Thank you for holding this important hearing today. The first step to ensure a healthy national infrastructure is keeping things from deteriorating. Allowing the Highway Trust Fund to become progressively underfunded in the coming decade would do great damage. The federal gas tax, which funds the HTF, is not indexed to inflation and hasn’t been increased since 1993; this means that the purchasing power of the HTF’s dedicated revenue source has been slowly declining. Since then, Congress has used general revenues to cover the gap between HTF project funding and the decaying value of its revenue source. The cumulative shortfall facing the HTF will reach $138 billion by fiscal year 2027.1 To ensure that HTF has resources to fund planned expenditures, the current gas tax should be raised or a new dedicated revenue source for the HTF should be found.

But we should be clear that keeping the status quo by finding a funding source for the HTF is far from adequate infrastructure policy. There is broad agreement that the current state of U.S. infrastructure is deeply deficient due to past neglect and underinvestment. For this reason, the U.S. economy would benefit greatly from a substantial increase in infrastructure investment. The American Society of Civil Engineers (ASCE) most recently put the 10-year infrastructure funding gap—the additional investment needed to maintain a state of good repair—at about $2.1 trillion.2 This estimate is for maintenance only; it doesn’t even include the imperative to modernize and upgrade our transportation, energy, and water systems.

Our research at EPI indicates strongly that reversing this chronic underinvestment in infrastructure will require a strong federal role and a commitment of federal resources. Currently, we rely heavily on state and local governments to finance a large share of infrastructure—particularly highways and transit. This heavy reliance on state and local governments is the strategy that has led us to the current situation, which virtually everybody agrees is suboptimal. Doing better going forward will require a stronger federal role and a significant commitment of federal resources.

Below I highlight some of the findings from our past research. Specifically, this research finds:

• Infrastructure done right would boost job creation as well as the long-run productivity of the American economy.
• The first step to doing infrastructure right is fixing the Highway Trust Fund (HTF). The most important issue is simply ensuring that the trust fund has the resources to fund its planned expenditures. The past practice of using gasoline taxes for the HTF is a perfectly sound strategy. Strategies that call for other funding sources that approximate user fees (like vehicle miles traveled [VMT] taxes) are also reasonable. But the most important goal is simply to provide the resources needed to keep highway and transit investments from being strangled.
• Doing infrastructure right will require a strong federal role and federal commitment of resources for the following reasons:
  • There is no free lunch, or road, or bridge. American households will, in the end, pay for improved infrastructure—either through higher taxes or through user fees and tolls. Too often, advocates of “leveraging the private sector” (via public-private partnerships, or P3s) obscure or underplay this basic economic truth.
  • The federal government provides some key advantages to financing over private actors and even over state and local governments. The clearest advantage is that the interest rate paid on federal debt is lower than what is available to private actors or states. This means long-term debt financing is cheaper for the federal government.
  • Despite this potential federal government advantage, our current mix of infrastructure funding and financing leans much more heavily on state and local governments.
  • There is no economic basis to the glib arguments that state and local provision of infrastructure is more efficient simply because these levels of government are “closer” to end users. Economic efficiency depends on the funding mechanism, not the level of government.
  • Because state and local governments are not incentivized to take account of externalities or regional spillovers, they may underinvest in key infrastructure projects.
  • Federally funded infrastructure investment is more likely to incorporate requirements for strong labor standards—ensuring that it supports good jobs with good wages. Plans that lean more heavily on private financing should not be used as an excuse to ignore labor standards, because if they did then these plans would likely see fewer good jobs created through infrastructure investments. Infrastructure projects that pay good wages have durable benefits for communities and local tax bases, unlike those that seek to undermine decent wages and standards.

Background: The large macroeconomic benefits of infrastructure done right

The United States economy has suffered from two glaring macroeconomic problems over the past decade. The first is a severe and chronic shortfall of spending by households, businesses, and governments relative to the economy’s productive potential (i.e., a shortfall of aggregate demand). This demand shortfall has slowed growth in both jobs and wages for most of the past 10 years. The second problem is a rapid deceleration in the pace of productivity growth. Productivity is the amount of income (or output) generated in an average hour of work. Productivity growth in turn provides the potential ceiling for how fast average income can rise without spurring inflation.

These are both serious problems, and policymakers should be concerned with each. A large, sustained increase in infrastructure investment would be an effective way to address both. Previous EPI research (Bivens 2017) found:3

• Infrastructure investment could be an extraordinarily useful tool for macroeconomic stabilization. Most estimates of the output “multiplier” for infrastructure investment are substantially higher than for other fiscal interventions. If the fiscal boost of infrastructure investment were accommodated by monetary policymakers, each $100 billion in infrastructure spending would boost job growth by roughly 1 million full-time equivalents (FTEs).
• While unemployment in 2017 was roughly on par with its pre–Great Recession level, this does not mean policymakers should stop worrying about macroeconomic stabilization and maintenance of aggregate demand. Growing fears of “secular stagnation”—a chronic shortfall of aggregate demand relative to the economy’s productive capacity—seem justified by several data points. Key among them is the unusually slow growth in nominal wages this late into an economic recovery.
• Productivity growth has decelerated sharply in recent years. Much of this deceleration is likely short-lived, and tighter labor markets should be expected to push productivity growth back toward more historically normal levels. Since infrastructure investment can lead to these tighter labor markets, it could have an immediate effect in restoring productivity growth.
• Further, and more important, a greater public infrastructure investment effort can also boost productivity in the long run by expanding the public capital stock. The rate of return to infrastructure investment is large; according to a review of dozens of studies on infrastructure, each $100 spent on infrastructure boosts private-sector output by $13 (median) and $17 (average) in the long run.

Other research (Bivens and Blair 2016) has pointed out that the potential job-creation benefits of infrastructure investment are more widespread and broader in impact than commonly thought.4 Bivens and Blair show that roughly two-thirds of the total jobs supported by a given investment in infrastructure are outside construction.5 Some of these jobs are supported in supplier industries (steel and concrete, for example), while others are “induced” jobs—jobs supported when workers employed directly and in supplier industries spend their paychecks in other sectors.

These large potential benefits from infrastructure investment are why we at EPI have called for years for this investment to be a federal priority.

Lessons for how to make infrastructure investment effective

While a sustained increase in infrastructure investment could bring potentially large benefits to America’s working families, too many current plans being debated would squander this potential. The evidence indicates clearly that strong federal leadership and a strong federal commitment of resources are needed to make the nation’s infrastructure healthy. It also matters how infrastructure investment is implemented. Below we review the arguments and evidence that lead us to this conclusion.

Funding versus financing

Infrastructure spending involves two distinct aspects: funding and financing. Funding refers to how infrastructure is paid for, which in practice will be through some combination of user fees and taxes. A defining characteristic of infrastructure investment is large upfront fixed costs, so that the bulk of money is needed at the outset, while funding sources may materialize slowly and over time. Financing bridges this gap between upfront spending needs and the ongoing stream of funding—structuring user fees and taxes in a way that allows upfront costs to be paid over time. Proposals that rely on shifts in financing will not address the challenge of finding a solution to long-term funding.6

World class infrastructure will require a strong federal role

If U.S. infrastructure is to be world class, a strong federal role will be necessary. Currently, state and local governments take on the bulk of infrastructure spending. According to the Congressional Budget Office (CBO), state and local governments accounted for 77 percent of total public spending on transportation and water infrastructure in 2014. They take on their largest role in operations and maintenance, where they account for 88 percent of such spending. However, they are also the majority partner in capital investment, accounting for 62 percent.7

The current system is one in which the responsibility for funding infrastructure has been largely left to the state and local governments. This is the system that has led us to where we are today, which most agree is inadequate. Any plan that doubles down on this approach and puts still more of the onus on state and local governments for finding infrastructure funding will not address our long-term infrastructure needs. Devolving this financial responsibility to the states does nothing to ensure that adequate funds will be available. State and local governments continue to face their own financial challenges. Some of this is purely political, with state governments refusing to adequately fund infrastructure (as well as other pressing public priorities) simply for ideological reasons. But states also face genuine economic and legal constraints that can make it harder for them to borrow money at the scale needed to finance a world-class infrastructure. The federal government’s financing constraints are far less binding.

Economic efficiency depends most strongly on the funding mechanism, not on the level of government

Strict economic efficiency argues that infrastructure investment should be funded by those who use it. This insight has occasionally been used to argue that the federal government should only fund projects that benefit the nation as a whole, while projects that wholly benefit a particular state or locality should be left to their respective governments.8 Often, this is the line of thinking used to argue for assigning further infrastructure funding responsibilities to state and local governments.

But this reasoning for assigning federal, state, and local government roles is a bad approximation of efficiency. It ignores funding mechanisms, which play the much more important role in ensuring economic efficiency.

The gas tax provides a clear example for the role funding mechanisms can play in ensuring economic efficiency. Historically, the gas tax has been used to fund surface transportation infrastructure because of its ability to approximate road usage. However, as the number of hybrid and electric vehicles increases, the gas tax’s usefulness as an approximation of road usage declines. If a road is funded by just a gas tax, then electric vehicle drivers can obtain all the benefits of road usage while incurring none of the costs.

User fees are a far better guarantor of economic efficiency than simply assigning certain levels of government to different infrastructure project types. For example, the benefits of a local road may largely be enjoyed by local residents, but there will be a leakage of benefits to nonlocal residents and the correspondence between geography and efficiency of infrastructure breaks down quickly.9 For example, if a local income tax was used to fund the local road this cost would only fall on local residents, but we would expect some nonlocal households to receive benefits from the road without paying for them. For example, if the road is used to transport a consumer good from a local company to a nonlocal consumer, then nonlocal consumers will have benefited from the road while not paying for its usage. Because some beneficiaries are not bearing the cost, we would expect these local roads would eventually be underprovided if their construction is reliant only on local resources. Whereas a direct user fee would ensure that beneficiaries bear the cost (through an increase in shipping costs). And no matter which level of government has assigned the user fee, it remains the more efficient option.

In short, there is no compelling efficiency-based reason to think that the current practice of having state and local governments take a dominant role in infrastructure management is optimal. Once this argument is set aside, the affirmative case for a stronger federal role becomes undeniable.

Externalities imply a strong role for federal government

The previous section discussed why efficiency does not dictate that state and local governments should bear the funding and financing burden of mostly local projects. But there is also an affirmative case for a strong federal role. This is because infrastructure is usually part of a network—e.g., our nation’s roads, bridges, airports, waterways, and broadband. These network characteristics create externalities—benefits or harms that fall on third parties to an economic transaction. In order to maximize economic efficiency, externalities must be taken into account.

Network effects, where the benefit of a good or service increases with the number of users in the network, are one example. For examples, think of the nation’s telephones, airports, and broadband. State and local governments will not internalize the benefit extra investments confer on nonlocal others in the network by providing an additional node. This failure to internalize these benefits means that if state and local governments are left alone to fund infrastructure with network effects, it will likely end up underprovided.

Spillover effects provide another externality-driven reason why a strong federal role is needed to ensure infrastructure is not underprovided. Infrastructure investments in one city may provide benefits to those connected to it in a network, or may draw in economic activity from connected cities, having negative effects on those cities. As before, state and local governments will not internalize these effects, and this in turn implies that the federal government may be in a better position to ensure efficiency. Economic evidence so far suggests that spillover effects are substantial.10 This puts the federal government in the optimal position to increase the efficiency of infrastructure investment by helping to coordinate those investments that result in positive spillovers and discouraging those projects with negative spillovers.

Mass transit provides one instance where a substantial federal investment could provide spillover effects. Public transportation serves as a lifeline for many low-income urban residents who do not have access to a car.11 There is evidence that mass transit can reduce traffic congestion, while highway capacity expansions provide only temporary relief to congestion.12 13 Public transportation also has environmental benefits, from improved air quality to reduced greenhouse gas emissions.14 This means that mass transit can mitigate environmental externalities and provide spillover effects that can sometimes cross state lines. This puts the federal government in a position to coordinate investments to ensure positive spillovers. Finally, there is strong evidence that agglomeration economies increase the productivity of cities.15 It is hard to imagine modern American cities could exist without mass transit, and every indicator argues that mass transit will have to be expanded for American cities to absorb those workers wanting to move to them. Insufficient mass transit investments will strangle the ability of high-productivity cities to grow, and mass transit investments in turn will suffer without strong federal commitments.

Finally, infrastructure networks act as intermediate goods in the production process of firms. Problems in electricity generation or transportation will not confine themselves to those sectors, but will instead have knock-on effects that reduce output throughout other sectors of the economy. Maintaining economic efficiency means ensuring consistent quality throughout the system—a chain is only as strong as its weakest link. For example, if one state doesn’t maintain its transportation infrastructure, truck drivers may have to avoid those roads or else damage their vehicles, which will have productivity repercussions in the sectors of the economy that rely on trucking. Again, ensuring consistent quality in infrastructure across regions calls for a stronger federal role.

A strong federal role provides the best potential protection for vital labor standards

For several decades now, wages for the vast majority of American workers have lagged far behind overall economic growth and productivity. What we now know from years of research at EPI is that this delinking of wage and productivity growth is not just some sad accident, but is instead the product of a decades-long policy project aimed precisely at wage suppression. This policy assault on wage growth was not one single piece of legislation. Instead it was a concerted effort to reduce workers’ economic leverage and ability to bargain for higher wages along every policy margin. Macroeconomic policy kept labor markets too slack for workers to credibly threaten to quit unless their wages were hiked; the federal minimum wage stagnated and shrank in the face of price inflation; labor law enforcement failed to keep the playing field level for workers trying to organize, while employers undertook ever more aggressive tactics to thwart them; trade policy exposed workers to fierce global competition while providing greater protections for corporate profits; and regulatory and tax policies gave corporate managers greater incentive and ability to claim a larger share of the income that their firms generated.

Since intentional wage suppression occurred along dozens of margins, a campaign to raise Americans’ pay must also be fought along every margin possible. One key margin is labor protections that have traditionally covered workers engaged in infrastructure investments. These protections help to ensure that contractors do not engage in a race to the bottom on wages and benefits. They also help ensure that contractors receiving public funds contribute resources to help train and expand the skilled construction workforce. The most well-known and important infrastructure-related labor standard is, of course, the Davis-Bacon Act’s prevailing wage provision, which protects community wage and benefit standards for all construction workers on federally funded projects.

Public infrastructure investments that contain strong labor protections can be an arrow in the quiver of attempts to reverse the era of wage stagnation for America’s workers. Infrastructure plans that are managed and financed by private actors are less likely to contain strong labor protections, and hence represent an opportunity squandered when it comes to using public investment to restore broadly shared prosperity.

Finally, a strong federal role also provides the best opportunity for making sure that best practices in inclusive hiring are followed as contractors bid on projects. In the past, communities of color were too often formally excluded from the employment generated by public investment. Recent improvements in this regard must be built upon and extended.16

Conclusion: The status quo must be fixed

We know that the current status quo, where state and local governments are required to bear the brunt of infrastructure funding, is failing to meet our long-term infrastructure needs. Fixing this state of affairs is the most obvious way to put U.S. infrastructure investment back on track. Given this, any plan that doesn’t put up significant new federal commitment of resources should be viewed as a distraction from the real issue at hand.

