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Inequality as a barrier to economic integration? An experiment

Experimental Economics volume 26, pages 383–411 (2023)Cite this article

Abstract

International economic theory suggests that people should embrace economic integration because it promises large gains. But policy reversals such as Brexit indicate a desire for economic disintegration. Here we report results of an experiment of how size and cross-country distribution of gains from integration influence individuals’ inclination to cooperate to reap its intended benefits and to embrace or reject integration. The design considers an indefinitely repeated helping game with multiple equilibria and strategic uncertainty. The data reveal that inequality of potential gains neither affected behavior nor reduced support for economic integration. However, integration may lead to disappointing, unequally distributed welfare gains, undermining support for the policy. This suggests that to better assess integration policies, we should account for the spillover effects of integration on behavior. Miscalculating this behavioral aspect may undermine the intended development goals and motivate calls for dramatic policy-reversals.

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Notes

  1. Brexit may cost up to 10 percent of UK per capita GDP (Sampson, 2017) and Chakraborty et al. (2017) estimate the cost of financial disintegration in Europe at half percent of GDP.

  2. These considerations seem also relevant for smaller-scale integration phenomena. Universities often confront the problem of reorganizing separate (and differently compensated) units by merging them into a larger one, which may lack cohesiveness and perform poorly. Or, consider vertical mergers, when the contribution to value-creation of each firm is heterogeneous, and corporate settings where personnel from different units work in teams.

  3. Our group formation rule randomly lets one subset of players (one type) select group configuration. Initial random assignment to types implies that if participants have heterogeneous inclinations towards cooperation, then neither choosing “isolation” nor “integration” allows self-selection into a cooperative coalition. As we are interested in economic integration, this ensures that, if we think of the three types as countries, individuals cannot leave their country, or create a new entity comprising arbitrary regions from different countries. Countries can only aggregate into a bigger economic entity, or choose the status quo.

  4. This means that in all treatments and all groups a strategy always exists that, if adopted by the entire group, can support the efficient outcome as an equilibrium. According to this strategy, which is discussed in Sect. 4, a player should fully cooperate in equilibrium, and should choose to form mixed groups if given the chance.

  5. In the experiment types are color-coded (green, red, and blue). A related experiment uses neutral data (Phase 1, only) to study if the assignment to types artificially induces group-identity that constitutes a psychological basis for intergroup discrimination (see Camera & Hoh,l 2021, footnote 9). No evidence of group effects from the initial categorization into color-coded types is detected.

  6. This is unlike most cooperation experiments, which use a synchronous cooperation task (e.g., a PD). Our task is asynchronous—a repeated helping game with alternating decision-makers who experience a time delay between cost of and benefit from cooperation. This creates a sharper distinction between isolated and integrated economies as it removes strategic uncertainty in fixed pairs (see the discussion in Bigoni et al., 2019). It also emphasizes the intertemporal nature of cooperation, thus capturing the spirit of the dynamic macroeconomics and trade literature, where the benefits of trade derive from an intertemporal exchange of goods and services.

  7. This information is anonymized, see the results screen in the instructions in Appendix B, column “Same Outcome In All Pairs.” We provided it to ensure that the economy size did not affect the condition for existence of the efficient equilibrium—as discussed in Sect. 4.

  8. Suppose type 1 players are selected to determine the economy configuration. If their majority chose to exclude type 3, we form a mixed group with types 1 and 2, and four fixed pairs of type 3. If the majority chose to leave, we form a mixed group with types 2 and 3, and four fixed pairs of type 1. The computer resolves ties via a coin flip. The instructions explain that participants would have an opportunity to alter size and composition of the economy in supergame 5, in a manner specified at the end of supergame 4. Given the default assignment to a single mixed group consisting of all 24 session participants, a “leave” choice can be interpreted choosing economic disintegration.

  9. Counting all choices in the session would have been also problematic for two reasons. It would have precluded the possibility of “leaving” ever being the majority choice, and it would have increased the complexity of determining an outcome (e.g., type 1 wants to exclude 2, type 2 wants to exclude 3, and 3 wants to exclude 1).

  10. Avoiding integration reduces potential surplus, while conditioning cooperation on (own) type lowers the player’s payoff in equilibrium because uncooperative actions trigger defections; off equilibrium, unconditional defection is a best response to others defecting. Hence, players who are income-maximizing or who seek to maximize efficiency have no economic reason to coordinate on less than full cooperation and to avoid integration.

  11. For session-level analysis we have 8 independent observations per treatment, used to perform statistical tests. For economy-level analysis we have 192 observations for fixed pairs and 32 observations for mixed groups, in Phase 1, per treatment. Here, the only truly independent observations are from supergame 1 (2 for mixed groups and 12 for fixed pairs) while the others may be correlated within a session; overall, in Phase 1 of each session we have 4 (not independent) mixed groups and 24 (not independent) fixed pairs. These possible correlations are mitigated by our strangers matching protocol, but are not entirely eliminated. We address possible interdependencies by means of regression analysis with cluster-robust standard errors, with clustering at the session level. Similar considerations apply to subject-level analysis, where we have 192 observations per treatment.

  12. In Phase 1, round 1 cooperation rates are 0.46, 0.60, 0.44 and 0.55, for neutral, Converge, Diverge and neutral+. Using two-sided Wilcoxon rank-sum tests, we can only reject the hypothesis that round 1 cooperation rates are similar in Converge vs. Diverge (p value = 0.0995, \(N1=N2=8\)). Using a logit panel regression, we cannot reject the null of identical round 1 cooperation rates for any treatment comparison; see Appendix B.

