A Regional Analysis of Productivity in Business Services: Implications for the UK Knowledge Economy

Joanne Roberts and Andrew Hunt

Background and Purpose of the paper• Exploratory in nature

• Reporting findings of an initial analysis

• Investigates difference in productivity levels in the UK business services sector by region and sub-sector.

• Reviews GVA data and GVA per head

• Employs the econometric technique of stochastic production functions to examine efficiency in selected business service sectors.

• Identifies directions for further development of the research

• Broad aim to contribute to a deeper appreciation of UK business services

• In so doing, to offer insights into an important component of national and regional knowledge economies.

Table 1. UK Standard Industrial Classification of Economic Activities 2003, Section K: real estate, renting and business activities

• Division Group Description• 70 Real estate activities•• 71 Renting of machinery and equipment without operator and of personal and household

goods•• 72 Computer and related activities• 72.1 Hardware consultancy• 72.2 Software consultancy and supply• 72.3 Data processing• 72.4 Database activities• 72.5 Maintenance and repair of office, accounting and computing machinery• 72.6 Other computer related activities•• 73 Research and development• 73.1 Research and experimental development on natural sciences and engineering• 73.2 Research and experimental development on social sciences and humanities•• 74 Other business activities• 74.1 Legal, accounting, book-keeping and auditing activities; tax consultancy; market research and

public opinion polling; business and management consultancy; holdings• 74.2 Architectural and engineering activities and related technical consultancy• 74.3 Technical testing and analysis• 74.4 Advertising• 74.5 Labour recruitment and provision of personnel• 74.6 Investigation and security activities• 74.7 Industrial cleaning• 74.8 Miscellaneous business activities not elsewhere classified

Source: Extract from UK SIC 2003, available from the Office of National Statistics,

http://www.statistics.gov.uk/methods_quality/sic/contents.asp (assessed 15th July 2008).

Significance of Business Services• Engage in the creation, dissemination and application of

knowledge both within and between firms at the level of the region, the nation and internationally (Miles et al., 1995; Antonelli, 1999; Andersen et al., 2000).

• Contribute to the competitiveness of enterprises generally - an important factor driving long-term growth (OECD, 1999; CEC, 1998, 2001).

• Among the EU 15 employment in the sector has grown at a rate of 4.4 per cent per annum between 1979 and 2003 (Kox and Rubalcaba, 2007 p. 6 & 7)

• Total employment level of over 19 million or 11.4 per cent of total EU 15 employment by 2003 (ibid)

• Over the same period value added grew by 4.2 per cent per annum amounting to 11.2 per cent of total value added in the EU 15 in 2003 (ibid)

BS Contribute to:

• Client performance (O’Farrell et al., 1995; Dawson, 2000)

• Economic performance across the economy (Tomlinson, 2000; Antonelli, 1999)

• Regional development (Marshall et al., 1988; Perry, 1991; Kebble et al., 1991)

• Innovation (Howells, 2006; Metcalfe and Miles, 2000; Wood, 2002)

Productivity in Services and BS• Traditionally associated with low levels of

productivity because of their labour intensive nature (Baumol, 1967; Petit, 1986)

• Growing interest in understanding productivity in the service sector (Wolfl, 2003; Gronroos and Ojasalo, 2004; OECD, 2005; Crespi, Criscuolo, Haskel and Hawkes, 2006; Griffith, Harrison, Haskel and Sako, 2003; inter alia.)

• Productivity levels vary across service sub-sectors. • Studies of the business service sector highlight

variability in the levels of productivity by sub-sector and location (Rubalcaba-Bermejo, 1999; Kox and Rubalcaba, 2007)

• Measuring productivity in business services

Regional Productivity Levels in BS

• To explore productivity we begin by looking at Gross Value Added (GVA) by sector and region

• Productivity can be measured by GVA per head

• Such data gives an indication of levels of productivity

• What factors account for the variations in levels of productivity?

