Overview of source data and estimating methods

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-1

CHAPTER 5:

PERSONAL CONSUMPTION EXPENDITURES

(Updated: November 2019)

Definitions and Concepts

Recording in the NIPAs

Overview of Source Data and Estimating Methods

Benchmark-year estimates

Nonbenchmark-year estimates

Current quarterly and monthly estimates

Quantity and price estimates

Table 5.A—Summary of Methodology for PCE for Goods

Table 5.B—Summary of Methodology for PCE for Services

Technical Note: Special Estimates

New motor vehicles

Net purchases of used motor vehicles

Gasoline and other motor fuel

Rental of tenant- and owner-occupied nonfarm housing

Financial service charges and fees

Securities commissions

Financial services furnished without payment

Life insurance

Property and casualty insurance

Nonprofit institutions serving households

Personal consumption expenditures (PCE) is the primary measure of consumer

spending on goods and services in the U.S. economy.

It accounts for about two-thirds of

domestic final spending, and thus it is the primary engine that drives future economic

growth. PCE shows how much of the income earned by households is being spent on

current consumption as opposed to how much is being saved for future consumption.

PCE also provides a comprehensive measure of types of goods and services that

are purchased by households. Thus, for example, it shows the portion of spending that is

accounted for by discretionary items, such as motor vehicles, or the adjustments that

consumers make to changes in prices, such as a sharp run-up in gasoline prices.

In addition, the PCE estimates are available monthly, so they can provide an early

indication of the course of economic activity in the current quarter. For example, the PCE

For a comprehensive presentation of BEA’s information on PCE, go to www.bea.gov, select

“Data,” then

“By Topic,” and then “Consumer Spending” from the list of options.

For a long-term look at consumer spending, see Clinton P. McCully, “Trends in Consumer Spending and

Personal Saving, 1959–2009,” Survey of Current Business 91 (June 2011): 14–21.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

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estimates for January are released at the end of February, and the estimates for February

are released at the end of March; the advance estimates of gross domestic product (GDP)

for the first quarter are released at the end of April.

The PCE estimates are an integral part of the U.S. national income and product

accounts (NIPAs), a set of accounts that provides a logical and consistent framework for

presenting statistics on U.S. economic activity (see “Chapter 2: Fundamental Concepts”).

Definitions and Concepts

PCE measures the goods and services purchased by “persons”—that is, by

households and by nonprofit institutions serving households (NPISHs)—who are resident

in the United States. Persons resident in the United States are those who are physically

located in the United States and who have resided, or expect to reside, in this country for

1 year or more. PCE also includes purchases by U.S. government civilian and military

personnel stationed abroad, regardless of the duration of their assignments, and by U.S.

residents who are traveling or working abroad for 1 year or less.

Table 5.1 shows the kinds of transactions that are included in and excluded from

PCE. Most of PCE consists of purchases of new goods and of services by households

from private business. In addition, PCE includes purchases of new goods and of services

by households from government and government enterprises, the costs incurred by

NPISHs in providing services on behalf of households, net purchases of used goods by

households, and purchases abroad of goods and services by U.S. residents traveling,

working, or attending school in foreign countries. PCE also includes expenditures

financed by third-party payers on behalf of households, such as employer-paid health

insurance and medical care financed through government programs, and it includes

expenses associated with life insurance and with private and government employee

pension plans. Finally, PCE includes imputed purchases that keep PCE invariant to

changes in the way that certain activities are carried out—for example, whether housing

is rented or owned or whether employees are paid in cash or in kind. PCE transactions are

valued in market prices, including sales and excise taxes.

In the NIPAs, final consumption expenditures by NPISHs is the portion of PCE

that represents the services that are provided to households by NPISHs without explicit

charge (such as the value of the education services provided by a nonprofit college or

university that is over and above the tuition and other costs paid by or for the student’s

household). It is equal to their gross output, which is measured as their current operating

expenses (not including purchases of buildings and equipment, which are treated as

private fixed investment), less their sales to households and to other sectors of the

economy (such as sales of education services to employers) and less the value of any

investment goods (such as software) that are produced directly by the NPISH. Services

that are provided by NPISHs and are paid by or on behalf of households (such as the

tuition and other costs) are already accounted for in PCE as purchases by households.

(For more information, see the section on NPISHs in the technical note at the end of this

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chapter.)

Table 5.1—Content of PCE

Category of expenditure

Comments

Market-based purchases of new goods and of services by

hou

seholds from business, from government, and from

nonpro

fit institutions serving households (NPISHs) and

pur

chases of the services of paid household workers

Includes the full value of financed purchases.

ncludes net outlays for health and casualty insurance.

ncludes direct and indirect commissions on securities

ransactions.

ncludes purchases directly financed by government social

bene

fits, such as Medicaid.

xcludes services (other than owner-occupied housing)

hat are produced by households for their own use.

xcludes expenses associated with operating an

incorporated business.

xcludes services provided directly at government-owned

acilities (such as Veterans’ Administration hospitals).

xcludes finance charges.

xcludes purchases of dwellings and major improvements to

wellings.

xcludes expenses associated with owner-occupied

hou

sing—such as maintenance and repair, mortgage

inancing, and property insurance.

Excludes purchases of illegal goods and services.

Costs incurred by NPISHs in providing services to

hou

seholds less sales by NPISHs to households (final

consumption expenditures by NPISHs)

Costs consist of current operating expenses, including

onsumption of fixed capital.

Excludes purchases of structures and equipment.

Net purchases of used goods by households from business

d from government

Transactions between households are not reflected in PCE

cause they cancel in the aggregation of the personal sector.

Purchases of goods and services abroad by U.S. residents

These transactions are included in PCE in the category

“

foreign travel and other, net.” They are not included in the

various detailed PCE components.

Purchases imputed to keep PCE invariant to whether:

using and institutional structures and equipment are rented

r owned

mployees are paid in cash or in kind

arm products are sold or consumed on farms

aving, lending, and borrowing are direct or are

ntermediated

nancial and insurance service charges are explicit or implicit

Estimates for the following PCE components are entirely

mputed: the space rent of nonfarm owner-occupied housing,

arm products consumed on farms, wages and salaries paid in

ind, private workers’ compensation, services furnished

ithout payment by financial intermediaries except life

nsurance carriers, and the expenses associated with life

nsurance and pension plans.

ther imputations include the imputed rental value of buildings

d equipment owned and used by NPISHs

(

included in their current operating expenditures), the

pace rent of owner-occupied farm housing (included in the

ren

tal value of farm housing), the imputed value of employer-

id medical care and hospitalization insurance, and the

mputed value of premium supplements for property and

asualty insurance.

PCE records purchases for personal use by U.S. residents, wherever the purchases

take place. Thus, the payments by U.S. residents to foreign residents for passenger fares

and travel services and the purchases by U.S. residents while traveling, working, or

attending school outside the United States are included in PCE—though they are not

included in U.S. production. In PCE, these expenditures are recorded collectively as

“Foreign travel by U.S. residents” in the category “Net foreign travel”; they are not

distributed among the individual PCE categories.

In the NIPAs, these expenditures are

For the results of research aimed at better separating spending by nonresidents from spending by

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

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also recorded as imports of goods and services; thus, the PCE and import entries cancel

out in deriving GDP.

Conversely, the payments by foreign residents to U.S. residents for travel services

and the purchases by foreign residents while traveling, working, attending school, or

receiving medical treatment in the United States are not included in PCE—though they

are included in U.S. production. However, these expenditures are included in the source

data that underlie the estimates of most individual PCE categories, where they are

indistinguishable from expenditures made by U.S. residents.

In order to exclude these

expenditures from PCE, they are recorded collectively as “Less: Expenditures in the

United States by nonresidents” in the category “Net foreign travel”; this entry negates the

expenditures by foreign residents that are embedded in the source data. In the NIPAs, the

expenditures by foreign residents are also recorded as exports of goods and services; thus,

they are included in deriving GDP.

PCE is classified by type of product as follows. Goods consist primarily of

tangible commodities that can be stored or inventoried, but they also include certain

intangible products, such as software. Durable goods are goods that have an average

useful life of at least 3 years. Nondurable goods are goods that have an average useful life

of less than 3 years. Services are commodities that cannot be stored or inventoried and

that are usually consumed at the place and time of purchase.

In the 2009 comprehensive update of the NIPAs, BEA introduced a new

classification system for PCE.

This system reflects long-term changes in consumption

patterns due to shifts in consumer demographics, income, and tastes; to the increased

importance of services; and to the introduction of a wide variety of new products. The

system follows recommendations for the classification of household and nonprofit

consumption by the international System of National Accounts (SNA), thus improving

consistency with international standards.

PCE by type of product is classified into the following broad categories:

•

Durable goods: motor vehicles and parts, furnishings and durable household

equipment, recreational goods and vehicles, and other durable goods.

•

Nondurable goods: food and beverages purchased for off-premises consumption,

U.S. residents in the detailed PCE statistics, see Michael Armah and Teresita Teensma, “Research

Spotlight: Estimates of Categories of Personal Consumption Expenditures Adjusted for Net Foreign

Travel Spending,” Survey 92 (April 2012): 13–21.

The portions of travel and passenger fare imports accounted for by business and by government are

not offset in PCE. Rather, these purchases are recorded as business intermediate expenditures and as

government consumption expenditures, respectively.

Passenger fares paid by foreign residents to U.S. carriers for transportation to and from the United States

are not included in any of the PCE categories; these expenditures are recorded as exports in the NIPAs.

Foreign residents’ expenditures for transportation within the United States are recorded in both exports and

PCE for public transportation.

See Clinton P. McCully and Teresita D. Teensma, “Preview of the 2009 Comprehensive Revision of the

National Income and Product Accounts: New Classifications for Personal Consumption Expenditures,”

Survey 88 (May 2008): 6–17.

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clothing and footwear, gasoline and other energy goods, and other nondurable goods.

•

Services: housing and utilities, health care, transportation services, recreation

services, food services and accommodations, financial services and insurance, and

other services.

PCE by function is classified into the following broad categories:

•

Food and beverages purchased for off-premises consumption

•

Clothing, footwear, and related services

•

Housing, utilities, and fuels

•

Furnishings, household equipment, and routine household maintenance

•

Health

•

Transportation

•

Communication

•

Recreation

•

Education

•

Food service and accommodations

•

Financial services and insurance

•

Other goods and services

•

Net foreign travel and expenditures abroad by U.S. residents

In addition, household consumption expenditures and the final consumption

expenditures of NPISHs are now shown separately in the PCE tables. Household

consumption expenditures comprise purchases from business, government, and the rest of

the world and from NPISHs (which are included in the health, recreation, education, and

“other goods and services” categories). Final consumption expenditures of NPISHs are

measured as gross output less own-account investment and less sales to households and

other sectors (see the technical note).

Recording in the NIPAs

As described in chapter 2, the NIPAs can be viewed as aggregations of accounts

belonging to individual transactors in the economy. Thus, PCE represents the final

demand for goods and services by households and NPISHs. In the seven summary

accounts of the NIPAs, PCE appears in the Domestic Income and Product Account

(Account 1), where it is the largest component of final demand, and in the Personal

Income and Outlay Account (Account 3), where it is the dominant outlay.

In the NIPAs, PCE by major type of product is presented in NIPA table group 2.3,

and more detailed information by type of product is presented in NIPA table group 2.4.

This presentation is based on the classification of the PCE categories into durable goods,

nondurable goods, and services (for more information, see the section “Type of product”

in chapter 2). PCE by function is presented in NIPA table group 2.5. This presentation is

based on the classification of the PCE categories into broad expenditure categories (for

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5-6

more information, see “Function” in chapter 2). PCE by type of product on a monthly

basis is presented in NIPA table group 2.8. In addition, separate annual estimates for the

income and outlays of households and of NPISHs are provided in NIPA table group 2.9.

The following is a list of the principal NIPA tables that present the PCE estimates:

2.3.1 Percent Change From Preceding Period in Real Personal Consumption

Expenditures by Major Type of Product

2.3.2 Contributions to Percent Change in Real Personal Consumption Expenditures by

Major Type of Product

2.3.3 Real Personal Consumption Expenditures by Major Type of Product, Quantity

Indexes

2.3.4 Price Indexes for Personal Consumption Expenditures by Major Type of Product

2.3.5 Personal Consumption Expenditures by Major Type of Product

2.3.6 Real Personal Consumption Expenditures by Major Type of Product, Chained

Dollars

2.3.7 Percent Change from Preceding Period in Prices for Personal Consumption

Expenditures by Major Type of Product

2.4.3 Real Personal Consumption Expenditures by Type of Product, Quantity Indexes

2.4.4 Price Indexes for Personal Consumption Expenditures by Type of Product

2.4.5 Personal Consumption Expenditures by Type of Product

2.4.6 Real Personal Consumption Expenditures by Type of Product, Chained Dollars

2.5.3 Real Personal Consumption Expenditures by Function, Quantity Indexes

2.5.4 Price Indexes for Personal Consumption Expenditures by Function

2.5.5 Personal Consumption Expenditures by Function

2.5.6 Real Personal Consumption Expenditures by Function, Chained Dollars

2.8.1 Percent Change From Preceding Period in Real Personal Consumption

Expenditures by Major Type of Product, Monthly

2.8.3 Real Personal Consumption Expenditures by Major Type of Product, Monthly,

Quantity Indexes

2.8.4 Price Indexes for Personal Consumption Expenditures by Major Type of Product,

Monthly

2.8.5 Personal Consumption Expenditures by Major Type of Product, Monthly

2.8.6 Real Personal Consumption Expenditures by Major Type of Product, Monthly,

Chained Dollars

2.8.7 Percent Change from Preceding Period in Prices for Personal Consumption

Expenditures by Major Type of Product, Monthly

2.9 Personal Income and Its Disposition by Households and by Nonprofit

Institutions Serving Households

BEA also prepares estimates of PCE that are not seasonally adjusted; these are available in

Section 8 of the NIPA Interactive Data Tables. The tables present nominal, or “current-

dollar” measures, “real,” or inflation-adjusted measures, and price indexes.

Additionally, BEA prepares “Underlying Detail Tables” for PCE by type of product that

provide current-dollar, chained-dollar, and price estimates at a greater level of detail than

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are shown in the above tables.

BEA does not include these detailed estimates in the

published tables because their quality is significantly lower than that of the higher-level

categories of which they are a part. In particular, these detailed estimates are more likely

to be based on judgmental trends or on less reliable source data.

Overview of Source Data and Estimating Methods

As described earlier, the NIPA estimates, including those for PCE, are prepared

using a wide variety of source data (see “Chapter 3: Principal Source Data”) and using

estimating methods that adjust the source data to the required NIPA concepts and that fill

in gaps in coverage and timing (see “Chapter 4: Estimating Methods”). For PCE, the

estimates are based on statistical reports, primarily from the U.S. Census Bureau but also

from other government agencies; on administrative and regulatory agency reports; and on

reports from private organizations, such as trade associations. The following are among

the principal source data used for the PCE estimates: BEA’s Benchmark Input-Output (I-

O) Accounts, which are based primarily on the Census Bureau’s Economic Censuses, and

BEA’s International Transactions Accounts; the Census Bureau’s Annual Retail Trade

Surveys, Service Annual Surveys, Quarterly Services Reports, and Monthly Retail Trade

Surveys; and the Bureau of Labor Statistics’ Consumer Price Indexes.

Tables 5.A (PCE for goods) and 5.B (PCE for services) following the main text

summarize the source data and estimating methods that are used to prepare the current-

dollar benchmark, nonbenchmark, and current quarterly estimates and the quantity and

price estimates for the categories of PCE as shown by type of product in NIPA table

group 2.4. The source data and methods for the current quarterly estimates reflect both

seasonally adjusted and not seasonally adjusted estimates unless otherwise noted.

Benchmark-year estimates

The source data used for the PCE estimates are complete only for “benchmark”

years—that is, years in which the benchmark I-O accounts are used to establish the level

of PCE and of its components during a comprehensive update. The I-O accounts show the

domestic output of each commodity and its disposition—either as intermediate

consumption by industries or as purchases by final users, including consumers. In the I-O

accounts, PCE is presented as the sum of detailed commodities—goods and services—

purchased by persons.

These commodities are then grouped into the PCE categories

shown in the NIPA tables.

Go to www.bea.gov; select “Tools,” “Interactive Data,” then “GDP and Personal Income,” “Access

Underlying Detail Tables,” “Begin Using the Data,” and “Section 2 – Personal Consumption

Expenditures.”

For more information on the preparation of the I-O benchmark accounts, see U.S. Bureau of Economic

Analysis, Concepts and Methods of the U.S. Input-Output Accounts, April 2009; ; go to www.bea.gov

, and

select “Resources,” “Methodologies,” and scroll down to “Industry.”

