PRODUCTIVITY MEASUREMENT WITHIN A NEW ARCHITECTURE
FOR THE U.S. NATIONAL ACCOUNTS: LESSONS FOR ASIA

byDale W. Jorgenson
Samuel W. Morris University Professor
Harvard University
January 15, 2009

APO-Keio Lecture
Keio University
Tokyo, Japan

PRODUCTIVITY MEASUREMENT WITHIN A NEW ARCHITECTURE
FOR THE U.S. NATIONAL ACCOUNTS: LESSONS FOR ASIA

byDale W. Jorgenson1
Abstract. The key elements of a new architecture for the U.S. national accounts
have been developed in a prototype system constructed by Dale W. Jorgenson and
J. Steven Landefeld, Director of the Bureau of Economic Analysis, U.S.
Department of Commerce. The focus of the U.S. national accounts is shiftingfrom economic stabilization policy toward enhancing the economy’s growthpotential. This paper outlines the measurement of productivity within the new
system of U.S. national accounts. (JEL Classification: E01.)
This paper describes the measurement of productivity within a new architecture
for the U.S. national accounts.2 In this context “architecture” refers to the conceptual
framework for the national accounts. An example is the seven-account system recently
introduced by the Bureau of Economic Analysis (BEA).3 A second example is the United
Nations’ 1993 System of National Accounts (1993 SNA).4 Both provide elements of acomplete accounting system, including production, income and expenditures, capitalformation, and wealth accounts. The purpose of such a framework is to provide a strategy
for developing the national accounts.
The first question to be addressed is, why do we need a new architecture? The
basic architecture of the U.S. national accounts has not been substantially altered in fifty
years. The national accounts were originally constructed to deal with issues arising fromthe Great Depression of the 1930s, focusing on the current state of the economy.5 In themeantime, the focus of U.S. monetary and fiscal policies has shifted from economic

1

Samuel W. Morris University Professor, Harvard University, and Chairman, Bureau of Economic
Analysis Advisory Committee. More information about the author is available from:http://www.economics.harvard.edu/faculty/jorgenson/.
2
I am much indebted to J. Steven Landefeld for his collaboration on an earlier phase of this research.
Special thanks are due to Jon Samuels of Johns Hopkins University for excellent research assistance andvery helpful comments. Financial support by the Alfred P. Sloan Foundation and the Donald B. Marron
Fund for Research at Harvard University is gratefully acknowledged.
3
The BEA’s seven-account system is summarized in Jorgenson and Landefeld (2006).
4
United Nations, Commission of the European Communities, International Monetary Fund, Organisation
for Economic Cooperation and Development, and the World Bank (1993). Implementation of the SNA in
Australia, Canada, and the United Kingdom is described in Karen Wilson (2006).
5
See Landefeld (2000) on the origins of the U.S. national accounts.

stabilization to enhancing the economy’s growth potential.6 In addition, the U.S.
economy is confronted with new challenges arising from rapid changes in technology andglobalization. Meeting these challenges will require a new architecture for the U.S.
national accounts.
America’s economy is large and diverse. It is not surprising that accounting forthe vast range of economic activities requires a decentralized statistical system. The
major agencies involved in generating the national accounts include the Bureau of
Economic Analysis (BEA) in the Department of Commerce, the Bureau of Labor
Statistics (BLS) in the Department of Labor, and the Board of Governors of the Federal
Reserve System (FRB). The Census Bureau, also in the Department of Commerce, andthe Statistics of Income (SOI) division of the Internal Revenue Service in the Departmentof the Treasury are major sources of primary data. Many other public agencies andprivate sector organizations provide data for the national accounts.
Without being exhaustive it is useful to enumerate some of the key assignments of
the leading contributors to the U.S. national accounts. BEA has responsibility for the coresystem of accounts, the National Income and Product Accounts (NIPAs). BLS generates
employment statistics, wage and salary data, and productivity statistics, as well as almost
all of the underlying price information. FRB produces the Flow of Funds Accounts,
including income statements and balance sheets for major financial and non-financial
sectors. The Census Bureau collects and reports much of the primary information throughits business and population censuses and surveys. SOI generates tax-based data on
individual and corporate incomes.7
The national income and product accounts, the productivity statistics, and theflow of funds have different origins, reflecting diverse objectives and data sources.
However, they are intimately linked. For example, the BLS productivity statistics employ
data on output, income, and investment from the NIPAs. The flow of funds incorporates
BEA data on investment and stocks of reproducible assets and the U.S. International
Investment Position. An important part of the motivation for a new architecture is tointegrate the different components and make them consistent.
As an illustration, both BEA and BLS measure industry output.8 BEA’s estimates
are used to allocate the gross domestic product to individual industries. BLS’s estimatesof output are employed in measures of industry-level productivity growth. Unfortunately,
the BEA and BLS estimates of industry output do not coincide. An important objective of
the new architecture is to integrate the data sources employed by BEA and BLS in order
to arrive at a common set of estimates. This is a crucial ingredient in long-term
projections of the U.S. economy. These depend on disparate trends in productivity
6

See Jorgenson, Ho, and Stiroh (2008) for an application of the new architecture in assessing the potential
growth of the U.S. economy.
7
The extensive documentation available for the U.S. national accounts, much of it on line, is described inJorgenson and Landefeld (2006, pp. 107-109). A recent summary is provided in Landefeld, Seskin, andFraumeni (2008).
8
BEA and BLS measures of industry output have been compared in detail by Fraumeni, Harper, Powers,
and Yuscavage (2006).

growth in key industries, such as information technology producers and intensive users of
information technology.
The foregoing review identifies a clear need to update, integrate, and extend the
U.S. system of national accounts. Development of a fully integrated and consistentsystem of accounts will require close collaboration among BEA, BLS, and FRB, as wellas coordination with Census, the most important agency for generating primary source
data. The first and most important objective is to make the NIPAs consistent with theaccounts for productivity compiled by BLS. This will require a new approach to
productivity measurement.
1. The New Architecture.
The key elements of the new architecture are outlined in a “Blueprint for
Expanded and Integrated U.S. Accounts,” by Jorgenson and Landefeld.9 They present a
prototype system that integrates the national income and product accounts withproductivity statistics generated by BLS. The system features gross domestic product(GDP), as does the National Income and Product Accounts; however, GDP and grossdomestic income (GDI) are generated along with productivity estimates in an internallyconsistent way.
Issues in measuring productivity were considered by a Statistical Working Partyof the OECD Industry Committee, headed by Edwin Dean, former AssociateCommissioner for Productivity and Technology of BLS. The Working Party establishedinternational standards for productivity measurement at both aggregate and industry
levels. The results are summarized in Paul Schreyer’s OECD Productivity Manual,published in 2001. Estimates of multifactor productivity in the prototype systemdeveloped by Jorgenson and Landefeld conform to the standards presented in Schreyer’s
Productivity Manual.
In integrating the components of the U.S. national accounts, the first question to
be addressed is, why not use the 1993 SNA? BEA income and expenditures data and
FRB flow of funds data have been integrated within the framework for 1993 SNA byAlbert Teplin, et al. This initial effort has been followed by an annual update, publishedin the Survey of Current Business, BEA’s monthly journal, and available on the BEA
website.10 SNA-USA is not the only effort at BEA to provide the U.S. national accounts
in the 1993 SNA format. The U.S. national accounts are reported annually to the OECDin this format and the results are published in the OECD’s internationally comparable
national accounts.11
The 1993 SNA is part of the new architecture, since it embodies the collective
experience of the national accounting community and is familiar to many people working
on the U.S. national accounts. However, the SNA 1993 does not provide the production
9

