Innovation, Intellectual Property, and Economic Growth

Innovation, Intellectual Property, and Economic Growth
Lecture outline: Overview of course Introduction to innovation Definitions Nature of innovation Microeconomics Questions Readings

Overview of course Details of course Teaching Resources Assessment

What is course about? Applying economic analysis to the understanding of the innovative process Determinants Consequences Market failure (are optimal resources devoted to innovation) Some key questions What drives innovation? How does intellectual property influence innovation? Which market structures yield more or better innovations? Why are some countries rich and some poor? Is economic regulation good or bad for innovation?

What is the ‘economics of innovation’?
Microeconomics – understanding processes, including how incentives affect firms Macroeconomics – ‘innovation’ drives economic growth.. and economic growth drives living standards, environmental, political… Economic Policy – are there market failures in the innovation process and what, if anything, should the government do? Business Strategy – this is not a course on advising firms how to innovate, but does include some insight into this

Definition of innovation
Basic definition Introduction of new ideas that add ‘value’ to a firm’s activities OECD The Oslo Manual (1997, p.28) introduction of a new product or a qualitative change in an existing product process innovation new to an industry the opening of a new market development of new sources of supply for raw materials or other inputs changes in industrial organisation

Innovation and business
Some students may benefit from a brief comment on why innovation is so important to business Some example of quotes "Business has only two functions, innovation and marketing." Peter F Drucker “Creativity is thinking up new things. Innovation is doing new things.” Theodore Levitt (management guru) Innovation distinguishes between a leader and a follower.“ Steve Jobs

The innovation process
Figure 1.1 Greenhalgh and Rogers (2010)

Invention, Innovation, Diffusion (Schumpeterian trilogy)
Invention: creation of an idea to do or make something (profitability not yet verified) Innovation: new product/ process commercially valuable i.e. successfully developed inventions. Diffusion: the spread of a new invention/innovation throughout society or at least throughout the relevant part of society. Without this cannot gain full benefits Some of this represents ‘spillovers’ or ‘positive externalities’

Scientists, Knowledge and Technology
Discover knowledge by research Disseminate knowledge (open science?) Knowledge is public good(non-rival in use), hence created externalities Universities, government labs, some large firms It may represent the basis for technological advances Technology Application of knowledge to ‘production’ Firms driven by profit incentive Private good: investment (R&D) projects, appropriate, use of intellectual property

Product and process innovations
Product innovations product used by consumers Microwaves, computers, mobile phones, etc Products use by firms Shipping containers, computers, robots, etc Process innovations Used by consumers Fast food, air travel Used by firms Assembly lines, software

Defining an innovation
Can be defined as new to Firm Market (industry) World No universal agreement of which Radical vs incremental Radical (steam, internal combustion engine, computers, internet) Incremental (constant improvements) Both important in driving economic growth

Further ideas Can extend the introduction by considering
Further examples of specific innovations, including cases studies of famous innovations Look at country / state / city comparisons of innovativeness Can provide overview of productivity, economic growth, etc

Microeconomic effects of innovation
Following slides could be part of introduction or separate lecture Can expand formality of this topic, including introducing maths-based questions relating to consumer surplus changes, optimal subsidies, public goods

Figure 1.2 Process innovation in perfectly competitive market

Figure 1.3 Process innovation for a monopoly

Figure 1.4 New product demand curve

Figure 1.5 A product innovation represented by a shift in existing demand curve

Innovations and Market Failure
Innovation as a public good Non-rival and non-excludable Externalities from innovative activity R&D spillovers Indivisibilities, uncertainty, and capital markets Fixed costs, uncertainties Do capital markets cope with these? Patent races and duplication

Restoring incentives to invent and innovate
Public provision of a public good Club provision of a local public good Pigovian subsidies Definition of property rights The trade-off between incentives and monopoly power

Subsidies for R&D

Questions for discussion
How would you distinguish between an invention and an innovation? What are the key characteristics of a public good? Is all new knowledge a public good? What is a positive externality? How does this differ from a public good? How does innovation create positive externalities? Why are they a problem? What are the key market failures surrounding investment in innovation? Does the creation of intellectual property rights help or hinder the markets for innovative goods and processes?

References Key textbook for this course is
Greenhalgh, C and Rogers, M (2010) “Innovation, Intellectual Property and Economic Growth”, Princeton University Press For this week read Chapter 1 Future lectures will follow each of the chapters of the book Additional articles will be given each week

Nature and role of intellectual property
Lecture outline: Introduction to the topic Why are Intellectual Property Rights awarded? Main types of intellectual property Patents Trade marks Designs and utility models Copyright Alternatives to IPRs Questions for discussion

Introduction Range of issues can be discussed, including
Historical development Recent controversies (see Chapter 11 and/or)

Why are patents awarded?
Incentive to invest in innovation Note: invention may occur without monetary incentives (due to human curiosity), but an innovation requires investment Patents balance the need to provide incentives with the introduction of market failure (i.e. high prices of non-rival good) Have patent protection for up to 20 years, then knowledge/innovation can be exploited by all

Illustrating the role of patents
Figure 2.1 shows a drastic process innovation Patent owner now has monopoly (sets high price compared to marginal cost, and restricts quantity) BUT, price is lower than previous price (pre-innovation), hence society wants innovation. Society would also like lower prices (P=MC), and this happens when patent protection expires (normally after 20 years) Note: the above logic applies for all product and process innovation, but easy to illustrate with drastic process innovation

Figure 2.1 A drastic process innovation

Patents What can be patented? How to get a patent?
Dimensions of patent Markets for patent rights Who uses patents most? (Above are sub-headings in Chapter 2 and summary of material can be found there) May also want to illustrate some famous patents and/or specifics of own country (see below for sources)

Top patentees at US Patent Office and European Patent Office
Top patentees at US Patent Office and European Patent Office US Patents (grants) 2006 EPO (grants) IBM 3,621 Phillips 4,425 Samsung 2,451 2,355 Canon 2,366 Siemens 2,319 Matsushita 2,229 1,529 Hewlett-Packard 2,099 BASF 1,459 Intel 1,959 LG Electronics 1,214 Sony 1,771 Robert Bosch 1,093 Hitachi 1,732 1,088 Toshiba 1,672 Nokia 882 Micron 1,610 General Electric 768

Further information on patents
US: UK: European Patent Office: World IP Office: Patent scoreboards (national offices and also There are many on-line resources, including free patent searches (e.g.

Trademarks What can be registered? How is a trademark obtained?
Length, breath and geographical coverage Markets for trademarks Who uses trademarks most? (Above are sub-headings in Chapter 2) Further information can be found at national IP office web-sites. Note also that ‘brands’ are worlds most successful trademarks (see : or BrandFinance)

Top trademarkers in the US and Europe
Mattel 639 Glaxo 154 Deutsche Telekom 429 L’Oreal 138 Novartis 134 135 American Int’l AIG) 126 El Corte Ingles 127 Disney Enterprises 120 Barilla G. e R. Fratelli Società per Azioni 115 Proctor and Gamble 117 Bristol-Myers Squibb 106 Mars 101 105 IGT 96 Viacom International 104 Beautybank 93 Lidl Siftung 87 US Trademarks (registered) 2006 EC trademarks (registered) Nedboy, Robin 90 Sony 76

Proportion of firms applying for IPRs by sector (large firms in UK,1996-2000)
No. firms in sample U.K. Trademarks Community U.K. Patents EPO Patents 1 Agriculture/Mining 67 0.19 0.12 0.21 2 Manufacturing 640 0.67 0.55 0.40 0.35 3 Utilities 26 0.85 0.62 0.50 0.42 4 Construction 89 0.39 0.22 0.09 5 Finance 191 0.52 0.26 0.05 0.06 6 Real Estate 112 0.03 0.01 7 Wholesale 181 0.33 0.07 8 Retail 132 0.75 0.08 9 Hotel/Catering 54 0.65 0.00 10 Transport/Comm. 115 0.57 0.43 0.10 11 Bus. Services 259 12 Other Services 188 0.56 0.37

Other IPRs Designs and utility models Copyright (see section 2.6)
- Section 2.5 discusses these - Next table illustrates use of designs Copyright (see section 2.6) Copyright, and specifically the file sharing issue, may be a key issue for students Hence, could be that copyright issues is developed in separate lecture and/or as an assignment (some readings for students at end of lecture outline)

UK Top Ten IPR Scoreboard 2003
UK PATENTS UK TRADEMARKS UK DESIGNS NEC 209 GLAXO GROUP 118 ORIENTAL WEAVERS 90 HEWLETT PACKARD 196 UNILEVER 104 TY INC SAMSUNG 177 NATIONAL LOTTERY 87 MAINETTI 72 SCHLUMBERGER 172 BRITISH TELECOMS 82 KEEL TOYS 47 IBM 171 ICI 80 NIKE 44 BAKER HUGHES 120 WESTWOOD CONSULTING 59 WITHIT 38 ERICSSON 115 EMBRAER AERONAUTICA 58 MAYFAIR BRASSWARE 34 MOTOROLA 113 BOOTS 46 BLACK AND DECKER 33 VISTEON GLOBAL TECH. 112 GLAXOSMITH- KLINE BIO. 42 NOKIA CORP FORD 100 AVON PRODUCTS 40 DEVONSHIRE STATUARY 30

Further questions about IPRs
Is patenting always the best route to protection? Secrecy vs. disclosure. Trade secrecy law Optimal patent length Box 2.1 uses some formal analysis. This can be extended and/or used for maths-based problem. See references in box. Alternatives to IPRs? This is only briefly covered in Ch. 2, but extended in Ch. 11. Should alert students to this issue. Could use as on-going assignment through course.

