Description of original award (Fiscal Year 2008, $35,000)
This study will estimate the trajectories of crime rates of cities in seven similar counties that have seen dramatic population growth since World War II: Orange County, CA; the San Diego area; the Silicon Valley area; the Denver area; the Miami area; the Dallas area; and the Las Vegas area. Employing cities from counties at a similar 'developmental' stage will provide more appropriate comparisons of these trajectories of crime. A key test of this study is what effect the race and class composition of a city has on its trajectory of crime. Specifically, this study will tease out the effects of the overall level of these measures in cities, the effects of the distribution of these measures across households in cities, and the effects of the spatial distribution of these measures across neighborhoods in cities on city crime trajectories. This approach will allow disentangling competing perspectives: a political perspective argues that the overall inequality in a city affects the amount of crime by reducing the political will to address underlying disorder in the community. In contrast, the social distance/social disorganization model posits that the amount of inequality in neighborhoods is important for driving crime and its increase over time. Likewise, this study will test whether a simple measure of the level of poverty in the overall city affects crime, or whether highly disadvantaged neighborhoods with high levels of poverty have a nonlinear effect on crime (Sampson and Wilson 1995). This study will also attempt to disentangle two robust findings in the literature: studies using both cities and neighborhoods (such as census tracts) as the unit of analysis have found a positive relationship between racial/ethnic heterogeneity and crime rates. By accounting for the spatial distribution of such heterogeneity in cities, this study will test whether this effect occurs at the tract level or at the city-level. The study will use latent trajectory models to estimate these trajectories of city crime rates, as well as the determinants of these trajectories. Separate trajectories will be estimated over the 1970-80 period, 1980-90 period, 1990-2000 period, and from 2000-05. This will allow testing not only the effect of these structural measures on city crime trajectories, but also whether these effects have changed over this 35 year period.