technology, productivity and public policy

FISCAL STUDIES, vol. 28, no. 3, pp. 273–291 (2007) 0143-5671

© 2007 The Author Journal compilation © Institute for Fiscal Studies, 2007. Published by Blackwell Publishing Ltd, 9600 Garsington Road, Oxford, OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA

Technology, Productivity and Public Policy*

RACHEL GRIFFITH†

†Institute for Fiscal Studies; University College London ([email protected])

Abstract

The poor productivity performance of the UK and the EU when compared with the US has been a major driver of policy reforms over the past decade. This paper considers what the evidence suggests about why we have lagged behind the US, considering among other factors the importance of globalisation and outsourcing, the role for public policy intervention and what the key drivers of growth are likely to be for the future.

I. Introduction

This paper addresses a very broad topic, and one on which a lot has been said and written. Achieving productivity growth and closing the productivity gap with the US has been one of the central targets of this government’s policy agenda since it came to power 10 years ago. This Introduction gives a very broad picture of the current situation regarding productivity in the UK, while Sections II to IV consider three more specific topics and Section V makes some final comments.

*Submitted May 2007. This paper is a revised text of the author’s inaugural lecture given at UCL on 17 May 2007. Much of

the research drawn on here was supported by the ESRC through the Centre for the Microeconomic Analysis of Public Policy (CPP) at IFS and through the ESRC/EPSRC AIM Initiative. This paper draws heavily on discussions and work with a large number of colleagues and co-authors to whom the author is indebted. In particular, she would like to thank Laura Abramovsky, Philippe Aghion, Richard Blundell, Heike Harmgart, Rupert Harrison, Andrew Leicester, Aviv Nevo, Mari Sako, Helen Simpson and John Van Reenen for many interesting discussions. Responsibility for any errors is the author’s alone.

JEL classification numbers: D20, H32, O30, O40.

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© 2007 The Author Journal compilation © Institute for Fiscal Studies, 2007

FIGURE 1 GDP per capita

Source: Groningen Growth & Development Centre, www.ggdc.net, ted07I.xls, Total Economy Database, January 2007, Geary Khamis PPPs.

Figure 1 shows gross domestic product (GDP) per capita from 1960 to

2007 for the market economy (this is everything except the public sector). These figures are shown in US dollars and are expressed in constant prices. Broadly since the end of the Second World War, output per capita has been growing fairly steadily in the UK. However, the level of income per person in the UK has persistently lagged behind that in the US, while France grew more rapidly during the 1960s and 1970s, which has meant that it has gone further to closing the gap with the US, although in more recent years France has fallen behind again, as US growth has accelerated.

GDP per person is affected by many things. Two very obvious factors are the proportion of people that work and how many hours they work. If GDP is instead scaled by total hours worked in the economy, we get Figure 2. This shows the most commonly used measure of productivity – GDP per hour worked. This has also grown fairly steadily in the UK over the past four-and-a-half decades. From the 1960s until the early 1990s, the UK was gradually closing the gap with the US. But since the mid-1990s, growth in the US has accelerated, leading to a recent widening in the gap. Last year (2006), the level of output per worker in the UK was around 84 per cent of that in the US. France, on the other hand, had caught up to the US by the early 1990s, and has kept up in levels terms. These figures taken together

Technology, productivity and public policy

© 2007 The Author

Journal compilation © Institute for Fiscal Studies, 2007

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FIGURE 2 GDP per hour worked

Source: Groningen Growth & Development Centre, www.ggdc.net, ted07I.xls, Total Economy Database, January 2007, Geary Khamis PPPs.

show that the French have achieved similar levels of productivity to the Americans, but because they work fewer hours they have lower levels of total income per capita. The UK, on the other hand, works more similar hours to the US, but because labour productivity is lower, achieves less for that input. The current UK government has made closing this gap one of its main policy aims.

Labour productivity is an important determinant of economic welfare, and standard growth models suggest that we would expect to see levels of labour productivity converging across countries over time. So why is it that the UK has so far not managed to achieve that objective? Why has UK productivity lagged behind the US in particular? While there are a large number of possible suspects, the reasons for the UK’s lagging performance are still rather poorly understood. Are new policies needed, what would they be and how effective would they be? And despite years of reforms to product and labour markets, why does the gap persist?

