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Sensitivity to scope in estimating the social benefits of prolonging lives for regulatory decisions using national stated preference tradeoffs

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A Correction to this article was published on 14 July 2023

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Abstract

Regulatory decisions on environmental issues often entail comparing a proposed regulation’s benefits to its costs, usually presuming that the rule should be adopted only if benefits justify costs. Conventional benefits estimation usually defines benefits of a human-mortality-reducing regulation as the product of the number of lives expected to be prolonged and the “value of a statistical life,” usually estimated by averaging citizens’ responses when asked their willingness to pay for a specified small reduction in the probability of their own death. A novel approach to estimating life-prolonging benefits elicits stated preference tradeoffs between national benefits and national costs, a method more compatible with actual regulatory decisions (Finkel and Johnson Environ Law 48:453–476, 2018). All national-tradeoff studies to date presented subjects with only one magnitude, thus not testing within-person scope sensitivity. A U.S. experiment (n = 600) presented ascending or descending sequences of national regulatory benefits (a hypothetical regulation prolongs 10, 100, or 1000 lives) or national regulatory costs ($100 million, $1 billion, or $10 billion). The former yielded decreasing, the latter increasing, values per life when magnitudes increased, without within-frame order effects. Willingness to trade off benefits and costs generally rose or fell less than tenfold overall with a tenfold benefit/cost change, although strict proportionality and super-proportionality also occurred in various sub-groups. Averaged across frames, the implicit value per life prolonged increased with regulatory initiative size, contradicting the premise of invariant life value. Trimmed results mostly matched values of a statistical life used by U.S. federal regulatory agencies. This novel method could expand regulators’ benefit-valuing repertoire.

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Data availability

Data and instruments for all project studies, including the one reported here, are archived at Johnson, Branden, and Finkel, Adam. Estimating the Net Benefits of Environmental, Public Health and Safety Regulations. Ann Arbor, MI: Interuniversity Consortium for Political and Social Research [distributor], 2022-07-30. https://doi.org/10.3886/E175661V1

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Notes

  1. Johnson and Finkel (2022a) proposed adding the asterisk to make the acronym “SB1LP*,” indicating that there is as yet no adjustment for possible double-counting of altruism; when discussing Finkel and Johnson (2018) we use their unadorned term.

  2. A reviewer was concerned that our trim excluding tradeoff values yielding SB1LP* estimates exceeding $1 billion would preclude expression of altruism. However, the costs-first frame using a $1 billion stimulus would require a response involving a fraction of a life to generate implausibly high values, which none of our respondents offered in prior macro-risk studies. Our usual 100 lives-first frame requires a tolerable tradeoff involving > $100 billion in regulatory costs to generate implausibly high values, which happened rarely. Most implausible calculated SB1LP* values were on the low side (< $10,000), for which altruism is irrelevant. We therefore suspect that our few high-end implausible values reflected protests rather than extreme altruism.

  3. Economists also use this term, although there are exceptions. For example, Norinder et al. (2001) use the term “scale effects” for different risk reductions, and use “scope effects” to refer to different outcomes (e.g., slight versus severe injury).

  4. Applying proportionality to mortality probabilities, which need not evoke the same familiarity and emotional engagement as whole numbers in macro-risk research do, might be problematic, and yet economists do it anyway.

  5. The “stated VSL” term seems to refer to the calculated VSL, not to stated WTP.

  6. This text comes from the LF frame version when lives prolonged were 100; alternative content varied either the LF magnitude, or reflected the CF version (e.g., regulatory costs of $1 billion or other).

  7. The quotation marks reflect that 14 people did not actually reject the geometric mean, but rather their CF bounds included zero, which precluded calculation of a geometric mean, at which point they were asked for an exact number. We also note that only eight people (6.8% of the rejectors) rejected all three geometric means they faced, with most (n = 98, 83.8%) rejecting just one geometric mean. Using a descending order, which meant starting with the large numbers (1000 lives or $10 billion in costs), prompted more rejections than did the subsequent smaller numbers (12 versus 9 for lives; 31 versus 27 for costs), suggesting that people might have needed to get more familiar with the task. However, this pattern was less clear for ascending orders, starting with the smallest number (11, 7 and 12 rejections for lives; 15, 13 and 7 for costs); some rejections were clearly protest bids (e.g., when some exact values provided were in the double digits or less); and we cannot rule out other explanations, such as cognitive overload.

