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3 Technological progress, churning and inequality

3 Technological progress, churning and inequality

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268  THE CORE The long run

of technological progress for consumers (and, by implication, for firms and their shareholders) and the risks for workers is well captured in the cartoon here. The tension between the

large gains for all of society from technological change and the large costs of that technological change for the workers who lose their jobs is explored in the following Focus box.

© Chappatte in Die Weltwoche, Zurich, www.globecartoon.com


Job destruction, churning and earnings losses

Technological progress may be good for the economy,

but it is tough on the workers who lose their jobs. This is

documented in a study in 2011 by Steve Davis and Till von

Wachter, who used records from the social security system

between 1974 and 2008 to look at what happens to workers who lose their job as a result of a mass layoff.

Davis and von Wachter first identified all the firms with

more than 50 workers where at least 30% of the workforce was laid off during one quarter, an event they call a

mass layoff. Then they identified the laid-off workers who

had been employed at that firm for at least three years.

These are long-term employees. They compared the labour

market experience of long-term employees who were laid

off in a mass layoff to other similar workers in the labour

force who did not leave in the layoff year or in the next

two years. Finally, they compared the workers who experienced a mass layoff in a recession to those who experienced a mass layoff in an expansion.

M13 Macroeconomics 85678.indd 268

Figure 13.6 summarises their results. The year 0 is the

year of the mass layoff. Years 1, 2, 3, and so on are the

years after the mass layoff event. The negative years are

the years prior to the layoff. If you have a job and are a

long-term employee, your earnings rise relative to the

rest of society prior to the mass layoff event. Having a

long-term job at the same firm is good for an individual’s wage growth. This is true in both recessions and


Look at what happens in the first year after the layoff. If you experience a mass layoff in a recession, your

earnings fall by 40 percentage points relative to a worker

who does not experience a mass layoff. If you are less

unfortunate and you experience your mass layoff in an

expansion, then the fall in your relative earnings is only

25 percentage points. The conclusion: mass layoffs cause

enormous declines in relative earnings whether they

occur in a recession or an expansion.

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Chapter 13  Technological progress: the short, the medium and the long runs   269

Figure 13.6 makes another important point. The decline

in relative earnings of workers who are part of a mass layoff

persists for years after the layoff. Beyond 5 years or even

up to 20 years after the mass layoff, workers who experienced a mass layoff suffer a relative earnings decline of

about 20 percentage points if the mass layoff took place

in a recession and about 10 percentage points if the mass

layoff took place in an expansion. Thus, the evidence is

strong that a mass layoff is associated with a very substantial decline in lifetime earnings.

It is not hard to explain why such losses in earnings are

likely, even if the size of the loss is surprising. The workers who have spent a considerable part of their career

at the same firm have specific skills, skills that are most

useful in that firm or industry. The mass layoff, if due to

technological change, renders those skills much less valuable than they were.

Other studies have found that in families that experience

a mass layoff, the workers have a less stable employment

path (more periods of unemployment), poorer health outcomes and children who have a lower level of educational

achievement and higher mortality when compared with the

workers who have not experienced a mass layoff. These are

additional personal costs associated with mass layoffs.

So, although technological change is the main source of

growth in the long run, and clearly enables a higher standard of living for the average person in society, the workers

who experience mass layoffs are the clear losers. It is not

surprising that technological change can and does generate anxiety.


Per cent loss in earnings from being laid off











Figure 13.6


Earnings losses of workers who experience a mass



Source: Steven J. Davis and Till M. von


Wachter, ‘Recessions and the cost of job loss’,

–6 –5 –4 –3 –2 –1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 National Bureau of Economics Working Paper

Years before and after job loss in mass layoff

No. 17638, 2011.

The increase in wage inequality

For those in growing sectors, or those with the right skills, technological progress leads to

new opportunities and higher wages. But for those in declining sectors, or those with skills

that are no longer in demand, technological progress can mean the loss of their job, a period

of unemployment and possibly much lower wages. The last 25 years in the United States

have seen a large increase in wage inequality. Most economists believe that one of the main

culprits behind this increase is technological change.

