Association for Public Policy Analysis & Management

Adult mental health is an important outcome in itself, and is likely to have ramifications for child skill development. It is therefore worth understanding how exactly neighbourhoods affect mental health, in order to glean local policy prescriptions for which neighbourhood characteristics matter most.

We will study mental health in the context of residential neighborhoods, using the findings from the Moving to Opportunity (MTO) study. The MTO randomly allocated families from high-poverty neighbourhoods to low-poverty neighbourhoods. Using the random assignment of households, existing research has found positive causal effect of a for moving to a better neighborhood on adult mental health. However, the positive impact of neighbourhood improvments is a “black box”: the mechanism of transmission is unclear. In this paper, we aim to decompose the MTO effects on adult mental health, to uncover which neighbourhood amenities matter in the determination of adult mental health. In particular, we will consider measures of neighborhood crime, distance to city center, as well as school quality.

To decompose these neighborhood effects, we develop an empirical strategy that exploits cross-city variation in the neighborhood choices available to voucher recipients in each city. We argue that, although voucher amounts were identical across cities, the impact of these vouchers on recipient household's choice sets varied with the city of implementation. This variation comes from two sources. First, cross-city differences in the effective price of different neighborhood attributes. Second, a subset of MTO recipients received vouchers that were only valid in low-poverty neighborhoods. Across cities, there are differences in the other characteristics of such eligible neighborhoods. Following this intuition, we develop an instrumental variables estimation strategy, which uses cross-city differences in MTO treatment effects to identify the effects of different neighborhood attributes.

The findings will suggest to researcher and policymakers which specific neighborhood attributes appear to contribute most to improvements in outcomes, allowing for better policy targeting.