US Manufacturing Is Far From Healthy And The Main Reason Appears To Be Globalization

Public awareness and acceptance of the negative consequences of corporate-driven globalization on US workers has grown dramatically over the last years, aided in part by Donald Trump’s attacks on trade agreements like NAFTA.  Of course, Trump deliberately and misleadingly claims that US corporations have also suffered.  And, his tariff-raising actions are an ineffective response to worker difficulties.

Still, many economists continue to argue that the concern over trade is misplaced, that the US manufacturing sector is generally healthy, and it is technology, in particular automation, that is the main reason for the decline in US manufacturing employment.

A new paper by the economist Susan Houseman, “Understanding the Decline of US Manufacturing Employment,” is an effective rebuttal to their arguments. As she concludes: “The widespread denial of domestic manufacturing’s weakness and globalization’s role in its employment collapse has inhibited much-needed, informed debate over trade policies.”

What’s up with the manufacturing sector?  

Figure 1 shows that manufacturing employment remained roughly stable from the mid-1960s through the early 1980s, then began a slow decline until 2000, after which it fell dramatically.

Figure 2 compares the performance of the manufacturing sector–production and employment–with that of the private sector as a whole.  As we can see, the real GDP growth of the manufacturing sector has roughly matched the real GDP growth of the private sector (red and yellow lines; left scale).

Figure 2 also shows that manufacturing’s share of private sector GDP and employment has steadily fallen (green and blue-gray lines; right scale). Manufacturing’s share of private sector GDP peaked at 33 percent in 1953, falling to 13 percent in 2016.  Manufacturing’s share of private sector employment peaked at 35 percent, also in 1953, and fell to just under 10 percent in 2016.

Those who argue that our manufacturing sector remains healthy do so on the basis of the sector’s relatively strong growth record and the fact that it was achieved with ever fewer workers.  As Houseman comments:

many [research economists] have taken it as strong prima facie evidence that higher productivity growth in manufacturing—implicitly or explicitly assumed to reflect automation—has largely caused the relative and absolute declines of manufacturing employment. Even when some role for trade is recognized, it is deemed small, and the decline is taken as inevitable.

However, there is a bit of a puzzle here.  Figure 2 shows that manufacturing GDP growth has generally matched the GDP growth of the entire private sector at the same time that manufacturing’s share of private GDP has steadily fallen.  Houseman offers the solution to this puzzle: “If real GDP growth for manufacturing has kept pace with real GDP growth in the aggregate economy yet manufacturing’s share of private sector GDP is falling, then it must be the case that the average price growth of manufactured goods has been slower than the average price growth for the goods and services produced in the economy.”

In other words, a relatively slow growth in the price of manufactured goods would boost the real value of the goods produced.  At the same time, it would also cause a decline in the manufacturing sector’s share of total output.  And, an examination of price deflators shows just such price trends, with the overall price deflator for the private sector steadily rising and the price deflator for manufacturing remaining relatively constant in the post 1980 period.  Thus, the strong growth in manufacturing GDP and its related productivity/automation story rests heavily on the striking behavior of the manufacturing price deflator.

And therein lies the problem.  Houseman finds that the strong growth in real manufacturing GDP is driven by the price behavior of goods produced by a small subset of manufacturing, namely the computer industry (which she broadens to include semiconductors).  “Although the computer industry has accounted for less than 15 percent of value-added in manufacturing throughout the period, it has an outsized effect on measured real output and productivity growth in the sector, skewing these statistics and giving a misleading impression of the health of American manufacturing.”

Digging into the data 

Figure 4 shows price indices for private industry and manufacturing, omitting the computer industry, and for the computer industry alone. Without the computer industry, the price indices for private industry and manufacturing have largely tracked each other.  The computer industry price index, on the other hand, has marched to the beat of a far different drummer.

Figure 5 illustrates the importance of the above deflators to the debate about the health of the manufacturing sector.  Starting in the mid-1980s we see an ever-greater gap between the real GDP growth of manufacturing without the computer industry (blue-gray line) and the growth of real GDP in the private sector and manufacturing (including the computer industry).

More specifically, “From 1979 to 2000, measured real GDP growth in manufacturing was 97 percent of the average for the private sector; when the computer industry is dropped from both series, manufacturing’s real GDP growth rate is just 45 percent that of the private sector average.” Growth in the manufacturing sector, with the computer industry omitted, has been exceptionally slow over the years 2000 to 2016. Over that period, “real GDP growth in manufacturing was 63 percent of the average private sector growth. Omitting the computer industry from each series, manufacturing’s measured real output growth is near zero (about 0.2 percent per year) and just 12 percent of the average for the private sector in the 2000s.”

So, without the computer industry, manufacturing is clearly struggling.  But what explains the strong computer industry performance?  As we see next, there is also reason to believe that the computer industry’s performance, and thus its contribution to the manufacturing sector, is also seriously overstated, thereby further undermining claims of manufacturing’s health.

The computer industry

The real GDP of an industry is calculated by dividing the yearly dollar value of industry sales by its price deflator.  A real increase in output thus requires that industry sales grow faster than industry prices; if sales double and prices double there is no real gain.

Product quality changes slowly in most industries allowing rather straightforward year to year comparisons of dollar output.  However, the computer industry stands as an outlier; for years now, it has produced significantly more powerful products each year.  And, on top of that, it has even lowered their prices.

As a result of this unusual behavior, estimating the real growth of the computer industry requires a complicated adjustment of the industry’s price index to account for the yearly increase in computer power and speed.  In broad brush the adjustment is handled as follows: If a consumer buys a computer that has 20 percent more computing power than the previous year’s model, the government considers that every 100 new computers produced are the equivalent of 120 of the previous year’s model.  The result of such an adjustment is a significant increase in the industry’s output even if the same number of actual computers are produced, an increase that is further magnified by the decline in industry prices.

While it is entirely reasonable to adjust the computer industry’s output for quality when studying the performance of that industry, we have to be careful when the results are used in the calculation of manufacturing’s overall performance. In fact, the computer industry’s rapid gains, based on significant increases in output with declining employment, are misleading as a measure of actual manufacturing activity for two reasons: first, they owe more to difficult-to-measure quality improvements driven by research and development, and second, a growing share of computer industry production has been globalized which means that it takes place outside the country.

As Houseman says, “quality adjustment [for the computer industry] can make the numbers difficult to interpret. Because the computer industry, though small in dollar terms, skews the aggregate manufacturing statistics and has led to much confusion, figures that exclude this industry, as shown in Figure 5, provide a clearer picture of trends in manufacturing output.”  And as we can see those trends do not support the claims made that we have a healthy manufacturing sector.

The decline in manufacturing employment

Houseman similarly shows that productivity’s role in the decline in manufacturing employment has also been seriously overstated. As Figure 1, above, makes clear, the number of manufacturing workers has been falling for some time.

