Nir Jaimovich and Henry Siu have written a very helpful and useful paper that summarizes the empirical literature by labor economists on how automation affect the labor market and the middle class.

Their main arguments can be summarized as follows:

• The labor markets in the US (and other industrialized countries) has become increasingly “polarized” in recent decades, as wage and employment have grown at the top and bottom of the market while they have declined in the middle.
• The polarization has mostly been driven by skill-biased technical change (rather than globalization), with automation replacing workers performing mostly routine tasks in production and clerical occupations.
• Less-educated workers and especially men have been most hurt by these forces, with many exiting the labor force as their prospective earnings have fallen.
• These forces will likely continue to occur as robotics and artificial intelligence (AI) spread throughout the labor market in the coming years and decades.
• But humans will retain a “comparative advantage” relative to machines in many jobs, especially those requiring the performance of social and interactive personal tasks.
• Policy options such as retraining displaced workers for such jobs look promising and should be further explored.

I find most of these arguments quite reasonable and well-supported by the evidence they provide. At the same time, their presentation of the literature on job polarization is a bit one-sided. Counter-arguments and evidence such as that provided by Hunt and Nunn (2019) get very little attention in this paper.

While the authors do acknowledge a few important and contrary points – such as the far greater growth of employment in low-wage than high-wage occupations since the Great Recession – a more balanced discussion of this literature would have been welcome. For instance, nowhere do they even acknowledge evidence that labor market outcomes may have been heavily affected by institutional as well as market forces, as Fortin et al. (2018) have recently shown. And the important growth of middle-paying jobs requiring some postsecondary education in health care, information technology and other fields is only acknowledged towards the very end of the paper.

More broadly, I find the paper useful as a summary of the mostly academic research among economists in this area, but it ignores other important research and policy analysis on these issues. As such, the paper is extremely cautious when it comes to fleshing out the likely future effects of automation in the labor market, as well as important policy prescriptions; and its appeal to more applied audiences will be limited.

For instance, on the supply (worker) side of the labor market, social scientists have reviewed the most important “21^st century skills” that will likely complement automation – besides just social/interactive ones (National Academies of Science, 2014). On the demand side, it is clear that employers have many choices on how to implement automation (Helper et al., 2019) – and that worker voice in this process can really affect outcomes such as whether workers are retrained for new jobs or displaced. Recent trends on the demand side that will likely inhibit worker voice in these matters – such as the increasingly “fissured” workplace in which responsibility for training and other human resource functions is outsourced to other firms (Weil, 2014) – will affect outcomes as well.

The broad range of social, economic, institutional, and policy forces that will determine the pace and nature of automation (National Academies of Science, 2017) need more coverage here. The likely labor market effects of future automation in the labor market could also be fully fleshed out. For instance, it is likely that automation will raise average worker productivity and therefore compensation over time, but inequality will probably rise while labor force participation falls (Holzer, 2019). Automation will continue to hurt less-educated workers relatively more than those more-educated, as the incidence of displacement will be higher among the former while adjustments through the development of skills that complement automation will be more successful among the latter.

If accurate, these projections also imply the need for policies that go well beyond those reviewed by Jaimovich and Siu. Such policies might include:

• Greater efforts to teach students a range of “21^st century skills” in grades K-12 and beyond;
• Lifelong learning accounts for workers that will pay for new skill development (Fitzpayne and Pollack, 2018) when they face displacement, as well as efforts to make new training more accessible to working students (through online teaching platforms);
• Improving the quality of displaced worker training in the labor market, which now has limited success (Jacobson et al., 2005);
• Subsidizing employer provision of on-the-job training for workers facing imminent displacement;
• Raising taxes on employers who displace workers (but not on adoption of robotics or AI per se) beyond that currently provided by experience rating in the Unemployment Insurance system;
• Strengthening the workforce development system through more resources for One-Stop offices and certificate programs in community colleges;
• Strengthening worker “voice” in the workplace (Kochan and Kimball, 2019); and
• Providing wage insurance for displaced workers who can only gain new jobs at well below their former levels of pay.

Thus, while the paper by Jaimovich and Siu provides a useful review of the academic literature on automation and polarization by labor economists, we should cast a wider net when discussing their potential labor market effects and appropriate policy responses.

       

September is Workforce Development Month and Congress has until the end of the month to reach an agreement to fund the government, including many workforce and education programs that rely on this investment to help workers prepare for jobs at the backbone of our economy – those that require some postsecondary education but not a four-year degree. These programs have helped prepare millions of nurses, carpenters, computer support specialists and machinists across the country for their careers.

Congressional investment in skills for backbone jobs is overwhelmingly popular. Nearly 80 percent of leaders of small or mid-size companies support new, public investments in skills as do 93 percent of likely 2020 voters. And more than just being popular, voters are 50 percent more likely to vote for candidates who are strong on skills.

But we have done much too little in the U.S. to help workers without BA degrees. Such workers make up two-thirds of all Americans, and their wages have largely stagnated over the past four decades while those with college degrees have made strong advances. Men with high school or less education have been hit particularly hard, as unskilled but well-paid manufacturing and other blue-collar jobs have disappeared. And good-paying in health care, advanced manufacturing, IT and transportation/logistics are out of their reach, since they require education and training that most have not received.

Employers in these sectors also have difficulty finding skilled workers for these jobs, especially in a tight labor market like we now have. More employers could invest in training their workers, but this is a difficult task for small and medium-sized employers who face large startup costs for such training, and who worry that these newly trained workers might not stay with their firms. Such employers can clearly benefit from more training in community colleges, or work-based learning options like apprenticeship in which their participation remain too low.

