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Can Social Group-Formation Norms Influence Behavior?: An Experimental Study Alexandros Rigos Lund University Lund Brown Bag Seminar 2017-03-31 Alex Rigos (Lund) Social Group-Formation Norms Title Motivation Evolutionary Game Theory: More

  1. Can Social Group-Formation Norms Influence Behavior?: An Experimental Study Alexandros Rigos Lund University Lund Brown Bag Seminar 2017-03-31 Alex Rigos (Lund) Social Group-Formation Norms Title

  2. Motivation Evolutionary Game Theory: More successful strategies evolve faster than less successful ones. (Maynard Smith and Price, 1973) Alex Rigos (Lund) Social Group-Formation Norms 1 / 34

  3. Motivation Evolutionary Game Theory: More successful strategies evolve faster than less successful ones. (Maynard Smith and Price, 1973) Usual assumption: random matching. Alex Rigos (Lund) Social Group-Formation Norms 1 / 34

  4. Motivation Evolutionary Game Theory: More successful strategies evolve faster than less successful ones. (Maynard Smith and Price, 1973) Usual assumption: random matching. But people do not meet at random. Alex Rigos (Lund) Social Group-Formation Norms 1 / 34

  5. Motivation Evolutionary Game Theory: More successful strategies evolve faster than less successful ones. (Maynard Smith and Price, 1973) Usual assumption: random matching. But people do not meet at random. What if individuals meet similarly behaved ones more often? Alex Rigos (Lund) Social Group-Formation Norms 1 / 34

  6. Motivation Evolutionary Game Theory: More successful strategies evolve faster than less successful ones. (Maynard Smith and Price, 1973) Usual assumption: random matching. But people do not meet at random. What if individuals meet similarly behaved ones more often? Such “assortative” group-formation norm would affect long-run outcomes ( e.g. it can support cooperation in a PD). Alex Rigos (Lund) Social Group-Formation Norms 1 / 34

  7. Motivation Evolutionary Game Theory: More successful strategies evolve faster than less successful ones. (Maynard Smith and Price, 1973) Usual assumption: random matching. But people do not meet at random. What if individuals meet similarly behaved ones more often? Such “assortative” group-formation norm would affect long-run outcomes ( e.g. it can support cooperation in a PD). We test the predictions of nonrandom matching models in a game of aggression (Hawk/Dove). Alex Rigos (Lund) Social Group-Formation Norms 1 / 34

  8. Motivation Questions If there was such assortative matching in place, would it actually change participants’ behaviour? Alex Rigos (Lund) Social Group-Formation Norms 2 / 34

  9. Motivation Questions If there was such assortative matching in place, would it actually change participants’ behaviour? How quickly do participants adapt under different matching regimes? Alex Rigos (Lund) Social Group-Formation Norms 2 / 34

  10. Motivation Questions If there was such assortative matching in place, would it actually change participants’ behaviour? How quickly do participants adapt under different matching regimes? How do they learn? Alex Rigos (Lund) Social Group-Formation Norms 2 / 34

  11. Motivation Questions If there was such assortative matching in place, would it actually change participants’ behaviour? Answer: Yes! How quickly do participants adapt under different matching regimes? How do they learn? Alex Rigos (Lund) Social Group-Formation Norms 2 / 34

  12. Background Evolutionary Game Theory (EGT) Standard: Individuals meet at random. No support for pro-social behaviour. Alex Rigos (Lund) Social Group-Formation Norms 3 / 34

  13. Background Evolutionary Game Theory (EGT) Standard: Individuals meet at random. No support for pro-social behaviour. Deviations from random matching Kin selection (Hamilton, 1964). Alex Rigos (Lund) Social Group-Formation Norms 3 / 34

  14. Background Evolutionary Game Theory (EGT) Standard: Individuals meet at random. No support for pro-social behaviour. Deviations from random matching Kin selection (Hamilton, 1964). Local interactions (Boyd and Richerson, 2002). Alex Rigos (Lund) Social Group-Formation Norms 3 / 34

  15. Background Evolutionary Game Theory (EGT) Standard: Individuals meet at random. No support for pro-social behaviour. Deviations from random matching Kin selection (Hamilton, 1964). Local interactions (Boyd and Richerson, 2002). Homophily (Alger and Weibull, 2011). Alex Rigos (Lund) Social Group-Formation Norms 3 / 34

  16. Background Evolutionary Game Theory (EGT) Standard: Individuals meet at random. No support for pro-social behaviour. Deviations from random matching Kin selection (Hamilton, 1964). Local interactions (Boyd and Richerson, 2002). Homophily (Alger and Weibull, 2011). Meritocracy (action assortativity) (Nax, Murphy, and Helbing, 2014). Alex Rigos (Lund) Social Group-Formation Norms 3 / 34

