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On the interpretation of bribery in a laboratory corruption game: moral frames and social norms


Past studies on laboratory corruption games have not been able to find consistent evidence that subjects make “immoral” decisions. A possible reason, and also a critique of laboratory corruption games, is that the experiment may fail to trigger the intended immorality frame in the minds of the participants, leading many to question the very raison d’être of laboratory corruption games. To test this idea, we compare behavior in a harassment bribery game with a strategically identical but neutrally framed ultimatum game. The results show that fewer people, both as briber and bribee, engage in corruption in the bribery frame than in the alternative and the average bribe amount is lesser in the former than in the latter. These suggest that moral costs are indeed at work. A third treatment, which relabels the bribery game in neutral language, indicates that the observed treatment effect arises not from the neutral language of the ultimatum game but from a change in the sense of entitlement between the bribery and ultimatum game frames. To provide further support that the bribery game does measure moral costs, we elicit the shared perceptions of appropriateness of the actions or social norm, under the two frames. We show that the social norm governing the bribery game frame and ultimatum game frame are indeed different and that the perceived sense of social appropriateness plays a crucial role in determining the actual behavior in the two frames. Furthermore, merely relabelling the bribery game in neutral language makes no difference to the social appropriateness norm governing it. This indicates that, just as in the case of actual behavior, the observed difference in social appropriateness norm between bribery game and ultimatum game comes from the difference in entitlement too. Finally, we comment on the external validity of behavior in lab corruption games.

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  1. 1.

    For instance, Camerer (Forthcoming) in his reply to Levitt and List (2007) shows that the overwhelming majority of lab experiments do indeed generalize to comparable field settings. Kessler and Vesterlund (2014) emphasize that it is the qualitative effect (i.e. direction of effect), as opposed to the quantitative effect (i.e. precise size of the effect), which is more generalizable.

  2. 2.

    Levitt and List (2007) warn us that lab experiments may not reveal so much when it comes to identifying deep structural parameters. Then one needs to take recourse to field experiments despite the fact that it is often prohibitively expensive as List (2012) found out with a $103,000 field experiment on corruption.

  3. 3.

    Two distinct questions emerge from this: One, do people operate under different moral environment in the two frames and if not, is this why one does not observe framing effects? Two, what is the appropriate counterfactual of a corruption experiment that may potentially yield evidence of moral cost at work? Abbink and Hennig-Schmidt (2006) speculate that neutral frames are insufficient to induce an alternative behavioral norm.

  4. 4.

    We follow Fehr and Fischbacher (2004) to define social norm for our purpose: “The standards of behavior that are based on widely shared beliefs how individual group members ought to behave in a given situation”. There have been various other definition of social norms in the literature: Pareto noted that “…people have opinions about how they should or should not behave. They also have opinions about how others should or should not behave.” Ostrom (2000) further emphasized on the mutually shared aspect of social norms and defined it as “…shared understandings about actions that are obligatory, permitted or forbidden”.

  5. 5.

    Harassment bribery is a form of bribery where a public official asks for bribe from a citizen who is entitled to a service that the official is obligated to provide. This form of bribery is very common in developing countries where citizens are entitled to government services but either they have to pay a bribe in order to obtain them or avoid inordinate procedural delays. Such services include issuance of a passport or a driver’s license (given that the candidate has passed the driving test).

  6. 6.

    Though here we mainly discuss the experimental literature, several theoretical explanations have been advanced about why people may conform to social norms. While Banerjee (1992) explained preponderance of adherence to social norms in terms of informational advantage of others, Fehr and Fischbacher (2004) and Bernheim (1994) explained the conformity to social norms in terms of fear of sanction in case of violation and desire to gain social esteem, respectively.

  7. 7.

    Though Reuben and Riedl (2013) acknowledge that this tool is clearly a superior method of eliciting normative views than those based on questionnaires, only a handful of studies (for example Gächter et al. (2013)) have used this.

  8. 8.

    The lack of framing effects has also been found in dictator games (Dreber et al. 2013).

  9. 9.

    Barr and Serra (2009) does find that the share of public servants who refuse to take a bribe is consistently higher in the corruption frame than in the abstract frame but the differences are not significant.

  10. 10.

    Abbink et al. (2014) implements a version of harassment bribery game but it was not known to the author when this experiment was conceived.

  11. 11.

    There is a fourth possibility of a complete \(2 \times 2 \) design—one where the ultimatum game treatment is framed in terms of loaded language but passing the test only qualifies one to the next stage of the game. Since a citizen does not deserve a prize, the question of bribe becomes irrelevant. One can however introduce an ultimatum game at the second stage with a neutral word for bribe such as transfer. With a mix of loaded terms (citizen, public official) and neutral terms (transfer instead of bribe), it is not clear what the treatment will measure.

  12. 12.

