In his 1976 book, The Selfish Gene, the biologist Richard Dawkins introduced the concept of “memes” — ideas that individuals spread throughout a culture. The transmission of a meme can occur in a variety of ways, such as writing or speaking, perhaps through social media. Dawkins compared memes to genes in the way that they evolve and change in response to environmental pressures. From my perceptive, the concept of a meme is a useful way of thinking about the widespread adoption of increasing block tariffs (IBTs), the approach most municipal water utilities in Southeast Asia now use to calculate their customers’ water bills.
IBTs use two or more volumetric prices for determining a household’s water bill. In the first, or “lifeline” block, the volumetric price charged is set very low. If the household uses more water than specified by the first block, any additional water use is charged at a higher price. And if the household uses more water than the amount in the second block, additional water use is billed at a third, even higher volumetric price. The basic intuition is that poor households can access some minimum amount of water at very low prices, and the rich households which use more water will cross-subsidize the water use of poor households who use less water.
The “IBT meme” has spread rapidly throughout the community of water professionals and civil society over the past few decades, largely replacing uniform volumetric tariffs. The IBT meme’s message is that the IBT is a fair and efficient approach to determining water bills.
As described by Dawkins, memes can evolve, and this indeed has happened to the basic IBT structure as it has been adopted by water utilities in developing countries. Some water utilities have expanded the size of the first block so that the water use of the majority of households falls within this lifeline block. Other water utilities have expanded the number of blocks from 2 or 3 to more than 10. Many water utilities have added a fixed monthly charge to the volumetric component of households’ water bills to increase the magnitude and stability of revenues.
IBTs perform poorly in terms of targeting subsidies to low-income households regardless of the magnitude of financial subsidies that a utility receives from high-level government.
All these variations of the IBT meme are perceived to be fair and helpful to poor households, which is the main source of the IBT’s widespread appeal. But the intuition that IBTs are fair rests on two key assumptions. The first is that the correlation between household income and water use is high. The second is that water utilities charge volumetric prices in the upper blocks that are above average costs. Are these assumptions true?
In a new paper published in the World Development,1 Celine Nauges and I show that in fact the IBT tariff structure is not as fair (or efficient) as intuition suggests because in fact, these two assumptions are rarely true. Specifically, we show that IBTs perform poorly in terms of targeting subsidies to low-income households regardless of the magnitude of financial subsidies that a utility receives from high-level government. We also show that when cost recovery is low, the distribution of subsidies under IBTs is even worse if the correlation between water use and household income is high.
Figure 1 presents some of key analytical results of our paper. This figure shows the distribution of subsidies across household income quintiles for four combinations of the percent cost recovery that a water utility achieves and the correlation between household income and water.2 The results presented in the NW cell of the figure assume that 1) the utility achieves 50% cost recovery, and 2) the correlation between household income and water use is +0.1. The results presented in the SW cell assume that 1) the utility achieves 100% cost recovery, and 2) the correlation between household income and water use is +0.1. In the NE cell, we assume that 1) the utility achieves 50% cost recovery, and 2) the correlation between household income and water use is (unrealistically) +0.8. Finally, the SE cell we assume that the utility is achieving 100% cost recovery and the correlation between household income and water is +0.8.
Figure 1. Distribution of subsidies across quintiles (Q1 to Q5) under four different scenarios (IBT with US$0 fixed charge and 10m3 lifeline block)
We argue that the results in Figure 1 for Case 1 (NW cell) are typical of many utilities in developing countries. As shown, the poorest households only receive a small share of the total financial subsidies. In other words, the financial subsidies are very poorly targeted. Moving from Case 1 to Case 4 (from NW to SE) does improve the distribution of subsidies across income quintiles substantially, but we argue that this case is very unlikely to exist in practice.
In the paper, we also show that the welfare gains to poor households are much smaller in Case 4 than in Cases 1 and 2. The main beneficiaries of the 100% cost recovery constraint are taxpayers, not poor households (although poor households may also pay taxes). Moreover, the correlation between household income and water use is outside the control of the water utility, so a water utility with a low correlation (Cases 1 and 3) cannot simply choose to move to Case 4 to improve subsidy targeting.
In the past, water utility managers and policy makers generally have not been overly concerned with setting water prices either to achieve financial cost recovery or to send a signal to households to use water wisely (efficiently). Municipal water tariffs typically have been set below cost for political objectives. However, increasing water scarcity and climate change are making this strategy of pricing municipal water supplies far below cost increasingly untenable. Climate change in particular presents water and wastewater utilities with a complex new set of management and strategic challenges. One important way for water utilities to deal with the uncertainty introduced by climate change is to maintain cash reserves that can be deployed to address problems as they arise. But few water utilities generate sufficient cash to cover their full costs, and typically are unable to invest to protect strategic capital assets from extreme events or to build new capital facilities to address changes in rainfall and streamflow variability.
It is thus increasingly important for water utilities in Southeast Asia to adopt financially and economically sound water tariff designs that enable them to reliably provide essential services to their customers and that encourage households to use water efficiently. As we argue in our paper, the IBT meme is now an obstacle to this transition to improved municipal water tariff prices.
1. Nauges, C. and Whittington, D. (2016). Evaluating the performance of alternative municipal water tariff designs: Quantifying the trade-offs between equity, economic efficiency, and cost recovery. World Development. In press.
2. It is assumed that the IBT has a lifeline block of 10 m3 and no fixed charge.