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the short run, so that society is plagued by neither high unemployment nor
high inflation
This chapter is devoted to the theory of economic growth and to the policies that this
theory suggests.
Corresponding to the two tasks listed just above, there are two ways to think about
what is to come in this and subsequent chapters. In discussing growth policy in this
chapter, we study the factors that determine an economy™s long-run growth rate of po-
tential GDP, and we consider how policy makers can try to speed it up. When we turn
to stabilization policy, starting in the next chapter, we will investigate how and why ac-
tual GDP deviates from potential GDP in the short run and how policy makers can try
to minimize these deviations. Thus the two views of the macroeconomy complement
one another.




CONTENTS
GROWTH POLICY: ENCOURAGING CAPITAL
PUZZLE: WHY DOES COLLEGE EDUCATION KEEP PUZZLE RESOLVED: WHY THE RELATIVE PRICE
GETTING MORE EXPENSIVE? OF COLLEGE TUITION KEEPS RISING
FORMATION
THE THREE PILLARS OF PRODUCTIVITY GROWTH IN THE DEVELOPING COUNTRIES
GROWTH POLICY: IMPROVING
GROWTH EDUCATION AND TRAINING The Three Pillars Revisited
Capital Some Special Problems of the Developing Countries
GROWTH POLICY: SPURRING
Technology
TECHNOLOGICAL CHANGE FROM THE LONG RUN TO THE SHORT RUN
Labor Quality: Education and Training
THE PRODUCTIVITY SLOWDOWN AND
LEVELS, GROWTH RATES, AND THE SPEED-UP IN THE UNITED STATES
CONVERGENCE HYPOTHESIS
The Productivity Slowdown, 1973“1995
The Productivity Speed-up, 1995“?




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Part 2
134 The Macroeconomy: Aggregate Supply and Demand



PUZZLE: WHY DOES COLLEGE EDUCATION KEEP GETTING MORE EXPENSIVE?
Have you ever wondered why the cost of a college education rises more
rapidly than most other prices year after year? If you have not, your par-
ents surely have! And it™s not a myth. Between 1978 and 2007, the compo-
nent of the Consumer Price Index (CPI) that measures college tuition costs
rose by about 800 percent”compared to about 218 percent for the overall
CPI. That is, the relative price of college tuition increased massively.
Economists understand at least part
of the reason, and it has little, if any-
thing, to do with the efficiency (or lack
thereof) with which colleges are run.
Rather, it is a natural companion to the
economy™s long-run growth rate. Fur-
thermore, there is good reason to expect
the relative price of college tuition to
keep rising, and to rise more rapidly in
faster-growing societies. Economists
believe that the same explanation for




SOURCE: © Jose Luis Pelaez, Inc./CORBIS
the unusually rapid growth in the cost
of attending college applies to services
as diverse as visits to the doctor, the-
atrical performances, and restaurant
meals”all of which also have become
relatively more expensive over time.
Later in this chapter, we shall see pre-
cisely what this explanation is.




THE THREE PILLARS OF PRODUCTIVITY GROWTH
As we learned in the previous chapter, the growth rate of potential GDP is the sum of the
growth rates of hours of work and labor productivity. It is hardly mysterious that an econ-
omy will grow if its people keep working harder and harder, year after year. And a few
societies have followed that recipe successfully for relatively brief periods of time. But
there is a limit to how much people can work or, more important, to how much they
want to work. In fact, people typically want more leisure time, not longer hours of work,
as they get richer. In consequence, the natural focus of growth policy is on enhancing
productivity”on working smarter rather than working harder.
The last chapter introduced a tool called the production function, which tells us how
much output the economy can produce from specified inputs of labor and capital, given
the state of technology. The discussion there focused on two of the three main determinants
of productivity growth:1
• The rate at which the economy builds up its stock of capital
• The rate at which technology improves
Before introducing the third determinant, let us review how these first two pillars
work.




If you need review, see pages 108“110 of Chapter 6.
1




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Chapter 7 135
Economic Growth: Theory and Policy



Capital
K
3
Figure 1 resembles Figure 1 of the last chapter (see
c
page 108). The lower curve 0K1 is the production func- Yc
tion when the capital stock is some low number K1. Its K2
upward slope indicates, naturally enough, that more b
Yb




Output
labor input produces more output. (Remember, technol-
K1
ogy is held constant in this graph.) The middle curve 0K2 a
Ya
is the production function corresponding to some larger
capital stock K2, and the upper curve 0K3 pertains to an
even larger capital stock K3.
To keep things simple at first, suppose hours of work
do not grow over time, but rather remain fixed at L1. 0 L1
However, the nation™s businesses invest in new plant Hours of Labor Input
and equipment, so the capital stock grows from K1 in the
first year to K2 in the second year and K3 in the third year.
F I GU R E 1
Then the economy™s capacity to produce will move up from point a in year 1 to point b in
Production Functions
year 2 and point c in year 3. Potential GDP will therefore rise from Ya to Yb to Yc. Because
Corresponding to
hours of work do not change in this example (by assumption), every bit of this growth
Three Different
comes from rising productivity, which is in turn due to the accumulation of more capital.2 Capital Stocks
In general:
For a given technology and a given labor force, labor productivity will be higher when
the capital stock is larger.
This conclusion is hardly surprising. Employees who work with more capital can
obviously produce more goods and services. Just imagine manufacturing a desk, first
with only hand tools, then with power tools, and finally with all the equipment avail-
able in a modern furniture factory. Or think about selling books from a sidewalk stand,
in a bookstore, or over the Internet. Your productivity would rise in each case. Further-
more, workers with more capital are almost certainly blessed with newer”and, hence,
better”capital as well. This advantage, too, makes them more productive. Again, com-
pare one of Henry Ford™s assembly-line workers of a century ago to an autoworker in a
Ford plant today.


Technology
In Chapter 6, we saw that a graph like Figure 1 can also be used to depict the effects of im-
provements in technology. So now imagine that curves 0K1, 0K2, and 0K3 all correspond to
the same capital stock, but to different levels of technology. Specifically, the economy™s
technology improves as we move up from 0K1 to 0K2 to 0K3. The graphical (and common-
sense) conclusion is exactly the same: Labor becomes more productive from year 1 to year
2 to year 3, so improving technology leads directly to growth. In general:
For given inputs of labor and capital, labor productivity will be higher when the
technology is better.
Once again, this conclusion hardly comes as a surprise”indeed, it is barely more than
the definition of technical progress. When we say that a nation™s technology improves, we
mean, more or less, that firms in the country can produce more output from the same inputs.
And of course, superior technology is a major factor behind the vastly higher productivity
of workers in rich countries versus poor ones. Textile plants in North Carolina, for exam-
ple, use technologies that are far superior to those employed in Africa.



Because productivity is the ratio Y/L, it is shown on the graph by the slope of the straight line connecting the
2

origin to point a, or point b, or point c. Clearly, that slope is rising over time.




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Part 2
136 The Macroeconomy: Aggregate Supply and Demand



Labor Quality: Education and Training
It is now time to introduce the third pillar of productivity growth, the one not mentioned
in Chapter 6: workforce quality. It is generally assumed”and supported by reams of evi-
dence”that better-educated workers can produce more goods and services in an hour
than can less well-educated workers. And the same lesson applies to training that takes
place outside the schools, such as on the job: Better-trained workers are more productive.
The amount of education and training embodied in a nation™s labor force is often referred
to as its stock of human capital.
Human capital is the
amount of skill embodied Conceptually, an increase in human capital has the same effect on productivity as an
in the workforce. It is most increase in physical capital or an improvement in technology, that is, the same quantity of
commonly measured by the
labor input becomes capable of producing more output. So we can use the ever-adaptable
amount of education and
Figure 1 for yet a third purpose”to represent increasing workforce quality as we move up
training.
from 0K1 to 0K2 to 0K3. Once again, the general conclusion is obvious:
For a given capital stock, labor force, and technology, labor productivity will be higher
when the workforce has more education and training.
This third pillar is another obvious source of large disparities between rich nations,
which tend to have well-educated populations, and poor nations, which do not. So we can
add a third item to complete our list of the three principal determinants of a nation™s pro-
ductivity growth rate:
• The rate at which the economy builds up its stock of capital
• The rate at which technology improves
• The rate at which workforce quality ( or “human capital”) is improving
In the contemporary United States, average educational attainment is high and workforce
quality changes little from year to year. But in some rapidly developing countries,
improvements in education can be an important engine of growth. For example, average
years of schooling in South Korea soared from less than five in 1970 to more than nine in
1990, which contributed mightily to South Korea™s remarkably rapid economic development.
Although there is no unique formula for growth, the most successful growth strategies of
the post“World War II era, beginning with the Japanese “economic miracle,” made ample
use of all three pillars. Starting from a base of extreme deprivation after World War II, Japan
showed the world how a combination of high rates of investment, a well-educated work-
force, and the adoption of state-of-the-art technology could catapult a poor nation into the
leading ranks within a few decades. The lessons were not lost on the so-called Asian
Tigers”including Taiwan, South Korea, Singapore, and Hong Kong”which developed
rapidly using their own versions of the Japanese model. Today, a number of other countries,
most notably China, are applying variants of this growth formula once again. It works.




LEVELS, GROWTH RATES, AND THE CONVERGENCE HYPOTHESIS
Notice that, where productivity growth rates are concerned, it is the rates of increase of capi-
tal, technology, and workforce quality that matter, rather than their current levels. This dis-
tinction may sound boring, but it is important.
Productivity levels are vastly higher in the rich countries”that is why they are called
rich. The wealthy nations have more bountiful supplies of capital, more highly skilled
workers, and superior technologies. Naturally, they can produce more output per hour of
work. Table 1 shows, for example, that an hour of labor in France in 2005 produced 99 per-
cent as much output as an hour of labor in the United States, when evaluated in U.S.
dollars, whereas the corresponding figure for Brazil was only 23 percent.
But the growth rates of capital, workforce skills, and technology are not necessarily
higher in the rich countries. For example, Country A might have abundant capital, but the
amount might be increasing at a snail™s pace, whereas in Country B capital might be scarce



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Chapter 7 137
Economic Growth: Theory and Policy



but growing rapidly. When it comes to determining the TA BL E 1
long-run growth rate, it is the growth rates rather than the Productivity Levels and Productivity Growth Rates
current levels of these three pillars that matter. in Selected Countries
In fact, GDP per hour of work actually grew faster over


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