Update: Read the analysis of 2016 nonemployer establishment data.

Last week’s release of the new Bureau of Labor Statistics (BLS) Contingent Worker Survey (CWS) has renewed public interest in tracking the number of self-employed or independent contractors. The upcoming release of the U.S. Census nonemployer establishment data for 2016 this Thursday will provide another useful data point about the trends in self-employment.

Our analysis of nonemployer establishment data through 2015 indicates that these data confirm previous general findings regarding Uber drivers, all online demand platform work, and independent contractors more generally. These previous findings are:

1. There is an increase in the amount of people involved in these types of work activity;
2. The increase is primarily among people who are doing so to earn supplementary income and for a short amount of hours. The increase in the various self-employment activities has not occurred in people’s “main job” or as their main source of income; and
3. The economic scale of these activities has not increased greatly when measured as a share of hours worked or compensation earned. While “headcount” measures do show a large increase, the overall economic impact is relatively small.

As we will show, there has been a significant increase in the headcount of nonemployer establishments. However, the economic impact, as measured by the share of nonemployer establishment revenues in total revenues, has not increased in roughly 20 years. This indicates that the growth of nonemployer establishments seems to reflect the growth of self-employed individuals operating unincorporated businesses that generate very little revenue.

Background on CWS and nonemployer data

The CWS is based on a household survey and showed that in 2017, the share of independent contractors in total employment was 6.9 percent, comparable to what was reported in all of the other CWS surveys back to 1995. This has elicited surprise by many observers, especially those that have touted the explosion of gig work or freelancing.

The release of new Census data on nonemployer establishments for 2016 this month provides another opportunity to track these trends. These Census data capture the phenomenon of self-employment by examining business establishment/firm data rather than asking individual workers or households about employment. Census describes the data as:

“data for businesses that have no paid employees and are subject to federal income tax. Most nonemployers are self-employed individuals operating unincorporated businesses (known as sole proprietorships), which may or may not be the owner’s principal source of income.”

Various analysts have used these data to track the rise of self-employment with many arguing that the rapid rise of nonemployer establishments reflect a surge of self-employment and gig work. Abraham et al. (2017) note that the growth of nonemployer establishments was faster than self-employment in the Current Population Survey (CPS). They cite this evidence (along with tax records) as being consistent with the argument that the CPS is missing some of the growth of in self-employment, pointing out that nonemployer establishments “have trended upwards as a percent of the number of earners.” Steve King of Emergent Research, a leading analyst of gig and “independent worker” trends, has also said that nonemployer data are “a useful general indicator of U.S. self-employment.”

All of the analyses we have seen of these data solely focus on headcount measures, tracking the number of nonemployer establishments, and do not examine the economic impact, as we do in our analysis by examining the revenues of nonemployer establishments.

This may be surprising since the Census used to (but now does not) warn data users of the following:

“The majority of all business establishments in the United States are nonemployers, yet these firms average less than 4 percent of all sales and receipts nationally. Due to their small economic impact, these firms are excluded from most other Census Bureau business statistics.”Read more

There is much discussion about the potential for artificial intelligence (AI) to transform our workplaces, possibly leading to fewer overall jobs and greater economic inequality in the future. This discussion has always made me wonder to what extent AI is already being used to produce goods and services. So, I was excited to learn about the AI Index from reading the recent Furman and Seamans paper on “AI and the Economy.” Furman and Seamans write: “The AI index, a non-profit project designed to track activity and progress in AI, provides a number of interesting facts designed to track the scientific progress in and impact of artificial intelligence and robotics.” I was even more excited to see the AI index reporting on “the growth of the share of US jobs requiring AI skills.” However, my excitement soon ended when I realized that the information they offered completely obscured the (lack of) importance of the underlying data, and I have to reluctantly conclude that the AI index offers extremely misleading hype on AI jobs rather than useful information. I am getting tired of overhyped phenomena, so this blog post is to alert the public.

The AI Index highlights the fact that “the share of jobs requiring AI skills in the US has grown 4.5x since 2013” (see the graph below). That sounds like a huge explosion of jobs related to AI, right? But exactly how many jobs are they talking about being AI-related now compared with in the past? One cannot tell from their information, because while it shows the growth in the share of AI jobs, it provides no information of the level of these shares (either now or in the past). I am always careful to not present data showing the percent changes of percentages, because this is often misleading. For example, when a share rises from 1 percentage point to 2 percentage points, it has risen 100 percent. If a share rises from 20 percentage points to 22 percentage points, it has only risen by 10 percent. Yet in the latter example the change in the level of the share is twice as large (2 percentage points, compared to 1). So what does it tell us about the share of AI jobs in the economy today to tell us that this share has grown 350 percent, without telling us the initial level of the share? Absolutely nothing.

