Labor Representation in Governance as an Insurance Mechanism

measlyincompetentUrban and Civil

Nov 29, 2013 (3 years and 11 months ago)

72 views

Labor Representation in Governance as an

Insurance Mechanism

E
. Han Kim, Ernst Maug and Christoph
Schneider

Presentation at the Ackerman Conference on Corporate Governance

Bar
-
Ilan University, 17.12.2012


Motivation

Question: What is the impact of labor representation on boards


on employment


on wages


on economic efficiency?


Contrasting views


Efficient contracting: Labor representation supports efficient insurance contracts


Workers receive insurance in exchange for lower wages (e.g.,
Baily (1974), Harris &
Holmstrom (1982) , Holmstrom (1983
)
)


Labor representation prevents ex
-
post expropriation


Rent seeking: Labor representation protects rents of workers and managers


Jensen
&
Meckling (1979)
,
Pagano & Volpin (2005), Cronqvist et al. (2009
)


Views on Labor Representation

“The campaigns for ‘worker participation’ or ‘industrial democracy’ or codetermination
on boards of directors appear to be attempts to control the wealth of stockholders'
specialized assets … a wealth confiscation scheme.”

(
Alchian
,
1984)



The

Chicago

view
:

The

European

view
:

“Allen
and Gale (2002) argue that in incomplete, imperfect markets, a stakeholder
system of corporate governance that stresses cooperation between management and
employees may allocate resources more efficiently in the long run than a shareholder
system.” (Fauver and Fuerst, 2006, p. 674)

World Map of Labor Representation on
Boards

Institutional background

Codetermination
in Germany


Up to 500 employees
in Germany:


no
worker representation


More than 500 up to 2000 employees
in Germany:


1/3
of the board members have to be worker representatives


Board size between 3 and 21 can be chosen (multiple of
3)


More than 2000 employees in
Germany:


1/2
of the board members have to be worker representatives


Casting vote of the chairman (shareholder representative)



Board size 12, 16 or
20 (cutoff:s
10,000 and 20,000
employees)


Exception in the iron
, coal,
and steel industry: one
neutral
member in firms with more
than 1000 employees (board size:
11, 15, 21)



Research questions

What is the impact of parity codetermination on


employment: do parity
-
codetermined firms provide more insurance to workers
against adverse shocks?


wages: to the extent that the workers in parity
-
codetermined firms recieve
insurance, do they pay an insurance premium?


firm risk: are parity
-
codetermined firms more risky because they provide insurance
to their workers?

Sample


184
large listed German corporations
(1990
-
2009
)


All DAX and MDAX companies


Most
publicly available information (governance, stock market, balance sheet, and P&L
data
)



IAB sample of all German businesses (1975
-
2008)


Detailed establishment level data on industry,
location, employment,
wages,
education,
age, (nationality
)


In total approx. 33.4 million establishment
-
year observations
for
period
1990
-
2008




34,000
establishments matched to 142 of our 184 firms


Matching on company and subsidiary names and addresses for the year 2006 (2004,
2005)


Research design


Compare how negative shocks affect employees and


firms with parity codetermination vs.


firms with less or no representation on the board


Difference
-
in
-
difference
model:




i

indexes establishments


j

indexes firms


k

indexes state of location


l

indexes industry


t

indexes time


ijklt i t k jt lt jt lt ijt ijklt
y Parity Shock Parity Shock X
a a a d q b g e
= + + + + + ´ + +
Definition of shocks


Shock needs to be


large enough
to have a significant impact


frequent enough to permit identification


exogenous to the firm



We use non
-
sample firms with establishments in Germany (IAB employment data)


Based on >30 million establishment
-
years


Industry defined as 3
-
digit NACE (subsector), similar to NAICS



Shock
lt

=
1 in
industry
l if
employment in the industry decreases
by at least
5%


Shock
lt
=
1 in industry l only if employment growth ≤ 0 in year t+1 (persistence)

Shocks: Examples


Shocks can be long
-
lived
:


2
-
year shocks:
Shock
lt+1
= 1 if
Shock
lt
= 1 and employment growth ≤ 0 in year t+1


4
-
year shocks:
Shock
lt+j
= 1 if
Shock
lt
= 1 and employment growth ≤ 0 in year t+j

for j=1, 2,
3


baseline case




t

1

2

3

4

5

Case A


Employment
growth

-
6%

-
2%

0%

2%

-
1%


Shock
(4
-
year interval)

1

1

1

0

0

Case B


Employment
growth

-
10%

2%

0%

2%

-
1%


Shock
(4
-
year interval)

0

0

0

0

0

Case C


Employment
growth

-
10%

-
2%

0%

-
2%

-
1%


Shock
(4
-
year interval)

1

1

1

1

0

Case D


Employment
growth

-
10%

-
2%

0%

-
5%

-
1%


Shock
(4
-
year interval)

1

1

1

1

0

0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2 years
up to 4 years
Distribution of shocks across time




Parity codetermination is a commitment device. With parity
codetermination, workers receive full
insurance against
adverse shocks
to employment.


