An analytical review of the efficiency of water and sanitation utilities in developing countries

Water Research 161 (2019) 372e380

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Water Research journal homepage: www.elsevier.com/locate/watres

Review

An analytical review of the efficiency of water and sanitation utilities in developing countries Tiago Balieiro Cetrulo a, b, *, Rui Cunha Marques b, Tadeu Fabrício Malheiros a a b

~ocarlense Ave., 13566-590, Sao Carlos, SP, Brazil Research and Extension Center in Sustainability, University of Sao Paulo, 400 Trabalhador Sa Instituto Superior T ecnico, University of Lisbon, Rovisco Pais Ave., 1049-001, Lisbon, Portugal

a r t i c l e i n f o

a b s t r a c t

Article history: Received 21 March 2019 Received in revised form 14 May 2019 Accepted 15 May 2019 Available online 16 May 2019

Due to the importance of analyzing the efficiency of water utilities and the large number of publications in this area, at least five reviews have already been carried out to identify patterns and trends. These reviews aimed to cover worldwide studies, and the results may not correspond to the reality in developing countries. Therefore, this review provides a literature update on the quantitative studies of water and sanitation services, focusing on studies carried out in developing countries. This overview mainly examines the economies of scale and scope, public versus private ownership, and the impact of regulation. As expected, our results show patterns that differ from those found in worldwide reviews (e.g., the influence of regulatory incentives on operator efficiency and economies of scope). In addition, this paper presents patterns regarding the quantitative methods adopted, as well as some trends and areas for possible future research. © 2019 Published by Elsevier Ltd.

Keywords: Water and sanitation utilities Efficiency Benchmarking Quantitative techniques

Contents 1. 2. 3. 4. 5.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 372 Research characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373 Quantitative techniques used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 Issues addressed by the studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378 Declaration of interests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379

1. Introduction The performance of the operators of water supply and sanitation services (WSS) has been the focus of much research given the international interest in the economy of public resources and the development of competition simulations (yardstick competition)

* Corresponding author. Research and Extension Center in Sustainability, Uni~ocarlense Ave., 13566-590, Sao Carlos, SP, versity of Sao Paulo, 400 Trabalhador Sa Brazil. E-mail addresses: [email protected], [email protected] (T.B. Cetrulo). https://doi.org/10.1016/j.watres.2019.05.044 0043-1354/© 2019 Published by Elsevier Ltd.

due to the monopolistic nature of the sector. Indeed, over time, an increasing number of studies have acknowledged the importance of performance and its economic impact on WSS. Aspects related to performance evaluation (efficiency/productivity) and its determinants, benchmarking, incentives and market structure have gained relevance in the research in this sector. Following the growing scientific literature on the performance of WSS operators, at least five bibliographic reviews have discussed how the international scientific community is making progress from theoretical and practical points of view. Berg and Marques (2011) conducted a comprehensive review until the end of 2008 based on 190 studies. These authors found strong evidence of a positive influence of regulatory incentives on the efficiency of

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operators, but mixed results have been found in the analysis of privatization and economies of scale, scope and density. Abbott and Cohen (2009) also presented a comprehensive review based on more than 75 studies through early 2009. They concluded that there are economies of scale and of scope in the sector (water and sanitation), especially for small utilities. However, the results for privatization were ambiguous. Walter et al. (2009) focused their review on water distribution in the period between 1998 and 2008. They concluded that the influence of privatization on operator performance was not clear but that institutional designs tend to be a dominant factor in efficiency. They also found an omnipresence of economy of density and evidence of economies of scope. A review on market structure analysis was conducted by Carvalho et al. (2012), in which a meta-regression applied to more than 60 articles indicated a higher probability of finding diseconomies of scale and scope in large operators and in those under public management. Worthington (2014), focusing on frontier analysis, reviewed 27 studies between 1990 and 2014 and found patterns on the impact of privatization and regulation on efficiency. They analyzed patterns of economies of scale, scope and density. Despite the five reviews, two comprehensive and three more focused, in studies that included all countries, the trends and patterns found do not seem to represent the reality in the developing countries.1 First, this is because the number of studies conducted in developed countries is much higher, influencing the patterns found. Second, the developing countries present specific features, such as the need for universality of service, along with issues of equity, continuity and water quality. In addition, the high levels of water losses found can skew the analysis of performance and the low availability of data, which may limit the evaluation methodologies. Therefore, in this article, we provide a review of the literature for developing countries on the efficiency of WSS and the application of econometric and linear programming models. In addition, we have compiled the most important conclusions in relation to the market structure, operating environment, privatization and incentives. These results can be particularly useful for decisionmakers, public services managers and other stakeholders. After this brief introduction, the article is organized as follows. Section 2 presents the characteristics of the research, focusing on the publishing area, countries, data availability and the authors of these studies. Section 3 explores the quantitative techniques used in performance evaluations, with details about the most often used basic, qualitative and explanatory variables. Section 4 presents the main conclusions about the market structure, property, operational environment, incentives and benchmarking. Section 5 lists important implications learned from the review and suggests an outlook of research needs. 2. Research characteristics Overview. A comprehensive review (through May 2019) of the literature was conducted, including studies that use quantitative methods to evaluate the performance of WSS operators in developing countries. The review was based on research published in international journals, since this is a more accessible type of publication and is submitted to impartial review. We searched for literature in the Scopus, Science Direct and Google Scholar Databases using the following Boolean search string: (“DEA” OR “data envelopment analysis” OR “SFA” OR “stochastic frontiers analysis” OR “SBM” OR “slack-based measure” OR “TFP” “total factor productivity” OR “DDF” OR “directional distance function” OR “Luenberger” OR “Malmquist” OR “OLS” OR “ordinary Least squares” OR

