This study explores the relationship between economic regulation and user prices in the Portuguese water industry. The empirical analysis demonstrates that economic regulation based on the rate of return model is attached to higher user prices in a comparison with the other organizations that are directly dependent on political decisions. Moreover, comparisons between operators through benchmarking might have an impact on user prices. In addition, this study shows that a stronger prediction of user prices exists when considering the adopted management model for the delivery of water services. Main findings: the managerial element is not a primary goal, instead, the political option still prevails for user prices.

Introduction

To what extent does economic regulation shape user prices? The concept of regulation is understood as the establishment of specific rules for the functioning of certain sectors based on the public interest (Marques, 2005). Economic regulation becomes a central feature when dealing with services provision, especially in those sectors where direct competition does not exist. Major concerns are centered in user exploitation since there are no alternative ways to satisfy their needs. Thus regulation can play a major role in order to encourage those firms to accomplish higher results and as a consequence to lower user prices (Bös, 2001).

In the past decades, new public management (NPM) became the theoretical reference for public administration institutional and managerial reforms (Peters, 2000). Among others, NPM supported the split between politics and management since all public services should be run like businesses (Hood, 1991). Politicians must pursue the public interest by means of their authority to make decisions regarding what services should be provided to fulfill citizens’ needs. The NPM paradigm differs in several ways from the professional model that endured until the end of the 1970s. This is because in bureaucracies there is no split between politics and administration. Furthermore, bureaucrats play a central role both in making policy and in implementing it (Osborne, 2006). Given this dual role, the focus of the bureaucracy was on organizational inputs rather than outputs. Decisional processes were not flexible, and managerial accountability was not possible because of the connection between political decisions and managerial actions (Pollitt & Bouckaert, 2011).

Bearing this in mind, public sector institutional reform was carried out with the establishment of publicly owned enterprises (Tavares & Camões, 2007) that would increase organizational responsibilities while keeping politicians away from management. Managers must by those means improve services provision based on managerial decisions, namely through correct balancing of production costs and revenues. According to the authors, publicly owned enterprises are single-purpose bodies financially independent from public structures and must run their daily activities like businesses. In other words, that political influences in managerial decisions would no longer happen in publicly owned enterprises. In theory, and without political influence, these organizations should run their businesses from a technical and economic perspective becoming efficient, effective and providing higher quality service levels.

Besides the introduction of publicly owned enterprises, institutional reform undertaken beneath the NPM theoretical framework also highlighted the role of private skills and expertise for delivering those same services. Private sector participation in service delivery was promoted due to the belief that private firms present better results than the traditional public bureaucracy (Girard et al., 2009). In that sense, the main goal of private sector organizations is to be lucrative and that would be possible by making best use of scarce financial and economic resources. This will lead to improved operational results thus increasing private firm profits. At the same time, the split between politics and administration would also be achieved, however economic regulation must be assured to avoid exploitation of users where direct competition is not possible.

Economic regulation assumes a major role, especially regarding public utilities due to the specific environment where they operate. That is the reason why regulation becomes so important (Bös, 2001): economic policy plays a major role through the regulation design decisions. It is thus hypothesized that a relationship exists between organizational results and the regulatory framework (Darnall, 2009). The relationship is grounded on the belief that economic regulation must force public utilities to make a better use of scarce financial and economic resources, and without increasing user prices. Moreover, where direct competition is not possible, virtual competition through benchmarking will also make monitoring organizational results possible. Besides, the introduction of competition would allow lower user prices of services that have been provided (Drewry, 2005). Nevertheless, it is a fact that studies in this area seem to address their attention more often on the adverse-selection problem and the associated asymmetrical information when the decision has been achieved (Bös, 2001). That is to say, we need further explanation about the relationship between regulation and user price.

For that reason, this study aims to describe and understand if a relationship exists between regulation and user prices. Bearing in mind the research question and the research objective, the Portuguese water sector was chosen to conduct the survey making use of a panel research design (Blaikie, 2000). In the first place the option relies on data availability – from 2007 to 2012; where user prices can be compared between organizations regulated by the rate of return economic model (the one adopted in Portugal for concession and multi-concession contracts) and with the other organizations that are politically dependent from local governments to set user prices. In addition, the study introduces a control variable (the adopted management model) in order to understand if regulation is really the main predictor of user prices in the Portuguese water sector.

This manuscript is organized as follows: firstly, the literature concerning the description of the concept of economic regulation adopted in the water industry, namely the rate of return and benchmarking tools, is discussed; then, predictors and hypothesis for user prices settlement are presented and debated. After that, details of research design and variables are discussed. Lastly, the research results and conclusions are presented.

Economic regulation and user prices

Economic regulation is not a new issue, since competitiveness between firms is a major concern (Arrow & Kurz, 2011 (first published in 1970)). It is a fact that market prices can exclude some citizens from the consumption of primary goods and services. For that reason, public goods provision must be examined in the light of efficiency production. Higher levels of efficiency production will theoretically allow higher consumption levels for citizens. If citizens can more easily access those services, the fairness of their consumption will also increase.

The NPM paradigm highlights this subject, since services can be provided through private sector participation or public sector organizations. However, governmental authorities are still responsible for the correct functioning of these markets and therefore they must create the regulatory conditions to avoid exploitation of users from misuse of market power (Frontiers Economics, 2014). As mentioned by Frontiers Economics (2014), efficiency and optimal social outcomes must be regulated under essential goods and services and several models exist to achieve it especially the ones that are based on a direct price control: rate of return, external benchmarking, price caps and revenue caps.