  8. A reviewer asked how rejectors might differ from others. We present this information cautiously, given the small numbers involved, diverse potential reasons for rejection, and the few variables on which we could compare these groups given the need to include three tradeoffs in the surveys (versus earlier macro-risk studies, which had just one or two). We used independent-sample t tests to compare groups on attention check scores, gender, age, and education. Rejectors overall did not differ significantly from non-rejectors on these variables; rejectors who then offered exact numbers had better attention (p < .001) and education (one-sided p = .005) than rejectors who did not.

  9. Open-ended comments by sample members about taxes or national debt conflict with regulatory costs as usually defined (e.g., price increases borne by all in society), but in prior research (Johnson & Finkel 2016) Americans found it much easier to define “regulatory costs” as government budgets or government-funded projects (e.g., wasteful, cost over-runs, completed late or never).

  10. Another affect-based solution (Slovic & Västfjäll 2019) makes lives at risk more concrete using perspective clauses (see macro-risk contextual information; Johnson & Finkel 2022a): e.g., prolong one life every “5 weeks” (10 lives annually), “4 days” (100 lives), and “8 h” (1000 lives).

References

  • Alberini A (2004) Willingness to pay for mortality risk reductions: the robustness of VSL estimates from contingent valuation studies (final report, cooperative agreement 015-29528). US Environmental Protection Agency, Washington, DC

    Google Scholar 

  • Alolayan MA (2012) PM2.5 in Kuwait: sources valuation of mortality and benefits of control. Harvard School of Public Health, Boston, p 247

    Google Scholar 

  • Andersson H (2006) Willingness to pay for road safety and estimates of the risk of death: evidence from a Swedish contingent valuation study. Accid Anal Prev 39:853–865

    Google Scholar 

  • Arana JE, Leon CJ (2002) Willingness to pay for health risk reduction in the context of altruism. Health Econ 11(7):623–635

    Google Scholar 

  • Bell DE, Raiffa H, Tversky A (eds) (1988) Decision making: descriptive, normative, and prescriptive interactions. Cambridge University Press, New York

    Google Scholar 

  • Bergstrom TC (2006) Benefit-cost in a benevolent society. Am Econ Rev 96(1):339–351

    Google Scholar 

  • Berinsky AJ, Margolis MF, Sances MW (2014) Separating the shirkers from the workers? Making sure respondents pay attention on self-administered surveys. Am J Polit Sci 58:739–753

    Google Scholar 

  • Bhattacharya S, Alberini A, Cropper ML (2007) The value of mortality risk reductions in Delhi, India. J Risk Uncertain 34:21–47

    Google Scholar 

  • Biddlestone M, Roozenbeek J, van der Linden S (2022) Once (but not twice) upon a time: narrative inoculation against conjunction errors indirectly reduces conspiracy beliefs and improves truth discernment. Appl Cognit Psychol Early Online Publ. https://doi.org/10.1002/acp.4025

    Article  Google Scholar 

  • Bosworth R, Cameron TA, DeShazo JR (2010) Is an ounce of prevention worth a pound of cure? Comparing demand for public prevention and treatment policies. Med Decis Making 30(4):E40–E56

    Google Scholar 

  • Carson RT, Mitchell RC (2006) Public preferences toward environmental risks: the case of trihalomethanes. In: Alberini A, Bjornstad D, Kahn J (eds) Handbook of contingent valuation. Brookfield, Vermont

    Google Scholar 

  • Caviola L, Faulmüller N, Everett JAC, Savulescu J, Kahane G (2014) The evaluability bias in charitable giving: saving administration costs or saving lives? Judgm Decis Mak 9:303–315

    Google Scholar 

  • Corso PS, Hammitt JK, Graham JD (2001) Valuing mortality-risk reduction: using visual aids to improve the validity of contingent valuation. J Risk Uncertain 23(2):165–184

