Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
Saturday, 12 March 2016
5:38 AM
12.11
Traps
A heffalump is a type of fictional
elephant in the Winnie the Pooh stories
by A. A. Milne. In the fifth chapter of
Winnie-the-Pooh, Pooh and Piglet
attempt bravely to capture a heffalump
in a trap.
The term “heffalump trap” has been
used in political journalism for a trap
that is set up to catch an opponent but
ends up trapping the person who set
the trap (as happens to Winnie the
Pooh in The House at Pooh Corner).
12.22
Behavioural Traps
“Thank you for calling. All of our operators are
temporarily busy. Please stay on the line and your call
will be answered in the order received.”
A minute passes. Two minutes. You begin to wonder
whether you should hang up and redial. Maybe you
got transferred to an empty line – a telephone
twilight zone of some kind.
If a call rings in the forest and no one is there to
answer it!
12.33
Behavioural Traps
On the other hand, hanging up probably means starting
over. Other people will advance in the queue and you
will lose whatever priority you had. Better to keep
waiting. Who knows you may even be next in line.
You wait a while longer. Three minutes. Four minutes.
What is taking so long, you wonder?
Finally you make a decision. If an operator doesn’t pick
up the phone in the next sixty seconds, you will hang
up. Thirty seconds goes by, Forty seconds. Fifty
seconds and still no answer. As the deadline passes you
hesitate a few hopeful moments, then slam the
receiver down in frustration.
12.44
Behavioural Traps
Sound familiar? This situation has all the features of
a “behavioural trap”.
A behavioural trap is a situation in which individuals
or groups embark on a promising course of action
that later becomes undesirable and difficult to
escape from.
This definition is similar to one developed by Platt
(1973) in his pioneering work on social traps, and
explored by Cross and Guyer (1980). Because traps
can be non-social as well as social, however, the
general term “behavioural trap” will be used rather
than the more traditional “social trap”.
12.55
1.66
Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
12.77
Behavioural Traps - A
Taxonomy Of Traps
In 1980, Cross and Guyer published a taxonomy of
traps and counter-traps.
In the words of Cross and Guyer (1980 p. 18)
“Counter-traps (sins of omission) arise when we
avoid potentially beneficial behaviour while
traps (sins of commission) occur when we take
potentially harmful courses of action.”
As mentioned above, one common trap involves
waiting for a telephone operator.
12.88
Behavioural Traps - A
Taxonomy Of Traps
Ordinary counter-traps include aversive cleaning
chores (in which messes worsen with time) and
overdue correspondence (in which embarrassment
increases with the length of delay).
There are several distinct types of traps, each with
a corresponding counter-trap.
12.99
Behavioural Traps - A
Taxonomy Of Traps
Using the Cross-Guyer taxonomy as a starting point,
we can divide traps into five general categories:
1. Time delay traps
2. Ignorance traps
3. Investment traps
4. Deterioration traps
5. Collective traps
Although the elements of these five traps often
combine to form hybrid traps, each trap works on
somewhat different principles.
The following sections therefore discuss each type
12.10
10
of trap separately.
1.11
11
Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
12.12
12
Behavioural Traps - Time
Delay Traps
If you find it hard to diet or exercise regularly, you
know the power of time delay traps, momentary
gratification clashes with long-term consequences.
What begins innocently enough with a favourite
dessert or a few cigarettes ends up many years later
in obesity or lung cancer.
Or, in the counter-trap version, the avoidance of
what is momentarily unpleasant – aerobic exercise
for some people, dental examinations for others –
eventually leads to a heart attack or periodontal
disease.
12.13
13
Behavioural Traps - Time
Delay Traps
In fact tooth decay and heart disease are related?
Sounds weird, but it is true. Many studies have found
out that there is indeed a connection.
Periodontal (gum) disease is an infection caused by
bacteria that gets under the gum tissue and begins
to destroy the gums and bone. Teeth become loose,
chewing becomes difficult, and teeth may have to be
extracted. Gum disease also may be connected to
damage elsewhere in the body; recent studies link
oral infections with diabetes, heart disease, stroke,
and premature, low-weight births.
CDC - Chronic Disease - Oral Health - At A Glance
12.14
14
Behavioural Traps - Time
Delay Traps
What is striking about these traps and counter-traps
is that relatively small pains and pleasures in the
short run are sufficient to produce behaviour that is
devastating or even lethal in the long run.
Any situation in which short-term consequences run
counter to long-term consequences has the potential
for becoming a time delay trap.
12.15
15
Behavioural Traps - Time
Delay Traps
Prototypic conflicts include
the euphoria of drinking versus the next day’s
hangover;
the momentary pleasure of unprotected sex versus
the deferred prospect of AIDS or unwanted
pregnancy;
the convenience of disposable products versus the
long range environmental consequences
the “buy now, pay later” option afforded by credit
cards and higher purchase schemes;
the quick but ultimately counter productive results
12.16
16
brought by corporal punishment.
Behavioural Traps - Time
Delay Traps
the euphoria of drinking versus the next day’s hangover;
David Nutt (Director of the Neuropsychopharmacology Unit,
Imperial College London) reported: “Science now allows us to
develop a safer way to get drunk. But before we can sober up in
minutes, the drinks industry needs to embrace this healthier
approach.” … “All that is needed now is funding to test and put
them on the market.”
Alcohol without the hangover? It's closer than you think - The
Guardian - 11 November 2013
But was this new!!
Alcohol substitute that avoids drunkenness and hangovers in
development - Telegraph - 26 Dec 2009
12.17
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Behavioural Traps - Time
Delay Traps
Even the apple in the Garden of Eden can be
regarded as bait in a time delay way – the ultimate
symbol of temptation and its potentially entrapping
consequences.
12.18
18
Behavioural Traps - Time
Delay Traps
People in time delay traps often realise the long-term
consequences of their behaviour.
Over-eaters are usually very aware of putting on
weight.
Smokers some times even refer to cigarettes as
“cancer sticks” or “coffin (coughing) nails”.
Warnings about weight gain or cancer are rarely
effective against time delay traps.
12.19
19
Behavioural Traps - Time
Delay Traps
Doyle (2013) surveys over twenty models of delay
discounting (also known as temporal discounting, time
preference, time discounting), that psychologists and
economists have put forward to explain the way
people actually trade off time and money, see Reed
et al. (2012) for a simple Excel model.
12.20
20
Behavioural Traps - Time
Delay Traps
Aggregate indifference curves
(indifference between the
immediate and delayed
consequences) for participants in
the gambling and non-gambling
contexts for delay discounting.
Data points represent medians of
the individual indifference points.
Error bars represent the interquartile range of the individual
indifference points at each delay. The solid line shows the best fit in
the gambling context, and the dashed line shows the best fit in the
non-gambling context (Dixon et al. 2006).
12.21
21
Behavioural Traps - Time
Delay Traps
Error bars represent the
interquartile range of the
individual indifference points at
each delay. The solid line shows
the best fit in the gambling
context, and the dashed line
shows the best fit in the nongambling context (Dixon et al.
2006).
The evidence suggests that empirically derived sensitivity to change in
delay values (k, see below) from delay-discounting tasks are context
sensitive and are not constant across various settings for the
individual.
The research findings illustrate that most pathological gamblers
12.22
22
discounted delayed rewards to a greater degree in a gambling context.
Behavioural Traps - Time
Delay Traps
People are constantly making decisions that involve
whether they take gains (also losses) now or at some
later time(s). Individuals ‘discount the future’ when
they value imminent goods over future goods.
Discounting is typically assessed by offering real or
hypothetical choices between different monetary
sums after different delays.
12.23
23
Behavioural Traps - Time
Delay Traps
For example if we offer a person who likes apples a
choice between receiving one apple today or receiving
two apples in a month, that person may choose the
apple today because
(a)
the future apples are discounted such that
they are worth subjectively less as a result of
the delay,
(b)
the person does not trust us to deliver the
apples in a month,
(c)
arranging to obtain the two apples in a month
might be costly or inconvenient, thereby
offsetting the value of the additional apple.
12.24
24
Behavioural Traps - Time
Delay Traps
Indifference between a smaller, earlier reward
(£tomorrow) and a larger, later reward (£future) indicates
the following hyperbolic discount parameter k (Kirby and
Santiesteban 2003 also Reed et al. 2012):
£future - £tomorrow
k=
delay(in days) × £tomorrow - £future
How do people choose between a smaller reward available
sooner and a larger reward available later?
The predictive accuracy of intertemporal-choice models
Arfer, K.B. and Luhmann, C.C.
British Journal Of Mathematical & Statistical Psychology
2015 68(2) 326-341 DOI: 10.1111/bmsp.12049
12.25
25
Behavioural Traps - Time
Delay Traps
Wilson and Daly (2004) found that seeing
pictures of the faces of attractive women
induced men to discount money more steeply
than if the faces were unattractive. Van den
Bergh et al. (2008) reached similar conclusions
for men who were asked to handle bikinis.
After looking at sexually arousing images, men,
but not women, become more impatient for
financial rewards and more willing to take
financial risks.
A current stimulus for future behaviour.
12.26
26
Behavioural Traps - Time
Delay Traps
Now a study has shown that women too show these
changes to their decision making if they touch
“sexually laden stimuli” - in this case men's boxer
shorts (Festjens et al. 2014)!
12.27
27
Behavioural Traps - Time
Delay Traps
What explains these effects on behaviour? Festjens
and her colleagues believe that the touch of men's
boxer shorts have sexual connotations that trigger
the general reward circuitry in the women's brains hence their subsequent risk-taking and willingness to
pay more for other rewards. For men, a similar, yet
broader, process is triggered by the sight or touch
of stimuli with sexual connotations. They said, “We
call upon further research to investigate the genderspecific sensitivity to sexual cues and their effects”.
12.28
28
Behavioural Traps - Time
Delay Traps
Skakoon-Sparling et al. (2015)
report that sexual arousal has
emerged as an important
contextual feature in sexual
encounters that can impact
safer-sex decision-making. They
conducted two experiments
(decribed below) that
investigated the effects of
sexual arousal among male and
female participants.
12.29
29
Behavioural Traps - Time
Delay Traps
Skakoon-Sparling et al. (2015) experiment 1 (N = 144)
examined the impact of sexual arousal on sexual
health decision-making. Sexually explicit and neutral
video clips as well as hypothetical romantic scenarios
were used to evaluate the effects of sexual arousal
on sexual risk-taking intentions. Men and women who
reported higher levels of sexual arousal also
displayed greater intentions to participate in risky
sexual behaviour (e.g., unprotected sex with a new
sex partner).
12.30
30
Behavioural Traps - Time
Delay Traps
Skakoon-Sparling et al. (2015) experiment 2 (N = 122) examined
the impact of sexual arousal on general risk-taking, using the
same videos clips as in Experiment 1 and a modified version of a
computerized Blackjack card game. Participants were offered a
chance to make either a risky play or a safe play during ambiguous
conditions. Increased sexual arousal in Experiment 2 was
associated with impulsivity and a greater willingness to make risky
plays in the Blackjack game.
These findings suggest that, in situations where there are strong
sexually visceral cues, both men and women experiencing strong
sexual arousal may have lower inhibitions and may experience
impaired decision-making. This phenomenon may have an impact
during sexual encounters and may contribute to a failure to use
12.31
31
appropriate prophylactic protection.
Behavioural Traps - Time
Delay Traps
It is reported that young men
who have sex with men and
have detectable levels of the
human immunodeficiency virus
(HIV) were more likely to
report condomless anal sex,
including with a partner not
infected with HIV, than
virologically suppressed young
men who have sex with men,
according to Wilson et al.
(2015).
12.32
32
Behavioural Traps - Time
Delay Traps
A willingness to take risks enhances men's sex
appeal. This much we know from past research.
What's not clear, is whether this is because of
cultural beliefs about traditional gender roles, or if
it's an evolutionary hang-over (or perhaps both).
John Petraitis and his colleagues (2014) have put
these two explanations to the test by drawing a
distinction between risk-taking behaviours that
reflect the challenges faced by our ancestors, and
contemporary risks based around modern technology.
12.33
33
Behavioural Traps - Time
Delay Traps
The young male and female participants agreed that the
sex appeal of both sexes was boosted by engaging in
risky behaviours relevant to our hunter gatherer
ancestors. However, this attractiveness enhancement
was far more pronounced for men, than for women. In
contrast, men and women agreed that the sex appeal of
both sexes was actually diminished by engaging in risky
behaviour based on modern technology or contexts.
Petraitis, J., Lampman, C., Boeckmann, R., and Falconer, E. (2014).
Sex differences in the attractiveness of hunter-gatherer and
modern risks Journal of Applied Social Psychology, 44 (6), 442-453.
12.34
34
Behavioural Traps - Time
Delay Traps
So losses stink!
Loss aversion was larger when prospects were
displayed in the presence of methylmercaptan
(an unpleasant odour) compared to jasmine or
clean air. Moreover, individual differences in
changes in loss aversion to the unpleasant as
compared to pleasant odour correlated with
odour pleasantness but not with odour
intensity. Skin conductance responses to
losses during the outcome period were larger
when gambles were associated with
methylmercaptan compared to jasmine
(Stancak et al. 2015).
