Volume 56, Number 2, March-April 2022
|Page(s)||501 - 528|
|Published online||15 March 2022|
The performance of regional governments under the results-based budgeting framework: A two-stage sectoral analysis
CENTRUM Católica Graduate Business School, Lima, Peru
2 Pontifical Catholic University of Peru, Lima, Peru
3 Universidad Nacional Mayor de San Marcos, Lima, Peru
4 University Miguel Hernandez of Elche, Elche, Peru
* Corresponding author: firstname.lastname@example.org
Accepted: 2 February 2022
The results-based budgeting (RBB) framework is a public management strategy in which economic resources are allocated to certain budget programs, oriented towards delivering specific products and results to the population. The present paper analyzes the regional governments’ efficiency in using their economic resources, under the RBB framework, with an application to the Peruvian context. To this end, we employ a data envelopment analysis (DEA) model with bootstrapping. In the first stage, different sectors of the regional governments are considered individually: education, security, health, sanitation, transportation, and recreation. In the second stage, the overall efficiency index is calculated using the sectoral indices obtained in the first stage. Finally, the factors or determinants influencing the level of efficiency are analyzed. The results show improvements in efficiency levels in the areas of health and sanitation, to the detriment of the rest of the sectors. The average overall efficiency level over the period 2013–2016 remains in the range of 0.25–0.30, which indicates an inefficiency level of 70%. Finally, the variables fiscal autonomy, capital stock, and population density show a positive relationship with respect to the overall efficiency index.
Mathematics Subject Classification: C14 / D61 / H61 / R58
Key words: Public resources / performance / efficiency / DEA / bootstrapping
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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