• No results found

R&D, ICT and Productivity

N/A
N/A
Protected

Academic year: 2021

Share "R&D, ICT and Productivity"

Copied!
42
0
0

Loading.... (view fulltext now)

Full text

(1)

R&D, ICT and Productivity

Neil Lee

Philippe Schneider

Ian Brinkley

(2)

R&D, ICT and Productivity



Contents

1. Introduction to the project: R&D, ICT and productivity

3

. R&D, ICT and their role in the UK economy

4

3. ICT: Why it matters

8

4. Variations in the impact of ICT

1

5. Explanations – Measurement, environment or organisation? 15

6. R&D and productivity

3

7. UK R&D performance

5

8. Government policy and the barriers to R&D

34

Conclusion: A jigsaw, not a puzzle

39

(3)

1. Introduction to the project: R&D, ICT and productivity

This document is the first paper in Programme 5 of The Work Foundation’s Knowledge Economy Programme, a three-year research project launched in 006. Programme 5 looks at the role of ICT and R&D on productivity in the UK.

This piece is intended to establish future research questions around this topic, and set the scene for further research in this area. It will attempt to answer the following questions:

How does the UK perform in terms of R&D, ICT and productivity? What are the links between these factors? What are the measurement issues and how do they change the situation?

What are the key constraints and determinants of investment in R&D and ICT in the UK compared with other OECD economies? Do these explain why parts of Europe (and the UK) have not seen a similar related impact on productivity growth as in the US?

What are the implications of the above for government and for business? More information about the knowledge economy programme and accompanying papers can be found at:

http://www.theworkfoundation.com/futureofwork/research/ knowleconomyworkprogramme.aspx

1.

.

(4)

R&D, ICT and Productivity

4

. R&D, ICT and their role in the UK economy

The UK has a stable economy, a reasonable tax base and good product market regulation. The country has experienced over a decade of growth and weathered difficult times for the international economy. With this in mind, it would not be an irrational guess to suggest that the UK would be fairly productive.

And it is, but not as productive as comparable nations. In 004, output per worker was 7% higher in the US than the UK and 11% higher in France, while GDP per hour worked is 16% higher in the US and 9% higher in France1. While this relatively poor productivity performance should not be overstated (it is both reasonable on a global scale and improving), it remains a challenge for policymakers and a cause of concern for the country.

It is no surprise, then, that there has been considerable interest in this issue. Some notable work in this area has been done by the OECD, with Chief Economist Philipe Cotis setting out the idea of the ‘UK Productivity Paradox’. He defines it as the question: ‘Why on earth isn’t UK productivity catching-up faster, given economic theory, good UK policies and comparatively low productivity levels to start with?’ 

The government has also engaged with this debate, with the Treasury paying particular attention to the problem, and publishing a series of reports setting out ideas for addressing it. Under the banner ‘Productivity in the UK’, these reports have attempted to analyse UK productivity at a variety of spatial scales, and produced a shopping list of ‘drivers’ of productivity: investment, innovation, skills, enterprise and competition.

But the drivers of productivity are broad and, to some extent, contested. Within each of the Treasury’s drivers lies a subset of other important influences on innovation. This paper looks at two of these: Research and Development (R&D) and Information and Communications Technology (ICT).

These two drivers have become increasingly prominent in public debate. This is, in part, due to the shift to the ‘knowledge economy’. This concept is, as has been pointed out, both vital to our future success and fuzzily, imprecisely defined3.

1 Office of National Statistics (005) Productivity Statistics: First Release, www.statistics.gov.uk  Jean-Philipe Cotis (006) ‘Economic Growth and Productivity’, Speech to the Annual Conference of the

Government Economic Service, Nottingham, 13 and 14 July 006

(5)

R&D, ICT and their role in the UK Economy

It can be defined broadly as ‘what you get when organisations bring together powerful computers and well-educated minds to create wealth’.4 The knowledge economy has meant a shift to new organisational forms, the introduction of new methods of economic competition and the development of new theories to explain these. A combination of technological improvement and this changing view of the way the economy works has highlighted the importance of both drivers – R&D and ICT – in the UK economy.

The argument proceeds as follows. Firstly, the paper is put in context through a brief discussion of the UK productivity problem and the role of R&D and ICT in addressing this. Second, the evidence on ICT is discussed, looking at how ICT has been important for the US economy and why the UK has not had comparable payoffs. Next, the paper turns to R&D, looking at the UK’s relatively weak position, the explanations for this and the policies which might address this. The paper concludes by setting out further questions for study.

The UK productivity problem has been well documented. The average worker in the US produces around 7% more than the average UK worker, and the average French worker 11% more. However, the UK’s standing relative to these nations has improved since 199.

These figures mask differences in the labour market, and adjusting for these differences changes the international comparisons. As Americans work longer hours, their GDP per hour worked is slightly lower. In 004, GDP per hour worked in the UK was around 9% higher in France, and around 16% higher in the US5. And while the UK has caught up slightly (with rates converging overall), between 00-004 the US again increased its lead.

Of course, the measurement of productivity and growth is difficult. Dirk Pilat6 has looked at several areas where measurement is difficult. Of particular salience for this piece is output measurement, where there have been claims that the output differential between the US and the EU is explained largely by measurement issues. However, Pilat dismisses this suggestion – the use of different

4 Ian Brinkley (006) ibid

5 DTI (006) UK Productivity and Competitiveness Indicators 006, DTI Economics Paper No. 17 6 Dirk Pilat (00) International Comparisons of Productivity – key findings and measurement issues,

OECD

The UK productivity problem

(6)

R&D, ICT and Productivity

6

R&D, ICT and their role in the UK Economy

measurement techniques ‘balances out at the aggregate level’. There may however be measurement effects regarding individual components of investment, such as ICT. An in-depth discussion of these issues is beyond the scope of this paper.

In short, despite some ambiguity it is clear that UK productivity is not as good as it might be. The following section outlines two factors which might explain why. Although technological change has long been a part of models of economic growth, the recent focus on R&D has in large part been derived from the prominence of endogenous growth theory in modern policy7. Previous neoclassical models of economic growth took technological changes as exogenous or external to the model: given, rather than produced. Based on the work of Romer in the 1980s, endogenous growth theory models technological change and innovation as internal to the model, or endogenous. This means it is possible for growth in the stock of knowledge to impact on technological change and for the economy to grow. In simple terms, this involves pushing out the technological frontier – the boundary that represents the limit of what can be produced with current resources (including knowledge). Investment in R&D may push this frontier further out, as new methods of production and new products are created. As more can be produced with a given set of resources, productivity increases and the economy grows. This conception of growth places the emphasis on innovation through research and technology.

ICT is one such technology, and one that has become ubiquitous and important across the developed world. Despite breathless predictions of its power to transform the economy, it has not ‘changed everything’. But in certain sectors ICT has had a profound effect. Its strength lies not just in being a sector subject to rapid technological change (and with high rates of R&D), but also in that it can increase productivity in other sectors of the economy.

