IDEAS home Printed from https://ideas.repec.org/p/pum/wpaper/2013-09.html
   My bibliography  Save this paper

Optimizing Distance-Based Methods for Big Data Analysis

Author

Listed:
  • Tobias Scholl

    (House of Logistics and Mobility (HOLM), Frankfurt and Economic Geography and Location Research, Philipps-University, Marburg)

  • Thomas Brenner

    (Philipps-Universität Marburg)

Abstract

Distance-based methods for measuring spatial concentration such as the Duranton-Overman index undergo an increasing popularity in the spatial econometrics community. However, a limiting factor for their usage is their computational complexity since both their memory requirements and running-time are in O(n2). In this paper, we present an algorithm with constant memory requirements and an improved running time, enabling the Duranton-Overman index and related distance-based methods to run big data analysis. Furthermore, we discuss the index by Scholl and Brenner (2012) whose mathematical concept allows an even faster computation for large datasets than the improved algorithm does.

Suggested Citation

  • Tobias Scholl & Thomas Brenner, 2013. "Optimizing Distance-Based Methods for Big Data Analysis," Working Papers on Innovation and Space 2013-09, Philipps University Marburg, Department of Geography.
    • Handle: RePEc:pum:wpaper:2013-09
    as

    Download full text from publisher

    File URL: https://repec.geographie.uni-marburg.de/pum/wpaper/wp0913.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stefania Vitali & Mauro Napoletano & Giorgio Fagiolo, 2013. "Spatial Localization in Manufacturing: A Cross-Country Analysis," Regional Studies, Taylor & Francis Journals, vol. 47(9), pages 1534-1554, October.
    2. Tobias Scholl & Thomas Brenner, 2013. "Detecting Spatial Clustering Using a Firm-Level Index," Working Papers on Innovation and Space 2012-02, Philipps University Marburg, Department of Geography.
    3. Harvey J. Miller, 2010. "The Data Avalanche Is Here. Shouldn’T We Be Digging?," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 181-201, February.
    4. repec:hal:spmain:info:hdl:2441/9932 is not listed on IDEAS
    5. Thomas Klier & Daniel P. McMillen, 2008. "Evolving Agglomeration In The U.S. Auto Supplier Industry," Journal of Regional Science, Wiley Blackwell, vol. 48(1), pages 245-267, February.
    6. repec:hal:wpspec:info:hdl:2441/9932 is not listed on IDEAS
    7. Glenn Ellison & Edward L. Glaeser & William R. Kerr, 2010. "What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns," American Economic Review, American Economic Association, vol. 100(3), pages 1195-1213, June.
    8. Eric Marcon & Florence Puech, 2003. "Evaluating the Geographic Concentration of Industries Using Distance-Based Methods," Post-Print halshs-00372646, HAL.
    9. Reinhold Kosfeld & Hans-Friedrich Eckey & Jørgen Lauridsen, 2011. "Spatial point pattern analysis and industry concentration," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 47(2), pages 311-328, October.
    10. Eric Marcon & Florence Puech, 2010. "Measures of the geographic concentration of industries: improving distance-based methods," Journal of Economic Geography, Oxford University Press, vol. 10(5), pages 745-762, September.
    11. Eric Marcon & Florence Puech, 2003. "Evaluating the geographic concentration of industries using distance-based methods," Journal of Economic Geography, Oxford University Press, vol. 3(4), pages 409-428, October.
    12. Eric Marcon & Florence Puech, 2003. "Evaluating the Geographic Concentration of Industries Using Distance-Based Methods," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00372646, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gibbons, Steve & Overman, Henry G. & Patacchini, Eleonora, 2015. "Spatial Methods," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 115-168, Elsevier.
    2. Marcon, Eric & Traissac, Stéphane & Puech, Florence & Lang, Gabriel, 2015. "Tools to Characterize Point Patterns: dbmss for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(c03).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tobias Scholl & Thomas Brenner, 2015. "Optimizing distance-based methods for large data sets," Journal of Geographical Systems, Springer, vol. 17(4), pages 333-351, October.
    2. Gibbons, Steve & Overman, Henry G. & Patacchini, Eleonora, 2015. "Spatial Methods," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 115-168, Elsevier.
