Date: 2024-10-31 Page is: DBtxt003.php txt00019368 | |||||||||
Economy / Economics | |||||||||
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Burgess COMMENTARY Peter Burgess | |||||||||
| We can reshore manufacturing jobs, but Trump hasn’t done it Trade rebalancing, infrastructure, and climate investments could create 17 million good jobs and rebuild the American economy Report • By Robert E. Scott • August 10, 2020 EPI Policy Center Download PDF Press release While the Trump administration has claimed that the era of U.S. offshoring is “over,” the reality is that the United States has not begun to address the root causes of America’s growing trade deficits and the decline of American manufacturing. Decades of trade, currency, and tax policies that incentivized offshoring, combined with an utter failure to invest adequately in infrastructure and good jobs at home, have contributed to growing inequality and an eroding middle class. President Trump’s erratic, ego-driven, and inconsistent trade policies have not achieved any measurable progress, despite the newly combative rhetoric. On top of that, COVID-19—and the administration’s mismanagement of the crisis—has wiped out much of the last decade’s job gains in U.S. manufacturing. Unless steps are taken now—to reform our trade policy, to curb dollar overvaluation, to eliminate tax incentives for offshoring, and to rebuild the domestic economy—there won’t be a comeback. As this policy report makes clear: Offshoring and the loss of manufacturing plants have continued under Trump, notwithstanding U.S. Trade Representative Robert Lighthizer’s claim that the administration’s trade policy is helping U.S. workers (Lighthizer 2020a). The strong and rising U.S. dollar is a major cause of the continuing growth of U.S. trade deficits. While manufacturing employment rose steadily between 2010 and 2019, the COVID-19 shutdown has wiped out more than half of the jobs gained in the past decade. The U.S. economy is in the midst of a historic collapse due to the uncontrolled coronavirus pandemic and recession. Restructuring and rebuilding the economy will require a coordinated and comprehensive strategic policy response that includes rebalancing of U.S. trade, as well as massive public investments in infrastructure, clean energy, training, R&D, and other industrial policies. These investments can create millions of skilled, high-wage jobs for non-college-educated workers in the U.S., who have been hard hit by the coronavirus downturn—especially Black, Latinx, and women workers—who have been left behind as manufacturing employment shrinks. Under current government procurement policies and trade rules, much of the public spending for infrastructure and clean energy systems would leak away to foreign providers, in the form of increased imports. Thus, new public investments should all include strong “Buy America” clauses. Joe Biden has recently proposed major investments in infrastructure, climate, and rebuilding manufacturing. These proposals could make a substantial contribution to meeting U.S. investment needs and generating a strong, sustainable, broadly shared recovery. The Trump administration has not succeeded in reshoring manufacturing In recent congressional testimony, U.S. Trade Representative Robert Lighthizer praised several companies that have scrapped offshoring efforts or have announced plans to move production to the United States, and he has further claimed that the “era of reflexive offshoring is over” (Lighthizer 2020b, 2020c). He also praised both the U.S.-Mexico-Canada Trade Agreement (USMCA)—which took effect July 1—and the current “Phase One” China trade deal. These are supposed to be signature accomplishments for the administration, contributing to a purported “blue-collar boom.” It is important to note that the Trump administration has a habit of issuing press releases citing plans for major foreign investments in the U.S. that never materialize. In July 2017 Foxconn announced—to great fanfare from the White House–plans to invest $10 billion and bring “thousands of new American jobs” to Wisconsin and elsewhere in the United States (White House 2017). News reports indicate that Foxconn’s buildings in Wisconsin were still empty as of April 2020 (Dzieza and Patel 2020).1 But offshoring has in fact continued throughout this time, as reflected in changes in the total number of U.S. manufacturing plants, shown in Figure A. Overall, the U.S. has suffered a net loss of more than 91,000 manufacturing plants and nearly 5 million manufacturing jobs since 1997. Nearly 1,800 factories have disappeared during the Trump administration between 2016 and 2018 (BLS 2020; U.S. Census Bureau 2020a, 2020b). The U.S. has experienced a net loss of manufacturing plants (establishments) in every year between 1998 and 2018 (the most recent year for which data are available). FIGURE A More than 5 million manufacturing jobs and 91,000 plants have been lost since 1998 Change in number of manufacturing establishments (actual), and change in manufacturing employment (thousands), 1998–2018 Change in number of establishments Change in employment (thousands) 1998 -578 297 1999 -3,835 -269 2000 -3,606 -66 2001 -4,712 -364 2002 -6,665 -1495 2003 -8,155 -722 2004 -4,904 -434 2005 -2,231 -18 2006 -1,447 -55 2007 -2,849 -244 2008 -5,943 -311 2009 -13,551 -1451 2010 -11,283 -755 2011 -5,515 222 2012 -2,938 223 2013 -4,220 101 2014 -4,056 121 2015 -2,129 192 2016 -999 33 2017* -782 50 2018* -1,005 216 297 -269 -66 -364 -1,495 -722 -434 -18 -55 -244 -311 -1,451 -755 222 223 101 121 192 33 50 216 -578 -3,835 -3,606 -4,712 -6,665 -8,155 -4,904 -2,231 -1,447 -2,849 -5,943 -13,551 -11,283 -5,515 -2,938 -4,220 -4,056 -2,129 -999 -782 -1,005 Change in number of establishments Change in employment (thousands) 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017* 2018* ChartData Note: *Establishment estimates for 2017 and 2018 are from analysis of the U.S. Census Bureau County Business