From 1979 to 1989 manufacturing lost 1.4 million jobs, with the losses concentrated in the primary metals and textile and apparel industries. “Employment in manufacturing was relatively stable in the 1990s. Although measured employment declined by about 700,000, or 4 percent, from 1989 to 2000, the net decline in jobs can be entirely explained by the [domestic] outsourcing of tasks previously done in-house. . . . Had these workers been counted in manufacturing, manufacturing employment would have risen by an estimated 1.3 percent rather than declining.”

As Figure 1 also shows, the explosive decline in manufacturing employment begins in the 2000s.  From 2000 to 2007, manufacturing employment fell by 3.4 million, or 20 percent. From 2007 to 2016, manufacturing fell by another 1.5 million.  And, of course, this was a period of intensified globalization, perhaps best marked by China’s 2001 entry into the WTO.

Examining the data, Houseman found that average annual employment growth in manufacturing was approximately 2.5 percent lower than the average employment growth in the private sector as a whole over the period 1977 to 2016.  Only 15 percent of that differential is accounted for by lower output growth in manufacturing, the rest is explained by higher productivity growth.  However, “When the computer industry is omitted from both series, 61 percent of the lower manufacturing employment growth is accounted for by manufacturing’s lower output growth, and just 39 percent by its higher labor productivity growth.”

As Housemen comments, “The point of this exercise is to show that there is no prima facie evidence that productivity growth is entirely or primarily responsible for the relative and absolute decline in manufacturing employment.”

And there is also reason to question the meaning of the strong computer industry productivity figures. Labor productivity is defined as the value-added of an industry divided by labor input.  In the case of the computer industry, the industry’s productivity growth was probably driven most by product improvements, not automation, that boosted its value added. However, global outsourcing of production also made a contribution. While outsourcing reduces the value added of the industry, the decline in labor input is far greater. Thus, it remains unclear how much productivity increases based on the automation of production have actually contributed to the decline in US manufacturing employment, even in the computer industry.

Most importantly, there is a growing body of research that points to globalization as the major factor behind the recent decline in US manufacturing employment.  For example, Economists David Autor, David Dorn and Gordon Hanson “conservatively estimate that Chinese import competition explains 16 percent of the U.S. manufacturing employment decline between 1990 and 2000, 26 percent of the decline between 2000 and 2007, and 21 percent of the decline over the full period.”  They also find that Chinese import competition “significantly reduces earnings in sectors outside manufacturing.”

In sum, there are good reasons for concern about the health of the US manufacturing sector and opposition to corporate-driven globalization strategies.

Advertisements

The US Is A World Leader In Income and Wealth Inequality

A recent article published in the American Economic Review, “Global Inequality Dynamics: New Findings from WID.world,” draws upon the World Wealth and Income Database to examine trends in global inequality.

Two main takeaways:

  • US economic dynamics have greatly enriched those at the top at the expense of the great majority.
  • Chinese elites, thanks to China’s post-Mao capitalist transformation, are hard at work replicating US patterns of inequality.

While US and Chinese political leaders threaten each other with talk of trade wars, there has certainly been a lot of win-win for those at the top in both countries.

Income inequality

Figure 1, below, highlights the sharp rise in the income share of the top 1 percent and the sharp fall in the income share of the bottom 50 percent in the United States.  It also shows that while China’s elite have also found globalization dynamics beneficial, especially after the country’s 2001 entrance into the WTO, their relative income position has changed little since the Great Recession.  Perhaps most striking is the steady fall in the income share going to the bottom 50 percent of Chinese since the late 1970s start of the country’s process of marketization and privatization.  In contrast to both countries, income shares in France have been remarkably stable.

As shown in Table 1, real income growth for those at the top is positively correlated with earnings—the greater the income, the greater the percentage gain. Things were not so positive for the bottom 50 percent in the US, as the group actually lost income over the period despite overall economic growth.

In the case of China, it appears that growth was so great over the period 1978 to 2015, that even the bottom 50 percent benefited, with that group’s income growing by 401 percent.  However, that figure needs to be treated with caution.  Before the reform period, most Chinese workers earned low salaries but that was balanced by the fact that the Chinese government provided them with a vast array of goods and services at little or no cost.  Everything changed with the country’s capitalist transformation.  Thus, while Chinese workers now earn far more money from their work than in the past, their costs for housing, health care, food, transportation, education, and the like, has also soared.  As a result, income gains for most Chinese likely overstate the benefits they have received from their country’s high rates of growth.

Privatization and concentration of wealth

The article also highlighted trends in the share of private wealth.  As the authors comment:

We observe a general rise of the ratio between net private wealth and national income in nearly all countries in recent decades. It is striking to see that this phenomenon was largely unaffected by the 2008 financial crisis. The unusually large rise of the ratio for China is notable: net private wealth was a little above 100 percent of national income in 1978, while it is above 450 percent in 2015. The private wealth-income ratio in China is now approaching the levels observed in the United States (500 percent), United Kingdom, and France (550–600 percent).

Figure 2 illustrates trends in the share of public wealth in national wealth. China’s downward trend reflects the country’s capitalist transformation, which has led to an increase in the share of national wealth in private hands.  More striking is the fact that “Net public wealth has become negative in the United States, Japan, and the United Kingdom, and is only slightly positive in Germany and France.”

Figure 3 reveals a sharp and sustained rise in the share of wealth held by the top 1 percent in the United States and China in recent decades, and more moderate increases in France and the United Kingdom.

It remains to be seen whether these trends in income and wealth inequality will continue. The fact that inequality trends in France differ greatly from those in the US and China strongly suggests that while capitalist globalization exerts a strong pull in favor of the rich and powerful everywhere, national institutions and relations of power also matter.  And that means that future developments will likely depend heavily on the actions of workers in the US and China, the two countries whose accumulation dynamics appear to exert the strongest force on the international economy.

The Chinese Economy: Problems and Prospects

The Chinese economy is big. In 2017, it was the world’s biggest based on purchasing power parity.  Its output equaled $23.12 trillion, compared with $19.9 trillion for the EU and $19.3 trillion for the US.

China also regained its position as the world’s largest exporter in 2017, topping the EU which held the position in 2016.  Chinese exports totaled $2.2 trillion compared with EU exports of $1.9 trillion. The United States was third, exporting $1.6 trillion.

The Chinese economy also recorded an impressive 6.9 percent increase in growth last year, easily beating the government’s 2017 target of 6.5 percent and the 6.7 percent rate of growth in 2016.  According to international estimates, China was responsible for approximately 30 percent of global economic growth in 2017.

The Chinese government as well as many international analysts also claim that China has entered a new economic phase, one that is far more domestic-centered and responsive to popular needs, and thus more stable than in the past when the country relied on exports to record even higher rates of growth.

It all sounds good.  However, there are many reasons to question China’s growth record as well as the stability of the country’s economy and turn towards a new domestic-centered growth strategy.  Glowing reports aside, hard times might well lie ahead for workers in China and the broader Asian region.

Chinese Growth

As the chart below shows, China’s rate of growth fell for six straight years, from 2011 to 2016, before registering an increase in 2017. Current predictions are for a further decline, down to 6.5 percent, in 2018.

