Absence of conflict of interest.
Citation
Highlights
- The study’s objective was to examine the impact of increases in the state minimum wage on labor force participation.
- Using monthly data from the Current Population Survey (CPS), the author used an interrupted time series design to estimate the impact of increases in the state minimum wage on labor force participation. The authors used a statistical model to compare the labor force participation status of individuals before and after the implementation of an increase in their state’s minimum wage.
- The study examined the impact of state minimum wage increases on labor force participation by individuals’ age, sex, and race or ethnicity. For most age, sex, and race or ethnicity groups, the study did not detect statistically significant relationships between state minimum wage increases and labor force participation. However, the study did detect a statistically significant association between minimum wage increases and increased labor force participation for white men ages 26-30, Latino men ages 16-20, Latino men ages 36-40, and Latina women ages 51-55. The study also detected a statistically significant association between minimum wage increases and decreased labor force participation for Latina women ages 46-50.
- This study received a low causal evidence rating. This means we are not confident that the estimated effects are attributable to state minimum wage increases; other factors are likely to have contributed.
Intervention Examined
State-level changes in the minimum wage
Features of the Intervention
The author measures effective changes in state minimum wages. Effective changes in a state’s minimum wage can occur when statutory changes take effect, when there are increases in the federal minimum wage that exceed the state’s existing minimum wage, and in states where state law requires that the minimum wage be indexed to inflation.
Over the period 1990 to 2018, the author identified a total of 516 effective changes in state minimum wages. The median state experienced nine effective changes in the minimum wage over this period, and the average effective increase was $0.48.
Features of the Study
Using monthly data from the Current Population Survey (CPS) from 1990 through 2017, the author used an interrupted time series design to estimate the impact of increases in the state minimum wage on labor force participation.
The author observed 4,243,774 unique individuals ages 16-64 during their first four-month rotation in the CPS sample. Of these, 432,978 individuals experienced a change in the state effective minimum wage during their four-month rotation. At most, individuals are observed at four points in time (months) in the author’s sample.
The author used a statistical model with individual-level fixed effects to compare the labor force participation of individuals both before and after their state’s minimum wage change. The model also includes state by calendar month year fixed effects to adjust for state-level seasonal fluctuations in labor force participation.
Findings
Labor Force Participation
- For most age, gender, and race-ethnicity groups, the study did not detect a statistically significant relationship between state minimum wage increases and labor force participation.
- For White men ages 26-30, Latino men ages 16-20, Latino men ages 36-40, and Latina women ages 51-55, study findings suggested a statistically significant, positive association between minimum wage increases and labor force participation.
- For Latina women ages 46-50, study findings suggested a statistically significant negative association between minimum wage increases and labor force participation.
Considerations for Interpreting the Findings
To be eligible for a moderate causal evidence rating, CLEAR guidelines require that interrupted time series designs observe outcomes for at least three time periods both before and after the implementation of the intervention (i.e., at least six time periods in total). This requirement is designed to ensure that results are not biased by pre-existing trends before the intervention period and are stable over time in the post-intervention period. At most, the author’s data allows for the observation of individuals at four time periods.
When analyzing the impact of minimum wage increases on labor force participation, the author conducts statistical tests for fifty-six age, sex, and race or ethnicity subgroups. Performing multiple statistical tests on related outcomes makes it more likely that some impacts will be found statistically significant purely by chance and not because they reflect intervention effectiveness. The author did not perform statistical adjustments to account for the multiple tests, so the number of statistically significant findings might be overstated.
Causal Evidence Rating
The quality of causal evidence presented in this report is low because the author was not able to observe individuals for a sufficient period of time before and after the implementation of the intervention. This means we are not confident that the estimated effects are attributable to state minimum wage increases; other factors are likely to have contributed.