i

U.S. DEPARTMENT OF COMMERCE

Donald L. Evans, Secretary

ECONOMICS AND STATISTICS ADMINISTRATION

Kathleen B. Cooper, Under Secretary for Economic Affairs

BUREAU OF ECONOMIC ANALYSIS

J. Steven Landefeld, Director

Rosemary D. Marcuss, Deputy Director

SEPTEMBER 2003

 ECONOMICS

 AND STATISTICS

 ADMINISTRATION

www.bea.gov
ii

Suggested Citation

U.S. Department of Commerce. Bureau of Economic Analysis. Fixed Assets and Consumer

Durable Goods in the United States, 1925–99. Washington, DC: U.S. Government Printing

Office, September, 2003.
iii

This publication was written by Shelby W. Herman,

Arnold J. Katz, Leonard J. Loebach, and Stephanie H.

McCulla with assistance from Michael D. Glenn. The

estimates of fixed assets and consumer durables were

prepared by the National Income and Wealth Division

and the Government Division of BEA. Specifically, the

estimates for the private sector and the chain-type estimates for the private and government sectors were prepared by Michael D. Glenn, Phyllis Barnes, Kurt Kunze,

Leonard J. Loebach, and Dennis R. Weikel, under the

direction of Shelby W. Herman. The estimates for the

government sector were prepared by Charles S. Robinson

and Jennifer A. Bennett, under the direction of D. Timothy Dobbs. Paul R. Lally, Chief of the Investment Branch,

and Randal T. Matsunaga oversaw preparation of the

published volume. Barbara M. Fraumeni, BEA’s Chief

Economist, recommended the depreciation profiles that

were used.

Overall supervision was provided by Carol Moylan,

Chief of the National Income and Wealth Division; by

Karl Galbraith, former Chief of the Government Division; by Brooks B. Robinson, Chief of the Government

Division; and by Brent R. Moulton, Associate Director

for National Economic Accounts. Kristina Maze edited

the volume and W. Ronnie Foster of Publication Services in the Communications Division coordinated the

production of this publication and designed the cover.

Duane Hackmann prepared the tables for typesetting.

Acknowledgments
v

Contents

Acknowledgments................................................................................................................................................. iii

Introduction .......................................................................................................................................................... M–1

Uses of the Estimates....................................................................................................................................... M–1

Relationship to the National Income and Product Accounts..................................................................... M–2

Other stock measures ..................................................................................................................................... M–3

Concepts and Methodologies .............................................................................................................................. M–5

Classification conventions ............................................................................................................................. M–5

Overview of the estimating methodology .................................................................................................... M–6

Perpetual inventory method ................................................................................................................... M–6

Investment................................................................................................................................................ M–6

Depreciation ............................................................................................................................................ M–6

Basic Formulas ............................................................................................................................................... M–7

Valuation ........................................................................................................................................................ M–8

Current-cost valuation ........................................................................................................................... M–8

Real-cost valuation .................................................................................................................................. M–9

Quality change ......................................................................................................................................... M–9

Historical-cost valuation ........................................................................................................................ M–10

Relationship among estimates ................................................................................................................ M–10

Adjustments for catastrophic losses and obsolescence ....................................................................................... M–10

Derivation of Investment Estimates ................................................................................................................... M–13

Investment in Private Fixed Assets ................................................................................................................ M–13

Sources...................................................................................................................................................... M–13

New nonresidential investment .............................................................................................................. M–16

 Investment controls by industry..................................................................................................... M–17

 Investment controls by type of asset ............................................................................................... M–23

 Adjustment of industry controls .................................................................................................... M–24

Distribution by type of asset and industry ............................................................................................ M–24

New residential investment ..................................................................................................................... M–25

Net purchases of used assets .................................................................................................................... M–25

 Nonresidential assets ........................................................................................................................ M–25

 Residential assets ............................................................................................................................... M–26

Investment by legal form of organization ............................................................................................. M–26

 Nonresidential investment ............................................................................................................... M–26

 Residential investment...................................................................................................................... M–27

Government Fixed Assets .............................................................................................................................. M–27

Consumer Durable Goods ............................................................................................................................ M–27
vi

Derivation of Depreciation Estimates ................................................................................................................ M–29

Service lives ..................................................................................................................................................... M–30

Private equipment ................................................................................................................................... M–32

Private nonresidential structures ........................................................................................................... M–33

Residential structures..................................................................................................................................... M–33

Government-owned fixed assets ............................................................................................................. M–33

Durable goods owned by consumers ..................................................................................................... M–33

Retirement patterns ....................................................................................................................................... M–33

Derivation of Estimates of Privately-owned Automobiles ............................................................................... M–35

Glossary and Guide to the Tables........................................................................................................................ M–37

 Glossary .......................................................................................................................................................... M–37

 Guide to the Tables ......................................................................................................................................... M–38

List of Tables

1. Fixed Assets and Consumer Durable Goods

1.1. Current-Cost Net Stock of Fixed Assets and Consumer Durable Goods ........................................... 1

1.2. Chain-Type Quantity Indexes for Net Stock of Fixed Assets and Consumer Durable Goods .......... 3

1.3. Current-Cost Depreciation of Fixed Assets and Consumer Durable Goods ..................................... 5

1.4. Chain-Type Quantity Indexes for Depreciation of Fixed Assets and Consumer Durable Goods .... 7

1.5. Historical-Cost Investment in Fixed Assets and Consumer Durable Goods ..................................... 9

1.6. Chain-Type Quantity Indexes for Investment in Fixed Assets and Consumer Durable Goods ........ 12

1.7. Current-Cost Average Age at Yearend of Fixed Assets and Consumer Durable Goods .................... 15

2. Private Fixed Assets by Type

2.1. Current-Cost Net Stock of Private Fixed Assets; Equipment, Software, and Structures .................. 17

2.2. Chain-Type Quantity Indexes for Net Stock of Private Fixed Assets; Equipment, Software,

and Structures.......................................................................................................................................... 23

2.3. Historical-Cost Net Stock of Private Fixed Assets; Equipment, Software, and Structures ............... 29

2.4. Current-Cost Depreciation of Private Fixed Assets; Equipment, Software, and Structures............. 35

2.5. Chain-Type Quantity Indexes for Depreciation of Private Fixed Assets; Equipment, Software,

and Structures.......................................................................................................................................... 41

2.6. Historical-Cost Depreciation of Private Fixed Assets; Equipment, Software, and Structures ......... 47

2.7. Historical-Cost Investment in Private Fixed Assets; Equipment, Software, and Structures............. 53

2.8. Chain-Type Quantity Indexes for Investment in Private Fixed Assets; Equipment, Software,

and Structures.......................................................................................................................................... 61

2.9. Current-Cost Average Age at Yearend of Private Fixed Assets; Equipment, Software,

and Structures.......................................................................................................................................... 69

2.10. Historical-Cost Average Age at Yearend of Private Fixed Assets; Equipment, Software,

and Structures.......................................................................................................................................... 75

3. Private Fixed Assets by Industry

3.1ES. Current-Cost Net Stock of Private Fixed Assets ............................................................................... 81

3.1E. Current-Cost Net Stock of Private Equipment and Software ........................................................... 85

3.1S. Current-Cost Net Stock of Private Structures .................................................................................... 89
vii

3.2ES. Chain-Type Quantity Indexes for Net Stock of Private Fixed Assets .............................................. 93

3.2E. Chain-Type Quantity Indexes for Net Stock of Private Equipment and Software .......................... 97

3.2S. Chain-Type Quantity Indexes for Net Stock of Private Structures ................................................... 101

3.3ES. Historical-Cost Net Stock of Private Fixed Assets ............................................................................ 105

3.3E. Historical-Cost Net Stock of Private Equipment and Software ........................................................ 109

3.3S. Historical-Cost Net Stock of Private Structures ................................................................................. 113

3.4ES. Current-Cost Depreciation of Private Fixed Assets ......................................................................... 117

3.4E. Current-Cost Depreciation of Private Equipment and Software ..................................................... 121

3.4S. Current-Cost Depreciation of Private Structures .............................................................................. 125

3.5ES. Chain-Type Quantity Indexes for Depreciation of Private Fixed Assets ........................................ 129

3.5E. Chain-Type Quantity Indexes for Depreciation of Private Equipment and Software .................... 133

3.5S. Chain-Type Quantity Indexes for Depreciation of Private Structures ............................................. 137

3.6ES. Historical-Cost Depreciation of Private Fixed Assets ...................................................................... 141

3.6E. Historical-Cost Depreciation of Private Equipment and Software .................................................. 145

3.6S. Historical-Cost Depreciation of Private Structures ........................................................................... 149

3.7ES. Historical-Cost Investment in Private Fixed Assets ......................................................................... 153

3.7E. Historical-Cost Investment in Private Equipment and Software ..................................................... 157

3.7S. Historical-Cost Investment in Private Structures .............................................................................. 161

3.8ES. Chain-Type Quantity Indexes for Investment in Private Fixed Assets ............................................ 165

3.8E. Chain-Type Quantity Indexes for Investment in Private Equipment and Software ........................ 169

3.8S. Chain-Type Quantity Indexes for Investment in Private Structures ................................................. 173

3.9ES. Current-Cost Average Age at Yearend of Private Fixed Assets ........................................................ 177

3.9E. Current-Cost Average Age at Yearend of Private Equipment and Software .................................... 181

3.9S. Current-Cost Average Age at Yearend of Private Structures ............................................................. 185

3.10ES. Historical-Cost Average Age at Yearend of Private Fixed Assets ................................................... 189

3.10E. Historical-Cost Average Age at Yearend of Private Equipment and Software ............................... 193

3.10S. Historical-Cost Average Age at Yearend of Private Structures ........................................................ 197

4. Nonresidential Fixed Assets by Industry Group and Legal Form of Organization

4.1. Current-Cost Net Stock of Nonresidential Fixed Assets ...................................................................... 201

4.2. Chain-Type Quantity Indexes for Net Stock of Nonresidential Fixed Assets ..................................... 207

4.3. Historical-Cost Net Stock of Nonresidential Fixed Assets................................................................... 213

4.4. Current-Cost Depreciation of Nonresidential Fixed Assets ................................................................ 219

4.5. Chain-Type Quantity Indexes for Depreciation of Nonresidential Fixed Assets ............................... 225

4.6. Historical-Cost Depreciation of Nonresidential Fixed Assets ............................................................. 231

4.7. Historical-Cost Investment in Nonresidential Fixed Assets ................................................................ 237

4.8. Chain-Type Quantity Indexes for Investment in Nonresidential Fixed Assets ................................... 245

4.9. Current-Cost Average Age at Yearend of Nonresidential Fixed Assets ............................................... 253

4.10. Historical-Cost Average Age at Yearend of Nonresidential Fixed Assets .......................................... 259

5. Residential Fixed Assets by Type of Owner, Legal Form of Organization, Industry, and Tenure Group

5.1. Current-Cost Net Stock of Residential Fixed Assets ............................................................................. 265

5.2. Chain-Type Quantity Indexes for Net Stock of Residential Fixed Assets ............................................ 267

5.3. Historical-Cost Net Stock of Residential Fixed Assets ......................................................................... 269

5.4. Current-Cost Depreciation of Residential Fixed Assets ....................................................................... 271

5.5. Chain-Type Quantity Indexes for Depreciation of Residential Fixed Assets ...................................... 273

5.6. Historical-Cost Depreciation of Residential Fixed Assets ................................................................... 275

5.7. Historical-Cost Investment in Residential Fixed Assets ....................................................................... 277

5.8. Chain-Type Quantity Indexes for Investment in Residential Fixed Assets ......................................... 280
viii

5.9. Current-Cost Average Age at Yearend of Residential Fixed Assets ...................................................... 283

5.10. Historical-Cost Average Age at Yearend of Residential Fixed Assets ................................................ 285

6. Private Fixed Assets by Industry Group and Legal Form of Organization

6.1. Current-Cost Net Stock of Private Fixed Assets ................................................................................... 287

6.2. Chain-Type Quantity Indexes for Net Stock of Private Fixed Assets .................................................. 289

6.3. Historical-Cost Net Stock of Private Fixed Assets ................................................................................ 291

6.4. Current-Cost Depreciation of Private Fixed Assets ............................................................................. 293

6.5. Chain-Type Quantity Indexes for Depreciation of Private Fixed Assets............................................. 295

6.6. Historical-Cost Depreciation of Private Fixed Assets .......................................................................... 297

6.7. Historical-Cost Investment in Private Fixed Assets ............................................................................. 299

6.8. Chain-Type Quantity Indexes for Investment in Private Fixed Assets ................................................ 302

6.9. Current-Cost Average Age at Yearend of Private Fixed Assets ............................................................ 305

6.10. Historical-Cost Average Age at Yearend of Private Fixed .................................................................. 307

7. Government Fixed Assets

7.1. Current-Cost Net Stock of Government Fixed Assets .......................................................................... 311

7.2. Chain-Type Quantity Indexes for Net Stock of Government Fixed Assets ......................................... 317

7.3. Current-Cost Depreciation of Government Fixed Assets .................................................................... 323

7.4. Chain-Type Quantity Indexes for Depreciation of Government Fixed Assets ................................... 329

7.5. Historical-Cost Investment in Government Fixed Assets .................................................................... 335

7.6. Chain-Type Quantity Indexes for Investment in Government Fixed Assets ...................................... 343

7.7. Current-Cost Average Age at Yearend of Government Fixed Assets ................................................... 351

8. Consumer Durable Goods

8.1. Current-Cost Net Stock of Consumer Durable Goods ........................................................................ 357

8.2. Chain-Type Quantity Indexes for Net Stock of Consumer Durable Goods ....................................... 359

8.3. Historical-Cost Net Stock of Consumer Durable Goods .................................................................... 361

8.4. Current-Cost Depreciation of Consumer Durable Goods .................................................................. 363

8.5. Chain-Type Quantity Indexes for Depreciation of Consumer Durable Goods ................................. 365

8.6. Historical-Cost Depreciation of Consumer Durable Goods .............................................................. 367

8.7. Historical-Cost Investment in Consumer Durable Goods .................................................................. 369

8.8. Chain-Type Quantity Indexes for Investment in Consumer Durable Goods .................................... 372

8.9. Current-Cost Average Age at Yearend of Consumer Durable Goods ................................................. 375

8.10. Historical-Cost Average Age at Yearend of Consumer Durable Goods ........................................... 377

9. Chained Dollar Tables

9.1. Real Net Stock of Fixed Assets and Consumer Durable Goods ........................................................... 379

9.2. Real Depreciation of Fixed Assets and Consumer Durable Goods ..................................................... 379

9.3. Real Investment in Fixed Assets and Consumer Durable Goods ........................................................ 379
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–1

This publication presents estimates prepared by the

Bureau of Economic Analysis (BEA) of the stocks and

depreciation of fixed assets and consumer durable

goods and of the investment flows used to derive them.

Specifically, it presents estimates for the United States

of the stocks of private and government fixed assets

(durable equipment, software, and structures) and

consumer durables for 1925–99. It also presents the

underlying investment expenditures for most assets for

1901–99.

The first chapter discusses the conceptual and statistical considerations underlying BEA’s estimates of fixed

assets and consumer durables. The second and third

chapters explain the calculation of the investment

flows and the depreciation estimates that are used with

the perpetual inventory method to derive estimates of

the net stocks of fixed assets and consumer durables.

The fourth chapter explains the derivation of net

stocks of privately owned automobiles, which are not

based on the perpetual inventory method. The final

chapter provides a glossary and a detailed guide to

types of estimates available in each table—that is, the

category of ownership or sector available for different

time periods and at different valuations. The balance

of the publication comprises the tables themselves.

The estimates incorporate the definitional and statistical improvements introduced in the 1999 comprehensive revision of the national income and product

accounts (NIPAs), including the recognition of business and government expenditures for software as investment, a new pattern of depreciation for personal

computers, and a new service life for highways.1

 BEA

also prepares estimates of stocks of U.S. direct investment abroad and of foreign direct investment in the

United States that are consistent with the estimates

presented here; these are published annually in the July

issue of the SURVEY OF CURRENT BUSINESS.

1. The new depreciation patterns are discussed in Shelby W. Herman,

“Fixed Assets and Consumer Durables,” Survey of Current Business 80,

(April 2000): 19–20. Revisions to the investment data are discussed in

Eugene Seskin, “Improved Estimates of the National Income and Product

Accounts for 1959–98: Results of the Comprehensive Revision,” Survey 79,

(December 1999): 15–43. Results of the 1999 comprehensive revision of the

NIPAs are presented in U.S. Department of Commerce, Bureau of Economic Analysis, National Income and Product Accounts of the United States,

1929–97, 2 vols. (Washington, D.C: U.S. Government Printing Office, September 2001).

The estimates in this publication supersede those

published in the preceding edition of this publication

and in the Survey prior to September 2000.2

 (Abbreviated time series that reflect the revisions made to

NIPAs for the previous 3 years are generally published

in the September issues of the Survey in the following

year; they are made available on the Web site at about

the same time.)

Uses of the Estimates

BEA’s estimates of the net stocks and depreciation of

fixed assets and consumer durables are used in other

sets of statistics, such as the Flow-of-Funds Accounts

prepared by the Federal Reserve Board, and in studies

of national income, product, and wealth. For instance,

the estimates of consumer durable goods presented in

this volume have been used in preparing alternative estimates of personal savings.3

 Studies of asset valuation

based on “Tobin’s-Q ratio” often use BEA’s measures of

capital stock as the denominator; BEA uses the estimates of produced assets presented in this volume in

its calculation of Q ratios as well as in its calculation of

the rate of return for domestic nonfinancial corporations.4

 The estimates have also been used in international comparisons of profitability.

The depreciation estimates, in the form of consumption of fixed capital (CFC), are also an integral

part of the NIPAs. Specifically, CFC is a component of

gross domestic income (GDI), which measures output

as the costs incurred and the incomes earned in the

production of GDP and is therefore the equivalent of

GDP on the income side of the National Income and

Product Account. As a cost incurred in the production of GDP, CFC reflects the use of private and

2. See Fixed Reproducible Tangible Wealth in the United States, 1925–94,

(Washington, D.C: U.S. Government Printing Office, August 1999) and

Eugene P. Seskin and David F. Sullivan, “Annual Revision of the National

Income and Product Accounts: Annual Estimates, 1997–1999 and Quarterly Estimates, 1997:I–2000:I,” Survey 80 (August 2000): 6–33.

3. See Maria G. Perozek and Marshall B. Reinsdorf, “Alternative Measures

of Personal Saving,” SURVEY 82, (April 2002): 13–24.

4. Property income’s rate of return to capital is calculated by BEA as the

ratio of property income of domestic nonfinancial corporations—that is,

their profits from current production—to the value of produced assets,

which is the current-cost value of the net stock of equipment and software

and of structures, and the replacement-cost value of inventories. See Dan

Larkins, “Note on the Profitability of Domestic Nonfinancial Corporations,

1960–2001,” SURVEY 82, (September 2002): 17–20.

Introduction
M–2 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

government fixed assets located in the United States,

and is defined as the decline in the value of the stock of

assets due to wear and tear, obsolescence, accidental

damage, and aging.5 CFC is used in the context of measuring sustainable income and product: It is deducted

from GDP and GDI to derive net domestic product

and net domestic income—rough measures of the level

of consumption that can be maintained while leaving

capital assets intact. Similarly, CFC is deducted from

the appropriate NIPA gross investment flows to obtain

net investment in fixed assets for the total economy, for

private business, and for government. These measures

of net investment are rough indicators of whether the

corresponding capital stocks have been maintained intact.

Additionally, the current-cost depreciation estimates for private fixed assets are used to derive the

NIPA estimates of capital consumption adjustment

(CCAdj), which in turn are used to estimate NIPA estimates of corporate profits and the income of other

types of business.6

Relationship to the National Income and 

Product Accounts

The estimates presented in this publication are part of

BEA’s work on measuring the wealth of the Nation.

Fixed assets are produced assets that are used repeatedly, or continuously, in processes of production for

more than one year. (Produced assets are nonfinancial

assets that have come into existence as outputs from a

production process.) The acquisition of fixed assets by

private business is presented in the NIPAs as part of

gross private domestic investment. The acquisition of

fixed assets by government is presented as part of government consumption expenditures and gross investment. Consumer durable goods are tangible

commodities purchased by consumers that can be used

repeatedly and continuously over a period of three or

5. For military facilities and U.S. embassies abroad, the locations of assets

are worldwide.

6. For corporations and nonfarm sole proprietorships and partnerships,

the CCAdj is the difference between tax-return-based capital consumption

estimates and the CFC. The CCAdj restates the tax-return-based measures

to be consistent with the NIPA concept of profits from current production.

For farm sole proprietorships and partnerships and for other private business, the CCAdj is the difference between two capital consumption measures valued on the basis of BEA’s depreciation schedules—one at historical

cost and the other at current cost. (The industry depreciation estimates in

this publication are not appropriate for deriving industry estimates of the

CCAdj for use in the NIPAs because the tax-return-based NIPA estimates of

business income and of depreciation are compiled on a company basis,

while the depreciation estimates associated with the stock estimates are

compiled on an establishment basis.)

Table 8.15 in the NIPAs presents the CCAdj by legal form of organization,

and the corresponding estimates of CFC are shown in table 8.14.The estimates of CFC for nonprofit institutions serving households that appear in

table 8.14 are also recorded as part of personal consumption expenditures. 

more years. Purchases of consumer durable goods by

persons are presented in the NIPAs as part of personal

consumption expenditures. Another part of BEA’s

work on measuring wealth is estimates of inventories

owned by private business. The change in private inventories is presented in the NIPAs as part of gross private domestic investment; estimates of the stocks of

private inventories also appear in selected NIPA tables.7

Estimates of depreciation for private business and

government presented in this publication are generally

the same as the CFC estimates presented as a component of GDI in the NIPAs. For private business, the two

are identical. However, the adjustments made to general government capital for catastrophic losses are not

included in NIPA CFC because general government

output is measured by adding up costs including CFC;

the inclusion of these losses would cause government

output to increase.8

 Except during war times, these differences are minor and the terms are used synonymously in this publication.9

 The NIPA CFC estimates

exclude the depreciation of consumer durables, because purchases of consumer durables are not treated

as investment in the NIPAs.

Changes in the stock of fixed assets and private inventories are presented together in NIPA table 5.16 to

provide an integrated analysis of the changes in the net

stock of produced assets (excluding consumer durables)—that is, fixed assets and private inventories—

from opening to closing balance sheets. The table fully

accounts for changes in the net stock of produced assets excluding consumer durables by showing the

sources of change—investment in fixed assets and in

inventories, stock reconciliation adjustments, depreciation, catastrophic losses, and nominal and real holding gains—and how each of these factors affects the

annual change in the net stock of produced assets valued at current cost.

