Cainelli, Giulio, Ganau, Roberto and Jiang, Yuting (2020) Detecting space–time agglomeration processes over the Great Recession using firm-level micro-geographic data. Journal of Geographical Systems, 22 (4). 419 - 445. ISSN 1435-5930
Text (Detecting space–time agglomeration processes over the Great Recession using firm-level micro-geographic data)
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Abstract
We analyze the spatio-temporal agglomeration dynamics that occurred in the Italian manufacturing industry during the recent period of the Great Recession. To study this phenomenon, we employ three different statistical methods—namely, Ellison and Glaeser’s index of industrial geographic concentration, the spatial K-function, and the space–time K-function—, and rely on a large sample of geo-referenced, single-plant manufacturing firms observed over the period 2007–2012. First, we demonstrate that different statistical techniques can lead to (very) different results. Second, we find that most Italian manufacturing sectors experienced spatial dispersion processes during the period of the Great Recession. Finally, we show that space–time dispersion processes occurred at small spatial distances and short time horizon, although we do not detect statistically significant space–time interactions.
Item Type: | Article |
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Official URL: | https://www.springer.com/journal/10109 |
Additional Information: | © 2020 The Authors |
Divisions: | Geography & Environment |
Subjects: | G Geography. Anthropology. Recreation > G Geography (General) |
Date Deposited: | 29 Jul 2020 15:54 |
Last Modified: | 20 Sep 2024 19:15 |
URI: | http://eprints.lse.ac.uk/id/eprint/105822 |
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