12.35
35
1.36
36
Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
12.37
37
Behavioural Traps - Delay
Traps - Procrastination
Students procrastinate instead of doing their
schoolwork. In one study (Day et al. 2000), 32% of
surveyed university students were found to be severe
procrastinators — meaning that their procrastination
had gone from being an annoyance to an actual problem
— while only 1% claimed that they never procrastinated
at all.
Getting Over Procrastination - New Yorker - 22 July 2014
12.38
38
Behavioural Traps - Delay
Traps - Procrastination
Employees procrastinate instead of taking care of their
office tasks.
D'Abate and Eddy (2007) in a survey found the average
employee spends about an hour and twenty minutes each
day putting off work. That time, in turn, translates to a
loss of about nine thousand dollars per worker per year.
In the study, about a quarter of surveyed adults
reported that procrastination was one of their defining
personality traits. In addition to Americans, the sample
included Europeans, South Americans, and Australians.
12.39
39
Behavioural Traps - Delay
Traps - Procrastination
About 95% of people who procrastinate wish they could
reduce that tendency (O'Brien 2002); and, as Steel
(2012) writes in his book, “The Procrastination
Equation,” procrastination leads to lower over-all wellbeing, worse health, and lower salaries. To test the
notion of procrastination directly, a study of three
hundred and forty-seven pairs of same-sex identical
(monozygotic) and fraternal (dizygotic) twins from the
Colorado Longitudinal Twin Study was conducted
(Gustavson et al. 2014).
The Procrastination Equation - Steel - Psychology Today 2014
12.40
40
Behavioural Traps - Delay
Traps - Procrastination
The study had been ongoing since the twins’ birth, in the
nineteen eighties, and had already yielded vast amounts of
data on impulsivity, such as whether or not subjects had
trouble initiating difficult tasks. They looked at the
relationship between procrastination and impulsiveness
more closely.
They asked each twin to complete questionnaires measuring
procrastination, impulsivity, and goal management, so that
they could evaluate the extent to which those
characteristics and behaviours are genetically, as opposed
to environmentally, determined. The researchers found
that each trait was moderately heritable: about 46% of
the tendency to procrastinate, and 49% of the tendency
12.41
41
toward impulsiveness, was attributable to genes.
1.42
42
Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
12.43
43
Behavioural Traps Ignorance Traps
Ignorance traps operate differently.
In these traps, the negative consequences of
behaviour are not understood or forseen at the
outset.
12.44
44
Behavioural Traps Ignorance Traps
For example, smokers in the nineteenth century did
not realise that smoking was related to lung cancer,
and if this information had been available, many
people would never have begun to smoke (of course
smoking still has the properties of a time delay trap,
and millions of people continue to be trapped even
though the link with lung cancer is now well known).
12.45
45
Behavioural Traps Ignorance Traps
Sir Richard Doll (Doll and Hill 1954) made history in the
1950’s as the scientist who established beyond doubt
that smoking caused lung cancer. He is revered in the
medical and scientific establishment not only for what he
achieved but the way he achieved it: through painstaking
analysis of the evidence. More recently Sir Richard Doll
and colleagues from Oxford presented findings from the
50 years of follow-up of British doctors in relation to
cancer risk (Doll et al. 2005).
There are many important aspects surrounding this
article, some of which deserve wider and deep reflection.
12.46
46
Behavioural Traps Ignorance Traps
Ignorance traps are common when new life paths are
taken. For example,
college students some times end up specialising in a
field that is not as exciting as initially imagined;
workers some times find themselves trapped in a job
that does not live up to expectations;
lovers some times get involved with partners who are
less appealing than they first seemed to be.
Such traps are an inevitable part of life, though there
are ways to minimise the chances of being trapped
(techniques to reduce or avoid entrapment are discussed
later in the chapter).
12.47
47
Behavioural Traps Ignorance Traps
One particular tragic example of an ignorance trap is
the story of insecticide dependence in American
agriculture.
When synthetic organic insecticides such as DDT
were introduced in the 1940’s, they appeared to be
an effective way to protect crops against insect
damage. Soon after these products became available,
American farmers adopted them as the method of
choice for insect control.
12.48
48
Behavioural Traps Ignorance Traps
Then two unforeseen events occurred:
Birds and other insect predators began to die.
Insects developed a resistance to the chemicals that
were used.
Insect damage began to increase. New insecticides
were invented, but resistant strains of insects
emerged once again.
After 400 hundred million years of evolution, the
insects were not giving up without a fight.
12.49
49
Behavioural Traps Ignorance Traps
For decades this battle has been fought on the
farmlands, yet each new round of chemical weapons
serves only to provoke further pestilence.
The percentage of American crops lost to insects
doubled between the years 1950 and 1974 (Robbins
1987), and according to entomologists at the
University of California, 24 of the 25 most serious
agricultural pests in California are now insecticide
induced or insecticide aggravated (Luck et al. 1977).
Each year, more than 100 million pounds of
insecticides are used in the United States, much to
the detriment of wildlife, vegetation, waterways, and
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50
human safety.
1.51
51
Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
12.52
52
Behavioural Traps Ignorance Traps - PayDay
Payday loans (examples of Investment
Traps) in the United Kingdom are a rapidly
growing industry, with four times as many
people using such loans in 2009 compared
to 2006.
In 2009, 1.2 million people took out 4.1 million loans,
with total lending amounting to £1.2 billion. The average
loan size is around £300, and two-thirds of borrowers
have annual incomes below £25,000. There are no
restrictions on the interest rates payday loan companies
can charge, although they are required by law to state
the effective annual percentage rate (APR).
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Behavioural Traps Ignorance Traps - PayDay
According to Consumer Focus, “the cost of obtaining
a loan online (often £25-£30 [per month] per £100)
exceeds the costs of obtaining a loan on the High
Street (often £13-£18 per £100)” because the
lenders reject fewer applicants and face higher
rates of fraud and default.
Marie Burton, Consumer Focus, Keeping the plates spinning:
Perceptions of payday loans in Great Britain
12.54
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Behavioural Traps Ignorance Traps - PayDay
In 2009, the payday loan industry generated around
£242m in revenue - around 20% of the total lending.
The largest lender is Dollar Financial Group (which
includes The Money Shop and Express Finance),
which provided around a quarter of all payday loans
in 2009. In February 2011 Dollar Financial
additionally acquired the largest British internet
payday lender, PayDay UK, and suggested The
Money Shop's network could grow from around 350
shops to around 1200.
If you have financial problems contact our own Student Financial
Support Fund.
US payday loan firms plan rapid expansion in cash-strapped Britain | 11 February 2011 | The Guardian 12.55
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Behavioural Traps Ignorance Traps - PayDay
As the BBC (25-11-2013) report Payday lenders are
facing a cap on the cost of their loans, under new
government plans.
An official study in 2010 said they provided a
legitimate, useful, service that helped to cover a
gap in the market.
But in early 2013, the Office of Fair Trading said
that there was widespread irresponsible lending in
the industry.
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Behavioural Traps Ignorance Traps - PayDay
And by the end of the year, the government said
there was “growing evidence” in support of a cap on
the cost of a loan, including the fees and interest
rates.
Why borrowing £400 can cost from £3 to £130 - Telegraph 30 Jan 2014
12.57
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Behavioural Traps Ignorance Traps - PayDay
New rules being brought in to clean up the payday lending
industry may result in the eradication of specialist high street
lenders altogether, the head of the Financial Conduct
Authority has admitted as he outlined a radical shake up of
the controversial industry.
Payday lenders will be forced to limit charges on loans under
tough new rules set by the UK’s financial regulator on
Tuesday. A cap will apply from January next year (2015) to
ensure daily charges for interest and fees do not exceed 0.8%
of the loan amount.
New rules could wipe out payday lenders - FT - 11 Nov 2014
Use the up-to-date list to compare different loans.
12.58
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Behavioural Traps Ignorance Traps - PayDay
Using the BBC (3-12-2013) monthly PayDay interest rate
calculator with an APR of 4670% on a loan of £250.
12.59
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Behavioural Traps Ignorance Traps - PayDay
Under-fire FCA spells out its targets for the year ahead | The Guardian | 31-3-2014
A review of how firms can prevent traders manipulating key benchmarks in a bid to stop
a new Libor scandal and an investigation into how lenders treat borrowers who have
fallen behind on repayments are among the City regulator's plans for the year ahead.
The FCA takes over regulation of the consumer credit sector on Tuesday, and it also
outlined plans for a review of how struggling borrowers are treated by the industry, and
how loans are advertised.
It has already signalled that it plans to get tough on the payday lenders that offer
short-term loans at high interest rates, with new restrictions set to come into force in
July, and it said it planned to visit the top five firms to check they are following the
rules.
Wheatley said: “Taking on the regulation of consumer credit is an enormous task which
effectively doubles the number of firms we regulate.”
“Using our new power we want to tackle harm to consumers who are most at risk and our
work will focus on protecting vulnerable consumers.”
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Behavioural Traps Ignorance Traps - PayDay
Britain’s crackdown on payday lending is forcing a mass exodus from the quick credit
market, with up to half the lenders pulling out in the past 18 months.
A Financial Times analysis of data from the Financial Conduct Authority found that at
least a third of the UK’s 210 payday lenders had failed to apply for permission to
operate under the new regulatory regime introduced last month.
That was on top of about 30 lenders that had surrendered licences or had them revoked
by the Office of Fair Trading (OFT) since the end of 2012. The OFT said in 2012 that
about 240 lenders were operating in the market.
Tougher UK rules drive payday lenders away - FT - 22/5/2014
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Behavioural Traps Ignorance Traps - PayDay
A cap on charges that payday loan companies levy on customers came into effect on
Friday, putting new constraints on the industry’s profitability.
Regulations imposed by the Financial Conduct Authority mean customers taking out a loan
will now never need to pay back more than twice the amount they borrowed. Interest and
fees charged must not exceed 0.8% a day on the sum lent.
If borrowers default, charges must not be greater than £15. Companies can continue to
charge interest on the loan after default, but not above the initial rate.
Some lenders such as Wonga have already restructured their rates and fees ahead of
the introduction of the new rules. Others have closed down.
Crackdown on payday loans charges - FT - 2 Jan 2015
Wonga rolls out revamped payday loans - FT - 19 May 2015
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Behavioural Traps Investment Traps
Cross and Guyer (1980) did not explicitly include
investment traps in their taxonomy, but this type of
trap has recently become the topic of a great deal of
research.
Investment traps occur when prior expenditures of
time, money, or other resources lead people to make
choices they would not otherwise make.
In the parlance of decision research, these traps
result in “sunk cost effects”.
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Behavioural Traps Investment Traps
This discussion closely follows that of Kahneman
(2011). An ironic example that Thaler (1999) related
in an early article remains one of the best
illustrations of how mental accounting affects
behaviour:
Two avid sports fans plan to travel 40 miles to see a
basketball game. One of them paid for his ticket; the
other was on his way to purchase a ticket when he
got one free from a friend. A blizzard is announced
for the night of the game. Which of the two ticket
holders is more likely to brave the blizzard to see
the game?
What do you think?
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Behavioural Traps Investment Traps
The answer is immediate: we know that the fan who
paid for his ticket is more likely to drive.
A rational decision maker is interested only in the
future consequences of current investments.
Justifying earlier mistakes is not among an
economist’s concerns. The decision to invest
additional resources in a losing account, when better
investments are available, is known as the sunk-cost
fallacy, a costly mistake that is observed in decisions
large and small. Driving into the blizzard because one
paid for tickets is a sunk-cost error.
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Behavioural Traps Investment Traps
Arkes and Blumer (1985) illustrated the effects of
sunk costs in ten different mini-experiments.
In one of these experiments, a group of subjects
were given the following problem:
As the president of an airline company, you have
invested 10 million dollars of the company’s money
into a research project.
The purpose was to build a plane that would not be
detected by conventional radar, in other words, a
radar-blank plane.
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Behavioural Traps Investment Traps
When the project is 90% completed, another firm
begins marketing a plane that cannot be detected by
radar.
Also, it is apparent that their plane is much faster
and far more economical than the plane your company
is building.
The question is: should you invest the last 10% of the
research funds to finish your radar-blank plane, yes
or no?
What would you do?
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Behavioural Traps Investment Traps
Arkes and Blumer found that 85% of their subjects
recommended completing the project, even though
the finished aircraft would be inferior to another
plane already on the market.
Then a second group were given the following
problem.
As president of an airline company, you have received
a suggestion from one of your employees.
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Behavioural Traps Investment Traps
The suggestion is to use the last 1 million dollars of
your research funds to develop a plane that would
not be detected by conventional radar, in other
words, a radar-blank plane.
However, another firm has just begun marketing a
plane that cannot be detected by radar.
Also, it is apparent that their plane is much faster
and far more economical than the plane your company
could build.