7. Estimates of the stock of private inventories appear in tables 5.12 and

5.13 in National Income and Product Accounts of the United States, 1929–97,

for 1947–97, and in the same tables in the August issues of the Survey for

subsequent years. Current estimates of the stock of private inventories

appear in the “Selected NIPA Tables” in each issue of the Survey. As available data are insufficient for preparing estimates of investment in inventories by government, the change in government inventories is treated as part

of government consumption expenditures.

8. Note that in the NIPAs, the services of general government fixed assets

are estimated to be equal to CFC. This does not provide an estimate of the

full value of these services because the net return on the underlying assets is

not included in this measure. See Robert P. Parker and Jack E. Triplett, “Preview of the Comprehensive Revision of the National Income and Product

Accounts: Recognition of the Government Investment and Incorporation

of a New Methodology for Calculating Depreciation,” Survey 75 (September 1995): 36.

9. See Shelby W. Herman, “Fixed Assets and Consumer Durables,” SURVEY,

80 (April 2000): 17–30.
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–3

Other stock measures

Alternative measures of the Nation’s capital stock or of

the services that it provides are estimated by other government agencies. The Bureau of Labor Statistics

(BLS) estimates a capital services index, and corresponding productive capital stock, that is used as a

measure of capital input in the estimation of multifactor productivity.10 The measure of capital services is

designed to measure the flow of services provided by

capital assets in the production process, similar to the

flow of labor hours. The BLS is not able to use a direct

measure of these services because companies own,

rather than rent, most of the capital assets that they

use. Instead, the BLS estimates the capital service flow

from historical data on investment, from estimates of

the rates of deterioration and depreciation of capital,

and from income data of firms utilizing capital. Although BLS uses formulas for deterioration that are

not strictly consistent with formulas used by BEA for

depreciation, the investment, income, and service-life

data used by BLS are roughly similar to the estimates

presented by BEA, resulting in depreciation rates that

are generally consistent with BEA’s estimates.11

The Office of Management and Budget (OMB), as

part of its annual federal budget presentations to the

President, prepares estimates of federally-financed

capital stocks. These estimates are described by OMB

10. For those fixed assets depreciated with a geometric rate, there is no

difference between the wealth stock and the productive stock; however, BLS

productive stocks are different from BEA’s wealth stocks, as they use a different depreciation pattern. For example, the BLS productive stocks for

each type of asset are based on estimates of how capital service flows of various vintages “deteriorate” as the asset ages. These measures are then aggregated into indexes of capital inputs using weights based on the implicit

rental prices for each type of asset. These capital input indexes are used for

productivity studies, such as those conducted by the BLS. Capital input

indexes constructed in a similar way are used in studies by Edward F. Denison, John W. Kendrick, and Dale W. Jorgenson. For an explanation of the

difference between productive capital stock and wealth stock, see Jack E.

Triplett, “Depreciation in Production Analysis and in Income and Wealth

Accounts: Resolution of an Old Debate,” Economic Inquiry 34 (January

1996): 93–115.

11. See Edwin R. Dean and Michael J. Harper, “The BLS Productivity

Measurement Program,” in New Developments in Productivity Analysis,

Charles R. Hulten, Edwin R. Dean, and Michael J. Harper (eds.), (Chicago

and London, University of Chicago Press, 2001): 55–84.

as “very rough measures over time” of public physical

capital, research and development, and education financed by the Federal Government.12 The OMB estimates differ from those presented here both in terms of

coverage and underlying source data. Specifically,

while OMB’s estimates of public physical capital are

similar to BEA’s estimates of government fixed assets,

OMB also presents estimates of research and development capital and education capital. Likewise, while the

coverage of OMB’s estimates of “direct federal capital”

is similar to that of the estimates of Federal Government stocks in this publication, OMB’s estimates of

“federally financed physical capital” also include “capital financed by Federal grants,” such as highway construction financed by Federal grants-in-aid. Even

where the coverage is the same, OMB’s estimates differ

somewhat from BEA’s estimates because of differences

in sources and methods. For instance, OMB uses its

own fiscal-year historical investment data, which differ

somewhat from the investment data underlying BEA’s

estimates. Additionally, the OMB estimates are prepared at a more aggregated level of detail. For example,

defense equipment is a single category in the OMB estimates, while BEA’s estimates of defense equipment

consist of about 80 sub-categories.

12. Office of Management and Budget, “Federal Investment Spending and

Capital Budgeting,” Analytical Perspectives, Budget of the United States Government, Fiscal Year 2003 (Washington, D.C.: U.S. Government Printing

Office, 2002).

Data Availability

Aggregate estimates—valued at current cost, historical cost, and real cost (chained dollars)—and chaintype quantity indexes of net stocks, depreciation, and

investment are available on BEA’s Web site at

www.bea.gov. Detailed estimates—valued at current

cost, historical cost, and real-cost—and chain-type

quantity indexes, by industry and by type of asset, are

also available on these Web sites. All of these estimates are also available on CD–ROM (NCN–0314)

upon request. Please call the BEA Order Desk at

1–800–704–0415.
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–5

Wealth, in the broadest sense, consists of assets that

provide the capacity to produce output and income.

The components of the Nation’s wealth that are measured in this publication are fixed assets (equipment,

software, and structures, including owner-occupied

housing) owned by private business and nonprofit institutions or by governments, and durable goods

owned by consumers.13

BEA’s featured measure of the nation’s fixed nonfinancial wealth is the net stock of fixed assets and consumer durables. Conceptually, the net stock estimates

represent the value remaining in the capital stock after

depreciating the assets using BEA’s assumed depreciation patterns.14

Depreciation is defined as the decline in the value of

the stock of assets due to wear and tear, obsolescence,

accidental damage, and aging. For most types of assets,

BEA’s estimates of depreciation are based on geometric

depreciation patterns, which are supported by empirical studies of the prices of used equipment and structures in resale markets.15

In addition to estimates of net stocks and depreciation and the associated investment flows, this volume

provides estimates of the average age of the assets remaining in stock after being depreciated. The average

age is derived as the weighted average of the ages of all

depreciated investment in the stock as of yearend. The

13. Some wealth studies have also included human capital and land. For

example, see John W. Kendrick, The Formation and Stocks of Total Capital

(New York, NY: Columbia University Press, for the National Bureau of Economic Research, 1976) and Robert Eisner, The Total Incomes System of

Accounts (Chicago, IL: The University of Chicago Press, 1989). 

14. One of the improvements to BEA’s wealth estimates made in the 1995

comprehensive revision of the NIPAs involves the use of geometric depreciation rates derived from empirical studies instead of the use of the straightline method. With the previous methodology, all assets were fully depreciated at the end of their (finite) services lives. This method of depreciation

allowed BEA to prepare two other “wealth” measures—gross stocks, which

is the value of the stock of fixed assets and consumer durables before the

deduction of depreciation, and “discards,” which is the gross value of the

investment that is retired. BEA no longer produces estimates of these two

measures because, in using geometric depreciation rates, at least some

assets in each vintage of the stock have infinite service lives and are never

fully depreciated. For a more complete discussion of these improvements,

see Barbara M. Fraumeni, “The Measurement of Depreciation in the U.S.

National Income and Product Accounts, Survey 77 (July 1997): 7–23, and

Arnold J. Katz and Shelby Herman, “Improved Estimates of Fixed Reproducible Tangible Wealth, 1929–95,” Survey 77 (May 1997): 69–89.

weight for each age is based on the proportion of its

value as part of the total net stock.

Classification conventions

The estimates in this publication are classified by

owner. In general, data limitations require the assumption that assets remain, throughout their lives, in the

stock of the sector, industry, or legal form of organization that originally purchased them. However, the estimates do reflect net purchases of used assets among

sectors for certain types of assets where data are available, including used autos sold by private business to

consumers, exported used equipment, government

surplus assets sold to private business, privately-owned

public utilities purchased by government, and farm

housing shifted to nonfarm use.16

Fixed assets held under operating leases are recorded in the stock of the lessor (owner) rather than in

that of the lessee (user) in order to be consistent with

the NIPA measures of product and income by industry.

Assets held under other leases (that is, capital leases)

are recorded in the stock of the lessee because the lessee

has effective ownership of them.17

For private fixed assets, estimates by industry are

classified according to the 1987 Standard Industrial

Classification (SIC), which groups establishments into

industries on the basis of their principal product or

15. The basis for BEA’s methodology is described in Barbara M. Fraumeni, “The Measurement of Depreciation in the U.S. National Income and

Product Accounts,” SURVEY 77 (July 1997): 7–23. The geometric rates are

based on studies by Hulten and Wykoff. See for example Frank C. Wykoff

and Charles R. Hulten, “Tax and Economic Depreciation of the U.S. Capital

Stock: A First Step,” Washington D.C.: U.S. Department of the Treasury,

Office of Tax Analysis, July 1979. In comparison, the BLS productive stocks

for each type of asset are based on estimates of how capital service flows of

various vintages “deteriorate” as the asset ages. These measures are then

aggregated into indexes of capital inputs using weights based on the

implicit rental prices for each type of asset. These capital input indexes are

used for productivity studies, such as those conducted by the BLS. Capital

input indexes constructed in a similar way are used in studies by Edward F.

Denison, John W. Kendrick, and Dale W. Jorgenson.

16. Net purchases of used assets are valued at acquisition cost less accumulated depreciation.

17. Operating leases are chiefly distinguished from capital leases in that

the net present value of the payments during the entire lease period is generally less than the cost of the asset. Estimates of net stocks that classify

leased assets in the industry of the user may be preferable, but the data necessary to derive such estimates are not available.

Concepts and Methodologies
M–6 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

service.18 These industry estimates are for establishments rather than companies. An establishment is an

economic unit, generally at a single physical location,

where business is conducted or where services or industrial operations are performed. A company consists

of one or more establishments owned by the same legal

entity or group of affiliated entities. Most source data

are collected at the establishment level. Where source

data are collected at the company level, those companies are classified into a single SIC industry based on

the principal SIC industry of all their establishments.

Because large companies often own establishments

that are classified in different SIC industries, the industrial distributions of investment, fixed assets, and capital consumption for establishments could be

significantly different from the analogous industrial

distributions for companies.

For residential assets, each dwelling is considered to

be an establishment: Farm dwellings owned by farm

operators are classified in the farms industry, and all

other dwellings are classified in the real estate industry.

Overview of the estimating methodology

There are two basic methods for measuring net stocks.

The physical inventory method applies independently

estimated prices to a direct count of the number of

physical units of each type of asset. The perpetual inventory method cumulates past investment flows to indirectly estimate the value of the stock. (To simplify the

exposition, in this publication the terms “investment”

or “fixed investment” denote any addition to the net

stocks of fixed assets and consumer durables.) The

physical inventory method is more direct, but is used

only for autos because they are the only type of asset

for which detailed data on the prices and number of

units of used assets in the stock of each vintage is available (from registration data). For all other assets, the

perpetual inventory method is used.

Perpetual inventory method. Estimates of net

stocks and depreciation are generally calculated at the

type-of-asset level of detail. For net stocks of private

fixed assets, the level of detail is generally the same as

that presented in NIPA tables 5.7, 5.9, and 5.15 on private fixed investment. For consumer durable goods, it

generally is the same as that presented in NIPA table

2.7 on consumer durable purchases. For net stocks of

government fixed assets, the type-of-asset level of de18. BEA’s industry estimates of fixed assets published before 1992 were

classified according to the 1972 SIC. For a detailed presentation of the 1987

SIC revisions, see Executive Office of the President, Office of Management

and Budget, Standard Industrial Classification Manual, 1987 (Washington,

D.C.: U.S. Government Printing Office, 1987). With the next comprehensive revision of the NIPAs, these industry estimates will be classified according to the North American Industry Classification System (NAICS).

tail is greater than that published in the NIPA tables.

For each type of good, the perpetual inventory

method calculates the net stock in each year as the

cumulative value of gross investment through that

year—including both new investment and net purchases of used assets—less the cumulative value of depreciation through that year. In general, the

calculations are performed at the type-of-asset level of

detail. For current- and real-cost estimates, these detailed estimates are initially constructed in constantdollar terms and reweighted and aggregated using the

appropriate prices as described in the section on “Valuation” below. For historical-cost estimates, the detailed estimates are constructed in current-dollar terms

and aggregates are obtained by directly summing the

detailed estimates.

Investment. The estimates of investment underlying the estimates of net stocks are developed to be conceptually and statistically consistent with the NIPA

estimates of investment as well as with the classifications of the SIC. To ensure this consistency, BEA derives its estimates of investment to meet three

requirements: First, for each asset, new investment

summed across all industries equals the NIPA estimate

of total investment in that asset. Second, industries are

classified on an establishment basis. Finally, assets are

classified in the industry that purchases them.

The estimates of investment in new assets and of net

purchases of used assets are derived from a combination of NIPA data and industry data. These data are

reconciled to be consistent with NIPA totals and modified to be consistent with establishment-based industry classifications and ownership. These estimates are

described in detail in the chapter on “Derivation of Investment Estimates.”

Depreciation. BEA assumes most assets have depreciation patterns that decline geometrically over time.

For any given year, the constant-dollar depreciation

charge on an existing asset is obtained by multiplying

the depreciation charge in the preceding year by one

minus the annual depreciation rate.19 BEA’s geometric

depreciation rates are derived by dividing declining

balance rates by service lives, as illustrated in the equations on page M–7. Declining-balance rates are multiples of the comparable rate of depreciation that would

be obtained for the first period of an asset’s life using

the straight-line method. Thus, when the declining

balance rate is equal to 2 (referred to as a “double-declining balance”), the rate of depreciation in the first

period of an asset’s life is equal to twice the rate that

19. New assets are assumed, on average, to be placed in service at midyear,

so that depreciation on them in the first year is equal to one-half the new

investment times the depreciation rate.
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–7

would have been obtained using the straight-line

method. Although there are exceptions, the declining-balance rates for specific types of assets are basedon the empirical studies of Hulten and Wykoff, and the

Net stocks are estimated using the perpetual inventory

method with geometric depreciation. The method begins

with the investment for each year i in asset j, that is, Iij.

For current-cost and real-cost valuation, the investment

that is used in the calculation is in constant dollars; that

is, investment in current dollars has been deflated by the

price index for that type of asset with 1996 as the reference year. For historical-cost valuation, investment in

current dollars is used.

The annual geometric rate of depreciation for type of

asset j, j

, is related to the declining-balance rate for type

of asset j, Rj

, and to the average service life for type of

asset j in years, Tj

, by:

Consider the contribution of investment during year i

in type of asset j to the real-cost net stock at the end of

year t, Ntij. New assets are assumed, on average, to be

placed in service at midyear; thus, depreciation on them

is equal to one-half the new investment times the depreciation rate. Therefore, the contribution to the real-cost

net stock at the end of year t is given by:

To calculate the real-cost net stock at the end of year t for

asset j, Ntj, the contributions are summed over all vintages of investment flows for that asset so that:

The equations used to estimate historical-cost stocks

are identical to equations (2) and (3) except that the

investment flows are expressed at historical cost rather

than real cost.

Current-cost estimates of the net stock of asset j (in

dollars), Ctj, are obtained by multiplying the constantdollar net stock at the end of year t for asset j by the value

at the end of year t of the price index that was used to

deflate nominal investment in asset j,Ptj, so that:

The current-cost net stock of assets at the end of the

year t, Ct

, is estimated as the sum across all types of assets

of the stocks derived above, so that:

() δ 1 j

Rj

Tj

= ----

( ) 2 Ntij Iij 1

δj

2 – ----     1 δj –    t i –

= , where t i ≥

( ) 3 Ntj

t

Σ

i =1

= Ntij

( ) 4 Ctj = Ptj Ntj

( ) 5 Ct Σ

j

Ctj =

Depreciation on asset j during year t, Dtj, equals the net

stock of asset j at the end of year t-1 plus investment in

asset j during year t less the net stock of asset j at the end

of year t, so that:

This equation holds under real-cost and historical-cost

valuation.

Current-cost depreciation, Mtj, is calculated by multiplying constant-dollar depreciation from equation (6) by

the average price of asset j during year t, Ptj, so that:

Current-cost depreciation for an aggregate of assets in

year t is calculated by summing across the various type so

of assets, that is, by:

Quantity Indexes

Chain-type quantity indexes are computed using the

Fisher ideal index formula. For net stocks, the relative

change in the value of the index, QN

t

, between time t and

t-1 is given by

where Ntj is the net stock of asset j at time t, and Ptj is the

end of year price index for asset j at time t.

Similarly, for depreciation, the relative change in the

value of the index, QD

t

, between time t and t-1 is given by

where D tj is the depreciation of asset j at time t, and Ptj

 is the average price index for asset j at time t.

The values for each index are estimated by setting the

level of the index to 100 in the reference year and then

repeatedly using the quantity relatives from equations (9)

or (10) for each pair of years to compute successive values of the index.

( ) 6 Dtj Nt – 1, j Itj Ntj = + –

( ) 7 Mtj = PtjDtj.

( ) 8 Mt Σ

j

M

tj = ·

( ) 9 Qt

N

Qt – 1

N ------------ Σj

NtjPtj

ΣjNt – 1, jPtj

---------------------------- Σj

NtjPt – 1, j

ΣjNt – 1, jPt – 1, j

= ⋅ -------------------------------------

( ) 10 Qt

D

Qt – 1

D ------------ Σj

DtjPtj

ΣjDt – 1, jPtj

---------------------------- Σj

DtjPt – 1, j

ΣjDt – 1, jPt – 1, j

= ⋅ -------------------------------------

Basic Formulas

–

– δ
M–8 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

service lives are developed by BEA.20 The chapter on

“Derivation of Depreciation Estimates” discusses these

estimates in detail.

The main advantage of the perpetual inventory

method is that for the most part, comprehensive, detailed, and relatively reliable data on new investment

are available to implement it. The main limitations relate to the uncertain accuracy of the depreciation rates

(which are generally a function of the assumed service

lives), and of the value of net purchases of used assets.

The information currently available on service lives is

limited with respect to detail and may not fully reflect

the effects of changes in business conditions and technology that may have led to variations in service lives

over time. The information currently available on the

value of net purchases of used assets is largely limited

to net purchases between private businesses and governments, consumers, and nonresidents; net purchases

between industries or between legal forms of organization within private business are not reflected. These estimates of net purchases at depreciated cost are

discussed in the chapter on “Derivation of Investment

Estimates.”

Valuation

BEA values the net stocks and depreciation of fixed assets and consumer durables at historical cost, current

cost, and real cost. The construction and aggregation

of each type of estimate is discussed below and illustrated in the equations on page M–7. Estimates of the

average age of net stocks are constructed only at historical- and current-cost.

Current-cost valuation. Current-cost estimates of

net stocks and depreciation reflect the prices of the

given period. For instance, the estimate of the net stock

for 1997 reflects the value of the stock expressed in the

prices that would have been paid for those assets if they

had been purchased at the end of 1997. Similarly, the

1925 net stock estimate reflects the value of the stock in

1925 expressed at the prices that would have been paid

for them if they had been purchased in 1925.

In principle, the current-cost net stock is the mar20. Information on Hulten and Wykoff’s methodology is largely found in

the following three sources: (1) Frank C. Wykoff and Charles R. Hulten,

“Tax and Economic Depreciation of Machinery and Equipment: A Theoretical Appraisal, Phase II Report,” Economic Depreciation of the U.S. Capital Stock: A First Step, Washington, D.C.: U.S. Department of the Treasury,

Office of Tax Analysis, July 26, 1979; (2) Charles R. Hulten and Frank C.

Wykoff, “The Estimation of Economic Depreciation Using Vintage Asset

Prices,” Journal of Econometrics 15, (April, 1981): 367–396; and (3) Charles

R. Hulten and Frank C. Wykoff, “The Measurement of Economic Depreciation.” In Depreciation, Inflation, and the Taxation of Income from Capital,

edited by Charles R. Hulten, 81–125. Washington, D.C.: The Urban Institute Press, 1981. For further elaboration on the specific BEA rates, see Fraumeni, “The Measurement of Depreciation.”

ket, or replacement, value of the stock; that is, the value

for which the assets in the stock could be bought or

sold in that year. In equilibrium, this market value will

equal the present value of all expected future services

embodied in existing assets.

Current-cost estimates of net stocks and depreciation are derived by converting the corresponding constant-dollar estimates of depreciation and net stocks to

the prices of the current period. Specifically, estimates

of investment in current dollars are deflated, using the

appropriate price index for that asset for each year, to

reflect 1996 prices.21 Estimates of depreciation are derived by applying to this constant-dollar investment

series assumed depreciation patterns and service lives.

Following the perpetual inventory method, constantdollar estimates of net stocks for each year are derived

by deducting these estimates of depreciation, summed

over all years, from the constant-dollar estimates of investment, also summed over all years. These constantdollar estimates are then multiplied by the appropriate

price indexes of the current year to derive current-dollar estimates of net stocks and depreciation: Net stock

estimates are derived using indexes that reflect new asset prices at the end of the given year, and depreciation

estimates are derived using indexes that reflect the average prices of new assets over the entire year.22 (For

quarterly CFC estimates in the NIPAs, average quarterly prices are used.) Current-cost aggregates are

21. The price indexes used to derive the stock estimates for current-cost

and real-cost estimates are the same as those used to derive real GDP and its

components. These price indexes are described in “Updated Summary

NIPA Methodologies,” SURVEY 82 (October 2002), especially in Table 2,

“Methodologies Used in Preparing Estimates of Real GDP,” pp. 34–38. The

price indexes are also described in “The Comprehensive Revision of the

U.S. National Income and Product Accounts: A Review of Revisions and

Major Statistical Changes,” SURVEY 71 (December 1991): 37–40 and “Annual

Revision of the U.S. National Income and Product Accounts,” SURVEY 72

(July 1992), table 8, pp. 37–42. For personal consumption expenditures for

durable goods, see U.S. Department of Commerce, Bureau of Economic

Analysis, Personal Consumption Expenditures, NIPA Methodology Paper

No. 6 (Washington DC: U.S. Government Printing Office, June 1990):

67–73; and for government investment, see U.S. Department of Commerce,

Bureau of Economic Analysis, Government Transactions, NIPA Methodology Paper No. 5 (Washington DC: U.S. Government Printing Office,

November 1988): 50–64.

For investment in electric light and power structures, the NIPA price

indexes are modified to reflect price changes in the value of completed

plant, in accordance with the modifications to the NIPA investment data

described in the section “Investment control totals by type of asset” in the

chapter “Derivation of Investment Flows.”

22. Beginning with 1947, yearend prices are derived as the average of

fourth-quarter prices in the current year and first-quarter prices in the following year. Before 1947, yearend prices are derived as the average of the

annual average price of the current year and the annual average price of the

following year. Average annual price indexes are equal to 100 in the base

period, 1996. Thus, the 1996 values of real-cost and current-cost depreciation (and of discards) are equal, because these are average annual values.

