This paper explores the individual and joint predictive power of concepts from economics, psychology, and criminology for individual norm enforcement behavior. More specifically, we consider economic preferences (patience and attitudes towards risk), personality traits from psychology (Big Five and locus of control), and a self-control scale from criminology. Using survey data, we show that the various concepts complement each other in predicting self-reported norm enforcement behavior. The most significant predictors stem from all three disciplines: stronger risk aversion, conscientiousness and neuroticism as well as higher levels of self-control increase an individual’s willingness to enforce norms. Taking a broader perspective, our results illustrate that integrating concepts from different disciplines may enhance our understanding of heterogeneity in individual behavior.
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We analyze norm enforcement behavior self-reported in the laboratory instead of actual norm enforcement behavior in the laboratory or the field. There is lots of evidence, on risky or intertemporal choice, for example, that self-reports are well aligned with incentivized decisions in experiments and good predictors of actual behavior in the field (e.g., Dohmen et al. 2011; Falk et al. 2016; Vischer et al. 2013). Moreover, findings in experiments about cheating, for instance, are consistent with choices in the field (e.g., Dai et al. 2016; Potters and Stoop 2016).
We use the Grasmick et al. (1993) scale as opposed to other also well-established scales for measuring self-control (Tangney et al. 2004 or Rosenbaum 1980) since it is the only scale that specifically conceptualizes self-control as a predictor of norm violations. Already by the year 2000, it had been employed by more than 40 studies (see the meta-analysis by Pratt and Cullen 2000).
Borghans et al. (2008) provide a detailed description of research on the development of the Big Five.
See, for example, Almlund et al. (2011) for a more extensive description of the Big Five.
On the screen, the response categories were always displayed in reversed order, i.e.,  at the top and  at the bottom but without numbers attached to them.
In 1999, the mean (standard deviation) for avoiding a fare in public transport is 2.79 (2.21) and 2.74 (2.22) for tax evasion. In 2008, the corresponding numbers are 2.58 (2.10) for fare dodging and 2.28 (1.96) for tax evasion. These numbers are quoted from Douhou et al. (2011) who additionally find similar results for a representative sample of the Dutch adult population in 2008.
For clarity and conceptual reasons, Table 2 does not display correlations between the different Big Five personality traits. They are assumed to be independent factors by construction and their pairwise Pearson correlations are indeed small (i.e., always below 0.3), in 8 out of 10 cases even below 0.1 and not significant. The exceptions are significant correlations between agreeableness and extraversion (positive) and between neuroticism and extraversion (negative). In contrast, the locus of control is a further personality trait that has originated outside the Big Five taxonomy and is significantly correlated with extraversion (positive) and neuroticism (negative), see Table 2.
Almlund, M., Duckworth, A., Heckman, J., & Kautz, T. (2011). Personality psychology and economics. In E. A. Hanushek, S. Machin, & L. Woessmann (Eds.), Handbook of the economics of education. San Diego: North Holland.
Balafoutas, L., & Nikiforakis, N. (2012). Norm enforcement in the city: A natural field experiment. European Economic Review, 56, 1773–1785.
Becker, G. S. (1968). Crime and punishment: An economic approach. Journal of Political Economy, 76, 169–217.
Becker, A., Deckers, T., Dohmen, T., Falk, A., & Kosse, F. (2012). The relationship between economic preferences and psychological personality measures. Annual Review of Economics, 4, 453–478.
Borghans, L., Duckworth, A. L., Heckman, J. J., & ter Weel, B. (2008). The economics and psychology of personality traits. Journal of Human Resources, 43, 972–1059.
Burks, S. V., Lewis, C., Kivi, P. A., Wiener, A., Anderson, J. E., Götte, L., et al. (2015). Cognitive skills, personality, and economic preferences in collegiate success. Journal of Economic Behavior & Organization, 115, 30–44.
Carpenter, J., & Matthews, P. H. (2012). Norm enforcement: Anger, indignation, or reciprocity? Journal of the European Economic Association, 10, 555–572.
Cobb-Clark, D. A., & Schurer, S. (2012). The stability of Big-Five personality traits. Economics Letters, 115, 11–15.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Mahwah: Lawrence Erlbaum Associates.
Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI) manual. Odessa, FL: Psychological Assessment Resources.