This includes vague promises to leverage public-private partnerships (P3s). P3s provide an alternative financing option for infrastructure, but do not provide any funding. Private partners will not build infrastructure for free. They invest only in return for a future revenue stream. This revenue must come from some combination of taxes or user fees, meaning that P3s do nothing to address the funding question. And the natural monopoly characteristics of infrastructure mean that P3s come with their own set of problems and do not avoid the need for an engaged public role.17 Because P3s are no free lunch and because state and local governments already bear a too-large burden for the nation’s infrastructure investment, new plans must include substantial new sources of federal funding.

Additional distractions from this central fact include plans that emphasize changes to the environmental review process. These plans tend to claim benefits from rolling back environmental regulations that are vastly overstated and rely on data on project completion that is significantly out of date.18 For example, between 2012 and 2016, the average time needed to complete Environmental Impact Statements (EIS) under the National Environmental Policy Act (NEPA) fell to 3.6 years. This fall in the review time was driven by reforms included in the Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (SAFETEA-LU) of 2005 as well as subsequent transportation reauthorizations.19 More importantly, only 4 percent of approved Federal Highway Administration projects required completing an EIS at all.20

The central problem facing the nation’s infrastructure is an insufficient commitment of federal resources. Nothing else besides this strong federal commitment will fix our public investment shortfall, and plans focusing on other issues are distractions. Fixing the Highway Trust Fund (HTF) is an important step that nevertheless just keeps the status quo from getting worse. We need to aim much higher than this.

1. Congressional Budget Office. 2017. “Projections of Highway Trust Fund Accounts – CBO’s June 2017 Baseline.”

2. American Society of Civil Engineers. 2017. 2017 Infrastructure Report Card: A Comprehensive Assessment of America’s Infrastructure.

3. Josh Bivens, The Potential Macroeconomic Benefits from Increasing Infrastructure Investment, Economic Policy Institute, 2017.

4. Josh Bivens and Hunter Blair, A Public Investment Agenda That Delivers the Goods for American Workers Needs to Be Long-Lived, Broad, and Subject to Democratic Oversight, Economic Policy Institute, 2016.

5. Josh Bivens and Hunter Blair, A Public Investment Agenda That Delivers the Goods for American Workers Needs to Be Long-Lived, Broad, and Subject to Democratic Oversight, Economic Policy Institute, 2016.

6. Hunter Blair, No Free Bridge: Why Public-Private Partnerships or Other ‘Innovative’ Financing of Infrastructure Will Not Save Taxpayers Money, Economic Policy Institute, 2017.

7. Congressional Budget Office, Public Spending on Transportation and Water Infrastructure, 1956 to 2014, 2015.

8. Congressional Budget Office, Public Spending on Transportation and Water Infrastructure, 1956 to 2014, 2015.

9. Hunter Blair, What Is the Ideal Mix of Federal, State, and Local Government Investment in Infrastructure?, Economic Policy Institute, 2017.

10. Hunter Blair, What Is the Ideal Mix of Federal, State, and Local Government Investment in Infrastructure?, Economic Policy Institute, 2017.

11. Alan Berube, Elizabeth Deakin, and Steven Raphael, Socioeconomic Differences in Household Automobile Ownership Rates: Implications for Evacuation Policy, The University of California Transportation Center. 2006.

12. Michael L. Anderson, “Subways, Strikes, and Slowdowns: The Impacts of Public Transit on Traffic Congestion,” American Economic Review vol. 104, no. 9 (2014), 2763–96.

13. Kevin DeGood, Debunking the False Claims of Environmental Review Opponents, Center for American Progress, 2017.

14. Federal Transit Administration, “Transit’s Role in Environmental Sustainability” (webpage), last updated May 9, 2016.

15. Daniel G. Chatman and Robert B. Noland, Transit Service, Physical Agglomeration and Productivity in US Metropolitan Areas, Urban Studies vol. 51, no. 5 (2014), 917–37.

16. Lawrence Mishel, Diversity in the New York City Union and Nonunion Construction Sectors, Economic Policy Institute, 2017.

17. Hunter Blair, No Free Bridge: Why Public-Private Partnerships or Other ‘Innovative’ Financing of Infrastructure Will Not Save Taxpayers Money, Economic Policy Institute, 2017.

18. Kevin DeGood, Debunking the False Claims of Environmental Review Opponents, Center for American Progress, 2017.

19. Federal Highway Administration, “Estimated Time Required to Complete the NEPA Process” (webpage), n.d.

20. Linda Luther, The Role of the Environmental Review Process in Federally Funded Highway Projects: Background and Issues for Congress, Congressional Research Service, 2012.

On December 14, 2017, President Trump held a press conference to take credit for the “most far-reaching regulatory reform in history,” claiming his administration has been responsible for more than 1,500 cancelled or delayed regulatory actions.1 He is expected to tout this number again at his upcoming State of the Union address to Congress. While the specific figure Trump cited at the press conference has been called into question, there is no disputing that Trump and congressional Republicans have engaged in an unprecedented attack on regulations over the last year, rolling back rules that were intended to protect workers, consumers, and public health.

The Economic Policy Institute’s Perkins Project on Worker Rights and Wages has been tracking Trump and Congress’s decimation of federal labor standards through deregulation since January 2017.2 Regulations play an essential role in protecting workers—ensuring safe workplaces and fair pay and protecting workers’ rights to organize and join a union so they can bargain collectively with their employers. But not only do regulations provide essential protections; research shows that federal regulations in fact provide an overall net benefit to the economy—contrary to what its opponents would have people believe.

In this report, we review what the research says about the benefits of regulations, and we shine a spotlight on Trump and Congress’s most egregious deregulatory actions—actions that advantage corporate interests and those at the top of the income distribution at the expense of low- and middle-income workers.

The facts about regulation

Regulations put laws into action, protecting America’s workers

Regulations are simply the rules of the game. Congress passes laws, and then federal agencies set the rules for how those laws are followed. For example, if Congress passes a law directing the Occupational Safety and Health Administration (OSHA) to ensure “safe and healthful working conditions” in America’s workplaces, OSHA responds by promulgating specific rules that employers must follow in order to establish safe and healthful workplaces for their employees.

Regulations not only provide essential protections, but their economic benefits generally outweigh their costs

Opponents of regulations routinely emphasize the costs associated with regulations while ignoring their benefits. Rhetoric attacking regulations generally alleges that regulations are overly burdensome for employers and cost jobs. However, research shows that federal regulations in fact provide an overall net benefit to the economy and that they have a modestly positive or neutral effect on employment.

Federal regulations currently provide a net benefit to society of over $100 billion per year

To assess whether a regulation should be undertaken, agencies consider a comprehensive set of benefits and costs over a broad time horizon. For example, regulations establishing workplace safety standards save lives, and environmental protection regulations conserve natural resources and improve public health, which may provide benefits for generations. Safety regulations may require substantial upfront investments in safety equipment, but those investments pay off over the long term through a reduction in illnesses like lung cancer and through lives saved over decades. In addition, the need for the safety equipment creates jobs for the people producing the equipment.

Each year the Office of Management and Budget (OMB) reports to Congress on the costs and benefits of federal regulations, with a focus on regulations for which agencies are able to estimate and monetize both costs and benefits. In its most recent report, OMB found that during the last administration, from January 21, 2009, to September 20, 2015, the estimated annual net benefit (benefits minus costs) of major federal regulations was between $103 and $393 billion.3 In other words, federal regulations are providing a net benefit to society of over $100 billion per year. And these numbers are consistent with prior OMB reports, as described below.

The ratio of benefits to costs is about 7 to 1

OMB reviewed major regulations from 2000 to 2010 and estimated that the average annual benefit of major regulations is about seven times the cost.4 OMB’s findings are even more significant when you consider studies showing that government regulators generally overestimate costs.5 Also, many benefits are never monetized, but almost all costs are.

Regulations have a modestly positive or neutral effect on employment

Research on the relationship between employment and regulations generally finds that regulations have a modestly positive or neutral effect on employment.6

How do regulations create jobs? When regulations reduce jobs in one area, they create jobs in another. For example, factories making lead paint shut down after regulations banning lead paint were issued in the late 1970s, but enterprises manufacturing lead-free alternatives arose in their place. And some of the older factories hired people to retool their machinery to begin manufacturing lead-free paint.

Mass layoffs are not caused by regulations, but lack of regulations can lead to job loss

“Mass layoff events” are incidents in which at least 50 unemployment insurance claims are filed against an employer during a five-week period. According to the latest data available (2011 and 2012), employers cite regulations as the reason for mass layoffs in just a tiny share of mass layoff events—one-quarter of one percent.7

On the other hand, the lack of sensible regulations can lead to economic catastrophe and the loss of millions of jobs. The belief that financial markets can “self-regulate” led to a wave of deregulation and lax enforcement beginning in the late 1970s and persisting right up to the financial crisis that precipitated the Great Recession of 2007–2009. Deregulation and lax enforcement played a major role in the housing bubble and the financial and economic crisis that ensued when the bubble burst.8 Nearly nine million jobs were lost in 2008 and 2009. In the wake of this crisis, officials in charge of the nation’s two main financial regulatory agencies stated that self-regulation had failed. As Christopher Cox, then-chairman of the Securities and Exchange Commission, stated, “We have learned that voluntary regulation does not work. . . . The lessons of the credit crisis all point to the need for strong and effective regulation.”9

Trump’s year of deregulation

Aside from a tax measure that overwhelmingly favored the wealthy, the first year of the Trump administration and the Republican-controlled Congress saw little in the way of substantive legislative accomplishments. However, the Trump administration and congressional Republicans have been successful in repealing many existing regulations and making it more difficult for government agencies to effectively regulate industries. One of Trump’s first actions after taking office was to issue an executive order requiring federal agencies to identify at least two existing regulations to “repeal” when proposing a new regulation.10 In December, Trump boasted that his administration had exceeded that goal, repealing 22 regulations for every new regulation proposed.11 While these claims have not been verified, the Trump administration’s Office of Information and Regulatory Affairs has reported that federal agencies have issued 67 deregulatory actions and 3 regulatory actions during fiscal year 2017;12 it has also reported that a total of 1,579 regulations were withdrawn or delayed (635 withdrawn, 244 “made inactive,” and 700 “added to the Long Term list”).13

Congressional Republicans have been instrumental in supporting this deregulatory effort. In the first 90 days of the congressional session, the House and Senate used Congressional Review Act (CRA) resolutions—which provide for a quick process to overrule recent regulations—to overturn 14 Obama-era rules.14 Prior to the 115th Congress, the CRA had only been successfully used to repeal a rule once, in 1996.15

An examination of the regulations repealed or rescinded reveals that many of the rules that were eliminated provided important protections to our nation’s workers. President Trump and congressional Republicans have blocked regulations that protect workers’ pay, safety, and rights to organize and join a union. By blocking these rules, the president and Congress are raising the risks for workers while rewarding companies that put their employees’ health, safety, and paychecks at risk.

This section lists the casualties of Trump’s war on regulations.

Deregulation casualty #1: Workers’ health and safety

Rolling back a rule that required employers to keep accurate records of workplace injuries and illnesses

Congressional Republicans approved and President Trump signed a Congressional Review Act resolution blocking the Workplace Injury and Illness recordkeeping rule, which clarifies an employer’s obligation under the Occupational Safety and Health Act to maintain accurate records of workplace injuries and illnesses.16

Recordkeeping is about more than paperwork. If an employee is injured on the job (for example, is cut or burned, or suffers an amputation), contracts a job-related illness, or is killed in an accident on the job, then it is the employer’s duty to record the incident and work with the Occupational Safety and Health Administration to investigate what happened. Failure to keep injury/illness records means that employers, OSHA, and workers cannot learn from past mistakes and makes it harder to prevent the same tragedies from happening to others. By signing the resolution to block this rule, Trump gave employers a get-out-of-jail-free card when they fail to maintain—or when they falsify—their injury/illness logs. Workers who could have been saved from preventable accidents on the job will have to pay the price with their health or even their lives.

The history of the rule is as follows: Since the early 1970s, the Occupational Safety and Health Administration has required many employers to keep careful records of workplace injuries and illnesses and to maintain those records for five years. If an employer’s injury/illness logs are inaccurate—for example, if a worker is injured on the job and the employer fails to log it—OSHA can issue a citation and fine.

For 40 years, from the early 1970s through 2012, OSHA had been able to issue those citations at any time within the five-year period that the illness/injury record was required to be kept. But in 2012, the D.C. Circuit Court of Appeals ruled that, if a worker was injured, OSHA had only six months to check an employer’s log to make sure the injury was recorded and to issue a citation if it was not.17 That meant that even though employers are supposed to maintain injury/illness records for five years, an employer is off the hook if OSHA inspectors do not catch the employer’s record omission within the first six months after the injury. Since OSHA inspections generally take longer than six months, the court’s ruling made it a lot harder for OSHA to penalize companies for bad recordkeeping. One of the judges on the court, though, wrote that OSHA could issue a new rule clarifying employers’ recordkeeping duties.

In response, OSHA promulgated a rule to allow OSHA to resume what it had already been doing for 40 years: cite employers for failure to log injuries/illnesses anytime within the entire five-year period that the records must be kept.18 This rule created no new recordkeeping requirements for employers; it just allowed OSHA more time to do its work to ensure that employers are held accountable for protecting workers’ health and safety.

Delaying a rule requiring employers submit injury and illness records electronically to OSHA

OSHA’s electronic recordkeeping rule is an important supplement to the recordkeeping rule described above. The Obama-era rule does not create any new reporting requirements for employers—it simply requires employers who are currently required to keep OSHA injury and illness records to submit their records to OSHA electronically, making them publicly available. Improving data collection and dissemination of injury and illness incidents in America’s workplaces will allow OSHA, employers, employees, employee representatives, other government agencies, and researchers to identify patterns so that workplace hazards can be addressed and worker injuries and illnesses prevented. And because this information will be easily accessible to a broad audience on OSHA’s website, employers are more likely to comply with workplace safety rules to protect their workers—knowing that they’ll have to answer to the public if they don’t.19

According to the final rule, employers covered by the rule were required to submit their 2016 records electronically by July 1, 2017. But delays by OSHA pushed back the compliance date to December 2017, nearly six months after the original date.20 Most troubling, though, was OSHA’s November 2017 announcement that it intends to “reconsider, revise, or remove portions of that rule in 2018.”21

In 2016 alone, well over 5,000 workers died on the job.22 If OSHA rescinds or weakens this rule in 2018, it will mean that patterns of unsafe working conditions may be harder to detect, making workplaces even more dangerous for workers.

Delaying a rule protecting workers from exposure to harmful silica dust

After delaying enforcement for months, the Department of Labor announced in September 2017 that it would begin enforcing a rule to protect construction workers from occupational exposure to crystalline silica; however, enforcement of provisions protecting general industry and maritime workers will not begin until June 2018.23 This Obama administration rule lowered workers’ permissible exposure limit to deadly crystalline silica dust. The rule is made up of two permissible exposure standards, one for construction and one for general industry and maritime. The rule became effective June 23, 2016, and enforcement was originally scheduled to begin on June 23, 2017, but was delayed by the Trump administration. OSHA began enforcing most provisions of the standard for construction on September 23, 2017, and has announced that it will begin enforcing most provisions of the standard for general industry and maritime on June 23, 2018.