And R&D is also, as will be shown later, a conditioning factor in the extent of innovation in the ICT sector. This is reflected in one of the key themes of this paper – the complexity of the interactions between these (and other) drivers of

7 David Coats (005) ‘What is the Knowledge Economy’, Ideopolis Working Paper 1, London: The Work

Foundation

R&D, ICT and the economy

(7)

R&D, ICT and their role in the UK Economy

productivity which points to a requirement of a more in-depth understanding of change.

Given the productivity problem, it may come as little surprise that the UK is falling short on both R&D and ICT investment. UK R&D intensity (R&D as a percentage of GDP) is 1.9%, considerably below that of comparable nations, such as Germany (.5%) and the US (.8%). This problem, as is shown later, is peculiar given the relative quality of the UK university research system, and has been addressed by recent policy initiatives such as the tax credit.

ICT presents a similar problem. There have been suggestions that the rise in US productivity has derived from growth in only six sectors – and these sectors are unified by the role of ICT in increasing their productivity and so leading to growth. While the UK has invested in ICT: in 003, 3% of GDP was spent on ICT investment, compared to under % in Germany and France8. This has not been matched by the benefits that have been experienced by the US.

This suggests there are further barriers to the UK exploiting the productivity gains from ICT. These might be barriers to successful exploitation (for example, and as esoteric as this may at first appear, planning regulations) there may also be complementary investments which are missing (such as management skills), or it may simply be a matter of time before the economy catches up.

R&D and ICT constitute important factors in the shift to the knowledge economy. The ‘Knowledge Economy’ refers to a series of technological and economic changes in the economy. Ian Brinkley9 has identified a series of characteristics behind this shift, two of which are particularly relevant here:

The knowledge economy has a high and growing intensity of ICT usage by well educated knowledge workers The knowledge economy consists of innovating organisations using new technologies to introduce process, organisational and presentational innovation

These two characteristics demonstrate the importance of the subjects examined in this paper.

8 OECD (005) OECD Science, Technology and Industry Scoreboard 2005 – Briefing Note for the United

Kingdom, Paris: OECD

9 Ian Brinkley (006) ibid, p. 3

R&D, ICT and the knowledge economy programme

(8)

R&D, ICT and Productivity

8

3. ICT: Why it matters

It is now a common argument that ICT has led to increases in productivity, and even that it was responsible for the US productivity boom. But it might be more appropriate to say that – rather than widespread productivity gains across the level of the whole economy – ICT has led to massive increases in productivity in certain sectors and certain places. There is plentiful evidence on this. So while it has become common to cite Carr10 as arguing that – because of its replicability – the productivity gains from ICT as a competitive factor are only short-term, there remain significant differences by sector and nation in the extent to which ICT has been successfully exploited. This remains a key challenge for policymakers. The benefits of ICT are fairly clear. In short, we can identify four related benefits, one through its role as a sector, one through allowing new sectors and two through improvements to overall Total Factor Productivity. These are:

As a knowledge-based sector. The ICT producing sector has been

subject to some of the most extreme improvements in productivity of any sector, with processor prices falling alongside massive increases in processor power. It is a sector with a high level of investment in research and development and is highly innovative and subject to rapid technological change. In short, ICT is important as a sector in itself.

In allowing new industries. ICT uptake in the economy allows new

forms of industry, which were previously not considered feasible or even technologically possible. While we cannot expect an immediate improvement in productivity, the new industry may perform a function more efficiently than the old one. An example of this is eBay, which is a new electronic marketplace that replaces, and is more efficient than, older forms of trading. This effect is significant, but was overstated by some commentators during the dot-com boom.

As capital. ICT is in itself a capital good, and investment in ICT will

increase labour productivity through the effect of people using computers.

10 See Nicholas G. Carr (003) ‘IT Doesn’t Matter’, Harvard Business Review, 3, Although this is not what

he necessarily meant, see Alan Hughes and Michael S. Scott Morton (005) ‘ICT and Productivity Growth – the Paradox Resolved?’, Centre for Business Research, University of Cambridge, Working Paper No. 316

1.

.

(9)

ICT: Why it matters

ICT and Total Factor Productivity (TFP). Related to the above, the

exploitation of ICT technology can help firms to be more productive, raising overall TFP. In this case, the use of ICT can allow a given input to produce a greater output than without ICT.

These four processes together account for some of the significant improvements in productivity in the UK. There are a wealth of studies which attempt to dissect US productivity growth over the latter half of the 1990s, within which these four factors are evident.

Much of the interest in ICT has been spurred by studies of the US ‘Productivity Miracle’ – the period of roughly a decade after 1995 that saw exceptional productivity growth in the US economy. This US productivity picture has largely been defined in contrast to the less encouraging picture in Europe. Between 1995-003 the annual growth rate in output per hour was around double in America compared to Europe11. A series of studies have dissected this, normally using standard growth accounting techniques. They attempt to account for the differential impact of investment and capital in US productivity growth.

Often, these studies attempt to isolate the impact of ICT in sectors in a particular country. In a famous early example Robert Gordon1 found that the entire US productivity boom was concentrated in ICT producing sectors. This paper was one of the early studies of the new economy, and Gordon was, at that time, a notable sceptic. (He has since, however, changed his position13.)

Oliner and Sichel have produced two such pieces. In the first14, they use data for three periods (1974-90, 1991-1995 and 1996-000) to assess:

The contribution to productivity growth caused by the use of

information technology (for example, computer hardware, software and communications equipment) an industry which, they note, ‘surged in the second half of the 1990s’,

11 Robert J. Gordon (004) ‘Why was Europe Left at the Station When America’s Productivity

Locomotive Departed?’, NBER Working Paper W10661

1 Robert J. Gordon (1999) ‘Has the ‘New Economy’ Rendered the Productivity Slowdown Obsolete?’

Available from www.northwestern.edu

13 See Robert J. Gordon (004) ‘Five Puzzles in the Behaviour of Productivity, Investment and

Innovation’ NBER Working Paper W10660

14 Stephen D. Oliner and Daniel E. Sichel (000) ‘The Resurgence of Growth in the Late 1990’s: Is

Information Technology the Story’, Journal of Economic Perspectives, 14 (4), 3- 4.

a.

The US ‘productivity miracle’

(10)

R&D, ICT and Productivity

10

ICT: Why it matters

and;

The impact of productivity growth caused by technological change in industries that produce computers.

They find that ICT has led to a large proportion of the productivity growth, with the striking conclusion that: ‘All in all, we estimate the use of information technology and the production of computers accounted for about two-thirds of the 1 percentage point step-up in productivity growth between the first and second halves of the decade.’ This conclusion, albeit varying in extent, appears to be common across a number of different studies.

A more pertinent question, they suggest, is to what extent this growth is sustainable and whether it can be expected to persist? They answer these questions in a second paper15, written in 00: after the collapse of the IT sector had raised questions about earlier empirical results and put the sustainability of the growth in question. They found that productivity growth was still strong, with the data showing a substantial pickup in labour productivity. Both the use of information technology and gains in efficiency in the IT production sector themselves were central factors in the resurgence of productivity growth.

