United States General Accounting Office

GAO Congressional Requesters

June 1999 CONSUMER PRICE

INDEX

Impact of Commodity

Analysts’

Decisionmaking Needs

to Be Assessed

GAO/GGD-99-84

GAO United States

General Accounting Office

Washington, D.C. 20548

General Government Division

B-279259 

June 15, 1999

The Honorable John L. Mica

Chairman, Subcommittee on Criminal Justice,

 Drug Policy, and Human Resources

Committee on Government Reform

House of Representatives

The Honorable Christopher Shays

House of Representatives

One of the most important economic indexes produced by the federal

government is the Consumer Price Index (CPI). According to the Bureau of

Labor Statistics (BLS), which publishes the index, the CPI is the principal

measure of trends in consumer prices and inflation in the United States.

The CPI is used by the federal government, businesses, and others. In fiscal

year 1998, $499 billion in federal spending, such as income payments to

Social Security beneficiaries, was automatically linked to price changes

measured by the CPI. In addition, because it is used annually to adjust

various aspects of federal individual income tax for inflation, such as the

tax brackets and the amounts of personal exemptions, every individual

income taxpayer is affected by changes in the CPI.

The CPI tracks the prices of a fixed market basket of goods and services

that consumers purchase. There are thousands of different products and

services in the market basket, and BLS attempts to obtain prices on the

exact same products and services each month. By tracking the exact same

items each month, BLS seeks to avoid capturing price differences that are

due to changes in the characteristics of a product or service rather than

simply changes in price. However, BLS cannot always find the exact same

item each month; and when this happens, BLS price takers in the field

“substitute” a new version of the product for the old version. Substitutions

occur for a variety of reasons, including changes in technology or style as

well as when an item is out of stock at a store in which prices are being

collected. In calendar year 1997, according to BLS data, substitutions

ranged from 1.4 percent in the food and beverages component to

12.8 percent in the apparel and upkeep component.

After substitutions are made in the field, BLS’ commodity analysts in

Washington, D.C., decide if there are significant differences in

characteristics between the items and their substitutes. When commodity

analysts determine that the differences are significant, they make what BLS

refers to as quality adjustments to separate pure price changes from price

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changes that are due to other factors, such as differences in quality, size,

or quantity.1

The adjustments made by commodity analysts affect the price changes

that go into computing the CPI. Evidence indicates that substitutions (those

that are adjusted together with those that are not adjusted) have a

significant impact on the CPI. A BLS study estimated that, while less than

4 percent of the price quotations used to calculate the CPI in 1995 were

substitutions, these substitutions were responsible for about one-half of

the price increase in the CPI for the items studied.2

 To the extent that more

than pure price changes are included in the CPI, the index’s accuracy is

affected.

As you requested, this report describes (1) how commodity analysts

decide whether to make adjustments, (2) the adjustment methods they

use, and (3) how supervisors of commodity analysts review the analysts’

decisions. For this report, we gathered descriptions from commodity

analysts on how they made decisions for specific substitutions that ranged

across the major components of the CPI.

Results in Brief Commodity analysts use a combination of professional judgment, general

procedures, specific methods, and limited written guidance in deciding

whether and how to make adjustments for substitutions. The relative

importance of these four elements varies in the analysts’ decisionmaking,

depending upon the specific substitutions. In some cases, judgment is of

primary importance. According to BLS, the commodity analysts’

supervisors usually review substitution decisions only when they consider

the price increases or decreases that result from the analysts’ decisions to

be large. Beyond the specific reviews performed by supervisors, BLS does

not have a program of assessing the decisionmaking patterns of

commodity analysts.

In making adjustments, BLS’ objective is to include only pure price change

in the calculation of the CPI and, to the extent possible, eliminate price

change that is the result of other factors, such as improvements in quality,

1

In this report, we refer to all adjustments—whether for quality or other reasons—simply as

adjustments.

2

This BLS study included data from about 83 percent of the 1995 item strata. (BLS groups items in the

CPI together at broad levels of similarity—food and beverages—and then at sublevels of similarity.

Item strata—ground beef, chuck roast—are sublevels.) The study attributed the disproportionate

impact of substitutions on the CPI to manufacturers’ tendency to increase prices when new products

were introduced, and retailers’ tendency to discount prices when old products were discontinued.

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size, or quantity. Commodity analysts receive and review information

about the old and new versions of the commodity from which they make a

series of determinations that revolve around whether the two versions are

similar and, if not, which adjustment method to apply.

Commodity analysts compare the characteristics of the original item with

the replacement and then use their professional judgment to decide if the

two are comparable. For example, a commodity analyst who reviewed a

substitution of an electric blanket with a 5-year warranty for an electric

blanket with a 2-year warranty judged them to be comparable. In calendar

year 1997, analysts concluded that a majority—58 percent—of about

29,000 substitutions were comparable. For other than certain food items,

no current written guidance was available for commodity analysts to

follow in making their decisions. In some instances, according to BLS, the

decisions are straightforward and involve little judgment. In other

instances, the analysts must exercise a significant degree of judgment to

make decisions. For items that are judged to be comparable, no

adjustment is made; and the difference between the prices of the new and

old versions, expressed as a percentage, is used in the calculation of the

CPI for that month.

When a substitution is not comparable with the item it replaces,

commodity analysts either use a direct adjustment method to make an

adjustment themselves or assign one of two indirect methods, in which

case BLS computer programs make the adjustments. In 1997, about

one-third of all nonrent adjustments were made directly; about two-thirds

were made indirectly. Direct adjustments are made when commodity

analysts have data on the ways the old and new versions differ and have

information with which to assess the value of those differences. They are

made when the specific cost of a quality change can be estimated either by

the manufacturer of the items or by using BLS’ statistical models that

incorporate price data. Direct adjustments are also made when an item’s

size or quantity changes. Most direct adjustments in calendar year 1997

were for apparel items and new and used vehicles. Although BLS’ process

for reviewing changes that affect residential rent is somewhat outside the

process that it follows for other CPI items, the majority of adjustments

made to residential rent are direct adjustments.

When an adjustment is judged to be warranted, but a direct adjustment

cannot be made, commodity analysts apply one of two indirect adjustment

methods that impute a rate of price change. Both methods impute the pure

price change by averaging the rates of price changes experienced by the

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same type of items in the CPI. The two methods, “class mean” and linking,

differ in terms of the subsets of items included in calculating the rate of

price change. The class-mean method is generally used for products where

new models or product lines are introduced fairly regularly. It is based on

the rate of price changes experienced by other substitutions—of the same

type of product or service—in the particular geographic location. These

other substitutions are those that the commodity analyst had judged for

that month to be comparable or had directly adjusted. Thus, the

class-mean method relies exclusively on an analyst’s judgments for related

substitutions. The linking method is not limited to price changes resulting

from substitutions. This method includes all items of the same type and in

the same location as the item in question, and it is most heavily influenced

by items that had not changed; that is, those that were not substitutions.

The linking method includes a larger array of products and services than

the class-mean method.

According to BLS, there are no guidelines or policies in writing for

supervisors to follow in selecting and reviewing the substitution decisions

of commodity analysts. In practice, according to BLS, there is an unwritten

policy that supervisors are to review substitution decisions when they

consider the price increase or decrease to be large. Few other adjustments

are reviewed. BLS has no policy to randomly or otherwise select and review

substitution decisions.

Beyond the specific reviews performed by supervisors, BLS does not have a

program to assess the decisionmaking patterns of commodity analysts.

However, studies have been conducted from time to time, and three were

conducted in the 1980s and early 1990s. The studies found the

decisionmaking process to be susceptible to producing errors and

inconsistencies and recommended actions intended to promote greater

controls over the decisionmaking process. According to officials we

interviewed, however, BLS now takes the position that such controls are

not required for experienced commodity analysts.

We found no evidence to indicate whether errors or inconsistencies in

commodity analysts’ decisions or lack of comprehensive reviews of those

decisions has had a material effect on the calculation of the CPI. However,

it is sound management practice for BLS to assess, on a periodic basis,

whether errors and inconsistencies in commodity analysts decisions

materially affect the CPI and we make a recommendation to that effect.

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Background Every month, usually by the middle of the month, BLS, which is a part of

the U.S. Department of Labor, publishes a new CPI based on data collected

in the previous month. Two CPIs are published, and the data for each are

arrayed in various ways, such as by nationwide average for urban areas

and by selected local areas.3

 To produce these indexes, BLS collects and

processes large amounts of data.

According to BLS data, an average of about 77,000 price quotations—price

and characteristics about a product or service—were collected each

month in calendar year 1997. To obtain these quotations, approximately

30,000 retail and service establishments and nearly 4,000 landlords and

tenants were visited or contacted every month. All together, BLS tracked

the prices of about 94,000 specific items in 1997, although every item was

not priced every month. The many kinds of products and services under

which these thousands of items were categorized ranged from white bread

to funeral expenses (see app. VIII).

Although some pricing information is gathered by BLS headquarters

personnel, most price quotations are collected by BLS field representatives

who are also referred to as price takers. According to BLS, each price taker

is assigned specific outlets (e.g., supermarkets, department stores, car

dealers, housing units, and doctors offices) to visit and a list of goods and

services within those outlets to price.

If an outlet does not have the exact item, BLS requires the price taker to

select a substitute item in that outlet. Depending on the item, the price

taker may visit or contact the outlet more than once to find the missing

item before making a substitution. In calendar year 1997, acceptable

substitutions were made for about 3.3 percent of the 872,829 nonrent price

quotations collected.4

 Price takers are to select substitutions that are as

similar as possible to the items that were not found.

Substitutions are reviewed by commodity analysts who work in the

Consumer Prices Branch of the Division of Consumer Prices at BLS’

headquarters. The branch, which is headed by a branch chief, is divided

3

The two CPIs are the CPI for All Urban Consumers (CPI-U) and the CPI for Urban Wage Earners and

Clerical Workers (CPI-W). According to BLS, the CPI-U represents about 87 percent of the U.S.

population, and the CPI-W represents about 32 percent of the U.S. population. BLS began publishing the

CPI-U in 1978. Until then, it published only the CPI-W.

4

Upon review, BLS may classify a substitution as an unacceptable replacement if, for example, a

substitution occurred outside of the time frame BLS has designated for a seasonal item—a spring or

summer raincoat for a fall or winter coat. Unacceptable substitutions are discarded, and BLS does not

include them in its statistics on substitutions.

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B-279259 

into five sections, each of which is headed by a section chief. There were

three supervisors in April 1998 who, in addition to the section chiefs,

supervised 29 commodity analysts.

Appendix II provides more information about the general construction of

the CPI and the collection of prices.

Scope and

Methodology

For our first and second objectives—to describe how commodity analysts

decide whether to make adjustments and the adjustment methods they

use—we (1) obtained relevant documents and data from BLS; (2) had

commodity analysts walk us through selected substitutions that they had

reviewed, asking them to explain what they did and why; and

(3) discussed the methods used to make adjustments with the supervisors

of commodity analysts.

Among the documents we reviewed were BLS manuals and handbooks

pertaining to the CPI, such as an instruction manual for price takers,5

 a

handbook that included descriptions of the adjustment methods,6

 and a

handbook that described procedures for reviewing housing rental data.7

 In

addition, we reviewed BLS’ descriptions of the adjustment procedures that

were published either as internal research papers or in professional

journals. With the exception of certain food items, BLS did not have a

current set of written procedures that commodity analysts followed when

reviewing nonrent substitutions.

At our request, BLS provided us with 1997 summary data on the number of

price quotations collected, the number of substitutions, and the number of

times the different methods of adjustment were used. These data are

reproduced in appendix VIII.

To obtain an understanding of the commodity analysts’ decision

processes, we talked with analysts about specific substitutions. We

interviewed a judgmental selection of 19 out of 28 commodity analysts

5

Consumer Price Index: C&S Pricing Data Collection Manual, BLS (Washington, D.C.: U.S. Department

of Labor, n.d.).

6

BLS Handbook of Methods, BLS (Washington, D.C.: U.S. Department of Labor, April 1997).

7

Housing Commodity Analyst Handbook, BLS (Washington, D.C.: U.S. Department of Labor,

January 1996).

Page 6 GAO/GGD-99-84 Consumer Price Index
B-279259 

about their decisions on 120 specific substitutions.8 (See appendix I for the

details of how we selected the analysts and substitutions.) In addition, we

talked to a supervisor about another 16 specific substitutions because the

analyst who had reviewed these substitutions no longer worked at BLS. We

asked the analysts and supervisor questions, such as what characteristics

changed between the substitution and the item it replaced, what led to the

decision that a substitution was comparable or not comparable, and why a

particular adjustment method was applied.

After these interviews, we judgmentally selected 13 substitutions to serve

as illustrative examples for this report. These examples cover

(1) substitutions from the six major components of the CPI, (2) comparable

substitutions, and (3) the major adjustment methods. See appendix I for

the details of how we selected the examples.

For our third objective—to describe how supervisors review commodity

analysts’ decisions—we interviewed supervisors and reviewed BLS studies

that considered issues relating to supervision. We also discussed the

methods used to make adjustments with the supervisors. The supervisors

we interviewed were the chiefs of the five sections into which the

commodity analysts are divided and three supervisors who were not

section chiefs. In addition, we also interviewed the Branch Chief for

Consumer Prices, who is responsible for all five sections. The studies we

reviewed were an assessment of analysts’ decisionmaking over time,9

 a

quality assurance report on analysts’ decisions,10 and an evaluation of a

project to develop decisionmaking computer software that would assist

analysts and supervisors.11

Because the procedures that commodity analysts follow in reviewing

substitutions for most CPI items are unwritten, we relied mostly on our

interviews with commodity analysts and their supervisors and managers to

piece together what those procedures were. To the extent possible, we

8

One of the 29 commodity analysts had not worked for the CPI in 1997 and was excluded from our

survey. Four of the 19 commodity analysts reviewed substitutions connected with residential housing

rent. The others reviewed substitutions for various goods and services, such as over-the-counter drugs.

Analysts who review residential rent follow different procedures than the others. Appendix VII

provides information on the procedures for residential rent.

9

Jack Galvin, “A Control Chart Analysis of Commodity Analyst Review Activity.” Unpublished study,

BLS, October 1985.

10Paul A. Armknecht, “Commodity Analyst Updates During 1985 for C&S Survey Quality Assurance

Report.” Unpublished study, BLS, May 1986.

11Bob Adkins et al., “The Development and Testing of the CPI Commodities and Services

Comparability Expert System.” Unpublished study, BLS, February 1993.

Page 7 GAO/GGD-99-84 Consumer Price Index
B-279259 

verified what we were told by cross-checking what one person said with

what another person said. We did not verify the computerized data that BLS

provided to us, such as statistics on substitutions. Nor did we verify the

studies or any other materials BLS provided to us. 

This report describes procedures which, according to BLS, are intended to

contribute to the accuracy of the CPI but does not assess the accuracy of

the methods BLS uses to make adjustments or estimate the effects of those

adjustments on the CPI. Similarly, our work is not intended to evaluate the

overall accuracy of the CPI.

We did our audit work in Washington, D.C., from November 1997 through

January 1999 in accordance with generally accepted government auditing

standards. We requested comments on a draft of this report from the

Secretary of Labor or her designee. The Commissioner of BLS provided

written comments, which are discussed near the end of this letter and

reprinted in appendix IX along with our additional comments.

Description of How

Analysts Decide to

Make Adjustments

and the Adjustment

Methods

BLS has two processes for reviewing changes in products and services that

are in the CPI: one for residential rental units and another for all other

items in the CPI. Although BLS does not substitute one residential unit for

another, according to BLS officials, changes in a rental unit may cause BLS

to adjust the reported rent. For example, if a landlord added a clothes

washer and dryer to the unit since BLS last collected data, BLS would adjust

the current rent for the value of the addition of the washer and dryer so

the rental unit would be comparable to what it was earlier. BLS’ process for

reviewing changes to rental units is somewhat outside the process that it

follows for other CPI items. Appendix VII discusses the procedures and

adjustment methods used for residential rent.

Using information gathered from our interviews with commodity analysts

and their supervisors and confirmed by BLS officials, we sketched out how

commodity analysts review nonrent substitutions and the adjustments

they make. Figure 1 illustrates that process. It begins when commodity

analysts receive commodity review listings, after which they make a series

of determinations, such as whether a substitution is acceptable, whether

an acceptable substitution will be adjusted, and which adjustment method

will be applied.

BLS has not documented the process it uses to review and adjust most

nonrent substitutions; but BLS officials have agreed that, although there are

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B-279259 

probably some exceptions, the figure 1 flowchart reasonably illustrates

that process.

Page 9 GAO/GGD-99-84 Consumer Price Index
B-279259 

Figure 1: BLS’ Process for Making Nonrent Substitutions and Adjustment Decisions

Commodity analysts

receive commodity

listing reviews.

Commodity

analyst kills the

substitution.

Is the 

replacement

comparable to 

the original

item?

Does the

commodity analyst

have information to

make the replacement

more similar to the

original?

Yes

Yes

Yes

No

No

A

B

Is this

an acceptable

substitution?

Substitution is

“killed,” it is not 

used in the CPI, 

and a price 

imputation

is made.a

No

Did the 

price taker 

identify the 

item as a 

substitution?

Yes

Yes Should the 

item be 

classified

as a 

substitution?

No

Commodity analyst

creates a

substitution.

No

Processed 

with other 

items in the CPI.

Replacement is used 

in the CPI this month

with the commodity 

analyst directly 

comparing the prices 

of the original and its

replacement.

Page 10 GAO/GGD-99-84 Consumer Price Index
B-279259 

No

A

Is the

item one

for which BLS

has designated

that the classmean method

can be used?

Is the classmean method 

appropriate 

to apply?

Does the

commodity analyst

have information on the

value of the difference

between the original

item and its

replacement?

B

Yes

No Yes Yes

Yes No No

Replacement is not 

used in the CPI this

month, and a price 

imputation is made 

using the linking

method.a

Replacement is not used

in the CPI this month, 

and a price imputation

is made using the

class-mean method.a

Replacement is used 

in the CPI this month, 

with the commodity 

analyst making a 

direct adjustment.

aPrice imputation is a term used by BLS to indicate that the actual price of the substitution is not

used. Instead, an average is calculated from the price changes experienced that month by the

same type of items in the CPI to handle a missing or unusable price quotation.

Source: BLS.

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Commodity Review

Listings Provide Analysts

With Information for

Decisionmaking

Commodity review listings (CRL) provide commodity analysts with

information for making various judgments about substitutions and are the

primary tool used by analysts in the process of reviewing changes in

products and services. CRLs are generated each month from the data that

have been collected by price takers. CRLs contain data about a product or

service, such as its characteristics (referred to as specifications by BLS)

and price history. For example, for a cola soft drink, the CRL may list the

packaging (e.g., 12 pack), container construction (e.g., metal can), and

caffeine content (e.g., caffeine free). CRLs for items that were reported as

substitutions by price takers include the specifications and prices for both

the substitution and the item it replaced. All specifications are listed

according to a hierarchy of importance for comparing the two versions,

and specifications that differ between the two versions are automatically

noted.

According to BLS, two conditions usually cause a CRL to be generated for

substitution review: (1) the price taker reported an item as a substitution

and (2) BLS computers, which have been programmed to identify changes

in specific characteristics that the price taker recorded for the item,

identify a change in a key specification. Computer routines, according to

BLS, compare the item reported one month with the item that was reported

the previous month in which the item was priced. In these

computer-identified cases, price takers would not have reported the

current item to be a substitution.

Upon receiving these CRLs, one of the first judgments that a commodity

analyst is to make is (1) whether an item was correctly reported as a

substitution or (2) whether the change in specification should cause the

item to be treated as a substitution. The analyst may decide that the price

taker inappropriately identified an item as a substitution based on the

specifications that the price taker provided, in which case, according to

BLS, the substitution is deleted and not used in the CPI. If the

computer-identified change in specification is significant in the analyst’s

judgment, the analyst can classify the current month’s item as a

substitution.

Determining Whether a

Substitution Is Acceptable

After the pool of substitutions has been identified, then the commodity

analysts determine if each of them is acceptable for use in the CPI.

According to a BLS official, there are several reasons why a substitution

may be unacceptable. For example, a substitution is deemed unacceptable

when the commodity analyst waits to see if the old version is only

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temporarily unavailable at the retail outlet. Unacceptable substitutions are

“killed” in BLS’ terminology—deleted and not used in the CPI—and,

according to a BLS official, excluded from statistics on substitutions

(including those presented in this report). This BLS official told us that

1,065 substitutions were killed between October 1997 and September 1998.

In calendar year 1997, commodity analysts determined that 28,881 nonrent

substitutions were acceptable and eligible for use in the CPI. These 28,881

substitutions represented about 3.3 percent of the 872,829 nonrent prices

collected by BLS in 1997.

Determining Whether the

New and Old Versions Are

Comparable

For substitutions that are accepted, the next step commodity analysts take

is to judge whether the price change resulting from the substitution can be

used in the CPI without adjustment or whether an adjustment is necessary

to account for differences between the substitution and the item it

replaced. BLS officials reported that the analysts make this determination

based on the extent of the differences between the old and new versions

of the substituted item and the methods and information available to them.

In some instances, according to BLS, the decisions are straightforward and

involve little judgment. In other instances, a significant degree of judgment

is required.

When the new version and the old version are judged similar enough to

preclude the need for an adjustment, they are said by BLS to be

comparable. In 1997, commodity analysts judged about 58 percent of the

28,881 nonrent substitutions to be comparable. For example, in one

substitution we reviewed, the level of membership in a tennis club

changed from “Tennis plus” to “Gold tennis” but the analyst determined

that the memberships were essentially the same and comparable. In

another substitution, the manufacturer increased the warranty of an

electric blanket from 2 years to 5 years, but the analyst concluded that the

blankets were comparable.

However, if the new version had characteristics that the commodity

analyst considered significantly different from the old version, such as

changes in materials, features, or size, the analyst would have to consider

whether, and how, to make an adjustment. In such cases, the substitutions

and the items they replaced are generally judged by BLS to be not

comparable. For example, in one substitution we reviewed, the size of a

bed dust ruffle changed from twin (old item) to queen (substituted item),

causing the commodity analyst to judge them to be not comparable. In

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another case, there were differences in ingredients and size between two

packages of soup, and the analyst classified them as not comparable.

When the two versions are judged to be comparable, the price of the old

version is compared with the price of the new version and the result,

expressed as a percentage, is used to calculate the CPI for that month. For

example, if two coats were comparable and the new version cost $115 and

the old version cost $95, the rate of change for the coat would be

21 percent. However, when an adjustment is made, the percentage price

change that results from that adjustment is used in calculating the CPI. If

the two coats were not comparable because the new one had a lining and

the old one did not, and the cost associated with the lining was $5, an

adjustment of $5 would be made. The rate of change used in the CPI for

that month would be an increase of 15 percent instead of 21 percent.

Most commodity analysts that we interviewed did not have written criteria

to guide them in making their comparability decisions. But a few food

commodity analysts showed us criteria that they had developed with their

supervisors for specific types of products to help them decide whether

substitutions are comparable.

Regardless of whether comparability criteria were available, all of the

commodity analysts we interviewed indicated that they examine the

specifications on the CRL and decide if the differences in characteristics

between a substitution and the item it replaced warrant an adjustment. If

they decide that the differences are not major, the commodity analysts

said they will code the substitution as comparable. Their supervisors

stated that, in some instances, the differences did not allow for clear-cut

decisions, and that the analysts’ judgment had to be exercised.

Adjustment Methods and

Determining Which

Method to Use

When a substitution is not comparable with the item it replaced,

commodity analysts make a direct adjustment or cause an indirect

adjustment to be made. When direct adjustments are made, BLS has

information on the ways the new version changed from the old version

and the value of those changes to adjust the price of the substitution

directly. BLS uses several different direct adjustment methods. Indirect

adjustments are made when there is insufficient information available with

which to make a direct adjustment. Unlike the direct adjustment methods,

which are based on information that is specific to the item being adjusted,

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the two indirect adjustment methods that BLS uses, class-mean and linking,

are based on averages of other price changes experienced that month.12

The number of direct and indirect adjustments made to nonrent

substitutions in calendar year 1997 totaled 12,131. This number was about

42 percent of the 28,881 nonrent adjustments. Table 1 shows the number

of direct and indirect adjustments by major CPI component. As the table

indicates, when the number of substitutions is compared to the number of

price quotations, substitutions occur unevenly among the CPI components.

Table 1: CPI Price Quotations, Substitutions, and Methods of Adjustment by Major Components for 1997

Indirect adjustments

Adjusted substitutions by adjustment

method

Major components

Number of

price

quotations

Number of

substitutions

(accepted)

Substitutions

not adjusted

(comparable)

Direct

adjustments

Class-mean

methoda

Linking

method

Food and beverages 459,635 6,485 3,640 107 31 2,707

Housingb 136,430 4,047 2,453 132 1,023 439

Apparel and upkeep 76,736 9,797 6,598 1,223 1,796 180

Transportation 94,336 5,660 2,699 1,837 823 301

Medical care 50,237 1,116 355 336 3 422

Entertainment 32,985 1,327 763 95 321 148

Other goods and services 22,440 422 215 40 52 115

All items 872,829 28,881 16,750 3,770 4,049 4,312

aThis column includes some adjustments made using a method that BLS was phasing out of use.

BLS estimated the number of these adjustments to be at least 77.

bHousing totals exclude residential rent adjustments. The full version of this table, which is

contained in appendix VIII, contains data on rent.

Source: BLS.

Regardless of whether an adjustment is direct or indirect, the basic intent

is to keep the known differences in characteristics between substitutions

and original items from affecting the CPI’s measurement of price change.

The CPI is designed to include only “pure” price changes, and the

adjustments that BLS makes in connection with substitutions are intended

to separate pure price increases from increases due to other factors, such

as improvements in quality.13

12BLS refers to these two methods as “imputations.” For ease in reading we use the term “indirect

adjustments” to refer to the class-mean and linking methods.

13The difference in price that remains after pure price is referred to generically as quality by BLS.

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Direct Adjustments About 31 percent of the 12,131 nonrent adjustments in 1997 were made

using direct adjustment methods. On the basis of BLS’ use, these direct

adjustments can be classified into a manufacturers’ cost method; a

statistical modeling method, which BLS refers to as a hedonic regression

method; and a final method that can best be described as a catchall

“other,” which includes adjustments for changes in size or quantity or for

error.

• For the manufacturers’ cost method, BLS uses cost information from

manufacturers to identify individual characteristics or options that have

changed and the cost of those changes. In 1997, all of the manufacturers’

cost adjustments were in the new and used vehicle item strata. BLS collects

information from automakers on the changes they make each model year

and the cost of those changes. After screening these changes to make sure

they meet BLS’ criteria for quality, BLS then uses the information to make

adjustments. BLS collects this change and cost information for a sample of

domestically produced models each year. The great majority of the 1,837

direct adjustments made in the transportation component of the CPI used

the manufacturers’ cost method.

In an automobile substitution that we reviewed, the commodity analyst

used an automaker’s information to determine that a 1998 model had

lower fuel emissions and safer air bags than the 1997 model. Using

information from the automaker, the analyst valued these improvements at

$135. The analyst then made a direct adjustment, reducing the difference

in price between the 1997 model and the 1998 model by $135 to account

for the change in quality.14 The remaining difference in price (expressed as

a percentage) went into the CPI as the pure price change.

• Under the hedonic regression method, BLS uses statistical models to

estimate a value for individual characteristics of a product, such as the

value of adding a lining and hood to a coat. According to BLS, in 1997,

statistical models were used to make most of the 1,223 direct adjustments

to apparel items, which were the only type of item for which BLS had

statistical models.15

14As of January 1999, BLS no longer treats changes made solely to meet air quality standards as quality

improvements for determining the rates of price changes for the CPI.

15BLS has developed a statistical model for computer items, which it began using in 1998, and another

for televisions, which it began using in January 1999.

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For one of the apparel substitutions we reviewed, for example, the

commodity analyst used a statistical model to assign value to certain

differences—design, fiber content, and cleaning method—between two

versions of a woman’s coats. Based on information from the model, the

analyst assigned these differences a combined value of $33.85. This value

was then, in effect, subtracted from the difference in price between the old

and new versions.

• A broad array of direct price adjustments fall within the other direct

method, including those for a change in size (e.g., 8 ounces instead of 10

ounces), for a change in the number of units (e.g., 15 tablets instead of 12

tablets), and to correct for errors made by price takers (e.g., to correct an

inaccurate recording of the number of ounces in a container). BLS

considers adjustments for size or unit count to be direct adjustments

because they adjust for a particular countable characteristic of a good or

service. Most of the direct adjustments in the major components of the CPI,

other than apparel and transportation, were these types of direct

adjustments.

Commodity analysts we interviewed who reviewed automobile and

apparel substitutions said that they often made direct adjustments to

increase the level of similarity between old and new versions. Without

these adjustments, the substitutions would have been classified as

comparable, according to the analysts, because the differences were

minor. For example, the commodity analyst who made the $135 direct

adjustment in the previously mentioned automobile substitution said that

the difference in fuel emissions and air bags between the two models

would have been insufficient to make them not comparable. In addition,

regardless of type of product or service, analysts who have the information

available with which to make a direct adjustment may do so without first

going through the step of contemplating whether the new and old versions

are comparable.

When using the direct adjustment methods based on manufacturers’ cost

information or statistical models, BLS first estimates the value of quality

changes and then removes that value from the difference in price between

the substitution and the original item. The pure price change is the

residual after the adjustment for quality is made. For example, in the

automobile substitution we discussed previously, the 1998 model cost

$23,180 while the 1997 model cost $22,104, a difference of $1,076. If no

adjustment had been made, this difference would have constituted a price

increase of 4.9 percent. However, an adjustment of $135 was made for

improvements in fuel emission levels and air bag safety. As a result, the

Page 17 GAO/GGD-99-84 Consumer Price Index
B-279259 

adjusted price difference between the 1998 model and the 1997 model was

$941, or 4.3 percent. Therefore, in this case, 0.6 percent (or $135) of the

unadjusted price difference of 4.9 percent was attributed to quality

change, and the remainder of 4.3 percent was attributed to pure price

change.

Appendix IV provides more information about the direct adjustment

method, including examples that illustrate its use.

Indirect Adjustments BLS uses either a class-mean method or a linking method to make indirect

adjustments. Both of these indirect methods first estimate the pure price

change and exclude any residual, which is reverse of what the direct

adjustment methods do where price change is the residual. Both methods

impute the pure price change by averaging the rates of price changes

experienced by the same type of items in the CPI. This averaging is done by

computer program. However, the same type of items are defined narrowly

for the class-mean method but are defined much more broadly for the

linking method.

Because the linking method is, in effect, based on the average rates of

price change for all of the same type of items in a geographic location, it

cannot affect the average rates of price change for that geographic

location. In addition, estimates by BLS researchers indicate that, overall,

the linking method causes lower price increases than the class-mean

method. The researchers estimated that the average monthly price change

for adjustments made with the linking method was less than 1 percent in

1995 while the average monthly price change for adjustments made with

the class-mean method was about 5 percent. Because the methods by

definition use different sets of goods and services in the calculations, BLS’

estimates of 1 percent and 5 percent reflect differences due to the manner

in which the calculations were made as well as differences in the type of

products used in the calculations. BLS designed the class-mean method

with the intention to produce more accurate rates of price change for

items involving new models and products than the linking method because

in BLS’ research, new models and products generally incorporated larger

price changes.

