Tariff (un)sustainability in contexts of price (in)stability: The case of the Buenos Aires water and sanitation concession

Utilities Policy 63 (2020) 101005

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Tariff (un)sustainability in contexts of price (in)stability: The case of the Buenos Aires water and sanitation concession Augusto C. Mercadier a, *, Federica S. Brenner b a b

Universidad Nacional de La Plata (UNLP), Argentina Centro de Estudios Transdisciplinarios Del Agua (UBA), Argentina

A R T I C L E I N F O

A B S T R A C T

Keywords: Water and sanitation Tariff structure Buenos Aires

We aim to analyze tariff sustainability in the Buenos Aires water and sanitation concession amidst price insta­ bility. We use the 3Ts model (Tariff, Taxes and Transfers) to discuss tariff resetting from 2002 to 2019. We show that both level and tariff structure reflect the national administrations’ preferences as regards service cost allocation among stakeholders. Despite the efforts, revenue has been below operative expenditure, which shows the company’s difficulty to remain operationally sustainable and the differences between the ex-ante and ex-post burden of the three Ts. We suggest recommendations for the regulator to shield the sector against price instability.

1. Introduction

However, it is interesting to point out that only a minority of pro­ viders actually achieve full cost recovery from tariff revenues. Subsidies are widely used in the sector. Komives et al. (2005) report that a survey by Global Water Intelligence (GWI) covering water utilities in 132 major cities worldwide revealed that underpricing of water supply services is widespread, even in high-income and upper middle-income countries. According to the survey data and estimated tariffs to achieve varying cost recovery levels, 39% of water utility companies set their average tariff too low to cover basic operation and maintenance (O&M) costs. In addition, 30% of the companies set their tariffs below the level needed to make any reasonable contribution towards capital cost recovery. In line with these findings, Andr� es et al. (2019) analyze utilities in 147 countries within the World Bank’s International Benchmarking Network for Water and Sanitation Utilities (IBNET) database. They conclude that only 14% generate enough revenue to cover all service provision costs, while only 35% manage to cover O&M cost. There is consensus on desirable practices from an economic theory perspective, but these practices have proved difficult (or unfeasible) to apply for several reasons. As a result, the sustainable cost recovery model has imposed itself in most cases. Experts are divided as to which aspects need to be taken into account as it depends on each particular situation. However, most of them agree that the price should at least equal operation, treatment and maintenance costs, whereas subsidies and external financing from the State and/or international bodies should cover construction and amortization expenses.

The importance of water and sanitation services for life and devel­ opment implies an endless number of particularities and challenges from an economic standpoint. Especially, the impossibility of separating sectoral policy from political and social issues. Following this line of thought, Rogers et al. (1997) and Rogers et al. (2002) suggest that economic principles for water resources management should be applied from a broad social, institutional and cultural perspective. When we look into water and sanitation financing, there is consensus that full cost recovery is the ideal target from the perspective of eco­ nomic theory. To illustrate this, we may refer in Europe to Article 9 of the Water Framework Directive (WFD), which lays down the principle of cost recovery for water services, including environmental and scarcity costs. Any decision that may undermine the tariff-financing model will inevitably result in a decline in the quality of the service provided and in an increase in environmental and public health hazards as a result of a lack of maintenance and infrastructure investments (EurEau, 2017). This definition aligns with the water and sanitation the total cost re­ covery model, which ensures the proper operation and sustainability of the facilities but leads to several resounding failures. In many devel­ oping countries, populations are often deprived of these essential ser­ vices and are expected to fully finance water and sanitation projects within the space of just a few years, when most developed countries achieve it in around a hundred years.

* Corresponding author. E-mail addresses: [email protected] (A.C. Mercadier), [email protected] (F.S. Brenner). https://doi.org/10.1016/j.jup.2019.101005 Received 4 June 2019; Received in revised form 30 December 2019; Accepted 30 December 2019 Available online 31 January 2020 0957-1787/© 2019 Elsevier Ltd. All rights reserved.

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Utilities Policy 63 (2020) 101005