This paper focuses on three specific issues that are relevant to policy and where current research has contributed something to our understanding of the UK’s performance, or where it has raised some new questions, which hopefully will be answered in future research. There are, of course, a host of other factors that will also be important, but they are not touched on here and are much too numerous to mention.

The three topics that are addressed in this paper are:

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• knowledge creation and high-tech industries, which are traditionally thought of as one of the fundamental drivers of growth;

• technology adoption and diffusion, an area that it turns out is particularly important in explaining the productivity gap between the US and European countries; and

• the retail sector, which is responsible for a large part of the productivity gap between the UK and both the US and France.

In each area, some comments are made about what has been learned from recent research about the role that policy might play in helping to close the productivity gap.

II. Knowledge creation and high-tech sectors

The generation of new ideas and invention is one of the main drivers of productivity growth. By pushing the technological frontier forward, more can be produced for the same amount of labour input. So a first question to ask is ‘Is this where we are behind?’.

There is both good and bad news. Productivity in many high-tech sectors in the UK is high compared with that in the US, and levels of growth have largely kept pace with the US. However, high-tech sectors make up a relatively small part of the economy.

In terms of basic research, the UK also ranks very highly. It is second only to the US in terms of academic citations, accounting for an impressive 11.9 per cent of total world citations (compared with around 1 per cent of the world’s population).1 The UK ranks fifth in the world for the number of Ph.D.s produced per unit of higher education research and development spending2 and it consistently wins a high share of the world’s major scientific prizes. But anecdotal evidence suggests that while the UK is good at invention, it is rather poor at the commercial exploitation of new ideas.

Looking at the statistics, we see that businesses do relatively less research and development (R&D) in the UK than in the other major industrialised countries. For example, if we look at the amount of business sector R&D (BERD) that is carried out in the UK (i.e. geographically located in the UK), we see a more worrying picture. Figure 3 shows that expenditure by businesses on R&D as a share of GDP for the UK has declined substantially over the past two decades. The picture is even more worrying when we compare with the US, where the share of expenditure on R&D has remained persistently higher, or with France, where it grew over the 1980s and has remained high while it has declined in the UK.

1See Department of Trade and Industry, Office of Science and Technology (2005). 2See Department of Trade and Industry, Office of Science and Technology (2005).


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FIGURE 3 Business sector R&D as a percentage of GDP

Source: OECD STAN data.

While the UK has a comparatively low level of domestic business R&D

relative to other G5 countries, it has played a much more active role in terms of international flows of business R&D, both in terms of its role as an investor overseas and in terms of its capacity to attract business R&D from abroad. Multinationals and foreign firms carry out a large share of R&D in the UK. Griffith, Redding and Simpson (2004) showed that foreign multinationals perform more than 40 per cent of R&D in the UK, with US multinationals accounting for the bulk of that (25 per cent). As well as foreign firms doing R&D in the UK, UK firms are carrying out an increasing share of their R&D abroad, with the US being the main recipient of this investment.3 For example, Figure 4 shows a measure of the amount of innovative activity that is carried out offshore by firms in the pharmaceutical industry, the UK’s biggest innovating sector. It considers all patents that were taken out by firms located in the US, UK and France, looking at the location of the inventors who worked on each patent. Over the last decade or so, around 23 per cent of inventors working for UK-based innovative pharmaceutical firms were located abroad, compared with around 10 per cent for US and French firms.

So what we have seen is that the UK has higher international flows of innovative activity. This globalisation means that productivity and growth in

3See Abramovsky, Griffith and Harrison (2005) and Griffith, Harrison and Van Reenen (2006).

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FIGURE 4 Percentage of inventors located abroad for firms in the pharmaceutical industry

by location of firm, 1992–2001

Notes: Average percentage of inventors located abroad by location of corporate applicant. Patents filed at European Patent Office in pharmaceuticals and chemicals. Source: Author’s calculations using European Patent Office PATSTAT data.

the UK depend not only on what firms do within the national boundaries of the UK, but also on what they do abroad and what foreign firms do here. What implications does this have for policy? It means that when considering the impact of any specific policy, what is important is not just how it affects activities located in the UK, but also how it affects productivity- and growth-enhancing activities conducted abroad.

