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OCR for page 86
4
Studies of the Impact of Technological
Change on Employment, Skills, and
Ear sings: A Critical Review
This chapter reviews a number of studies that analyze the influence of
new technologies on jobs, worker skills, and earnings. As in other areas
of our inquiry, the extensive empirical literature covering these topics
often is inconclusive and supers from methodological weaknesses.
Nonetheless, several important conclusions emerge from the discussion
that follows. First, new technology will not bring massive unemploy-
ment; few studies predict large employment losses from such changes.
Neither does it appear that, as a result of technological change, the skills
required to get a job or to keep a job in the future will be substantially
different from what they are today. Finally, technological change and
productivity growth are associated with growth in real earnings. A1-
though technological change in the U.S. economy has been cited by
some as contributing to lower earnings growth and a more unequal
distribution of income, there is little evidence to suggest that technol-
ogy, as opposed to slow economic growth, has been responsible for
these trends.
THE EMPLOYMENT EFFECTS OF TECHNOLOGICAL CHANGE
As we noted in Chapter 2, a number of factors interact to influence how
technological change affects the level of employment in an industry or
sector:
· the speed with which a product or process innovation is adopted;
86
OCR for page 87
STUDIES OF THE IMPACT OF TECHNOLOGICAL CHANGE 87
· for a product innovation, the size and rate of growth of the domestic
and international markets for the new product;
· for a process innovation, the size of any reductions in labor require-
ments per unit of output (i.e., increases in labor productivity);
· the magnitude of reductions in output prices resulting from labor
productivity increases, movement down the "learning curve" (cost
reductions associated with more extensive use of the new process
technology), and subsequent refinements of the technology;
· the size of the increase in domestic and international demand for the
product in response to price reductions resulting from the adoption of a
new process technology;
· interindustry effects (e.g., expansion or contraction in another indus-
try in response to changes in the cost of a key input); and
· the. ~.ff~.~.t~ of t~c~hnolo~ical chance on wages in the industry or
~ ~ A ~ C ~
sector.
These variables exert offsetting influences on the demand for labor
within sectors, and they operate with varying lags. A complete accounting
of all of their effects is impossible. The studies considered below, in a
survey that is meant to be illustrative rather than exhaustive, all ignore
one or more of the variables in this list. The range of influences
considered within each study, as well as the level of aggregation at which
each is conducted, varies considerably. As the number of sectors or
technologies expands, however, the data requirements rapidly become
overwhelming. To circumvent this difficulty, the studies cited here focus
on the impacts of a single technology in many industries or on the effects
of technological change within a single industry-with the exceptions of
the U.S. Bureau of Labor Statistics (1986b) forecasts of employment and
the policy-oriented studies by the Temporary National Economic Com-
mittee (1941) and the National Commission on Automation, Technology,
and Economic Progress (1966~.
Policy-Oriented Studies
A perception that technological change had played a role in the Great
Depression led to the publication of studies of the economic effects of
technological change by the Congress (U.S. House of Representatives,
Committee on Labor, 1936), the National Resources Committee (1937),
and the Temporary National Economic Committee (19411. Many of these
'For comprehensive surveys of this large and rapidly expanding literature, see Blair
(1974), Brooks and Schneider (1985), Fechter (1974), Freeman and Soete (1985), and
Kaplinsky (1987).
OCR for page 88
88 TECHNOLOG Y AND EMPLO YMENT
studies reached pessimistic conclusions. The following comments from
the report of the Temporary National Economic Committee are repre-
sentative:
. . . there is unmistakable evidence of a change in kind as well as severity of
unemployment in the last depression. This change is characterized by the
widespread use of electrical power and mass production methods which have
shown a capacity to increase industrial activity on the upturn of the business cycle
without a corresponding ability to absorb unemployed labor. (p. xvi)
With the return of full employment during World War II and sustained
prosperity during the remainder of the 1940s, the conclusions of these
studies had little discernible impact on policy or economic research. But
high (by comparison with prior years) U.S. unemployment rates during
the late l950s and early 1960s,2 coupled with rates of economic growth
that fell behind those of Western European nations, fueled a resurgence of
the debate over the employment consequences of automation. Pessimism
and concern about the consequences of technological change were
reflected in such work as Michael (1962), and this concern contributed to
the formation of the National Commission on Technology, Automation,
and Economic Progress in 1964 (see Critchlow, 19871. The tone of this
commission's report, however, contrasted with the pessimistic views that
had spurred its development.
The commission strongly endorsed the importance of technological
change in raising living standards and improving the quality of worklife
but acknowledged that its benefits were not costless. Moreover, despite
its endorsement of the benefits of technology, the commission echoed the
reports of the 1930s in expressing concern over a "glut of productivity."
The historically unprecedented productivity growth rates of the postwar
period were expected to continue, and the commission argued that
increases in output per worker (i.e., labor productivity) would reduce the
demand for labor if they were not offset by growth in the demand for
output. Aggregate demand, the commission warned, had to be maintained
at a level that ensured sufficient jobs for the growing work force.
Although it recommended additional assistance for the technologically
displaced, the commission concluded that if macroeconomic policy were
properly managed, the probability of massive technological unemploy-
ment was low because expanding aggregate demand could ensure more
jobs, even in the face of an expanding work force and growing labor
productivity. Such optimism rested on the apparent triumph in the early
2Annual unemployment averaged 5.8 percent during 1958-1962, well above the average
rate of 4 percent that prevailed during 195~1957 (President's Council of Economic
Advisers, 1987, Table B-35).
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STUDIES OF THE IMPACT OF TECHNOLOGICAL CHANGE 89
1960s of policies for the management of aggregate demand. By the time
the commission's report was released in 1966, however, the economic and
political outlook had changed dramatically. Concern over the impacts of
new technology had declined, in part because the U.S. unemployment
rate was only 3.8 percent, having fallen from 5.2 percent in 1964 in
response to an expansionary fiscal policy (President's Council of Eco-
nomic Advisers, 19874. This improvement in the economic environment,
as well as the escalating U.S. involvement in the Vietnam conflict, meant
that the commission's policy recommendations were largely ignored by
the Johnson administration. During the 1970s the employment conse-
quences of technological change received little attention, but the subject
returned to a position of prominence in public debate in the 1980s.
Studies of Individual Firms, Industries,
or Occupations
A recent survey by Flynn (1985) analyzed almost 200 case studies of
the employment effects of process innovations during 1940-1982. The
technological advances considered by Flynn were evenly divided be-
tween those affecting the automation of production or distribution and
those affecting office automation. Process innovations in skill-intensive
manufacturing processes often eliminated high-skill jobs and generated
low-skill jobs. The opposite was true, however, for the adoption of data-
and word-processing technologies in offices, which eliminated low-skill
jobs and created high-skill jobs. Flynn concluded that the net effect of
process innovations on employment was indeterminate and depended
heavily on conditions within individual industries or firms.
Hunt and Hunt (1986) surveyed the effects of technological change on
clerical employment. The authors criticized several other studies of this
topic for overlooking the often slow pace of technological change and
diffusion, the output-expanding impacts of reductions in the price of such
clerical or secretarial activities as text editing, and the effect of expanding
aggregate demand. They argued that these flaws led the studies to
overstate the job-displacing impact of technological change on clerical
workers:
The forecasts of declining clerical employment are based on over-optimistic
expectations of technological improvements or exaggerated productivity claims
on behalf of existing technology. In our opinion, current office technology offers
significant improvements in product quality and modest improvements in produc-
tivity. There is as yet no empirical evidence of an office productivity revolution
that will displace significant numbers of clerical workers. (p. 65)
Osterman (1986) also studied the impact of information technologies on
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90 TECHNOLOG Y AND EMPLO YMENT
office and clerical employment in several industries and found that
displacement was partly offset by an expansion in the demand for
automated activities or functions. Although the adoption of computers
initially reduced the employment of clerks and managers in these indus-
tries during 1972-1978, displacement typically was followed in a few years
by increases in clerical and managerial employment.
The timing of the employment-displacing and employment-expanding
effects of technological change in Osterman's study suggests the empirical
problems that result from differences in the rates and timing of produc-
tivity growth, cost reduction, and output and employment growth.
According to Osterman, the increases in employment that followed the
introduction of computers generally were insufficient to overcome the
employment losses. Over a longer period, however, the net employment
losses might well have been smaller or nonexistent. Osterman also did not
consider the employment effects of new jobs created elsewhere within the
firms adopting computers. Nevertheless, differences in the timing of
employment displacement and creation mean that the workers who are
initially displaced may not be the individuals who are subsequently hired.
Significant displacement problems thus may develop even in the face of
expanding employment opportunities.
In their recent analysis of office automation, Roessner et al. (1985)
present conclusions that contrast sharply with those of the National
Research Council's Panel on Technology and Women's Employment. In
its 1986 report the panel concluded that "massive job loss is unlikely to
occur" (p. 125) within clerical and office occupations as a result of
technological change. The Roessner team, on the other hand, projected
that office automation could displace as much as 40 percent of 1980
clerical employment within the financial services and insurance industries
by the year 2000. To reach this conclusion the authors surveyed experts
on likely improvements in office automation technologies and applied
these forecasts to a functional taxonomy of clerical tasks. They assumed
that the functional composition of typical clerical tasks and duties would
be unaffected by technological change during 1980-2000. They also
assumed that technological change and diffusion would be rapid and
minimized or dismissed the possibility that the enhanced productivity of
clerical workers might increase the demand for clerical services. Finally,
the study ignored the employment implications of product innovations
that result from office automation technologies, even though executives
within the financial services industry, among other sectors, have cited
such innovations as important sources of employment growth.
Denny and Fuss (1983) investigated the effects of automation on
occupational groups within Bell Canada, using data on four separate
occupations and a direct measure of the rate of technological change
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STUDIES OF THEIMPACTOF TECHNOLOGICAL CHANGE 91
(based on the share of direct distance dialing in total telephone traffic).
Technological change in Bell Canada during 1952-1972 increased the
amount of capital and reduced the amount of labor per unit of output, with
the laborsaving effects felt most strongly in the least skilled occupations.
The study found, however, that net employment growth within these
occupations was positive because output growth more than offset the
impact on employment of reductions in labor requirements per unit of
output. The Denny-Fuss study did not deal with the potentially
employment-creating effects of these innovations on other industries or
on occupations within Bell Canada beyond the four considered.
Levy et al. (1984) analyzed the interactions among technological
change, growth in productivity, and growth in output and employment in
a number of industries. They assessed the effects on output growth and
employment of labor productivity growth resulting from technological
change and increases in production plant scale during 1960-1980 in five
manufacturing and mining industries (steel, aluminum, automobiles, coal
mining, and iron mining). Within all these industries, technological
change led to the substitution of capital for labor and to increases in labor
productivity (although steel exhibited a very low rate of technological
change), a finding similar to that of Denny and Fuss. An important
improvement in this analysis, however, is the Levy team's consideration
of the effect of productivity growth on the demand for the output of these
industries. By lowering prices and increasing the demand for industry
output, labor productivity growth supported employment growth that
offset much or all of the reduction in labor demand associated with the
productivity-increasing impact of technological change. In three of the
five industries (coal mining, iron mining, and aluminum production), the
output-enhancing effect of technological change increased total employ-
ment; in the other two (steel, where technological change was minimal,
and automobiles), demand growth was insufficient to offset the impact of
reductions in the labor required per unit of output.
