A recent working paper from the National Bureau of Economic Research by the economists Jeffrey Clemens, Lisa B. Kahn, and Jonathan Meer should make us pause and question the wisdom of higher minimum wages. The economists explore how minimum wages affect the probability of employer-provided health coverage and find that a chunk of the increased earnings for workers who get higher wages will be offset by a reduction in employer-provided health coverage.
…[T]here’s a lot more to a job than wages. People want work that is meaningful or enjoyable. They might especially value safety, comfort, or flexibility. People can also get a lot of non-wage benefits like health coverage, scholarship opportunities, and paid vacation. Workers can (and do) “buy” these perks by accepting lower wages than they would require if the job weren’t as pleasant, meaningful, or safe or if the fringe benefits weren’t as good.
In short, workers don’t live on wages alone, and minimum wages might not change what workers get paid but rather how they get paid. Minimum wages mandate that cash wages take up a bigger part of employee compensation.
Clemens, Kahn, and Meer are limited by available data, so they can’t measure everything comprehensively. They narrow their focus to the relationship between minimum wages and employer-provided health coverage and find that for Very Low wage workers (e.g. food service), about 9% of increase in earnings due to a $1 per hour increase in the minimum wage is offset by the lower probability of employer-provided health coverage. For Low Wage workers (e.g. retail sales), its 16%. For Modest Wage workers ( clerks and food service supervisors), it’s 57%—which is unsurprising since workers with higher wages get a smaller bump from minimum wage increases.
When it comes to worker pay, total compensation must be considered, not just wages.
First, we sought to understand the sources of the decline in teen employment that began around 2000—in particular, the decline in employment among those age 16–17—as well as, more generally, changes in teen employment and school enrollment behavior. Second, we wanted to explore the implications of these changes for human capital, given that the decline in employment consisted of fewer teens in school and employed, and more teens in school exclusively, suggesting a greater focus on schooling. We have considered three explanatory factors: (1) a rising minimum wage that could reduce employment opportunities for teens and potentially also increase the value of investing in schooling; (2) rising returns to schooling; and (3) increasing competition from immigrants that, like the minimum wage, could reduce employment opportunities but also raise the returns to human capital investment.
With respect to the first question, we find some evidence of the expected effects of all three explanatory factors on teen employment and school enrollment—and in particular for those age 16–17. However, in terms of explaining changes in the behavior of teens age 16–17 since 2000, the role of the minimum wage is predominant. Increases in the returns to schooling appear to have played almost no role, and immigrant competition a minor role. In contrast, our simulation results suggest that minimum wages explain about a quarter of the shift, since 2000, from being simultaneously employed and enrolled in school to being exclusively enrolled in school.
Turning to the second question, our examination of the longer-term effects of these three factors uncovers no evidence that higher minimum wages, which underlie teens shifting from combining work and schooling to being in school exclusively, led to greater human capital investment. If anything, the evidence is in the other direction. Thus, it is more likely that the principal effect of higher minimum wages in the 2000s, in terms of human capital, was to reduce employment opportunities that could enhance labor market experience. Further, we find no evidence of net-positive human capital effects of rising returns to schooling or increased immigration in this period, even though these latter two factors—more so immigration—played at least a minor role in the changes in teen employment and school enrollment.
Based on this evidence, then, it appears that the changes in teen labor market and schooling behavior since 2000—stemming in part from adverse effects of minimum wages on employment opportunities, and to a lesser extent from immigration—did not reflect greater human capital investment that would raise future earnings. It is not clear that immigration delivered any other short-term benefits to teens. In contrast, some teens surely benefited directly in the short run from higher minimum wages. But there appear to have been either no effects or adverse effects on longer-run earnings for those exposed to these higher minimum wages as teenagers (pgs. 47-48).
