Posts Tagged ‘World Trade Organization

10
Nov
18

The China Toll – loss of 3.4 million US jobs to China from 2001-2007

The China Toll

The China toll deepens growth in the bilateral trade deficit between 2001 and 2007 cost 3.4 million U.S. jobs, with losses in every state and congressional district

Summary and key findings

The United States has a massive trade deficit with China. The growth of the U.S. trade deficit with China, which has increased by more than $100 billion since the beginning of the Great Recession, almost entirely explains why manufacturing employment has not fully recovered along with the rest of the economy. And the growing trade deficit with China isn’t just a post-recession phenomenon hitting manufacturing: it has cost the U.S. millions of jobs throughout the economy since China entered the World Trade Organization (WTO) in 2001, a finding validated by numerous studies.

This report underscores the ongoing trade and jobs crisis by updating EPI’s research series on the jobs impact of the U.S.–China trade deficit. The most recent of these reports (Scott 2012; Kimball and Scott 2014; Scott 2017a) look at the effect of the U.S. trade deficit with China since China entered the WTO in 2001. Our model examines the job impacts of trade by subtracting the job opportunities lost to imports from those gained through exports. As with our previous analyses, we find that because imports from China have soared while exports to China have increased much less, the United States is both losing jobs in manufacturing (in electronics and high tech, apparel, textiles, and a range of heavier durable goods industries) and missing opportunities to add jobs in manufacturing (in exporting industries such as transportation equipment, agricultural products, computer and electronic parts, chemicals, machinery, and food and beverages).

The growing trade deficit with China since China entered the WTO affects different regions in different ways. Some regions are devastated by layoffs and factory closings while others are surviving but not growing the way they could be if new factories were opening and existing plants were hiring more workers. This slowdown in manufacturing job generation is also contributing to stagnating wages of typical workers and widening inequality.

Following are the key highlights of this report:

U.S. jobs lost are spread throughout the country but are concentrated in manufacturing, including in industries in which the United States has traditionally held a competitive advantage.

  • The growth of the U.S. trade deficit with China between 2001 and 2017 was responsible for the loss of 3.4 million U.S. jobs, including 1.3 million jobs lost since 2008 (the first full year of the Great Recession, which technically began at the end of 2007). Nearly three-fourths (74.4 percent) of the jobs lost between 2001 and 2017 were in manufacturing (2.5 million manufacturing jobs lost).
  • The growing trade deficit with China has cost jobs in all 50 states and in every congressional district in the United States. The 10 hardest-hit states, when looking at job loss as a share of total state employment, were New Hampshire, Oregon, California, Minnesota, North Carolina, Rhode Island, Massachusetts, Vermont, Wisconsin, and Texas. Job losses in these states ranged from 2.57 percent (in Texas) to 3.55 percent (in New Hampshire) of total state employment. The five hardest-hit states based on total jobs lost were California (562,500 jobs lost), Texas (314,000), New York (183,500), Illinois (148,200), and Pennsylvania (136,100).
  • The trade deficit in the computer and electronic parts industry grew the most: 1,209,000 jobs were lost in that industry, accounting for 36.0 percent of the 2001–2017 total jobs lost. Not surprisingly, the hardest-hit congressional districts (those ranking in the top 20 districts in terms of jobs lost as a share of all jobs in the district) included districts in Arizona, California, Illinois, Massachusetts, Minnesota, New York, Oregon, and Texas, where jobs in that industry are concentrated. A district in Georgia and another in North Carolina were also especially hard hit by trade-related job displacement in a variety of manufacturing industries, including computer and electronic parts, textiles and apparel, and furniture.
  • Surging imports of steel, aluminum, and other capital-intensive products threaten hundreds of thousands of jobs in key industries such as primary metals, machinery, and fabricated metal products as well.
  • Global trade in advanced technology products—often discussed as a source of comparative advantage for the United States—is instead dominated by China. This broad category of high-end technology products includes the more advanced elements of the computer and electronic parts industry as well as other sectors such as biotechnology, life sciences, aerospace, and nuclear technology. In 2017, the United States had a $135.4 billion trade deficit in advanced technology products with China, and this deficit was responsible for 36.1 percent of the total U.S.–China goods trade deficit that year. In contrast, the United States had a $24.5 billion trade surplus in advanced technology products with the rest of the world in 2017.

Growing trade deficits are also associated with wage losses not just for manufacturing workers but for all workers economywide who don’t have a college degree.

  • Between 2001 and 2011 alone, growing trade deficits with China reduced the incomes of directly impacted workers by $37 billion per year, and in 2011 alone, growing competition with imports from China and other low wage-countries reduced the wages of all U.S. non–college graduates by a total of $180 billion. Most of that income was redistributed to corporations in the form of higher profits and to workers with college degrees at the very top of the income distribution through higher wages.

The U.S. trade deficit with China has increased since China entered into the WTO

U.S. proponents of admitting China into the World Trade Organization frequently claimed that letting China into the WTO would increase U.S. exports, shrink the U.S. trade deficit with China, and create jobs in the United States.1 In 2000, President Bill Clinton claimed that the agreement then being negotiated to allow China into the WTO would create “a win-win result for both countries.” Exports to China “now support hundreds of thousands of American jobs,” said Clinton, and these figures “can grow substantially with the new access to the Chinese market the WTO agreement creates” (Clinton 2000, 9–10).

China’s entry into the WTO in 2001 was supposed to bring it into compliance with an enforceable, rules-based regime that would require China to open its markets to imports from the United States and other nations by reducing Chinese tariffs and addressing nontariff barriers to trade. Promoters of liberalized U.S.–China trade argued that the United States would benefit because of increased exports to a large and growing consumer market in China. The United States also negotiated a series of special safeguard measures designed to limit the disruptive effects of surging imports from China on domestic producers.

However, China’s trade-distorting practices, aided by China’s currency manipulation and misalignment and its suppression of wages and labor rights, resulted in a flood of dumped and subsidized imports that greatly exceeded the growth of U.S. exports to China. These trade-distorting practices included extending large subsidies to industries such as steel, glass, paper, concrete, and renewable energy industries and rapidly growing its state-owned enterprises, both of which generated a massive buildup of excess capacity in a range of these sectors. This excess capacity created a supply of goods far exceeding Chinese consumer demand, and China dealt with the oversupply by dumping the exports elsewhere, primarily in the United States (Scott 2017a).

The promised surge of U.S. exports to China was also hampered by China’s failure to implement certain policies to increase domestic demand for goods, including goods produced by trading partners. Specifically, for China to become a better market for U.S. exports, it needed to stimulate the growth of domestic consumption through policies that would allow workers to organize and bargain collectively, thus raising wages. China also needed to increase domestic consumption through increased social spending and reductions to the country’s massive savings rate (Scott 2017a). Such policies are all elements of a program of domestic, demand-led growth that the United States, other advanced countries, and international agencies have called on China to implement for many years. But none of these policies have been implemented at anywhere near a large enough scale, and China’s national savings rate has actually increased significantly over the past 15 years (Setser 2016; IMF 2018), which has contributed to the growth of U.S. trade deficits (Bernstein 2016).

In addition, the WTO agreement spurred foreign direct investment (FDI) in Chinese enterprises and the outsourcing of U.S. manufacturing plants, which has expanded China’s manufacturing sector at the expense of the United States, thereby affecting the trade balance between the two countries. Finally, the core of the agreement failed to include any protections to maintain or improve labor or environmental standards or to prohibit currency manipulation. (The descriptions in this paragraph derive from Scott 2017a.)

As a result of these forces, the U.S. trade deficit with China soared after China entered the WTO.

Table 1 displays changes in the U.S.–China goods trade deficit and job displacement from 2001 to 2017 (when the term “trade deficit” is used in this report, it always refers to the goods trade deficit). As the table shows, imports from China increased dramatically in this period, rising from $102.3 billion in 2001 to $505.6 billion in 2017.2 U.S. exports to China rose at a rapid rate from 2001 to 2017, but from a much smaller base, from $19.2 billion in 2001 to $130.4 billion in 2017. As a result, China’s exports to the United States in 2017 (“U.S. general imports”) were nearly four times greater than U.S. exports to China. These trade figures make the China trade relationship the United States’ most imbalanced trade relationship by far (authors’ analysis of USITC 2018).

Table 1

U.S.–China goods trade and job displacement, 2001–2017

Change ($billions) Percent change
2001 2008 2017 2001–2017 2008–2017 2001–2017 2008–2017
U.S. goods trade with China ($billions, nominal)
U.S. total exports* $19.2 $71.5 $130.4 $111.1 $58.9 577.8% 82.4%
U.S. general imports $102.3 $337.8 $505.6 $403.3 $167.8 394.3% 49.7%
U.S. trade balance ‑$83.0 ‑$266.3 -$375.2 -$292.2 -$108.9 351.8% 40.9%
Average annual change in the trade balance -$18.26 -$15.56 9.9%
Change (thousands of jobs) Percent change
U.S. trade-related jobs supported and displaced (thousands of jobs)
U.S. total exports—jobs supported 179.2 564.2 959.1 780.0 395.0 435.3% 70.0%
U.S. general imports—jobs displaced 1,170.7 3,616.9 5,311.3 4,140.6 1,694.4 353.7% 46.8%
U.S. trade deficit—net jobs displaced 991.5 3,052.7 4,352.2 3,360.6 1,299.4 338.9% 42.6%
Average annual change in net jobs displaced 210.0 185.6 9.7%

* Total exports as reported by the U.S. International Trade Commission include re-exports. The employment estimates shown here are based on total exports. See note 2 for additional details.

Source: Authors’ analysis of U.S. Census Bureau 2013, U.S. International Trade Commission 2018, and Bureau of Labor Statistics Employment Projections program 2017a and 2017b. For a more detailed explanation of data sources and computations, see the appendix.

Overall, the U.S. goods trade deficit with China grew from $83.0 billion in 2001 to $375.2 billion in 2017, an increase of $292.2 billion. Put another way, since China entered the WTO in 2001, the U.S. trade deficit with China has increased annually by $18.3 billion, or 9.9 percent, on average. Although not shown in the table, we can also examine the trade deficit in another way—not by how much it grew annually, but by adding up what the total deficit was each year to produce a cumulative figure. The data reveal that the cumulative U.S. trade deficit with China over the 2002–2017 (post-WTO) era was $4.2 trillion (USITC 2018 and authors’ calculations).

Between 2008 and 2017, the U.S. goods trade deficit with China increased $108.9 billion. This 40.9 percent increase occurred despite the Great Recession–induced collapse in world trade between 2008 and 2009 and the 23.4 percent decline in the U.S. trade deficit with the rest of the world between 2008 and 2017. As a result, China’s share of the overall U.S. goods trade deficit increased from 32.2 percent in 2008 to 46.5 percent in 2017. (The figures in this paragraph derive from the authors’ analysis of USITC 2018 and U.S. Census Bureau 2018c.)

The growing trade deficit with China has led to U.S. job losses

Each $1 billion in exports to another country from the United States supports some American jobs. However, each $1 billion in imports from another country leads to job loss—by eliminating existing jobs and preventing new job creation—as imports displace goods that otherwise would have been made in the United States by domestic workers.3 The net employment effect of trade depends on the changes in the trade balance. An improving trade balance can support job creation, but a growing trade deficit usually results in growing net U.S. job displacement. The net change in the U.S.–China trade balance between 2001 and 2017 also reflects the effect of trade in intermediate products between the two countries on net trade flows and job losses.

This is what has occurred with China since it entered the WTO; the United States’ widening trade deficit with China has been costing U.S. jobs. While some imports of parts and components from China have gone into the production of final goods, some of which have then been exported to China and the rest of the world, the overall U.S. trade deficit in manufactured products with China and the rest of the world has grown substantially since China entered the WTO.

This paper describes the net effect of the growing U.S.–China goods trade deficit (hereafter referred to as the U.S.–China trade deficit) on employment as jobs “lost or displaced,” with the terms “lost” and “displaced” used interchangeably.4 The employment impacts of the growing U.S. trade deficit with China are estimated in this paper using an input-output model that estimates the direct and indirect labor requirements of producing output in a given domestic industry. The model includes 205 U.S. industries, 76 of which are in the manufacturing sector (see the box titled “Trade and employment models,” as well as the appendix, for details on model structure and data sources). The Bureau of Labor Statistics Employment Projections program (BLS-EP) revised and updated its labor requirements model and related data in October 2017 (BLS-EP 2017a, 2017b). Our models have been revised and updated for this report using the latest available data.5

Scott 2017a estimated jobs lost or displaced due to the growth in the U.S.–China trade deficit from 2001 to 2015. The total job losses reported for 2001 to 2017 in Table 1 in this report are not significantly different than the job losses for 2001 to 2015 reported in Scott 2017a, despite a small increase in the trade deficit since 2015. This is primarily caused by changes in the structure of industry-specific price deflators from the Bureau of Labor Statistics (BLS-EP 2017b). In Scott 2017a, the deflators had a base year of 2005 (the price index is set to 1,000 in the base year). However, in their latest update (BLS-EP 2017b), BLS uses a base year of 2009. There are also some minor revisions in the most recent updates to the deflators that cause the real value of imports and exports to vary from previous years.6 Finally, deflators for 2017 have not yet been published by BLS. In the past, producer price indexes from BLS were used to extrapolate the deflators to the most recent year. In this version of the report, we use the 2026 price projections published by BLS to estimate deflators for 2017, by interpolation. Specifically, the annualized percent change between the 2016 and the 2026 price projections for each industry is applied to the deflator for 2016, to estimate price levels in 2017.

Trade and employment models

The Economic Policy Institute and other researchers have examined the job impacts of trade in recent years by subtracting the job opportunities lost to imports from those gained through exports. That general approach is used in this report. Specifically, this report uses standard input-output models and data to estimate the jobs displaced by trade. Many economists in the public and private sectors have used this type of all-but-identical methodology to estimate jobs gained or displaced by trade, including Groshen, Hobijn, and McConnell (2005) of the Federal Reserve Bank of New York and Bailey and Lawrence (2004) in the Brookings Papers on Economic Activity. The U.S. Department of Commerce has published estimates of the jobs supported by U.S. exports (Tschetter 2010). That study uses input-output and “employment requirements” tables from the Bureau of Labor Statistics Employment Projections program (earlier editions of BLS-EP 2017a), the same source used to develop job displacement estimates in this report. The Tschetter report represents the work of a panel of experts from 20 federal agencies.7

The model estimates the amount of labor (number of jobs) required to produce a given volume of exports and the labor displaced when a given volume of imports is substituted for domestic output. The difference between these two numbers is essentially the jobs displaced by the growing trade deficit, holding all else equal.

Jobs displaced by the United States’ growing trade deficit with China are a net drain on employment in trade-related industries, especially those in manufacturing. Even if increases in demand in other sectors absorb all the workers displaced by trade (which is unlikely), job quality will likely suffer because many nontraded industries such as retail trade and home health care pay lower wages and have less comprehensive benefits than traded-goods industries (Scott 2013, 2017a).

As shown in the bottom panel of Table 1, U.S. exports to China in 2001 supported 179,200 jobs, but U.S. imports displaced production that would have supported 1,170,700 jobs. Therefore, the $83.0 billion trade deficit in 2001 displaced 991,500 jobs in that year. Net job displacement rose to 3,052,700 jobs in 2008 and 4,352,200 jobs in 2017. As a result, since China’s entry into the WTO in 2001 and through 2017, the increase in the U.S.–China trade deficit eliminated or displaced 3,360,600 U.S. jobs. Also shown in Table 1, the U.S. trade deficit with China increased by $108.9 billion (or 40.9 percent) between 2008 and 2017. During that period, the number of jobs displaced increased by 1,299,400 (or 42.6 percent).

For comparative purposes, the growth of the U.S.–China trade deficit between 2001 and 2017 represents a direct loss of 1.5 percent of U.S. GDP in 2017 (authors’ analysis of BEA 2018). Using a macroeconomic model with standard economic multipliers (see Appendix: Methodology in Scott and Glass 2016 for further details) yields an estimate of 3.2 million jobs displaced by a trade deficit of this magnitude, providing further support for the job displacement estimates shown in Table 1.8

Total jobs lost or displaced between 2008 and 2017 alone amounted to 1,299,400, either by the elimination of existing jobs or by the prevention of new job creation through the displacement of domestic production by imports.

The total number of jobs displaced by the growing U.S.–China trade deficit, as estimated here, is thus directly proportional to the size of the total bilateral deficit, which has increased steadily throughout the 2001–2017 period, except for a sharp decline in the recession year of 2009 and a much smaller drop in 2016. Figure A shows visually how rising trade deficits have displaced a growing number of jobs every year since China joined the WTO, with the exception of 2009 (during the Great Recession) and 2016 (during a brief lull in imports from China). On average, 210,000 jobs per year have been lost or displaced since China’s entry into the WTO (as shown in Table 1, last row, data column four).

Figure A

U.S. jobs displaced by the growing goods trade deficit with China since 2001 (in thousands of jobs)

Year  Jobs displaced (thousands)
2001 0.0
2002 225.5
2003 459.3
2004 872.3
2005 1,334.9
2006 1,686.8
2007 1,998.0
2008 2,061.2
2009 1,713.6
2010 2,339.2
2011 2,645.0
2012 2,785.8
2013 2,823.8
2014 2,990.0
2015 3,191.6
2016 2,999.6
2017 3,360.6

Source: Authors’ analysis of U.S. Census Bureau 2013, U.S. International Trade Commission 2018, and Bureau of Labor Statistics Employment Projections program 2017a and 2017b. For a more detailed explanation of data sources and computations, see the appendix.

The continuing growth of job displacement between 2008 and 2017 slightly outpaced the increase in the bilateral trade deficit in this period because of the relatively rapid growth of U.S. imports of computer and electronic parts from China, discussed below, and the fact that the price index for most of these products fell continuously throughout the study period. The share of U.S. imports from China accounted for by computer and electronic parts (in current, nominal dollars) increased from 32.0 percent in 2008 to 36.5 percent in 2017 (according to the authors’ analysis of USITC 2018).

Unfortunately, growing job losses due to outsourcing and growing trade deficits with China are only part of the story.

Next we turn to analysis of direct China trade and job loss in more detail.

The trade deficit and job losses, by industry

The composition of imports from China is changing in fundamental ways, with significant, negative implications for certain kinds of high-skill, high-wage jobs once thought to be the hallmark of the U.S. economy. Since it entered the WTO in 2001, China has moved rapidly “upscale,” from low-tech, low-skill, labor-intensive industries such as apparel, footwear, and basic electronics to more capital- and skills-intensive industries such as computers, electrical machinery, and motor vehicle parts. It has developed a rapidly growing trade surplus in these specific industries and in high-technology products in general.

Table 2 provides a snapshot of the changes in U.S.–China goods trade flows between 2001 and 2017, by industry, for imports, exports, and the trade balance. The rapid growth of the bilateral trade deficit in computer and electronic parts (including computer and peripheral equipment, semiconductors, and audio and video equipment) accounted for 50.7 percent of the $292.1 billion increase in the U.S. trade deficit with China between 2001 and 2017. In 2017, the total U.S. trade deficit with China was $375.2 billion—$167.3 billion of which was in computer and electronic parts (trade flows by industry in 2001 and 2017 are shown in Supplemental Table 1, available at the end of this document).

