These slides present the first results from the second wave of a pilot survey, the Management and Expectations Survey, which gathered information on British management practices and firms' expectations for future growth.

1. Management practices and productivity in Great Britain:
First results from the Management and expectations survey
ESCOE Conference 2018
Philip Wales (ONS)
Gaganan Awano (ONS), Nicholas Bloom (Stanford), Ted Dolby (ONS), Jenny Vyas
(ONS), Paul Mizen (Nottingham), Rebecca Riley (NIESR), Tatsuro Senga (QMUL)
and Philip Wales (ONS)

2. Overview
• Motivation
• The Management and Expectations Survey
• Preliminary results
• Next steps

3. Motivation

4. • The UK’s recent labour productivity performance has
been strikingly weak…
4
Motivation

5. 5
75
80
85
90
95
100
105
1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
Output per hour Output per worker
The UK’s ‘Productivity Puzzle’: Q4 2007=100
Source: ONS Labour Productivity
Motivation

6. • The UK’s recent labour productivity performance has
been strikingly weak…
• …the UK’s ‘productivity gap’ remains stubbornly wide…
6
Motivation

7. Motivation
7
Labour productivity (OPW) in the G7: UK=100
Source: ONS International Comparisons of Productivity

8. • The UK’s recent labour productivity performance has
been strikingly weak…
• …the UK’s ‘productivity gap’ remains stubbornly wide…
• …while the ‘gaps’ between firms are equally striking…
8
Motivation

9. 9
0.0%
0.5%
1.0%
1.5%
2.0%
-10 0 10 20 30 40 50 60 70 80 90 100
Density, %
Productivity, £,000
Firm-level output per worker, 2015
Source: ‘Who are the laggards?’ Understanding firms in the bottom 10% of the labour productivity distribution
Motivation

10. • Common, cross-country finding of wide dispersion in productivity levels across
businesses (Syverson 2004, 2011, ONS 2017), even within tightly defined industries
(Foster, Haltiwanger and Syverson 2008).
• Management found to be a significant covariate with productivity at the business level
(Bloom and Van Reenen 2007, 2010), suggesting that the way managers approach the
management function may be an important determinant of firm performance (Bloom
et al 2012, 2014)
• Growing literature which examines the drivers of management (ONS 2017, Broszeit et
al 2016), highlighting ownership status and size in particular.
• Earlier ONS pilot survey - Management Practices in the Manufacturing Industries –
followed up with Management and Expectations Survey
10
Literature

11. Motivation
11
Decile of Management Practice Score
Productivity Operating Profit Output Growth
Source: Bloom et al, 2013,“Management in America”, Center for Economic Studies Working Paper, US Census
Bureau

12. Management and Expectation Survey
(MES)

13. Management and Expectations Survey (MES)
Survey of 25,000 firms, covering
private business economy
Excludes finance and agriculture
Designed to give representative
results by size-band, industry and
region
15 questions on management and
organisation

14. Management questions
Questions following US Management and Organisational
Practices Survey (MOPS) to assess:
• Business characteristics (size, ownership, qualifications)
• Continuous improvements (problems in production)
• Key performance indicators (how many, monitoring frequency, by whom)
• Targets (time-frame, ambition, incentives)
• Employment practices (promotion, performance review, underperformance)

15. Management and Expectations Survey (MES)

16. Score
1/3
2/3
1
0

17. Response rates
17
Count Percent
Total sample 25006 100%
Non-response 15325 61%
Of which:
No reply 14432 58%
Opt outs 893 4%
Responded 9681 39%
Of which:
Also responded to ABS 8222 33%
Met management score threshold 7841 31%

18. 53%
52%
55%
64%
4%
3%
4%
7%
43%
45%
41%
29%
10-49
50-99
100-249
250+
No reply Refused Replied
Response rates by employment size
18

19. Results

20. Mean management results
20
Domain result Question result(s)

21. 21
Distribution of management results
Share of
population
80%
11%
5%
4%
100%

22. 0
0.5
1
1.5
2
2.5
3
3.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Density, %
Score
10 to 49 50 to 99 100 to 249 250+ Population
Distribution of management score by firm size

23. 23
Share of
population
20%
80%
100%
7%
1%
12%
19%
20%
2%
9%
30%
Distribution of management score by industry

24. Share of
population
95%
5%
55%
11%
66%
34%
100%
Distribution of management score by industry

25. Management & Productivity

26. Conditional analysis
Interested in two questions:
1. What determines management practices?
2. How are they related to productivity?
𝑀 = 𝑓 𝑥
𝑦 = 𝑓 𝑥, 𝑀

