Since the start of the bull market in early
2015, the magnitude of average price rises of the 70-city basket in China has
reached 30%; the trend accelerated further in early 2016 (eg. Shenzhen prices
were up 16% in Q1 alone), triggering a wave of government crack down policies
in Q4 2016 in an attempt to rein in the run-away prices. To date, over 20
cities have launched their versions of policies, but the impressive performance
of the domestic property stocks in recent months could herald further home
price increases ahead. This article attempts to look into the nature of the
official statistics that stand behind these incredible price increases.
Official
statistics suggest further price rises ahead
Many market commentators and analysts
follow the property market in China by tracking the ‘Price Indices of
Second-Hand Residential Buildings in 70 Large and Medium-Sized Cities’ published
by the National Bureau of Statistics (NBS) – we will refer to this below as the
official indices.
Under normal circumstances, the property
market should be close to, or at a peak when the bulk of the basket cities are showing
price rises (green bars in Chart 1).
To illustrate, when the green bars begin to grow from the bottom (e.g. in April
2012 and April 2015), home prices usually rise, as proxied by Guangzhou (red
line); on the other hand, when the green bars begin to shrink from high levels,
a down-trend in property prices should also ensue (as shown in July 2011 and
April 2014).
Chart 1: Official
data suggest that the bull market has more to run
If one applies
this relationship to the above chart, one may reach the conclusion that the
current bull market in prices will continue because the green bars are still
some distance from reaching the peak yet. However, the reality is not quite as
straightforward as the above simple relationship suggests.
Is it the market or market statistics that local governments
are trying to manage?
While gathering
data for analysis, this writer has noticed a curious pattern – that whenever there
is a meangingful surge in home prices, the official indices tend to lag
comparable non-official ones; as shown in Chart
2, from a common starting point of 100, when steep rises in the
non-official indices (red arrows) take place, the official equivalents (blue
arrows) often underperform, with the blue line either remaining flat or even falling.
It seems there is a mismatch between the official indicators and reality. In a
short period of under eight years, the non-official index is now some 69%
higher than the official index.
Chart 2: Official
index always lagged behind in bull markets
Chart
3 provides another perspective on this
discrepancy. Rebounds in home prices during bull markets (i.e. when the red
line rises, represented by the upward sloping red arrows, e.g. from mid-2012 to
mid-2013) have been accompanied by big outperformances in non-official indices vs
their official equivalents (represented by rising non-red lines, which are collectively
annotated by the upward blue arrows). Furthermore, this deviation happens in
all the cities, and magnitudes of outperformance are not reverted during the
downcycles (e.g. between late 2013 and early 2015), suggesting that the issue is
not limited to isolated cases, but is a systematic aberration.
Chart 3: Non-official
price index rises tend to outpace official ones
Another intriguing observation is that how
far official indices deviate from non-official indices depends on how far that
city is away from the capital: while the official index of Beijing (light blue
line in Chart 3), which is right
under the nose of the central government, did not drift too far away from the
non-official indices in the past few years, that of Tianjin (dark blue line in Chart 3), which is a bit more ‘out of
sight’, was able to lag non-official readings by over 100%!
Chart
4 clearly shows the local governments’
practice of understating the substantial rises in home prices in order to avoid
drawing attention or policy crackdowns from the central government.
Chart 4: The
bigger the price increase (x-axis), the bigger the gap against non-official
indices (y-axis)
This is understandable behaviour given the
civil service performance system in China – officials’ future prospects are
tied closely to the rate of GDP growth in their sphere of influence, providing
great incentive for them to maximise their reported economic output. At the end
of the day, gross capital formation has been major component of GDP
calculations, making up 40%-50% of GDP growth (Chart 5), and in turn the housing sector with its related
industries are a significant driver of capital formation. It is no wonder that local
officials are tempted to grow their own housing investments as fast as possible
while under-reporting this fact, because their political careers are heavily
dependent on the continued boom of this sector.
Chart 5: Significant
contribution of Capital Formation induces data manipulation
Once the drivers of behaviours are
revealed, it is not hard to understand why the gentle rises in official indices
are so inconsistent with both non-official figures, and even more at odds with
news reports of soaring home prices. Tampering with official statistics may be
the easiest way for local officials to produce flashy GDP
figures while avoiding being accused of stoking housing bubbles!
Non-official
data suggest home prices may have peaked
Given the lower reliability of the
official statistics, it is perhaps more appropriate to deduce (using
non-official data) the ratio of basket cities experiencing inflating home
prices discussed in Chart 1. This
exercise results in a picture from which one would draw an opposite conclusion on
the state of the market: by as early as Q2 2016, the home prices in all of the basket
cities could have already been rising. In other words, the green bars have rocketed
to 100% (Chart 6) well before
indicated in Chart 1, and at speeds
far more rapid than the up-cycles in 2010-11 and 2013-14!
Chart 6: Non-official data suggest that home prices may have already peaked
As the green bars have already reached the
top for over a year, the author fears that the housing market may soon correct,
if it has not already started to do so. It is regrettable that the unreliability
of official data makes it hard to diagnose the symptoms, and yet another
opportunity to deflate the housing bubbles could have been missed.
To conclude, the above analysis serves as a
good example to support reports that official statistics in the mainland lack
robustness, and in this case, confidence in housing data may be further undermined
as well. In terms of investments, readers might want to consider selling
physical properties in the mainland; however, exposure to housing can be
maintained by putting the proceeds in mainland property stocks, some of which
still trade at reasonable valuations and have growth factors besides just the
residential sub-segment.
With special thanks to Eugene Lai and Stewart Ng for their contribution to this
article.
