The Three Provinces Still Struggling to Recover from China’s Covid-19 Outbreak
Alternative data from inside China continue to reveal the extent of the impact.
It’s now 8 weeks since the first reported death in Wuhan, Hubei province from Covid-19.
When we first started reporting on the economic impact of the Coronavirus 2019 (Covid-19) outbreak back in February it was immediately clear that critical export provinces were showing signs of major disruption.
Despite China’s notoriously challenging informational environment, our objective, daily observations on the activity and stability of hundreds of millions of internet connections have proven the value of high quality alternative data during critical incidents.
Our consistently measured Internet Connectivity Index for Guangdong, Fujian, Zhejiang, Shandong, Henan and Jiangsu all fell dramatically, as expected, during the Lunar New Year vacation (24–30 Jan).
But then, Covid-19 showed itself.
Despite the official ‘return to work’ order of Feb 10, all of these strategic provinces, each generating over USD 100 billion of export revenue per annum, stayed frozen.
Reports of manufacturing zones “grinding to a halt” began to emerge online.
A week ago, when we updated our analysis, we identified two speeds emerging in the speed of recovery. Whilst Guangdong, Fujian, and Henan were on the way back, three provinces started to flatline.
While stock-markets have been hit by a bout of violent volatility, the true impact of the crisis on global logistics and manufacturing supply lines may still be to come.
In this update, we check in on the three lagging provinces through the lens of our global observational technology.
The Three Provinces Struggling to Recover
Then as now, Jiangsu, Shandong and Zhejiang remain well behind other provinces in their revealed economic recovery from the virus’s impact.
As can be seen in Figure 1 above, the stagnation of early March gave way to a period of growth for Shandong and Jiangsu, starting around 5 March, in line with similar trends in Fujian and Henan.
In the case of Shandong and Jiangsu, this latest movement is interesting given the obvious mountain to climb in terms of revealed economic impact of the Covid-19 outbreak in the Connectivity Index.
However, notably, Zhejiang has entered another plateau phase, breaking a sustained growth phase that started on the 16 February.
The last time Zhejiang stagnated, the phase lasted over two weeks.
Only time will tell if this pause is a bump in the road, or an indicator of something more serious in efforts to re-start the engines of economic and social activity in this major export powerhouse.
Going Online In Hubei
Figure 1 also reveals the extent to which life is now online in Hubei, the epicenter of the Covid-19 outbreak.
Hubei was already above normal in internet connectivity following the Jan 23 lock-down declaration.
The Lunar New Year saw connectivity drop a little, before Hubei roared into life, staying high and increasing of late as the Chinese central government demanded all education move online, and consequently, parents faced the ominous task of overseeing their children’s education in their living rooms during the lock-down.
Once again, consistent, objective measurements of online activity is confirmed as the true nexus of human behaviour, political policy, and economic activity.
Consistent, Objective, Global Measurement with Alternative Data
At KASPR Datahaus, our distributed technology scans, aggregates, analyses and visualizes real-time information on Internet activity and quality by measuring hundreds of millions of connected fixed Internet devices at all over the world.
Our technology has already been applied to create insights for decision makers during various critical events such as natural disasters and political crises.
Every one of these events has either a direct or indirect impact on internet activity and quality. This creates signals that are detected by our geo-located global technology in near real-time, days or weeks before the market knows about them.
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Now you can be the first to know when any region goes down, or changes pattern. Probably before the asset owner themselves.
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