How does intellectual property differ from tangible property, such as a house or a car? Do patents provide socially optimal incentives? Why do firms use trademarks? Should copyright be made shorter or longer than at present? Why do different industries make use of different types of rights? What factors influence the optimal length of an intellectual property right?

References General: Landes, W. M. and R. A. Posner (2003), The economic structure of intellectual property law, Boston: Belknap/Harvard University Press. HM Treasury (2006), Gowers Review of Intellectual Property, Norwich: The Stationery Office. Lerner, J. (2002). "150 Years of Patent Protection." American Economic Review 92(2): Hall, B. (2007). "Patents and Patent Policy." Oxford Review of Economic Policy 23(4): Copyright: Corrigan, R. and Rogers, M. (2005), ‘The economics of copyright’, World Economics: The Journal of Current Economic Analysis and Policy, 6(3), Lessig, L. (2004). Free Culture: How Big Media Uses Technology and the Law to Lock Down Culture and Control Creativity. London, Penguin Press. Boyle, J. (2003). "The Second Enclosure Movement and the Construction of the Public Domain " Law and Contemporary Problems 66(Winter-Spring):

Measurement of innovation, productivity and growth
Outline: How can innovation be measured? Illustrations of innovation statistics Productivity at the firm, industry and economy level Comparing productivity and growth across countries

Introduction The basic motivation for this chapter is to convey to students that innovation and its implications can be measured and analysed There are many problems in this process, but this is true across all of economic policy Without measurement & analysis, understanding and policy will be based on rhetoric, anecdote and lobbying Since ‘innovation’ is defined as ‘new ideas that add value’, this automatically means that innovation is driving force behind growth Clearly some authors think of technology, or human capital, as driving growth. These are discussed more in Chap 8, but essentially these are different perspectives on the same process. We argue that ‘innovation’ is a better generic term.

How can innovation be measured?
Surveys Chapter discusses Community Innovation Survey (CIS), but lecturer may be able to access local/regional/national examples Input measures R&D is main measure (see next slide) Output measures Patents and other IP Ultimately, productivity and growth are the outputs Note that Innovation Indexes tend to mix up inputs and outputs in very ad hoc way

% of firms involved in innovative activities, CIS 1998-2000
Innovative Activities (%) Product innovation New-to- market product innovation Process innovation Belgium 50 40 14 31 Denmark 44 37 19 26 France 41 29 10 21 Germany 61 42 13 34 Italy 36 25 Sweden 47 32 12 20 UK 6 17

R&D This discussion of R&D is extended in Chap. 4
It is possible to extend this discussion here by Focusing on national trends, industry breakdowns and specific firms In most countries there are a few major companies that dominate absolute amount, but amount done by smaller companies may be very important for future growth Specific R&D policies (see later discussion in Chap.11 section 11.3) Problems of compiling real R&D measures and cross country measures

R&D – (OECD Frascati Manual)
Basic Research: experimental/ theoretical work undertaken primarily to acquire new knowledge of the underlying foundations and phenomena and observable facts, without any particular application or use in view Applied Research: original investigation undertaken in order to acquire new knowledge , directed primarily towards a specific practical aim or objective Experimental Development: systematic work, drawing on existing knowledge gained from research and practical experience, directed to producing new materials, products and devices; to installing new processes, systems or services; to improving substantially those already produced or installed. Science Technology

R&D in Europe, Japan and the United States (2003, or 2002*)
Country R&D/GDP % Value of R&D (millions of euros) Annual Growth of R&D (%) EU15 1.99* 149,231 4.31* EU25 1.93* 154,941 3.98* Germany 2.50 43,507 2.70 France 2.19 27,727 2.36 UK 1.87* 23,314 3.52* Japan 3.12* 87,968 2.18* USA 2.76 227,030 2.69

R&D personnel in Europe and Japan (2004, or 2003*)
Country R&D personnel/ labour force % R&D personnel (in FTEs) Share working in BES % in GOV % in HES % EU25 1.49 2,040,667 53.7 14.3 31.0 EU15 1.59 1,867,505 56.2 13.2 29.5 Germany 1.85 469,100 63.5 15.3 21.1 France 1.71* 346,078* 55.8* 14.8* 27.5* Japan 1.66* 882,414 65.8 7.0 25.4

Patent applications by domestic residents by country (RH scale: US & Japan)

Trademark applications by domestic residents by country (RH scale: US & Japan)

Productivity and growth
To measure real output we use value added Value added is defined as sales minus raw materials used Indicates what the firm has truly produced when transforming the raw materials into the final product Both sales and raw materials have to be deflated for any price inflation when measuring over time Definitions of partial factor productivity: labour productivity (value added per unit of labour) capital productivity (value added per unit of capital) High labour productivity is often largely explained by high levels of capital per worker (e.g. in mining and the steel industry) High capital productivity will be present when labour is used intensively (e.g. in developing countries with scarce capital)

Measuring total factor productivity
This measure improves on partial factor productivity by correcting for growth in inputs Derivation of total factor productivity: Suppose value added (Y) is produced by two input factors capital (K) and labour (L) and by total factor productivity (A) according to: Y = A K a L b Then growth of TFP is calculated by residual: gA = gY – a gK – b gL Growth in TFP is equal to the growth in value added, less a times the growth in capital input and b times the growth in labour input

Annual average growth in GDP per hour worked (1970-2006)
Australia Canada France Germany Italy Japan UK US 1.5 1.8 4 3.7 4.2 2.7 1.6 2.2 3.1 2.1 1.2 2.5 0.2 0.4 2.3 1.4 1.3 2 1.9 2.9 2.8 1.1 0.9 1 2.6 3 1.7

Average growth of GDP per capita in emerging markets
Brazil China India Japan Korea Taiwan Thailand 3.93 4.11 1.57 7.54 1.03 4.44 -0.15 4.34 1.45 2.69 9.74 5.82 7.04 5.07 5.38 4.18 1.61 3.18 5.93 7.75 4.62 0.21 8.43 3.48 3.43 7.90 6.59 6.08 0.53 9.15 3.41 1.01 5.19 5.49 3.03 0.09 7.44 4.19 0.72 4.09 2.16 3.97

Other economic growth resources
There is a vast amount of productivity and economic growth data on web that could be used to look at specific countries, periods or industries e.g. National statistical agencies World Bank, OECD (includes regular country studies), IMF The Groningen Growth and Development Centre Penn World Table

Possible additional topics
There are a large number of other areas that can be mentioned, or developed, in a course, including: Service sector productivity (e.g. Bosworth, B. and J. Triplett (2003). "Productivity Measurement Issues in Services Industries: "Baumol's Disease" Has Been Cured." The Brookings Institution, September 1. IT and productivity (e.g. Triplett, J. E. (1999). "The Solow Productivity Paradox: What Do Computers Do to Productivity?" Canadian-Journal-of-Economics 32(2)(April 1): Regulation and productivity (e.g. Crafts, N. (2006). "Regulation and Productivity Performance " Oxford Review of Economic Policy 22(2):

Questions List the input, and output, measures of innovation. How should one deal with so many possible measures? “R&D is the only important measure of innovation”. Discuss. Choose a selection of firms, or countries, and attempt to produce a ranking or innovation scoreboard. What is meant by partial productivity measures? Should only total factor productivity be used? What measurement issues should be considered when comparing GDP per capita across countries? What about when comparing GDP per capita through time? What is the use of growth accounting studies?

References Griliches, Z. (1990) ‘Patent statistics as economic indicators: a survey’, Journal of Economic Literature, XXVIII (December), Lipsey, R. G. and K. I. Carlaw (2004), 'Total factor productivity and the measurement of technological change', Canadian Journal of Economics, 37(4), Schreyer, P. and D. Pilat (2001) "Measuring Productivity“, OECD Economic Studies 33: 128. The Economist (14 Nov. 2009) Economic Focus: ‘Secret Sauce’.

