The culprit behind manufacturing job losses

Before, during, and since the 2016 presidential election, there has been considerable discussion on whether trade or automation is responsible for America’s long-term loss in manufacturing employment. A December New York Times article highlights several examples of studies finding automation has been the key perpetrator.  Recent research from Adams Nager of the Information Technology and Innovation Foundation (ITIF), however, pins the problem on trade and competition. ITIF suggests that roughly two-thirds of the 5.7 million U.S. manufacturing jobs lost between 2000 and 2010 were a result of international trade pressure and wavering U.S. competitiveness. As economist Paul Krugman recently noted, accounts stating that either trade or automation are the cause can both be accurate and are not necessarily contradictory.

In Trade vs. Productivity: What Caused U.S. Manufacturing's Decline and How to Revive It, Nager highlights two areas where statistical research showing that automation and productivity growth are the primary causes of manufacturing job losses may be misguided. First, Nager says that productivity growth in manufacturing compared to the rest of the economy was consistent from 1990 to 2010, though job losses in the latter decade were considerably larger. Second, Nager finds that government statistics overstate manufacturing productivity growth, especially around computer manufacturing. He argues that when accounting for this mismeasurement, manufacturing’s productivity rate has been much more modest.

At the root of the problem, Nager contends, is a trade deficit. ITIF posits that rapid growth in imports, which replace domestic production, reduced output in nearly two-thirds of manufacturing sectors. In order to close the trade deficit, Nager recommends producing more goods domestically – in part by substantially increasing rates of manufacturing productivity growth. ITIF estimates that the U.S. would gain an additional 1.3 million manufacturing jobs by eliminating its manufacturing trade deficit. In other words, ITIF is suggesting that more automation, not less, will help make manufacturing great again by increasing its productivity.

Nager’s findings are similar to an Economic Policy Institute report by Robert Scott that argues trade, not productivity, is the real culprit behind manufacturing job loss. In particular, Scott suggests that growing trade deficits and the shortfall in demand caused by the Great Recession are leading causes of manufacturing job loss.  Scott recommends two actions in particular to address this issue: increasing investments in domestic infrastructure, and addressing currency manipulation, which Scott contends distorts trade flows by artificially lowering import costs and raising export costs.

In making its argument, the ITIF report seeks to refute other claims that point to automation, not trade, as having larger impact on manufacturing sector employment. Notably, Nager questions a study from Ball State’s Center for Business and Economic Research that finds 87 percent of manufacturing job losses are due to enhanced productivity and automation. Shortly after the release of the ITIF report, the authors from Ball State responded by reiterating their belief that automation is responsible for the longer trend in manufacturing job losses. Recent Boston University research suggests that the impacts of automation on employment are complicated, and that jobs are more likely to be modified, rather than replaced, by automation.

Ultimately, it is difficult to place full blame on either automation or on trade and competitiveness as the leading contributor to manufacturing job losses, and it is likely that both offer potential explanations. Research cited in The Financial Times finds that generally, both trade and automation have contributed to manufacturing employment declines. Similarly, a recent analysis by economist Paul Krugman examines both arguments and finds that the two camps often differ in the specific questions they are trying to ask, and that in many instances, they do not have to necessarily contradict one another.