OSHA issued this rule to reduce workers’ exposure to cancer-causing respirable crystalline silica. Studies have linked exposure to silica to lung cancer, silicosis, chronic obstructive pulmonary disease, and kidney disease. About 2.3 million workers are exposed to respirable crystalline silica in their workplaces, including 2 million construction workers who drill, cut, crush, or grind silica-containing materials such as concrete and stone.24 Responsible employers have been protecting workers from harmful exposure to silica for years, using widely available equipment that controls silica dust with a simple water spray to wet the dust down or a vacuum system to contain the dust. OSHA estimates that the rule will save over 600 lives and prevent more than 900 new cases of silicosis each year, once its effects are fully realized.25 It is past time for the Trump administration to start taking workers’ sides by enforcing this rule to protect working people’s lives and livelihoods.

Rolling back protections for workers exposed to beryllium

On January 9, 2017, the Occupational Safety and Health Administration published its final rule on occupational exposure to beryllium and beryllium compounds, which was promulgated to protect employees exposed to beryllium from significant risks of chronic beryllium disease and lung cancer.26 Under the Trump administration, OSHA proposed to rescind provisions of the rule intended to protect workers in the construction and shipyards sectors.27 DOL announced that OSHA will not enforce these January 9, 2017, shipyard and construction standards until further notice while this new rulemaking is underway.28

About 62,000 workers are exposed to beryllium in their workplaces, including approximately 11,500 construction and shipyard workers.29 The Trump administration’s proposal would rescind important protections in the new rule, which was issued after decades of effort and study that uncovered overwhelming evidence that OSHA’s 35-year-old beryllium standard did not protect workers from severe lung disease and lung cancer.30 Under Trump’s proposal, employers would no longer have to measure beryllium levels or provide medical testing to workers at risk of fatal lung disease. This proposal is another example of Trump’s willingness to abandon workers’ rights to come home safe and healthy at the end of the day, in favor of corporate profits.

Proposing to weaken the inspection rule for metal and nonmetal mines

In September 2017, the Trump DOL’s Mine Safety and Health Administration (MSHA) proposed to weaken metal/nonmetal mine safety inspection requirements that went into effect at the end of January 2017. Under the Obama-era rule, mine safety inspectors were allowed to conduct a safety examination at any time, including during the mineworkers’ shifts, which allows inspectors to spot unsafe practices and stop them before someone gets hurt. But in response to pressure from mine operators, Trump’s appointees have issued a proposed rule that would permit a mine safety inspection to occur only before or right as workers are beginning their shift in the mine.31

The proposed rule puts workers in danger and allows unscrupulous mine operators to conceal safety hazards. If mine safety inspectors are only permitted to evaluate a mine before or at the beginning of a shift, the safety inspectors will never discover unsafe working conditions or unsafe mining procedures that occur during the shifts themselves. A mine operator could easily tell his employees to wait until after the inspection at the beginning of the shift before commencing unsafe mining practices for the remainder of their workday.

In addition, the Obama-era rule required mine operators to record all hazardous conditions found by inspectors, even if they are immediately corrected. Under the Trump administration’s proposed rule, only hazardous conditions that are not immediately corrected would have to be recorded. This would significantly cut down on the evidence and documentation needed by MSHA, workers, and mine operators to identify and fix patterns of unsafe mining practices.

This proposal to prohibit mine safety inspectors from performing critical workplace examinations means more miners will be exposed to unsafe work conditions. From January 2010 through mid-December 2015, 122 miners were killed in 110 accidents at metal and nonmetal mines.32 Another 16 died in 2016,33 and another 13 died in 2017.34

Considering a proposal to increase poultry line speeds, endangering workers

The Trump Department of Agriculture has indicated that it is open to relaxing existing regulations of line speeds in poultry plants, placing poultry slaughter and processing workers at increased risk of injury, illness, or death.35 Regulations issued in 2014 stated that line speeds in poultry plants should not increase beyond the already fast rate of 140 birds per minute.36 Under existing regulations, the poultry industry’s own data show that poultry workers are injured at twice the rate of the national average. And these statistics likely undercount the number of injuries. The USDA itself has recognized “systemic underreporting of work-related injuries and illnesses” that makes it difficult to accurately evaluate the extent to which poultry workers suffer injuries.37 Regardless, it is clear that poultry workers face great risk in their jobs and that increasing line speeds would only increase those risks.

Proposing to weaken protections for farmworkers

The Trump Environmental Protection Agency proposed weakening regulations protecting farmworkers from harmful effects of pesticide exposure.38 The regulations prohibit workers younger than 18 from handling pesticides, require that other workers receive annual safety training on handling pesticides, and require employers to post warning signs around pesticide-treated areas.39 The EPA proposed these standards in 2014, and many of the protections have already gone into effect.40 The EPA itself has estimated that roughly 2,000–3,000 cases of acute pesticide exposure occur among farmworkers every year,41 with health effects ranging from rashes, nausea, blisters, and respiratory issues to Parkinson’s disease.42 Rolling back these standards exposes farmworkers to additional risks of illness and death.

Deregulation casualty #2: Workers’ wages

Proposing to make it legal for employers to take workers’ hard-earned tips

On December 5, the Trump administration took its first major step toward allowing employers to legally take tips earned by their employees. The current restrictions on “tip pooling,” instituted by the Department of Labor in 2011, allow restaurants to pool the tips servers receive but stipulate that the employer may only share pooled tips with other workers who customarily receive tips, such as bussers and bartenders.43 Employers are prohibited from retaining any of the pooled tips themselves. But the Trump Department of Labor has proposed rescinding those restrictions.44

At first glance, the proposed rule seems benevolent: restaurants would be able to pool the tips servers receive and share them with untipped employees, such as cooks and dishwashers, in addition to tipped employees. But, crucially, the new rule would mean that employers are not required to distribute pooled tips among their workers: as long as tipped workers earn at least the minimum wage, the employer can legally pocket their tips. And basic economic logic dictates that it is highly unlikely that back-of-the-house workers will get more pay. There is currently no limit to what these workers can be paid, so employers are already paying their nontipped workers what they need to pay to attract workers willing to work in those jobs. Thus, if employers do share some tips with them, the extra cash would likely be offset by a reduction in their base pay, leaving their take-home pay unaffected.

We estimate that under Trump’s proposed rule, employers will likely pocket $5.8 billion of their workers’ hard-earned tips each year—around $1,000 a year per tipped worker.45 And because women are both more likely to be tipped workers and to earn lower wages, this rule would disproportionately harm them. We estimate that of the $5.8 billion, nearly 80 percent—$4.6 billion—would be taken from women working in tipped jobs.46

Taking money out of workers’ pockets by weakening the overtime rule

In 2016, after years of work, the Department of Labor (DOL) updated the “overtime pay” rule, raising the salary threshold below which workers are automatically eligible for overtime pay to $47,47647 and giving 12.5 million people new or strengthened overtime protections.48 Because the threshold had not been adequately updated over the last few decades, it had eroded dramatically with inflation. The percentage of full-time salaried workers automatically eligible for overtime based on their pay dropped from more than 60 percent in 1975 to less than 7 percent in 2016.49 Prior to the 2016 rule, low-level managers at retail and fast-food outlets who made only $23,660 a year—lower than the poverty rate for a family of four—could be required to work long hours without any extra pay for the extra hours worked.50

The 2016 updated overtime pay rule would have helped ensure that middle-class Americans who work hard get a fair return on that work—putting money in people’s pockets and giving them the chance to spend more time with their families. However, the Obama administration DOL’s overdue attempt to restore lost pay to America’s workers was blocked in the courts by corporate interests, and, on October 30, 2017, the Trump administration made clear that it would not defend the rule. The Trump administration has signaled that it is going to undermine the rule, once again siding with corporate interests over workers.51

Deregulation casualty #3: Workers’ savings

Rolling back rules that made it easier for workers to save for retirement

On April 13, 2017, Trump signed two resolutions blocking DOL rules that assisted local governments that create Individual Retirement Account (IRA) programs for private-sector workers. Many municipalities have sought to establish initiatives requiring employers that do not offer a workplace retirement plan to automatically enroll workers in payroll-deduction IRAs administered by the local government. The DOL rule paved the way for these initiatives by simply clarifying that these plans are not covered by the Employee Retirement Income Security Act (ERISA), the federal law governing private-sector employer-sponsored plans, addressing localities’ concerns that they may be subject to certain liabilities under ERISA.52 The Government Accountability Office warned that such legal uncertainties could delay or deter states’ efforts to expand coverage.53

By blocking this rule, Trump blocks a path for retirement savings for the roughly 55 million private-sector wage and salary workers ages 18–64 who do not have access to retirement savings plans through their employers. Local payroll-deduction savings initiatives encourage workers to contribute to tax-favored IRAs through automatic deduction. These savings initiatives provide important assistance to workers in saving for retirement, as few workers contribute to a retirement plan outside of work. Without innovations like these, fewer workers will be able to afford retirement.54

Delaying a rule providing protections for retirement savers

The Trump administration’s Department of Labor is actively working to weaken or rescind the “fiduciary” rule.55 The latest step in these efforts is an 18-month delay of key provisions of the rule.56 The rule simply requires financial advisers to provide what most clients probably already think they are receiving: advice about their retirement plans untainted by conflicts of interest.57 It would prohibit common practices such as steering clients into investments that provide lower rates of return for the client but higher commissions for the adviser. The financial industry strongly opposes this rule because it wants to preserve a system that allows financial advisers to give their clients advice that is in the adviser’s interest rather than the client’s.

Conflicted advice leads to lower investment returns,58 causing real losses for the clients who are victimized.59 We estimate that retirement savers who will get or have gotten bad advice during the various delays imposed by the Trump administration will lose a total of $18.5 billion over the next 30 years.60 Further, the rule is being delayed with the clear intent of never fully implementing it. Instead, the Trump administration is buying time until they can permanently dismantle key elements of the rule. People who have worked hard to save for retirement need and deserve the fiduciary rule to be fully implemented and enforced.

Deregulation casualty #4: Workers’ safety nets

Rolling back a rule ensuring that unemployment workers can access earned benefits

Congressional Republicans approved and Trump signed a resolution that blocked a regulation establishing rules for drug testing applicants for unemployment insurance (UI) benefits.61 As part of the deal, states were permitted to drug test only those UI applicants who had been discharged from their last job for drug use or whose only suitable work opportunity is in a field that regularly drug tests workers. The rule directed the secretary of labor to determine which occupations regularly drug test workers. The Department of Labor issued a rule defining such “occupations” as those that are required, or may be required in the future, by state or federal law, to be drug tested.62

This rule would have clarified circumstances under which individuals filing for unemployment benefits may be subjected to drug testing. Mandatory drug testing for UI applicants is arguably unconstitutional and unnecessarily stigmatizes jobless workers. Conditioning receipt of UI benefits on this type of requirement fundamentally challenges our nation’s UI system, creating the perception that workers do not earn unemployment insurance. But workers do earn the right to unemployment insurance benefits through their prior participation in the workforce. Workers only access their earned benefits when they lose their jobs and are actively working to find new ones; this insurance is intended to help cover workers’ basic needs during this gap period between jobs. The repeal of this rule will hurt workers when they are at their most vulnerable, while benefiting companies seeking to reduce their tax obligations.

Deregulation casualty #5: Pay equity

Putting the EEO-1 pay data rule on hold

The EEO-1 pay data collection rule was an Obama-era rule intended to identify and fix pay disparities in America’s workplaces. The rule would have required large companies (with 100 or more employees) to confidentially report to the EEOC information about what they pay their employees by job category, sex, race, and ethnicity.63 The goal of this rule was to help employers, the public, and the government identify and remedy gender and racial/ethnic pay inequities. But the Trump administration has put the EEO-1 pay data collection rule on hold.64

By putting the equal pay data rule on hold, the Trump administration is making it harder for employers and federal agencies to identify pay disparities and root out employment discrimination. Further, this decision ignores what the research shows—inequities have gotten worse, not better. Even among workers with the same level of education and work experience, black–white wage gaps are larger today than nearly 40 years ago65 and gender pay disparities have remained essentially unchanged for at least 15 years.66 In both cases, discrimination has been shown to be a major factor in the persistence of those gaps.

When this rule was first announced, former EEOC Chair Jenny R. Yang stated, “Collecting pay data is a significant step forward in addressing discriminatory pay practices. This information will assist employers in evaluating their pay practices to prevent pay discrimination and strengthen enforcement of our federal anti-discrimination laws.”67 By staying this rule, the Trump administration has shown that it does not value equal pay for equal work.

Proposing to roll back an SEC rule that requires disclosure of CEO-to-employee pay ratios

The Trump administration has proposed rolling back the 2015 Securities and Exchange Commission rule requiring that public companies disclose the ratio of compensation of its chief executive officer (CEO) to the median compensation of its employees.68 The rule was mandated by the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010.69

Rolling back the rule will simply deny workers and shareholders information necessary for them to evaluate CEO compensation and performance and determine the fairness of their own compensation structure. This allows corporate interests to operate behind closed doors with less accountability to the public and to workers. CEO pay continues to be very, very high and has grown far faster in recent decades than typical worker pay. CEO compensation has risen by 807 or 937 percent (depending on how it is measured—using stock options granted or stock options realized, respectively) from 1978 to 2016. In 2016 CEOs in America’s largest firms made an average of $15.6 million in compensation, or 271 times the annual average pay of the typical worker.70

Deregulation casualty #6: Workers’ rights to organize and join a union

Rolling back a transparency rule that would allow workers to know when their employer has hired outside anti-union consultants during a union election

The rights of most workers to organize and bargain collectively with their employers are protected under the National Labor Relations Act (NLRA) of 1935. But when workers seek to exercise these rights, employers often hire union avoidance consultants—also known as “persuaders”—to orchestrate and roll out anti-union campaigns. Union avoidance consultants may engage with workers directly, for example, delivering their anti-union presentations in face-to-face meetings. Or they may influence workers indirectly by providing management with ammunition for campaigns, including anti-union flyers, speeches, videos, and other materials.71 The Trump DOL has proposed rolling back an important rule (the “persuader rule”) that ensured workers would have accurate information about their employer’s use of anti-union consultants surrounding union election campaigns.72

The rule Republicans are rolling back closed a massive reporting loophole that has allowed employers to keep indirect persuader activity secret. Disclosure of the large amounts of money employers pay to anti-union consultants—sometimes hundreds of thousands of dollars—would allow workers to know whether the messages they hear are coming directly from their employer or from a paid, third-party consultant.73 Seeing how much money employers are paying out to these consultants would provide important perspective on employers’ frequent argument that they cannot afford to pay union wages, and it would give workers the information they need to make informed choices as they pursue their right to organize. This disclosure rule would have helped level the playing field for workers who want to join together to negotiate with their employers for better pay and working conditions.

