This explains it all. However, I noticed that they didn't revise
Pakistan's GDP/PPP downwards as well. I'm sure that if they did,
Pakistan would be (on paper) 40% poorer.
http://www.rediff.com/money/2008/jan/15guest.htm
Fact check, reality check? New GDP data
Arvind Subramanian | BS | January 15, 2008 | 08:42 IST
The World Bank's statisticians have changed the economic facts. Under
these cir***stances, Keynes, the economist, would have us change our
opinions, while the great scientist, Einstein, would have us tamper
with the facts especially if they clash with our theoretical priors.
Which should it be? A little bit of both, it seems.
The key to constructing internationally comparable GDP data is
purchasing power parity=EF=BF=BDexchange rates, which are different from
market exchange rates. For example, in 2005, the market exchange rate
of a dollar was 44 rupees. But 44 rupees bought more of a typical
basket of goods and services in India than a dollar did in the United
States because a lot of nontraded goods such as haircuts, education
and health, which make up this basket, were cheaper in India than in
the US.
PPP exchange rates are the metric that tells us how many rupees (the
new answer is 14.7) have the same command over goods and services in
India that a dollar does in the US.
Since the 1970s, the Penn World Tables=EF=BF=BDproduced several editions
of
cross-country data on PPP exchange rates and PPP-adjusted GDP, each
based on detailed prices that were obtained periodically and most
recently in 1993. For the years beyond 1993, the PWT and the World
Bank continued producing GDP numbers, which can best be described as
intelligent "guesstimates."
These guesstimates used the 1993 numbers as the base and extrapolated
beyond using price data from the national income accounts for each
country. For several countries, including China and the oil ex****ters,
which never provided the detailed price data, there was not even a
base year with firm data from which to extrapolate. The latest numbers
produced by the Bank are therefore superior by construction because
they replace the old guesstimates with actual data.=EF=BF=BD
Unsurprisingly, the old numbers have been substantially revised. For
example, in about 40 per cent of cases, GDP per capita has been
revised upwards or downwards by more than 20 per cent. For China and
India, the downward revision was about 40 per cent. Many oil
ex****ters=EF=BF=BD-- Saudi Arabia (28 per cent) and Iran (34 per
cent)=EF=BF=
=BD-- saw
significant upward revisions. Understanding these revisions is
critical to acquiring trust in them.
One way of *****sing the new data would be to check for patterns in
the revisions. It turns out that, on average, the magnitude of the
revisions to the data was much smaller for countries that participated
in the 1993 exercise than for countries that never provided detailed
price data (see table). For example, the mean percentage revision
(treating positive and negative revisions alike) in the GDP per capita
for the latter group was about 34 per cent compared with 14 per cent
for the former group (the difference remains substantial even after
excluding rich countries, and is larger for PPP revisions).
The variability in the revisions (or standard deviation) was also
greater for the latter group, especially for revisions to the PPP
exchange rates. Thus, the revisions are not random but reassuringly
consistent with what we might expect: the more dated the previous
data, the greater and more variable the subsequent revisions.
That said, a number of specific revisions raise questions to which the
Bank will have to provide answers.=EF=BF=BD
Poverty: The reductions in GDP per capita imply a large increase in
measured poverty, especially in China and India. Is this a problem?
Yes, the new numbers are going to be awkward for the Bank because
China and India cannot suddenly have hundreds of millions more poor
people because new data have been produced. We are not quite in a
Heisenberg quantum world where measurement affects underlying
realities.
But the problem is less big than it appears. First, it should be
emphasised that the new revisions change poverty rates according to
the international one-dollar-a-day standard. But most researchers and
policy-makers place far more faith in nationally determined poverty
benchmarks and estimates. India's poverty rate will always be
determined by the NSS surveys (fraught and contentious though even
they are) not by international measurements.
The international standard was created to facilitate cross-country
comparisons. But it was always recognised that setting this standard
was hazardous because of the difficulties in comparing poverty across
borders and time. The new revisions have merely served to expose these
difficulties, and it is going to be very interesting to see how the
Bank extricates itself out of this problem.
China: Perhaps a better basis for judging, and being wary about, the
new China numbers relate to their implications for the Chinese
exchange rate. The new data suggest that renminbi undervaluation is
about 16 per cent, which is not only substantially lower than most
analysts' estimates (of about 30-40 per cent) but also implausibly
lower than the estimates for other countries, including India's
(undervaluation of about 26 per cent). The price estimates for China
were based on urban data, leaving open the possibility that
including=EF=BF=
=BD
rural prices will yield more plausible numbers for the magnitude of
undervaluation.
Singa****e: It is surprising why data for this country, which has
presumably one of the better statistical systems, should be amongst
those with the greatest revisions (plus 40 per cent).
India:=EF=BF=BDWhile China's large revision might be understandable
because
the old data were particularly shaky, why did the Indian numbers
change? Recall that the old estimates for 2005 were really
extrapolations. For those 115 countries (including Singa****e) that
provided detailed price data in 1993, these extrapolations were for 12
years. But India last participated in 1985, so the extrapolation was
for 20 years.
Indian numbers, therefore, saw greater revisions in part because
India's data were older than for other countries. It is possible that
the Indian economy has seen so much change since 1985 that
extrapolations for twenty years failed to reflect these changes.
The broader policy question that India and the world community should
be asking is why nearly 15 years had to elapse before GDP data were
updated. Had the Bank devoted more time, effort, and financial
resources to doing more such exercises in the past, there would be
fewer surprises today.
The World Bank has just replenished its coffers by about $40 billion
to keep concessional finance flowing to poor countries. Nancy
Birdsall, President of the Center for Global Development and I have
argued that a large share of the Bank's resources=EF=BF=BD-- substantially
larger than currently foreseen=EF=BF=BD-- should be channelled to
activities=
that produce global public goods. A great example of such goods is
knowledge produced by the Bank, including the knowledge embodied in
the new GDP data generated by the Bank's statisticians.=EF=BF=BD Like the
efforts of the PWT in the past, this knowledge has transformed and
enriched our understanding of the poorer parts of the world.
We should therefore raise a toast to these humble folk, the bean
counters, who beaver away at such un***y but invaluable tasks. But as
we do so, we should not shy away from asking this question: can the
loanwallahs at the World Bank (and elsewhere) make comparable claims
of adding value to the world.
Senior Fellow, Peterson Institute for International Economics and
Center for Global Development, and Senior Research Professor Johns
Hopkins University.
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