1

We used the classification of the International Monetary Fund.

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“FDH” OR “full disposal hull” OR “order-m” OR “order-a”) AND (“water utilities” OR “water industry” OR “water sector” OR “water supply” OR “WSS”). We also included relevant papers encountered when screening or reviewing other studies. The studies were selected following the rules: Inclusion of studies carried out in developing countries; Inclusion of research published in international journals; Exclusion of studies which do not include quantitative results; Exclusion of studies in other languages than English; Exclusion of duplicates. Forty-six articles were selected among the identified pieces of literature, most of which were published in the last 20 years. Therefore, this type of study in developing countries is quite recent, and its increase is mainly due to the availability of data and interest in the recent privatization and regulation processes in the sector. Some interesting patterns were found when analyzing the authorship, publishing area, countries studied and data sources. Chronological analysis. The first study found for a developing country was Akosa et al. (1995), who used the Data Envelopment Analysis (DEA) to rank 10 sanitation projects in Ghana. This was the only article found up to the year 2000. There was a lag in publications when compared to those in developed countries. In their review, Berg and Marques (2011) found 69 publications through 2000, with the first being the article of Ford and Watford in 1969. The delay in publications occurred because of a shortage of sufficient data to carry out performance analyses (Walter et al., 2009). Only 7 years after the first publication, two other articles were published on this topic, but the most typical objectives were the performance evaluation of operators: one focused on analyzing the efficiency of regulation in Mexico (Anwandter and Ozuna, 2002), and another focused on checking the influence of privatization on the performance of Asian and Oceania operators (Estache and Rossi, 2002). In the 2000s, a total of 19 articles were published. The main focus was comparing the efficiency of public and private companies accompanying the privatization process that took place in developing countries. Some examples are the process that took place in Argentina, in which, at the end of the 1990s, 70% of the urban population was served by private providers (Estache and Trujillo, 2003); the phenomenon that began in Chile in 1998 and culminated in 2014 with 95.7% of consumers being served by private providers (Molinos-Senante et al., 2016); and the process that increased in Africa from the mid-1990s until the end of the decade, driven by international funding agencies such as the World Bank (Kirkpatrick et al., 2006). Accordingly, studies were conducted in Brazil, Argentina and Malaysia (e.g., Estache and Trujillo, 2003; Sabbioni, 2008; Munisamy, 2009) and others in multiple countries (Kirkpatrick et al., 2006; Estache and Rossi, 2002). At that time, it was also possible to observe the appearance of benchmarking studies that were mostly linked to the implementation of regulation processes (e.g., Corton, 2003; Berg and Lin, 2008). The only article dedicated solely to checking economies of scale, scope and density was conducted then (Nauges and Van den Berg, 2008). From 2010 to the present, 26 additional articles were published. The themes of privatization and regulation are still prevalent due to the processes that occurred in those countries, although studies with other scopes also appear. Some of them examine exogenous variables that influence the efficiency of the operators (e.g., Ferro et al., 2011; See, 2015), and others include the variables of quality and efficiency in their analyses by comparing their results with traditional modeling (e.g., Lin and Berg, 2008; Mbuvi et al., 2012). Fig. 1 summarizes the number of publications per year. Area of publication. The items found were categorized into 4 areas: a) business and administration; b) economics, econometrics

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T.B. Cetrulo et al. / Water Research 161 (2019) 372e380 Table 1 Number of studies in each journal.