Almost half (48 percent) of workers polled said they’d vote to create a union in their workplace tomorrow if they got the chance.74 However, the intensity with which employers have opposed organizing efforts,75 and the continuing tilt of the legal and policy playing field against workers seeking to bargain collectively, have led to a decline in union membership. DOL’s rescission of the persuader rule is just one more indicator that the Trump administration is working on behalf of corporate interests to further rig the system against working people.

Rolling back rules to modify and streamline union elections

On December 12, 2017, the National Labor Relations Board (NLRB) took the first step toward rolling back a 2014 rule that simplified the union election process by which working people can join together to bargain for better wages and working conditions. The NLRB announced the issuance of a Request for Information (RFI) asking for public input on the 2014 election rule—indicating that Trump’s appointees to the NLRB plan to alter the rule.76 The election rule, which has been upheld by a federal court of appeals, includes a series of reforms that eliminate unnecessary delay in the election process and modernize agency procedures.

The NLRB protects the rights of most private-sector employees to join together, with or without a union, to improve their wages and working conditions. Employees covered by the National Labor Relations Act are guaranteed the right to form, join, decertify, or assist a labor organization; to bargain collectively through representatives of their own choosing; or to refrain from such activities. The NLRB’s decision to reexamine the rule demonstrates that the Trump board majority has little interest in maintaining an efficient election process for this nation’s workers. Ironically, the NLRB will accept electronic responses to the RFI for the election rule that, if rolled back, will affect the ability of workers to file electronic election petitions.

Deregulation casualty #7: Consequences for employers who violate workers’ rights

Rolling back the Fair Pay and Safe Workplaces rule

Senate Republicans approved a resolution that President Trump signed that rolled back a rule that required federal contractors to disclose workplace violations—specifically violations of federal labor laws and executive orders that address wage and hour, safety and health, collective bargaining, family medical leave, and civil rights protections.77 The rule had directed that such violations be considered when awarding federal contracts. In addition, the rule had also mandated that contractors provide each worker with written notice of basic information including wages, hours worked, overtime hours, and whether the worker is an independent contractor. Finally, the rule had prohibited contractors from requiring workers to sign predispute arbitration agreements for discrimination, harassment, or sexual assault claims.

Currently, there is no effective system to ensure that taxpayer dollars are not awarded to contractors who violate basic labor and employment laws. As a result, the federal government awards billions of dollars in contracts to companies that break the law.78 This rule would have helped ensure that federal contracts (and taxpayer dollars) are not awarded to companies with track records of labor and employment law violations. Workers, taxpayers, and law-abiding contractors would have benefited from this rule. Contractors with records of cutting corners by violating labor and employment laws will benefit from the congressional resolution blocking this rule. What’s more, by repealing this rule, the federal government will be rewarding companies that force workers to waive their rights to go to court and instead sign agreements requiring them to resolve claims of sexual harassment or discrimination in private arbitration.

Conclusion

Regulations establish the rules of the game and assure important protections for working people. Corporations and wealthy special interests have demonstrated that—if there’s nothing stopping them—they will do what they can to squeeze out more profits for themselves, even if it means jeopardizing workers’ health and safety and retirement funds. The Great Recession is proof that it is dangerous to assume that corporations and Wall Street will police themselves. American workers deserve a fair system—with rules that serve their interests as opposed to deregulating to rig the system so that corporate interests can rake in ever-larger profits at the expense of workers. The Trump administration and congressional Republicans have spent an enormous amount of time and political capital in their first year in control doing exactly that—by painting regulations as the “problem.” It is time to end this deception and return to defending the rules that protect workers, consumers, and public health.

Endnotes

1. White House Office of the Press Secretary, “Remarks by President Trump on Deregulation” [transcript], December 14, 2017.

2. Economic Policy Institute, Policy Watch (Perkins Project on Worker Rights and Wages), www.epi.org/policywatch.

3. Office of Management and Budget, 2016 Draft Report to Congress on the Benefits and Costs of Federal Regulations and Agency Compliance with the Unfunded Mandates Reform Act, 2016; see also Heidi Shierholz and Celine McNicholas, Understanding the Anti-Regulation Agenda: The Basics, Economic Policy Institute, April 11, 2017.

4. John Irons and Isaac Shapiro, Regulation, Employment, and the Economy: Fears of Job Loss are Overblown, Economic Policy Institute, April 12, 2011.

5. John Irons and Isaac Shapiro, Regulation, Employment, and the Economy: Fears of Job Loss are Overblown, Economic Policy Institute, April 12, 2011.

6. Josh Bivens, “Testimony before the Judiciary Subcommittee on Regulatory Reform, Commercial and Antitrust Law,” February 24, 2016; John Irons and Isaac Shapiro, Regulation, Employment, and the Economy: Fears of Job Loss Are Overblown, Economic Policy Institute, April 12, 2011.

7. U.S. Bureau of Labor Statistics, “Extended Mass Layoffs in 2012,” BLS Reports, September 2013.

8. Heidi Shierholz and Celine McNicholas, Understanding the Anti-Regulation Agenda: The Basics, Economic Policy Institute, April 11, 2017.

9. Heidi Shierholz and Celine McNicholas, Understanding the Anti-Regulation Agenda: The Basics, Economic Policy Institute, April 11, 2017, citing Christopher Cox, testimony before the House Committee on Oversight and Government Reform, October 23, 2008.

10. White House Office of the Press Secretary, “Presidential Executive Order on Reducing Regulation and Controlling Regulatory Costs,” January 30, 2017; Economic Policy Institute, “Executive Order on Reducing Regulation and Controlling Regulatory Costs: EO 13771,” Policy Watch (Perkins Project on Worker Rights and Wages), January 30, 2017.

11. White House Office of the Press Secretary, “Remarks by President Trump on Deregulation” [transcript], December 14, 2017.

12. Office of Information and Regulatory Affairs, Office of Management and Budget, Executive Office of the President, “Regulatory Reform: Two-for-One and Regulatory Cost Caps,” accessed January 25, 2018, at www.reginfo.gov/public/do/eAgendaEO13771.

13. Office of Information and Regulatory Affairs, Office of Management and Budget, Executive Office of the President, “Current Regulatory Plan and the Unified Agenda of Regulatory and Deregulatory Actions,” accessed January 25, 2018, at www.reginfo.gov/public/do/eAgendaMain.

14. Eric Lipton and Jasmine C. Lee, “Which Obama-Era Rules Are Being Reversed in the Trump Era,” New York Times, May 18, 2017. A CRA resolution either blocks a rule from taking effect or, if the rule has already taken effect, it prohibits the rule from continuing to be in effect. It also blocks any agency from issuing a new rule in “substantially the same form” as the disapproved rule—thus limiting options for restoring lost protections. (Technically, a disapproved rule could be reissued if Congress passed a bill specifically authorizing an agency to reissue the rule, but this is unlikely.)

15. Stuart Shapiro, “The Congressional Review Act, Rarely Used and (Almost Always) Unsuccessful,” The Hill, April 17, 2015; Eric Lipton and Jasmine C. Lee, “Which Obama-Era Rules Are Being Reversed in the Trump Era,” New York Times, May 18, 2017.

16. H.J. Res. 83, 115th Congress (2017); PL 115-21.

17. AKM LLC dba Volks Constructors v. Secretary of Labor, 675 F.3d 752 (D.C. Cir. 2012).

18. Clarification of Employer’s Continuing Obligation to Make and Maintain an Accurate Record of Each Recordable Injury and Illness, 81 Fed. Reg. 91792 (December 19, 2016).

19. As noted on the informational page about the May 2016 final rule on OSHA’s website, “Behavioral economics tells us that making injury information publicly available will ‘nudge’ employers to focus on safety” (U.S. Department of Labor, Occupational Safety and Health Administration, “Final Rule Issued to Improve Tracking of Workplace Injuries and Illnesses” [webpage], accessed January 25, 2018, at www.osha.gov/recordkeeping/finalrule). For the full text of the May 2016 rule, see Improve Tracking of Workplace Injuries and Illnesses, 81 Fed. Reg. 29624 (May 12, 2016).

20. In June 27, 2017, OSHA proposed to push back the compliance date to December 1, 2017. On November 22, 2017, OSHA announced a further delay, to December 15, 2017. Finally, on December 18, 2017, OSHA announced that it would “not take enforcement action against those employers who submit their reports after the December 15, 2017, deadline but before December 31, 2017, final entry date.” See U.S. Department of Labor, Occupational Safety and Health Administration, “US Labor Department’s OSHA Proposes to Delay Compliance Date for Electronically Submitting Injury, Illness Reports” [news release], June 27, 2017; U.S. Department of Labor, Occupational Safety and Health Administration, “U.S. Department of Labor’s OSHA Extends Compliance Date for Electronically Submitting Injury, Illness Reports to December 15, 2017” [news release], November 22, 2017; U.S. Department of Labor, Occupational Safety and Health Administration, “U.S. Labor Department’s OSHA Accepting Electronically Submitted Injury, Illness Reports through December 31” [trade release], December 18, 2017.

21. U.S. Department of Labor, Occupational Safety and Health Administration, “U.S. Department of Labor’s OSHA Extends Compliance Date for Electronically Submitting Injury, Illness Reports to December 15, 2017” [news release], November 22, 2017; Improve Tracking of Workplace Injuries and Illnesses: Delay of Compliance Date, 82 Fed. Reg. 55761 (November 24, 2017).

22. U.S. Department of Labor, Bureau of Labor Statistics, “National Census of Fatal Occupational Injuries in 2016” [news release], December 19, 2017.

23. Economic Policy Institute, “DOL Begins Enforcing Silica Rule,” Policy Watch (Perkins Project on Worker Rights and Wages), September 23, 2017.

24. U.S. Department of Labor, Occupational Safety and Health Administration, OSHA’s Proposed Crystalline Silica Rule: Overview [fact sheet], accessed January 25, 2018, at www.osha.gov/silica/factsheets/OSHA_FS-3683_Silica_Overview.html.

25. U.S. Department of Labor, Occupational Safety and Health Administration, OSHA’s Proposed Crystalline Silica Rule: Overview [fact sheet], accessed January 25, 2018, at www.osha.gov/silica/factsheets/OSHA_FS-3683_Silica_Overview.html.

26. Occupational Exposure to Beryllium, 82 Fed. Reg. 2470 (January 9, 2017).

27. Occupational Exposure to Beryllium and Beryllium Compounds in Construction and Shipyard Sectors, 82 Fed. Reg. 29182 (June 27, 2017).

28. U.S. Department of Labor, Occupational Safety and Health Administration, “US Labor Department’s OSHA Publishes Proposed Rule on Beryllium Exposure” [news release], June 23, 2017.

29. U.S. Department of Labor, Occupational Safety and Health Administration, “Final Rule to Protect Workers from Beryllium Exposure” [webpage], accessed January 25, 2018, at www.osha.gov/berylliumrule/index.html.

30. Jordan Barab, “OSHA Launches Rollback of Beryllium Worker Protections,” Confined Space Blog, June 23, 2017.

31. Examinations of Working Places in Metal and Nonmetal Mines, 82 Fed. Reg. 42757 (September 12, 2017).

32. U.S. Department of Labor, Mine Safety and Health Administration, Questions & Answers [about the proposed rule amending the final rule on examinations of working places in metal and nonmetal mines (82 Fed. Reg. 42757)], accessed January 25, 2018, at www.msha.gov/sites/default/files/Regulations/rollout-qas-q1-through-q8.pdf.

33. U.S. Department of Labor, Mine Safety and Health Administration, The Metal–Nonmetal Monitor: 2016 Fatal Accidents, January 6, 2017.

34. U.S. Department of Labor, Mine Safety and Health Administration, Preliminary Accident Reports, Fatality Alerts, and Fatal Accident Reports, accessed January 25, 2018, at arlweb.msha.gov/fatals.

35. Deborah Berkowitz, NELP Applauds GAO Report on Workplace Hazards in Meat and Poultry Industry, December 7, 2017.

36. Modernization of Poultry Slaughter Inspection; Final Rule, 79 Fed. Reg. 49566.

37. Nicole Erwin, “Too Fast for Safety? Poultry Industry Wants to Speed Up the Slaughter Line,” NPR’s The Salt, October 27, 2017.

38. Pesticides; Agricultural Worker Protection Standard; Reconsideration of Several Requirements and Notice About Compliance Dates, 82 Fed. Reg. 60576 (December 21, 2017).

39. National Safety Council, “EPA Proposes ‘Commonsense’ Changes to Protect Farmworkers from Pesticides,” Safety+Health, February 21, 2014; 40 CFR 170.

40. United States Environmental Protection Agency, “Agricultural Worker Protection Standard” [webpage], accessed January 25, 2018, at www.epa.gov/pesticide-worker-safety/agricultural-worker-protection-standard-wps.

41. According to Pesticides; Agricultural Worker Protection Standard Revisions, 80 Fed. Reg. 67495 (November 2, 2015), “EPA estimates that about 1,810 to 2,950 acute pesticide exposure incidents occur annually on agricultural establishments.”

42. Penn State College of Agricultural Sciences, Potential Health Effects of Pesticides, November 6, 2017; National Institutes of Health, “NIH Study Finds Two Pesticides Associated with Parkinson’s Disease” [news release], February 11, 2011.

43. U.S. Department of Labor, Fact Sheet #15: Tipped Employees under the Fair Labor Standards Act, revised December 2016.

44. Tip Regulations under the Fair Labor Standards Act, 82 Fed. Reg. 57395 (December 5, 2017).

45. Heidi Shierholz et al., Employers Would Pocket $5.8 Billion of Workers’ Tips under Trump Administration’s Proposed ‘Tip Stealing’ Rule, Economic Policy Institute, December 12, 2017.

46. Heidi Shierholz et al., Women Would Lose $4.6 Billion in Earned Tips if the Administration’s ‘Tip Stealing’ Rule Is Finalized: Overall, Workers Would Lose $5.8 billion, Economic Policy Institute, January 17, 2018.

47. U.S. Department of Labor Wage and Hour Division, “Final Rule: Overtime. Defining and Delimiting the Exemptions for Executive, Administrative, Professional, Outside Sales and Computer Employees under the Fair Labor Standards Act” [informational webpage], accessed January 26, 2018, at www.dol.gov/whd/overtime/final2016.

48. Ross Eisenbrey and Will Kimball, The New Overtime Rule Will Directly Benefit 12.5 Million Working People: Who They Are and Where They Live, Economic Policy Institute, May 17, 2016.

49. Celine McNicholas, Samantha Sanders, and Heidi Shierholz, What’s at Stake in the States if the 2016 Federal Raise to the Overtime Pay Threshold Is Not Preserved—and What States Can Do about It, Economic Policy Institute, November 15, 2017.

50. Celine McNicholas, Samantha Sanders, and Heidi Shierholz, What’s at Stake in the States if the 2016 Federal Raise to the Overtime Pay Threshold Is Not Preserved—and What States Can Do about It, Economic Policy Institute, November 15, 2017.