    Google Scholar 

  • Cranor CF, Finkel AM (2018) Toward the usable recognition of individual benefits and costs in regulatory analysis and governance. Regul Gov 12:131–149

    Google Scholar 

  • Cropper M, Hammitt JK, Robinson LA (2011) Valuing mortality risk reductions: progress and challenges. Annu Rev Health Econ 3:313–336

    Google Scholar 

  • de Blaeij A, Florax RJGM, Rietveld P, Verhoef E (2003) The value of a statistical life in road safety: a meta-analysis. Accid Anal Prev 35(6):973–986

    Google Scholar 

  • Dickert S, Västfjäll D, Kleber J, Slovic P (2012) Valuations of human lives: normative expectations and psychological mechanisms of (ir)rationality. Synthese 189:95–105

    Google Scholar 

  • Dickert S, Västfjäll D, Kleber J, Slovic P (2015) Scope insensitivity: the limits of intuitive valuation of human lives in public policy. J Appl Res Mem Cogn 4(3):248–255

    Google Scholar 

  • Dubourg WR, Jones-Lee MW, Loomes G (1997) Imprecise preferences and survey design in contingent valuation. Economica 64:681–702

    Google Scholar 

  • Ellig J, McLaughlin PA, Morrall JF III (2013) Continuity, change, and priorities: the quality and use of regulatory analysis across US administrations. Regul Gov 7(2):153–173

    Google Scholar 

  • Executive Order No. 12866, 58 Federal Register 190 (October 4, 1993)

  • Fechner GT (1860) Elemente der psychophysik. Breithof and Harterl, Leipzig

    Google Scholar 

  • Fennema H, van Assen M (1998) Measuring the utility of losses by means of the tradeoff method. J Risk Uncertain 17:277–295

    Google Scholar 

  • Fetherstonhaugh D, Slovic P, Johnson SM, Friedrich J (1997) Insensitivity to the value of human life: a study of psychophysical numbing. J Risk Uncertain 14:283–300

    Google Scholar 

  • Finkel AM, Johnson BB (2018) The limits of self-interest: results from a novel stated-preference survey to estimate the social benefits of life-prolonging regulations. Environ Law 48:453–476

    Google Scholar 

  • Frankfurt HG (2015) On inequality. Princeton University Press, Princeton, NJ

    Google Scholar 

  • Friedrich J, Barnes P, Chapin K, Dawson I, Garst V, Kerr D (1999) Psychophysical numbing: when lives are valued less as the lives at risk increase. J Consum Psychol 8:277–299

    Google Scholar 

  • Galanter E (1962) The direct measurement of utility and subjective probability. Am J Psychol 75:208–220

    CAS  Google Scholar 

  • Gregory R, Failing L, Harstone M, Long G, McDaniels T, Ohlson D (2012) Structured decision making: a practical guide to environmental management choices. Wiley-Blackwell, New York

    Google Scholar 

  • Gregory R, Harstone M, Slovic P (2018) Improving intervention decisions to prevent genocide: less muddle, more structure. Genocide Stud Prev 11(3):109–127

    Google Scholar 

  • Hammitt JK (2000) Valuing mortality risk: theory and practice. Environ Sci Technol 34:1396–1400

    CAS  Google Scholar 

  • Hammitt JK, Graham JD (1999) Willingness to pay for health protection: inadequate sensitivity to probability?”. J Risk Uncertain 18(1):33–62

    Google Scholar 

  • Hammitt JK, Treich N (2007) Statistical vs. identified lives in benefit-cost analysis. J Risk Uncertain 35:45–66

    Google Scholar 

  • Hershey JC, Kunreuther HC, Schoemaker PJH (1982) Sources of bias in assessment procedures for utility functions. Manag Sci 28(8):936–954

    Google Scholar 

  • Hsee CK, Zhang J, Lu ZY, Xu F (2013) Unit asking: a method to boost donations and beyond. Psychol Sci 24:1801–1808. https://doi.org/10.1177/0956797613482947