Fig. 1. Number of quantitative studies published per year.

Fig. 2. Categorization of publications.

and finance; c) engineering; and d) environmental sciences.2 Fig. 2 shows the distribution of 46 articles found in these four categories. The publications are concentrated in the area of business and administration because many journals include that kind of study. However, a tendency toward change has been observed: for the past 10 years, publications in the areas of administration and economy have jointly fallen 50%, while publications in the environmental sciences have tripled. This can be mainly attributed to the tendency of studies to focus on equity and accessibility issues rather than on economic performance. Table 1 shows the number of publications by journal. Forty-six papers were published in 24 different journals. The journal Utilities Policy published 39.1% of all studies. Only five other journals had more than one publication: Water Policy, with three publications, and Environmental Science & Policy, the Journal of Infrastructure Systems, the Journal of Cleaner Production, and the World Bank Economic Review, each with two publications. Of the 24 scientific periodicals, 89.5% are indexed in the Scopus database, and 87% are in the Thompson database. Authors. Performance studies of WSS operators require knowledge of the quantitative tools used, of the institutional and managerial issues of the operators, of the real significance and limitations of the available data and of the possible interpretations made from the results. Therefore, it was expected that several authors participated in the studies. However, 71% of the publications had a maximum of two authors, as shown in Fig. 3.

2 The area of science and water technology according to the Scimago categorization.

Journal

Number of studies

Utilities Policy Water Policy Environmental Science & Policy J. of Infrastructure Systems J. of Cleaner Production The World Bank Economic Review African Journal of Business Management Applied Economics China Economic Review Environment and Development Economics Environmental Science and Pollution Research ^micos Estudos Econo Int. J. of Environmental Sciences Int. J. of Water Resources Development Int. Review of Business Research Papers J. of Environmental Management J. of Regulatory Economics J. of the American Water Resources Association J. of the Asia Pacific Economy Jurnal Teknologi Procedia Review of Industrial Organization Water Resources and Economics Water Science & Technology: Water Supply Total

18 3 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 46

A total of 46 articles were produced by 77 authors, 77.9% of whom participated in only one article. These figures show that the authors study the performance of operators in developing countries but do not go beyond that. This can be mainly attributed to the non-availability of reliable data to perform such analysis. Only 9.1% of the authors had three or more publications: Molinos-Senante, with five publications, Sala-Garrido, with four publications, and Berg, Ferro, Lin, Moreira, and Mugisha, each with three publications. This finding could also be attributed to the fact that most of the studies were conducted by researchers who were not from the countries they studied. Of the 46 articles, 54.4% had at least one author from a developed country, while nearly 29% were exclusively authors from developed countries. Of the 77 authors, 41.6% were from academic institutions in developed countries, 44.2% were from academic institutions in developing countries, 11.7% were from governmental institutions, and only 2.6% were from institutions linked to local water services. Countries studied. A total of 74 developing countries were covered by the WSS performance studies. However, Fig. 4 shows that nine articles analyzed more than one country (cross-country).

Fig. 3. Publications per level of authorship.

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Fig. 4. Publications per country.

It is important to note that the main purpose of these articles was not to compare efficiency between countries, but it was a way to address the lack of data (DMU) that prevented the models from being run in only one country.3 Of the countries studied, 79.7% were exclusively covered in the nine cross-country studies. The studies that covered only one specific country (37 articles) were for 15 countries. The cross-country studies exclusively covered 100% of the countries from Oceania, 88.9% from Africa, 75% from Asia and 64.7% from America. This shows the absence of data for individual analyses in the countries of these continents. The countries that had more studies were Brazil (9 individual and 2 cross-country), Chile (6 individual and 1 cross-country), India and Peru (4 individual and 1 cross-country), Malaysia (3 individual and 2 crosscountry), Uganda (2 individual and 2 cross-country), Ghana (1 individual and 3 cross-country), and Zambia (4 cross-country). Apart from Zambia, where all the analyses were carried out in conjunction with other countries, all other countries presented systematic data provision, as shown in the next section. Of all the articles, 53.2% were conducted on the American continent, 29.8% in Asia, 14.9% in Africa and 2.1% in Oceania. Two of the articles were based on intercontinental data. Nauges and Van den Berg (2008) compared the structure of the market (scale, scope and density) in Brazil, Moldova, Romania and Vietnam, and Estache and Rossi (2002) analyzed the efficiency of public and private companies in 31 countries in Asia and Oceania. Data source. Most developing countries do not provide periodic operational, economic or financial and quality of service information about WSS. This is the main reason for the small number of quantitative studies in these countries. However, the 15 countries that were covered by individual studies showed sufficient data for these studies. This was the case in the 11 studies conducted in Brazil that collected data from the National Sanitation Information System (SNIS). The SNIS was created in 1996 as an integral part of the National Sanitation Policy. As this was a periodic database and was relatively old, it allowed the authors to carry out various quantitative performance analysis techniques, including hypothesis testing that involved the evolution of efficiency in time. Of the eleven articles, ten used panel data, such as Carvalho and Sampaio (2015), who analyzed the efficiency of regulation, and Carvalho et al. (2015), who checked for efficiency