Studies by Ayres and Miller (1983) and Hunt and Hunt (1983) consid-
ered the impact of robots on manufacturing employment. Ayres and
Miller concluded that current robotics technologies could displace 1.5
million jobs in current manufacturing and as many as 4 million by 2005.
Hunt and Hunt, on the other hand, estimated that total employment
displacement by 1990 would amount to only 68,000-134,000 jobs well
below levels of normal turnover within the manufacturing work force.
(Turnover in U.S. manufacturing averages more than 20 percent per year,
based on data from 1976-1980 cited in Levy et al., 1984.)
One reason for these divergent estimates is Ayres and Miller's assumption
that diffusion and technological improvement within robotics would be rapid.
Ayres and Miller's study focused on the technological "frontier" and
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92 TECHNOLOGY AND EMPLOYMENT
considered the number of jobs that potentially could be performed by robots
in 2005. The alternative approach, developing a model that incorporates
adoption costs and diffusion rates, places greater emphasis on the length of
time needed for investment in and adoption of the new technology. The
Ayres-Miller study also surveyed a small and narrow sample of firms and
industries (16 firms, almost all of which were in the automotive industry and
therefore contained a high proportion of jobs that could be performed by
currently available robots). The empirical basis for the less dramatic dis-
placement estimates of Hunt and Hunt's 1983 work, which made explicit
assumptions about rates of adoption of robotics technologies and employed
a broader data base for estimates of employment effects, seems stronger than
that for Ayres and Miller's predictions. Neither study considered the
employment implications of the potential growth in output resulting from the
positive effects of robots on manufacturing productivity growth, although
Hunt and Hunt compared their displacement estimates with the BLS
estimates of employment growth in affected occupations through 1995.
The contrasting results of these studies, like those of the studies by
Roessner et al. (1985) and the National Research Council's Panel on
Women's Employment and Technology (1986), illustrate the sensitivity of
empirical estimates of the employment impacts of technological change to
detailed assumptions concerning diffusion rates, technological improvement,
and the organization of manufacturing and office production processes. Yet
prediction of these vanables, which is necessary for forecasts of employment
impacts, is extremely difficult and frequently incorrect; therefore, the
forecasts based on such assumptions are often unreliable.
An important collection of sectoral studies of employment and techno-
logical change in Great Britain recently has been completed by the
Science Policy Research Unit of the University of Sussex. Known as the
TEMPO (Technological Trends and Employment) project, these studies
(Clark, 1985; Freeman, 1985a; Guy, 1984; Smith, 1986; Soete, 1985)
analyzed recent trends in technological change, productivity growth, and
employment in 17 British manufacturing and service industries. The
project focused on sectoral studies because of the evidence that the
impacts of technological change on productivity and employment growth
varied greatly across sectors.3
The TEMPO studies also undertook forecasts of employment through
the late l990s. The analytic framework used by most of the studies (with
the exceptions of Ray, 1985, and the studies of the services sector in
3"A broad macroeconomic approach was therefore deemed to be inadequate for
assessing the specific employment effects of technological change. It was felt that only
in-depth studies of each of the main sectors would encompass the full range and variety of
technical change" (Guy, 1984, p. vii).
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STUDIES OF THE IMPACT OF TECHNOLOGICAL CHANGE 93
Smith, 1986) is discussed in Clark and Patel (19841; it relied on estimates
of investment and the rate of growth of the capital stock to compute
measures of growth in "best-practice" and "average" productivity for
both labor and capital. ("Best-practice" productivity is the level attain-
able with the latest process technologies; "average" represents the actual
level of measured productivity.) Estimation of these trends relied heavily
on imperfect data on the value of the capital stock in industrial categories
that are highly aggregated; the estimates also incorporated strong assump-
tions concerning the rate of growth in the productivity of new technolo-
gies. The methodology demands considerable data, and the absence of an
aggregate analytic framework precludes the examination of interindustry
effects of the type that are salient within input-output analysis (see
below). Nonetheless, by emphasizing the roles of capital formation and
diffusion in the growth of sectoral productivity and employment, this
methodology makes an important contribution.
For many of the sectors in the TEMPO series, projected employment
growth was low or even negative; these predictions were affected by the
inability of the researchers to take into account interindustry linkages, by
the low rate of growth of the British economy during the late 1970s and
1980s, and by the extensive penetration of many British markets by
imports. Many of the studies examined capital productivity trends and
reached conclusions resembling those of Baily (19861; in a number of
British industries during the 1970s and early 1980s, the measured produc-
tivity gains from additional investments in physical capital appear to have
declined somewhat for reasons that are not well understood. Freeman
(1985b), for example, suggested that the radical nature of many new
technologies made it difficult for British firms to exploit their productive
potential rapidly.4
As this survey of the empirical literature suggests, few case studies are
able to consider the complex effects of technological change on employ-
ment beyond the confines of a single firm, industry, or occupation. A
study of the effects of robotics on assembly line workers, for example,
may estimate the worker displacement that occurs due to one aspect of
this technological change, but it cannot assess all the employment impacts
of the new technology. Such an assessment requires additional informa-
tion on the number of jobs created in designing, manufacturing, and
servicing robotics machinery, as well as data on the effects on prices,
4Freeman (1985b) stressed the ". . . tendency to diminishing returns with incremental
innovations and economies of scale in the older electro-mechanical plant and equipment of
the 1960s . . . ," and the ". . . failure to exploit the full productivity potential of the
revolutionary new technologies, based on computerization, because of the piecemeal
pattern of implementation and the lack of necessary skills" (p. 77).