We use the 3Ts (taxes, tariffs and transfers) concept to look into water and sanitation service financing (OECD, 2009). As such, the 3Ts approach refers to accounting, raising and balancing finance through tariffs (customer fees), taxes (subsidies) and transfers (external funds) (EEA, 2013). This shows that choosing a tariff level to finance a certain expenditure level cannot be made independently from transfers or subsidies. In that fashion, customers are billed differently and, thus, they participate differently in the financing of the service (Pinto and Mar­ ques, 2017). Pinto and Marques (2015) review 185 publications con­ cerning the importance of tariff structures in specifying objectives or perspectives of both water customers and suppliers. The standpoint concerning possible misapplication of different sources of revenue, herein focused on water tariffs, mainly refers to the promotion of pol­ icies which were successfully applied elsewhere, but which then proved to be unfit, harming the goals initially set. In the present work, we analyze the tariff sustainability in the Buenos Aires Metropolitan Area (BAMA) during the 2002–2019 period with reference to its macroeconomic context, an exogenous factor in the performance of the utility (Ordoqui Urcelay, 2007). We also show the difficulties or dilemmas policy makers face when setting tariffs and the direct implications on the 3Ts that finance the service. We chose this case study for several reasons. Firstly, because the macroeconomic context in Argentina has undergone many changes, the main one being that since 2002 inflation rate has remained above 23%. Therefore, the water and sanitation sector has been under stress and many providers’ operational balances and investment plans have been jeopardized. Following an analysis of 11 providers in Argentina, it was found that 7 companies were off-balance, and in 6 cases the turnover/ operation cost ratio was below 75% (Lentini and García Larumbe, 2015). Secondly, the particular case of Agua y Saneamientos Argentinos S.A. (AySA) was chosen because it is the largest company in the country and had the lowest income coverage ratio from 2006 to 2015. Thirdly, because during the period under analysis a major institutional trans­ formation took place: the company went from international private provider to 90% public national company. Finally, in 2015, the Secretariat of Infrastructure and Water Policy (SIPH, as per its initials in Spanish) carried out the National Plan for Drinking Water and Sanitation (PNAPyS, as per its initials in Spanish) setting guidelines and instruments on economic-financial matters and setting cost recovery goals for the providers. Since the SIPH is directly responsible for tariff setting in the Buenos Aires Metropolitan Area (BAMA), it is interesting to analyze and discuss the implementation of these guidelines. When analyzing tariff evolution in BAMA, we introduce cost recov­ ery concepts into an inflationary context. To the best of our knowledge, MacDonald (1955) is the only available reference. This circumstance might be of special interest for other services providers operating in inflationary contexts to warn them against the consequences of a tariff policy subordinated to macroeconomic policies. It might also be of in­ terest for other providers with operational deficits looking to restore cost equilibrium as it may shed some light on alternatives to tariff, subsidies and transfers. By choosing the 2002–2019 period we offer an alternative narrative to the Buenos Aires case study, focused on comparing the performances of the early-terminated private concession and that of the public com­ pany (Urbiztondo, 2016). Therefore, we aim to analyze the financial sustainability of the Buenos Aires concession and to evaluate the changes in the 3Ts (tariff levels, taxes and transfers). Tariff evolution for the 2002–2015 period, divided into three sub-periods, is presented in section 2; the 2016–2019 period, with a special focus on changes in tariff structure, is presented in section 3. Finally, our conclusions are presented in section 4.

a 30-year concession contract. The Concessionaire was the private company Aguas Argentinas S.A. (AASA), whose principal technical operator was Suez. As of January 1, 2002, the last tariff increase granted to AASA (approved before December 2001) came into effect. At the same time, Argentina sunk itself in its worst crisis and the economic emergency was declared by means of Law No. 25561. Its enactment rendered void all adjustment clauses in dollars or other foreign currencies, indexation clauses based on foreign price indexes and all other indexing mecha­ nisms in contracts entered into by the public administration under public law norms, including public works and services. Consequently, prices and tariffs were set in pesos at the exchange rate $1 Argentine peso per US$ 1. In addition, the National Executive Power was autho­ rized to renegotiate public service contracts. The following criteria were taken into consideration: 1) the impact of tariffs on public services’ competitiveness, the economy, and income distribution; 2) service quality and investment plans, when they were contractually planned; 3) customers’ best interests and service accessibility; 4) the security of the systems included; and 5) the companies’ profitability. Table 1 shows the evolution of income (column (i)), defined as mean tariff per user per month in dollars, and opex (column (ii)), defined as mean cost per user per month in dollars. Column (iii) shows income-toopex ratio. Two periods can be clearly distinguished. The first one goes from 2001 to 2006, when the ratio is above 100%, meaning tariff covered opex. The second one, from 2007 to 2015, when the ratio is below 100%. From January 2002 to March 2006, average inflation according to the National Institute of Statistics and Censuses (INDEC, in its Spanish acronym) was 75%. In this context, while the contracts were being renegotiated, costs increased and tariffs remained nominally fixed in Table 1 Tariff sustainability. Year

2001 2002a 2003a 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Income

Opex

Income/ Opex

CPIb

Income change

Opex change

US $/user/ month

US $/user/ month

%

Unit

Unit

Unit

(i)

(ii)

(iii)¼ (i)/ (ii)

(iv)

(v)

(vi)

17.92 7.75 6.25 6.36 6.35 6.29 6.01 6.02 5.12 4.90 4.76 5.60 4.77 6.55 8.12 14.07 17.04 14.80 12.72

12.14 6.66 5.79 5.73 6.20 4.96 6.07 8.21 8.86 10.45 12.78 15.18 16.36 16.23 19.56 18.24 20.14 18.26 14.43

148 116 108 111 102 127 99 73 58 47 37 37 29 40 42 77 85 81 88

1.00 1.26 1.43 1.49 1.63 1.81 2.11 2.62 3.07 3.79 4.73 5.96 7.21 9.99 12.69 17.29 21.58 31.85 49.36c

1.00 1.35 1.03 1.04 1.04 1.08 1.05 1.06 1.07 1.07 1.10 1.42 1.46 2.97 4.20 11.58 15.75 20.16 31.59

1.00 1.71 1.41 1.39 1.49 1.26 1.56 2.14 2.72 3.37 4.35 5.69 7.39 10.86 14.92 22.17 27.48 36.72 52.93

a After the abandonment of the Convertibility Plan, adjustment for inflation was allowed in financial statements between January 2002 and February 2003. b For the period 2007–2015 we used Pricestats statistics. c CPI - Survey of market expectations. Central Bank of the Argentine Republic. Source: own elaboration based on AASA and AySA’s financial statements, and INDEC for Consumer Price Index (CPI) (See Cavallo (2013)).

