class: center, middle, inverse, title-slide # Econ 414 - Urban Economics ## Neighborhood Effect ### Marcelino Guerra ### April 22, 2021 --- # Motivation * Sociologists and Economists are thinking about the causal role of neighborhoods/social contacts in shaping lives * Decisions of whether or not to buy a new product, commit a crime, smoke, among others, are often influenced by friends, neighbors, classmates, etc. * In the job-market, referrals from coworkers/professional contacts can be very important * One can model social interactions defining a set of individual agents, as well as connections among them * Peer effects in education * How the composition of a neighborhood shapes individual educational achievement/ability to find a job? * The mechanisms through which social interactions may affect behavior and outcomes are many: * Contacts facilitate the flow of information, opportunities for cooperation, influence tastes, among others --- # Bird's-Eye View of Chicago Neighborhoods <iframe src="maps/crime2.html" style="width: 1100px; height: 500px; border: 5px" alt=""> --- # The Enduring Effects of Violence <iframe src="maps/crime1.html" style="width: 1100px; height: 500px; border: 5px" alt=""> --- class: inverse,center, middle # Examples: Some Theories of Disorder & Deviance --- # Social Disorganization * Between 1833 and 1910, Chicago experienced a sharp increase in population: from 4,000 people to two million inhabitants. This generated a very strong cultural, ethnic, and religious heterogeneity among residents .pull-left[ * In that context, Robert Park and Ernest Burgess created a theoretical model to describe the urban development * The city was divided into concentric circles. The center concentrates on commercial activities, which grow continuously over time. With this expansion, part of the population decides to move, and some then residential spots are transformed into offices/factories * That deterioration of residential zone was called social disorganization ] .pull-right[] --- # Social Disorganization * The transition zone is always suffering from the invasion of commercial activities. The low-income residents stay there, and the high-income people move to the suburbs (residential zone). The transition zone is characterized by dilapidated buildings, heterogeneous population, and constant inflows of international migrants with low-income/low-education .pull-left[ * This idea sparked more work focusing on the urban environment as a causal factor of crime (see Shaw and Mckay) * There is a strong correlation between delinquency and other community characteristics * For instance, a neighborhood with residents frequently moving out has lower interactions between neighbors and lower **informal social controls** ] .pull-right[] --- # Differential Association & Social Controls .pull-left[ ### Social Controls * At some point in our lives, we think that an illegal behavior looks attractive/exciting. However, most of the population decide not to engage in illicit activities. According to the social control theory, there are many potential deviance restrictions: from disappointing family members to future career losses. * Travis Hirschi associates criminal conduct with social bonds such as personal attachment to others, believing in wider social values, etc. When those bonds are strong, there is a low probability of engagement in illicit activities. ] .pull-right[ ### Differential Association * In general, differential association/social learning theories argue that crime is a result of a process of assimilation and socialization that comes from interactions with people in the same social circle * Edwin Sutherland suggests that criminal behavior is something people learn during the communication/interaction with others close to them. Ronald Akers reformulated/expanded Sutherland's theory modeling delinquency as imitation - deviant behavior comes from observation and reinforcement (e.g., social approval) ] --- class: inverse,center, middle # Non-Experimental Approach: Collective Efficacy and Violence --- # Sampson et al. (1997) * You just saw that violence is not randomly distributed over space - the variations in rates of homicides across neighborhoods are very high * Of course, there are well-established correlations between neighborhood characteristics and violence such as racial composition, median income, educational attainment, etc. But why is that happening? * **What are the social processes that might explain the variation in crime rates?** * [Sampson, Raudenbush and Earls (1997)](https://science.sciencemag.org/content/277/5328/918) argue that informal mechanisms/social controls within the neighborhood have a major impact on violence * Social controls refers to the capacity of a group to regulate its members according to desired principles * For instance, a willingness to intervene to prevent public disorder acts within the neighborhood such as vandalism, disputes on the streets, among others * **This willingness to intervene comes from mutual trust and solidarity among the members of the community** --- # Sampson et al. (1997) * To measure informal social controls and social cohesion and trust, 8782 residents of Chicago were interviewed in 343 neighborhood clusters * Residents were asked about the likelihood that their neighbors could be counted on to intervened in different situations such as children skipping school and hanging out on a street corner, children showing disrespect to an adult, public services in the neighborhood facing a budget cut, among others * Respondents were also asked how strongly they agreed on statements such as "people in this neighborhood can be trusted", "people around here are willing to help their neighbors", etc. * Then, "collective efficacy" is a summary measure of those individual-level relations * Sampson and coauthors found that * Collective efficacy across neighborhoods is explained by concentrated disadvantage, immigration concentration, and residential stability * Collective efficacy, in turn, was highly correlated with rates of violence --- class: inverse,center, middle # Experimental Approach: Moving to Opportunity --- # MTO Experiment Design </br> * The Moving to Opportunity Experiment was designed to explore the effects of increasing the mobility of households from high-poverty areas * From 1994 to 1998, the US Department of Housing and Urban Development (HUD) enrolled 4,604 families (15,892 individuals in total) of five cities in the MTO experiment. The prerequisite was that families had children and resided in public housing or project-based Section 8 assisted housing in high-poverty census tracts * The cities were Baltimore, Boston, Chicago, Los Angeles, and New York * Families were randomized into three groups: * The experimental group - the ones who got the voucher that could be only be used in census tracts with 1990 poverty rates below 10 percent * The Section 8 group, which received regular housing vouchers without any relocation constraint * **The control group**, which received no assistance through MTO --- # MTO Experiment Early Results <br/> * Early research (up to 2013) found small effects on the economic circumstances and school achievement of the recipients. Adults reported improved mental health but no significant increase in job opportunities * For youths, test scores were unaffected by moves to new neighborhoods * Beneficial effects for female youth were offset by adverse effects for male youth * The conclusion was that changing the address of families do not changed their earnings, educational attainment or employment * Overall, the older research on the Moving to Opportunity experiment stated that **MTO did not generate sufficiently large change in living conditions to provide a reliable test of either neighborhood effects or the spatial mismatch** --- # MTO Experiment New Results * [Chetty et al. (2016)](https://www.aeaweb.org/articles?id=10.1257/aer.20150572) revisit the MTO experiment and focus on its impacts on children of different ages when their families moved to better neighborhoods * **Young children**: below age 13 at random assignment * **Older children**: age 13-18 at random assignment * The idea was to speculate about two opposite effects: exposure and disruption. Older children would face difficulties moving to new neighborhoods and spend less time absorbing the neighborhood effects. On the other hand, when children move young, there will be more years of exposure to a better environment (younger children had seven more years of exposure to better neighborhood) * As time passed, those youths entered the job market and started filling their tax returns. And the authors could link MTO data to federal income tax returns from 1996 to 2012 * The results point to an increase in college attendance, earnings and a reduction of single parenthood rates when moving to a better neighborhood at young age * In their mid-twenties, the youngsters' income was, on average, $1,624 higher compared to the control group * Consistent with earlier work, Chetty et al. (2016) found no impact of MTO on adults' outcomes