Show simple item record

Information effects on lay tradeoffs between national regulatory costs and benefits

dc.contributor.authorJohnson, Branden B.
dc.contributor.authorFinkel, Adam M.
dc.date.accessioned2023-02-01T18:57:28Z
dc.date.available2024-01-01 13:57:26en
dc.date.available2023-02-01T18:57:28Z
dc.date.issued2022-12
dc.identifier.citationJohnson, Branden B.; Finkel, Adam M. (2022). "Information effects on lay tradeoffs between national regulatory costs and benefits." Risk Analysis 42(12): 2620-2638.
dc.identifier.issn0272-4332
dc.identifier.issn1539-6924
dc.identifier.urihttps://hdl.handle.net/2027.42/175748
dc.description.abstractA novel stated-preference “macro-risk” approach introduced to estimate the life-prolonging benefits of proposed environmental, health, and safety regulations may answer questions unasked or wrongly answered by conventional revealed-preference (e.g., “wage premiums” for high occupational risks) and stated-preference methods (e.g., willingness to pay for tiny reductions in one’s own premature death risk). This new approach asks laypeople to appraise directly their preferred tradeoffs between national regulatory costs and lives prolonged nationwide (regulatory benefits). However, this method may suffer from incomplete lay understanding of national-scale consequences (e.g., billions of dollars in regulatory costs; hundreds of lives prolonged) or tradeoffs (e.g., what are lives prolonged worth?). Here we (1) tested effects of numerical contextual examples to ground each hypothetical regulatory tradeoff, and (2) explored why some people implicitly offer “implausible” values (< $10,000 or > $1 billion) for the social benefit of prolonging one life. In Study 1 (n = 356), after testing their separate effects, we combined three contextual-information aids: (1) comparing hypothetical regulatory costs and benefits to real-life higher and lower values; (2) reframing large numbers into smaller, more familiar terms; and (3) framing regulatory costs as having diffuse versus concentrated impacts. Information increased social benefits values on average (from $4.5 million to $13.8 million). Study 2 (n = 402) found that the most common explanations for “implausible” values included inattention, strong attitudes about regulation, and problems translating values into responses. We discuss implications for this novel stated-preferences method, and for comparing it to micro-risk methods.
dc.publisherHarvard School of Public Health
dc.publisherWiley Periodicals, Inc.
dc.subject.othercalibration
dc.subject.othervaluation
dc.subject.otherstated preferences
dc.subject.othernational tradeoffs
dc.subject.othercost-benefit analysis
dc.titleInformation effects on lay tradeoffs between national regulatory costs and benefits
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBusiness (General)
dc.subject.hlbtoplevelBusiness and Economics
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/175748/1/risa13886.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/175748/2/risa13886_am.pdf
dc.identifier.doi10.1111/risa.13886
dc.identifier.sourceRisk Analysis
dc.identifier.citedreferencePearce, D., & Özdemiroglu, E. ( 2002 ). Economic valuation with stated preference techniques: Summary guide. Department for Transport, Local Government and the Regions.
dc.identifier.citedreferenceCohen, J. ( 1992 ). A power primer. Psychological Bulletin, 112, 155 – 159.
dc.identifier.citedreferenceCropper, M., Hammitt, J. K., & Robinson, L. A. ( 2011 ). Valuing mortality risk reductions: Progress and challenges. Annual Review of Health Economics, 3, 313 – 336.
dc.identifier.citedreferenceDickert, S., Västfjäll, D., Kleber, J., & Slovic, P. ( 2012 ). Valuations of human lives: Normative expectations and psychological mechanisms of (ir)rationality. Synthese, 189, 95 – 105.
dc.identifier.citedreferenceFagerlin, A., Zikmund-Fisher, B. J., Ubel, P. A., Jankovic, A., Derry, H. A., & Smith, D. M. ( 2007 ). Measuring numeracy without a math test: Development of the subjective numeracy scale. Medical Decision Making, 27, 672 – 680.
dc.identifier.citedreferenceFerguson, C. J. ( 2009 ). An effect size primer: A guide for clinicians and researchers. Professional Psychology: Research and Practice, 40 ( 5 ), 532 – 538.
dc.identifier.citedreferenceFinkel, A. M., & Johnson, B. B. ( 2018 ). The limits of self-interest: Results from a novel stated-preference survey to estimate the social benefits of life-prolonging regulations. Environmental Law, 48, 453 – 476.
dc.identifier.citedreferenceGlickman, M. E., Rao, S. R., & Schultz, M. R. ( 2014 ). False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies. Journal of Clinical Epidemiology, 67, 850 – 857.
dc.identifier.citedreferenceHammitt, J. K., & Treich, N. ( 2007 ). Statistical vs. identified lives in benefit-cost analysis. Journal of Risk and Uncertainty, 35, 45 – 66.
dc.identifier.citedreferenceJacquemet, N., Joule, R.-V., Luchini, S., & Shogren, J. F. ( 2013 ). Preference elicitation under oath. Journal of Environmental Economics and Management, 65, 110 – 132.
dc.identifier.citedreferenceJohansson, P.-O. ( 1992 ). Altruism in cost-benefit analysis. Environmental and Resource Economics, 2, 605 – 613.
