Producer Price Index Manual: Theory and Practice ... - METAC

Producer Price Index Manual
qvist indices are equally good alternatives. Indeed,
the Fisher may be preferred to the Walsh on axiomatic
grounds, given that the two indices will tend
to give almost identical results for comparisons between
successive time periods.
1.130 As already noted, for practical reasons the
PPI is often calculated as a time series of Laspeyres
indices based on some earlier period 0. In this case,
the published index between t – 1 and t may actually
be the monthly change version of the Laspeyres
index given in equation (1.4) above. Given that
some substitution effect is operative, which seems
extremely likely on both theoretic and empirical
grounds, it may be inferred, by reasoning along
lines explained in Chapter 15, that the monthlychange
Laspeyres index will tend to be less than the
Walsh index between t – 1 and t. If the PPI is intended
to measure producer inflation, therefore, the
monthly change Laspeyres could have a downward
bias, a bias that will tend to get worse as the current
period for the Laspeyres index moves further away
from the base period. This is the kind of conclusion
that emerges from the index theory presented in
Chapters 15 and 16. It is a conclusion with considerable
policy and financial implications. It also has
practical implications because it provides an argument
for rebasing and updating a Laspeyres index
as often as resources permit, perhaps on an annual
basis as many countries are now doing.
1.131 If the objective of the PPI is to measure the
current rate of change in revenues for a fixed, given
technology and set of inputs, to be used for output
deflation, this translates into asking what is the best
estimate of the change in producer output prices.
The theory elaborated in Chapter 17 shows that the
best estimate will be provided by a superlative index.
The three commonly used superlative indices
are Fisher, Törnqvist, and Walsh. One or the other
of these indices emerges as the theoretically most
appropriate formula, whether the objective is to
measure the current rate of factory gate inflation or
as a deflator. A monthly-change Laspeyres is likely
to have the same bias whatever the objective.
1.132 If the objective were to measure price
changes over long periods of time—say, 10 or 20
years—the main issue for long-term comparisons is
whether to chain or not, or at least how frequently
to link.
I. Elementary Price Indices
1.133 As explained in Chapters 9 and 20, the calculation
of a PPI typically proceeds in two or more
stages. In the first stage, elementary price indices
are estimated for the elementary aggregates of a
PPI. In the second stage, these elementary indices
are combined to obtain higher-level indices using
the elementary aggregate indices with revenue
weights. An elementary aggregate consists of the
revenue for a small and relatively homogeneous set
of products defined within the industrial classification
used in the PPI. Samples of prices are collected
within each elementary aggregate, so that elementary
aggregates serve as strata for sampling purposes.
1.134 Data on the revenues, or quantities, of the
different goods and services may not be available
within an elementary aggregate. Since it has been
shown that it is theoretically appropriate to use superlative
formulas, data on revenues should be collected
alongside those on prices whenever possible.
Given that this may not possible, that there are no
quantity or revenue weights, most of the index
number theory outlined in the previous sections is
not applicable. An elementary price index is a more
primitive concept that relies on price data only. It is
something calculated when there is no explicit or
implicit quantity or revenue data available for
weights. Implicit quantity or revenue data may arise
from a sampling design whereby the selection of
products is with probability proportionate to quantities
or sales revenue.
1.135 The question of what is the most appropriate
formula to use to estimate an elementary price
index is considered in Chapter 20. This topic was
comparatively neglected until a number of papers in
the 1990s provided much clearer insights into the
properties of elementary indices and their relative
strengths and weaknesses. Since the elementary indices
are the building blocks from which PPIs are
constructed, the quality of a PPI depends heavily on
them.
1.136 As explained in Chapter 6, compilers have
to select representative products within an elementary
aggregate and then collect a sample of prices
for each of the representative products, usually
from a sample of different establishments. The individual
products whose prices are actually collected
are described as the sampled products. Their
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