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Behavioural Traps Investment Traps
The question is: should you invest the last million
dollars of your research funds to build the radarblank plane proposed by your employee?
What would you do?
Only 17% opted to spend money on the project.
(This version of the problem did not mention prior
investments.)
A sunk cost of $10 million made the difference.
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Behavioural Traps Investment Traps
In another experiment, Arkes and Blumer (1985)
showed that sunk costs could have long lasting
effects.
The subjects in this study were 60 theatre patrons
who approached the ticket window to buy season
tickets for the Ohio University Theatre.
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Behavioural Traps Investment Traps
Unbeknownst to these people, they were randomly
sold one of three tickets
a normal ticket for $15
a ticket discounted by $2
a ticket discounted by $7
Subjects lucky enough to receive discounted tickets
were told that the discounts were part of a
promotion by the theatre.
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Behavioural Traps Investment Traps
Each type of ticket was a different colour, so Arkes
and Blumer (1985) were able to collect the stubs
after each performance and determine how many
subjects attended each play.
For purposes of analysis the theatre season was
divided into two halves, each with five plays that ran
over the course of six months.
Although Arkes and Blumer did not find significant
differences in the second half of the season, they
found that, for the first six months, subjects who
had paid the full ticket price attended more plays
than those who had received a discount (regardless
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of the size of the discount).
Behavioural Traps Investment Traps
Thus, even a paltry $2 difference in investment
continued to influence behaviour for up to six
months.
This study is important for two reasons.
First, it shows that sunk cost effects are not limited
to paper and pencil measures.
Second, it shows that differences in investment can
have relatively enduring effects on behaviour.
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Behavioural Traps Investment Traps
As Fischhoff et al. (1981 p. 13) wrote, “The fact that no
major dam in the United States has been left unfinished
once begun shows how far a little concrete can go in
defining a problem.”
Not the case with Mount
Rushmore. The initial concept
called for each president to
be depicted from head to
waist. Lack of funding forced
construction to end in late
October 1941 with only the
heads completed.
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Behavioural Traps - Investment Traps
Pseudo-Certainty Effect
Investors will limit their risk exposure if they think
their portfolio/investing returns will be positive –
essentially protecting the lead – but they will seek more
and more risk if it looks like they are heading for a loss.
Basically, investors avoid risk when their portfolios are
performing well and could bear more. They seek risk
when their portfolios are floundering and don't need
more exposure to possible losses. This is largely due to
the mentality of winning it all back. Investors are willing
to raise the stakes to “reclaim” capital, but not to create
more capital.
How long would a race car driver survive if he only used
his brakes when he had the lead?
(4 Psychological Traps That Are Killing Your Portfolio - Investopedia) 12.76
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Investment Traps - Avoidance
Hammond et al., 2006
1. Seek out and listen carefully to the views of
people who were uninvolved with the earlier
decisions and who are hence unlikely to be
committed to them.
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Investment Traps - Avoidance
2. Examine why admitting to an earlier mistake
distresses you. If the problem lies in your own
wounded self-esteem, deal with it head-on. Remind
yourself that even smart choices can have bad
consequences, through no fault of the original
decision maker, and that even the best and most
experienced managers are not immune to errors in
judgment. Remember the wise words of Warren
Buffett: “When you find yourself in a hole, the best
thing you can do is stop digging.”
(Warren Buffett 1930- is an American investor, industrialist and
philanthropist. He is widely regarded as one of the most
successful investors in the world.)
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Investment Traps - Avoidance
3. Be on the lookout for the influence of investment
cost biases in the decisions and recommendations
made by your subordinates. Reassign
responsibilities when necessary.
4. Don't cultivate a failure-fearing culture that
leads employees to perpetuate their mistakes. In
rewarding people, look at the quality of their
decision making (taking into account what was
known at the time their decisions were made), not
just the quality of the outcomes.
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Behavioural Traps Deterioration Traps
Deterioration traps are similar to investment traps,
except that the costs and benefits of behaviour
change over time.
These traps – which Cross and Guyer (1980) called
“sliding reinforcement traps” – occur when initially
rewarding courses of action gradually become less
reinforcing and/or more punishing.
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Behavioural Traps Deterioration Traps
The emblematic example of a deterioration trap is
heroin addiction (though heroin addiction can also be
considered a time delay trap and an ignorance trap).
At first, heroin users find the drug enjoyable. In
time, however, they build up a tolerance. Larger
doses are needed to achieve the same feeling and
eventually, heroin users end up taking the drug to
avoid with-drawl symptoms rather than to experience
euphoria. What begins as a pleasant experience turns
into a nightmare of dependence.
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Behavioural Traps Deterioration Traps
Much the same process operates with “insecticide
addiction.” Although the use of insecticides may have
begun as an ignorance trap, it continues in part as a
deterioration trap.
According to a report in BioScience, insecticide
dependence works like this:
There is first a period of variable duration, in which
crop losses to insects are greatly reduced. . . .
Eventually, however, resistance develops in one of
the primary, occasional, or insecticide induced pests.
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Behavioural Traps Deterioration Traps
This problem is met by adding (diversifying) and
changing insecticides, but the substituted materials
. . . are generally more ephemeral and thus must be
applied more frequently to effect the same degree
of control.
At this point, it also becomes difficult if not
impossible for growers to extricate themselves from
the strategy. As they continue to apply insecticides,
their problems magnify (Luck et al. 1977 p. 607).
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Behavioural Traps Deterioration Traps
Its still on-going!
Insecticide regulators ignoring risk to bees, say MPs
Damian Carrington
The Guardian 12-12-2012
A parliamentary inquiry has uncovered evidence that
links widespread use of neonicotinoid pesticides to
decline in bees.
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Behavioural Traps Deterioration Traps
A growing body of scientific evidence has linked the
widespread use of neonicotinoid pesticides on crops
to a serious decline in the bees and other pollinators,
which are vital in producing a third of all food. The
inquiry has uncovered evidence, apparently ignored
by regulators, that the toxic insecticide can build up
in soil to levels likely to be lethal to most insects,
including the bees that overwinter in soil.
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Behavioural Traps Deterioration Traps
Studies strengthen insecticide link to bee population decline - FT - 22 April 2015
Two studies have added powerful scientific evidence to the view
that agricultural pesticides are contributing to a decline in bee
populations across Europe and North America.
One research team in Sweden found that neonicotinoid insecticides
(neonics) reduced wild bee numbers. The other in the UK
(Newcastle) discovered that bees preferred nectar containing
neonics to uncontaminated nectar. Both studies appear in Nature,
the scientific journal.
Neonics have become a cause célèbre for the environmental
movement in its battle against the agrochemical industry. Their
worldwide sales are about $2bn a year, with Bayer of Germany and
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Syngenta of Switzerland the largest producers.
Behavioural Traps Deterioration Traps
Deterioration traps and counter-traps often produce
behaviour that seems absurd or self destructive to
bystanders who have not watched the situation
evolve.
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck skip
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Behavioural Traps Deterioration Traps
In his memoir Skinner (1980 pp. 150-1) described one
example of such behaviour involving Bill and his
truck:
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Behavioural Traps Deterioration Traps
Bill’s truck is his only means of support – like a
fisherman’s boat or a small farmer’s cow and plough
horse. The island salt air, badly maintained roads,
and the abuse of a drunken driver have nearly
finished it.
The windshield is full of small holes with radiating
cracks. The fenders are rusted to thin sheets, bent
and torn. Only fragments of padding remain on the
springs of the seat.
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Behavioural Traps Deterioration Traps
I asked Bill to help bring our boat down the hill. The
truck was parked on a downgrade in front of the
village store. I got in and sat on what was left of the
right side of the seat. Bill gave the truck a push,
jumped in, set the gear, and, as we picked up a little
speed, let in the clutch. A violent jerk, and the motor
began to cough. Bill . . . pumped the accelerator
wildly, keeping his hand on the choke. Satisfied that
the motor was started, he reversed and backed
rapidly to the store to turn around. The truck stalled
across the road.
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Behavioural Traps Deterioration Traps
Three or four of us pushed, including two young men
from a car whose way was blocked. . . . We went
downgrade again, starting and stalling. From time to
time Bill would jump out, open the hood and adjust
something with a wrench. We worked our way a tenth
of a mile in the wrong direction, the engine coughing
and exploding and refusing to race as Bill pumped
gas. Eventually he explained that his starter was in
for repairs. It might come back on the excursion
boat. How would it be if he came up for the boat in a
couple of hours? He did not come. Forty-eight hours
later he was still parking his truck on downgrades. No
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one would tow him anymore.
Behavioural Traps Deterioration Traps
Why does he go on? For one thing there is no
alternative. He drinks away his income . . . [But his]
lack of alternatives is not the whole story. His
zealous preoccupation with the truck is the result of
a [shrinking ratio of reinforcement to effort] . . . Bill
will not take no from the truck.
If it were a horse, he would have beaten it to death
long ago, for it is also the lot of an aging horse to
reinforce the behaviour of its owner on a lengthening
ratio of work per task. Bill’s truck is being beaten to
death too.
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Behavioural Traps Deterioration Traps
To an outside observer who does not know Bill’s
history, his actions may seem ludicrous and bizarre.
Yet the same dynamic operates routinely in
deteriorating social or romantic relationships. When
interpersonal relationships erode gradually over time,
they create a counter-trap in which exiting becomes
extremely difficult.
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Behavioural Traps Deterioration Traps - Facit
Consider the Facit case, for a real
world example. A Swedish firm,
Facit AB, formed in 1920 to make
mechanical calculators and it then
operated with great success for
almost 50 years.
Besides mechanical calculators, it made typewriters and
office equipment like desks and chairs. A few of its
personnel had dreamed of someday making electronic
equipment. Facit’s mechanical calculators contained
approximately 2,300 components that required
specialized machinery to be produced.
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Behavioural Traps Deterioration Traps - Facit
The Facit calculator was arguably one of the most
profitable products in Sweden. Even though Facit’s
performance declined from the mid-1960s, minutes from
board and top management meetings in 1965 and 1966 do
not reveal any concerns. Rather, management seems to
have been occupied with expansion plans.
In 1966, a company forecast was presented to
management projecting that sales of mechanical
calculators would continue to increase 12% annually over
the coming years, which implied that the number of
employees in the calculator business in Atvidaberg would
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increase from 1,060 to 1,830.
Behavioural Traps Deterioration Traps - Facit
Facit made its first entry into electronics in the
1950s when it created the subsidiary Facit
Electronics. Calculators based on individual
transistors started to emerge in the early 1960s.
Did it not see the writing on the wall? It used
electronic calculators to perform quality control on
its manual calculator production lines!
For more details see Sandstrom (2013) or Starbuck
and Nystrom (1997).
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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106
Behavioural Traps Collective Traps
Unlike the previous traps, collective traps involve
more than one party.
In collective traps, the pursuit of individual selfinterest results in adverse consequences for the
collective. A simple example is rush hour traffic.
Hundreds of people prefer to drive at the same time,
but if each person operates according to selfinterest, everyone suffers.
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Behavioural Traps Collective Traps
Collective traps – a close cousin of the “social
dilemma” in mathematical and game theory (Dawes
1980) – have received more research attention than
all the other traps combined.
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Behavioural Traps Collective Traps
The most celebrated example of a collective trap is
the Prisoner’s Dilemma in which two prisoners are
confined in separate jail cells and offered a deal
such as the following.
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma skip
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
12.111
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Behavioural Traps Collective Traps
District Attorney: Listen Billy Boy. We’ve got enough
evidence to send you and your partner up the river
for a year if neither of you confesses.
What we’d really like, though, is to get at least one
confession.
If you confess and your partner doesn’t, we’ll hit
your partner with 10 years and let you go free.
On the other hand if you play it quiet and your
partner comes clean, you’ll be the one who gets 10
years.
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Behavioural Traps Collective Traps
Wild Bill: What if we both confess – will we both get
10 years.
District Attorney: No. In that case, we’ll reward your
honesty with a reduced sentence of 5 years.
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Behavioural Traps Collective Traps
In a standard Prisoner’s Dilemma, both prisoners
face the same choice – a choice in which they are
better off confessing regardless of what their
partner chooses.
If their partner refuses to confess, they are set
free; if not, they are at least protected against a 10year sentence.
The dilemma is that if both prisoners follow their
self-interest and confess, they will each receive a
sentence five times longer than if both keep quiet.
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Behavioural Traps Collective Traps
For a recent paper on the prisoner’s dilemma see
Pothos et al. (2011).
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
12.117
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Behavioural Traps Collective Traps
Another famous collective trap is what biologist
Hardin (1968) dubbed “the tragedy of the commons.”
In the classic version of this trap, a herding
community uses common pastureland to graze cattle.
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Behavioural Traps Collective Traps
At first there is no problem, but in time the number
of cattle reaches the carrying capacity of the land. At
that point, the utility of adding another animal to the
herd has two components – one positive and one
negative.
