A reasonable expectation
What low-income households pay for essential service in the United States
Over the past 18 months I’ve been working to develop a valid, generalizable depiction of water and sewer affordability in the United States. There’s currently no nationally-representative dataset on water and sewer rates, so my Texas A&M research assistant Jake Metzler and I painstakingly gathered water and sewer rates data from an original, nationally-representative sample of American water utilities.* We then calculated basic single-family residential water and sewer service prices and developed affordability estimates for each utility using the double-barreled methods I published earlier this year.
All that effort is now ready to bear fruit. An initial working paper reports the full methodology and findings in gory academic detail. If there’s interest here, I’ll share more about our findings here over the next few weeks and months – without the academic gore.
Today I’ll start by sketching the basic picture: how we measured affordability, and how affordable water and sewer services are in the US.
The sample & data
We drew our sample from the EPA’s Safe Drinking Water Information System (SDWIS), which SDWIS contains basic system information for the country’s nearly 50,000 water systems. An overwhelming majority of systems serve fewer than 3,300 people, and so a simple random selection would result in a sample of mostly small systems that collectively serve a tiny minority of the total population. So we stratified the sample—that is, we intentionally “oversampled” different kinds of utilities in order to get a wide variety of systems. Our analysis then adjusted mathematically for the sampling procedure to make sure we get truly representative results.
Single-family residential rates data were collected in the summer of 2017. To call the process laborious is an understatement (I’ll probably blog about that some other time!). For most large and medium-sized utilities, rates data were readily available on websites. When rates were unavailable online—especially common among smaller utilities—we inquired by telephone, repeating calls as necessary. Efforts to collect rates data were abandoned after multiple refusals or non-responses. The final dataset included full water and sewer rates data for 329 utilities. That might not seem like much, but it’s a larger sample than most, it’s representative, and we’re highly confident in the validity of the data.
Basic water & sewer as share of disposable income
We measured affordability in two ways; the first is with the Affordability Ratio (AR).
AR estimates basic water and sewer costs as a share of disposable income, which for present purposes is total income minus essential living costs (taxes, housing, food, health care, and home energy), estimated using Consumer Expenditure Survey data. To focus on low-income households, we measure AR at the 20th-income percentile (AR20). The 20th percentile household typically identifies the lower boundary of the middle class. These working poor households have very limited financial resources, but may not qualify for much public assistance.
Here’s what we found:
AR20 averaged 9.7. In substantive terms, that means that in the average utility, a household at the 20th income percentile must spend about 9.7 percent of its disposable income on basic water and sewer service. But AR20 varies widely, from a low of 0.6 to a high of 35.5. As the figure above indicates, AR20 is less than ten for about two-thirds of systems. A handful are very high—but these values reflect very low 20th percentile incomes as much as they do water/sewer costs.
Basic water & sewer in hours at minimum wage
My other way of measuring affordability is to express basic water/sewer costs in terms of Hours’ Labor at Minimum Wage (HM). This approach may not express affordability quite as accurately, but it’s precise and wonderfully intuitive: it represents the cost of water/sewer service in terms of labor. For those of us who have worked at minimum wage at some point in our lives, it is a powerful way to understand the cost of something.
Here’s affordability in the United States measured as HM:
As you’d expect, the distribution is very similar to AR20, ranging from 1.1 to 25.6. The overall average is 9.5, meaning that in the average utility, paying for basic water and sewer service requires about 9.5 hours of labor at minimum wage.
So is water affordable in America?
When confronting affordability, utility leaders are really asking: how much is it reasonable to expect households of limited means to pay? What economic sacrifices are reasonable?
These are ultimately questions about community values. There is no scientific answer to philosophical questions. No metric can define what is “affordable,” but good measurement can help us think about our values.
In the past I’ve suggested AR20 less than 10% and HM less than 8.0 as rules-of-thumb or point of departure to guide discussion. By these guidelines, 51 percent of the sampled utilities are affordable as measured by AR20 and just 39 percent are affordable according to HM.
