- Joshua Konstantinos
Manufacturing Job Losses are from Trade not Automation
Many people today are concerned about automation. And not without good reason - automation has been blamed for the dramatic job losses seen in manufacturing over the last few decades. And we are warned that automation will soon come for a wider range of jobs - which some think could cause "Depression-level" unemployment.
However, last year an paper was published which overturned the consensus narrative on what exactly is responsible for the job losses the U.S. has seen in the manufacturing sector. Many experts and economists have argued for decades that automation, not foreign trade is responsible for the job losses.
This concept being overturned should have been front-page news in every paper in America – but it is now finally beginning to get the press it deserves. Foreign Affairs, The Washington Post, and others have discussed it. One excellent article in Quartz, said in part:
For a decade or so, this phenomenon had been put forth by Ivy League economists, former US secretaries of treasury, transportation, and labor, Congressional Research Services, vice president Joe Biden, president Barack Obama—and by Quartz too, for that matter. In a 2016 New York Times article titled “The Long-Term Jobs Killer is Not China. It’s Automation,” Harvard economist Lawrence Katz laid out the general consensus: “Over the long haul, clearly automation’s been much more important—it’s not even close.”
Thanks to a painstaking analysis by a handful of economists, it’s become clear that the data that underpin the dominant narrative—or more precisely, the way most economists interpreted the data—were way off-base. Foreign competition, not automation, was behind the stunning loss in factory jobs. And that means America’s manufacturing sector is in far worse shape than the media, politicians, and even most academics realize.
Essentially, with access to a more granular data set than had been publicly available, the economists could see that growth in manufacturing over the decades was almost entirely a result of statistical adjustments for improvement in semiconductor performance. Not to say that this statistical adjustment was not legitimate — the point is that this masked the fact that all other manufacturing output was stagnating so significantly.
The narrative had been that manufacturing job losses — which were visible in the data — were the result of improved automation. The argument was that manufacturing was growing just fine. Manufacturing was not declining or stagnating, it was just doing more with less people because of automation. An example, which was highlighted in the paper, Understanding the Decline of U.S. Manufacturing Employment, is the New York Times article published in late 2016:
From an economic perspective . . . there can be no revival of American manufacturing, because there has been no collapse. Because of automation, there are far fewer jobs in factories. But the value of stuff made in America reached a record high in the first quarter of 2016, even after adjusting for inflation.
Yet, as the economist behind the research, Susan Hosueman, said in an interview with the Washington Post:
…the basis for the automation story is that output growth has been about as high in manufacturing as in the rest of the economy and productivity growth has been much higher. Neither is true in most — 87 percent — of manufacturing.
Many processes in manufacturing have been automated. But automation and other types of labor-saving technology have been introduced throughout the economy, not just in manufacturing. The critical difference is that, unlike in other sectors, output in most manufacturing industries has barely risen or declined since the late 1990s.
With the more grandeur data set available, Houseman was able to see that that this is not the the case for the vast majority of manufacturing. And that if you look at U.S. manufacturing without the statistical adjustments for improvement in computers, the data shows the clear stagnation.
we can see that the U.S. manufacturing sector, less computers, has been stagnating since the mid 1970's - right as the gigantic U.S. trade deficit emerged.
And the job losses are not insignificant, especially since 2001 when China joined the WTO. Quoting Susan Houseman's paper, Understanding the Decline of U.S. Manufacturing Employment:
The precipitous decline in manufacturing employment in the 2000s is historically unprecedented. Between the business cycle peaks of 2000 and 2007, manufacturing employment declined by 3.4 million, or 20 percent. Although employment in manufacturing, a cyclically sensitive sector, often drops sharply during recessions, the early 2000s marked the first period in which employment in the sector did not entirely or largely recover during the subsequent expansion. Manufacturing employment was hard-hit again during the Great Recession of 2008–2009, rebounding only slightly during the ensuing recovery. From 2007 to 2016, manufacturing employment declined on net by 1.5 million. In total, since 2000, manufacturing employment has fallen by nearly 5 million, or by over 28 percent.
Houseman’s research definitively shows that, contrary to what has been reported, automation has not been responsible for the extremely large job losses the U.S. manufacturing sector has seen in the last two decades. Moreover, the flawed analysis which blamed automation has meant that the shock of China joining the WTO has not been fully appreciated. The labor market has not adjusted smoothly — as widely cited research such as Autor, Dorn, and Hanson’s The China Shock clearly detailed in 2016.
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About the Author Joshua Konstantinos Founder and Global Macro Strategist at Cassandra Capital LLC and author of Sleeping on A Volcano: The Worldwide Demographic Upheaval and the Economic and Geopolitical Implications,
Joshua has been obsessively following global trends and collecting data for over a decade. His analysis takes into account not only the larger view of the rapidly changing global economy but also the longer demographic and geopolitical trends.