ECONOMICS OF MARITIME DISASTERS ESSAYS ON THE TITANIC … · examine the sinking‘s of the R.M.S....
Transcript of ECONOMICS OF MARITIME DISASTERS ESSAYS ON THE TITANIC … · examine the sinking‘s of the R.M.S....
ECONOMICS OF MARITIME DISASTERS:
ESSAYS ON THE TITANIC AND LUSITANIA
David A. Savage
BIT BBus
Primary Supervisor: Professor Benno Torgler
Submitted in fulfilment of the requirements for the degree of
Master of Business (Research)
Centre for Learning Innovation
Faculty of Education
Queensland University of Technology
Submitted December, 2009
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Economics of Maritime Disasters: Essays on the Titanic and Lusitania i
Keywords
Altruism and Self-Interest; Decision under Pressure; Excess Demand; Disasters; Life
and Death; Lusitania; Quasi-Natural Experiment; Social Norms; Survival of the
Fittest; Titanic; Tragic Events; Women and Children First
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Abstract
This work seeks to fill some of the gap existing in the economics and behavioural
economics literature pertaining to the decision making process of individuals under
extreme environmental situations (life and death events). These essays specifically
examine the sinking‘s of the R.M.S. Titanic, on 14th
April of 1912, and the R.M.S.
Lusitania, on 7th
May 1915, using econometric (multivariate) analysis techniques.
The results show that even under extreme life and death conditions, social norms
matter and are reflected in the survival probabilities of individuals onboard the
Titanic. However, results from the comparative analysis of the Titanic and Lusitania
show that social norms take time to organise and be effective. In the presence of such
time constraints, the traditional ―homo economicus‖ model of individual behaviour
becomes evident as a survival of the fittest competition.
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Table of Contents
Keywords .................................................................................................................................................i
Abstract .................................................................................................................................................. ii
Table of Contents .................................................................................................................................. iii
List of Tables........................................................................................................................................... v
Dedication .............................................................................................................................................. vi
Statement of Original Authorship ......................................................................................................... vii
Acknowledgments ............................................................................................................................... viii
CHAPTER 1: INTRODUCTION ........................................................................................................ 1
CHAPTER 2: THEORETICAL BACKGROUND ............................................................................ 5
2.1 Panic ............................................................................................................................................ 6
2.2 Fight and Flight ............................................................................................................................ 9
2.3 Social and Moral Norms ............................................................................................................ 11
2.4 Queuing Behavior ...................................................................................................................... 13
CHAPTER 3: METHODOLOGICAL BACKGROUND ............................................................... 17
3.1 Experimentation: laboratory vs Field ......................................................................................... 17
3.2 Essays ......................................................................................................................................... 19
CHAPTER 4: NOBLESSE OBLIGE? DETERMINANTS OF SURVIVAL IN A LIFE AND
DEATH SITUATION ......................................................................................................................... 23
4.1 Introduction ................................................................................................................................ 24
4.2 Theoretical Background ............................................................................................................. 26
4.3 Empirical Results ....................................................................................................................... 31
4.4 Conclusions ................................................................................................................................ 38
4.5 Table .......................................................................................................................................... 41
CHAPTER 5: SURVIVING THE TITANIC: ECONOMIC, NATURAL AND SOCIAL
DETERMINANTS .............................................................................................................................. 43
5.1 Introduction ................................................................................................................................ 44
5.2 Theoretical Hypotheses about who is Expected to be Saved ..................................................... 47 5.2.1 Economic Determinants .................................................................................................. 50 5.2.2 Natural Determinants ...................................................................................................... 52 5.2.3 Social Determinants ........................................................................................................ 55
5.3 The Data ..................................................................................................................................... 57
5.4 Econometric Estimates and Results............................................................................................ 59 5.4.1 Testing Economic Determinants ..................................................................................... 59 5.4.2 Testing Natural Determinants ......................................................................................... 61 5.4.3 Testing Social Determinants ........................................................................................... 61
5.5 Conclusions ................................................................................................................................ 65
5.6 Table .......................................................................................................................................... 66
CHAPTER 6: SHOULD I STAY OR SHOULD I GO NOW? AND TIME AND TIDE:
CONSTRAINED ALTRUISM? ......................................................................................................... 67
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6.1 Introduction ................................................................................................................................ 68
6.2 Data and Model .......................................................................................................................... 72
6.3 Results ........................................................................................................................................ 74 6.3.1 Is self-interest dominant in the Lusitania case? .............................................................. 74 6.3.2 Pro-social behaviour and social power in the Titanic? ................................................... 77
6.4 Conclusions ................................................................................................................................ 79
CHAPTER 7: CONCLUDING REMARKS .................................................................................... 81
BIBLIOGRAPHY ............................................................................................................................... 85
APPENDICES 103 Appendix A: Publications ........................................................................................................ 103
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List of Tables
Table: 4.1 Survival Probability and Pro-Social Behaviour ...................................... 35
Table: 4.2 Survival of Women ................................................................................. 38
Table: 4.3 Mean Values ............................................................................................ 41
Table: 5.1 Economic and Natural Determinants ...................................................... 60
Table: 5.2 Social Determinants of Survival ............................................................. 62
Table: 5.3 Robustness Tests Including Interaction Terms........................................ 64
Table: 5.4 Summary Statistics .................................................................................. 66
Table: 6.1 Lusitania vs. Titanic ................................................................................ 70
Table: 6.2 Determinants of Passengers‘ Survival on Lusitania ............................... 76
Table: 6.3 Determinants of Passengers‘ Survival on Titanic ................................... 78
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Dedication
I would like to dedicate this work to the victims and their families, who have died
tragically in disasters. Specifically, I wish to acknowledge the victims, families and
loved ones of those who lost their lives onboard the Titanic and Lusitania, and whose
untimely passing was neither forgotten nor in vain. It is my hope that this work will
add to the understanding of human behaviour in these disasters so as to reduce future
losses of life.
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Statement of Original Authorship
The work contained in this thesis has not been previously submitted to meet
requirements for an award at this or any other higher education institution. To the
best of my knowledge and belief, the thesis contains no material previously published
or written by another person except where due reference is made.
Signature: _________________________
Date: _________________________
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Acknowledgments
One of the most difficult voyages an individual can undertake is that of self
discovery, there are no charts or maps to provide direction, nor are there other
explorers whose prior paths one can follow. At best one is able find a friend with
whom you can share the journey and the occasional guide to assist with course
corrections. The old idiom states that nothing of value is easily obtained, it is the
struggle and the effort that makes the prize all the better for winning. Similarly the
journey for knowledge and understanding is equally fraught with problems and
pitfalls, but this makes achievement all the sweeter. For me, these journeys have been
simultaneous, and I have indeed been fortunate to have both a dear friend and partner
with whom to share the voyage and a mentor to direct and share.
First and foremost I would like to thank my best friend and partner, Deborah Stewart.
Thank you for not only allowing me to undertake this journey but for coming along
and sharing it with me, success is meaningless without someone to share it with.
Secondly I would like to thank my supervisor, mentor, teacher and friend, Professor
Benno Torgler, and partner in crime Dr. Clevo Wilson. Without whose incessant
badgering and thinly veiled suggestions, I would never have taken up this challenge.
Thank you both from the bottom of my heart, I hope you continue to identify and
pick out the annoying students and convince them to stay and grow. And I hope that I
can follow your shining example and show future students the same level of empathy
and commitment as you both showed me. Additionally, I would like to thank
Manuela, for allowing me to ‗borrow‘ so much of your husband‘s time and being so
welcoming and friendly. I would like to include thanks to the ―Disciples‖ whose
friendship and support made the journey a much better experience. I expect that one
day the number of ―Disciples‖ will swell into a fully fledged cult, with members
spread the world over, mixing research with camaraderie.
Additionally I would like to thank the School of Economics and Finance, The Faculty
of Business and Queensland University of Technology staff. Specifically I would like
to thank the Head of School, Tim Robinson and Professor Stan Hurn for their initial
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Economics of Maritime Disasters: Essays on the Titanic and Lusitania ix
support, allowing my entry into the post graduate program when others turned me
away. To Professor Uwe Dulleck for showing me how much I really didn‘t know
then helping me understand much of it and Professor Paul Frijters for opening my
eyes and demonstrating the Dutch method of asking questions, I thank you both.
Additionally, I would like to thank my co-authors, collaborators and conference
attendees for their input and feedback on these and other works. Specifically I would
like to thank: Professor Bruno S. Frey, Professor Benno Torgler, Dr Lionel Page;
Martin Gächter, Marco Piatti, and the attendees at brown bag sessions, the Australian
Conference of Economists ‘09, the ANU/QUT cross institutional PhD workshop and
the Faculty of Business Research Colloquium.
And finally I need to thank all the very patient economists, post graduate
students and random rail commuters, to whom I have posed all the truly stupid
questions.
Chapter 1: Introduction 1
Chapter 1: Introduction
“This awful catastrophe is not the end but the beginning. History does not end so. It
is the way its chapters open.”
St. Augustine
On the morning of December 6th
1917, an unfortunate series of events and bad luck
set into motion a chain reaction that reduced the port city of Halifax to a freezing,
wet and smouldering ruin. On this morning a French freighter the Mont Blanc was
leaving the harbour laden with 2,500 tons of explosives bound for the war in Europe.
While attempting leaving the harbour an accidental collision with another vessel, the
Imo, started a fire on the French ship turning it into a floating time bomb. The
ensuing explosion, the largest in history, shattered windows up to 60 miles away and
rained down fiery molten death, killing many and setting the city ablaze. However, as
almost prophetically stated by St. Augustine, this was not the end but the beginning
of the destruction. The explosion also created a massive tidal wave that swamped the
shore, drowning many of those along the shoreline and all but destroying the port. In
a final unfortunate piece de résistance, that night Mother Nature wracked the city
with a blizzard; the final death toll from the event was 1,963 people (Prince, 1920).
Bearing witness to this event was Samuel Henry Prince, a pastor who 5 years earlier
had performed burials at sea for another world shaking disaster, the sinking of the
Titanic. Prince observed the behaviour of the citizens of Halifax and was greatly
puzzled, he commented on the ―…utter and complete social disintegration which
followed (…) Old traditional social lines were hopelessly mixed and confused (…)
Rich and poor, debutante and chambermaid, official and bellboy met for the first time
as victims of a common calamity‖ (Prince, 1920: pp 31-32). Parents did not
recognise their children, even in the morgue; individuals underwent painful surgery
with little or no anaesthetic without complaint or outcry; and the first triage station
was setup by a troupe of actor‘s not trained medical staff. From this observer‘s
perspective, nothing was as it should have been.
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Prince went on after these two disasters to write a PhD thesis analysing the behaviour
of people in disasters, which for the most part languished on the dusty shelves of
libraries until very recently. In the last few decades a slowly growing resurgence in
the behaviour of individuals in these disaster situations has occurred. In the wake of
the September 11 attacks on the World Trade Centre and the evacuation debacle of
Hurricane Katrina, an explosion of research attempted to understand how and why
individuals behave in disasters. Prince‘s work had returned with renewed vigour and
purpose, almost 80 years prior Prince foresaw the need for the continuance of his
research stating "This little volume on Halifax is offered as a beginning; don't let it
be the end. Knowledge will grow scientific only after the most faithful examination
of many catastrophes." (Prince, cited in Ripley 2008: pp. xi) In this work, I return to
Princes vision and begin anew, with a ―faithful‖ and detailed examination of human
behaviour during disasters using the rigour of an economics perspective. The specific
events under investigation in this work are the sinking‘s of the Titanic on April 14th
1912 and the Lusitania on May 7th
1915.
The disaster scenario is a staple of the Hollywood movie industry, when the end of
the world scenario ensures the depicted behaviour is stereotypical and matches the
traditional view, which is that of mass panic (see e.g. Armageddon (1998), 2012
(2010), War of the Worlds (1938, 1953, 2005), Deep Impact (1998) or The Day After
Tomorrow (2004)). The fictional behaviour in disasters movies closely matches that
of the traditional disaster literature, where the expected behaviour is that of mass
panic entailing some chaotic or random actions. Within this panic behaviour, movies
portray the full spectrum of emotive action, including: quiet resigned acceptance of
death; immobilized panic inaction; frenzied action without direction or coordination;
the obligatory looting and random killings; to the desperate seeking out of loved
ones. But do individuals in real world disaster situations, behave in this manner or
are the popular myths, the traditional panic literature and Hollywood completely
wrong and engaged in good hype?
This work began life as an interesting detour prior to starting my ‗real‘ research, as I
began dissecting the Titanic and observed the event for what it was, an excess of
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Chapter 1: Introduction 3
demand (for survival) market, my interest rapidly grew. Here was, an almost perfect
natural field experiment, designed for analysing the decision making process of
individuals with a shortage of supply (life boat seats) under high stakes (life or
death). The initial research examined the determinants of survival, or the factors
determining the allocation of the scarce lifeboat resource. Some of the results were
unsurprising given the common familiarity of the myth, but others were somewhat
inexplicable. Such as why, given the standard homo economicus model, did social
norms prevail when surely a survival of the fittest competition should prevail for the
allocation of such a life saving resource? This research sparked a plethora of other
questions that I suddenly needed to find answers for, unfortunately I found a rather
large gap in the economics literature. Nowhere to be found was an economic analysis
of the decision making process in extreme environments, as all the existing
experimental literature was performed under normal everyday environmental
conditions. Furthermore, the Titanic occurred almost 100 years ago, would the social
norms observed in this event still hold today? As this research was presented at
economics conferences and seminars interest in the subject material was clearly
evident, but this raised a raft of further questions. Questions ranging from cultural
norms, interdependent preferences, biological instinct, parental investment, a
plethora of questions presented themselves and demanded to be accounted for.
The initial paper received an amazing amount of attention from the world‘s
mainstream media, published in print in over 50 countries around the world, as well
as numerous broadcast media outlets (such as ABC, BBC and CBC national radio‘s).
The topic became a hotbed of discussion on blogs and discussion boards, raising
even more questions and demands for further empirical evidence. It quickly became
evident that this topic had supplanted my original research topic to become the focus
of my post graduate study. The initial discussions led me to question which of the
many theories of human behaviour were evident within this event, this inevitably led
to the second paper: Surviving the Titanic: Economic, Natural and Social
Determinants (see chapter 5). From these finding, supporting social normative
behaviour a new aspect of the research appeared. Has the behaviour of individuals
changed over time, such that if a Titanic type event happened in another time period
would the outcomes remain the same?
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4 Chapter 1: Introduction
From the questions investigations into the Lusitania (1915), Andrea Doria (1956)
and Estonia (1994) began, 4 events over the last century provided an opportunity to
examine the change in social norms. Beginning with the Lusitania, this was sunk by
a German u-boat in less than 18 minutes, on 7th May 1915, killing 1198 of the 1950
on board. Given the closeness in history between the Titanic and Lusitania and the
close demographical makeup of the ships, it became clear that the only major
difference was the time the vessels took to sink. The research resulted in: Should I
stay or Should I go Now? and Time and Tide: Constrained Altruism? (see chapter 6).
Chapter 2: Theoretical Background 5
Chapter 2: Theoretical Background
Traditionally the economist‘s sole interest in disaster analysis was to calculate the
economic costs associated with these events over the short, medium, and long term,
in line with the seminal contributions by Hirshleifer (1963) or Dacy and Kunreuther
(1969). Other fields, such as psychology and sociology, have focused on the actual
behaviour of the people involved in the disaster itself, often as a group such as a
collective action problem or mass panic (e.g. Aguirre et al. 1998; Elster 1985; Fehr et
al. 2002; Johnson 1988; Kelley et al. 1965; Mawson 1980; Quarantelli 2001; Smelser
1963). Much of this literature rejects the commonly held assumptions about
individual behaviours in these types of events, such as: the inability to act rationally
(the so-called ―disaster syndrome‖); or the reign of chaos, panic, social breakdown
and antisocial behaviour, such as: crime, looting, or exploitation (e.g. Brown 1954;
Drabek 1986; Goldthorpe 1988; Gwynne et al. 2006; der Heide 2004; Howard
1966p; Johnson 1988; Mawson 1978; Mintz 1951; Quarantelli 1972 & 2001). Indeed
it has been found using empirical analysis that morals, loyalty, respect for law and
customs, and tenets of acceptable behaviour do not instantly break down with a
disaster. This is consistent with some of the findings of the newly emerged field of
behavioural economics, which shows that people do not necessarily exploit an
opportunity presented to them when it can hurt other people. Rather, they are often
inclined to help other people. Substantial evidence has been generated that motives
such as altruism, fairness, or morality affect the behaviour of many individuals (e.g.
Becker 1974; Camerer et al. 2004; Drago & Garvey 1998; Elster 2007; Fehr &
Schmidt 1999; Frey 1997; Kahneman et al. 1986; Thaler 2000).
Utilizing a behavioural economics approach in this way can provide some new and
important insights into the disaster and behavioural literature, by using improved
structural design, up to date econometrical and experimental modelling tools.
Economics employs the scientific rigour of laboratory experimentation and
implements this expertise into the world of natural and field experimentation,
providing better, more realistic results. Moreover, economics, and more specifically
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behavioural economics, has failed to explore the decision making process of
individuals in high cost environments (such as life and death events). At best only
some theoretical conjecture has been offered on the subject, even though a large
number of laboratory experiments have been carried out (such as ultimatum and
dictator games numerous settings). One of the problems stems from a core tenet of
decision theory, namely the rationality condition, where economists assume that all
individuals making decisions are rational and able to correctly weigh options.
However, experimentation has shown that under pressure and duress this function
can break down leading to inefficient, sub-optimal outcomes (Jamal 1984; Keinan
1987; Meichenbaum 2007; Schultz 1966; Wright 1997).
Before examining the individual behaviour on board the Titanic or Lusitania, I begin
this work by examination of some of the underlying behavioural literature, which
includes: panic; fight or flight; social norms (altruism, fairness, reciprocity retaliation
and helping behaviours); queuing behaviours and field experimentation. However,
this section will not contain a complete theoretical discussion, given that some
concepts are discussed in detail in the literature section of the papers that make up
each of the chapters. These broad concepts discussions will be examined further and
in more detail in each of the essays, in a more contextual setting. But they are
provided here as an overview of the surrounding literature on individual and groups
behaviours in extreme life and death events.
2.1 PANIC
Panic is perhaps one of the most misunderstood, misinterpreted and contradictive of
all human behaviour, the traditional and common understanding of the phenomenon
is erroneous and based on myth rather than reality. The basis of the word comes from
the ancient Greek deity ―Pan‖, who was said to be able to instil an irrational and
unfounded fear into individuals. The use of the term ‗panic‘ is extremely prolific in
disaster literature, but has conjured up as many various definitions and causes as the
depicted behaviour ranging from: any fear, flight, or uncoordinated activity (Heide,
2004); fear and/or flight behaviour that is considered inappropriate, excessive or
Chapter 2: Theoretical Background 7
irrational (Mawson, 2005); a reaction involving terror, confusion and irrational
behaviour (Goldenson, 1984); to a breakdown of social ties and social order
(Johnson, 1988). The most common threads in the popular panic mythology are
irrationality and social breakdown. Traditional models state that individual behaviour
in these types of events becomes illogical, without reason, random or nonsensical and
the breakdown of social order is oft repeated. Additionally, the typical behavioural
response depicted is either: self-preservative aggression or flight (Brown, 1954;
Cannon, 1929a, 1929b); or flight towards objective safety and away from danger
(Smelser, 1963). Some of the traditional literature indicates that physical dangers are
considered to be more disturbing than other (psychological) kinds of events, such that
seeing the danger is greater than the threat of danger. Additionally, they indicate that
flight behaviour is supposedly prevented in danger situations by social control, such
that social norms and other controls regulate or constrain individual‘s natural
tendency to flee danger. Problems arise from these contradictive models, given that it
is from these traditional perceptions of behaviour that governments and other
agencies build and design disaster plans, as well as create building and evacuation
codes and provide disaster relief.
This can obviously present serious problems, as Heide (2004) states, ―Disaster
planning is only as good as the assumptions it is based upon. Unfortunately this
planning is often based upon a set of conventional beliefs that have been shown to be
inaccurate or untrue when subjected to empirical analysis…It is more efficient to
learn what people tend to do naturally in disasters and plan around that, rather than
design your plan and then expect people to conform to it.‖ (Heide 2004: p340). He
also denoted the 4 conditions that must be present for panic to occur, which include:
1) Victims perceive an immediate threat of entrapment; 2) Escape routes appear to be
rapidly closing; 3) Flight seems the only way to survive; and 4) No one is available to
help. Heide (2004) further states that because this combination of conditions is so
uncommon in disasters, panic is also rare. Mawson (2005) extended these concepts
through his investigation into mass panic and collective behaviour, which reinforced
that some of these panic conditions are also required for group flight to occur. He
states that conditions required for group flight include: 1) people believe that major
physical danger is present or imminent; and 2) that escape routes are either limited or
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rapidly closing. He adds a caveat to this by saying that mass flight from community
disasters is uncommon and that ‗organized and altruistic behaviour is the rule‘
(Mawson, 2005: 97). Panic and flight in these traditional models of behaviour, are
representative of pure self interest or survival behaviour, where the individual flees in
order to preserve their own life, possibly even at the expense of others.
However, the social attachment model of human behaviour in disasters (see Mawson,
1978, 1980) states that maintaining proximity to the familiar (people and locations) is
a dominant behaviour. Therefore flight can be considered an anti affiliative
behaviour, thus the flight-and-affiliate behaviour depends on the degree of social
contact and the degree of danger, such that the presence of the familiar influences the
perception of danger and the measure of response, where close proximity diminishes
fear responses. ―The most extreme stresses, including drowning at sea, can be calmly
faced if the individual is not separated from his fellows … conversely being alone in
an unfamiliar environment or with strangers heightens the response to stress and
increase the probability of flight‖ (Mawson 2005). Here we observe that contrary to
the expected social breakdown or irrational behaviour we observe collective
behaviour and an affiliative response to danger. This point is neatly concluded by
Quarantelli (2001), that despite major evidence to the contrary, panic remains part of
the popular imagination and continues to be evoked as part of disaster management
plans worldwide. This flight and affiliate behaviour is more in line with socially
normative behaviour, where individuals run to those they have the strongest social
bond (family, friends etc.).
This affiliative behaviour was observable in the investigation by Aguirre et al. (1998)
into group responses during the 1993 World Trade Centre (WTC). After the
explosion inhabitants of the WTC experienced numerous after effects including:
power failure (computers and lighting); phone lines were cut; and the majority of
people felt the explosion (which created a crater approximately 120m wide and 7
stories deep). Over 75% of the survey respondents indicated that they knew
something serious had occurred but only 8.7% of the groups1 surveyed chose to act
1 The vast majority of the groups were formed by persons who knew each other prior to the event.
Chapter 2: Theoretical Background 9
immediately and evacuate. All the remaining groups delayed evacuation, 63% of the
groups sought additional information2 before committing to a course of action, this
information gathering cost several minutes. The investigation also found that larger
groups took much longer to organize, on average over 6.7 minutes longer before
beginning evacuate, additionally the research found that familiarity with the WTC
was not a significant factor for evacuation. Additionally Rosenkoetter et al. (2007)
has investigated what are the factors that determine the evacuation of the elderly and
supports the fight or flight vs. social norms arguments. The results show that living
alone, gender (females are more sensitive to danger) and fear for their own safety are
the best predictors for evacuation. This holds with the concept that individuals are
more prone to flight if they are not part of a social group and are more willing to do
so if they fear for their own safety.