The National Innovation System
Outline Introduction Defining the national innovation system Central role of R&D The tripod Government Business Universities NIS in emerging markets

Introduction This chapter sets out the complex interrelations concerning innovation in an economy. Discuss ‘science-base’ and ‘knowledge economy’ Business does not stand alone, government and universities are integral part of innovation system Research and development (R&D) is investment spent both to develop new ideas and science and to transform them into commercial innovations Chapter illustrates these ideas with data from OECD and, at end, with emerging market examples

Definitions National system of innovation
“The national innovation system essentially consists of three sectors: industry, universities, and the government, with each sector interacting with the others, while at the same time playing its own role.” Goto (2000, p. 104) Also called Triple Helix model, there are a number of ways to discuss/define basic idea but note: national innovation system is a complex conglomerate of interacting independent parties

Roles of the three players
Universities – undertake basic science and technology research – educate scientists and technologists needed by business and government Governments – design IPR system for business and universities – commission science research e.g. for defense – finance universities, subsidise business R&D Business – conduct R&D to develop commercial products – launch innovative products – start up new firms to exploit new science

The central role of R&D Lecture 3 has begun the discussion of R&D by giving the definitions and showing some aggregate measures Next three tables illustrate breakdowns: Who funds R&D? Where is it conducted? What are main subjects for research? Note variations across countries in these tables. Other sources of data include: National statistical offices OECD

Table 4.1 Funding of R&D by government and business
Country R&D/GDP in 2004 funded by GOV in 2005 GOV R&D / Total R&D x 100% % of R&D BES in 2003 EU25 1.86 0.74 39.8 54.3 EU15 1.92 0.76 39.6 54.6 Germany 2.49 30.5 67.1 France 2.16 0.94 43.5 50.8 UK 1.79 0.73 40.8 43.9 Japan 3.20 0.71 22.2 74.5 USA 2.66 1.06 61.4

Table 4.2 The conduct of R&D by business, government and universities in 2003
Country R&D/GDP conducted by BES by GOV by HES Sum of columns 1 to 3 Total EU25 1.22 0.25 0.41 1.88 1.90 EU15 1.26 0.42 1.93 1.95 Germany 1.76 0.34 0.43 2.53 2.52 France 1.37 0.36 2.15 2.18 UK 1.24 0.18 0.40 1.82 Japan 2.40 0.30 0.44 3.14 3.20 USA 1.86 0.33 0.37 2.56 2.67

Table 4.3 Percentage allocation of government R&D support by objective in 2005
Country Land Health Energy Industry University Defence All Other EU25 9.6 7.3 2.8 10.9 32.0 13.6 24.0 EU15 9.3 2.7 32.4 13.8 23.8 Germany 8.9 4.4 2.9 12.4 40.3 5.8 26.0 France 6.5 6.1 4.5 6.2 24.8 22.3 29.5 UK 8.5 14.7 0.4 1.7 21.7 31.0 22.0 Japan 10.3 3.9 17.1 7.1 33.5 5.1 23.0 USA 22.8 1.1 .. 56.6 14.6

The Government-University Axis
Knowledge is a public good (non-rival), hence market mechanism alone cannot generate optimal amount Government funding of university research, and government research labs, are main solutions in modern economies Discussion of historical origins (including your own university/college role in science) Funding mechanisms – is there an optimal one?

Changing provision of basic science for knowledge economy
Historical system: Provision of basic science as a public good Discoveries were placed in the public domain without any private ownership Motivation of scientists was respect of scientific community or ‘peer review’ Use of science base open to all types of business Recent changes: Government finance for research is conditional on the research having more immediate application in industrial and commercial products

The University-Business Axis
University-business links - many dimensions: IPRs held by university Research joint ventures Spin-outs/start-ups Personnel pooling Growth of university IPRs US Bayh-Dole Act 1980 stimulated change Before - government owned any patents on federally funded science and then issued non-exclusive licences After – university/scientists own IPRs and can licence exclusively to key firms Often achieved via technology transfer offices (TTOs) Many EU countries have followed these changes

University-Business Linkages
Collaboration in Research Joint, contract, and commissioned research, Consultancy by academics Spin-outs, Start-ups, Science Parks Formation of spin-outs and joint ventures Formation of university incubators Growth of science parks near to university Personnel Linkages Formal and informal social and professional networks Continuing professional development and education, including public university lectures and workshops Academic-scientist exchanges with firms Recruitment of students from universities by firms

The Government-Business Axis
Key areas of innovation policy: IPRs - the enforcement of IPRs can be influenced by national policy, as is legislation to some extent Tax policy - corporate tax policy can affect innovation in various ways; key areas include R&D tax concessions, rules surrounding IP, and venture capital Competition policy - the stance of competition policy matters, especially when decisions involve innovation (e.g. a firm has a dominant market position but also leads the industry in terms of innovation)

Further key areas of innovation policy:
Government-business targeted funding – can be of specific research areas, technology development and small business Standard setting - government is involved in setting various standards for measurement, performance, safety, testing and interoperability Procurement policies - as a large purchaser of goods and services, the government can influence business activity (e.g. its decisions about purchasing computers)

National Innovation Systems in Emerging Markets
South Korea and Taiwan: - 50 years ago both were poor countries - Their governments promoted research and technology setting up important university research institutes - Firms were encouraged to do R&D - Initial approach was reverse engineering and technology transfer from the rich world - Later graduated to developing world class innovations China and India: - Began with large populations but small % highly educated - China has encouraged FDI and technology transfer - India less open, but in 1990s expanded higher education - Indian firms have focused on pharmaceuticals and software

Patenting, national innovation systems and performance
Emerging countries have taken different routes for acquiring and developing technologies Catching up through technology transfer precedes the stage of becoming innovators Big differences in US patent applications by emerging economies in last 20 years (next slide) Korea and Taiwan show rapid growth since 1990 China is also beginning to emerge as an innovating country after 2000 India slower growth in IPRs due to narrow range Brazil, Mexico and Russia very low figures

US patents granted to firms from emerging economies
Country 1987 1990 1995 2000 2005 2006 2007 BRAZIL 35 45 70 113 98 148 118 CHINA 23 48 63 162 565 970 1235 INDIA 12 38 131 403 506 578 KOREA 105 290 1240 3472 4591 6509 7264 MEXICO 54 34 100 95 88 RUSSIA 99 185 154 176 193 TAIWAN 411 861 2087 5806 5993 7920 7491

Questions Identify the three main partners within the NIS. Should they play complementary or competing roles in generating innovation? What are the main ways in which universities and private businesses interact? Is it a good idea for university science departments or individual academics to patent their scientific research findings? If universities do patent, should they offer licenses to one or more firms? How much should the licences cost? Should government regulate these activities? In public/private partnerships, is the presence of government a 'dead hand' or a necessary catalyst for innovation? Discuss the role of government in supporting the NIS in emerging economies. Do national statistics on the number of patents tell us anything important?

References Freeman, C. (1995), 'The National System of Innovation in Historical Perspective', Cambridge Journal of Economics, 19: Goto, A. (2000), ‘Japan’s National Innovation System: Current Status and Problems’, Oxford Review of Economic Policy, 16(2), Lundvall, B. (1992), National Systems of Innovation, London, Pinter. Siegel, D., Veugelers, R. and Wright, M. (2007), 'Technology transfer offices and commercialization of university intellectual property: performance and policy implications', Oxford Review of Economic Policy, 23(4): Thursby, J. and M. Thursby (2007), 'University licensing', Oxford Review of Economic Policy 23(4),

Further References National Innovation Systems in Emerging Markets:
Hobday, M. (1995). Innovation in East Asia. Aldershot, UK, Edward Elgar. Kim, D. S. and D. K. Kim (2005), 'The Evolutionary Responses of Korean Government Research Institutes in a Changing National Innovation System', Science, Technology and Society 10, Kumar, N. (2003). "Intellectual Property Rights, Technology and Economic Development Experiences of Asian Countries." Economic and Political Weekly January 18: Lundin, N. and S. Serger (2007), 'Globalization of R&D and China', Research Institute of Industrial Economics, Sweden, IFN Working Paper 710.

Innovative Firms and Markets Outline
Entrepreneurship and new firms Innovation and firms Markets and innovation Empirical evidence on returns to innovation Evidence on interactions between competition and innovation

Entrepreneurship and new firms
Some basic questions: Inventors – what do they do? Entrepreneurs – what role do they play? Society’s capacity to be entrepreneurial – does it differ across time and place? Larger firms – are they entrepreneurial? Two routes to innovation – individual effort versus team based organised R&D

Innovation and firms Reasons to innovate: Economics literature:
Motive: it maximises current/future profits R&D is investment yielding future returns Management literature To ensure survival of the firm To increase market share To satisfy customers Choice of being leader or follower

Markets and innovation
Creative destruction - Schumpeter’s term Innovation creates profits for owner, but also destroys profits in other firms Dynamic competition – characteristic of innovative markets Entry of new products and firms and exit of unsuccessful ones Distortions possible if Too few entrepreneurs Too many new firms fail Barriers to entry exist

Dynamic competition Dynamic process of competition can be imperfect:
New firms may be unable to gain access to finance, skilled labour, technology or information This leads to a high failure rate by new firms forcing innovative products out of the market Incumbent firms may attempt to prevent new firms entering using large scale R&D Incumbent firms may innovate infrequently due to lack of profitability from innovation

Does competition generate the optimal number of products?
Business stealing effect - New firms ignore loss of profits by incumbents Result - Too many products Appropriability effect - Firms cannot appropriate all consumer surplus Result - Too few products Spillover effect - New products demonstrate knowledge to other firms

