IDEAS home Printed from https://ideas.repec.org/a/spr/envsyd/v38y2018i2d10.1007_s10669-018-9681-x.html
   My bibliography  Save this article

Taking the reins: how regulatory decision-makers can stop being hijacked by uncertainty

Author

Listed:
  • Adam M. Finkel

    (University of Pennsylvania
    University of Michigan School of Public Health)

  • George Gray

    (George Washington University)

Abstract

Several decades after the mechanics of quantitative uncertainty analysis (QUA) for risk assessment and regulatory cost analysis were developed and refined, QUA still rarely reaches the minds of decision-makers. The most common justification for this situation is that “decision-makers want a number, not a set of statistical distributions.” This may be an accurate assessment of their druthers, but one obvious though perhaps impractical retort is to say that if decision-makers insist on misleading point estimates, then we need new and better decision-makers. This article offers a way out of this dilemma. Decision-makers do not have to understand (or even receive) all the information contained in a complete QUA, but they do have to drive the QUA. They need to instruct analysts how to approach the phenomena they analyze (parameter uncertainty, model uncertainty, interindividual variability, offsetting and second-order effects, and the monetary value of future uncertainty reductions), they need to insist that uncertainties in cost be treated a priori as exactly as important as uncertainties in risk, and—even more importantly—they need to instruct analysts which estimator(s) to seek, report, and explain. Here we offer 10 detailed principles to guide decision-makers into a new relationship with risk and cost analysts—10 observations about how “eyes wide open” point estimates can vastly outperform point estimates handed to the decision-maker without context, justification, or honesty about the value judgments they impose upon the decision. A decision-maker who explains “I chose Option A because its benefits of 2.345 exceed its costs of 1.234” can be replaced by a dollar-store calculator. We need decision-makers who can say “I chose Option A because the spectrum of benefits it likely offers, to these citizens, considering the range of costs it likely imposes, makes it a superior choice to any other.” QUA, performed carefully and following clear policy instructions, can empower decision-makers to earn their influential roles.

