Nudging and Boosting: A Theoretical Framework for Policy Optimization
- 1 Department of Business and Law, School of Economics and Management, University of Siena, Siena, Italy
- 2 Department of Economics and Finance, Catholic University of the Sacred Heart, Milano, Italy
- 3 Doctoral School of Social Sciences, University of Trento, Trento, Italy
Abstract
Problems of optimization are pervasive in the modern world. Policy Makers, indeed, have the aim of adopting the best policies mix, under their budge t con straint, to maximize economic and social welfare. We exploit the classical Consumer Theory to introduce the Policy Maker optimization problem in steering or empowering good decisions. Specifically, we focus on two main behavioral policies: nudging and boosting. This framework allows us, indeed, to focus on the main building blocks of the so-defined evolutionary function . Since the policy mix depends on the cost of the different policies and their different elasticities, under the (debatable) assumption of rational citizens (i.e. constant returns to scale), this means that these latter are the most important variables that should be estimated. Specifically, by means of surveys, we suggest approximating the elasticities level.
- Bicchieri, C., & Dimant, E. (2019). Nudging with Care: The Risks and Benefits of Social Information. Public Choice, 191, 443-464. https://doi.org/10.2139/ssrn.3319088
- Bühren, C., & Daskalakis, M. (2020). Which Green Nudge Helps to Save Energy? Experimental Evidence. MAGKS Joint Discussion Paper Series in Economics. https://www.uni-marburg.de/en/fb02/research-groups/economics/macroeconomics/ research/magks-joint-discussion-papers-in-economics/papers/2020-papers/42-2020_buehren.pdf
- Carter, S. (2014). “On the Cobb-Douglas and All That …”: The Solow-Simon Correspondence over the Aggregate Neoclassical Production Function. Journal of Post Keynesian Economics, 34, 255-274. https://doi.org/10.2753/PKE0160-3477340204
- Cialdini, R. B., Demaine, L. J., Sagarin, B. J., Barrett, D. W., Rhoads, K., & Winter, P. L. (2006). Managing Social Norms for Persuasive Impact. Social Influence, 1, 3-15. https://doi.org/10.1080/15534510500181459
- Frederiks, E. R., Stenner, K., & Hobman, E. V. (2015). Household Energy Use: Applying Behavioral Economics to Understand Consumer Decision-Making and Behaviour. Renewable and Sustainable Energy Reviews, 41, 1385-1394. https://doi.org/10.1016/j.rser.2014.09.026
- Hertwig, R., & Grüne-Yanoff, T. (2017). Nudging and Boosting: Steering or Empowering Good Decisions. Perspectives on Psychological Science, 12, 973-986. https://doi.org/10.1177/1745691617702496
- Hertwig, R., & Ryall, M. D. (2019). Nudge versus Boost: Agency Dynamics under Libertarian Paternalism. The Economic Journal, 130, 1384-1415. https://doi.org/10.1093/ej/uez054
- Intriligator, M. D. (2013). Mathematical Optimization and Economic Theory. PHI Learning Private Limited.
- Kahneman, D. (2003). Maps of Bounded Rationality: Psychology for Behavioral Economics. American Economic Review, 93, 1449-1475. https://doi.org/10.1257/000282803322655392
- Levin, J., & Milgrom, P. (2004). Consumer Theory (pp. 1-33). Stanford University. https://web.stanford.edu/~jdlevin/Econ%20202/Consumer%20Theory.pdf
- Miller, E. (2008). An Assessment of CES and Cobb-Douglas Production Functions. Congressional Budget Office. https://www.cbo.gov/sites/default/files/cbofiles/ftpdocs/94xx/doc9497/2008-05.pdf
- Simon, H. A. (1984). On the Behavioral and Rational Foundations of Economic Dynamics. Journal of Economic Behavior & Organization, 5, 35-55. https://doi.org/10.1016/0167-2681(84)90025-8