Doctoral Dissertation Research in Economics: Residential Segregation and Neighbor-Based Informal Hiring

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).

Place-based job policies, such as informal neighborhood job search, are common tools to promote local job growth and reduce regional economic inequality. It is however not clear what makes a neighborhood good for job search. This research project will study one such mechanism---the use of neighbor networks in job search.

It explores which type of neighborhood---segregated or integrated, by race and by education---is more conducive to a successful job search. Disentangling the neighborhood effects on job search is difficult partly because people self-select into neighborhoods. The researchers use a policy experiment on refugee that were randomly assigned to neighborhoods throughout the country to overcome the self-selection problem.

The project can help shed light on how local social connections can be harnessed for effective resettlement and faster integration of these special immigrants into the labor market at the destination. Second, in answering this question, this research project will be a step towards understanding the relationship between neighborhood diversity and prosperity.

The results of this research can provide guidance on improving the functioning of labor markets, especially for those in segregated neighborhoods. The results could therefore help guide policies to reduce unemployment in low income segregated neighborhoods.

Identifying neighborhood effects in general is challenging because of residential sorting. Different individuals may choose to live in different places for reasons unobservable to the econometrician. To overcome this selection issue and obtain causality, the project will exploit a refugee settlement program that randomly dispersed refugees across the country, conditional on a set of demographic characteristics and housing availability.

This natural experiment introduces conditionally exogenous variation in the demographic composition at the neighborhood level for new and incumbent residents. The project will complement this natural experiment with granular geographical data that accommodate the resizing/redefining of neighborhoods. This flexibility and the policy-induced variation will allow causal estimation of the impacts of neighborhood segregation on the use of neighbor networks in job search.

In so doing, the research will help bridge two areas of economic literature – neighborhood effects and networks-based informal hiring – that heretofore have developed largely in isolation from each other. The results of this research will provide guidance on improving the functioning of labor markets, especially for those in segregated neighborhoods.

The results could therefore help guide policies to reduce unemployment in low income segregated neighborhoods.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.