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

22. Treatment of Seasonal Products
products. 58 Many users will be interested in
these indices; moreover, these indices are the
building blocks for annual indices and for rolling-year
indices. As a result, statistical agencies
should compute these indices. They can
be labeled analytic series in order to prevent
user confusion with the primary month-tomonth
PPI;
• Rolling-year indices should also be made
available as analytic series. These indices will
give the most reliable indicator of annual inflation
at a monthly frequency. This type of index
can be regarded as a seasonally adjusted PPI.
It is the most natural index to use as a central
bank inflation target. It has the disadvantage of
measuring year-over-year inflation with a lag
of six months; thus, it cannot be used as a
short-run indicator of month-to-month inflation.
However, the techniques suggested in
Sections F and K could be used so that timely
forecasts of these rolling-year indices can be
made using current price information;
• Annual basket indices can also be successfully
used in the context of seasonal commodities.
However, many users of the PPI will want to
use seasonally adjusted versions of these annual
basket-type indices. The seasonal adjustment
can be done using the index number
methods explained in section K or traditional
statistical agency seasonal adjustment procedures;
59
58 There can be problems with the year-over-year indices
if shifting holidays or abnormal weather changes normal
seasonal patterns. In general, choosing a longer time period
will mitigate these types of problems; that is, quarterly seasonal
patterns will be more stable than monthly patterns,
which in turn will be more stable than weekly patterns.
59 However, there is a problem with using traditional X-
11-type seasonal adjustment procedures for adjusting the
PPI because final seasonal adjustment factors are generally
not available until an additional two or three years’ data
have been collected. If the PPI cannot be revised, this may
preclude using X-11-type seasonal adjustment procedures.
Note that the index number method of seasonal adjustment
explained in this chapter does not suffer from this problem.
It does, however, require the use of seasonal factors derived
from a single year of data, so that the year used should reflect
a normal seasonal pattern. If the seasonal patterns are
irregular, it may be necessary to use the average of two or
more years of past adjustment factors. If the seasonal patterns
are regular but slowly changing, then it may be preferable
to update the index number seasonal adjustment factors
on a regular basis.
• From an a priori point of view, when making a
price comparison between any two periods, the
Paasche and Laspeyres indices are of equal
importance. Under normal circumstances, the
spread between the Laspeyres and Paasche indices
will be reduced by using chained indices
rather than fixed-base indices. As a result,
when constructing year-over-year monthly or
annual indices, choose the chained Fisher index
(or the chained Törnqvist-Theil index,
which closely approximates the chained
Fisher) as the target index that a statistical
agency should aim to approximate. However,
when constructing month-to-month indices,
chained indices should always be compared to
their year-over-year counterparts to check for
chain drift. If substantial drift is found, the
chained month-to-month indices must be replaced
with fixed-base indices or seasonally
adjusted annual basket-type indices; 60
• If current period revenue shares are not all that
different from base year revenue shares, approximate
chained Fisher indices will normally
provide a close practical approximation
to the chained Fisher target indices. Approximate
Laspeyres, Paasche, and Fisher indices
use base period expenditure shares whenever
they occur in the index number formula in
place of current period (or lagged current period)
revenue shares. Approximate Laspeyres,
Paasche, and Fisher indices can be computed
by statistical agencies using their normal information
sets; and
• The geometric Laspeyres index is an alternative
to the approximate Fisher index that uses
the same information. It will normally be close
to the approximate Fisher index.
It is evident that more research needs to be done on
the problems associated with the index number
treatment of seasonal products. A consensus on
what is best practice in this area has not yet
formed.
60 Alternatively, some sort of multilateral index number
formula could be used; for example, see Caves, Christensen,
and Diewert (1982) or Feenstra and Shapiro (2003).
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