See Jorgenson and Landefeld (2006). An updated version is presented by Jorgenson (2009).
The most recent annual update is presented by Bond, Martin, McIntosh, and Mead (2007).
11
Details on the U.S. national accounts in 1993 SNA format are presented by Mead, Moses, and Moulton(2004).
10

account in current and constant prices required for productivity measurement within the
new architecture.12 Also, consistency of the boundaries among the various component
accounts is an unresolved issue. Wealth, for example, refers to a different set of economic
units than income and product.
The prototype system of Jorgenson and Landefeld begins with the NIPAs andgenerates the production accounts in current and constant prices. The production accounts
provide a unifying methodology for integrating the NIPAs generated by BEA and the
productivity statistics constructed by BLS. Adding productivity statistics to the national
accounts remedies a critical omission in the NIPAs and the 1993 SNA. Other important
advantages of beginning with the NIPAs are that the existing U.S. national accounts canbe incorporated without modification and improvements in the NIPAs can be added asthey become available.
For example, BEA is currently engaged in a major program to improve theexisting system of industry accounts and accelerate the production of industry data by
2008.13 This program will integrate the NIPAs with the Annual Input-Output Accounts
and the Benchmark Input-Output Accounts produced every five years. Improvements inthe source data are an important component of this program, especially in measuring theoutput and intermediate inputs of services.14 The Census Bureau has generated important
new source data on intermediate inputs of services and BLS has devoted a major effort toimproving the service price data essential for measuring output in constant prices.15
The major challenge in implementing a consistent and integrated production
account is the construction of a measure of GDI in constant prices. The 1993 SNA and
BLS (1993) have provided appropriate measures of the price and quantity of labor
services. These can be combined with the price and quantity of capital services
introduced by BLS (1983) to generate price and quantity indexes of GDI, as well as
multifactor productivity. The primary obstacle to constructing of capital service measures
is the lack of market rental data for different types of capital. Although rental markets
exist for most types of assets, such as commercial and industrial real estate and industrial
and transportation equipment, relatively little effort has been made to collect rental
prices, except for renter-occupied housing.
An alternative approach for measuring rental prices, employed by BLS, is to
impute these prices from market transactions prices for the assets, employing the user
cost formula introduced by Jorgenson (1963). This requires estimates of depreciation andthe rate of return, as well as asset prices based on market transactions. Measures of asset
prices and depreciation, as well as investment and capital stocks, are presented in BEA’s
12

A program to update the 1993 SNA is scheduled for completion in 2008 and 2009. A report on therevision is presented by the United Nations Statistical Commission (2007). Proposals for revision of the1993 SNA are discussed by Moulton (2004).
13
The BEA industry program is described by Lawson, Moyer, Okubo, and Planting (2006) and Moyer,
Reinsdorf, and Yuscavage (2006).
14
This is the subject of important research by Triplett and Bosworth (2004). An update is presented in
Triplett and Bosworth (2006).
15
See the Panel Remarks by Mesenbourg (2006) and Utgoff (2006).

(2003) reproducible wealth accounts. BLS has generated estimates of the rate of return by
combining property income from the NIPAs with capital stocks derived from BEA’s
estimates of investment. BLS employs the imputed rental prices as weights foraccumulated stocks of assets in generating price and quantity measures of capital
services.
The most important innovation in the prototype system of national accounts
developed by Jorgenson and Landefeld is to include prices and quantities of capital
services for all productive assets in the U.S. economy. The incorporation of the price andquantity of capital services into the revision of the 1993 SNA was approved by theUnited Nations Statistical Commission at its February-March 2007 meeting. A draft ofChapter 20 of the revised SNA, “Capital Services and the National Accounts,” isundergoing final revisions and will be published in 2009. Paul Schreyer, head of national
accounts at the OECD, has prepared an OECD Manual, Measuring Capital, that will be
published in 2008. This provides detailed recommendations on methods for theconstruction of prices and quantities of capital services
In Chapter 20 of the revised 1993 SNA, estimates of capital services are describedas follows: “By associating these estimates with the standard breakdown of value added,
the contribution of labour and capital to production can be portrayed in a form ready foruse in the analysis of productivity in a way entirely consistent with the accounts of the
System.” The measures of capital and labor inputs in the new architecture for the U.S.
national accounts are consistent with the revised SNA and the OECD Manual, Measuring
Capital. The volume measure of input is a quantity index of capital and labor services,while the volume measure of output is a quantity index of investment and consumption
goods. Productivity is the ratio of output to input.
The new architecture has been endorsed by the Advisory Committee on
Measuring Innovation in the 21st Century Economy to the U.S. Secretary of Commerce,
Carlos Guttierez.16 The first recommendation of the Advisory Committee is:Develop annual, industry-level measures of total factor productivity by
restructuring the NIPAs to create a more complete and consistent set of accounts
integrated with data from other statistical agencies to allow for the consistentestimation of the contribution of innovation to economic growth.17
The Advisory Committee endorses the new architecture in the following words:

16

The Advisory Committee on Measuring Innovation in the 21st Century Economy (2008). The Advisory
Committee was established on December 6, 2007, with ten members from the business community,
including Carl Schramm, President and CEO of the Kauffman Foundation and chair of the Committee, Sam
Palmisano, Chairman and CEO of IBM, and Steve Ballmer, President of Microsoft. The Committee also
had five academic members, including Jorgenson. The Advisory Committee met on February 22 andSeptember 12, 2007, to discuss its recommendations. The final report was released on January 18, 2008.
17
The Advisory Committee on Measuring Innovation in the 21st Century Economy (2008, p. 7).

