‐ Rela<onship
owners
(stakeholders)/directors
-­‐ In
large
public
companies
execu<ve
tasks
are
covered
by
managers,
while
board
in
is
in
charge
of
the
corporate
governance
(recrui<ng
and
compensa<ng
the
CEO
and
the
managers,
defining
the
strategic
goals
and
direc<ons
of
the
organiza<on,
developing
a
governance
system
which
regulates
how
the
board
interacts
with
the
CEO,
looking
aWer
the
assets
of
the
company)
Func<ons
Internal
(Execu<ve)
They
serve
execu<ve
func<ons
within
the
organiza<on
External
(non
execu<ve)
They
are
officers
of
other
large
firms,
eg:
bankers,
insurance
company
execu<ves,
investment
bankers,
a>orneys,
accountants,
and
officers
of
firms
in
a
variety
of
nonfinancial
sectors,
representa<ves
of
groups
such
as
civil
rights
organiza<ons,
of
large
external
stockholders,
including
those
involved
in
recent
acquisi<ons
of
the
firm.
Defini<on

3. Ø Interest
in
the
representa<on
of
banks
and
financial
ins<tu<on
(financial
capital).
Due
to
the
conspicuous
investments,
financial
ins<tu<ons
started
to
request
increasing
controlling
posi<ons
in
large
organiza<ons,
thus
producing
numerous
interlocks.
Ø Geographical
differences:
§ one
<er
(all
directors
in
the
same
board,
like
in
the
US)
or
two-­‐<er
(execu<ve
directors
in
one
board,
non
execu<ve
directors
in
another
board,
like
in
Germany)
board
structure.
§ Uneven
geographical
distribu<on
of
firms
included
in
the
top
European
companies
together
with
varia<ons
in
the
organiza<ons’
sectors.
The
UK
sample
of
top
financial
firms
tend
to
include
more
capital
(finance
related)
corpora<ons,
while
Germany
counts
more
labour
(industry)
oriented
firms.
§ When
looking
at
the
overall
European
network,
German,
English,
French
and
Dutch
firms
are
over-­‐represented,
and
also
account
for
most
of
the
European
interlocks
(Heemskerk
2010).
Ø Evolu<on
of
interlocks:
are
they
increasing
or
decreasing?
Ø Lack
of
variety
in
gender
and
ethnicity
Interlocking
directorates
occur
when
directors
sit
in
different
boards

4. The
old
boys’
network
refers
to
an
informal
group
of
people
with
a
shared
educa<onal
background,
tradi<onally
former
students
of
elite
schools.
Reasons
for
forming
old
boys
networks:
Ø In
UK,
eli<st
public
schools
(like
Eton
and
Winchester)
and
Universi<es
(like
Oxford
and
Cambridge),
have
tradi<onally
being
acknowledged
with
their
role
in
shaping
a
close
knit
group
of
former
members
who
would
then
maintain
privileged
rela<ons
with
each
other.
Ø Similar
func<ons
of
the
Grandes
Ecoles
in
France.
Ø In
the
Netherlands,
the
student
fraterni<es
(studentencorpora)enabled
elite
dis<nc<on
at
the
universi<es.
Ø In
Japan,
elites
are
formed
via
academic
background,
poli<cal
affilia<ons,
rela<onships
with
the
government,
and
marriage
<es.
In
the
Japanese
culture
the
term
“old
boy”
specifically
refers
to
a
former
government
official
who
aWer
re<rement
is
re-­‐employed
in
poli<cs
or
in
the
private
sector
due
to
the
exper<se
and
personal
rela<onships
he
accumulated
in
his
former
profession
as
a
bureaucrat

