Sometimes important questions in environmental economics are not particularly glamorous.  Take for example, a recent project I completed together with Laura Taylor, Professor and Director of the Center for Environmental Economics at NCSU and Jonathan Lee, a Ph.D. student at NCSU.  This project examines cost effectiveness of a program in Cary, NC that offers rebates to households that replace old toilets with new, low-flow toilets.  On good days we call this the “toilet project.”  I’ll leave it to your imagination to determine what we call it on bad days!

The Town of Cary (TOC) introduced its High Efficiency Toilet (HET) Retrofit Rebate program in June 2008. During the first 13 months of the program, TOC offered a \$150 rebate per toilet for water customers who replaced toilets that use 3.5 gallons or more per flush with WaterSense labeled high efficiency toilets which use 1.28 gallons per flush (gpf).

In June 2010 we mailed a survey to the 305 households that received a rebate during the first year of the program.  We received responses from 245 (80.3%) of participants.  The survey is structured to let us to compute the water savings that can be attributed to the rebate program.

Before we talk about economics, let’s think about engineering estimates of water savings. On a per-flush basis, an engineering estimate of the water savings is simply the difference in gpf used by the original toilet and the HET.  To compute an annual savings, we multiply the per-flush savings by the expected number of flushes per year. Carrying out this multiplication exercise and using data on how many toilets are in the home and how many people live in the home, we estimated an average savings of 4,577 gallons per high efficiency toilet installed.

Why might the water savings from the rebate program differ from these engineering estimates?  This is where the economics begins.  First, there is the possibility of a “rebound effect.”  That is, people install a higher efficiency appliance and they feel justified in using it more.  In the case of HETs the concern is probably NOT that they go to the bathroom more, but rather that they flush more because the toilet doesn’t work as well as they would like.  Second, some of these toilets may have been replaced even without the rebate.  A household doing a complete bathroom remodel may replace their low-efficiency toilets anyway and the rebate is just a windfall gain to that household.

We are able to examine real water savings from water utility bills for both program participants and similar households that did not participate.  We find little evidence of a rebound effect, the HETs toilets seem to deliver the expected engineering reductions in water use and that each toilet installed saves between 4,000 and 4,500 gallons per year per toilet.  The water savings that is attributable to the rebate program, however, is significantly less – approximately 1,750 gallons per year, per toilet installed with a rebate.  About 40% of the rebate participants would have replaced their old toilets with an HET even if the rebate had not been available to them.  In addition, we find that approximately 20% of rebate recipients would have replaced their old toilets with a new standard toilet (not HET) had the rebate program not been available to them.  New toilets are much more water efficient even if they aren’t HET.  The water savings of going from a new toilet to a new HET toilet are only 0.4 gpf (1.6 gpf for new toilet – 1.2 gpf for a new HET toilet).

Our final analysis focuses on the cost-effectiveness of the rebate program.  By investing in HET toilet replacement through the rebate program, the Town of Cary avoids future costs over the lifetime of the HET (assuming the old toilet would not be replaced in the future).  We focus on two measures of the avoided sewer treatment costs associated with fewer gallons flowing back to the system as a result of HET installation.  The present value of the avoided costs outweigh the initial investment cost (the rebates) if one assumes all toilets were replaced because of the rebate program.  However, if we consider only the water savings that is directly attributable to the rebate program, we find that the rebate program’s benefits to the Town of Cary did not outweigh the initial investment cost.

One way to increase the cost effectiveness is to reduce the up-front cost of the rebate program. Our calculations indicate that if the Town of Cary reduced the rebate to \$115 per toilet, the program would have been cost-effective under all scenarios considered.  Since the first year of the program, the Town of Cary has reduced its rebate from \$150 to \$100.  Even with the lower rebate, the Town reports that the requests for rebates have exhausted each year’s budget, suggesting the \$100 rebate is still a substantial incentive to households.  If the \$100 rebate results in about 30% of rebate takers being households that would not have replaced their toilet at all without the rebate, and another 20% being households that chose an HET over a new 1.6 gpf toilet as a result of the rebate, then the program is cost-effective.

Questions for Discussion:

1. One of the analytic challenges for the project was determining what the costs-savings were to the TOC when a toilet uses less water.  Our first approach assumed that if they didn’t sell a gallon of water to one of their own households, that was a gallon they could sell to a neighboring utility.  However, the central NC utilities have an agreement to sell water to each other at their lowest residential rate.  So no profit would be made by selling water to Durham instead of to a Cary resident.  We settled on avoided treatment costs.  What do you think the benefits to the TOC are?  How could the program be adjusted to provide more benefits to the TOC for conservation?
2. Another strategy for increasing cost-effectiveness of the rebate program is to better target rebates to households that wouldn’t otherwise replace their toilets.  Can you think of feasible ways to do that?