    Article  Google Scholar 

  • Jacquemet N, Joule R-V, Luchini S, Shogren JF (2013) Preference elicitation under oath. J Environ Econ Manag 65:110–132

    Google Scholar 

  • Jakobsson KM, Dragun AK (1996) Contingent valuation and endangered species: methodological issues and applications. Edward Elgar, Cheltenham

    Google Scholar 

  • Johnson BB, Finkel AM (2016) Public perceptions of regulatory costs, their uncertainty and interindividual distribution. Risk Anal 36:1148–1170

    Google Scholar 

  • Johnson BB, Finkel AM (2022a) Information effects on lay tradeoffs between national regulatory costs and benefits. Risk Anal Early Online Publ. https://doi.org/10.1111/risa.13886

    Article  Google Scholar 

  • Johnson BB, Finkel AM (2022b) Stated-preference tradeoffs between regulatory costs and benefits: testing unit asking and double framing effects. J Risk Res Early Online Publ. https://doi.org/10.1080/13669877.2022.2127848

    Article  Google Scholar 

  • Johnston RJ, Boyle KJ, Adamowicz W, Bennett J, Brouwer R, Cameron TA, Hanemann WM, Hanley N, Ryan M, Scarpa R, Tourangeau R, Vossler CA (2017) Contemporary guidance for stated preference studies. J Assoc Environ Resour Econ 4(2):319–405

    Google Scholar 

  • Jones-Lee MW (1992) Paternalistic altruism and the value of statistical life. Econ J 102(410):80–90

    Google Scholar 

  • Jones-Lee MW, Hammerton M, Philips PR (1985) The value of safety: results of a national sample survey. Econ J 95:49–72

    Google Scholar 

  • Kahneman D, Knetsch JL (1992) Valuing public goods: The purchase of moral satisfaction. J Environ Econ Manage 22(1):57–70

    Google Scholar 

  • Karlsson H, Hellström S, Moche H, Västfjäll D (2020) Unit asking—a method for increasing donations: a replication and extension. Judgm Decis Mak 15(6):989–993

    Google Scholar 

  • Krupnick A (2007) Mortality-risk valuation and age: stated preference evidence. Rev Environ Econ Policy 1(2):261–282

    Google Scholar 

  • Laziċ A, Žeželj I (2021) A systematic review of narrative interventions: lessons for countering anti-vaccination conspiracy theories and misinformation. Public Underst Sci 30(6):644–670

    Google Scholar 

  • Lindhjem H, Navrud S, Braathen NA, Biausque V (2011) Valuing mortality risk reductions from environmental, transport, and health policies: a global meta-analysis of stated preference studies. Risk Anal 31(9):1381–1407

    Google Scholar 

  • Norinder A, Hjalte K, Persson U (2001) Scope and scale insensitivities in a contingent valuation study of risk reductions. Health Policy 57:141–153

    CAS  Google Scholar 

  • Public Law 104–121 [aka “Congressional review act”], title II, §251, March 29, 1996, 110 Statutes 868

  • Raile ED, Shanahan EA, Ready RC, McEvoy J, Izurieta C, Reinhold AM, Poole GC, Bergmann NT, King H (2022) Narrative risk communication as a lingua franca for environmental hazard preparation. Environ Commun 16(1):108–124

    Google Scholar 

  • Robinson LA, Hammitt JK, Zeckhauser R (2014) The role of distribution in regulatory analysis and decision making. Retrieved from http://www.hks.harvard.edu/var/ezp_site/storage/fckeditor/file/RPP_2014_03.pdf

  • Rubaltelli, E., Hysenbelli, D., Dickert, S., Mayorga, M., & Slovic, P. (2021). Sensitivity to perceived costs and benefits in donation decisions. Organizational Behavior and Human Decision Processes, in press

  • Shapiro S, Morrall JF III (2012) The triumph of regulatory politics: benefit-cost analysis and political salience. Regul Gov 6(2):189–206

    Google Scholar 

  • Slovic P (1975) Choice between equally valued alternatives. J Exp Psychol Hum Percept Perform 1(3):280–287

