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Study Suggests That Local Chinese Officials Manipulate GDP

A study by Yale SOM’s Frank Zhang suggests that local Chinese governments often inflate GDP figures in order to meet targets. Some officials may do so by pushing through projects without long-term economic value, such as unnecessary infrastructure investments, while others fabricate numbers outright.

A construction worker in China

Photo: Zhang Qiang/Visual China Group via Getty Images.

After three decades of rapid growth, China’s economy is the second-largest in the world, and a key economic engine for the rest of the world. But journalists, policymakers, and researchers debate whether economic data from China can be trusted.

Resolving this question is critical to policy decisions around the world. For example, if reports are inflated, the United States might overestimate how much China will import from American companies, and firms could be left with excess inventory. Or the United States could have more leverage to squeeze China in the ongoing trade war than policymakers think.

Studies to determine the reports’ accuracy have produced mixed results. But new research by Frank Zhang, a professor of accounting at Yale SOM, and his co-authors has revealed what Zhang calls a “clean answer.” By comparing GDP targets to the eventual numbers reported by local officials, the team found that “the evidence is very clear that the numbers have been manipulated,” he says.


Read the study: “GDP management to meet or beat growth targets”

Zhang’s team was not able to determine how much officials had inflated the figures. But he says that policymakers should exercise caution in interpreting the reports. Instead of basing decisions heavily on GDP, they should place more weight on other economic indicators that are less likely to be manipulated, such as electricity usage or freight volume.

“The easiest thing people can do is rely less on the GDP numbers,” he says.

Zhang defines GDP manipulation, also called “GDP management,” in two ways. First, officials could simply cook the books—that is, report incorrect numbers. Second, they could push through projects such as building infrastructure that temporarily boost GDP numbers, even if the investments don’t make sense for long-term economic health. In this scenario, “the government will simply spend the money without considering the future benefits,” he says. “If they build a bridge or build a highway that goes nowhere, it will not bring economic value.”

Officials may be motivated to artificially boost numbers because meeting GDP targets is an important factor in determining whether they get promoted. On the other hand, Zhang notes, the Chinese central government does want local reports to be accurate so that federal officials can make better economic decisions, such as whether to increase the interest rate. The National Bureau of Statistics of China has uncovered cases of manipulation in the past. But how common this misbehavior is has remained unknown.

To find out, Zhang, working with Changjiang Lyu, Kemin Wang, and Xin Zhang at Fudan University in Shanghai, studied 431 reported GDP numbers from provinces and 3,418 from prefectures from 2002 to 2015. In each case, they compared the reported GDP to the target set by government officials.

On average, prefectures and provinces beat their targets by 0.47 and 1.56 percentage points, respectively. But that result alone didn’t confirm manipulation because the targets could have been conservative.

So Zhang’s team conducted a subtler test. If everything is above board, the chances of reporting a GDP number just below the target should be similar to the chances of reporting a number just over the target. But that wasn’t what happened. Instead, provinces were four times more likely, and prefectures five times more likely, to meet or beat targets by a narrow margin than to barely miss them.

The researchers then tried to figure out whether officials were fabricating numbers or manipulating activities in the real world—for example, funding unnecessary infrastructure projects. By studying other economic indicators such as electricity use and freight volume, the team found that both types of GDP management were likely occurring. The evidence was stronger for cooking the books, which “makes intuitive sense because it’s much easier,” Zhang says. “Just make up some numbers."

GDP reports were more likely to show signs of manipulation if officials in that area had a stronger incentive to do so—for instance, if they lacked political connections to help them get promoted. And evidence of GDP management also was more common if officials had the resources to fund unneeded projects—for instance, if they had a large budget surplus.

Since the research was published, China has cracked down on such manipulation by requiring companies to report performance directly to the national statistics bureau, Zhang says. Still, he advises treating GDP reports with caution and relying on other economic signals.

Researchers could use the same method as Zhang’s team to search for evidence of GDP management in specific regions of China, as well as other parts of the world. “We provide a simple approach to help people figure out which region’s numbers are manipulated,” he says.

Department: Research