The importance of market power
Schumpeter’s first hypothesis was that firms with larger market shares should innovate more Large market share gives more certainty about recouping returns to R&D once innovation occurs It also implies more current profits to finance the expenditure on R&D This hypothesis has led to substantial theoretical and empirical work on the relationship between market structure, competition and innovation Possible there is an inverted U-shaped relationship (see next slide), but economists cannot yet identify the optimal degree of competition C*

Inverted U-shape between innovation and competition

The importance of absolute size
Schumpeter’s second hypothesis was that larger firms should innovate more Large size implies diversification of R&D risks and ability to finance Empirical evidence on this second hypothesis is mixed: Large firms are more likely to do R&D or be IP active But smaller firms that are R&D or IP active have higher intensities of such activity

Evidence on returns to innovation
Evidence of private rates of return to R&D: Investigated using either market value or productivity approaches Both approaches suggest private rates of return to R&D are higher than for standard, tangible investment projects Excess returns may be reward for higher risk High rates of return also suggest that there is not free entry into R&D Could be due to barriers, e.g. raising finance, lack of skilled labour, or IPRs Also possible R&D requires complementary assets e.g. tacit knowledge and skilled labour

Evidence on social returns
The productivity approach can also be used to estimate the social returns to R&D Do this either by investigating the interactions between firms Or by using industry data to observe aggregate returns to R&D Many studies have suggested that the social returns are higher than private returns This implies that there are positive externalities to R&D from spillovers of technology

Evidence on interaction between competition and innovation
Absolute firm size is not necessarily beneficial to innovation Larger market share has been found to increase the returns to R&D But those with very high degree of market dominance may become complacent Recent evidence relating rates of patenting to degree of product market competition supports the inverted U-shape

Should policymakers attempt to encourage entrepreneurship? Are entrepreneurship and innovation different? Why do firms innovate? What costs and benefits accrue to firms from innovation? What are Schumpeter’s two main hypothesis concerning innovation? How would you test them? What have we learned from empirical studies about the returns to R&D? What sectors of the economy are omitted in these studies and why? How does competition affect innovation in theory and in practice?

References Hall, B. (2000), ‘Innovation and market value’, in R. Barrell, G. Mason and M. O'Mahoney (eds.), Productivity, innovation and economic performance’, Cambridge UK, Cambridge University Press. Cohen, W. (1995), ‘Empirical studies of innovative activity’, in P. Stoneman (ed.), Handbook of the Economics of Innovation and Technological Change, Oxford, Blackwell. Greenhalgh, C. A. and Rogers, M. (2006), ‘The value of innovation: The interaction of competition, R&D and IP’, Research Policy, 35(4), Aghion, P. and Griffith, R. (2005), Competition and Growth: Reconciling Theory and Evidence, Cambridge, Mass., MIT Press.

Intellectual Property Rights and Firms
Outline How can firms benefit from IPRs? Exploring the returns to IPRs Markets for IPRs Costs of obtaining and enforcing IPRs Strategies for IPRs Empirical studies on the value of IPRs

How can firms benefit from IPRs?
Lowering costs via process innovation: can increase profit at current price can increase market share if lower price With product innovation firm expects to increase sales/gain market share as novelty of the product attracts customers Also has option to license process or product to other firms and collect fees Broader technology exchange agreements can be made – termed patent pools Signalling value to investors using IPRs

Are IPRs critical to innovation?
Unregistered intellectual property rights also play a role in sustaining profits Trade secrets Confidential information Examples – technological know-how, formulas, recipes, customer information Advantages of secrecy over patents – do not have to reveal information to wider world

Effectiveness of different methods of appropriability

Other alternatives to IPRs
Open innovation model – individual firms cannot sustain complex innovation projects Engage in sharing of knowledge, ideas and inventions Can include university departments as well as other firms Open source and public licence in field of computer software Access to source code and permission to modify it provided extend same rights to others when releasing their products

Skewness in returns A few patents have very high values but many patents have little or no value In aggregate total value can be high but value is very unevenly distributed Similar differentials are seen for trademarks – compare top twenty brands (Coca Cola, Disney, Google) with any new shampoo or toothpaste now being launched Also for copyright – compare successful Hollywood movie with value of this book

Markets for IPRs Licensing decision influenced by:
novelty, codified/tacit knowledge, breadth, small firm size, not core tech., degree of competition Compulsory licensing requested: for national emergency, to restore competition, Patent trolls - market liquidity or market impediment?

Costs of obtaining and enforcing IPRs
Direct costs of obtaining IPRs vary Generally not too high for each country Costs mount if seeking coverage worldwide Wide coverage needed for traded goods and services Enforcement can be very costly Lawyers fees mount with length of case Small firms can be disadvantaged Settlement out of court is a useful option

Strategies for benefiting from patents I
Strategy Description Obtain market, or monopoly, power Standard economic argument to increase profits. Lipitor, which is Pfizer’s patented cholesterol-lowering drug, is estimated to have sales of $12 billion in 2007. To act as a signal A patent may signal to financiers, granting agencies, customers, suppliers, universities or others that the firm is innovative. Hsu and Ziedonis (2007) find some evidence for this in 370 US start-up semi-conductor firms. To restrain power of suppliers For example, Nokia has patents relating to loudspeakers and other components, even though these are manufactured by suppliers.

Strategies for benefiting from patents II
Strategy To build negotiating power Description This relates to the idea of patent pools. Firms may need their own patents to enter cross- licensing. To avoid being invented around This is the idea of patent thickets. Having a number of patents covering similar areas makes it more difficult to invent around. To prevent others from patenting (‘blocking’), or developing certain technologies (‘fencing’), or raise costs of entrants or rivals (‘flooding’ or ‘blanketing’) These strategies are self-explanatory. They result in patent thickets and/or act to change rival’s costs or strategies.

Strategies for benefiting from trademarks
Strategy Description / examples Signal origin and quality of product Such a signal allows marketing and advertising to build this into a brand (e.g. Coca-Cola or Intel Inside) Families of trademarks McCafe, McChicken and McFeast - common element to link products. Multiple trademarks Intel Inside strategy includes words, logos, musical jingle. Intel currently has over 9,000 trademarks. Umbrella or corporate trademarking Including a single name in many trademarks (e.g. Virgin Megastore, Virgin Atlantic, Virgin Brides. Strategic opposition Trademark owners monitor and object to new trademarks, so as to prevent potential competition

Empirical studies on the value of patents
What metrics for IPR value? Stock market value - reflects investors perceptions of value of IPR now and in future Studies show patents (weighted by citations) are associated with increased market value Firm productivity - reflects ability to generate high value output from inputs at current time Studies again show a positive association between productivity and patents

Analysis of patent renewals
Demonstration of inequality in patent value using renewals data After initial period of grant patents have to be renewed with a fee being paid Firms will not pay to renew patents that have no value Renewal fees filter out less valuable patents leaving those where value > or = fees Evidence for Europe has been used to calculate lower bound estimates of total value of patents

Returns to trademarks, copyright
Parallel methods have been applied to trademark evaluation as to patents Stock market value, productivity and firm profits are positively associated with trademark acquisition Copyright is much harder to evaluate No requirement to register and no option to do so outside of US, so no databases Get indirect assessment from rising value of firms when copyright extended from 50 to 70 years after death of author

Why are the returns to IPRs so skewed? Does the existence of patent trolls imply the patent system is working well? When, if ever, should compulsory licenses be used? How can one empirically assess the value of IPRs to firms? Are small or large firms more likely to use patent system? Does the patent system help or hinder new firms? Find some examples of (a) patenting strategies and (b) trademarking strategies.

References Gambardella, A., P. Giuri and A. Luzzi (2007), 'The market for patents in Europe', Research Policy, 36, Heller, M. A. and R. Eisenberg (1998), 'Can patents deter innovation? The anticommons in biomedical research', Science 280, Hall, B. (2000), ‘Innovation and market value’, in R. Barrell, G. Mason and M. O'Mahoney (eds.), Productivity, Innovation and Economic Performance, Cambridge UK, Cambridge University Press. Bloom, N. and J. van Reenen (2002), ‘Patents, real options and firm performance’, Economic Journal, 112, C Schankerman, M. and A. Pakes (1986), ‘Estimates of the value of patent rights in European countries during the post-1950 period’, Economic Journal, 96(384),

Diffusion and Social Returns
Outline Modelling the rate of adoption of an innovation Statistical evidence on rates of adoption Spillovers and social returns to innovation Empirical studies of social returns Spatial dimensions of spillovers

What is diffusion? Diffusion involves:
Transfer of information to customers about innovations Decisions by buyers to adopt the innovative product or process Eventual saturation of the market by the new generation of products or processes Then there is full realization of Schumpeter’s process of creative destruction

Modelling the rate of adoption of an innovation
Biological approach – an epidemic model – random encounters cause transfer of information (analogy with catching disease) Once information has been transmitted there is a fixed probability of the potential new customer deciding to buy the innovation A few early adopters, then an epidemic Lastly the few laggards adopt, so reach saturation in the market Rate of adoption follows a bell-shape so cumulative proportion is an S-shape

