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OCR for page 234
Appendix C
Procedures for Deriving
Bureau of Labor Statistics
Measures of Productivity
for Service Industries
The Bureau of Labor Statistics (BLS) measures of productivity are in the
form of indexes of output per unit of labor input derived from dividing an
index of output for an industry by the corresponding index of labor input.
INDUSTRY-LEVEL MEASUREMENT OF OUTPUT
Table C.1 describes the procedures used by the BLS to derive the in-
dexes of output for each of the service industries for which it publishes
productivity measures. A summary of those methods follows. Table C.1
also provides Standard Industrial Classification code information to clarify
industry definitions as they are used by the BLS.
Transportation
The BLS publishes indexes of productivity for five transportation in-
dustr~es: railroads, intercity buses, intercity trucking, air transportation,
and petroleum pipelines. These measures cover 35 percent of transportation
employment.
NOTE: This appendix updates and expands on previous work presented in Mark, Jerome A.,
1986, "Measuring Productivity in Services Industries," pp. 139-lS9 in Technology in Services:
Policies for Growth, Trade, and Employment, Bruce R. Guile and James Brian Quinn (eds.),
National Academy Press, Washington, D.C.
234
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APPENDIX C
TABLE C.1 Methods Used by the Bureau of Labor Statistics to Derive
Indexes of Output for the Service Industries
235
Industry SICa Procedure
Railroads 4011 pt.
Bus carriers, 411, 413,
Class 1 414 pt.
Intercity trucking 4213
Air transportation 4512,22
Petroleum pipelines 4612,3
Telephone 481
communications
Electric utilities 491,493 pt.
Gas utilities 492,493 pt.
Gas and electric 491,2,3
utilities
Scrap and waste 5093
materials
Hardware stores 5251
Department stores 5311
Variety stores 5331
Freight ton-miles and passenger-miles weighted with
labor expenses. Freight ton-miles adjusted by unit-
revenue-weighted commodity ratios.
Intercity and local indexes combined with employment
weights. Four components of each index passenger-
miles, passengers, charter passengers, and deflated
freight revenue combined with revenue weights.
Indexes for general freight, specialized carriers, and
household-goods carriers combined with employment
weights. Freight ton-miles for components of each
index combined with employment weights.
Freight ton-miles and passenger-miles separately
weighted for domestic and international services.
Unweighted barrel-miles.
Separately deflated revenues from local, wide-area toll
service (WATS), measured toll (MTS) and
miscellaneous services.
Kilowatt-hours for 7 classes of A & B service and 4
classes of Rural Electrification Administration service
combined with revenue weights.
Therms sold for residential, commercial, industrial, and
other classes of service combined with revenue
weights.
Output indexes for electric and gas utilities combined
with employee-hour weights.
Scrap index based on tons by types of scrap combined
with unit-labor-requirement weights. This index
combined with wastepaper index using employment
weights.
Deflated merchandise line sales combined with
employment weights.
Merchandise line sales for 16 departments separately
deflated with consumer price indexes. Deflated
department sales then combined with employment
weights. This index of output then combined with
deflated mail-order sales using employment weights.
Deflated sales for 29 merchandise lines combined with
gross margin weights.
Continues
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236
TABLE C. 1 Continued
INFORMATION TECHNOLOGY IN THE SERVICE SOCIETY
Industry SICa Procedure
Grocery stores 541 1
Retail bakeries 546
Retail food stores 54
New- and used-car 5511
dealers
From 1958 to 1972 for general grocery stores, deflated
merchandise line sales for meat, produce, dry grocery,
dairy, frozen food, and other departments combined
with labor-cost weights; from 1972, gross margin
weights used. For specialty stores, merchandise line
sales separately deflated and aggregated. The two
indexes then combined with all person-hour weights.
Deflated merchandise line sales combined with gross
margin weights.
Indexes for grocery stores and retail bakeries combined
with index for other food stores using hours of all
persons for weights. Index for other food stores
derived by combining indexes for meat, fish markets,
fruit stores, markets, dairy stores, and confectioneries
with employee weights. Detailed indexes based on
deflated merchandise line sales combined with gross
margins.
Combined count of new- and used-car sales and
deflated parts and service sales with employment
weights.
Auto and home 553 Deflated merchandise line sales combined with gross
supply stores margin weights.
Gasoline service 5541 Sales deflated by price index from consumer price
stations indexes (CPIs) weighted by merchandise line sales.