Between these models, price cap has been favored for essential goods provision regulation, e.g. water services. According to Kirkpatrick & Parker (2004), from the 36 countries included in the analyses of the regulatory regime in Asian countries, 17 of those countries applied for the rate of return model. They also mention that in South America the trend is quite similar. For example: Argentina, Brazil, Columbia, Ecuador, Mexico, Peru and Venezuela applied for a price cap regulation model and only Bolivia and Chile applied for the rate of return regulation model in the water industry. Price cap has been used more often because productive incentives are stronger under this regulation model, in theory.

Water sector industry academicians have been focusing on the relationship between the adopted regulatory frameworks and the impact on productive and cost efficiency. For example, Aubert & Reynaud (2005) sought to understand the relationship between regulatory policies and cost efficiency in the water industry in Wisconsin, USA. Making use of panel data regarding the 1998 to 2000 period, they compare 211 operators’ efficiency results that are regulated under different economic models. They concluded higher efficiency levels were obtained for the rate of return regulated organizations in comparison with those organizations regulated under a price cap model. It is noteworthy that the organizations under price cap regulation were still quite efficient but not as efficient as those regulated under the rate of return model.

It is a fact that inefficiencies may arise under rate of return regulation, however they should not be overstated since there are still some merits in this model. Besides, rate of return has been applied in several countries, including Portugal, which we are now going to describe in detail.

The rate of return economic regulation model

Rate of return was introduced for economic regulation during the 19th century in the USA (Kirkpatrick & Parker, 2004; Aubert & Reynaud, 2005). The main reason to apply for this economic regulation model was due to a political attempt to avoid consumer exploitation by franchised monopolies. That is true since rate of return was designed to allow the recovery of the investment made initially by the operator. According to Armstrong & Sappington (2007), rate of return can be characterized as follows: regulated organizations do not have flexibility over relative prices since those prices are attached to an agreement between the firms and the town which is responsible for the negotiation of the contract. The regulatory lag is small (usually for 1 year) which allows possible adjustments between cost/investments versus profits on a comparative basis – it should be remembered that a contract with a span time of 25 to 30 years is usual in order to allow concessionaries to recover their initial investments. Furthermore, the price sensibilities are lofty, setting aside organizational corrections on operational costs deviance [‘regulation must not eliminate the public utility’ (Bös, 2001, p. 3)].

This means that even if investments are high in a first stage, concessionaries cannot overcome those investments with user price unsupportable increases. Marques (2005) argues that rate of return can increase productive efficiency and innovative operational designs since user prices are established in the long run – ex-ante. The only method those firms have to quickly recover their investment is to make better use of available resources. However, and still in accordance with Armstrong & Sappington (2007), cost reduction incentives are low, because concessionaries know that costs must be covered due to the initial financial investments because concessionaries know that costs must be covered due to the initial financial investments.

According to Marques (2005) under rate of return, social goals such as lowering user prices can be accomplished if the operators operate efficiently. Two main concerns arise regarding user prices: in the first place the use of rate of return is politically justifiable when the lack of investment is a reality, namely on infrastructure improvements (Armstrong & Sappington, 2007). In the Portuguese case, that is a fact and we witness a lack of financial capability of Portuguese local governments to undertake those investments. Concession contracts based on rate of return became common, since politicians wanted the job done while keeping the local government sheet balanced and without user price increases (Silvestre, 2012). This suggests the following hypothesis:

H1: Rate of return has a prevailing relationship with user prices.

Even if it is argued that rate of return might improve productive and cost efficiencies, we can also find several criticisms of the model. According to Kirkpatrick & Parker (2004), the most common criticisms in the Asian water industry are: informational asymmetries; serious levels of customer complaints about rising prices; enterprises overinvesting in capital equipment; and political pressures, among others. User prices will be higher in this sense because a recovery of initial investments must be assured and the utility will try to maximize its profits (Aubert & Reynaud, 2005).

Despite this, rate of return still presents its merits: it allows a better understanding of user prices due to a clearer process where costs are the basis for the negotiation between the parties; it can assure the necessary investment from other sources, who know that return on investment is much more stable under this model in comparison with other economic regulation models; and the risk of political and social rejection is lower since costs are the rationale for user price settlement (Kirkpatrick & Parker, 2004). We should remember Aubert & Reynaud's (2005) research conclusions, where inefficiency decreases under rate of return in comparison with other economic regulation models. However, to overcome the appointed criticisms of rate of return, several governments introduced benchmarking as a complementary tool to promote competition among operators (Marques, 2005).

Benchmarking as a complement in economic regulation

As mentioned earlier, NPM became the framework for the institutional and organizational reforms in services provision. The political option was intended to increase performance organizational levels, which would be possible with the introduction of competition between providers (Hood, 1991). Once adopted for organizational reforms, some governments adopted benchmarking as a complement for economic regulation in order to promote competition between operators. General beliefs indicate that competition will lead to higher efficiency levels and lower user prices since organizations will not want to be negatively publicly exposed (Marques, 2005). In public utilities cases, this competition will be virtual due to the impossibility of a market demand and supply negotiation between involved parties. That is the reason why it is called ‘virtual’ competition, nevertheless it remains a complementary tool in order to improve organizational results.

Benchmarking became, for those reasons, a device to be used by providers as well as for decision makers (Corton & Berg, 2007). Overall, benchmarking can embrace the comparison of operational, cost or quality performance indicators in the form of the composition and publication of league tables. As Corton & Berg (2007) found for the water and sanitation industries operating in Latin America and the Caribbean, benchmarking has been used to improve efficiency levels in both industries, and through continuous monitoring of the efficiency levels operators are able to learn which best practices should be adopted in order to raise organizational efficiency. Comparisons also allow policymakers to observe how the system is behaving. Considering everything, greater competition leads to higher efficiency levels and thus user prices can be lowered. This suggests the following hypothesis:

H2: Benchmarking has a prevailing relationship with user prices.

The debate about economic regulation has matured with NPM. As we mentioned, private sector participation was highlighted to improve services provision. However, the privatization of public utilities brought the monopoly prices issue to public debate (Kirkpatrick & Parker, 2004). The achieved results under private sector participation in essential services provision seem to have reached an end (Hill & Hupe, 2009) because the existing regulation arrangements might not be able to control user prices (Frontiers Economics, 2014). Because of this, municipal corporations have been developed to increase efficiency and to control user prices.

Municipal corporations as alternatives for services provision

Regarding the Portuguese experience, municipal corporations were created due to the political conviction that under a different public management model from the traditional bureaucracy it would be possible to improve financial performance (Tavares & Camões, 2007, 2010). According to the authors, quicker decisions will then lead to a better organizational management. Also, these arrangements are described as single-purpose bodies, which are financially, legally and in terms of assets independent from local structure. They are also dependent on user fees rather than budget transfers from local government, thus their managerial responsibility is much higher. This is to say that municipal corporations have to balance their revenues (which are based on user fees) with their organizational costs rather than being continuously subsidized by local governments. In sum, municipal corporations emerged as a way of enhancing financial and economic performance, the assumption being that public sector organizations can be as efficient and productive as private firms.

If public organizations under a private and commercial legal framework are economically and financially viable, they can focus also on user prices. With a greater emphasis on social goals, municipal corporations will be able to keep user prices low (Silvestre, 2012). This suggests the following hypothesis:

H3: Municipal corporations have a prevailing relationship with lower user prices.

Nevertheless, a major concern exists beyond this public management model application: the split between political and managerial decisions might be compromised. According to Niskanen (1971), politicians are driven by the wish of maximizing their political power in order to be re-elected. In such cases, a cut back management will not be possible because the political capture will not allow public sector organizations to settle user prices according to operational results. Politicians will also intervene in organizational decisions, which might lead to under-pricing and insufficient business planning (Kirkpatrick & Parker, 2004).

Research design and methods

User prices became an important topic for services delivery. This status is due to the existence of non-competitive markets and the associated monopoly prices (in the water sector, for example). Since direct competition is not possible, regulation becomes a major issue (Martins et al., 2013a, 2013b). However, there still exists a lack of studies testing the relationship between social goals (Dawson, 2006), such as user prices, and economic regulation. This study focuses exactly on those social goals, considering that society is in general concerned with the cost for consumption (Pollitt & Steer, 2012).

In order to overcome rate of return criticisms, national regulation policies in the delivery of water points to a benchmarking program between those firms with economic regulation under the rate of return model and the other organizations that are publicly owned (Marques, 2005). Concessionaries are directly responsible for providing reports to the regulator which must include several indicators such as efficiency, and quality of services, among others. For the publicly owned organizations in their place, only a few indicators are demanded from the operators. This means that artificial competition between Portuguese water sector operators is possible but only for a very few dimensions.

Data and variables

The study is based on a panel research design (Blaikie, 2000; Camões, 2012), which means that the data collection was carried out throughout several periods and for several units of analysis (the 2007, 2009, 2011 and 2012 years in this case). This research design is justifiable since it will allow us to understand the behavior of user prices within the considered period. Data for these years were obtained from the Portuguese Water and Waste Services Regulation Authority (ERSAR) (2010, 2013, 2014a, 2014b). This list contains information for the Portuguese mainland water companies (Portuguese islands of Azores and Madeira were excluded because for the last 2 years no data were available and a comparison throughout the period would not be possible).

It should be noted that between 2007 and 2012, some changes occurred regarding the used model for water services delivery, e.g. Azambuja, Campo Maior, Cartaxo, Elvas, Fundão and Vila do Conde changed from a public to a private concession contracts arrangement. There are also some municipalities where more than one organization provides water services, for example in the Loulé council, INFRALOBO, INFRAQUINTA and INFRAMOURA, all municipal corporations, are all operating. The above reasons explain the existence of a larger n than the actual municipalities.

The empirical analysis thus engages the use of 12 dependent variables. For user prices, ERSAR established the following figures for domestic use in each municipality: user prices (in €) for a 60 m3 consumption level (to compare consumer prices for low consumption levels and this variable will be codified as CP'60); user prices (in €) for a 120 m3 consumption level (to compare consumer prices for medium consumption levels and this variable will be codified as CP'120); and user prices (in €) for a 180 m3 consumption level (to compare the consumer prices for high consumption levels and this variable will be codified as CP'180). In this study, client prices in all consumption levels will be considered and codified for each year – Table 1.

Table 1.

Summary of descriptive statistics.