The cumulative path of adoption for an epidemic model

Economic model of diffusion
Introduce prices, costs of adoption, tastes Only adopt when net gain is positive, taking account of all these factors Formally differentiate customers by variety of taste and cost characteristics (indexed by Z) Distribution of Z is bell-shaped (e.g. Normal) As product price falls (or costs of adoption fall) then over time those with less favourable Z values will find it worthwhile to adopt Again cumulative rate of adoption S-shaped

How characteristics (index Z) determine the rate of adoption

Network and lock-in effects
Network effects arise whenever there are gains to using the same products or technologies that others are using Lock-in occurs when once consumer adopts one system it costs a lot to change to another - examples QWERTY and videos Can be due to need for interoperability and/or to users’ learning investments Market failure occurs if the first system to gain critical mass becomes the standard, even if does not have the best overall product characteristics

Statistical evidence on rates of adoption
Process of reaching market saturation is slow and often incomplete This is demonstrated for older manufacturing technologies in Figure 7.3 (not shown here due to limitation of copyright license!) Slow pattern of adoption is also seen in information and communications technology Examples are: (see Tables 7.1 and 7.2) use of computers in process technology use of Internet across countries

Spillovers and social returns to innovation
Three beneficiaries from positive externalities of innovation: Final consumers - Consumer welfare rises as product price falls or product quality rises Competing firms in industry - Knowledge spillovers inform their production Licensing technology can improve their profitability Firms in other industries - Reduced input costs and/or better input variety

Methods of assessing spillovers
Input–Output Method: Models the whole economy Traces flows of intermediate products between firms in same and different sectors to see who buys what Innovations that are produced in one sector flow out to all their buyers in other sectors Econometric studies These studies use firm or industry data Assess how a rise in innovation in one firm/sector affects performance in another

Empirical studies of social returns – input-output evidence
Input-output studies are able to identify significant differences between sectors in their roles as innovation producers and as innovation users For the US see study by Scherer For the UK see study by Greenhalgh and Gregory Both innovation producers and users contribute to the diffusion of returns to final consumers

Empirical studies of social returns – micro evidence
Econometric micro-analysis indicates that knowledge spillovers are substantial This implies that policies to encourage innovation and R&D are justified. Knowledge spillovers are influenced by level of absorptive capacity of receiving firms Conducting R&D can increase a firm’s absorptive capacity Policy to encourage R&D thus improves “the two faces of R&D”

Spatial dimensions of spillovers
If spatial spillovers are instantaneous and complete: Countries lagging behind technology frontiers would catch up quickly showing high growth Less incentive exists for subsidising domestic R&D as the benefits diffuse to other countries Evidence that the spatial proximity is still important in knowledge spillovers Spillovers from R&D diminish with distance across major countries Studies of patent citations show: more likely to be citing domestic than foreign patent more likely to be citing patent from same region

Why is diffusion generally a slow process? Are there cases when the epidemic model is better than the economic model? What factors speed up or slow down the adoption of new technology by industry? Should policy be concerned about ‘lock-in’ or ‘network effects’? What lessons can be learnt from input-output analysis of R&D and innovation?

More difficult questions
6. Choose an innovation you are familiar with and outline the potential customers and firms affected by it. How would you attempt to quantify these effects? 7. Define a) knowledge spillovers and b) business stealing. How could one test the relative importance of each? 8. What are hedonic price indices? Are they important? 9. What lessons should policymakers learn from the economics of diffusion?

References Gold, B., W. S. Peirce and G. Rosegger (1970), 'Diffusion of major technological innovations in U.S. iron and steel manufacturing', Journal of Industrial Economics, July. Scherer, F M (1984), Innovation and Growth: Schumpeterian Perspectives, Cambridge Mass., MIT Press. Greenhalgh, C and M Gregory (2000) ‘Labour productivity and product quality: their growth and inter-industry transmission’, Ch.3 of R. Barrell, G. Mason and M. O’Mahoney (eds.), Productivity, Innovation and Economic Performance, Cambridge U.P. Bloom, N., M. Shankerman and J. Van Reenen (2007), 'Identifying technology spillovers and product market rivalry', NBER Working Paper

Innovation and globalization
Outline: What is globalization? World trade in historical perspective Theories of trade and growth International knowledge and technology flows: theory and evidence International financial flows International aspects of IPRs

What is globalisation? “The increased interdependence of economies across the world” Dimensions of globalization include trade, technology, finance and labour migration Rise of Internet and falling costs of transport and communications make it easier/cheaper for firms of any size to gain access to foreign markets Firms may export their products, source inputs from abroad, outsource part of their production Financial flows lead to investment in any country Most importantly, technology transfers across boundaries can be increased

World trade in historical perspective
International trade as a proportion of world GDP has risen very rapidly in last forty years Trade/GDP ratio: % -> % -> % (figures from Dean and Sebastia-Barriel, 2004) These trends differ greatly from historical levels of trade/GDP: 1870 5% -> % -> % (figures from Maddison, 2001) Large rise in trade between rich countries Countries with high growth rates often experienced rapid growth in trade

Theories of trade and growth
It can be difficult to know where to start here. Students may have done some aspects in other courses. Core approaches: Theory of comparative advantage Product cycle models Export growth models Learning by doing models Technology catch-up models The book discusses these in general terms. The following slides add some aspects/ideas for teaching.

International knowledge and technology flows
The book argues that ‘knowledge and technology’ flows are the most important aspect influencing growth One can introduce/discuss the ideas of technology flows, or technological catch-up, in many ways: - Historical approaches (e.g. discuss US’s catch-up, China’s falling behind from 15th to 19th century and its subsequent catching up). Focus on specific countries and/or discuss empirical evidence - Theoretical models (Box 9.1 – next 5 slides) - Consider firm-level perspective (Box 9.2)

Poorer countries : technological catch-up models
Assume growth rate of technology (Ai) in a poorer country depends on technology gap with leading country (e.g. (Ausa – Ai)/Ai). Further, assume that the ability to learn, absorb and implement overseas technology is a critical factor. Call this absorptive capability, f . This ‘model’ implies growth of follower country is ‘pulled up’ to level of leader country (convergence in growth rates of technology)

Implications of technological catch-up models
Assume growth in A drives growth in GDP per capita Note this is result in steady state in Solow model, and also major implication from many endogenous growth models Then technological catch-up model implies poorer countries grow faster initially but converge to growth rates of leader poorer countries have lower level of technology (and GDP p.c in ‘steady state’) higher absorptive capability (f)  faster short run growth & higher long run level

Graphical illustration
Assuming f>0, poorest countries grow fastest. Converge in growth rates to g (lead country growth rate). Do not converge in levels. Note this model could apply to recent China/India growth, but implies decline in their growth rates in future.

Catching-up and falling behind
Above model predicts all poor countries catch-up but many show very low growth rates (Africa) To avoid this, can assume some countries have f =0, or that very poor countries find lead country technology inappropriate (i.e. can’t learn from it) Either will modify the model to allow countries to ‘fall behind’ – and be closer to empirical realities More formal endogenous growth models also include ‘catch-up’ idea. They model as: Firms in poorer countries invest in imitating products or technologies in lead countries. Costs and benefits of imitation drive growth (as in R&D models). Can have conditions where growth does not occur.

What determines absorptive capability?
Appropriate ‘institutions’ Accessibility to overseas technology involves business, educational, trade, FDI links with other countries Influenced by geography and transport Ability to learn includes broad human capital, but also specialist language and technical skills Schooling, higher education, training, management Incentives to implement new technologies combination of institutional and macroeconomic factors that allow firms to invest Stable inflation, interest rates. Taxation system. Property rights.

