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2002-23

August 9, 2002

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Technical Change and the Dispersion of Wages
Bharat Trehan
What the data show
Technology as first cause
Labor supply as first cause
A tentative assessment
References
In the last 25 years, the wage gap in the U.S. between highly skilled and less skilled workers has
widened noticeably. For example, in 1975 the gap in average annual earnings between high school
graduates and non-graduates was 26%; by 1999, the gap was 52%. The gap widens even more when
comparing workers with advanced degrees and those with relatively little education. This rise in
inequality has led to considerable debate about the underlying causes. This Letter reviews some of the
evidence on this issue and discusses some recent explanations relating these phenomena to another
development that has been much in the news recently, namely, an increase in the pace of technical
progress.
What the data show
Figure 1 shows relative annual earnings from 1975
to 1999 for U.S. workers divided according to five
categories of educational levels; educational levels
commonly proxy for skill levels, which are hard to
measure directly. (Note that these data are from
the Census Bureau, which redefined the groups in
1991 to focus on degrees earned rather than years
in school; this definitional change does not alter the
basic message of the data, but it does alter the
relative size of each group, as will be discussed
below.) To focus more closely on the changes in the
dispersion of earnings over time, these data have

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Federal Reserve Bank San Francisco | Technical Change and the Dispersion of Wages |

been normalized to equal 100 in 1975. While wages
in all five categories rose over the sample, the
wages of skilled workers rose noticeably more than
those of less skilled workers. (These results are
confirmed by a detailed analysis of the data; see,
for instance, the influential study by Juhn, Murphy,
and Pierce 1993.)
The distribution of wages depends on the supply of
different kinds of workers relative to the demand
for them. For instance, the relative wages of
workers who did not complete high school could
have declined if the number of people in this
category had risen relative to the others. Figure 2
presents evidence against this explanation; it plots
the number of workers in the same five categories
and again shows data normalized to 100 in 1975.
The number of workers who did not finish high
school actually fell by about a third over this period,
while the number of workers with college degrees
grew to more than 2½ times its original size, and
the number of workers with advanced degrees
doubled. (The figure suggests that these ratios
would have been different in the absence of the
change in the Census Bureau methodology in 1991;
for our purposes the most important characteristic
of the data is that the series moved in the same direction both before and after the change in
methodology.)
The fact that skilled workers’ wages increased at the same time that their number increased suggests
that an increase in demand was the dominant force behind the rising dispersion of wages in the data. Of
course, the supply of skilled labor could have risen independently of any increase in demand; however,
the wage data imply that the demand for skilled labor has gone up by more than whatever increase in
supply might have taken place. The remainder of this Letter discusses research that assigns a prominent
role to technical change when accounting for this increase in demand. Since the amount of research on
this issue is too large to be addressed in this Letter, I will focus on some recent work and try to provide
a flavor of the rest.
Technology as first cause

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Federal Reserve Bank San Francisco | Technical Change and the Dispersion of Wages |

Several studies have developed models and documented evidence to show that the observed increase in
wage dispersion has been driven by technical change. Griliches (1969) presented one of the key
concepts for studying these issues. He assumed the existence of two kinds of labor, skilled and
unskilled, and posited that capital and skilled labor were “complements.” While this term has a precise
technical meaning, for our purposes the key implication is that an increase in the capital stock raises the
productivity of a skilled worker more than that of an unskilled worker. Given this assumption, an
increase in the stock of capital raises the demand for skilled workers relative to unskilled workers and so
pushes up the wages of the former relative to the latter.
Based on this work, Krusell, et al. (2000) develop a model to carry out a quantitative analysis of the skill
premium (which is defined as the average wage of skilled workers relative to that of unskilled workers).
They argue that steady improvement in the quality of capital equipment over their 1963-1992 sample
has led to a secular decline in the price of this equipment relative to other goods in the economy.
(Consider, for example, how the price of computers has fallen relative to the price of haircuts.) Since
capital goods and skilled labor are complements, this has pushed up the demand for skilled labor and,
hence, pushed up the skill premium. Further, there is evidence that the pace of decline of the relative
price of capital has picked up since the 1970s, which means that the skill premium has been pushed up
even further.
After defining skilled labor as workers who have at least 16 years of education, they find that the capitalskill complementarity effect raised the skill premium by roughly 60% over their sample. The contribution
of this component was particularly marked during the 1960s, when it raised the skill premium by an
average of 2.5% per year, and after 1980, when it raised the premium by about 2.1% per year. They
also show that in the absence of the capital-skill complementarity effect, the increase in the relative
supply of skilled labor observed over the 1963-1992 period would have pushed the skill premium down
by about 40%.
Greenwood and Yorukoglu (1997) emphasize a somewhat different channel through which technical
progress affects wage dispersion. According to their hypothesis, skilled workers are able to learn how to
work with new technologies more easily than unskilled workers. Therefore, periods of rapid technical
progress lead to an increase in the demand for skilled workers, which pushes up the skill premium. Note
that this hypothesis implies that the rise in the skill premium that accompanies the introduction of a new
technology will be temporary; as time goes by, relatively low skilled workers will learn how to work with
the new technologies as well, and the skill premium will dissipate. Thus, wage dispersion should fall
back over time.
In their model, each vintage of capital embeds the latest technology. An increase in the pace of technical
progress raises investment in capital goods. Because skilled workers are needed to operate the new
plants, every 1% increase in the capital-equipment ratio pushes up the ratio of skilled to unskilled
employment by 2.5%. As the plant ages, it is no longer profitable to hire as many skilled workers.
Greenwood and Yorukoglu find that an increase of one year in the age of the plant reduces the share of
skilled labor in the total wage bill by roughly 0.6%.
Labor supply as first cause
The research we have discussed so far explains the increase in the dispersion of wages and in the
number of skilled workers as a response to a change in technology. Another strand of the literature
points out that innovation responds to economic incentives and presents models where changes in the
supply of labor trigger changes in technology and relative wages.
According to Kiley (1999), an economy with a larger share of skilled labor offers greater incentives for
developing skill-biased technologies than an economy with a smaller share. Entrepreneurs respond to
this larger market by developing technologies that can take advantage of this skilled labor pool. The

