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Complexity and Choice

Author

Listed:
  • Yuval Salant
  • Jörg L. Spenkuch

Abstract

We study two dimensions of complexity that may interfere with individual choice. The first one is object complexity, which corresponds to the difficulty in evaluating any given alternative in a choice set. The second dimension is composition complexity, which increases when suboptimal alternatives become more similar to optimal ones. We develop a satisficing-with-evaluation-errors theory that incorporates both dimensions and delivers sharp empirical predictions about their effect on choice behavior. We confirm these predictions in a novel data set with information on hundreds of millions of decisions in chess endgames. First, as the object complexity of an optimal (suboptimal) alternative increases, it becomes less (more) likely to be chosen. Second, even highly experienced decision-makers are more likely to make mistakes when choosing from sets with higher composition complexity. These findings help to shed some of the first light on the effect of complexity on choice behavior outside of the laboratory.

Suggested Citation

  • Yuval Salant & Jörg L. Spenkuch, 2021. "Complexity and Choice," CESifo Working Paper Series 9239, CESifo.
  • Handle: RePEc:ces:ceswps:_9239
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    File URL: https://www.cesifo.org/DocDL/cesifo1_wp9239.pdf
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    References listed on IDEAS

    as
    1. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    2. Steven D. Levitt & John A. List & Sally E. Sadoff, 2011. "Checkmate: Exploring Backward Induction among Chess Players," American Economic Review, American Economic Association, vol. 101(2), pages 975-990, April.
    3. Ariel Rubinstein, 2007. "Instinctive and Cognitive Reasoning: A Study of Response Times," Economic Journal, Royal Economic Society, vol. 117(523), pages 1243-1259, October.
    4. Steven D. Levitt & John A. List & David H. Reiley, 2010. "What Happens in the Field Stays in the Field: Exploring Whether Professionals Play Minimax in Laboratory Experiments," Econometrica, Econometric Society, vol. 78(4), pages 1413-1434, July.
    5. Neyman, Abraham, 1985. "Bounded complexity justifies cooperation in the finitely repeated prisoners' dilemma," Economics Letters, Elsevier, vol. 19(3), pages 227-229.
    6. Andrew Caplin & Mark Dean & Daniel Martin, 2011. "Search and Satisficing," American Economic Review, American Economic Association, vol. 101(7), pages 2899-2922, December.
    7. Yuval Salant, 2011. "Procedural Analysis of Choice Rules with Applications to Bounded Rationality," American Economic Review, American Economic Association, vol. 101(2), pages 724-748, April.
    8. Ignacio Palacios-Huerta & Oscar Volij, 2009. "Field Centipedes," American Economic Review, American Economic Association, vol. 99(4), pages 1619-1635, September.
    9. Ignacio Palacios-Huerta & Oscar Volij, 2008. "Experientia Docet: Professionals Play Minimax in Laboratory Experiments," Econometrica, Econometric Society, vol. 76(1), pages 71-115, January.
    10. Jörg L. Spenkuch & B. Pablo Montagnes & Daniel B. Magleby, 2018. "Backward Induction in the Wild? Evidence from Sequential Voting in the US Senate," American Economic Review, American Economic Association, vol. 108(7), pages 1971-2013, July.
    11. Andrea Wilson, 2014. "Bounded Memory and Biases in Information Processing," Econometrica, Econometric Society, vol. 82, pages 2257-2294, November.
    12. John Wooders, 2010. "Does Experience Teach? Professionals and Minimax Play in the Lab," Econometrica, Econometric Society, vol. 78(3), pages 1143-1154, May.
    13. Kalai, Ehud & Stanford, William, 1988. "Finite Rationality and Interpersonal Complexity in Repeated Games," Econometrica, Econometric Society, vol. 56(2), pages 397-410, March.
    14. Michael Woodford, 2020. "Modeling Imprecision in Perception, Valuation, and Choice," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 579-601, August.
    15. Xavier Gabaix & David Laibson & Guillermo Moloche & Stephen Weinberg, 2006. "Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model," American Economic Review, American Economic Association, vol. 96(4), pages 1043-1068, September.
    16. Mark E. Glickman, 1999. "Parameter Estimation in Large Dynamic Paired Comparison Experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(3), pages 377-394.
    17. González-Díaz, Julio & Palacios-Huerta, Ignacio, 2016. "Cognitive performance in competitive environments: Evidence from a natural experiment," Journal of Public Economics, Elsevier, vol. 139(C), pages 40-52.
    18. Martin J. Osborne & Ariel Rubinstein, 1994. "A Course in Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262650401, December.
    19. Abreu, Dilip & Rubinstein, Ariel, 1988. "The Structure of Nash Equilibrium in Repeated Games with Finite Automata," Econometrica, Econometric Society, vol. 56(6), pages 1259-1281, November.
    20. Ignacio Palacios-Huerta, 2003. "Professionals Play Minimax," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 395-415.
    21. Johannes Abeler & Simon Jäger, 2015. "Complex Tax Incentives," American Economic Journal: Economic Policy, American Economic Association, vol. 7(3), pages 1-28, August.
    22. Mark Walker & John Wooders, 2001. "Minimax Play at Wimbledon," American Economic Review, American Economic Association, vol. 91(5), pages 1521-1538, December.
    23. Rubinstein, Ariel, 1986. "Finite automata play the repeated prisoner's dilemma," Journal of Economic Theory, Elsevier, vol. 39(1), pages 83-96, June.
    24. Ryan Oprea, 2020. "What Makes a Rule Complex?," American Economic Review, American Economic Association, vol. 110(12), pages 3913-3951, December.
    25. repec:feb:artefa:0094 is not listed on IDEAS
    26. Steven D. Levitt & John A. List, 2007. "What Do Laboratory Experiments Measuring Social Preferences Reveal About the Real World?," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 153-174, Spring.
    27. Steven Levitt & John List & David Reiley, 2010. "What happens in the field stays in the field: Professionals do not play minimax in laboratory experiments," Artefactual Field Experiments 00080, The Field Experiments Website.
    28. P.-A. Chiappori, 2002. "Testing Mixed-Strategy Equilibria When Players Are Heterogeneous: The Case of Penalty Kicks in Soccer," American Economic Review, American Economic Association, vol. 92(4), pages 1138-1151, September.
    29. Ariel Rubinstein, 2016. "A Typology of Players: Between Instinctive and Contemplative," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(2), pages 859-890.
    30. Ariel Rubinstein, 2007. "Instinctive and Cognitive Reasoning: Response Times Study," Levine's Bibliography 321307000000001011, UCLA Department of Economics.
    31. Huck, Steffen & Weizsacker, Georg, 1999. "Risk, complexity, and deviations from expected-value maximization: Results of a lottery choice experiment," Journal of Economic Psychology, Elsevier, vol. 20(6), pages 699-715, December.
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    1. Gian Caspari & Manshu Khanna, 2021. "Non-Standard Choice in Matching Markets," Papers 2111.06815, arXiv.org.

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    More about this item

    Keywords

    complexity; choice; satisficing; bounded rationality;
    All these keywords.

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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