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Improving Local Governments’ Financial Sustainability by Using Open Government Data: An Application of High-Granularity Estimates of Personal Income Levels in Romania

Author

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  • Vlad-Cosmin Bulai

    (Department of Business and Economics, Faculty of International Business and Economics, The Bucharest University of Economic Studies, 010374 Bucharest, Romania)

  • Alexandra Horobeț

    (Department of Business and Economics, Faculty of International Business and Economics, The Bucharest University of Economic Studies, 010374 Bucharest, Romania)

  • Lucian Belascu

    (Department of Management, Marketing and Business Administration, Faculty of Economic Sciences, “Lucian Blaga” University of Sibiu, 550224 Sibiu, Romania)

Abstract

The availability of open government data has expanded considerably in recent years. This expansion is expected to generate significant benefits not just for increasing government transparency, but also for the economy. The aim of this study is to illustrate the use of open government data in estimating personal income levels for all 3181 municipalities, towns, and communes in Romania. The novelty of our work comes from the high granularity of the estimates obtained. We use tax revenues collected by local governments in Romania on vehicles and buildings owned by natural persons, as well as data on energy subsidies. The classification is conducted using the k-means clustering algorithm. We find three distinct clusters of communities, which we map. The results can benefit both businesses and policymakers. The former can use the income level estimates for market intelligence purposes, while for the latter, these may aid in determining the financial sustainability of local governments and a better allocation of central government resources at the subnational level.

Suggested Citation

  • Vlad-Cosmin Bulai & Alexandra Horobeț & Lucian Belascu, 2019. "Improving Local Governments’ Financial Sustainability by Using Open Government Data: An Application of High-Granularity Estimates of Personal Income Levels in Romania," Sustainability, MDPI, vol. 11(20), pages 1-11, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:20:p:5632-:d:275872
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    References listed on IDEAS

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    1. András Bethlendi & Csaba Lentner, 2018. "Subnational Fiscal Consolidation: The Hungarian Path from Crisis to Fiscal Sustainability in Light of International Experiences," Sustainability, MDPI, vol. 10(9), pages 1-16, August.
    2. Erico Przeybilovicz & Wesley Vieira da Silva & Maria Alexandra Cunha, 2015. "Limits and Potential for eGov and Smart City in Local Government: A Cluster Analysis Concerning ICT Infrastructure and Use," International Journal of E-Planning Research (IJEPR), IGI Global, vol. 4(2), pages 39-56, April.
    3. Hongbo Jiang & Qigan Shao & James J.H. Liou & Ting Shao & Xiaosheng Shi, 2019. "Improving the Sustainability of Open Government Data," Sustainability, MDPI, vol. 11(8), pages 1-27, April.
    4. Per Ronnas, 1989. "Turning the Romanian peasant into a new socialist man: An assessment of rural development policy in Romania," Europe-Asia Studies, Taylor & Francis Journals, vol. 41(4), pages 543-559.
    5. Jan Schepers & Eva Ceulemans & Iven Mechelen, 2008. "Selecting Among Multi-Mode Partitioning Models of Different Complexities: A Comparison of Four Model Selection Criteria," Journal of Classification, Springer;The Classification Society, vol. 25(1), pages 67-85, June.
    6. Glenn Milligan & Martha Cooper, 1985. "An examination of procedures for determining the number of clusters in a data set," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 159-179, June.
    7. Andrés Navarro-Galera & Manuel Pedro Rodríguez-Bolívar & Laura Alcaide-Muñoz & María Deseada López-Subires, 2016. "Measuring the financial sustainability and its influential factors in local governments," Applied Economics, Taylor & Francis Journals, vol. 48(41), pages 3961-3975, September.
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    Cited by:

    1. Cristina Raluca Gh. Popescu & Gheorghe N. Popescu, 2019. "An Exploratory Study Based on a Questionnaire Concerning Green and Sustainable Finance, Corporate Social Responsibility, and Performance: Evidence from the Romanian Business Environment," JRFM, MDPI, vol. 12(4), pages 1-79, October.
    2. Vicente Pina & Patricia Bachiller & Lara Ripoll, 2020. "Testing the Reliability of Financial Sustainability. The Case of Spanish Local Governments," Sustainability, MDPI, vol. 12(17), pages 1-22, August.
    3. Inna Gryshova & Tatyana Shabatura & Stasys Girdzijauskas & Dalia Streimikiene & Remigijus Ciegis & Ingrida Griesiene, 2019. "The Paradox of Value and Economic Bubbles: New Insights for Sustainable Economic Development," Sustainability, MDPI, vol. 11(24), pages 1-17, December.
    4. Francisco Cifuentes-Silva & Daniel Fernández-Álvarez & Jose Emilio Labra-Gayo, 2020. "National Budget as Linked Open Data: New Tools for Supporting the Sustainability of Public Finances," Sustainability, MDPI, vol. 12(11), pages 1-12, June.

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