For example, policies such as the R&D tax credit or subsidies to the science base that target activity located in the UK may be either ineffective or counterproductive. If R&D is mainly locating abroad to help firms access large and growing markets, then these policies can do little to encourage private sector R&D. If technology sourcing is the main driver, then these policies, which encourage firms to bring R&D back to the UK, may have counteracting negative effects, as firms no longer participate in leading-edge research.

Griffith, Harrison and Van Reenen (2006) found that by locating R&D in the US, UK firms had helped boost UK productivity; over the 1990s at least, technology sourcing seemed to be an important motivation for firms moving R&D abroad. However, the factors that determine firms’ location decisions may be changing. Griffith, Lee and Van Reenen (2007) found evidence that suggests that, as communication and travel costs have fallen, technology sourcing has become less important as a driver of location.

So key issues for policy are ‘Why are UK firms going abroad?’, ‘Why are foreign firms locating in the UK?’ and ‘What impact does this have on UK


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productivity?’. There is a need for more and better systematic evidence on these issues.

A final point to make about knowledge creation relates to the increase in collaborative research. It has been noted in the literature that the proportion of patents that are collaborative – i.e. in which the intellectual property rights (IPR) are shared by more than one applicant (firm) – has increased. Researchers and policy commentators have emphasised the importance of research collaborations, and competition policy reforms have become more lenient in allowing firms to collaborate in research (for example, the National Cooperative Research Act Extension (1989) and the Cooperative Productivity and Competitiveness Act (1989) in the US and the EU’s Block Exemption Regulations for R&D and specialisation).

An important question, which to my knowledge has not yet been investigated in the literature, is whether the increase in cooperation and collaborative research is driven by technological complexity, or whether the increased collaboration between firms is in fact a response to tougher competition laws and enforcement. This is a thorny issue for competition authorities, and one that is currently being debated in the US and the EU. If it were the case that cooperating in R&D facilitated firms’ ability to collude in the product market, then the recent move towards more lenient treatment of collaboration in R&D might be brought into question.

In collaborative work with Susanne Prantl at WZB in Berlin, colleagues and I at IFS are investigating this issue. For example, we are considering the reforms that were undertaken as part of the European Union Single Market Programme and which were widely believed to increase competition in some industries more than in others. We can categorise industries into those that were strongly affected and those that were not affected so much, and we can consider the period before the Single Market Programme (SMP) and compare it with the period afterwards. We are taking all patents granted to UK firms over the period up to 12 years before the reform and up to 12 years after, allocating them to industries based on the activities of the firm that took out the patent.

Table 1 shows that the increase in collaborative patenting was more pronounced in those industries that experienced a bigger increase in competition. In industries that were not as affected by the SMP, the share of patents that were collaborative grew by just under 2 percentage points, while

TABLE 1 Share of patents that are collaborative, UK firms

Less-affected sectors More-affected sectors Pre-SMP reform 2.43% 3.25% Post-SMP reform 4.34% 8.41% Source: Griffith and Prantl, 2007.

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it grew by over 5 percentage points in those industries that were more affected. This is, of course, only suggestive, and there could be many other explanations for this pattern in the data. We are working on developing a more formal test of these ideas to bring to the data.

III. Technology diffusion

The focus on R&D, patents and high-tech industries may obscure some important issues for productivity growth. These are relatively easy things to measure, and as such they have become the focus of target setting. But it is likely that diffusion is equally (probably more) important as a determinant of productivity levels and growth. A consensus has emerged in the literature that faster growth in the US can be traced largely to those sectors that use new technologies, rather than those that produce them.4 So I now turn to issues related to the diffusion and use of technology.

One of the biggest technological changes of recent years has been the revolution in information and communication technology (ICT). Computers have become faster, smaller, cheaper, more flexible and easier to network together. The quality-adjusted real price of computers has been declining at a compound rate of about 20 per cent per year.5 These and other changes in technical complements to computers have led to very rapid growth in demand for ICT. Figure 5 plots investment in ICT as a share of GDP over the past two decades. Investment in these new technologies has risen rapidly in the UK, though recently it seems to have flattened out. In contrast, investment in ICT in the US continues to accelerate, while France lags behind even the UK.