  13. We thank an anonymous Referee for suggesting this additional analysis.

  14. In all treatments, there are also winners and losers within the same player type. If we interpret a type as a country, then this observation would seem consistent with international trade theories. Yet, these differences within a type are due to unequal cooperation rates, with frequent cooperators being “losers” and frequent defectors “winners.”

  15. Using a session as an independent observation, we can reject the null hypothesis of equality of frequencies of “leave” and “stay,” against the alternative that “leave” is more frequent in Converge, neutral, and Diverge (one-sided signtest, p values = 0.0352, 0.0078, 0.0039, \(N1=N2=8\)) but not in neutral+ (p value = 0.6367). We can reject the null of equality of frequencies of “leave” and “exclude,” against the alternative that “leave” is more frequent for neutral and Converge (p values = 0.0352 in each case) but not Diverge and neutral+ (p values = 0.6563, 0.9648). We reject the null of equal frequencies for “exclude” and “stay,” against the alternative that “exclude” is more frequent in neutral and Diverge (p values = 0.0625, 0.0156) but not in Converge and neutral+ (p values = 0.5000, 0.1445).

  16. Using two-sided Wilcoxon-Mann Whitney ranksum test with exact statistics we cannot reject the null of equal frequency of “leave” choices in any of the first three treatments, at the 10% level. We can reject that the difference between “exclude” and “stay” frequencies is equal in Diverge and Converge (p value=0.0959, \(N1=N2=8\)). We can reject the null of identical “leave” choices in neutral and neutral+, but not “stay” (p values = 0.047,0.165).

  17. Participants’ realized gains depend on their relative cooperativeness, with cooperators being more likely to have losses from integration and free-riders gains. The reason is that cooperators are more easily exploited by free riders in mixed groups (vs. fixed pairs) because strangers’ interaction prevents identification and directly sanctioning of free riders. This issue is studied in Bigoni et al. (2019, pp. 210–211), which provides evidence on this point and reveals that—as self-selection is ruled out—free riders more frequently select large groups, while cooperators fixed pairs.

  18. We can reject the null that cooperative participants have a higher propensity to choose the socially efficient 24-player group. We categorize subjects into three groups (low, moderate, high) based on cooperation relative to their opponent(s), for fixed pairs and mixed groups of Phase 1. This categorical variable is used in a regression model as in Table 4, but omitting realized gains. Relative cooperativeness in fixed pairs does not affect group choices. Instead, Low cooperators in mixed groups are significantly more likely to choose the socially efficient “stay” choice, while high cooperators are significantly less likely to do so. This evidence is consistent with the results in Bigoni et al. (2019), suggesting that high cooperators avoid mixed groups to coordinate on cooperation with a fixed partner, while low cooperators seek large groups where free-riding cannot be directly sanctioned.

  19. Middle players behave similarly to Disadvantaged. They fall in-between Advantaged and Disadvantaged. We can only reject the null of equal coefficients on Middle and Advantaged for the “exclude” choice in Panel C (Wald test, p value = 0.0139). Table B12 in Appendix B reports the distribution of choices by type.

  20. We thank an anonymous referee for suggesting this line of inquiry.

  21. Fetzer (2019) notes that the austerity-induced welfare reform in the UK may have created losses that partly made economic integration seem responsible for their fate. Fetzer and Wang (2020) offer a measure of the economic cost of Brexit, in the very short-run. They find sizable and unevenly distributed costs across the 382 U.K districts, and classify about 168 districts as losers, 78 as winners, and the remaining as neither. Interestingly, they also find more pronounced losses in districts that more strongly supported Leave.

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Acknowledgements

The authors acknowledge partial research support through the SNSF Grant No. 100018.172901; G. Camera acknowledges partial research support through an IFREE Small Grant.

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Authors and Affiliations

  1. Economic Science Institute, Chapman University, One University Dr., Orange, CA, 92866, USA

    Gabriele Camera

  2. Faculty of Business and Economics, University of Basel, Peter Merian-Weg 6, 4002, Basel, Switzerland

    Lukas Hohl

  3. Faculty of Business and Economics, University of Basel, Peter Merian-Weg 6, 4002, Basel, Switzerland

    Rolf Weder

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  1. Gabriele Camera
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  2. Lukas Hohl
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Correspondence to Gabriele Camera.

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The authors thank Editors L. Gangadharan and J. Duffy, two anonymous reviewers for many helpful comments, N. Schmitt, the ESI lab manager and seminar participants at: CSU Fullerton, Universities of Basel, Hamburg, Miami, USC, UC Santa Barbara, Canadian Economics Association 2019 meetings, World Bank ABCDE 2019 conference, 2019 GSE Summer Forum (Pompeu Fabra), 2019 SSES Conference (Geneva), 2018 and 2019 ESA meetings (Berlin, Los Angeles). The replication material for the study is available at https://doi.org/10.7910/DVN/FNRYHO. The authors acknowledge partial research support through the SNSF Grant No. 100018.172901.

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Camera, G., Hohl, L. & Weder, R. Inequality as a barrier to economic integration? An experiment. Exp Econ 26, 383–411 (2023). https://doi.org/10.1007/s10683-022-09777-4

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Keywords

  • Economic opportunity
  • Endogenous institutions
  • Globalization
  • Indefinitely repeated games
  • Social dilemmas

JEL Classification

  • C70
  • C90
  • F02