Driving Productivity Growth: The Importance of Firm-Specific Knowledge Assets

Rebecca Riley National Institute of Economic and Social Research & LLAKES

OECD Global Forum on Productivity UK Workshop, HM Treasury, London

14 October 2016

Disclaimer: This work contains statistical data which is Crown Copyright; it has been made available by the Office for National Statistics (ONS) through the Secure Data Service (SDS) and has been used by permission. Neither the ONS nor the SDS bear any responsibility for the analysis or interpretation of the data reported here. This work uses research datasets which may not exactly reproduce National Statistics aggregates. The financial support of the Economic and Social Research Council (ESRC) is gratefully acknowledged. The work was part of the programme of the Centre for Learning and Life Chances in Knowledge Economies and Societies (LLAKES), an ESRC-funded Research Centre – grant reference ES/J019135/1.

Growth in the knowledge economy

• Sustained increases in the demand and supply of skilled labour – Technology

• New technology - skill complementarity (Goldin & Katz, 1998) • Displacement of routine tasks (Manning & Goos, 2003; Autor, Levy, Murnane, 2003)

– Globalisation • Trade with labour intensive markets (Autor, Dorn, Hanson, 2013)

– Rapid expansion of higher education

• Skills matter for productivity – Labour quality directly influences productivity – As well as via spillovers/knowledge diffusion

• And the output of skilled labour has “investment” properties

– Intangibles seen as the “missing input” in the knowledge economy • Stems from the ICT-growth literature (O’Mahony & van Ark, 2003) • Growing recognition of the importance of management and organisation (Black and Lynch,

2001; Basu et al, 2003; Bloom et al, 2007 ) • R&D literature

How much do intangibles matter?

• Macro studies have looked at intangibles in the national accounting framework (Corrado et al, 2005; Giorgio Marrano et al, 2009; Haskel et al, 2011) – Economic competencies, Innovative property, Computerized information – Treated as intermediates – Need to be capitalised

• Magnitudes – Evidence for the US: Corrado et al (2009) estimate around $800 billion are missing from

US GDP – Evidence for Europe: Taking a relatively broad definition, estimates range from 7-12 per

cent of GDP over the 1990s and early 2000s (Roth and Thum, 2010) – Evidence for the UK:

• Giorgio Marrano et al (2009) find GVA in market sectors is understated to the tune of around 6 per cent in 1970, increasing to 13 per cent by 2004.

• Haskel et al (2011) find investments in intangibles to be as important as tangibles in the 1990s and MORE important from 2000 onwards.

• Dal Borgo et al (2013) analysing input-out tables suggest organisational investment accounts for more than half of UK intangible investment (mostly management & training).

More to learn from looking at firms’ use of intangibles

• Develop new data on firms’ knowledge assets – Based on similar methods to those used in the recent macroeconomic

literature on intangibles

– Providing a bottom-up approach to evaluating potential magnitudes and patterns in intangible investment and capital

– Facilitating new analysis

• Study the role of knowledge assets in driving growth – Within the unifying framework of the macroeconomic intangibles literature

– But at a more disaggregate level

– Within regression analysis frameworks

Measuring firms’ investments in intangibles

• Evaluate firms’ expenditures on intangibles: – Using information on firms’ purchases of intangibles

– And costs of workers undertaking “intangible” tasks

– Evaluate investment share • using common assumptions in the literature

– Capitalise investment flow (PIM) • using depreciation rates in the literature

• Data sources: – Annual Respondents Database

– Annual Survey of Hours and Earnings

Occupations involved in the production of knowledge assets

• Digitised Information

– ICT professionals & managers

• Intellectual Property – Natural & Social Science professionals & managers – Architects, Engineering professionals, Business research professionals – Highly skilled artistic workers, designers

• Organisational Capital (Economic Competencies) – HRM: human resources managers and directors, vocational

and industrial trainers – BRAND: sales, marketing, advertising & public relations managers – MANAGEMENT: chief executive and senior officials, production &

operations department managers

For related , but broader, occupational classifications of occupations involved in the production of intangibles see FP7 INNO DRIVE and Riley and Robinson (2011) Skills and Economic Performance: The Impact of Intangible Assets on UK Productivity Growth, UK Commission for Employment and Skills.

