Which estimator to measure local governments’ cost efficiency? The case of Spanish municipalities

Abstract

We analyse overall cost efficiency in Spanish local governments during the crisis period (2008-2015). To this end, we first consider some of the most popular nonparametric methods to evaluate local government efficiency, data envelopment analysis and free disposal hull, as well as recent proposals, namely the order-m partial frontier and the nonparametric estimator proposed by Kneip et al. (Econom Theory 24(6):1663-1697, 2008). Second, to compare the four methods and choose the most appropriate one for our particular context and dataset (local government cost efficiency in Spain), we carry out an experiment via Monte Carlo simulations and discuss the relative performance of the efficiency scores under various scenarios. Our results suggest that there is no one approach suitable for all efficiency analysis. We find that for our sample of 1846 Spanish local governments, the average cost efficiency would have been between 0.5417 and 0.7543 during the period 2008-2015, suggesting that Spanish local governments could have achieved the same level of local outputs with about 25% and 46% fewer resources. Keywords Efficiency • Local government • Monte Carlo simulations • Nonparametric frontiers JEL Classification C14 • C15 • H70 • R15 We thank Víctor Giménez, Diego Prior, and José Luis Zafra for helpful suggestions. We are particularly grateful to two anonymous reviewers whose comments have contributed to improve the overall quality of the paper. All authors acknowledge the financial support of the Ministerio de Economía y Competitividad (ECO2017-88241-R and ECO2017-85746-P), Generalitat Valenciana (PROMETEO/2018/102) and Universitat Jaume I (UJI-B2017-33 and UJI-B2017-14). The usual disclaimer applies.

Quality of government and economic growth at the municipal level: Evidence from Spain

“…Third, given the intricacy of selecting the bundle of output variables to be included in the efficiency analysis (Balaguer‐Coll et al, 2013) as well as the number of variables to include in the efficiency analysis, we considered an alternative output specification model to assess the robustness of our results (Narbón‐Perpiñá et al, 2019; Narbón‐Perpiñá et al, 2020; Narbón‐Perpiñá & De Witte, 2018a; Narbón‐Perpiñá et al, 2021). Specifically, this second output specification includes only six output variables (instead of 10) which represent all the minimum compulsory services for all local governments, regardless of their population size (see the first horizontal panel in table 2).…”

“…On the output side, the selection of variables is a complex task, given the difficulties in the data collecting process, the availability of data, and the accurate and direct measurement of local services and facilities provision (Balaguer‐Coll et al, 2013). Following previous literature focused on Spanish municipalities (e.g., Balaguer‐Coll & Prior, 2009; Balaguer‐Coll et al, 2007, 2013; Bosch‐Roca et al, 2012; Narbón‐Perpiñá et al, 2019; Narbón‐Perpiñá et al, 2020; Zafra‐Gómez & Muñiz‐Pérez, 2010) as well as others papers focused on different European countries (e.g., Cordero et al, 2017; DaCruz & Marques, 2014; Doumpos & Cohen, 2014; Kalb et al, 2012; Štastná & Gregor, 2015), we use proxies for the services and facilities provided to citizens. Specifically, we selected 10 output variables which represent the specific services and facilities that municipalities should provide according to the Spanish law which regulates the local system ( Ley 7/1985, Reguladora de Bases de Régimen Local ).…”

“…Regarding the variables used to compute the efficiency estimator for each municipality, on the input side, the variable used represents the total costs of the municipal services and facilities provided (). The use of budget expenditures as inputs is a common practice in previous literature given the unavailability of data for the costs of each municipal service and facility (e.g., Balaguer‐Coll & Prior, 2009; Balaguer‐Coll et al, 2007, 2010, 2013; Bosch et al, 2000; DaCruz & Marques, 2014; Narbón‐Perpiñá et al, 2019; Narbón‐Perpiñá et al, 2020; Narbón‐Perpiñá et al, 2020; Prior et al, 2019; Zafra‐Gómez & Muñiz‐Pérez, 2010). Our variable is calculated by using information retrieved from the municipal budget expenditures annually published by the Ministry of the Treasury ( Ministerio de Hacienda ).…”

Women's management in local government: The effects of substantive representation on welfare service efficiency

“…Data Envelopment Analysis (DEA) is the most suitable and most often used non‐parametric method for calculating efficiency in the public sector. Although there are other non‐parametric (Free Disposable Hull, Order‐m) and parametric (Stochastic Frontier Analysis) methods, DEA works best to analyse local governments in Spain (Narbón‐Perpiñá et al, 2019). Furthermore, it allows for the selection of multiple inputs and outputs, is adaptable to situations where factor pricing is difficult and does not require prior knowledge of the production function.…”

“…Much literature has analysed the efficiency of different public services (water, rubbish, street lighting, etc. ), but very few studies have dealt with welfare services at the local level (Narb on-Perpiñá et al, 2019). The literature has also extensively discussed substantive representation from a theoretical perspective (see Section 2) without paying much attention to quantitative evaluation.…”