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Ownership and Performance in Water Services Revisited: Does Private Management Really Outperform Public?

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Abstract

Since the late 1970s, water services have been privatised in some developed countries in an attempt to improve performance. However, after three decades of privatisations the superiority of private management is being called into question and several cities are returning to public provision. In this paper we revisit the relationship between ownership and performance in urban water services management using directional distance functions, metafrontiers and Data Envelopment Analysis (DEA) techniques. The technical efficiency in the provision of water delivery services in a sample of Spanish municipalities is assessed at the level of the management of specific production factors; moreover, we discuss whether differences in efficiency between private and public decision units are due to either different capabilities of managers (managerial efficiency) or different technological restrictions (ownership efficiency). Our main finding is that private management is more efficient in the use of labour input, mainly because of the technological restrictions faced by public management units, such as legal and institutional restrictions. Conversely, private management appears to be less efficient at managing operational costs.

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Notes

  1. In addition, some papers have analysed the impact of changes in regulation on the performance of the privatised English and Welsh water industry (Erbetta and Cave 2007; Maziotis et al. 2016).

  2. In addition to water delivery, some water utilities in Spain also provide sewage treatment services; however, this is not the case with the operators in our sample.

  3. García-Valiñas et al. (2013) provides a detailed description of legal forms for the management of urban water services in Spain. Furthermore, following previous literature, institutionalised PPPs have been considered as private management units given that day-to-day management is carried out by the private partner (see García-Valiñas et al. 2013; Picazo-Tadeo et al. 2012). Finally, it is worth mentioning that in compliance with Spanish law only the management of the urban water service can be privatised, while infrastructures always remain under public property.

  4. Spanish legislation prevents data on inputs and outputs of water suppliers from being made public. When creating our database, we submitted information requests to nearly 1000 Spanish municipalities, either via web pages or directly to city councils and utilities. Of these, we received 141 positive responses. After discarding observations with deficient or incomplete information, we selected 70 operators that are exclusively dedicated to water service delivery. Unfortunately, the aforementioned lack of publicly-available information makes it very difficult to obtain reliable and largely representative data on the production processes of Spanish water services operators. This is reflected in previous studies on Spanish water utilities, which make use of samples of similar size (Picazo-Tadeo et al. 2011; Picazo-Tadeo et al. 2009a, 2009b).

  5. Operational costs include all expenses required for day-to-day management of the service, e.g., raw water, chemicals employed to make water suitable for human consumption, energy and office expenses, among others. Conversely, wages and other labour costs are excluded. Furthermore, the fee paid by utilities to the local government when they are first awarded the service management contract is also excluded from operational costs. Finally, it is worth highlighting that operational costs are measured in euros, which means that computed technical efficiency might also include a component of allocative (price) efficiency. This is, however, a common problem in efficiency analyses that would have only a minor impact on the measurement of technical efficiency if production factor markets are assumed to be competitive with small price differences.

  6. See Beltrán-Esteve (2013), Beltrán-Esteve et al. (2014) and Picazo-Tadeo et al. (2014) for recent empirical applications of this approach.

  7. In this general setting, best practices are determined by those productive plans, either observed productive plans or resulting from their linear combinations, which obtain more outputs with fewer variable inputs usage, always for given endowment of the fixed input.

  8. By construction, directional distance functions computed relative to the technology of group h will always be equal to or lower than directional metadistance functions computed with respect to the metatechnology.

  9. The reason for this choice is that, although directional metadistance/distance functions can also be directly interpreted as measures of technical efficiency, distances for efficient management units are equal to zero and, thus, metatechnology ratios would not be defined for these operators (Sáez-Fernández et al. 2012).

  10. For example, a score for the directional distance function in the radial scenario of 0.1 would indicate, as already mentioned, that outputs could be maintained while reducing labour and operational costs by 10 %. In this case, the technical efficiency score would be 0.9, indicating that it would be possible to maintain the same level of water delivered and population served with only 90 % of observed inputs usage.

  11. Note that the exactness of the decomposition of technical efficiency presented in this table does not hold at the aggregate level due to the use of arithmetic means.

  12. This does not necessarily mean that all inefficient operators could adopt the best practices irrespective of the local context in which they develop their productive activity, or without undermining variables such as quality or sustainability. In this sense, research in this field has highlighted how the characteristics of operating environments can affect the technical efficiency of water utilities (Picazo-Tadeo et al. 2009a, 2009b; Ménard and Saussier 2000; González-Gómez et al. 2013); likewise, service quality also matters in measuring the performance of water utilities (Picazo-Tadeo et al. 2008).

  13. This means, by way of example, that the efficient level of labour input usage needed to produce a given output vector relative to the joint technology is 83.3 % of the efficient usage relative to the technology of the group of privately managed units.

  14. Table 4 and Figure 2 also include results and Kernel density functions obtained in the scenarios of input-specific performance assessment, which are discussed later; Kernels have been drawn directly using the metatechnology ratios obtained from expressions (8) and (10).

  15. Picazo-Tadeo et al. (2009b) also used a methodological approach based on the computation of input-specific scores of technical efficiency to provide evidence of the superiority of private utilities regarding the management of labour. However, here we go one step further by decomposing technical efficiency into managerial efficiency and ownership efficiency.

  16. There is no consensus about the effect of privatisation on the quality of the urban water service, either. In this respect, Galiani et al. (2005) found that the privatisation of local water companies in Argentina lead to a significant reduction in child mortality from causes directly related to water conditions such as infectious and parasitic diseases; also Marin (2009) suggested that privatisation in developing countries leads to improved service quality, especially by reducing water rationing. Conversely, Barrera-Osorio et al. (2009) showed that privatization in Colombia has strong negative effects on the access to water in rural areas. Furthermore, some papers suggest that privatisation has been followed by deterioration in service quality in the United Kingdom in such aspects as supply continuity and leakage control (Lobina and Hall 2000; Lobina and Hall 2001).

  17. These hypotheses would need, however, to be empirically tested. Using an indirect approach, we have found that private management is positively correlated with certain variables representing the complexity of operating environments, e.g., a dummy variable that characterises municipalities where intensive treatment is required to make raw water suitable for drinking, and an index of delivery network density computed as kilometres of network per 1000 inhabitants.

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Acknowledgments

The authors gratefully acknowledge the valuable comments and suggestions from two anonymous referees, as well as the comments from the participants in the international seminar ‘European Water Utility Management: Promoting Innovation within the Water Industry and Spreading Knowledge on Relevant and Cutting Edge Water Utility Issues’ (Pisa, June 2015), where an earlier version of the manuscript was presented. The financial support of the Spanish Ministry of Economy and Competitiveness (project ECO2012-32189) and the Regional Government of Andalusia (projects P11-SEJ-7039 and P11-SEJ-7294) is also gratefully acknowledged. The usual disclaimer applies.

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Suárez-Varela, M., de los Ángeles García-Valiñas, M., González-Gómez, F. et al. Ownership and Performance in Water Services Revisited: Does Private Management Really Outperform Public?. Water Resour Manage 31, 2355–2373 (2017). https://doi.org/10.1007/s11269-016-1495-3

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