Table 2

Change in U.S. goods trade with China, by industry, 2001–2017

U.S. imports U.S. exports Trade balance
Industry* Change ($billions, nominal) Share of total change Change ($billions, nominal) Share of total change Change ($billions, nominal) Share of total change
Total change $403.2 100.0% $111.1 100.0% $-292.1 100.0%
Agriculture, forestry, fishing, and hunting 2.3 0.6% 17.3 15.6% 15.0 -5.1%
Mining -0.1 0.0% 8.5 7.7% 8.6 -3.0%
Oil and gas 0.1 0.0% 6.8 6.2% 6.8 -2.3%
Minerals and ores 0.1 0.0% 1.7 1.5% 1.6 -0.5%
Manufacturing 400.8 99.4% 80.0 72.0% -320.8 109.8%
Nondurable goods 44.1 10.9% 3.5 3.2% -40.6 13.9%
Food 3.2 0.8% 2.5 2.3% -0.6 0.2%
Beverage and tobacco products 0.1 0.0% 0.2 0.2% 0.1 0.0%
Textile mills and textile product mills 11.8 2.9% 0.4 0.4% -11.4 3.9%
Apparel 20.7 5.1% 0.1 0.1% -20.7 7.1%
Leather and allied products 8.3 2.0% 0.3 0.3% -7.9 2.7%
Industrial supplies 44.5 11.0% 20.3 18.3% -24.2 8.3%
Wood products 3.1 0.8% 1.8 1.6% -1.3 0.4%
Paper 2.6 0.6% 2.2 2.0% -0.4 0.1%
Printed matter and related products 2.1 0.5% 0.1 0.1% -2.0 0.7%
Petroleum and coal products 0.5 0.1% 1.1 1.0% 0.7 -0.2%
Chemicals 16.4 4.1% 12.9 11.7% -3.4 1.2%
Plastics and rubber products 14.6 3.6% 1.5 1.3% -13.1 4.5%
Nonmetallic mineral products 5.4 1.3% 0.7 0.6% -4.7 1.6%
Durable goods 312.2 77.4% 56.2 50.6% -230.5 78.9%
Primary metals 3.6 0.9% 2.0 1.8% -1.6 0.5%
Fabricated metal products 18.8 4.7% 2.1 1.9% -16.8 5.7%
Machinery 30.5 7.6% 6.8 6.1% -23.7 8.1%
Computer and electronic parts 160.0 39.7% 11.8 10.6% -148.2 50.7%
Computer and peripheral equipment 50.4 12.5% 0.7 0.7% -49.7 17.0%
Communications, audio, and video equipment 81.3 20.2% 1.1 0.9% -80.3 27.5%
Navigational, measuring, electromedical, and control instruments 6.1 1.5% 4.6 4.1% -1.5 0.5%
Semiconductor and other electronic components, and reproducing magnetic and optical media 22.2 5.5% 5.4 4.9% -16.8 5.7%
Electrical equipment, appliances, and components 34.2 8.5% 2.8 2.5% -31.4 10.8%
Transportation equipment 17.2 4.3% 26.6 24.0% 9.4 -3.2%
Motor vehicles and motor vehicle parts 14.8 3.7% 12.9 11.6% -1.9 0.6%
Aerospace products and parts 0.9 0.2% 13.7 12.3% 12.8 -4.4%
Railroad, ship, and other transportation equipment 1.6 0.4% 0.1 0.1% -1.5 0.5%
Furniture and related products 18.6 4.6% 0.2 0.1% -18.4 6.3%
Miscellaneous manufactured commodities 29.3 7.3% 3.9 3.5% -21.0 7.2%
Scrap and secondhand goods 0.2 0.1% 5.3 4.8% 5.1 -1.7%

* Excludes utilities, construction, and service sectors, which reported no goods trade in this period, and information, which reported negligible goods trade in this period.

Source: Authors’ analysis of U.S. International Trade Commission 2018. For a more detailed explanation of the data sources and computations, see the appendix.

As evident in the increasing trade deficit and also shown in Table 2, imports from China far exceeded exports to China between 2001 and 2017. Table 2 further shows that the growth in manufactured goods imports explained virtually all (99.4 percent) of total growth in imports from China between 2001 and 2017 and included a wide array of products. Computer and electronic parts were responsible for 39.7 percent of the growth in imports in this period, including computer equipment ($50.4 billion, or 12.5 percent of the overall growth in imports) and communications, audio, and video equipment ($81.3 billion, or 20.2 percent). Other major importing sectors included electrical equipment ($34.2 billion, or 8.5 percent), machinery ($30.5 billion, or 7.6 percent), apparel ($20.7 billion, or 5.1 percent) and miscellaneous manufactured commodities ($29.3 billion, or 7.3 percent).

As Table 2 shows, manufacturing was also the top sector exporting to China—72.0 percent of the growth in exports to China between 2001 and 2017 was in manufactured goods, totaling $80.0 billion. Within manufacturing, key export-growth industries included chemicals ($12.9 billion, or 11.7 percent of the growth in exports), aerospace products and parts ($13.7 billion, or 12.3 percent), motor vehicles and parts ($12.9 billion, or 11.6 percent), computer and electronic parts ($11.8 billion, or 10.6 percent), and machinery ($6.8 billion, or 6.1 percent). Scrap and secondhand goods industries—which support no jobs, according to the models used in this report (BLS-EP 2017a)9—accounted for 4.8 percent ($5.3 billion) of the growth in exports.

Agricultural exports—which were dominated by corn, soybeans, and other cash grains—grew faster than any individual manufacturing industry except for transportation equipment, increasing $17.3 billion (15.6 percent of the total increase) between 2001 and 2017. Nonetheless, the overall scale of U.S. total exports to China in 2017 was dwarfed by imports from China in that year, which exceeded the value of exports by nearly 4 to 1, as shown in Table 1.

The import data in Table 2 reflect China’s rapid expansion into higher-value-added commodities once considered strengths of the United States, such as computer and electronic parts, which accounted for 36.5 percent ($184.4 billion) of U.S. imports from China in 2017 (as shown in Supplemental Table 1). This growth is apparent in the shifting trade balance in advanced technology products (ATP), a broad category of high-end technology goods trade tracked by the U.S. Census Bureau (but not broken out in Table 2, which uses U.S. International Trade Commission data).10 ATP includes the more advanced elements of the computer and electronic parts industry as well as other sectors such as biotechnology, life sciences, aerospace, nuclear technology, and flexible manufacturing. The ATP sector includes some auto parts; China is one of the top suppliers of auto parts to the United States, having surpassed Germany (Scott and Wething 2012).

In 2017, the United States had a $135.4 billion trade deficit with China in ATP, reflecting a tenfold increase from $11.8 billion in 2002.11 This ATP deficit was responsible for 36.1 percent of the total U.S.–China trade deficit in 2017. It dwarfs the $25.0 billion surplus in ATP that the United States had with the rest of the world in 2017. As a result of the U.S. ATP deficit with China, the United States ran an overall deficit in ATP products in 2017 (of $110.4 billion), as it has in every year since 2002 (U.S. Census Bureau 2018b).

Job loss or displacement by industry is directly related to trade flows by industry, as shown in Table 3.12 The growing trade deficit with China eliminated 2,500,500 manufacturing jobs between 2001 and 2017, nearly three-fourths (74.4 percent) of the total. By far the largest job displacements occurred in the computer and electronic parts industry, which lost 1,209,900 jobs (36.0 percent of the 3.4 million jobs displaced overall). This industry includes computer and peripheral equipment (661,300 jobs lost, or 19.7 percent of the overall jobs displaced), semiconductors and components (284,200 jobs, or 8.5 percent), and communications, audio, and video equipment (247,800 jobs, or 7.4 percent).

Table 3

Net U.S. jobs created or displaced by goods trade with China, by industry, 2001–2017

Total Share of total jobs displaced
Total* -3,360,600
Subtotal, nonmanufacturing -860,100 25.6%
Subtotal, manufacturing -2,500,500 74.4%
Agriculture, forestry, fishing, and hunting 76,500 -2.3%
Mining 1,300 0.0%
Oil and gas 4,400 -0.1%
Minerals and ores -3,000 0.1%
Utilities -9,500 0.3%
Construction -13,500 0.4%
Manufacturing -2,500,500 74.4%
Nondurable goods -332,900 9.9%
Food -6,400 0.2%
Beverage and tobacco products 0 0.0%
Textile mills and textile product mills -119,100 3.5%
Apparel -169,000 5.0%
Leather and allied products -38,500 1.1%
Industrial supplies -226,700 6.7%
Wood products -29,600 0.9%
Paper -24,000 0.7%
Printed matter and related products -28,400 0.8%
Petroleum and coal products -900 0.0%
Chemicals -32,400 1.0%
Plastics and rubber products -78,700 2.3%
Nonmetallic mineral products -32,800 1.0%
Durable goods -1,940,800 57.8%
Primary metals -53,200 1.6%
Fabricated metal products -144,100 4.3%
Machinery -108,700 3.2%
Computer and electronic parts -1,209,900 36.0%
Computer and peripheral equipment -661,300 19.7%
Communications, audio, and video equipment -247,800 7.4%
Navigational, measuring, electromedical, and control instruments -16,600 0.5%
Semiconductors and other electronic components, and reproducing magnetic and optical media -284,200 8.5%
Electrical equipment, appliances, and components -145,300 4.3%
Transportation equipment -17,800 0.5%
Motor vehicles and motor vehicle parts -44,700 1.3%
Aerospace products and parts 32,500 -1.0%
Railroad, ship, and other transportation equipment -5,700 0.2%
Furniture and related products -135,200 4.0%
Miscellaneous manufactured commodities -126,600 3.8%
Wholesale trade -184,000 5.5%
Retail trade -43,200 1.3%
Transportation and warehousing -92,700 2.8%
Information -43,100 1.3%
Finance and insurance -62,600 1.9%
Real estate and rental and leasing -12,300 0.4%
Professional, scientific, and technical services -104,400 3.1%
Management of companies and enterprises -122,900 3.7%
Administrative and support and waste management and remediation services -161,700 4.8%
Education services -1,800 0.1%
Healthcare and social assistance -1,600 0.0%
Arts, entertainment, and recreation -10,100 0.3%
Accommodation and food services -34,400 1.0%
Other services (except public administration) -26,700 0.8%
Public administration -13,600 0.4%

* Subcategory and overall totals may vary slightly due to rounding.

Source: Authors’ analysis of U.S. Census Bureau 2013, U.S. International Trade Commission 2018, and Bureau of Labor Statistics Employment Projections program 2017a and 2017b. For a more detailed explanation of data sources and computations, see the appendix.

Other hard-hit industries include apparel (169,000 jobs displaced, equal to 5.0 percent of the total), electrical equipment, appliances, and components (145,300 jobs, or 4.3 percent), fabricated metal products (144,100 jobs, or 4.3 percent), furniture and related products (135,200 jobs, or 4.0 percent), miscellaneous manufactured commodities (126,600 jobs, or 3.8 percent), textile mills and textile product mills (119,100 jobs, or 3.5 percent), plastics and rubber products (78,700 jobs, or 2.3 percent), and motor vehicles and motor vehicle parts (44,700 jobs, or 1.3 percent). In addition, surging imports of steel, aluminum, and other capital-intensive products threaten hundreds of thousands of jobs in key metal-using industries such as primary metals, machinery, and fabricated metal products.

Several service industries, which provide key inputs to traded-goods production, experienced significant job displacement, including administrative and support and waste management and remediation services (161,700 jobs, or 4.8 percent of overall jobs displaced) and professional, scientific, and technical services (104,400 jobs, or 3.1 percent).

These job displacement estimates are based on changes in the real value of exports and imports. For example, while the share of U.S. imports accounted for by computer and electronic parts from China rose from 23.8 percent in 2001 to 36.5 percent in 2017 (to $184.4 billion, as shown in Supplemental Table 1), the average price indexes (deflators) for most of these products fell sharply between 2001 and 2017—47.4 percent on a trade-weighted basis. Thus, the real value of computer and electronic parts imports increased more than twelvefold in this period, rising from $16.3 billion in 2001 to $208.7 billion in 2017 in constant 2009 dollars (authors’ analysis of real trade flows; see the methodology appendix for data sources and computational details).13

Missed opportunities to create more jobs through fair trade with China

The trade and jobs analysis in this report is focused on the actual jobs gained and lost due to increased trade with China over the past 16 years. This raises the question of what trade and employment could have looked like but for the massive growth of the U.S. trade deficit with China between 2001 and 2017. A full analysis of such scenarios at the level of employment impacts by industry and geographic area is beyond the scope of this report. It will be the subject of future research. But the broad outlines of one such scenario can be quickly sketched from the trade data in Table 2.

To have maintained a stable trade balance with China between 2001 and 2017, imports would have had to grow less rapidly or exports would have had to grow more rapidly—or some combination of the two. For example, had U.S. export growth to China matched the growth of China’s exports to the United States dollar for dollar between 2001 and 2017, balanced trade would have required roughly a fourfold increase in U.S. exports to China in 2017.14 If actual 2017 exports in each industry (shown in Supplemental Table 1) had increased by this ratio (the specific ratio is 3.88-to-1), then the largest growth in exports would have occurred in transportation equipment ($111.7 billion), agricultural products ($71.0 billion), computer and electronic parts ($61.0 billion), chemicals ($56.6 billion), machinery ($33.6 billion), and food and beverage products ($12.8 billion). In total, U.S. exports to China would have increased by $486.4 billion, $375.2 billion more than they actually did.15

If exports to China had increased at this pace, it would have supported the creation of millions of U.S. manufacturing jobs and prevented much of the collapse of overall U.S. manufacturing employment between December 2001 and December 2017, when 3.2 million U.S. manufacturing jobs were lost (BLS 2018b). This level of growth in U.S. exports to China could not have taken place without major structural changes in China’s trade, industrial, macroeconomic, and labor policies. This analysis does illustrate the potential gains had China trade delivered on the promises made by China trade proponents when China entered the WTO in 2001.

Job losses by state

Growing U.S. trade deficits with China have reduced demand for goods produced in every region of the United States and have led to job displacement in all 50 states and the District of Columbia, as shown in Table 4 and Figure B. (Supplemental Table 2 ranks the states by the number of net jobs displaced, while Supplemental Table 3 ranks the states by jobs displaced as a share of total state jobs and presents the states alphabetically.) Table 4 shows that jobs displaced from 2001 to 2017 due to the growing goods trade deficit with China ranged from 0.29 percent to 3.59 percent of total state employment. The 10 hardest-hit states ranked by job shares displaced were New Hampshire, Oregon, California, Minnesota, North Carolina, Rhode Island, Massachusetts, Vermont, Wisconsin, and Texas. This list includes states with high-tech industries (California, Massachusetts, Minnesota, Oregon, and Texas) and manufacturing states (New Hampshire, North Carolina, Rhode Island, Vermont, and Wisconsin). Job losses in these states ranged from 2.57 percent to 3.55 percent of total state employment. Other traditional manufacturing powers—such as Georgia, Kentucky, Indiana, Illinois, South Carolina, and Tennessee—are among the top 20 hardest-hit states, as is Idaho, also a high-tech hub.

Table 4

Net U.S. jobs displaced due to goods trade deficit with China, by state, 2001–2017 (ranked by jobs displaced as a share of total state employment)

Rank State Net jobs displaced State employment Jobs displaced as share
of state employment
1 New Hampshire 24,000 675,500 3.55%
2 Oregon 62,900 1,873,900 3.36%
3 California 562,500 16,818,700 3.34%
4 Minnesota 88,300 2,932,100 3.01%
5 North Carolina 130,800 4,415,800 2.96%
6 Rhode Island 14,100 494,500 2.84%
7 Massachusetts 99,100 3,609,500 2.75%
8 Vermont 8,600 314,200 2.74%
9 Wisconsin 78,700 2,945,200 2.67%
10 Texas 314,000 12,224,200 2.57%
11 Indiana 77,900 3,105,300 2.51%
12 Idaho 17,600 716,600 2.46%
13 Illinois 148,200 6,062,400 2.45%
14 South Carolina 50,800 2,091,500 2.43%
15 Kentucky 45,400 1,921,200 2.36%
16 New Jersey 96,700 4,129,100 2.34%
17 Alabama 46,900 2,015,400 2.33%
18 Georgia 103,100 4,453,400 2.32%
19 Tennessee 69,300 3,011,200 2.30%
20 Pennsylvania 136,100 5,948,000 2.29%
21 Arizona 63,400 2,774,000 2.29%
22 Connecticut 38,400 1,681,600 2.28%
23 Colorado 59,500 2,658,700 2.24%
24 Mississippi 25,300 1,152,200 2.20%
25 Ohio 121,400 5,528,600 2.20%
26 Arkansas 26,800 1,239,600 2.16%
27 Michigan 92,400 4,372,500 2.11%
28 Utah 29,100 1,468,700 1.98%
29 New York 183,500 9,523,300 1.93%
30 Oklahoma 31,900 1,662,600 1.92%
31 Maine 11,900 622,800 1.91%
32 Iowa 29,900 1,573,200 1.90%
33 Washington 58,100 3,326,100 1.75%
34 Missouri 49,800 2,868,400 1.74%
35 Virginia 66,200 3,952,100 1.68%
36 Maryland 43,000 2,723,700 1.58%
37 New Mexico 12,800 830,800 1.54%
38 Kansas 21,700 1,403,900 1.54%
39 Florida 125,500 8,569,600 1.46%
40 South Dakota 6,300 434,900 1.44%
41 West Virginia 10,600 745,400 1.42%
42 Nebraska 14,200 1,018,000 1.40%
43 Delaware 6,000 456,200 1.32%
44 Nevada 15,900 1,341,400 1.18%
45 Louisiana 21,200 1,970,800 1.08%
46 Hawaii 6,200 652,800 0.95%
47 Montana 4,200 472,700 0.89%
48 Alaska 2,700 329,100 0.83%
49 North Dakota 3,400 430,700 0.78%
50 Wyoming 2,000 281,700 0.72%
51 District of Columbia 2,300 790,500 0.29%
Total* 3,360,600 146,614,300 2.29%

* Totals may vary slightly due to rounding.

Source: Authors’ analysis of U.S. Census Bureau 2013, U.S. International Trade Commission 2018, and Bureau of Labor Statistics Employment Projections program 2017a and 2017b. For a more detailed explanation of data sources and computations, see the appendix.

Figure B

Net U.S. jobs displaced due to the goods trade deficit with China as a share of total state employment, 2001–2017

State Jobs displaced as share of state employment
New Hampshire 3.55%
Oregon 3.36%
California 3.34%
Minnesota 3.01%
North Carolina 2.96%
Rhode Island 2.84%
Massachusetts 2.75%
Vermont 2.74%
Wisconsin 2.67%
Texas 2.57%
Indiana 2.51%
Idaho 2.46%
Illinois 2.45%
South Carolina 2.43%
Kentucky 2.36%
New Jersey 2.34%
Alabama 2.33%
Georgia 2.32%
Tennessee 2.30%
Pennsylvania 2.291%
Arizona 2.286%
Connecticut 2.28%
Colorado 2.24%
Mississippi 2.20%
Ohio 2.20%
Arkansas 2.16%
Michigan 2.11%
Utah 1.98%
New York 1.93%
Oklahoma 1.92%
Maine 1.91%
Iowa 1.90%
Washington 1.75%
Missouri 1.74%
Virginia 1.68%
Maryland 1.58%
New Mexico 1.54%
Kansas 1.54%
Florida 1.46%
South Dakota 1.44%
West Virginia 1.42%
Nebraska 1.40%
Delaware 1.32%
Nevada 1.18%
Louisiana 1.08%
Hawaii 0.95%
Montana 0.89%
Alaska 0.83%
North Dakota 0.78%
Wyoming 0.72%
District of Columbia 0.29%

 

Source: Authors’ analysis of U.S. Census Bureau 2013, U.S. International Trade Commission 2018, and Bureau of Labor Statistics Employment Projections program 2017a and 2017b. For a more detailed explanation of data sources and computations, see the appendix.

