Indian media — as well as several official
representatives of the government — are full of excitement at the
possibility that in the coming year India’s rate of growth of economic
activity might actually be higher than that of China.
It
is not just that the extremely rapid growth of the giant Asian
neighbour is slowing down substantially, but also that India’s GDP
growth is projected to be higher than before, and the Central
Statistical Organisation’s latest revisions to the GDP estimates suggest
that the recent deceleration was less sharp than generally perceived.
But
as it happens, over the past two decades the differential performance
of the two economies has been such that — even with the recent slowdown —
China is still likely to account for a larger contribution to global
GDP growth than India for some time to come, simply because of its much
greater size.
Chart 1 describes the share of China and India in global GDP (according to World Bank estimates).
China’s great leap
This
shows that until the late 1970s, the Indian economy was actually larger
in size and accounted for a slightly bigger share of world GDP
(although it must be borne in mind that Chinese data for that period are
notoriously unreliable). It was only in 1979 — just after the
agricultural reform in China that unleashed the productive forces of the
peasantry in the context of a relatively egalitarian countryside — that
China overtook India in terms of global income share.
Thereafter,
and particularly in the 2000s, the gap grew by leaps and bounds, to the
point that in 2013 the size of the Chinese economy was around 3.3 times
that of the Indian economy when measured in terms of US dollars at 2005
prices.
This means that, if India is even to equal
the output contribution of China in the coming year, its growth rate
must exceed three times the growth rate of the Chinese economy. The
difference in GDP growth is also obviously reflected in differences in
per capita GDP.
Taken once again in terms of 2005 dollar prices, per capita GDP in China was only around half that of India in 1960.
China
exceeded India in per capita GDP only in 1985, but thereafter the
divergence was dramatic, because of the combination of faster aggregate
output growth and lower population growth in China compared to India.
Per head performance
In 2013, Chinese per capita GDP was more than three times that of India.
These
estimates consider GDP as estimated in terms of nominal exchange rates,
in constant US$ prices for 2005. This is one way of considering the
relative size of the two economies.
But a more
popular way of comparing per capita GDP is the use of deflators based
not on nominal exchange rates but on purchasing power parity (PPP)
exchange rates that seek to establish the relative purchasing power of
each currency in terms of prices of a common basket of commodities.
This
has become the preferred way of comparing cross-country incomes and
even poverty within countries, in much of the international discussion.
However, the use of PPP exchange rates can be quite dubious, as they are
based on prices of a basket of average representative consumption goods
in the US, which may not be so relevant to consumption elsewhere,
especially the poor in much of the developing world.
They
are unchanging over time, even though consumption patterns tend to
shift with technological change and evolving preferences.
PPP
exchange rates are also notoriously imperfect because of the
infrequency and unsystematic nature of the price surveys that are used
to derive them, which can make them quite dated or even misleading.
There is a less talked about but possibly even more significant conceptual problem with using PPP estimates.
In
general, countries that have high PPP, that is where the actual
purchasing power of the currency is deemed to be much higher than the
nominal value, are typically low-income countries with low average
wages.
It is precisely because there is a
significant section of the workforce that receives very low
remuneration, that goods and services are available more cheaply than in
countries where the majority of workers receive higher wages.
Therefore,
using PPP-modified GDP data may miss the point, by seeing as an
advantage the very feature that reflects greater poverty of the majority
of wage earners in an economy.
There is another
concern: that the use of PPP estimates may also be misleading because in
effect the World Bank tends to use a simple multiple to derive the data
across a long period of years, on the basis of a price survey for a
particular year, without considering the significant volatility in
prices that may affect genuine purchasing power.
This
is particularly the case with respect to China and India, two countries
for which the PPP data have fluctuated wildly over time depending upon
the changing nature of price surveys and other factors.
The
most recent revision of the PPP index has increased the income
estimates for both countries. Charts 2 and 3 show the estimates of per
capita income in US dollar terms for China and India in PPP (based on
2011 surveys) and nominal (based on 2005 prices) exchange rates.
Price concerns
It
appears that the gap between nominal and PPP per capita income has been
widening, but that is really an optical illusion: in fact, the World
Bank in its latest estimates based on price surveys for 2011 has simply
used the multiplicands of 3.22 for China and 4.5 for India to derive the
PPP estimates for all the previous and subsequent years!
This
explains why the per capita income estimates in PPP terms appear to
move broadly in consonance with the per capita GDP of either country
relative to the world average (with the differences mainly due to the
change in the denominator).
This tendency would
otherwise be hard to explain in economic terms, but not so hard to
explain if it is simply the result of a statistical artefact!
This tendency would otherwise be hard to explain in
economic terms, but not so hard to explain if it is simply the result of
a statistical artefact!
Source : http://www.thehindubusinessline.com/opinion/columns/c-p-chandrasekhar/theres-no-comparison-statistically-speaking/article7049744.ece
(This article was published on March 30, 2015)
