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Home Opinion Perspectives on industrial policy for the global age
Industrial Policy • Economy • Technology

Perspectives on industrial policy for the global age

Alan Hughes - 12 February 2015

In the technological and globally competitive context it must now operate in, it is a mistake to view selective industrial policy as ‘picking winners'

After decades in the policy wilderness industrial policy has returned to the fold. In the UK and elsewhere in the aftermath of the financial crisis policymakers have resurrected industrial policy pursuit of rebalancing the economy away from financial services. This resurrection implies selective identification of support for specific sectors and increasingly particular technologies. Key questions are how this will be achieved and what will determine whether selective policies will succeed in meetings their objectives.

Industrial policy support went out of fashion because of the belief that selective policies in the 1970s (often labelled ‘picking winners’) led to a set of policies which were bad for competition, wasted public sector resources and were ineffective. The charge was made that losers picked policy support rather than policy support picking winners. Membership of the EU also meant that national industrial policy became increasingly restricted because of the potential distortion on intra-EU competition of any policy that sought to selectively support sectors in an individual member state. The decline of industrial policy went alongside a growing emphasis on ‘non-selective’ horizontal policies affecting broad classes of businesses such the promotion of competition, support for entrepreneurship and small firms and a new interest in technology and innovation policy. This was increasingly marked by an emphasis on the potential role that the publicly funded science base could and should play in the promotion of productivity and output growth.

The technological and globally competitive context in which industrial policy must now operate is, however, strikingly different from the world of the 1970s so the lessons to be learned for that era are less important than understanding the challenge of the new context. Two factors, in particular, are important here. The first is the increased globalisation both of competition and of the distribution of activities of multinational corporations across national boundaries. Businesses choose the different stages of production in their value chain to be located where it is competitively advantageous to do so. This has led to a general trend towards the move of manufacturing and fabrication activities away from relatively high-cost high-wage cost economies such as the EU and the US to China, India and elsewhere. Moreover, this has been associated with a very rapid growth in what may be called ‘vertically specialised trade’ in which the import content of exports has increased. This makes outcomes of sectoral policy in terms say of improving the trade balance more complex to predict since exports increasingly suck in imports.

This increased importance of vertically specialised trade is associated with a so-called ‘second unbundling’ of vertically linked stages in production. These arise from rapidly falling communications costs and the pervasiveness of information-communication-technology solutions to dispersing production stages that previously had to be performed in close proximity. This contrasts with the first unbundling based essentially on falling transport costs linked to steamships railways and the telegraph. The ability, for example, in the second unbundling to digitally transmit designs for production to a separate location has increased the extent to which the whole production process from R&D and design through manufacturing/fabrication and the marketing of the final product can be diced and sliced across different national boundaries. Identifying sectors for industrial policy support is now less important than focussing on the different stages in the overall production process in which an economy such as the UK can have or develop a comparative advantage.

This means that policy must be based on a sophisticated understanding of these global value chains. It includes in particular the identification of those sectors where a regular and steady flow of information and feedback between, for example, research and development, product design and manufacturing is enhanced by close proximity. These connections may be particularly important where there is rapid innovation in the processes by which new products are developed and productivity evolves. Thus, for example, in biotech drugs, super-miniaturised assemblies or advanced semiconductors, where processes are changing rapidly, there is a significant advantage in integrating R&D and manufacturing. The physical separation of these may be a hindrance to rapid progress. Identifying which sectors and technologies gain competitive advantage from national, regional or locally clustered activity is an important task in developing an effective industrial and technology policy.

These contextual factors against which the new industrial policy must be developed means that policymakers face significant challenges. These challenges arise in terms of the informational content required to derive effective policies. They also arise from the need to develop efficient governance and organisational structures to implement effective policy.

The informational content required to understand the policy challenge and respond to it requires a deep engagement with the industrial players themselves and effective ways of incorporating that knowledge into policy development. This may take the form of foresight exercises linked to particular technologies or sectors. These scan future potential developments and practical policy steps to resolve them. They also address the ways in which new organisational forms may be developed to bridge the gap between potential players in the development of technologies towards different industrial uses. In this area the increased emphasis in the UK, for example, on intermediate technology organisations such as the Catapult programme is an example of this policy-learning process. The potential for the capture by special interest groups of policy arising from close engagement with key players makes it imperative, however, that policy development and design be as transparent as possible.

The increasingly uncertain and risky nature of strategies based on emerging technologies and their potential application in particular sectors and elements in the value chain or across many sectors means that policy must also acknowledge that failures will and do occur. There will be many ‘honourable dead ends’. Policy should be seen to clearly incorporate the cessation of support when these dead ends are reached. Government policy should be more like the approach of a venture capitalist (but with a longer-term perspective than that typically implies). The venture capital element is the requirement to see policy not as ‘picking winners’, but as ‘placing bets’ on new technologies or ‘choosing technological races’ to enter. Initial support gives an option to place further bets on those technologies that emerge as successful and stop backing the losers. This technological perspective needs to be married to an approach that seeks to identify sectoral value chain pull through of emerging technologies. This will include the public sector as a potential purchaser of goods and services, including technological services from the science base, and the private sector.

The overall framework for policy development outlined here is captured in the diagram below:



(© Alan Hughes)

This emphasises the need for a patient long-term approach by showing across the top of the diagram the number of years which it may take for a new idea emerging from research to find its way into final production. It also shows the extent to which a ‘holistic policy’ to support this process encompasses science policy, technology policy-innovation policy as well as what was previously thought of as ‘old’ industrial focusing primarily on industrial sectors.

The long-term, uncertain nature of policy support is captured by the funnel in the middle of the diagram with multiple feedback loops as technologies emerge and develop in a non-linear fashion. This illustrates the extent to which areas and technologies for support will be winnowed down as lessons are learned in the development process and honourable dead ends are encountered.

The bottom half of the diagram attempts to summarise the imperative to think about policy from both a technological push and a sectoral pull perspective. It emphasises, in particular, language based around ‘placing bets’ and ‘choosing races’ rather than the tired rhetoric of ‘picking winners’ which characterised earlier critiques of industrial policy.

The importance of organisational and institutional design is captured in the box in the middle of the bottom section of the diagram. This emphasises industrial policy as a process of selecting options; the need to understand value chains; the relevance of proximity; and the importance of institutional design and government capacity. It also contains the term ‘diffusion’ to represent the importance of spreading new technologies across sectors (and across firms within sectors).

The return to the fold of industrial policy is an important development but places major burdens on the public sector and its involvement with the private sector if it is to be successful. It is a matter of great concern that, at the time that industrial policy is emerging from the wilderness, the departments tasked with implementing it must do so with falling resources in real terms.

Alan Hughes is Margaret Thatcher Professor Emeritus of Enterprise Studies at Cambridge Judge Business School at the University of Cambridge. He is also director of the UK Innovation Research Centre, a joint venture between the Centre for Business Research at Cambridge Judge and Imperial College London

For a fuller exposition of the arguments outlined here see Crafts, N. and Hughes, A. (2013) Industrial Policy for the Medium to Long Term

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