As shown in Supplemental Table 2, the top 10 states in terms of total jobs lost were California (562,500 jobs), Texas (314,000), New York (183,500), Illinois (148,200), Pennsylvania (136,100), North Carolina (130,800), Florida (125,500), Ohio (121,400), Georgia (103,100), and Massachusetts (99,100).

The map in Figure B shows the broad impact of the growing trade deficit with China across the United States, with no areas exempt from job displacement. The 3.4 million U.S. jobs displaced due to the growing trade deficit with China between 2001 and 2017 represented 2.29 percent of total U.S. employment.

Job losses by congressional district

This study also reports the employment impacts of the growing U.S. goods trade deficit with China in every congressional district and in the District of Columbia. Table 5 lists the top 20 hardest-hit congressional districts (those with the largest job losses as a share of overall district employment). Figure C shows job displacement as a share of total district employment in all 435 congressional districts plus the District of Columbia. (Supplemental Table 4 shows the same data, but ranked by net jobs displaced, and Supplemental Table 5 provides the data sorted alphabetically by state.) Because the largest growth in the goods trade deficits with China from 2001 to 2017 occurred in the computer and electronic parts industry, 18 of the 20 hardest-hit districts were in Arizona, California, Illinois, Massachusetts, Minnesota, New York, Oregon, and Texas, where remaining jobs in that industry are concentrated. Georgia and North Carolina, which suffered considerable job displacement in a variety of manufacturing industries, also each have one district in the top 20 hardest-hit districts.16

Table 5

Twenty congressional districts hardest hit by U.S. goods trade deficit with China, 2001–2017 (ranked by jobs displaced as a share of district employment)

Rank State District Net jobs displaced District employment (in 2011) Jobs displaced as a share of district employment
1 California 17 59,500 346,100 17.19%
2 California 18 48,300 344,500 14.02%
3 California 19 38,600 324,000 11.91%
4 Texas 31 34,400 323,000 10.65%
5 Oregon 1 31,600 377,200 8.38%
6 California 15 26,900 336,400 8.00%
7 Georgia 14 17,600 290,700 6.05%
8 Texas 3 21,100 371,200 5.68%
9 Massachusetts 3 20,000 355,400 5.63%
10 California 40 14,800 280,500 5.28%
11 Texas 10 16,900 342,600 4.93%
12 California 52 16,900 350,100 4.83%
13 Illinois 6 17,000 355,600 4.78%
14 California 34 14,600 309,400 4.72%
15 Minnesota 1 16,400 348,200 4.71%
16 California 45 16,100 354,400 4.54%
17 Texas 18 13,700 306,400 4.47%
18 New York 18 14,800 332,100 4.46%
19 Arizona 5 13,500 317,900 4.25%
20 North Carolina 2 12,900 303,800 4.25%

Source: Authors’ analysis of U.S. Census Bureau 2013, U.S. International Trade Commission 2018, and Bureau of Labor Statistics Employment Projections program 2017a and 2017b. For a more detailed explanation of data sources and computations, see the appendix.

Figure C

Net U.S. jobs displaced due to the goods trade deficit with China as a share of total congressional district employment, 2001–2017

  0.74% or less   0.75% to < 1.44%   1.44% to < 2.14%   2.14% to < 2.84%   2.84% to < 3.54%   3.54% or more
Jobs displaced as a share of employment
Hover or click a district to view data
Rank (by jobs displaced as a share of total):
Net jobs displaced:
District employment (in 2011):
Rank (by jobs displaced as a share of total) State District Net jobs displaced District employment (in 2011) Jobs displaced as a share of employment
349 Alabama 1 4,200 283,000 1.48%
232 Alabama 2 5,700 276,900 2.06%
126 Alabama 3 7,100 274,600 2.59%
61 Alabama 4 8,500 262,900 3.23%
45 Alabama 5 10,900 311,900 3.49%
245 Alabama 6 6,400 318,400 2.01%
316 Alabama 7 4,200 253,500 1.66%
428 Alaska Statewide 2,700 344,300 0.78%
376 Arizona 1 3,600 264,900 1.36%
302 Arizona 2 5,200 299,200 1.74%
373 Arizona 3 3,600 262,200 1.37%
355 Arizona 4 3,400 233,500 1.46%
19 Arizona 5 13,500 317,900 4.25%
152 Arizona 6 9,000 366,000 2.46%
153 Arizona 7 6,900 282,300 2.44%
227 Arizona 8 6,300 301,700 2.09%
59 Arizona 9 11,800 360,300 3.28%
291 Arkansas 1 5,000 277,400 1.80%
211 Arkansas 2 7,200 336,300 2.14%
115 Arkansas 3 8,600 327,000 2.63%
236 Arkansas 4 6,000 295,100 2.03%
265 California 1 5,000 260,300 1.92%
356 California 2 4,700 323,100 1.45%
425 California 3 2,600 286,600 0.91%
78 California 4 8,900 294,200 3.03%
221 California 5 6,900 326,800 2.11%
257 California 6 5,600 288,300 1.94%
53 California 7 10,600 313,200 3.38%
381 California 8 3,100 235,500 1.32%
336 California 9 4,200 275,300 1.53%
252 California 10 5,500 277,200 1.98%
281 California 11 6,000 324,200 1.85%
112 California 12 10,600 399,400 2.65%
68 California 13 10,700 340,200 3.15%
28 California 14 14,600 364,000 4.01%
6 California 15 26,900 336,400 8.00%
433 California 16 1,700 244,900 0.69%
1 California 17 59,500 346,100 17.19%
2 California 18 48,300 344,500 14.02%
3 California 19 38,600 324,000 11.91%
241 California 20 6,100 302,500 2.02%
436 California 21 200 243,800 0.08%
423 California 22 2,700 289,600 0.93%
432 California 23 2,000 274,100 0.73%
400 California 24 3,800 323,500 1.17%
151 California 25 7,500 302,700 2.48%
178 California 26 7,500 325,900 2.30%
132 California 27 8,500 332,200 2.56%
237 California 28 7,300 359,900 2.03%
156 California 29 7,400 303,700 2.44%
135 California 30 9,100 358,200 2.54%
240 California 31 5,900 292,200 2.02%
86 California 32 8,700 293,800 2.96%
187 California 33 8,200 364,200 2.25%
14 California 34 14,600 309,400 4.72%
31 California 35 11,300 284,800 3.97%
422 California 36 2,400 251,900 0.95%
108 California 37 9,000 335,600 2.68%
71 California 38 9,800 313,300 3.13%
37 California 39 12,600 332,000 3.80%
10 California 40 14,800 280,500 5.28%
214 California 41 5,800 271,900 2.13%
98 California 42 8,600 307,000 2.80%
128 California 43 7,800 302,800 2.58%
56 California 44 9,000 270,600 3.33%
16 California 45 16,100 354,400 4.54%
40 California 46 11,700 314,400 3.72%
154 California 47 8,000 327,600 2.44%
29 California 48 14,100 352,600 4.00%
30 California 49 11,900 299,700 3.97%
144 California 50 7,400 296,200 2.50%
301 California 51 4,500 258,600 1.74%
12 California 52 16,900 350,100 4.83%
184 California 53 7,800 342,700 2.28%
263 Colorado 1 7,400 384,400 1.93%
47 Colorado 2 13,400 384,600 3.48%
395 Colorado 3 4,000 331,400 1.21%
48 Colorado 4 11,800 344,100 3.43%
176 Colorado 5 7,300 315,900 2.31%
191 Colorado 6 8,200 369,600 2.22%
243 Colorado 7 7,300 362,500 2.01%
266 Connecticut 1 6,700 349,800 1.92%
264 Connecticut 2 6,700 348,600 1.92%
173 Connecticut 3 8,200 352,700 2.32%
172 Connecticut 4 8,000 343,000 2.33%
145 Connecticut 5 8,700 348,300 2.50%
430 DC Statewide 2,300 310,600 0.74%
363 Delaware Statewide 6,000 420,400 1.43%
418 Florida 1 3,000 303,900 0.99%
397 Florida 2 3,600 301,500 1.19%
420 Florida 3 2,700 277,000 0.97%
364 Florida 4 4,700 329,900 1.42%
359 Florida 5 4,100 284,000 1.44%
338 Florida 6 4,300 283,200 1.52%
308 Florida 7 5,500 322,500 1.71%
100 Florida 8 7,900 283,400 2.79%
413 Florida 9 3,400 317,200 1.07%
385 Florida 10 4,300 331,500 1.30%
372 Florida 11 3,000 217,400 1.38%
201 Florida 12 6,200 283,200 2.19%
180 Florida 13 7,100 309,200 2.30%
332 Florida 14 5,000 320,700 1.56%
341 Florida 15 4,600 304,200 1.51%
320 Florida 16 4,500 276,100 1.63%
435 Florida 17 1,500 248,700 0.60%
367 Florida 18 4,000 284,000 1.41%
414 Florida 19 2,800 265,200 1.06%
348 Florida 20 4,500 302,100 1.49%
340 Florida 21 4,800 316,800 1.52%
207 Florida 22 7,200 332,000 2.17%
204 Florida 23 7,400 339,900 2.18%
362 Florida 24 4,200 293,400 1.43%
300 Florida 25 5,700 326,000 1.75%
383 Florida 26 4,400 335,600 1.31%
312 Florida 27 5,300 313,600 1.69%
403 Georgia 1 3,300 286,100 1.15%
267 Georgia 2 4,800 251,200 1.91%
89 Georgia 3 8,400 285,800 2.94%
269 Georgia 4 5,900 311,700 1.89%
279 Georgia 5 5,900 318,100 1.85%
129 Georgia 6 9,300 361,200 2.57%
51 Georgia 7 10,600 312,500 3.39%
345 Georgia 8 4,100 272,700 1.50%
81 Georgia 9 8,500 284,600 2.99%
228 Georgia 10 6,000 287,400 2.09%
167 Georgia 11 8,000 340,900 2.35%
258 Georgia 12 5,400 278,200 1.94%
298 Georgia 13 5,500 312,800 1.76%
7 Georgia 14 17,600 290,700 6.05%
394 Hawaii 1 4,000 330,100 1.21%
431 Hawaii 2 2,200 299,400 0.73%
83 Idaho 1 9,800 329,900 2.97%
197 Idaho 2 7,800 355,000 2.20%
328 Illinois 1 4,600 290,200 1.59%
259 Illinois 2 5,400 278,200 1.94%
229 Illinois 3 6,600 319,500 2.07%
97 Illinois 4 9,200 326,600 2.82%
175 Illinois 5 9,200 397,600 2.31%
13 Illinois 6 17,000 355,600 4.78%
318 Illinois 7 4,900 298,500 1.64%
41 Illinois 8 13,100 366,300 3.58%
110 Illinois 9 9,300 347,200 2.68%
52 Illinois 10 11,000 324,800 3.39%
66 Illinois 11 11,000 347,300 3.17%
331 Illinois 12 4,700 301,000 1.56%
380 Illinois 13 4,300 326,600 1.32%
67 Illinois 14 11,100 351,000 3.16%
276 Illinois 15 5,900 316,500 1.86%
205 Illinois 16 7,200 330,800 2.18%
169 Illinois 17 7,300 311,700 2.34%
262 Illinois 18 6,500 337,500 1.93%
226 Indiana 1 6,500 310,600 2.09%
62 Indiana 2 10,200 317,800 3.21%
43 Indiana 3 11,600 327,000 3.55%
168 Indiana 4 7,700 328,500 2.34%
235 Indiana 5 7,300 357,700 2.04%
96 Indiana 6 8,800 311,900 2.82%
171 Indiana 7 7,300 312,200 2.34%
60 Indiana 8 10,700 329,300 3.25%
185 Indiana 9 7,700 339,400 2.27%
138 Iowa 1 9,900 392,300 2.52%
183 Iowa 2 8,500 373,400 2.28%
335 Iowa 3 6,000 390,800 1.54%
360 Iowa 4 5,500 382,300 1.44%
405 Kansas 1 3,900 345,900 1.13%
323 Kansas 2 5,500 339,900 1.62%
181 Kansas 3 8,500 370,300 2.30%
404 Kansas 4 3,800 332,900 1.14%
174 Kentucky 1 6,600 284,800 2.32%
109 Kentucky 2 8,500 317,100 2.68%
114 Kentucky 3 8,800 333,300 2.64%
246 Kentucky 4 6,700 333,500 2.01%
357 Kentucky 5 3,400 234,300 1.45%
50 Kentucky 6 11,400 335,400 3.40%
409 Louisiana 1 3,900 354,000 1.10%
421 Louisiana 2 3,200 329,000 0.97%
411 Louisiana 3 3,600 328,100 1.10%
393 Louisiana 4 3,800 311,100 1.22%
419 Louisiana 5 2,800 283,900 0.99%
408 Louisiana 6 4,100 367,800 1.11%
287 Maine 1 6,200 340,400 1.82%
270 Maine 2 5,700 302,700 1.88%
333 Maryland 1 5,300 342,300 1.55%
384 Maryland 2 4,600 351,700 1.31%
371 Maryland 3 5,100 369,500 1.38%
354 Maryland 4 5,600 384,100 1.46%
390 Maryland 5 4,600 368,200 1.25%
288 Maryland 6 6,600 363,200 1.82%
375 Maryland 7 4,300 315,700 1.36%
311 Maryland 8 6,800 400,100 1.70%
297 Massachusetts 1 6,000 341,000 1.76%
25 Massachusetts 2 14,800 356,500 4.15%
9 Massachusetts 3 20,000 355,400 5.63%
39 Massachusetts 4 14,000 374,800 3.74%
55 Massachusetts 5 12,900 387,400 3.33%
127 Massachusetts 6 9,600 372,000 2.58%
334 Massachusetts 7 5,700 369,800 1.54%
202 Massachusetts 8 8,200 375,600 2.18%
188 Massachusetts 9 7,900 352,300 2.24%
322 Michigan 1 4,700 290,200 1.62%
74 Michigan 2 9,700 315,900 3.07%
121 Michigan 3 8,200 315,300 2.60%
216 Michigan 4 6,100 286,300 2.13%
282 Michigan 5 4,900 264,800 1.85%
150 Michigan 6 7,700 310,400 2.48%
247 Michigan 7 6,000 299,100 2.01%
195 Michigan 8 7,300 330,800 2.21%
193 Michigan 9 7,200 326,100 2.21%
124 Michigan 10 8,000 308,700 2.59%
149 Michigan 11 8,500 342,100 2.48%
327 Michigan 12 5,000 313,800 1.59%
277 Michigan 13 4,300 230,700 1.86%
286 Michigan 14 4,700 257,700 1.82%
15 Minnesota 1 16,400 348,200 4.71%
24 Minnesota 2 15,000 358,300 4.19%
21 Minnesota 3 15,000 353,800 4.24%
155 Minnesota 4 8,200 336,000 2.44%
113 Minnesota 5 9,300 352,000 2.64%
64 Minnesota 6 11,100 348,700 3.18%
209 Minnesota 7 7,100 328,700 2.16%
244 Minnesota 8 6,100 303,400 2.01%
42 Mississippi 1 10,900 305,600 3.57%
329 Mississippi 2 4,200 266,900 1.57%
306 Mississippi 3 5,200 303,900 1.71%
314 Mississippi 4 5,100 304,900 1.67%
352 Missouri 1 4,900 331,500 1.48%
198 Missouri 2 8,300 378,600 2.19%
309 Missouri 3 6,300 370,000 1.70%
353 Missouri 4 4,800 324,900 1.48%
303 Missouri 5 6,000 345,300 1.74%
321 Missouri 6 5,800 355,900 1.63%
208 Missouri 7 7,300 337,400 2.16%
222 Missouri 8 6,300 298,500 2.11%
426 Montana Statewide 4,200 480,000 0.88%
307 Nebraska 1 5,500 321,700 1.71%
293 Nebraska 2 5,600 316,300 1.77%
416 Nebraska 3 3,100 305,600 1.01%
415 Nevada 1 3,000 284,700 1.05%
284 Nevada 2 5,700 309,400 1.84%
402 Nevada 3 3,900 336,500 1.16%
396 Nevada 4 3,300 274,300 1.20%
65 New Hampshire 1 11,200 352,600 3.18%
33 New Hampshire 2 12,800 332,200 3.85%
256 New Jersey 1 6,600 339,200 1.95%
368 New Jersey 2 4,500 324,400 1.39%
292 New Jersey 3 6,200 344,200 1.80%
239 New Jersey 4 6,600 326,400 2.02%
93 New Jersey 5 10,400 356,100 2.92%
157 New Jersey 6 8,600 353,600 2.43%
49 New Jersey 7 12,900 377,100 3.42%
120 New Jersey 8 9,700 371,000 2.61%
140 New Jersey 9 8,500 338,500 2.51%
274 New Jersey 10 5,800 310,700 1.87%
104 New Jersey 11 9,800 358,800 2.73%
242 New Jersey 12 7,100 352,400 2.01%
234 New Mexico 1 6,400 311,900 2.05%
429 New Mexico 2 2,100 273,100 0.77%
342 New Mexico 3 4,300 284,800 1.51%
141 New York 1 8,600 343,300 2.51%
139 New York 2 9,000 357,800 2.52%
273 New York 3 6,300 336,700 1.87%
374 New York 4 4,700 342,500 1.37%
315 New York 5 5,600 336,200 1.67%
305 New York 6 5,600 327,000 1.71%
159 New York 7 7,800 322,200 2.42%
346 New York 8 4,400 292,700 1.50%
366 New York 9 4,600 324,900 1.42%
347 New York 10 5,400 360,300 1.50%
351 New York 11 4,700 317,500 1.48%
290 New York 12 7,600 418,800 1.81%
350 New York 13 4,700 317,200 1.48%
337 New York 14 5,200 341,800 1.52%
358 New York 15 3,700 255,900 1.45%
326 New York 16 5,200 323,600 1.61%
249 New York 17 6,800 341,400 1.99%
18 New York 18 14,800 332,100 4.46%
84 New York 19 9,700 327,300 2.96%
296 New York 20 6,300 357,600 1.76%
272 New York 21 5,800 309,200 1.88%
131 New York 22 8,200 320,200 2.56%
182 New York 23 7,400 324,600 2.28%
166 New York 24 7,700 327,300 2.35%
73 New York 25 10,300 335,400 3.07%
294 New York 26 5,800 327,700 1.77%
199 New York 27 7,400 337,800 2.19%
186 North Carolina 1 6,600 291,800 2.26%
20 North Carolina 2 12,900 303,800 4.25%
398 North Carolina 3 3,600 305,600 1.18%
95 North Carolina 4 10,000 350,900 2.85%
44 North Carolina 5 11,500 324,500 3.54%
35 North Carolina 6 13,100 341,800 3.83%
324 North Carolina 7 5,100 315,400 1.62%
27 North Carolina 8 12,400 301,700 4.11%
111 North Carolina 9 9,900 371,400 2.67%
23 North Carolina 10 13,600 324,000 4.20%
88 North Carolina 11 8,700 295,400 2.95%
76 North Carolina 12 9,800 319,800 3.06%
32 North Carolina 13 13,600 349,900 3.89%
424 North Dakota Statewide 3,400 370,800 0.92%
261 Ohio 1 6,400 332,300 1.93%
280 Ohio 2 6,000 323,600 1.85%
278 Ohio 3 6,200 333,000 1.86%
91 Ohio 4 9,300 317,900 2.93%
105 Ohio 5 9,100 334,200 2.72%
190 Ohio 6 6,500 292,300 2.22%
90 Ohio 7 9,600 326,800 2.94%
119 Ohio 8 8,600 328,800 2.62%
224 Ohio 9 6,600 315,000 2.10%
206 Ohio 10 6,800 312,800 2.17%
289 Ohio 11 5,000 275,200 1.82%
255 Ohio 12 7,000 359,500 1.95%
107 Ohio 13 8,600 320,400 2.68%
80 Ohio 14 10,500 349,700 3.00%
283 Ohio 15 6,200 336,400 1.84%
137 Ohio 16 9,000 355,600 2.53%
130 Oklahoma 1 9,300 361,900 2.57%
304 Oklahoma 2 5,000 290,300 1.72%
378 Oklahoma 3 4,400 329,900 1.33%
223 Oklahoma 4 7,400 350,900 2.11%
319 Oklahoma 5 5,700 348,800 1.63%
5 Oregon 1 31,600 377,200 8.38%
317 Oregon 2 5,200 314,200 1.65%
87 Oregon 3 11,300 383,300 2.95%
179 Oregon 4 7,100 309,000 2.30%
164 Oregon 5 7,700 326,700 2.36%
299 Pennsylvania 1 4,800 273,300 1.76%
379 Pennsylvania 2 3,600 273,100 1.32%
94 Pennsylvania 3 9,100 317,700 2.86%
163 Pennsylvania 4 8,100 342,900 2.36%
162 Pennsylvania 5 7,500 316,800 2.37%
123 Pennsylvania 6 9,400 362,300 2.59%
194 Pennsylvania 7 7,500 339,700 2.21%
122 Pennsylvania 8 9,300 357,800 2.60%
215 Pennsylvania 9 6,500 304,800 2.13%
146 Pennsylvania 10 7,800 312,500 2.50%
217 Pennsylvania 11 7,000 329,300 2.13%
142 Pennsylvania 12 8,300 331,900 2.50%
225 Pennsylvania 13 7,100 339,000 2.09%
254 Pennsylvania 14 6,300 323,200 1.95%
99 Pennsylvania 15 9,600 343,800 2.79%
161 Pennsylvania 16 7,800 327,700 2.38%
147 Pennsylvania 17 7,800 312,600 2.50%
148 Pennsylvania 18 8,600 345,000 2.49%
106 Rhode Island 1 6,800 250,900 2.71%
101 Rhode Island 2 7,200 260,300 2.77%
361 South Carolina 1 4,300 299,800 1.43%
230 South Carolina 2 6,300 305,600 2.06%
36 South Carolina 3 10,100 264,500 3.82%
63 South Carolina 4 9,600 301,000 3.19%
58 South Carolina 5 9,100 275,200 3.31%
253 South Carolina 6 5,000 253,500 1.97%
170 South Carolina 7 6,300 269,400 2.34%
339 South Dakota 1 6,300 415,600 1.52%
125 Tennessee 1 7,700 297,600 2.59%
285 Tennessee 2 6,000 327,200 1.83%
117 Tennessee 3 7,800 297,000 2.63%
92 Tennessee 4 9,200 314,500 2.93%
103 Tennessee 5 9,700 353,400 2.74%
158 Tennessee 6 7,400 304,500 2.43%
79 Tennessee 7 8,600 285,800 3.01%
177 Tennessee 8 6,900 299,200 2.31%
248 Tennessee 9 6,100 305,300 2.00%
313 Texas 1 5,000 297,700 1.68%
22 Texas 2 15,400 364,600 4.22%
8 Texas 3 21,100 371,200 5.68%
212 Texas 4 6,400 299,300 2.14%
238 Texas 5 6,100 300,800 2.03%
160 Texas 6 8,400 348,800 2.41%
72 Texas 7 11,600 376,300 3.08%
260 Texas 8 6,000 309,200 1.94%
196 Texas 9 7,200 326,400 2.21%
11 Texas 10 16,900 342,600 4.93%
410 Texas 11 3,400 308,800 1.10%
85 Texas 12 10,000 337,500 2.96%
389 Texas 13 3,900 309,000 1.26%
386 Texas 14 3,900 303,300 1.29%
399 Texas 15 3,300 280,900 1.17%
250 Texas 16 5,600 281,300 1.99%
26 Texas 17 13,600 329,300 4.13%
17 Texas 18 13,700 306,400 4.47%
407 Texas 19 3,500 310,700 1.13%
388 Texas 20 4,000 311,400 1.28%
192 Texas 21 8,000 361,200 2.21%
251 Texas 22 7,000 352,500 1.99%
391 Texas 23 3,600 289,700 1.24%
54 Texas 24 13,100 388,600 3.37%
34 Texas 25 11,600 302,200 3.84%
133 Texas 26 9,400 368,300 2.55%
330 Texas 27 4,800 305,600 1.57%
406 Texas 28 3,000 266,300 1.13%
219 Texas 29 6,200 292,900 2.12%
200 Texas 30 6,400 292,300 2.19%
4 Texas 31 34,400 323,000 10.65%
38 Texas 32 13,600 360,900 3.77%
46 Texas 33 9,900 283,900 3.49%
412 Texas 34 2,600 242,200 1.07%
213 Texas 35 6,800 318,200 2.14%
343 Texas 36 4,400 291,900 1.51%
220 Utah 1 6,600 312,400 2.11%
189 Utah 2 6,800 305,700 2.22%
136 Utah 3 7,900 311,200 2.54%
165 Utah 4 7,800 331,500 2.35%
116 Vermont Statewide 8,600 327,300 2.63%
344 Virginia 1 5,300 352,400 1.50%
370 Virginia 2 4,700 339,800 1.38%
382 Virginia 3 4,200 320,100 1.31%
295 Virginia 4 5,800 327,900 1.77%
218 Virginia 5 6,700 316,100 2.12%
271 Virginia 6 6,400 339,900 1.88%
275 Virginia 7 6,800 364,600 1.87%
417 Virginia 8 4,200 423,700 0.99%
102 Virginia 9 8,200 298,400 2.75%
203 Virginia 10 8,200 376,400 2.18%
365 Virginia 11 5,700 400,900 1.42%
82 Washington 1 9,900 332,300 2.98%
387 Washington 2 4,100 318,900 1.29%
70 Washington 3 8,900 284,500 3.13%
427 Washington 4 2,300 284,500 0.81%
325 Washington 5 4,700 291,500 1.61%
392 Washington 6 3,400 275,500 1.23%
233 Washington 7 7,800 380,000 2.05%
369 Washington 8 4,400 318,000 1.38%
268 Washington 9 6,500 341,400 1.90%
231 Washington 10 6,000 291,300 2.06%
310 West Virginia 1 4,400 258,700 1.70%
377 West Virginia 2 3,600 266,900 1.35%
401 West Virginia 3 2,600 223,000 1.17%
75 Wisconsin 1 10,500 342,500 3.07%
210 Wisconsin 2 8,400 390,000 2.15%
77 Wisconsin 3 10,700 353,500 3.03%
143 Wisconsin 4 7,700 308,000 2.50%
57 Wisconsin 5 12,300 370,600 3.32%
69 Wisconsin 6 11,100 353,600 3.14%
134 Wisconsin 7 8,600 338,400 2.54%
118 Wisconsin 8 9,500 362,800 2.62%
434 Wyoming Statewide 2,000 290,000 0.69%