The proposed new ‘architecture’ for the NIPAs would consist of a set of income
statements, balance sheets, flow of funds statements, and productivity estimates
for the entire economy and by sector that are more accurate and internallyconsistent. The new architecture will make the NIPAs much more relevant totoday’s technology-driven and globalizing economy and will facilitate thepublication of much more detailed and reliable estimates of innovation’scontribution to productivity growth.18
In response to the Advisory Committee’s recommendations, BEA and BLS haveproduced a first set of estimates integrating multifactor productivity with the NIPAs.
The results were reported at a special session on economic statistics at the Annual
Meeting of the American Economic Association in San Francisco on January 4, 2009.
This is an important step in implementing the new architecture.
The production account for the prototype system of accounts presented below isbased on the gross domestic product (GDP) and gross domestic income (GDI) in current
and constant prices. Multifactor productivity is the ratio of GDP to GDI in constantprices. Estimates of productivity are essential for projecting the potential growth of the
U.S. economy, as demonstrated by Jorgenson, Mun Ho, and Kevin Stiroh (2008). The
omission of productivity statistics from the NIPAs and the 1993 SNA is a serious barrier
to application of the national accounts in assessing potential economic growth.
The production account has been disaggregated to the level of 85 industries,
covering the period 1960-2005 by Jorgenson, Mun Ho, Jon Samuels, and Kevin Stiroh(2007), Industry Origins of the American Productivity Resurgence. The methodology
follows that of Jorgenson, Ho and Stiroh (2005), Information Technology and theAmerican Growth Resurgence. This methodology conforms to the international standards
established the OECD Productivity Manual (2001).19 The EU KLEMS project has
recently developed systems of production accounts based on this methodology for the
economies of all European Union (EU) member states.20 For major EU countries thisproject includes accounts for 72 industries, covering the period 1970-2005.
A combined production account for Japan and the U.S. for 42 industries, covering
the period 1960-2004, has been presented by Jorgenson and Koji Nomura (2007) in theirpaper, The Industry Origins of the U.S.-Japan Productivity Gap.21 The JapaneseIndustrial Productivity Data Base 2008 has been released by the Research Institute on
Economy, Trade, and Industry.22 This provides an industry-level production account for
108 sectors for the period 1970-2005. The JIP Data Base has been used for international

18

The Advisory Committee on Measuring Innovation in the 21st Century Economy. (2008, p. 8).
See Schreyer (2001).
20
The EU KLEMS project was completed on June 30, 2008. For further details see: www.euklems.net/.
A summary of the findings is presented by Ark, O’Mahoney, and Timmer (2008).
21
Additional details on the production account for Japan are given by Jorgenson and Nomura (2005), The
19

Industry Origins of Japanese Economic Growth.
22

See Kyoji Fukao and Tsutomu Miyagawa (2008), JIP Data Base 2008, Tokyo, Research Institute on
Economy Trade, and Industry, September.

comparisons as a part of the EU KLEMS project by Fukao and Miyagawa (2007),
Productivity in Japan, the US, and the Major EU Economies: Is Japan Falling Behind?
The first step in implementing the prototype accounting system in Section 2 is todevelop the production account in current prices for the U.S. economy for 1948–2006.
Section 3 introduces accounts in constant prices with a description of index numbers forprices and quantities. The accounts in constant prices begin with production. The productside includes consumption and investment goods output in constant prices. The income
side includes labor and capital inputs in constant prices. Multifactor productivity is theratio of real product to real input. Section 4 illustrates the application of the newarchitecture for the U.S. national accounts by considering the sources of U.S. economic
growth. Section 5 concludes.
2. Prototype Accounting System.
This section lays out a prototype system of U.S. national accounts that builds
directly on the NIPAs. The measurement of income and wealth requires a system ofseven accounts. This system must be carefully distinguished from the new system ofseven accounts employed in presenting the NIPAs. The Domestic Income and ProductAccount provides data on the outputs of the U.S. economy, as well as inputs of capitaland labor services. Incomes and expenditures are divided between two accounts – theIncome and Expenditures Account and the Foreign Transactions Current Account.
Capital accumulation is recorded in two accounts – the Domestic Capital Account and theForeign Transactions Capital Account. Finally, assets and liabilities are given in the
Wealth Account and the U.S. International Position.
A schematic representation of the prototype accounting system for the newarchitecture is given in figure 1.The complete accounting system includes a production
account, incorporating data on output and input, an income and expenditures account,giving data on income, expenditures, and saving, and an accumulation account, allocating
saving to various types of capital formation. A national balance sheet contains data on
national wealth. Finally, the accumulation accounts are related to the wealth accounts
through the accounting identity between period-to-period changes in wealth and the sumof net saving and the revaluation of assets.
The production, income and expenditures, accumulation, and wealth accounts arelinked through markets for commodities and factor services. For example, the price ofinvestment goods output in the production account is linked to the price of assets in thewealth account. This price is a component of the price of capital services in the
production account. The price of capital services also includes the change in the price of
the asset and this also occurs as the price of revaluation in the accumulation account. The
price of labor input is the price of labor services in the production account and the priceof labor income in the income account. Finally, the price of consumption appears as theprice of consumption goods output in the production account and the price ofconsumption expenditures in the income and expenditure account.

The Domestic Income and Product Account features gross domestic product(GDP) and gross domestic income (GDI), following the NIPAs. Both GDP and GDI arepresented in current and constant prices. The fundamental accounting identity is that
GDP is equal to GDI in current prices. Multifactor productivity, a summary measure ofinnovation, is defined as the ratio of GDP to GDI in constant prices. The interpretation of
output, input, and productivity requires the concept of a production possibility frontier.23
In each period the inputs of capital and labor services are transformed into outputs ofconsumption and investment goods. This transformation depends on the level ofproductivity.
The Domestic Income and Product Account for the U.S. economy includes
business, household and government sectors.24 Imputations for the services of consumer
durables and durables used by nonprofit institutions, as well as the net rent on
government durables and government and institutional real estate, are introduced in orderto achieve consistency between investment goods production and property compensation.
The services of these assets are included in the output of services, together with theservices of owner-occupied dwellings, so that both are included in consumption goods
production. Both also appear in property compensation, assuring that the accounting
identity between the value of output and the value of input is preserved.
Gross domestic product in the NIPAs is divided among non-durable goods,
durable goods, and structures, as well as services. The output of durables includes
consumer durables and producer durables used by governments and nonprofit
institutions, as well as producer durables employed by private businesses. The output ofstructures includes government structures, private business structures, institutional
structures, and new residential housing.
In the NIPAs the rental value of owner-occupied residential real estate, including
structures and land, is imputed from market rental prices of renter-occupied residential
real estate. The value of these services is allocated among net rent, interest, taxes, andconsumption of fixed capital. A similar imputation is made for the services of real estateused by nonprofit institutions, but the imputed value excludes net rent. Finally,
depreciation on government capital is included, while net rent on this capital is excluded.
No property compensation for the services of consumer durables or producer durables
used by nonprofit institutions is included. By imputing the value of these services and the
net rent of government capital and real estate used by nonprofit institutions, the treatmentof property compensation for these assets is aligned with that for assets used by private
businesses.
Taxes charged against revenue, such as excise or sales taxes, must be carefully
distinguished from taxes that are part of the outlay on capital services, such as property
taxes. In the production account output taxes are excluded from the value of output,
23