    A version of the matrix or box task, introduced by Mazar and Ariely (2006), was used. In the task subjects had fifteen minutes to find two numbers in a 3 by 3 matrix which added up to 10. For example a matrix may have 4.55 and 5.45 which adds up to 10. There were twenty such matrices. The task was specifically chosen to ensure that subjects knew how many they had solved correctly. Thus, they knew whether they had won the prize and any demand for a bribe might have been considered unfair.

  13. 13.

    Notice that letting citizens pay a bribe when they have failed the test is bribery for sure but does not amount to harassment bribery. The ultimatum game parallel applies only for the latter and thus, we were specially interested in it—hence the calibration. In this treatment 95 % of the participants scored at least 10.

  14. 14.

    Calibration of the task ensured that 92.5 % of the subjects qualified for the next round.

  15. 15.

    A referee rightly points out that the UG frame not just eliminates the moral cost of indulging in corruption but replaces it with the moral cost associated with ultimatum games. It is governed by its own moral frame driven by a set of non-monetary motivations which are distinctly different from the one in the BG frame.

  16. 16.

    I thank two anonymous referees for suggesting this treatment.

  17. 17.

    The information that an envelope filled with money is placed underneath the desk is revealed only at the end when they are about to receive their earnings. So, this does not have any impact on the earlier behavior.

  18. 18.

    One referee points out that this in the true sense is not equivalent to observing the subjects in the field. Though they were not observed by the experimenter, they were still in a lab. We acknowledge that this is not the best design to capture external validity of unethical behavior and perhaps that is why the results are, at best, weak. However, subjects felt unobserved and it was not obvious to them that the remaining number of notes in the unmarked envelope would be matched back to their responses.

  19. 19.

    Mohar or gold coin was a precious unit of exchange used in medieval India, an etymological history of which can be traced back to the persian word mohr, meaning seal.

  20. 20.

    While both the situations in BG and UG are governed by injunctive norms, i.e. what one should or should not do, the nature injunction that works for the two frames are very different.

  21. 21.

    Figure 5 and Table 4 in Appendix 1 lays out the categories.

  22. 22.

    Presumably because the P-B realized that he could increase his own earnings by letting the P-A pass.

  23. 23.

    If zeroes were included then the average bribe demanded in BG was M163 while that in BG-N was M179 (\(MW\)-test, \(p\) value = 0.76)

  24. 24.

    Lack of sufficient number of observations make mean comparison test redundant.

  25. 25.

    We thank an anonymous referee for suggesting this specification.

  26. 26.

    Though the Participant Bs in UG had the opportunity to steal, it is not clear how to interpret the correlation between ultim demand and stealing. Hence we don’t report it.

  27. 27.

    Direct stealing of cash and deliberately failing to return excess money are two alternative ways in which unethical behavior can be examined on the field however one may note that these two methods appeal to different degrees of unethicality. Our conjecture is that the latter will result in fewer observations in the false-positive domain. Also note that none of our other results hold when stealing is used as the dependent variable.

  28. 28.

    This regression is done with only 20 observations—however, that the standard assumptions of ordinary least square regressions still hold is evident from the diagnostics of Fig. 5 included in the Appendix 2. The result of an outlier test based on inter-quartile range shows the presence of only one outlier. Re-estimating this specification by excluding the outlier does not lead to any significant difference.

  29. 29.

    Qualitative interactions after the BG-N treatment revealed that the subjects thought it was Participant A’s prize and it was unfair for Particpant B to take away a share of her prize.


  1. Abbink, K., & Hennig-Schmidt, H. (2006). Neutral versus loaded instructions in a bribery experiment. Experimental Economics, 9(2), 103–121.

    Article  Google Scholar 

  2. Abbink, K., Irlenbusch, B., & Renner, E. (2002). An experimental bribery game. Journal of Law, Economics and Organization, 18(2), 428–454.

    Article  Google Scholar 

  3. Abbink, K., Dasgupta, U., Gangadharan, L., & Jain, T. (2014). Letting the briber go free: An experiment on mitigating harassment bribes. Journal of Public Economics, 111(C), 17–28.

    Article  Google Scholar 

  4. Alatas, V., Cameron, L., Chaudhuri, A., Erkal, N., & Gangadharan, L. (2009). Subject pool effects in a corruption experiment: A comparison of Indonesian public servants and Indonesian students. Experimental Economics, 12(1), 113–132.

    Article  Google Scholar 

  5. Armantier, O., & Boly, A. (2013). Comparing corruption in the laboratory and in the field in Burkina Faso and in Canada. The Economic Journal, 123, 1168–1187.

    Article  Google Scholar 

  6. Banerjee, A. V. (1992). A simple model of herd behavior. The Quarterly Journal of Economics, 107(3), 797–817.

    Article  Google Scholar 

  7. Banerjee, R, Baul, T., & Rosenblat, T. (2015). On self selection of the corrupt into the public sector. Economics Letters, 127, 43–46.