Class-Mean Adjustments According to BLS, the class-mean method is the designated method for item

strata where new models or product lines are introduced regularly. These

strata have included vehicles and apparel items if direct adjustments could

not be made; household appliances; and other household goods.

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The item that was substituted is put aside under the class-mean method in

computing price changes. Instead, to impute a price change, BLS selects a

subset of substitutions from the same item stratum and geographic

location as the original item. For example, if a price taker who tracks

prices in Urbantown substituted one refrigerator for another, BLS would

use this Urbantown stratum (refrigerators and home freezers) to compute

the price change rather than specific price information on the refrigerator

that the price taker reported. BLS has decided that the most appropriate

subset of substitutions for items involving new models or product lines are

(1) those that were not adjusted (i.e., those that were comparable) and

(2) those that were adjusted through a direct adjustment method. All of

the comparable and direct-adjusted substitutions within a stratum are to

be used. According to BLS, this subset of substitutions is the best

approximation of the pure price changes that come about with the

introduction of new models and product lines.

New class-means are computed each month, and the class-mean for a

particular item stratum is assigned, in effect, to all class-mean

substitutions in that stratum and location. For example, if the class-mean

for Urbantown’s refrigerators and home freezers stratum was an increase

of 10 percent and five class-mean substitutions to that stratum were made,

each of those substitutions would reflect a price increase of 10 percent. In

turn, that percentage would be used five times in computing the CPI index

for Urbantown for that particular month.

In 1997, the class-mean method accounted for about 33 percent of the

12,131 adjustments. One of those class-mean adjustments was for another

car substitution that we reviewed. The analyst knew that improvements

had been made to the 1998 model but did not have sufficient information

to make a direct quality adjustment. In this instance, the 1998 model cost

$14,408 while the 1997 model cost $14,010, a price change of 2.8 percent.

However, the class-mean method set aside this actual price increase and

imputed a price increase based on other new automobile models in the

same geographic area. There were 11 comparable and directly adjusted

new models (substitutions) in that geographic area for which BLS had

collected information. As these 11 models had increased in price by an

average of 4.0 percent, the price of the 1998 model was imputed to have

risen by 4.0 percent.

Appendix V provides more information about the class-mean method,

including examples that illustrate its use.

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Linking Method Adjustments According to BLS, the linking adjustment method is to be used when

neither a direct adjustment nor a class-mean adjustment can be made. BLS

has designated the linking method for item strata where new models or

product lines are not introduced fairly regularly, such as food items. It is

also the designated method for most services, such as medical services,

because, in BLS’ opinion, changes in the quality of services are difficult to

measure. The linking method was used for about 36 percent of the 12,131

adjustments made in 1997. It was used in nearly all of the nonrent item

strata in which an adjustment was made and accounted for a majority of

the adjustments in the food and beverage component of the CPI and the

medical care component.

As with the class-mean method, substitutions under the linking method are

put aside in calculating price changes for the month. Instead, a rate of

price change is imputed from the same item stratum and geographic

location as the original item. All items in the item strata with usable prices

are to be used to compute a weighted-average price change, which is

expressed as a percentage.16 BLS then, in effect, assigns this percentage or

rate of change to all linked adjustments in that item stratum and

geographic location for the month in which the calculation was made.

The linking method was used for a soup substitution that we reviewed. On

a per-ounce basis, the new package of soup cost 34.5 percent more than

the old package of soup. However, this price increase was set aside

because of differences in soup ingredients and package size. Instead, a

price increase of 0.6 percent was imputed under the linking method, based

on the items with usable prices in that item stratum and geographic region.

In addition to being used for linked substitutions, this method is also used

when a substitution is unacceptable and killed. According to BLS, when a

substitution is killed, an imputed rate of price change is assigned to the old

item (the item for which the killed substitution was going to replace), and

the same calculation that is used in the linking method is used for this

price change.

Appendix VI provides more information about the linking method,

including examples that illustrate its use.

16BLS defines items with usable prices as those for which (1) no substitutions were made,

(2) substitutions were made and no adjustments were necessary, and (3) substitutions were made and

then adjusted using a direct method. Items that do not have usable prices are those, for example, that

were temporarily unavailable for pricing because they were out of season.

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B-279259 

Description of How

Supervisors Review

Commodity Analysts’

Decisions

BLS relies on supervisors to review the substitutions decisions made by

commodity analysts. According to BLS, there are no guidelines or policies

in writing for supervisors to follow in selecting and reviewing the

decisions made by analysts. In practice, according to the BLS Branch Chief

for Consumer Prices, there is an unwritten policy that supervisors each

month are to review large price changes going into the CPI. When those

changes involve substitutions, the decisions made by commodity analysts

are reviewed. Few other adjustments are reviewed. BLS has no policy to

randomly or otherwise select and review substitution decisions.

According to BLS officials, supervisors and commodity analysts working

together set the levels of price change that trigger a review. These levels

can vary by item strata and can differ between price increases and price

decreases within a stratum. According to BLS officials, large price changes

are reviewed because they are the price changes that could have the

greatest impact on the indexes. BLS officials said BLS does not keep count

of the number of substitutions receiving supervisory review.

According to BLS officials, supervisors are to examine the reasons for the

analysts’ decisions for price quotations that produce large price changes.

The supervisors reported that they frequently did this by examining the

brief explanations that are printed on the price quotations lists that they

review. Commodity analysts write these explanations when they review

substitutions. If the supervisors are not satisfied with the explanations in

these messages, they are to ask the analysts to explain their decisions in

person. All the supervisors said that they usually accept the analysts’

explanations, either through the written explanations or in person.

Beyond the specific reviews performed by supervisors, BLS does not have a

program of assessing the decisionmaking patterns of commodity analysts.

However, BLS has studied the process by which commodity analysts make

decisions at least three times in the 1980s and early 1990s, and the studies

found that the decisionmaking process is susceptible to producing errors

and inconsistencies.

As explained by one study, substitution review is potentially prone to

(1) visual search errors, as commodity analysts locate information in

product descriptions; (2) comprehension errors, as they extract the

content of these descriptions; and (3) consistency errors, if they irregularly

apply a particular rule. In addition, according to the study, inconsistencies

may occur when one commodity analyst does the work of another

commodity analyst or when different commodity analysts use different

Page 21 GAO/GGD-99-84 Consumer Price Index
B-279259 

approaches to substitution of their product groups, resulting in different

products being treated in different ways. Each of the three studies

recommended actions intended to promote greater control over the

decisionmaking process to reduce the potential for errors and

inconsistencies. We found that BLS’ implementation of these

recommendations has varied, with action in most cases diminishing after

initial steps were taken. According to officials we interviewed, BLS now

takes the position that these controls are not required for experienced

commodity analysts.

Appendix III provides further information about how commodity analysts

decide whether to make adjustments and how supervisors review those

decisions.

Conclusions BLS faces a difficult task each month of collecting tens of thousands of

prices, reviewing those prices, computing the CPI, and ensuring its

accuracy in a timely manner. In this process, BLS commodity analysts

review the substitutions that price takers make each month for items they

cannot find. Substitutions are not inconsequential because BLS has

determined that they can have a significant impact on the CPI.

To account for substitutions, BLS has developed a set of procedures and

methods to determine whether a substitution is comparable to the item it

replaced and, if not, what adjustment to make for its inclusion into the CPI.

BLS depends on commodity analysts to make the decisions on whether

substitutions are comparable and, to a lesser extent, which adjustment

method to apply. By the very nature of the differences that can exist

between original and substituted items, commodity analysts must exercise

a degree of professional judgment in making decisions, more with some

substitutions and less with others. They make these judgments with little

or no written criteria to follow. In terms of review or quality controls,

supervisors review large price changes and rely on commodity analysts for

explanations for their decisions. Beyond these reviews, BLS has no

program to review commodity analysts’ decisions either preissuance or

postissuance of the CPI.

In the past, BLS has studied the process by which the commodity analysts

make decisions and found that the decisionmaking process was

susceptible to producing errors and inconsistencies. But BLS did not fully

act upon the recommendations that came from those studies; its actions

on most recommendations diminished after it took initial steps.

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B-279259 

We found no evidence to indicate whether errors or inconsistencies in

commodity analysts’ decisions or lack of comprehensive review of those

decisions has had a material effect on the calculation of the CPI. We are not

suggesting that the CPI is inaccurate. Indeed, any errors or inconsistencies

could be random in nature and in effect cancel each other out without

material effect on the CPI. However, prior BLS studies have noted that the

decisionmaking process was susceptible to producing errors and

inconsistencies—a situation that has not been remedied by sustained

corrective action. Given this susceptibility, it is a matter of sound

management practice to (1) periodically evaluate the degree to which

commodity analysts are actually making errors and inconsistent decisions

and (2) evaluate the material effects, if any, of errors or inconsistencies

upon the CPI. Moreover, the need for such management practices is

underscored by the significant uses made of the CPI in the public and

private sectors and the effect those uses can have on individuals and

businesses nationwide.

Recommendation To help ensure that the CPI is protected from potential effects of errors

and/or inconsistencies resulting from commodity analysts’ substitution

decisionmaking, we recommend that the Commissioner of BLS evaluate, on

a periodic basis, the degree of consistency and accuracy in analysts’

substitution determinations and the resulting effects on the CPI.

Agency Comments

and Our Evaluation

In a letter dated April 7, 1999, the Commissioner of BLS provided comments

on a draft of this report for the Department of Labor. The Commissioner

commented that our descriptions of the procedures will be useful to BLS

and to many CPI users. In discussing our recommendation, she said that

periodically evaluating the degree of consistency and accuracy in analysts’

substitution decisions and the resulting effects on the CPI was certainly a

desirable thing to do and that BLS would explore ways it could enhance its

existing review processes in that area.

The Commissioner mentioned several ways in which BLS could implement

the recommendation. The first two ways were to (1) evaluate

enhancements to the data used to monitor commodity analysts’ handling

of substitutions and (2) review the documention of commodity analyst

procedures to see if it could be made more complete. We agree that these

actions would represent good first steps but note that they would not

necessarily implement all the parts of our recommendation. For example,

more complete documentation of commodity analyst procedures could

Page 23 GAO/GGD-99-84 Consumer Price Index
B-279259 

improve the analysts’ consistency and accuracy but would not measure the

degree of consistency and accuracy.

A third way mentioned by the Commissioner was for BLS to consider the

possible use of “expert systems” software (i.e., computer software that

helps individuals make consistent and accurate decisions on complex

issues) to assist commodity analysts and enhance the consistency of their

decisions. BLS developed an expert software system several years ago,

which BLS did not subsequently implement for reasons the Commissioner

explains in her comments. BLS demonstrated this software to us. While we

have not evaluated such software, the demonstration to us showed that

such a system could help commodity analysts enhance the consistency of

their decisions. In addition, such a system might also help BLS to assess the

degree of accuracy in its decisions. However, BLS would have to develop

specific methods for using the data from an expert system to meet the

second part of our recommendation, which was to evaluate the effect of

the analysts’ decisions on the CPI.

The Commissioner’s letter is reprinted in appendix IX. She made

additional comments in her letter, which we addressed as appropriate in

appendix IX.

We are sending copies of this report to Alexis Herman, Secretary of Labor;

Katharine Abraham, the Commissioner of BLS; Patsy Mink, Ranking

Minority Member, Subcommittee on Criminal Justice, Drug Policy, and

Human Resources; and other interested parties. We will also make this

report available to others on request.

Page 24 GAO/GGD-99-84 Consumer Price Index
B-279259 

Major contributors to this report are listed in appendix X. If you have any

questions about this report, please call me on (202) 512-8676.

Laurie E. Ekstrand

Associate Director, Federal Management

 and Workforce Issues

Page 25 GAO/GGD-99-84 Consumer Price Index
Contents

Letter 1

Appendix I 

Additional

Information on Our

Methodology

30

Methodology Used to Select Examples, Substitution Decisions,

and Commodity Analysts

30

Survey Methodology 32

Appendix II 

Background

Information on the

Consumer Price Index

34

Construction of the CPI 35

Appendix III 

How Commodity

Analysts Decide to

Make Adjustments

41

Role of Commodity Analysts 41

Use of Commodity Review Listings 42

Process of Making Decisions About Substitutions 43

BLS Processes and Procedures for Reviewing Substitution

Decisions

53

Appendix IV 

Direct Adjustments

57

Manufacturers’ Costs 57

Example 1 - New Car (Under the New Cars Item Stratum) 62

Hedonic Regression Estimates 63

Example 2 - Woman’s Coat (Under the Women’s Coats and

Jackets Item Stratum)

68

Other Direct Adjustments 70

Example 3 - Season Ticket (Under the Admission to Sporting

Events Item Stratum)

72

Example 4 - Canned Soup (Under the Canned and Packaged Soup

Item Stratum)

73

Appendix V 

Class-Mean Method of

Adjustment

76

Background 76

How Price Changes Are Calculated With the Class-Mean Method 78

How Quality Improvements Are Accounted for in the Class-Mean

Method

80

Examples of BLS’ Use of the Class-Mean Method 81

Page 26 GAO/GGD-99-84 Consumer Price Index
Contents

Example 1 - Bedroom Linens (Under the Linens, Curtains,

Drapes, and Sewing Materials Item Stratum)

81

Example 2 - Woman’s Parka (Under the Women’s Coats and

Jackets Item Stratum)

83

Example 3 - New Car (Under the New Cars Item Stratum) 85

Appendix VI 

Linking Method of

Adjustment

88

Background 88

How Price Changes Are Calculated With the Linking Method 89

How BLS Accounts for Quality Change in Using the Linking

Method

90

Examples of BLS’ Use of the Linking Method 91

Example 1 - Packaged Soup (Under Canned and Packaged Soup

Item Stratum)

92

Example 2 - Multivitamin Tablets (Under Internal, Respiratory,

and Over-the-Counter Drugs Item Stratum)

94

Appendix VII 

Measurement of

Residential and

Homeowners’

Equivalent Rents

96

Background 96

Adjustments for Changes in Units 98

Adjustments Are Made by Computer and by Analysts 100

Addition and Deletion of Housing Units 104

Accounting for Quality Change 105

Examples of BLS’ Adjustments for Residential Rent and REQ 106

Example 1 - Automatic Adjustment 106

Example 2 - Pricing-Links-Cancel Adjustment 108

Example 3 - Links-Pause Adjustment 109

Appendix VIII 

CPI Price Quotations,

Substitutions, and

Methods of

Adjustment for 1997

112

Page 27 GAO/GGD-99-84 Consumer Price Index
Contents

Appendix IX 

Comments From the

Bureau of Labor

Statistics

153

Appendix X 

Major Contributors to

This Report

158

Related GAO Products 160

Abbreviations

BLS Bureau of Labor Statistics

CAL Commodity analyst listing

CEX Consumer Expenditure Survey

CRL Commodity review listing

CPI Consumer Price Index

CPI-U Consumer Price Index representing all urban consumers

CPI-W Consumer Price Index representing all urban wage earners

and clerical workers

ELI Entry level item

POPS Point-of-Purchase Survey

PPI Producer Price Index

PSU Primary sampling unit

REQ Homeowners’ equivalent rent

Page 28 GAO/GGD-99-84 Consumer Price Index
Page 29 GAO/GGD-99-84 Consumer Price Index
Appendix I 

Additional Information on Our Methodology

In our scope and methodology section, we explained how we obtained the

information necessary to describe the Bureau of Labor Statistics’ (BLS)

methods and procedures for reviewing substitutions. This work included

judgmentally selecting 13 examples of substitution decisions to illustrate

the methods. To select these examples, we discussed 136 substitution

decisions with 19 commodity analysts1

 in BLS’ Consumer Prices Branch.

This appendix explains how we selected these examples, substitution

decisions, and commodity analysts. We also explain how we administered

a questionnaire to BLS’ commodity analysts.

Methodology Used to

Select Examples,

Substitution

Decisions, and

Commodity Analysts

We judgmentally selected a small number of examples to illustrate the use

of BLS’ quality adjustment methods across the major components of the

Consumer Price Index (CPI). We discussed these examples with the

commodity analysts who had reviewed them and requested that the

analysts consult their supervisors about our selection. The analysts and

their supervisors agreed that the examples we had selected were broadly

representative of common situations that analysts encounter when

reviewing substitutions. Because substitutions for the nonrent items of the

CPI are very different from substitutions for rent items, we used different

procedures to select examples for each group.

For the nonrent items, we first obtained a selection of the commodity

review listings (CRL) that commodity analysts use when reviewing

substitutions and deciding whether an adjustment should be made. BLS

automatically generates a CRL each time a substitution is made, and these

lists are the main source of information about substitutions and the items

they replace. Because BLS made 28,881 substitutions for nonrent items in

1997, we limited our request to 2 months of CRLs. We requested CRLs for

substitutions in October and November 1997 because we wanted the most

recent months relative to when we began our work, so that the analysts

would be most likely to recall the reasons for which they had made their

decisions. According to BLS, 6,257 substitutions were made for nonrent

items in October and November 1997. BLS provided us with the CRLs for

substitutions that had been made in the priced, nonrent item strata of the

CPI during those 2 months.2

To arrive at a small number of illustrative examples from the 6,257 nonrent

substitutions, we made a series of selections to reduce the number of

1

In one instance, the analyst responsible for the item strata was no longer employed by BLS. However,

the analyst’s supervisor discussed the substitutions with us.

2

According to BLS data, there were 204 nonrent item strata, of which 181 were priced.

Page 30 GAO/GGD-99-84 Consumer Price Index
Appendix I 

Additional Information on Our Methodology

substitutions we were considering. First, we selected 18 of the 181 nonrent

priced item strata for an in-depth review. We made our initial selection by

item strata because the CRLs were organized by item strata and because BLS

makes its decisions on which adjustment methods to apply by item strata.

We judgmentally selected these item strata to ensure that we covered

(1) all of BLS’ direct and indirect adjustment methods and (2) all the major

components of the CPI with the exception of the other goods and services

component.3

 The major components of the CPI that we covered were food

and beverages, apparel and upkeep, housing, transportation, medical care,

and entertainment. In a few instances, our selection of the item strata was

influenced by the opinions of experts we had interviewed. For example,

we included poultry items because an official at the Department of

Agriculture had suggested that poultry would be interesting to study

because of recent developments in the ways it was cut and packaged. Our

selection of 18 item strata contained 1,212 substitutions.

Having made this selection of 18 item strata, we examined the CRLs for

these strata and selected a number of them for discussion with the

commodity analysts. We selected CRLs that appeared to illustrate the

adjustment methods used in each item stratum. We based our selection on

(1) the number of substitutions and types of adjustments that were made

in each item stratum and (2) preliminary discussions with commodity

analysts.4

We met with the 9 commodity analysts and 1 supervisor who were

responsible for the 18 item strata and had detailed discussions with them

on 106 CRLs. BLS assigns commodity analysts to particular item strata and,

therefore, one analyst reviews all the substitutions in an item strata. We

discussed the selected CRLs with the analysts and also asked them to

explain the procedures they normally follow when reviewing substitutions.

After these interviews, we judgmentally selected 10 nonrent substitutions

to serve as illustrative examples for this report. These examples cover the

six major components of the CPI. They also cover comparability decisions

3

The “other” component was a miscellaneous collection of other items that did not fit into the other

major categories of the CPI. It consisted of items such as personal-care appliances and services, school

books, and day-care services. The “other” component had fewer than 100 of the 6,257 substitutions

that occurred in October and November 1997.

4

We conducted some preliminary discussions to obtain an idea of what analysts do, so that we would

be better able to later hold discussions with the analysts responsible for the 18 item strata. For these

preliminary discussions, we simply picked out a few CRLs—25 in 6 additional item strata—that looked

as if they would be useful to talk to analysts about (e.g., involved the various adjustment

methods)—and then discussed them with the responsible analysts. These 25 substitutions are included

in the 136 we report that we conducted. We used information on 2 of these 25 substitutions in the

letter portion of this report.

Page 31 GAO/GGD-99-84 Consumer Price Index
Appendix I 

Additional Information on Our Methodology

and BLS’ direct and indirect adjustment methods. We did not include an

example of the only other method that was used, the overlap method,

because it was used for less than 100 of the 28,881 substitutions and is

being phased out, according to BLS officials. We selected our examples to

meet the following criteria: (1) it reflected a common pattern of

decisionmaking in that item stratum or item strata, (2) it lent itself to a

straightforward description, (3) it was not atypical or unusual in any way,

and (4) it did not contain errors made by the analysts. To ensure that our

selections did indeed meet these criteria, we showed our examples and

criteria to the analysts and their supervisors; and we asked them if our

examples were good illustrations of their decisionmaking in those strata,

and if the examples met the criteria. The analysts and their supervisors

agreed this was the case.

In addition to the 18 nonrent item strata, we also covered 2 rent item

strata: residential rent and homeowners’ equivalent rent. The procedures

used to make adjustments in these item strata differ from those used

elsewhere in the CPI. See appendix VII for information about these

adjustments.

The procedures we used to select CRLs as illustrative examples for the rent

item strata differed from those we used in the nonrent item strata. We

randomly selected one example for each of the three main methods of

adjustment used in the rent strata. We discussed these examples with the

commodity analysts and their supervisor for the rent strata; and, when the

analysts and/or their supervisor noted that the initial selections were

atypical or problematic, we randomly selected alternative examples. In all,

we discussed five rent item CRLs with four commodity analysts and their

supervisors.

To select the examples, we discussed 120 specific substitutions (115

nonrent plus 5 rent substitutions) with 19 commodity analysts (15 nonrent

plus 4 rent commodity analysts). In addition, we discussed 16 nonrent

substitutions with one nonrent supervisor. Following these discussions,

we selected 13 substitutions (10 nonrent plus 3 rent substitutions) to serve

as illustrative examples in this report.

Survey Methodology To gain a better understanding of the processes the commodity analysts

follow when making substitution decisions and their educational and

professional backgrounds, we asked them to complete a written

questionnaire. We divided the commodity analysts into two groups: those

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Appendix I 

Additional Information on Our Methodology

who review residential rent and those who review all nonrent items in the

CPI. The analysts who review residential rent follow different procedures

than the others; therefore, they could not be asked all the same questions.

All four residential rent analysts, as of September 1998, responded to a

limited version of this survey. All 24 individuals who were nonrent

analysts in October and November 1997 and were still analysts in

April 1998 responded to our full survey. Three nonrent supervisors, who

also had some responsibilities for deciding whether to make substitution

decisions and adjustments, also responded.

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Appendix II 

Background Information on the Consumer

Price Index

BLS produces the CPI by measuring the average change over time in the

prices paid by urban consumers for a fixed market basket of consumer

goods and services. The selection of items for the market basket is

determined from detailed records of purchases made by thousands of

individuals and families, as reported on periodic surveys. The items

selected for the market basket, such as potatoes, are to be priced each

month at specific retail outlets, such as grocery stores and supermarkets,

in urban areas throughout the country. According to BLS, in 1997, price

takers collected the prices of about 94,000 items (goods and services) in 85

urban areas of the country. These prices were collected from about 30,000

retail and service establishments and from about 46,000 landlords and

tenants, who provided data on housing units.

The CPI is used as a measure of price changes to make economic decisions

in the private and public sectors. According to BLS, the CPI has three major

uses indicated as follows:

Economic indicator of inflation. The administration, Congress, and the

Federal Reserve use trends in the CPI as an aid to formulating fiscal and

monetary policies. Business and labor leaders as well as private citizens

use the CPI as a guide to making economic decisions.

Escalator for wages, benefit payments, and tax brackets. The CPI is used by

collective bargaining units to adjust the wages of workers. Also, it is the

basis for automatic changes in some federal benefit payments. For

example, in December 1997, as a result of changes in the CPI, 44 million

Social Security beneficiaries and 6.5 million Supplemental Security Income

recipients had their benefits adjusted for inflation. More than 21 million

food-stamp recipients in 1997 were affected by changes in the CPI.

1

 Also,

millions of railroad, military, and federal civilian retirees and survivors are

affected by changes in the CPI. The CPI is also used to adjust key elements

of the individual income tax to limit the extent to which individuals must

pay higher taxes solely because of inflation. For example, the amount

allowed for personal exemption, the amount of the standard deduction,

and tax brackets are adjusted annually according to changes in the CPI.

Deflator of selected economic statistical data series. The CPI is used to

adjust selected economic statistical series for price changes and to

translate these series into inflation-free dollars. Examples of data series

1

The federal expenditure estimates given on page 1 of this report do not include the food stamps

program or the school-lunch program because these programs are affected by the “food away from

home” CPI subindex, whereas the other programs use the overall CPI that includes all items.

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Price Index

that are adjusted by the CPI include retail sales, hourly and weekly

earnings, and components of the National Income and Product Accounts.

The CPI was initiated during World War I, when rapid increases in the

prices of goods and services, particularly in shipbuilding centers where

workers were demanding wage adjustments, made such an index essential

for calculating cost-of-living adjustments. In 1921, BLS began regular

publication of an index representing the expenditures of urban wage and

clerical workers, which was then called the Cost-of-Living Index. The

name of the index was changed to the CPI following controversy during

World War II over the index’s validity as a measure of the cost of living.

According to BLS, the CPI has always been a measure of the changes in

prices for goods and services purchased for family living.

Major revisions were made to the CPI about once each decade to update

the fixed market basket, with the most recent revision occurring in

January 1998. Because consumers’ buying habits change, new studies were

made of what goods and services consumers were purchasing, and major

revisions to the CPI were made in 1940, 1953, 1964, 1978, and 1987 as well

as 1998.2

 In the 1978 major revision, BLS began publication of a new index

for all urban consumers—the CPI-U. According to BLS, the CPI-U, which

represents the expenditures of about 87 percent of the population, takes

into account the buying patterns of professional employees, part-time

workers, the self-employed, the unemployed, and retired people as well as

those previously covered in the CPI. BLS has continued publication of the

older index, the CPI-W, which represents the expenditures of urban wage

and clerical workers or about 32 percent of the population.

Construction of the

CPI

Construction of the CPI begins by selecting a collection of goods and

services that is usually bought by the reference population in the index.

The collection of goods and services, called items, is known as the market

basket. The CPI market basket is developed from detailed expenditure

information that is provided by thousands of families and individuals who

participate in the Consumer Expenditure Survey (CEX), which is conducted

for BLS by the Bureau of the Census over several years. For example, the

1987 CPI revision was based on CEX data collected from 1982 through 1984,

2

For this report we reviewed item substitutions that BLS made during October and November of 1997.

At that time, the last major revision to the CPI was in 1987. Therefore, the information contained in

this report is based on the CPI structure for the 1987 revision rather than the 1998 revision. Although

there were changes between the 1987 and 1998 revisions, the general steps BLS follows to construct

the CPI described in this appendix did not change between the two CPI revisions.

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Appendix II 

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Price Index

from about 29,000 individuals and families.3 Expenditure data from the CEX

are used to select the categories of items from which specific, unique

commodity and service items are selected to be priced for the CPI.

BLS measures price changes each month by checking the prices of the

items in the market basket and then comparing the aggregate costs of the

market basket with those for the previous month. BLS price takers obtain

prices for most of the items by visiting or contacting thousands of

retailers, service providers, and landlords and tenants each month.

Classification of Market

Basket Items

BLS classified all CEX expenditure items for the 1987 CPI revision into 206

item strata, which are arranged into 7 major components:4

 (1) food and

beverages; (2) housing; (3) apparel and upkeep; (4) transportation;

(5) medical care; (6) entertainment; and (7) other goods and services, such

as haircuts, college tuition, and bank fees. Taxes that are directly

associated with the prices of specific goods and services, such as sales and

excise taxes, are also included.5

The 206 item strata are divided into specific subcategories, which are

called entry level items (ELI). For example, item stratum 0101 flour and

prepared flour mixes has two ELIs: flour (01011) and prepared flour mixes

(01012). All item strata have at least one ELI, and some strata have more

than one. Appendix VIII lists item strata and related ELIs.

Expenditure Weights of

Market Basket Items

Expenditure weights are used to give proportionate emphasis for price

changes of one item in relation to other items in the CPI. Expenditure

weights allow the CPI to distinguish between items that have a major

impact on consumers and to provide appropriate emphases to price

changes associated with these items. For example, if ground beef were

assigned a weight representing about one-third of 1 percent of the

expenditures of the typical urban consumer and if sirloin steak were

assigned a smaller weight representing less than one-tenth of 1 percent,

3

The 1998 CPI revision was based on CEX data collected from 1993 through 1995, from about 36,000

individuals and families.

4

In the January 1998 revision, the major categories changed from seven to eight and include food and

beverages, housing, apparel, transportation, medical care, recreation, education and communication,

and other goods and services. The number of item strata also changed from 206 to 211.

5

The CPI includes various governmental-charged user fees, such as water and sewerage charges, auto

registration fees, and vehicle tolls. Taxes not directly associated with the purchase of consumer goods

and services, such as income and Social Security taxes, are excluded. In addition, the CPI does not

include investment items, such as stocks, bonds, real estate, and life insurance because they relate to

savings, not daily living expenses.

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Appendix II 

Background Information on the Consumer

Price Index

then the price changes of ground beef would have about 3 times as much

impact on the overall CPI as similar price changes for sirloin steak.

Weights derived from consumers’ expenditures, as reported in the CEX, are

assigned to the 206 item strata. To compute the weights, BLS first totals the

amount spent on an item stratum, such as white bread, during the base

weighting period by CEX respondents, who BLS refers to as consumer units.6

BLS then divides that total by the number of consumer units, which results

in an average expenditure per unit. Next, the average expenditures per

unit are weighted with data from the decennial census to represent the

U.S. urban population. To do so, the average expenditures per unit are

multiplied by certain factors to represent the geographic dispersion of the

urban population. Finally, these nationwide urban expenditures on the

market basket items are totaled into an aggregate amount. The 206

expenditure weights are the percentages of this aggregate amount that are

spent on each of the 206 item strata (e.g., white bread).

Expenditure weights remain fixed until the next major revision of the CPI

and serve as a benchmark from which price comparisons are calculated.

The weights of the components for the 1987 major revision are those that

have derived from the 1982 through 1984 CEX.

Relative Importance of

Market Basket Items

Relative importance is related to, but not the same as, expenditure

weights. Relative importance can be used to show the direct effect an item

has on the overall CPI price change because it shows the share of total

expenditure that would occur if consumed quantities of the items remain

constant. Although the expenditure weights remain fixed until a major

revision, which had occurred about every 10 years, the relative importance

changes over time, reflecting the effect of price changes.

Expenditure weights equal the relative importance percentages at the time

of a major revision. But since BLS maintains the quantities of the items as

the same amounts that were consumed in the base period, the relative

importance percentages change as a result of changing prices. Items

registering a greater-than-average price increase become relatively more

important. Conversely, items registering a smaller-than-average price

increase become relatively less important. Therefore, as the time between

major revisions increases, items with higher-than-average rates of inflation

have increasing rates of influence upon the CPI. As shown in figure II.1, the

6

The CEX collects data from “consumer units,” which are defined by BLS as either financially

independent, unrelated individuals or groups of individuals who pool their resources to make joint

consumption decisions.

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Appendix II 

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Price Index

relative importance of medical care in the index for all urban consumers,

which was 5.7 in December 1986, increased to 7.4 in December 1997

because medical prices increased at a greater rate than the rate for the all

items CPI—the overall CPI. During the same period, the relative importance

of apparel and upkeep fell from 6.3 percent to 5.3 percent because apparel

and upkeep prices increased at a lower rate than the all items CPI.

Figure II.1: Relative Importance of

Components in the CPI-U, 1986 and

1997

Percent

0

10

20

30

40

Housing

Transportation

Food and beverages

Apparel and upkeep

Other goods and services

Medical care

Entertainment

1986

1997

Source: BLS.