Making such public investments is growing more critical than ever. In addition to addressing the current needs of workers and employers, our workforce system will soon bear the responsibility of preparing workers for the jobs of the 21st century, responding to changes caused by technology, automation and artificial intelligence (AI). Millions will face possible displacement from their current jobs, and will need to retrain to keep those jobs or find new ones. And the changing demographics of the U.S., as baby boomers age and retire, will require an especially robust effort to prepare those from lower-income or foreign-born families for the new needs of the workplace.

But our public investment in skills hasn’t even come close to meeting workers needs or business demand, let alone achieving parity with the investment of other industrialized countries. According to a recent report from the White House’s Council of Economic Advisers, a report flawed in much of its analysis of workforce academic literature, but accurate in its assessment of U.S. investment, the U.S. would need to invest $80 billion more annually just to reach the average investment other OECD countries. The nearly $19B of federal funding for the U.S. invests in workforce programs constitutes less than one-tenth of one percent of U.S. GDP, a paltry sum in comparison to spending in most European Union countries on “active labor market policy” and for an American economy with 160 million workers.

Instead of recognizing this imperative, Congress has, since 2001, passed spending bills that have cut funding for our public workforce system by 40 percent, for career and technical education by nearly 30 percent and for adult basic education by nearly 15 percent. Even the guidance and other workforce services provided by local One-Stop offices of the Labor Department, which are very clearly cost-effective, have been starved for funds in this era.

Of course, state and federal governments do spend very heavily on subsidizing higher education in public colleges and universities, including community colleges, where certificate and associate degree programs help prepare both youth and adults for the good jobs now available that don’t require BAs. But students in many such shorter-term and non-credit programs are not eligible federal Pell grants and loans, and the colleges themselves are often too strained for cash to expand teaching capacity in these fields or provide guidance and supports (like child care) for students who desperately need them.

The imperative of these investments can be seen by looking at what participation in them can mean for workers and businesses. The best “sector-based” or “career pathway” programs show large and lasting impacts on disadvantaged worker earnings. These mostly local (though now spreading) programs – like Per Scholas, Project QUEST, the Wisconsin Regional Training Partnership, the Jewish Vocational Services-Boston, and Year Up – have generated large and lasting earnings impacts in several rigorous evaluation studies.

Of course, training alone – even robust programing with wrap around supports – isn’t a panacea for economic inequality, the racial wealth gap or business skill needs. But it’s a piece of the puzzle. A sensible policy discussion would focus on how to replicate and scale the best sector-based efforts at community colleges or other training providers with available or new federal and state funding. And Congress can start this conversation now by investing in skills training that works.

       

The Department of Education has rescinded the Gainful Employment regulations developed by the Obama administration. These regulations were designed to cut off federal student aid to postsecondary programs that produce earnings too low to support the debt students incur while earning credentials that promise to lead to good jobs. This action is a significant step toward removing necessary protections for vulnerable students.

In an effort to justify its action, the department cited research about community colleges in our 2017 book, Making College Work, seriously distorting its message.

Our work shows that unlike other community-college credentials, which are valued by employers, associate degrees in the liberal arts hold little labor market value as final degrees. The Education Department uses this finding to argue that the gainful-employment rules — which actually apply to non-degree programs at all institutions, not just the for-profits — unfairly singled out the for-profit institutions. The department rescinded these rules rather than applying them strongly and sensibly or improving them.

The problems some community-college students face in no way justify loosening the accountability of for-profit institutions. Most for-profit programs explicitly promise students preparation for specific occupations. General associate degrees are not directly career oriented; instead they are designed to lead to transfer to four-year programs.

As we note in our book, credentials from for-profit institutions often have less value than similar ones from community colleges, while students pay vastly more for them. Indeed, the evidence is even more negative now on the value of for-profit credentials than when we wrote our book.

Credentials from for-profit institutions often have less value than similar ones from community colleges, while students pay vastly more for them.

Moreover, debt loads are much higher among for-profit students than among those who attend community colleges. More than half of the students who earn certificates and associate degrees at public two-year colleges leave without debt. Only about a quarter borrow $10,000 or more. Tuition prices are much higher at for-profit institutions and the vast majority of students borrow; almost 60 percent of associate-degree recipients borrow $20,000 or more and about 20 percent of those earning short-term certificates in this sector borrow this much.

Given these facts, we clearly and explicitly argue for stronger regulation of the for-profit schools, through Gainful Employment or other such rules. Treating them differently than community colleges makes complete sense, in light of their stated goals and their worse records on all of these dimensions.

But the Education Department not only ignores our writings on for-profit institutions; they also distort and misinterpret our results on liberal arts associate degrees.

Though associate degrees in liberal arts have little market value on their own, they can be valuable for students who transfer to four-year institutions; and liberal-arts curricula in community colleges provide important general education for all students, even in occupational programs, no doubt improving their problem-solving and communications skills.

We therefore argue in our book that, while more students should be encouraged to earn associate degrees in high-value fields, we should also improve transfer to and completion at four-year schools — rather than abandoning associate degrees in liberal arts or regulating them.

It is important to recognize the strengths and weaknesses of all programs at all institutions. But the problem of students incurring high levels of debt while pursuing preparation for specific types of employment is unique to the programs covered by the gainful-employment rules. The decision to rescind these rules is a mistake, given the poor record of the for-profit institutions. To base that decision to any extent on a misreading of our research adds insult to injury. The department should not misuse such research to justify its ill-advised policy actions.

