Regional policy and spillovers from FDI in the UK

This paper tests one of the fundamental assumptions of regional policy makers over the last 20 years. Western governments, in seeking to attract internationally mobile capital have spent significant sums of public money on subsidies and grants. This is justified on the basis that the social returns to FDI are significantly greater than the private returns, due to productivity or technology spillovers from inward investors to domestic industry. However, this paper generates some estimates of these spillovers for both assisted areas and non-assisted areas in the UK, and questions the size of these social returns, arguing that productivity spillovers do not occur in regions where significant inward investment incentives are available.

Wage spillovers, inter-regional effects and the impact of inward investment

This paper evaluates the extent of inter-industry and inter-regional wage spillovers across the UK. An extensive body of literature exists suggesting that wages elsewhere affect wage determination and levels of satisfaction, but this paper extends the analysis of wage determination to examine the effects of inward investment in the process. Thus far the specific effect of foreign wages on domestic wage determination has not been evaluated. We employ industry- and regional-level panel data for the UK, and contrast results from alternative approaches to space-time modelling. Each supports the notion that such wage spillovers do occur, though assumptions made concerning the modelling of spatial interaction are important. Further, such wage spillovers are more widespread for skilled than for unskilled workers and also lower in areas of high unemployment. © 2006 Regional Studies Association.

Planning and decision-making for energy recovery from waste at the sub-regional level

This research project has developed a novel decision support system using Geographical Information Systems and Multi Criteria Decision Analysis and used it to develop and evaluate energy-from-waste policy options. The system was validated by applying it to the UK administrative areas of Cornwall and Warwickshire. Different strategies have been defined by the size and number of the facilities, as well as the technology chosen. Using sensitivity on the results from the decision support system, it was found that key decision criteria included those affected by cost, energy efficiency, transport impacts and air/dioxin emissions. The conclusions of this work are that distributed small-scale energy-from-waste facilities score most highly overall and that scale is more important than technology design in determining overall policy impact. This project makes its primary contribution to energy-from-waste planning by its development of a Decision Support System that can be used to assist waste disposal authorities to identify preferred energy-from-waste options that have been tailored specifically to the socio-geographic characteristics of their jurisdictional areas. The project also highlights the potential of energy-from-waste policies that are seldom given enough attention to in the UK, namely those of a smaller-scale and distributed nature that often have technology designed specifically to cater for this market.

Understanding U.S. regional linguistic variation with Twitter data analysis

We analyze a Big Data set of geo-tagged tweets for a year (Oct. 2013–Oct. 2014) to understand the regional linguistic variation in the U.S. Prior work on regional linguistic variations usually took a long time to collect data and focused on either rural or urban areas. Geo-tagged Twitter data offers an unprecedented database with rich linguistic representation of fine spatiotemporal resolution and continuity. From the one-year Twitter corpus, we extract lexical characteristics for twitter users by summarizing the frequencies of a set of lexical alternations that each user has used. We spatially aggregate and smooth each lexical characteristic to derive county-based linguistic variables, from which orthogonal dimensions are extracted using the principal component analysis (PCA). Finally a regionalization method is used to discover hierarchical dialect regions using the PCA components. The regionalization results reveal interesting linguistic regional variations in the U.S. The discovered regions not only confirm past research findings in the literature but also provide new insights and a more detailed understanding of very recent linguistic patterns in the U.S.

The Digital Observatory for Protected Areas (DOPA) Explorer 1.0

The Digital Observatory for Protected Areas (DOPA) has been developed to support the European Union’s efforts in strengthening our capacity to mobilize and use biodiversity data, information and forecasts so that they are readily accessible to policymakers, managers, experts and other users. Conceived as a set of web based services, DOPA provides a broad set of free and open source tools to assess, monitor and even forecast the state of and pressure on protected areas at local, regional and global scale. DOPA Explorer 1.0 is a web based interface available in four languages (EN, FR, ES, PT) providing simple means to explore the nearly 16,000 protected areas that are at least as large as 100 km2. Distinguishing between terrestrial, marine and mixed protected areas, DOPA Explorer 1.0 can help end users to identify those with most unique ecosystems and species, and assess the pressures they are exposed to because of human development. Recognized by the UN Convention on Biological Diversity (CBD) as a reference information system, DOPA Explorer is based on the best global data sets available and provides means to rank protected areas at the country and ecoregion levels. Inversely, DOPA Explorer indirectly highlights the protected areas for which information is incomplete. We finally invite the end-users of DOPA to engage with us through the proposed communication platforms to help improve our work to support the safeguarding of biodiversity.