Source: Authors’ analysis of U.S. Census Bureau 2013, U.S. International Trade Commission 2018, and Bureau of Labor Statistics Employment Projections program 2017a and 2017b. For a more detailed explanation of data sources and computations, see the appendix.

Specifically, of the 20 hardest-hit districts, eight were in California (in rank order, the 17th, 18th, 19th, 15th, 40th, 52nd, 34th, and 45th), four were in Texas (31st, 3rd, 10th, and 18th), and one each were in Oregon (1st), Georgia (14th), Massachusetts (3rd), Illinois (6th), Minnesota (1st), New York (18th), Arizona (5th), and North Carolina (2nd). Job losses in these districts ranged from 12,900 jobs to 59,500 jobs, and from 4.25 percent to 17.19 percent of total district jobs. These distributions reflect both the size of some states (e.g., California and Texas) and the concentration of the industries hardest hit by the growing U.S.–China trade deficit. We have already mentioned the prevalence of the computer and electronic parts industry in certain states; other industries with a presence in these districts include furniture, textiles, apparel, and other manufactured products.

The three hardest-hit congressional districts were all located in Silicon Valley (South Bay Area) in California, including the 17th Congressional District (encompassing Sunnyvale, Cupertino, Santa Clara, Fremont, Newark, North San Jose, and Milpitas), which lost 59,500 jobs, equal to 17.19 percent of all jobs in the district; the 18th Congressional District (including parts of San Jose, Palo Alto, Redwood City, Menlo Park, Stanford, Los Altos, Campbell, Saratoga, Mountain View, and Los Gatos), which lost 48,300 jobs, or 14.02 percent; and the 19th Congressional District (most of San Jose and other parts of Santa Clara County), which lost 38,600 jobs, or 11.91 percent.17

Although the San Francisco Bay Area has experienced rapid growth over the past decade in software and related industries, this growth has come at the expense of direct employment in the production of computer and electronic parts. The computer and electronic parts manufacturing sector has experienced more actual job losses than any other major manufacturing industry has since China joined the WTO.18 There are substantial questions about the long-run ability of firms in the high-tech sectors to continue to innovate while offshoring most or all of the production in their industries (Shi 2010).

Other research confirms job losses from U.S.–China trade

Recent academic research has confirmed findings in this and earlier EPI research (e.g., Kimball and Scott 2014) that the growing U.S.–China trade deficit has caused significant loss of U.S. jobs, especially in manufacturing.

For example, Acemoglu et al. (2014) find that import competition with China from 1999 to 2011 was responsible for up to 2.4 million net job losses (including direct, indirect, and respending effects).19 This result compares with the finding in this paper that 2.6 million jobs were lost due to growing trade deficits with China between 2001 and 2011, as shown in Figure A. Thus, over a roughly comparable period, Acemoglu et al. estimate an employment impact that is roughly 90 percent as large as the estimate found in this study.20

Further academic confirmation of the impacts of China trade on manufacturing employment is provided by Pierce and Schott (2016). Pierce and Schott use an entirely different estimation technique based on differences in the pre- and post-China WTO entry maximum tariff rates, with and without permanent normal trade relations (PNTR) status, which the United States granted to China in the China–WTO implementing legislation. Pierce and Schott estimate the impacts of changes in U.S. international transactions between 1992 and 2008. They find that the grant of PNTR status to China “reduced relative employment growth of the average industry by 3.4 percentage points…after one year [and] 15.6 percentage points after 6 years” (following the grant of PNTR status to China in 2001). They do not translate percentage-point changes in employment into total jobs displaced, but data on changes in total manufacturing employment in this period provide a base of comparison.

The research in this paper looks at the total loss or displacement of jobs due to the growing trade deficit with China and the number of those lost jobs that are manufacturing jobs. We can check the consistency of this finding with a different approach—looking at the total loss of manufacturing jobs and estimating the number of those job losses that are due to growing trade deficits with China. The United States lost 3.2 million manufacturing jobs between December 2001 and December 2017, a decline of 20.0 percent in total manufacturing employment (BLS 2018b). Drawing from Pierce and Schott 2016 above, if 15.6 percentage points of this 20.0 percent decline can be attributed to the growth of the U.S. trade deficit with China, this implies that about 77.7 percent (or 2.5 million) of the manufacturing jobs lost in this period were lost due to the growing trade deficit with China. This estimate is identical to this study’s estimated total manufacturing jobs displaced by the growing U.S.–China trade deficit (2.5 million net jobs displaced). Thus, two other recent academic studies have concluded that the growing U.S.–China trade deficit is responsible for the displacement of at least 2 million U.S. manufacturing jobs since 1990, with most jobs lost since China entered the WTO in 2001.

Lost wages from the increasing trade deficit with China

Growing trade-related job displacement has several direct and indirect effects on workers’ wages. The direct wage effects are a function of the wages forgone in jobs displaced by growing U.S. imports from China minus wage gains from both jobs added in export-producing industries, versus the (lower) wages paid in alternative jobs in nontraded industries (U.S. workers displaced from traded-goods production in manufacturing industries who find jobs in nontraded goods industries experience permanent wage losses, as discussed below). Standard trade theory assumes that economic integration leads to “gains from trade” as workers move from low-productivity jobs in import-competing industries into higher-productivity jobs in export-competing industries. However, this assumption is proven incorrect in Scott 2013, which shows that import-competing jobs pay better than alternative jobs in export-producing industries. Specifically, Scott examines the gains and losses associated with direct changes in employment caused by growing U.S.–China trade deficits between 2001 and 2011, and finds that jobs displaced by imports from China actually paid 17.0 percent more than jobs exporting to China: $1,021.66 per week in import-competing industries versus $872.89 per week in exporting industries (Scott 2013, 24, Table 9a).21 Therefore, simple trade expansion that increases total trade with no underlying change in the trade balance will result in a net loss to workers as they move from higher-paying jobs in import-competing industries to lower-paying jobs in exporting industries.

Furthermore, jobs in both import-competing and exporting industries paid substantially more than jobs in nontraded industries, which pay $791.14 per week (Scott 2013, Table 9a, 24). Between 2001 and 2011, growing exports to China supported 538,000 U.S. jobs, but growing imports displaced 3,280,200 jobs, for a net loss of 2.7 million U.S. jobs (Scott 2013, Table 5, 13). Thus, not only did workers lose wages moving from import-competing to exporting industries, but 2.7 million workers were displaced from jobs where they earned $1,021.66 per week on average and (if they were lucky enough to find jobs) were mostly pushed into jobs in nontraded industries paying an average of only $791.14 per week (a decline of 22.6 percent). In total, U.S. workers suffered a direct net wage loss of $37 billion per year (Scott 2013, 26, Table 9b) due to trade with China. But the direct wage losses are just the tip of the iceberg.

As shown by Josh Bivens in Everybody Wins, Except for Most of Us (Bivens 2008a, with results updated in Bivens 2013), growing trade with China and other low-wage exporters essentially puts all American workers without a college degree (roughly 100 million workers) in direct competition with workers in China (and elsewhere) making much less. He shows that trade with low-wage countries was responsible for 90 percent of the growth in the college wage premium since 1995 (the college wage premium is the percent by which wages of college graduates exceed those of otherwise-equivalent high school graduates), relative to the wages earned by the 100 million non-college-educated workers. The growth of China trade alone was responsible for more than half of the growth in the college wage premium in that period, Bivens finds. To put these estimates in macroeconomic terms, in 2011, trade with low-wage countries lowered annual wages by 5.5 percent—roughly $1,800 per worker for all full-time, full-year workers without a college degree. To provide comparable economywide impact estimates, assume that 100 million workers without a college degree suffered average losses of $1,800 per year, which yields a total national loss of $180 billion (Scott 2017b). Therefore, the indirect, macroeconomic losses to U.S. workers without college degrees caused by growing trade with low-wage nations were about five times as large as the $37 billion in direct wage losses in 2011 from trade with China, and about 40 times as many workers were affected indirectly due to globalization’s wage-lowering effect (100 million) as were displaced by trade with China (2.7 million).22 And China trade alone was responsible for about 56.8 percent of the increase in the overall college/noncollege wage gap between 1995 and 2011.23

Additionally, Autor, Dorn, and Hanson estimate that rising exposure to low-cost Chinese imports lowers labor force participation and reduces wages in local labor markets; in particular, they find that increased import competition has a statistically significant depressing effect on nonmanufacturing wages (Autor, Dorn, and Hanson 2012, abstract). This confirms the findings of Bivens (2008a, 2013). They also find that “transfer benefits payments for unemployment, disability, retirement, and healthcare also rise sharply in exposed labor markets” and that “for the oldest group (50–64), fully 84% of the decline in [manufacturing] employment is accounted for by the rise in nonparticipation, relative to 71% among the prime-age group and 68% among the younger group” (Autor, Dorn, and Hanson 2012, abstract, 25). Thus, Autor, Dorn, and Hanson find that more than two-thirds of all workers displaced by growing competition with Chinese imports dropped out of the labor force. These results are explained, in part, by the finding that “9.9%…of those who lose employment following an import shock obtain federal disability insurance benefits [Social Security Disability Insurance (SSDI) benefits].” Additionally, “rising import exposure spurs a substantial increase in government transfer payments to citizens in the form of increased disability, medical, income assistance and unemployment benefits.” Moreover, “these transfer payments vastly exceed the expenses of the TAA [Trade Adjustment Assistance] program, which specifically targets workers who lose employment due to import competition” (Autor, Dorn, and Hanson 2012, 25, 30). In Autor and Hanson 2014, the effects are totaled, and they find that “for regions affected by Chinese imports, the estimated dollar increase in per capita SSDI payments is more than 30 times as large as the estimated dollar increases in TAA payments.”

The job and wage losses stemming from the growing U.S.–China trade deficit are real—and also increase demands on the social safety net

Some economists and others in the trade debate have argued that job loss numbers extrapolated from trade flows are uninformative because aggregate employment levels in the United States are set by a broad range of macroeconomic influences, not just by trade flows.24 However, while the trade balance is but one of many variables affecting aggregate job creation, it plays a large role in explaining structural change in employment, especially in the manufacturing sector. As noted earlier, between December 2001 and December 2017, 3.2 million U.S. manufacturing jobs were lost (BLS 2018b). The growth of the U.S. trade deficit with China was responsible for the displacement of 2.5 million manufacturing jobs in this period, or about 78.1 percent of manufacturing jobs lost. Thus, manufacturing job loss due to the growing trade deficit with China accounts for roughly four out of five U.S. manufacturing jobs lost or displaced in this period.

The employment impacts of trade identified in this paper can be interpreted as the “all else equal” effect of trade on domestic employment. The Federal Reserve, for example, may decide to cut interest rates to make up for job losses stemming from deteriorating trade balances (or any other economic influence), leaving net employment unchanged. This, however, does not change the fact that trade deficits by themselves are a net drain on employment. Even if macroeconomic policy is adjusted to offset the negative impact of the growing trade deficit with China on total employment, the structure of production and employment in the United States has been negatively affected (Scott 2017a).

The growing trade deficit with China has clearly reduced domestic employment in traded-goods industries, especially in the manufacturing sector, which has been pummeled by plant closings and job losses. Workers from the manufacturing sector displaced by trade have had particular difficulty securing comparable employment elsewhere in the economy. According to the most recent Bureau of Labor Statistics survey covering displaced workers (BLS 2018a, Table 4), more than one-third (35.3 percent) of long-tenured (employed more than three years) manufacturing workers displaced from January 2015 to December 2017 were not working in January 2018, including 21.7 percent who were not in the labor force, i.e., no longer even looking for work, and 13.7 percent who were unemployed.