A complete listing of the commodities underlying each PCE product category is available at

www.bea.gov; under “Help,” select “Frequently Asked Questions,” then search for

“What is the I-O

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Two methods are used in preparing the benchmark estimates of PCE: commodity-

flow and direct estimation. Direct estimates are made for the PCE categories that, by

definition, are purchased only by persons: food furnished to employees (including the

military and food produced and consumed on farms), standard clothing issued to military

personnel, net expenditures abroad by U.S. residents, the rental value of owner- and

tenant-occupied dwellings, services of workers employed by households, health

insurance, and expense of handing life insurance and pension plans. In addition, direct

estimates are made for expenditures in the United States by nonresidents—which include

personal, business, and government expenditures and which are subtracted in their

entirety in determining PCE.

For most PCE categories, purchases by persons are estimated using the

commodity-flow method (see the section “Commodity-flow method” in chapter 4).

Generally, this method begins with the value of domestic output based on data from the

economic census—such as manufacturers’ shipments for most goods, revenue for

utilities, receipts for most services, and commissions for securities brokerage.

Next, the

domestic supply of each commodity—the amount available for domestic consumption—

is estimated by adding imports and subtracting exports and inventory change. Then, this

supply, denominated in producers’ prices, is allocated among domestic purchasers. The

value of consumer purchases is then converted from producers’ prices to purchasers’

prices by adding wholesale margins and taxes, transportation costs, and retail margins and

taxes.

For some categories, variations of this method are used. For new motor vehicles

and for motor vehicle fuels, the domestic supply is converted to purchasers’ prices and

then allocated among persons, business, and government based on trade source data. For

electricity and for natural gas, residential revenue data provide direct estimates of

purchases by persons. For prescription drugs, retail and health services sales from the

economic census are allocated to PCE using Census Bureau data on sales by class of

customer. For purchased meals and beverages (excluding school sales), food services

sales from the economic census are allocated to PCE by type of eating place.

Nonbenchmark-year estimates

In years other than the benchmark years, the PCE estimates are mainly prepared

using indicator series to represent the pattern of expenditures (see the section

“Interpolation and extrapolation using an indicator series” in chapter 4). The estimates for

most categories of PCE goods are prepared using the retail control method. The estimates

commodity composition of the National Income and Product Accounts (NIPA) PCE categories?”

Three adjustments are made to the economic census data to bring the coverage of industries to levels

that reflect all of their economic activities. The nonemployer adjustment extends the economic census

coverage to establishments without employees or payrolls. The tax-misreporting adjustment corrects for

the underreporting of income and for illegal nonfiling or late filing of tax returns. The tips or gratuity

adjustment corrects for underreporting of receipts in certain industries, such as accommodation, food

service

s, taxi services, and beauty salons. For more information, see Concepts and Methods of the U.S.

Input-Output Accounts, chapter 5, pages 6–7.

See Concepts and Methods of the U.S. Input-Output Accounts, chapter 8.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

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for the remaining categories—motor vehicles; food furnished to employees; food

produced and consumed on farms; tobacco; standard clothing issued to military

personnel; motor vehicle fuels, lubricants, and fluids; and net expenditures abroad by

U.S. residents—are prepared separately (see tables 5.A and 5.B; for motor vehicles and

motor vehicle fuels, see also the technical note).

The retail control method provides the indicator series used in interpolating and

extrapolating the total for most goods, and it provides the “control total” to which the

categories included in the retail control group must sum. This method is implemented as

follows:

1. The estimate of total PCE for most goods is derived by extrapolation from the

benchmark-year estimate using a retail control total of sales by most kinds of business

from the annual retail trade survey.

2. The estimates for prescription drugs are prepared by extrapolation using data from

IMS Health Inc.

3. The estimates for audio discs, tapes, vinyl, and permanent digital downloads are

prepared by extrapolation using data from the Recording Industry Association of

America.

4. The estimates for the rest of the detailed PCE categories are prepared by extrapolation

using estimates of retail sales by corresponding product lines that, in turn, are based

on commodity sales data from the most recent economic census. For goods bought at

grocery stores, the economic census allocations are updated annually using retail

point-of-sale scanner data from Information Resources, Inc.

For goods bought at

radio, television, and electronics stores, at computer and software stores, and at

camera and photographic supply stores, the allocations are updated using retail point-

of-sale scanner data from NPD Group.

For goods bought at electronic shopping and

mail order retailers, the allocations are updated using annual merchandise line sales

from the Census Bureau E-commerce Report and retail point-of-sale scanner data

from NPD Group.

5. The expenditures estimates for the categories in step 3 are adjusted proportionately so

that their sum plus the expenditures for prescription drugs and for audio discs, tapes,

vinyl, and permanent digital downloads is equal to the retail control total in step 1.

(For a general illustration of this method, see the section “Retail control method”

in chapter 4.)

A variety of sources and methods are used to construct the indicator series for the

PCE services categories. For many services, the service annual survey is the primary data

source.

See Eugene P. Seskin and Shelly Smith, “Annual Revision of the National Income and Product

Accounts,” Survey 88 (August 2008): 18.

See Clinton P. McCully and Steven Payson, “Preview of the 2009 Comprehensive Revision of the

NIPAs: Statistical Changes,” Survey 89 (May 2009): 9.

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Current quarterly and monthly estimates

The seasonally adjusted current dollar quarterly and monthly estimates for most

PCE categories are prepared by using seasonally adjusted indicator series to extrapolate

from the annual estimates. Most goods categories are estimated by the retail control

method using data on retail sales from the monthly retail trade survey (MRTS).

The rest

of the goods categories are estimated using other indicator series.

For many services categories, the indicator series are based on data from the

Census Bureau’s Quarterly Services Report. For the remaining categories, the current

estimates are extrapolated based on other source data or on judgmental trends. In general,

the real-dollar series for these categories are extrapolated using the rate of change in

population and a projected rate of change in real per capita consumption based on the

results of the most recent NIPA annual update. The real-dollar estimates are then

converted to current dollars using the appropriate monthly price indexes.

The not seasonally adjusted estimates are derived using the same methods as the

seasonally adjusted estimates, using the not seasonally adjusted versions of the same

indicators

Quantity and price estimates

The estimates of quantities purchased, or real spending, for most of the detailed

PCE categories are prepared by deflation. In this method, the quantities are calculated by

dividing the current-dollar value of the component by an appropriate price index (with the

reference-year value set to 100). For most PCE categories, the closest matching price

index is a consumer price index or indexes. In addition, the quantity estimates for some

detailed components are prepared by quantity extrapolation or by direct valuation. (For

descriptions of the three methods, see the section “Estimates for detailed components” in

chapter 4.)

The aggregate PCE measures are calculated from the detailed components as

chain-type quantity and price indexes (for information about these calculations, see the

section “Estimates for NIPA aggregates” in chapter 4). BEA also prepares measures of

real PCE and its components in a dollar-denominated form, designated “chained-dollar”

estimates (see “Chained-dollar measures” in chapter 4).

For the advance quarterly estimate, the source data for the third month are from the Census Bureau’s

advance monthly retail sales survey because the MRTS data are not yet available.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

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Table 5.A—Summary of Methodology Used to Prepare Estimates of PCE for Goods

Line in

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years except

the most recent year

Most recent year

Current quarterly

estimates**

Goods:

Durable goods:

Motor vehicles and parts:

New motor vehicles

[For more detail,

see the technical

note “Special

Estimates.”]

Based on unit data from

Wards’ Automotive Reports

and registration data from

R.L. Polk & Co. times

average price data from J.D.

Power and Assoc.

Same as for benchmark year.

Same as for

benchmark year.

Same as for

benchmark year.

CPI for new cars and CPI for new

trucks.

Net purchases of

used

motor

vehicles [For more

detail, see the

technical note

“Special

Estimates.”]

Dealers’ margins: retail sales

from EC and margin rate

from ARTS.

Net transactions

commodity

-flow method,

starting with manufacturers’

shipments from EC.

Dealers' margins:

extr

apolation based on

Census gross margins for

used vehicle dealers and

wholesale margins for motor

vehicle and motor vehicle

parts and supplies, except

MSBOs.

Net transactions

: quantities

based on vehicles in

operation data from R.L. Polk

& Co. and average p

rices

based on National Automobile

Dealers Association (NADA).

Dealers' margins:

extrapolation based

on retail sales of

used vehicle dealers

from MRTS.

et transactions:

same as for

nonbenchmark year.

Dealers’ margins:

me as for most

ecent year.

Net

transactions:

extrapolation by

retail sales of used

vehicle dealers

from MRTS.

Dealers’ margins: PPI for used

vehicle sales at new car dealers.

Net transactions

: CPI for used

cars and trucks.

Motor vehicle parts

and accessories

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for tires and CPI for vehicle

parts and equip

ment other than

tires.

Furnishings and durable household equipment:

Furniture and

Commodity-flow method,

Retail control method, using

Retail control

Same as for most

CPI for furniture and bedding,

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

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Table 5.A—Summary of Methodology Used to Prepare Estimates of PCE for Goods

Line in

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years except

the most recent year

Most recent year

Current quarterly

estimates**

furnishings

starting with manufacturers’

shipments from EC.

retail sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report.

method, using retail

sales from MRTS.

recent year.

CPI for clocks, lamps, and

decorator items, CPI for floor

coverings, and C

PI for window

coverings.

Household

appliances

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

etail sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for major appliances and CPI

for other appliances.

Glassware,

tableware, and

household utensils

Commodity-flow method,

starting with

manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for dishes and flatware and

CPI for nonelectric cookware and

tableware.

Tools and

equipment for

house and garden

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent

year.

CPI for tools, hardware, and

supplies and CPI for outdoor

equipment and supplies.

Recreational goods and vehicles:

Video, audio,

photographic, and

information

processing

equipment and

media

Commodity-flow method,

starting with

manufacturers’

shipments from EC. For

computers

/tablets,

peripherals, and software,

the consumer share is based

on retail “class of customer”

data from EC.

For most components, retail

ntrol method, using retail

ales from ARTS. For audio

discs

, tapes, vinyl, and

permanent

digital downloads,

Recording Industry

Association of America

industry data on sales of

physical music and

permanent digital downloads.

omposition of goods sold

rtly based on scanner data

om NPD group and Census

-commerce Report.

For most

components, r

etail

ntrol method,

sing retail

sal

es from MRTS.

For

audio discs,

tapes, vinyl, and

permanent digital

downloads, same as

for nonbenchmark

year.

For most

components, s

ame

s for most recent

ear. For audio

discs, tapes, vinyl,

and permanent

digital downloads

extrapolated using

Nielsen quantity

data on music

sales times the CPI

for

recorded music

and music

subscriptions.

CPI for televisions, CPI for other

ideo equipment, CPI for audio

equi

pment, CPI for recorded

music and music subscriptions

CPI

for video discs and other

dia, CPI for

pho

tographic equipment, CPI for

rsonal computers and

ripheral equipment, CPI for

mputer software and

cessories, and CPI for

elephone hardware, calculators,

d other consumer information

tems.

Sporting

Commodity-flow method,

Retail control method, using

Retail control

Same as for most

CPI for sports equipment.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-13

Table 5.A—Summary of Methodology Used to Prepare Estimates of PCE for Goods

Line in

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years except

the most recent year

Most recent year

Current quarterly

estimates**

equipment,

supplies, guns, and

ammunition

starting with manufacturers’

shipments from EC.

retail sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report.

method, using retail

sales from MRTS.

recent year.

Sports and

recreational

vehicles

Commodity-flow method,

starting with manufacturers’

shipments

from EC.

Retail control method, using

retail sales from ARTS.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for new motorcycles and CPI

for sports vehicles including

bicycles.

Recreational books

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for recreational books.

Musical instruments

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for music instruments and

accessories.

Other durable goods:

Jewelry and

watches

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for jewelry and CPI for

watches.

Therapeutic

appliances and

equipment

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Retail control

method,

using retail

sales from MRTS.

Same as for most

recent year.

CPI for medical equipment and

supplies and CPI for eyeglasses

and eye care.

Educational books

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for educational books and

supplies.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-14

Table 5.A—Summary of Methodology Used to Prepare Estimates of PCE for Goods

Line in

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years except

the most recent year

Most recent year

Current quarterly

estimates**

Luggage and

similar personal

items

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for miscellaneous personal

goods.

Telephone and

communication

equipment

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

partly based on scanner data

from NPD

group.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for telephone hardware,

calculators, and other consumer

information items.

Nondurable goods:

Food and beverages purchased for off-premises consumption:

Food and

nonalcoholic

beverages

purchased for off

premises

consumption

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

largely based on scanner data

from Information Resources,

Inc. and from Fresh Look

Marketing Group.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

Detailed price components of the

CPI for food at home.

Alcoholic

beverages

purchased for off

premises

consumption

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

partly based on scanner data

from Information R

esources,

Inc.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for distilled spirits at home,

CPI for wine at home, and CPI

for beer, ale, and other malt

beverages at ho

me.

Food produced and

consumed on farms

Data from U.S. Department

of Agriculture (USDA).

Same as for benchmark year.

Same as for

benchmark year.

Judgmental trend.

BEA composite index of USDA

prices received by farmers.

Clothing and footwear:

Garments:

Women’s and girls’

clothing

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

partly based on Census E-

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for women’s and girls’

apparel.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-15

Table 5.A—Summary of Methodology Used to Prepare Estimates of PCE for Goods

Line in

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years except

the most recent year

Most recent year

Current quarterly

estimates**

commerce Report.

Men’s and boys’

clothing

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for men’s and boys’ apparel.

Children’s and

infants’ clothing

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for infants’ and toddlers’

apparel.

Other clothing

materials and

footwear

Standard clothing issued

military

: federal budget data.

Other components

commodity

-flow method,

starting with manufacturers’

shipments from EC.

Standard clothing issued

military

: same as for

benchmark year.

Other components

: retail

control method, using retail

sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report.

Standard clothing

issued military: same

as for benchmark

year.

Other components

retail control method,

using retail sales

from MRTS.

Standard clothing

issued military

judgmental trend.

Other components:

same as for most

recent year.

Standard clothing issued military:

PPI for apparel.

Other components

: CPI for

sewing machines, fabri

c, and

supplies and CPI for footwear.

Gasoline and other energy goods:

Motor vehicle fuels,

lubricants, and

fluids [For more

detail on gasoline

and other motor

fuel, see the

technical note

“Special

Estimates.”]

Gasoline and other motor

fuel

: Primarily EC receipts

data on automotive fuels

sold at gasoline stations.

Other components

commodity

-flow method,

starting with manufacturers’

shipments from EC.

Nondiesel gasoline:

information on quantities from

EIA and on prices from BLS.

esel gasoline: information

on household purchases from

BLS

Consumer Expenditure

urvey.

Other components

manufacturers’ shipments

from Census Bureau annual

Nondiesel gasoline:

same as for

nonbenchmark

years.

Diesel gasoline

inform

ation on

quantities from EIA

and on prices from

BLS.

Other components

Diesel and

nondiesel gasoline:

same as for most

recent year.

Other

components: same

as for most recent

yea

CPI for motor fuel and CPI for

motor oil, coolants, and fluids.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-16

Table 5.A—Summary of Methodology Used to Prepare Estimates of PCE for Goods

Line in

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years except

the most recent year

Most recent year

Current quarterly

estimates**

survey of manufactures.

motor fuel quantities

from EIA times CPI

for motor oil,

coolants, and fluids.

Fuel oil and other

fuels

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Retail control

method,

using retail

sales from MRTS.

Same as for most

recent year.

CPI for fuel oil and CPI for

propane, kerosene, and firewood.

Other nondurable goods:

Pharmaceutical and

other medical

products

Prescription and

nonprescription drugs

: EC

data on product

-line sales.

Other components

commodity

-flow method,

starting with manufacturers’

shipments from EC.

Prescription drugs: value of

sales to consumers from IMS

Health, Inc.

Other components

: retail

control method, using retail

sales from ARTS

Composition of goods sold

partly based on Census E

commerce Report.

Prescription drugs:

same as for

nonbenchmark

years.

Other components

retail control method,

using retail sales

from MRTS.

Same as for most

recent year.

CPI for prescription drugs, CPI

for nonprescription drugs, and

CPI for medical equipment and

supplies.

Recreational items

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for toys, CPI for pets and pet

products, CPI for indoor plants

and flowers, and CPI for film and

pho

tographic supplies.

Household supplies

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for household cleaning

products, CPI for household

paper products, CPI for other

linens, CPI for sewing machines,

fabric, and supplies, and CPI for

miscellaneous household

products.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-17

Table 5.A—Summary of Methodology Used to Prepare Estimates of PCE for Goods

Line in

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years except

the most recent year

Most recent year

Current quarterly

estimates**

Personal care

products

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for hair, dental, shaving, and

miscellaneous personal care

products and CPI for cosmetics,

perfume, bath, nail preparations,

and implements.

Tobacco products

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Nielsen point-of-sale data for

tobacco and smoking

products.

Same as for

nonbenchmark

years.