The positive utility consists of whatever profit can be
made from raising one more animal. This profit belongs
solely to the herder who adds the animal;
the negative utility is a function of the additional over
grazing caused by a new animal. This cost is borne by
all members of the community and is negligible to any
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one herder.
Behavioural Traps Collective Traps
The result is a dilemma in which one person benefits
from adding another animal to the herd, but the
pursuit of individual self-interest leads to an
outcome that is less than ideal.
Hardin likened the tragedy of the commons to
problems such as over population, pollution, global
resource depletion, and the proliferation of nuclear
weapons.
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Behavioural Traps Collective Traps
The tragedy of the commons is similar in many ways
to the infamous “mattress problem,” a collective
counter-trap first described by Schelling (1971).
In the mattress problem thousands of cars on a twolane highway are returning from a weekend on Cape
Cod when a mattress falls into the northbound lane,
unnoticed, from the top of a station wagon. The
question is: Who stops to move the mattress?
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Behavioural Traps Collective Traps
Often times, the answer is that no one does.
People far back in the stream of traffic don’t know
what the problem is and can’t help.
People who are passing the mattress have waited so
long in line that all they can think of is how to get
around it. After such a long wait, the last thing they
want to do is spend another few minutes pulling a
mattress out of the lane.
And those who have already passed the mattress no
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longer have a direct stake in moving it.
Behavioural Traps Collective Traps
The mattress problem resembles the type of
collective counter-trap found in emergency situations
(in which responsibility is diffused and bystanders
are slow to intervene or simply film the outcome).
Leytonstone Tube station stabbing a 'terrorist incident' - BBC News - 6 Dec
2015 “video of the aftermath of the attack has been posted online”
It may also provide a partial explanation for the
political “apathy” so prevalent in the United States.
Unfortunately, as Hofstadter (1985 p. 757) has
succinctly observed “Apathy at the individual level
translates into insanity at the mass level”.
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Behavioural Traps –
Bystander Behaviour
Darley and Latané (1968) ran a series of experiments in
the late 1960s. The most famous exercise took place in a
room into which smoke could be piped.
Research participants were taken inside, where they
might be left alone; with two other participants; or with
two researchers masquerading as participants oblivious
to the incoming smoke. The majority of participants
(75%) who were alone in the room reported the smoke;
by contrast, only 10% of those in a room with two
seemingly unobservant researchers reported it.
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Behavioural Traps –
Bystander Behaviour
Darley and Latané attributed this to two factors: one
was the “diffusion of responsibility effect”, where the
presence of others leads individuals to assume that
someone else will help or already has. The other factor
was “the power of social norms”; in which people observe
others’ reactions to evaluate the severity of a situation.
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Behavioural Traps –
Bystander Behaviour
Darley et al. (1973) note that previous studies of
bystander intervention in emergencies have found that
an individual is more likely to intervene if he witness the
emergency alone than as a member of a group. In a
study with 50 male undergraduates, pairs of students
working on a task overheard a loud crash in an adjoining
room. Some pairs of students were seated in a pattern
that facilitated the visual communication exchanges
that naturally occur when a noisy event takes place and
others were seated so as to block these
communications.
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Behavioural Traps –
Bystander Behaviour
When the emergency occurred, groups which could
exchange reactions were not reliably less likely to
respond than were a third group of students who faced
the emergency alone. The blocked communications
groups tended not to respond and responded
significantly less than the other 2 conditions. Results
support the hypothesis that a group of people who
witness an ambiguous event interact to arrive at a
definition or interpretation of it, which then guides
each member's reactions to the event.
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Behavioural Traps –
Bystander Behaviour
Levine et al. (1994) evaluated “helping behaviours” in
cities all over the world. In each city, Levine and his
team have run a series of experiments in which
bystanders have the opportunity to help or not help a
stranger. In one experiment, for example, researchers
feigned a leg injury and dropped a large pile of
magazines, in view of a passing pedestrian, and visibly
struggled to bend over and pick them up.
Rankings were obtained on a number of criteria for 36
US cities, the most helpful was Rochester (NY) and the
least Patterson (NJ).
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Bystander Behaviour
Two experiments (Levine et al. 2005) exploring the effects of
social category membership on real-life helping behaviour were
reported.
In Study 1, inter-group rivalries between soccer fans are used to
examine the role of identity in emergency helping. An injured
stranger wearing an in-group team shirt is more likely to be helped
than when wearing a rival team shirt or an unbranded sports shirt.
In Study 2, a more inclusive social categorisation is made salient
for potential helpers. Helping is extended to those who were
previously identified as out-group members but not to those who do
not display signs of group membership.
Taken together, the studies show the importance of both shared
identity between bystander and victim and the inclusiveness of
salient identity for increasing the likelihood of emergency
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intervention.
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Behavioural Traps – Herd
Behaviour
Modern psychological and economic research has
identified herd behaviour in humans to explain the
phenomena of large numbers of people acting in the
same way at the same time.
For example, stock market bubbles, large stock market
trends often begin and end with periods of frenzied
buying (bubbles) or selling (crashes) (Lee and Ahn 2015).
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Behaviour
What is a bubble? It cannot exist in rational markets
because bubbles imply deviations of prices from intrinsic
values. A positive bubble in a security exists when its
price is higher than its intrinsic value. Whereas a
negative bubble exists when its price is lower than its
intrinsic value.
Bubbles can persist in unbeatable markets if investors
are unable to exploit them for excess returns because,
for example, digging for information about intrinsic
values is difficult. Trading on such information is costly,
and risk which is embedded in necessarily imprecise
estimations of intrinsic values can bring losses (Shefrin
and Statman 2012).
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Behavioural Traps – Herd
Behaviour
Many observers cite these episodes as clear examples of herding
behaviour that is irrational and driven by emotion –
greed in the bubbles,
fear in the crashes.
Individual investors join the crowd of others in a rush to get in or
out of the market (Brunnermeier 2001). One of the distinctive
features of the start of this century was the formation and
collapse of two financial market bubbles – one in internet stocks
and a second in the housing and mortgage finance system.
The Bank of England has said it is poised to take fresh steps to
slow down Britain's housing market if the pickup in prices and
mortgage demand threatens a new property bubble.
Bank of England poised to act over house price momentum | The Guardian | 27/3/2014. 12.136
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Behaviour
London house prices rose 18% in a year (2013/4) fuelling fears of a
bubble. Nationwide's figures put London house prices above pre-crisis
peak at an average £362,699, as gap widens with rest of UK.
House prices in London have increased by almost a fifth over the past
12 months, and are now 20% above their pre-crisis peak, according to
the latest data from the country's biggest building society.
In news that will fuel concerns of a price bubble in the capital,
Nationwide Building Society said the average price of a London home
had increased by 18% over the year and by 5.3% in the past three
months alone, and at £362,699 was now more than twice the figure
for the rest of the UK.
London house prices rise 18% in year fuelling fears of bubble | The Guardian |
1/5/2014 also see Later Slide (Bank of Mum and Dad).
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Behaviour
Bank of England deputy (Cunliffe) argues it would be “dangerous to ignore
the momentum that has built up in the UK housing market”. Surging house
prices pose the single biggest threat to UK financial stability.
Cunliffe, who is in charge of financial stability at the Bank, suggested
that it might have to take radical steps to curb the recent housing boom,
which could include introducing a cap on how much Britons can borrow.
Surging house prices pose the single biggest threat to UK financial
stability, the deputy Governor of the Bank of England has warned.
Cunliffe said that policymakers must decide quickly whether to take
action to cool the market and, in the starkest warning yet that rapid
price rises could derail Britain’s recovery, argued that it would be
“dangerous to ignore the momentum that has built up in the UK housing
market”.
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Behaviour
Price rises have not been limited to London and “pent-up demand”
could “add significantly to pressure on the market for the next few
years.” “All of this paints a picture of further pressure on
transactions that could take us quickly to pre-crisis rates,” he said.
Dangerous to ignore house price boom warns BoE deputy | Telegraph |
1/5/2014
Jon Cunliffe, Threadneedle Street's deputy governor for financial
stability, said it would be dangerous to ignore the momentum
apparent across the country and dropped strong hints of new
measures to slow down the market in the months ahead.
Bank of England warns housing market boom may turn to crash | The Guardian
| 1/5/2014
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Behaviour
The behavioural finance literature is full of examples of
measurable stock price distortions. It would seem easy to
build superior performing portfolios, but doing so would
mean taking positions that are opposite to the crowd.
The powerful need for social validation acts as a strong
deterrent for many investors, discouraging them from
pursuing such an approach. It is tough to leave the
emotional crowd and become behavioural-data investors.
Though we find price distortions to be measurable and
persistent, building a portfolio benefiting from them is
emotionally challenging (Howard 2013).
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Behavioural Traps – Herd
Behaviour
Hey and Morone (2004) analysed a model of herd
behaviour in a market context. Their work is related
to at least two important strands of literature.
The first of these strands is that on herd behaviour
in a non-market context. Private information that is
not publicly shared.
The second of the strands is that of information
aggregation in market contexts. Uninformed traders
in a market context can become informed through
the price in such a way that private information is
aggregated correctly and efficiently.
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Behaviour
For strand 1, the seminal references are Banerjee
(1992) and Bikhchandani, Hirshleifer and Welch
(1992), both of which showed that herd behaviour
might result from private information not publicly
shared.
More specifically, both of these papers showed that
individuals, acting sequentially on the basis of private
information and public knowledge about the
behaviour of others, might end up choosing the
socially undesirable option.
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Behavioural Traps – Herd
Behaviour
The second of the strands of literature motivating
this chapter is that of information aggregation in
market contexts.
A very early reference is the classic paper by
Grossman and Stiglitz (1976) that showed that
uninformed traders in a market context could become
informed through the price in such a way that private
information is aggregated correctly and efficiently.
A summary of the progress of this strand of
literature can be found in the paper by Plott (2000).
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Behavioural Traps – Herd
Behaviour
Hey and Morone (2004) showed that it is possible to
observe herd-type behaviour in a market context.
Their result is even more interesting since it refers
to a market with a well-defined fundamental value
(they designed a simplified share market). Even if
herd behaviour might only be observed rarely, this
has important consequences for a whole range of real
markets – most particularly foreign exchange
markets.
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Behaviour
Empirical results are consistent with the notion that
concern about reputation causes herding. Thus,
younger portfolio managers deviate less from
consensus than their older colleagues. Possibly
because they have more at stake in terms of
reputation, as they face a longer working life ahead
(Hong, Kubik, and Solomon, 2000).
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Behavioural Traps – Herd
Behaviour
Experiments with professional stock analysts have also
demonstrated reputational herding.
In one study (Cote and Sanders, 1997), the participants’
task was to predict future returns.
After each prediction, the average prediction was shown
to the participants, giving them an opportunity to adjust
their own predictions. The results showed that
presenting the average prediction had a significant
influence and that the degree of influence was related to
the participants’ perceptions of their own ability and
motivation to create or maintain a good reputation. 12.146
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Behavioural Traps – Herd
Behaviour
Motivated by extant theories of herding behaviour,
Wei et al. (2015) empirically identify contrarian
mutual funds, those trading most frequently against
the crowd. They find that “contrarian funds
generate superior performance both when they trade
against and with the herd”, indicating that they
possess superior private information.
Uncommon Value: The Characteristics and Investment
Performance of Contrarian Funds (Wei et al. 2015)
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Behaviour
Furthermore, contrarians do not trade in a
particularly correlated fashion with each other.
Consistent with these funds having disparate
information. The fund-level contrarian measure is
largely unrelated to existing measures of fund
strategy uniqueness, as both contrarian and herding
funds score highly on such measures.
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Behaviour
Contrarian investment funds far outperform their
herd-fund rivals in several performance
measurements. Research suggests, that their
managers have found ways to gather information
that other managers have not figured out.
Wei et al. 2015 also Zig while others zag for more successful
investments - ScienceDaily - 13 Nov 2015
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1.150
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Emotional Crowds Or
Behavioural-Data Investors
Behavioural portfolio management, a concept within
the broader paradigm of behavioural finance.
Assumes most investors make decisions based on
emotions and shortcut heuristics (see lecture 1).
Behavioural portfolio management posits that there
are two categories of financial market participants:
emotional crowds and behavioural-data investors.
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Emotional Crowds Or
Behavioural-Data Investors
Emotional crowds are made up of investors who base
decisions on anecdotal evidence and emotional
reactions to unfolding events. Human evolution
hardwires us for short-term loss aversion and social
validation, which are the underlying drivers of
today’s emotional crowds (Howard 2013).
Emotional investors make their decisions based on
what Kahneman (2012) refers to as System 1
thinking: automatic, loss-avoiding and quick, with
little or no effort and no sense of voluntary control.
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Emotional Crowds Or
Behavioural-Data Investors
On the other hand, behavioural-data investors make
their decisions using thorough and extensive analysis
of available data. Behavioural-data investors use
what Kahneman (2012) refers to as System 2
thinking: effortful, high-concentration and complex.
Behavioural portfolio management is built on the
dynamic interplay between these two investor groups
(Howard 2013).