This interpretation is developed by Jorgenson (1966), Jorgenson and Stiroh (2000), and Jorgenson(2001).
24
Our estimates are based on those of Jorgenson (2001), updated through 2006 to incorporate data from the2003 benchmark revision of the U.S. national accounts.

reflecting prices from the producers’ point of view. However, taxes on input are included,
since these taxes are included in the outlay of producers. Taxes on output reduce theproceeds of the sector, while subsidies increase these proceeds; accordingly, the value of
output includes production subsidies. To be more specific, excise and sales taxes,
business non-tax payments, and customs duties are excluded from the value of output andindirect business taxes plus subsidies are included. This valuation of output corresponds
to the value of output at “basic prices” in the 1993 SNA. The Domestic Income andProduct Account for 2006 is presented in table 1.
Gross domestic income includes income originating in private enterprises andprivate households and institutions, as well as income originating in government. The
imputed rental value of consumer durables, producer durables utilized by institutions, andthe net rent on government durables and real estate and institutional real estate are added,
together with indirect taxes included in the value of these inputs. The value of capital
inputs also includes consumption of fixed capital and the statistical discrepancy;
consumption of fixed capital is a component of the rental value of capital services. The
value of gross domestic income for 2006 is presented in table 1.
Product and income accounts are linked through capital formation and property
compensation. To make this link explicit gross domestic product is divided between
consumption and investment goods and gross domestic income between labor andproperty compensation. Investment goods production is equal to the total output of
durable goods and structures. Consumption goods production is equal to the output of
non-durable goods and services from the NIPAs, together with the imputations for theservices of consumer and institutional durables and the net rent on government durables
and real estate, as well as institutional real estate.
Property income includes the statistical discrepancy and taxes included inproperty compensation, such as motor vehicle licenses, property taxes, and other taxes.
The imputed value of the services of government, consumer and institutional durables,
and the net rent on government and institutional real estate are also included. Labor
income includes the compensation of employees of private enterprises, households andnonprofit institutions, as well as government. The value of labor input also includes thelabor compensation of the self-employed. This compensation is estimated from theincomes received by comparable categories of employees.25 Gross domestic product,
divided between investment and consumption goods output, and gross domestic income,divided between labor and property income, are given for 1948-2006 in table 2.
Although it will eventually be desirable to provide a breakdown of the prototype
system of U.S. national accounts by industrial sectors, the prototype system constructedby Jorgenson and Landefeld is limited to aggregates for the U.S. economy as a whole.
Disaggregating the production account by industrial sector will require a fully integrated
system of input-output accounts and accounts for gross product originating by industry,
as described by Ann Lawson, et al. (2006), and Brian Moyer, et al. (2006). This can be
combined with the measures of capital, labor, and intermediate inputs by industry
25

Details are provided by Jorgenson, Ho, and Stiroh (2005, pp. 201-290).

presented by Jorgenson, et al. (2005), to generate production accounts by sector.26 The
principles for constructing these production accounts are discussed by Fraumeni, et al.
(2006).
3. Production Account.
In order to express an accounting magnitude in constant prices the value incurrent prices must be separated between prices and quantities. Estimates in constantprices are associated with a quantity index, while the price index is an implicit deflator.
As an illustration, GDP in current prices in the Domestic Income and Product Account is
the product of GDP in constant prices and the implicit price deflator for GDP. Similarly,
GDI in current prices is the product of GDI in constant prices and the implicit deflator for
GDI.
The principal innovation in presenting the Domestic Income and ProductAccount in constant prices is to introduce a user cost formula for imputing the rental
price of capital services from market prices for the underlying assets. Systems of national
accounts have traditionally relied on market rental prices for making these imputations,but data on market rentals are too limited in scope for an integrated and consistent system
of U.S. national accounts. In this section the Domestic Income and Product Account ispresented in constant prices.
3.1. Index Numbers.
To illustrate the construction of price and quantity index numbers for output in
the Domestic Income and Product Account, suppose that m components of output are
distinguished in the accounts; the value of output, say qY, can be written:
qY = q1Y1 + q2Y2 + L + qmYm .

The system of index numbers consists of a price index for output q and a quantity index
for output Y, defined in terms of the prices (qi) and quantities (Yi) of the m components.
The base for all price indexes in the prototype system of U.S. national accounts is 1.000
in 2000, following the December 2003 benchmark revision of the NIPAs. The base forthe quantity indexes is the corresponding value in 2000.
Landefeld and Robert Parker (1997) provide a detailed exposition of the chained
Fisher ideal price and quantity indexes employed in the NIPAs. Erwin Diewert (1976)
has defined a superlative index number as an index that exactly replicates a flexible
representation of the underlying technology (or preferences). A flexible representation
26

A system of production accounts for industrial sectors of the U.S. economy is given by Jorgenson,
Gollop, and Fraumeni (1987). This incorporates a consistent time series of input-output tables and provides
the basis for the industry-level production accounts presented in Schreyer (2001). The system of production
accounts of Jorgenson, Gollop, and Fraumeni has been updated and revised to incorporate information on
information technology producing sectors by Jorgenson, Ho, and Stiroh (2005). Chapter 4, pp. 87-146,
provides details on the construction of the time series of input-output tables.

provides a second-order approximation to an arbitrary technology (or preference system).
A.A. Konus and S. S. Byushgens (1926) first showed that the Fisher ideal index
employed in the NIPAs is superlative in this sense. Laspeyres and Paasche indexes are
not superlative and fail to capture substitutions among products in response to pricechanges.
In the 1993 SNA superlative systems of index numbers like those employed in
the U.S. national accounts are recommended for the output side of the production accountand for labor input. As the base period is changed from time to time, chain-linking of theresulting price and quantity indexes is recommended. The index numbers in the prototype
system of U.S. national accounts are chain-linked Fisher ideal indexes of components
from the NIPAs.
At a number of points data net and gross of taxes are required, reflecting
differences between sellers and buyers that result from tax wedges. As one illustration,
consumer expenditures on goods and services in the Income and Expenditures Accountinclude sales and excise taxes, reflecting the purchasers’ point of view. Sales of the same
goods and services in the Domestic Income and Product Account exclude these taxes,
reflecting the perspective of producers. The prices net of taxes are denoted “basic prices”
in the 1993 SNA. Sales and excise taxes are treated as part of the price paid byconsumers, so that the value of transactions can be separated into three components—
price, quantity, and tax rate.27
3.2. Output.
The first step in constructing a quantity index for GDP is to allocate the value of
output between consumption and investment goods. Investment goods include durable
goods and structures. Consumption goods include non-durable goods and services. Datafor prices and quantities of consumption and investment goods are presented in the
NIPAs. Price and quantity index numbers for the services of consumer, institutional andgovernment durables, as well as institutional and government real estate, are part of theimputation for the value of the capital services.
The value of output from the point of view of the producing sector excludes sales
and excise taxes and includes subsidies. These taxes and subsidies are allocated inproportion to the consumption and investment goods output in current prices. The priceindex for each type of output is implicit in the value and quantity of output included in
the GDP. Price and quantity indexes of GDP are constructed by applying chained Fisher
ideal index numbers to price and quantity data for consumption and investment goods
product. The results are given in table 3.
3.3. Labor Input
Construction of a quantity index of labor income begins with data on hours
worked and labor compensation per hour. Hours worked and labor compensation by sex,
27

