Abstract
Highly influential recent work by Benartzi et al. (2017) argues—using comparisons of effectiveness and costs—that behavioral interventions (or nudges) offer more cost-effective means than traditional regulatory instruments for changing individual behavior to achieve desirable policy goals. Based on this finding, these authors further conclude that governments and other organizations should increase their investments in nudging to supplement traditional interventions. Yet a closer look at Benartzi et al.’s (2017) own data and analysis reveals that they variously exclude and include key cost elements to the benefit of behavioral instruments over traditional ones and overstate the utility of cost-effectiveness analysis for policy selection. Once these methodological shortcomings are corrected, a reassessment of key policies evaluated by the authors reveals that nudges do not consistently outperform traditional interventions, neither under cost-effectiveness analysis nor under the methodologically required cost-benefit analysis. These illustrative findings demonstrate that governments concerned with social welfare cannot simply assume the superiority of behavioral instruments and should strive instead to conduct cost-benefit analyses of competing interventions, including nudges, to identify the most efficient of the available instruments.
Funding source: Notre Dame Law School
Funding source: Israel Institute for Advanced Studies
Acknowledgments
This project benefited from the generous support of Notre Dame Law School and the Israel Institute for Advanced Studies to the first author and the insightful comments of participants at the Hebrew University of Jerusalem Law and Economics Workshop, the 2022 ND LAMB-Tel Aviv University Faculty of Law conference on Empirical, Behavioral, and Experimental Analyses of Law, and the 32nd Annual Meeting of the American Law and Economics Association. Isabella Wilcox and Margarete Tompkins provided excellent research assistance.
References
Adler, M.D. and Posner, E.A. (2001). Cost-benefit analysis: legal, economic, and philosophical perspectives. The University of Chicago Press, Chicago, IL.Search in Google Scholar
Adler, M.D. and Posner, E.A. (2006). New foundations of cost-benefit analysis. Harvard University Press, Cambridge, MA.10.2307/j.ctv1nzfgqtSearch in Google Scholar
Allcott, H. (2011). Social norms and energy conservation. J. Publ. Econ. 95: 1082–1095. https://doi.org/10.1016/j.jpubeco.2011.03.003.Search in Google Scholar
Allcott, H. and Greenstone, M. (2012). Is there an energy efficiency gap? J. Econ. Perspect. 26: 3–28. https://doi.org/10.1257/jep.26.1.3.Search in Google Scholar
Allcott, H. and Rogers, T. (2014). The short-run and long-run effects of behavioural interventions: experimental evidence from energy conservation. Am. Econ. Rev. 104: 3003–3037. https://doi.org/10.1257/aer.104.10.3003.Search in Google Scholar
Allcott, H. and Kessler, J. (2019). The welfare effects of nudges: a case study of energy use social comparisons. Am. Econ. J. Appl. Econ. 11: 236–276. https://doi.org/10.1257/app.20170328.Search in Google Scholar
Arimura, T., Li, S., Newell, R., and Palmer, K. (2012). Cost-effectiveness of electricity energy efficiency programs. Energy J. 33: 63–99. https://doi.org/10.5547/01956574.33.2.4.Search in Google Scholar
Asensio, O.I. and Delmas, M.A. (2015). Nonprice incentives and energy conservation. Proc. Natl. Acad. Sci. U.S.A. 112: E510–E515. https://doi.org/10.1073/pnas.1401880112.Search in Google Scholar
Baskette, C., Horiia, B., Kollmanb, E., and Price, S. (2006). Avoided cost estimation and post-reform funding allocation for California’s energy efficiency programs. Energy 31: 1084–1099. https://doi.org/10.1016/j.energy.2005.03.009.Search in Google Scholar
Behavioral Insights Team (2019). Annual report 2017–2018, Available at: https://www.bi.team/wp-content/uploads/2019/01/Annual-update-report-BIT-2017-2018.pdf.Search in Google Scholar