Read more

This post originally appeared on the CEPR blog.

Earlier this year we did an analysis of CEO compensation in the health insurance industry to see if it was affected by the cap on deductibility imposed by the Affordable Care Act (ACA). One of the provisions of the ACA limited the amount of CEO pay that health insurers could deduct on their taxes to $500,000, beginning in 2013.

This provision effectively raised the cost of CEO pay to insurers by more than 50 percent. Prior to 2013, the deduction in effect meant that the government was picking up 35 cents of every dollar of CEO pay, while the companies were paying just 65 cents. 1 With the new provision in place, insurers are now paying 100 cents of every dollar of CEO pay in excess of $500,000.

If the pay reflects the value of the CEO to the company, we should expect this change to reduce the pay of CEOs in the insurance industry. For example, if a CEO gets paid $20 million a year, this should mean that she delivers roughly $20 million in additional value to shareholders.

When the CEO’s pay was fully deductible, the $20 million paid to the CEO actually only cost the company $13 million. This would presumably be the number that matters to shareholders since they care about how much money comes out of their pockets, not the number on the CEO’s paycheck.

Read more

Police in Westport, Connecticut are resisting an attempt to slash their pension and partially replace it with a 401(k)-style plan. Such a move would mess with a tried-and-true system that promotes secure and orderly retirement, in favor of an inefficient one that harms workers with no benefit to taxpayers.

Westport is a latecomer to a trend that appears to have nearly run its course. A few years ago, the Wall Street Journal praised San Jose Mayor Chuck Reed for taking an axe to police and other public employee pensions. Along with Rhode Island Treasurer (later Governor) Gina Raimondo, Reed had become a public face of the pension gutting movement, leading a statewide initiative backed by hedge fund billionaires. Reed and Raimondo, both Democrats, were lauded by conservative think tanks and the Journal for taking on public-sector unions, ignoring the fact that they were courting more powerful interests—the financial industry and wealthy donors.

Similar initiatives followed in Dallas, Memphis, and Palm Beach, among other places. But as the Journal reported last year, in an apparent change of heart, cities that slashed police pensions were later forced to restore benefits or spend millions on retention bonuses in efforts to stem outflows of experienced officers. In Palm Beach, for example, 24 mid-career police officers left in the four-year period after the city cut police and firefighter pensions and partly replaced them with 401(k)-style plans, compared with just one mid-career officer in the previous four years. The exodus of police and firefighters to neighboring jurisdictions caused the city to incur millions in additional training and overtime costs. Five years later, the city reversed course, restoring pension benefits and dropping the 401(k)-style plans.

Read more

There’s no real news in the Social Security trustees report released this afternoon. We’re now a year closer to the date the trust fund will be exhausted, 2034 (same as last year’s projection), at which point current revenues will still be sufficient to cover 77 percent of benefits even if nothing is done to shore up the system’s finances. Each year, the release of the trustees report provides an occasion for Social Security scaremongering by those wanting to shrink our social insurance system. But not only can we afford current benefits, we can afford to expand them.

The average retired worker beneficiary receives an annual benefit of $16,933. Disability and survivor benefits are even more modest. Social Security benefits are replacing a declining share of income at retirement, thanks to a rising normal retirement age and increased taxation of benefits—cuts passed in 1983 that are gradually taking effect (an increase in the retirement age is really just an across-the-board benefit cut that can be offset by retiring later). Rising Medicare premiums, which are deducted from Social Security, also reduce net benefits.

Despite these trends, recent Census research has found that retirees are somewhat better off than previously thought, thanks to income from traditional defined benefit pensions that is underreported in household surveys. Nevertheless, Social Security remains by far the most important source of income for most seniors. It constitutes most of the income of seniors in the bottom half of the income distribution and is the single biggest source of income for all but those in the ninth and tenth income deciles, for whom defined benefit pensions and earned income loom larger.