Variable Observations Minimum Maximum Mean Std. Dev. 
2007 CP'60 279 4.20 116.40 47.41 20.35 
2007 CP'120 279 8.40 186.60 85.17 31.52 
2007 CP'180 279 27.00 305.76 137.29 49.31 
2009 CP'60 279 5.28 126.24 48.31 23.16 
2009 CP'120 279 18.00 202.44 89.50 34.22 
2009 CP'180 279 33.60 307.80 146.10 52.50 
2011 CP'60 282 9.00 192.96 57.32 25.74 
2011 CP'120 282 18.00 244.56 102.35 36.29 
2011 CP'180 282 33.60 316.18 160.82 53.21 
2012 CP'60 281 9.00 192.96 61.13 26.54 
2012 CP'120 281 18.00 244.56 108.11 37.73 
2012 CP'180 281 33.60 324.00 166.62 54.35 
RM 311 1.87 0.34 
MgM 311 2.33 0.91 
Variable Observations Minimum Maximum Mean Std. Dev. 
2007 CP'60 279 4.20 116.40 47.41 20.35 
2007 CP'120 279 8.40 186.60 85.17 31.52 
2007 CP'180 279 27.00 305.76 137.29 49.31 
2009 CP'60 279 5.28 126.24 48.31 23.16 
2009 CP'120 279 18.00 202.44 89.50 34.22 
2009 CP'180 279 33.60 307.80 146.10 52.50 
2011 CP'60 282 9.00 192.96 57.32 25.74 
2011 CP'120 282 18.00 244.56 102.35 36.29 
2011 CP'180 282 33.60 316.18 160.82 53.21 
2012 CP'60 281 9.00 192.96 61.13 26.54 
2012 CP'120 281 18.00 244.56 108.11 37.73 
2012 CP'180 281 33.60 324.00 166.62 54.35 
RM 311 1.87 0.34 
MgM 311 2.33 0.91 

The study will make use of one independent variable as a predictor of user prices: the economic regulation model. The regulation model (this variable will be codified as RM) is a dichotomous variable where (1) is the rate of return (this variable will be codified as RoR) and (2) is for others (this variable will be codified as others). Rate of return was applied to concession contracts where private operators settle on an agreement with the town in order to deliver water for citizens. There are also other publicly owned firms regulated under this model: multi-concessions, for example. Contrary to this, the other organizations are regulated by the town.

The study also introduces a control variable: the adopted management model for each organization (this variable will be codified as MgM). The first model identified is bureaucracy itself (this variable will be codified as Bur). Here, water delivery is the responsibility of the local structure. The second model is the municipalized services (this variable will be codified as MSer). These entities rely on their administrative and financial autonomy in order to improve financial and managerial performance. However, they lack legal personality, which continues to be controlled by the local bureaucracy. In practical terms, they are still local bureaucracies, but with their own boards and structure. The third model identified is the municipal corporation (this variable will be codified as MCor). Here, administrative, financial and asset independence in relation to local political bodies do exist, yet executive boards are appointed by local government politicians. The main difference when compared with the municipalized services is that municipal corporations have their own legal personality and commercial law frames their actions. The fourth model corresponds to a private firm operating the facility through a municipal concession contract (this variable will be codified as Priv). Finally, we find the multi-concession model, where central government, and not local government, establishes a concession contract with a public enterprise (this variable will be codified as Multi).

Analytical tools

The analysis of variance (ANOVA) statistical tool has been applied which allows us to examine patterns matching logical association (Yin, 2009) in order to describe and establish the regularities between concepts (Blaikie, 2000). By applying ANOVA, the main differences between the dependent and independent variables in a single measurement can be tested (Grice & Iwasaki, 2007). If the main differences between variables can be tested, the results can distinguish the null hypothesis for the two independent variables: the regulation model and management model. This method was applied due to the existing frequencies between the chosen independent variables – for example, the minority of Portuguese water organizations applied for a rate of return economic regulation model in a comparison with the ‘others’. In order to overcome such a statistical problem, we applied a comparison of means, which will give us appropriate statistical results.

Furthermore, the null hypothesis presupposes no differences amidst the distribution of variables. Thus, when the p-value is lower than the significance level (p < 0.05), the null hypothesis is rejected and the existence of differences is accepted. This means that if p < 0.05 it can be assured that there are statistical main differences between groups. Regarding the forthcoming tables, all p-values are less than 0.001, which means that models are statistically significant, i.e., the statistical relationships between dependent and independent variables are proved.

Moreover, ANOVA allows knowledge of the strength of the relationship between variables (η2) to be known. This means that a higher η2 indicates a stronger relationship between variables. Since the study's intention is to examine the relationship between the variables from a separate perspective rather than in an integrated one, using this particular tool is justifiable. Nonetheless, linearity was considered in the model in order to find out if the amount of change between means is constant through the whole series of variables (p < 0.05). If this is the case, the study can ascertain the statistical results. Having said this, the next section will showcase the results of the empirical analysis using APA Style (cf.American Psychological Association, 2010).