Benartzi, S., Beshears, J., Milkman, K., Cass, S., Thaler, R., Shankar, M., Tucker-Ray, W., Congdon, W., and Galing, S. (2017). Should governments invest more in nudging? Psychol. Sci. 28: 1041–1055. https://doi.org/10.1177/0956797617702501.Search in Google Scholar
Boardman, A., Greenberg, D., Vining, A., and Weimer, D. (2018). Cost-benefit analysis: concepts and practice, 5th ed. Cambridge University Press, Cambridge, UK.10.1017/9781108235594Search in Google Scholar
Brandon, A., List, J.A., Metcalfe, R.D., Price, M.K., and Rundhammer, F. (2019). Testing for crowd out in social nudges: evidence from a natural field experiment in the market for electricity. Proc. Natl. Acad. Sci. U.S.A. 116: 5293–5298. https://doi.org/10.1073/pnas.1802874115.Search in Google Scholar
Carroll, G., Choi, J., Laibson, D., Madrian, B., and Metrick, A. (2009). Optimal defaults and active decisions. Q. J. Econ. 124: 1639–1674. https://doi.org/10.1162/qjec.2009.124.4.1639.Search in Google Scholar
Chetty, R., Friedman, J., Leth-Petersen, S., and Nielsen, T. (2014). Active vs. Passive decisions and crowd-out in retirement savings accounts: evidence from Denmark. Q. J. Econ. 129: 1141–1219. https://doi.org/10.1093/qje/qju013.Search in Google Scholar
De Francesco, F. (2012). Diffusion of regulatory impact analysis among OECD and EU member states. Comp. Polit. Stud. 45: 1277–1305. https://doi.org/10.1177/0010414011434297.Search in Google Scholar
De Jonge, P. (2018). Putting the public back in behavioural public policy. Behav. Public Policy 2: 218–226, https://doi.org/10.1017/bpp.2018.23.Search in Google Scholar
DellaVigna, S. and Linos, E. (2020). RCTs to scale: comprehensive evidence from two nudge units. In: SSRN working paper, Available at: https://www.nber.org/papers/w27594.10.3386/w27594Search in Google Scholar
Duflo, E. and Saez, E. (2003). The role of information and social interactions in retirement plan decisions: evidence from a randomized experiment. Q. J. Econ. 118: 815–842. https://doi.org/10.1162/00335530360698432.Search in Google Scholar
Duflo, E., Gale, W., Liebman, J., Peter, O., and Saez, E. (2006). Savings incentives for low- and middle-class families: evidence from a field experiment with H&R block. Q. J. Econ. 121: 1311–1346. https://doi.org/10.1162/qjec.121.4.1311.Search in Google Scholar
Duflo, E., Gale, W., Liebman, J., Peter, O., and Saez, E. (2007). Savings incentives for low- and moderate-income families in the United States: why is the Saver’s credit not more effective? J. Eur. Econ. Assoc. 5: 647–661. https://doi.org/10.1162/jeea.2007.5.2-3.647.Search in Google Scholar
Dunlop, C. and Radaelli, C. (2016). Handbook of regulatory impact assessment. Edward Elgar Publishing, London, United Kingdom.10.4337/9781782549567Search in Google Scholar
European Commission (2016). Behavioral insights applied to policy: european report 2016, Available at: https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/behavioural-insights-applied-policy-european-report-2016.Search in Google Scholar
European Commission (2021). Better regulation toolbox, Available at: https://ec.europa.eu/info/law/law-making-process/planning-and-proposing-law/better-regulation-why-and-how_en.Search in Google Scholar
Exec. Order No. 12, 866 (1993). Fed. Regist. 58: 735, Available at: https://www.archives.gov/files/federal-register/executive-orders/pdf/12866.pdf (Accessed 4 October 1993).Search in Google Scholar
Goldin, J., Homonoff, T., Patterson, R., and Skimmyhorn, W. (2020). How much to save? Decision costs and retirement plan participation. J. Publ. Econ. 191: 104247. https://doi.org/10.1016/j.jpubeco.2020.104247.Search in Google Scholar
Hagmann, D., Ho, E., and George, L. (2019). Nudging out support for a carbon tax. Nat. Clim. Change 9: 484–489. https://doi.org/10.1038/s41558-019-0474-0.Search in Google Scholar
Hershfield, H., John, E., and Joseph, R. (2018). Using vividness interpretations to improve financial decision making. Policy Insights Behav. Brain Sci. 5: 209–215, https://doi.org/10.1177/2372732218787536.Search in Google Scholar
Hitch, C.J. and McKean, R.N. (1960). Economics of defense in the nuclear age, 1st ed. Harvard University Press, Cambridge, MA.10.4159/harvard.9780674865884Search in Google Scholar