These patterns are mirrored in the productivity statistics. Figure 6 shows the average growth in GDP per worker (the productivity figures in Figure 2 were in levels; Figure 6 gives the average rate of change of those lines over the period since US growth started to accelerate). The market economy is broken down into three groups – those industries that produce ICT, those that use it intensively and those that have little to do with ICT. In terms of growth rates over the recent period, France does poorly. The graph shows that the UK does relatively well (in terms of growth rates) in the sectors that produce ICT – the high-tech sectors that were the subject of Section II – but it does relatively worse in those sectors that are intensive users of ICT. I now turn to the issues raised by this middle group of industries – those sectors for which adoption of new technologies is likely to be an important source of growth.

4See, for example, Inklaar and Timmer (2006) and Inklaar, Timmer and van Ark (2006). 5See, for example, the discussion in Bresnahan (2001).


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FIGURE 5 Investment in ICT as a percentage of GDP

Note: Gross fixed capital formation in software divided by GDP, both in 2000 prices. Source: Timmer, Ypma and van Ark (2003), updated June 2005.

FIGURE 6 Average annual growth of GDP per hour worked, 1995–2002

Source: O’Mahony and van Ark, 2003.

ICT and productivity

How exactly do we expect ICT to affect productivity? Simply plugging in a large number of computers will not lead to productivity growth (in fact, it may lead initially to a slowdown as people get distracted). Several papers in

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the literature have emphasised complementarities between ICT and the internal reorganisation of the firm. New technologies mean that firms are able to become less hierarchical. They are able to get information to the people within the workplace who need it, and allow them to make decisions, reducing bureaucratic inefficiencies. But this requires complementary investments either in skills (e.g. Krueger, 1993; Autor, Katz and Krueger, 1998) and/or in organisational capital (e.g. Bresnahan, Brynjolfsson and Hitt, 2002). These adjustment processes may be an important reason why ICT investment has been slow to have productivity effects, and greater adjustment costs may have been one of the reasons that European countries have been slower to take up ICT.

What is also emphasised in the management literature and business press is the way that ICT enables firms to restructure externally. New technologies have meant that transactions that previously had to be conducted face-to-face within the firm can now be effectively conducted at arm’s length. It is thus now feasible for firms to outsource a host of activities that it was previously prohibitively expensive to do. In general, there has been a large increase in trade in previously ‘untradable’ activities, such as many services (think of call centres). New technologies may therefore have changed the optimal boundaries of the firm, and an interesting question is whether and how these changes may have fed through into productivity.

There are three main ways in which outsourcing can affect productivity:

• Specialised service providers can exploit economies of scale and/or scope.

• Independent service providers may have greater incentives to innovate (where they were not previously the residual claimant on the benefits from innovation, but they now are).

• Purchasers of services may become more productive in their core activities by outsourcing non-core activities (for example, if they were previously suffering from managerial overload or other constraints to productivity improvement).

There is some empirical evidence for these last two effects in the UK. For example, Acemoglu et al. (2005) considered the second of the effects above. They argued that as technology becomes more important for production, it becomes more important for productivity that the organisational structure gives the biggest incentives to the agent that is making the largest technology investment. Intermediate goods and services are becoming more technologically sophisticated. Vertically disintegrated structures give greater incentives to suppliers to invest in innovation. Technologies that reduce the costs of market transactions will in this case be productivity enhancing. Acemoglu et al. provided empirical support for these ideas by showing that


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producing–supplying firm pairs are more likely to be vertically integrated when the producer is technologically advanced, but less likely to be vertically integrated when the supplier is the more technologically advanced partner.6

Abramovsky and Griffith (2006, 2007) explored the importance of outsourcing for productivity in the purchasers of intermediate services, the third channel mentioned above. Developments in ICT have been particularly relevant for business processes such as finance and accounting, human resource management, sales and marketing (for example, call centres), purchasing and supply chain management, and even research and development.7 This is in fact where there have been some of the biggest structural changes to the US and UK economies. There has been very rapid growth in business service providers in the UK – employment in UK business services accounted for over half of total employment growth from 1984 to 2001 and this sector now accounts for around one in seven jobs in the whole economy.8 Abramovsky and Griffith provided empirical support for these ideas. They used a large nationally representative data-set for the UK and showed that ICT and outsourcing are complements in production – firms that outsource more services and use ICT are more productive than firms in their industry that do not do both. The idea that the authors exploited is that there are important adjustment processes, which for a number of reasons will vary across firms within an industry, and they used this variation in the speed of adjustment across firms to identify the impact of investment in ICT and outsourcing on productivity. This is, of course, only suggestive, and more work needs to be done on whether these correlations are driven by some other common factor.