Men's and boys' 5611 Sales deflated by price index from CPIs weighted by
clothing stores merchandise line sales.
Women's clothing 5621 Sales deflated by price index from CPIs weighted by
stores merchandise line sales.
Family clothing 5651 Sales deflated by price index from CPIs weighted by
stores merchandise line sales.
Shoe stores 5661 Sales deflated by price index from CPIs weighted by
merchandise line sales.
Furniture and home 571 Merchandise line sales for individual SIC 4-digit
furnishings stores industries deflated with matching CPIs combined with
gross margin weights. Indexes then combined with all
person-hour weights.
Household 572
appliance stores
Merchandise line sales for individual 4-digit industries
deflated with matching CPIs combined with gross
margin weights. Indexes then combined with all
person-hour weights.
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APPENDIX C
TABLE C. 1 Continued
237
Industry SICa Procedure
Radio and 573
television stores
Eating and 58
drinking places
Drug and proprietary 5912
stores
Retail liquor stores 5921
Commercial banking 602
Hotels and motels 7011
Laundry and dry 721
. .
cleaning services
Beauty and 7231,41
barber shops
Automotive 753
repair shops
Merchandise line sales for individual 4-digit industries
deflated with matching CPIs combined with gross
margin weights. Indexes then combined with all
person-hour weights.
For each type of outlet (restaurants, cafeterias, and
so on), CPI-deflated merchandise line sales combined
with gross margin weights. Outlet indexes in turn
combined with employment weights.
Prescription sales, meals and snacks, and general
merchandise sales deflated by matching CPIs. Deflated
sales then combined with employee-hour weights.
Deflated merchandise line sales combined with gross
margin weights.
Indexes for three major banking activities (deposits,
loans, and fiduciary) combined with employment
weights. Measure for deposits includes demand
deposits (based on number of checks and electronic
transactions) and estimated number of transactions in
time and savings accounts. Measure for loans based on
number of various types of loans combined with
employment weight. Measure for fiduciary activities
based primarily on number of trust accounts.
Separate indexes for hotels, motels, and tourist courts
combined with employment weights. For each index,
receipts for various activities (e.g., room rentals, food
sales, beverage sales, etc.) are deflated with matching
CPIs.
Deflated revenues from 8 types of laundry and dry
cleaning services combined with employment weights.
Beauty shop index based on deflated revenues for 14
types of services and barber shop index based on
deflated revenues for 13 services combined with all
person-hour weights.
Receipts from 12 industry activities deflated by
matching CPIs and combined with employment
weights.
aStandard Industrial Classification system code.
SOURCE: Bureau of Labor Statistics, unpublished data.
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238
INFORMATION TECHNOLOGY IN THE SERVICE SOCIETY
Conceptually, the measures for the transportation industries are easier
to develop than those for other service industries because transportation
industry output the movement of goods or passengers over distances is
more easily quantified. Units of output in transportation have two dimen-
sions, quantities and distance, that reflect how much has been transported
how far. As such, ton-miles, passenger-miles, barrel-miles, and so forth are
the primary indicators of output for these series of indexes.
For the most part, historically, these data have been available from the
regulatory agency of the particular transportation industry, such as the In-
terstate Commerce Commission (ICC) or the Civil Aeronautics Board. In
many cases, however, there are data gaps that place certain limitations on
the measures. For example, it is sometimes impossible to adjust the mea-
sures of output adequately for changes in the average length of haul. The
labor requirements associated with the movement of freight and passengers
are usually greater for short hauls than for long hauls. Therefore, a shift
from a long haul to a series of short-haul trips or vice-versa could be
interpreted as a change in productivity, although only the mix of trips has
changed.
For the two major freight-carrying industries, railroads and trucking,
undifferentiated data on ton-miles are reported for various classes of freight
operations. In trucking, the ton-mile data are reported separately for gen-
eral freight, specialized carriers, and carriers of household goods. But the
measures of output should reflect the kinds of commodities handled and the
average distance they are moved, since they represent separate types of
services. The preferred way to develop such measures would be to combine
the tonnage and average haul of each commodity with its respective re-
quirements for labor input and then aggregate the results for all commodi-
ties transported. Unfortunately, this cannot be done with currently avail-
able data.
However, for the railroad industry, information on tonnage for separate
commodities is available from the ICC for about 170 commodity lines,
ranging from agricultural and mining products to motor vehicles and scien-
tific instruments. Several years ago similar information was available for
the trucking industry, but its collection has been discontinued. The BLS
uses these data to adjust the overall measure of freight ton-miles for changes
in the composition of goods carried.