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Price Index

Collecting Prices of Market

Basket Items

Each month, BLS price takers visit or call thousands of retail stores, service

establishments, rental units, and doctors’ offices all over the United States.

Each month, they record the prices of about 80,000 items.7

To determine which retail outlets its price takers should visit to obtain

monthly price quotations for nonrent items, BLS sponsors the

Point-of-Purchase Survey (POPS), which is conducted by the Bureau of the

Census. The survey respondents are asked, by item categories such as

doctors, whether they made specific purchases and, if so, the names and

locations of all places of purchases and the expenditure amounts. BLS uses

the results from the survey to select outlets for pricing.

BLS price takers visit each selected retail outlet to initially select items that

will be priced either monthly or bimonthly. For each outlet, categories of

items are selected for pricing. Using probability selection methods that are

based on revenues and volume information that is provided by the retail

outlet, BLS price takers use a table of random numbers to select for pricing

a unique item within the specified categories.

BLS collects rent prices for rental units in a different manner than that used

to identify and price other items in the market basket. BLS uses monthly

price changes of rental units in the CPI housing survey for the residential

rent and homeowners’ equivalent rent items in the CPI housing component.8

Residential rent and homeowners’ equivalent rent are estimated from

approximately 36,000 rented units and 26,000 owned units in the survey.

Each month, BLS price takers obtain information from renter units on the

rent for the current month, the previous month, and the services that the

landlord provides. These data are used to measure changes in rent prices

for residential rent as well as homeowners’ equivalent rent. (For detailed

information about this process see app. VII).

Replacement of Market

Basket Items No Longer

Available for Pricing

Because the CPI uses a fixed market basket of goods and services, BLS price

takers are instructed to collect price information for the same item (e.g.,

one dozen pink carnations, with greenery, wrapped in paper, and not

delivered) each time they visit the retail outlet or rental unit. However, in

many instances, the same identical item is not available for purchase in

each subsequent visit. In these situations, price takers are to follow certain

7

Prices are not collected monthly on all items in the CPI. Some are collected bimonthly and rent is

collected every 6 months for housing units.

8

BLS determines the value of owner-occupied housing by using a rental equivalent method, which

estimates the amount of rent that would be paid if it were rented.

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Price Index

procedures to make a substitution—selection of a new version

(replacement) that is similar to the old version of the item that is no longer

available.9 BLS has different procedures for the price takers to follow to

bring into the CPI new products or services from the POPS that are not

substitutions for items that are in the fixed market basket.

In selecting a substitution the price takers are to follow specific guidance

for choosing the new version. In general, the price taker is to select the

item with specifications most consistent with the old version. After the

price taker selects a new version and records the information about the

item, the information is sent to BLS headquarters in Washington, D.C.,

where it is coded, entered into computer systems, verified, and examined

by commodity analysts for inconsistencies. Appendix III describes further

the procedures commodity analysts are to follow in examining

substitutions.

9

As described in appendix VII, price takers in the CPI housing survey return to the same address in

each collection period and record information about the residential unit at that address. Substitutions

do not take place between residential units as they do elsewhere in the CPI. However, as described in

appendix VII, adjustments are made to make the current unit similar to what it was at the prior price

collection.

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Appendix III 

How Commodity Analysts Decide to Make

Adjustments

Commodity analysts review information collected by the price takers and

judge whether the substitution (new version) is an acceptable replacement

for the item that disappeared (old version) and, when acceptable, whether

it is comparable—similar—to the old version. Where versions are not

comparable, the analysts then select a method of adjustment. When the

substitutions have large price increases or decreases, supervisors review

the outcomes of the commodity analysts’ decisions.

According to BLS, the analyst’s knowledge and judgment about the

comparability of the two versions is very important because the analyst’s

decision determines the rate of price change that will be used in

computing the CPI. BLS further states that bias can enter the index if

substitutions are not carefully reviewed by commodity analysts.

This appendix provides information about (1) BLS’ procedures and

practices that are used by the commodity analysts to make their decisions

for substitutions of nonrent commodities and services and (2) the review

of those decisions by supervisors. (See app. VII for information about the

measurement of residential rent and homeowners equivalent rent.)

Role of Commodity

Analysts

According to BLS, when receiving the price information that was collected

by the price takers and entered into BLS’ computer system, the commodity

analysts—who are to have detailed knowledge about the particular goods

or services—check the data for completeness, accuracy, and consistency.

For example, if there are accuracy questions, analysts are to obtain a copy

of the form used by the responsible price taker to record price data to

verify that the actual collected values were captured in the system. The

analysts then make any necessary corrections. Analysts make adjustments

for changes in quality between new and old versions of a product or

service. They also make adjustments for differences not necessarily

related to quality. For example, they make adjustments to correct for

errors, to account for differences in size or quantity between new and old

versions, and to account for substitutions that, although acceptable, are

dissimilar to the items replaced (e.g., a pizza pan for a pie pan).

BLS describes commodity analysts as economists responsible for validating

and analyzing price data and for explaining short-run and long-run price

trends. Each analyst is responsible for specific item strata (e.g., the

commodity analyst for the pork item stratum would be responsible for

bacon, pork chops, ham, and other pork items, including sausage). The

analysts are expected to learn as much as they can about the items and the

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Appendix III 

How Commodity Analysts Decide to Make

Adjustments

consumer markets assigned to them. Drawing on that knowledge and

considering item-specific information supplied by price takers, commodity

analysts decide whether and how certain price information will be used in

computing each month’s CPI.

As part of our study of the procedures BLS follows to handle substitutions

and make adjustments, we collected information from 24 commodity

analysts about their educational and professional backgrounds and their

job responsibilities. The 24 analysts completed a questionnaire we gave

them in April 1998. The survey included all 24 individuals who had been

commodity analysts in October and November 1997 (the months in which

the substitutions we reviewed were made) and who were still commodity

analysts in April 1998.1

Nearly all of the commodity analysts (22 of 24) reported that they had

college degrees, with most of them reporting a bachelor’s degree and a

major in economics. They varied in terms of job experience from 1 to 27

years as a commodity analyst, 11 years was the median. As a commodity

analyst, they also varied from 1 year to 27 years working in the same

principal item strata, 9 years was the median.

Commodity analysts have a number of responsibilities, we were told in the

survey. The analysts reported that they spent the most time reviewing

price quotations, which include substitutions. The median amount of work

time they reported spending on these reviews was about 40 percent. The

commodity analysts generally said they research the industries in the item

strata for which they had responsibility and developed and modified the

forms that price takers use to collect price quotes. Some analysts reported

doing statistical analyses to develop regression models. In 1997, the

commodity analysts also had to prepare for the January 1998 revision of

the CPI.

Use of Commodity

Review Listings

The primary tool used by commodity analysts in the process for reviewing

changes in products and services is the commodity review listing (CRL).

After the data have been collected by the price takers and entered into BLS’

computer system, CRLs are generated for review by commodity analysts.

CRLs are computer printouts of data, such as the characteristics and price

history, on items meeting certain conditions. CRLs are generated when

1

These 24 commodity analysts reviewed nonrent substitutions, which are the subject of this appendix.

In addition to these 24 analysts, we later surveyed the 4 commodity analysts who were reviewing rent

data as of September 1998. These four analysts all had college degrees and had worked 2 to 14 years as

commodity analysts.

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Adjustments

conditions indicate a substitution (e.g., item was reported as a substitution

by the price taker) and for conditions having nothing to do with

substitutions.

Among the data CRLs list for an item are the item’s specifications, which

show various characteristics of the item, such as the packaging (e.g., 12

pack), container construction (e.g., metal can), and caffeine content of

cola drinks. If the CRL is for an item that the price taker identified as a

substitution, it includes the specifications for both the substitution and the

item it replaced. Specifications that changed from the prior price

collection are specially noted for the commodity analyst, and all

specifications are listed according to a hierarchy of importance for judging

the comparability of the two versions. For example, in the “canned fish or

seafood” entry level item (ELI), the order of importance is type (e.g.,

salmon), followed by variety (e.g., pink), and then form (e.g., solid),

thereby signaling that type and variety are more important than form of

the canned seafood in making comparability decisions. In some apparel

ELIs, the specifications are grouped by order of importance into three tiers

to guide the price takers in making substitutions and commodity analysts

in making their decisions about the substitutions.

Process of Making

Decisions About

Substitutions

According to BLS officials, the process through which commodity analysts

make their decisions about substitutions begins when the commodity

analyst receives CRLs. CRLs are generated for substitution review usually

for one of two conditions: (1) the item was reported as a substitution by

the price taker or (2) a change occurred to a key specification, although

the item itself was not reported by the price taker to be a substitution.

According to BLS, there may be a change or modification to an item being

priced, such as a change in color, that does not warrant substitution. BLS

refers to such changes as specification corrections. However, BLS

computers are programmed to identify changes in specific characteristics;

and, when any of the key specifications change, a CRL will be printed for

substitution review by the commodity analyst.2

The general process for making substitution and adjustment decisions is

illustrated in figure 1 in this report, and includes a series of questions that

2

Some changes, however, will not generate a CRL for substitution review. According to BLS,

commodity analysts have identified the specifications that when changed are least likely to cause the

item to be classified as a substitution.

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Adjustments

analysts answer in determining how best to deal with substitutions.3 We

note, however, that the process is not followed in all cases because many

analysts have some leeway in the process as a result of special

circumstances related to their respective item strata. The process

description that follows is based on our interviews of commodity analysts,

their supervisors, and BLS managers. This process has not been thoroughly

documented by BLS.

Determining Whether

Substitutions Were

Identified

According to BLS officials, the commodity analysts review CRLs. For the

price quotations that the price takers identified as substitutions, the

analysts determine whether the price takers appropriately identified them

as substitutions. For price quotations that the price taker did not treat as

substitutions, the analysts determine whether these should be classified as

substitutions.

According to the BLS officials, the majority of CRLs reviewed for

substitutions are those identified as such by the price takers. Based on the

specifications for an item that the price taker reported, the commodity

analyst may decide that the price taker inappropriately identified an item

as a substitution; in that case, the CPI will treat it as if there were not a new

version. The price-taker-identified substitutions that the commodity

analysts deem appropriately identified go to the next stage of substitution

processing.

For items that have changed in characteristics but were not identified as

substitutions by price takers, the commodity analyst can reclassify them

as substitutions by “upping the version.” The commodity analyst uses the

changes in specifications and, to a limited extent, the price to judge

whether the modification in the item was a significant change. The

commodity analyst reclassifies an item as a substitution by making the

item priced in the current month a new version and making the item

priced in the previous collection period the old version. By doing so, the

commodity analyst converts the item into an acceptable substitution.

Determining Whether a

Substitution Is Acceptable

According to BLS officials, when the commodity analysts review the CRLs,

they determine if the price quotation that the price taker identified as a

3

The decisions leading to the application of the overlap method are not included in the figure or in this

appendix because, according to a BLS official, this method was used for a small number of

substitutions in 1997. BLS estimated that at least 77 substitutions were adjusted with this method in

1997. In addition, BLS was phasing out the use of this method of adjustment for substitutions at the

time of our study.

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Adjustments

substitution is eligible for use in the CPI. In 1997, commodity analysts

determined that 28,881 price quotations that they reviewed were

acceptable substitutions for use in the CPI. This number excludes price

quotations for rent.

If in the analyst’s opinion it is not an acceptable substitution, the new

version is “killed” or deleted by the analyst. In these instances, the price

taker in the next collection period must select another replacement for the

item that disappeared. A BLS official said that the reasons for killing a

substitution included when

• the new version is out of scope (outside the definition of possible

substitutions in the item’s ELI);

• the substitution occurred outside of the time frame for making a

substitution for an item that has been designated by BLS as a “seasonal”

item, such as substituting a spring or summer raincoat for a fall or winter

coat;

• the commodity analyst waits to see if the old version is only temporarily

unavailable in the outlet. The commodity analyst bases this decision on

knowledge of the item and its price history;

• the commodity analyst, using industry and item knowledge, believes that

the price taker did not follow selection criteria to find the closest

substitution to the item that disappeared; and

• the specifications recorded by the price taker for the new version are

unclear or incomplete.

When a substitution is killed, it is deleted and is not used in the CPI and an

imputed price is assigned to the item that disappeared.4

 The imputation for

a killed substitution is the same as that used in the linking method (see

app. VI). That is, a rate of price change is calculated based on other similar

items that were priced in the killed substitution’s item stratum and

geographic location. The calculated rate of price change is applied to the

previous price of the item that disappeared, and the imputed price for that

item will be used to calculate the CPI in the next collection period.

BLS was unable to provide us with the number of substitutions that were

killed in 1997. However, BLS reported that over 12 months from October

1997 through September 1998, 1,065 substitutions were killed. Since killed

substitutions are not regarded as substitutions by BLS, they are not

reflected in any of the tables presented in this report.

4

Imputed price is a term used by BLS to indicate that the actual price of the substitution is not used.

Instead, an average is calculated from the price changes experienced that month by similar items in

the CPI to handle a missing or unusable price quotation.

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Determining the Need to

Make an Adjustment

According to BLS officials, after substitutions are accepted, they go through

additional steps to determine if adjustments are necessary to account for

differences between them and the items they replaced. The first

determinations after acceptance, we found, depend on a substitution’s

item stratum and the nature of any difference between the two versions. If

the substitution is in an automobile or apparel stratum where information

about the value of the differences is available to make a direct adjustment,

the commodity analysts are likely to consider whether to make a direct

adjustment. This is also the case, regardless of stratum, if the analyst is

correcting a past recording error or making adjustments to account for

changes in the size of a product or in the number of items.

If a direct adjustment cannot be made, then another set of processes

comes into play regardless of item stratum. In this case, the first question

usually asked is whether the two versions of the item are

comparable—similar.

Determining Whether a

Substitution Is Comparable

When the analysts determine that the new version is comparable to the old

version, no adjustment is made; and the ratio of the new version’s price in

the current period to the old version’s price in the previous period is used

in the calculation for the CPI for that month. This process is similar to the

way the CPI calculation uses the ratio of current-period price to the

previous-period price of items in the CPI that were not substitutions. In

1997, of the 28,881 nonrent substitutions reviewed by commodity analysts,

16,750, or 58 percent, were determined to be comparable without

adjustments. The rate of comparability differed among the CPI’s seven

components, with the highest rate in the apparel and upkeep component

(67 percent) and the lowest rate in the medical care component

(32 percent).

BLS uses computer codes—called comparison codes—to control the way a

CPI price change calculation handles a price quotation. BLS’ computers are

programmed to generate comparison codes to provide the commodity

analysts an initial basis for making their comparability decisions. Based on

the degree of difference between the “effective” prices of the old and the

new versions, one of three comparison codes appears on the CRLs. An

effective price is the price taker’s reported price that is adjusted, if

appropriate, for the size of the item, such as price per ounce of a food

item. If the price change, which is expressed as a percentage, is within a

specified interval,5

 then BLS’ computers are programmed to generate a

5

The upper and lower levels of these tolerance intervals are determined by the respective commodity

analysts and their supervisors.

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Adjustments

code indicating that the two versions are comparable. However, if the

difference in effective prices is outside the specified interval, then the

computer generates either one of two adjustment codes (class mean or

linking) signaling that the versions may not be comparable. In our survey

of commodity analysts, how often the analysts agreed with the

computer-generated codes varied widely. The range of agreement was

from 25 percent to 100 percent of the CRLs reviewed for substitutions that

were made in calendar year 1997, 70 percent agreement with the codes

was the median.

In the limited number of ELIs that we studied, most commodity analysts

did not have written comparability criteria to guide them in making their

decisions. But a few food commodity analysts showed us criteria that they

had developed with their supervisors for specific ELIs to help them decide

whether substitutions are comparable. The analysts used these criteria as

guides to identify the characteristics (shown as specifications on the CRL)

that, if different between the old and new versions, indicated that the new

version was not comparable to the old version. For example, if a can of

sardines replaced a can of salmon, the analyst would determine that the

two versions were not comparable.

These comparability criteria also identified the specifications that were

less important in deciding comparability. That is, the old and new versions

might differ with regard to these characteristics, but that condition would

not usually warrant a decision of not comparable. For example, if the

change between two cans of salmon was only the origin (e.g., from

imported to domestic), the analyst most likely would determine that the

two versions were comparable.

Regardless of whether comparability criteria were available, all of the

commodity analysts we interviewed indicated that they examine the

specifications on the CRLs for substitutions and decide if the differences in

the characteristics indicate a difference in quality between the old and

new versions. If the commodity analysts determine that the differences do

not indicate a major change in quality, they said they would leave the

comparison code for the substitution as comparable or code the

substitution as comparable if a different code was assigned by the

computer.

Comparable Substitution

Decision

The following example of a comparable substitution decision comes from

our interview with a commodity analyst’s supervisor. According to the

supervisor, this example is illustrative of an analyst’s comparability

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decisions for this ELI and shows an analyst’s decision when it is fairly easy

to make.

The example includes a price calculation, showing the percentage change

in price that went into the CPI for that month as a result of no adjustment

being made. This percentage change in price is applicable only to the

particular case illustrated. It is not intended to be representative of the

percentage change in price that occurred for similar kinds of comparable

substitutions. Nor is the percentage of change intended to be

representative of the impact on the CPI of not making an adjustment.

The example includes (1) a table showing the specifications of the old

version and the new version that replaced it (differences in the

specifications between the old and new versions are highlighted by

shading), (2) the analyst’s reasons for judging the two versions to be

comparable, and (3) the calculation of price change that was made for use

in the CPI calculation.

Example - Club Membership

(Under the Club Membership

Dues and Fees Item Stratum)

A new version of club membership was substituted for the old version and,

as shown in table III.1, the “level of membership” differed. The analyst

concluded that the two versions were comparable even with the difference

in type of membership.

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Table III.1: Characteristics of Two

Tennis Club Memberships Description Old version New version

Specifications

Type of enrollment Family Family

Type of member Existing Existing

Level of membership Tennis plus Gold tennis

Length of period covered Per month Per month

Type of organization Health club Health club

Bathing facilities Yes Yes

Towels Yes Yes

Pool Yes Yes

Exercise facilities Yes Yes

Lessons Yes Yes

Other clarifying data Husband, wife, and 2 

children

Husband, wife, and 2 

children

Price information

Amount $148.00 $150.00

As of September October

Collected/imputed Collected Collected

 Specifications that differ between old and new versions

Source: BLS.

Analyst’s Reasons for

Comparable Decision

A field message from the price taker informed the commodity analyst that

the level of membership had not changed. To confirm the field message,

the analyst reviewed the other specifications and found no changes except

for a $2 increase in price. Accordingly, the analyst determined that this

was a comparable substitution.

Calculation of Price Change The calculation of price change for comparable substitutions is done

entirely by computer routine without direct involvement by commodity

analysts. For this item the computer calculated a 1.4 percent rate of

change for October 1997, and the CPI in October reflected the same

percentage increase for this tennis club membership, as it would have

done if the name of the membership level had not changed.

Directly Adjusting for

Differences

According to BLS officials, the commodity analyst, after deciding that the

substitution is acceptable and in conjunction with the comparability

determination, will determine if information is available to do a direct

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adjustment. If the information is available, the commodity analyst is to

make a direct adjustment.

Because the information is often available, direct adjustments are

commonly made for automobiles and most apparel items. BLS works with

automakers each year to obtain information on improvements made to

new vehicles and the costs of those improvements. Also, BLS has built

statistical models to help it value the various features of most apparel

items.

Commodity analysts also make direct adjustments to correct errors and to

account for changes in an item’s size or quantity. For example, a direct

adjustment may be made for a change in the number of events covered by

a season ticket. These kinds of adjustments are not limited to any one

stratum or group of strata, and the information to make them is usually

available from the CRL. BLS does not consider adjustments made only to

correct an error or account for a change in size or quantity to be true

adjustments for quality.

In 1997, of the 28,881 substitutions, 3,770, or 13 percent, were directly

adjusted by commodity analysts. As appendix VIII shows, the majority of

these direct adjustments were for automobile and various apparel items.

The adjustment amount is applied to the price of the old version. Then the

adjusted price of the old version is compared with the price of the new

version and the change, if any, expressed as a percentage, goes into

calculating the CPI. Appendix IV further describes direct adjustments.

Making Direct Adjustments to

Increase Comparability

Previously, we said commodity analysts compared old and new versions of

items to determine whether they were comparable. When analysts working

with automobile and apparel substitutions make these comparisons, they

do so with a different twist from those working with other substitutions.

The analysts we interviewed who reviewed automobile and apparel

substitutions said that they may consider the new and old versions of an

item to be essentially comparable but will still make a direct adjustment.6

In these cases, the analysts said, the adjustments are relatively minor and

are made to increase the already high level of similarity between the old

and new versions. For example, an apparel commodity analyst said that an

adjustment was made for a minor difference in the fiber content of a coat,

even though the difference would have been insufficient to make the old

6

BLS research on direct adjustments that were made in selected apparel item strata for 6 months in

1991 indicated that more than two-thirds of the substitutions would have been deemed comparable if

they had not been directly adjusted. See Paul R. Liegey, Jr., “Apparel Price Indexes: Effects of Hedonic

Adjustment,” Monthly Labor Review, Vol. 117 (May 1994), p. 40.

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coat and new coat not comparable. The new coat had 15 percent less wool

than the old coat. The analyst used a statistical model to estimate the value

associated with less wool and then reduced the price of the old coat by

that amount, making the two coats more alike.

According to the analysts, when they make a direct adjustment, the

substitution is counted with other not-comparable items. However, BLS

could not identify the number of times this happened because it does not

track whether quality-adjusted price comparisons would have otherwise

been comparable. Since information that is used to make adjustments to

increase comparability is restricted to automobile and apparel ELIs, for

which the commodity analysts have information to make direct

adjustments, only a limited number of comparable substitutions would be

directly adjusted for quality changes.

Using Class-Mean and

Linking Methods to Adjust

for Differences

In 1997, 29 percent of the nonrent substitutions were not comparable and

could not be directly adjusted for differences between the old and new

versions. Two indirect methods—linking and class mean—were

commonly used to adjust these 8,361 substitutions. In both methods the

price of the new version is set aside for the current month, and an

adjustment determined from price movements of the same type of items is

applied to the previous price of the old version. The class-mean method is

to be used in item strata where new models or product lines are

introduced regularly, whereas the linking method is to be used where new

models or product lines are not regularly introduced. In 1997, BLS had

designated the class-mean method to be applicable to 53 of the 206 item

strata. Of the substitutions that were not directly adjusted in 1997, the

substitutions were almost equally divided between the linking and

class-mean methods.7

As previously described in this appendix, when there is a substitution, BLS’

computers will indicate one of three codes on the CRL. One code indicates

that the computer will apply the class-mean method of adjustment if the

substitution is in an item stratum for which BLS has designated the

class-mean method. Another code indicates that the linking method will be

applied if the substitution is not in a class-mean designated item stratum.

The third code indicates that the substitution and the item it replaced are

comparable and, therefore, no adjustments are needed. However, the

commodity analysts can overrule these computer-generated codes. When

7

BLS officials also noted that substitutions are not equally distributed across all ELIs. As shown in

appendix VIII, some ELIs experience more substitutions than others.

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commodity analysts overrule those substitutions coded as comparable,

they are to determine if the substitution is in an item strata for which the

class-mean method has been designated in deciding the adjustment

method to apply.

Although the new version is set aside when the linking or class-mean

method is applied, it is used beginning in the following collection period.

The substituted product or service will become the item that the price

taker is to price for the CPI in future price collection periods.

Applying the Class-Mean

Method

If the commodity analyst decides that the class mean is the appropriate

adjustment method for the substitution, then the price of the new version

is set aside for the current month, and a procedure is followed by BLS

computers to impute a rate of change. This imputation is based on a

particular subset of items in the CPI that BLS considers to be most

appropriate for the calculation. The class mean imputation is described in

detail in appendix V. In 1997, of the 28,881 substitutions, 4,049, or

14 percent, were adjusted with the class-mean method.

Applying the Linking Method According to BLS, if the substitution that the commodity analyst deemed as

not comparable resides in an item stratum that is not a class-mean

designated item stratum and was not directly adjusted for quality change,

then the linking method will be applied. In the linking method, the price of

the new version is set aside, and a procedure is followed by BLS computers

to impute a rate of change that is based on all the other items with usable

prices in the geographic area and item stratum. This procedure is further

described in appendix IV.

Some of the commodity analysts who work on class-mean designated item

strata told us that under certain circumstances, they use the linking

method for substitutions that are in class-mean designated item strata. For

example, the analyst for new automobiles reported that he used the

linking method when the price taker appeared to have collected incorrect

information.

Of the 28,881 substitutions in 1997 that commodity analysts reviewed,

4,312 (about 15 percent) were adjusted with the linking method. Of these

linked-adjusted substitutions, 371 were in class-mean item strata.

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BLS Processes and

Procedures for

Reviewing

Substitution Decisions

BLS relies on supervisors to review the substitution decisions made by

commodity analysts. Although there are no written guidelines for

supervisors to follow in selecting and reviewing the decisions made by

analysts, BLS officials stated that the supervisors follow unwritten policies.

There is no unique set of procedures for selecting and reviewing these

decisions. The reason for most supervisory reviews, according to BLS, is a

large price change, with the definition of large varying among and within

item strata. Supervisory reviews are scheduled three times during the

month’s pricing periods and after all of the pricing information has been

collected. For those substitutions selected for review, supervisors

normally rely heavily on commodity analysts in carrying out the scope of

their reviews.

Supervisors Review

Substitutions That Result

in Large Price Changes

According to BLS, supervisors are to review large price changes going into

the CPI each month, with the definition of large varying among and within

item strata. Large price changes are reviewed because they are the price

changes that could have the greatest impact on the indexes. As part of this

review, substitution decisions made by commodity analysts are reviewed

when those decisions produce large price changes. Substitution decisions

that produce price changes that are too small to meet the selection criteria

are usually not subject to review. The branch chief for consumer prices

reported that there is no random review of analysts’ decisions. According

to BLS, it does not track the percentage of substitution decisions that are

reviewed because of large price changes.

A BLS official reported that supervisors and analysts working together set

the levels of price change that trigger a review. Levels are set for each

individual item stratum. To establish these levels, the analyst and

supervisor responsible for an item stratum consider that stratum’s current

and historical price data but also rely on their own judgment and industry

knowledge. As a result, the levels of price change that require a

supervisory review can vary by item strata and can differ between price

increases and price decreases within the same stratum. For example, the

supervisor for the household-goods item stratum reviews price increases

or decreases of 15 percent or more. However, in the women’s coats and

jackets item stratum, price increases of 25 percent or more are to be

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reviewed, while price decreases require a change of 20 percent or more.

Price changes that do not meet or exceed these levels are not reviewed.8

Supervisory Reviews

Occur After Data

Collection Periods End

For the purpose of collecting CPI prices, BLS divides each month into three

collection periods, which it calls pricing periods. At the end of each

pricing period, BLS officials stated, all the price quotations in which a price

change meets or exceeds the trigger levels for supervisory review are

identified by computer routines, including some that resulted from the

substitution decisions of commodity analysts. At the end of each pricing

period, computer routines produce lists of these quotations, called

supervisory query review lists, that are organized by each commodity

analyst, item stratum, and geographic region. These lists, which are

produced at the end of each pricing period, provide basic information for

each price quotation that was flagged for review. This information

includes the old and new prices of the items, the percentage of price

change, and any short messages the analysts provided to explain the

change.9

 The lists can be lengthy; one chief of a section said that the three

supervisor query lists have generated a total of more than 1,000 price

quotations in some months.

The Branch Chief for Consumer Prices reported that BLS does not have any

written policies or guidance for supervisors to follow when reviewing

analysts’ decisions. However, the branch chief stated that the unwritten

policy requires supervisors to review and approve every price change that

appears on the supervisory query lists. One section chief said that, in

general, each of the three reviews was completed in about a day.

Review Also Occurs After

Preliminary Indexes Are

Produced

After the supervisory review of price changes is complete, BLS computer

routines produce preliminary basic indexes for each item stratum and

geographic area. The supervisors are required to review these preliminary

indexes. According to BLS, review of these preliminary basic indexes is an

additional quality control that has been built into the CPI to identify and

verify large price changes. After any changes that result from the review of

the preliminary basic indexes are entered into the computer, the final

8

These levels were for “regular” prices of women’s coats and jackets (i.e., the prices of items that were

not on sale). BLS normally set different levels of price change for regular and sale prices. For example,

substitutions for women’s coats and jackets at regular prices were reviewed if the new version had

decreased by 20 percent. However, substitutions for women’s coats and jackets at sale prices were

reviewed only if the new version decreased by 75 percent or more.

9

The lists do not routinely include information about whether the price quotation was a substitution

and, if so, what decision the analyst made. However, this information might be included in the

analysts’ explanatory messages.

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basic indexes are calculated and combined to form the CPI indexes that are

published.

More than 8,000 preliminary basic indexes were produced each month in

1997, according to BLS officials.10 The production schedule was supposed

to allow supervisors about 2 days each month to review all preliminary

basic indexes.11 However, because of production delays, supervisors often

had much less time to review the indexes, BLS officials said.

The Branch Chief of Consumer Prices stated that the supervisors are to

identify large price changes in the preliminary indexes, and investigate the

price quotations responsible for those changes. According to BLS officials,

there are no set levels of price changes that require investigations. Instead

the supervisors are to decide what levels require investigation. By way of

illustration, one section chief stated that the rates of price change that

would prompt him to investigate an index varied by item stratum, and

could change over time, but generally ranged between 12 to 20 percent at

the time of our interview.12

During an investigation, the supervisors typically are to identify the

quotations that are causing increases from a list containing all the price

quotations for the month.13 This list, which is called the Commodity

Analyst Listing (CAL), contains basic information for each quotation, and

includes the old and new prices, the percentage price change, the analyst’s

decision, and any short explanatory messages provided by the analyst.

According to the Branch Chief for Consumer Prices, when the supervisors

identify quotations that cause large changes in a preliminary basic index,

they can ask the commodity analyst responsible to explain what had

occurred. However, it is possible that, because of the three supervisory

query reviews that occurred earlier in the month, quotations with large

price changes may have already been examined.

10The preliminary basic indexes were produced for each of BLS’ 183 priced item strata in each of its 44

geographic regions. Following the 1998 revision of the CPI, the number of preliminary basic indexes

diminished because the number of geographic regions decreased to 38.

11The chiefs of the Consumer Price Branch’s four Commodities and Services sections were responsible

for the supervisory review. However, at the time of our field work, two of the chiefs also had a

supervisor in their sections who assisted them in the review.

12The levels of price change that prompt supervisors to review an index can be different from the

levels of price change that require supervisors to examine a price quotation during the earlier

supervisory query review.

13About 80,000 price quotations were collected each month in 1997. The section chiefs of the

Consumer Price Branch received information for all the price quotations in their sections.

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Normal Scope of

Supervisory Review

The Chief of the Consumer Prices Branch stated that the supervisors are

required to examine the reasons for the analysts’ decisions for price

quotations that produce large price changes. The supervisors reported that

they frequently did this by examining the short messages that commodity

analysts attached to each price quote and that are printed on the

supervisory query and CALs. These messages were short, in large part,

because the computer system limits messages to 128 characters. We found

the following examples of short messages for price quotations that were

substitutions for apparel items in October and November 1997:

• “Approximately same specs;”

• “Price change O.K.;”

• “Same regular price;” and

• “Change in fiber.”

If the supervisors are not satisfied with explanations in the short

messages, they are to ask the analysts to explain their decisions in person.

