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OCR for page 50
4
Measures of
Government
Productivity:
Concepts,
Methods, and
Sources
Previous chapters have discussed the concepts of productivity. We turn
now to the way in which these concepts have been defined and measured in
practice. This chapter describes the data sources and methods used by
government agencies, particularly the Bureau of Labor Statistics (BES), in
measuring productivity. It also includes brief comments on the adequacy
and reliability of the official measures; major evaluation of these measures
is included in Chapters 5 and 6. Productivity measures by private
researchers that are almost as well known and widely used as the
government measures are also covered in later chapters.
Following a brief overview of government measures, the rest of this
chapter is divided into sections on each of the major classifications of the
economy for which official productivity measures are prepared: economy-
wide, industry divisions, selected detailed industries, and the federal
government. The last section, "Omissions from Existing Measures," deals
with sectors and external effects not covered in any official Pleasures of
productivity.
Although this survey points up some gaps and weaknesses in the current
official programs, we do not mean to imply that the current measures are
not useful or that the agency personnel responsible for the series are not
well aware of the weaknesses and gaps. Indeed, in many cases it was
agency personnel who called our attention to the problems. For example,
much of our analysis of weaknesses in the measurement of labor input
came from a report of the Bureau of Labor Statistics Task Force on Hours
Worked (1976~.
50
OCR for page 51
Government Measures of Productivity
OVERVIEW OF GOVERNMENT MEASURES
51
BES iS the major producer of government productivity measures.) It
publishes or maintains measures for a wide array of sectors and
industries from aggregate measures covering almost the whole economy
to measures for detailed industry classifications. However, BES publishes
only measures of labor productivity. Measures of output per unit of labor
and physical capital combined, although widely estimated by private
investigators, are not now part of the official program to measure
productivity.2
Our review considers the various sector and industry measures
separately since issues about data and concepts diner somewhat for the
aggregate economy, industry divisions, and detailed industries. Two basic
considerations apply to the official measures at all levels of aggregation,
however, and it is useful to set them out in advance. One is the use of many
secondary data sources in measuring productivity. The other is the
difficulty of measuring real output for some sectors and industries.
DATA SOURCES
Unlike the government's series of measures of unemployment and prices,
official measures of productivity are made up of data components that
come from separate and independent surveys that are conducted for
purposes other than measuring productivity. Even in measuring productiv-
ity for detailed industry categories (e.g., cereal breakfast foods), BES must
usually combine data from two independent surveys of the establishments
in the industry. Data for labor input and the value of output come from
one survey (taken by the Census Bureau); data on prices, which are needed
to convert the value data into measures of real output change, come from
another survey (usually taken by BES). For measuring productivity at high
levels of aggregation (e.g., the private business sector), many different data
sources must be combined. Not only do the data on value of output, price
change, and labor input come from different sources, but also for each of
the three components a number of different sources must be used
(especially for value of output). Moreover, the data sources are not all
governmental; trade associations and large companies are important
sources of data for some industries. Neither are all the sources statistical
surveys; some data are by-products of activities of regulatory agencies.
This situation makes it difficult to develop objective measures of the
margin of error in productivity estimates, especially the more aggregate
ones. The well-established methodologies for estimating sampling error
that are applied to other official statistics, like the unemployment rate,
OCR for page 52
52
REPORT OF THE PANEL
cannot be applied to the official productivity measures. Holland and King
(in this volume) attempt to measure overall sampling error of output-per-
hour measures from the sampling error in individual data series that are
used in constructing these measures.
Recommendation 3. The Panel recommends that the Bureau of Labor
Statistics and the Bureau of Economic Analysis explore methods for
estimating the implications of error reduction in component measures
for the reduction of overall error in productivity measures beyond
that corrected by routine revisions.
The Panel recognizes that BES must continue for the present to use
many sources of data because of the very high cost of carrying out a large-
scale special survey to collect all the data components needed for
productivity measures.3 The full expense of such a survey would involve
not only direct outlays by the federal government but also the cost to firms
to respond. (Ways to improve indirect measures of output per hour and
other government statistics through cooperation among the many statisti-
cal collection agencies are explored in Chapter 8.)
PROBLEMS OF MEASURING REAL OUTPUT
The difficulty of measuring changes in real output varies greatly across
sectors and industries. At one extreme is an industry like copper whose
output is a simple standardized product that does not change either over
time or from place to place. At the other extreme are firms and agencies in
the not-for-profit and government sectors, for which output measurement
is extremely di~cult.4 Along a spectrum between these extremes are
products and services for which good measures of output are available but
only with increasing degrees of difficulty: apparel, consumer durables, new
construction, producer durables, prescription drugs, the services of doctors
and dentists, and the services of financial intermediaries are some examples
of the more difficult ones.
The current official program only publishes measures for specific
industries when the concepts and data permit relatively good measures.