What are the policy implications of this? ICT adoption is clearly important for productivity. There is evidence of ICT leading to productivity growth in the UK. Estimated rates of return to ICT are very high (in both the US and the UK). So why are UK investment rates in ICT so low and why have they flattened off? This remains a puzzle.

A wide range of statistics seem to point pretty clearly to the idea that ICT adoption is an important explanation for the productivity gap. Why then have investment rates in the UK declined recently? It seems that some firms within the UK are able to exploit these new technologies to their productivity advantage. What is stopping the others? The main rigidities emphasised in the literature have been in labour markets, and while these may be important in many continental countries, it is unlikely that they are important for the UK given the widespread reforms over the 1980s and

6See also Aghion, Griffith and Howitt (2006a and 2006b) for a consideration of the relationship between competition and vertical integration.

7See Sako (2005). 8See Abramovsky, Griffith and Sako (2004).

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1990s to UK labour markets. What other mechanisms are holding UK firms back? Another one that has been emphasised in the literature is skills, but which skills? Attention has focused on poor management skills – for example, Bloom, Sadun and Van Reenen (2006) showed that US firms operating in the UK are better able to exploit ICT than are UK-owned firms9 – but others may be relevant. Clearly, many questions remain to be answered.

IV. The retail sector

The retail sector is one of the largest sectors in the UK that is an intensive user of ICT. In particular, ICT is used to manage the supply chain, i.e. to ensure goods get to the right place at the right time. This sector of the economy accounts for a large part of the productivity gap between the UK and the US, for several reasons: it is a large sector, its productivity is low in the UK compared with both the US and France, and the retail sector has been responsible for a substantial part of the recent US acceleration in labour productivity (see Griffith et al. (2003) and O’Mahony and van Ark (2003)).

Figure 7 shows a similar picture of productivity to the one in Figure 2, but just for the retail sector. The series presented is value-added per hour

FIGURE 7 Value-added per hour in retail

Source: Groningen Growth & Development Centre, 60-Industry Database, October 2005, www.ggdc.net; updated from O’Mahony and van Ark (2003).

9See also Draca, Sadun and Van Reenen (2006) for a recent survey of evidence in this area.


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FIGURE 8 Number of new stores opened by Big Four supermarkets

(Asda, Safeway, Sainsbury and Tesco)

Source: Griffith and Harmgart, 2007. worked in the retail sector, and the latest figures show that in the UK this is about 65 per cent of that in the US or France.

Why does the UK do so poorly in this sector? Attention has focused on supermarkets, which are one of the larger components of this industry. One issue that has received a lot of attention in the UK has been land use regulations.10 Over the 1980s, the UK saw rapid growth in large out-of-town stores. Reforms to land use in the early to mid-1990s led to regulations that favour development of in-town sites. The concern has been expressed that regulations, particularly restrictions on large-format stores, have led to fewer new stores, which has meant slower adoption of ICT and new technologies, to more smaller stores, which has meant more stores below minimum efficient scale, and to less entry, which has meant less competition.

Commentary and evaluations of these reforms have largely considered data of the form shown in Figure 8. They have concluded that changes to the regulations have had a large impact on market structures.11 Figure 8 shows the number of new stores opened in England from 1991 to 2003 by the Big Four supermarkets (Asda, Safeway, Sainsbury and Tesco). The solid line shows the number of new stores over 30,000 square feet that have opened over the period. The Competition Commission (2000) estimates this to be

10See, for example, McKinsey Global Institute (1998), HM Treasury and Department of Trade &

Industry (2006) and Griffith and Harmgart (2005). 11See, for example, Office of the Deputy Prime Minister (2004).