3 These cross-comparison countries generate problems between operators in different operational environments (Walter et al., 2009) but are used to avoid the problems of degrees of freedom. For example, the DEA method requires that the number of DMUs is greater than or equal to a maxfn: de inputs*n: de outputs; 3ðn: de inputs þn: de outputsÞg (Banker et al., 1989).

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differences in clusters. Other countries presented similar databases, and for this reason, there are individual studies for them. This was the case for information systems that we could find in a) Argentina, managed by the National Agency for Water and Sanitation Works (ENOHSA) (Estache and Trujillo, 2003); b) Iran, administered by the National Company of Water and Wastewater Engineering (NWWEC) (Nourali et al., 2014); c) Mexico, managed by the National Water Commission (ANC) (Anwandter and Ozuna, 2002); d) Palestine, whose data were provided by the Palestinian Authority of WaterPWA (Alsharif et al., 2008); e) Malaysia, which has provided data relative to sanitation since 1994 through the Malaysian Water Association (MWA) (Kamarudin et al., 2016); f) India, which does not have a specific water and sanitation utilities performance information system but has a Ministry of Urban Development (MoUD) that publishes performance reports of its operators (Vishwakarma and Kulshrestha, 2010); and g) China, which also does not have a specific information system but the National Bureau of Statistics (NBS) of China provides an annual survey from industrial firms (Li, 2018). Another form of data availability was the data published by regulatory authorities. This is the case of Peru, whose data have been available since 1999 through the National Superintendence of Sanitation Services (SUNASS) (Corton, 2003; Berg and Lin, 2008), and of Chile, whose data are available through the Superintendence of Sanitary Services (SISS) (Molinos-Senante et al., 2016; Ferro and Mercadier, 2016). We found another method that consisted of obtaining data from a single operator that operates in several cities. In this way, articles have compared the efficiency between units of an operator but not between operators. This was found for studies in Uganda, in which the data were extracted from the Regulation Audit Reports of the National Water and Sewerage Corporation (NWSC), which operates in the 22 major cities of Uganda, including Kampala (Mugisha, 2007, 2008 and 2014). Mellah and Amor (2016) used the data from a report from the Tunisia Water Utility (TWU), which is a state-owned monopoly holder of water services in the country. This was also the strategy used for the study in Sri Lanka, in which Dharmaratna and Parasnis (2012) collected the data from a public utility with monopoly over water supply (National Water Supply and Drainage Board - NWSDB). In addition, we found a study in Venezuela, in which the data were provided by the utilities ~ ía Ano nima Hidrolo gicas de Venezuela with the help of the Compan (Hidroven) (Higuerey et al., 2017). For studies involving more than one country, data sources can come from international partnerships. This was the case in Africa, in which the partnership between Water Operators (WUP) provided a report on performance indicators through SPBNET (Mbuvi et al., 2012; Kirkpatrick et al., 2006). The same occurred in Southeast Asia, in which the data could be collected from reports provided by the Water Services Network of Southeast Asia (SEAWUN) (See, 2015), and in South America, where information could be consulted from the Latin Association of Water Regulators (ADERASA) (Ferro et al., 2011; Corton and Berg, 2009). Another data source in the studies between countries was the surveys conducted by development agencies. In Asia, the Asian Development Bank (ADB) conducted research with 50 water services companies (Estache and Rossi, 2002). In Africa, the World Bank, in partnership with the African Development Bank (ADB) and other institutions, provided a diagnosis of the existing infrastructure in sub-Saharan Africa, in which information about water operators was included (Buafua, 2015). Although the IBNET (International Benchmarking Network for Water and Sanitation Utilities) is the world largest database for water and sanitation utilities performance information, only two studies used this database: Nauges and Van den Berg (2008) and Corton and Berg

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(2009). Note that Corton and Berg verified the IBNET data contacting the utilities and they also used other data source (ADERASA database). Evaluating the performance of the sector and identifying the strengths and weaknesses of current regulatory and managerial arrangements without financial and operational statistics is an arduous, if not impossible, task. This kind of observation implies the need for a permanent regulatory effort related to the collection and verification of data and the investment of operators in robust information systems (Berg and Phillips, 2017). Note that developing countries lack such systems of information, but their implementation is critical for monitoring performance and reaching related goals.