Thus, research has shown that the supposed panic reaction of the population is almost
exclusively a mass media creation, and that pro-social rather than anti-social
behaviours dominate in such situations (see Johnson, 1988; Johnson et al., 1994;
Mawson, 2005, 2007; Quarantelli, 1960, 1972, 2001; Schultz 1966). Through
investigation of the Titanic and Lusitania events, it can be empirically shown that
contrary to popular myth, mass panic did not occur. Additionally, the evidence
supports non-random actions and behaviour, which would indicate rational and thus
predictable decision making. However, we still observe that under specific conditions
in some events, flight behaviour occurs. This raises the questions about why
individuals flee, given the affliliative behaviour described above.
2.2 FIGHT AND FLIGHT
Humans, like all animals, have an automatic biological response system that triggers
to threats and danger. When threatened the body chemistry is altered, such that they
are ready to run from danger or fight it, to better understand this instinctive behaviour
process included here are some limited biology and neuroscience theory (see, e.g.,
2 26% sought additional information and advice from those in the area, 25.5% tried to phone for
help/information and 11.3% turned to the media for information.
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Cannon, 1929a, 1929b 1935; Selye, 1936; Bracha, 2004). The biological make up of
the human brain consists of three distinct and separate sections that had developed at
different times for specific tasks, known as the Triune Brain (MacLean 1990). The
oldest and centre portion is the brain stem or Proto-Reptilian Complex, found in
lower order animals, is primarily concerned with instinctive behaviour and biological
function including self preservation3. The next layer which surrounds the brain-stem
is the limbic system or Paleo-Mammalian Complex, which account for warm-
bloodedness, nursing, infant care and extended social bonding4. The newest addition
and outermost layer is the neo-cortex or the Neo-Mammalian Complex5, which
allows for complex social interaction, an awareness of self and a sense of time
(which in turn allows for planning).
The speed at which the brain processes information and the reaction process as each
portion of the brain interprets the information varies depending on level of the brain
it needs to reach. Fight or flight6 behaviour is a survival mechanism, believed to be
controlled by the oldest portions of the brain. The flight or fight survival mechanism
has traditionally been viewed as ―irrational‖ behaviour, but as Johnson (1988, as
cited in Quarantelli, 2001) illustrates that if this behaviour is taken from the
perspective of those inside the disaster area an alternative view is constructed. To the
actors inside the event the action is meaningful and purposeful and is thus far from
the concept of ―irrationality‖. Grays updated version of flight or fight includes a pre-
stage of freeze, when danger is first sensed then a freeing action is undertaken, this
act is used to assess and hide from the threat.7 Under time sensitive conditions, an
extended freeze period uses valuable time, and the first to enter flight mode would
have a greater probability of survival.
3 Lower order animals generally refer to reptiles/snakes and the like, for this reason this brain function
if generally known as the reptilian complex (R-Complex) 4 Social Bonding of this level is that of the pack or herd, is observable in the lower mammalian species
wolves, lions etc. 5 The Neo-Cortex is visible in all primates to some degree, but only humans has developed this far
enough for language and cognitive generalizations. Primates have some sense of individualism but not
that of ego or id. 6 Fight or Flight originally formulated by Cannon (929) and extended and refined by Gray (1988)
7 Predator species, especially males, eyesight has developed to detect movement. Freezing in place
increases the chance of non-detection
Chapter 2: Theoretical Background 11
This is instinctual behaviour and as it only needs to pass into one portion of the brain
is by far the fastest processed and is immediately acted upon. For fight or flight
instinct to be counteracted by social norms, the brain must pass the problem from the
brain-stem into the limbic system, then onto the neo-cortex. It is within the neo-
cortex that an individual must assess the situation and either maintain the flight or
fight behaviour or attempt to over ride it with cognitive reasoning from either moral
or social norms. There currently exists a gap in neuroscience literature pertaining to
duration of flight behaviours as well as the requirements for individuals to overcome
the fight or flight instinct. This work provides some evidence to support that while
instinctual flight occurs in some situations, given some (unknown) period of time
individuals are able to overcome this and reapply social normative behaviour. This is
observable in the variation in survival rates between the Titanic and Lusitania, where
the defining factor between socially normative behaviour and survival of the fittest
behaviour, is time (see chapter 6). However, the existing literature does demonstrate
that humans, like all other animals, instinctively respond to danger by either flight or
fight. This is a survival mechanism, which would satisfy a survival of the fittest or
self interest behavioural models.
2.3 SOCIAL AND MORAL NORMS
As discussed in the panic section, affiliative or social behaviours are clearly observed
and seem to predominate in extreme life and death, disaster type situations. Social
norms are the generally accepted conditions under which society operates, not only
how individuals are expected to act and behave towards each other but the moral and
ethical compass with which to navigate existence. Social norms direct both
individual and group behaviours under normal conditions, specifically the group herd
mentality once some members of society conform to the social norm others will
follow (Banerjee, 1992). Social norms are enforced society and are not always in the
best interest of a particular individual, but are in general better for the group as a
whole (Elster, 1985, 2006). While this societal enforcement works in nearly all cases
an example of this not holding can be observed in Germany during the Second World
War. It is this enforcement of the social norm by others of the group that would make
12
12 Chapter 2: Theoretical Background
it possible for individuals to take a course of action that would otherwise seem
irrational by either shaming or forcing them into the required action (Elster, 1989,
1998). Elster (2007) differentiates moral and social norms into either unconditional
or conditional respectively. Moral norms are guided by the individuals own internal
belief systems which would be completely encompassed within the neo-cortex and
does not require exogenous stimuli8. This means that it takes little or no time to
determine a ―moral‖ course of action for an individual. Social norms are conditional
on social situation and as such require social interaction between individuals to form
social groups before decision making.
Models of rational action show that actions are driven by the desires (values) and
beliefs of an individual. The desires or values of an individual are derived via the
influence of factors such as: moral norms; social norms; religious ideology; and
political ideology (Elster 2007). These factors directly influence beliefs systems
which in turn re-influence the desires and values of individuals. Beliefs can skew
information and knowledge assimilation, reinforcing the desires leading to action.
Social norms, or the ―collective consciousness‖, are the set of values and beliefs
shared by a society‘s members (Elster 2007). These norms are the accepted, enforced,
conditions under which a society functions, guiding how individuals act and behave
towards each other. These behaviours can include selfishness (homo economicus) or
deviations away from selfish behaviour. In the last few decades these deviations to
homo economicus have been the subject of much study which has included: altruism,
extreme altruism (self sacrifice), fairness, helping behaviour, punishment and
reciprocity (see e.g. Batson, (1992); Camerer et al., (2004); Elster, (1985, 1996, 2006,
2007); Fehr et al., (2002); Fehr, and Fischbacher, (2003); Henrich, (2004);
Kahneman, Knetsch, and Thaler (1986a, 1986b); Krebs (1991); Piliavin and Charng,
(1990)). The inter-relationship amongst individuals as defined by their roles and
statuses is the social structure of a society. It is the interactions between structure,
status and culture that we use to define a society (Schooler 1996). It could be argued
that actions and behaviours are the observable physical manifestations of these social
norms.
8 Moral norms require a sense of self and as such must be located with the neo-cortex.
Chapter 2: Theoretical Background 13
Individuals are immersed in the social norms of society, codes of behaviour and
expectations, which are ingrained and adhered to throughout their life (Foucault
1979). Long lived norms eventually become institutionalized, which has been used to
explain some cross-national values and behaviour (Frank, Meyer, & Miyahara 1995).
When social norms are internalized they become an integral part of an individual‘s
personality and are used as a reference in the interplay between actors within that
society (Parsons 1964). Internalized norms have a stronger influence on behaviour
while social norm violations do not engender a sense of guilt or shame. It is the
observation of the transgression, by a third party, that triggers shame in the
transgressor not the violation itself. Norms that are internalized become more like
moral norms, such that any transgression would elicit a sense of shame and guilt in
the individual, observed or not (Elster 1985). Once norms are identified as being
shared by other members of society they cannot be easily disregarded, individuals
will follow the prescripts of a social norm even when it is clearly not in their own
best interest to do so (Elster 1989). An analogy used by Weber likened the adherence
to norms to be like the use of a taxi, such that individuals cannot embark or
disembark at will, for to do so would be deemed irrational (Weber 1930). This raises
both a temporal and biological problem, social norms are interactionary and should
take time to evolve and enforce behaviour, and additionally we observe that
instinctive behaviour in the face of danger is to flee. This is observed in the analysis
of the Lusitania and Titanic (chapter 6), where a short event horizon results in a clear
survival of the fittest competition and a long horizon leads to stable social normative
outcomes.
2.4 QUEUING BEHAVIOR
A specific instance of socially interactional behaviour is that of queuing, which has
its own set of rules, principles and culturally instituted norms. Given the nature of
disaster evacuations where time can be crucial factor in determining survival,
queuing may be useful in explaining some behavioural outcomes. Queuing behaviour
can be viewed as an attempt at solving several competing issues: firstly it can be seen
as an attempt to maximise social welfare (Hassin & Haviv 2006); secondly resolution
14
14 Chapter 2: Theoretical Background
of the scarcity of resources; or ordered queues are used in an attempt to maintain
some level of social justice or fairness (Avi-Itzhak & Levy 2004; Avi-Itzhak, Levy,
& Raz 2005; Larson 1987). While the allocation of scarce resources is a basic tenet
of economics, only in the last few decades has this discussion included the aspect of
fairness. Surveys have shown that using pricing controls for allocation under scarcity
was viewed as being unfair (Kahneman, Knetsch, & Thaler 1986a, 1986b). Within
most western societies, formal laws have been instituted to penalise vendors who
take advantage of shortages after disasters by raising prices (Camerer & Fehr 2006).
In a shortage situation an allocation process following the queuing tradition of first
come, first served (FIFO) is perceived as being the fairest (Camerer, Loewenstein, &
Rabin 2004; Savage & Torgler 2008).
This type of allocation purely a function of time of arrival (time in queue) and is not
dependant on other factors like age, gender, class etc. In times of scarcity individuals
can be viewed as having two competing and diametrically opposed natures:
Individualism based on rational self-interest; and Egalitarianism based on social
justice and fairness (Singer 1999). It would stand to reason that cultural variations
could have great affect on the creation of, the willingness to enter and the adherence
to queuing culture. However Mann‘s (1969) work on queue culture posed that
egalitarianism by itself does not relate to respect for queue etiquette or adherence to
queue priority. Stating that the English are famous for their strictly democratic
queuing behaviour, despite the rigid class structure, where as American‘s are much
less likely to join or acknowledge queuing rules and behaviours (Mann 1969). If as
suggested by Mann (1969) that the English are by nature willing to queue where
Americans are not, then this should be observable in a greater probability of survival
of for non-queuers.
This concept of fairness and queuing may have been importantly evident with the
context of the Titanic disaster, much in line with the Kahneman et al. (1986)
examinations. The Titanic had a catastrophic design flaw, namely the severe shortage
of lifeboats, where at best only 50% of those onboard would have been able to obtain
a seat. This would indicate that some allocation system had to have been used in the
evacuation process. Given that those individuals who did not secure a lifeboat seat
Chapter 2: Theoretical Background 15
were guaranteed a death sentence, it was in the best interest of all individuals on the
vessel to secure a seat (survival). Failure to secure a seat or refusal to compete/queue
for one resulted in the same, worst possible outcome that is death of the individual.
The first come first served (FCFS) system was deemed to be the fairest method of
allocation for a scarce resource over any other method (Frey & Pommerehne, 1988;
Savage & Torgler, 2008). If this FCFS system was implemented we would possibly
see a much more random survival effect and not such a strong social norm effect.
However that is not to say that no queuing effect was evident, and may in part
explain the much higher rate of British deaths.
Chapter 3: Methodological Background 17
Chapter 3: Methodological Background
3.1 EXPERIMENTATION: LABORATORY VS FIELD
The analyses of these events are done post mortem, as opposed to peri mortem and
unlike laboratory experimentation, disasters do not afford the researcher the ability to
formulate questions or model the event beforehand. These result in less than perfect
data, with missing data or pertinent questions not posed to respondents. Therefore,
complex or multivariate analysis is required to formulate clearer pictures about what
happened post event. Given that it was not possible to observe the event directly, any
analysis of this event must in a sense work backwards, here the outcome is known
and the analysis attempts to determine the factors that are most likely to be
responsible for it. This is in essence what the first work is about (Chapter 4)
estimating the determinants of survival during the Titanic disaster. In other research
areas, it is possible to create simulations or laboratory experimentations to test
hypothesis under controllable conditions. However, several serious problems arise
when conducting experiments on these types of events, such as believability and
natural reaction. Amato (1990) has criticised that ―Researchers who value the rigor of
the laboratory have been reluctant to extend the study of prosocial behaviour to
everyday life, where the possibility of control is minimal‖ (p. 31). It is well
understood that individuals alter behaviour under experimental conditions if they are
aware of being observed. Such that the actions taken are not an accurate or
representative reflection of that individual‘s normal behaviour. Additionally, these
types of laboratory experiments do not create the stress and pressures needed to
simulate the life and death nature of true disasters. Both these factors result in
inaccurate and often mixed reactions to experimental modelling.
Another criticism is the use of field data in a multiple regression context instead of
non-random experimental data. Multiple regressions are not fully able to estimate
without noise the single estimate for the effect of stress on performance as it is
18
18 Chapter 3: Methodological Background
impossible to measure all the variables that might conceivably affect performance.
Allison (1999, p. 20) nicely points out ―No matter how many variables we include in
a regression equation, someone can always come along and say, ―Yes, but you
neglected to control for variable X and I feel certain that your results would have
been different if you had done so‖. The question now arises whether we are able to
find work environments that are close to an experimental setting.
Thus these events can be considered a quasi-natural experiment where subjects are
acting in the natural environment instead of an artificial laboratory environment
(natural incentives to perform). It has been shown that experiments performed in an
environment where the test subjects are keenly aware that their behaviour is being
monitored are prone to change their normal behaviour such that it is difficult to
generalize the results (Levitt and List, 2009). Moreover, selection effects are also
visible when recruiting subjects for (lab) experiments (e.g., ―scientific do-gooders‖
interested in research). Individuals in these events compete in an actual high stakes
contest (life and death), in a very controlled environment. This realism provides
researchers with a clear advantage over laboratory, self-reporting and other forms of
experiments while maintaining the randomness of natural data (Reiley and List,
2007). Additionally, laboratory experiments are unable to replicate or even
approximate the levels of stress and danger to provide sufficient threat of panic in
test subjects. The disaster events are also relatively controlled events where all
participants encounter the same environmental variables, which allow for a large
number of the exogenous (external) factors to be controlled, such that the
environmental and situational conditions were identical for every individual onboard
these vessels.
However, these natural field experiments are not with their limitations, by gaining the
randomness and natural behaviour of the participants the experimenter loses some
control over the experiment. This is especially true in the case of the Titanic, the
event was not observed firsthand and analysis is done post mortem without the
chance to implement experimental controls. Thus this is not a true natural field
experiment but is very close in this instance. Each event was impacted by an
exogenous shock that affected everyone onboard in the same manner, individuals
19
Chapter 3: Methodological Background 19
were not able to abstain from or remove themselves from the effects of the event.
This meant that all individuals had to partake, those not willing to participate in the
event received the same outcome as those who did participate and failed to secure a
safe seat, death. In addition, we can largely exclude that potential helping behaviour
could have been driven by future reciprocity. Such a life-and death-situation can be
seen as a ―one-shot game‖.
The Titanic and Lusitania disasters fit remarkably well into the model of a quasi-
natural field experiment, every individual was involved in the event (willing or not)
and the situation was enclosed, all individuals in the experiment were known and no
one was able to leave. This type of experiment would not have worked as well for an
open type of event, where the number of individuals involved in the experiment was
unknown, such as the September 11 World Trade Centre (WTC) attacks. Where
number of victims is known but the exact numbers of individuals within the complex
at the time of the initial incident means it is not possible to perform such a
determinant analysis.
3.2 ESSAYS
While the unfortunate and tragic loss of life from these types of disasters is indeed
sorrowful, these events do provide me with an excellent source of data that has
enabled examination of the decision-making processes of individuals under extreme
pressure. In these types of life and death events individuals are forced to make
choices that will affect their probability of surviving. Both events demonstrated
similar excess of demand situations for the limited lifeboats available, albeit for
slightly different reasons that will be discussed further. Failure to evacuate or failure
to secure a lifeboat seat virtually guaranteed death of an individual. Additionally all
individuals were required to make a decision about competing for lifeboat seats as
failure to make a decision carried the same costs as failing to secure a seat, a high
probability of death.
20
20 Chapter 3: Methodological Background
The essays presented in this work are the first steps into a much larger study, into
which the decision making process of individuals will be examined in many extreme
environmental conditions. The essays are presented such that they form a logical
experimental progression, beginning with a determinants study, to hypothesis testing
and finally to imposing an experimental treatment. The three essays presented here
are collaborative works, co-authored by Professor Bruno S. Frey, Professor Benno
Torgler and myself. The first essay, entitled ―Noblesse Oblige? Determinants of
Survival in a Life and Death Situation,‖ is forthcoming in the Journal of Economic
Behaviour and Organisation (JEBO) and as such has been included as submitted.
Additionally the second essay, entitled ―Surviving the Titanic: Economic, Natural
and Social Determinants,‖ has been included as submitted. The final essay included
in this work is an amalgamation of two papers, entitled ―Should I stay or Should I go
Now?‖ and Time and Tide: Constrained Altruism?‖ Both of these papers have been
included in this format so both economic and non-economic perspectives into the
comparative Lusitania event can be considered.
The first essay explores what determines the survival of people in a life–and-death
situation. The sinking of the Titanic allows us to inquire whether pro-social
behaviour matters in such extreme situations. This event can be considered a quasi-
natural experiment. The empirical results suggest that social norms such as ‗women
and children first‘ are persevered during such an event. Women of reproductive age
and crewmembers had a higher probability of survival. Passenger class, fitness, group
size, and cultural background also mattered. The second essay develops a simple
theoretical framework that allows us to develop nine hypotheses (arranged according
to whether they belong to what can be called ―economic,‖ ―natural,‖ or ―social‖
factors) that can be tested using the data on who survived and who perished in the
Titanic disaster. The motivation for the economic, natural and social factors is
developed within the paper and thus not included here (see chapter 5).
Finally, the third essay explores the interaction of natural survival instincts and
internalized social norms using data on the sinking of the Titanic and the Lusitania.
We show that time pressure is crucial when explaining behaviour under extreme
conditions of life and death. Even though the two vessels and the composition of
21
Chapter 3: Methodological Background 21
their passengers were quite similar, the behaviour of the individuals on board was
dramatically different. On the Lusitania, selfish behaviour dominated (which
corresponds to the classical homo economicus); on the Titanic, social norms and
social status (class) dominated, which contradicts standard economics. This
difference can be attributed to the fact that the Lusitania sank in 18 minutes, creating
a situation in which the short-run flight impulse dominates behaviour. On the slowly
sinking Titanic (2 hours, 40 minutes), there was time for socially determined
behavioural patterns to re-emerge.
Knowing human behaviour under extreme conditions allows us to gain insights about
how varied human behaviour can be depending on differing external conditions. The
study of the Titanic sinking may also have major policy consequences beyond that
implemented shortly after the disaster (e.g. life boat regulations and evacuation
training drills). Do more stringent safety regulations crowd out intrinsically moral
behaviour, and could they possibly lead to worse outcomes than less strict
regulations? These events demonstrate that behaviour of individuals in disaster
events does not follow the traditional mythology of mass panic. Their behaviour is
neither random nor inexplicable and as such it can be accounted for by using
economic analysis. ―Disaster planning is only as good as the assumptions it is based
upon. Unfortunately this planning is often based upon a set of conventional beliefs
that have been shown to be inaccurate or untrue when subjected to empirical
analysis…It is more efficient to learn what people tend to do naturally in disasters
and plan around that, rather than design your plan and then expect people to conform
to it.‖ (Heide 2004: p340). These works demonstrate that economic analysis can
account for human behaviour in such situations. And those simple models of
behaviour do not fully predict survival outcomes. It could be that a mixed strategy
approach may provide better modelling outcomes. Through these better models,
better plans can be made to help after disasters, which will in turn improve the
survivability of individuals caught in these types of events.
Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation 23
Chapter 4: Noblesse Oblige? Determinants
of Survival in a Life and Death
Situation
Statement of Contribution of Co-Authors for
Thesis by Published Paper
The authors listed below have certified* that:
1. they meet the criteria for authorship in that they have participated in the conception, execution, or
interpretation, of at least that part of the publication in their field of expertise;
2. they take public responsibility for their part of the publication, except for the responsible author
who accepts overall responsibility for the publication;
3. there are no other authors of the publication according to these criteria;
4. potential conflicts of interest have been disclosed to (a) granting bodies, (b) the editor or publisher
of journals or other publications, and (c) the head of the responsible academic unit, and
5. they agree to the use of the publication in the student‘s thesis and its publication on the
Australasian Digital Thesis database consistent with any limitations set by publisher requirements.
In the case of this chapter:
Noblesse Oblige? Determinants of Survival in a Life or Death Situation.
October 2008 - Forthcoming in Journal of Economic Behavior and Organization.
Contributor Statement of contribution*
David A. Savage
Has equally contributed to all aspects of this paper, including research, analysis
and writing
Date 3/11/2009
Bruno S. Frey*
Has equally contributed to all aspects of this paper, including research, analysis
and writing
Benno Torgler*
Has equally contributed to all aspects of this paper, including research, analysis
and writing
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24
24 Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation
How selfish soever man may be supposed, there are evidently some principles in his
nature, which interest him in the fortune of others, and render their happiness
necessary to him, though he derives nothing from it, except the pleasure of seeing it.
The Theory of Moral Sentiments (Smith, 1790)
4.1 INTRODUCTION
At the very core of economics lies the question of scarcity, or ―how society makes
choices concerning the use of limited resources‖ (Stiglitz, 1988). To achieve utility-
maximization from a limited set of resources, traditional economic models assume
that individuals are exclusively pursuing their material self-interest. The Homo
Economicus theory has shown to be useful in many cases. However, substantial
evidence has been generated that suggests that other motives, such as altruism,
fairness, and morality profoundly affect the behaviour of many individuals. People
may punish others who have harmed them or reward others who have helped them,
sacrificing their own wealth (Camerer, Loewenstein & Rabin, 2004). People donate
blood or organs without being compensated; they donate money to charitable
organizations. During wartime many individuals volunteer to join the armed forces
and are willing to take high risks as soldiers (Elster, 2007). Citizens vote in elections
incurring higher private costs than benefits and people show greater tax compliance
than a traditional economics-of-crime model would predict (Torgler, 2007).
