among possible alternatives in allowing for modi-
fications in existing specifications. When the PPI
resource cost methodology declined in usefulness
due to the lack of reliable estimates by the re-
porter, the regression adjustment estimates were
employed. If the regression model did not spec-
ify the specific characteristic that changed in the
product, we linked to show no change. This com-
posite methodology is best explained by a deci-
sion tree:
(A) When a substitute product is available:
(1) Apply producer cost data gathered
from the manufacturer:
If producer cost information is not
available, use the regression adjust-
ments for valuing the improvement
or deterioration in the product; and
If a quality valuation is unavail-
able from the two previous meth-
ods, apply the ppi link-to-show-
no-change procedure.

(2)

(3)

(B) When a substitute is not available, de-
fault to the cell-relative procedure.

The procedure described under (A)(3) was
used when manufacturers’ estimates were lacking
and the new substitute item had a characteristic
change not specified by the model. In these in-
stances, we applied the pp! link-to-show-no-
change procedure if cost adjustments were
missed, or we directly compared the prices be-
tween the two products if the change had no ef-
fect on resource costs.

The decision rule indicated in (B) applies to
products that have been dropped from produc-
tion, are no longer shipped, and have no substi-
tute. In prior years, the PPI program had two
procedures for estimating missing prices when
reporters were late or delinquent. One procedure
simply held the missing price unchanged from its
previously reported value, clearly entering a bias
of unknown direction, and was dropped from the
ppl. The other procedure used the remaining
prices of similar products as a proxy for move-
ment of the missing price. This procedure is re-
ferred to as the “default estimation method” or
“cell-relative method” and was implemented as
policy in January 1984. It was felt that the method
would have the “least negative impact on the
index” and that it should be used when the indus-
try analyst had no further information as to how
the price should move. For example, if there were
four products in a cell (the most detailed aggrega-
tion of published BLS indexes), and one product
was no longer manufactured and shipped, the re-
maining products in the cell would act as the
proxy for price movement of the missing product.

Other things being equal, the assumption is that
substitute products move similarly.

Experimental index sample design

During the pilot phase of the project, we needed
a sample of products that would provide a ro-
bust test of the various quality adjustment pro-
cedures under consideration. It was felt that the
competitive nature pervading the microcom-
puter market would result in frequent model
changes. This view was based on our expecta-
tion that high-performance systems would have
longer development cycles, compared to those
of “off-the-shelf” microcomputers, but would
then also have a longer market life to recoup their
greater development costs. Another rationale for
focusing on microcomputers during the pilot
phase was that larger computers have a much
lower sales volume, potentially making observed
transactions more difficult to price. However, for
the experimental phase, almost all types of com-
puters were included for measurement.

Attention should be focused on the reporting
unit that will ultimately provide the detailed in-
formation on products and prices used for calcu-
lating indexes. Ideally, the manufacturer selected
should have the records necessary to clarify any
questions conceming the products included for
index calculation. Under the normal sampling
strategy used in the PPI program, every potential
sampling unit must be given a chance of being
selected. To accomplish this objective, a sam-
pling frame must be established that identifies
every potential domestic manufacturer and pro-
vides a measure of size for selecting samples.
Because the pilot and experimental indexes were
test cases, it was decided that only part of the PPI
sampling strategy would be followed, thereby
saving time and resources in the research. Nor-
mally, sample weights are developed by deter-
mining a unit’s probability of being selected and a
measure of its size (revenue). The measure of
size we used was the selected company’s
value of shipments for the most recent fiscal
or calendar year. The unit's probability of
being selected, as such, was not used,
because our original sample was judgmental
in this regard. We therefore asked for four
quotes on products from all companies se-
lected that had revenues of less than $10 mil-
lion, six quotes from companies that had
revenues from $10 million to $100 million,
and eight quotes trom companies that had
revenues of more than $100 million, for the
latest time period. This distribution of quotes
determined the weights for the products
within the individual companies selected for

The computer

industry required
a better yardstick

to measure
improvements in
quality and
lower costs.

Monthly Labor Review October 1990

19



Experimental Computer Price Index

and quality adjustment procedures, as well as a
different overall treatment of the data. The project
went a long way toward dealing with these issues.
Normal operational procedures have been modi-
fied, namely, by dedicating resources for resam-
pling every 2 years, possibly by telephone. to
expedite product selection. A data base for cross-

Footnotes

sectional regression estimates must also be re-cre-
ated for the same time period. This task will be-
come easier as more data are entered into the
modeling data base, ensuring the availability of
timely, current data. All things considered, the
expanding computer industry is far too important
to be excluded from the PPI program. Oo

' For a more detailed explanation of the pilot indexes,
see Brian C. Catron, “Price Measurement for Computer
Hardware: A Demonstration of Quality Adjustment Tech-
niques” (Bureau of Labor Statistics, Division of Industrial
Prices and Price Indexes, Apr. 14, 1989, unpublished internal
document)

* John F. Early and James H. Sinclair, “Quality Adjust-
ment in the Producer Price Indexes,” in Murray Foss. ed.
The US. National Income and Product Accounts, vol. 47
(Washington, National Bureau of Economic Research,
1983), p. 109.

