Jason Mumm, global director of financial, commercial and risk management services
In describing this ‘new economy’ – a term coined in the media to represent the state of economic affairs in the post-financial meltdown world – I’ve often said it is a place where what worked before doesn’t and where everything is harder than it once was. Nowhere has this been truer than in the context of typical residential households. By 2007, U.S. household income was gradually recovering from the 2001 recession and had almost recovered all of its losses. It wasn’t to last. By 2013, real household income had fallen 8% from its 2007 peak and ended the year at same level as it was back in 1995 erasing nearly all the gains from the tech boom of the 1990s.
Unfortunately, the tale of median household income, as startling as it is, doesn’t even come close to describing the new economy for the millions of households that saw their real income decline while the real cost of necessary goods and services to keep those households running increased significantly. Spending on housing in the U.S. increased by 44% in real dollars between 2000 and 2013; fuel prices increased 67%; food by 19%; health care by 55%….you get the picture. During this same period, household spending on water and sewer utility services increased 26% in real dollars as prices for water and sewer services increased 2.6 times faster than standard inflation.
The new economy also accelerated the skew in income distribution. The financial meltdown didn’t start this one — it is a trend that started in the 1970s – but when you consider the changing shape of household income, the pace of inflation for basic goods, and the resulting residual (sometimes called disposable) income, the fact that more and more of the total money income in the economy has moved further to the right of the distribution (to those in higher income brackets) has additional implications.
All of this might only concern academics and social scientists were it not for the fact that the U.S. Environmental Protection Agency (EPA) uses these income data sets to make very big demands from local governments. In determining levels of enforcement of the Clean Water Act, the EPA assesses the financial capability of a community to absorb the financial burdens imposed by the enforcement order. EPA may, for example, require a local government to install a billion dollars of sewer improvements in order to address water quality concerns in the area. The billion-dollar order is then evaluated against the community’s income levels to determine if the burden is too high. For communities demonstrating a high burden, EPA may allow an extended time to implement its order (or not!).
The problem with the EPA’s measurements in these cases is that it depends on a single data point that is increasingly not indicative of what is really going on in the new economy. Their simple measurement converts the cost of their enforcement order to a hypothetical annual bill for a resident and divides that by the median household income for the community. The resulting quotient is the “residential indicator” and when the RI exceeds 2%, EPA acknowledges that the cost of enforcement is a high burden to the community. The question is: does median income really reflect the full burden of costs in a community?
To help support our clients’ cases with the EPA more aggressively, Hawksley Consulting developed a technique for analyzing financial burdens that augments those required by EPA in these cases. Called WARi™ for Weighted Average Residential Index, our measure enhances visibility of financial burdens by focusing on three key areas that the usual calculation neglects: effects on neighborhoods; the full distribution of income unique to the community; and real rather than hypothetical bills. To summarize the difference is to say that instead of relying on two data points to determine financial burden for an entire community as the EPA does, we provide 53 data points for every neighborhood (measured as a census tract). For a typical community with 30 – 40 census tracts, our technique provides 1,590 to 2,120 data points for a single year resulting in a weighted average residential index that, as anyone might expect, is very different from the EPA’s simplistic one. Better yet, when we link our WARi™ analysis to one of our standard long-term financial plans, we can evaluate how financial burden is expected to shift in the community over time, resulting in a 30-year (or longer) projection that paints a very vivid picture of the future burdens (See below: The “red” cells indicate neighborhoods where the financial burden is greater than or equal to “High Burden” as defined by EPA).
A 20-year projection could have over 42,000 data points depending on the number of census tracts included. Making sense of so much data is its own challenge, but as you can see above, we’ve reduced the relevant outputs into a GIS layer (tabular data is also available as shown) that makes the presentation the results as compelling as it is actionable.
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This blog post describes the problems that our clients face and introduces the techniques that Hawksley Consulting has developed and trademarked in an attempt to add greater clarity to the issue of financial burden within the context of the EPA consent decree cases. The WARi™ approach is unique to Hawksley Consulting and MWH Global. In part II of this blog post, I will describe more of the technical features of WARi™ and why our technique helps our clients not only in consent decree cases, but in every decision making situation.