Read more

As debate continues on a referendum to raise the tipped minimum wage in Washington, D.C., to the minimum wage for nearly all other workers, we wanted to take a few minutes to set the record straight on the facts about tipped worker wages and incomes. Currently, eight states do not have differential treatments of the tipped workforce in terms of the minimum wage.1 Throughout this post, these will be referred to as “equal treatment” states. To be clear, tipped workers in these equal treatment states receive the full, regular state minimum wage plus tips.

Over the last several years, there has been a great deal of research about the minimum wage and tipped restaurant workers, in particular, and we are going to draw on some of that research to make several key points: 1. In the District of Columbia, women, African American, and Hispanic workers are disproportionately minimum wage workers, including tipped minimum wage workers; 2. Maintaining a separate, lower minimum wage for tipped workers perpetuates racial and gender inequities; 3. In states that have a lower tipped minimum wage, tipped workers have worse economic outcomes and higher poverty rates than their counterparts in equal treatment states; 4. Tipped work is overwhelmingly low-wage work, even in D.C.; 5. Wage theft is particularly acute in food and drink service, and restaurants across the country have been found to be in violation of wage and hour laws; 6. Waitstaff have higher take-home pay in equal treatment states than in D.C.; and 7. The restaurant industry thrives in equal treatment states.

Here, we take a closer look at each point:

1. Women, African Americans, and Hispanic workers have disproportionately benefited from minimum wage increases in Washington, D.C. Furthermore, contrary to popular opinion, the vast majority of minimum-wage earners are not teenagers or college students working part-time jobs.

2. Research indicates that having a separate, lower minimum wage for tipped workers perpetuates racial and gender inequities, and results in worse economic outcomes for tipped workers. Forcing service workers to rely on tips for their wages creates tremendous instability in income flows, making it more difficult to budget or absorb financial shocks. Furthermore, research has also shown that the practice of tipping is often discriminatory, with white service workers receiving larger tips than black service workers for the same quality of service.

Read more

Although in last month’s jobs report we saw a fall in the unemployment rate accompanied by a drop in labor force participation—which showed the unemployment rate dropping for the wrong reasons—the longer-term trends suggest that displaced workers continue to return to the labor market. This is to be expected as the labor market improves, and what we’ve been expecting for years. The unemployment rate of 3.9 percent seems to be overstating the strength of the labor market given how many sidelined workers appear to want jobs. Furthermore, upwards of 70 percent of the newly employed are coming from out of the labor force as opposed to those “actively” looking for work, that is, among those officially counted in the U3 unemployment rate. We only need to look as far as nominal wage growth to know that we are not yet unambiguously at full employment. Employers and workers alike seem to recognize the slack out there and workers still do not have sufficient leverage to bid up their wages. Year-over-year nominal wage growth has averaged 2.6 percent over the last couple of years, consistently below target levels.

Unfortunately, nominal wage growth for private-sector workers found in the monthly jobs report’s payroll survey offers only a limited view on wage growth in the economy today. One of the major benefits of a full employment economy is that wage growth isn’t simply strong for workers at the top of the wage distribution or for workers with more educational attainment, but that it allows low-wage workers to make gains as well. To get finer-grained estimates of what’s happening to wage growth for particular groups of workers, we have to turn to the Current Population Survey Outgoing Rotation Group (ORG). The ORG is a household-based survey, not an employer-based one like the payroll survey, which each month provides widely reported estimates of job growth and wage growth for private-sector workers. This is important because this means the ORG can not only ask questions of wages, but also make comparisons of wages across the wage distribution. Adding to that information gleaned from the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) allows for comparisons about incomes, notably information on poverty rates.

Over the last couple of weeks, EPI has been highlighting some important statistics in commemoration of the 50th anniversary of the Poor People’s Campaign. We’ve pointed out the changes in the poverty rate over the last 50 years, where gains have been made, particularly among the elderly, and where disparities remain. We also discussed how poverty reduction can be improved with a stronger safety net and a better labor market. The truth is that full employment that makes more hours available to lower-wage workers and broad-based wage growth are key tools in the fight against poverty, and many people who live below the poverty line rely on a stronger economy to make ends meet.

