It is quite uneasy to track China’s monetary and fiscal policies and and to disentangle what really happens on the ground from official communication lines. Most western media fall in the trap and take Chinese official communications, including official statistics, at face value, without bothering to analyse and cross-check the underlying data.
It is quite straightforward to focus on the Chinese as it was the only major economy to post a positive growth in 2020. The whopping 18.3 percent year on year growth reported in Q1 2021 has been erroneously interpreted as a sign of a strong recovery by mainstream media. In fact it only signals that China has recovered its pre-pandemic growth trend.
Some unpleasant GDP growth arithmetics
On a Q-o-Q basis, GDP growth stands at 0.7 percent for Q1 2021 – or an annualized growth rate of 2.8 percent. Given the growth rates witnessed over Q2-Q4 2020, this translates into a carryover effect of 6.4 percent for annual GDP growth in 2021. In other words, even if growth stalls on a quarter-to-quarter basis from now on, the Chinese economy will still manage to growth by 6.4 percent in 2021, compared to 2020.
However, for the Chinese economy to completely erase the economic impact of the COVID-19 crisis by the end of this year, our calculations show that this would require the economy to grow by 10 percent in 2021. Taking into account the aforementioned carryover effect, this would require the economy to growth at annualized rates of respectively 8.7, 8.7, 8.2 over the Q2-Q4 2021 period. This is a far cry from the 6 percent minimum growth stated in the Government work programme for 2021, which is by all means already guaranteed as could be inferred from the above mentioned carryover effect.
Stimulus, what stimulus?
After this little appetiser, let us examine what the Chinese authorities did in 2020 before tackling the outlook for 2021.
What kind of stimulus did the Chinese authorities implement in 2020? If any, did this stimulus have any impact on economic activity? Or did the Chinese economy rebound mechanically following the end of the removal of the pandemic related lockdowns and other restrictive measures that weighed on both supply and demand? What about the debate between growth and financial stability? Was shadow banking involved in the stimulus?
Following the outburst of the Covid-19 pandemic the Chinese authorities refrained from a massive monetary stimulus, learning from the lessons of 2009 and correctly interpreting the Covid-19 recession as an outlier, much like a large-scale disaster than like a classic economic recession – or even a not so classic one (cf. the Great Recession).
Data from the BIS regarding banking and non bank credit to the private sector give some hints about the magnitude of the monetary stimulus. The BIS provide data on both Bank and Non Bank credit to domestic borrowers. The Non Bank metric is a reasonably good proxy for the “shadow banking” sector.
The Chinese authorities borrowed to lend to regional and local governments as a way to keep money flowing to the infra-national level while keeping the lid on bank credit growth, and more importantly on non banking “shadow” credit growth. Credit to the private sector did rise in 2020 but from a low baseline. In fact, more than anything else, the sharp rise observed in the credit-to-GDP ratio in 2020 illustrates the concomitant slump in GDP growth due to the pandemic.
The Loan Prime rate has been lowered in 2020 but much less than in 2008.
The credit channel of monetary policy
We performed an econometric analysis on the 2002-2021 period (with quarterly frequency) using a Bayesian hierarchical VAR with four quarterly lags in order to uncover the relationships between Loans growth and China’s main monetary gauges: the 3 Months Interbank Interest Rate (SHIBOR), the 12 months Loan Prime Rate (LPR) and the the Cash Reserve Ratio for the largest banks.
Our results show that a variation in the Loan Prime Rate and the Interbank Rate both have a permanent effect on Loans Growth. A unit standard deviation shock on the LPR (~ 0.9 percentage point) produces a 2 percent permanent decrease in Loans growth. The model accounts for a large variation of yearly (Q/Q-4) outstanding loans growth, as can be seen from the Residuals plot. Indeed, the Root Mean Square Error of the fitted versus actual variable is 1.55 percent over the 2003-2021 period. This compares with a median yearly growth rate of 14.5 percent for outstanding bank loans over the same period.
Using the same econometric methodology (i.e. Bayesian hierarchical VAR) this time with 8 lags (i.e. on the 2004-2021 period), we analyse the impact of Outstanding Loans growth on our quarterly averaged Monthly Composite Output factor for the Chinese economy and on the yearly (Q/Q-4) GDP growth rate (the Composite Output Factor is correlated at around 80 percent with the GDP growth rate), we find out that – as expected – a positive shock of one standard deviation (+4.5 percentage points) to yearly loans growth induces a positive reaction of the Output factor and subsequently on GDP growth (+0.5 percent after 5 quarters). The response is significant from a statistical perspective but it is very muted considering China’s mean yearly GDP growth rate of 8.8 percent over the period. The main conclusion here is that the variation of loans growth has to be significant, as in 2009 to influence GDP growth. Otherwise the authorities have to – and do – use other tools to macro-manage growth expectations and growth outcomes. By all accounts, this is now increasingly achieved through fiscal subsidies trickling down from the central government to the provincial/local governments and no more – or less so – through credit control.