Patterns data for 2016–2018, compared with U.S. Census Bureau Business Dynamics Statistics data for 1997–2016. Sources: Employment numbers: EPI analysis of Bureau of Labor Statistics (BLS) Current Employment Statistics establishment employment data. Establishment numbers: EPI analysis of U.S. Census Bureau Business Dynamics Statistics data for 1997–2016 and U.S. Census Bureau County Business Patterns data for 2016–2018. Share Tweet Embed Download image Employment per plant has ebbed and flowed, increasing during recoveries and dropping much more sharply in downturns, as shown in Figure A. Massive job losses in just six years—during the 2001 recession and the China import surge of 2002–2004, and during the Great Recession of 2008–2009—account for more than all of the net loss of nearly 5 million manufacturing jobs in this period. The loss of these jobs was particularly costly for women, Black, and Latinx workers, who were left behind as employment collapsed and many of the remaining manufacturing plants shifted to rural locations in right-to-work states in the West and South (Madland, Walter, and Eisenbrey 2012). Here’s what the data actually show about the purported “blue-collar boom” under the Trump administration: The U.S. gained roughly 500,000 U.S. manufacturing jobs from 2016 to 2019. But these gains are exactly on par with gains across the entire economic recovery period from 2010 to 2019, during which 166,000 manufacturing jobs were gained each year, on average. The 2016–2019 gains did not represent an improvement over prior years in that decade, and even the decade’s overall gains had managed to restore only a fraction of the jobs lost in the prior decade. And recent years’ manufacturing gains were abruptly wiped out by the COVID-19 crisis—with a staggering 740,000 manufacturing jobs lost this year, as shown in Figure B (BLS 2020). If President Trump wants to take credit for the job growth at the tail end of a decade of recovery from the Great Recession, then he must also own this collapse, thanks to his administration’s mismanagement of the pandemic—including a refusal to organize an effective national response (Scott 2020b). And while the June 2020 data show an upswing in manufacturing jobs, more recent jobs data indicate that the nascent and partial recovery in manufacturing is at risk due to recurrence of COVID-19 in states that have reopened, including many in the South and Western United States (Hannon and Kiernan 2020; WSJ Pro 2020; Bartash 2020). FIGURE B Manufacturing employment is down 740,000 jobs since February 2020 amid the coronavirus crisis U.S. manufacturing employment (thousands), January 2010–July 2020 Date Total employment, thousands of jobs Jan-2010 11,460 Feb-2010 11,453 Mar-2010 11,453 Apr-2010 11,489 May-2010 11,525 Jun-2010 11,545 Jul-2010 11,561 Aug-2010 11,553 Sep-2010 11,563 Oct-2010 11,562 Nov-2010 11,585 Dec-2010 11,595 Jan-2011 11,621 Feb-2011 11,654 Mar-2011 11,675 Apr-2011 11,704 May-2011 11,713 Jun-2011 11,727 Jul-2011 11,746 Aug-2011 11,764 Sep-2011 11,769 Oct-2011 11,780 Nov-2011 11,770 Dec-2011 11,802 Jan-2012 11,838 Feb-2012 11,860 Mar-2012 11,898 Apr-2012 11,916 May-2012 11,927 Jun-2012 11,936 Jul-2012 11,964 Aug-2012 11,960 Sep-2012 11,954 Oct-2012 11,961 Nov-2012 11,950 Dec-2012 11,960 Jan-2013 11,983 Feb-2013 11,996 Mar-2013 11,999 Apr-2013 12,000 May-2013 12,000 Jun-2013 12,004 Jul-2013 11,984 Aug-2013 12,014 Sep-2013 12,032 Oct-2013 12,056 Nov-2013 12,079 Dec-2013 12,083 Jan-2014 12,081 Feb-2014 12,106 Mar-2014 12,120 Apr-2014 12,134 May-2014 12,146 Jun-2014 12,170 Jul-2014 12,189 Aug-2014 12,208 Sep-2014 12,226 Oct-2014 12,259 Nov-2014 12,284 Dec-2014 12,292 Jan-2015 12,292 Feb-2015 12,301 Mar-2015 12,312 Apr-2015 12,318 May-2015 12,333 Jun-2015 12,334 Jul-2015 12,349 Aug-2015 12,345 Sep-2015 12,354 Oct-2015 12,362 Nov-2015 12,357 Dec-2015 12,362 Jan-2016 12,379 Feb-2016 12,367 Mar-2016 12,345 Apr-2016 12,349 May-2016 12,332 Jun-2016 12,351 Jul-2016 12,369 Aug-2016 12,348 Sep-2016 12,347 Oct-2016 12,347 Nov-2016 12,342 Dec-2016 12,356 Jan-2017 12,369 Feb-2017 12,384 Mar-2017 12,395 Apr-2017 12,400 May-2017 12,406 Jun-2017 12,418 Jul-2017 12,417 Aug-2017 12,461 Sep-2017 12,470 Oct-2017 12,492 Nov-2017 12,514 Dec-2017 12,541 Jan-2018 12,558 Feb-2018 12,588 Mar-2018 12,611 Apr-2018 12,632 May-2018 12,658 Jun-2018 12,687 Jul-2018 12,706 Aug-2018 12,719 Sep-2018 12,740 Oct-2018 12,764 Nov-2018 12,784 Dec-2018 12,805 Jan-2019 12,825 Feb-2019 12,830 Mar-2019 12,827 Apr-2019 12,829 May-2019 12,829 Jun-2019 12,838 Jul-2019 12,845 Aug-2019 12,848 Sep-2019 12,851 Oct-2019 12,810 Nov-2019 12,868 Dec-2019 12,866 Jan-2020 12,844 Feb-2020 12,852 Mar-2020 12,806 Apr-2020 11,489 May-2020 11,729 Jun-2020 12,086 Jul-2020 12,112 Manufacturing employment (thousands) 12,112 2010 2012 2014 2016 2018 2020 11,000 11,500 12,000 12,500 13,000 ChartData Source: EPI analysis of Bureau of Labor Statistics (BLS) Current Employment Statistics (CES) data series [CES3000000001]. Share Tweet Embed Download image Contrary to popular myth, growing trade deficits, and not automation, are responsible for the vast bulk of manufacturing job and plant losses in the past two decades (Guilford 2018). Growing trade deficits with China between 2001 and 2018 (2.8 million manufacturing jobs lost) and the U.S. trade deficit with the Trans-Pacific Partnership countries in 2015 alone (1.1 million manufacturing jobs lost) account for more than three-fourths of the U.S. manufacturing jobs lost in the past 20 years (Scott and Mokhiber 2020; Scott and Glass 2016). This is confirmed by Susan Houseman’s extensive review of the research literature, “which finds that trade significantly contributed to the collapse of manufacturing employment in the 2000s, but finds little evidence of a causal link to automation” (Houseman 2018). The rising dollar is responsible for growing trade deficits U.S. manufacturing was struggling long before COVID-19. Starting in 2014, the U.S. dollar has appreciated in fits and starts, climbing nearly 23%, as shown in Figure C (Fed 2020b). More than half of that rise has come since the Trump tariffs were first imposed in March 2018. This stronger dollar keeps making U.S. exports more expensive and imports cheaper. Equally problematic, the 2017 Trump tax cuts on corporate profits incentivized offshoring for certain types of production while also raising after-tax profits. This has attracted more foreign capital to U.S. stock markets, spurring the dollar even higher. The dollar has also been driven higher during the coronavirus recession by “safe haven” effects, with foreign capital surging into the U.S.