OMICRON moves fast. This makes it difficult to contain – even for China, which tries to stop any outbreak. A cluster of infections in Shanghai, for example, has shattered the city’s reputation for managing the epidemic perfectly, forcing the government to impose an indefinite stagnant lockdown, for which it appears surprisingly ill.
Alternative speed means it is unusually difficult to track China’s economic prospects. A lot can happen between the release of a data point and its reference time. The most recent hard numbers in the Chinese economy point to two months, January and February. Those (surprisingly good) figures already look dated, even weird. There was no war in Europe for most of that time. And on average, there are less than 200 new covid-19 cases per day in mainland China, compared to the 13,267 infections reported on April 4th. Relying on these official economic statistics is like using a rear view mirror to walk through a chicken.
To make China’s rapidly deteriorating economy more timely, some analysts are leaning towards the less conventional index. Baidu, for example, a popular search engine and mapping tool, provides a daily mobility indicator based on tracking smartphone activity. In the seven days since April 3, the index was down 48% from a year earlier.
The Baidu indicator is most suitable for tracking movement between cities, says Ting Lu of Nomura, a bank. To measure the hustle and bustle in the city, he uses other indicators, such as subway travel. In the week ending April 2, the number of metro trips to eight major Chinese cities was about 34% lower than a year earlier. Lock-down in Shanghai, where many subway lines are now closed, the number of trips has dropped by almost 93%, a worse drop than the damage the city suffered in early 2020.
Mr Luke worries that the two numbers track the economy’s distribution system the most, especially couriers and lorries. In the week ended April 1, an index of express delivery by courier companies was about 27% below its level in the same period last year. Over the same period, a data provider, the Road Freight Index compiled by Wind, showed a 12.8% decline. The fall is particularly evident as the index rose more than 7% at the end of last year.
Unconventional indicators in China are even more valuable due to doubts about official data. For example, the strong figures for January and February are not only outdated but also bizarre. They suggest that investment in “fixed” assets, such as infrastructure, manufacturing facilities and assets, increased by a nominal 12.2% year-on-year. But with a double-digit reduction in the output of steel and cement, it is difficult to square it. The decline in housing sales, start-ups and land purchases, as well as recovery in property investments, also looks strange. When local governments in the provinces of Shanxi, Guizhou and Inner Mongolia said they were double-checking their figures at the behest of the National Bureau of Statistics (NBS), it became clear that the official figures looked strange, even to official statisticians.
China’s high-frequency indices have proven their worth in the spring of 2020, during the fog of the initial epidemic. Although everyone knew the economy would suffer, forecasters were at first afraid to cut their growth forecasts. No one knew how the economy would react or what NBS would be prepared to report. With evidence gathering from high-frequency data, forecasters were finally brave enough to predict negative growth in the first quarter of 2020. In fact, according to official figures, GDP is down 6.8%.
The relevance of these indicators makes them valuable during the flow period. But they still need to be explained carefully. “There are a lot of traps in this number,” Mr Lu said. Any short period of seven days can be distorted by strange events like bad weather or holidays. And the annual growth rate may be skewed by similar variations from a year ago. Moreover, many of these indicators have a history of only a few years. Explaining them is therefore more art than science. What does a dramatic weekly fall in street freight mean for quarterly GDP growth? It is impossible to say with any accuracy. Mr. Lu was extensively trained in economics when he was a PhD student at the University of California, Berkeley. “But with just one or two years of data, if I use the kind of techniques I learned in school, people will laugh at me.”
To help avoid some of the traps hidden in these obsolete indicators, Mr. Lu and his team look at “a bunch of numbers instead of just one.” In a recent report, he highlighted 20 indicators, ranging from asphalt production to movie ticket sales. “If seven or eight out of ten indicators are bad, we can be confident that GDP growth is getting worse,” he said. At the moment, he thinks, the direction is clear. “Something must be wrong.”
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