Although this adjustment for commodities hauled represents an improvement
over undifferentiated ton-mile figures, refinements cannot be developed to
the extent desirable. The adjustments to the index for the commodity hauled
are made in terms of unit revenue weights. The underlying assumption,
therefore, is that differences in labor requirements among commodities are
similar to differences in unit revenues. Since labor costs constitute more
than half of each industry's total operating costs, this assumption may not
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APPENDIX C
239
be unreasonable; however, the proportions could conceivably differ by commodity.
In deriving the index of total industry output for each of the transportation
industries, the freight ton-mile measure (adjusted or not) is combined with
the revenue passenger-mile measure.
The deregulation of many transportation industries has resulted in the
elimination of some of the operating statistics previously published and
used to develop the indexes of output. As a result, some of the measures
for the transportation industry have had to be extended on the basis of more
limited information. The BLS has been cooperating with other government
agencies to ensure that adequate statistics remain available for transporta-
tion industries.
Communications
The BLS index of productivity for telephone communications covers
about 70 percent of the employment of the communications sector. The
index of output is derived as a weighted aggregate of revenues adjusted for
changes in price for four different categories of telephone service: local
calls, measured toll service (MTS), wide-area toll service (WATS), and all
other services, including private-line service. The data on revenue are col-
lected and published by the Federal Communications Commission. Defla-
tors are derived from price indexes compiled and published by the BLS
under its Producer Price Index program.
The measure of deflated revenue includes revenues from private-line
services. It also accounts for TV, radio, and computer transmission by
telephone industry facilities as well as directory services.
Despite the detail that is included in the measure of output, improve-
ments could be made if information were available on the intensity of use of
telephone equipment by customers. The number of calls made can vary
without revenue also varying proportionately because of flat charges such
as WATS-line or local-call charges. To the extent that the number of such
calls varies over time, the index overstates or understates changes in output.
Electric, Gas, and Sanitary Services
Services rendered by public utilities range from the provision of light,
heat, and water to the disposal of solid and liquid wastes. In this area the
BLS currently publishes indexes of productivity for electric utilities, gas
utilities, and a combination of the two.
The measure for electric utility output covers all privately owned utili-
ties, which account for roughly 80 percent of the total output generated in
the United States. Output is defined in terms of kilowatt-hours generated
and distributed. - The measure of the output of gas utilities is defined in
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INFORMATION TECHNOLOGY IN THE SERVICE SOCIETY
terms of therms (one therm equals 100,000 British thermal units) delivered
to customers by all privately owned companies (which account for 95 per-
cent of total gas output).
Since the labor requirements per kilowatt-hour or per therm are higher
for residential than for commercial and industrial customers and are higher
for small establishments than for larger ones, BLS differentiates among
both kilowatt-hours and therms by type of customer.
Retail Trade
Although the BLS has been publishing measures of productivity for
retail trade industries since 1975, the number of such industries has in-
creased markedly in recent years. At present, indexes are available for 11
important industries-retail food stores, franchised new-car dealers, gaso-
line service stations, apparel and accessory stores, furniture and appliance
stores, eating and drinking places, drug and proprietary stores, and liquor
stores. Apparel and accessory stores are further broken out into men's and
boys' clothing stores, women's ready-to-wear stores, family clothing stores,
and shoe stores. Also, furniture and appliance stores are disaggregated into
furniture and furnishings stores, and appliance stores. Work is currently
under way on measures for hardware stores, auto and home supply stores,
and department stores.
For most retail trade industries, data on gross sales in current dollars,
deflated by appropriate price indexes, are used to estimate real output. This
method can yield good measures of real output if adequate consumer price
indexes can be developed that reflect the price movements of the various
commodities sold by the establishments. The recent improvements that
have been made in the BLS Consumer Price Index program have enabled it
to develop indexes of output and productivity for more components of retail
trade.
Indexes of productivity based on deflated value of sales output mea-
sures reflect shifts among services with different levels of sales but the
same trade labor requirements. Therefore, the overall industry productivity
index can show movements without any change in component elements.
In retail industries a large portion of the value of sales is provided by
the manufacturers and the wholesalers of the products sold. A measure of
net output would be desirable since it would most closely correspond to the
functions provided by the retailer. Unfortunately, measures of net output
based on data with separately deflated final sales and cost of materials can
result in large errors of measurement when the cost of materials is a large
proportion of the final value. This is because all the errors in the current
value of sales, the current value of material purchases, the Consumer Price
Index, and the Producer Price Index affect this residual.
