Understanding Recent Minimum Wage Increases - Oren Levin-Waldman

RESEARCH REPORT

Regional Labor Review (Spring/Summer 2018)

Understanding Recent Minimum Wage Increases in the New York Metro Area

by Oren Levin-Waldman

The federal minimum wage was last raised in 2007. Over the decade since, inflation has eroded its purchasing power by nearly 18%. The recent response in many states – 18 more, as of January 2018 – has been to raise their own state wage floors. Both New York and New Jersey have phased in minimum wage hikes since 2014.

New York, like some others, raised the minimum by different amounts in large urban areas than in the rest of the state: in NYC, it just rose among large employers to $13; in Long Island to $11; elsewhere to $10.40.

Although Connecticut did as well, it had been raising its minimum wage all along.

A $15 hourly wage floor will be set in New York City by 2020 and two years later in Long Island and Westchester County. After that it is to be indexed to a cost-of-living measure. Still, these are legislated increases, and to date New Jersey’s minimum wage, while lower than in New York and Connecticut, is the only minimum wage in the tristate area to be indexed to the Consumer Price Index. Connecticut’s minimum is still a legislated increase, although it does increase to one-half of one percent above the federal minimum wage if the federal minimum wage becomes either equal to or higher than the state’s minimum wage. So, the Connecticut state minimum wage is always higher than the federal floor. Nevertheless, current rates are still less than half of average annual earnings ($25.50), which historically is what Congress strived to keep the federal minimum wage at. Were that still the case, the federal minimum wage would be $12.75.

These differences are by no means trivial. If we understand the statutory minimum wage as a reference point for the larger low-wage labor market, that $12.75 an hour is most likely the wage being earned by the

“effective” minimum wage population ---- those workers that earn in wage ranges around the statutory minimum. The difference between the statutory minimum and effective minimum wage populations is also an important distinction because the effective minimum wage speaks to a larger segment of the labor market --often up to 18 percent rather than the less than 3 percent earning the statutory minimum. Instead of a minimum wage labor market comprised mostly of teenagers as many critics allege, the effective minimum wage labor market is comprised mostly of single women who are raising children. Although the minimum wages in the tristate area are low, especially when compared to Massachusetts and California, these increases will nonetheless bring about an increase in these states’ effective minimum wages. Nevertheless, these differences don’t really tell us anything about why these states may have felt compelled to raise their wages when the federal government has been unable to.

In this paper, I look at microdata from the Integrated Public Use Microdata Series (IPUMS) Current Population Survey (CPS) for the tristate area in an effort to discern reasons why these states felt a need for increases. It would no doubt be convenient to dismiss this question with the pat answer that all three states are blue states that are overwhelmingly Democratic, and therefore they were naturally more inclined to do so.

Although New Jersey is considered a blue state, its Republican governor was no fan of raising the minimum wage and it only increased following a legislative override of his initial veto. Of course, it is common knowledge that the tristate area, especially in the metro area around New York City, is an area where the cost of living is high, and certainly higher than most regions in the country. But an issue that affects primarily lowwage workers, many of whom do not participate in elections, is not likely to sway many in the legislature to take notice that they are unable to make ends meet. Rather, it is more likely the case that certain demographic and labor market changes perhaps made it a foregone conclusion that these states would have no choice but to raise their minimum wages.

What my data analysis here shows is that labor market changes along with other demographic changes

only made it a foregone conclusion that wages would have to be pushed with a nudge from policymakers. The types of jobs that have been lost are not coming back and those that are replacing them are not paying as much as the jobs lost. Moreover, institutions like unions that have served to bolster wages have also overall been in sharp decline, although the decline in New York has been considerably less than elsewhere.

The textbook story of competitive labor markets expects workers’ pay to mainly reflect their productive value to employers. Economic change that results in the replacement of good-paying manufacturing jobs with low-wage service jobs that don’t require much skill means that wages will be forced down at the bottom, especially if there is a already an oversupply of low-skilled workers. There is no question that the data examined here bears this out, but there is clearly more to the story.

Wages weren’t historically higher in postwar U.S. manufacturing because there was an under-supply of skilled workers; rather they were higher because manufacturing workers were unionized and this labor market institution played a significant role in building the middle class.

Institutional economists will argue that low wages are not the product of natural market forces, but rather of asymmetrical power relations between employers and workers. Marxists take this argument a step further and maintain that capitalism is at root a system of control, and because workers have no other choice but to work in order to survive, they are effectively being oppressed and exploited by their employers. The data, however, suggests that the decline in institutions most probably exacerbates the power imbalance between employers and workers, and may even exacerbate the exploitation. But the decline in institutions also suggests that, in a climate of increasing globalization and rising inequality, a legislative response in the form of higher wages may be the only remedy left, short of the revolution that Marxists would like to see.

Conventional & Rival Views The standard economics textbook view is critical of legal wage floors. This view is based on a model of

competitive markets in which market-clearing equilibrium wages are achieved when the demand for labor is exactly equal to the supply of labor. In such a market, there is no such thing as unemployment because wages either rise or fall until labor demand matches supply. A wage floor such as a mandated minimum wage prevents the cost of labor from dropping below the legal minimum. Therefore, a minimum wage higher than the equilibrium wage will result in fewer workers being hired than are willing to work, with the end result being unemployment. In the competitive markets assumed by the mainstream model, each worker receives the value of his or her marginal revenue product, which is the market value of the output resulting from an increase in a unit of labor. If adding an additional worker results in a rise in the firm’s total output, once it’s sold the firm’s sales revenue will rise as well. An effective minimum wage, then, will do one of two things: it will either result in the layoff of those workers whose value is less than the minimum, or it will result in an increase in productivity among low-efficiency workers.1 As the cost of labor increases (due to a mandated minimum higher than the market-clearing wage), firms will hire fewer workers and employment will decrease. Therefore, a policy that artificially raises wages to help some at the expense of others is simply inefficient because an economy forced to lay off workers due to artificially inflated wages isn’t utilizing its full labor capacity. Even if there is some outward appearance of benefit to be derived from an increase in the wage floor, there will invariably be a cost to be borne whether in the form of job loss, lost opportunity for jobs, lost benefits, higher public assistance costs, or increased output per man hour — the demand for higher productivity.