5. Ways
of
maintaining
old
boys’
networks:
Ø Various
informal
strategies
through
which
the
Japanese
elites
maintain
their
networks,
like
the
mee<ngs
of
the
“Tuesday
club”,
or
private
lunches,
or
even
official
mee<ngs
organised
by
the
ministry
to
keep
the
former
bureaucrats
informed
on
relevant
policy
issues
.
Ø Similarly
a
rela<onship
was
found
between
the
loca<on
of
firms’
headquarters
in
ci<es
where
there
are
exclusive
upper
class
social
clubs
and
the
maintenance
of
local
interlocks,
which
conversely
was
not
found
for
firms
without
headquarters
in
places
with
such
clubs.
Thus,
old
boys’
network
§ Forms
on
the
ground
of
elite
family
background
and
shared
educa<onal
background
§ It
is
preserved
via
a
common
lifestyles
that
requires
belonging
to
the
same
clubs
and
a>ending
the
same
social
events.

6. Reasons
for
interlocks
• Collusion
and
social
cohesion:
interlocks
are
used
by
elites
and
power
groups
to
maintain
privileges
and
exercise
control
over
the
economy.
Elite
studies.
No
systema<c
evidence
of
interlocks
as
mechanisms
to
coordinate
specific
interests
and
favouring
collusion.
• Co-­‐opta<on
and
monitoring:
interlocks
as
an
expression
of
inter-­‐firms’
resource
dependency.
The
interlocks
may
be
used
to
control
the
external
environment
and
access
resources
not
produced
internally,
or
to
pass
informa<on
on
new
policies
and
governances
at
work
in
similar
firms.
Inclusion
of
banks,
financial
and
insurance
companies
in
the
boards
of
directors
as
a
way
in
which
firms
may
guarantee
access
to
liquidi<es,
and
conversely
investors
keep
control
over
their
investments
• Legi<macy
and
career
advancement:
new
companies
try
to
find
directors
with
some
established
reputa<on,
already
serving
in
the
boards
of
successful
organiza<ons,
with
a
diversity
of
skills
and
a
large
number
of
personal
contacts
Unclear
direc<on
of
causality:
interlocked
directors
may
improve
a
firm’s
success,
or
successful
firms
a>ract
well
connected
directors.

7. Network
models
of
interlocking
directorates
Ø One-­‐mode,
“directors
by
directors”
or
“firms
by
firms”,
networks.
§ Analysis
of
composi<on,
as
in
the
type
of
directors
and
firms
that
belong
to
them
(gender,
geographical
loca<on,
industry
sector)
§ Analysis
of
structure,
by
looking
at
size,
cohesiveness,
centraliza<on
and
structural
hole
§ Analysis
of
dynamics,
by
observing
if
the
number
of
interlocks
increases
or
diminishes
over
<me.
SIENA
models
of
1mode:
preferen<al
a>achment
(legi<macy),
homophily
(collusion),
brokerage
(monitoring).
ü Unimodal
projec<ons
implies
a
loss
of
informa<on
(value
of
<es)
and
spurious
structural
features
in
the
randomiza<on
of
the
original
bipar<te
network.
ü In
these
models
“changes
are
largely
explained
through
corporate
specific
covariates
(size,
solvency,
profitability,
etc.)
rather
than
in
terms
of
structural
aspects
of
the
bipar<te
(and
unimodal)
network(s),
i.e.
endogenous
self-­‐
organising”
(Koskinen
et
al.
2012).
ü Previous
models
assume
dyad-­‐independence.

8. Models
for
bipar<te
and
mul<par<te
networks
1. Koskinen
et
al.
(2012)
adapt
a
stochas<c
actor-­‐oriented
model
to
the
study
of
the
evolu<on
of
bipar<te
networks,
which
aims
to
model
the
evolu<on
through
<me
of
the
random
set
of
edges
via
a
con<nuous-­‐<me
Markov
chain.
Ø Peer
referral
measured
by
coun<ng
the
number
of
3paths
that,
in
<me,
become
4cycles
Ø Homophily
and
heterogeneous
cycles

