Royal Economic Society The history of Regret Theory Robert Sugden - - PowerPoint PPT Presentation

Royal Economic Society

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The history of ‘Regret Theory’

Robert Sugden

Contribution to Economic Journal 125th anniversary session ‘On and beyond regret theory’ Royal Economic Society Conference University of Manchester 30 March 2015

It’s a great honour to find Graham Loomes’s and my 1982 paper ‘Regret Theory’ included in a collection of 13 ‘classic papers’ from the 125-year history

• f the EJ, alongside papers by Dalton, Ramsey, Keynes, Harrod, Becker, Stiglitz,

Atkinson…

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But I should mention two other papers published in the same year:

David Bell, ‘Regret in decision making under uncertainty’, Operations Research 1982. Peter Fishburn, ‘Nontransitive measurable utility’, Journal of Mathematical Psychology 1982.

Bell, Fishburn and Loomes/Sugden present very similar theories, developed

• independently. We found out about Bell and Fishburn only at a late stage in

writing our paper. I’ll talk about the history of ‘Regret Theory’ [the paper], not the history of regret theory [the idea].

Graham and I started thinking about regret theory in 1981.

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We were both young appointments in the economics department at the University of Newcastle. Graham was the ‘Research Officer’, previously a school teacher, mainly working on Marxian economics (and also on the value of statistical life). I was the new Reader, appointed on promise rather than achievement, mainly working on social choice theory.

One day at the tea break, Graham asked me (as a social choice theorist, who

• ught to know): Why is transitivity treated as an axiom of rationality?

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I didn’t think anything more about this conversation – but it shows the lines

• n which we were thinking.

This was a time when the axiomatic analysis of rational choice was one of the hottest topics for theorists. We were sceptics – initially, about whether the conventional model of rationality was conceptually/ normatively defensible. My reply was that I thought there wasn’t any real justification for this – Savage had proposed a model of minimax regret back in 1951. This was an internally consistent model of reasoning which could induce cycles of binary choice.

Some time later, Graham heard from a colleague about a Radio 4 programme featuring Kahneman and Tversky’s ideas about framing [‘The framing of decisions and the psychology of choice’, Science, January 1981] – she thought it might be relevant to Graham’s work on the value of statistical life. He followed this up and found K&T’s paper ‘Prospect theory’[Econometrica 1979], then started thinking about their experimental results.

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The first thing I knew about this was when he showed me the sketch of a theory he’d thought up, which explained many of Kahneman and Tversky’s results in a new way. The key idea was regret. It was the prototype of our regret theory.

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As soon as I understood how the theory worked, I could see that this was a great idea. As I had more (but not a lot of) experience of writing theoretical papers, there seemed to be scope for mutually beneficial collaboration. So we developed the theory together. Our joint work seems to have started in April 1981. By June, we had a finished paper to send to Econometrica. They rejected it (after genuinely considering it – desk rejections were unknown then), so we sent it to the EJ. By December 1982, the paper had appeared. By June 1983, we also had a paper in AER, showing how regret theory could explain preference reversal (as an instance of non-transitive preferences).

Why regret theory seemed such a good idea (to me, in 1981):

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* These feelings are psychologically credible – most people can recognise them by introspection – and don’t seem irrational. * Viewed in the perspective of axiomatic rational-choice theory, it is radically non-standard. It allows preferences which violate transitivity and stochastic

• dominance. Most theorists at the time treated these axioms as fundamental

principles of rationality (but might just be willing to consider giving up the Neumann-Morgenstern independence axiom). * It represents decision-making in a way that decision theorists ought to recognise as rational (the decision-maker maximizes the expected value of experienced utility; experienced utility can include positive and negative feelings from comparisons between ‘what is’ and ‘what might have been’). * Mathematically, regret theory is simple, elegant and general. So it’s a counter-example to theorists who think that psychological realism is incompatible with these features. * These supposedly irrational patterns of behaviour are observed in controlled experiments.

So regret theory is an exhibit in a critique of axiomatic rational-choice theory which challenges both its claim to predict behaviour and its claim to characterise ‘rationality’.