Because there is also a need for productivity measures that cover broad
sectors of the economy, BES has a program of measures covering the
private business sector and major industry divisions. However, the data for
constructing these measures vary in quality. In making aggregate
measures, the better data are combined with weaker data, and the resulting
measures necessarily suffer from some of the drawbacks of the weaker
OCR for page 53
Government Measures of Productivity
-
c'
.o
_ 8
An
IL
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J
1
LO
o
Cry 5
o
I
to
LL
~ 4
J
o
53
9
7
6
Productivity at
constant rate of growth
(3.3 percent per year) ''
' ~Actual productivity
/
3LI 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1948 1
1952 1956 1960 1964 1968 1972 1976
YEAR
FIGURE 4-1 Productivity in the private business sector. (U.S. Department of
Labor.)
components. Our presentation will try to allow the reader to identify these
weak spots.
ECONOMY-WIDE MEASURES
The most inclusive productivity measure regularly published quarterly and
annually by BES iS real output of the private business sector per
unweighted hour of all workers. Figure 4-1 shows the trend since World
War II in this measure. This measure undoubtedly has an important
influence on public policy formation. Its movements over long periods
have given rise to the current concern over the productivity slowdown,
while its movements from quarter to quarter and year to year are closely
watched as an important cyclical indicator.5
The productivity measure in Figure 4-1 is composed of a numerator that
measures real output produced and a denominator that measures the labor
input used in producing that output. Table 4-1 shows the value of labor
OCR for page 54
54
REPORT OF THE PANEL
TABLE 4-1 Components of the Bureau of Labor Statistics' Productivity
Measure for the Private Business Sector, 1''73-1977
Labor Inputb Output per Annual Change in
Outputa (billions (billions of Hour (billions Output per Hour
Yearof 1972 dollars) hours) of 1972 dollars) (id)
1973974.5 134.0 7.27 2.0
197495 1.3 134.6 7.07 .-2.7
1975929.1 129.1 7.20 2.4
1976993.6 132.6 7.49 4.0
19771,053.4 137.1 7.68 2.5
aFrom last row of Table 4-2.
bUnpublished data from the Bureau of Labor Statistics, U.S. Department of Labor.
input, output, and the ratio of the two for the private business sector for
1973-1977. BLS generates its own measure of the denominator, relying
largely on data it collects itself. For the numerator, BES uses, with minor
modifications, measures produced by the Bureau of Economic Analysis
(BEA) in the U.S. Department of Commerce as part of the program of
national income and product accounts. BEA uses data from a large number
of sources to estimate income and product.
REAL OUTPUT
The numerator of the private business sector series is derived from
measures of the gross national product (GNP) and its components. The GNP
measures the market value of the output of all capital and labor resources
that generate observable income transactions, plus the imputed product of
some resources for which there are no observable market transactions,
such as the services of owner-occupied homes and food produced and
consumed on farms. The GNP includes the output of domestic workers
hired by households (although not that of people who do the same work
for themselves). The GNP also includes the output of employees of local,
state, and federal government agencies and of not-for-profit organizations.
However, BES subtracts the measures of output for these three sectors-
household employment of domestic workers, employees hired directly by
government, and not-for-profit organizations-from the GNP because at
present the output measures for these sectors are based only on the
amounts of labor inputs that are used. In the absence of any observable
transactions involving output, BEA uses changes in inputs to measure
changes in real output. When BES measures changes in labor productivity,
it excludes these sectors from the output measure because, by definition,
OCR for page 55
Government Measures of Productivity
TABLE 4-2 Components of the Difference Between the Gross National
Product and the Numerator of the Bureau of Labor Statistics' Productivity
Measure for the Private Business Sector, 1973-1977 (billions of 1972 dollars)
55
Component1973a1974al97sa1976a 1g77b
._ .
Gross national product 1,235.0 1,217.8 1,202.1 1,274.71,337.5
Less: rest of world 7.6 6.8 4.9 6.77.4
Gross domestic product 1,227.4 1,211.0 1,197.2 1,268.01,330.1
Less: government 138.9 141.9 144.6 145.8147.5
Gross domestic private
product 1,088.5 1,069.1 1,052.6 1,122.21,182.6
Less: households
and institutions 38.1 38.0 38.9 40.241.4
Gross domestic business
product 1,050.4 1,031.1 1,013.7 1,082.01,141.2
Less: Gross product
of owner-occupied
housings 71.0 74.5 79.0 83.286.1
Less: "residual" 4.9 5.3 5.6 5.21.7
Bureau of Labor Sta
tistics numerator
(private business
sector) 974.5 951.3 929.1 993.61,053.4
aBureau of Economic Analysis (1977) Survey of Current Business, July, Table 1.8.
bBureau of Economic Analysis (1978) Survey of CurrentBusiness, February, Table 3.
CUnpublished estimates by the Bureau of Economic Analysis, U.S. Department of
Commerce.
productivity change is zero.6 BES also excludes from output the imputed
rental value of the services of owner-occupied homes. This is done because
there is no way of obtaining good measures of the labor input (e.g.,
maintenance activities) associated with this output. Finally, BLISS deducts
the output of resources owned by U.S. citizens but located in foreign
countries and adds the output of resources owned by foreigners but located
in the United States. This is done because the data for measuring labor
input include only labor at work in the United States.
In BEA terminology the numerator of the BES measure is equal to gross
domestic business product in constant dollars minus the imputed value (in
constant dollars) of the services of owner-occupied homes. Table 4-2 shows
the components of the difference between GNP and the numerator of the
BES productivity measure.
