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Effects of the General System of Royalties on municipal fiscal performance in Colombia: a dose-response analysis

Author

Listed:
  • Jaime Bonet
  • Karelys Guzman
  • Joaquin Urrego
  • Juan Villa

Abstract

There is an extensive literature on the impact of nonrenewable natural resources (NNR) in the fiscal performance of countries. Overall, with few exceptions, the studies suggest an inverse relationship between these two variables. According to the IDB (2013), the presence of NNR can lead to the so called 'resource curse', where the abundance of income that comes from this source adversely affects institutional capacity, governance, and economic growth. There is not too much literature about the impact of the relative abundance of NNR on the fiscal performance of sub-national governments and conflicting results have been found. One of the most recent changes in regional policy in Colombia was the creation of the General Royalties System (SGR by its Spanish acronym) in 2011. Before the new scheme, royalties were distributed to those territories where NNR were extracted and to the maritime or river ports used to transport these resources. With the creation of SGR, these resources began to be distributed between all municipalities and departments through various funds and according to the socioeconomic conditions of each territory. As a result of the increased mining and energy production, royalties increased from 0.6% of GDP in 2002 to 1.66% in 2012. These resources are an important source of funding for projects in sub-national governments. For municipalities, these funds are twice the amount collected by two of the most important municipal taxes, property tax and industry and commerce tax. This is an excellent opportunity to assess the impact of the new system on the fiscal behavior of local authorities. This paper evaluates the effects of the implementation of the SGR on the fiscal performance at the municipality level in 2012, employing a dose-response analysis based on Hirano and Imbens (2004) for a sample of 1,025 municipalities. Unlike conventional impact evaluations comparing treatment and control groups, the dose-response analysis compares municipalities with higher and lower allocation of royalties. The non-randomness of assignments is controlled by estimating the generalized propensity score. The results indicate that a level of 20% allocation of royalties in the total revenue of the municipalities represents an important threshold performance of these localities. It was found that in the 93% of municipalities, where the proportion of royalties in their total revenues are less or equal to 20%, the fiscal performance measured by several indexes worsens, while the dependency on the royalties increases. On the other hand, if such proportion is higher than 20% the fiscal performance improves but the local investment falls. Given that the reform assigned resources but did not guarantee their appropriation by the municipalities, these results can be explained by the low execution of royalties during 2012.

Suggested Citation

  • Jaime Bonet & Karelys Guzman & Joaquin Urrego & Juan Villa, 2015. "Effects of the General System of Royalties on municipal fiscal performance in Colombia: a dose-response analysis," ERSA conference papers ersa15p312, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa15p312
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    References listed on IDEAS

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    1. Fernando Antonio Slaibe Postali & Fabiana Fontes Rocha, 2011. "Resource windfalls,fiscal effort and public spending: evidence from Brazilianmunicipalities," Anais do XXXVII Encontro Nacional de Economia [Proceedings of the 37th Brazilian Economics Meeting] 64, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    2. José A. Tijerina–Guajardo & José A. Pagán, 2003. "Government Spending, Taxation, and Oil Revenues in Mexico," Review of Development Economics, Wiley Blackwell, vol. 7(1), pages 152-164, February.
    3. Alejandro Gaviria Uribe & Juan Gonzalo Zapata & Adriana González, 2002. "Petróleo y región: El caso del Casanare," Cuadernos de Fedesarrollo 12733, Fedesarrollo.
    4. Jaime Bonet Morón, 2007. "Regalías y finanzas públicas en el Departamento del Cesar," Documentos de Trabajo Sobre Economía Regional y Urbana 4308, Banco de la República, Economía Regional.
    5. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    6. Michela Bia & Alessandra Mattei, 2008. "A Stata package for the estimation of the dose–response function through adjustment for the generalized propensity score," Stata Journal, StataCorp LP, vol. 8(3), pages 354-373, September.
    7. Guillermo Perry & Mauricio Olivera, 2010. "El impacto del petróleo y la minería en el desarrollo regional y local en Colombia," Working Papers Series. Documentos de Trabajo 9070, Fedesarrollo.
    8. Kosuke Imai & David A. van Dyk, 2004. "Causal Inference With General Treatment Regimes: Generalizing the Propensity Score," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 854-866, January.
    9. Mr. Steven A Barnett & Mr. Rolando Ossowski, 2002. "Operational Aspects of Fiscal Policy in Oil-Producing Countries," IMF Working Papers 2002/177, International Monetary Fund.
    10. Perry, Guillermo & Olivera, Mauricio, 2009. "El impacto del petróleo y la minería en el desarrollo regional y local en Colombia," Research Department working papers 199, CAF Development Bank Of Latinamerica.
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    Cited by:

    1. Collazos-Ortiz, María Antonieta & Wong, Pui-Hang, 2024. "The effects of resource rents and elections on human capital investment in Colombia," Resources Policy, Elsevier, vol. 89(C).

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    More about this item

    Keywords

    Dose-Response Analysis; fiscal performance; Royalties; Colombia;
    All these keywords.

    JEL classification:

    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation
    • H71 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Taxation, Subsidies, and Revenue
    • Q38 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Government Policy (includes OPEC Policy)

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