Read more

Uber made news yesterday when the company announced that it will end mandatory arbitration for sexual harassment and assault complaints. Lyft quickly followed suit and said that it would also do away with mandatory arbitration agreements for sexual misconduct claims. These companies are the latest in a growing number of corporations that have moved to eliminate mandatory arbitration agreements for sexual harassment claims. There is no doubt that these companies are being driven to action by the power of #MeToo and #TimesUp. And, while a move away from mandatory arbitration by firms like Uber and Microsoft should be celebrated as a victory for these movements, it is important to recognize that for women in low-wage jobs, challenging workplace sexual harassment and assault remains largely impossible, unless companies also end bans on class and collective action.

Workers depend on class and collective actions to enforce many workplace rights. Employment class action cases have helped to combat race and sex discrimination and are fundamental to the enforcement of wage and hour standards. Without the ability to aggregate claims, it would be very difficult, if not impossible, for workers to find legal representation in these matters. This is particularly true for low-wage workers, whose cases are unlikely to involve large enough awards to attract attorneys to invest time in the case. That is the power of class and collective action suits: they let workers pool their claims, making it possible for an attorney to earn enough to make the case worth pursuing.

Banning mandatory arbitration in sexual harassment and sexual assault claims but continuing to restrict class and collective action will do little to help women in low-and middle-wage jobs access justice when they face sexual harassment or assault. These women will still face challenges finding legal representation and find the cost of litigation prohibitive. And it will do nothing to help women facing other kinds of workplace violations. This is especially concerning considering the majority of low-wage workers in the United States are women.  And research shows that low-wage workers in the United States lose more than $50 billion annually as a result of wage theft by their employers. Workers have the right to a workplace free of sexual harassment as well as their right to be paid fairly, and creating a hierarchy of worker protection laws by privileging certain types of claims over others is fundamentally unjust—particularly for low-wage workers. Companies should not be applauded for such a minimal response to workplace misconduct and advocates should not be fooled into seeing this as a solution.

Our nation’s labor and employment laws need reform. A key element of reform must be to end employers’ ability to require workers to sign away their rights as a condition of employment. The Supreme Court will soon decide National Labor Relations Board v. Murphy Oil USA, which will determine whether employers can lawfully require workers to sign arbitration agreements that include class and collective action waivers. If the Court denies workers this fundamental right, Congress must act to protect it. If policymakers leave the solution to corporations, we will end up with a system that privileges some claims and fails most workers.

The last few years has seen a major shift in minimum wage policies as states like California and New York and cities like Seattle and Washington, DC, have passed laws phasing in a $15 minimum wage, targeting bolder increases than had been the pattern over the last two decades. Federal proposals such as the Raise the Wage Act of 2017, which would bring the minimum wage to $15 by 2024, are consistent with these bolder local approaches. This is bold, as it mandates a 71.9 percent real increase in the minimum wage. But even this bold increase only brings the minimum wage to 29 percent above its 1968 purchasing power, despite productivity nearly doubling over the same timeframe. Many policymakers have concluded, in effect, that years of modest or no change in the minimum wage have created a situation where bold increases are required just to move the minimum wage closer to being a living wage.

This shift in policy now necessitates a rethinking of the flawed way we have evaluated minimum wage increases over the last few decades. There have been, in particular, two flaws. One was first highlighted by economists Fiedler, Howell, and Luce, who noted that public discussion of various minimum wage proposals, including among economists, tends to center solely on whether there will be any job loss. In effect, minimum wage proposals are being evaluated according to a “no job loss” criterion, which specifies that the “right” wage floor is the one that previous research has demonstrated will pose little or no risk of future job loss, anywhere.” A no job loss criterion implies that if a minimum wage increase has any costs (whether loss of employment or work hours), regardless of benefits, then it is inappropriate.

Read more

Earlier this week, EPI released an analysis of economic performance in Wisconsin and Minnesota since 2010, which showed that by virtually every available measure, Minnesota has outperformed Wisconsin. This is notable because lawmakers in the two states adopted vastly different policy agendas coming out of the recession. Wisconsin adopted a highly conservative agenda of cutting taxes, shrinking government, and weakening unions. Minnesota, in contrast, enacted many key progressive priorities: raising the minimum wage, strengthening safety net programs and labor standards, and boosting public investment in infrastructure and education, financed by raising taxes, primarily on the wealthy.

Skeptical readers might argue that as much as the two states are similar, they are sufficiently different such that the diverging economic outcomes observed in our report are the result of fundamental differences in the two states’ economies and that state policy decisions were largely irrelevant. I think there’s ample evidence to indicate that such readers are wrong. In the paper, I discuss some of the policy decisions—such as those around Medicaid expansion, investment in infrastructure, and worker organizing—where one can draw a fairly straight line from the policy decision to the observed economic result. I also note that wage growth was actually stronger in Wisconsin than Minnesota in the seven years prior to Great Recession.

