MEASURING AND EXPLAINING MANAGEMENT
PRACTICES ACROSS FIRMS AND COUNTRIES
February 2006
Nick Bloom
Stanford, Centre for Economic Performance and AIM
John Van Reenen
LSE and Centre for Economic Performance
MOTIVATION
Large persistent profit and productivity spread across firms
and countries - Economists since Marshall typically claim this is
due to differences in “management” ability
• But what is the role of management?
•
Is management simply “Good” or “Bad”; or
•
Does management vary optimally according to firms
conditions – different “styles”
• And why does it vary so much across firms and countries?
SUMMARY OF THE PAPER (1 of 3)
(1) Measuring Management
• Develop a survey tool to “measure” management practices
• New data on 732 firms in US,UK, France & Germany.
• Management data:
• Correlated productivity, profits, Tobin’s Q, growth &
survival - there is “Good” and “Bad” management
•
•
Correlated environment – also some optimal response
Robust to measurement error and bias
• This survey tool can be applied much more broadly - e.g.
empirically modelling firm organisational structures
SUMMARY OF THE PAPER (2 of 3)
(2) Explaining Management
• Observe big spread in management practices (Fig. 2 over)
• Wide cross firm spread (like profits & productivity)
•
Significant differences across countries
• US 1st, Germany 2nd, France 3rd and UK 4th
• Demonstrate that two factors appear significant:
• Production market competition – positive effect
• Family managed firms – negative effect
• Family firm ownership but not management is fine
•
Family ownership and management problematic,
particularly under primo geniture CEO succession
n=157
.8
0
.2
.4
.6
Density
.8
.6
.4
.2
0
2
3
4
1
2
3
4
US
5
n=290
.8
.6
.4
.2
0
0
.2
.4
.6
Density
.8
1
n=154
1
UK
5
1.2
1
1.2
Germany
1
n=137
1
France
1.2
1.2
FIRM LEVEL AVERAGE MANAGEMENT SCORES
1
2
3
4
5
1
2
3
4
5
SUMMARY OF THE PAPER (3 of 3)
(3) Quantifying this Effect
• Competition and family-management important, explains:
(a) Over 50% of the tail of badly managed firms
(b) Between 1/3 to 2/3 of US-Europe management gap:
• Europe has lower levels of competition
• UK & France also many more primo geniture
family firms due to Norman legal origin & tradition
• Our management measure can account for up to 20%
(OLS) or 60% (IV) of the productivity dispersion
OUTLINE
1. Why should management practices vary?
2. “Measuring” management practices
3. Evaluating the reliability of this measure
4. Describing management across firms & countries
5. Explaining management across firms & countries
Why Should Management Practices Vary?
Two models - not mutually exclusive
• “Optimal choice of management practices”
• Another factor of production (like advertising)
•
No “better” or “worse” style of management – depends
on firm’s circumstances
• “Exogenous managerial inefficiency
• Part of total-factor productivity
• Strictly “better” or “worse” styles of management
• Empirically we find some support for both
Pure Models of Management Practices (1/2)
Optimal choice of management practices

 1  1


 1

Y  B1M 1    B2 M 2 


with M1 and M2 management practices (i.e. “physical” & “human”
capital management) costing ρ1 and ρ2, wit impact B1 and B2
Simple predictions from FOC:
• Productivity will be correlated with management
• Profitability will not be correlated with management
• Ratio M1/M2 will be correlated with B1/B2 and P2/P1
• i.e. relative importance and price of skills
Pure Models of Management Practices (1/2)
Exogenous managerial inefficiency – part of “TFP”
Mundlak (1961) and Lucas (1978) style concept of productivity
differences:
Y  A( M ) ( X )
where M scale indicator of management practices, A(M) is TFP
and dA(M)/dM > 0
Simple predictions from FOC:
