Why Has Income Inequality Been Rising Since the 1970’s?

Why Has Income Inequality Been Rising Since the 1970’s?
Due in NetTutor through the link in Blackboard (learn.wsu.edu) by February
18, by 11:50 pm (PST)
Below are two competing views (Proposition #1 and Proposition #2) on why income inequality
has been rising (even among the lower 99%) in the United States since the 1970’s.
Reading: “Skills, education, and the rise of earnings inequality among the “other 99 percent,”
David H. Autor, Science 23 May 2014: 843-851. [DOI:10.1126/science.1251868] (see below)
Proposition #1:
“More people are falling behind today because they’re lazy. In the U.S. anyone willing to work can
earn a decent living. The income distribution is the same as the effort distribution. People who work
hard earn a good living. Lazy people stay poor. The income distribution has been skewing because of
a growing culture of dependency. It used to be shameful to accept handouts from the government, but
now it’s perfectly acceptable. So more people opt out of the labor force and sit around collecting
handouts from the rest of us. Of course their incomes are going to be lower than those in the top
Proposition #2:
“The incomes of the rich and poor have been growing farther apart due to purposeful policy
decisions that have favored the rich at the expense of the poor. Starting with Ronald Reagan’s
financial deregulation, and continuing with successive Republican attacks on New Deal and Great
Society social programs to finance tax cuts for their Wall Street cronies, government policy in this
country has systematically channeled the rewards of our immensely productive economy towards the
rich and away from the poor. America needs to open the gateway to prosperity for all through fair tax
policies, decent minimum wages, better public schools, aid to low-income college students, and a
universal health care system.”
EconS 101 WA 1
Page 2 of 3
Assess the degree to which each of those propositions is actually consistent with David H.
Autor’s well-researched explanation of the same phenomenon. That is, for each of the
propositions tell me whether or not Autor would agree that the underlying factor described in
the proposition is the major cause of the pattern of income inequality since the 1970’s. (2
1) Begin with a topic sentence that concisely states your judgment about how consistent the two
propositions are with Autor’s analysis, and complete that paragraph with a summary of
Autor’s explanation. Be sure to mention some of the factors Autor identifies as having
contributed to an increase in the demand for highly-educated workers and a decrease in the
demand for less-educated workers.
2) In your second paragraph, discuss the degree to which the two propositions are consistent
with Autor’s analysis. Is one more consistent than the other?
EconS 101 WA 1
Page 3 of 3
Grading Rubric
Please include your name, instructor’s name (Dr. Prera), course and section number (i.e. EconS
101.01 [MWF 9:10-10 am] or 101.03 [TTh 10:35-11:50 am]), and writing assignment
(Assignment 1) on the top of your assignment.
This is the first of four writing assignments. After receiving feedback, you may re-submit the
essay to NetTutor for another try – but you only get one second chance on each writing
assignment. If you don’t get an acceptable score, even after revising and resubmitting this
assignment, you can still rescue your writing assignment average by doing well on the next three
assignments. I will take the three highest writing assignment scores to compute your writing
assignment average.
Criteria Meets Expectations Needs Improvement
Ideas are well-organized.
Transition sentences effectively
connect one idea to the next. The
essay is free of typos and
grammatical errors.
The writing is difficult to
follow and/ or poorly
Transition sentences are
absent or ineffective.
Typos and/ or grammatical
errors distract the reader.
Economic analysis
The topic sentence clearly states
the student’s judgment about the
degree to which Propositions #1
and #2 are consistent with
Autor’s study.
The topic sentence does not
state the student’s judgment
about the degree to which
Propositions #1 and #2 are
consistent with Autor’s study.
Correctly identifies the major
cause of rising inequality in
Autor’s analysis.
Autor’s argument is
misrepresented, and/or the
summary is too skimpy.
Explicitly state the degree to
which the two propositions are
consistent with Autor’s research,
and supports his or her claims
with examples from the reading.