All of the supervisors said that they usually accept the analysts’

explanations, either through the short messages or in person. Three of the

four supervisors stated that it was very rare for them to formally review an

analyst’s decision by examining the characteristics and price histories of

the quotations themselves. One supervisor stated that he did not review

the characteristics and price histories because of the confidence he had in

his commodity analysts.

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Appendix IV 

Direct Adjustments

A direct adjustment is a price adjustment for specific differences between

the characteristic of a good or service that the CPI priced in one collection

period and the characteristics of a substitute good or service that the CPI

priced in the next collection period. Direct adjustments can be classified

on the basis of BLS’ use into the following:

• a manufacturers’ cost method, which uses cost information from

manufacturers to identify the cost of individual characteristics or options

that have changed;

• a hedonic regression method, which uses statistical models to estimate a

value for (or implicit “price” of) the individual characteristics of a good,

such as the cost of adding a lining and hood to a coat; and

• an “other” method, which covers a broad array of direct price adjustments,

including those made for a change in the number of units (e.g., 15 tablets

instead of 12 tablets) or the size of an item (e.g., 8 ounces instead of 10

ounces), and to correct data-entry errors made by BLS.

Similar to the indirect adjustment methods of linking and class mean that

BLS uses, the direct adjustment methods divide the total price change into

a pure price change component and a quality change component. The CPI

is to incorporate only the pure price component.

A fundamental difference between the indirect and the direct adjustment

methods is that the indirect methods first estimate the pure price change

and then assign any remaining or residual portion of the price difference

to quality. The direct methods do the opposite. They first estimate the

value of quality changes and, in essence, remove that value from the price

difference. The pure price change is the residual after the adjustment is

made. Hence, unlike the appendixes on the class mean and linking

methods, this appendix first describes how quality changes are estimated

before discussing how price changes are calculated as a residual.

Manufacturers’ Costs BLS uses manufacturers’ cost information to make direct adjustments for

changes in quality in the new and used vehicles item strata. Each year, BLS

collects information from the manufacturers of automobiles and trucks on

the costs of the new features in each model and uses this information to

make adjustments. For used vehicles, BLS uses data from prior years’ new

vehicles.

All of BLS’ manufacturers’ cost adjustments were in the new and used

vehicle item strata. In 1997, BLS made 1,828 direct adjustments in these

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Direct Adjustments

items. According to BLS officials, about 90 percent of these adjustments

were made using manufacturers’ cost information, and the remainder were

made using the other method.

Background on

Manufacturers’ Costs

Since 1967, BLS has asked the major domestic automobile and truck

manufacturers for information about the cost of quality improvements in

the new models that are used for the Producer Price Index (PPI).1 BLS

requests all manufacturers of domestically produced vehicles to

participate in this process. Domestically produced vehicles include those

produced in the United States by both U.S. and foreign automobile

manufacturers. The manufacturers are very cooperative, according to BLS.

Manufacturers that produce their models overseas and import them into

the United States are not included in this annual information gathering

process.

For the 1998 model year (introduced in the fall of 1997), BLS requested

information on the 20 car models it had selected for pricing in the PPI.

Manufacturers provided information on only 15 models in time for the BLS

press release on 1998 models published in October 1997. According to BLS,

the five models lacking information either had so many changes that the

manufacturer could not accurately break out the cost associated with each

change, or the information, while usable for direct adjustments when

reviewing substitutions, was provided too late to be incorporated in the

press release.

The manufacturers provide BLS with lists of improvements they have made

to the new models in the PPI sample and the cost of producing those

improvements. According to BLS, the manufacturers often claim that

improvements in style, comfort, and convenience are quality

improvements. However, BLS does not consider such improvements to be

quality improvements unless they are presented with evidence of

functional improvements. BLS has developed criteria for quality

improvements that include improvements in safety, durability, and

performance. BLS analysts use these criteria to review the manufacturers’

1

BLS bases the PPI on producers’ output. According to BLS the PPI sample of new model vehicles was

representative in the sense that it included the platforms that accounted for the automakers’ largest

outputs. The PPI sample selection process focuses on vehicle platforms, officials stated, because a

single platform usually includes a number of nameplates, and each nameplate may have numerous

models. For example, the H platform for General Motors has three nameplates: the Buick LeSabre,

Oldsmobile Eighty-Eight, and Pontiac Bonneville, each of which has its own models. All of the models

are built on the same platform and have basically the same power trains. The differences between the

models include styling and equipment changes. According to BLS, it generally uses one model to

represent an entire platform because of the similarity between the models.

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lists of improvements and decide whether they are, in fact, quality

improvements. Through their review, BLS analysts developed lists detailing

every quality improvement and the cost of every quality improvement for

all models in the model-year sample.2

For the 15 new domestic passenger cars in the 1998 PPI sample, according

to BLS, the average increase in the manufacturers’ suggested retail price

over the 1997 versions of these models was $363.27. Of this increase, BLS

attributed $230.81 (or 63.5 percent) to quality changes. BLS estimated that

$52.14 of the $230.81 was for changes in accordance with the 1990 Clean

Air Act Amendments and $178.67 was for other quality changes, such as

powertrain improvements, corrosion protection upgrades, and changes in

the levels of standard or optional equipment.3

The CPI program applies this information to models that were in the PPI

sample and to similar models that were outside the PPI sample. CPI

commodity analysts use information from the manufacturers and publicly

available publications, such as Automotive News, to help determine

whether models outside the PPI sample shared the same platform as

models inside the PPI sample.

In some cases, BLS analysts apply manufacturers’ information from the

sample to models outside the sample that do not share the same platform

with a model in the PPI sample. For example, if a rear defogger was added

to a new model outside the sample, the analyst might estimate the average

price of defoggers added to models inside the sample and use the estimate

to make an adjustment to the model outside of the sample, even though it

did not have the same platform. Sample information might also be used to

make adjustments to foreign manufacturers’ models imported into the

United States, in instances where the domestic manufacturer’s information

appeared applicable. In cases such as the ones just described, BLS analysts

rely on judgment rather than a set of uniform rules and procedures.

How Quality Changes Are

Calculated Using

Manufacturers’ Costs

The CPI’s commodity analyst for new cars uses the lists of quality changes

when reviewing substitutions. If the substitution (a 1998 model) is in the

PPI sample, the analyst looks for improvements that have been made in the

model under review. The analyst may find, for example, that the engine of

2

According to BLS, officials from the CPI and the International Price Program also participate in the

review process that determines whether improvements are, in fact, quality improvements.

3

As of January 1999, BLS no longer treats changes made solely to meet air quality standards as quality

improvements in the CPI.

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Direct Adjustments

a particular model has been upgraded. The manufacturer’s information in

the sample also lists the costs of producing the improvement. For

example, the engine upgrade might cost $100. The analyst will then

multiply this cost by a factor to adjust for the difference between producer

and retail prices. For example, if the analyst used 20 percent as a factor,

the result would be $120 ($100 x 1.20 = $120).

Using this methodology, an adjustment of $120 would be made to ensure

that the new (1998) and old year’s (1997) models were comparable in

terms of quality. If the price of the new model was $11,750 and the price of

the old model was $11,500, BLS would add $120 to the price of the old

model so that the comparison would be between $11,750 and $11,620

instead of between $11,750 and $11,500.

According to BLS, if a model priced in the CPI sample is not in the PPI

sample, the analyst is to use the manufacturers’ and publicly available

information to determine whether the price is similar to one of the models

in the sample. For example, the available information may show that a

Ford Escort is built on the same platform as a Mercury Tracer. If the Ford

Escort was in the sample, but the Mercury Tracer was not, and the analyst

concludes that the two models are sufficiently similar, the manufacturer’s

information on the Ford Escort could be applied to the Mercury Tracer.

If a model is not in the PPI sample and is not built on the same platform as

a model in the PPI sample, the analyst may still be able to use some

manufacturer’s information obtained in the sample. However, in the

absence of manufacturer’s information, it is much more likely, according

to BLS, that the analyst will use the class-mean method of adjustment.4

 In

general, prices of new foreign models manufactured abroad and imported

to the United States are more likely than domestically produced items to

be adjusted using the class-mean method.

Direct adjustments for used vehicles rely on manufacturers’ information

that was obtained in previous years. The CPI used-car index is based on the

prices of vehicles that are between 2 and 6 years old. For example, the

used-car index in 1998 might include the substitution of a 1995 for a 1994

Chevrolet Cavalier. In that instance, the BLS analyst would make

adjustments if the manufacturers’ information for the 1995 and 1994

4

BLS officials report that, if a new model has been significantly redesigned, they may consider it too

different to be compared to the old model. Under those circumstances, BLS will not use the

manufacturers’ information—if it is available—to make direct adjustments, but will use the class-mean

method of adjustment.

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Chevrolet Cavaliers indicated that quality changes had occurred between

the model years.

A direct adjustment for used cars relies on the information collected in

earlier years for new cars, with the dollar amount of the adjustment

translated into percentage terms. In the above example, the estimated $120

quality improvement equals 1.0 percent of the $11,500 price for the model

of prior year (1997). If BLS uses the two models in the price index 3 years in

the future (2001), a 1.0 percent quality adjustment would be added to the

used-car price collected for the 1997 model before it is compared with the

used-car price collected for the 1998 version.

How Price Changes Are

Calculated After Making an

Adjustment Using

Manufacturers’ Costs

In the example above, an adjustment of $120 would be added to the price

of the previous year’s model to make the new and old year’s models

comparable with the terms of quality. Then the adjusted price of the old

model ($11,620) would be compared to the price of the new model

($11,750). The CPI would incorporate an increase of 1.1 percent to reflect

the $130 difference between the two prices. Of the $250 total price

difference between the two models in the example, BLS procedures

allocate $120 to quality and $130 to price.

BLS’ Use of Manufacturers’

Costs

The following example results from our interviews with a BLS commodity

analyst. According to the commodity analyst and supervisor, it is

representative of the adjustments that employ manufacturers’ costs to

adjust for quality improvements in vehicles.

The example includes a price calculation that shows the percentage

change in price that went into the CPI for that month, as a result of the

direct adjustment. This percentage change in price is applicable only to

the particular case illustrated. It is not intended to be representative of the

percentage changes in price that occurred for similar kinds of

substitutions in which direct adjustments are made. Nor is the percentage

change in price intended to be representative of the impact that direct

adjustments have on the CPI.

The example includes (1) a table showing the characteristics of the old

version and the new version that replaced it (differences between the old

and new versions are highlighted by shading), (2) the analyst’s reasons for

judging the two versions to be comparable, (3) the rationale for selecting

the method of adjustment, and (4) the price calculation that was made.

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Example 1 - New Car

(Under the New Cars

Item Stratum)

Although the specifications for the 1998 and 1997 models were alike, the

commodity analyst made an adjustment because the analyst had been

provided with information by the automaker that showed improvements

had been made to the 1998 model.

Table IV.1: Characteristics of Two

Versions of a New Car Description Old version New version

Specifications

Model year 1997 1998

Model 4-door sedan 4-door sedan

Engine size 3.8 liter engine 3.8 liter engine

Number of cylinders Six cylinders Six cylinders

Transmission 4-speed automatic 4-speed automatic

AM/FM radio and cassette Yes Yes

Rear window defroster Yes Yes

Power-assisted driver seat Yes Yes

Price information

Amount $22,104 $23,180

As of September October

Collected/imputed Collected Collected

 Specifications that differ between old and new versions

Source: BLS.

Analyst’s Reasons for

Deciding the Items Were

Comparable

Even though the specifications of the old model and the new model were

unchanged, the analyst knew that changes had been made to the new

model because of information provided by the automaker. This

information showed that the engine had been improved to reduce fuel

emissions and that the air bags had been depowered to improve passenger

safety. In the analyst’s opinion, despite the improvements, the new and old

models were broadly comparable. Nevertheless, the analyst concluded

that an adjustment for the engine improvements and depowered airbags

would make them even more comparable.

Rationale for Selecting the

Method of Adjustment

To make the adjustment, the analyst had to override another adjustment

code that was computer generated. A computer routine automatically

calculates any change in prices between the old and new versions of a

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substitution. If the price change is below a predetermined level, the

computer is programmed to default to a comparable substitution code. If

the price change exceeds the predetermined level, the computer defaults

to a not-comparable code. In the new cars item stratum, the

not-comparable code would indicate that the class-mean method should

be used. The computer routine cannot default to a direct adjustment code.

In this case, the computer generated the code for a comparable

substitution.

If the analyst had not made the adjustment the models would have been

considered comparable, and the 4.9 percent difference between the

collected price of the new model and that of the old model would have

been incorporated into the CPI. However, the analyst had the necessary

data from the sample of manufacturers to make an adjustment and

believed that an adjustment would make the new and the old models more

comparable in terms of quality.

Calculation of Price

Change

The automaker had reported that the wholesale cost of the engine

improvements was $105, and the cost of depowering the airbags was $10.

The analyst added these two costs together ($105 + $10 = $115), and then

multiplied the total by 118 percent to account for the difference between

the wholesale costs and their retail equivalent. The analyst used a markup

factor of 118 percent because, according to BLS, the available data

indicated this was the most appropriate markup for this type of vehicle in

1998. The cost total of $115 multiplied by 118 percent was $135.70, which

the analyst rounded to $135.

To make the adjustment, the analyst added the $135 to the price of the

1997 model ($22,104 + $135), creating an adjusted price of $22,239. As a

result of this action, BLS’ computer routines compared the adjusted price

of $22,239 for the old model with the actual price of the new model,

$23,180, and recorded a price increase of 4.3 percent for the new model.

This price increase was included in the CPI calculations for October 1997.

Hedonic Regression

Estimates

BLS first introduced the use of adjustments based on hedonic regression

estimates into the CPI in 1988 to adjust for the effect of aging on housing

units. In 1991, hedonic regression estimates were applied to adjust apparel

items. According to BLS, the extensive and frequent seasonal and

style-driven changes in characteristics of apparel items pose numerous

problems for the maintenance of a constant quality market basket of

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apparel items in the CPI. The use of hedonic regression methods in apparel,

BLS reported, has helped address these problems.

In 1997, BLS used hedonic regression estimates exclusively for apparel

items. According to BLS officials, at least 95 percent of the 1,223 direct

adjustments that were made for apparel items in 1997 used hedonic

regression estimates; the remainder used the other method.

BLS is undertaking a major research program with the goal of applying

adjustments based on hedonic regression estimates to other consumer

items where satisfactory models can be developed. The effort will place

particular emphasis on consumer durable goods, such as electronic

products, likely to experience significant quality change over time. In

January 1998, hedonic regression models that were initially developed for

the PPI began to be used for computer items in the CPI. Effective with the

release of the CPI for January 1999, BLS introduced hedonic adjustments in

the television stratum of the CPI.

Background on Hedonic

Regression Estimates for

Adjustments

Hedonic regression estimates are used to make direct adjustments to the

price of an item when it is replaced by a substitute item so that BLS can

compare its price with the price of its replacement. The values, or the

implicit prices, of the various quality characteristics that affect the total

price of a particular good are estimated using regression techniques.

A fundamental assumption underlying the hedonic price framework,

according to economists, is that an individual good can be viewed as a

combination of a number of observable characteristics.5

 The hedonic

modeling technique—based on the prices paid by consumers for the goods

for which the CPI collects prices—provides an estimate of the value or

implicit price of each characteristic of the good that is modeled in the

hedonic regression equation.

The implicit prices for individual product characteristics that are

estimated using hedonic regressions can be used to adjust the prices of

two items with different characteristics. After these adjustments, the

remaining difference between the prices of the two items can be

considered as an estimate of the pure price difference between them. This

pure price change can then be incorporated in a constant-quality price

index such as the CPI.

5

See, for example, Triplett, Jack E., “The Economic Interpretation of Hedonic Methods,” Survey of

Current Business, January 1986, p. 40, and Berndt, Ernst R., The Practice of Econometrics: Classic and

Contemporary, Addison-Wesley, New York, 1991, p. 117.

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How Quality Changes Are

Calculated Using Hedonic

Regression Models

For the period reviewed in our report (October and November 1997), the

application of hedonic techniques among nonrent items was limited to

apparel items. BLS has found that measuring price change for goods such

as apparel items presents considerable problems because these items

undergo numerous changes in characteristics as fashions evolve.6

 Since

January 1991, BLS has been using hedonic regression models to make

direct adjustments for quality differences in apparel items. According to

BLS, the hedonic regression models develop estimates for the values of

product features. These estimates are then used to make adjustments to

the prices of apparel items for the changes in quality. Previously, BLS relied

heavily on the linking method to adjust apparel items.

Hedonic regression modeling in apparel utilizes the general framework in

which an item can be viewed as a collection of characteristics, which,

taken together, provide satisfaction or value to the consumer. A woman’s

jacket, for example, can be considered an aggregation of its features, such

as its fiber content (e.g., percentage wool) and type of closure (button or

zipper), each of which contributes to the value of the jacket in the eyes of

the consumer.

Figure IV.1 describes the hedonic regression equation that BLS uses for

apparel items.

Figure IV.1 Description of a Hedonic

Regression Equation for Apparel Items

The standard hedonic regression equation for apparel commodities uses the natural

logarithm of the item’s price as the dependent variable and several independent

variables capturing different characteristics of the apparel item. The values of the

independent variables are measured linearly (i.e., measured in levels, rather than

logarithms). The coefficients in such a semilog specification provide an estimate of the

proportional change in price that results from a one-unit change in a quality

characteristic. In most cases, an independent variable representing a characteristic is

dichotomous, in the sense that it indicates whether or not the item possesses the

characteristic. The value of the variable is 1 for an item with the characteristic and 0 for

an item without it. In some cases, an independent variable measures a continuous

quantity, such as the content of a particular fiber. An item’s percentage of wool, for

example, would range from 0 to 100. Additional variables called control variables usually

also are included to capture the effect of price variations by city size, region, and type of

business.

Source: BLS.

Determining the best set of characteristics to explain prices in apparel

poses a challenge because fashion influences price. BLS analysts found,

6

BLS Handbook of Methods, U.S. Department of Labor, BLS, (April 1997) p. 184.

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however, that fashion can be approximated to some extent through such

characteristics as whether the item is a store or national brand and the

type of closure (e.g., zipper or buttons). According to BLS, other

characteristics such as lining and fiber are always included in the apparel

regression models because they are fundamental to the price of an apparel

item. According to BLS, all these characteristics can be observed and tested

to see the degree of influence, if any, they exert on price.

For example, a 1997 version of the hedonic regression model for women’s

coats provides estimates of the effect on price of almost 30 different

characteristic and control variables. These estimates included

dichotomous variables indicating whether or not the item was one of

several types of coats, such as a windbreaker, a parka, a trench coat,

among others. Continuous variables included the percentage content of

cashmere, camel hair, wool, cotton, and other fibers. The equation

included variables to control for other factors, such as whether the price

was collected at a discount department store, in a large city, and from the

Northeast.

According to BLS guidelines, the value to consumers of particular product

attributes change over time. Hence, the hedonic regression estimates need

to be updated periodically. For example, BLS’ detailed written guidelines

for the apparel modeling process include a requirement that the apparel

regression models be updated at least every 12 to 15 months. Should a

sharp market change occur, however, BLS’ guidelines call for earlier

updating.

How BLS Accounts for

Quality Change Using

Hedonic Regression

Estimates

BLS’ exclusion of quality differences using the hedonic regression estimates

can be demonstrated with a hypothetical case based on a woman’s trench

coat. For example, assume that the new version of the trench coat had a

lining, but the old version did not, and the two versions had no other

differences. In this example, assume that the BLS commodity analyst

determined that the two versions were not comparable but was able to use

the estimated hedonic regression equation for women’s coats to adjust for

the effect of the difference.

For this illustration, assume that the price of the old trench coat was $100

and that the price of the new version was $125. The estimated hedonic

regression coefficient for the lining characteristic was .13470725, which

represents the lining’s logarithmic effect on the price of the coat. To

determine the quality adjusted price of the old version, the logarithmic

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price effect is exponentiated and multiplied by the old price: $100 x

exp(.13470725) = $114.42.

The hedonic quality adjustment has the effect of adding $14.42 ($114.42 -

$100.00) to the price of the old item to make it comparable to the new

item. In effect, the hedonic regression adjustment implies that if the old

version had a lining, the lining would have added $14.42 to its price.

How BLS Calculates a

Price Change After Making

a Hedonic

Regression-Based

Adjustment

Following the hedonic regression adjustment described above, the old

item’s adjusted price of $114.42 is compared with the new item’s price of

$125.00. The 9.2 percent difference between the two prices is incorporated

in the calculation of the CPI as a pure price increase. Thus, of the $25

actual price difference between the two versions of the coat, $14.42 was

allocated to a quality difference; and the remaining $10.58 was determined

to represent a pure price increase.

Example of BLS’ Use of the

Hedonic Method

The following example results from our interviews with a BLS commodity

analyst. According to the commodity analyst and supervisor, it is

representative of the methods in which they use hedonic regression

estimates to adjust for quality change in apparel items.

The example includes a price calculation that shows the percentage

change in price that went into the CPI for that month as a result of the

direct adjustment. This percentage change in price is applicable only to

the particular case illustrated. It is not intended to be representative of the

percentage changes in price that occurred for similar kinds of

substitutions in which direct adjustments are made. Nor is the percentage

change in price intended to be representative of the impact that direct

adjustments have on the CPI.

The example includes (1) a table showing the characteristics of the old

item and the new item that replaced it (differences between the old and

new versions are highlighted by shading), (2) the analyst’s reasons for

judging the two versions to be not comparable, (3) the rationale for

selecting the method of adjustment, and (4) the price calculation that was

made.

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Example 2 - Woman’s

Coat (Under the

Women’s Coats and

Jackets Item Stratum)

A new version of heavyweight woman’s coat was substituted for the old

version and, as shown in table IV.2, several important characteristics of

the two versions differed. The analyst decided that the two versions were

not comparable, and made a direct adjustment by using values from a

hedonic regression.

Table IV.2: Characteristics of Two

Versions of a Woman’s Coat Description Old version New version

Specifications

Type Heavyweight Heavyweight

Design Shirt jacket/Battle jacket Parka

Body fiber 100 percent cotton 60 percent cotton and 40 

percent polyester

Brand/label name Local brand name Different local brand name

Size range Junior/misses Junior/misses

Length Waist Waist

Cleaning method Machine washable Dry clean only

Type of pockets 2 slot a

Lining Yes Yes

Method of closure Button closure Zipper and button closure

Color Biscuit (Tan) Ivory/Hunter green

Other information Corduroy Drawstring waist

Price information

Amount $32.028 $125.00

Type of price Sale Regular

As of August October 

Collected/imputed Imputed Collected

 Specifications that differ between old and new versions

aThere was no information about the type of pockets in the new version.

Source: BLS.

Analyst’s Reasons for

Deciding the Items Were

Not Comparable

The commodity analyst noted that there were several major differences

between the old and new versions in the design, body fiber, and method of

cleaning. The analyst said that BLS research had shown that these

differences had a significant effect on the price of women’s coats and

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jackets. The differences were sufficient for the analyst to determine that

the items were not comparable. The analyst used hedonic regression

estimates to adjust for the quality differences and make the items

comparable. Without the adjustments the class-mean method would have

been applied to the item by default.

Rationale for Selecting the

Method of Adjustment

To make the adjustment, the analyst had to override another adjustment

code that was computer generated. A computer routine automatically

calculates any change in prices between the old and new versions of a

substitution. If the price change percentage is within a predetermined

interval, the computer is programmed to default to a comparable

substitution code. If the price change is outside the interval, the computer

defaults to a not-comparable code. In the women’s coats and jackets item

stratum, the not-comparable code would indicate that the class mean

should be used. Because the computer routine is based on price change, it

cannot default to a direct adjustment code. In this case, the

computer-generated the code for a not-comparable substitution, which

means that the class-mean method of adjustment would have been used.

However, the hedonic regression model for women’s coats and jackets

provides estimates of the price effects of differences in design, body fiber,

and method of cleaning. Therefore, the analyst was able to apply the

hedonic regression estimates to adjust for quality differences and make

the substitution comparable.

Calculation of Price

Change

The analyst used the results of the hedonic regression to calculate the

adjustment attributable to the quality change in design, body fiber, and

method of cleaning. The analyst calculated this to be $33.850 and added

this value to the price of the old version to derive an adjusted price of

$65.88 ($32.028 + $33.850).7

 The difference between the adjusted 

price of the old version ($65.88) and the price of the new version

($125.00) represented a pure price increase of 89.7 percent, which was

incorporated into the CPI.

7

In this instance, the price of the old version was an imputed price. Imputed price is a term used by

BLS to indicate that the old version did not have a usable price. Instead, an average was calculated

from the price change experienced in the previous collection period by the same type of items in the

CPI to handle a missing or unusable price quotation.

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Other Direct

Adjustments

A third method of direct price adjustments includes adjustments for an

item’s size or the number of units it includes. BLS considers adjustments

for unit count or size to be direct adjustments because they adjust for a

particular characteristic of a good or service. BLS also includes data-entry

corrections for individual items in this direct adjustment method.

In 1997, BLS made direct adjustments to at least 719 items to account for

unit-count changes, size differences, or data errors, which represented

about 6 percent of the 12,131 adjusted substitutions in 1997 that involved

nonrent items. Of these 719 direct adjustments, 336 involved medical-care

items, 132 were for housing-related items, 107 were in food and beverage

items, 95 involved entertainment items, and the remaining 49 were in

transportation and the “other” goods and services ELIs.

According to BLS, a large number of adjustments for unit count or size

differences are made automatically in the CPI. For example, most food and

beverage prices are automatically converted to an effective price on a

per-ounce basis. These conversions are not counted as substitutions and

are not reflected in the count of direct adjustments.

How BLS Accounts for

Quality Changes

Associated With

Differences in Unit Count

or Size, and Corrections

For purposes of measuring the price change of an item of constant quality,

the item should remain the same in unit count or size between collection

periods. Before calculating the price change between two versions of an

item that have experienced a size or unit count change, BLS adjusts the

price of the old version to the level it would have been if the old version

had the same unit count or size as the new version.

How BLS Calculates Price

Changes After Direct

Adjustments for

Differences in Unit Count

or Size, and Corrections

To illustrate a price calculation with an “other” direct adjustment method,

suppose for example, that a package of gum has five sticks in one period

and sells for 50 cents, and at the next price collection period the package

has six sticks of gum and sells for 60 cents. According to BLS, the

difference in unit count would make this substitution not comparable.

However, the BLS commodity analyst can make a direct quality adjustment

to the price of the old version to account for the difference in unit count.

The analyst would calculate the price per stick of gum in the previous

collection period as 10 cents. The 10 cents is added as a direct adjustment

to the 50 cents price of the old version to price it as if it had six sticks.

After the adjustment, the old price for the pack of gum is 60 cents. The 10

cents is what BLS would count as quality change in the context in which BLS

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generally uses the term quality—all changes that are not pure price

changes.

If no adjustment for unit count had been made, the price difference

between the two packages of gum would have been reflected as a

20-percent increase (the increase from 50 cents to 60 cents per pack).

However, after the direct adjustment to the price of the old version, based

on the price per stick of gum in the package, the price of the old version

was 60 cents. Because the price of the new version was also 60 cents, the

CPI would reflect no price change (0 percent) for the item.

Examples of BLS’ Use of

Direct Adjustments for

Size or Unit Count, and

Corrections

The following two examples of BLS’ use of direct adjustments for unit

count or size, or corrections come from our interviews with BLS

commodity analysts. According to the commodity analysts and

supervisors, these examples are illustrative of the substitutions in which

they use such direct adjustments in their respective CPI components. These

examples show analysts’ decisions when the difference in unit count or

size between versions are large enough to make the items not comparable,

even though, according to BLS, it also makes such adjustments when the

differences are not as large. In addition, in these examples the analyst has

sufficient information to make a direct adjustment to the price of the old

version, and compare that adjusted price with the price of the new

version.

The examples include a price calculation that shows the percentage

change in price that went into the CPI for that month as a result of the

direct adjustments. These percentage changes in price are applicable only

to the particular cases illustrated. They are not intended to be

representative of the percentage changes in price that occurred for similar

kinds of substitutions in which direct adjustments are made. Nor are the

percentage changes in price intended to be representative of the impact

that direct adjustments have on the CPI.

Both examples include (1) a table showing the specifications of the old

version and the new version that replaced it, (2) the analyst’s reasons for

judging the two versions to be comparable or not comparable, (3) the

rationale for selecting the method of adjustment, and (4) the price

calculation that was made. Within each table, differences in specifications

between the old and new versions are highlighted by shading.

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Example 3 - Season

Ticket (Under the

Admission to Sporting

Events Item Stratum)

The new version of the season ticket included 44 hockey games, while the

old version included 43 games. The analyst decided to make a direct

adjustment to account for the difference in the number of games.

Table IV.3: Characteristics of Two

Versions of a Season Ticket Package Description Old version New version

Specifications

Type of event Hockey Hockey

Level of competition Professional Professional

Admission type Season ticket for 43 events Season ticket for 44 events

Seating location Middle price Middle price

Type of purchase In person In person

Price information

Amount $1,617.432 $1,677.00

As of September October

Collected/imputed Imputed Collected

 Specifications that differ between old and new versions

Source: BLS.

Analyst’s Reasons for

Deciding the Items Were

Not Comparable

The commodity analyst decided that, because the number of tickets in the

season ticket package increased from 43 to 44 hockey games, a direct

quality adjustment could be made. According to BLS, it is not clear whether

the analyst would have decided this was a comparable or a

not-comparable substitution if a direct adjustment had not been made.

Rationale for Selecting the

Method of Adjustment

To make a direct adjustment in this case, the analyst overrode the default

comparison code that the computer had generated. For items in the

entertainment component of the CPI, a computer routine automatically sets

the comparison codes so that the prices of the old and new versions will

be compared unless the analyst sets them to another value. This computer

routine also calculates the percentage change in the versions’ prices for

the convenience of the analyst. When there is a change that meets or

exceeds a predetermined amount, the computer is programmed to

calculate a price increase (or decrease) and a commodity listing review is

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forwarded to the commodity analyst. In this case, the computer defaulted

to a comparable adjustment code signifying that the old and new versions

were alike, and the computer generated a price increase of 3.7 percent.

However, the analyst overrode this adjustment code to make the direct

adjustment. The analyst calculated the quality adjustment factor by

calculating the incremental difference in the increase in the number of

hockey tickets and then entered this factor (1/43 = 0.233) as part of the

adjustment procedure.

Calculation of Price

Change

The price calculation for the direct quality adjustment method is done by

computer using the adjustment factor. According to BLS, the price of the

old version was increased by 2.33 percent to have it represent what a

44-event season ticket would have cost. Using this increased cost of the

old version, the computer compared it with the cost of the new version of

the season ticket.8

 In doing so, according to BLS, the computer calculated a

1.3 percent increase for this season ticket, and this percentage increase

was incorporated into the CPI for October 1997.

Example 4 - Canned

Soup (Under the

Canned and Packaged

Soup Item Stratum)

The analyst concluded that two soups were not comparable and made a

direct adjustment to correct for the size of the container.

8

In this instance, the price of the old version was an imputed price. BLS officials said that, when prices

are unavailable (e.g., because the item is out of season), they impute the prices of those items, using

the same imputation that is used for the linking method. BLS imputes prices using averages calculated

from the price changes experienced in the same month by the same type of items in the CPI to handle

missing or unusable price quotations.