—as it does during most global downturns. FIGURE C The real value of the U.S. dollar has risen 22.7% since July 2014 Real value of the U.S. dollar, January 2006 to July 2020 (indexed to January 2006) Date Real Dollar Index, Goods & Services Jan-2006 100 Feb-2006 100.2649 Mar-2006 100.5431 Apr-2006 100.0597 May-2006 97.8741 Jun-2006 99.2033 Jul-2006 99.383 Aug-2006 98.8428 Sep-2006 98.5785 Oct-2006 98.364 Nov-2006 97.3742 Dec-2006 96.7967 Jan-2007 97.8403 Feb-2007 97.6842 Mar-2007 97.441 Apr-2007 96.1432 May-2007 95.4189 Jun-2007 95.1556 Jul-2007 93.7533 Aug-2007 94.0843 Sep-2007 92.8925 Oct-2007 90.7738 Nov-2007 89.7054 Dec-2007 90.5478 Jan-2008 90.0062 Feb-2008 89.011 Mar-2008 87.2242 Apr-2008 86.8394 May-2008 87.1765 Jun-2008 87.7577 Jul-2008 87.3568 Aug-2008 89.6971 Sep-2008 92.0468 Oct-2008 97.9836 Nov-2008 99.1472 Dec-2008 97.5436 Jan-2009 98.4616 Feb-2009 101.2442 Mar-2009 101.5294 Apr-2009 98.8865 May-2009 95.7444 Jun-2009 94.8421 Jul-2009 94.4023 Aug-2009 93.1692 Sep-2009 92.518 Oct-2009 91.2647 Nov-2009 90.7908 Dec-2009 91.1302 Jan-2010 91.0045 Feb-2010 92.1814 Mar-2010 91.2772 Apr-2010 90.634 May-2010 93.2442 Jun-2010 93.6119 Jul-2010 92 Aug-2010 91.1986 Sep-2010 90.2195 Oct-2010 87.6708 Nov-2010 87.7801 Dec-2010 88.4843 Jan-2011 87.405 Feb-2011 86.7848 Mar-2011 86.0017 Apr-2011 84.5549 May-2011 84.6455 Jun-2011 84.4904 Jul-2011 83.8936 Aug-2011 84.5546 Sep-2011 87.2545 Oct-2011 87.911 Nov-2011 88.5353 Dec-2011 89.3335 Jan-2012 88.6605 Feb-2012 87.2091 Mar-2012 87.6315 Apr-2012 87.8522 May-2012 89.2569 Jun-2012 90.4848 Jul-2012 89.9252 Aug-2012 89.2768 Sep-2012 87.9707 Oct-2012 87.8269 Nov-2012 88.2349 Dec-2012 87.4631 Jan-2013 87.3772 Feb-2013 88.2478 Mar-2013 88.7274 Apr-2013 88.1082 May-2013 88.5064 Jun-2013 89.2261 Jul-2013 89.78 Aug-2013 89.6929 Sep-2013 89.2466 Oct-2013 88.2424 Nov-2013 88.9969 Dec-2013 89.1647 Jan-2014 90.0628 Feb-2014 90.1859 Mar-2014 90.0125 Apr-2014 89.4858 May-2014 89.1681 Jun-2014 89.2731 Jul-2014 89.0348 Aug-2014 89.8448 Sep-2014 91.155 Oct-2014 92.2651 Nov-2014 93.6136 Dec-2014 95.4894 Jan-2015 97.2271 Feb-2015 98.5745 Mar-2015 100.5459 Apr-2015 99.6299 May-2015 98.8479 Jun-2015 99.6383 Jul-2015 101.4492 Aug-2015 103.091 Sep-2015 103.6871 Oct-2015 102.722 Nov-2015 104.4278 Dec-2015 105.2221 Jan-2016 107.5865 Feb-2016 106.2559 Mar-2016 103.9964 Apr-2016 102.4904 May-2016 103.5767 Jun-2016 104.0482 Jul-2016 104.7442 Aug-2016 103.9419 Sep-2016 104.7599 Oct-2016 105.828 Nov-2016 108.2749 Dec-2016 110.0398 Jan-2017 109.8301 Feb-2017 108.3929 Mar-2017 107.6034 Apr-2017 106.6168 May-2017 106.0208 Jun-2017 104.6501 Jul-2017 102.9546 Aug-2017 102.0232 Sep-2017 101.353 Oct-2017 103.1251 Nov-2017 103.3262 Dec-2017 103.0038 Jan-2018 100.7984 Feb-2018 100.2119 Mar-2018 100.3821 Apr-2018 100.48 May-2018 103.3839 Jun-2018 105.0459 Jul-2018 105.0507 Aug-2018 105.6461 Sep-2018 105.8108 Oct-2018 106.4923 Nov-2018 107.6852 Dec-2018 107.6407 Jan-2019 105.9023 Feb-2019 105.9229 Mar-2019 106.282 Apr-2019 106.3842 May-2019 107.2646 Jun-2019 106.7702 Jul-2019 106.4977 Aug-2019 108.394 Sep-2019 108.5591 Oct-2019 107.9687 Nov-2019 107.7399 Dec-2019 107.0521 Jan-2020 106.3611 Feb-2020 107.7051 Mar-2020 111.7106 Apr-2020 113.3896 May-2020 112.814 Jun-2020 110.2523 Jul-2020 109.2665 Index, 2006 = 100 109.3 2006 2008 2010 2012 2014 2016 2018 2020 80 90 100 110 120 ChartData Note: Rates in currency units per U.S. dollar except as noted. Index January 2006=100, monthly, not seasonally adjusted. Source: Author’s analysis of data from the Federal Reserve, Nominal/Real Indexes, [Foreign Exchange Rates - H.10] Real Broad Dollar Index—Monthly Index. Share Tweet Embed Download image Unfortunately, the Trump administration has simply ignored the linkage between these policies and a rising U.S. trade deficit, despite the fact that as a candidate, Donald Trump promised to declare China a “currency manipulator” on “day one” of his administration (Talley 2016). While the Treasury did, finally, name China a currency manipulator last year, it was too little, too late (Scott 2019). China’s currency, the yuan (or RMB), has continued to fall relative to the U.S. dollar since March 2018, despite the inclusion of a “currency clause” in the Phase One U.S.–China trade deal (Fed 2020a). Notably, the agreement was neither a binding constraint on Chinese monetary policy nor a real commitment to action on the part of the U.S. Treasury. Overvaluation of the dollar is one of the most important structural causes of growing U.S. trade deficits. In order to help rebalance U.S. trade flows, the dollar needs to fall 25–30% overall on a real trade-weighted basis, and more against the currencies of surplus countries and areas such as China, the European Union, Japan, and Korea (Scott 2019). The strength of the dollar was sustained by massive currency manipulation between 2000 and 2014 (Bergsten and Gagnon 2017), but since then large private capital inflows to U.S. financial markets have continued the trend. There are several tools that can be used to address dollar overvaluation.2 Perhaps the most effective proposal to reduce and manage excessive private capital flows on a sustained basis is a bipartisan bill, the “Competitive Dollar for Jobs and Prosperity Act,” introduced last year by Senators Baldwin (D-Wis.) and Hawley (R-Mo.) (S.2357).3 Their legislation would impose a small tax, or “market access