• Productivity will be correlated with management
• Profitability will be correlated with management
• Ratio M1/M2 will not be correlated with B1/B2 and P2/P1
1. Why should management practices vary?
2. “Measuring” management practices
3. Evaluating the reliability of this measure
4. Describing management across firms & countries
5. Explaining management across firms & countries
SOME RELATED LITERATURE - EXAMPLES
Management, organisation & performance
•
HRM / Management practices:
Ichinowski, Shaw, and Prenushi (1997),
Ichinowski and Shaw (1995), Black and
Lynch (2001), and Lazear (2000); Bartel,
Ichniowski and Shaw (2004)
•
Organisational practices: Bresnahan,
Brynjolfsson and Hitt (2002) and Caroli
and Van Reenen (2001)
•
Individual managers: Bertrand and
Schoar (2003)
Productivity dispersion & dynamics
•
Establishments: Baily, Hulten, and
Campbell (1992), Bartelsman and
Dhrymes (1998), and Jensen,
McGuckin and Stiroh (2001), Foster,
Haltiwanger and Syverson (2003)
•
Countries: O’Mahony & Van Ark (2004),
Caselli (2005)
Family firms
•
Empirical: La Porta, Lopez-DeSilanes and Schleifer (1999),
Bertrand et al (2004), Sraer &
Thesmar (2004), Bennedsen,
Nielsen, Perez-Gonzales &
Woflenzon (2005)
•
Theory: Burkart, Panunzi and
Schleifer (2003), Caselli and
Gennaioli (2005)
•
Economic History: Landes (1969),
Chandler (1994), Nicholas (1999)
Competition and firm performance
•
Empirics: Nickell (1996), Syverson
(2004), and Aghion, Bloom, Blundell,
Griffith, and Howitt (2005)
•
Dynamic theory: Jovanovic (1982)
and Hopenhayn (1992)
•
Theory: Schmidt (1997), Raith
(2003) and Vives (2004)
STEPS TO TRY TO MEASURE MANAGEMENT
1) Developing management scoring
• Scorecard for key practices (next slide)
• 1 hour telephone interview of (manufacturing plant) managers
2) Obtaining unbiased responses
• “Double-blind”
• Managers are not informed (in advance) they are scored
• Interviewers do not know company performance
•
Detailed controls for interviewee, interviewer & timing
3) Getting firms to participate in the interview
•
•
•
Introduced as “Lean-manufacturing” interview, no financials
Endorsement of Bundesbank ,UK Treasury, Banque de France
Run by 10 MBAs (loud, pushy & business experience)
SCORECARD COVERS 18 QUESTIONS IN 4 AREAS
Initially Developed by an international management consultancy
All questions & 50 examples in the paper – in summary:
OPERATIONS (3 questions) – problem fixing, standard Lean
manufacturing
MONITORING (5) - tracking, review & evaluation, follow-up etc.
TARGETS (5) - transparent, stretching, inter-connected, time
horizon, etc
INCENTIVES (5) - promotions, rewards, fix/fire, retention etc.
MONITORING - i.e. “HOW IS PERFORMANCE TRACKED?”
Score (1) Measures tracked
do not indicate
directly if overall
business objectives
are being met.
Certain processes
aren’t tracked at all .
(3) Most key
performance
indicators are
tracked formally.
Tracking is overseen
by senior
management.
(5) Performance is
continuously tracked and
communicated, both
formally and informally, to
all staff using a range of
visual management tools.
“A US manager who
tracked a range of
measures when he
didn’t think output
was sufficient. He last
requested reports 8
months ago, checked
them for one week,
and then stopped
checking once output
had increased again”
“A US firm barcoded every product,
and performance
indicators were
tracked throughout
the production;
however this
information was not
communicated to
workers”
“A US firm had screens
visible to every production
line displaying hourly
progress to target. The plant
manager met daily with the
shop floor to discuss these.
He even stamped canteen
napkins with key
performance achievements”
E.G.