As noted above, U.S. workers who were directly displaced by trade with China between 2001 and 2011 lost a collective $37.0 billion in wages as a result of accepting lower-paying jobs in nontraded industries or industries that export to China assuming, conservatively, that those workers are reemployed in nontraded goods industries (Scott 2013).25 Worse yet, growing competition with workers in China and other low-wage countries reduced the wages of all 100 million U.S. workers without a college degree, leading to cumulative losses of approximately $180 billion per year in 2011 (Bivens 2013; Scott 2017b). The lost output of unemployed workers, especially that of labor force dropouts, can never be regained and is one of the larger costs of trade-related job displacement to the economy as a whole.26

Trade Adjustment Assistance (TAA) program is a Department of Labor program to provide retraining and unemployment benefits to certain workers who have been displaced by growing imports. However, new research suggests that significant shares of displaced workers are signing up for disability and retirement benefits, other government income assistance, and government medical benefits, in addition to temporary trade adjustment assistance. Many of these workers, such as those on disability and retirement, are permanently dropping out of the labor force, resulting in permanent income losses to themselves and the economy. TAA benefits represent only a tiny share of the costs of adjustment. Examining only those costs for which workers actually qualify for government benefits, Autor, Dorn, and Hanson (2012, Figure 7 at 32) find that unemployment and TAA benefits represent only 6.3 percent of the total benefit costs associated with a $1,000 increase in imports per worker in “commuting zones” over the 1990–2007 period.27 Given the low level of coverage of social safety net programs in the United States versus other developed countries (such as those in the EU), actual adjustment costs for displaced workers are likely substantially larger than the actual U.S. benefits estimated by Autor, Dorn, and Hanson.

Conclusion

The growing U.S. goods trade deficit with China has displaced millions of jobs in the United States and has contributed heavily to the crisis in U.S. manufacturing employment, which has heightened over the last decade largely due to trade with China. Moreover, the United States is piling up foreign debt, losing export capacity, and facing a more fragile macroeconomic environment.

China and America are locked in destructive, interdependent economic cycles, and both can gain from rebalancing trade and capital flows. Although economic growth in China has been rapid, it is unbalanced and unsustainable. Growth in China slowed to 6.9 percent in 2017, and it is projected to fall to 5.5 percent in 2023 (IMF 2018). China’s economy is teetering on the edge between inflation and a growth slump, and a soft landing is nowhere in sight. China needs to rebalance its economy by becoming less dependent on exports and more dependent on domestic demand led by higher wages and infrastructure spending. It also needs to reduce excessive levels of domestic savings to better align savings levels with domestic investment and government borrowing. The best ways to do this are to raise wages and to increase public spending on pensions, health care, and other aspects of the safety net. This will reduce private saving and increase Chinese domestic demand for both domestic and imported goods, reducing China’s trade surplus (Scott 2017a).

The effects on the United States of China’s destructive, rapidly growing trade surplus are outlined in this report. To summarize, the growing U.S. trade deficit with China has eliminated 3.4 million U.S. jobs between 2001 and 2017, including 1.3 million jobs lost since 2008 (the first full year of the Great Recession). Nearly three-fourths of the jobs lost were in manufacturing. These losses were responsible for a substantial share of the 3.2 million U.S. manufacturing jobs lost between December 2001 and December 2017. The growing trade deficit with China has reduced wages of those directly displaced by $37 billion through 2011 alone, and it is largely responsible for the loss of nearly $2,000 per worker per year, due to wage suppression, for all non-college-educated workers in the United States. These losses have been extremely costly for the workers and communities affected, as shown in this report.

The U.S.–China trade relationship needs to undergo a fundamental change. Addressing unfair trade, weak labor, and environmental standards in China, and ending currency manipulation and misalignment, should be our top trade and economic priorities with China (Scott 2017a).

About the authors

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, the impacts of trade and manufacturing policies 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 in 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 TimesNewsdayUSA TodayThe Baltimore SunThe Washington Times, and other newspapers. He has also provided economic commentary for a range of electronic media, including NPR, CNN, Bloomberg, and the BBC. He has a Ph.D. in economics from the University of California at Berkeley.

Zane Mokhiber joined EPI in 2016. As a research assistant, he supports the research of EPI’s economists on topics such as wages, labor markets, inequality, trade and manufacturing, and economic growth. Prior to joining EPI, Zane worked for the Worker Institute at Cornell University as an undergraduate research fellow.

Acknowledgments

The authors thank Josh Bivens, Scott Boos, Lora Engdahl, Riley Ohlson, Scott Paul, and Michael Wessel for comments. This research was made possible by support from the Alliance for American Manufacturing.

Appendix: Methodology

The trade and employment analyses in this report are based on a detailed, industry-based study of the relationships between changes in trade flows and employment for each of approximately 205 individual industries of the U.S. economy, specially grouped into 45 custom sectors,28 and using the North American Industry Classification System (NAICS) with data obtained from the U.S. Census Bureau (2013) and the U.S. International Trade Commission (USITC 2018).

The number of jobs supported by $1 million of exports or imports for each of 205 different U.S. industries is estimated using a labor requirements model derived from an input-output table developed by the BLS-EP (2017a).29 This model includes both the direct effects of changes in output (for example, the number of jobs supported by $1 million in auto assembly) and the indirect effects on industries that supply goods (for example, goods used in the manufacture of cars). So, in the auto industry for example, the indirect impacts include jobs in auto parts, steel, and rubber, as well as service industries such as accounting, finance, and computer programming that provide inputs to the motor vehicle manufacturing companies. This model estimates the labor content of trade using empirical estimates of labor content and goods flows between U.S. industries in a given base year (an input-output table for the year 2001 was used in this study) that were developed by the U.S. Department of Commerce and the BLS-EP. It is not a statistical survey of actual jobs gained or lost in individual companies, or the opening or closing of particular production facilities (Bronfenbrenner and Luce 2004 is one of the few studies based on news reports of individual plant closings).

Nominal trade data are used in this analysis are converted to constant 2009 dollars using industry-specific deflators (see below for further details). This is necessary because the labor requirements table is estimated using price levels in that year. Data on real trade flows are converted to constant 2009 dollars using industry-specific price deflators from the BLS-EP (2017b). Use of constant 2009 dollars is required for consistency with the other BLS models used in this study.

Estimation and data sources

Data requirements

Step 1. U.S.–China trade data are obtained from the U.S. International Trade Commission DataWeb (USITC 2018) in four-digit, three-digit, and two-digit NAICS formats. General imports and total exports are downloaded for each year.

Step 2. To conform to the BLS Employment Requirements tables (BLS-EP 2017a), trade data must be converted into the BLS industry classifications system. For NAICS-based data, there are 205 BLS industries. The data are then mapped from NAICS industries onto their respective BLS sectors.

The trade data, which are in current dollars, are deflated into real 2009 dollars using published price deflators from the BLS-EP (2017b). As noted above, deflators for 2017 have not yet been published by the BLS. In this version of the report, we use the 2026 price projections published by BLS to estimate deflators for 2017, by interpolation. Specifically, the annualized percent change between the 2016 and the 2026 price projection for each sector is applied to the deflator for 2016, to estimate price levels in 2017.

Step 3. Real domestic employment requirements tables are downloaded from the BLS-EP (2017a). These matrices are input-output industry-by-industry tables that show the employment requirements for $1 million in outputs in 2009 dollars. So, for industry i the aij entry is the employment indirectly supported in industry i by final sales in industry j and, where i=j, the employment directly supported.

Analysis

Step 1. Job equivalents. BLS trade data are compiled into matrices. Let [T2001] be the 205×2 matrix made up of a column of imports and a column of exports for 2001. [T2017] is defined as the 205×2 matrix of 2017 trade data. Finally, [T2008] is defined as the 205×2 matrix of 2008 trade data. Define [E2001] as the 205×205 matrix consisting of the real 2001 domestic employment requirements tables. To estimate the jobs displaced by trade, perform the following matrix operations:

[J2001] = [T2001] × [E2001]

[J2008] = [T2008] × [E2001]

[J2017] = [T2017] × [E2001]

[J2001] is a 205×2 matrix of job displacement by imports and jobs supported by exports for each of 205 industries in 2001. Similarly, [J2008] and [J2017] are 205×2 matrices of jobs displaced or supported by imports and exports (respectively) for each of 205 industries in 2008 and 2017, respectively.

To estimate jobs created/lost over certain time periods, we perform the following operations:

[Jnx01-17] = [J2017] − [J2001]

[Jnx01-08] = [J2008] − [J2001]

[Jnx08-17] = [J2017] − [J2008]

Step 2. State-by-state analysis. For states, employment-by-industry data are obtained from the Census Bureau’s American Community Survey (ACS) data for 2011 (U.S. Census Bureau 2013) and are mapped into 45 unique census industries and eight aggregated total and subtotals, for a total of 53 sectors.30 We look at job displacement from 2001 to 2017 so from this point, we use [Jnx01-17]. In order to work with 45 sectors, we group the 205 BLS industries into a new matrix, defined as [Jnew01-17], a 45×2 matrix of job displacement numbers.31 We define [St2011] as the 45×51 matrix of state employment shares (with the addition of the District of Columbia) of employment in each industry. We calculate:

[Stjnx01-17] = [St2011]T [Jnew01-17]

where [Stjnx01-17] is the 45×51 matrix of job displacement/support by state and by industry. To get state total job displacement, we add up the subsectors in each state.

Step 3. Congressional district analysis. Employment by congressional district, by industry, and by state is obtained from the ACS data from 2011, which use geographic codings that match the district boundaries of the 113th, 114th, and 115th Congresses. In order to calculate job displacement in each congressional district, we use the columns in [Stjnx01-17], which represent individual state job-displacement-by-industry estimates, and define them as [Stj01], [Stj02], [Stji]…[Stj51], with i representing the state number and each matrix being 45×1.

Each state has Y congressional districts, so [Cdi] is defined as the 45×Y matrix of congressional district employment shares for each state. Congressional district shares are calculated thus:

[Cdj01] = [Stj01]T [Cd01]

[Cdji] = [Stji]T [Cdi]

[Cdj51] = [Stj51]T [Cd51]

where [Cdji] is defined as the 45xY job displacement in state i by congressional district by industry.

To get total job displacement by congressional district, we add up the subsectors in each congressional district in each state.

Endnotes

1. The World Trade Organization, which was created in 1994, was empowered to engage in dispute resolution and to authorize imposition of offsetting duties if its decisions were ignored or rejected by member governments. It expanded the General Agreement on Tariffs and Trade (GATT) trading system’s coverage to include a huge array of subjects never before included in trade agreements, such as food safety standards, environmental laws, social service policies, intellectual property standards, government procurement rules, and more (Wallach and Woodall 2004).

2. Tables 1 and 2 report U.S. general imports from China as measured by “customs value” (the value of imports as appraised by the U.S. Customs Service) and total exports to China as measured by “free alongside” or FAS value (the value of exports at the U.S. port, including the transaction price, inland freight, insurance, and other charges) to China. News releases from the U.S. Census Bureau and the Commerce Department usually emphasize general imports and total exports. The U.S. Internal Trade Commission (USITC) often refers to this netting out of general imports and total exports as the “broad” measure of the trade balance, as opposed to the “narrow” measure, which relies on imports for consumption and domestic exports. (For an example, see USITC 2014. For an explanation of the difference between general imports and imports for consumption, see the U.S. Census Bureau’s online trade glossary [2018e].) The key difference between these two measures is that total exports, as reported by the U.S. Census Bureau, include foreign exports (re-exports), i.e., goods produced in other countries and shipped through the United States, while domestic exports, as implied by the name, do not include re-exports. While a previous version of this report (Kimball and Scott 2014) relied on the narrow definition, using imports for consumption and domestic exports for the analysis, the broad measure was used in Scott 2017a. For 2017, imports for consumption were $504.0 billion, domestic exports were $120.0 billion, and the reported (narrow) trade balance was $384.0 billion. When we compare the trade deficit and job displacement estimates we obtained using the broad measure with the estimates we would have obtained using the narrow measure, we find the difference to be insignificant. The broad measure delivers an estimate of 3.36 million net jobs displaced in 2017, whereas the narrow measure delivers an estimate of 3.44 million net jobs displaced in 2017 (USITC 2018). In this report, all estimates for trade and jobs gained and lost for prior years are based on the broad measure of the trade balance. Data for individual years, and for the change in net jobs displaced, are reported in Table 1, in Figure A, and in other exhibits in this report.

3. While some small proportion of goods imported from China represent a category of goods that may not be produced in the United States, and thus would be “noncompeting” goods, the model used in this report produces an overall estimate of the net jobs displaced by the growing trade deficit. It is, in essence, an estimate of the jobs displaced by the growth of imports in excess of the growth of exports. Since virtually all U.S. imports from China are manufactured goods, as shown in Table 2 in this report, nearly all could be produced in the United States but for China’s unfair trade and currency policies and its domestic “savings glut” (Setser 2016).

4. The term “displaced” would be appropriate to an economy that was at true full employment, where any displaced worker would immediately take a job in another sector of the economy. However, the workers displaced by goods trade are almost exclusively manufacturing workers, and these workers have not been successfully moving into different parts of the economy in recent years: more than one-third of manufacturing workers who were displaced between 2015 and 2017 and who had previously been employed for at least three years were either unemployed or out of the labor force in January 2018 (BLS 2018a). Thus, trade-related job displacement does result in at least some workers moving to a nonworking status, thus “lost” jobs, even if other workers are reemployed elsewhere in the economy (reemployment would result in a change in the composition, rather than the level, of employment).

5. The BLS updated its Employment Requirements Matrix in October 2017 (BLS-EP 2017a), as it normally does every two years. Those revisions have been taken into account in this update. There are 205 NAICS-based BLS industries in the 2017 BLS update (NAICS stands for North American Industry Classification System). The underlying population data from the American Community Survey used to analyze the geographic impacts of trade-related job loss was last updated in Kimball and Scott 2014, with data from the American Community Survey for the 113th Congress census boundaries, which were redrawn after the 2010 census (U.S. Census Bureau 2013).

6. The shift in the deflator base year from 2005 in the previous report to 2009 in this report significantly reduced our estimates of jobs displaced in the computer and electronic parts industry, because large price declines in this industry and its sectors result in outsized impacts on changes in estimated real trade flows (compared with industries that have experienced lower levels of inflation, such as steel or automobile parts), and those price declines were smaller in 2017 than in 2015 (estimated using a 2005 deflator), due to the use of a 2009 base year for deflators in this report (see also note 13, below). Thus, in Scott 2017a, Table 3, we estimate that 1,238,300 direct jobs were displaced in this sector in the 2001–2015 period, a number greater than the 1,209,900 jobs displaced from 2001 to 2017, as shown in Table 3 of this report. The previous report has a greater job displacement estimate in computer and electronic parts despite the fact that the nominal trade deficit in this sector grew less in the 2001–2015 period (by $140.2 billion, as shown in Scott 2017a, Table 2) than it did in the 2001–2017 period (by $148.2 billion, Table 2 in this report).

7. Updated in Rasmussen 2017. Employment requirements tables in that report are derived from BEA input-output data, which are the primary source of data used to estimate BLS employment requirement tables (BLS-EP 2017a).

8. The macroeconomic model developed in Scott and Glass 2016 assumes that a 1.5 percent decrease in GDP would reduce total direct and indirect U.S. employment by roughly 1.3 percent. There were, on average, 153.3 million people employed in the United States in 2017 (BLS 2018c), thus yielding 2.0 million direct and indirect jobs displaced. The macroeconomic model also assumes a respending multiplier of 0.6 and yields a total of 3.2 million direct and indirect and respending jobs displaced by a trade deficit of this magnitude.

9. Scrap and used or secondhand goods are industries 203 and 204, respectively, in the BLS model, and there are no jobs supported or displaced by the production of or trade in goods in these sectors, according to the BLS model. (The jobs supported or displaced by trade are counted in the year these goods are originally manufactured—that is, when they are new—not when they are traded in the secondhand market.)

10. ATPs are an amalgamation of products from a variety of industries and subsectors within the broad NAICS-based categories shown in Table 2. They consist of 10 categories of products including biotechnology, life science, opto-electronics, information and communications, electronics, flexible manufacturing, advanced materials, aerospace, weapons, and nuclear technology (U.S. Census Bureau 2018a). In total ATP trade with the world in 2017, the United States had exports of $353.9 billion, imports of $464.3 billion, and a trade deficit of $110.4 billion. In total ATP trade with China in 2017, the United States had exports of $35.7 billion, imports of $171.1 billion, and a trade deficit of $135.4 billion. This exceeded the overall U.S. ATP deficit of $110.4 billion. Thus, the United States had an ATP trade surplus with the rest of the world in 2015 of $25.0 billion ($135.4 billion − $110.4 billion) (U.S. Census Bureau 2018b).

11. Data for trade in advanced technology products (ATP) by country are not available before 2002.

12. These results are derived from the trade and employment model described in the appendix to this report.

13. Deflators for many sectors in the computer and electronics parts industry fell sharply between 2001 and 2017 due to rapid productivity growth in those sectors. For example, the price index for computer and peripheral equipment fell from 2,666.4 in 2001 to 760.1 in 2017, a decline of 71.5 percent (the price index is set at 1,000 in 2009, the base year). In order to convert exports or imports of computers and peripheral equipment from nominal to real values for 2017, the nominal value is multiplied by 1,000/760.1 (the price index in year 2017 = 1.32). Thus, the real value of computers and peripheral products, a subset of the computer and electronic parts industry, is 32 percent larger than the nominal value in 2017 (in constant 2009 dollars). Overall, the real value of all computer and electronic parts imports in 2017 exceeded nominal values in that year by 11.2 percent. See the appendix for source notes and deflation procedures used.

14. Total imports from China in 2017 exceeded exports by a factor of 3.88-to-1 (505.6/130.4, as shown in Table 1). Thus, exports to China would have had to be roughly four times larger than they actually were in 2017 to achieve balanced trade with China.

15. Data not shown in Table 2. Authors’ analysis based on the change in exports shown, by industry, and the multiplier referred to in the previous note (3.88), based on analysis of data shown in Supplemental Table 1.

16. The computer and electronic parts industry’s share of all jobs lost due to the growth in the U.S.–China trade deficit from 2001 to 2017 ranged from 54.7 percent in Illinois’s 6th District to 92.3 percent in California’s 17th District (authors’ analysis of U.S. Census Bureau 2013; USITC 2018; BLS-EP 2017a, 2017b), compared with the national average of 36.0 percent of jobs (Table 3). In these states the only exceptions—that is, districts where job losses were concentrated in industries other than computer and electronic parts—were California’s 34th and 40th districts, where jobs losses in the apparel industry were 65.3 percent and 56.3 percent, respectively, of jobs lost in each district (compared with the national average of apparel industry job losses accounting for 5.0 percent of jobs lost due to U.S.–China trade, as shown in Table 3). Georgia is also one of the states that are host to one of the 20 hardest-hit congressional districts; Georgia’s 14th Congressional District’s job losses due to the trade deficit include a very large share of jobs in manufacturing, overall, 88.9 percent of all jobs lost, according to unpublished data available upon request. Nationally, manufacturing accounted for a smaller, 74.4 percent share, of all jobs lost (Table 3). Overall, nearly two-thirds (65.4 percent) of jobs lost in Georgia’s 14th district were in textile mills and textile product mills alone. North Carolina’s 2nd district also suffered a large number of job losses in a wide range of manufacturing industries, totaling 88.9 percent of job losses in that district. These losses were spread over a large number of industries, including computer and peripheral equipment, apparel, textiles, and furniture manufacturing.