The question of the degree to
which the two propositions
are consistent with Autor’s
research is not addressed
and/or, is not supported with
DOI: 10.1126/science.1251868
Science 344, 843 (2014);
David H. Autor
”other 99 percent”
Skills, education, and the rise of earnings inequality among the
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of rising or shrinking inequality. Which one
dominates depends on the institutions and policies
that societies choose to adopt.
1. S. Kuznets, Shares of Upper Income Groups in Income and
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Perspect. 27, 3–21 (2013).
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Personal Wealth from a Global Perspective (Oxford Univ. Press,
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Wealth Inequality Over the Path of Development (Lund
University, Sweden, 2009)
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22. R. Goldsmith, Comparative National Balance Sheets: A Study of
Twenty Countries, 1688-1978 (Univ. of Chicago Press, Chicago,
IL, 1985)
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Supplementary Text
Figs. S1 and S2
References (31, 32)
Skills, education, and the rise of
earnings inequality among
the “other 99 percent”
David H. Autor
The singular focus of public debate on the “top 1 percent” of households overlooks the
component of earnings inequality that is arguably most consequential for the “other
99 percent” of citizens: the dramatic growth in the wage premium associated with higher
education and cognitive ability. This Review documents the central role of both the supply
and demand for skills in shaping inequality, discusses why skill demands have persistently
risen in industrialized countries, and considers the economic value of inequality alongside
its potential social costs. I conclude by highlighting the constructive role for public policy in
fostering skills formation and preserving economic mobility.
Public debate has recently focused on a
subject that economists have been analyzing
for at least two decades: the steep,
persistent rise of earnings inequality in
the U.S. labor market and in developed
countries more broadly. Much popular discussion
of inequality concerns the “top 1 percent,”
referring to the increasing share of national income
accruing to the top percentile of households.
Although this phenomenon is undeniably
important, an exclusive focus on the concentration
of top incomes ignores the component
of rising inequality that is arguably even more
consequential for the “other 99 percent” of
citizens: the dramatic growth in the wage premium
associated with higher education and,
more broadly, cognitive ability. This paper considers
the role of the rising skill premium in
the evolution of earnings inequality.
There are three reasons to focus a discussion
of rising inequality on the economic payoff
to skills and education. First, the earnings
premium for education has risen across a large
number of advanced countries in recent decades,
and this rise contributes substantially to
the net growth of earnings inequality. In the
United States, for example, about two-thirds
of the overall rise of earnings dispersion between
1980 and 2005 is proximately accounted
for by the increased premium associated with
schooling in general and postsecondary education
in particular (1, 2). Second, despite a
lack of consensus among economists regarding
the primary causes of the rise of very top
incomes (3–6), an influential literature finds
that the interplay between the supply and
demand for skills provides substantial insight
into why the skill premium has risen and fallen
over time—and, specifically, why the earnings
gap between college and high school graduates
has more than doubled in the United States over
the past three decades. A third reason for focusing
on the skill premium is that it offers broad
insight into the evolution of inequality within a
market economy, highlighting the social value of
inequality alongside its potential social costs and
illuminating the constructive role for public policy
in maximizing the benefits and minimizing the
costs of inequality.
The rising skill premium is not, of course, the
sole cause of growing inequality. The decadeslong
decline in the real value of the U.S. minimum
wage (7), the sharp drops in non-college
employment opportunities in production, clerical,
and administrative support positions stemming
from automation, the steep rise in international
competition from the developing world,
the secularly declining membership and bargaining
power of U.S. labor unions, and the
successive enactment of multiple reductions in
top federal marginal tax rates, have all served to
magnify inequality and erode real wages among
less educated workers. As I discuss below, the
foremost concern raised by these multiple forces
is not their impact on inequality per se, but
rather their adverse effect on the real earnings
and employment of less educated workers.