But through which processes did this happen? As part of their growth accounting model, they divide non-farm produce into five sectors. Three of these – computer hardware, software and communications equipment – produce final IT goods. A non-IT sector produces all other final goods and services. A fifth sector – albeit relatively small – produces semi conductors for export or as intermediary inputs in the IT sectors. They find that ‘rapid capital deepening related to information technology capital – the greater use of information technology – accounted for about three-fifths of this pickup [since 1995-00]’16, a slightly smaller but still significant amount.

A similar study is produced by Jorgenson et al17, who look at two periods – 1995-000 and from 1995-000. They find that for the first period the surge in productivity

15 Stephen D. Oliner and Daniel E. Sichel (003) ‘Information Technology and Productivity: Where are

we now and where are we going?’, FRBA Economic Review, Third Quarter, 15-44

16 Oliner and Sichel (003) ibid, 1

17 Dale Jorgenson, Ho S. Mun and Kevin Stiroh (006) ‘The Sources of the Second Surge of US

Productivity and Implications for the Future’, Harvard University Mimeo b.

(11)

ICT: Why it matters

was driven by IT in two ways. IT improved efficiency in other sectors (TFP growth) and investment in ICT (Capital deepening)

Their results present a picture of productivity growth concentrated in relatively few sectors. Accounting for the production of information technology, they show that there is a considerable rise in the contribution to multifactor productivity accounted for by semiconductor producers in the period after 1995. This is due in large part to falls in semiconductor prices. The other IT producing sectors were only slightly more productive in the period 1995-0 than they were in the period 1990-95.

This result is particularly salient for what it reveals about the rest of the sector – it implies that production of semiconductors was responsible for most growth across the industry, while there were only relatively modest gains in the other sectors of computer manufacturing. After 1995, use of ICT and efficiency gains from IT producing sectors accounted for more than the 0.89% increase in labour productivity growth. This, of course, points to the importance of future productivity gains in the semi-conductor industry for the US economy, and highlights a problem for countries which lack such an industry.

(12)

R&D, ICT and Productivity

1

4. Variations in the impact of ICT

While ICT is clearly important, its impact varies significantly. This suggests there is a need for a more detailed breakdown of the situation. Two facets of this are variation by sector and by nation.

Kevin Stiroh has produced one of the more memorable sectoral studies18. Rather than using standard growth accounting methodology, as is common across many papers, he uses disaggregated data at the level of the industry.

He divides the economy into three sectors: those industries involved in the production of ICT, those which make significant use of ICT (such as retail and finance) and the other sectors of the economy. Those first two categories – those that produce and use ICT – are found to be responsible for all the increase in US productivity. This means it is not limited to ICT producing sectors, an interesting contrast when compared to the earlier study, although the productivity increases remain reliant on ICT. Of that part of the productivity growth which can be attributed to particular industries, it is possible to attribute it all to ICT using and producing ones.

Many of the sectoral studies highlight the role of retailing and wholesaling19. These two sectors are, by various counts, responsible for a considerable portion of the US productivity growth of the 1990s. This phenomenon has been described as the ‘Wal-Mart Effect’, where the scale and efficiency of a single retailer has had a significant impact at the level of the entire economy. They argue that the two sectors here - retailing and wholesaling - were: ‘responsible for the bulk of the widening of the productivity growth gap between the USA and Europe’ over the period. The improvements in warehousing, bar-coding and electronic interchange were important, but cannot explain why the productivity gains of these were only felt in America. And furthermore, given the competitive nature of the supermarket industry, is there any reason to believe that, for example, Tesco’s, is anything less than a highly productive organisation?

They draw two important conclusions from this analysis. The first, with implications for the UK, is that there was a considerable time lag between the investment in ICT and the growth of labour productivity. This raises the optimistic

18 Kevin J. Stiroh (00) ‘Information Technology and the U.S. Productivity Revival: What do the industry

data say?’ American Economic Review, 9 (5), 1559-1576

19 Hughes and Scott Morton (005) ibid

The picture by sectors

(13)

Variations in the Impact of ICT

idea that the UK may soon see productivity growth from investments made in the past. The second lesson is the importance of the users – they must be in a position to positively exploit the benefits of technology, and this is dependent on a host of factors, including culture and skills.

At a macro level, cross-country perspectives of growth may reveal both the impact of ICT and the conditioning factors which allow its exploitation. The Economist Intelligence Unit0 model the impact of ICT on growth using a cross-section growth model for 60 countries for the period 1995-00. They find that beyond a certain level of development there is a positive relationship between ICT investment and growth. ICT is found to be the ‘main factor’ behind the differences in productivity between Europe and the US. But this varies by country, with the estimate for Italy, France and Germany accounting for 0.4 of the 0.5% difference in GDP per capita growth rates across the period. They also find evidence of a time lag between investment in ICT and resulting productivity benefits.

But more importantly, this study moves beyond quantifying the role of ICT and begins to look at the reasons why ICT is responsible for productivity growth – the enablers are complementary investments, which may allow growth. Clearly, some of these may be intangible, but the EIU presents some interesting conclusions. These include:

The business environment – Those countries which score high on

the EIU’s business environment model (which includes factors for labour, product and financial markets) are more effective at gaining the benefits of ICT.

Education – As might be expected, higher levels of education within

the economy are associated with a more effective uptake of ICT. To test these in further detail, they also conduct a survey with senior executives in firms. It is important to note the methodological problems: the view of the executives is partial and dependent on their own views, this means that rather than make comments based on an objective analysis of their companies performance, they may simply be repeating the very mistakes which have led to reduced productivity growth in the first place. Overall, the results from the EIU

0 Economist Intelligence Unit (004) ibid

International perspectives

(14)

R&D, ICT and Productivity

14

Variations in the Impact of ICT

highlight four important factors in enabling innovation: ICT-Related management skills

R&D

Innovation enablers, such as venture capital Open and competitive markets.

These results are interesting as they begin to highlight the factors behind the successful use of ICT. ICT is not a static input from which productivity gains flow automatically through some magical process, but a tool whose impact is conditioned by the context in which it is exploited. The following section explores the context and suggests what the impact of other factors on the payoffs from ICT might be.

(15)

5. Explanations – Measurement, environment or organisation?

The above evidence begs the question – why has this ICT led productivity miracle not manifested itself in the UK? A number of reasons have been given, including those of the Economist Intelligence Unit. Arguments for external factors are, to a certain extent, based on the universality of computer equipment – as Robert Gordon has pointed out: ‘Since Europe uses the same computer hardware and software as the US, the impediments to European growth must lie elsewhere than inadequate investment in ICT’.1

There are three broad categories of explanation for this. The first are those explanations which argue that the productivity problem is a measurement problem – a construct of the official statistics we use to measure it. By digging into the data, the problem can be ‘explained away’ or shown not to exist. The second group of explanations look inside the organisation at factors such as management skills or the complementary investments made alongside ICT investment. The third looks at the economic environment in which the firms are situated, and seeks to look at factors such as the nature of market competition which might explain the behaviour of the firm. The following looks at a selection of these possible explanations.

