Advertisement

The nudge wars: A modern socialist calculation debate

  • Abigail N. Devereaux
Article

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.

Keywords

Nudge theory Behavioral economics Economic calculation Libertarian paternalism Behavioral paternalism 

JEL codes

B53 E03 D03 

References

  1. Abdukadirov, S. (2016). Who should nudge?. In S. Abdukadirov (Ed.). Nudge Theory in Action (pp. 159–191). New York: Springer International Publishing.Google Scholar
  2. Arrow, K. J. (1986). Letter to Alain Lewis, July 21, deposited in: Kenneth arrow papers. Perkins Library: Duke University.Google Scholar
  3. Arrow, K. (2007). Leonid Hurwicz: an appreciation. Unpublished.Google Scholar
  4. Arthur, W. B. (2013). Complexity economics. Oxford: Oxford University Press.Google Scholar
  5. Berg, N., & Gigerenzer, G. (2010). As-if behavioral economics: neoclassical economics in disguise? History of Economic Ideas, 18(1), 133–165.Google Scholar
  6. Bergson, H. (1908). L’Evolution Creatrice. Philosophical Review 17 (1):84-89.Google Scholar
  7. Bergson, A. (1948). Socialism. 1949, a survey of contemporary economics. New York: Blakiston.Google Scholar
  8. Bergson, A. (1967). Market socialism revisited. Journal of Political Economy, 75(5), 655–673.CrossRefGoogle Scholar
  9. 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
  10. Boettke, P. J., & O'Donnell, K. W. (2013). The failed appropriation of FA Hayek by formalist economics. Critical Review, 25(3–4), 305–341.CrossRefGoogle Scholar
  11. 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.Google Scholar
  12. 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.
  13. Bowles, S., Kirman, A., & Sethi, R. (2017). Retrospectives: Friedrich Hayek and the market algorithm. Journal of Economic Perspectives, 31(3), 215–230.CrossRefGoogle Scholar
  14. 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.CrossRefGoogle Scholar
  15. Colander, D., & Kupers, R. (2014). Complexity and the art of public policy: solving society's problems from the bottom up. Princeton: Princeton University Press.CrossRefGoogle Scholar
  16. Das, S. (2006). On agent-based modeling of complex systems: learning and bounded rationality. Department of Computer Science and Engineering. La Jolla, 92093-0404.Google Scholar
  17. Daskalakis, C. (2013). On the complexity of approximating a nash equilibrium. ACM Transactions on Algorithms, 9(3), 1–35.CrossRefGoogle Scholar
  18. Dickinson, H. D. (1939). The economics of socialism . Oxford: Oxford University Press.Google Scholar
  19. Epstein, J. M. (2006). Generative social science: studies in agent-based computational modeling. Princeton: Princeton University Press.Google Scholar
  20. 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).Google Scholar
  21. Gigerenzer, G. (2015). On the supposed evidence for libertarian paternalism. Review of Philosophy and Psychology, 6(3), 361–383.CrossRefGoogle Scholar
  22. 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.CrossRefGoogle Scholar
  23. Glod, W. (2015). How nudges often fail to treat people according to their own preferences. Social Theory and Practice, 41(4), 599–617.CrossRefGoogle Scholar
  24. Grill, K. (2014). Expanding the nudge: Designing choice contexts and choice contents. Rationality, Markets and Morals, 5, 139–162.Google Scholar
  25. Halpern, D. (2015). Inside the nudge unit: how small changes can make a big difference. London: W.H. Allen.Google Scholar
  26. 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.CrossRefGoogle Scholar
  27. Hayek, F. A. (1937). Economics and knowledge. Economica, 4(13), 33–54.CrossRefGoogle Scholar
  28. Hayek, F. A. (1940). Socialist calculation: the competitive solution. Economica, 7(26), 125–149.CrossRefGoogle Scholar
  29. Hayek, F. A. (1945). The use of knowledge in society. The American Economic Review, 35(4), 519–530.Google Scholar