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At first, I (we?) saw the theory mainly as an exhibit of the limitations of the standard theory, but we became more interested in trying to explain actual judgements and decisions under uncertainty… We started running experimental tests of regret theory. (First experiment May 1984; from 1986, a systematic research programme at UEA , with Chris Starmer.) … particularly after a visit from Sarah Lichtenstein, who thought we were just armchair economists playing with psychological ideas – if we had run experiments we would know that regret theory wasn’t a genuine explanation

• f preference reversal.

Looking back, what did we achieve?

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* Introducing psychological concepts into the theory of choice. * Formulating theories with novel predictions that are bold and testable. We were among the pioneers of a new methodology for studying individual

• choice. In contrast to the ‘pure theory’ of the time…

* Subjecting our theories to those tests. * Challenging the normative status of even the most sacred ‘rationality’ axioms. * Publishing the results as we find them, whether we like them or not. For me, this is more significant than regret theory itself. * Taking experimental evidence seriously and trying to configure theory to be consistent with it.

‘Bliss was it in that dawn to be alive/ And to be young was very heaven’ : Wordsworth

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And looking back, how did it feel to be part of a tiny group of people developing a new methodology for economics?

Timeline: 1/81: Kahneman and Tversky’s Science paper. 4/81: Graham and I start writing ‘Regret theory’ paper. 6/81: First version of ‘Regret theory’ sent to Econometrica. 12/82: ‘Regret theory’ published in Economic Journal. 6/83: ‘A rationale for preference reversal’ published in American Econ Review 8/2/83: Started writing ‘Disappointment theory’ paper. 8/6/83: send off ‘Disappointment theory’ to Econometrica. 15-16/8/83: Sarah Lichtenstein visits to talk about a collaborative experiment – we propose tests of regret theory, she chickens out. 18/11/83: our application for £420 for regret theory experiments to University Research Committee – they give £210, department pays the rest. 8/5/84: our first experiment begins (pilot at Durham). 6/84: we present our work at the second FUR conference in Venice.

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Royal Economic Society

How successful regret theory has been relative to its competitors

Peter P. Wakker 30 March 2015 Until end 1970s: rational homo economicus ruled. Arrow (1951 Econometrica p. 406): “In view of the general tradition of economics, which tends to regard rational behavior as a first approximation to actual, I feel justified in lumping the two classes [normative and descriptive] of theory together.”

1979: 1) Allais’53 paradox first appeared in English language (Allais & Hagen’79). 2) Lindman’71, Slovic & Lichtenstein’71 preference reversal first appeared in economics (Grether & Plott’79) 3) Edwards (1955)-type psychological theory first appeared in economics (Kahneman & Tversky’79 prospect theory): birth of behavioral economics.

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Big novelty of behavioral theories: Rational theories of irrational behavior! Contrary to Arrow con suis: Irrational theories are not chaotic, but tractable models can be developed. Sugden said:

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is replaced by

* Mathematically, regret theory is simple, elegant and general. So it’s a counter-example to theorists who think that psychological realism is incompatible with these features.

(Btw., unlike me, Loomes & Sugden do not consider such psych. theories to be irrational.)

• 1. The paradoxes

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Allais’ (1953) paradox (later confirmed empirically) violates expected utility. Preferences below are majority preferences, and violate independence, so EU.

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

10M

0.25 0.75

40M

0.8 0.2

0.75 0.25

10M

0.75 0.25

10M

0.80 0.20

40M 

=!

40M

0.8 0.2

M: €106 Violates independence! 

If problems so far were signals of things to come, then now the most serious blow for

• rdinal approach & homo economicus.

The ultimate plague sent to the classical economic model.

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Most serious blow for ordinalism: Preference reversals (Lichtenstein & Slovic '71; Lindman ’71; Grether & Plott 1979). $-prospect:

• Prob. 0.31: $16

nil otherwise P-prospect:

• Prob. 0.97: $4

nil otherwise Choice-question: Which of these two prospects would you choose? Write it on a piece of paper.

