
Testing for Localization Using Micro‐Geographic Data
Author(s) -
Duranton Gilles,
Overman Henry G.
Publication year - 2005
Publication title -
review of economic studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 15.641
H-Index - 141
eISSN - 1467-937X
pISSN - 0034-6527
DOI - 10.1111/0034-6527.00362
Subject(s) - randomness , scale (ratio) , econometrics , set (abstract data type) , space (punctuation) , contrast (vision) , dispersion (optics) , cluster (spacecraft) , statistics , computer science , economics , mathematics , geography , artificial intelligence , cartography , physics , optics , programming language , operating system
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 U.K. data‐set. For four‐digit industries, we find that (i) 52% of them are localized at a 5% confidence level, (ii) localization mostly takes place at small scales below 50 km, (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.