Findings

The starting points for 2007 user prices in a comparison between rate of return and the others are not the same – Table 2. Rate of return presents a difference of around 50% for the 60 m3 consumption; 44% for the 120 m3 consumption and 38% for the 180 m3 consumption in comparison with the others. The user prices levels are much higher under rate of return. This is not unexpected since all the assigned concession contracts demand high investment levels in the first years. Hence, it would be expected that user prices could be higher under rate of return since those firms need to internalize all investment and operational costs in order to be economically viable in the short run (Silvestre, 2012). According to the regulator (ERSAR, 2014b), and for 2012, operators’ economic and financial sustainability (total costs versus revenues) is not satisfactory since their revenues are lower than their total organizational costs. In that sense, operators’ mean score for this particular indicator is around 0.7, when a score between 1.0 and 1.1 would be expected (to be considered a sustainable financial and economic score). Regarding the scores under the rate of return, and from the available data, few operators score positively, e.g. Mafra (1.0); Santa Maria da Feira (1.1); Santo Tirso (1.4) and Trofa (1.0). However, the majority score below the expected means, e.g. Alenquer (0.1); Fafe (0.4); Matosinhos (0.4); Ourém (0.3); and others. As discussed previously, the main reason to apply for rate of return was due to a political attempt to avoid consumer exploitation by franchised monopolies. Nevertheless, this regulation model was designed to allow the recovery of the investment made initially by the operator, which is the reason why user prices might increase in the meantime.

Table 2.

Client prices evolution between 2007 and 2012.

Year RM
 
MgM
 
RoR Other MSer Bur MCor Priv Multi 
2007 60 m3 €68.23 €45.36 €60.95 €41.46 €61.99 €70.20 €59.92 
2007 120 m3 €117.78 €81.96 €108.71 €75.53 €108.94 €120.50 €99.11 
2007 180 m3 €183.63 €132.73 €172.30 €123.52 €170.17 €187.65 €138.31 
2009 60 m3 €75.55 €45.63 €63.90 €41.11 €64.62 €77.83 €57.78 
2009 120 m3 €127.61 €85.75 €116.75 €78.52 €114.62 €131.02 €93.05 
2009 180 m3 €198.40 €140.95 €183.24 €131.24 €179.19 €203.44 €128.32 
2011 60 m3 €82.94 €53.21 €71.63 €47.03 €70.18 €89.52 €70.05 
2011 120 m3 €137.71 €96.68 €127.99 €87.88 €117.75 €148.51 €113.63 
2011 180 m3 €207.85 €153.27 €193.84 €143.39 €172.57 €227.86 €157.20 
2012 60 m3 €88.68 €56.42 €76.15 €49.83 €75.33 €91.71 €85.92 
2012 120 m3 €147.46 €101.39 €135.80 €92.07 €124.24 €154.67 €131.94 
2012 180 m3 €220.87 €157.35 €199.94 €147.22 €177.73 €236.77 €177.97 
Year RM
 
MgM
 
RoR Other MSer Bur MCor Priv Multi 
2007 60 m3 €68.23 €45.36 €60.95 €41.46 €61.99 €70.20 €59.92 
2007 120 m3 €117.78 €81.96 €108.71 €75.53 €108.94 €120.50 €99.11 
2007 180 m3 €183.63 €132.73 €172.30 €123.52 €170.17 €187.65 €138.31 
2009 60 m3 €75.55 €45.63 €63.90 €41.11 €64.62 €77.83 €57.78 
2009 120 m3 €127.61 €85.75 €116.75 €78.52 €114.62 €131.02 €93.05 
2009 180 m3 €198.40 €140.95 €183.24 €131.24 €179.19 €203.44 €128.32 
2011 60 m3 €82.94 €53.21 €71.63 €47.03 €70.18 €89.52 €70.05 
2011 120 m3 €137.71 €96.68 €127.99 €87.88 €117.75 €148.51 €113.63 
2011 180 m3 €207.85 €153.27 €193.84 €143.39 €172.57 €227.86 €157.20 
2012 60 m3 €88.68 €56.42 €76.15 €49.83 €75.33 €91.71 €85.92 
2012 120 m3 €147.46 €101.39 €135.80 €92.07 €124.24 €154.67 €131.94 
2012 180 m3 €220.87 €157.35 €199.94 €147.22 €177.73 €236.77 €177.97 

For 2011 user prices, rate of return presents a 10%, 8% and 5% change in comparison with 2009 results for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively. Just for ‘other’ organizations those differences for the same period are 17%, 13% and 9% change comparing with 2009 results for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively. Higher user prices for publicly owned organizations can be explained by the introduction of a new law (Decree-Law 184/2009) which demands internalization of all costs for the water sector industry. This means that the water service provision by local structures cannot ‘share’ costs between departments in order to promote the efficient use of water department/organization resources. Due to the new Decree-Law, those organizations had to raise user prices in order to cover the organizational costs. The consequence was the transfer of those costs to the user and thus the user price increase is explained.

For 2012, in a comparison to 2011, rate of return presents a 7%, 7% and 6% change for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively. Just for the ‘others’, changes are lower in all levels of consumption, around 6% for 60 m3, 5% for 120 m3, and 3% for 180 m3. Finally, the study shows that user prices grew 30%, 25% and 20% for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively, under rate of return between 2007 and 2012. For the others, the user prices are lower for the same period (user prices grew 24%, 24% and 19% for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively).

Based on Table 2 user prices evolution, between the adopted regulation models (rate of return and others), and Table 3 statistical results we conclude that the economic regulation model effects user prices at all levels of consumption and for all considered years (p < 0.001), thus the relationship between variables is confirmed. However the strength of the relationship is changing. For 2007 client prices the strength of the relationship was η2 = 0.103 for the 60 m3 consumption level, η2 = 0.106 for the 120 m3 consumption level and η2 = 0.087 for the 180 m3 consumption level – Table 3. For 2012 client prices the strength of the relationship was η2 = 0.185 for the 60 m3 consumption level, η2 = 0.187 for the 120 m3 consumption level and η2 = 0.171 for the 180 m3 consumption level. It is still important to notice that it is for the highest consumption level that the adopted economic regulation model has the major explanation capacity.

