A California surprise, Part I
Something unexpected happened when California ordered its utilities to save water: the state’s investor-owned private utilities out-conserved local governments.
California’s long-term drought began as early as 2007, but intensified to crisis conditions by 2012. Conditions worsened, and in response 2015 Governor Jerry Brown and the California State Water Resources Control Board imposed restrictions on 408 drinking water utilities designed to reduce urban water usage by 25% statewide. The order required utilities to cut water use, but left individual utilities to choose the means by which to achieve conservation. The mandate assigned each utility its own conservation target, with standards ranging from 4-36% reductions relative to 2013 levels. These standards were formulaic, and varied based on utilities’ historical water consumption.
These conservation rules were in place for twelve months—June 2015 through May 2016—and applied to both local government utilities and private, investor-owned utilities. Conservation rules were assigned based on historical demand patterns and supply considerations only, not on ownership or governance.
Happily, the State of California has shared utility-level conservation data lavishly—a boon to water policy researchers! Over the past year, I’ve been sifting through that mountain of data with Youlang Zhang and David Switzer to see how California’s conservation efforts have fared. We’re discovering some fascinating things. The first of our studies is now forthcoming in Policy Studies Journal.
Restricting the flow
Faced with water scarcity, communities frequently restrict residential outdoor water use, such as car washing and especially lawn/garden irrigation. These water restrictions are effective in driving immediate reductions in water consumption. In California those restrictions typically take the form of limiting the number of days when outdoor irrigation is allowed each week. The graph below shows how public and private utilities regulated outdoor irrigation during the drought.
Eyeballing that graph, there doesn’t appear to be much difference between public and private utilities. But after adjusting statistically for a host of factors like utility size, demographic composition, and hydrological conditions, it turns out that private, profit-seeking, investor-owned utilities restricted irrigation about 4% more than public, local government utilities. That may not seem like much, as we’ll see it’s actually huge.
Meeting the mandate
We were also interested in what made utilities more or less likely to comply with the state’s conservation rules. Overall compliance was about 53%–that is, on average 53% of utilities reached their conservation targets each month. We modeled compliance statistically, and found a number of interesting correlates of success and failure. But most notable was a yawning gap between public and private sector: after adjusting for other factors, private utilities were nearly twice as likely as similar public utilities to meet the state’s conservation standards.
Finally, we analyzed overall conservation during the mandatory conservation period. And again, we found that, after accounting for other factors, private utilities conserved an average of 3% more water each month than their public counterparts during the mandatory restriction period. Although this difference is small in percentage terms, it reflects an enormous difference in absolute volume of water. This plot presents the distributions of conservation results from June 2015-May 2016 for local government utilities (green), and what it would have been if each utility had saved 3% more:
The areas within the white bars on the right side of the distribution represent the conservation that didn’t happen due to differences in ownership. Three percent greater conservation would have boosted public utilities’ restriction compliance rate from 51 to 62 percent.
In substantive terms, three percent greater conservation by California’s local government utilities during the mandate period would have reduced the state’s water consumption by 54.6 billion gallons—enough to supply the City of San Francisco for more than two years.
So what happened?
California is once again in the midst of a hot, dry summer; other parts of the world are, too. So it’s worth trying to figure out what’s behind the public-private disparity in drought response. Although it’s surprising at first blush, it’s actually a logical result of the institutions that govern water in America generally and California specifically. My next post will explain why.*
*Spoiler: as usual, it’s about money and politics. If you can’t wait for the next post, you can read the forthcoming article.
Terrible, horrible, no good, very bad measurement, part 4
My criticism of average bill ÷ Median Household Income (MHI) as a measure of household-level water affordability isn’t especially new. Lots of other people have pointed out the problems with this conventional methodology, and I’ve been presenting and publishing these arguments for more than twelve(!) years. But golden numbers are stubborn, and bad habits are hard to break—even when people know better.
The remarkable persistence of a bad idea
Over the years I’ve presented to hundreds of utility professionals and spoken personally with scores of managers, analysts, and rate consultants about the pathologies of %MHI and the virtues of alternative approaches. The reception is universally warm and agreeable, as most water professionals genuinely care about affordability and immediately recognize the fundamental flaws of the conventional approach.
Alas, there’s an and yet.