This week, I’m featuring a guest post from Christopher Timmins, Associate Professor of Economics at Duke University.

Prompted by a number of headline cases of hazardous waste contamination in the late 1970s, the US Congress established the Superfund program under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) of 1980.  Under that program, the Environmental Protection Agency has placed some of the most contaminated waste sites in the country on the National Priorities List, where federal funds are directed towards cleanup when those funds cannot be recovered from a “responsible party”.  Since that time, the EPA has identified more than 47,000 hazardous waste sites that potentially require some sort of cleanup action.  By 2007, more than 1,500 sites had been placed on the NPL.

Superfund site cleanups are not cheap.  Even before the budget crisis in Washington, there were many calls for an evaluation of the costs and the benefits of the program – the former requiring a careful accounting of all the resources that go into a cleanup, and the latter necessitating a non-market valuation exercise.  Superfund cleanups do not trade in the marketplace, but the houses surrounding a remediated site do – this provides one of the most simple and straightforward ways in which to look for estimates of the benefits of a Superfund cleanup – property value hedonics.  Economic theory tells us that homebuyers’ marginal willingnesses to pay for the remediation of a site can be deduced from what they are willing to additionally pay for a house that is near a remediated site versus a house that is near a site that has not been cleaned up.[1] This seems like it should be a simple empirical problem.  Take two houses – one in a neighborhood surrounding a site that has been cleaned up and one in a neighborhood surrounding a site that has not.  How do their prices differ?  The problem here (and in most hedonic analysis) is that these two neighborhoods may be different in ways that are not observed by (and hence, not controlled for) by the researcher.  These unobservables can confound the effect we are trying to measure.[2]

Empirical techniques have been developed to try to deal with these confounding unobservables.  In the parlance of applied microeconomists, researchers have looked for “quasi-experimental” data variation.  True “experimental” variation would require the researcher to randomize over which sites get cleaned up – something that the real world isn’t quite ready for yet.  Quasi-experimental variation is variation in which sites are cleaned that mimics experimental variation in one way or another.  One of the cleanest forms of variation used to date in the literature was suggested by Michael Greenstone and and Justin Gallagher.[3] They demonstrated that a twist in how the first wave of sites proposed to the NPL in 1982 were funded led to two batches of sites that were very similar in terms of how the EPA evaluated the hazard they posed, but only one of which received funding.  Comparing similar neighborhoods across these two groups allows the researcher to safely assume that unobservables are not the driving force in any differences in housing prices.  Rather, those differences must arise from the effect of the treatment being administered by EPA.

The Greenstone and Gallagher analysis, while relying on a clean source of quasi-experimental variation in data, suffered from another flaw.  In particular, it relied on publicly available data describing housing prices at the level of the Census tract.  Census tracts are areas containing several thousand individuals and can have a radius of several kilometers.  In their hedonic analysis, Greenstone and Gallagher used the median housing price in each census tract as their housing price measure.  While this may seem like an innocuous choice, it can have big impacts.  In particular, the externalities associated with many Superfund sites are highly localized – unless contamination works its way into groundwater or leaks into the air, it may not affect people outside a narrow geographical range.  Still it could have a big impact on the people it does affect.  Given the size of a census tract, it is therefore possible that a tract median price may not be affected at all by the cleanup of a Superfund site, while other parts of the house price distribution could be dramatically affected.  Indeed, Greenstone and Gallagher found no effect of  Superfund cleanup on median house prices.  This result has had big effects on Superfund program policy decisions over the last few years.

In our work,[4] we address this problem of localized externalities on several levels.  First, using publicly available census housing price data, we take an extra step to construct other parts of the house price distribution (e.g., the 10th, 20th, etc… percentiles of the distribution of house prices in each census tract) and look to see how these vary with site cleanup.  Where effects at or above the median become small or disappear altogether, we find big effects of cleanup (e.g., 18.2%) at the bottom end of the of the house price distribution.  Within a census tract, it is the cheaper houses that are benefitting from the Superfund program.

Next, we verify this result using restricted-access census block data.  Census blocks are much smaller than tracts (think about a typical city block).  Data on census blocks can only be used on-site in a Census Bureau Research Data Center, and only after going through a long series of security checks.  These data confirmed once again the presence of big cleanup effects on nearby houses (e.g., 19.4% on houses within one kilometer).

