Waters, R. and Lawton Smith, Helen (2012) Clusters, human capital and economic development in Oxfordshire and Cambridgeshire. Working Paper. Birkbeck College, University of London, London, UK.
|
Text
8465.pdf - Published Version of Record Download (609kB) | Preview |
Abstract
Oxfordshire and Cambridgeshire are two of the most high tech economies in the UK (see for example DTI, 2002 and Garnsey and Lawton Smith, 1998). They are home to world class research universities and public and private research laboratories as well as a full range of business and professional services which support the development of their clusters. Building on previous work (Lawton Smith and Waters, 2011) this paper draws on national datasets to review the continued development of these economies. The paper considers issues such as new firm formation, sectoral composition and gross value added and relates them to social inclusion and worklessness. The paper draws on literature which emphasises the endogeneity of processes within regions, but also on studies which show that there are different kinds of high tech regions with varying industrial structures. Conclusions are drawn on the extent to which the presence of successful clusters (Spencer et al, 2010) influences outcomes for the local economy more generally, and how Oxfordshire and Cambridgeshire have performed over the last ten years.
Metadata
Item Type: | Monograph (Working Paper) |
---|---|
Additional Information: | CIMR Research Working Paper Series, Working Paper No. 2 ISSN: 2052-062X |
Keyword(s) / Subject(s): | high tech economies, Oxfordshire and Cambridgeshire, employment, social inclusion |
School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
Research Centres and Institutes: | Innovation Management Research, Birkbeck Centre for |
Depositing User: | Administrator |
Date Deposited: | 15 Oct 2013 13:28 |
Last Modified: | 02 Aug 2023 17:07 |
URI: | https://eprints.bbk.ac.uk/id/eprint/8465 |
Statistics
Additional statistics are available via IRStats2.