Increased productivity could be the key to preserving robust, noninflationary GDP growth. But what is the best measure of productivity? This Economic Commentary explores the relationship between labor productivity and multifactor productivity, a measure that accounts for factors other than technological improvement. It concludes that MFP provides a better measure of productivity due solely to technical change.Productivity ; Technology ; Labor productivity

Paul W. Bauer

English

Research Papers in Economics

W ith the U.S. unemployment rate at a
30-year historic low and the labor force
expected to grow only about 1 percent in
the near future, increased productivity
could be the key to preserving the coun-
try’s robust, noninflationary GDPgrowth.
As a result of compounding, even a small
boost in annual productivity growth can
yield large benefits in the long run. Pro-
viding more goods and services without
expending additional resources is a sure-
fire way of relieving supply-side bottle-
necks and improving living standards
over time.
Because productivity growth is so
important, volumes have been written on
how to measure its growth rate and how
to nurse an acceleration of that rate.
Although the general concept of produc-
tivity is straightforward (getting more
with less), when we introduce multiple
inputs and outputs, scale economies, and
quality changes in those inputs and out-
puts, obtaining estimates becomes con-
siderably more complicated. The pres-
ence of any of these factors can bias
measures of productivity gains.
Economists have developed a set of pre-
cise definitions to explore these jumbled
effects. The measure of productivity
growth most commonly written about is
labor productivity, because it is available
quarterly and has a direct bearing on
labor income. Under some circum-
stances, labor productivity is also a good
measure of technical change—that is, the
boost in output resulting from improve-
ments in technology, even if no more
inputs are employed. Technical change is
a more precise measure of productivity
than labor productivity, because it incor-
porates changes in the productivity of
other inputs and can adjust for changes in
scale economies and the quality of inputs
and outputs. Unfortunately, technical
change is also harder to measure.
This Economic Commentary explores
multifactor productivity (MFP), an
approach employed by the Bureau of
Labor Statistics, and examines the impli-
cations of the latest estimates from this
approach.1  MFPovercomes some of the
shortcomings of labor productivity as a
measure of technical change. By this
measure, although private nonfarm busi-
ness productivity growth rebounded in
1995–97, it has yet to reach the average
rate achieved during 1948–73. Based on
the relationship between labor produc-
tivity and MFPand the apparent short-
run stability of its other components,
MFPgrowth will likely be found to have
been robust in 1998 as well. In contrast,
from 1990 to 1996, manufacturing MFP
growth exceeded its 1949–73 rate, with
the two most recent years’rates being
particularly strong.2
 The Shortcomings of 
Labor Productivity
Measuring technical change can seem
relatively straightforward when one
service (Y ) is produced by employing 
a single input (L). In this case, labor
productivity (Y/L) is an obvious meas-
ure of the level of productivity, and
changes in this level estimate the rate 
of productivity growth.
Even in this simple case, complications
may arise in treating changes in labor
productivity as a measure of technical
change. First, changes in the quality of
the service or in the labor input could bias
this measure. For example, if a higher-
October 15, 1999
Federal Reserve Bank of Cleveland
Are We in a Productivity Boom? Evidence
from MultifactorProductivity Growth
by Paul W. Bauer
Increased productivity could be the
key to preserving robust, noninfla-
tionary GDPgrowth. But what is the
best measure of productivity? This
Economic Commentary explores the
relationship between labor productiv-
ity and multifactor productivity,  a
measure that accounts for factors
other than technological improve-
ment. It concludes that MFPprovides
a better measure of productivity due
solely to technical change.
ISSN 0428-1276
quality service were offered that required
more labor, then labor productivity would
appear to fall. This phenomenon is miti-
gated in practice, because output is usu-
ally measured by the value of goods and
services produced, particularly when
multiple goods and services are involved.
Higher-quality output is likely to com-
mand a premium price, so the bias due to
changes in output quality would be miti-
gated. Alternatively, improvements in
labor quality do not have this offsetting
characteristic; rather, higher-quality labor
(for example, additional education or
training) will likely boost labor produc-
tivity, but economists usually want to
examine the source of any productivity
gains for policy implications. If the gains
stem from higher labor quality, then
devoting additional resources to training
and education may further improve gains.
