With updates on the econometric debates on effects, and efficacy in targeting low income groups (3/30)
Minimal employment number impacts and minimal inflation impacts. But I am sure the resistance to having a greater share of income going to labor will continue.
From Goldman Sachs, “What to Expect from a Minimum Wage Hike” (3/25, not online), a survey of studies relevant to the debate over employment effects:
Source: Michael Cahill and David Mericle, “What to expect from a minimum wage hike,” GS Daily (3/25/2014).
Confirming the summaries of the literature contained in CBO and CEA (discussed in this post), most estimates are for quantitatively small impacts on employment, even when the estimates are statistically significant. It’s important to further recall that in the CBO assessment, the distribution of estimates spans positive impacts on employment (for some simple analytics of why this can occur in the short run, see this post; people averse to analytics should steer clear). Regarding the CBO midpoint estimate, the authors remark:
In our view, the CBO estimate is likely a bit toward the upper end of reasonable estimates, for two reasons. First, as Exhibit 3 shows, a large number of economic studies have found no statistically significant effect. Second, demand effects are likely to be particularly pronounced under current conditions in which considerable slack remains in the economy with the funds rate already near zero. As a result, raising the incomes of low-wage workers, who are likely to spend a larger share of their income, should provide a larger-than-usual offsetting boost.
That is, for the same reason fiscal policy has a greater impact at the ZLB and when slack exists,  boosts to labor income from an increase in the minimum wage can have a meaningful impact.
I’m teaching econometrics this semester, and it’s interesting to see how some of the prominent studies in the minimum wage literature dovetail with the more recent (not new any more) approaches to controlling for endogeneity — in particular the use of quasi-natural experiments, as in the Card and Krueger (AER, 1994) study of the New Jersey minimum wage increase. In that case, they used a differences-in-differences approach, examining how the gap between NJ-PA employment growth changed after the advent of the minimum wage. Card and Krueger found that there was a small employment increase in employment growth when NJ raised its minimum wage (borderline significant in many cases, and significant in others).
As the Note remarks upon, a number of states have recently implemented increases in their minimum wage rates; these changes constitute a series of quasi-experiments. Here is their assessment of the early outcomes:
… January’s state-level payrolls data failed to show a negative impact of state-level hikes. Relative to recent averages, the group of states that had hikes at the start of 2014 in fact performed better than states without hikes. While this is only one month’s data, it suggests that the negative impact of a higher federal minimum wage–if any–would likely be small relative to normal volatility.
The authors also conduct an event analysis of minimum wage increases on inflation on post-1990 data. They find no evidence of a discernable impact on PCE inflation. Their best estimate is 0.3 percent elevation in the price level by the end of the three year implementation of the minimum wage increase to $10.10.
The impact on employment is minimal, while wages will rise for many, thereby inducing an increase in the low-wage labor share. If we are concerned about affecting inequality, rather than mouthing platitudes, then the minimum wage seems a reasonable place to start.
Digression: Since I’m teaching the Card Krueger paper in my econometrics course, I have been reading the rebuttals and replies. In the Card-Krueger reply to the Neumark and Wascher paper, they discuss the latter’s use of an “interesting” dataset — with markedly different attributes from other data sets in use — originally compiled by the “Employment Policies Institute”. I find it remarkable how influential this think tank has been — see discussion here; link to IRS form 990 for interesting reading) (it gives “cozy” industry ties a new meaning). One of the most recent takes on the employment impact, accounting for spillover effects, is in Dube, Lester and Reich (REStat, 2010).
Update, 6:40PM Pacific: Neumark provides a critique of the DLR and other papers, in an Employment Policies Institute document (January 2013).
The Employment Policies Institute has an interesting blogpost observing that some of the 600 or so economists who signed the petition in favor of raising the minimum wage are “Specifically, at least 40 of the signers are specialists in or have done considerable work in the economics of Marxism or Socialism, or are affiliated with the “radical” study of economics.” (Full disclosure: I signed the petition, and I once took a course on Socialism from the famous leftist(!!!) Adam Ulam, so I must be on their list as well).
Update, 10:20PM Pacific: Professor Reich directs me to this paper which addresses critiques leveled by Neumark et al. (see Appendix B).
Update, 3/30 2:15PM Pacific: Recent work documenting the increasing target efficiency of the minimum wage, in this paper:
In this study I show that the target efficiency of the minimum wage improved between 1999 and 2013. In 1999-2001, 15.3% of the minimum wage benefits went to workers in poor families. By 2011-2013 this figure had risen to 18.8%. Nearly two-thirds of the improvement in target efficiency occurred during pre-recession years (1999-2001 to 2005-2007), and the balance of the improvement occurred since the onset of the Great Recession. The improvement in target efficiency during pre-recession years was entirely due to an increase in the share of minimum wage workers in poor families. Decreased income among near-poor minimum wage workers drove the majority of the increase in the share of minimum wage workers in poverty. Reduced teen employment, increased teen wages (relative to the minimum wage), and increased employment among poor low-skilled 20-29 year-olds also contributed.