The Chinese Economy’s Fatal Flaws

Dr. Per Bylund’s recently published article poignantly states one of the core problems in the Chinese economy and its the state-manipulated Keynesian foundation. I do agree with his opinion. And if we dig deeper into the exact situation of Chinese economy, we will find that it’s a typical failing of the Keynesian, cronyist system.
By using the perspective of Austrian business cycle theory, lets take a look at China’s real estate industry, which is suffering more and more painfully from artificial credit issued by China’s central bank, the People’s Bank of China (PBC). During the 2008 global economic crisis, China’s central government issued the famous RMB 4 Trillion Stimulus Package Plan (equaling to $586 billion). Since 2009, the Chinese real estate economy has already suffered from three small economic cycles. As it is becoming more difficult for real estate companies to live on artificial prosperity, the duration of every business cycle has become shorter than the previous one. We also see more and more ghost cities because of the economic boom in every sub-economic cycle. There were at least 12 ghost cities founded in 2013, and the number of them jumped to at least 50 in 2017! Bankruptcy is happening more frequently among Chinese real estate enterprises. Since 2016, at least three real estate companies – with a combined debt of at least RMB 763 million – have gone bankrupt. The story of bankruptcy is continuing, with one of the biggest real-estate-driven enterprises, Wanda Group, facing financing problems. If Wanda no longer has access to cheap debt, it might not be able to refinance or roll over all its debt again. If Wanda has to face bankruptcy, it could possibly accelerate an end of the the current Chinese boom.
The data from the Chinese local governments is also not optimistic; their debt levels have reached almost RMB 25 trillion (US$ 4 trillion) at the end of 2014. In 2015, even the PBC admitted in one of its annual reports saying that China’s financial system is facing higher instability and uncertainty.

This post was published at Ludwig von Mises Institute on August 22, 2017.

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