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$-prospect:

• Prob. 0.31:

$16 nil otherwise P-prospect:

• Prob. 0.97:

$4 nil otherwise Money-value question: Determine for each prospect its subjective monetary value for you. Write those two values on a piece of paper.

$-prospect ~ its monetary value  monetary value of P-prospect ~ P-prospect  $-prospect

> <

transitivity:

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$-prospect:

• Prob. 0.31: $16

nil otherwise P-prospect:

• Prob. 0.97: $4

nil otherwise Common finding  Choice: majority prefers P-prospect.  Monetary evaluation: Majority assigns higher monetary value to … $-prospect!

• 2. NonEU theories ≠

regret theory

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𝑞1 𝑞2

1-𝑞1-𝑞2

x1 x2 1979 prospect theory (OPT), for regular prospects: → 𝑥 𝑞1 𝑉(𝑦1) + 𝑥 𝑞2 𝑉 𝑦2 = 𝑃𝑄𝑈

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𝑦1 𝑦𝑜 𝑞1 𝑞𝑜 . . . . . .

𝑞𝑘 𝑉(𝑦𝑘) Chew’s (1983) weighted utility

𝑔(𝑦𝑘)

𝑞𝑘𝑔(𝑦

𝑘)

→

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𝑦k+1 𝑦1 𝑦𝑙 𝑞1 𝑞𝑜 . . . . . . 𝑦𝑜 . . . Assume 𝑦1 ≥ ⋯ ≥ 𝑦𝑙 ≥ 𝐷𝐹 ≥ 𝑦k+1 ≥ ⋯ ≥ 𝑦𝑜 𝐷𝐹 Gul’s (1991) disappointment aversion theory:

𝑞𝑗𝑉(𝑦𝑗)

𝑙 𝑗=1

+

𝑜 𝑘=𝑙+1

𝑞𝑗

𝑙 𝑗=1

+ (1 + 𝛾)𝑞𝑘

𝑜 𝑘=𝑙+1

Disappointment aversion (DA) theory =

𝑞𝑘𝑉(𝑦𝑘)

1 + 𝛾

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𝑦1 𝑦𝑜 𝑞1 𝑞𝑜 . . . . . .

(𝑥 𝑞𝑘 + ⋯ + 𝑞1 − 𝑥 𝑞𝑘 − 1 + ⋯ + 𝑞1 )𝑉(𝑦𝑘) Quiggin’s (1982) rank-dependent utility →

Assume 𝑦1 ≥ ⋯ ≥ 𝑦𝑜

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𝑦1 𝑦𝑜 𝑞1 𝑞𝑜 . . . . . .

(𝑥+ 𝑞𝑗 + ⋯ + 𝑞1 − 𝑥 𝑞𝑗 − 1 + ⋯ + 𝑞1 )𝑉(𝑦𝑗)

𝑙 𝑗=1

+ 𝜇 (𝑥− 𝑞𝑘 + ⋯ + 𝑞𝑜 − 𝑥 𝑞𝑘 + 1 + ⋯ + 𝑞𝑜 )𝑉(𝑦𝑘)

𝑜 𝑘=𝑙+1

Tversky & Kahneman’s (1992) (cumulative) prospect theory →

Assume 𝑦1 ≥ ⋯ ≥ 𝑦𝑙 ≥ 0 ≥ 𝑦k+1 ≥ ⋯ ≥ 𝑦𝑜

• 3. Regret theory

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𝑦1 𝑦𝑜 𝑞1 𝑞𝑜 . . . . . .

𝑞𝑘 𝑉(𝑦𝑘) − 𝑉(𝑧𝑘)

𝑜 𝑘=1

≥ 0 Loomes & Sugden’s (1982) (regret theory) ≽

𝑧1 𝑧𝑜 𝑞1 𝑞𝑜 . . . . . .