“Not all physical changes are treated as changes in
quality. If a component does not perform its function better,
it is not assumed to have undergone a change in quality An
example would be style changes in automobiles

* See “Guidelines for Adjustment of New Automobile
and Truck Prices for Changes in Quality of Product” (Bureau
of Labor Statistics. 1980. rev.. unpublished internal docu-
ment). This document describes and defines the concepts and
procedures used in adjusting quoted prices for quality
change.

* 1987 Current Industrial Reports, MA35RU87-1 (U.S
Department of Commerce, Bureau of the Census, August
1988), p. 2

° This company, located in Lexington, ma, provided a
computer tape that identified a large number of manufactur-
ers, prices, and products in the microcomputer industry that
were used for modeling.

" See Office of Management and Budget, Standard In-
dustrial Classification Manual, 1987 (Washington, U.S.
Government Printing Office), p. 215.

“Computers and Office and Accounting Machines,”
Current Industrial Reports, MA3SR(87)-1 (Bureau of the
Census, August 1987).

” Peter L. Burris, ed., The Grey Sheet, Computer Indus-
try Report, vol. 24, nos. 17=18 (International Data Corpora-
tion, 1989)

See chapter on “Producer Prices,” in sis Handbook of
Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988),
p. 126.

nts Handbook, p. 126.

' Excerpt from Producer Price Indexes, Data for July
1990 (Bureau of Labor Statistics, 1990), p. 199.

'* See “Industry Leaders Put Brakes on pc Discounting.”
re World, Mar 5, 1990, p. 1

A note on communications

The Monthly Labor Review welcomes communications that supplement,

challenge, or expand on research published in

pages. To be considered for

publication, communications should be factual and analytical, not polemical
in tone. Communications should be addressed to the Editor-in-Chief, Monthly
Labor Review, Bureau of Labor Statistics, U.S. Department of Labor, Wash-

ington, bc 20212

24 Monthly Labor Review October 1990

i
q
i
i



{October 1988 = 100]

Table 2. Experimental price indexes and percent changes for the computer industry

Unadjusted Index Unadjusted
Industry and product - To ~ Percent cnange,
Code Aprit1990 | July 1990 | ending July 1990

General-purpose digital computers 3671 80.4 79.5 12.4
16-bit wordsize computers .. | 8571-8 725 78 | 195
8000 and 80000 series microprocessor based 3571-Alt 72.2 70.6 19.7
Other 16-bit wordsize computers 3571-A12 976 94.4 66
32-bit wordsize computers 3871-8 877 ant | 17
80000 series microprocessor based 3571-B21 76.6 m4 | -18.2
68000 series microprocessor based | 3571-B22 87.5 87.5 | 76
Other 32-bit wordsize computers 3571-B23 94.8 94.7 AT
Greater than 32-bit wordsize computers, 3671-C 84.8 a5 | 66

tion into a pretest interview with a number of
manufacturers and asked them how they sold
their computers to customers. The predominant
form in which the computers were sold was as
a system. There were exceptions, however, es-
pecially as the computer approached the tradi-
tional mainframe configuration. In these cases,
we accepted the vernacular used by manufactur-
ers in describing a computer. Usually, this
meant that the computer consisted solely of a
processor with no storage or operating system,
items that were considered extras and purchased
separately. As a result of the manufacturers’ an-
swers to the key question posed during the inter-
view, the predominant form under which a
computer was sold for the purposes of our exper-
imental index included the processor. both main
and auxiliary memory, and other peripherals.
The validity of an index is inextricably con-
nected to the type of price the index is supposed
to measure. For the PPI program. the preferred
price is defined as “the net revenue accruing to a
specified producing establishment from a spec
fied kind of buyer for [a] specified product
shipped under specified transaction terms on a
specified day of the month.” Emphasis is placed
on the prices charged for items shipped in the
same month, rather than “orders” or “futures”
prices. Further, a distinction must be made be-
tween “listTM or “book” prices and net transaction
prices. The Bureau has always asked for net
transaction prices, because it is felt they are a
more realistic indication of what is really occur-
ring in the marketplace: “BLS emphasizes . . . the
need for reports of realistic transaction prices, in-
cluding all discounts, premiums, rebates, allow-
ances, etc., rather than fictitious list or book
prices. The use of list prices in the industrial price
program has been the exception, not the rule.”!!

More specifically, even before the transition to
the current industry-focused methodology of the
PPI, a BLS survey concluded that approximately
20 percent of the traditional commodity indexes
were based on list prices. Since that time (1978),
the percentage most probably has declined due to
more accurate reporting and a more concerted
effort by BLS data collectors to collect the price of
the net shipment.

