The Overlooked Insights from Correlation Structures in Economic Geography

Matias Iglesias

No 2105, Papers in Evolutionary Economic Geography (PEEG) from Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography

Abstract: Measures of cooccurrence computed from cross sectional data are used to rationalize connections among economic activities. In this work we show the grounds for unifying a multiplicity of similarity techniques applied in the literature and we precise the identification of cooccurrence to actual coexistence in space, when one side of the cross section are small administrative areas. All the similarity techniques studied here are akin to a correlation structure computed from spatial intensity, also known as locational correlation. We argue that these correlations offer objective tools to detect spatial patterns. Indeed we show that when applied to data of employment by industry and county in United States (from 2002-7) the communities of networks derived from locational correlations detect spatial patterns long acknowledged in economic geography. By addressing critical open issues on the interpretation of cooccurrence indices, this work o↵ers technical guides for their exploitation in Economic Geography studies.

Keywords: Economic geography; co-location; spatial analysis; areal data; point data; correlation structures; distribution of economic activities (search for similar items in EconPapers)
Date: 2021-01, Revised 2021-01
New Economics Papers: this item is included in nep-big, nep-geo and nep-ure
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