It’s also instructive to compare job growth in the two states in the economic expansion prior to the Great Recession. The data suggest that whatever their differences, prior to the recession, Wisconsin and Minnesota followed a very similar trajectory for employment growth.

Figure A

Minnesota and Wisconsin had similar job growth trends leading up to the Great Recession, but not after it: Employment levels relative to the start of Governor Walker and Governor Dayton’s terms (Jan 2011)

	UNITED STATES	Minnesota	Wisconsin
Nov-2001	100.2%	100.5%	101.6%
Dec-2001	100.1%	100.2%	101.3%
Jan-2002	100.0%	100.2%	101.5%
Feb-2002	99.9%	100.2%	101.5%
Mar-2002	99.9%	100.0%	101.5%
Apr-2002	99.8%	100.0%	101.4%
May-2002	99.8%	100.0%	101.4%
Jun-2002	99.9%	100.1%	101.4%
Jul-2002	99.8%	100.3%	101.3%
Aug-2002	99.8%	100.1%	101.4%
Sep-2002	99.7%	100.3%	101.2%
Oct-2002	99.8%	100.0%	101.6%
Nov-2002	99.8%	100.2%	101.8%
Dec-2002	99.7%	100.0%	101.5%
Jan-2003	99.8%	100.1%	101.2%
Feb-2003	99.7%	100.1%	101.3%
Mar-2003	99.5%	100.0%	101.1%
Apr-2003	99.5%	100.1%	101.2%
May-2003	99.5%	100.1%	101.2%
Jun-2003	99.5%	99.9%	101.1%
Jul-2003	99.5%	99.9%	100.7%
Aug-2003	99.5%	100.0%	100.7%
Sep-2003	99.5%	100.0%	100.9%
Oct-2003	99.7%	99.8%	101.3%
Nov-2003	99.7%	99.7%	101.3%
Dec-2003	99.8%	99.9%	101.4%
Jan-2004	99.9%	99.8%	101.5%
Feb-2004	100.0%	99.9%	101.6%
Mar-2004	100.2%	100.0%	101.7%
Apr-2004	100.4%	100.6%	101.8%
May-2004	100.6%	100.8%	102.0%
Jun-2004	100.7%	100.8%	102.1%
Jul-2004	100.7%	100.8%	102.5%
Aug-2004	100.8%	100.9%	102.8%
Sep-2004	100.9%	101.0%	102.4%
Oct-2004	101.2%	101.3%	102.8%
Nov-2004	101.3%	101.3%	102.8%
Dec-2004	101.4%	101.4%	102.8%
Jan-2005	101.5%	100.9%	102.8%
Feb-2005	101.7%	101.2%	103.1%
Mar-2005	101.8%	101.3%	103.2%
Apr-2005	102.0%	102.0%	103.5%
May-2005	102.2%	102.3%	103.3%
Jun-2005	102.4%	102.1%	103.2%
Jul-2005	102.6%	102.6%	103.5%
Aug-2005	102.8%	102.7%	103.6%
Sep-2005	102.8%	102.9%	103.9%
Oct-2005	102.9%	103.0%	103.7%
Nov-2005	103.2%	103.1%	103.8%
Dec-2005	103.3%	103.2%	104.0%
Jan-2006	103.5%	103.6%	104.0%
Feb-2006	103.7%	103.7%	104.1%
Mar-2006	104.0%	103.9%	104.2%
Apr-2006	104.1%	103.7%	104.4%
May-2006	104.1%	103.4%	104.2%
Jun-2006	104.2%	103.7%	104.5%
Jul-2006	104.3%	103.6%	104.4%
Aug-2006	104.5%	103.6%	104.4%
Sep-2006	104.6%	103.6%	104.5%
Oct-2006	104.6%	103.4%	104.4%
Nov-2006	104.7%	103.5%	104.5%
Dec-2006	104.9%	103.8%	104.6%
Jan-2007	105.1%	104.0%	104.7%
Feb-2007	105.1%	104.1%	104.7%
Mar-2007	105.3%	104.2%	104.8%
Apr-2007	105.3%	104.1%	104.8%
May-2007	105.4%	104.0%	105.0%
Jun-2007	105.5%	104.2%	105.4%
Jul-2007	105.5%	104.2%	105.1%
Aug-2007	105.5%	104.1%	105.1%
Sep-2007	105.5%	104.0%	105.1%
Oct-2007	105.6%	104.0%	104.8%
Nov-2007	105.7%	104.1%	104.8%
Dec-2007	105.8%	104.1%	105.0%
Jan-2008	105.8%	104.3%	105.2%
Feb-2008	105.7%	104.5%	105.2%
Mar-2008	105.7%	104.4%	105.0%
Apr-2008	105.5%	104.1%	104.9%
May-2008	105.3%	104.1%	105.0%
Jun-2008	105.2%	104.0%	104.9%
Jul-2008	105.1%	103.9%	104.8%
Aug-2008	104.9%	103.8%	104.6%
Sep-2008	104.5%	103.6%	104.7%
Oct-2008	104.1%	103.4%	104.3%
Nov-2008	103.6%	103.0%	104.0%
Dec-2008	103.0%	102.5%	103.4%
Jan-2009	102.4%	101.8%	102.5%
Feb-2009	101.9%	101.2%	101.9%