2. Tariff evolution and sustainability: 2002–2015 In 1993, water and sanitation services provision in BAMA was under 2

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Utilities Policy 63 (2020) 101005

Fig. 1. Tariff Sustainability. Source: Own elaboration based on AASA and AySA’s financial statements. Table 2 Comparison of tariff increases. Beginning of the tariff increase

April 2016

May 2017

May 2018

January 2019

May 2019

Tariff change (%) Cost Change (%) Inflation (as in Tariff Proposal) Inflation (actual rate)

217 49 23 40

23 24 22 25

26 34 21 48

17

49 44 25 40

23

Source: Own elaboration based on tariff proposals presented by AySA and REM Reports (https://www.bcra.gob.ar/Pdfs/PublicacionesEstadisticas/REM190430% 20Resultados%20web.pdf).

Marques (2017),2 this two-part bill has: a) a fixed component depending on land registry parameters (total surface area, covered area, year of construction and construction quality); b) a volumetric component that in the case of no-metered customers mimics the fixed component; c) adjustment components: the Z-coefficient, a cross-subsidy between different areas of the concession included in the fixed component (a map of the Z-coefficients for the different areas within the concession is provided in Appendix A - Annex C); and d) a fixed amount for universal service provision and environmental maintenance, also included in the fixed charge.

pesos. Until December 2005 accumulated inflation was 63%, whereas AASA average tariff increased by 3.6% and average opex by 49%. AASA maintained levels of financial sustainability mainly at the expense of a reduction in investment levels (Ordoqui Urcelay, 2007). The strong tension between the national government and the concession (exercised by the Grantor) resulted in the early termination of the contract and the creation of Agua y Saneamientos Argentinos S.A. (AySA), a limited lia­ bility (public) company whose social capital is held by the National State (90%) and by the company employees (10%). AySA was created in March of 2006 and it is governed by a regulatory framework approved by Law no. 26221. The Secretariat of Infrastructure and Water Policy of the Ministry of the Interior, Public Works and Housing of the Nation is the regulatory authority and is responsible for determining key aspects tariff setting among them - of the sector organization in BAMA. As mentioned, AySA was created after the early termination of the concession contract granted to AASA. AySA only achieved operative results in the first two years, if we consider 99% to be almost even. Inflation did not stop in 2006. It continued its upward spiral1 at a pace of 24% per year from 2006 to 2015 while average operation costs increased year-on-year at a rate of 32% and average tariffs at a rate of 20%. We then aim to analyze in detail tariff revisions in the 2002–2015 period by dividing it into three sub-periods. It must be noted that the main feature of the tariff regime is that tariff structure and level are independent (the actual billing formula is provided in Appendix A Annex A). This is represented by the K-coefficient, a scalar that multi­ plies the whole tariff structure to target a certain revenue goal. The structure is complex as customers pay a two-part bill, and we must bear in mind that only 18% of customers are metered. Following Pinto and

2.1. The freezing of tariffs The freezing of tariffs ended in November 2011. AASA was granted its last tariff increase on January 1, 2002 setting the K-coefficient at 0.9572. This value remained unchanged for almost a decade. During this period there was no change in any other parameters or subsidies. It should be noted that with the enactment of the new regulatory frame­ work, the changes that the new tariff regime introduced in the structure were neutralized in such a way that they did not affect the user or the company’s turnover (Bereciartua, 2017). During the last 4 years of AASA and the first 6 years of AySA, cus­ tomers did not see any changes in their billing, even though there had been a formal change in the tariff structure. Here lies the importance of analyzing the concession itself, irrespective of its private and public management stages. The freezing of tariffs extended beyond the termi­ nation of the private concession. The Emergency Law stated that the concession contract was to be renegotiated. During this period, it was only reasonable for the national government headed by N� estor Kirchner (2003–2007) not to grant a tariff increase. For example, Salant and Worock (1992) show that once costs are sunk, there is no incentive to set

1 There is no precision as to what the price variation was since 2007 because the National Institute of Statistics (INDEC) was intervened and the reliability of the Consumer Price Index (CPI) has been questioned.

2

3

See Equation (1).