We adhered strictly to the above methodology
during both the pilot and experimental phases of
our project. Not only did we request that all appli-
cable discounts be reported in each measurement
period, but we asked to whom the computer was
sold (that is, the type of buyer). Discounts took
many forms, including cash rebates and discounts
on cumulative volume, quantity, and trade. Nor-
mally in the PPI program, we would use a proba-
bility selection technique that would identify a
specific discount. Here, we asked for the
company’s normal price adjustments. In a small
number of instances during the pilot study, we
took more than one discount for the same product
to see whether price adjustments moved differ-
ently. It has been suggested that a net transaction
price is nothing more than a list price less a stand-
ard discount, implying that discounts move simi-
larly in both magnitude and direction. In the small
number of cases we investigated in the pilot
study, there were instances where various
counts exhibited different magnitudes and moved
in differem directions. Examples of this phenom-
enon were in the areas of “original equipment
manufacturer” (OEM), “value-added dealer”
(VAD), and “value-added reseller” (VAR).

Experimental computer price index

Table 2 is an excerpt from the July 1990 Pro-
ducer Price Indexes monthly detailed report.'?

Monthly Labor Review

October 1990 21



An issue that
plagued the
Project from its
inception: when
is a computer a
computer?

20 Monthly Labor Review

Experimental Computer Price Index

our experimental index. These weights are re-
ferred to as item weights and are given by:

ty = WU; x VOS;
where:

I; = tem weight for reporting unit i ;

Uj = Number of quotes attempted for
reporting unit i; and

Vos

Dollar amount of reporting unit's
shipments and receipts.

The sampling frame normally used for the PPI
program is the Unemployment Insurance (UI) file
that identifies domes stablishments that have
three or more employees by specific industry, ac-
cording to the Government’s Standard Industrial
Classification. The 1972 definition for computers
when we began this project was described by sic
3573, “Electronic Computing Equipment.” Un-
fortunately for our purposes, this 1972 ¢ ica
tion structure was all-encompassing in that not
only were computers included, but so were stor-
age devices, terminals, magnetic disks, and other
peripheral equipment. Consequently, we had to
refine the sampling frame to include only those
companies dedicated to the manufacture of com-
puters, as identified in the 1987 revised sic 3571,
“Electronic Computers.”

In addition to having the UI file combined
under the 1972 definition, it was not current
enough to select sampling units without augmen-
tation and updating. The time lag in the UI file is
approximately 2 years. Therefore, we felt that
because the computer industry is replete with
rapid exit and entry of firms, we would have to
use a more current sampling frame. A GML data
file was purchased that apparently had more cur-
rent information on “microcomputer” companies.
For companies that manufactured larger comput-
ers, we contracted with GML to provide company-
of characteristics for these

cts. We then
cross-verified the Ut file against the GML data and
stratified by domestic manufactures. This gave us
our target frame by which to select individual
companies.

The normal pp! sampling strategy selects units
by ascribing to them a probability proportional to
their size. The unit of measure for selecting sam-
ples included the number of employees in each
establishment, The larger the number of employ-
ees ina given firm, the greater was the probability
of selecting that firm. Because our research was a
test case, we decided to use judgment in the selec-
tion of companies for our sample. We knew that
by injecting judgment into the selection process,
we could not say how statistically representative
our sample was of the true population of com-

October 1990

puter companies. However, we attempted to gain
cooperation from as many companies as we could
among those already in our PPI program, as well
as those never previously contacted. We were
pleased to gain the cooperation of 33 computer
manufacturers for our experimental index.

The relative importance of the items selected
(and their price changes) to one another is highly
significant in determining an accurate price
index. Not only must weights be developed in the
sampling process that proportion items within
companies, but they must also be determined for
companies within cells. For example, in table 2,
“3571-B21—80000 series microprocessor based”
is considered a cell.

The cell weights are usually determined from
Census Bureau information for individual catego-
ties. These weight determinations are needed if
one wants to aggregate upward to a less detailed
published category. For example, in table 2, “sic
3571-General-purpose digital computers” is an
aggregate of everything under this category. Un-
fortunately, the Census of Manufactures break-
downs were of little help to us, because they only
identified digital, compact, and other computers.
Also, the publication Current Industrial Reports*
distinguished categories of computers by dollars,
again something that was not very useful to us.
As previously discussed, even though the dollar
categories listed were by definition mutually ex-
clusive, computers can cross these categories al-
most monthly because of price changes. Further,
identical central processing units sold with differ-
ent combinations of peripheral devices would be
classified into different categories. Once we de-
cided on the cell definitions we would publish,
we took the overall dollar weight for sic 3571 as
defined in the 1987 Current Industrial Reports
and apportioned this weight into our cell catego-
ties using a secondary source, namely, the Inter-
national Data Corporation.’ This company uses
classifications for the industry that are labeled pc,
midrange, and large computers.