Key assumptions

Intangibles Data description Source Investment Depreciation

share rate

Digitised information

Own account Labour costs of IT occupations ASHE/ARD 0.50 0.33

Purchased Investment in Software ARD 1.00 0.33

Intellectual property (OA) Labour costs of R&D occupations ASHE/ARD 1.00 0.20

Organisational

Brand

Own account Labour costs of sales occupations ASHE/ARD 0.40 0.55

Purchased Purchases of Advertising Services ARD 0.60 0.55

Management (OA) Labour costs of manager occupations ASHE/ARD 0.20 0.40

HRM (OA) Labour costs of HR occupations ASHE/ARD 0.20 0.40

Depreciation rates and investment shares based on assumptions in Corrado, Hulten & Sichel (2005, 2006), Giorgio Marrano, Haskel & Wallis (2009), Görzig, Piekkola & Riley (2011), Corrado, Haskel, Jona-Lasinio & Iommi (2012).

Occupations, qualifications & experience

Potential Experience % with Highest Educational Qualification

Intangible Occupations (years) Higher

Degree Education GCE, A-level Other

Digitised information 19 62% 10% 15% 13%

Intellectual property 21 63% 14% 13% 10%

Organisational

Brand 22 53% 10% 17% 20%

Management 26 35% 12% 22% 31%

Other Occupations 24 26% 10% 24% 40%

Source: Labour Force Survey, Apr-Jun 2012; Authors' calculations

Note: Potential experience=Age-Age left continuous full-time education.

Broad sectors

• High tech manufacturing – chemicals, computers, electrical machinery & communications equipment,

non-electrical machinery, precision instruments, motor vehicles & other transport equipment

• Low (medium) tech manufacturing – petroleum refinery, rubber & plastic products, non-metal mineral products,

non-ferrous metals, fabricated metals, manufacturing nec, recycling

• Knowledge intensive services – Post & telecommunications; computers & related activities; R&D; water & air

transport; renting of machinery & equipment; other business activities; recreational, cultural & sporting activities

• Other services – wholesale & retail trade, hotels & restaurants, land transport, supporting

transport activities, sewage & refuse, activities of membership organisations, other services

Based on Eurostat definitions

Intangible investment by sector (share of GVA, average 2000-2012)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

MF High Tech MF Other SERV KnowledgeIntensive

SERV Other

Tangible

Intangible

Source: ARD and ASHE; NIESR LLAKES research – preliminary results

Intangible investment by sector (change in share of GVA between 2001-2005 and 2006-2010)

-0.03

-0.025

-0.02

-0.015

-0.01

-0.005

0

0.005

0.01

MF High Tech MF Other SERV KnowledgeIntensive

SERV Other

Tangible

Intangible

Source: ARD and ASHE; NIESR LLAKES research – preliminary results

Intangible investment by sector and type (share of GVA, average 2000-2012)

Source: ARD and ASHE; NIESR LLAKES research – preliminary results Note: No account of purchased intellectual property or management here or elsewhere in this presentation.

Manufacturing Services

High Tech Other Knowledge Intensive Other

Digitised Information 0.015 0.008 0.037 0.012

Intellectual Property (OA) 0.065 0.027 0.046 0.010

Brand 0.035 0.038 0.043 0.045

Management (OA) 0.016 0.016 0.017 0.020

All Intangibles 0.130 0.089 0.142 0.088

Production function coefficients (very large firms)

Manufacturing Services

High-tech Other Knowledge intensive Other

Employment 0.625 *** 0.431 *** 0.637 *** 0.795 ***

Physical capital 0.056 0.248 ** 0.022 0.146 ***

Digitised information 0.076 *** -0.032 0.071 ** 0.03

Intellectual property 0.044 * 0.027 -0.025 0.005

Brand -0.018 0.129 ** 0.006 0.061 *

Management 0.073 *** 0.019 0.041 ** -0.025

HRM 0.015 0.048 ** 0.002 0.002

Observations 394 435 1078 2007

Source: Annual Respondents Database and Annual Survey of Hours and Earnings; Machinery & Equipment capital s tocks made available by Richard Harris; NIESR LLAKES research – preliminary results.

Notes : Large firm sample; 1998-2012; manufacturing & business services excl. finance; tangibles include machinery & equipment; f irms with a minimum of 4 observations; GMM system estimation; DPV is log GVA.

Firms, intangible assets and productivity

• Clear role for intangible assets in explaining firms’ productivity performance

• Potentially at least as important as physical capital in determining growth

– particularly in knowledge intensive sectors

• Organisational capital is important in all sectors

– possibly more important in low-skill sectors, depending on asset type

– difficult to disentangle individual components

– and matters for decisions to invest in innovation

• Digitised information more important in the skill-intensive/high-tech sectors

– IT/Skill complementarity

• Intellectual property (own account) mainly important in high-tech manufacturing

• Heterogeneity in links to productivity (across sectors/types of firm)

• Complex linkages