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minimum efficient scale for supermarkets. Looking at the period before the planning regulation reform, the number of big stores opening averages about 55 per year; after the reform, the number drops to around 35 per year. The dashed line shows the number of small stores that have opened. There is a rapid acceleration in the opening of new small stores, particularly after the reform. These new stores are mainly the new-format convenience stores – Tesco Metro/Express and Sainsbury Local.

Griffith and Harmgart (2007) considered the impact of planning regulations on market structures in the grocery retail industry and in particular considered the fact that other things have also changed contemporaneously with reforms to regulation. In particular, there have been demographic changes that may have led to differences in consumer behaviour, which may have driven the diversification into the smaller store format. Note, for example, that Tesco started the expansion of the Metro and Express brands before the reforms. Griffith and Harmgart incorporated planning regulation into an equilibrium model of firm entry and showed that the impact of regulation on equilibrium market structures is overestimated if these other factors are not accounted for. In order to identify the impact of planning regulations, the paper used variation across local authorities in their economic plans and the way that they were implemented, as well as variation in demographics across towns in the UK. This work shows the importance of embedding evaluations in economic models of behaviour: failing to do so can give a very misleading picture.

What are the policy implications of this work? It shows that planning is not as important a determinant of store size as a look at the raw data would suggest, but that does not mean that small average store size is not an important reason for labour productivity figures being low. However, if the reasons for small store size are due to consumer preferences rather than regulatory constraints, then this does change the policy implications. Also, it is worth emphasising that this does not mean that planning regulations should not be reformed. However, we should not necessarily expect these reforms to lead to rapid productivity growth in the retail sector. Recent figures from the Better Regulation Executive (Cabinet Office, 2006) show that after corporation tax, planning regulation has the highest administrative and compliance costs of any regulation.

A final point to make is that Tesco is a high-productivity firm and it has invested intensively in ICT. But it uses that ICT differently from Walmart. For Tesco, it is about keeping the small Tesco store in central London stocked, not about managing trucks driving long distances across the Mid-West.

Another indicator of how well retail markets are functioning might be prices. If productivity were very low, we would expect to see that reflected in prices. Generally, less-productive firms are expected to charge higher


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prices, because they face higher costs. This is related to the other main concern about the retail sector, which is the state of competition. There have been a number of government inquiries of different forms into the supermarket sector, including repeated competition investigations. Widespread concern has been expressed that the largest supermarket chain, Tesco, has a market share of over 30 per cent, which is nearly double that of the next biggest firm, Asda. Also, consumers’ perceptions seem to be of high prices – for example, a recent survey carried out by the consumer group Which? (2006) suggested that seven out of ten people in the UK thought that food shopping was more expensive in the UK than in the US. However, by taking the retail price index for food in the UK relative to the general retail price index, and comparing it with the same index for the US, Figure 9 shows that the relative price of food has fallen by much more in the UK than in the US. This is partly driven by the fact that the price index for other items has risen faster in the UK than in the US, but also by the fact that food prices have risen at a slower rate in the UK than in the US.

This is also the case for many other retail goods, such as clothing. But it does not tell us about the price level, which turns out to be quite a difficult comparison to make. Over the last few years, colleagues and I at IFS have built up data that are allowing us to understand the behaviour of consumers and firms in the grocery market. Working with colleagues in the US, we are attempting to understand the extent to which differences in consumer behaviour between the two countries may help to explain differences in firm

FIGURE 9 Relative price index for food a

aPrice index for ‘food’ divided by price index for ‘all items’. Source: Griffith, Leicester and Nevo, 2007.

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TABLE 2 Average annual expenditures and volumes purchased per household

US spend ($)

US volume (oz)

UK spend ($)

UK volume (oz)

Relative ‘price’

(UK/US) Cereal 70.73 487 59.91 525 0.78 Jams and spreads 17.56 170 13.21 130 0.98 Pasta 10.69 178 9.72 156 1.04 Tea 7.60 61 25.98 117 1.77 Source: Griffith, Leicester and Nevo, 2007.

performance. The data are based on large representative panels of household expenditures in each country.