17. California’s 17th Congressional District is home to Santa Clara University and corporate offices for Apple, Intel, Yahoo, and eBay (Wikipedia 2018). The 18th Congressional District is home to the headquarters of Google, Netflix, and HP, among others (Eshoo 2018).

18. The term “major manufacturing sector” refers here to employment by three-digit NAICS manufacturing industries. The computer and electronic parts industry lost 1,209,900 of the 3,360,600 U.S. manufacturing jobs lost between December 2001 and December 2017 (Table 3), more than six times as many jobs as were lost as in apparel, the next largest of the hardest-hit three-digit manufacturing industries. Trade-related job losses in these industries, shown in Table 3, reflect both potential jobs displaced by the growth of imports (which represents domestic consumption that could have been supplied by domestically produced goods) and by the failure of exports to grow, resulting in large trade deficits in these products.

19. In earlier research, Autor, Dorn, and Hanson “conservatively estimate” that growing “Chinese import competition…imply a supply-shock driven net reduction in U.S. manufacturing employment of 548 thousand workers between 1990 and 2000, and a further reduction of 982 thousand workers between 2000 and 2007.” They note further that these results are based on microeconomic research “exploiting cross-market variation in import exposure” (Autor, Dorn, and Hanson 2012, 19–20, abstract). These estimates are conservative, for several reasons, as noted by the authors. They fail to account for the overall macroeconomic impacts of growing U.S. trade deficits with China, including the direct and indirect effects of growing China trade deficits on U.S. employment, as noted by Acemoglu et al. (2014). As shown in Table 3, the growing U.S. goods trade deficit with China displaced 2.5 million total manufacturing jobs between 2001 and 2017, and an additional 860,100 nonmanufacturing jobs. Thus, approximately 0.34 nonmanufacturing jobs were displaced for each manufacturing job displaced. Differences in parameter estimates notwithstanding, it is important to note that Autor, Dorn, and Hanson (2012) confirm that growing Chinese import competition is responsible for the displacement of approximately 1.5 million U.S. manufacturing jobs from 1990 to 2007, generally confirming the results of current and earlier EPI research.

20. Acemoglu et al. (2014) examine the impacts of U.S.–China trade from 1999 to 2011. The U.S. trade deficit with China increased from $68.7 billion in 1999 to $83.1 billion in 2001 to $295.2 billion in 2011 (U.S. Census Bureau 2018d). Thus, 93.6 percent of the growth of the U.S. trade deficits with China in the 1999–2011 period occurred after China entered the WTO in 2001.

21. Scott’s 2013 estimates are based on average wages from a three-year pooled sample of workers by industry from 2009–2011. These estimates are not updated in this report.

22. The $180 billion in income is redistributed to college-educated workers in the top third of the labor force and to owners of capital. Bivens and Mishel (2015, Figure C) find that for the period of 1973–2014, the loss in the labor share of income was responsible for 8.9 percentage points of the gap between net productivity and real median hourly compensation (a measure of the growth in inequality in this period).

23. Between 1995 and 2011, growing trade with China was responsible for 51.6 percent of the increase in the college/noncollege wage gap in the United States in this period (Bivens 2013, Table 1), 57.1 percent of this wage gap. Thus, China is responsible for a sizeable majority (56.8 percent) of the overall impact of least-developed-countries (LDC) trade on the noncollege wage gap in this period. This analysis decomposes the overall increase in the wage gap (4.8 percentage points), the share attributable to LDC trade, and the share of LDC trade accounted for by China.

24. One frequent criticism of trade and employment studies is that the growth of imports does not displace domestic production, and thus the claim is that such imports do not actually cost jobs. In addition, some assert that if imports from China fell, they would be replaced by imports from some other low-wage country (see, for example, U.S.–China Business Council 2014). However, important empirical research by Autor, Dorn, and Hanson (2012, 4) has shown that “increased exposure to low-income country imports is associated with rising unemployment, decreased labor-force participation, and increased use of disability and other transfer benefits, as well as with lower wages.” The bottom line is that “trade creates new jobs in exporting industries and destroys jobs when imports replace the output of domestic firms. Because trade deficits have risen over the past decade, more jobs have been displaced by imports than created by exports” (Bivens 2008b, 1).

25. This analysis refers to the wage impacts of net jobs lost due to the growth of the U.S.–China trade deficit between 2001 and 2011. It includes net wage gains in the 538,000 jobs supported by increased employment in export industries, less net wage losses in the 3.2 million jobs displaced by increased imports, assuming that all of the 2.7 million net displaced workers are rehired and receive average earnings in jobs in nontraded goods industries (Scott 2013, Table 9a). It is conservative in the sense that it assumes that all of the net displaced workers are rehired in jobs in nontraded goods industries; it excludes the wage losses absorbed by those displaced workers who are not reemployed (for example, the 35.3 percent of long-tenured workers in manufacturing who had been displaced between January 2015 and December 2017 and were not employed in January 2018, as estimated in the BLS Displaced Worker Survey [BLS 2018a]).

26. These losses can never be regained in that the hours unemployed are a permanent loss to the economy, even if an individual worker later finds employment at wages equal to or higher than predisplacement wages. Unemployment costs are a dead-weight loss to the economy, in the same way that unemployment during a recession generates a permanent loss in national economic output.

27. Autor, Dorn, and Hanson (2012) use an analytic technique that compares employment in import-sensitive industries in various geographic areas at a fairly disaggregated level (roughly, cities or counties), referred to in their research as “commuting zones.” They use these zones and data on imports in each region over the study period to do their statistical analysis.

28. A previous edition of this research used data for 56 industries provided by the ACS (Scott 2012). The BLS-EP consolidated several industries, including textiles and apparel, which required us to consolidate data for these industries in our ACS state and congressional district models. Other “not elsewhere classified” industries were consolidated with other industries (e.g., “miscellaneous manufacturing”) or deleted (e.g., in the case of “not specified metal industries”) to update and refine the crosswalk from BLS-EP to ACS industries. As a result of these consolidations, there are 45 industries in the ACS data set used for this study. The current (BLS-EP 2017a) iteration of the employment requirements tables used in this study breaks the economy down into 205 industries, including 76 manufacturing industries. The previous iteration of employment requirements tables, used in Scott 2017a, broke the economy down into 195 industries, including 77 manufacturing industries. The apparel industry and the leather and allied products industry—NAICS 315 and 316—were consolidated into one sector in the BLS-EP 2017a model. We disaggregated job losses in these two sectors in this report using the results from Scott 2017a.

29. The model includes 205 NAICS industries. The trade data include only goods trade. Goods trade data are available for 85 commodity-based industries, plus information (publishing and software, NAICS industry 51), waste and scrap, used or secondhand merchandise, and goods traded under special classification provisions (e.g., goods imported from and returned to Canada; small, unclassified shipments). Trade in scrap, used, and secondhand goods has no impact on employment in the BLS model. Some special classification provision goods are assigned to miscellaneous manufacturing.

30. The U.S. Census Bureau uses its own table of definitions of industries. These are similar to NAICS-based industry definitions, but at a somewhat higher level of aggregation. For this study, we develop a crosswalk from NAICS to Census industries, and we use population estimates from the ACS for each cell in this matrix.

31. The switch from the 195-45 industry crosswalk to the 205-45 industry crosswalk created one inconsistency. The apparel manufacturing and leather and allied products manufacturing industries were separate in the previous (2013, referenced in Scott 2017a) version of the BLS-EP (2017a) model and were combined into one category in the 205 industry table. However, in the 45 industry table, there are two separate categories for these industries. In order to accurately assign jobs displaced to both industries, we apply the ratio of jobs displaced in these two industries in 2015, from the previous version of this report, to the number of jobs displaced in the (now combined) apparel and leather products industry as specified in the current 205 industry table. These inconsistencies will be addressed in the next revision of this trade and employment model.

References

Acemoglu, Daron, David Autor, David Dorn, Gordon H. Hanson, and Brendan Price. 2014. Import Competition and the Great U.S. Employment Sag of the 2000s. National Bureau of Economic Research Working Paper no. 20395, August 2014.

Autor, David H., David Dorn, and Gordon H. Hanson. 2012. The China Syndrome: Local Labor Market Effects of Import Competition in the United States. National Bureau of Economic Research Working Paper no. 18054, May 2012.

Autor, David, and Gordon Hanson. 2014. “Labor Market Adjustment to International Trade.” NBER Reporter 2014, no. 2.

Bailey, Martin N., and Robert Z. Lawrence. 2004. “What Happened to the Great U.S. Jobs Machine? The Role of Trade and Electronic Offshoring.Brookings Papers on Economic Activity 35, no. 2: 211–284.

Bernstein, Jared. 2016. “Sometimes, Your Trade Deficit Is Thrust upon You.” PostEverything (Washington Post blog), October 31, 2016.

Bivens, Josh. 2008a. Everybody Wins, Except for Most of Us: What Economics Teaches about Globalization. Washington, D.C.: Economic Policy Institute.

Bivens, Josh. 2008b. Trade, Jobs, and Wages: Are the Public’s Worries about Globalization Justified? Economic Policy Institute Issue Brief no. 244, May 2008.

Bivens, Josh. 2013. Using Standard Models to Benchmark the Costs of Globalization for American Workers without a College Degree. Economic Policy Institute Briefing Paper no. 354, March 2013.

Bivens, Josh, and Lawrence Mishel. 2015. Understanding the Historic Divergence between Productivity and a Typical Worker’s Pay: Why It Matters and Why It’s Real. Economic Policy Institute Briefing Paper no. 406.

Bronfenbrenner, Kate, and Stephanie Luce. 2004. The Changing Nature of Corporate Global Restructuring: The Impact of Production Shifts on Jobs in the U.S., China, and around the Globe. Commissioned research paper for the U.S. Trade Deficit Review Commission.

Bureau of Economic Analysis (BEA). 2018. “Industry Data: GDP-by-Industry.”

Bureau of Labor Statistics (BLS). 2018a. “Displaced Workers Summary: Worker Displacement: 2015–17” (news release). August 28, 2018.

Bureau of Labor Statistics (BLS). 2018b. “Employment, Hours, and Earnings from the Current Employment Statistics Survey (National): Manufacturing Employment, Seasonally Adjusted” [Excel file]. Downloaded September 2018 from https://data.bls.gov/cgi-bin/surveymost?ce.

Bureau of Labor Statistics (BLS). 2018c. “Employment Level” [Labor Force Statistics from the Current Population Survey Data Series LNS12000000]. Accessed September 2018.

Bureau of Labor Statistics, Employment Projections program (BLS-EP). 2017a. “Chain-Weighted (2009 Dollars) Real Domestic Employment Requirements Table for 2001” [Excel sheet, converted to Stata data file]. In Historical Employment Requirements Tables, 1997–2016 [data series]. Last modified October 24, 2017.

Bureau of Labor Statistics, Employment Projections program (BLS-EP). 2017b. “Domestic Industry Output Chain Weighted Deflator, 2009=1000” [CSV file “ind16.csv” from “Industry Output and Employment Projections files—Data for Researchers,” converted to Excel sheet and Stata data file].

Clinton, Bill. 2000. “Expanding Trade, Protecting Values: Why I’ll Fight to Make China’s Trade Status Permanent.” New Democrat 12, no. 1: 9–11.

Eshoo, Anna G. 2018. “About the 18th District” (web page). Website of Congresswoman Anna G. Eshoo. Accessed October 18, 2018.

Groshen, Erica L., Bart Hobijn, and Margaret M. McConnell. 2005. “U.S. Jobs Gained and Lost through Trade: A Net Measure.” Current Issues in Economics and Finance 11, no. 8: 1–7.

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Kimball, Will, and Robert E. Scott. 2014. China Trade, Outsourcing and Jobs: Growing U.S. Trade Deficit with China Cost 3.2 Million Jobs between 2001 and 2013, with Job Losses in Every State. Economic Policy Institute Briefing Paper no. 385, December 2014.

Pierce, Justin R., and Peter K. Schott. 2016. “The Surprisingly Swift Decline of U.S. Manufacturing Employment.American Economic Review 106, no. 7: 1632–1662. https://doi.org/10.1257/aer.20131578.

Rasmussen, Chris. 2017. Jobs Supported by Exports 2016: An Update. U.S. Department of Commerce, International Trade Administration, August 2017.

Scott, Robert E. 2012. The China Toll: Growing U.S. Trade Deficit with China Cost More Than 2.7 Million Jobs between 2001 and 2011, with Job Losses in Every State. Economic Policy Institute Briefing Paper no. 345, August 2012.

Scott, Robert E. 2013. Trading Away the Manufacturing Advantage: China Trade Drives Down U.S. Wages and Benefits and Eliminates Good Jobs for U.S. Workers. Economic Policy Institute Briefing Paper no. 367, September 2013.

Scott, Robert E. 2017a. Growth in U.S.–China Trade Deficit between 2001 and 2015 Cost 3.4 Million Jobs: Here’s How to Rebalance Trade and Rebuild American Manufacturing. Economic Policy Institute, January 2017.

Scott, Robert E. 2017b. We Still Haven’t Recovered Well-Paying Construction and Manufacturing Jobs (economic snapshot). Economic Policy Institute, August 2017.

Scott, Robert E., and Elizabeth Glass. 2016. Trans-Pacific Partnership, Currency Manipulation, Trade, and Jobs: U.S. Trade Deficit with the TPP Countries Cost 2 Million Jobs in 2015, with Job Losses in Every State. Economic Policy Institute Briefing Paper no. 420, March 2016.

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Setser, Brad. 2016. “The Return of the East Asian Savings Glut.” Council on Foreign Relations Discussion Paper, October 2016.

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Supplemental tables


See related work on Trade deficit | China trade | Trade and Globalization | Trade

See more work by Robert E. Scott and Zane Mokhiber

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10
Oct
17

Free Trade: Evil or Good?

Free Trade Evil or Good

There is a conflict within the struggling Democratic Party as to whether to support Free Trade or to ban it. Traditionally, for the past 150 years, Democrats have been the political party for the working class, to improve worker’s wages and their working conditions. Looking at the issue of whether you are for workers or against them, it is rather simple: you are either for workers or for the employers (you can’t be both). If you are against workers, then you are not called “Anti-worker”,  but “Pro-Business”. And there is nothing more “Pro-Business” than the issue of Free Trade.

What is Free Trade?

To understand “Trade” let us go back to the beginning – the writing of the U.S. Constitution, written mainly by James Madison, but implemented by Alexander Hamilton, the first Secretary of the Treasury. Part of “Trade” is customs or import taxes (taxes that are levied on products brought in from other countries into the USA). This was one of the first orders of the day. Import taxes did two important things: 1) it brought in a substantial amount of revenue into the US Treasury (in order to pay the back wages of soldiers of the Revolutionary War who had gone unpaid for many years) without individually taxing individuals and 2) it protected fledgling American businesses from being over-run by foreign companies. In fact, Hamilton set the Coast Guard to patrol offshore waters to intercept contraband (untaxed smuggled products).

It was Alexander Hamilton’s vision, as well as George Washington’s, that the United States should encourage manufacturers, especially textiles. This can be best exemplified by the ceremonial outfit worn by George Washington, who, at the first inauguration, wore a plain brown suit of American broadcloth woven at a mill in Hartford. (from Alexander Hamilton p277, by Ron Chernow). At that time, England was a giant manufacturer, holding secrets of manufacturing from competitors. England wanted to keep the US as a natural reserve of raw material and limiting any US manufacturing. It was one of the more important items that American colonists had rebelled against. Funny, the USA is once again becoming less a manufacturing power and more of a reserve of raw material, due to Free Trade.

Now, to more modern times, 1980s, The United States was the disputed king of manufacturing. The beginning of the end was that corporations and big business took over Congress (unfettered lobbying/corruption as it caused in every other country). These big monied business people, in an effort to increase profits while simultaneously decreasing pay for American workers, came up with the concept of “Free Trade”. By eliminating import taxes on products coming from other countries, corporations/big businesses could exploit low wages and decreased standard of living conditions of foreign nations to undercut the price of all products made in the USA, which caused tens of thousands of Americans businesses to fold or to move to  other countries like China or India and millions of Americans to lose their jobs. (7.23 million lost manufacturing jobs since 1979). This has caused the decay of American manufacturing and has hit some areas extremely hard, especially the small rural towns where manufacturing was their main source of revenue.(Globalization when factories close down and towns struggle).

Who is Helped by Free Trade?

Free Trade policies actually do help farmers. It did open more markets for American farmers to send their products. Of course, farmers only make up 1% of the US population. Other winners, CEOs of large companies. More profits, less responsibility. That is why someone like Donald Trump who says “America First”, still keeps his manufacturing plants in China.

The losers: American workers, loss of millions of American manufacturing jobs, decrease of US wages. When you open up the job market to the whole rest of the world, it mean the American worker had to compete against the global workforce of 1,12 billion workers. The worker glut has caused a decrease of American wages and benefits (Invisible Influence of China, Robert Samuelson for the Washington Post). Not only are the workers hurt, but so are the families, the towns, cities and communities as well as the associated businesses with manufacturing. Plus, as the World Trade Organization becomes bigger and bigger, the United States can no longer impose its own safety regulations such as on meat because it makes it unfair for countries with less regulation to compete with the US (The Official End to Country of Origin Meat Labels). So, there are a lot of down sides to Free Trade. Let us not forget the loss of all the revenue to the US Treasury by getting rid of all those trillions of dollars by eliminating the import taxes.

But how about the other winners? Well, the countries that the United States has shipped all their jobs to have certainly been helped. For example, China builds skyscrapers and bullet trains at a rate that we can not even comprehend. Rich Chinese businessman come to the United States and buy up American properties. Poverty is less worldwide.

The main argument for Free Trade is that it brings down costs. While inflation seems to hit everything, in clothing, due to mass production and slave labor, you can buy some clothing at the same price as you could in 1979. But is decreased prices everything? Cheap products have changed people’s philosophy, people now spend terribly unwisely – it has become an uncontrolled spending economy. And overproduction of products is also a bad thing: clothing is manufactured in such an overwhelming volume, 26 billion tons per year to the landfills, that landfills are having troubles taking it all in, while stripping away natural and unnatural resources to make them.

Which Political Party is For Free Trade?

The North America Free Trade Agreement (NAFTA) an agreement between the US, Canada and Mexico was the first Free Trade Agreement.  This was a Republican plan written up by Republicans, started under the administration of George H.W. Bush, voted on by a majority of Republicans and a minority of Democrats. But, sometimes considered a Democratic bill because George Clinton signed it into law. Almost immediately an infinitely larger Free Trade  deal happened, the World Trade Organization (WTO). It should be noted that all Free Trade bills are Republican bills, and they always will be. Even Donald Trump was Free Trade, still is Free Trade, except when he hypocritically says he is not. Free Trade is the Republican platform. Even Breitbart which is “anti Republican establishment” is Pro Free Trade. The Democratic Party is 85% Against Free Trade. And it is quite possible that if there will be a limitus test for the future Democratic Party, it is whether a Democrat is for Free Trade/Pro-Business/Anti-Worker or Against Free Trade/Pro-Worker. If the Democrats want to win back any part of the Senate, House or Presidency, they should all be Pro-Worker. The Democratic motto should be: “All People deserve the right to Life, Liberty, and the Pursuit of Happiness with Good Wages and Benefits.