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Utilities Policy 63 (2020) 101005

prices equal to average cost but to marginal cost, and Guasch (2004) reviews renegotiation models. Nonetheless, after the termination of the concession contract, tariff freeze continued with the subsequent �ndez de Kirchner (2007–2011). administration headed by Cristina Ferna During that period, Argentina abandoned the convertibility plan (currency board), which resulted in sharp devaluation and sustained price increase. Given that the Consumer Price Index was unreliable, for the period 2001 to 2010 we refer to the Wholesale Domestic Price Index (IPIM, in its Spanish acronym) (309%) and the Construction Cost Index (ICC, in its Spanish acronym) (321%). As we can see in Table 1, our proxy of CPI increased by 279%, and while the average income was fixed, average costs increased by 237%. Consequently, the cost coverage ratio decreased to 47%. The difference between constant income and costs increase gener­ ated a growing operational deficit that was financed through transfers from the national government. Given that the Government was the biggest shareholder, this subsidy could be interpreted as a capital contribution. Going back to the 3Ts, services provision costs were increasingly financed by AySA’s shareholders through taxes; that is, by all taxpayers in Argentina no matter whether they were in the conces­ sion area or not. As time went by, the inflationary dynamics worsened the situation. This exerted political pressure to restore operational equilibrium as the gap kept growing between BAMA, receiving the service in a subsidized manner, and the provinces, paying for the service in full.

probably threefold. Firstly, increasing tariffs due to increasing costs would have weakened the State’s stance in the lawsuit brought by the former concessionaire’s shareholders over the termination of AASA’s contract. Secondly, increasing tariffs in a generalized manner would have implied acknowledging a price variation that the State refused to acknowledge by manipulating the inflation rate index (CPI) as regulated tariffs were often used as nominal anchors in inflationary processes (Ordoqui Urcelay, 2007). And thirdly, openly granting subsidies politi­ cally implied “offering essential services very cheaply". Pinto and Marques (2015) state that water tariffs are a powerful tool as they can be seen as a conceptually simple way to promote multiple, possibly conflicting, objectives. Those trade-offs spark discrepancies between stakeholders and may produce undesirable results. Going back to the 3Ts model, tariffs were far below costs as we can see in Table 1 and taxes were not only applied in the concession area. Taxes collected by the national administration throughout the country meant a transfer of funds from the provinces to BAMA. It is also important to mention that another financing resource used was inflation tax. This model of cheap water and sanitation provision was implemented at the expense of tax­ payers who covered two thirds of the service cost with taxes or inflation. In 2013 the income-to-opex ratio decreased to 29%. Since inflation rate is considered one of the most regressive taxes, this provision model favored the rich in BAMA and penalized the poor outside BAMA.

2.2. General subsidy scheme

In April 2014, under Resolution No. April 2014 of the Undersecretary of Water Resources, a new subsidy scheme was implemented with the same goal but with three levels of subsidies granted automatically ac­ cording to the geographical area. To set up the subsidy, the K-coefficient was used this time. The Z-coefficient was used to make cross-subsidies between customers in different geographical areas within the conces­ sion area. The range of the Z-coefficient was divided into three groups (low, middle and high) and a 50%, 25% and 5% discounted K-coefficient was granted accordingly. Even if not explicitly stated, it seems reason­ able to assume that these groupings respond to a qualitative apprecia­ tion of socio-economic differences. A map displaying the Z-coefficient groupings is included in Appendix A - Annex C. As regards the demarcation of Z-coefficient areas, it is interesting to point out that they are borrowed from the 1993 concession company National Sanitation Works (in Spanish, Obras Sanitarias de la Naci� on, OSN). There is no record of the demarcation criteria used, nor is there a procedure or methodology to update it. These coefficients were estab­ lished in the ‘60s and the latest modifications date back to the ‘80s. Even if urban transformations over more than 30 years have led to the need to update this parameter, it never materialized (Brenner, 2015). In addi­ tion, districts recently incorporated into the concession area did not have zonal coefficient values. AySA carried out a qualitative study of the areas taking into account aspects such as infrastructure, level of com­ mercial activity and housing typology. Based on this and by analogy with other areas within the concession, the company suggested new values. The practical implementation was the same as before: setting a Kcoefficient high enough to allow for O&M cost recovery and then setting a discount on that coefficient according to the customers’ locations. The tariff increase involved a 37% increase in the K-coefficient and a subsidy reduction that ranged from 74.36% to 50%, 25% or 5%, depending on the area. This resulted in an average increase of 408% for the high tier, 301% for the middle tier, and 167% for the low Z-coefficient. At least three observations are worth making at this stage. The first is that the K-coefficient adopted a value of 5.1138, which reflected the operation and maintenance investment costs for the year 2012. With this, all cost inflation between 2012 and April 2014 meant an operating loss for the company that had to be compensated with contributions from the National Treasury. The second observation is that tariff in­ creases were not neutral but pro-poor biased and generated actual