Gross or total sales will represent a good measure of net output or value
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APPENDIX C
241
added with less measurement error if the value added as a percent of sales
(gross margin) does not change over time. Available data seem to indicate
that for the industries published, average gross margins have not changed
substantially over time. To introduce labor input weighting, the indexes for
retail trade industries for the most part are developed in two stages. De-
flated output measures are first developed for detailed merchandise lines.
These are aggregated to higher levels, and the resultant indexes are then
combined with labor-cost weights. For example, in retail food stores, sales
for 13 key merchandise lines are deflated using specially prepared price
indexes based on the BLS Consumer Price Index components. The indexes
for the merchandise lines are aggregated to five department lines meat,
produce, frozen food, dry groceries and dairy, and all others. These in turn
are aggregated with labor-cost weights to develop a measure of overall
output for grocery stores.
Wholesale Trade
Until recently the BLS did not publish any measures for wholesale
trade. Currently, only an index for scrap and waste materials dealers is
published. The measure of output is derived by combining the quantities of
various types of processed scrap into a broad product group and the various
types of processed wastepaper into an overall wastepaper group. Measures
for these two groups are then combined with employment weights to yield
measures of overall output.
The BLS is currently examining three industries in considerable detail
to derive reliable measures: metal service centers, petroleum bulk stations,
and beer, wine, and distilled spirits distributors. These industries include
about half a million workers, or 10 percent of the employment in the sector.
Data on physical quantity are available to develop measures of output for
these industries. The data on quantity for disaggregated commodities will
be combined with fixed-period labor input weights reflecting the services
provided by the wholesalers to retailers and other users.
Several measurement problems with respect to these industries need to
be resolved. Some firms perform work on commodities that they distribute
to retailers, but this practice varies substantially among wholesale distribu-
tors. Whether the labor input weights can adequately take this variation
into account is questionable. In addition, in some instances a regional
wholesaler distributes commodities to local wholesalers. This creates a
problem of duplicate counting in the measure of overall industry output.
Finance
In the area of finance, the BLS publishes a measure of productivity for
the commercial banking industry that reflects the three major services com
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INFORMATION TECHNOLOGY IN THE SERVICE SOCIETY
mercial banks render their customers-deposits, loans, and trust services.
While banks also perform nonfund-using services, such as safe deposit ser-
vices and customer payroll accounting, lack of adequate data precludes
deriving a measure for them. However, because the proportion of employ-
ees engaged in such services is small, the overall validity of the measure is
little affected by the omission.
There has been a great deal of discussion over the years as to the appro-
priate measure of the output of banking. Much of the discussion addresses
whether the appropriate concept is one based on what has been called the
liquidity approach or one based on a transactions approach. In the liquidity
approach the banks are viewed as providers of money to hold, and their output
is measured in terms of the interest received on the volume of deposits held.
Such interest received by banks is assumed to be equivalent to the income
foregone by depositors due to their preference for holding deposits rather than
for investing directly. The interest the depositors forego represents the value
of the banks' services for such liquidity preference. This approach can be
extended to all types of savings accounts, the assumption being that the fore-
gone net interest is the value of the banks' services.
According to the transactions approach, the banks are providers of a
series of services to their clients that are reflected in the transactions per-
formed. The volume of the banks' output is proportional to the volume of
the transactions handled. Thus the final output of commerical banking
represents an array of services provided to bank customers relating to the
depository, lending, and fiduciary functions of banks. In developing a mea-
sure of productivity for banking, the BLS adopted the transactions approach
for the measure of output.
Estimates of the number of transactions in each of the service functions
of banks are derived. In some instances, no direct count of transactions is
available, and so the number of transactions is estimated from data on the
total value of transactions and on the results of surveys of the average
dollar-value of transactions. Although these estimates have some limita-
tions, the derived count of the number of transactions is the measure used to
reflect the quantities of services provided.
Deposit activity is measured in terms of the number of checks trans-
acted and the number of time- and savings-account deposits and withdraw-
als. The data for demand deposit activities are derived ultimately from
Federal Reserve Bank counts and official benchmark surveys. For time-
and savings-deposit activity, the measure of output is derived from data
published by the Federal Deposit Insurance Corporation and the Functional
Cost Analysis conducted annually by the Federal Reserve Board. Lending
services provided by banks are also measured in terms of units. As in the
case of deposit activity and trust department activity, the BLS does not use
banks' financial data to arrive at measures of component output.