Same as for

nonbenchmark

years.

CPI for tobacco and smoking

products.

Magazines,

newspapers, and

stationery

Commodity-flow method,

starting with manufacturers’

shipments from EC.

Retail control method, using

retail sales from ARTS.

Composition of goods sold

partly based on Census E

commerce Report.

Retail control

method, using retail

sales from MRTS.

Same as for most

recent year.

CPI for newspapers and

magazines and CPI for

stationery, stationery supplies,

and gift wrap.

Net expenditures

abroad by U.S.

residents.

BEA international

transactions accounts

estimates (based on BEA

model).

Same as for benchmark year.

Same as for

benchmark year.

Same as for

benchmark year.

Personal remittances in kind to

non

residents: CPI for

mmodities.

ther components: BEA price

ndex for installation support

services.

* The description “Same as for benchmark year” indicates that the estimate is prepared using a methodology similar to that used for the benchmark

estimate rather than by using an indicator series to interpolate or extrapolate the benchmark estimate.

** For the components that use MRTS for the advance quarterly estimate, the source data for the third month of the quarter are from the Census

Bureau’s Advance Monthly Retail Sales for Retail and Food Services because the MRTS data are not yet available. For some other components, the

source data may be available for only the first 2 months of the quarter; in such cases, the estimates for the third month are based on judgmental trend.

ARTS Annual Retail Trade Survey, Census Bureau

BLS Bureau of Labor Statistics

CES Current Employment Statistics, BLS

CPI Consumer Price Index, BLS

EC Economic Census, Census Bureau

MSBO Manufacturer Sales Branches and Offices

MRTS Monthly Retail Trade Survey, Census Bureau

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-18

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

Services:

Household consumption expenditures:

Housing and utilities:

Housing:

Rental of tenant-

occupied nonfarm

housing [For more

detail, see the

technical note

“Special

Estimates.”]

Unit stocks and average rent

based on Census Bureau

decennial census of housing.

Unit stocks based on Census

Bure

au biennial American

housing survey or on Census

Bureau current population

survey; average rent based on

CPI for rent of primary residence.

Unit stocks adjusted using

Census Bureau data on

housing completions; average

rent same as for

nonbenchmark years.

Tenant-occupied stationary and

mobile homes:

CPI for rent of

primary residence

Tenant landlord durables:

CPI for

major appliances

Imputed rental of

owner

-occupied

nonfarm housing

[For more detail,

see the technical

note “Special

Estimates.”]

Unit stocks based on Census

Bureau decennial census of

housing; average annual rent

based on Census Bureau

residential finance survey.

Unit stocks based on Census

Bureau biennial American

housing survey or on Census

Bureau current population

urvey; average rent based on

CPI for owners’ equivalent rent of

primary residence.

Unit stocks adjusted using

Census Bureau data on

housing completions; average

rent same as for

nonbenchmark years.

CPI for owners’ equivalent rent of

primary

residence.

Rental value of farm

dwellings

Gross rental value of farm

dwellings from USDA.

Same as for benchmark year.

Judgmental trend.

Quantity extrapolation using real-

dollar net stock of farm housing

from BEA capital stock estimates.

For current quarterly based on CPI

for owners’ equivalent rent of

primary residence.

Group housing

Rooming and boarding houses:

commodity

-flow method, starting

with receipts from EC.

Employee lodging

: QCEW

employment times CPI for rent of

primar

y residence.

Rooming and boarding houses:

QCEW wage data.

Employee lodging

: same as for

benchmark year.

Judgmental trend.

CPI for rent of primary residence.

Household utilities:

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-19

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

Water supply and

sanitation

Commodity-flow method, starting

with water, sewerage, and waste

collection receipts from EC and

from COG.

Water supply and sewerage

maintenance

: for third most

recent year, GF receipts adjusted

from fiscal year to calendar year

basis; for second most recent

year, GF receipts and

judgmental

trend; for most recent year,

judgmental trend.

Garbage and trash collection

SAS receipts data.

Water supply and sewerage

maintenance

: same as for

most recent year.

Garbage and trash collection

for

second and third estimate,

QSR

total receipts data; for

advance estimate

, judgmental

trend.

Water supply and sewerage

maintenance

: CPI for water and

sewerage maintenance.

Garbage and trash collection

: CPI

for garbage and trash collection.

Electricity and gas:

Electricity

Variation of commodity-flow

method, using annual residential

revenue from EIA.

Same as for benchmark year,

except most recent year based

on residential revenue from

monthly EIA survey.

EIA data on kilowatt-hour sales

to residential customers and on

cents per kilowatt hour, both

adjusted by BEA from a billing

to a usage basis.

CPI for electricity.

Natural gas

Variation of commodity-flow

method, using EIA annual

residential unit and price data.

Same as for benchmark year.

EIA data on cubic-feet sales of

gas to residential customers

and on cents per cubic foot,

both adjusted by BEA from a

billing to a usage basis.

CPI for utility (piped) gas service.

Health care:

Outpatient services:

Physician services

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For second and third

estimate

s, QSR receipts data;

for

advance estimate,

judgmental trend.

PPI for offices of physicians.

Dental services

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For third estimate, QSR

receipts data; for second and

advance estimates, judgmental

trend.

CPI for dental services.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-20

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

Paramedical

services

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For second and third

estimate

s, QSR receipts data;

for

advance estimates, CES

data on employment, hours,

and earnings.

Home health care: PPI for home

health care services

Medical laboratories

: PPI for

medical laboratories

and PPI for

diagnostic imaging centers

Specialty outpatient care facilities

and health and allied services, and

all other professional medical

services

: CPI for services by other

medical

professionals.

Hospitals and nursing home services:

Hospitals

Private: commodity-flow method,

starting with receipts from EC.

Government

: commodity-flow

method, starting with receipts

from COG and federal agency

data.

Private: SAS receipts data.

Government: federal agency data

and for third most recent year,

GF receipts adjusted from a fiscal

year basis to a calendar year

basis; for second most recent

year, GF receipts and judgmental

trend; for most recent year,

judgmental trend.

Private: for second and third

estimate

s, QSR receipts data;

for

advance estimates, CES

employment, hours, and

earnings.

Government

same as for most

recent year

PPI for hospitals.

Nursing homes

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For second and third

estimate

s, QSR receipts data;

for

advance estimate, CES

employment, hours, and

earnings.

PPI for nursing care facilities.

Transportation services:

Motor vehicle services:

Motor vehicle

maintenance and

repair

Commodity-flow method, starting

with receipts from EC.

SAS, National Automobile

Dealers Assn. (NADA), and

ARTS receipts data, except most

For third estimate, QSR

receipts data; for second and

advance estimates, judgmental

CPI for motor vehicle maintenance

and repair.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-21

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

recent year based on SAS,

NADA, and MRTS receipts data.

trend.

Other motor vehicle

services

Motor vehicle leasing: BLS

nsumer expenditures survey

data.

Motor vehicle rental

: commodity-

flow method, starting with

receipts from EC.

Parking fees and tolls

commodity

-flow method, starting

with state and local government

enterprise receipts from Federal

Highway Administration.

Motor vehicle leasing: same as

for benchmark year, except most

recent year based on

personal

lease registrations from R.L. Polk

& Co. and on BEA estimate of

average expenditures.

Motor vehicle rental

: SAS

receipts data.

Parking fees and tolls

: same as

for b

enchmark year, except most

recent year based on judgmental

trend.

Motor vehicle leasing: same as

for most recent year.

Motor vehicle rental

: for third

estimate,

QSR receipts data;

for second and advance

estimates, judgmental trend.

Parking fees and tolls: same as

for most recent year.

Motor vehicle leasing: CPI for

leased cars and trucks.

Motor vehicle rental

: CPI for car

and truck rental.

Parking fees and tolls

: CPI for

parking fees and tolls.

Public transportation:

Ground transportation:

Railway

Commodity-flow method, starting

with passenger revenue from

Amtrak annual report

, S&L

government data on Alaska

Railroad, and Class 1

railroad

passenger data from the Surface

Transportation Board.

Passenger revenue from Amtrak

monthly reports.

Same as for nonbenchmark

years.

CPI for other intercity

transportation

Intracity mass

transit

Commodity-flow method, starting

with

receipts from American

Public Transit Assn. (APTA).

Data on receipts from APTA and

from SAS,

except most recent

year based on number of

passenger trips from APTA times

CPI for intracity

mass transit and

on SAS receipts data

For second and third

estimate

s, APTA trips data

times CPI for intracity mass

transit and

QSR receipts data;

for

advance estimate, APTA

trips data times CPI for intracity

mass transit.

CPI for intracity transportation.

Taxicabs and ride

Variation of commodity-flow

Information on household

For third estimate, QSR

CPI for intracity transportation.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-22

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

sharing services

method, based primarily on BLS

consumer expenditures survey

data on taxi fares and limo

services receipts.

purchases from BLS Consumer

Expenditure Survey

; for most

recent

year, judgmental trend.

receipts data; for second and

advance estimates, judgmental

trend.

Intercity bus

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For third estimate, QSR

receipts data; for second and

advance estimates, passenger

revenue data from Greyhound

CPI for other intercity

transportation

Other road

transportation

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For third estimate, QSR

receipts data; for second and

advance estimates, judgmental

trend.

CPI for other intercity

transportation

Air transportation

Commodity-flow method, starting

with

receipts from EC.

SAS receipts data.

For second and third

estimate

s, QSR receipts data;

or advance estimates,

judgmental trend.

PPI for domestic scheduled

passenger air transportation.

Water

transportation

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For third estimate, QSR

receipts data; for second and

advance estimates, judgmental

trend.

CPI for other intercity

transportation

Recreation services:

Membership clubs,

sports centers,

parks, theaters, and

museums

High school sports: commodity-

flow method, starting with sales

data from Census Bureau census

of governments.

College sports

: commodity-flow

method, starting with

National

Collegiate Athletic Assn. (NCAA)

sales data.

Other components: commodity-

High school sports: for third most

recent year, GF receipts adjusted

from a fiscal year basis to a

calendar year basis; for

second

most recent year, GF receipts

and judgmental trend; for most

recent year, judgmental trend.

College sports

: NCAA

admissions times CPI for

Membership clubs and

participant sports cent

ers: for

third estimate,

QSR receipts

data; for second and advance

estimates, CES employment,

hours, and earnings.

Amusement parks,

campgrounds, and related

recreational services: for third

Membership clubs and participant

sports centers

: CPI for club dues

and fees for participant sports and

group exercises

;

Amusement parks, campgrounds,

and related recreational services

CPI for

other recreation services;

Spectator sports

CPI for admission

to sporting events;

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-23

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

flow method, starting with

receipts from EC.

admission to sporting events.

Other components

: SAS receipts

data.

estimate, QSR receipts data;

for second and advance

estimates, jud

gmental trend.

Motion picture admissions: box

office receipts from

Boxofficemojo

.com.

Spectator sports

: for third

estimate,

QSR receipts data;

for second and advance

estimates, judgmental trend.

Live entertainment other than

sports

: for third estimate, QSR

receipts data; for second and

advance estimates, judgmental

trend.

Museums and libraries

: CES

employment, hours, and

earnings.

Motion picture theaters, live

entertainment, excluding sports,

and museums and libraries

CPI for

mission to movies, theaters, and

concerts.

Audio-video,

photographic, and

information

processing

equipment services

Commodity-flow method, starting

with receipts from EC.

Video streaming and rental: SAS

receipts data and company

revenue

reports.

Audi

o streaming and radio

services

: Recording Industry

Association of America industry

data on paid subscription

streaming and company revenue

reports.

Other components

: SAS receipts

data.

Cable, satellite, and other live

television services

: for second

and

third estimates, QSR

residential receipts data

and

HarrisX data on live streaming

revenues

; for advance

estimate

, judgmental trend

and

HarrisX data on live streaming

revenues

Video streaming and

rental:

for

video streaming, HarrisX data

n on-demand streaming

revenues; for video rental,

Cable, satellite, and other live

television services

: CPI for cable

and satellite television service

;

Repair

and rental of audio-visual,

photographic, and information

processing equipment

: CPI for

video and audio

;

Photo processing

: CPI for film

processing

;

Photo studios

: CPI for

photographer fees

;

Video

streaming and rental:

CPI for

rental of video discs and other

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-24

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

judgmental trend.

Repair

and rental of audio-

visual, photographic, and

information processing

equipment

: for third estimate,

QSR

receipts data; for second

and advance estimates,

judgmental trend.

Other components: judgmental

trend.

media.

Audi

o streaming and radio services

CPI

for recorded music and music

subscriptions

Gambling

Casino gambling: commodity-flow

method, starting with receipts

from EC.

Lotteries

: commodity-flow

method, starting with receipts

from COG.

Pari

-mutuel net receipts:

commodity

-flow method, starting

with receipts from EC.

Casino gambling: receipts data

from SAS, ARTS, and National

Indian Gaming Commission,

except most recent yea

r based

on SAS receipts data.

Lotteries

: for third most recent

year, GF receipts adjusted from a

fiscal year basis to a calendar

year basis; for second most

recent year, GF receipts and

judgmental trend; for most recent

year, judgmental trend.

Pari

-mutuel net receipts: SAS

receipts data.

Casino gambling: for third

estimate,

QSR receipts data

and revenue data from state

gaming control commissions;

for second and advance

estimates, revenue data from

state gaming control

commissions.

Lotteries

: same as for most

recent year.

Pari

-mutuel net receipts: for

third estimate,

QSR receipts

data; for second and advance

estimates, judgmental trend.

CPI for all items.

Other recreational services:

Veterinary and

other services for

pets

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

CES employment, hours, and

earnings.

CPI for pet services including

veterinary.

All other recreation

services

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

Package tours: for third

estimate,

QSR receipts data;

for second and advance

Package tours: CPI for other

recreation services

Maintenance and repair of

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-25

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

estimates, judgmental trend.

Other components: judgmental

trend.

recreational and sports equipment:

CPI for sporting goods.

Food services and accommodations:

Food services:

Purchased meals

and beverages

Meals at schools: receipts from

COG.

Other components

: receipts from

EC and from COG.

Meals at schools: for third most

recent year, GF receipts adjusted

from a fiscal year basis to a

calendar year basis; for second

most recent year, GF receipts

and judgmental trend; for most

recent year, judgmental trend.

Other

components

: sales by food

services and drinking places from

ARTS; for most recent year, from

MRTS instead of ARTS.

Meals at schools: same as

most recent year.

Other components

: same as

for most recent year.

Meals at schools: CPI for food at

employee sites and schools.

Meals at limited service eating

places

: CPI for limited service

meals and snacks

Meals at other eating places, and

Meals at drinking places

: CPI for

full service meals and snacks

Alcohol in purchased meals

CPI for

alcoholic beverages away from

home

Food furnished to

employees

(including military)

Civilian employees: number of

employees in certain industries

from CES times judgmental

estimate of average

consumption.

Military employees

: expenditures

from federal budget data.

Civilian employees: number of

employees in ce

rtain industries

from CES times CPI for food at

employee sites and schools.

Military employees

: same as for

benchmark year.

Civilian employees: same as

for most recent year.

Military employees

: number of

active duty personnel based on

Federal employment da

times CPI for food at employee

sites and schools.

CPI for food at employee sites and

schools.

Accommodations

Hotels and motels: commodity-

flow method, starting with EC

data on guest room rentals and

using American Hotel and

Lodging Assn. (AHLA)

data for

consumer share of lodging

expenditures and using ITA data

Hotels and motels: ARTS, AHLA,

and ITA data, except most recent

year based on hotel and motel

room revenue data from Smith

Travel Research instead of AHLA

data.

Housing at schools: NCES data

Hotels and motels: hotel and

motel room revenue data from

Smith Travel Research.

Housing at schools: judgmental

trend.

Hotels and motels: CPI for other

lodging away from home including

hotels and motels.

Housing at schools: CPI for housing

at school, exclu

ding board.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-26

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

on travel exports.

Housing at schools

: commodity-

flow method, using National

Center of Education Statistics

(NCES) data on enrollment,

average room rates, and portion

of students living in

student

housing.

on enrollment and on average

room rates.

Financial services and insurance:

Financial services:

Financial services

furnished without

payment [For more

detail, see the

technical note

“Special

Estimates.”]

Commodity-flow method,

primarily based on data

from

federal government

administrative agencies.

Pension plans: same as for

benchmark year, except most

recent year based on QCEW.

Other components

: same as for

benchmark year.

Commercial banks and Other

depository institutions

: for third

estimate, data from federal

government administrative

agencies; for second and

advance estimates, judgmental

trend.

Regulated investment

companies

: Investment

Company Institute data on

mutual fund assets.

Pensi

on plans: judgmental

trend.

Commercial banks: for annual,

quantity extrapolation, using BLS

banking output indexes; for

quarterly, judgmental trend.