MANAGEMENT SURVEY SAMPLE
•
US (290), UK, France and Germany (≈150 each)
•
Medium sized manufacturers (50 - 10,000 employees, median
≈ 700)
• Medium sized because firm practices more homogeneous
• Manufacturing as easier to measure productivity
•
Obtained 54% coverage rate from sampling frame
• Response rates uncorrelated with performance measures
SAMPLE NOISE/BIAS CONTROLS
8 INTERVIEWEE CONTROLS
• Gender, seniority, post tenure, firm tenure, countries worked
in, foreign, worked in US, plant location, reliability score
3 INTERVIEWER CONTROLS
• Set of analyst dummies, cumulative interviews run, prior firm
contacts
5 TIME CONTROLS
• Day of the week, time of day (interviewer), time of the day
(interviewee), duration of interview, days from project start
ADDITIONAL MATCHED DATA WE COLLECTED
HR Survey
• Skills, demographics, hours, organisational characteristics,
number of competitors etc.
Ownership & Family Survey
• Shareholders & managerial characteristics, family involvement,
family progression rules etc.
Performance Data
• Separately match company accounts - so collect management
and performance data from completely different sources
Industry and Trade Data
•
OECD
1. Why should management practices vary?
2. “Measuring” management practices
3. Evaluating the reliability of this measure
a) Internal/External validation
b) Contingency
c) Measurement error/bias
4. Describing management across firms & countries
5. Explaining management across firms & countries
INTERVAL VALIDATION OF THE SCORING
• Re-interviewed 64 firms with different interviewers and managers
Firm average scores (over 18 question)
2nd interview
5
4
• Firm-level average
correlation of 0.759
3
`
2
1
1
2
1st
3
interview
4
5
EXTERNAL VALIDATION OF THE SCORING
Performance
measure
country c
yitc  MNGic   c l litc   c k kitc   c m mitc   c ' xitc  uitc
management
(average z-scores)
ln(capital)
other controls
ln(labor)
ln(materials)
•
Use up to 11 years of accounting data for 1994-2004
•
Note – not a causal estimation, only an association
EXTERNAL VALIDATION: PRODUCTIVITY & PROFIT
Dependent
variable
Sales
Sales
Sales
(in Ln)
(in Ln)
(in Ln)
Estimation1
OLS
OLS
OLS
All
All
All
Firms
ROCE Tobin Q
Exit
(in Ln)
Sales
growth
OLS
OLS
OLS
Probit
All
Quoted
All
All
Managementi
0.085
0.034
0.250 0.018
0.042
2.469
(0.025) (0.011) (0.012) (0.688) (0.075)- (0.006)
-0.200
[0.026]
Ln(Labor) it
0.999
0.539
0.540
2.172
(0.014) (0.021) (0.021) (1.202)
0.209
(0.109)
-0.022
(0.011)
0.233
[0.045]
Ln(Capital) it
0.103
0.104 -0.148
(0.013) (0.013) (0.899)
-0.029
(0.086)
0.024
(0.008)
-0.158
[0.045]
Ln(Materials) it
0.362
0.354 -0.439
(0.020) (0.020) (0.723)
0.130
(0.050)
-0.010
(0.007)
-0.084
[0.231]
Controls1
No
Yes
Yes
Yes
Yes
Yes
Yes
Noise controls
No
No
Yes
Yes
Yes
Yes
Yes
Observations
6,267
5,350
5,350
5,089
2,635
4,777
709
Firms
732
709
709
690
374
702
709
1 Includes country, year, SIC3 industry, skills, hours, firm-age, and public/private
Robust S.E.s in ( ) below. For probit p-values in [ ] below
EXTERNAL VALIDATION – ROBUSTNESS
Productivity correlations robust to type of TFP estimation
•
OLS, Olley-Pakes, GMM & Within-Groups
Results also significant in most recent cross-section (2003/04)
Results significant in both Anglo-Saxon (US and UK) and
European” (France and Germany) countries
CONTINGENT MANAGEMENT PRACTICES
Dependent Var
Level
Ln (% degrees)i
firm level
HC
Manage
ment
FC
Manage
ment
HC-FC
Manage
ment
HC-FC
Manage
ment
HC-FC
Manage
ment
Firm
Firm
Firm
Firm
Industry
0.220
(0.039)
0.100
(0.043)
0.120
(0.043)
Ln (ave wage)i
firm level
0.337
(0.122)
0.281
(0.169)
Ln (% degrees)j
Industry level (US)
Standard Errors
Firms
Robust
Robust
Robust
Robust
Clustered
732
732
732
424
732
Note: “HC management” average z-score of the 3 most human capital focused
questions (questions 13, 17 and 18). “FC management” average z-score of the
3 most fixed capital focused questions (1, 2 and 4). “HC-PC management” is
the difference of these two measures.
