Testing for Localization Using Micro-Geographic Data

Gilles Duranton and Henry Overman

No 3379, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: To study the detailed location patterns of industries, and particularly the tendency for industries to cluster relative to overall manufacturing, we develop distance-based tests of localization. In contrast to previous studies, our approach allows us to assess the statistical significance of departures from randomness. In addition, we treat space as continuous instead of using an arbitrary collection of geographical units. This avoids problems relating to scale and borders. We apply these tests to an exhaustive UK data set. For four-digit industries, we find that (i) only 51% of them are localized at a 5% confidence level, (ii) localization takes place mostly at small scales below 50 kilometres, (iii) the degree of localization is very skewed, and (iv) industries follow broad sectoral patterns with respect to localization. Depending on the industry, smaller establishments can be the main drivers of both localization and dispersion. Three-digit sectors show similar patterns of localization at small scales as well as a tendency to localize at medium scales.

Keywords: Localization; Clusters; K-density; Spatial statistics (search for similar items in EconPapers)
JEL-codes: R12 (search for similar items in EconPapers)
Date: 2002-05
New Economics Papers: this item is included in nep-geo and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (52)

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Related works:
Journal Article: Testing for Localization Using Micro-Geographic Data (2005)
Working Paper: Testing for localization using micro-geographic data (2005)
Working Paper: Testing for Localisation Using Micro-Geographic Data (2003)
Working Paper: Testing for Localisation Using Micro-Geographic Data (2002)
Working Paper: Testing for localisation using micro-geographic data (2002)
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