9. 2. Bohman
(2012)
observes
the
probability
that
a
director
interlock
is
formed
if
two
firms
are
owned
by
the
same
owner,
thus
forming
a
4cycle
of
one
owner,
two
firms,
and
one
director.
3mode,
as
directors
and
owners
can
only
relate
to
firms
3. Robins
and
Alexander
(2004)
compare
the
interlocking
directorates’
system
in
US
and
Australia
in
1996.
They
test
whether
these
networks
present
the
proper<es
of
small
worlds,
consis<ng
simultaneously
in
short
path
lengths
and
high
clustering.
Local
proper<es
are
Ø the
geodesic
distances
between
companies,
between
people
and
between
companies
and
people;
Ø the
degree
distribu<on
of
both
people
and
companies;
Ø the
number
of
edges,
stars,
3paths
and
4cycles;
Ø and
the
bipar<te
clustering
coefficient
calculated
as
the
ra<o
of
4cycles
over
3paths.
Compare
observed
against
randomised
networks
as
the
best
way
to
sta:s:cally
test
network
proper:es
where
observa:ons
(dyads)
are
not
independent

10. The
project:
modelling
the
evolu<on
of
the
bipar<te
network
of
European
interlocking
directorates
It
aims
to
develop
innova<ve
methods
for
the
study
of
large,
mul<ple
and
longitudinal
two
mode
networks
of
directors.
It
does
so
by
inves<ga<ng
the
rela<onship
between
the
“old
boys’
network”
and
the
system
of
peer
referral
in
the
boards
of
directors
of
European
firms
listed
on
the
stock
exchange.
AIM
1:
To
look
at
overall
structure
and
composi<on
of
the
social
network
of
both
firms
and
directors.
In
par<cular,
we
want
to
see
if
it
is
possible
to
iden<fy
some
meaningful
clusters,
and
if
these
clusters
represent
significant
subgroups.
We
aim
to
observe:
Ø The
posi<on
of
specific
sectors,
like
financial
organiza<ons,
in
the
network
of
European
interlocks.
Ø If
the
network
is
na<onally
bounded,
or
if
it
is
possible
to
observe
the
emergence
of
an
European
system
of
interlocks,
and
if
that
is
the
case,
if
some
countries,
like
Germany,
France,
the
Netherlands,
and
the
UK,
occupy
central
posi<ons.
Ø From
an
individual
perspec<ve,
we
want
to
see
if
gender
and
ethnicity
boundaries
are
s<ll
in
place,
if
there
are
any
significant
differences
between
execu<ve
and
non-­‐execu<ve
directors,
and
if
it
is
possible
to
iden<fy
the
common
characteris<cs
of
big
linkers.

11. AIM
2:
To
verify
if
a
peer
referral
system
is
in
place,
and
if
it
is
has
been
increasing
or
declining
through
the
years.
Ø We
do
so
by
looking
at
how
previous
affilia<ons
to
the
same
board
of
directors
influence
subsequent
appointments,
controlling
for
relevant
a>ributes
like
gender,
na<onality,
and
age.
Ø We
model
the
probability
of
closing
a
3path
in
a
4cycle
over
<me
by
comparing
the
observed
data
against
randomly
generated
networks.
The
baseline
network
is
the
bimodal
“director
by
firms”
network.
AIM
3:
To
inves<gate
if
there
is
a
rela<onship
between
the
various
informal
networks
that
emerge
over
<me
by
virtue
of
being
affiliated
in
various
types
of
networks
(educa<on,
leisure,
voluntary
ac<vi<es,
and
the
like)
and
the
subsequent
peer
referral
mechanisms.
Ø We
do
so
by
observing
the
probability
that
a
3path
closes
into
a
4cycle
depending
on
affilia<ons
to
other
ac<vi<es.
A>ributes
(of
people
and
firms)
are
used
as
covariates.
Circles = directors
Squares = firms
Hexagon=universities
Stars=private association
Plus=previous employment