Figure 13.7 shows the evolution of relative wages for various groups of workers in the

United States, by education level, from 1973 to 2012. The figure is based on information

about individual workers from the Current Population Survey. Each of the lines in the figure

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270  THE CORE The long run

Figure 13.7

Evolution of relative

wages by education level,


Since the early 1980s, the relative

wages of workers with a low education

level have fallen; the relative wages

of workers with a high education level

have risen.

Source: Economic Policy Institute Datazone,


Relative wage by level of education



Advanced degree


College degree

Some college




High school diploma

1973 = 1.0

Some high school


1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012

shows the evolution of the wage of workers with a given level of education – ‘some high

school’, ‘high school diploma’, ‘some college’, ‘college degree’, ‘advanced degree’ – relative

to the wage of workers who only have high school diplomas. All relative wages are further

divided by their value in 1973, so the resulting wage series are all equal to one in 1973. The

figure yields a striking conclusion.

Starting in the early 1980s, workers with low levels of education saw their relative wage

fall steadily over time, whereas workers with high levels of education saw their relative wage

rise steadily. At the bottom end of the education ladder, the relative wage of workers who

have not completed high school has declined by 15% since the early 1980s. This implies that,

in many cases, these workers have seen a drop not only in their relative wage, but in their

absolute real wages as well. At the top end of the education ladder, the relative wage of those

with an advanced degree has increased by 34%. In short, wage inequality has increased a lot

in the United States over the last 30 years.

The causes of increased wage inequality

What are the causes of this increase in wage inequality? There is general agreement that

the main factor behind the increase in the wage of high-skilled relative to the wage of lowskilled workers is a steady increase in the demand for high-skilled workers relative to the

demand for low-skilled workers. This trend in relative demand is not new, but it appears to

have increased. Also, until the 1980s it was largely offset by a steady increase in the relative

supply of high-skilled workers. A steadily larger proportion of children finished high school,

went to college, finished college, and so on. Since the early 1980s, however, relative supply

has continued to increase, but not fast enough to match the continuing increase in relative

demand. The result has been a steady increase in the relative wage of high-skilled workers

versus low-skilled workers. The next Focus box shows how not only the demand but also the

supply of skills have shaped the evolution of wage inequality in the United States during the

twentieth century.

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Chapter 13  Technological progress: the short, the medium and the long runs   271


The long view: technology, education and inequality

For the first three-quarters of the twentieth century,

inequality declined. Then it started to rise and it has kept

growing since. Claudia Goldin and Larry F. Katz, two economists at Harvard University, point to education as a major

factor behind the two different trends in inequality.

US educational attainment, measured by the completed

schooling levels of successive generations of students, was

exceptionally rapid during the first three-quarters of the

century. Educational advance slowed considerably, however, for young adults beginning in the 1970s and for the

overall labour force by the early 1980s. For generations

born from the 1870s to about 1950, every decade was

accompanied by an increase of about 0.8 years of education. During that 80-year period the vast majority of parents had children whose educational attainment greatly

exceeded theirs. A child born in 1945 would have been in

school 2.2 years more than his or her parents born in 1921.

But a child born in 1975 would have been in school just

half a year more than his or her parents born in 1951.

Underlying the decision to stay in school longer were

clear economic incentives. As shown in Figure 13.8, the

return to one more year of college education (meaning

how much higher the average wage of a worker is with

one more year of college education) was high in the 1940s:

11% for young men and 10% for all men. This induced

US families to keep their children in school longer and

then send them to college. The increase in the supply of

educated workers lowered both the returns to education

and the wage differentials. By 1950, the return to one more

year of college education had fallen back to 8% for young

men and 9% for all men. But by 1990, rates of return were

back to their 1930s levels. The return to a year of college

today is higher than in the 1930s.

There are two lessons to be drawn from this evidence.

The first is that technological progress (even when skill

biased), accompanied by an increase in the demand for

skilled and educated workers, does not necessarily increase

economic inequality. For the first three-quarters of the

twentieth century, the increase in demand for skills was

more than met by an increase in the supply of skills, leading to decreasing inequality. Since then, demand growth

has continued, whereas supply growth has decreased,

leading to increasing inequality again.

The second is that, although market forces provide

incentives for demand to respond to wage differentials,

institutions are also important. For most Americans in

the early twentieth century access to schooling, at least

through high school, was largely unlimited. Education

was publicly provided and funded and was free of direct

charge, except at the highest levels. Even the most rural

Americans had the privilege of sending their children to

public secondary schools, although African Americans,

especially in the south, were often excluded from various

levels of schooling. This made an essential difference.




Returns to a year of college


Return to college,

young men



90–10 log wage







Return to college,

all men







M13 Macroeconomics 85678.indd 271











90–10 log wage differential



Figure 13.8

Wage differentials and the

returns to education, 1939

to 1995

Sources: Claudia Goldin and Larry F. Katz,

‘Decreasing (and then increasing) inequality

in America: a tale of two half centuries’, in

Finis Welch, The Causes and Consequences

of Increasing Inequality (Chicago: University of

Chicago Press, 2001), 37–82.

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272  THE CORE The long run

This leads to the next question: What is behind this steady shift in relative demand?

Pursuing the effects of international

trade would take us too far afield. For a

more thorough discussion of who gains

and who loses from trade, look at the

book by Paul Krugman and Maurice

Obstfeld, International Economics, 9th

edition (Englewood Cliffs, NJ: Pearson

Education, 2012).

One line of argument focuses on the role of international trade. Those US firms that employ

higher proportions of low-skilled workers, the argument goes, are increasingly driven out of

markets by imports from similar firms in low-wage countries. Alternatively, to remain competitive, firms must relocate some of their production to low-wage countries. In both cases,

the result is a steady decrease in the relative demand for low-skilled workers in the United

States. There are clear similarities between the effects of trade and the effects of technological progress. Although both trade and technological progress are good for the economy as

a whole, they lead nonetheless to structural change and make some workers worse off.

There is no question that trade is partly responsible for increased wage inequality. But a

closer examination shows that trade accounts for only part of the shift in relative demand.

The most telling fact countering explanations based solely on trade is that the shift in relative demand towards high-skilled workers appears to be present even in those sectors that

are not exposed to foreign competition.

The other line of argument focuses on skill-biased technological progress. New machines

and new methods of production, the argument goes, require more and more high-skilled

workers. The development of computers requires workers to be increasingly computer literate. The new methods of production require workers to be more flexible and better able to

adapt to new tasks. Greater flexibility in turn requires more skills and more education. Unlike

explanations based on trade, skill-biased technological progress can explain why the shift in

relative demand appears to be present in nearly all sectors of the economy. At this point, most

economists believe it is the dominant factor in explaining the increase in wage inequality.

Does all this imply that the United States is condemned to steadily increasing wage

inequality? Not necessarily. There are at least three reasons to think that the future may be

different from the recent past:

The trend in relative demand may simply slow down. For example, it is likely that computers

will become steadily easier to use in the future, even by low-skilled workers. Computers may

even replace high-skilled workers, those whose skills involve primarily the ability to compute

or to memorise. Paul Krugman has argued – only partly tongue in cheek – that accountants,

lawyers and doctors may be next on the list of professions to be replaced by computers.

Technological progress is not exogenous. This is a theme we explored earlier (in

Chapter 12). How much firms spend on research and development (R&D) and in what

directions they direct their research depend on expected profits. The low relative

wage of low-skilled workers may lead firms to explore new technologies that take

advantage of the presence of low-skilled, low-wage workers. In other words, market

forces may lead technological progress to become less skill biased in the future.