Other depository institutions

PCE deflator for services furnished

without payment by commercial

banks

her components

: BEA composite

indexes of input costs.

Financial service charges, fees, and commissions:

Financial service

charges and fees

[For more detail,

see the technical

note “Special

Estimates.”]

Commodity-flow method, based

on data

from EC, from other

federal government sources, and

from private sources.

Based on data from Federal

Deposit Insurance Corporation

(FDIC), from other federal

government sources, and from

private sources.

For third estimate, primarily

FDIC data and

judgmental

trend; for second and advance

estimates, judgmental trend.

CPI for checking account and other

bank services.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-27

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

Securities

commissions [For

more detail, see the

technical note

“Special

Estimates.”]

Commodity-flow method,

primarily based on data f

rom EC,

federal

government

administrative agencies, and

stock exchanges

Primarily based on Financial and

Operational Combined Uniform

Single Reports data, other

federal government

administrative agency data, and

stock exchange data.

For third estimate, same as for

nonbenchmark years; for

second and advance

estimates, stock exchange

data and Investment Company

Institute (ICI) data.

Direct commissions on exchange-

listed

equities: PPI for brokerage

services,

equities and ETFs.

Other direct

commissions: PPI for

brokerage services, all other

securities

Imputed commissions on over

-the-

counter equity securities

: PPI for

dealer transactions,

equity

securities.

Other imputed commissions

: PPI

for dealer transactions, debt

securities and all other

trading.

Commissions on mutual fund sales:

quantity extrapolation using mutual

fund sales from ICI deflated by CPI

for all items.

Portfolio

management and

investment advice

services

Commodity-flow method,

primarily based on data from EC.

SAS receipts data.

For third estimate, QSR

receipts data; for second and

advance estimates, CES data

on employment, hours, and

earnings.

Fixed-weighted average of PPI for

Portfolio management and PPI for

investment advice.

Trust, fiduciary, and

custody activ

ities

Commodity-flow method,

primarily based on data from EC

and from the Federal Financial

Institution Examination Council.

FDIC data.

For third estimate, same as for

nonbenchmark years; for

second and advance

estimates, judgmental trend.

PPI for Commercial bank trust

services

Insurance:

Life insurance [For

more detail, see the

technical note

“Special

Primarily based on data on

operating expenses from A.M.

Best Co.

Same as for benchmark year,

except most recent year

based

on QCEW wage data.

CES data on earnings.

BEA composite index of input

costs.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-28

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

Estimates.”]

Net household

insurance [For more

detail, see “Property

and casualty

insurance” in the

technical note.]

Based on A.M. Best Co. data on

premiums and losses.

Same as for benchmark year.

Judgmental trend.

PPI for homeowners’ insurance.

Net health

insurance [For more

detail on workers’

compensation, see

“Property and

casualty insurance”

in the technical

note.]

Medical care and hospitalization:

premiums from N

ational Center

for Health Statistics (NCHS);

benefits from EC.

Workers’ compensation

commodity

-flow method, based

on A.M. Best Co. data on

premiums and losses.

Medical care and hospitalization:

premiums

from NCHS and A.M.

Best Co. except judgmental trend

for most recent year; benefits

based on a ratio using A.M. Best

data on benefits and premiums

except for judgmental trend for

most recent year.

Workers’ compensation: same as

for benchmark year.

Judgmental trend.

Medical care and hospitalization:

PPI for d

irect health and medical

insurance carriers.

Workers’ compensation

: PPI for

workers’ compensation insurance.

Income loss

: CPI for all items.

Net motor vehicle

and other

transportation

insurance [For more

detail, see “Property

and casualty

insurance” in the

technical note.]

Based on A.M. Best Co. data on

premiums and losses.

Same as for benchmark year.

Judgmental trend.

PPI for private passenger auto

insurance.

Other services:

Communication:

Telecommunication

services

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

Cellular telephone: for second

and

third estimates, QSR total

Cellular telephone: Fixed-weighted

average of CPI for wireless

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-29

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

receipts data; for advance

estimate, judgmen

tal trend.

Other components

: for second

and

third estimates, QSR

residential receipts data; for

advance estimate

judgmental

trend.

telephone services and CPI for

smartphones

Land

line, telephone services, local

charges and long

-distance charges

CPI for land line telephone

services.

Postal and delivery

services

Commodity-flow method, starting

with revenues from U.S. Postal

Service (USPS) and

receipts

from EC.

USPS and SAS receipts data.

For second and third

estimate

s, USPS receipts data

and

QSR receipts data; for

advance estimate

, judgmental

trend.

First-class postal service (by U.S.

Postal Service)

: CPI for postage.

Other delivery services (by non

U.S. postal facilities)

: CPI for

delivery services.

Internet access

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For second and third

estimate

s, QSR receipts data;

for

advance estimate,

judgmental trend.

CPI for internet services and

electronic information providers.

100

Education services:

101

Higher education

Private: commodity-flow method,

starting with receipts data from

NCES

Public

: commodity-flow method,

starting with tuition receipts from

COG.

Private: same as for benchmark

year, except judgmental trend for

2 most recent years.

Public

for third most recent year,

tuition receipts adjusted from

a fiscal year basis to a calendar

year basis; for second most

recent year, GF receipts and

judgmental trend; for most recent

year, judgmental trend.

Nonprofit: CES employment

times CPI for colle

ge tuition

and fees.

Public and proprietary

judgmental trend.

CPI for college tuition and fees.

102

Nursery,

elementary, and

secondary schools

Elementary and secondary:

commodity

-flow method, starting

with estimated receipts based on

Elementary and secondary:

Expenses from NCES.

Nursery: SAS receipts data.

Elementary and secondary:

CES employment times CPI for

elementary and high school

Elementary and secondary: CPI for

elementary and high school tuition

and fees.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-30

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

expenses from NCES and tuition-

-expenses ratios from National

Catholic Education Assn. data.

Nursery

: commodity-

flow method,

starting with receipts from EC.

tuition and fees.

Nursery

: For third estimate,

QSR

receipts data; for second

and advance estimates, CES

employment times CPI for child

care and nursery school.

Nursery: CPI for child care and

nursery school.

103

Commercial and

vocational schools

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For third estimate, QSR

receipts data; for second and

advance estimates,

CES

employment times CPI

for

technical and business school

tuition and fees

CPI for technical and business

school tuition and fees.

104

Professional and other services:

Legal services

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For second and third

estimate

s, QSR receipts data;

for

advance estimate,

judgmental trend.

CPI for legal services.

Accounting and

other business

services

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

Judgmental trend.

Tax preparation and other related

services

: CPI for tax return

preparation and other accounting

fees

Employment agency services

: PPI

for employment placement

agenc

ies—primary services.

Other personal business services

CPI for miscellaneous personal

services.

Labor organization

dues

Commodity-flow method, based

on wages from QCEW and on

IRS ratio of membership dues to

QCEW wage data.

Based on CES employment,

hours, and earnings.

BEA composite index of input

costs.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-31

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

wage expenses for labor,

agricultural, and ho

rticultural

organizations.

Professional

association dues

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For third estimate, QSR

receipts data; for second and

advance estimates, based on

CES employment, hours, and

earnings.

CPI for legal services.

Funeral and burial

services

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

For second and third

estimate

s, QSR receipts data;

for

advance estimate,

judgmental trend.

CPI for funeral expenses.

105

Personal care and

clothing services

Commodity-flow method, starting

with receipts from EC.

SAS receipts data.

Repair and hire of footwear:

judgmental trend.

Other components

: for second

and

third estimates, QSR

receipts data; for

advance

estimate

, judgmental trend.

Hairdressing salons and personal

grooming establishments

: CPI for

haircuts and

other personal care

services

Miscellaneous personal care

services; clothing repair, rental and

alterations; and, repair and hire of

footwear

: CPI for apparel services

other than laundry and dry

cleaning

Laundry and dry

cleaning services:

CPI for

laundry and dry cleaning

services.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-32

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

106

Social services and

religious activities

Religious organizations:

commodity

-flow method, starting

with receipts based on

Independent Sector study of

church finances.

Other private social service

activities

: commodity-flow

method, starting with receipts

from EC.

Public social service activities

government sales from COG.

Religious organizations: data on

change in charitable giving to

religious organizations from

Giving USA publication

, except

most

recent year based on

QCEW wage data.

Other private social service

activities

: SAS receipts data.

Public social service activities: for

third most recent year, GF

receipts

adjusted from a fiscal

year basis to a calendar year

basis; for second most recent

year, GF receipts and judgmental

trend; for most recent year,

judgmental trend.

Community food and

housing/emergency/other relief

services

: for second and third

estimates, QSR receipts data;

for

advance estimate, based

on CES employment, hours,

and

earnings.

Religious organizations

judgmental trend.

Foundations: for third estimate,

QSR

receipts data; for second

and advance estimates,

judgmental trend.

Other social service activities

for third estimate,

QSR

receipts data; for second and

advance esti

mates, based on

CES employment, hours, and

earnings

Child care: CPI for child care and

nursery school.

Other components: BEA composite

index of input costs.

107

Household

maintenance

Domestic services: receipts of

residential cleaning services from

and earnings of private

household workers from Census

Bureau current population survey

(CPS).

Other components

: commodity-

flow method, starting with

receipts from EC.

Domestic services: receipts of

residential cleaning services from

SAS and

earnings of private

household workers from CPS.

Other components

: SAS receipts

data.

Domestic services and other

household services

judgmental trend

Moving, storage, and freight

services

: for second and third

estimates, QSR receipts data;

for

advance estimate,

judgmental trend.

Other components: f

or third

estimate,

QSR receipts data;

for second and advance

estimates, judgmental trend.

Domestic services: CPI for

domestic services, CPI for food at

home, and CPI for

laundry and dry

cleaning services

Moving, storage, and freight

services

: CPI for moving, storage,

freight expense

Repair of furniture, furnishings, and

floor coverage; and repair of

household appliances

: CPI for

repair of household items

Other household services: CPI for

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-33

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

household operations.

108

Net foreign travel:

109

Foreign travel by

U.S. residents

Travel expenditures and

passenger fares paid to foreign

air and ocean carriers

: ITA data

on travel and passenger fare

imports. Consumer share based

on International Trade

Administration in

-flight survey

data.

Passenger fare payments to U.S.

air carriers

: international air

passenger revenue from

, less

data on air

passenger fare

exports. Consumer share based

on International Trade

Administration in

-flight survey

data.

Travel expenditures and

passenger fares paid to foreign

air and ocean carriers

: Same as

for benchmark year.

Passenger fare payments to U.S.

air carrie

rs: international air

passenger revenue from

SAS,

less data on air passenger fare

exports.

Travel expenditures and

passenger fares paid to foreign

air and ocean carriers: for third

and second estimates, same

as for benchmark year; for

advance estimate, sam

except using monthly U.S.

international trade in goods

and services.

Passenger fare payments to

U.S. air carriers

: for second

and

third estimates, QSR

receipts

data, less ITA data on

air

passenger fare exports; for

advance

estimate, same

except using monthly U.S.

international trade in goods

and services.

Travel: BEA composite index of

foreign CPIs (exchange

-rate

adjusted).

Passenger fare imports: BLS import

price index for air

passenger fares.

Passenger fare payments to U.S.

carriers

: PPI for international

scheduled passenger air

transportation.

110

Less: Expenditures

in the United States

by nonresidents

ITA data on exports.

Same as for benchmark year.

For third and second

estimates, same as for

benchmark year; for advance

estimate, monthly U.S.

international trade in goods

and services.

Foreign travel in the United States:

BEA composite price index from a

number of CPI and PPI component

indexes.

Medical expenditures

of foreigners:

CPI for hospital and related

services.

Expenditures of foreign students in

the United States

: CPI for college

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-34

Table 5.B—Summary of Methodology Used to Prepare Estimates of PCE for Services

Line

NIPA

table

group

2.4

Component

Current-dollar estimates

Quantity and price estimates

(Quantity estimate prepared by

deflating with price index unless

otherwise indicated)

Benchmark year

Indicator series used to interpolate and extrapolate*

Nonbenchmark years

Current quarterly estimates

tuition and fees.

111

Final consumption

expenditures of

nonprofit institutions

serving households

Calculated as line 112 minus line 113.

112

Gross output of

nonprofit institutions

[For more detail,

see technical note

“Special

Estimates.”]

See the technical note and the relevant detailed categories above.

BEA indexes of input costs.

113

Less: Receipts from

sales of goods and

services by

nonprofit institutions

[For more detail,

see technical note

“Special

Estimates.”]

See the technical note and the relevant detailed categories above.

See relevant detailed categories

above.

* The description “Same as for benchmark” indicates that the estimates are prepared using a methodology similar to that used for the benchmark

estimates rather than by using an indicator series to interpolate or extrapolate the benchmark or annual estimates.

ARTS Annual Retail Trade Survey,

Census Bureau

BEA Bureau of Economic Analysis

BLS Bureau of Labor Statistics

BTS Bureau of Transportation Statistics

CES Current Employment Statistics, BLS

COG Census of Governments, Census

Bureau

CPI Consumer Price Index, BLS

EC Economic Census, Census Bureau

EIA Energy Information Administration

GF Annual Survey of Government

Finances, Census Bureau

IRS Internal Revenue Service

ITA International Transactions

Accounts, BEA

MRTS Monthly Retail Trade Survey,

Census Bureau

PPI Producer Price Index, BLS

QCEW Quarterly Census of Employment

and Wages, BLS

QSR Quarterly Services Report, Census

Bureau

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-35

SAS Service Annual Survey, Census

Bureau

USDA U.S. Department of Agriculture

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-36

Technical Note: Special Estimates

This technical note provides detailed descriptions of the sources and methods used

to estimate the following key components of personal consumption expenditures (PCE):

new motor vehicles; net purchases of used motor vehicles; motor vehicle fuels; rental of

tenant- and owner-occupied nonfarm housing; financial service charges and fees;

securities commissions; financial services furnished without payment; life insurance;

property and casualty insurance (household insurance, workers’ compensation, and motor

vehicle insurance); and nonprofit institutions serving households.

New motor vehicles

The annual and quarterly estimates of PCE for new motor vehicles are derived by

summing monthly estimates that are prepared separately for domestic autos, for foreign

autos, for domestic light trucks, and for foreign light trucks.

The monthly estimates of

the value of motor vehicle sales are derived as the number of units sold times the average

expenditure per transaction, and the shares of these sales that are accounted for by

persons are derived using information on new motor vehicle registrations.

The data on monthly unit sales of autos and of light trucks (including vans and

sport utility vehicles) are obtained from Wards’ Automotive Reports. The share of these

sales that are accounted for by persons is derived from monthly data on new registrations

by persons, government, and business from R.L. Polk & Co. For autos, the business

portion of “mixed-use” autos—that is, autos used both for business and personal use—is

removed from sales to persons; this adjustment, which was initially based on data on

business mileage driven by household members from a since-discontinued Census Bureau

Current Population Survey (CPS) report, “Current Buying Indicators,” is updated

annually to reflect changes in the ratio of self-employed persons to households based on

CPS data.

For trucks, the share of sales to persons is benchmarked to information on the

personal share of new truck purchases from the Vehicle Inventory and Use Survey in the

Census Bureau’s Economic Census. For foreign autos, the share of sales to persons is

equal to total unit sales less unit sales to business and government, which is estimated

annually using data on business and total registrations. For domestic autos, sales to

In the NIPA estimates of PCE, sales of domestic motor vehicles consist of units assembled in the United

States, Canada, and Mexico; sales of foreign motor vehicles are those assembled elsewhere. (In contrast, in

the addenda to NIPA table 7.2, “Motor Vehicle Output,” “domestic output of new autos” refers only

autos assembled in the United States, and “sales of imported autos” refers to autos assembled outside the

United States.)

According to the international System of National Accounts, “when the owner of a business uses a

vehicle partly for business purposes and partly for personal benefit, the expenditure on the purchase of the

vehicle should be split between gross capital formation and household final consumption expenditures in

proportion to its use for business and personal purposes.” See Commission of the European

Communities, International Monetary Fund, Organisation for Economic Cooperation and Development,

United Nations, and the World Bank, System of National Accounts 2008

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-37

persons is equal to total unit sales to persons less foreign unit sales to persons.

The estimates of average expenditure per transaction are derived from data on

monthly retail transactions prices by make, model, and trim level from J.D. Power and

Associates.

Overall average expenditures are obtained using these detailed average

transactions prices and the data on unit sales by model.

For the current quarterly and monthly estimates, the business portion of “mixed-

use” autos and the business portion of foreign car sales are held constant at the

percentages for the most recent year, and the business portions of domestic autos and of

light trucks are based on the monthly registrations data. For the advance quarterly

estimate, 3 months of unit sales and price data and 2 months of registrations data are

available; the business portions for the third month of the quarter are estimated by

applying the previous month’s personal registration percentages by make to the third

month’s sales by make.