I begin by documenting the centrality of the
rising skill premium to the overall growth of
earnings inequality. I next consider why skills
are heavily rewarded in advanced economies
and why the demand for them has risen over
time. I then demonstrate the substantial explanatory
power of a simple framework that
embeds both the demand and supply for skills
in interpreting the evolution of the inequality
over five decades. The final section considers
the productive role that inequality plays in a
market economy and the potential risks attending
very high and rising inequality; evidence on
whether those risks have been realized; and
the role of policy and governance in encouraging
skills formation, fostering opportunity,
Department of Economics and National Bureau of Economic
Research, Massachusetts Institute of Technology, 40 Ames
Street, E17-216, Cambridge, MA 02142, USA. E-mail: dautor@
SCIENCE sciencemag.org 23 MAY 2014 • VOL 344 ISSUE 6186 843
and countering the possibility that extremes of
inequality erode economic mobility and reduce
economic dynamism.
The Critical Role of Skills in the
Labor Market
There is no denying the extraordinary rise in
the incomes of the top 1% of American households
over the past three decades. Between
1979 and 2012, the share of all household income
accruing to the top percentile of U.S.
households rose from 10.0% to 22.5% (8, 9). To
get a sense of how much money that is, consider
the conceptual experiment of redistributing
the gains of the top 1% between 1979 and
2012 to the bottom 99% of households (10).
Howmuchwould this redistribution raise household
incomes of the bottom 99%? The answer
is $7107 per household—a substantial gain, equal
to 14% of the income of the median U.S. household
in 2012. (I focus on the median because it
reflects the earnings of the typical worker and
thus excludes the earnings of the top 1%.)
Now consider a different dimension of inequality:
the earnings gap between U.S. workers
with a 4-year college degree and those with
only a high school diploma (11). Economists frequently
use this college/high school earnings
gap as a summary measure of the “return to
skill”—that is, the gain in earnings a worker
can expect to receive from investing in a college
education. As illustrated in Fig. 1, the earnings
gap between the median college-educated
and median high school–educated among U.S.
males working full-time in year-round jobs was
$17,411 in 1979, measured in constant 2012 dollars.
Thirty-three years later, in 2012, this gap
had risen to $34,969, almost exactly double its
1979 level. Also seen is a comparable trend among
U.S. female workers, with the full-time, fullyear
college/high school median earnings gap
nearly doubling from $12,887 to $23,280 between
1979 and 2012. As Fig. 1 underscores, the
economic payoff to college education rose steadily
throughout the 1980s and 1990s and was
barely affected by the Great Recession starting
in 2007.
Because the earnings calculations in Fig. 1 reflect
individual incomes while the top 1% calculations
reflect household incomes, the two
calculations are not directly comparable. To
put the numbers on the same footing, consider
the earnings gap between a college-educated
two-earner husband-wife family and a high school–
educated two-earner husband-wife family, which
rose by $27,951 between 1979 and 2012 (from
$30,298 to $58,249). This increase in the earnings
gap between the typical college-educated
and high school–educated household earnings
levels is four times as large as the redistribution
that has notionally occurred from
the bottom 99% to the top 1% of households.
What this simple calculation suggests is that
the growth of skill differentials among the “other
99 percent” is arguably even more consequential
than the rise of the 1% for the welfare of
most citizens.
The median earnings comparisons in Fig. 1 also
convey a key feature of rising inequality that
cannot be inferred from trends in top incomes:
Wage inequality has risen throughout the earnings
distribution, not merely at the top percentiles.
Figure S1 documents this pattern by plotting,
for 12 Organization for Economic Cooperation
and Development (OECD) member countries over
three decades (1980 to 2011), the change in the
ratio of full-time earnings of males at the 90th
percentile relative to males at the 10th percentile
of the wage distribution. Although the 90/10
earnings ratio differed greatly across countries
at the earliest date of the sample—from a low
of 2.0 in Sweden to a high of 3.6 in the United
States—this earnings ratio increased substantially
in all but one of them (France) over the
next 30 years, growing by at least 25 percentage
points in 10 countries, by at least 50 percentage
points in 8 countries, and by more than 100 percentage
points in three countries (New Zealand,
the United Kingdom, and the United States).
How much does the rising education premium
contribute to the increase of earnings inequality?