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94 TECHNOLOG Y AND EMPLO YMENT
demand (how much will demand for the product increase if the price is
reduced?), and, consequently, employment in all industries affected by
the robotics technology. A broad analytic perspective is needed to
capture interactions among firms, industries, and occupations, as well as
changes over time in these effects. Despite their value as descriptions of
potential employment impacts, sectoral studies cannot incorporate these
complex interactions and should not be relied on for forecasts of the
aggregate employment impacts of technological change.
Aggregate Analyses
Input-output analysis can incorporate the interactions among indus-
tries that are essential to determining the total employment effects of
technological change. The expanded scope of such an analysis, however,
creates extensive data requirements. Input-output analysis requires the
estimation of "input-output coefficients," which describe the amount of
labor and each industry's output needed to produce the outputs of all
other industries in the analysis.5 The effect of technological change on
these coefficients must be estimated, and final demand for each good must
be projected in forecasts of the employment impact of new technologies.
The input-output coefficients in many cases are invariant with respect to
price: doubling the cost of an input need not affect the amount of that
input consumed by an industry. Thus, most forms of input-output
analysis can account only for changes in interindustry relationships that
are based on the technologically driven substitution of one input (e.g.,
capital) for another (e.g., labor).
Recent applications of input-output methodology to the analysis of the
employment effects of new technologies largely ignore changes in final
demand and in the demand for inputs that result from changes in price.
This means that there is no link between growth in labor productivity and
growth in demand within a specific industry. Because input-output
analysis typically projects the existing matrix of output and input require-
ments forward in time, predictions based on this methodology also have
difficulty incorporating the employment effects of product innovation.
Howell (1985) used an input-output framework to forecast the employ-
ment effects of industrial robots. His methodology required projections of
the use of robots in each of 86 industrial sectors in 1990, as well as
estimates of input-output coefficients that measure the robotics indus-
try's consumption of the output of other industries in the production of
robots. Howell considered the employment consequences of six different
5Leontief and Duchin (1985) used an 89-industry input-output table.
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STUDIES OF THE IMPACT OF TECHNOLOGICAL CHANGE 95
estimates of the number of installed robots in 1990, ranging from 72,000 to
285,000.6 Howell's analysis did not consider the increases in employment
that might result from reductions in price and increases in demand
associated with the diffusion of robotics technology. For example, the
introduction of robots within an industry might lower prices and increase
demand for the industry's output, but Howell's methodology largely
ignores the employment effects of such potential growth in output.
Using a methodology that may overstate the potential employment
displacement due to robots, Howell concluded that the net number of jobs
displaced by robots by 1990 would range from 168,000 (assuming slow
diffusion of robotics) to 718,000 (for the most rapid assumed diffusion
rate). The latter figure is only 0.7 percent of total U.S. employment and
3.7 percent of manufacturing employment in 1986; it accounts for an even
smaller share of total projected 1990 employment.
Leontief and Duchin (1985) undertook the most extensive input-output
study of the effects of computer technology on employment. Their study
concluded that the widespread use of this technology would reduce
employment in the year 2000 to approximately 8-12 percent below the
levels that would be needed to produce this output with an unchanged
technology. The Leontief-Duchin study illuminates the serious limitations
of aggregate studies of technological change. The study's assumptions
concerning the quantity of labor displaced as a result of computer
diffusion were based on limited evidence from case studies. Rates of
diffusion and technological change were assumed to be rapid, but the
authors did not allow for any output- and employment-expanding erects
of reductions in the costs of clerical and other functions as a result of
technological change and productivity growth.
A more serious defect of the Leontief-Duchin study is that it combined
an economy-wide analysis of employment impacts with the assumption
that advances would occur in only one technology. For example, as a
result of assuming that no technological change beyond that in computers
would occur within the agricultural sector and that demand for total
output would grow, the authors projected employment gains in farming by
the year 2000. Such an outcome is open to considerable question. The
Leontief-Duchin projections of reduced employment by the year 2000
were criticized by the National Research Council's Panel on Technology
and Women's Employment (1986), which concluded that "there is
insufficient evidence to support the . . . negative outlook of the Leontief-
Duchin study" (p. 1111. This panel concurs in that assessment.
6In 1986, according to the Robotic Industries Association (1986), the U.S. stock of
industrial robots was slightly more than 25,000.
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96 TECHNOLOG Y AND EMPLO YMENT
The most recent aggregate projections of employment that incorporate
the effects of technological change were prepared by BLS for 378
industries and 562 occupations in 1995. In the past the BLS projections
have proved quite accurate in tracking changes in employment, although
they tend to understate employment growth in the fastest growing
occupations and employment decreases in declining occupations (Carey,
1980; Carey and Kasunic, 1982; Rumberger and Levin, 19841. For its 1986
forecasts, the bureau used a system of five interconnected economic
models to project growth in the labor force, the level of aggregate
economic activity, each industry's output of goods and services, and each
industry's demand for labor. The industry demand projections were based
on historical relationships between growth in GNP and growth in the
output of individual industries.7
In recent years the bureau has disclosed much of its methodology for
measuring and incorporating technological change within these projec-
tions, and further disclosure and discussion of these methods are highly
desirable. Technological change was incorporated into the BLS projec-
tions through assumptions about the rates of development and diffusion of
new technologies and their direct impacts on occupational structure and
input-output coefficients. BLS also allowed for changes in output de-
mand resulting from productivity increases and changes in production
processes within industries. The bureau was conservative in making
technology adjustments in these models. Nevertheless, hundreds of
adjustments were made in the most recent revision of the projections
(Hansen, 19841.