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1.155
155
Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
12.156
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Behavioural Traps – Herd
Behaviour
Peer-to-peer lending (also known as person-to-person
lending, peer-to-peer investing, and social lending;
abbreviated frequently as P2P lending) is the
practice of lending money to unrelated individuals, or
“peers”, without going through a traditional financial
intermediary such as a bank or other traditional
financial institution. This lending takes place online
on peer-to-peer lending companies' websites using
various different lending platforms and credit
checking tools.
Peer-to-peer lending - Wikipedia
12.157
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Behaviour
The results of an empirical study (Dholakia and
Soltysinski, 2001) provide evidence of strategic
herding behaviour by lenders such that they have a
greater likelihood of bidding on an auction with more
bids (a 1% increase in the number of bids increases
the likelihood of an additional bid by 15%), but only to
the point at which it has received full funding.
After this point, herding diminishes (a 1% increase in
bids increases the likelihood of an additional bid by
only 5%).
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Behaviour
They also found a positive association between
herding in the loan auction and its subsequent
performance. That is, whether borrowers pay the
money back on time.
Unlike eBay auctions where herding impacts bidders
adversely, their findings reveal that strategic
herding behaviour in P2P loan auctions benefits
bidders, individually and collectively (Dholakia and
Soltysinski, 2001).
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Behaviour
Michal Herzenstein et al. (2011) studied herding
behaviour in peer-to-peer loan auctions. Online Peer-toPeer (P2P) loan auctions enable individual consumers to
borrow and lend money directly to one another.
They studied herding behaviour, defined as a greater
likelihood of bidding in auctions with more existing bids,
in P2P loan auctions on Prosper.com.
Unlike eBay auctions where herding impacts bidders
adversely, their findings reveal that strategic herding
behaviour in P2P loan auctions benefits bidders,
individually and collectively.
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Equity income and multi-asset fund managers are adding peerto-peer debt to their portfolios after the launches of two
investment trusts opened up access to the fast-growing sector
through listed shares.
Managers of F&C and Axa Investment have been attracted to
peer-to-peer by annual target yields of six to eight per cent,
combined with a perceived low correlation with other asset
classes.
They see potential for long-term growth in the sector, in which
consumers and institutions lend directly to individuals or
businesses through online platforms.
Fund managers turn to P2P - FT - 6 May 2015
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Behavioural Traps – Herd Behaviour
It must be succeeding, if its being copied.
Six months ago Goldman Sachs was a lead underwriter on the
initial public offering of Lending Club, the biggest and brashest
of a new breed of online lenders. Now the Wall Street titan is
looking to disrupt the disrupters, launching its own web-based
business offering loans to consumers and small businesses.
Rather than using a peer-to-peer model — matching borrowers
and investors through the online platform — Goldman will look to
fund loans directly via its New York State-chartered banking
subsidiary, which was set up after Goldman became a bankholding company in the wake of the 2008 financial crisis. To
date, the unit — with $128bn in assets at the end of March —
has mostly provided loans to private clients and institutions.
Goldman joins online lenders’ club - FT - 16 June 2015
12.162
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Behaviour
Growth in peer-to-peer lending passed a new milestone this
week. Data revealed that platforms such as Zopa, RateSetter
and Funding Circle lent out more than £500m in the first half
of the year.
The latest figures from the Peer-to-Peer Finance Association
show the nascent industry’s expansion is picking up speed, with
lending on track to hit a record £1bn in 2014.
More than 66,000 individuals have lent money through these
platforms to entrepreneurs and businesses such as start-up
airlines or wind turbine projects, in return for high rates of
interest at around 6%.
Peer-to-peer lending: the risks and rewards - FT - 4 Aug 2014
Lending services revolution piles pressure on banks as fintech sector grows - FT - 8 Dec 2015
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Behaviour
Consumers from lower income groups look set to be the big beneficiaries of the
peer-to-peer rental market generated through the sharing economy, according
to the latest research from professors at New York University (NYU).
Peer-to-peer rental — of houses or cars, for example — has grown in popularity
in recent years as an alternative to outright purchase. One of the things the
research set out to determine was how these developments changed people’s
modes of consumption, says Arun Sundararajan, professor of information,
operations and management sciences at NYU Stern, and one of the two
researchers on the preprint.
The research focused on peer-to-peer rental in the car market in San
Francisco, where 10% of the population rent cars through the sharing economy.
Some of the findings were to be expected, says Prof. Sundararajan — only a
fraction of the population stopped buying and started renting instead, for
example.
Sharing economy benefits lower income groups - FT - 27 April 2015
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Behavioural Traps – Herd
Behaviour
Crowd funding (alternately: crowdfunding, crowd
financing, equity crowdfunding) (Prpića et al. 2015) is
a process in which web sites provide Internet
platforms which support the collective cooperation,
attention and trust by people who network and pool
their money and other resources for projects
initiated by other people or organizations.
Comparison of crowd funding services – Wikipedia
One in five UK crowdfunding investments fail - FT 19 Nov 2015
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Behavioural Traps – Herd
Behaviour
While crowdfunding is usually aimed at start-ups and
asks backers to invest to get an idea off the ground,
P2P is usually directed at businesses that have been
around for at least a few years.
Crowdfunding and peer-to-peer lending: How start-ups learnt to work a
crowd, Independent, 6 April 2013 includes two interesting case studies. Of
course there is a cost P2P providers urged to come clean on fees - FT - 7
Sept 2015.
Popular capitalism or the madness of crowds - FT - 6 March 2015
A beer or a milkshake? Crowdfunding can bring delicious dividends - The
Guardian - 10 March 2015
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Behaviour
However the following comments from the Financial
Services Authority should be noted.
“We believe most crowdfunding should be targeted
at sophisticated investors who know how to value a
startup business, understand the risks involved and
that investors could lose all of their money.”
“We want it to be clear that investors in a crowdfund
have little or no protection if the business or project
fails, and that they will probably lose all their
investment if it does.”
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Behaviour
We are also concerned that some firms involved in
crowdfunding may be handling client money without
our permission or authorisation, and therefore may
not have adequate protection in place for investors.
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Behaviour
Savers warned of dangers of investing in start-ups through crowdfunding websites as
investors in Bubble & Balm face losing their shirts - Daily Mail - 11 September 2013
Savers who lent money to start-up firm Bubble & Balm on a
crowdfunding website recently learned they could lose all their cash.
THE MINOR INVESTOR: The wisdom of the crowd or herd mentality? Crowdfunding
looks tempting but it pays to tread carefully - Daily Mail - 5 Feb 2015
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Behavioural Traps – Herd
Behaviour
Alternative financing draws in almost £1bn - FT - 13-12-2013
Almost £1bn in loans and equity funding has been
generated through crowdfunding, peer-to-peer
lending and invoice trading, according to a
comprehensive study of the market.
Data compiled by the think-tank Nesta with the
Universities of Cambridge and Berkeley (California),
put the total value of this type of activity – which
relies on online marketplaces bringing together those
who have cash and those who want it to bypass the
banks – at £939m.
The Rise of Future Finance - Nesta - 13/12/2013
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Behaviour
Linked to P2P is the so called “Bank Of Mum And Dad”. However
the Council of Mortgage Lenders (CML 5 June 2013) have published
a worrying report.
Millions of parents are “unable or unwilling” to help their children.
“Deposit constraints loom large in framing people’s perceptions
about their ability to buy a home”. Deposit demand is major worry
for parents and many can't help children.
In 2006, 67% of first-time buyers got on the housing ladder
without financial help from parents - but by last year (2012) this
figure had collapsed to just 36%.
Bank Of Mum And Dad - Council of Mortgage Lenders - News & Views Issue no. 10 - 5 June 2013
Youngsters who need to inherit to buy a house: Half of parents fear their children will never be
able to own their own property - Daily Mail - 21 April 2015
Now it's the 'bank of son and daughter': Parents increasingly turning to children for mortgage
help after 'ageist' lenders turn them down - Daily Mail - 19 May 2015
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Behavioural Traps – Herd
Behaviour
On the other hand, according to the Office For
National Statistics (2013), there has been a large
increase in 20 to 34-year-olds living with parents
since 1996. In 2013, over 3.3 million adults in the UK
aged between 20 and 34 were living with a parent or
parents. That is 26% of this age group.
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Behavioural Traps – Herd
Behaviour
However Nikolaev (2015) found
Living at the parental home past adolescence is
associated with lower life satisfaction.
The negative effect of living at the parental home is
non-linear with age.
The difference in life satisfaction is stronger for
individuals around the ages of 35-45.
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Behaviour
Nearly two million working young adults aged between 20 and 34
years old in England are still living with their parents according
to Shelter, which is urging stronger action to help the “clipped
wing generation” fly the nest.
The charity said data it has taken from the Census shows that
there are 1.97 million people in this age group in England who are
still living with their parents, accounting for one quarter of all
young adults in employment.
A survey commissioned by the charity also found that nearly half
(48%) of 250 young adults who live with their parents said they
do so because they cannot afford to rent or buy their own home.
'Clipped wing generation' still live with mum and dad - Telegraph
- 29/7/2014
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Behaviour
More children in the Western world are staying at
home longer, but their parents often pay the price as
tensions flare and conflict damages relationships, an
international literature review shows. The study,
conducted by researchers at the University of
Melbourne, concluded that the changing nature of
family living situations often led to avoidable conflict.
Boomerang families and failure-to-launch: commentary on adult
children living at home.
Katherine Burn, Cassandra Szoeke.
Maturitas, 2016; DOI: 10.1016/j.maturitas.2015.09.004
More young adults are failing to launch or 'boomerang' home,
study shows - ScienceDaily - 12 Nov 2015
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Behaviour
Average house price in England could double in next decade, report
says. Research by Shelter and KPMG shows a radical new
housebuilding programme is needed to provide nearly 250,000 new
homes a year.
The average price of a house in England could double in the next
decade and hit more than £900,000 by 2034, unless there is a
radical new house building programme to provide nearly a quarter of
a million new homes a year, a report claims today.
Research by the housing charity Shelter and consultancy firm KPMG
suggests that more than half of those aged 20-34 could be living
with their parents by 2040 as rising housing costs lock them out of
the property market.
Average house price in England could double in next decade, report says - The
Guardian - 1/5/2014
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Behaviour
Parents with adult children still living at home are typically spending
£1,200 a year more on items such as groceries and bills than those
whose offspring have flown the nest, according to a new report.
It claimed some “full nesters” were putting their own financial
futures at risk as a result of having to provide room and board for
grown-up children at a time when they would prefer to be focusing on
preparing for their old age.
The findings are contained in a report called Meet the Full Nesters,
published by the Centre for the Modern Family, a think tank set up
three years ago by the insurer Scottish Widows.
Parents with adult children at home putting financial future at risk –
Guardian - 22/Oct/2014
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Behavioural Traps – Other
Sources
Owners of young businesses often have an abundance of ideas and
enthusiasm, but a shortage of cash. A loan seems like the most
logical answer, right?
That would be the case if loans were given out like candy, but
unfortunately, small business loans are still a challenge to come by.
Alternative lending options exist, but those come with downsides too.
So, many default to borrowing money from more financially stable
friends and family.
But does a friends and family loan always make sense? Is there any
situation that it actually works out for every one involved?
Why It’s So Hard to Succeed With Friend or Family Loans Business.com - 11 June 2015
12.178
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Behavioural Traps – Other
Sources
New research shows what many people can guess intuitively: Lending
money can cause negative effects on the relationships between
people who borrow and people who lend.
According to an article in the Boston Globe (26 July 2012), Dezső
and Loewenstein (2012) say that their investigation into the impact
of personal loans on people’s feelings “is the first to academically
study the consequences of personal loans between friends, coworkers, siblings, and cousins.” They found “that borrowers have a
blind spot when it comes to recognising the negative feelings and
perceptions evoked in lenders by delinquent loan repayment”.
With Personal Loans, Lenders Have "Blind Trust" and Borrowers Have
"Blind Spots" - MIT Sloan Review - 26 July 2012
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Behavioural Traps – Other
Sources
Dezső and Loewenstein (2012) surveyed 971 individuals about their
experiences with personal loans. Beyond the objective
characteristics of the loans (e.g., whether interest was charged), and
the purpose of the loan, they tested – and found support for – two
main predictions:
(1) that recall and evaluation of loans would be subject to a selfserving bias such that borrowers would, for example, recall
having paid back a larger proportion of the loan
(2) that loans, and particularly those not paid off by the agreed upon
date, would have pernicious effects on the personal relationship
between lender and borrower.
