Bolstering community ties and its effect on crime: Evidence from a quasi-random experiment Magdalena Dom´ınguez and Daniel Montolio∗ Work in progress - Do not cite without permission This version: February 2019 Abstract In this paper we study the effect of bolstering community ties on local crime rates. To do so, we take advantage of the quasi-random nature of the implementation of a community health policy in the city of Barcelona. Salut als Barris (BSaB) is a policy that through community-based initiatives and empowerment of citizenship aims at improving health outcomes and reducing inequalities of the most disadvantaged neighborhoods. Based on economic and sociological literature it is also arguable that it may affect other relevant variables for overall welfare, such as crime rates. In order to test such a hypothesis, we use monthly data at the neighborhood level and a staggered Differences-in-Differences approach. Overall we find that BSaB highly reduces crimes related to non-cognitive features as well as those where there is a very close personal link (labeled as home crimes), with responses ranging from 9% to 18%. Additionally, female victimization rates drop for all age groups as well as the offense rates of younger cohorts. We argue that such outcomes are due to stronger community ties. Such results provide evidence in favor of non-traditional crime preventing policies. Keywords: crime; community action; differences-in-differences. JEL codes: C23, I18, I28, J18. ∗Dept. of Economics, University of Barcelona and IEB: [email protected] ; [email protected] We are grateful to Elia Diez and Maribel Pasarin at the Barcelona Public Health Agency (ASPB) and IGOP researchers Raquel Gallego and Ernesto Morales at Autonomous University of Barcelona (UAB) for their insightful comments on the program. We also thank Judit Vall, Antonio di Paolo, Juan S. Morales and Ana Tur-Prats for their feedback on previous versions of this paper. All remaining errors are our own. 1 Introduction Urban economics has vastly differences between and within cities in many aspects, among which growth and inequality have taken most attention. However, as already pointed out by Glaeser et al. (1996) and Glaeser and Sacerdote (1999), crime related contrasts are also striking. Such outcomes are of particular relevance both for individual and overall welfare. On this matter, recent literature has confirmed that individual choices of crime participation may be significantly affected by existing norms and networks (Glaeser et al. 1996; Patacchini and Zenou 2009). Regarding the relationship between crime and social networks, there is no clear-cut consensus whether the empirical correlation should be positive or negative, if it reflects a causal link (and in what direction), and what implications it has for policy-making. On one side, social networks may work as communication channels for criminals and may also offer cover-up to criminal activities. Recent work emphasizes that denser social networks might raise aggregate crime levels due to know-how sharing among criminals (Calv´o-Armengoland Zenou 2004) or imitation of peer behavior (Glaeser et al. 1996; Calv´o-Armengolet al. 2009). However, on the other side, they will also increase the opportunity cost of committing a crime. Such possible outcome closely relates to the concept of social capital, defined by Guiso et al. (2011) as a set of values and beliefs that help cooperation in a community. On this matter, Coleman (1988) already related the strength of social sanction to social network closure. Additionally, systemic models of community organization are built on the notion that well developed local network structures reduce crime (Flaherty and Brown 2010). This relates to the fact that networks may increase returns to non-criminal activities and raise detection probabilities. In this paper, we argue that initiatives that bolster community ties in disadvantaged neighborhoods succeed at reducing crime rates, especially those that are not driven by monetary incentives. We test such hypothesis by analyzing a community health policy that took place in the city of Barcelona (Barcelona Salut als Barris, BSaB) and that was implemented in a quasi-random fashion, and by using a unique geocoded dataset on criminal offenses. In order to do so, we follow a staggered differences-in-differences methodology combined with a battery of economic controls and a rich set of time and space fixed effects. On this matter, the existing literature has not taken such an approach, with similar rich data and methodology. Our estimates suggest that the reduction in certain crime rates can be attributed to this policy. Specifically, we find that BSaB highly reduces personal crimes, those related to non-cognitive features as well as those where there is a very close personal link (labeled as home crimes), with responses ranging from 9% to 18%. Additionally, female victimization rates drop for all age groups as well as the offense rates of younger cohorts. This research is ambitious since it deals