It has been argued that the productivity gap is the result of measurement issues. For example, as it is harder to measure productivity growth in services, this results in a downward bias to UK productivity; growth will be understated. One of the reasons its that it is difficult to measure is that prices – which are commonly used to measure productivity growth – imperfectly represent the significant quality improvements in computer hardware, a problem overcome with the use of hedonic indicators.

These difficulties are reflected in revisions of the statistics. ICT investment is difficult to define, and cross-national measures may vary. Work by the Office of National Statistics has shown that by changing the definition of software investment, it can leap from below 1 to almost % of GDP (003 figures)3. For some growth accounting methodologies, this may imply a significant deviation in results.

1 Robert J. Gordon (004) ‘Why was Europe Left at the Station When America’s Productivity

Locomotive Departed?’, CEPR Discussion Paper, p3

 Dirk Pilat, Frank Lee and Bart van Ark (00) ‘Production and use of ICT: A Sectoral Perspective on

Productivity Growth in the OECD area’, OECD Economic Studies, 35, 48-76

3 Tony Clayton, Emma Edworthy and Gavin Wallis (006) Technology Measurement: Impact on the UK

Economy, Presentation

Measurement issues

(16)

R&D, ICT and Productivity

16

Explanations – Measurement, Environment or Organisation?

It has become clear that ICT (and R&D) should not be viewed removed from the context in which they are used. ICT and R&D depend on individual level factors (eg skills), organisational level factors (eg management capability) and economy level factors (eg product market regulation). Evidence for these comes from three sources: first, the sectoral studies with information at the level of the firm; second, in the few cross-national studies which show framework conditions, and; third, in those studies which offer a more qualitative or case study based look at individual industries or firms.

Ownership

The ownership of the firm might influence the use of ICT. In a study of UK firms, Bloom, Sadun and Van Reenan4 stress that the impact of ICT is higher in the US due to the superior organisational design of US firms. They test this through looking at the IT performance of US owned organisations in the UK – the assumption being that US multinationals export their business models to affiliates. If organisational factors are important, this should show up as an increase in IT-related productivity gains.

For a sample of 7,500 firms which are based in the UK, they find US owned establishments are 8.5% more productive than UK owned establishments, while firms owned by multinationals from other countries are 4.8% more productive. In terms of value added per worker US multinationals are 3% more productive than the industry average, and non-US multinationals 16% more so. In terms of output per worker, the US advantage is 1.5% and non-US advantage 17.5%.

Breaking these results down by sector suggests that the biggest returns to ICT are found in those sectors – wholesale and retail – in which the US productivity revival was felt most strongly. Their findings are robust against other alternative explanations, notably ‘cherry-picking’ where multinationals only buy the strongest UK firms. As a control for this they ensure they test the productivity of firms both before and after US takeovers.

4 Nick Bloom, Rafaella Sadun and John Van Reenen (005) ‘It ain’t what you do, it’s the way that you do

I.T. – Testing explanations of productivity growth using US affiliates’, Centre for Economic Performance, LSE

Factors behind success: Environment and organisation

(17)

Explanations – Measurement, Environment or Organisation?

Management practices

In accounting for the differences in productivity, Bloom et al.5 argue that management practices are important. This argument draws on work done by McKinsey looking at the practices of 730 manufacturing firms in France, Germany, the US and the UK. The work employs an interview-based management practice evaluation tool to rate from 1 (worst practice) to 5 (best practice) across 4 main areas: shopfloor operations (the extent to which firms have understood and implemented lean manufacturing); performance monitoring (how successfully firms track internal developments); target setting (whether firms set the right targets and have effective feedback mechanisms in place); and incentive setting (whether firms hire and reward the right people).

Their main finding is that US firms are significantly better managed than those from mainland Europe or UK firms. German firms rank nd, French 3rd and UK firms last. They find that these management practices explain up to 10-15% of the productivity gap between the US and the UK.

There is a high degree of intra-country variation, with the UK’s top firms equalling the success of the top firms in the US. Firms of different nations tend to excel at different things, implying structural factors are at work. For instance, German firms excel at shop floor and process management, while US firms specialise in spotting talent and incentivising people.

Black and Lynch6 test for the impact of management practices using a data set compiled from US businesses over the period 1987-1993 (a period, it should be noted, prior to the ‘productivity miracle’). They looked at workplace practices, and their role in productivity, but incorporated a variable for ICT use. Estimating a Cobb-Douglas production function for firms using panel data from the US, they established a number of interesting findings. In the first place, more non-managers using computers was associated with a higher level of productivity. But more significantly, they find that ‘new workplace practices’ such as those for employee voice and reward, are the most important factors. They suggest that: ‘it matters less whether or not an employer adopts a particular work practice, but

5 Nick Bloom, Stephen Dorgan, John Downdy, John Van Reenen and Tom Rippin (005) ‘Management

Practices Across Firms and Nations’, Centre for Economic Performance, LSE

6 Sandra Black and Lisa Lynch (1997) ‘How to compete: The impact of workplace practices and

(18)

R&D, ICT and Productivity

18

Explanations – Measurement, Environment or Organisation?

rather how that work practice is actually implemented within the establishment’. The time period for this paper is actually before the productivity miracle took place, but in a second paper (1993-1996) their dates match the upturn in US productivity. This paper again uses panel data, and has similar results – workplace practices are important. This effect, they suggest, is more than directly through the use of ICT, but ICT allows firms to implement important organisational changes such as decentralisation.

ICT and the decentralised firm

Of the management practices most effective, the decision to centralise or decentralise an organisations decision making structures is particularly salient. In short, decentralised decision making structures are supposed to lead to benefits in terms of motivation, initiative and creativity7. The decision whether to decentralise or not involves a series of trade offs, including:

The value of the remote decision information used (the cost of not considering it)

The costs of communicating the remote decision information

Where costs of communication are particularly high, the cost (ii) will outweigh the benefits (i).

Malone8 argues that improved ICT has tipped this balance: by reducing the cost of communication it has made decentralisation a more appropriate form of decision making. He argues that this has occurred in three stages. Firstly, with relatively high costs decisions need to be made through independent, decentralised decision making. But, secondly, as information costs begin to fall, it becomes worthwhile to collect global information together in one central place, where decision makers can work strategically with a more informed view than local decision makers can. The traditional 0th Century Fordist production model is an example of this. But as costs fall a third model gains in importance, decentralised decision making becomes increasingly important, as information becomes easier to transmit. In this way, ICT allows larger firms to use both the benefits of large organisations (economies of scale and knowledge), and those of smaller ones (freedom, motivation, creativity and flexibility).

7 J. Richard Hackman and Greg R. Oldham (1980) Work Redesign, Mass: Addision

8 Thomas W. Malone (004) The Future of Work: How the New Order of Business Will Shape Your

Organisation, Your Management Style, and Your Life, Boston, MA: Harvard Business School Press i.

(19)

Explanations – Measurement, Environment or Organisation?

The example given is the retail sector, where supermarkets have replaced independent cornershops. Supermarkets, through centralised pricing, buying and promotional decisions at a national level, are often able to offer better quality products at lower prices. But, interestingly, they have slowly returned to decentralisation. Equipped with national sales data and other information which is only possible to collect and transmit using ICT, local store managers have been granted considerable freedom to allocate space and order stock. The prices of over 500 price-sensitive items, are now set by local managers according to local conditions.

