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Schikora, Jan (2011): Four Essays on Corruption and Cooperation: Theory and Evidence. Dissertation, LMU München: Faculty of Economics



This dissertation contains four separate studies in the fields of corruption and cooperation. The first chapter explicates the mechanism that links the fractionalization of society with its level of corruption within a theoretical model of relational contracting. The other three chapters describe experimental studies. The second and third chapters evaluate two popular anti-corruption policies, the ‘Four-Eyes-Principle’ and ‘Whistle- Blowing’, with respect to their effectiveness in decreasing the level of corruption and increasing social welfare. The last chapter considers the effect of endowment uncertainty on cooperative behaviour in a linear public goods game and explains it by specific conditional cooperation preferences. Cooperation between decision-making agents is recognized as one of the single most important mechanisms in economic research and represents one of the cornerstones of economic development. Countless economic activities have been analysed with game theoretic models of cooperation. Experimental methods may not only demonstrate the deficiencies of standard economic theory in terms of explanation and predictive power, they may also help to improve existing models. The public goods game (Isaac and Walker 1988) represents one of the most popular vehicles to experimentally analyse cooperative behaviour. It models the dilemma of the opposition between selfish preferences and social efficiency. Numerous experiments have shown that participants behave in a highly cooperative way in situations for which the standard economic theory of rational payoff maximization predicts strictly selfish behaviour. In my view, the most convincing approach to explaining the phenomenon of cooperation is the existence of conditional cooperative behaviour. This links the public goods game to games that are specifically designed to analyze trust and reciprocity, e.g. the gift exchange game (Fehr et al. 1993), the investment game (Berg et al. 1995) and the ultimatum game (Güth et al. 1982). Applications of these games even extend to criminal activities such as corruption. Administrative corruption, defined as ‘the misuse of public power for public gain’ (Klitgaard 1988) is recognized as the ‘single most important obstacle to economic development’ (The World Bank 2008). The key to effective anti-corruption policy with respect to institutional design is the understanding of the determinants, mechanisms and weaknesses of corruption. This demands the analysis of two different levels of cooperation common to most corrupt transactions. Since any corrupt relationship is by definition illegal, the corrupt partners cannot rely on legal third parties, i.e. the courts, to enforce their contracts. The transaction between a client and a corrupt official depends on trust and reciprocity which may be fostered for example by repeated interaction. This kind of cooperation is similar to the mechanism modelled in the gift exchange game. In contrast to the original gift exchange game, where cooperation is efficient with respect to social welfare (measured e.g. in the sum of payoffs to all affected individuals), corrupt reciprocity is socially undesirable due to the reasonable assumption of its strong negative externality to the public (Shleifer and Vishny 1993, Rose-Ackermann 1999). In the case of instable corruption, it would be socially optimal for all agents to stay away from reciprocity and cooperation, and adhere to their selfish rationality. The situation involving all members of a society with respect to their choices for or against corrupt reciprocity can hence be seen as a reverse public goods dilemma in a broader sense. The first chapter focuses on the role of the fractionalization of a society in determining the level of corruption. In a series of empirical cross-country studies social fractionalization, often (crudely) measured by the Ethno-Linguistic Fractionalization Index (ELF, see Appendix 1A) has been identified as an important determinant of the level of corruption measured by the Corruption Perception Index or similar indices (Alesina and Ferrara 2002, Mauro 1995, Bardhan 1997). In a cross regional analysis, providing a more controlled environment, Dincer (2008) finds an inversely U-shaped relationship between the two variables. However, none of these studies provides a model based theoretical explanation for the empirical evidence. As a basis of our analysis we use an infinitely repeated version of a standard, multi stage game of administrative corruption which captures the enforcement problem of the illegal transaction. In order to describe the main mechanism underlying the relationship between the social structure and corruption we define the structure of society in terms of its fractionalization as a vector of separated sub-networks whose members share information. Assuming that clients use simple punishment strategies as devices to maintain corrupt cooperation within relational contracting, we find that the maximum level of corruption is to be expected in societies that consist of a large but not maximal number of small (but not minimal) groups. This is due to the inversely U-shaped relationship between the relative size of a sub-network (measured in the number of group members relative to the size of society) and its members’ ability to stabilize corrupt transactions. The (relative) size of a sub-group has two countervailing effects on the corruption level. On the one hand, the (average) probability of a successful corrupt transaction (expected frequency) increases in the number of group members. This is because the incentives for opportunism decrease due to growing stakes for the official. On the other hand, an increase in the relative sub-group size increases the (personal) costs for the clients through the internalization of a larger part of the negative externality. Thus, necessary compensation of a growing number of peers decreases the profitability of corruption. This chapter provides a model-based explanation of the inversely U-shaped relationship between