MEASURING AND EXPLAINING MANAGEMENT PRACTICES ACROSS FIRMS AND COUNTRIES October 2007

(1)

MEASURING AND EXPLAINING MANAGEMENT PRACTICES ACROSS FIRMS AND COUNTRIES October 2007

Nick Bloom

Stanford & NBER John Van Reenen LSE & NBER

(2)

MOTIVATION

Large persistent productivity spread across firms and countries:

people typically claim this is due to differences in “management”

• But what is the role of management?

• And why does it vary so much across firms and countries?

(3)

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:

• Appears consistently measured within firms

• Correlated with productivity, profits, Tobin’s Q, growth

& survival

• Robust to measurement error and bias

(4)

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 1^st, Germany 2^nd, France 3^rd and UK 4^th

•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

(5)

0.2.4.6.811.2Density

1 2 3 4 5

0.2.4.6.811.2Density

1 2 3 4 5

0.2.4.6.811.2Density

1 2 3 4 5

0.2.4.6.811.2Density

1 2 3 4 5

FIRM LEVEL AVERAGE MANAGEMENT SCORES

France n=137 n=157

n=290 n=154

UK US

Germany

(6)

SUMMARY OF THE PAPER (3 of 3)

(3) Quantifying this Effect

•Competition and family-management important, explains about 50% of firm-level management tail; and 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

(7)

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

OUTLINE

(8)

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 (Mundlak, 1961;

Lucas 1978)

• Part of total-factor productivity

• Strictly “better” or “worse” styles of management

•Empirically we find some support for both

(9)

1. Why should management practices vary?

2. “Measuring” management practices 3. Evaluating the reliability of this measure

(10)

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);

Cappelli and Neumark (2001), Bartel, Ichniowski and Shaw (2004),

• Organisational practices: Bresnahan, Brynjolfsson and Hitt (2002) and Caroli and Van Reenen (2001)

• Individual managers: Bertrand and Schoar (2003)

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)

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-De- Silanes and Schleifer (1999),

Bertrand et al (2004), Villalonga and Amit (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)

(11)

STEPS TO TRY TO MEASURE MANAGEMENT

1) Developing management practice scoring

• Scorecard for 18 monitoring, targets and incentives practices

• 45 minute phone interview of (manufacturing plant) managers 2) Obtaining unbiased responses

• “Double-blind”

•Interviewers do not know company performance

•Managers are not informed (in advance) they are scored 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, assertive & business experience)

(12)

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

MONITORING - i.e. “HOW IS PERFORMANCE TRACKED?”

Note: All 18 dimensions and over 50 examples in Bloom & VanReenen (2006).

(13)

ADDITIONAL CONTROLS FOR BIAS & NOISE

8 INTERVIEWEE CONTROLS

• Gender, seniority, tenure in post, tenure in firm, 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

(14)

MANAGEMENT SURVEY SAMPLE

• US (290), UK, France and Germany (≈150 each)

• Medium sized manufacturers (100 - 10,000 employees, median ≈ 600)

•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

(15)

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

(16)

1. Why should management practices vary?

3. Evaluating the reliability of this measure a) Internal/External validation

b) Contingency

c) Measurement error/bias

(17)

INTERVAL VALIDATION OF THE SCORING

1^st interview 2nd interview

• Re-interviewed 64 firms with different interviewers and managers Firm average scores (over 18 question)

• Firm-level average correlation of 0.759

(18)

EXTERNAL VALIDATION OF THE SCORING

Performance measure

c it c

it c

c m it

c c

k it c c

l it c c

i c

it

MNG l k m x u

y           ' 

ln(capital)

ln(materials) management

(average z-scores) ln(labor)

other controls

• Use up to 11 years of accounting data for 1994-2004 country c

• Note – not a causal estimation, only an association

(19)

Dependent variable

Sales

(in Ln) Sales

(in Ln) ROCE Tobin Q

(in Ln)

Sales

growth Exit

Estimation¹ OLS OLS OLS OLS OLS OLS Probit

Firms All All All All Quoted All All

Management_i 0.085

(0.025) 0.034

(0.011) 0.042 (0.012)

2.469 (0.688)

0.250

(0.075)- 0.018 (0.006)

-0.200 [0.026]

Ln(Labor) _it 0.999 (0.014)

0.539

(0.021) 0.540

(0.021) 2.172 (1.202)

0.209 (0.109)

-0.022 (0.011)

0.233 [0.045]

Ln(Capital)_it 0.103

(0.013) 0.104 (0.013)

-0.148 (0.899)

-0.029

(0.086) 0.024 (0.008)

-0.158 [0.045]

Ln(Materials) _it 0.362

(0.020) 0.354

(0.020) -0.439 (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

EXTERNAL VALIDATION: PRODUCTIVITY & PROFIT

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

(20)

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) country subsets

(21)

CONTINGENT MANAGEMENT PRACTICES

Dependent Var HC Manage

ment

FC Manage

ment

HC-FC Manage

ment

Level Firm Firm Firm Firm Industry

Ln (% degrees)_i firm level

0.220 (0.039)

0.100

(0.043) 0.120 (0.043) Ln (ave wage)_i

firm level

0.337 (0.122) Ln (% degrees)_j

Industry level (US)

0.281 (0.169) Standard Errors Robust Robust Robust Robust Clustered

Firms 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.

