Herewith are further (partial, impressionistic) notes from the second day of the two-day workshop (programme) on Rationality and Emotions organized by Miriam Teschl at Robinson College here in Cambridge.


S-Shaped Probability Weighting and Hyperbolic Preference Reversal – An Intimate Relationship by Herbert Walther

Walther has published these results as a 2003 paper in Journal of Economic Behaviour and Organization.

http://www.robinson.cam.ac.uk/academic/robinson_rationality_walther.pdf

Overview

  • Empirical regularities:
    • hyperbolic discounting
    • sign effect: loss discounted less than gains
    • preference reversal:
    • magnitude effect: preference for losses before gains
    • s-shaped prob weighting (Gonzales and Wu 1999, Fehr-Duda, 2006 et al.)
      • prob weighting can explain Allais paradox
  • How to resolve?
  • Ans: EU maximizer considers anticipated emotions reactions to resoluton of uncertainty
    • prob weight derived via intertemporal state dependent EU max
    • using this can explain most empirical effects

Model and Results

Part 1: Generating the S-shape prob distbn

  • EU of some binary prospect L(p, w1, w2), w1
  • EU of wealth
  • EU of elation (if you win)
  • EU of disappointment (if you lose)
  • last two both fade away over time
  • Implied prob q(p) is as follows:
    • $$q(p) = p \frac{1 + (1-p)\mu}{1 + (1-p)p(\gamma + \mu)}$$ where
    • $$\gamma = \frac{\delta \alpha}{\delta + \theta}$$ where $$\delta$$ is discount rate, $$\alpha$$ is weighting of elation and $$\theta$$ is the exponential rate of elation decay
    • $$\mu = \frac{\delta + \beta}{\delta + \rho}$$ where $$\beta$$ is weighting of disappointment and $$\rho$$ is exponential rate of disappointment decay.
  • Really recommend looking at Walther’s paper (fig 1) which is on Robinson website
  • Generates the S-shaped effect
    • furthermore have testable empirical predictions: higher time preference (i.e. more impatient) should be associated with more pronounced S-shape (i.e. more risk-loving). So e.g. people who are gamblers should be saving less.
  • Part 2: Empirical regularities

    Having generated the S-shaped result Walther goes on to show how this can generate most of the empirical regularities we are interested in.

    • Look at some payment/contract whose probability of payment fulfilment is falling over time (this way we get probability in which we need)
    • Now have some S-shaped setup and probability that goes into this S-shape is dropping over time (contract is less likely to be fulfilled).
    • Hyperbolic discounting: can also now generate hyperbolic discounting within this same framework (other explanations e.g. Souzou 1998, Dasgupta and Maskin (2005) only do it on its own).
      • Logic underlying hyperbolicity: at start contract is very likely to be fulfilled so if it does not lots of disappointment — so (exp) discount rate is very high. Over time prob falls and S-shape prob distbn kicks in (so elation outweighing disappointment) and discount rate falls.
      • prediction: poor will show more hyperbolicity than rich
    • The sign effect: gains discounted more than losses
      • Logic: again simple. If loss is very likely little disappointement but a very certain gain has lots of potential for disappointment.
      • prediction: again the sign effect is more pronounced for poor than the rich.
      • magnitude effect for losses: higher losses have higher impact that lower losses (because straightforward wealth utility becomes more important than disappointment/elation effect).
    • preference reversal
      • poor will prefer losses before rich subject but gains after rich subject
      • preferences are same but marginal utility of wealth is different

    Summary

    • Simple model that is a small extension of basic EU maximization most of the empirical regularities.
    • If diminishing marginal utility of wealth poor people will behave ‘less rationally’ than rich people despite having same preferences
    • For the future: Why is prob weighting evolutionary sustainable?
      • potential answer: in hunter gather society there are externalities in that (large) gains and losses are shared (this would => S-shaped prob distbn).

    “It’s a boy! Behavioural and Neural Evidence on Self Delusion” by Danica Mijovic-Prelec

    • Deficits (due to lesion) on right side of brain lead to deficits in left hemisphere
    • Furthermore these patients are not aware of the deficit and deny its existence (to the extent of confabulating experiences)
    • Sackheim-Gur 1979: self-deception in social psychology
      • played people mixture of their own phone and others
      • averse to your own voice
      • people would not hear their own voice and furthermore physiological measure of stress indicated it went up when ‘not hearing their voice (when it was there) — i.e. when people were self-deceiving
    • Sackheim-Gur criteria:
      • individual holds 2 contradictory beliefs
      • beliefs held simultaneously
      • individual is not aware of of holding one of the two beliefs
      • nonawareness of this belief is motivated

    Experiment

    • shown korean figures and asked to classify as male/female
    • first stage: get figures and must classify (5c for each correct prediction — correct measured against classification by some control group)
    • second stage: must also predict gender of next figure (and then classify)
      • paid like before for classification but bonus for being in top x% of predictors

    Results

    • Focus on items that were ‘well-classified’ by control
    • First classification: 65% accurate
    • Anticipation: 50% accurate (as expected since randomized)
    • Second classification: <65%
      • anticipation effects classification
    • stronger for males: anticipated as male results in classification as male 72% (for females like first time round)
    • calculate self-delusion index for each subject
      • four options for response pattern (starting with female) of form 1st classif, anticipation, 2nd classif:
        • FMF: honest
        • FMM: self-deluding
        • FFM: inconsistent
        • FFF: consistent
      • need to subtract inconsistency from self-delusion percentage to get ‘true’ self-delusion
      • index = % self-delusion / % inconsistency (could use difference)
    • fMRI
      • expect that self-deluding subjects behave differently from inconsistent (and honest and consistent)
        • notably don’t show this activation on consistent trial (when they also confirm their prediction)
      • this is what they find (v. significantly)
      • in attentional and cog. control regions
        • self-deluding and inconsistent is similar
        • however big difference in parahippocampal gyrus (associated with memory)
    • [rp] question: could some of this come from a priming effect combined with better recall. I anticipate X, which primes me. Then suppose I see the figure and have a vague recall from before. Suppose that people experience different priming effects — then those with a strong priming effect feel conflicted and have more stress (i remember Y sort of but do I really or I just doubtful because of having seen X) which means more fMRI anomalies and and means they are more likely to ’self-delude’ while those with weak priming simply aren’t sure what they think (not really excited/conflicted) and just go randomly with M/F (so ’self-delusion’ or ‘inconsistency’ are equally likely).

    Herding and Social Influence in Economic Decision Making by Michelle Baddeley

    • Solomon Asch
      • Length of line experiments (everyone says line is B when actually A)
    • Task design: stock-picking
      • two charts for past prices of a stock
      • shown faces along with their associated choice (controlled by experimenter)
    • Results:
      • strong effect of other decisions on own decision (on average 72% vs. 50% choose the one chosen by herd)
      • perhaps not very surprising here given the lack of info about stocks (and their underlying equivalence) — a small piece of information should have a dramatic effect

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