Individuals also help others in many situations in the workplace (Drago & Garvey,
1998). In many experiments subjects have shown to care about aspects as fairness,
reciprocity, and distribution. Ultimatum experiments have shown that the modal offer
is (50, 50) and that the mean offer is somewhere around (40, 60). This also
demonstrates that the smaller the offer, the higher the probability that the offer will
be rejected (Ochs & Roth, 1989; Roth, 1995). We also observe helping to be a key
element in our work environment ―Within every work group in a factory, within any
division in a government bureau, or within any department of a university are
countless acts of cooperation without which the system would break down. We take
these everyday acts for granted, and few of them are included in the formal role
prescriptions for any job‖ (Katz & Kahn, 1966).
25
Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation 25
Individuals compare themselves to their environment and care greatly about their
relative position, which can influence individual choices. Thus, not only is the
absolute level of an individual‘s situation important (e.g. income), but also the
relative position. Researchers have included the concept of interdependent
preferences to allow for social comparison (e.g., Akerlof & Yellen, 1990; Becker,
1974; Clark et al., 2008; Easterlin, 1974; Frank, Meyer & Miyahara 1995; Pollak,
1976; Schelling, 1978; Scitovsky, 1976). Frank (1999) emphasizes that research
provides ―compelling evidence that concern about relative position is a deep-rooted
and ineradicable element in human nature‖ (Frank, 1999:p. 145).
Thus, several approaches try to take into account the deviation of a self-interested
model by extending the motivation structure (e.g. Andreoni & Miller, 2002; Becker,
1974; Bolton & Ockenfels, 2000; Dufwenberg & Kirchsteiger, 2004; Fehr &
Schmidt, 1999; Frey, 1997; Rabin, 1993; Sobel, 2005). In general, Thaler (2000)
stresses that the Homo Economicus will evolve to Homo Sapiens: ―As economists
become more sophisticated, their ability to incorporate the findings of other
disciplines such as psychology improves‖ (Thaler, 2000:p. 140).
Despite the large number of studies in this area, there is hardly any empirical
evidence that demonstrates that interdependent preferences and pro-social behaviour
matter in extreme situations such as life-and-death situations. This paper tries to
rectify this shortcoming by exploring this question using data from the sinking of the
RMS Titanic, the most recognizable maritime disaster in history. While the
unexpected loss of life from this tragedy was indeed sorrowful, the event provides us
with data that help us to better understand decision-making processes under extreme
pressure. Individuals are forced to make choices that affect their probability of
surviving. What makes the event interesting for research is that it is a contained and
controlled event; much like a natural field experiment would be designed, wherein
the majority of the exogenous factors are controlled and the endogenous factors can
be tested and investigated. The environmental or situational conditions were identical
for every person on board the Titanic. This allows us to explore behavioural reactions
to an external shock, as well as to investigate people‘s behaviour under scarcity. The
26
26 Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation
issue of scarcity or shortage arose, as there existed a severe lack of lifeboats. The
Titanic carried only 20 lifeboats adequate for 1178 people (or 53% of the passengers
on board). The problem was exacerbated further by the panicked deck crew, who
began launching lifeboats that had not been loaded to capacity. This meant an excess
demand situation as people wishing to survive had to compete with others on board
for a place on the lifeboats. A failure to secure a seat virtually guaranteed death as the
average water temperature of the surrounding ocean was approximately 2 degrees
Celsius (35 Fahrenheit). Anyone left in the freezing water would quickly succumb to
hypothermia and drown. We can expect a certain level of agreement among those
already in a lifeboat and those still waiting to board a lifeboat to limit the lifeboat to
its maximum safe load to avoid the boat falling into serious danger (Martin, 1978). In
addition, we can largely exclude that potential helping behaviour could be motivated
by future reciprocity, a key element in the helping literature (e.g. Batson et al., 1979;
Gouldner, 1960). A life-and-death situation can be seen as a ―one-shot game‖.
Moreover, previous research has shown that legitimacy affects helping behaviour.
Legitimate need elicits more help than does illegitimate need (e.g. own laziness)
(Berkowitz, 1969; Schwartz & Fleishman, 1978). In our case, people were
confronted with an ―external shock‖ which in a substantial manner helps to control
legitimacy.
Thus, the intention of the paper is to investigate the decisions made under these
extreme conditions and see if the survival outcomes fit with the literature on
interdependent preferences. The key question is whether we are able to observe social
norms, fairness and social preferences in a life or death situation.
4.2 THEORETICAL BACKGROUND
Previous studies have explored the link between fairness and shortage using survey
data. In telephone surveys of randomly selected residents of two Canadian
metropolitan areas, Kahneman, Knetsch & Thaler (1986a) has shown that people
consider the use of prices to eliminate the excess of demand to be unfair. This is
consistent with the observation that firms do not adjust prices and wages as often as
traditional economic theory would suggest. Moreover, we also observe formal laws
27
Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation 27
that penalize vendors who take advantage of shortages by increasing prices for water,
fuel and other necessities after a natural disaster (Camerer et al., 2004). Frey &
Pommerehne (1993) and Savage & Torgler (2008) replicated the study using
European samples, and found similar results. In a shortage situation an allocation
process in line with tradition (first-come, first-served) is perceived to be fairest,
followed by administrative allocation procedures. However, in contrast to these
studies, which consider attitudes we explore behavioural consequences of excess
demand in a life-and-death situation.
Our research focus is closely linked to the question in line with the traditional
economic approach, whether people behave according to the notion ―every man for
himself‖ or whether a ―helping hand‖ effect can be observed. Interestingly, the
willingness to help others in such situations is not uncommon. (Perlow & Weeks,
2002) stress that helping behaviour is required within organizations for increased
efficiency, flexibility, learning and innovation: ―Therefore, it has never been more
important for us to understand why people help each other at work and why they
don‘t‖ (Perlow & Weeks, 2002:p. 343). Shotland and Stebbins (1983) refer to two
lines of thoughts: firstly an ―altruism school‖ with the premise that people have a
need (innate or acquired) to help others in need; secondly a ―hedonistic base‖ that
suggests that people weigh the benefits and costs to themselves to reach the decision
to help or not (Shotland & Stebbins, 1983:p. 36). The second one is close to a
traditional economic approach.
Helping behaviour is not only linked to altruism (Piliavin & Charng, 1990), but also
to reciprocity or exchange (Fehr, Fischbacher, & Gachter, 2002; Henrich, 2004;
Oberholzer-Gee, 2007). The idea of reciprocity is helping those who have helped us.
Exchange not only focuses on direct reciprocity but also on expectations that lead to
solidarity and indirect reciprocity in more anonymous settings such as, helping lost
tourists (Rabinowitz et al., 1997). However, as discussed in the introduction, in the
case of the sinking of the Titanic, we are able to exclude such motivation due to the
nature of the event studied.
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28 Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation
Altruistic motivation has been defined as the desire or motivation to enhance, as the
ultimate goal, the welfare of others even at a net welfare loss to oneself (Batson,
1992; Elster, 1996). An additional definition of an altruistic act is ―an action for
which an altruistic motivation provides a sufficient reason‖ (Elster, 1996). However,
altruistic behaviour is often framed described as being somewhat selfish. It is stressed
that what appears to be motivated by a concern for others is often ultimately driven
by selfish motives (Piliavin & Charng, 1990). The differentiation between motivation
and act is useful, as identifying altruistic motivation is problematic. For example, a
so-called ―warm glow effect‖ can be observed when people give. Giving makes
people feel good. Piliavin and Charng (1990) when summarizing the literature refer
to a ―paradigm shift‖ that emphasizes the importance of altruistic behaviour: ―The
central point we attempt to make in this review is that the data from sociology,
economics, political science, and social psychology are all at least compatible with
the position that altruism is part of human nature. People do have ―other regarding
sentiments‖, they do contribute to public goods from which they benefit little, and
they do sacrifice for their children and even for others to whom they are not related‖
(Piliavin & Charng, 1990:p. 29).
When people sacrifice their life or when they increase the fitness or the survival
possibility of others in the Titanic disaster, at the expense of their own survival
chances, we are observing altruistic behaviour. Self-sacrifice can be seen as an
extreme form of altruism. For example, Krebs (1991) stresses: ―On my definition of
altruism, behaviours directed toward the enhancement of the welfare of another
increase in altruism in proportion to the anticipated costs to self: Risking your life to
save a drowning person is more altruistic than throwing him or her a lifesaver‖
(Krebs, 1991:p. 137). A person could have done better for herself not helping others
and therefore ignoring the effects of her choice on others (Margolis, 1982). Such a
notion is consistent with the definition of altruism in social biology (Wilson, 1975).
There are various approaches to model altruistic behaviour. An altruistic individual i
would have the following function:
29
Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation 29
Ui = Ui (si, sj), (1)
where si, sj measure the survival probability of i and other individuals j. If i were an
egoist the utility function only depends on his own survival. This can be modelled
using the following specific utility function:
jij
ijii sssU )( (2)
ij is a factor that shows how much individual i cares about j. If i doesn‘t care at all,
i‘s utility only depends on the own survival. A positive ij reflects altruism. The
utility of i increases when individual j survives. On the other hand, a negative ij
reflects spite (Sobel, 2005). The utility of i decreases if individual j has a higher
probability of surviving. The degree of ij depends on the relation (closeness)
between i and j. Higher positive values are expected for family members and friends.
Personal and societal norms are implicated in altruism (Piliavin & Charng, 1990).
Altruistic motivation may be driven by moral norms such as sharing equitably or
helping others in distress (Elster, 2006). Norms are the generally accepted conditions
under which society functions, guiding how individuals act and behave towards each
other. They are adopted and enforced by members of that society and are not always
in the best interest of the individual within that society (Elster, 1985). Elster (2007)
sees moral norms as unconditional while social norms are conditional and therefore
influenced by the presence or the behaviour of other people (Elster, 2007:p. 104.). A
key norm that we are going to explore is ―women and children first‖. Interestingly, no
international maritime law requires that women and children are rescued first. Such a
social norm was first documented during the sinking of HMS Birkenhead in 1852.
The Birkenhead sank only twenty-five minutes after having struck a rock off the
South African coast. The seven women and thirteen children onboard were rowed
away from the wreck to safety. Captain Seton drew his sword ordering men to ―stand
an‘ be still‖ (Kipling, 1892) to avoid men rushing to the lifeboats putting the life of
women and children in danger. Similar norms have been found in other areas where
people had to be evacuated. Humanitarian agencies often first evacuate ―vulnerable‖
30
30 Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation
and ―innocent‖ civilians such as women, children and the elderly. The Geneva
Convention provides special protection and evacuation priority for pregnant women
and mothers of young children (Carpenter, 2003).
How can we explain that such a social norm may arise? Helping children and women
as their caregivers serves to strengthen the chances of their survival and thereby helps
to guarantee the survival of future generations. This may explain why it was also
considered vital for women to be rescued. Behavioural evidence is consistent with
the norm of social responsibility. For example, studies report that motorists are more
willing to stop on a busy street for a woman who is pushing a baby carriage than for a
woman who is pushing a grocery cart (Harrell, 1994). Helping behaviour is also
exhibited during common threat situations (Batson et al., 1979). An increased level
of helping behaviour may be observed during situations of common threat that may
generate ―we-feelings‖ and as a consequence a concern for the welfare of others
(Worman, 1979). In other words closeness strongly correlates to helping behaviour
(Amato, 1990) and being connected during an external and shocking event may
induce closeness.
Eagly and Crowley (1986) in their meta-study report that traditional male gender
roles may matter and encourage chivalrous and heroic acts. The results show that
men may be predisposed to being more helpful than women during situations which
women judge to be more dangerous than men do. Moreover, women usually receive
more help than men and males believe themselves to be more competent and more
comfortable helping than females. This would suggest a higher probability of
survival among females.
In addition, socio-biology also stresses the relevance of the ―procreation instinct‖.
The survival of a species relies on its progeny; thus a high value must be placed upon
females of reproductive age as a valuable resource. Social norms may be created to
protect the reproductive and child-rearing role of women. It is an attempt to protect
children rather than the desire to help a woman. A potential shortage of women
would limit the number of offspring, while a shortage of men would not (Felson,
2000).
31
Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation 31
In humans the period of peak reproduction is between the age of 15 and 35
(American Society for Reproductive Medicine, 2003). Prior to age 15 females on
average are not yet reproductively functional and after the age of 35 the reproductive
cycle begins to slow until at about 50 the reproductive function is lost. Others also
stress that the emergence of a social norm, which gives preference to women, may be
related to an increased physical and structural vulnerability in women (Felson, 2000).
Females may also have a strong incentive to guarantee the survival of their children.
In the study of anthropology “parental investment” is an important concept. The
study argues that females of most species invest more in the survival of their
offspring than males do. Females invest a whole range of benefits, over a period of
time, on their offspring starting with the gestation period, lactation, predatory
protection and education (Geary, 1998) whereas a male‘s investment is much
smaller. Because of this much larger investment the opportunity costs of losing
offspring are much higher and the drive to ensure offspring survival is therefore
much stronger (Campbell, 1999). It has been shown that the mortality rates of
children with a surviving mother are 1.4 times lower than those without (Voland,
1998). The survival rates of offspring can be directly linked to maternal survival
(Bjorklund & Shackelford, 1999). Under these conditions it would be expected that
females with children would be much more wary of possible danger and would
aggressively fight other females to ensure a safe haven (Cashdan, 1997). Moreover, it
has been stressed that the sex that puts in greater parental investment to promote the
prosperity of offspring, is the more valued resource (Eswaran & Kotwal, 2004;
Trivers, 1972).
4.3 EMPIRICAL RESULTS
Amato (1990) criticizes that a large amount of literature in this area of helping is
laboratory-based: ―Researchers who value the rigor of the laboratory have been
reluctant to extend the study of prosocial behaviour to everyday life, where the
possibility of control is minimal‖ (Amato, 1990:p. 31). Working with the Titanic data
provides an alternative strategy to explore whether ―social norms of helping‖ survive
32
32 Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation
in a real life-and-death situation. We cannot observe the detailed rescue process but
we can evaluate the overall outcome, which provides an indication about the level of
social norms or altruism among crew and passengers.
We use a probit model of the survival probability for a typical Titanic passenger:
Pr (y = 1 | x1, x2, …, xk ) = ( + 1x1 + 2x2 + … + kxk). (3)
Here y is a dummy variable indicating whether the passenger survived (y = 1) or not
(y = 0); the variables (x1, x2, …, xk) are explanatory variables such as gender, age,
etc; ( , 1, 2, … k) are parameters to estimate; and is the cumulative standard
normal distribution function. The role of , which is increasing in its argument, is to
keep the probability Pr(y = 1) in the zero to one interval. Each passenger contributes
one observation on (y, x1, x2, …, xk). From a sample of such observations, assumed
independent, the parameters can be estimated by maximum likelihood. This is a
standard probit model.
Since the coefficients are difficult to interpret directly, the marginal effect of a
continuous explanatory variable xj will, as usual, be interpreted through the partial
derivative
Pr(y 1 | x1,x2,...,xk )
x jj ( 1x1 2x2 kxk ) , (4)
evaluated at the means, where is the standard normal density function (not the
cumulative density ). Since > 0, the sign of the marginal effect is the same as the
sign of j. For a discrete xj, a difference rather than a derivative will be used in place
of (4).
Tables 4.1 and 4.2 present the results. For each coefficient of each probit, we report
the maximum likelihood estimates of the coefficient (first value), the z-statistic (ratio
of coefficient to its standard deviation, in italics), and the marginal effect (in bold).
33
Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation 33
At the bottom of the table, for each probit, we also report the sample sizes and the
pseudo-R2s. The pseudo-R2 is 1–(L1/L0), where L0 is the log-likelihood value for
the null model excluding all explanatory variables, and L1 is the log-likelihood value
for the fitted model.
Our gender variable (female=1) will be a key factor that we will explore. We predict
that the coefficient is statistically significant with a positive sign. In addition, we will
observe whether children and women with children have a higher probability to
survive. To measure the age range of a child we use the United Nations provisional
guidelines of standard international age classifications (United Nations, 1982). The
guidelines classify children as up to the age of 15. Moreover, to develop further age
dummies we rely on an age notion that the British Royal Commission used in 1870-
74 and which appeared in a subsequent Act in 1875 in regard to age benefits. The
transition into ―old age‖ was defined to begin at 50 (e.g. Arias, 2004; Boyer, 1988;
Eysenck, 2004; Gorsky, 1998). We will also explore whether females in their
reproductive age are more likely to survive compared to other women. Moreover, we
will examine (check) whether individuals or females with a larger potential pool of
helpers (family members) have a higher probability of surviving.
In addition to controls for gender, age and family or travel group size9, we also
explore the following independent variables: passenger-class, crew member, and
nationality. The data was generated from numerous sources, in particular the
Encyclopaedia Titanica (Encyclopaedia Titanica, 2008). Passengers were separated
into three different classes, namely: first class, second class and third class. It can be
expected that first class passengers tried to obtain preferential treatment. A higher
level of (bargaining) power, better access to information about imminent danger,
persons of power and decision makers such as leading crew members may facilitate
(lead to a better) access to lifeboats and therefore raise the probability of survival.
Moreover, first class cabins were closest to the boat deck. We control for nationality
9Singles, singles with children, singles with servants, couples, couples with children, couples with
servants, families/friends, families/friends with children and families/friends with servants. The
families/friends groups include extended family groups and groups of friends travelling together as a
34
34 Chapter 3: Noblesse Oblige? Determinants of Survival in a Life and Death Situation
as previous studies on helping behaviour did report cultural differences (Perlow &
Weeks, 2002). Moreover, it is worthwhile to explore differences between the crew
and the passengers. Crew members are better prepared for a catastrophic event and
are also in the position of obtaining the information earlier than the passengers. They
could use this information advantage to generate a higher survival rate. They have
also better access to important resources such as lifeboats. On the other hand, they
are restrained by the expectation to be among the very last to leave the sinking ship.
Table 4.1 presents the empirical results for the first set of estimations. We begin by
first examining if we can find the expected gender effect. In the first four
specifications we only include the coefficient FEMALE in the specification, focusing
on all the individuals on board the Titanic (see specification 1), only passengers (2),
crew members (3), and couples (4). The results indicate that a strong gender effect
exists. Being female rather than male increases the probability of surviving between
23.7% (specification 3) and 53.9% (specification 4).
In a next step we explore whether children also have a higher probability of
surviving. In specification (5) we focus only on passengers, controlling for passenger
class using the age dummies AGE Sub 15 (age 15 and below), AGE 16-50 and
AGE51+ (which is the reference group) to explore the age-survival relationship. The
results support the notion that children have a higher probability of survival than
other age groups reporting the largest marginal effects. Being a child rather than a
person AGE 51+ (reference group) increases the probability of survival by 32%.
Moreover, the coefficient AGE 16-50 is also statistically significant. Thus, we find a
negative relationship between age and survival probability.
Specification (5) and the following ones in Table 4.1 also show that first and second-
class passengers have a higher probability of survival. Being a first class passenger as
opposed to a third class passenger (which is the reference group) increases the
party families/friends groups include extended family groups and groups of friends travelling together
as a party.
Chapter 4: Noblesse Oblige? Determinants of Survival in a Life and Death Situation 35
Table: 4.1 Survival Probability and Pro-Social Behaviour
Probit
All Passenger Crew Couple Passenger All All Couples All All All
[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11]
FEMALE 1.413**
*
1.462*** 1.858**
*
1.477**
*
1.469*** 1.493**
*
1.488**
*
1.702**
*
1.517**
*
1.509*** 1.512***
20.22 18.34 5.50 10.29 17.39 18.29 18.16 9.8 18.11 17.98 17.84 0.517 0.529 0.237 0.539 0.530 0.542 0.541 0.605 0.550 0.547 0.548
AGE SUB 15 0.832*** 0.764**
*
0.758**
*
0.745**
*
0.745*** 0.753***
4.12 3.94 3.89 3.76 3.75 3.77 0.322 0.293 0.291 0.286 0.285 0.289
AGE 16 - 50 0.474*** 0.416**
*
0.445**
*
0.463**
*
0.462*** 0.469***
3.01 2.84 3.01 3.11 3.10 3.14 0.162 0.131 0.139 0.143 0.143 0.145
CREW 0.536**
*
0.546**
*
0.493**
*
0.649*** 0.631***
6.51 6.61 5.42 5.62 5.37
0.189 0.193 0.174 0.229 0.223
1st CLASS 1.149*** 1.140**
*
1.122**
*
0.833**
*
1.194**
*
1.173*** 1.136***
10.95 10.92 10.68 3.85 10.91 10.67 9.36 0.432 0.429 0.422 0.320 0.448 0.440 0.427
2nd CLASS 0.409*** 0.407**
*
0.390**
*
1.577**
*
0.412**
*
0.481 0.454***
3.93 3.9 3.72 7.9 3.89 4.34 3.97 0.156 0.150 0.144 0.569 0.153 0.179 0.169
HAS CHILD/
CHILDREN
0.523**
*
0.596**
*
0.713**
*
0.688 0.682***
2.69 2.77 3.39 3.26 3.22 0.199 0.234 0.274 0.264 0.261
SMALL
GROUP
(Couples)
-0.274** -0.254 -0.252***
-2.47 -2.28 -2.25 -0.090 -0.084 -0.084
LARGE
GROUP
(Families)
-0.479 -0.033 -0.023
-0.47 -0.33 -0.22 -0.017 -0.012 -0.008
ENGLAND
(1143)
-
0.201***
-2.20
-0.070
IRELAND
(114)
0.140
0.85 0.050
SWEDEN
(106)
0.068
0.40 0.024
USA (424) 0.236**
2.18 0.085
ALL OTHER
NATIONS
(399)
0.206*
1.89 0.040
Obs. 2186 1300 886 376 1300 2186 2186 376 2186 2186 2186
Pseudo R2 0.161 0.211 0.041 0.221 0.286 0.209 0.212 0.389 0.214 0.216 0.216
Notes: z- values in italics, marginal effects in bold. The symbols *, **, *** represent statistical significance at the 10%, 5%
and 1% levels, respectively.
36
36 Chapter 4: Noblesse Oblige? Determinants of Survival in a Life and Death Situation
probability of survival by about 40%. Thus, more (bargaining) power, better access to
information and lifeboats increases the probability of survival quite substantially.
In specification (6) we work with the entire data set using a CREW dummy variable.
The results show that crew-members had a higher probability of survival which may
indicate their taking advantage of their increased opportunities (better possibilities) to
acquire resources and to be informed which promoted their survival rate. Thus, such
a result is more in line with a self-interested approach.
In a next step specification (7) and in the following ones we explore whether having
a child increases the survival rate of an individual. This is indeed the case. Having a
child increases the probability of survival by 20%. This effect in part explains not
only the social norm of ―children first‖, but also the parental investment norm.
Having children motivates parents (especially mothers - women being the main
caregivers at that time) to fight harder for their child‘s survival. Helping children
increases the possibility of guaranteeing the survival of future generations.