Skills

As was shown earlier, the Economist Intelligence Unit identified management ICT skills as important in harnessing the value of ICT. While Management practices are clearly conditioned by skills, there is the need to clarify further the role of ICT skills. One aspect of the ICT skills link has been set out widely in the literature around Skills Biased Technological Change9. This argues that the new technology has changed the pattern of labour demand, and that this may have changed the appearance of the labour market, which would take on an ‘hourglass’ shape. There is also considerable work at the level of the organisation, looking at what management skills are necessary to allow the adoption and diffusion of ICT. Workforce skills generally in the UK are seen as lower than in the US, and some studies have flagged this as a reason for the slower diffusion of ICT (and the associated slower increases in productivity).

John Forth and Geoff Mason30 use a sample of over 500 companies in the UK for the period 1997-1999. They have a negative skill variable – reported skills gaps rather than actual skills possessed. They find a negative relationship between skills gaps and ICT adoption and a negative relationship between skills gaps and ICT use (ie when there are skills gaps firms are less likely to adopt and subsequently use firms). This leads to a corresponding decline in financial performance of the firm.

9 See Rebecca Fauth and Ian Brinkley (006) Efficiency and Labour Market Polarisation, London: The

Work Foundation

30 John Forth and Geoff Mason (004) ‘Information and Communications Technology Adoption and

Utilisation, Skill Constraints and Firm-Level Performance: Evidence from UK Benchmarking Surveys’, NIESR Discussion Paper No. 234

(20)

R&D, ICT and Productivity

0

Explanations – Measurement, Environment or Organisation?

ICT skills, of course, differ in their impact by sector. Jagger et al.31regress the percentage of staff working in ICT against TFP in a selection of firms, to assess which sectors ICT is most important for (ICT employment can be assumed to be a reasonable indicator of skills). They find that this is positive for most service sector employment, but a significant negative relationship for firms in other sectors.

ICT diffusion

The diffusion of ICT throughout the economy may also be related to costs, and this may be an example of where the US stole a lead. During the 1990s US and Canadian firms had considerably lower costs for ICT than those in Europe and Japan3, and this may have slowed the diffusion of ICT.

The diffusion of ICT is also derived, in part, from regulation. Where product market regulation restricts competition, it is likely to restrict ICT investment as competition proves an incentive for firms to invest in ICT and gain a productivity edge of their competitors, in theory, it may also reduce the cost of ICT. Meanwhile, labour market regulation may prevent firms from undergoing the organisational changes which allow firms to produce the productivity gains of ICT.

Environment Vs. Organisation?

The McKinsey study attributes differences in management practices to the degree of competition within different industries, and labour regulations. Competition forces firms to improve managerial practices by shaping up or losing business, while permitting greater entry to the market. Labour market practices, however, obstruct competition by restricting hiring practices and talent management. However, competition seems to have little impact on effort. The authors find little difference in terms of the hours worked by managers and workers in firms in sectors of high and low competition.

This explanation leaves some room for ambiguity. Bloom et al. distinguish between environmental and organisational factors through highlighting the role of management practices. The role of management practices in harnessing ICT are, according to this theory, the factor that makes the difference. However, an alternative view is that management concerns are themselves due to the intensity

31 Nick Jagger, Lionel Nesta, Vania Gerova and Parima Patel (005) Sectors Matter: An International Study

of Sector Skills, SSDA Research Report RR14

(21)

Explanations – Measurement, Environment or Organisation?

of competition and the role this plays in moderating the survival and evolution of firm practices in a dynamic market: in a highly competitive market, firms are placed in the position where they either exploit ICT through decent management or fail to survive. Clearly, this case is overstated. A host of other factors, including the history of the firm, embedded assets and market failures, condition this effect. But the distinction between the market environment in which a firm is placed and the structure of the organisation is closely connected. This may be a reason for the consistent lead in some American firms, which often compete in a larger market.

Beyond ‘shopping lists’

Creating a general list of potential explanations, such as has been done here, is interesting for what it illuminates about each of these conditions. But the exploitation of ICT is more complicated than this, dependent on the simultaneous confluence of framework conditions, organisational design and other ‘enablers’. As Hughes and Scott Morton put it: ‘…success comes from the artful crafting of a series of interrelated and mutually interdependent driving forces.33

This is reflected in the ICT statistics, which indicate that – while ICT investment is relatively high, the actual hardware component is relatively low compared to the values of other investments, be they intangible and organisational34, with hardware accounting for as little as 0%, or less. Firms will invest in ICT but they’ll invest more in the soft factors which accompany it.

Investment in ICT tends to happen alongside other management changes such as decentralised structures, individual decision making, team based incentive systems and skills training35. Brynjolfsson, Renshaw and Van Alstyne36 used the example of a large medical products manufacturer where substantial investments were made in computer integrated manufacturing yet failed to produce the desired results. Further study revealed that workers were still attached to many of the old work-practices (such as high levels of vertical integration, narrow job descriptions and rank-based authority, function based working groups) unconsciously as inherited tendencies. The new technology was instead

33 Alan Hughes and Michael S. Scott Morton (005) ibid, p. 3

34 Hughes and Scott Morton (005), ibid. Also see: Erik Brynjolfsson and Lorin Hii (000) ‘Beyond

computation: information technology, organisational transformation and business performance’, Journal of Economic Perspectives, 14 (4), 3-48

35 Hughes and Scott Morton (005) ibid

36 Erik Brynjolfsson, A. Renshaw and M. C. Van Alsytne (1997) ‘The Matrix of Change’, Sloan Management

(22)

R&D, ICT and Productivity



Explanations – Measurement, Environment or Organisation?

introduced successfully in a new site, with new employees and new systems. Process changeovers were reorganised leading to a 67% reduction in setup times, a fourfold increase in throughput and a 65% cut in waste costs.

In short, the actual ICT investment matters less than how the ICT is invested and the wider context of the firm. The high-tech industries are the key areas for technological change, meaning these industries are likely to be among the key drivers of productivity growth in the future37. This implies that countries that specialise in these industries are likely to succeed.

37 Jorgensen (001) ‘Information Technology and the US Economy’, Harvard Institute of Economic

(23)

6. R&D and productivity

There is a considerable body of evidence linking research and development to productivity growth. What is less obvious is why there is often a relatively narrow focus on R&D, as opposed to a more general focus on innovation. There are arguments that the R&D focus reflects relatively poorly on the UK, as our sectors are more likely to be in areas where R&D is less important or does not measure other factors.

Studies looking at the role of R&D in the economy generally find a significant relationship between R&D and productivity growth. One such paper, produced by Dominique Guellec and Bruno van Pottelsberghe de la Potterie38 of the OECD, look at the impact of R&D on productivity in a panel of 16 OECD countries since 1980. Their analysis is interesting because they divide R&D into three types: domestic public R&D, domestic business R&D and foreign business R&D (R&D performed in foreign countries, although which may impact on national productivity if the ‘absorbative capacity’ of the state in question is high enough. They find that the elasticity’s with respect to productivity of foreign business R&D is 0.45, that of public R&D 0.17 and that of domestic business R&D as only 0.13. This implies that foreign R&D has the greatest long term impact on productivity, followed by public and domestic R&D (although some of the benefits of R&D are not included in this model).