       

Abstract

Current estimates suggest that over the coming decades, slower population growth and lower labor force participation will constrain the supply of labor in the U.S. The U.S. labor force will also become more diverse as immigration and fertility trends increase the size of minority populations. New forms of automation will likely require workers to adapt to keep their old jobs, while many will be displaced or face less demand for their work (while others benefit). Firms will continue to implement alternative staffing arrangements, like turning workers into independent contractors or outsourcing their human resource management to other firms; and many will adopt “low-road” employment practices to keep labor costs low. Exactly whom these changes will benefit or harm remains unclear, the author finds, though non-college workers will likely fare the worst; higher productivity from new technologies and reduced labor supply could raise average wages, but many workers will clearly be worse off. According to the author, policymakers should provide incentives for firms to train current employees, rather than replace them, and should encourage schools and colleges to teach flexible, transferable skills, as the future workforce will likely need to adapt quickly to new and changing job requirements. Lifelong learning accounts for workers could help. Expanding wage insurance and improving unemployment insurance and workforce services could help workers adapt after suffering job displacement. Policies that make work pay, like the EITC, and others designed to increase labor force attachment, like paid family leave, could help mitigate declines in the labor force. Reforms in immigration and retirement policy will help as well, as would policy experimentation at the state and local level (with federal support).

       

The Higher Education Act (HEA) is the primary law through which the federal government regulates and helps finance postsecondary education in the United States. Title IV, in particular, authorizes Pell grants for poor students and myriad other grant and loan programs (as well as work-study); other titles provide aid to colleges and universities, especially those serving mostly minority and/or disadvantaged students. As Congress prepares to reauthorize HEA, many issues regarding how the federal government can best improve access of all students to higher education, while improving student outcomes like credential attainment and subsequent earnings, are being debated.

In this brief, I consider one such issue: how to strengthen workforce and occupational programs in U.S. higher education, and thereby improve the future employment outcomes of low-income students. I define these programs broadly to include certificate programs at community and for-profit colleges as well as occupational degree programs there (in health care, business, and other fields) at the associate degree level. Since only students in for-credit programs at accredited institutions currently qualify for financial aid under Title IV, these certificate and degree programs are what I primarily focus on.

The Barriers to Greater Attainment of High-Value, Sub-BA Credentials

Students pursuing workforce occupational credentials – including both young and nontraditional older students – often do so at the sub-BA levels, at community and for-profit colleges. In doing so, they face many challenges.

For one thing, credential completion rates in institutions are very low, averaging 30-40 percent.[1] Furthermore, while some of these sub-BA degrees and certificates generate strong earnings in the labor market (Jepsen et al., 2014; Backes et al., 2015; Stevens et al., 2018), many students emerge with terminal credentials (such as associate degrees in “liberal studies” or “general studies”) that have little labor market value, relative to a high school degree.² And, though debt levels among these students are lower than for those in BA and graduate programs, their default rates are relatively high, especially among those not completing a credential (Holzer and Baum, op. cit).

Academic research (e.g., Bound et al., 2010) suggests that a number of problems, reflecting characteristics both of students and the institutions they attend, now limit their ability to complete programs and obtain high-value credentials. Regarding students, many come from disadvantaged families where they are the first generation to attend college. Their basic academic skills are often weak (requiring remediation). Too many must work full-time to support families while attending college, and often struggle with child care and other needs. Many also lack basic information about which colleges to attend and how to succeed once they get there, making poor choices about what to study and sometimes wandering aimlessly in the process (Scott-Clayton, 2011).

To take one example, as many as 85 percent of traditional (younger) students enter community college believing they will transfer and ultimately obtain a BA, so they take mostly liberal arts classes somewhat aimlessly; in fact, only about 14 percent successfully transfer and obtain a BA (Holzer and Baum, 2017). With better guidance and more information about their own prospects as well as the market value of different credentials, one can imagine that many would choose fields of study more realistically, generating higher completion rates and more labor market value than now.

Regarding institutions, community colleges receive too few resources from states, relative to four-year colleges and universities (The Century Foundation, op. cit.).[3] But they also face too few incentives to respond to labor market signals. Their state subsidies depend primarily on enrollment, not completion of credentials or labor market value; and most faculty want to teach liberal arts, despite the fact that these degrees have low market value. And instruction in some of the “in-demand” technical fields is quite expensive, both due to instructor and equipment costs. Accordingly, there are few incentives for community colleges to spend their very limited resources in ways that expand teaching capacity in health care and other in-demand fields.

In contrast, the various for-profit schools are less bureaucratic and more responsive to shifts in labor market demands for skills. But they charge vastly higher tuition than their public counterparts, creating high levels of debt and default rates among students, while generating credentials that are sometimes not valued as seriously by the labor market as those from traditional institutions (Deming et al., 2014; Cellini et al., 2017). They also consume disproportionately high levels of Title IV funding for low-income students.

There are other approaches to workforce development at community colleges that appear successful in rigorous evaluations. For instance, sector-based partnerships between employers and community colleges in high-demand fields (like health care, information technology, advanced manufacturing and transportation/logistics) often lead to degrees and certificates that have strong market value, creating large positive impacts on the subsequent earnings of disadvantaged students (Maguire et al., 2010; Elliott and Roder, 2019).[4] In response to this evidence, the partnerships that create such programs have proliferated, but they often remain at too small a scale to meaningfully improve opportunities for disadvantaged students and workers.

Apprenticeships create another pathway to credential attainment with market value. Apprenticeships generate strong earnings for workers who complete them, while allowing employers to train workers for the skills they need. They also solve at least some of the problems noted above, like the high costs of equipment for community colleges, since much instruction and use of equipment is on the job.

Apprenticeships generate strong earnings for workers who complete them, while allowing employers to train workers for the skills they need.

