روابط قوی و ضعیف در استخدام و جرم و جنایت

This paper analyzes the interplay between social structure and information exchange in two competing activities, crime and labor. We consider a dynamic model in which individuals belong to mutually exclusive two-person groups, referred to as dyads. There are multiple equilibria. If jobs are badly paid and/or crime is profitable, unemployment benefits have to be low enough to prevent workers for staying too long in the unemployment status because they are vulnerable to crime activities. If, instead, jobs are well paid and/or crime is not profitable, unemployment benefits have to be high enough to induce workers to stay unemployed rather to commit crime because they are less vulnerable to crime activities. Also, in segregated neighborhoods characterized by high interactions between peers, a policy only based on punishment and arrest will not be efficient in reducing crime. It has to be accompanied by other types of policies that take into account social interactions.

Social interactions and peer effects have proved to be crucial in various aspects of economic activities, including education, crime, smoking, teenage pregnancy, school dropout, etc. (see Durlauf, 2004, for a survey). In the present paper, we focus on the role of social contacts in crime and our main objective is to show how policies aiming at reducing crime are affected by the mode of socialization between agents. For that, we distinguish between weak and strong ties in the pattern of social interactions.1 Following Granovetter (1973), we consider that the strength of a social tie corresponds to the duration of a relationship. We define as strong tie a social relationship between two agents that is repeated over time (for example members of the same family or very close friends) and as weak tie a transitory social encounter between two persons.2 We show that different modes of socialization affect differently the agents' incentives to enter either the labor or the crime market. The structure of social interactions thus affects the aggregate crime and employment level in the economy, and has consequences for the design of optimal crime policies. To be more precise, we consider a model in which individuals belong to mutually exclusive two-person groups, referred to as dyads. Dyad members do not change over time so that two individuals belonging to the same dyad hold a strong tie with each other. However, each dyad partner can meet other individuals outside the dyad partnership, referred to as weak ties or random encounters. By definition, weak ties are transitory and only last for one period. We then assume that individuals learn about crime opportunities by interacting with active criminals. These interactions can take the form of either strong or weak ties. The process through which individuals learn about crime behavior and opportunities results from a combination of a socialization process that takes place inside the family (in the case of strong ties) and a socialization process outside the family (in the case of weak ties). Bisin and Verdier (2000) refer to the former as vertical socialization and to the latter as oblique socialization. Both currently active criminals and potential criminals exert an influence over one another to commit offences by meeting each other. In contrast, we assume that individuals learn about job opportunities exclusively through employment agencies.3 We analyze the flows of dyads between states and characterize all the steady-state equilibria of this dynamic economy. For this purpose, we solve for the endogenous individual decisions to switch between the three possible statuses, that is, criminal, unemployed and employed. We work throughout with forward-looking agents, who anticipate fully the impact of their current decisions on their future opportunities and payoffs. Four equilibria can emerge, that differ in their composition by agent's statuses. In one equilibrium, all agents are unemployed. We also find two polar equilibria composed either of criminals and unemployed agents, or employed and unemployed agents. Finally, a mixed equilibrium exists, where both criminals, employed and unemployed workers coexist. We characterize the ranges of exogenous parameter values for which each of those equilibria emerges. Multiple equilibria only arise for a particular range of values, where both a completely mixed economy and a degenerate economy composed solely of criminals can emerge. We then analyze how endogenous outcomes (crime, employment and unemployment) respond to variations of the exogenous parameters. This comparative static exercise sheds light on the interplay between the crime market and the labor market, and illuminates the impact of pure labor market interventions or pure crime policies on both markets. Pure labor market interventions consist on modifying the unemployment benefit, while pure crime policies impinge on deterrence. In substance, we show how altering agents' incentives in one market spills over to the other (related) market. Thus, deterrence affects unemployment rates while unemployment benefits influence crime rates. This relationship is not trivial. It depends on the relative gains from crime and the labor market, and also from the social cohesion of the economy. When jobs are badly paid and/or crime is profitable, we show that the aggregate crime level increases with the unemployment benefit. The labor market regulation has thus an impact on crime rates and, here, the optimal policy to reduce crime consists on decreasing the unemployment insurance. The reason is the following. First, when the unemployment benefit is low, the opportunity cost of searching a job decreases, and workers have more incentives to find jobs quickly. As such, the unemployment spell decreases. Second, note that unemployed workers are more prone to enter in the crime business than employed workers. This is because their rents are lower. A shorter unemployment spells thus reduces the workers' exposure to crime opportunities. Therefore, through its dynamic effect on the duration of unemployment, a reduction in unemployment benefits decreases aggregate crime. Suppose now that workers are well paid and/or crime is not a profitable case. With a similar reasoning, we can conclude that a higher unemployment benefit induces workers to stay unemployed longer rather than to commit crime, and the crime rate decreases. Unemployment, in our model, is not only the “waiting room” for employment (as it is usually perceived) but also for crime. Unemployed workers trade off the costs and benefits from becoming employed or a criminal. In