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Should US manufacturing policy embrace job restoration or retraining? 

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Should US manufacturing policy embrace job restoration or retraining? 

In the run-up to the 2024 elections, Joe Biden and Donald Trump are targeting industrial states such as Michigan, Pennsylvania and Wisconsin that played key roles in determining the outcome of the two previous elections.

Despite their numerous differences, both candidates have emphasized the need to restore jobs that were lost in manufacturing. President Biden has kept most of Trump’s tariff increases in place, and he recently announced plans to more than triple the tariff rate on Chinese steel and aluminum to 25 percent from 7.5 percent. Previously, Donald Trump indicated he is considering tariffs of more than 60 percent on Chinese imports if he becomes president.

Partly as a result of their efforts, there are now about 600,000 more jobs in manufacturing since 2017.  This increase represents one-tenth of the losses since 2001 when China joined the World Trade Organization. 

These efforts might be viewed as an attempt to reverse the decline in labor’s share of national income over the past 40 years. Data compiled by the Bureau of Labor Statistics, for example, indicate the share has fallen from about 64 percent in the mid-1980s to about 58 percent recently, with most of the decline occurring in the past 25 years. However, a National Bureau of Economic Research study finds no consensus among economists about the decline’s extent or key drivers.

Amid this, an important question is unresolved: Namely, does the focus on increasing manufacturing jobs make for good economic policy?

Former U.S. Trade Representative and World Bank President Robert Zoellick discussed this in a Wall Street Journal opinion piece criticizing both Biden and Trump for wanting “to return the country to a fantasy mid-20th century past.” Zoellick argues that America’s economic success is largely due to its ability to move from low-tech, less productive sectors to higher-value ones.

Also, while manufacturing deploys fewer workers than before, the manufacturing sector is much more productive today, a recent study by the Cato Institute points out that U.S. manufacturing accounts for a larger share of global output than Japan, Germany, South Africa and India combined.

Zoellick is also dubious that the attempts to increase manufacturing jobs will lead to higher wages. The reason: Manufacturing workers earn less than workers in other sectors, especially those in technology-related sectors, where productivity is considerably higher.

A counterargument by proponents of “fair trade” is that free trade advocates are primarily concerned with economic efficiency rather than social justice. Nobel laureate Angus Deaton of Princeton writes in a recent commentary for the International Monetary Fund: “When efficiency comes with upward wealth redistribution, our (economists) recommendations frequently become little more than a license for plunder.”

Deaton is more skeptical of the benefits of free trade to American workers than before in light of what has happened to blue-collar workers. Economic theory asserts that workers who lose their jobs or are adversely impacted by foreign competition can be compensated by those who gain from lower prices for goods. But Deaton observes this redistribution never happens in practice.  

So, how might the U.S. achieve a better balance in promoting economic efficiency and lessening income inequality?

One way is to recognize the role that technological change might play if it is properly managed.

Heretofore, most of the benefits of technological change have accrued to businesses and workers who are highly educated. For example, another NBER study found that the adoption of computers from 1970-1995 increased the demand for college graduates relative to workers without college degrees. As a result, the use of computers contributed to increased wage differentials between high-skilled and low-skilled workers over this period.

Looking ahead, there are some grounds for believing that artificial intelligence could help to lessen income inequality. The main reason is that applying AI to routine processes can improve the efficiency of less skilled workers fairly quickly.  

Toward this end, professors Daron Acemoglu, David Autor and Simon Johnson recently announced the launch of the MIT Shaping the Future of Work Initiative. Its mission is to analyze the forces eroding job quality and labor market opportunities for non-college workers and move the economy onto a more equitable trajectory.

The directors of the MIT program observe that the prevailing view is that little can be done to maintain the well-being of workers without college degrees due to powerful forces such as globalization, technological change and de-unionization. They maintain that this assumption is false.

In their inaugural policy memo entitled “Can We Have a Pro-Worker AI?” they argue that the best path forward is to develop worker-augmenting AI tools that enable less-educated or less-skilled workers to perform higher value-added tasks.

The bottom line is that there is legitimate reason for politicians to be concerned about the plight of U.S. workers who do not have a four-year college degree. Collectively, they represent nearly two-thirds of the U.S. workforce. 

But, history also demonstrates that countries that impose high tariffs to protect workers inevitably fall behind those that pursue export-oriented policies: Witness the outperformance of economies in Asia relative to those in Latin America in the post-WWII era.

Consequently, my position is that higher tariffs make for poor economic policy. That said, I acknowledge that political considerations will likely win out over sound economics — at least until after the outcome of this year’s election. 

Nicholas Sargen, Ph.D., is an economic consultant with Fort Washington Investment Advisors and is affiliated with the University of Virginia’s Darden School of Business. He has authored three books including “Investing in the Trump Era: How Economic Policies Impact Financial Markets.”

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