As we saw in the Focus box, the relative supply of high-skilled versus low-skilled workers

is also not exogenous. The large increase in the relative wage of more educated workers

implies that the returns to acquiring more education and training are higher than they

were one or two decades ago. Higher returns to training and education can increase the

relative supply of high-skilled workers and, as a result, work to stabilise relative wages.

Many economists believe that policy has an important role to play here. It should ensure

that the quality of primary and secondary education for the children of low-wage workers does not further deteriorate and that those who want to acquire more education can

borrow to pay for it.

Inequality and the top 1%

We have focused on wage inequality, the distribution of wages across all wage earners.

Another dimension of inequality, however, is the proportion of income that accrues to the

richest households (e.g. those in the top 1% of the income distribution). When we consider

inequality at very high levels of income, wages are not a good measure of income because

entrepreneurs derive a large fraction of their income (sometimes almost all of it) not from

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Chapter 13  Technological progress: the short, the medium and the long runs   273


Figure 13.9

Top 1%

income share

The evolution of the top 1%

income share

Per cent


Top 1–5%

income share



Top 5–10%

income share

















(a) In the United States since 1913: the

top 1% refers to the top percentile. In

2014, these were families with annual

incomes (including capital gains) above

$387,000. Top 1% to 5% is the next

4%, with annual income between

$167,000 and $387,000. Top 5% to

10% is the bottom half of the top decile,

families with annual income between

$118,000 and $167,000. Income

is defined as annual gross income

reported on tax returns excluding all

government transfers. (b) In the United

Kingdom since 1962

Source: The World Top Income Database,



wages but from capital income and capital gains. This is because they are typically not paid

with wages but with company shares that they can then sell (with some limitations) at a profit.

The evolution of the top 1% share, shown in Figure 13.9, is striking. Although the share of

total income going to households in the top 1% was around 10% in the United States in the

late 1970s (around 5% in the United Kingdom), it now stands at more than 20% today (more

than 15% in the United Kingdom). And while the graph stops in 2008, inequality appears to

have gotten worse since then, with the top 1% capturing 95% of income growth from 2009

to 2014, if capital gains are included. Inequality in the United States, measured this way, is ➤ Note that the sharp increase is limited

to the top 1%. The shares of the other

‘probably higher than in any other society at any time in the past, anywhere in the world’,

groups in the top 10% have increased,

writes Thomas Piketty, whose book, Capital in the XXI Century, when it was published in

but by much less. This suggests that

2014, topped the list of best-selling books worldwide.

there is more than skill bias at work.

Why is this going on? Piketty attributes it in part to unjustifiably large salaries for people

he calls ‘supermanagers’. By his calculations, about 70% of the top 0.1% of earners are corporate executives. Piketty points to bad corporate governance: company boards who grant

CEOs exorbitant pay packages. Above a certain level, he argues, it is hard to find in the data

any link between pay and performance. Although there is plenty of anecdotal evidence for

such excesses, Figure 13.9 suggests that perhaps another factor is at play. Note that the two

periods during which the share of the top 1% has increased are periods of rapid technological

innovation: the 1920s, when electric power was brought into US factories, revolutionising

production; and the years since the early 1980s when personal computers and eventually

the Internet became available. This suggests that innovation and the share of the top 1% are

correlated. Indeed, Figure 13.10, which plots the evolution of patents and the top 1% income

share in the United States since 1960, shows that the two have moved very much together.

Philippe Aghion and co-authors, in the article from which Figure 13.10 is taken, make the

point that a technological innovation allows the innovator to get ahead of competing producers. Often it also allows the innovator to produce with fewer workers. Both of these, the

new technology and the lower labour input, contribute to increasing the innovator’s share

of income at the expense of the workers’ share of income, at least until other entrepreneurs

catch up with the new technology. Through this mechanism, innovation raises top income

inequality, the more so, the higher the number of innovations, and this can explain the rise

in the share of the top 1% in the 1920s and since the early 1980s. However, even if the benefits of innovation may initially be captured by those who generate it, eventually it is shared

broadly as it diffuses through the economy. Moreover, innovation also appears to foster social

mobility; for example, the most innovative state in the United States, California, has both top

1% income shares and a level of social mobility that are much higher than those in the least

innovative state, Alabama. This happens, Aghion argues, as a result of ‘creative destruction’.