Definitional and related issues

An ie that plagued the project from its in-
ception was, When is a computer a computer?
We asked this question of industry representa-
tives, trade associations, and Government agen-
cies. As anticipated, no uniform response was
forthcoming. Some suggested that the proper
level of aggregation would be “boards.” Others
felt that the “box” or processor was the appro-
priate measure. Still others suggested that the
“system” was the key measure because comput-
ers are sold such. (Systems may include a
processor, display, keyboard, some storage, and
an operating system.) We incorporated the ques-



In almost all instances, the regression adjust-
ment methodology was used for the first three
categories: storage capacity, main memory, and
clock speed (measured in megahertz for micro-
processor-based computers and in millions of
instructions per second (MIPS) for larger comput-
ers). Even though an attempt was made to acquire
the resource cost information from the respondent
for these functional changes, in more than 90 per-
cent of the cases observed such information was
not available for the first three categories of com-
ponents. This is, however, to be expected,
because the more sophisticated the item’s func-
tional change is, the more difficult it is to measure
with traditional cost estimates. In other nonper-
formance areas, producer cost information was
available on changes in such items as keyboards,
terminals, and warranties.

Of the 170 computer models from 33 com-
puter manufacturers that were originally tracked,
we lost 31 models (18 percent of our original
sample) and 6 manufacturers between October
1988 and July 1990. Overall, 144 different modi-
fications with associated quality adjustments
were made to items in the categories listed in
table 3 as of the July 1990 quarter. This relatively
high figure is a reflection of the many and fre-
quent improvements that occur in this rapidly
changing industry and indicates the time horizon
necessary for reselecting a new market basket of
products.

The regression model for each publication cat-
egory was able to specify the functional changes
for three performance categories—auxiliary stor-
age, main memory, and clock speed—and was
used predominantly in quality adjustment. In a
number of instances, the manufacturer could give
us an estimate of the packaged items, such as
terminals, keyboards, and operating software up-
grades, and we accepted these values for the
Tesource cost adjustment approach. The catego-
ries of number of users and ports were used more.
as a marketing tool and were usually very low-
cost, sometimes free, items. The flexibility of the
composite quality adjustment methodology al-
lowed us to use both implicit estimates of func-
tional changes from regressions and resource cost
estimates from the manufacturer for other
changes if available.

Does the index mirror the industry?

Caution should be exercised in drawing conclu-
sions from table 2, because the table reflects
only seven quarters worth of data and uses a
classification structure that is currently different
from Census Bureau categories. In classifying
computers, we attempted to avoid adjectives,
applications, and dollar categories. As men-

tioned earlier, we debated at considerable length
the question of how actually to publish the
many different types of products included in the
computer industry.

Competition among 16-bit and 32-bit word-
size computers with 8000, 80000, and 68000 se-
ries microprocessors has been fierce for a number
of years. Competition still appears to be the driv-
ing force behind the declining indexes. With
more powerful, faster chips in plentiful supply
and the next generation of chips on the horizon,
prices are expected to decline. Even the 3571-B23
category of “Other 32-bit wordsize computers,”
which encompasses the traditional midrange
computers, has shown a modest price decline
since October 1988. This category also includes
what some refer to as minicomputers and com-
petes with the high-end 32-bit workstation mar-
ket. Moreover, the category 3571~C, of “Greater
than 32-bit wordsize computers,” or what others
refer to as mainframe computers, has undergone a
marked decline in price from the base-period
price. In fact, all the declines we evidenced in our
experimental index seem to mirror trade press
reports. Whether this phenomenon will prevail in
the future remains to be seen. For example, recent
trade press reports suggest that manufacturers of
personal computers are implementing programs
to stabilize prices. As one source put it, “The days
of bargain-basement PC prices may be over as the
industry takes steps to end the price wars that
marked 1989.”"3 Of course, only time can sub-
stantiate that statement. However, based on the
limited evidence presented in table 2, competition
will still prevail.

Conclusion

From the outset, the goal of the experimental
project was to demonstrate a feasible and sup-
portable method for producing timely, ongoing,
and maintainable price indexes for computer in-
dustry products. The most dramatic finding from
the collection and repricing phase of the project
was that the time horizon for many of the products
included in this industry is extremely short relative
to that of other industries repriced in the PPI. As
previously mentioned, the normal resampling of
industries for the PPI ranges from 5 to 7 years,
depending on the complexity of the approximately
500 industries included in the index program. If
we used this same time period as a reference for
repricing for a major portion of the computer
industry, it would include approximately two-
and-one-half generations of computers, based
‘on our study results!

Obviously, then, measuring price changes in a
high-tech industry such as computers for the PPI
program requires different collection, repricing,

Monthly Labor Review October 1990 23

All the declines
we evidenced in
our index seemed
to mirror trade
press reports.



James Sinclair
and
Brian Catron

James Sinclair is a
supervisory economist in
the Division of Industrial
Prices and Price Indexes,
Office of Prices and Living
Conditions, Bureau of
Labor Statistics. Brian
Catron is a supervisory
‘economist in the Division
of Services Industry Prices
in the same office.