• To address this question we turn to an examination of efficiency levels

SIC London

South East

North West

East West Midlands

East Midlands

Scotland

South West

Yorkshire and The Humber

North East

Wales Grand Total

Grand Total £’m

721 : Hardware consultancy 19% 24% 8% 11% 7% 10% 6% 4% 7% 3% 1% 100% 745

722 : Software consultancy etc

25% 32% 7% 9% 6% 5% 4% 5% 4% 1% 1% 100% 16260

723 : Data processing 19% 27% 12% 7% 11% 9% 3% 4% 3% 4% 1% 100% 2743

724 : Data base activities 47% 20% 7% 6% 2% 6% 2% 5% 2% 2% 1% 100% 508

725 : Maintenance and repair of office, & computing machinery

18% 22% 7% 9% 4% 8% 13% 7% 6% 3% 2% 100% 1192

726 : Other computer activities

28% 25% 11% 8% 4% 6% 5% 7% 4% 1% 2% 100% 4902

731 : R & D on natural sciences and engineering

14% 24% 6% 12% 7% 12% 5% 8% 5% 4% 1% 100% 3056

732 : R & D on social sciences and humanities

37% 26% 4% 5% 2% 9% 0% 12%

2% 1% 2% 100% 130

741 : Legal, accounting, book-keeping, auditing activities; etc

47% 13% 7% 5% 5% 5% 5% 5% 5% 2% 2% 100% 38975

742 : Architectural and engineering activities & related

27% 18% 9% 7% 6% 5% 11% 6% 5% 3% 2% 100% 13345

743 : Technical testing & analysis

11% 30% 11% 8% 10% 6% 11% 2% 4% 5% 2% 100% 1239

744 : Advertising 58% 14% 8% 3% 4% 3% 3% 4% 3% 1% 0% 100% 4766

745 : Labour recruitment and provision of personnel

34% 16% 10% 7% 7% 6% 6% 6% 5% 2% 2% 100% 15882

746 : Investigation and security activities

30% 13% 11% 7% 7% 7% 7% 6% 7% 4% 2% 100% 3502

748 : Miscellaneous business activities not elsewhere classified

40% 16% 8% 6% 5% 6% 4% 5% 5% 2% 2% 100% 16419

Grand Total 36% 18% 8% 7% 6% 6% 5% 5% 5% 2% 2% 100% 123,664

Regions Share of GB total GVA 17% 16% 10% 10% 8% 7% 8% 8% 8% 3% 4% 100% 898,446

Locations of regional sectoral GVA, proportions averaged over 2001-3

SIC 724 : Data base

activities

731 : R & D on natural

sciences and engineering

741 : Legal, accounting,

book-keeping, auditing

activities; etc

744 : Advertising

Grand Total Regions Share of GB total GVA

London 47% 14% 47% 58% 36% 17%South East 20% 24% 13% 14% 18% 16%North West 7% 6% 7% 8% 8% 10%East 6% 12% 5% 3% 7% 10%West Midlands

2% 7% 5% 4% 6% 8%

East Midlands

6% 12% 5% 3% 6% 7%

Scotland 2% 5% 5% 3% 5% 8%South West 5% 8% 5% 4% 5% 8%Yorkshire and The Humber

2% 5% 5% 3% 5% 8%

North East 2% 4% 2% 1% 2% 3%Wales 1% 1% 2% 0% 2% 4%Grand Total 100% 100% 100% 100% 100% 100%Grand Total £’m

508 3056 38975 4766 123,664 898,446

Locations of regional and selected sectoral GVA, proportions averaged over 2001-3

SIC London South East

North West

East West Midlands

East Midlands

Scotland

South West

Yshire & Humber

North East

Wales Grand Total

721 : Hardware consultancy

50,000 41,000 38,000

39,000 33,000 32,000 41,000

29,000

40,000 31,000

28,000

37,000

722 : Software consultancy etc

60,000 57,000 49,000

55,000 45,000 39,000 44,000

38,000

46,000 46,000

35,000

47,000

723 : Data processing 72,000 71,000 64,000

55,000 69,000 60,000 52,000

53,000

42,000 56,000

43,000

58,000

724 : Data base activities 66,000 42,000 29,000

36,000 28,000 29,000 36,000

42,000

34,000 21,000

28,000

36,000

725 : Maintenance and repair of office, & computing machinery

63,000 55,000 48,000

44,000 40,000 41,000 62,000

48,000

44,000 45,000

38,000

48,000

726 : Other computer activities

50,000 49,000 40,000

39,000 32,000 35,000 43,000

34,000

36,000 25,000

28,000

38,000

731 : R & D on natural sciences and engineering

34,000 29,000 43,000

45,000 40,000 35,000 25,000

39,000

41,000 67,000

31,000

40,000

732 : R & D on social sciences and humanities

39,000 35,000 35,000

33,000 28,000 29,000 - 28,000

32,000 31,000

16,000

31,000

741 : Legal, accounting, book-keeping, auditing activities; etc

69,000 39,000 33,000

36,000 33,000 33,000 33,000

33,000

37,000 34,000

28,000

37,000

742 : Architectural and engineering activities & related

63,000 44,000 34,000

34,000 35,000 30,000 42,000

35,000

35,000 37,000

30,000

38,000

743 : Technical testing & analysis

47,000 70,000 34,000

34,000 44,000 37,000 43,000

28,000

32,000 37,000

27,000

39,000

744 : Advertising 73,000 40,000 46,000

30,000 33,000 29,000 35,000

34,000

34,000 27,000

24,000

37,000

745 : Labour recruitment and provision of personnel

35,000 22,000 21,000

20,000 18,000 17,000 21,000

19,000

19,000 19,000

14,000

20,000

746 : Investigation and security activities

27,000 24,000 20,000

24,000 23,000 22,000 19,000

35,000

22,000 22,000

17,000

23,000

748 : Miscellaneous business activities not elsewhere classified

60,000 35,000 31,000

33,000 30,000 31,000 31,000

30,000

29,000 33,000

27,000

34,000

GrandTotal 54,000 44,000 38,000

37,000 35,000 33,000 38,000

35,000

35,000 36,000

27,000

37,000

GVA per head average over 2001-3

SIC 724 : Data base

activities

731 : R & D on natural

sciences and engineering

732 : R & D on social

sciences and humanities

741 : Legal, accounting,

book-keeping, auditing

activities; etc

744 : Advertising

GrandTotal

London 66,000 34,000 39,000 69,000 73,000 54,000

South East 42,000 29,000 35,000 39,000 40,000 44,000

North West 29,000 43,000 35,000 33,000 46,000 38,000East 36,000 45,000 33,000 36,000 30,000 37,000

