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flowbca: A flow-based cluster algorithm in Stata

Author

Listed:
  • Jordy Meekes

    (Utrecht University School of Economics)

  • Wolter H. J. Hassink

    (Utrecht University School of Economics)

Abstract

In this article, we introduce the Stata implementation of a flow-based cluster algorithm, flowbca, written in Mata. The main purpose of flowbca is to identify clusters based on relational data of flows. We illustrate the command by providing multiple examples of applications from the research fields of economic geography, industrial input–output analysis, and social network analysis.

Suggested Citation

  • Jordy Meekes & Wolter H. J. Hassink, 2018. "flowbca: A flow-based cluster algorithm in Stata," Stata Journal, StataCorp LP, vol. 18(3), pages 564-584, September.
    • Handle: RePEc:tsj:stataj:y:18:y:2018:i:3:p:564-584
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    Cited by:

    1. Stenfors, Alexis & Susai, Masayuki, 2021. "Spoofing and pinging in foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).
    2. Jordy Meekes, 2022. "Agglomeration Economies and the Urban Wage Premium in Australia," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 25(1), pages 25-54.
    3. Jordy Meekes & Wolter H. J. Hassink, 2023. "Endogenous local labour markets, regional aggregation and agglomeration economies," Regional Studies, Taylor & Francis Journals, vol. 57(1), pages 13-25, January.
    4. Michael Coelli & James Maccarrone & Jeff Borland, 2023. "The dragon Down Under: the regional labour market impact of growth in Chinese imports to Australia," Regional Studies, Taylor & Francis Journals, vol. 57(11), pages 2148-2163, November.

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