However, Chinese growth figures still need to be taken with the proverbial “grain of salt.”  As Lucy Hornby, Archie Zhang, and Jane Pong discuss in a Financial Times article, Chinese provinces routinely fudge their growth data, which compromises the reliability of national growth figures.  For example:

Inner Mongolia, one of China’s most coal-dependent areas, and the major northern port city of Tianjin, have admitted to falsifying data that will probably require their 2016 GDP to be revised down. They join neighboring Liaoning, the first province to admit to a contraction during the four-year correction in commodities markets.

Inner Mongolia admitted this month that its data for “added value of industrial enterprises of a certain scale” were inflated 40 per cent in 2016. According to the Chinese statistical yearbook, secondary industry comprises 47 per cent of its GDP. Assuming its 2015 figures are accurate, the revised 2016 figures mean the region’s economy shrank 13 per cent. . . .

Like Inner Mongolia, Liaoning admitted to a contraction in 2016 compared with its official performance in 2015. Liaoning admits it faked data for about five years but has not issued a revised series. . . .

Tianjin, one of the big ports that services northern China, could also see a revision. Its Binhai financial district, which offers tax and foreign exchange incentives to registered businesses, swelled to comprise roughly half of Tianjin’s reported GDP last year.

Binhai included in GDP the commercial activity of companies that were only registered there for tax purposes, according to revelations last week. That could result in a 20 per cent drop in reported GDP for Tianjin in 2017, according to FT calculations. Binhai’s high debt levels and access to domestic and international financing make its phantom results a concern for broader markets.

Another possible data offender is Shanxi, China’s most coal-dependent province. Its official GDP growth held up admirably during the commodities downturn.

Last summer China’s anti-corruption watchdog announced unspecified problems with Jilin’s data, adding another troubled northeastern province to the list of candidates to watch.

Wang Xiangwei, former editor-in-chief of the South China Morning Post, sums up the situation as follows:

This [falsification of data] has given rise to a popular saying that “data makes an official and an official makes data”.  The malpractice is so rampant and blatant that over the years, a long-running joke is that simply adding up the figures from all the provinces and municipalities reveals a sum that overshoots the national GDP – by 6.1 trillion yuan (more than 10 per cent!) in 2013, 4.78 trillion yuan in 2014, and 3.6 trillion yuan in 2016.

This data manipulation certainly suggests that China has regularly failed to meet government growth targets.  Perhaps more importantly, even the overstated published nation growth statistics show that China’s rate of growth has steadily fallen.

Debt problems threaten economic stability

There are also reasons to doubt that China can sustain its targeted growth rate of 6.5 percent. A major reason, as the next chart shows, is that China’s growth has been underpinned by ever increasing debt.  Said differently, it appears that ever more debt is required to sustain ever lower rates of growth.

As Matthew C Klein, writing in the Financial Times Alphaville Blog, explains:

The rapidity and size of China’s debt boom in the past decade has been almost entirely without precedent. The few precedents that do exist — Japan in the 1980s, the US in the 1920s— are not encouraging.

Most coverage has rightly focused on China’s corporate sector, particularly the debts that state-owned enterprises owe to the big four state-owned banks. After all, these liabilities constitute the biggest bulk of the total debt outstanding, and also explain most of the total growth in Chinese debt since the mid-2000s.

The explosive nature of China’s corporate sector debt growth is well illustrated by comparisons to the relatively stable corporate debt ratios in other major countries, as shown in the following chart.

China’s growing debt means it likely that sometime in the not too distant future the Chinese state will be forced to tighten its monetary policy, making it harder for Chinese companies to borrow to finance their existing levels of employment and investment, thus triggering a potentially sharp slowdown in growth.  At the same time, since much of China’s corporate debt is owed to government-controlled banks, it is also likely that the Chinese state will be able to limit the economic fallout from expected corporate defaults and avoid a major financial crisis.

But, while corporate debt has drawn the most attention, household debt is also on the rise, and not so easily managed if serious repayment problems develop. According to Klein,

Since the start of 2007, Chinese disposable household income has grown about 12 per cent each year on average, while Chinese household debt has grown about 23 per cent each year on average. The cumulative effect [as illustrated below] is that (nominal) income has slightly more than tripled but debts have grown by nearly a factor of nine. . . .

All this is finally starting to affect the aggregate debt numbers. Household debt in China is still small relative to the total — about 18 per cent as of mid-2017 — but household borrowers are now responsible for about one third of the growth in total nonfinancial debt.

By mid-2017, Chinese households held debt equal to approximately 106 percent of their disposable income, roughly equal to the current American ratio.  What makes Chinese household debt so dangerous is that, as Klein notes, “households cannot service their debts out of GDP. Instead they have to rely on their meagre incomes.”  And as we see below, the share of Chinese national output going to households is not only low but has generally been trending downward.  By comparison, disposable income in the US normally runs around 72-76 percent of GDP.

In addition, it has been “finance companies and private loan sharks” that have done most of the consumer lending, not state banks.  This will make it harder for the state to keep repayment problems from having a significant negative effect on domestic economic activity.

Thus, while Chinese officials argue that China’s new lower rate of growth represents a switch to a new more stable level of economic activity, the country’s debt explosion suggests otherwise.  As Michael Pettis argues in his August 14, 2017 Monthly Report on China:

To argue that the authorities have been successful in stabilizing GDP growth rates and now must address credit growth misses the point entirely. If GDP growth “stabilizes” while credit growth accelerates, GDP growth cannot be said to have stabilized, at least not in any meaningful way. Chinese economic growth can only be said to have stabilized if GDP growth rates remain constant without any increase in the debt burden – i.e. credit grows in line with or slower than nominal GDP – and in my opinion, as I said above, this cannot happen except at growth rates well below half the current reported GDP growth rate, or less than 3 percent.

What new growth model?

For several years Chinese leaders have acknowledged the need for a new growth model that would produce slower but more sustainable rates of growth.  As Chinese Premier Li Keqiang explained in a recent speech to the National People’s Congress:

China’s economy is now in a pivotal period in the transformation of its growth model, its structural improvement and its shift to new growth drivers.  China’s economy is transitioning from a phase of rapid growth to a stage of high-quality development.

In other words, China is said to have abandoned its past export-driven high-speed growth strategy in favor of a slower, more domestic, human-centered growth strategy.  China’s current slower growth is in line with this transformation and thus should not be taken as a sign of economic weakness.

However, there are few signs of this transformation, other than a lower rate of growth.  For example, one hallmark of the new growth model is supposed to be the shift from external to domestic, private consumption-based drivers of growth.  The slowdown in the global economy in the post 2008 period certainly makes such a shift necessary. But the data, as shown below, reveals that there has been no significant gain in private consumption’s share of GDP.  In fact, it actually declined in 2017.

China’s private consumption accounted for 39.1 percent of GDP in Dec 2017, compared with a ratio of 39.4 percent the previous year.  The ratio recorded an all-time high of 71.3 percent in Dec 1962 and a record low of 35.6 percent in Dec 2010. And as we saw above, there has been no significant increase in disposable income’s share of GDP. Moreover, the existing consumption, in line with income trends, remains heavily skewed towards the wealthy.

