Science, Technology and Innovation (STI), Growth and Development

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Science, Technology and Innovation (STI), Growth and Development Michael Lim Policy Review Section Science, Technology and ICT Branch UNCTAD-DTL P166 short course on STI and development 12 December 2011 Geneva

Outline Technology and economic growth Technology and innovation The importance of STI Innovation and innovation systems Conclusions

The Global Distribution of Knowledge (from UNCTAD LDCR 2007)

The Global Distribution of Poverty (from UNCTAD LDCR 2007)

Economic growth and income trends: 3 big issues to explain There is huge variation in per capita income across countries. Why? There is huge variation in growth across countries. Why? Global growth was close to zero until about 1500, rose slightly until about 1800, and has accelerated since 1800. Growth patterns varied by region and country (and this continues). Why?

Technology and economic growth (1) Output (Y) is a function of capital (K), labour (L) and technology (T) Y=f(K, L, T) or Output (Y) is a function of physical capital (Kp), human capital (Kh), labour (L), and technology (T) Y=f(Kp, Kh, L, T) In standard neoclassical growth theory Y =T*f(Kp, Kh, L) with technology (T) exogenous (external) ie T=f(?) T is unexplained Kp=f(Kpt, It) It is new investment in physical capital Kh=f(Kht, Iht) Iht new investment in education, training and health L=f(Lt, grL) grL is population growth (t is time)

Technology and economic growth (2) Economic growth is directly a function of Kp, Kh and improved technologies. Controversy over the relative importance of each. Additional growth determinants: Initial conditions; institutions and incentive structures; geography; national policies; perhaps culture.

Technology and economic growth: historical viewpoints (3) Neoclassical: Technology is exogenous (unexplained), but drives productivity of labour and capital. Adam Smith (1770s): labour specialization and innovative production processes increase productivity. Karl Marx (1850s): technology-driven economy and social relations. Friedrich List (1880s): importance of national policy frameworks, government coordination of learning, knowledge, technology to promote innovation. Joseph Schumpeter (1930s): creative destruction, competition and new firm entry (entrepreneurship) create innovation; types of innovation. Endogenous growth theory: increasing returns from knowledge accumulation through development of technology, human capital and R&D (Paul Romer). Evolutionary economics: learning required for technological progress, cumulative learning, path dependency etc. Innovations systems theory: technology and innovation are endogenous, depend on complex, dynamic systems (Chris Freeman, B.A. Lundvall, Richard Nelson 1980s/90s).

Innovative Capabilities and Income (from UNCTAD LDCR 2007)

The technology frontier is dynamic

Why STI is important Building strong STI capabilities, accessing foreign technologies and building strong national systems of innovation are important for economic growth and development, social welfare and addressing environmental challenges. STI applications: -improving productivity in manufacturing, agriculture and services -increasing value added locally -diversifying production into knowledge-intensive activities -mitigating/adapting to climate change -developing new energy sources (renewable energy technologies RETs) -building good infrastructure -conserving water in agriculture -improving public services (health, education) -addressing disease epidemics -organizing large and mega-cities (smart urban planning) -early warning systems for natural disasters (tsunamis, hurricanes) -adapting buildings for earthquake prone zones -slowing desertification etc.

STI capabilities: what are they? (1) Scientific, technological and innovative capabilities. Broad definition add capabilities in engineering, other technical capabilities, entrepreneurship, management and organizational capabilities. SET, S&T, STEM.

STI capabilities: What are they? (2) Scientific capabilities – the ability to learn, understand and apply scientific knowledge and skills to solve problems. Engineering capabilities – the ability to learn, understand and apply engineering knowledge and skills to solve problems. Technological capabilities – the ability to learn, understand and master the use of existing (both traditional and recent) technologies to solve problems and to produce new technologies. Innovative capabilities – the ability to innovate. Technological learning by enterprises (firms and farmers most importantly) is important for technological development of a country. Policy learning by STI policymakers also important.

What is technology? Technology - knowledge applied to the production of goods or services or solving practical problems. Different forms: machinery, processes and knowledge - physical machinery -production processes -software -codified and tacit knowledge Knowledge – the theoretical or practical understanding of a subject.