charge” (MAC), on all foreign capital inflows (Hansen 2017). Their proposal would direct the U.S. Federal Reserve Board of Governors to set this tax at a level needed to rebalance trade and capital flows, giving the Fed both a new mandate—to achieve balanced trade—and a new tool to achieve that goal. Millions of good, high-wage manufacturing jobs can be created by rebalancing trade flows, something that would contribute to recovery from the COVID-19 recession. If Trump’s trade policy really encouraged reshoring, America’s trade balance would have improved in the past three years. But the U.S. trade deficit in manufactured goods rose significantly between 2016 and 2019, as shown in Figure D. In fact, the real U.S. trade deficit has increased in every year since 2016, reducing GDP growth by roughly one-quarter of one percent annually over the past three years (USITC 2020; BEA 2020). FIGURE D The U.S. manufacturing trade deficit has been growing above trend since 2016 U.S. manufacturing imports, exports, and trade deficit, 1997–2019 (annual) Date Mfg exports Mfg imports Mfg trade deficit (M−X) Mfg trade deficit trend (M−X) 1997 613.3336 744.028 130.6943 188.402 1998 612.459 799.0056 186.5467 213.414 1999 627.1599 886.1852 259.0253 238.426 2000 707.1855 1024.421 317.2358 263.438 2001 656.4526 960.563 304.1104 288.45 2002 622.0002 984.6372 362.637 313.462 2003 644.9062 1048 403.0937 338.474 2004 726.5793 1214.015 487.4357 363.486 2005 805.9644 1347.361 541.3967 388.498 2006 923.1392 1481.677 558.5378 413.51 2007 1019.377 1551.459 532.0817 438.522 2008 1121.873 1577.942 456.0694 463.534 2009 916.7261 1236.014 319.2879 488.546 2010 1100.394 1513.041 412.6465 513.558 2011 1276.906 1717.455 440.5491 538.57 2012 1341.398 1809.135 467.7364 563.582 2013 1375.17 1833.984 458.8136 588.594 2014 1403.782 1930.685 526.9032 613.606 2015 1317.019 1946.797 629.7783 638.618 2016 1264.011 1911.335 647.3241 663.63 2017 1323.595 2019.639 696.0444 688.642 2018 1400.022 2182.385 782.3625 713.654 2019 1365.305 2159.552 794.2464 738.666 Trade flow (nominal U.S. dollars, billions) 2,160 1,365 794 Mfg imports Mfg exports Mfg trade deficit (M−X) Mfg trade deficit trend (M−X) 2000 2005 2010 2015 2020 0 500 1,000 1,500 2,000 2,500 ChartData Source: EPI analysis of data from U.S. International Trade Commission Trade DataWeb. Share Tweet Embed Download image Furthermore, the strong dollar has also decimated farmers, and it is a much more significant driver of the decline in farm incomes than Trump’s China trade war. There is a single world price for commodity products like wheat and soybeans, as Dean Baker has noted (Baker 2018, 2019). If the dollar rises relative to those of our competitors, then the dollar price of U.S. farm products must fall. Thus, there is a strong, negative correlation between soybean prices, for example, and exchange rates, as shown in Figure E. FIGURE E Exchange rates explain nearly 80% of the movement in soybean prices U.S. soybean prices and the real value of the U.S. dollar, January 1997–May 2020 Date Real dollar index Soybean price index Jan-1997 89.846 124.4 Feb-1997 91.3934 127.1 Mar-1997 92.3092 144.8 Apr-1997 92.6654 142.4 May-1997 91.5753 149.8 Jun-1997 91.1354 140.0 Jul-1997 92.1604 137.1 Aug-1997 93.7113 124.5 Sep-1997 93.9532 120.6 Oct-1997 94.6141 119.1 Nov-1997 95.9972 124.5 Dec-1997 99.3624 117.8 Jan-1998 102.1075 113.2 Feb-1998 100.3897 116.9 Mar-1998 100.0598 113.3 Apr-1998 99.7845 107.8 May-1998 100.562 110.2 Jun-1998 102.727 104.8 Jul-1998 103.0308 109.6 Aug-1998 104.6407 93.7 Sep-1998 102.8371 90.5 Oct-1998 99.946 92.2 Nov-1998 99.6076 96.0 Dec-1998 98.7106 92.7 Jan-1999 98.7733 91.8 Feb-1999 99.9907 84.0 Mar-1999 101.0852 78.5 Apr-1999 100.998 80.8 May-1999 100.7253 79.6 Jun-1999 101.1534 79.1 Jul-1999 101.4274 70.5 Aug-1999 100.4354 79.9 Sep-1999 100.0213 82.3 Oct-1999 99.5535 80.0 Nov-1999 99.8412 78.6 Dec-1999 99.9463 76.5 Jan-2000 99.8799 79.6 Feb-2000 101.2479 83.9 Mar-2000 101.7325 87.1 Apr-2000 102.299 87.3 May-2000 104.5402 91.6 Jun-2000 103.6564 87.0 Jul-2000 103.9295 80.8 Aug-2000 104.4002 77.8 Sep-2000 105.8875 82.8 Oct-2000 107.3917 79.4 Nov-2000 108.0006 79.1 Dec-2000 107.1324 84.1 Jan-2001 107.4905 82.8 Feb-2001 108.2975 75.0 Mar-2001 109.891 76.2 Apr-2001 110.5281 73.3 May-2001 110.5766 76.5 Jun-2001 111.4064 80.8 Jul-2001 111.5364 87.0 Aug-2001 109.554 88.4 Sep-2001 110.1595 80.1 Oct-2001 110.54 75.3 Nov-2001 111.0101 74.7 Dec-2001 110.9411 73.6 Jan-2002 112.1863 74.5 Feb-2002 112.8094 73.8 Mar-2002 112.2398 76.7 Apr-2002 112.0559 78.3 May-2002 110.5853 81.4 Jun-2002 109.1517 86.2 Jul-2002 107.5697 97.8 Aug-2002 108.8697 100.4 Sep-2002 109.7111 99.5 Oct-2002 110.5092 92.6 Nov-2002 109.2711 95.9 Dec-2002 108.679 95.4 Jan-2003 107.366 93.3 Feb-2003 107.5059 97.4 Mar-2003 107.0154 97.6 Apr-2003 105.837 105.5 May-2003 102.2899 109.6 Jun-2003 101.7892 108.0 Jul-2003 103.0553 102.0 Aug-2003 104.4244 96.6 Sep-2003 103.3567 104.8 Oct-2003 101.047 125.1 Nov-2003 100.6482 131.3 Dec-2003 99.2942 134.2 Jan-2004 97.8175 141.8 Feb-2004 98.4235 144.0 Mar-2004 99.3359 162.6 Apr-2004 99.9257 165.9 May-2004 101.6737 178.4 Jun-2004 100.8244 154.4 Jul-2004 100.05 153.7 Aug-2004 100.0206 99.1 Sep-2004 99.7427 96.0 Oct-2004 98.5743 84.2 Nov-2004 96.3623 85.7 Dec-2004 95.2261 94.3 Jan-2005 95.612 92.6 Feb-2005 95.8581 91.7 Mar-2005 95.4702 112.4 Apr-2005 96.4072 102.9 May-2005 96.6458 107.7 Jun-2005 97.5106 116.0 Jul-2005 98.178 118.3 Aug-2005 97.3399 109.2 Sep-2005 98.2219 93.2 Oct-2005 99.1157 88.5 Nov-2005 99.2465 97.7 Dec-2005 98.4504 100.9 Jan-2006 97.3054 96.3 Feb-2006 97.4982 96.7 Mar-2006 97.6888 95.4 Apr-2006 97.2008 92.6 May-2006 95.2746 98.1 Jun-2006 96.521 96.7 Jul-2006 96.6865 98.6 Aug-2006 96.2415 90.7 Sep-2006 95.9166 87.0 Oct-2006 95.6514 91.8 Nov-2006 94.6661 109.1 Dec-2006 94.0612 108.9 Jan-2007 94.9926 108.4 Feb-2007 94.8199 123.1 Mar-2007 94.5743 115.9 Apr-2007 93.4545 119.4 May-2007 92.7996 125.3 Jun-2007 92.5428 131.9 Jul-2007 91.1791 140.6 Aug-2007 91.3879 128.5 Sep-2007 