Risk-Averse and Self-Interested Shifts in Groups in Both Median and Random Rules
Abstract
:1. Introduction
2. Materials and Methods
2.1. Part 1 (Tasks 1 and 2)
2.2. Part 2 (Tasks 3 and 4)
2.3. Procedure
3. Results
3.1. Descriptive Statistics
3.2. Group Effect
3.2.1. Risk Attitude
3.2.2. Altruistic Preferences
3.3. Effect of the Collective Decision Rule
3.3.1. Risk Attitude
3.3.2. Altruistic Preferences
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A. Experiment Instructions (in English for the Median Rule)
Appendix A.1. Introduction
- Instructions
- Experimental agreement form
- Receipt
- Ballpoint pen
Appendix A.2. Experimental Description
Appendix A.3. Experimental Tasks
Appendix A.3.1. Task 1
Appendix A.3.2. Task 2
Exercise 1
- ○
- Member investing 120 yen: yen
- ○
- Member investing 60 yen: yen
Exercise 2
- ○
- Member investing 180 yen: yen
- ○
- Member investing nothing at all: yen
Individual-Choice Task
Group-Choice Task
Appendix A.3.3. Task 3
Individual-Choice Task
Group-Choice Task
Appendix A.3.4. Task 4
Individual-Choice Task
Group-Choice Task
Appendix B. Experiment Instructions (in English for the Random Rule)
Appendix B.1. Introduction
- Instructions
- Experimental agreement form
- Receipt
- Ballpoint pen
Appendix B.2. Experimental Description
Appendix B.3. Experimental Tasks
Appendix B.3.1. Task 1
Appendix B.3.2. Task 2
Exercise 1
- ○
- Member investing 120 yen: yen
- ○
- Member investing 60 yen: yen
Exercise 2
- ○
- Member investing 180 yen: yen
- ○
- Member investing nothing at all: yen
Individual-Choice task
Group-Choice Task
Appendix B.3.3. Task 3
Individual-Choice Task
Group-Choice Task
Appendix B.3.4. Task 4
Individual-Choice Task
Group-Choice Task
1 | In social psychology, the two main explanations for these shifts are social comparison theory (Levinger & Schneider, 1969) [3] and persuasive argument theory (Burnstein et al., 1973; Brown, 1974) [4,5]. Social comparison theory states that people are motivated to perceive and present themselves in a socially desirable way. According to persuasive argument theory, group decisions lead to a particular direction because once certain novel arguments are shared during group discussions, these arguments persuade other group members on the issue. |
2 | |
3 | In line with peer effects research, the presence of peers influences group decision-making related to risk via group discussions and interactions (Gardner & Steinberg, 2005; Blakemore et al., 2012; Albert et al., 2011; Bougheas et al., 2013; Pincham et al., 2015; Gioia, 2017; Van Hoorn et al., 2017; Haller et al., 2018; Zhang & Zhu, 2021; Zhang et al., 2022) [10,11,12,13,14,15,16,17,18,19]. Additionally, Braams et al. (2019) and Osmont et. al (2020) [20,21] showed that peers’ perceived choices affect the decisions of others. Moreover, altruistic preferences are influenced by peer effects via group interactions (Guroglu et al., 2015; Burnett-Heyes et al., 2015; Van Hoorn et al., 2016; Xiong et al., 2020; Bourlès, et al., 2021; Chennells et al., 2022) [22,23,24,25,26,27]. |
4 | Another perspective in economic studies of group decision-making is determining whether groups are more rational than individuals (Bornstein & Yaniv, 1998; Cox & Hayne, 2006; Kocher & Sutter, 2005; Song, 2008) [28,29,30,31]. Charness and Sutter (2012) [32] concluded that group decision-making is more likely close to standard game-theoretic predictions; groups are more cognitively sophisticated and productive (due to peer effects) while having more self-interested preferences. |