Economic Forecast

Don’t be fooled, the United States and the world has been in the biggest economic boom ever seen. It has been going on the last seven years, but because the United States is not participating in manufacturing, workers have not seen wages increase. Donald Trump had promised 4% Gross Domestic Product (GFP) growth, but that will never happen without manufacturing which has been left behind. (7 Reasons why Trumps promise of 4% GDP growth will never happen in 2017) In reality we are probably close to the end of this economic tech boom. The stock market is way over valued, just like it always happens before the recession happens. Are the Day Traders afraid? NO. The reason, the big boys have super fast computers and lines of communication that allows them to almost instantaneously withdraw their money before they get hurt, while all the workers with their 401Ks will have to see their retirement plans slowly go down the drain. Not a rosy prediction. The path to a more stable future is to invest in manufacturing, especially making the more expensive technical components and to invest in infrastructure. Doubling down on trickledown economics, giving tax breaks to the rich and decreasing revenue to the Treasury is a sure way to continue on the same path we are on.. The rich get richer, the poor get poorer and the middle class once again becomes the poor class. Final Verdict: Free Trade is a menace to the American working class, but a real boon to the top 1% and other countries.

Remember to buy American, the job you save may be your own.

22
Mar
16

Why Free Trade is Devastating to the USA

Why Free Trade is Devastating to the USA

1) The Original Idea

This is a quick look at Free Trade. I am not against trade. Trade between countries is beneficial as long as all the countries follow the rules. Historically, all countries have placed import taxes of products coming into their countries to protect their own businesses from being destroyed. Some import taxes have been much higher than others. So, in order to improve trade, Free Trade Treaties were created (only 25 short years ago) which basically repealed the import tax. Theoretically, if agreements between countries with the same standards- like the USA and Canada – were created, this would be a good idea.

Free Market Tonic

2) The Problem

The problem with the real life treaties is that the countries do not have similar economic conditions or moral convictions. A third world country will always have a lower cost of living, little regulation in the treatment of workers, unregulated working conditions and no protection of the environment  which creates a great advantage in making very inexpensive products compared to developed nations. In addition, many countries have been breaking the underlying principals of trade: some countries have: 1) de-valued their monetary units towards the U.S. dollar (thereby gaining an advantage in exporting into the US); 2) have persistently engaged in the practice of dumping – making so much a product that it artificially lowers prices and puts the other country’s businesses out of business; and 3) have been using slave labor and childhood labor.

3) Manufacturing Towns Take a Big Hit

As the Free Trade Advocates like to say so easily about Free Trade Treaties, there will be some “losers”. It was predicted that some manufacturing would be hurt, but nobody thought for a second that it would be this severe. It was acknowledged that major manufacturing cities would get hit – they were. (Think of Detroit and Flint, Michigan). But so were the small towns.

NAFTA would create jobs

Within 8 years after NAFTA (North American Free Trade Act) passed, 700,000 American jobs were sent to Mexico. Here is a classic example of NAFTA: Hershey’s Chocolates no longer make any chocolate in the United States, it is all made in Mexico. As Hershey’s offshored all of its US jobs to Mexico. It has created numerous manufacturing ghost towns of cities like Oakdale, CA, Robinson, IL, Hazelton, PA, Stuart’s Draft, VA  Naugatuck, CT and, Hershey’s PA. From 1994 to 2015, the Labor Department certified that more than 216,000 workers in North Carolina were displaced by global economic pacts and qualified for assistance — making it the hardest-hit state in the country. (Ref 1).

Loss of US manufacturing jobs 1980-2012. NAFTA 1994, WTO 1995, China joins WTO 2001

NAFTA 1994, World Trade Organization 1995, China joins WTO 2001

4) The Loss of U.S. Manufacturing and Other Jobs

The loss of manufacturing jobs is sometimes called deindustrialization.  Since 1998, not only have we lost a “net” 8 million manufacturing jobs to offshoring, we continue to shed manufacturing jobs very fast almost at the same rate as we can create new ones. Also, Free Trade Advocates never mention (among many other things) is that we have lost many “associated” manufacturing jobs, like transportation, affiliated jobs, and community jobs that serviced the manufacturing workers which is usually equal to 2.5 to 3 jobs per manufacturing job. In addition (totally separate from manufacturing), there are the millions of service jobs that have been offshored to other countries just so large corporations can make greater profits.

chinas import

The winner of Free Trade: China. Loser:United States

5) Free Trade Lowers Middle Class Wages

One thing that both Republicans and Democrats can agree on is that middle class wages have been stagnant, and most agree that it is due to disastrous Free Trade Treaties. (Interesting reading, Jared Bernstein’s article: The Era of Free Trade Might Be Over. That’s a Good Thing. – The New York Times). The reason wages are not increasing: 1) manufacturing used to be good paying jobs, but now we have much less manufacturing jobs and the “new” manufacturing jobs that are coming back are paying less; and 2) almost all jobs can be readily off-shored, so it makes it difficult to ask for raises. In fact, 25% of all service jobs or 40 million US jobs could be sent overseas in the next few years. (Ref 3).

6) Which Party Likes Free Trade Treaties?

So, who is to blame for these Free Trade Treaties? Although they are considered “bi-partisan”, it is really more partisan. You can decide for yourself. The North American Trade Agreement NAFTA) was started by Bush’s father, George H.W. Bush in 1990 and signed into law by President Bill Clinton in December 9, 1993 after being ratified by the House 234- 200 (Yeas: 132 GOP, 102 Dems, Nays: 43 GOP, 156 Dems) and the Senate 61-38 (Yeas: 34 GOP, 27 Dems, Nays: 10 GOP, 28 Dems).

Fast Track

The Trans-Pacific Partnership Pact (TPP) which will probably pass during the lame duck session (see my entry When Will the TPP Become Law)  has had a similar vote. In order to help pass the TPP, Fast Track (meaning you can not filibuster or add amendments to the the TPP), also known as the Trade Promotion Authority (TPA) was added. The vote in the Senate: passed 60-38 (Yeas: 47 GOP, 13 Dems; Nays: 7 GOP, 31 Dems & Ind.). The House vote: The vote was 218-208 (Yeas: 190 GOP, 28 Dems, Nays: 50 GOP, 158 Dems).

One of the things that have made Republicans so mad (besides listening to right wing media) is that their political party has consistently made their lives worse by supporting Trickledown economic theories, with the worst one being the Free Trade Treaties. And yet, the Republicans want to pass an even bigger one, the TPP, which is expected to cost the US 2 million jobs in just one year. (Ref 2).

stop the TPP

7) Other Criticisms of Free Trade

There are many arguments besides economic against Free trade policies. First, Free Trade heavily favors large corporations destroying infant industries as well as the small and medium sized companies. It undermines long-run economic development – it is difficult to revive manufacturing ghost towns, and difficult to plan for growth when American jobs can be offshored at any time. Free Trade has definitely caused income inequality, and environmental degradation.

Born to Work Picture from the Daily Beast in 2009

Born to Work
Picture from the Daily Beast in 2009

Free Trade is supportive of countries sticking to their native practices which often means supporting child labor and working in sweatshops where workers get no benefits in often poorly ventilated and dangerous work environments.

Bangladesh factory collapse

Bangladesh Clothing factory collapse

Free Trade has definitely caused the race to the bottom, wage slavery, accentuating poverty in poor countries, harming national defense, and forcing cultural change. One additional criticism is that it allows large corporations to ignore local, state and governmental rules and laws: U.S. Appeals WTO Ruling on Meat Labeling Laws – where the American Meat Institute refused to label their meats as to where the originated. The Congress has successfully repealed the Country of origin labeling law this past winter. Instead of raising global standards, free trade tries to lower standards of countries that are more advanced. We need to stop all of these Free Trade Treaties, because they are devastating to the USA in so many ways.

free-trade-at-last-cartoon

22
Jun
15

The TPP comes Knocking on Your Door on Tuesday

House Sends Trade Bill Back to Senate in Bid to Outflank Foes – The New York Times.

One of the most important legislative battles of this century comes back to the Senate on Tuesday, June 23, 2015. For those who do not know what is going on, I am not surprised (because a lot of it is secret).  But I will simplify it all: what is the Trans-Pacific Partnership; what is Fast Track; who is for it and who is against it; the expected results of the TPP and the legislative wrangling that has led us up to Tuesday’s crucial vote.

What is the Trans-Pacific Partnership?

For those of you who know nothing at all about The Trans-Pacific Partnership (TPP), it is a Free Trade treaty between the USA, Canada, Mexico, Australia, New Zealand, Brunei, Chile, Peru, Japan, Vietnam, Thailand and Singapore. What “Free Trade” Treaties do is it eliminates import taxes and therefore, theoretically, increases trade between countries. So, why have import taxes in the first place? Right? Nobody likes taxes.

The Reason For Import Taxes

After the US Constitution was ratified, our Founding Fathers, at the very beginning, had placed a 95% tax on all imports (like other countries did at the time). The reason: they wanted to assure that American businesses had a fair shot at staying in business (so England did not overrun U.S. businesses) and to raise money for the government. Through the 20th Century, the US gradually decreased rate on import taxes.

Free Trade Treaties

Then, in 1990, US businesses got even more aggressive and start pushing “Free Trade” Treaties – eliminating all import tax form countries that had treaties with the U.S.. The first modern Free Trade Treaty was the North American Free Trade Act (NAFTA) between the US, Canada and Mexico, which became law on January 1,1994. The next year, and an even bigger Free Trade Treaty came into being on January 1, 1995, called the World Trade Organization (WTO) which presently encompasses 144 countries with China joining in 2001. Today, the average import tax rate into the US is 2.5% (which is almost non-existent).

What is the Result of Free Trade Treaties?

The results of Free Trade Treaties has been very mixed. The winners: people who like $6 shirts from Old Navy (and don’t care how it got that way); China; India; Multi-national Corporations; and anti-union people. The losers: small businesses, the American middle class, small towns (the multiple manufacturing ghost towns caused by offshoring), manufacturing jobs and its related jobs, and multiple other conditions (see the movie “The True Cost“).

Why Have Free Trade Treaties been Bad for the United States?

When Free Trade Treaties were initially discussed, economists knew that there would be loss of some US jobs, especially the industrial type jobs. It was 1994, America was in the middle of an economic boom, loss of US jobs didn’t seem to be such a big deal. However, the economists were greatly off in their predictions. According to the Economic Policy Institute, NAFTA costs the US 3.1 million jobs (examples: car manufacturers moved many plants to Mexico; Hersheys moved all of its operations to Mexico), and the World Trade Organization costs the US over 20 million jobs (even a recent report by the Congressional Research Service acknowledges that America lost over 2 million factory jobs just to China).

Why were the economists so far off?  First, globalization – all of the world became instantly interconnected by telephone, internet and travel. Because of this interconnectedeness, US corporations suddenly became multi-national corporations to take advantage of several issues: decreased of costs of wages, minimal safety regulations for workers, minimal regulation of pollution standards, subsidies from the US government to move their US companies overseas, avoid American taxation, and special kickbacks to CEOs from foreign governments to take advantage of the 0% import tax into the United States. To become multi-national corporations, CEOs had to offshore millions of U.S. jobs, not only manufacturing jobs, but also technical and service jobs. And it is still going on.The US offshored more than 2.6 million jobs in 2013 and there is a potential of offshoring another 25% of the American workforce or around 40 million jobs in the next few years according to the Congressional Research Service. These are all products of the Free Trade Treaties.

For more details (and graphs and citations) on the Global economy see my Blog entry: The global economy: A Short Lesson.

Who Are For the TPP and Who Are Against It?

The people who are for are the ones that wrote the Trans-Pacific Partnership, obviously. The people who wrote the TPP: 28 trade advisory committees have been intimately involved in the negotiations. Of the 566 committee members, 480, or 85 percent, are senior corporate executives or representatives from industry lobbying groups. Many of the advisory committees are made up entirely of industry representatives. From leaked documents, we know that Big Pharma is a big player. The TPP has written sections to increase the length of their drug patents and make generics more difficult to produce.  Big Ag has been a big player and they have been trying to get countries to accept their GMO vegetables/fruits or hormonally treated livestock. We also know that intellectual property is also another section that has been leaked, which means this involves number of large corporations, Wall Street as well as Hollywood/Big Media. So, in a couple of words the ones that wrote the TPP: Big Businesses (small companies not allowed).
Politically, who supports Big Business? The biggest supporter is the Republican Party. Even most Tea party members support the TPP, see the voting record. Another group of supporters are big corporate Democrats, called “bought” Democrats, which are less than 15% of all Democrats. And, of course, President Barack Obama.

Who is against the TPP? The middle class, the poor, progressives, Tea Party members who have seen US jobs offshored, people who care about the US economy and its future as well as organized labor. If you do see anything printed in the newspaper about the TPP, it says that the only opponents to the TPP is organized labor. Really?!! Organized labor comprises only 7% of private businesses. It is the ordinary citizens who are against the TPP and we don’t even get to vote on this. Not only do we not get to vote on the issue, we are forbidden to read it. And Big Media rarely report anything about the TPP. But, the grassroots movement from the opponents of the TPP have been making the legislative process bumpy.

The Legislative Process of the TPP

Now this is where things get a little hairy. After years and years of private negotiations, the TPP finally was brought to Congress, just at a time when things seemed favorable for passage, a Republican majority in both the Senate and The House. To get around the usual wrangling in Congress, the President with the permission of Congress is trying to pass the Trade Promotion Authority – which is used to be called “Fast Track” (probably changed the name to confuse the public), which means Congress can not debate aspects or add amendments to the bill, just an up or down vote. This was introduced to the Senate, however it could not pass the 60 vote filibuster needed to send it to the House. So, to entice some Democrats, the Senate added another bill that would help out workers that will be displaced by the TPP, called the Trade Adjustment Assistance Enhancement Act (TAA). These two bills were coupled and sent to the House of Representatives to be passed. However, the House couldn’t get enough votes to pass the coupled package. Then, this where the wrangling starts. The House of Representatives then de-coupled the two bills and just voted on the Fast Track (TPA) and passed it on a 219-211 vote. However, it is not law because the two bills were de-coupled. So, the House just kicked the can over to the Senate to see if they can pass Fast Track without the Trade Adjustment Assistance Enhancement Act. The Senate vote is scheduled for Tuesday, June 23rd. Write to your Senators. We have seen what previous Free Trade agreements have caused. The TPP is absolutely no different. And China can join this treaty as well. Why President Obama is pursuing this is beyond me. Stop The TPP. My prediction: The TPP, if passed, will cause a loss of more than 5 million US jobs in 15 years and make income inequality worse.

 

29
May
15

The Trade Debate Moves to the House

The Trade Debate Moves to the House | Alliance for American Manufacturing.

The Trans-Pacific Partnership (TPP), a large Free Trade deal, is just one small hurdle into becoming law. The TPP has passed the Senate and is now on to the House of Representatives. The TPP is an agreement between the United States and other countries: Australia, Brunei, Canada, Chile, Peru, Malaysia, Mexico, New Zealand, Singapore, Vietnam, and Japan. It effects 40% of all of the world’s economy. The TPP would eliminate import taxes from these countries into the U.S. and if history is any indication (see NAFTA – loss of 3.1 million U.S. jobs and the World Trade Organization – loss of 21 million U.S. jobs) we should see an increase in the offshoring of U.S. jobs. Below is the article:

 

The Trade Debate Moves To The House  written May 26, 2015 by Taylor Garland from the Alliance for American Manufacturing

The House will now have the chance to make trade work for American manufacturers and workers.

The Senate worked late on Friday to pass several bills before the holiday recess, one of which was the notorious Trade Promotion Authority (TPA). The bill passed the Senate 62-37 without strong and enforceable currency rules, regrettably.

That’s not to say the Senate didn’t have the chance. The Senate voted to reject the Portman-Stabenow amendment to address currency manipulation with strong and enforceable provisions in TPA on Friday afternoon by a vote of 48-51.

But all is not lost in the trade debate for American manufacturers and workers.

The Obama administration and Republican leadership in the House may need to extend an olive branch — trade enforcement — to Members of Congress who represent districts that have been negatively impacted by unfair trade. There are two bills in the House that that would make it easier for U.S. industries to fight back against unfair foreign trade practices.

The first, the Trade Facilitation and Trade Enforcement Act, overwhelmingly passed the Senate 78-20. This bill includes the Schumer Currency Amendment that directs the Comerce Department to investigate undervalued currencies as a subsidy under U.S. trade remedy laws. The second enforcement measure, the American Trade Enforcement Effectiveness Act, was introduced in the House last week by Rep. Mike Bost (R-Ill.).  Both bills are backed by several steel industry leaders.

The House of Representatives has the chance to stand up for American businesses and workers who face of flood of illegally dumped imports. “Trade enforcement and currency manipulation must also be addressed as a part of Trade Promotion Authority legislation, or trade agreements such as the Trans-Pacific Partnership will fail to deliver for American workers,” said Alliance for American Manufacturing President Scott Paul.

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The legislative wrangling in trying to pass the Treaty is interesting. It pits politicians whose areas that do not depend on any manufacturing (they are for the TPP) against politicians that still have some remnants of American manufacturing who are verbally against it. Since America does not have much manufacturing anymore, the manufacturing politicians are in the minority. And to cope with the expected loss of U.S. jobs, these politicians have worked hard to add an amendment to compensate for the Americans that will lose their jobs. Obviously, corporate America does not want this amendment. And corporate America has a history of looking for quick profits at the expense of America’s future.

It is truly amazing that this big news which will cause the loss of millions of U.S. jobs, yet, gets no media coverage. In fact, if you ever read the rare newspaper article, it is no mistake that they avoid using the terms: “Free Trade” or the Trans-Pacific Partnership. Reuters’ newspaper recently did a poll about “The Trade Policy”, 56% of Americans were for it! There is a major problem with this survey: I know that less than 10% of Americans know a single thing about the TPP. How could they? Nobody on the American news mentions it and no one can not even read about the actual legislation. So, why have a poll about an issue that nobody has ever heard of? Obviously, it is a ploy to sway public opinion.

Consumers Reports reported that more than 80% of Americans would like to buy American made products, even if it costs more. However, there is a giant business conglomerate that doesn’t want you to buy anything American and if it has it’s way, you won’t even be able to tell whether anything is “Made in the USA.” It is called the World Trade Organization. Their agenda is to offshore all American manufacturing for increased corporate profits and to end labeling of all products. They have already been successful in repealing laws that says where meat comes from (Country of Origin Labeling [COOL]) and they have passed legislation so that Americans can not know when chickens are processed in China and then sold in the USA. It is just a tiny step until they repeal the labeling of clothing, appliances, automobiles, food, etc (obviously objects “made in China” are going to suffer when it goes directly up against “made in USA”- you saw the Consumers Reports article didn’t you?).

The Trans-Pacific Partnership is bad for America’s present and future. Especially when you consider that China (which is the world’s largest economy – thanks to the WTO) joins the TPP – which it can do at any time. NAFTA and the World Trade Organization has put American manufacturing and the American middle class on its deathbed, the TPP is NAFTA on steroids, and it will nail the coffin shut and bury our future 6 feet under. Why is this Free Trade Treaty any different than the other Free Trade treaties (NAFTA, WTO)?  It is exactly the same.  Conservatively, it will cost the United States over five million jobs (and it won’t just be manufacturing jobs) over the next 15 years. You can take that to the bank. Got any good ideas on how to bring good paying jobs into the United States over the next 15 years? No? Funny, nobody does. Certainly, free trade deals will not do this.