Additional details are given by Jorgenson and Landefeld (2006), pp. 66-68.

age, educational attainment, and employment class are obtained from the Census ofPopulation and the Current Population Survey. These data are based on household
surveys. Control totals for hours worked and labor compensation are taken from the
NIPAs. These totals are based on establishment surveys and reflect payroll records.28
Denoting the labor income quantity index by L and the corresponding price index
by pL, the value of labor input is the sum over all categories of labor input:
pL L = ∑ pL, j L j ,where pL, j is the price of the j-th type of labor input and Lj is the number of hours
worked by workers of this type. Price and quantity indexes of labor income areconstructed from chained Fisher ideal quantity indexes, as recommended in the 1993
SNA.
Price and quantity indexes of labor income for1948-2006 are given in table 4,along with employment, weekly hours, hourly compensation, and hours worked. Labor
quality in table 4 is defined as the ratio of the quantity index of labor income to hours
worked. Labor quality captures changes in the composition of the work force by thecharacteristics of individual workers, as suggested by BLS (1993). A more detailed
description of the sources and methods for these estimates is provided by Jorgenson, Hoand Stiroh (2005).
3.4. Capital Input
Estimates of capital income, property compensation, depreciation, and capital
assets in constant prices require data on prices and quantities of capital goods.29 The
starting point for a quantity index of capital income is a perpetual inventory of capitalstocks. Under the assumption that efficiency of capital assets declines geometrically withage, the rate of depreciation, say δ, is a constant. Capital stock at the end of every period
can be estimated from investment and capital stock at the beginning of the period:
K t = At + (1− δ )K t−1,

where Kt is end-of-period capital stock, At the quantity of investment and Kt-1 the capitalstock at the beginning of the period. To transform capital stocks into flows of capital
services, an assumption about the time required for new investment to begin to contributeto production must be introduced, namely, that the capital service from each asset is
proportional to the arithmetic average of current and lagged capital stocks30.

28

Details are given by Jorgenson, Ho, and Stiroh (2005, pp. 201-290).
Further details are given by Jorgenson, Ho, and Stiroh (2005, pp. 147-200).
30This assumption is employed by Jorgenson and Stiroh (2000), Jorgenson (2001), Jorgenson, Ho, andStiroh (2005) and Oliner and Sichel (2000). Jorgenson, Gollop and Fraumeni (1987) had assumed that
capital services were proportional to lagged capital stocks.
29

The perpetual inventory estimates of capital stocks are based on BEA’s fixed
assets accounts (2003). These data include investment by asset class for 61 types of nonresidential assets from 1901-2006, 48 types of residential assets for the same period, and13 types of consumers’ durables from 1925-2006. Government capital includes 12 typesof structures, six types of defense equipment, as well as other equipment and software.
As described by Fraumeni (1997), the reproducible wealth accounts use
efficiency functions for most assets that decline geometrically with age. The geometricdepreciation rates for these assets are taken from Fraumeni (1997). To simplify theaccounts for tangible wealth, the age-efficiency profiles that are not geometric areapproximated by Best Geometric Average (BGA) profiles that are geometric, following
Charles Hulten and Frank Wykoff (1982).31 Benchmark estimates of capital stocks in
2006, expressed in constant prices of 2000, rates of depreciation, and the sources of priceindexes for each type of capital are presented in table 5.
The price indexes for reproducible assets are taken from the NIPAs. These prices aremeasured in “efficiency” units, holding the performance of assets constant over time. For
example, the performance of computers and peripheral equipment is held constant, using
hedonic price indexes constructed by a BEA-IBM team and introduced into the NIPAs in
1985. Ellen Dulberger (1989) presents a detailed report on her research on the prices ofcomputer processors for the BEA-IBM project. Speed of processing and main memory
played central roles in her model. Jack Triplett (1989, 2005) has provided exhaustive
surveys of research on hedonic price indexes for computers. The official price indexes forcomputers provide the paradigm for economic measurement and capture the steadydecline in IT prices.32
Both software and hardware are essential for information technology and this isreflected in the large volume of software expenditures. The eleventh comprehensive
revision of the national accounts, released by BEA on October 27, 1999, re-classified
computer software as investment33. Before this important advance, business expenditures
on software were treated as current outlays, while personal and government expenditures
were treated as purchases of non-durable goods. Software investment is growing rapidly
and is now much more important than investment in computer hardware.
The value of wealth from the Flow of Funds accounts includes both reproducible
and non-reproducible assets. However, the BEA’s fixed assets accounts are limited toreproducible assets. We employ data for the price and quantity of land for households andnonprofit institutions, non-farm non-corporate business, and non-farm corporate businessprepared by Morris Davis (2008). These data are based on value of real estate from theFlow of Funds Accounts. The value of land is obtained by subtracting the cost of
structures from the value of real estate. We employ data on the value of farm land fromthe U.S. Department of Agriculture (2008) and data on government land and inventories
31

BEA efficiency profiles are discussed in Bureau of Economic Analysis (2008).
A survey of hedonic methods in the NIPAs is given by Wasshausen and Moulton (2006). Triplett (2004)
discusses the construction and application of hedonic price indexes.
33
Moulton (2000) describes the 11th comprehensive revision of NIPA and the 1999 update.
32

from the Office of Management and Budget (2008).34 Inventory data for the private
sector are from the NIPAs.
Given data on market rental prices by class of asset, the implicit rental values
paid by owners for the use of their property can be imputed by applying these rental rates
as prices. This method is used to estimate the rental value of owner-occupied dwellings in
the U.S. national accounts. The main obstacle to broader application of this method is thelack of data on market rental prices. A substantial portion of the capital goods employedin the U.S. economy has an active rental market. Most classes of structures can be rented
and a rental market exists for many types of equipment, especially aircraft, trucks,
construction equipment, computers, and so on. Unfortunately, very little effort has been
devoted to compiling data on rental rates for either structures or equipment.
An alternative approach for imputation of rental prices is to extend the perpetualinventory method to include prices of capital services.35 For each type of capital perpetualinventory estimates are prepared for asset prices, service prices, depreciation, andrevaluation. Under the assumption of geometrically declining relative efficiency of
capital goods, the asset prices decline geometrically with vintage. The formula for thevalue of capital stock,q A,t K t = ∑ q A,t (1 − δ )τ At −τ ,is the sum of past investments weighted by relative efficiencies and evaluated at the pricefor acquisition of new capital goods qA,t . Second, depreciation qD,t is proportional to thevalue of beginning of period capital stock:
qD,t K t−1 = δqA ,t K t−1.
Finally, revaluation (q A,t − q A,t −1 )K t −1 is equal to the change in the acquisition price of
new capital goods multiplied by beginning of period capital stock.
Households and institutions and government are not subject to direct taxes. Noncorporate business is subject to personal income taxes, while corporate business is subject
to both corporate and personal income taxes. Businesses and households are subject toindirect taxes on the value of property. In order to take these differences in taxation into
account each class of assets is allocated among the five sectors of the U.S. domestic
economy — corporations, non-corporate business, households, nonprofit institutions, andgovernment.36 The relative proportions of capital stock by asset class for each sector for2006 are given in table 6.
34