Based on these results, we feel confident that Superfund cleanups do, in fact, provide benefits to nearby homeowners.  Whether those benefits are big enough to exceed cleanup costs is another question that we are currently studying.  Passing a simple cost-benefit test will be made more difficult by the fact that benefits are localized, so a small set of houses will see price increases from cleanup.  Whether the benefits to those houses are sufficient to justify the costs is an empirical question.  Note that this sort of analysis ignores benefits that might arise from improved labor market conditions if a site cleanup leads to economic revitalization of a neighborhood.  It may also ignore health benefits if people aren’t aware of them, and hence don’t build them into their home-buying decisions.

[1] Note to reader – this is a delicately worded sentence.  Current research in non-market valuation theory (hedonic theory in particular) is aimed at rectifying shortcomings in the simple hedonic analysis that prevent the researcher from recovering preferences from compensating differentials in housing prices.  For example, when a change in a neighborhood is non-marginal (i.e., big relative to the size of the housing market), simple welfare measures are invalid.  Moreover, we may expect people to move around (i.e., re-optimize) in response to the change.  Simple hedonic techniques are not able to handle either of these possibilities.

[2] Note that research on this question has seldom even bothered trying to compare neighborhoods containing Superfund sites (cleaned or uncleaned) with neighborhoods that contain no sites at all – the thought being that the determinants of housing prices that we can’t see are likely to be very different across these two groups – we should at least restrict those unobservables to be the sort we would find in the vicinity of a site of some type.

[3] Greenstone, Michael, and Justin Gallagher, “Does Hazardous Waste Matter?  Evidence from the Housing Market and the Superfund Program,” The Quarterly Journal of Economics, 123 (2008), 951-1003.

[4] Gamper-Rabindran and Timmins (2011).  “Does Cleanup of Hazardous Waste Sites Raise Housing Values?  Evidence of Spatially Localized Benefits.”  http://econ.duke.edu/~timmins/Gamper_Rabindran_Timmins.pdf

In January 2009 I was awoken by the sound of my eldest child wheezing and gasping for air.  We called 911 and emergency personnel arrived to give her some oxygen.  After a short time they determined it was a severe croup episode and not, as I feared, a first asthma attack.  But that is a night I will never forget.  The fear you feel as a parent when your child cannot breathe is intense.  Millions of parents live with that background fear on a daily basis because their children suffer from chronic asthma. The Centers for Disease Control estimate that 7.0 million children (9.4%) have asthma as do 17.5 million (7.7%) adults.[i] Asthma results in 17.0 million health visits per year, 450,000 inpatient hospital stays with an average length of 3 days, and 3,447 deaths.[ii]

What does all this have to do with Environmental Economics?

President Obama recently asked EPA Administrator Lisa Jackson to withdraw a proposed refinement of the National Ambient Air Quality Standards (NAAQS) for ground level ozone that would have lowered allowable ozone levels from 0.84 parts per billion (ppb) to a range of 0.60 to 0.70 ppb.  Ground level ozone (not to be confused with stratospheric ozone which has the big hole) is also known as smog, and is a key contributor to asthma and other illnesses and deaths.

To be fair, the ozone NAAQS will be revisited in 2013, so Obama’s decision really only put off the debate for two years.  But why delay two years when the rule was ready to go forward now?  Must be economics.  Or is it?

In announcing his decision, President Obama said “I have continued to underscore the importance of reducing regulatory burdens and regulatory uncertainty, particularly as our economy continues to recover.”[iii] The announcement was made shortly after a bad jobs report was issued which further enhances the appearance that the postponed regulation was a “job killer.”  But the jobs versus environment rhetoric is just that—rhetoric.  It has no basis in economic analysis because economic analysis is not based on counting up jobs!

A good economic analysis compares the costs of complying with the regulation to the benefits resulting from the regulation.  The benefits in this case are the health benefits associated with reduced incidence of asthma and other health impacts.  Compliance costs include costs of purchasing new pollution control equipment, changing fuel sources, changing operational practices, and so forth.  The jobs analysis is really a non-starter.  Could we lose some jobs if we require more regulatory expenditures—certainly.  Could we gain jobs in industries that are selling and developing pollution control equipment–certainly.  Are these exactly a wash—probably not.  But we will also reduce hospitalizations, school days missed, and even deaths from asthma and other illness.  The key is that economic analysis is not “jobs analysis.” We do our best to measure the benefits and the costs of compliance in dollars.  Then we can compare dollars spent to dollars gained and not compare jobs to asthma cases.