51. In November 2016, the United States District Court for the Eastern District of Texas, Sherman Division, issued a preliminary nationwide injunction blocking the rule from taking effect. In December 2016 the Department of Justice, on behalf of the Department of Labor, filed a notice with the U.S. Circuit Court of Appeals for the Fifth Circuit to appeal the preliminary injunction. In August 2017, the United States District Court for the Eastern District of Texas issued a final ruling concluding that the overtime rule was invalid, rendering Justice’s 2016 appeal moot. On October 30, 2017, the Department of Justice, on behalf of the Department of Labor, filed a notice to appeal the judge’s decision as part of a process under which the Trump administration DOL will undertake its own rulemaking to determine a new salary threshold (see U.S. Department of Labor, “Department of Labor Provides Update on Overtime” [news release], October 30, 2017).

52. Savings Arrangements Established by Qualified State Political Subdivisions for Non-Governmental Employees, 81 Fed. Reg. 92639 (December 20, 2016).

53. United States Government Accountability Office, Retirement Security: Federal Action Could Help State Efforts to Expand Private Sector Coverage, September 2015.

54. David John and Gary Koenig, Fact Sheet: Workplace Retirement Plans Will Help Workers Build Economic Security, AARP Public Policy Institute, October 2014; Anqi Chen and Alicia H. Munnell, Who Contributes to Individual Retirement Accounts? Center for Retirement Research at Boston College, Issue in Brief no. 17-8, April 2017.

55. White House Office of the Press Secretary, “Presidential Memorandum on Fiduciary Duty Rule,” February 3, 2017.

56. U.S. Department of Labor, “US Labor Department Extends Fiduciary Rule Applicability Date” [news release], April 4, 2017.

57. Definition of the Term “Fiduciary”; Conflict of Interest Rule—Retirement Investment Advice, 81 Fed. Reg. 20946 (April 8, 2016).

58. Ross Eisenbrey, “Labor Department’s Common Sense Fiduciary Rule Survives the House of Representatives,” Working Economics (Economic Policy Institute blog), December 16, 2015.

59. Heidi Shierholz, “EPI Comment on the Proposal to Extend the Applicability Date to the Fiduciary Rule,” letter to the U.S. Department of Labor, March 17, 2017.

60. We estimate that delays through January 1, 2018, would cost retirement savers $7.6 billion and that an additional 18-month delay would cost retirement savers an additional $10.9 billion. See Heidi Shierholz, Another Fiduciary Rule Delay Would Cost Retirement Savers $10.9 Billion over 30 Years, Economic Policy Institute, August 10, 2017.

61. H.J. Res. 42, 115th Congress (2017); PL 115-17.

62. Federal-State Unemployment Compensation Program; Middle Class Tax Relief and Job Creation Act of 2012 Provision on Establishing Appropriate Occupations for Drug Testing of Unemployment Compensation Applicants, 81 Fed. Reg. 50298 (August 1, 2016).

63. U.S. Equal Employment Opportunity Commission, “EEOC to Collect Summary Pay Data” [press release], September 29, 2016.

64. U.S. Equal Employment Opportunity Commission, “What You Should Know: Statement of Acting Chair Victoria A. Lipnic about OMB Decision on EEO-1 Pay Data Collection” [webpage], accessed January 25, 2018, at www.eeoc.gov/eeoc/newsroom/wysk/eeo1-pay-data.cfm.

65. Valerie Wilson and William M. Rodgers III, Black–White Wage Gaps Expand with Rising Wage Inequality, Economic Policy Institute, September 20, 2016.

66. Elise Gould, Jessica Schieder, and Kathleen Geier, What Is the Gender Pay Gap and Is It Real?: The Complete Guide to How Women Are Paid Less Than Men and Why It Can’t Be Explained Away, Economic Policy Institute, October 20, 2016.

67. U.S. Equal Employment Opportunity Commission, “EEOC to Collect Summary Pay Data” [press release], September 29, 2016.

68. U.S. Securities and Exchange Commission, “Reconsideration of Pay Ratio Rule Implementation,” public statement by Acting SEC Chairman Michael S. Piwowar, February 6, 2017; see also “Presidential Executive Order on Core Principles for Regulating the United States Financial System,” issued by the White House, February 3, 2017.

69. U.S. Securities and Exchange Commission, “SEC Adopts Rule for Pay Ratio Disclosure” [press release], August 5, 2015.

70. Lawrence Mishel and Jessica Schieder, CEO Pay Remains High Relative to the Pay of Typical Workers and High-Wage Earners, Economic Policy Institute, July 20, 2017.

71. U.S. House of Representatives, Education and Workforce Committee, Minority Views: H.J. Res. 87, Providing for Congressional Disapproval under Chapter 8 of Title 5, United States Code, of the Final Rule of the Department of Labor relating to “Interpretation of the ‘Advice’ Exemption in Section 203(c) of the Labor-Management Reporting and Disclosure Act.” 114th Congress, Second Session, September 9, 2016.

72. Rescission of Rule Interpreting “Advice” Exemption in Section 203(c) of the Labor-Management Reporting and Disclosure Act, 82 Fed. Reg. 26877 (June 12, 2017).

73. Marni von Wilpert, “Union Busters Are More Prevalent Than They Seem, and May Soon Even Be at the NLRB,” Working Economics (Economic Policy Institute blog), May 1, 2017.

74. Josh Bivens et al., How Today’s Unions Help Working People, Economic Policy Institute, August 24, 2017.

75. Kate Bronfenbrenner, No Holds Barred—The Intensification of Employer Opposition to Organizing, Economic Policy Institute Briefing Paper no. 235, May 20, 2009.

76. National Labor Relations Board, Office of Public Affairs, “Request for Information Regarding Representation Election Regulations” [announcement], December 12, 2017; Representation-Case Procedures, 82 Fed. Reg. 58783 (December 14, 2017).

77. H.J. Res. 37, 115th Congress (2017); PL 115-11.

78. Office of Senator Elizabeth Warren, Breach of Contract: How Federal Contractors Fail American Workers on the Taxpayer’s Dime, 2017.

Estimates made by the Environmental Protection Agency of the likely employment effects of a proposed rule (the Clean Power Plan or CPP) mandating reductions in greenhouse gas emissions from existing power plants are likely incomplete. These estimates undercount both positive and negative influences on employment. This paper provides a comprehensive overview of the channels through which the mandated emission reductions may lead to employment changes, both positive and negative. It finds that the CPP is likely to lead to a net increase in of roughly 360,000 jobs in 2020, but that the net job creation falls relatively rapidly thereafter, with net employment gains of roughly 15,000 jobs in 2030. This paper also provides comparisons of the composition of employment in job-gaining versus job-losing industries. While workers in job-losing industries are less likely to have four-year college degrees, jobs in these industries are far less likely to be low-wage than in the overall economy, or in job-gaining industries. Workers in job-losing industries are also substantially more likely to be represented by a union. The characteristics of employment in job-losing industries, as well as the likely geographic concentration of gross job losses in poorer states, is likely to lead to transition challenges for workers and communities in responding to the CPP. This suggests the potential for a key role for federal assistance and complementary policies to aid these groups.

Introduction and summary of findings

In June 2014, the Environmental Protection Agency (EPA) issued a proposed regulation that instructs states to develop plans to reduce greenhouse gas emissions from existing fossil fuel–fired electric generating units (EGUs). The Clean Power Plan (or CPP) calls for the emission limits to be met by 2020.

This rule is the most substantial U.S. regulatory undertaking aimed at mitigating global climate change. In 2007, the Supreme Court ruled that greenhouse gas emissions are covered by the 1970 Clean Air Act’s definition of an air pollutant, and that the EPA must determine whether these emissions cause or contribute to air pollution that may be reasonably anticipated to endanger public health or welfare. Legislative efforts to mitigate greenhouse gas emissions passed in the House of Representatives in 2009, but failed to gain a vote in the Senate, despite widespread recognition that they likely had majority support. Passage of such legislation to mitigate greenhouse gas emissions would almost certainly have kept the proposed EPA rule from moving forward.

Although the economic, health, and environmental effects of the proposed rule are significant, this paper will focus on just one narrower effect: potential impacts on employment. Despite the fact that jobs and employment growth are among the smaller outcomes of the proposed rule, they tend to garner outsized attention in debate over the rule—as does the jobs impact of most environmental legislation. In the Regulatory Impact Analysis (RIA) that accompanied the release of the proposed rule, the EPA provided preliminary estimates of some of the rule’s direct impacts on U.S. employment. This paper aims to build and improve upon the EPA estimates and provide a comprehensive accounting of how the proposed rule is likely to affect U.S. employment. The key findings of this paper are:

• The proposed rule will generate both gross job gains and gross job losses, with the sum of these being a net job gain in each of the three years surveyed. The EPA estimates that in 2020 investments in energy efficiency and construction of new generating capacity (both natural gas and renewables) will boost direct employment by roughly 120,000 jobs while reduction in coal-fired electricity generation will lead to the direct displacement of roughly 24,000 jobs. These direct job gains and displacements will hence lead to a direct net job gain of roughly 96,000.
• Each job directly created or displaced will create substantial ripple effects in other sectors. This paper aims to assess the “employment multiplier” associated with each of these first-round job impacts estimated by the EPA, accounting for the effect of these direct job gains and losses on supplier jobs, induced (re-spending or “Keynesian” effect) jobs, and public-sector jobs. Jobs in losing industries tend to have slightly higher employment multipliers than jobs in gaining industries, but when these effects are factored in, the net number of jobs supported in 2020 is roughly 360,000.
• In the longer term (through 2030), in part because employment multipliers are slightly higher in losing industries, the CPP’s indirect effects actually reduce the net number of jobs supported below the EPA estimates of net direct job creation, yielding roughly 24,342 net jobs supported by that year.
• Another channel through which the CPP could affect employment that is missing from EPA estimates concerns the effect of electricity price increases. The CPP is estimated to raise electricity prices by 5 percent in 2020, and by smaller amounts in 2025 and 2030. In the longer term (2025 and 2030), there is little evidence that these price increases will measurably impact employment. In the near term (2020), if consumers and businesses fail to anticipate or properly plan for these price increases, employment could fall by between 25,000 and 150,000 jobs.
• The labor force characteristics of jobs displaced and jobs supported following the CPP are quite different. Jobs displaced are more likely to be unionized and skew even more toward male workers than jobs supported. Jobs displaced are also less likely to be low-wage and more likely to be high-wage than jobs supported, even though jobs displaced are more likely to be filled by workers without a four-year college degree.
• Gross job losses are likely to be geographically concentrated, raising the challenge of ensuring a fair transition for workers in sectors likely to contract due to the CPP.

The first section of the paper describes the possible theoretical channels through which the CPP may affect employment. Subsequent sections provide an empirical assessment of each channel, followed by a sum of the effects to provide an overall estimate of the employment changes likely to be spurred by the CPP. This estimate includes gross job gains, gross job losses, and net changes (the sum of gross positive and negative changes). Finally, the paper examines job quality differences between gross job gains and gross job losses.

Channels through which the CPP may affect employment

The CPP mandates emission reductions on a state-by-state basis. By setting an overall state target, however, it leaves states many margins of adjustment along which to realize these emission reductions. For example, states could mandate that a share of overall electricity generation come from non-emitting sources. Or they could provide incentives for businesses, utilities, and households to make investments in energy efficiency. There is even the possibility of states joining together to form a regional cap and trade system that only allows utilities to emit greenhouse gases after purchasing a marketable permit to do so. Given this flexibility in how states respond to the CPP, there is great uncertainty in the precise economic outcomes that will be driven by the rule’s implementation. For the purposes of this paper, I follow the economic modeling undertaken by the EPA in its RIA and translate its economic projections (including preliminary employment projections) into comprehensive measures of employment changes.

Economic margins of adjustment

The EPA’s RIA identifies a number of margins of economic adjustment as likely to be most important to states to meet the emissions reduction guidelines. In the near term, electricity production from coal-fired electrical generating utilities will fall, and output by natural gas-fired power plants will increase. Construction of new electricity generation capacity from renewables (mostly wind and solar) will be front-loaded during the first 10 years of the rule, accelerating additions of renewable generating capacity. Solar and wind power will then replace some of the declines in coal-fired generation, particularly in the medium term (more than five years out). Energy efficiency investments will also be accelerated by the rule. These efficiency investments in homes, businesses, and industry will allow electrical generation to fall significantly relative to the non-CPP baseline by 2030. Examples of such energy efficiency investments include the purchase of more efficient home appliances and upgrading of insulation in residential homes; the optimization of heating, ventilation, air-conditioning systems, and electrical lighting in commercial buildings; and process optimization through modern instrumentation and control systems in the industrial sector.

Further, the sum of these effects is expected to raise electricity prices, particularly in the near term. The efficiency investments will, however, sufficiently dampen the demand for electricity quantities to lower overall household electricity spending by the end of the period described in the EPA RIA.

Employment margins of adjustment

Employment changes will follow directly from these economic margins of adjustment. A number of channels will lead to employment reductions. For example, retirement of coal-fired electrical generating capacity will lead to losses in operations and maintenance employment at existing coal-fired power plants. These effects show up in both short- and longer-run horizons examined in the RIA. The switch from coal-fired generation will lead to a reduction in demand for coal, and subsequent significant declines in both the short and long term for coal mining jobs. Increases in energy prices will spur employment responses, including demand-side reductions in spending, as households facing higher electricity bills (at least in the short run) curtail spending on non-energy goods. There will also be supply-side reductions as the (slight) decline in real wages spurred by rising energy prices affects labor supply decisions. Finally, there may be responses related to international competitiveness, as higher domestic energy prices affect the cost of industrial production in the United States.

Conversely, a number of changes spurred by the CPP will lead to employment gains (or at least to no losses) in both the near and longer term. For example, investments in energy efficiency will lead to employment increases in all time horizons. Short-term investments in heat rate improvement of existing fossil-fuel power plants will spur employment in the near term without reducing employment in the longer term.

Some of these margins of economic adjustment to the CPP have different employment impacts depending on the time horizon. For example, construction of new natural gas generation capacity boosts employment in the short run, but reduces employment in the longer run, as jobs associated with planned EGU expansions from natural gas are pulled forward in time by the rule. In the near term, this implies increases in construction jobs for building this new capacity, but some of this short-term employment boost comes at the expense of construction in the medium and longer term. Similarly, construction of new renewable generation capacity creates employment growth in the short term, but reductions in the medium and longer term as these jobs are pulled forward relative to the non-CPP baseline. Finally, operations and maintenance jobs at natural gas power plants will rise slightly in 2020 and 2025 and fall slightly in 2030.

Finally, each of these channels will in turn spur indirect effects. The indirect effects tracked in this paper will include: supplier jobs, induced (Keynesian) re-spending jobs, and public-sector jobs supported through tax revenue. The sections that follow will provide an empirical estimate of the effects (including indirect effects) of each of these channels.

Direct employment effects: Translating changes by economic activity into industry changes

This section will first report the estimates on direct employment effects contained in the EPA’s RIA, and will then assign these employment effects specific industry codes that can be used as inputs into employment requirement matrices in order to undertake the analysis of indirect effects included in later sections of the report.

