Responding to high crime rates: what is the mix of prevention, insurance and mitigation individuals choose and its results?

In this paper we take first steps in providing parameters capturing some wider impacts of crime on individuals for the cost benefit analysis of investments in justice infrastructure. Statistical matching methods are applied to the HILDA dataset in the first broad economic analysis of how individuals respond to living in an acutely high crime environment and the consequences. Compared with individuals living in a postcode with a moderately high crime rate, the matching analysis shows individuals living in postcodes with acutely high crime rates are more likely to be a victim of a violent crime and spend less on insurance. They are also more likely to have a family member incarcerated even if they are no more likely to be incarcerated themselves. There are no significant differences in household incomes or full-time employment rates though those living in an acutely high crime rate postcode are more likely to be unemployed. Finally, although there are no significant differences in measures of mental health, individuals in acutely high crime rate areas spend less on health. This could be because they are less likely to have a long term health condition but could also reflect underinvesting in health care which may have negative consequences for health in the long term.