The 1995 employment projections issued by BLS forecast growth in
virtually all of its more than 350 occupations with at least 25,000 workers.
Some categories, however, were projected to decline in absolute terms as
a result of technological change. Information technologies affected a
number of the 11 occupations posting absolute declines in projected
employment as a result of technological change (Table 4-11. The declining
occupations fall into four groups: office workers involved primarily in
data-entry tasks; communications workers who are displaced by declines
in the service requirements of telecommunications equipment; truck and
tractor operators affected by increases in warehouse automation; and
'The moderate-growth scenario used by BLS as the basis for industrial and occupational
employment projections assumes strong productivity and investment growth, a declining
unemployment rate (6 percent in 1995), and a real annual rate of GNP growth of 2.9 percent
between 1984 and 1995; using those assumptions, the bureau forecast that employment in
the U.S. economy will increase by 16 million. For a detailed discussion of these assumptions
and those underlying the alternative low- and high-growth scenarios, see U.S. Bureau of
Labor Statistics (1986b).
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102 TECHNOLOG Y AND EMPLO YMENT
of product innovation and redesign (e.g., substituting microelectronics for
electromechanical components in office equipment) on skills are also
considerable.
Case Studies of Office Automation
Numerous case studies of office automation have analyzed the impact
of a single group of technologies information and computer technolo-
gies on skill requirements. A review of these studies suggests that the
impact of these technologies on job skill requirements has changed as the
technologies have developed, a phenomenon consistent with the discus-
sion in Chapter 2 of the skill-intensive characteristics of new technologies
in the early stages of their development. As a result of this characteristic
of technological development, successive studies of these technologies
have reached different conclusions.
Studies of office automation in the 1950s and 1960s (summarized in
Flynn, 1985) found that office and "back-office" (transactions processing,
recordkeeping, data entry, and other functions involving little or no
customer contact) automation created new employment opportunities for
skilled computer programmers, systems analysts, computer maintenance
engineers, and other administrative and managerial personnel. At the
same time, back-office automation eliminated low-skill clerical positions
but created positions for low-skill data-entry workers. Many of these
early case studies reported "job enlargement" for clerical positions as the
personnel occupying them became less specialized and absorbed new,
computer-related tasks. As computer technology developed, however,
the number of higher-skill opportunities for clericals appeared to decline.
Many case studies during the 1970s (see Baran, 1986) reported that
automation fragmented and standardized clerical work, requiring lower-
level and narrower skills.
The most recent set of case studies suggests that a new wave of
computer technology, supporting the movement of office automation out
of the back office and into desktop and distributed data processing, may
be reversing these tendencies toward reductions in skill requirements.
Baran (1986) reports that the introduction of minicomputers, personal
computers, and higher-level programming languages has restructured office
work. The insurance clerical worker of the future, for example, is likely to
have a computerized workstation. Because of increased desktop computing
power, this worker will be responsible for a wider range of tasks including
rating, underwriting, issuing new policies, and policy updating and renewal.
Continued advances in data-processing and office automation technologies
have also changed the skills required for many of the support personnel
employed in data-processing departments. Consistent with the argument that
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STUDIES OF THE IMPACT OF TECHNOLOGICAL CHANGE 103
skill requirements change over the life cycle of a technology, many of the
operating tasks assigned to engineers in the 1950s shifted to technicians in the
1960s; in the 1980s, they appear to be shifting to clerical employees (Flynn,
1985).
Like the literature and evidence on the employment impacts of tech-
nological change, the empirical evidence of technology's effects on skills
is too fragmentary and mixed to support confident predictions of aggre-
gate skill impacts. Despite this uncertainty, however, the evidence
suggests that the skill requirements for entry into future jobs will not be
radically upgraded from those of current jobs. Many of the computer-
based technologies examined by this panel are now being developed with
more powerful software and user-friendly interfaces, which should reduce
the device-specific skills needed to operate them. As more such "intelli-
gence" is embedded in hardware or software, users will require less
training for particular equipment. Consequently, the workplace of the
future will place a greater premium on a strong foundation in basic skills
for career advancement and for changing jobs but should not require
massive investments in computer literacy for all entrants or employees.
Even more than in the analysis of the employment impacts of techno-
logical change, the evidence on skill impacts has led us to stress the
considerable uncertainties that pervade the issue. In examining educa-
tional and other policy responses to the challenges of technological
change, it behooves policymakers and others to avoid planning based on
inflexible commitments to a single (and almost certainly flawed) vision of
the skill and vocational requirements of the workplace of the future.
Nonetheless, education and training that improve the basic and job-
related skills of American workers are important contributors to U.S.
competitiveness and living standards. Continued investment in the train-
ing of professional scientists and engineers to sustain the development
and adoption of new technologies is also critical.