BEA estimates gross domestic business product in constant dollars in
two ways. One involves measuring the flow of real goods and services to
the final-demand categories, and the other involves measuring the real
OCR for page 56
S6
REPORT OF THE PANEL
gross product originating in the industries that make up the private
business sector.7 If all the data used in the two approaches were without
error, the two measures would be equal. In practice, of course, the data
have errors that lead to a difference between the two measures. The
difference, called the residual, has been between 0.1 and 0.5 percent, with
the final-demand measure always exceeding the product-originating
measure. The rest of this section describes the BEA method based on the
sales to final-demand approach. The following section, which is devoted to
measures for industry divisions, describes the data and procedures used by
BEA to measure real gross product originating by industry.8
The BEA procedure for estimating domestic business product in constant
dollars involves two steps. First, BEA estimates output in current dollars
from data on business sales to the major categories of final demand:
personal consumption expenditures (PCE, 72.2 percent), producers' dura-
ble equipment (PDE, 7.5 percent), structures (7.7 percent), government
purchases of goods and services from private business (11.0 percent),
change in inventories (0.8 percent), and net exports (0.9 percent).9 Second,
it converts the current-dollar measure to one in constant dollars by a
detailed deflation procedure.
i. . r . ~
.
BEA eStlmaleS OI current-aollar components come in a sequence ot
preliminary and revised estimates for any given year (called a reference
year) with each subsequent revision being based on more comprehensive
and more direct sources of data. Table 4-3 shows some of the data sources
used by BEA for making the annual current-dollar estimates. The table is
arranged by final-demand category and revision sequence.l° The data
sources listed in Table 4-3 are a subset of all the sources used; the other
data used are more specialized and are usually collected either by a trade
association or by a government regulatory agency. The data sources diner
in terms of sample size and the randomness of sampling procedures as well
as in the degree to which they directly measure the magnitudes of interest.
Some detail on the estimation of current-dollar PCE in 1974 will illustrate
the characteristics of some of the data sources.
In 1974, 42.8 percent of current-dollar PCE was based on data from the
current-dollar sales of goods (durable and nondurable) reported in the
monthly and annual Census Bureau Surveys of Retail Trade (see Once of
Federal Statistical Policy and Standards 1977, Chapter 5~. For the
remainder of PCE goods-new and used cars and trucks, and gasoline and
oil (13 percent of PCE - BEA uses data from business and trade association
sources. For new cars, four data sources are used. One trade source
provides data every 6 months on auto production and list prices broken
down by detailed categories of nameplate, model, and options. These are
used to establish the average list price. Another trade source provides data
OCR for page 57
Government Measures of Productivity
57
on overall auto sales (i.e., sales to consumers, businesses, and govern-
ments) in quantity units. BES provides data on auto price discounts from
the consumer price index Icy. Finally, a third industry source provides
data used to estimate what part of the unit sales went to consumers. For
consumer expenditures on gasoline and oil, BEA uses data provided by the
Ethyl Corporation on the quantity of gasoline sold in a sample of gasoline
stations and the data from the BES consumer price index for gasoline
prices.
For the services component of PCE (44 percent of PCE), a number of data
sources are used. For hotel, personal, recreational, medical, and legal
servicesii (6 percent of PCE), the data come from the Census Bureau's
Monthly Selected Services Receipts Survey (see Once of Federal Statisti-
cal Policy and Standards 1977, Chapter 5~. For the rents paid for rented
dwellings (4 percent of PCE), BEA combines information on the number of
tenant-occupied housing units from the Annual Housing Survey (of the
Census Bureau and the U.S. Department of Housing and Urban
Development) with information on rental prices from both the latest
decennial census and the consumer price index. To estimate expenditures
on auto repair services (2 percent of PCE), BEA combines trade source data
on the number of car registrations with cat information on prices of auto
repairs. For household utilities gas, electricity, telephone, etc.-(6
percent of PCE), BEA uses either company or industry sources. For
example, the American Telephone and Telegraph Company supplies data
on residential local and long distance telephone calls.
The discussion above relates to estimation of output in current dollars;
to measure output in constant dollars, BEA deflates the current-dollar
data. For the large part of PCE that involves direct and explicit money
transactions between consumers and private business firms (about 80
percent of PCE), BEA uses price change information from the cat for
deflation purposes. The deflation is carried out at a fairly detailed level of
product and service disaggregations.~3
The remainder of private business PCE iS made up almost entirely of the
services of life insurance companies and banks and other financial
intermediaries. For this sector, because of conceptual and data gaps, BEA
measures real output change by measuring input change. For life insurance
companies, the current value of operating expenses is deflated;~4 for
financial institutions, changes in unweighted employee-hours between the
base year and the current year are used to extrapolate the base-year value
of operating expenses.
For deflating PDE, which involves direct money transactions between
business firms, BEA relies mainly on the price change information in the
producer price index UPPED.
OCR for page 58
58
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OCR for page 59
Government Measures of Productivity
59
The remaining major components of current-dollar business product
shown in Table 4-3 are structures and government purchases from private
firms, for both of which there is very little coverage of prices by
government statistical agencies. For deflation, BEA uses price indexes from
a wide variety of trade associations, regulatory agencies, and other
governmental and private sources.