Table 3.

Results of the ANOVA using SPSS to analyze changes in client prices by the regulation model (to test H1).

Source SS df MS P Eta2 
2007 CP'60* RM 11,901.68 11,901.68 31.94 <0.001 0.103 
Error 103,237.47 277 372.69    
Total 115,139.15 278     
2007 CP'120* RM 29,193.84 29,193.84 32.75 <0.001 0.106 
Error 246,942.47 277 891.49    
Total 276,136.31 278     
2007 CP'180* RM 58,976.74 58,976.74 26.48 <0.001 0.087 
Error 617,017.89 277 2,227.50    
Total 675,994.63 278     
2009 CP'60* RM 20,364.39 20,364.39 43.82 <0.001 0.137 
Error 128,745.29 277 464.78    
Total 149,109.68 278     
2009 CP'120* RM 39,867.12 39,867.12 38.62 <0.001 0.122 
Error 285,747.92 277 1,031.58    
Total 325,615.04 278     
2009 CP'180* RM 75,109.60 75,109.60 30.10 <0.001 0.098 
Error 691,154.21 277 2,495.14    
Total 766,263.81 278     
2011 CP'60* RM 29,703.00 29,703.00 53.16 <0.001 0.160 
Error 156,458.80 280 558.78    
Total 18,616,180 281     
2011 CP'120* RM 56,577.98 56,577.98 50.54 <0.001 0.153 
Error 313,479.90 280 1,119.57    
Total 370,057.90 281     
2011 CP'180* RM 100,107.30 100,107.30 40.30 <0.001 0.126 
Error 695,500.80 280 2,483.93    
Total 795,608.10 281     
2012 CP'60* RM 36,435.53 36,435.53 63.22 <0.001 0.185 
Error 160,792.60 279 576.32    
Total 197,228.10 280     
2012 CP'120* RM 74,333.07 74,333.07 63.98 <0.001 0.187 
Error 324,170.40 279 1,161.90    
Total 398,503.50 280     
2012 CP'180* RM 1,411,285.20 141,285.16 57.49 <0.001 0.171 
Error 685,720.90 279 2,457.78    
Total 827,006.10 280     
Source SS df MS P Eta2 
2007 CP'60* RM 11,901.68 11,901.68 31.94 <0.001 0.103 
Error 103,237.47 277 372.69    
Total 115,139.15 278     
2007 CP'120* RM 29,193.84 29,193.84 32.75 <0.001 0.106 
Error 246,942.47 277 891.49    
Total 276,136.31 278     
2007 CP'180* RM 58,976.74 58,976.74 26.48 <0.001 0.087 
Error 617,017.89 277 2,227.50    
Total 675,994.63 278     
2009 CP'60* RM 20,364.39 20,364.39 43.82 <0.001 0.137 
Error 128,745.29 277 464.78    
Total 149,109.68 278     
2009 CP'120* RM 39,867.12 39,867.12 38.62 <0.001 0.122 
Error 285,747.92 277 1,031.58    
Total 325,615.04 278     
2009 CP'180* RM 75,109.60 75,109.60 30.10 <0.001 0.098 
Error 691,154.21 277 2,495.14    
Total 766,263.81 278     
2011 CP'60* RM 29,703.00 29,703.00 53.16 <0.001 0.160 
Error 156,458.80 280 558.78    
Total 18,616,180 281     
2011 CP'120* RM 56,577.98 56,577.98 50.54 <0.001 0.153 
Error 313,479.90 280 1,119.57    
Total 370,057.90 281     
2011 CP'180* RM 100,107.30 100,107.30 40.30 <0.001 0.126 
Error 695,500.80 280 2,483.93    
Total 795,608.10 281     
2012 CP'60* RM 36,435.53 36,435.53 63.22 <0.001 0.185 
Error 160,792.60 279 576.32    
Total 197,228.10 280     
2012 CP'120* RM 74,333.07 74,333.07 63.98 <0.001 0.187 
Error 324,170.40 279 1,161.90    
Total 398,503.50 280     
2012 CP'180* RM 1,411,285.20 141,285.16 57.49 <0.001 0.171 
Error 685,720.90 279 2,457.78    
Total 827,006.10 280     

It should be kept in mind that alone the rate of return does not seem to be the sweetest option to lower user prices since incentives to be efficient are really low (Armstrong & Sappington, 2007). Like Bös (2001, p. 7) argues: ‘the utility may have an incentive to increase costs in the long-run because waste today leads to a higher price level tomorrow and increases the long-run profits’ – this is the case since negative results will be considered during the rate review. However, it should not be forgotten that initial investments under the rate of return model might have an influence on final scores, i.e. those efforts are not observable (Armstrong & Sappington, 2007). Besides, this economic regulation model is the finest option when investment in infrastructure is the main political goal, but to Marques (2005) it seems that improvements are not accomplishable by such methods. Due to these findings, it is concluded that the economic regulation model is becoming more important for user prices in the Portuguese water industry. This confirms the first working hypothesis. However, the political influence must be measured regarding the adopted model for water delivery – which is the reason why a control variable was considered.

