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Beyond BLS

Beyond BLS briefly summarizes articles, reports, working papers, and other works published outside BLS on broad topics of interest to MLR readers.

March 2020

Employment barriers within low- and moderate-income communities

Summary written by: Lisa N. Huynh

Although the U.S. labor market has shown strong growth in recent years, low- and moderate-income (LMI) communities have not always experienced the benefits. The median incomes within LMI tracts are less than 80 percent of the overall median income in a particular area. Residents of poorer communities often lack the necessary resources, opportunities, and capabilities to find and maintain jobs with decent pay, so they are less likely to work than people living in higher income communities.

In “Why aren’t more people working in low- and moderate-income areas?” (Economic Review, Federal Reserve Bank of Kansas City, fourth quarter 2019), economist Kelly D. Edmiston examines prominent barriers to employment within LMI communities. The article is divided into three sections: The first section explains the difference in employment-to-population ratios within LMI and non-LMI communities. (The employment-to-population ratio is the share of a given population that is employed.) The second section reviews the survey responses that identify the obstacles to working within LMI communities. The third section compares the findings to explain why employment-to-population ratios differ between LMI communities and non-LMI communities.

The tract-level data used in this article come from the U.S. Census Bureau’s American Community Survey (ACS). The “communities” are defined as census tracts using residence-based employment measures. When the employment-to-population ratio from the 2017 ACS is compared, the ratio for non-LMI tracts was 75.1, whereas the ratio for LMI communities was 65.0. In this article, Edmiston looks at the ratio for the working-age population (18 to 64 years) and excludes individuals who are weakly attached to the labor force (e.g., retirees and full-time students).

To analyze why the employment-to-population ratios vary between the two communities, Edmiston uses the Federal Reserve Bank of Kansas City’s LMI Survey to identify common barriers to employment reported by LMI communities. From the survey, he identifies the following factors: job availability and pay; qualifications, education, and training; transportation; childcare and family issues; crime and substance abuse; housing instability; disabilities and mental and physical health; and public assistance programs.

Edmiston compares the statistics between LMI and non-LMI communities on the basis of the employment barriers from the survey results. He finds that nearly all of the categories of employment barriers are more prominent in LMI communities. For instance, an individual’s access to secure and stable housing can influence the ability to find or maintain a job. LMI tracts are 34 percent more likely to spend over 35 percent of their gross income on rent or live in a different place each year (10.3 percent in LMI communities, compared with 7.0 percent for non-LMI communities). In addition, people in LMI communities who have minimal access to jobs with relatively decent pay often struggle with finding employment opportunities. Aside from residents having different educational qualifications, Edmiston finds that residents within non-LMI tracts have job prospects closer to their homes. There are 0.73 workers per resident within LMI tracts, while non-LMI tracts have 1 worker per resident.

Among all the factors identified, LMI tracts tend to have more disadvantages and obstacles, and people living in these areas may find it less worthwhile to pursue employment opportunities. Edmiston finds that it is crucial to overcome these institutional barriers to improve employment prospects in LMI communities and restructure programs to incentivize more workforce participation.