Welfare to work propensities: administrative record evidence

ABSTRACT

The study examines the role of home-to-new-job-hub distance on employment propensity using a unique data set compiled from integrated micro-level administrative records of work-eligible welfare recipients and earnings. Our empirical findings confirm the spatial mismatch hypothesis. Our home-to-new-job-hub distance measure is an innovative weighted measure incorporating both abundance of actual employment opportunities and geographic distance. Other unique contributions of this study include using point-to-point residence and job hub locational information, modelling with community controls and industry-specific analysis. This study also identifies policy implications in advancing employment prospects of inner-city residents receiving government assistance.

KEYWORDS:

• Job access
• spatial mismatch
• welfare to work

JEL CLASSIFICATION:

• I38
• R49
• J49

Acknowledgment

The study relied on data from Family Investment Administration, Maryland Department of Human Resources & Office of Workforce Information and Performance, Maryland Department of Labor, Licensing and Regulation. We deeply appreciate the important support from those two agencies. In addition, we feel deeply indebted to David Stevens and Regina Bento’s advice and a couple of Jacob France Institute staff members’ research support. The author accepts full and sole responsibility for the content of this study. Agreement or disagreement with the views expressed here should not be attributed to any other person or organization.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Those data were extracted under inter-agency agreement, subject to strict security and confidentiality clauses.

² They consist of 18,528 individuals across different communities.

³ This gives great-circle distances(d) between two points (O and D) on a sphere (i.e., the earth in this case) from their longitudes and latitudes (Y and X) using the radius of the earth at Washington DC, d = 2*r *arcsin(.

⁴ In Equation 1 the ‘i’ subscripts are suppressed to promote clarity and compactness.

⁵ In Equation 2 the ‘i’ subscripts are suppressed to promote clarity and compactness.

⁶ The Census Community Statistical Areas used here are clusters of neighborhoods identified and developed by the local Planning Dept. They combine Census Bureau geographies in a manner that matches the local area’s understanding of community boundaries and are used in social planning (See Baltimore City Health Department 2017).