Stop the TPP. Make the government reveal the Trans-Pacific Partnership to the public.

19
May
15

Perils of Globalization When Factories Close and Towns Struggle

Perils of Globalization When Factories Close and Towns Struggle – NYTimes.com.

With the legislation of the Trans-Pacific Partnership (a free Trade treaty) coming perilously close to passing, we should look at a much smaller fore-runner of the TPP, it was called NAFTA – The North American Free Trade Agreement between the U.S., Canada and Mexico. The below article was written by The New York Times. And one of the results from NAFTA is a unique phenomenon – it caused “manufacturing ghost towns”. It is very difficult to rehab these small little towns that were devastated by NAFTA (and the World Trade Organization).

Perils of Globalization When Factories Close and Towns Struggle

From the New York Times

Michael Patrick by the defunct Maytag factory in Galesburg, Ill., last week. Credit Ryan Donnell for The New York Times

GALESBURG, Ill. — Even in this city of abandoned factories, it is possible to see some of the benefits the United States reaps from increased foreign trade: At the rail yard, where boxcars of bargain-price Asian goods are routed to American consumers; at the nearby slaughterhouse, where pigs are packaged for the global market; and at Knox College, where almost 10 percent of the students now come from foreign countries.

It is also hard to miss the enduring costs. In 2004, Maytag shut down the refrigerator factory that for decades was Galesburg’s largest employer and moved much of the work to Mexico. Barack Obama, then running to represent Illinois in the Senate, described the workers as victims of globalization in his famous speech that year at the Democratic National Convention.

A decade later, many of those workers are still struggling. The city’s population is in decline, and the median household income fell 27 percent between 1999 and 2013, adjusting for inflation.

George Carney, who drove a forklift until the day the factory closed, and then found work as a bartender, is now receiving federal disability benefits. He says he is bitter that American policy makers smoothed Maytag’s road to Mexico by passing the North American Free Trade Agreement in the early 1990s.

“I don’t believe in laying someone off, in taking away someone’s livelihood just so other people can make more money,” Mr. Carney said as he nursed a beer in a windowless bar on the banks of the Mississippi River. “Why would I want to destroy that person? Why would I want to destroy lives?”

It is one of the basic principles of economics that trade is good and more trade is better. But as Mr. Obama presses Congress for the authority to negotiate a new generation of trade deals, the struggles of Galesburg illustrate why some economists have come to doubt the relevance of that orthodoxy. The costs of globalization have been greater and more enduring than they expected, and government efforts to mitigate the impact on American workers have often proved insufficient.

“I think what we’ve learned is that U.S. labor markets aren’t as flexible and self-correcting as I think we had presumed,” said Gordon Hanson, an economist at the University of California, San Diego. “The uneasiness I have about the way we’ve handled globalization is not so much globalization itself. It’s that if you don’t have the right safety net, you’re going to impose an enormous amount of hardship.”

There is also mounting evidence that the benefits of globalization have accrued disproportionately to upper-income households, while the costs have fallen heavily on the less affluent, contributing to the rise of economic inequality.

The Obama administration has presented the proposed agreements — one with nations that border the Pacific Ocean, the other with Europe — as, in part, a shield against globalization that would require other nations to move closer to American standards for environmental protection, worker rights and intellectual property.

But the administration and many outside economists say further trade, despite the negatives, is still clearly beneficial.

David Weinstein, a Columbia University economist, said the image of downtrodden Galesburg should be set alongside the prosperity of Silicon Valley, because the decline of manufacturing in the United States helped free resources to feed the high-tech boom.

“There was a sense that by losing the ability to produce computer chips, we were going to see the American electronics industry collapse, and it turns out that those cheap imported electronic components were just the thing that all of these companies needed,” he said. “What these critiques miss systematically is that the losers know who they are, but the winners don’t know who they are yet.”

Drop in the Bucket

Trade deals are at the center of the political debate about globalization, but for all the sound and fury they generate, recent deals have played only a small role in the expansion of global trade. In 2013, on the 20th anniversary of Nafta, the Congressional Research Service reviewed the research and concluded it was not that big a deal. [Well not compared to the WTO -Ed.]

“In reality, Nafta did not cause the huge job losses feared by the critics or the large economic gains predicted by supporters,” the report concluded.

[Editor’s note: the report doesn’t say how many U.S. jobs that were lost – some sources have said as little as 670,000 jobs and as high as 3.1 million jobs. Before NAFTA, the trade between U.S, and Mexico went from (1993) a $1.7 Billion surplus to (2012) $61.4 Billion deficit. Before NAFTA, there were zero cars imported into the USA, now Mexico has imported $40.1 Billion vehicles into the USA].

Since Nafta, the United States has made trade agreements with 17 other countries, but the estimated impact of those deals, taken together, is even smaller — a few snowflakes added to a snowball already rolling downhill.

The seismic shift came after World War II, when the United States and other developed nations began to minimize tariffs and other barriers. Global trade grew as industrialization spread, particularly in China, and thanks to innovations including the standardized shipping container and the Internet.

Tracy Warner, who worked at the factory for 15 years, is now a teacher’s assistant. Credit Ryan Donnell for The New York Times

Just as individuals benefit by working in one field and using their earnings to pay for other goods and services, economists contend that nations, too, prosper by specializing: exporting what they have and importing what they want.

A 2005 study by the Peterson Institute for International Economics, a research group in Washington that is a strong proponent of trade deals, estimated that embracing trade had added about 7.3 percent to America’s economic output — or about $10,000 in annual income for every household in the United States.

But the benefits are not distributed evenly. Trade increases overall prosperity by eliminating less productive jobs. In theory, the workers find new jobs. In practice, studies by Mr. Hanson and other economists show that in cities like Galesburg, global competition is increasing unemployment and reducing wages.

Josh Bivens, an economist at the liberal Economic Policy Institute, estimates that increased globalization, aided by a strong dollar that led to a persistent trade deficit, reduced the annual earnings of the roughly 70 percent of American workers without college degrees by about $1,800.

Joseph Stiglitz, a Columbia University economist and Nobel laureate, said the magnitude of these losses was large enough that increased trade may now be harming the American economy.

“The argument was always that the winners could compensate the losers,” Mr. Stiglitz said. “But the winners never do. And that becomes particularly relevant when we have a society with as much inequality as we have today.”

Few Job Options

Richard Lindstrom, whose family has owned an appliance store on Galesburg’s Main Street for the last 89 years, said sales fell when Maytag left. But that was about the same time he started selling many imported high-definition televisions.

“We rode that crest, and it really offset the drop in appliance sales,” he said.

Some Maytag workers were able to find better jobs. Mark Semande is now a foreman on the BNSF railroad, which has prospered greatly from increased trade. He made $14.50 an hour at the factory. Now he makes $28.93. With overtime, he estimates that his pay has tripled.

But many of the 1,600 Maytag workers were not as fortunate, according to Chad Broughton, a lecturer in public policy at the University of Chicago who chronicled Galesburg’s struggles in his book, “Boom, Bust, Exodus.”

Tracy Warner, who worked at the factory for 15 years, has not come close to matching her former salary of about $37,000 a year. She works as a teacher’s assistant by day and a janitor by night and makes about $21,000.

Mr. Semande — whose father also worked at the factory — said he expected that his two daughters, ages 13 and 15, would move away when they grow up. “Maybe they could find jobs and live in the community,” he said, “but not if they want to do as well as us.”

Downtown, Lindstrom’s Appliances displays an early refrigerator. Credit Ryan Donnell for The New York Times

Trade also tends to reduce prices, and there is evidence that lower-income households may benefit disproportionately, because they spend a larger share of income than wealthier households on the goods with the largest price declines. This Walmart effect may partly offset the distribution of income gains.

A study published last year estimated that international trade had lifted the purchasing power of lower-income American households, at the 10th percentile of the income distribution, about 62 percent. For wealthy households, at the 90th percentile of the income distribution, the power increase was 3 percent.

The variety of imports has also roughly tripled since the 1970s, according to a 2006 study that Mr. Weinstein, the Columbia economist, helped write. “We benefit from the fact that it’s no longer just a choice between Maxwell House and Folger’s,” he said.

Walmart opened a supercenter in Galesburg in 2007, but Mr. Broughton said the arrival of the store could hardly offset the loss of the factory.

“The decline in the quality of life for working-class families has not been nearly matched by the low, low prices,” he said. “Maybe those diffuse benefits have benefited America more generally. But it’s not the case in Galesburg.”

Lying Idle

President Obama returned to Galesburg in 2013 to deliver an economic policy speech at Knox College. “Let’s tell the world that America is open for business,” he said. “I know there’s an old site right here in Galesburg, over on Monmouth Boulevard — let’s put some folks to work.”

But most of the old factory has been demolished. The last trace of its former life is a “Maytag Drive” street sign. The last refrigerators to roll off the line sit in a makeshift museum at the back of a downtown antiques mall.

Michael Patrick, who started working at the factory in 1959 and became a senior union official representing workers throughout the region, said job losses were nothing new. Companies went out of business, mechanized, moved to new cities. He recalled that in the 1970s, the workers who made the shells of refrigerators were replaced by a new machine the size of a football field.

The difference in recent decades, he said, is the absence of new companies.

But Mr. Patrick is not sentimental about what he views as the end of manufacturing in Galesburg. He said he focused on getting as much funding as possible to help his members train for new careers. He went to work after high school, he said, partly because there was no junior college in Galesburg. Now there is.

“Manufacturing was for people like me,” Mr. Patrick, who is now 73, said.

When Ms. Warner, 49, learned that the plant would close, she finished an associate’s degree at the local community college, then won a share of that training money to pursue a degree in communications at Western Illinois University.

But two years of tuition was not enough to reconstruct her life.

She is proud of the degree, but it has not helped her find a job. She lacks professional experience, and jobs in Galesburg are scarce. She has a teenage son and she does not want to move.

“I just needed a little more help,” she said. “I didn’t ask for my job to be taken out of the country.”

Thanks to the Alliance for American Manufacturing for pointing out this article.

07
Apr
15

What is a Free Trade Treaty?

With the upcoming April 13, 2015 vote on The Trans-Pacific Partnership Treaty (TPP), it may be important to know what a Free Trade treaty is (which the TPP is). This article is devoted to the non-economist in all of us.  But, in order to define “Free Trade”, we must first know what “Import Tax” is, because “Free Trade” basically eliminates import taxes. As I am writing this article for an American audience and will  use references specifically to the USA. For the bullet points, skip to the Economics for Dummies points.

Import Tax History in the USA

Import tax is a tax on materials that comes from other countries. It has two functions: 1) to protect businesses in the United States from foreign competition; and 2) to raise money for the government, so as to finance standing armies and other functions. Our forefathers knew that American businesses needed protection from foreign competition. In the original “Constitution” called the Articles of Confederation (1776-1783), which was a loosely based agreement of governance by the individual states, there was no import tax and American businesses suffered greatly from all the numerous British imports. After the Articles of Confederation was thrown out, the U.S. Constitution was written and ratified to establish a strong central government. Alexander Hamilton, founding father and first Secretary of the Treasury, established (or re-established like in colonial times) import taxes and protected American businesses from having to survive practices such as “dumping” – where a foreign country produces so much of the same product that it artificially drops the price of that object giving the foreign nation an unfair trading position. Economics For Dummies Point: Import Tax and “Protectionism” had been an unqualified success in the United States for over two centuries.

Inventing a New Way of Thinking – Free Trade

The “New Way of Thinking” actually came from very old thinking of Adam Smith (1723-1770) and his disciple David Ricardo (1772-1823) who wrote about the theory of comparative advantage in his 1817 book On the Principles of Political Economy and Taxation, it makes a case for free trade based not on absolute advantage in production of a good, but on the relative “opportunity costs” of production. A country should specialize in whatever good it can produce at the lowest cost, trading this good to buy other goods it requires for consumption. This allows for countries to benefit from trade even when they do not have an absolute advantage in any area of production. Criticism Of Ricardo’s theory: The theory was written in 1817, before there was Industrialization or mass production; before there was dependable transportation like steamships, freeways, semi-trucks, airplanes or goliath cargo ships; and well before globalization where you communicate instantly between countries  and before countries could “change their specialties” in a couple of years. None of Ricardo’s mathematical formulas even came close to addressing this.  And overall, very few countries practiced Free Trade Treaties and, therefore, it was put on the shelf for many years. It does seem that this 1817 theory would have absolutely no relevance to the late 20th or 21st Century, but we would be wrong. Economics For Dummies Point: Free Trade eliminates import taxes which makes cheap crap from China even cheaper.

The Return of Free Trade

So, why would this outmoded 1817 theory that was never truly tested have a comeback? Let us look at few of the factors. America’s hubris was at its highest, in the late 1970’s. America was definitely the number one economy in the world and the world’s largest manufacturer. There wasn’t even a close second. The U.S. ruled the entire world, installing puppet governments and paying other countries to be our friends (we still pay countries to be our friends). America could do no wrong.

Then, there was the new school of economists, now called Libertarian Economists (in classic economic terms it was called Liberal Economics but it became very confusing and so it is rarely called that) lead by Milton Friedman, (financial adviser to President Ronald Reagan) and later Alan Greenspan (chairman of the Federal Reserve) who had bold “new”plans like “Trickledown” economics, an obsolete policy that did not work in the 1920’s, where it proposed that if you gave more money (decreased taxes) to the richest people, this money would gradually trickle down to the masses (which it never did), and “De-regulation” where control is done only by the businesses themselves -like in the 1700s (As well as the aforementioned revival of Free Trade).

Then, there was also the “Mega” business movement. Within this movement (economists forgot 200 years of banking tradition), it proposed to make banks not only interstate, but also international. This created too big too fail banks who possessed more assets than most countries. With this “Mega Movement” regular companies jumped in and laws were allowed to let them become mega-companies. These Mega-companies by their sheer volume were able to artificially bringing prices down and therefore eliminated most small business and middle size companies. Thus, the “Big Box Store” boom was created and the importance of small businesses became a thing of the past. Economics for Dummies Point: Factors that allowed Free Trade to prosper was unimpeded greed.

The Passage of Free Trade Treaties

The first Free Trade Agreement was negotiated by the Reagan administration and signed into law by President Ronald Reagan. This treaty was between the United States and Canada. The next free trade trade was spearheaded under the George H.W. Bush administration in 1990 which was to be called the North American Free Trade Treaty  (NAFTA) – an agreement between Mexico, the USA and Canada. NAFTA became famous as it was debated in the public forum (unlike all other Free Trade Treaties). In the Presidential Debates of 1992 between incumbent President Bush (R), Bill Clinton (D) and third party candidate Ross Perot, Mr. Perot correctly predicted if the U.S. passed NAFTA “we would hearing “a giant sucking sound” coming from the south, which was his colorful phrase for the future term called offshoring. Bill Clinton won the 1992 election and NAFTA passed in 1994. Within 8 years, 700,000 American jobs were sent to Mexico. Here is a classic example of NAFTA: Hershey’s Chocolates no longer make any chocolate in the United States, it is all made in Mexico. As Hershey’s offshored all of its US jobs to Mexico it has created numerous manufacturing ghost towns of cities like Oakdale, CA, Robinson, IL, Hazelton, PA, Stuart’s Draft, VA  Naugatuck, CT and, Hershey’s PA.

Then, came the mother of all Free Trade agreements, with the formation on January 1, 1995 of the World Trade Organization. Talks had started in earnest under The Ronald Reagan administration in 1986 to replace the previous world agreement called The General Agreement on Tariffs and Trade (GATT) – the most successful world agreement in history running from 1/1/48 to 1/1/95 (although it had been reality been phased out in 1986). With the GATT agreement, there were many agreements with favored countries to lower import tax rates. But with the WTO – this became an agreement with 161 countries with China joining in 2001. The WTO had really forced down import tax rate on products shipped to America.

Historically, in the 1800’s the average rate on import tax was anywhere from 15% up to 50%. From 1960-1970, the import tax rate was between 6.0 – 7.3%. In 2015, the import tax rate into the United States on average is 1.5% which is one of the lowest if not the lowest in the world. And with extremely low rate, it has allowed countries like China to overproduce and drive out U.S. businesses or even worse caused U.S. companies to pack up and join the enemy – offshoring of U.S. jobs. Economics for Dummies Point: Free Trade Agreements have virtually eliminated import taxes allowing companies to offshore U.S. jobs

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The Effect of the WTO

Below are two graphs. One is the loss of manufacturing jobs in the U.S. due to Free Trade and the second graph is the actual Gross Domestic Product (GDP) figures (a way to characterize economic growth) of the U.S and China. Note in 1999, China was preparing to join the WTO (which it did in 2001) by revving up its factories as it knew that this was exactly the time that the United States was eliminating quotas (The quota laws called the Multi Fibre Acts were passed in 1974 to protect U.S. companies from “dumping”). And then China continuously dumped their untaxed products onto the United States. Did David Ricardo predict this? Did Milton Friedman predict this? No, only Ross Perot did.

 

Loss of US manufacturing jobs 1980-2012. NAFTA 1994, WTO 1995, China joins WTO 2001

Loss of US manufacturing jobs 1980-2012. NAFTA 1994, WTO 1995, China joins WTO 2001

 

 

U.S, China, India GDP growth from 2003 - 2015

U.S, China, India GDP growth from 2001 – 2015

Besides NAFTA and the World Trade Organization which affects 160 other countries, the United States also has 13 other smaller Free Trade agreements. Really too small to even mention individually. Economics For Dummies Point: Free Trade Agreements are devastating to the U.S. economy especially the World Trade Organization.

Other Criticisms of Free Trade

There are many arguments besides economic against Free trade policies. First, Free Trade heavily favors large corporations destroying infant industries as well as the small and medium sized companies. It undermines long-run economic development – it is difficult to revive manufacturing ghost towns, and difficult to plan for growth when American jobs can be offshored at any time. Free Trade has definitely caused income inequality, and environmental degradation.

Born to Work Picture from the Daily Beast in 2009

Born to Work
Picture from the Daily Beast in 2009

Free Trade is supportive of countries sticking to their native practices which often means supporting child labor and working in sweatshops where workers get no benefits in often poorly ventilated and dangerous work environments.

Bangladesh factory collapse

Bangladesh factory collapse

Free Trade has definitely caused the race to the bottom, wage slavery, accentuating poverty in poor countries, harming national defense, and forcing cultural change. One additional criticism is that it allows large corporations to ignore local, state and governmental rules and laws: U.S. Appeals WTO Ruling on Meat Labeling Laws – where the American Meat Institute refused to label their meats as to where the originated. The Congress has successfully repealed the Country of origin labeling law this past winter. Instead of raising global standards, free trade tries to lower standards of countries that are more advanced. All of these inequities have been created so you can buy cheap crap from China at even lower prices. Economics for Dummies Point: If You Think Free Trade is Good, Then You Are a Sociopath.

What To Do About The Trans-Pacific Partnership Treaty?

Do we really need another free trade agreement, our import tax rate is already a record low at 1.5%. We already know the economic impact of previous Free Trade policies. It has been very devastating to the U.S. economy. If you want to stop the TPP from becoming a reality, you will need to write, or e-mail or tweet your Congressman. I have a link that will get you the address or email of your Senator: Listing of U.S. Senator addresses. Write today. the job you save may be your own or at least your neighbors. Stop the TPP!

 

 




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