Although data limitations make it difficult to
answer this question for most countries, we do
know the answer for the United States. Goldin
and Katz (1) found that the increase in the education
wage premium explains about 60 to 70%
of the rise in the dispersion of U.S. wages between
1980 and 2005 and, similarly, Lemieux (12)
calculated that higher returns to postsecondary
education can account for 55% of the rise in
male hourly wage variance from 1973–1975 to
2003–2005. Firpo et al. (13) found that rising
returns to education can explain just over 95% of
the rise of the U.S.male 90/10 earnings ratio between
1984 and 2004. That is, holding the expanding
education premium constant over this
period, there would have been essentially no increase
in the relative wages of the 90th-percentile
worker versus the 10th-percentile worker.
I have so far used the terms education and
skill interchangeably.What evidence do we have
that it is skills that are rewarded per se, rather
than simply educational credentials? The Program
for the International Assessment of Adult
Competencies (PIAAC) provides a compelling
data source for gauging the importance of
skills in wage determination. The PIAAC is an
internationally harmonized test of adult cognitive
and workplace skills (literacy, numeracy,
and problem-solving) that was administered
by the OECD to large, representative samples
of adults in 22 countries between 2011 and
2013 (14). Figure 2, sourced from (15), plots the
relationship between adults’ earnings and their
PIAAC numeracy scores across these 22 countries.
The length of each bar reflects the average
percentage earnings differential between
full-time workers ages 35 to 54 who differ by
one standard deviation in the PIAAC score.
The whiskers on each bar provide the 95%
confidence intervals for the estimates.
College/high school median annual earnings gap, 1979–2012
In constant 2012 dollars
70,000 dollars
1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012
Household gap
$30,298 to $58,249
Male gap
$17,411 to $34,969
Female gap
$12,887 to $23,280
Fig. 1. College/high school median annual earnings gap, 1979–2012. Figure is constructed using
Census Bureau P-60 (1979–1991) and P-25 (1992–2012) tabulations of median earnings of full-time,
full-year workers by educational level and converted to constant 2012 dollars (to account for
inflation) using the CPI-U-RS price series. Prior to 1992, college-educated workers are defined as
those with 16 or more years of completed schooling, and high school–educated workers are those
with exactly 12 years of completed schooling. After 1991, college-educated workers are those who
report completing at least 4 years of college, and high school–educated workers are those who
report having completed a high school diploma or GED credential.
844 23 MAY 2014 • VOL 344 ISSUE 6186 sciencemag.org SCIENCE
This figure conveys three points. First, cognitive
skills are substantially rewarded in the labor
market across all 22 economies. The average
wage premium corresponding to one “unit” (i.e.,
one standard deviation) increase in measured
cognitive skills is 18%. In addition, cognitive earnings
premiums differ substantially across countries.
The premium is below 13% in Sweden,
the Czech Republic, and Norway. It is above
20% in six countries. The United States stands
out as having the highest measured return to
skill, with a premium of 28% per unit increment
to cognitive ability. Concretely, comparing two
U.S. workers who are one standard deviation
above and one standard deviation below the
population average of cognitive ability, we would
expect their full-time weekly earnings to differ
by 50 to 60%. Notably, the high return to
cognitive ability in the United States does not
follow automatically from high levels of U.S.
earnings inequality. If U.S. wages were determined
mainly by luck, beauty, or family connections,
we would expect little connection
between workers’ cognitive ability and their labor
market rewards (16). Figure 2 demonstrates
that this is not the case.
Of course, these data do not explain why
the skill premium has risen over time, nor
why the United States has a higher skill premium
than so many other advanced nations.
The next section considers the supply and demand
for skill in the labor market—specifically, why
they fluctuate over time and how their interaction
helps to determine the skill premium. I
focus on the United States in this section to allow
a deeper exploration of the data.
Education and Inequality
Workers’ earnings in a market economy depend
fundamentally (some economists would
say entirely) on their productivity—that is, the
value they produce through their labor. And in
turn, workers’ productivity depends on two factors.