CONCERNS WITH OUR MANAGEMENT MEASURE?
Three potential issues:
1) Measurement error (classical), but
•
Attenuation downwardly biases our results
•
We try to control for this with “Noise” controls
(management & interview characteristics)
CONCERNS WITH OUR MANAGEMENT MEASURE?
(2) Firm performance-related measurement bias in
management score (i.e. good firms “talk-up” practices), but
• Surveying methodology designed to try to minimize this
• Competition and management positively linked (later)
• Management-performance link is as important in France &
Germany (where managers less likely to “talk up” AngloSaxon practices) as it is in UK & US
• No link between past productivity growth & management
• Not all questions significant (and not linked to “subjectivity”)
• Other subjective questions insignificant – i.e. “feel-good” worklife balance questions, organisational devolvement questions
So potential problem – but no evidence that major phenomenon
CONCERNS WITH OUR MANAGEMENT RESULTS?
(3) Reverse causality (management correctly measured
but better firm performance causes better management),
• Main point of performance estimations is external
validity of the measure
• But if interpretation is effect of management on
productivity note that the bias is ambiguous
• When use IV (later) management coefficient
increases substantially
OUTLINE
1. “Measuring” management practices
2. Evaluating the reliability of this measure
3. Describing management across firms & countries
4. Explaining management across firms & countries:
- competition
- family managed firms
n=157
.8
0
.2
.4
.6
Density
.8
.6
.4
.2
0
2
3
4
1
2
3
4
US
5
n=290
.8
.6
.4
.2
0
0
.2
.4
.6
Density
.8
1
n=154
1
UK
5
1.2
1
1.2
Germany
1
n=137
1
France
1.2
1.2
FIRM LEVEL AVERAGE MANAGEMENT SCORES
1
2
3
4
5
1
2
3
4
5
COUNTRY LEVEL MANAGEMENT SCORES*
US
3.35
Germany
3.31
France
UK
3.14
3.07
Typical UK managers?
Bad manufacturing management - a UK tradition?
“Efficient management is the single most significant factor
in the American productivity advantage”
[Marshall Plan Anglo-American productivity mission, 1947]
* With controls for size & public/private values are 3.35, 3.27, 3.16 & 3.07 respectively.
Gaps between UK/France and the US significant at the 5% level
OUTLINE
1. “Measuring” management practices
2. Evaluating the reliability of this measure
3. Describing management across firms & countries
4. Explaining management across firms & countries:
- competition
- family managed firms
Competition & Models of Management Practices
“Exogenous managerial inefficiency” – positive impact
• Selection models Hopenhayn (1992) or Syverson (2004)
“Optimal choice model” – ambiguous impact
• In contracting models balance between opposing profit
and market-size effects (Raith 2003, Vives 2004).