The standard model, however, has not been without its critics. First and foremost, the real-world labor market is by no means monolithic; rather there are multiple labor markets. In the real world, the minimum wage will affect people in different job sectors differently.2 More to the point, the model assumes the worker to be the source of his/her own employment based on the wage demands that s/he makes. The model of perfect competition assumes the minimum wage to be irrelevant because the source of low wages is not a function of distorted power, but the failings of individuals. Their skills are simply not worth more than the low wages they

have been receiving. Because the locus of the model is on the individual, it tends to negate structural variables that may affect individual behavior.

In the standard model, there is little difference between labor and other goods and services. Both firms and individual workers in competitive markets are considered to be “wants traders.” For the firm, the purchase of labor is a matter of preference, and so too is the sale of that labor to the firm for those workers. If both are wants traders, then both enjoy equal bargaining power.

Against this voluntary-exchange view there has long been a contrary position: capitalist markets are about disciplining workers. Because workers don’t have the means to live without being dependent on others for income through work, they are forced to conform to the dictates of those who control the means of production or face uncertainty through unemployment and eventual poverty. This means that as income inequality increases, those at the bottom of the distribution become more dependent and ultimately more vulnerable. As such, their rights as workers also diminish. 3 Workers, however, often have no choice but to sell their labor services, which only makes them needs traders.

The resultant pay exploitation may also have psychological impacts on motivation and productivity. For example, Kristian Braekkan and Victoria Sowa argue that wage cuts threaten what they call “psychological contracts:” the expectations workers have based on the employer’s explicit and implicit promises communicated prior to hiring. Their research found that perceived contract violations led to decreased organizational commitment and to decreased trust in the employing organization. It then follows that technological change which forces down the wages of low skilled workers is effectively exploiting them, and that income inequality is simply a manifestation of that exploitation.4 The basic power imbalance, however, isn’t the only flaw in the textbook economic model. The greatest flaw is perhaps the assumption that workers through their wage demands ultimately determine whether they will be employed. But it isn’t their wage demands that primarily determine whether they will be employed, rather it

is aggregate demand for goods and services.5 According to Keynesian macroeconomists, a reduction in money wages might somewhat reduce prices, and might involve a redistribution of real income from wage earners to other factors. But this transfer from wage earners to other factors would in most likelihood diminish the propensity to consume, which in turn would only result in lower demand for goods and services, thereby resulting in even greater contraction of productive industry.6 Flexible wages will not assure full employment if effective demand is deficient.7 An episode of deflation could also result in a decrease of net financial wealth.8 Still, there is a limit to how much prices can be reduced following wage reductions. Employers still have fixed costs, and if they cannot reduce their prices enough to meet the new lower wages, the result will be a drop-off in demand because of reduced purchasing power. In a survey of business executives during the 1930s and 1940s, Richard Lester observed that business executives tended to think that costs and profits were contingent on the rate of output; not the other way around. Employment levels were not determined by wage rates, but by the rate of output.9 This would only suggest that no matter how low workers are willing to reduce their wage demands, if there is no demand for their firm’s goods and services, they simply will not be employed.

All of this would suggest that labor markets really are not monolithic. Rather there are different markets for different occupations and industries depending on relative skills requirements. Most minimum wage earners, it is understood, are unskilled workers, and an oversupply of low-skilled workers will drive down the wages of workers in those industries and occupations likely to employ them. Changes in the economy have effectively resulted in a two-tier economy with highly skilled and highly educated workers at the top and poorly skilled and poorly paid workers at the bottom. Economic transformations biased towards technical change will no doubt lead to this type of two tier economy. Often referred to as the “canonical� model, this model maintains that because of technological advances, there has been a greater demand for skilled workers. As a result, the oversupply of unskilled labor will only push down wages, and inequality will increase. In this model there are

two distinct groups: college and high school workers performing two distinct and imperfectly sustainable occupations or producing two imperfectly sustainable goods.10 As a result of technological change the labor market has become greatly polarized. Therefore The standard model doesn’t account for the power dynamics. If technological change is today causing polarization of the labor market between high-skill jobs and low-skill jobs, then any institution that bolsters wages, especially through policy, must be an artificial one doomed to failure. Market forces will cause the employment (if not always the wages) of unskilled workers to be forced down while the wages of the skilled workers are driven up, thereby increasing the gap between the two.11 Arguably, changes in the economy may explain in part why wages are declining, but they don’t make higher wages any less necessary. Rather these trends only leave a sizeable population in need of social supports.

Moreover, because the nature of the economy differs from one region of the country, it may not necessarily be the case that a one size fits all is necessarily the answer. The federal minimum wage merely establishes a uniform floor; it doesn’t prevent individual states from having higher state minimum wages. Although minimum wages in the tristate area are higher than the federal minimum, they are not among the highest. And yet, the changing demographics of the labor market more than parallel the changes in the rest of the nation.

They actually are more acute.

Statistical Analysis In this section, I make use of microdata from the BLS’s Current Population Survey (CPS) in order to investigate key differences between the overall U.S. labor market and the tristate NY/NJ/CT metro area. The microdata was drawn from the Integrated Public Use Microdata Series (IPUMS), to ensure uniformity in variables across time periods.12 Although minimum wages have risen in the last couple years specifically in New York and New Jersey (and have been rising all along in Connecticut), the real question is what economic

changes have been occurring that may have made increases more inevitable in the tristate area than elsewhere.

