Residential water tariffs typically consist of a fixed element and a per unit (variable) element. The fixed element is usually designed to cover the fixed costs of connecting to the water network.Footnote 11 The per unit element can be a constant uniform price or a price which varies with consumption. Uniform pricing is unlikely to satisfy all policy objectives: a low unit price ensures water is affordable to the poor but may create challenges around recovering costs and water conservationFootnote 12; a high price should conserve water but may lead to poor households consuming below an advisable level and/or facing financial hardship.
A price mechanism where the per-unit price varies with consumption, such as an IBT, attempts to find a balance between affordability and conservation. An IBT is defined by a set of k (≥2) consumption levels (or blocks), w1…wk, where w1 < w2 < … < wk, a set of k associated prices P1 < P2 < … < Pk and a billing period, t, after which the consumption level is returned to zero (Boland and Whittington 1998).
Figure 2 illustrates a three-block IBT. Compared to a uniform price, Pu, the IBT involves a lower price for consumption up to w1, a higher price for additional consumption up to w2, and a much higher price for consumption above w2. Intuitively the aim is to construct a first block corresponding to the essential consumption during a billing period and then price subsequent blocks of consumption increasingly as a luxury.Footnote 13
IBT Design Issues
The success of an IBT in meeting both distributional and conservation objectives depends on its design and consumer response.
In 1995 Santa Cruz, California introduced a third price block to its existing two-block IBT. Nataraj and Hanemann (2011) find this change led to a 12% decrease in water consumption among high water users. However, the marginal price facing high water users increased by nearly 100% implying that the price required to choke off demand may have to be very high.
Renwick and Archibald (1998) find low-income households to be five times more responsive to water price changes than high-income households. If under the uniform price, pu, there are consumers who consume less than w1, an IBT which lowers the price for the first block is likely to increase these consumers’ consumption (Wichman 2014; Asci et al. 2017). Consequently, prices for subsequent blocks, where households are relatively less price sensitive, may have to exceed pu very significantly, otherwise total demand would increase.Footnote 14 Wichman (2014) found the introduction of an IBT in North Carolina in 2007 led to an increase in water consumption overall.
To avoid an unplanned expansion in demand, the initial block size has to closely match the ‘recommended’ consumption for a specific household. A one-size-fits-all IBT with the same block size (w1) for all households is unlikely to deliver this, as essential water consumption increases with the number of household occupants. In some areas ‘water budgets’ have been used where the consumption allowed at each block price is individualised using household-specific characteristics and environmental conditions (Baerenklau et al. 2014). The main challenge is the availability of comprehensive and current data on household characteristics to set water budgets. Where consent is required to collect personal data, households may choose not to provide this. Also, if households understand that the information they provide will determine their water price, there is an incentive not to report their characteristics truthfully. One could set water budgets using less finely granulated government data, although at the cost of a less precise IBT design. Another approach for ensuring equity across households of varying sizes when using IBTs is to offer special rebates for large households (Kayaga and Smout 2014).
The need for a tightly designed initial block, combined with a high price for the final block, raises questions regarding the optimal number of blocks. First, consider where there are either errors in estimating the initial block size or ‘errors’ in consumption (see section 2.2). Given the large financial penalty for those ‘unintentionally’ consuming more water than assigned in the initial block, it may be sensible to introduce intermediate blocks with smaller price increases. This may explain why most observed IBTs have more than two blocks.
Second, households’ intertemporal decisions in response to uncertainty can lead to different behavioural patterns. For some households, there is an option value from reducing consumption today.Footnote 15 At any point in time within a billing period, a consumer will rationally constrain consumption to guard against hitting the next consumption block and its higher price. For low-income consumers who are more likely to consume within the initial block and who tend to be price sensitive, the consequences of the option value are particularly problematic since it implies they will consume below the minimum recommended level of water. This uncertainty effect is likely to be particularly pronounced when expected consumption is close to the boundary of a block, the price increase from moving into the next block is large, and/or the impact of a higher bill on a household is significant.
Third, it takes time, even for rational consumers, to learn about their demand and how an IBT functions. The larger the price increase between blocks, the more costly are mistakes during any learning phase. While painful mistakes may offer incentives to learn quickly, households differ in their ability to cope with cost shocks.
If we think the high price of subsequent blocks is a ‘punishment’ for over-consumption, there is the issue that the water company will benefit from higher revenue when meting out a harsher punishment.Footnote 16 The politics of this issue for privately owned firms (as in England and Wales) are probably challenging, as how can a consumer be sure the punishment is reasonable rather than a sign of corporate greed?
Finally, since the design choices above are made for a given billing period, an overlooked issue is that changing billing frequency usually requires changes in block size and/or prices. Wichman (2017) estimates the effect of increased billing frequency on household consumption. Halving the block size after halving the billing period does not control for the effect of billing frequency on consumer behaviour. Depending on households’ consumption patterns, it is possible for some households to have increased bills, despite identical annual consumption.Footnote 17 Thus the periodicity of households’ water demand becomes important.
