Explaining Spatial Patterns of Industrial Diversity: An Analysis of Sub-regions in Great Britain

Abstract

This paper argues that effective local policy development requires a thorough understanding of patterns of spatial diversity involving the integration of theoretical work from geography, economics and management. An empirical analysis of diversity in Great Britain for the period 1995-2002 is presented utilising entropy measures of diversity. The results of empirical models of the determinants of diversity across sub-regions examine the significance of a number of explanatory factors including regional size, level of urbanisation, industry structure, market structure and key resources. Decomposing the model into related and unrelated diversity components reveals some important differences between the two types of diversity. The paper concludes that policies fostering long-term diversity are a crucial complement to policies focusing on key sectors.

Spatial Externalities, Relatedness and Sector Employment Growth in Great Britain

“…For example, sectors operating with highly specialised technologies, may find it difficult to benefit from spillovers as there are few local sectors utilising similar technologies. Conversely, sectors operating on a more generic or diverse basis may find more opportunities to exploit spillovers (BISHOP AND GRIPAIOS, 2007).…”

“…Table 1 inserted approximately here The dependent variable, employment growth, is defined as the change in the log of employment in a sector in a particular area over the period [1995][1996][1997][1998][1999][2000][2001][2002]. This time period is one of positive economic growth and stable levels of diversity and, consequently, the impact of diversity can be examined in the absence of major changes in economic structure (BISHOP AND GRIPAIOS, 2007). However, it is important to recognise that the relationship between diversity and growth may change in more turbulent periods.…”

Neighborhood Change in Metropolitan America, 1990 to 2010

“…White (1986) produced two diversity measurements: the entropy or Shannon index, and the interaction or Simpson index. Entropy is favored by many authors as a principal measure of diversity, evenness, or segregation (Bishop and Gripaios, 2007;Fischer, 2003Fischer, , 2008, which allows for comparisons among more than two groups (Fischer, 2003) and avoids the problem of subjectivity.…”

Untitled

“…Cross-sector fertilisation is possible with the existence of service industrial clusters as they enable structural change and innovation (Bishop and Gripaios 2007). Cooperation among cluster firms from different sectors or industries results in effective value chains that are characterised by innovation, knowledge transfer and new product development (Tallman et al 2004;Hansen and Birkinshaw 2007).…”