Skip to main content

The nudge wars: A modern socialist calculation debate

Abstract

We investigate the claims of behavioral paternalism in the more realistic framework of complex choice. In particular, we analyze the claims made by behavioral paternalists that predictive analytics over large amounts of data will make it possible to target and successfully implement purportedly welfare-enhancing nudges deemed to make nudged agents better off “as judged by themselves” (AJBT). We draw parallels between the socialist calculation debate and nudge theoretical arguments, particularly the libertarian socialism of H. D. Dickinson and the libertarian paternalism of Cass Sunstein and Richard Thaler. We find that if actual idealized behavior is a more complicated process of recursive feedback using a knowledge classification method, behavioral paternalists engaging in an automatized process of notice-and-comment rulemaking using Big Data methods still encounter epistemological problems and the problems associated with radical uncertainty unearthed during the socialist calculation debate and afterwards.

This is a preview of subscription content, access via your institution.

Notes

  1. Furthermore, a well-founded concern about nudge outside the scope of this paper is that it applies a veneer of scientific respectibility to the historically illiberal institution of public manipulation. Even a naïve application of the theorems of public choice to nudge units seems to suggest that nudges would center on promoting the worldview of public choosers rather than enhancing public welfare.

  2. This debate may largely parallel the after-debate of socialist calculation, and especially theories of intervention post Sonneschein-Mantel-Debreu. This is where we can make a contribution to the larger critique of behavioral paternalism, in a way that is hopefully more robust to the latest volley from libertarian paternalists regarding the ability of Big Data or machine learning methods or agent-based methods to overcome epistemological constraints.

  3. See in particular Bowles et al. (2017), who cite the existence of cascades and herding effects like those observed in the 2007–2008 financial crisis and physical stampedes like the 2006 Hajj stampede that resulted in the death of almost 350 people as clear justifications for regulatory intervention in the interest of preventing herding effects (pp. 222–224). It is interesting to note that Hayek himself never advocated for catallaxy in all things. Hayek advocated for both designed and undesigned orders but emphasized that design is more efficient at the level of individuals and smaller groups and that the individual use of knowledge as a coordinative tool would be hampered by rules that were insufficiently general.

  4. Leonid Hurwicz explicitly describes the program of mechanism design in economic theory as a response to Hayek’s challenge of the Lange-Lerner model (Hurwicz 1973).

  5. Unlike nudging, jolting aims to explicitly manipulate preferences in favor of a choice outcome deemed better in some way by the social planner. Arguments for jolting typically rely on the indeterminate nature of preferences (Grill 2014).

  6. As mentioned in note 85 on page 930 of Rizzo and Whitman (2009), applying the regret criterion begs empirical evidence as to whether regret follows certain actions in a consistent way relevant to the specific individual in question.

  7. Since we can’t compare subjective outcomes using any constructive method, nudge theorists typically resort to non-constructive representative agent methods.

  8. Planning and prediction using game theory, however, come with the same stringent computational requirements as planning using traditional field-theoretic rational choice theory, in that the computation of the Nash equilibria of mixed games is generally NP-hard (Daskalakis 2013).

  9. Readers may object with the observation that mechanism design is still an open research area. There exists a controversy in the field about whether or not general equilibria are computable through approximation. Velupillai (2016) discusses so-called computable general equilibria (CGE) and demonstrates of the non-constructiveness of the proof of the existence of computable fixed-point approximations.

  10. The calculation and computability problems enter in here, which is why we must stress that we use “maximization” in a much looser sense than the exacting procedure agents undergo in the neoclassical utility maximization process. Our maximization is more like Herbert Simon’s satisficing.

References

  • Abdukadirov, S. (2016). Who should nudge?. In S. Abdukadirov (Ed.). Nudge Theory in Action (pp. 159–191). New York: Springer International Publishing.

  • Arrow, K. J. (1986). Letter to Alain Lewis, July 21, deposited in: Kenneth arrow papers. Perkins Library: Duke University.

    Google Scholar 

  • Arrow, K. (2007). Leonid Hurwicz: an appreciation. Unpublished.

  • Arthur, W. B. (2013). Complexity economics. Oxford: Oxford University Press.

    Google Scholar 

  • Berg, N., & Gigerenzer, G. (2010). As-if behavioral economics: neoclassical economics in disguise? History of Economic Ideas, 18(1), 133–165.

  • Bergson, H. (1908). L’Evolution Creatrice. Philosophical Review 17 (1):84-89.

  • Bergson, A. (1948). Socialism. 1949, a survey of contemporary economics. New York: Blakiston.

    Google Scholar 

  • Bergson, A. (1967). Market socialism revisited. Journal of Political Economy, 75(5), 655–673.