  30. Hayek, F. A. (1948). Individualism and economic order. Chicago: University of Chicago Press.Google Scholar
  31. Hayek, F. A. (2013/1960). The constitution of liberty: the definitive edition (Vol. 17). London: Routledge.Google Scholar
  32. 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.
  33. 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.Google Scholar
  34. Hurwicz, L. (1973). The design of mechanisms for resource allocation. The American Economic Review, 63(2), 1–30.Google Scholar
  35. 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.CrossRefGoogle Scholar
  36. Jung, J. Y., & Mellers, B. A. (2016). American attitudes toward nudges. Judgment and Decision making, 11(1), 62–74.Google Scholar
  37. 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.CrossRefGoogle Scholar
  38. Kautsky, K. (1902). The social revolution. Chicago: CH Kerr.Google Scholar
  39. Knight, F. H. (1921). Risk, uncertainty and profit. New York: Hart, Schaffner and Marx.Google Scholar
  40. Koppl, R. (2018). Expert failure. Cambridge: Cambridge University Press.Google Scholar
  41. Koppl, R., Kauffman, S., Felin, T., & Longo, G. (2015). Economics for a creative world. Journal of Institutional Economics, 11(01), 1–31.CrossRefGoogle Scholar
  42. Kramer, G. H. (1967). An impossibility result concerning the theory of decision-making (no. 218). Cowles Foundation for Research in Economics, Yale University.Google Scholar
  43. Lange, O. (1936). On the economic theory of socialism: part one. The Review of Economic Studies, 4(1), 53–71.CrossRefGoogle Scholar
  44. Lange, O. (1937). On the economic theory of socialism: part two. The Review of Economic Studies, 4(2), 123–142.CrossRefGoogle Scholar
  45. Lange, O. (1972). The computer and the market. In S. Economics (Ed.), A. Nove and D. Nuti. London: Penguin Books.Google Scholar
  46. Lavoie, D. (1985). Rivalry and central planning: the socialist calculation debate reconsidered. Cambridge: Cambridge University Press.Google Scholar
  47. Lee, J. Y., Bachrach, D. G., & Lewis, K. (2014). Social network ties, transactive memory, and performance in groups. Organization Science, 25(3), 951–967.CrossRefGoogle Scholar
  48. Lerner, A. P. (1934). Economic theory and socialist economy. The Review of Economic Studies, 2(1), 51–61.CrossRefGoogle Scholar
  49. Lerner, A. P. (1937). Statics and dynamics in socialist economics. The Economic Journal, 47(186), 253–270.CrossRefGoogle Scholar
  50. Levine, J. M., & Hogg, M. A. (2010). Encyclopedia of group processes and intergroup relations (Vol. 1). Washington, D.C.: Sage.Google Scholar
  51. 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.CrossRefGoogle Scholar
  52. 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
  53. Mirowski, P. (2002). Machine dreams: economics becomes a cyborg science. Cambridge: Cambridge University Press.Google Scholar
  54. Mirowski, P., & Nik-Khah, E. (2017). The knowledge we have lost in information: the history of information in modern economics. Oxford: Oxford University Press.Google Scholar
  55. Mises, L. V. (1920). Die wirtschaftsrechnung im sozialistischen gemeinwesen. Archiv für Sozialwissenschaft und Sozialpolitik, 47(1), 86–121.Google Scholar
  56. Morgenstern, O. (1963). On the accuracy of economic observations. Princeton: Princeton University Press.Google Scholar
  57. Morgenstern, O. (1972). Thirteen critical points in contemporary economic theory: an interpretation. Journal of Economic Literature, 10(4), 1163–1189.Google Scholar
  58. Peltokorpi, V. (2008). Transactive memory systems. Review of General Psychology, 12(4), 378.CrossRefGoogle Scholar
  59. Popper, K. R. (1982). The open universe: an argument for indeterminism. Cambridge: Routledge.Google Scholar
  60. Prigogine, I., & Stengers, I. (1997). The end of certainty. New York: Simon and Schuster.Google Scholar
  61. Reisch, L., & Sunstein, C. R. (2016). Do Europeans like nudges? Judgment and Decision Making, 11, 310–325.Google Scholar