Table 2 List of selected variables used in developing countries. Inputs

Outputs

Labor (number or expenditure) (34) Water/sewer network extension (20) Operational costs (19) Electricity (8) Other operational costs (8) Total costs (5) Water losses (4) Number of connections (4) Water production capacity (3) Capital costs (3) Costs with contracted services (2) Others (10)

Water provided (16) Number of customers (15) Total revenue (15) Water production (11) Service coverage (9) Number of connections (8) Volume of treated wastewater (5) Indicators of service quality (4) Volume of collected wastewater (3) Continuity of supply (2) Others (6)

3. Quantitative techniques used

Note: The figure in brackets indicates frequency. Others: variables that appear in only one work.

The quantitative studies in the sector are usually categorized as parametric and nonparametric. The main difference between them is that the parametric studies need to define a priori a function for production technology, whereas the nonparametric studies do not have this requirement. In studies on the efficiency of water operators in developing countries, there is a dominance of nonparametric methods (54.4%) over parametric methods (39.1%). Only 6.5% of studies used both methods. Almost all of the parametric studies used stochastic frontiers (SFA) in their analysis. Only the article by Sabbioni (2008) used a variation of the least squares regression, the least square dummy variables (LSDV). Stochastic frontiers can be divided on the basis of cost, production function and distance function. Of the sixteen SFA studies, ten used cost functions, and the most commonly used distributions were Cobb-Douglas (44.4%), Translog (33.3%), halfnormal (11.1%), exponential (11.1%), and natural logarithmic (11.1%). The studies that used production functions (31.3%) primarily adopted the translog distribution, one article used it along with the Cobb-Douglas distribution, and another only used the Cobb-Douglas distribution. All the studies adopting the distance function (44%) were based on inputs and used the translog distribution, except for two (that used log-linear and Cobb-Douglas distribution). Data envelopment analysis (DEA) was the most commonly used nonparametric methodology (68%). There are two approaches to DEA, one that compares only operators at the same level of scale (variable returns to scale-VRS) and another that assumes that all operators operate at an optimum level (constant returns to scale e CRS). Only three studies exclusively used the CRS approach, nine used the VRS approach, and eight used both of them (usually to deduce the scale efficiency). DEA can also be categorized into two more approaches. The first (input-oriented) aims to optimize efficiency by securing the outputs and inputs, contracting the inputs. In the second (output-oriented) approach, the optimization is performed by setting the vector of inputs and expanding the outputs. A portion of the articles that used DEA (23.8%) also used the Malmquist productivity index, which captures changes in productivity between two periods. The study of Lin and Berg (2008), in addition to the traditional DEA, used a nonradial approach in which a nonproportional reduction of inputs or a nonproportional increase of outputs is possible. Only seven works exclusively used other nonparametric methods: Estache and Trujillo (2003) and Li (2018) used the total production factor (TFP); Molinos-Senante and Sala-Garrido (2015), See and Ma (2018), and Sala-Garrido et al. (2019) used a generalization of the Malmquist productivity index (Luenberger productivity indicator) to compute changes in productivity; Kamarudin et al. (2016) and Sala-Garrido et al. (2019) applied a directional distance function (DDF) for simultaneously contracting inputs and expanding outputs and thus considering