5 | The individual and group choice tasks were conducted in the same session while the instruction sheets the subjects received were identical (see Appendix A and Appendix B). |
6 | Regarding group decision-making without anonymity, Shupp and Williams (2008), Baker et al. (2008), Rockenbach et al. (2007), and Cason and Mui (1997) [33,34,37,40] used face-to-face discussions with group members to examine the preferential differences toward risk or altruism between the individuals and groups as mentioned in the Introduction. |
7 | He and Villeval (2014) [46] reported that, in groups, people tend to make very different choices between first and final choices, especially after observing the other member’s choices in an ultimatum game and a modified dictator game. While the authors investigated how individual preferences were aggregated in groups, the present study aimed to examine the subjects’ preferential differences in deciding whether to be alone or in a group. Thus, we focused on their choices in each one-shot decision. |
8 | Our subjects were from various disciplines (economics, management, law, literature, science, etc.), and they had native-level Japanese language skills (almost all of our subjects were Japanese undergraduate students). |
9 | As choosing a safe option in the tenth decision means preferring a certain 200 yen over a certain 380 yen, we interpreted this as a sign that the subject did not understand the instructions (Anderson & Mellor, 2008 p. 1265) [48]. |
10 | We determined the lower bound of the range by the first choice of the risky option and the upper bound by the last choice of the safe option (Anderson & Mellor, 2008, p. 1265) [48]. |
11 | |
12 | The mean values of the investment and donation variables for individual choice are 113.89 yen and 48.12 yen, respectively, while those for group choice are 93.48 yen and 31.52 yen, respectively. |
13 | In our sample, approximately 45.1% of the subjects were defined as “prosocial.” This ratio is consistent with Au and Kwong (2004) [54], who reported that roughly 45% were categorized as “prosocial” (on average) in various studies. |
14 | Our study excluded the university dummy variables from the model as the random rule conditions were only performed at Kansai University. |
15 | We take values of −2 and 2 for choosing the risky option in Decision 1 and the safe option in Decision 10, respectively, as the midpoints of the CRRA interval, following Reynaud and Couture (2012) [55]. |
References
- Stoner, J.A.F. A Comparison of Individuals and Group Decisions Involving Risk. Unpublished. Master’s Thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, 1961. [Google Scholar]
- Moscovici, S.; Zavalloni, M. The group as a polarizer of attitudes. J. Pers. Soc. Psychol. 1969, 12, 125–135. [Google Scholar] [CrossRef]
- Levinger, G.; Schneider, D.J. Test of the “risk is value” hypothesis. J. Pers. Soc. Psychol. 1969, 11, 165–169. [Google Scholar] [CrossRef]