The 1996 values of real-cost and current-cost net stocks are usually not

equal, because these are yearend values, and prices usually change during

the year.
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–9

obtained by directly summing the current-cost estimates for the various types of assets.

Real-cost valuation. Real-cost estimates, expressed

in this publication as chain-type quantity indexes or as

chained (1996) dollars, remove the effects of price

change and are often called “physical-volume” estimates. Detailed real-cost estimates for each asset type

are the constant-dollar estimates described above. Aggregate real-cost estimates of net stocks and depreciation are derived by weighting and chaining the detailed

constant-dollar estimates of net stocks and depreciation described above. That is, the detailed constantdollar estimates are entered along with price weights

(derived by dividing the relevant current-dollar estimates by their constant-dollar counterparts) into a

Fisher formula that uses the price weights from adjacent years to calculate the rate of change in quantities

from year to year. For example, the 1996–97 rate of

change in real investment uses prices for 1996 and

1997 as weights. These annual rates of change are then

“chained” (multiplied) together to form a time series

of rates of quantity change that is expressed as index

numbers or as chained dollars with 1996 as the reference year.

The chain-type quantity indexes provide accurate

estimates of the growth rate from one year to the next

because they use relevant weights—that is, weights

that reflect the composition of prices in adjacent years

rather than the weights of a single base year. Thus,

when the base year is updated, the levels of the estimates change but the growth rates of the various series

do not, and the revisions to the growth rates that result

from updating the base period of a fixed-weighted

index are avoided.23

Quality change. The deflation of current-dollar investment estimates to the prices of a base year to obtain a real-cost investment series is complicated by the

need to account for new products or quality changes

introduced since the base period. Similarly, depreciation patterns estimated using empirically-measured

23. See Jack E. Triplett, “Economic Theory and BEA’s Alternative Quantity and Price Indexes,” SURVEY 72 (April 1992): 49–52. The percentage

changes calculated from the chained-dollar estimates and from the chaintype quantity indexes are the same; the chained-dollar estimates are most

appropriately interpreted as index numbers with a reference value other

than 100. However, because the relative prices used as weights for any

period other than the reference year differ from those used for the reference

year, the chained-dollar values of components will not necessarily sum to

the chained-dollar values of aggregates. As the relative prices—or weights—

change with time, the difference—or residual—between the sums of the

chained-dollar values of the components and chained-dollar values of the

aggregate may become larger as one moves further from the reference year.

Thus, the chained-dollar estimates become less useful as an approximate

measure of relative magnitude as one moves further from the reference

year. In general, the use of chained-dollars to calculate component shares or

contributions to growth may be misleading for periods away from the reference year.

transactions prices for used assets must also be adjusted for quality change.24 Where possible, these adjustments are introduced into BEA’s estimates of

investment, and thus into net stocks and depreciation

through the use of quality-adjusted price indexes in the

deflation process. The price indexes incorporate adjustments for quality change through a number of

methods.25 For instance, for the deflation of equipment, BEA primarily uses producer price indexes

(PPI’s) published by BLS. Five methods are used by

BLS to adjust the PPI’s for quality change.26

The explicit quality adjustment method uses the ratio of the producer’s cost of the new product to the

producer’s cost of the old product to evaluate their relative quality so that the price of the new product can

be adjusted accordingly. This method is used when

quality changes are considered to be significant and

when the necessary producer cost data are available.

With the overlap method, the ratio of the price of

the new model to that of the old model during the

overlap period provides the basis for evaluating relative

quality. This method is used when quality change is

considered to be significant and the data necessary to

implement the explicit quality adjustment method are

not available.

The method of linking prices of new and old models

attributes all of the difference in prices between old

and new models to a change in quality. This method is

used when quality changes are considered to be significant, and data are not available to implement either the

explicit quality adjustment method or the overlap

method. To the extent that pure price changes occur

when new models are introduced, this method tends to

attribute too much of the difference in price between

24. Oliner discussed this problem when he stated that depreciation patterns in the NIPAs should be based on “partial,” rather than on “full” depreciation; See Stephen D. Oliner, “Price Change, Depreciation, and

Retirement of Mainframe Computers,” in Price Measurements and Their

Uses, Murray F. Foss, Marilyn E. Manser, and Allan H. Young (eds.), Studies

in Income and Wealth, vol. 57 (Chicago: University of Chicago Press, for

the National Bureau of Economic Research, 1993): 48–61.

25. See Jack E. Triplett, “Concepts of Quality in Input and Output Price

Measures: A Resolution of the User-Value Resource-Cost Debate,” in The

U.S. National Income and Product Accounts: Selected Topics, Murray F. Foss

(ed.), Studies in Income and Wealth, vol. 47 (Chicago, IL: University of

Chicago Press, for the National Bureau of Economic Research, 1983). Also

see Robert J. Gordon, The Measurement of Durable Goods Prices, National

Bureau of Economic Research Monograph Series, (Chicago and London,

University of Chicago Press, 1990).

26. The treatment of quality change in the PPI’s is described in John F.

Early and James H. Sinclair, “Quality Adjustment in the Producer Price

Indexes,” in The U.S. National Income and Product Accounts: Selected Topics,

Murray F. Foss (ed.), Studies in Income and Wealth, vol. 47 (Chicago, IL:

University of Chicago Press, for the National Bureau of Economic Research,

1983). BLS uses similar methods for the consumer price index, which is the

basis for deflating expenditures on consumer durable goods. Also, see

James Sinclair and Brian Catron, “An Experimental Price Index for the

Computer Industry,” Monthly Labor Review 113 (October 1990): 16–24. For

computers and computer peripheral equipment, BEA also uses price

indexes that it has developed using hedonic methods.
M–10 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

new and old models to quality change.

Hedonic quality adjustment measures quality

change as a weighted average of changes in the physical

characteristics of the fixed asset with weights determined by multiple regression analysis.27 The weights

that are estimated by regression analysis can be interpreted as the approximate market valuations of each

characteristic.

Finally, the direct price comparison method counts

quality change as zero, and prices of new and old models are directly compared. This method is used when

quality changes are assumed to be very small.

Adjusting prices for quality change is difficult for

some assets. For example, estimates of investment in

new permanent-site housing are adjusted for quality

change by using separate hedonic price indexes for single-family housing and for multifamily housing in the

deflation process.28 But distinguishing between price

and quality change is more difficult for nonresidential

structures because the unique nature of many construction projects limits the comparable projects available for price comparisons. As no price indexes that

incorporate an explicit adjustment for quality change

are available for the types of structures being deflated,

these estimates, which are deflated using a variety of

price and cost indexes, are not adequately qualityadjusted.29

Historical-cost valuation. Historical-cost estimates

of net stocks are analogous to book value estimates

used on company reports and financial statements in

that assets are valued at the prices prevailing when they

were purchased. Historical cost estimates of the net

stock are the depreciated values of these acquisition

costs of assets using BEA’s assumed depreciation patterns.

Following the perpetual inventory method, estimates of net stocks at historical cost are derived for

each year by deducting historical-cost depreciation estimates, summed over all years, from historical-cost estimates of investment, also summed over all years.

Specifically, for each year, investment is depreciated by

applying to the acquisition cost of each asset the same

depreciation patterns and service lives used to derive

the current-cost estimates. These historical-cost depreciation estimates are summed over all years and deducted from the historical-cost estimates of investment

summed over all years to derive net stocks for each

27. See Jack E. Triplett, “The Economic Interpretation of Hedonic Methods,” SURVEY 66 (January 1986): 36–40. 

28. See “The Comprehensive Revision of the U.S. National Income and

Product Accounts: A Review of Revisions and Major Statistical Changes,”

SURVEY 71 (December 1991): 40. 

29. For sources of construction prices see Value of Construction Put in

Place, Appendix D, “Adjustment For Seasonal Variation and Cost Changes,”

U.S. Bureau of the Census (C40), monthly.

year. The resulting estimates of depreciation and net

stocks are directly summed to derive aggregates at the

industry, legal form, and national levels.

Relationship among estimates. As noted above, for

historical-cost estimates, the conceptual relationships

among investment, net stocks, and depreciation are

simple: the change in the net stock from the end of one

year to the next equals investment less depreciation,

and the sum of depreciation charges for an individual

asset over its life (or for a group of assets over their

lives) is equal to the amount of the original investment.

These relationships do not hold for current- and realcost estimates. First, the current-cost and real-cost estimates are derived using weights that reflect prices of

more than one period and are therefore not additive.

Specifically, the first relationship does not hold for current-cost estimates because end-of-year price indexes

are used to revalue constant-dollar estimates of net

stocks to the prices of each year, while average annual

price indexes are used to revalue the estimates of depreciation. Real-cost aggregates are estimated using a

chain-type quantity index and therefore do not equal

the sum of their components. At the level at which the

most detailed estimates of investment are calculated,

the real-cost end-of-period net stock does equal the

beginning-of-period stock plus investment less depreciation. However, this relationship does not hold for

some types of assets for which the estimate of investment is built up from components that have different

deflators.30 The relationship for lifetime depreciation

charges does not hold for similar reasons: current-cost

depreciation estimates are valued in the prices of the

year in which the depreciation occurs, while investment is valued at acquisition costs. At the lowest level

of detail, this relationship does hold for real-cost estimates (except when an asset is prematurely retired,

such as through surplusing from the stock of government assets), but does not hold for aggregated estimates because the estimates are not additive.31

Adjustments for catastrophic losses and 

obsolescence

BEA adjusts the value of net stocks to account for catastrophes, such as hurricanes, earthquakes, and the

terrorist attacks of September 11, 2001, in which large

amounts of fixed assets and consumer durables are destroyed.32 The adjustments for fixed assets are presented in the NIPAs in table 5.16, along with the other

30. In general, when “real” estimates are derived using a chained-type

quantity index, the sum of the real values of the various components of an

aggregate will differ from the aggregate’s real value by a “residual.” 

31. When the depreciation pattern is strictly geometric, some assets have

infinite lives so that this relationship only holds asymptotically.

32. See the “Business Situation,” SURVEY 72 (September 1992): 2, and the

“Business Situation,” SURVEY 81(November 2001): 2.
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–11

sources of change in the value of the net stocks of fixed

assets and private inventories, as described above. In

general, the adjustments for catastrophes are made if

the cost of the damage equals at least one-quarter of

one percent of total private consumption of fixed capital (this proportion of consumption of fixed capital

was about $2.1 billion in 1997). The adjustments to

general government assets are not included in the

NIPA estimates of consumption of fixed capital that

are included in gross domestic product (GDP) because

government consumption expenditures are measured

by adding up costs including CFC. Excluding these adjustments avoids increasing the measured output of

fixed government assets in GDP when there are catastrophic losses.

The depreciation schedules used to derive the estimates reflect the effects of normal obsolescence over

time. Ideally, the estimates of net stocks should also be

adjusted for declines in value caused by unusually or

unexpectedly large amounts of obsolescence, as the depreciation rates used to derive the estimates reflect

only the effects of normal obsolescence over time.33

However, the data on the impact of obsolescence that

are necessary to make such adjustments are not available.

33. Some argue that government pollution abatement and safety regulations, sudden changes in energy prices, and increased foreign competition

have caused certain capital assets to experience significantly higher-thannormal amounts of obsolescence.
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–13

This chapter describes the investment flows underlying

BEA’s perpetual inventory estimates of net stocks and

depreciation. Specifically, this chapter explains the derivation of the estimates of investment in private and

government fixed assets and the estimates of expenditures by consumers on durable goods.

Investment in Private Fixed Assets

The estimates of investment by industry and by type of

asset used to derive the perpetual inventory estimates

of private fixed assets are designed to be consistent

with the NIPAs and with the SIC. The estimates reflect

three requirements: First, for each asset, new investment summed across all industries equals the NIPA estimate of total investment in that asset. Second,

industries are classified on an establishment basis. Finally, assets are classified in the industry that owns

them.

In general, estimates are developed in the following

manner: First, estimates are derived of investment in

new nonresidential and residential assets for each industry and of net purchases of used assets between private business and other types of owners. Second, these

estimates are distributed by legal form of organization.

Finally, the estimates of investment by type of asset, industry, and legal form of organization are deflated to

constant dollars using appropriate price indexes.

These estimates are then used in the derivation of current- and real-cost estimates. The first two steps are described in the following sections; deflation is discussed

in the section on valuation in the previous chapter.

Sources

The estimates of investment in new nonresidential and

residential assets and of net purchases of used assets

are primarily based on NIPA data on investment by

type of asset and industry data from several sources.

The NIPAs provide data on investment by type of asset

for years since 1929. Estimates of expenditures on prepackaged, custom, and own account software—now

recognized as investment in the NIPAs and included in

net stocks of fixed assets—are available for 1959 to

1997. (Before 1959, expenditures on software were

insignificant.) To derive estimates of net stocks for

1925–1929, the NIPA investment estimates are extrapolated back to before 1900 for some assets (see the section “Investment controls by type of asset”).

The NIPA estimates of investment in equipment

and software and in structures are sometimes modified

for estimating net stocks, primarily to exclude dealers’

margins or brokers’ commissions from net purchases

of used assets among sectors of the economy.34 In addition, the NIPA estimates are supplemented to provide

detail not available in the NIPAs, primarily on the industrial distribution of investment in private fixed assets.

Estimates of investment by industry in nonresidential assets are available from several sources. Some provide information for selected benchmark years; others

provide information for interpolations between and

extrapolations from the benchmark years. Wherever

possible, the investment control totals are based on

capital expenditures data collected from each industry.

Where these data are not available, the estimates are

derived as the change in net stocks plus depreciation

from industry balance sheet data. The balance sheet

data are primarily from the Statistics of Income published by the Internal Revenue Service (IRS) and from

Federal regulatory agencies.

There are five major sources of data on industry

capital expenditures. The first, economic censuses conducted by the Bureau of the Census, provide data classified on an establishment basis on capital

expenditures in the mining, construction, manufacturing, wholesale trade, retail trade, and selected service

industries. Most of these data are available only at intervals of several years (every 5 years since 1967), and

all data prior to 1977 provide only a two-way split by

type of asset (that is, total equipment and total structures). Beginning with the 1977 economic census, the

data on equipment expenditures in the manufacturing

industries includes detail on highway vehicles, computers and peripheral equipment, and other equipment. This expanded asset detail is also available

beginning with the 1987 census for construction,

34. Dealers’ margins for used equipment and brokers’ commissions on

sales of used structures are included in fixed investment in the NIPAs but

are not included in nonresidential fixed stocks.

Derivation of Investment Estimates
M–14 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

Table A. Source Data for Preparation of Estimates of New Private Nonresidential Investment by Industry

Industry Years before 1947

1947–77 

(includes census years up to 

and including 1977)

1978–92

Years after 1992 2

Economic census years 1982, 

1987, and 1992 Noncensus years 1

Agriculture, forestry, and fishing:

Farms .............................................. USDA, Trends USDA USDA, NIPA USDA, NIPA USDA, NIPA

Agricultural services, forestry, and 

fishing .......................................... USDA, Trends P&E P&E, NIPA P&E, NIPA ACES, NIPA, P&E

Mining.................................................. HS, EC (CMI and CM), NIPA EC (CMI), ES, P&E, NIPA, Oil 

& Gas

EC (CMI), ES, NIPA P&E, NIPA ACES, NIPA, P&E

Construction ........................................ Boddy & Gort, HS EC (CCI), ES, P&E, NIPA EC (CCI), ES, NIPA P&E, NIPA ACES, NIPA, P&E

Manufacturing...................................... Chawner, NIPA, CS, HS, EC 

(CM), Kuznets, Shaw

EC (CM), ASM, ES, P&E, NIPA EC (CCI), ES, NIPA ASM, NIPA ASM, ACES, NIPA

Transportation and public utilities:

Transportation:

Railroad transportation................ ICC, NIPA, Ulmer, TA, CS ICC, NIPA, TA, P&E P&E, NIPA, TA , ICC 

(1982)

P&E, NIPA ACES, NIPA

Local and interurban passenger 

transit....................................... Ulmer, CS, TA, NIPA, ICC ICC, TA, CS, P&E, NIPA P&E, NIPA P&E, NIPA ACES, NIPA, P&E

Trucking and warehousing........... NIPA, Ulmer, TA, ICC ICC, EC (CWT), EC, (CT) 3

, P&EICC (1982), P&E, EC, (CT) 3 P&E, TA, NIPA ACES, NIPA

Water transportation.................... NIPA, HS, ICC NIPA, ICC, P&E P&E, NIPA, TA P&E, NIPA ACES, NIPA. P&E

Transportation by air.................... NIPA, HS NIPA, DOT, P&E DOT, NIPA, P&E, TA DOT, NIPA, P&E DOT, ACES, NIPA

Pipelines, except natural gas ...... ICC, NIPA, CS, HS ICC, NIPA, P&E NIPA, P&E NIPA, P&E ACES, NIPA

Transportation services ............... ICC, NIPA, Ulmer, TA, CS ICC, NIPA, TA, P&E P&E, NIPA, TA P&E, NIPA ACES, NIPA, P&E

Communications:

Telephone and telegraph................. NIPA, CS, USDA, Ulmer NIPA, TA, CS, USDA, FCC, 

Crandall, P&E, CAR

FCC, NIPA, CAR, TA, Crandall, 

ACES, P&E, USDA

FCC, NIPA, CAR, TA, Crandall, 

ACES, P&E, USDA

ACES, NIPA, FCC, CAR, TA, 

P&E, USDA

Radio and television........................ Boddy & Gort P&E, TA, NIPA P&E, TA, UC, NIPA P&E, TA, UC, NIPA ACES, NIPA

Electric, gas, and sanitary services:

Electric services .............................. Ulmer, NIPA, CS, USDA, DOE 

FS

DOE FS, NIPA, USDA, P&E DOE FS, DOE EP, NIPA, 

USDA, UC

DOE FS, DOE EP, NIPA, 

USDA, UC

DOE FS, DOE EP, NIPA, 

USDA, UC, ACES

Gas services ................................... Ulmer, NIPA, CS, TA, UC NIPA, CS, UC, TA, P&E NIPA, P&E, TA NIPA, P&E, TA NIPA, ACES

Sanitary services............................. Ulmer P&E, DOE FS, TA P&E, DOE FS, TA P&E, DOE FS, TA, NIPA ACES, DOE FS, TA, NIPA

Wholesale trade .................................. Boddy & Gort EC (CWT) 4, P&E, ES EC (CWT) 4, ES, TA P&E, NIPA ACES, NIPA, P&E, UC

Merchant wholesale ........................ ............................................... EC (CWT) 4, ES EC (CWT) 4

, ES ................................................ ...............................................

Nonmerchant wholesale.................. ............................................... EC (CWT), ES EC (CWT), ES, TA ............................................... ...............................................

Retail trade.......................................... CS, HS EC (CRT) 4

, P&E EC (CRT) 4 P&E, NIPA ACES, NIPA, UC

Finance, insurance, and real estate:

Finance and insurance.................... SOI, HS P&E, TA P&E, TA P&E, NIPA ACES, NIPA, P&E

Real estate ...................................... SOI, HS, CS, UC, TA P&E, TA, UC, NIPA, SOI P&E, TA, NIPA, UC, EC(CCI) P&E, NIPA ACES, NIPA, P&E

Services:

Hotel and other lodging places........ SOI, UC EC (CSI) 4, P&E, UC EC (CSI) 4, NIPA NIPA ACES, NIPA

Personal services............................ SOI, UC EC (CSI) 4, P&E, UC EC (CSI) 4 P&E, NIPA ACES, NIPA

Business services ........................... SOI, UC EC (CSI) 4

, P&E, UC EC (CSI) 4, TA P&E, NIPA ACES, NIPA

Auto repair, services, and parking... SOI, UC EC (CSI) 4

, P&E, UC EC (CSI) 4, TA, NIPA P&E, TA, NIPA ACES, TA, NIPA, P&E

Miscellaneous repair services......... SOI, UC EC (CSI) 4, P&E, UC EC (CSI) 4 P&E, NIPA ACES, NIPA

Motion pictures................................ SOI, UC EC (CSI) 4, P&E, UC EC (CSI) 4, UC P&E, UC, NIPA ACES, UC, NIPA

Amusement and recreation 

services ....................................... SOI, UC EC (CSI) 4, P&E, UC EC (CSI) 4, UC P&E, UC, NIPA ACES, UC, NIPA

Health services ............................... SOI, TA P&E, TA EC (CSI) 4

, P&E, NIPA, TA P&E, NIPA ACES, NIPA, P&E

Legal services ................................. SOI, TA P&E EC (CSI) 4, P&E P&E, NIPA ACES, NIPA

Education services.......................... NIPA, CS, SOI, USDE NIPA, P&E, USDE EC (CSI 1987, 1992) 4

, P&E, 

NIPA, USDE

P&E, NIPA ACES, NIPA

Other services 5............................... SOI, NIPA, CS P&E, NIPA EC (CSI 1987, 1992) 4

, P&E, 

NIPA

P&E, NIPA ACES, NIPA

1. Used to interpolate between economic census year estimates.

2. Used to extrapolate forward from 1992.

3. Data are from the truck inventory and use survey taken as part of the Census of Transportation for years

1963, 1967, 1972, 1977, 1982, and 1987; and for 1992 taken as part of the Census of Transportation, Communications, and Utilities.

4. Data are from the capital expenditures survey taken as part of the economic census for the years through

1982 and for 1987 and 1992 from the assets and expenditures survey taken as part of the economic census.

5. “Other” services consists of the following industries: Social services; museums; botanical, zoological

gardens; membership organizations; engineering and management services; and services, not elsewhere classified.

NOTE. The source data provided in this table are those used to allocate estimates of private nonresidential

investment to the various industries. For most economic census years, the distribution is based on the capital

flow tables prepared by BEA as part of the benchmark input-output accounts.

ACES U.S. Department of Commerce, Bureau of the Census, Annual Capital Expenditures Survey (Washington, DC: U.S. Government Printing Office, annually beginning in 1992).

ASM U.S. Department of Commerce, Bureau of the Census, Annual Survey of Manufac-

 tures (Washington, DC: U.S. Government Printing Office, annually).

Boddy & Gort Rayford Boddy and Michael Gort, “Capital Expenditures and Capital Stocks,” Annals of

Economic and Social Measurement 2/3 (1973); and “The Derivation of Investment

 Expenditures and Capital Stocks” (typewritten, 1968).

CAR Data from company annual reports.

Chawner Lowell J. Chawner, “Capital Expenditures for Manufacturing Plant and Equipment—

1915 to 1940,” SURVEY OF CURRENT BUSINESS 21 (March 1941): 9–15; “Capital Expenditures in Selected Manufacturing Industries,” SURVEY 21 (December 1941): 19–26;

and “Capital Expenditures in Selected Manufacturing Industries, Part II,” SURVEY 22

(May 1942): 14–23.

