Market institutions and the evolution of culture

Abstract

We find experimental evidence suggesting that market institutions are capable of developing their own cultures by influencing generalized and individualized trust. We employ two different markets in this study: the first market fully and automatically enforces all agreed-upon contracts; and the second market offers no such enforcement and allows subjects to defect on previously agreed-upon contracts. We find that a type of culture where people treat one another more or less equally and indiscriminately emerges with the first market, while a culture where people differentiate between the trustworthy and the untrustworthy emerges with the second market. While generalized trust remains the same across both treatments, individualized trust was only important in the treatment where contracts were not enforced in the experimental market. In the treatment where the market offered no enforcement, subjects exhibited less trust towards those with whom they had developed negative relationships and reciprocated at higher levels to those with whom that had developed positive relationships.

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Notes

  1. 1.

    Several empirical studies have used trust as a proxy for culture (e.g., Knack and Keefer 1997; Tabellini 2010).

  2. 2.

    See Alesina and Giuliano (2015) for a comprehensive overview of the empirical research in economics that concludes culture matters for economic outcomes.

  3. 3.

    While we specifically focus on market institutions here, Ockenfels and Weimann (1999) more broadly addresses formal institutions. Their study speaks to how the types of institutions to which individuals are exposed can influence their social and cultural norms, which in turn inform their economic decisions. They attribute apparent cultural differences between eastern and western Germans to their exposure to socialism or capitalism during the Cold War. “After the end of the cold war, we can now examine cultural differences, namely differences in the cooperation and solidarity behavior of subjects living in former East and former West Germany. Eastern subjects grew up in a socialist planned economy, while western subjects have been socialized in a market-oriented environment” (Ockenfels and Weimann 1999, 276).

  4. 4.

    There was one Market ZE session with twelve subjects. In this session, the market consisted of six buyers and six sellers. Comparisons showed the Market ZE session with twelve subjects to be no different from those with eight subjects (analysis not included in this study).

  5. 5.

    Coincidentally, no two buyers received the same value within the same round.

  6. 6.

    For clarification, the computer displayed no information about executed contracts in past trading rounds. We employed record sheets to allow subjects to carry their own market histories, which we further discuss in Sect. 3.4.

  7. 7.

    This is the original, unmodified trust game as implemented by Berg, Dickhaut and McCabe (1995).

  8. 8.

    In an ideal laboratory economic experiment, any systematic difference(s) observed between treatments (i.e., the main/treatment effect) is a direct result of a change(s) in the decision environment operationalized through the experimental design itself. In such cases, the experimenter is able to then speak about her hypothesis by linking the main design manipulation to the observed effect. The worst-case scenario for such an experiment would be one where the main effect is, instead, a direct result of a fundamental difference across treatments at the subject-level (and not of the main design manipulation). To mitigate the possibility of the worst-case scenario, experimentalists have designed and adopted a best-faith recruiting method where participants for an experiment are randomly selected from the same subject pool. While not a guarantee, this random sampling method assuages experimenters that (1) a representative sample was chosen for each of the various treatments and (2) any biases specific to this subject pool would then be minimized as an issue for their results. Since we adopted this standard recruiting method, we are confident that we had comparable samples in Markets ZE and FE treatments. Note that this is not necessarily true of all experimental studies in economics; some studies do want to examine how different groups of people (e.g., members of different cultures, countries, age groups, or the different sexes) behave in the same decision environment. In those experimental studies, any systematic difference(s) observed at the treatment-level would be attributed to how these groups are fundamentally different.

  9. 9.

    One subject opted to not fully complete the survey and another chose not to complete the risk attitude measure. The graduate students were not working on an economics degree and were previously not acquainted with either of the authors.

  10. 10.

    In the experimental economics literature, there are studies that speak to how first impressions can matter for economic decisions. For instance, Eckel and Petrie (2011) and Centorrino et al. (2015) find that appearances matter for trust games. Castillo and Petrie (2010) report that subjects utilize race to predict economic behavior when payoff relevant information is absent. To the best of our knowledge, there is no experimental literature that directly addresses last impressions; last impressions, as defined here, differ from last round (or end-of-game) effects because our subjects interact with each other again after the last trading round. The closest analogy may be the restart effect. Andreoni (1988), for example, finds that restarting a public goods game has a disparate effect on stranger- and partner-plays.

  11. 11.

    This is, of course, not to say that objective facts about what happened do not matter; it is simply that our primary interest in this study was our subject’s perceptions.

  12. 12.

    Several subjects misreported their trading partner’s identities onto the market record sheets, thus affecting the total number of positive and negative interactions they had with a particular trading partner. Because this paper seeks to understand how a subject’s perception about a trading partner and their shared relationship affects the trust and reciprocity he exhibits to the said trading partner, we do not view the subject errors to be an issue. It should be noted, however, that the significance of our results (Sect. 5) becomes even stronger if we use z-Tree records instead of subject-reported records (analysis not included in this study).

  13. 13.

    The Market ZE session with twelve subjects generates a total of 36 possible buyer–seller relationships.

  14. 14.

    We rationalize that enjoying a positive relationship with a person, for example, does not preclude us from enjoying a positive relationship with another person. Furthermore, looking at just those buyer–seller pairs who interacted at least once on the market, the median number of interactions per trading partner is 2 with the midspread occurring between 1 and 3 for both Markets FE and ZE. Hence, choosing to interact with a specific trading partner in a trading round does not seem to have cost the other three potential trading partners the opportunity to interact and form relationships with the subject.

  15. 15.

    For this analysis, we exclude any subject who reported that they held dual (or more) citizenships or that they belonged to more than one race.

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Acknowledgements

This paper has been presented at BEEMA Conference (2015), North American Economic Science Association (2016) and Southern Economic Association (2016) as “Learning Whom to Trust.” We thank the participants of these conferences and our other colleagues at ICES, The Mercatus Center and Saint Vincent College for helpful comments and suggestions. This work was funded by The Mercatus Center at George Mason University.

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Correspondence to Ginny Seung Choi.

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Choi, G., Storr, V.H. Market institutions and the evolution of culture. Evolut Inst Econ Rev 15, 243–265 (2018). https://doi.org/10.1007/s40844-018-0103-z

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Keywords

  • Culture
  • Trust
  • Markets

JEL Classification

  • Z10
  • B52
  • P10