What has remained high, as we see in the next chart, is investment, a pillar of the old growth model.

China’s Investment accounted for 44.4 percent of GDP in Dec 2017, compared with a ratio of 44.1 percent in the previous year. The ratio reached an all-time high of 48.0 percent in Dec 2011 and a record low of 15.1 percent in Dec 1962.

This investment continues to emphasize infrastructure, real estate development and enhancing manufacturing capacity.  One example:

A symbol of the investment addiction can be found in “China’s Manhattan.”

Tianjin’s Conch Bay, a 110-hectare district with a cluster of 40 high-rise buildings, was supposed to be the country’s new financial capital as outlays surged over the past several years. But in late November there were few signs of life. A number of buildings were still under construction; the streets were empty; and even completed buildings had no occupants.

From 2000 to 2010, investment in Tianjin — the hometown of former Premier Wen Jiabao — swelled by a factor of 10.3.

In fact, despite official pronouncements, China’s accelerated growth in 2017 owes much to external sources of demand.  As Reuters describes:

China’s economy grew faster than expected in the fourth quarter of 2017, as an export recovery helped the country post its first annual acceleration in growth in seven years, defying concerns that intensifying curbs on industry and credit would hurt expansion. . . .

A synchronized uptick in the global economy over the past year, driven in part by a surge in demand for semiconductors and other technology products, has been a boon to China and much of trade-dependent Asia, with Chinese exports in 2017 growing at their quickest pace in four years.

With fixed asset-investment growth at the weakest pace since 1999, exports helped pick up the slack.

“Real growth of overall exports…more than fully (explained) the pick-up in GDP growth last year,” Oxford Economics head of Asia economics Louis Kuijs wrote in a note.

And as we can see from the chart below, China’s export gains continue to depend heavily on the US market—a market that is becoming increasingly problematic in the wake of US tariff threats.

China’s real new growth strategy: The One Belt, One Road initiative

There are many pressures keeping Chinese leaders from seriously pursuing a real domestic-centered, consumption-based growth model.  One of the most important is that the interests of powerful political forces would be damaged if the government took meaningful steps to significantly increase the wages and improve the working conditions of Chinese workers.  And since many in the government and party directly benefit from existing relations of production they have little reason to pursue a strategy that would threaten the profitability of China-based production activity.

At the same time, it was clear to Chinese leaders that a new strategy was necessary to keep Chinese growth from further decline, an outcome which they feared could spur regime-threatening labor militancy.  Their answer, first discussed in 2013, appears to be the One Belt, One Road initiative.  The beauty of this initiative is that it allows the existing political economy to continue functioning with little change while opening up new outlets for basic industrial products produced by leading state firms, creating new export markets for private producers, and expanding the huge infrastructure that underpins the Chinese construction industry.

Asia Monitor Research Center, in the introduction to its Asian Labor Update issue on the One Belt, One Road initiative, describes what is at stake as follows:

Xi Jinping’s One Belt, One Road has been described as the next round of “opening up” by the Chinese government, following the development of Special Economic Zones and China’s accession to the WTO. Indeed, the OBOR strategy can be seen as a very significant and ambitious next step in the expansion of the role that China plays globally and its implementation will impact on the lives of millions of people domestically and globally.

Chinese government strategies towards both the BRICS and even more so towards OBOR, which has been dubbed “globalization 2.0”, potentially have important implications for the direction of globalization in the future. Given the way that China’s development strategies have led to significant environmental destruction and labor rights violations domestically, and the way that its investment overseas has been frequently criticized or led to opposition due to their adverse social and environmental consequences, suggest that there are legitimate causes for concern about the impacts on people and the environment of this direction.

In fact, the special issue includes several contributions which highlight the negative consequences of this initiative.  The initiative is first and foremost designed to enable Chinese companies to build roads, railway lines, ports and power grids for the benefit of China’s economy.  These projects come with massive environmental degradation, displacement of local communities, and local labor exploitation.  It also aims to advance Chinese efforts to control agricultural land and raw materials in targeted countries and promote the creation of Yuan currency area.

It remains to be seen how successful the One Belt, One Road initiative will be in achieving its aims.  What does seem clear is the talk of a new more stable, humane, high-quality Chinese economy is largely just that, talk.  Chinese leaders appear heavily invested in trying to breathe new life into the country’s existing growth model, a model that comes with enormous human and environmental costs.

What’s Driving Trade Tensions Between The US and China

There is a lot of concern over the possibility of a trade war between China and the US.  In early April President Trump announced that his administration was considering levying $100 billion of additional tariffs on Chinese exports, after the Chinese government responded to a previously proposed US tariff hike on Chinese goods of $50 billion by announcing its own equivalent tariff hikes on US exports.  And the Chinese government has made clear it will again respond in kind if these new tariffs are actually imposed.

So, what’s it all about?

To this point, it is worth emphasizing that no new tariffs have in fact been levied, by either the US or Chinese governments.  The first round of announced US tariffs on Chinese goods are still subject to a public comment period before becoming effective, and the content of the second round has yet to be formally decided upon.  Thus, both countries have time to back away from their threats.

Also significant is the fact that both countries are being careful about the products they are threatening to tax.  For example, the Trump administration has carefully avoided talking about placing tariffs on computers or cell phones, two of the biggest US imports from China.  The US has also refrained from putting tariffs on clothing, shoes, and furniture, also major imports from China.

It is not hard to guess the reason why: these goods are produced as part of multinational corporate controlled production and marketing networks that operate under the direction of leading US corporations like Dell, Apple, and Walmart.  Taxing these goods would threaten corporate profitability. As a former commissioner of the US International Trade Commission pointed out: “It seems that the U.S. trade representative was very much aware of the global value chains in keeping some of these items off the list.”

The Chinese government, for its part, as been equally careful. For example, it put smaller planes on its proposed tariff list while exempting the larger planes made by Boeing.

Although the media largely echoes President Trump’s claim that his tariff threats directed at China are all about trying to reduce the large US trade deficit with China in order to save high paying manufacturing jobs and revitalize US manufacturing, the president really has a far narrower aim—that is to protect the monopoly position and profits of dominant US corporations.  The short hand phrase for this is the protection of “intellectual property rights.” As Trump tweeted in March: “The U.S. is acting swiftly on Intellectual Property theft. We cannot allow this to happen as it has for many years!”

Bloomberg News offers a more detailed explanation of the connection between the tariff threats and the goal of defending corporate intellectual property:

the White House is considering imposing tariffs on a broad range of consumer goods to punish China for its IP [intellectual property] practices. . . . the U.S. alleges . . . that China has been stealing U.S. trade secrets, forcing American companies to hand over proprietary technology as a condition of doing business on the mainland, and providing state support for Chinese firms to acquire critical technology abroad. A consensus is growing that these policies, designed to establish China as a dominant player in key technologies of the future, from semiconductors to electric cars, threaten to erode America’s technological edge, both commercial and military.