Numerous studies over the years have demonstrated how ignorant the general public is regarding political matters. This systemic ignorance and misinformation in turn warps the public’s policy preferences. AEI’s Mark Perry points out another example of public ignorance: corporate profits. He writes,
When a random sample of American adults were asked the question “Just a rough guess, what percent profit on each dollar of sales do you think the average company makes after taxes?” for the Reason-Rupe poll in May 2013, the average response was 36%! That response was very close to historical results from the polling organization ORC International polls for a slightly different, but related question: What percent profit on each dollar of sales do you think the average manufacturer makes after taxes? Responses to that question in 9 different polls between 1971 and 1987 ranged from 28% to 37% and averaged 31.6%.
How do the public’s estimates of corporate profit margins compare to reality? Not surprisingly they are off by a huge margin. According to this NYU Stern database for more than 7,000 US companies (updated in January 2018) in many different industries, the average profit margin is 7.9% for all companies and 6.9% for more than 6,000 companies excluding financials…Interestingly, for nearly 100 industries analyzed by NYU Stern, there’s only one industry that had a profit margin as high as 36% – and that was tobacco at 43.3%. The next highest profit margin was 26.4% for financial services, but more than 72% of industry profit margins were single-digits and the median industry profit margin is 6%.
“Big Oil” companies make a lot of profits, right? Well, that industry (Integrated Oil/Gas) had a below-average profit margin of 5.6% in the most recent period analyzed, and separately, the Production and Exploration Oil/Gas industry is losing money, reflected in a -6.6% profit margin. For the general retail sector, the average profit margin is only 2.3% and for the grocery and food retail industry, it’s even lower at only 1.6%. And evil Walmart only made a 2.1% profit margin in 2017 (first three quarters) which is less than the industry average for general retail, possibly because grocery sales now make up more than half of Walmart’s revenue and profit margins are lower on food than general retail. Interestingly, Walmart’s profit margin of 2.1% is actually less than one-third of the 6.5% the average state/local government takes of each dollar of Walmart’s retail sales for sales taxes. Think about it – for every $100 in sales for Walmart, the state/local governments get an average of $6.50 in sales taxes (and as much as $10.12 in Louisiana and $9.45 in Tennessee, see data here), while Walmart gets only $2.10 in after-tax profits!
Perry concludes, “The public’s complete overestimation of how much companies earn in profits as a share of sales explains a lot…The general public that believes in the fantasy-world of unrealistically, sky-high 36% profit margins would naturally think companies are just being greedy and stingy when they don’t pay higher “living wages” and have to be forced to do so through minimum wage legislation. If the average person could realize that a 36% profit margin isn’t even close to reality and that the typical, median firm has a profit margin of only less than 8% or almost 30 percentage points below what the public thinksis a normal profit margin, then hopefully the average person would become a little more realistic about how the business world operates. Companies aren’t being stingy when they pay competitive wages, they’re just trying to survive on what are sometimes razor-thin profit margins, in a competitive environment where there’s not a large margin of error.”
Minimum wage laws in the US typically institute a schedule of increases rather than one-off hikes. After the corresponding legislation is passed, the minimum wage increases in steps over several years to the final value set in the law. Especially the later steps are known long in advance, and firms may increase prices in anticipation of higher future minimum wages. To take this possibility into account, we estimate the minimum wage elasticity of grocery prices at the time future increases become known and when they are implemented. We collect legislation dates for every increase, and show that these dates capture a salient event at which people get information about future minimum wage hikes. We combine this data with monthly store-level price indices for about 2000 grocery stores during the 2001–2012 period, which we construct from grocery store scanner data. We find robust significant effects on grocery prices at the time of legislation, but not at the time of implementation of minimum wage increases. Our baseline estimate of the overall minimum wage elasticity of prices in grocery stores is about 0.02. The average minimum wage legislation increases binding minimum wages by about 20% over several years. Our estimates suggest that such an increase raises grocery prices by 0.4% over three months around the time legislation is passed, long before the final level of the new minimum wage is implemented. During these three months, price inflation in grocery stores almost doubles relative to its average rate.