Alternatively, if the source of the gains
lies elsewhere, then this policy would not
be as attractive.Another possibility is that the production
process exhibits scale economies (or pos-
sibly diseconomies). Scale economies are
found in industries where unit costs fall
as the scale of operations increases. This
phenomenon was first studied in pipeline
industries at the turn of the century, when
it was observed that the amount of mater-
ial required to make a pipe of a given
diameter increased only two-thirds as
quickly as the carrying capacity of the
pipe. This observation led to larger pipes
having lower unit costs. Here, the gain in
productivity came not from an advance
in technology or higher-quality inputs,
but from a larger scale of operations.
Again, the source of gains is important
because it may affect policy decisions: in
industries with scale economies, policy-
makers may want to encourage output
growth and maybe even consolidation—
as long as pricing remains competitive.
Matters get even more involved when
there are multiple inputs, a much more
realistic case. In this scenario, labor pro-
ductivity is a biased measure of technical
change if the employment of other inputs
does not increase proportionally to labor.
Consider capital deepening—that is,
more capital employed per unit of labor.
If, for instance, a farmer employs satellite
imagery and global positioning technol-
ogy to more effectively manage his
acreage, his labor productivity should
rise. However, not all of this gain is tech-
nical change, because the farmer is now
also employing more capital. The addi-
tional capital must be accounted for to
obtain a measure of productivity gains
resulting solely from improvements in
technology. 
   Measuring Technical Change
It is useful to disentangle productivity
gains that result from technological
improvements from gains that result
from other sources (capital deepening,
changes in input quality, and scale
economies). One way to think about
technical change is as an outward shift in
the production-possibility curve. This
curve represents the maximum amount
of output that can be produced from a
given bundle of inputs. In figure 1, the
curve PPFt represents the combinations
of outputs Y1 and Y2 that can be pro-
duced from inputs available at time t.
Similarly, PPFt + 1 represents the output
choices possible at time t + 1. Because
of advances in technology, more of both
outputs can be produced from the fixed
bundle of inputs. Ameasure of technical
change should be a single number that
describes the shift in the production-
possibility curve from PPFt to PPFt + 1,
say, from A to B. 
The most widely reported measure of
technical change is calculated by the BLS
and is reported as the multifactor produc-
tivity index, also referred to in other con-
texts as total factor productivity or the
Solow residual. MFPis less widely
known and reported than labor productiv-
ity because it is only available annually
and is only released biennially. The rea-
son for the delay and the relative infre-
quency of reporting is that MFPrequires
more data to calculate. Labor productiv-
ity requires only estimates of output and
labor input, both of which are available
quarterly. In addition to output and labor,
MFPalso requires an estimate of capital,
which is only available annually.3
For the purposes of this study, we have
abstracted from productivity changes due
to scale economies. While the assump-
tion of constant returns to scale could be
a problem for some industries, it is a rea-
sonable approximation for the economy
as a whole and for most subsectors. For
sectors in which this assumption is not
reasonable, the estimated technical
change will be biased upward when out-
1948–97 1948–73 1973–79 1979–90 1990–97 1996 1997 1998
Labor 
productivity 2.0 2.9 1.1 1.0 1.2 2.5 1.2 2.3
Contribution of capital 
deepeningb 0.7 0.8 0.6 0.7 0.4 0.7 0.4 —
Contribution of 
labor qualityc 0.2 0.1 0 0.3 0.4 0.4 0.3 —
Multifactor 
productivity 1.1 1.9 0.4 0 0.4 1.5 0.4 —
a. Excludes government enterprises.
b. Calculated as the growth rate in capital services per hour multiplied by capital’s share of current dollar costs.
c. Calculated as the growth rate of labor composition (the growth rate of labor input less the growth rate of hours
of all persons) multiplied by labor’s share of current dollar costs.
NOTE: Multifactor productivity and contributions may not equal labor productivity due to independent rounding.
SOURCE: U.S. Department of Labor, Bureau of Labor Statistics.
1949–96 1949–73 1973–79 1979–90 1990–96 1995 1996
Labor 
productivity 2.8 3.0 2.1 2.6 3.4 3.9 4.1
Multifactor 
productivity 1.3 1.8 –0.6 1.0 1.7 3.8 2.1
SOURCE: U.S. Department of Labor, Bureau of Labor Statistics.