We’re now in the process of analyzing the policy, organizational, economic, and demographic correlates of affordability. I’ll be publishing and blogging about what we find over the next several months. For now, I hope these figures provide some food for thought and help frame an agenda for tackling a tough issue.
*Collecting rates data is surprisingly difficult labor-intensive. Jake and I wrote a fun article on that topic–look for it next month.
During California’s recent drought, the utilities that own their supply sources conserved more than the those that purchase water from wholesale suppliers
-Warning: this post contains hardcore wonkery-
A while ago I blogged about my ongoing work with Youlang Zhang and David Switzer on water conservation in California. The first of our studies is now published at Policy Studies Journal; more are on the way. There we saw that financial incentives and institutional politics led to the surprising result that private, for-profit companies out-conserved local government utilities during a recent drought.
But another interesting pattern emerged from that study: a significant difference in conservation between utilities that draw their water supplies from wholesale sources.
Where utilities get their water
The drinking water utilities that serve American communities get their water in one of three ways*:
1) Pumping groundwater from wells that tap underground aquifers;
2) Drawing surface water from lakes and rivers; or
3) Purchasing water from a wholesale water utility.
In the first two cases, local utilities own wells, surface water intakes, and treatment plants. About 29% of American utilities fall in the third category, getting their water through wholesalers. In these cases, the local utility owns a distribution and/or storage system, but the supply works and perhaps the treatment facilities belong to another utility. Sometimes these wholesale utilities have retail customers of their own, sometimes they are purely wholesale suppliers.
In California, more than a third (36%) of water systems get at least part of their water from a wholesale supplier. A handful of very large wholesale water suppliers like Metropolitan Water District, San Diego County Water Authority, and Santa Clara Valley Water District manage major supply works, and then sell water to cities, special districts, and investor-owned retail water utilities.
Spreading the risk
A major advantage of big wholesale water utilities is that they allow a region’s water supply to be managed holistically and comprehensively. Rather than individual communities competing and depleting water supplies, regional wholesalers can plan and balance water supply needs. From the local perspective, wholesale utilities help diversify supply and so guard against catastrophic supply shortages. They also allow communities across a region to pool their capital for greater efficiency. Together these features spread both supply risk and financial risk across many local utilities.
Sales agreements between retails and wholesalers vary widely across the country, so generalizing is difficult. But one common feature of wholesale contracts is the take-or-pay provision. Under take-or-pay arrangements, the wholesaler agrees to supply and the retailer agrees to purchase a fixed volume of water over a given period of time for a given price. If retail demand exceeds the contract volume, the retailer pays for more on a volumetric basis. If retailer demand falls short of the contracted volume, the take-or-pay provision requires the retailer to pay the wholesaler anyway, as if it had used the entire contract volume.†
In other words, under take-or-pay contracts, the retailer pays the wholesaler the same amount, even if the retailer uses far less water than the contracted volume.
Wholesale supply & the logic of conservation
Got all that? Still with me?
Here’s what it all means for conservation. Wholesale supply arrangements reduce supply risk and long-term financial risk to local utilities. Take-or-pay contracts make a lot of sense for long-term stability for supply systems that have high fixed costs.
But in the short-term, these wholesale arrangements create disincentives for retail conservation during a drought. Under wholesale agreements, short-term supply risk from drought is shifted from the local utility to the wholesaler: the wholesaler is legally responsible for maintaining adequate supply. Meanwhile, fixed take-or-pay contracts leave retailers on the hook for the same amount no matter how much water their customers actually buy. The retailer may suffer significant sales declines if it rains all summer, or if the state imposes drought restrictions, but the retailer still has to pay the wholesaler as if demand was normal.
Together, these factors create structural disincentives for emergency conservation for retail utilities under wholesale agreements.
Does diluting risk also dilute conservation? As I explained in an earlier post, the recent drought in California prompted that state to impose conservation rules on retail water utilities from June 2015-May 2016. Each utility was assigned a specific conservation target and the state recorded overall conservation by each utility.