Therefore, I look at three snapshots in time over a 15-year period beginning in 2000. Beginning in 2007, following Congress’s enactment of the first increase in the federal minimum wage since 1998, the minimum was raised in steps. The phased increase to $7.25 happened in 2009. I give special attention to 2009 and to 2015. The latter is an important year because many states responded further to the stagnation and declining value of the federal minimum wage with either first-time increases or further raises to their minimum wages.

Both New York and New Jersey first increased their minimum wages in 2014 and then again in 2015.

Connecticut had been increasing its minimum wage all along.

The first question that might be asked is just what the impact of raising the minimum wage in these three states is on wages around the minimum. If we accept that the minimum wage is important because it is a reference point for wages around it, then increases in the minimum wage may be much more important. First of all, it means that the minimum wage really refers to a broader labor market — what we could label the effective minimum wage population, because these are workers earning in wage ranges around the statutory minimum wage. Critics of the minimum wage often attempt to narrow the scope of public debate by focusing only on those workers specifically earning the statutory minimum wage, which is perhaps less than 2 percent of the entire labor market. This narrower focus, of course, raises the question of why the minimum wage should even be much of an issue, if only a small number of people earning it. But if the minimum wage is recognized as a reference point for the larger low-wage labor market, then we are looking at close to 20 percent of the labor market. A broader focus effectively socializes the conflict and makes it clear that our wages perhaps fall into contours and that what happens in one contour will have an impact on what happens in another.

Elsewhere I have argued that the minimum wage has what can be called “contour effects.” A contour consists of wages revolving around a reference point. With the minimum wage being the first contour in the distribution, it then is the reference point for wages around it, which would be the low-wage industry. Since we

would expect one contour to impact those immediately around it, we could then construct several intervals beginning with the statutory minimum and ranging 25 percent above. Then the next contour would begin where the last left off and range another 25 percent. On the basis of CPS data for 1962-2008, I created 10 such contours and found that in each year that the statutory minimum wage increased, so too did the median wage in each contour. In those years when the minimum wage was not increased, median wages remained unchanged.

That the median wage rose in each of the ten constructed contours suggests middle class welfare effects.13 Table 1 shows similar effects for only five constructed wage contours for the tristate area.

In Connecticut where the minimum wage has been raised more consistently, there do not appear to be any serious wage contour effects. From 2014 to 2015, there were median wage increases in the second, third and fifth contours. In both New York and New Jersey where there had not been an increase in the states’ minimum wages prior to 2014, we see wage contour effects in all five contours. In New Jersey when the minimum wage increases an additional 13 cents in 2015, there is no real contour effects until the fourth and fifth contours. Then in New York where the minimum wage increases an additional 75 cents from 2014 to 2015, there are contour effects in the second through fifth contours, but no effect in the first. It may be that for there to be serious contour effects the increase has to be sizeable and that where the increase appears to be minuscule, the effects will be negligible to non-existent. New Jersey’s increase from 2014 to 2015 was also on the basis of an increase in the CPI rather than a specified amount to be raised that year. Still, it appears that there are some welfare effects in the tristate area that are not limited to only those earning the minimum wage or even those who make up the effective minimum wage population. That there are effects through at least five contours of the wage distribution will be critical if we can establish that these increases were necessary because of the changing nature of the tristate economies.

There are two different changes that are important to track. The first are basic demographic shifts in the

labor market and the second are shifts in industry and occupational composition. Table 2 shows the changes in demographics from 2000 through 2015 with 2009 in between.

Compared to the other states in the country, the percentage change in minority composition increased considerably more in the tristate area. Overall between 2000 and 2015 the black population in New York increased by 48.5 percent while it only increased by 22.7 percent in other states. The black population decreased by 16.7 percent in New Jersey and by 6.9 percent in Connecticut. The percentage of Asian or Pacific Islanders increased by 219 percent in Connecticut and by 125 percent and 129.4 percent in New Jersey and New York respectively.

This population only increased by 88.6 percent in other states. Interestingly enough, the largest percentage increase in Hispanics during this period was in Connecticut (19.8 percent), then followed by New Jersey (14.6 percent). It only increased by 5.5 percent in all other states and declined by 15.8 percent in New York. The percentage increase of those living below the poverty line was greatest in New Jersey, where it increased by 24 percent. It only increased by 10.5 percent in Connecticut and declined by 17.4 percent in New York and 4.3 percent in all other states.

The most interesting changes were in terms of educational attainment, which would only lend support to the idea that there may be a larger skills gap between the top and the bottom in the tristate area than in all other states. Of those who attained less than a 12th grade education the greatest decline was in Connecticut (59.9 percent). The decline was 35.2 percent in New York, 16.1 percent in New Jersey, and 30.9 percent in all other states. Meanwhile, the number of those earning a high school diploma declined by 22.5 percent in Connecticut, 23.8 percent in New

Jersey, 20.1 percent in New York, and 6.7 percent in all other states. Those earning Associates degrees declined by 15.4 percent in Connecticut, 24.5 percent in New Jersey, 11.7 percent in New York and 6.6 percent. Those completing BA degrees increased the most in all other states by 53.8 percent. It increased by 31.6 percent in New Jersey and 17.5 percent in New York, and only by 5.8 percent in Connecticut. It is the changes among those attaining a graduate or professional degree that is perhaps most revealing. The largest percentage increase in this category was in Connecticut (44.2 percent), followed by New Jersey (40.8 percent) and then New York (36.3 percent). The percentage increase in graduate or professional degree graduates was only 32.2 percent in all other states. These differences alone would appear to suggest greater skills in the tristate area than in the other states.