Consumers’ Decision-Making Under IBTs
Under an IBT, the marginal price increases with each successive block but remains the same within each block; hence, households must consider not only the marginal price of the next unit to be consumed, but also the likelihood that their total consumption will end up in a higher priced block (Carter and Milon 2005). To make a fully rational decision, consumers need perfect information about the IBT’s structure, real-time information regarding their consumption, and the ability to form unbiased expectations about future consumption up to the end of a billing period (Hewitt and Hanemann 1995; Wichman 2014). Meeting all of these requirements is challenging. Where a water bill is small relative to household income, the time and mental effort to fully understand an IBT may exceed the potential monetary saving.
Also, households may form inaccurate perceptions of prices and consumption, preventing them from making a fully rational decision (Nieswiadomy and Molina 1989; Nataraj and Hanemann 2011).Footnote 18 Even with consumption data available, consumers may struggle to predict consumption over the long-term (Borenstein 2009) as they may fail to establish a link between day-to-day consumption and block price increases. These challenges can result in unexpected ‘bill shocks’, which will be particularly difficult for low-income households.
Clear and accurate water bills should aid learning and reduce uncertainty. Cater and Milon (2005) estimate water demand conditional on households’ knowledge of prices, using data from North-Central Florida. They find price information lowers water consumption, but this effect is weaker under IBTs than uniform pricing because households facing IBTs are less likely to know the marginal price of water. Using American data, Gaudin (2006) shows having price information next to consumption on bills increases price elasticity by 30%. However, increased billing frequency does not necessarily reduce water consumption. Gaudin (2006) explains two opposing forces operate: frequent bills help households establish a clear relationship between tariffs and consumption, but as bills become smaller they receive less attention. Empirical studies on whether increased billing frequency reduces water consumption are inconclusive (Kulshreshtha 1996; Arbués et al. 2003).Footnote 19
IBTs in Practice
Among developed countries, IBTs are widely used in the US (Olmstead et al. 2007; Asci et al. 2017),Footnote 20 some parts of the Europe, such as Spain (Arbués and Barberán 2012; Suárez-Varela et al. 2015) and Portugal (Monteiro 2010), and parts of Australia including Melbourne, Perth and Sydney (Brennan 2006). Unsurprisingly, these areas are associated with an existing high drought risk. Reviewing existing IBTs offers two general observations: first, IBTs’ structures can vary considerably across geographical areas and time periods, and second, IBTs’ effects are mixedFootnote 21 – some IBTs have reduced residential water consumption, while others have not, and some have even increased aggregate consumption.
Arbués and Barberán (2012) describe the water tariffs in Spanish provincial capitals in 2008. While more than 90% of cities used IBTs, their designs varied: the number of blocks ranged from two to eight, while the variance in the size and price of blocks was even larger. To understand these differences Suárez-Varela et al. (2015) analyse the determinants of the progressivity of Spanish IBTs. Greater water scarcity and greater economic activity led to more progressive block prices, while longer-ruling local government officials were related to less progressive tariffs. This suggests IBTs’ design and effects depend on local and household characteristics, and caution is needed when attempting to generalise results. Nevertheless, our review suggests some lessons can be drawn.
First, the high blocks must have sufficiently high prices, especially when non-essential water consumption lies mainly in high-income households. Second, there needs to be frequent adjustment of blocks’ sizes and prices to reflect changing environmental and socio-economic conditions (Nataraj and Hanemann 2011; Asci et al. 2017). Third, season, weather and outdoor water use are correlated, resulting in seasonality in residential water demand, which in some countries is found to influence price elasticity estimates significantly (Espey et al. 1997; Worthington and Hoffman 2008).Footnote 22 It follows that an IBT might vary block prices by season. Klaiber et al. (2014) measure the effect of seasonal changes in block prices by exploiting a natural experiment in Phoenix, Arizona between 2000 and 2003. They find that while high water users are more price responsive in summer months, responsiveness reduces substantially if a year is particularly dry. Fourth, an appropriate billing frequency and clear price information on bills should improve households’ learning. Fifth, IBTs need to be implemented for a sufficiently long period. While many studies obtain short-run measures of IBTs’ effectiveness, there are reasons to believe IBTs are more effective over the long-run. Empirical findings show price sensitivity is significantly higher in the long-run (Espey et al. 1997; Sebri 2014), mainly due to information accessibility and water-related investments by households (Carver and Boland 1980), while water use habits may take a long time to change (Gregory and Di Leo 2003; Asci et al. 2017). Illustrating the role of time, Baerenklau et al. (2014) investigate an IBT’s effects in southern California finding water demand was 17% lower than under a uniform price, however, the reduction occurred gradually over more than three years.
In all the studies reviewed, the water companies were monopolists.Footnote 23 Competition may undermine companies’ incentive and ability to adopt IBTs. If one company introduced an IBT with a high price for high water users, a sensible competitive response by rivals would be to charge a relatively low price for high water use. Rather than water conservation the likely end result would be the sorting of households across companies by households’ level of consumption. However, empirical evidence from the Texas energy market shows that even with competition, IBTs continued to be used (e.g. Puller and West 2013)Footnote 24.