In specification (8) we again focus on couples only. We find that passenger class and
having children also mattered. In this specification we observe the strongest gender
effect. A possible explanation could be that husbands and fathers fought to secure a
place on a lifeboat for their wives and children but perished as they did not attain a
seat for themselves. Specifications (9) to (11) allow us to explore whether being
active within a small or large group increases the probability of survival. Joint efforts
may lead to a higher probability of survival, but they may also lead to a lower level of
flexibility during critical situations. The results indicate that both coefficients, the
one for small groups (couples) and large groups (families), are negative. Thus, people
acting alone have a higher probability of survival. There is even a statistically
significant difference for the smaller group.
Finally, in the last two specifications in Table 4.1 we control for nationality. First we
include a dummy for the single largest group on board: people from England. We
find that English people had a lower probability of survival. To deal with the
heterogeneous structure of the reference group in specification (10) we use people
37
Chapter 4: Noblesse Oblige? Determinants of Survival in a Life and Death Situation 37
from England as the reference group in specification (11) and compare them with
other nationalities such as the US Americans, Irish, Swedes and the remaining
countries. Interestingly, the results show that Americans had ceteris paribus the
highest probability of surviving.
Next we investigate the survival factors among females. This allows us to test, for
example, if indeed a higher priority is placed upon females in their prime
reproductive age. We therefore construct three dummy variables, namely age 16-35,
age below 16 and age 36+. Table 4.2 presents the results. The findings indeed
indicate that women in their prime reproductive age were more likely to survive.
Compared to the reference group (age 36+) their probability increases by more than
16% (see specification 12). This result remains robust after including further factors
(see other specifications).
We again observe a passenger class effect. Table 4.2 shows that the class coefficients
report the largest marginal effects. Being a first class passenger increased the
probability of surviving among women by around 40%. Interestingly, there exists no
statistically significant difference between children and the reference group. One
reason could be that several women above the reproductive age may be active as
caregivers.
Specifications (14) to (18) show that having a child increases, ceteris paribus, the
probability of surviving among women. Interestingly, we observe that female
crewmembers also had a higher probability of survival. The quantitative difference is
quite substantial (close to 20%). On the other hand, being in a small group (with only
a partner) reduces the probability of survival while being part of a larger group
(family) does not lead to a statistically significant difference in relation to women
who are travelling alone. Finally, Table 4.2 shows that nationality does not matter.
Thus, the advantage of being a US citizen disappears when the focus lies on women
only.
38
38 Chapter 4: Noblesse Oblige? Determinants of Survival in a Life and Death Situation
Table: 4.2 Survival of Women
Probit
Passenger All All Couples All All All
[12] [13] [14] [15] [16] [17] [18]
AGE SUB15 0.147 0.060 0.086 0.993 -0.011 -0.012 0.054
0.61 0.25 0.35 1.15 -0.04 -0.05 0.21 0.044 0.017 0.023 0.089 -0.003 -0.003 0.015
AGE 16 – 35 0.528*** 0.421** 0.457** 0.272 0.473*** 0.472*** 0.425**
2.85 2.39 2.55 0.83 2.62 2.60 2.29 0.169 0.125 0.132 0.048 0.135 0.135 0.121
CREW DUMMY 1.177*** 1.22*** 1.007*** 1.014*** 1.031***
3.41 3.54 2.81 2.64 2.66 0.200 0.194 0.174 0.175 0.177
1st CLASS 1.964*** 2.001*** 1.99*** 2.899*** 2.170*** 2.168*** 2.138***
7.96 8.45 8.21 6.04 8.74 8.69 7.89 0.415 0.403 0.389 0.527 0.408 0.407 0.403
2nd CLASS 1.131*** 1.118*** 1.111*** 1.168*** 1.202*** 1.205*** 1.188***
6.40 6.37 6.25 3.77 6.43 6.11 5.80 0.274 0.241 0.231 0.136 0.240 0.241 0.238
HAS CHILD / CHILDREN 1.024** 1.45*** 1.457*** 1.456*** 1.536***
2.37 2.98 3.18 3.17 3.16 0.186 0.154 0.215 0.215 0.220
SMALL GROUP (Couples) -0.661*** -0.660*** -0.623***
-3.43 -3.40 -3.18 -0.197 -0.196 -0.185
LARGE GROUP (Families) -0.167 -0.166 -0.154
-0.95 -0.94 -0.86 -0.047 -0.047 -0.044
ENGLAND -0.009
-0.05 -0.003
IRELAND 0.203
0.76 0.052
SWEDEN -0.413
-1.40 -0.130
USA 0.016
0.07 0.0040
ALL OTHER
NATIONS
0.045
0.21 0.012
Obs. 433 482 482 169 482 482 482
Pseudo R2 0.2198 0.2338 0.2466 0.4505 0.2683 0.2683 0.2761
Notes: z- values in italics, marginal effects in bold. The symbols *, **, *** represent statistical significance at the 10%, 5%
and 1% levels, respectively.
4.4 CONCLUSIONS
There has been little evidence available that illuminates whether interdependent
preferences or prosocial behaviours matter in extreme situations such as life-and-
39
Chapter 4: Noblesse Oblige? Determinants of Survival in a Life and Death Situation 39
death events. This paper tries to address this shortcoming by exploring these
questions using data from the sinking of the Titanic. This data set allows us to
explore not only the behavioural consequences of an extraordinary event, but also
provides evidence of an individual‘s reaction in a situation where there exists an
excess of demand due to the shortage of lifeboats. Moreover, the analysed event can
be considered a quasi-natural experiment. The environmental or situational
conditions were identical for every person on board the Titanic. The event can be
seen as an external shock that affected everyone on board in the same manner. In
addition, we can largely exclude that potential helping behaviour could have been
driven by future reciprocity. Such a life-and death-situation can be seen as a ―one-
shot game‖.
The results offer strong support for the assumption that social norms and altruism
matter. The adherence to the norm ―women and children first‖ is apparent in such a
life and death situation. Being female rather than male increases the probability of
survival between 23.7% and 53.9%, depending on the specification used. This is a
large quantitative effect. Interestingly, females had a lower probability to survive
among crew-members than among passengers. However, the effect is still quite
substantial (23.7%). Moreover, the survival rate of females increases when focusing
only on couples. Similarly, being a child rather than a person of AGE 51+ (reference
group) increases the probability of survival by about 30%. Having a child and being
of reproductive age strongly raises the survival probability. Having a child also
increases the probability of survival when males are considered also. Such results are
in line with socio-biological theories (e.g. procreation instincts or parental
investment) that were discussed in the theoretical part. The findings are also
consistent with previous results that report that males are more willing to help in
critical situations (e.g. chivalrous and heroic behaviour).
Social class has a strong effect. Passengers of the first and second class had a higher
probability of survival. Preferential treatment, a higher level of (bargaining) power,
better access to information about imminent danger, persons of power and decision
makers such as leading crew members, tend to raise the probability of survival as
they allow for better access to lifeboats. Moreover, these passengers were closer to
40
40 Chapter 4: Noblesse Oblige? Determinants of Survival in a Life and Death Situation
the boat deck10
. Similarly, it seems that crew-members used their information
advantage and their superior access to resources (e.g. lifeboats) to generate a higher
probability of survival.
In sum, the intention of the paper was to investigate the decisions made under these
extreme conditions and to see if the survival outcomes correspond with the literature
on interdependent preferences and social norms. Helping behaviour is common and
altruism or social and moral norms seem to play a central role in such a risky and
extreme situation. For example, social norms such as ―women and children first‖ are
maintained during such external shocks that create life and death situations. Such an
effect is only observable when both, crew and passengers agree to defer to such
norms. Otherwise, it would have been easy for male passengers to revolt against such
a norm. Actions are guided by norms and rationality in the sense that society profits
when a large number of females and offspring survive. The social norms are strong
enough to keep the ―public good‖ problems under control, limiting individual self-
interested behaviour although people also take advantage of their relative situation as
can be seen by the higher survival rate of crew and first and second class passengers.
Our findings clearly show the importance of working with Richard Thaler‘s notion of
a Homo Sapiens able to understand an individual‘s behaviour in a life-and-death
situation.
10
Unfortunately, there are only very sketchy data on where the cabins of passengers were located on
the Titanic. We could only collect information on the distance to the lifeboats in meters for 325
persons of which 64 percent survived. As the overall survival rate is 32 percent, this sample is likely to
be highly skewed; that is, the information on the distance to the lifeboats comes predominantly from
passengers saved. Nevertheless, using this questionable and small sample, the estimates of the
determinants discussed are robust: the effects of gender, cabin class, and reproductive age remain
statistically significant and of similar magnitude.
41
Chapter 4: Noblesse Oblige? Determinants of Survival in a Life and Death Situation 41
4.5 TABLE
Table: 4.3 Mean Values
Variables Mean
SURVIVED 0.319
FEMALE 0.220
AGE SUB 15 0.052
AGE 16 - 50 0.891
CREW 0.405
1st CLASS 0.146
2nd
CLASS 0.129
HAS CHILDREN 0.031
SMALL GROUPS (Couples) 0.171
LARGE GROUPS (Families) 0.167
ENGLAND 0.529
IRELAND 0.052
SWEDEN 0.048
USA 0.191
ALL OTHER NATIONALITIES 0.180
FEMALE AGE 16-35 0.121
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 43
Chapter 5: Surviving the Titanic: Economic,
Natural and Social Determinants
Statement of Contribution of Co-Authors for
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interpretation, of at least that part of the publication in their field of expertise;
2. they take public responsibility for their part of the publication, except for the responsible author
who accepts overall responsibility for the publication;
3. there are no other authors of the publication according to these criteria;
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5. they agree to the use of the publication in the student‘s thesis and its publication on the
Australasian Digital Thesis database consistent with any limitations set by publisher requirements.
In the case of this chapter:
Surviving the Titanic Disaster: Economic, Natural and Social Determinants.
January 2009 - Working Paper: Submitted for Publication.
Contributor Statement of contribution*
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44
44 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
5.1 INTRODUCTION
During the night of April 14, 1912, the Titanic collided with an iceberg on her
maiden voyage. Two hours and forty minutes later she sank, resulting in the loss of
1,517 lives—more than two-thirds of her 2,207 passengers and crew.11
This remains
one of the deadliest peacetime maritime disasters in history and by far the most
famous.12
It is one of those rare events that are imprinted on human memory, like
President Kennedy‘s assassination, the first moon landing, and the terrorist attacks on
the Twin Towers on 9/11. The disaster came as a great shock to many because the
vessel was equipped with the most advanced technology at that time, had an
experienced crew, and was thought to be (practically) ―unsinkable.‖13
The myths surrounding the Titanic disaster were kept alive by the many attempts to
find her wreckage. It was not until 1985 that a joint American-French expedition, led
by Jean-Louis Michel and Dr. Robert Ballard, located the wreckage and collected
approximately 6,000 artefacts, which were later shown in a successful exhibition that
toured the world.
The Titanic‘s fame was enhanced by the considerable number of films made about it,
especially the 1997 production of Titanic, which was directed by James Cameron and
11
For accounts of the disaster, see, for example, Eaton & Haas (1994); Lord (1955, 1988); Quinn
(1999); Ruffman (1999) as well as the Encyclopaedia Titanica (www.encyclopedia–titanica.org) and
the information provided by RMS Titanic, Inc. that were granted ―salver-in-possession‖ rights to the
wreck by the U.S. District Court for the Eastern District of Virginia (www.titanic-online.com). 12
The Titanic‘s death toll was exceeded by the explosion and sinking of the steamboat Sultana on the
Mississippi River in 1985 when 1,700 people perished. The worst peacetime maritime disaster
happened in 1987 when the passenger ferry Doña Paz collided with an oil tanker and caught fire. The
sinking of the ferry claimed between 1,500 and 4,000 lives. However, the worst maritime disasters
happened during wartime. For instance, the sinking of the Wilhelm Gustloff by Soviet submarines in
January 1945 caused the deaths of between 7,000 and 9,000 people. The Titanic is not the only major
vessel that did not survive her maiden voyage. The British RMS Tayleur in 1854 and the Danish Hans Hedthoft in 1995 were also technically innovative vessels that sank on their first trip. The famous
Gustav Vasa met with the same fate in 1628; it capsized while still in port at Stockholm. 13
In contrast to popular mythology, the Titanic was never described as ―unsinkable‖ without
qualification. The notion entered the public‘s consciousness only after the sinking see Howell (1999)
or in general, Tierney (2006).
45
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 45
starred Leonardo Di Caprio and Kate Winslet.14
It was (at the time) the most
expensive film ever made, costing approximately US$200 million, and was funded
by Paramount Pictures and 20th Century Fox. The film was a major commercial and
critical success. It is the highest grossing film of all time, earning US$1.8 billion, and
it won eleven Academy Awards, tying with Ben Hur and The Lord of the Rings: The
Return of the King for the most Oscars won by a movie.
The extent of the tragedy is mainly because there were too few lifeboats on the
Titanic. The vessel carried only 20 lifeboats, which could accommodate 1,178
people, or 52 percent of the people aboard.15
As the Titanic did not show any signs of
being in imminent danger, passengers were reluctant to leave the apparent security of
the vessel to board small lifeboats. The panicking deck crew exacerbated the
situation further at the beginning by launching lifeboats that were partially empty. As
a consequence, there was an even greater demand for lifeboat places when the
remaining passengers finally realized that the ship was indeed sinking. People
struggling to survive had to compete with other people aboard for a place in the few
remaining lifeboats. Failure to secure a seat virtually guaranteed death because the
average ocean temperature was about 2 degrees Celsius (35 degrees Fahrenheit); any
survivors of the sinking vessel left in the water would have quickly frozen to death.
Only a handful of swimmers were rescued from the water.16
This paper analyses the determinants of who is more likely to survive such a tragic
event. This is an interesting issue in itself as the probability of survival differs greatly
between individuals. For example, according to the official casualty figures, men
travelling first class were much more likely to survive than men in second and third
class, and nearly all women travelling in first class survived compared to women
14
For example, Saved from the Titanic (1912), In Nacht und Eis (1912), Atlantic (1929), Titanic (1943 and 1953), A Night to Remember (1958), Raise the Titanic! (1980). In addition, there were
several TV movies and series. 15
There were more lifeboats than required by the rules of the British Board of Trade, which were
drafted in 1894 and which determined the number of lifeboats required by a ship‘s gross register
tonnage, rather than the number of persons aboard. 16
Anecdotal evidence taken from (Subcommittee of the Committee on Commerce, 1912).
46
46 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
travelling in the other two classes.17
Yet, the Titanic disaster is also relevant in a
more general context. It allows us to analyse behaviour under extraordinary
conditions, namely in a life and death situation. Do human beings behave more in
line with the selfish homo economicus, where everybody is out for himself or herself
and possibly even puts other people‘s lives in danger? If that were the case, we would
expect that physically stronger people, that is, adult males, would have a higher
probability of survival than women, children, and older people. Otherwise, when it
comes to a life or death decision, are human beings capable of unselfishness and
perhaps even chivalrous behaviour? The answer to this question is open.18
Some economists argue that the tendency to act selfishly arises when the stakes are
high; in particular, when survival is at stake. Other economists are less certain.19
In
contrast, socio-biologists argue that under such circumstances genetic influences
become more powerful, resulting in more women of childbearing age being saved
than those not of childbearing age or men. The study of the sinking of the Titanic
may also have major policy consequences beyond what was implemented shortly
after the disaster.20
Thus, provided unselfish behaviour can be identified, the question
then becomes—Do more stringent safety regulations crowd out intrinsically moral
behaviour, and could they possibly lead to worse outcomes than less strict
regulations? The data available to us can be considered to be the outcome of a quasi-
natural experiment; the disaster occurred due to an exogenous event, and the
resulting life and death situation affected all persons aboard equally. The tragic event
17
Titanic Disaster: Official Casualty Figures and Commentary (http://www.anesi.com/
titanic.htm). 18
Helping behaviour has been shown to exist under particular circumstances; see, for example, Amato
(1990); Batson et al. (1979); Harrell (1994); Worman (1979), and for a survey Eagly & Crowley
(1986). 19
This issue has been debated and experimentally analysed in the context of high-stakes games. See,
for example, Camerer (2003); Camerer & Fehr (2006); Fehr et al. (2002). For life or death decisions,
see more generally Howard (1966, 1980); Shepard & Zeckhauser (1984); Slonim & Roth (1998);
Smith & Keeney (2005). 20
The sinking of the Titanic led to the first International Convention for the Safety of Life at Sea in
London on November 12, 1913, resulting in a treaty that was to go into effect on July 1, 1915, but
which was delayed by World War I. It established the International Ice Patrol to monitor and report on
the location of North Atlantic icebergs that could pose a threat to shipping. In addition, it was agreed
that all passenger vessels must have sufficient lifeboats for everyone aboard, safety drills must be
instituted, and radio communication must be operated 24 hours a day.
47
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 47
occurred in a closed environment, undisturbed by the outside intervention of other
agents.
We proceed by first developing the theoretically grounded hypotheses of what
determined the survival probability of the people aboard the Titanic. Section II
discusses the data we use, and Section III presents the econometric estimates,
including various robustness tests. The first set of hypotheses relate to economic
determinants. Our estimates suggest that the first-class passengers‘ income and
wealth greatly helped in saving their lives as compared to the second-class
passengers, and even more so the third-class passengers. The crew had access to
more informational and relational resources and therefore had a higher survival
chance than the passengers, in particular, the deck crew. The second set of
hypotheses deal with natural determinants. We find that people in their prime (ages
15–35) had a higher chance of survival than older people. Women of reproductive
age and women with children also had a higher probability of being rescued, which
speaks for the socio-biological approach. The third set of hypotheses refers to various
social determinants of survival. It seems that (at least to some extent) the social norm
that ―women and children first‖ was followed in this situation, overcoming
completely selfish behaviour. The British passengers did not, or could not, take
advantage of being on a British ship; indeed, passengers from the USA had a higher
survival probability than citizens of other nations. Section IV concludes by drawing
general consequences for the behaviour of human beings in life or death situations.
5.2 THEORETICAL HYPOTHESES ABOUT WHO IS EXPECTED TO BE
SAVED
Economists have mainly studied the consequences of disasters by analysing the
effects for the short, medium, and long term, following the path-breaking
contributions by Hirshleifer (1963) or Dacy and Kunreuther (1969).21
Psychologists
and sociologists, on the other hand, focus more on the behaviour of people during
48
48 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
disasters. Much of the latter literature rejects the idea that during a disastrous event
many people are stunned, become immobilized, and are unable to act rationally (the
so-called ―disaster syndrome‖). This literature also rejects the concept that in the
event of a disaster chaos, panic, social breakdown and antisocial behaviour, such as
crime, looting, or exploitation, often occur. Indeed, it has been found that morals,
loyalty, respect for law and customs, and tenets of acceptable behaviour do not
instantly break down with a disaster.22
This is consistent with the empirical evidence
accumulated in behavioural economics (or economic psychology), which shows that
people do not necessarily exploit an opportunity presented to them when it can hurt
other people. Rather, they are often inclined to help other people. Substantial
evidence has been generated that motives such as altruism, fairness, or morality
affect the behaviour of many individuals. People sometimes punish others who have
harmed them or reward those who have helped them, sacrificing their own wealth
(Camerer et al., 2004). People donate blood or organs without being paid and give
money for charitable purposes. In wartime, many individuals volunteer and are
willing to take high risks as soldiers (Elster, 2007). Citizens‘ vote in elections,
incurring more private costs than benefits and people are paying more taxes than a
traditional economics-of-crime model would predict (Torgler, 2007). Individuals also
help others in many situations on the job (Drago & Garvey, 1998).23
For our purpose, we develop a simple theoretical framework that allows us to
develop nine hypotheses (arranged according to whether they belong to what can be
called ―economic,‖ ―natural,‖ or ―social‖ factors) that can be tested using the data on
who survived and who perished in the Titanic disaster. The factual knowledge about
the conditions aboard the Titanic has been gathered from various sources, most
21
Other contributions are, for instance, Albala-Bertrand (1993); De Alessi (1975); Grossi & Kureuther
(2005); Kunreuther & Pauly (2005); Sorkin (1982). Particular attention has been paid to insurance
against natural disasters, for example, Kunreuther (1996); Kunreuther & Roth (1998). 22
See, for example, Aguirre, Wenger, & Vigo (1998); Drabek (1986); Hancock & Szalma (2008);
Johnson (1988); Johnson, Feinberg, & Johnston (1994); Quarantelli (1960); Quarantelli (1972);
Tierney, Lindell, & Perry (2001). 23
See, for example, Meier (2006, 2007) for an extensive survey; Camerer (2003); Camerer & Thaler,
(1995); Frey & Meier (2004); Ledyard (1995) specifically for voluntary contributions to public goods;
and Andreoni & Miller (2002); Eckel & Grossman (1996); Henrich et al. (2001) for dictator and
ultimatum games. Surveys on the related topic of fairness are provided, for example, by Camerer
(2003); Fehr & Schmidt (1999); Konow (2003).
49
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 49
importantly from the Encyclopedia Titanica and various official accounts as well as
monographs.24
The hypotheses should be understood in the ceteris paribus sense.
They are not mutually exclusive, but can occur simultaneously. The theoretical
framework is influenced by tournament theory (see Kräkel, 2008; Lazear & Rosen,
1981; Nalebuff & Stiglitz, 1983) and biological theories on efforts to understand
fitness in a cooperative animal society, such as the wasp (see Cant & Field, 2001).
Surviving the Titanic disaster can be modelled as a tournament with two risk averse
contestants i and j. Survival (s) can be described as a production function is = ii ae
and jjj aes 25 where e is the effort expended to save oneself, and a is the ability
to do so. 1
, jis indicates that individual i or j survives and 0
, jis that the individual does
not survive. The ability difference ∆a between individual j and i is: ∆a = ij aa . We
assume that ∆a 0 . Exerting effort imposes costs on an individual, described by the
function c( ie ) and c( je ) with c(0) = 0, c ( jie ,) > 0 and c ( jie ,
) > 0. The utility
functions can be written as:
)()()1()()( 01
iiiiiii ecsupsupeUii
(5)
)()()()()1()( 01
jjijjijj ecsupsupeUj
(6)
with aeeFssprobp jijii ()( ). In other words, the probability is a
cumulative distribution based on individual effort and ability difference (Kräkel,
2008). We normalize the utility of those persons not surviving to )( 0
isui = 0 and
)( 0
jj su =0. Thus, we can reformulate equations (5) and (6) as:
24
Official British and American inquiries by The Wreck Commissioner‘s Court (Wreck
Commissioner's Court, 1912) and The Committee on Commerce (Subcommittee of the Committee on
Commerce, 1912). 25
The production function is also affected by noise or random shocks, but we assume that both
subjects are affected identically.