International financial flows
Long-term foreign direct investment flows Short-term capital flows (shares, bonds, etc) Foreign direct investment (FDI): FDI should directly raise domestic productivity (i.e. GDP p.w.), and some of this retained in domestic economy (suggests  rate of economic growth) FDI may transfer skills or knowledge to domestic firms (suggests  growth) FDI may increase competition for domestic firms ( or ↓ economic growth)

Short term financial flows
Controversy over role of short term flows Positive effects: ease capital market constraints and raise competition in financial markets Negative effects: focus on short run, introduce instability (via asset prices and exchange rates) Stiglitz (2000): capital market liberalization needs to be done slowly and with care. Asian crisis reduced growth rates. China and India less affected, both had capital controls. Credit crunch and collapse of confidence in global banking supports Stiglitz

Private capital flows into emerging markets and developing countries

Trade openness and growth
By way of summary, there are four key mechanisms at work in models of trade and growth Trade increases potential market size (via exports) Increasing market size  more profits and, possibly, ‘scale effects’ ( growth) Trade increases domestic competition (via imports) Increasing competition  less profits (↓ growth) … although there may be an incentive effect ( growth) Trade and factor price equalisation (FPE) FPE, if it holds,  marginal product of capital equal across countries (diminishing returns reflect world averages, growth rates convergence) Dynamic comparative advantage (DCA) - see next slide

Growth and trade continued
Dynamic comparative advantage (DCA) Assume countries have multiple sectors (e.g. low tech and high tech) International trade creates specialisation (static theory of comparative advantage), which means some countries increase size of high (low) tech sectors This affects growth if inherent differences in sectoral growth rates, or scale effects, vary between sectors. DCA  countries’ growth rates may diverge (e.g. richer countries (+ a few) may grow faster)

International aspectsof intellectual property rights
Historically each country choose IPRs This gives incentive to ‘free ride’ on others inventions Solution was introduction of “national treatment” (i.e. give foreigners same rights as domestic inventors) in 19th Century by various international agreements However, “national treatment” on its own leads to sub-optimal length of protection (since we assume countries ignore welfare in other countries). Solution is introduction of TRIPs, but this also means poorer countries have to pay more See fuller discussion in later lecture (Chapter 12)

What theories of trade are best able to explain the rapid rise in world trade to GDP ratio since 1950? Do exports cause economic growth? Which model is best for understanding technological catch-up by poorer countries? “International financial flows can only hinder economic growth.” Discuss. What conceptual factors are involved in international IPR agreements? Under what circumstances might the TRIPS agreement damage welfare in poorer countries?

References Dean, M. and M. Sabastia-Barriel (2004), 'Why has world trade grown faster than world output?', Bank of England Quarterly Bulletin, 3(Autumn), Maddison, A. (2001), The World Economy: A Millennial Perspective, OECD. Rogers, M. (2003), Knowledge, Technological Catch-up and Economic Growth, Cheltenham, Edward Elgar. Vernon, R. (1966), 'The product cycle hypothesis in a new international environment', Quarterly Journal of Economics, 80, Watal, J. (1998), 'The TRIPS agreement and developing countries - strong, weak or balanced protection?', Journal of World Intellectual Property, 1, Young, A. (1991), 'Learning by doing and the dynamic effects of international trade', Quarterly Journal of Economics, 106,

Technology, wages and jobs Outline
Introduction Microeconomic models of innovation and labour markets Innovation and labour markets: evidence from firms Macroeconomic and trade models of innovation and labour markets

Does new technology destroy jobs?
Two kinds of innovation with different impacts: Process innovation – new ways of making and delivering products Effects of Process Innovation: New technique increases efficiency and thus lowers costs of production Fewer workers can produce same output This can cause technological redundancy BUT Cost reduction may lead firm to expand its output as it gains market share Potentially this leads to more jobs on balance

Innovation to create demand
Product innovation – firm brings new varieties and qualities of products to the market Effects of Product Innovation: Firm can capture new or increased segments of markets Again this is likely to lead to more jobs Why the fear of new technology among workers? This is a longstanding issue: Luddites (early 19th century England) smashed new equipment being installed in textile industry Saw this as destroying their craft jobs and permitting unskilled labour to take over their work at lower wages

Technological progress which adds to labour productivity
If assume a constant elasticity of substitution (CES) production function and cost minimisation in production of given output level then it can be shown: Demand for labour depends positively on the level of output (Y), negatively on the real wage (W/P), Other influences are the degree of substitutability (σ) between capital (K) and labour (L) and the rate of labour-augmenting technological progress (A) (improving productivity of labour) ln L = ln Y – σ ln W/P + (σ – 1) ln A

What happens to demand for labour as its efficiency improves?
Can also show that elasticity of labour demand w.r.t. labour augmenting technol. change (ΔA) is: ηLA = ηP θ + (σ – 1) where (σ – 1) is the ‘substitution effect’ of ΔA: +σ use more L as now more cost effective -1 as get more output per worker by ΔA and ηP θ is the ‘scale effect’ of expanding Y: ηP is price elasticity of output demand θ is production cost reduction effect of ΔA

Effects of improved technology (if labour augmenting)
Good news for workers (ηLA is +ve) if: Capital and labour are easily substituted (σ is large) Cost savings are passed through to customers (θ is significant) Product demand is price elastic (ηP is large) Bad news for workers (ηLA is -ve) if: Product has highly inelastic demand (ηP small) Cost savings are kept in firm to raise profits (θ = 0) There is very little substitutability between capital and labour (σ is small)

Employment growth and innovation in firms in Europe Source: Table 10.1 of Greenhalgh and Rogers drawn from Harrison et al. NBER WP (2008) France Germany Spain UK Manufacturing employment growth 8.3 5.9 14.2 6.7 Process innovation - 0.1 - 0.6 0.3 - 0.4 Product innovation 5.5 8.0 7.4 4.8 Services employment growth 15.5 10.2 25.9 16.1 0.1 0.0 0.2 7.6 6.5 5.4

Innovation and wages in firms – micro aspects
Rent sharing with innovation Innovation raises profits and affords some monopoly power to firm Firm shares some of returns to raise worker loyalty (efficiency wage argument) New processes embodied in better machinery, computers and robotics Increased productivity for complementary workers raises their wages (designers, programmers, managers, technicians) Reduced demand for substituted workers causes lowering of their wages (shop floor workers, call centre workers)

Innovation and wages – micro evidence
Van Reenen (1996) data for GB showed innovation led to rises in profits and rent sharing occurred as 20-30% awarded to workers in wage rises Greenhalgh et al. (2001) data for UK found positive effect on wages both when firm is doing R&D and when making use of trademarks (indicator of product launch) Krueger (1993) US data for 1980s, estimates that workers using computers earned a premium of 10 – 15% Entorf and Kramarz (1997) for France caution that those selected to work with computers are the more able, so wage gain is more modest

Innovation, jobs and wages. - the macro picture Source: Table 10
Innovation, jobs and wages - the macro picture Source: Table 10.1, drawn from Machin (2001) Share of graduates in total employment (%) US UK Relative wages of graduates to non-graduates US UK 1980 19.3 5.0 1.36 1.48 1990 23.8 10.2 1.55 1.60 2000 27.5 17.2 1.66 1.64

Reasons for the shift in demand towards the skilled workers
In remainder of the lecture we compare three possible sources of skill shift in demand for labour in rich countries: Skill-biased technological change Globalisation and specialisation in trade Changes in composition of final demand Perhaps all three have operated at once?

Relative wages, differential productivity and supply growth Source: Hornstein et al and Greenhalgh & Rogers Box 10.2 Assume two types of labour, skilled and unskilled with wages ws and wu respectively Elasticity of substitution between labour types is σsu Relative wage of skilled to unskilled labour is driven by two ratios: Difference in productivity growth of each type of labour Relative supply of each type of labour

Predictions of this model for relative wages of skilled/unskilled
If productivity of skilled labour rises faster than that of unskilled labour, the relative wage for skilled workers will rise If supply of skilled labour rises faster than that of unskilled, then relative wage will fall The higher the degree of substitutability between skilled and unskilled workers σsu then the larger is the positive effect of rising relative productivity on relative wages the smaller is the negative effect of rising relative supply

Three-input model - two types of labour and capital equipment Source: Hornstein (2005) and Greenhalgh & Rogers Box 10.2 Assume in this framework that unskilled labour is more easily substitutable with equipment than is skilled labour The relative wage equation is now driven by three elements: Difference in productivity growth of each type of labour as above Relative supply of each type of labour as above The added effect driving demand for skilled labour is that it is complementary with capital equipment

Predictions of three-input model for relative wages of skilled/unskilled
Relative wage of skilled workers rises with any increase in ratio of equipment to skilled labour Innovation has improved productivity of capital, so an increase in capital intensity has occurred Big rise in computer use, especially in services sector, has increased demand for skilled labour In manufacturing the use of robots and other automation has reduced demand for unskilled Evidence for US - these factors explain much of change in relative wages from 1960s to 1990s

Globalization - Is international trade also skill biased?
Asian development 1970s & 80s ‘the Asian tigers’ (Hong Kong, Singapore, S. Korea Taiwan) - made small inroads into Western manufacturing More Asian development 1990s (China and India) jointly have 37% of world population) so have much larger impact on world trade HOS model of trade based on domestic factor endowments predicts specialisation by factors Opening up of countries with large supply of low cost unskilled labour leads rich countries to specialise in goods using skilled labour Employment and wages of unskilled labour in West expected to fall (see Wood 1994)

Demand - A third cause of skill bias?
Income growth in rich countries has been steady and sustained over last 25 years Composition of demand will change due to varying income elasticity of demands for goods and services Luxuries (income elastic) account for more spending than necessities and demand for inferior goods falls as incomes rise High technology innovative products require skilled labour to design and produce and Relative demand for these will grow as these innovative products will be in luxury category

Three causes of skill bias in demand for labour, UK Source: Greenhalgh and Rogers Table 10.3, from Gregory et al. Oxford Economic Papers, 2001 Total % change in employment Final demand Net exports Technological change High skill 28.8 28.2 – 4.1 4.6 Intermediate skill 0.1 21.1 – 4.8 – 16.2 Low skill – 14.9 17.9 – 5.7 – 27.1 Total change 3.5 22.0 – 13.7

Questions for Discussion
Can the ‘Luddite view’ be justified? Why does it matter whether or not technical change is factor-biased? Why is the impact of innovation on wages and employment difficult to determine? Discuss the trends in relative wages of skilled to unskilled workers in your country. What forces might affect relative wages in (a) developed economies (b) developing countries?