Mar-2009	101.3%	100.6%	101.1%
Apr-2009	100.7%	100.0%	100.3%
May-2009	100.5%	100.0%	100.3%
Jun-2009	100.1%	99.4%	99.8%
Jul-2009	99.8%	99.3%	99.4%
Aug-2009	99.7%	99.0%	99.1%
Sep-2009	99.5%	98.4%	99.1%
Oct-2009	99.4%	98.8%	99.1%
Nov-2009	99.4%	98.8%	98.9%
Dec-2009	99.2%	98.9%	98.9%
Jan-2010	99.2%	98.7%	98.9%
Feb-2010	99.1%	98.6%	98.9%
Mar-2010	99.3%	98.7%	99.0%
Apr-2010	99.4%	99.0%	99.4%
May-2010	99.8%	99.2%	99.5%
Jun-2010	99.7%	99.2%	99.4%
Jul-2010	99.7%	99.1%	99.5%
Aug-2010	99.7%	99.3%	99.6%
Sep-2010	99.6%	98.9%	99.6%
Oct-2010	99.8%	99.6%	99.9%
Nov-2010	99.9%	99.7%	99.9%
Dec-2010	100.0%	99.7%	99.9%
Jan-2011	100.0%	100.0%	100.0%
Feb-2011	100.1%	100.1%	100.1%
Mar-2011	100.3%	100.3%	100.2%
Apr-2011	100.6%	100.5%	100.3%
May-2011	100.6%	100.8%	100.3%
Jun-2011	100.8%	100.8%	100.2%
Jul-2011	100.9%	100.2%	100.7%
Aug-2011	101.0%	101.1%	100.6%
Sep-2011	101.1%	101.6%	100.7%
Oct-2011	101.3%	101.4%	100.5%
Nov-2011	101.4%	101.5%	100.5%
Dec-2011	101.6%	101.6%	100.8%
Jan-2012	101.8%	101.7%	100.6%
Feb-2012	102.0%	101.8%	100.8%
Mar-2012	102.2%	102.2%	101.4%
Apr-2012	102.3%	102.5%	101.7%
May-2012	102.4%	102.1%	101.6%
Jun-2012	102.4%	102.3%	101.6%
Jul-2012	102.5%	102.0%	101.2%
Aug-2012	102.7%	102.4%	101.4%
Sep-2012	102.8%	103.0%	101.6%
Oct-2012	102.9%	103.0%	101.8%
Nov-2012	103.0%	103.2%	102.1%
Dec-2012	103.2%	103.3%	101.9%
Jan-2013	103.4%	103.7%	101.6%
Feb-2013	103.6%	104.0%	102.2%
Mar-2013	103.7%	104.1%	102.3%
Apr-2013	103.8%	103.4%	101.9%
May-2013	104.0%	104.0%	102.3%
Jun-2013	104.1%	104.2%	102.5%
Jul-2013	104.2%	103.7%	102.5%
Aug-2013	104.4%	104.2%	102.7%
Sep-2013	104.6%	104.7%	102.9%
Oct-2013	104.7%	104.8%	103.0%
Nov-2013	104.9%	104.9%	103.0%
Dec-2013	105.0%	105.0%	103.1%
Jan-2014	105.1%	104.9%	103.3%
Feb-2014	105.2%	105.0%	103.3%
Mar-2014	105.4%	105.0%	103.4%
Apr-2014	105.7%	105.0%	103.6%
May-2014	105.9%	105.6%	103.8%
Jun-2014	106.1%	105.8%	104.0%
Jul-2014	106.3%	105.9%	104.1%
Aug-2014	106.4%	106.0%	104.5%
Sep-2014	106.6%	105.9%	104.5%
Oct-2014	106.8%	106.1%	104.5%
Nov-2014	107.1%	106.3%	104.9%
Dec-2014	107.3%	106.4%	104.8%
Jan-2015	107.4%	106.4%	104.9%
Feb-2015	107.6%	106.6%	105.0%
Mar-2015	107.7%	106.7%	105.1%
Apr-2015	107.9%	106.9%	105.2%
May-2015	108.2%	107.3%	105.4%
Jun-2015	108.3%	107.4%	105.5%
Jul-2015	108.5%	107.6%	105.7%
Aug-2015	108.6%	107.5%	105.7%
Sep-2015	108.7%	107.4%	105.8%
Oct-2015	109.0%	107.8%	105.9%
Nov-2015	109.2%	108.0%	105.9%
Dec-2015	109.3%	108.0%	106.2%
Jan-2016	109.4%	108.1%	106.5%
Feb-2016	109.6%	108.3%	106.6%
Mar-2016	109.8%	108.3%	106.6%
Apr-2016	109.9%	108.5%	106.8%
May-2016	109.9%	108.5%	106.6%
Jun-2016	110.2%	108.2%	106.5%
Jul-2016	110.4%	109.0%	106.9%
Aug-2016	110.5%	109.2%	107.1%
Sep-2016	110.7%	109.2%	107.0%
Oct-2016	110.9%	109.1%	106.9%
Nov-2016	111.0%	109.3%	107.2%
Dec-2016	111.1%	109.2%	107.0%
Jan-2017	111.3%	109.9%	107.3%
Feb-2017	111.5%	110.0%	107.4%
Mar-2017	111.5%	110.2%	107.4%
Apr-2017	111.7%	109.9%	107.4%
May-2017	111.8%	110.0%	107.4%
Jun-2017	112.0%	110.1%	107.5%
Jul-2017	112.1%	110.3%	107.5%
Aug-2017	112.3%	110.2%	107.4%
Sep-2017	112.3%	110.3%	107.4%
Oct-2017	112.5%	110.6%	107.5%
Nov-2017	112.7%	110.6%	107.5%
Dec-2017	112.8%	110.7%	107.8%