(22)

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)

(23)

CONCERNS WITH OUR MANAGEMENT MEASURE?

(2) Firm performance-related measurement bias in

management score (i.e. the “happy manager” problem), but

• Surveying methodology using examples tries 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” Anglo- Saxon 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” work- life balance questions, organisational devolvement questions So potential problem – but no evidence that major phenomenon

(24)

CONCERNS WITH OUR MANAGEMENT RESULTS?

(3) Reverse causality (management correctly measured but better firm performance causes better management),

• Yes – but main point of performance estimations is external validity of the measure

• Also note that if interpretation is effect of management on productivity note that the bias is ambiguous

(25)

3. Describing management across firms & countries

4. Explaining management across firms & countries:

- competition

- family managed firms

OUTLINE

(26)

0.2.4.6.811.2Density

1 2 3 4 5

0.2.4.6.811.2Density

1 2 3 4 5

0.2.4.6.811.2Density

1 2 3 4 5

0.2.4.6.811.2Density

1 2 3 4 5

FIRM LEVEL AVERAGE MANAGEMENT SCORES

France n=137 n=157

n=290 n=154

UK US

Germany

(27)

COUNTRY LEVEL MANAGEMENT SCORES*

US

Germany

UK 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]

France

(28)

US FIRMS ARE ALSO BETTER IN EUROPE

Average management score by firm type in UK, France and Germany*

Domestic

Non-US multinational subsidiary

US multinational subsidiary

* Controls for any sample selection on size (direct and group) and listing

# in sample 379

44

20

(29)

3. Describing management across firms & countries

4. Explaining management across firms & countries:

- competition

- family managed firms

OUTLINE

(30)

Factors we did not find a significant relationship for

Unions: negative but not significant

•But: (i) sample ≈ 450 firms; and (ii) issues over causation

•Was negative and significant for two individual practices:

• Fixing/firing bad performers,

• Rewarding good performers

CEO Pay: no link in levels – but issues over causation

Ownership/Governance: positive but insignificant for ownership concentration and board indepedence measures:

•But sample only UK/US quoted firms (≈ 350)

Leverage: nothing with debt/equity – but issues over causation

(31)

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).

(32)

Competition proxies Dependent variable: Management Import penetration

(SIC-3 industry, 1995-1999)

0.144 (0.040)

0.156 (0.084) 1 - Lerner index¹

(SIC-3 industry except firm itself, 1995-1999)

1.515 (0.683)

1.318 (0.637)

# of competitors (Firm level,

2004)

0.142

(0.051) 0.145 (0.049)

Full controls^2,3 No Yes No Yes No Yes

COMPETITION AND MANAGEMENT PRACTICES (TABLE 4)

1 Lerner 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

3 competition proxies from Nickell (1996) & Aghion et al. (2005)

(33)

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 19^th Century basked complacently in the sunset of economic hegemony. Now it was the turn of the 3^rd generation…and the weakness of British enterprise

reflected their combination of amateurism and complacency”

“French enterprise was family-owned and operated, security- orientated rather than risk-taking, technologically conservative and economically inefficient”

1 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)

(34)

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 2^nd 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.

(35)

WHY DOES FAMILY INVOLVEMENT VARY ACROSS COUNTRIES?

• Historical differences

• UK & French 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 German tradition of equal division (Menchik, 1980)

• Estate tax headline rates¹: on family firms

• US ≈ 50% France ≈ 25%

• UK = 0% Germany ≈ 15%

1 Rate 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.

(36)

FAMILY FIRMS AND MODELS OF MANAGEMENT PRACTICES

Likely family impact 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)

(37)

FAMILY OWNERSHIP AND FAMILY MANAGEMENT (TABLE 5)

% Dependent variable: Management

Family¹ largest shareholder -0.029 (0.094)

0.304 (0.166) Family¹ largest shareholder &

family CEO

-0.100 (0.078)

-0.175 (0.188) Family¹ largest shareholder, family

CEO & primo geniture

-0.281 (0.097)

-0.382 (0.128

Observations² 732 732 732 732

1 Family defined as 2^nd generation or later

2 Note includes SIC-3 digit, country, skills, firm size, firm age & public controls

(38)

QUANTIFYING THESE EFFECTS:

• ACROSS FIRMS

• ACROSS COUNTRIES

(39)