One is their capabilities, concretely, the
tasks they can accomplish (i.e., their skills). A
second is their scarcity: The fewer workers that
are available to accomplish a task, and the more
employers need that task accomplished, the
higher is workers’ economic value in that
task. In conventional terms, the skill premium
depends uponwhat skills employers require (skill
demand) and what skills workers have acquired
(skill supply). To interpret the evolution of this
premium, we need to account for both forces.
Skill Demands: The Long View
A technologically advanced economy requires
a literate, numerate, and technically and scientifically
trained workforce to develop ideas,manage
complex organizations, deliver healthcare
services, provide financing and insurance, administer
government services, and operate critical
infrastructure. This was not always the case. In
1900, 4 in 10 U.S. jobs were in agriculture, 11%
of the population was illiterate, a substantial
fraction of economic activity required hard physical
labor, and workers’ strength and physical
stamina were key job skills (17, 18). Few citizens
would have predicted at the time that a century
later, health care, finance, information technology,
consumer electronics, hospitality, leisure,
and entertainment would employ farmoreworkers
than agriculture—which employed only 2%
of U.S. workers in 2010. As physical labor has
given way to cognitive labor, the labor market’s
demand for formal analytical skills, written communications,
and specific technical knowledge—
what economists often loosely term cognitive
skills—has risen spectacularly.
The central determinant of the supply of
skills available to an advanced economy is its
education system. In 1900, the typical young,
native-born American had only a common school
education, about the equivalent of six to eight
grades (19). By the late 19th century, however,
many Americans recognized that farm employment
was declining, industry was rising, and
their children would need additional education
to earn a living. Over the first four decades of the
20th century, the United States became the first
nation in the world to deliver universal high
school education to its citizens. Tellingly, the high
school movement was led by the farm states.
As the high school movement reached its
conclusion, postsecondary education became
increasingly indispensable to the growing occupations
of medicine, law, engineering, science,
and management. In 1940, only 6% of
Americans had completed a 4-year college
degree. From the end of the Second World
War to the early 1980s, however, the ranks of
college-educated workers rose robustly and
steadily, with each cohort of workers entering
the labor market boasting a proportionately
higher rate of college education than
the cohort that preceded it. This intercohort
pattern, which was abetted by the Second
World War and Korean War GI Bills (20) and
by huge state and federal investments in public
college and university systems, is depicted in
Fig. 3A. From 1963 through 1982, the fraction
of all U.S. hours worked that were supplied
by college graduates rose by almost 1 percentage
point per year, a remarkably rapid gain.
After 1982, however, the rate of intercohort
increase fell by almost half—from0.87 percentage
points to 0.47 percentage points per year—and
did not begin to rebound until 2004, nearly
two decades later. As shown in fig. S2, this deceleration
in the supply of college graduates is
particularly stark when one focuses on young
adults with fewer than 10 years of experience—
that is, the cohorts of recent labor market
entrants at each point in time. Although the
supply of young college-educated males relative
to young high school–educated males increased
rapidly in the 1960s and early 1970s
(and indeed throughout the postwar period), this
rising tide reached an apex in 1974 from which
Fig. 2. Cross-national differences
in wage returns to skills,
2011–2013. Reproduced with
permission from Hanushek et al.
[(15), table 2]. Estimates are
obtained by regressing the
natural logarithm of workers’
weekly full-time earnings on test
scores while controlling for sex
and labor market experience
(both a linear and a quadratic
term). Regression estimates are
performed separately for each
country and test scores are
normalized with mean zero and
unit standard deviation within
each country. Estimates that
normalize test scores on a
common basis across countries,
or that use literacy or
problem-solving scores rather
than numeracy scores,
yield qualitatively similar patterns.
Cross-national differences in wage returns
to skills, 2011–2013
Percentage increase for a one standard deviation
increase in skill
0 5 10 15 20 25 30 percent
Czech R.
Slovak R.
95% confidence
SCIENCE sciencemag.org 23 MAY 2014 • VOL 344 ISSUE 6186 845
it barely budged for the better part of the next
30 years. Among young females, the deceleration
in supply was