𝑅

⇔

Mathematics: Kreweras (1961), Fishburn (1982); Multi-attribute utility: Bell (1982); Economic foundations: Loomes & Sugden (1982). (probabilities “correlated”)

More fundamental breakaway than other theories: Still today, regret theory (and follow-ups including PRAM) is only quantitatively sophisticated tractable theory that can accommodate preference reversals.

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The end

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Royal Economic Society

On Applications of Regret Theory:

Consequences of Comparing what is to what might have been

Marcel Zeelenberg

Tilburg University

Regret Theory

• People compare the outcome of their choice

with what the outcome would have been, had they chosen differently, and experience regret and rejoicing as a consequence

• These emotions are taken into account when

making decisions

• Thus, resolution of both the chosen and

unchosen option is central to regret theory

The Faces of Regret

You want to buy an instant lottery ticket. You are just in time, there are only 2 lottery tickets left. You choose a ticket and open it. You have won a liquor store token for € 15. Someone else buys the lottery ticket that was left, the

• ne you didn’t choose.

This person wins a book token of € 50.

4,71 3,64 3,91 4,64 1 2 3 4 5 6 7 8 9

Regret

€ 50 Book Token € 50 Liquor Token € 15 Book Token € 15 Liquor Token

Missed sed prize Obtained ed prize

The horrible world that might have been:

On April 8 1995 Tim O’Brien, an inhabitant of Liverpool, UK (aged 51) took his own life after missing out on a £2 million price in the National

• Lottery. He did so after discovering that that

week’s winning combination were the numbers he always selected, 14, 17, 22, 24, 42 and 47. On this occasion, however, he had forgotten to renew his five-week ticket on time. It had expired the previous Saturday.

Brief voorkant

Achterkant

Anticipated Regret Subjective Norm Attitude Behavioral Expt.

State lottery .23* .12 .10

Significantly larger than in the State lotery

Postcode lotttery .31* .10 .29*

What Next?

How do decision makers prevent future regret? Regret averse choices Better choices Insurance Bracing for loss How do decision makers manage current regret? Reverse decision Psychological repair work Individual differences in regret aversion

Thank you

Marcel@uvt.nl

Royal Economic Society

The Empirical Success of Regret Theory

Han Bleichrodt

RES meeting Manchester, 30 March 2015

Loomes (1988)

Action 1 40 41 100 A £a0 £0 B £0 £12

Loomes (1988)

Action 1 40 41 100 A £a0 £0 B £0 £12 Action 1 40 41 60 61 100 A’ £a1 £0 £0 B’ £12 £12 £0

Utility Difference

a0 12

Q(a0) Q(12)

Q

Utility Difference

a0 12

Q(a0) Q(12)

Q a0 12

Q(a0 12)

Utility Difference

a0 12

Q(a0) Q(12)

Q a0 12

Q(a0 12)

a1 12

Q(a1 12)

Loomes (1988)

Action 1 40 41 100 A £a0 £0 B £0 £12

Loomes (1988)

Action 1 40 41 100 A £a0 £0 B £0 £12 £a0 = £17.52

Loomes (1988)

Action 1 40 41 100 A £a0 £0 B £0 £12 Action 1 40 41 60 61 100 A’ £a1 £0 £0 B’ £12 £12 £0 £a0 = £17.52

Loomes (1988)

Action 1 40 41 100 A £a0 £0 B £0 £12 Action 1 40 41 60 61 100 A’ £a1 £0 £0 B’ £12 £12 £0 £a0 = £17.52 £a1 = £22.58

Studies supporting regret theory

• Loomes & Sugden (1987, EJ)
• Loomes (1988, Economica)
• Loomes (1989, Annals OR)
• Loomes, Starmer, & Sugden (1989, EJ)
• Starmer & Sugden (1989, Annals OR)
• Loomes, Starmer, & Sugden (1992, Economica)
• Loomes & Taylor (1992, EJ)
• Starmer (1992, Review of Economic Studies)

Preference reversals

Action 1 30 31 60 61 100 £-bet £18 £0 £0 P-bet £8 £8 £0 CE £4 £4 £4

Action

1 40 41 100 A £20 £0 B £0 £12 Action 1 40 41 60 61 100 A’ £20 £0 £0 B’ £12 £12 £0