Eldon Ball of the USDA generously provided the data on farm land. Richard Anderson of OMB kindly
provided the historical data on government land and inventories in electronic form.
35
Christensen and Jorgenson (1973) present a detailed extension of the perpetual inventory method torental prices assets. They also provide a prototype accounting system for the private sector of the U.S.
economy with prices and quantities of capital services for all assets.
36
A detailed derivation of prices of capital services for all five sectors is given by Jorgenson and KunYoung Yun (2001).

For a sector not subject to either direct or indirect taxes, the capital service priceqK,t is:q K ,t = q A,t −1 [rt − π t + (1 + π t ) δ ],where rt is the nominal rate of return and π t is the rate of inflation in the acquisition
price of new capital goods. This formula can be applied to government and nonprofit
institutions by choosing an appropriate rate of return, as described below.37 Given the rateof return for government and nonprofit institutions, estimates can be constructed forcapital service prices for each class of assets held by these sectors —land held bygovernment and institutions, residential and nonresidential structures, producer andconsumer durables.
Households hold consumer durables and owner-occupied dwellings that are taxed
indirectly through property taxes. To incorporate property taxes into the estimates of theprice and quantity of capital services taxes are added to the cost of capital, depreciation,and revaluation. The household rate of return is a weighted average of the rate of interestand the nominal rate of return on equity in household assets. The weights depend on theratio of debt to the value of household capital stock. The nominal rate of return on equity
is set equal to the corresponding rate of return for owner-occupied housing after all taxes.
Given the rate of return for households, estimates of capital service prices can beconstructed for each class of assets held by households—land, residential structures, andconsumer durables. Separate effective tax rates are employed for owner-occupied
residential property, both land and structures, and for consumer durables.
The main challenge in the measurement of price and quantity of capital services
for non-corporate business is to separate the income of unincorporated enterprises
between labor and property compensation. Labor compensation of the self-employed isestimated from the incomes received by comparable categories of employees.38 Property
compensation as the sum of income originating in business, other than corporate businessand government enterprises and the net rent of owner-occupied dwellings, less theimputed labor compensation of proprietors and unpaid family workers, plus noncorporate consumption of fixed capital, less allowances for owner-occupied dwellings
and institutional structures, and plus indirect business taxes allocated to the non-corporate
sector. The statistical discrepancy is allocated to non-corporate property compensation.
The personal income tax must be taken into account in order to obtain an
estimate of the non-corporate rate of return. The capital service price must be modified toincorporate income tax and indirect business taxes.39 The non-corporate rate of return is aweighted average of the rate of interest and the nominal rate of return on non-corporate
37

Alternative methods for imputing the rate of return to capital are reviewed by Schreyer (2008).
Estimation of the labor compensation of the self-employed is discussed by Jorgenson, Ho, and Stiroh(2005).
39
Details are given by Jorgenson and Landefeld, pp. 77-78.
38

assets with weights that depend on the ratio of debt to the value of non-corporate capitalstock Given data on prices of acquisition, stocks, tax rates, and replacement rates, capital
service prices can be estimated for each class of assets held by the non-corporate sector.
Finally, corporate property compensation is the income originating in corporate
business, less compensation of employees, plus corporate consumption of fixed capital,plus business transfer payments, plus the indirect business taxes allocated to the corporate
sector. The corporate income tax must be taken into account to obtain an estimate of thecorporate rate of return.40 The method for estimating the corporate rate of return is thesame as for the non-corporate rate of return. Property compensation in the corporate
sector is the sum of the value of services from residential and nonresidential structures,producer durable equipment, inventories, and land held by the sector.
The nominal rate of return is assumed to be the same for all assets within a given
sector. For the corporate and non-corporate sectors this rate of return is inferred from thevalue of property compensation, asset prices based on market transactions, stocks ofcapital goods, rates of replacement, and variables describing the tax structure. For
households the rate of return is inferred from income from owner-occupied housing. For
government, the imputed rate of return is set equal to the average of corporate, noncorporate, and household rates of return after both corporate and personal taxes.
To obtain price and quantity indexes for capital services in the domestic sector
chained Fisher ideal and quantity indexes like those used in the NIPAs are calculated foreach of the five sub-sectors—corporations, non-corporate business, households,
institutions, and government. Price and quantity indexes of capital income forcorporations, non-corporate business, households, institutions, and government, as wellas the U.S. domestic economy are given for 1948-2006 in table 7.
Price and quantity index numbers for GDI are constructed by combining indexesof labor and capital income. The weights for labor and capital are the relative shares oflabor and capital income in GDI. Price and quantity indexes of GDI for the U.S. domestic
economy are given for 1948-2006 in table 8. Multifactor productivity, also given in table
8, is defined as the ratio of GDP in constant prices to GDI in constant prices.41 Growth inmultifactor productivity can be interpreted as an increase in efficiency of the use of input
to produce output or as a decline in the cost of input required to produce a given value of
output.

40

Details are given by Jorgenson and Landefeld, pp. 79-83.
This index of multifactor productivity conforms to the international standards presented in Schreyer(2001). For further discussion, see Jorgenson (2001).

41

4. The Sources of Economic Growth.

An important application of the prototype system of accounts is the analysis ofsources of U.S. economic growth.42 The sources of growth are essential for assessing the
growth potential of the U.S. economy. The sources of post-war U.S. economic growthrequire measures of output, input, and multifactor productivity from the Domestic
Income and Product Account presented in table 8.
The interpretation of outputs, inputs, and productivity requires the production
possibility frontier introduced by Jorgenson (1966):