Crandall Robert W. Crandall, After the Breakup: U.S. Telecommunications in a More

Competitive Era (Washington, DC: The Brookings Institution, 1991).

CS U.S. Department of Commerce, Business and Defense Services Administration,

Construction Statistics 1915–64: A Supplement to Construction Review (Washington, DC: U.S. Government Printing Office, 1966).

DOE EP U.S. Department of Energy, Energy Information Administration, Electric Power

Annual, 2 vols. (Washington, DC: U.S. Government Printing Office, annually).

DOE FS U.S. Department of Energy, Energy Information Administration, Financial Statistics

of Selected Investor-Owned Electric Utilities (Washington, DC: U.S. Government

Printing Office, annually).

DOT U.S. Department of Transportation, Air Carrier Financial Statistics (Washington,

DC: U.S. Government Printing Office, annually).

EC U.S. Department of Commerce, Bureau of the Census, Census of Construction

Industries (CCI): 1967, 1972, 1977, 1982, 1987, and 1992; Census of Manufactures (CM): 1947, 1958, 1963, 1967 1972, 1977, 1982, 1987, and 1992; Census of

Mineral Industries (CMI): 1954, 1958, 1963, 1967, 1972, 1977, 1982, 1987, and

1992; Census of Retail Trade (CRT): 1958, 1963, 1967, 1972, 1977, 1982, 1987,

and 1992; Census of Service Industries (CSI): 1958, 1963, 1967, 1972, 1977,

1982, 1987, and 1992; Census of Transportation (CT): 1963, 1967, 1972, 1977,

1982, 1987, and 1992; and Census of Wholesale Trade (CWT): 1958, 1963, 1967,

1972, 1977, 1982, 1987, and 1992 (Washington, DC: U.S. Government Printing

Office, quinquennially).

ES U.S. Department of Commerce, Bureau of the Census, Enterprise Statistics: 1954,

1958, 1963, 1967, 1972, 1977, 1982, 1987, and 1992 (Washington, DC: U.S.

Government Printing Office, quinquennially).

FCC Federal Communications Commission, Statistics of Communications Common

Carriers (Washington, DC: Federal Communications Commission, annually).

HS U.S. Department of Commerce, Bureau of the Census, Historical Statistics of the

United States, Colonial Times to 1970, 2 vols. (Washington, DC: U.S. Government

Printing Office, 1975).

ICC Interstate Commerce Commission, Transport Statistics in the United States (Washington, DC: U.S. Government Printing Office, annually).
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–15

wholesale and retail trade, and services, and beginning

with the 1992 census for mining.

The second major source of data, the capital flow tables prepared by BEA as part of the input-output

(I-O) accounts, provides distributions of industry

investment by type of asset.35 These data are largely

consistent with NIPA definitions, but investment is

classified by the using, rather than by the owning, industry, and industries are classified according to the

I-O rather than the NIPA classification system (though

both are based on the SIC). These data are available

only for 1963, 1967, 1972, 1977, 1982, and 1992.36 (For

a list of NIPA industries used for net stocks, see table

3.1 in this publication.)

The third source of data is the Census Bureau’s annual survey of manufactures (ASM), which provides

annual data on investment in equipment and in structures by manufacturing industries. This survey has

been available for noncensus years (that is, years in

which an economic census was not conducted) since

1949.

The fourth source, the Census Bureau’s plant and

equipment expenditures (P&E) survey, which was discontinued in 1993, provided annual data for 1947 to

1993 on investment in nonresidential capital by industry for companies primarily engaged in nonfarm activities. These data are not consistent with the NIPA

35. The capital flow tables through 1992 do not provide data on industry

expenditures on software. Expenditures on software were not recognized as

investment until the 1999 NIPA comprehensive revision, after the release of

the 1992 I-O accounts. See Robert P. Parker and Bruce Grimm, “Recognition of Business and Government Expenditures for Software as Investment:

Methodology and Quantitative Impacts, 1959–98,” 2000. Paper presented

to BEA’s Advisory Committee, May 5, 2000. Available at www.bea.doc.gov/

bea/papers/software.pdf.

36. More information on the BEA capital flow tables is available: For the

1992 capital flow table, see Belinda Bonds and Tim Aylor, “Investment in

New Structures and Equipment in 1992 by Using Industry,” SURVEY 78

(December 1998): 26–51.The unpublished 1982 table is provided on BEA’s

Web site at www.bea.gov/bea/dn2.htm. For the 1977 table, see “New Structures and Equipment by Using Industries, 1977,” SURVEY 65 (November

1985): 26–35; for the 1972 table, see U.S. Department of Commerce,

Bureau of Economic Analysis, New Structures and Equipment by Using

Industries, 1972: Detailed Estimates and Methodology, BEA Staff Paper No.

35, Washington, D.C.: U.S. Government Printing Office, 1980; and for the

1963 and 1967 tables, see U.S. Department of Commerce, Bureau of Economic Analysis, Interindustry Transactions in New Structures and Equipment, 1963 and 1967, 2nd volume, Springfield, VA: National Technical

Information Service, 1975.

investment totals (mostly due to industry coverage and

definitions of investment), provide only a two-way

split by type of asset (total equipment and total structures), and are classified on a company basis.

The fifth source, the Census Bureau’s annual capital

expenditures survey (ACES), which replaced the P&E

survey in 1994, provides data on annual capital expenditures for equipment and structures of the companies

surveyed.37 Periodically, more detailed expenditure

data are collected. For estimates for 1992–93, data

from both the ACES survey and P&E series are sometimes available. BEA evaluates the quality of each and

uses whichever is deemed the most accurate for each

industry to extrapolate NIPA estimates of investment

in equipment and in structures by industry.38 Beginning with 1994, for most nonmanufacturing industries, NIPA estimates are extrapolated using ACES

data. For manufacturing industries, ASM data are used

wherever possible.

Where the industry data do not meet all of the requirements stated above, they are supplemented by

data from other sources, as described in Table A and in

the section on “Investment controls by industry” below. Additionally, the source data for each industry are

adjusted so that the control totals are consistent with

respect to definitions and coverage. Specifically, adjustments are made for:

(1) Industrial classification: Establishment-based

source data that are not classified according to the 1987

SIC are converted to this basis, primarily using data

from the 1987 economic censuses.

(2) Establishment basis: Where necessary, industry

investment estimates are adjusted to an establishment

basis. The Census Bureau’s P&E series and the series

published by the IRS in Statistics of Income are adjusted

from a company to an establishment basis. The Census

Bureau’s ACES series is adjusted from an activity basis

to an establishment basis because a single activity, or

business segment, may have establishments in more

37. The Census Bureau’s ACES series is not collected on an establishment

basis. In some cases, the data are collected on a company basis; in others,

the data are collected on a division or major activity basis.

38. The Census Bureau conducted pilot ACES surveys in 1992 and 1993 at

the same time as the P&E survey.

Kuznets Simon Kuznets, Capital in the American Economy: Its Formation and Financing

(Princeton, NJ: Princeton University Press, for the National Bureau of Economic

Research, 1961).

NIPA For 1929–94, U.S. Department of Commerce, Bureau of Economic Analysis,

National Income and Product Accounts of the United States, 1929–94, 2 vols.

(Washington, DC: U.S. Government Printing Office, 1998); and for 1995–96, see

SURVEY 77 (August 1997): 6–167. See the following tables: Current-dollar expenditures, tables 2.6, 5.6, 5.8, and 5.14 and chain-type quantity and price indexes,

tables 7.5, 7.7, 7.8, and 7.13. 

Oil & Gas U.S. Department of Commerce, Bureau of the Census, Annual Survey of Oil and

Gas (Washington, DC: U.S. Government Printing Office, annually through 1982).

P&E U.S. Department of Commerce, Bureau of the Census, Plant and Equipment

Survey (unpublished annual data for 1947–93).

Shaw William H. Shaw, Value of Commodity Output Since 1869 (Princeton, NJ: Princeton

University Press, for the National Bureau of Economic Research, 1947).

SOI U.S. Department of the Treasury, Internal Revenue Service, Statistics of Income:

Corporation Income Tax Returns; Statistics of Income: Partnership Income Tax

Returns; and Statistics of Income: Nonfarm Proprietorship Returns (Washington,

DC: U.S. Government Printing Office, annually).

TA Trade association data (published and unpublished).

Trends Robert E. Gallman, “Commodity Output, 1839–99,” and Marvin W. Towne and

Wayne D. Rasmussen, “Farm Gross Product and Gross Investment in the Nineteenth Century,” both in Trends in the American Economy in the Nineteenth

Century, Studies in Income and Wealth, vol. 24 (Princeton, NJ: Princeton University

Press, for the National Bureau of Economic Research, 1960).

UC Unpublished data from the Bureau of the Census.

Ulmer Melville J. Ulmer, Capital in Transportation, Communications, and Public Utilities: Its

Formation and Financing (Princeton, NJ: Princeton University Press for National

Bureau of Economic Research, 1960).

USDA U.S. Department of Agriculture, Farm Income Statistics; Statistical Report, Rural

Telephone Borrowers; and Statistical Report, Rural Electric Borrowers (Washington, DC: U.S. Government Printing Office, all annually).

USDE U.S. Department of Education data (unpublished).
M–16 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

than one industry. For example, a manufacturing activity may also include sales branch offices, which are

classified as wholesale establishments by the SIC.

Where the coverage in principal source data of investment expenditures for an establishment-based industry is incomplete, the gaps are filled using estimates

derived from secondary source data such as employment data or trade sources.

(3) Central administrative offices and auxiliaries

(CAO’s). The SIC classifies auxiliary establishments in

the industry they serve. Where source data do not include them, such as for mining, construction, manufacturing, and wholesale trade, BEA adjusts the

investment estimates to include them.

(4) Ownership basis: To derive stocks by establishment-based industry on an ownership basis, several

conventions are adopted. First, leased assets except

those held under capital leases are classified in the industry of the lessor. Assets held under capital leases are

classified in the industry of the lessee.39 Second, for assets used in establishments of multi-industry companies where the legal owner of the assets is the parent

company, the assets are classified in the industry of the

establishment where they are used. Third, assets

owned by manufacturers' sales branches and offices are

classified in the wholesale trade industry. Finally, assets

owned and used by nonprofit institutions that primarily serve individuals are classified in the real estate industry to provide consistency with the NIPA

business-sector treatment and industrial classification

of these assets.

(5) Employee-owned autos: The source data for

each industry do not include expenditures for autos

owned by individuals that are used wholly or partly for

business purposes. Therefore, the portion of the expenditures attributable to business use are estimated as

discussed in the chapter on “Derivation of Estimates of

Privately-Owned Automobiles.”

(6) Employee-owned trucks. The source data for

each industry do not include expenditures for trucks

owned by individuals that are used wholly or partly for

business purposes. Therefore, the portion of the expenditures attributable to business use are estimated

using data from the Census of Transportation Truck

Inventory and Use Survey, from NIPA data on investment, from the capital flow tables for 1982 and 1992,

39. Capital expenditures data for the mining, construction, manufacturing, trade, and service industries from the economic censuses include capital leases, which corresponds with NIPA conventions. Capital expenditures

for the agriculture, transportation, communication, utilities, and finance

industries are adjusted to account for capital leasing. Capital leases are

defined here as including “full-payout” and “equity” leases and are included

in the industry of the lessee. Also included in the industry of the lessee are

assets related to sale and leaseback arrangements and assets related to “safe

harbor” leases for the period 1981–83.

and from the Census Bureau’s Enterprise Statistics.

(7) Software. The source data for each industry do

not include expenditures for software: The Census Bureau’s ACES series included expenditures for software

that is capitalized in company financial accounts beginning in 1995 (most software, however, is not capitalized). The ASM does not explicitly include

expenditures on software. Therefore, software expenditures are distributed in the following manner: For

prepackaged software, expenditures are distributed to

industries based on NIPA data on expenditures for

personal computers. For custom and own-account

software, expenditures are distributed to industries

based on NIPA data on expenditures for computer

processors.

The specific sources and derivation of estimates of

investment in nonresidential and residential assets by

industry and of net purchases of used assets among

sectors are provided below.

New nonresidential investment

Estimates of investment for new nonresidential assets

by industry are generally derived in four steps. First,

controls for annual investment in total equipment and

in total structures for each industry and major industry group are derived as described in the section on

“Investment controls by industry” below. Second, limited modifications, as described in “Investment controls by type of asset,” are made to the NIPA estimates

of new investment by type of asset to make these estimates consistent with the conceptual basis underlying

the net stock estimates. Third, these two series are reconciled; that is, the industry controls are adjusted so

that total equipment and total structures summed over

all industries equal the corresponding asset totals from

the modified NIPA estimates. (The differences between

these two sets of investment totals are due to differences in definition and measurement problems with

both sets of estimates. For the NIPA estimates of investment in fixed assets, these problems include the

use of shipments data to estimate purchases of equipment and the allocation of these purchases among final

users. For the estimates of investment by industry, they

include gaps in coverage.) The adjustments are either

prorated among all industries or added to a few industries based on BEA’s assessment of the relative quality

of the various sources of industry investment data. Finally, distributions of industry investment by asset

from the capital flow tables are used to distribute the

adjusted industry totals to detailed assets. In this final

process, an iterative procedure is used to ensure that:

(1) The detailed asset estimates summed over all industries equal the corresponding NIPA estimates; and

(2) the totals for equipment and for structures for each
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–17

industry approximate as closely as possible the controls

derived in the first step. As the source data for each

industry do not include expenditures for software,

software expenditures are distributed to industries

based on NIPA data on expenditures for personal computers (for prepackaged software) and on NIPA data

on expenditures for computer processors (for custom

and own-account software).

Investment controls by industry. As summarized

above, the first step in constructing estimates of investment in new nonresidential fixed assets by industry is

the derivation of controls for annual investment in total equipment and total structures for each industry

and major industry group. To prepare stock estimates

for each industry beginning with 1947, BEA must derive control totals for investment in new nonresidential

fixed assets by industry back to earlier years (1921 for

most types of equipment and before 1900 for most

types of structures). To derive stock estimates by major

industry group for 1925–1946, it is necessary to derive

control totals for investment in new nonresidential

fixed assets for farms, for manufacturing, and for nonfarm nonmanufacturing before 1900.

For early years for which neither capital expenditures data nor balance sheet data are available for a

particular industry, the investment estimates are interpolated and extrapolated using related data on expenditures for the types of fixed assets purchased by the

industry. For the most recent year, where industry capital expenditures data are not yet available, industry-specific indicator series and NIPA investment data

by type of asset are used to estimate investment in fixed

assets by industry.

Farms. Estimates of investment by the farm industry

beginning with 1910 are based on investment data

available from the U.S. Department of Agriculture

(USDA) and on NIPA data. These estimates are extrapolated using the estimates of Gallman and of

Towne and Rasmussen to derive estimates for earlier

years.40

Agricultural services, forestry, and fisheries. Estimates

of investment by the Agricultural services, forestry, and

fisheries industry beginning with 1994 are extrapolated using ACES data and NIPA data. For 1947–1993,

estimates are based on P&E data and NIPA data. These

estimates are extrapolated using the investment estimates for the farms industry to derive estimates for the

years before 1947.

Mining. Estimates of investment in the mining in40. Robert E. Gallman, “Commodity Output, 1829–1899” and Marvin W.

Towne and Wayne D. Rasmussen, “Farm Gross Product and Gross Investment in the Nineteenth Century,” in Trends in the American Economy in the

Nineteenth Century, Studies in Income and Wealth, vol. 24 (Princeton, NJ:

Princeton University Press, for the National Bureau of Economic Research,

1960).

dustry are based on expenditures data for establishments with payroll available from the census of

mineral industries for 1954, 1958, 1963, 1967, 1972,

1977, 1982, 1987, and 1992. Data for equipment only is

available for 1939. Expenditures for the oil and gas extraction industry are adjusted to include establishments without payroll, using data on the value of

shipments from the Census Bureau’s annual survey of

oil and gas. Data are not available for making similar

adjustments to other mining industries; investment by

establishments without payroll in these other industries is considered to be very small. The census data for

all mining industries are adjusted to include investment by CAO’s using investment data from the Census

Bureau’s Enterprise Statistics.

Estimates of investment in structures for the oil and

gas extraction industry—which include expenditures

for plants and both capitalized and expensed drilling

and exploration costs—beginning with 1994 are extrapolated using ACES data and NIPA data on investment in mining structures. For noncensus years

between 1947 and 1993, estimates are derived by interpolating between and extrapolating from census year

estimates using P&E data and NIPA data for investment in mining structures. Estimates for years before

1947 are extrapolated using the following sources: For

1929–1946, the NIPA series on investment in petroleum and natural gas exploration, shafts, and wells; for

1901–1928, data on the value of petroleum production

from the Census Bureau’s Historical Statistics of the

United States.41

Estimates of investment in structures for other mining industries beginning with 1994 are extrapolated

using ACES data and NIPA data. For noncensus years

between 1947 and 1993, estimates are derived by interpolating between and extrapolating from census year

estimates using the P&E data and NIPA data. Estimates

for years before 1947 are extrapolated using data on

the value of mining production by industry from Historical Statistics.

Estimates of investment in equipment by mining industries beginning with 1994 are extrapolated using

ACES data and NIPA data. For noncensus years between 1947 and 1993, equipment estimates are derived

by interpolating between and extrapolating from census year estimates using the P&E data and NIPA data.

For years before 1947, estimates are extrapolated using

data on the value of shipments of mining and oil field

equipment from the census of manufactures for 1925,

1927, 1929, 1933, 1935, and 1939, and annual data on

the value of mining production by industry from

41. U.S. Department of Commerce, Bureau of the Census, Historical Statistics of the United States, Colonial Times to 1970, 2 vols. (Washington, D.C.:

U.S. Government Printing Office, 1975).
M–18 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

Historical Statistics.

Construction. Estimates of investment for establishments with payroll in the construction industry are

available from the census of construction industries for

1967, 1972, 1977, 1982, 1987, and 1992. These estimates are adjusted to include establishments without

payroll using receipts data from the censuses and are

adjusted to include CAO’s using investment data from

Enterprise Statistics. Census estimates for subdividers

and developers are excluded because these establishments are classified by the SIC in the real estate industry (SIC 65).

Estimates of investment in structures beginning

with 1994 are extrapolated using ACES data and NIPA

data. For noncensus years between 1947–1993, estimates are derived by interpolating between and extrapolating from census year estimates using P&E data

and NIPA data. For years before 1947, structures estimates are extrapolated using the following sources: For

1921–1946, the estimates of Boddy and Gort; and for

1900–1920, the F.W. Dodge series on the value of construction contract awards from Historical Statistics.42

Estimates of investment in equipment beginning

with 1993 are extrapolated using ACES data and NIPA

data. For noncensus years between 1947 and 1992, estimates are derived by interpolating between and extrapolating from census year estimates using the P&E

data and NIPA data on investment in construction

tractors and other machinery. For years before 1947,

equipment estimates are extrapolated using the estimates of Boddy and Gort.

Manufacturing. Estimates of investment in the manufacturing industry are available for establishments

with payroll from the census of manufactures for 1947,

1954, 1958, 1963, 1967, 1972, 1977, 1982, 1987, and

1992. Beginning with 1977, adjustments are made to

include establishments without payroll (the adjustment is carried forward to 1997). Before 1977, no data

are available for making the adjustments, but investment by these establishments is very small. The census

data for all manufacturing industries are adjusted to

include investment by CAO’s, using investment data

from Enterprise Statistics.

Estimates of investment in equipment and structures for noncensus years beginning with 1947 are derived by interpolating between and extrapolating from

census year estimates using capital expenditures data

from the ASM and NIPA data. For years before 1947,

equipment investment estimates are extrapolated using the following sources: For 1941–1946, the NIPA series for investment in industrial equipment; for

42. Rayford Boddy and Michael Gort, “Capital Expenditures and Capital

Stocks,” Annals of Economic and Social Measurement, 1973; and “The Derivation of Investment Expenditures and Capital Stocks,” Mimeo, 1968.

1921–1940, the estimates of Chawner, Kuznets, and

Shaw.43 For years before 1947, structures estimates are

extrapolated using the following sources: For 1929–

1946, the NIPA estimates of investment in industrial

buildings; for 1915–1928, estimates of the value of new

construction put in place for industrial buildings from

the U.S. Department of Commerce’s Construction Statistics 1915–1964;44 and for 1900–1914, balance sheet

data from the census of manufactures for 1900, 1904,

1909, and 1914 and the F.W. Dodge series on the value

of construction contract awards from Historical Statistics.

Motor vehicle industry equipment estimates before

1972 are adjusted to include investment in special tools

and dies, which is excluded from the pre-1972 census

data. Estimates of investment for the industrial machinery and equipment industry for census years prior

to 1982 are adjusted to include the value of computers

leased to other industries.45

Railroad transportation. Estimates of investment in

structures by the railroad industry beginning with

1929 are based on the NIPA series on investment in

railroad structures. Estimates of investment in replacement track for the years before 1929 are based on data

published by the Interstate Commerce Commission

(ICC) in Transport Statistics in the United States.46 Estimates of investment in structures other than replacement track for the years before 1929 are based on the

following sources: For 1915–1928, the data on the

value of new construction put in place for railroads

from Construction Statistics, 1915–1964; and for

1900–1914, data from a study by Melville Ulmer.47

Investment estimates for equipment beginning with

1994 are extrapolated using ACES data and NIPA data.

For 1977–1993, estimates are based on P&E data and

NIPA data. Before 1977, estimates are based on capital

expenditures data from Transport Statistics and the

43. Lowell J. Chawner, “Capital Expenditures for Manufacturing Plant

and Equipment—1915 to 1940,” SURVEY 21 (March 1941): 9–15; “Capital

Expenditures in Selected Manufacturing Industries,” Survey 21 (December

1941): 19–26; and “Capital Expenditures in Selected Manufacturing Industries, Part II,” Survey 22 (May 1942): 14–23. Simon Kuznets, Capital in the

American Economy: Its Formation and Financing (Princeton, NJ): Princeton

University Press, for the National Bureau of Economic Research, 1961. William H. Shaw, Value of Commodity Output Since 1869 (Princeton, NJ): Princeton University Press, for the National Bureau of Economic Research,

1947.

44. U.S Department of Commerce, Business and Defense Services

Administration, Construction Statistics 1915–64; A Supplement To Construction Review (Washington, D. C.:U.S. Government Printing Office,1966)

45. These adjustments are not made to the estimates for census years after

1982 because leased computers are included in the data on equipment

expenditures from the census of manufactures and from Enterprise Statistics.

46. Interstate Commerce Commission, Transport Statistics in the United

States, Washington D.C: U.S. Government Printing Office, annually.

47. Melville J. Ulmer, Capital in Transportation, Communications, and

Public Utilities: Its Formation and Financing (Princeton, NJ): Princeton University Press, for National Bureau of Economic Research, 1960.
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–19

American Association of Railroads, on the NIPA series

on investment in railroad equipment, and on P&E

data.