Hypothesis
1

Do parity firms protect their employees?

Dependent variable
:

log
number of employees



(1)

(2)

(3)

(4)

(5)

(6)

(7)

Shock
×

Parity

0.2000

0.1900

0.1700

0.1630

0.1470

0.1340

0.1380

(3.00)

(3.03)

(3.09)

(2.17)

(2.37)

(1.82)

(2.20)

Shock

-
0.1860

-
0.1760

-
0.1390

-
0.1760

-
0.1370

-
0.1460

-
0.1270

(
-
3.16)

(
-
3.07)

(
-
2.85)

(
-
2.62)

(
-
2.54)

(
-
2.34)

(
-
2.51)

Parity

-
0.1780

-
0.0180

-
0.0400

-
0.1030

-
0.1070

-
0.1000

-
0.1030

(
-
1.48)

(
-
0.21)

(
-
0.56)

(
-
0.88)

(
-
1.08)

(
-
0.91)

(
-
1.12)

LogPlantAge

0.0100

0.1200

0.0080

0.1010

0.0220

0.1020

(0.40)

(4.17)

(0.33)

(4.05)

(0.86)

(4.13)

LogSales

-
0.0450

0.1040

-
0.1170

0.0110

0.4310

0.1090

(
-
1.02)

(2.31)

(
-
2.65)

(0.29)

(1.47)

(0.34)

Leverage

-
0.1000

-
0.1740

-
0.0310

-
0.0710

0.0000

-
0.0670

(
-
1.21)

(
-
2.36)

(
-
0.46)

(
-
1.08)

(0.00)

(
-
0.79)

LogEmployees

0.4450

0.4080

0.5890

0.6490

(3.74)

(3.93)

(1.31)

(1.48)

LogSales²

-
0.0120

-
0.0020

(
-
1.70)

(
-
0.29)

LogEmployees²

-
0.0080

-
0.0130

(
-
0.30)

(
-
0.49)

adj. R²

0.908

0.913

0.916

0.917

0.919

0.917

0.92

Observations

52,756

51,188

51,188

51,188

51,188

51,188

51,188

F
-
Test: Shock
×

Parity+Shock=0

0.675

0.829

0.244

0.729

0.729

0.737

0.714

Year F.E.

No

No

Yes

No

Yes

No

Yes

Establishment F.E.

Yes

Yes

Yes

Yes

Yes

Yes

Yes

State F.E.

No

Yes

Yes

Yes

Yes

Yes

Yes

Do parity firms protect their employees?

Employment changes after adverse industry shocks

-15%
-10%
-5%
0%
5%
Non-parity
Parity
All employees

-15%
-10%
-5%
0%
5%
Non-parity
Parity
Do parity firms protect their employees?

Employment changes after adverse industry shocks

All employees

White collar

-15%
-10%
-5%
0%
5%
Non-parity
Parity
Do parity firms protect their employees?

Employment changes after adverse industry shocks

All employees

White collar

Blue
collar

-15%
-10%
-5%
0%
5%
Non-parity
Parity
Do parity firms protect their employees?

Employment changes after adverse industry shocks

All employees

White collar

Blue
collar

Unskilled blue
collar




Firms with parity codetermination pay on average lower
wages.


Hypothesis 2

Do
employees pay
an i
nsurance premium
?

Dependent variable

Median wage of unskilled
employees

Median wage of skilled
employees

Median wage of highly
skilled employees

(2)

(3)

(5)

(6)

(8)

(9)

Parity

-
0.0560

-
0.0570

-
0.0120

-
0.0130

-
0.0310

-
0.0300

(
-
1.66)

(
-
1.69)

(
-
0.64)

(
-
0.68)

(
-
2.03)

(
-
2.03)

LogPlantAge

-
0.0010

0.0000

-
0.0160

-
0.0160

0.0020

0.0020

(
-
0.06)

(
-
0.04)

(
-
1.90)

(
-
1.88)

(0.66)

(0.74)

LogSales

0.0140

0.0140

0.0130

0.0130

0.0480

0.0480

(0.80)

(0.81)

(1.18)

(1.17)

(4.42)

(4.36)

LogMedianEmpAge

0.1680

0.1660

0.1370

0.1380

0.1400

0.1400

(5.35)

(5.32)

(4.46)

(4.49)

(7.16)

(7.06)

adj. R²

0.812

0.813

0.894

0.895

0.832

0.833

Observations

84,751

84,751

233,396

233,396

81,817

81,817

Year F.E.