90.3068 145.3 Oct-2007 88.3764 151.1 Nov-2007 87.3326 173.2 Dec-2007 87.9654 192.5 Jan-2008 87.3029 211.2 Feb-2008 86.2413 219.4 Mar-2008 84.5722 228.7 Apr-2008 84.1423 228.2 May-2008 84.5052 226.9 Jun-2008 84.9997 242.6 Jul-2008 84.6115 259.5 Aug-2008 86.681 203.0 Sep-2008 88.7885 200.6 Oct-2008 93.8688 144.1 Nov-2008 94.705 147.2 Dec-2008 93.1988 135.1 Jan-2009 93.9809 161.9 Feb-2009 96.6073 164.7 Mar-2009 96.8163 150.9 Apr-2009 94.4326 176.1 May-2009 91.6955 193.3 Jun-2009 91.0825 213.0 Jul-2009 90.6763 182.5 Aug-2009 89.618 200.0 Sep-2009 88.9744 162.1 Oct-2009 87.8368 170.1 Nov-2009 87.3979 160.0 Dec-2009 87.6292 176.2 Jan-2010 87.655 167.1 Feb-2010 88.6481 157.9 Mar-2010 87.7638 160.1 Apr-2010 87.1576 163.2 May-2010 89.3522 161.7 Jun-2010 89.7047 163.4 Jul-2010 88.2443 174.3 Aug-2010 87.4789 176.2 Sep-2010 86.5285 173.3 Oct-2010 84.1785 192.2 Nov-2010 84.2268 219.1 Dec-2010 84.8632 216.2 Jan-2011 83.8443 227.4 Feb-2011 83.2495 229.8 Mar-2011 82.555 214.5 Apr-2011 81.274 224.5 May-2011 81.294 226.2 Jun-2011 81.0863 233.2 Jul-2011 80.5208 232.7 Aug-2011 81.0682 222.2 Sep-2011 83.46 227.9 Oct-2011 84.0356 205.5 Nov-2011 84.5622 201.2 Dec-2011 85.2467 190.3 Jan-2012 84.5898 206.5 Feb-2012 83.3299 214.3 Mar-2012 83.6939 229.9 Apr-2012 83.8977 243.1 May-2012 85.1276 240.7 Jun-2012 86.2289 245.1 Jul-2012 85.7197 274.7 Aug-2012 85.1596 282.8 Sep-2012 84.0119 289.8 Oct-2012 83.8167 263.1 Nov-2012 84.0993 240.7 Dec-2012 83.3883 252.3 Jan-2013 83.266 246.8 Feb-2013 84.1226 244.9 Mar-2013 84.5212 254.4 Apr-2013 83.9251 242.5 May-2013 84.2258 254.6 Jun-2013 84.8774 265.5 Jul-2013 85.3251 274.6 Aug-2013 85.2633 225.6 Sep-2013 84.8615 241.6 Oct-2013 83.9076 222.2 Nov-2013 84.5661 226.3 Dec-2013 84.7464 227.4 Jan-2014 85.5269 224.9 Feb-2014 85.6968 227.1 Mar-2014 85.6206 241.0 Apr-2014 85.1966 257.9 May-2014 84.8808 255.4 Jun-2014 84.9584 250.3 Jul-2014 84.7193 212.6 Aug-2014 85.3542 196.2 Sep-2014 86.4823 180.9 Oct-2014 87.4385 164.1 Nov-2014 88.6746 175.4 Dec-2014 90.4614 177.6 Jan-2015 91.964 168.5 Feb-2015 93.1384 163.5 Mar-2015 94.8318 167.0 Apr-2015 93.8084 164.5 May-2015 93.1702 159.8 Jun-2015 93.959 164.4 Jul-2015 95.5444 176.4 Aug-2015 97.1718 169.5 Sep-2015 97.6601 151.3 Oct-2015 96.7364 152.9 Nov-2015 98.2176 144.8 Dec-2015 98.9911 146.7 Jan-2016 101.1672 147.9 Feb-2016 99.8781 145.6 Mar-2016 97.8761 150.0 Apr-2016 96.433 156.7 May-2016 97.495 180.2 Jun-2016 97.9256 195.7 Jul-2016 98.4625 186.0 Aug-2016 97.6919 170.2 Sep-2016 98.3665 161.4 Oct-2016 99.2993 158.0 Nov-2016 101.6476 163.4 Dec-2016 103.3297 170.8 Jan-2017 103.0893 168.4 Feb-2017 101.779 173.1 Mar-2017 101.0801 164.5 Apr-2017 100.0849 154.8 May-2017 99.5332 161.3 Jun-2017 98.2288 155.4 Jul-2017 96.7998 171.9 Aug-2017 95.8465 153.7 Sep-2017 95.1008 157.7 Oct-2017 96.6601 158.2 Nov-2017 96.8122 159.9 Dec-2017 96.4675 161.9 Jan-2018 94.3155 159.7 Feb-2018 94.7214 168.5 Mar-2018 95.0048 172.9 Apr-2018 94.999 174.8 May-2018 97.5243 169.5 Jun-2018 99.0216 159.0 Jul-2018 99.3349 143.3 Aug-2018 100.2812 143.1 Sep-2018 100.2619 131.5 Oct-2018 100.9126 136.8 Nov-2018 101.9838 140.8 Dec-2018 102.0031 148.4 Jan-2019 100.4012 143.6 Feb-2019 100.403 148.6 Mar-2019 100.7722 144.8 Apr-2019 100.7457 145.8 May-2019 101.6032 134.0 Jun-2019 101.1344 140.4 Jul-2019 100.9148 146.4 Aug-2019 102.8088 144.5 Sep-2019 102.7664 141.6 Oct-2019 102.2026 153.6 Nov-2019 101.9538 152.2 Dec-2019 101.4637 151.8 Jan-2020 100.8096 158.5 Feb-2020 102.0839 149.5 Mar-2020 105.8784 148.2 Apr-2020 107.4852 143.7 May-2020 107.0985 144.2 Soybean price index, 1982=100 Real dollar index, 1973=100 144.200 107.099 Soybean price index Real dollar index 2000 2005 2010 2015 2020 0 100 200 300 400 80 90 100 110 120 ChartData Note: The Real Broad Dollar index (Goods only) was extrapolated to May 2020 using the percentage change Real Broad Dollar index (Goods and Services) for each corresponding month. Source: Author’s analysis of Federal Reserve, Nominal/Real Indexes, [Foreign Exchange Rates - H.10] Real Broad Dollar Index—Monthly Index and Bureau of Labor Statistics (BLS) Producer Price Index (PPI) commodity price series data. Share Tweet Embed Download image When the real (price-adjusted) dollar declines, as it did between 2002 and 2012, soybean prices increase. Grain and soybean prices started falling as soon as the dollar began to rise in 2014. Movements in the dollar alone explain nearly 80% of the change in soybean prices, with the rest having to do with changes in weather conditions, incomes, farm decisions (e.g., crop allocations), and other factors. We need to realign the dollar to rebalance trade. Manufacturing and the farm sector will both benefit directly from dollar realignment. President Trump has utterly failed to address this core issue, despite his baseless and self-serving promises to address currency manipulation and rebuild manufacturing by getting “tough on trade.” Trump’s trade deals have not helped U.S. workers The USMCA—which was touted as a replacement for NAFTA—is unlikely to resolve longstanding U.S.–Mexico trade issues. America’s trade deficit with Mexico increased by more than 29% in 2019 alone (U.S. Census Bureau 2020c). And when it comes to important sectors like autos and auto parts, General Motors has been closing assembly plants in Ohio, Michigan, and Maryland while increasing its reliance on imports from Mexico (AP 2019; Samilton 2019; Mirabella 2019). In fact, GM has been ceding market share to foreign producers for decades, and has grown increasingly reliant on imports from Mexico and other countries. Meanwhile, market share has been captured by foreign producers. Recently, BMW, Mercedes/Infiniti, and Kia opened plants in Mexico—a missed opportunity to reshore production to the United States (Szczesny 2019; Mexico Now 2018a, 2018b). And the supplier networks for these plants will be built in Mexico, not the U.S.