Dai, Z., Galeotti, F., & Villeval, M. C. (2016). Cheating in the lab predicts fraud in the field: An experiment in Public Transportations. New York: Mimeo.
Davis, M. L. (1988). Time and punishment: An intertemporal model of crime. Journal of Political Economy, 96, 383–390.
Dohmen, T., Falk, A., Huffman, D., & Sunde, U. (2008). Representative trust and reciprocity: Prevalence and determinants. Economic Inquiry, 46, 84–90.
Dohmen, T., Falk, A., Huffman, D., Sunde, U., Schupp, J., & Wagner, G. G. (2011). Individual risk attitudes: Measurement, determinants and behavioral consequences. Journal of the European Economic Association, 9, 522–550.
Douhou, S., Magnus, J. R., & van Soest, A. (2011). The perception of small crime. European Journal of Political Economy, 27, 749–763.
Eisenhauer, J. G. (2008). Ethical preferences, risk aversion, and taxpayer behavior. Journal of Socio-Economics, 37, 45–63.
Ellickson, R. C. (1998). Law and economics discovers social norms. Journal of Legal Studies, 27, 537–552.
Engels, R., Luijpers, E., Landsheer, J., & Meeus, W. (2004). A longitudinal study of relations between attitudes and criminal behavior in adolescents. Criminal Justice and Behavior, 31, 244–260.
Falk, A., Becker, A., Dohmen, T., Huffman, D., & Sunde, U. (2016). The preference survey module: A validated instrument for measuring risk, time, and social preferences. New York: Mimeo.
Falk, A., Fehr, E., & Fischbacher, U. (2005). Driving forces behind informal sanctions. Econometrica, 73, 2017–2030.
Fehr, E., & Fischbacher, U. (2004). Third-party punishment and social norms. Evolution and Human Behavior, 25, 63–87.
Fehr, E., & Gächter, S. (2000). Cooperation and punishment in public goods experiments. American Economic Review, 90, 980–994.
Fischbacher, U. (2007). z-Tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10, 171–178.
Fischbacher, U., Hertwig, R., & Bruhin, A. (2013). How to model heterogeneity in costly punishment: Insights from responders’ response times. Journal of Behavioral Decision Making, 26, 462–476.
Friehe, T., & Schildberg-Hörisch, H. (2017). Self-control and crime revisited: Disentangling the effect of self-control on risk taking and antisocial behavior. International Review of Law and Economics, 49, 23–32.
Gottfredson, M. R., & Hirschi, T. (1990). A general theory of crime. Stanford, CA: Stanford University Press.
Grasmick, H. G., Tittle, C. R., Bursik, R. J., & Arneklev, B. J. (1993). Testing the core empirical implications of Gottfredson and Hirschi’s General Theory of Crime. Journal of Research in Crime and Delinquency, 30, 5–29.
Greiner, B. (2015). Subject pool recruitment procedures: Organizing experiments with ORSEE. Journal of the Economic Science Association, 1, 114–125.
Heckman, J. J., Stixrud, J., & Urzua, S. (2006). The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior. Journal of Labor Economics, 24, 411–482.
Kagel, J., & McGee, P. (2014). Personality and cooperation in finitely repeated prisoners’s dilemma games. Economics Letters, 124, 274–277.
Leibbrandt, A., & López-Pérez, R. (2012). An exploration of third and second party punishment in ten simple games. Journal of Economic Behavior & Organization, 84, 753–766.
McAdams, R. H. & Rasmusen, E. B. (2007). Norms and the law. In A. M. Polinsky, & S. Shavell (Eds.), The handbook of law and economics. North Holland: North Holland publishing.
McFadden, D., Talvitie, A. P., et al. (1977). Demand model estimation and validation. Urban Travel Demand Forecasting Project, Final report, Vol. V, Institute of Transportation Studies. University of California, Berkeley. http://eml.berkeley.edu/wp/utdfp/vol5/i-1.pdf
Megens, K. C. I. M., & Weerman, F. M. (2010). Attitudes, delinquency and peers: The role of social norms in attitude-behaviour inconsistency. European Journal of Criminology, 7, 299–316.
Nagin, D. S., & Pogarsky, G. (2004). Time and punishment: Delayed consequences and criminal behavior. Journal of Quantitive Criminology, 20, 295–317.