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APPENDIX C
243
Business and Personal Services
In the business and personal services sector, the BLS publishes mea-
sures for four industries hotels, motels, and tourist courts; laundry and dry
cleaning services; beauty and barber shops; and automotive repair shops.
The output for each of these industries is measured by total revenues from
the various activities of establishments within the industry adjusted by price
changes. These measures are then combined with employment weights to
derive an index of output for each industry. The BLS uses special price
indexes derived from its Consumer Price Index program for deflating the
receipts from the principal activities of each of the industries. For ex-
ample, in hotels and motels, the receipts from room rentals, food sales,
beverage sales, and so on are separately deflated by the appropriate price
measures, and these measures are then combined with employment weights.
It would be desirable to differentiate between all the separate activities of
these establishments, but because of the limited number of price indexes
that can be developed, some broader groupings have to be used.
Government
For the last 2 decades, the BLS has been conducting a program of
developing indexes of labor productivity for all federal government agen-
cies with 200 or more employees. Currently, the measures cover 390 orga-
nizations in 59 agencies that account for 60 percent of civilian government
employment. The agency measures are grouped into functional groups rep-
resenting relatively homogeneous activities, such as library services, loans
and grants, and information services.
Where possible, the output of a government agency is defined as its
final output what it produced for use outside the government. Therefore,
measures are also developed for agencies (and parts of agencies) providing
services to other parts of the government, such as printing, personnel man-
agement, communications, and supply and inventory control. Because of
the inclusion of intermediate activities and output, the index of overall
productivity is not final for the entire government. The summary produc-
tivity measure reflects the average of changes in the productivity of the
measured federal organizations.
The measures of output used in productivity calculations are diverse,
including such indicators as inspections completed and reports prepared (for
audit functions), statistical reports issued, maps produced, or weather fore-
casts made (for public information functions), food inspections conducted,
drug arrests made, applications and licenses issued, drugs approved, and
patents approved (for regulatory functions). Currently, output information
is collected on about 3000 indicators.
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INFORMATION TECHNOLOGY IN THE SERVICE SOCIETY
Hospitals
For several years the BLS has been working to develop a measure of
productivity for hospitals but has not yet determined whether the measure it
has developed is adequate for publication.
Hospitals provide services designed to eliminate, retard, or prevent pa-
thologies. Treatments, which can be regarded as producer technologies by
which those services are rendered, are specified to produce desired out-
comes. However, outcomes depend on factors other than, and in addition
to, treatments, such as the pre-admission health of the patient. There is thus
some question as to whether a measure of output related to hospital labor
and other resources should be based on outcomes. The BLS does not adjust
for outcomes in deriving its index of productivity for hospitals and instead
uses a different approach.
Clinically named illnesses have been classified according to diagnosis,
and diagnoses in turn are standardized into diagnosis-related groups re-
ferred to as DRGs. A DRG implies a complex of treatments or procedures,
which in turn are associated with the use of certain kinds and amounts of
resources.
All diagnosis codes have been condensed into 23 major diagnostic cat-
egories (MDCs). The MDCs are generally based on diseases that tend to be
diagnosed and similarly treated by specialists. Hospital discharges are first
coded by diagnosis and then into DRGs.
The BLS measure of output for hospitals is derived from data on the
number of inpatient discharges in each diagnostic category weighted by
average hospital operating costs and the number of outpatient visits for each
diagnostic category.
MEASURES OF LABOR INPUT
Productivity calculations require data on the hours worked of nonsupervisors,
supervisors, unpaid family workers, and the self-employed. The principal
source of data on employment and hours for all of the service industries for
which BLS publishes indexes of productivity is the BLS survey of estab-
lishments' payrolls, the Current Employment Survey (CES). This survey
provides good measures of the employment and hours of nonsupervisory
workers by industry, but it does not provide data on the average hours of
supervisory workers or on the employment and hours of unpaid family
workers and the self-employed.
Information on the self-employed and unpaid family workers is derived
from a survey of non-institutional households, the Current Population Sur-
vey (CPS). Based on 60,000 households in the United States, these data are
adequate for aggregate measures such as those for the business economy as
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APPENDIX C
245
a whole or even major sectors, but they present limitations when used for
such detailed measures as those for specific service industries.
Currently, the average weekly hours of supervisory workers are as-
sumed to be equal to those of nonsupervisory workers in the service indus-
tries. This assumption presents fewer limitations for developing measures
of change than for developing base labor input.