  17. Background Evolutionary Game Theory (EGT) Standard: Individuals meet at random. No support for pro-social behaviour. Deviations from random matching Kin selection (Hamilton, 1964). Local interactions (Boyd and Richerson, 2002). Homophily (Alger and Weibull, 2011). Meritocracy (action assortativity) (Nax, Murphy, and Helbing, 2014). Jensen and Rigos, (2014) generalize nonrandom matching rules. Alex Rigos (Lund) Social Group-Formation Norms 3 / 34

  18. Background Evolutionary Game Theory (EGT) Standard: Individuals meet at random. No support for pro-social behaviour. Deviations from random matching Kin selection (Hamilton, 1964). Local interactions (Boyd and Richerson, 2002). Homophily (Alger and Weibull, 2011). Meritocracy (action assortativity) (Nax, Murphy, and Helbing, 2014). Jensen and Rigos, (2014) generalize nonrandom matching rules. Different matching rules lead to different evolutionary outcomes. Alex Rigos (Lund) Social Group-Formation Norms 3 / 34

  19. Background Related Experiments Friedman and Oprea, (2011) and Oprea, Henwood, and Friedman, (2011) look at similar evolutionary setup in the lab in continuous time with random matching. They find fast convergence to theoretical predictions (Nash equilibrium). Yang, Yue, and Yu, (2007) show experimentally that assortative matching based on past actions increases cooperation in PD games. Nax et al., (2015) study public goods games under meritocratic matching. High levels of contributions are sustained. Alex Rigos (Lund) Social Group-Formation Norms 4 / 34

  20. Background Related Experiments Friedman and Oprea, (2011) and Oprea, Henwood, and Friedman, (2011) look at similar evolutionary setup in the lab in continuous time with random matching. They find fast convergence to theoretical predictions (Nash equilibrium). Yang, Yue, and Yu, (2007) show experimentally that assortative matching based on past actions increases cooperation in PD games. Nax et al., (2015) study public goods games under meritocratic matching. High levels of contributions are sustained. What about other types of games? Alex Rigos (Lund) Social Group-Formation Norms 4 / 34

  21. Theoretical Concepts The Game There is a population of individuals. Alex Rigos (Lund) Social Group-Formation Norms 5 / 34

  22. Theoretical Concepts The Game There is a population of individuals. Each individual can follow one of two strategies: H or D. Alex Rigos (Lund) Social Group-Formation Norms 5 / 34

  23. Theoretical Concepts The Game There is a population of individuals. Each individual can follow one of two strategies: H or D. At each time t they are drawn to form pairs (1-population matching protocol). Alex Rigos (Lund) Social Group-Formation Norms 5 / 34

  24. Theoretical Concepts The Game There is a population of individuals. Each individual can follow one of two strategies: H or D. At each time t they are drawn to form pairs (1-population matching protocol). Each individual in each pair gets payoff according to HD game. Dove Hawk Dove 11,11 5,17 Hawk 17,5 2,2 Table: (Adapted from Oprea, Henwood, and Friedman, (2011)) Alex Rigos (Lund) Social Group-Formation Norms 5 / 34

  25. Theoretical Concepts The Game There is a population of individuals. Each individual can follow one of two strategies: H or D. At each time t they are drawn to form pairs (1-population matching protocol). Each individual in each pair gets payoff according to HD game. Dove Hawk Dove 11,11 5,17 Hawk 17,5 2,2 Table: (Adapted from Oprea, Henwood, and Friedman, (2011)) Assumption: More successful strategies have more followers next round (because of imitation, replicator dynamics). Alex Rigos (Lund) Social Group-Formation Norms 5 / 34

  26. Theoretical Concepts Matching Protocols Say at time t there are (proportions of) x D Doves and x H Hawks in the population. Alex Rigos (Lund) Social Group-Formation Norms 6 / 34

  27. Theoretical Concepts Matching Protocols Say at time t there are (proportions of) x D Doves and x H Hawks in the population. Random matching: both Doves and Hawks have the same probability to get matched to a Dove ( p DD = p HD = x D ). Alex Rigos (Lund) Social Group-Formation Norms 6 / 34

  28. Theoretical Concepts Matching Protocols Say at time t there are (proportions of) x D Doves and x H Hawks in the population. Random matching: both Doves and Hawks have the same probability to get matched to a Dove ( p DD = p HD = x D ). Assortative matching: p DD − p HD = α (Index of Assortativity). Alex Rigos (Lund) Social Group-Formation Norms 6 / 34

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