But employer willingness to provide apprenticeships, and to partner more generally with education providers, remains quite low and successful efforts lack scale. The reasons are likely many – lack of information on how to set them up, high start-up costs, exaggerated fears of costs and “red tape,” and fears of “poaching” by other employers (Lerman, 2018).

As much as possible, HEA reauthorization should address these many barriers to higher rates of credential attainment in high-demand occupations and sectors. To achieve the general goals of more credential attainment in high-demand fields, I argue that we should strive to strengthen guidance (and other supports) for community college students, provide more resources for the colleges but also stronger incentives to respond to the labor market, and fund more partnerships and training opportunities with employers.

What Has Been Proposed to Date: PROSPER and AIM HIGHER

In 2017 and 2018, both Republicans and Democrats in the House of Representatives separately drafted proposed reforms to HEA, entitled PROSPER and AIM HIGHER respectively. Both proposals purport to strengthen occupational and workforce programs in public and for-profit institutions.

PROSPER aims to improve credential completion overall by streamlining financial aid and regulation of higher education programs, and by encouraging innovation in such programs.[5] Regarding workforce programs, it would lower the required credit hours and weeks needed for certificate programs to be eligible for Title IV funding from 600 hours and 15 weeks currently to 300 and 10 respectively. This would open federal financial aid to students in many shorter-term certificate programs, as long as evidence of labor market value is provided.

PROSPER would also dramatically limit current regulations on for-profit institutions. For instance, it would eliminate the “90/10” rule that currently requires these institutions to generate at least 10 percent of their funding outside of federal financial aid; and it would also drop the “Gainful Employment” regulations protecting student outcomes in occupational and for-profit programs, replacing them only with the provision of more data on such outcomes.[6] It would also make it much easier for a range of new institutions to become accredited, by granting waivers to accreditors and shortening the time periods under which institutions can undergo federal review.

PROSPER also would completely replace Title II grants (to enhance teacher quality) with a program to fund apprenticeships. This program would skirt the current regulations associated with registered apprenticeship and gives industry-wide latitude for designing and implementing them with federal funding.

Some aspects of PROSPER are appealing. It would expand the numbers of certificate programs in which disadvantaged students could receive financial aid. It would undoubtedly generate many newly accredited occupational training institutions and programs, some of which would be of high quality.

But the track record of the for-profit sector to date does not merit a dramatic reduction in regulation, to put it mildly. Making it easier for many new private programs to gain accreditation could generate many more such for-profit ventures, with fairly negative outcomes similar to those we now observe.

Perhaps the apprenticeship proposal will appeal to employers, and make them more interested in setting up such programs. At the same time, the proposal opens the floodgates for programs that might differ substantially from the registered model that now appears so cost-effective (Reed et al., 2012).

In contrast, AIM HIGHER seeks to expand targeted funding for many disadvantaged students and institutions, strengthen accountability standards for occupational programs and proprietary schools more generally, and encourage more states to offer free community college. It would expand funding for childcare and other necessary supports on campuses, and would generate a new competitive grant program (called “Student Success”) to help strengthen support services (including guidance) at under-resourced institutions.

Regarding occupational programs, AIM HIGHER would limit the current hour and week regulations for certificate programs to achieve Title IV eligibility by more than PROSPER (to 150 hours and 8 weeks respectively), while providing more oversight of program outcomes. It would strengthen regulation of for-profit institutions and accountability of occupational programs more broadly in a variety of ways, such as changing the “90/10” rule to “85/15.”[7] It would also allow and encourage more work-based learning in its Career and Technical Education (CTE) programs and Federal Work Study (FWS).

AIM HIGHER would undoubtedly expand access to college for disadvantaged students and generate more resources for some institutions. But I fear its provisions are too limited to have great impact on occupational programs. Specifically, I worry that:

• Making apprenticeships or other work-based learning “allowable” in CTE or FWS will increase their numbers by fairly little, since they are costly to set up; institutions will still be incentivized to do what’s easier, such as more traditional campus-based jobs.
• The competitive grants in “Student Success” and other HEA programs will generate needed supports for some institutions, but they will reach only small numbers of students and will not provide sustainable funding over time.
• Reforming accreditation or changing the “90/10” rule to “85/15” only affects the lower bound of desired performance, and does not incentivize the stronger changes we need.

At the same time, both PROSPER and AIM HIGHER currently have relatively little to say about two of the most influential and potentially powerful reforms that many states and community colleges are embracing to improve their outcomes: outcome-based funding (where states use outcomes of institutions to determine their funding levels) and guided pathways.

Over 30 states now use some version of outcome-based funding for public higher education (National Conference of State Legislators, 2019). I believe the most promising models are those that reward schools for employment outcomes as well as credential completion, that statistically adjust for the limited preparedness of many entering students (to deter “creaming” in admissions which would hurt the disadvantaged), and especially those that explicitly reward institutions for enrolling more minority or disadvantaged students and improving their outcomes (which are called “equity measures” by Cielinski and Pham, 2017). Since most states are using some version of OBF, it is important for reauthorized HEA to influence these efforts in a positive way. We also need more evidence of exactly what works and for whom in these efforts (Deming and Figlio, 2016; Dougherty, 2017).

Regarding guided pathways, there has been much institutional interest since Bailey et al. (2015) was published. But, once again, current evidence is too limited on what works, and many institutions need more resources to implement these changes effectively.

Interestingly, much of the career guidance that students need is already provided at about 2500 American Job Centers (formerly known as One-Stops). Leveraging the widespread availability of these services at such centers might prevent the need for community colleges to reinvent this wheel on their own.