a dynamic setting, the opportunity cost of searching for a good job becomes a crucial determinant of this trade-off. The impact of the unemployment insurance on crime thus depends on the relative values of being employed or criminal. Our analysis suggests that an optimal unemployment benefit policy should discriminate among the different characteristics of local labor markets. Beyond agents' incentives, the pattern of social interactions also shapes market outcomes and affects the effectiveness of policy interventions. Recall that, in our model, crime opportunities are only disseminated through word-of-mouth communication among criminals, and between criminals and jobless agents. The information flows from crime insiders to crime outsiders depend on the frequency of encounters between the two types of agents. If transitory encounters are rare and most interactions take place within strong ties, crime opportunities only flow within dyads composed of a criminal and an unemployed, but almost never across dyads. Crime feeds itself with crime, and there is little osmosis between crime and unemployment. Suppose, instead, that transitory encounters are more frequent. Then, many interactions take the form of occasional weak ties outside best-friend partnerships. Information flows are not circumscribed to the dyad but are very intense across dyads, and crime opportunities spread widely in the society. Unemployed agents, which are also would-be criminals, now face a high chance to undertake an illegal activity. Crime thus feeds itself with both crime and labor because of the strong connection between these two markets. A first consequence of this observation is that an increase in the frequency of weak ties raises crime but reduces both employment and unemployment. When people spend most of their time in extroverted interactions with outside peer (weak ties), and are not stuck to introverted meetings with the reduced circle of best friends (strong ties), the crime rate soars to a very high level while employed falls down sharply. Again, this is because when one is pulled towards crime activities and both his best friend and peers are criminal, it becomes extremely difficult to go back to the labor market. You need that you and your best friend are caught, and then you get a job offer, an event that can take quite a long time. This interplay between modes of socialization and crime and labor market outcomes has implications for the design of crime policies. The direct effect of increasing the arrest probability is, of course, to pull criminals outside from crime into unemployment, the doorstep for employment. But, in our model, unemployment is also the “waiting room” for crime, not only for employment. Therefore, the actual decrease in crime following an increase in deterrence depends on the unemployment-to-crime flows. These flows are higher when weak tie encounters dominate strong tie interactions. The impact of higher deterrence is thus relatively moderate under frequent random encounters, compared to the case where agents meet within their circles of close friends. Acknowledging the fact that homogamy favors socialization (Conley and Topa, 2002), neighborhood segregation usually fosters broad socialization patterns at the neighborhood level, and outside inner family circles. In these cases, a policy based only on punishment and arrest will not be that efficient in reducing crime. It has to be accompanied by other types of policies designed from a community-wide, multiple solution perspective to the crime problem, rather than from a purely individualistic approach. Related literature It is well-recognized that labor market opportunities have a strong impact on criminal behavior. For instance, there are also sizable and significant effects of unemployment (Raphael and Winter-Ebmer, 2001), wages (Machin and Meghir, 2004) and inequality (Bourguignon et al., 2003) on crime. More important for our purpose, friends and, more generally, the social environment, are also conducive to criminal behavior. For instance, the positive correlation between self-reported delinquency by adolescent and the number of delinquent friends is among the strongest and most consistent findings in the delinquency literature (Warr, 2002 and Matsueda and Anderson, 1998). More precisely, Glaeser et al. (1996) find that across crimes, crime committed by younger people has higher degrees of social interaction, while, across cities, for serious crimes in general and for larceny and auto theft in particular, the degree of social interactions is larger in those communities where families are less intact, that is, have more female-headed households. Ludwig et al. (2001) and Kling et al. (2005) use data from the Moving to Opportunity (MTO) experiment, which relocates families from high to low-poverty neighborhoods. They show that this experiment reduces juvenile arrests for violent offences by 30 to 50% of the arrest rate for control groups. In their study of a gang located in a black inner-city neighborhood, Levitt and Venkatesh (2000) also find that social/nonpecuniary factors play an important role in criminal decisions and gang activities. More recently, using a very detailed data-set of friendship networks in the United States from the National Longitudinal Survey of Adolescent Health (AddHealth), Calvó-Armengol et al. (2005) test directly the impact of social networks on juvenile crime. They show that, after controlling for observable individual characteristics and unobservable network specific factors, the individual's position in a network is a key determinant of his or her level of criminal activity. A standard deviation increase in an individual's centrality in a network increases the level of individual delinquency by 45% of one standard deviation. Using the same dataset, Patacchini and Zenou (2005) find that conformity is very strong within groups of delinquents and that the higher the taste for conformity of an individual, the lower the deviation from the norm's group. Their results suggest that, for teenagers, the decision to commit crimes is not a simple choice based primarily on individual considerations but is strongly affected by their environment and peers.4 The rest of the paper is organized as follows. The model is described in Section 2. We first focus on imperfectly myopic agents. The steady-state equilibrium analysis is in Section 3, while Section 4 is devoted to the comparative statics exercise. Section 5 analyzes the case of perfectly forward-looking agents, and both a theoretical analysis and numerical simulations are proposed. All proofs are relegated to an Appendix.