In terms of union membership, which has overall been in a state of decline in the last several decades, the decline during this period was greater in New Jersey. Union membership has certainly not been high across the board. In 2000 union membership in New York was 29.1 and 22.4 percent in New Jersey. In Connecticut it was 17.5 percent and in all other states it was 14.5 percent. By 2015 union membership dropped to 26.4 percent in New York, a decline of 9.3 percent. It dropped to 20 percent in New Jersey, a decline of 10.7 percent and it dropped to 15 percent in Connecticut, a decline of 14.3 percent. In all other states it had dropped to 11.4 percent, a decline of 21.4 percent.xiv New York still has the highest union membership in the tristate area. Although the union membership is small and has been small during this entire period, its importance cannot be overstated. Unions have traditionally been a key labor market institution bolstering wages. Unions have also impacted the wages of nonunion workers.

Average wages of nonunion members have been higher in those areas where union density has

been highest.xv Moreover, unions were always a key constituency supporting increases in the minimum wage. When unions were stronger, minimum wages tended to increase.xvi There is also the issue of whether inequality in these states has also increased more so relative to the rest of the states.

This can be seen in Table 3.

We can see reductions in inequality following the 2014 increases in the minimum wage in New Jersey and New York on the 90/10 measure.

In Connecticut where the minimum wage has been increasing all along, there is a decrease in inequality in 2014 and 2015 on all measures. In New Jersey following the increase in 2014 there is a decrease on all measures except the top-to-bottom quintile ratio, but in 2015 when the increase is minimal inequality increases on the 90/10 ratio, it remains unchanged on the 90/50 ratio and decreases on both the 50/10 and top-to-bottom quintile ratios. In New York there is a decrease on all measures in 2014, but an increase again in 2015 on all measures despite the sizeable increase in the minimum wage that year. In the rest of the states for the exception of the top-to-bottom quintile measure in 2014 there is no real change. And yet, it is worth noting that inequality on all measures, save for a few exceptions, is higher in New York than elsewhere. Does this then mean that inequality was necessarily a factor behind increases in the minimum wage?

The key questions are what changes have occurred in industry and occupational composition, which can be seen in Table 4. In terms of occupations, the increase between 2000 and 2015 in those working in professional and technical occupations in the tristate area increased the most in Connecticut, but it was still less than in all other states. Meanwhile, the greatest decrease in those working as Managers, Officials and Proprietors was greatest in New Jersey during this period. Perhaps of greatest interest is the change in what would fall into the purview of blue collar occupations: craftsmen, operatives, and laborers. Of those working as craftsmen, the greatest decline during this period was in New Jersey (34 percent), followed

by New York (19.8 percent). The decline in all other states was 16.3 percent. The number of those working as craftsmen actually increased 3.5 percent in Connecticut. Of those working as operatives, the greatest decline was in Connecticut (38.9 percent), followed by New York (28.9) percent.

The decline in all other states was 11 percent and 8.7 percent in New Jersey. The percentage of laborers declined by 13.9 percent in New York and by

3.4 percent in Connecticut. In all other states the decline was 14.3 percent. Among service workers not in private households, the greatest increase was in Connecticut (30.4 percent), followed by New York (10 percent), and then New Jersey (9.7 percent). In all other states, the increase was 6.6 percent.

In terms of industry, the greatest decrease during this period was in manufacturing. The decrease was greatest in New York (58.4 percent), followed by Connecticut (45.7 percent) and then New Jersey (30.6 percent). In all other states manufacturing decreased by 30.9 percent. Meanwhile, the greatest increase in retail trade was in Connecticut (25.2 percent), followed by New Jersey (21.8 percent). Retail trade only increased by 1.9 percent in New York and decreased by 5.1 percent in all other states. At the same time, business and repair services increased by 37.5 percent in Connecticut while it decreased by 47.4 percent in New Jersey and by 33.3 percent in New York. It only decreased by 11.1 percent in all other states.

The biggest increase was in New York in Entertainment and Recreation Services (65.2) percent, and this would include the restaurant industry and those working as servers. This industry actually decreased by 8.3 percent in Connecticut and by 4.5 percent in New Jersey. The increase in all other states was 18.2 percent.

At least in New York, it would appear that the loss of better paying “working class� jobs was greater. Although the increase in skilled occupations was greater in other states, it certainly was substantial in New York. These demographics might lend support to the economic transformations that have resulted in a two-tiered economy with highly paid workers at the top and poorly paid workers at the bottom. And while the data can say nothing about the motivations of public officials, it may nonetheless speak to the type of forces that at a minimum would require higher wages in these areas.

Analysis The question, then, is what factors, if any, made it more likely that these states would increase their minimum wages. These issues can be sorted out with a logistical regression analysis with both 2014 and 2015 pooled together. There are two issues to sort through which will entail two separate regressions. The first is: what were the characteristics of states generally throughout the U.S. that were more likely to pass higher minimum wages than the current federal minimum of $7.25 an hour? And the second is: what changes occurred in the tristate area that may have been a factor in these states raising their minimum wage?

It is generally assumed that Democratic states are more likely to have higher minimum wages whereas Republican states are least likely to.

Because the states in the tristate area could be considered high-cost-of-living it is useful to test for those effects as well. The National Tax Foundation has ranked states according to how much value the dollar has in each. Therefore, states can be divided into low-dollar value and high dollar value and these values can be incorporated into the CPS data. Here I use the low-dollar variable as a proxy for high-cost-of living. As the change in demographics has already shown, there have been significant increases in the black population, especially in New York. Therefore, it is useful to test for that. Because there have also been significant changes in the percentage of those who have attained advanced degrees, it is useful to test for that as well. Also as there was a big drop in union membership in the tristate area, the question is just what role union density has in a state’s likelihood of passing a higher minimum wage than the federal.

The dependent variable in my regressions is dichotomous: does each state have a minimum wage higher than the federal minimum? I test the impacts on it of regressors reflecting: whether each state has higher inequality than inequality at the national level; being a blue state (one with Democratic majorities in their governments); being a state with a high cost of living as measured by having a low dollar value (i.e. the dollar buys less in those states than elsewhere); being a right to work state; being black; and having a professional and/or graduate degree. All variables are set to a value of 1 and can be seen in Table 5.