An experimental price index
for the computer industry

A pilot study begun in 1987 produced a new

price index for computer industry products;

chief among the study’ s findings was that resampling
would have to be done over a much shorter time period
than the 5 to 7 years now in force for industries
covered by the Bureau’ s existing Producer Price Index

ecently, the Bureau of Labor Statistics’
Revs periodical, Producer Price In-

dexes, began publication of experimental
price indexes for the computer industry. Publica-
tion of this material was an outgrowth of a pilot
study initiated in 1987. The goal of the study was
to test a number of different quality adjustment
methodologies for developing constant-quality
Price indexes for the computer industry in an
operational environment. More specifically, the
project sought to measure the cost improvements
embodied in computers and computer peripheral
equipment and to develop a methodology for
excluding the cost of the improvements from
reported prices.

Price indexes should measure only pure price
changes and not include the cost of any embodied
technological changes. The normal Producer Price
Index (PPI) quality adjustment methodology, by it-
self, was not flexible enough to measure quality
improvements in an industry with steadily declining
prices. Thus, a new approach was required.

Once the results of the pilot study were evalu-
ated and incorporated into an operational method-
ology, calculation of comprehensive computer
product indexes could begin. This permitted the
publication of the experimental index, with its
base period beginning in October 1988, in the
August issue of Producer Price Indexes. This ar-
ticle presents an overview of the experimental
computer price index.' After discussing how
quality adjustment is measured in the PPI pro-

16 Monthly Labor Review October 1990

gram, the article focuses on the level of detail
selected for publication purposes, sampling and
weighting issues, and the quality adjustment
methodology that was ultimately selected. Fi-
nally, the current status of the experimental index
is examined, together with some economic and
statistical issues surrounding it.

Measurement of PPI quality adjustment

Theoretically, Laspeyres (fixed-input/output)
price indexes measure pure price changes for a
fixed production mix. In reality, however, many
products seldom remain the same over time.
Products are always being discontinued, modi-
fied, or replaced. The challenge of calculating
continuous price indexes in the face of these
product dynamics can be met by what we gen-
erally refer to as quality adjustment.

Quality adjustment in the PPI occurs in three
stages. First, the physical changes in the product
being priced must be identified. Second, a charac-
terization must be made for each change as to
whether it is an improvement or a deterioration, or
whether no change in quality has arisen. Finally,
each modification that affects cost or functionality
must be evaluated in dollar terms.

Because the most appropriate adjustment pro-
cedure is crit four different quality adjust-
ment approaches were investigated during the
pilot study. The composite quality adjustment
methodology finally selected for the experimental



Experimental Computer Price Index

The experimental indexes in this report are
treated separately from the traditional PPI com-
modity grouping system. Even though industry
codes are provided that detail a published cate-
gory, the indexes are wherever made, commodity
based (similar commodity groupings without re-
gard to the particular industries for which they are
published). At present, the experimental series are
excluded from the stage-of-processing indexes.

The experimental series are issued quarterly,
with a base period of October 1988 = 100, as shown
in the table. In Producer Price Indexes, they appear
in table 13, which also provides year-to-year and
quarter-to-quarter percent changes for these in-
dexes. The indexes are not seasonally adjusted.

We decided on quarterly indexes for a number
of reasons. The primary reason was more practi-
cal than empirical in nature: because the com-
puter industry is a new industry on which the
Bureau would be collecting price and product in-
formation, care would have to be taken to ensure
that the frequency of repricing (or burden level)
would be minimal relative to normal monthly
pricing. We decided to collect lagged monthly
prices for internal use, but publish indexes only
four times a year. For example, if the quarter
ending in October is our pricing period, we also
ask for August and September prices. Our pricing
date is the same as in the PPI, the Tuesday of the
week that includes the 13th day of the month. We
price as of the first month of the calendar quarter.

Secondly, results from the pilot study sug-
gested to us that the incidence of price changes
for computers occurred more on a quarterly,
rather than a monthly, basis. If, after a designated
period of time, we find the opposite to be true,
and a change to monthly pricing does not burden
our respondents, we will implement such a
change. As a complicating factor, however, many
of the price changes occurred on or just before
major computer hardware and software trade
shows, the most prominent of which are the Com-
puter Distribution Expo (COMDEX) and the Fed-
eral Office Systems Expo (FOSE). Whether a
causal connection exists between the two phe-
nomena or whether their mutual occurrence is
just random can only be answered by future ob-
servations made over a longer period of time.

Obviously, other market forces have an impact
on price changes, and these changes may or may
not coincide with our repricing quarters of Janu-
ary, April, July, and October. For example, dur-
ing the first part of 1988, there was a shortage of
dynamic random-access memory (DRAM) chips in
the marketplace that was reflected in our pilot in-
dexes. Depending on a particular manufacturer's
inventory of these chips, prices declined more
slowly, remained the same under the pressure of

22 Monthly Labor Review October 1990

competition, or actually increased for a short pe-
riod of time. By late 1988 the supply stabilized
itself, and the disruptions are not reflected in our
experimental index.