50
50 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
)()()( 1
iiiii ecsupeUi
(7)
)()()1()( 1
jjijj ecsupeUj
(8)
Agents choose their efforts in order to maximize equations (7) and (8). The first-
order condition can be written as:
0)()( *1**
iiji ecuaeef (9)
0)()( *1**
jjji ecuaeef (10)
Equations (9) and (10) indicate that the flatter the density f(.), or in other words the
higher the survival rate and the steeper the cost function, the lower the equilibrium
effort of an agent will be. Moreover, the stronger the ability disadvantage, a , the
higher the survival rate. On the other hand, the more i tries to generate a relative
effort advantage, (**
ji ee ), the lower the survival rate. Furthermore, an individual‘s
incentive to survive increases with an increase in the value of surviving because
0/ 1
,
1
, jiji su . In addition, an individual requires less effort to survive if his
marginal costs are lower. These findings allow us to develop several testable
hypotheses with regard to economic and natural determinants.
5.2.1 ECONOMIC DETERMINANTS
The 1,316 passengers on the Titanic were divided into three different classes: 325 in
first class, 285 in second class, and 706 in third class. It is to be expected that the
first-class passengers tried to obtain the same preferential treatment with respect to
lifeboat access that they generally received on the vessel. People with more income
and wealth, such as first-class passengers, are more able to secure a place on a
lifeboat than people of lesser economic means. Thus, they have a relative ability
advantage compared to the second- and third-class passengers. They were used to
giving orders to employees (in this case the crew), and they were better able to
51
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 51
bargain, in the extreme case even offering financial rewards. They were also in closer
contact with the upper echelon crewmembers (in particular, First Officer Murdoch,
who commanded the loading of lifeboats on the starboard side, and Second Officer
Lightoller, who did the same on the port side). Moreover, the first-class passengers
had better access to information about the imminent danger and were aware that the
lifeboats were located close to the first-class cabins. Thus, their marginal effort costs
to survive were lower. In contrast, most third-class passengers had no idea where the
lifeboats were located (safety drills for all passengers were introduced after the
Titanic disaster), and they did not know how to reach the upper decks where the
lifeboats were stowed. A relative advantage in the ability, the effort, and the marginal
costs raises the probability of survival, leading to the following hypotheses:
Hypothesis E1: First-class passengers have a higher probability of survival than
second-class passengers; second-class passengers, in turn, have a higher probability
of survival than third-class passengers.
One would expect the experienced crew of 886 men and women to be better prepared
for a catastrophic event, to be earlier and better informed about the location of
lifeboats and the danger of sinking, and to have closer personal contacts with the
crewmembers in charge of loading the lifeboats. This gives them a relative advantage
over passengers regarding saving their own lives (relative ability and effort/cost
advantage). On the other hand, it is their duty to help save passengers, and they are
only supposed to abandon a sinking ship when that task has been fulfilled. We expect
that in life or death situations, such as that encountered on the Titanic, selfish
interests tend to dominate.
Hypothesis E2: Crewmembers have a higher probability of survival than passengers.
Not all crewmembers benefited from the same favourable conditions. Some of the
conditions just mentioned are more likely to apply to the deck crew (who was, for
instance, in charge of manning the lifeboats) or the engine crew (who had
information about the damage done to the ship). The crew directly responsible for
52
52 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
passenger amenities (victualling and a la carte crew) did not have the same
information as the deck and engine crews. Therefore, the deck and engine
crewmembers could use their comparative advantage to increase their chances of
survival. We may also observe a ―closeness effect.‖ The officers directing the loading
of the lifeboats and deciding which crew went with which boat were members of the
deck crew. They would have been somewhat biased towards those of their own work
group.
Hypothesis E3: The deck and engine crewmembers have a higher chance of survival
than other crewmembers.
5.2.2 NATURAL DETERMINANTS
Based on the theoretical framework, we are also able to cover natural (biological)
determinants. In the situation of a large excess demand for places in the lifeboats, a
selfish homo economicus, faced with life or death, would fight to be able to board a
lifeboat. People with greater physical strength, that is, people in their prime, would
have an advantage over older people in the fight for survival. Physical strength is
correlated with higher ability and lower marginal effort costs in the event of such a
disaster. Thus, we can develop the following hypothesis:
Hypothesis N1: People in their prime have a higher chance of survival than older
people.
As a next step, let us assume that some people onboard the Titanic make the effort to
help others survive. For example, let us assume that j is willing to help i and that the
utility function depends on the level of relatedness (r) between individuals, where
0/ ,, jiji ru . Moreover, we assume that j is prepared to make additional efforts to
help i (e.g., due to moral costs). We define individual i‘s fitness to survive without
help as 0
iF and individual j‘s fitness to survive without helping as 0
jF . This model
of helping behaviour is similar to biological studies conducted on helping effort and
fitness in cooperative animal societies (see (Cant & Field, 2001) assuming that
53
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 53
individuals have interdependent preferences (see, e.g., Becker (1974); Sobel (2005)).
The fitness level of j due to helping h can be written as:
hjF 0
jF (1 – h) (11)
where h is the level of h and the cost of helping (cost per unit of help extended).
Thus, hjF is a decreasing function of h. The maximum possible level of help would
be 1/ , where hjF 0.
Individual j‘s investment in h increases the survival probability of individual i.
Helping investment, I(h), is subject to diminishing benefits in terms of efficiency so
that I(h) is a positive but decelerating function of h. The level of investment is taken
to be driven by society‘s helping norms, n (e.g., ―women and children first‖). Thus,
the helping investment, I(h), can be written as:
I(h) = n(1 - qhe ) (12)
where q determines how rapidly the marginal investment of help diminishes. This
allows us to define new utility functions for i and j:
Uhj =
hjF + r I(h) (13)
U hi = 0
iF + I(h) + r hjF (14)
The utility function of individual i(j) is positively correlated with a higher survival
rate of j(i), which means that preferences are interdependent. Substituting equations
(11) and (12) with (13) and (14) leads to:
Uhj =
0
jF (1 – h) + r n(1 - qhe ) (15)
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54 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
U hi = 0
iF + n(1 - qhe ) + r 0
jF (1 – h) (16)
The optimal level of help is generated by maximizing equations (15) and (16) with
respect to h. This leads to:
0
* ln1
jj F
nqrq
h (17)
0
* ln1
ji rF
nqq
h (18)
Equation (17) measures the optimal level of help from the perspective of the helper,
j, and equation (18) from the perspective of the person being helped, i. They can be
seen as an upper and lower limit. We observe that individual j‘s optimal level of help
increases with an increase in society‘s norm of helping (n) and the level of
relatedness (r).
An alternative determinant of survival is based on socio-biology. It stresses the
relevance of the ―procreation instinct.‖ As the survival of a species depends on its
offspring, a high value must be placed upon females of reproductive age as a valuable
resource. Social norms may be created to protect the reproductive and child-rearing
role of women (higher n). It is an attempt to protect children rather than the result of
a greater value put on women‘s lives. A potential shortage of women would limit the
number of offspring, while a shortage of men would not (Felson, 2000). In humans,
the period of peak reproduction is between the ages of 16 and 35 (American Society
for Reproductive Medicine, 2003). Females (on average) are not reproductively
functional before age 15, and the reproductive cycle begins to slow down from age
35 to age 50 when the reproductive function is usually lost altogether. It has also
been emphasized that the social norm of helping women may be related to the
relative physical and structural vulnerability of women (Felson, 2000).
Females may also have a strong incentive to ensure the survival of their children in
the event of a disaster like the Titanic (strong r relationship between child and
55
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 55
mother). In anthropology, ―parental investment‖ is an important concept. It argues
that the females of most species invest more in ensuring the survival of their
offspring than the males. The females of the species are the ones who are responsible
for their young during gestation and lactation, and they generally protect them from
predators and educate them (Geary, 1998). The male contribution is usually much
smaller. Because of the much larger investment on the part of the females, the
opportunity cost of losing offspring is higher and the drive to ensure offspring
survival is stronger (Campbell, 1999). It has been shown that the mortality rates of
children with a mother are 1.4 times lower than those without a mother (Voland,
1998) and that the survival rates of offspring can be directly linked to maternal
survival (Bjorklund & Shackelford, 1999). Under these conditions, it is to be
expected that females with children would be much more alert to possible danger and
would aggressively fight other females to ensure a safe haven (Cashdan, 1997).
Moreover, it has been emphasized that it is the parent who has the greater investment
in promoting the survival of offspring who is the more valued resource (Eswaran &
Kotwal, 2004; Trivers, 1972). These socio-biological considerations lead to the
following two hypotheses:
Hypothesis N2: Women of reproductive age have a higher probability of survival due
to being subject to a social norm of helping.
Hypothesis N3: Women with children have a higher probability of survival than
women without children.
5.2.3 SOCIAL DETERMINANTS
A key norm under life and death conditions is that women and children are to be
saved first (higher n). This norm may work directly in the sense that men let women
and children board the lifeboats first. The norm may also have been supported
institutionally, thus it could have worked indirectly if the officers in charge of
loading the lifeboats directed the male passengers to let women and children proceed
first. Interestingly, there is no international maritime law that requires that women
and children be rescued first. Similar norms can be found in other areas where people
56
56 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
need to be evacuated. Humanitarian agencies often evacuate ―vulnerable‖ and
―innocent‖ civilians, such as women, children, and elderly people first. The Geneva
Convention provides special protection and evacuation priority for pregnant women
and mothers of young children (Carpenter, 2003). The following hypothesis tests
whether this social norm was acted upon when the Titanic sank.
Hypothesis S1: Women and children have a higher probability of survival than men.
Passengers travelling alone may be expected to have a lower chance of survival in
life and death situations because they are less likely to receive information indirectly
and to obtain psychological and physical support from others (lower r). On the other
hand, being alone makes decision making less cumbersome and conflictive (lower
transaction costs), increasing the survival chance of all (lower ). Following the
(crude) homo economicus concept centred on individualistic considerations, the
advantage of being able to act alone and to only have to consider one‘s own best
interests seems to prevail. Moreover, a higher r increases j‘s willingness to help i
(e.g., one‘s partner), but also reduces a partner‘s incentive to request help.
Hypothesis S2: Passengers travelling alone have a higher probability of survival
than those travelling in a group (n 2).
The Titanic was built in Great Britain, operated by British subjects, and manned by a
British crew.26
It is to be expected that national ties were activated during the disaster
and that the crew would give preference to British subjects, easily identified by their
language (higher r). In contrast, passengers from other nationalities, in particular
Americans, Irish, and Scandinavians would be at a disadvantage.
Hypothesis S3: British subjects have a higher chance of survival than people of other
nationalities.
26
Interestingly enough, the Ocean Steam Navigation Company, popularly known as the ―White Star‖
line because of the white star appearing on the company flag, was under the management of the
industrial giant, J.P. Morgan. Nevertheless, the public perceived the Titanic as being a British ship.
57
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 57
5.3 THE DATA
The sinking of the RMS Titanic was a tragic event and resulted in a sorrowful loss of
life. However, the event offers economic researchers an exceptional opportunity to
control exogenous factors within a quasi-natural field experiment. The event itself is
completely isolated, making the external shock applicable to every person aboard the
ship and the exogenous factors the same for everyone. The event is such that every
person is impacted by the shock and is unable to defer making a decision. Even if one
chooses not to participate in the scramble for lifeboat seats, the outcome is the same
as that of someone who does strive for a seat and fails. The great advantage of a
natural field experiment is the randomization and realism. The participants do not
know that their fate can be looked at as being the result of an (natural) experiment;
their behaviour is therefore unaffected (Reiley & List, 2007).
We have been able to construct a detailed dataset, despite the facts that the event
occurred almost 100 years ago and the records were not very detailed. Our data
consist of 2,207 persons who were confirmed to be aboard the R.M.S. Titanic. The
data were gathered from the Encyclopaedia Titanica and crosschecked with other
sources.27
Summary statistics of the variables collected are reported in the Appendix
(see Table 5.4). The dependent variable is whether someone survived or not. Out of
2,207 passengers and crewmembers, 1,517 people died. Based on the records, we
were able to gather information about the gender, age, nationality, port where people
boarded the Titanic, ticket price and therefore the passenger-class status (first,
second, or third class). In addition, we were able to generate individual information
related to travel plans and companions. Limited information was available with
regard to the cabin allocation (only 15.2 percent).28
Of the 2,207 persons onboard, the
27
The cross-checked resources include: Beavis (2002); Bryceson (1997); Eaton & Haas (1994); Geller
(1998); Howell (1999); Lord (1955, 1988); Nova Scotia Archives and Records Management (2008);
Quinn (1999); Ruffman (1999); Subcommittee of the Committee on Commerce (1912); U.S. National
Archives (2009); Wreck Commissioner's Court (1912). 28
The data also indicate that this information has been mainly provided by the survivors and is
therefore biased. Moreover, as the iceberg was struck shortly before midnight, some passengers were
not yet in their cabins, but somewhere else on the ship.
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58 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
age of all but 21 individuals is known. Thus, using age in the regression reduces the
number of observations to 2,186 persons.29
Out of the 2,186 people onboard, 1,300
were passengers and 886 crewmembers. Among the passengers, 43 were servants.
Additionally, of the 2,186 aboard, 1,704 were male (78 percent), and 460 of the 1,300
passengers were female (35 percent).
We have complete information on each person‘s country of residence (nationality).
From this, we have been able to generate several variables to investigate the effects
of nationality. We have created dummies for the most populous national groups
aboard the Titanic. These include Great Britain (the largest group), Ireland, Sweden,
the USA, and a group for all other nationalities. Passenger groupings have been
identified by anecdotal evidence taken from family histories and known travel
arrangements, ticket numbers, and cabin allocations.30
Because the impact of age is prominent in this investigation, it is important to use
generally accepted groupings: children, adults, and older people. The United Nations
standard for age, which classifies children as being fifteen years of age or under, is
used. Among the 2,186 people aboard, 124 were children (65 girls and 59 boys).
Adulthood begins post childhood and ends at old age, defined by the British Royal
Commission in 1894 as beginning at age 50.31
In humans, the peak reproductive age,
as defined by the American Society for Reproductive Medicine (2003), is between 15
and 35 years of age. There were 280 women out of the 2,186 people aboard between
16 and 35 years of age. While there is some anecdotal conjecture that there may have
been other people aboard (stowaways), the list of survivors corresponds to the
―official‖ passenger lists, which would indicate that the stowaways did not compete
with other passengers for lifeboat seats.
29
Out of these 21 people, four were crewmembers and 17 passengers. 30
Those passengers for whom there is no clear or known evidence were assumed to be travelling alone
and assigned as single. 31
The British Royal Commission was based upon the payment of benefits from the friendly societies
(see Boyer (1988)) to its members who were too old to work; these benefits began at age 50. The
Commission accepted the reasoning and adopted this for government-aged welfare.
59
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 59
5.4 ECONOMETRIC ESTIMATES AND RESULTS
The nine hypotheses developed are empirically tested using probit estimates. The
tables below show the estimated parameter and the significance level (indicated by z-
values). The respective marginal effects are also indicated. Table 5.1 deals with the
economic and natural determinants and Table 5.2 with the social determinants.
5.4.1 TESTING ECONOMIC DETERMINANTS
Table 5.1 presents the results of the first set of hypotheses, those relating to economic
determinants.
The estimates are consistent with the hypotheses. According to estimation (1),
passengers in first class had a higher chance of survival than those in second class,
and second-class passengers had a higher chance of survival than those in third class.
The marginal effects suggest that a passenger in the highest class was 40 percent
more likely to survive the catastrophe than a passenger in third class. A second-class
passenger had a 16 percent higher chance of survival than somebody travelling in
third class. These are large and robust differences. Adding controls for the gender
composition of the various classes (estimation 2) as well as possible effects of the
crew (estimation 3) has practically no impact on these marginal effects. Thus,
hypothesis E1 cannot be rejected.
Estimation (3) indicates that the crew had an 18 percent higher chance of survival
than the passengers, controlling for passenger class and gender. This result is
consistent with the second economic hypothesis (E2).
Consistent with hypothesis E3, the survival rate is higher among deck and engine
crewmembers than among members of the rest of the crew. In particular, the deck
crew were more likely to save themselves than other crewmembers. According to
estimation (4), the deck crew had a much higher (74 percent) chance of survival,
compared to 39 percent for the engine crew and 32 percent for the victualling crew
(always compared to the remaining crew).
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60 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
Table: 5.1 Economic and Natural Determinants
Probit Passenger Passenger All Crew Adult
Passenger
All
Adult
Female
Passenger
Adult
Female
Passenger
[1] [2] [3] [4] [5] [6] [7]
1st CLASS 0.990*** 1.020*** 1.023*** 1.309*** 2.156*** 2.158***
11.24 10.32 10.33 10.76 8.25 8.07 0.378 0.387 0.387 0.484 0.43 0.417
2nd CLASS 0.408*** 0.368*** 0.368*** 0.318** 1.060*** 1.068***
4.46 3.59 3.58 2.79 5.59 5.57 0.158 0.14 0.136 0.119 0.211 0.204
FEMALE 1.485*** 1.509*** 2.097*** 1.641***
17.7 18.59 6.1 17.69 0.536 0.547 0.694 0.581
FEMALE AGE
16–35
0.528**
0.572**
2.83 3.00 0.15 0.159
AGE 16–35
0.512***
4.66 0.177
CREW 0.496***
6.21 0.176
DECK CREW 2.322***
6.47 0.744
ENGINE CREW 1.211***
3.65 0.385
VICTUALLING
CREW
1.091**
3.32 0.319
HAS CHILD
/CHILDREN
0.937*
2.05 0.158
Obs. 1300 1300 2186 886 1178 401 401
Prob.>chi2 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Pseudo R2 0.076 0.276 0.203 0.12 0.328 0.249 0.26
Notes: Dependent variable: Survival (value=1). The symbols *, **, *** represent statistical significance at the 5,
1, and 0.1% levels, respectively. Adult=Age>15. In the reference group: THIRD CLASS, MALE, PASSENGER
(EQ3), A LA CARTE CREW (EQ4), AGE>36 (EQ5), FEMALE AGE>35 (EQ6 & EQ7), NOT HAVING A
CHILD/CHILDREN (EQ7).
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Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 61
5.4.2 TESTING NATURAL DETERMINANTS
Table 5.1 also shows the results obtained with respect to the natural (socio-
biological) determinants of surviving the catastrophe. Passengers in their prime (16
to 35 years of age) had an 18 percent higher chance of surviving the disaster
(estimation 5) than older people. These results are consistent with hypothesis N1. In
line with the socio-biological hypotheses N2 and N3, females of childbearing age
(16–35) had a 15 percent higher probability of survival than older women (estimation
8). In addition, if these women had a child, their survival probability was further
increased by 16 percent (estimation 7).
5.4.3 TESTING SOCIAL DETERMINANTS
Estimation (8) suggests that being a female or child had a highly significant positive
effect on being saved. The probability of surviving is 53 percent higher for females
than for males and 15 percent higher for children than for adults (i.e., age 16 and
above). The same effect can be observed for the crew where females even had a 64
percent higher chance of being saved (estimation 9). These results are consistent with
hypothesis S1, suggesting that social norms were to some extent observed even under
conditions of extreme duress.
Being aboard the Titanic as a single person did not increase the chance of survival
(see estimation 10). The advantage of lower transaction costs in the decision-making
process when travelling alone may have been overshadowed by psychological or
even physical disadvantages and a lack of information. Thus, we can reject
hypothesis S2.
Similarly, hypothesis S3 is refuted. As can be seen in estimation (11), British subjects
had a 10 percent lower chance of survival than passengers from other countries. This
may be because the norms of being a ―gentleman,‖ even under extreme duress, were
valid at that time in Britain. Estimation (12) shows that passengers from the USA had
a 12 percent higher probability of survival than British subjects.
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62 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
Table: 5.2 Social Determinants of Survival
Probit Passenger Crew Passenger Passenger Passenger All
[8] [9] [10] [11] [12] [13]
FEMALE 1.468*** 1.858*** 1.456*** 1.444*** 1.447*** 1.475***
17.44 5.50 16.77 16.58 16.41 17.38 0.53 0.64 0.526 0.522 0.523 0.536
AGE SUB 15
(CHILDREN)
0.382** 0.807*** 0.808*** 0.821*** 0.754***
2.83 3.93 3.91 3.96 3.78 0.148 0.313 0.313 0.318 0.289
AGE 16–50 0.470** 0.476** 0.479** 0.422**
2.99 3.01 3.03 2.86 0.161 0.162 0.163 0.132
1st CLASS 1.066*** 1.140*** 1.122*** 1.075*** 1.072***
10.62 10.75 10.55 9.00 9.09 0.403 0.429 0.423 0.406 0.404
2nd CLASS 0.387*** 0.407*** 0.500*** 0.471*** 0.451***
3.74 3.90 4.51 4.10 3.97 0.148 0.155 0.191 0.180 0.168
TRAVELLING ALONE -0.057 -0.070 -0.078 -0.071
-0.62 -0.76 -0.84 -0.77 -0.021 -0.026 -0.029 -0.024
ENGLAND (1,143) -0.268*
-2.56 -0.096
IRELAND (114) 0.238 0.180
1.37 1.10 0.091 0.065
SWEDEN (106) 0.090 0.053
0.52 0.31 0.034 0.019
USA (424) 0.309* 0.258*
2.49 2.39 0.116 0.093
ALL OTHER NATIONS
(399)
0.283* 0.237*
2.37 2.19 0.106 0.085
CREW 0.644***
5.47 0.228
Obs. 1300 886 1300 1300 1300 2186
Prob.>chi2 0.000 0.000 0.000 0.000 0.000 0.000
Pseudo R2 0.280 0.041 0.286 0.290 0.291 0.212
Notes: Dependent variable: Survival (value = 1). The symbols *, **, *** represent statistical significance at the 5, 1, and
0.1% levels, respectively. In the reference group: MALE, AGE>15 (EQ8), AGE >50 (EQ10-EQ13), THIRD CLASS,
GROUP (couples with and without children and/or servants, singles with children and/or servants, extended group also
covering friends), NOT FROM ENGLAND, (EQ11), ENGLAND (EQ12 & EQ13), PASSENGER (EQ13).
63
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 63
The last estimation (13) in Table 5.2 includes all the social determinants. It is
presented to indicate that the estimated parameters and marginal effects are quite
robust. They are of similar magnitude, independent of which further determinants are
included in the estimate.
Instead of splitting up the sample of persons aboard the Titanic as in Tables 5.1 and
5.2, Table 5.3 considers the complete sample and then captures the influence of
gender by using interaction effects. As can be seen, the estimates are robust when the
additional determinants relating to the crew, the reproductive age of women, and
children are added. The qualitative results and the statistical significance remain
unchanged when compared to the estimates in Tables 5.1 and 5.2.
The most comprehensive estimate presented in estimation (17) suggests that the
survival probability more than doubles in its magnitude for women travelling in first
class compared to males travelling in third class. Similarly, females travelling in
second class have a 67 percent higher probability of surviving the disaster than our
base group of third-class males. Men travelling in first class had a 30 percent higher
chance of surviving than men travelling in third class, but there is no statistically
significant difference between men travelling in second or third class.