Average annual growth rates (percent)
Industry 1949–96 1949–73 1973–79 1973–96 1990–96
All manufacturing 1.2 1.5 –0.5 1.0 1.7
Nondurable manufacturing 0.7 1.4 –0.5 0.3 0.3
Durable manufacturing 1.5 1.5 –0.5 1.6 3.0
Industrial and 
commercial machinery 1.6 0.7 –0.2 2.9 4.6
Electrical and 
electronic machinery 2.9 2.0 1.1 2.6 8.9
NOTE: Multifactor productivity measures by industry are not directly comparable to measures for aggregate
manufacturing because industry measures exclude transactions only within the specific industry, while the aggre-
gate manufacturing measures also exclude transactions between all manufacturing industries.
SOURCE: U.S. Department of Labor, Bureau of Labor Statistics.
TABLE 1 PRIVATE NONFARM BUSINESS 
PRODUCTIVITY
a
TABLE 3 MANUFACTURINGINDUSTRIES: MULTI-
FACTOR PRODUCTIVITYTRENDS, 1949–96
TABLE 2 PRODUCTIVITYIN MANUFACTURINGput is growing, as some of the gains
attributed to technical change will actu-
ally accrue from exploiting scale econ-
omies. In analyzing the latest MFP
growth estimates, we will make use of a
decomposition that separates labor pro-
ductivity gains into effects stemming
from MFPgrowth, capital deepening,
and improvements in labor quality.4
 MFPGrowth Estimates  
Because MFPgrowth is not as widely
reported as labor productivity, first con-
sider the long-run trends to see how the
two measures have related over time. For
the private nonfarm business sector, both
labor productivity and MFPhave grown
sharply since 1948 (see figure 2 and table
1). The postwar pattern for labor produc-
tivity is well known. In the “golden age,”
1948–73, growth averaged 2.9 percent
annually. From 1973 to 1990, though,
labor productivity was only 1.1 percent.
The overall rate in the 1990s has shown a
barely perceptible increase to 1.2 percent.
This rate appears to have increased in the
last year of available data; however, the
2.3 percent rate reported for 1998 stills
falls short of the 2.9 percent rate aver-
aged in the golden age.
Table 1 shows how the sources of labor
productivity gains have changed over
time. Technical change, as measured by
MFPgrowth, accounted for well over
half of labor productivity gains in the
golden age, averaging 1.9 percent annual
growth. Now, however, it accounts for
only one-third. From 1973 to 1979, MFP
growth fell to 0.4 percent and then plum-
meted to zero from 1979 to 1990. During
the 1990s, MFPgrowth has recovered to
0.4 percent, yet it is still below the rate
posted during the golden age.
The share of labor productivity growth
attributed to capital deepening has been
about one-third over the postwar period.
The magnitude of the contribution has
fallen as the growth rate of capital
slowed (see figure 3). In the golden age,
it accounted for 0.7 percentage points of
the observed growth in labor productiv-
ity, but now accounts for only 0.4 per-
centage points.
In the 1990s, improvements in labor
quality in the form of additional educa-
tion and work experience accounted for
one-third of labor productivity gains.
This is a significant change since the
golden age, when improvements in labor
quality boosted labor productivity only
0.1 percentage points. In the 1990s,
improvements in labor composition have
contributed 0.4 percentage points to
labor productivity growth. 
Because of the relationship between
labor productivity and MFP, we can use
more recent estimates of labor produc-
tivity to forecast MFP. Given that labor’s
cost-share is 65 percent–70 percent
(depending on the economic sector
under consideration); that the capital
deepening and labor quality components
of the decomposition tend to remain sta-
ble in the short run; and that labor pro-
ductivity has been strong the last couple
of years, MFPgrowth should have been
robust in the years for which data on
MFPare not yet available. Of course, it
should be remembered that the U.S.
economy has been in the midst of a capi-
tal investment boom, with capital ser-
vices accelerating to a growth rate of 
4.4 percent, the highest rate since 1984.
Thus, it is conceivable that capital deep-
ening could be driving a slightly larger
share of labor productivity, cutting into
that which might be provided by MFP.
