Divided

The poor live with much more pollution than the affluent under government policies that concentrate toxic discharges where people with little income and even less political power live. The assumptions of cost-benefit analysis encourage this sort of inequality of hazard, as an economist and an environmental law professor explain.

The environmental justice movement emerged in the 1980s with disputes about the siting of undesirable facilities in communities of color. A protest in North Carolina, at the proposed site of a landfill for polychlorinated biphenyls (PCBs)—highly toxic and persistent chemicals that have been banned in this country and many others—is often cited as the launching point of the movement. This protest inspired several national studies on the siting problem; the studies eventually provided clear statistical evidence that racial minorities were more likely to live near hazardous-waste dumps.

In the early years of the movement, there was a lengthy discussion of whether this uneven burden was primarily based on the legacy of racial discrimination or the stark facts of economics. But underlying that debate is the more profound question of why a market economy produces, and condones, such a marked inequality of hazard.

Siting decisions are only one of the many ways that injustice manifests itself in health and environmental policy. For example, government decisions about which polluters to target for enforcement actions and possible financial penalties, and about where and how thoroughly to clean up contaminated sites, have also been shown to be correlated with race and ethnicity—and not in a way that works to the advantage of minorities.

Even the building blocks of health and environmental regulation—scientific assessments of risk—are often infused with assumptions that ignore or intensify racial and ethnic inequality. Assessments of the risk from eating fish contaminated with hazardous chemicals, for example, have often failed to account for the higher fish consumption of certain groups, such as Native Americans. Likewise, studies on pesticide risk often have assumed that the people exposed to pesticides have the body weight and other physiological characteristics of adults, yet many farmworkers bring their children to the fields with them when they work. Assumptions like these have the effect of understating risks to minority racial and ethnic groups, and thus threaten to reduce the health protections afforded these groups.

Likewise, there is increasing concern that the current enthusiasm for market-mimicking regulatory approaches—like pollution trading—has overlooked the potential for injustice in these approaches. A pollution-trading program in Southern California, for example, allowed marine terminals to avoid installing expensive new pollution-control equipment by buying old, highly polluting cars. That got the clunkers off the road. And it meant that increased pollution at the marine terminals was “traded” for lower pollution from cars.

Such systems are supposed to promote efficiency by lowering the total cost of pollution control; in this case, removing old cars from the road is a cheaper way to reduce emissions than controlling air pollution at marine terminals.

Unfortunately, the program did not always reduce pollution from cars; many of the scrapyards where the cars ended up just put the old, dirty engines into other cars that went right back on the roads. More significantly, the pollution levels in the mostly Latino, low-income neighborhoods surrounding the marine terminals went sky-high, thanks to emissions from the terminals (because increased pollution at these facilities, in just a few neighborhoods, was supposedly being traded for decreases on the roads throughout a four-county area).

Eventually the car-scrapping program was itself scrapped due to these problems. A seemingly sophisticated market mechanism only succeeded in creating inequality and environmental injustice because the more intense pollution continued in the poorer areas near the port.

There are multiple lessons to be learned from this experience. One is the power of the Enron effect: when a complex new market is introduced, the most profitable short-run strategy, if you understand the market, may be simply to cheat. It will take some time for everyone else to figure out what is going on, and until they do you can make out, literally, like a bandit. Those who like to invent market mechanisms should note the importance of transparency in new institutions, and the essential role of law enforcement.

A deeper lesson is the potential connection between pollution trading and inequality. Even if the California trading system had worked as intended—that is, even if the scrapyards had actually scrapped the dirty old engines—its effect would have been to trade reduced pollution in neighborhoods where the old cars were previously being driven for increased pollution around the marine terminals. Thus the efficiency achieved by the trading system, consisting of lower total costs for pollution reduction, would have come at the expense of shifting pollution into poorer neighborhoods. The economists who originally came up with the idea of pollution trading, more than thirty years ago, would not have been surprised to learn that the California trading program created heavily polluted “hot spots.” In fact, they thought something like this might happen, and embraced the idea. In their naive optimism, they thought that local variation in pollution levels would be associated with freedom of choice, not with inequality of power and income.

J.H. Dales, a Canadian economist who is often credited with first introducing the idea of pollution trading, concluded that it would be a good idea to allow lots of pollution in some places while allowing very little in others. Polluting an already polluted area was better, Dales thought, than spreading the pollution around so that every place was dirty. “We all benefit from variety,” Dales wrote in his 1968 book Pollution, Property and Prices.

