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Flowbca: A flow-based cluster algorithm in Stata

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  • J. Meekes
  • W.H.J. Hassink

Abstract

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

Suggested Citation

  • J. Meekes & W.H.J. Hassink, 2017. "Flowbca: A flow-based cluster algorithm in Stata," Working Papers 17-09, Utrecht School of Economics.
    • Handle: RePEc:use:tkiwps:1709
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    File URL: https://dspace.library.uu.nl/bitstream/handle/1874/352470/17_09.pdf
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    Cited by:

    1. 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.
    2. Stenfors, Alexis & Susai, Masayuki, 2021. "Spoofing and pinging in foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).
    3. 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.
    4. Michael Coelli & James Maccarrone & Jeff Borland, 2021. "The dragon down under: The regional labour market impact of growth in Chinese imports to Australia," Melbourne Institute Working Paper Series wp2021n09, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.

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    Keywords

    clusters; aggregation; flows;
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