    Article  Google Scholar 

  • Bernheim, B. D., & Rangel, A. (2007). Behavioral public economics: Welfare and policy analysis with non-standard decision makers. In P. Diamond & H. Vartiainen (Eds.), Behavioral economics and its applications (pp. 7–84). Princeton: Princeton University Press.

    Google Scholar 

  • Boettke, P. J., & O'Donnell, K. W. (2013). The failed appropriation of FA Hayek by formalist economics. Critical Review, 25(3–4), 305–341.

    Article  Google Scholar 

  • Boettke, P. J., Coyne, C. J., & Leeson, P. T. (2008). The continuing relevance of FA Hayek's political economy. In R. Koppl (Ed.), Explorations in Austrian Economics Vol. 11 (pp. 79–98). Emerald Group Publishing Limited.

  • Botsman, R. (2017, Oct. 21). Big data meets big brother as China moves to rate its citizens. Retrieved from http://www.wired.co.uk. Accessed 20 Nov 2017.

  • Bowles, S., Kirman, A., & Sethi, R. (2017). Retrospectives: Friedrich Hayek and the market algorithm. Journal of Economic Perspectives, 31(3), 215–230.

    Article  Google Scholar 

  • Camerer, C., Issacharoff, S., Loewenstein, G., O’Donoghue, T., & Rabin, M. (2003). Regulation for conservatives: behavioral economics and the case for “asymmetric paternalism”. University of Pennsylvania Law Review, 151(3), 1211–1254.

    Article  Google Scholar 

  • Colander, D., & Kupers, R. (2014). Complexity and the art of public policy: solving society's problems from the bottom up. Princeton: Princeton University Press.

    Book  Google Scholar 

  • Das, S. (2006). On agent-based modeling of complex systems: learning and bounded rationality. Department of Computer Science and Engineering. La Jolla, 92093-0404.

  • Daskalakis, C. (2013). On the complexity of approximating a nash equilibrium. ACM Transactions on Algorithms, 9(3), 1–35.

    Article  Google Scholar 

  • Dickinson, H. D. (1939). The economics of socialism . Oxford: Oxford University Press.

  • Epstein, J. M. (2006). Generative social science: studies in agent-based computational modeling. Princeton: Princeton University Press.

    Google Scholar 

  • Farmer, J. D. (2012). Economics needs to treat the economy as a complex system. In Paper for the INET Conference ‘Rethinking Economics and Politics’ (Vol. 14).

  • Gigerenzer, G. (2015). On the supposed evidence for libertarian paternalism. Review of Philosophy and Psychology, 6(3), 361–383.

    Article  Google Scholar 

  • Gigerenzer, G., Mata, J., & Frank, R. (2009). Public knowledge of benefits of breast and prostate cancer screening in Europe. Journal of the National Cancer Institute, 101, 1216–1220.

    Article  Google Scholar 

  • Glod, W. (2015). How nudges often fail to treat people according to their own preferences. Social Theory and Practice, 41(4), 599–617.

    Article  Google Scholar 

  • Grill, K. (2014). Expanding the nudge: Designing choice contexts and choice contents. Rationality, Markets and Morals, 5, 139–162.

    Google Scholar 

  • Halpern, D. (2015). Inside the nudge unit: how small changes can make a big difference. London: W.H. Allen.

    Google Scholar 

  • Harré, R. (2002). Rom Harre on social structure and social change: social reality and the myth of social structure. European Journal of Social Theory, 5(1), 111–123.

    Article  Google Scholar 

  • Hayek, F. A. (1937). Economics and knowledge. Economica, 4(13), 33–54.

    Article  Google Scholar 

  • Hayek, F. A. (1940). Socialist calculation: the competitive solution. Economica, 7(26), 125–149.

    Article  Google Scholar 

  • Hayek, F. A. (1945). The use of knowledge in society. The American Economic Review, 35(4), 519–530.

    Google Scholar 

  • Hayek, F. A. (1948). Individualism and economic order. Chicago: University of Chicago Press.

    Google Scholar 

  • Hayek, F. A. (2013/1960). The constitution of liberty: the definitive edition (Vol. 17). London: Routledge.

    Book  Google Scholar 

  • Helbing, D., Frey, B.S.,  Gigerenzer, G., Hafen, E., Hagner,  M., Hofstetter, Y., van den Hoven, J., Zicari, R.V., Zwitter, A. (2017, Feb. 25). Will Democracy Survive Big Data and Artificial Intelligence. Retrieved from http://www.scientificamerican.com. Accessed 20 Nov 2017.

  • Horvitz, E. J. (1987) Reasoning about beliefs and actions under computational resource constraints. In Proceedings of the 3rd AAAI Workshop on Uncertainty in Artificial Intelligence, 429–444.

  • Hurwicz, L. (1973). The design of mechanisms for resource allocation. The American Economic Review, 63(2), 1–30.