with the impact of community ties on crime 1 in an urban context, a line of research of high relevance in the field of economics of crime. The final goal is to better understand the empirical determinants of criminal activities, how networks deter/encourage them and how they interact with socioeconomic factors. The novelties of this paper come from many factors. Firstly, the deployment of the policy provides us with an exogenous variation of community ties drivers at a very small geographical level, which allows us to determine causal links. Secondly, we make use of a geocoded and very detailed database that includes data on registered crime, offenders and victims. This also adds to the accuracy of the analysis, as we can analyze whether there are differential effects by crime types, and demographic characteristics of those involved. Finally, we contribute to the literature outside the United States and make a case for a city in which individuals are heterogeneous in terms of economic and sociodemographic characteristics. These features adds up to the external validity of our exercise. Outcomes will contribute to academic research and will offer specific guidance for policy-making to deter criminal activities, going beyond traditional approaches. Furthermore, this case study will benefit other cities given that policy recommendations will be applicable to similar urban settings. This paper is organized as follows. Section 2 analyzes the link in the literature between social capital and crime. Section 3 describes the institutional framework of the initiative under analysis. Section 4 presents the data to be used as well as the definition of our main variables. Section 5 shows the proposed methodology to follow as well as our empirical model. Section 6 presents the main results and Section 7 provides our main conclusions and policy recommendations. 2 Brief review on social capital Crime and social interactions have been studied in economics for quite some time. On this, it is imperative to account for the seminal paper by Glaeser et al. (1996) (and Glaeser et al. 2002) who detected a large number of social interactions in criminal behavior. These authors present a model where social interactions create enough covariance across individuals to explain the high cross-city variance of crime rates in the US. Additionally, their model provides an index of social interactions, namely the proportion of potential criminals who respond to social influences. This index suggests that the amount of social interactions is highest in petty crimes, moderate in more serious crimes, and almost negligible in murder and rape. Fairly related, there has been an extensive debate in the literature regarding social capital, what it actually is and how it can be measured. On this matter, Putnam et al. (1994) set up the basis for such considerations when analyzing the effects of social engagement. Ever since, social capital has been defined and measured in several ways by economic researchers. For example, Tabellini (2010) measured culture by indicators 2 of individual values and beliefs (such as trust and respect for others) in order to explore if it has a causal effect on economic development. Indeed, he finds that the exogenous component of culture due to history is strongly correlated with current regional economic development. Taking a different approach, Nannicini et al. (2013) investigate political accountability as a channel through which social capital may improve economic well- being. Authors find that punishment for political misbehavior is larger in districts with higher social capital, approximated by blood donations. Finally, Guiso et al. (2011) take a more theoretical perspective on social capital. They review previous research on its role, as they understand previous definitions were too vague or broad, leading to mixed results and interpretations. To solve such discrepancies, authors restrict their definition of social capital to one of civic capital, seen as a set of values and beliefs that help cooperation in a community. Very recently, Jackson (2017) provides a typology of social capital and considers seven forms: information, brokerage, coordination and leadership, bridging, favor, reputation, and community capital. On this matter, he defines community capital to be the ability to sustain cooperative behavior in transacting, the running of institutions, the provision of public goods, the handling of commons and externalities, and/or collective action, within a community. Certainly, social capital can play an important role in many economic spheres. Among these, economics of crime is a very relevant one, and a number of papers have focused on social capital as a driver of crime at a small geographical level (Hirschfield and Bowers 1997; Lederman et al. 2002; Buonanno et al. 2009; Ak¸comakand Ter Weel 2012). On this matter, results do not present a crystal clear conclusion. For example, while in Buonanno et al. (2009) authors do not find a clear effect of social capital on crime, Lederman et al.