In other words, US tariff threats are, in reality, a bargaining chip to get the Chinese government to accept stronger protections for the intellectual property rights and technology of leading US firms in industries such as pharmaceuticals, aerospace, telecommunications, and autos.  If Trump succeeds, US multinational corporations will become more profitable.  But there will be little gain for US workers.

The auto industry offers a good case in point.  President Trump has repeatedly said that forcing China to lower its tariffs on imported US cars will help the US auto industry.  As he correctly points out, there is a 2.5 percent tariff on cars shipped from China to the U.S. and a 25 percent tariff on cars shipped from the U.S. to China.  Trump claims that lowering the Chinese tariff would allow US automakers to export more cars to China and boost auto employment in the US.

However, GM, Ford and other automakers have already established joint ventures with Chinese firms and the great majority of the cars they sell in China are made in China.  This allows them to avoid the tariff.  China is GM’s biggest market and has been for six years straight.  The company has 10 joint ventures and two wholly owned foreign enterprises as well as more than 58,000 employees in China. It sells approximately 4 million cars a year in China, almost all made in China.

The two largest automobile exporters from the US to China are actually German.  BMW shipped 106,971 vehicles from the U.S. to China in 2017; Mercedes sent 71,198.  Ford was the leading US owned auto exporter and in third place with total yearly exports of 45,145 vehicles.  Fiat Chrysler was fourth with 16,545.

In short, lowering tariffs on auto imports from the US will do little to boost auto production or employment in the US, or even corporate profits.  The leading US automakers have already globalized their production networks.  But, changes to the joint venture law, or a toughening of intellectual property rights in China could mean a substantial boost to US automaker profits.

For its part, the Chinese government is trying to use its large state-owned enterprises, control over finance, investment restrictions on foreign investment, licensing powers, government procurement policies, and trade restrictions to build its own strong companies.  These are reasonable development policies, ones very similar to those used by Japan, South Korea, and Taiwan.  It is short-sided for progressives in the US to criticize the use of such policies.  In fact, we should be advocating the development of similar state capacities in the US in order to rebuild and revitalize the US economy.

That doesn’t mean we should uncritically embrace the Chinese position.  The reason is that the Chinese government is using these policies to promote highly exploitative Chinese companies that are themselves increasingly export oriented and globalizing.  In other words, the Chinese state seeks only a rebalancing of power and wealth for the benefit of its own elites, not a progressive restructuring of its own or the global economy.

In sum, these threats and counter-threats over trade have little to do with defending worker interests in the US or in China.  Unfortunately, this fact has been lost in the media frenzy over how to interpret Trump’s grandstanding and ever-changing policies.  Moreover, the willingness of progressive analysts to join with the Trump administration in criticizing China for its use of state industrial policies ends up blurring the important distinction between the capacities and the way those capacities are being used.  And that will only make it harder to build the kind of movement we need to reshape the US economy.

US Trade Deficits, Trump Trade Policies, and Capitalist Globalization

Understandably concerned about the consequences of the large and sustained US trade deficit, many workers have grown tired of waiting for so-called market forces to produce balance.  Thus, they cheer Trump administration promises to correct the imbalance through tariffs or reworked trade agreements that will supposedly end unfair foreign trade practices.

Unfortunately, this view of trade encourages workers in the United States to see themselves standing with their employers and against workers in other countries who are said to be benefiting from the trade successes of their employers.  As a consequence, it also encourages US workers to support trade policies that will do little to improve their well-being.

To understand the driving force behind and develop a helpful response to US trade imbalances one must start by recognizing the interrelated nature of US domestic and international patterns of economic activity.  Large US multinational corporations, seeking to boost profits, have slowly but steadily globalized their economic activity through either the direct establishment of overseas affiliates or their use of foreign-owned subcontractors that operate under terms set by the lead multinational.  This process of globalization has meant reduced investment in plant and equipment and slower job creation in the United States, and the creation of competitiveness pressures that work to the disadvantage of workers in both the US and other countries.  It has also led to the creation of a structural trade deficit that is financed by massive flows of money back into the US as well as consumer debt, both of which swell the profits of the financial industry.  In other words, the real problem confronting workers here is capitalist globalization.

The globalization of the US economy

The World Bank divides international trade into either intra-firm trade or arm’s length trade.  Intra-firm trade refers to international trade carried out between affiliates of the same multinational corporation.  Arm’s length trade refers to international trade carried out between “independent” firms.  Independent is in quotes here because international trade between a multinational corporation and a firm operating in another country under contract would still be classified as arm’s length, even though the production and resulting trade activity is determined by the needs of the dominant multinational corporation.

As the World Bank explains in its study of intra-firm trade:

In practice, multinationals employ intra-firm and arm’s length transactions to varying degrees. In 2015, intra-firm transactions are estimated to have accounted for about one-third of global exports. Vertically integrated multinational companies, such as Samsung Electronics, Nokia, and Intel, trade primarily intrafirm. Samsung, the world’s biggest communications equipment multinational, has 158 subsidiaries across the world, including 43 subsidiaries in Europe, 32 in China and 30 in North and South America. Other multinationals, such as Apple, Motorola, and Nike, rely mainly on outsourcing, and hence on arm’s length trade with non-affiliated suppliers.

The four figures below, taken from the World Bank study, illustrate the extent to which multinational corporations shape US trade patterns with both other advanced economies (AEs) and emerging markets and developing economies (EMDEs).  The numbers shown in figures A and B are averages for the period 2002 to 2014.

Figure A shows that approximately one-third of all US exports of goods are intra-firm, meaning that they were sold by one unit of a multinational corporation operating in the US to another unit of the same multinational corporation operating outside the US.  Figure B shows that approximately one-half of all US imports of goods are intra-firm.  In both cases the share of intra-firm trade was higher with AEs than with EMDEs.  Figure E shows that the share of intra-firm exports to AEs remained remarkably constant despite the overall slump in trade that followed the 2008 Great Recession.  Figure F reveals that the share of imports that are intra-firm actually grew over the period, especially from EMDEs.


As noted above, many multinational corporations choose to subcontract production, producing arm’s length trade, rather than establish and buy goods from their own foreign affiliates.  In this case, arm’s length trade is not really independent trade.  We can gain some insight into how important this development is by examining the main sources of arm’s length US imports.  As we can see in figure B below, more than half of all US arm’s length imports come from China.

Most of these Chinese imports are actually exported by non-affiliated suppliers that operate within corporate controlled cross border production or buyer networks. For example, China is the primary US supplier of many high technology consumer goods, most notably cell phones and laptops.  Almost all are manufactured by foreign companies operating in China under according to terms set by the relevant lead multinational corporation.  The same is true for many low technology, labor intensive products such clothing, toys, and furniture, which are usually produced under contract by foreign suppliers for large retailers like Walmart.

Thus, the relatively low share of intra-firm imports from EMDEs compared with AEs owes much to the preference of many important US based multinational corporations–like Apple, Dell, and Nike–to have non-affiliated supplier firms hire workers and produce for them in China.  The same is true, although not on such a large scale, for a significant share of arm’s length US imports from Mexico.

In sum, it is likely that the globalization strategies of multinational corporations, not the decisions of truly independent foreign producers, are responsible for some 2/3 of all US imports.

