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The Rise of Merit-based Inequality Acceptance After Exposure to Competition: Experimental Evidence among Chinese University Students

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Abstract

This laboratory study examines an individual’s acceptance of distributional inequality after exposure to competition and the role of competitive intensity in this relationship among young adults in mainland China. We randomly assigned participants to tournaments with different levels of prize spread and winning selectivity, thereby engendering different levels of competitive intensity. Moreover, the lab experiment measured the participants’ preference for inequality in the distribution of tournament awards–what we call merit-based inequality acceptance. We obtained three main results. (1) Exposure to competition increases the level of inequality acceptance, and the effect of such increase tends to be great among strong performers in a tournament. (2) Exposure to competition with large prizes is positively associated with high level of inequality acceptance, whereas the relationship of winning selectivity to inequality acceptance has an inverted U shape. (3) The main source of inequality acceptance is the difference in the payoffs to strong and poor performers in a tournament. Results suggest that increasing competition intensity for economic rewards may have the unintended consequence of enhancing merit-based inequality acceptance among young Chinese university students.

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Notes

  1. For instance, three salient fairness are summarized (Almås et al. 2010) as strict egalitarianism (Rawls 1971)—finding all inequalities unfair, meritocratism (Arrow et al. 2000)—justifying inequalities reflecting differences in talents and production, and libertarianism (Nozick 1974)—justifying all inequalities in earnings even if the disparities are outcomes of luck or any uncontrolled reason.

  2. Inequality acceptance refers to an acceptance towards inequality based on talents, efforts and merits in this case and hereafter.

  3. A total of 352 Chinese young adults participated in the experiment, of which 342 were left when 10 failed cases were excluded. In one session, eight participants encountered a connection problem during the experiment. Two additional participants failed to understand the experimental procedures.

  4. This following payment structure (35, 35, 15, 15) is used for brevity.

  5. Participants were unaware of the other group’s decisions until the end of the experiment, which was designed to avoid reciprocity effect.

  6. For each participant, the reward for the other group was proportional to the average of the distributive decisions by four participants in another group. Thus, all decisions were considered.

  7. The distributive plan failed to change the payment of the decision-maker.

  8. This selection ensures that payment structure will not distort our results.

  9. Since the sample size for low- and high-inequality groups is the same, we weight the mean to reflect a balanced sample size for low- and high-competition groups.

  10. If we include four competition treatments in the analysis, the results remain robust. The difference on distributional inequality acceptance is significant between competition and inequality (t(298) = 3.52, p = 0.001), and competition and control (t(276) = 2.86, p = 0.005).

  11. We rescale the variance of the implicit latent outcome variable to 1.

  12. Mean score is 77.46, and standard deviation is 18.62. The score difference is insignificant (p > 0.15) across experimental groups.

  13. The difference between control group and Treatment II LPHS (40, 20, 20, 20) is insignificant (F = 0.28, p > 0.15 in the ANOVA test).

  14. We append an additional check to exclude those majoring in economics and rerun the regression. The main findings remain unchanged; thus, those participants do not alter our results.

  15. When prize is added as a continuous variable, the values for high prize, low prize, and control group are 40, 20, and 0, respectively. The values for low selectivity, high selectivity, and control are 0.5, 0.25, and 1, respectively (See Table 2).

  16. We initially use a continuous prize in Model 3 and Table 4 and discover that the relationship between continuous prize and the odds of accepting larger inequality in a subsequent distribution is at a significance level of 0.001.

  17. We only account for prize levels in two inequality groups given that we tested prize rather than selectivity in a competition as the major determinant of inequality acceptance in the previous discussion.

  18. The coefficient for prize under competition situation is significant (at a level of 0.05), while this coefficient for inequality situation is not.

  19. We control two variables in regression, and neither of the variables significantly affect inequality acceptance (p value > 0.15).

  20. The problem of generalizability should not prevent social science researchers from acquiring knowledge through lab experiments (Falk and Heckman 2009).

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Acknowledgements

The authors gratefully acknowledge funding support from the CUHK-CASS Joint Lab on Social Psychology, sponsored by CUHK Research Committee via the Faculty of Social Science Chinese University of Hong Kong, Guangzhou Association of Social Science “Social mentality research in new era: merit-based distribution and sense of acquisition” (No2018GZQN21) and MOE “Trend and Pattern of Chinese Social Mobility: Ethnic minorities’ educational and occupational attainments” (No. 16YJC880104).

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Correspondence to Jacqueline Chen Chen.

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Appendix

Appendix

See Tables 5 and 6.

Table 5 Ordered logit regression of inequality acceptance by male
Table 6 Ordered logit regression of inequality acceptance by female

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Chen, J.C., Tam, T. & Chiang, Ys. The Rise of Merit-based Inequality Acceptance After Exposure to Competition: Experimental Evidence among Chinese University Students. Soc Indic Res 144, 707–728 (2019). https://doi.org/10.1007/s11205-018-2011-3

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