Ito, K. (2015). Asymmetric incentives in subsidies: evidence from a large-scale electricity rebate program. Am. Econ. J. Econ. Pol. 7: 209–237. https://doi.org/10.1257/pol.20130397.Search in Google Scholar
Layard, R. and Glaister, S. (1994). Cost-benefit analysis, 2nd ed. Cambridge University Press, Cambridge, UK.10.1017/CBO9780511521942Search in Google Scholar
Levin, H. and Belfield, C. (2015). Guiding the development and use of cost-effectiveness analysis in education. J. Res. Educ. Effect. 8: 400–418. https://doi.org/10.1080/19345747.2014.915604.Search in Google Scholar
Levin, H. and McEwan, P. (2001). Cost-effectiveness analysis, 2nd ed. Sage Publications, Thousand Oaks, CA.Search in Google Scholar
Miller, W., Robinson, L.A., and Lawrence, R.S. (2006). Valuing health for regulatory cost-effectiveness analysis. National Academies Press, Washington, DC.Search in Google Scholar
Minor, L. (2019). DSM budget trends through 2020. In: E-Source, Available at: https://www.esource.com/429191abpd/dsm-budget-trends-through-2020 (Accessed 14 June 2019).Search in Google Scholar
Organisation for Economic Co-operation and Development (2017). Behavioral insights and public policy: lessons from around the world. OECD Publishing, Paris, FR, Available at: https://read.oecd-ilibrary.org/governance/behavioural-insights-and-public-policy_9789264270480-en.Search in Google Scholar
Organisation for Economic Co-operation and Development (2018). Cost-benefit analysis and the environment: further developments and policy use. OECD Publishing, Paris, FR, Available at: https://www.oecd.org/governance/cost-benefit-analysis-and-the-environment-9789264085169-en.htm.Search in Google Scholar
Organisation for Economic Co-operation and Development (2020). Regulatory policy and COVID-19: behavioural insights for fast-paced decision making. OECD Publishing, Paris, FR, Available at: https://read.oecd-ilibrary.org/view/?ref=137_137590-2p5x0tveyp&title=Regulatory-policy-and-COVID-19-Behavioural-insights-for-fast-paced-decision-making.Search in Google Scholar
Pearce, D.W. (1983). Cost-benefit analysis, 2nd ed. Palgrave Macmillan, London.10.1007/978-1-349-17196-5Search in Google Scholar
Posner, E.A. (2003). Transfer regulations and cost-effectiveness analysis. Duke Law J. 53: 1067–1110.10.2139/ssrn.398820Search in Google Scholar
Sovacool, B.K., Kim, J., and Yang, M. (2021). The hidden costs of energy and mobility: a global meta-analysis and research synthesis of electricity and transport externalities. Energy Res. Social Sci. 72: 101885. https://doi.org/10.1016/j.erss.2020.101885.Search in Google Scholar
Sugden, R. and Williams, A.H. (1978). The Principles of practical cost-benefit analysis. Oxford University Press, Oxford, England.Search in Google Scholar
Sunstein, C. (2018). Better off as judged by themselves: a comment on evaluating nudges. Int. Rev. Econ. 65: 1–8.10.1007/s12232-017-0280-9Search in Google Scholar
Tannenbaum, D., Fox, C.R., and Rogers, T. (2017). On the misplaced politics of behavioural policy interventions. Nat. Human Behav. 1: 0130. https://doi.org/10.1038/s41562-017-0130.Search in Google Scholar
Tor, A. (2021). The target opportunity costs of successful nudges. In: Mathis, Klaus and Tor, Avishalom (Eds.), Consumer Law and economics. Springer, Cham, Switzerland.10.1007/978-3-030-49028-7_1Search in Google Scholar
Tor, A. (2022). The law and economics of behavioral regulation. Rev. Law Econ. 18: 223–281.10.1515/rle-2021-0081Search in Google Scholar
Tor, A. (2023). The private costs of behavioral interventions. Duke Law J. 72: Forthcoming.10.2139/ssrn.4083707Search in Google Scholar
Weimer, D. (2017). Behavioral economics for cost-benefit analysis: benefit validity when sovereign consumers seem to make mistakes. Cambridge University Press, Cambridge, UK.10.1017/9781108178389Search in Google Scholar
Wirtshafter Associates (2006). Evaluation of the california statewide 20/20 demand reduction programs.Search in Google Scholar
Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/rle-2021-0048).
© 2022 Walter de Gruyter GmbH, Berlin/Boston