Trends in trade

Global trade growth has dramatically slowed since the end of the Great Recession.  Global trade grew by an average of 7.6 percent a year over the years 2002 to 2008.  It has grown by an average of only 4.3 percent a year over the years 2010-14.  Significantly, the greatest decline has come in arm’s length trade.  This should not be surprising, since intra-firm trade is essential to the operation of the world’s leading multinational corporations.  US trade exhibits a similar trend.

In the words of the World Bank:

The U.S. trade data highlight that arm’s length trade accounted disproportionately for the overall post-crisis trade slowdown. This reflected a higher pre-crisis average and a weaker post-crisis rebound in arm’s length trade growth compared with intrafirm trade. . . . By 2014, intra-firm trade growth had returned close to its pre-crisis average (4.3 percent of exports and 5.0 percent for imports). In contrast, arm’s length trade growth remained significantly below its high pre-crisis average: its growth slowed to a post-crisis annual average of 4.7 percent compared to 11.3 percent during 2002-08.

Figures A and B below highlight these trends in US trade.

As trade becomes ever more dominated by intra firm exchanges, it will become ever more difficult for governments to manage their international trade accounts using traditional trade tools, and that includes the US government.  For example, according to the World Bank:

Trade conducted through global value chains generally shows less sensitivity to real exchange rates. That’s because competitiveness gains from real depreciations are partly offset by rising input costs. To the extent that intra-firm trade is more strongly associated with global value chains than arm’s length trade, intra-firm U.S. exports may have benefited less from the pre-crisis U.S. dollar depreciation and been dampened to a lesser degree by the post-crisis appreciation than arm’s-length exports. In addition, firms integrated vertically may have a wider range of tools available to them to hedge against exchange rate movements.

The take-away

The US trade deficit is the result of a conscious globalization strategy by large multinational corporations.  And this strategy has greatly paid off for them.  They have been able to use their mobility to secure lower wages (by putting workers from different countries into competition for employment) and reduced regulations and lower taxes (by putting governments into competition for investment).  The result is a structural deficit in US trade that is no accident and not likely to be significantly reduced by policies that do not directly challenge multinational corporate production and investment decisions.

It is hard to imagine that the Trump administration, no matter its public pronouncements, will pursue its tariff policy or NAFTA renegotiation efforts in ways that will threaten corporate power and profits.  Whether its misdirection efforts on trade can continue to encourage workers in the United States to see other workers rather than corporate globalization as the main cause of its problems remains to be seen.

Globalization and US Labor’s Falling Share Of National Output

As the Trump administration pushes ahead with its effort to renegotiate NAFTA, we must never miss an opportunity to remind people that the globalization of US economic activity has, by design, shifted the balance of class power away from working people.  A commonly cited indicator of class power is labor’s share of output (or income), which, as shown below, dramatically fell after the turn of the 21st century after decades of slow decline.

Michael W. L. Elsby, Bart Hobijn, and Aysegül Sahin, writing in the Fall 2013 Brookings Papers on Economic Activity, tested several hypotheses about the cause of labor’s declining share of output.  They concluded, based on their econometric work, that “increases in the import exposure of U.S. businesses” was key, accounting for approximately 85 percent of the decline in the U.S. payroll share over the period 1987 to 2011.  This finding led them to suggest “that a particularly fruitful avenue for future research will be to delve further into the causal channels that underlie this statistical relationship, in particular the possibility that the decline in the U.S. labor share was driven by the offshoring of the labor-intensive component of the U.S. supply chain.”

Labor’s share of income

It is important to be clear about how the labor share is estimated and how well it captures class dynamics.  The starting point is simple: labor’s share of output is calculated by dividing the labor compensation earned during a given period by the economic output produced over the same period.  Things quickly get more complicated, however, because the labor compensation used in the calculation is actually the sum of the labor earnings of two different groups of workers: those who work for others and those who work for themselves.

The compensation of the first group includes the sum of all employee pay and benefits: wages and salaries; commissions; tips; bonuses; severance payments; early retirement buyout payments; exercised stock options; and employer contributions to employee pension and insurance funds, and to government social insurance.  Calculating the employee share of output, known as the payroll share, is relative straightforward thanks to employer fillings.

Things are not so simple when it comes to the second group, since their earnings reflect “both returns to their work effort and returns to the business property they invested in” and there is no simple way to separate their earnings into those two components.  The Bureau of Labor Statistics (BLS) handles this problem by assuming that the self-employed receive an hourly labor compensation similar to that earned by employees who work in the same sector of the economy.

The figure below, from the Brookings Papers article, shows the division of the labor share into its two component parts, the payroll share and the self-employed share.  As we can see, the payroll share is significantly greater than the self-employed share.  In fact, the share of hours of the self-employed in total work hours “has declined steadily from about 14 percent in 1948 to 8.5 percent in 2012.”  However, as Elsby, Hobijn, and Sahin point out, “In spite of the relatively small share of self-employment hours, the treatment of self-employment income plays an important role in the recent behavior of the evolution of the labor share.”

A number of economists have raised concerns about the methodology used by the BLS to divide the compensation of the self-employed into its labor and capital returns components.  One example: the BLS methodology ends up crediting the self-employed with more labor compensation than their total reported earnings for much of the 1980s and early 1990s, a highly unlikely outcome.

Alternative methodologies have been suggested, and the authors of the Brookings Papers article calculate labor’s share using the two most often cited.  The one they call the “asset basis” assumes that the return on self-employed capital is the same as the return on capital in the non-farm business sector, with the remaining earnings credited to labor.  The other, called the “economy-wide basis,” assumes that the division between labor compensation and capital income is the same for the self-employed as it is for the non-farm business sector.  As we see below, the two alternatives generally produce labor share trends that are relatively close together, and significantly lower than that published by the Bureau of Labor Statistics from the start of the series until the late 1990s, when all three series generally converge.

Because of its methodological shortcoming, Elsby, Hobijn, and Sahin prefer either of the two alternative measures, which leads them to the conclusion that use of the BLS series overstates the actual decline in the labor share.  As they explain:

The upshot of these comparisons is that around one third of the decline in the headline measure of labor’s share appears to be a by-product of the methods employed by the BLS to impute the labor income of the self-employed. Alternative measures that have less extreme implications regarding the return to capital among proprietors are more consistent with one another and indicate a more modest decline.

The fact that the difference between the BLS and the alternative measures of labor’s share largely disappeared beginning in the late 1990s suggests that the average hourly earnings of the self-employed have grown much faster than that of the employed.  This, in turn, suggests a significant transformation in the make-up of the self-employed; in particular an increase in the number of individuals engaged in highly lucrative professional work.  In this regard it is important to recall that labor compensation includes not just wage and salary earnings but also things like bonuses and stock options, rewards that became increasingly popular for a select few starting in the late 1990s thanks to the run-up in the stock market.