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Table IV.4: Characteristics of Two

Versions of a Canned Soup Description Old version New version

Specifications

Where purchased (in 

store)

Shelf Shelf

Type Condensed Condensed

Brand classification Nationally marketed brand Nationally marketed brand

Flavor Chicken Chicken

Other major ingredients Noodles Noodles

Packaging Canned Canned

Weight 10.375 oz. 10.75 oz.

Price information

Amount $1.324 $0.95

As of October November

Collected/imputed Imputed Collected

 Specifications that differ between old and new versions

Source: BLS.

Analyst’s Reasons for

Deciding the Items Were

Not Comparable

The commodity analyst decided that the two versions were the same soup,

but a message from the price taker indicated that the size of the container

had been corrected. The size of the soup was previously reported

incorrectly as 10.375 ounces and was now being reported correctly as

10.75 ounces. To make a correction for this weight error, the commodity

analyst made the two soups not comparable.

Rationale for Selecting the

Method of Adjustment

To make a direct adjustment in this case, the analyst had to override

another adjustment code that was computer generated. In this case, the

computer defaulted to a comparable adjustment code signifying that the

old and new versions were alike, and the computer generated a price

decrease of 30.75 percent. However, because the analyst wanted to correct

the weight error, the analyst overrode this adjustment code. The analyst

calculated the quality adjustment factor by calculating the percentage that

represents the proportion of the price of the old version that was in error

to make it the same as the larger-size new version and then entered this

factor (–0.0597) as part of the adjustment procedure.

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For not-comparable substitutions in this item stratum, BLS designated the

linking method as the standard method of adjustment when other methods

are not usable. However, in this instance, the analyst had enough

information to make a direct adjustment to equate the two sizes of soup.

The analyst said that if the linking method had been selected, the soup

would have been excluded from the calculation for the CPI that month.

According to the analyst, a quality adjustment would allow a continuation

of the same item in the CPI and allow the analyst to correct the weight

error.

Calculation of Price

Change

The price calculation for the direct quality adjustment is done by computer

using the adjustment factor. According to BLS, the effective price per ounce

of the old version was decreased by 0.0597 percent to have it priced at the

correct weight. Using this decreased cost of the old version of the soup,

the computer compared the corrected unit price with the unit price of the

new version. In doing so, according to BLS, the computer calculated a

26.4 percent decrease for this canned chicken soup, which was

incorporated into the CPI for November 1997.

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Class-Mean Method of Adjustment

According to BLS, the class mean is an indirect method of adjustment that

is used for not-comparable substitutions in item strata where price

changes are closely associated with annual or periodic introductions of

new models or product lines. For example, BLS uses the class-mean

method for the new cars item strata because researchers noted that

automobile manufacturers often increase the prices of their automobiles

when they introduce the new year’s models. Although BLS officials said

they would prefer to make a direct adjustment under these circumstances,

often they do not have the information they need to do so. (See app. IV for

a discussion about direct adjustments.) When a direct adjustment cannot

be made for a new model, the class-mean method is used because,

according to BLS, it more accurately reflects the manufacturers’ price

increase than the linking method, the other available method of

imputation.1

BLS reported that the class-mean method is similar to the linking method in

several ways (see app. VI). Both methods use imputations to estimate

rates of price change when an item in the CPI is replaced by a

not-comparable substitution and a direct adjustment cannot be made. (BLS

also refers to these rates of price change as price relatives.) Both methods

depend upon two fundamental assumptions: (1) the price change

applicable to the not-comparable substitution cannot be directly

calculated and (2) the best available estimate of this price change is the

rate of price change that occurs for the same type of items in the same

geographic area.

The class-mean differs from the linking method in that it is based on the

price changes of a much more specific group of price quotations. Whereas

the linking method is based on all price quotations in the same item

stratum in the same geographic area, the class-mean method is based on a

specific subset that includes only quotations for substitutions, which are

judged comparable and/or to which direct adjustments are made in the

same item stratum in the same geographic area.2

Background BLS officials said they developed the class-mean method in response to a

problem they perceived in the linking method in the late 1980s. Until the

class-mean method was developed, the linking method was the only

1

Imputation is a term used by BLS to indicate that the actual price of the substitution is not used.

Instead, an average is calculated from the price change experienced that month by the same types of

items in the CPI to handle a missing or unusable price quotation.

2

BLS refers to an item stratum in a geographic area as an item stratum-index area.

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Class-Mean Method of Adjustment

method of imputation available to BLS for most substitutions that were

judged to be not comparable.3

 In BLS’ opinion, the linking method tended to

understate the degree of price increase for items for which new models or

product lines were frequently introduced.

According to BLS, its original research indicated that manufacturers usually

raised the price of an item when they introduced a new model or product

line. As a result, BLS officials stated, new models and products usually had

higher average price increases than unchanged models and products.

However, because the linking method was heavily influenced by

unchanged models and products, it tended to understate the level of price

increase when it was applied to new models and products.4

In response to this problem, BLS developed a method for calculating a price

relative that was based on comparable and directly adjusted substitutions

because the prices of these substitutions, BLS officials said, were more

likely to have changed due to the introduction of new models or products.

BLS officials relied on both logic and research to justify their use of this

subset of substitutions for the class mean.

BLS made several assumptions in arriving at this subset of substitutions for

the class mean. It assumed that this subset of substitutions contained a

large percentage of new models or products lines. BLS further assumed that

the not-comparable substitutions in these item strata also contained a

large percentage of new models or product lines but that the unchanged

items did not.5

 Under these circumstances, BLS officials stated, it is more

appropriate to impute the prices of not-comparable substitutions from a

subset of comparable and directly adjusted substitutions than from all

price quotations, most of which consist of items that were not

substitutions and whose characteristics were unchanged.

3

The only other method of imputation available at the time, the overlap method, could only be applied

to substitutions for items that had been on sale. The purpose of the overlap method, BLS officials

stated, was to prevent biases from entering the CPI as a result of substitutions for items that had been

on sale. BLS officials said that, as a result of the introduction of other methods for preventing biases

from sale price items entering the CPI, the overlap method had almost entirely been phased out by

December of 1997.

4

According to BLS officials, the class mean was developed in the late 1980s to address the higher than

average price increases that usually accompanied the introduction of new models or product lines.

However, in recent years, BLS has reported that some manufacturers have decreased the prices of new

models or product lines. If this decrease was lower than the average decrease that would have

occurred if the linking method was used, the price changes of the adjusted items would be overstated

if the linking method was used.

5

By unchanged items, we mean items that were not substitutions and whose characteristics had not

changed.

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To check these assumptions, BLS conducted research, in the early 1990s,

the average price changes for (1) comparable and directly adjusted

substitutions and (2) unchanged items. BLS looked at each item stratum

individually, and compared average price changes. BLS reported that it

found the rates of price change for comparable and directly adjusted

substitutions higher than for unchanged items in many item strata where

their industry knowledge indicated that new models and products were

regularly introduced. The reason for this, BLS officials decided, was that

the new models and products in these item strata generally had higher

rates of price increase than the unchanged items.

In the early 1990s, BLS conducted a broad review of the CPI item strata.

Following this review, it decided that the class-mean method would be

used in item strata where (1) new models or products were known to be

introduced on a regular basis and (2) the average price increase for the

comparable and directly adjusted items was significantly higher than for

unchanged items. Under these circumstances, BLS officials stated, the class

mean was a better method of imputation than the linking method.

BLS commodity analysts used the class-mean method in 33 percent of the

12,131 not-comparable substitutions in 1997. In December 1997, the class

mean was designated for 53 of the 183 priced item strata.6

 These included

most apparel item strata, some transportation item strata, such as new

trucks and cars, and many household-goods item strata. The

household-goods item strata included furniture, kitchen appliances,

electrical goods, utensils, linens, and cleaning agents and tools. In

addition, the class mean was designated for a variety of other items, such

as printed items, boats, bicycles, outdoor equipment, photographic goods,

pet food, and auto repair services.

How Price Changes

Are Calculated With

the Class-Mean

Method

In the class-mean method, the replacement version is put aside in

calculating the price change. Instead, a computerized procedure is

followed to impute a rate of change that is based on items similar to the

old version. A first step in this procedure is for the computer to identify

the substitution’s item stratum and geographic area. For example, if a

price taker in Urbantown made a not-comparable replacement for a new

car in November 1997, the class-mean method would use the new cars

item stratum for Urbantown, November 1997.

6

After the 1998 revision of the CPI, the class mean was designated for 51 of the 186 priced item strata.

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Class-Mean Method of Adjustment

The next step in the computerized procedure is to identify all the

comparable and direct adjusted substitutions and calculate a price change

rate for the applicable item stratum. As a result, the class-mean

method—unlike the linking method—excludes all items that are not

substitutions from its calculations.7

 Because the great majority of the

items are not substitutions each month, this means that the class mean

often is based on a fairly small number of items.8

 In the three illustrations

that follow this section, the class means were based on as few as 1

substitution and as many as 11 substitutions. If there are no comparable or

directly adjusted substitutions in the item stratum for the geographic area

in question, BLS said the computer routines would search other item strata

or geographic areas that had been defined as similar until an item stratum

with at least one comparable and/or directly adjusted substitution is

found. For example, if there were no comparable or directly adjusted

substitutions in women’s coats and jackets in Urbantown in

November 1997, the computer would search for comparable or directly

adjusted substitutions in women’s separates and sportswear stratum in

Urbantown in November 1997.9

When comparable and/or directly adjusted items are identified, either in

the original item stratum in the original geographic area or in similar strata

or areas, a weighted-average price change is determined. BLS then assigns

this weighted average to all class-mean replacement items, in that item

stratum, in that geographic area, in that month. For example, assume an

item stratum in a geographic area contained eight items with equal

weights. Of those eight items, one is the item under review, which is a

not-comparable substitution. The other seven are one comparable

substitution whose price has increased by 5 percent, one directly adjusted

substitution whose price has increased by 1 percent, and five items that

are not substitutions. Only the comparable and the directly adjusted

7

Because the class-mean method only includes comparable and/or directly adjusted substitutions, it

also excludes all linked substitutions from its calculations.

8

Less than 4 percent of the 872,829 monthly or bimonthly price quotations in the CPI were

substitutions in 1997. However, the rate of substitutions varied by major components, ranging from

12.8 percent for apparel items to 1.4 percent for food items.

9

According to BLS officials, judgment was used to establish fairly elaborate search routines for the

class mean. Officials said they ordered the item strata in terms of their similarity with the item stratum

in the geographic area under consideration. For example, in the example given here, if there were no

comparable or directly adjusted substitutions in the women’s separates and sportswear item stratum,

the routine would perform a search on the women’s dresses item stratum. If there were no comparable

or directly adjusted substitutions in that item stratum, the computer would perform a search on the

women’s underwear, nightwear, and accessories item stratum. In other item strata, such as new cars,

the computer routine would search other geographic areas for comparable or directly adjusted

substitutions. For example, if there were no comparable or directly adjusted substitutions for new cars

in the New York City suburbs, the routine would search New York City.

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Class-Mean Method of Adjustment

substitutions would be used to calculate the class mean. The percentage

changes would be added together for a total of 6 percent, and divided by

the number of substitutions used. The result would be an average increase

of 3 percent, which would be the price relative for all class-mean

substitutions in that item stratum in that geographic region for that month.

Of course, the computations that BLS makes to obtain a weighted-average

price change are more complex than those in the illustration. For example,

BLS assigns a weight to each item in a stratum to reflect its relative

importance to consumers. (The weights are based on consumer spending

patterns with the larger weights assigned to items on which consumers

spend the most.) BLS uses these weights in calculating the overall net price

change (price relative) for the class-mean method. Because the price

change of each item is multiplied by the weight of the item, price changes

in items with large weights are likely to have a greater impact on the

overall net price change than price changes in items with smaller weights.

Price relative calculations for the class-mean method are made by

computer routine after all of the month’s prices have been collected and

the replacement items have been reviewed by the commodity analysts.

Each month, a single price relative is computed for each item stratum in

each of the CPI geographic areas that BLS has designated for the class mean

and that has at least one not-comparable substitution.

How Quality

Improvements Are

Accounted for in the

Class-Mean Method

Quality improvements are accounted for in the class-mean method exactly

as they are in the linking method (see app. VI). Conceptually, under the

class-mean method, BLS divides any difference in price between the old

item and the replacement item into two parts—pure price and quality. BLS

makes the implicit assumption that the pure price change is an amount

that can be estimated by the rate of price change that occurred for a

subset of the same types of items in the same geographic area. In other

words, BLS assumes that the pure price change is the price relative

calculated through the class-mean method. BLS assumes that any remaining

difference in price—the residual—reflects differences in quality between

the old item and its replacement. This residual is excluded from the price

relative calculation because the CPI is designed to reflect only pure price

change.

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Class-Mean Method of Adjustment

Examples of BLS’ Use

of the Class-Mean

Method

The following three examples of BLS’ use of the class-mean method come

from our interviews with three BLS commodity analysts. See appendix I for

a detailed discussion of how these examples were selected. According to

the commodity analysts and their supervisors, these examples illustrate

how the class-mean method works. These examples show analysts’

decisions when the replacement is different from the old version and is

viewed as a dissimilar item.

Each example includes a price calculation, showing the percentage change

in price that went into the CPI for that month as a result of the class-mean

adjustment. Each percentage change in price is applicable only to the

particular case illustrated. The examples are not intended to be

representative of the percentage changes that occurred for similar kinds of

substitutions in which class-mean adjustments are made. Nor are the

percentage changes intended to be representative of the impact that

class-mean adjustments have on the CPI.

Each example includes (1) a table showing the specifications of the old

version and the new version that replaced it, (2) the analyst’s reasons for

judging the two versions to be not comparable, (3) the rationale for

selecting the method of adjustment, and (4) the calculation of price

change that was made. Within each table, differences in specifications

between the old and new versions are highlighted by shading.

Example 1 - Bedroom

Linens (Under the

Linens, Curtains,

Drapes, and Sewing

Materials Item

Stratum)

The analyst decided that the new version of a bed dust ruffle was not

comparable with the old version. The substitution was adjusted using the

class-mean method, which was the designated method of adjustment for

this item stratum.

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Class-Mean Method of Adjustment

Table V.1: Characteristics of Two

Versions of a Dust Ruffle Description Old version New version

Specifications

Quality First First

Item priced Dust ruffle Dust ruffle

Style Ruffles Ruffles

Size Standard, twin, or single Queen

Fabric Woven Woven

Fiber 90 percent cotton 90 percent cotton

Backing No backing No backing

Brand/label name Different from the new 

version

Different from the old version

Price information

Amount $39.12 $199.99

Type of price Sale Regular

As of August October

Collected/imputed Imputed Collected

 Specifications that differ between old and new versions

Source: BLS.

Analyst’s Reasons for

Deciding the Items Were

Not Comparable

The analyst said that the new version of the ruffle was different in size

from the old version because it was a queen-size dust ruffle, as compared

to the old version which was a single-size dust ruffle.10 Therefore, the

versions were not comparable, and an adjustment had to be made.

Rationale for Selecting the

Method of Adjustment

For not-comparable substitutions in this item stratum, BLS designated the

class-mean method as the standard method of adjustment for substitutions

that were not comparable. In this instance, the class-mean adjustment

code was generated by computer routines because the price difference

between the two versions exceeded a predetermined level. As the analyst

decided that this substitution was not comparable, the class-mean

adjustment code was not changed, and the class-mean method of

adjustment was used.

10BLS price takers can report that the bedroom linens fall into one of five sizes: (1) standard, twin, or

single, (2) full, (3) queen, (4) king, or (5) other. Throughout this discussion, we refer to the standard,

twin, or single-size dust ruffle as a single-size dust ruffle.

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Class-Mean Method of Adjustment

Calculation of Price

Change

The price calculation for the class-mean method is done entirely by

computer routines without the direct involvement of the analyst. The

method calculates a rate of price change based on the price movement of

comparable and/or directly adjusted prices in the same item stratum in the

same geographic area. In this instance, according to BLS, there was only

one comparable substitution in the same item stratum in the same

geographic area, and that served as the class mean. The comparable

substitution was for a quilt and comforter whose price had changed from

$179.99 to $179.00. Therefore a –0.5 percent rate of change was calculated

for this item stratum in this geographic area for use with class-mean

adjustments for October 1997, and the price of the old version of the dust

ruffle was adjusted by –0.5 percent, from $39.12 to $38.91.11 This means

that the CPI in October 1997 reflected the same percentage change for this

dust ruffle.

Example 2 - Woman’s

Parka (Under the

Women’s Coats and

Jackets Item Stratum)

The analyst decided that the new version of a woman’s parka was not

comparable with the old version. The substitution was adjusted using the

class-mean method, which is the designated method of adjustment for this

item stratum when direct adjustments cannot be made.

11The price for the old version was an imputed price. BLS officials said that, when prices are

unavailable (e.g., because the item is out of season) they impute the prices of those items using the

same imputation method that is used for the linking method.

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Class-Mean Method of Adjustment

Table V.2: Characteristics of Two

Versions of a Woman’s Parka Description Old version New version

Specifications

Type Heavyweight Heavyweight

Design Parka Parka

Body fiber Leather Leather

Brand/label name Local brand name Different local brand name

Size range Junior/misses Junior/misses

Length Fingertip length Fingertip length

Details/ features Hood No hood

Other information Fur-like lining Fur-like lining

Other information Gold Brown

Price information

Amount $153.45 $79.99

Type of price Regular Regular

As of August October

Collected/imputed Imputed Collected

 Specifications that differ between old and new versions

Source: BLS.

Analyst’s Reasons for

Deciding the Items Were

Not Comparable

The analyst noted that there was a big difference in the prices of the old

and the new versions ($153.45 compared with $79.99). The analyst also

said that the research BLS had conducted to develop hedonic models for

direct adjustments had found that hoods could influence the price of a

coat. Furthermore, he was not familiar with the brand names of the old

and new versions and did not know how they might differ in terms of

quality. According to BLS, there are thousands of brands of women’s coats,

and it is not possible for commodity analysts to be familiar with all of

them. Even though there is a hedonic regression model for the women’s

coats and jackets item stratum, the analyst could not make a direct

adjustment because the model did not contain any cost factors for

differences in brand names. Taking all of this into consideration, the

analyst decided this substitution needed to be adjusted by an indirect

method.

Rationale for Selecting the

Method of Adjustment

For not-comparable substitutions in this item stratum, BLS has designated

the class-mean method as the standard method of adjustment if a direct

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Appendix V 

Class-Mean Method of Adjustment

adjustment could not be made. In this instance, the computer routine had

generated a class-mean adjustment code because the price difference

between the two versions exceeded a predetermined level. As the analyst

decided that the substitution was not comparable, and a direct adjustment

could not be made, the computer-generated code was not changed, and

the substitution was adjusted using the class-mean method.

Calculation of Price

Change

The price calculation for the class-mean method is done entirely by

computer routines without the direct involvement of the commodity

analyst. The method calculates a rate of price change based on the

observations for comparable and/or directly adjusted substitutions in the

same item stratum in the same geographic area. In this case, a BLS

computer routine found three comparable substitutions in the original

item stratum and geographic area. These were substitutions for (1) a

heavyweight leather jacket, for which the price had risen by 1.9 percent,

(2) a heavyweight polyester jacket, for which the price had fallen by

29.8 percent, and (3) a heavyweight leather anorak, for which the price

had risen by 69.2 percent. There were no directly adjusted substitutions in

this item stratum and geographic area.

The class mean, which is a weighted average of these three items, was

calculated to be 6.1 percent for October 1997. Therefore, the price of the

old version was adjusted by 6.1 percent, from $153.45 to $162.81. This

means that the CPI in October 1997 reflected the same percentage change

for this version of a woman’s jacket.

Example 3 - New Car

(Under the New Cars

Item Stratum)

The analyst decided that the new version of a new car was not comparable

with the old version. The substitution was adjusted using the class-mean

method, which was the designated method for not-comparable

substitutions in this item stratum when direct adjustments could not be

made.

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Class-Mean Method of Adjustment

Table V.3: Characteristics of Two

Versions of a New Car Description Old version New version

Specifications

Model year 1997 1998

Number of doors 4-doors 4-doors

Body type Sedan Sedan

Number of cylinders 4 4

Engine displacement or 

size

1.6 liters 1.6 liters

Transmission 3-speed standarda 1722a

Options package

Rear defogger Yes Yes

Power steering Yes Yes

AM/FM cassette No Yes

Tilt wheel No Yes

Power windows, locks, 

and mirror

No Yes

Air conditioning Yes Yes

Price information

Amount $14,010 $14,408

As of August October

Collected/imputed Collected Collected 

 Specifications that differ between old and new versions

aAlthough this information was reported on the CRL, the analyst for new cars stated that, in fact,

both the old and new models of this car had 4-speed automatic transmissions.

Source: BLS.

Analyst’s Reasons for

Deciding the Items Were

Not Comparable

A 1998 model of a car had replaced the 1997 model. According to the

commodity analyst, the characteristics of the new version, and publicly

available industry information, showed that the 1998 model contained

significant quality changes over the 1997 model. However, the analyst did

not have the information that would have allowed a direct adjustment to

be made because the automaker had not provided sufficient information

to BLS, and the information provided by other automakers could not be

applied to this model.

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Class-Mean Method of Adjustment

Rationale for Selecting the

Method of Adjustment

In this case, the computer-generated default comparison code was

comparable based on the level of the price change. If the analyst had

judged the substitution to be comparable, the price change would have

been 2.8 percent. However, the analyst stated that publicly available

industry information indicated that there were significant differences in

the features of the old and new versions. In the analyst’s opinion, quality

changes had been made, but the automaker had not provided the

information necessary to make a direct adjustment; and the information

provided by other automakers was not applicable to this model. Therefore,

the analyst inserted a code indicating that the class-mean method should

be used. In the new cars item strata, the analyst stated, the class mean is

always used when the manufacturer makes significant quality changes to a

new year’s model but does not provide the information to allow BLS to

make direct adjustments.

Calculation of Price

Change

The price calculation for the class-mean method is done entirely by

computer routines without direct involvement by the commodity analyst.

The method calculates a rate of price change based on other changes in

the same item stratum in the same geographic area. In this instance, a BLS

computer routine searched for all the comparable and directly adjusted

substitutions in the item stratum of the substituted item in its geographic

area. Of the 11 substitutions that were found, 5 were comparable

substitutions and 6 were directly adjusted substitutions. The 11

substitutions, which had price changes ranging from a 0.3 percent

decrease to a 10.5 increase, were all used to calculate a weighted-average

price increase of 4.0 percent. Therefore, the price of the 1997 model was

imputed to have risen by 4.0 percent, from $14,010 to $14,570. This means

that the CPI in October 1997 incorporated the same percentage change for

this car.

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Appendix VI 

Linking Method of Adjustment

BLS’ linking method is an indirect adjustment method. It uses imputations1

to produce rates of price change when an item in the CPI is replaced with a

substitution that is not comparable and no other adjustment method can

be used. (BLS also refers to these rates of price change as price relatives.)

With the linking method, BLS makes two fundamental assumptions: (1) the

price change applicable to the not-comparable substitution cannot be

directly calculated and (2) the best available estimate of this price change

is the rate of price change that occurs for the same type of items in the

same geographic area. If prices for these items went up or down 5 percent,

then the price of the item in question is imputed to go up or down

5 percent as well.

Background According to BLS, the linking method is one of several adjustments that can

be used when a BLS price taker submits a replacement—a new

version—that a commodity analyst judges to be very different from the old

version (the versions are not comparable). The difference between the

new and old versions is so large, in the analyst’s view, that a determination

cannot be made as to whether it is due solely to pure price change. In

addition to such a difference, two other conditions must also exist for a

commodity analyst to designate the linking method: (1) data are not

available to use a direct adjustment method and (2) BLS has not designated

use of the class-mean method for the item’s-in-question item strata. In

other words, analysts are to use linking when they cannot use any other

adjustment method. (The direct adjustment and the class-mean methods

are discussed in apps. IV and V, respectively.)

When faced with not-comparable substitutions in 1997, BLS commodity

analysts used the linking method to determine price changes for

36 percent of the 12,131 adjusted substitutions in 1997 involving nonrent

items. The use of linking was also widespread. It was used in nearly all of

the nonrent item strata in which an adjustment was made in 1997. In

addition, a majority of the adjustments for two CPI components—food and

beverages and medical care—were calculated using the linking method.

1

Imputation is a term used by BLS to indicate that the actual price of the substitution is not used.

Instead, an average is calculated from the price change experienced that month by the same type of

items in the CPI to handle a missing or unusable price quotation.

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Linking Method of Adjustment

How Price Changes

Are Calculated With

the Linking Method

In the linking method, the new version is put aside in calculating the price

change. Instead, a procedure is followed to impute a rate of change that is

based on the remaining items priced in the appropriate item stratum. A

first step in this procedure is to identify the item strata category, which

contains items that are similar by definition to the old version. There are

over 200 of these categories, and they are replicated for each geographic

area in which BLS collects CPI data. The item stratum that is used must be

for the same geographic area and month in which the replacement

occurred. For example, if a price taker in Urbantown made a

not-comparable replacement for a soup in November, the linking method

would use the canned and packaged soups item stratum for Urbantown for

November.

Next, an average of price change rates is calculated for the applicable item

stratum. In essence, BLS excludes from this computation all items that

entered the item stratum during the month through the linking method, as

well as those items that for various reasons do not have a usable price,

such as a seasonal item that is temporarily unavailable. BLS includes all

other items in that stratum in the computation—those with a price change

and those with no change in price. For these items a price relative, which

BLS refers to as a weighted-average price change, is determined for the

item-stratum index for that geographic area.2

 This weighted-average price

change, expressed as a percentage, is assigned to all linked replacement

items for that item stratum, month, and geographic location.

The calculations for a weighted-average price change are complex but

basically involve two concepts: determining an average and weighting the

items that are averaged. For example, assume an item stratum in a

geographic area contained six items with equal importance in the CPI. Of

those 6 items, 4 had no change in price during the month, 1 had a price

increase of 20 percent, and 1 was a replacement that was going to be

adjusted by the linking method. The replacement item would be put aside,

and the total of the price change for the 5 items (20 percent) would be

divided by 5, the number of items remaining with usable prices. The result

would be an average increase of 4 percent—the price relative for the

geographic area’s item-stratum index for the replacement item, which

would be used only for that month.

Before calculating the average price change, BLS assigns a weight to each

item in an item stratum to give proportionate emphasis to it in relation to

2

Each month BLS calculates indexes for each item stratum and geographic area, which total to more

than 8,000 indexes. BLS refers to these as “item stratum-index areas,” which are aggregated into a U.S.

city average index for all items.

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Appendix VI 

Linking Method of Adjustment

other items in the item stratum. (The weights are based on consumer

spending patterns with the larger weights assigned to items on which

consumers spend the most.) BLS uses these weights in calculating the

overall weighted-average price change (price relative) for the linking

method. Because the change in the price of each item is multiplied by the

item’s weight, price changes in items with large weights are likely to have

greater impact on the overall net price change than price changes in items

with smaller weights.

Price relative calculations for the linking method are made by computer

routine after all of the prices for the month have been collected and the

replacement items have been reviewed by the commodity analysts. A

single price relative is computed for each item stratum as appropriate for

the month. Normally, this price relative is most heavily influenced by items

that were not substitutions in the item stratum, which generally are most

items.

According to BLS, the use of the linking method is the same as setting aside

the individual price quotation from the CPI calculations for the period. That

is, although the collected price of the item is not used in the CPI that

month, it is still represented in the CPI through a weighted average of the

same type of items that are in the CPI for that month. Then in the following

pricing period the price that was previously set aside is used for the price

comparison in the next month.

How BLS Accounts

for Quality Change in

Using the Linking

Method

When using the linking method, BLS makes the implicit assumption that the

pure price change is an amount that corresponds to the rate of price

change that occurred for the same type of items in the same geographic

area. In other words, BLS assumes that the pure price change is the price

relative calculated through the linking method. BLS assumes that any

remaining difference in price—the residual—reflects differences in quality

between the old version and its new version. This residual is excluded

because the CPI is designed to reflect only true changes in price.

BLS’ exclusion of quality in the linking method can be demonstrated using

example 1 at the end of this appendix. There was a difference of $0.128 in

the effective (per ounce) price of the two soups.3

 If the commodity analyst

had determined that the two soups were comparable, a 34.5 percent

3

To make reading the appendix easier, we rounded the effective price per ounce amounts. The

numbers we used for rounding appeared on the listing that the commodity analysts use to review the

substitutions. For instance, the difference in effective price for these two soups was $0.12760—the

price per ounce of the new version ($0.49737) minus the price per ounce of the old version ($0.36977).

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Linking Method of Adjustment

increase would have entered into the CPI as a pure price change. Or, if the

commodity analyst had determined that the soups were not comparable

and the $0.128 difference between the soups was entirely due to better

ingredients (quality improvement), a direct adjustment would be made. If

under this adjustment the entire difference in price was deemed to have

resulted from better ingredients, no price increase would have entered

into the CPI. But neither of these events occurred.

Instead, the two soups were considered by the commodity analyst to be

not comparable because there was a weight change and a change in

ingredients between the two versions and through the linking method a

price relative increase of 0.58 percent was computed. To conceptually

allocate the $0.128 difference to pure price and quality, BLS first applies the

rate of change for this soup (0.58 percent) to the effective price of the old

version ($0.370) to obtain an imputed price ($0.372). Then by subtracting

the price of the old version from its imputed price BLS obtains the change

in pure price ($0.372 - $0.370 = $0.002). BLS then assumes that the residual

($0.128 –$0.002 = $0.126) is a quality increase. According to BLS, $0.002 is

included in the CPI as a price increase; whereas the $0.126 is excluded from

the CPI because it is the quality difference between the two soups.

Examples of BLS’ Use

of the Linking Method

The following two examples of BLS’ use of the linking method come from

our interviews with two BLS commodity analysts. According to the

commodity analysts and supervisors, these examples are illustrative of the

substitutions in which they use the linking method in their respective CPI

components. These examples show analysts’ decisions when the

replacement is extremely different from the old version and is viewed as a

dissimilar item.

Each example includes a price calculation that shows the percentage of

changes in price that went into the CPI for that month as a result of using

the linking method. They are applicable only to the particular cases

illustrated. They are not intended to be representative of the percentage of

changes that occurred for similar kinds of substitutions in which the

linking method was used. Nor is the percentage change intended to be

representative of the impact that the linking method has on the CPI.

Each example includes (1) a table showing the characteristics of the old

version and the new version that replaced it, (2) the analyst’s reasons for

judging the two versions to be not comparable, (3) the rationale for

selecting the method of adjustment, and (4) the calculation of price

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Linking Method of Adjustment

change that was made. Within each table, differences in specifications

between the old and new versions are highlighted by shading.

Example 1 - Packaged

Soup (Under Canned

and Packaged Soup

Item Stratum)

A new version of packaged soup was substituted for the old version and,

as shown in table VI.1, certain characteristics of the two versions differed.

The analyst concluded that the two versions were not comparable and

designated linking as the method of adjustment.

Table VI.1: Characteristics of Two

Versions of a Packaged Soup Description Old version New version

Specifications

Where purchased (in 

store)

Shelf Shelf

Type Dried Dried

Brand classification Nationally marketed brand Nationally marketed brand

Flavor Chicken Chicken

Other major ingredients Pasta and beans Pasta and herbs

Packaging Envelope Envelope

Weight 4.3 oz. 3.8 oz.

Other features Just add water

Cooks in about 15 minutes

Just add water

Cooks in about 15 minutes

ZZ99a Chicken flavor with pasta 

and beans

New country chicken with 

pasta and herbs

Price information

Amount $1.59 $1.89

As of October November

Collected/imputed Collected Collected

Effective price per ounce $0.36977 $0.49737

 Specifications that differ between old and new versions

aA designated line for the price taker to put information that may not belong elsewhere on the

checklist.