12. The
dataset
Boardex
data
covers
the
years
1999
to
2010
for
2.208
European
boards
Ø Company
a>ributes:
geographical
loca<on;
the
sector;
the
financial
index
in
which
it
is
listed;
the
market
cap;
the
revenue
at
the
end
of
the
year.
Ø Director
a>ributes:
age;
date
of
birth;
gender;
na<onality;
the
number
of
boards
to
date
s/he
has
been
si*ng
on;
the
number
of
current
boards
s/he
sits
on;
the
average
number
of
years
spent
in
quoted
boards.
Ø Director
employment
history:
it
links
director
and
companies
indica<ng
current
and
past
board
roles
(in
quoted
firms);
current
and
past
non-­‐board
roles
(in
non
quoted
firms).
Ø Director
educa<on
history:
the
country
of
the
ins<tu<on,
the
type
of
qualifica<on
achieved,
and
the
date
of
the
achievement.
Ø Director
history
in
other
ac<vi<es:
geographical
loca<on
of
these
ins<tu<ons,
and
current
and
past
roles.

13.
Directors
Firms
All
38994
2744
One
mode
dd_current
17441
2156
One
mode
dd_past
28881
2276
One
mode
dd_maincomp_current
12421
One
mode
dd_maincomp_past
26825
One
mode
ff_current
17441
1613
One
mode
ff_past
28881
2276
One
mode
ff_maincomp_current
1436
One
mode
ff_maincomp_past
2229
Ø One
mode
networks,
director
by
director
and
company
by
company,
where
weight
=
the
director
has
sat
in
the
company
board
more
than
once,
or
in
different
roles
(quoted/private).
Ø Two
mode,
director
by
company
network,
which
cons<tute
the
dependent
variable
in
the
longitudinal
analysis.

14. Preliminary
analysis:
directors’
a>ributes
0.2%
3.9%
16.8%
26.2%
22.3%
7.8%
23.0%
Less
than
30
30-­‐39
40-­‐49
50-­‐59
60-­‐69
Over
70
n.a
Directors:
age
distribu<on
%
of
age
categories
11.5%
88.5%
F
M
Directors:
gender
distribu<on
%
of
gender
categories
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
Albania
Indonesia
Latvia
Lituania
Slovakia
Estonia
Monaco
Caribbean
Croa<a
Bermuda
Bulgaria
Slovenia
Romania
Hungary
Ukraina
Cyprus
Czech
Rep
New
Zeland
Iceland
Israel
South
Asia
China
Africa
East
Leichtenstein
Middle
East
Poland
India
Japan
North
Africa
Australia
South
America
Luxemburg
South
Africa
Canada
Russia
Finland
Portugal
Austria
Greece
Denmark
Ireland
Belgium
Switzerland
Spain
Norwegia
Netherlands
US
Italy
Sweden
UK
France
Germany
Unknown
Directors:
na<onality

15. 11.4%
42.2%
24.4%
8.7%
2.8%
1.1%
0.5%
0.5%
8.4%
Less
than
1
1
to
5
5
to
10
10
to
15
15
to
20
20
to
25
25
to
30
Over
30
na
Directors:
%
of
average
years
in
boards
75.6%
12.1%
4.0%
1.6%
0.7%
0.2%
0.1%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
5.6%
1
2
3
4
5
6
7
8
9
10
11
12
13
15
n.a
Directors:
number
of
current
boards
Descrip<ve
Value
MEAN
1.319
MAXIMUM
VALUE
15
MINIMUM
VALUE
1
STANDARD
DEVIATION
0.798