The estimates of real PCE for new motor vehicles are prepared by deflation. For

autos, the CPI for new cars is used as the deflator; for trucks, the CPI for new trucks is

used.

The make is the brand name of the vehicle (such as BMW or Chevrolet). The model is the classification

of the vehicle as a particular variety within the same make (such as BMW 3-Series or Chevrolet Malibu).

The trim level is the classification of the vehicle as a particular type within the same model (such as BMW

328i or Malibu 1LT).

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-38

Net purchases of used motor vehicles

In PCE, net purchases of used motor vehicles consist of dealers’ margins on

purchases of these vehicles by persons and of net transactions between persons and other

sectors of the economy. Net transactions for the personal sector are positive, because

persons buy more vehicles from the other sectors than they sell to those sectors; in

contrast, net transactions for business are negative.

In calculating GDP, the intersectoral

net transactions offset, leaving the margins on the transactions as value added. Separate

estimates are made for used autos and for used light trucks.

Dealers’ margins

All purchases of used vehicles by persons from dealers include the retail margin—

the difference between the selling price and the dealer’s cost of acquisition. Additionally,

they may include a wholesale margin (for vehicles sold to dealers by wholesalers) and

sales taxes that are collected by dealers on behalf of government.

For benchmark years, total margins are estimated by applying margin rates and

sales-tax rates to retail and wholesale sales of used motor vehicles. Then, the proportion

of this total that applies to sales to persons is determined.

Retail and wholesale margin

rates are estimated using data from the Census Bureau’s Annual Retail Trade Survey

(ARTS) and Annual Wholesale Trade Survey (AWTS). Wholesale and retail sales of

used motor vehicles are based on product-line sales data from the Census Bureau’s

Economic Census. Sales taxes are calculated using data from the Census Bureau’s Census

of Governments, from individual states on tax collections, from ARTS, and from AWTS.

For autos, almost all the margin is allocated to sales to persons; for light trucks, the

allocation to persons is based on information from the Census Bureau’s Vehicle

Inventory and Use Survey.

For nonbenchmark years, retail and wholesale margins are extrapolated using

Census Bureau’s gross margins for used car dealers and wholesale margins excluding

Manufacturers’ Sales Branches and Offices (MSBOs) for motor vehicle and motor

vehicle parts and supplies, respectively. Once retail and wholesale margins are estimated,

both used margin components are summed to derive a total used margin of motor

vehicles. For the most recent year, total retail and wholesale margins are extrapolated

using Census Bureau’s retail sales of used car dealers and wholesale sales except MSBOs

for motor vehicle and motor vehicle parts and supplies, respectively. The total used

margin is then allocated to used autos and to used light trucks based on changes in used

vehicle unit registrations from R.L. Polk & Co. and on average prices of used

These values plus the associated margins are shown as “net purchases of used autos and used light trucks”

in lines 9 and 18 in NIPA table 7.2.5B.

For a general discussion of the estimation of wholesale and retail margins and taxes, see U.S. Bureau of

Economic Analysis, Concepts and Methods of the U.S. I-O Accounts, 8: 6–14; go to www.bea.gov,

select

“Resources,” then “Methodologies.””

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-39

vehicles sold at wholesale auctions from the Auto Dealers Exchange Service of America

(ADESA).

The current quarterly and monthly estimates of margins on used autos and used

light trucks are extrapolated from the annual estimates using data on retail sales of used

car dealers from the monthly retail trade survey. The estimates of real margins are

prepared by deflation, using the PPI for used vehicle sales at new car dealers.

Net transactions

Net transactions between persons and other sectors of the economy primarily

consist of the wholesale value of purchases by persons from dealers less sales by

persons to dealers (either directly or as trade-ins).

In addition, transactions may occur

between persons and businesses other than dealers (such as the sale of scrapped

vehicles), government, and nonresidents. Transactions among persons are intra-sectoral

and so do not affect PCE.

For benchmark years, purchases of used motor vehicles by persons from dealers

is estimated as (1) dealer sales less (2) exports less (3) dealers’ margins, (4) split into

purchases by persons and by business. Dealer sales are from the Economic Census

merchandise line data, adjusted to include sales taxes using data from the ARTS; exports

are from Census’ Foreign Trade Statistics and BEA’s Balance of Payments Division;

dealers’ margins is from the ARTS; and the split is based on information from 2012

Economic Census of Retail Trade Class of Customer data and BEA’s Government

Expenditure data.

Sales of used motor vehicles by persons to dealers is estimated as (1) dealer

sales less (2) dealers’ margin plus (3) the change in dealers’ inventories of used motor

vehicles, (4) split into sales by persons and by business. The change in dealer

inventories is based on inventory data from the ARTS; the split between sales by persons

and by business is based on data from 2012 Economic Census of Retail Trade Class of

Customer data and BEA’s Government Expenditure data.

For nonbenchmark years, estimates of net transactions are developed by

valuing the annual change in unit stocks of used motor vehicles held by persons, rather

than by explicitly taking into account each type of transaction listed above. Yearend

unit stocks of used autos and of used light trucks are estimated for each year of original

sale (vehicles greater than 11 years old are grouped together) using annual data on new

motor vehicle purchases and retention information developed from R.L. Polk & Co.

data on vehicles in use by model year.

Unit stocks held by business are based on

For autos, net purchases also includes reimbursement of government employees for use of personal autos

on government business.

The year of original sale is the year in which the vehicle was sold as new. Thus, for example, the stock of

used autos at yearend 2007 consists of all new autos that were sold in 2007, all new autos that were sold in

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-40

business purchases of new motor vehicles and on retention rates for rental vehicles (6–

18 months), leased vehicles (2–4 years), and other business vehicles (1–9 years). Unit

stocks held by government are based on government purchases of new vehicles and on

assumed retention rates. Stocks held by persons are then calculated as the residual.

Changes in the unit stocks of autos and of light trucks held by persons reflect

purchases of new vehicles, scrappage of old vehicles, and net unit transactions other than

scrappage. Purchases of new autos and of light trucks by persons are estimated

separately (see the section “New motor vehicles”). Scrapped units are calculated by age

of vehicle as a proportion of total vehicle scrappage; this proportion is assumed to be

equal to the ratio of the unit stock held by persons to the total unit stock. Net unit

transactions other than scrappage is then calculated as the residual.

The changes in unit stocks, grouped by age, are then valued at wholesale prices.

The average wholesale value for each age group of used autos and of used light trucks is

based on average used auto and used light truck prices by model year from National

Automobile Dealers Association (NADA). Scrapped units by age are valued at 8

percent of the wholesale price.

Current quarterly and monthly estimates of net transactions are extrapolated from

the annual estimates, using data on retail sales of used car dealers from the monthly

retail trade survey. The estimates of real net transactions are prepared by deflation, using

the CPI for used autos and trucks.

2006 and were not subsequently scrapped or otherwise disposed, and so on.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-41

Gasoline and other motor fuel

The estimates of PCE for gasoline and other motor fuel are derived as the product

of the quantity purchased for personal use and the average retail price per gallon. The

estimates cover the personal use of motor fuel for all vehicles owned, leased, and rented

by households.

Benchmark-year estimates. The benchmark estimates rely on the U.S. Census

Bureau’s Economic Census product-line data on receipts for automotive fuels sold at

gasoline stations. The product line for automotive fuels is comprised of:

•

Unleaded regular gasoline

•

Unleaded mid-grade gasoline

•

Unleaded premium gasoline

•

Diesel fuel

•

Other automotive fuels

The product line for diesel fuel is used to estimate total diesel gasoline

consumption; the portion of this consumption that is accounted for by households is

based on judgmental analysis of various source data. The remaining product lines for

automotive fuels are used to estimate total non-diesel gasoline and other motor fuel

consumption. The portion of this consumption that is accounted for by households is

based primarily on the Census Bureau’s Class of Customer data from the 2012

Economic Census. Aviation gasoline or air fuel is also included in this estimate; fuel

purchased for airplanes is calculated as total gallons of gasoline consumed for aviation

(which excludes jet fuel) from the Federal Highway Administration (FHWA) times a

consumer share based on Federal Aviation Administration data on the proportion of

hours flown in general aviation use that is accounted for by personal use.

Nonbenchmark-year estimates. Nonbenchmark-year estimates of PCE for

gasoline and other motor fuel are prepared by separately extrapolating PCE for non-

diesel gasoline and PCE for diesel gasoline from the preceding annual estimate and then

summing the two estimates. PCE for non-diesel gasoline is based on data on the quantity

of gasoline supplied from the Energy Information Administration (EIA) and on average

prices of gasoline by grade from the Bureau of Labor Statistics (BLS). PCE for diesel

gasoline is based on the BLS Consumer Expenditure Survey data on household

purchases of diesel fuel, when available. Because the Consumer Expenditure Survey

lags by 1 year, the estimate for the most recent year is based on EIA quantity supply of

gasoline data and the BLS average price data for diesel fuel.

Current-quarterly estimates. For the current quarterly estimates, the third estimate

is prepared using the same methodology as that used for the most-recent-year estimates.

For the second quarterly estimate, EIA data on monthly quantities by grade are available

for the ﬁrst 2 months of the quarter, and weekly EIA data for total gasoline supplied is

used for the third month. For the advance quarterly estimate, monthly quantities by

grade are available for the first month, and weekly EIA data on total gasoline supplied

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-42

are used for the third month.

Quantity estimates. The estimates of real PCE for gasoline and other motor fuel

are prepared by deflation using the CPI for motor fuel.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-43

Rental of tenant- and owner-occupied nonfarm housing

As noted in “Chapter 2: Fundamental Concepts,” purchases of newly constructed

housing are treated as private fixed investment rather than as consumption expenditures

in the NIPAs, and the stock of housing is treated as fixed assets. The housing stock

provides a flow of housing services that are consumed by persons who rent their housing

and by persons who own the housing they occupy (referred to as “owner-occupants”). In

the NIPAs, owner-occupants are treated as owning unincorporated enterprises that

provide housing services to themselves in the form of the rental value of their

dwellings.

Thus, PCE for housing services includes both the monetary rents paid by

tenants and an imputed rental value for owner-occupied dwellings (measured as the

income the homeowner could have received if the house had been rented to a tenant).

This treatment is designed to make PCE (and GDP) invariant to whether the house is

rented by a landlord to a tenant or is lived in by the homeowner.

PCE for rental of tenant-occupied dwellings is based on the rent paid by tenants—

which may include charges for major appliances and furnishings, utilities, or services.

The rent paid is then adjusted to exclude any utility payments and to include tenant

expenditures for major replacements, maintenance, and repairs that are not reimbursed

by the landlord owner. Payments for utilities are subtracted because they are already

accounted for elsewhere in PCE, and tenants’ unreimbursed expenditures are added

because they are considered part of the rental cost to the tenant. The rental value of

owner-occupied dwellings is based on that of equivalent tenant-occupied dwellings, but

it consists of the rental value of the dwelling alone.

Separate estimates are prepared for owner-occupied permanent-site dwellings,

owner-occupied mobile homes, tenant-occupied permanent-site dwellings, and tenant-

occupied mobile homes. For each type of dwelling, rent equals the number of occupied

units times the rent per unit.

Number of housing units

The benchmark estimates of units for each type of dwelling are based on data

from the Census Bureau’s decennial Census of Housing (COH).

For tenant- and

owner- occupied permanent-site homes, the number of units from the COH is adjusted

by BEA to reﬂect the stock at midyear and to account for certain vacant units, such as

This treatment is consistent with that of the international System of International Accounts (SNA):

“Households that own the dwellings they occupy are formally treated as owners of unincorporated

enterprises that produce housing services consumed by those same households” (SNA 2008: 6.117).

The income earned from the rental of housing, including the provision of owner-occupied housing

services, is reflected in the NIPA measure of rental income of persons. For more information on this

measure, see chapter 12 of this handbook.

According to the SNA, “The ratio of owner-occupied to rented dwellings can vary significantly…so both

international and inter-temporal comparisons of the production and consumption of housing services could

be distorted if no imputation were made for the value of own-account housing services.” (

SNA 2008: 6.34).

Thus, in the comprehensive update of the NIPAs, the benchmark estimates for PCE for housing services

are made for the years ending in “0,” and the estimates for other years are nonbenchmark annual estimates.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-44

vacation homes.

For permanent-site (or stationary) homes, nonbenchmark annual estimates are

interpolated and extrapolated from the benchmark estimates. For years for which data

from the Census Bureau’s biennial American Housing Survey (AHS) are available, unit

stocks from the AHS are used as the indicator series; for other years, data from the

Census Bureau’s Current Population Survey are used to interpolate and extrapolate the

AHS-based estimates. For mobile (or manufactured) homes, the indicator series is based

on changes in unit stocks that are derived from data on shipments of manufactured

homes in the Census Bureau’s Monthly Construction Statistics, using a perpetual

inventory calculation (see “Chapter 4: Estimating Methods”).

Rent per unit

For tenant-occupied permanent-site dwellings, the benchmark estimates of rent

per unit are based on COH data on units by rent class. The charges for utilities—energy

(electricity, gas, and fuel oil and other fuels) and water and sewerage maintenance—that

must be subtracted from rent are estimated as follows:

•

The PCE estimates for each type of energy are allocated between tenant-occupied

housing and owner-occupied housing using data from the Department of Energy’s

Residential Energy Consumption Survey (RECS), and the portion of the tenant

expenditures for energy that is included in rent is derived using AHS data. In the

cases where the RECS or AHS are not conducted in the benchmark year, proportions

derived from surveys in nearby years are interpolated for the benchmark estimates.

•

PCE for water and sewerage maintenance is allocated between tenant-occupied

housing and owner-occupied based on the tenant-occupied share of total nonfarm

permanent-site units, and the portion of the tenant expenditures that is included in

rent is derived using AHS data.

The nonbenchmark annual estimates of rent per unit less utilities are derived from

data on average rental value that includes expenditures for utilities whether they are paid

separately or included in rent, so these data must be adjusted to exclude average utility

payments. The average rental value is benchmarked using COH data on units by rent

class and is interpolated and extrapolated using AHS data on units by rent class. In non-

AHS years, this rental value is interpolated and extrapolated from the AHS estimates

using the CPI for rent of primary residence. Average expenditures for utilities are

calculated as total expenditures for utilities (estimated as described above) divided by

total tenant-occupied units.

The rental value of appliances and furnishings provided by property owners is

equal to BEA’s estimate of depreciation at current replacement cost. For both benchmark

and nonbenchmark years, tenants’ unreimbursed expenditures for major replacements

and for maintenance and repairs—originally reported in the Census Bureau’s Survey of

Residential Alterations and Repairs—are extrapolated using data from the BLS

Consumer Expenditure Survey (CEX).

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-45

For owner-occupied permanent-site homes, the benchmark estimates of rent per

unit are derived using landlord-reported rent receipts and housing values from the

Census Bureau’s Residential Finance Survey, which is conducted in conjunction with

the COH.

1. A unit-weighted average rent-to-value ratio is estimated for each market-value

class of one-unit tenant-occupied dwellings.

2. This ratio is multiplied by a midpoint housing value for the class to derive an

average rent per unit for each value class.

3. The average rent per unit for each value class is multiplied by the corresponding

number of owner-occupied units to derive imputed rent receipts for these units.

4. Rent receipts and owner-occupied units are summed across all value classes and

then the former is divided by the latter to derive an imputed average rent for owner-

occupied permanent-site homes.

The nonbenchmark annual estimates of owner-occupied contract rent per unit are

prepared by extrapolation using the product of (1) the CPI for owners’ equivalent rent,

which captures changes in the rental value of constant-quality owner-occupied

dwellings, and (2) the constant-dollar per-unit value of owner-occupied nonfarm

dwellings, which captures changes in the rental value that result from changes in the

average quality of these dwellings. The constant-dollar per-unit values are derived by

dividing the BEA estimates of constant-dollar net stocks by the corresponding unit

stock.

For all years, the rental value of the dwelling alone (or “space rent”) for owner-

occupied permanent-site homes is derived by multiplying the rent excluding utilities by

the number of owner-occupied units and then subtracting BEA’s estimate of current-cost

depreciation of major appliances.

For tenant-occupied manufactured homes, the estimates of rent per unit are

derived as rent (which may include utilities) plus separately paid utilities less average

utility payments. Benchmark estimates of average rent per unit are based on rental-

value- range and unit data from the COH. For owner-occupied manufactured homes,

gross rent per unit is estimated as the product of rent per unit of tenant-occupied units

and the ratio of the average number of rooms in owner-occupied units to those in tenant-

occupied units. For nonbenchmark years, average rent is interpolated and extrapolated

using median rent from AHS, or for non-AHS years, using the CPI for rent of primary

residence. Data on average utility payments are from RECS, interpolated and

extrapolated using the product of the number of units and of the CPI for gas (piped) and

electricity.