    Google Scholar 

  • Slovic P (2007) “If I look at the mass, I will never act”: psychic numbing and genocide. Judgm Decis Mak 2:79–95

    Google Scholar 

  • Slovic P (2015) When (in)action speaks louder than words: confronting the collapse of humanitarian values in foreign policy decisions. Ill Law Rev Slip Opin 2015(1):24–31

    Google Scholar 

  • Slovic P, Västfjäll D (2019) The arithmetic of compassion and the future of risk management. In: Kunreuther H, Meyer RJ, Michel-Kerjan EO (eds) the future of risk management. University of Pennsylvania Press, Philadelphia, pp 13–29

    Google Scholar 

  • Slovic P, Finucane M, Peters E, MacGregor DG (2002) The affect heuristic. In: Gilovich T, Griffin D, Kahneman D (eds) Heuristics and biases: the psychology of intuitive judgment. Cambridge University Press, New York, pp 397–420

    Google Scholar 

  • Slovic P, Zionts D, Woods AK, Goodman R, Jinks D (2013) Psychic numbing and mass atrocity. In: Shafir E (ed) The behavioral foundations of public policy. Princeton University Press, Princeton, pp 126–142

    Google Scholar 

  • Small DA, Loewenstein G, Slovic P (2007) Sympathy and callousness: the impact of deliberative thought on donations to identifiable and statistical victims. Organ Behav Hum Decis Process 102:143–153

    Google Scholar 

  • Stevens SS (1975) Psychophysics. John Wiley, New York

    Google Scholar 

  • Tversky A, Sattath S, Slovic P (1988) Contingent weighting in judgment and choice. Psychol Rev 95(3):371–384

    Google Scholar 

  • U.S. Environmental Protection Agency (2010) Valuing mortality risk reductions for environmental policy: a white paper. USEPA, National Center for Environmental Economics, Washington, DC

    Google Scholar 

  • Västfjäll D, Slovic P (2013) Cognition and emotion in judgment and decision making. In: Robinson MD, Watkins ER, Harmon-Jones E (eds) Handbook of cognition and emotion. Guilford Press, New York, pp 252–271

    Google Scholar 

  • Västfjäll D, Slovic P, Mayorga M, Peters E (2014) Compassion fade: affect and charity are greatest for a single child in need. PLoS ONE 9(6):e100115

    Google Scholar 

  • Västfjäll D, Slovic P, Mayorga M (2015) Pseudoinefficacy and the arithmetic of compassion. In: Slovic S, Slovic P (eds) Numbers and nerves: information, emotion, and meaning in a world of data. Oregon State University Press, Corvallis, pp 42–52

    Google Scholar 

  • Weber EH (1834) De pulsu, resorptione, auditu et tactu. Koehler, Leipzig

    Google Scholar 

  • Weinstein MC, Shepard DS, Pliskin JS (1980) The economic value of changing mortality probabilities: a decision-theoretic approach. Quart J Econ 94:373–396

    Google Scholar 

  • Woods ND (2018) Regulatory analysis procedures and political influence on bureaucratic policymaking. Regul Gov 12(2):299–313

    Google Scholar 

Download references

Funding

Funding for this work was provided by the U.S. National Science Foundation under Grant # 1629287. Marcus Mayorga programmed and oversaw online data collection.

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Authors and Affiliations

  1. Decision Research, P.O. Box 72538, Springfield, OR, 97475, USA

    Branden B. Johnson

  2. School of Public Health, University of Michigan, Ann Arbor, MI, USA

    Adam M. Finkel

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  1. Branden B. Johnson
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  2. Adam M. Finkel
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Authors shared idea generation and experimental design. BBJ did statistical analyses and wrote the first draft. Authors collaborated on all revisions.

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Correspondence to Branden B. Johnson.

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Johnson, B.B., Finkel, A.M. Sensitivity to scope in estimating the social benefits of prolonging lives for regulatory decisions using national stated preference tradeoffs. Environ Syst Decis 43, 509–528 (2023). https://doi.org/10.1007/s10669-023-09899-x

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