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1.181
181
Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
12.182
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Behavioural Traps – Herd
Behaviour
An example of a
P2P auction
Funding Circle
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Behavioural Traps – Herd Behaviour
An example of a
P2P auction
Funding Circle
12.184
184
1.185
185
Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Behavioural Traps – Herd
Behaviour
Some Examples Of Bubbles
Tulip mania (1637)
Mississippi Company (1720)
Encilhamento (“Mounting”) (1886–1892)
Roaring Twenties stock-market bubble (19221929)
Japanese asset price bubble (1980s)
The Dot-com bubble (1995–2000)
Australian first home buyer (FHB) property
bubble (2009)
British property bubble (2006)
United States housing bubble (2007)
Spanish property bubble (2006)
Romanian property bubble (2008)
South Sea Company (1720)
Railway Mania (1840s)
Florida speculative building bubble (1926)
Poseidon bubble (1970)
Asian Financial Crisis (1997)
Real estate bubble (2000s)
Indian property bubble (2005)
Irish property bubble (2006)
The former Florida swampland real estate bubble
(2007)
China stock and property bubble (2007)
Uranium bubble (2007)
source and links
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Behavioural Traps – Herd
Behaviour – Bubble Examples
For instance
The Rhodium bubble of 2008 (increase from
$500/oz to $9000/oz in July 2008, then down to
$1000/oz in January 2009)
Exotic Livestock production in North America (i.e.
llamas, ostriches, white tail deer, elk, wild boar, and
to a lesser extent bison) and the U.K. (i.e. ostrich
eggs, ostriches, llamas, wild boar and emu eggs).
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Behavioural Traps – Herd
Behaviour – Bubble Examples
Higher education bubble (1980–Present) the steep
increase of tuition and other costs at colleges and
universities, and a possible future collapse.
The expansion of higher education raises the risk
environment for school-leavers, as more occupations
become partially graduate with the result that
occupational signals are fuzzy. It is shown that a rising
proportion of graduates receive only average pay, thus
raising the risks associated with educational investments
even further.
Malcolm Brynin, “Individual Choice and Risk: The Case of Higher Education”
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Sociology April 2013 47(2) 284-300.
Behavioural Traps – Herd
Behaviour – Bubble Examples
The earnings of recent English graduates have
deteriorated so rapidly since the financial crisis that the
latest class is earning 12% less than their pre-crash
counterparts at the same stage in their careers. They
also owe about 60% more in student debt.
Graduate data reveal England’s lost and indebted
generation - FT - 18 November 2013
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Behavioural Traps – Herd
Behaviour – Bubble Examples
As Britain starts to emerge from the downturn, a
Financial Times analysis of student loan data exposes the
damage done to a generation of graduates, for whom a
degree has all but ceased to be a golden ticket to a
decent job. Tuition fees in England almost tripled last
year to a maximum £9,000 a year.
Graduate data reveal England’s lost and indebted
generation - Financial Times - 18 Nov 2013
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Behavioural Traps – Herd
Behaviour – Bubble Examples
Nearly three-quarters of UK students will fail to clear
their student loans before they are written off after 30
years, and the large majority will still be paying off their
loans well into their forties and early fifties, according to
new research for the Sutton Trust by the Institute for
Fiscal Studies (IFS) published today.
The research by Crawford and Jin of IFS sets out in
detail, for the first time, the full implications for
graduates of the new student loan system which
accompanied the higher tuition fees introduced in 2012.
Payback Time? Student debt and loan repayments: what will the 2012
reforms mean for graduates? - Sutton Trust - 10 April 2014
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Behavioural Traps – Herd
Behaviour – Bubble Examples
The trebling of UK university tuition fees has resulted in a highly
uncertain future for higher education funding and produces just a 5%
saving for the taxpayer, research shows.
A report, published on Thursday by the Institute for Fiscal Studies
think-tank, calculated that for every £1 loaned by the government to
students to cover fees and maintenance, 43p will not be recouped.
The study calculates that each student will be lent an average of just
over £40,000, meaning the amount not recovered will be about
£17,000 a student.
Trebling university tuition fees cuts taxpayer costs just 5%
Helen Warrell, Financial Times, 23 April 2014
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Behavioural Traps – Herd
Behaviour – Bubble Examples
When LaTisha Styles graduated from Kennesaw State
University in Georgia in 2006 she had $35,000 of student
debt. This obligation would have been easy to discharge if
her Spanish degree had helped her land a well-paid job.
Ms. Styles found herself working in a clothes shop and a
fast-food restaurant for no more than $11 an hour.
Frustrated, she took the gutsy decision to go back to the
same college and study something more pragmatic. She
majored in finance, and now has a good job at an
investment consulting firm. Her debt has swollen to
$65,000, but she will have little trouble paying it off!
194
Higher education: Is college worth it? | The Economist | 5 Apr12.194
2014
Behavioural Traps – Herd
Behaviour – Bubble Examples
On the plus side, new figures from the UK Office for National
Statistics suggest.
One in five graduates now go on to become millionaires.
Only 3% of millionaires have no formal qualifications.
20% of all adults who hold at least one university degree — more
than two million people — now have wealth totalling at least
£1 million.
Almost a tenth of all British adults now own assets — property,
pensions, savings and physical objects — worth £1 million or more.
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Behavioural Traps – Herd
Behaviour – Bubble Examples
More recently, there were two bubbles, the first
emerged in technology, media and telecommunications
stocks – the so-called internet or Nasdaq craze of the
late 1990s.
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Behavioural Traps – Herd
Behaviour – Bubble Examples
The second occurred in 2008 when the mortgage
financing system (Fannie Mae and Freddie Mac are
government sponsored enterprises that purchase
mortgages, buy and sell mortgage-backed securities, and
guaranteed nearly half of the mortgages in the U.S.) and
was characterised by a rapid rise in housing prices,
surging household and financial system debt levels and a
subsequent retrenchment in prices and housing finance.
The collapse of the mortgage bubble was associated with
the worst economic downturn since the 1930s.
Federal takeover of Fannie Mae and Freddie Mac - Wikipedia
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Behavioural Traps – Herd
Behaviour – Bubble Examples
For a little more on Fannie Mae and Freddie Mac
(2000’s) and the Libor scandal (2010’s), refer back to
chapter 5.
Housing bubble brewing – prices are now unaffordable for middle earners, says
Business Secretary Vince Cable - The Independent - 4 Apr 2014
Despite Fannie Mae’s Bulk Sales Of NPLs, Number Of Delinquent Loans Remains
High - ValueWalk - 7 Dec 2015 (NPL – NonPerforming Loan!)
Other goods which have produced bubbles include
postage stamps (1970’s) and coin collecting (2010’s –
linked to the bullion bubble), obviously any collecting
craze can cause a bubble, even in the playground.
Stamps: China’s next bubble? - FT - 2 March 2011
10 Collectible Crazes That Were A Waste Of Money - Business Insider - 31 May 2012
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Behavioural Traps – Herd
Behaviour – Bubble Examples
The first large-scale empirical analysis of online news-seeking
behaviour, has found that people who seek out news and
information from social media are at higher risk of becoming
trapped in a 'collective social bubble' compared to using search
engines (Nikolov et al. 2015).
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Behavioural Traps – Herd
Behaviour – Bubble Examples
Each circle represents a unique website, and its area is
proportional to the number of pages accessed on that website.
(A)Links clicked by a single search engine user.
(B) Links shared by a single Twitter user.
(C) Search traffic generated by a collection of users.
(D) Social media traffic generated by a collection of users.
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Behavioural Traps – Herd
Behaviour – Bubble Examples
In each case, a random sample of 50 links was taken for a period
of one week. These examples illustrate typical behaviours gleaned
from our data. On the left we see more heterogeneous patterns
with search traffic distributed more evenly among several
sources. The patterns on the right are more homogeneous, with
fewer sources dominating most social traffic (Nikolov et al. 2015).
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Bubble Model
Following Utkus (2011) the difference between a
bubble and crash scenario versus the more common bull
and bear phases of a market may be only a question of
degree. In bubbles and crashes, the psychological
biases discussed in the model may simply reach more
extreme levels.
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Bubble Model (Utkus 2011)
Stage
1.
2.
Behavioural heuristics
Characteristics
The initial
Representativeness
Forecasts of future asset values are developed with
forecast
heuristic
embedded errors in statistical inference
Overconfidence
Overconfidence,
Future forecasts become excessively rosy and are
excessive extrapolation
skewed to the positive, especially based on recent
experience
3.
Group
Groupthink, group
Overly optimistic forecasts are widely
transmission/
polarisation
disseminated and lead the group as a whole to
amplification
4.
Recalibration
higher risk-taking levels
Group polarisation
Forecasts are deflated by actual experience and
revised downward rapidly and beyond realistic
values
Explored below
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Bubble Model
Stage
1.
Behavioural heuristics
Characteristics
The initial
Representativeness
Forecasts of future asset values are developed with
forecast
heuristic
embedded errors in statistical inference
In Stage 1, investors develop initial
forecasts of asset prices based on
errors in statistical inference, broadly
captured under the idea of the
representativeness heuristic (where
‘heuristic’ means a decision shortcut).
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Bubble Model
Stage
2.
Overconfidence
Behavioural heuristics
Characteristics
Overconfidence,
Future forecasts become excessively rosy and are
excessive extrapolation
skewed to the positive, especially based on recent
experience
In Stage 2, these forecasts of future
price appreciation become exaggerated.
Overconfidence and excessive
extrapolation of recent positive
experience come into play.
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Bubble Model
Stage
3.
Behavioural heuristics
Characteristics
Group
Groupthink, group
Overly optimistic forecasts are widely
transmission/
polarisation
disseminated and lead the group as a whole to
amplification
higher risk-taking levels
In Stage 3, individual forecasts influence the
behaviour of the group (in this case, the market or
financial system as a whole). Through a process
known as group polarisation, the financial system
takes on higher risk exposures than individual
members would separately agree is prudent.
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Bubble Model
Stage
3.
Behavioural heuristics
Characteristics
Group
Groupthink, group
Overly optimistic forecasts are widely
transmission/
polarisation
disseminated and lead the group as a whole to
amplification
higher risk-taking levels
With Groupthink a particular group begins to feel
invulnerable; it rationalises its behaviour; and it
systematically ignores external and contradictory
sources of information. There is a failure to examine
alternatives, poor information search, and a failure to
work out contingency plans.
Group polarisation is the tendency for a group to make
riskier decisions than individuals alone would make.
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Bubble Model
Survation conducted a careful telephone poll for the 2015 UK election
“the results seemed so out of line with all the polling conducted by
ourselves and our peers that I chickened out of publishing the figures.”
The same thing happened in the days before the 1992 election, another
so-called “surprise” Conservative victory.
Classic examples of the influence of groupthink. This is exactly the same
phenomenon which led to the financial crisis. The influence of the
network of peers becomes so strong that individual judgement is
overridden. “Everyone” knew that mortgage-backed securities were a
licence to print money, “everyone” knew that debt was no longer a
problem in the new economic paradigm. Even the strong willed leaders of
major institutions capitulated in the face of such pressure, no matter
what their private doubts.
Polling errors and the financial crisis: Why groupthink is to blame for
both - City A.M. - 13 May 2015
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Bubble Model
Stage
4.
Recalibration
Behavioural heuristics
Group polarisation
Characteristics
Forecasts are deflated by actual experience and
revised downward rapidly and beyond realistic
values
Finally, in Stage 4, as actual market data begins to
undermine the group’s overconfident forecast of the
future, the group polarisation process plays in reverse,
and the collective market outlook shifts sharply to the
negative.
This is the point at which actual data from the field
causes market participants to begin to question their
too-rosy forecasts and the consensus group opinion. In
particular, it consists of a recalibration of the overly
optimistic group forecasts based on the actual
observed data in the economy and financial markets.12.211
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Behavioural Traps - How Much
Would You Pay For A Dollar?
One of the best-known behavioural traps in
psychological research is the dollar auction game – a
game that combines the features of a collective trap,
and an ignorance trap.
In this game, invented by Shubik (1971), a dollar bill
is auctioned to the highest bidder. As outlined by
Platt (1973), the dollar auction game has four simple
rules:
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Behavioural Traps - How Much
Would You Pay For A Dollar?
1.
No communication is allowed among bidders while the auction is
taking place.
2. Bids can be made only in multiples of 5 cents, beginning with a
nickel.
3. Bids must not exceed $50 (to protect bidders from wild
enthusiasm).
4. The two highest bidders both have to pay what they bid, even
though the dollar goes only to the highest bidder (after all, the
auctioneer has to recover expenses some how).
Lets play!
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Behavioural Traps - How Much
Would You Pay For A Dollar?
Although the game sounds innocent enough, there are
two “points of no return” worth noting.
The first one comes when the two highest bids
cumulatively exceed $1, thereby assuring the
auctioneer of a profit (e.g. when one person bids 50
cents and another bids 55 cents). At this point, the
auction still seems attractive from a bidders point of
view (a dollar bill in return for 55 cents), but the
pursuit of individual self-interest has already
ensnared a collective loss to the bidders.
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Behavioural Traps - How Much
Would You Pay For A Dollar?
The second slippery slope appears with the first bid
above $1.
Why might people bid more than $1 for a dollar bill,
consider the predicament of someone who has just
bid 95 cents, only to have someone else bid $1.