In terms of the characteristics that states with higher minimum wages have, they are likely to have high union density and have a high cost-ofliving. The strongest effect for having a higher minimum wage is high union density, followed by a low dollar value, followed by higher inequality.

Interestingly the advanced degree variable is positive and statistically significant, but its effect is minuscule. States with right-to-work laws are less likely to have higher minimum wages, which is what we would expect given that right-to-work laws are effectively anti-labor market institutions — their effects are to suppress wages. What is odd is the negative coefficient for the blue state variable. In that blue states are Democratic states, we would expect that they would be more likely to pass higher minimum wages than red states which are predominantly Republican. It might be that relative to the other variables in accounting for why states are more likely to adopt higher minimum wages, the fact that these states are also blue really is not that important.

Nevertheless, this first set of regressions sets the stage for a better understanding of what is happening in the tristate area that can be seen in Table 6. With increases in minimum wages as the dependent variables in Connecticut, New Jersey, and New York, I test for changes in certain demographics and industries. I specifically test for changes in the percentage of minorities; changes in the percentage of those with advanced degrees; changes in the percentage of those who are union members; changes in the percentage of those in manufacturing; changes in the percentage of those in Transportation, Telecommunications, and Utilities; changes in the percentage of those who are Craftsmen; changes in the percentage of those who are in Services (non-private household); and changes in the percentage of those in Business and Repair Services. All variables are set to a value of 1.

In terms of demographic changes, increases in the percentage of blacks had the strongest effect in New York. Also, increases in the percentage of Hispanics also had positive effects. In New Jersey, the strongest positive effect was an increase in the percentage of those with advanced degrees. This variable also appears to be important in Connecticut and New York too. In the first set of regressions, the effects of being

black was negative; in this set it has positive effects. The increase in professional and graduate degrees is also important because having these degrees in the first set is almost to no effect. The decrease in the percentage of those in manufacturing does appear to have a positive effect in Connecticut, and in New Jersey the decrease in the percentage of those who are working in Transportation, Telecommunications, and Utilities. The effects of changes in other industries and/or occupations don’t appear to be that strong. That the strongest effects appear to be in changes in the percentages of those with advanced degrees is suggestive of a growing skills mismatch in these three states. Those with advanced degrees have greater skills and can command higher wages. Those at the bottom of the distribution with no skills are consigned to the low-wage labor market, in which case higher minimum wages in states where the cost of living is generally higher than the rest of the nation is seen as more essential. When these three states are put together, it would appear that states were more likely to have higher minimum wages, where there were greater percentage increases in advanced education.

Conclusion Generally speaking, states with high union density, a high cost-of-living, and even higher inequality are more likely to have adopted higher minimum wages over the last few years. The reasons for this ought to be obvious enough. Historically minimum wages increased when there was a constituency to support those increases, and that constituency has been organized labor.xvii Union density certainly speaks to the presence of that constituency, and the size of it may speak to its relative influence. We would certainly expect that states with higher costs of living would be more likely to pass higher minimum wages because low-wage workers need higher wages in order to make ends meet. And to a certain extent we would expect states with higher rates of inequality to raise the legal wage floor because inequality speaks to a widening gap between the top and the bottom.

Higher minimum wages can certainly reduce inequality in that the effect is for the average incomes of the bottom to rise at a higher percentage rate than the average incomes of those at the top.

In the tristate NY-NJ-CT metro area, however, at issue are changes that have occurred. We might conclude that the changing economy in which more skills are required for better paying jobs, especially in high cost-of-living states, does make a higher minimum wage a necessity for those who have been left behind. If there has been an increase in minority populations, who on average might be more concentrated in the low-skilled and low-wage market, an oversupply in that market will only further suppress wages at the bottom, thereby making the gap between the top and the bottom more acute. States where racial and ethnic tensions already run high may be more inclined to adopt measures that in part might smooth out some of those tensions. Changing industrial and occupational composition appears not to be as much as a factor. Rather, it would appear to be the case that states with higher percentages of skilled workers are more likely to have passed higher minimum wages. That might speak to the growing skills gap between the top and the bottom, with the bottom having an oversupply of low-skilled workers. All three states in the tristate area appear to fall into that category.

Does this necessarily imply that more attention should be placed on education and training? It is hard to say. Despite the apparent skills gap, the real issue still appears to be institutions. Had institutions been in place to bolster wages, wages, even those at the bottom, would most likely be higher. The jobs paying well are highly skilled jobs requiring advanced degrees. It is highly unlikely that the types of retraining programs that policymakers have long talked about would be of much help. It is conceivable that New York’s new program that effectively offers free college to those whose family incomes fall below a certain threshold might help. But helping people to afford college does not guarantee that students will necessarily learn the needed skills, or even have the aptitude for, required by today’s economy. What these trends might imply is that, in line with Goldin and Katz, more emphasis needs to be placed on K to 12 education so that the high school premium can be restored.xviii Still, as important as more education and training may be, it is more likely the case that strong labor market institutions, like minimum wages, need to be in place for those

who will continue to be among the unskilled and at the bottom of the income distribution. It was unions that made the low-skilled jobs in manufacturing of yesteryear middle class jobs. Similar type institutions are needed to make the low-skilled service jobs of today middle class jobs.

Oren M. Levin-Waldman is professor of public policy in School for Public Affairs and Administration at Metropolitan College of New York, Research Scholar at the Binzagr Institute for Sustainable Prosperity and adjunct professor at the Milano School for International Affairs, Management, and Urban Policy at The New School . His new book, Restoring the Middle Class Through Wage Policy: Arguments for a Minimum Wage is forthcoming from Palgrave.

