Iowa lawmakers denied raises to tens of thousands of women workers by preempting local minimum wages: Workers who would have been directly affected by increasing the Johnson, Linn, Wapello, Polk, and Lee County minimum wages

  Estimated county workforce Share of county workforce Directly affected Share of group directly affected Share of county’s affected workers
Johnson County ($10.10 by January 2017) 40,000 100.0% 10,100 25.3% 100.0%
Gender
Women 20,100 50.3% 5,700 28.4% 56.4%
Men 19,900 49.8% 4,400 22.1% 43.6%
Linn County ($10.25 by January 2019) 101,600 100.0% 18,400 18.1% 100.0%
Gender
Women 48,300 47.5% 9,900 20.5% 53.8%
Men 53,400 52.6% 8,500 15.9% 46.2%
Wapello County ($10.10 by 2019) 13,000 100.0% 2,200 16.6% 100.0%
Gender
Women 5,900 45.2% 1,500 25.1% 68.5%
Men 7,100 54.8% 700 9.5% 31.5%
Polk County ($10.75 by January 2019) 252,700 100.0% 38,000 15.0% 100.0%
Gender
Women 127,400 50.4% 22,100 17.3% 58.2%
Men 125,300 49.6% 15,900 12.7% 41.8%
Lee County ($8.20 by May 2017) 15,000 100.0% 2,100 14.3% 100.0%
Gender
Women 6,000 40.1% 1,300 21.0% 59.0%
Men 9,000 59.9% 900 9.8% 41.0%

Notes: Estimated workforce describes employed ACS respondents ages 16 and older for whom a valid hourly wage can be determined. Directly affected workers are those that would otherwise have had hourly wages below the specified wage value. Totals may not sum due to rounding.

Extended notes: The smallest geographic unit in the ACS public-use microdata does not uniquely identify Wapello or Lee Counties. The count and shares of affected workers in Wapello County were estimated from the population of workers in Davis, Van Buren, Wapello, Jefferson, Washington, Keokuk, and Mahaska counties, and then scaled to reflect those counties' share of employment in Wapello County using published Census Bureau data on employment in each geography. Similarly, the values for Lee County were estimated from data on workers in Louisa, Des Moines, Henry, and Lee Counties, then scaled using the the Lee County share of employment for those 4 counties.

Sources: Fisher 2016, IPP 2015, and Economic Policy Institute analysis of American Community Survey microdata, 2012–2015.

View the underlying data on epi.org.