Griffith, Leicester and Nevo (2007) compared total expenditure on food over a year across different types of households in the UK and the US. So far, we have found that total expenditure is remarkably similar between the two countries. We can compare expenditure per volume purchased, which is like a price, for individual goods. For example, Table 2 shows expenditures and volumes purchased for four goods – cereal, jams and spreads, dried pasta, and tea. The first column shows total average annual expenditure on each good by US households. The second column shows the average annual volume purchased. So US households spent on average $70.73 on cereal and bought 487 ounces. In contrast, UK households spent $59.91 and purchased 525 ounces. By calculating the average unit price for cereal in the two countries and comparing them, the final column shows that the price paid by UK consumers is around 78 per cent of the price paid by US consumers. The prices for jams and spreads and for pasta are around the same in both countries, while UK consumers buy much more tea and pay more for it. Relative prices vary quite a bit for individual goods, but overall the prices look quite similar; if anything, it looks as if prices in the US are higher, but this is still work in progress.

Of course, there are many reasons to be wary of comparing price levels – for example, differences in taxes and many other factors may affect the levels, and further consideration needs to be given to what effect these will have. However, if the figures quoted above prove accurate, then the similarity in prices is remarkable, given that consumer behaviour in fact varies substantially between the two countries: UK consumers shop more frequently (about twice as often), buy smaller amounts when they do shop (maybe because they have less storage space in their houses), buy smaller pack sizes and buy less often on sale.12 All of these factors suggest that UK consumers would pay higher prices, but they seem not to. So in ongoing work, we are seeking to understand better the links between consumer

12Figures from Griffith, Leicester and Nevo (2007).


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behaviour and firm behaviour and how they differ between the two countries.

What are the policy implications of this work? When we compare two indicators of industry performance – the relative levels of output per hour worked and relative food prices – between the UK and US, they do not seem to indicate the same thing, which is puzzling. The relative levels of output per hour worked show that the UK has failed to keep up with US levels of growth, while an initial look at relative food prices suggests that if anything prices have fallen in the UK relative to the US. There are numerous measurement issues, but there are also questions about whether US levels of output per hour are achievable and/or desirable for the UK, i.e. are the differences driven by market failures that can be addressed by government policy, or by market outcomes in response to other factors such as differences in consumer behaviour?

V. Final comments

To finish, it is interesting to return to where we started. A central objective of government policy has been to close the gap in labour productivity. The ideas that this should be a central target, and that it is an achievable target, are well founded in standard growth theory. In the Solow model of growth, we expect to see convergence in labour productivity. The puzzle then is what factors are stopping the UK converging to US levels. In this paper, we have emphasised that in trying to answer this question, it is important to consider micro policies. In order to understand which policies are likely to have an impact, it is important to evaluate policies in the context of a well-formulated model of economic behaviour to understand the mechanisms at work; for this, we need careful modelling of the behaviour of firms, workers and consumers. We have also emphasised that technology adoption and diffusion are at least as important as knowledge creation. In addition, it is worth pointing out that we tend to focus on comparisons between the UK and the US, but comparisons with France and other countries may also be interesting and informative. One reason why France may have higher levels of productivity is likely to be lower participation rates, but is this the only reason?

But to end, we may want to ask a bigger question: ‘Is closing the gap achievable?’. The expectation that labour productivity should converge across countries comes out of standard growth models; it does not stand up to many of the newer growth models that relax various assumptions about the returns to capital, the role of human capital and the idea that there is one common world production function. But how important is heterogeneity across countries in underlying fundamentals, such as consumer preferences

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and endowments (for example, land)? It may be that convergence to the US level is not in fact an achievable target.

References

Abramovsky, L. and Griffith, R. (2006), ‘Outsourcing and offshoring of business services: how important is ICT?’, Journal of the European Economic Association, vol. 4, pp. 594–601.

— and — (2007), ‘ICT, corporate restructuring and productivity’, Institute for Fiscal Studies, mimeo.

—, — and Harrison, R. (2005), Background Facts and Comments on ‘Supporting Growth in Innovation: Enhancing the R&D Tax Credit’, Briefing Note no. 68, Institute for Fiscal Studies, http://www.ifs.org.uk/bns/bn68.pdf.

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