27. Conditional analysis
Interested in two questions:
1. What determines management practices?
2. How are they related to productivity?
𝑀 = 𝑓 𝑥
𝑦 = 𝑓 𝑥, 𝑀

28. Management practices
Standard errors in parentheses
* p < 0.05, ** p < 0.01, *** p < 0.001
Table 2: Multivariate analysis of management score by business characteristics, Great Britain, 2016
Dependent variable is management score
(1)
Log(employment) 0.081
***
(0.00)
Family-owned
Family-owned and non-family-
managed
Family-owned and family-managed
Foreign owned
Age
Age squared
Industry dummies Yes
Education controls No
Location dummies No
R-squared 0.238
Observations 7841

29. Management practices
Standard errors in parentheses
* p < 0.05, ** p < 0.01, *** p < 0.001
Table 2: Multivariate analysis of management score by business characteristics, Great Britain, 2016
Dependent variable is management score
(1) (2)
Log(employment) 0.081
***
0.077
***
(0.00) (0.00)
Family-owned 0.000
(0.01)
Family-owned and non-family-
managed
Family-owned and family-managed
Foreign owned 0.083
***
(0.01)
Age
Age squared
Industry dummies Yes Yes
Education controls No No
Location dummies No No
R-squared 0.238 0.244
Observations 7841 7810

30. Management practices
Standard errors in parentheses
* p < 0.05, ** p < 0.01, *** p < 0.001
Table 2: Multivariate analysis of management score by business characteristics, Great Britain, 2016
Dependent variable is management score
(1) (2) (3)
Log(employment) 0.081
***
0.077
***
0.082
***
(0.00) (0.00) (0.00)
Family-owned 0.000 -0.005
(0.01) (0.01)
Family-owned and non-family-
managed
Family-owned and family-managed
Foreign owned 0.083
***
0.078
***
(0.01) (0.01)
Age 0.007
*
(0.00)
Age squared -0.000
***
(0.00)
Industry dummies Yes Yes Yes
Education controls No No No
Location dummies No No No
R-squared 0.238 0.244 0.263
Observations 7841 7810 7810

31. Management practices
Standard errors in parentheses
* p < 0.05, ** p < 0.01, *** p < 0.001
Table 2: Multivariate analysis of management score by business characteristics, Great Britain, 2016
Dependent variable is management score
(1) (2) (3) (4)
Log(employment) 0.081
***
0.077
***
0.082
***
0.064
***
(0.00) (0.00) (0.00) (0.00)
Family-owned 0.000 -0.005 -0.005
(0.01) (0.01) (0.01)
Family-owned and non-family-
managed
Family-owned and family-managed
Foreign owned 0.083
***
0.078
***
0.065
***
(0.01) (0.01) (0.01)
Age 0.007
*
0.006
(0.00) (0.00)
Age squared -0.000
***
-0.000
**
(0.00) (0.00)
Industry dummies Yes Yes Yes Yes
Education controls No No No Yes
Location dummies No No No No
R-squared 0.238 0.244 0.263 0.343
Observations 7841 7810 7810 7115

32. Management practices
Standard errors in parentheses
* p < 0.05, ** p < 0.01, *** p < 0.001
Table 2: Multivariate analysis of management score by business characteristics, Great Britain, 2016
Dependent variable is management score
(1) (2) (3) (4) (5)
Log(employment) 0.081
***
0.077
***
0.082
***
0.064
***
0.064
***
(0.00) (0.00) (0.00) (0.00) (0.00)
Family-owned 0.000 -0.005 -0.005 -0.004
(0.01) (0.01) (0.01) (0.01)
Family-owned and non-family-
managed
Family-owned and family-managed
Foreign owned 0.083
***
0.078
***
0.065
***
0.063
***
(0.01) (0.01) (0.01) (0.01)
Age 0.007
*
0.006 0.007
*
(0.00) (0.00) (0.00)
Age squared -0.000
***
-0.000
**
-0.000
***
(0.00) (0.00) (0.00)
Industry dummies Yes Yes Yes Yes Yes
Education controls No No No Yes Yes
Location dummies No No No No Yes
R-squared 0.238 0.244 0.263 0.343 0.356
Observations 7841 7810 7810 7115 7115

