The minimum wage, which has been in the news recently, seems to be part of two related but slightly different concerns. One is earnings inequality, which a higher minimum wage could potentially reduce. The other is poverty, which a higher minimum wage could also potentially reduce by helping a low-income worker afford a basic basket of goods. Putting aside the ability of the minimum wage to achieve either of these two goals (which economists actively debate), we still have these two different ways to measure the minimum wage and how it has evolved.
To quantify the purchasing power of the minimum wage, we can simply deflate the nominal value of the minimum wage. The red line shows the value of the federal minimum wage deflated by the PCE price index. We might be equally interested in whether the minimum wage pushes up the bottom of the wage distribution: How the minimum wage affects wage inequality is related to where it lands in the wage distribution. The blue line shows the fraction of hourly workers whose wages are at or below the minimum wage. This measures the value of the minimum wage by showing how many workers are directly affected by it.
The red line shows the minimum wage drifting up and down as its nominal value is eroded by inflation and as it is legislatively adjusted. The blue line shows it drifting downward consistently for the whole period as it fails to keep up with the growth in wages of most of the distribution.
How this graph was created: Search for “percent paid minimum wage” and add the annual series to the graph. Add the second series to the graph by searching for “federal minimum wage” and adding it as series 2. Then add “Personal Consumption Expenditures: Chain-type Price Index” by selecting “Modify existing series 2.” Finally, use the “Create your own data transformation” to apply the formula 100*a/b. (You need to multiply by 100 as the PCE index is normalized at 100.)
Suggested by David Wiczer.
View on FRED, series used in this post: