Because powerful government policy segregated us, racial boundaries violate the fifth, 13th, and 14th amendments. Our nation thus has a positive constitutional obligation to redress segregation with policies as intentional as those that segregated us.

The federal government made housing and homeownership critical to families’ economic stability and upward mobility. But we routinely excluded African Americans from government benefits that propelled whites into the middle class.

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Key takeaways:

• We need new narratives around Black economic disadvantage.
• In today’s heightened public awareness of racial inequalities, the ways we talk about racial economic disparities shape the solutions we develop for those disparities—and whether we consider disparities as problems worth solving at all.
• Americans have historically had a tendency to individualize both successes and failures—that is, to look at groups of individuals and assume their outcomes are just the combined result of individual decisions, something known as “methodological individualism.” It fails to account for the ways that structural features of the U.S. economy narrow the options for Black workers and their families.
• In this blog post, I offer tools for gaining the deeper understanding of statistics that allow us to actually tackle the problems of inequity with impactful solutions instead of explaining them away.

Black workers disproportionately experienced the darkest side of 2020, both in terms of health and labor market outcomes—a reality that was not unexpected.

Researchers, advocates, and activists have spent years pointing out that Black Americans are more likely to have the health conditions that significantly increase the mortality rate of COVID-19 infection. We have known for years that Black American households have a fraction of the wealth that white American households do, meaning that in the event of an economic shock they would be less resilient, more likely to default on loans, and unable to draw upon savings to pay rent, possibly leading to evictions.

The last 50 years of labor market data have given us two recognizable facts:

1. The Black unemployment rate is consistently around double the white unemployment rate under normal economic conditions.
2. Black workers find employment more slowly, especially in the wake of an economic downturn.

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Today, the Bureau of Labor Statistics (BLS) reported that the overall consumer price index (CPI) in March 2021 was 2.6% higher than in March 2020, while the “core” measure of the CPI (which excludes volatile food and energy prices) was 1.6% higher than a year ago. Given that these are noticeable (if modest) increases over recent months’ year-over-year inflation rates, some might be tempted to argue that this data should make policymakers worry about economic “overheating” stemming from “too much” fiscal support provided in recent recovery legislation. This is clearly wrong, for a number of reasons:

• The data released today do not show that prices have risen rapidly since recovery legislation passed—instead they just show that prices plummeted during the near-total shutdown of large swaths of the economy a year ago in response to the COVID-19 shock.
  • Measured on an annualized basis from February 2020—before the COVID-19 economic shock—inflation in March 2021 was running at just 1.5%.
  • Measured since October—shortly before the $2.8 trillion in additional relief spending provided by legislation in December 2020 and the American Rescue Plan (ARP) in March—inflation is running at an annualized rate of 1.3%.

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• The bulk of these tax provisions undo some of the worst parts of the Tax Cuts and Jobs Act (TCJA) passed in the first year of the Trump administration. Given this, to make the case that rolling back these parts of the TCJA will harm the U.S. economy, one has to believe that the passage of the TCJA benefited the U.S. economy. There is no evidence this is the case.
• The entire case for corporate tax cuts benefiting the U.S. economy hinges on the effects on business investment. But business investment growth in the two years following the TCJA’s passage (even before the COVID-19 shock) was cratering, not rising.
• The vast majority of new revenue that will be raised from the AJP tax provisions will come from taxing “excess profits”—profits accrued by virtue of monopoly or other privileged market positions. As such, this extra revenue will have little to no effect on economic decision-making and hence will not reduce business investment or economic growth more generally.
• Two “model-based” analyses of the AJP find very different things: Moody’s Analytics forecasts strong positive effects on economic growth over the next 10 years, while the Penn Wharton Budget Model forecasts very slight negative growth effects by 2030. The finding that the AJP might reduce economic growth rests on a number of bad assumptions: that the corporate tax changes will significantly affect economic decision-making and reduce investment; that the productivity gains stemming from public investment are small; that budget deficits will crowd out large amounts of private capital formation over the next decade; and that AJP’s care investments will reduce labor supply. None of these assumptions are likely to be correct.

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In 1979, 27.0% of workers were covered by union contracts. By 2019, that number had dropped to 11.6%. New research finds that this single factor dragged down the typical full-time workers’ wages by over $3,000/year.

Recent research on trends in wages over the last four decades has demonstrated that:

• For the “typical” or median worker, declining unionization translates to a loss of $1.56 per hour worked, the equivalent of $3,250 for a full-time, full-year worker. The erosion of collective bargaining lowered the median hourly wage by $1.56, a 7.9% decline (0.2% annually), from 1979 to 2017. Deunionization lowered the male median hourly wage by $2.49, an 11.6% (0.29% annual) decline, over the 1979–2017 period. These losses from deunionization are the equivalent of annual losses for a full-time, full-year median worker and median male worker, respectively, of $3,250 and $5,171. This impact is due to both the direct effect on wages of union workers and the spillover effect on wages of nonunion workers.
• Declining unionization widened inequality between high-wage earners and middle-wage earners. Deunionization widened the 90/50 wage gap (the gap between earners at the 90th percentile of the wage distribution and the 50th percentile, measured in logs) by 7.7 points and therefore explains 33.1% of the 23.2 point growth of the wage gap between high- and middle-wage earners over the 1979–2017 period. Deunionization has this result because it depressed the wages of middle-wage earners but had little impact on high-wage earners at the 90th percentile.
• Unions disproportionately benefit those with low and moderate wages, those with lower levels of education, and nonwhites, and this has been the case since the birth of the modern labor movement in the New Deal. The erosion of collective bargaining, correspondingly, has therefore increased wage inequality.

Collective bargaining increases and equalizes wages for union workers and nonunion workers in unionized occupations and sectors

Researchers have long demonstrated the connection between being represented by a union and earning higher wages. This advantage, called the “union wage premium,” measures the percent difference between the wages of unionized workers and those of nonunionized workers with the same characteristics. That collective bargaining also leads to more equal wage outcomes was firmly established by Richard Freeman and James Medoff in the late 1970s and popularized in their important 1984 book, What Do Unions Do? (Jake Rosenfeld’s 2014 book, What Unions No Longer Do, provides an update of the issues). Of primary importance are the ways in which collective bargaining leads to more equal wage outcomes among unionized workers and in unionized industries and occupations.4 First, unions make wage differences between occupations more equal because they give a larger wage boost to low- and middle-wage occupations than to high-wage occupations. Second, unions make wages of workers with similar characteristics more equal because wages are “standardized” in union settings, meaning that wages are set for particular types of work and do not vary much across people doing the same work, at least not to the same degree as in nonunion settings. Third, unions have historically been more likely to organize middle-wage than high-wage workers, thereby lowering inequality by closing gaps between, say, blue-collar and white-collar workers.5 Last, where unions are strong the wages of comparable nonunion workers are also increased. The bottom line result of these influences is that being represented by a union or being in a heavily unionized industry or occupation has boosted wages for low-wage workers in these settings the most, and these union wage boosts have been larger at the middle than at the highest wage levels, larger for Black and Hispanic workers than for white workers, and larger for those with lower levels of education. This pattern of wage increases narrows wage inequalities. That unions have disproportionately benefited Black workers and workers with low and moderate wage levels and lower levels of education has been true as far back as the 1940s (Farber et al. 2018). The union impact on inequality is even greater when measured with total compensation (wages plus benefits) than with wages alone (Pierce 1999).

Research from the early 1990s documented that the erosion of collective bargaining was responsible for around a fifth of the rise in wage inequality among men in the 1980s (Card 1991; DiNardo, Fortin, and Lemieux 1996; Freeman 1991) but had a more modest impact among women.

Widespread collective bargaining has a ‘spillover’ effect on nonunion wages—it increases and equalizes wages for all workers

Recent research assessing the impact of unions on nonunion workers’ wages—sometimes referred to as “spillover effects”—finds an even larger impact of deunionization on wage inequality. When the share of workers who are union members is relatively high, as it was in 1979, wages of nonunion workers are higher. For example, had private-sector union density in 2013 remained at its 1979 level, weekly wages of nonunion men in the private sector would have been 5% higher, equivalent to an additional $2,704 in earnings for year-round workers; among those same workers but without a college education wages would be 8% higher, or $3,016 more per year (Rosenfeld, Denice, and Laird 2016; Denice and Rosenfeld 2018).6 Consequently, estimates of the impact of eroded collective bargaining on wage inequality that incorporate union spillover effects find a larger role of the impact of unions on wage inequality than do studies that focus on unionized workers alone. For instance, Western and Rosenfeld (2011, Table 2 and analyzed in Mishel et al. 2012, Table 4.38) find that the weakening of collective bargaining explains a third of the increase in wage inequality among men and a fifth of the rise of wage inequality among women over the 1973–2007 period. This research demonstrates that the erosion of collective bargaining has been the largest single factor driving a wedge between middle- and high-wage male workers, the primary feature of rising wage inequality among men (other than the pulling away of the top 1%).7

About a third of the growth in the 90/50 wage gap and other key inequality measures can be explained by the decline of unions

The most recent research on the effect of eroded collective bargaining on wage inequality, conducted by Fortin, Lemieux, and Lloyd (2021) and summarized in Table 1, incorporates a spillover effect and reports directly on the impact of eroded collective bargaining on the wage gap between high-wage (90th percentile) and middle-wage (50th percentile) workers by gender.

Table 1

The erosion of unions (column 3) can explain from 28.8% to 36.7% of the growth of male wage inequality as commonly measured, respectively, by the standard deviation of log wages and the Gini coefficient. The most salient finding is that over the 1979–2017 period eroded unionization explains 37.3% of the growth of the 90/50 wage gap for men, which is the only source of growing wage inequality among men in the bottom 90% of earners. The authors found a smaller impact of eroded unions on women’s wage inequality; it explains 6.7% to 8.8% of the growth as measured by the standard deviation of log wages and the Gini coefficient and only 13.0% of the growth of the 90/50 wage gap. As noted earlier, the erosion of unions had a smaller impact on women’s than men’s wages because women were far less unionized in 1979 (which is unlikely to be true moving forward).

We can examine the impact of deunionization on the median and the 90th percentile wage levels for men and women combined from 1979 to 2017 using an (unpublished) analysis by Thomas Lemieux, who relied on the model in Fortin, Lemieux, and Lloyd (2021). Deunionization widened the log 90/50 wage gap (the inequality in the top half of the wage structure) by 7.7 log points from 1979 to 2017. This increase in the size of the gap came about almost entirely by reducing the median hourly wage by 7.6 log points, or, equivalently, by 7.9% (0.2% annually) over the 1979–2017 period. The impact on men alone is much larger, with deunionization lowering the male median wage by 10.9 log points, or 11.6% (0.29% annually). Because we know that the 90/50 wage gap grew 23.2 log points over the 1979–2017 period, we can compute that the 7.7 log point effect of deunionization explains 33.1% of the growth of the 90/50 wage gap.

This impact of eroded collective bargaining lowered the median hourly wage by $1.56 over the 1979–2017 period (Figure A). Put another way, the median hourly wage was $19.70 in 2017 but would have been $21.27 had collective bargaining not declined (all in 2020 dollars). For men, the erosion of collective bargaining lowered the median hourly wage by $2.49 over the 1979–2017 period. The median male hourly wage was $21.49 in 2017 but would have been $23.97 had collective bargaining not declined (all in 2020 dollars; see Figure B). These losses from deunionization are the equivalent of annual losses for a full-time, full-year median worker and comparable male worker, respectively, of $3,250 and $5,171.

Figure A

Figure B

The Fortin, Lemieux, and Lloyd (2021) results are very comparable to those of Stansbury and Summers (2020). In particular, we have benchmarked the Fortin, Lemieux, and Lloyd estimates of the impact of deunionization on the median wage with the estimate of Stansbury and Summers of the impact on the wages of workers without a college degree. Once one aligns the time periods, one finds that the Stansbury and Summers estimate is even larger.8 The Fortin, Lemieux, and Lloyd results for how much deunionization explains the growth of wage inequality also align with those by Western and Rosenfeld (2011).9

Midcentury unions were a powerful force for greater equality

Newly developed historical data from the early postwar period affirm that collective bargaining was a strong force for greater equality of wages. For instance, Callaway and Collins (2017), using data from a survey of men living in Philadelphia; New Haven, Conn.; Chicago; St. Paul, Minn.; San Francisco; and Los Angeles in 1951, found “the [union] wage premium was larger at the bottom of the income distribution than at the middle or higher, larger for African Americans than for whites, and larger for those with low levels of education,” findings that are “consistent with the view that unions substantially narrowed urban wage inequality at mid-century.” It follows, of course, that the consequent erosion of collective bargaining would increase wage inequality and have the most adverse impact on nonwhite workers, workers with the least education, and low- and moderate-wage workers.

Likewise, Farber et al. (2018, 33), who developed data on union households from Gallup surveys going back to 1936, found that “mid-century unions [were] a powerful force for equalizing the income distribution.” This happened because unions disproportionately represented “disadvantaged” workers (nonwhite or less educated), raised the wages of low- and moderate-wage workers the most, and had a large, stable impact of raising wages for union workers by roughly 15–20 log points over the last 80 years.10

Worker preferences and automation are not the cause of union decline

Some pundits and analysts, skeptical about the impact of weaker unions on wages or wage inequality, claim that the decline of unions reflects a decline in worker interest in unions or is due to globalization and automation, i.e., union decline itself is caused by other factors (is endogenous) and therefore should not be considered the cause of wage decline. Neither contention—that workers no longer care for unions or that automation is what led to union decline—is well founded.

Kochan et al. (2018) examined the level of interest in joining a union among unorganized workers and found that the “demand for unions” has risen substantially since the late 1970s. Kochan and Kimball (2019) described these results as

differences in the percentage of non-union workers who indicated a preference for union representation in nationally representative surveys in 1977, 1995, and 2017. Note that the 1977 and 1995 results were nearly identical: approximately one third of the non-union workforce indicated they would vote to have union representation if given an opportunity to do so on their current job. In 2017 that number increased to 48 percent. This number translates into an under-representation of unions of approximately 58 million workers.

These findings indicate that there has continuously been a large unmet demand for collective bargaining over the last four decades.

As for the role of globalization and automation in union decline, Mishel, Rhinehart, and Windham (2020) found that the shrinkage of manufacturing from ongoing automation and globalization indeed contributed to the shrinkage of employment and the loss of union jobs, but the declines in that sector can account for only a small portion of deunionization, perhaps 15–20%. They also note that the share of workers covered by collective bargaining declined strongly across the private sector in industries not heavily affected by globalization, such as construction, transportation, communications, utilities, supermarkets, hotels, and mining. So, any focus solely on manufacturing will not capture the full picture of union decline. Moreover, the erosion of unions in manufacturing is not due only to automation and globalization.

An Organisation for Economic Co-operation and Development (OECD 2019) analysis of the cross-country decline in collective bargaining across advanced nations found that, “Contrary to a commonly held belief, the combined contributions of demographic changes and structural shifts, such as the shrinking of the manufacturing sector, are small and leave most of this declining trend [in collective bargaining] unexplained.”

This conclusion confirmed an earlier finding by Schmitt and Mitukiewicz (2012) that “national politics are a more important determinant of recent trends in unionization than globalization or technological change.”

Then why has collective bargaining eroded? The primary reason was a concerted corporate attack on unions, starting in the 1970s, that exploited weaknesses in our labor laws to suppress the ability of workers to choose collective bargaining and organize (Windham 2017). The scale of union organizing collapsed dramatically in that decade as the share of nonagricultural workers in private-sector National Labor Relations Board elections fell from 1.0% to 1.2% each year in the 1950s and 1960s to just 0.3% each year in the 1980s and to 0.1% each year in the early 2000s (Mishel, Rhinehart, and Windham 2020). As Windham (2017) documents, this collapse of organizing was due to increased employer aggressiveness and use of both legal and illegal tactics, including captive audience meetings (meetings delivering anti-union messages that employees must attend or else be disciplined or fired), threats of shutdowns or relocation, firing of union organizers, use of a rapidly expanded group of anti-union consultants, and process delays.

McNicholas et al. (2019), analyzing union representation elections that took place in 2016–2017 and building on earlier work by Bronfenbrenner (2009), documented the current pervasive lawlessness prevailing in union organizing attempts:

Employers are charged with violating federal law in 41.5% of all union election campaigns. And one out of five union election campaigns involves a charge that a worker was illegally fired for union activity. Employers are charged with making threats, engaging in surveillance activities, or harassing workers in nearly a third of all union election campaigns.

Other developments, enabled by employer aggressiveness and changes in the rules governing collective bargaining, limited collective bargaining power by eroding coverage and weakening unions’ ability to strike (Mishel, Rhinehart, and Windham 2020).

Conclusion: Widening wage inequality is a policy decision that can be reversed

Between 1979 and 2017 the growth of productivity (net of depreciation) grew far faster than the inflation-adjusted growth of hourly compensation (wages and benefits) of the typical, or median, worker (Mishel and Bivens 2021). This divergence is the consequence of policy decisions made on behalf of wealthy interests and corporations, and they include acts of omission (failing to raise the minimum wage or improve labor law) and commission (the Federal Reserve targeting inflation goals and raising interest rates in a way that leads to excessive unemployment to restrain wage growth and policymakers pursuing corporate-driven globalization).

In other words, wage growth has been greatly directed by policy decisions and is a political variable. It responds—robustly—to big policy changes. Policymakers can deliver prosperity to the vast majority of U.S. workers based on faster wage growth. Whether workers obtain a fair share of the economy’s gains in the future will depend not so much on abstract forces beyond their control but on demanding that their political representatives restore bargaining power to workers, individually and collectively. Legislation that expands collective bargaining by enabling workers to choose union representation and strengthens union rights is critically important to the enterprise of restoring robust wage growth.

Endnotes

1. This report draws heavily from a longer, forthcoming EPI report, Identifying the Policy Levers Generating Wage Suppression and Wage Inequality, written with Josh Bivens. Both reports are part of the Economic Policy Institute’s Unequal Bargaining Power project funded by the Nick and Leslie Hanauer Foundation, the William and Flora Hewlett Foundation, and the Bernard and Anne Spitzer Charitable Trust. For this report, I am indebted to Thomas Lemieux, who provided estimates of the impact of deunionization on specific percentiles, such as the median, using the model and data in Fortin, Lemieux, and Lloyd 2021.

2. Time and again, the Federal Reserve has prematurely slowed economic recoveries by raising interest rates in the name of fighting prospective inflation. Policymakers as well have too quickly withdrawn fiscal stimulus early in economic recoveries. As a result, the economy has rarely run “hot” enough (at a low enough unemployment rate) for long enough to make employers compete for workers by raising wages. See the forthcoming EPI report, Identifying the Policy Levers Generating Wage Suppression and Wage Inequality (Mishel and Bivens 2021).

3. These data are the share with collective bargaining coverage for “1979,” calculated as a pooled average of 1977–1980 shares from the Current Population Survey May CPS data.

4. This discussion draws heavily from Bivens et al. 2017 and McNicholas et al. 2020.

5. Evidence for these effects can be found in Mishel et al. 2012: union impact and coverage by demographic groups (Table 4.33) and by education, occupation, and wage fifth (Table 4.37).

6. These estimates look at what wages would have been in 2013 had union density remained at its 1979 levels.

7. Keep in mind that the wage gap between middle- and low-wage men has not grown over the last four decades.

8. Fortin, Lemieux, and Lloyd (2021) find a 7.6 log point impact of deunionization on the median. This amount includes both direct and spillover impacts. Their estimate of the direct union impact on the 90/50 wage gap is 52.8% of the total union impact. Applying that share to 7.6 points yields a 4.0 log point estimate of a direct union effect on the median wage. Anna Stansbury provided a benchmark for comparisons to the Fortin, Lemieux, and Lloyd results based on her work with Summers (2020): “We estimate for the nonfinancial corporate sector a direct effect of union decline on labor rents for noncollege workers of 2.9 percent of compensation over 1984 to 2016.” The Fortin, Lemieux, and Lloyd estimates line up close to, even below, the Stansbury-Summers estimate if one adjusts the Stansbury-Summers results for the longer time period used by Fortin, Lemieux, and Lloyd, 1979–2017. There was a very steep decline in union membership from 1979 to 1984, accounting for 40% of the total decline from 1979 to 2016. If one scales the Stansbury-Summers estimate to the total decline since 1979, their estimated impact would be 4.8% (2.9% times (1/60.4%)), an even larger impact than Fortin, Lemieux, and Lloyd.

9. Western and Rosenfeld find that deunionization’s impact (direct and spillover) on wage inequality explained 33.9% of male wage inequality and 20.4% of women’s wage inequality. The comparable estimate for Fortin, Lemieux, and Lloyd (2021) is deunionization explaining 28.8% and 6.7%, respectively, of men’s and women’s wage inequality.

10. Farber et al. (2018, 33) note: “We show that a combination of low-skill composition, compression, and a large union income premium made mid-century unions a powerful force for equalizing the income distribution.” Specifically (p. 24): “During our long sample period, the union premium has remained between ten and twenty log points, with the less-educated receiving an especially large premium. Moreover, the negative effect of unions on residual income variance is large and also relatively stable over time. By contrast, selection into unions is not constant across time. In the Great Compression period, when unions were at their peak and inequality at its nadir, disadvantaged households were much more likely to be union members than either before or since.”

References

Bivens, Josh, Lora Engdahl, Elise Gould, Teresa Kroeger, Celine McNicholas, Lawrence Mishel, Zane Mokhiber, Heidi Shierholz, Marni von Wilpert, Valerie Wilson, and Ben Zipperer. 2017. How Today’s Unions Help Working People: Giving Workers the Power to Improve Their Jobs and Unrig the Economy. Economic Policy Institute, August 2017.

Bronfenbrenner, Kate. 2009. No Holds Barred: The Intensification of Employer Opposition to Organizing. Economic Policy Institute and the American Rights at Work Education Fund, May 2009.

Callaway, Brantly, and William J. Collins. 2017. “Unions, Workers, and Wages at the Peak of the American Labor Movement.” National Bureau of Economic Research Working Paper 23516. https://doi.org/10.3386/w23516.

Card, David. 1991. “The Effect of Unions on the Distribution of Wages: Redistribution or Relabelling?” National Bureau of Economic Research Working Paper 287. https://doi.org/10.3386/w4195.

Denice, Patrick, and Jake Rosenfeld. 2018. “Unions and Nonunion Pay in the United States, 1977–2015.” Sociological Science 5: 541–561.

DiNardo, John, Nicole M. Fortin, and Thomas Lemieux. 1996. “Labor Market Institutions and the Distribution of Wages 1973–1992: A Semiparametric Approach.” Econometrica 64, no. 5: 1001–1044.

Farber, Henry S., Daniel Herbst, Ilyana Kuziemko, and Suresh Naidu. 2018. “Unions and Inequality over the Twentieth Century: New Evidence from Survey Data.” National Bureau of Economic Research Working Paper 24587. https://doi.org/10.3386/w24587.

Fortin, Nicole M., Thomas Lemieux, and Neil Lloyd. 2021. “Labor Market Institutions and the Distribution of Wages: The Role of Spillover Effects.” National Bureau of Economic Research Working Paper 28375.

Freeman, Richard B. 1991. “How Much Has De-Unionization Contributed to the Rise in Male Wage Inequality?” National Bureau of Economic Research Working Paper 3826. https://doi.org/10.3386/w3826.

Freeman, Richard B., and James l. Medoff. 1984. What Do Unions Do? New York: Basic Books.

Hirsch, Barry T., and David A. Macpherson. 2020. Union Membership and Coverage Database from the CPS. unionstats.com, data compiled from the Current Population Survey February 24, 2020.

Kochan, Thomas A., and William T. Kimball. 2019. “Unions, Worker Voice, and Management Practices: Implications for a High-Productivity, High-Wage Economy.” Russell Sage Foundation Journal of the Social Sciences 5, no. 5.

Kochan, Thomas A., William T. Kimball, Duanyi Yang, and Erin L. Kelly. 2018. “Worker Voice in America: Is There a Gap Between What Workers Expect and What They Experience?” ILR Review 72, no. 1: 3–38. https://doi.org/10.1177/0019793918806250.

Lemieux, Thomas. 2021. Unpublished Excel files provided by Thomas Lemieux, using the model and data in Fortin, Lemieux, and Lloyd (2021).

McNicholas, Celine, Margaret Poydock, Julia Wolfe, Ben Zipperer, Gordon Lafer, and Lola Loustaunau. 2019. Unlawful: U.S. Employers Are Charged with Violating Federal Law in 41.5% of All Union Election Campaigns. Economic Policy Institute, December 2019.

McNicholas, Celine, Lynn Rhinehart, Margaret Poydock, Heidi Shierholz, and Daniel Perez. 2020. Why Unions Are Good for Workers—Especially in a Crisis Like COVID-19, Economic Policy Institute, August 2020.

Mishel, Lawrence, and Josh Bivens. 2021. Identifying the Policy Levers Generating Wage Suppression and Wage Inequality, Economic Policy Institute’s Unequal Power project, forthcoming.

Mishel, Lawrence, Josh Bivens, Elise Gould, and Heidi Shierholz. 2012. The State of Working America, 12th Edition. An Economic Policy Institute book. Ithaca, N.Y.: Cornell Univ. Press.

Mishel, Lawrence, Lynn Rhinehart, and Lane Windham. 2020. “Explaining the Erosion of Private-Sector Unions: How Corporate Practices and Legal Changes Have Undercut the Ability of Workers to Organize and Bargain.” Economic Policy Institute, November 2020.

Organisation for Economic Co-operation and Development (OECD). 2019. Negotiating Our Way Up: Collective Bargaining in a Changing World of Work.

Pierce, Brooks. 1999. “Compensation Inequality.” Department of Labor, Bureau of Labor Statistics Working Paper 323.

Rosenfeld, Jake. 2014. What Unions No Longer Do. Cambridge, Mass.: Harvard Univ. Press.

Rosenfeld, Jake, Patrick Denice, and Jennifer Laird. 2016. Union Decline Lowers Wages of Nonunion Workers: The Overlooked Reason Why Wages Are Stuck and Inequality Is Growing. Economic Policy Institute.

Schmitt, John, and Alexandra Mitukiewicz. 2012. “Politics Matter: Changes in Unionization Rates in Rich Countries, 1960–2010.” Industrial Relations Journal 43, no. 3: 260–280.

Stansbury, Anna, and Lawrence Summers. 2020. “Declining Worker Power and American Economic Performance.” Brooking Papers on Economic Activity: BPEA Conference Drafts.

Western, Bruce, and Jake Rosenfeld. 2011. “Unions, Norms, and the Rise in U.S. Wage Inequality.” American Sociological Review 76, no. 4: 513–537.

Windham, Lane. 2017. Knocking on Labor’s Door: Union Organizing in the 1970s and the Roots of a New Economic Divide. Chapel Hill: Univ. of North Carolina Press.

One of the most striking indicators from today’s report from the Bureau of Labor Statistics (BLS) is the job seekers ratio—the ratio of unemployed workers (averaged for mid-February and mid-March) to job openings (at the end of February). On average, there were 9.8 million unemployed workers compared with only 7.4 million job openings. This translates into a job seekers ratio of about 1.3 unemployed workers to every job opening. Put another way, for every 13 workers who were officially counted as unemployed, there were only available jobs for 10 of them. That means, no matter what they did, there were no jobs for 2.5 million unemployed workers.

As with job losses, workers in certain industries are facing a steeper uphill battle. In the construction industry as well as arts, entertainment, and recreation, there were more than three unemployed workers per job opening. In educational services, accommodation and food services, other services, and transportation and utilities, there were more than two unemployed workers per job opening. As bad as these numbers are, they miss the fact that many more weren’t counted among the unemployed: The economic pain remains widespread with 23.6 million workers hurt by the coronavirus downturn.

On the whole, the U.S. economy is seeing a significantly slower hiring pace than we experienced in May or June. While the pickup in job openings is a promising sign, hiring in February was below where it was before the recession. There was an increase in jobs in the mid-March employment report, but we still have a long way to go before recovering the large job shortfall—11.0 million when using a reasonable counterfactual of job growth if the recession hadn’t occurred—that remains.

One misguided critique of the effort to raise the federal minimum to $15 in 2025 is that there is a need to establish a regionally adjusted federal minimum wage set to local conditions. In fact, federal minimum wage policy has always provided for tailored standards, by coupling a strong national wage floor with the ability for cities and states to adopt higher standards. Our ability to set a national wage floor is much easier now than it was decades ago when lawmakers last raised the federal minimum wage to new heights. In 1968, when the federal minimum wage was lifted to its highest value in U.S. history and coverage of the law was vastly expanded, there were much larger differences in wage levels throughout the country. Yet, we now have empirical evidence that establishing this unprecedented, nationwide minimum wage did not have adverse employment impacts.

Today, the wage levels of lower-wage states, primarily Southern ones, are much closer to overall national wage levels, so there is even less validity to claims that the federal minimum wage must be lowered to accommodate certain areas. Moreover, the ‘bite’ of a $15 minimum wage in 2025—i.e., the share of workers and businesses impacted, and the magnitude of resulting wage increases—will be well within the range of recent experiences of minimum wage increases in states and localities that studies have shown had little, if any, impact on employment. The proposed increase to $15 by 2025 will lead to improved annual earnings for nearly all low-wage workers.

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Even at this pace, it could take more than a year to dig out of the total jobs shortfall. However, today’s number is certainly a promising sign for the recovery, especially as vaccinations increase and vital provisions in the American Rescue Plan (ARP) have continued to ramp up since the March reference period to today’s data. The benefits of the ARP will continue to be captured in coming months.

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A year into the recession, the labor market is still down 9.5 million jobs from where it stood immediately before the COVID-19 shock. If we add in jobs that should have been created over that time to absorb new workers, we’re facing a jobs shortfall today of nearly 12 million jobs.

As the labor market finally picks up, the key indicators to watch are where the jobs are returning and for whom. The biggest deficit remains in leisure and hospitality, with 3.5 million fewer jobs relative to its February 2020 level. The economic pain caused by losses in this lowest-paying sector was enormous.

Meanwhile, public-sector employment—primarily education employment at the state and local level—remains 1.4 million jobs below pre-pandemic levels. I’m optimistic that the state and local relief that was part of the American Rescue Plan will provide tremendous support to this sector in terms of employment and the vital public services they provide.

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In this blog post, I argue that insufficient attention has been paid to this third channel, and that government efforts to help firms “take the high road” could ease firms’ transition to higher wages in a way that also benefits workers and consumers.

Much research documents the ways that firms can utilize high-road policies or good-jobs strategies to tap the knowledge of all their workers to create innovative products and processes. In retail, for example, firms such as Costco and Trader Joe’s pay far above minimum wage, yet remain profitable, as MIT’s Zeynep Ton has shown. The key to their success is a mix of complementary practices in marketing (reducing the number of products and promotion so that stores can manage inventory efficiently), human resources (cross-training workers so they can respond to a variety of demands), and operations (avoiding unneeded steps, in part by soliciting feedback from employees).

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Key takeaways:

• Most of the biggest users of the H-1B visas—the U.S.’s largest temporary work visa program—are companies that have an outsourcing business model.
• These companies exploit the H-1B program’s weaknesses to facilitate the transfer of U.S. jobs offshore as a lower cost alternative to hiring U.S. workers, and sometimes to replace incumbent U.S. workers with H-1B workers who are paid wages that are far below market wage rates.
• The latest data show that over 33,000 new H-1Bs were issued to the top 30 H-1B employers, accounting for nearly 40% of all new H-1Bs in 2020 that are subject to the annual limit of 85,000.
• Of the top 30 H-1B employers, 17 of them were outsourcing firms. Those 17 outsourcing firms alone were issued 20,000 H-1B visas, nearly one-quarter of the total 85,000 annual limit.
• President Joe Biden can and should implement regulations so that outsourcing companies can no longer exploit the program and to prevent them from underpaying skilled migrant workers.

The U.S.’s largest temporary work visa program is the H-1B—an important program that allows U.S. employers to hire college-educated migrant workers. However, the H-1B program is not operating as intended and needs to be fixed: Instead of being used to fill genuine labor shortages in skilled occupations without negatively impacting U.S. labor standards, the latest data show that the H-1B’s biggest users are companies that have an outsourcing business model. President Joe Biden can and should implement regulations so that outsourcing companies can no longer exploit the program and to prevent them from underpaying skilled migrant workers.

Outsourcing companies exploit the H-1B program’s weaknesses to build and expand a business model based on outsourcing jobs from other companies. In this arrangement, rather than being employed directly by the outsourcing company that hired them, the outsourcer sends its H-1B workers to work for third-party clients, either on- or off-site. The aim of the outsourcing company is ultimately to move as much work as possible abroad to countries where labor costs are lower and profit margins are higher. The H-1B workers serve three purposes in this business model: to facilitate the transfer of jobs and tasks offshore; to coordinate offshore teams; and to serve as a lower cost alternative to hiring U.S. workers for on-site jobs. H-1B outsourcing companies also replace incumbent U.S. workers with H-1B workers and typically pay their H-1B workers the lowest wages permitted by law, far below market wage rates.

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There is no one right answer to this question. The “right” number for this upcoming proposal depends on what particular set of social problems you think can and should be fixed through public investment and fiscal redistribution. For this reason, any headline cost number needs to be derived from a “bottom-up” assessment that figures out the “right” cost of a rescue package by deciding which specific proposals would be good things to do and scoring them based on that.

This focus on identifying some “right” number that is derived instead from some top-down macroeconomic analysis is understandable. Since the COVID-19 shock first hit the U.S. economy, there has been an obvious and measurable “output gap” that will eventually need to be filled in to restore the labor market to pre-COVID health (or even better). This output gap is the difference between what the economy could produce if most resources (most importantly, workers) were fully utilized and what is actually being produced. The gap between this potential and actual gross domestic product (GDP) is generally driven by a shortfall of demand (spending by households, businesses, and governments) relative to the economy’s productive capacity. This gap can be reasonably measured (not with real precision, but at least in rough magnitude). Once the gap is identified, policies that pump up spending—either by direct federal government expenditures or by transferring resources to households and state and local governments to spend—can quickly close the gap. It was this sort of rough gap analysis that informed debates about the proper size of the American Rescue Plan (ARP).

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The mass shootings that killed six women of Asian descent and two other people at Atlanta area spas have left the AAPI community in Atlanta and across the country in mourning and on high alert. While the man arrested for the murders has not yet been charged with a hate crime, the hate and discrimination being directed toward Asian Americans is an inescapable fact. According to Stop AAPI Hate, nearly 3,800 incidents targeting Asian-Americans were reported to the organization between mid-March 2020 and the end of February 2021. AAPI women were more than twice as likely to report hate incidents as men. And these incidents, which range from verbal harassment to civil rights violations to physical assault, “represent only a fraction of the number of hate incidents that actually occur,” a Stop AAPI Hate report said.

Advocates attribute the rise of hate and harassment of Asian Americans to the increasingly xenophobic language connecting the COVID-19 pandemic with Asian Americans. In reality, AAPI individuals are suffering under the pandemic, especially Asian American women.

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Unfortunately, their experiences are far from unique—employers are charged with violating the law in 41.5% of all union elections supervised by the National Labor Relations Board (NLRB). The numbers are worse for large employers, like Amazon, where more than half (54.4%) of employers are charged with violating the law.

We have only to look to the recovery from the Great Recession to know that reforming this system is critical to an equitable recovery now. Even though the unemployment rate ultimately got down to 3.5% in the recovery from the Great Recession, low- and middle-wage workers did not get a fair share of that economic growth. If policymakers do not address our nation’s broken labor law system, then they will be the architects of an economy marked by continued inequality and injustice. This moment is an opportunity to prioritize policies that enable working people to have agency over their working lives and win both economic and democratic reforms for themselves and their co-workers.

The Protecting the Right to Organize (PRO) Act addresses many of the major shortcomings with our current law. Specifically, it would institute meaningful penalties for private-sector employers that coerce and intimidate workers seeking to unionize—as has been clearly documented in the Amazon organizing campaign in Bessemer.

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Last week was the 53rd straight week total initial claims were greater than the second-worst week of the Great Recession. (If that comparison is restricted to regular state claims—because we didn’t have PUA in the Great Recession—initial claims are still greater than the 14th worst week of the Great Recession.)

Figure A shows continuing claims in all programs over time (the latest data for this are for March 6). Continuing claims are currently nearly 17 million above where they were a year ago, just before the virus hit.

Figure A

The good news in all of this is Congress’s passage of the sweeping $1.9 trillion relief and recovery package. It is both providing crucial support to millions of working families and setting the stage for a robust recovery. One big concern, however, is that the bill’s UI provisions are set to expire the first week in September, when, even in the best–case scenario, they will still be needed. By then, Congress needs to have put in place long-run UI reforms that include automatic triggers based on economic conditions.

A strong domestic steel industry is critical to U.S. national defense, to the health of America’s critical infrastructure, and to the competitiveness of many domestic manufacturing industries. Beyond supplying high-quality steel in sufficient quantities to meet national defense needs, the U.S. steel industry also plays a critical role in supporting the welfare of other industries essential to the broader health and operation of the economy and government. For decades, chronic global steel supply gluts have undermined the U.S. steel industry with surging imports to U.S. markets undercutting prices, domestic production, employment, and investments. This oversupply jeopardizes the fundamental health of the U.S. steel industry—one of the cleanest and most energy-efficient steel industries globally.

Global steel surpluses are the result of chronic global excess steelmaking capacity in major exporting countries, including China, India, Brazil, Korea, Turkey, the EU, and other nations, much of it from state-owned and state-supported enterprises that are heavy polluters. In 2018, the United States determined that steel imports posed significant risks to national security and imposed a 25% tariff and other trade remedies on certain steel products under Section 232 of the Trade Expansion Act of 1962. This report examines the impacts of these measures on domestic steel production and consuming industries, and it recommends that these measures be retained until a multilateral solution to the problem of global excess steel capacity can be achieved.

Key conclusions of this report include:

• The U.S. steel industry is a vital component of the American economy. In 2017, prior to Sec. 232 import measures, the U.S. steel industry supported nearly 2 million jobs that paid, on average, 27% more than the median earnings for men and 58% more than the median for women.

• Global steel markets are plagued by chronic excess capacity. Measured by the Organisation for Economic Co-operation and Development (OECD), global excess capacity is 5.8 times the productive capacity of the entire U.S. steel industry. Massive overcapacity driven by subsidies and other anti-competitive policies can only be disposed of by these producers flooding U.S. and other markets with exports, posing material harm to U.S. steel producers and risking the U.S. industry’s ability to maintain operations, grow, and invest in areas essential to national defense, critical infrastructure, and broader economic welfare.

• The economic picture for U.S. steel producers brightened considerably beginning in 2018 until the pandemic began. Following implementation of Sec. 232 measures in 2018—and prior to the global downturn in 2020—U.S. steel output, employment, capital investment, and financial performance all improved. In particular, U.S. steel producers announced plans to invest more than $15.7 billion in new or upgraded steel facilities, creating at least 3,200 direct new jobs, many of which are now poised to come online. In addition, more than $5.9 billion was invested by nine firms in plant acquisitions as part of industry restructuring to increase efficiency, preserving additional jobs at those facilities.

• Administrations dating back to the mid-20th century have worked to mitigate the effects on U.S. steel producers of unfair global practices. For decades, unfair trade practices have threatened the U.S. steel industry with repeated crises. In this context, the recent Sec. 232 import measures simply continue a long thread of executive policy actions to provide relief for the damages wrought on U.S. producers by unfair competition and global surplus capacity in steel. For example, President Obama pressed the excess capacity issue through diplomatic channels at the G20 and in the U.S.-China Strategic and Economic Dialogue and under U.S. law, overseeing 370 trade remedy actions on imported steel products.

• China has massively and rapidly expanded its steel production capacity. China, the world’s largest steel producer, used subsidies and other forms of distortionary government support to expand steel capacity by 418%, or 930 million metric tons (MMT), since 2000, such that by 2019 it controlled just shy of half of global steel capacity. Chinese steel firms are also investing in developing capacity overseas, including in Europe, Asia, and Latin America, in efforts to evade trade enforcement actions.

• Countries across several continents followed in China’s footsteps, developing more excess capacity. Rapid growth in overcapacity is not limited to China. Other major steel-producing countries achieving rapid capacity growth between 2000 and 2019 include India, Turkey, Iran, South Korea, Vietnam, Russia, Brazil, Mexico, and Taiwan, with increases ranging from 8 MMT in Taiwan to 95 MMT in India. These are all countries where the state dominates or plays a significant role directing steel and other heavy industries, where government policies provide trade-distorting support to steel producers, or where producers have histories of unfair trade the in U.S. market. Governments are also intervening in markets to maintain capacity, including in the EU.

• Rapid expansion elsewhere comes with falling domestic production. In the United States, by contrast, total steel production capacity fell by 5.5 MMT to 110 MMT in 2019, with world market share shrinking to less than 5% in 2019 from 10% in 2000.
• Section 232 measures delivered near-immediate benefits. Once implemented in 2018, such Sec. 232 steel import measures as 25% tariffs on imported steel and import quotas on select countries helped curb U.S. steel imports by 27% by 2019. Import penetration of the U.S. market fell to 26% of all steel consumed in the United States in 2019, from 35% in 2017.
• Section 232 measures have had no meaningful real-world impact on the prices of steel-consuming products (such as motor vehicles). Econometric analysis shows that price changes in basic steel products had statistically zero or economically negligible causal effects on prices of “downstream,” or steel-using goods, including new motor vehicles, construction equipment, electrical equipment and household appliances, motor vehicle parts, nonresidential construction goods, food at home, and durable goods more broadly—industries accounting for the majority of U.S. steel consumption. This lack of impact is unsurprising, given that steel is just one cost in a long list of inputs to production.
• Widespread exclusions to Section 232 measures mitigate positive economic impacts. Despite benefiting U.S. steel producers and having no discernible impact on steel consumers, Sec. 232 import measures have been progressively undermined by nearly 108,000 product-specific exclusions through July 2020 alone and broad, countrywide tariff exemptions for roughly one-third of all imports.
• Jobs, national security, and the steel industry itself are at risk if Section 232 measures are discontinued or weakened in the post-pandemic economy. The diminished global economic outlook as the world emerges from the COVID-19 pandemic means that the brief reprieve from a global supply glut and nascent recovery enjoyed by U.S. steelmakers is likely to evaporate. Premature relaxation or elimination of Sec. 232 measures, in the absence of any concrete measures to eliminate excess capacity and trade-distorting policies that contribute to the global steel glut, would put the U.S. steel industry at risk, imperiling new investments and hundreds of thousands of good jobs in steelmaking and in other indirect and induced jobs supported by steelmaking activity.
• Relaxing or reversing Section 232 measures also would provide an advantage for low-priced, high carbon-polluting producers overseas.
• A permanent global solution is the best answer. The Biden-Harris administration should press for a permanent multilateral solution to the chronic problem of excess global steel production capacity. But until such a solution is achieved, national security concerns and ensuring a sustainable economic recovery for the steel industry require the continuation of comprehensive Sec. 232 import measures and other policies to preserve the U.S. steel industry.

Introduction

In January 2018, the U.S. Department of Commerce (Commerce) concluded an investigation determining that imports of steel products pose significant risks to U.S. national security and the industry’s ability to maintain operations, grow, and invest in areas essential to national defense, critical infrastructure, and broader economic welfare under Section 232 of the Trade Expansion Act of 1962 (BIS 2018). Sec. 232 provides the president with authority to impose restrictions on products for which an investigation determines that the quantity or circumstances of imports to the United States “threaten to impair the national security” (CRS 2020).1 Beyond supplying high-quality steel in sufficient quantities to meet national defense needs, the U.S. steel industry also plays a critical role in supporting the welfare of other industries essential to the broader health and operation of the economy and government.

Following the Commerce determination, President Trump authorized tariffs of 25% on imported steel products in March 2018.2 The move also provided flexibility in implementation with respect to country of origin and product coverage and allowed domestic parties to petition for exclusion from tariffs where substitute domestic-sourced products were insufficiently available.3 This action follows a continuous thread of presidents—including President Obama—seeking to redress unfair trade practices that for decades have kept the U.S. steel industry on the brink of crisis.

President Biden and his administration undoubtedly will want to reevaluate the policies inherited from their predecessors. To provide perspective for this reevaluation, this report reviews recent developments in global steel markets and analyzes the economic impacts of Sec. 232 steel import measures to assess their efficacy in reversing the long-term trends undermining U.S. steel producers, as well as for evaluating the relative costs and benefits of this policy. Specifically, we examine the effects of Sec. 232 measures on:

• the decades-long problem of chronic global surplus capacity in steel plaguing U.S. producers
• the economic viability of U.S. steel producers
• downstream consumers of steel products
• expected effects of prematurely relaxing or removing Sec. 232 measures

The results presented here demonstrate that Sec. 232 measures on imported steel products remain an important and necessary policy tool. The U.S. steel industry is critical not just for national defense, but also for infrastructure sectors, including electricity systems and equipment, transportation infrastructure and equipment, food and agricultural systems, water systems, energy security and independence, and metal-making and other advanced manufacturing uses. It is also a vital component of the American economy. In 2017, prior to the Sec. 232 import measures and the pandemic, the U.S. steel industry supported nearly 2 million jobs that paid, on average, 27% more than the median earnings for men and 58% more than the median for women (Schieder and Mokhiber 2018; AISI 2018).

Currently, the United States has an excessive dependence on unreliable foreign sources to supply national needs. In 2020, the pandemic and resulting economic contraction showed the dire consequences of reliance on uncertain foreign supplies for personal protective equipment, critical medical goods, and supplies of many other essential products. Policymakers should heed this sober warning when considering how to secure the future for U.S. steel production.

Policy action under Sec. 232 follows decades of a mounting crisis for U.S. steel producers that risks their continued ability to meet the needs of national defense, critical infrastructure, and the broader domestic economy. Steel producers support good-paying, middle-class jobs both directly and indirectly in related industries and throughout local communities where they serve as anchors for regional economies. In 2001, a similar Commerce investigation found “no probative evidence” that imported semi-finished steel products threatened U.S. producers (Bureau of Export Administration 2001). This determination resulted in severe negative consequences for the domestic industry—soon thereafter, nearly 40 U.S. steel producers declared bankruptcy (CRS 2003).

The threat to U.S. steel producers has only worsened in the intervening period, as chronic overcapacity in foreign steel-producing industries has become a permanent feature of global steel markets, driven by countries supporting their national industries on noncommercial terms. A flood of underpriced imports to the United States and third-country markets has done significant harm to U.S. producers and put the future viability of U.S. steel production in jeopardy.

Section 232 measures on imported steel products serve as a last resort to preserve the U.S. steel industry and domestic industrial base. To be certain, the best policy outcome would be for President Biden to achieve a permanent, multilateral solution to the chronic problem of global excess steel capacity. But the failures of decades-long efforts to eliminate global overcapacity through multilateral diplomatic engagement, coupled with foreign governments’ failures to address persistent and growing excess capacity, leave U.S. policymakers to choose between Sec. 232 measures and losing an industry critical for national security and broader economic well-being. Our analysis finds the choice is clear: President Biden should maintain these measures while pursuing multilateral efforts to achieve a long-term solution to unfair competition in global steel. Backtracking on Sec. 232 measures now, without a global solution to surplus capacity, would leave the U.S. industry and steelworkers in an even more precarious situation as more steel production and good-paying American jobs are moved offshore, including to countries with the worst environmental records.

Chronic global overcapacity threatens U.S. steel industry

Over the past several decades, chronic conditions of oversupply have come to define global steel markets—there is significantly more capacity to produce steel than there is demand for steel around the world. This chronic excess capacity is a direct result of policies pursued in many countries to support domestic steel producers on anti-competitive terms, with negative consequences for producers elsewhere around the world. It is also due to the basic economics of production in highly capital-intensive industries like steel, which encourages firms to maintain high levels of production capabilities. For decades, the United States has sought multilateral solutions to this persistent problem to little avail. Scant progress on the excess capacity issue made through diplomatic channels, and continued deterioration of the situation faced by producers operating on a commercial basis, left few other viable options for U.S. policymakers.

Surplus capacity puts downward pressure on prices for steel products, squeezing producer profit margins to an extent that threatens the ability of firms to service debts; to invest in research and development in more advanced products and cleaner production technology; to maintain workers’ jobs, compensation, and retiree pensions; and even to remain financially solvent. Businesses incur both fixed costs and variable costs in the course of steel production. Variable costs change with the quantity a firm produces, whereas fixed costs must be incurred no matter how much a firm produces. For example, in the case of steel, variable costs include the cost of material inputs like iron ore, scrap, and coal, as well as electricity and compensation for workers. However, capital-intensive industries like steel face enormous fixed costs for investments in production facilities and equipment that dominate total costs of production.4

The capital intensity of steel production has several economic consequences that contradict textbook economic models of production and competition. First, in industries like steel, the capital-intensive nature of production means that producers face increasing returns to scale—the more raw steel that is produced, the more efficient it is to produce additional output—such that the minimum efficiency of scale for entering the market with competitive costs is so large as to create a nontrivial addition to industrywide capacity (Crotty 2002). That is, in order to be viable, steelmakers must maintain large production capacity and, when expanding capacity, must add capacity in large chunks. Second, because fixed costs of production dominate variable costs, it is almost always desirable for producers to operate near full capacity in order to minimize the average cost of production. For producers in many countries, production exceeds what can be consumed in domestic markets, and the excess must be disposed of through exports.

Finally, the capital invested in fixed assets is quite specific, meaning the equipment cannot be easily redeployed to other uses outside of steel production, as is typically assumed in textbook models of economic competition. This means that, typically, productive capacity of financially nonviable steel producers is not removed from the market, but rather acquired by other producers in better financial standing. Thus, the market mechanism of price competition and creative destruction does not work well to self-regulate excess capacity in the industry (Crotty 2002). In fact, the OECD finds that foreign governments maintain policies and implement barriers that prevent the contraction of steelmaking capacity during economic downturns (Rimini et al. 2020). Combined, these features of the steel industry create incentives for producers to build big and run hot, no matter what other producers in the market do. But when all producers follow this logic, the result, in aggregate, is chronic overinvestment in productive capacity.

In order to maintain the viability of national steel industries under such financial conditions, many countries have instituted policies designed to maintain and expand production on noncommercial terms or other policies impermissible under international trade rules like the World Trade Organization (WTO)’s Agreement on Subsidies and Countervailing Measures. Commerce and the U.S. International Trade Commission, as well as the WTO, regularly find such measures do significant material harm to U.S. producers operating on a commercial basis, discussed in further detail in the box below. At the time of the Sec. 232 report, Commerce had authorized 164 orders on steel imports for illegal dumping or trade-distorting subsidies by 40 countries, with another 20 ongoing investigations (BIS 2018). Some foreign producers also benefit from other policies favorable to domestic industries but not explicitly prohibited by international agreements, such as discretionary regulatory forbearance of environmental standards, discussed later in the report, in the section “Retreating from Section 232 measures would squeeze vulnerable producers, increase greenhouse gas emissions.”

As a result, international disputes over steel capacity and multilateral efforts to resolve them are not new. The European Coal and Steel Community was formed in the aftermath of World War II to resolve continental tensions over steel production, providing a foundation for the European Union. The United States has been involved in international steel diplomacy since at least the Lyndon Johnson administration. In 1989, President George H.W. Bush launched efforts to reach a global agreement to abolish steel production subsidies. In the late 1990s, President Clinton initiated a “Steel Action Plan” in response to a flood of underpriced steel imports being dumped in the U.S. market. On a bilateral basis, President Obama pressed steel capacity issues with China for years through the Strategic and Economic Dialogue. He also moved multilateral partners to launch the Global Steel Forum at the 2016 G20 leaders’ summit, and to find common ground and establish a level playing field through the decades-old Organisation for Economic Co-operation and Development (OECD)’s Steel Committee (White House Office of the Press Secretary 2017).

Despite these efforts, capacity for global steel production continues to substantially exceed global demand for steel products, as shown in Figure A. In 2000, the peak year before a recession and the year before China acceded to the World Trade Organization, global excess capacity of 282 million metric tons already exceeded production by one-third of total output (850 MMT). With surplus capacity already at substantial levels, capacity growth outstripped steel production growth for the next decade and a half. From 2000 to 2015, production volume increased by 91% to 1,625 MMT, while excess capacity grew 166% to 752 MMT.

Figure A

By the mid-2010s, total world production capacity stabilized near 2,400 MMT, and increased demand for steel products led production to increase and capacity utilization rates to rise. However, by 2017 excess capacity still remained high, at 616 MMT, and capacity utilization remained below the level in 2000. Only beginning in 2018 and 2019, coinciding with Sec. 232 measures, did world capacity utilization surpass the level in 2000. The global economic slowdown in 2020 resulting from the COVID-19 pandemic once again sent excess steel capacity up and dragged the capacity utilization rate down. By 2020, excess capacity reached 633 MMT, or the equivalent of 5.8 times total U.S. production capacity.

That world production capacity stabilized after 2014 belies significant changes in the composition of steel production capacity by country. Figure B illustrates these changes in the composition of global steel supply by plotting the production capacities of the world’s largest steel-producing countries and country groups in 2000 on the horizontal axis against the percentage change in steel capacities in these country and country groups from 2000 to 2019 on the vertical axis; the size of each bubble indicates each country’s relative share of global steel capacity in 2019. China, the world’s largest steel producer, expanded production capacity by 418% since 2000, such that by 2019 it controlled just shy of half of global steel capacity.

Just the additional capacity installed in China since 2000 exceeds the combined capacity in 2019 of all other individual countries depicted in Figure B. During this time, U.S. capacity contracted 5.5 MMT, and its global market share was cut in half to less than 5% in 2019 from 10% of world capacity in 2000. Although Chinese producers are the largest culprits driving chronic excess steel capacity, they are far from alone in aggressive expansions that have displaced other producers and reshuffled the structure of world production. Other major steel-producing countries achieving rapid capacity growth between 2000 and 2019 include India (95 MMT, 280%), Turkey (30 MMT, 151%), Iran (27 MMT, 300%), Korea (26 MMT, 47%), Vietnam (22 MMT, 2,036%), Russia (21 MMT, 31%), Brazil (17 MMT, 51%), Mexico (9 MMT, 46%), and Taiwan (8 MMT, 40%). Each of these countries features state-dominated or state-directed economies, trade-distorting government policies supporting steel producers, or a history of shipping unfairly traded steel products to the U.S. market.

Figure B

A multilateral solution to the chronic problem of global excess steel capacity remains essential. But until that time, the inefficacy of market mechanisms to address surplus overcapacity and national policy distortions introduced by foreign trade partners will continue plaguing U.S. steel producers, risking the industry’s survival at a scale necessary to meet national security demands.

Section 232 measures improve industry conditions, spur investments and jobs

Given that the problem of global excess capacity for U.S. steel producers is clear, policymakers should ask: “Are Section 232 measures on imported steel working to improve their conditions?” In considering this question, it is important to understand that the effectiveness of relief has been undermined by considerable “leakage” from Commerce-granted exclusions and broad countrywide exclusions that have curtailed tariff coverage on imported steel. Nevertheless, our analysis demonstrates that Sec. 232 measures remain critical to the long-term prospects of U.S. steel producers. A survey of publicly available sources reveals that following implementation of Sec. 232 measures, U.S. steel producers announced new investments, upgrades, plant expansions, and reopenings of idled facilities in at least 15 states, including plans to invest more than $15.7 billion in new or upgraded steel facilities, creating at least 3,200 direct new jobs, many of which are now poised to come online (see Appendix Table 1A). In addition, more than $5.9 billion was invested in plant acquisitions by nine firms, as part of industry restructuring to increase efficiency, preserving additional jobs at those facilities (see Appendix Table 1B).8

Individual anecdotes provide a suggestive initial glimpse at the effects of Sec. 232 steel import measures. But a more systematic assessment of available data demonstrates that the import measures coincided with improving conditions for U.S. producers—prior to the pandemic-related global recession beginning in 2020. Relief from the pressure of anti-competitive steel imports facilitated recovery of industrywide sales margins (a measure of profitability), production and capacity utilization rates, and a resurgence of new investment in steel industry fixed assets. Importantly, as discussed in the next section, these measures achieved improvements for U.S. steel producers without causing harm to downstream consumers of steel products in the United States.

From the trough of the Great Recession in 2009, U.S. steel imports rose sharply from 14.7 MMT to 40.2 MMT by 2014, as seen in Figure C. A series of nearly 69 new anti-dumping and countervailing duty determinations between 2014 and 2016 curbed the inflow of steel imports to 30 MMT in 2016—temporarily (USITC 2021).9 However, many foreign producers evaded these import surge measures by relocating steel production and processing to third countries, and imports climbed once again, reaching 34.5 MMT in 2017. But the Sec. 232 measures successfully slowed the pace of imports in 2018 and 2019, when imports fell to just 25.3 MMT. Overall, the volume of steel imports fell 27% between 2017 and 2019—before the pandemic’s “Great Lockdown” slowed U.S. and global economic activity. Separate data analysis shows that import penetration of the U.S. steel market fell to 26% of all steel consumed in the United States in 2019, from 35% in 2017. As a result, the rate of capacity utilization for U.S. steel producers rose to 80% in 2019 from 72% in 2017 (WSA 2020a; OECD 2020a). Commerce (BIS 2018) found that an 80% capacity utilization, sustained over the business cycle, is a critical threshold for U.S. steel producers to achieve long-term financial viability.

Figure C

Sec. 232 measures placing tariffs and quotas on foreign steel products were intended to create some breathing room for U.S. steel producers to recover market share and sustainable financial conditions enabling them to increase domestic production—which they did. The Sec. 232 measures have afforded the U.S. steel industry an opportunity to recover to a level of financial performance not experienced since before the Great Recession (Figure D), although this recovery has been undermined as exemptions from Sec. 232 measures allowed “leakage” of uncovered imports, and as recession from the pandemic’s 2020 Great Lockdown set in. Following the Great Recession of 2007–2009, U.S. steel producers strained to achieve profitability. From the third quarter of 2009 through 2016, net income for the U.S. steel industry averaged just $73 million. Over the same period, net income as a share of sales—a measure of profitability—averaged 0%. In 2018, the year Sec. 232 measures were first imposed, net income in the steel industry reached $7.9 billion, or 6.4% of sales—its highest level since the real estate construction boom that preceded the Great Recession. Since then, however, the domestic industry has faced serious challenges. In 2019, the industry’s net income receded to $2.9 billion, and in 2020 it sunk back into negative territory, posting losses with the pandemic-induced global recession.

Figure D

U.S. steel producers recovered with the Sec. 232 measures, bringing idled capacity back online with expectations for improving market conditions. However, more recently, the erosion of import coverage under Sec. 232 measures has coincided with declining prices and financial performance in the industry. Although the Sec. 232 measures initially covered all steel imports, Commerce has granted nearly 108,000 product exclusion requests from Sec. 232 measures as of July 2020 (CRS 2020; U.S. Department of Commerce 2021). A number of significant steel-producing countries, including Argentina, Brazil, Canada, Mexico, and South Korea, also obtained outright exemptions from Sec. 232 measures or quantitative quotas to replace import tariffs. These exclusions and exemptions significantly curtailed the coverage of Section 232 measures, although the measures remain significant in reversing the trend of declining viability of the U.S. steel industry. Today, a majority of steel products are imported to the United States either on a duty-free basis or under Sec. 232 product exclusions.

The U.S. steel industry’s initial recovery under Sec. 232 measures and the expectations of relief from conditions of chronic global excess capacity helped draw new investments into U.S. steel production (Figure E). New investment, adjusted for inflation, surpassed $5 billion in 2018 and reached nearly $5.9 billion in 2019. However, the dwindling coverage of Sec. 232 measures mentioned above and resulting decline in net income seen in Figure D will make it difficult for the industry to sustain this investment trend and could put many producers in further financial jeopardy. As discussed earlier, capital-intensive investments to upgrade and expand production are long-lived fixed costs that only can be reversed at prohibitively high cost. Firms that have made substantial new investments under the expectations of strong domestic demand and continuing Sec. 232 import relief may be deterred from future investments in technological upgrading and be squeezed by debt service commitments; those exploring expansion will likely shelve their plans.

Figure E

Despite a 25% tariff, the Sec. 232 measures had a limited effect on U.S. import prices of steel products, as seen in Figure F. The product categories in Figure F represent roughly three-fourths of total U.S. steel imports. Unit prices for imports of most steel products increased from 2017 to 2018—the year Sec. 232 import measures began. But then, import prices fell in 2019 and again in 2020, such that overall, averaged across all products, the import price of steel fell to $833 per metric ton in 2020 from $845 per metric ton in 2017.

Figure F

Sec. 232 import measures coincided with and contributed to an increase in prices for steel products in the U.S. market, as can be seen in Figure G, comparing prices paid to domestic steel producers relative to those paid by U.S. steel consumers purchasing comparable products on international markets for import. Unsurprisingly, both U.S. producer and import prices follow a common trend, although imports generally are lower priced than U.S.-made steel, as excess capacity and trade-distorting foreign government policies depress global prices. As the world emerged from the Great Recession in July 2009, particularly with China’s outsized stimulus investments in infrastructure and real estate construction (Hersh 2014), steel prices around the world began rising sharply. Steel demand was so strong that it pushed up prices for key steel inputs globally, including iron ore and coal (World Bank 2020). Then, as discussed in Section 2 above, expanded world steel production and surplus capacity through the middle of the last decade began driving prices down.

Figure G

Following implementation of Sec. 232 measures, Figure G shows domestic steel prices rose faster than U.S. import prices. This is due to a combination of the Sec. 232 measures, other trade remedies—including anti-dumping and countervailing duty orders—and the appreciation in value of the U.S. dollar relative to foreign currencies, making foreign products comparatively less expensive in dollar terms. These factors drove a wedge between domestic and foreign prices, which enabled U.S. steelmakers to achieve more sustainable operating margins. As input prices again eased in late 2018, steel prices fell in the U.S. market and globally—although they likely would have fallen further were it not for Sec. 232 import measures.

In recent months, U.S. and foreign steel prices are on the upswing—likely a temporary phenomenon caused by the lag between increasing demand as parts of the world economy recover from the Great Lockdown and the re-employment of steelmaking capacity—which, for blast furnace operations in particular, can take time and may occur only after market conditions create confidence that a facility can operate at a high level of capacity for a sustained period. In this environment, maintenance of Sec. 232 import measures will remain critical to ensuring the economic stability and financial viability of the U.S. industry. Country- and product-specific trade remedies, though significant, on their own have proven insufficient to abate the risk to the U.S. steel industry from anti-competitive imports and chronic excess production capacity.

Steel consumers face negligible effects from Section 232 measures

An important concern in assessing the impacts of Sec. 232 measures on imported steel products is how these measures affect downstream industries and consumers of products that use steel inputs. Indeed, as Sec. 232 measures were going into effect, a group of business lobbying associations representing downstream users sent a joint letter to the U.S. Trade Representative expressing this concern and claiming “significant harm” from this policy (Industry Week 2018). Our analysis in this section shows this claim proved incorrect.

Critics of import measures more broadly, including those levied in 2018 against China for unfair trade practices pertaining to technology transfer, intellectual property, and innovation (USTR 2018), often point to a recent Federal Reserve study purporting to find that tariffs are associated with negative outcomes for the U.S. manufacturing sector (Flaaen and Pierce 2019). However, this analysis should be treated with a healthy dose of skepticism due to myriad methodological issues that introduce statistical bias and call into question the validity of their findings.10 Weaknesses of Flaaen and Pierce’s (2019) results are illustrated in their own Figures 4 and B3, which demonstrate that import protection has no statistically significant impact on manufacturing employment, industrial output, or producer prices for virtually all of the period under consideration.

Given the inherent shortcomings of Flaaen and Pierce 2019, we implement an empirical strategy focused more narrowly on steel products and explicitly evaluating the causal effect of changes in the price of steel inputs on the prices of goods using steel. Our econometric analysis demonstrates that this relationship ranges from statistically insignificant (i.e., not statistically different from zero effect) to negligible. In other words, the statistical evidence does not support claims of harm from Sec. 232 measures that were predicted by certain steel-using businesses. This fact should not be surprising: Even in the downstream industries consuming the most steel, steel inputs amount to a minor share of overall production costs.

Harm to downstream industries would occur if Sec. 232 measures significantly increased steel prices, causing increased costs for producers or consumers of primary steel-containing goods, and then those costs squeezed profit margins or consumer welfare—by forcing consumers to either pay more for or consume less of a given product. To assess this linkage between steel input prices and end-user prices, we employ standard, related, and time-tested econometric techniques known as Granger causality analysis and vector autoregression (Granger 1969; Sims 1980). Vector autoregression (VAR) is a statistical method for modeling a system of variables and their interrelationship and co-evolution over time. In this case, we model (1) the price of primary steel inputs, (2) the price of steel-consuming products, and (3) the effective federal funds rate.11

Granger causality analysis uses the VAR model to test for evidence of a statistically causal relationship between the variables in the model. If past values of variable 1 are shown to significantly predict current values of variable 2, then it can be concluded that variable 1 “Granger-causes” variable 2. While the price variable used in this modeling includes the effects of Sec. 232 tariffs and quotas, the results of the statistical test are not limited to the effects of Sec. 232 measures, but rather evaluate whether a change in prices resulting from any factor causes a change in the price of the steel-using good. Technical discussion of this methodology and detailed results are presented in Appendix 2.

We summarize the results of this causal analysis in Table 1. Each row of the table presents a separate VAR model relating the price of a steel-containing product with the price of its most relevant primary steel input(s) and reports the causal effect found on end-use product prices. The end-use products investigated represent the U.S. industries consuming the largest volume of steel products: nonresidential construction, motor vehicles, motor vehicle parts, construction machinery, electrical equipment and household appliances, and food processing (food consumed at home). We also evaluate the possible impacts of Sec. 232 steel measures at a broader level by modeling the effects of steel product prices on aggregated prices for durable goods.

As shown in Table 1, this analysis finds no discernible effect of steel prices causing price changes in new motor vehicles, motor vehicle parts, construction machinery, electrical equipment and household appliances, or, broadly, durable goods. These results, therefore, suggest that even if Sec. 232 measures caused an increase in the price of steel products, one would not expect a significant impact on the price of downstream goods. For prices of nonresidential construction goods and food consumed at home, the price of relevant steel inputs is found to be statistically significant in causing changes in the prices of steel-using products.12 While finding a statistical relationship between steel input prices and final goods prices, the same analysis shows that the economic significance of the impact is negligible: A 1% increase in steel input prices caused a 0.1% change in the price of construction goods and a less than 0.05% change in the price of food at home. However, as discussed in Appendix 2, causal analysis suggests the relationship between steel inputs and construction goods actually runs in the opposite direction, with demand for construction goods driving prices in the market for intermediate inputs.

Table 1

To recap, while conceptually a relationship exists between input prices and final goods prices, econometric analysis of the causal relationship between prices finds effects ranging from statistically zero to essentially nothing. Sec. 232 measures simply did not have a meaningful, real-world impact on prices for steel-consuming products. This fact should not be surprising. Even in the industries that consume the largest volumes of steel products, steel is just one cost in a long list of inputs to production. Despite these industries accounting for the lion’s share of steel consumption in the U.S. economy, the cost of their steel inputs is minor relative to their gross production. As shown in Table 1, the steel content as a share of total production ranges from 1% in food consumed at home to 9.8% in the motor vehicle parts industries. Illustrating the point in dollar terms, the average passenger car contains roughly 900 kg of steel (WSA n.d.). At a current cost of $1,048 per metric ton, the steel inputs amount to just 2% of the sales price for the average new U.S. car (Steel Benchmarker 2020; Kelley Blue Book 2020). In contrast, electronics components make up roughly 40% of a new car’s price (Deloitte 2019).

Retreating from Section 232 measures would squeeze vulnerable producers, increase greenhouse gas emissions

Thus far, we have seen that Sec. 232 import measures have helped improve market conditions for U.S. steel producers amid chronic global excess capacity that threatens their financial viability. We also have seen that the impact of these measures on steel-consuming U.S. industries has ranged from zero to economically insignificant. Furthermore, the benefits of this policy have eroded since it began as more steel imports have been exempted from the Sec. 232 regime. As the world looks to move forward from the economic shock of the Great Lockdown caused by COVID-19, it is clear that eliminating or even further relaxing the steel import measures likely would pose serious economic consequences for U.S. steel producers. Two important points are noteworthy here.

First, a slow and uneven recovery from the 2020 economic downturn is expected, with global demand for steel products uncertain. The International Monetary Fund (IMF) recently revised down its global economic growth forecast for 2021; it projects “limited progress toward catching up to the [expected] path of economic activity for 2020–2025” (IMF 2020).13 Families around the world have suffered deep economic scarring from lost jobs and income and depleted savings—not to mention, tragically, the many who have lost prime wage-earners. Millions of people worldwide who contracted the virus are likely to suffer long-term effects, reducing prospects for employment and earnings and allocating a larger share of disposable income toward health care services and away from goods consumption. At the same time, the downturn and its long-lasting effects have dampened public-sector revenues at a time when governments have undertaken unprecedented expenditures meeting the public health crisis and providing social protections. The enduring effects of this shock will dampen, in the near term, a recovery of household consumption and, in turn, business investment. In the longer term, the human toll will dampen prospects for economic potential, dragging down investments in human and fixed asset capital and the productivity growth these investments provide.

Economic recovery, of course, is contingent on how well world governments abate the global health crisis, but it is clear that even under optimistic scenarios, demand for steel production will remain muted for some time. U.S. steel demand declined 16% in 2020, and in 2021 it is expected to remain more than 10% below 2019 levels (WSA 2020c). Globally, steel demand declined 6.4% from 2019 to 2020 and is forecast to remain nearly 3% below 2019 levels (OECD 2020c). At the same time, countries have not retreated from policy efforts to prop up national steel industries (see text box, “Widespread government interventions drive unfair trade in steel products”) and are continuing to install additional productive capacity. The OECD (2020b) projects that by 2022, producers will add as much as another 3% of steelmaking capacity worldwide, concentrated in Asia and the Middle East.

Together, these trends point to increased excess steelmaking capacity and lower capacity utilization rates that would drive prices down and squeeze U.S. steel producers who face competition with imports produced on a noncommercial basis. These are exactly the pressures Sec. 232 measures are designed to address, in the absence of multilateral agreements to manage excess capacity. Retreating from these measures now, particularly after many U.S. companies committed to new investments in production (Figure E; Appendix 1), would leave U.S. steel producers in untenable financial positions, further jeopardizing their capacity to meet national security needs.

Second, a significant ancillary benefit of Sec. 232 import measures has been to divert steel production to more environmentally sustainable producers. Relaxing Sec. 232 measures would reverse this progress as the world looks to decarbonizing and achieving net-neutral emissions by midcentury. The U.S. steel industry is one of the cleanest and most energy-efficient steel industries globally. A 2019 report measuring the CO2 emissions intensity of steel industries in 15 major steel-producing countries ranked U.S. steelmakers among the least CO2 intensive industries—with industries in Brazil, Canada, China, France, Germany, India, Japan, South Korea, and other countries having higher CO2 emissions intensity (Hasanbeigi and Springer 2019, Figure 14).

Even this analysis understates that difference in environmental impact, as it does not account for the substantial pollution from ocean freight required to transport raw materials and finished products in supply-chain webs around the world before foreign steel products can reach the U.S. market (ENVI 2020). If Sec. 232 measures are relaxed, it is precisely the most polluting national steel industries, in countries that have rapidly expanded capacity at the expense of more efficient producers, that stand to capture marginal changes in market share. And as excess capacity further squeezes prices and profit margins, firms will face difficulty investing in new technologies to allow for greener steel production and will risk being shut out of markets as consumers develop preferences for low-carbon products.

Conclusion: The Section 232 trade measures helped slow the flood of unfair imports that was squeezing the U.S. steel industry without hurting downstream steel-using producers and consumers

Surging steel imports have undermined domestic steel production, prices, employment, profits, investments, and the fundamental health of the U.S. domestic steel industry. Global steel surpluses are the result of chronic global excess steelmaking capacity in major exporting countries. The steel Section 232 trade restraints imposed in 2018, including both tariffs and quotas on imports from selected countries, helped slow the flood of steel imports. Following imposition of these measures, U.S. steel output, employment, capital investment, and financial investment all improved.

Meanwhile, statistical analysis in this report has demonstrated that Section 232 measures have had no economically significant impacts on the prices of downstream products. Despite the benefits of the Section 232 tariffs for the domestic steel industry and its workers, and the minimal impacts of trade restraints on downstream industries, these measures have been progressively weakened by nearly 108,000 product-specific exclusions and broad tariff exemptions for a number of countries.

The domestic steel industry is just beginning to emerge from the depths of the COVID-19 recession with a steep hill to climb, given widening excess global steel capacity. With the right policies and major investments planned by the new administration in economic rebuilding, clean energy, and infrastructure construction, U.S. steel producers can be poised for a substantial upswing in employment, output, and investment that fuels growth in clean, efficient, state-of-the-art domestic steel production. The window to this opportunity could be slammed shut by the premature and unplanned elimination of the Section 232 import measures.

Acknowledgments

The authors thank Jori Kandra for technical and research assistance and Colleen O’Neill and Lora Engdahl for editing assistance. This research was made possible by support from the Partners for American-made Steel.

About the authors

Adam S. Hersh, Ph.D., is director of Washington Global Advisors, LLC, and a research associate at the Political Economy Research Institute, University of Massachusetts Amherst. Hersh was formerly chief economist for the Congressional Joint Economic Committee, Democratic staff; senior economist at the Franklin and Eleanor Roosevelt Institute and the Center for American Progress; a visiting scholar at Columbia University’s Initiative for Policy Dialogue and the Shanghai University of Finance and Economics; and a research fellow at the University College, London’s Institute for Innovation and Public Purpose. He is a contributing author with Joseph Stiglitz of Rewriting the Rules of the American Economy: An Agenda for Growth and Shared Prosperity (2015).

Robert E. Scott joined the Economic Policy Institute in 1996 and is currently director of trade and manufacturing policy research. His areas of research include international economics, trade, and manufacturing policies and their impacts on working people in the United States and other countries, the economic impacts of foreign investment, and the macroeconomic effects of trade and capital flows. He has published widely in academic journals and the popular press, including The Journal of Policy Analysis and Management, The International Review of Applied Economics, and The Stanford Law and Policy Review, as well as The Los Angeles Times, Newsday, USA Today, The Baltimore Sun, The Washington Times, and other newspapers. He has also provided economic commentary for a range of electronic media, including NPR, CNN, Bloomberg, and the BBC. Mr. Scott has a Ph.D. in economics from the University of California, Berkeley.

Endnotes

1. 19 U.S.C. §1862; https://www.law.cornell.edu/uscode/text/19/1862.

2. Adjusting Imports of Aluminum Into the United States, 83 Fed. Reg. 25849–25855 (March 15, 2018).

3. Adjusting Imports of Steel Into the United States, 83 Fed. Reg. 25857–25877 (March 15, 2018).

4. The capital-to-labor ratio for primary metals producers is 76% higher than for durable goods manufacturing industries overall. See BLS (2020).

5. This section is based, in part, on information summarized in Examples of Policies and Practices Contributing to the Global Excess Capacity Crisis, a report by the American Iron and Steel Institute and the Steel Manufacturers Association included at the end of this report.

6. There are two anti-dumping orders in place against Canadian steel products, and there are both anti-dumping and countervailing duty orders in place against wind towers, a major steel-using product. South Korean steel orders include six countervailing duty orders and 26 antidumping orders. EPI analysis of USITC (2021).

7. Countries receiving Chinese direct foreign investment in steel include Cambodia, Malaysia, Indonesia, Myanmar, Pakistan, the Philippines, Bolivia, Vietnam, the United Kingdom, and the Netherlands. See OECD (2020b).

8. These are direct steelmaking jobs; the investments would also generate indirect employment through the goods and services procured in expansion products, as well as induced employment generated by the incomes from direct and indirect employees.

9. The USITC (2021) lists 276 anti-dumping and countervailing duties in effect on steel products (categories ISM, ISO, and ISP) as of December 28, 2020, and of those, 69 orders went into effect between 2014 and 2016.

10. It is worth briefly considering several reasons why. First, the core explanatory variable—“import protection”—ignores the actual incidence and evolution of protection over time as more products received exclusions from tariffs. Second, their statistical model explicitly embraces violations of the core assumptions on which the statistical method is built, biasing the results. In particular, equation 7 specifies measures of import protection, input costs, and foreign retaliation as “independent” variables associated with the dependent variables of manufacturing employment, output, and producer prices. In fact, as Flaaen and Pierce appropriately theorize, input costs and foreign retaliation are, at least in part, caused by import protection. Finally, Flaaen and Pierce’s analysis conflates the effects of Sec. 232 import measures with Sec. 301 trade remedies. Conditions of chronic excess global steel capacity—explained in Section 2 above—mean that market conditions are significantly different for steel products than for other manufactured goods, suggesting that pooling data for steel products and other manufactured goods more broadly is inappropriate and may bias estimates of the statistical significance.

11. The federal funds rate—the interest rate at which depository institutions borrow and lend federal balances held at Federal Reserve Banks—is the primary target for Federal Reserve monetary policy actions and is linked both in theory and in practice to changes in price levels as well as to the level of demand for goods and services across the economy.

12. The causal effect of steel prices on food-at-home prices shows only weak statistical significance, at the 90% probability threshold; the model for other significant goods found 95% to 99% probability.

13. What’s more, as dour as the IMF’s assessment is, their forecasts are notorious for being overly optimistic. See Rosnick and Weisbrot (2007).

14. Producer Price Index by Commodity: Metals and Metal Products: Iron and Steel (WPU101); Producer Price Index by Commodity: Metals and Metal Products: Cold Rolled Steel Sheet and Strip (WPU101707); Producer Price Index by Commodity: Metals and Metal Products: Hot Rolled Steel Sheet and Strip, Including Tin Mill Products (WPU101703); Producer Price Index by Commodity: Metals and Metal Products: Hot Rolled Steel Bars, Plates, and Structural Shapes (WPU101704); Producer Price Index by Commodity: Metals and Metal Products: Steel Wire (WPU101705); Consumer Price Index for All Urban Consumers: New Vehicles in U.S. City Average (CUUR0000SETA01); Producer Price Index by Commodity: Transportation Equipment: Motor Vehicles Parts (WPU1412); Producer Price Index by Industry: Construction Machinery Manufacturing (PCU333120333120); Producer Price Index by Commodity: Inputs to Industries: Net Inputs to Nonresidential Construction, Goods (WPUIP2312001); Producer Price Index by Industry: Electrical Equipment and Appliance Manufacturing (PCU335335); Consumer Price Index for All Urban Consumers: Food at Home in U.S. City Average (CUSR0000SAF11); Personal consumption expenditures: Durable goods (chain-type price index) (DDURRG3M086SBEA); and Effective Federal Funds Rate (FEDFUNDS).

15. Motor vehicle parts manufacturing requires significant inputs from both hot-rolled sheet and strip as well as hot-rolled bars, plates, and structural shapes. Electrical equipment and household appliances require significant inputs from both cold-rolled sheet and strip and carbon steel wire. Therefore, these products are modeled as a four-equation VAR of the form

where and are 4 × 4 matrices of coefficients.

Appendix 1: New and expanded U.S. steel production under Section 232 measures capacity

Appendix Table 1A

Appendix Table 1B

Appendix 2: Methodology for analyzing causal relationship between steel prices and steel-consuming industries

This appendix outlines the methodological approach for assessing how Sec. 232 measures on imported steel products may affect downstream industries and consumers of products that use steel inputs. Harm to downstream industries and consumers could occur if Sec. 232 measures caused an increase in prices for steel products paid by U.S. users of steel and if those price increases were passed through to producer or consumer prices for steel-embodying goods. In order to assess this possibility, we evaluate a more basic question: Do changes in prices of basic steel products cause changes in steel-using products? This question asks whether any change in steel prices is a significant determinant of goods prices that use steel as an intermediate input, irrespective of what factors cause a change in steel prices.

Data and methodology

To evaluate this question, we estimate reduced-form vector autoregressions (VARs) that model the variables of interest as an interrelated system that co-evolves over time (Sims 1980). The VAR is an attractive analytical tool because it does not force an assumed structural form onto the data. Each variable in the system is modeled jointly as a function of its past values and the past values of the other related variables in the system. After estimating the system, we can evaluate causal relationships between the variables by testing whether past values of one variable are statistically significant determinants of the current value of another variable, following Granger (1969).

Our variables of interest are (1) prices for steel products, (2) prices for steel-using products, and (3) the effective federal funds rate—the interest rate at which depository institutions borrow and lend reserve balances held at Federal Reserve Banks.14 This interest rate is the primary target for Federal Reserve monetary policy actions and is linked both in theory and in practice to changes in general price levels, as well as to the level of demand for goods and services across the economy via the Taylor Rule (Taylor 1993). Data are observed monthly and drawn from the Federal Reserve Bank of St. Louis’s FRED Economic Data, spanning December 2001 to January 2020, or two business cycle expansions, other than for steel wire, for which available data begin in July 2004. Univariate analysis with a modified Dickey-Fuller test (Cheung and Lai 1995) fails to reject the null hypothesis of a unit root for each variable under consideration. While the individual variables are nonstationary (integrated of order one, or first-difference stationary), tests with Johansen’s procedure show that there is no cointegration—or a stable, long-run relationship—between the variables (Johansen 1995), and the system can be modeled with a VAR, as opposed to a vector error correction model.

The VAR model consists of

where   is the natural log of price at time of the relevant steel product input price,   is the natural log of the price of the steel-using product, and is the natural log of the effective federal funds interest rate. The pairings of steel product input prices and steel-using product prices are given in Section 4, Table 1.15 The model estimates parameters , to , and , which are, respectively, a vector of constant terms, 3×3 matrices of coefficients relating the current dependent variable to past values of the independent variables, and a vector of randomly distributed residual with mean zero and uncorrelated across time.

The specific number lags of the dependent and independent variables specified varies for each set of steel product and steel-consuming goods modeled, and they are chosen with some subjectivity, though guided by minimizing a battery of statistical tests, including the likelihood ratio test, the final prediction error, Akaike’s information criterion, Schwarz’s Bayesian information criterion, and the Hannan and Quinn information criterion (Neilsen 2001; Lütkepohl 2005). Results were robust to alternative lag-length specifications. The VAR parameters were estimated simultaneously by the “seemingly unrelated regression” method of Zellner and Theil (1962). Post-estimation, the statistical assumptions were tested to confirm that the VAR parameters are stable (with eigenvalues lying within the unit circle), and that the residual is normally distributed and not serially correlated, indicating that the models are well-specified.

The specific parameters estimated that define the structures of VARs are typically of less concern than how the system behaves when there is an exogenous change in one of the variables. In this case, we are concerned whether a change in the price  causes a change in , evaluated with a Granger (1969) causality test. This evaluates the hypothesis that the coefficients on are jointly statistically significant in determining  against the null hypothesis that the coefficients are all equal to zero. If the test statistic exceeds a critical value at a 95% probability or higher, we can reject the null hypothesis and conclude that Granger-causes . In the event we identify a significant causal relationship, then the system of equations making up each VAR can be used to simulate the effect on of a shock to  by simulating an impulse response function.

Results

Appendix Table 2 reports the Wald test statistic χ² and the associated probability for rejecting the null hypothesis of zero causal effect for each pair of prices. For the majority of end-use products considered, we find no statistical evidence that steel input prices affect the price of end-use products (<95% probability). This means that a change in steel prices is expected to have no effect on the price of end-use goods. We do find statistically significant causal effects (>95% probability) of steel input prices on the prices of nonresidential construction goods and food at home.

Appendix Table 2

For end-use goods experiencing a causal effect of steel prices, we estimate the impact of a 1% increase in steel input prices using an orthogonalized impulse response function, with results summarized in the final column of Appendix Table 2. For each end-use good, the shock from an initial change in steel prices reaches its maximum impact on end-use prices in the following one to two months, then gradually dissipates to zero over the ensuing months, meaning there is no permanent effect on prices.

These were not the only statistically significant causal relationships identified in the VAR modeling. In a majority of the models, Granger analysis finds that the effective federal funds rate has a causal effect on steel product price levels, as theory would predict. We also find that prices of nonresidential construction goods have a causal effect on prices of hot-rolled bars, plates, and structural shapes—more than five times the size of the effect of hot-rolled bar prices on nonresidential construction goods—suggesting that demand for construction projects leads demand, and therefore pricing, of intermediate inputs to construction.

Appendix 3: Countries of concern—examples of policies and practices contributing to the global excess capacity crisis

Interventionist policies by governments around the world have driven a buildup of excess steel production capacity. Because China is the largest source of global excess steel capacity, the crisis is frequently mischaracterized as “just a China problem.” However, as a report from the American Iron and Steel Institute and the Steel Manufacturers Association shows, numerous countries contribute to global overcapacity through state interventions that commonly include: the provision of low-cost inputs, subsidized loans and equity infusions, grants, tax breaks, support for acquisition of overseas raw materials, export restraints on domestically produced raw materials, state-led debt restructuring and other corporate reorganizations, local content requirements, transnational subsidies for establishing third-country operations, and other measures that forestall the exit of inefficient capacity. Read the report, Examples of Policies and Practices Contributing to the Global Excess Capacity Crisis, to learn how global steel overcapacity is fueled by government policies in South Korea, Japan, Vietnam, Indonesia, the Russian federation, Brazil, the Netherlands, Germany, the United Kingdom, Italy, Canada, and Mexico.

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On Monday, the Supreme Court heard oral arguments in this dispute: In Cedar Point Nursery v. Hassid, two agricultural employers are challenging the 1975 California regulation that allows union representatives to visit private farms. The case could have implications for union organizing across the country.

If the challenge by the employers is successful, it will keep the United Farm Workers (UFW) away from their employees, so they won’t be able to organize them. Such a restriction would be particularly egregious given the harsh working conditions farmworkers face and given that a growing share are temporary migrant workers with H-2A visas who live in housing that is either owned or controlled by their employers.

Farmworkers are employed in one of the most hazardous and lowest paying jobs in the entire U.S. labor market, a fact that isn’t often mentioned in the mainstream coverage. As research I coauthored has shown, farmworkers suffer very high rates of wage and hour violations, yet the number of inspections of agricultural employers has been cut in half in recent years, likely due to the U.S. Department of Labor being perennially underfunded by Congress. Since farmworkers are one of the most vulnerable groups in the U.S. workforce, they would benefit enormously from joining a union.

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