16. Preliminary
analysis:
companies’
a>ributes
0%
2%
4%
6%
8%
10%
12%
14%
16%
Germany
France
UK
Sweden
Netherlands
Switzerland
Italy
Norway
Republic
Of
Spain
Belgium
Greece
Finland
Denmark
Austria
Luxembourg
Russian
Portugal
Poland
Cyprus
Iceland
North
Africa
US
China
Monaco
South
Asia
Hong
Kong
Croa<a
Czech
Republic
Hungary
Malta
Ukraine
Canada
Liechtenstein
Romania
Australia
Bermuda
Bulgaria
Caribbean
Slovenia
South
Africa
South
America
Unknown
Companies:
na<onality
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
Real
Estate
SoWware
&
Computer
Banks
Transport
Speciality
&
Other
Oil
&
Gas
Pharmaceu<cals
and
Engineering
&
Diversified
Industrials
Construc<on
&
Media
&
Investment
Companies
Health
Telecommunica<on
Food
Producers
&
Business
Services
Clothing,
Leisure
and
Electronic
&
Electrical
Leisure
&
Hotels
Informa<on
Mining
Renewable
Energy
Chemicals
General
Retailers
Insurance
Automobiles
&
Parts
Private
Equity
Steel
&
Other
Metals
Electricity
Household
Products
U<li<es
-­‐
Other
Beverages
Food
&
Drug
Retailers
Forestry
&
Paper
Aerospace
&
Defence
Containers
&
Life
Assurance
Publishing
Tobacco
Blank
Check
/
Shell
Consumer
Services
Wholesale
Trade
Regulators
Trade
Associa<on
Companies
by
sector

17. Over
100000
0.5%
50000-­‐100000
1%
10000-­‐50000
7%
1000-­‐10000
22%
Less
1000
70%
Companies:
revenue
(Millions
of
Euros).

18. One
mode
“directory
by
director”
network
The
“director
by
director”
network
is
obtained
by
transforming
the
two
mode
original
“director
by
company”
network
into
the
corresponding
one
mode,
where
the
value
indicates
the
number
of
boards
two
directors
sit
together.
The
analysis
is
done
on
the
filtered
data
to
be
matched
with
people’s
a>ributes,
both
for
current
and
past
appointments,
reducing
the
total
number
of
directors
in
the
network
to
17441
nodes
in
the
current
network,
and
28881
nodes
in
the
past
network.
The
current
network
There
are
614
components
in
the
current
network,
where
the
main
one
includes
71%
(12421)
of
directors.
The
others
are
all
very
small
components,
with
less
than
50
directors
in
them.
The
distribu<on
of
directors’
a>ributes
in
components,
in
terms
of
age,
gender
and
na<onality,
does
not
significantly
diverge
from
the
overall
directors’
characteris<cs.
A>ribute
of
directors
in
main
component
Yule’s
Q
(+1=heterophily)
Gender
-­‐0.0092
Na<onality
0.9005
Age
0.0859

19. The
past
network
There
are
313
components
in
the
past
network,
half
than
the
number
of
components
in
the
current
network,
indica<ng
a
progressive
fragmenta<on.
Also,
main
one
includes
93%
(26825)
of
directors,
compared
to
the
71%
of
the
current
network,
confirming
this
fragmenta<on
tendency.
The
distribu<on
of
a>ributes
is
rela<vely
similar
to
the
one
of
the
overall
directors,
with
the
only
difference
that
Ø the
directors
aged
between
60
and
70
are
more
numerous
than
the
average
of
all
directors,
and
of
the
current
networks
Ø men
are
slightly
overrepresented
A>ribute
of
directors
in
main
component
Yule’s
Q
(+1=heterophily)
Gender
0.1073
Na<onality
0.9240
Age
0.0858

20. One
mode
“company
by
company”
network
The
“company
by
company”
network
is
obtained
by
transforming
the
two
mode
original
“director
by
company”
network
into
the
corresponding
one
mode,
where
the
value
indicates
the
number
of
directors
two
boards
share
together.
The
analysis
is
done
on
the
filtered
data
to
be
matched
with
companies’
a>ributes,
both
for
current
and
past
appointments,
reducing
the
total
number
of
firms
to
1613
nodes
in
the
current
network,
and
2276
nodes
in
the
past
network
The
current
network
There
are
75
components
in
the
current
company
by
company
network,
and
the
main
one
includes
89%
(1436)
of
nodes.
The
distribu<on
of
a>ributes
slightly
diverges
from
the
overall
companies.
Ø UK
is
not
well
embedded
in
the
main
component,
although
it
represents
the
third
country
for
number
of
companies.
Ø SoWware
companies
are
not
predominant
in
the
main
component,
despite
the
large
number
of
companies
listed.
Ø The
main
component
seem
to
be
composed
by
companies
with
a
slightly
be>er
revenue
than
average,
possibly
indica<ng
the
tendency
of
interlocking
with
firms
of
similar
size.