Y ( I , C ) = A ⋅ X ( K , L),
Gross Domestic Product in constant prices Y consists of outputs of investment goods I
and consumption goods C. These products are produced from capital services K and labor
services L. These factor services are components of Gross Domestic Income in constantprices X and are augmented by multifactor productivity A.
The key feature of the production possibility frontier is the explicit role itprovides for changes in the relative prices of investment and consumption outputs. The
aggregate production function is a competing methodology and gives a single output as afunction of capital and labor inputs. There is no role for separate prices of investment andconsumption goods. Under the assumption that product and factor markets are incompetitive equilibrium, the share-weighted growth of outputs is the sum of the shareweighted growth of inputs and growth in multifactor productivity:
wI ΔI + wC Δ ln C = v K Δ ln K + v L Δ ln L + Δ ln A ,where w and v denote average shares of the outputs and inputs, respectively, in the valueof GDP in current prices.
Table 9 presents accounts for U.S. economic growth during the period 1948-2006
and various sub-periods, following Jorgenson (2001). The earlier sub-periods are divided
by the business cycle peak in 1973. The period since 1995, the beginning of a powerfulresurgence in U.S. economic growth linked to information technology, is divided in 2000,
the start of the dot-com crash. The contribution of each output is its growth rate weighted
by the relative value share. Similarly, the contribution of each input is its weighted
growth rate. Growth in multifactor productivity is the difference between growth rates of
output and input.
For the period 1948-2006 the most important source of economic growth wascapital services at 49.4 percent, while labor services contributed 31.6 percent. Multifactor
42

The international standards for aggregate growth accounting presented in Schreyer (2001) are discussed
in detail by Jorgenson, Ho, and Stiroh (2005, pp. 17-58). The demise of traditional growth accounting is
described by Jorgenson, Ho, and Stiroh (2005, pp. 49-58).

productivity growth contributed 19.0 percent of economic growth. After strong output
and productivity growth in the 1950s, 1960s and early 1970s, the U.S. economy slowedmarkedly from 1973 through 1995. Output growth fell from 3.99 to 2.79 percent andmultifactor productivity growth declined precipitously from 0.98 to 0.25 percent. The
contribution of capital input also slowed from 1.89 percent for 1948-73 to 1.41 percent
for 1973-95, while the labor input contribution increased slightly from 1.11 to 1.13
percent.
U.S. economic growth surged to 4.09 percent during the period 1995-2000.
Between 1973-1995 and 1995-2000 the contribution of capital input jumped by 0.76
percentage points, accounting for more than half the increase in output growth of 1.30
percent. This reflects the investment boom of the late 1990s, as businesses, households,
and governments poured resources into plant and equipment, especially computers,
software, and communications equipment. The contribution of labor input increased by arelatively modest 0.13 percent, while multifactor productivity growth accelerated by 0.41
percent.
After the dot-com crash beginning in 2000, U.S. economic growth slowed
substantially to 2.83 percent per year and the relative importance of investment declined
sharply. The contribution of capital services to economic growth dropped by 0.68 percent
per year, reverting almost to the level before 1995. The growth of multifactor
productivity also declined, but not as sharply, to 0.74 percent per year, while thecontribution of labor input sank to 0.60 percent per year.
The results presented above highlight the importance of having an internallyconsistent set of accounts like those provided by the new architecture. In the absence ofan integrated production account, the analysis of sources of economic growth at theaggregate and industry level would have to rely on a mixture of BEA industry accounts
estimates and BLS productivity estimates, combined with an analyst’s estimates of
missing information, such as growth in labor input per hour worked. With inconsistentsource data, different analysts could produce inconsistent results during periods of higher
or lower growth, such as the post-1973 productivity slowdown and the more recent spurt
in productivity growth since 1995.
5. Summary and Conclusions.

The first major innovation in the new architecture for the U.S. national accounts isthe utilization of imputed rental prices for capital assets, based on the user cost formula
introduced by Jorgenson (1963), for all productive assets in the U.S. economy. This is the
key to integration of the NIPAs generated by BEA with the BLS productivity accounts.
The price and quantity of capital services also provide a valuable link between the NIPAs
and the revised 1993 SNA that will be released in 2008 and 2009.
The second major innovation in the new architecture is the presentation of all
accounts in both current and constant prices. This makes it possible to incorporate data on
productivity into the NIPAs and the revised 1993 SNA. The new architecture challenges

conventional views of the U.S. economy. First, investment is the most important sourceof U.S. economic growth, growth of labor input is next, and productivity is a relativemodest contributor.
The implementation of a new architecture for the U.S. national accounts will open
new opportunities for development of the U.S. statistical system. The boundaries of the
U.S. national accounts are defined by market and near-market activities. An example of amarket-based activity is the rental of residential housing, while a near-market activity is
the rental equivalent for owner-occupied housing. The new architecture project is not
limited to these boundaries. Under the auspices of the National Research Council, theCommittee on National Statistics has outlined a program for development of non-market
accounts, covering areas such as health, education, household production, and theenvironment.43
BEA has recently extended the NIPAs to include a satellite account forinvestment in scientific research and development. Investment in software has been
included in the core system of accounts since 1999. Corrado, Hulten, and Sichel (2006)
have proposed a system of accounts for other intangible forms of investment.44 They
propose to include investments in scientific research and development and software, as
well as minerals exploration, training of workers, advertising, and non-scientific researchand development, such as the development of intellectual capital in the form of movies,
music, and the like. Other than software and scientific research and development, none ofthese intangible investments is now included in the NIPAs or in a satellite system ofaccounts.
Finally, the EU KLEMS project has generated industry-level production accounts,
like those described above for the U.S., for the economies of EU members and othermajor U.S. trading partners such as Australia, Canada, Japan, and Korea. These data will
greatly facilitate international comparisons and research into the impact of globalizationon the major industrialized economies. Efforts are also underway to extend the EU
KLEMS framework to important developing and transition economies, such as Brazil,
China, India, and Russia. This will open new opportunities for research on the impact of
globalization.
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43

The NRC report in summarized by Abraham and Mackie (2006). The conceptual framework for nonmarket accounts is presented by Nordhaus (2006).
44
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Figure 1: New Architecture for an Expanded and Integrated Setof National Accounts for the United States
1. PRODUCTION
Gross Domestic Product Equals
Gross Domestic Factor Outlay
2. DOMESTIC RECEIPTS

3. FOREIGN TRANSACTION CURRENT ACCOUNTAND EXPENDITURES

Receipts from Rest of World Equal

Domestic Receipts Equal

Payments to Rest of World andDomestic Expenditure

Balance on Current Account

4. DOMESTIC CAPITAL ACCOUNT

5. FOREIGN TRANSACTION CAPITAL ACCOUNT

Gross Domestic Capital Formation Equals

Balance on Current Account Equals

Gross Domestic Savings

Payments to Rest of the World andNet Lending or Borrowing

6. DOMESTIC BALANCE SHEET

7. U.S. INTERNATIONAL POSITION

Domestic Wealth Equals

U.S.-Owned Assets Abroad Equal

Domestic Tangible Assets andForeign-Owned Assets in U.S. and

U.S. Net International Position

U.S. Net International Position

Table 1: Domestic Income and Product Account, 2006
Line
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20 =

Product

GDP (NIPA)+ Services of consumers' durables+ Services of household land (net of BEA estimate)+ Services of durables held by institutions+ Services of durables, structures, land, and inventories held by government+ Private land investment+ Government land and inventory investment- General government consumption of fixed capital- Government enterprise consumption of fixed capital- Federal taxes on production and imports- Federal current transfer receipts from business- S&L taxes on production and imports- S&L current transfer receipts fom business+ Capital stock tax+ MV tax+ Property taxes+ Severance, special assessments, and other taxes+ Subsidies- Current surplus of government enterprises

