This is part 2 in a series on promoting equity in your rate structure and protecting your most vulnerable citizens.
Water and wastewater systems are notoriously expensive to fund; between aging infrastructure, population fluctuations, and natural disasters, operating a financially sustainable system can be difficult at best.
In part two of this series, we broadly define three levels of water usage, and how they are represented on an example of a billing distribution chart in Waterworth. We also explore how the water industry measures affordability (buckle up for some economics!) and how to identify vulnerable rate payers in your own customer base.
Finally, in the third upcoming part of this series, we tie these concepts together to explain how through assessment of your community’s financial capability and analysis of your billing data distribution, cross-class subsidies are an option to promote affordability.
Broadly defining levels of water usage
This discussion focuses on residential rate payers and assumes the use of an increasing block rate structure. In a utility rate analysis tool like Waterworth, the identification of these different groups across billing data will look something like this:
Water is an essential service of life, and every individual requires it, every day. As such, your first (or lowest) usage group are your essential users. Their total usage almost always remains within your first pricing tier as they are using as little as possible, due to the aforementioned reasons. This basic, conservative usage is, to many community leaders, the goal, and hopefully the average when it comes to water conservation. In terms of standards like Median Household Income (MHI), these are often the users paying near or over 2% of their median household income, even if it’s not 2% of the municipality’s MHI. These are the individuals and families most affected by rate changes. The usage patterns of this group can be used as a guide for determining the threshold of the first tier in your rate structure (more on this to come in part 3). If the tier threshold is set appropriately, all users should be effectively incentivized to remain below it.
The next usage group are the moderate users: those who place some limits on their usage, but do not worry about an extra load of laundry. In many communities, this is the true “average” user and rate payer, who may observe conservation and personal price saving efforts, but still utilizes water services as they deem fit.
Lastly, the highest usage group are your excessive users: these are the rate payers who have no fear in their ability to pay the water bill, regardless of the amount; the ones who may not even notice if there is an increase in their utility bill. These users have lawns that require watering during a drought, own large properties, or are financially comfortable enough to go unaffected by rate changes. If you’re a Waterworth user, they might make up a large part of the “tail” on the x-axis of your Billing Distribution graph (above). Excessive users do not represent the vast majority of your users, but may inflict significant wear on the system.
The usage levels of these groups do not directly indicate where to set your tier thresholds, but depending on affordability and conservation goals, they can inform how to 1. Protect “essential” users and 2. Disincentivize “excessive” users, through cross-class subsidizations (again, more on this in part 3).
How the water industry measures water affordability
Median Household Income
Since the mid-20th century, Median Household Income — specifically, 2% of MHI — was the key measurement used to determine what was considered ‘affordable’ for water and sewage bills. With the EPA’s inception of the Clean Water Act, “Residential Indicator” took over as the new industry standard, calculated by finding the annual residential cost of the water or sewer service, and dividing it by the U.S. Census’ MHI. While this was an improvement from one data input source to two, its hyper-focus on the median means it still fails to accurately capture the diversity of cost of living, or changes that occur over the years, such as increasing service costs, erosion of the middle class, and stagnant household earnings.
Recently the industry and government institutions have determined that it is ineffective to take a vague and general formula and apply it to a specific municipality. Rather, it would be more effective to create a rate structure tailored to that community’s rate payer data and habits.
Moving beyond EPA's criteria
The American Water Works Association suggests “moving beyond EPA’s Criteria”. One way they suggest of achieving this includes measuring affordability across income distribution. Each municipality has a different amount of low-income households, who would be unable to afford 2% of what the designated median household income is, making that measurement inapplicable. By analyzing the average water and wastewater bills as a percentage across different income distributions, your rate-setting groups will more accurately reflect your actual rate payers and the people in your community.
Another method is segmenting your groups based on household type, such as renters, and/or elderly households, and using the average water and wastewater bills for those different household types as the means to measure what is “affordable” based on water used within the home and its occupants.
Alternatively, AWWA also suggests measuring across “neighborhoods or similar geographic units, such as Census tracts, or Public Use Microdata Areas”. This information can be considered when at-risk portions of the community, highlighting affordability issues that may be masked when the area is looked at as a whole. “Alternative measures of poverty, such as the Supplemental Poverty Measure (SPM) recently developed by the U.S. Census Bureau, can be
especially useful in this respect”.
The more input factors, the merrier?
There are even more expansive suggestions, such as the Weighted Average Methodology index (WARi™) featured in AWWA’s Transformative Issues Symposium on Affordability collection, which uses over 53 input factors, compared to RI using 2 input factors, or MHI using 1. Regardless, it’s becoming more and more clear that both the MHI and RI are not thorough enough to be sole sources of data for determining rate-setting groups.
All of these alternatives provide more detailed and case-specific datapoints than simply the MHI; after all, the data that comes out is only as good as the data that goes in. Other indicators that can also be considered include the unemployment rate, the percentage of customers eligible for water affordability programs, the percentage paying high housing rates, and many others. The key takeaway here is that in order to successfully implement cross-class subsidies, there needs to be more input data into identifying these classes than simply the MHI—which is only accurate for a very small subsect of your community.
So what's the solution?
In part 1, and now part 2, we’ve covered the topics of water equity and equality, cross-class subsidies, usage groups, and affordability calculations. But how do we put that all together in order to create a more sustainable, equitable, and successful water system? Stay tuned for part 3, where all these ideas will come together to create a solution for you and your rate payers.
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