—further eroding America’s auto industry. Offshoring to Mexico is also taking place in aerospace and other sectors, with aerospace exports from Mexico increasing 10% in 2019 (Krause 2020). While the USMCA significantly improves domestic labor protections in Mexico compared with the earlier version of NAFTA, its overall provisions are inadequate to stem these offshoring trends. The Phase One China trade deal is a bust, too. China promised to increase purchases of U.S. goods and services by $200 billion over 2017 imports. But Beijing is unlikely to meet these targets (Craymer and DeBarros 2020). And the deal doesn’t even address China’s egregious, systematic labor rights violations. Beijing has also strategically adjusted to the Trump tariffs. China is simply exporting more goods elsewhere, and the U.S. trade deficit with China’s trading partners rose rapidly in 2019. In fact, China’s overall trade surplus with the world climbed significantly in 2019 (Setser 2020a). China also reduced the value of its currency by 10.0% against the U.S. dollar since March 2018, helping to offset the tariffs (Fed 2020a). The tariffs remain a “signature” element of the Trump trade agenda. And they’ve helped sectors like steel and aluminum (Scott 2018a, 2018b). But the president misses a key point: If you increase tariffs without taking steps to prevent the dollar’s appreciation, the overall benefits can be simply neutralized. Trump’s tax policies have encouraged outsourcing America’s trade problems have been exacerbated by mistakes and/or malfeasance in Trump’s tax policymaking. U.S. multinational corporations continually engage in massive, international tax avoidance—with some paying no U.S. income tax at all. The 2017 tax cut exacerbated this problem by creating a new, lower corporate tax rate for “global intangibles income.”4 The pharmaceuticals industry has since reaped major rewards and has moved plants to countries with the lowest possible corporate tax rate (Setser 2020b). As a result, the U.S. now has a massive trade deficit in pharmaceuticals, which exceeds the trade surplus in aerospace products, the strongest U.S. export industry. Leading suppliers of pharmaceutical imports—many produced by U.S. firms, such as Pfizer, which had no taxable U.S. income over the entire decade from 2007 to 2016 (Rice, Kitson, and Clemente 2017)—include Ireland, Germany, Switzerland, India, and China. The U.S. trade deficit is likely to shrink during COVID-19 simply because of the decline in consumer income and spending. But unless steps are taken to address dollar overvaluation and the tax incentives that encourage offshoring, these deficits will simply reemerge when recovery occurs (Scott 2020a). Manufacturing job loss was a key issue for voters in the 2016 election Voters from manufacturing states have been hardest hit by growing trade deficits and failed trade and investment deals. In 2016, Donald Trump ran on a nationalist campaign platform, based in part on a critique of globalization that cited EPI research (Trump 2016). Hillary Clinton and Bernie Sanders have also cited EPI research on, for example, jobs lost due to growing trade deficits with China (Clinton 2007; Sanders 2020). Globalization is clearly an issue of bipartisan concern. In 2016, voters from the top 25 manufacturing states, ranked by share of total employment in manufacturing, gave nearly 80% of their electoral votes to Donald Trump, as shown in Figure F, the manufacturing electoral heat map. Hillary Clinton prevailed in the bottom 25 manufacturing states, by a margin of 61% to 39%, but it was not enough to offset Trump’s advantage in the manufacturing states. However, Trump’s policies have failed to stop offshoring or the erosion of the U.S. manufacturing base. FIGURE F In states where manufacturing composes a larger share of overall employment, Trump garnered more electoral votes in 2016 Manufacturing share of employmentElectoral votes Maine Vt. N.H. Wash. Idaho Mont. N.D. Minn. Ill. Wis. Mich. N.Y. R.I. Mass. Ore. Nev. Wyo. S.D. Iowa Ind. Ohio Pa. N.J. Conn. Calif. Utah Colo. Neb. Mo. Ky. W.Va. Va. Md. Del. Ariz. N.M. Kan. Ark. Tenn. N.C. S.C. D.C. Okla. La. Miss. Ala. Ga. Alaska Hawaii Texas Fla. 0.0%17.1% Click map to view data. State Manufacturing employment share Electoral votes Electoral votes for Clinton Electoral votes for Trump Indiana 17.1% 0 0 11 Wisconsin 16.2% 0 0 10 Iowa 14.2% 0 0 6 Michigan 14.1% 0 0 16 Kentucky 13.0% 0 0 8 Alabama 12.9% 0 0 9 Mississippi 12.8% 0 0 6 Arkansas 12.6% 0 0 6 Ohio 12.5% 0 0 18 Kansas 11.7% 0 0 6 South Carolina 11.7% 0 0 9 Tennessee 11.3% 0 0 11 Minnesota 10.8% 2 10 0 North Carolina 10.4% 0 0 15 New Hampshire 10.3% 2 4 0 Oregon 10.1% 2 7 0 South Dakota 9.9% 0 0 3 Nebraska 9.6% 0 0 5 Vermont 9.5% 2 3 0 Connecticut 9.5% 2 7 0 Missouri 9.5% 0 0 10 Illinois 9.4% 2 20 0 Pennsylvania 9.4% 0 0 20 Idaho 8.8% 0 0 4 Georgia 8.7% 0 0 16 Utah 8.6% 0 0 6 Maine 8.4% 1 3 1 Washington 8.4% 0 12 0 Oklahoma 8.1% 0 0 7 Rhode Island 7.8% 2 4 0 California 7.5% 2 55 0 Texas 7.0% 0 0 38 Louisiana 6.9% 0 0 8 Massachusetts 6.6% 2 11 0 West Virginia 6.5% 0 0 5 Arizona 6.0% 0 0 11 New Jersey 6.0% 2 14 0 Virginia 6.0% 2 13 0 North Dakota 5.9% 0 0 3 Delaware 5.8% 2 3 0 Colorado 5.3% 2 9 0 New York 4.5% 2 29 0 Florida 4.3% 0 0 29 Montana 4.2% 0 0 3 Nevada 4.2% 2 6 0 Maryland 4.1% 2 10 0 Alaska 3.7% 0 0 3 Wyoming 3.5% 0 0 3 New Mexico 3.4% 2 5 0 Hawaii 2.1% 2 4 0 Washington D.C. 0.0% 2 3 0 Note: Manufacturing data are for 2019. Source: EPI analysis of Bureau of Labor Statistics Current Employment Statistics, State and Metro Area (BLS-CES/SAE) Employment, Hours and Earnings Data; and Politico, “2016 Presidential Election Results.” Share Tweet Embed Download image The restoration of manufacturing in the United States will be essential to the COVID-19 economic recovery. It is time to consider a progressive alternative for rebuilding manufacturing. The components of such a plan are described in the following section. The COVID-19 recovery will require major investments in infrastructure and clean energy The coronavirus crisis has devastated the U.S. and global economies. Black, Latinx, and