Local and interurban passenger transit. Estimates of

investment in structures by the local and interurban

passenger transit industry beginning with 1994 are

extrapolated using ACES data and NIPA data. For

1973–1993, estimates are based on P&E data and NIPA

data. Before 1973, structures estimates are derived for

two categories: Electric railway and trolley and “other.”

For electric railway and trolley, the following series are

used: For 1959–1972, balance sheet data from Transport Statistics and P&E data; for 1915–1958, the series

on the value of new construction put in place for local

transit from Construction Statistics, 1915–1964; and for

estimates before 1915, data from Ulmer’s study. For the

“other” category, the following sources are used: For

estimates for 1940–1972, capital expenditures data

from Transport Statistics and P&E data; and for estimates before 1940, data from Ulmer’s study.

Estimates of investment in equipment beginning

with 1994 are extrapolated using ACES data and NIPA

data. For 1973–1993, estimates are based on P&E data

and NIPA data. Before 1973, equipment estimates are

derived separately for four categories: Buses, electric

railway and trolley, taxicabs, and “all other.” For buses,

the estimates for 1940–1972 are based on capital expenditures data from Transport Statistics, from Transit

Fact Book, and on P&E data; the estimates for

1921–1939 are based on data from Ulmer’s study.48 For

electric railway and trolley equipment, the estimates

for 1940–1972 are based on capital expenditures data

from the Transit Fact Book and P&E data; the estimates

for 1921–1939 are based on data from Ulmer’s study.

For taxicabs, the estimates for 1929–1972 are based on

data from the International Taxicab Association, on

the NIPA series on investment in new autos, and on

P&E data; estimates for 1921–1928 are based on data

from Ulmer’s study. For “all other” equipment, estimates for 1940–1972 are based on capital expenditures

data from Transport Statistics and P&E data; estimates

for 1921–1939 are based on data from Ulmer’s study.

Trucking and warehousing. Estimates of investment

by the trucking and warehousing industry beginning

with 1994 are extrapolated using ACES data and NIPA

data. For census years between 1977–1993, estimates

are based on P&E data and are adjusted to include the

unregulated portion of the industry using information

from the census of wholesale trade and the census of

transportation. Investment estimates for noncensus

years between 1977–93 for the unregulated portion of

the industry are derived by interpolating between and

48. American Public Transit Association, 1996 Transit Fact Book. (Washington, D.C.: 1996).

extrapolating from census year estimates using the

P&E series and NIPA data.

For noncensus years between 1940 and 1977, estimates of investment by the regulated portion of the industry are based on balance sheet data from Transport

Statistics. For years before 1940, estimates are extrapolated using the following sources: For 1929–1939, the

NIPA series on investment in trucks, buses, and truck

trailers; and for estimates before 1929, data from Ulmer’s study and from the American Trucking Association.

Water transportation. Estimates of investment in

structures in the water transportation industry beginning with 1994 are extrapolated using ACES data and

NIPA data. For 1977–1993, estimates are based on P&E

data and NIPA data. Estimates for 1940–1976 are based

on balance sheet data from Transport Statistics and on

P&E data; and before 1940, estimates are extrapolated

using data from Historical Statistics on the number of

ships built.

Estimates of investment in equipment beginning

with 1994 are extrapolated using ACES data and NIPA

data. For 1977–1993, estimates are based on P&E data

and NIPA data. Estimates for 1940–1976 are based on

the following sources: Balance sheet data from

Transport Statistics, the NIPA series on investment in

ships and boats, and P&E data. For 1929–1939, estimates are based on the NIPA series on investment in

ships and boats; estimates for 1921–1928 are based on

data from Historical Statistics on the number of ships

built. The data for equipment are adjusted to include

the value of ships and boats owned and leased to other

industries.

Transportation by air. Investment estimates for the

transportation by air industry beginning with 1994 are

extrapolated using ACES data and NIPA data. For

1965–1993, estimates are based on balance sheet data

published by the U.S. Department of Transportation,

on P&E data, and on NIPA data.49 Before 1965,

estimates are based on the following sources: For

1929–1964, the NIPA series on investment in aircraft;

for years before 1929, data on air carrier operations

from Historical Statistics.

Pipelines, except natural gas. Estimates of investment

in structures by the pipelines (except natural gas) industry beginning with 1994 are extrapolated using

ACES data and NIPA series data. For 1983–1993, estimates are based on P&E data and NIPA data. For

1929–1982, estimates are based on the NIPA series on

investment in petroleum pipeline structures. For

49. For 1973–1993, estimates of investment by medium and small private

commercial air carrier operations are developed using U.S. Department of

Transportation data on the number of planes owned by small carriers and

are included in the estimate of investment by the air transportation industry. 
M–20 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

1915–1928, estimates are based on the value of new

construction put in place for petroleum pipelines from

Construction Statistics, 1915–1964; for 1900–1914, estimates are extrapolated using data from Historical Statistics on petroleum production.

Estimates of investment in equipment beginning

with 1994 are extrapolated using ACES data and NIPA

data. For 1977–1993, estimates are based on P&E data

and on the NIPA series on investment in petroleum

pipeline structures. For 1942–1976, estimates are based

on data from Transport Statistics on capital expenditures and on P&E data; for 1921–1941, estimates are

extrapolated using the same data sources as those used

for the estimates of structures.

Transportation services. Investment estimates for the

transportation services industry—most of which consists of expenditures by establishments engaged in

freight forwarding and in the rental of railroad cars—

beginning with 1994 are extrapolated using ACES data

and NIPA data. For 1973–1993, estimates are based on

P&E data and NIPA railroad equipment data. Estimates for 1945–1972 are based on balance sheet data

from Transport Statistics, on trade association data, on

the NIPA series on investment in railroad equipment,

and on P&E data. For years before 1945, estimates are

extrapolated using the investment flows for the railroad transportation industry.

Telephone and telegraph. The telephone and telegraph industry includes establishments engaged in

telephone and nonvocal message communications and

in satellite tracking. (Online information retrieval services are classified in business services.) Estimates of

investment in equipment and structures beginning

with 1994 are extrapolated using ACES data and NIPA

data. For 1972–1993, estimates are based on data from

the following sources: Industry annual reports made to

the Federal Communications Commission (FCC),

USDA Rural Utility Service (RUS—formerly the Rural

Electrification Administration), trade association data,

P&E data, company annual reports, and the Census

Bureau data on construction-put-in-place.

Estimates of investment in structures for years before 1972 are based on the following sources: For

1929–1971, the NIPA series on investment in telecommunications structures; for 1915–1928, data from

Construction Statistics 1915–1964 on the value of new

construction put in place for the telephone and telegraph industry; and for 1900–1914, data from Ulmer’s

study.

Investment by rural telephone cooperatives in telephone and telegraph equipment for years before 1972

is estimated using RUS data. Estimates of investment

in equipment by private businesses other than cooperatives before 1972 are based on the following

sources: For 1947–1971, industry reports to the FCC,

trade association data, P&E data, company annual reports, and data from a study by Crandall; and for

1921–46, data from Ulmer’s study.50

Radio and television. This industry includes establishments providing cable, satellite, and other pay television services. Estimates of investment by radio and

television establishments classified as nonprofit institutions primarily serving individuals are derived from

Census Bureau data and are reclassified to the real estate industry. Estimates of investment in the radio and

television industry beginning with 1994 are extrapolated using ACES data and NIPA data. For 1947–1993,

estimates are based on the following sources: P&E

data, unpublished census data, and trade association

data. For years before 1947, estimates are extrapolated

using data from the Boddy and Gort studies.

Electric services. Estimates of investment in the electric services industry includes investment by investor-owned electric services, nonpublic cooperative

electric services, nonutility electric services, and the

electric services portions of combination utilities including nonpublic combination utilities. Nonutilities

include cogenerators and independent power producers. Estimates of investment beginning with 1997 are

based on the NIPA electric light and power structures

series and on ACES data. For 1972–1996, estimates are

based on U.S. Department of Energy (DOE) data, on

RUS data, on Census Bureau data, and on the NIPA

data.

Before 1972, estimates of investment in structures

are based on the following sources: For 1929–1971, the

NIPA series on investment in electric light and power

structures; for 1915–1928, data from Construction Statistics, 1915–1964 on the value of new construction

put in place for electric light and power; and for

1900–1914, data from Ulmer’s study. These data are

adjusted from a “value-put-in-place” basis to a

“when-completed” basis as described in the section

“Investment controls by type of asset.”

Before 1972, estimates of investment in equipment

are based on the following sources: For rural electric

cooperatives, RUS data; for private business other than

cooperatives for 1937–1971, DOE data and P&E data,

and for 1921–36, data from Ulmer’s study.

Gas services. Investment estimates for the gas services industry include investment by the following

types of establishments: Natural gas transmission and

distribution, certain types of manufactured gas production, and the gas portions of combination utilities.

Natural gas exploration and natural gas production are

50. Robert W. Crandall, After the Breakup: U.S. Telecommunications in a

More Competitive Era, (Washington D.C.: Brookings Institution, 1991).
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–21

classified in oil and gas extraction. Estimates beginning

with 1929 of investment in structures are based on the

NIPA data on investment in gas utility structures. Before 1929, structures estimates are based on the following sources: For 1915–1928, the data from

Construction Statistics, 1915–1964 on the value of new

construction put in place for gas; and for 1900–1914,

data from Ulmer’s study.

Estimates of investment in equipment beginning

with 1994 are extrapolated using ACES data and NIPA

data. For 1973–1993, estimates of investment in equipment are based on P&E data, NIPA data, and trade association data; for 1946–1972, estimates are based on

industry reports to the Census Bureau and P&E data.

For 1921–1945, estimates are based on data published

by the American Gas Association in Gas Facts.51

Sanitary services. Estimates of investment by the

sanitary services industry include investment by the

following types of establishments: Water supply, sanitary services, steam and air-conditioning supply, irrigation systems, and other utility portions of

combination utilities. Estimates beginning with 1994

are extrapolated using ACES data and NIPA data. For

1973–1993, estimates are based on P&E data, DOE

data, and trade association data; estimates for 1947–

1972 are based on P&E data. Before 1947, these data

are extrapolated using data from Ulmer’s study.

Wholesale trade. The wholesale trade industry includes merchant wholesalers—which are wholesale entities that take title to the assets they sell—and

nonmerchant wholesalers—which consist of manufacturers’ sales branches, sales offices and agents, brokers,

and commission merchants. Investment data for merchant wholesale establishments are available from the

capital expenditures survey conducted as part of the

census of wholesale trade for 1958, 1963, 1967, 1972,

1977, 1982 and from the assets and expenditures survey (AES) conducted as part of the 1987 and 1992 economic censuses. Beginning with 1978, estimates of

investment by merchant wholesalers are adjusted to include expenditures related to CAO’s and establishments without payroll.52

Estimates of investment by nonmerchant wholesalers (which include estimates for equipment owned by

nonmerchant wholesalers but leased to other industries) for 1982, 1987, and 1992 are based on data from

Enterprise Statistics, the census of wholesale trade, and

trade association data. For census years prior to 1982,

51. American Gas Association, Gas Facts, annual.

52. Although CAO’s are included in the AES results for merchant wholesalers, the capital expenditures related to them may be reduced when the

AES results are adjusted to the results of the census of wholesale trade

(which excludes CAO’s). Beginning with 1982, BEA adjusted the wholesale

trade estimate for merchant wholesale CAO’s.

estimates of investment in equipment are based on

Census employment data while estimates of investment in structures are based on Census inventories

data. The estimates of investment in equipment by

nonmerchant wholesalers are adjusted to include the

value of computers owned by manufacturers’ sales

branches and leased to other industries. No adjustments are made for establishments without payroll,

because investment by these establishments is considered to be very small. Estimates of investment by nonmerchant wholesalers are added to the merchant

wholesale estimates to derive estimates of investment

by the entire wholesale trade industry for Census years.

Investment estimates for the total wholesale industry

beginning with 1994 are extrapolated using ACES data

and NIPA data. For noncensus years between 1947 and

1993, estimates are derived by interpolating between

and extrapolating from the census year estimates using

P&E and NIPA data; for years before 1947, estimates

are extrapolated using data from Boddy and Gort.

Retail trade. Investment data for retail trade establishments are available from the capital expenditures

survey taken as part of the census of retail trade for

1958, 1963, 1967, 1972, 1977, and 1982 and from the

assets and expenditures survey taken as part of the

1987 and 1992 economic censuses. These surveys cover

all of retail trade, including establishments with payroll, CAO’s, and except for 1982 and 1987, establishments without payroll. Estimates for 1982 and 1987

are adjusted for establishments without payroll.

Estimates of investment for the retail trade industry

beginning with 1994 are extrapolated using ACES data

and NIPA data. For noncensus years between 1947 and

1993, estimates are interpolated between and extrapolated from census year estimates, using P&E data and

NIPA data. For years before 1947, investment estimates

are extrapolated using the following sources: For

1915–1946, the series on value of new construction put

in place for stores, restaurants, and garages from Construction Statistics, 1915–1964; and before 1915, the

F.W. Dodge series on the value of construction contract awards from Historical Statistics.

Finance and insurance. Investment estimates for the

finance and insurance industry are adjusted to account

for leased assets that are not accounted for by the

source data series. Investment estimates for this industry were available for most establishments for the first

time in the 1992 census of finance, insurance, and

real estate. Beginning with 1994, the census data are

extrapolated forward using ACES data and NIPA data.

For 1947–1993, investment estimates are derived from

P&E data and from trade association data. Before

1947, estimates are extrapolated using balance sheet

data from Statistics of Income and data from Historical
M–22 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

Statistics on the activities of the finance and insurance

industries. Estimates of investment by insurance and

holding company establishments that are classified as

nonprofit institutions primarily serving individuals are

derived mainly from Census data on tax and tax-exempt payrolls and revenues and are reclassified to the

real estate industry.

Real estate, with nonprofit institutions serving individuals. This industry includes establishments of the

real estate industry and also establishments of nonprofit institutions serving individuals, which, by NIPA

convention, are classified in the real estate industry

rather than in the industry of their primary activity.

Investment estimates for both of these components beginning with 1994 are extrapolated using ACES data

on equipment and on structures and NIPA data. Estimates for 1972–1993 are based on the following series:

P&E data, data from the census of construction industries, NIPA data, trade association data, and the series

for investment by nonprofit institutions serving individuals, which is based mainly on Census data on tax

and tax-exempt payrolls and revenues (see the radio

and television, finance and insurance, and services industries sections of this document). For 1947–1971,

investment estimates for nonprofit institutions serving

individuals are derived from Census data. For entities

reporting rental income on IRS Schedule E, investment

estimates are derived using the percentage of total industry investment made up of investment by those entities from Statistics of Income data on investment for

1977 and data on depreciation for 1960, 1961, 1967,

and 1973, as well as the NIPA series for investment in

commercial structures. For sole proprietorships, partnerships, and corporations, investment estimates are

based on the P&E data. For 1915–1946, investment estimates are extrapolated using the following series on

the value of new construction put in place from Construction Statistics, 1915–1964: For nonprofit institutions that primarily serve individuals, total investment

in structures by religious, educational, hospital and institutional, and amusement and recreational buildings;

for the remainder of this industry, commercial buildings. For 1900–1914, the structures estimates are extrapolated using the F.W. Dodge series on the value of

construction contract awards from Historical Statistics.

Services except health, legal, educational, and “other.”

Investment data for these services industries are available for equipment and for structures for 1972, 1977,

1982, 1987, and 1992 and for the total of equipment

and structures for 1958, 1963, and 1967, from the capital expenditures survey taken as part of the census of

service industries through 1982 and from the assets

and expenditures survey taken as part of the censuses

for 1987 and for 1992.

The investment estimates include CAO’s, establishments with payroll, and establishments without payroll. Estimates of investment for selected service

industries are also adjusted for the value of certain

types of equipment owned by these industries and

leased to other industries as follows: Autos, trucks, and

trailers in the auto repair, services, and parking industry and aircraft, furniture and fixtures, construction

machinery (except tractors), computers (other than

those leased by the manufacturers or by manufacturers’ sales branches), and other types of equipment in

the business services industry. Estimates of investment

by nonprofit institutions in the hotel and amusement

and recreation industries that primarily serve individuals are derived from Census Bureau data and are reclassified to the real estate industry.

Investment estimates for these service industries beginning with 1994 are extrapolated, in most instances,

using ACES data and NIPA data. Investment estimates

for noncensus years between 1977 and 1993 are interpolated and extrapolated from census year estimates

using one or more of the following sources: P&E data,

various types of NIPA structures or equipment investment data, trade association data, Census

value-put-in-place structures data, and other indicator

series based on NIPA or trade association data where

two-digit SIC industry-specific capital expenditures

series are not available.53 For noncensus years between

1947 and 1977, investment estimates are derived by interpolating between and extrapolating from census

year estimates using P&E data and NIPA data. Before

1947, estimates are extrapolated using balance sheet

data from Statistics of Income.

Health services. The health services industry consists

of two components: Hospitals and “other” health services. Hospital capital expenditures are available for

1987 and for 1992. Hospital investment for other census years are derived from P&E and NIPA data. Data

on the investment of “Other” health services are

available from the capital expenditures survey taken as

part of the census of service industries for 1982 and

from the assets and expenditures survey taken as part

of the census of service industries for 1987 and for

1992. The investment estimates include CAO’s, establishments with payroll, and establishments without

payroll.

Investment estimates beginning with 1994 are

extrapolated using ACES data and NIPA data. For noncensus years between 1947 and 1993, estimates are interpolated and extrapolated from census year estimates

using P&E data and NIPA data. Before 1947, invest53. SIC Industries 70–79 are all included in the single P&E series “personal and business services.”
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–23

ment estimates are extrapolated using balance sheet

data from Statistics of Income. Estimates of investment

by hospitals and other health services establishments

classified as nonprofit institutions primarily serving

individuals are derived from Census Bureau and trade

association data and are reclassified to the real estate

industry.

Legal services. Data on investment for legal services

are available from the capital expenditures survey

taken as part of the census of service industries for

1982 and from the assets and expenditures survey

taken as part of the census of service industries for

1987 and for 1992. Investment for other census years is

derived using P&E and NIPA data.

Investment estimates beginning with 1993 are extrapolated using ACES data and NIPA data. Estimates

for noncensus years between 1947 and 1992 are interpolated and extrapolated from census year estimates,

using P&E data and NIPA data. Before 1947, investment estimates are extrapolated using balance sheet

data from Statistics of Income. Estimates of investment

by legal services establishments that are classified as

nonprofit institutions primarily serving individuals are

derived from Census Bureau data and are reclassified

to the real estate industry.

Educational and “other” services. Data on investment

for selected portions of educational services (correspondence and vocational schools), selected portions

of “other” services (engineering, research, and management services), and selected portions of social services (job training and vocational rehabilitation, child

day care, and residential care) are available from the

assets and expenditures survey taken as part of the census of service industries for 1987.54 Coverage was expanded in the assets and expenditures survey for 1992

to include capital expenditures by the following industry components: Libraries, museums and art galleries,

part of membership organizations, and accounting

and other professional services. The investment estimates include CAO’s, establishments with payroll, and

establishments without payroll. These Census tabulations are supplemented as necessary with P&E data

and NIPA data on investment for education buildings

for 1982 and for 1987.

Investment estimates beginning with 1994 are extrapolated using the ACES data and NIPA data. Investment estimates for noncensus years between 1982 and

1993 are interpolated and extrapolated from census

year estimates, using P&E data, NIPA data, or trade association data.

54. “Other” services industries consists of the following industries: Social

services; museums and botanical and zoological gardens; membership

organizations; engineering and management services; and services not elsewhere classified.

Estimates of investment in structures for years before 1982 are extrapolated using the following

sources: For 1947–1981, P&E data and NIPA data;

for 1929–1946, NIPA investment in educational buildings and religious buildings; for 1915–1928, data from

Construction Statistics, 1915–1964 on the value of new

construction put in place for educational buildings

and religious buildings; and for 1900–1914, balance

sheet data from Statistics of Income.

Estimates of investment in equipment for years before 1982 are extrapolated using the following sources:

For 1947–1981, P&E data and NIPA data; before 1947,

the same sources as those used for structures. Estimates of investment by educational and “other” services establishments by nonprofit institutions that

primarily serve individuals are derived from U.S. Department of Education data and Census Bureau data

and are reclassified to the real estate industry.

Investment controls by type of asset. As summarized above, the second step in constructing estimates

of investment in new nonresidential fixed assets by industry is the derivation of estimates of investment by

type of asset. Beginning with 1929, estimates are derived from the NIPA series on nonresidential fixed investment, a component of gross private domestic

investment. In order to derive stock estimates for early

years, the NIPA estimates are extrapolated back to the

19th century using data from various public and private

sources.55

Limited modifications are made to the NIPA estimates in accordance with the conceptual basis underlying estimates of net stocks. The NIPA estimates of

investment in electric light and power structures are

modified so that the estimates of stock and depreciation will reflect the availability of the capital assets for

use in production and will be consistent with the timing of tax depreciation. Specifically, the NIPA estimates

are modified from a “value-put-in-place” basis (that is,

the value of new construction put in place in a particular year for both completed plants and plants under

construction in that year) to a “when-completed” basis

(that is, the value of plants actually completed and put

into service during the year). NIPA estimates for other

55. These sources are as follows: William H. Shaw, Value of Commodity

Output Since 1869, Princeton, NJ: Princeton University Press, for the

National Bureau of Economic Research, 1947; U.S. Department of Labor

and U.S. Department of Commerce, Construction Volume and Costs

1915–1956: Statistical Supplement to Construction Review, Washington,

D.C.: U.S. Government Printing Office, 1958; Simon Kuznets, Capital in the

American Economy: Its Formation and Financing, Princeton, NJ: Princeton

University Press, for the National Bureau of Economic Research, 1960; U.S.

Department of Agriculture, Farm Income Situation, Washington, D.C.: U.S.

Government Printing Office, 1965; and Robert E. Gallman, “Commodity

Output,” and Marvin W. Towne and Wayne D. Rasmussen, “Farm Gross

Product and Gross Investment.” Both are in Trends in the American Economy in the Nineteenth Century, vol. 24 (Princeton , N.J.): Princeton University Press, for the National Bureau of Economic Research, 1960. 
M–24 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

types of structures are not modified because the value

of uncompleted structures has been both small and

stable relative to the value of completed plants. For

electric light and power plants, however, the value of

uncompleted plants has been large, and the ratio of

this value to the value of completed plants has fluctuated significantly over time.