COMPETITION AND MANAGEMENT PRACTICES (TABLE 4)
3 competition proxies from Nickell (1996) & Aghion et al. (2005)
Competition proxies
Import penetration
(SIC-3 industry,
1995-1999)
Dependent variable: Management
0.144 0.156
(0.040) (0.084)
1 - Lerner index1
(SIC-3 industry except
firm itself, 1995-1999)
1.515 1.318
(0.683) (0.637)
# of competitors
(Firm level,
2004)
Full controls2,3
0.142 0.145
(0.051) (0.049)
No
Yes
No
Yes
No
Yes
index = (operating profit – capital costs)/sales ≈ rents
2 Includes 108 SIC-3 industry, country, firm-size, public and interview noise
(analyst, time, date, and manager characteristic) controls, = 732 obs
3 S.E.s in ( ) below, robust to heteroskedasticity, clustered by country-industry
1 Lerner
FAMILY FIRMS & MANAGEMENT – AN OLD TOPIC
Alfred Chandler1 and David Landes2 both claimed UK & French
industrial decline relative to US & Germany linked to family firms
“The Britain of the late 19th Century basked complacently in
the sunset of economic hegemony. Now it was the turn of the
3rd generation…and the weakness of British enterprise
reflected their combination of amateurism and complacency”
“French enterprise was family-owned and operated, securityorientated rather than risk-taking, technologically conservative
and economically inefficient”
Alfred Chandler, “Scale and Scope: The Dynamics of Industrial Capitalism”, (1994)
2 David Landes, “The Unbound Prometheus: Technological Change and Industrial
Development in Western Europe from 1750 to the Present”, (1969)
1
WE DO FIND GREATER UK & FRENCH FAMILY
MANAGEMENT IN OUR DATA (100 YEARS ON),
%
UK
Fra
Ger
US
Family1 largest shareholder
30
32
30
10
Family1 largest shareholder
and family CEO
23
22
12
7
Family1 largest shareholder,
family CEO & primo geniture2
15
14
3
3
1 Family
defined as 2nd generation or beyond (so not the founder).
Shareholdings combined across all family members.
2 Based on question: “How was management of the firm passed down:
was it to the eldest son or by some other way?”. Non primo geniture
alternatives in frequency order: other sons, son in-laws, daughters,
brothers, wives, nephews and cousins.
WHY DOES FAMILY INVOLVEMENT VARY ACROSS
COUNTRIES?
• Historical differences
• UK & France tradition of Primo Geniture:
[Oxford English Dictionary, 2005]
“Feudal rule of inheritance introduced into England by the
Norman Conquest. Replaced Teutonic gavelkind. Obligatory
until the Statute of Wills [1540]. Still common in many places”
• US and Germany tradition of equal division (Menchik, 1980)
• Estate tax headline rates1: on family firms (on standard assets)
• US ≈ 50% (50%); France ≈ 25% (40%)
• UK = 0% (40%);
1 Rate
Germany ≈ 15% (45%)
on a $25m firm. In practice these taxes are often reduced/avoided by advanced
tax planning, although this involves foresight, financial costs and some control loss.
FAMILY FIRMS AND MODELS OF MANAGEMENT
PRACTICES
“Exogenous managerial inefficiency” – depends on involvement
• Ownership but not management probably positive
• Concentrated ownership so better monitoring
• Management probably negative
• Smaller pool to select CEO from
• Possible “Carnegie” effect on future CEO’s
• Both effects will be worse with primo geniture
(succession of eldest son to CEO position)
“Optimal choice model” – ambiguous impact
• Variety possible effects, but unlikely linked to primo
geniture (which is empirically important)
FAMILY OWNERSHIP AND FAMILY MANAGEMENT (TABLE 5)
%
Dependent variable: Management
Family1
-0.029
(0.094)
largest shareholder
Family1 largest shareholder &
family CEO
0.304
(0.166)
-0.100
(0.078)
Family1 largest shareholder, family
CEO & primo geniture
Observations2
1 Family
732
732
-0.175
(0.188)
-0.281
(0.097)
-0.382
(0.128
732
732
defined as 2nd generation or later
2 Note includes SIC-3 digit, country, skills, firm size, firm age & public controls
REVERSE CAUSALITY AND INSTRUMENTAL VARIABLES
• The productivity & management correlations are tests of external
validity of management score, not causal relations
• Productivity shocks may cause management (generating bias):
• Positive bias: more productive firms “buy in” better managers
• Negative bias: in the more productive firms the managers
can “afford” to exert less effort
• Management regressions suggest possible IVs:
(i) competition; and (ii) family primo geniture management
• But need to assume that the only way that competition and primo
geniture effect productivity is through management - strong
I.V. MANAGEMENT IN PRODUCTION FUNCTION
Dependent Var
Estimation1
Ln
(Sales)
Ln
(Sales)
Ln
(Sales)
Ln
(Sales)
Ln (Sales)
OLS
OLS
OLS
OLS
IV
0.042
(0.012)
0.216
(0.097)
Management
Competition
(Import penetr.)