0.2.4.6.811.2Density

1 2 3 4 5

Average management score across questions and interviews - note dropping lean3

0.2.4.6.811.2Density

1 2 3 4 5

Average management score across questions and interviews - note dropping lean3

MANY COMPETITORS AND NO (PG) FAMILY CEO

FEW COMPETITORS AND/OR (PG) FAMILY CEO

2.7% firms in tail¹

9.0% firms in tail¹

1 Tail defined as a score ≤ 2. In the whole sample 6.9% of firms are in the tail.

Sample splits significantly different at 5%, but not if exclude firms with score ≤ 2

N=415 N=317

(40)

Dependent variable Management

Country is US Baseline Baseline Baseline Baseline Baseline Country is Germany -0.045

(0.064)

-0.081 (0.075)

-0.090 (0.075)

-0.051 (0.074)

0.010 (0.076) Country is France -0.202

(0.086)

-0.183 (0.104)

-0. 131 (0.103)

-0.075 (0.102)

-0.028 (0.102)

Country is UK -0.276

(0.078)

-0.276 (0.093)

-0.227 (0.091)

-0.199 (0.091)

-0.126 (0.079) Family owned, family

CEO & primo geniture -0.638

(0.101) -0.628

(0.100) -0.584 (0.098)

# of competitors 0.142

(0.052) 0.161 (0.051) Ln (% employees with

a degree) 0.145

(0.037)

Public & size controls No Yes Yes Yes Yes

Observations 732 732 732 732 732

ACCOUNTING FOR THE CROSS-COUNTRY SCORES

1 OLS on 732 observations. S.E.s in ( ) robust to arbitrary heteroskedasticity

(41)

• 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

• Last summer ran 3500 firm survey on firms in Europe, US and Asia covering management and organisational structure

Research design very flexible so any suggestions welcome Quotes:

TO SUMMARIZE

(42)

BACK-UP

(43)

MY FAVOURITE QUOTES:

[Male manager speaking to an Australian female interviewer]

Production Manager: “Your accent is really cute and I love the way you talk. Do you fancy meeting up near the factory?”

Interviewer “Sorry, but I’m washing my hair every night for the next month….”

The British Chat-Up

(44)

Interviewer: “How many production sites do you have abroad?

Manager in Indiana, US: “Well…we have one in Texas…”

Americans on geography

Production Manager: “We’re owned by the Mafia”

Interviewer: “I think that’s the “Other” category……..although I guess I could put you down as an “Italian multinational” ?”

The difficulties of defining ownership in Europe

(45)

The bizarre

Interviewer: “[long silence]……hello, hello….are you still there….hello”

Production Manager: “…….I’m sorry, I just got distracted by a submarine surfacing in front of my window”

The unbelievable

[Male manager speaking to a female interviewer]

Production Manager: “I would like you to call me “Daddy” when we talk”

[End of interview…]

(46)

Score (1) People are promoted

primarily upon the basis of tenure

(3) People

are promoted upon the

basis of

performance

(5) We actively identify, develop and promote our top performers

INCENTIVES - i.e. “HOW DOES THE PROMOTION SYSTEM WORK?”

(47)

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

TARGETS - i.e. “HOW TOUGH ARE TARGETS?”

(48)

Dependent Var Ln

(Sales) Ln

(Sales) Ln (Sales) Estimation¹ Reduced form, OLS Full, OLS Full, IV

Management 0.042

(0.012)

0.216 (0.097) Competition

(Import penetr.)

0.089 (0.032)

0.088 (0.032) Family CEO &

primo geniture

-0.060 (0.030)

-0.058 (0.030) Instruments

(F-test) Imports,Family

(20.79) Over-identifying

restriction (p-val) 0.520

% 75:25 TFP gap

accounted for 12% 63%

I.V. MANAGEMENT IN PRODUCTION FUNCTION

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

(49)

-.2-.10.1.2ephi_orig/ephi_p5/ephi_p95

1 2 3 4 5

Log firm age

ephi_orig ephi_p5 ephi_p95

AGE AND MANAGEMENT PRACTICES (KERNEL

¹

)

Firm age (in logs)

Management score

10 years

1 Point-wise confidence intervals (in feint) generated from 1000 bootstraps

75 years

(50)

34567Sales per employee

-2 -1 0 1 2

Management Score

bandwidth = .8

Lowess smoother

(51)

FAMILY OWNERSHIP PROBIT

Dependent variable 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

1 Marginal effects, p-values in [ ] brackets underneath

(52)

SOME LIMITED EVIDENCE FOR EFFORT EFFECTS?

*Includes 108 SIC-3 digit dummies, country dummies, firm size and type S.E.s robust to arbitrary heteroskedasticity, clustered by country-industry

Dependent

variable Managerial Hours Worked

Lerner index (5-yr lagged)

6.660

(4.129) 1.809 (5.869) Import penetration

(5-yr lagged)

-0.230

(0.444) 1.082 (0.948) Number of

competitors

1.155

(0.509) 0.935 (0.623)

Firms 727 727 733 733 733 733

Observations 727 727 733 733 733 733

Full controls* No Yes No Yes No Yes