THE EFFECTS OF TECHNOLOGICAL CHANGE
ON THE LEVEL OF EARNINGS
Technological change and its effects on earnings have long been topics
of debate among economists and other analysts. Poll data (Cambridge
Reports, Inc., 1986) suggest that a large segment of the U.S. public views
technological change as a force that may erode wages, leading (among
other things) to a polarized wage and income distribution. This section
reviews the evidence on the impact of technological change on the level
of wages and considers the relationship between technological change and
the distribution of earnings (i.e., salaries and wages) and income within
the United States.
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104 TECHNOLOGY AND EMPLO YMENT
20
18
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Hourly Output
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~ Hourly Compensation
O- 1 1 1 1 1 1 1
1950 1955 1960 1965 1970 1975 1980 1985
YEAR
FIGURE 4-1 Real output per hour and real employee compensation, 195~1985.
SOURCE: U.S. Bureau of Labor Statistics, Office of Productivity and Technology.
Developed by the bureau from U.S. Department of Commerce, Bureau of Economic
Analysis, national income and product account data.
Growth in Real Earnings During the
Postwar Period
A widely accepted measure of real earnings growth is average real
compensation (wages and salaries plus employee benefits) per hour in the
nonfarm business sector. Figure 4-1 plots trends in this quantity and in
labor productivity over time, revealing a close relationship between the
two.~° The share of labor in total output has remained fairly stable
throughout the postwar period in the U.S. economy, in contrast to its
behavior in Western European economies in which, according to Bruno
and Sachs (1985), this share fluctuates. Increases in U.S. real compensa-
tion therefore depend on growth in labor productivity; far from supporting
erosion in real earnings, technological change, by increasing labor pro-
ductivity, is associated with increases in them. The stagnation in U.S. real
'°Figure 4-1 plots real nonfarm output per hour and real compensation per hour. Both
series are deflated (converted into constant dollars) by the implicit nonfarm output
deflator.
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STUDIES OF THE IMPACT OF TECHNOLOGICAL CHANGE 105
earnings that has occurred since 1973 reflects lagging labor productivity
growth. Improvements in real earnings within this economy depend on
renewed productivity growth, which in turn requires more rapid genera-
tion and adoption of new technologies.
The Impact on Compensation of Worker Movement
Among Sectors
The growth rate of average compensation within the overall economy
can be broken down into a weighted average of the growth rates of
earnings within each sector and a composition erect, reflecting the
impact on average compensation of shifts in the shares of total employ-
ment accounted for by sectors with different levels of average earnings.
Costrell (1987) broke down growth in real hourly compensation into
compositional edects and changes in real compensation growth within
sectors (the 12 sectors of Table 3-7) and obtained striking results. The
effect on real compensation growth of changes in employment shares
was modest and, if anything, positive (approximately 1-2 percent) prior
to 1979. During 1979-1985, however, the impact on average compensa-
tion of changes in employment shares became negative and increased in
size (to more than 10 percent), consistent with the findings of Bluestone
and Harrison (1986) for 1979-1984. Yet real compensation growth within
sectors remained positive during 1979-1985, increasing by almost 7
percent. Costrell identified the decline in the share of durables manu-
facturing employment and growth in the share of services employment
during 1979-1985 as the major contributors to the negative compensa-
tion impact of intersectoral employment shifts. This finding is qualified,
however, by the small number of workers that have actually moved from
the manufacturing to the nonmanufacturing sector; absolute levels of
manufacturing employment have not fallen below the levels of the 1960s.
Although these estimates are based on aggregate data and represent
average compensation losses, they are broadly consistent with survey
data on earnings losses among displaced manufacturing workers
(Podgursky, 1987~. Relatively well-paid, unionized, blue-collar workers in
durables manufacturing have made disproportionate contributions to the
displaced worker population, as was noted in Chapter 3, and many (but
not all) of these workers have found new jobs outside of manufacturing
that pay substantially lower wages than their previous jobs.
"More than 40 percent of the displaced workers formerly employed in durables
manufacturing and more than 30 percent of those previously employed in nondurables
manufacturing found jobs in wholesale and retail trade or services, according to data from
the 1984 survey of displaced workers summarized in Podgursky (1987).
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106 TECHNOLOG Y AND EMPLO YMENT
This evidence suggests that recent structural change in the U.S.
economy that is, changes in the employment shares of different sec-
tors has contributed to lower earnings growth. Domestic technological
change, however, is not the primary factor affecting the displacement of
manufacturing workers. In addition, the role of technological change in
supporting productivity growth and competitiveness in many U.S. man-
ufacturing industries means that new technologies may aid in the stabili-
zation, rather than any erosion, of high-wage manufacturing employment.
We must also distinguish the impact on average earnings of movements of
workers among different industries from the impacts of changes in the
occupational structure of the economy. The potential reductions in
average U.S. wages caused by employment growth in lower-wage indus-
tries have thus far been largely offset by growth in employment in
higher-wage occupations. Nevertheless, the wage reductions associated
with movement of displaced workers from manufacturing (especially
those from durables manufacturing) to nonmanufacturing employment
contribute to the high social and individual costs of displacement.
TECHNOLOGICAL CHANGE AND THE DISTRIBUTION
OF EARNINGS AND INCOME
Trends in the distribution of income and earnings within the United
States recently have received considerable attention (Blackburn and
Bloom, 1985, 1986, 1987; Bluestone and Harrison, 1986; Harrison et al.,
1986; Henle and Ryscavage, 1980; Kuttner, 1983; Lawrence, 1984;
Levy, 1987; Levy and Michael, 1983, 1985; Medoff, 1984; Rosenthal,
1985~. Some analysts have attributed increased inequality in the distri-
bution of income and wages to the growth of service sector employment
and the development of "two-tiered" occupational structures within
high-technology and service industries, both of which are widely per-
ceived to result from technological change (Industrial Union Depart-
ment, 19841. This section briefly reviews the evidence concerning
changes in household incomes and earnings~3 distributions and dis-
cusses explanations for these distributional shifts. It is important to note
at the outset that the distribution of income may shift with no corre-
sponding change in the distribution of earnings as a result of changes in
household structure. Moreover, the distribution of annual earnings also
'~Household income is defined as all income received by a household, which in turn is
defined to be a housing unit occupied by related or unrelated individuals.