It is difficult to look at the effect of public research on productivity, in part because of the difficulties in measuring the output (the authors use the example of Health investment, which has no direct impact on productivity but an indirect one through making people healthier). The study finds that all three forms of R&D are important for productivity growth.

Research which takes place in the higher education sector is likely to increase long run economic growth – but this is dependent on the intensity of business R&D. Business R&D is also increasingly important to productivity growth with time. Finally, Public R&D is very important to the economy, although there is a negative effect of the share of defence R&D in this situation (it is not, they note, the main purpose of defence R&D to increase productivity).

38 Dominique Guellec and Bruno Van Pottelsberghe de la Potterie (001) ‘R&D and Productivity Growth:

Panel Data Analysis of 16 OECD Countries’, OECD Economic Studies, 33, 103-15

R&D and productivity studies

(24)

R&D, ICT and Productivity

4

R&D and productivity

In a paper for the Institute for Fiscal Studies, Griffith et al39 argue that there is an additional reason why productivity growth may arise from R&D, through: ‘facilitating the imitation of other’s discoveries’. They test this hypothesis for 1 OECD countries in the period since 1970. As is common for many studies, they analyse the role of R&D on productivity growth and also look at the distance of each country studied from their technology frontier, which is said to induce a ‘catch-up’ effect.

They find a positive relationship between R&D and productivity growth, but in addition they find that the effect is more powerful the further from the technology frontier the country is (the less technologically advanced). They conclude that previous studies then underestimate the effect of R&D, as they mainly use America as a case, and America is on the frontier and so benefits less. But against this aggregate work, there is also evidence that the framework conditions matter. In their most recent Economic Survey of Japan40, the OECD criticised the method of Japanese innovation: while R&D intensity is the third highest in the OECD, this has not been matched by growth. Although the pure R&D investment is in place, it is inefficient, with efficiency (a ratio of profits to R&D expenditure) falling steadily. This suggests firstly that emphasis on the input of R&D ignores the crucial framework conditions around needed for growth. Secondly, as the OECD point out, it indicates the dangers in concentrating finance on artificial R&D targets, which leads to the inefficient use of resources41. In addition qualitative factors may be important, with the role of the relatively closed Japanese innovation system being criticised. The idea that foreign innovators are important will be examined later.

39 Rachel Griffith, Stephen Redding and John van Reenen (004) ‘Mapping the Two Faces of R&D:

Productivity Growth in a Panel of OECD Industries’, The Review of Economics and Statistics, 86 (4), 883-895

40 OECD (006) Economic Survey of Japan 006, Paris: OECD

41 There are some implications here for the Lisbon Agenda, see Ian Brinkley and Neil Lee (006) The

(25)

7. UK R&D performance

The UK performs relatively weakly in terms of R&D spending. According to the OECD science and technology scoreboard, UK R&D intensity (the percentage of GDP accounted for by R&D) was 1.9% in 003, against an average of .0% for the EU15 (a figure which includes such poor performers as Greece, Portugal and Spain). This compares unfavourably with European nations such as France, whose R&D intensity is .% and Germany, whose R&D intensity is .4%. Against the US and Japan, whose R&D intensities are .6% and 3.% respectively, the UK performs even worse. The best performer, Sweden, has an intensity of 4%, more than double that of the UK.

Fig. 1 R&D Intensity – Key OECD Nations (2003)

R&D

Intensity Business Enterprise R&D Intensity Portugal (00) Spain Ireland (00) Italy (00) Netherlands (00) EU5 United Kingdom EU15 France OECD Belgium Denmark (00) Germany United States Japan Finland Sweden 0.9 1.1 1.1 1. 1.8 1.9 1.9 .0 . . .3 .5 .6 .6 3. 3.5 4.0 0.5 0.8 1.1 0.8 1.5 1.7 1.8 1.8 .0 .1 .6 .8 .6 .6 3. 3.7 4.7

Source: OECD Science and Technology Scoreboard 200542

UK growth rates of gross expenditure on R&D have been declining as well. The EU15 saw an average annual growth of 3.3% in the period 1995-003; the OECD grew at an average of 3.7%. Against this, the UK grew at only .4%. While growth has been higher than France, which grew at only 1.4%, it remains lower than leading nations such as the US (.7%), Japan (.7%) and Germany (.9%).

(26)

R&D, ICT and Productivity

6

UK R&D performance

The statistics mask a reasonable performance in government funded R&D (GERD) and a relatively poor performance in Business funded R&D (BERD). This is despite government efforts towards the UK Science and Innovation Framework which set an ‘ambition’ to increase R&D intensity in the UK to .5% by 014.

This performance is despite excellent UK performance in several areas which are seen as linked to R&D. The universities are perhaps the UK’s most important strength. In terms of citations, the UK performs very well. In 00, the UK had 0.5 citations per 1,000 people, compared to 0.43 in the US, 0.43 in Germany and 0.8 in France43. This, as the DTI notes, is despite relatively low levels of funding. The UK also performs well in league tables of international universities, and many institutions are regarded as ‘world class’. In the 006 World University Rankings, published by the Times Higher Education Supplement, the UK has three universities in the world top ten (Cambridge, Oxford and Imperial), with all the other universities being American, and none being from continental Europe. While the methodology may be dubious, it is clear that the UK has some universities that perform well44. Although the UK performs well in terms of citations, it performs less well for patents. But the existence of these strengths makes the UK’s R&D performance even more surprising.

One potential explanation for the UK’s poor R&D performance is the mix of industries in the UK. If the UK’s economy is concentrated in sectors in which relatively little R&D is performed (or necessary) or in those sectors in which innovation is achieved through other means which may go unmeasured, R&D can seem low, despite the industry being innovative. However, this ‘industry mix hypothesis’ ignores other factors which may be important in explaining the UK’s relative R&D performance. Market structure is one such factor, as firms in niche markets may have less incentive to invest, as an innovation would be spread across a smaller number of units, making it more expensive for the firm and so less likely45. In markets using a technology which is new, the potential gains from innovation will be greatest46. So sectoral variations are clear across industries, and this ‘industry mix’ hypothesis becomes a relatively appealing one.

43 Evidence Ltd/Thompson ISI, Cited in DTI (003) Competing in the Global Economy – the Innovation

Challenge, DTI Economics Paper No. 7

44 Alexandra Smith (006) ‘Oxbridge closes gap on Harvard in world university rankings’, The Guardian,

5.10.006

45 DTI (003) Competing in the Global Economy: The Innovation Challenge, DTI Economics Paper, 7 46 DTI (005) R&D Intensive Businesses in the UK, DTI Economics Paper 11

Ownership, size and structure: Explaining the UK’s poor performance

(27)

UK R&D performance

It is not, however, entirely true: the ‘industry mix hypothesis’ has important caveats. Figure , taken from the OECD economic outlook, outlines the proportion of the gap which can be explained by effects within the industry, and that which can be attributed to industry mix effects. A considerable proportion of the gap in R&D can be explained by the industrial mix of the UK – the UK’s performance relative to France (80% explained by industry mix effects) and Germany (73%) is promising. But compared to the United States, the statistics indicate that taking the industry mix into account makes the UK’s relative performance even worse, with minus 7% explained.