And in fact, this transformation is confirmed by the authors, who disaggregated the structure of the labor share for employees and total earnings for the self-employed.  The results are illustrated in the following figure, which shows that “the share of income accounted for by both payroll wages and salaries and by proprietors’ income [the sum of their labor and nonlabor earnings] has been buoyed up since the 1980s by substantial rises in the shares accounted for by the very top fractiles of households in the United States.”

As the authors point out:

This rise in inequality is even more striking for proprietors’ income than it is for payroll income. In 1948 the bottom 90 percent of employees earned 75 percent of payroll compensation. By 2010 this had declined to 54 percent. For entrepreneurial income, however, this fraction declined from 42 percent in 1948 to 14 percent in 2010. Even more starkly, over the same period the share of proprietors’ income accounted for by the bottom 99 percent fell from 74 percent to 45 percent. This suggests that the sharp rise in the average hourly compensation of proprietors relative to the payroll-employed since the late 1980s is related to substantial increases in income inequality among proprietors that dominate even the considerable rise in inequality witnessed among the payroll-employed. Moreover, this has been driven by extreme rises in proprietors’ income at the very top of the income distribution—the top 1 percent in particular.

In short, there are a lot of moving parts to the calculation of and evaluation of trends in the labor share of income.  The BLS measure may have overstated the decline, but the explosion of inequality means that the measure’s two components mask an even greater fall in the share of income going to the great majority of working people.

Globalization and the decline in the payroll share of output

Although the labor share is the “headline” statistic, the authors decided to narrow their focus to the payroll share.  As we saw above, it is no simple matter to determine the labor compensation of the self-employed.  In contrast, the payroll share is relatively easy to measure and, as a bonus, can be disaggregated by industry.  Moreover, it is the largest component of the labor share, which means that its movement is most responsible for changes in the overall labor share.

Elsby, Hobijn, and Sahin begin with a standard neoclassical aggregate production model and the most common neoclassical explanations for the decline, which rest on investment and technological change: the growth in the capital/labor ratio and skill-biased technical change.  The basic neoclassical argument is that growing investment shifts income away from labor in the first case and unskilled workers in the second.  However, in both cases the authors found that the movement in relevant variables was not consistent with the actual movement in the payroll share.

Recognizing the limitations inherent in a simple aggregate production function model of the economy, the authors decided to take advantage of their industry data to see whether a more micro/industry perspective yielded better results. More specifically, they econometrically tested whether investment specific technological change, declines in unionization, or increases in import competition can explain the decline in the payroll share.  They found that “Our data yield one robust correlation: that declines in payroll shares are more severe in industries that face larger increases in competitive pressures from imports.”

In the case of investment specific technical change, the authors looked to see whether those industries which enjoyed the lowest price increases for investment goods had the largest declines in payroll share, with the assumption being that these industries would be the most likely to replace workers with capital.  In fact, it turned out that there was a weak negative relationship between the change in equipment prices and the change in payroll shares across industries, the opposite of what was expected “if capital deepening due to the decline in price of equipment were the driving force of the decline in the payroll share.”  This result reinforced the conclusion from their aggregate analysis that investment activity does not explain the decline in the payroll share of output.

The test of unionization was more straight forward.  The authors looked to see if there was a positive relationship between changes in union density in an industry and changes in payroll shares.  While they did find “a positive correlation between the change in unionization and the change in payroll shares across industries,” the relationship was weak. “The weighted least squares regression indicates that cross-industry variation in changes in unionization rates explains less than 5 percent of the variation in changes in payroll shares across industries.”

Last was the test of globalization, or more specifically a test of whether the import-caused hollowing out of US industry was a primary cause of the decline in the payroll share.  Elsby, Hobijn, and Sahin assumed two possible channels for a rise in imports to cause a fall in the payroll share.  The first involved trade-generated capital deepening.  In this case, the outsourcing of production by US firms would lead to a reduction in labor, a rise in the capital-labor ratio, and a decline in the payroll share of income.  However, as the authors noted, they had already tested capital deepening as a potential cause of the decline and found no support for the hypothesis.

The second trade channel relied on wage differentials rather than shifts in capital intensity.  Industries with high labor shares likely have high labor costs, making them vulnerable to import competition.  The greater the competition the more likely firms in these industries were to take actions to lower those costs, including offshoring segments of their production process, thereby producing a decline in their payroll share.

The authors pursued this possibility by computing the import exposure of each industry.  They did so by asking the following question:

If the United States were to produce domestically all the goods that it imports, how much additional value added would each industry have to produce? For example, if all U.S. imports of clothes were produced domestically, how much would value added increase in sectors like retail, textile manufacturing, and so on.

To be able to calculate this measure of import exposure we use the annual input-output matrices that are available for the years 1993 to 2010 from the BLS. Import exposure is expressed as the percentage increase in value added needed to satisfy U.S. final demand if the United States would produce all its imports domestically.

The figure below shows the relationship between changes in import exposure and changes in the payroll share for each industry.  As we can see, import exposure increased for almost all industries—reflecting the growing hollowing out of the US economy–and the larger the exposure the greater the decline in payroll share.  A simple regression showed that the import exposure variable was significant in explaining changes in the payroll share, with cross-industry variation in changes in import exposure explaining 22 percent of the variation in changes in payroll share.

The authors then ran a regression which included all three possible explanations for the decline in the payroll share.  The globalization variable remained highly significant and was the only variable to do so.  With the import exposure valuable included in the regression, the unionization variable became insignificant.  “This suggests that those sectors where deunionization was most prevalent are also sectors that saw the biggest increase in import exposure.”

Elsby, Hobijn, and Sahin conclude:

our results indicate a cross industry link between the increases in import exposure and the decline in the labor share.  While this result cannot be interpreted as causal, it is worth noting that the statistical relationship between import exposure and payroll shares across industries is large enough to account for a substantial fraction of the aggregate trend decline in the labor share. In particular, aggregating the results of the weighted-least-squares regression across industries suggests that increases in the import exposure of U.S. businesses can account for 3.3 percentage points of the 3.9 percentage point decline in the U.S. payroll share over the past quarter century.

 

We know that trade agreements are about a lot more than lowering tariffs to promote trade.  Foremost, they are about strengthening corporate power and profitability.  And despite mainstream economic theorizing to the contrary, there is strong evidence that these corporate gains come, as designed, at the expense of majority well-being.

Studies of the effect on US workers from imports from China (see Autor, Dorn, and Hanson)  and Mexico (see Hakobyan and McLaren), most of which are produced within US transnational corporate-controlled production networks, show that US workers pay a steep price in terms of job loss and lost earnings from corporate driven globalization.  And, as we have seen, Elsby, Hobijn, and Sahin’s work strongly suggests that this process is also the main factor behind the decline in the payroll share of output.  This is class power at work–unfortunately theirs, not ours.

False Promises: Trump And The Revitalization Of The US Economy

President Trump likes to talk up his success in promoting the reindustrialization of the United States and the return of good manufacturing jobs.  But there is little reason to take his talk seriously.

Microsoft closes shop

For example, as reported in a recent article in the Oregonian, Microsoft just decided to close its two year old Wilsonville factory, where it built its giant touch-screen computer, the Surface Hub.  As the article explains :

Just two years ago, Microsoft cast its Wilsonville factory as the harbinger of a new era in American technology manufacturing.

