Benchmarking the knowledge competitiveness of the globe's high performing regions:a review of the World Knowledge Competitiveness Index

Purpose – The purpose of this paper is to analyze the way in which the knowledge competitiveness of regions is measured and further introduces the World Knowledge Competitiveness Index (WKCI) benchmarking tool. Design/methodology/approach – The methodology consists of an econometric analysis of key indicators relating to the concept of knowledge competitiveness for 125 regions from across the globe consisting of 55 representatives from North America, 45 from Europe and 25 from Asia and Oceania. Findings – The key to winning the super competitive race in the knowledge-based economy is investment in the future: research and development, and education and training. It is found that the majority of the high-performing regional economies in the USA have a knowledge competitive edge over their counterparts in Europe and Asia. Research limitations/implications – To an extent, the research is limited by the availability of comparable indicators and metrics at the regional level that extend across the globe. Whilst comparative data are often accessible at the national level, regional data sources remain underdeveloped. Practical implications – The WKCI has become internationally recognized as an important instrument for economic development policymakers and regional investment promotion agents as they create and refine their strategies and targets. In particular, it has provided a benchmark that allows regions to compare their knowledge competitiveness with other regions for around the world and not only their own nation or continent. Originality/value – The WKCI is the first composite and relative measure of the knowledge competitiveness of the globe's best performing regions.

World knowledge competitiveness index 2002:benchmarking the globes high-performing regions

The World Knowledge Competitiveness Index 2002 is the first composite and relative measure of the knowledge economies of the globe's best performing regions. It represents an integrated and overall benchmark of the knowledge capacity, capability and sustainability of each region and the extent to which this knowledge is translated into economic value and transferred into the wealth of the citizens of each region. This publication has over 50 pages and covers the following sections: The Economics of Knowledge Competitiveness The Rankings - World Knowledge Competitiveness Index Human Capital Components Knowledge Capital Components Regional Economy Outputs Knowledge Sustainability Components Driving Knowledge-Based Growth

Can you tell your clunis from your cubitus? A benchmark for functional imaging

Advances in functional brain imaging have allowed the development of new investigative techniques with clinical application—ranging from presurgical mapping of eloquent cortex to identifying cortical regions involved in religious experiences. Similarly a variety of methods are available to referring physicians, ranging from metabolic measures such as functional magnetic resonance imaging and positron emission tomography to measurements based on electrical activity such as electroencephalography and magnetoencephalography. However, there are no universal benchmarks by which to judge between these methods. In this study we attempt to develop a standard for functional localisation, based on the known functional organisation of somatosensory cortex. Studies have shown spatially distinct sites of brain activity in response to stimulation of various body parts. Generally these studies have focused on areas with large cortical representations, such as the index finger and face. We tested the limits of magnetoencephalography source localisation by stimulation of body parts, namely the clunis and the cubitus, that map to proximal and relatively poorly represented regions of somatosensory cortex.

The forecast performance of competing implied volatility measures:the case of individual stocks

This study examines the information content of alternative implied volatility measures for the 30 components of the Dow Jones Industrial Average Index from 1996 until 2007. Along with the popular Black-Scholes and \model-free" implied volatility expectations, the recently proposed corridor implied volatil- ity (CIV) measures are explored. For all pair-wise comparisons, it is found that a CIV measure that is closely related to the model-free implied volatility, nearly always delivers the most accurate forecasts for the majority of the firms. This finding remains consistent for different forecast horizons, volatility definitions, loss functions and forecast evaluation settings.