21. A>ribute
of
companies
in
main
component
Yule’s
Q
(+1=heterophily)
Geographical
loca<on
0.9346
Sector
0.6644
Revenue
0.3809
The
past
network
22
components,
many
less
than
in
the
current
one.
All
the
companies
used
to
belong
to
the
main
component
(97%).
Switzerland
is
be>er
interlocked
than
in
the
past.
SoWware
companies
and
other
financial
sectors
were
be>er
embedded.
No
differences
in
the
Yule’s
Q
compared
to
the
current
network.

22. Discussion
Directors:
Ø Male
dominance
Ø Most
of
them
in
the
age
range
of
40
–
70
Ø Most
of
them
European
Ø Years
in
boards:
between
1
and
15
Ø 75%
do
not
interlock,
and
most
interlocks
only
share
2/3
boards
Companies:
Ø Overrepresenta<on
of
Germany,
France,
UK,
Sweden.
Followed
by
Netherlands,
Switzerland
and
Italy
Ø Sectors:
Banks
and
financial
ins<tu<ons
s<ll
occupy
the
third
and
fiWh
place
in
terms
of
presence
Ø 70%
with
a
revenue
less
than
1000
millions,
but
22%
between
1000-­‐10.000,
and
few
very
rich
companies

23. Discussion
One
mode
director
by
director
network:
Ø 1
large
component
Ø Interlockers
interlock
with
people
of
different
na<onali<es
(but
mainly
European)
Ø The
network
is
fragmen<ng
in
a
higher
number
of
small
components,
and
the
main
component
is
decreasing
in
size
Ø More
men
and
older
people
in
the
past
network,
possibly
indica<ng
the
tendency
to
appoint
female
and
younger
directors
One
mode
company
by
company
network:
Ø 89%
of
companies
in
the
main
component,
although
this
is
decreasing
in
size
(fragmenta<on)
Ø UK
and
soWware
companies
are
less
embedded
in
the
main
component
compare
to
their
overrepresenta<on
in
the
data
Ø Homophily
in
revenue:
interlocks
between
companies
of
similar
success
Ø No
na<onal
networks,
but
a
European
one
Ø Directors
interlock
across
sectors:
no
sector
specializa<on

24. Challenges
Ø Large
networks:
implementa<on
of
network
measures
in
Phyton
Ø Missing
data:
lack
of
informa<on
across
all
the
variables
S<ll
to
do…
Ø Analysis
of
the
old
boys
network:
§ Educa<onal
ins<tu<ons
§ Other
ac<vi<es
Ø Modelling
bipar<te
network
(peer
referral
system)
§ Implementa<on
of
directors
trajectories
Ø Modelling
mul<mode
networks
(condi<oning
peer
referral
system
against
old
boys
network
Ø How
to
handle
missing
data.
Possibility
of
crossing
informa<on
with
other
datasets,
and/or
of
es<ma<ng
the
missing
informa<on

25. The
project
is
intended
to
be
the
first
step
toward
a
bigger
proposal
to
look
at
extending
the
analysis
to
the
US
and
UK
networks,
and
to
connect
the
various
na<onal
networks
together.
This
last
step
will
grant
the
possibility
of
observing
cross-­‐na<onal
forms
of
corporate
governance
over
<me,
and
to
answer
some
substan<al
ques<ons
over
the
extension
and
the
connec<veness
of
the
globaliza<on
process.
Future
projects
If
you
are
interested
in
par:cipa:ng
to
future
bids,
please
come
to
talk
to
us!
elisa.belloA@manchester.ac.uk