Re‐assessing the Spatial Mismatch Hypothesis – Federal Reserve Bank of Minneapolis

Report on Spatial Mismatch, Racial Earnings Gaps, and Sustainable Development Goals

Introduction and Methodology

This report analyzes new evidence on the effects of spatial mismatch on the earnings of Black workers in large U.S. cities, utilizing detailed location data from the Longitudinal Employer‐Household Dynamics (LEHD) database. The study’s objective is to assess whether geographic proximity to high-quality employment contributes to racial earnings disparities, a key concern for Sustainable Development Goal 10 (Reduced Inequalities). Workplaces are classified by the size of the pay premiums they offer, providing a metric for defining “good jobs” in the context of SDG 8 (Decent Work and Economic Growth).

Key Findings and Analysis

The research produced four primary findings with significant implications for understanding urban economic structures and inequalities.

1. Equitable Wage Premiums: Black workers were found to earn nearly the same average wage premiums as white workers within the same workplaces. This suggests that when Black workers access “good jobs,” the direct compensation structure does not exhibit a significant racial gap, a crucial insight for policies targeting SDG 8.
2. Proximity to Employment: Contrary to the traditional spatial mismatch hypothesis, the data indicates that in most cities, Black workers live closer to jobs—and specifically to “good jobs”—than their white counterparts. This challenges conventional thinking on urban planning and its impact on inequality, directly informing strategies for SDG 11 (Sustainable Cities and Communities).
3. Commuting Distances: Black workers typically commute shorter distances than white workers. This finding further complicates the narrative that geographic barriers and long commutes are a primary driver of economic disadvantage, impacting how we approach inclusive urban mobility under SDG 11.
4. Returns on Commuting: While longer commutes are correlated with higher average pay premiums for all workers, the elasticity with respect to distance traveled is slightly lower for Black workers. This indicates a subtle disparity in the economic returns on mobility, representing a nuanced barrier to achieving the objectives of SDG 10 and SDG 8.

Conclusion and SDG Implications

The central conclusion of this analysis is that geographic proximity to high-quality employment is unlikely to be a major source of the racial earnings gap in major U.S. cities today. This has profound implications for policy and future research related to the Sustainable Development Goals.

• Policy interventions aimed at achieving SDG 10 (Reduced Inequalities) and SDG 8 (Decent Work and Economic Growth) may be more effective if they focus on factors other than the physical location of workers relative to jobs.
• Urban development frameworks aligned with SDG 11 (Sustainable Cities and Communities) must recognize that simply ensuring residential proximity to employment may not be sufficient to close racial economic gaps.
• The findings compel a deeper investigation into other systemic barriers—beyond spatial mismatch—that perpetuate earnings disparities, in order to create more effective strategies for achieving sustainable and equitable economic outcomes for all.

Analysis of SDGs in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

   The article’s investigation into racial earnings gaps, job quality, and the geographic relationship between homes and workplaces in US cities connects to several Sustainable Development Goals (SDGs).

   • SDG 8: Decent Work and Economic Growth

     The article directly addresses this goal by focusing on employment and earnings. It analyzes the quality of jobs, defining “good jobs” based on the “pay premiums they offer,” and examines disparities in earnings between Black and white workers.

   • SDG 10: Reduced Inequalities

     This is a central theme of the article. The entire study is framed around understanding a key source of inequality: the “relative earnings of Black workers” and the “racial earnings gaps in major U.S. cities.” It investigates whether spatial factors contribute to economic inequality between racial groups.

   • SDG 11: Sustainable Cities and Communities

     The article’s methodology, which uses “detailed location information” to study “spatial mismatch,” commute distances, and the “geographic proximity to good jobs,” is directly related to urban planning and the structure of cities. It examines how the physical layout of a city impacts economic outcomes for its residents.

2. What specific targets under those SDGs can be identified based on the article’s content?

   The article’s focus allows for the identification of specific targets under the aforementioned SDGs.

   • Under SDG 8: Decent Work and Economic Growth

     • Target 8.5: “By 2030, achieve full and productive employment and decent work for all women and men… and equal pay for work of equal value.” The article’s analysis of “good jobs” (decent work) and the “racial earnings gaps” directly relates to the principle of equal pay and economic outcomes for different demographic groups.

   • Under SDG 10: Reduced Inequalities

     • Target 10.2: “By 2030, empower and promote the social, economic and political inclusion of all, irrespective of… race, ethnicity…” The study’s core purpose is to analyze the economic inclusion of Black workers by examining their earnings relative to white workers.
     • Target 10.3: “Ensure equal opportunity and reduce inequalities of outcome…” The article investigates a potential barrier to equal opportunity (spatial mismatch) and measures an “inequality of outcome” (the racial earnings gap).

   • Under SDG 11: Sustainable Cities and Communities

     • Target 11.2: “By 2030, provide access to safe, affordable, accessible and sustainable transport systems for all…” While not focused on transport mode, the article’s analysis of commute distance (“Black workers typically commute shorter distances than whites”) and the relationship between home and work locations (“Black workers live closer to jobs”) is fundamental to assessing the accessibility of employment opportunities within a city.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

   The article uses several quantitative measures that serve as direct or implied indicators for the identified targets.

   • For Targets 8.5 and 10.3 (Equal Pay and Reduced Inequality of Outcome)

     • Indicator: Racial Earnings Gap / Relative Earnings. The article explicitly states its goal is to develop “new evidence on the effects of spatial mismatch on the relative earnings of Black workers.” It measures this through “average wage premiums” and concludes by discussing the “racial earnings gaps.” This serves as a direct measure of economic inequality.

   • For Target 11.2 (Access to Transport/Jobs)

     • Indicator: Commute Distance. The article uses commute distance as a key variable, noting that “Black workers typically commute shorter distances than whites” and that “people who commute further earn higher average pay premiums.” This measures the physical distance workers travel to access employment.
     • Indicator: Geographic Proximity to Jobs. The study measures whether “Black workers live closer to jobs, and closer to good jobs, than do whites.” This indicator directly assesses the spatial relationship between residential areas and employment centers, which is a core component of job accessibility.

4. Table of SDGs, Targets, and Indicators

   SDGs	Targets	Indicators (as identified in the article)
   SDG 8: Decent Work and Economic Growth	8.5: Achieve full and productive employment and decent work for all… and equal pay for work of equal value.	Relative earnings and average wage premiums between Black and white workers.
   SDG 10: Reduced Inequalities	10.2: Empower and promote the social, economic… inclusion of all, irrespective of… race… 10.3: Ensure equal opportunity and reduce inequalities of outcome.	The racial earnings gap as a measure of inequality of economic outcome.
   SDG 11: Sustainable Cities and Communities	11.2: Provide access to… accessible… transport systems for all.	Average commute distance by race; Geographic proximity of residences to “good jobs”.

Source: minneapolisfed.org