social fractionalization and corruption found in Dincer (2008). The results of our model are also in line with empirical observations of cross-country comparisons (Gunasekara 2008, La Porta et al. 1999 and Alesina et al. 2003). Our model can be extended to account for considerations of the influence of different types of social capital on corrupt behaviour. Using the standard model of self-interested payoff maximization to analyse the mechanisms that underlie the determinants of corruption may only be reasonable in situations in which limit values and benchmark examinations are considered, and therefore simplifying assumptions such as infinite repetitions are justified. In finitely repeated interaction (or one shot games) of corruption, neither the standard self-interested model nor models of strong reciprocity relying on social preferences such as altruism (Andreoni and Miller 2002), inequity aversion (Fehr and Schmidt 1999) or intentions (Dufwenberg and Kirchsteiger 2004) can provide a consistent explanation or predictions for corrupt behaviour based on cooperation. This and the scarcity of reliable field data complicate any analysis of corruption that aims at deriving policy implications. In order to evaluate the usefulness of proposed anti-corruption measures, or those that are in force, controlled experiments are indispensible to complement empirical studies. The findings of several studies, e.g. Armantier and Boly (2008), demonstrate the external validity of laboratory corruption experiments (Dusek et al. 2004). Following Abbink et al. (2002) with respect to experimental methodology, the second chapter describes an experimental approach to assess one of the most potent countercorruption policy tools, the ‘Four-Eyes-Principle’ (business has to be conducted by at least two individuals, hence four eyes). Although proposed in various reports and lists of recommendations for anti-corruption measures by national and international organizations, it lacks any theoretical or empirical justification (Pörting and Vahlenkamp 1998, Rieger 2005, Wiehen 2005). In our laboratory experiment we replace a single decision-maker with a small group of two officials who decide jointly in the role of the official in order to model the introduction of the ‘Four-Eyes-Principle’. We show that the introduction of the ‘Four-Eyes-Principle’ can lead to an increase rather than a decrease of the level of corruption. This result comes as a surprise when considering predictions from the standard self-interested model alone and ignoring effects stemming from the dynamics of group decision-making. Controlling for effects that are purely driven by differences in marginal incentives (i.e. effects stemming from the splitting of the benefits and costs of corruption between two officials) we find that group decision-making is dominated by the motive of individual (long term) profit maximizing, which has been identified as a main explanation for group decision-making (Kocher and Sutter 2007). Combining data of final choices (outcomes) with evidence from inside the decision-making process (i.e. the dynamics of individual choices), we show that groups follow strategies that foster reciprocity in a more sustainable way than their individual counterparts, which leads to a higher number of successful corrupt transactions. To explain the behavioural characteristics in more detail, we analyse the content of electronic chat messages exchanged during the joint decision-making process. In an average situation of disagreement between two officials, it is the official with the more corrupt agenda who dominates the decisions despite the honest official’s veto power. Since corrupt reciprocity maximizes individual payoffs for the immediate transaction partners, arguments in favour of a strategy that fosters corrupt reciprocity are most persuasive. We interpret this result as support for the Persuasive Argument Theory attributing groups a higher ability to adhere to behaviour that generates maximum individual payoffs (Pruitt 1971). Our results show that the profit maximizing motive may dominate in the group decision-making process even though there is an obvious trade-off with social efficiency. Since they ignore the negative external effects of corruption, groups produce the least desirable outcomes in terms of welfare by their reciprocal behaviour. Against existing policy recommendations, the results of our experiment cast doubt on the usefulness of the introduction of the ‘Four-Eyes-Principle’. This chapter does not only evaluate an anti-corruption measure, it also provides insights into the motivations, within groups and individuals, that underlie strategic decisions in social dilemmas in general and in the dilemma of corruption in particular. The third chapter experimentally assesses the effectiveness of another tool of anticorruption policy. The institutional enabling of whistle-blowing is seen as a powerful measure to contain corrupt activity (Drew 2003). Whistle-blowing is generally defined as ‘the act of disclosing information in the public interest’. Despite its widespread use and perceived success, experimental evidence seems to cast doubt on its usefulness (Abbink 2006, Lambsdorff and Frank 2010, forthcoming). This may be because the analysis of whistle-blowing within the standard set-up of a corrupt transaction accounts for only one aspect of its total effect on social welfare. The standard game of corruption, often used to analyse the effect of a determinant on the frequency of corruption, only considers the direct but not the indirect consequences of corruption on social efficiency. While the direct consequences may be captured by the expected negative externality to the public resulting from a successful corrupt transaction, the indirect consequences include efficiency losses caused by honest clients leaving productive markets because of their fear of being exploited by corrupt officials. Where in the standard game of corruption the official has a passive role with respect to the initiation of a corrupt transaction, we expand the standard model by allowing both sides of the transaction to activate corruption. The symmetry of corrupt engagement enables us to assess the potential