What would you do in such a situation? If you quit at
that point, you are sure to lose 95 cents. On the
other hand, if you bid $1.05 and win the dollar, you
lose only a nickel. The problem is that the person you
are bidding against faces the same situation.
And as a result, the bidding often reaches a few
dollars.
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Behavioural Traps - How Much
Would You Pay For A Dollar?
One reason the dollar auction game has received so
much attention is that it resembles the nuclear arms
race and other international conflicts (Costanza
1984).
In 1980 Teger published an entire book (Too Much
Invested To Quit) devoted to research on the dollar
auction game, and many of his conclusions are
directly applicable to military conflict.
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Behavioural Traps - How Much
Would You Pay For A Dollar?
According to Teger subjects are usually motivated
initially by personal gain, but in time their motivation
changes.
As the bidding continues, subjects become concerned
with winning the competition, saving face, minimizing
losses, and punishing their opponent for getting them
into such a mess (typically, only two bidders remain
active in late stages of the trap).
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Behavioural Traps - How Much
Would You Pay For A Dollar?
Teger found that when the bidding approached $1,
both sides felt they were being forced by the other
bidder to continue, and many subjects thought the
other person was crazy to continue – without seeing
that identical forces were operating on both
participants.
This “mirror image” is strikingly reminiscent of the
nuclear arms race.
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1.221
221
Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep! skip
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Behavioural Traps - Knee
Deep In The Big Muddy
Once bidders in the dollar auction game are caught –
“knee deep in the big muddy,” as Staw (1976) puts it
– they usually continue clobbering each other before
someone finally gives up.
Brockner and Rubin (1985 p. 5) refer to this dynamic,
as “entrapment” defined as “a decision making
process whereby individuals escalate their
commitment to a previously chosen, though failing,
course of action in order to justify or ‘make good on’
prior investments.”
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Behavioural Traps - Knee
Deep In The Big Muddy
One of the first studies of entrapment was
conducted by Staw (1976). Staw presented business
students with a hypothetical but richly detailed
scenario concerning a high-tech company that had
begun to lose money, and he asked them to assume
the role of Financial Vice President.
According to the scenario, the company’s directors
have decided to pump $10 million of additional
research and development funds into one of the two
largest divisions – Consumer Products or Industrial
Products.
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Behavioural Traps - Knee
Deep In The Big Muddy
In Part 1 of the study, half the students were asked
to choose which division should receive the additional
funding.
Roughly half the students were then told that the
chosen division outperformed the unchosen division
over the next five years (i.e., that the choice had
yielded positive consequences), and roughly half were
told the reverse (i.e., that the choice had yielded
negative consequences).
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Behavioural Traps - Knee
Deep In The Big Muddy
In Part 2 of the experiment, students learned that a
re-evaluation by company managers had led to the
allocation of an additional $20 million for research
and development, and they were asked to split this
amount between the consumer and industrial divisions
in any way they saw fit.
What Staw (1976) found was entrapment – the
escalation of commitment to a failing course of
action.
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Behavioural Traps - Knee
Deep In The Big Muddy
Students who were personally responsible for an
initially unsuccessful choice allocated an average of
approximately $13 million to the previously chosen
division – about $4 million more than the allocation
made by other students. When responsibility was
high, failure produced greater investment, not lesser
investment.
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Behavioural Traps - Knee
Deep In The Big Muddy
Is this a good plot?
Note the
false origin!
The following
plot is clearer.
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Behavioural Traps - Knee
Deep In The Big Muddy
14
Millions of dollars allocated
12
10
8
Positive consequences
Negative consequences
6
4
2
0
Low responsibility
High Responsibility
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Behavioural Traps - Knee
Deep In The Big Muddy
Staw’s (1976) experiment stimulated a great deal of
subsequent research, and since the time of his study,
several theoretical analyses of entrapment have
appeared (two of the best are Brockner and Rubin
1985 and Staw and Ross 1987). Although research on
entrapment is still relatively new, experimental
evidence suggests that:
Situations in which passivity maintains the status quo,
such as automatic investment plans, are more
entrapping than situations in which decisions to
continue must be made actively (Brockner et al. 1979).
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Behavioural Traps - Knee
Deep In The Big Muddy
Entrapment is greater in competitive social situations
than in non-social situations, at least for men (Rubin
et al. 1980).
Entrapment occurs as readily with groups as with
individuals (Bazerman et al. 1984), though this may
be true only for women (Brockner and Rubin 1985).
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Behavioural Traps - Knee
Deep In The Big Muddy
There is also some data on entrapment in romantic
relationships.
Rusbult (1980) found that college students in a role
playing experiment were more committed to a romantic
partner – and less likely to date other people – when
the relationship had lasted a year rather than a month.
Thus, all things being equal, the amount of time
students had already invested in the relationship was
directly related to their degree of future commitment.
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Behavioural Traps – Antiherding
Rülke et al. (2016) use a large international data set, to
analyse whether business cycle forecasters herd or
anti-herd. In general, they find evidence for antiherding, i.e. forecasters appear to scatter their
forecasts deliberately away from the forecasts of
others. Anti-herding tends to be more prevalent for
the longer (next year) horizon. There is some evidence
for a reduced level of anti-herding at times of
increased forecast uncertainty and when the forecasts
are being revised more substantially.
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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235
Why Do Lie-Catchers Fail?
How do you tell if senior management are lying?
Their lips are moving! (possibly Mark Twain 1835–
1910 or Will Rogers 1879–1935)
Hartwig and Bond (2011) provide valuable insight into
the behaviour of lying. They employ a meta-analysis
to combine more than one hundred studies which
were conducted over 50 years into lying and lie
detection.
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Why Do Lie-Catchers Fail?
People are generally very bad at detecting lies. In fact
the analysis shows that people are only able to detect
lies about 54% of the time. Only slightly better than
chance. The authors note that “contrary to common
expectations, presumed lie experts who routinely
assess credibility in their professional life do not
perform better than lay judges do.” Why is this?
Two main theories try to explain the poor ability of
people to detect lies:
1.
People have a false stereotype about what
constitutes lying behaviour. That is, they are
using the wrong cues to detect lies.
2.
There is only a minute behavioural difference
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237
between truth-tellers and liars.
Why Do Lie-Catchers Fail?
Hartwig and Bond (2011) found that the first
hypothesis (false stereotype ) did not hold. In general
people are using behavioural cues to identify lying.
However, the behavioural cues that subjects reported
using are not the cues they actually utilized to detect
lies. The subjects were, able to detect lies at an
intuitive level, but they didn’t consciously know how
they were doing it.
As for the second hypothesis (only a minute
behavioural difference), the researchers did find
strong evidence that there are only small behavioural
differences between truth-tellers and liars.
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Why Do Lie-Catchers Fail?
What about the overall accuracy of truth detectors?
Hartwig and Bond (2011) measured the ability of truth
detectors as a Pearson product-moment correlation
coefficient — that is, the correlation between actual
lying (RDec), perceptions of lying (RPer), and the accuracy
of the detection methods (G). Put mathematically, the
accuracy of truth detection is calculated as follows
(Tucker, 1964):
racc = RDec × RPer × G = 0.36 × 0.63 × 0.93 = 0.21
The accuracy of lie detection is hurt most by the lack
of valid behavioural cues (r = 0.36). The behavioural
difference between truth-tellers and liars is small. Lie
detectors’ perceptions of lying behaviour are strong
(r = 0.63). Lie detectors appear to be using the correct
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239
cues to detect lying (r = 0.93).
Why Do Lie-Catchers Fail?
In different assessments of human judgment of
behaviours other than lying, the average accuracy
coefficient is much higher. One study of peoples’
ability to perceive other qualities in human behaviour
had an accuracy coefficient of 0.56 (Karelaia and
Hogarth 2008). This compares to the accuracy
coefficient of 0.21 (previous slide) for lie detectors.
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Why Do Lie-Catchers Fail?
Though many people believe they can recognize when
someone is lying, detecting deception is difficult.
Accuracy rates in experiments have proven to be only
slightly greater than chance, even among trained
professionals.
But a new study published recently in Proceedings of
the National Academy of Sciences finds that groups
are consistently more accurate in distinguishing truths
from lies than one individual is.
Nadav Klein and Nicholas Epley 2015 Group discussion improves lie
detection. Proceedings of the National Academy of Sciences 112(24)
7460–7465 DOI: 10.1073/pnas.1504048112
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In More Depth
Researchers have been increasingly focusing on the
science behind interrogation techniques and
confessions — and emerging criminal justice system
data patterns — with the hope of better
understanding how false confessions are produced and
how to limit the chances innocent persons are
imprisoned.
False confessions, new data and law enforcement interrogations:
Research findings - Journalists Resources
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1.243
243
Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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244
What Cues Can I Rely On?
The best indications of a lie are not single behaviours
but the overall impression the liar makes on the truth
detector. Research has continually demonstrated that
overall impressions of lying dominate individual cues.
The top five behavioural cues to deception, each of
which is positively correlated with lying, but the
correlations are low. Just because you witness the
following behaviours does not necessarily mean that
the speaker is lying.
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245
What Cues Can I Rely On?
Cue to Deception
Indifferent (speaker seems
unconcerned)
Thinking hard
N
Actual Correlation to Lying
P
100
0.45
1.00
8
0.29
0.76
243
0.19
0.90
46
0.19
0.99
144
0.19
1.00
Ambivalent (communication
seems internally inconsistent
or discrepant)
Not spontaneous (statement
seems planned or rehearsed)
Not fluent (miscellaneous
speech disturbances)
The strongest indication that someone is lying is
indifference.
The impression that a speaker is thinking hard is also a
relatively strong indication that the speaker is lying (r =
0.29). Ambivalence and lack of spontaneity and fluency
are signs of lying, but weak signs.
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What Cues Are Less Reliable?
Cue to Deception
Competent
Arm movements
Object fidgeting
Involved
Pleasant face
Plausibility
N
536
232
130
622
370
1103
Actual Correlation to
Lying
0.59
0.37
0.49
-0.42
-0.44
-0.47
N
Perceived Correlation to Lying
Difference
90
52
420
214
635
395
-0.02
-0.19
-0.02
0.05
-0.05
-0.11
0.61
0.56
0.51
0.47
0.39
0.36
People tend to think that someone they perceive as
incompetent (negative correlation to competence) is
lying; yet the actual correlation between perceived
incompetence and lying is almost zero.
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What Cues Are Less Reliable?
Cue to Deception
Competent
Arm movements
Object fidgeting
Involved
Pleasant face
Plausibility
N
536
232
130
622
370
1103
Actual Correlation to
Lying
0.59
0.37
0.49
-0.42
-0.44
-0.47
N
Perceived Correlation to Lying
Difference
90
52
420
214
635
395
-0.02
-0.19
-0.02
0.05
-0.05
-0.11
0.61
0.56
0.51
0.47
0.39
0.36
If communicators use lots of arm movements or
fidget, people tend to think it is a sign of lying
(positive correlations of 0.37 and 0.49).
A person who move their arms/fidget slightly less
(negative correlation of -0.19 and -0.02) are more
likely to be lying.
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What Cues Are Less Reliable?
Cue to Deception
Competent
Arm movements
Object fidgeting
Involved
Pleasant face
Plausibility
N
536
232
130
622
370
1103
Actual Correlation to
Lying
0.59
0.37
0.49
-0.42
-0.44
-0.47
N
Perceived Correlation to Lying
Difference
90
52
420
214
635
395
-0.02
-0.19
-0.02
0.05
-0.05
-0.11
0.61
0.56
0.51
0.47
0.39
0.36
Lie detectors tend to think that a lack of involvement
is a sign of lying, but in fact, to a slight degree (0.05)
the more involvement, the greater the chance that a
lie has been told.
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What Cues Are Less Reliable?
Cue to Deception
Competent
Arm movements
Object fidgeting
Involved
Pleasant face
Plausibility
N
536
232
130
622
370
1103
Actual Correlation to
Lying
0.59
0.37
0.49
-0.42
-0.44
-0.47
N
Perceived Correlation to Lying
Difference
90
52
420
214
635
395
-0.02
-0.19
-0.02
0.05
-0.05
-0.11
0.61
0.56
0.51
0.47
0.39
0.36
Perhaps most surprisingly, implausibility is actually not
a strong indication that a lie is being perpetrated.
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What Cues Are Less Reliable?
Cue to Deception
Ambivalent (communication
seems internally inconsistent
or discrepant)
Vocal uncertainty
(impressions of uncertainty
and insecurity, lack of
assertiveness)
Not spontaneous (statement
seems planned or rehearsed)
Unfilled pauses (periods of
silence)
Gaze aversion
N
Actual Correlation
to Lying
N
Perceived Correlation to Lying
Difference
502
0.49
243
0.19
0.3
826
0.43
329
0.14
0.29
175
0.48
46
0.19
0.29
718
0.27
655
0.01
0.26
202
0.28
411
0.05
0.23
Sometimes truth detectors err by using the proper
criteria to detect a lie but placing too much
significance on a particular cue. Kraut (1980) was
the first to suggest that behaviours are more
strongly related to perceived deception than actual
deception.