REGIONAL LABOR REVIEW, vol. 20, no.2 (Spring/Summer 2018). Š 2018 Center for the Study of Labor and Democracy, Hofstra University

Table 1 Wage Contours by State

Minimum Wage

First

Second

Third

Fourth

Fifth

2010

$8.25

$9.14

$12.02

$14.42

$17.79

$23.08

2011

$8.25

$9.62

$11.95

$14.42

$18.27

$23.08

2012

$8.25

$9.62

$12.02

$14.42

$18.27

$23.08

2013

$8.25

$9.62

$11.66

$14.42

$18.27

$23.08

2014

$8.70

$9.62

$12.02

$15.38

$19.23

$24.04

2015

$9.15

$9.62

$12.98

$15.87

$$19.23

$25.00

2010

$7.25

$8.17

$9.62

$12.02

$15.38

$19.71

2011

$7.25

$8.17

$10.00

$12.50

$15.38

$19.23

2012

$7.25

$8.17

$9.62

$12.50

$15.49

$19.23

2013

$7.25

$8.22

$9.62

$12.02

$15.46

$19.71

2014

$8.25

$9.62

$12.02

$14.42

$18.27

$23.08

2015

$8.38

$9.62

$12.02

$14.42

$18.75

$24.04

2010

$7.25

$8.50

$9.62

$12.50

$15.38

$19.23

2011

$7.25

$8.36

$9.62

$12.02

$15.38

$19.23

2012

$7.25

$8.31

$9.62

$12.02

$15.38

$19.71

2013

$7.25

$8.41

$10.00

$12.36

$15.38

$19.41

2014

$8.00

$9.62

$11.54

$14.42

$18.00

$22.60

Connecticut

New Jersey

New York

2015

$8.75

$9.62

$12.02

$15.38

$19.23

$24.04

Table 1 Source: CPS data from IPUMS files. See Miriam King, et al. (2010)

Table 2 Demographic Changes

2000/2009

2009/2015

2000/2015

CT

NJ

NY

All Others

CT

NJ

NY

All Others

CT

NJ

NY

All Others

White

-3.9

-4.2

-10.2

-7.7

-1.8

-1.3

-7.4

1.7

-5.6

-5.5

-16.9

-9.5

Black

-7.8

-29.7

+26.9

+19.3

+1.1

+18.6

+17.0

+2.9

-6.9

-16.7

+48.5

+22.7

American Indian

0

-75.0

-42.9

+8.3

0

+250.0

+200.0

0

0

-12.5

-14.3

+8.3

Asian or Pacific Islander

+166.7

+143.8

+66.7

+57.1

+19.6

-7.7

+37.6

+20.0

+219.0

+125.0

+129.4

+88.6

+100.0

-33.3

-41.2

-5.3

Race

Mixed Race Hispanic

Non-Hispanic

-3.3

-4.5

+2.5

+1.2

+1.3

+0.9

+1.7

-2.2

-2.1

-3.6

+4.3

-1.1

Hispanic

31.3

+18.2

-2.3

-6.1

-8.7

-3.0

-7.2

+12.4

+19.8

+14.6

-15.8

+5.5

+26.3

+8.0

-6.5

-10.6

-12.5

+14.8

-11.6

+7.1

+10.5

+24.0

-17.4

-4.3

-0.5

-0.2

+0.3

+0.5

+0.3

-0.4

+0.5

-0.3

-0.2

-0.6

+0.8

+0.2

-22.1

-4.3

-29.7

-25.2

-38.8

-12.4

-7.8

-7.6

-59.9

-16.1

-35.2

-30.9

Poverty Level

Below Poverty Above Poverty Education

HS Dropout

HS Diploma

-10.5

-10.4

-3.0

-1.2

-13.5

-19.4

-17.7

-6.1

-22.5

-23.8

-20.1

-6.7

Associates Degree

-17.1

-20.8

+4.3

-2.0

+2.1

-4.7

-2.9

-4.6

-15.4

-24.5

-11.7

-6.6

BA Degree

+7.7

+13.2

+10.5

+38.5

-1.8

+16.3

+6.3

+11.1

+5.8

+31.6

+17.5

+53.8

Grad/Profesnl Degree

+29.0

+23.6

+9.9

+20.8

+14.5

+13.9

+24.2

+9.4

+44.2

+40.8

+36.3

+32.2

-8.7

+3,8

-3,4

+1,3

+13.1

+.8

+8.0

+1.2

+4,4

+4,6

+4.3

+42.3

-7.6

+1.4

-6.2

-39.8

-3.4

-10.5

-16.2

-14.3

-10.7

-9.3

Unionization No Union Coverage Member of labor union

Table 2 Note: Entered values equal changes in percentage values of each characteristic between specified years.

Source: Current Population Survey microdata, IPUMS files.