With the adopted management model and user price evolution descriptive statistics a different starting point is being seen between the lowest user price means for all the consumptions levels in a comparison with multi-concession (45%, 31% and 12% for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively), municipalized services (47%, 44% and 39% for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively), municipal corporations (50%, 44% and 38% for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively), and the highest user prices for private firms (70%, 60% and 52% for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively).

This study shows, based on descriptive statistics, that benchmarking can explain changes in user prices. For example after the first league table exposition in 2007, a decrease in user costs was realized in 2009 for multi-concessionaries (−4%, −6%, −7% for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively) but an increase after the internalization of all costs was demanded by the new Decree-Law in 2009 (21%, 22%, 23% for the 60 m3, 120 m3 and 180 m3 consumption levels, respectively). In 2011 user costs grew for all management models, only decreasing for the 180 m3 consumption level under municipal corporations (−4%).

This means that benchmarking can influence user prices with the exposition of league tables. For that reason, the second hypothesis cannot be rejected because the user price levels between operators became stable, see Table 2. After the first league table was published, user prices decreased. After the entrance of a new Decree-Law in 2009, publicly owned organizations had to internalize their costs and hence user prices increased since operational costs had to be accounted for in tariffs. Nevertheless, between 2007 and 2012, user prices became closer considering both the economic regulation model and the adopted management model. Marques (2005) argues that benchmarking is a promising additional regulation model for the purpose of decreasing user costs. However, he criticizes the non-existence of productive efficiency indicators in order to push all organizations to be more efficient and not to increase tariffs to cover their organizational costs.

The second ANOVA examines the relationship between the management model and user prices and ascertains that the first variable has an effect on user prices at all levels of consumption and for all considered years (p < 0.001) – Table 4. This means that a relationship between variables is confirmed. However the strength of the relationship is also changing: for 2007 client prices the strength of the relationship was η2 = 0.258 for the 60 m3 consumption level, η2 = 0.279 for the 120 m3 consumption level and η2 = 0.234 for the 180 m3 consumption level. For 2012 client prices the strength of the relationship was η2 = 0.362 for the 60 m3 consumption level, η2 = 0.378 for the 120 m3 consumption level and η2 = 0.317 for the 180 m3 consumption level. Due to these findings it is concluded that the management model does have a superior impact on user prices in comparison with the adopted regulation figure, thus confirming the third working hypothesis.

Table 4.

Results of the ANOVA using SPSS to analyze changes in client prices by the management model (to test H3).

Source SS Df MS Eta2 
2007 CP'60* MgM 29,739.63 7,434.91 23.85.15 <0.001 0.258 
Error 85,399.52 274 311.68    
Total 115,139.15 278     
2007 CP'120* MgM 77,021.06 19,255.26 26.50 <0.001 0.279 
Error 199,115.25 274 726.70    
Total 276,136.31 278     
2007 CP'180* MgM 157,866.67 39,466.67 20.87 <0.001 0.234 
Error 518,127.95 277 1,890.98    
Total 675,994.63 278     
2009 CP'60* MgM 44,805.49 11,201.37 29.43 <0.001 0.300 
Error 104,304.19 274 380.67    
Total 149,109.68 278     
2009 CP'120* MgM 101,289.48 25,322.37 30.93 <0.001 0.311 
Error 224,325.56 274 818.71    
Total 325,615.04 278     
2009 CP'180* MgM 188,770.50 47,192.62 22.39 <0.001 0.246 
Error 577,493.32 274 2,107.64    
Total 766,263.81 278     
2011 CP'60* MgM 63,611.66 15,902.92 35.95 <0.001 0.342 
Error 122,550.12 277 442.42    
Total 186,161.78 281     
2011 CP'120* MgM 129,351.30 32,337.83 37.21 <0.001 0.350 
Error 240,706.56 277 868.98    
Total 370,057.85 281     
2011 CP'180* MgM 225,938.69 56,484.67 27.47 <0.001 0.284 
Error 569,669.45 277 2,056.57    
Total 795,608.15 281     
2012 CP'60* MgM 72,453.09 18,113.27 40.07 <0.001 0.367 
Error 124,775.02 276 452.08    
Total 197,228.11 280     
2012 CP'120* MgM 150,561.16 37,640.29 41.90 <0.001 0.378 
Error 247,942.35 276 898.34    
Total 398,503.51 280     
2012 CP'180* MgM 262,075.06 65,518.77 32.01 <0.001 0.317 
Error 564,931.00 276 2,046.85    
Total 827,006.06 280     
Source SS Df MS Eta2 
2007 CP'60* MgM 29,739.63 7,434.91 23.85.15 <0.001 0.258 
Error 85,399.52 274 311.68    
Total 115,139.15 278     
2007 CP'120* MgM 77,021.06 19,255.26 26.50 <0.001 0.279 
Error 199,115.25 274 726.70    
Total 276,136.31 278     
2007 CP'180* MgM 157,866.67 39,466.67 20.87 <0.001 0.234 
Error 518,127.95 277 1,890.98    
Total 675,994.63 278     
2009 CP'60* MgM 44,805.49 11,201.37 29.43 <0.001 0.300 
Error 104,304.19 274 380.67    
Total 149,109.68 278     
2009 CP'120* MgM 101,289.48 25,322.37 30.93 <0.001 0.311 
Error 224,325.56 274 818.71    
Total 325,615.04 278     
2009 CP'180* MgM 188,770.50 47,192.62 22.39 <0.001 0.246 
Error 577,493.32 274 2,107.64    
Total 766,263.81 278     
2011 CP'60* MgM 63,611.66 15,902.92 35.95 <0.001 0.342 
Error 122,550.12 277 442.42    
Total 186,161.78 281     
2011 CP'120* MgM 129,351.30 32,337.83 37.21 <0.001 0.350 
Error 240,706.56 277 868.98    
Total 370,057.85 281     
2011 CP'180* MgM 225,938.69 56,484.67 27.47 <0.001 0.284 
Error 569,669.45 277 2,056.57    
Total 795,608.15 281     
2012 CP'60* MgM 72,453.09 18,113.27 40.07 <0.001 0.367 
Error 124,775.02 276 452.08    
Total 197,228.11 280     
2012 CP'120* MgM 150,561.16 37,640.29 41.90 <0.001 0.378 
Error 247,942.35 276 898.34    
Total 398,503.51 280     
2012 CP'180* MgM 262,075.06 65,518.77 32.01 <0.001 0.317 
Error 564,931.00 276 2,046.85    
Total 827,006.06 280     