The RIA essentially provides four different estimates (or scenarios) for each of these flows in every year. The RIA estimates effects stemming from a “state-only” or single state approach and a “regional” approach to meeting emissions targets. The CPP provides the option for states to collectively meet combined (regional) emissions targets. This may alter the margins of adjustment for meeting emissions guidelines as compared with a single-state approach. The RIA also provides two different options for the level and pace of emissions reductions that states must meet. One of these options is recommended by the EPA; the second is offered (and public comment is invited). In what follows, I average the outcomes estimated in the RIA in the four different scenarios (two emissions guidelines that can be met by either single-state or regional action). Because the differences in outcomes stemming from the four different scenarios are quite small, this averaging approach does not compromise the overall findings.

The main driver of these direct effects on employment is simply the change in electricity generation: both overall and by type (summarized in Table 1). Throughout this paper, economic impacts (whether on electrical generation, prices, or job flows) of the CPP will be expressed relative to a baseline estimated by the EPA regarding the likely path of these variables if the CPP is not implemented. Relative to this non-CPP baseline projection for future electricity generation, the CPP leads to an 18.6 percent decline in coal-fired electricity generation by 2020, and a 26.1 percent decline by 2030. Renewables, conversely, rise by 6.4 percent by 2020 relative to the non-CPP baseline. By 2030, however, renewable generation is just 1.7 percent above the projected baseline. Natural gas generation rises by 14.6 percent relative to the non-CPP baseline by 2020, but by 2030 actually falls 5.7 percent. Besides the decline in coal-fired generation, the most striking finding in Table 1 is the decline in total generation, which is essentially a reflection of energy efficiency investments. Relative to the baseline, total generation falls 2.8 percent by 2020 and 11.3 percent by 2030.

Table 1

The projected change in total electrical generation leads to corresponding changes in employment flows that are directly estimated by the RIA. The directly estimated employment changes by category are summarized in an appendix in Table A1. Before presenting these findings on the direct employment flows, however, it is important to be specific about how these are expressed.

Again, each employment impact is relative to what would occur in the EPA’s non-CPP baseline. Relative to this baseline, the EPA estimates a change in coal extraction in 2020, 2025, and 2030. In 2020, coal extraction employment is down 12,600 jobs relative to the non-CPP baseline. This means that employment in coal mining is lower by 12,600 jobs than would otherwise be expected in that year because of the CPP. In 2025, coal extraction employment is down 15,300 jobs relative to the baseline. This does not mean that coal-mining employment is lower by 15,300 jobs in 2025 than it was in 2020, but that the estimate is relative to that in a non-CPP world. Further, one cannot add the 2020 and 2025 estimates together and say that coal-mining employment is reduced by 27,900 in 2025 due to the CPP. One can infer that the effect of the CPP on coal-mining employment between 2020 and 2025 is a reduction of 2,700 (the difference between 15,300 and 12,600). Qualitatively, this means that the bulk of the effect of the CPP on coal-mining extraction occurs before 2020, and that the rule’s drag on coal extraction employment thereafter is less intense (although it does still grow).

Identifying the specific industries affected by the EPA employment estimates

Indirect employment effects associated with the direct employment consequences identified in the RIA lean heavily on the use of input-output (or employment requirements) matrices to identify supplier jobs associated with direct employment changes. This approach necessitates categorizing the direct employment losses identified in the RIA according to the 195 industrial sectors covered by the employment requirements matrices (ERMs) that are available from the Bureau of Labor Statistics (BLS). The EPA analysis of employment changes by economic activity detailed in Table A1 can be translated into employment changes occurring in the industrial sectors in the ERM. The exact mapping of economic activity identified by the EPA employment estimates to an industrial classification is provided in Appendix C. The outcome of this mapping is summarized in Table 2, which presents employment changes by gaining and losing industries separately for 2020, 2025, and 2030, as well as the net industry employment effects. I discuss the BLS ERM in greater detail in the next section.

Table 2

Indirect employment effects

By taking the EPA’s estimates of first-round employment changes spurred by the CPP and calculating their indirect job impacts, this paper adds to the CPP’s impact assessment. In particular, because jobs in different industries can have very different levels of indirect jobs associated with them, the EPA estimates of net job creation and displacement could be different or even change in sign from positive to negative when these indirect effects are taken into account. In this section, I estimate three separate categories of indirect job impacts that are spurred by the first-round employment changes documented in the RIA: supplier jobs, induced (or re-spending) jobs, and public-sector jobs. I label the total of these influences as the “employment multiplier.”1

Supplier jobs, materials

Supplier jobs are generally the most intuitive category of indirect employment changes. Put simply, when jobs are lost in one industry sector, the sectors that provide inputs and materials also suffer losses. Take a concrete example: When coal-mining activity shrinks, it leads to a reduction in demand for industries that provide inputs to coal mining, such as those that provide safety equipment, industrial equipment, and/or transportation equipment.

Supplier job estimates can be calculated directly from the BLS ERM. The ERM shows how many jobs are supported by $1 million in final demand in a given sector, jobs both in the sector directly satisfying the final demand as well as ones supplying inputs. For example, each $1 million in final demand for construction services supports jobs in the construction sector, but also supports jobs in concrete production, bulldozer manufacturing, and accounting services. The ERM tracks how many jobs in these supplier industries are supported by each $1 million in construction services purchased.

Because the ERM is set up in terms of dollar flows rather than job flows, translating the direct employment impacts identified by the RIA into supplier jobs requires a small manipulation. Specifically, I take the ratio of jobs supported by a given amount of spending in a sector that are supplier jobs to direct jobs, and then multiply this ratio by the number of direct jobs identified in the RIA. The estimate for supplier jobs supported by each 100 direct jobs in a given sector is calculated using the following equation: 

Supplier jobs, capital services

One weakness of the BLS ERM is that it does not account for the depreciation of capital goods (plant, equipment, and structures) that is caused by production. For very capital-intensive industries—and utilities and extraction are both notably capital-intensive—this could have nontrivial impacts on jobs supported.

To correct this, I estimate the number of jobs associated with producing the capital goods that would be needed to replace the amount of depreciation associated with 100 direct jobs in an industry. First, I estimate the value of capital services used in each industry’s production. To do this, I use data from the BLS data series on multi-factor productivity (MFP), which provides data on the capital share of output (that is, the share of income generated by each industry that goes to pay owners of capital goods rather than workers). Combining industry output with the capital share of output provides an estimate of the amount of new capital goods that must be produced each period to replace this capital service flow. Essentially, capital-intensive industries will have to spend more money to replace capital services that are used up during production. Because I begin with a given number (100) of jobs (rather than output) in each industry, calculating industry output again requires a small manipulation of the data. The first expression, in parentheses, shows how output (measured in dollars) per each 100 workers in a given industry can be calculated. This output measure is then multiplied by the capital share to give the expression for depreciation (or capital service inputs) associated with each industry.

This measure of depreciation is then used to estimate industry capital demand. Based on ratios that approximately reflect the economy-wide division of aggregate capital investment to structures versus equipment, I assume that 40 percent of this total spending flows into construction to replace new structures and that 60 percent flows into equipment manufacturing to replace machinery. From here, the formula for supplier jobs to replace the depreciation involved with every 100 direct jobs in a given industry is:

Induced (or re-spending) jobs

Another category of indirect jobs concerns those that are supported by the demand that relies on the wage and salary income of direct jobs. For example, each 100 jobs in construction also support jobs in restaurants and diners where construction workers eat, grocery stores where they shop for food, and doctors’ offices where they pay for medical services.

The scale of induced jobs supported by each 100 direct jobs depends on the overall “re-spending multiplier.” Bivens (2003) reviewed evidence on this multiplier and took 0.5 as a conservative estimate of this effect. Induced jobs also depend on the relative wages of both direct and supplier industries. As an example, if automobile assembly jobs have wages that are 50 percent higher than the economy-wide average wage, this would lead to spending induced by each 100 jobs in that sector that is 50 percent higher than the economy-wide average, making the induced spending multiplier this much higher. Further, if the supplier jobs supported by automobile assembly (steel, iron, glass, etc.) pay higher-than-average wages, then this will also increase the induced spending multiplier for the automobile assembly sector.

In this paper, I index hourly wages by industry to establish an economy-wide average of one. From here, one can express the induced jobs supported by each 100 direct jobs in an industry as simply 100 times the index of average hourly wages in the industry times 0.5 (our re-spending multiplier). For supplier jobs, I multiply the (195 industries) vector of supplier jobs associated with a given 100 jobs in the direct industry by each industry’s average hourly wage index, multiply by 0.5 (the re-spending multiplier) and then sum to estimate the induced spending from supplier jobs associated with direct employment in a given sector.

Public-sector jobs

Finally, we can estimate the number of public-sector jobs (federal, state, and local) associated with each 100 direct jobs in an industry. This measure differs across industries based on the relative wage of the industry. To generate the inputs for this calculation, I multiply each industry’s hourly wage by 2,000 to express it as a full-time, full-year salary. For federal taxes, I multiply this figure by 0.2, and for state and local taxes, by 0.1. This provides a rough measure of the tax revenue supported by each job in an industry.

I then use U.S. Census Bureau data to obtain estimates of overall tax revenue and employment in federal, state, and local governments. Dividing total tax revenue by employment, I get a measure of how much tax revenue is required to support a public-sector employee in federal versus state and local government employment. I then divide the tax revenue generated by each 100 jobs in a given industry by this per employee wage bill to get a measure of public-sector employment generated.

Summing up the indirect effects of changing industry employment

Table 3 provides a summary of the indirect effects (or employment multipliers) for each of the direct industry job flows estimated by the EPA. The largest multipliers, by a considerable margin, are in the oil and gas mining sector and the utilities (electric power) sector. Large multipliers also are found in most of the manufacturing industries that receive considerable direct job flows. The overarching effect of the job multipliers is to increase the total net employment impact spurred by the direct spending flows that are likely to occur due to the CPP in the near term. In 2020, approximately 95,000 more direct jobs are generated directly through energy efficiency investments, heat rate investments, and construction of new capacity than are displaced directly from coal plants retiring early and mining jobs being lost. Further, more than 264,000 additional jobs are generated when indirect effects are considered. However, by 2030, the estimated job gains are smaller than the direct employment flows would indicate. This is largely due to two influences: First, direct job creation in later years is expected to ebb because renewable and natural gas generation investments triggered by the CPP largely represent an acceleration of investments that would have occurred eventually even in the absence of the CPP; and second, the employment multipliers of jobs in EGUs and coal mining are large, and these sectors are projected to shed jobs even in the medium and longer terms.

Table 3

Price effects on employment

There will also be job effects stemming from the rise in electricity prices projected to result from the new rule. On average across the four scenarios (“Option 1 and 2” and “State and Regional” approaches in the RIA), the electricity price increase by 2020 will be 5 percent, and will decline to 2.7 and 2.9 percent in 2025 and 2030, respectively. Economic theory is far from settled on how the rise in a single price in the economy will affect economy-wide employment. In this section, I provide some broad parameters about the possible impacts, and then offer some evidence from simple regressions to assess the impact of electricity price changes on employment.

In order to establish some parameters to check the plausibility of regression results, assume first that the entire 5 percent increase in electricity prices leads to no reduction in electricity demand from consumers. Multiplying this 5 percent by electricity’s share in the total economy (2.4 percent)2 translates to a 0.12 percent decline in economy-wide demand for goods and services besides electricity. That is, by having to pay 5 percent more for electricity and not adjusting their demand at all, American households would have 0.12 percent less to spend on non-electricity goods and services. Given that economy-wide consumption spending in 2013 was roughly $11.5 trillion, this implies an approximate $14 billion decline in purchasing power. Given that each job in the U.S. economy is associated with roughly $140,000 in gross domestic product, this approximate $14 billion decline in purchasing power in turn translates into an estimated 100,000 jobs that would be displaced by a demand reduction of this magnitude.3

But of course, this assumption of no demand response is extremely strong. Responsiveness of consumers to energy price increases (or the elasticity of demand for electricity) may be relatively low in the short run, but is expected to be greater than zero, and there is strong evidence that it rises sharply over time (see Maddala et al. 1997.)

A strong assumption in the opposite direction, that a 5 percent increase in the price of electricity would be met immediately by a 5 percent reduction in demand for electricity (implying an elasticity of demand of one), would suggest that there would be no overall demand effect stemming from reduced consumer spending; consumers would simply shift their spending away from electricity and toward other goods and services.

This thought experiment helps to establish some parameters for what a reasonable estimate of the employment response to an electricity price increase should be based simply on consumers’ responses. Given that consumer spending is two-thirds of the U.S. economy, the employment response due to changes in consumer spending is expected to be a large part of the total employment effects.4 Any estimates of job declines that are much larger than the high end of these rough benchmarks essentially need to be accompanied by a compelling theoretical reason for why so they are so large, since the high end of mechanical effects of higher electricity prices “crowding out” spending on other goods seems well-defined for price increases of 5 percent or less.

Regression analysis

In this section, I undertake two methods of regression analysis to assess the impact of higher electricity prices on overall employment. First, I use a vector autoregression of total nonfarm payroll employment on changes in electricity prices (following Killian 2008). By ordering electricity prices first, and making the assumption that employment changes in a given month do not affect electricity price changes in that same month, the results can be interpreted as the causal effect of electricity price changes on employment. Second, I assemble a panel dataset of states from 1976 to 2013 to test how changes in electricity prices correlate with employment changes. For this set of regressions, I follow Deschenes (2012).

Vector autoregression estimates

For the vector autoregression test, I use data on nonfarm payroll employment and electricity price data from the consumer price index (CPI), both from the BLS. I run a vector autoregression with electricity prices ordered first. To assess the effect of higher electricity prices on employment, I simulate the effect of an electricity price shock. Figure A shows the results of this “impulse response function,” showing how employment responds to a one standard deviation shock to electricity prices.

Figure A

The data show a clear pattern of a quick decline in employment that converges back toward zero effect. The magnitudes (.015 percent, multiplied by the 2014 work force of roughly 140 million) suggest an employment decline of nearly 20,000 (0.015 percent, as indicated on the figure) after three to five months, and then a fadeout of more than 90 percent of the effect within a year (with the remaining negative effect no longer statistically significant). A one standard deviation shock to electricity prices in this data is 4 percent, so I multiply the employment decline from the impulse response function by five fourths to estimate the employment impact of a 5 percent increase in electricity prices generated by the CPP, giving a final point estimate of 25,000 jobs displaced by higher electricity prices.

State panel regressions

The state/year panel results are summarized in Appendix Table A4. This table shows the results of a regression that uses the log of the level of state employment on the log of electricity prices across states. The employment data come from the BLS, while state-level electricity price data come from the State Energy Data Service (SEDS). This electricity price used is the average retail price for all end-users in each year between 1979 and 2012.

The preferred specification is shown in column 3 of Table A4, which controls for time and year fixed effects, state-level time trends, and the unemployment gap (which is important to include as it seems to be absorbing some employment variation not controlled for in the state, year, and time-trend dummy variables). The data cover the period from 1979 to 2012. For this specification, the coefficient of employment on energy prices is -0.017. This implies that a 10 percent change in electricity prices reduces employment by 0.17 percent, or that a 5 percent increase in electricity prices (as forecast by the CPP RIA) will reduce employment by 0.085 percent, or by just under 100,000 jobs.

As noted by Deschenes (2012), this is best interpreted as the short-run effect on employment of unanticipated increases in electricity prices. Electricity price changes that are fully expected and take some time before implementation are expected to be significantly smaller.