Adjustment of industry controls. As summarized

above, BEA adjusts the industry controls so that the

all-industry totals equal the NIPA totals for new investment in fixed assets. In this process, the data from the

economic censuses and ASM are assumed to be the

most accurate: Controls for census years for census-covered industries and controls for manufacturing

industries in noncensus years are adjusted only where

they differ significantly from the NIPA totals. For industries not covered by the economic census in census

years, and for nonmanufacturing industries in noncensus years, the difference between the sum of the industry controls and the sum of the NIPA estimates is

allocated to industries so that the estimates of assets totaled across industries are consistent with the NIPA totals for those assets.

Distribution by type of asset and industry. Once

the control series for investment in total equipment

and total structures by industry are adjusted to equal

the corresponding totals from the NIPAs, the industry

estimates are distributed to detailed assets using data

from BEA’s capital flow tables for 1963, 1967, 1972,

1977, 1982, and 1992. This requires the conversion of

the capital flow tables from the I-O industry classification system to the NIPA industry classification system.

Specifically, investment by nonprofit institutions that

primarily serve individuals is reclassified to the real estate industry; investment in mining exploration,

shafts, and wells is reclassified from construction to the

mining industries; and own-account construction is

reclassified from the construction industry to the industries performing the construction.56 The detailed

type-of-asset-by-industry distributions are then converted from a use basis to an ownership basis using

data from unpublished I-O studies, from industry

trade associations, and from secondary sources. These

modifications yield the detailed type-of-asset-by-industry distributions for equipment and structures for

1963, 1967, 1972, 1977, 1982, and 1992. BEA did not

release a capital flow table on a use basis for 1987; however, a table on an ownership basis was developed specifically to distribute industry estimates to detailed

56. Own account construction is that performed by a business or government entity acting as its own builder or contractor. Examples of own

account construction are expenditures on engineers employed by State

highway departments to design highways and remodeling crews employed

by realtors.

assets. This unpublished table was based on the 1982

and 1992 capital flow tables, 1987 economic census

data, P&E data, I-O studies, trade association data,

NIPA data, and other sources. Software investment by

industry is not included in the capital flow tables; it is

allocated by industry using computer investment by

industry.

For years between 1963–1992 not covered by capital

flow tables, the estimates of investment in total equipment and total structures by industry are distributed to

detailed assets by interpolating between and extrapolating from the modified capital flow distributions, including the unreleased table for 1987. For years before

1963, the 1963 table is extrapolated back, and for years

beginning with 1993, the 1992 table is extrapolated

forward. Once these initial distributions are made, an

iterative process is used to ensure that: (1) All-industry

totals for investment in each type of asset equal the totals of the NIPA estimates by type of asset and (2) industry totals for equipment and for structures

approximate as closely as possible the industry control

totals derived from the independent sources described

above and in Table A.

The exact iterations used to reconcile the industry

controls with the NIPA estimates differ for different

periods and for equipment and structures. For years

before 1972, detailed estimates of structures and

equipment by type of asset and by industry are derived

as follows. First, the industry controls of investment in

total equipment and in total structures are estimated.

Second, these industry controls are allocated to assets

using the interpolated or extrapolated capital flow distributions (as described in the previous paragraph).

Third, these allocations are totaled across industries

and adjusted to equal, in total, the NIPA controls for

each type of asset. Fourth, the totals for each industry

are recalculated and the second and third steps are repeated so that the following two balancing conditions

are met: (1) All industry totals for investment in each

type-of-asset equal the NIPA new investment by type

of asset totals; and (2) totals for industry investment

for equipment and for structures approximate as

closely as possible the industry control totals derived

from independent sources.

Beginning with 1972, detailed investment in new

equipment by type of asset and by industry is estimated in a similar manner. First, the industry estimates of investment in total equipment are adjusted so

that the sum across all industries equals the NIPA estimate of investment in total equipment. Second, these

adjusted industry controls are allocated to assets using

the interpolated or extrapolated capital flow distributions as described above. Third, these allocations are

totaled across industries and adjusted to equal, in total,
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–25

the NIPA controls for each type of asset. The differences between the NIPA estimates and the sum across

all industries of investment in detailed types of equipment are allocated to nonmanufacturing industries on

the basis of the allocations performed in the second

step, using the interpolated and extrapolated capital

flow distributions.57 Fourth, each nonmanufacturing

industry equipment total is adjusted accordingly, so

that the sum across all industries of investment in total

equipment equals the NIPA estimate of total investment in new equipment. Fifth, several iterations may

be performed until investment is balanced—that is,

until the sums by industry and asset type equal the

NIPA estimates and are as close as possible to the industry controls. (As noted above, software investment

by industry is not included in the capital flow tables

and is allocated by industry using computer investment by industry.)

For structures, the process is similar, but the differences between the NIPA estimates and the industry

controls are allocated differently for 1972–1992 and for

years beginning with 1993. For the 1972–1992 period,

the estimates are modified by an iterative balancing

process similar to that described for years before 1972,

until additional iterations yield only small improvements in the allocations by type of asset and by industry. For industries other than mining and utilities, the

remaining residual differences between NIPA estimates

of new structures by type of structures and the sum

across all industries of detailed structures are allocated

to the real estate industry.58 For the mining and utilities

industries, the remaining residual differences are allocated to mining and utilities. Beginning with 1993, detailed investment in new structures by type of asset and

by industry is estimated using the same procedure as

that described above for equipment.

New residential investment

Estimates of net stocks and depreciation of residential

assets are presented by industry—either farm or real

estate—and within these industries, by tenure group—

that is, tenant- or owner-occupied. Beginning with

1929, estimates of investment in new residential fixed

assets by industry are taken directly from the NIPA estimates of residential fixed investment, a component of

gross private domestic investment. For years before

57. Distributions are only made to nonmanufacturing industries because

the estimates for manufacturing industries are based on interpolations or

extrapolations of census year estimates using ASM establishment data,

which more closely approximate BEA industry definitions in terms of coverage.

58. For 1972–92, adjustments are made to estimates of investment by the

real estate industry in structures and in equipment to correct for undercoverage of both the number of establishments and the growth of capital

expenditures in structures and equipment in the P&E data on the real estate

industry. 

1929, the estimates are based on data from various

public and private sources.59

These NIPA estimates are then distributed to industries as follows. First, NIPA estimates of investment in

farm residential structures are allocated between

owner and tenant-occupied structures for both

1-to-4-unit structures and for mobile homes using

USDA data. All owner- and tenant-occupied farm residential structures owned by farm operators are included in the farm industry, while tenant-occupied

farm structures owned by nonfarm landlords are included in the real estate industry. Estimates of investment in nonfarm residential structures (dormitories,

fraternity and sorority houses, nurses’ homes, etc.) are

grouped separately and are allocated between ownerand tenant-occupied separately for 1-to-4-unit structures, 5-or-more-unit structures, and mobile homes

using information from the Census Bureau’s census of

housing (decennial) and American housing survey (biennial). All nonfarm residential structures are included

in the real estate industry. All residential equipment,

which consists of equipment owned by landlords and

rented to tenants, is also included in the real estate industry.

Net purchases of used assets

Data are available only to adjust for net purchases of

used assets among different types of owners (private

business, governments, households, and nonresidents). These data are based for the most part on

modified NIPA flows for net purchases of used assets.

Data are not available to adjust for net purchases

among industries or among legal forms of organization within the private sector.

Nonresidential assets. The largest net purchases of

used nonresidential assets between private business

and other types of owners involve sales of used autos

by private business to households, exports of used

equipment, purchases of government surplus assets,

and government purchases of privately owned public

utilities. As annual data are available on stocks and

unit values of autos by type of owner, the physical inventory method—which applies prices to direct counts

of the physical units of an asset—is used, and it is not

necessary to make explicit adjustments for net purchases of used autos among types of owners.

In the NIPAs, exports of used equipment and purchases of government surplus assets by private business

are valued at secondhand sales prices. For the stock

59. These sources are as follows: U.S. Department of Labor and U.S.

Department of Commerce, Construction Volume and Costs 1915–1956: Statistical Supplement to Construction Review (Washington, D.C.: U.S. Government Printing Office, 1958); David M. Blank, The Volume of Residential

Construction, 1889–1950 (Princeton, NJ: Princeton University Press, for the

National Bureau of Economic Research, 1954); and Historical Statistics.
M–26 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

estimates, however, these NIPA estimates of exports

and most of the estimates of government surplus assets

are revalued at their original acquisition prices less accumulated depreciation so that the value of the transferred assets is consistent with the value of the assets

remaining in the stock of the original owner. Government surplus assets that were built during wartime

with special characteristics that are of no use to their

new peacetime owners are valued at the prices that

would have been paid for equally productive new assets designed for the uses to which the surplus assets

are put by their new owners.60 Revalued estimates of

exports of used equipment and government surplus

assets are distributed by year of transfer and type of asset to industries using the following sources: For exports of used equipment, data from the Census

Bureau’s foreign trade statistics and for purchases of

government surplus assets, surplus property reports

from the General Services Administration and the U.S.

Department of Defense.

Estimates of net purchases of power plants between

the private sector and the Federal Government during

the 1980s are derived from Department of Energy

(DOE) data. Similar estimates are derived for purchases by State and local governments of privately

owned railroads, transit systems, electric utilities, and

water systems. Separate estimates of the original value

of equipment and structures are derived for utilities

and transit systems. These estimates are based on data

from the following sources: For railroads, Moody’s

transportation manuals; for transit, Moody’s transportation manuals and the American Public Transit Association; for electric utilities, Moody’s public utility

manuals and two U.S. Department of Energy publications, Statistics of Privately Owned Electric Utilities in

the United States and Statistics of Publicly Owned Electric Utilities in the United States; and for water systems,

Moody’s public utility manuals.

Residential assets. The largest net purchases of used

residential assets between private business and other

types of owners and between industries involve purchases of private housing by State and local governments, conversions of Federal military housing to

private ownership, and purchases of farm housing by

nonfarm owners. The estimates of net purchases between private business and government are derived

from the NIPA estimates; the estimates of conversions

of farm housing are derived from the census of housing. Net purchases of existing residential structures be60. The derivation and revaluation of the estimates of investment for

exports of used equipment and business purchases of government surplus

assets is explained in more detail in Robert C. Wasson, John C. Musgrave,

and Claudia Harkens, “Alternative Estimates of Fixed Business Capital in

the United States, 1925–1968,” SURVEY 50 (April 1970): 18–36.

tween government and private business consist

primarily of State and local government acquisitions of

private housing to acquire land for new roads or buildings. In the NIPAs, these net purchases are offset in estimates of government and private fixed investment

and are valued at sales prices. In the stock estimates,

however, these transferred structures are treated as

permanent losses from the housing stock rather than

as shifts from the private to the public stock. The housing involved in these purchases is removed from the

stock of the real estate industry in the year of government acquisition because they are acquired to allow

construction of highways or buildings. World War II

Federal military housing converted to private ownership after the war is estimated using NIPA data and

transferred from the Federal Government stock to the

stock of the real estate industry in the year of conversion.

The post-World War II shift of farm housing in urban fringe areas to nonfarm housing affects the industry stock estimates, but not the NIPA estimates of

investment. Estimates of the value of these net purchases are derived from the census of housing and reclassified from the farm industry to the real estate

industry in the year of transfer.

Investment by legal form of organization

The estimates of investment in new and used assets for

each industry are also distributed by legal form of organization—corporate business, which is further split

into financial and nonfinancial; sole proprietorships

and partnerships; and other private business—persons, nonprofit institutions serving individuals, and

tax exempt cooperatives. Persons and nonprofit institutions are included in the real estate industry, while

tax exempt cooperatives are included in the communications, electric utilities and wholesale industries. The

data that support the distributions do not support adjustments for shifts from one legal form to another (for

example, when an unincorporated enterprise incorporates).

Nonresidential investment. In general, investment

in nonresidential assets is allocated annually by legal

form of organization within industries by using percentages based on Census data, where available.

For the mining, construction, manufacturing, retail

trade, and selected services industries, Census data are

available for all Census years. For selected transportation, communication, utility, finance, insurance, and

real estate industries, Census coverage began in 1992.

Where Census data are used, the allocation of nonresidential investment by legal form of organization is

usually based on the proportions of total capital expenditures that are attributed to corporations, sole
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–27

proprietorships and partnerships. When data on capital expenditures by legal form of organization are unavailable, the allocations are based on data on revenue,

sales, or receipts from the economic censuses. When

necessary, adjustments are made to the Census data for

establishments without payroll and CAO’s. For noncensus years, the allocations are based on distributions

of expenditures interpolated by depreciation data from

Statistics of Income.

For industries not covered by the economic census,

percentage distributions of investment by legal form of

organization are based on the distribution-of-depreciation data by legal form from Statistics of Income.

For the farm industry beginning with 1973, the allocation to legal forms of organization is based on capital

expenditures data from USDA’s annual farm costs and

returns survey. For years before 1973, the allocation is

based on assets data from the census of agriculture.

For the telephone and telegraph industry and the

electric services industry, and wholesale trade industry,

nonresidential investment is first allocated to “other

private business;” the remainder is then allocated to

the other legal forms of organization. Within other

private business, the percentage of investment allocated to tax exempt cooperatives is based on RUS data

for the telephone and telegraph industry and the electric services industry and from the census of wholesale

trade for the wholesale industry. The percentage allocated to persons is based on investment by entities reporting rental income on nonresidential property on

IRS Schedule E, derived from data on investment and

depreciation from Statistics of Income. The percentage

allocated to nonprofit institutions that primarily serve

individuals is derived from data from the following

sources: the economic censuses for 1982, 1987, and

1992; Census Bureau data on the value of new construction put in place; trade association data; American Hospital Association data; and DOE data. The

remaining investment is then distributed between corporate business and sole proprietors and partnerships.

For the telephone and telegraph industry, the percentages for years before 1992 are based on capital expenditures data from RUS, the FCC, the United States

Telephone Association, and company annual reports;

for years after 1992, percentages are based on estimates

derived from the economic censuses extrapolated by

RUS, FCC, and trade data and depreciation from Statistics of Income. For the electric services industry, the

percentages for years before 1992 are based on capital

expenditures data from RUS and DOE. Those after

1992 are derived from census data extrapolated by

RUS, DOE, and trade data and depreciation from Statistics of Income. For the wholesale industry, percentages are based on data from economic censuses,

adjusted where necessary for non-employers and

CAO’s. Where these data are not available, the percentages are based on depreciation data from Statistics of

Income.

For the real estate industry for 1992 forward, the

percentages of investment allocated to each legal form

are based on economic census data for 1992 extrapolated by Statistics of Income data on depreciation. For

years before 1992, the percentages are based on these

same depreciation data.

Residential investment. Among private businesses,

only the farm and real estate industry invest in residential assets. For the farm industry, estimates of investment in owner-occupied residential assets are assigned

by convention to sole proprietorships and partnerships; investment in tenant-occupied residential assets

is distributed to all legal forms of organization using

USDA data. For the real estate industry, estimates of

investment in owner-occupied residential assets and

other nonfarm residential structures (such as dormitories, fraternity and sorority houses, and nurses’ homes)

are assigned by convention to other private business,

while investment in tenant-occupied residential assets

is distributed to all legal forms of organization, using

data from the Census Bureau’s survey of residential finance.

Government-Owned Fixed Assets

Government fixed assets are presented for Federal and

for State and local governments. Federal government

assets are further split into defense and nondefense assets. The underlying estimates of investment by government beginning with 1929 are derived from the

NIPA series on gross government investment and are

modified for the revaluation of net purchases of used

assets, as described in the section “Net purchases of

used assets.” Estimates for years before 1929 are

derived by extrapolating these estimates backward using data from Raymond Goldsmith.61

Consumer Durable Goods

Estimates of additions to the stock of consumer durable goods beginning with 1929 are taken directly from

the NIPA series on personal consumption expenditures for durable goods. Estimates for years before

1929 are derived by extrapolating the NIPA estimates

backwards using data from Shaw.62

61. Raymond W. Goldsmith, A Study of Saving in the United States, 3 volumes (Princeton, NJ: Princeton University Press, 1955).

62. William H. Shaw, Value of Commodity Output Since 1869 (Princeton,

NJ: Princeton University Press, for the National Bureau of Economic

Research, 1947). 
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–29

In the perpetual inventory method, the pattern of depreciation charges for an asset of a given type is determined by its “depreciation profile”—that is, how the

price of that type of asset declines as it ages in the absence of inflation. The profile for a given type of asset

of a given vintage is assumed to be constant over time.

However, the profile for one vintage of a given asset

may differ from the profile of a different vintage of the

same asset.

BEA bases its depreciation patterns on empirical evidence of used asset prices in resale markets wherever

possible. For computer and computer peripheral

equipment and for autos, information on used asset

prices is extensive, and the actual empirical profiles are

used. These profiles are provided in table B. The profile

for personal computers (PCs) is based on a study of the

fair-market value of personal property including PCs

in California. The resulting truncated geometric pattern of depreciation results in a residual value of less

than 10 percent of a PC’s original value by the end of

the fifth year.63 For other categories of computers and

peripheral equipment, the profiles are taken from

studies prepared by Oliner.64 For autos, the profiles are

derived from new car prices and used car prices (from

the National Automobile Dealer Association’s Official

Wholesale Used Car Trade-In Guide) for a sample of

models.

For most other assets, geometric patterns are used

because the available data suggest that they more

closely approximate actual profiles of price declines

than straight-line patterns.65

63. As a result of an earlier application of this methodology, the California

State Board of Equalization recommended depreciation schedules for computers that were widely adopted across California and in several other western states. For further details, see Richard N. Lane, “Appraisal Report ‘Large

Aerospace Firm’ Personal Property, Los Angeles County, March 1, 1995,”

revised February 2, 1999.

64. A general description of this work appears in Stephen D. Oliner,

“Constant-Quality Price Change, Depreciation, and Retirement of IBM

Mainframe Computers,” in Murray F. Foss, Marilyn E. Manser, and Allan

H. Young (eds.), Price Measurements and Their Uses, Conference on

Research in Income and Wealth (Chicago, IL: University of Chicago Press,

for the National Bureau of Economic Research, 1993). The depreciation

profiles used by BEA were taken from that article and from unpublished

detail provided by Oliner.

The geometric rates for specific types of assets are

determined by dividing the appropriate declining-balance rate for each asset by the asset’s assumed service

life, as illustrated in equation (1) on page M–7. The declining-balance rates used by BEA are derived from estimates made by Hulten and Wykoff under the

auspices of the U.S. Department of the Treasury and

are shown in table C.66 For the purposes of determining the appropriate rates, they divided assets into three

major types. Type A assets are those for which extensive data were available for estimating declining-balance rates: Tractors, construction machinery,

metalworking machinery, general industrial equipment, trucks, autos, industrial buildings, and commercial buildings.67 In 1977, these categories accounted for

about 55 percent of investment expenditures on equipment and 42 percent of spending on nonresidential

structures.

Type B assets are those for which the limited studies

on depreciation or other relevant data did not support

defensible estimates of the rate of declining balance.

For these assets, Hulten and Wykoff used the results of

empirical research by others, including the research of

BEA, Dale Jorgenson, the Bureau of Labor Statistics,

and Jack Faucett Associates, as well as their own judgement.

No data were available for Type C assets. Hulten and

Wykoff estimated the average declining-balance rates

from information on the eight categories of type A assets combined with information on the average life of

the type B assets. They determined that, on average,

the declining-balance rate for equipment was 1.65 and

that for private nonresidential structures was 0.91.

65. Except for missiles and nuclear fuel rods, where an explicit retirement

pattern and distribution of service lives is used, the BEA depreciation profiles are for an entire cohort of assets of a given type. When different assets

within a cohort have different service lives, the profile for the cohort as a

whole will be more convex (accelerated) than the profile for a single asset.

For further discussion of this point, see Frank C. Wykoff, “Economic

Depreciation and the User Cost of Business-Leased Automobiles,” Technology and Capital Formation (Cambridge, MA: MIT Press, 1989): 262–265. 

66. The following discussion is extracted from Fraumeni, “The Measurement of Depreciation”, op cit 16–20.

67. As noted above, an actual empirical profile is used for autos rather

than the geometric rate estimated by Hulten and Wykoff.

Derivation of Depreciation Estimates
M–30 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

These averages serve as the rates for assets where no

data are available.

At the time of the Hulten-Wykoff studies, computer

software was not treated as a capitalized asset in the

NIPAs. As there have been no subsequent studies of

software depreciation, pre-packaged, custom, and

own-account software are treated as type C assets.

The geometric depreciation rates and the underlying declining-balance depreciation rates and service

lives used by BEA to derive the estimates of net stocks

and depreciation are shown in table C. Separate depreciation rates and service lives are used for each type of

asset at the level of detail for which annual data are

available from the NIPAs. For some types of private

fixed assets, different depreciation rates and service

lives are also used in different industries.

For missiles and nuclear fuel rods, depreciation is

estimated using a straight-line pattern (to reflect the

pattern of rotation and replacement of nuclear fuel)

and a Winfrey retirement pattern, as discussed below.