In a second step, we estimate the minimum wage elasticity of grocery store cost using county-sector level data from the Quarterly Census of Employment and Wages and sectorlevel data on grocery stores’ labor cost share. We find that the minimum wage elasticity of costs is about the same size as the minimum wage elasticity of prices. Our results thus suggest a full pass-through of all future cost increases at the time minimum wage legislation is passed. This forward-looking behavior is qualitatively consistent with the predictions of pricing models with nominal rigidities.
Finally, we calculate the welfare cost of grocery stores’ price response based on consumption data from the Consumer Expenditure Survey. We show that low-income households are disproportionately affected, since they spend a larger share of their expenditures at grocery stores. In particular, the price response of grocery stores alone undoes at least 10% of the nominal income gains of the poorest households. For other income brackets, this number ranges between 3% and 13%. Overall, the price response reduces the nominal gains for all households, but also makes minimum wage increases less redistributive in real than in nominal terms (pgs. 1-2).
In short, the cost of minimum wage increases are passed on to consumers. What’s worse, poor consumers are hurt the most.
A new working paper provides some interesting results about the interplay between immigration and minimum wage laws:
Our first empirical strategy exploits the non-linearity of the minimum wage across U.S. States to investigate the role played by the minimum wage in shaping the impact of immigration on the wages and employment of competing native workers. We find that on average, immigration has relatively small detrimental effects on the wages and employment outcomes of competing native workers. The main contribution of this study is not to provide yet another estimate of the wage and employment responses to immigration but, rather, to investigate the role of minimum wages in determining such responses. Indeed, we show that the labor market effects of immigration are heterogeneous across U.S. States characterized by different levels of minimum wage. In particular, we find that the impact of immigration on natives’ labor market outcomes is more negative in states where the effective minimum wage is relatively low. In contrast, sufficiently high minimum wages tend to protect native workers from any adverse wage or unemployment effects of immigration.
Our second empirical methodology uses a difference-in-differences approach. We use cross-state differences in the impact of federal minimum wage adjustments on state effective minimum wages. Over our period of interest, the successive rises in the federal minimum wage have fully affected the states where the effective minimum wage is equal to the federal one (the treatment group), with no impact in high minimum wage states (the control group). Thus, we can estimate the difference between the labor market impact of immigration before and after the federal policy changes between the treatment group and the control group. Our estimates indicate that the detrimental impact of immigration on natives’ wages and employment have been mitigated thanks to the federal minimum wage increases that occurred in three installements between 2007 and 2010.
Taken together, our results indicate that high minimum wages tend to protect employed native workers against competition from immigrants. This may come at the price, obviously, of rendering access to employment more difficult for outsiders such as the unemployed natives and new immigrants, a question we cannot investigate given the limits of our data (pg. 51-52).
Interesting, but not surprising. Case in point, consider my summary of Thomas Leonard’s Illiberal Reformers:
The book meticulously demonstrates that the progressive impulse toward inflating the administrative state was driven largely by self-promotion (i.e, the professionalization of economists), racist ideologies (i.e., the fear of race suicide), and an unwavering faith in science. Not only should the “undesirables” of the gene pool be sterilized, but they should be crowded out of the labor force as well. Those considered “unfit” for the labor market included blacks, immigrants, and women. In order to artificially raise the cost of employing the “unfit,” progressives sought to implement minimum wage (often argued to be a “tariff” on immigrant labor), maximum hours, and working standard legislation.
Other studies show that an increased minimum wage causes firms to incrementally move toward automation. Now, this too could be seen as a trade-off: automation and technological progress tend to make processes more efficient and therefore increase productivity (and eventually wages), raising living standards for consumers (which include the poor). Nonetheless, the point is that while unemployment in the short-term may be insignificant, the long-term effects could be much bigger. For example, one study finds that minimum wage hikes lead to lower rates of job growth: about 0.05 percentage points a year. That’s not much in a single year, but it accumulates over time and largely impacts the young and uneducated.