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274  THE CORE The long run

The top income share and

patenting in the United

States, 1963–2013

The figure plots the number of patent applications per 1,000 inhabitants

against the top 1% income share.

Observations span the years between

1963 and 2013.

Source: P. Aghion, U. Akcigit, A. Bergeaud,

R. Blundell and D. Hemous, ‘Innovation and

top income inequality’, CEPR Discussion

Paper No. 10659, 2015.

Number of patents per 1,000 inhabitants

Figure 13.10







Top 1% income share












As older firms are replaced by firms employing the new technology, older entrepreneurs are

replaced by newer ones, thus enhancing social mobility.

In our discussion of wage inequality, and of the top 1% income share, we have focused on

the United States. Interestingly, other advanced countries, which are presumably exposed to

the same forces of globalisation and skill-biased technological progress, have typically seen

less of an increase in wage inequality, and much less of an increase in the top 1% income

share. This suggests that institutions and policy do play an important role in shaping these

evolutions. Given the economic and political importance of the question, the debate about

the sources of inequality, and whether governments have the tools to deal with it, is likely to

remain one of the central debates in macroeconomics for some time to come.


People often fear that technological progress destroys jobs

and leads to higher unemployment. This fear was present

during the Great Depression. Theory and evidence suggest

these fears are largely unfounded. There is not much support, either in theory or in the data, for the idea that faster

technological progress leads to higher unemployment.

In the short run, there is no reason to expect, nor does

there appear to be, a systematic relation between changes

in productivity and movements in unemployment.

If there is a relation between changes in productivity

and movements in unemployment in the medium run,

it appears to be an inverse relation. Lower productivity

growth appears to lead to higher unemployment; higher

productivity growth appears to lead to lower unemployment. An explanation is that it takes higher unemployment some time to reconcile workers’ wage expectations

with lower productivity growth.

Technological progress is not a smooth process in which

all workers are winners. Rather, it is a process of structural change. Even if most people benefit from the

M13 Macroeconomics 85678.indd 274

increase in the average standard of living, there are losers

as well. As new goods and new techniques of production

are developed, old goods and old techniques of production become obsolete. Some workers find their skills in

higher demand and benefit from technological progress.

Others find their skills in lower demand and suffer unemployment or reductions in relative wages.

Wage inequality has increased in the past 30 years in

most advanced countries, especially in the United States,

but also in the United Kingdom. The real wage of lowskilled workers has declined not only relative to the real

wage of high-skilled workers but also in absolute terms.

The two main causes are international trade and skillbiased technological progress.

The income share of the top 1% has dramatically

increased in the United States as well as in the United

Kingdom and other advanced economies since the early

1980s. How much of this is explained by poor governance of firms or by high returns to innovation is hotly


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Chapter 13  Technological progress: the short, the medium and the long runs   275

Key terms


unemployment 263

structural change 267

churning 267

skill-biased technological

progress 272

creative destruction 267

Questions and problems

Quick Check

All ‘Quick check’ questions and problems are available on


1.Using the information in this chapter, label each of the following statements true, false or uncertain. Explain briefly.