Another pricing phenomenon emerged in our
pilot project in the 16-bit and 32-bit wordsize
computer categories, and we assume that it is
mirrored in the experimental index. When new
microprocessor technology entered the market—
for example, an 80386 replacing an 80286 chip or
a 68030 replacing a 68020 chip—the price of the
older technologies did not af first decline. One
might have thought at a cursory glance that the
price would have declined through market clear-
ing. However, quite a different thing occurred:
the price of the older model actually stabilized
when that model was sold alongside the new
model. Because our experimental index is a
Laspeyres index designed to measure pure price
change from items selected during the base pe-
riod (from a fixed market basket), the new tech-
nology would not enter into our calculation,
unless the old model were no longer manufac-
tured or shipped. We thus expected the price of
the older model to come down immediately upon
introduction of the new model, contrary to what
actually happened. One explanation of this phe-
nomenon is that, even though the newer technol-
ogy cost less, was faster, and provided more
functionality than the older chip, the latter was
still meeting customers’ needs. There appeared to
be a demand for the older processor, and manu-
facturers were still serving the niche created by
that demand.

A good indication of how the computer indus-
try is constantly changing is provided by an ex-
amination of the types and frequency of changes.
in components that have occurred in the experi-
mental index for the past seven quarters. Table 3
summarizes these changes.

Table 3. Frequency of changes in
computer components,
October 1988—July 1990
[In percent)
Category of components, Frequency
quality adjusted of change
Hard-disk storage 9
Random-access memory 18.8
Clock speed 14.6
Warranty 68
Floppy disk storage 49
Tape drive 48
Number of users 42
Keyboard 35
Operating system 35
Port 35
Terminal | 35

—



The quality
adjustment
methodology
selected for the
experimental
index blended

three procedures.

Experimental Computer Price Index

often referred to as “minis,” had declining
prices and were crossing into the high-end
“workstation” dollar categories. Based on the
competitive conditions in the computer market,
the composition of the products that fall into the
various categories is always in flux. In addition,
if a substitution were required due to product
obsolescence, the substitute product’s price
would probably be different from the base-pe-
riod product’s price. If this were the case, the
tule for properly classifying the new product
into a specific dollar category would have to be
very specific and consistent.

The question then arises as to what is a reason-
able pricing structure for publication purposes. Both
trade and popular press reports provide guidance in
the microcomputer area. The personal computer
classes, dominated by machines that work alike, or
“clones,” use the Microsoft/1BM operating system.
This system software was originally designed for
16-bit processors from Intel, namely, the 8088
and the 8086. These machines, along with the
MS/DOS operating systems, set the standards for
hardware and software that still dominate the per-
sonal computer market today.

However, there was a significant market for
other, more powerful machines. These were most
often designed around a 32-bit Motorola 68000
family microprocessor and used a different oper-
ating system, usually a Unix derivative. Users of
these machines often required multitasking or
communication capabilities not possible with the
aforementioned 16-bit hardware/software combi-
nation. Thus, the different user needs were an-
swered with different hardware/software solutions.

Given the aforementioned considerations, the
breakdown selected for the experimental computer
indexes was by wordsize, specifically, 6-bit
wordsize microcomputers, 32-bit wordsize micro-
computers, and computers with a greater than 32-bit
wordsize. The only categories we excluded were the
rapidly growing laptop computers and the aging 8-bit
wordsize computers. We avoided 8-bit wordsize mi-
crocomputers for both the pilot and experimental
phases, as these mature products would not have pro-
vided a rigorous test for our new quality adjustment
procedures and are a very small portion of the over-
all industry. On the other hand, an attempt to include
laptops in our resampling efforts for the experimental
index will take place for the new sample of products
in October 1990. We further categorized processor
type where applicable. The implications here are
that some parameter estimates are significantly
different between the Intel and Motorola classes
of processors. Thus, separate modeling efforts
would improve the estimated coefficients’ quality.
Publication and sampling strategies would naturally
flow around all these divisions.

18 Monthly Labor Review October 1990

Selected methodology

In the absence of information from primary
sources, it was our intention to determine cost
estimates of product differences in a regression
environment that could be made operational in-
side the PPI. We utilized regression coefficients
derived from cross-section estimation equations
for the valuation of technological improvements
and deteriorations.

Regression analysis is a search for functional
relationships among different variables. These re-
lationships are expressed mathematically in the
form:

Y = bo + biX1 + b2X2 +... + bnXn

The dependent variable Y is the price of a
specific computer product. The estimated coeffi-
cients 5; represent the change in Y for each unit
change in their respective independent variable.
The X;’s are the various price-determining or
functional characteristics. They may be continu-
ous or discrete dummy variables (0 or 1). The
regression coefficients are applied only when
product substitution occurs and the manufacturer
cannot quantify the improvements in terms of
resource cost. For example, if product A is re-
placed by product B and the marginal change is
an increase of two megabytes in main memory,
an obvious improvement, the regression coeffi-
cient for that computer characteristic within a
specific publication category may estimate the
dollar value at $925.00. This implicit estimate of
the embodied technological change is then de-
ducted from the reported price, leaving a measure
of pure price change for the good valued at its
base-period capabilities.

