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Risky Choice and the Construction of Preferences

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The Selten School of Behavioral Economics

Abstract

Imagine your doorbell rings. You open to find a young professional salesperson offering you a new type of electronic data loss insurance. You may wish to send him away immediately, but he talks so fast that you cannot help hearing the details of the deal. The contract will pay you a certain amount, if your electronic data storages are lost due to power blackouts or irregularities, due to fluid damages (water, coffee, soft drinks, etc.), or due to other unforeseen accidents or natural disasters. The insurance agent has a certified table listing the historic frequencies of all these events, i.e. you have reliable estimates of the event probabilities. The agent also quotes a price (or perhaps a number of prices for variants of the contract, insuring more or less of the data loss events). All you have to do now is to assess the value of your electronic data, match it up with your risk preferences, compare cost to benefit, relate the net benefit of the insurance contract to all other prospects that life offers, and you can immediately tell the friendly salesperson, whether the suggested insurance contract is a deal or is no deal. This should not be a big deal, right?

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Notes

  1. 1.

    Typically preference functions represent preference orderings that are complete, monotonic (i.e. not contradicting stochastic dominance criteria), transitive. This is true for expected utility theory (von Neumann and Morgenstern 1947) and for most of the non-expected utility (or “generalized expected utility”) theories that provide a preference function (e.g. Machina 1982; Quiggin 1982; Tversky and Kahneman 1992). In expected utility theory preference orderings are also assumed to fulfill the independence axiom, which basically states that if one prospect is preferred to another, combining both with a third common prospect should lead to the same preference relation between the combined prospects as between the original prospects.

  2. 2.

    McFadden (1999, p. 75) sums up the classical economic model as follows: “The standard model in economics is that consumers behave as if information is processed to form perceptions and beliefs using strict Bayesian statistical principles (perception-rationality), preferences are primitive, consistent and immutable (preference-rationality), and the cognitive process is simply preference maximization, given market constraints (process-rationality).”

  3. 3.

    Herbert Simon’s work on boundedly rational decision making was an important early influence for Reinhard Selten, who says that in the late 1905s he was “converted to Simon’s views.” (Selten 1993, p.117).

  4. 4.

    The “legend” of Sect. 3 is that the paper had be accepted for publication in Econometrica under the provision that some minor revisions are made and that the paper’s Section 3 is removed. Instead of revising and resubmitting the paper, however, Reinhard Selten withdrew the paper from Econometrica and submitted it to Theory & Decision insisting that it is either rejected or taken as it is. The paper was published in Theory & Decision without major revisions and turned out to be one of the most frequently cited papers in game theory.

  5. 5.

    While the distorted usage of the term used to infuriate Reinhard Selten early on, he has now accepted it as the result of an evolutionary process (personal communication).

  6. 6.

    See Brandts and Charness (2009) for a survey comparing the strategy elicitation method to spontaneous play.

  7. 7.

    Amongst these the most notable are the strategy tournaments that ask subjects (often self-selected subjects) to send in a full strategy that can be run in a tournament against others. See e.g. Axelrod (1984), Friedman and Rust (1993), and Erev et al. (2010).

  8. 8.

    If the decision rules do not specify a unique choice, the task is skipped and the subject receives no payment for the specific choice task. Note, however, that subjects are allowed to include a random draw rule (e.g. “flip a coin”) to make a decision when indifferent.

  9. 9.

    Many subjects take notes that are later used to update their set of decision rules.

  10. 10.

    We use MAD instead of SD or VAR, because MAD is much simpler to explain than the other measures of dispersion. It is also easier to calculate MAD without a calculator, because there are no exponents involved.

  11. 11.

    See e.g. Ariely et al. (2006) and the references therein. Amir and Levav (2008) study the stability of preferences that have been constructed in different framing tasks.

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  1. Fakultät für Wirtschaftswissenschaft, Otto-von-Guericke-Universität Magdeburg, 41 20, Magdeburg, 39106, Germany

    Abdolkarim Sadrieh

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  1. Magdeburg, Otto-von-Guericke-Universität, Magdeburg, 39106, Germany

    Abdolkarim Sadrieh

  2. Staatswissenschaftliches, (Volkswirtschaftliches) Seminar, Universität Köln, Albertus-Magnus-Platz, Köln, 50923, Germany

    Axel Ockenfels

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Sadrieh, A. (2010). Risky Choice and the Construction of Preferences. In: Sadrieh, A., Ockenfels, A. (eds) The Selten School of Behavioral Economics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13983-3_16

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  • DOI: https://doi.org/10.1007/978-3-642-13983-3_16

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