2.3. Subsidy scheme according to the geographical areas

�ndez de After the October 2011 elections, in which Cristina Ferna Kirchner won re-election to a second term in office, AySA was granted its first tariff increase. It was implemented alongside other public utilities services. Although this process was called “partial withdrawal of sub­ sidies”, in the water and sanitation sector, this resulted in a) tariff in­ crease and b) the implementation of a general subsidy. In November 2011, the national government modified the K-coeffi­ cient from 0.9572 to 3.73319,3 which implied a 290% tariff increase but only a 30% billing increase. The reason was that, at the same time, almost all customers received a subsidy that consisted of a 74.36% reduction in the K-coefficient. As long as 3.73319*(1–74.36%) ¼ 0.9572, all the beneficiaries of this general subsidy saw the tariff in­ crease neutralized by this reduction percentage which meant the value was equivalent to the previous K-coefficient. Only 170,000 customers (representing 5% of total customers) did not benefit from this subsidy. Criteria for subsidy withdrawal were estab­ lished alongside other public services as regards non-residential cus­ tomers, a list of activity types and companies was drafted, and concerning residential customers, it was presumed that in certain geographical areas customers had sufficient income to pay the full tariff. We should bear in mind that in the tariff structure there was already a Zcoefficient to make cross-subsidies between customers. In this case, we had an additional geographical instrument to distinguish among customers. In order to avoid any exclusion errors, residential customers could apply for retain the subsidy. In an additional attempt to restore full cost recovery, customers who considered themselves capable of paying the full tariff could voluntarily decline the subsidy which was otherwise granted automatically. As of December 2013, only 7% of customers were unsubsidized. Therefore, for most customers, tariffs were frozen for 12 years, as was the billing revenue for AySA. This period was marked by an increase in transfers from the national government, which within only a few years became insufficient to cover all operation costs. The decision to maintain a general subsidy on the service was 3

See Resolution Undersecretary of Water Resources N� 44/11. 4

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Utilities Policy 63 (2020) 101005

billing increases of 408%, 301% and 167%, respectively. Finally, the third observation is that this subsidy scheme by geographical areas was in effect until February 2016 inclusive, and that the high, medium and low tiers are currently in use to differentiate the price of the cubic meter. Changes in the sector are relatively slow and there is a high degree of inertia.

Although PNAPyS guidelines and Art. 72 of AySA’s Regulatory Framework state that “the concession is in economic and financial equi­ librium if the tariffs for the services provided are sufficient to recover all associated costs, including operation, investment, tax and financial, if any, contemplated in the approved plans as long as those costs are efficient",6 economic and financial equilibrium was never achieved. The reason for this is that revenues were projected on the basis of forecasts which underestimated actual inflation rates. This in turn implied higher operation costs. To illustrate this point, Table 2 presents each tariff increase when it began (columns). In the first row, the tariff level variation (K-coefficient); the second one, cost variation estimated in the tariff increase requests. Except for the last year projected, in all cases cost variation was above the variation in the tariff increase requested. Nonetheless, on August 25th due to a political shift back to the left, exchange rate devalued by one third and a 50% pass-through to inflation is expected. This leads us to the last two rows: the inflation rate forecasted in the proposal and the actual inflation rate. Forecasted inflation in each of the tariff adjustment requests was below actual inflation. For example, inflation rates of 22% and 21% were forecasted for the years 2017 and 2018, but the actual inflation rates were 25% and 48%, respectively. For 2019, the inflation rate contemplated in the tariff proposal was 25%. The Survey of Market Expectations (REM) reported by the Central Bank of Argentina, estimated an inflation rate of around 40% for the whole year. This implies that operational balance will not be possible this year either, even though (as noted) tariff increases were partially advanced to January to compensate for some of the 48% inflation of the year 2018 and the remainder of the tariff increase was implemented as of May. One possible course of action in this respect would be to limit cost variation so that productive efficiency closes the gap between income and opex. This line of action has not yet been explored; actually, personnel (which represents more than half the share of operation costs) increased by 61% from 2006 to 2018 whereas customers increased only by 15%. Nevertheless, it should be noted that, given the instability of relative prices, decisions on input combinations may not be optimal.

3. Tariff evolution and sustainability (2015 to, 2018): economic balance as a utopia In December 2015, Mauricio Macri won the presidency. This implied a shift from a left-wing government to a right-wing one in a context of deep financial deficit (more than 5.1%)4 and high inflation rates. Given that the new government could no longer afford to finance BAMA through inflation rate and was trying to restore market conditions. In February 2016, the National Government launched the National Potable Water and Sanitation Plan (PNAPyS),5 which sets performance of the operator as one of the axes to reach 100% drinking water coverage and 75% wastewater services coverage in urban areas of the country. The PNAPyS presented a series of guidelines and instruments on economic-financial matters and listed certain goals to be reached by the providers to ensure compliance: � to progressively adjust tariff levels to cover efficient operation and maintenance costs (and subsequently part of the investments); � to reformulate the tariff structure to promote efficiency; � to design subsidy schemes to protect vulnerable customers; � to strengthen operators’ management (micrometering, loss control, benchmarking, regulatory accounting, energy efficiency); and � to implement investment co-financing schemes (government, oper­ ators, private sector and multilateral banking). All this is in line with Pinto and Marques (2017) and Maríne­ ~ eira et al. (2012), who recommend the establishment of binding z-Espin criteria to guide tariff design. These objectives went far beyond corpo­ rate finance and implied at least two things: general tariff adjustment and withdrawal of subsidy schemes.