References P Cahuc and A Zylberberg (2004) Labor Economics, Chapter 10: Technological Progress, Globalization and Inequalities, parts 2 and 3. Hornstein, A., P. Krusell and G. L. Violante (2005), 'The effects of technical change on labor market inequalities', in Handbook of Economic Growth, Volume 1B, P. Aghion and S. Durlauf, (eds.), Amsterdam: North Holland/Elsevier B.V. Machin S. (2001), 'The changing nature of labour demand in the new economy and skill-biased technical change', Oxford Bulletin of Economics and Statistics, 63, Special Issue: The Labour Market Consequences of Technical and Structural Change, Wood, A. (1994), North-South Trade Employment and Inequality, Oxford, Clarendon Press.

Microeconomic policies to promote firm-level innovation
Outline: Introduction Is the IP system working? patents copyright Incentives for R&D Other innovation policies There is substantial material in addition to that in Ch. 11 that can be added to this topic and some suggestions are given below

Introduction Most important issue is to convey clearly to students why policy has potential to increase innovation Chapter 1 had theoretical section on market failures involved in innovation – this lecture should show how this links to policies Across the OECD countries and beyond there is wide agreement that governments have a vital role to play in promoting innovation The exact nature of this role and specific policies are still subject of debate In fact, as has been discussed in previous Chapters, there is often a weak evidence base for many of the policies This not surprising. In many areas of economic policy there is much uncertainty (e.g. monetary/finance policy – witness 2008 financial crisis) Innovation policy is at least as complex as other areas, and one could argue that it is not sufficiently studied

Is the IP system working?
First consider the ‘patent explosion’ Patents granted in the US were 52,000 in 1979 but rose to 182,000 in 2008 The US patent explosion is an interesting way to motivate this discussion but … Patents in the EU have also risen rapidly, tripling between 1985 and 2005 Most recent data for US is at

Causes of patent growth in US
US Supreme Court extended patent protection to new areas: biotechnology, computer software, business method patents, scientific research methods Universities have increased opportunity to patent scientific discoveries (Bayh-Dole Act, 1980) Since 1982 a dedicated court handles patent cases (Court of Appeal of the Federal Circuit) and this is considered a ‘friendly court’ for patentees A 1984 Act permits drug companies to extend patents by five years where they had spent time gaining approval for patented drug These factors extended the range and offered better incentives to potential patentees

Is growth of IPRs conducive to innovation and growth?
Strategic use of patents can reduce competition: Patents may create barriers to entry and raise production costs of incumbent or new firms (see Ch. 6, 6.4 and 6.6) Patents can hinder sequential innovation: Patents held by one firm can increase costs of other firms’ R&D, affecting the next generation of innovators The patent system adversely affects smaller and start-up firms: Both the above can create problems for smaller and start-up firms. Plus high cost of monitoring, obtaining and defending patents create problems (see Ch. 6, 6.5) Patent races are inefficient: Competition to be the first to patent can lead to excessive and inefficient R&D spending (see Ch. 6, 6.2)

Problems with patent system
Low patent quality Too many patents are granted, especially in the US, for obvious inventions - clogs up the patent system and devalues novel patents High uncertainty. Related to the above, but also to: Litigation system - has made some very large awards Strategic use of patents by firms High costs. Problem both for US Patent and Trademark Office and for users of the patent system - overall cost of the patent system is now several billion dollars per year There is an ‘arms race’ effect where all companies struggle to keep up

Note to lecturer: Can also discuss legal cases and/or specific firms at this point – this may be especially appropriate for law/management/business students See: Students may have heard of Blackberry (Research in Motion) patent dispute (settled in 2006 for $612 million) There are many other cases/examples that can be found by searching Google, etc

Examples of IP policies – see Table 11.1 for detailed examples
IPR Policy Comments Patent insurance Government can organise/subsidise insurance against litigation Dispute resolution IP offices can offer independent advice/mediation services Lengthening protection To encourage more use of IPRs and increase innovation. Enforcement Action to detect and stop infringement (including counterfeiting). Scope and/or breadth Legislative or legal rulings can alter the scope or breadth of IPRs. Non-obviousness or ‘inventive step’ ‘Non-obviousness’ (US) or ‘inventive step’ (Europe) means that the patented invention should not be obvious to a person skilled in the relevant art. Altering this can make it harder to gain IP rights.. Opposition or re- examination system EPO has opposition system for patents; US PTO has re-examination system but EU system much more widely used. Cost of obtaining and maintaining IPRs Application and renewal fees for patents and trademarks affect numbers of applications and the stock of IPRs. Utility models TRIPs allows countries the option of having a ‘utility model’, best described as a cross between a patent and a design (see Chapter 2, section 2.5). Education and outreach Inform firms, especially SMEs, of possible benefits of IPRs.

Is copyright working? Copyright term has been lengthening in most countries and is now equal to the life of the author plus 70 years (WTO and TRIPS) Tracing this rise in the US over 200+ years (maximum copyright terms, including renewals): 1790: 28 years, 1831: 42 years, 1909: 56 years, 1962: 75 years, 1976: life plus 50 years, and 1998: life plus 70 years In comparison with patents (20 years) this protection looks overly long Note that copyright protection can be narrower than patents (e.g. in literary works)

Can copyright be enforced?
Piracy has long been a problem for literary and musical works Problem has exploded with advent of new technologies for copying (photocopiers, computers, Internet, file-sharing software) But if too many elements of societal knowledge are held as IPRs this can stifle creativity Lack of empirical evidence about the role of copyright in stimulation or stifling of creativity means we cannot adjudicate Lack of formal registration of copyright means that legal aspects of infringement are muddied – hard to find out if infringing or infringed, and hard to sue

Do we really need patents and copyright?
Lengthy historical debate about whether firms need these incentives for innovation Counter argument is that being first to market is a sufficient incentive for many Also firms can/do use trade secrecy protection in many fields of enterprise Surveys of firms show that they rate trade secrecy more highly than patents as a means to appropriate rewards from innovation (Ch.6) But in some key fields secrecy is very hard to maintain (e.g. pharmaceuticals) and then the patent system is vital to maintaining ownership

Are trademarks useful? Trademarks signal the origin and quality of products So they give firms incentives to maintain that quality (e.g. present Toyota problems) Allow flexibility in production as franchising is possible leading to arms-length quality control Here the franchise owner specialises in marketing and innovation, while franchisee produces to a known and trusted recipe/formula But do successful brands in fact restrain market competition? If incumbents saturate markets with varieties backed by advertising then new entrants face higher costs of entry

Incentive Systems for Encouraging Firm-Level R&D
R&D Tax Incentives: (see Hall and Van Reenen 2000) - Common in OECD countries - Two main types “level” and “incremental” - Level scheme offers tax relief on all R&D so has some deadweight loss as not all the R&D is new - Incremental scheme offers tax relief on increases in R&D over a given period but is more complex in practice Direct R&D Grants and Other Schemes: (see OECD 2006) - These are now a declining share of business R&D expenditure - Problems are ‘selectivity’ and ‘crowding out’ Prizes, Awards, and Patent Buyouts: (see Kremer 1998) - Alternative incentive systems can be used

Other innovation policies
Policy toward Universities (Chap 4 has some discussion but could extend here) - Establishment of Technology Transfer Offices (TTOs) - Increased interface between university research and private business - Rise in licensing revenues to universities SMEs, High-tech Start-ups, and Entrepreneurship (See Lerner 1999, OECD 2008) - Enterprise culture - Knowledge and skills - Access to finance - Regulation

Other innovation policies (contd.)
Competition Policy (less material on this, but has been an area of interest in recent years) Industry Standard Setting (if students have not heard of QWERTY issues then cover here - see Chap 7) Government procurement policy - large purchasing power can target innovation (e.g. development of zero carbon buildings) - as early users of new products government can support development by giving feedback - pitfalls if fail to assess full costs of products over their lifecycle in use - problems when commissioning departments lack expertise to choose wisely

Why has patenting increased so much in recent years? Will this trend continue? What policies might improve the working of the a) patent, b) copyright and c) trademark systems? Should patents be replaced by a system of rewards and prizes? Why are ‘markets for technology’ important? How would you evaluate the effectiveness of an R&D tax incentive scheme? Are direct R&D grants a better policy than either R&D tax incentives or patents? Would the money spent on R&D tax credits be better spent on educating scientists?