SourceTotal

NIPA 1.1.5 line 1
our imputation
our imputation
our imputation
our imputation
our imputation
our imputation
NIPA 3.10.5 line 5
NIPA 3.1 line 38 - 3.10.5 line 5
NIPA 3.2 line 4
NIPA 3.2 line 16
NIPA 3.3 line 6
NIPA 3.3 line 18
NIPA 3.5 line 28
NIPA 3.3 line 8
NIPA 3.5 line 29,30,31
NIPA 3.1 line 25
NIPA 3.1 line 14

13,194.7
1,249.8
-16.0
40.1
424.1
10.2
61.9
223.6
44.1
98.6
20.0
868.8
40.6
0.0
8.2
367.8
77.2
49.7
-13.9

Gross domestic productLine

14,185.8
Income

1
2
3
4
5
6
7
8
9
10
11
12
13
14

+ Consumption of fixed capital+ Statistical discrepancy+ Services of consumers' durables+ Services of household land (net of BEA estimate)+ Services of durables held by institutions+ Services of durables, structures, land, and inventories held by government+ National Income Adjustment for Land Investment- General government consumption of fixed capital- Government enterprise consumption of fixed capital+ National income- ROW income- Sales tax+ Subsidies- Current surplus of government enterprises

15= Gross domestic income

SourceTotal

NIPA 5.1 line 13
NIPA 5.1 line 26
our imputation
our imputation
our imputation
our imputation
our imputation
NIPA 3.10.5 line 5
NIPA 3.1 line 38 - 3.10.5 line 5
NIPA 1.7.5 line 16
NIPA 1.7.5 line 2-3
Product Account
NIPA 3.1 line 25
NIPA 3.1 line 14

1,615.2-18.1
1,249.8
-16.0
40.1
424.1
72.1
223.6
44.1
11,655.6
58.0
574.8
49.7
-13.9
14,185.8

Table 2: Domestic Income and Product Account, 1948-2006
Product
Gross Domestic Product
Investment Goods ProductConsumption Goods Product
IncomeGross Domestic Income
Labor Income
Capital Income

1948

1973

1995

2000

2006

288.8
78.7
210.2

1,544.5
398.4
1,146.1

7,916.7
1,782.7
6,134.0

10,634.2
2,528.7
8,105.5

14,185.9
3,133.2
11,052.6

1948

1973

1995

2000

2006

288.8
172.2
115.9

1,544.5
883.2
661.4

7,916.7
4,553.3
3,363.3

10,634.2
6,224.5
4,410.1

14,185.9
7,980.3
6,205.8

Table 3: Domestic Product Growth, 1948-2006
Quantities
Gross Domestic Product
Investment Goods ProductConsumption Goods Product

PricesGross Domestic Product
Investment Goods ProductConsumption Goods Product1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

3.42
3.85
3.29

3.99
4.35
3.87

2.79
3.03
2.72

4.09
7.02
3.19

2.83
2.10
3.05

1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

3.29
2.50
3.54

2.72
2.14
2.92

4.64
3.78
4.90

1.82
-0.03
2.38

1.98
1.47
2.12

Table 4: Labor Growth, 1948-2006
Quantities
Labor Income
Employment
Hours Worked
Quality

PricesLabor Income
Hourly Compensation

1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

1.87
1.58
1.28
0.59

1.92
1.63
1.17
0.75

1.95
1.73
1.48
0.48

2.21
1.98
1.89
0.32

1.08
0.52
0.54
0.53

1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

4.75
5.33

4.62
5.37

5.50
5.98

4.05
4.37

3.06
3.60

Table 5: Benchmarks, Depreciation Rates, and Deflators
Line

Asset Class
1
2
3
4
5
6

7

Consumer Durables
Nonresidential Structures
Residential Structures
Equipment and Software
Nonfarm inventories
Farm inventories

Land

2006 Benchmark(billions of 2000 dollars)

Depreciation Rate

Deflator

4,806.6
12,221.3
12,181.4
6,488.6
1,716.4
125.7

0.201
0.026
0.016
0.145
-

NIPA
NIPA
NIPA
NIPA
NIPA
NIPA

-

Price by Legal Formfrom Morris Davisand Eldon Ball

8,780.1

Table 6: Relative Proportions of Capital Stock by Asset Class and Sector, 2006
Line
1
2
3
4
5
6
7

Asset Class

Corporate

SectorNoncorporate

Households

Government

Total

Consumer durables
Nonresidential structures
Equipment and software
Residential structures
Nonfarm inventories
Farm inventories
Land
Total

0.107
0.075
0.002
0.026
0.029
0.239

0.027
0.010
0.042
0.002
0.003
0.054
0.137

0.070
0.018
0.003
0.215
0.102
0.408

0.118
0.016
0.005
0.005
0.072
0.216

0.070
0.270
0.104
0.264
0.033
0.003
0.257
1.000

Table 7: Capital Income Growth, 1948-2006
Quantities
Capital Income
Corporate Income
Noncorporate Income
Household Income
Government Income

PricesCapital Income
Corporate Income
Noncorporate Income
Household Income
Government Income

1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

4.05
4.59
2.29
5.08
1.73

4.58
4.80
2.97
6.29
1.51

3.37
4.23
1.84
3.68
1.99

5.08
6.77
1.98
5.45
1.36

3.43
3.22
1.31
4.88
2.02

1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

2.82
2.40
4.36
2.02
4.14

2.39
1.65
3.61
1.35
5.69

4.03
3.88
5.34
3.70
3.32

0.34
-1.23
-0.63
1.29
4.99

2.26
3.15
8.09
-0.70
-0.04

Table 8: Domestic Income and Product and Productivty Growth, 1948-2006
Quantities
Gross Domestic Product
Gross Domestic Income

PricesGross Domestic Product
Gross Domestic Income

Multifactor Productivity

1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

3.42
2.76

3.99
2.99

2.79
2.54

4.09
3.43

2.83
2.09

1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

3.29
2.76

2.72
2.99

4.64
2.54

1.82
3.43

1.98
2.09

1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

0.66

0.99

0.25

0.66

0.74

Table 9: Contributions to Output and Growth, 1948-2006
OutputGross Domestic ProductContribution of Consumption
Contribution of Investment
GrowthGross Domestic Income
Contribution of Capital Services
Contribution of Labor Services
Multifactor Productivity

1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

3.42
2.46
0.96

3.99
2.84
1.15

2.79
2.07
0.72

4.09

2.83

2.44
1.65

2.39
0.44

1948-2006

1948-1973

1973-1995

1995-2000

2000-2006

2.76
1.69
1.08
0.66

2.99
1.89
1.11
0.99

2.54
1.41
1.13
0.25

3.43

2.09

2.17
1.26

1.49
0.60

0.66

0.74