The modeling efforts toward developing these
implicit prices, just as in the pilot approach, were
separated into two phases with respect to data
collection: The prefieldwork phase and the
postfieldwork phase. The prefieldwork phase
provided the basis for sampling decisions, a pub-
lication structure, and familiarization with the
product. Further, a general sense of how strongly
performance characteristic levels influenced the
price of a computer was investigated. The
postfieldwork regression analysis pooled the sec-
ondary-source data base purchased from the GML
Corporation® with our collected data. We used a
dummy variable to differentiate the collected ob-
servations from the secondary-source data base.

The methodologies tested separately during
the pilot study were ranked into a composite qual-
ity adjustment methodology for the published ex-
perimental index. Each quality adjustment
methodology employs certain strengths. Ostensi-
bly, the composite quality adjustment methodol-
ogy gives the index maker a measure of freedom


index blended three specific procedures: The stand-
ard PPI resource cost adjustment approach, the im-
plicit regression adjustment approach, and the PPI
“cell relative” approach for missing prices. A more
detailed explanation of these procedures and how
they are applied is given later in the article.

A priori arguments have been made that the
ppt indexes have an upward bias due to the ab-
sence of accurate quality adjustment information
in technologically sophisticated industries. To
overcome any such bias, the standard resource
cost adjustment approach used in the PPI was the
first attempt to value modifications made on se-
lected computer specifications. To implement this
approach, a decision strategy for quality adjusting
substitute products must include information
from computer manufacturers regarding the
resource cost estimate (the fixed cost of overhead,
costs that vary with output, and any return to the
investor—that is, profit) of any improvements or
deteriorations. This estimate should reflect the
differences in the amounts and kinds of labor and
material inputs used in the production of the old
and new product. The marginal change in cost is
based on “the cost differences in inputs under the
cost structure and technological regimen that ex-
isted at the time of introduction of the new variety.”

The basic underlying assumption of the stand-
ard PPI procedure for quality adjustment is that
rising resource costs indicate an improvement in
quality. Conversely, if resource costs decline, the
product’s attributes are assumed to be diminish-
ing in quality. Further, if resource costs change
for a new product, it must be determined whether
the change is in any way a consequence of the
product’s ability to function differently.’ As an
example in the area of automobiles, the quality
changes for which adjustments will be made in-
clude “those structural and engineering changes
which affect safety, reliability, performance. du-
rability, economy, carrying capacity, maneuver-
ability, and/or comfort and convenience.”
However, situations arise whereby the manufac-
turer cannot determine the resource cost of the im-
provements—for example, when there is a lack of
communication of information between engineers
and pricing departments, or when there are survey
burden requirements. In these instances, the PPI
resource cost quality adjustment approach as-
sumes that the entire change between the old and
new product is related to quality. The resultant
index level then remains unchanged.

Operationally, this selected approach used in
the ppl is referred to as a link to show no change.
Here, the new product is substituted for the old
one (after ascertaining that the old product is no
longer being manufactured or shipped), and the
index level remains the same. In a competitive

environment with very sophisticated products,
this procedure would introduce an upward bias
into an existing index because it would fail to
capture the improvement in quality embodied in
the new product.

In capital-intensive industries, the majority of the
quality improvements are associated with resource
cost increases. For those areas in which resource costs
and functionality decline, resource cost savings are
reported to the Bureau, and prices are adjusted ac-
cordingly. However, the computer industry is one of a
few exceptional cases. Marked by tremendous im-
provements in quality at lower costs, it required a
better yardstick to value these improvements.

Publication structure

We focused our analysis on product types
within the fairly ambiguous classes of machines
labeled microcomputers, midsized computers,
and large computers. The usual guide for BLS
index structures is the Bureau of Census product
classifications. Table 1 shows MA3SR(87)-I°
breakdowns for electronic computers, Standard
Industrial Classification (SIC) code 3571. From
the table, it is plain that dollar values in this
industry are not appropriate definers for price
index series. Rather, a stable product definer
was needed that did not fluctuate with market
conditions. For example, midlevel machines,

Table 1. Value of shipments of electronic computers, sic 3571,

1987

[Value in thousands of dollars]

Product code | Product description
35711 | Computers, complete except parts (nonretail)
General-purpose computers
Digital:
35711 01 Less than $500 (retail price)
35711 02 {$500 to $1,000 (retail price)...
35711 03 | $1,000 to $2,500 (retail price).
35711 04 $2,500 to $5,000 (retail price).
35711 05 | $5,000 to $15,000 (retail price).
38711 06 $15,000 to $60,000 (retail price)
35711 07 | {$50,000 to $250,000 (retail price).
35711 08 $250,000 to $1 milion (retail price)
35711 09 Over $1 million (retail price)
35711 22 ‘Analog
35711 25 Hybrid
| Special-purpose computers
35711 31 Digital
35711 32 ‘Analog
35711 33 Hybrid... Sepeeeeeeeeeea
35711 35 | Computers kits to be assembled by purchaser .