References – IPR systems
Bessen, J. and M. Meurer (2008), Patent Failure, Princeton, N.J., Princeton University Press. Corrigan, R. and M. Rogers (2005), 'The economics of copyright', World Economics: The Journal of Current Economic Analysis and Policy, 6(3), Hall, B. (2005), 'Exploring the patent explosion', Journal of Technology Transfer, 30(1/2), Hall, B. (2007), 'Patents and patent policy', Oxford Review of Economic Policy, 23(4), Jaffe, A. and J. Lerner (2004), Innovation and Its Discontents: How Our Broken Patent System is Endangering Innovation and Progress, and What to Do About It, Princeton N. J., Princeton University Press. Lessig, L. (2002), The Future of Ideas: The Fate of the Commons in a Connected World, New York, Random House. Lessig, L. (2004), Free Culture: How Big Media Uses Technology and the Law to Lock Down Culture and Control Creativity, London, Penguin Press.

References – public policy
Edler, J., L. Hommen, J.Rigby and L.Tsipouri (2005), Innovation and Public Procurement: Review of Issues at Stake, study for the European Commission co-ordinated by the Fraunhofer Institute. Hall, B. and J. Van Reenen (2000), 'How effective are fiscal incentives for R&D? A review of the evidence', Research Policy, 29, 449–69. Kremer, M. (1998), 'Patent buyouts: a mechanism for encouraging innovation', Quarterly Journal of Economics, 113(4), Lerner, J. (1999), 'The government as venture capitalist: the long-run impact of the SBIR program', Journal of Business, 72(3), OECD (2002), Tax Incentives for Research and Development: Trends and Issues, Science Technology and Industry, Paris, OECD. OECD (2006), Government R&D Funding and Company Behaviour: Measuring Behavioural Additionality, Paris, OECD. OECD (2008), OECD Framework for the Evaluation of SME and Entrepreneurship Policies and Programmes, Paris, OECD.

Macroeconomic issues and policies
Outline: IPRs and Economic Growth Trade-Related Aspects of Intellectual Property (TRIPS) Intellectual Property Rights, Exhaustion, and Parallel Imports Piracy and Counterfeit R&D in the Global Economy International Migration of Skilled Labor

Introduction Ultimately would like to know impact of IPRs on economic growth and the welfare of society This is a difficult question, but gathering evidence on this may increase chances of ‘getting policies right’ Note theoretical arguments not conclusive - can have models with positive or negative outcomes (Chapter 9) Different types of evidence can be gathered: Cross-country regression evidence (this chapter) Firm-level analysis (Chapters 5 – 7) Historical evidence (some examples in this chapter) Policy-type experiments (analysis of US patent surge, Chapter 11) Survey evidence on agent’s perceptions (some discussion in Chapter 3)

IPRs and economic growth
Complex set of relationships (see Figure 12.1, on next slide, and further diagram on slide after that) IPRs can affect investment, trade, FDI, and R&D These ‘proximate factors’ can in turn affect a country’s rate of growth Evidence from study by Park and Ginarte (1997) using cross-section data for 60 countries supports this indirect role of IPRs on growth by enhancing investment and R&D Further summaries of evidence are in Allred and Park (2007) and Rogers (2009), see Additional References

Figure 12.1

Impacts of patenting

Complex relationship between IPRs and growth
In order to benefit from strong IPRs a country needs to have a range of factors conducive to growth Countries at different stages of development benefit in different ways Falvey et al. (2006) found that having strong IPRs benefits both the richest and the poorest nations, but not the middle-income countries Positive effects are due to increased FDI and trade Negative effects arise from inability to imitate and adopt technology freely A further indication from historical studies is that the strength of IPRs may affect the nature of innovation in a country rather than the level of innovation

Trade-Related Aspects of Intellectual Property (TRIPS)
TRIPS agreement membership of the World Trade Organisation (WTO) was made conditional on signing it TRIPS agreement established minimum standards of IPR protection in all WTO member countries Developing countries were given time to make the transition, but grace periods generally expired within a few years of such countries joining the WTO China and India have both become members of WTO/TRIPS Differential impacts of TRIPS – immediate effect (expected) was that rich countries gained more revenues from licensing their technology and exporting high-tech products Poorest countries (esp. Africa) suffered most, because of higher prices for protected products and technologies

TRIPS, FDI and technology transfer
FDI is sensitive to the IPR regime as transnational corporations (TNCs) fear to invest where no IPRs (Maskus, 2000) Can argue that technology transfer is enhanced due to FDI as these firms bring modernising technology and domestic enterprise can learn from them But technology transfer can only occur if country has the ability to absorb it – needs education and entrepreneurial talent to do this Any new domestic firms will of course be paying higher licence fees for their new technology or higher import prices for imported capital goods that are protected Even so, before the IPR regime, no licences would have been offered

Contentious and enforcement aspects of TRIPS
TRIPS allows for some flexibility in how countries design and operate IPRs One key issue concerns supply of pharmaceuticals How can poor country improve access to patented but essential medicines for its population (e.g. for AIDS)? One route is to use ‘compulsory licensing’ which means the government intervenes to confer licence to produce patented drug – obviously not popular with rich countries! Another route is to encourage price discrimination by the rich country producer, but this can run into problems if buyers in poor country can arbitrage by re-exporting (see next slide) Even if IPR regime exists many countries do not have the resources to enforce their own rules

Intellectual Property Rights, Exhaustion, and Parallel Imports
Exhaustion means that, once a product with IP protection has been sold, the IP rights attached to it are exhausted and no longer offer any means of control to its producer Product can be re-sold by the buyer without the permission of the owner(s) of the IPRs contained in the product Example of international exhaustion – a patented product is sold in the US; this item can be resold to a buyer in Japan and is thus imported into Japan This leads to parallel imports – sales from US producer and onward sales from US buyer can both reach Japan Result is producer cannot separate his international markets, even if he wants to do so in order to charge different prices At present WTO & TRIPS allows each country to decide if it does, or does not, want to apply international exhaustion

Piracy and Counterfeiting
Piracy refers to large-scale infringement of copyright, particularly for DVDs: One area of interest is the estimates of revenue losses by such agencies as the International Federation of the Phonographic Industries (IFPI) – and specifically whether these estimates are too high - see Png (2007) Another issue is what country-specific factors affect the rate of piracy - see Goel and Nelson (2009) Counterfeit products are those that imitate trademarked products in terms of design and packaging Deceptive counterfeits are assumed to be the real thing and this can be dangerous, for example if drugs, or spare parts Non-deceptive counterfeits may be less harmful, but original manufacturers can still be faced with loss of status for brand

R&D in the Global Economy
Are R&D spillovers global? Evidence demonstrates spillovers between rich countries Absorptive capacity is enhanced by trade and by presence of highly educated populations The globalization of the innovation process Since 1950s/60s the emergence of trans-national corporations (TNCs) has led to spreading of R&D facilities across rich countries UNCTAD (2005) study contains a mass of information and background to this and also shows new trends: Globalisation of R&D to China and India: China: rising R&D in Beijing, Shanghai, Guangzhou India: rising R&D concentration around Bangalore (See details in Box 12.1)

International migration of skilled labour
Two way international flows of workers accompany the geographical clustering of innovation Skilled personnel from innovative regions travel abroad, taking their tacit knowledge for which employers elsewhere are willing to pay them high wages Innovative regions attract inward migration of high skilled workers who want to learn the latest techniques and discoveries Each side will complain about their ‘brain drain’ problem Benefits can be the establishment of new firms and new trade links, as migrants often retain links with former countries Example – Silicon Valley in California has high population of ‘non-resident Indians’ who have set up companies in both the US and India

Why might strong IPRs hinder economic development? Classify the potential effects of TRIPS by a) income level of country b) mechanism of effects (e.g. FDI) What is the difference between deceptive and non-deceptive counterfeit goods? Does the distinction matter for policy? Conduct some research on the importance of piracy and counterfeit. What is the extent of lost sales to major companies in the US? What forces are driving the globalization of R&D? What effects will it have on the countries involved? Can the ‘brain drain’ of skilled labour from poorer to richer countries ever be a good thing?

References IPRs and growth:
Falvey, R., N. Foster and D. Greenaway (2006), 'Intellectual property rights and innovation in developing countries', Review of Development Economics, 10(4), Park, W. and J. Ginarte (1997), 'Intellectual property rights and economic growth', Contemporary Economic Policy, XV(July), TRIPS Agreement and Globalisation of R&D: Lall, S. and M. Albaladejo (2002), ‘Indicators of the relative importance of IPRs in developing countries’, , Queen Elizabeth House Working Paper, QEHWPS85, Oxford. Maskus, K. (2000), Intellectual Property Rights in the Global Economy, Washington: Institute for International Economics. UNCTAD (2005), World Investment Report, New York and Geneva, United Nations.

Additional References
IPRs and growth: Allred and Park (2007) “Patent rights and innovative activity: evidence from national and firm-level data”, Journal of International Business Studies, 38: 6, Rogers, M. (2009), “The Incidence and Significance of Patenting”, available online at: Piracy: Png, I. (2007) “On the Reliability of Piracy Statistics”, (Google this title for most recent publication source). Goel, R. K. and M. Nelson (2009) “Determinants of software piracy: economics, institutions and technology”, Journal of Technology Transfer, 34:637–658

Innovation, Intellectual Property, and Economic Growth

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