Now comes the new NBER working paper, “People Versus Machines: The Impact of Minimum Wages on Automatable Jobs” by Grace Lordan and David Neumark (bold is mine):
“Based on CPS data from 1980-2015, we find that increasing the minimum wage decreases significantly the share of automatable employment held by low-skilled workers. The average effects mask significant heterogeneity by industry and demographic group. For example, one striking result is that the share in automatable employment declines most sharply for older workers. An analysis of individual transitions from employment to unemployment (or to employment in a different occupation) leads to similar overall conclusions, and also some evidence of adverse effects for older workers in particular industries. … Our work suggests that sharp minimum wage increases in the United States in coming years will shape the types of jobs held by low-skilled workers, and create employment challenges for some of them. … Therefore, it is important to acknowledge that increases in minimum wage will give incentives for firm to adopt new technologies that replace workers earlier. While these adoptions undoubtedly lead to some new jobs, there are workers who will be displaced that do not have the skills to do the new tasks. Our paper has identified workers whose vulnerability to being replaced by machines has been amplified by minimum wage increases. Such effects may spread to more workers in the future.”
Three things: First this study is a great companion piece to a recent one by Daron Acemoglu and Pascual Restrepo analyzing the effect of increased industrial robot usage between 1990 and 2007 on US local labor markets: “According to our estimates, one more robot per thousand workers reduces the employment to population ratio by about 0.18-0.34 percentage points and wages by 0.25-0.5 percent.”
Second, Lordan and Neumark note that minimum wage literature often, in effect, ends up focusing on teenager employment as it presents aggregate results. But that approach “masks” bigger adverse impacts on some subgroups like older workers who are “more likely to be major contributors to their families’ incomes.” This seems like an important point.
Third, some policy folks argue that it’s a feature not a bug that a higher minimum wage will nudge firms to adopt labor-saving automation. (Thought not those arguing for robot taxes.) The result would be higher productivity and economic growth. But perhaps we are “getting too much of the wrong kind of innovation.”
One of the explanations for the decline of the labor share has been an increase in productivity that has outpaced an increase in real wages, with several studies attributing half the decline to this trend.
This increase in productivity has been driven by technological progress, as manifested in a decline in the relative price of investment (that is, the price of investment relative to the price of consumption).As the relative price of investment decreases, the cost of capital goes down, and firms have an incentive to substitute capital for labor. As a result, the labor share declines.
The decline in the labor share that results from a decline in the relative price of investment has contributed to an increase in inequality: A decrease in the cost of capital tends to induce automation in routine tasks, such asbookkeeping, clerical work, and repetitive production and monitoring activities. These are tasks performed mainly by middle-skill workers.
Hence, these are the segments of the population that are more affected by a reduction in the relative price of investment. The figure below displays the correlation between changes in the advanced economies’ labor share and their Gini coefficients (which measure income inequality).
The Fed concludes,
Technological progress promotes economic growth, but as the findings above suggest, it can also reduce the welfare of a large part of the working population and eventually have a negative effect on economic growth.
An important role for policymakers would be to smooth the transition when more jobs are taken over by the de-routinization process. At the end of the day, technology should relieve people from performing repetitive tasks and increase the utility of our everyday lives.
Ready for the second minimum wage paper in a row today? A new working paper looks at the Danish experience, where the minimum wage increases drastically when individuals turn 18 years old. So what happens when individuals become adults? “Danish minimum wages cause an increase in average wages of 40 percent when workers reach age 18. This increase in wages causes a 33 percent decrease in employment when workers turn 18, almost all of which comes from job loss” (pgs. 30-31).