Family CEO &
primo geniture
Instruments
(F-test)
Over-identifying
restriction (p-val)
0.089
(0.032)
0.088
(0.032)
-0.060
(0.030)
-0.058
(0.030)
Imports,Family
(20.79)
0.520
% 75:25 TFP gap
accounted for by
12%
63%
management
1 Other variables include log(Labor), log(Capital), log(Materials), country, year,
SIC3 industry, skills, hours, firm-age, and public/private. All 709 observations
S.E.s in ( ) below, robust to arbitrary heteroskedasticity
QUANTIFYING THESE EFFECTS:
• ACROSS FIRMS
• ACROSS COUNTRIES
1.2
MANY COMPETITORS AND NO (PG) FAMILY CEO
.8
1
N=317
0
.2
.4
.6
2.7% firms in tail1
1
2
3
4
5
Average management score across questions and interviews - note dropping lean3
1.2
FEW COMPETITORS AND/OR (PG) FAMILY CEO
1
N=415
0
.2
.4
.6
.8
9.0% firms in tail1
1
2
3
4
5
Average management score across questions and interviews - note dropping lean3
1
Tail defined as a score ≤ 2. In the whole sample 6.9% of firms are in the tail.
ACCOUNTING FOR THE CROSS-COUNTRY SCORES
Dependent Variable1
Country is US
Management
Baseline
Baseline
Baseline
Baseline
Country is Germany
-0.045
(0.064)
-0.036
(0.063)
-0.004
(0.063)
0.063
(0.067)
Country is France
-0.202
(0.086)
-0. 115
(0.088)
-0.077
(0.088)
-0.021
(0.089)
Country is UK
-0.276
(0.078)
-0.199
(0.076)
-0.188
(0.076)
-0.107
(0.079)
-0.658
(0.102)
-0.648
(0.102)
-0.606
(0.100)
0.147
(0.052)
0.154
(0.051)
Family owned, family CEO
and primo geniture
# of competitors
Ln (% employees with a
degree)
Observations
1
0.134
(0.037)
732
732
OLS estimation on 732 observations
S.E.s in ( ) below, robust to arbitrary heteroskedasticity
732
732
TO SUMMARIZE
•
Original methodology for measuring management
•
Product market competition & family management important
•
•
Explain 50% of tail of badly managed firms
•
Explain 2/3 of US-France gap & 1/3 of US-UK gap
Immediate 2006 plan follow up with larger survey:
•
Get ≈ 2500 sample and panel dimension
•
Extend to Italy, Poland and Sweden (and Asia in 2008)
•
Include questions on organisational structure,
communication and control
Design very flexible so any suggestions welcome
Quotes:
THE WORLD OF MANUFACTURING
Spoke to companies making…..
• Coffin liners
• Plastic balls to stop birds nesting on water near airports
(reported no competitors)
• German sex-toys (few exports – aimed at domestic “tastes”)
….and an amazing array of people
• “I spend most of my time walking around cuddling and
encouraging people - my staff tell me that I give great hugs”
• [US male manager to an Australian female interviewer]
“Your accent is great and I like your talk – are you married?”
• “……….…..[long silence]………….sorry I just got distracted
by a submarine surfacing in front of my office window”
BACK-UP
TARGETS – e.g. TARGETS ARE STRETCHING (Q.11)
Score (1) Goals are either
too easy or
impossible to
achieve; managers
low-ball estimates
to ensure easy
goals
(3) In most areas, top
management pushes for
aggressive goals based on
solid economic rationale.
There are a few "sacred
cows" not held to the
same rigorous standard
(5) Goals are genuinely
demanding for all
divisions. They are
grounded in solid,
solid economic rational
E.G.
A chemicals firm has 2
divisions, producing
special chemicals for
military and civilian
markets. Easier levels of
targets are requested from
the founding and more
prestigious military
division.