Source: BLS.

Analyst’s Reasons for

Deciding Items Were Not

Comparable

The analyst said that the change in “other” major ingredients from beans to

herbs indicated a change in the item. According to the analyst, this was

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Linking Method of Adjustment

confirmed in the “ZZ99” specification, which reiterated that the ingredients

had changed from beans to herbs.

A weight change also indicated to the analyst that these versions were not

comparable. The commodity analyst said that a decrease from 4.3 to 3.8

ounces suggested a change from one standard size to another and that

made the versions not comparable. The comparability criteria that BLS

established for this item stratum allow the analyst to exercise judgment in

determining if the change in weight is substantial enough to make the

version not comparable.

The comparability criteria for the item stratum, to which the analyst

referred in making the comparability decision, indicated whether a change

in various specifications between the old and the versions would make the

versions not comparable. According to the criteria, a substantial change in

either weight or “other” major ingredients would make the versions not

comparable.

Rationale for Selecting the

Method of Adjustment

Because the class-mean method had not been designated for the item

strata and adequate information needed to make a direct adjustment was

not available, the analyst chose the linking method. To designate the

linking method in this case, the analyst had to override another adjustment

code that was computer generated. A computer routine automatically

calculates any change in the effective prices (the unit prices) between the

old and new versions. When there is a change that meets or exceeds

predetermined amounts, the computer is programmed to use particular

comparison codes. In this case, the computer defaulted to a comparable

comparison code signifying that the old and new versions were alike, and

the computer generated a price increase of 34.5 percent. However,

because the analyst judged the old and new versions to be not comparable,

the analyst overrode this comparison code.

Calculation of Price

Change

The calculation of price change for the linking method is done entirely by

computer routine without direct involvement by the commodity analyst.

The method calculates a rate of price change based on the price movement

of usable collected prices in the item-stratum index for the area. For the

canned and packaged soup item stratum in this soup’s geographic

location, a 0.58 percent rate of change was calculated for November 1997.

This means that the CPI in November 1997 reflected the same imputed

increase (0.58 percent) for this package of chicken soup.

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Example 2 -

Multivitamin Tablets

(Under Internal,

Respiratory, and

Over-the-Counter

Drugs Item Stratum)

A new version of multivitamin tablets was substituted for the old version

and, as shown in table VI.2, certain characteristics of the two versions

differed. The analyst concluded that the old and new version were not

comparable and designated the linking method to adjust the price of the

old version.

Table VI.2: Characteristics of Two

Versions of Multivitamin Tablets Description Old version New version

Specifications

Type Vitamins Vitamins

Form Plain tablets Plain tablets

Brand Store brand Store brand

Size 130 tablets 100 tablets

Units of vitamin C, per tablet 60 60

Units of vitamin D, per tablet 400 400

Units of vitamin E, per tablet 30 international units 45 international units

Labeling "one daily plus minerals" "for mature adults"

Price information

Amount $6.49 $6.49

As of September October

Collected/imputed Collected Collected

 Specifications that differ between old and new versions

Source: BLS.

Analyst’s Reasons for

Deciding Items Were Not

Comparable

The commodity analyst decided that the two versions were not

comparable because there were so many important differences between

their specifications. These differences included the number of tablets in

the bottles, the potency of vitamin E, and the labeling of the bottles.

Rationale for Selecting the

Method of Adjustment

For substitutions that are not comparable in this item stratum, BLS

designated the linking method as the standard method of adjustment when

other methods are not usable. In accordance with this procedure, the

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Linking Method of Adjustment

analyst marked this case for adjustment by the linking method. To do so,

the analyst had to override a comparable comparison code that generated

a price change of 0.0 percent (no price change).

The analyst considered the possibility of using an adjustment method to

directly adjust the price of the old version rather than using the linking

method. According to the analyst, a direct adjustment would have been

made to the price of the old version if the only change had been the

number of tablets. (This would have been done by computing the cost per

tablet of 130 tablets and then multiplying that cost by 100 tablets.)

However, according to the analyst, the changes in vitamin E potency and

label information prevented a direct adjustment because there was no

sensible way to directly adjust the price of the old version for these

changes. Also, because a class-mean method had not been designated for

the item stratum, this method of adjustment could not be used. The analyst

was therefore left with only the linking method.

Calculation of Price

Change

The calculation of price change for the linking method is done entirely by

computer routine without direct involvement by the commodity analyst.

The method calculates a rate of price change based on other changes in

the item stratum in the same geographical area. For over-the-counter

drugs in the same geographical area, a minus 0.58 percent rate of change

was calculated for October 1997. The CPI in October 1997 effectively

reflects the same percentage decrease for this item, even though the old

version of vitamins has been replaced by a new, not comparable bottle of

vitamins.

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Appendix VII 

Measurement of Residential and

Homeowners’ Equivalent Rents

The housing component of the CPI includes residential rent and

homeowners’ equivalent rent. Residential rent measures the changes in

rents paid by renters in the United States. Homeowners’ equivalent rent

measures the changes in rental value of owner-occupied houses or

apartments. BLS determines this value using a rental equivalence method,

which estimates the amount of rent that would be paid for owner-occupied

housing if it were rented.1 BLS refers to homeowners’ equivalent rent as

REQ.

In comparison to changes in the prices of other items in the CPI, price

changes in residential rent and REQ have the greatest influence upon the

CPI. For example, as of December 1997, the relative importance (a concept

explained in app. II) of these two rent items combined to almost

26 percent (19.9 percent for REQ and 5.8 percent for residential rent). This

means that changes in rent directly affected slightly more than one-quarter

of all of the price changes that were measured in the CPI in 1997. No other

item in the CPI has as much influence as either residential or homeowners

equivalent rent items (new cars was the next item in importance in 1997 at

less than 4 percent).

BLS collects and processes residential rent and REQ in several ways that are

different from other items in the CPI, including those in the rest of the

housing component. For example, the selection of housing units from

which rent prices are obtained is done using a survey that is separate from

the survey used to select other housing and CPI items. This appendix

provides information about BLS’ procedures and practices for residential

rent and REQ.

Background The CPI housing survey is used to estimate changes in rent for both renters

and home owners if they were to pay rent for the use of their homes. The

CPI housing survey sample is made up of approximately 36,000 rental units

and 26,000 owner units. The housing units in the sample were selected

from two sources: the 1980 Decennial Census for units built before 1980

and the U.S. Bureau of Census’ sample of building permits for units built

1

The rental equivalence method seeks to measure the costs of consuming housing services over time

rather than the value of housing as an asset that might appreciate over time. The latter approach was

used before 1983. For further information about this earlier method, see Consumer Price Index:

Cost-of-Living Concepts and the Housing and Medical Care Components (GAO/GGD-96-166, Aug. 26,

1996).

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Homeowners’ Equivalent Rents

after 1980.2 A sample of renters has been chosen from 85 geographic areas,

which BLS refers to as primary sampling units (PSU).

The CPI uses the rental units in the CPI housing survey to determine the

price change for both residential rent and REQ. In the rental equivalence

method that is used for REQ, rental units are matched to owner units in the

CPI housing survey, and the change in the rents reported for those rental

units is used to adjust the REQ for the matching homeowner units. In

matching rental units with homeowner units, BLS takes into account their

locations (must be in the same PSU), structure type (e.g., single-family

dwellings), and whether the units have air conditioning.

The basis for determining REQ, however, is different from that used for

residential rent in one important way. The rental value of homeowner

units excludes utilities; the rents of residential renters include any utilities

paid by landlords. A BLS official said that approximately 20 percent of the

rental units have their utilities provided by the landlord. Therefore,

according to the official, the cost of landlord-provided utilities is

subtracted from the rent whenever it is used to calculate REQ.

BLS divides the rental units in the housing survey into six groups, with the

units in each group to be contacted twice a year. For example, units in one

group are priced in January and again 6 months later in July; units in a

second group are contacted in February and again in August. BLS price

takers are to record basic information about the rental unit, any extra

charges paid for the unit, rent subsidies, and other information, such as

any familial relationship between the renter and the landlord.

After the data have been collected by the price takers and entered into BLS’

computer system, CRLs are generated for review by commodity analysts.

CRLs are computer printouts of data for the units that have certain

problems, inconsistencies, or changes requiring a commodity analyst’s

attention. Current and historical data are printed for each unit as well as

the reason why a CRL was triggered.

The reasons that trigger the printing of a CRL include

• rent increases or decreases of 20 percent or more;

2

In January 1999, BLS revised the CPI housing survey with a sample of housing units based on the 1990

Decennial Census and will update the sample with building permits for units built after 1990.

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Measurement of Residential and

Homeowners’ Equivalent Rents

• a message from the price taker, such as the rent increased because a new

tenant moved in, or the rent did not go up as much for one tenant as for

other tenants because of the number of years the tenant had been renting;

• inconsistencies, such as a rental unit with “owner” data reported for it;

• a change in housing tenure, such as from renter to owner occupied;

• dollar values reported to questions in the survey instrument about free

rent, rent reductions, or any extra charges;

• changes in utilities;

• any differences in house trailers, such as a new trailer on the same lot;

• structural changes, such as an addition of a bathroom; and

• anything that the commodity analyst has asked to be programmed for

review in order to follow up on an unusual circumstance.

The housing commodity analysts use the CRLs to (1) review the units’

eligibility for use in the CPI, (2) determine whether adjustments should be

made for changes in the units, (3) identify problems that the price takers

have in locating units or answering the questions on the CPI housing survey

questionnaire, and (4) communicate with the price takers, (e.g., follow up

on a particular issue). After the analysts have reviewed the CRLs and

approved the information or made corrections, adjustments, or changes,

the units are ready to be used in calculating the CPI.

The CPI measures rent price changes by comparing the rents tenants pay

with the rent they paid 6 months earlier. Before the comparison is made,

any necessary adjustments to the current rent for the month are to be

made. Some adjustments are automatically identified and made during

computer processing of the data. Others are identified by commodity

analysts.

Adjustments for

Changes in Units

Adjustments are made so that the same unit with the same features is

priced each time (every 6 months). If a feature of the rental unit has

changed, BLS makes a dollar adjustment to the current rent so the unit is

comparable to what it was earlier. This adjustment is for that month and is

not retained for future comparisons.

BLS does not make adjustments for ordinary maintenance (e.g., painting or

replacing an appliance) as these mostly restore the unit to its earlier

condition. However, when the landlord provides an appliance or service,

BLS lowers the current rent because the cost to live in the unit has gone

down. This situation would occur, for example, if the landlord installed a

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Measurement of Residential and

Homeowners’ Equivalent Rents

clothes washer and dryer in the unit. The tenant would no longer have to

use a laundromat (or privately owned washer and dryer).

However, if the landlord stops providing an appliance or service, BLS raises

the current rent because the cost to live in the unit has gone up. This

situation would occur, for example, if the rent for a unit no longer

included the cost of electricity and the tenant had to begin paying for it

separately.

BLS makes these adjustments even when the landlord adds or removes a

feature but does not change the rent. It also makes these adjustments

when the landlord raises the rent for adding an appliance or service or

lowers the rent for removing something. In all of these cases, BLS is

attempting to make the current unit comparable to what it was 6 months

earlier when data were last collected. (This is the reverse of the

adjustments made elsewhere in the CPI where adjustments are made to the

previous version to make it comparable to the current version of the

replacement.)

Any adjustments made to the current unit to make it comparable with

what it was 6 months earlier are dropped after the comparison is made.

Whatever features the current unit now includes become the basis against

which the unit will be compared to 6 months in the future. For example, if

an appliance were newly installed, BLS would adjust current rent, in effect,

to remove the appliance. However, the data records for the unit would

include this appliance for future comparisons because the renter’s cost of

living in the unit will have decreased.

BLS makes adjustments for changes to features of the rental unit; it does

not make adjustments for changes in the tenants. For example, the

landlord may charge a pet fee if a tenant has a pet and the previous tenants

paid a fee. BLS would not show a decrease in rent if the new tenants did not

have a pet and did not pay the fee. However, if the landlord stopped

charging pet fees altogether, this decrease in rent would appear in the CPI.

In summary, if the value of the unit has gone up since data were last

collected, a subtraction to the current month’s rent is made. If it is costing

more for the tenants to live there (by getting less than before), an addition

to the current month’s rent is made.

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Measurement of Residential and

Homeowners’ Equivalent Rents

Adjustments Are

Made by Computer

and by Analysts

In calendar year 1997, approximately 6,180 adjustments were made

because of changes in rental units. Nearly all (91 percent) of the

adjustments were made automatically by computer routine without direct

involvement of the housing commodity analysts. The other adjustments

(9 percent) were made by housing commodity analysts. In addition to

these adjustments, every rental unit is adjusted by computer routine for

age depreciation.

Automatic Adjustments by

Computer

The rent adjustments that are automatically identified and made by

computer routine involve only direct adjustments. That is, the item or

service in the housing unit that changed is clearly identifiable, and its cost

can be reasonably calculated. According to BLS, automation of these direct

adjustments saves the time and efforts of commodity analysts and enables

calculations and adjustments to be made on a consistent basis. Computer

routines adjust the rent automatically whenever the rental unit has a

change in facilities, utilities, or structure.

Changes in Facilities Prior to January 1999, facilities adjustments included additions or

subtractions of dollar amounts for changes in the provision of appliances

and parking. To determine the dollar amounts for changes in appliances,

BLS used studies published in trade journals. The published average cost of

the appliance was divided by its published average life in months to arrive

at its monthly value. Example 1 at the end of this appendix provides an

illustration of such an automatic adjustment.

Off-street parking costs are based on the PSU’s average of such charges

paid by tenants in the CPI housing survey. This adjustment is made, for

example, if off-street parking is no longer provided by the landlord.

According to BLS, adjustments are no longer made for changes in

furnishings because apartments, BLS concluded, do not change in the

provision of furnishings. They tend to stay furnished or unfurnished.

According to a BLS official, the data BLS used to make appliance

adjustments are not up to date, and there is no cost-effective way to

update them. He said that since the revision of the housing component in

January 1999, BLS makes facilities adjustments for changes only in parking

and air conditioning equipment. Since the majority of automatic direct

adjustments are for changes in the provision of appliances, this will reduce

the number of direct adjustments made to rental units.

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Homeowners’ Equivalent Rents

Changes in Utilities Utility adjustments are made when the landlord alters the provision of a

utility, such as installing a separate meter for an apartment and making the

tenant responsible for payment of the utility. BLS calculates the dollar

amount of utility adjustments in two steps. First, BLS uses Department of

Energy data to determine average consumption amounts by housing unit

for electricity, gas, propane, and oil. These estimated amounts are based

on the rental unit’s location, number of heating and cooling degree days,

number of rooms, and type of structure. Second, to compute the monthly

cost, BLS multiplies the consumption amounts by the average price of

electricity, gas, natural gas, or oil paid by households in the unit’s PSU. The

average price is based on data BLS collects monthly for the CPI.

3

BLS calculates water and sewer utility adjustment dollar amounts by

determining average bills from housing units in the CPI housing survey for

each PSU. The survey gathers data from renters on the amount of their

water and sewer bills.

As previously noted in this appendix, utility adjustments are only made to

the residential rental units. No adjustment is made to REQ because it

already excludes the cost of utilities.

Depreciation and Changes in

Structure

The dollar amounts for various structural changes (e.g., the addition of a

bedroom or bathroom) and depreciation are based on estimates that come

from regression-based formulas. The formulas account for the age of the

unit and a number of structural characteristics. The dollar amounts from

these formulas are then used to adjust residential rent and REQ for

structural changes in the rental units. BLS recomputes these estimates

annually.

Regression-based formulas have been used since January 1988 to account

for the small loss in quality as housing units age (depreciate) over time.

According to a BLS official, the age-bias regression is recomputed every

year, and one-twelfth of the annual bias is applied by computer routine to

every unit in the housing sample each month.

Adjustments by

Commodity Analysts

The housing commodity analysts make three types of adjustments:

“pricing-links-cancel,” “links-pause,” and direct. Of the three types, the

links-pause adjustment is by far the most frequently used. About

3

BLS makes approximations of average costs for wood and coal heat by converting the standard

amount of energy from a cord of wood or ton of coal into gallons of oil, and then using the average

consumption and cost estimations for oil.

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Measurement of Residential and

Homeowners’ Equivalent Rents

80 percent of the adjustments made by commodity analysts in 1997 were

links-pause adjustments.

Pricing-Links-Cancel

Adjustment

In the pricing-links-cancel adjustment, the analyst determines that the unit

is no longer comparable to the unit for which the rent was collected 6

months earlier or that the old rent is no longer accurate for comparison.

Examples of units that, according to BLS, are no longer comparable

include: a house trailer that is replaced with a different trailer, a unit in

which the price taker discovers that BLS has been pricing the wrong unit,

or a unit in which a major structural change has occurred (e.g., the

addition of a swimming pool) and BLS does not have a way to make an

adjustment.

Examples cited by BLS of units for which the old rent is no longer accurate

for comparison include: (1) a unit that the price taker recorded as

government subsidized and for which the renter was not paying the full

rent that was recorded 6 months earlier or (2) a unit in which the renter

was related to the landlord and was not paying the full rent that was

recorded 6 months earlier. Example 2 at the end of this appendix provides

an illustration of a pricing-links-cancel adjustment for a rental unit whose

old rent had been imputed because of a long-term vacancy and was

therefore no longer appropriate for a price comparison.

The pricing-links-cancel adjustment treats the rental unit in the same way

that the linking adjustment treats commodities and services substitutions

that are not comparable (see app. VI). In the pricing-links-cancel

adjustment, the weight of the rental unit is redistributed to housing units

in the PSU of that rental unit. To do this redistribution, BLS uses the rental

units in the PSU of the pricing-links-cancel that have usable prices—units

that had a rent 6 months earlier from which a price change could be

calculated—and a computer routine then calculates the average

percentage change of these rents for that PSU. In effect, BLS assigns the

PSU’s average percentage change to the unit that is adjusted by the

pricing-links-cancel method.

Links-Pause Adjustment In the links-pause adjustment, the commodity analyst is suspicious of the

accuracy of the current rent. In this adjustment, the current month’s rent is

not used in the CPI that month. The current month’s rent is replaced with

an imputed value that is based on rent changes of a subset of housing units

in the unit’s geographic location. In the next pricing cycle, the analyst will

determine the accuracy of the reported rent.

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Homeowners’ Equivalent Rents

Until confirmed, the unit’s rent that was collected 6 months earlier is

adjusted by computer routine. First, the computer calculates the average

change in rent for units in a subset of housing units, which BLS refers to as

a cell. All rental units are assigned to 1 of 18 cells in a PSU. These cells

contain units that have similar characteristics based on the renter-owner

ratio (e.g., the unit is in a location that has equal proportions of owners

and renters) and on the level of rent paid (high, medium, and low). Next,

the computer routine then applies the cell’s rate of change to the unit’s

rent that was collected 6 months earlier. Any difference from a

comparison of the imputed rent and the rent from 6 months earlier goes

into computing the CPI for the current month.

Six months later, the analyst will use rent reported in that period to

confirm the previous rent that the analyst thought was suspicious. If the

two rents are dissimilar (that is, the suspicious rent is not confirmed and

the rent 6 months later is similar to what it was a year earlier), the

computer routine will compare the rent that was imputed 6 months earlier

with the rent most recently collected. Alternatively, if the two rents are

similar (that is, the previous rent is confirmed), then the commodity

analyst will allow the large price change to enter the CPI at this time.

A links-pause adjustment is shown in example 3 where the unit in the

Urbantown PSU had a May 1997 rent of $513 and a November 1997 rent of

$158. The analyst questioned the accuracy of the current month’s

(November) rent because the information about the unit did not indicate a

reason for such a decrease. As a result, the analyst decided to make a

links-pause adjustment. Using the units with usable rents for November

1997 in that unit’s cell, the computer routine calculated an average price

increase of 3.3 percent. Next, the computer applied that increase to the

unit’s May 1997 rent and imputed a rent of $530.208 ($513 x 1.033). In this

example the CPI calculations for November 1997 reflected a 3.3 percent

increase for this rental unit and the additional rental and owner-occupied

units it represents.

As further explained in example 3, BLS collected rent data on the unit again

in May 1998 and generated a CRL for the unit for analyst review. The

analyst used the May 1998 information about the unit to confirm the

accuracy of the reported November 1997 rent. The information indicated

that the tenancy of the unit changed from renter occupied to owner

occupied. Since BLS does not use owner-occupied units in the CPI

calculations, the unit was excluded from CPI calculations.

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According to BLS officials, for the units where the links-pause adjustment

is used, the price increase (or decrease) occurs but with a delay of 6

months (or, as in our example, does not occur). Nonetheless, BLS said the

adjustment prevents large increases or decreases if the rent 6 months

earlier was incorrect. They noted that the size of the inaccuracies during

the lag is smaller than the errors that would be incorporated into the CPI if

erroneous rents were used.

Direct Adjustment According to a BLS official, the housing analysts also directly adjust a

negligible number of units for changes in extra charges that result from

unusual situations. He said these instances are the only occasion in which

a commodity analyst directly enters in a dollar adjustment in the CPI. For

example, a renter may have been paying an additional monthly fee to have

a pet living in the apartment. If the pet dies, the renter no longer pays the

pet fee. In these situations, the analyst will look in the historical data for

the unit to determine the amount of the fee and add the extra charge to the

current rent to make it comparable to the rent of 6 months earlier.

Addition and Deletion

of Housing Units

The sample of housing units that BLS uses in calculating the CPI is not static

and represents the housing stock of the urban population. Rental units are

removed from the sample, and new units are added to the sample.

According to a BLS official, rental units are removed when they no longer

exist because they represent units that drop out of the housing stock. New

rental units are added through new construction. According to BLS, the

new units are not added to replace units that were removed; the new units

are not considered to be substitutions, as would be the case for

replacement of other nonrent items in the CPI.

In 1997, according to a BLS official, 14 rental units were removed from the

housing survey because they no longer existed. Another official

determined that about 15 percent of the rental units in the housing survey

in 1997 entered the survey from new construction permits.

Rental units are lost to the housing sample for various reasons, such as

destruction by floods, tornadoes, and urban renewal. Whenever a rental

unit is lost, BLS does not replace it with another unit. In these instances, BLS

removes the unit and, implicitly, the residential rental and REQ units it

represents, from the computer system. However, according to BLS, if the

building foundation for the lost unit still exists, the address is retained in

the system and price takers are periodically sent to the address to see if

the unit has been rebuilt.

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Measurement of Residential and

Homeowners’ Equivalent Rents

Units are added to the CPI housing survey by using information that is

collected by the Bureau of the Census. New construction permit

information is obtained by Census from the appropriate government

entities. Census then samples from that population of permits and sends

the addresses of these new permits to BLS. BLS then adds the addresses to

the housing sample with representation (weighting) for both residential

rent and REQ in the same manner that it subtracts units that have been

destroyed. Once the address is added, BLS continues to survey that

location.

Accounting for

Quality Change

Whenever a substitution is not comparable to the CPI item it replaced, BLS

will make an adjustment to separate pure price change from price changes

that are due to other factors, such as differences in quality. (BLS refers to

these other factors under the general term quality.) Although BLS has

accounted for this separation when making adjustments to nonrent items,

it has not accounted for such a separation for the types of adjustments

described in this appendix.

Nonetheless, we believe a case can be made for attributing part of a

change in rent to price and another part to quality. We draw this view from

two sets of similarities that exist between the types of adjustments BLS

makes for rent and the adjustment methods it uses for nonrent items. One

set of similarities involve rent adjustments made automatically by

computer routine and the direct adjustment methods used for nonrent

items. In order for these automatic adjustments to be made, there must be

sufficient information about the change to a rental unit and its associated

cost to directly adjust the rent. This is the case for the direct adjustments

used elsewhere in the CPI; there must be sufficient information to directly

adjust the price of the item. If BLS were to consider these adjustments to

rent as direct adjustments, then the assumptions used to account for price

and quality with the direct adjustment method would likely apply as well.

As such, the implicit assumption would be that the entire amount of the

adjustment could be accounted for as quality change. For example, in

example 1 at the end of this appendix, 29 cents was subtracted from the

unit’s rent and this could be accounted for as a change in quality.

The second set of similarities involves the pricing-links-cancel and the

links-pause adjustment methods used to adjust rent and the linking

method used to adjust nonrent prices. Under each method, an average rate

of price change is computed using other rents or other prices. Under the

linking method, BLS assumes that any difference between the imputed

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Measurement of Residential and

Homeowners’ Equivalent Rents

price and the price of the substitution is reflective of quality and,

therefore, not to be included in the CPI. If BLS were to make this same

assumption for the pricing-links-cancel and the links-pause adjustment

methods, any difference—the residual—between the unit’s recorded rent

and the imputed rent could reflect quality differences between the current

unit and what was recorded for it 6 months previously.

As previously stated, BLS has not made this accounting to price and quality

for residential rent and REQ, which represent more than one-quarter of the

CPI.

Examples of BLS’

Adjustments for

Residential Rent and

REQ

The following three examples of BLS’ adjustments to residential rent and

REQ come from our interviews with three BLS housing commodity analysts.

According to the commodity analysts and their section chief, these are

examples of the adjustments that are made in residential rent and REQ. One

example is of an adjustment made by computer routine without direct

involvement of the housing commodity analysts. The other examples are

of analysts’ decisions to use two variations of the linking method.

Generally, these are used when a rental unit is no longer comparable to

the same unit for which the rent was collected 6 months earlier. In the

table for each example, changes between the current unit and its

characteristics 6 months earlier are shaded.

The examples include a calculation that shows the percentage changes in

price that went into the CPI for that month as a result of the adjustments.

These percentages are applicable only to the particular cases illustrated.

They are not intended to be representative of the percentage changes that

occurred for similar kinds of adjustments that are made. Nor is the

percentage change intended to be representative of the impact that these

adjustments have on the CPI.

Example 1 -

Automatic Adjustment

As shown in table VII.1, the landlord made changes in the appliances

furnished in the apartment. To account for the changes in the unit’s

appliances a direct adjustment was made by computer routine without the

direct involvement of a commodity analyst.

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Measurement of Residential and

Homeowners’ Equivalent Rents

Table VII.1: Characteristics of the

Rental Unit Description 6 months earlier Current

Specifications

Number of bedrooms 2 2

Number of bathrooms 1 1

Utilities included in rent No No

Heating fuel Oil Oil

Hot water fuel Oil Electricity

Dishwasher Yes, supplied by landlord None

Washing machine None Yes, supplied by landlord

Dryer None Yes, supplied by landlord

Price information

Amount $500.00 $500.00

As of April October 

 Specifications that differ between old and new versions

Source: BLS.

Analyst’s Reasons for

Not-Comparable Decision

BLS has developed computer routines to identify changes in a rental unit’s

appliances and, when identified, to calculate with preprogrammed data the

dollar value associated with those changes. Commodity analysts are not

involved in making these adjustment decisions.

Rationale for Selecting the

Method of Adjustment

Selecting a method of adjustment was not necessary.

Calculation of Price

Change

According to BLS, a computer routine automatically added 50 cents to the

unit’s current rent for the removal of the dishwasher and subtracted 79

cents for the addition of a washing machine and clothes dryer. Since the

landlord did not provide the utilities, a utility adjustment was not made by

the computer. The computer then compared the adjusted current rent of

the unit ($499.71) to the rent for the unit 6 months earlier ($500.00). The

new rent was 29 cents less than the rent 6 months earlier, a decrease of

0 percent. In effect, no price change was entered for this unit into the data

with which the CPI was computed for October 1997.

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Measurement of Residential and

Homeowners’ Equivalent Rents

Example 2 -

Pricing-Links-Cancel

Adjustment

The rent for the unit increased significantly, as shown in table VII.2. The

commodity analyst determined that the imputed April rent for the unit was

not appropriate for comparison purposes and designated the

pricing-links-cancel method to calculate the rate of price increase between

April 1997 and October 1997.

Table VII.2: Characteristics of the

Rental Unit Description 6 months earlier Current

Specifications

Number of bedrooms 3 3

Number of bathrooms 1 and a half bath 1 and a half bath

Landlord furnishes utilities No No

Price information

Amount $271.325 $400.00

As of April 1997 October 1997

Collected/imputed Imputed Collected

Source: BLS.

Analyst’s Reasons for

Not-Comparable Decision

A lengthy period of vacancy for the unit suggested to the commodity

analyst that the rental amounts for the unit for the two collection periods

should not be compared. The CRL for the unit indicated that the rent had

been imputed for more than 2 years; BLS has no standard or limit on how

long rent can be imputed for a unit. The CRL did not indicate the origin of

the rent on which the imputations were based. The analyst said that the

price comparison for the CPI should not be based on a comparison of a

collected rent with an imputed rent whose origin is unknown.

The analyst said another reason for not using the April rent was that the

unit was in a small geographic area and that a large price increase of about

150 percent (increase from $271 to $400) could cause an upward bias in

the CPI for that area.

Rationale for Selecting the

Method of Adjustment

The analyst first looked at the percentage change in rent to see if it

exceeded what BLS terms a “flinch point,” a mathematically determined

percentage change rate indicating that the change in rent is doubtful and

should not be used in calculating the CPI for that month. According to BLS,

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Appendix VII 

Measurement of Residential and

Homeowners’ Equivalent Rents

the use of the flinch point is a main criterion for making a links-pause

adjustment—the other linking adjustment method used for rental units.

The analyst noted that a percentage change of about 150 percent was

about 3 points above the flinch point. Although this met the criterion, the

amount of difference did not clearly indicate that holding the unit’s

October rent for 6 months was appropriate, which would occur with the

other linking adjustment method.

Another factor the analyst considered was the geographic location of the

unit. The two-story duplex was located in a small geographic area in which

rental units were difficult to keep in the CPI housing survey. The analyst

said that it was desirable to have units with collected rent data, rather than

imputed rental amounts, included in CPI calculations. Therefore, the

analyst chose the pricing-links-cancel method so the unit would be used in

the next pricing period.

Calculation of Price

Change

The calculation of price change for the pricing-links-cancel method is done

automatically by computer routine without direct involvement of the

commodity analyst. The method calculates a rate of price change based on

other units that had usable rents and were located in the unit’s geographic

area. For these rental units, a 0.12 percent rate of change was calculated

for October 1997. This means that the CPI in October 1997 reflected this

same percentage of increase for this rental unit and the owner-occupied

units it represents.

Example 3 -

Links-Pause

Adjustment

As shown in table VII.3, the rent for the unit increased significantly. The

commodity analyst determined that the November rent for the unit could

be inaccurate and designated the links-pause method to calculate the rate

of price increase between May 1997 and November 1997.

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Measurement of Residential and

Homeowners’ Equivalent Rents

Table VII.3: Characteristics of the

Rental Unit Description 6 months earlier Current

Specifications

Number of bedrooms 1 1

Number of bathrooms 1 1

Landlord furnishes utilities Yes Yes

Price information

Amount $513.27 $157.78

As of May 1997 November 1997

Source: BLS.

Analyst’s Reasons for

Not-Comparable Decision

A rent decrease of 69 percent suggested to the commodity analyst that the

unit in November had changed in some major way from what was

recorded for it in May and was no longer comparable.

Rationale for Selecting the

Method of Adjustment

The analyst used two criteria to determine which linking method to use.