The most desirable measure of productivity is one that uses only the
amount of labor actually involved in the generation of the services provided
and excludes paid time off. The CES's data on hours are based on hours
paid and include paid vacations, holidays, sick leave, and other time off in
addition to actual hours worked. To the extent that leave practices change,
the resultant measures of productivity overstate or understate the actual
change in output per hour.
To develop a better series of hours at work, the BLS has been conducting
an annual survey (now in its ninth year) of some 4000 establishments to
collect data on hours at work and hours paid for nonsupervisory workers in the
private nonagricultural business sector. From this survey, ratios are developed
to adjust the present measures of hours paid (based on the CES data) to reflect
hours at work. After careful study, "hours at work" was defined as time on
the job or at the place of work and includes coffee breaks, short rest periods,
paid cleanup time, and other paid time at the workplace besides actual time
worked. Conceptually, this definition was considered to be the most accept-
able one to use for extracting data from establishments' records. Although the
appropriate information is available on hours at work at an aggregate level, a
substantial expansion of this survey will be required to develop reliable data
for specific service industries.
The BLS measures of productivity based on the hours at work for all
persons assume that workers are homogeneous with respect to skill that an
hour of one worker's time is as productive as an hour of any other worker's
time. However, a highly skilled worker can be viewed as providing more
labor services per hour than a less highly skilled one. Shifts within the
labor force from less skilled workers to more highly skilled ones because of
increased education or experience are not reflected as increases in the mea-
sures of labor input. When skill differences are ignored, increases in skill
levels are measured as increases in productivity.
To the extent that there are changes in the composition of the work
force with respect to education and experience that result in skill differ-
ences, it may be desirable to reflect those changes in measures of labor
input, since they will otherwise be reflected in measures of productivity.
To address this problem, previous studies have usually taken the posi-
tion that relative wage- or income-level differentials associated with spe-
cific worker characteristics reflect marginal productivity of these attributes.
Generally, the characteristics included are the number of years of schooling,
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INFORMATION TECHNOLOGY IN THE SERVICE SOCIETY
age, sex, and possibly industry and occupation. Weighting the quantity of
labor (hours of employment), classified by these characteristics of the work
force, by relative wage or income differentials results in an aggregate mea-
sure of labor input intended to reflect the composition of the work force.
But this procedure is not without problems. For example, workers with
similar characteristics have different earnings in different occupations and
industries. However, the correlation between industry and occupation and
earnings may also be due to influences other than productivity, such as
regional differences in the cost of living, degree of unionization, and so on.
The BLS has developed some experimental measures of labor input
based solely on changes in the amount of work experience and schooling
workers have.2 The methods used follow directly from the economic theory
of human capital developed by Mincers and Becker.4 The method rests on
the assumption that increased schooling and on-thejob training increase
one's stock of skills and productivity. It also assumes that economic re-
turns to higher education and additional work experience reflect the mar-
ginal productivity of these characteristics. The BLS has developed a multi-
dimensional database that cross-classifies the annual hours of workers grouped
by schooling and experience. The database has been developed from vari-
ous models that make use of decennial census data, a matched sample from
the CPS, and social security records.
As mentioned above, it is recognized that hourly wages differ not only
because of differences in skills but also because of factors unrelated to
productivity. Accordingly, simple averages of hourly wage rates for each
education and experience group are not necessarily appropriate approxima-
tions of marginal productivity. Consequently, the BLS has developed an
econometric model that provides measures of wages dependent on changes
in education and experience but that simultaneously controls for other types
of variation.
Skill-adjusted measures of labor input have been developed for the
business sector as a whole, and this work is currently being extended to
determine the feasibility of developing corresponding measures for specific
industries, especially service industries.
NOTES
1Gorman, J. 1969. "Alternative Measures of the Real Output and Productivity of Com-
mercial Banks," pp. 155-188 in Production and Productivity in the Service Industries, V.R.
Fuchs (ed.), Columbia University Press, New York.
2Waldorf, W.H., et al. 1986. "New Measures of the Contribution of Education and
Experience to U.S. Productivity Growth." Paper presented at the annual meetings of the
American Economic Association, December 28-30, New Orleans, La.
3Mincer, J. 1974. Schooling, Experience and Earnings, Columbia University Press, New
York.
4Becker, G. 1975. Human Capital, University of Chicago Press, Chicago and London.
Representative terms from entire chapter:
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