A female member of the crew had a 59 percent higher probability of surviving the
disaster than the male members of the crew and a 77 percent higher probability of
surviving than non-crew male members. Female crewmembers have a 57 percent
higher survival probability than non-crew women. In addition, male crewmembers
had an 18 percent higher chance of survival than male non-crew members. Women of
reproductive age had a higher survival chance than males and females in other age
categories. Female (male) children had a 77 percent (14 percent) higher probability of
surviving than adults. Moreover, female children had a 62 percent higher survival
probability than male children. Finally, those from the USA had a 9 percent higher
chance to save themselves than the British.
64
64 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
Table: 5.3 Robustness Tests Including Interaction Terms
Probit All All All All
(14) (15) (16) (17)
FEMALE 1.054*** 0.942*** 0.710*** 0.532**
9.86 8.21 4.61 3.17 0.395 0.354 0.267 0.199
AGE -0.014*** -0.010*
-4.36 -2.60 -0.005 -0.003
1st CLASS 0.640*** 0.603*** 0.790*** 0.777***
4.96 4.65 5.71 5.59 0.243 0.229 0.301 0.296
2nd CLASS -0.008 -0.047 -0.008 -0.015
-0.05 -0.32 -0.06 -0.10 -0.003 -0.017 -0.003 -0.005
CREW 0.443*** 0.377** 0.451*** 0.492***
3.85 3.22 3.76 4.04 0.159 0.135 0.162 0.178
IRELAND 0.268 0.294 0.223 0.245
1.67 1.84 1.36 1.50 0.100 0.110 0.082 0.091
SWEDEN 0.125 0.129 0.114 0.091
0.74 0.77 0.68 0.54 0.045 0.047 0.041 0.033
USA 0.242* 0.237* 0.259* 0.249*
2.19 2.15 2.32 2.22 0.088 0.087 0.095 0.091
ALL OTHER
NATIONS
0.238* 0.236* 0.184 0.175
2.18 2.17 1.67 1.57 0.087 0.086 0.067 0.064
TRAVELLING
ALONE
-0.120 -0.136 -0.082 -0.032
-1.34 -1.52 -0.89 -0.34 -0.042 -0.047 -0.029 -0.011
HAS CHILD /
CHILDREN
0.379*
2.08 0.143
1st CLASS*
FEMALE
1.118*** 1.225*** 1.337*** 1.402***
4.55 4.92 5.14 5.25 0.424 0.459 0.494 0.513
2nd CLASS*
FEMALE
1.088*** 1.197*** 1.260*** 1.284***
4.95 5.35 5.53 5.56 0.414 0.450 0.470 0.477
CREW* FEMALE 0.906* 0.982** 1.034**
2.53 2.77 2.93 0.349 0.376 0.395
REPRODUCTIVE
AGE* FEMALE
0.334* 0.523**
2.20 3.01 0.124 0.199
CHILDREN*
FEMALE
1.118*
2.48 0.423
Obs. 2186 2186 2186 2186
Prob.>chi2 0.000 0.000 0.000 0.000
Pseudo R2 0.221 0.224 0.234 0.238
Notes: Dependent variable: Survival (value = 1). The symbols *, **, *** represent statistical
significance at the 5, 1, and 0.1% levels, respectively. Reference group: Male, 3rd Class, England, Not
Travelling Alone, Not a Child (EQ17).
65
Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants 65
5.5 CONCLUSIONS
The econometric estimates of the factors determining survival during the sinking of
the Titanic produce a coherent story. However, this story is not necessarily in line
with the simple model of selfish homo economicus. While people in their prime were
more likely to be saved, it was women—rather than men—who had a better chance
of being saved. Children also had a higher chance of surviving. At the time of the
disaster, the unwritten social norm of ―saving women and children first‖ seems to
have been enforced.
There is also support for socio-biological explanations of who was saved and who
perished. Women of reproductive age and women with children had a higher
probability of being saved.
However, we do find evidence suggesting that the effects predicted using the
standard homo economicus model are also important. People in their prime drowned
less often than older people. Passengers with high financial means, travelling in first
class, were better able to save themselves as were passengers in second class
(compared to third class). Crewmembers who had access to better informational and
relational resources managed to survive more often than others aboard. This applies
in particular to the deck crew who were partly in charge of the rescue operations. In
contrast, the British passengers who were the same nationality as most of the
crewmembers did not take advantage of this fact. They had a higher probability of
perishing than other nationalities, thus exhibiting behaviour consistent with the
prevailing concept of being a gentleman.
The sinking of the Titanic represents a rare case of a well-documented and most
dramatic life and death situation. However, even under these extreme situations, the
behaviour of human beings is not random or inexplicable, but can be accounted for
by economic analysis.
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66 Chapter 5: Surviving the Titanic: Economic, Natural and Social Determinants
5.6 TABLE
Table: 5.4 Summary Statistics
Variables Mean Std. Dev. Min Max N
SURVIVED 0.319 0.467 0 1 2207
FEMALE 0.220 0.414 0 1 2207
AGE 30.044 11.610 1 74 2186
AGE< 16 (CHILDREN) 0.052 0.221 0 1 2186
AGE 16-50 0.891 0.312 0 1 2186
FEMALE 16-35 0.121 0.324 0 1 2186
1st CLASS 0.146 0.354 0 1 2207
2nd CLASS 0.129 0.335 0 1 2207
TRAVELING ALONE 0.217 0.412 0 1 2207
ENGLAND 0.529 0.499 0 1 2207
IRELAND 0.052 0.221 0 1 2207
SWEDEN 0.048 0.214 0 1 2207
USA 0.191 0.394 0 1 2207
OTHER NATIONALITIES 0.180 0.385 0 1 2207
CREW 0.405 0.491 0 1 2207
Sources: The Encyclopaedia Titanica (2008) has been used as the primary source, which was crosschecked across
the following resources: Beavis (2002), Bryceson (1997), Subcommittee on Commerce (1912), Eaton and Hass
(1994), Geller (1998), Howell (1999), Lord (1955), Lord (1988), NSARM (2008), Quinn (1999), Ruffman (1999),
U.S. National Archives (2008), Wreck Commissioner‘s Court (1912).
Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism? 67
Chapter 6: Should I stay or should I go
now? and Time and tide:
constrained altruism?
Statement of Contribution of Co-Authors for
Thesis by Published Paper
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1. they meet the criteria for authorship in that they have participated in the conception, execution, or
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3. there are no other authors of the publication according to these criteria;
4. potential conflicts of interest have been disclosed to (a) granting bodies, (b) the editor or publisher
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In the case of this chapter:
Combined Papers: Should I stay or should I go now? and Time and Tide: Constrained
Altruism? Both April, 2009 -Papers completed and submitted for publication.
Contributor Statement of contribution*
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Has equally contributed to all aspects of these papers, including research,
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Date
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68
68 Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism?
6.1 INTRODUCTION
On Friday the 7th
of May 1915 the German u-boat U-20 torpedoed sank the passenger
liner R.M.S Lusitania south of Kinsale, off the Irish coast. In less than 18 minutes32
the liner had slipped beneath the waves taking almost 1200 lives, despite valiant
efforts of crew and fishing boats racing to the rescue. This occurred only three years
after the most famous maritime disaster in history, the sinking of the RMS Titanic
with comparable loss of life. And like the Titanic the sinking of the Lusitania has
been surrounded by myth and mystery, creating an enduring interest that survives to
this day. In the 90 years since the sinking many books, movies and documentaries
have attempted unravel some of the murky innuendo and mystery that surrounds this
vessel.33
Despite such fame and frequent disaster reports in the media, a quantitative
understanding of the survival in life and death situations is still lacking. In this study,
we explore the interaction between natural survival instincts and the materialization
of internalized social norms using data on these two disasters. While it is virtually
impossible for any two natural disasters to be identical there are numerous and
strongly compelling parallels that can be drawn between the Titanic and the
Lusitania. Both of which demonstrate a similar shortage of lifeboats and survival
rates (around 30 percent), a comparable number of crew members in relation to
passengers (around 40 percent) and similarities in passengers‘ socio-demographic
and socio-economic structures (see Table 6.1). As the two maritime disasters
occurred within three years of each other, one can also assume stable historical
norms. In addition, maritime disasters can be seen as quasi-natural experiments.
The disasters occur due to an exogenous event, and the resulting life and death
situation affects all persons aboard equally and nobody is unable to defer making a
decision. Even if one chooses not to participate in the scramble for lifeboat seats, the
outcome is the same as that of someone who does strive for a seat and fails. The great
32
Testimony given by Captain Turner to the British Wreck Commission Inquiry 15th
June, 1915 33
For example Sinking of the Lusitania (2008), Lusitania (2003), Last Voyage of the Lusitania (2005),
The Last Voyage (2006), The Lusitania Murders (2007).
69
Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism? 69
advantage of such natural experiments is the randomization and realism. The people
do not know that their fate can be looked at as being the result of an (natural)
experiment; their behaviour is therefore unaffected. In addition, the real life or death
situation guarantees that the reactions and behaviours of all individuals can be taken
as natural. Additionally it is impossible to replicate or even approximate the levels of
fear or stress under any laboratory conditions (Reiley & List, 2007; Levitt & List,
2008). These are strong advantages compared to a laboratory experimental setting.
An important aspect in both disasters is the shortage of lifeboat spaces creating an
excess of demand for survival. It is a combination of time and the excess of demand
that determined the type of competition observed in each event. The Lusitania sank
in under 18 minutes whereas the Titanic slowly sank over a 2 hour 40 minutes. Thus,
we are able to compare these two maritime disasters, similar to an experimental
design consisting of a control and treatment group. Where the essential differences
between both cases is the level of time restriction.
We believe this is the first time that these arguably very well-known shipping
disasters have been analysed in a comparative manner with advanced statistical
(econometric) techniques using individual data of the passengers and crew. The
analysis provides innovative insights into the behaviour of individuals under extreme
conditions. Economics traditionally assumes that human beings behave in a rational
and selfish way, which is shaped by external conditions (Becker, 1976; Frey, 1999).
Recent research has provided evidence that these assumptions do not always hold
(Kahneman et al., 1982; Thaler & Sunstein, 2008; Fehr & Fischbacher, 2003). Even
though the two vessels and the composition of the passengers were quite similar, the
behaviour of the individuals on board was dramatically different. On the Lusitania,
selfish behaviour prevailed (which corresponds to the classical homo oeconomicus),
while on the Titanic the adherence to social norms and social status (class)
dominated. This difference could be attributed to the fact that the Lusitania sank in
only 18 minutes, creating a situation in which the short-run flight impulse dominates
behaviour; while on the slowly sinking Titanic (2 hours, 40 minutes), there was time
for socially determined behavioural patterns to re-emerge. It also could be argued that
the Lusitania was sunk during a time of war, which may provoke different reactions.
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70 Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism?
Table: 6.1 Lusitania vs. Titanic
Disasters Lusitani
a
Titanic
Variables Mean Mean
SURVIVED 0.326 0.32
FEMALE 0.26 0.22
AGE 31.57 30.04
AGE < 16 0.15 0.051
AGE 16 – 35 0.475 0.663
AGE 36 – 50 0.281 0.217
AGE 50 + 0.094 0.069
1st CLASS 0.149 0.147
2nd
CLASS 0.307 0.129
TRAVEL ALONE 0.386 0.217
CREW 0.355 0.403
HAS CHILDREN 0.21 0.0531
For example, we may observe less risk-averse passengers on the Lusitania. Warning
notices had been printed in the leading newspapers reminding transatlantic
passengers that a state of war was in effect and any vessel travelling under the British
flag was liable to destruction, and passengers sailed at their own risk. On the other
hand, there are several reasonable suppositions supporting the idea that the Lusitania
‗should‘ not have been at risk, primarily because it was capable of speeds fast enough
to outrun enemy torpedoes. The Lusitania held the transatlantic Blue Riband award
for speed, and it was a vessel carrying civilian passenger, not a warship. Finally, it
was carrying a number of neutral American civilians. Maritime law states that in
wartime merchant vessels must be given a warning prior to attack, whereas warships
should not expect any warning. The Lusitania was never given such a warning by the
attacking U-boat (Bailey, 1935).
The likelihood that the passengers of the Lusitania knew about the tragic events of
the sinking of the Titanic should not be excluded. For example, whereas many of the
passengers on the Titanic may have (wrongly) believed that they would ultimately be
rescued (Subcommittee of the Committee on Commerce, 1912), those on the
Lusitania may have learned from the experience of the Titanic. This may have led
those passengers to change their behaviour (increase in self-preserving behaviour).
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Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism? 71
Nevertheless, maritime disasters have similarities to quasi-natural experiments whose
great advantage is randomization and realism (Reiley & List, 2007; Levitt & List,
2008; List, 2008).
Many social scientists assume that in a life-and-death situation self-interested
reactions predominate. Social cohesion is expected to disappear, and the desire to act
in accordance with self interests takes over (Mintz, 1951; Kelley et al., 1965). In
states of extreme privatization (Lang & Lang, 1962), ‗the social contract is thrown
away, and each man single-mindedly attempts to save his own life at whatever cost to
others‘ (Brown, 1965). On the other hand, social norms are followed for intrinsic
reasons; people believe them to be ‗right‘ (Elster, 2006), or they fear social sanctions
when violating them (Polinsky & Shavell, 2000). The emerging disaster literature
suggests that pro-social behaviour predominates in such contexts (Quarantelli, 2001).
Laboratory experiments have shown that strategic incentives are important to
understand whether self-regarding or other-regarding preferences dominate (Camerer
& Fehr, 2006).
Our study proposes that context differences matter. Time appears to be a key
parameter for explaining the adoption of either social or self-interested behaviours.
Our results indicate that adherence to social norms and social power requires time to
manifest (evolve) and cannot compete against individual self-interested flight
behaviour in a shorter window of opportunity where competition for survival of the
fittest prevails. The rapid sinking of the Lusitania very likely created a situation in
which simple physical prowess and maybe also good fortune or randomness played a
larger role, while social norms were much more influential in the case of the Titanic.
To have more time at one‘s disposal, as in the case of the Titanic, may also have
eased the restrictions on bargaining for lifeboats and facilitated information
generating advantages, which may have benefited first- and second-class passengers
when compared to third-class passengers (with the crew favouring the rich and
powerful).
The research on fight or flight behaviour may also provide further insights into how
people reacted in these different conditions. Fight or flight behaviour, as the
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72 Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism?
instinctual reaction to a perceived danger, has been discussed in different disciplines
such as biology, psychology and sociology (Cannon, 1929a, 1929b; Gray, 1988;
Mawson, 2007; Cory, 2000). Biologically, fight or flight behaviour has two distinctly
separate stages (Vingerhoets & Perski, 1999). The short-term response triggers a
surge in adrenaline production via the hypothalamus and can last from a few seconds
to a few minutes. This response is limited to a few minutes because adrenaline
degrades rapidly and leaves the body in a state of exhaustion (Henry & Wang, 1998).
The elevated operational state is maintained for a short period after the threat has
passed, then the response mechanism switches off and the system returns to
homeostasis (Everly, 2002). The duration extends beyond the active flight response
time and includes a cool down period. Only after returning to homeostasis do the
higher-order brain functions of the neo-cortex begin to override instinctual responses,
which may lead to a change towards pro-social individual behaviours.
6.2 DATA AND MODEL
We were able to collect unique data sets containing detailed information about
gender, age, ticket price and thus the passenger-class status for both the Titanic and
the Lusitania with which to test these propositions. The dependent variable in the
multivariate analysis is a 0/1 variable that indicates whether an individual survived
the disaster or did not survive (survived = 1). Table 6.2 shows the estimated
parameters, the significance level (indicated by z-values) and the quantitative
(marginal) effects for the Lusitania (L) and Table 6.3 for the Titanic (T). The Titanic
data consist of 2,207 persons confirmed to be aboard the R.M.S. Titanic. The data
was gathered from the Encyclopaedia Titanica and crosschecked with other sources
(Beavis, 2002; Eaton & Haas, 1994; Geller, 1998; Howell, 1999; Lord, 1955, 1988;
Quinn, 1999; Ruffman, 1999).
The dependent variable is whether someone survived or not. Out of 2,207 passengers
and crewmembers, 1,517 people died. Out of the 2,186 people onboard, 1,300 were
passengers and 886 crewmembers. Among the passengers, 43 were servants, of the
2,186 aboard, 1,704 were male (78 percent), and 460 of the 1,300 passengers were
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Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism? 73
female (35 percent). The Lusitania data consist of 1,949 persons confirmed to be
aboard the R.M.S. Lusitania. The data was gathered from numerous sources and
crosschecked with other sources (Butler, 2000; O‘Sullivan, 2000; Wreck
Commissioner‘s Court, 1915; Preston, 2002). The dependent variable is whether
someone survived or not. Out of 1,949 passengers and crewmembers, 1,313 people
died. Out of the 1,949 people onboard, 1,258 were passengers and 691 crewmembers.
Among the passengers, 19 were servants, of 1,949 aboard, 1,441 were male (73
percent), and 483 of the 1,258 passengers were female (38 percent).
Based on the records, we were able to gather information about the gender, age,
nationality, port where people boarded, ticket price and therefore the passenger-class
status (first, second, or third class). In addition, we were able to generate individual
information related to travel plans and companions. We have complete information
on each person‘s country of residence (nationality). From this, we have been able to
generate several variables to investigate the effects of nationality. We have created
dummies for the most populous national groups aboard both the Titanic and
Lusitania. These include Great Britain (the largest group), Ireland, Sweden, the USA,
and a group for all other nationalities. Passenger groupings have been identified by
anecdotal evidence taken from family histories and known travel arrangements, ticket
numbers, and cabin allocations. Because the impact of age is prominent in this
investigation, it is important to use generally accepted groupings: children, adults,
and older people. The United Nations standard for age (American Society for
Reproductive Medicine, 2003) which classifies children as being fifteen years of age
or under is used. Adulthood begins post childhood and ends at old age, defined by a
British Royal Commission in 1894 as beginning at age 50. In humans, the peak
reproductive age, as defined by the American Society for Reproductive Medicine
(1982), is between 15 and 35 years of age.
We use a probit model of the survival probability for a typical passenger:
Pr(y = 1 | x1, x2, …, xk ) = ( + 1x1 + 2x2 + … + kxk). (19)
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74 Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism?
Here y is a dummy variable indicating whether the passenger survived (y = 1) or not
(y = 0); the variables (x1, x2, …, xk) are explanatory variables such as gender, age,
etc; ( , 1, 2, … k) are parameters to estimate; and is the cumulative standard
normal distribution function. The role of , which is increasing in its argument, is to
keep the probability Pr(y = 1) in the zero to one interval. Each passenger contributes
one observation on (y, x1, x2, …, xk). From a sample of such observations, assumed
independent, the parameters can be estimated by maximum likelihood. This is a
standard probit model (see e.g. Baum, 2003; Wooldridge, 2002, 2003). Since the
coefficients are difficult to interpret directly, the marginal effect of a continuous
explanatory variable xj will, as usual, be interpreted through the partial derivative
Pr(y 1 | x1,x2,...,xk )
x jj ( 1x1 2x2 kxk ) , (20)
evaluated at the means, where is the standard normal density function (not the
cumulative density ). Since > 0, the sign of the marginal effect is the same as the
sign of j. For a discrete xj, a difference rather than a derivative will be used in place
of a partial derivative.
6.3 RESULTS
6.3.1 IS SELF-INTEREST DOMINANT IN THE LUSITANIA CASE?
A self-interested reaction in a situation of life and death is predominantly used as a
theoretical foundation. Unstable rewarding structure (survival) in a competitive
environment (shortage of lifeboats) leads to the disappearance of cohesion and the
desire to act in accordance with own individual needs or in other words to pursuit self
interests (Mintz, 1951; Kelley et al., 1965). In a period of 18 minutes individuals also
have problems organizing themselves. It is difficult to secure a place on a lifeboat
through economic means (bargaining power). The danger is eminent and there is a
low distribution of information asymmetry between the passengers on board. Thus,
class status shouldn‘t matter and physical power should dominate social power. Only
crew members are supposed to be better prepared for such a catastrophic event. The
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Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism? 75
battle for lifeboats can be seen as a survival of the fittest competition. In such a flight
period physical attributes (e.g., strength and speed or agility) are expected to be quite
successful in determining the survival success. Therefore, we should observe people
between the ages 16 and 35 to have higher survival probabilities. Not only prime
males should have a relative advantage but also prime females in their main
reproductive age. Procreation instinct places a high value on its progeny as the
survival of a species relies on females in their reproductive age. A potential shortage
of such women would limit the number of off-spring while a shortage of men would
not (Felson, 2000). A self-interested reaction in the Lusitania may also be driven by
instinctual reaction to a perceived danger that includes self preservation functions
(Cannon, 1929a, 1929b; Gray, 1988). The short term response triggers the adrenal
production via the hypothalamus which promotes flight behaviour that can last from
a few seconds to a few minutes (Everly, 2002).
Table 6.2 shows the estimated parameters, the significance level (italics) and the
quantitative (marginal) effects (bold). EQ1 shows that the reference group (prime age
16-35) has the highest probability of surviving and the oldest age group (age>50) the
lowest one (59% lower than the prime age group). Females have ceteris paribus not a
higher probability of surviving than males. Children have even a 26% lower
probability of surviving than the reference group. Moreover, we don‘t observe that
first and second class passengers have a higher probability of surviving. Passengers
in the first class fared even worse than those in third class. Thus, physical power
indeed dominates social power. In EQ2 we recode the prime age category into males
and females. The results show that both, males and females have a higher probability
of surviving (between 7.8 and 10.5%). Thus, not only physical strength but also
procreation instinct seemed to matter. In EQ3 we extend the regression exploring
whether persons accompanying children have a higher survival chance than persons
without children. This seems not be the case. In EQ4 we control whether individuals
travelling alone have a higher probability of surviving. People travelling alone have
lower transaction costs and are more prone to flight behaviour (Mawson 2005). EQ4
shows a positive relationship without being statistically significant. In EQ5 we
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76 Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism?
Table: 6.2 Determinants of Passengers‘ Survival on Lusitania
Probit
Lusitania
[1] [2] [3] [4] [5]
Female -0.030 -0.31
-0.010
Age<16 -0.261**
-1.97 -0.083
Age 35 - 50 -0.170
-1.57
-0.056
Age 50+ -0.589***
-3.21
-0.167
1st Class -0.339*** -0.360*** -0.358*** -0.350*** -0.334***
-2.85 -3.07 -3.02 -2.96 -2.84 -0.109 -0.116 -0.115 -0.112 -0.112
2nd
Class 0.038 0.005 0.002 0.026 0.038
0.36 0.05 0.02 0.25 0.36 0.013 0.002 0.001 0.009 0.013
Male Age 16-35 0.227** 0.231** 0.218** 0.286***
2.16 2.13 2.00 2.91 0.079 0.080 0.075 0.103
Female Age 16-35 0.297** 0.299** 0.314*** 0.292***
2.55 2.55 2.67 2.56 0.105 0.106 0.111 0.107
Has Children 0.016 0.150 0.159
0.15 1.07 1.13 0.005 0.052 0.057
Single 0.190 0.178
1.56 1.46 0.064 0.062
Crew 0.622***
3.73 0.236
Obs. 933 933 933 933 933 Prob > chi2 0.0000 0.0000 0.0001 0.0001 0.0000
Pseudo R2 0.0276 0.0230 0.0231 0.0253 0.0409 Notes: Dependent variable: Probit Model. Survival (value = 1). The symbols *, **, *** represent statistical
significance at the 10, 5, and 1% levels, respectively. Reference groups: MALE and AGE 16-35 [1]; MALE,
ADULTS, and THIRD CLASS [2]; MALE/FEMALE AGE >35, THIRD CLASS and NOT HAVING
CHILDREN [3]; MALE/FEMALE AGE >35, THIRD CLASS, NOT HAVING CHILDREN and NON-
SINGLE [4]; MALE/FEMALE AGE >35, THIRD CLASS, NOT HAVING CHILDREN, NON-SINGLE
and PASSENGERS [5]. Coefficients are in normal text, z-stat in italics and marginal effects in bold.
extend the regression adding also crew members to see whether they are better
prepared for a catastrophic event. The results indeed indicate that crew members are
able to push through their comparative advantage reporting a 34% higher survival
probability.