    Article  Google Scholar 

  8. Banuri, S., & Eckel, C. (2012). Experiments in culture and corruption: A review. In W. D. S. Leonard (Ed.), New advances in experimental research on corruption, research in experimental economics, chapter 3 (pp. 51–76). Bingley: Emerald Group Publishing Limited.

    Chapter  Google Scholar 

  9. Banuri, S., & Eckel, C. (2012). On the effects of culture on punishment of bribery: US versus Pakistan, CBEES Working Paper Series 11-05.

  10. Baran, N. M., Sapienza, P., & Zingales, L. (2010). Can we infer social preferences from the lab? Evidence from the trust game. NBER Working Papers 15654, National Bureau of Economic Research, Inc January 2010.

  11. Barr, A., & Serra, D. (2009). The effects of externalities and framing on bribery in a petty corruption experiment. Experimental Economics, 12(4), 488–503.

    Article  Google Scholar 

  12. Barr, A., & Serra, D. (2010). Corruption and culture: An experimental analysis. Journal of Public Economics, 94(11–12), 862–869.

    Article  Google Scholar 

  13. Bernheim, B. D. (1994). A theory of conformity. Journal of Political Economy, 102(5), 841–877.

    Article  Google Scholar 

  14. Bicchieri, C, & Xiao, E. (2009). Do the right thing—but only if others do so. Journal of Behavioral Decision Making, 22, 191–208.

    Article  Google Scholar 

  15. Bucciol, A., Landini, F., & Piovesan, M. (2013). Unethical behavior in the field: Demographic characteristics and beliefs of the cheater. Journal of Economic Behavior & Organization, 93(C), 248–257.

    Article  Google Scholar 

  16. Camerer, C. (2007). The promise of lab-field generalizability in experimental economics: A reply to levitt and list. In F. Guillaume & A. Schotter (Eds.), Methods of modern experimental economics. Oxford: Oxford University Press.

    Google Scholar 

  17. Cameron, L., Chaudhuri, A., Erkal, N., & Gangadharan, L. (2009). Propensities to engage in and punish corrupt behavior: Experimental evidence from Australia, India, Indonesia and Singapore. Journal of Public Economics, 93(7–8), 843–851.

    Article  Google Scholar 

  18. Cason, T. N., & Mui, V. -L. (1998). Social influence in the sequential dictator game. Journal of Mathematical Psychology, 42, 248–265.

    Article  Google Scholar 

  19. Cooper, D. J., Kagel, J. H., Lo, W., & Gu, Q. L. (1999). Gaming against managers in incentive systems: Experimental results with Chinese students and Chinese managers. The American Economic Review, 89(4), 781–804.

    Article  Google Scholar 

  20. Dreber, A., Ellingsen, T., Johannesson, M., & Rand, D. (2013). Do people care about social context? Framing effects in dictator games. Experimental Economics, 16(3), 349–371.

    Article  Google Scholar 

  21. Englmaier, F., & Gebhardt, G. (2011) Free-riding in the lab and in the field. Technical report 2011.

  22. Falk, A., & Heckman, J. J. (2009). Lab experiments are a major source of knowledge in the social sciences. Science, 326(5952), 535–538.

    Article  Google Scholar 

  23. Fehr, E., & Fischbacher, U. (2004). Social norms and human cooperation. Trends in Cognitive Sciences, 8(4), 185–190.

    Article  Google Scholar 

  24. Fisman, R., & Miguel, E. (2007). Corruption, norms, and legal enforcement: Evidence from diplomatic parking tickets. Journal of Political Economy, 115(6), 1020–1048.

    Article  Google Scholar 

  25. Franzen, A., & Pointner, S. (2013). The external validity of giving in the dictator game. Experimental Economics, 16(2), 155–169.

    Article  Google Scholar 

  26. Gächter, S., Nosenzo, D., & Sefton, M. (2013). Peer effects in pro-social behavior: Social norms or social preferences? Journal of the European Economic Association, 11(3), 548–573.

    Article  Google Scholar 

  27. Gneezy, U., Saccardo, S., & van Veldhuizen, R. (2013). Bribery: Greed versus reciprocity. UC San Diego Working Papers, UC San Diego June 2013.

  28. Hoffman, E., McCabe, K. A., & Smith, V. L. (1996). On expectations and the monetary stakes in ultimatum games. International Journal of Game Theory, 25(3), 289–301.

    Article  Google Scholar 

  29. Hoffman, E., McCabe, K., Shachat, K., & Smith, V. (1994). Preferences, property rights, and anonymity in bargaining games. Games and Economic Behavior, 7(3), 346–380.