undesirable outputs; and Barbosa et al. (2016) used a model based on dynamic slacks (DSBM) able to estimate production through time. No studies were carried out using partial frontiers (order-m and order-a) or conditional frontiers. In the nonparametric methods, because they are deterministic, it is not possible to distinguish the random variations of inefficiency in relation to the frontier. In this way, exogenous factors are accounted for as inefficiencies. To overcome this limitation, some studies used a second stage after obtaining efficiency scores, mainly to return the DEA efficiency measures against a number of explanatory variables. Tobit regression was used in four studies, as was the bootstrap technique (or double bootstrap). Nonparametric statistical tests were used in two studies, and generalized estimating equations (GEE) and LSDV were used in only one study. No studies were found to use least squares regression (OLS) or maximum likelihood estimation (MLE). Variables used. The choice of inputs and outputs to be used in quantitative methods for analyzing the efficiency of operators is very relevant. However, it is also rather complicated due to the complexity of the water industry and, in developing countries, the availability of data. Table 2 shows the frequency of inputs and outputs used. The input labor is usually measured in terms of wages, total expenditure with employees or number of employees. The extension of the water network is used as a proxy for capital expenditure of the operators, which is very difficult to achieve in developing countries. Total revenue is usually measured as the total water volume accounted for. Lin (2005) and Singh et al. (2010) argue that operators with good cost efficiency do not necessarily feature good quality of services. Therefore, it is desirable to incorporate quality variables into performance analysis (Picazo-Tadeo et al., 2008; Romano et al., 2017). Molinos-Senante et al. (2015) state that the inclusion of these variables can encourage operators to improve customer services and aid regulators in developing incentives. However, Lin and Berg (2008) argue that most studies conducted in developing countries do not consider qualitative variables due to methodological limitations and data availability. In fact, in our review, only 37% of the studies included quality variables in their analyses, with the most frequent variables being water losses, chlorination, continuity of supply and service coverage. Most authors (50%) modeled these variables as outputs, the other works modeled them as inputs (25%) or undesirable outputs (25%). Regarding the qualitative variable water losses, the main strategy adopted was to use it as an input. However, two other strategies were found in our review, which were to model it as undesirable output or to consider the total amount of water produced as an input and the amount of water delivered as an output.

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Explanatory variables refer to contextual issues affecting efficiency but are outside the scope of action of the operators, and ignoring them in the analyses could lead to biased results. Berg and Marques (2011) found more than 20 explanatory variables in their study while in this study more than 25 were found. The most frequent were the scope of operation (local or regional), independent adjustment, private participation, type of economic regulatory mechanisms (price-cap, revenue-cap and rate of return), density of connections, water losses and water sources. Others were examined in only a few studies.4

4. Issues addressed by the studies Categorization. According to the main issues addressed by the studies, the results were categorized into (1) market structure (economies of scale, scope and density); (2) private participation; (3) regulatory incentives; (4) benchmarking; and (5) exogenous factors that influence performance. Market structure. We found 25 works that studied the economies of scale, scope and density. However, only Nauges and Van den Berg (2008) focused on the market structure. In developed countries, it is more common to find diseconomies of scale in large operators and in operators under public management (Carvalho et al., 2012). However, only economies of scale were identified in developing countries. In Brazil, Barbosa et al. (2016), Carvalho et al. (2015), Sabbioni (2008) and Seroa da Motta and Moreira (2006) identified economies of scale, and Nauges and Van den Berg (2008) identified positive but not significant effects. Carvalho et al. (2015) analyzed approximately 4900 DMUs between 2001 and 2011 and estimated the optimal volume of the water supply to be 600,000 m3/year. Economies of scale have also been found in India (Gupta et al., 2012; Kumar and Managi, 2010; Singh et al., 2010), Mexico (Anwandter and Ozuna, 2002), Malaysia (Munisamy, 2009), Vietnam (Nauges and Van den Berg, 2008), Tunisia (Mellah and Amor, 2016), Iran (Nourali et al., 2014), Sri Lanka (Dharmaratna and Parasnis, 2012), and six Central American countries (Corton and Berg, 2009). In Chile, the results were not significant (Molinos-Senante et al., 2015) although positive and negative economies of scale were found for full private and concessionary water utilities, respectively (Molinos-Senante et al., 2018). Although in the water supply and wastewater sectors, economies of density can be measured in terms of customers, networks and production (Walter et al., 2009), in developing countries, they were analyzed only with regard to network concentration. Fifteen studies performed this analysis, and in eight, it was concluded that network density increased the efficiency of operators since it reduced costs (e.g., Souza et al., 2008). The other seven works found similar results, but they were not statistically significant (e.g., Tupper and Resende, 2004). Concerning the economies of scope, different approaches may also exist, for example, integrating the water sector with the provision of electricity and gas. Few studies have examined economies of scope (10%) in developing countries, and all of them addressed the vertical integration between water services and sanitation. In Brazil, Carvalho et al. (2015) and Barbosa et al. (2016) found economies of scope, Nauges and Van den Berg (2008) did not find significant results, and Ferro et al. (2014) found diseconomies of

4 Other explanatory variables include the ratio of metered connections, continuity of supply, water storage capacity by the operator, temperature of the region, financial incentives, tariff value, peak factor, complaints, operator size, ratio of water volume intended for tourism, treated wastewater volume, scope of the operator (water or wastewater), regions, number of residential connections and gross domestic product per capita.