When the constant-dollar measures of change in inventories and net
exports are added to the estimates described above, the result is BEA'S
official gross domestic business product in constant dollars (see Office of
Federal Statistical Policy and Standards 1977, Chapters 5 and 8~; BES
subtracts the constant-dollar value imputed to the services of owner-
occupied dwelling units to arrive at the numerator of its measure of
productivity for the private business sector.
LABOR INPUT
The concept of labor input used by BLS iS the unweighted sum of the hours
of all workers engaged in the production of the output measured in the
numerator of the productivity ratio. The data used to measure labor input
come from different sources and sometimes involve imputations or
assumptions. Unlike the output data, which come from many sources, the
hours data are based primarily upon sample data from two sources: the
current employment statistics (CES) program and the Current Population
Survey (cPs). The CES covers all wage and salary workers in the
nonagricultural business sector, who account for about 80 percent of total
hours of the private business sector. For workers not covered by the CES,
primarily those in agriculture and the self-employed, BES relies largely on
the cPs. Table 4-4 summarizes the sources and imputations of hours of
labor input for major components of the private business sector.~5
Like the output data, the input data come from programs not
specifically designed to measure productivity. The CES iS designed to
provide timely information on employment, hours, and earnings for the
nonagricultural economy and also for detailed industries and for metropol-
itan areas and state. The cPs, conducted by the Census Bureau for BES, iS
designed primarily to provide timely information about the labor force,
employment, and unemployment.
The CES data are collected in a mail survey from the payroll records of
about 165,000 sample establishments. State employment agencies, cooper-
ating with BES, choose the state samples and survey the establishments
that participate in the program, which is voluntary. The data cover 1
week, the survey week containing the twelfth day of the month, and
become the basis of monthly estimates of employment, average hourly
OCR for page 60
60
REPORT OF THE PANEL
TABLE 4-4 Source Data for Hours in the Private Business Sector, 1977
Percentage of
Components'
Average Weekly Hours to Total
Total and Components Hours (AWH) Employment Hours (Jo)
Private business sectora 100.0
Manufactunngb 29.3
Production workers C CES CES 20.8
Nonproduction workersC assumed constantd CES 8.0
Self-employment CPS CPS 0.5
Nonmanufactunuge 63.8
NonsupervisoryC'f CES CES 46.0
Supervisory workersC same as nonsupervisory CES 7.9
Self-employed CPS CPS 9.2
Unpaid family workers CPS CPS 0.7
Government enterprises CPS BEA 2.2
Farm-all employees CPS CPS 4.7
CES = Consumer Expenditure Survey, CPS = Current Population Survey, BEA = Bureau
of Economic Analysis.
aNot-for-profit institutions are excluded from measures of the private business sector, so
the Bureau of Labor Statistics subtracts their hours from those of the entire sector. Esti-
mates of not-for-profit institutions" hours are calculated by dividing compensation in
not-for-profit institutions by the compensation per hour figure for the entire industry.
BEA is the source of the compensation data, collected annually.
bBureau of Labor Statistics assumes no unpaid family workers in manufacturing.
CEstimates of employment are benchmarked to unemployment insurance, Social Se-
curity, regulatory and other government agencies, and private sources.
dBureau of Labor Statistics has held AWH for nonproduction workers in nondurable
manufacturing constant at 39.1 and for durable at 39.7 since 1962. Prior to 1962, it
estimated these hours from its Area Wage Surveys but has found them changing very
gradually and so has not changed estimates in recent years.
eNonmanufacturing includes mining, construction, transportation, wholesale and retail
trade, finance, insurance and real estate, and public utilities.
Construction workers in the construction industry.
SOURCE: Derived from unpublished data provided by the Bureau of Labor Statistics,
U.S. Department of Labor.
earnings, and average weekly hours. (When a survey week contains a
holiday, BES makes adjustments so that data for that week correspond to a
regular 5-day week.)
The cPs sample consists of about 56,000 households. Since it is a
probability sample, reliable estimates can be constructed from the sample
data for the entire labor force. The sample households are visited by a
Census Bureau enumerator or are interviewed by telephone: a respondent
is asked to report hours at work and where worked for each member of the
household who is 16 years of age and older. Like the CES data, the monthly
cPs data are based on 1 week, the survey week containing the twelfth day
OCR for page 77
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78
REPORT OF THE PANEL
TABLE 4-8 Selected Activities and Output Indicators, by Selected
Functional Groups, from the Bureau of Labor Statistics' Federal
Government Productivity Program
Finance and accounts
Regulation-inspection
and enforcement and
rulemaking and li-
censlng
Commissary store operations;
laundry and dry cleaning
Dining facilities operations;
recruit training
Flight training
Active duty personnel, pay ac-
counts (Navy); civilian time
cards (shipyard, Norfolk)
Invoices and travel processing
(shipyard, Norfolk); billing,
bill and collect for GSA
Accounting obligations and
expenditures (USIA); pay-
ment and reconciliation of
of checks (Treasury)
Background checks on persons
assuming sensitive positions
in Department of Defense;
develop and publish rail
safety standards (DOT)
Inspections of manufacturing
plants, retail stores, etc.