women workers have been hardest hit, and without special efforts made for low-income communities, they will be the last to recover (Gould 2020b). With the economy in freefall, the U.S. needs to engage in massive and widespread relief. America also needs a plan for economic reconstruction in the wake of the COVID-19 pandemic, one that is specifically designed to address the needs of those hardest hit in the economy. Millions of jobs and small businesses have been lost in sectors such as retail trade, travel, tourism, and restaurants, and many will never come back. The economy must be restructured—new and better jobs are needed for displaced workers. Properly done, the required investments can create good jobs with excellent wages and benefits for Black, Latinx, and women workers who have suffered from racism or discrimination and economic inequality (Gould 2020a; Gould and Wilson 2020). Thus, any relief and rebuilding plan must address the following core issues. The U.S. must continue to provide massive and widespread relief Relief spending must be continued and expanded. The U.S. has recently encountered a Wile E. Coyote moment—it just ran off the edge of a cliff—with the expiration of an expanded unemployment compensation program that was giving 33 million workers a $600 weekly unemployment insurance boost (Shierholz 2020). The failure to renew this and other relief programs will cause a collapse in consumer spending and business investment, resulting in an economic tsunami that threatens to deepen the coronavirus recession into a depression in the fall, while potentially exacerbating the health crisis by pushing people to go back to work before it’s safe to do so (Bivens 2020b). We need expanded relief for all workers in the next coronavirus bill, and we also need to add at least $1 trillion in federal aid for state and local governments, support for public health measures (testing, tracing, and isolation, with paid leave), unemployment, and continuing income supports for the tens of millions who are furloughed or unemployed and for businesses that are shuttered (Bivens 2020a). Without aid for state and local governments, in particular, 5.3 million jobs are at risk by the end of 2021, which threatens to further deepen the coronavirus recession (Bivens and Cooper 2020). The U.S. must rebuild a sustainable, resilient, manufacturing-based economy Even if the coronavirus pandemic is successfully controlled, we are likely to experience recurrent infections and hot spots (as has already occurred in the South and West) until vaccines and more effective treatments arrive. Meanwhile, massive effort is needed, starting today, to rebuild and restructure the economy in ways that will address the needs of Black, Latinx, and women workers. Millions of low-wage service jobs are unlikely to return. As we rebuild our economy, these jobs can and should be replaced with higher-wage jobs in manufacturing and construction that provide excellent benefits and afford workers the right to organize and bargain collectively. Planning and organizing these rebuilding efforts—including design, permitting, and purchase of materials and rights-of-way—should begin now, so that funding, projects, and employment can flow in earnest once the pandemic has been brought under control. There are three essential components of a sustainable U.S. economy Looking forward, the three pillars of building a sustainable, resilient, manufacturing-based economy are: (1) rebalancing trade flows; (2) rebuilding U.S. infrastructure; and (3) supporting the transition to efficient and clean energy systems.5 In 2017, the American Society of Civil Engineers estimated in its Infrastructure Report Card that the United States needs $4.6 trillion in infrastructure spending over 10 years for sorely needed repairs and modernization (ASCE 2017). This exceeds planned spending by $2 trillion. Similarly, Robert Pollin at the University of Massachusetts-Amherst suggests that the U.S. needs to devote roughly two percent of GDP annually to increased energy efficiency and clean energy conversion, or roughly $400–$500 billion per year (Drollette 2019). Thus, for infrastructure and clean energy transition, the U.S. needs additional investments of $650–$750 billion per year in rebuilding the economy. The U.S. goods trade deficit exceeded $860 billion in 2019. By rebalancing trade and expanding U.S. public investment as described above, we can increase overall demand for U.S. production by up to $1.5 trillion per year, directly stimulating the manufacturing and construction industries while rebuilding the economy. This could generate massive increases in overall demand for goods and services produced in the United States that would support and create more than 17 million good jobs.6 These steps alone would absorb more than half of the 33 million workers who were drawing unemployment benefits or have applied and are waiting for benefits as of August 1 (Shierholz 2020). Joe Biden has recently proposed a $2 trillion initiative for clean energy and infrastructure (Glueck and Friedman 2020; Erickson 2020). He has also proposed investing $300 billion in manufacturing R&D and implementing policies designed to maximize the domestic content of infrastructure investments through “Buy America” policies (Goldmacher and Tankersley 2020). These proposals could make a substantial contribution to meeting U.S. investment needs and generating a strong, sustainable, broadly shared recovery. The U.S. must rebalance trade flows Realigning the dollar, as described above, could help to eliminate U.S. trade deficits and prevent the reemergence of larger trade gaps in the future. Rebalancing trade can also generate millions of good manufacturing jobs and prevent the offshoring of more manufacturing plants in the future. We must revise government procurement policies and trade rules to ensure that public infrastructure investments actually benefit U.S. workers and the U.S. economy Steps must be