3.Discuss the following statement: ‘Higher labour productivity allows firms to produce more goods with the same number

of workers and thus to sell the goods at the same or even lower

prices. That’s why increases in labour productivity can permanently reduce the rate of unemployment without causing


a. The change in employment and output per person in the

United States since 1900 lends support to the argument

that technological progress leads to a steady increase in


4.How might policy changes in (a) to (d) affect the wage gap

between low-skilled and high-skilled workers in the United


b.Workers benefit equally from the process of creative


b. Restrictions on the number of foreign temporary agricultural workers allowed to enter the United States.

c. In the past two decades, the real wages of low-skilled US

workers have declined relative to the real wages of highskilled workers.

c. An increase in the number of public colleges.

d. Technological progress leads to a decrease in employment

if, and only if, the increase in output is smaller than the

increase in productivity.

Dig Deeper

e. The apparent decrease in the natural rate of unemployment in the United States in the second half of the 1990s

can be explained by the fact that productivity growth was

unexpectedly high during that period.

f. If we could stop technological progress, doing so would

lead to a decrease in the natural rate of unemployment.

2.Suppose an economy is characterised by the following


Price setting: P = (1 + m)(W/A)

Wage setting: W = AeP e(1 - u)

a. Solve for the unemployment rate if P e = P but Ae does not

necessarily equal A. Explain the effects of (Ae/A) on the

unemployment rate.

b. Now suppose that expectations of both prices and productivity are accurate.

c. Solve for the natural rate of unemployment if the mark-up

(m) is equal to 5%.

d.Does the natural rate of unemployment depend on productivity? Explain.

a. Increased spending on computers in public schools.

d. Tax credits in Central America for US firms.

All ‘Dig deeper’ questions and problems are available on


5.Technological progress, agriculture and employment

Discuss the following statement: ‘Those who argue that technological progress does not reduce employment should look

at agriculture. At the start of the last century, there were

more than 11 million farm workers. Today, there are fewer

than 1 million. If all sectors start having the productivity

growth that took place in agriculture during the 20th century, no one will be employed a century from now.’

6.Productivity and the aggregate supply curve

Consider an economy in which production is given by:

Y = AN

Assume that price setting and wage setting are described in

the following equations:

Price setting: P = (1 + m)(W/A)

Wage setting: W = AeP e(1 - u)

Recall that the relation between employment, N, the labour

force, L, and the unemployment rate, u, is given by:

N = (1 - u)L

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276  THE CORE The long run

a.Derive the aggregate supply curve (i.e. the relation

between the price level and the level of output, given the

mark-up, the actual and expected levels of productivity,

the labour force and the expected price level). Explain the

role of each variable.

b. Show the effect of an equiproportional increase in A and

Ae (so that A/Ae remains unchanged) on the position of the

aggregate supply curve. Explain.

e. What happens to the labour-demand curve if the level of

technology improves? (Hint: What happens to MPL when

technology improves?) Explain. How is the real wage

affected by an increase in the level of technology?

Explore Further

8.The churn

c. Suppose instead that actual productivity, A, increases, but

expected productivity, Ae, does not change. Compare the

results in this case with your conclusions in (b). Explain

the difference.

The Bureau of Labor Statistics presents a forecast of occupations with the largest job decline and the largest job growth.

Examine the tables at www.bls.gov/emp/emptab4.

htm (for the largest job decline) and www.bls.gov/emp/

emptab3.htm (for the largest job growth).

7.Technology and the labour market

a. Which occupations in decline can be linked to technological change? Which can be linked to foreign competition?

In the appendix to Chapter  7, we learned how the wagesetting and price-setting equations could be expressed in

terms of labour demand and labour supply. In this problem,

we extend the analysis to account for technological change.

Consider the wage-setting equation:

W/P = F(u, z)

as the equation corresponding to labour supply. Recall that

for a given labour force, L, the unemployment rate, u, can be

written as:

u = 1 - N/L

where N is employment.

a.Substitute the expression for u into the wage-setting


b.Using the relation you derived in (a), graph the labour

supply curve in a diagram with N on the horizontal axis

and W/P, the real wage, on the vertical axis.