— an Value ot

shipments

$23,261,842

275,532
354,833
2,123,875
5,019,345
1,473,348

3,360,006
2,770,430
2,639,284
1,973,604

“| } 14.620

2,462,140

} 704,825

Monthly Labor Review

October 1990


Table 15. Industries with largest total employment Table 16. Occupations with largest employment
percentage gain due to various defense percentage gain, alternative scenarios

cuts in spending
[Employment in thousands]

regarding cuts in defense spending
[Employment in thousands]

Percent increase from Percent increase from
Industry low-detense 1 Occupation low-detense 1
Number | Percent Number | Percent
Conventional cuts Conventional cuts
eee ee
Guided missiles and space vehicles 142.4 72 ‘Aeronautical and astronautical engineers 792 18
Radio and TV communication equipment 436.7 16 Aircraft assemblers, precision : 28.1 16
Engineering and scientific instruments 122.6 15 Electronic semiconductor processors. . 33.8 4
! Etecmecharical equipment assemblers,
Electronic tubes . . 32.0 16 52.3 08
Miscellaneous electronic components 359.3 14 lectieal and electronic equipment assemblers, :
Aircraft and missile engines and equipment 370.3 | 13 precision 393 | 08
Aircraft... 356.0 orl Electrical and electronic assemblers .. . 133.3 06
Office and accounting machines 45.6 09 Electncal and electronics engineers... .. 5964 05
Industrial engineers, except safety engineers 152.3 05
Optical and ophthalmic products 749 08 Coil winders, tapers, and finishers... 206 05
‘Semiconductors and related devices 298 | 0? Electrical and electronic technicians
High-tech cuts
Ship- and boatbuilding and repairing 155.9 | 20.7 Shipfitters
Ordnance, except vehicles and missiles 55.4 15.0 Riggers...
Miscellaneous transportation equipment 50.1 54 Painters, transportation equipment. 0
Engines and turbines 769 25 Welders and cutters 0
Petroleum engineers 6
Crude petroleum, natural gas. and gas liquids 180.9 09
Petroleum refining 105.8 07 Grinders and polishers, hand . 734 | 08
Pipelines, except natural gas 189 | 05 Boilermakers... 24.6 07
| Gas and petroleum plant and system occupations 224 | 05
Miscellaneous fabricated metal products 223.7 0.4 Painting, coating, and decorating workers, hand 35.1 08
Fabricated structural metal products 412.9 0.3 All atner electrical and electronic equipment
Blast furnaces and basic stee! products 244.9 02 mechanics ..... | 544 08

IN SUMMARY, the Bureau has explored several
alternatives for future defense spending, in ag-
gregate economic terms and in terms of employ-
ment in specific industries and occupational
groups. Although the effects tend to be rela-
tively minor at the aggregate level. they may be
significant in certain industries and occupations
most closely tied to the Department of Defense.
While those industries and occupations may suffer
from significant defense spending cutbacks, other
industries and occupations may improve as a re-

Footnotes

sult of offsetting economic factors.

Further efforts could fruitfully be aimed at the
estimation of regional effects of defense spending
cuts,’ or by estimating the employment and occu-
pational effects of more narrowly defined cuts.> At
this point, both the extent and timing of any possible
cuts in defense spending are unknown. When the
first round of budget-making for the 1990’s defense
establishment is completed, more narrowly defined
approaches might be feasible. im)

' “Outlook 2000,” Monthly Labor Review. November

1989, pp. 3-74. This series of five articles on the BLS
projections to 2000 outlines the shape of the economy and
detailed labor supply and demand.

The estimate of defense-related employment in 1988
was derived by multiplying a 1988 employment-requirements
matrix by a detailed vector of Defense Department commodity
purchases. An employment-requirements matrix shows the
direct and indirect employment in all industries generated by
$1 of final production and is derived from a detailed total-re-
quirements input-output matrix and similarly detailed estimates
of total industry employment for the year in question,

* The initial calculations for each scenario assumed only
the change noted in defense spending in order to determine

the sensitivity of the aggregate economic model to these
changes alone. The aggregate economic projections of the
Bureau of Labor Statistics are performed in the context of
Data Resources, Inc., Long Term Model of the U.S. Econ-
omy. For a full description of the model, refer to “The Dri
Annual Model of the U.S. Economy.” by Joyce Yanchar, in
Data Resources U.S. Long-Term Review, Winter 1986-87,
pp. 30-43.

‘This type of regional analysis was presented in “The
Peace Economy.” Business Week, Dec.. 11, 1989, pp. 50~

* For an example of these types of studies, which are just
now beginning to appear, see Budgetary and Military Effects
of a Treaty Limiting Conventional Forces in Europe, a Special
Study of the Congressional Budget Office, January 1990,

Monthly Labor Review October 1990