3.2. Progress of subsidy scheme

3.1. Tariff resetting

Since almost all customers had some kind of subsidy, in 2016 reve­ nue could have been increased by resetting the tariff level or sweeping all subsidies, or a combination of both. In Table 3, subsidized customers are presented in the first column, 48% had a 50% discounted K-coeffi­ cient, 32% had a 25%, 15% a 5%, and only 5% had no subsidies at all. The actual tariff reset consisted of a 217% increase in the K-coeffi­ cient plus a reduction in the subsidies for customers that went from 5% or 25%–0%, and from 50% to 25% for the first year. The final effect of the tariff reset for each user is shown in column (ii) as “Actual reset in 2016”. As we can see, people living in the poorest areas received a 375% tariff increase and those in the richest areas, a 217% increase. This created a dilemma for policy makers. On the one hand, if they kept subsidies so as not to punish the poor, the final tariff reset would have meant a 328% increase for all customers (column (iii)). This value was arrived at by multiplying the share of customers (i) times the actual reset (column (ii)). On the other hand, if they were unwilling to raise tariffs, the minimum increase would have been 176% for the richest and 432% for the poorest (column (iv)). This value was arrived at assuming a 217% increase and all subsidies withdrawn. Then, we scaled down the tariff increase to 328%. These alternatives show the difficulty (and the political cost) of dismantling a strongly redistributive subsidy scheme. Reversing a pro­ gressive policy is regressive. The solution adopted was in-between those

In the case of AySA, Fig. 1 graphically shows the information pro­ vided in Table 1. On the left axis we see that costs (red bars) have always been above operating income (blue bars). In turn, on the right axis the green line shows the income-to-opex ratio. A great leap can be seen between the 2011–2015 and the 2016–2019 periods, in which the coverage ratio went from an average of 37%–83% and always remained below 100% (dash line). It is important to note that the company’s capital investments took a different tack. During the last AASA period, when the company still showed surplus values, these investments were practically paralyzed. Conversely, during the AySA period, when growing operating deficits were recorded, great investments were being made such as the con­ struction of a 900,000 m3/day capacity water treatment plant serving 4,000,000 inhabitants and an effluent pretreatment plant processing 2.2 million m3. For reference, during the 2010–2014 period capital expen­ diture tripled or even quadrupled tariff revenues. This situation could be construed as confirmation that the water and sanitation sector was being privileged with transfers for current expenditure and capital investment as well. Under the left-wing administration, it was politically decided to implement a low-tariff-high-investment policy, which materialized through enormous taxpayer transfers. 4

See Observatorio Fiscal Federal. http://www.observatoriofiscal.org.ar/#. See https://www.argentina.gob.ar/sites/default/files/interior_agua_plan_a gua_saneamiento.pdf. 5

6 See id¼125875.

5

http://servicios.infoleg.gob.ar/infolegInternet/verNorma.do?

A.C. Mercadier and F.S. Brenner

Utilities Policy 63 (2020) 101005

Table 3 Tariff increase: actual resetting versus corner solution alternatives. Z– coefficient

Share of customers

Actual reset in 2016

Alternative 1: Only Kcoefficient

Alternative 2: Only subsidy withdrawal

Comparisons: Actual vs. Alternative 1

Comparisons: Actual vs. Alternative 2

Low Middle High No subsidy

(i) 48% 32% 15% 5%

(ii) 375% 322% 233% 217%

(iii) 328% 328% 328% 328%

(iv) 432% 261% 189% 176%

(v)¼(iii)/(ii)-1 13% 2% 41% 51%

(vi)¼(iv)/(ii)-1 15% 19% 19% 19%

Source: Own elaboration based on tariff proposals presented by AySA.

extremes. Columns (v) and (vi) compare the actual reset with a simple increase and with subsidy withdrawal. In the first case, the variation in the K-coefficient benefits the poor. In the second case, the withdrawal of subsidies favors everyone but the poorest. Before 2015, there had been other subsidy policies focused on the poor that complemented (an eventually competed against) the rein­ forcement of the Z-coefficient as a cross-subsidy mechanism. This gen­ eral subsidy meant that customers who were on the Social Tariff Program (see Appendix A - Annex B for a brief description of the pro­ gram) no longer considered the program attractive and would not renew their membership. In fact, one year after the 2014 tariff increase, the number of customers decreased by 2% and reached its lowest point with 14,452 customers in March 2016 before the 2016 tariff increase. Conversely, tariff increases after 2016 had strong regressive conse­ quences since low areas were the most affected by the reset but at the same time, customers were given online access to a social tariff and the number of applicants to the program increased 17.9 times to 258,293 customers.7 Clearly, it took a long while to withdraw subsidies from customers in the low areas. This withdrawal was carried out in stages. The first 25% was withdrawn over six consecutive two-month periods from nonresidential customers first and then from residential customers. As regards affordability, before the 2015 tariff increase, water and sanitation services represented a financial burden of only 0.4% of household income (Ingreso Total Familiar (ITF), INDEC) for residential customers. In 2016, after the first increase, the tariff represented a burden of 1.01% of household income and nowadays it represents a 1.33%. These values fall well under the rule-of-thumb 5% threshold for water and sanitation expenditure to be considered unaffordable (Komives et al., 2005). Even if we consider the poorest 25%, the values are 0.80% in 2015, 2.23% in 2016 and 2.97% in 2019, which means that the tariff increase was not an affordability problem but rather a political one.