  62. 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.Google Scholar
  63. Rizzo, M. J., & Whitman, D. G. (2009). The knowledge problem of new paternalism. Brigham Young University Law Review, 2009(4), 905.Google Scholar
  64. Room, G. (2011). Complexity, institutions and public policy: agile decision-making in a turbulent world. Cheltenham: Edward Elgar Publishing.CrossRefGoogle Scholar
  65. Room, G. (2016). Agile actors on complex terrains: transformative realism and public policy. London: Routledge.Google Scholar
  66. Russell, S. J. (1997). Rationality and intelligence. Artificial Intelligence, 94(1), 57–77.CrossRefGoogle Scholar
  67. 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.Google Scholar
  68. Schwartz, B. (2000). Self-determination: the tyranny of freedom. American Psychologist, 55(1), 79.CrossRefGoogle Scholar
  69. Schwartz, B. (2004). The paradox of choice: why more is less. New York: HarperCollins Publishers.Google Scholar
  70. Shackle, G. (1972 (1991)). Epistemics and economics. a critique of economic doctrines. London: Routledge.Google Scholar
  71. Simon, H. A. (1977). The logic of heuristic decision-making. In R. S. Cohen & M. W. Wartofsky (Eds.), Models of discovery. Boston: D. Reidel.CrossRefGoogle Scholar
  72. Simon, H. A. (1996). The sciences of the artificial. Cambridge: MIT press.Google Scholar
  73. Smith, V. L. (2003). Constructivist and ecological rationality in economics. The American Economic Review, 93(3), 465–508.CrossRefGoogle Scholar
  74. Sunstein, C. R. (2014). Cost-benefit analysis and the knowledge problem. Accessed on SSRN.Google Scholar
  75. Sunstein, C. R. (2015). Choosing not to choose: understanding the value of choice. USA: Oxford University Press.Google Scholar
  76. Sunstein, C. R. (2016). The ethics of influence. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  77. Sunstein, C. R. (2017). 'Better off, as judged by themselves': a comment on evaluating nudges. Available at SSRN.com.
  78. 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.
  79. Taylor, F. M. (1929). The guidance of production in a socialist state. The American Economic Review, 19, 1–8.Google Scholar
  80. Thaler, R. H. (2012). The winner's curse: paradoxes and anomalies of economic life. New York: Simon and Schuster.Google Scholar
  81. Thaler, R. H. (2015). Misbehaving. New York: Norton.Google Scholar
  82. Thaler, R. H., & Benartzi, S. (2004). Save more tomorrow™: using behavioral economics to increase employee saving. Journal of Political Economy, 112(S1), S164–S187.CrossRefGoogle Scholar
  83. Thaler, R. H., & Sunstein, C. (2008). Nudge: improving decisions about health, wealth, and happiness. New Haven: Yale University Press.Google Scholar
  84. 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.Google Scholar
  85. Varian, H. R. (2014). Big data: new tricks for econometrics. Journal of Economic Perspectives, 28(2), 3–28.CrossRefGoogle Scholar
  86. Velupillai, K. V. (2010). Computable foundations for economics. London: Routledge.Google Scholar
  87. Velupillai, K. V. (2016). Seven kinds of computable and constructive infelicities in economics. New Mathematics and Natural Computation, 12(03), 219–239.CrossRefGoogle Scholar
  88. Wagner, R. E. (2010). Mind, society, and human action: time and knowledge in a theory of social-economy. London: Routledge.Google Scholar
  89. Wagner, R. E. (2012). A macro economy as an ecology of plans. Journal of Economic Behavior & Organization, 82(2), 433–444.CrossRefGoogle Scholar
  90. Whitman, D. G., & Rizzo, M. J. (2015). The problematic welfare standards of behavioral paternalism. Review of Philosophy and Psychology, 6(3), 409–425.CrossRefGoogle Scholar
  91. Yeung, K. (2017). ‘Hypernudge’: big data as a mode of regulation by design. Information, Communication & Society, 20(1), 118–136.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.George Mason UniversityFairfaxUSA

Personalised recommendations