Greater losses result if the sample is cut off in 2008 (as is done in columns 4 to 6 of Table A4). Here, the coefficient estimates suggest job losses of more than 150,000 in the specification (column 6) that includes all other controls. It is unclear why including the latest five years of data changes the results to such a great extent, but it is regarded as more robust to proceed by including more data rather than less.

Finally, regressions that used state/industry cells as the unit of analysis are reported. The employment data let us examine 13 separate industrial sectors within states. Despite the larger sample size, the overall coefficient on state/industry employment in this larger panel never achieved statistical significance. Later sections focus just on manufacturing employment across states and do find significant and disproportionate job losses in this sector that are correlated with electricity price differences.

Combining the VAR and state-panel regression results

The two different regression techniques provide results that span most of the plausible variation identified in the introduction to this section. The results range from 20,000 to 100,000 in the preferred specifications, with 150,000 in the panel regression with the time period truncated in 2008.

Lacking any better alternative, I average the results provided by each method to establish the point estimate of the employment impact of higher energy prices. This method gives a net decrease of 75,000 jobs (the average of 25,000 and 125,000). Further, given the sharp fadeout of negative employment impacts in the vector autoregression, the interpretation of state panel regression results as measuring the responsiveness of employment to unanticipated short-run electricity price changes, and the evidence that the long-run elasticity of demand with respect to electricity prices is much larger than the short-run elasticity, I can only be confident about these negative price effects for the first year examined in the RIA–2020.

Total net employment impacts

Table 4 provides the final tally on employment impacts, showing gross gains and gross losses by each employment channel: direct effects, indirect effects, and price effects, in 2020, 2025, and 2030.

The negative price effects are not large enough to swamp the positive net effect of tallying the direct and indirect job flows. The key driver of these positive net effects is the large increase in energy efficiency investments. These investments are large in direct scale (accounting for more than half of the total direct gross gains in 2020, and accounting for essentially all of the gross gains in 2025 and 2030), and also tend to have higher than average employment multipliers. These energy efficiency investments also implicitly drive a large part of the generation response, as an overall decline in electricity use of roughly 11 percent is spurred by the rule relative to the non-CPP baseline in 2035.

In 2020, net employment changes resulting from the rule total to an employment gain of more than 285,000 jobs. This net gain drops off rapidly in 2025 and 2030 but remains positive, assuming that price effects are no longer significantly affecting employment in 2025 and 2030.

Table 4

Sensitivity check on energy efficiency jobs and full-time equivalents

The EPA RIA’s estimates of jobs supported by energy efficiency investments include a caution that these are not expressed as full-time equivalents, while the other direct job flows are. This could potentially skew upward the estimate of jobs supported through these investments. My primary estimate of employment changes has not adjusted the overall numbers for this caution, mostly because the gap between total employment and full-time equivalent employment in sectors heavily represented in energy efficiency investments (mostly manufacturing and construction) is very small. However, I did experiment with adjusting the jobs supported by energy efficiency investments downward by the economy-wide ratio of full-time equivalents to overall employment, with the results shown in Appendix Table A5. This adjustment leads to a roughly 10 percent reduction in jobs supported by energy efficiency investments, which in turn leads to direct and indirect job gains in 2020 falling to approximately 330,000 (down from 360,000 reported in earlier results), and leads to small net job losses in these categories by 2030 (less than 15,000).

It is worth noting that in a well-functioning economy (i.e., one without substantial degrees of economic slack and one no longer stuck in the liquidity trap that has characterized much of the past six years in the American economy), any significant impact on economy-wide employment—either positive or negative—would likely be met by a countervailing response from the Federal Reserve. In a sense, the Fed’s job is precisely to make sure that the economy-wide employment response to any shock like the CPP is zero. However, the Fed’s countervailing response may be imperfect, and it is useful to know the direction in which the Fed will have to push the economy following the implementation of the CPP. And, as I will explain, the geographic distribution of gains and losses means that even if the Fed were to fully neutralize the national employment impacts of the CPP, impacts that differ across regions would remain.

Comparison of job composition of gaining versus losing industries

In addition to changes in employment levels, policymakers may also be interested in changes in the composition of jobs spurred by labor market responses to the CPP. This section combines information from the BLS ERM and demographic and labor market data from the Current Population Survey (CPS) to predict the characteristics of workers that will populate the jobs either displaced or created by the CPP.

I use the CPS to estimate the share of each industry’s workforce by gender, race, educational attainment, union status, and wage level. I then multiply these shares by the total number of jobs displaced or created by the CPP. I present the results separately for gaining and losing industries in Tables 5 and 6.

The broad summary of differences in job composition between gaining and losing industries can be summarized briefly: Losing industries tend to have fewer workers with a four-year college degree or more education (20.8 percent versus 29.8 percent in gaining industries) and yet have fewer low-wage and more middle-wage jobs. This is likely in part because jobs in Iosing industries are significantly more unionized than in gaining industries (19.8 percent versus 9.0 percent). Jobs in both gaining and losing industries have higher shares of male workers and white workers than economy-wide averages.

Table 5

Table 6

Specific challenges posed by transition from losing industries

These indicators of job quality highlight some of the key challenges in managing the labor market transitions that are likely to result from the CPP. Specifically, workers displaced by the CPP will tend to have less formal credentials than economy-wide averages and also skew older. Both of these characteristics correlate with lower re-employment probabilities and lower quality jobs when alternative employment is secured (Sum et al. 2011). Further, because jobs in losing industries pay higher than average wages even for a workforce that has fewer formal educational credentials, the expected wage loss from displacement from these industries is expected to be higher.

Another transition issue comes from the disproportionate impact of job losses due to price effects on energy-intensive, trade-exposed industries. As Figure B shows, there are a small number of manufacturing industries that have significantly higher energy cost shares than others, and so these industries may see a significant decline in their international competitive position if domestic policy (i.e., the CPP) were to make electricity significantly more expensive for them relative to the global competition.

Figure B

I first examine whether manufacturing overall bears a disproportionate share of job losses stemming from price increases. Appendix Table A6 shows the results of the state/panel regressions examined earlier, but now with manufacturing employment as the dependent variable. In the preferred specification (column 2), the coefficient on electricity prices is larger than for overall employment (0.03 versus 0.017) and is statistically significant. Applying this coefficient result to the expected price change resulting from the CPP implies manufacturing job loss of roughly 20,000, or about one-fifth of the entire predicted job losses due to higher prices. Manufacturing employment is far below 10 percent of total employment, so this is clearly a disproportionate effect.

While manufacturing overall bears a disproportionate burden from price increases, this still leaves open the question of how much of this burden stems from eroded international competitiveness. Aldy and Pizer (2014) recently studied how much of output and employment declines stemming from increasing energy prices is the result of declining international competitiveness. Their results for overall manufacturing, as well as for some particularly energy-intensive sectors, are shown in Figure C. For particularly energy-intensive industries, about one-fifth of the entire output and employment decline stemming from higher energy prices is due to an eroded position in international markets.

Figure C

Figure D highlights another concern related to transition challenges posed by the CPP. The drivers of job displacements in our analysis are the closure of coal-fired EGUs and the reduction in coal mining. Figure D adds together state employment in mining and a rough estimate of state employment in coal-fired EGUs and divides by total employment in the state, to gain a measure that can be thought of as potential exposure to job losses from the CPP.4 It then plots this measure of potential exposure to job losses against each state’s average per capita personal income. The key finding is that potential exposure to job displacements caused by the CPP seems likely to occur disproportionately in poorer states, which could hence have greater trouble finding resources to deal with the needed transitions. Because of this issue, and because the benefits of mitigating carbon emissions are national (indeed, global), this seems like a strong basis for federal policymakers to act to provide relief for states and communities that will have the largest necessary adjustments stemming from the CPP.

Figure D

Transition policies

President Obama’s fiscal year 2016 budget proposal includes support for managing the transition to the CPP. This proposal—so far unapproved—included a new $4 billion fund to encourage states to make faster and deeper cuts to emissions from power plants and an additional $2 billion tax credit for power plants that capture their carbon dioxide. These recommended financial supports indicate that the administration acknowledges that a key downside to addressing greenhouse gas mitigation through regulation rather than legislation is that it has the potential to create market distortions that may require additional intervention. A legislative solution would have provided the opportunity to bundle job-creating investments and transition assistance as a combined policy package that would raise the cost of fossil fuel energy production and trigger displacements from “dirty” to “clean” power. The regulatory approach does not offer that same opportunity. The legislative defeat of greenhouse gas mitigation approaches in 2009 made the regulatory track the only available option, and so it is vital that policymakers concerned about jobs and incomes take steps to blunt any economic harm caused by job displacements spurred by the CPP.

There are many such steps that could be taken. Possibly the most important includes ensuring the viability of the health and pensions funds of coal companies. Many retirees rely on this income, and they should not be punished for policy changes that make company pension obligations untenable. Currently the United Mine Workers (UMW) multi-employer pension fund is roughly $1 billion short of being in actuarial balance, driven predominantly by the rapid shrinkage of the current workforce relative to retirees. Another significant blow to the level of the current workforce could be disastrous for the pension fund. The Obama administration’s fiscal year 2016 budget includes transfers to the UMW pension fund through the Pension Benefits Guaranty Corporation to insure the solvency of the plan. The fiscal year 2016 budget also boosts transfers to health plans administered by the UMW to insure their viability.

Another set of tools would aim to ameliorate the decline in industrial competitiveness that could accompany the rule. For example, if other countries undertook measures to raise the price of carbon emissions, this would stem the competitiveness loss. Signing international agreements that raise the cost of greenhouse gas emissions would be an effective policy tool to mitigate the negative effects of labor market transitions stemming from the rule (and would further make the rule more effective in reducing global emissions by stopping carbon-intensive production from simply “leaking” abroad to other countries that do not regulate or price emissions). Until such an international agreement is reached, the United States could unilaterally impose a “border-adjustment” tariff based on the carbon-intensity of the production of imports. Such a tariff would make the global reduction in emissions stemming from the rule larger, would blunt the employment dislocation in the United States caused by the rule, and is in fact necessary for preserving the principle of nondiscrimination in trade relationships.

Conclusion

The CPP is the largest U.S. undertaking to date aimed at mitigating the effects of global climate change. Given the vast importance of global climate change, this means that the impact of the CPP on economic, health, and environmental outcomes is likely to be quite large—and this is indeed what the EPA’s own impact analysis of the CPP shows. Yet much debate about the CPP (and indeed, about nearly all environmental regulations) has focused on the narrower issue of employment changes spurred by the proposed rule. Economic theory suggests that such employment changes are likely to be modest (see Goodstein 1997 and Bivens 2011). This paper offers a comprehensive account of the economic channels through which the rule’s effects could alter U.S. employment. It finds that these effects are relatively modest in the near term, and are more likely to provide a small net boost in employment by 2020. After this date, the net impacts of the rule on employment converge quickly to zero—becoming almost completely insignificant by 2030.

While the proposed rule’s effect on employment levels is small (and positive), the concentration of job dislocations and the composition of jobs in the losing industries suggest that policymakers should consider complementary policies to adjust and to blunt some of the less desirable outcomes of the rule. The clearest virtue to addressing climate change and greenhouse gas emissions through legislation is precisely that such complementary policies can be bundled together with the mechanisms that reduce emissions. This virtue does not accompany the current efforts to limit greenhouse gas emissions through regulation. While a regulatory approach can be effective in achieving the primary target of reducing greenhouse gas emissions, it needs to be supported by policies that will ensure that groups of workers and communities bearing a disproportionate burden of adjustment are fairly compensated.

About the author

Josh Bivens joined the Economic Policy Institute in 2002 and is currently the director of research and policy. His primary areas of research include mac­roeconomics, social insurance, and globalization. He has authored or co-authored three books (including The State of Working America, 12th Edition) while working at EPI, edited another, and has written numerous research papers, including for academic journals. He appears often in media outlets to offer eco­nomic commentary and has testified several times before the U.S. Congress. He earned his Ph.D. from The New School for Social Research.

Endnotes

1. The employment multipliers for all 195 industries are available upon request.

2. Electricity’s share in the total economy is based on data from 2013 using data collected by the Bureau of Economic Analysis (BEA).

3. For translating changes in spending flows and gross domestic product (GDP) into jobs, see Bivens (2011).

4. The labor supply effects of such an electricity price increase are likely to be considerably smaller. The 5 percent increase in electricity prices represents roughly a 0.12 percent reduction in real wages. Typical labor supply elasticities range from 0.1 to 0.3, so this implies a 0.0036 percent reduction in labor supply at most, or roughly 5,400 fewer jobs stemming from workers’ voluntary labor supply decisions.

5. For the estimate of employment in EGUs by state, we allocate nationwide employment in coal-fired plants by each state’s share of national coal-fired electrical generation, using data from the U.S. Energy Information Association (EIA).

 References

Aldy, Joseph, and William Pizer. 2014. The Competitiveness Impacts of Climate Change Mitigation Policies. Working paper, March 2014 draft.

Bivens, Josh. 2003. Updated Employment Multipliers for the US Economy. EPI Working Paper No. 268.

Bivens, Josh. 2011. A Life-Saver, Not a Job-Killer: EPA’s Proposed ‘Air Toxics Rule’ Is No Threat to Job Growth. EPI Briefing Paper No. 312.

Bureau of Labor Statistics (U.S. Department of Labor) Employment Requirements Matrix. 2012. “Historical Employment Requirements Tables, 1993–2012.”

Bureau of Labor Statistics (U.S. Department of Labor) Current Employment Statistics program. Various years. Employment, Hours and Earnings—National [database].

Bureau of Labor Statistics (U.S. Department of Labor) Multifactor Productivity program. Various years. Multifactor Industry Productivity [database].

Bureau of Labor Statistics (U.S. Department of Labor) Consumer Price Indexes program. Various years. All Urban Consumers: Chained Consumer Price Index (CPI) [database].

Current Population Survey public data series. Various years. Aggregate data from basic monthly CPS microdata are available from the Bureau of Labor Statistics through three primary channels: as Historical ‘A’ Tables released with the BLS Employment Situation Summary, through the Labor Force Statistics Including the National Unemployment Rate database, and through series reports.

Deschenes, Olivier. 2012. “Climate Policy and Labor Markets” in The Design and Implementation of US Climate Policy, Don Fullerton and Catherine Wolfram, eds. Chicago: University of Chicago Press.

Electric Power Research Institute. 2014. US Energy Efficiency Potential Through 2035.

Environmental Protection Agency (EPA). 2014. Regulatory Impact Analysis for the Proposed Carbon Pollution Guidelines for Existing Power Plants and Emission Standards for Modified and Reconstructed Power Plants.

Goodstein, Eban. 1997. Jobs and the Environment: The Myth of a National Trade-Off. Economic Policy Institute.

Killian, Lutz. 2008. “The Economic Effects of Energy Price Shocks.” Journal of Economic Literature, volume 46(4), 871-909.

Maddala, G. S., R.P. Trost, H. Li, and F. Joutz. 1997. “Estimation of Short-run and Long-run Elasticities of Energy Demand from Panel Data Using Shrinkage Estimators.” Journal of Business & Economic Statistics, 15(1), 90-100.