A UK manager insists
that he sets aggressive
and demanding goals
for everyone – even
security. If they hit all
their targets he worries
he hasn’t stretched
them enough.
A French firm uses
easy targets to
improve staff
morale. They find it
difficult to set
harder goals
because people give
up and managers
refuse to work
people harder
INCENTIVES – e.g. PROMOTIONS (Q.16)
Score (1) People are
promoted primarily
upon the basis of
tenure
(3) People are
(5) We actively identify,
promoted upon the develop and promote our
basis of
top performers
performance
E.G.
People learn on the
job and are
promoted based on
their performance
on the job.
A UK firm promotes
based on an
individual’s
commitment to the
company, typically
measured by
experience. Almost
all employees move
up in lock-step.
In a UK firm each employee
is thoroughly assessed every
6 months and given a red
light (not performing), amber
light (doing well – on track)
a green light (high performer
- promote) and a blue light
(extreme performer promote twice)
US FIRMS ARE ALSO BETTER IN EUROPE
Average management score by firm type
in UK, France and Germany*
# in sample
Domestic
379
Non-US multinational
subsidiary
US multinational
subsidiary
3.13
3.25
3.58
44
20
* Controls for any sample selection on size (direct and group) and listing
0
score
Management
-.1
.1
.2
AGE AND MANAGEMENT PRACTICES (KERNEL1)
-.2
10 years
1
2
75 years
3
Log firm age
4
5
Firm age (in logs)
1
ephi_orig
ephi_p95
ephi_p5
Point-wise confidence intervals (in feint) generated from 1000 bootstraps
3
4
5
6
7
Lowess smoother
-2
bandwidth = .8
-1
0
Management Score
1
2
FAMILY OWNERSHIP PROBIT
Dependent variable
1 Marginal
Family owned, family
CEO & primo geniture1
Country = UK
0.109
[0.015]
Country = France
0. 096
[0.042]
Country = Germany
0.058
[0.303]
Log (employees)
-0.022
[0.012]
Log (firm-age)
0.052
[0.017]
Industry controls
Yes
Observations
718
effects, p-values in [ ] brackets underneath
EFFORT EFFECTS OF COMPETITION (APPENDIX E)
•
With fixed number of firms ambiguous
(Schmidt 1997; Raith 2003; Vives 2004 )
•
“Bankruptcy effect”: competition increases effort as
managers strive to avoid bankruptcy (+tive)
•
“Business stealing effect”: competition makes market
share more sensitive to differences in marginal cost,
increasing contracting on effort (+tive)
•
“Scale effect”: competition lowers profits so lowers
returns to increasing market share, reducing contracting
on effort (-tive)
•
Raith (2003) Under free entry higher competition reduces
number of firms “scale effect” switched off, comp
unambiguously +tive
SOME LIMITED EVIDENCE FOR EFFORT EFFECTS?
Dependent
variable
Lerner index
(5-yr lagged)
Managerial Hours Worked
6.660
1.809
(4.129) (5.869)
Import penetration
(5-yr lagged)
-0.230 1.082
(0.444) (0.948)
Number of
competitors
1.155
0.935
(0.509) (0.623)
Firms
727
727
733
733
733
733
Observations
727
727
733
733
733
733
Full controls*
No
Yes
No
Yes
No
Yes
*Includes 108 SIC-3 digit dummies, country dummies, firm size and type
S.E.s robust to arbitrary heteroskedasticity, clustered by country-industry
THE SELECTION EFFECTS OF COMPETITION
•
Pure “Selection” effects predicts older firms better managed
•
But “Vintage” effects predict older firms worse managed
•
•
Management practices improve over time
•
But organisational adjustment costs (Shaw et al, 1997)
•
So firms do not fully keep up with the frontier
Simulate this with a Hopenhayn (1992) style model assuming
•
Equilibrium rate of entry and exit (2%)
•
Entrants from relative upward trending normal distribution
•
Exits by noisy signal of management ability
COMPETITION AND AGE SIMULATION
Management score
Kernels of age vs. management score for simulated data*
Firm age (in logs)
* see http://cep.lse.ac.uk/matlabcode