General information on WKCI Compares regions across some knowledge economy benchmarks 2008: 145 regions: 63 represent North America, 54 from Europe, 28 from Asia and Oceania Eastern Europe: Latvia, Lithuania, Estonia, Prague, Bratislava, Budapest Asian and East European regions do not have GDP as high as the rest of Europe and North America but have experienced a high level of economic growth, especially rate of knowledge-based economic growth Regions selected on the basis of a survey of most internationally competitive regions Index provides a visible yardstick of economic strength and weaknesses going beyond narrow focus on macroeconomic performance

1. human capital 2. financial capital 3. knowledge capital 4. regional economy outputs 5. knowledge sustainability 5 components of WKCI

Human capital components of WKCI employment per employees in production of: 1)IT and computer manufacturing; 2)biotechnology and chemicals; 3)automotive and mechanical engineering; 4)instrumentation and electrical machinery; 5)high tech services Economic activity rate Number of managers per employees

Knowledge capital components of WKCI Per capita expenditures on: 1)R&D performed by government 2) R&D performed by business 3) number of registered patents per one million inhabitants

Knowledge sustainability Per capita public expenditures on: 1) primary and secondary education 2)higher education Secure servers per one million inhabitants Internet hosts per inhabitants broadband access per inhabitants

Regional economy outputs labor productivity, mean gross monthly earnings, unemployment rates AND Financial capital component: per capita private equity investment

Financial capital Availability of venture capital Per capita private equity investment

How to calculate WKCI? Following statistical methods used : - factor analysis to simplify complex and diverse relationships among set of observed variables by uncovering factors that link together unrelated variables - an extraction method showing the location of each region within the structure of the data provides the scores for sub-composite indices -data envelopment analysis (DEA)( linear programming technique) to obtain a single composite index from sub-composite indices. -DEA seeks a set of weights for each region that maximises a weight sum of variables, with the constrain that no region has a weighted sum >1 -each region receives a score between 0 and 1 A DEA score: geometric mean of all scores is taken for each region

World knowledge competitiveness index 2008 (top ten regions) 1. San Jose-Sunnyvale-Santa Clara USA Boston-Cambridge-Quincy USA Hartford USA Bridgeport-Stamford-Norwalk USA San Francisco,-Oakland-Fremont USA Stockholm Sweden Seattle-Tacoma-Bellevue USA Providence-Fail River-Warwick USA Tokyo Japan San Diego-Carlsbad-San Marcos USA Source:

number one in the ranking: US metropolitan area San Jose The home of Silicon Valley is a leader because: -enormous investment in knowledge-intensive business development in fields of: high technology, engineering, computers and microprocessors - a large employment in knowledge sectors - number one for investment in education and business R&D -a number one for productivity and earnings

Other top regions Number two: metropolitan area of Boston -a region with high levels of intellectual and financial capital - a home to 8 research universities including Harvard and MIT Number three: Hartford with: -high R&D spending and private equity investment, one of the highest productivity Number sixth: Stockholm -continues improvement of the regions ranking because of: business R&D spending, biotechnology and chemical employment, higher education spending Ninth position of Tokyo (moves up from 22 place)

Emerging regions Regions from China, India and Eastern Europe Bagalore region (India) the lowest ranked Shanghai continues to perform best, being ahead of Berlin and British Columbia

Why to analyze regions in a global world? Does the progress in ICT diminish the importance of location? NO, the location does matter in a global economy, especially in knowledge intensive activities. The geographic concentration of resources and industries still important „Location paradox” explained by M. Porter: „Although global sourcing mitigates disadvantages, it does not create advantages… paradoxically, the most enduring competitive advantages in a global economy seem to be local”.

Examples of localised advantages of agglomeration -access to specialised inputs, employees, information and institutions encourage firms to cluster new firms attracted by the same advantages of concentration -factors increasing productivity encourage innovation within the cluster Localised advantages of access to specialized information via personal relationships traditional form of advantage vanish – competitive advantage lying outside companies as the business environment- become more important

Conclusion Concept of localised competition supports the thesis that data analysis and policy approach needed more at regional than national level