My Proposals

I propose a set of amendments to HEA that would:

• Make academic and career guidance to community college students much more widely available than they are now;
• Provide more targeted resources for “in-demand” occupational programs plus support services at community colleges, but also generate stronger incentives for colleges to expand occupational programs, especially in ways that benefit minority and disadvantaged students; and
• Expand employer creation of apprenticeship and other forms of engagement with or support for community or four-year colleges.

1) To make academic and career guidance more available, I would:

• Create a competitive grant program for community colleges to build and evaluate “guided pathways” to improve both credential completion and transfer rates to four-year institutions; and
• Create a formula fund to pay for more academic/career counseling and “navigators,” at an average of $100,000 per college, either on campus or at local American Job Centers, for each community college where minority or low-income students constitute a majority of those enrolled.[8]

The competitive program to expand and evaluate “guided pathways” would help community colleges implement this important new reform proposal, while we learn the extent to which it is cost-effective. The formula grant would ensure that community colleges serving large numbers of minority or disadvantaged students have the resources to provide them with academic and career guidance, which should improve their outcomes as well.

2) To provide targeted resources to in-demand occupational (including both degree and certificate) programs and related supports, while also strengthening incentives for community colleges to expand these:

• Create a major competitive matching grants to states for expanding teaching capacity in high-demand fields plus support services, conditional on their use of some outcome-based funding for community colleges (and maybe 4-year colleges), in ways that emphasize employment outcomes, especially among minority and disadvantaged students without generating “creaming”;[9] and
• Provide resources to evaluate outcome-based funding formulas that states are already using.

These funds would help steer the outcomes-based reforms that so many states are implementing towards those that best serve minority and disadvantaged students. At the same time, they would also spur evaluations to inform us about the extent to which these reforms work without generating adverse consequences.

3) To expand employer creation of apprenticeships and other modes of sector-based partnership with community colleges:

• Create a formula fund for states to provide resources and technical assistance to both employers and community colleges, and sector-based partnerships between them, which could be integrated into state workforce plans to encourage more sector-based training and apprenticeships;[10] and
• Reward institutions with additional funding if at least some minimal percentage of their resources are provided by tuition payments from employers.[11]

The new formula fund would provide more resources to states as they seek to scale up sector-based training and apprenticeships with local employers. And the rewards for institutions that successfully engage employers will hopefully encourage more such cooperation between community colleges and local industry.

Conclusion

As Congress wrestles with how to reauthorize HEA, both Republicans and Democrats have expressed a desire to strengthen workforce programs in higher education, especially at community and for-profit colleges and universities.

But neither of their proposals does enough to expand support and accountability in ways that would matter the most: by providing more guidance to students, by raising both institutional funding and incentives to improve employment, and by directly funding more registered apprenticeships and sector-based training partnerships between employers and community colleges.

Above I lay out a set of proposals to do that. I hope these provide some basis for an ongoing conversation about how best to use HEA reauthorization to improve the skills and earnings of disadvantaged American students.

REFERENCES

Backes, Benjamin; Harry Holzer and Erin Velez. 2015. “Is it Worth It? Postsecondary Education and Labor Market Outcomes for the Disadvantaged.” IZA Journal of Labor Policy, 4(1).

Bailey, Thomas; Shanna Jaggers and Davis Jenkins. 2015. Redesigning America’s Community Colleges. Cambridge: Harvard University Press.

Bound, John et al. 2010. “Why Have College Completion Rates Declined? An Analysis of Changing Student Preparation and Collegiate Resources.” American Economic Journal: Applied Microeconomics. 2(3).

Cellini, Stephanie et al. 2017. Gainful Employment Regulations Will Protect Students and Taxpayers. Don’t Change Them. Brookings Brief, Economic Studies, Washington DC.

Century Foundation. 2019. Restoring the American Dream: Providing Community Colleges with the Resources They Need. Report of the Working Group on Community College Financial Resources. New York: The Century Foundation Press.

Cielinski, Anna and Duy Pham. 2017. EQUITY MEASURES IN STATE OUTCOMES-BASED FUNDING: Incentives for public colleges to support low-income and Underperforming Students. Center for Law and Social Policy, Washington DC.

Deming, David and David Figlio. 2016. “Accountability in US Education: Applying Lessons of K-12 to Higher Education.” Journal of Economic Perspectives. 30(3).

Deming, David and Christopher Walters. 2017. “The Impact of Price Caps and Spending Cuts on US Postsecondary Attainment.” National Bureau of Economic Research Working Paper.

Deming, David et al. 2017. “The Value of Post-secondary Credentials in the Labor Market: An Experimental Study.” American Economic Review 106(3).

Dougherty, Kevin et al. 2016. Performance Funding for Higher Education. Baltimore: Johns Hopkins University Press.

Elliott, Mark and Anne Roder. 2019. Nine-Year Gains: Project Quest’s Continuing Impacts. New York: Economic Mobility Corporation.

Holzer, Harry and Sandy Baum. 2017. Making College Work: Pathways to Success for Disadvantaged Students. Brookings.

Jepsen, Christopher et al. 2014. “The Community College Returns to Degrees, Diplomas and Certificates.” Journal of Labor Economics. 32(1).

Lerman, Robert. 2018. ”Restoring Opportunity by Expanding Apprenticeship.” Urban Institute, Washington DC.

Maguire, Sheila et al. 2010.  Tuning Into Local Labor Markets. Public-Private Ventures, Philadelphia PA.

National Conference of State Legislatures. 2019. “Performance Based Funding for Higher Education.” http://www.ncsl.org/research/fiscal-policy/performance-based-funding-for-higher-education.aspx

Shireman, Robert. 2019. Testimony to the (Maryland) House Appropriations Committee on HB464: Private Career Schools and For-Profit Institutions of Higher Education – Disclosures and Regulation, February 12.