So what did the economic analysis of the proposed ozone rule say about the costs and benefits of tightening the standard?  Not a lot that is useful, unfortunately.  This is not because the economic analysis is badly done (although I might quibble a bit on a few points), but rather because there is significant uncertainty over both costs and benefits of the proposed rule.  There are at least three major sources of uncertainty in the economic analysis.

1. Modeling uncertainty:  Ozone isn’t a pollutant that gets directly emitted from smokestacks or tailpipes.  Ozone is the result of combining two other pollutants, NOx and VOCs, with sunlight.  As a result, you have to model the ozone-generating process and estimate how many counties might not be in compliance when the rule becomes binding in 2020.
2. Cost uncertainty:  Once you estimate which counties would exceed the standard you need to come up with estimates of compliance.  But for some counties it was estimated that compliance was not possible with known technologies.  Compliance in 2020 relies on technologies that we don’t know about in 2011 and cannot accurately price.  It also relies on estimates of how costs of current technologies may change over the next 9 years.
3. Benefits uncertainty:  The benefits estimates rely on models of the relationship between ozone levels and deaths and illnesses.  There are several different models available in the peer-reviewed literature including three meta-analyses, yet these models still give answers that vary significantly.

These uncertainties mean that for each of the standards considered there is a large spread in estimated costs and estimated benefits such that the range of possible net benefits (benefits minus costs) always straddles zero.  The figure below captures the highest and lowest benefit and cost estimates for each standard.  You can see that the uncertainty in benefits is greater than the uncertainty in costs at all levels and that the uncertainty in both benefits and costs increases as the standard becomes more stringent.

click image to enlarge

###### Figure Source: United States Environmental Protection Agency.  Summary of the updated Regulatory Impact Analysis (RIA) for the Reconsideration of the 2008 Ozone National Ambient Air Quality Standard (NAAQS).  January 1, 2010. Available at:  http://www.epa.gov/ttnecas1/regdata/RIAs/s1-supplemental_analysis_full.pdf.  Last accessed, September 7, 2011.

With this much uncertainty in both costs and benefits, reasonable people could certainly disagree about the best course of action. I personally was very disappointed in President Obama’s decision.  I would strongly support an increase in stringency for the ozone standard based on the economic analysis presented in the Regulatory Impact Analysis.

How could I feel so strongly given all the uncertainties?  The reason is that historically we have systematically underestimated benefits from air pollution regulations and overestimated costs.  The retrospective benefit-cost analysis of the Clean Air Act from 1970-1990 estimated total benefits attributable to air regulations between 5.6 and 49.4 trillion dollars with a central tendency of 22.2 trillion.  The total costs were roughly 0.5 trillion.  That means that we are better off by around 21.7 trillion dollars because of these regulations.[iv]

Furthermore, most of the “unexpected” gains in benefits came from regulations of particulate matter.  The proposed ozone rule lowers emissions of NOx which also results in lower emissions of small particles (PM2.5) which are very harmful for health.  So if I had to bet on where we were likely to end up on the “distribution” of net benefits I would place my bet on higher end of the range.  And that means I’m betting that we are better off as an economy with more stringent ozone regulations.  I wish President Obama hadn’t caved to political pressures and supported his EPA Administrator in making that same bet.

[i] Centers for Disease Control and Prevention.  Fast Stats:  Asthma. Available at:  http://www.cdc.gov/nchs/fastats/asthma.htm.  Last Accessed:  September 8, 2011.

[ii] ibid

[iii] White House.  Office of the Press Secretary.  Statement by the President on the Ozone National Ambient Air Quality Standards. September 2, 2011.  Available at:  http://www.whitehouse.gov/the-press-office/2011/09/02/statement-president-ozone-national-ambient-air-quality-standards.  Last Accessed:  September 9, 2011.

[iv] United States Environmental Protection Agency. The Benefits and Costs of the Clean Air Act, 1970 to 1990.  Executive Summary. pp: ES-8.  Available at:  http://www.epa.gov/oar/sect812/1970-1990/812exec2.pdf.  Last Accessed: September 8, 2011.

Everywhere you turn these days in the environmental world, people are talking about fracking.  Fracking is short hand for hydraulic fracturing, a high tech method of extracting natural gas from shale located 1000s of feet under the earth’s surface. Basically, they drill a vertical well which then curves and goes horizontally, sometimes over a mile from the actual well-head.  The entire pipeline is cased in cement and then high pressure fluids—water, sand, and other things—are pushed down the well causing fracturing in the shale.  These fractures release the stored natural gas into the well.[i] The folks at the NY Times have got some great graphics that explain it.

