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min-wage ball n chain

An analysis by the Economic Policy Institute (EPI) is the basis for breathless claims by the Left that a substantial increase in the minimum wage would have “sweeping benefits for low-income families.” The EPI study purports to show that spending on public assistance will decline significantly with the increase in the minimum wage. Author David Cooper’s analysis is purely static, dressed up with a few linear regression equations relating participation in federal welfare programs to the wage distribution. However, his conclusion is preordained by the very design of the analysis, which relies on pooled data from public assistance programs across 2012 – 2014. This was a period over which wages were generally rising, but the federal minimum wage was constant (and only a few state minimum wages were increased).

It’s no surprise that higher wages are associated with a reduced likelihood of receiving needs-based public assistance in a cross section. That’s not quite the same as measuring the dynamic impact of an increase in the minimum wage. The adjustment to a higher wage floor involves more complex shifts in the structure of the economy, including higher prices, a higher incidence of small business failure and the substitution of automated systems for labor. And celebration would not be in order if the policy change prompted a deterioration in the employment prospects of the least-skilled workers, and it would.

There are a few gaping holes in the EPI analysis. One involves a data limitation whereby the distribution of public assistance by wage decile is related to individual workers or their families. It is one thing to say that most recipients of public assistance work for a living. It is quite another to say “Most recipients of public assistance work or have a family member who works.” Obviously, the latter does not imply the former, yet the analysis asks you to accept that the wage rates of family members who perform work during a year are the determining factor in welfare program participation, rather than the employment status and hours of all members of the household.

The analysis includes cross-sectional regressions relating the receipt of public assistance (yes or no) to wages imputed at the individual level, controlling for a complex function of age (polynomial terms), other demographic factors and part-time work status during the previous year. As stated above, the data are plagued by measurement issues. Furthermore (and this is a technical critique), linear regression is not an appropriate statistical methodology with a binary dependent variable. The author should have known better, but we’ll leave that aside.

Controlling for part-time status is intended to create a more reliable estimate of the effect of wages on program participation, as part-timers are more likely to earn low wage rates. But if hours matter in that way, then the regression is all the more suspect because hours of work are otherwise ignored (except in the imputation of wage rates).

The truth is that poverty is not a wage problem as much as a jobs and hours problem. A recent post by Angela Rachidi  of the American Enterprise Institute notes that “Only 11.7% of poor working-age adults worked full-time for the entire year in 2014.” Impoverished individuals who work full or part-time are concentrated in low-skilled occupations. Those are likely to be the same kinds of jobs for which impoverished non-workers might otherwise compete. Many of those jobs are at or near the minimum wage, but increasing the wage floor will only exacerbate the problem of unemployment or underemployment.

An increase in the minimum wage might help those workers who are able to keep their jobs. Unfortunately, if they remain employed, they are likely to suffer non-wage repercussions at their jobs. Therefore, the size of the net economic gain for those lucky enough to keep their jobs is open to question, though their measured income will rise. Still, keeping your job may be a big challenge.

The EPI analysis pays no heed to the negative employment effects of changes in the minimum wage. These stem from  employers’ efforts to control costs, hiring only when the skills and expected productivity of a worker exceed the cost. Growth and job opportunities are thus quashed by the intervention, including the gain in skills that comes with experience. If a business hikes price to defray higher labor costs, the negative impact on customers will induce them to buy less, reducing the need for labor. Another possible impact may be caused by the so-called “welfare cliff“, or the tendency of many program benefits to decline as income rises, which imposes a marginal tax rate on beneficiaries’ labor income. A higher wage floor might induce a worker to reduce hours to avoid the cliff, if their employer allows it, or it might induce another employed member of the same household to reduce hours.

Here is the extent of EPI’s treatment of the negative employment effects of a higher minimum wage, quoting the Congressional Budget Office (CBO):

CBO predicts that federal expenses would initially go down, but could later increase if the higher minimum wage has a significant negative effect on employment. On net, they conclude that ‘it is unclear whether the effect for the coming decade as a whole would be a small increase or a small decrease in budget deficits.’ It is important to note that the CBO’s ambiguity on this point is driven by their atypically high estimates of the probability of significant employment loss stemming from such an increase. If employment loss is insignificant (as most research on a minimum-wage increase of this magnitude indicates), the budget savings would surely dominate.” [Emphasis added]

The parenthetical, bolded statement is offered by Cooper without any support whatsoever, and it is incorrect. First, the evidence that the wage floor has negative employment effects “has been piling up” of late. “Living wage” advocates should not be encouraged by the recent experience of six large cities that have increased their minimum wages. Here is further information on the District of Columbia and WalMart’s reaction to a recent wage hike. The long-run effects of minimum wages are the most destructive, according to a recent paper authored by David Neumark and Olena Nizalova:

The evidence indicates that even as individuals reach their late 20’s, they earn less and perhaps work less the longer they were exposed to a higher minimum wage at younger ages. The adverse longer-run effects of facing high minimum wages at young ages are stronger for blacks. From a policy perspective, these longer-run effects of minimum wages are likely more significant than the contemporaneous effects of minimum wages on youths that are the focus of most research and policy debate.

Other recent work shows that minimum wage increases during the Great Recession increased unemployment among workers age 16 – 30 with less than a high-school education. Another paper finds that minimum wage hikes are bad anti-poverty measures, poorly targeted and regressive in their effects on the poor due to higher prices. A couple of previous posts on Sacred Cow Chips include many links to other work on minimum wages: “Major Mistake: The Minimum Opportunity Wage“, and “Unintended Consequences: Living (Without a) Wage“. Today, many jobs are at risk of automation, so the responsiveness of employers might be greater than ever.

In a strong sense, EPI’s findings and conclusion are beside the point for the many low-skilled workers whose jobs would be at risk, as well as those who might never be given legitimate employment opportunities under a higher wage floor. Those erstwhile workers and job seekers are generally the least skilled and most in need of experience. But EPI, and unthinking living wage advocates, are all too eager to signal the humanity and virtue of their favored policies, foolishly ignoring the negative and inhumane employment consequences.