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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How Can I Improve My
Ability to Detect a Lie?
Interestingly the authors suggest a holistic approach
to lie detection. That is, do not rely upon individual
behavioural cues, as a preponderance of lying
behaviours is more indicative than any single cue.
Another method for improving your ability to detect a
lie is to trust your intuition rather than what you
perceive are good behavioural cues. Studies continually
demonstrate that when lies are successfully detected
the methods of detection ascribed by detectors are
not the ones they actually use. This suggests a
disconnect between the potency of unconscious
detection and impotency of conscious method. 12.254
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How Can I Improve My
Ability to Detect a Lie?
The typical prescription of truth-detection trainers is
to give prospective truth detectors a list of
behavioural cues to look for and then give feedback on
performance to improve the results. But these
methods have statistically been demonstrated to be
ineffective, or only marginally effective.
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How Can I Improve My
Ability to Detect a Lie?
Hartwig and Bond (2011) feel that the best way to
improve one’s ability to assess a lie is to increase the
difference in the behaviours of liars and truth-tellers.
One way to do this is to engage in interactional
interviews. Because lying requires greater cognitive
energy than telling the truth, you can increase the
cognitive demand of your questions.
For example, ask someone a question that challenges
them to place a detail of their complex story back in
its proper chronological context, to see if they can
remember where the detail fits in the timeline. 12.256
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Why Do Lie-Catchers Fail?
Finally, the business of investing requires an ability to
discern the truth and veracity of the information you
are using in your analytical process. Yet, most of us are
in fact very poor at catching lies when they are told.
Statistically, more than 50 years of research has
shown this is because there is not that much
difference between liars and truth tellers in how they
communicate, and because, in all likelihood, you are
ignoring your intuitive faculties.
A liar CAN look you in the eye...but watch out for a twitching nose: World's
leading human lie detector divulges how to sniff out deceit (and it's not how you
might think) - Daily Mail - 1 May 2015
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Deception Detection using Real-life Trial Data?
Sample screenshots showing facial displays and hand
gestures from real-life trial clips.
deceptive trial withdeceptive trial
with
one head
hand
forward
with both hands
movement (Move movement (Both
(Single
hand)
forward)
hands)
truthful trial with deceptive trial
with scowl face
with
aneyebrows
up gaze
raised
(Gaze
up) raising) (Scowl)
(Eyebrows
Which are truthful and which deceptive?
Pérez-Rosas et al. 2015
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Deception Detection using Real-life Trial Data?
The experiment started with an analysis of the nonverbal behaviours occurring in deceptive and truthful
videos. Comparing the percentage of each behaviour as
observed in each class.
For instance, there is a total of 61 videos in the
dataset that include the Eyebrows raising feature, out
of which 24 are part of the deceptive set of 61 videos,
and 37 are part of the truthful set (60 videos).
See next slide.
Pérez-Rosas et al. 2015
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Deception Detection using Real-life Trial Data?
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Distribution for nine facial displays and hand gestures
Pérez-Rosas et al. 2015
Deception Detection using Real-life Trial Data?
These ratios (24/61 = .39 and 37/60 = .62) are shown in
the following figure. Hence, the percentages of existence
of this feature are 39% in the deceptive class and 62% in
the truthful class. The figure shows the percentages of all
the non-verbal features for which we observe noticeable
differences for the deceptive and truthful groups.
As the figure suggests, eyebrow and eye gestures help
differentiate between the deceptive and truthful
conditions. For instance, we can observe that truth-tellers
appear to raise their eyebrows (Eyebrows raising), shake
their head (Head repeated shake), and blink (Eyes closing
repeated) more frequently than deceivers. Interestingly,
deceivers seem to blink and shake their head less
frequently than truth-tellers.
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See next slide.
Pérez-Rosas et al. 2015
Deception Detection using Real-life Trial Data?
Distribution of non-verbal features for deceptive and
truthful groups
Rather sketchy error bars!
Pérez-Rosas et al. 2015
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Deception Detection using Real-life Trial Data?
In summary
How to REALLY spot a liar: Scowling, eye contact and exaggerated hand
movements are all signs someone is hiding the truth - Daily Mail - 11 Dec 2015
•Researchers studied video clips from media coverage of criminal
trials
•They trained software to recognise so-called 'tells' of people who
had lied
•This combined gestures, such as hand movements, with vocal clues
•Experts conclude that liars tend to give confident answers, use 'um'
and 'er' more regularly, scowl or grimace while talking and make eye
contact
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Behavioural Traps - The
Great Escape
As sticky as traps can be, they rarely last forever.
Eventually, people waiting on hold, hang up.
Corporate officers stop throwing good money after
bad.
Romantic partners who are unhappy break up.
Usually the problem is not that behavioural traps
capture victims permanently, but that in retrospect,
people wish they had exited the trap sooner than
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they did.
Behavioural Traps - The
Great Escape
Luckily, there are several ways that entrapment can be
reduced or avoided (for reviews, see Brockner and Rubin
1985; Cross and Guyer 1980; Staw and Ross 1987).
One technique proposed by Staw and Ross (1987) is to
“bring phase-out costs forward” before a commitment is
made – that is, to explicitly consider the costs of
withdrawal before embarking on a long-term venture.
Experimental evidence suggests that entrapment is
reduced or eliminated when the costs of participation
are made salient up front (Brockner et al. 1981;
Nathanson et al. 1982).
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Behavioural Traps - The
Great Escape
In their book on entrapment, Brockner and Rubin
(Entrapment in escalating conflicts: A social psychological
analysis 1985 p. 203) advise decision makers to set limits in
advance whenever possible, and to use these limits in the
following way:
Rather than to quit automatically upon investing the amount
specified by their limits, decision makers should use their
limit point as a time to reassess whether persistence or
withdrawal is wiser; independent of the fact that prior
investments have been made.
That is, if individuals decide to invest beyond their earlier
set limit, this must be the result of a prospective, future
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(rather than past-oriented) cost benefit analysis.
Behavioural Traps - The
Great Escape
In a business context, Staw and Ross (1987a)
recommend asking the question: “If I took over this
job for the first time today and found this project
going on, would I support it or get rid of it?”
This question can easily be adapted for use in
contexts other than business (e.g. “If I were
meeting this person for the first time today, would I
be attracted?”).
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Behavioural Traps - The
Great Escape
One other technique is to have different people make
initial and subsequent decisions (Bazerman et al. 1984;
Staw and Ross 1987).
For example, a financial loan might be made by one
bank officer and reviewed for renewal by another.
The advantage of this technique is that later decisions
are made by people who are not responsible for earlier
blunders (and who therefore have little reason to
escalate commitment).
The disadvantage however, is a disruption in continuity
and a potential loss in “institutional memory.”
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Behavioural Traps - The
Great Escape
How to improve group decision making? When it
operates efficiently, a group's decision making will
nearly always outperform the ability of any one of its
members working on their own. This is especially the
case if the group is formed of diverse members. One
problem: groups rarely work efficiently.
How to improve group decision making BPS Research Digest Blog
Mesmer-Magnus, J., & DeChurch, L. (2009). Information sharing
and team performance: A meta-analysis. Journal of Applied
Psychology, 94 (2), 535-546 DOI: 10.1037/a0013773
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Behavioural Traps Conclusion
Behavioural traps are a ubiquitous part of life, and if
unchecked, they can lead to serious consequences.
Staw (1981) has argued that many of the most
damaging personal decisions and public policies arise
from sequential and escalating commitments (such as
those found in the Vietnam War).
Platt (1973 p. 651) went even further, claiming “traps
represent all of our most intractable and large scale
urban, national, and international problems today.”
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Behavioural Traps Conclusion
Yet traps are not always bad. As Brockner and Rubin
(1985) observed, there are many cases in which
people deliberately attempt to trap themselves.
For example, recovering alcoholics, ex-smokers, and
dieters often “screw their courage to the sticking
place” (From Shakespeare's Macbeth (1605) - Lady
Macbeth) by intentionally trapping themselves in
healthful patterns of living.
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Behavioural Traps Conclusion
When entrapment is desired, decision makers should:
Avoid information about the costs of entrapment
Refrain from setting limits or evaluating the costs of
continuing
Make a public declaration of commitment (Alcoholics
Anonymous meeting, Weight Watchers…)
Compete with other people who are striving towards
the same goal (Weight Watchers…).
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Behavioural Traps Conclusion
As with many of the biases discussed above,
behavioural traps are neither inherently good nor
inherently bad, and it is not the purpose of
psychology research to adjudge this issue.
Rather, the purpose of entrapment research – and
decision research in general – is more circumscribed.
It is to further our understanding of how decision
processes operate, and in so doing, contribute to the
quality of the decisions that are made.
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Next Week
Also worth an easy read is Michael Bond 2009 “Risk School” Nature 461 1189-1192 |
DOI: 10.1038/4611189a
Can the general public learn to evaluate risks accurately, or do authorities need to steer
it towards correct decisions? Michael Bond talks to the two opposing camps.
References – also worth a look
1. Gigerenzer, G., Gaissmaer, W., Kurz-Milcke, E., Schwartz, L. M. & Woloshin, S.
“Helping Doctors and Patients Make Sense of Health Statistics” Psychol. Sci.
Publ. Int. 8, 53-96 (2007). | Article | OpenURL
2. Frederick, S. J. “Cognitive Reflection and Decision Making” Econ. Persp. 19, 2542 (2005). | Article | OpenURL
3. Fong, G. T., Krantz, D. H. & Nisbett, R. E. “The effects of statistical training on
thinking about everyday problems” Cogn. Psychol. 18, 253-292
(1986). | Article | OpenURL
4. Milkman, K. L., Chugh, D. & Bazerman, M. H. “How Can Decision Making Be
Improved?” Persp. Psychol. Sci. 4, 379-383 (2009). | Article | OpenURL
5. Dieckmann, N. F., Slovic, P. & Peters, E. M. “The Use of Narrative Evidence and
Explicit Likelihood by Decisionmakers Varying in Numeracy” Risk Anal. 29, 14731488 (2009). | Article | PubMed | OpenURL
6. Peters, E. et al. “Bringing meaning to numbers: The impact of evaluative
categories on decisions”J. Exp. Psychol. Appl. 15, 213-227
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(2009). | Article | PubMed | OpenURL
Next Week
While not intended as a review Soufian et al. (2014)
does contain numerous useful links and interesting
ideas.
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Traps
Introduction
Herd Behaviour
Next Week
Taxonomy
Investors
Where Next?
Time Delay Traps
Peer To Peer
Procrastination
Funding Circle
Ignorance Traps
Examples of Bubbles
Investment Trap
Bubble Model
Avoidance
Buy a Dollar?
Deterioration Traps
Knee Deep!
Bill's Truck
Lie Catchers Fail?
Facit
Can I Rely On?
Collective Traps
Can I Improve?
Prisoner's Dilemma
Why Fail?
Tragedy of the Common's
Great Escape
Bystander Behaviour
Conclusion
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Where Next?
For those considering a career in banking/financial risk
they might explore “A Flight Simulator for Financial
Risk”. Described here. Freely available here (there is no
registration charge). Explanatory video.
Take it for a flight, did you loose money?
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Where Next?
The internship: Generation i - The Economist – 6 Sept 2014
“Don’t talk to the press. Have a good attitude. Always say
yes. You are not here to change the world.” And ladies,
please, “Do not put us in a position to remind or suggest
what qualifies as proper attire.”
These are among the instructions given to interns in the
office of John Boehner, the Speaker of the United States
House of Representatives.
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Where Next?
Daily chart: CV fillers - The Economist - 8 Sept 2014
During the summer months waves of young, temporary
workers flood the private and public sectors. They hope
that fetching coffee and photocopying will bulk up their
CVs — and help secure a permanent job. But in which
industries is it easiest to get work experience? And which
are most likely to retain their interns?
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Where Next?
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But It Might Be Too Late!
Work experience: an essential socialising influence - FT - 20 Oct 2014
The phrase “work experience” is one parents dread. Even if you have friends
that you can beg favours from, it is a very uncomfortable process. But for a
child at any stage from 14 to University graduation, it is an important part of
becoming "career-ready".
Work experience is important for two reasons.
The first is to learn what is expected in a work environment – to turn up on
time, shake people’s hands firmly, look them in the eye, wear appropriate
clothing, don’t be too chatty, and so on.
The second is to understand what people in various jobs actually do. How do you
know what you want to do in life if you haven’t seen others do it?
How to turn an internship into a job offer - FT - 29 June 2015
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And Finally!
How to negotiate a job offer and salary - FT - 17 July 2015
When you receive an offer, you should first and foremost thank the employer
and genuinely express your interest in the position. This will lay the groundwork
for a positive discussion if you pursue the position and decide to negotiate.
Even if you know that you will accept the position, ask for time to consider the
offer to make an informed decision. This request is customary, it gives you
bargaining room and allows you time to think clearly.
Career Builder reveals how to avoid classic CV mistakes - Daily Mail - 15 Aug 2015
The end!
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