There are many potential externalities associated with fracking.  An excellent analysis of potential externalities from methane contamination of groundwater by Osborn, Vengosh, Warner, and Jackson, all from Duke, can be found in this paper.  Today’s blog will focus on a different aspect of the fracking debate—the negative externalities associated with radioactive wastewater.

As it turns out, the rock formation that has trapped centuries old supplies of natural gas also contains radionuclides like radium.  Some of the hydraulic fluid that is pumped into the well to open the fractures is lost to the rock formation, and some comes back up as wastewater.  That wastewater contains elements from the rock formation including radioactive materials.

What happens to the wastewater?  In most states it is injected underground.  In Pennsylvania however, underground injection in not a viable option.  In that state, up to half of it gets trucked to wastewater treatment facilities where it is treated and then discharged into local waterways.[ii] But those wastewater treatment facilities were designed to treat the pathogens and contaminants that come from your household wastewater—the water from your toilet, shower, dishwasher, and washing machine.  They are not required to treat for radionuclides and are typically unequipped to do so.  The fracking wastewater is treated and discharged into the waterbody, potentially with significant radioactivity remaining.[iii]

Meanwhile downstream there is often a drinking water intake pipe.  That drinking water is further treated and tested for a variety of contaminants and sent to faucets in homes.  EPA has drinking water standards for radionuclides including a standard of 5 picocuries per liter (pCi/L) for radium.  EPA has standard for radium because exposure to radium in drinking water is associated with increased cancer risk.  If a community water system violates the radium standard they have to notify their customers. Furthermore the utility has to figure out a way to come into compliance, which generally involves more expensive treatment.

Time for some economics.  In last week’s post I argued that economists don’t think free markets can solve environmental problems and we needed regulation.  So far, nobody has called me on that one.  Probably because this is an environment school and I’m preaching to the choir.  But, it turns out, that there is a strain of economics dating back to 1960s that argues regulation is not always necessary.  The economist who first articulated this argument was Ronald Coase and he eventually won a nobel prize for this research.  Coase would argue that if property rights are well-defined, the actors in my stylized fracking example could sort the problem out themselves through negotiation.

Let’s imagine that the right to dispose of the wastewater is granted to the drilling company. The burden of treating the radionuclides, should they exceed regulated levels, is on the drinking water utility.  Coase would argue that the water utility could negotiate with the drilling company (or the wastewater treatment plant) to reduce the radium that is discharged, maybe by offering to pay for a program to recycle some of the wastewater or paying for additional treatment at the wastewater facility.  The drinking water utility would choose to do that if those options were less expensive than treatment options at the drinking water plant.  Alternatively, if the property rights to radionuclide free water were assigned to the drinking water utility, the drilling company or the wastewater plant could negotiate with the water utility to accept higher levels of radium in exchange for compensation to cover the additional treatment costs.  The drilling company and/or wastewater plant would do this if those options were less expensive.  Coase’s insight was that as long as property rights are well-defined and transactions costs are low, the parties can sort this out amongst themselves and the government need not get involved.

Notice that the Coasian solution to this problem existed only in the shadow of regulation–the radioactive wastewater imposed higher costs on the drinking water utility because they had to meet the EPA standard.  However,  in PA the radium standard for drinking water has essentially been nullified. PA water systems are only required to test for radium every 6-9 years and many drinking water facilities downstream of wasterwater plants accepting fracking waste have not been tested since 2005.[iv] We really don’t know how much of the radioactivity from the fracking waste might be making its way into drinking water supplies.  Maybe dilution in the river is sufficient to lower radioactivity to levels acceptable by regulation.  Maybe not.  But perhaps it is time to enforce our existing environmental laws so that we can at least find out.

Discussion questions:

1. In the absence of a binding EPA standard for radium, how well do you think the Coase Theorem will work?
2. What would be involved in a non-governmental solution to the radioactive waste problem in the absence of direct drinking water regulation?
3. Are there any positive externalities associated with fracking?  If so, what are they?

[i] Kerr RA (2010) Natural gas from shale bursts onto the scene. Science 328:1624–1626.

[ii] Urbina, Ian “Regulation Lax as Gas Wells’ Tainted Water Hits Rivers,” New York Times.  February 26, 2011.  Available at: http://www.nytimes.com/2011/02/27/us/27gas.html?ref=drillingdown.  Last accessed, September 1, 2011.

[iii] ibid

[iv] ibid.

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