for non-metered customers it equals the fixed part of the fixed charge; that is, the previously mentioned 40%. The first problem faced by customers is that for their consumption decisions to have an impact on the bill, the variable charge had to sur­ pass 40%. For this reason, the incidence of the variable charge was increased to 80%. For already metered customers, this implied that customers with high Z-coefficients and low consumption would see their bills reduced, and low Z-coefficient customers and high consumption would see them increase. Finally, since the Z-coefficient modifies the fixed part of the bill, which is limited to the universal service charge, a cross-subsidy instru­ ment was lost. The way to restore it was to set different prices per cubic meter for customers in high, middle and low areas. There is no evidence in the economic literature to justify this third-degree price discrimina­ tion. However, this discrimination should allow the company to improve its collection rate as opposed to a uniform price per cubic meter for the whole concession area. This way, the bill places a similar burden on all household incomes. The relationship with the user changes radically since it implies new fraud prevention efforts and keeping quality records. In the use of the service, a drinking water user is no longer the one whose home is served by the water supply line but the one who uses cubic meters of water. The focus is on service consumption and not on service availability, and temporarily unmetered demands and the replacement of non-potable water (water from household wells in the Greater Buenos Aires area) with water supplied by AySA gain relevance. Following this change, reductions in unaccounted-for water are ex­ pected because now every cubic meter of water lost before the meter is both unaccounted-for water and unaccounted-for income. Besides, the integration of the technical and commercial areas of the company im­ proves asset control and optimizes pressure, thereby increasing the lifecycle of assets and reducing investment demands in excess capacity. We should bear in mind that generalized metering programs have longrun benefits. As a result, the discount rate these projects receive is extremely relevant when deciding whether they are convenient or not, and in turn this rate will depend on the (un)certainty of the general economy. Therefore, we return to the point we made earlier as regards operation costs. With high inflation, operative equilibrium cannot be reached and efficient long-term investments cannot be made either, as that long term is not worth it in an unpredictable economic context.

3.3. Changes in the tariff structure and new challenges Along with the 2017 K-coefficient increase, there was another sub­ stantial change as regards tariff structure: the first steps were taken to go from a cadastral scheme - still in force despite the fact that its modifi­ cations date back to Decree 9026/63 - to a metered scheme. This change in the tariff structure stems from the guidelines presented in the PNAPyS to promote efficiency and to increase the cubic meter price.8 Following Pinto and Marques (2017), if the cubic meter price were not corrected, moving from unmetered to metered tariffs would not have had any chance of success. Conceptually, the billed amount consists of a fixed charge and a variable charge. The fixed charge includes the universal service charge, a fixed uniform amount for all customers. On average, it represents 20% whereas the fixed component of the fixed charge represents 40%. The variable charge for metered customers sets a price per amount used, and

4. Conclusions In this work, we have used the 3Ts model to analyze the tariff policy and the financial sustainability of the Buenos Aires Metropolitan Area concession of the water and sanitation sector since 2002 with reference to its macroeconomic context. As regards the shift from private to public company, there is evidence of tariff policy continuity. Neither ownership nor change in government administrations was an obstacle for tariff resetting. Water and sanitation tariffs abide by a general public services policy and are subordinated to macroeconomic fiscal policies. Therefore, transfers (subsidy policy) do not respond to the specific needs of the sector (such as guaranteeing the human right to water and sanitation), but to the use of water and sanitation tariffs as nominal anchors in the

7 According to the Commercial Reports reported monthly by AySA. As of April 2019, the number of beneficiaries of the social tariff is 304,150. 8 It increased from USD 0.24 to USD 0,75 (including sanitation charge).

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A.C. Mercadier and F.S. Brenner

Utilities Policy 63 (2020) 101005

fight against inflation. In fact, no severe affordability problems were found after tariff resetting. This subordination of sectoral tariffs to macroeconomic needs directly affects the financial sustainability and performance of the water utility. Generally, the greater the delay in tariff resetting, the greater the effort to restore the initial equilibrium and the greater the political and social cost. To lower these deficits, the company has to issue new debt or reduce renewals and maintenance investment plans (increasing the burden of future customers). This creates a vicious circle as service quality and efficiency levels decrease. For example, it leads to greater losses in the network and, subsequently, higher costs. This is an inter­ generational transfer between customers (from future to current). Alternatively, the government can bring public funds to the sector by cutting other expenditures or further increasing taxes. Both options imply a transfer from taxpayers to customers. The utility provider has fewer incentives to improve its efficiency. In practice, in all cases the provider’s reported costs in each tariff resetting were validated. The growing imbalance between income and operative expenditure until 2015 was covered with bigger Transfers from the national state so the company did not receive any price signals to improve its performance. When metered, low (subsidized) tariffs are associated with higher consumption and this threatens the rational use of water. The bottom line of the matter is that the uncertainty of the infla­ tionary process affects policy making in that the distribution of financing resources (3T) planned may not be met ex post. Actual inflation has been higher than estimated inflation and this generates greater deficits than initially expected, which end up being covered through further transfers from the national treasury. There has been a single annual tariff revision with a high-cost procedure (entailing public hearings). The greater the price variation, the faster the information becomes obsolete and the faster it loses its decision-making value. In this situation, the dilemma is whether to prioritize the promptness or the quality of information. For the regulator, information quality deteriorates and asymmetric infor­ mation grows. The 3Ts model can be applied to any provider, but this case reveals that macroeconomic instability can reshape (involuntarily) the planned burden of each T. It raises the question: what can we do to shield water and sanitation utilities from macroeconomic policies and from the po­ litical cycle? Firstly, tariffs should be indexed to keep up with operation costs. In order to keep tariffs up to date, resets should be fast, frequent, and based on public indexes such as Consumer Price Index (CPI) or Producer Price Index (PPI). That would provide allocative efficiency relieving ex post involuntary transfers. In order to increase productive efficiency, certain goals must be set according to the quantitative vari­ ables. For example, personnel expenses account for half of the operation costs so controlling the number of employees per thousand of connec­ tion ratio would provide an anchor for these costs. Secondly, investment (especially in network capacity and expansion) should be financed with public funds so that no investment is cut back to meet OPEX targets. Finally, regulators should design temporary subsidies to address affordability problems of the poor based on household income and living standards measurements because general subsidies have proven not to