Figure 2. Industrial structure and cross-Country Differentials in R&D

Intensity Relative to the United Kingdom, Percentage points, 2002 (2000 for Sweden, 2001 for US).

France Germany US Japan Finland Sweden R&D Intensity Gap 0.0 0.53 0.63 0.88 1.36 .08

Due to ‘within industry intensity’

• 0.04 0.14 0.68 0.35 0.61 1.51

Due to ‘industry mix’

• 0.16 0.39 -0.05 0.53 0.75 0.57

Percentage of R&D intensity gap accounted for by:

Within industry effect

• 0 7 107 39 45 73

Industry mix effect

• 80 73 -7 61 55 7

Source: OECD (2005) Economic Survey of the United Kingdom

The DTI has produced a convincing analysis of the ‘industrial mix’ explanation. They build on the analysis of the Science and Innovation framework, which argued that UK manufacturing has lower R&D intensity than those sectors in similar countries. Their analysis agrees with the basic analysis that – like for like – UK firms perform less R&D than those of comparator nations. However, their analysis is subtler, relying on the combination of three factors – sector, size and ownership.

(28)

R&D, ICT and Productivity

8

Their first finding is that firms in the UK actually tend to produce similar, or even slightly more, R&D relative to foreign counterparts of similar sizes and in similar sectors. They find: ‘the largest UK owned R&D performing businesses within any given sector tend to spend slightly more on R&D as a percentage of sales than their foreign counterparts’47.

But UK R&D is still low, something they attribute to the sectoral composition of large UK firms: they are located in sectors in which firms conduct less R&D. This suggests the ‘industry mix’ hypothesis is important for large firms, which are less likely to be R&D intensive. For medium sized firms (those with sales of £56-500 million per year) ‘industrial mix’ is again important, with a slight bias towards R&D intensive sectors.

Finally, while the UK has been open in persuading foreign owned firms to locate plants here, firms tend to locate R&D facilities near their headquarters. The UK is less well represented in industries such as the Automotive industry, an industry which is normally relatively R&D intensive48. Foreign ownership in these industries may mean less R&D is produced here.

This position exists despite the strong research base in the UK. The UK’s performance is the highest in the G7 in terms of both citations and published papers per head. It comes second only to Germany in terms of PhD’s awarded49. This strong research performance might be expected to have an eventual positive impact on productivity. Similarly, beyond the universities there are relatively strong levels of public R&D spending. But this link does not seem so clear, raising the question of the relationship between the strong research base and business R&D spending.

A number of the processes through which public and private research may impact on each other have been identified. Within organisations, Lach50 has isolated three impacts of publicly funded R&D. The first is through reducing the private cost of an individual R&D project, making it more likely to occur. The second is through knowledge transfers within the organisation decreasing the cost of other

47 DTI (005) ibid: 4 48 DTI (005) ibid

49 DTI (006) UK Productivity and Competitiveness Indicators, DTI Economics Paper No. 17

50 Saul Lach (000) ‘Do R&D Subsidies Stimulate or Displace Private R&D’, NBER Working Paper W7943

UK R&D performance

R&D Complementarity: Why does the UK do well in universities but not in business research?

(29)

projects, which can build on publicly funded advances. Thirdly, public funding can subsidise equipment, reducing the private cost of R&D.

At the level of the economy, Falk51 highlights two such processes. Firstly, publicly funded R&D may lead to the crowding out of private R&D. This problem may be particularly acute where there is a shortage of highly skilled labour, as public research agencies compete with private companies for a relatively small and specialised group of people. Secondly, however, public R&D can lower the cost of private R&D, as it allows it to build on the results of publicly funded studies. This may work through published research, improved training for researchers or through advances in equipment and techniques. Sometimes, these processes will be geographically constrained knowledge spillovers, implying a transfer of knowledge through networking or skilled staff movements5. If true, these location specific positive externalities lie behind some concepts of knowledge cities, and have significant implications for spatial economic policy53

A plethora of studies have sought to determine the relationship between public R&D and private R&D. These studies tend to take place at the level of the economy, or using firm level datasets, and there is considerable variety of methodology. A relatively old paper by David Hall and Toole54 look critically at this body of work. They find the results of these studies are considerably less clear than is sometimes expressed. The diverse results and methodologies used make firm conclusions difficult. They argue that given the diversity of publicly funded R&D and the subtle nature of the characteristics of the public R&D on the functioning of the private sector, many of these empirical studies do not give a complete picture. Instead, they suggest a need for further macro studies. While this paper is relatively old, this argument remains salient when accounting for newer evidence.

Set against the results of studies, the position of the UK still seems curious. Falk55, for example, finds a positive relationship between the amount spent in

51 Martin Falk (006) ‘What drives business Research and Development (R&D) intensity across

Organisation for Economic Co-operation and Development (OECD) countries?’ Applied Economics, 38, 533-547

5 David B. Feldman and Maryann P. Audretch (1996) ‘R&D Spillovers and the Geography of Innovation

and Production’, American Economic Review, 86 (3), 630-640

53 See Jones et al. (006) Ideopolis: Knowledge City Regions, London: The Work Foundation

54 Paul A. David, Bronwyn, H. Hall, Andrew A. Toole (000) ‘Is Public R&D a Complement or a Substitute

for Private R&D? A review of the econometric evidence’, Research Policy, 9, 497-59

55 Falk (006) ibid

(30)

R&D, ICT and Productivity

30

universities and private R&D spending, while the OECD study56 finds Universities important.

The question remains – if the UK is performing poorly on R&D, but the economy remains strong in many areas compared to our neighbours, does this matter? In many respects it is not so important. In the first place, it should be remembered that while R&D is an important factor in growth, it is not the only factor. Indeed, some nations (such as Japan) have maintained a sluggish economy alongside high levels of spending on R&D.

There are some heretic voices in academia. Diego Comin57 tries to assess the role of R&D in US productivity growth since 1945. Regarding previous studies in growth, which typically find very large percentages of growth performance are explained by R&D investment. In some cases, he argues, the entire R&D investment accounts for all the unexplained portion of growth regressions (making R&D responsible for an almost unbelievable portion of growth). He notes that these studies suffer from ‘omitted variable bias’, in that not all those factors which may lead to innovation are included in the growth model. Furthermore it is not possible to predict the direction of the bias – it could over or understate the effects of R&D on growth. As was shown earlier with ICT, the impact of R&D is contingent on other, unmeasured factors (for ICT these included management skills). In particular, using traditional methods the gains from changes in

management practices (such as inventory management systems) will be attributed to R&D. To test this, a new method for measuring the growth effect is necessary. Comin does this in two stages, looking only at those innovations which produced a new good. He looked at the impact of increases in research spending on new technologies, and how the growth rate of these new technologies affected productivity. His results undermine the importance of this form of R&D; of an average annual growth rate of .% in the period in question, only 0.3-0.5% is still attributed to R&D.

