Living Wage Policies and Health: Quasi-experimental Evidence from the Community Tracking Study

In the 1990s and early 2000s, many US metropolitan jurisdictions (e.g. cities, counties) enacted living wage (LW) ordinances to help lift working families out of poverty. Adopted policies mandated wage floors that were substantially (>>50%) higher than prevailing minimum wages, and typically included provisions for wage updating (e.g. with inflation), health insurance coverage, and worker protection. Despite covering only a small percentage (<20%) of low-wage workers (typically those employed by contractors or businesses receiving economic assistance), evidence suggests these LW policies resulted in sizable declines in urban poverty and modest disemployment. Whether these economic effects translated into health improvements remains largely unknown. Analyzing the health effects of these prototypical policies uniquely informs the debate on the value of LW policies for the wellbeing of working families.

We used data from 4 rounds (1996-2004) of the Community Tracking Study (CTS) on a representative sample of adults (18-64) from 46 metropolitan sites across the United States (n=126,863). LW policies were enacted in 13 sites, varying in effective dates, mandated floors, coverage, enforcement, insurance offering, and geographic region. CTS rounds provided baseline and follow-up data spanning 1-3 years before and after LW enactment. We exploited the potentially exogenous timing and location of LW policies in a difference-in-difference-in-differences (DDD) design, where mean outcomes were contrasted across time (pre/post-LW), sites (with LW vs. without), and groups defined by poverty/skill level (proxied by education). This third source of variation captures LW effects on the group(s) likely receiving the most economic benefit, and controls for differential trends within sites. In logit models with DDD interactions, site- and individual-level controls, round and site fixed effects, site-specific trends, and site-clustered errors, we analyzed LW effects on poor self-rated health status, feeling depressed, frequently smoking, and having unmet healthcare needs.

We observed declines in all four outcome measures post-LW enactment, particularly in the near-poor, low-skilled (≤high school) group where the prevalence of depressive symptoms declined by 2.94 percentage points (SE: 1.47; P<0.1) and unmet care needs declined by 3.25 percentage points (SE: 1.46; P<0.05). These respectively represent 41% and 33% declines from pre-LW levels. Prevalence of poor health also declined 3-4 years post-LW by 10.28 percentage points (SE: 2.99; P<0.001). Decreases in depressive symptoms and poor health were generally sustained 5-6 years post-LW. Smoking rates, however, increased steadily over time, particularly in the poor, low-skilled group, who experienced a 39% increase (14.34 percentage points; P<0.05) 5-6 years post-LW. Having unmet healthcare needs also rebound 5-6 years post-LW. Our estimates were larger when policies covered economic assistance recipients, and with stricter enforcement. These findings were robust to multiple alternative specifications (e.g. using cleaner but restricted portions of the sample).

Our analyses suggest that LW policies have had sizable, sustained positive effects, particularly among those above the poverty line, on health status and depressive symptoms, and improvements in covering basic healthcare needs (though short-lived). Nevertheless, smoking rates seem to have increased, especially among the poor. These findings underscore the role economic policy plays as a modifiable determinant of population health and equity.