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Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism? 77
6.3.2 PRO-SOCIAL BEHAVIOUR AND SOCIAL POWER IN THE TITANIC?
There is a growing viewpoint in the disaster literature that pro-social behaviour,
rather than antisocial behaviour, predominates in such contexts (Quarantelli, 2001).
However, empirical evidence is still scarce how and to what extent social norms
survive in a life threatening situation. Social norms may followed for intrinsic
reasons also in life threatening situations, because people take them to be ―right‖
(Elster, 2006) or because they fear the social sanctions when violating them (Polinsky
& Shavell, 2000). Moreover, once the first stage of flight behaviour has run its course
and exhaustion has set in (Henry & Wang, 1998) we may observe a change in
individual behaviours and actions due to self awareness and the consideration of
complex social interactions (Everly, 2002). The slowly sinking of the Titanic over 2
hours and 40 minutes allows for such a cool down period. Social interactions should
become more important allowing for the creation of and adherence to social norms. It
may enhance norms that promote social responsibility such as ―women and children
first‖. Such a norm has been found in other areas where people were evacuated
(Carpenter 2003). Moreover, more time also means fewer restrictions to bargain for
lifeboats and to generate information advantages. Thus, we would expect a
comparative advantage for first and second class passengers. Social power can be
achieved while physical power gets less important. In other words, individuals in the
prime age may a lower comparative advantage in the Titanic compared to the
Lusitania. This may hold in particular for males as we may still observe the
procreation instinct for females in this age group. Moreover, the survival rates of
offspring may be directly linked to maternal survival (Bjorklund and Shackelford,
1999). Table 6.3 presents the results. EQ6 reports that females have 53% higher
probability of surviving than males.
In addition EQ6 shows that children have a 10.6% higher probability of surviving
than the prime age group. Thus, the norm ―women and children first‖ is very
dominant in the Titanic case. Nevertheless, physical power is still relevant. Older age
groups (age 35 to 50 and age>50) have a lower probability of surviving than the
prime age group (between 14 and 24%). According to EQ7, passengers in first class
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78 Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism?
Table: 6.3 Determinants of Passengers‘ Survival on Titanic
Probit
Lusitania
[6] [7] [8] [9] [10]
Female 1.48*** 17.32 0.533
Age<16 0.279**
2.03 0.107
Age 35 - 50 -0.416*** -3.61 -0.145
Age 50+ -0.793*** -4.66 -0.241
1st Class 1.35*** 0.977*** 0.963*** 0.947*** 0.9998***
11.46 9.94 9.74 9.53 10.21 0.501 0.372 0.367 0.361 0.379
2nd
Class 0.455*** 0.394*** 0.378*** 0.374*** 0.389***
4.33 3.99 3.81 3.77 3.93 0.174 0.151 0.145 0.143 0.145
Male Age 16-35 -0.438*** -0.409*** -0.364*** -0.211***
-4.77 -4.42 -3.89 -3.03 -0.159 -0.149 -0.133 -0.074
Female Age 16-35 1.04*** 1.06*** 1.05*** 1.14***
9.62 9.70 9.55 11.07 0.397 0.402 0.398 0.432
Has Children 0.555*** 0.463*** 0.486***
3.13 2.59 2.72 0.217 0.180 0.185
Single -0.284*** -0.301***
-3.33 -3.55 -0.104 -0.101
Crew 0.178**
2.12 0.063
Obs. 1300 1300 1300 1300 1300 Prob > chi2 0.0000 0.0000 0.0000 0.0000 0.0000
Pseudo R2 0.2967 0.1932 0.1990 0.2055 0.1495 Notes: Dependent variable: Probit Model. Survival (value = 1). The symbols *, **, *** represent statistical
significance at the 10, 5, and 1% levels, respectively. Reference groups: MALE and AGE 16-35 [6]; MALE,
ADULTS, and THIRD CLASS [7]; MALE/FEMALE AGE >35, THIRD CLASS and NOT HAVING
CHILDREN [8]; MALE/FEMALE AGE >35, THIRD CLASS, NOT HAVING CHILDREN and NON-
SINGLE [9]; MALE/FEMALE AGE >35, THIRD CLASS, NOT HAVING CHILDREN, NON-SINGLE
and PASSENGERS [10]. Coefficients in normal text, z-stat in italics and marginal effects in bold.
had a higher chance of survival than those in second class, and second-class
passengers had a higher chance of survival than those in third class. The marginal
effects suggest that a passenger in the highest class was 50 percent more likely to
survive the catastrophe than a passenger in third class. Thus, social power is quite
important. The effect remains robust for all the remaining equations in Table 6.3. In
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Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism? 79
EQ8 we are interested to see gender differences in regards to the prime age group. In
contrast to the Lusitania case, on the Titanic only females in the reproductive age
group 16-35 have a (40%) higher probability of surviving supporting the importance
of the procreation instinct. Conversely the male age group 16-35 has a lower survival
chance (16%) despite their physical strength. Not only children have a higher
probability of surviving but also persons accompanying children have an around 20%
higher probability of surviving that persons without children (see EQ8 to 10). In
addition, contrary to the Lusitania case, being aboard the Titanic as a single person
did not increase the chance of survival (see EQ9). The advantage of lower transaction
costs in the decision-making process when travelling alone may have been
overshadowed by psychological or even physical disadvantages and a lack of
information. Finally, also in the Titanic case we observe that the crew members have
a higher probability of surviving (EQ10).
6.4 CONCLUSIONS
In our paper we show that time appears to be a key parameter linked to the adoption
of individualistic self-centred or social behaviour. When time is scarce individual
self-interested flight behaviour becomes more important resulting in a stronger
survival of the fittest competition. On the other hand, altruism and social norms are
still observed in an extreme life or death situation, given sufficient time to evolve.
These results suggest a stronger competition for survival (of the fittest) in the
Lusitania case. In the environment of the Titanic, social norms were enforced more
often, and there was also a higher willingness among males to surrender a seat on a
lifeboat. Moreover, the results indicate that social power also requires time to evolve
and cannot compete against physical strength in a shorter window of opportunity.
Economic class or social power warranted a relative advantage. First-class
passengers, and to some extent also second-class passengers, tried to secure the same
preferential treatment with respect to lifeboat access that they were used to receiving
on the vessel. However, the generation of such a relative advantage takes time.
Indeed, Tables 6.2 and 6.3 shows a higher survival rate for the Titanic, but not the
Lusitania where first-class passengers fared even worse than those in third class. On
the other hand, the results in regards to the crew member seemed to indicate that
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80 Chapter 6: Should I stay or should I go now? and Time and tide: constrained altruism?
access in advance to more information and relational resources enhanced the survival
rate. This empirical analysis suggests that the adoption of a specific behaviour can
depend on time as a factor, although one should note that time may not be the only
factor at work. Such a natural environment is less controlled than an experimental
setting. However, it seems that on the more slowly sinking Titanic pro-social
behaviour predominated (in a stronger manner), while a more selfish conduct
prevailed on the rapidly sinking Lusitania.
81
Chapter 7: Concluding Remarks
These three essays are the first steps into the analysis of individual behaviour and
choices made under extreme environmental conditions, such as life and death disaster
events, utilising a behavioural economics approach. This chapter provides a summary
or overview of the previous chapters.
The sinking of the Titanic and Lusitania allows the exploration of the behavioural
actions and decisions of individuals in extreme events but also demonstrates the
choices made in an excess of demand situation with the highest possible stakes,
which is the difference between life and death. As discussed in the introduction
sections, there exists little to no experimental or empirical work pertaining to the
decision making process in extreme situations. To the best of my knowledge these
works form the first attempt to analyse this problem using econometric methodology.
There is little empirical evidence available that illuminates whether interdependent
preferences or pro-social behaviours matter in extreme situations, such as helping
behaviour, altruism, social or moral norms.
While the econometric estimates of the factors determining survival during the
sinking of the Titanic produce a coherent story, it is at times contrary to the myth that
surrounds the event. The story is not necessarily in line with a simple model of
selfish homo economicus, such that the results offer strong support for the
assumption that social norms and altruism matter. The adherence to the unwritten
social norm of ―women and children first‖ was enforced in this life and death
situation, where being female or being a child strongly raised the probability of
survival. Additionally, females of reproductive age and having a child also increased
the probability of survival in relation to the males onboard. These results are in line
with the socio-biological theories of procreation instincts or parental investment.
However, there is some evidence that does support the outcomes that would be
predicted by using of a standard homo economicus model of behaviour on the Titanic
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82
event. Individuals utilised whatever advantages they possessed to aid in their
survival, such as social power, physical fitness or informational advantage. People in
their prime drowned less often than older people. Social class has a strong effect,
passengers of the first and second class may have utilised their social power to affect
a higher probability of survival. Similarly, crew-members who had access to better
informational and relational resources (deck and engine crew) may have used their
advantage to generate a higher probability of survival. However, this advantage did
not extend to nationality advantages, the British passengers who were the same
nationality as most of the crewmembers were not able to take advantage of this.
These effects were clearly secondary to the ―women and children first‖ social norm,
they remained thus because of the adherence of the male passengers to follow the
norm. Otherwise, it would have been easy for male passengers to revolt against this
norm and enforce a survival of the fittest competition, which would have ensured a
greater rate of males. This demonstrates that the social norms were strong enough to
keep the ―public good‖ problems under control, limiting individual self-interested
behaviour.
In contrast to these findings the Lusitania, can be viewed as a time treatment for the
Titanic. Assuming stable historical norms and given the closeness in the
demographic makeup of the two vessels, the only significant variation in the events is
the amount of time taken for the Lusitania to sink, 18 minutes versus 2 hours and 40
minutes. The results demonstrate that time is a key factor in the adoption of
individualistic self-centred or social behaviour. In time restricted events or where the
event horizon is extremely shortened, individual self-interested flight behaviour
becomes predominant, resulting in a stronger survival of the fittest competition. This
result is observed in the Lusitania event, where individuals with a greater fitness for
survival have a greater probability to do so. Individuals who are physically stronger
or fitter, such as males at peak age (16-35), had better information about the vessel,
such as crew members, both had higher survival rates in relation to others. Moreover,
the results indicate that social power also requires time to evolve and cannot compete
against physical strength in a shorter window of opportunity. Economic class or
social power warranted a relative advantage but such an advantage takes time to
enforce. On the Titanic, 1st Class passengers demonstrated a much higher survival
83
83
rate than 2nd
Class, which in turn had a better survival rate than 3rd
Class passengers,
but not the Lusitania where first-class passengers fared even worse than those in third
class. This was further reflected in the survival rates of the crew, where access in
advance to more information and relational resources enhanced the survival rate.
Even while following the social convention of ―women and children first‖,
individuals will utilise any remaining advantage that increases survival outcomes.
Altruistic and socially normative behaviour were the predominate behaviour on the
Titanic, but underlying this behaviour was still the self-interested homo economicus.
Such that, even though an individual followed the normative behaviour, they would
use any possible advantage if a chance to save them self became available. These
self-interested advantaged could have included, superior fitness (age), improved
information advantage (knowledge of life saving devices), class or some other type of
advantage. These events demonstrate that behaviour of individuals in disaster events
does not follow the traditional mythology of mass panic. Their behaviour is neither
random nor inexplicable and as such it can be accounted for by using economic
analysis. Additionally, it can be observed that simple models of behaviour do not
fully predict survival outcomes. It could be that a mixed strategy approach may
provide better modelling outcomes.
What does the future hold for this research area? I hope to be able to continue
this work: firstly by finishing the initial maritime theme with a paper using the
Estonia as a historical treatment to examine changes over time. Beyond this, I plan on
extending the research into other areas where individuals are forced to make
decisions under extreme pressures. I have begun this by analysing the decision
process of elite athletes, by empirically investigate the relationship between stress
and performance, in an extreme pressure situation (football penalty kicks) in a winner
take all sporting environment (FIFA World Cup and UEFA European Cup
competitions). Specifically, the penalty shootouts between 1976 and 2008 covering in
total 16 events. The results indicate that extreme stressors can have a positive or
negative impact on individuals‘ performance. On the other hand, more commonly
experienced stressors do not affect professionals‘ performances (Savage & Torgler
84
84
2009). Other research areas include mountaineering in the Himalayan Mountains,
natural disasters (such as forest fires, floods, tornados etc.). It will be these topics that
will form the basis of my PhD research and will most likely remain the focus of
investigations for many years to come.
Bibliography 85
Bibliography
Aguirre, B. E., Wenger, D., & Vigo, G. (1998). A test of the emergent norm theory of
collective behaviour. Sociological Forum, 13, 301-319.
Akerlof, G. A., & Yellen, J. L. (1990). The fair wage-effort hypothesis and
unemployment. Quarterly Journal of Economics, 105, 255-284.
Albala-Bertrand, J. M. (1993). The Political Economy of Large Natural Disasters:
With Special Reference to Developing Countries. Oxford: Clarandon Press.
Allen, R. D., Hitt, A. M., & Greer, C. R. (1982). Occupational stress and perceived
organizational effectiveness in formal groups: An examination of stress level
and stress type. Personal Psychology, 35, 359-370.
Allison, P. D. (1999). Multiple regression: A primer. Thousand Oaks: Pine Forge
Press.
Amato, P. R. (1990). Personality and social network involvement as predictors of
helping behaviour. Social Psychology Quarterly, 53, 31-43.
American Society for Reproductive Medicine. (2003). Reproductive aging in women.
A.S.R.M. Journal, 2008(13th August ). Retrieved from
http://www.asrm.org/Patients/FactSheets/reproaging.pdf
Andreoni, J., & Miller, J. H. (2002). Giving according to GARP: An experimental
test of the consistency of preferences for altruism. Econometrica 70, 737-753.
Archer, W. (1899). Observations and Reflections. New York: Charles Scribner's
Sons.
Arias, E. (2004). United Stated Life Tables. Retrieved 10th August 2008. from
http://www.cdc.gov/nchs/data/nvsr/nvsr52/nvsr52_14.pdf.
Avi-Itzhak, B., & Levy, H. (2004). On measuring fairness in queues. Advances in
Applied Probability, 36, 919-936.
86
86 Bibliography
Avi-Itzhak, B., Levy, H., & Raz, D. (2005). Quantifying Fairness in Queuing
Systems: Principles, Approaches and Applicability. New Jersey: Rutgers
University.
Bailey, T. A. (1935). The sinking of the Lusitania. The American Historical Review,
41, 54-73.
Banerjee, A. V. (1992). A simple model of herd behavior. The Quarterly Journal of
Economics, 107, 797-817.
Batson, D. (1992). Experimental Tests for the Existence of Altruism. Paper presented
at the Proceedings of the Biennial Meeting of the Philosophy of Science
Association.
Batson, D., Pate, S., Lawless, H., Sparkman, P., Lambers, S., Worman, B. (1979).
Helping under conditions of common threat: Increased ―we-feeling‖ or
ensuring reciprocity. Social Psychology Quarterly, 42, 410-414.
Baum, C. F. (2003). An Introduction to Modern Econometrics Using Stata. Texas:
Stata Press.
Bay, M. (Director) Abrams, J. J., & Gilroy, T. (Writer) (1998). Armageddon. In J.
Bruckheimer & G. A. Hurd (Producer). USA: Buena Vista.
Beavis, D. (2002). Who Sailed on the Titanic? The Definitive Passenger Lists (1st
ed.). London: Ian Allen Publishing.
Becker, G. S. (1974). A theory of social interaction. Journal of the Political
Economy, 41, 54-73.
Becker, G. S. (1976). The Economic Approach to Human Behavior. Chicago:
Chicago University Press.
Berberich, C. (2007). The Image of the English Gentleman in Twentieth-Century
Literature: Ashgate.
Berkowitz, L. (1969). Resistance of improper dependency relationships. Journal of
Experimental Social Psychology, 5, 283-294.
87
Bibliography 87
Bjorklund, D., & Shackelford, T. (1999). Differences in parental investment
contribute to important differences between men and women. Current
Directions in Psychological Science, 8, 86-89.
Bolton, G. E., & Ockenfels, A. (2000). ERC: Theory of equity, reciprocity, and
competition. American Economic Review, 90, 166-193.
Bourne, L. E., & Yaroush, R. A. (2003). Stress and Cognition: A Cognitive
Psychological Perspective: National Aeronautics and Space Administration
(N.A.S.A.).
Boyer, G. R. (1988). What did unions do in nineteenth-century Britain? The Journal
of Economic History, 48, 319-332.
Bracha, H. S. (2004). Freeze, flight, fight, fright, faint: Adaptionist perspectives on
the acute stress response spectrum CNS Spectrums, 9, 679-685.
Braithwait, R. (1994). The English Gentleman. Bristol: Thoemmes Press.
Brown, R. W. (1954). Mass Phenomena. In G. Lindzey (Ed.), Handbook of Social
Psychology (1 ed., Vol. 2). Reading: Addison-Wesley.
Brown, R. (1965). Social Psychology. New York: Free Press.
Bryceson, D. (1997). The Titanic Disaster: As reported in the British National Press
April - July 1912. New York: W.W. Norton & Company Inc.
Butler, D. A. (2000). The Lusitania: The Life, Loss and Legacy of an Ocean Legend.
Mechanicsburg: Stackpole Books.
Camerer, C. F. (2003). Behavioural Game Theory: Experiments in Strategic
Interaction. Princeton: Princeton University Press.
Camerer, C. F., & Fehr, E. (2006). When does ―economic man‖ dominate social
behaviour? Science 311, 47-52.
Camerer, C. F., Loewenstein, G., & Rabin, M. (2004). Advances in Behavioral
Economics. Princeton: Princeton University Press.
Camerer, C. F., & Thaler, R. H. (1995). Anomalies: Ultimatums, dictators and
manners. Journal of Economic Perspectives, 9, 209-219.
88
88 Bibliography
Campbell, A. (1999). Staying alive: Evolution, culture and women's intra-sexual
aggression. Behavioural and Brain Sciences, 22, 203-252.
Cannon, W. B. (1929a). Organization for physiological homeostasis. Physiological
Reviews, 9, 399-431.
Cannon, W. B. (1929b). Bodily changes in pain, hunger, fear and rage. New York:
D. Appleton & Co.
Cannon, W. B. (1935). Stresses and strains of homoeostasis. American Journal of
Medical Science, 189.
Cant, M. A., & Field, J. (2001). Helping effort and future fitness in cooperative
animal societies. Proceedings of the Royal Society: Biological Sciences, 268,
1959-1964.
Carpenter, R. C. (2003). "Women and children first": Gender, norms and
humanitarian evacuation in the Balkans 1991-95. International Organization,
57, 661-694.
Cashdan, E. (1997). Women's mating strategies. Evolutionary Anthropology, 5, 134-
143.
Clark, A. E., Frijters, P., & Shields, M. A. (2008). Relative income, happiness, and
utility: An explanation for the Easterlin paradox and other puzzles. Journal of
Economic Literature, 46, 95-144.
Cory, G. A. (2000). From MacLean's triune brain concept to the conflict systems
neurobehavioral model: The subjective bias of moral and spiritual
consciousness. Zygon, 35, 385-413.
Dacy, D., & Kunreuther, H. (1969). The Economics of Natural Disasters:
Implications for Federal Policy. New York: Free Press.
De Alessi, L. (1975). Towards an analysis of post disaster cooperation. American
Economic Review, 65, 127-138.
Drabek, T. E. (1986). Human System Responses to Disaster: An Inventory of
Sociological Findings. New York: Springer.
89
Bibliography 89
Drago, R., & Garvey, G. T. (1998). Incentives for helping on the job: Theory and
evidence. Journal of Labour Economics, 16, 1-25.
Dufwenberg, M., & Kirchsteiger, G. (2004). A theory of sequential reciprocity.
Games and Economic Behaviour, 47, 268-298.
Eagly, A. H., & Crowley, M. (1986). Gender and helping behaviour: A meta-analytic
review of the social psychological literature. Psychological Bulletin, 100,
283-308.
Easterlin, R. (1974). Does economic growth improve the human lot? Some empirical
evidence. In P. A. David & M. W. Reder (Eds.), Nations and Households in
Economic Growth: Essays in Honour of Moses Abramovitz (pp. 89-125).
New York: Academic Press.
Eaton, J. P., & Haas, C. (1994). Titanic: Triumph and Tragedy (2nd ed.). London:
Patrick Stephens Ltd.
Eckel, C., & Grossman, P. J. (1996). Altruism in Anonymous Dictator Games.
Games and Economic Behaviour, 16, 181-191.
Elster, J. (1985). Rationality, morality, and collective action. Ethics, 96, 136-155.
Elster, J. (1989). Social norms and economic theory. The Journal of Economic
Perspectives, 3, 99-117.
Elster, J. (1990). Norms of revenge. Ethics, 100, 862-885.
Elster, J. (1996). Rationality and the emotions. The Economic Journal, 106, 1386-
1397.
Elster, J. (1998). Emotions and economic theory. Journal of Economic Literature,
36, 47-74.
Elster, J. (2006). Fairness and norms. Social Research, 73, 365-376.
Elster, J. (2007). Explaining Social Behaviour. More Nuts and Bolts for the Social
Sciences. Cambridge: Cambridge University Press.
Emmerich, R. (Director, Screen Writer) Nachmanoff, J. (Screen Writer) Bell, A., &
Strieber, W. (Authors) (2004). The Day after Tomorrow. In R. Emmerich &
M. Gordon (Producer). USA: 20th Century Fox.
90
90 Bibliography
Emmerich, R. (Director, Writer) (2009). 2012. In R. Emmerich, L. Franco & M.
Gordon (Producer): Sony Pictures Entertainment.
Encyclopaedia Titanica. (2008). RMS Titanic passenger and crew biography, Titanic
history, research and discussions. Retrieved 20th March, 2008, from
http://www.encyclopedia-titanica.org/
Eswaran, M., & Kotwal, A. (2004). A theory of gender differences in parental
altruism. Canadian Journal of Economics, 37, 918-950.
Everly, G. S. (2002). A Clinical Guide to the Treatment of the Human Stress
Response (2nd Edition ed.). New York: Kluwer Academic/Plenum
Publishers.