Yearnings are typically defined as employment-related wages and salaries, commissions,
and tips received by an individual. Both hourly and annual measures of earnings have been
used in analyses of the distribution of earnings.
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STUDIES OF THE IMPACT OF TECHNOLOGICAL CHANGE 107
may change with no corresponding shift in hourly earnings as a result of
changes in the shares of full- and part-time employment within the work
force.
The Distribution of Earnings and Income
Nearly all of the analyses to date (most of which examine data from
the CPS compiled by BLS) agree that household income inequality-
however it is measured has increased during the past two decades.
This tendency reverses a previous trend of increasing equality, which
appears to have peaked in the late 1960s. The current level of inequality
in the U.S. household income distribution is slightly less pronounced
than in 1947 (Levy and Michael, 19831.
Researchers have used several measures of household income to reach
these conclusions. Blackburn and Bloom (1987) analyzed changes in the
distribution of total household income (including income derived from
sources not related to the occupations of household members-e.g.,
interest income) and the distribution of household earnings during
1967-1984.~4 Analyzing changes in the number of households in each
quintile of this distribution, Blackburn and Bloom found that the distri-
butions of both household income and household earnings exhibited
increasing inequality during this period. In the case of total household
income, increased inequality reflected increases in the number of house-
holds classified as "upper middle" or "upper" class, at the expense of
middle class households. The distribution of household earnings dis-
played a similar trend while also exhibiting growth in the number of
households whose total earnings placed them in the "lower" class. Levy
and Michael (1983) adjusted household income for taxes paid and food
stamps received and found increasing inequality in the distribution of this
category of household income. Thurow (1987) used data from the U.S.
Bureau of the Census to trace declines during 1969-1985 in the share of
total income received by the poorest 60 percent of the population. During
this period, the income share of the top 20 percent of all U.S. families
increased.
'4Blackburn and Bloom divided the distribution into five categories, or quintiles. "Lower
class" households received incomes of less than or equal to 60 percent of the median
income; "lower middle class" households received incomes greater than 60 percent but less
than or equal to 100 percent of the median income. "Middle class" households received
incomes greater than 100 percent but less than or equal to 160 percent of the median income;
"upper middle class" households received incomes greater than 160 percent of the median
income but less than or equal to 225 percent of the median; and "upper class" households
received incomes greater than 225 percent of the median income.
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108 TECHNOLOG Y AND EMPLO YMENT
The evidence on trends toward polarization in the distribution of
earnings in the U.S. economy is much weaker than it is for the distribu-
tion of income during the past two decades. Blackburn and Bloom (1986)
found "no evidence of any trend in the dispersion [i.e., polarization] of
annual individual earnings over time" (p. 7) during 1967-1983, based on
analyses of data for the "principal earners" in each household. Kosters
and Ross (1987) found that the dispersion of average hourly earnings (a
measure of the inequality of the distribution of earnings i.e., greater
dispersion implies a more unequal distribution) for full-time workers has
declined since 1973.
Other researchers, however, have detected some tendency toward
increased inequality in the earnings distribution. Henle and Ryscavage
(1980) detected a modest tendency toward increased inequality in the
annual earnings of all workers during 1958-1977, although this polarizing
trend peaked during 1968-1973, well before technological or other forms
of employment displacement were a major concern.~5 Moreover, Henle
and Ryscavage found growing earnings inequality only among part-time
workers, a group that largely excludes the "principal earners" analyzed
by Blackburn and Bloom. (Interestingly, the distribution of the earnings
of women does not exhibit increasing inequality during or after this
period.) Blackburn and Bloom (1987), however, suggest that during
1967-1984, the inequality of the annual earnings distribution may have
increased among both full- and part-time male workers (although the
inequality of the earnings distribution among women declined during this
period). Tilly et al. (1987) also found increases in the inequality of annual
earnings among male workers during 1979-1984, although their results are
influenced by declines in labor force participation among older male
workers and by the poor performance of the economy during this period.
As in the case of Bluestone and Harrison (1986), the magnitude of the
increases in earnings in equality found by Tilly et al. (1987) therefore may
be sensitive to the choice of years for analysis. Without additional data
and analysis, it is difficult to determine the significance or durability of
any trend toward greater inequality in the earnings distribution.
Explaining the Trends
The trends in the distribution of household income reflect changes in
the structure of the American family and increased participation by
'5The results of the Henie-Ryscavage analysis conflict with the findings of Harrison et al.
(1986), who detected no trend toward increased earnings inequality prior to the late 1970s.
Harrison et al. found increasing inequality ~ in the earnings distribution beginning in the
late 1970s.
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STUDIES OF THE IMPACT OF TECHNOLOGICAL CHANGE 109
women in the labor force, all of which affect household income rather
than individual wages. The number of single-parent, low-income house-
holds has grown since the 1970s, fattening the lower "tail" of the family
income distribution. The number of two-earner households also has
grown, which has led to some expansion in the upper reaches of the
income distribution. According to Levy and Michael (1983), changes in
federal tax and income support policies during the early 1980s also
increased household income inequality. Reductions in transfer payment
programs benefiting low-income households, combined with large tax
reductions in the uppermost income brackets, increased the polarization
of the distribution of after-tax income.