National Bureau of Economic Research (NBER). 2013. NBER-CES Manufacturing Industry Database.

Pollin, Robert, James Heintz and Heidi Garrett-Peltier. 2009. The Economic Benefits of Investing in Clean Energy: How the economic stimulus program and new legislation can boost US economic growth and employment. Report jointly released by the Political Economic Research Institute and the Center for American Progress.

Sum, Andrew, and Myrkhaylo Trubskyy, Ishwar Khatiwada, Joseph McLaughlin, and Sheila Palma. 2011. The Job Dislocation and Re-employment Experiences of America’s Older Workers During the Great Recessionary Period of 2007-2009: The Economic Consequences for the Dislocated and the Rest of Society. Center for Labor Market Studies report prepared for Senior Service America

U.S Energy Information Administration (EIA) – Independent Statistics and Analysis. Various Years. State Energy Data System (SEDS) [databases].

Wei, Max, Shana Patadia, and Daniel M. Kammen. 2010. “Putting Renewables and Energy Efficiency to Work: How Many Jobs Can the Clean Energy Industry Generate in the US?” Energy Policy 38, no. 2: 919-931.

Appendix A: EPA estimates of job changes by activity

Table A1 reports directly the EPA estimates of employment change by activity spurred by the CPP. It breaks out these employment changes by three different employment flows:  (1) construction of new EGUs and heat rate improvements to existing EGUs and energy efficiency investments; (2) operation and maintenance (O&M) employment in the electrical power generating sector; and (3) extraction of fossil fuels. As with Table 1 in the main text, the employment flows shown in Table A1 average the four different estimates provided in the RIA (state versus regional and option 1 versus option 2).

Table A1 provides the averaged estimates for each employment flow (O&M, construction, and extraction) in each year examined by the RIA (2020, 2025, and 2030). In 2020, construction of natural gas generating capacity increases, as does renewable generation, heat-rate improvement investments, and energy efficiency investments. The sum of this short-run construction activity is 123,000 additional jobs relative to the baseline. In later years, however, this pulling forward of natural gas and renewable construction actually depresses construction employment (relative to the baseline) in 2025 and 2030. Energy efficiency investments, conversely, continue to grow through 2030, though at a slower pace.

The large negative impact of the CPP on coal-sector employment is obvious in O&M employment. O&M employment in coal-fired EGUs falls by nearly 20,000 by 2020, and stays about that depressed relative to the baseline all the way through 2030. This is obviously consistent with the significant decline in coal-fired generation identified in Table 1. In the near term, natural gas O&M employment rises, while O&M employment in oil and gas plants falls. Over longer horizons, O&M employment in all fossil fuel generation (including natural gas) falls relative to the baseline. In 2020, the sum total of O&M employment losses is just under 20,000, rising to roughly 24,000 by 2030.

Losses in coal extraction are large and significant in all three years—12,600 in 2020 and rising to 17,300 by 2030. Natural gas extraction employment actually rises slightly in the near term—increasing by 5,050 in 2020 but then falling. By 2030, it is 2,000 jobs lower than the baseline. Again, the CPP pulls forward natural gas-related jobs and leaves them lower in later years.

Table A1

Appendix B: Consistency check on EPA employment estimates

The information provided in the RIA and summarized in Tables 1 and 2 allows us to undertake a quick consistency check to see if the numbers seem to be in concordance with what employment and generation estimates from other sources indicate. Specifically, from Table 1, we see that coal-fired generation falls by nearly 20 percent by 2020. Coal EGU O&M employment falls by 19,400, according to Table A1.

Table A2 combines data from the Bureau of Labor Statistics (BLS) Current Employment Statistics (CES) and the Energy Information Agency (EIA) to provide a consistency check on these estimates. The BLS CES data indicate that all fossil fuel–generated electrical utility activity in 2013 generated 100,000 jobs. The EIA data indicate that coal-fired EGUS generated a bit under two-thirds of all fossil fuel-generated electricity in 2013. So, if employment fell in strict proportion to generation, this would imply that a 20 percent reduction in coal-fired generation should only see employment losses of roughly 12,000–14,000 jobs. The fact that the CPP RIA instead forecasts losses of nearly 20,000 jobs due to the 20 percent reduction in coal-fired generation implies that coal-fired EGUs—or at least those coal-fired EGUs that are likely to close in response to the CPP—are more labor-intensive than other fossil fuel-generated EGUs.

This same logic holds in reverse for the short-term changes in natural gas generation. The RIA indicates that natural gas-fired EGU generation increases by 15 percent by 2020. EIA estimates indicate that natural gas is roughly one-third of all fossil fuel-generated electricity; so, if employment were to rise in proportion to generation, this would imply an increase in natural gas O&M employment of roughly 5,000 in 2020. The fact that the CPP RIA only forecasts an increase of 2,000 jobs in natural gas O&M indicates that natural gas—or at least the natural gas generation that increases due to the CPP—is less labor intensive than overall fossil fuel generation.

This implicit finding that coal-fired EGU generation is more labor intensive is largely in line with other data. The EIA data show that levelized costs for fixed O&M (which is largely dominated by labor costs) is higher for coal-fired EGUs than for (most) natural gas EGUs. And Wei, Patadia, and Kammen (2010) show that while fixed O&M employment in both coal and natural gas-fired plants is low compared with other forms of generation, coal O&M employment (per unit of generation) is higher than for natural gas.

In short, the data on generation and direct employment impacts from the CPP RIA seem to be roughly plausible (the employment losses/gains are clearly of the same order of magnitude and quite close to overall generation losses/gains), and the implicit relative rankings of labor intensity match other data.

Table A2

Appendix C: Mapping EPA employment estimates into specific industries

Table A3 maps the employment changes by economic activity identified in Table A1 for specific industries that we can use to identify indirect impacts. Many of the employment changes identified in Table A1 are quite straightforward to slot into ERM industries. Coal mining job losses enter into ERM industry code 8—Coal Mining. Natural gas extraction gains (in 2020) and subsequent losses (in 2025 and 2030) enter into ERM code 7—Oil and Gas mining. O&M employment changes (both positive and negative) unfortunately (for the sake of precision) all have to be placed in the same ERM industry classification, 12—electric power utilities.

Slightly more complex decisions must be made to determine which industries are the direct recipients of employment flows due to other effects. Energy efficiency, for example, is not the name of a single industry sector in the ERM. To apportion changes due to energy efficiency investments, we used the data provided by the Electric Power Research Institute (EPRI 2014). EPRI estimates the areas with the highest potential for achieving energy efficiency savings in the residential, commercial, and industry sectors. We used the EPRI estimates of potential savings as weights to apportion the spending flow of investments in energy efficiency. For example, in its estimates for the residential sector, EPRI highlights the highest potential savings from the following categories: space cooling, electronics, water heating, lighting, and household appliances. EPRI provides similar estimates for the commercial and industrial sectors. These categories match tightly to existing ERM categories, and I assume that these flows will be proportional to the amount of energy savings achieved through these investments estimated in the EPRI report. If, for example, lighting accounts for 15 percent of energy savings in the residential sector, I apportion 15 percent of employment gains spurred by energy efficiency investments to the sector in the ERM that best approximates this (electrical lighting equipment).

For apportioning employment flows stemming from investments in electricity generation from renewable sources, we drew on estimates from Pollin, Heintz, and Garrett-Peltier (2009), who undertake a detailed analysis of job creation stemming from clean energy production and provide a mapping of industrial spending associated with investment in renewable energy, based on surveys with industry professionals. We used these mappings to assign direct employment flows stemming from renewable generation construction. Both solar and wind generation require construction employment as the single largest input. The remaining inputs constitute a mix of manufactured goods and technical services, as shown in Table A3.

For apportioning employment flows to ERM industry that occur due to construction of natural gas capacity, we assume that one-third of such flows go to construction jobs, one-third to manufacturing of transmission equipment, and one-sixth each to design services and fabricated metals.

Finally, for heat-rate improvements at existing EGUs, we assign the employment flows equally between EGU O&M jobs, ventilation and cooling equipment, power transmission equipment, and scientific and technical services.

Table A3

Appendix D: State by year panel regressions of electricity prices and employment

Table A4 shows the results of a panel regression with the log of state employment as the dependent variable and the log of end-user electricity prices (and other relevant controls) as the independent variables.

Column 1 shows the results from this regression with year and state fixed effects included. Column 2 includes a state-specific time trend. Column 3 includes a measure of the unemployment gap—the difference between a state’s unemployment rate in a given year and the average unemployment rate for that state over the entire sample period.

We note that higher results are gained if one cuts off the sample in 2008 (as is done in columns 4-6), with the coefficient estimates suggesting job losses of over 150,000 in the specification (column 6) that includes all other controls. It is unclear why including the most recent five years of data changes the results so much, but we prefer to include more data rather than less.

Finally, we also ran regressions that used state/industry cells as the unit of analysis. The employment data let us examine 13 separate industrial sectors within states. Despite the larger sample size, the overall coefficient on state/industry employment in this larger panel never achieved statistical significance. Later sections look just at manufacturing employment across states and do find significant and disproportionate job losses in this sector that are correlated with electricity price differences.

Tables A5 and A6 show the employment impacts of higher energy prices and of energy efficient investments adjusted on an economy-wide full-time equivalent basis.

Table A4

Table A5

Table A6

If the monetized benefits and costs of these 11 individual rules are tabulated (hereafter referred to as the “Obama EPA rules”), the results are strikingly positive. As the table at the end of this post indicates:

• The benefits of the finalized Obama EPA rules are valued at $98 billion a year (all figures in 2010 dollars).  Most of the benefits come from saving lives and other health benefits, but also include economic benefits such as reduced fuel expenditures by consumers or increased worker productivity.
• The compliance costs of the Obama EPA rules amount to just $8.3 billion a year, or far below one one-thousandth of the economy.
• The net benefits from these rules is $90 billion a year. The ratio between benefits and costs is 12-to-1.
• Using methodology I wrote up previously, I estimate the economic benefits from the joint EPA/DOT rules alone, connected to fuel efficiency and greenhouse gas standards for cars, amount to about $13 billion a year, or more than the compliance costs for all 11 Obama EPA rules.

Since the OMB report is designed to cover data only through the end of the previous fiscal year, it does not include EPA’s “air toxics” rule that was finalized on Dec. 16, 2011. This rule has significant compliance costs, amounting to $10 billion a year, but much larger benefits, amounting to $64 billion a year (using the midpoint of the benefit range). Combining this rule with the rules in the OMB report, the benefits of Obama EPA rules finalized to date amount to $162 billion a year, compared to compliance costs of $18.3 billion a year (about one one-thousandth of the economy). The net benefit figure for this combination of EPA rules is $144 billion a year.

Cost-benefit data should not be considered precise, and there are many complexities to such analysis that have not been fully addressed (such as many benefits are not monetized). Nonetheless, the magnitude of the net benefits of the Obama EPA rules shown by this data indicates that they are likely to be of much value to the nation.

The cost and other data on the final rule that have been released differ little from information available about the proposed rule.  It is thus very unlikely that the final Regulatory Impact Analysis (RIA) describing the expected impacts of the final rule will differ significantly from the proposed Regulatory Impact Analysis and other information released with the proposed rule in March of this year. This information makes clear that with benefits exceeding costs by at least 5-to-1, the rule is well worth doing – with up to 17,000 lives saved per year after its implementation and 850,000 additional days of work added to the economy because workers are healthier and would require fewer sick days.

Opponents of the act predictably characterized the air toxics rule as a “job-killer.” Even normall,y this is pretty bad economics – no serious economist thinks that regulatory changes on the scale of the air toxics rule have non-trivial impacts on national job growth. And during times like now – with the economy mired in a “liquidity trap” (very large amounts of productive slack persist even as short-term interest rates are stuck at zero) – this is completely upside-down economics. In today’s circumstances (with very high rates of unemployment) the jobs directly created by the need to install pollution abatement and control technologies will almost surely not be offset by rising interest rates or prices, as could happen if these regulations took effect in an economy with no productive slack.

Our own earlier research, based on the information provided with the proposed rule, indicated that it would lead to roughly 92,000 net new jobs by 2015. The nature of this estimate is likely to apply to the final rule as well. To be clear, this rule isn’t a significant jobs policy that would put a large dent in the current unemployment crisis. But, it is a very valuable rule that would only push in the correct direction in the labor market.

We will re-examine the job impacts of the final rule when full information is available.

This can be demonstrated by looking at the economic benefits of just two of the rules finalized so far by EPA.  These are joint rules with the Department of Transportation that regulate greenhouse gas emissions from, and establish fuel standards for, various-size vehicles for model years 2012-2016.  The economic benefits from these two rules are particularly sizable, as they produce large savings to drivers in the form of reduced expenditures on gasoline.

In 2010 dollars, a conservative estimate (see explanation below) of the economic benefits from these two rules amounts to $6 billion to $20.6 billion a year.  This range is above the range of estimated compliance costs for all 11 major rules finalized so far by the Obama EPA; that range is $5.9 billion to $12 billion a year.  Even if the four major proposed rules are also taken into account, the economic benefits from the fuel standard rules alone offset much of the combined costs of the final and proposed rules ($19.7 billion to $27 billion a year).

Stated simply, the economic benefits of just two of the major Obama EPA rules offset much of the economic compliance costs of all the rules.  It also bears noting that companies have several years or more to comply with the rules, diminishing immediate costs and facilitating transitions.  Further, an array of economic benefits is not considered here, including the economic benefits from the other nine final rules and the four proposed rules; these economic benefits range from workers spending more time at their jobs because they or their children are healthier to reduced expenditures on health care.  The modest employment gains from the largest rule, the air toxics rule, are also not considered; these gains reflect the fact that compliance expenditures generate jobs when the economy has substantial unused capacity.

So especially once offsetting economic benefits are considered, it is hard to conceive how the EPA rules advanced so far during the Obama administration could drag down the overall economy.

What is conceivable, and indisputable, is that the health benefits from these rules are large.  Every year, the cleaner air and other environmental benefits from the rules will save tens of thousands of lives, prevent tens of thousands of heart attacks, and mean hundreds of thousands fewer people will contract respiratory illnesses, thereby diminishing hospital stays.  When all benefits, including health benefits, are considered, the benefits from the rules dwarf any compliance costs.

Note:  Explanation of calculation.  For the two rules that raise fuel standards for, and reduce greenhouse gas emissions from, various-sized vehicles, this blog considers the following benefits as economic:  reductions in fuel expenditures, the value of time savings from needing to refuel less often, and the value of the decreased chance of economic disruption due to reduced dependence on foreign oil.  The costs of time lost due to increased congestion (due to more driving since fuel costs less) and the costs of increased crashes (also reflecting more driving) are considered economic losses.  The additional value drivers attach to driving more are not considered economic, nor are the costs assigned to increased traffic noise (reflecting more driving).  The method is conservative because due to technical obstacles, no economic benefits are attached to reducing carbon dioxide or other emissions.  Additionally, the health benefits from these rules, which EPA calculated for 2030 and did not annualize, are not included in the calculation.