Even well-informed specialists continue to use and promote the tried-and-false conventional methodology. Researchers who recognize that average-bill-as-%MHI is deeply flawed employ it anyway because it’s easy and widely recognized (for example). Managers who know that %MHI is a misleading statistic continue to put it in front of their elected officials because it’s familiar and they feel that they have to use this metric because everyone else does, and because they believe it’s an EPA standard (it isn’t). Advocates, analysts, and rate consultants who I like and respect persist with the conventional approach in their studies, even when they know these metrics are fundamentally flawed (many have told me as much!).
Examples abound. The Alliance for Water Efficiency has a nice tool that’s designed to help water utilities model the financial impacts of various rate structures. Sensibly enough, their model includes an assessment of affordability. Unfortunately, it uses the familiar flawed metric:
UNC’s Environmental Finance Center continues to feature average-bill-as-%MHI as the sole affordability indicator on its rates dashboards. Folks at EFC know about the problems with this metric (they blogged about it here), but continue to display it prominently nonetheless.
Easy metrics die hard, it seems.
Water and sewer ratemaking is a niche specialty (to put it mildly). That’s good news, because if the community of specialists who analyze and design rates for a living get affordability metrics right, there’s a good chance that the utilities they serve will get affordability right, too.
I’ve developed better ways to measure affordability; others are working on this issue, too. At this stage there’s no consensus over the best metrics (naturally, I think mine are great). But abandoning the flawed measurement convention is an important first step.
A feral howl on the conventional method of assessing household water affordability, part 1
Recently a colleague asked me how I first got interested in water and sewer affordability. I was tempted to claim that it was pure concern for the welfare of my fellow human being. That’s certainly the main reason. But I think there’s another factor at work: my near-pathological intolerance of bad measurement in public policy.
This is the first in a series of posts in which I
advance a critique of rant about the long-standing, widely-applied standard method of measuring water and sewer utility affordability in the United States. The lengthier, formal version of this discussion is in an article published earlier this year in Journal AWWA.
Next week I’ll be in Las Vegas at the AWWA Annual Conference & Exposition, where I’ll present better metrics, show some initial results of a new national study of affordability, and join Kathryn Sorensen in telling the story of how better measurement is helping to shape policy in Phoenix. But in this post I’m just going to rant.
The most widely applied method of measuring water/sewer utility affordability in the United States is to calculate the average residential bill for a given utility as a percentage of the community’s Median Household Income (%MHI). Usually this percentage is calculated for an entire utility, but sometimes it is calculated for a neighborhood or a census tract. This percentage is then compared with an affordability standard (usually 2.0 or 2.5 percent). A simple binary declaration follows this standard: if a utility’s average bill as %MHI is less than this standard, then it is deemed “affordable;” if it is greater, then it is “unaffordable.” Sometimes these %MHI standards are applied separately to water and sewer rates, other times they are combined water-plus-sewer costs (thus the standard becomes 4.0 or 4.5 %MHI).
This approach has become the default way to measure affordability in both scholarly research and policy analysis, with no other rationale than that it is convenient (a 4th grader could do it on the back of an envelope) and conventional (everybody else does it that way).
The reasonable origins of a silly idea
The %MHI method originated with the EPA, where the metric was first developed as a gauge of a community’s financial capability for purposes of negotiating regulatory compliance by its utilities. The idea of %MHI as a measure of financial capability traces at least to the EPA’s 1984 Financial Capability Guidebook. The idea of identifying specific %MHI thresholds for financial capability apparently come from EPA’s 1995 guidelines on Water Quality Standards (though these documents don’t offer an empirical or theoretical rationale for 1.0, 2.0, or 2.5%MHI standards).
As a measure of utility-level financial capacity (can a utility handle the costs of regulatory compliance?), average bill as %MHI isn’t crazy—it gives a vaguely reasonable sense of the utility’s demands on a community’s financial resources.
Here’s where it fails…
Unfortunately, at some point over the past 20 years, researchers, policy analysts, managers, and rate consultants started using %MHI as a measure of household-level affordability (can a poor family pay its water/sewer bill?). Despite its widespread use, %MHI is seriously, fundamentally, irredeemably flawed as a metric of household affordability.
The main trouble with using average bill ÷ MHI as a measure of affordability is that it does not measure affordability—at least not at the household level, in the way that most people think about affordability. Although EPA has drawn a great deal of criticism for its affordability metrics, this misapplication of %MHI to household-level analysis really isn’t EPA’s fault; the federal government never intended for their utility-level metric to be used in customer-level analysis. Alas, lots of otherwise smart and well-meaning people have done just that.
Over the next few posts I’ll get into the many reasons why average bill ÷ MHI is a terrible, horrible, no good, very bad metric.