West Midlands

28,000 40,000 28,000 33,000 33,000 35,000

East Midlands

29,000 35,000 29,000 33,000 29,000 33,000

Scotland 36,000 25,000 - 33,000 35,000 38,000

South West 42,000 39,000 28,000 33,000 34,000 35,000

Yshire & Humber

34,000 41,000 32,000 37,000 34,000 35,000

North East 21,000 67,000 31,000 34,000 27,000 36,000

Wales 28,000 31,000 16,000 28,000 24,000 27,000

Grand Total 36,000 40,000 31,000 37,000 37,000 37,000

GVA per head selected averages over 2001-3

Stochastic Production Frontiers

Input 1

Input 2

f(xi,β)

Standard frontier

Stochasticfrontier

yi≤f(xi,β)

Estimated function

v is not a measure of efficiency but rather an approximation of inefficiency

A trans-log production function was estimated, in natural log form...

Results - Sector effects 

COLSHalf normal

Exponential Truncated normal

ONE 2.63 2.75 2.70 2.70S721 0.49 0.51 0.54 0.54S722 0.32 0.33 0.34 0.34S723 0.87 0.88 0.88 0.88S724 0.54 0.58 0.64 0.64S725 0.59 0.61 0.62 0.62S726 0.39 0.41 0.44 0.44S731 0.21 0.22 0.25 0.25S732 0.45 0.48 0.52 0.52S742 0.10 0.11 0.12 0.12S743 0.45 0.47 0.49 0.49S744 0.47 0.48 0.50 0.50S745 -0.38 -0.38 -0.41 -0.41S746 -0.23 -0.23 -0.25 -0.25S748 0.03 0.04 0.04 0.04

Results – Labour effects  COLS Half

normalExponential

Truncated normal

ln(w p) -0.54 -0.53 -0.54 -0.54ln(ft e) 1.34 1.35 1.37 1.37ln(pt e) 0.03 0.01 -0.03 -0.02ln (wp * wp)

-0.10 -0.10 -0.09 -0.09

ln(ft e * ft e)

-0.09 -0.10 -0.10 -0.10

ln(pt e * pt e)

-0.02 -0.03 -0.05 -0.05

ln (wp * ft e)

0.21 0.20 0.18 0.18

ln (wp * pt e)

-0.01 0.00 0.01 0.01

ln (ft e * pt e)

0.03 0.04 0.07 0.07

Results – Error terms etc  COLS Half

normalExponential

Truncated normal

TIME 0.09 0.09 0.09 0.09Lambda 1.04 15.13Sigma 0.23 2.24Theta 9.00

Sigmav 0.15

Mu -44.62

R2 0.99

LnL 117.83 125.38 125.30

Observations

449.00 449.00 449.00 449.00

Efficiency  Mean Std.Dev. Minimu

mMaximum

EFFTRU 0.90 0.07 0.44 0.98EFFEXP 0.90 0.07 0.44 0.98EFFHAL 0.88 0.05 0.61 0.97

EFFTRU

1.79

3.59

5.38

7.18

8.97

.00.20 .40 .60 .80 1.00.00

Kernel density estimate for EFFTRU

Den

sit

y

Truncated Normal Efficiency Kernel

The efficiency equationVariable CoefficientONE ***0.896HIGHSKIL 0.0246GVAUNIT ***3.77e-005S723 ***-0.0405

S724 ***-0.0527

S725 **-0.0256

S731 ***-0.0675

S732 **-0.0325

R7 *0.0194PERWP **-0.0216

R2 9.56E-02N 449

Key Points• Consistent conclusions across specifications• The broad business service sector is estimated as just under

90% efficient• The maximum observed efficiency is 97-8%• Certain sectors appear to be less efficient, namely those

among computer and related activity and research and development

• Increases in the proportion of working proprietors was associated with a decline in efficiency – possibly correlated to sectors

• Significant ‘London effect’ - higher efficiency– Differences in skill level does not appear to fully account

for the gap between London and other regions • Further work needed to unpick relationship between skill

levels, sector and efficiency

Policy Implication

• Scope to improve BS efficiency levels• The role of working proprietors• Skills development is important, but not

sufficient• Support further research into the business

service sector at both a national and regional level

Next Steps

• Further exploration of interrelationships between working proprietors, sectors, skill levels

• Adding in 2004-5 data• Adding in variables relating to the condition of

regional economies and sector specific variables (output growth?)

• Incorporating additional factors, e.g.:• Innovation• International trade