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Improvement on the association strength: implementing a probabilistic measure based on combinations without repetition

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  • Mathieu P.A. Steijn

Abstract

The use of co-occurrence data is common in various domains. Co-occurrence data often needs to be normalised to correct for the size-e↵ect. To this end, van Eck and Waltman (2009) recommend a probabilistic measure known as the association strength. However, this formula is based on combinations with repetition, even though in most uses self-co-occurrences are non-existent or irrelevant. A more accurate measure based on combinations without repetition is introduced here and compared to the original formula in mathematical derivations, simulations, and patent data, which shows that the original formula overestimates the relation between a pair and that some pairs are disproportionally more overestimated than others. The new measure is available in the EconGeo package for R by Balland (2016).

Suggested Citation

  • Mathieu P.A. Steijn, 2020. "Improvement on the association strength: implementing a probabilistic measure based on combinations without repetition," Papers in Evolutionary Economic Geography (PEEG) 2043, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Sep 2020.
    • Handle: RePEc:egu:wpaper:2043
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    File URL: http://econ.geo.uu.nl/peeg/peeg2043.pdf
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    References listed on IDEAS

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    4. Ron Boschma & Pierre-Alexandre Balland & Dieter Franz Kogler, 2015. "Relatedness and technological change in cities: the rise and fall of technological knowledge in US metropolitan areas from 1981 to 2010," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 24(1), pages 223-250.
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    6. Frank Neffke & Martin Henning & Ron Boschma & Karl-Johan Lundquist & Lars-Olof Olander, 2011. "The Dynamics of Agglomeration Externalities along the Life Cycle of Industries," Regional Studies, Taylor & Francis Journals, vol. 45(1), pages 49-65.
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