+3.9 -21.4

Table 3 Changes in Inequality by State Connecticut

New Jersey

New York

All Other States

90/10 percen tile

90/50 percen tile

50/10 percen tile

top-tobottom ratio

90/10 percen tile

90/50 percen tile

50/10 percen tile

top-tobottom ratio

90/10 percen tile

90/50 percen tile

50/10 percen tile

top-tobottom ratio

90/10 percen tile

90/50 percen tile

50/10 percen tile

top-tobottom ratio

2000

6.3

2.1

3.0

7.1

5.9

2.1

2.8

8.2

10.8

2.2

5.0

11.7

6.4

2.1

3.1

8.7

2001

5.6

1.9

3.0

8.6

5.6

2.0

2.7

9.0

9.0

2.0

4.4

12.1

5.9

2.1

2.8

8.8

2002

5.3

2.0

2.7

8.9

6.3

2.0

3.1

9.6

6.3

2.1

3.0

10.7

5.9

2.1

2.8

9.0

2003

6.7

1.8

3.6

11.0

7.1

2.1

3.3

9.5

8.3

2.2

3.8

11.9

6.6

2.2

3.0

10.1

2004

5.8

1.9

3.0

8.5

5.8

2.1

2.8

8.3

9.7

2.2

4.4

14.1

6.3

2.2

2.9

8.9

2005

6.7

2.0

3.4

10.5

6.4

2.2

2.9

9.2

6.8

2.0

3.4

10.4

6.5

2.2

3.0

9.5

2006

7.4

2.2

3.4

11.7

6.0

2.0

3.0

8.9

6.6

2.1

3.2

10.1

6.3

2.2

2.9

9.4

2007

7.9

2.3

3.4

11.2

6.9

2.3

3.0

8.7

6.9

2.2

3.1

10.5

6.3

2.1

3.0

9.7

2008

7.4

1.9

3.9

10.4

6.3

2.1

3.0

8.5

5.5

2.2

2.5

7.9

5.6

2.0

2.8

8.7

2009

6.1

2.0

3.1

8.8

6.4

2.3

2.7

9.0

6.4

2.2

2.9

9.0

6.0

2.2

2.8

8.3

2010

5.7

2.2

2.6

9.6

7.0

2.3

3.1

10.8

6.3

2.3

2.8

9.7

5.8

2.2

2.7

8.5

2011

7.7

2.2

3.4

8.8

5.8

2.0

2.9

7.7

6.0

2.1

2.8

9.3

5.9

2.2

2.7

8.3

2012

6.5

2.1

3.0

10.7

7.5

2.3

3.3

8.7

6.4

2.3

2.8

9.3

5.9

2.2

2.7

8.8

2013

7.5

2.2

3.5

11.4

6.7

2.3

2.9

8.1

7.3

2.3

3.1

11.9

6.0

2.2

2.8

9.2

2014

6.2

2.1

2.9

9.3

6.0

2.3

2.6

9.1

5.4

2.2

2.5

8.8

6.0

2.2

2.8

9.0

2015

5.7

2.1

2.7

7.1

6.9

2.3

3.1

8.6

7.5

2.5

3.0

11.2

6.3

2.3

2.8

9.0

Table 4 Industrial and Occupational Changes 2000/20009

2009/2015

2000/2015

CT

NJ

NY

All others

CT

NJ

NY

All others

CT

NJ

NY

All others

+9.0

+27.0

+23.7

+12.4

+12.4

-29.0

+12.5

+5.0

+22.5

-9.8

+9.7

+24.2

0

-100.0

-300.0

-20.0

0

0

0

0

0

-100.0

-300.0

-20.0

Managers, Officials & Proprietors

-3.2

-3.8

-17.0

-11.6

-7.4

-9.9

+12.8

+0.8

-10.4

-12.1

-6.4

-10.9

Clerical & Kindred

-7.2

-8.0

-7.0

+1.9

-8.4

-4.4

+0.6

-5.5

-15.0

-13.1

-6.8

-3.7

Sales Workers

+4.8

-16.4

+3.2

-6.6

-18.2

-1.7

-9.4

-1.8

-14.3

-17.8

-9.7

-8.2

Craftsmen

0

-23.4

-10.5

-4.0

+3.5

-13.9

-10.4

-10.4

+3.5

-34.0

-19.8

-16.3

Operatives

-32.4

-20.4

-8.7

-12.8

-9.6

+14.6

-22.0

+2.1

-38.9

-8.7

-28.9

-11.0

Service Workers, private household

+12.5

+71.4

+27.3

+57.1

0

0

-28.6

+9.0

+12.5

+71.4

-9.0

+71.4

Service Workers, nonprivate household

+18.8

+13.7

+5.9

+7.3

+10.5

-3.5

+3.9

-0.7

+30.4

+9.7

+10.0

+6.6

Farm Laborers

-75.0

0

-50.0

-40.0

-100.0

+300.0

-.50.0

+16.7

-400.0

+300.0

-.75.0

-30.0

Laborers

+24.1

-14.6

+2.8

-16.3

-22.2

+17.1

-16.2

+2.4

-3.4

0

-13.9

-14.3

+36.4

+.30

0

-12.2

-26.7

+30.8

-18.2

+10.3

0

+70.0

-18.2

-3.0

Occupation Professional, Technical

Farmers

Industry Agriculture, Forestry,

Fishing Mining

0

0

0

+16.7

+200.0

0

-100.0

+42.9

0

0

0

+900.0

Construction

+40.8

0

+8.2

+9.9

-2.9

+7.3

-6.0

-9.0

+36.7

+7.3

+1.6

0

Manufacturing

-37.2

-25.4

-38.1

-26.2

+3.6

-24.5

-15.1

-6.4

-45.7

-32.2

-58.4

-30.9

Transport, Telecom, Utilities

-45.7

-29.3

-12.2

+10.3

+21.1

0

-20.9

0

-62.9

-29.3

-30.6

-15.4

Wholesale Trade

-48.7

-32.7

-21.9

-34.2

+5.0

-8.6

+4.0

+14.3

-46.2

-38.5

-18.8

-36.8

Retail Trade

+25.9

+13.6

+4.4

+4.0

-0.6

+7.2

-2.4

-8.7

+25.2

+21.8

+1.9

-5.1

Finance, Insurance, Real Estate

+12.4

+2.4

-5.8

-2.4

+4.5

-4.6

+13.8

-21.7

+17.5

-2.4

+7.1

+0.8

Business & Repair Services

+25.0

-31.2

-22.2

-16.7

+10.0

-30.8

-14.3

+6.7

+37.5

-47.4

-33.3

-11.1

Personal Services

+19.2

-17.1

0

-15.0

+22.6

+10.3

-19.0

0

+46.2

-8.6

-19.0

-15.0

Entertainment & Rec Srvcs

-5.6

+36.4

+13.0

+18.2

-2.9

-30.0

+46.2

-21.2

-8.3

-4.5

+65.2

+18.2

Professional & Related

+13.4

+39.5

+20.7

+22.7

+3.9

+6.8

+2.4

+2.5

+19.3

+31.1

+23.6

+25.7

Table 5 Regression Coefficients for U.S.

