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Testing for Localisation Using Micro-Geographic Data

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  • Gilles Duranton
  • Henry Overman

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 localisation. 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 localised at a 5% confidence level, (ii) localisation takes place mostly at small scales below 50 kilometres, (iii) the degree of localisation is very skewed, and (iv) industries follow broad sectoral patterns with respect to localisation. Depending on the industry, smaller establishments can be the main drivers of both localisation and dispersion. Three-digit sectors show similar patterns of localisation at small scales as well as a tendency to localise at medium scales.

Suggested Citation

  • Gilles Duranton & Henry Overman, 2002. "Testing for Localisation Using Micro-Geographic Data," CEP Discussion Papers dp0540, Centre for Economic Performance, LSE.
  • Handle: RePEc:cep:cepdps:dp0540
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    References listed on IDEAS

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    More about this item

    Keywords

    Localisation; Clusters; K-density; Spatial Statistics.;
    All these keywords.

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • L70 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - General

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