Ozer, D. J., & Benet-Martinez, V. (2006). Personality and the prediction of consequential outcomes. Annual Review of Psychology, 57, 401–421.
Potters, J., & Stoop, J. (2016). Do cheaters in the lab also cheat in the field? European Economic Review, 87, 26–33.
Pratt, T. C., & Cullen, F. T. (2000). The empirical status of Gottfredson and Hirschi’s General Theory of Crime: A meta-analysis. Criminology, 38, 931–964.
Proto, E., & Rustichini, A. (2014). Cooperation and personality. Department of Economics at the University of Warwick Research Paper No 1045.
Rammstedt, B., & John, O. P. (2007). Measuring personality in one minute or less: A 10-item short version of the Big Five inventory in English and German. Journal of Research in Personality, 41, 203–212.
Rosenbaum, M. (1980). A schedule for assessing self-control behaviors: Preliminary findings. Behavior Therapy, 11, 109–121.
Rotter, J. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs, 80, 1–28.
Shaw, J. M., & Scott, W. A. (1991). Influence of parent discipline style on delinquent behaviour: The mediating role of control orientation. Australian Journal of Psychology, 43, 61–67.
Tan, F., & Xiao, E. (2014). Third-party punishment: Retribution or deterrence? MPI for Tax Law and Public Finance Working Paper 2014-05.
Tangney, J. P., Baumeister, R. F., & Boone, A. L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72, 271–324.
Traxler, C., & Winter, J. (2012). Survey evidence on conditional norm enforcement. European Journal of Political Economy, 28, 390–398.
Vischer, T., Dohmen, T., Falk, A., Huffman, D., Schupp, J., Sunde, U., et al. (2013). Validating an ultra-short survey measure of patience. Economics Letters, 120, 142–145.
Volk, S., Thöni, C., & Ruigrok, W. (2011). Personality, personal values and cooperation preferences in public good games: A longitudinal study. Personality and Individual Differences, 50, 810–815.
Volk, S., Thöni, C., & Ruigrok, W. (2012). Temporal stability and psychological foundations of cooperation preferences. Journal of Economic Behavior & Organization, 81, 664–676.
Zhang, Q., Loeber, R., & Stouthamer-Loeber, M. (1997). Development trends of delinquent attitudes and behaviors: Replications and synthesis across domains, time, and samples. Journal of Quantitative Criminology, 13, 181–215.
Financial support from SFB-TR 15 that did not influence study design, data analysis or interpretation. We gratefully acknowledge helpful comments from Fabian Kosse and two anonymous reviewers.
Appendix 1: More information on data collection
The sequence of each session of our experiment was as follows: introductory task—decision 1—decision 2—survey questionnaire. We used a 2 × 2 design. The introductory task was aimed at inducing ego-depletion or no ego-depletion. Subjects then made one decision in a take game and one in a risky investment task. The order of the two decisions varied across sessions. Further details of the experiment are described in Friehe and Schildberg-Hörisch (2017). In our analysis in the main part of the paper, we use all 180 participants’ responses to the survey questionnaire.
In order to document that the variables we use in our analysis are not affected by treatment variations in the introductory task or by order effects concerning decisions 1 and 2, Table 7 displays results of a Kruskal–Wallis test for each variable.
Results in Table 7 show that we cannot reject the hypothesis that data from the four different experimental treatments are drawn from the same population with p < 0.05 for any variable. For most variables, p values are substantially larger than 0.05. To judge the overall result of Table 7, one should keep in mind that if all 13 variables were statistically independent and each of the four treatment groups was drawn from the same underlying population, we would still expect to reject 5% (about 1) of the hypotheses at the 5% level.
As a further robustness check we run the same regressions as in Tables 3, 4, 5 and 6 with treatment dummies as additional covariates (the omitted baseline category is ego-depletion and risky investment task played before take game). Compared to our baseline results reported in Tables 3, 4, 5 and 6, the results with treatment dummies as additional controls are stable, qualitatively very similar, and only 1 out of 12 treatment dummies is significant. The results are available from the authors upon request.
Appendix 2: Additional tables
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Friehe, T., Schildberg-Hörisch, H. Predicting norm enforcement: the individual and joint predictive power of economic preferences, personality, and self-control. Eur J Law Econ 45, 127–146 (2018). https://doi.org/10.1007/s10657-017-9556-5
- Norm enforcement
- Economic preferences
- Personality traits