The first was whether the percentage change in rent exceeded the flinch

point. The rent change met this first criterion. The second consideration

was whether the same tenants lived there. The analyst indicated that a

change in tenants might explain a large change in rent. The information on

this housing unit indicated that these were the same tenants. Since both

criteria were met, the analyst indicated that the links-pause method would

be used for this unit.

Calculation of Price

Change

BLS took two actions, 6 months apart, that affected the calculations of

price change for this rental unit. For the current month (November 1997),

the links-pause designation caused a computer routine to calculate a rate

of price change based on a subset of other units that were similar to this

rental unit. These similar units were in Urbantown and had usable rents.

For the subset of units, a 3.3 percent increase was calculated for

November 1997. This means that the CPI in November 1997 reflected a

3.3 percent increase for this rental unit and the owner-occupied units it

represents.

BLS collected information on this unit again in May 1998 and, on the basis

of this information, decided that no calculation should be made. BLS

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Measurement of Residential and

Homeowners’ Equivalent Rents

learned that the tenancy for the unit changed from renter occupied to

owner occupied. Because BLS does not use owner-occupied units in

making the monthly CPI calculations, it excluded the unit from the

May 1998 CPI calculation. According to BLS, the unit will remain excluded

from the CPI as long as it is owner occupied. However, the unit would be

returned to the CPI calculation if it again becomes a rental unit.

Page 111 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Table VIII.1 contains information on the relative importance and summary

data on CPI price quotations; substitutions; and methods of adjustment by

major component, expenditure class, item stratum, and entry level item

(ELI) for 1997.

While most column headings in the table are self-explanatory, we believe

that three require some explanation. They are the columns on relative

importance, percent of quotations with price changes, and class mean

and/or overlap. Relative importance shows the share of total expenditures

that would occur if consumed quantities of the items at the stratum level

remained constant. Relative importance is a concept that is related to

expenditure weights, but unlike those weights, which have been

recomputed only about every 10 years or so, BLS computes relative

importance at least annually to reflect the effect of price changes. Relative

importance can be used to show the direct effect an item has on the

overall CPI price change. (See app. II for further information about relative

importance and expenditure weights.)

The price quotations represented by the percent of quotations with price

changes include both those where an increase in price occurred and those

where a decrease in price occurred. Also, these changes in prices were for

goods and services for which a substitution was made and those for which

no substitution was made.1

The class-mean and/or overlap column combines the number of

adjustments made by both methods. BLS was unable to separate the

number of each of these methods by ELI, but officials told us that nearly all

of the substitutions listed in this column were adjusted by using the

class-mean method. This is because BLS has been phasing out use of the

overlap adjustment method.

Table VIII.1 includes two overall totals: all items with residential rent units

and all items without residential rent units. Because the adjustments made

by BLS to residential rent differ from those made elsewhere in the CPI, we

present the totals separately. See appendix VII for information on how

adjustments are made to rental units. In table VIII.1 these adjustments are

reported in the residential rent ELI under the housing component.

Table VIII.1 is further organized as follows: The broadest of the categories

are the seven major components. Components are indicated as totals (e.g.,

1

According to BLS, this column excludes substitutions for which there was no price change between

the two versions of the item.

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Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

food and beverages component totals). Under each component is the

expenditure class category, the next broadest category. Expenditure class

appears bolded in the table (e.g., cereal and cereal products). Adding all of

the numbers in the expenditure class for a given column will equal the

major component total. Under expenditure class are the item strata, which

when totaled in a given column will equal the reported subtotals for

expenditure class. For example, under the expenditure class of cereal and

cereal products the item strata are “flour and prepared flour mixes”;

“cereal”; and “rice, pasta, and cornmeal.”

The final category, as well as the most specific, is the ELI. For example,

under the item stratum of flour and prepared flour mixes are the two ELIs,

“flour” and “prepared flour mixes.” In some cases, only one ELI existed for

a single item stratum. When the item stratum and the ELI were the same

and the stratum was not broken down into additional ELIs, we deleted the

ELI from the table. By doing so, we avoided duplication of information,

since the numbers for both the stratum and the ELI were identical. ELIs do

not have relative importance assigned to them; and, where noted in the

table, some ELIs are not priced.

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Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Table VIII.1: Relative Importance and Summary Data on CPI Price Quotations, Substitutions, and Methods of Adjustment by

Categories for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

All items (with residential rent units) 100.000% 918,561 n/a 35,061

All items (without residential rent units) 74.309 872,829 n/a 28,881

Food and beverages component

total 17.465 459,635 n/a 6,485

Cereal and cereal products 0.449 19,574 25.0% 279

Flour and prepared flour mixes 0.075 6,507 27.0 90

Flour a 2,027 29.0 14

Prepared flour mixes a 4,480 26.1 76

Cereal 0.272 6,516 23.8 116

Rice, pasta, and cornmeal 0.102 6,551 24.4 73

Rice a 3,085 23.2 37

Macaroni, similar products,

and cornmeal a 3,466 25.4 36

Bakery products 1.027 24,431 26.2 494

White bread 0.260 6,249 23.3 78

Other breads, rolls, biscuits, and

muffins 0.239 6,124 24.3 142

Bread other than white a 3,538 27.8 70

Rolls, biscuits, and muffins,

excluding frozen a 2,586 19.5 72

Cakes, cupcakes, and cookies 0.249 6,274 27.7 141

Cakes and cupcakes,

excluding frozen a 2,433 19.5 64

Cookies a 3,841 32.9 77

Other bakery products 0.279 5,784 29.9 133

Crackers a 2,279 39.7 27

Bread and cracker products a 140 25.7 3

Sweetrolls, coffee cake, and

doughnuts, excluding frozen a 1,404 18.1 47

Frozen bakery products,

frozen and refrigerated

doughs, and batters a 1,241 26.8 22

Pies, tarts, and turnovers,

excluding frozen a 720 27.9 34

Beef and veal 0.933 47,442 46.4 312

Ground beef 0.309 6,302 43.0 35

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Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

3.8% n/a n/a 18,311 9,411 4,049 4,851

3.3 16,750 58.0% 12,131 3,770 4,049 4,312

1.4 3,640 56.1 2,845 107 31 2,707

1.4 163 58.4 116 6 2 108

1.4 57 63.3 33 2 1 30

0.7 9 64.3 5 0 1 4

1.7 48 63.2 28 2 0 26

1.8 65 56.0 51 3 1 47

1.1 41 56.2 32 1 0 31

1.2 23 62.2 14 0 0 14

1.0 18 50.0 18 1 0 17

2.0 229 46.4 265 15 1 249

1.3 45 57.7 33 2 0 31

2.3 67 47.2 75 2 0 73

2.0 29 41.4 41 0 0 41

2.8 38 52.8 34 2 0 32

2.3 48 34.0 93 4 0 89

2.6 17 26.6 47 0 0 47

2.0 31 40.3 46 4 0 42

2.3 69 51.9 64 7 1 56

1.2 17 63.0 10 1 0 9

2.1 0 0.0 3 0 0 3

3.4 19 40.4 28 2 1 25

1.8 10 45.5 12 2 0 10

4.7 23 67.6 11 2 0 9

0.7 87 27.9 225 0 7 218

0.6 19 54.3 16 0 0 16

(continued)

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Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Chuck roast 0.083 5,910 53.5 40

Round roast 0.048 5,824 51.5 31

Round steak 0.076 5,989 46.6 41

Sirloin steak 0.072 5,924 47.3 33

Other steak, roast, and other

beef 0.345 17,493 43.0 132

Other roasts, excluding chuck

and round a 2,521 40.1 23

Other steak, excluding round

and sirloin a 10,900 46.4 74

Other beef a 4,072 35.8 35

Pork 0.595 29,378 42.3 446

Bacon 0.112 6,056 38.6 93

Pork chops 0.137 6,249 46.9 18

Ham 0.138 5,298 44.6 179

Ham, excluding canned a 5,013 46.3 173

Canned ham a 285 14.0 6

Other pork, including sausage 0.208 11,775 40.7 156

Pork roasts, picnics, and

other pork a 6,718 44.8 88

Pork sausage a 5,057 35.1 68

Other meats 0.393 12,020 27.6 261

Frankfurters a 2,627 35.4 55

Bologna, liverwurst, and

salami a 2,852 24.5 43

Other lunchmeats, excluding

bologna, liverwurst, and

salami a 5,521 26.3 143

Lamb, organ meats, and

game a 1,020 23.1 20

Poultry 0.439 17,348 36.9 463

Fresh whole chicken 0.148 5,996 37.0 118

Fresh or frozen chicken parts 0.205 6,092 39.3 78

Other poultry 0.086 5,260 34.0 267

Fish and seafood 0.373 12,036 32.1 215

Canned fish and seafood 0.072 6,469 26.4 102

Fresh or frozen fish and seafood 0.301 5,567 38.7 113

Shellfish, excluding canned a 1,646 32.6 34

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CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

0.7 6 15.0 34 0 1 33

0.5 6 19.4 25 0 2 23

0.7 9 22.0 32 0 1 31

0.6 12 36.4 21 0 1 20

0.8 35 26.5 97 0 2 95

0.9 5 21.7 18 0 1 17

0.7 21 28.4 53 0 1 52

0.9 9 25.7 26 0 0 26

1.5 247 55.4 199 0 5 194

1.5 62 66.7 31 0 0 31

0.3 5 27.8 13 0 2 11

3.4 95 53.1 84 0 0 84

3.5 93 53.8 80 0 0 80

2.1 2 33.3 4 0 0 4

1.3 85 54.5 71 0 3 68

1.3 45 51.1 43 0 3 40

1.3 40 58.8 28 0 0 28

2.2 160 61.3 101 0 0 101

2.1 35 63.6 20 0 0 20

1.5 20 46.5 23 0 0 23

2.6 90 62.9 53 0 0 53

2.0 15 75.0 5 0 0 5

2.7 398 86.0 65 0 2 63

2.0 109 92.4 9 0 0 9

1.3 59 75.6 19 0 1 18

5.1 230 86.1 37 0 1 36

1.8 124 57.7 91 3 1 87

1.6 67 65.7 35 3 0 32

2.0 57 50.4 56 0 1 55

2.1 18 52.9 16 0 0 16

(continued)

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Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Fish, excluding canned a 3,921 41.3 79

Eggs 0.187 6,500 63.1 38

Fresh milk and cream 0.61 12,970 34.5 125

Fresh whole milk 0.352 6,545 35.1 56

Other fresh milk and cream 0.257 6,425 34.0 69

Processed dairy products 0.608 19,066 31.6 308

Cheese 0.338 6,380 31.5 123

Ice cream and related products 0.157 6,396 29.0 96

Other dairy products, including

butter 0.113 6,290 34.4 89

Butter a 2,152 50.0 21

Other dairy products a 4,138 26.3 68

Fresh fruits 0.740 43,203 51.3 118

Apples 0.116 8,460 41.5 21

Bananas 0.067 6,493 37.8 1

Oranges, including tangerines 0.084 7,531 53.9 40

Other fresh fruits 0.474 20,719 58.6 56

Fresh vegetables 0.631 31,291 53.4 62

Potatoes 0.100 6,320 46.3 23

Lettuce 0.077 6,396 55.3 1

Tomatoes 0.115 6,204 66.4 18

Other fresh vegetables 0.339 12,371 49.5 20

Processed fruits 0.349 19,567 28.3 354

Fruit juices and frozen fruit 0.273 12,963 33.0 229

Frozen orange juice a 2,415 33.0 21

Other frozen fruits and fruit

juices a 1,154 26.8 12

Fresh, canned, and/or bottled

fruit juices a 9,394 31.5 196

Canned and dried fruits 0.077 6,604 22.2 125

Processed vegetables 0.261 13,020 26.6 200

Frozen vegetables 0.087 6,434 29.5 104

Processed vegetables,

excluding frozen 0.174 6,586 23.9 96

Canned beans other than lima a 926 24.3 10

Canned cut corn a 854 28.9 9

Other processed vegetables a 4,806 22.9 77

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Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

2.0 39 49.4 40 0 1 39

0.6 22 57.9 16 0 0 16

1.0 102 81.6 23 0 0 23

0.9 46 82.1 10 0 0 10

1.1 56 81.2 13 0 0 13

1.6 180 58.4 128 0 3 125

1.9 72 58.5 51 0 1 50

1.5 56 58.3 40 0 2 38

1.4 52 58.4 37 0 0 37

1.0 12 57.1 9 0 0 9

1.6 40 58.8 28 0 0 28

0.3 80 67.8 38 0 0 38

0.3 14 66.7 7 0 0 7

0.0 0 0.0 1 0 0 1

0.5 32 80.0 8 0 0 8

0.3 34 60.7 22 0 0 22

0.2 43 69.4 19 0 0 19

0.4 15 65.2 8 0 0 8

0.0 0 0.0 1 0 0 1

0.3 16 88.9 2 0 0 2

0.2 12 60.0 8 0 0 8

1.8 242 68.4 112 0 1 111

1.8 145 63.3 84 0 1 83

0.9 13 61.9 8 0 0 8

1.0 6 50.0 6 0 0 6

2.1 126 64.3 70 0 1 69

1.9 97 77.6 28 0 0 28

1.5 146 73.0 54 0 3 51

1.6 76 73.1 28 0 0 28

1.5 70 72.9 26 0 3 23

1.1 7 70.0 3 0 0 3

1.1 6 66.7 3 0 0 3

1.6 57 74.0 20 0 3 17

(continued)

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Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Sugar and sweets 0.332 11,935 19.2 187

Sugar and artificial sweeteners 0.085 5,810 21.8 74

Sweets, including candy 0.247 6,125 16.7 113

Candy and chewing gum a 4,675 14.8 91

Other sweets, excluding

candy and gum a 1,450 22.8 22

Fats and oils 0.241 13,191 24.6 137

Margarine a 1,999 25.7 22

Other fats and oils a 7,583 23.3 83

Nondairy cream substitutes a 1,571 22.3 13

Peanut butter a 2,038 29.9 19

Nonalcoholic beverages 0.747 19,262 31.7 267

Carbonated drinks 0.348 6,639 35.3 69

Cola drinks a 4,046 38.5 26

Carbonated drinks other than

cola a 2,593 30.2 43

Coffee 0.263 6,314 37.8 83

Roasted coffee a 3,685 44.3 50

Instant and freeze dried coffee a 2,629 28.8 33

Other noncarbonated drinks 0.136 6,309 21.9 115

Noncarbonated fruit-flavored

drinks a 2,079 21.8 34

Tea a 1,856 22.0 23

Other noncarbonated drinks a 2,374 22.0 58

Other prepared foods 1.046 31,997 26.9 506

Canned and packaged soup 0.096 6,504 25.5 90

Frozen prepared food 0.165 6,185 36.1 146

Frozen prepared meals a 2,213 37.1 69

Frozen prepared foods other

than meals a 3,972 35.5 77

Snacks 0.205 6,321 24.7 124

Potato chips and other snacks a 5,098 25.2 101

Nuts a 1,223 22.7 23

Seasonings, condiments,

sauces, and spices 0.282 6,539 22.6 77

Salt, other seasoning, and

spices a 1,447 15.6 16

Olives, pickles, and relishes a 713 26.0 11

Page 120 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

1.6 104 55.6 83 0 0 83

1.3 38 51.4 36 0 0 36

1.8 66 58.4 47 0 0 47

2.0 54 59.3 37 0 0 37

1.5 12 54.6 10 0 0 10

1.0 97 70.8 40 0 0 40

1.1 18 81.8 4 0 0 4

1.1 55 66.3 28 0 0 28

0.8 11 84.6 2 0 0 2

0.9 13 68.4 6 0 0 6

1.4 169 63.3 98 9 2 87

1.0 46 66.7 23 3 0 20

0.6 17 65.4 9 0 0 9

1.7 29 67.4 14 3 0 11

1.3 50 60.2 33 3 1 29

1.4 34 68.0 16 1 0 15

1.3 16 48.5 17 2 1 14

1.8 73 63.5 42 3 1 38

1.6 20 58.8 14 0 0 14

1.2 15 65.2 8 1 1 6

2.4 38 65.5 20 2 0 18

1.6 273 54.0 233 11 3 219

1.4 47 52.2 43 1 1 41

2.4 79 54.1 67 4 1 62

3.1 39 56.5 30 3 0 27

1.9 40 52.0 37 1 1 35

2.0 62 50.0 62 0 0 62

2.0 50 49.5 51 0 0 51

1.9 12 52.2 11 0 0 11

1.2 35 45.5 42 3 0 39

1.1 8 50.0 8 2 0 6

1.5 6 54.6 5 0 0 5

(continued)

Page 121 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Sauces and gravies a 3,269 26.2 41

Other condiments, excluding

olives, pickles, and relishes a 1,110 19.2 9

Miscellaneous prepared food,

including baby food 0.299 6,448 25.9 69

Canned or packaged salads

and desserts a 638 27.4 12

Baby food a 1,389 22.0 10

Other canned or packaged

prepared foods a 4,421 26.8 47

Food away from home 5.923 60,536 13.9 1,336

Lunch 2.097 21,256 13.6 431

Dinner 2.512 27,850 14.0 665

Other meals and snacks 1.004 11,430 14.0 240

Snacks and nonalcoholic

beverages a 8,413 13.9 209

Breakfast or brunch a 3,017 14.2 31

Unpriced board and catered

affairsb 0.310 0 0.0 0

Alcoholic beverages 0.813 14,868 23.7 377

Beer, ale, and other alcoholic

malt beverages at home 0.415 3,919 30.3 64

Distilled spirits 0.209 3,803 23.1 27

Whiskey at home a 1,553 25.3 9

Distilled spirits at home,

excluding whiskey a 2,250 21.5 18

Wine at home 0.189 3,844 28.6 194

Alcoholic beverages away from

home 0.765 3,302 10.8 92

Beer, ale, and other alcoholic

malt beverages away from

home a 1,333 9.7 30

Wine away from home a 834 10.4 42

Distilled spirits away from

home a 1,135 12.3 20

Housing component total 41.469 182,162 n/a 10,254

Renters’ costs 8.169 70,792 n/a 6,524

Rent, residential 5.810 45,732 n/a 6,180

Lodging while out of town 2.089 22,889 39.0 297

Lodging while at school 0.236 390 47.4 24

Page 122 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

1.3 15 36.6 26 1 0 25

0.8 6 66.7 3 0 0 3

1.1 50 72.5 19 3 1 15

1.9 11 91.7 1 0 0 1

0.7 8 80.0 2 1 0 1

1.1 31 66.0 16 2 1 13

2.2 533 39.9 803 41 1 761

2.0 175 40.6 256 10 0 246

2.4 279 42.0 386 19 0 367

2.1 79 32.9 161 12 1 148

2.5 68 32.5 141 10 1 130

1.0 11 35.5 20 2 0 18

0.0 0 0.0 0 0 0 0

2.5 241 63.9 136 22 0 114

1.6 36 56.3 28 5 0 23

0.7 17 63.0 10 2 0 8

0.6 5 55.6 4 1 0 3

0.8 12 66.7 6 1 0 5

5.1 145 74.7 49 2 0 47

2.8 43 46.7 49 13 0 36

2.3 12 40.0 18 6 0 12

5.0 21 50.0 21 4 0 17

1.8 10 50.0 10 3 0 7

5.6 n/a n/a 7,774 5,773 1,023 978

9.8 n/a n/a 6,228 5,658 0 570

13.5 n/a n/a 6,180 5,641c 0 539

1.3 264 88.9 33 12 0 21

6.2 12 50.0 12 5 0 7

(continued)

Page 123 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Tenants’ insurance 0.034 1,781 10.1 23

Rental equivalence and

household insurance 20.269 d d d

Owners’ equivalent rent 19.881 e e e

Household insurance 0.388 f f f

Maintenance and repair services 0.202 457 19.3 17

Property maintenance and

repair services 0.126 457 19.3 17

Inside home maintenance

and repair services a 381 17.3 8

Repair and/or replacement of

hard surface flooring a 0 0.0 0

Replacement of installed

wall-to-wall carpet a 76 29.0 9

Repair of disposal, built-in

dishwasher, and range hood a 0 0.0 0

Maintenance and repair

commodities 0.076 1,637 15.6 57

Materials, supplies, and

equipment for home repairs 0.034 825 19.5 29

Paint, wallpaper, and supplies a 408 20.1 13

Tools and equipment for

painting a 61 19.7 4

Lumber, paneling, wall and

ceiling tile, awnings, and glass a 179 25.1 4

Blacktop and masonry

materials a 23 17.4 0

Plumbing supplies and

equipment a 67 6.0 1

Electrical supplies and

heating and cooling

equipment a 87 16.1 7

Other maintenance and repair

commodities 0.042 812 11.7 28

Miscellaneous supplies and

equipment a 609 9.2 22

Hard surface floor covering a 136 16.2 4

Landscaping items a 67 25.4 2

Fuel oil and other fuels 0.368 5,297 43.0 23

Fuel oil 0.254 2,383 55.4 9

Page 124 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

1.3 20 87.0 3 0 0 3

d d d d d d d

e e e e e e e

f f f f f f f

3.7 2 11.8 15 1 0 14

3.7 2 11.8 15 1 0 14

2.1 2 25.0 6 0 0 6

0.0 0 0.0 0 0 0 0

11.8 0 0.0 9 1 0 8

0.0 0 0.0 0 0 0 0

3.5 37 64.9 20 2 0 18

3.5 20 69.0 9 1 0 8

3.2 8 61.5 5 0 0 5

6.6 3 75.0 1 0 0 1

2.2 3 75.0 1 1 0 0

0.0 0 0.0 0 0 0 0

1.5 1 100.0 0 0 0 0

8.1 5 71.4 2 0 0 2

3.4 17 60.7 11 1 0 10

3.6 15 68.2 7 1 0 6

2.9 1 25.0 3 0 0 3

3.0 1 50.0 1 0 0 1

0.4 12 52.2 11 6 0 5

0.4 4 44.4 5 2 0 3

(continued)

Page 125 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Other household fuel

commodities 0.113 2,914 32.9 14

Bottled or tank gas a 2,073 35.4 8

Coal a 0 0.0 0

Other fuels a 841 26.8 6

Gas (piped) and electricity 3.401 28,152 51.4 123

Electricity 2.265 15,586 40.6 78

Utility natural gas service 1.136 12,566 64.9 45

Other utilities and public services 3.246 28,653 13.4 260

Telephone services, local

charges 1.115 6,450 12.7 26

Interstate toll calls 0.305 5,265 18.5 34

Intrastate toll calls 0.227 5,674 6.9 23

Water and sewerage

maintenance 0.795 4,112 10.9 42

Community antenna and cable

television 0.582 3,867 25.2 93

Garbage and trash collection 0.221 3,285 7.4 42

Textile house furnishings 0.313 3,898 34.7 289

Bathroom linens a 679 35.2 55

Bedroom linens a 1,638 39.1 130

Kitchen and dining room

linens a 220 23.2 22

Curtains and drapes a 648 36.6 42

Slipcovers and decorative

pillows a 106 23.6 12

Sewing materials for

household items a 607 26.4 28

Furniture and bedding 1.089 7,469 32.9 566

Bedroom furniture 0.361 2,154 31.4 142

Mattress and springs a 941 33.1 65

Bedroom furniture other than

mattress and springs a 1,213 30.2 77

Sofas 0.225 1,330 33.6 103

Living room chairs and tables 0.179 1,341 33.4 105

Living room chairs a 871 36.6 84

Living room tables a 470 27.5 21

Other furniture 0.324 2,644 33.6 216

Page 126 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

0.5 8 57.1 6 4 0 2

0.4 4 50.0 4 2 0 2

0.0 0 0.0 0 0 0 0

0.7 4 66.7 2 2 0 0

0.4 98 79.7 25 14 0 11

0.5 63 80.8 15 14 0 1

0.4 35 77.8 10 0 0 10

0.9 173 66.5 87 54 0 33

0.4 17 65.4 9 0 0 9

0.7 2 5.9 32 32 0 0

0.4 16 69.6 7 0 0 7

1.0 34 81.0 8 6 0 2

2.4 85 91.4 8 2 0 6

1.3 19 45.2 23 14 0 9

7.4 187 64.7 102 0 99 3

8.1 39 70.9 16 0 16g 0

7.9 86 66.2 44 0 42g 2

10 a 0 12 54.6 10 0 9g 1

6.5 24 57.1 18 0 18g 0

11.3 6 50.0 6 0 6g 0

4.6 20 71.4 8 0 8g 0

7.6 238 42.1 328 0 320 8

6.6 60 42.3 82 0 80 2

6.9 32 49.2 33 0 32g 1

6.4 28 36.4 49 0 48g 1

7.7 51 49.5 52 0 49g 3

7.8 42 40.0 63 0 62 1

9.6 35 41.7 49 0 49g 0

4.5 7 33.3 14 0 13g 1

8.2 85 39.4 131 0 129 2

(continued)

Page 127 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Kitchen and dining room

furniture a 1,193 34.5 84

Infants’ furniture a 253 23.3 19

Outdoor furniture a 201 43.8 39

Occasional furniture a 997 33.0 74

Television and sound equipment 0.385 5,327 36.9 711

Television sets 0.128 2,170 43.3 306

Video products other than

televisions 0.065 683 32.9 108

Video cassette recorders,

disc players, cameras, and

accessories a 376 41.0 63

Video cassettes and discs,

blank and prerecorded a 236 18.2 28

Video game hardware,

software, and accessories a 71 39.4 17

Audio components, radios,

recordings, and other audio

equipment 0.192 2,474 32.3 297

Radios, phonographs, and

tape recorders and players a 293 39.9 43

Components and other sound

equipment a 961 32.3 148

Records and tapes,

prerecorded and blank a 1,220 17.8 106

Unpriced accessories for

electronic equipmentb 0.000 0 0.0 0

Household appliances 0.274 3,124 46.4 287

Refrigerators and home freezers 0.084 819 47.6 79

Laundry equipment 0.092 820 47.0 60

Washers a 507 48.3 43

Dryers a 313 44.7 17

Stoves, ovens, portable

dishwashers, and window air

conditioners 0.098 1,485 45.5 148

Stoves and ovens, excluding

microwave ovens a 576 47.2 55

Microwave ovens a 658 45.7 80

Portable dishwashers a 24 25.0 1

Window air conditioners a 227 42.3 12

Page 128 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

7.0 27 32.1 57 0 56g 1

7.5 11 57.9 8 0 7g 1

19.4 24 61.5 15 0 15g 0

7.4 23 31.1 51 0 51g 0

13.4 438 61.6 273 5 264 4

14.1 191 62.4 115 1 113g 1

15.8 76 70.4 32 3 28 1

16.8 44 69.8 19 0 19g 0

11.9 22 78.6 6 3 3g 0

23.9 10 58.8 7 0 6g 1

12.0 171 57.6 126 1 123 2

14.7 18 41.9 25 0 25g 0

15.4 60 40.5 88 0 87g 1

8.7 93 87.7 13 1 11g 1

0.0 0 0.0 0 0 0 0

9.2 263 91.6 24 0 23 1

9.7 72 91.1 7 0 7g 0

7.3 59 98.3 1 0 1 0

8.5 43 100.0 0 0 0g 0

5.4 16 94.1 1 0 1g 0

10.0 132 89.2 16 0 15 1

9.6 49 89.1 6 0 6g 0

12.2 74 92.5 6 0 5g 1

4.2 0 0.0 1 0 1g 0

5.3 9 75.0 3 0 3g 0

(continued)

Page 129 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Information processing

equipment 0.064 649 42.4 119

Personal computers and

peripheral equipment a 375 57.6 103

Computer software and

accessories a 97 21.7 9

Telephone, peripheral

equipment, and accessories a 125 26.4 6

Calculators, adding

machines, and typewriters a 41 4.9 1

Other information processing

equipment a 11 27.3 0

Other household equipment and

furnishings 1.107 9,383 26.8 784

Floor and window coverings,

and outdoor, infants’, laundry,

and cleaning equipment 0.176 1,533 25.2 101

Floor coverings a 544 21.7 38

Window coverings a 519 29.7 13

Infants’ equipment a 111 23.4 10

Laundry and cleaning

equipment a 271 18.8 29

Outdoor equipment a 88 42.1 11

Clocks, lamps, and decorator

items 0.218 1,570 26.1 181

Clocks a 80 21.3 9

Lamps and lighting fixtures a 353 29.8 37

Household decorative items a 1,137 25.2 135

Tableware, serving pieces, and

nonelectric kitchenware 0.198 1,790 24.3 162

Plastic dinnerware a 30 10.0 1

China and other dinnerware a 389 31.6 42

Flatware a 223 29.6 18

Glassware a 228 24.1 17

Silver serving pieces a 0 0.0 0

Serving pieces other than

silver or glass a 57 33.3 4

Nonelectric cookware a 236 24.6 19

Tableware and nonelectric

kitchenware a 627 17.7 61

Page 130 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

18.3 67 56.3 52 0 0 52

27.5 59 57.3 44 0 0 44

9.3 5 55.6 4 0 0 4

4.8 2 33.3 4 0 0 4

2.4 1 100.0 0 0 0 0

0.0 0 0.0 0 0 0 0

8.4 443 56.5 341 5 317 19

6.6 56 55.5 45 1 43 1

7.0 22 57.9 16 1 14g 1

2.5 10 76.9 3 0 3g 0

9.0 7 70.0 3 0 3g 0

10.7 14 48.3 15 0 15g 0

12.5 3 27.3 8 0 8g 0

11.5 97 53.6 84 0 80 4

11.3 4 44.4 5 0 5g 0

10.5 23 62.2 14 0 13g 1

11.9 70 51.9 65 0 62g 3

9.1 74 45.7 88 1 83 4

3.3 1 100.0 0 0 0g 0

10.8 19 45.2 23 1 20g 2

8.1 10 55.6 8 0 8g 0

7.5 7 41.2 10 0 9g 1

0.0 0 0.0 0 0 0 0

7.0 1 25.0 3 0 3g 0

8.1 9 47.4 10 0 10g 0

9.7 27 44.3 34 0 33g 1

(continued)

Page 131 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Lawn and garden equipment,

tools, and hardware 0.173 1,665 24.1 109

Lawn and garden equipment a 819 33.7 80

Power tools a 339 16.2 11

Other hardware a 263 11.8 9

Nonpowered hand tools a 244 16.0 9

Small kitchen appliances,

sewing machines, and portable

heating and cooling equipment 0.113 1,615 32.8 144

Floor cleaning equipment and

sewing machines a 597 38.5 63

Portable heating and cooling

equipment, and small electric

kitchen appliances a 1,018 29.5 81

Indoor plants and fresh cut

flowers 0.150 1,210 29.1 87

Unpriced household equipment

parts and small furnishingsb 0.079 0 0.0 0

Housekeeping supplies 1.090 10,013 23.8 446

Laundry and cleaning products 0.380 4,170 25.1 144

Soaps and detergents a 2,512 26.6 97

Other laundry and cleaning

products a 1,658 23.0 47

Household paper products,

including stationery 0.364 2,974 22.1 195

Cleansing and toilet tissue,

paper towels, and napkins a 1,531 27.3 53

Stationery, stationery

supplies, and gift wrap a 1,443 16.5 142

Other household products, lawn,

and garden supplies 0.346 2,869 23.6 107

Miscellaneous household

products a 2,111 23.4 61

Lawn and garden supplies a 758 24.0 46

Housekeeping services 1.492 7,311 6.6 48

Postage 0.254 1,578 0.0 0

Appliance and furniture repair 0.182 817 8.6 3

Repair of television, radio,

and sound equipment a 415 4.6 0

Repair of household

appliances a 229 18.8 1

Page 132 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

6.6 88 80.7 21 1 20 0

9.8 69 86.3 11 1 10g 0

3.2 7 63.6 4 0 4g 0

3.4 7 77.8 2 0 2g 0

3.7 5 55.6 4 0 4g 0

8.9 93 64.6 51 1 45 5

10.6 48 76.2 15 1 14g 0

8.0 45 55.6 36 0 31g 5

7.2 35 40.2 52 1 46g 5

0.0 0 0.0 0 0 0 0

4.5 206 46.2 240 19 0 221

3.5 58 40.3 86 5 0 81

3.9 35 36.1 62 3 0 59

2.8 23 48.9 24 2 0 22

6.6 95 48.7 100 12 0 88

3.5 16 30.2 37 7 0 30

9.8 79 55.6 63 5 0 58

3.7 53 49.5 54 2 0 52

2.9 31 50.8 30 2 0 28

6.1 22 47.8 24 0 0 24

0.7 20 41.7 28 9 0 19

0.0 0 0.0 0 0 0 0

0.4 1 33.3 2 1 0 1

0.0 0 0.0 0 0 0 0

0.4 0 0.0 1 1 0 0

(continued)