However, some explanations are demanded. The first conclusion is that user prices are politically dependent for all the adopted models. For concessionaries, the contract obliges them to make an initial investment and at the same time user prices must be stabilized otherwise that might put in danger politicians’ re-election. Bearing in mind that local government politicians are the ones who negotiate the contracts with the concessionaries, they will not risk huge user price increases in the first mandate – 4 years on average – in order to be politically and social credible for the second mandate (cf.James & John, 2006). That can be confirmed in the Portuguese water sector where user prices from 2009 to 2012 (the second half of local politicians’ mandates) did not increase that much in comparison with the 2007 to 2009 (the first half of local politicians’ mandate) period under rate of return economic regulation. This means that since elections took place in 2013, user prices did not increase that much in 2012.

Referencing Pinto & Marques (2015), user prices are defined by local governments and existing legislation. In addition, and based on the assigned contracts, public interest is not safeguarded. That conclusion is drawn from a study where assigned contracts involving public–public and public–private agents were compared. In such a way, contractual details under the public–private contractual scheme are not safeguarding the public interest (Pinto et al., 2015). Even though the Portuguese Regulation Authority was recently empowered, a power difficulty still remains (Pinto & Marques, 2015), especially concerning what actions can be taken with regard to user price interventions. This is because for private organizations, user prices are defined during the concession contracts and the regulator cannot oppose them (Martins et al., 2013a, 2013b).

On the other hand, when dealing with publicly owned organizations, politicians do have considerable power to intervene in the service (Buckland & Fraser, 2001; Marques, 2005). Because of this, politicians know a pronounced increase in water prices under the town hall direction ‘may influence political participation, including how people vote’ (James & John, 2006, p. 569). In other words, politicians will not risk a high tariff increase; otherwise their re-election could be in danger. Besides, the increase in user prices under the town hall remained the same in the period. In that sense, bureaucracies are the organizational arrangement that is closer to the local government politician's influence. This is the reason why user prices are lower in comparison with the others’ mentioned arrangements.

Conclusions

This study explores the relationship between economic regulation and user prices in the Portuguese water industry. The empirical analysis demonstrates that economic regulation based on the rate of return model is attached to higher user prices in comparison with the other organizations that are directly dependent on political decisions. The study also shows that a stronger prediction of user prices exists when considering the adopted management model for the delivery of water services. Main findings: the managerial element is neglected and the political option still prevails.

All the same, it is concluded that politics really matters (Yang & Hsieh, 2007) and ‘the connection between public management and political behavior has been neglected’ (James & John, 2006, p. 568). NPM ideas, especially the ones that aimed to split politics from management, have not been very successful in the Portuguese water industry so far. The politics-management split conviction was based on the idea of efficient services that would allow a decrease in user prices through private sector participation in services delivery, something that was not proven for the Portuguese water sector industry. Instead this study shows that political intervention is more suitable for the settlement of user prices. Regarding traditional public water delivery services organizations, user prices are lower but that can be a problem in the following years since those organizations might not be able to continuously operate without the recovery of operational costs. In that sense, strategic decisions need to be discussed between politicians and executives, while operational tasks are the latter's main responsibility (Alexius & Örnberg, 2015). In theory, municipal corporations are independent from political bodies from an operational perspective. In that sense, they might be a preferable arrangement in order to split politics from management while keeping lower user prices.

All these subjects must be discussed, since Pinto & Marques (2015) show that ongoing national tariff calculation is still attached to social and economic inequity. Because of this, better-off households are privileged and such conclusions put at risk desirable social goals. In that sense, tariff calculations must be considered in order to allow water organizations to recover their operational costs, while promoting higher efficiency levels. By the end, users will be privileged.

This is not an end but just a start to undertaking actions that can be effective to raise competition and to decrease user costs. We should bear in mind that differences exist between operators, namely their main organizational aims: social goals for public organizations and financial and economic goals for private organizations (Suleiman, 2005). Nevertheless, it is still recommended to continuously monitor user price evolution for the Portuguese water industry. If concessionaries started with a higher user price level, it is expected that tariffs still continue to grow in order to allow the private firms return on investment. On the other side, town halls do not have the financial capabilities to support services where costs are higher than revenues so they become suspicious about higher tariffs under publicly owned organizations. The solution is to wait and monitor the next round. The political variable must also be monitored through a better understanding of the political role in managerial decisions especially the analysis of those rules with higher costs and therefore greater public attention (Shapiro & Morrall III, 2012).

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