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Municipal population size and the benefits of inter-municipal cooperation: panel data evidence from Japan

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  • Hiroki Baba
  • Yasushi Asami

Abstract

Intermunicipal cooperation (IMC) facilitates efficient public service delivery. This study measures how the benefits municipalities gain through IMC differ according to municipal population size and service provision type. Focusing on public health and fire protection services, this study employs panel data regression for 1,706 Japanese municipalities over a five-year period, 2012–2017. This study has several major findings. First, an increase in the IMC spending ratio reduces public spending in both the studied services. Second, the marginal effect of IMC varies depending on the size of the municipal population. More specifically, the marginal effect of IMC on public health has a narrow confidence interval with a wide ranging population scale, while the marginal effect of IMC on fire protection produces negative values for only 151 municipalities due to extensive standard error. These findings can help municipalities take advantage of IMC to improve public service delivery.

Suggested Citation

  • Hiroki Baba & Yasushi Asami, 2020. "Municipal population size and the benefits of inter-municipal cooperation: panel data evidence from Japan," Local Government Studies, Taylor & Francis Journals, vol. 46(3), pages 371-393, May.
  • Handle: RePEc:taf:flgsxx:v:46:y:2020:i:3:p:371-393
    DOI: 10.1080/03003930.2019.1624257
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    Cited by:

    1. Eva Wolfschuetz, 2020. "The Effect of Inter-municipal Cooperation on Local Business Development in German Municipalities," MAGKS Papers on Economics 202005, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    2. Hiroki Baba & Yasushi Asami, 2022. "Cost-efficient factors in local public spending: Detecting relationships between local environments, population size and urban area category," Environment and Planning B, , vol. 49(1), pages 241-258, January.

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