This article is important both for mellowing our assumptions about R&D (although even with this cautious analysis it remains important), but also for indicating that there are factors behind R&D that enable it to produce successful

56 Dominique Guellec and Bruno van Pottelsberghe de la Potterie (001) ibid

57 Diego Comin (004) ‘R&D: A Small Contribution to Productivity Growth’, Journal of Economic Growth,

9 (4), 391-41

UK R&D performance

(31)

results. In this respect, our argument for R&D echoes that for ICT – it is the positioning which matters.

In addition, recent evidence has suggested that the impact of R&D on firm profitability is not as definite as is sometimes claimed. The Booz Allen Hamilton Innovation 100058 uses data from the 1000 public global firms which spend the most on R&D. Correlating R&D spending with several measures of firm performance (including profits and dividends), they find little or no relationship. Instead, they point to the complexity of firm innovation systems, and the lack of success in commercialisation from which many firms suffer. While their evidence is limited, representing a sample of only large firms and one which is taken from a single point in time, it does suggest the R&D/profitability nexus is more murky than it may appear.

Internationalisation

One such theory around R&D regards the role of internationalisation. While much innovation systems literature concentrates on local cluster of innovative networks, such as Silicon Valley, these localised systems form part of a global network of goods production. The role of the Multinational Enterprise (MNE) is particularly important here. There is already considerable evidence that MNE’s are more efficient, partly due to the skills which allowed them to grow to such size, economies of scale and the ‘cherry-picking’ of local affiliates. But they also hold a key role in the R&D process.

And there is some evidence that the same applies for UK firms who outsource R&D. Griffith, Harrison and Van Reenen59 find that this can have large benefits for UK firms. Their argument here hinges on the idea of ‘knowledge spillovers’, or geographically limited spatial externalities. Using a panel data set at the firm level accounts for differences in firms and geographically linked patent data. They look at increases in TFP for UK firms who invest in R&D in the US. The US is assumed to be closer to the technological frontier, and so spillovers increase the gains from R&D in those countries. A firm moving 10% of innovative activity to the US would increase TFP by about 3-7%. They note that this increase is equivalent to ‘a doubling in its R&D stock’ (p.8).

58 Barry Jaruzelski, Kevin Dehoff and Rakesh Bordia (005) The Booz Allen Hamilton Global Innovation

1000: Money Isn’t Everything. Available from: http://www.boozallen.com

59 Rachel Griffith, Rupert Harrison and John Van Reenen (004) ‘Technology sourcing: an empirical

analysis using firm-level patent data’, Paper Presented to the Royal Economic Society Annual Conference, No. 1

(32)

R&D, ICT and Productivity

3

This raises an intriguing question. If UK firms gain more from outsourcing than conducting the R&D in the UK, does this mean that the low level of BERD (research perfomed by businesses rather than government) matters little? Productivity gains can be accrued through R&D conducted abroad, which – as part of a global market – the UK does not specialise in. Griffiths et al. note that policies which provide incentives for British companies to conduct R&D in the UK may lead to a misallocation of resources, if the most efficient place to conduct R&D is actually abroad60.

The problem for the UK economy is implicit in the Griffiths et al. piece. If we believe that the knowledge economy is subject, at least in part, to these knowledge spillovers, then without a critical mass of these industries the consequences for UK science may be grave. There is evidence for considerable agglomeration effects, or benefits from a critical mass of such industries. Paul Krugman61 has modelled the consequences of such spillovers and shown that they may lead in the long run to considerable specialisation of these industries, subject to external shocks. Different places may, according to this line of argument, specialise in different industries. And the UK would not specialise in science.

But would the UK be willing to lose its science base? More severely, are these spillover effects limited to the R&D sector? It is likely that R&D is targeted to local conditions, and so will benefit local firms more than those from further away. Some would therefore have to be done near to the market (and so within the UK). In addition, the internationalisation thesis does not answer why UK university performance can be so good without spillovers into R&D performance.

What it does clearly demonstrate is the role of internationalisation of innovative activities. In one sense, this means increased flows of information, students and knowledge about innovation6; it also implies the role of multinational firms in the innovation process are not entirely clear.

60 R&D Tax Credits for UK firms are, subject to caveats, claimable for work which is either conducted

or subcontracted abroad. Caveats include restrictions on the ownership of intellectual property and profit based accounting

61 Paul Krugman (1991) ‘What’s New About the New Economic Geography’, Oxford Review of Economic

Policy, 14, 7-17

6 Rajneesh Narula and Antonalla (005) ‘Globalization of Innovation: The role of multinational

enterprises’, DRUID Working Paper No. 03-15

(33)

UK R&D performance

Of course, this analysis ignores the role of foreign firms in exporting R&D to the UK. There is some evidence that this foreign export presents considerable benefits to the UK economy. The DTI R&D scoreboard have looked at those foreign firms which perform R&D in the UK. The vast majority of this is done by relatively few firms. In the UK, Ford and Pfizer make up 36% of the foreign-owned companies R&D. The top five make up over 60% of the production.

One OECD paper sheds light on the reasons why the UK performs poorly63. Using, again, cross-country data, this paper is important for the disaggregation of their findings. Public R&D funding has positive impacts on productivity growth, but this impact is increasing with the amount of business research which is being conducted. They put this down to the role of business researchers in exploiting basic public research. When they disaggregate and look at the type of public research, they find that defence research actually has a negative effect. They also find that university research is more important research conducted by institutes, a conclusion they attribute to the nature of funding – university research is more flexible and project based, and so adapts more quickly to changing economic needs.

63 Dominique Guellec1 and Bruno Van Pottelsberghe de la Potterie (004) ‘From R&D to Productivity

Growth: Do the Institutional Settings and the Source of Funds of R&D Matter?’, Oxford Bulletin of Economics and Statistics, 66 (3), 353-378

References

Related documents

A subgroup of patients who met a predetermined definition of clinical or culture confirmed neonatal sepsis (protocol-defined sepsis), had blood and naso/oro-pharyngeal (NPOP)

This paper starts with the urban traffic theory, introduces the co integration theory, analyzes the urban traffic motorization and social and economic development, through

Sjúklingum sem höfðu áverka á ósæð eða bráða ósæðarflysjun (acute aortic dissection) var sleppt en árangur þeirra aðgerða á Ís- landi hefur áður verið birtur

Operating mode Timing chart A: ON-delay B: Flicker OFF start B2: Flicker ON start C: Signal ON/ OFF-delay t t t Power Start Reset Output relay (NC) Power indicator Power Output

If 248 statistical features are used to characterize network traffic flows, the computation cost of classifier will be overlarge. The feature selection methods referenced here

The detection results for the deauthentication attack, based on individual metric, is presented in Table 2. Regarding the deauthentication attack detection, one noticeable result

This study has shown that using indirect leaf area estimates and other stand and climate variables have the potential to be used as independent variables for estimating basal area for

Another interesting feature of the approach based on multiple chi-square tests is its ability to identify the right pattern (independently of the obtained p-value). Note that