(Consumer Product Safety
Comm.); consumer com-
plaints (CAB)
New animal drug review and
approval process (FDA);
patent application exami-
nation.
Functional Grouping
Military base services
and military training
Activity
Output Indicator
Deflated dollar value of
sales; pieces processed
Number of meals served;
students enrolled
Student-years trained
Number of active duty ac-
counts maintained; num-
ber of time cards
processed
Number of invoices and
travel claims processed;
bills mailed
Obligation and expendi-
ture documents processed;
checks paid and reconciled
and tax deposit forms
processed
Number of cases closed
Number of new standards
and modifications com-
pleted
Number Inspections
made
Number of consumer com-
plaints processed
Number of new animal
drug applications; ap-
plication disposed
DOT = Department of Transportation; GSA = General Services Administration; CAB =
Civil Aeronautics Board; USIA = U.S. Information Agency; FDA = Federal Drug Ad-
ministration.
SOURCE: Productivity Programs in the Federal Government. Supplement to Vol. 1.
The Measurement Data Base. Annual Report to the President and the Congress by
the Joint Financial Management Improvement Program.
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Government Measures of Productivity
79
pool garage, categories such as number of tune-ups, number of oil changes,
etc., are preferable to the single category "number of cars serviced." In
addition, as with other productivity measures, even the most detailed
output can change in quality over time. The main approach used to
minimize these difficulties is to collect data with as much output detail as
possible.
There are differences of opinion about whether productivity measures
can be used to improve the current measure of real output for the federal
government in the national accounts. BEA'S current method of measuring
government output assumes that no productivity change takes place in the
public sector; therefore, BES must exclude this sector in calculating its
aggregate productivity measure.
Some analysts note that almost all of the output measures are of
intermediate activities that, although needed if the government sector is to
produce anything, do not relate directly to the final services that taxpayers
expect for their tax dollar national security, improved allocation of
resources, etc.28 When any agency provides its intermediate services more
efficiently, this only means that the potential for increasing overall
government productivity has improved: we say "potential" because there
is no direct link between increases in productivity at the intermediate level
and at the level of final output. This may be shown by a hypothetical
example. One agency produces its output faster than before-getting out a
report for the use of another agency. But the second agency cannot
implement the report any faster. Therefore a chain of events that might
have reduced the amount of labor needed to produce the same level of
national defense, or improved resource allocation, is choked oh. There is
no way to confirm such a situation because there is no measure of final
output. Other analysts stress that, for some programs, activities and output
measures are closer to the flow of final services than for others, and that
with further research and development the measures might be made worth
using (see Searle and Waite 1980~.
EXCLUSIONS FROM EXISTING MEASURES
Several sectors of the economy are omitted from the official measures of
output per hour. Some sectors included in GNP are excluded from
productivity measures because BEA estimates their output by labor (and
sometimes other) inputs. This results in essentially no measured productiv-
ity change for these sectors (see the first part of Chapter 5~. General
government, including federal, state, and local governments, is the largest
of the excluded sectors. (As discussed above, the BES has a program to
measure the productivity of the federal government that could, in
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80
REPORT OF THE PANEL
principle, be used to extend the coverage of the aggregate productivity
measures.) Other sectors omitted for this reason include not-for-profit
institutions, like private hospitals and universities, and domestic services
purchased by households.
Still other sectors are excluded both from GNP and from productivity
measures. The largest of these is the household sector, which produces
such output as child care, using nonpurchased inputs. The GNP measure
also does not include, as a deduction from output, the effects of
environmental pollution, congestion, or noise. This section describes
measurement efforts by BEA and by private investigators for the omitted
sectors; for further discussion of sectors and effects not included in GNP,
see Moss (in this volume).
STATE AND LOCAL GOVERNMENT
There is evidence of widespread interest in and use of productivity
measures by state and local governments throughout the country. One of
the main activities of the National Center for Productivity and Quality of
Working Life (see its report 1975) was to help make state and local
government managers aware of organizational and other innovations,
including the use of productivity measurement, that would lead to cost
savings and enhance productivity.
There is an important difference between state and local governments
and the federal government in the potential for developing productivity
measures that could be used to expand the economy-wide productivity
measures, namely, that most activities of state and local governments
deliver final services directly to taxpayers. This makes it possible to
measure quantities of those final services. Activities such as garbage
collection, recreation services, library services, public transportation,
water supply, and elementary and secondary schooling deliver a service of
value to final consumers. Some kind of quantity measure, such as tons of
garbage collected, number of visitors to the zoo, or number of passenger-
miles traveled, is conceptually straightforward and possible to develop.
There remains the problem of quality change. Work currently under
way at the Urban Institute seeks to develop objective measures of the
quality dimensions of the services of state and local governments (see
Hatry et al. 1977~. That work suggests that two quality characteristics for
garbage collection, "spillage of garbage collections" and "damage to
private property by collection crews," could be measured by means of
household and business sample surveys. Changes in tons of garbage
collected is a good measure of real output change if the responses to the
questions about these characteristics do not change. If the responses to the
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Government Measures of Productivity
81
quality questions do change, the problem remains of how to value the
change in quality in terms of the appropriate amount of adjustment to the
quantity measure. Of course, there is an analogous problem in the private
sector whenever there are changes in the performance charactistics of
goods and services sold. Private sales in current dollars are deflated by
price change data that may not adequately allow for changes in the quality
of the service sold. (For further discussion of measuring quality change in
output, see Chapter 5.)