What is innovation? New to world: the introduction for the first time by an organization (or person) of a novel product or process that is new to the world. New to the firm/industry: The introduction of new or improved products, or of new or improved processes and organizational methods in the design, production and distribution of goods and services. Invention: U.S. Patent Law: a new, useful process, machine, improvement, etc., that did not exist previously and that is recognized as the product of some unique intuition or genius, as distinguished from ordinary mechanical skill or craftsmanship. Innovation vs invention

Types of innovation All along the production value chain: design, production, distribution and marketing. Technological (related to the introduction of new technologies) or non-technological (organizational, managerial or institutional). Based on formal training and R&D or based on informal learning, trial and error, use and experience Size of impact: -Incremental/marginal (through small improvements) -radical (through major breakthroughs) -revolutionary (a fundamentally important new technology is created).

What drives innovation? Two basic conceptual approaches: Linear approaches The systems approach

Linear models of innovation

National systems of innovation (source: Arnold and Bell (2001)) Framework conditions ▪ Financial environment ▪ Taxation and incentives ▪ Propensity for innovation and entrepreneurship ▪ Trust ▪ Mobility ▪ Education, Literacy Demand ▪ Consumers (final demand) ▪ Producers (intermediate demand) Business system ▪ Companies ▪ Farms ▪ Healthcare, etc Education and research system ▪ Professional education and training ▪ Higher research ▪ Public sector Intermediate Organizations ▪ Research institutes ▪ Brokers, etc Infrastructure ▪ Banking, venture capital ▪ IPR and information system ▪ Innovation and business support system ▪ Standards and norms

National systems of innovation (source: OECD (1999))

Sectoral IS: an agricultural innovation system (from Spielman and Birner (2008), adapted from Arnold and Bell (2001)).

Agricultural Innovation Systems Macroeconomic & International Regulatory Environment Education System & Training Physical Infrastructure Global Innovation networks Agricultural Knowledge Generation, Diffusion and Use Firms and Networks Regional innovations systems Research & standard Setting Bodies supply led systems & value chains Industry, other Agricultural Innovation Systems FARMERS Science suppliers Supporting Institutions An innovation capacity development approach does not mean throwing away our old policy tools (such as research investment). But it does mean rethinking how these are used, sequenced, clustered, embedded and what additions might be necessary and how the role of certain policy tools might need to migrate to perform new functions. National Innovation System Agricultural Innovation Capacity Farming & Soil Conditions Product Market Conditions Sector Performance Growth, Jobs, Competitiveness Source: UNCTAD Technology and Innovation Report 2010, Adapted from OECD, Managing National Innovation Systems, 1999

Some central tenets of evolutionary economics and the IS framework knowledge important (not just information) learning and decisions are made under high levels of uncertainty focus more on production than consumption based on dynamic comparative advantage, not static comparative advantage production patterns and export specialization matter a lot government and market both have a role; activist state needed – technology markets highly imperfect – social returns higher than private ones) financial markets often work poorly in financing innovation market failures occur but also systemic failures, state intervention is to correct systemic failures (and market failures) markets do not find an equilibrium firms innovate in a system (and are not atomistic and independent) institutions (formal and informal) important for collaboration and learning as well as contract enforcement uneven development (not convergence) among countries probable without activist state promoting learning and innovation

Problems with IS framework The IS framework is useful but imperfect. It is a complex tool to use because the systems are complex and dynamic. There is much conceptual work on IS, but limited empirical work on building IS. The boundaries of an IS are not completely clear; IS are very broad. It is not prescriptive in nature, so inadequate for detailed guidance with policy prescriptions. It remains a useful but possibly inadequate framework used on its own.

How to build innovation systems? Strong innovation systems may develop only very slowly. Developing countries often have emerging, incomplete, weak innovation systems. NSI are context specific; have historical roots; embedded in local social and institutional setting; no single, ideal system for all countries (no one-size-fits-all). National policies can help accelerate the process. Problem: How to build them is not well understood; no blueprint. Policy experimentation and policy learning needed.

Conclusions Strong STI capabilities, human capital, access to technologies (and absorption), and effective innovation systems are important for sustainable and inclusive growth and development, improving social welfare, solving environmental problems. Policymakers should think about how to build each. How can policies make a difference?

Discussion issues What is the purpose of science: conquer nature? Help mankind? Is technology always good? Is innovation always good? Do all countries innovate? Can STI solve all our problems? Does technology create new problems?