Regulation of health and safety has placed an unacknowledged burden on low-income households and workers. Billions of dollars are spent every year on regulations that seek to reduce life-threatening risks that arise from auto travel, air travel, air and water pollution, food, drugs and construction; the list goes on. Today, some form of regulation affects nearly every aspect of our lives (Shleifer, in: Kessler (ed) Regulation vs. litigation: perspectives from economics and law, University of Chicago Press, Chicago, 2010). All of the regulatory rules ostensibly intend to make consumers or workers better off, but the cost of regulation usually is borne by the same consumers and workers, reducing their ranges of choice; it therefore crowds out private spending. The crowding out effect can be particularly detrimental for low-income households. This special issue explores the various ways in which regulation may have such regressive effects as well as the political determinants of how regulation, despite its unfavorable consequences for low-income households, may come about.
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Wildavsky (1981) argues that regulation is an attempt to identify excessive risks that adversely affect specific groups and to buy risk reductions for such groups at the expense of society as a whole. He suggests that the relevant question to ask when considering regulation of risks is “how much reduction of risk by direct expenditure on that very purpose versus how much increase in safety by expanding the national product?” (Wildavsky 1981, p. 19).
Baumol and Oats (1975, p. 191) show theoretically that environmental policy in particular may have redistributive effects of this kind. Such regulations represent the preferences of the wealthy but lower-income households primarily pay for them in the form of higher prices and lower wages.
The death rate measures the number of deaths, usually per 100,000 of population. It is distinct from the morbidity rate, which measures the number of newly appearing cases of a specific disease.
This paper considers only mortality risks addressed by regulation. Reductions in morbidity and secondary effects on mortality are difficult to quantify and therefore are not considered here or in most of the existing literature on the relative cost and benefits of regulation. The estimates presented in later sections of the paper may understate the overall benefits of regulation as regulation often results in a reduction in disease morbidity without affecting mortality directly. Similarly, the indirect effects of regulation on health and mortality—for example, the fact that requiring infant seats on airplanes drives up the number of infants injured in car crashes—are ignored. The estimates presented for the costs and benefits of private risk-mitigation strategies in Sect. 3 similarly are limited, so a comparison of the two may still be of interest.
Economists treat regulation as a cost imposed on producers and consumers, similar to taxation. See any standard microeconomics textbook for more detail.
The literature does not provide a definitive answer to the question of the incidence of corporate taxation. For a recent discussion of the topic from both a theoretical and empirical perspective, see the March 2013 issue of the National Tax Journal. Out of four contributions to the issue, two (Clausing 2013; Gravelle 2013) find that corporate taxes are born almost exclusively by capital, one (Cronin et al. 2013) finds that corporate taxes are born in part by capital (82%) and in part by labor (18%), and the last articler (Liu and Altshuler 2013) suggests that a one-dollar increase in corporate tax revenue reduces wages by about 60 cents.
Using risk–risk analysis Viscusi (1994, p. 13) similarly finds that "policies costing more than $35.7 million per life saved will not be beneficial from a health standpoint." Lutter et al. (1999) develop a model of the conditions under which risk regulations have adverse health effects when their costs are too high. They find that a $15 million decline in income is associated with the loss of one additional statistical life.
“Diminishing marginal utility” is an economics term that applies to most goods. It means that as people get more of something, they become less enamored with it. For example, one might pay a great deal for the first daily glass of water or for the first personal computer. But it would be expected that people would be willing to pay a great deal less, because it is not as valuable to them, for the 10th or 20th personal computer.
The NHTSA announced a final rule mandating installation of rearview cameras on March 31, 2014, after significant delay. The delay in the ruling can be attributed to the limited benefits and high costs associated with the mandate, which were debated fiercely by safety advocates and their opponents. The Cameron Gulbransen Kids Transportation Safety Act of 2007 originally required NHTSA to provide a final rule by the yearend 2011. See Cameron Gulbransen Kids Transportation Safety Act of 2007, Public Law 110–189, U.S. Statutes at Large 122 (2008): 639, http://www.gpo.gov/fdsys/pkg/PLAW-110publ189/pdf/PLAW-110publ189.pdf.
This calculation uses 2013 Estimates of the US resident population of children under age five from the Census Bureau, which was 19,868,088. See U.S. Census Bureau, Table: Annual Estimates of the Resident Population for Selected Age Groups by Sex, April 1, 2010 to July 1 2013 available at: http://www.census.gov/popest/data/national/asrh/2013/index.html.
This calculation uses the 2013 Census Estimates of the Resident Population of the United States, which was 316,128,839 (Ibid.).
Department of Transportation, "Value of Statistical Life and Injuries", March 18, 2009, http://www.dot.gov/regulations/value-statistical-life-and-injuries.
When the relative price of new cars increases, the demand for used cars (a substitute) likewise increases, which drives up the prices of used cars. For more information on the effect of a change in the price of a substitute on the market for a particular good, see any introductory microeconomics textbook.
Secondary consequences potentially are associated with such risk-reducing regulations. When low-income households are forced to pay higher prices for new cars as a result of the backup camera mandate, they may be forced into the market for used cars instead and end up purchasing older vehicles with neither the newly regulated safety feature, nor other important safety features, thereby leaving them driving a less safe vehicle overall. Alternatively, they may forgo the purchase of other safety features that might have offered more benefits to the particular household because to avoid the extra cost of the newly regulated safety feature.
To some extent, such regressive effects may be mitigated when low-income individuals can avoid purchasing regulated products. Note that that reasoning also implies that households may be worse off because they are discouraged from buying a product they may have otherwise wanted to buy.
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I would like to thank Dr. William F. Shughart III for his helpful comments and suggestions on all the papers in this special issue. In addition, I would like to thank the contributors for their thoughtful and well-developed articles as well as their participation in several rounds of reviews and conference presentations leading up to the publication of this special issue. Finally, I would like to thank the Mercatus Center at George Mason University for their support of several of the contributions in this special issue including this introduction.
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Thomas, D.W. Regressive effects of regulation. Public Choice 180, 1–10 (2019). https://doi.org/10.1007/s11127-018-00634-8
- Regressive effects