NOT-FOR-PROFIT SECTOR
Hospitals and colleges and universities are the two major industries in the
not-for-profit sector. These organizations, although not-for-profit, have
become increasingly concerned about cost and efficiency. There is an
extensive literature by educators, medical and operations research special-
ists, and economists on output, input, and productivity measurement and
analysis for many aspects of hospital and university operations (see
Froomkin et al. 1976, Institute of Medicine 1976, Stanford Center for
Health Care Research 1976, Feldstein and Taylor 1977~. Much of the
work (like that of the BES program for federal agencies, described above) is
aimed at helping not-for-profit organizations improve their own efficiency
rather than at developing measures that would permit comprehensive
comparisons of productivity change between these sectors and the private
business sector. One exception in higher education has been the use of
weighted indexes of courses taken, using credit hours to aggregate the
various kinds of course enrollments, such as full-time, part-time, degree
credit, and nondegree credit (see O'Neill 1976~.
The use of such output measures (and analogous measures, such as
patient days, for hospitals) is similar to using tons of garbage collected to
measure the output of garbage collectors; it is satisfactory as long as the
quality of the basic unit of quantity does not change. This is particularly
important for schools and hospitals because changes in the output quantity
measure can themselves be associated with quality changes. If improve-
ments in surgical procedures shorten the length of a hospital stay, they
might result in lower output as measured by average patient load, and the
productivity measure based on this output could decrease. If class size is
significantly increased to reduce expenditures and the quality of instruc-
tion falls, the output measured by credit hours would not change and the
productivity ratio would increase. Indicators of changes in various quality
dimensions (e.g., mortality rates adjusted by case mix, length of stay by
type of ailment, class size, etc.) are needed to supplement pure quantity
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82
REPORT OF THE PANEL
measures. (For further discussion on measuring output in hospitals, see
Scott in this volume.)
HOUSEHOLDS
In recent years there has been much work by economists analyzing the
family as a producing unit. A behavioral model is used in which the goods
purchased from business firms are considered intermediate inputs that are
then combined within the family with other "inputs" the non-market
time of family members to produce the final services of ultimate interest
(good health, vacations abroad, dinner or theatre evenings out, etch. This
approach is an outgrowth of earlier work by labor economists who, in
analyzing trends and cyclical movements in the labor force participation of
women and teenagers, were forced to expand their models of labor supply
to include the interrelationships of the work and leisure choices of all
family members.
A related topic involving the use of consumers' time is the time used in
obtaining market goods and services. For many goods and services, such
as medical care, repair services, travel, banking, and shopping, the input of
the time of the consumer is an important factor of production. Entrepre-
neurs are aware of this in making decisions about resource allocation,
location, and technical change.
Despite the widespread interest in non-market uses of time, there has as
yet been no systematic effort by government agencies to develop data series
that measure the utilization and productivity of non-market time, either of
time used in conjunction with purchased goods and services or of time
used to purchase goods and services.
There is one nongovernmental project of sufficient size and scope that it
may produce information about the productivity of non-market time
although it is not directly aimed at measuring productivity change. This is
a project by researchers at six institutions called "Cooperative Research in
Goals Accounting.''29 Its primary objective is to measure changes in
various broad aspects of"well-being" (such as life expectancy, mental
health, and safety) and to relate these changes to a number of categories of
input: purchased consumer goods and services, expenditures and services
of government, and the non-market time input of individuals. The project
also seeks to explore exogenous factors that influence such broad goals as
mental and physical health, including factors involving demographic and
mobility trends. (These objectives go beyond the usual province of analysis
of household productivity the saving of time and market goods in such
activities as doing housework or in shopping.) Some of the work of the
project, which combines survey data on the uses of non-market time by
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Government Measures of Productivity
83
type of activity with national accounts data on purchased goods and
services, may produce measures of secular changes in the time devoted to
various activities. Moss (in this volume) discusses traditional measures of
national income and broader measures of welfare.
EXTERNAL EFFECTS AND OUTPUT
The erects of production on the environment and on worker health and
safety are now of great concern. Regulation of these erects is now
pervasive and is widely believed to have had a significant erect on the
change in measured productivity.
To incorporate these effects fully into a productivity measure would
require estimates of how much of every industry's activities has changed
the quality of the environment at different times. This erect could be
positive, as when regulations require firms to reduce their level of air or
water pollution, or it could be negative or zero. The information could
then be used to adjust the traditional measure of the industry's real output,
which measures only its output of conventional goods.30 The change in
the ratio of an index of adjusted output to an index of inputs-those
devoted solely to producing conventional output and those being used
specifically to influence the effects on the environment would yield a
measure of productivity that fully reflected the ability of the industry to
produce environmental erects in addition to conventional goods and
services. It is not possible to perform this type of analysis with data now
available. However, BEA iS planning to develop such information as part of
its new Environmental and Nonmarket Economics Division.
