Has the U.S.-China Trade War Hurt the Chinese Economy?

Tuck professor Davin Chor analyzed night light data from satellite imagery to infer the impact of the new tariffs on China’s economy.

When the Trump Administration began levying tariffs on goods exported from China, starting in early 2018, the stated goal was to safeguard American producers and to punish China for its unfair trade practices around technology transfer, intellectual property, and innovation.

But as the tariffs escalated through 2019 to affect 93 percent of products exported from China to the U.S., researchers were finding that the only ones being punished were U.S. consumers. To offset the new costs from the tariffs, firms were raising their prices on domestic goods, which reduced the real income of American households. By the end of 2020, the New York Times was declaring “American Consumers, Not China, Are Paying for Trump’s Tariffs.”

New research from Davin Chor, an associate professor at Tuck and globalization chair at Dartmouth, shows that those earlier conclusions may have been premature. In a working paper titled “Illuminating the Effects of the US-China Tariff War on China’s Economy,” Chor and co-author Bingjing Li of the University of Hong Kong find that China has indeed paid an economic price during the trade war. They estimate that the tail two-and-a-half percent of China’s population who were most exposed to the U.S. tariffs suffered a 2.52 percent decrease in per-capita income and a 1.62 percent decrease in manufacturing employment.

If labor demand goes down, you might expect night lights emitted from those worker quarters to also go down.

It has taken some time for this part of the trade war narrative to emerge, because it’s very difficult to obtain reliable and up-to-date data at the subnational level on China’s economy. Chor and Li mostly circumvented this problem by measuring a common proxy for economic activity: night light intensity, as depicted in high-resolution satellite imagery. “This data has been passively collected since the 1990s,” Chor says, “and development and growth economists recognize there’s a sharp correlation between local economic outcomes and the intensity of the area’s night lights.” In the context of China, more light is emitted when factories are busy and running night shifts, and when the workers in those factories, who often live in nearby dormitories, are more numerous. Conversely, “if labor demand goes down,” Chor explains, “you might expect night lights emitted from those worker quarters to also go down.”


An associate professor in Tuck’s economics group and a chair in Dartmouth’s academic cluster on globalization, Davin Chor teaches Global Economics for Managers.

Chor and Li analyzed night light data as it related to both the U.S.-based tariffs on Chinese exports, and on China’s retaliatory tariffs on intermediate inputs exported to China from the U.S. To do this, they closely studied night light activity in 100,000 grids across China, each measuring 11 square kilometers. Inside those grids, they geo-located 280,000 firms, and constructed a measure of the grid’s exposure to tariffs based on the initial product composition of its exports and imports. In their main analysis, they examined the impact of the tariff shocks during 2018 and 2019 on night light intensity during roughly the same period. They found that each one-percentage-point increase in exposure to U.S. tariffs lowered night light intensity by 0.59 percentage points. “By contrast,” they write, “we do not find statistically significant effects for the retaliatory tariffs on inputs.” They speculate that China was strategic about choosing retaliatory tariffs that wouldn’t harm its own citizens, such as tariffs on agricultural goods they could get from elsewhere, as well as by reducing their most-favored nation (MFN) tariffs.

The final step was to map the night light changes to changes in GDP and manufacturing employment, based on a historical relationship between those variables. Here they found that the impact of the U.S. tariffs was significant but also very skewed. Seventy percent of China’s population had a negligible amount of exposure to the tariffs, but the 2.5 percent of the population that was most heavily exposed saw a big impact to their income (2.52% decrease) and employment (1.62% decrease).

While the trade war began with the Trump Administration, it doesn’t look likely to end under President Biden. That means consumers will probably continue to pay higher prices for goods imported from China, and that China’s citizens in the most exposed industrial zones will continue to suffer from the overhang of these tariffs even as China’s economy seeks to rebound from the COVID-19 pandemic.

In Chor’s view, the impact of the trade war on firms may come into focus in the next few years, as they evaluate their options. “This is reaching a point where companies start to reexamine their global strategy,” he says, “in terms of where you want to locate your production facilities, and how exposed you want to be to China’s supply chain linkages. Those are questions I think managers dealing with complex global operations are examining very closely now.”