    Google Scholar 

  • Johnson, E. J., Shu, S. B., Dellaert, B. G., Fox, C., Goldstein, D. G., Häubl, G., et al. (2012). Beyond nudges: tools of a choice architecture. Marketing Letters, 23(2), 487–504.

    Article  Google Scholar 

  • Jung, J. Y., & Mellers, B. A. (2016). American attitudes toward nudges. Judgment and Decision making, 11(1), 62–74.

    Google Scholar 

  • Kao, Y. F., & Velupillai, K. V. (2015). Behavioural economics: classical and modern. The European Journal of the History of Economic Thought, 22(2), 236–271.

    Article  Google Scholar 

  • Kautsky, K. (1902). The social revolution. Chicago: CH Kerr.

    Google Scholar 

  • Knight, F. H. (1921). Risk, uncertainty and profit. New York: Hart, Schaffner and Marx.

    Google Scholar 

  • Koppl, R. (2018). Expert failure. Cambridge: Cambridge University Press.

  • Koppl, R., Kauffman, S., Felin, T., & Longo, G. (2015). Economics for a creative world. Journal of Institutional Economics, 11(01), 1–31.

    Article  Google Scholar 

  • Kramer, G. H. (1967). An impossibility result concerning the theory of decision-making (no. 218). Cowles Foundation for Research in Economics, Yale University.

  • Lange, O. (1936). On the economic theory of socialism: part one. The Review of Economic Studies, 4(1), 53–71.

    Article  Google Scholar 

  • Lange, O. (1937). On the economic theory of socialism: part two. The Review of Economic Studies, 4(2), 123–142.

    Article  Google Scholar 

  • Lange, O. (1972). The computer and the market. In S. Economics (Ed.), A. Nove and D. Nuti. London: Penguin Books.

    Google Scholar 

  • Lavoie, D. (1985). Rivalry and central planning: the socialist calculation debate reconsidered. Cambridge: Cambridge University Press.

    Google Scholar 

  • Lee, J. Y., Bachrach, D. G., & Lewis, K. (2014). Social network ties, transactive memory, and performance in groups. Organization Science, 25(3), 951–967.

    Article  Google Scholar 

  • Lerner, A. P. (1934). Economic theory and socialist economy. The Review of Economic Studies, 2(1), 51–61.

    Article  Google Scholar 

  • Lerner, A. P. (1937). Statics and dynamics in socialist economics. The Economic Journal, 47(186), 253–270.

    Article  Google Scholar 

  • Levine, J. M., & Hogg, M. A. (2010). Encyclopedia of group processes and intergroup relations (Vol. 1). Washington, D.C.: Sage.

  • Lewis, A. A. (1985). On effectively computable realizations of choice functions: dedicated to professors Kenneth J. Arrow and Anil Nerode. Mathematical Social Sciences, 10(1), 43–80.

    Article  Google Scholar 

  • Mayer-Schönberger, V., & Cukier, K. (2013). Big data: a revolution that will transform how we live, work, and think. Boston: Houghton Mifflin Harcourt.

    Google Scholar 

  • Mirowski, P. (2002). Machine dreams: economics becomes a cyborg science. Cambridge: Cambridge University Press.

  • Mirowski, P., & Nik-Khah, E. (2017). The knowledge we have lost in information: the history of information in modern economics. Oxford: Oxford University Press.

  • Mises, L. V. (1920). Die wirtschaftsrechnung im sozialistischen gemeinwesen. Archiv für Sozialwissenschaft und Sozialpolitik, 47(1), 86–121.

    Google Scholar 

  • Morgenstern, O. (1963). On the accuracy of economic observations. Princeton: Princeton University Press.

    Google Scholar 

  • Morgenstern, O. (1972). Thirteen critical points in contemporary economic theory: an interpretation. Journal of Economic Literature, 10(4), 1163–1189.

    Google Scholar 

  • Peltokorpi, V. (2008). Transactive memory systems. Review of General Psychology, 12(4), 378.

    Article  Google Scholar 

  • Popper, K. R. (1982). The open universe: an argument for indeterminism. Cambridge: Routledge.

    Google Scholar 

  • Prigogine, I., & Stengers, I. (1997). The end of certainty. New York: Simon and Schuster.

    Google Scholar 

  • Reisch, L., & Sunstein, C. R. (2016). Do Europeans like nudges? Judgment and Decision Making, 11, 310–325.

    Google Scholar 

  • Rizzo, M. J. (2016). The four pillars of behavioral paternalism. In S. Abdukadirov (Ed.), Nudge Theory in Action (pp. 37–63). New York: Springer International Publishing.

  • Rizzo, M. J., & Whitman, D. G. (2009). The knowledge problem of new paternalism. Brigham Young University Law Review, 2009(4), 905.