dc.identifier.citedreferenceJohnson, B. B., & Finkel, A. M. ( 2016 ). Public perceptions of regulatory costs, their uncertainty and interindividual distribution. Risk Analysis, 36, 1148 – 1170.
dc.identifier.citedreferenceJones-Lee, M. W., Hammerton, M., & Philips, P. R. ( 1985 ). The value of safety: Results of a national sample survey. The Economic Journal, 95, 49 – 72.
dc.identifier.citedreferenceKnoblauch, T. A. K., Stauffacher, M., & Trutnevyte, E. ( 2017 ). Communicating low-probability high-consequence risk, uncertainty and expert confidence: Induced seismicity of deep geothermal energy and shale gas. Risk Analysis, 38 ( 4 ), 694 – 709.
dc.identifier.citedreferenceKoford, B. C. ( 2010 ). Public budget choices and private willingness to pay. Public Budgeting and Finance, 30, 47 – 68.
dc.identifier.citedreferenceManiaci, M. R., & Rogge, R. D. ( 2014 ). Caring about carelessness: Participant inattention and its effects on research. Journal of Research in Personality, 48, 61 – 83.
dc.identifier.citedreferencePew Research Center. ( 2017 ). Public trust in government remains near historic lows as partisan attitudes shift. Pew Research Center for People & the Press.
dc.identifier.citedreferencePew Research Center. ( 2018 ). Democrats, Republicans give their parties so-so ratings for standing up for “traditional” positions. Pew Research Center for People & the Press.
dc.identifier.citedreferenceRobinson, L. A., Sullivan, R., & Shogren, J. F. ( 2021 ). Do the benefits of COVID-19 policies exceed the costs? Exploring uncertainties in the age-VSL relationship. Risk Analysis, 41 ( 5 ), 761 – 770.
dc.identifier.citedreferenceU.S. Environmental Protection Agency. ( 2016 ). Valuing mortality risk reductions for policy: A meta-analytic approach. Prepared by the U.S. Environmental Protection Agency’s Office of Policy, National Center for Environmental Economics, for review by the EPA’s Science Advisory Board, Environmental Economics Advisory Committee. https://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86e/0CA9E925C9A702F285257F380050C842/$File/VSL+white+paper_final_020516.pdf
dc.identifier.citedreferenceViscusi, W. K. ( 2020 ). Pricing the global health risks of the COVID-19 pandemic. Vanderbilt Law Research Paper No. 20–42. Journal of Risk and Uncertainty, 61, 101–128 https://ssrn.com/abstract=3670841
dc.identifier.citedreferenceVisschers, V. H. M., Meertens, R. M., Passchier, W. W. F., & De Vries, N. N. K. ( 2009 ). Probability information in risk communication: A review of the research literature. Risk Analysis, 29 ( 2 ), 267 – 287.
dc.identifier.citedreferenceWeinstein, N. D., Sandman, P. M., & Hallman, W. K. ( 1994 ). Testing a visual display to explain small probabilities. Risk Analysis, 14 ( 6 ), 895 – 896.
dc.identifier.citedreferenceAlberini, A. ( 2019 ). Revealed versus stated preferences: What have we learned about valuation and behavior? Review of Environmental Economics and Policy, 13 ( 2 ), 283 – 298.
dc.identifier.citedreferenceAlolayan, M. A. ( 2012 ). (2012). PM2.5 in Kuwait: Sources, valuation of mortality and benefits of control. Sc.D. Dissertation, Harvard School of Public Health, p. 247 pp.
dc.identifier.citedreferenceAndersson, H. ( 2006 ). Willingness to pay for road safety and estimates of the risk of death: Evidence from a Swedish contingent valuation study. Accident Analysis and Prevention, 39, 853 – 865.
dc.identifier.citedreferenceBaik, S., Davis, A. L., & Morgan, M. G. ( 2019 ). Illustration of a method to incorporate preference uncertainty in benefit-cost analysis. Risk Analysis, 39, 2359 – 2368.
dc.identifier.citedreferenceBarrio, P. J., Goldstein, D. G., & Hofman, J. M. ( 2015 ). Improving comprehension of numbers in the news. ACM Conference on Human Factors in Computing Systems (CHI ’16). http://cj2015.brown.columbia.edu/papers.html
dc.identifier.citedreferenceBergstrom, J. C., Boyle, K. J., & Yabe, M. ( 2004 ). Trading taxes vs. paying taxes to value and finance public environmental goods. Environmental and Resource Economics, 28, 533 – 549.
dc.identifier.citedreferenceBerinsky, A. J., Margolis, M. F., & Sances, M. W. ( 2014 ). Separating the shirkers from the workers? Making sure respondents pay attention on self-administered surveys. American Journal of Political Science, 58, 739 – 753.
dc.identifier.citedreferenceBraathen, N. A., Lindhjem, H., & Navrud, S. ( 2011 ). Valuing mortality risk reductions from environmental, transport, and health policies: A global meta-analysis of stated preference studies. Risk Analysis, 31 ( 9 ), 1381 – 1407.
dc.identifier.citedreferenceCarson, R. T., & Mitchell, R. C. ( 2000 ). Public preferences toward environmental risks: The case of trihalomethanes. In A. Alberini, D. Bjornstad, J., Kahn (Eds.), Handbook of contingent valuation. Edward Elgar.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.