Automation is hardly the main worry in U.S. manufacturing employment.
The conventional wisdom about the decline in American manufacturing jobs is that automation is to blame—“Most US manufacturing jobs lost to technology, not trade,” a Financial Times headline claims. Similarly, a December New York Times article self-assuredly states, “The Long-Term Jobs Killer Is Not China. It’s Automation,” as does CNN Money in its article, “Rise of the machines: Fear robots, not China or Mexico.”
This assessment of the state of U.S. manufacturing rests on two statistics that seem to be in tension. First, employment in U.S. manufacturing has plunged 30 percent since 2000. Second, manufacturing output has held steady as a percentage of GDP. Improvements in productivity, including automation, explain the divergence of these trends: factories are making more with fewer workers. In other words, the only concern regarding American manufacturing competitiveness is what to do with the workers who’ve lost their jobs to robots.
In fact, the conventional narrative is wrong; it is based on misleading manufacturing statistics. A new, more informed counter-narrative is emerging from a handful of economists and Washington policy analysts. This highly technical analysis involves knowledge of the way U.S. statistical agencies calculate manufacturing output. It shows that employment has indeed fallen in manufacturing, but it is likely that output has fallen, too.