Current quarterly and monthly estimates

According to the SNA, “When well-organized markets for rented housing exist, the output of own-

account housing services can be valued using the prices of the same kind of services sold on the market…”

(SNA 2008: 6.117).

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-46

The quarterly and monthly current-dollar estimates are prepared by reﬂating the

estimates of real PCE for each type of dwelling using the CPI for rent of primary

residence for tenant-occupied dwellings and the CPI for owners’ equivalent rent of

primary residence for owner-occupied dwellings. The monthly estimates in real terms

are based on the number of units for each type of dwelling adjusted for changes in the

quality of the housing stock. Stocks of permanent-site homes are interpolated and

extrapolated from the annual estimates, using monthly Census Bureau data on housing

completions. The total stock of manufactured homes is estimated by interpolating and

extrapolating from the annual estimates, using monthly Census Bureau data on

shipments of manufactured homes (for the advance quarterly estimate, the shipments

data are available only for the first 2 months of the quarter). The distributions of the

permanent-site stock and of the manufactured home stock between owner-and tenant-

occupied units are based on recent trends. The unit estimates are adjusted for changes in

the quality of the housing stock based on historical relationships between average rental

values and the respective CPIs.

Quantity estimates

The estimates of the real rental value of tenant-occupied nonfarm dwellings are

derived by deflation: the CPI for rent of primary residence is used to deflate space rent,

and the CPI for major appliances is used to deflate depreciation at current-replacement

costs of major appliances and furnishings provided by property owners. The estimates of

the real rental value of owner-occupied nonfarm dwellings are derived by deflation using

the CPI for owners’ equivalent rent of primary residence.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-47

Financial service charges and fees

This PCE services component consists of commercial bank service charges on

deposit accounts, commercial bank and nondepository credit intermediation fees on

credit card accounts, and other financial service charges and fees.

Commercial bank service charges on deposit accounts

Benchmark estimates are based on Census Bureau’s Economic Census data on

fees for individual deposit account services (other than ATM and electronic transactions

fees) and fees for bundled deposit account services. Nonbenchmark annual estimates are

interpolated and extrapolated using data on total service charges on deposit accounts of

commercial banks from Statistics on Depository Institutions produced by the Federal

Deposit Insurance Corporation (FDIC). For the current quarterly estimates, the third

estimate is also based on the FDIC data, and the second and advance estimates are

judgmentally trended.

Commercial bank and nondepository credit intermediation fees on credit card accounts

Fees on credit card accounts consist of membership fees, cash advance fees, late

fees, over-limit fees, and other miscellaneous credit card fees.

The benchmark

estimates are equal to cardholder fees reported in the economic census times a consumer

share based on the noncommercial share of bank card purchases from the Nilson Report,

a credit-card industry newsletter. Nonbenchmark annual estimates of credit card fees are

interpolated and extrapolated using data on bank card dollar-volume data from

CardWeb.com Inc. The third quarterly estimate is extrapolated using CardWeb.com Inc.

data, and the advance and second estimates are judgmentally trended.

Other financial service charges and fees

This category consists of commercial bank other fee income, savings institution and

credit union charges and fees, activities related to credit intermediation charges and fees,

and postal money order and money transfer services fees.

Commercial bank other fee income consists of automated teller machine (ATM)

and other electronic transactions fees, consumer loan fees, and other fees. Benchmark

estimates of ATM and other electronic transactions fees are based on fees for individual

deposit accounts reported in the Economic Census. Benchmark estimates of fees on

unsecured consumer loans are also based on economic census data. Other fees are based

on data on safe deposit box rental charges reported in the BLS Consumer Expenditure

Survey. Nonbenchmark annual estimates are interpolated and extrapolated using FDIC

data on “additional noninterest income.”

Service charges and fees on credit card accounts do not include finance charges, which are included in

personal interest payments.

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5-48

Savings institution and credit union charges and fees consists of service charges

on deposit accounts, service charges and fees on credit card accounts, ATM and other

electronic transaction fees, and fees on unsecured consumer loans. The benchmark

estimates are based on economic census data. Service charges on deposit accounts and

ATM and other electronic transactions fees are based on fees for individual deposit

accounts, and consumer loan fees are based on fees for unsecured consumer loans.

Service charges and fees on credit card accounts equal cardholder fees times a consumer

share based on the non-commercial share of bank card purchases from the Nielsen

Report.

The nonbenchmark annual estimates of PCE for savings institutions are

interpolated and extrapolated using the sum of Office of Thrift Supervision (OTS) data

on nonmortgage fees and charges for OTS-regulated savings institutions and of FDIC

data on service charges on deposit accounts and income from fiduciary accounts of

FDIC-regulated savings institutions. For credit unions, the nonbenchmark annual

estimates are interpolated and extrapolated using data on fee income and other operating

income from the National Credit Union Administration.

Activities related to credit intermediation charges and fees consists of ATM and

other electronic transaction fees, automated clearing house (ACH) and other electronic

transaction fees, credit card charges and fees, and check cashing and other payment

product fees. The benchmark estimates are based on economic census data, including

payment product fees of commercial banks and other depository institutions. The

nonbenchmark annual estimates are interpolated and extrapolated using BLS Quarterly

Census of Employment and Wages data on other activities related to credit

intermediation wages and salaries.

For postal money order fees, benchmark and nonbenchmark annual estimates are

based on money order fees reported by the U.S. Postal Service, adjusted from a fiscal

year basis to a calendar year basis.

For money transfer services fees, benchmark and nonbenchmark annual estimates

are based on payment services revenue data from Form 10K annual reports filed by First

Data Corporation and Moneygram International with the Securities and Exchange

Commission. Revenue data are adjusted to total money transfers and then to transfers

originating in the United States based on information from the company reports, and

these revenues are then allocated almost entirely to consumers.

The current quarterly estimates of other financial service charges and fees of other

depository institutions are judgmentally trended.

The quantity estimates for all components of PCE for financial service charges and

fees are prepared by deflation, using the CPI for checking account and other bank services.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

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Securities commissions

This PCE services component consists of direct commissions on securities

transactions, of indirect commissions on securities transactions, and of mutual fund sales

charges.

Direct commissions

Direct commissions—those for which an explicit commission is charged—consist

of commissions on equities transactions executed on an exchange and of commissions

on all other securities transactions, including equities transactions executed on over-the-

counter (OTC) markets and transactions in debt securities.

The benchmark estimates of total commissions on equities and on debt securities

are based on data from the Census Bureau’s Economic Census. Total equities

commissions are allocated between exchange-traded equities and equities traded on OTC

markets using commissions data by market from Securities and Exchange Commission

(SEC) tabulations of Financial and Operational Combined Uniform Single (FOCUS)

Reports filed by broker-dealers. Then, commissions charged to other brokers from

FOCUS Report data are subtracted to derive commissions charged to the public.

Equities commissions charged to the public are allocated to persons using

estimates of shares traded by individuals and institutions and of cents-per-share

commission rates. Estimates of shares traded, which reflect the purchasing and selling

sides of share volume are derived as follows.

1. For registered exchanges, shares traded by the public equal total shares traded less

member trading.

a. For the New York Stock Exchange (NYSE), share volume and member purchases

and sales are reported by the exchange.

b. For other registered exchanges, share volume is reported by the SEC, and member

purchases and sales are estimated by applying the American Stock Exchange

member percentage to total purchases and sales.

2. For OTC markets, shares traded by the public equal public-to-public trading and

the public side of dealer-to-public transactions.

a. Public-to-public share volume is based on National Association of Securities

Dealers Automated Quotation (NASDAQ) data on electronic communication

networks.

b. Dealer-to-public trading volume is derived from total trading volume and

estimates of public-to-public and dealer-to-dealer volume. Total OTC volume is

reported by NASDAQ, and dealer-to-dealer volume is based on National Association

of Securities Dealers estimates of the share of total volume accounted for by these

transactions.

Debt securities consist of negotiable certificates of deposit, commercial paper, bankers acceptances, U.S.

Treasury bills, other money market instruments, corporate and trust notes and bonds, U.S.

government notes

and bonds, and state and local government notes and bonds.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-50

3. The shares of public trading accounted for by individuals on the NYSE, on other

registered exchanges, and on OTC markets were each initially based on Securities

Industry Association (SIA) reports and are now extrapolated by the household

shares of corporate equity holdings based on Federal Reserve Board’s Flow of

Funds data.

The estimates of cents-per-share commission rates on registered exchanges and on

OTC markets are based on total commissions, the institutional and individual

percentages of public-share volume, and the assumption that individual commission

rates are twice the institutional rates, based on an SEC survey of commission rates.

To the equities commissions charged to individuals are added commissions

charged to nonprofit institutions serving households (NPISHs). First, the share of total

commissions charged to all nonprofit institutions is estimated using flow of funds data

on corporate equity holdings. Then, the NPISH share of the nonprofit commissions is

estimated using IRS data on the NPISH share of securities investments of tax-exempt

organizations. The allocation of NPISH commissions between registered exchanges and

OTC markets is the same as that for individual commissions.

The benchmark estimates of commissions on debt transactions are derived as the

product of total commissions charged to domestic purchasers and of a consumer share

based on the percentage of marketable debt securities held by households from flow of

funds data.

For nonbenchmark years, equities commissions on registered exchanges are

extrapolated using FOCUS Report data on total commissions on equity transactions

executed on exchanges less commissions charged to other brokers. The allocation of

commissions charged to individuals and to NPISHs is based on shares traded by

individuals and institutions on registered exchanges and on an assumed ratio of

individual to institutional commission rates. Other direct commissions, which consist of

commissions on OTC equities transactions and on debt transactions, are extrapolated

using FOCUS report data on OTC commissions less commissions charged to other

brokers. The allocation to individuals is based on shares traded by individuals and

institutions on OTC markets and on the assumed ratio of individual to institutional

commission rates.

For the current quarterly estimates, FOCUS Report commissions data are used to

extrapolate the third estimate, and NYSE round lot and odd-lot share volume and

NASDAQ OTC share volume are used to extrapolate the second and advance estimates.

The estimates of real direct commissions on exchange-listed equities are prepared

by deflation, using the “PPI for brokerage services, exchange-listed equities.” Direct

commissions on OTC equities and on debt transactions are deflated using the “PPI for

brokerage services, all other securities.”

Indirect commissions

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Indirect commissions—those for which the commission is charged indirectly

through a dealer markup or “spread”

—comprise commissions on OTC equity

securities and other indirect commissions, which consist of gains from specialist

transactions in equities on registered exchanges and from brokering and dealing debt

securities and derivatives.

The benchmark estimates of total indirect commissions on equities, debt

securities, and derivatives are based on data from the economic census on net gains

(excluding interest income) in trading accounts for brokering and dealing securities. For

equities, the allocation of total indirect commissions to persons is made using the

personal share of equities holdings (including NPISHs and bank personal trusts and

estates). The personal share of equities holdings is based on averages of yearend

holdings from flow of funds data. Total PCE for indirect commissions on equities

transactions is allocated between OTC markets and registered exchanges using estimates

based on total shares sold and cents-per-share spreads.

•

For OTC markets, individual purchases from dealers are equal to total dealer sales to

the public less purchases by institutions. Total dealer sales to the public is derived by

subtracting dealer-to-dealer and public-to-public share volume from the total and

using a BEA assumption that one-half of the remaining dealer-to- public transactions

is accounted for by sales. The institutional share of OTC transactions is based on SIA

reports. Average cents-per-share spreads are from NASDAQ, extrapolated by the

“PPI for dealer transactions, market making in over-the-counter equities.”

•

For registered exchanges, the NYSE ratio of specialist sales to total purchases and

sales is applied to total purchases and sales on all registered exchanges to derive total

specialist sales. The individual share of specialist sales is based on SIA reports.

Average cents-per-share spreads are assumed to equal the volume- weighted spread

for NYSE specialists as reported by the exchange.

To indirect commissions charged to individuals are added commissions charged to

NPISHs, based on the nonprofit share of total corporate equity holdings from flow of

funds data applied to total indirect commissions and an allocation of nonprofit

commissions to NPISHs based on IRS data.

The benchmark estimates of indirect commissions on transactions in U.S.

government and agency securities, in municipal securities, and in corporate debt

securities are allocated to persons using the personal share of holdings (including

NPISHs and bank personal trusts and estates). The personal share of equities holdings is

based on averages of yearend holdings from flow of funds data. The allocation of

benchmark estimates of commissions on derivatives to persons is based on an assumed

Dealers who make markets in securities do not charge commissions; instead, they retain as compensation

the income resulting from acquiring securities at a price lower than the price at which the securities are

subsequently sold to their customers.

Derivatives consist of futures contracts, option contracts, forward contracts, swaps, and other derivative

contracts.

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5-52

15-percent share.

For nonbenchmark years, PCE for indirect commissions on OTC equities is

extrapolated by the product of OTC share volume (excluding matched volume) from

NASDAQ and of the “PPI for dealer transactions, market making in over-the-counter

equities.” PCE for other indirect commissions is estimated in three parts: specialists’

gains on equities trading on registered exchanges, gains on brokering and dealing debt

securities, and gains on brokering and dealing derivatives.

• Specialists’ gains are extrapolated by specialists’ sales from the NYSE.

• Gains on debt securities are estimated for U.S. government securities, for U.S.

government agency and government-sponsored enterprises securities, for state and

local government debt securities, for corporate debt securities, and for open-market

paper. In each case, total indirect commissions are extrapolated by the value of

trading and allocated to persons (including NPISHs) based on the share of each

type of security held by persons, based on flow of funds data. The source for U.S.

government and for agency securities is total primary dealer sales excluding other

brokers and dealers, from Federal Reserve Bank of New York (FRBNY) data. For

state and local government securities and for corporate debt securities, the value of

trading is from the Securities Industry and Financial Markets Association

(SIFMA). For open-market paper, the source is primary dealer volume with others

in corporate debt securities due in less than 1 year, from FRBNY data.

• Derivatives commissions are extrapolated in two parts: options and future and

forward contracts. Options commissions are extrapolated using SEC data on the

value of options trading. Commissions on futures and forward contracts are

extrapolated using futures contracts data from the Futures Industry Association.

The current quarterly estimates of indirect commissions of OTC equities

transactions are extrapolated using the value of OTC trading from NASDAQ. Other

indirect commissions are extrapolated using FRBNY data on dealer transactions with

others in U.S. government, federal agency, and government-sponsored enterprise

securities.

The estimates of real OTC equities commissions are prepared by deflation, using

the “PPI for dealer transactions, market-making in over-the-counter equities.” For other

indirect commissions, the “PPI for dealer transactions, debt securities, and all other

trading” is used as the deflator.

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5-53

Broker charges on mutual fund sales

The benchmark estimates of total broker charges on mutual fund sales are based

on economic census data. Charges for nonbenchmark years are interpolated and

extrapolated using data on revenue from the sale of investment company securities from

the FOCUS Report. Commissions are allocated to individuals, fiduciaries, and

nonprofits based on data on their respective shares of mutual fund assets from the

Investment Company Institute (ICI). For current quarterly estimates, the third estimate is

extrapolated using data on charges on the sale of investment company securities from

the FOCUS Report, and the second and advance estimates are extrapolated using data on

sales of mutual fund shares reported by the ICI. The estimates of real broker charges on

mutual fund sales are derived by quantity extrapolation, using an indicator equal to

mutual fund sales from the ICI deflated by the all-items CPI.

For a general description of the quantity extrapolation method, see the section “Estimates for detailed

components” in chapter 4.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-54

Financial services furnished without payment

Financial services furnished without payment includes depository institutions—

commercial banks, savings institutions, and credit unions—and regulated investment

companies (mutual funds), which provide services to persons without explicitly charging

for these services.

This component also includes pension plans—private pension plans

and publicly administered government employee retirement plans—which earn property

income (dividend and interest income) on plan reserves that have been contributed

directly by employers and employees and are held on behalf of beneficiaries to be paid

out to them as annuity or lump-sum distributions of income in the future.

In the

NIPAs, the value of these types of services is imputed to PCE as financial services

furnished without payment in order to make PCE invariant to whether the charges are

implicit or explicit.

In the NIPAs, imputations are made for the value of the services (such as check

clearing, recordkeeping, and investment services) that are provided by depository

institutions.

For commercial banks and other depository institutions, services to

borrowers are estimated as the difference between the rate of return on loans and a

riskless “reference rate”—measured as the average rate earned by banks on U.S.

government and agency securities

—times the value of loans that involve direct

customer contact.

Services to depositors are estimated as the difference between the

reference rate and the rate paid on deposits times the value of deposits that involve direct

customer contact. These estimates are based on the premise that rather than pay explicit

fees, borrowers accept a higher interest rate, and depositors a lower rate, than they would

otherwise. The differences in interest rates are used to infer the implicit value of the

services that the banks are providing to their customers. Interest flows are adjusted

because a portion of the money paid as interest by borrowers represents a payment for

these services and because the interest forgone by depositors reflects the value of the

services they receive.