Stevens, Ann Huff; Michal Kurlaender and Michel Grosz. 2019. “Career and Technical Education and Labor Market Outcomes: Evidence from California Community Colleges.” Journal of Human Resources, 54(2).

       

When congressional Republicans and the Trump administration pushed for their tax cuts in 2017, they promised American workers that slashing the corporate tax rate would raise their wages.

They offered two rationales for this promise: that companies would share some of their gains with workers right away by raising their pay, and that they would also invest more in equipment, thereby raising productivity and worker wages over time. Indeed, higher wages were supposed to be the main benefit to the broad public of a tax cut package that otherwise was heavily tilted toward the rich and inflated the national debt.

But, to date, those predictions have mostly failed to come true. Corporate stock buybacks have swamped other uses of the tax savings. Wage growth has edged up very modestly since the tax cuts passed, more likely due to tight labor markets than the tax cut. When helping workers, many companies have chosen one-time bonuses instead of permanent increases in base pay. Furthermore, the growth in investment has also been modest, and more likely driven by high oil prices than lower taxes.

But a different version of the same corporate tax cut could indeed raise worker wages. Suppose Congress, which cut the corporate tax rate from 35 percent to 21 percent in 2017, clawed back several percentage points — and then doled them back out to companies that actually paid their workers more. In this case, the overall size of the corporate tax cut could remain the same, but it would encourage companies to raise wages.

How would such a tax law work? In one approach, firms could earn reductions in their tax rate for annual wage increases above a certain base rate of wage growth, with tax cuts growing larger as wage growth rises. And firms that already pay their workers above their industry average might also get a tax cut, with larger cuts for companies paying more above the average. We could also provide additional tax cuts for profit-sharing, generous benefits or even apprenticeships through which companies invest in their workers’ productivity and pay.

Would such a proposal constitute undue government meddling in private-sector labor markets? Not at all. The wages of America’s workers — especially those without college degrees — have stagnated for decades now, with too little of private-sector productivity growth being shared with them. In fact, the stagnation in the living standards of ordinary American workers, along with massively growing inequality in wages and incomes, ultimately threatens the legitimacy of our private market system and the stability of our politics.

And there is another strong economic rationale for rewarding good-paying firms. Companies in any given industry don’t all pay their workers a single market wage — they often choose to pay well above or below that average, even in competitive markets. Companies choosing the “low road” in wages compete on the basis of low labor costs, while those choosing the “high road” compete on the basis of higher worker performance and productivity, as well as lower turnover costs.

If some companies can be equally profitable by paying workers less or more, while also making the overall economy less or more productive, then the high-wage approach is what economists call a “public good” — and private markets provide too little of it on their own. So the government should encourage higher-wage employers through subsidies (including tax cuts) and other regulations, including higher minimum wages and legal protections for unions.

In recent years, fewer and fewer companies appear to be taking the high road — though there are some exceptions. For instance, Walmart and Amazon have recently chosen to raise their employees’ pay and invest more in training them. They are experimenting with whether a higher-road approach to employment actually improves their bottom lines. (Amazon chief executive Jeff Bezos owns The Post.)

Of course, some companies might respond to tax cuts for higher pay by gaming the system. They might lay off some of their lower-wage workers, or turn them into independent contractors, to raise the average pay of those still on their payrolls. They could also raise average pay but meanwhile cut benefits such as health insurance. But Congress could stipulate that companies engaging in such tactics would forfeit their rights to the larger tax cut.

Right now, we’re not sure how much companies would respond to these kinds of tax incentives by raising worker wages. But, given the costs that wage stagnation now imposes on American workers, and our overall economy and politics, it’s worth a shot. And we would finally make true the original promise of higher wages on which the Republican tax cuts were based, while imposing no great burden on corporate America.

       

Are U.S. workers now threatened by a new and powerful form of automation that could displace tens of millions from their current jobs and dislodge them from the middle class? If so, are college-educated or professional workers at the upper range of the middle class as much threatened as those with fewer such credentials at the lower end? And can policy do much to protect the middle class status of either group?

Old fears, new trends

The fear that automation will eliminate millions of jobs, leaving masses of workers jobless, has periodically emerged in industrialized countries at least since the Luddites first made that claim in Britain in the mid-19^th century. In the US, such fears occasionally surface as well, as they did during a brief “automation scare” in the late 1950’s and early 1960’s, when a wide swath of workers felt some risk of displacement. To date, these fears have never proven accurate in any industrial country. New jobs always emerge to replace those that have been lost. This is true because automation raises worker productivity and reduces the costs and prices of goods and services, which makes consumers richer. They can now afford to buy more products than before, which then creates new jobs for workers to fill.

