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A typology of distance-based measures of spatial concentration

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  • Marcon, Eric
  • Puech, Florence

Abstract

Over the last decade, distance-based methods have been introduced and then improved in the field of spatial economics to gauge the geographic concentration of activities. There is a growing literature on this theme including new tools, discussions on their specific properties and various applications. However, there is currently no typology of distance-based methods. This paper fills that gap. The proposed classification helps understand all the properties of distance-based methods and proves that they are variations on the same framework.

Suggested Citation

  • Marcon, Eric & Puech, Florence, 2017. "A typology of distance-based measures of spatial concentration," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 56-67.
    • Handle: RePEc:eee:regeco:v:62:y:2017:i:c:p:56-67
    DOI: 10.1016/j.regsciurbeco.2016.10.004
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    Cited by:

    1. A. Tidu & S. Usai & Frederick Guy, 2021. "Agglomeration in manufacturing and services: an experimental application of a distance-based measure to Sardinia," Working Paper CRENoS 202110, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. Smirnova, Ekaterina & Khormali, Omid & Egan, Joel M., 2019. "Functional analysis of spatial aggregation regions of Jeffrey pine beetle-attack within the Lake Tahoe Basin," Statistics & Probability Letters, Elsevier, vol. 144(C), pages 57-62.
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    4. Gabriel Lang & Eric Marcon & Florence Puech, 2020. "Distance-based measures of spatial concentration: introducing a relative density function," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 243-265, April.
    5. Xiaoxiang Zhang & Jing Yao & Katarzyna Sila-Nowicka & Chonghui Song, 2021. "Geographic concentration of industries in Jiangsu, China: a spatial point pattern analysis using micro-geographic data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 66(2), pages 439-461, April.
    6. Mauro Ferrante & Giovanni Luca Lo Magno & Stefano De Cantis & Geoffrey J.D. Hewings, 2020. "Measuring spatial concentration: A transportation problem approach," Papers in Regional Science, Wiley Blackwell, vol. 99(3), pages 663-682, June.
    7. Ludwig von Auer & Mark Trede, 2021. "Urbanization in Industrialized Countries: Appearances Are Deceptive," Research Papers in Economics 2021-04, University of Trier, Department of Economics.
    8. Shuju Hu & Wei Song & Chenggu Li & Charlie H. Zhang, 2019. "The Evolution of Industrial Agglomerations and Specialization in the Yangtze River Delta from 1990–2018: An Analysis Based on Firm-Level Big Data," Sustainability, MDPI, vol. 11(20), pages 1-21, October.
    9. S. Usai & Frederick Guy & A. Tidu, 2022. "Measuring spatial dispersion: an experimental test on the M-index," Working Paper CRENoS 202206, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

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    More about this item

    Keywords

    Spatial concentration; Aggregation; Point patterns; Agglomeration; Economic geography;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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