- Burnstein, E.; Vinokur, A.; Trope, Y. Interpersonal comparisons versus persuasive argument: A more direct test of alternative explanations for group-induced shifts in individual choices. J. Exp. Soc. Psychol. 1973, 9, 236–245. [Google Scholar] [CrossRef]
- Brown, R. Further comment on the risky shift. Am. Psychol. 1974, 29, 468–470. [Google Scholar] [CrossRef]
- Kerr, L.N.; MacCoun, R.J.; Kramer, G.P. Bias in judgment: Comparing individuals and groups. Psychol. Rev. 1996, 103, 687–719. [Google Scholar] [CrossRef]
- Sunstein, C.R. Deliberative trouble? Why groups go to extremes. Yale Law J. 2000, 110, 71–119. [Google Scholar] [CrossRef]
- Sunstein, C.R. The law of group polarization. J. Political Philos. 2002, 10, 175–195. [Google Scholar] [CrossRef]
- Manin, B. Deliberation: Why We Should Focus on Debate Rather than Discussion; Paper delivered at the Program in Ethics and Public Affairs Seminar; Princeton University: Princeton, NJ, USA, 2005. [Google Scholar]
- Gardner, M.; Steinberg, L. Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: An experimental study. Dev. Psychol. 2005, 41, 625–635. [Google Scholar] [CrossRef]
- Albert, D.; Steinberg, L. Judgment and decision making in adolescence. J. Res. Adolesc. 2011, 21, 211–224. [Google Scholar] [CrossRef]
- Blakemore, S.; Robbins, T.W. Decision-making in the adolescent brain. Nat. Neurosci. 2012, 15, 1184–1191. [Google Scholar] [CrossRef]
- Bougheas, S.; Nieboer, J.; Sefton, M. Risk-taking in social settings: Group and peer effects. J. Econ. Behav. Organ. 2013, 92, 273–283. [Google Scholar] [CrossRef] [PubMed]
- Pincham, H.L.; Wu, C.; Killikelly, C.; Vuillier, L.; Fearon, R.M. Social provocation modulates decision making and feedback processing: Examining the trajectory of development in adolescent participants. Dev. Cogn. Neurosci. 2015, 15, 58–66. [Google Scholar] [CrossRef] [PubMed]
- Gioia, F. Peer effects on risk behaviour: The importance of group identity. Exp. Econ. 2017, 20, 100–129. [Google Scholar] [CrossRef]
- Van Hoorn, J.; Crone, E.A.; Van Leijenhorst, L. Hanging out with the right crowd: Peer influence on risk-taking behavior in adolescence”. J. Res. Adolesc. 2017, 27, 189–200. [Google Scholar] [CrossRef]
- Haller, S.P.W.; Bang, D.; Bahrami, B.; Lau, J.Y.F. Group decision-making is optimal in adolescence. Sci. Rep. 2018, 8, 15565. [Google Scholar] [CrossRef]
- Zhang, W.; Zhu, L. The influence of peers on adolescents’ risk-taking behavior and its mechanism. Adv. Psychol. Sci. 2021, 29, 1462–1471. [Google Scholar] [CrossRef]
- Zhang, W.; Jiang, Y.; Wang, C.; Zhu, L. Group decision-making on risky choice in adolescents and young adults. Curr. Psychol. 2022, 1–10. [Google Scholar] [CrossRef]
- Braams, B.R.; Davidow, J.Y.; Somerville, L.H. Developmental patterns of change in the influence of safe and risky peer choices on risky decision-making”. Dev. Sci. 2019, 22, e12717. [Google Scholar] [CrossRef]
- Osmont, A.; Camarda, A.; Habib, M.; Cassotti, M. Peers’ choices influence adolescent risk-taking especially when explicit risk information is lacking. J. Res. Adolesc. 2021, 31, 402–416. [Google Scholar] [CrossRef]
- Guroglu, B.; van den Bos, W.; Crone, E.A. Fairness considerations: Increasing understanding of intentionality during adolescence. J. Exp. Child Psychol. 2009, 104, 398–409. [Google Scholar] [CrossRef]