    Article  Google Scholar 

  30. Robert, I., & Arnab, M. (2013). Is dishonesty contagious? Economic Inquiry, 51(1), 722–734.

    Article  Google Scholar 

  31. Kessler, J. & Vesterlund, L. (2014). The external validity of laboratory experiments: Qualitative rather than quantitative effects. In: F. Guillaume & A. Schotter (Eds.), Methods of Modern Experimental Economics. Oxford University Press, Oxford Forthcoming.

  32. Krupka, E., & Weber, R. A. (2009). The focusing and informational effects of norms on pro-social behavior. Journal of Economic Psychology, 30(3), 307–320.

    Article  Google Scholar 

  33. Krupka, E. L., & Weber, R. A. (2012). Identifying social norms using coordination games: Why does dictator game sharing vary? Journal of European Economic Association, 11, 495–524.

    Article  Google Scholar 

  34. Levitt, S. D., & List, J. A. (2007). What do laboratory experiments measuring social preferences reveal about the real world? The Journal of Economic Perspectives, 21(2), 153–174.

    Article  Google Scholar 

  35. List, J. (2012). Using field experiments to understand the economics of crime, Working Paper 2012.

  36. Mazar, N., & Ariely, D. (2006). Dishonesty in everyday life and its policy implications, Technical Report 2006.

  37. Ostrom, E. (2000). Collective action and the evolution of social norms. Journal of Economic Perspectives, 14(3), 137–158.

  38. Oxoby, R. J., & Spraggon, J. (2008). Mine and yours: Property rights in dictator games. Journal of Economic Behavior & Organization, 65(3–4), 703–713.

    Article  Google Scholar 

  39. Reuben, E., & Riedl, A. (2013). Enforcement of contribution norms in public good games with heterogeneous populations. Games and Economic Behavior, 77(1), 122–137.

    Article  Google Scholar 

  40. Ruffle, B. J. (1998). More is better, but fair is fair: Tipping in dictator and ultimatum games. Games and Economic Behavior, 23(2), 247–265.

    Article  Google Scholar 

  41. Serra, D. (2006). Empirical determinants of corruption: A sensitivity analysis. Public Choice, 126(1), 225–256.

    Article  Google Scholar 

  42. Serra, D., & Wantchekon, L. (2012). Experimental research on corruption: Introduction and overview. In W. D. S. Leonard (Ed.), New advances in experimental research on corruption, research in experimental economics, chapter 1 (pp. 51–76). Bingly: Emerald Group Publishing Limited.

    Google Scholar 

  43. Treisman, D. (2000). The causes of corruption: A cross-national study. Journal of Public Economics, 76(3), 399–457.

    Article  Google Scholar 

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I thank Goutam Gupta and Amitabha Chatterjee for letting me conduct the experiment at Jadavpur University and Presidency University, respectively. I am grateful to Abhishek Das for his excellent assistance while conducting the experiment. I am also thankful to Alexander Koch, John A List, Klaus Abbink, Roel van Veldhuizen, Arnab Mitra, Joydeep Bhattacharya, Marco Piovesan, Tor Eriksson, Bertil Tungodden, Alexander Cappelen and participants at TIBER XII and the 24th Jerusalem School in Economic Theory and two anonymous referees for their comments and suggestions. All remaining errors are mine. The grant for the experiment came from the Department of Economics and Business, Aarhus University.

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Correspondence to Ritwik Banerjee.

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Appendix 1

See Fig. 4.

Fig. 4

Distribution of norm rating for each category of ultim/bribe in UG and BG. The figure maps the entire distribution of the social norm ratings for UG, BG and BG-N treatments. For example, the blue box plot corresponds to the norm ratings for a bribe/ultim demand between 60 and 100 (from the legend). The social norm ratings for that amount of ultim (bribe) may be read from the left (right) panel. The diamond marks the median of the distribution of ratings for each category. The social norm of UG treatment is an inverted U with the equal split considered as most appropriate. The social norm of the BG and BG-N treatments decline monotonically indicating that social appropriateness goes down with the bribe amount, irrespective of framing. (Color figure online)

Table 4 Frequency distribution of norm ratings

Appendix 2

Fig. 5

A small sample regression, like the one described in Footnote 28, produces biased estimates. To the extent that the distribution of the data can help, the quantile plots of the frequency of observations in each bin and the mean of social norms rating for each bin are given here. The distribution of residuals from the regression is also included. The result of the outlier test, based on inter-quartile range, shows the presence of one outlier. Re-estimating the specification and excluding the outlier does not lead to any significant difference.

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Banerjee, R. On the interpretation of bribery in a laboratory corruption game: moral frames and social norms. Exp Econ 19, 240–267 (2016).

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  • Corruption
  • Framing effects
  • Social norms
  • External validity

JEL Classification

  • C91
  • C92
  • D03