The data currently available primarily cover the resource costs that
firms have incurred in meeting specific environmental standards imposed
by regulatory agencies. Although these data alone do not allow for the
computation of a comprehensive productivity ratio of the kind discussed
above, they can be used to correct conventional productivity measures for
the erects of requiring the firm to shift partially into the production of
some favorable environmental output. These corrected ratios measure the
trends in productivity that would have occurred if resources had all been
used to produce conventional output and none had been used to reduce
external environmental effects. Some researchers have used the available
data to make such adjustments and thus to improve understanding of the
trends in measured productivity in the period since 1966, which was one of
rapidly increasing environmental and health and safety regulation.
Chapter 7, which reviews the sources of measured productivity change,
discusses the data and methods used in estimating these erects.
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REPORT OF THE PANEL
Recommendation 5. The Panel recommends that research on the
measurement of the output and productivity of the resources in
excluded sectors be expanded. However, there should be no prema-
ture selection or foreclosing of any of the alternative measures of
output for such systems as health care and higher education.
Although progress has been made in measurement in these areas, we
do not yet know enough about the operation of such systems either to
measure precisely their salient outcomes or to assume that we
understand the processes that account for them.
NOTES
1. The Economics, Statistics, and Cooperatives Service of the U.S. Depart-
ment of Agriculture is the only other major government producer of productivity
measures. It publishes both labor and multi-factor productivity measures for the
farm sector. Since a task force of the American Agricultural Economics
Association is currently assessing the data and methodology underlying USDA'S
measures, our study did not include a review of those measures.
2. BES does develop measures of physical capital input (and other inputs, such
as weighted labor input) on a periodic basis in order to analyze the factors
underlying changes in labor productivity (see Norsworthy and Fulco 1977), but
such measures are not published on an ongoing basis.
3. BES experimented with collecting all the productivity data from a single
survey; the cost and complexity of the statistical design made the approach
infeasible (see Mark 1961~.
4. BES does not publish any economy-wide productivity measures that include
the not-for-profit and government sectors because there are no independent
measures of output for those sectors (see Chapter 5~.
5. BES also publishes series on other, less-inclusive, aggregate measures: for
the private nonfarm economy and for all non-financial corporations. Our
discussion focuses on the measures for the private business sector.
6. This statement is not precisely true in all cases. The output measure used by
BEA for employees of government involves a weighted sum in which senior and
higher-grade employees count for more labor. Since the BES labor input measure is
an unweighted sum, the resulting productivity ratio would show increases
whenever the experience/skill mix increased. However, it is generally recognized
that using inputs, even with this kind of adjustment, to measure real output is of
limited value. There is interest in finding more direct measures of government
output (see the section below on measuring productivity in the federal govern-
ment).
7. The final-demand categories include sales of goods and services by business
firms to households, other business firms on capital account (including the net
changes in inventories of all firms), government, and the rest of the world (exports
minus imports). The only business sales that are excluded are those that go to
another firm on current account, so-called intermediate purchases. Gross product
originating for an industry is defined as the value of its sales (adjusted for net
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Government Measures of Productivity
85
change in inventories) minus all purchases from other firms on current account. If
this quantity is summed over all industries, then all intermediate purchases and
sales will drop out and what is left are the sales (net of inventory change) by firms
to the final-demand categories.
8. There is a third way of measuring business product based on the accounting
identity between total value of production and the sum of payments to the factors
of production (including any indirect taxes and including a profit component
defined so that the two sides will always balance). When these factor payments are
summed over all finals, they will be equal, conceptually, to current-dollar business
product measured as the sum of sales to the final-demand categories. In practice,
they differ by an amount called the "statistical discrepancy." Thus, the factor-
payments data could be used to estimate current-dollar business product, and real
product can be derived by deflating current-dollar product by the ratio of current-
to constant-dollar business product derived from the data on sales to final-demand
categories. In effect, one first estimates real business product via the sales to final-
demand approach and then uses this information to form a deflator to apply to the
current-dollar product estimate derived from the income side.
9. The percentages in the text show the share of each category in final demand
after subtracting estimates of the contribution to these categories of the non-
business sectors and of the resources located in the rest of the world. Thus, total
purchases by government in 1976 were $264.4 billion (in 1972 dollars) of which
$145.8 billion was for direct hire of employees and $1 18.6 billion was for purchases
of goods and services from private business. The percentage above for government
reflects only the $1 18.6 billion, since we are excluding sectors with no independent
measure of output (Survey of Current Business 1977, Tables 1.2 and 1.8~.
10. The most comprehensive data sources are quinquennial censuses, and
although they are listed at the end of the sequence, they also play an important role
in making the preliminary estimates for many subsequent years. For example, the
data available from monthly and annual surveys to estimate current-dollar PCE and
PDE do not contain enough product detail for carrying out the deflation process for
conversion to real product. These more detailed current-dollar components are
estimated using information contained in the large input-output (I-O) table
maintained by BEA. The detailed cells of the I-O table, showing product shipments
and purchases by detailed industry, are revised on the basis of information in the
quinquennial censuses. Thus, when the data from the 1967 censuses became
available in 1976, it meant that all the product estimates in the period 196~1976
were subject to revision.
