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  Cooperation in social dilemmas

Hagel, K. (2017). Cooperation in social dilemmas. PhD Thesis, Christian-Albrechts-Universität, Kiel.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-5479-9 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-7F3D-E
Genre: Thesis

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 Creators:
Hagel, Kristin1, Author              
Traulsen, Arne1, Referee              
Schulenburg, Hinrich, Referee
Affiliations:
1Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

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 Abstract: In evolutionary theory individuals are assumed to maximise their Darwinian fitness, which is defined as an individual’s relative genetic contribution to the gene pool of the next generation. 33, 55, 74, 173 However, while cooperation increases the fitness of the recipient it is costly for a cooperator in terms of forgoing own reproductive potential128; even though cooperation can also entail benefits, e.g. if reciprocated by other group members.8, 197, 213 If a non-cooperator has a higher individual fitness level than a cooperator, although a group of cooperators is better off than a group of defectors, a social dilemma arises.44, 76 Here, cooperation is undermined by the conflict between self and group-interest. The goal of this thesis has been to study human cooperation in such dilemmas. Using the collective risk social dilemma game,122 the studies of this thesis particularly focus on the influence of risk scenarios and temporal discounting on cooperation. In the standard variant of the game,122 human subjects can either cooperate at their own expense in order to avoid simulated ‘dangerous climate change’, or they risk monetary losses with a predefined probability – hence the collective risk. In terms of evolutionary game theory, such studies have been designed to allow human subjects to maximise their fitness,127, 192 here modelled either by monetary payoffs or by indirect benefits through supporting descendants. A main finding of the thesis is the role of a stepwise risk scenario with a strict threshold as a mechanism for the evolution of cooperation. In a computerised behavioural experiment with such a scenario, participants coordinated their group contributions around the social optimum, where group members achieve maximum joint outcomes; even though in the experiment the participants have not been restricted exactly to an equal share principle. On the other hand, risk and investment were balanced out more generously if the risk decays stepwise linearly or piecewise linearly. In particular the ratio between the first derivative of a risk curve and the number of players determines the level of contributions, as further demonstrated by a theoretical model. While cooperation usually decreases with the number of group members, only a stepwise risk scenario turned out to stabilise cooperation (a) for a large number of players and (b) independent of individual risk preferences. However, cooperation can even fail under a stepwise risk scenario when benefits are deferred to future generations, as it is likely in the prevention of real climate change.161 This was shown in an inter- and intergenerational study about discounting, where student participants reduced climate investments when their own payoffs were delayed in time and widely stopped contributing when they had no prospects of higher expected returns in the future. A different picture arises in a follow up experiment with elderly subjects where the question was investigated whether people are more willing to invest in climate change mitigation when they have descendants. As a result, descendants did not play a decisive role in participants’ climate contributions. However, participants donated altruistically for a climate change mitigation measure; especially when they were wealthy in their real life. This demonstrates broader motives than pure payoff maximisation among the participants. The study further implies an effect of age on cooperation due to an overall high contribution level among the elderly compared to the former student experiment.

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Language(s): eng - English
 Dates: 2017-05-022017-05-02
 Publication Status: Published in print
 Pages: 117
 Publishing info: Kiel : Christian-Albrechts-Universität
 Table of Contents: Contents
1 Introduction 1
1.1 Cooperation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Social dilemmas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Game theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Mechanisms of cooperation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.5 Cooperation in the climate game . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.6 Goals of the dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2 The level of climate-change mitigation depends on how humans assess
the risk arising from missing the 2 C target 13
2.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.3.1 Maximising expected winnings . . . . . . . . . . . . . . . . . . . . . 19
2.3.2 Group investments . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3.3 Pay-out per subject . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3.4 Reaching the target sum . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3.5 Free-riders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.4 Discussion and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3 Which risk scenarios can drive the emergence of costly cooperation? 26
3.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.3 Model and analytical results . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.3.1 Linear risk curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.3.2 Piecewise linear risk curve . . . . . . . . . . . . . . . . . . . . . . . . 31
3.3.3 Synergy and discounting . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.3.4 Fermi function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.3.5 More complicated risk curves . . . . . . . . . . . . . . . . . . . . . . 34
3.4 Evolutionary dynamics of strategies . . . . . . . . . . . . . . . . . . . . . . . 34
3.5 Risk preferences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.6 Discussion and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
4 Intra- and intergenerational discounting in the climate game 40
4.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.4 Discussion and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.5 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
5 Cooperation in the climate game is not determined by having descendants
but by wealth 50
5.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
5.3.1 Experimental design . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
5.3.2 Statistical models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
5.4.1 Group investments at both locations . . . . . . . . . . . . . . . . . . . 56
5.4.2 Covariates of interest at the first location . . . . . . . . . . . . . . . . . 57
5.4.3 Covariates of interest at the second location . . . . . . . . . . . . . . . 57
5.4.4 Covariates of interest at both locations . . . . . . . . . . . . . . . . . . 60
5.5 Discussion and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
6 Main Discussion 64
7 Supplementary Information 69
7.1 The level of climate-change mitigation depends on how humans assess the risk
arising from missing the 2 C target . . . . . . . . . . . . . . . . . . . . . . . 69
7.1.1 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
7.1.2 Frequency of selfish, fair-share, and altruistic individual investments . . 72
7.1.3 Experiment instructions . . . . . . . . . . . . . . . . . . . . . . . . . 72
7.2 Theoretical predictions of cooperation in the empirical investigated risk curves . 79
7.3 Intra- and intergenerational discounting in the climate game . . . . . . . . . . . 81
7.3.1 Experiment instructions . . . . . . . . . . . . . . . . . . . . . . . . . 81
7.3.2 Hamburger Abendblatt newspaper advertisement . . . . . . . . . . . . 90
7.3.3 Tree planting receipt . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
7.4 Cooperation in the climate game is not determined by having descendants but
by wealth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
7.4.1 Sourcing of the participants . . . . . . . . . . . . . . . . . . . . . . . 95
7.4.2 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
7.4.3 Game instructions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
7.4.4 Allocation of the participants into poor and rich . . . . . . . . . . . . . 96
7.4.5 Mixed effects models . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
7.4.6 Comparison with the student experiment . . . . . . . . . . . . . . . . 98
7.4.7 Questionnaires . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
Bibliography 102
 Rev. Method: -
 Identifiers: Other: Diss/12851
 Degree: PhD

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