For all those commenting on 'aren't more polluted areas just more criminal due to other factors", as far as I can tell the researchers examined crime rates for the same place and find correlation with whether there was more Ozone and PM 2,5 on a particular day or not. So they are not comparing clean air neighborhoods to highly polluted neighborhoods, but the same neighborhood on different days. https://www.sciencedai…
Well yeah, but they have to remove all the other factors like heat, wind and rain, which are correlated to air pollution. There is likely less violent crimes on rainy days, just because more people stay home. To do this properly, they would have to do a controlled experiment with people in rooms with or without air pollution. And measure how sanguine they get or something of that nature.
"Pollution and crime rates may have common correlations with location and time-varying unobservables. For example, PM2.5 or ozone levels and crime rates may be correlated with county-level covariates such as traffic density, population density, demographics, and industrial activity. Failing to control for such covariates will lead to biased estimates of γPM and γo.
Our identification strategy explicitly addresses omitted variable bias in several ways.
First, we show that endogeneity with respect to violent crimes and pollution can be addressed by including a series of high-dimensional fixed effects. In our primary specification, we include county-by-year-by-month-by-day of the week fixed effects to control for county level unobservables that are either constant over time, such as state and county-level policies, or that are time-variant, such as changes in population density, demographic composition, seasonal variation in pollution or crime, or changes in state and county-level policies that limit pollution or crime enforcement. These fixed effects also control for cyclical within-week, within-county variation in pollution and crime. Thus, our data allows us to compare for example, the effect of changes in pollution within a series of Mondays within a given county within a given month. We argue that changes in pollution across a series of Mondays within a county-month, conditional on weather controls, is random and thus exogenous to crime.
Second, crime has been shown to respond to changes in temperature, and temperature is generally correlated with air pollution (Field 1992; Jacob et al. 2007; Ranson 2014). Thus, failure to adequately control for temperature, and weather more generally, will lead to biased estimates. To address this concern, we include temperature and precipitation splines in our primary specification, we provide robustness checks with alternative functions of temperature, and in Section 5.3 we perform a series of tests to show that our results are not confounded by unaccounted for variation between temperature and air pollution. For example, we show that effect of PM2.5 on violent crime is larger at lower temperatures, opposite of the effect of temperature alone."