Action

1 40 41 100 A £20 £0 B £0 £12 Action 1 40 41 60 61 100 A’ £20 £0 £0 B’ £12 £12 £0 Action 1 40 41 81 81 100 A £20 £0 £0 B £0 £12 £12

Action

1 40 41 100 A £20 £0 B £0 £12 Action 1 40 41 60 61 100 A’ £20 £0 £0 B’ £12 £12 £0 Action 1 40 41 81 81 100 A £20 £0 £0 B £0 £12 £12 Action 1 40 41 81 81 100 A’ £20 £0 £0 B’ £12 £0 £12

Applications of regret

• Finance
• Barberis, Huang & Thaler (2006)
• Gollier & Salanié (2006)
• Muermann et al. (2006)
• Michenaud & Solnik (2008)
• Insurance
• Braun & Muermann (2004)
• Health
• Ritov & Baron (1990,1995)
• Smith (1996)
• Murray & Beattie (2001)
• Auction theory
• Feliz-Ozbay & Ozbay (2007)
• Engelbrecht-Wiggans & Katok
• Operations Research
• Perakis & Roels (2008)
• Axiomatizations
• Köbberling & Wakker (2003)
• Zank (2010)

New insights

• Neuroeconomics
• Camille et al. (2004)
• Bourgeois-Gironde (2010)
• Giorgetta et al. (2013)
• New models
• Sarver (2008)
• Hayashi (2008)
• Loomes (2010)
• Bordalo, Gennaioli, & Shleifer (2012)

Royal Economic Society

Beyond Regret Graham Loomes, University of Warwick

Beyond Regret Graham Loomes, University of Warwick

Models Behaviour

Beyond Regret Graham Loomes, University of Warwick

Models Deterministic (mostly) Behaviour

Beyond Regret Graham Loomes, University of Warwick

Models Deterministic (mostly) Behaviour Probabilistic

Beyond Regret Graham Loomes, University of Warwick

Models Deterministic (mostly) Parsimonious/restricted Behaviour Probabilistic

Beyond Regret Graham Loomes, University of Warwick

Models Deterministic (mostly) Parsimonious/restricted Behaviour Probabilistic Multi-faceted

Beyond Regret Graham Loomes, University of Warwick

Models Deterministic (mostly) Parsimonious/restricted Procedurally invariant Behaviour Probabilistic Multi-faceted

Beyond Regret Graham Loomes, University of Warwick

Models Deterministic (mostly) Parsimonious/restricted Procedurally invariant Behaviour Probabilistic Multi-faceted Sensitive to context/frame

Consider a ‘simple’ choice and a ‘typical’ participant

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

Consider a ‘simple’ choice and a ‘typical’ participant

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

Many things s/he might attend to

Consider a ‘simple’ choice and a ‘typical’ participant

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

Many things s/he might attend to Payoff comparisons between alternatives

Consider a ‘simple’ choice and a ‘typical’ participant

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

Many things s/he might attend to Payoff comparisons between alternatives Best and worst payoffs overall; spreads

Consider a ‘simple’ choice and a ‘typical’ participant

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

Many things s/he might attend to Payoff comparisons between alternatives Best and worst payoffs overall; spreads ‘Absolute’ and ‘relative’ subjective values

Consider a ‘simple’ choice and a ‘typical’ participant

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

Many things s/he might attend to Payoff comparisons between alternatives Best and worst payoffs overall; spreads ‘Absolute’ and ‘relative’ subjective values ‘Decent’ chances; weights; probability-payoff combinations

Consider a ‘simple’ choice and a ‘typical’ participant

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

Many things s/he might attend to Payoff comparisons between alternatives Best and worst payoffs overall; spreads ‘Absolute’ and ‘relative’ subjective values ‘Decent’ chances; weights; probability-payoff combinations And other things may be suggested by different choices . . .