Did utilities that operate under wholesale supply arrangements perform differently from utilities that own their own supplies?
Our analysis of data from the drought mandate period is pretty striking. After accounting for a host of organizational and environmental conditions, we found that water systems that rely on wholesale water supplies were 42% less likely to meet state conservation standards, compared with systems that own their own supplies.
We also found that, after accounting for other factors, utilities under wholesale contracts conserved an average of 2.6% less each month relative to systems that use their own wells or surface water sources. In a state as large as California, this small percentage difference equates to tens of billions of gallons.
Follow the money
These patterns don’t prove that wholesale contracts caused California utilities to slack on conservation. But the data certainly align with the short-term incentives that wholesale supply arrangements create, and there aren’t other obvious reasons for the disparity. The lesson here is to pay close attention to wholesale contracts when setting conservation rules, so that conservation and financial incentives work in concert.
*Technically there are other sources, too—desalination and water reuse, for example–but they’re so rare that they don’t allow for much meaningful analysis.
†”Take-or-pay” is a weird phrase, since there’s really no “or” to the arrangement. Seems like “fixed fee” is a more accurate label, but then I’m not a lawyer.
Another way in which it’s tough to be poor
Drinking water utilities are great, but they aren’t perfect. Sometimes there are problems. Do those problems occur randomly? Or are there observable patterns in the water service problems?
Recently I’ve been posting about some findings from a Texas A&M Institute for Science, Technology & Public Policy (ISTPP) national public opinion survey. The survey’s carefully-designed sample of nearly 2,000 individuals is representative of the US population, and so offers an extraordinary look at public perceptions about water service. Earlier posts reported on attitudinal differences between water professionals and the general public, and on the ways that gender predicts opinion on water issues. I’m continuing to write up interesting findings from the ISTPP survey as time allows.
Today I’m looking at income.
Water service problems
The ISTPP survey asked respondents to say whether they had experienced each of the following problems with their drinking water with a simple yes/no answer:
- The water does not taste good (31.5% yes)
- The water is cloudy or dirty (19.5%)
- Water pressure is low (29.2%)
- The water causes sickness (3.8%)
- Water billing or payment problems (10.2%)
Importantly, this survey captures perceived water service problems, not actual problems—we don’t know that any given respondent actually experienced low water pressure, for example. We only know whether a respondent thinks (s)he experienced a problem. Likewise, we don’t know whether water actually caused sickness, only whether the respondent believes that it did. Fortunately, the large majority of respondents said “no” to all of these.
But the “yes” responses didn’t happen by chance. I fitted logistic regression models to identify correlates of water service experiences using the demographic variables in the ISTPP survey, such as race, ethnicity, age, urban/rural location, region, and income. These models estimate the likelihood of experiencing each of the five service problems.
A troubling pattern
The demographic correlates of water service problems vary, but across all five items, household income was the single strongest and most consistent predictor of water service problems. The graph below shows the likelihood of reporting that water billing problems at various income levels, with all else held equal (vertical spikes represent 95% confidence intervals):
At a $20,000 household income, there is a 13% chance of reporting billing problems. At $50,000, the likelihood is to about 9%; at $100,000 the likelihood drops to about 8%. That all makes some sense; we’d generally expect billing problems to correlate with income.
But the same pattern emerges for other kinds of water service problems, too. Here is the likelihood of reporting that water tastes bad at various income levels, again with other variables held constant:
At a $20,000 household income, there is a 37% chance of reporting bad-tasting tap water. At $50,000, the likelihood is to about 30%; at $100,000 the likelihood drops to about 25%.
Here’s the likelihood of experiencing cloudy or dirty water by household income:
Here’s the likelihood of reporting low water pressure by income:
And finally, here’s the likelihood of reporting that water caused illness by income:
Taken together, this is a sobering picture.* There is a clear relationship between income and the way that Americans experience their drinking water utility service. These results resonate with recent research finding a positive relationship between tap water consumption and income, with attendant implications for public health.
*In a future post I’ll look at race and drinking water experience; the picture won’t be much prettier.