effects of the introduction of the opportunity to blow the whistle on the two main negative consequences of corruption. First, whistle-blowing may reduce the negative effect of corruption hindering ‘honest’ clients to engage in productive activity by providing a tool against demanding corrupt officials. Second, whistle-blowing may affect the stability of the corrupt transaction and influence the number of successful deals and hence the amount of realized negative externalities. We find that the total effect of symmetrically punished whistle-blowing (i.e. the punishment is independent of who has blown the whistle) is ambiguous. Confirming the findings of Lambsdorff and Frank (2010) and Abbink (2006), whistle-blowing increases the stability of a corrupt transaction. However we find that it also reduces the effect of corruption deterring productive activity, offering a safeguard for an ‘honest’ client against the extortion by a corrupt official. We demonstrate that asymmetric leniency for the official can offset the negative effect of whistle-blowing. Our results can be explained using simple arguments as to subjects’ belief structures and payoff maximization. Moreover, we find that leniency is especially effective for male officials. The consideration of asymmetric punishment of illegal activities in general and leniency for whistle-blowing in particular should be considered in legislature. Our extended model of corruption provides the basis for experimental research targeting both direct and indirect effects of corruption. While the focus of the first three chapters is on the negative consequences of cooperative behaviour in corruption, the fourth chapter, which is joint work with Johannes Maier, considers socially desirable cooperation. In an experimental public goods game using the Voluntary Contribution Mechanism (Isaac and Walker 1988) we study the effect of uncertainty as to others’ endowments on contribution behaviour. In most applications of public goods provision it is more realistic to assume heterogeneity instead of homogeneity of initial endowments between cooperation partners. The own endowment can be private information, which means that endowment levels of fellow group members can be unknown. In situations of charitable giving, for example, endowments (individual wealth levels) are likely to be heterogeneous and information about them remains private, while information about actual contributions (donations) are often made publicly available. To quantify and explain the effect of endowment uncertainty on cooperative behaviour we use an adapted version of the experimental two-stage approach used by Fischbacher and Gächter (2010). In the first stage of our experiment, subjects had to state their contribution preferences conditional on their group partners’ contributions and endowments. Here we used an incentivized strategy method (Selten 1967). In the second stage, we quantify the effect of uncertainty in a repeated linear public goods game (ten periods) played in partner design with groups of three participants. While subjects knew their own endowment and the endowments of their two group partners in the certainty treatment, they only knew their own endowment, low or high, in the uncertainty treatment. However, they knew that the others were either high or low endowed. When we pool all observations of each treatment, we only find a small negative but insignificant effect of uncertainty on average contribution levels. When we separate observations according to participants’ endowments, we find that subjects with high initial endowments contribute slightly more, while participants with low endowments contribute substantially less under uncertainty. These two opposing effects of uncertainty lead to lower contribution levels in poor and higher contribution levels in rich groups. The inequality in income levels between low and high endowed subjects therefore increases through uncertainty. We explain our treatment effects by two mechanisms, the effect of deviating beliefs and the net effect of (strategic) over-contribution. We attribute both effects to conditional contribution preferences. One of our main results is that subjects are relative conditional contributors. In the context of heterogeneous endowments this means that they contribute more, the lower their group partners’ endowments holding their absolute contributions constant. This and the findings of systematically deviating beliefs explain the former of the two mechanisms. Under uncertainty, low endowed subjects believe that they are in a richer group than they actually are and therefore contribute less in the repeated public goods game than they would have done, had they known the correct endowments of their group partners. High endowed subjects, on the contrary, believe that their group members are poorer on average and hence contribute more. The preference for relative conditional cooperation also explains the treatment differences in (strategic) over-contribution that remains when we subtract the effect of deviating beliefs. The intuition for (strategic) over-contribution is that subjects contribute higher levels in repeated games than their stated preferences should allow in order to trigger positive reciprocity and thereby sustain cooperation (see e.g. Fischbacher and Gächter 2010). In contrast to groups in the certainty treatment and groups consisting of high endowed individuals in the uncertainty treatment, we do not find (strategic) over-contribution in groups of low endowed individuals under uncertainty. We attribute this to their fear of sending the wrong signals (i.e. being high endowed) by making large contributions. This fear may be due to participants’ anticipation of others’ relative conditional cooperation preferences. Overall, the combination of the two mechanisms explains a large fraction of our treatment effects. This paper not only explicates contribution behaviour under uncertainty, it also expands the knowledge of conditional cooperation preferences in general. Its results motivate future research on the theoretical foundations of conditional cooperation. All four chapters contain their own introductions and appendices so they can be read independently.