- Burnett Heyes, S.; Jih, Y.R.; Block, P.; Hiu, C.F.; Holmes, E.A.; Lau, J.Y. Relationship reciprocation modulates resource allocation in adolescent social networks: Developmental effects. Child Dev. 2015, 86, 1489–1506. [Google Scholar] [CrossRef] [PubMed]
- Van Hoorn, J.; van Dijk, E.; Meuwese, R.; Rieffe, C.; Crone, E.A. Peer Influence on Prosocial Behavior in Adolescence. J. Res. Adolesc. 2016, 26, 90–100. [Google Scholar] [CrossRef]
- Bourlès, R.; Bramoullé, Y.; Perez-Richet, E. Altruism and Risk Sharing in Networks. J. Eur. Econ. Assoc. 2021, 19, 1488–1521. [Google Scholar] [CrossRef]
- Chennells, M.; Wozniak, M.; Butterfill, S.; Michael, J. Coordinated decision-making boosts altruistic motivation-But not trust. PLoS ONE 2022, 17, e0272453. [Google Scholar] [CrossRef] [PubMed]
- Xiong, W.; Gao, X.; He, Z.; Yu, H.; Liu, H.; Zhou, X. Affective evaluation of others’ altruistic decisions under risk and ambiguity. Neuroimage 2020, 218, 116996. [Google Scholar] [CrossRef]
- Bornstein, G.; Yaniv, I. Individual and group behavior in the ultimatum game: Are groups more “rational” players? Exp. Econ. 1998, 1, 101–108. [Google Scholar] [CrossRef]
- Cox, J.C.; Hayne, S.C. Barking up the right tree: Are small groups rational agents? Exp. Econ. 2006, 93, 209–222. [Google Scholar] [CrossRef]
- Kocher, M.; Sutter, M. The decision maker matters: Individuals versus group behaviour in experimental beauty-contest games. Econ. J. 2005, 115, 200–223. [Google Scholar] [CrossRef]
- Song, F. Trust and reciprocity behavior and behavioral forecasts: Individuals versus group-representatives. Games Econ. Behav. 2008, 622, 675–696. [Google Scholar] [CrossRef]
- Charness, G.; Sutter, M. Groups make better self-interested decisions. J. Econ. Perspect. 2012, 263, 157–176. [Google Scholar] [CrossRef] [Green Version]
- Baker, R.; Laury, S.; Williams, A. Comparing small-group and individual behavior in lottery-choice experiments. South. Econ. J. 2008, 752, 367–382. [Google Scholar] [CrossRef]
- Shupp, R.S.; Williams, A.W. Risk preference differentials of small groups and individuals. Econ. J. 2008, 118, 258–283. [Google Scholar] [CrossRef]
- Masclet, D.; Loheac, Y.; Denant-Boemont, L.; Colombier, N. Group and individual risk preferences: A lottery-choice experiment. J. Econ. Behav. Organ. 2009, 703, 470–484. [Google Scholar] [CrossRef]
- Mifune, N.; Hizen, Y.; Kamijo, Y.; Okano, Y. Preemptive striking in individual and group conflict. PLoS ONE 2016, 115, e0154859. [Google Scholar] [CrossRef]
- Rockenbach, B.; Sadrieh, A.; Mathauschek, B. Teams take the better risks. J. Econ. Behav. Organ. 2007, 633, 412–422. [Google Scholar] [CrossRef]
- Zhang, J.; Casari, M. How groups reach agreement in risky choices: An experiment. Econ. Inq. 2012, 502, 502–515. [Google Scholar] [CrossRef]
- Harrison, G.W.; Lau, M.I.; Rutstrom, E.E.; Tarazona-Gomez, M. Preferences over social risk. Oxf. Econ. Pap. 2012, 651, 25–46. [Google Scholar]
- Cason, T.N.; Mui, V.L. A laboratory study of group polarisation in the team dictator game. Econ. J. 1997, 107, 1465–1483. [Google Scholar] [CrossRef]
- Luhan, W.J.; Kocher, M.G.; Sutter, M. Group polarization in the team dictator game reconsidered. Exp. Econ. 2009, 12, 26–41. [Google Scholar] [CrossRef]
- Gillet, J.; Schram, A.; Sonnemans, J. The tragedy of the commons revisited: The importance of group decision-making. J. Public Econ. 2009, 93, 785–797. [Google Scholar] [CrossRef]
