Mathematical models of social norms and petty corruption

University dissertation from Västerås : Mälardalen University

Abstract: Corruption is a problem all around the world, but the extent of the problem varies between countries and situations. In this thesis, I focus on how corruption levels can change when they are culturally determined. For this reason, I study the dynamics of the cultural underpinnings: social norms and conventions.The dissertation consists of six papers. In the first paper, I expand a common definition of social norms. The aim of the extension is to capture the fact that the scope of a social norm may be larger than just a single specific situation. I introduce a similarity measure and develop a mathematical model according to which all situations' social norms are interconnected, and affect each other, but those situations that are most similar and most recent have the greatest normative effect on a current situation. Given this model I test the effect of bringing about norm change by temporarily dismantling institutions and then reestablishing them.In the second paper, I show in a mathematical model how it is possible to design fine and reward mechanisms that make it superfluous for individuals to form beliefs about how others will act. Through this mechanism, it should be possible to circumvent the problem that norm change typically will be successful only if it is synchronized across a large part of the population.In the third paper, I and my co-authors, first conducted a survey. The results of which demonstrate that there is a general tendency among people to consider themselves to be less prone to corrupt behavior than the average person. Such an "everyone-is-better-than-average" effect is a well-established phenomenon in social psychology but not previously demonstrated in the corruption domain. We then show in a mathematical model that such systematic biases in estimation of own versus others' corruption make it more difficult to achieve norm change in the direction of less corruption.In the fourth and fifth paper we again consider the "everyone-is-better-than-average" effect and see how in certain value based groups the effect can be reversed. This changes the insight from the third paper slightly.The last paper considers a classic question of how a collective can succeed in collective action when it is risky to be among the first individuals to act. I and my co-author investigate how the collective can benefit from access to a set of signal acts that signal an individual's level of commitment to the collective cause. The problem is modeled as a threshold model where an individual's inclination to conduct a specific act depends on the previous commitment level in the population.