Measurement of innovation, productivity and growth

1. 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

2. 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.

3. 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

4. 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 14 26 Sweden 47 32 12 20 UK 36 21 6 17 % of firms involved in innovative activities, CIS 1998-2000

5. 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

6. 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

7. 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 in Europe, Japan and the United States (2003, or 2002*)

8. Country R&D personnel/ labour force % R&D personnel (in FTEs) Share working in BES % Share working in GOV % Share working 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 R&D personnel in Europe and Japan (2004, or 2003*)

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

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

11. 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)

12. 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 aL 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

13. Annual average growth in GDP per hour worked (1970-2006)

14. Average growth of GDP per capita in emerging markets

15. 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

16. 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): 309-34. • Regulation and productivity (e.g. Crafts, N. (2006). "Regulation and Productivity Performance " Oxford Review of Economic Policy 22(2): 186-202.

17. 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?

18. References Griliches, Z. (1990) ‘Patent statistics as economic indicators: a survey’, Journal of Economic Literature, XXVIII (December), 1661-1707. Lipsey, R. G. and K. I. Carlaw (2004), 'Total factor productivity and the measurement of technological change', Canadian Journal of Economics, 37(4), 1118-50. Schreyer, P. and D. Pilat (2001) "Measuring Productivity“, OECD Economic Studies 33: 128. The Economist (14 Nov. 2009) Economic Focus: ‘Secret Sauce’.