11. For the hotel, personal, and recreational categories, the monthly Census
Bureau survey is used for all the non-benchmark estimates-quarterly, and the
first, second, and third July revisions. For medical and legal services the monthly
survey is used only for the quarterly and first July revisions. The second and third
revisions are based on the business receipts data in the Internal Revenue Service's
Statistics of Income.
12. BEA uses a deflation procedure to obtain what it calls "output in constant
dollars." This terminology is somewhat misleading because the procedure used by
BEA iS a mixture of a constant-dollar quantity index (with base-year price weights)
and a deflated-value index using price indexes with base-year quantity weights. BEA
divides the current-dollar value of expenditures into individual product classes and
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86
REPORT OF THE PANEL
deflates each one by a price index. Each of these indexes is weighted by the relative
quantities of individual products within the product class in the base year. If there
was no change in product mix, the deflated value for each product class would
precisely equal the value, in base-year prices, of the current-year mix of individual
products, and the sum over all product classes would be equal to current output at
base-year prices, i.e., "output in constant dollars." In general, however, the
product mix of product classes changes, the amount of change being larger the less
detailed the deflation categories. BEA iS aware of this problem and uses the most
detailed categories.
13. Information on the actual detailed product breakdown is not in the
quarterly and annual surveys that underlie the various July revisions. These
detailed components are estimated using information contained in the large I-O
table maintained by BEA (see note 10~.
14. The operating expense categories are paper, printing, telephone and
telegraph, utilities, rent, computer leasing, advertising, medical service, postage,
business travel and expense, and wages. Price change data for each of these
categories are obtained from the producer price index (PP~), the cat, and other
sources. The price change data are then used to deflate the current-dollar value in
each category.
15. Some government services are sold directly to consumers, for example,
those of the U.S. Postal Service. These activities, called "government enterprises"
by BEA, are treated like private firms in the national accounts and are included by
BES in the input and output of the private business sector.
16. The divisions of the private business sector are farming, mining, construc-
tion, manufacturing, transportation, communications, utilities, wholesale and retail
trade, finance, insurance and real estate, and services.
17. BES does not publish measures for the other divisions because the available
measures of output either are based primarily on inputs, as in finance and life
insurance, or are not considered reliable enough to justify publication on a regular
basis.
18. Industry measures of labor productivity based on a value-added concept of
industry output have some desirable properties compared with industry measures
based on total output. Value-added measures do not change when the vertical
integration structure of the industry changes, and they move in the right direction
when firms in the industry economize on purchased inputs per unit of output.
Neither of these properties is shared by measures based on total output. However,
for purposes of analyzing the sources of an industry's output growth, its cost and
price behavior, etc., a multi-factor productivity measure relating total output to all
inputs (both intermediate purchases and labor and capital) is more relevant.
19. This description focuses on the internal logic of the double-deflation
method and on how suitable the available data breakdowns (e.g., level of product
detail available on a year-to-year basis) are for this methodology. The ability of the
price change data to allow for changes in the performance characteristics of
products and services within the deflation categories used is discussed in Chapter 5.
20. Primary products are the 5-digit product classes or 7-digit products listed
under an industry in the Census Bureau's Numerical List of Manufactured
Products (Bureau of the Census 1972; see Table 4-5~. Products of an industry not
on this list are shown as secondary products.
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Government Measures of Productivity
87
21. Wherever-made shipments include those from plants where the products
are primary and from plants where they are secondary. Deflators calculated with
these shipment data are called "wherever-made deflators" and are based on the
product mix of all industries where the products are made. The use of these
deflators for industries where the products are primary and where the mix may
differ can result in some error.
22. For some 4-digit industries, shipments of secondary products are sig-
nificant. For these industries, the 5-digit product class mix of their secondary
products has to be estimated from the latest available quinquennial census. Also, if
an industry has a low "coverage ratio" of its primary products (e.g., the industry's
shipments of its primary products are less than 75 percent of the wherever-made
shipments), the industry deflator, which is based on wherever-made weights, may
have a large error if price behavior differed between primary producers and other
producers (see Myers and Nakamura in this volume).
23. There are 20 2-digit industry categories in manufacturing, such as food and
kindred products (sac 20), tobacco manufactures (sac 21), and textile mill products
(sac 22).
24. In connection with output measures based on the quinquennial censuses, it
should be noted that the Census Bureau publishes a volume showing real output
indexes for all 4-digit manufacturing industries (U.S. Bureau of the Census, Census
of Manufactures, Volume IV, Indexes of Production). See Myers and Nakamura
(in this volume) for a discussion of the methods used by the Census Bureau.
25. Very often, the match between a Census Bureau 7-digit product line and the
product specification used by the PP~ is approximate (Ruggles 1977~.
26. See note 15.
27. A total of about 1,600 individual output indicators are aggregated using
their respective base-year unit labor requirements for weights.
28. See the dissenting comment by Denison in Office of Federal Statistical
Policy and Standards (1977, p. 8~.
29. The project participants are Nestor Terleckyj, National Planning Associa-
tion; Abraham Charnes, University of Texas; William Cooper, Carnegie-Mellon
University; F. Thomas Juster, University of Michigan; Michael Levy, The
Conference Board; and Milton Moss, Stanford Research Institute.
30. Such an adjustment would require some judgment about the value to
consumers of the increment in environmental quality.
Representative terms from entire chapter:
private business