Service lives

As with depreciation patterns, service lives should reflect actual experience as closely as possible—separate

Age in years

Year asset was initially installed

Automobiles Computer mainframes Personal 

computers

All years 1958–69 1970–79 1980–94 All years

1 ..................... 0.8208 0.9787 0.9787 0.8980 0.7790

2 ..................... 0.5890 0.9074 0.8917 0.6893 0.4730

3 ..................... 0.4862 0.7779 0.7411 0.4901 0.2870

4 ..................... 0.4063 0.6429 0.5575 0.2989 0.1740

5 ..................... 0.3258 0.4891 0.4002 0.1732 0.1060

6 ..................... 0.2414 0.3498 0.2694 0.0894 0.0640

7 ..................... 0.1811 0.2412 0.1666 0.0434 0.0390

8 ..................... 0.1280 0.1618 0.0968 0.0197 0.0240

9 ..................... 0.0749 0.1090 0.0549 0.0087 0.0140

10 ................... 0.0363 0.0734 0.0302 0.0035 0.0090

11 ................... 0.0184 0.0483 0.0164 0.0015 0.0050

12 ................... 0.0092 0.0323 0.0089 0.0007 0.0030

13 ................... 0.0000 0.0222 0.0056 0.0004 0.0020

14 ................... 0.0000 0.0118 0.0029 0.0003 0.0010

15 ................... 0.0000 0.0057 0.0017 0.0002 0.0010

16 ................... 0.0000 0.0000 0.0000 0.0000 0.0000

17 ................... 0.0000 0.0000 0.0000 0.0000 0.0000

18 ................... 0.0000 0.0000 0.0000 0.0000 0.0000

19 ................... 0.0000 0.0000 0.0000 0.0000 0.0000

20 ................... 0.0000 0.0000 0.0000 0.0000 0.0000

Age in years

Year asset was initially installed

Computer printers

1958–69 1970–75 1976–80 1981–85 1986–94

1 ..................... 0.9274 0.9255 0.9004 0.8750 0.8478

2 ..................... 0.7870 0.7808 0.7109 0.6410 0.5678

3 ..................... 0.6534 0.6434 0.5415 0.4470 0.3570

4 ..................... 0.5277 0.5189 0.4031 0.3049 0.2205

5 ..................... 0.4206 0.4174 0.3002 0.2075 0.1343

6 ..................... 0.3333 0.3333 0.2231 0.1403 0.0822

7 ..................... 0.2606 0.2606 0.1656 0.0955 0.0516

8 ..................... 0.2017 0.2017 0.1237 0.0662 0.0335

9 ..................... 0.1559 0.1559 0.0936 0.0452 0.0220

10 ................... 0.1217 0.1217 0.0722 0.0321 0.0144

11 ................... 0.0960 0.0960 0.0553 0.0247 0.0093

12 ................... 0.0752 0.0752 0.0411 0.0178 0.0059

13 ................... 0.0576 0.0576 0.0299 0.0128 0.0037

14 ................... 0.0426 0.0426 0.0210 0.0090 0.0024

15 ................... 0.0302 0.0302 0.0141 0.0062 0.0015

16 ................... 0.0208 0.0208 0.0092 0.0041 0.0010

17 ................... 0.0140 0.0140 0.0059 0.0025 0.0006

18 ................... 0.0088 0.0088 0.0035 0.0014 0.0004

19 ................... 0.0053 0.0053 0.0020 0.0008 0.0002

20 ................... 0.0020 0.0020 0.0007 0.0003 0.0001

Age in years

Year asset was initially installed

Computer terminals and displays

1958–69 1970–75 1976–80 1981–85 1986–94

1 ..................... 0.9793 0.9777 0.9749 0.9704 0.9208

2 ..................... 0.9061 0.9006 0.8887 0.8702 0.7318

3 ..................... 0.7799 0.7707 0.7450 0.7084 0.5216

4 ..................... 0.6265 0.6180 0.5834 0.5388 0.3474

5 ..................... 0.4786 0.4754 0.4404 0.3957 0.2220

6 ..................... 0.3558 0.3558 0.3250 0.2821 0.1377

7 ..................... 0.2586 0.2586 0.2359 0.1986 0.0851

8 ..................... 0.1854 0.1854 0.1712 0.1407 0.0538

9 ..................... 0.1333 0.1333 0.1261 0.1023 0.0352

10 ................... 0.0979 0.0979 0.0958 0.0776 0.0237

Age in years

Year asset was initially installed

Computer terminals and displays

1958–69 1970–75 1976–80 1981–85 1986–94

11 ................... 0.0750 0.0750 0.0750 0.0614 0.0164

12 ................... 0.0603 0.0603 0.0603 0.0507 0.0118

13 ................... 0.0505 0.0505 0.0505 0.0438 0.0088

14 ................... 0.0442 0.0442 0.0442 0.0400 0.0069

15 ................... 0.0402 0.0402 0.0402 0.0387 0.0058

16 ................... 0.0381 0.0381 0.0381 0.0381 0.0055

17 ................... 0.0368 0.0368 0.0368 0.0368 0.0055

18 ................... 0.0355 0.0355 0.0355 0.0355 0.0058

19 ................... 0.0342 0.0342 0.0342 0.0342 0.0049

20 ................... 0.0264 0.0264 0.0264 0.0264 0.0037

Age in years

Year asset was initially installed

Computer tape drives

1958–69 1970–75 1976–80 1981–85 1986–94

1 ..................... 0.9229 0.9205 0.9175 0.9139 0.9094

2 ..................... 0.7741 0.7671 0.7566 0.7437 0.7272

3 ..................... 0.6333 0.6228 0.6031 0.5795 0.5516

4 ..................... 0.5010 0.4907 0.4655 0.4369 0.4045

5 ..................... 0.3875 0.3805 0.3544 0.3251 0.2921

6 ..................... 0.2948 0.2902 0.2661 0.2372 0.2060

7 ..................... 0.2184 0.2144 0.1958 0.1700 0.1435

8 ..................... 0.1576 0.1542 0.1419 0.0755 0.0998

9 ..................... 0.1113 0.1086 0.1015 0.0602 0.0698

10 ................... 0.0776 0.0755 0.0723 0.0418 0.0483

11 ................... 0.0535 0.0519 0.0504 0.0402 0.0325

12 ................... 0.0358 0.0347 0.0335 0.0282 0.0210

13 ................... 0.0229 0.0221 0.0213 0.0182 0.0129

14 ................... 0.0138 0.0132 0.0127 0.0112 0.0075

15 ................... 0.0077 0.0074 0.0071 0.0065 0.0042

16 ................... 0.0040 0.0038 0.0037 0.0028 0.0023

17 ................... 0.0020 0.0019 0.0018 0.0012 0.0012

18 ................... 0.0009 0.0008 0.0008 0.0008 0.0005

19 ................... 0.0004 0.0003 0.0003 0.0003 0.0002

20 ................... 0.0001 0.0001 0.0001 0.0001 0.0001

Age in years

Year asset was initially installed

Computer storage devices

1958–69 1970–75 1976–80 1981–85 1986–94

1 ..................... 0.9975 0.9925 0.9800 0.9700 0.9549

2 ..................... 0.9875 0.9775 0.9400 0.9100 0.7806

3 ..................... 0.9753 0.9598 0.9026 0.8426 0.5326

4 ..................... 0.8538 0.8376 0.7736 0.6913 0.3231

5 ..................... 0.6269 0.6213 0.5585 0.4779 0.1767

6 ..................... 0.4255 0.4255 0.3737 0.3063 0.0911

7 ..................... 0.2692 0.2692 0.2369 0.1877 0.0459

8 ..................... 0.1623 0.1623 0.1456 0.1134 0.0229

9 ..................... 0.0958 0.0958 0.0890 0.0687 0.0111

10 ................... 0.0569 0.0569 0.0553 0.0417 0.0053

11 ................... 0.0343 0.0343 0.0343 0.0255 0.0025

12 ................... 0.0210 0.0210 0.0210 0.0160 0.0012

13 ................... 0.0130 0.0130 0.0130 0.0103 0.0006

14 ................... 0.0082 0.0082 0.0082 0.0069 0.0003

15 ................... 0.0054 0.0054 0.0054 0.0050 0.0002

16 ................... 0.0038 0.0038 0.0038 0.0038 0.0001

17 ................... 0.0029 0.0029 0.0029 0.0029 0.0001

18 ................... 0.0023 0.0023 0.0023 0.0023 0.0001

19 ................... 0.0022 0.0022 0.0022 0.0022 0.0001

20 ................... 0.0011 0.0011 0.0011 0.0011 0

Table B. Depreciation Schedules for Autos, Computers, and Computer Peripherals

[In values relative to the price of a new asset]
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–31

lives should be used for each industry in which a particular type of asset is purchased, and service lives

should be varied over time to account for changes in

business conditions and technology. Because of data

limitations, the service lives BEA uses fall short of this

ideal in two ways. First, service lives can be computed

only for those types of assets and industries shown in

table C. Second, service lives can be varied over time

only for those types of assets and industries shown in

table C. All other service lives by type of asset and

Type of Asset Rate of

depreciation

Service

life

(years)

Declining

balance

rates

HultenWykoff

category 1

Private nonresidential equipment

Software:

Prepackaged ................................................... 0.5500 3 1.65 C

Custom............................................................ 0.3300 5 1.65 C

Own-account................................................... 0.3300 5 1.65 C

Office, computing, and accounting machinery 2

: Years before 1978 ........................................... 0.2729 8 2.1832 B

1978 and later years ....................................... 0.3119 7 2.1832 B

Communications equipment:

Business services 3......................................... 0.1500 11 1.65 C

Other industries 3 ............................................ 0.1100 15 1.65 C

Instruments 4 ....................................................... 0.1350 12 1.6203 C

Photocopy and related equipment 5 .................... 0.1800 9 1.6203 C

Nuclear fuel 6....................................................... ................ 4 ................ ................

Other fabricated metal products 7 ....................... 0.0917 18 1.65 C

Steam engines and turbines 8 ............................. 0.0516 32 1.65 C

Internal combustion engines 8............................. 0.2063 8 1.65 C

Metalworking machines 9 .................................... 0.1225 16 1.96 A

Special industrial machinery, n.e.c..................... . 0.1031 16 1.65 C

General industrial, including materials handling 

equipment........................................................ 0.1072 16 1.715 A

Electrical transmission, distribution, and 

industrial apparatus ......................................... 0.0500 33 1.65 C

Trucks, buses, and truck trailers:

Local and interurban passenger transit 10 ....... 0.1232 14 1.7252 A

Trucking and warehousing; and auto repair, 

services, and parking 10 ............................ 0.1725 10 1.7252 A

Other industries............................................... 0.1917 9 1.7252 A

Autos 11 ............................................................... ................ ................ ................ ................

Aircraft:

Transportation by air, depository institutions, 

and business services:

Years before 1960 ....................................... 0.1031 16 1.65 C

1960 and later years ................................... 0.0825 20 1.65 C

Other industries:

Years before 1960 ....................................... 0.1375 12 1.65 C

1960 and later years ................................... 0.1100 15 1.65 C

Ships and boats .................................................. 0.0611 27 1.65 B

Railroad equipment............................................. 0.0589 28 1.65 C

Household furniture and fixtures 12 ..................... 0.1375 12 1.65 C

Other furniture 12 ................................................. 0.1179 14 1.65 C

Farm tractors 13 ................................................... 0.1452 9 1.3064 A

Construction tractors 13 ....................................... 0.1633 8 1.3064 A

Agricultural machinery, except tractors ............... 0.1179 14 1.65 C

Construction machinery, except tractors ............. 0.1550 10 1.5498 A

Mining and oil field machinery............................. 0.1500 11 1.65 C

Service industry machinery:

Wholesale and retail trade 14........................... 0.1650 10 1.65 C

Other industries 14 ........................................... 0.1500 11 1.65 C

Household appliances 15 ..................................... 0.1650 10 1.65 C

Other electrical equipment 16 .............................. 0.1834 9 1.65 C

Other 4 ................................................................. 0.1473 11 1.623 C

Private nonresidential structures

Industrial buildings .............................................. 0.0314 31 0.9747 A

Mobile offices 17................................................... 0.0556 16 0.8892 A

Office buildings 17 ................................................ 0.0247 36 0.8892 A

Commercial warehouses 17 ................................. 0.0222 40 0.8892 A

Other commercial buildings 17 ............................. 0.0262 34 0.8892 A

Religious buildings .............................................. 0.0188 48 0.9024 C

Educational buildings .......................................... 0.0188 48 0.9024 C

Hospital and institutional buildings ...................... 0.0188 48 0.9024 B

Hotels and motels 18............................................ 0.0281 32 0.899 B

Amusement and recreational buildings 18 ........... 0.0300 30 0.899 B

All other nonfarm buildings 18 .............................. 0.0237 38 0.899 B

Railroad replacement track 19............................. 0.0249 38 0.948 C

Other railroad structures 19................................. 0.0176 54 0.948 C

Telecommunications 19 ........................................ 0.0237 40 0.948 C

Electric light and power 19: Years before 1946 ........................................... 0.0237 40 0.948 C

1946 and later years ....................................... 0.0211 45 0.948 C

Gas 19 .................................................................. 0.0237 40 0.948 C

Petroleum pipelines 19 ......................................... 0.0237 40 0.948 C

Farm 20 ................................................................ 0.0239 38 0.91 C

Mining exploration, shafts, and wells:

Petroleum and natural gas 21:

Years before 1973 ....................................... 0.0563 16 0.9008 C

1973 and later years ................................... 0.0751 12 0.9008 C

Other 21 ....................................................... 0.0450 20 0.9008 C

Local transit 22 ..................................................... 0.0237 38 0.899 C

Other 22 ............................................................... 0.0225 40 0.899 C

Table C. BEA Rates of Depreciation, Service Lives, Declining-Balance Rates, and Hulten-Wykoff Categories

Type of Asset Rate of

depreciation

Service

life

(years)

Declining

balance

rates

HultenWykoff

category 1

Residential capital (private and government)

1-to-4-unit structures–new 20 ............................... 0.0114 80 0.91 A

1-to-4-unit structures–additions and 

alterations 20 ..................................................... 0.0227 40 0.91 A

1-to-4-unit structures–major replacements 20 ...... 0.0364 25 0.91 A

5-or-more-unit structures–new 20 ......................... 0.0140 65 0.91 A

5-or-more-unit structures–additions and 

alterations 20 ..................................................... 0.0284 32 0.91 A

5-or-more-unit structures–major replacements 20 0.0455 20 0.91 A

Manufactured homes 20 ....................................... 0.0455 20 0.91 A

Other structures 20 ............................................... 0.0227 40 0.91 A

Equipment 23 ........................................................ 0.1500 11 1.65 C

Durable goods owned by consumers 24

Furniture, including mattresses and bedsprings.. 0.1179 14 1.65 B

Kitchen and other household appliances............. 0.1500 11 1.65 C

China, glassware, tableware, and utensils 25 ....... 0.1650 10 1.65 C

Other durable house furnishings 25 ...................... 0.1650 10 1.65 C

Video and audio products, computers and 

peripheral equipment, and musical 

instruments 26 .............................................. 0.1833 9 1.65 B

Jewelry and watches 25........................................ 0.1500 11 1.65 C

Ophthalmic products and orthopedic 

appliances 25..................................................... 0.2750 6 1.65 C

Books and maps 25 .............................................. 0.1650 10 1.65 C

Wheel goods, sports and photographic 

equipment, boats, and pleasure aircraft 27 ...... 0.1650 10 1.65 C

Autos 11 ................................................................ ................ ................ ................ ................

Other motor vehicles 28 ........................................ 0.2316 8 1.853 A

Tires, tubes, accessories, and other parts 28 ....... 0.6177 3 1.853 A

Government nonresidential equipment 29

Federal:

National defense:

Aircraft:

Airframes:

Bombers .............................................. 0.0660 25 1.65 C

F–14 type............................................. 0.0868 19 1.65 C

Attack, F–15 and F–16 types............... 0.0825 20 1.65 C

F–18 type ............................................ 0.1100 15 1.65 C

Electronic warfare................................ 0.0717 23 1.65 C

Cargo and trainers............................... 0.0660 25 1.65 C

Helicopters .......................................... 0.0825 20 1.65 C

Engines.................................................... 0.2750 6 1.65 C

Other:

Years before 1982................................ 0.1179 14 1.65 C

1982 and later years............................ 0.1650 10 1.65 C

Missiles: 30

Strategic .................................................. ................ 20 ................ ................

Tactical..................................................... ................ 15 ................ ................

Torpedoes................................................ ................ 15 ................ ................

Fire control equipment............................. ................ 10 ................ ................

Space programs ...................................... ................ 20 ................ ................

Ships:

Surface ships........................................... 0.0550 30 1.65 C

Submarines ............................................. 0.0660 25 1.65 C

Government furnished equipment:

Electrical.............................................. 0.1834 9 1.65 C

Propulsion ........................................... 0.0825 20 1.65 C

Hull, mechanical .................................. 0.0660 25 1.65 C

Ordnance............................................. 0.1650 10 1.65 C

Other ................................................... 0.1650 10 1.65 C

Vehicles:

Tanks, armored personnel carriers, and 

other combat vehicles.......................... 0.0825 20 1.65 C

Noncombat vehicles:

Trucks .................................................. 0.2875 6 1.7252 C

Autos 31 ................................................ ................ ................ ................ ................ Other ................................................... 0.2465 7 1.7252 C

Electronic equipment:

Computers and peripheral equipment 32 ................ ................ ................ ................

Electronic countermeasures.................... 0.2357 7 1.65 C

Other........................................................ 0.1650 10 1.65 C

Other equipment:

Medical .................................................... 0.1834 9 1.65 C

Construction ............................................ 0.1550 10 1.5498 C

Industrial.................................................. 0.0917 18 1.65 C

Ammunition plant..................................... 0.0868 19 1.65 C

Atomic energy.......................................... 0.1375 12 1.65 C

Weapons and fire control......................... 0.1375 12 1.65 C

General.................................................... 0.1650 10 1.65 C

See footnotes at the end of the table.
M–32 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

industry are held constant over time. Book value comparisons suggest that the use of constant service lives

has not produced any systematic bias in the BEA estimates of private fixed assets for the period (1959–81).68

As indicated in table C, the service lives for some

types of government fixed assets are varied over time

while others are held constant depending upon the

availability of data. The lives used for durable goods

owned by consumers are held constant over time, because the information necessary to estimate changing

lives over time was not available.

Private equipment. BEA’s service lives for private

equipment are based on service lives obtained from in68. Book value data, which relate directly to capital stocks, can be used as

checks on the validity of the information used to implement the perpetual

inventory method. Examples of such checks on the BEA estimates are given

in John A. Gorman, John C. Musgrave, Gerald Silverstein, and Kathy A.

Comins, “Fixed Private Capital in the United States: Revised Estimates,

1925–81 and Estimates by Industry, 1947–81,” SURVEY 65 (July 1985):

36–59.

dustry studies conducted during the 1970s by the

former Office of Industrial Economics (OIE) of the

U.S. Department of the Treasury and from industry

studies conducted during the 1980s and 1990s by the

Office of Tax Analysis (OTA) of the U.S. Department

of the Treasury, with the following exceptions: Nuclear

fuel; office, computing, and accounting machinery;

software; autos; and railroad equipment.69 The OIE results are particularly useful for manufacturing industries because they provide separate industry estimates

69. The results of the OIE studies are given in David W. Brazell, Lowell

Dworin, and Michael Walsh, A History of Federal Tax Depreciation Policy,

U.S. Department of the Treasury, OTA Paper 64 (Springfield, VA: National

Technical Information Service, May 1989): 33–58. The results of the OTA

studies that are used in the BEA wealth calculations are given in U.S.

Department of the Treasury, Report to the Congress on Depreciation of Scientific Instruments (Washington, D.C.: March 1990); U.S. Department of the

Treasury, Report to the Congress on Depreciation of Business-Use Passenger

Cars (Washington, D.C.: April 1991); and U.S. Department of the Treasury,

Report to the Congress on Depreciation of Business-Use Light Trucks (Washington, D.C.: September 1991).

Table C. BEA Rates of Depreciation, Service Lives, Declining-Balance Rates, and Hulten-Wykoff Categories—Continued

Type of Asset Rate of

depreciation

Service

life

(years)

Declining

balance

rates

HultenWykoff

category 1

Other ........................................................... 0.1375 12 1.65 C

Nondefense:

General government:

Computers and peripheral equipment 32 ................ ................ ................ ................ Aerospace equipment ............................. 0.1100 15 1.65 C

Vehicles ................................................... 0.4533 5 2.2664 C

Other ....................................................... 0.1650 10 1.65 C

Enterprises:

U.S. Postal Service:

Computers and peripheral 

equipment 32 ................................... ................ ................ ................ ................

Vehicles ........................................... 0.3238 7 2.2664 C

Other ............................................... 0.1100 15 1.65 C

Tennessee Valley Power Authority........... 0.0500 33 1.65 C

Bonneville Power Authority...................... 0.0500 33 1.65 C

Other ....................................................... 0.0660 25 1.65 C

State and local

Power tools, lawn and garden equipment............ 0.1650 10 1.65 C

Miscellaneous metal products ............................. 0.0917 18 1.65 C

Agricultural machinery and equipment ................ 0.1833 9 1.65 C

Construction machinery and equipment.............. 0.1650 10 1.65 C

Metalworking machinery and equipment............. 0.1031 16 1.65 C

General purpose machinery and equipment ....... 0.1500 11 1.65 C

Special industry machinery and equipment......... 0.1500 11 1.65 C

Integrating and measuring instruments ............... 0.1375 12 1.65 C

Motors, generators, motor generator sets ........... 0.0516 32 1.65 C

Switchgear and switchboard equipment.............. 0.0500 33 1.65 C

Electronic components and accessories ............. 0.1833 9 1.65 C

Miscellaneous electrical machinery..................... 0.1375 12 1.65 C

Calculating and accounting machines................. 0.2357 7 1.65 C

Typewriters........................................................... 0.2357 7 1.65 C

Type of Asset Rate of

depreciation

Service

life

(years)

Declining

balance

rates

HultenWykoff

category 1

Computers and peripheral equipment ................. ................ ................ ................ ................

Machine shop products ....................................... 0.2063 8 1.65 C

Wood commercial furniture.................................. 0.1179 14 1.65 C

Metal commercial furniture .................................. 0.1179 14 1.65 C

Household appliances ......................................... 0.1500 11 1.65 C

Home electronic equipment................................. 0.1500 11 1.65 C

Motor vehicles ..................................................... 0.1650 10 1.65 C

Motorcycles ......................................................... 0.1650 10 1.65 C

Aircraft ................................................................. 0.1100 15 1.65 C

Railroad equipment ............................................. 0.0590 28 1.65 C

Sporting and athletic goods................................. 0.1650 10 1.65 C

Photographic and photocopying equipment ........ 0.1650 10 1.65 C

Mobile classrooms, mobile offices, etc................ 0.1650 10 1.65 C

Musical instruments............................................. 0.1834 9 1.65 C

Other equipment.................................................. 0.1375 12 1.65 C

Government nonresidential structures 33

Federal, State, and local:

Buildings:

Industrial...................................................... 0.0285 32 0.91 C

Educational.................................................. 0.0182 50 0.91 C

Hospital ....................................................... 0.0182 50 0.91 C

Other ........................................................... 0.0182 50 0.91 C

Nonbuildings:

Highways and streets ...................................... 0.0202 45 0.91 B* Conservation and development....................... 0.0152 60 0.91 C

Sewer systems ................................................ 0.0152 60 0.91 C

Water systems................................................. 0.0152 60 0.91 C

Military facilities ............................................... 0.0182 50 0.91 C

Other ............................................................... 0.0152 60 0.91 C

* This type of asset was categorized by BEA rather than by Hulten and Wykoff.

1. This column refers to Hulten-Wykoff categories. Type A assets are types of assets for which Hulten-Wykoff specifically estimated age-price profiles. Type B assets are those for which Hulten-Wykoff used empirical research by others and

their judgement to estimate the depreciation rate. Type C assets are assets for which Hulten-Wykoff estimated an average

declining-balance rate from data for all type A and B assets. 

2. The depreciation rate for this type of asset is not used for computers and peripheral equipment. Depreciation rates for

these assets are taken from Oliner as described in the text.

3. The declining-balance rate is from the Hulten-Wykoff communications equipment aggregate.

4. Instruments and other private nonresidential equipment, called producer durable equipment by Hulten-Wykoff, are

classified by them to be of type C, but appear to be of type B as they were given a declining-balance rate of 1.6203.

