Association for Public Policy Analysis & Management

The paper evaluates a new labor law in Emeryville, CA, the Fair Workweek Ordinance (FWO), which aims to deter “on-call scheduling,” in which retail and food service employers shift the burden of decreased customer demand to low-wage workers by canceling or changing work schedules at the last minute. The FWO was passed in early 2017 and went into effect on July 1, 2017.

This paper will investigate 1) the impact of the FWO on workers’ schedule instability and 2) the effects of schedule instability on the well-being of low-wage workers and their families. We hypothesize that the FWO will decrease schedule instability and that such decreased instability will improving workers’ well-being and their families’ functioning.

We test these hypotheses using a daily diary methodology, gathering survey reports from respondents every day over one-month periods, for three waves. We use a new survey tool that we designed that utilizes basic SMS text messages to gather daily reports about low-wage workers’ schedules, including unanticipated changes in hours and shifts. Our data collection method allows us to obtain detailed daily information on workers’ schedules without recall bias.

Our team has gathered data from 96 low-wage workers with a child under age 6 in three waves: prior to FWO implementation (spring 2017); during “soft launch” enforcement (fall 2017); and during full enforcement of the law (spring 2018). The sample is balanced across: 1) retail and food firms that meet threshold local and global employment levels and are subject to regulation from the FWO and 2) otherwise similar control firms below those thresholds, which are exempt from the FWO.

At each wave, we measure daily schedule instability and daily family well-being outcomes every day for 30 days. We ask respondents whether they worked that day, and if so: when they started and stopped working and whether their hours were their originally scheduled hours. If not, they provide their originally scheduled hours. Thus, for each day that a respondent works at a given job, we calculate how their hours worked deviated from their originally scheduled hours, our key measure of schedule instability. Further, if respondents did not work at a given job on a given day, they are asked if they were originally scheduled to work and, if so, when they received notice that they would not work. Finally, for tipped jobs, we ask about daily earnings from tips, which, combined with the hours and wage data, enables us to calculate total earnings each day. Daily earnings volatility is a key characteristic of modern low-wage service jobs that has typically gone unmeasured.

We examine four outcomes on a daily basis: mood, sleep quality, parent-child interactions, and child behavior.

Analyses will examine whether:

1. Schedule instability has declined in regulated firms relative to unregulated firms, i.e. whether the legislation has had its intended effect on a relevant population of workers.
2. Decreases in population-level schedule instability lead to an effect on population-level family well-being predicted from within-family measurement in the pre-period.