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scope. In Vietnam, a study identified economies of scope (Nauges and Van den Berg, 2008). Private participation. The most frequently adopted objective was to identify the impact of public and private management on operator efficiency. Although there are theories that suggest increased efficiency by private operators, research shows mixed results in various sectors (Berg and Marques, 2011). Eighteen studies focused on this theme: eight of them concluded that private operators were more efficient than public operators, eight did not find significant differences, and only two identified public operators as being more efficient. Even within the same country, the results were diverse; in Brazil, three studies concluded that private operators were more efficient, three found no evidence, and one concluded that public operators were more efficient. Although these differences can be explained by differences in the method or database used, there was also evidence that the private sector ensured greater flexibility and productivity of labor (Sharma et al., 2007; Souza et al., 2007). However, capital expenditure was higher in the private sector than in public operators. Only four works that focused on comparing the efficiency between public and private operators used quality variables. In all, the private operators were more efficient than the public ones. Although the studies are few, there is evidence that private operators were more efficient when factors such as water losses (Buafua, 2015), water treatment (Carvalho et al., 2015), sanitation (Ferro et al., 2014) and quality of service (Munisamy, 2009) were included in the analysis models. Benchmarking. The second most representative objective of the studies considered in this review was to use quantitative techniques to measure the operators’ performance in the sample considered and identify best practices. This review found 16 studies that had benchmarking as one of their main objectives. Most of them compared operators within a country, but there were also studies that compared regions or countries (Alsharif et al., 2008; Corton and Berg, 2009). Some studies focused on the impact of quality of service variables on performance evaluation (Kumar and Managi, 2010; Lin, 2005; Lin and Berg, 2008; Mbuvi et al., 2012). The study of Singh et al. (2010) focused on incorporating sustainability parameters in benchmarking structures. According to Berg and Marques (2011), the relevance of the rankings generated in these studies should be investigated in future research. This topic is even more relevant in developing countries, since issues such as loss of water and universalization of service are not included in models focused on minimizing costs (Corrected Ordinary Least Squares, classic SFA or DEA with single outputs).5 Therefore, if the objective is to use these rankings to devise incentives for the operators, the use of traditional models may not enable the attainment of objectives such as universalization, equity, loss control and service quality. However, this review showed that these issues were seldom included in benchmarking studies; only seven studied water losses, six studied service coverage, and four studied the number of hours of water supply. These issues should be considered in models to prevent the use of benchmarking ranks based only on volumes and financial costs. For example, in countries such as Brazil, it could be cheaper to produce more water than to control losses (Sabbioni, 2008). Exogenous factors. Thirteen of the 46 articles studied the factors that influence the efficiency of operators as a main objective. The main results of these studies are briefly described below. In Brazil,

5 Berg and Lin (2008) ranked the operators from Peru using DEA and SFA to compare them with rankings generated by local regulatory SUNASS. They concluded that if it is necessary to include quality variables, the DEA or SFA methods based on the distance function are most suitable.

