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Monthly GDP tracker helps to better understand cyclical
economic developments in China
GDP tracker reinforce usefulness of monthly Caixin Composite
PMI data
Prior to the global pandemic, China's GDP growth figures
exhibited a noticeable degree of stability, with underlying growth
tending to ease in a gentle and broadly predictable pattern over
the decade leading up to the start of 2020.
In contrast, higher frequency indicators - such as the Caixin
China Composite PMI (compiled by IHS Markit) and, for that matter,
many official data statistics - have described more typical
cyclical changes in economic activity, for example indicating
slowdowns in growth in 2015 and 2018.
With little cyclicality apparent in the official headline GDP
growth statistics, in response - and as a means of providing
timelier and higher frequency estimates of changes in GDP - there
is a growing literature on alternative ways to track economic
performance in China. Two such approaches have been undertaken by
the
San Francisco Federal Reserve Bank and the New York Federal Reserve
Bank.
In this short note we closely follow the spirit of this recent
work and construct our own benchmark indicator to track Chinese
economic growth. Taking the common component from 12 high frequency
indicators that all provide insight on Chinese economic
developments, we create a useful benchmark to corroborate not just
our own PMI survey data, but to better understand on a monthly
basis cyclical trends in official Chinese data.
An alternative GDP growth indicator
There has been a notable development during recent years in the
scope and range of economic indicators available for China. From
these available data sources, we pick 12 that appear particularly
useful in tracking economic activity. These include indicators of
electricity production, industrial production, household
consumption, freight traffic, trade and investment*. Note that the
PMI survey data have been excluded as one of the intentions is to
compare the performance of the new indicator against our own PMI,
and to thereby create an time series against which PMI data can be
more accurately benchmarked than GDP.
To create our high frequency alternative indicator of Chinese
economic activity, we first need to disentangle the two principal
forces that act on growth: longer-term structural trend changes and
shorter-term cyclical developments.
This reflects the observation that China has grown and developed
at a startling pace over the past 30 years or so but, as the
economy undergoes a transition from being driven by high and rapid
increases in capital investment to being primarily driven by
consumption, growth rates have trended gently downwards. Indeed,
double digit annual growth rates seen in the early 2000s have now
given way - prior to the current COVID-19 pandemic - to gains
typically in the region of 6-7%. However, this long-term trend can
mask shorter-term changes in the business cycle, which tend to
dominate our interest when understanding near-term economic
developments.
We therefore first focus on extracting the cyclical component
from our individual data series, by effectively removing the
long-term trend in the data. We do this by transforming our
individual data series into year-on-year growth rates (except
consumer confidence, which we use annual level differences), before
a process of detrending via a five-year centred moving average
filter.
We then normalise all data series such that each series shows a
broadly similar magnitude of volatility, and then finally derive an
initial indicator of economic activity by extracting the common
cyclical component from our 12-time series. This is achieved
through the technique of principal component analysis.
*The full list of indicators relates to exports, industrial
production, electricity production, retail sales, fixed asset
investment, real estate investment, consumer confidence, civil
aviation passenger numbers, rail passenger numbers, freight traffic
volume, auto sales and floor space under construction.
Monthly GDP growth
To translate our derived monthly indicator into comparable
annual GDP growth rates we have also constructed a 'pseudo' monthly
GDP series from the official quarterly GDP data. Using
interpolation techniques to estimate a monthly time-series from the
quarterly GDP figures, this series is also detrended and the
cyclical component extracted.
Linking this series to the first principal component of our high
frequency indicators through linear regression provides us a new
series of year-on-year growth estimates based on the set of
alternative indicators. The results are charted below.
Finally, we can re-establish the linkage with the official
quarterly GDP data by adding back in the long-term trend component
to the GDP tracker. This is highlighted in the chart below.
From the two preceding charts we can see that China has indeed
likely experienced some cyclicality in GDP growth relative to that
indicated by the official GDP series. For instance, slower gains in
economic output were seen during 2015, before a growth upturn
occurred in 2016/2017. A further slowdown was again seen in 2018.
These cycles broadly correspond with those signalled by the monthly
PMI data (see chart below).
Whilst not directly comparable with each other - PMIs tend to
measure underlying changes in activity as opposed to the
year-on-year growth rates indicated by the GDP tracker, which is
why the PMI figures sometimes have a noticeable lead - the positive
relationship between the cyclical component of GDP and the Caixin
Composite PMI reinforces the usefulness of the business survey data
in understanding short-term economic developments.
October data
The latest mass release of official data confirms that the
Chinese economy continued its recovery during October, led by gains
in industrial production, retail and investment.
Taking the latest signal from the monthly data shows that the
economy was growing at a year-on-year rate of just below 5.0%
during October, signalling a positive start to the fourth quarter
of 2020 - albeit one below pre-pandemic trends as the recovery in
consumption continued to lag that seen in industry.
Recent PMI data have shown that growth, following a strong
recovery from the aftermath of the lockdowns related to COVID-19
earlier in the year, has recently steadied - albeit at elevated
levels which were last seen during 2011.
Expect official GDP growth to continue its recent trajectory
into year-end before settling around a rate broadly equivalent to
those seen before the pandemic.
Purchasing Managers' Index™ (PMI™) data are compiled by IHS Markit for more than 40 economies worldwide. The monthly data are derived from surveys of senior executives at private sector companies, and are available only via subscription. The PMI dataset features a headline number, which indicates the overall health of an economy, and sub-indices, which provide insights into other key economic drivers such as GDP, inflation, exports, capacity utilization, employment and inventories. The PMI data are used by financial and corporate professionals to better understand where economies and markets are headed, and to uncover opportunities.