The patterns for manufacturing’s labor
productivity growth and MFPgrowth are
similar, but with an important twist (see
table 2). Unlike private nonfarm busi-
ness, manufacturing’s MFPand labor
productivity in the 1990s have actually
surpassed that experienced 1949–73. The
BLS also estimates MFPfor specific
manufacturing industries (see table 3).5
Durable manufacturing’s recent 3.0 per-
cent annual growth rate is double that
experienced in the golden age; however,
the corresponding figures for nondurable
manufacturing are only 0.3 percent and
1.4 percent, respectively. While most
nondurable manufacturing industries
have underperformed the MFPgrowth
rates achieved in the 1949–73 period,
durable manufacturing has a few sectors
for which the 1990s are the golden age.
In particular, industrial and commercial
machinery and electrical and electronic
machinery have had MFPgrowth during
the 1990s far exceeding that achieved
from 1949 to 1973. As these two sectors
encompass computers and telecommuni-
cations, rapid technical change is not too
surprising; however, these are also two
sectors where the assumption of constant
returns to scale may be the most tenuous,
so some of these gains may be the result
of exploiting scale economies.6
0 5 10 15 20 25
0
5
10
15
20
25
Y2
Y1
PPFt
PPFt + 1
A
B
FIGURE 1 TECHNICAL
CHANGE
SOURCE: Author’s calculations.
300
Index, 1948 = 100
180
240
140
280
160
220
120
260
200
100
Labor productivity
Multifactor
productivity
1948 1957 1962 1967 1972 1977 1982 1987 1992 1997
FIGURE 2 PRIVATE NON-
FARM BUSINESS
PRODUCTIVITY
MEASURES
SOURCE: U.S. Department of Labor, Bureau of
Labor Statistics.
Index, 1948 = 100
450
400
350
300
250
200
150
100
50
0
Manufacturing
Private
nonfarm
business
1955 1950 1960 1965 1970 1975 1980 1985 1990 19952000
FIGURE 3 CAPITAL
DEEPENING
SOURCE: U.S. Department of Labor, Bureau of
Labor Statistics. Summary
This Economic Commentary has ex-
plored the relationship between labor
productivity and technical change (mul-
tifactor productivity). While labor pro-
ductivity is a useful measure, it can be
affected by factors other than improve-
ments in technology, such as scale econ-
omies, multiple inputs, and quality
changes. The MFPgrowth indexes are a
better measure of productivity gains due
solely to changes in technology.
Private nonfarm business productivity
growth has rebounded in recent years,
but it has yet to reach the average rate
achieved in 1948–73. However, manu-
facturing’s MFPgrowth has exceeded its
golden-age rate in the 1990s. Most of
this gain is concentrated in durable man-
ufacturing, mainly commercial and in-
dustrial machinery and electrical and
electronic machinery. Because of labor
productivity’s large share in the MFP
index and the short-run stability of the
effects of capital deepening and changes
in labor quality, MFPgrowth will likely
be found to have been strong in 1998
once those data become available.
 Footnotes
1. For complete details on how the Bureau
of  Labor Statistics calculates its MFP
indexes, see the BLS Handbook of Methods,
Chapter 10, “Productivity Measures: Business
Sector and Major Subsectors,” April 1997.
2. The years for which statistics are re-
ported for private nonfarm business and man-
ufacturing differ because of data availability.
3. For the more detailed manufacturing
MFPindexes, estimates of employment in
energy, materials, and business services are
also required, resulting in further delays.
4. For details, consult the BLS Handbook of
Methods.
5. In addition to labor and capital, energy,
nonenergy materials, and purchased business
services inputs are included. Due to the avail-
ability of data for these additional inputs,
MFPestimates extend only to 1996.
6. For more on the relationship between
computers and productivity, see Robert J.
Gordon, “Has the ‘New Economy’Rendered
the Productivity Slowdown Obsolete?”
Northwestern University, working paper,
June 1999.
Paul W. Bauer is an economic advisor at the
Federal Reserve Bank of Cleveland.
The views stated herein are those of the
author and not necessarily those of the Fed-
eral Reserve Bank of Cleveland or of the
Board of Governors of the Federal Reserve
System.
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Are we in a productivity boom? Evidence from multifactor productivity growth

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Are we in a productivity boom? Evidence from multifactor productivity growth

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