The tech giant stamped, “Manufactured in Portland, OR, USA” on each Surface Hub it made there. It invited The New York Times and Fast Company magazine to tour the plant in 2015, then hired more than 100 people to make the enormous, $22,000 touch-screen computer. . . .

“We looked at the economics of East Asia and electronics manufacturing,” Microsoft vice president Michael Angiulo told Fast Company in a fawning 2015 article that heaped praise on the Surface Hub and Microsoft’s Wilsonville factory.

“When you go through the math, (offshoring) doesn’t pencil out,” Angiulo said. “It favors things that are small and easy to ship, where the development processes and tools are a commodity. The machines that it takes to do that lamination? Those only exist in Wilsonville. There’s one set of them, and we designed them.” . . .

But last week Microsoft summoned its Wilsonville employees to an early-morning meeting and announced it will close the factory and lay off 124 employees – nearly everyone at the site – plus dozens of contract workers. . . .

Even as President Donald Trump heralds “Made in America” week, high-tech manufacturing remains an endangered species across the United States. Oregon has lost more than 14,000 electronics manufacturing jobs since 2001, according to state data, more than a quarter of the total job base.

Microsoft is moving production of its Surface Hub to China, which is where it makes all its other Surface products.  Apparently, the combination of China’s low-cost labor and extensive supplier networks is an unbeatable combination for most high-tech firms.  In fact, the Oregonian article goes on to quote a Yale economist as saying:

“Re-shoring” stories like the tale Microsoft peddled in 2015 are little more than public relations fakery,” [providing] “lip services or window-dressing to please politicians and the general public.”

Foxconn says it is investing

But now we have another bigger and bolder re-shoring story: The Taiwanese multinational Foxconn has announced it will spend $10 billion to build a new factory somewhere in Wisconsin (likely in Paul Ryan’s district), where it will produce flat-panel display screens for televisions and other consumer electronics.

As reported in the press, Foxconn is pledging to create 13,000 jobs in six years—but only 3000 at the start.  In return, the state of Wisconsin is offering the company $3 billion in subsidies.

According to the Trump administration, this is a sign that its efforts to bring back good manufacturing jobs is working.  The Guardian quotes a senior administration official “who said the announcement was ‘meaningful,’ because ‘it [represents] a milestone in bringing back advanced manufacturing, specifically in the electronics sector, to the United States.’”  President Trump followed with “If I didn’t get elected, [Foxconn] definitely would not be spending $10bn.”

However, there are warning signs.  For example, as an article in the Cap Times points out, Foxconn doesn’t always follow through on its promises:

  • Foxconn promised a $30 million factory employing 500 workers in Harrisburg, Pennsylvania, in 2013. The plant was never built, not a single job was created.
  • That same year, the company signed a letter of intent to invest up to $1 billion in Indonesia. Nothing came of it.
  • Foxconn announced it would invest $5 billion and create 50,000 jobs over five years in India as part of an ambitious expansion in 2014. The investment amounted to a small fraction of that, according to The Washington Post’s Todd Frankel.
  • Foxconn committed to a $5 billion investment in Vietnam in 2007, and $10 billion in Brazil in 2011. The company made its first major foray in Vietnam only last year. In Brazil, Foxconn has an iPhone factory, but its investment has fallen far short of promises.
  • Foxconn recently laid off 60,000 workers, more than 50 percent of its workforce at its IPhone 6 factory in Kushan, China, replacing them with robots that Foxconn produces.

In fact, even the Wisconsin Legislative Fiscal Bureau is worried that the state may be overselling the deal, promising billions for very little.  As a Verge article reported:

Wisconsin’s plan to treat Foxconn to $3 billion in tax breaks in exchange for a $10 billion factory is looking less and less like a good deal for the state. In a report issued this week, Wisconsin’s Legislative Fiscal Bureau said that the state wouldn’t break even on its investment until 2043 — and that’s in an absolute best-case scenario.

How many workers Foxconn actually hires, and where Foxconn hires them from, would have a significant impact on when the state’s investment pays off, the report says.

The current analysis assumes that “all of the construction-period and ongoing jobs associated with the project would be filled by Wisconsin residents.” But the report says it’s likely that some positions would go to Illinois residents, because the factory would be located so close to the border. That would lower tax revenue and delay when the state breaks even.

And that’s still assuming that Foxconn actually creates the 13,000 jobs it claimed it might create, at the average wage — just shy of $54,000 — it promised to create them at. In fact, the plant is only expected to start with 3,000 jobs; the 13,000 figure is the maximum potential positions it could eventually offer. If the factory offers closer to 3,000 positions, the report notes, “the break-even point would be well past 2044-45.”

The authors of the report even seem somewhat skeptical of the best-case scenario happening. Foxconn is already investing heavily in automation, and there’s no guarantee it won’t do the same thing in Wisconsin. Nor is there any guarantee that Foxconn will remain such a manufacturing powerhouse. (Its current success relies heavily on the success of the iPhone.)

It is because of concerns like these, that the Milwaukee Journal Sentinel reports that the state’s Senate Majority Leader has said he doesn’t yet have the votes to pass the tax package Governor Scott Walker has promised.

Forget the new trade deals

President Trump has also spoken often about his determination to revisit past trade deals and restructure them in order to strengthen the economy and boost manufacturing employment.  However, it is now clear that the agreement restructuring he has in mind is what he calls “modernization” and that translates into expanding the terms of existing agreements to cover new issues of interest to leading US multinational corporations.

As Inside US Trade explains:

Commerce Secretary Wilbur Ross on Wednesday said “the easiest issues” to be addressed in North American Free Trade Agreement modernization talks “should be” those that were not part of the existing agreement, which entered into force in 1994.

“The easiest ones will be the ones that weren’t contained in the original agreement because that’s new territory; that’s not anybody giving up anything,” Ross said at an event hosted by the Bipartisan Policy Institute on May 31. “And by and large, those should be the easiest issues to get done.”

Ross added that those new issues are important “because one of our objectives will be to try to incorporate in NAFTA kind of basic principles that we would like to have followed in subsequent free-trade agreements, rather than starting each one with a blank sheet of paper.”

Among those issues — which he called “big holes” in the old agreement — he listed the digital economy, services, and financial services. . . .

Ross reiterated the administration’s stance that the “guiding principle is do no harm” in redoing NAFTA, while the second “rule of thumb” is to view concessions made by Mexico and Canada in the Trans-Pacific Partnership negotiations “as sort of a starting point” for NAFTA talks.

Asked whether the administration has set itself up for “unrealistic aspirations” on NAFTA — promising to return to the U.S. jobs that the president has often claimed were lost due to the agreement with Mexico and Canada — Ross cautioned against viewing a retooled deal as a “silver bullet.”

In short, it is foolish and costly to believe the promises made to working people by leading corporations and the Trump administration.  Hopefully, growing numbers of people are getting wise to the game being played, making it easier for us to more effectively organize and advance our own interests.