If, for example, urban rivers are polluted but rivers in the countryside are kept pristine, the avid angler could enjoy city life yet still drive to a beautiful countryside to fish. Dales referred to his idea, following the lead of British economist E.J. Mishan, as the “separate facilities” approach.

But Dales forgot one important fact: people might live near each of his separate facilities, and living with pollution around them might harm more than their enjoyment of fishing. When the people who live around the “facilities” we’ve chosen to keep polluting are disproportionately African American, Hispanic, poor, or otherwise socially disadvantaged, even the term “separate facilities” has a sinister echo. It was, after all, racially separate facilities on passenger trains that the U.S. Supreme Court endorsed in its infamous nineteenth-century decision in Plessy v. Ferguson, with the impossible proviso that the facilities be “separate but equal.” The preference for “separate facilities” built into the original case for pollution trading makes it no surprise to learn that trading programs can worsen existing environmental inequalities.

It is widely agreed, at least in principle, that values like freedom and fairness are important considerations in health, safety, and environmental policy. Yet we have seen that market mechanisms such as pollution trading can work against fairness.

The problem is equally severe when it comes to monetization and cost-benefit analysis. Like life and health, the values discussed in this chapter do not come with price tags attached. There is no meaningful way to assign dollar values to risks when the upper limit of potential harm is unknown, when the risk is involuntary, or when the risk is unfairly distributed.

When the upper limit of potential harm is unknown, it is simply not possible to assign a number to the health and environmental benefits obtained by avoiding the harm. The number must either remain blank—in which case it will often be arbitrarily treated as if it were zero—or be based on a hopelessly speculative, perhaps misleadingly reassuring, guess.

In its unpredictability, terrorism closely resembles some of the major, uncertain, potentially unbounded environmental risks, such as climate change, in that reasonable, precautionary policies must be developed based on our current, imperfect understanding of the threats. Waiting for an impossibly precise measurement of the risks—or relying on wildly speculative, low-end predictions about the probability of harm—is a dangerous and shortsighted strategy for climate change, for terrorism, and for other fundamental threats to our future.

Likewise, the very nature of involuntary risks also defies monetization and creates troubles for cost-benefit analysis. The risks that led the Environmental Protection Agency to assume a value of $6.1 million for a human life are not the same kinds of risks that government often regulates. In the workplace setting involved in deriving that figure, the risks of death on the job are sometimes said to be voluntary; workers choose their jobs, the theory goes, based on their acceptance of a certain risk in return for a certain wage. Yet the choice of jobs is a somewhat more ambiguous process in reality, perhaps best described as partly, or occasionally, voluntary. However, in the environmental setting, risks are not allocated, even in theory, according to market transactions. No one has asked the citizens of Los Angeles whether they will accept money in return for dirty air; they just get the dirty air without being asked.

Some analysts have tried to incorporate the involuntary nature of environmental risks into cost-benefit analysis by proposing a higher dollar value for human life in the environmental setting, based on the claim that people will be willing to pay more to avoid involuntary risks than to avoid voluntary ones. This view misses the fundamental problem with translating involuntary risks to human life and health into dollars.

The philosophical premise of cost-benefit analysis is that a person is the best judge of his or her own welfare. When someone consents to accept an increased risk in exchange for money, the theory says that this choice should be respected for the sake of both freedom and rationality. But the same cost-benefit analysts don’t seem to think that people are very good judges of their own welfare when it comes to perceiving and assessing risks.

Aside from any other problems with this theory, the premise of rational, free choice obviously collapses when it comes to involuntary exchanges, which, by definition, take place without a person’s consent. An involuntary exchange is one forced on you, such as having to breathe dirtier air, if you live near the Port of Los Angeles, after that clunker car program.

Involuntary exchanges tell us nothing about a person’s true willingness to pay for benefits. No one, we suppose, would advocate using the money forked over to robbers or the ransom paid to kidnappers as evidence of the value of life or health.