The value of these services to government is imputed to government consumption expenditures and that

to foreigners is imputed to exports of services. For business, these services are considered intermediate

consumption and cancel out in the consolidation of the production account of the business sector.

Rental income is also earned by pension plans, but this amount is assumed to be small.

See Brent R. Moulton and Eugene P. Seskin, “Preview of the 2003 Comprehensive Revision of the

National Income and Product Accounts,” Survey 83 (June 2003): 23–27; see also Dennis J. Fixler, Marshall

B. Reinsdorf, and George M. Smith, “Measuring the Services of Commercial Banks: Changes in Concepts

and Methods,” Survey 83 (September 2003): 33–44.

The calculation of the reference rate excludes mortgage-backed securities.

As part of the 2013 comprehensive update of the NIPAs, the estimates of the output of commercial

banks were improved (1) by limiting the set of assets and liabilities included in the calculations to mainly

loans and deposits, (2) by removing from borrower services an estimate of expected losses in principal as a

result of borrower default, and (3) by refining the computation of the reference rate to reduce the volatility

in borrower and depositor services. For more information, see Kyle K. Hood, “

Measuring the Services of

Commercial Banks in the National Income and Product Accounts: Changes in Concepts and Methods in

the 2013 Comprehensive Revision,” Survey 93 (February 2013): 8–19. As part of the 2018 comprehensive

update, the same improvements were applied to the estimates for other depository institutions. See Jason

W. Chute, Stephanie H. McCulla, and Shelly Smith, “Preview of the 2018 Comprehensive Update of the

National Income and Product Accounts: Changes in Methods, Definitions, and Presentations,” Survey 98

(April 2018).

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5-55

Imputations are also made for the value of the services that are provided by

regulated investment companies (RICs) to their shareholders. These imputed service

charges are equal to the operating expenses of the RICs.

The imputations for these services are recorded in the Personal Income and Outlay

Account of the summary NIPAs as follows.

Personal interest income (and personal

income) is raised by an amount equal to the imputed service charges for the depositor

and investor services. In personal outlays, PCE is raised by the sum of the imputed

service charges for depositor and investor services and for borrower services, and

personal interest payments is reduced by the imputed service charges for borrower

services, since a portion of the interest payment is assumed to represent a fee for

unpriced borrower services. Thus, personal outlays is raised by the same amount as

personal interest income, and personal savings is not affected by the imputations.

In the NIPAs, pension plans are regarded as charging participants an implicit fee

that is equal to the plans’ administrative expenses for the package of imputed services

provided. The property income of pension plans is recorded in personal income as

monetary interest, as imputed interest on unfunded liabilities, and as dividends, and the

difference between this property income and the imputed fees is included in personal

savings. The benefit payments associated with pension plans are treated as transfers from

the pension subsector (included in the financial corporate sector) to the personal sector.

In effect, the NIPA treatment performs a timing change so that the property income that

has been accrued to the plan beneficiaries is recorded as if it were actually disbursed to

them in the current period.

Commercial banks, savings institutions, and credit unions

The value of implicit commercial bank and other depository institutions ‘services

to depositors is based on average deposit balances and on a “user-cost price” that is

calculated as the difference between the reference rate and the interest rate paid on

deposits. Similarly, the value of commercial bank and other depository institutions’

services to borrowers is based on average loan balances and on a user-cost price that is

calculated as the difference between the interest rate earned on loans and the reference

rate. The estimates of deposits and of loan balances, of interest paid and received on

deposits and loans, and of the reference rate for commercial bank and savings

institutions are based on data from the Federal Financial Institutions Examination

Council’s (FFIEC) Call Reports. For credit unions, the measures are based on data from

the National Credit Union Association’s (NCUA) Call Report Form 5300.

For a discussion of the summary NIPAs, see “Chapter 2: Fundamental Concepts” in this handbook.

As part of the 2013 comprehensive update of the NIPAs, the treatment of pension plans was improved

by recording the transactions of defined benefit pension plans on an accrual basis and by recognizing the

costs of unfunded liabilities. For more information, see “Preview of the 2013 Comprehensive Revision of

the National Income and Product Accounts,” Survey 93 (March 2013): 21–25.

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5-56

For each type of deposit and for loans

in domestic offices of U.S. chartered

banks, an average rate of interest is derived from the average balance and interest

income or expense, and the user-cost price is calculated as the difference between the

average interest rate and the reference rate. The value of the implicit service is calculated

by applying the user-cost price to the average deposit or loan balance, with an

adjustment to include balances in U.S. offices of foreign banks. Imputed services to

depositors are equal to the sum of services to all types of deposit accounts—demand

deposit accounts (noninterest-bearing checkable deposits) and interest-bearing accounts

(checkable deposit accounts, savings accounts, and time deposit accounts)—except

intrabank deposits.

The share of total imputed demand-deposit services that is allocated to persons is

based on the share of demand deposits held by persons. This share was initially based on

a since-discontinued Federal Reserve Board (FRB) survey of demand deposit ownership.

The personal share of demand deposits is no longer available, so the original estimate

from the FRB survey is extrapolated using the household share of transactions deposits

(which include interest-bearing checkable deposits as well as demand deposits) as

follows. FFIEC data on total transactions deposits in domestic offices are adjusted to

exclude deposits held by commercial banks and other depository institutions, and

deposits held by individuals, partnerships, and corporations are calculated as a

percentage of the adjusted total. FRB Financial Accounts of the U.S. data on the

distribution of checkable accounts among households and types of business are then

used to determine the household share of the adjusted transactions deposits.

For interest-bearing deposits, there are no data on the share of these deposits held

by persons, so the allocation of implicit services to persons is based on the household

share of interest-bearing deposits excluding checkable deposits (which include money

market deposit accounts, other savings deposits, and time deposits) derived from FFIEC

and flow of funds data. The FFIEC total of these deposits is adjusted to exclude holdings

of foreign governments and official institutions, and the percentage of deposits held by

individuals, partnerships, and corporations is calculated. Flow of funds data on the

distribution of savings and time deposits among households and types of businesses are

then used to determine the household share of the adjusted deposits total.

The imputed borrower services are allocated to persons based on FFIEC data on

the share of outstanding loans that is accounted for by credit card and other consumer

loans.

Annual quantity estimates. The annual estimates of real PCE for commercial bank

services are derived using a BLS banking output index that is based on volume measures

for the deposit, loan, and trust functions of commercial banks. There are component

indexes for U.S.-owned banks and for U.S. offices of foreign banks, each of which use

employment weights that are based on data from the Federal Reserve Banks’ Functional

Cost Analysis Report.

Also includes capital leases.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-57

•

For U.S.-owned banks, the BLS deposit index consists of a demand deposit

component, based on the number of checks processed and the number of electronic

transactions; a time deposit component, based on estimated deposits and withdrawals;

and an ATM component, based on ATM and point-of-sale volume. The BLS loan

index is based on the number of real estate, consumer, and commercial loans

outstanding and on the volume of credit card transactions.

•

For U.S. offices of foreign banks, the indexes for deposits and for loans are based on

the number of deposit accounts and loans, which are estimated from the total value

loans reported in the FRB Share Data for the U.S. Offices of Foreign Banking

Organizations report and on average deposit and loan sizes.

The U.S.-owned and foreign-owned banking output indexes are combined using

revenue data from the Census Bureau’s Economic Census that are extrapolated by assets

and aggregated using a Tornqvist aggregation procedure.

The BLS banking output index is used to extrapolate the total value of priced and

unpriced banking services from the base-year value. From the extrapolated value, the

real-dollar value of explicit service charges and fees (see the section “Financial service

charges and fees”) is subtracted to obtain the real-dollar value of unpriced banking

services, which is then allocated to persons in the same proportion as the current-dollar

estimates. For the most recent year, the BLS banking output index is extrapolated using

available data on deposit, loan, and trust activity.

The annual estimates of the real implicit services provided by other depository

institutions are derived by deflation, using the PCE implicit price deflator for services

furnished without payment by commercial banks.

Current quarterly estimates. For the current-dollar estimates, the third quarterly

estimate for commercial bank and other depository institutions’ services is derived by

extrapolation, using FFIEC data on deposit and loan values, on interest paid and

received, and on the reference rate. The second and advance estimates are judgmentally

trended. The current quarterly estimates of real commercial bank services are

judgmentally trended. The current quarterly estimates of real other depository institution

services are prepared by deflation, using the implicit price deflator for financial services

furnished without payment for commercial bank services.

Regulated investment companies

The total value of imputed services of RICs equals their operating expenses.

These expenses are measured as “total deductions” from IRS income statement data on

open-end investment funds, plus securities commissions and “services furnished without

payment” by other financial intermediaries. Securities commissions include direct

commissions paid on equities and options transactions and indirect commissions paid on

equities, debt securities, and options transactions. For the most recent year, “total

deductions” are extrapolated using data on mutual fund total net assets from the

Investment Company Institute (ICI).

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5-58

For all years, direct commissions paid by RICs are estimated as a share of total

institutional commissions paid by U.S. residents. The methodology used to derive the

estimates of total direct commissions charged to the public and of individual and

institutional commissions is described in the section “Securities commissions.”

Commissions paid by foreign residents, which are included in institutional commissions,

are estimated by applying the foreign share of the value of total purchases and sales of

U.S. equities to total commissions charged to the public. The value of foreign residents’

transactions in U.S. equities is from BEA’s International Transactions Accounts data;

the value of total purchases and sales is from the New York Stock Exchange, the

National Association of Securities Dealers Automated Quotation System for over-the-

counter markets, and the Securities and Exchange Commission for other registered

exchanges. The RIC share of institutional commissions paid by U.S. residents is equal to

equity holdings of mutual funds as a percentage of total equity holdings of domestic

institutions, based on flow of funds data.

The share of total indirect commissions that is accounted for by RICs is estimated

separately for equities, U.S. treasury securities, U.S. government agency and

government-sponsored enterprise securities, municipal securities, corporate debt

securities, and options transactions. The derivation of total indirect commissions for all

types of securities is described in “Securities commissions.” For each type of security

except options, the allocation to RICs is based on the RIC share of total marketable

securities averaged from yearend flow of funds data. The allocation of indirect

commissions on options transactions assumes the same distribution as that for the total

on debt and equity securities net transactions.

The allocation to persons of RIC services is based on flow of funds data on the

share of mutual fund assets that are held by the household sector.

“Services furnished without payment” by other financial intermediaries comprise

the implicit depositor services of depository institutions. These services are allocated to

RICs in proportion to the RIC shares of deposits, which are derived by the same method

as described above for commercial banks and other depository institutions.

Annual quantity estimates. The annual estimates of real implicit RIC services are

derived by deflation. A BEA input cost index—based on several PPI components and on

the average hourly earnings for the portfolio management sector from BLS Current

Employment Statistics (CES)—is used as the deflator.

Current quarterly estimates. The current-dollar quarterly estimates of implicit

RIC services are extrapolated using a 3-month moving average of mutual fund total net

assets from the ICI. The estimates in real terms are prepared by deflation, using a BEA

input cost index that is based on several PPI components and on monthly average hourly

earnings data for portfolio management from BLS Current Employment Statistics

(CES).

Pension plans

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For private pension plans, the annual estimates of PCE are calculated as the sum

of reported expenses of private defined benefit pension plans and of securities

commissions paid by these plans. Reported expenses are based on BEA tabulations of

annual report data (Form 5500) from the Department of Labor’s Employee Benefits

Security Administration. Reported expenses are not available for the most recent 2 years,

so the estimates for those years are judgmentally trended. Securities commissions

include both direct and indirect commissions on equity and debt securities and on

options and are estimated as described in “Securities commissions.” These commissions

are allocated to pension plans using flow of funds data on the distribution of securities

holdings.

For publicly administered government employee retirement plans, the annual

estimates of PCE are calculated as the sum of the administrative expenses of the federal

government plans and the administrative expenses and indirect securities commissions

of the state and local government plans. The estimates of the administrative expenses for

the federal plans—which consist of federal civilian and military retirement funds, the

Thrift Savings Plan, and the Uniformed Services Retiree Health Care Fund—are based

primarily on data from the U.S. Department of Treasury’s Monthly Treasury Statement.

The estimates of the administrative expenses for the state and local government

employee retirement plans are based on retirement systems data from the Census

Bureau’s annual Survey of Government Finances. The estimates of indirect commissions

on securities transactions are described in “Securities commissions” and are allocated to

state and local government pension funds using flow of funds data.

For the most-recent-year, the expenses of pension plans are extrapolated using

BLS Quarterly Census of Employment and Wages (QCEW) data on pension fund

industry wages and salaries. The current quarterly estimates are judgmentally trended.

The estimates of real PCE for pension plans are prepared by deflation, using a

BEA composite index of input prices. For this index, compensation costs are based on

average industry wages and salaries from the QCEW, and purchased goods and services

costs are based on a combination of price indexes from BLS and BEA. For the current

quarterly estimates of compensation costs, the QCEW data are extrapolated using CES

average hourly earnings.

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Life insurance

Life insurance carriers—legal reserve life insurance companies, fraternal benefit

societies, and mutual savings banks—provide services that combine elements of both

insurance and saving. These institutions earn property income (dividend, interest, and

rental income) on insurance reserves that have been contributed directly by, or are held

for the benefit of, policy holders and that will be paid out to the beneficiaries as annuity

or lump-sum distributions of income in the future.

In the NIPAs, life insurance carriers are regarded as charging policyholders an

imputed fee that is equal to the institutions’ operating expenses for the package of

services provided. The imputations for the value of these services are recorded in the

Personal Income and Outlay Account of the summary NIPAs as follows.

•

The imputed fees are treated as personal outlays and are recorded as “life

insurance” in PCE.

•

The property income of life insurance carriers is recorded as “imputed interest

received from life insurance carriers” in personal interest income. The underwriting

income of life insurance carriers (premiums less benefits) is treated as a transfer

payment within the personal sector; such intra-sectoral transactions are not recorded

in the NIPAs.

•

The savings of life insurance carriers is consolidated with that of the personal

sector. Personal saving is raised by the amount that the property income of these

institutions exceeds the imputed fees that are added to PCE.

In effect, the NIPA treatment performs a timing change so that the property

income that has been accrued to policy holders is properly recorded as if it were actually

disbursed to them in the current period. In the absence of these imputations, the

investment returns and the increases in life insurance reserves would be included in

business and government income and saving rather than in personal income and saving.

For legal reserve life insurance carriers, operating expenses consist of all

expenses related to life insurance and pension activities, including the following:

financial investment expenses, profits of stock life insurance companies, direct and

indirect commissions paid on securities transactions, and imputed services purchased

from commercial banks. Expenses related to life insurance and pension activities are

reported on annual statements filed with state insurance commissioners; expenses related

to real estate activities and to accident and health insurance are not included. For stock

life insurance companies, profits are included because they belong to shareholders in the

companies; however, profits of mutual insurance companies are not included because

they belong to policyholders.

For domestic legal reserve companies, the benchmark and nonbenchmark annual

estimates of operating expenses, except for the most recent year, are based on aggregates

prepared by A.M. Best Company. The following items in the A.M. Best Company data

For a discussion of the summary NIPAs, see “Chapter 2: Fundamental Concepts” in this handbook.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-61

are considered current expenses: commissions paid on premiums and annuity

considerations; general insurance expenses; investment expenses; insurance taxes,

licenses, and fees; and other miscellaneous expenses. Commissions paid on premiums

and annuity considerations, which measure only commissions on direct insurance

business, are adjusted to a measure of total net commissions paid by adding

commissions paid on reinsurance assumed and by subtracting commissions received on

reinsurance ceded.

Because the annual statements of domestic companies consolidate their activities

worldwide, the expenses of their operations in foreign countries must be subtracted in

order to derive expenses chargeable to U.S. residents. In addition, the expenses of

foreign life insurance companies operating in the United States must be added.

Benchmark estimates of the expenses of domestic companies abroad are estimated using

the relationship between domestic premium receipts and total premium receipts from the

American Council of Life Insurers’ (ACLI) Life Insurance Fact Book. Benchmark

estimates of the expenses of foreign companies operating in the United States are

estimated by calculating the ratio of U.S. residents’ premium payments to Canadian

companies to their payments to U.S. companies, based on ACLI Fact Book, and

applying this ratio to the expenses of domestic companies chargeable to U.S. residents.

For nonbenchmark years, the net of these geographic adjustments is extrapolated by the

operating expenses of domestic legal reserve companies.

Estimates of the profits of stock life insurance companies are based on IRS

tabulations of corporate tax returns. Direct and imputed commissions on securities

transactions are derived as described in the section “Securities commissions” and are

allocated to life insurers using holdings data by type of security from the Federal

Reserve Board’s Flow of Funds data. The estimates of imputed interest paid by

commercial banks are described in the section “Services furnished without payment by

financial intermediaries” and are also allocated to life insurers using flow of funds data.

