Data scientists: Jose Hernandez and Valentina Staneva
DSSG fellows: Lamar Foster, Delaney Glass, Christopher Salazar, Mahader Tamene
Participant bios available here.
Project Summary: This project examines the minimum wage as a solution to income inequality – and one potential limitation to this approach. In 2014, Seattle was the first major city to pass a $15 minimum wage. Policymakers hoped that higher wages for low-paid workers would reduce inequality and poverty and make Seattle workers and their families better off.
However, the phase-in of Seattle’s $15 wage coincided with another economic jolt– the rapid influx of tens of thousands of high-paid technology workers. These new arrivals needed housing. Rental prices climbed rapidly, and large swaths of the city quickly gentrified.
As a result, low-wage workers were likely priced out of Seattle housing just as the raise to $15 took effect. While economists argue over the extent to which increasing minimum wages lowers *demand* for low-paid workers, our hot housing market might have also affected the *supply* of people looking for low-paid jobs.
This project will probe the hypothesis that the supply of low-wage labor dropped in Seattle over the years 2014-2016. Our DSSG team will work to understand residential relocation (moves) relative to places of employment (jobs) in the Puget Sound.
Questions include, did lower earners move out of Seattle faster than higher earners? How many workers earning at or near the minimum wage in 2014 moved out of the city over the subsequent years? Was that rate of relocation faster than for earlier cohorts of low-paid workers? How did low-wage workers’ commutes change? For each low-paid position in the city, how many workers of similar wage rates live within reasonable commuting radii?
We will use new and unique data, the Washington Merged Longitudinal Administrative Data (WMLAD) that we have created during the past five years with the help of several state agencies. WMLAD is the most comprehensive state-level geocoded administrative dataset assembled to examine employment and earnings outcomes.