A few weeks ago, I published a blog post about how incarceration rates affect our measurement of the relative economic conditions of Blacks in America. My claim was that the statistics are hiding a reversal of the painfully achieved advances secured between 1870 and 1960. Basically, my claim was that those who (in greater numbers) found their ways to a prison cell tended to be at the bottom of the income distribution, were more susceptible to be unemployed and had lower wages. This creates a composition effect whereby the official surveys cream-skim the top of black wage, income and employment distributions.
But, could this problem also affect our measurement of the effects of minimum wage? Let me be clear before you continue ahead, I am just asking this question because I could find no satisfactory answer to (or even mention of) this issue.
In recent times, minimum wage surveys have tended to find some gains in earnings for some workers following increases in minimum wage rates. Regardless of how you look at the prison population, it increases – albeit at a decelerating rate since the early 2000s – since the 1980s. Coincidentally, that starting point is also the point at which the famous Minimum Wage Study Commission was published (1981). That report basically cemented the point made by George Stigler (i.e. minimum wages are not desirable). That report surveyed the entire literature to summarize the amplitude of the effects. That literature encompassed articles written between the end of the Second World War and … well… 1981. If you look below at the graph, incarceration rates were more or less constant during that regime. Thus, if there were composition effects associated with surveys of wages, incomes and employment, they were more moderate than after 1981 when incarceration rates surged.
But, its also after 1981 that some papers began to find some positive effects of minimum wage increases. These studies took place under a growing composition problem in surveys of wages, incomes and employment. Take the famous Dube, Lester and Reich paper in the Review of Economics and Statistics who used data from 1990 to 2006. During that period, the male incarceration rate surged from 297 per 100,000 to 501 per 100,000. I understand that DLR used a time fixed effect method, but would that be sufficient to at least deal with the issue of shifting labour supplied (it won’t for the data bias issues described notably by Bruce Western)
If we assume that those who are plausibly affected by minimum wages (i.e. lower income individuals) are also those more likely to end up in jail in the United States, then there is clearly a bias. As they are dropped from the labor market (or as they join the prison population), they leave only the workers least affected by the minimum wage inside the samples. That is one possibility.
The other possibility – which is that surveys do not suffer from a large composition, but which is not mutually exclusive to that composition problem – is that the growing prison population represents a year-over-year reduction in the labor supply which offsets the effects of hikes in the minimum wage (or maybe even eliminates them entirely if the shift is big enough).
I have tried many variations of this google scholar research and went back to my copy of the Handbook of Labor Economics and my Economics of Inequality, Poverty and Discrimination (a book worth reading by the way) and I found very little on this point. Very few scholars have considered the possibility of this problem (which implies a shift of the labor supply curve concurrent with minimum wage hikes and a composition problem where those affected are simply not measured anymore). Yet, I feel like this is a defensible claim. In England, where some studies also show minimal effects or positive effects of the minimum wage, there has also been an increase in the prison population. In contrast, Canada – whose prison population is declining moderately (meaning that the labor supply is increasing as the minimum wage is being increased – the studies do tend to find the “conventional” result.
Am I crazy or is this a case of poor measurement? Personally, I feel that there must an answer, but please tell me I did not just stumble on this!