Abstract
This paper introduces groups that are in conflict against each other in law enforcement policy. These groups can have an effect on the process of law enforcement by making upfront investments, such as bribes. We also investigate consequences when a policy maker acts to maximize a bribe instead of social welfare. Thus, this paper presents an inclusive framework for incorporating private law enforcement, corruption and avoidance activities. This article shows that this competition can lead to moderate and more efficient law enforcement activities. This indicates that inefficient law enforcement by authority with harm reduction motivation can be avoided. Additionally, this paper shows that depending on the policy maker’s objection between rent-seeking motivation or social welfare maximizer, deterrence effects vary. This paper provides a clear mechanism that the rent-seeking motivated policy maker tends to set less severe enforcement policies than the social welfare level.
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Notes
It also has been discussed in the law and economics literature that the government’s objectives should not include the benefits of offenders e.g., Dau-Schmidt (1990). One of the main reasons that public enforcers consider the benefit to criminals is that there exists some political pressure from the collective entity advocating a weak law enforcement policy. In this respect, this paper provides a framework for analyzing why the government cares about benefits to criminals.
This is because compared to changing sanctions, controlling detection efforts is easier and takes less time. Moreover, because detection activities have costs, this tends to reflect their attitudes towards law enforcement policies.
For simplicity, each group acts as a unitary actor, since we do not consider the collective action problem.
We assume that the second-order condition must be satisfied.
This situation occurs when \(\partial n_2/\partial p \le 0\). We also assume that if detection activity is 0 (\(p=0\)), a change in the degree of sanction has no meaning. This is intuitive because law enforcement has an effect when these two functions work effectively.
These papers used this type of probability function for analyzing caps on campaign contributions, immigration quotas and trade policy.
Another type of probability function is the lottery contest success function, as originally proposed by Tullock (1980). The winning probability is determined in accordance with the ratio of each group’s investment; thus, in contrast to the all-pay auction model, uncertainties play important roles.
Moreover, in the literature, the source of distortions of law enforcement policies demands only that there are no detection activities. Thus, in contrast to the literature, this paper considers not only these extreme illegal gainers that demand no detection efforts but also moderate players that desire less severe crackdown strategies; we investigate a wide range of strategic law enforcement process.
In the previous literature, the lottery function that uncertain factors work is implicitly used.
This setting is similar to the corruption law enforcement literature; see, e.g., Bowles and Garoupa (1997), Polinsky and Shavell (2001) and Echazu and Garoupa (2010). These papers focus on direct interaction between law enforcers and offenders, while this paper’s setting offers new insight about how to control their incentive for bribing. Because of this, from the social welfare point of view, the target to control the source of distortion is two groups. Additionally, this paper’s motivation is oriented toward more sophisticated political and institutional connections among high-ranking figures.
For example, when Group 2 invests y satisfying \(d_2> y\), Group 1 spends \(x=y+e\) satisfying \(d_1>x\). In this situation, Group 2 has an incentive to choose \(y=0\) as the optimal strategy. However, since the reasoning is similar for Group 1, this cannot be a pure-strategy Nash equilibrium. Thus, there is no pure-strategy Nash equilibrium.
According to Konrad (2009), the unique equilibrium in these mixed strategies are described by groups’ uniform cumulative distribution functions, which describe the distribution of investments choices: \(F_1 (x)=x/d_2\) for \(x\in [0,d_2]\). Further, \(F_2 (y)=[1-d_2 /d_1]+y/d_1\) for \(y\in [0,d_2]\). Thus, these results can be obtained by taking expected values.
If we have \(d'_2<0\), or the direct effect is larger than indirect effect for Group 2, this result always holds.
Friehe and Miceli (2017) present a setup similar to our own, in that the law enforcement authority and an illegal gainer choose simultaneously. However, the main differences are that they do not consider the law enforcement authority as one lobbyist and use a different method to choose the detection activities.
Although imposing the sanction also imposes some cost, our implication is unchanged.
One application of this framework is to examine the relationship between the quality of democracy and organized crime in which citizens and figures of organized crime groups are active. According to Sung (2004), “higher perceptions of victimization by organized crime were reported in moderately democratic countries than in both authoritarian societies and advanced democracies.” This is because, in the process of democratization, organized crime groups, such as the Mafia, have opportunities to obtain payments through political connections. In this respect, our analysis supports his result that the rent seeker tends to pursue his own private gain at the expense of desired and efficient law enforcement. Lin (2007) finds that major crime tends to be more punished than minor crimes in more developed countries than in less developed countries.
This paper is similar to that of Echazu and Garoupa (2010), in that law enforcement authority takes two actions. Although the motivation in Echazu and Garoupa is to see how the distortion is generated by multi-task jobs of law enforcers, in this paper, the setup is such that there is no trade-off between lobbying efforts and actual detection activities, and the target to control behavior is mainly groups with greater concerns about law enforcement policies. That is, it is not true that there is an interaction between law enforcement authority and offenders.
References
Amegashie JA (2004) A political economy model of immigration quotas. Econ Gov 5:255–267
Baye MR, Kovenock D, De Vries CG (1996) The all-pay auction with complete information. Econ Theor 8:291–305
Ben-Shahar O, Harel A (1995) Blaming the victim: optimal incentives for private precautions against crime. J Law Econ Organ 11:434–455
Bowles R, Garoupa N (1997) Casual police corruption and the economics of crime. Int Rev Law Econ 17:75–87
Che YK, Gale IL (1998) Caps on political lobbying. Am Econ Rev 88:643–651
Coe CK, Wiesel DL (2001) Police budgeting: winning strategies. Public Adm Rev 61:718–727
Costelloe MT, Chiricos T, Gertz M (2009) Punitive attitudes toward criminals: exploring the relevance of crime salience and economic insecurity. Punishm Soc 11:25–49
Dau-Schmidt KG (1990) An economic analysis of the criminal law as a preference-shaping policy. Duke Law J 1990:1–38
Dharmapala D, Garoupa N, McAdams RH (2016) Punitive police? agency costs, law enforcement, and criminal procedure. J Leg Stud 45:105–141
Dittmann I (2006) The optimal use of fines and imprisonment if governments do not maximize welfare. J Public Econ Theory 8:677–695
Echazu L, Garoupa N (2010) Corruption and the distortion of law enforcement effort. Am Law Econ Rev 12:162–180
Friedman D (1999) Why not hang them all: the virtues of inefficient punishment. J Polit Econ 107:259–269
Friehe T, Miceli TJ (2017) On punishment severity and crime rates. Am Law Econ Rev 19:464–485
Garoupa N (1997) The theory of optimal law enforcement. J Econ Surv 11(3):267–295
Garoupa N, Klerman DM (2002) Optimal law enforcement with a rent-seeking government. Am Law Econ Rev 4:116–140
Garoupa N, Klerman DM (2010) Corruption and private law enforcement: theory and history. Rev Law Econ 6:75–96
Grechenig K, Kolmar M (2014) The state’s enforcement monopoly and the private protection of property. J Inst Theor Econ 170:5–23
Hillman AL, Riley JG (1989) Politically contestable rents and transfers. Econ Polit 1:17–39
Konrad KA (2000) Trade contests. J Int Econ 51:317–334
Konrad KA (2009) Strategy and dynamics in contest. Oxford University Press, Oxford
Langlais E (2008) Detection avoidance and deterrence: some paradoxical arithmetic. J Public Econ Theory 10:371–382
Langlais E, Obidzinski M (2016) Law enforcement with a democratic government. Am Law Econ Rev 19:162–201
Lin MJ (2007) Does democracy increase crime? the evidence from international data. J Comp Econ 35:467–483
Malik AS (1990) Avoidance, screening and optimum enforcement. Rand J Econ 21:341–353
Nitzan S (1994) Modelling rent-seeking contests. Eur J Political Econ 10:41–60
Polinsky AM, Shavell S (2000) The economic theory of public enforcement of law. J Econ Lit 38:45
Polinsky AM, Shavell S (2001) Corruption and optimal law enforcement. J Public Econ 81:1–24
Sung HE (2004) State failure, economic failure, and predatory organized crime: a comparative analysis. J Res Crime Delinq 41:111–129
Tullock G (1980) Efficient rent seeking. In: Buchanan JM, Tollison RD, Tullock G (eds) Toward a theory of the rent-seeking society. Texas A and M University Press, College Station, pp 97–112
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I would like to thank the editor Marko Koethenbuerger, an anonymous referee, Koichi Suga and Kohei Kamaga for their helpful comments and suggestions.
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Yahagi, K. Private law enforcement with competing groups. Econ Gov 19, 285–297 (2018). https://doi.org/10.1007/s10101-018-0210-7
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DOI: https://doi.org/10.1007/s10101-018-0210-7