In a section of the paper that adds important new evidence to the debate, the authors look at the consequence of losing a job at age 18. One year after separation only 40% of the separated workers are employed but 75% of the non-separated workers are employed. Different interpretations of this are possible. The separated workers will tend to be of lower quality than the non-separated and maybe this is correlated with less desire to have a job. Without discounting that story entirely, however, the straightforward explanation seems to me to be the most likely. Namely, the minimum wage knocks low-skill workers off the job ladder and it’s difficult to get back on until their skills improve.
the Seattle Minimum Wage Ordinance caused hours worked by low-skilled workers (i.e., those earning under $19 per hour) to fall by 9.4% during the three quarters when the minimum wage was $13 per hour, resulting in a loss of 3.5 million hours worked per calendar quarter. Alternative estimates show the number of low-wage jobs declined by 6.8%, which represents a loss of more than 5,000 jobs. These estimates are robust to cutoffs other than $19. A 3.1% increase in wages in jobs that paid less than $19 coupled with a 9.4% loss in hours yields a labor demand elasticity of roughly -3.0, and this large elasticity estimate is robust to other cutoffs.
…Importantly, the lost income associated with the hours reductions exceeds the gain associated with the net wage increase of 3.1%…[W]e compute that the average low-wage employee was paid $1,897 per month. The reduction in hours would cost the average employee $179 per month, while the wage increase would recoup only $54 of this loss, leaving a net loss of $125 per month (6.6%), which is sizable for a low-wage worker (pgs. 35-36).
According to The Washington Post, economist David Autor described the study as one “that is likely to influence people,” calling it “very credible” and “sufficiently compelling in its design and statistical power that it can change minds.”
Do minimum wage increases cause low-wage workers to commute out-of-state more? A brand new paper in Regional Science and Urban Economics answers in the affirmative. According to the Cato Institute’s blog,
[Terra McKinnish] seeks to exploit the variation in minimum wage rates between states and the compressing effect of the 2009 federal minimum wage increase to analyze whether a relative increase in a minimum wage within a state led to more commuting into that state to work for under 30s or more commuting out of the state to work.
…McKinnish employs difference-in-differences techniques to try to find the answer, using commuting records of people earning both low and modest hourly rates to control for other factors which could influence commuting, such as the health of the economy.
Upon doing all this, three key findings arise from her work:
Prior to the 2009 federal minimum wage increase, there is no evidence that low-wage workers commuted at higher rates (relative to moderate-wage workers) to neighboring states with a higher minimum wage.
After the federal minimum wage increase, low-wage workers modestly increased out-of-state commuting out of states most affected by the federal minimum wage increase.
Moderate-wage workers reduced the rate at which they commuted out of states most affected by the federal increase following the rise in the rate (consistent with the idea that increasing minimum wages leads to employers replacing low productivity workers with higher productivity ones).
In short, “this study is further evidence to support the Econ 101 view of minimum wages.” Or, as the paper itself highlights, these “[r]esults are consistent with a disemployment effect of minimum wage increases.”
A brand new working paper looks at 2 million hourly wage workers from over 300 companies in order to determine the effects of minimum wage changes. As reported,
For the first time, a group of researchers at Washington University in St. Louis used a big-data approach to determine the effects of minimum-wage changes on business. Two professors and two doctoral candidates from the Olin Business School processed wage data on more than 2 million hourly workers from across the country over a six-year period. The results? There are winners and losers.
…“We found existing minimum-wage employees benefit from minimum-wage increases,” [co-author Radhakrishnan] Gopalan said. “Their wages go up, and they are no more likely to lose their jobs as compared to their counterparts in adjacent states. But following state minimum-wage hikes, companies are reluctant to hire new low-wage employees. In the one year following the wage hike, they increase the proportion of higher-wage (read: higher-skilled) employees and reduce the proportion of low-wage employees.”
…“For an area experiencing fast growth, having a high minimum wage will be a bad deal for the new entrants as they might have a tougher time finding a job. On the other hand, if you’re in an area whose population is not growing very fast, then raising the minimum wage will definitely benefit your existing low-wage employees, and the number of new employees who are hurt will be a minimum. Optimal policy will also depend on the industry composition of the establishments in the local economy.”