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

Producer Price Index Manual
reference period instead of 10 percent in the current
period because it might have been introduced
at a discount at that point in its life cycle to encourage
usage. Continuing to use the coefficients
from some far-off period to make price adjustments
in the current period is similar to using outof-date
base period weights. The comparison may
be well defined but have little meaning. If price adjustments
for quality differences are being made to
the old item in the price reference period using hedonic
estimates from that period, then there is a
need to update the estimates if they are considered
out-of-date, for example, due to changing tastes or
technology, and splice the new estimated comparisons
onto the old. Therefore, regular updating of
hedonic estimates when using the adjustments to
the old price is recommended, especially when
there is evidence of parameter instability over
time.
7.148 Third, the sample of prices and characteristics
used for the hedonic adjustments should be
suitable for the purpose. If they are taken from a
particular industry, trade source, or web page and
then used to adjust noncomparable prices for products
sold by quite different industries, then there
must at least be an intuition that the marginal returns
for characteristics are similar among the industries.
A similar principle applies for the brands
of products used in the sample for the hedonic regression.
It should be kept in mind that high
2
R statistics do not alone ensure reliable results.
Such high values arise from regressions in periods
before to their application and inform us of the
proportion of variation in prices across many
products and brands. They are not in themselves a
measure of the prediction error for a particular
product, sold by a specific establishment of a given
brand in a subsequent period, although they can be
an important constituent of this.
7.149 Fourth, there is the issue of functional
form and the choice of variables to include in the
model. Simple functional forms generally work
well. These include linear, semi-logarithmic (logarithm
of the left-hand side) and double log (logarithms
of both sides) forms. Such issues are discussed
in Chapter 21, Appendix 21. The specification
of a model should include all pricedetermining
characteristics. Some authors advise
quite simple forms with only the minimum number
of variables, as long as the predictive capacity is
high (Koskimäki and Vartia, 2001). For the CPI,
Shepler (2000) included 33 variables in her hedonic
regressions of refrigerators, a fairly homogenous
product. These included 9 dummy variables
for brand, 4 dummy variables for color, 5
types of outlets, 3 regions as control variables and
11 characteristics. These characteristics included
capacity, type of ice-maker, energy-saving control,
number of extra drawers, sound insulation, humidifier,
and filtration device. Typically, a study would
start with a larger number of explanatory variables
and a general econometric model of the relationship;
the final model is a more specific, parsimonious
one since it has dropped a number of variables.
The dropping of variables occurs after experimenting
with different formulations and seeing their effects
on diagnostic test statistics, including the
overall fit of the model and the accordance of signs
and magnitudes of coefficients with prior expectations.
Reese (2000), for example, started with a
hedonic regression for U.S. college textbooks. It
included about 50 explanatory variables; subsequently,
those variables were reduced to 14 with
little loss of explanatory power.
7.150 Finally, Bascher and Lacroix (1999) list
several requirements for successful design and use
of hedonic quality adjustment in the CPI, noting
that these requirements require heavy investments
over a long period. They involve: (i) intellectual
competencies and sufficient time to develop and
reestimate the model and to employ it when products
are replaced; (ii) access to detailed, reliable
information on product characteristics; and (iii) a
suitable organization of the infrastructure for collecting,
checking, and processing information.
7.151 It should be noted that hedonic methods
may also improve quality adjustment in the PPI by
indicating which product attributes do not appear
to have material impacts on price. That is, if a replacement
product differs from the old product
only in characteristics that have been rejected as
price-determining variables in a hedonic study, this
would support a decision to treat the products as
comparable or equivalent and include the entire
price difference (if any) as pure price change. Care
has to be exercised in such analysis because a feature
of multicollinearity in regression estimates is
that the imprecision of the parameter estimates
may give rise to statistical tests that do not reject
null hypotheses that are false, that is, they do not
find significant parameter estimates. However, the
results from such regressions can nonetheless pro-
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