    3. 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.
    4. Hiroyasu Inoue & Kentaro Nakajima & Yukiko Umeno Saito, 2019. "Localization of collaborations in knowledge creation," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(1), pages 119-140, February.
    5. Tobias Scholl & Thomas Brenner, 2013. "Detecting Spatial Clustering Using a Firm-Level Index," Working Papers on Innovation and Space 2012-02, Philipps University Marburg, Department of Geography.
    6. Nakajima, Kentaro & Saito, Yukiko Umeno & Uesugi, Iichiro, 2012. "Measuring economic localization: Evidence from Japanese firm-level data," Journal of the Japanese and International Economies, Elsevier, vol. 26(2), pages 201-220.
    7. Tobias Scholl & Thomas Brenner & Martin Wendel, 2016. "Evolving localization patterns of company foundationsEvidence from the German MST-industry," Journal of Evolutionary Economics, Springer, vol. 26(5), pages 1067-1087, December.
    8. Robert Schweizog & Alan Collins, 2015. "A Simple Location Index Plus Some Maps and no Apologies: Back to Basics on the Development of Links Between Economic Integration and Spatial Concentration of Industries," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 106(1), pages 17-35, February.
    9. Ana Isabel Moreno-Monroy & Gustavo Adolfo García Cruz, 2016. "Intra-Metropolitan Agglomeration of Formal and Informal Manufacturing Activity: Evidence from Cali, Colombia," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 107(4), pages 389-406, September.
    10. Jean Dubé & Cédric Brunelle, 2014. "Dots to dots: a general methodology to build local indicators using spatial micro-data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 245-272, August.
    11. Eckhardt Bode & Franz-Josef Bade Bade & Eleonora Cutrini Cutrini, 2011. "Domestic and International Offshoring of Tasks," ERSA conference papers ersa11p1840, European Regional Science Association.
    12. 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.
    13. Marta R. Casanova & Vicente Orts & José M. Albert, 2017. "Sectoral scope and colocalisation of Spanish manufacturing industries," Journal of Geographical Systems, Springer, vol. 19(1), pages 65-92, January.
    14. Behrens, Kristian & Bougna, Théophile, 2015. "An anatomy of the geographical concentration of Canadian manufacturing industries," Regional Science and Urban Economics, Elsevier, vol. 51(C), pages 47-69.
    15. Barlet, M. & Briant, A. & Crusson, L., 2013. "Location patterns of service industries in France: A distance-based approach," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 338-351.
    16. Bade, Franz-Josef & Bode, Eckhardt & Cutrini, Eleonora, 2011. "Does domestic offshoring precede international offshoring? Industry-level evidence," Kiel Working Papers 1699, Kiel Institute for the World Economy (IfW Kiel).
    17. Giulio Cainelli & Roberto Ganau & Yuting Jiang, 2020. "Detecting space–time agglomeration processes over the Great Recession using firm-level micro-geographic data," Journal of Geographical Systems, Springer, vol. 22(4), pages 419-445, October.
    18. Giuseppe Espa & Giuseppe Arbia & Diego Giuliani, 2013. "Conditional versus unconditional industrial agglomeration: disentangling spatial dependence and spatial heterogeneity in the analysis of ICT firms’ distribution in Milan," Journal of Geographical Systems, Springer, vol. 15(1), pages 31-50, January.
    19. William R. Kerr & Scott Duke Kominers, 2015. "Agglomerative Forces and Cluster Shapes," The Review of Economics and Statistics, MIT Press, vol. 97(4), pages 877-899, October.
    20. Valerien O. Pede & Raymond J. G. M. Florax & Henri L. F. de Groot & Gustavo Barboza, 2021. "Technological leadership and sectorial employment growth: A spatial econometric analysis for U.S. counties," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 50(1), February.

    More about this item

    Keywords

    Spatial concentration; Duranton-Overman index; big-data analysis; MAUP; distance-based measures;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pum:wpaper:2013-09. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Robert Csicsics (email available below). General contact details of provider: https://edirc.repec.org/data/vamarde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.