be a good instrument as they are highly inertial and politically costly to reverse. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.jup.2019.101005. References Andres, L.A., Thibert, M., Lombana Cordoba, C., Danilenko, A., Joseph, G., BorjaVega, C., 2019. Doing More with Less: Smarter Subsidies for Water Supply and Sanitation. World Bank, Washington, DC. Bereciartua, P., 2017. La nueva gesti� on de AySA: sostenibilidad financiera, micromedici� on, subsidios y participaci� on ciudadana. In: Colecci� on Plan Nacional del Agua, Serie No 1 Agua Potable y Saneamiento, Documento No 4. Subsecretaría de Recursos Hídricos de la Naci� on. Brenner, F., 2015. Subsidios geogr� aficos en los servicios de agua y saneamiento: el caso de los coeficientes zonales en la Ciudad de Buenos Aires. Master’s thesis. Universidad Torcuato Di Tella. Cavallo, A., 2013. Online and official price indexes: measuring Argentina’s inflation. J. Monet. Econ. 152–165. EEA, 2013. Assessment of Cost Recovery through Water Pricing. European Environment Agency, ISBN 978-92-9213-409-9. https://doi.org/10.2800/93669. EurEau, 2017. Customers and Cost Recovery: Realising the Water Framework Directive. http://www.eureau.org/resources/position-papers/139-customers-and-cost-rec overy-may2017/file. Guasch, J.L., 2004. Granting and Renegotiating Infrastructure Concessions: Doing it Right. World Bank Publications, The World Bank number 15024. Komives, K., Foster, V., Halpern, J., Wodon, Q., Abdullah, R., 2005. Water, electricity, and the poor: who benefits from utility subsidies?. In: Directions in Development. World Bank, Washington, DC. http://documents.worldbank.org/curated/en/606521 468136796984/Water-electricity-and-the-poor-who-benefits-from-utility-subsidies. Lentini, E.J., García Larumbe, J., 2015. An� alisis sobre la situaci� on del sector de agua y saneamiento en la Argentina. Banco Interamericano de Desarrollo. MacDonald, C., 1955. Effect of inflation on water rates. J. (Am. Water Works Assoc.) 47 (7), 657–659. Retrieved from. http://www.jstor.org/stable/41254142. Martínez-Espi~ neira, R., García-Vali~ nas, M., Gonz� alez-G� omez, F., 2012. Is the pricing of urban water services justifiably perceived as unequal among Spanish cities? Int. J. Water Resour. Dev. 28 (1), 107–121. https://doi.org/10.1080/ 07900627.2012.642231. OECD, 2009. Managing Water for All. An OECD Perspective on Pricing and Financing. OECD, Paris. Ordoqui Urcelay, B., 2007. Servicios de agua potable y alcantarillado en la ciudad de Buenos Aires, Argentina: factores determinantes de la sustentabilidad y el desempe~ no. Serie Recursos Naturales e Infraestructura n� 126 May 2007. Economic Commission for Latin America and the Caribbean. Pinto, F., Marques, R., 2015. Tariff structures for water and sanitation urban households: a Primer. In: Water Policy, vol. 17. IWA, pp. 1108–1126. ISSN: 0048-5950. Pinto, F., Marques, R., 2017. New Era/New Solutions: the role of alternative tariff structures in water supply projects. In: Water Research, vol. 126. Elsevier, pp. 216–231. ISSN: 0043-1354. Rogers, P., de Silva, R., Bhatia, R., 2002. Water is an economic good: how to use prices to promote equity, efficiency, and sustainability december 2002. Water Policy 4 (1), 1–17. https://doi.org/10.1016/S1366-7017(02)00004-1. Rogers, P., Bhatia, R., Huber, A., 1997. Water as a Social and Economic Good: How to Put the Principle into Practice. TAC Background Paper No.2. Global Water Partnership, Stockholm. Salant, D., Woroch, G., 1992. Trigger price regulation. RAND J. Econ. The RAND Corp. 23 (1), 29–51. Spring. Urbiztondo, S., 2016. La regulaci� on de los servicios públicos en Argentina, 2003:-2015: L� ogica y balance de tres períodos presidenciales bajo un mismo signo político, Documento de Trabajo Nº 124. Fundaci� on de Investigaciones Econ� omicas Latinoamericanas, Buenos Aires.

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