Eysenck, M. W. (2004). Adolescence, adulthood and old age. Psychology: An
International Perspective (pp. 1-27): Psychology Press Ltd.
Fehr, E., Fischbacher, U., & Gachter, S. (2002). Strong reciprocity, human
cooperation and the enforcement of social norms. Human Nature, 13, 1-25.
Fehr, E., & Fischbacher, U. (2003). The nature of human altruism. Nature, 425, 785-
791.
Fehr, E., & Fischbacher, U. (2004). Social norms and human cooperation. Trends in
Cognitive Sciences, 8, 185-190.
Fehr, E., & Schmidt, K. M. (1999). A theory of fairness, competition, and
cooperation. Quarterly Journal of Economics, 114, 817-868.
Fehr-Duda, H., De Gennaro, M., & Schubert, R. (2006). Gender, financial risk and
probability weights. Theory and Decision, 60, 283-313.
Felson, R. B. (2000). The normative protection of women from violence.
Sociological Forum, 15, 91-116.
Foucault, M. (1979). Discipline and Punish: the Birth of the Prison. Penguin.
Frank, D. J., Meyer, J. W., & Miyahara, D. (1995). The individualist policy and the
prevalence of professionalized psychology: a cross-national study. American
Sociological Review, 60, 360-377.
91
Bibliography 91
Frank, R. H. (1999). Luxury Fever: Why Money Fails to Satisfy in an Era of Excess.
New York: The Free Press.
Frankenhaeuser, M. (1996). Stress and gender. European Review, 4, 313-327.
Frey, B. S. (1997). Not Just for the Money: An Economic Theory of Personal
Motivation. London: Cheltenham.
Frey, B. S. (Ed.). (1999). Economics as a Science of Human Behavior (2nd ed.).
Dordrecht: Kluwer Academic Publishers.
Frey, B. S., & Meier, S. (2004). Social comparisons and pro-social behaviour:
Testing conditional coordination in a field experiment. American Economic
Review, 94, 1717-1722.
Frey, B. S ., & Pommerehne, W. (1993). On the fairness of pricing - An empirical
survey among the general population. Journal of Economic Behaviour and
Organization, 20, 295-307.
Frey, B. S., & Torgler, B. (2007). Tax morale and conditional cooperation. Journal of
Comparative Economics, 35.
Frey, B. S., Savage, D. A., & Torgler, B. (2010). Noblesse Oblige? Determinants of
survival in a life and death situation. Journal of Economic Behavior and
Organization, 74, 1-11.
Geary, D. C. (1998). Male, female: the evolution of human sex differences (1st ed.).
Washington, DC: American Psychological Association.
Geller, J. B. (1998). Titanic: Women and Children First. New York: W.W. Norton
and Company Inc.
Gilbert, P. (2001). Evolutionary Approaches to Psychopathology: the role of natural
defenses. Australian and New Zealand Journal of Psychiatry, 35, 17-27.
Goldenson, R. M. (Ed.). (1984). The Longman Dictionary of Psychology and
Psychiatry. New York: Longman.
Goldthorpe, J. H. (1998). Rational action theory for sociology. The British Journal of
Sociology, 49, 167-192.
92
92 Bibliography
Gorman, R. F., & Kehr, J. B. (1992). Fairness as a constraint on profit seeking:
Comment. The American Economic Review, 82, 355-358.
Gorsky, M. (1998). The growth and distribution of English friendly societies in the
early nineteenth century. Economic History Review, 3, 489-511.
Gouldner, A. W. (1960). The norms of reciprocity: A preliminary statement.
American Sociological Review, 2, 161-178.
Gray, J. A. (1988). The Psychology of Fear and Stress (2nd ed.). New York:
Cambridge University Press.
Griswold, W. (2008). Cultures and Societies in a Changing World (3rd Edition ed.).
Los Angeles: Pine Forge Press.
Gross, R. (1996). Psychology: The Science of Mind and Behaviour (3rd ed.). London:
Hodder and Stoughton.
Grossi, P., & Kureuther, H. (Eds.). (2005). Catastrophe Modelling. A New Approach
to Managing Risk. New York: Springer.
Gwynne, S., Galea, E. R., & Lawrence, P. J. (2006). The introduction of social
adaption within evacuation modeling. Fire and Materials, 30, 285-309.
Hancock, P. A., & Szalma, J. L. (2008). Performance under Stress. Farnham:
Ashgate.
Harrell, W. A. (1994). Effects of blind pedestrians on motorists. Journal of Social
Psychology, 134, 529-539.
Haskin, B. (Director) Lyndon, B. (Screen Writer) & Wells, H. G. (Author) (1953).
War of the Worlds. In G. Pal (Producer). USA: Paramount.
Hassin, R., & Haviv, M. (2006). To Queue or Not to Queue: Equlibrium Behavior in
Queuing Systems. London: Kluwer Academic Publishers.
der Heide, E. A. (2004). Common Misconceptions about Disasters: Panic, the
―Disaster Syndrome,‖ and Looting. In O. L. M (Ed.), The First 72 Hours: A
Community Approach to Disaster Preparedness (pp. 340-380). Lincoln:
iUniverse Publishing.
93
Bibliography 93
Henrich, J. (2004). Cultural group selection, co-evolutionary processes and large-
scale cooperation. Journal of Economic Behaviour & Organization, 53, 3-35.
Henrich, J., Boyd, R., Bowles, S., Camerer, C., Gintis, H., & McElreath, R. (2001).
In search of homo economicus: Experiments in 15 small-scale societies.
American Economic Review, 91, 3-79.
Henry, J., & Wang, S. (1998). Effects of early stress on adult affiliative behaviour.
Psychoneuroendocrinology, 23, 863-875.
Hirshleifer, J. (1963). Disaster and Recovery: A Historical Survey: Rand Corporation
Memorandum.
Howard, R. A. (1966). Life and Death Decision Analysis. Stanford University,
Stanford.
Howard, R. A. (1980). On making life and death decisions. In W. Albers & J.R.C.
Schwing (Eds.), Societal Risk Assessment. New York: Plenum.
Howell, R. (1999). The Myth of the Titanic. London: Palgrave McMillian.
Inkeles, A. (1969). Making men modern: On the causes and consequences of
individual change in six developing countries. American Journal of
Sociology, 75, 208-225.
Janis, I. L., & Mann, L. (1977). Decision Making. New York: Free Press.
Johnson, N. R. (1988). Fire in a crowded theatre: A descriptive analysis of the
emergence of panic. International Journal of Mass Emergencies and
Disaster, 6, 7-26.
Johnson, N. R., Feinberg, W. E., & Johnston, D. M. (1994). Microstructure and
panic: The impact of social bonds on individual action in collective flight
from the Beverly Hills Supper Club fire. In R. R. Dynes & K. J. Tierney
(Eds.), Disasters, collective behaviour and social organizations (pp. 168-
189). Newark: University of Delaware Press.
Johnston, J. H., Poirer, J., & Smith-Jentsch, K. A. (1998). Decision making under
stress: Creating a research methodology. In J. A. Cannon-Bowers & E. Salas
(Eds.), Decision Making Under Stress (pp. 39-60). Washington DC:
American Psychological Association
94
94 Bibliography
Kahneman, D., Knetsch, J. L., & Thaler, R. (1986a). Fairness as a constraint on profit
seeking: Entitlements in the market. The American Economic Review, 76,
728-741.
Kahneman, D., Knetsch, J. L., & Thaler, R. (1986b). Fairness and the assumptions of
economics. The Journal of Business, 59, 285-300.
Kahneman, D., Slovic, P., & Tversky, A. (Eds.). (1982). Judgment under
Uncertainty: Heuristics and Biases. Cambridge: Cambridge University Press.
Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision
under Risk. Econometrica, 47, 263-291.
Katz, D., & Kahn, R. L. (1966). The Social Psychology of Organizations. New York:
Wiley.
Keinan, G. (1987). Decision making under stress: scanning of alternatives under
controllable and uncontrollable threats. Journal of Personality and Social
Psychology, 52, 639-644.
Kelley, H. H., Condry, J. C., Dahlke, A. E., & Hill, A. H. (1965). Collective
behaviour in a simulated and panic situation. Journal of Experimental Social
Psychology, 1, 20-56.
Kipling, R. (1892). Soldier an' Sailor Too. In Barrack-Room Ballads.
Kitts, J. A. (2006). Collective action, rival incentives, and the emergence of
antisocial norms. American Sociological Review, 71, 235-259.
Konow, J. (2003). Which is the Fairest One of All? A Positive Analysis of Justice
Theories. Journal of Economic Literature, 41, 1188-1239.
Kräkel, M. (2008). Emotions in tournaments. Journal of Economic Behaviour &
Organization, 67, 204-214.
Krebs, D. L. (1991). Altruism and egoism: A false dichotomy? Psychological
Inquiry, 2, 137-139.
Kunreuther, H. (1996). Mitigating disaster losses through insurance. Journal of Risk
and Uncertainty, 12, 171-187.
95
Bibliography 95
Kunreuther, H., & Pauly, M. (2005). Insurance decision making and market
Behaviour. Microeconomics 1, 63-127.
Kunreuther, H., & Roth, R. J. (1998). Paying the Price: The Status and the Role of
Insurance against Natural Disaster in the United States. Washington: John
Henry Press.
Lang, K., & Lang, G. E. (1962). Collective Dynamics. New York: Thomas Y.
Crowell Company.
Larson, R. (1987). Perspectives on queues: social justice and psychology of queuing.
Operations Research, 35, 895-905.
Lazear, E. P., & Rosen, S. (1981). Rank-order tournaments as optimal labour
contracts. Journal of Political Economy, 89, 841-864.
Leder, M. (Director) Rubin, B. J., & Tolkin, M. (Writer) (1998). Deep Impact. In D.
Brown & R. D. Zanuck (Producer). USA: Paramount.
Ledyard, J.O. (1995). Public goods: A survey of experimental research. In J. Kagel &
A.E. Roth (Eds.), Handbook of Experimental Economics (pp. 111-194).
Princeton: Princeton University Press.
Levitt, S. D., & List, J. A. (2009). Field experiments in economics: The past, the
present and the future. European Economic Review, 53, 1-18.
List, J. A. (2008). Homo experimentalis evolves. Science, 321, 207-208.
Long, T. E., & Hadden, J. K. (1985). A reconception of socialization. Sociological
Theory 3:39-49.
Lord, W. (1955). A Night to Remember. New York: Bantam.
Lord, W. (1988). The Night Lives On. New York: Morrow.
MacLean, P. D. (1990). The Triune Brain in Evolution: Role in Paleocerebral
Functions (1st ed.). New York: Plenum Press.
Mann, L. (1969). Queue culture: The waiting line as a social system. The American
Journal of Sociology, 75, 340-354
Margolis, H. (1982). Selfishness, Altruism, and Rationality. Cambridge: Cambridge
University Press.
96
96 Bibliography
Martin, D. J. (1978). Commentary: Brotherhood and lifeboat ethics. BioScience, 28,
718-721.
Mawson, A. R. (1978). Panic behaviour: A review and new hypothesis. Paper
presented at the 9th World Congress of Sociology, Uppsala, Sweden.
Mawson, A. R. (1980). Is the concept of panic useful for study purposes? In B. Levin
(Ed.), Behaviour in Fires. Boston: National Fire Protection Agency.
Mawson, A. R. (2005). Understanding mass panic and other collective responses to
threat and disaster. Psychiatry, 68, 95-113.
Mawson, A. R. (2007). Mass panic and social attachment: The dynamics of human
behavior Ashgate: Aldershot.
Meier, S. (2006). The Economics of Non-selfish Behaviour. Cheltenham: Edward
Elgar.
Meier, S. (2007). A Survey of economic theories and field evidence on pro-social
behavior. In B.S. Frey & A. Stutzer (Eds.), Economics and Psychology: A
Promising New Cross-Disciplinary Field (pp. 51-88). Cambridge: MIT Press.
Mintz, A. (1951). Non-adaptive group behaviour. Journal of Abnormal Psychology,
46, 150-159.
Montgomerie, R., & Weatherhead, P. (1988). Risk and rewards of nest defense by
parent birds. The Quarterly Review of Biology, 63, 167-187.
Nalebuff, B. J., & Stiglitz, J. E. (1983). Prizes and incentives: Towards a general
theory of compensation and competition. Bell Journal of Economics, 14, 21-
43.
Nova Scotia Archives and Records Management. (2008). RMS Titanic: Full
Electronic List of Bodies and Disposition of Same. Retrieved 6/08/2008,
from http://www.gov.ns.ca/nsarm
Oberholzer-Gee, F. (2007). The helping hand: A brief anatomy. In B.S. Frey & A.
Stutzer (Eds.), Economics and Psychology: A Promising New Cross-
Disciplinary Field (pp. 229-239). Cambridge: MIT Press.
97
Bibliography 97
O'Sullivan, P. (2000). The Lusitania: Unraveling the Mysteries. Staplehurst: The
Collins Press.
Ochs, J., & Roth, A. E. (1989). An experimental study of sequential bargaining.
American Economic Review, 79, 355-384.
Peek, M., & Walsh-Johnson, K. (2008). Lusitania Online. Retrieved 1st June, 2008,
from http://www.lusitania.net
Perlow, L., & Weeks, J. (2002). Who‘s helping whom? Layers of culture and
workplace behaviour. Journal of Organizational Behaviour, 23, 345-361.
Piliavin, J. A., & Charng, H. W. (1990). Altruism: A review of recent theory and
research. Annual Review of Sociology, 16, 27-65.
Polinsky, M. A., & Shavell, S. (2000). The economic theory of public enforcement of
law. Journal of Economic Literature, 38.
Pollak, R. A. (1976). Interdependent Preferences. American Economic Review, 66,
309-320.
Preston, D. (2002). Willful Murder. London: Transworld Publishers.
Prince, S. H. (Ed.). (1920). Catastrophe and Social Change (Vol. 94). London: P.S.
King & Son Ltd.
Quarantelli, E. L. (1960). Images of withdrawal behaviour in disasters: Some basic
misconceptions. Social Problems, 9, 68-79.
Quarantelli, E. L. (1972). Study and research in the United States. In Proceedings of
Organizational and Community Response to Disasters (Vol. Book and
monograph#8.). Columbus: Disaster Research Centre, The Ohio State
University.
Quarantelli, E. L. (2001). The sociology of panic. In S.A. Baltes (Ed.), International
Encyclopaedia of the Social and Behavioural Sciences (30th ed.). London:
Pergamon Press.
Quinn, P. J. (1999). Dusk to Dawn: Survivor Accounts of the Last Night on the
Titanic (1st ed.). USA: Fantail.
98
98 Bibliography
Rabin, M. (1993). Incorporating fairness into game theory and economics. The
American Economic Review, 83, 1281-1302.
Rabin, M. (2000). Risk aversion and expected-utility theory: A calibration theorem.
Econometrica, 68, 1281-1292.
Rabinowitz, F. E., Sutton, L., Schutter, T., Brown, A., Krizo, C., & Larsen, J. (1997).
Helpfulness to lost tourists. Journal of Social Psychology, 137, 502-509.
Raz, D., Levy, H., & Avi-Itzhak, B. (2004). A resource-allocation queuing fairness
measure. Sigmetrics, 32, 130-141.
Reiley, D. H., & List, J. A. (2007). Field experiments in economics. In S. N. Durlaf
& E. Blume (Eds.), The New Palgrave Dictionary of Economics (2nd ed.).
London: Palgrave Macmillian.
Ripley, A. (2008). The Unthinkable: Who Survives When Disaster Strikes - and Why?
London: Random House.
Rosenkoetter, M. M., Covan, E. K., Cobb, B. K., Bunting, S., & Weinrich, M.
(2007). Perceptions of older adults regarding evacuation in the event of a
natural disaster. Public Health Nursing, 24, 160-168.
Roth, A. E. (1995). Bargaining experiments. In J. H. Kagel & A. E. Roth (Eds.), The
Handbook of Experimental Economics (pp. 253-342). Princeton: Princeton
University Press.
Rothstein, D. (1972). Culture creation and social reconstruction: The socio-cultural
dynamics of intergroup contact. American Sociological Review, 37, 671-678.
Ruffman, A. (1999). Titanic Remembered: The Unsinkable Ship and Halifax (1st ed.
ed.). Halifax: Formac Publishing Company Ltd.
Savage, D. A., & Torgler, B. (2008). Fairness and Allocation Systems. Queensland
University of Technology, Unpublished Works.
Savage, D. A., & Torgler, B. (2009). Nerves of Steel? Stress, Work Performance and
Elite Athletes. Working Paper: School of Economics and Finance Discussion
Papers and Working Papers Series 251, School of Economics and Finance,
Queensland University of Technology.
99
Bibliography 99
Schelling, T. C. (1978). Micro-motives and Macro-behaviour. New York: W.W.
Norton.
Schooler, C. (1996). Cultural and social-structure explanations of cross-national
psychological differences. Annual Review of Sociology, 22, 323-349.
Schultz, D. P. (1966). An Experimental Approach to Panic Behavior: Group
Psychology Branch.
Schwartz, S. H., & Fleishman, J. A. (1978). Personal norms and the mediation of
legitimacy effects on helping. Social Psychology Quarterly, 41, 306-315.
Scitovsky, T. (1976). The Joyless Economy: An Inquiry into Human Satisfaction and
Consumer Dissatisfaction. Oxford: Oxford University Press.
Selye, H. (1936). A syndrome produced by diverse noxious agents. Nature, 138, 32.
Shepard, D. S., & Zeckhauser, R. J. (1984). Survival versus consumption.
Management Science, 30, 423-439.
Sherif, M. (1966). The Psychology of Social Norms. New York: Harper & Row.
Shotland, R. L., & Stebbins, C. A. (1983). Emergency and cost as determinants of
helping behaviour and the slow accumulation of social psychological
knowledge. Social Psychology Quarterly, 46, 36-46.
Singer, M. (1999). Fairness. In P. E. Earl & S. Kemp (Eds.), The Elgar Companion
to Consumer Research and Economic Psychology. Cheltenham: Edward
Elgar.
Slonim, R., & Roth, A. E. (1998). Learning in high stakes ultimatum games: An
experiment in the Slovak Republic. Econometrica 66, 569-596.
Smelser, N. (1963). Theory of Collective Behaviour. New York: Free Press.
Smith, A. (1790). The Theory of Moral Sentiments (6th ed.). London: A. Millar.
Smith, J. E., & Keeney, R. L. (2005). Your money or your life: A prescriptive model
for health, safety and consumption decisions. Management Science, 51, 1309-
1325.
Smith, V. L. (1991). Rational choice: The contrast between economics and
psychology. The Journal of Political Economy, 99, 877-897.
100
100 Bibliography
Sobel, J. (2005). Interdependent preferences and reciprocity. Journal of Economic
Literature, 42, 392-436.
Sorkin, A. L. (1982). Economic Aspects of Natural Disasters. Lexington: Lexington
Books.
Spielberg, S. (Director) Friedman, J., Koepp, D. (Screen Writers) & Wells, H. G.
(Author) (2005). War of the Worlds. In K. Kennedy & C. Wilson (Producer).
USA: Paramount Pictures.
Stiglitz, J. E. (1988). Economics of the public sector (2nd ed.). New York: W.W.
Norton.
Subcommittee of the Committee on Commerce. (1912) in The Official Transcript of
the United States Senate Hearings into the Sinking of the RMS Titanic. U.S.
Senate. pp. 70, 77, 333, 806, 1029, 1042.
Thaler, R. H. (2000). From homo economicus to homo sapiens. Journal of Economic
Perspectives, 14, 133-141.
Thaler, R., & Sunstein, C. R. (2008). Nudge: Improving Decisions about Health,
Wealth and Happiness. New Haven: Yale University Press.
The Queen's Royal Surrey Regimental Association. (2008). The Queen's Royal
Surrey Regiment. Retrieved 1st August, 2008, from
http://www.queensroyalsurreys.org.uk/1661to1966/birkenhead/birkenhead.ht
ml
Tierney, K. J., Lindell, M. K., & Perry, R. W. (2001). Facing the Unexpected. New
York: Joseph Henry Press.
Torgler, B. (2007). Tax Compliance and Tax Morale: A Theoretical and Empirical
Analysis. Cheltenham: Edward Elgar.
Trivers, R. L. (1972). Parental investment and sexual selection In B. Campbell (Ed.),
Sexual Selection and the Descent of Man 1871-1997 (pp. 136-179). Chicago:
Aldine Transaction.
Turner, R. H., & Killian, L. M. (1987). Collective Behavior (3rd. ed.). Los Angeles:
Prentice-Hall Inc.
101
Bibliography 101
U.S. National Archives. (2009). Partial list of survivors of the Titanic who were
taken aboard the Carpathia, which arrived at the Port of New York, NY, April
18, 1912, Roll 1883, Vol. 4183. Retrieved 10th
of June, 2008, from
http://www.archives.gov
United Nations Department of International Economic and Social Affairs. (1982).
Provisional Guidelines on Standard International Age Classifications.
Retrieved10thAugust2008.http://unstats.un.org/unsd/publication/SeriesM/Seri
esM_74e.pdf.
Vingerhoets, A. J., & Perski, A. (1999). The psychobiology of stress. Unpublished
Working Paper. Department of Psychology: Tilburg University.
Voland, E. (1998). Evolutionary ecology of human reproduction. Annual Review of
Anthropology, 27, 347-374.
Wang, T. H. (2008). The Lusitania Resource. Retrieved 1st June, 2008, from
http://www.rmslusitania.info
Weber, M. (1930). The Protestant Ethic and the Spirit of Capitalism. Allen &
Unwin.
Wilson, E. O. (1975). Socio-biology: The New Synthesis. Cambridge: The Belknap
Press of Harvard University Press.
Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data.
Cambridge: MIT Press.
Wooldridge, J. M. (2003). Introductory Econometrics: A Modern Approach.
Chicago: Monarch Book Company.
Worman, B. (1979). Helping conditions of common threat: Increased "we-feeling" or
ensuring reciprocity. Social Psychology Quarterly, 42, 410-414.
Wreck Commissioner's Court. (1912). Formal Investigation into the loss of the S.S.
Titanic, Evidence, Appendices and Index. London: Public Records Office.
Wreck Commissioner's Court. (1915). in Official Transcript of the British Wreck
Commissioner's Inquiry. London: Public Records Office.
102
102 Bibliography
Wright, P. (1974). The harassed decision maker: Time pressures, distractions and the
use of evidence. Journal of Applied Psychology, 59, 555-561
Appendices 103
Appendices
APPENDIX A: PUBLICATIONS
Frey, B. S., Savage, D. A., & Torgler, B. (2010). Noblesse Oblige? Determinants of
survival in a life and death situation. Journal of Economic Behavior and
Organization, 74, 1-11.
Frey, B. S., Savage, D. A., & Torgler, B. (2010). Interaction of natural survival
instincts and internalized social norms exploring the Titanic and Lusitania disasters,
Proceedings of the National Academy of Science (P.N.A.S.), 107(11), 4862-4865