Page 133 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Reupholstery of furniture a 173 4.6 2

Gardening and other household

services 0.378 3,765 8.6 32

Gardening and lawn care

services a 1,535 11.1 20

Water softening service a 84 8.3 1

Moving, storage, and freight

expense a 1,033 10.1 10

Household laundry and

drycleaning, excluding coin

operated a 946 4.0 1

Coin-operated household

laundry and drycleaning a 167 1.2 0

Babysitting 0.271 h h h

Domestic services 0.237 1,010 7.5 10

Care of invalids, elderly, and

convalescents in the home 0.054 141 7.8 3

Unpriced rent and/or repair of

household equipment, and

sound equipmentb 0.116 0 0.0 0

Apparel and upkeep component

total 5.291 76,736 n/a 9,797

Men’s apparel 1.061 17,016 40.6 1,391

Men’s suits, coats, sportcoats,

and jackets 0.312 6,221 40.6 466

Men’s suits a 3,841 38.4 181

Men’s sportcoats and tailored

jackets a 619 47.0 40

Men’s coats and jackets a 1,761 43.3 245

Men’s furnishings 0.257 3,335 37.2 336

Men’s underwear and hosiery a 968 29.1 43

Men’s nightwear a 287 24.0 17

Men’s accessories a 1,067 29.6 88

Men’s sweaters a 474 58.0 93

Men’s active sportswear a 539 55.5 95

Men’s shirts 0.266 4,100 45.1 407

Men’s pants and shorts 0.212 3,360 38.5 182

Unpriced men’s uniforms and

other clothingb 0.014 0 0.0 0

Boys’ apparel 0.230 3,457 43.5 436

Page 134 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

1.2 1 50.0 1 0 0 1

0.9 17 53.1 15 3 0 12

1.3 10 50.0 10 2 0 8

1.2 0 0.0 1 1 0 0

1.0 7 70.0 3 0 0 3

0.1 0 0.0 1 0 0 1

0.0 0 0.0 0 0 0 0

h h h h h h h

1.0 1 10.0 9 4 0 5

2.1 1 33.3 2 1 0 1

0.0 0 0.0 0 0 0 0

12.8 6,598 67.3 3,199 1,223 1,796 180

8.2 989 71.1 402 192 183 27

7.5 285 61.2 181 101 69 11

4.7 93 51.4 88 71 14g 3

6.5 24 60.0 16 7 7g 2

13.9 168 68.6 77 23 48g 6

10.1 254 75.6 82 18 57 7

4.4 39 90.7 4 0 3g 1

5.9 16 94.1 1 0 1g 0

8.3 71 80.7 17 0 15g 2

19.6 51 54.8 42 18 22g 2

17.6 77 81.1 18 0 16g 2

9.9 306 75.2 101 53 42g 6

5.4 144 79.1 38 20 15g 3

0.0 0 0.0 0 0 0 0

12.6 305 70.0 131 1 125 5

(continued)

Page 135 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Boys’ coats and jackets a 264 66.3 58

Boys’ sweaters a 96 62.5 22

Boys’ shirts a 1,008 48.5 159

Boys’ underwear, nightwear,

and hosiery a 332 25.0 16

Boys’ accessories a 336 30.7 27

Boys’ suits, sportcoats, and

pants a 1,200 37.7 89

Boys’ active sportswear a 221 64.7 65

Unpriced boys’ uniforms and

other clothingb a 0 0.0 0

Women’s apparel 1.765 23,328 52.1 5,040

Women’s coats and jackets 0.181 1,960 55.6 503

Women’s dresses 0.246 2,299 65.5 853

Women’s separates and

sportswear 0.821 12,452 55.3 2,653

Women’s tops a 5,472 61.7 1,514

Women’s skirts a 704 64.6 208

Women’s pants and shorts a 5,272 46.6 653

Women’s active sportswear a 1,004 60.2 278

Women’s underwear, nightwear,

and accessories 0.323 5,449 35.2 653

Women’s nightwear a 1,155 56.0 288

Women’s underwear a 1,510 33.3 91

Women’s hosiery a 1,631 19.2 79

Women’s accessories a 1,153 39.4 195

Women’s suits 0.168 1,168 64.6 378

Unpriced women’s uniforms and

other clothingb 0.026 0 0.0 0

Girls’ apparel 0.307 4,414 49.2 918

Girls’ coats and jackets a 160 60.6 55

Girls’ dresses and suits a 547 75.1 238

Girls’ tops a 804 60.5 212

Girls’ skirts and pants a 1,334 45.4 185

Girls’ active sportswear a 283 63.3 97

Girls’ underwear and

nightwear a 599 33.4 55

Girls’ hosiery and accessories a 687 27.8 76

Page 136 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

22.0 44 75.9 14 0 14g 0

22.9 11 50.0 11 0 9g 2

15.8 104 65.4 55 0 53g 2

4.8 12 75.0 4 1 3g 0

8.0 21 77.8 6 0 6g 0

7.4 67 75.3 22 0 21g 1

29.4 46 70.8 19 0 19g 0

0.0 0 0.0 0 0 0 0

21.6 3,199 63.5 1,841 844 897 100

25.7 275 54.7 228 95 117g 16

37.1 486 57.0 367 176 175g 16

21.3 1,689 63.7 964 484 425 55

27.7 922 60.9 592 299 256g 37

29.6 103 49.5 105 62 39g 4

12.4 442 67.7 211 120 79g 12

27.7 222 79.9 56 3 51g 2

12.0 535 81.9 118 2 110 6

24.9 237 82.3 51 0 50g 1

6.0 71 78.0 20 1 19g 0

4.8 63 79.8 16 1 13g 2

16.9 164 84.1 31 0 28g 3

32.4 214 56.6 164 87 70g 7

0.0 0 0.0 0 0 0 0

20.8 584 63.6 334 129 183 22

34.4 34 61.8 21 4 15g 2

43.5 130 54.6 108 51 55g 2

26.4 148 69.8 64 30 32g 2

13.9 116 62.7 69 19 44g 6

34.3 58 59.8 39 22 11g 6

9.2 40 72.7 15 1 13g 1

11.1 58 76.3 18 2 13g 3

(continued)

Page 137 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Unpriced girls’ uniforms and

other clothingb a 0 0.0 0

Infants’ and toddlers’ apparel 0.182 1,819 28.5 167

Infants’ and toddlers’

outerwear a 37 59.5 11

Infants’ and toddlers’ play

and dresswear a 358 50.0 82

Infants’ and toddlers’

underwear a 1,268 20.4 52

Infants’ and toddlers’

sleepwear a 156 38.5 22

Unpriced infants’ accessories

and other clothingb a 0 0.0 0

Sewing materials, notions, and

luggage 0.083 1,464 32.3 121

Fabric for making clothes a 656 26.1 43

Sewing notions and patterns a 185 22.7 10

Luggage a 623 41.7 68

Jewelry 0.401 6,428 35.9 495

Watches 0.078 1,223 30.3 106

Jewelry 0.323 5,205 37.2 389

Footwear 0.719 11,159 39.7 1,193

Men’s footwear 0.224 2,972 35.6 235

Boys’ and girls’ footwear 0.154 1,537 38.2 203

Boys’ footwear a 760 44.1 115

Girls’ footwear a 777 32.4 88

Women’s footwear 0.341 6,650 41.8 755

Apparel services 0.543 7,651 7.1 36

Apparel laundry and dry

cleaning, excluding coin

operated 0.288 4,012 9.6 11

Other apparel services 0.255 3,639 4.4 25

Shoe repair and other shoe

services a 379 7.7 3

Coin-operated apparel

laundry and dry cleaning a 2,467 2.3 12

Alterations and repairs a 444 4.7 1

Clothing rental a 224 19.2 9

Watch and jewelry repair a 125 8.0 0

Page 138 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

0.0 0 0.0 0 0 0 0

9.2 126 75.5 41 0 39 2

29.7 8 72.7 3 0 3g 0

22.9 65 79.3 17 0 17g 0

4.1 35 67.3 17 0 15g 2

14.1 18 81.8 4 0 4g 0

0.0 0 0.0 0 0 0 0

8.3 79 65.3 42 0 41 1

6.6 31 72.1 12 0 11g 1

5.4 7 70.0 3 0 3g 0

10.9 41 60.3 27 0 27g 0

7.7 338 68.3 157 12 139 6

8.7 82 77.4 24 0 23g 1

7.5 256 65.8 133 12 116g 5

10.7 962 80.6 231 30 189 12

7.9 193 82.1 42 10 27g 5

13.2 169 83.3 34 0 31 3

15.1 96 83.5 19 0 17g 2

11.3 73 83.0 15 0 14g 1

11.4 600 79.5 155 20 131g 4

0.5 16 44.4 20 15 0 5

0.3 3 27.3 8 7 0 1

0.7 13 52.0 12 8 0 4

0.8 1 33.3 2 2 0 0

0.5 10 83.3 2 2 0 0

0.2 0 0.0 1 1 0 0

4.0 2 22.2 7 3 0 4

0.0 0 0.0 0 0 0 0

(continued)

Page 139 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Transportation component total 16.620 94,366 n/a 5,660

New vehicles 4.829 15,176 53.9 2,420

New cars 3.842 11,617 56.4 1,917

New trucks 0.894 2,192 52.2 341

New motorcycles 0.093 1,367 34.6 162

Used vehicles 1.195 5,067 100.0 1,097

Unpriced used carsb a 0 0.0 0

Motor fuel 2.925 29,524 75.0 172

Regular unleaded gasoline a 9,509 79.3 50

Mid-grade unleaded gasoline a 8,370 77.5 47

Premium unleaded gasoline a 9,186 76.3 64

Diesel a 2,285 45.4 9

Other motor fuel a 174 63.8 2

Automobile maintenance and

repair 1.546 8,401 25.6 1,303

Automotive body work 0.167 2,073 28.1 334

Automobile drive train and front

end repair 0.453 1,990 27.5 306

Automotive drive-train repair a 803 28.1 129

Automotive brake work a 545 25.3 81

Repair to steering, front end,

cooling system, and air

conditioning a 642 28.7 96

Automotive maintenance and

servicing 0.490 2,376 17.6 352

Power plant repair 0.412 1,962 30.5 311

Unpriced automotive repair

service policyb 0.023 0 0.0 0

Motor oil, coolant, and other

fluids 0.058 3,745 11.7 36

Motor oil a 2,676 11.2 18

Coolant brake fluid,

transmission fluid, and

additives a 1,069 12.9 18

Automobile parts and equipment 0.516 7,964 20.9 255

Tires 0.256 4,037 26.8 102

Vehicle parts and equipment

other than tires 0.260 3,927 14.9 153

Automobile insurance 2.647 5,111 25.0 147

Page 140 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

6.2 2,699 47.6 2,961 1,837 823 301

16.0 805 33.3 1,615 838 670 107

16.5 584 30.5 1,333 667 580g 86

15.6 80 23.5 261 171 75g 15

11.9 141 87.0 21 0 15g 6

21.7 0 0.0 1,097 990 0 107

0.0 0 0.0 0 0 0 0

0.6 159 92.4 13 2 0 11

0.5 47 94 3 0 0 3

0.6 45 95.7 2 0 0 2

0.7 59 92.2 5 2 0 3

0.4 7 77.8 2 0 0 2

1.2 1 50.0 1 0 0 1

15.5 1,169 89.7 134 3 117 14

16.1 287 85.9 47 1 38g 8

15.4 273 89.2 33 1 31 1

16.1 114 88.4 15 0 15g 0

14.9 73 90.1 8 1 6g 1

15.0 86 89.6 10 0 10g 0

14.8 339 96.3 13 1 10g 2

15.9 270 86.8 41 0 38g 3

0.0 0 0.0 0 0 0 0

1.0 27 75.0 9 0 0 9

0.7 12 66.7 6 0 0 6

1.7 15 83.3 3 0 0 3

3.2 211 82.8 44 2 36 6

2.5 85 83.3 17 0 17g 0

3.9 126 82.4 27 2 19g 6

2.9 133 90.5 14 0 0 14

(continued)

Page 141 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Vehicle finance charges 0.571 2,373 36.1 68

Unpriced other vehicle

finance chargesb a 0 0.0 0

Vehicle rental, registration, and

inspection 0.768 5,757 25.1 89

State and local automobile

registration, license, and

inspection 0.368 1,874 4.5 15

State automobile registration a 1,354 5.5 10

Local automobile registration a 249 2.4 5

Driver’s license a 227 1.8 0

Vehicle inspection a 44 0.0 0

Other automobile-related fees 0.372 3,883 35.1 74

Automobile rental a 2,141 54.3 62

Truck rental a 521 29.8 6

Parking fees a 697 4.5 4

Vehicle tolls a 464 2.6 1

Automobile towing charges a 60 0.0 1

Other vehicle rental a 0 0.0 0

Unpriced docking and landing

feesb 0.027 0 0.0 0

Public transportation 1.566 11,248 45.5 73

Airline fare 1.037 6,366 69.5 0

Other intercity transportation 0.139 2,318 26.2 59

Intercity bus fare a 407 35.9 4

Intercity train fare a 1,154 12.0 1

Ship fares a 757 42.7 54

Intracity transportation 0.378 2,564 3.6 14

Intracity mass transit a 2,040 2.2 13

Taxi fare a 524 9.2 1

Car and van pools a 0 0.0 0

Unpriced school busb 0.012 0 0.0 0

Medical care component total 7.426 50,237 n/a 1,116

Prescription drugs and medical

supplies 0.897 4,471 26.0 108

Nonprescription drugs and

medical 0.383 4,488 19.3 173

Page 142 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

2.9 66 97.1 2 0 0 2

0.0 0 0.0 0 0 0 0

1.6 77 86.5 12 2 0 10

0.8 12 80.0 3 2 0 1

0.7 8 80.0 2 1 0 1

2.0 4 80.0 1 1 0 0

0.0 0 0.0 0 0 0 0

0.0 0 0.0 0 0 0 0

1.9 65 87.8 9 0 0 9

2.9 57 91.9 5 0 0 5

1.2 4 66.7 2 0 0 2

0.6 2 50.0 2 0 0 2

0.2 1 100.0 0 0 0 0

1.7 1 100.0 0 0 0 0

0.0 0 0.0 0 0 0 0

0.0 0 0.0 0 0 0 0

0.7 52 71.2 21 0 0 21

0.0 0 0.0 0 0 0 0

2.6 40 67.8 19 0 0 19

1.0 2 50.0 2 0 0 2

0.1 0 0.0 1 0 0 1

7.1 38 70.4 16 0 0 16

0.6 12 85.7 2 0 0 2

0.6 12 92.3 1 0 0 1

0.2 0 0 1 0 0 1

0.0 0 0.0 0 0 0 0

0.0 0 0.0 0 0 0 0

2.2 355 31.8 761 336 3 422

2.4 49 45.4 59 11 0 48

3.9 41 23.7 132 43 0 89

(continued)

Page 143 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Internal and respiratory

over-the-counter drugs 0.245 2,392 19.9 73

Nonprescription medical

equipment and supplies 0.138 2,096 18.5 100

Topicals and dressings a 1,282 21.8 62

Medical equipment for

general use a 181 17.7 16

Supportive and convalescent

medical equipment a 195 14.9 11

Hearing aids a 438 10.7 11

Unpriced drugsb a 0 0.0 0

Professional services 3.518 18,430 9.4 210

Physicians services 1.904 8,664 8.7 106

Dental services 1.107 5,973 9.6 18

Eyeglasses and eye care 0.335 2,081 13.7 60

Services by other medical

professionals 0.172 1,712 7.2 26

Hospital and related services 2.310 22,848 18.9 625

Hospital services 2.159 19,913 19.5 581

Nursing home services 0.145 2,935 14.9 44

Unpriced itemsb 0.006 0 0.0 0

Health insurancei 0.318 0 n/a n/a

Entertainment component total 4.339 32,985 n/a 1,327

Reading materials 0.730 8,891 5.6 195

Newspapers 0.376 4,964 1.8 11

Magazines, periodicals, and

books 0.354 3,927 10.4 184

Magazines a 1,840 7.6 23

Books purchased through

book clubs a 362 14.4 34

Books not purchased through

book clubs a 1,725 12.5 127

Unpriced newslettersb 0.000 0 0.0 0

Sporting goods and equipment 0.391 4,303 26.3 384

Sport vehicles, including

bicycles 0.181 1,658 30.6 170

Outboard motors and

powered sports vehicles a 1,173 31.6 123

Unpowered boats and trailers a 136 19.1 11

Page 144 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

3.1 18 24.7 55 25 0 30

4.8 23 23.0 77 18 0 59

4.8 19 30.7 43 13 0 30

8.8 0 0.0 16 1 0 15

5.6 4 36.4 7 0 0 7

2.5 0 0.0 11 4 0 7

0.0 0 0.0 0 0 0 0

1.1 68 32.4 142 49 0 93

1.2 22 20.8 84 28 0 56

0.3 7 38.9 11 7 0 4

2.9 30 50.0 30 8 0 22

1.5 9 34.6 17 6 0 11

2.7 197 31.5 428 233 3 192

2.9 175 30.1 406 218 3 185

1.5 22 50.0 22 15 0 7

0.0 0 0.0 0 0 0 0

n/a n/a n/a n/a n/a n/a n/a

4.0 763 57.5 564 95 321 148

2.2 126 64.6 69 9 55 5

0.2 6 54.6 5 2 2g 1

4.7 120 65.2 64 7 53 4

1.3 13 56.5 10 3 7g 0

9.4 17 50.0 17 0 16g 1

7.4 90 70.9 37 4 30g 3

0.0 0 0.0 0 0 0 0

8.9 247 64.3 137 7 114 16

10.3 146 85.9 24 3 15 6

10.5 108 87.8 15 3 8g 4

8.1 10 90.9 1 0 1g 0

(continued)

Page 145 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Bicycles a 349 31.8 36

Sports equipment 0.210 2,645 23.6 214

Indoor, warm weather, and

winter sports equipment a 2,057 23.0 170

Hunting, fishing, and camping

equipment a 588 25.5 44

Toys, hobbies, and other

entertainment commodities 0.803 6,793 22.1 436

Toys, hobbies, and music

equipment 0.360 2,997 21.6 269

Toys, games, and hobbies a 2,477 20.4 239

Playground equipment a 8 75.0 3

Music instruments and

accessories a 512 26.6 27

Photographic supplies and

equipment 0.111 1,162 20.0 62

Film a 636 20.4 27

Photographic and darkroom

supplies a 24 8.3 0

Photographic equipment a 502 19.9 35

Pets and pet products 0.323 2,634 23.7 105

Pet food a 1,726 26.7 56

Purchase of pets, pet

supplies, and accessories a 908 18.1 49

Unpriced souvenirs, fireworks,

and optic goodsb 0.010 0 0.0 0

Entertainment services 2.415 12,998 14.4 312

Club memberships dues and

fees 0.346 2,363 12.1 35

Fees for participant sports 0.400 2,211 17.2 38

Admissions 0.726 4,014 17.9 149

Admission to movies,

theaters, and concerts a 3,323 14.1 98

Admission to sporting events a 691 36.5 51

Fees for lessons or instructions 0.256 888 11.5 38

Photographers, film procession,

and pet services 0.665 3,522 10.9 52

Photographer fees a 197 18.8 8

Film processing a 710 10.6 9

Pet services a 291 8.6 0

Page 146 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

10.3 28 77.8 8 0 6g 2

8.1 101 47.2 113 4 99 10

8.3 77 45.3 93 3 83g 7

7.5 24 54.6 20 1 16g 3

6.4 265 60.8 171 8 152 11

9.0 160 59.5 109 4 99 6

9.7 145 60.7 94 3 86g 5

37.5 0 0.0 3 0 3g 0

5.3 15 55.6 12 1 10g 1

5.3 46 74.2 16 1 13 2

4.3 20 74.1 7 1 5g 1

0.0 0 0.0 0 0 0g 0

7.0 26 74.3 9 0 8g 1

4.0 59 56.2 46 3 40 3

3.2 29 51.8 27 2 22g 3

5.4 30 61.2 19 1 18g 0

0.0 0 0.0 0 0 0 0

2.4 125 40.1 187 71 0 116

1.5 10 28.6 25 6 0 19

1.7 19 50.0 19 4 0 15

3.7 79 53.0 70 28 0 42

3.0 68 69.4 30 6 0 24

7.4 11 21.6 40 22 0 18

4.3 3 7.9 35 22 0 13

1.5 14 26.9 38 11 0 27

4.1 2 25.0 6 0 0 6

1.3 1 11.1 8 2 0 6

0.0 0 0.0 0 0 0 0

(continued)

Page 147 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Veterinarian services a 1,106 11.8 15

Other entertainment services a 1,218 9.7 20

Unpriced rental of recreational

vehiclesb 0.023 0 0.0 0

Other goods and services

component total 7.390 22,440 n/a 422

Tobacco products 1.688 4,120 27.3 15

Cigarettes a 3,710 28.8 10

Tobacco products other than

cigarettes a 356 14.3 3

Smoking accessories a 54 11.1 2

Unpriced smoking productsb a 0 0.0 0

Toilet goods and personal care

appliances 0.589 3,653 19.9 129

Cosmetics, bath, and nail

preparations and implements 0.263 1,214 16.8 50

Hair, dental, shaving, and

miscellaneous personal care

products 0.325 2,439 21.4 79

Products for the hair a 1,022 21.8 29

Nonelectric articles for the hair a 72 12.5 5

Women’s hair pieces and wigs a 0 0.0 0

Dental products and

nonelectric dental articles a 528 23.5 17

Shaving products and

nonelectric shaving articles a 158 24.1 6

Deodorant and suntan

preparations and sanitary and

footcare products a 580 19.1 15

Electric personal care

appliances a 79 22.8 7

Personal care services 0.564 5,576 4.1 16

Beauty parlor services for

females 0.447 3,679 4.2 15

Haircuts and other barber shop

services for men 0.116 1,897 4.0 1

Unpriced repair of personal care

appliancesb 0.000 0 0.0 0

School books and supplies 0.273 1,176 25.7 93

School books and supplies for

college 0.194 637 37.1 69

Page 148 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

1.4 2 13.3 13 4 0 9

1.6 9 45.0 11 5 0 6

0.0 0 0.0 0 0 0 0

1.9 215 50.9 207 40 52 115

0.4 5 33.3 10 2 0 8

0.3 2 20.0 8 2 0 6

0.8 1 33.3 2 0 0 2

3.7 2 100.0 0 0 0 0

0.0 0 0.0 0 0 0 0

3.5 63 48.8 66 5 0 61

4.1 26 52.0 24 2 0 22

3.2 37 46.8 42 3 0 39

2.8 11 37.9 18 0 0 18

6.9 2 40.0 3 0 0 3

0.0 0 0.0 0 0 0 0

3.2 9 52.9 8 2 0 6

3.8 1 16.7 5 1 0 4

2.6 9 60.0 6 0 0 6

8.9 5 71.4 2 0 0 2

0.3 8 50.0 8 0 0 8

0.4 7 46.7 8 0 0 8

0.1 1 100 0 0 0 0

0.0 0 0.0 0 0 0 0

7.9 35 37.6 58 2 52 4

10.8 19 27.5 50 2 45g 3

(continued)

Page 149 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Categories (name of component,

expenditure class, item stratum, and

ELI)

Relative

importance

for December

Number of price

quotations

Percent of

quotations

with price changes

Number of

substitutions

Reference books and

elementary and high school

books 0.064 539 12.2 24

Elementary and high school

books and supplies a 124 32.3 10

Encyclopedias and other sets

of reference books a 415 6.3 14

Unpriced miscellaneous school

purchasesb 0.014 0 0.0 0

Daycare, tuition, and other

school fees 2.863 4,685 23.7 104

College tuition and fees 1.685 1,334 48.8 69

Elementary and high school

tuition and fees 0.519 356 48.0 7

Child daycare and nursery

school 0.388 1,665 9.1 10

Other tuition and fees 0.155 1,330 10.3 18

Unpriced miscellaneous school

items, rentals, and other

servicesb 0.116 0 0.0 0

Legal, financial, and funeral

services 1.415 3,230 12.4 65

Legal fees 0.496 943 4.9 7

Personal financial services 0.407 1,047 12.2 23

Safe deposit box rental a 113 6.2 0

Checking accounts and

special check services a 390 12.3 15

Tax return preparation and

other accounting fees a 544 13.4 8

Cemetery lots and funeral

expenses 0.403 1,240 18.3 35

Funeral expenses a 905 20.8 29

Cemetery lots and crypts a 335 11.6 6

Unpriced miscellaneous

personal servicesb 0.109 0 0.0 0

Page 150 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Substitutions not adjusted

(comparable) Adjusted substitutions by method Percent of price

quotations that were

substitutions

Number not

adjusted

Percent of

substitutions

Number of

adjustments Direct

Class mean

and/or overlap Linking

4.5 16 66.7 8 0 7 1

8.1 2 20.0 8 0 7g 1

3.4 14 100.0 0 0 0g 0

0.0 0 0.0 0 0 0 0

2.2 70 67.3 34 16 0 18

5.2 57 82.6 12 6 0 6

2.0 5 71.4 2 1 0 1

0.6 6 60.0 4 2 0 2

1.4 2 11.1 16 7 0 9

0.0 0 0.0 0 0 0 0

2 34 52.3 31 15 0 16

0.7 2 28.6 5 1 0 4

2.2 11 47.8 12 6 0 6

0 0 0.0 0 0 0 0

3.9 9 60.0 6 2 0 4

1.5 2 25.0 6 4 0 2

2.8 21 60.0 14 8 0 6

3.2 18 62.1 11 5 0 6

1.8 3 50.0 3 3 0 0

0.0 0 0.0 0 0 0 0

Page 151 GAO/GGD-99-84 Consumer Price Index
Appendix VIII 

CPI Price Quotations, Substitutions, and

Methods of Adjustment for 1997

Legend: n/a = Not applicable

aELIs do not have relative importance assigned to them.

bThe weight for this unpriced ELI is moved by changes in its expenditure class.

cThis represents the lower bound of the number of direct adjustments. The upper bound of direct

adjustments of 6,042 represents the number of adjustments made to residential rent units. A unit

could have as many as three types of direct adjustments per collection period. The lower bound

of 5,641 excludes multiple adjustments made to one unit in a collection period.

dNone of these are directly priced and therefore do not experience substitution.

eThe residential rent units are also used for owners’ equivalent rent.

f

The price quotations collected under tenants’ insurance are also used for household insurance.

gThe class-mean method of adjustment can be used for this ELI.

hThe price quotations collected under child daycare and nursery school are used to determine

babysitting.

i

This expenditure class is moved by a combination of medical care price quotations and

insurance companies’ retained earnings, which BLS collects separately.

Source: BLS.

Page 152 GAO/GGD-99-84 Consumer Price Index
Appendix IX 

Comments From the Bureau of Labor

Statistics

Note: GAO comments

supplementing those in the

report text appear at the

end of this appendix.

Page 153 GAO/GGD-99-84 Consumer Price Index
Appendix IX 

Comments From the Bureau of Labor

Statistics

See comment 1.

Page 154 GAO/GGD-99-84 Consumer Price Index
Appendix IX 

Comments From the Bureau of Labor

Statistics

See comment 2.

Page 155 GAO/GGD-99-84 Consumer Price Index
Appendix IX 

Comments From the Bureau of Labor

Statistics

See comment 2.

Page 156 GAO/GGD-99-84 Consumer Price Index
Appendix IX 

Comments From the Bureau of Labor

Statistics

The following are GAO’s comments on the Bureau of Labor Statistics’ letter

dated April 7, 1999.

GAO Comments 1. The Commissioner listed several measures BLS had taken to improve the

substitution and quality adjustment processes in the CPI, and stated that

these measures worked to improve the accuracy of substitution handling.

However, because no data has been collected in periodic evaluations,

neither BLS nor we can assess what effects these measures have had on the

accuracy of commodity analysts’ substitution handling.

2. The Commissioner reported that the expert system software BLS

investigated in 1993 was limited because it only allowed for ex post

evaluations of commodity analysts’ decisions. Our recommendation,

however, allows for the ex post evaluation of decisions and is therefore

not affected by this limitation.

Page 157 GAO/GGD-99-84 Consumer Price Index
Appendix X 

Major Contributors to This Report

General Government

Division, Washington,

D.C.

Martin de Alteriis, Evaluator-in-Charge

Kathleen Scholl, Supervisory Economist

Tony Assia, Senior Evaluator

Amber Roos, Student Intern

Office of the Chief

Economist

Loren Yager, Acting Chief Economist

Richard Krashevski, Supervisory Economist

Dallas Office James Turkett, Senior Evaluator

Page 158 GAO/GGD-99-84 Consumer Price Index
Appendix X 

Major Contributors to This Report

Page 159 GAO/GGD-99-84 Consumer Price Index
Related GAO Products

Bureau of Labor Statistics: Making the CPI More Reflective of Current

Consumer Spending (GAO/T-GGD-98-115, Apr. 29, 1998).

Consumer Price Index: More Frequent Updating of Market Basket

Expenditure Weights Is Needed (GAO/GGD/OCE-98-2, Oct. 9, 1997).

Consumer Price Index: Cost-of-Living Concepts and the Housing and

Medical Care Components (GAO/GGD-96-166, Aug. 26, 1996).

Economic Statistics: Status Report on the Initiative to Improve Economic

Statistics (GAO/GGD-95-98, July 7, 1995).

Economic Statistics: Measurement Problems Can Affect the Budget and

Economic Policymaking (GAO/GGD-95-99, May 2, 1995).

Prescription Drug Prices: Official Index Overstates Producer Price

Inflation (GAO/HEHS-95-90, Apr. 28, 1995).

Developing a Consumer Price Index for the Elderly (GAO/T-GGD-87-22,

June 29, 1987).

Stabilizing Social Security—Which Wage Measure Would Best Align

Benefit Increases With Revenue Increases? (GAO/IMTEC-85-13, Aug. 27, 1985).

Funds Needed to Develop CPI Quality Control System (GAO/GGD-83-32, Apr. 1,

1983).

A CPI for Retirees Is Not Needed Now but Could Be in the Future

(GAO/GGD-82-41, June 1, 1982).

A Consumer Price Index for Retirees and Alternatives for Controlling

Indexing (Testimony, Apr. 20, 1982).

Measurement of Homeownership Costs in the Consumer Price Index

Should Be Changed (GAO/PAD-81-12, Apr. 16, 1981).

Alternatives for Modifying the Indexation of Federal Programs

(Testimony, Mar. 10, 1981).

(410197) Page 160 GAO/GGD-99-84 Consumer Price Index
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