5. The declining-balance rate is from the Hulten-Wykoff other producer durable equipment aggregate.

6. The depreciation rates for nuclear fuel are based on a straight-line rate pattern and a Winfrey retirement pattern.

7. The declining-balance rate is from the Hulten-Wykoff fabricated metal products aggregate.

8. The declining-balance rate is from the Hulten-Wykoff engines and turbines aggregate.

9. The depreciation rate and service life listed apply to nonmanufacturing industries; the service lives and depreciation

rates used for manufacturing industries differ by industry. The Hulten-Wykoff type of asset listed applies to all

industries.

10. The declining-balance rate is from the Hulten-Wykoff trucks, buses and truck trailer aggregate.

11. Depreciation rates for autos are derived from data on new and used auto prices.

12. The declining-balance rate is from the Hulten-Wykoff furniture and fixtures aggregate.

13. The declining-balance rate is from the Hulten-Wykoff tractors aggregate.

14. The declining-balance rate is from the Hulten-Wykoff service industry machinery aggregate.

15. The declining-balance rate is set to the Hulten-Wykoff producer durable equipment default.

16. The declining-balance rate is from the Hulten-Wykoff electrical equipment (not elsewhere classified) aggregate.

17. The declining-balance rate is from the Hulten-Wykoff commercial aggregate.

18. The declining-balance rate is from the Hulten-Wykoff other private nonresidential structures aggregate, which

consists of buildings used primarily for social and recreational activities and buildings not elsewhere classified.

19. The declining-balance rate is from the Hulten-Wykoff public utilities aggregate.

20. The declining-balance rate is set to the Hulten-Wykoff private nonresidential structures default.

21. The declining-balance rate is from the Hulten-Wykoff mining exploration, shafts and wells aggregate.

22. The declining-balance rate is from the Hulten-Wykoff other private nonresidential structures aggregate, which

consists of streets, dams and reservoirs, sewer and water facilities.

23. The declining-balance rate is set to the Hulten-Wykoff producer durable equipment default.

24. For all consumer durables except for motor vehicles and parts and computing equipment, the declining-balance rate

is set to the Hulten-Wykoff producer durable equipment default.

25. The corresponding Hulten-Wykoff consumer durables category is other.

26. Depreciation rates for computers and peripheral equipment are taken from Oliner as described in the text. The information listed applies to video and audio products and musical instruments. The corresponding Hulten-Wykoff aggregate is

radio and television receivers, recorders, and musical instruments. Radio and television receivers, recorders, and musical

instruments are classified by Hulten-Wykoff to be of type B, but are indistinguishable from type C as their declining-balance

rate is 1.65.

27. The corresponding Hulten-Wykoff consumer durables category is wheel goods, durable toys, sports equipment.

28. The declining-balance rate is from the Hulten-Wykoff motor vehicles and parts aggregate. The declining-balance

rate for this category is calculated under the assumption that the service life for consumer durables motor vehicles and

parts is equal to the service life for producer durable equipment autos previously used by BEA.

29. For most government nonresidential equipment, the declining-balance rate is set to the Hulten-Wykoff producer

durable equipment default. Where possible, the rate is set equal to the rate used for comparable equipment in the private

sector. 30. Missiles are depreciated using straight-line patterns of depreciation and a Winfrey retirement pattern.

31. Depreciation rates for government-owned autos are derived from data on autos that are privately owned.

32. Depreciation rates for these assets are taken from Oliner as described in the text.

33. For all government nonresidential structures, the declining-balance rate is set to the Hulten-Wykoff private nonresidential structures default.
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–33

of service lives for production-type equipment—metalworking machinery; special industry machinery, not

elsewhere classified; and general industrial machinery,

including materials handling equipment. The information on the service life for nuclear fuel was obtained

from Professor Madeline Feltus of the Pennsylvania

State University. The service life for office, computing,

and accounting machinery is derived, in part, from the

study by Oliner based on industry data.70 The service

lives for software were set judgmentally by BEA during

the 1999 comprehensive revision. The derivation of

stocks of autos does not require an explicit service-life

assumption, as explained in the section “Derivation of

Estimates of Privately-owned Automobiles.” The service life for railroad equipment is derived from information on service lives submitted by railroads to the

Interstate Commerce Commission as part of the 1983

annual reports of individual railroads.

Private nonresidential structures. For farm structures, the average service life is derived from USDA

studies. For telephone and telegraph, electric light and

power, gas, and petroleum pipelines structures, the

service lives are derived by comparing book value data

provided by regulatory agencies with various perpetual

inventory estimates calculated using alternative service

lives. For railroad structures, service lives are derived

from the same source as for railroad equipment (see

above). For petroleum and natural gas exploration,

shafts, and wells, the lives are based on data from the

Census Bureau’s annual surveys of oil and gas for

1979–1982. For other types of nonfarm structures, service lives are based on published and unpublished data

from studies conducted during the 1960s and 1970s by

the U.S. Department of the Treasury.71

Residential structures. The average service lives for

most types of new residential structures are taken from

a study by Goldsmith and Lipsey.72 Improvements to

residential structures are assigned the following lives:

Additions and alterations are assumed to have lives

one-half as long as those for new structures; and lives

for residential major replacements are based on industry estimates for items replaced during the 1970s.

Mobile homes are assigned a life of 20 years, based on

trade association data.

Government-owned fixed assets. Service lives for

most government assets are derived from those used

for corresponding assets owned by private business.

70. Oliner, 1993. 

71. See U.S. Department of the Treasury, Office of Industrial Economics,

Business Building Statistics (Washington, D.C.: U.S. Government Printing

Office, August 1975).

72. See Raymond W. Goldsmith and Robert Lipsey, Studies in the

National Balance Sheet of the United States, Volume 1 (Princeton, NJ: Princeton University Press, for the National Bureau of Economic Research,

1963).

For some Federal Government equipment (primarily

military equipment), depreciation patterns are based

on service lives estimated from U.S. Government administrative sources (primarily U.S. Department of

Defense data).

Based on recent studies, the service life for highways

was shortened to 45 years from 60 years so the geometric rate is 0.0202 instead of 0.0152 as it had been in

previously published estimates.73 The new rate is based

on the default declining balance rate (0.91).

Durable goods owned by consumers. For durable

goods owned by consumers, the average service lives

are based on unpublished trade association data, the

assumptions of other researchers, several USDA studies, and the age distribution of the stock of various

consumer durables reported in the 1960–61 and

1972–73 BLS surveys of consumer expenditures.74

Retirement patterns

Assets are “retired” from the stock when their value declines to zero. This normally occurs at the end of their

assumed service lives. However, some assets are retired

prematurely because of catastrophic losses and, for

military equipment and structures, because of surplusing by the Federal Government. For missiles and nuclear fuel rods, the depreciation profile is assumed to

decline to zero in a straight-line manner, but each vintage of a given type of asset is divided into several

dozen cohorts, each of which is assumed to have a different service life. These lives are assumed to be distributed about the mean according to a pattern

calculated using a modified version of a curve developed by Winfrey (see table D).75 Specifically, a Winfrey

S–3 curve, which is a bell-shaped distribution centered

on the average service life of the asset, is modified so

73. For information on the service life of highways, see Richard Beemiller,

Experimental Estimates of State and Local Government Highway Capital

Stocks (paper presented at the 1999 annual meeting of the Southern

Regional Science Association, Richmond, VA, April 1999); and Barbara M.

Fraumeni, Productive Highway Capital Stock Measures, a report prepared

for the Federal Highway Administration, U.S. Department of Transportation, January 1999.

74. See Lenore A. Epstein, Consumers’ Tangible Assets, Studies in Income

and Wealth, Volume 12 (Princeton, NJ): Princeton University Press, for the

National Bureau of Economic Research, 1950, 410–460; Raymond W. Goldsmith, The National Wealth of the United States in the Postwar Period (Princeton, NJ: Princeton University Press, for the National Bureau of Economic

Research, 1962); Marilyn Doss Ruffin and Katherine S. Tippett, “Service-Life Expectancy of Household Appliances: New Estimates from

USDA,” Home Economics Research Journal 3 (March 1975): 159–170; and

U.S. Bureau of Labor Statistics, “Survey of Consumer Expenditures,

1960–61, Expanding Ownership of Household Equipment,” BLS Report

No. 238–7, November 1964, and “Consumer Expenditure Survey Series:

Interview Survey, 1972–73, Inventories of Vehicles and Selected Household

Equipment, 1973,” BLS Report No. 455–5, 1978. 

75. See Robley Winfrey, Statistical Analyses of Industrial Property Retirements, Bulletin 125 Revised (Ames, IA: Engineering Research Institute,

Iowa State University, April 1967); and J.G. Russo and H.A. Cowles, “Revalidation of the Iowa Type Survivor Curves,” The Engineering Economist 26

(Fall 1980): 1–16.
M–34 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

that retirements start at 45 percent and end at 155 percent of the average service life.76 This retirement pattern results in a decline in the value of the net stock of

an entire vintage of missiles or nuclear fuel rods in a

manner that is somewhat more accelerated than that

given by the simple straight-line pattern.

For all other assets, no explicit retirement patterns

are used in constructing the estimates of the stocks, but

76. Winfrey developed a number of retirement curves. Some were symmetric about the mean; others were asymmetric. The designation S–3

means it is the third of three variations of a symmetric curve.

the depreciation rates that are used are based on empirical estimates that reflect the pattern of actual retirements. Retirements of autos are determined from

vehicle registration data, although all autos that are

more than 12 years old are fully depreciated. Computer equipment is implicitly retired at various ages;

that is, when it is fully depreciated, according to the assumed empirical profile. All remaining assets are assumed to have geometric depreciation profiles; their

assumed service lives only serve to help determine the

appropriate depreciation rates.

Table D. Modified Winfrey S–3 Retirement Pattern for Missiles and Nuclear Fuel Rods

Percent of average service life Cumulative percent of expenditures discarded Percent of average service life Cumulative percent of expenditures discarded

Less than 45........................................................................... 0 105........................................................... 61.6

45 ................................................................................... 1.2 110........................................................... 68.8

50 ................................................................................... 2.4 115........................................................... 75.4

55 ................................................................................... 4.1 120........................................................... 81.3

60 ................................................................................... 6.5 125........................................................... 86.3

65 ................................................................................... 9.7 130........................................................... 90.3

70 ................................................................................... 13.7 135........................................................... 93.5

75 ................................................................................... 18.7 140........................................................... 95.9

80 ................................................................................... 24.6 145........................................................... 97.6

85 ................................................................................... 31.2 150........................................................... 98.8

90 ................................................................................... 38.4 155........................................................... 100.0

95 ................................................................................... 46.1 More than 155 ................................................. 100.0

100 ................................................................................. 53.9
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–35

The extensive data available on automobiles77 allows

the use of the physical inventory method in deriving

estimates of net stocks and depreciation. As a result, it

is not necessary to assume a service life or retirement

pattern for autos or to make explicit adjustments to the

investment data for net purchases of used autos between different types of owners.

The number of autos in use and their respective ages

are estimated using registration data by model year

tabulated annually by R.L. Polk and Company. This information is used to derive estimates of the total stock

of autos owned by private business, government, and

consumers. The allocation of unit stocks (measured in

numbers of vehicles) among sectors is based on information on new auto sales by sector and assumed retention rates for private business and for government

autos. Estimates of the stock of consumer autos are

based on the difference between the total stock and the

stocks owned by business and by government.

The first step in deriving estimates of auto stocks

held by business, by government, and by consumers

involves the calculation of the total stock of autos in

use regardless of ownership. First, the number of new

autos entering the stock each year is estimated from

trade source data. Second, survival rates for each year

of original registration are estimated using annual Polk

tabulations of car registrations by model year. Finally,

the survival rates are applied to the estimates of new

autos to derive annual estimates of the total stock of

autos in use by year of original sale.78

The second step involves separating the total stock

of autos into stocks held by consumers, government,

and business, using Polk tabulations of registrations of

new autos as well as BLS and Census Bureau data on

autos owned by individuals but used wholly or partly

for business purposes. New autos owned by businesses

are assigned to the business stock, and new autos

77. The estimates of stocks of autos are derived from data used to estimate

purchases of autos by private business and by consumers in the NIPAs. A

detailed description of the derivation of auto data for cars-in-use and

expenditures data is given in Personal Consumption Expenditures, 55–58.

78. Survival rates for autos that are at least 4 years old are computed

directly from Polk cars-in-use data; survival rates for autos less than 4 years

old are estimated judgementally.

owned by individuals that are used exclusively for personal purposes are assigned to the consumer stock.

New autos owned by individuals that are used wholly

or partly for business purposes are allocated between

consumer and business stocks, according to the share

of business usage of these autos.79 The portion of these

autos allocated to the business stock provides the estimates of employee-owned autos discussed in the section “Investment controls by type of industry” in the

chapter “Derivation of Investment Flows.” These estimates are adjusted for purchases by consumers of used

autos from both business and government using assumed retention rates, based on an average retention

period of slightly more than one year for rental autos

and between 3 and 4 years for other autos owned by

business and government.

Third, the average unit values for business and consumer autos in each year of original sale are derived

from list prices by model (including options) from

trade sources. These prices are adjusted for transportation costs, discount factors, rebates, and sales taxes. Average unit values in 1996 prices are obtained by

deflation using the price indexes for the new-auto category of private equipment and personal consumption

expenditures, which are based on the consumer price

index for new autos. The annual real-cost net stocks of

business and consumer autos are obtained by multiplying the number of business autos and consumer autos for each year of original sale by the corresponding

deflated unit values, which are then adjusted for age,

according to the estimated depreciation profile.

Finally, the total business stock of autos is distributed by industry using data from capital flow tables

that have been adjusted to the NIPA industry classification and to an ownership basis.

79. The data on business usage of household-owned autos are derived

from U.S. Department of Labor, Bureau of Labor Statistics, Survey of Consumer Expenditures (Washington, D.C.: U.S. Government Printing Office,

1964); U.S. Department of Commerce, Bureau of the Census, Consumer

Buying Indicators (Washington, D.C.: U.S. Government Printing Office, July

1971); and U.S. Department of Commerce, Bureau of the Census, Current

Population Reports: Household and Family Characteristics (Series P–20)

(Washington, D.C.: U.S. Government Printing Office, annually).

Derivation of Estimates of Privately Owned Automobiles
Fixed Assets and Consumer Durable Goods in the United States, 1925–97 M–37

Glossary

Average age of net stock at the end of a given year is a

weighted average of the ages of all depreciated investment in the stock as of yearend. The weight for each

age is based on the proportion of its value as part of the

total net stock. The average ages of net stocks are presented only for the current-cost and historical-cost valuations.

Consumer durables. See Durable goods owned by consumers.

Corporate business consists of all entities required to

file Federal corporate income tax returns (IRS Form

1120 series), including mutual financial institutions

and cooperatives subject to Federal income tax, nonprofit organizations that primarily serve business, Federal Reserve banks, and federally sponsored credit

agencies.

Current-cost valuation measures the value of fixed

assets and consumer durables in the prices of the given

period, which are at year end for net stocks and annual

averages for depreciation.

Depreciation is the charge for the using up of private

and government fixed assets and consumer durables.

Specifically, it is defined as the decline in value due to

wear and tear, obsolescence, accidental damage, and

aging. For the estimates presented here, most assets are

assumed to have depreciation patterns that decline

geometrically over time so that, for a given year, the

constant-dollar depreciation charges on existing assets

are obtained by multiplying the prior year’s charge by

one minus the annual depreciation rate.

Durable goods owned by consumers are commodities

purchased by consumers for their nonbusiness use that

can be used repeatedly and continuously over a period

of three or more years.

Financial industries consists of the following SIC industries: Depository institutions, nondepository institutions, security and commodity brokers, insurance

carriers, regulated investment companies, small business investment companies, and real estate investment

trusts.80

80. Regulated investment companies, small business investment companies, and real estate investment trusts are included in the SIC classification

“holding and other investment offices” and are not shown separately in the

NIPA tables or in the estimates presented here.

Fixed assets consists of structures, equipment, and

software that are owned by private business, nonprofit

institutions, Federal, and State and local government

agencies including government enterprises that are located in the United States (except for national defense

equipment, for which coverage is worldwide).

Government fixed assets consists of equipment, software, and structures that are owned by Federal or State

and local governments, including government enterprises, and that are located in the United States (except

for national defense equipment and U.S. embassies

abroad, for which coverage is worldwide).

Gross investment is the value of purchases of new

fixed assets and net purchases of used assets at depreciated cost from other types of owners (private business,

governments, households, and nonresidents). Data are

not available to adjust for net purchases of used assets

at depreciated cost among industries or among legal

forms of organization. In this volume, purchases of

consumer durables are also treated as part of gross investment, in contrast to the NIPAs, which do not treat

them as investment.

Historical-cost valuation measures the value of fixed

assets and consumer durables in the prices of the periods in which the assets were purchased new.

National defense fixed assets consists of equipment,

software, and structures owned by the U.S. Department of Defense. It excludes family housing for the

armed forces, civil works construction by the Army

Corps of Engineers, industrial facilities, military hospitals, and the Soldiers’ and Airmen’s Home. 

Net stock is the value of fixed assets and consumer

durables after accounting for depreciation. For historical-cost valuation and for real-cost valuation at the deflation level, the perpetual inventory method calculates

the net stock as the cumulative value of past gross investment less the cumulative value of past depreciation, with adjustments for catastrophic losses and for

net purchases of used assets at depreciated cost. For

current-cost valuation, the net stock is the value of the

items in the real-cost net stock measured in current,

yearend prices.

Nondefense fixed assets consists of all structures and

equipment and software owned by the Federal Government other than National defense structures and

Glossary and Guide to the Tables
M–38 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

equipment and software.

Nonfinancial industries consists of all SIC private industries other than those classified as financial industries (and listed above).

Other private business consists of all entities that are

required to report rental and royalty income on the individual income tax return in IRS Schedule E (Supplemental Income and Loss) if the individual meets the

filing requirements, tax-exempt cooperatives,

owner-occupied nonfarm housing, and buildings and

equipment owned and used by nonprofit institutions

that primarily serve individuals.

Owner-occupied residential assets consists of housing

occupied by private owners.

Partnerships consists of all entities required to file

Federal partnership income tax returns, IRS Form

1065 (U.S. Partnership Return of Income).

Private fixed assets consists of equipment, software,

and residential and nonresidential structures, including owner-occupied housing, that are owned by private business or nonprofit institutions.81 All privatelyowned fixed assets located in the United States are included regardless of whether they are owned by U.S.

residents.

Real-cost valuation measures the value of fixed assets

and consumer durables after the effects of price change

have been removed. Estimates for the aggregates are

presented as chain-type quantity indexes, with 1996

equal to 100. These indexes are computed using annual-weighted Fisher-type indexes to obtain

year-to-year growth rates, which are chained together

to obtain cumulative growth rates. Estimates for selected higher-level aggregates are also presented in

chained (1996) dollars.82

Sole proprietorships consists of owner-occupied farm

housing and of all entities that are required to file IRS

Schedule C (Profits or Loss From Business) or Schedule F (Farm Income and Expenses) when the propri81. For private business and government, equipment is defined as assets

with a life expectancy of at least one year.

etor meets the filing requirements.

Tenant-occupied residential assets consists of rental

housing, including all government-owned residential

assets.

Guide to the Tables

The tables in this publication are presented in eight

sections. Section 1, which consists of seven tables, presents summary estimates of private fixed and government assets and durable goods owned by consumers.

Section 2, which consists of five tables, presents estimates of private fixed equipment and software and

structures by type of asset. Section 3, which consists of

five tables, presents estimates of private fixed nonresidential and residential equipment and software and

structures by industry. Section 4, which consists of five

tables, presents estimates of fixed nonresidential private assets, by major industry group and by legal form

of organization. Section 5, which consists of five tables,

presents estimates of residential fixed assets by type of

owner, by legal form of organization, by industry, and

by tenure group. Section 6, which consists of five tables, presents estimates of private fixed assets by legal

form of organization and by industry. Section 7, which

consists of four tables, presents estimates of fixed government assets. Section 8, which consists of four tables,

presents estimates of durable goods owned by consumers by type of good. Section 9, which consists of 3

tables, presents chained dollar estimates of net stocks,

depreciation, and investment.

82. The most detailed estimates presented in this volume are generally at

the deflation level, the lowest level of detail for which investment price

indexes exist. Estimates presented at this level are equivalent to estimates

measured in constant (1996) prices. However, a few of the detailed investment series within private equipment and software are more aggregated

than the deflation level; where the detailed components have different

deflators, the estimates are measured in constant (1996) prices and differ

slightly from comparable estimates measured in chained (1996) dollars. For

a discussion of the difference between chained-dollar and constant-price

estimates, see J. Steven Landefeld and Robert P. Parker, “BEA’s Chain

Indexes, Time Series, and Measures of Long-Term Economic Growth,” SURVEY 77 (September 1997): 58–68.
380 Fixed Assets and Consumer Durable Goods in the United States, 1925–97

Section 2. Private Fixed Assets by Type

1. Excludes software “embedded” or bundled in

computers and other equipment.

2. Consists of office buildings, except those occupied by electric and gas utility companies.

3. Consists primarily of stores, restaurants,

garages, service stations, warehouses, and other

buildings used for commercial purposes.

4. Consists of buildings not elsewhere classified,

such as passenger terminals, greenhouses, and animal hospitals.

5. Consists primarily of streets, dams, reservoirs,

sewer and water facilities, parks, and airfields.

6. Consists primarily of dormitories and of fraternity and sorority houses.

n.e.c. Not elsewhere classified.

Section 3. Private Fixed Assets by Industry

1. Fixed assets of nonprofit institutions serving

individuals are included in the real estate industry.

2. Consists of social services; museums, botanical

and zoological gardens; membership organizations;

engineering and management services; and services,

not elsewhere classified.

NOTE. Estimates in this table are based on the 1987

Standard Industrial Classification (SIC). 

Section 5. Residential Fixed Assets by Type of

Owner, Legal Form of Organization, Industry, and

Tenure Group

1. Excludes stocks of other nonfarm residential

fixed assets, which consist primarily of dormitories

and of fraternity and sorority houses.

Section 7. Government Fixed Assets

1. Consists of the fixed assets of general government and government enterprises.

2. Consists primarily of general office buildings,

police and fire stations, courthouses, auditoriums,

garages, and passenger terminals.

3. Consists of Department of Defense structures,

except family housing.

4. Consists primarily of electric and gas facilities,

transit systems, and airfields.

Section 8. Consumer Durable Goods

1. Consists of recreational vehicles and accessories

and parts.

2. Consists of refrigerators and freezers, cooking

ranges, dishwashers, laundry equipment, stoves, air

conditioners, sewing machines, vacuum cleaners,

and other appliances except for built-in appliances,

which are classified as part of residential structures.

3. Includes floor coverings, comforters, quilts,

blankets, pillows, picture frames, mirrors, art products, portable lamps, and clocks. Also includes writing equipment and hand, power, and garden tools.

Footnotes to the Tables

The following footnotes apply to all tables in the section in which they appear.