Higher Inequality State than in the U.S. as a whole

.566 .000

Blue State

-.517 .000

High Cost of Living

1.488 .000

High Union Density

1.761 .000

Right-to-Work State

-1.120 .000

Black

-.124 .000

Professional or Graduate Degree

.037 .012

Constant

-.027 .241

Table 5 Note: Dependent variable (dichotomous) = 1 if individual resides in state where the minimum wage is higher than the federal minimum wage; 0 otherwise.

Source: Current Population Survey microdata, IPUMS files.

Figures below coefficients are measures of statistical significance. A coefficient is statistically significant if below .05.

Table 6 Regression Coefficients for Tristate Area Connecticut Minimum wage Change in Black Population

Change in Hispanic Population

Change in % with Advanced Degrees

Change in % Workers Union Members

Change in % in Manufacturing

Change in % Transport, Telecomm & Utilities

Change in % craftsmen

New Jersey Minimum Wage

New York Minimum Wage

-.136

.124

.589

.000

.000

.000

-.226

.341

.254

.000

.000

.000

.314

.413

.310

.000

.000

.000

-.322

-.903

-.123

.476

.119

.664

.158

-.116

-.406

.005

.053

.000

-.187

.320

.106

.106

.000

.114

.075

-.257

-.111

.221

.000

.015

Change in % Operatives

-.309

-.024

-.274

.000

.707

.000

.072

-.285

.610

.013

-.343

-.085

-.267

.045

.578

.019

4.007

4.073

3.216

.000

.000

.000

Change in % in Services

Change in % in Business & Repair Services

Constant

Connecticut Minimum wage Change in Black Population

Change in Hispanic Population

Change in % with Advanced Degrees

Change in % Workers Union Members

Change in % in Manufacturing

Change in % Transport, Telecomm & Utilities

Change in % craftsmen

Change in % Operatives

New Jersey Minimum Wage

New York Minimum Wage

-.136

.124

.589

.000

.000

.000

-.226

.341

.254

.000

.000

.000

.314

.413

.310

.000

.000

.000

-.322

-.903

-.123

.476

.119

.664

.158

-.116

-.406

.005

.053

.000

-.187

.320

.106

.106

.000

.114

.075

-.257

-.111

.221

.000

.015

-.309

-.024

-.274

.000

.707

.000

.072

-.285

.610

.013

-.343

-.085

-.267

.045

.578

.019

4.007

4.073

3.216

.000

.000

.000

Change in % in Services

Change in % in Business & Repair Services

Constant

Table 6 Note: Dependent variable= increases in the minimum wage in Connecticut, New Jersey, and New York.

Source: Current Population Survey microdata, IPUMS files.

Figures below coefficients are measures of statistical significance. A coefficient is statistically significant if below .05.

Notes 1. Ronald G .Ehrenberg and Robert S. Smith, Modern Labor Economics: Theory and Public Policy (Sixth edition, Reading, MA: Addison-Wesley, 1997); and George Stigler, “The Economics of Minimum Wage Legislation,” American Economic Review 36 (June 1946):358-365.

2. Charles Brown, Curtis Gilroy and Andrew Kohen, “The Effects of the Minimum Wage on Employment and Unemployment,” Journal of Economic Literature 20 (June 1982):487–528.

3. David McNally, Global Slump: The Economics and Politics of Crisis and Resistance (Oakland, CA: PM Press, 2011) 4. Kristian Braekkan and Victoria Sowa, “Exploitation by Economic Necessity: Using the Marxist Conceptualization of Exploitation to Investigate the Impact of Workplace Violations” Journal of Workplace Rights (October-December 2015):1-10.

5. Hyman P. Minsky, Stabilizing an Unstable Economy (New Haven, Yale University Press, 1986), pp. 123-124 6. John Maynard Keynes, The General Theory of Employment, Interest, and Money (New York, Harvest/Harcourt, 1964), pp. 14, 262 7. Sidney Weintraub, “The Missing Theory of Money Wages,” Journal of Post Keynesian Economics 1,2 (Winter 1978-79):59-78.

8. Christopher Brown, “Commodity Money, Credit, and the Real Balance Effect,” Journal of Post Keynesian Economics 15,1 (Winter 1992):99-107 9. Richard A. Lester, “Shortcomings of Marginal Analysis for Wage-Employment Problems” American Economic Review 36,1 (March 1946):63-82.

10. Daron Acemoglu and David Autor, What Does Human Capital Do? A Review of Goldin and Katz’s The Race between Education and Technology,” Journal of Economic Literature. 50,2 (2012):426-463.

11. David H. Autor and David Dorn, “The Growth of Low-Skill Service Jobs and the Polarization of the U.S. Labor Market,” American Economic Review 103,5 (2013):1553-1597.

12. Sarah Flood, Miriam King, Steven Ruggles, and J. Robert Warren. Integrated Public Use Microdata Series, Current Population Survey: Version 4.0. [dataset]. Minneapolis: University of Minnesota, 2015. http://doi.org/10.18128/D030.V4.0.

13. Oren M. Levin-Waldman, Wage Policy, Income Distribution, and Democratic Theory (London and New York, Routledge, 2011) xiv Because I am specifically looking at full-time workers, the union membership figures from the sample are actually higher than on published reports from the BLS. When looking at all workers, however, the union figures in this sample are almost identical (within a .1 or .2 difference) to those in published reports. xv. Dale Belman and Paul J. Wolfson, What Does the Minimum Wage Do? (Kalamazoo, Upjohn Institute for Employment Research, 2014) xvi. Oren M. Levin-Waldman, The Case of the Minimum Wage: Competing Policy Models (Albany, State University of New York, 2001) 17. Levin-Waldman, ibid.

18. See Claudia Goldin and Lawrence F, Katz, The Race Between Education and Technology (Cambridge, MA and London: Belknap Press of Harvard University Press, 2008).