- Cason, T.N.; Saijo, T.; Sjostrom, T.; Yamato, T. Secure implementation experiments: Do strategy-proof mechanisms really work? Games Econ. Behav. 2006, 572, 206–235. [Google Scholar] [CrossRef] [Green Version]
- Holt, C.A.; Laury, S.K. Risk aversion and incentive effects. Am. Econ. Rev. 2002, 925, 1644–1655. [Google Scholar] [CrossRef]
- Bohnet, I.; Frey, B. The sound of silence in prisoner’s dilemma and dictator games. J. Econ. Behav. Organ. 1999, 381, 43–57. [Google Scholar] [CrossRef]
- He, H.; Villeval, M.C. Are Teams Less Inequality Averse than Individuals? IZA Discussion Paper 2014, No. 8217; Institute of Labor Economics (IZA): Bonn, Germany, 2014. [Google Scholar]
- Fischbacher, U. z-Tree: Zurich toolbox for ready-made economic experiments. Exp. Econ. 2007, 102, 171–178. [Google Scholar] [CrossRef]
- Anderson, L.R.; Mellor, J.M. Predicting health behaviors with an experimental measure of risk preference. J. Health Econ. 2008, 275, 1260–1274. [Google Scholar] [CrossRef] [PubMed]
- Lusk, J.L.; Coble, K.H. Risk perceptions, risk preference, and acceptance of risky food. Am. J. Agric. Econ. 2005, 872, 393–405. [Google Scholar] [CrossRef]
- Harrison, G.W.; Lau, M.I.; Rutstrom, E.E. Estimating risk attitudes in Denmark: A field experiment. Scand. J. Econ. 2007, 1092, 341–368. [Google Scholar] [CrossRef]
- Kamas, L.; Preston, A.; Baum, S. Altruism in individual and joint-giving decisions: What’s gender got to do with it? Fem. Econ. 2008, 14, 23–50. [Google Scholar] [CrossRef]
- Van Lange, P.A.; De Bruin, E.M.N.; Otten, W.; Joireman, J.A. Development of prosocial, individualistic, and competitive orientations: Theory and preliminary evidence. J. Pers. Soc. Psychol. 1997, 734, 733–746. [Google Scholar] [CrossRef]
- Van Lange, P.A.; Bekkers, R.; Shuyt, T.N.; Vugt, M.V. From games to giving: Social value orientation predicts donation to noble causes. Basic Appl. Soc. Psychol. 2007, 29, 375–384. [Google Scholar] [CrossRef]
- Au, W.T.; Kwong, Y.Y. Measurements and effects of social-value orientation in social dilemmas: A review. In Contemporary Research on Social Dilemmas; Suleiman, R., Budescu, D.V., Fischer, I., Messick, D.M., Eds.; Cambridge University Press: New York, NY, USA, 2004; pp. 71–98. [Google Scholar]
- Reynaud, A.; Couture, S. Stability of risk preference measures: Results from a field experiment on French farmers. Theory Decis. 2012, 732, 203–221. [Google Scholar] [CrossRef] [Green Version]
- Ambrus, A.; Greiner, B.; Pathak, P.A. How individual preferences are aggregated in groups: An experimental study. J. Public Econ. 2015, 129, 1–13. [Google Scholar] [CrossRef]
Decision | Option A | Option B | Proportion of Subjects | ||||||
---|---|---|---|---|---|---|---|---|---|
Probability | Payoff | Probability | Payoff | Probability | Payoff | Probability | Payoff | ||
1 | 10% | ¥200 | 90% | ¥160 | 10% | ¥380 | 90% | ¥10 | 0.6 |
2 | 20% | ¥200 | 80% | ¥160 | 20% | ¥380 | 80% | ¥10 | 0.3 |
3 | 30% | ¥200 | 70% | ¥160 | 30% | ¥380 | 70% | ¥10 | 0.6 |
4 | 40% | ¥200 | 60% | ¥160 | 40% | ¥380 | 60% | ¥10 | 5.2 |
5 | 50% | ¥200 | 50% | ¥160 | 50% | ¥380 | 50% | ¥10 | 13.9 |
6 | 60% | ¥200 | 40% | ¥160 | 60% | ¥380 | 40% | ¥10 | 12.5 |
7 | 70% | ¥200 | 30% | ¥160 | 70% | ¥380 | 30% | ¥10 | 28.4 |
8 | 80% | ¥200 | 20% | ¥160 | 80% | ¥380 | 20% | ¥10 | 27.0 |