It is possible, of course, that some voluntary market exchanges could exist with respect to involuntary risks. For example, a person might buy bottled water in order to avoid the risk associated with her contaminated tap water. Or she might buy an air filter to mitigate the risk from air pollution in her neighborhood. Thus, it could be argued, involuntary risks pose no special challenge for economic analysis based on “willingness to pay.” Such alternatives may not be practical in every case: to avoid climate change, will each person buy an unspoiled individual ecosystem, her own private Idaho?

But even when private expenditures, as for bottled water, could provide technical solutions, there is still a central issue to confront: who should have the right to go about her daily business without seeking permission from the people she affects—the polluter or the polluted?

If the consumer had a right to clean water, then whoever wanted to engage in activities that would contaminate her drinking water would have to seek her permission—and probably pay her—to go ahead with those activities. It may well be that a person would demand a much higher amount for her consent to have her drinking water contaminated than she would pay to filter or replace her water, once it was contaminated. She might even, for example, believe that her entitlement to clean water is not something to be bargained away, or she might have a moral aversion to the idea of befouling drinking water for economic profit.

In any case, market interactions between polluter and polluted likely would be very different from interactions between the polluted and a neutral third party, such as a bottled water supplier. By forcing even “involuntary” risks—risks not subjected to these kinds of market conversations—into cost-benefit analysis, economists and other analysts have contrived an unrealistic market where none realistically can exist.

Finally, and equally important, cost-benefit analysis also tends to ignore, and therefore to reinforce, patterns of economic and social inequality. Cost-benefit analysis consists of adding up all the costs and benefits of a policy and comparing the totals. Implicit in this innocuous-sounding procedure is the assumption that it doesn’t matter who gets the benefits and who pays the costs. Both benefits and costs are measured simply as dollar totals; those totals are silent on questions of equity and distribution of resources. If pollution trading reduces the total cost of pollution reduction, it increases efficiency as economists define the term, regardless of whether it also makes the dirtiest areas even dirtier. Yet concerns about equity frequently do and should enter into debates over public policy.

It is no coincidence that pollution so often accompanies poverty. Imagine a cost-benefit analysis of siting an undesirable facility, such as a landfill or incinerator. Benefits are often measured by willingness to pay for environmental improvement. Wealthy communities are able and willing to pay more for the benefit of not having the facility in their backyards; thus when measured this way the net benefits to society as a whole will be maximized by putting the facility in a low-income area.

Wealthy communities do not actually have to pay for the benefit of avoiding the facility; the analysis depends only on the fact that they are willing to pay. This kind of logic was made infamous in a 1991 memo circulated by Lawrence Summers (who later became Treasury secretary and later still president of Harvard University) when he was the chief economist at the World Bank. Discussing the migration of “dirty industries” to developing countries, Summers’s memo explained:

The measurements of the costs of health-impairing pollution depend on the foregone earnings from increased morbidity and mortality. From this point of view a given amount of health-impairing pollution should be done in the country with the lowest cost, which will be the country with the lowest wages. I think the economic logic behind dumping a load of toxic waste in the lowest-wage country is impeccable and we should face up to that.

After this memo became public, Brazil’s then–secretary of the environment Jose Lutzenburger wrote to Summers: “Your reasoning is perfectly logical but totally insane. . . . Your thoughts [provide] a concrete example of the unbelievable alienation, reductionist thinking, social ruthlessness and the arrogant ignorance of many conventional ‘economists’ concerning the nature of the world we live in.”

If decisions were based strictly on cost-benefit analysis and willingness to pay, most environmental burdens would end up being imposed on the countries, communities, and individuals with the least resources. This theoretical pattern bears an uncomfortably close resemblance to reality. Economic theory should not be blamed for existing patterns of environmental injustice; we suspect that pollution is typically dumped on the poor without waiting for formal analysis. Still, cost-benefit analysis rationalizes and reinforces the problem, allowing environmental burdens to flow downhill along the income gradients of an unequal world. It is hard to see this as part of an economically optimal or politically objective method of decision making.

When risks are reduced to numbers alone, funny things happen. Uncertainty collapses into a precise—which is not to say accurate—estimate of future hazards. Inequity is covered up by a market framework that is silent about the distribution of costs and benefits, and silently makes that distribution less equitable. The context of risk, the fairness of burdens and benefits—all these characteristics, which are all-important in real decisions—are priceless. They cannot be forgotten in making effective public policy, but they cannot be remembered with a number.

Adapted from Priceless: On Knowing the Price of Everything and the Value of Nothing.