ChartData Download data

The data below can be saved or copied directly into Excel.

The data underlying the figure.

Source: EPI analysis of Current Employment Statistics data from the Bureau of Labor Statistics

Share on Facebook Tweet this chart

Embed

Copy the code below to embed this chart on your website.

<iframe width="100%" height="460" src="https://www.epi.org?p=147474&view=embed&embed_template=charts_v2013_08_21&embed_date=20260709&onp=147643&utm_source=epi_press&utm_medium=chart_embed&utm_campaign=charts_v2" frameborder="0"></iframe>

Download image

Figure A shows the number of jobs in Wisconsin, Minnesota, and the United States from November 2001 to December 2017, relative to the number of jobs in each geography in January 2011, the month that Governors Walker and Dayton took office. As you can see from the figure, changes in the level of jobs throughout the business cycle leading up to the Great Recession were remarkably similar between the two states. Both Minnesota and Wisconsin had modest job losses in the beginning of the period in the wake of the early 2000s recession, followed by modest job growth that tracked the U.S. average for a while and then flattened out for roughly the last two years prior to the onset of the Great Recession. In that earlier business cycle from November 2001 to December 2007, cumulative job growth was 3.7 percent in Minnesota and 3.3 percent in Wisconsin. Subsequently, the two states suffered losses in the recession that were similar, albeit slightly more severe in Wisconsin—with losses of 4.3 percent and 4.9 percent in Minnesota and Wisconsin, respectively, from December 2007 to December 2010.

The period from January 2011 to December 2017, after Governors Walker and Dayton assumed office, shows a starkly different picture. From early on in the recovery, Minnesota’s job growth accelerated noticeably more quickly than Wisconsin’s and the gap between the two states has increased fairly steadily ever since.

Read more