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery C: 0.30 chance of £45; 0.70 chance of £12

Payoff comparisons between alternatives Best and worst payoffs overall; spreads ‘Absolute’ and ‘relative’ subjective values

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery C: 0.30 chance of £45; 0.70 chance of £12

Payoff comparisons between alternatives Best and worst payoffs overall; spreads ‘Absolute’ and ‘relative’ subjective values Similarities between payoffs and/or probabilities

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery C: 0.30 chance of £45; 0.70 chance of £12

Payoff comparisons between alternatives Best and worst payoffs overall; spreads ‘Absolute’ and ‘relative’ subjective values Similarities between payoffs and/or probabilities Extra difficulty of some operations / comparisons

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery C: 0.30 chance of £45; 0.70 chance of £12

Payoff comparisons between alternatives Best and worst payoffs overall; spreads ‘Absolute’ and ‘relative’ subjective values Similarities between payoffs and/or probabilities Extra difficulty of some operations / comparisons ‘Regret’, ‘disappointment’, ‘similarity’, ‘probability weighting’ are just some of the above; and each might be modelled in more than one way

The General Model

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

The General Model

Pairs of items / combinations are sampled momentarily

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

The General Model

Pairs of items / combinations are sampled momentarily The same comparison may register differently at different moments – variability of stock of experience / neuronal activity

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

The General Model

Pairs of items / combinations are sampled momentarily The same comparison may register differently at different moments – variability of stock of experience / neuronal activity The judgmental ‘evidence’ – which option is favoured and how strongly – is accumulated in some way

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

The General Model

Pairs of items / combinations are sampled momentarily The same comparison may register differently at different moments – variability of stock of experience / neuronal activity The judgmental ‘evidence’ – which option is favoured and how strongly – is accumulated in some way After sampling – deliberation – produces an imbalance that exceeds some threshold (level of confidence / speed-accuracy trade-off) a decision is triggered

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

Implications:

Implications: Exactly the same scenario may be processed differently when presented on different occasions – decisions are probabilistic

Implications: Exactly the same scenario may be processed differently when presented on different occasions – decisions are probabilistic May take different amounts of time, depending on balance

Implications: Exactly the same scenario may be processed differently when presented on different occasions – decisions are probabilistic May take different amounts of time, depending on balance Variability is not necessarily an error – it is not an error to get

• n with life if there are other things to be done

Implications: Exactly the same scenario may be processed differently when presented on different occasions – decisions are probabilistic May take different amounts of time, depending on balance Variability is not necessarily an error – it is not an error to get

• n with life if there are other things to be done

Omitting comparisons / operations will distort recovery / tests

Implications: Exactly the same scenario may be processed differently when presented on different occasions – decisions are probabilistic May take different amounts of time, depending on balance Variability is not necessarily an error – it is not an error to get

• n with life if there are other things to be done

Omitting comparisons / operations will distort recovery / tests Different procedures / frames may influence the sampling in ways that lead to systematically different patterns

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0

25% 55% 20% A £60 £10 £10 B £30 £30 0

Lottery A: 0.25 chance of £60; 0.75 chance of £10 Lottery B: 0.80 chance of £30; 0.20 chance of 0 25% 55% 20% A £60 £10 £10 B £30 £30 0 Not to mention PE, CE, Buy-Sell, MPL, Ranking . . .

Deterministic ‘core’ theory plus ‘add-on’ noise won’t do (although there IS extraneous as well as intrinsic noise)

Deterministic ‘core’ theory plus ‘add-on’ noise won’t do (although there IS extraneous as well as intrinsic noise) Building multiple-influence probabilistic process-based models where context/framing may be part of the story rather than an inconvenient truth is the way to go

Deterministic ‘core’ theory plus ‘add-on’ noise won’t do (although there IS extraneous as well as intrinsic noise) Building multiple-influence probabilistic process-based models where context/framing may be part of the story rather than an inconvenient truth is the way to go Not only ‘beyond’ regret but also before: Simon’s Nobel appeal to develop process models – still the challenge ahead

Beyond Regret Graham Loomes, University of Warwick

Royal Economic Society