But there are costs – even for the middle class

The adjustment process I describe above does not mean that no one suffers from automation. Some workers are directly displaced from their existing jobs; perhaps they can retrain for another job in the same firm or industry, and perhaps not. Most in the latter situation become unemployed, and suffer lengthy spells without work – sometimes for years – before accepting new jobs at lower wages or leaving the work force altogether. Displaced workers who are older or less educated are more likely to leave the labor force rather than retrain for another job.  For these workers, the thought of returning to a 2- or 4-year college to learn a new skill, or to start a low-wage entry level job as a trainee, is extremely unappealing – and may not be worth it if they only have a decade or two left to work. Those who were unsuccessful at school earlier in their lives, and emerged with at most a high school diploma, are especially poor candidates for more education later.  And facing the prospect of nothing but low-wage work for the rest of their lives can discourage them from ever taking another job. And automation can hurt workers beyond those directly displaced.  Since 1980, and perhaps well before, economists believe new technologies have been “skill-biased” – meaning that they substitute for less-educated workers broadly in the labor market, reducing the demand they face for their labor and thus reducing their wages and employment rates. In contrast, those with at least some postsecondary education, especially with bachelor (BA) degrees or higher, tend to complement the new technologies in a variety of ways – as engineers or technicians, or those who market and sell the new products, or those providing the health care that we demand with our higher incomes, or whose creativity in music or writing can now be enjoyed by vastly greater audiences.  The employment rates and earnings of these complementary workers rise as a result of automation. Indeed, most labor economists believe that skill-biased technical change (SBTC) has been the largest cause of growing inequality between college-educated and other workers in the past four decades.  Other forces have mattered as well – like globalization and weakening protections from unions and minimum wage laws. But new technologies have been the largest source of the new inequality. Accordingly, SBTC has made it harder for workers without postsecondary credentials, especially those without bachelor’s (BA) degrees, to join or remain part of the middle class, while those with BAs and higher have thrived. SBTC has particularly thinned the ranks of jobs in the middle of the earnings distribution for workers with high school or less education, like production and clerical jobs, which allowed workers who held them to join the middle class in larger numbers in the decades after World War II. And in regions where large numbers of these jobs have disappeared, such as the industrial Midwest and rural areas, broader declines in their local economies have hurt workers in other industries as well.  Those who cannot or will not earn a postsecondary degree or relocate to an economically growing region – perhaps because of strong social ties or another barriers to work (like a substance addiction, a criminal record or a disability) – will remain in those areas and perhaps forego work permanently.

Is this time different? 

While new digital technologies and other forces have caused rising inequality in late 20th and early 21^st century, many Americans now fear a new and potentially more threatening form of automation, where even those with BAs or professional degrees could become displaced and dislodged from the middle class.  Thus, it is possible that the employment consequences of this new automation will be more negative for the middle class than they were during any episode in the past. The greater potential for future employment loss exists because of the much greater potential reach of artificial intelligence (AI) into what have until now been exclusively human functions.  AI’s ability to read patterns in the physical environment and in human interactions, as well as its ability to learn over time and adjust itself accordingly, will likely enable robots and other forms of automation to perform tasks that historically have been undertaken by humans. Some such tasks, like driving a motor vehicle in traffic or responding to customer questions and complaints in retail and service establishments, are now becoming automated and will soon eliminate several million jobs that have paid middle-class wages to workers that fill them. And, as the dexterity of robots grows, they will not only be able to perform a range of physical tasks in jobs from manufacturing to handling inventories and delivering products; they will increasingly be able to perform a range of analytical tasks in health care, legal services, accounting and finance that have required professional degrees will increasingly be within their reach. Therefore, both the lower and upper middle classes will be at risk of robot replacement, and could face lower earnings opportunities as a result. On the more positive side, the higher productivity associated with such automation will reduce production costs and prices of a wide range of goods and services, effectively raising overall incomes and consumer spending, which will then generate millions of new jobs in existing and new industries. In addition, people in the jobs being at least partially automated will increasingly be able to focus on other tasks that robots and automation still cannot perform. Various forms of social interaction, more complex modes of analyzing data and making judgments, or more creative tasks will remain primarily within the human realm for the near future. This means that, within most jobs, some tasks will be automatable and some will not. The higher the percentage of tasks in any job that can be automated, the greater the likelihood of worker displacement; and the greater the ability of the worker to learn new tasks on the job, the greater their likelihood of being retained by their employer and retooled for new tasks.

Jobs impact: what do we know?

Given these facts, can we estimate what fractions of U.S. workers face potential displacement, and in which jobs and industries? And does this information give us a greater sense of how to help more workers enter or remain in the middle class? Over the past few years, estimates of potential displacement have been generated by analysts with two kinds of information: 1) the task content of occupations today in the U.S. and other industrial countries; and 2) estimates by computer scientists of which tasks will become readily automatable over the next few decades. Of course, considerable uncertainty remains about the latter. And just because tasks become automatable doesn’t mean that they will be automated in any particular job, since the latter also depends on a range of factors including the costs of implementing the new technology, the preferences of employers for different kinds of work arrangements, and the legal and institutional settings in which such decisions occur. The extent to which workers can voice their own ideas and preferences within workplaces will also influence the nature and extent to which tasks become automated. Still, the estimates of task automation and therefore potential job displacement rates are instructive, and merit some attention here. I therefore present a few such estimates from a very recent study by economists at the Organization for Economic Cooperation and Development (OECD). OECD estimates worker displacement rates in the U.S. and other OECD countries in the next few decades, distinguishing those who will almost certainly be displaced, with task replacement rates of 70 percent or higher, from those facing high potential task replacement – in the 50-70 percent range – but who still have potential for task readjustment and retraining within their current jobs. The results show that, in the U.S. and elsewhere, about 10 percent of workers will face high risks of complete displacement, while another 30 percent or so will face significant potential task replacement risk. Some specific occupations have higher or lower potential task replacement rates, as the next chart shows: Occupations where a great deal of routine tasks are performed, such as machine or vehicle operators and unskilled laborers, face the highest potential displacement risks; while those requiring more nuanced social interactions and analysis, like doctors, lawyers and managers more generally, face moderate risks (in the range of 20-30 percent) but will likely not be completely displaced. Viewing these estimates, it is immediately apparent that automation will continue to have a “skill bias” – in other words, less educated workers will remain at higher risk of direct displacement than most with postsecondary education, and will likely face lower demand in the labor market – resulting in lower wages and employment for them. Accordingly, not only will substantial fractions of workers face direct displacement – some of whom can be retrained for new jobs and some not – but overall labor market inequality between those with and without college education will continue to rise. Though rising productivity should help raise compensation levels overall, the skill bias of automation will likely leave many workers worse off, even if they take new jobs. In addition, those with more education will more easily retrain for new tasks at work or completely new jobs than those without it, and the better-educated will also be more open to relocating to regions with stronger economic growth. Accordingly, the more highly educated members of the middle class will continue to have higher odds of remaining there, while the less educated in the middle class may find their positions there increasingly precarious. And, if this occurs, the fallout might well be political as well as economic. The populism and nationalism that we find in industrialized democracies around the world might well grow stronger, and render politics in many countries more chaotic and polarized. This, in turn, would likely impede governments there from enacting policies to help protect the middle class from the worst effects of automation, and assist in the adjustments to labor market disruptions that will inevitably occur.