What factors might account for any observed increases in the disper-
sion of earnings? Among the least likely causes are movements of
workers from manufacturing into service sector occupations or a change
in the structure of the work force within high-technology industry. The
current share of manufacturing within total U.S. employment is suffi-
ciently small, and the size of the middle-income share of the manufactur-
ing work force sufficiently resembles that of nonmanufacturing, that
movements of labor out of manufacturing have little effect on recent
earnings trends (Lawrence, 1984~.'7 Moreover, the characteristic form of
structural change within this economy does not involve a large net
outflow of labor from manufacturing into nonmanufacturing employ-
ment; rather, it reflects more rapid employment growth in the
nonmanufacturing sector than in manufacturing industry. During the
past seven decades, employment has been growing in industries in
which average wages currently are lower than in manufacturing. At the
same time, however, the occupational structure of the U.S. economy
has shifted in an opposite direction, with faster growth in higher-skill,
higher-wage occupations (Leon, 1982; Singelmann and Tienda, 19851.
Partly for this reason the gap in average wages between manufacturing
and rapidly growing nonmanufacturing sectors such as business services
(which include computer services and consulting) has been shrinking
during the past decade (Howe, 19861. Many declining manufacturing
industries for example, textiles, apparel, and leather products now
pay wages that are low in comparison with those paid by much of the
services sector.
There is little evidence to suggest that newer high-technology manu-
facturing industries have occupational structures that support increases
in the inequality of the earnings distribution. Data from the 1980 census
'7Blackburn and Bloom (1987) concluded that the impact on the earnings distribution of
shifts in the sectoral distribution of employment during 1967-1984 was small.
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110 TECHNOLOG Y AND EMPLO YMENT
(Lawrence, 1984) suggest that high-technology industries "have smaller
shares of lower-class jobs than manufacturing in general has, and almost
all of them have larger shares of middle-class jobs" (p. 41. Assertions
that technological change will produce a "two-tiered" work force,
reducing the skills (and earnings) of a large share of jobs while producing
a much smaller number of highly paid jobs for scientists, managers, and
engineers thus receive little support from either this evidence on
occupational structure in high-technology industries or the evidence on
skill requirements discussed above.
Demographic trends and slow economic growth, rather than techno-
logical change, appear to be the primary causes of any tendency toward
earnings polarization. Dooley and Gottschalk (1984) found that in-
creases in the inequality of the distribution of weekly and annual
earnings for males were attributable to the "baby boom and bust" since
World War II, which brought large numbers of workers into the labor
force during the late 1970s and early 1980s. This surge in the labor
supply, along with low productivity growth and continued growth in the
real wages of established workers covered by cost-of-living clauses in
labor contracts, resulted in entry-level wages that were lower and that
grew more slowly than the wages of older workers. Slow growth in
earnings, which contributes to such increases in earnings inequality as
are detectable, appears to be concentrated among workers between the
ages of 25 and 34 (Lawrence, 1984~. Because of low productivity growth,
these new entrants have not experienced the rapid increases in earnings
that had characterized previous cohorts.
The lower end of the earnings distribution thus appears to have
expanded as a result of demographic and productivity trends rather than
because of technological or structural changes (Levy and Michael,
1985~. BLS projections of future employment growth do not suggest that
the jobs of the future will produce additional polarization in earnings.
Indeed, Rosenthal (1985) maintains that these projections "show an
increasing proportion of employment in higher than average earnings
occupations and a declining proportion in occupations with lower than
average earnings, rather than a trend toward bipolarization" (p. 61.
Completion of the absorption of the large baby boom cohort into the
labor force should reduce earnings inequality somewhat, whereas the
expansion of income transfer and entitlement programs could offset
trends toward increased inequality in the distribution of income. A
resumption of productivity growth also appears to be a major component
of the solution to the problem of earnings dispersion; because technolog-
ical change supports such growth, it may help to reverse any trends
toward the polarization of earnings in the U.S. economy.
The evidence suggests that reports of a vanishing middle class due to
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STUDIES OF THE IMPACT OF TECHNOLOGICAL CHANGE 111
technological change are exaggerated. The existing and very disturbing
tendencies toward increased inequality in the distribution of income
reflect changes in government policy, family structure, and labor force
participation rather than the effects of technological change. Earnings,
rather than household incomes, is the variable that should be most
responsive to technologically induced changes in employment opportuni-
ties; but the hypothesis that the distribution of earnings has become more
unequal receives limited support from the data. The data on the earnings
distribution (e.g., Henle and Ryscavage, 1980) also suggest that much of
the growth in earnings inequality predates the recent period of concern
over technological and structural change in the U.S. economy. Trends in
the distribution of earnings also appear to be influenced more by demo-
graphic than by technological factors, as well as by slow growth in
productivity and in the overall economy.
There is certainly cause for concern in the apparent inability of the
young workers of the 1980s to experience the earnings growth and
employment expansion that was the lot of their predecessors in the
l950s and 1960s. To ascribe this circumstance solely to the effects of
technological change, however, would be incorrect. The panel believes
that the answer to this problem is to be found in policies that will support
a resumption of productivity and output growth at the levels of the l950s
and 1960s. We further believe that the increased use of new technolo-
gies, in conjunction with policies to facilitate adjustment to them, is
indispensable to the achievement of this goal.
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Representative terms from entire chapter:
productivity growth