9 | 90% | ¥200 | 10% | ¥160 | 90% | ¥380 | 10% | ¥10 | 8.7 |
10 | 100% | ¥200 | 0% | ¥160 | 100% | ¥380 | 0% | ¥10 | 2.9 |
Variables | Definition |
---|---|
Investment | The amount of investment (Task 3), from 0 to 200 |
Donation | The amount of donation (Task 4), from 0 to 200 |
Risk preference | The level of “Risk preference” (Task 1) |
Contributions | The amount of contribution in the PGG (Task 2) |
Group dummy | Dummy variable for the subjects assigned to the group-choice tasks |
Prosocial | Dummy variable for the subjects defined as “Prosocial” in the SVO method |
Male | The gender dummy variable (1 if male, 0 otherwise) |
University | The university dummy variable (the baseline variable is Kansai University) |
Group-Choice Sub-Sample | Median Rule | Random Rule | MR—RR | ||
---|---|---|---|---|---|
Mean | Std. Dev. | Mean | Std. Dev. | p-Value | |
Investment | 101.74 | 67.41 | 84.65 | 56.50 | 0.12 |
Donation | 31.20 | 54.39 | 31.86 | 50.61 | 0.19 |
Risk preference | 0.44 | 0.41 | 0.51 | 0.60 | 0.30 |
Contributions | 63.91 | 74.83 | 47.56 | 59.98 | 0.36 |
Prosocial | 0.42 | 0.50 | 0.43 | 0.50 | 0.93 |
Male | 0.78 | 0.41 | 0.48 | 0.50 | 0.000 *** |
Individual-Choice Sub-Sample | Median Rule | Random Rule | MR—RR | ||
---|---|---|---|---|---|
Mean | Std. Dev. | Mean | Std. Dev. | p-Value | |
Investment | 116.24 | 62.45 | 111.53 | 68.11 | 0.64 |
Donation | 52.59 | 66.92 | 43.65 | 61.81 | 0.42 |
Risk preference | 0.52 | 0.53 | 0.53 | 0.50 | 0.89 |
Contributions | 67.29 | 69.03 | 58.59 | 64.87 | 0.50 |
Prosocial | 0.45 | 0.50 | 0.51 | 0.50 | 0.44 |
Male | 0.64 | 0.48 | 0.48 | 0.50 | 0.045 ** |
Investment | Model 1 | Marginal | Model 2 | Marginal |
---|---|---|---|---|
Effects | Effects | |||
Risk preference | −47.36 *** | −34.29 *** | −46.51 *** | −33.66 *** |
(10.92) | (7.60) | (10.76) | (7.49) | |
Group dummy | −28.38 ** | −20.32 ** | −27.74 ** | −19.87 ** |
(13.15) | (9.14) | (13.10) | (9.12) | |
Interaction term | −12.84 | −9.33 | −11.74 | −8.52 |
(group × random rule) | (18.74) | (13.61) | (18.57) | (13.48) |
Contributions | - | - | 0.16 ** | 0.11 ** |
- | - | (0.08) | (0.06) | |
Male | 28.36 *** | 20.82 *** | 27.70 *** | 20.32 *** |
(9.25) | (6.78) | (9.16) | (6.71) | |
Kochi University of Technology | −5.33 | −3.86 | −7.09 | −5.13 |
(14.80) | (10.68) | (14.61) | (10.53) | |
Kyoto Sangyo University | 7.82 | 5.68 | 7.09 | 5.15 |
(16.65) | (12.14) | (16.51) | (12.03) | |
Constant | 133.9 *** | - | 124.4 *** | - |
(12.29) | - | (12.98) | - | |
Observations | 348 | 348 | ||
Log pseudolikelihood | −1493.9 | −1491.4 |
Donation | Model 1 | Marginal | Model 2 | Marginal |
---|---|---|---|---|
Effects | Effects | |||
Contributions | 0.32 *** | 0.15 *** | 0.32 *** | 0.15 *** |
(0.10) | (0.05) | (0.10) | (0.05) | |
Group dummy | −43.28 ** | −23.78 ** | −42.46 ** | −23.27 ** |
(17.68) | (10.59) | (17.66) | (10.55) | |
Interaction term | 34.70 | 15.82 | 34.20 | 15.60 |
(group × random rule) | (23.64) | (10.07) | (23.50) | (10.02) |
Prosocial | 45.92 *** | 19.32 *** | 45.70 *** | 19.22 *** |
(12.33) | (4.30) | (12.38) | (4.33) | |
Risk preference | - | - | 8.55 | 4.14 |
- | - | (12.24) | (5.92) | |
Male | −23.83 * | −12.54 * | −22.98 * | −12.04 * |
(12.16) | (6.82) | (12.31) | (6.87) | |
Kochi University of Technology | 23.06 | 10.77 | 22.96 | 10.72 |