Five policies to help the middle class

A range of sensible policies at the federal and state levels can help limit worker risks of displacement and support adjustments when such displacements occur.

• Education for 21^st century skills

For instance, students at all levels of education will need better preparation in what are often called “21^st century skills.” These include communication and a range of social and interactive skills (such as the ability to work in teams), as well as critical thinking and various kinds of problem-solving abilities. Workers with more such skills will likely be more complementary with and less substitutable by automation, while also finding it easier to retrain for a range of new tasks that will need to be performed following automation.  It thus makes sense that educators in primary, secondary and postsecondary institutions should put greater emphasis on teaching such general skills, and policies should encourage this. But the issue is complicated by the following fact: the programs that most successfully raise skills among low-income workers (when rigorously evaluated), and prepare them for possible entry into the middle class, tend to be specific to a sector with high unmet demands for workers, such as health care, advanced manufacturing, information technology, and transportation/logistics. Such programs include those based on partnerships between industry representatives and community colleges, brought together by a knowledgeable intermediary; or those more specific to employers in these industries, like apprenticeship. Of course, the narrower and more specific the training, the greater the risks of displacement for workers trained in those skills in a dynamic and uncertain future labor market. On the other hand, given the fact of high current demand and compensation for such skills, and possible entry into the middle class for workers who have them, it would make it foolish not to provide them to currently low-income workers. Still, having more of the 21^st century skills would likely help workers perform better in these jobs, and make them more trainable in the future. Thus, wherever they can be provided, a good mix of general and specific skills should be imparted to those being trained for specific occupations and industries. This should be true in high-quality career and technical education (CTE) beginning in secondary school as well as in higher education.

• Lifelong learning accounts / Retraining support

Besides earlier educational preparation, what more can be done to help workers adapt when automation threatens them with job displacement? Financial support for retraining could be important here, and two forms of such funding could particularly help. First, states can create personal “lifelong learning” accounts into which workers pay a small percent of payroll each period, thus creating a fund for new education or training if/when displacement occurs. Indeed, the states of Maine and Washington already do so, and more might soon join them. Second, federal or state governments can provide financial and technical assistance to firms for on-the-job training, thereby encouraging employers to retrain rather than displace their employees. This will have some appeal to employers, since it will enable them to retain employees with good track records, and avoid recruitment and screening costs for new employees of uncertain ability. And the new expenditures could perhaps be financed by a new tax on worker displacement, since these impose a cost on society which employers should be required to partly carry.

• Workforce support

A wider range of additional policy initiatives could help as well. First, a more robust set of workforce services would help workers reeducate and relocate themselves. Information on career and training options as well as new jobs are available to workers at over 3000 of “America’s Job Centers” (formerly called One-Stop offices) around the country, though their funding and therefore their staffing quality has been quite limited. Improving the academic and career guidance available at community colleges would be very important as well.

• Wage insurance

Many workers who will be displaced over time but not retrained will likely face a future of lower wages than before or no work at all.  For them, some form of “wage insurance” makes sense.  Such a program would compensate displaced workers for some part of their job loss – say, half – for a period of years. Thus, workers who formerly earned $30 an hour but only $20 now would receive $5 from the government for a period of time, such as five years. They would therefore be incentivized to work and would also receive needed financial assistance at the same time.

• Unemployment and Disability Insurance reform

Finally, a set of reforms in our Unemployment and Disability Insurance systems might be warranted too. Reforms in the former might encourage them to obtain new training while they receive their stipends, while those in the latter would encourage workers and employers to engage in work rather than permanent lack of work for those with only moderate conditions. I believe this set of proposals makes vastly more sense than others, like guaranteed public employment or universal basic income payments, which would be hugely more expensive to implement and would not incentivize everyone to do whatever is necessary to stay employed.

• Employers: Take the high road

Though most of our policies above are aimed at helping workers adjust to automation, we should also have an overall policy goal for the employer side of the job market: encouraging them to take the “high road” in worker compensation and to actively invest in their employees as workplaces automate, to increase their productivity and performance. Economists have long argued that, in many industries, employers have some choice over whether to compete on the basis of high worker productivity and performance or merely low labor costs. Employers choose between these strategies, often called “high road” and “low road” approaches, early in the lives of their establishments, though they can also shift their strategies over time. Since “high road” employers invest more in their workers’ skills, and often allow them more “voice” in the operation of the workplace, they will be more open to implementing new automation in ways that are “worker-friendly” and to retraining them over time. Such approaches should be encouraged by policy at all levels. Overall, the policies I propose will not completely protect the middle class from the disruptions and displacements they will likely face in the coming decades. But they will certainly help millions of workers join this class or remain there in the face of displacement risks, and will raise the net positive effects on workers that always result from automation.