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Carvalho et al. (2015) found that local operators were more efficient than regional operators. However, the other three papers concluded the opposite (Seroa da Motta and Moreira, 2006; Sabbioni, 2008; Ferro et al., 2014). In addition, negative relationships were found between productivity and tariffs (Seroa da Motta and Moreira (2006) and between performance and GDP (Barbosa et al., 2016). Ferro et al. (2011), analyzing 16 Latin America and Central countries, found a negative relationship between the number of metered customers and operator performance. Gupta et al. (2012) concluded that in India, less populated cities showed relatively better performance. Mbuvi et al. (2012), studying 11 African countries, found a positive GDP influence on operator efficiency. In Uganda, the positive impacts of financial incentives (Mugisha, 2007, 2014), managerial improvements (Mugisha, 2008) and coverage improvements (Mugisha, 2014) were found. However, targets for water loss reduction had a negative influence on performance (Mugisha, 2014). In Chile, Molinos-Senante and SalaGarrido (2015) concluded that exogenous variables (the number of customers and size) did not affect the efficiency of operators, but Molinos-Senante et al. (2015) found a positive influence of peak water demand and a negative influence of water losses. Among 7 countries in Southeast Asia, See (2015) concluded that environmental variables (meteorological factors and GDP) do not affect the efficiency of the operators. Regulatory incentive. There was also a small group of six studies whose main objective was to analyze the impact of incentives on the water operators. In theory, one of the regulation objectives is to use benchmarking techniques to compare operators and to generate incentives for efficiency improvement. Benchmarking is used as a simulation of market forces to supplant potential abuses of the natural monopoly of the sector (Berg and Marques, 2011). Operators that are not subject to regulatory systems tend to negotiate their tariffs with the government. In those systems, there is no generation of incentives for performance improvement. Conversely, in regulatory regimes, the most common incentives were the price cap, the revenue cap and the rate of return. Only the work of Barbosa et al. (2016) studied the impact of different regulatory regimes on efficiency. In their study in Brazil, they found that operators under the price cap and revenue cap were associated with lower efficiency than those under the rate of return or those that were not regulated. The authors attributed this result to the possibility of negligent action and the political use of regulatory agencies. Ferro and Mercadier (2016), exploring a possible path to recognize the associated increased costs with water loss control, found that the regulators can induce providers to invest more through a K-factor. The other four studies compared the performance of operators under a regulatory regime. They adopted two approaches: a timeline, in which efficiencies were compared before and after the implementation of regulatory systems, and another in the form of clusters, in which a regulated cluster was compared with an unregulated cluster. Buafua (2015), analyzing the regulatory system in 16 sub-Saharan African countries, found that regulation via performance contracts led to greater efficiency than the controls carried out by independent regulators. Carvalho et al. (2015) and Carvalho and Sampaio (2015) showed that Brazilian operators were more efficient before the regulatory system had xico, Anwandter and Ozuna (2002) also been implemented. In Me found that regulation did not bring efficiency improvements for operators. Thus, surprisingly, no articles showed that performance improved because of regulatory incentives. Wren-Lewis (2014) argued that in Africa, this was due to institutional weaknesses and that the models imported from developed countries did not have any effect.

5. Conclusions Lessons learned. We provide a critical review across the literature for developing countries on the efficiency of WSS and the application of econometric and linear programming models. The important implications of our work are: ⁃ There was a tendency of private operators to exhibit better performance in developing countries, especially when qualitative variables were accounted for in the evaluations performed. ⁃ Regarding market structure, economies of scale have been found in Brazil, India, Mexico, Malaysia, Vietnam, Tunisia, Iran and six Central American countries. In other countries, this question was not analyzed, or the results were not statistically significant. All the works that examined economies of density found positive results, but only slightly more than 50% were significant. Concerning economies of scope, WSS studies were conducted only in Brazil, with diverging results, and in Vietnam, where economies of scope were found. ⁃ The regulatory incentives have not promoted performance improvement of water utilities in developing countries. ⁃ Some of the results of our review show patterns that differ from those found in the literature, covering developed and developing countries simultaneously (e.g., a positive influence of regulatory incentives in the efficiency of operators and the existence of economies of scope). Future research directions. Based on the outcomes of this review, the following research directions have been identified to help the research community and the professionals working on the performance evaluation of water utilities: ⁃ More than 70% of the nonparametric studies used the inputoriented approach, keeping in mind the studies conducted in developed countries, in which operators provide drinking water to (and collect wastewater from) all domestic customers and cannot encourage consumption. However, for developing countries, the need for universalization is a reality; Future studies should consider using a service maximization approach (in terms of number of connections or clients, service coverage or other). ⁃ The use of distance functions on SFA is a way to go beyond the inconvenience of SFA by not admitting multiple inputs and outputs simultaneously. ⁃ It is desirable to incorporate quality variables into performance analysis carried out on developing countries. Regarding the qualitative variable water losses, there are advantages in modeling water losses as an undesirable output, and this should be a strategy in future research. ⁃ Traditional benchmarking studies may not enable the attainment of objectives such as universalization, equity, loss control and service quality. Therefore, future research should focus on studying models that capture these issues. ⁃ Although the implementation information systems is critical for monitoring performance and reaching related goals, the use of panel data and more robust methods (e.g., partial frontiers methods) are interesting strategies to deal with data unavailability and data quality issues (e.g., ‘curse of dimensionality’, extreme data, and outliers). ⁃ There is a disbelief that such quantitative studies can lead to improvements in the performance of water companies in developing countries because the institutional weaknesses (e.g., limited regulatory capacity and limited fiscal efficiency) are the main issue of regulatory failure. Accordingly, addressing the related problems is more important than solving the concerns

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that are normally stressed in the regulation of utilities in developed countries (e.g., performance). Therefore, would be interesting that future publications in this field discuss this subject. ⁃ Some topics that should be addressed in future research are linked to the universalization and equity of access and water losses. Thus, future studies should incorporate qualitative variables that capture these issues, use appropriate models (e.g., DEA directed toward outputs) and compare the results with traditional approaches of cost minimization.

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