    Google Scholar 

  • Room, G. (2011). Complexity, institutions and public policy: agile decision-making in a turbulent world. Cheltenham: Edward Elgar Publishing.

    Book  Google Scholar 

  • Room, G. (2016). Agile actors on complex terrains: transformative realism and public policy. London: Routledge.

    Book  Google Scholar 

  • Russell, S. J. (1997). Rationality and intelligence. Artificial Intelligence, 94(1), 57–77.

    Article  Google Scholar 

  • Russell, S. (2016). Rationality and intelligence: a brief update. In V. C. Müller (Ed.), Fundamental Issues of Artificial Intelligence (pp. 7–28). New York: Springer International Publishing.

  • Schwartz, B. (2000). Self-determination: the tyranny of freedom. American Psychologist, 55(1), 79.

    Article  Google Scholar 

  • Schwartz, B. (2004). The paradox of choice: why more is less. New York: HarperCollins Publishers.

    Google Scholar 

  • Shackle, G. (1972 (1991)). Epistemics and economics. a critique of economic doctrines. London: Routledge.

  • Simon, H. A. (1977). The logic of heuristic decision-making. In R. S. Cohen & M. W. Wartofsky (Eds.), Models of discovery. Boston: D. Reidel.

    Chapter  Google Scholar 

  • Simon, H. A. (1996). The sciences of the artificial. Cambridge: MIT press.

    Google Scholar 

  • Smith, V. L. (2003). Constructivist and ecological rationality in economics. The American Economic Review, 93(3), 465–508.

    Article  Google Scholar 

  • Sunstein, C. R. (2014). Cost-benefit analysis and the knowledge problem. Accessed on SSRN.

  • Sunstein, C. R. (2015). Choosing not to choose: understanding the value of choice. USA: Oxford University Press.

    Google Scholar 

  • Sunstein, C. R. (2016). The ethics of influence. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Sunstein, C. R. (2017). 'Better off, as judged by themselves': a comment on evaluating nudges. Available at SSRN.com.

  • Sunstein, C.R., Reich, L., & Rauber, J. (2017). Behavioral insights all over the world? Public attitudes toward nudging in a multi-country study. Available at SSRN.com.

  • Taylor, F. M. (1929). The guidance of production in a socialist state. The American Economic Review, 19, 1–8.

    Google Scholar 

  • Thaler, R. H. (2012). The winner's curse: paradoxes and anomalies of economic life. New York: Simon and Schuster.

  • Thaler, R. H. (2015). Misbehaving. New York: Norton.

    Google Scholar 

  • Thaler, R. H., & Benartzi, S. (2004). Save more tomorrow™: using behavioral economics to increase employee saving. Journal of Political Economy, 112(S1), S164–S187.

    Article  Google Scholar 

  • Thaler, R. H., & Sunstein, C. (2008). Nudge: improving decisions about health, wealth, and happiness. New Haven: Yale University Press.

    Google Scholar 

  • Troumbley, R. (2015). Coercive cyberspaces and governing internet futures. In J. Winter and R. Ono (Eds.), The Future Internet (pp. 17-40). New York: Springer International Publishing.

  • Varian, H. R. (2014). Big data: new tricks for econometrics. Journal of Economic Perspectives, 28(2), 3–28.

    Article  Google Scholar 

  • Velupillai, K. V. (2010). Computable foundations for economics. London: Routledge.

    Google Scholar 

  • Velupillai, K. V. (2016). Seven kinds of computable and constructive infelicities in economics. New Mathematics and Natural Computation, 12(03), 219–239.

    Article  Google Scholar 

  • Wagner, R. E. (2010). Mind, society, and human action: time and knowledge in a theory of social-economy. London: Routledge.

    Book  Google Scholar 

  • Wagner, R. E. (2012). A macro economy as an ecology of plans. Journal of Economic Behavior & Organization, 82(2), 433–444.

    Article  Google Scholar 

  • Whitman, D. G., & Rizzo, M. J. (2015). The problematic welfare standards of behavioral paternalism. Review of Philosophy and Psychology, 6(3), 409–425.

    Article  Google Scholar 

  • Yeung, K. (2017). ‘Hypernudge’: big data as a mode of regulation by design. Information, Communication & Society, 20(1), 118–136.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Abigail N. Devereaux.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Devereaux, A.N. The nudge wars: A modern socialist calculation debate. Rev Austrian Econ 32, 139–158 (2019). https://doi.org/10.1007/s11138-018-0414-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11138-018-0414-7

Keywords

  • Nudge theory
  • Behavioral economics
  • Economic calculation
  • Libertarian paternalism
  • Behavioral paternalism

JEL codes

  • B53
  • E03
  • D03