For fraternal beneﬁt societies and mutual savings banks, data on current expenses

are not available. PCE for these institutions is estimated as premiums less beneﬁts and

less dividends paid to members and beneﬁciaries. For the fraternal beneﬁt societies,

estimates are based on data from the National Fraternal Congress of America. For

mutual savings banks, estimates are based on data from the ACLI fact book. In recent

years, the estimates have been judgmentally trended.

For the most recent year, data on life insurance industry wages and salaries from

the BLS Quarterly Census of Employment and Wages (QCEW) are used to extrapolate

PCE for life insurance. For the current quarterly estimates, BLS Current Employment

Statistics (CES) data on earnings are used as the extrapolator.

The estimates of real PCE for life insurance carriers are prepared by deflation,

using a BEA composite index of input prices. For this index, compensation costs are

based on CES average hourly earnings data, and purchased goods and services costs are

based on a combination of price indexes from BLS and BEA.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-62

Property and casualty insurance

Property and casualty insurance comprises three PCE services components: net

household insurance, private workers’ compensation, and net motor vehicle and other

transportation insurance. Household insurance consists of the following lines of

insurance: homeowners’ multiple peril, farm owners’ multiple peril, inland marine,

and earthquake. Private workers’ compensation consists of insurance provided by

commercial companies and of self-insurance by employers. Motor vehicle insurance

consists of private passenger auto liability and private passenger auto physical damage.

Property and casualty insurance companies provide three types of financial

services to policyholders:

•

risk-pooling services, which enable consumers and others exposed to property and

casualty losses to reduce their individual risk;

•

loss-related services—such as loss settlements, risk surveys, and loss prevention

plans; and

•

intermediation services, whereby policyholders earn property income (interest,

dividend, and rental income) on the investment of funds in “technical reserves,”

which consist of premiums paid by policyholders in advance of coverage periods

and of casualty losses incurred by insurers but not yet disbursed to policyholders.

In the NIPAs, the three types of property and casualty insurance services are each

measured as total premiums less “normal” losses incurred. Total premiums consist of

premiums earned plus “premium supplements” less dividends payable to policyholders.

Premiums are paid directly by policyholders and are earned by the insurers during the risk

period covered. Premium supplements equal the expected investment income on technical

reserves, including capital gains. According to the international System of National

Accounts (SNA), “the insurance company invests the premium, and the property income

is an extra source of funds to meet any claim due. The property income represents income

foregone by the client and so is treated as an implicit supplement to the actual

premium.”

The NIPA measure of insurance services recognizes that in most periods, the

insurance premiums received and the investment income earned provide the funds needed

by insurance companies for a normal, or expected, level of insurance claims and

insurance services and for additions to reserves. In setting their premiums, these

companies do not yet know the actual loss in the period; thus, an estimate of normal

losses—that is, the losses that insurers expect to pay—rather than actual losses is used in

calculating the value of insurance services.

Expected losses are estimated using a model

Inland marine insurance consists of coverage of goods transported by land and of transportable business

property and personal property (such as bicycles, furs, and jewelry).

Technical reserves are funds on which policyholders have a legal claim, so they are recognized as assets

belonging to them. Insurers also invest “own funds,” which belong to the companies’ stockholders.

SNA 2008: 6.184.

See Brent R. Moulton and Eugene P. Seskin, “Preview of the 2003 Comprehensive Revision of the

National Income and Product Accounts,” Survey 83 (June 2003): 19–23; see also Baoline Chen and Dennis

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-63

based on the past pattern of claims payable by the insurer. Under this treatment, actual

losses less normal losses, referred to as “net insurance settlements,” reflect the net value

of the transfer-like flows between the policyholders and the insurance companies.

Net

insurance settlements consist of disaster-related losses and of other net insurance

settlements.

In the absence of the imputations for premium supplements and normal losses,

property and casualty insurance services would be measured as direct premiums earned

less actual losses incurred and dividends to policyholders. However, policyholders pay a

smaller premium than they would in the absence of investment income, so premiums

alone do not fully account for the cost of insurance services. In addition, the use of

actual losses would result in a volatile measure of insurance services because of the large

swings in insurance payments that result from catastrophic losses. This treatment is

consistent with that recommended in the SNA, in which non-life insurance output is

measured as “total premiums earned, plus premium supplements, less adjusted claims

incurred,” which are defined as the claims that the insurance company expects to pay.

The treatment of property and casualty insurance services provided to persons is

recorded in the Personal Income and Outlay Account of the summary NIPAs as

follows.

•

The insurance services are treated as personal outlays and are recorded in PCE

according to the type of insurance provided.

•

The expected investment income on technical reserves (premium supplements) of

the insurance categories in PCE is classified as imputed interest and included in

personal interest income (a part of personal income receipts on assets in personal

income).

•

PCE for the premium supplements and the associated imputed personal interest

income are both raised by the same amount, so personal saving is not affected.

•

Private workers’ compensation premiums, entirely paid by employers and

including self-insurance, are included in employer contributions for employee

pension and insurance funds (a part of supplements to wages and salaries in

personal income).

•

Net insurance settlements other than disaster-related losses are included in “other

current transfer receipts from business (net)” (a part of personal current transfer

J. Fixler, “Measuring the Services of Property-Casualty Insurance in the NIPAs,” Survey 83 (October

2003): 10–26.

These flows do not meet the strict definition of a “transfer”—that is, a payment for which nothing is

provided in return—because the payment is made as part of a contract between the policyholder and the

insurance company. However, these flows are similar to transfers in that they reflect the part of the

payments that are not associated with the purchase of insurance services, so they are included in business

transfer payments in the NIPAs.

In the 2009 comprehensive update of the NIPAs, BEA changed the treatment of disasters to better

reflect the distinctions between current transactions, capital transactions, and events that directly affect

balance sheets and to bring the NIPAs in line with the recently updated SNA. See Eugene P. Seskin and

Shelly Smith, “

Preview of the 2009 Comprehensive Revision of the NIPAs: Changes in Definitions and

Presentations,” Survey 89 (March 2009): 11–15.

SNA 2008

: 6.185–6.189.

For a discussion of the summary NIPAs, see “Chapter 2: Fundamental Concepts” in this handbook.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-64

receipts in personal income).

Annual estimates

The annual estimates of property and casualty insurance except for the most

recent year are derived using data from Best’s Aggregate and Averages:

Property/Casualty by A.M. Best Company on direct premiums earned, direct losses

incurred, net investment income, and dividends to policyholders. For each line of

insurance included in PCE, normal loss ratios are derived for each year as the

exponentially weighted moving average of the actual loss ratios—that is, the ratio of

actual direct losses incurred to direct premiums earned—of past years. For insurance lines

affected by catastrophic losses, the years for which loss ratios are affected are treated as

missing observations in the calculation of the normal loss ratios. The catastrophic loss is

then computed as the difference between the actual loss ratio and the normal loss ratio

applied to direct premiums earned, and the catastrophic loss is spread forward equally

over 20 years. Normal losses for each year are derived as the normal loss ratio multiplied

by direct premiums earned. Similarly, the expected investment income ratio for each year

is derived as the exponentially weighted moving average of the investment income to

premiums ratios of past years.

Premium supplements for each year are then derived as

the expected investment income ratio multiplied by the direct premiums earned.

Once data for premium supplements and normal losses are derived, these data and

the A.M. Best data on direct premiums and dividends paid are used to derive total

insurance services for each line of insurance. Because the A.M. Best data cover the

consolidated worldwide operations of U.S. insurance companies, insurance operations in

foreign countries must be excluded from total insurance services; this adjustment is

accomplished by using A.M. Best data on direct business in foreign locations, by line of

insurance. Data on total imports of property and casualty insurance are from BEA’s

International Transactions Accounts; the total is separated out by line based on the

distribution of property and casualty insurance reflected in BEA’s Benchmark Input-

Output (I-O) Accounts for the United States, which are released approximately every 5

years. Distributions by line of insurance are derived by straight-line interpolation for the

years between I-O benchmarks and are held constant for the years following the most

recent benchmark. These adjustments to output measures based on A.M. Best data

provide estimates of insurance to U.S. residents by line of insurance.

For each line of insurance included in PCE, the portion accounted for by personal

use is estimated as follows:

•

For homeowners’ multiple peril insurance, the portion that covers renters and

condominium owners is estimated using data from the National Association of

Disaster-related losses are treated as capital transfers.

For detail on the estimation of expected loss ratios and expected income ratios, see Chen and Fixler

(2003).

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-65

Insurance Commissioners on premiums written as a share of total homeowners’

multiple peril premiums; this portion is allocated entirely to PCE. The remaining

portion of homeowners’ insurance, which covers owner-occupied (non-

condominium) dwellings and which accounts for about 94 percent of total coverage,

is allocated to PCE using information on coverage limitations for household

contents relative to dwelling values. This information indicates that household

contents coverage is about 20 percent of the value of dwelling coverage.

•

This 20-percent ratio is also used in the PCE allocation of farm owners’ multiple

peril and earthquake insurance.

•

Insurance on personal property is estimated to account for 27 percent of the total

for inland marine insurance, based on information from the Inland Marine

Underwriters Association and the American Association of Insurance Services.

•

For private workers’ compensation, all of domestic supply is attributed to persons, to

which are added estimates of self-insured premiums and benefits paid by employers.

•

For motor vehicle insurance, the services covering business use of household

owned-vehicles is excluded, based on the business portion of mixed-use

household motor vehicles.

Most-recent-year and current-quarterly estimates

A.M. Best data are released with a 9-month lag; therefore, for the most recent

year, estimates of direct premiums by line of insurance are extrapolated using A.M. Best

estimates of net premiums in written contracts from its Best’s Review & Preview report

on property and casualty insurers published in January of each year. Premium

supplements and dividends are extrapolated based on forecasts of investment income

growth rates. Normal losses are extrapolated using the growth in the combined ratios for

business lines and for personal lines. The current quarterly estimates are judgmentally

trended.

Quantity estimates

For household insurance, total premiums and benefits are deflated separately,

using the PPI for homeowners’ insurance. For private workers’ compensation, premiums

and benefits are deflated separately, using the PPI for worker’s compensation insurance.

For motor vehicle insurance, premiums and benefits are deflated separately, using the

PPI for private passenger auto insurance.

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-66

Nonprofit institutions serving households

In the NIPAs, nonprofit institutions serving households (NPISHs), which have

tax-exempt status, are treated as part of the personal sector of the economy. Because

NPISHs produce services that are not generally sold at market prices, the value of these

services is measured as the costs incurred in producing them.

In PCE, the value of a household purchase of a service that is provided by a

NPISH consists of the price paid by the household or on behalf of the household for that

service plus the value added by the NPISH that is not included in the price. For example,

the value of the educational services provided to a student by a university consists of the

tuition fee paid by the household to the university and of the additional services that are

funded by sources other than tuition fees (such as by the returns to an endowment fund).

NPISHs are accounted for in PCE by their “final consumption expenditures,”

which equal their gross output less sales to other sectors of the economy (such as sales of

education services to employers) and less sales to households. The gross output of

NPISHs is equal to their current operating expenses less sales to households that are not

related to the NPISHs’ primary activity (such as room and board charges by colleges and

universities). Operating expenses consist of compensation costs, purchased goods and

services except for capital outlays, and the imputed rental value of structures and

equipment owned by NPISHs. Capital outlays consist of the value of purchased

buildings and of equipment and software as well as the value of investment goods such

as software that are produced directly by the NPISHs. The imputed rental value of

structures and of equipment and software owned by NPISHs equals the sum of interest

paid, depreciation at current replacement cost, and property taxes. Sales of services by

NPISHs to households are subtracted from the NPISH expenses because these sales are

accounted for in household consumption expenditures in PCE.

In the PCE tables, NPISH final expenditures are not distributed among the

individual categories but are shown as a separate entry. NPISH sales of services to

households are accounted for in the following PCE categories:

•

Health

o Outpatient services

o Hospitals

o Nursing homes

•

Recreation

o Membership clubs and participant sports centers

o Performing arts

o Museums and libraries

o Other recreation services

•

Education

o Higher education

o Nursery, elementary, and secondary schools

o Commercial and vocational schools

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-67

o Research

•

Social services

o Child care

o Individual and family services

o Vocational rehabilitation services

o Community food and housing services

o Homes for the elderly

o Residential mental health and substance abuse

o Other residential care facilities

•

Religious organizations

•

Foundations and grantmaking and giving organizations

•

Social advocacy organizations

•

Civic and social organizations

•

Professional, labor, political, and similar organizations and legal services

Benchmark and annual estimates

The benchmark estimates of gross output and of sales for the following types of

NPISHs are based on data on expenses and receipts from the Census Bureau’s Economic

Census: health, recreation, nursery schools, commercial and vocational schools,

research, social services, foundations and grantmaking and giving organizations, social

advocacy organizations, civic and social organizations, and professional and similar

organizations and legal services. The expense data on depreciation is adjusted to a

replacement-cost basis using BEA estimates of current- and historical-cost depreciation.

The receipts data provide sales of both primary services and of unrelated and secondary

sales. The annual estimates for all of these types of NPISHs are based on data on

expenses and receipts from the Census Bureau’s Service Annual Survey.

The benchmark and annual estimates for higher education are based on expenses

and receipts data from the National Center for Education Statistics (NCES), adjusted

from a school-year basis to a calendar-year basis. Expenses include instruction, public

service, academic support, student services, institutional support, and operation and

maintenance of plant, less sales and services of educational activities. The expense data

on depreciation are adjusted to a replacement-cost basis using BEA estimates of current-

and historical-cost depreciation. For the second most recent year, expense data for the

first of the 2 school years needed for adjustment to a calendar-year basis are available,

and expenses for the second year are extrapolated using BLS Current Employment

Statistics (CES) employment data times the CPI for all items. For the most recent year,

calendar-year expenses are extrapolated using CES employment times the all-items CPI.

The benchmark estimates of elementary and secondary schools expenses are

based on NCES estimates of total expenditures adjusted from a school-year basis to a

calendar-year basis and adjusted to exclude capital outlays, scholarships and fellowships,

and unrelated sales and to include in-kind wages and depreciation valued at current

replacement cost. The annual estimates are extrapolated using the NCES expenditures

estimates, adjusted from a school-year basis to a calendar year basis. The benchmark

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-68

estimates of tuition and fee sales to households are based on the application of tuition-to-

expense ratios from the National Catholic Education Association. The annual estimates

are extrapolated using a tuition-revenue indicator equal to enrollment times average

tuition rates from the NCES when available; enrollment is extrapolated for the most

recent years using Census Bureau estimates of the population aged 5 to 17, and average

tuition is extrapolated using the CPI for elementary and high school tuition and fees.

The benchmark estimates for religious organizations expenses and sales are based

on a study of church finances by the Independent Sector, an advocacy group for

nonprofit organizations. The annual estimates are extrapolated using contributions data

from the National Council of Churches’ Yearbook of American and Canadian Churches

through 2010. For 2011 forward, the annual estimates are extrapolated using Giving

USA’s Annual Report of Philanthropy. The estimates for the most recent year are

extrapolated using QCEW wage data.

The benchmark estimates for labor organizations expenses are based on total

industry wages from the QCEW, to which is applied a ratio of expenses to wages and

salaries from IRS data on labor, agriculture, and horticultural organizations. A ratio of

membership dues to wages and salaries from the IRS data is applied to QCEW wages to

derive sales of labor organizations. The annual estimates are extrapolated using QCEW

wage data.

The benchmark and annual estimates of political organization expenditures are

based on data on contributions for Federal elections from the Federal Election

Commission, on independent expenditures for national office data from the Campaign

Finance Institute, and on state and local election spending from the National Institute for

Money in State Politics.

Current quarterly estimates

For most categories of NPISHs, the third current quarterly estimate is based on

expenses and receipts data from the Census Bureau’s Quarterly Services Report. The

second and advance estimates are based primarily on CES data on employment, hours,

and earnings: for categories other than education, a wages and salaries indicator equal to

total employment times average weekly hours times average hourly earnings is used; for

education categories, CES total employment times the all-items CPI is used.

Quantity estimates

The estimates of the real gross output of NPISHs are prepared by deflation using

input cost indexes. These indexes are weighted averages of indexes of compensation

costs and indexes of the prices of purchased goods and services. The weights for the

indexes are based on BEA’s Benchmark Input-Output estimates. For compensation

costs, the indexes are based on QCEW data on average wages by industry, except for the

indexes for hospitals and nursing homes, which are based on the BLS Employment Cost

Index. The indexes for the current quarterly estimates for all categories except education

CHAPTER 5: PERSONAL CONSUMPTION EXPENDITURES

5-69

are extrapolated using CES data on average hourly earnings; the indexes for education

categories are extrapolated using the CPI for education services. For purchased materials

and services, PPIs and CPIs are used for the associated expenses, and for expenses that

cannot be associated with specific price indexes, the all-items less food and energy CPI

is used.