Yes

No

Yes

No

Yes

No

Industry F.E.

No

No

No

No

No

No

Establishment F.E.

Yes

Yes

Yes

Yes

Yes

Yes

State F.E.

Yes

No

Yes

No

Yes

No

County F.E.

No

Yes

No

Yes

No

Yes

Is there any wage compression?

Dependent variable


3rd
-

1st quartile wage scaled
by

median
wage of all full
-
time employees



(1)

(2)

(3)

Parity

-
0.0050

-
0.0050

-
0.0050

(
-
0.71)

(
-
0.74)

(
-
0.73)

LogPlantAge

0.0250

0.0240

(2.56)

(2.52)

LogSales

0.0180

0.0180

(2.18)

(2.15)

LogMedianEmpAge

-
0.1060

-
0.1040

(
-
4.15)

(
-
4.11)

adj. R²

0.743

0.749

0.75

Observations

53,909

53,909

53,909

Year F.E.

Yes

Yes

No

Industry F.E.

Yes

No

No

Establishment F.E.

Yes

Yes

Yes

State F.E.

Yes

Yes

No

County F.E.

No

No

Yes




Parity
-
codetermined firms suffer larger reductions of
profitability after adverse shocks than non
-
parity firms.



Hypothesis 3

Performance of codetermined firms (1)



Dependent variable: ROA



(1)

(2)

(3)

(4)

FirmShock
×

Parity

-
0.0300

-
0.0310

-
0.0320

-
0.0320

(
-
2.22)

(
-
2.27)

(
-
2.34)

(
-
2.41)

FirmShock

-
0.0130

-
0.0260

-
0.0140

-
0.0260

(
-
1.07)

(
-
2.13)

(
-
1.15)

(
-
2.14)

Parity

-
0.0110

-
0.0140

-
0.0080

-
0.0110

(
-
1.32)

(
-
1.75)

(
-
0.95)

(
-
1.42)

adj. R²

0.488

0.501

0.493

0.512

Observations

1,815

1,815

1,815

1,815

Firm F.E.

Yes

Yes

Yes

Yes

All linear conrols

Yes

Yes

Yes

Yes

Squared controls

No

No

Yes

Yes

Year F.E.

No

Yes

No

Yes

Performance of codetermined
firms (2)



Dependent variable: Log TobinsQ



(1)

(2)

(3)

(4)

FirmShock
×

Parity

-
0.1380

-
0.1290

-
0.1090

-
0.0920

(
-
2.62)

(
-
2.47)

(
-
2.10)

(
-
1.80)

FirmShock

-
0.0740

-
0.1010

-
0.0660

-
0.0750

(
-
1.62)

(
-
2.24)

(
-
1.48)

(
-
1.70)

Parity

0.0450

0.0340

0.0460

0.0310

adj. R²

0.645

0.666

0.658

0.682

Observations

1,885

1,885

1,885

1,885

Firm F.E.

Yes

Yes

Yes

Yes

All linear conrols

Yes

Yes

Yes

Yes

Squared controls

No

No

Yes

Yes

Year F.E.

No

Yes

No

Yes

Performance of codetermined firms (3)

Dependent variable:

CAPM Beta



(1)

(2)

(3)

(4)

FirmShock
×

Parity

0.2830

0.2120

0.2750

0.2530

(2.13)

(1.86)

(2.06)

(2.21)

FirmShock

0.0140

-
0.1270

0.0110

-
0.1540

(0.12)

(
-
1.27)

(0.09)

(
-
1.54)

Parity

0.0740

0.0470

0.0670

0.0330

(1.47)

(1.11)

(1.32)

(0.78)

adj. R²

0.406

0.58

0.408

0.584

Observations

1,675

1,675

1,675

1,675

Firm F.E.

Yes

Yes

Yes

Yes

All linear conrols

Yes

Yes

Yes

Yes

Squared controls

No

No

Yes

Yes

Year F.E.

No

Yes

No

Yes

Conclusion


Employees of parity
-
codetermined firms receive substantially more employment
insurance


Only skilled blue
-
collar and white
-
collar workers benefit


Unskilled workers receive no protection


Only highly
-
qualified employees pay an insurance premium


Skilled blue
-
collar employees enjoy insurance without paying a premium


Parity
-
codetermined firms have significantly larger operating leverage


Larger declines in ROA and Tobin‘s q, increase in CAPM beta