taken to ensure that public investments maximize domestic bang-for-the-buck—in terms of job creation and GDP support—in the states and cities where they are needed most, providing good jobs for those who have been excluded from the economy of the past. Under current trade rules, much of the public spending for infrastructure and clean energy systems would leak away to foreign providers, in the form of increased imports. Thus, these proposals should all include strong “Buy America” clauses in state and federal procurement policies. Doing so will require modification of or withdrawal from the World Trade Organization government procurement agreement (Miller & Chevalier 2020). We must also implement supply-side policies to ensure jobs go to those U.S. workers who were left behind by the decline in manufacturing An array of supply-side policies are also needed to ensure that these investments generate jobs where they are needed most, for women, Black, and Latinx workers here in the United States. These workers have been hurt by the decline of these industries, which generate good jobs with excellent benefits, especially for non-college-educated workers. Supply-side policies include: An end to tax policies that encourage firms to offshore production, including all tax preferences for foreign investment and production. The U.S. should consider implementing a system of sales factor apportionment to fairly tax the global profits of all foreign and domestic companies, based on their total sales in the United States, and to further discourage offshoring (Stumo 2016). Substantial investments in R&D, training, school-to-work transition, job creation programs, expanded extension,7 and other industrial policies, including expanded financing of small and medium-sized manufacturing firms. The U.S. should also support improvements in labor rights in all 50 states (Madland, Walter, and Eisenbrey 2012) and measures to include workers, banks, and other community stakeholders on corporate boards, to improve their performance in local economies. Aggressive but strategic use of anti-dumping and enhanced safeguard measures to prevent surges of primary commodity imports, especially in sectors subject to chronic excess capacity (but with no across-the-board tariffs). The coronavirus has worsened a global metals glut, in part because China, the top producer of aluminum and steel, has kept up production as demand fell (Tita 2020). Aggressive enforcement of trade laws will be needed to limit damage to domestic producers during the coronavirus recession. Investments should be financed with public debt until the economic crisis has subsided Last, infrastructure and clean energy transition investments should be financed, at least during the COVID-19 recovery, by increasing public debt—including heavy borrowing until long-term interest rates begin to rise well in excess of a 2% inflation target (Bivens 2019). Then, and only then, can these needed investments be paid for by taxing capital, starting with the wealthy and those who can afford to pay, and with user fees as necessary and appropriate (offset by income transfers to low-income families). It is important to note that rebalancing trade will generate new federal revenues (through increased incomes), along with new revenues from the taxes imposed on foreign capital inflows, as referenced above. These revenues could also be used to pay off public debt. Conclusion: Progressives must reshape their approach to trade The coronavirus crisis is causing unprecedented damage to the U.S. economy and to the lives of tens of millions of Americans. This crisis will change the national economy in untold ways. Life in America will never be the same. But “in the midst of every crisis, lies great opportunity.”8 The need to rebuild America has never been greater, and the time to rebuild is now. For the past three decades, mainstream Democrats have tied their fates to the twin mantras of free trade and globalization, which have cost millions of jobs and many thousands of factories. Bill Clinton campaigned for and signed NAFTA in 1993. He also negotiated and signed the agreement that created the World Trade Organization in 1994. And he negotiated the agreement that resulted in China’s entry into the World Trade Organization in 2001. Barack Obama negotiated and campaigned for the failed Trans-Pacific Partnership agreement. It is time for progressives to own and reject these failed policies, and to build and campaign on a plan to develop a 21st-century New Deal for the domestic economy. In 2016, Donald Trump campaigned against globalization and these failed trade deals—which have clearly hurt U.S. manufacturing. It worked. He captured nearly 80% of the electoral votes in the top 25 manufacturing states, as shown above. But he has since failed to deliver for working Americans. Now the wheels are coming off. It’s time for a meaningful rewrite of failed U.S. trade and economic policies—all urgently needed to revive the U.S. economy at a critical time. Acknowledgments The author thanks Thea Lee for comments, Krista Faries for editorial guidance, and Daniel Perez for research assistance. Endnotes 1. For more on Foxconn’s history of announced intentions to invest in the U.S., see Frankel 2017. 2. See the “Fair Globalization and Balanced Trade” section of EPI’s Policy Agenda (EPI 2018). 3. Competitive Dollar for Jobs and Prosperity Act, S. 2357, 116th Cong. (2019). 4. Global intangibles income is “income earned by foreign affiliates of U.S. companies from assets such as patents, trademarks and copyrights” (TPC 2020). 5. See the “Climate Change” section of EPI’s Policy Agenda (EPI 2018). 6. Author’s calculations based on model in Scott and Glass 2016. 7. For example, through the U.S. Manufacturing Extension Partnership Program (Shapira 2001; NIST 2020). 8. This quote is frequently attributed to Albert Einstein, but the actual source cannot be verified. 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