Is there an optimal size for local governments? A spatial panel data model approach
EntityUAM. Departamento de Economía y Hacienda Pública
PublisherTaylor and Francis
10.1080/00343404.2019.1648786Regional Studies 54.7 (2020): 958 - 973
ISSN0034-3404 (print); 1360-0591 (online)
Funded byThis work was supported by the Ministerio de Economía y Competitividad (Spain) [grant number ECO2016-76681-R]
ProjectGobierno de España. ECO2016-76681-R
Subjectsoptimal government size; Spanish municipalities; spatial panels; topography; Economía
NoteThis is an Accepted Manuscript version of the following article, accepted for publication in Regional Studies 54.7 (2020): 958 - 973. It is deposited under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited
Rights© 2020 Taylor and Francis
Esta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial 4.0 Internacional.
The paper presents a framework for determining the optimal size of local jurisdictions and whether it varies depending on the geographical heterogeneity of the territory. To that aim, it first develops a theoretical model of cost efficiency that takes into account spatial interactions and spillover effects among neighbouring jurisdictions. The model solution leads to a spatial Durbin panel data specification of local spending as a non-linear function of population size. The model is tested using a large local data set over the period 2003–11 for an aggregate measure of public spending. The empirical findings suggest a ‘U’-shaped relationship between population size and the costs of providing public services. A second step investigates the role of geographical characteristics such as elevation and terrain ruggedness in the determination of the optimal jurisdiction size. The results reveal that optimal city size decreases with elevation and increases with ruggedness
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