Now write the price-setting equation as:

P = (1 + m)MC

where MC is the marginal cost of production. To generalise somewhat our discussion in the text, we shall write:


where W is the wage and MPL is the marginal product of


c. Substitute the expression for MC into the price-setting

equation and solve for the real wage, W/P. The result is

the labour-demand relation, with W/P as a function of the

MPL and the mark-up, m.

In the text, we assumed for simplicity that the MPL was constant for a given level of technology. Here, we assume that

the MPL decreases with employment (again for a given level

of technology), a more realistic assumption.

d. Assuming that the MPL decreases with employment, graph

the labour-demand relation you derived in (c). Use the

same diagram you drew for (b).

M13 Macroeconomics 85678.indd 276

b. Which occupations that are forecast to grow can be linked to

technological change? Which can be linked to demographic

changes – in particular, the aging of the US population?

9.Real wages

The chapter has presented data on relative wages of highskilled and low-skilled workers. In this question, we look at

the evolution of real wages.

a. Based on the price-setting equation we use in the text, how

should real wages change with technological progress?

Explain. Has there been technological progress during the

period from 1973 to the present?

b.Go to the website of the most recent Economic Report of

the President (https://www.whitehouse.gov/sites/

default/files/docs/cea_2015_erp.pdf) and find Table

B-15. Look at the data on average hourly earnings (in nonagricultural industries) in 1982–1984 dollars (i.e. real

hourly earnings). How do real hourly earnings in 1973

compare with real hourly earnings in the latest year for

which data is available?

c. Given the data on relative wages presented in the chapter,

what do your results from (b) suggest about the evolution

of real wages of low-skilled workers since 1973? What do

your answers suggest about the strength of the relative

decline in demand for low-skilled workers?

d. What might be missing from this analysis of worker compensation? Do workers receive compensation in forms

other than wages?

The Economic Policy Institute (EPI) publishes detailed

information about the real wages of various classes of

workers in its publication The State of Working America.

Sometimes, EPI makes data from it available at www.


10.  Income inequality

a. What evidence is presented in the text that income inequality has increased over time in the United States?

b.Use supply and demand of educated workers to explain

the increase in income inequality.

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Chapter 13  Technological progress: the short, the medium and the long runs   277

c.Use supply and demand of less educated workers to

explain the increase in income inequality.

d. Do a web search and contrast, if possible, the positions of

the Democrats and the Republicans on whether increased

income inequality is a problem in need of a policy solution.

e. There is some evidence on who married whom in 2011 by

level of education at http://www.theatlantic.com/sexes/

archive/2013/04/college-graduates-marry-othercollege-graduates-most-of-the-time/274654/. Explain

how, if like-educated people are more likely to marry each

other over time, this contributes to income inequality.

Log on to MyEconLab and complete the study plan exercises for this chapter to see

how much you have learnt, and where you need to revise most.

Further reading

For more on the process of reallocation that characterises

modern economies, read The Churn: The Paradox of Progress,

a report by the Federal Reserve Bank of Dallas (1993).

For a fascinating account on how computers are transforming

the labour market, read The New Division of Labour: How Computers Are Creating the Next Job Market, by Frank Levy and Richard

Murnane (Princeton, NJ: Princeton University Press, 2004).

For more statistics on various dimensions of inequality in the

United States, a useful source is The State of Working America,

published by the Economic Policy Institute, at http://www.


For more on innovation and income inequality you

can read, beyond Thomas Piketty’s Capital in the XXI

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Century (Cambridge, MA: Harvard University Press,

2014), another piece by Thomas Piketty and Emmanuel

Saez, ‘Income inequality in the United States, 1913–1998’,

Quarterly Journal of Economics, 118(1), 1–41; and that by

Emmanuel Saez, ‘Striking it richer: the evolution of top

incomes in the United States’, Mimeo, University of California, Berkeley, 2013.

For a more general view on technology and inequality, and

one that comes from a slightly different perspective, you can

also read ‘Technology and inequality’, by David Rotman, MIT

Technology Review, 21 October 2014, available at http://



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