33. Management practices
Standard errors in parentheses
* p < 0.05, ** p < 0.01, *** p < 0.001
Table 2: Multivariate analysis of management score by business characteristics, Great Britain, 2016
Dependent variable is management score
(1) (2) (3) (4) (5) (6)
Log(employment) 0.081
***
0.077
***
0.082
***
0.064
***
0.064
***
0.061
***
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Family-owned 0.000 -0.005 -0.005 -0.004
(0.01) (0.01) (0.01) (0.01)
Family-owned and non-family-
managed
-0.026
(0.02)
Family-owned and family-managed 0.002
(0.01)
Foreign owned 0.083
***
0.078
***
0.065
***
0.063
***
0.065
***
(0.01) (0.01) (0.01) (0.01) (0.01)
Age 0.007
*
0.006 0.007
*
0.004
(0.00) (0.00) (0.00) (0.00)
Age squared -0.000
***
-0.000
**
-0.000
***
-0.000
**
(0.00) (0.00) (0.00) (0.00)
Industry dummies Yes Yes Yes Yes Yes Yes
Education controls No No No Yes Yes Yes
Location dummies No No No No Yes Yes
R-squared 0.238 0.244 0.263 0.343 0.356 0.359
Observations 7841 7810 7810 7115 7115 7107

34. Conditional analysis
Interested in two questions:
1. What determines management practices?
2. How are they related to productivity?
𝑀 = 𝑓 𝑥
𝑦 = 𝑓 𝑥, 𝑀

35. (1)
Log(GVA/worker)
Management score
1.454
***
(0.16)
Log(employment)
Family-owned
Family-owned and non-family-managed
Family-owned and family-managed
Foreign owned
Industry dummies No
Location dummies No
Degree_m dummies No
Degree_nm dumiies No
Age No
Age squared No
R-squared 0.075
Observations 7416
Productivity and management practices
35
Standard errors in parentheses
* p < 0.05, ** p < 0.01, *** p < 0.001

36. (1) (2)
Log(GVA/worker) Log(GVA/worker)
Management score
1.454
***
1.136
***
(0.16) (0.14)
Log(employment)
0.001
(0.02)
Family-owned
Family-owned and non-family-managed
Family-owned and family-managed
Foreign owned
Industry dummies No Yes
Location dummies No No
Degree_m dummies No No
Degree_nm dumiies No No
Age No No
Age squared No No
R-squared 0.075 0.368
Observations 7416 7416
Productivity and management practices
36
Standard errors in parentheses
* p < 0.05, ** p < 0.01, *** p < 0.001

37. (1) (2) (3)
Log(GVA/worker) Log(GVA/worker) Log(GVA/worker)
Management score
1.454
***
1.136
***
1.101
***
(0.16) (0.14) (0.14)
Log(employment)
0.001 -0.023
(0.02) (0.02)
Family-owned
-0.08
(0.06)
Family-owned and non-family-managed
Family-owned and family-managed
Foreign owned
0.366
***
(0.06)
Industry dummies No Yes Yes
Location dummies No No No
Degree_m dummies No No No
Degree_nm dumiies No No No
Age No No No
Age squared No No No
R-squared 0.075 0.368 0.374
Observations 7416 7416 7388
Productivity and management practices
37
Standard errors in parentheses
* p < 0.05, ** p < 0.01, *** p < 0.001

38. (1) (2) (3) (4)
Log(GVA/worker) Log(GVA/worker) Log(GVA/worker) Log(GVA/worker)
Management score
1.454
***
1.136
***
1.101
***
0.961
***
(0.16) (0.14) (0.14) (0.16)
Log(employment)
0.001 -0.023 -0.081
**
(0.02) (0.02) (0.03)
Family-owned
-0.08
(0.06)
Family-owned and non-family-managed
-0.144
(0.08)
Family-owned and family-managed
-0.017
(0.06)
Foreign owned
0.366
***
0.357
***
(0.06) (0.07)
Industry dummies No Yes Yes Yes
Location dummies No No No Yes
Degree_m dummies No No No Yes
Degree_nm dumiies No No No Yes
Age No No No Yes
Age squared No No No Yes
R-squared 0.075 0.368 0.374 0.412
Observations 7416 7416 7388 6723
Productivity and management practices
38
Standard errors in parentheses
* p < 0.05, ** p < 0.01, *** p < 0.001

39. 0.0 0.2 0.4 0.6 0.8 1.0
Population
Management practice score
19% 12%
Management score and productivity
These results were obtained through OLS regression analysis, controlling for management practices, log(employment), family and
non-family ownership, foreign and domestic ownership, managers and non-managers with and without degree equivalent
qualifications, age, age squared, industry and location fixed effects.
Our population of interest covers businesses in production and services industries with employment of at least 10, in Great Britain.
Source: ONS
25th percentile Median 75th percentile
39

40. Key findings & Next steps
• Substantial variation in management scores amongst GB
businesses
• Management scores are highest among:
 Larger than smaller firms
 Not family owned than family owned
 Multinationals than domestic
 Services than production
• Management practice score is strongly correlated with
productivity
40

41. Key findings & Next steps
• Multi-factor productivity
• Longitudinal component
• Regional analysis
41

42. Questions?
42