(19.22) | (8.68) | (19.24) | (8.68) | |
Kyoto Sangyo University | 13.49 | 6.38 | 13.37 | 6.32 |
(18.69) | (8.62) | (18.67) | (8.61) | |
Constant | −15.98 | - | −21.20 | - |
(14.65) | - | (17.13) | - | |
Observations | 348 | 348 | ||
Log pseudolikelihood | −1139.5 | −1139.2 |
Group-Choice Sub-Sample | Model 1 | Marginal | Model 2 | Marginal | Model 3 | Marginal |
---|---|---|---|---|---|---|
Investment | Effects | Donation | Effects | Donation | Effects | |
Risk preference | −88.19 *** | −66.76 *** | - | - | −19.73 | −8.96 |
(21.85) | (15.57) | - | - | (27.24) | (12.35) | |
Interaction term | 57.88 ** | 40.50 ** | - | - | 35.22 | 14.86 |
(random rule × risk preference) | (25.10) | (15.63) | - | - | (32.24) | (12.58) |
Random rule | −40.68 ** | −30.66 ** | 30.19 | 12.01 | −2.67 | −1.23 |
(16.77) | (11.94) | (22.22) | (7.55) | (21.49) | (9.97) | |
Contributions | - | - | 0.28 | 0.12 | 0.15 | 0.07 |
- | - | (0.19) | (0.08) | (0.13) | (0.06) | |
Interaction term | - | - | −0.29 | −0.13 | - | - |
(random rule × contributions) | - | - | (0.25) | (0.12) | - | - |
Prosocial | - | - | 43.14 *** | 16.56 *** | 42.33 *** | 16.35 *** |
- | - | (15.89) | (5.05) | (15.76) | (5.04) | |
Male | 25.04 ** | 18.83 ** | −16.13 | −7.90 | −15.90 | −7.81 |
(11.21) | (8.32) | (15.89) | (8.35) | (15.99) | (8.42) | |
Constant | 126.6 *** | - | −39.13 * | - | −21.59 | - |
(14.65) | - | (23.41) | - | (23.33) | - | |
Observations | 178 | 178 | 178 | |||
Log pseudolikelihood | −780.1 | −549.2 | −549.4 |
Individual-Choice Sub-Sample | Model 1 | Marginal | Model 2 | Marginal | Model 3 | Marginal |
---|---|---|---|---|---|---|
Investment | Effects | Donation | Effects | Donation | Effects | |
Risk preference | −64.18 *** | −44.37 *** | - | - | −1.42 | −0.72 |
(24.16) | (16.07) | - | - | (28.52) | (14.55) | |
Interaction term | 41.05 | 28.18 | - | - | 21.39 | 10.59 |
(random rule × risk preference) | (36.61) | (24.58) | - | - | (39.29) | (18.75) |
Random rule | −22.22 | −14.90 | −29.55 | −16.10 | −30.83 | −16.83 |
(24.56) | (15.79) | (24.23) | (13.88) | (29.92) | (17.21) | |
Contributions | - | - | 0.42 ** | 0.21 ** | 0.49 *** | 0.25 *** |
- | - | (0.20) | (0.10) | (0.16) | (0.08) | |
Interaction term | - | - | 0.16 | 0.08 | - | - |
(random rule × contributions) | - | - | (0.30) | (0.15) | - | - |
Prosocial | - | - | 47.73 ** | 21.70 *** | 49.74 ** | 22.42 *** |
- | - | (19.73) | (7.56) | (19.85) | (7.45) | |
Male | 34.57 ** | 24.82 ** | −35.53 * | −19.74 * | −34.20 * | −18.92 * |
(14.61) | (10.64) | (18.16) | (10.63) | (18.44) | (10.73) | |
Constant | 141.2 *** | - | 0.21 | - | −6.04 | - |
(18.77) | - | (20.58) | - | (23.95) | - | |
Observations | 170 | 170 | 170 | |||
Log pseudolikelihood | −709.9 | −587.4 | −587.3 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Kamijo, Y.; Tamura, T. Risk-Averse and Self-Interested Shifts in Groups in Both Median and Random Rules. Games 2023, 14, 16. https://doi.org/10.3390/g14010016
Kamijo Y, Tamura T. Risk-Averse and Self-Interested Shifts in Groups in Both Median and Random Rules. Games. 2023; 14(1):16. https://doi.org/10.3390/g14010016
Chicago/Turabian StyleKamijo, Yoshio, and Teruyuki Tamura. 2023. "Risk-Averse and Self-Interested Shifts in Groups in Both Median and Random Rules" Games 14, no. 1: 16. https://doi.org/10.3390/g14010016