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Federal Reserve Bank San Francisco | Technical Change and the Dispersion of Wages |

invention of these new technologies pushes up the demand for skilled labor and ends up raising the
relative wages of skilled labor. Kiley also shows that an increase in the supply of skilled workers leads to
the creation of more skill-biased technologies and raises the relative wages of skilled workers in the long
run. The pattern of technical change since the mid-1970s and the rising dispersion of wages in the U.S.
is then explained as a response to an increase in the relative supply of labor since the 1970s, “…at least
in part exogenously due to government support for higher education.” (p. 720)
Acemoglu (2002) agrees with Kiley, arguing that one can understand technical change over a long span
of time by recognizing that the development and use of technology respond to profit incentives. In one
particularly interesting example, he points out that there was a large increase in the supply of unskilled
labor in English cities during the late nineteenth century. Among the factors responsible for this change
were rapid population growth in England, a large influx of labor from Ireland, as well as a substantial
release of labor from agriculture due to various factors. Acemoglu argues that this led to a major
increase in skill-replacing technologies, “…most notably the factory system replacing tasks previously
performed by skilled artisans” (p. 42). He also cites some historians who have pointed out that the
absence of cheap labor may have hampered the adoption of the factory system in the U.S. during this
period. The twentieth century represents a sharp contrast to the nineteenth, as the supply of skilled
labor has gone up rapidly, and this has led to an increase in skill-biased technical change. Taken
together, these two cases show that there is no reason to believe that technical change tends to favor
either highly skilled or low-skilled labor; instead, the kind of change that takes place depends upon the
opportunities facing innovators.
A tentative assessment
While economists have pointed to other factors that may have contributed to the increased dispersion of
wages we have seen over this period, available evidence does suggest that an increase in the demand
for skilled labor that is related to recent technical change has played a significant role. It is harder to
determine how much is explained by theories that emphasize an exogenous increase in labor supply as
a first cause; while these theories are appealing, there is little evidence yet on their quantitative
importance. Finally, from the perspective of the debate on wage dispersion, it will be interesting to
observe how the distribution of wages changes if, and when, the recent burst in innovation tapers off.
Bharat Trehan
Research Advisor
References
[URLs accessed July 2002.]
Acemoglu, Daron. 2002. “Technical Change, Inequality, and the Labor Market.” Journal of Economic
Literature 60 (March) pp. 7-72.
Census Bureau .
http://www.census.gov/population/socdemo/education/tableA-3.txt
Greenwood, Jeremy, and Mehmet Yorukoglu. 1997. “1974.” Carnegie-Rochester Series on Public Policy
46, pp. 49-95.
Griliches, Zvi. 1969. “Capital-Skill Complementarity.” Review of Economics and Statistics 51, pp. 465468.
Juhn, Chinhui, Kevin M. Murphy, and Brooks Pierce. 1993. “Wage Inequality and the Rise in Returns to
Skill.” The Journal of Political Economy 101 (June) pp. 410-442.
Kiley, Michael T. 1999. “The Supply of Skilled Labor and Skill-Biased Technological Progress.” The

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Federal Reserve Bank San Francisco | Technical Change and the Dispersion of Wages |

Economic Journal 109 (October) pp. 708-724.
Krusell, Per, Lee Ohanian, Jose-Victor Rios-Rull, and Giovanni L. Violante. 2000. “Capital-Skill
Complementarity and Inequality: A Macroeconomic Analysis.” Econometrica 68 (September) pp. 10291053.
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