The anatomy of UK labour productivity: lessons from new and existing data sources. Philip Wales Head of Productivity ONS Royal Economic Society Annual Conference 27 March 2018

1. The anatomy of UK labour productivity: lessons from
new and existing data sources
Philip Wales
Head of Productivity
Royal Economic Society Annual Conference
27 March 2018
1

2. Outline
1. Motivation
2. New aggregates from old data
3. New findings with blends of old data
4. New understanding with new data?
2

3. Outline
1. Motivation
2. New aggregates from old data
3. New findings with blends of old data
4. New understanding with new data?
3

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

5. Motivation
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

6. Motivation
6
UK output per hour growth, rolling 10-year compound
average annual growth rate, 1770-2017
-2
-1
0
1
2
3
4
5
1770 1790 1810 1830 1850 1870 1890 1910 1930 1950 1970 1990 2010
Bank of England ONS
%
Source: ONS Productivity Bulletin, January 2018

7. Motivation
• The UK’s recent labour productivity performance has
been strikingly weak…
• …the UK’s ‘productivity gap’ remains stubbornly
wide…
7

8. Motivation
8
Labour productivity (OPW) in the G7: UK=100
Source: ONS International Comparisons of Productivity

9. Motivation
• The UK’s recent labour productivity performance has
been strikingly weak…
• …the UK’s ‘productivity gap’ remains stubbornly
wide…
• …while the ‘gaps’ between businesses are equally
striking…
9

10. Motivation
10
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

11. Outline
1. Motivation
2. New aggregates from old data
3. New findings with blends of old data
4. New understanding with new data?
11

12. New aggregates from old data
• More labour productivity industry granularity…
12

13. New aggregates from old data
13
OPH by industry, Q4 2007=100
G – Wholesale & Retail
45 – W&R – Motor Vehicles
46 – Wholesale excluding MV
47 – Retail excluding MV
80
90
100
110
120
130
140
150
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
45
46
47
G
Source: ONS Labour Productivity

14. New aggregates from old data
• More labour productivity industry granularity…
• …as well as industry by region estimates…
14

15. New aggregates from old data
15
Finance OPH by region, CP, £/hr
10
20
30
40
50
60
70
80
90
100
1997 2001 2005 2009 2013
SC
LO
NI
UK
Source: ONS Labour Productivity

16. New aggregates from old data
16
Finance OPH by region, CP, £/hr
10
15
20
25
30
35
40
45
1997 2001 2005 2009 2013
SC
NW
SE
UK
WM
Manufacturing OPH by region, CP £/hr
10
20
30
40
50
60
70
80
90
100
1997 2001 2005 2009 2013
SC
LO
NI
UK
Source: ONS Labour Productivity

17. New aggregates from old data
• More labour productivity industry granularity…
• …as well as industry by region estimates…
• …to support more detailed analysis
17

18. Outline
1. Motivation
2. New aggregates from old data
3. New findings with blends of old data
4. New understanding with new data?
18

19. New findings with blends of old data
19
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
2007
Firm-level output per worker, constant prices
Source: ‘Who are the laggards?’ Understanding firms in the bottom 10% of the labour productivity distribution

20. New findings with blends of old data
20
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
2007 2009
Firm-level output per worker, constant prices
Source: ‘Who are the laggards?’ Understanding firms in the bottom 10% of the labour productivity distribution

21. New findings with blends of old data
21
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
2007 2009 2011
Firm-level output per worker, constant prices
Source: ‘Who are the laggards?’ Understanding firms in the bottom 10% of the labour productivity distribution

22. New findings with blends of old data
22
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
2007 2009 2011 2013
Firm-level output per worker, constant prices
Source: ‘Who are the laggards?’ Understanding firms in the bottom 10% of the labour productivity distribution

23. New findings with blends of old data
23
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
2007 2009 2011 2013 2015
Firm-level output per worker, constant prices
Source: ‘Who are the laggards?’ Understanding firms in the bottom 10% of the labour productivity distribution

24. New findings with blends of old data
24
Source: ‘Who are the laggards?’ Understanding firms in the bottom 10% of the labour productivity distribution

25. New findings with blends of old data
25
Source: ‘Who are the laggards?’ Understanding firms in the bottom 10% of the labour productivity distribution

26. New findings with blends of old data
26
£, 000 per worker per year
Median
No FDI FDI
2012 25.3 61.6
2013 26.5 53.4
2014 27.1 63.3
2015 27.7 59.3
Foreign Direct Investment and Productivity
Source: FDI and labour productivity, a micro-data perspective: 2012 to 2015

27. New findings with blends of old data
27
£, 000 per worker per year
Median Mean
No FDI FDI No FDI FDI
2012 25.3 61.6 44.3 123.0
2013 26.5 53.4 47.5 156.8
2014 27.1 63.3 48.6 153.4
2015 27.7 59.3 48.3 172.7
Foreign Direct Investment and Productivity
Source: FDI and labour productivity, a micro-data perspective: 2012 to 2015

28. New findings with blends of old data
28
£, 000 per worker per year
Median Mean Of which mean of:
No FDI FDI No FDI FDI Inward FDI Outward FDI
2012 25.3 61.6 44.3 123.0 125.5 119.2
2013 26.5 53.4 47.5 156.8 159.2 161.7
2014 27.1 63.3 48.6 153.4 165.7 109.0
2015 27.7 59.3 48.3 172.7 185.6 140.3
Foreign Direct Investment and Productivity
Source: FDI and labour productivity, a micro-data perspective: 2012 to 2015

29. What have we done (3)?
29

30. Outline
1. Motivation
2. New aggregates from old data
3. New findings with blends of old data
4. New understanding with new data?
30

31. New understanding with new data?
• Management practices are an area of growing
interest and attention in the academic literature as a
means of explaining the ‘long tail’ of British
businesses
• ESCoE and ONS have developed a survey of
management, and publicised the first results of this
survey at RES yesterday
31

32. 32
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
10-49
50-99
100-249
250+
Population
Management Practice Score
EmploymentSizeBand
Population
distribution
80%
100%
11%
5%
4%
Key: Line : 10th and 90th percentiles. Light blue box: Difference between 50th and 25th percentiles. Dark blue box: Diff between 75th and 50th percentiles.
Dots: 5th and 95th percentiles
New understanding with new data?

33. New understanding with new data?
33
33
0.0 0.2 0.4 0.6 0.8 1.0
Non-Manufacturing Production
Manufacturing
Construction
Services: Distribution, hotels &
restaurants
Services: Transport, storage, &
communication
Services: Business
Services: Other
Real Estate & Finance and
Insurance
Population
Management Practice Score
Industry
Key: Line : 10th and 90th percentiles. Light blue box: Difference between 50th and 25th percentiles. Dark blue box: Diff between 75th and 50th percentiles.
Dots: 5th and 95th percentiles
1%
100%
30%
9%
7%
Population
distribution
12%
20%
19%
2%

34. New understanding with new data?
• In the current policy context, there is real interest in
trade and in understanding the impact that it will have
on businesses
• ONS have arranged access to transaction level trade
in goods data from HMRC, for both statistical
production and for analytical purposes.
34

35. New understanding with new data?
35
IDBR
HMRC transaction level
dataset
ABS, MBS

36. New understanding with new data?
36
IDBR
HMRC transaction level
dataset

37. New understanding with new data?
37
IDBR
ABS, MBS

38. Outline
1. Motivation
2. New aggregates from old data
3. New findings with blends of old data
4. New understanding with new data?
38

39. Questions
39