Suggested Citation

  • Adam M. Finkel & George Gray, 2018. "Taking the reins: how regulatory decision-makers can stop being hijacked by uncertainty," Environment Systems and Decisions, Springer, vol. 38(2), pages 230-238, June.
  • Handle: RePEc:spr:envsyd:v:38:y:2018:i:2:d:10.1007_s10669-018-9681-x
    DOI: 10.1007/s10669-018-9681-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10669-018-9681-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10669-018-9681-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Winston Harrington & Richard D. Morgenstern & Peter Nelson, 2000. "On the accuracy of regulatory cost estimates," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 19(2), pages 297-322.
    2. Lisa A. Robinson & James K. Hammitt & Richard J. Zeckhauser, 2016. "Attention to Distribution in U.S. Regulatory Analyses," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 10(2), pages 308-328.
    3. Sunstein,Cass R., 2002. "Risk and Reason," Cambridge Books, Cambridge University Press, number 9780521791991, July.
    4. Adam M. Finkel, 1990. "A Simple Formula for Calculating the “Mass Density” of a Lognormally Distributed Characteristic: Applications to Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 10(2), pages 291-301, June.
    5. James K. Hammitt & Alexander I. Shlyakhter, 1999. "The Expected Value of Information and the Probability of Surprise," Risk Analysis, John Wiley & Sons, vol. 19(1), pages 135-152, February.
    6. Elizabeth L. Anderson & Dale Hattis, 1999. "A. Uncertainty and Variability," Risk Analysis, John Wiley & Sons, vol. 19(1), pages 47-49, February.
    7. Dale Hattis & Elizabeth L. Anderson, 1999. "What Should Be the Implications of Uncertainty, Variability, and Inherent “Biases”/“Conservatism” for Risk Management Decision‐Making?," Risk Analysis, John Wiley & Sons, vol. 19(1), pages 95-107, February.
    8. Fumie Yokota & Kimberly M. Thompson, 2004. "Value of Information Analysis in Environmental Health Risk Management Decisions: Past, Present, and Future," Risk Analysis, John Wiley & Sons, vol. 24(3), pages 635-650, June.
    9. Mark A. Burgman & David A. Keith & Terry V. Walshe, 1999. "Uncertainty in Comparative Risk Analysis for Threatened Australian Plant Species," Risk Analysis, John Wiley & Sons, vol. 19(4), pages 585-598, August.
    10. Alexander I. Shlyakhter, 1994. "An Improved Framework for Uncertainty Analysis: Accounting for Unsuspected Errors," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 441-447, August.
    11. Paul R. Portney & George M. Gray & John D. Graham, 1991. "Risk assessment and clean air policy," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 10(2), pages 286-295.
    12. Cynthia H. Stahl & Alan J. Cimorelli, 2005. "How Much Uncertainty is Too Much and How Do We Know? A Case Example of the Assessment of Ozone Monitor Network Options," Risk Analysis, John Wiley & Sons, vol. 25(5), pages 1109-1120, October.
    13. Adam M. Finkel, 1991. "Edifying presentation of risk estimates: Not as easy as it seems," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 10(2), pages 296-303.
    14. Martin L. Weitzman, 2011. "Fat-Tailed Uncertainty in the Economics of Catastrophic Climate Change," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 5(2), pages 275-292, Summer.
    15. Louis Anthony (Tony) Cox, 2012. "Confronting Deep Uncertainties in Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 32(10), pages 1607-1629, October.
    16. Kenneth T. Bogen, 1995. "Methods to Approximate Joint Uncertainty and Variability in Risk," Risk Analysis, John Wiley & Sons, vol. 15(3), pages 411-419, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Adam M. Finkel & Benjamin D. Trump & Diana Bowman & Andrew Maynard, 2018. "A “solution-focused” comparative risk assessment of conventional and synthetic biology approaches to control mosquitoes carrying the dengue fever virus," Environment Systems and Decisions, Springer, vol. 38(2), pages 177-197, June.
    2. Alan Kennedy & Jonathon Brame & Taylor Rycroft & Matthew Wood & Valerie Zemba & Charles Weiss & Matthew Hull & Cary Hill & Charles Geraci & Igor Linkov, 2019. "A Definition and Categorization System for Advanced Materials: The Foundation for Risk‐Informed Environmental Health and Safety Testing," Risk Analysis, John Wiley & Sons, vol. 39(8), pages 1783-1795, August.
    3. Fabian Pütz & Finbarr Murphy & Martin Mullins, 2019. "Driving to a future without accidents? Connected automated vehicles’ impact on accident frequency and motor insurance risk," Environment Systems and Decisions, Springer, vol. 39(4), pages 383-395, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carl F. Cranor & Adam M. Finkel, 2018. "Toward the usable recognition of individual benefits and costs in regulatory analysis and governance," Regulation & Governance, John Wiley & Sons, vol. 12(1), pages 131-149, March.
    2. Stavins, Robert & Hahn, Robert & Cavanagh, Sheila, 2001. "National Environmental Policy During the Clinton Years," RFF Working Paper Series dp-01-38, Resources for the Future.
    3. Michael R. Greenberg & Karen Lowrie, 2016. "Elizabeth Anderson: Cancer Risk Assessment Pioneer," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 646-649, April.
    4. Mitchell J. Small, 2008. "Methods for Assessing Uncertainty in Fundamental Assumptions and Associated Models for Cancer Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 28(5), pages 1289-1308, October.
    5. Susanna Gallani & Takehisa Kajiwara & Ranjani Krishnan, 2020. "Value of new performance information in healthcare: evidence from Japan," International Journal of Health Economics and Management, Springer, vol. 20(4), pages 319-357, December.
    6. Ken Silver & Richard Clapp, 2006. "Environmental Surveillance at Los Alamos: An Independent Reassessment of Historical Data," Risk Analysis, John Wiley & Sons, vol. 26(4), pages 893-906, August.
    7. Robert W. Hahn & Katrina Kosec & Peter J. Neumann & Scott Wallsten, 2006. "What Affects the Quality of Economic Analysis for Life‐Saving Investments?," Risk Analysis, John Wiley & Sons, vol. 26(3), pages 641-655, June.
    8. Ramya Chari & Thomas A. Burke & Ronald H. White & Mary A. Fox, 2012. "Integrating Susceptibility into Environmental Policy: An Analysis of the National Ambient Air Quality Standard for Lead," IJERPH, MDPI, vol. 9(4), pages 1-20, March.
    9. Vicki Bier, 2020. "The Role of Decision Analysis in Risk Analysis: A Retrospective," Risk Analysis, John Wiley & Sons, vol. 40(S1), pages 2207-2217, November.
    10. S. N. Rai & D. Krewski, 1998. "Uncertainty and Variability Analysis in Multiplicative Risk Models," Risk Analysis, John Wiley & Sons, vol. 18(1), pages 37-45, February.
    11. Zou, Guang & Faber, Michael Havbro & González, Arturo & Banisoleiman, Kian, 2021. "Computing the value of information from periodic testing in holistic decision making under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    12. Robert T. Clemen & Robert L. Winkler, 1999. "Combining Probability Distributions From Experts in Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 19(2), pages 187-203, April.
    13. Amanda P. Rehr & Mitchell J. Small & Paul S. Fischbeck & Patricia Bradley & William S. Fisher, 2014. "The role of scientific studies in building consensus in environmental decision making: a coral reef example," Environment Systems and Decisions, Springer, vol. 34(1), pages 60-87, March.
    14. Burtraw, Dallas & Woerman, Matt & Paul, Anthony, 2012. "Retail electricity price savings from compliance flexibility in GHG standards for stationary sources," Energy Policy, Elsevier, vol. 42(C), pages 67-77.
    15. Simon Levin & Anastasios Xepapadeas, 2021. "On the Coevolution of Economic and Ecological Systems," Annual Review of Resource Economics, Annual Reviews, vol. 13(1), pages 355-377, October.
    16. Managi, Shunsuke & Opaluch, James J. & Jin, Di & Grigalunas, Thomas A., 2006. "Stochastic frontier analysis of total factor productivity in the offshore oil and gas industry," Ecological Economics, Elsevier, vol. 60(1), pages 204-215, November.
    17. J. Park & T. P. Seager & P. S. C. Rao & M. Convertino & I. Linkov, 2013. "Integrating Risk and Resilience Approaches to Catastrophe Management in Engineering Systems," Risk Analysis, John Wiley & Sons, vol. 33(3), pages 356-367, March.
    18. Johannes Urpelainen, 2011. "Frontrunners and Laggards: The Strategy of Environmental Regulation under Uncertainty," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 50(3), pages 325-346, November.
    19. Nicky Welton & A. E. Ades, 2012. "Research Decisions In The Face Of Heterogeneity: What Can A New Study Tell Us?," Health Economics, John Wiley & Sons, Ltd., vol. 21(10), pages 1196-1200, October.
    20. Annika Styczynski & Jedamiah Wolf & Somdatta Tah & Arnab Bose, 2014. "When decision-making processes fail: an argument for robust climate adaptation planning in the face of uncertainty," Environment Systems and Decisions, Springer, vol. 34(4), pages 478-491, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:envsyd:v:38:y:2018:i:2:d:10.1007_s10669-018-9681-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.