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| DISCUSSION QUESTIONS |

1.If an earthquake destroys some of the factories in Poorland, what happens to Poorland’s potential GDP? What happens to Poorland’s potential GDP if it acquires some new advanced technology from Richland and starts using it?

2.Why is it not as terrible to become unemployed nowadays as it was during the Great Depression?

3.“Unemployment is no longer a social problem because unemployed workers receive unemployment benefits and other benefits that make up for most of their lost wages.” Comment.

4.Why is it so difficult to define full employment? What unemployment rate should the government be shooting for today?

5.Show why each of the following complaints is based on

amisunderstanding about inflation:

a.“Inflation must be stopped because it robs workers of their purchasing power.”

b.“Inflation makes it impossible for working people to afford many of the things they were hoping to buy.”

c.“Inflation must be stopped today, for if we do not stop it, it will surely accelerate to ruinously high rates and lead to disaster.”

| APPENDIX | How Statisticians Measure Inflation

INDEX NUMBERS FOR INFLATION

Inflation is generally measured by the change in some index of the general price level. For example, between 1977 and 2007 the Consumer Price Index (CPI), the most widely used measure of the price level, rose from 60.6 to 207.3—an increase of 242 percent. The meaning of the change is clear enough. But what are the meanings of the 60.6 figure for the price level of 1977 and the 207.3 figure for 2007? Both are index numbers.

A price index expresses the cost of a market basket of goods relative to its cost in some “base” period, which is simply the year used as a basis of comparison.

Because the CPI currently uses 1982–1984 as its base period, the CPI of 207.3 for 2007 means that it cost $207.30 in 2007 to purchase the same basket of several hundred goods and services that cost $100 in 1982–1984.

Now in fact, the particular list of consumer goods and services under scrutiny did not actually cost $100 in 1982–1984. When constructing index numbers, by convention the index is set at 100 in the base period. This conventional figure is then used to obtain index numbers for other years in a very simple way. Suppose that the budget needed to buy the hundreds of items included in the CPI was $2,000 per month in 1982–1984 and $4146 per month in 2007 Then the index is defined by the following rule:

CPI in 2007

CPI in 1982–1984

Cost of market basket in 2007

5 Cost of market basket in 1982–1984

Because the CPI in 1982–1984 is set at 100:

CPI in 2007	5	$4,146	5 2.073
100		$2,000

or

CPI in 2007 = 207.3

Exactly the same sort of equation enables us to calculate the CPI in any other year. We have the following rule:

Cost of market basket

in given year

CPI in given year 5 Cost of market basket 3 100 in base year

Of course, not every combination of consumer goods that cost $2,000 in 1982–1984 rose to $4,146 by 2007. For example, a color TV set that cost $400 in 1983 might still have cost $400 in 2007, but a $400 hospital bill in 1983 might have ballooned to $3,000. The index number problem refers to the fact that there is no perfect cost-of-living index because no two families buy precisely the same bundle of goods and services, and hence no two families suffer precisely the same increase in prices. Economists call this the index number problem:

When relative prices are changing, there is no such thing as a “perfect price index” that is correct for every consumer. Any statistical index will understate the increase in the cost of living for some families and overstate it for others. At best, the index can represent the situation of an “average” family.

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THE CONSUMER PRICE INDEX

The Consumer Price Index (CPI), which is calculated and announced each month by the Bureau of Labor Statistics (BLS), is surely the most closely watched price index. When you read in the newspaper or see on television that the “cost of living rose by 0.2 percent last month,” chances are the reporter is referring to the CPI.

The Consumer Price Index (CPI) is measured by pricing the items on a list representative of a typical urban household budget.

To know which items to include and in what amounts, the BLS conducts an extensive survey of spending habits roughly once every decade. As a consequence, the same bundle of goods and services is used as a standard for 10 years or more, whether or not spending habits change.10 Of course, spending habits do change, and this variation introduces a small error into the CPI’s measurement of inflation.

A simple example will help us understand how the CPI is constructed. Imagine that college students purchase only three items—hamburgers, jeans, and movie tickets—and that we want to devise a cost-of- living index (call it SPI, or “Student Price Index”) for them. First, we would conduct a survey of spending habits in the base year. (Suppose it is 1983.) Table 5 represents the hypothetical results. You will note that the frugal students of that day spent only $100 per month: $56 on hamburgers, $24 on jeans, and $20 on movies.

TABLE 5

Results of Student Expenditure Survey, 1983

			Average
			Quantity	Average
		Average	Purchased	Expenditure
	Item	Price	per Month	per Month
	Hamburger	$ 0.80	70	$56
	Jeans	24.00	1	24
	Movie ticket	5.00	4	20
	Total			$100

Table 6 presents hypothetical prices of these same three items in 2007. Each price has risen by a different amount, ranging from 25 percent for jeans up to 50 percent for hamburgers. By how much has the SPI risen?

10 Economists call this a base-period weight index because the relative importance it attaches to the price of each item depends on how much money consumers actually chose to spend on the item during the base period.

TABLE 6

Prices in 2007

		Increase
		over
Item	Price	1983
Hamburger	$1.20	50%
Jeans	30.00	25
Movie ticket	7.00	40

Pricing the 1983 student budget at 2007 prices, we find that what once cost $100 now costs $142, as the calculation in Table 7 shows. Thus, the SPI, based on 1983 5 100, is

Cost of budget in 2007

SPI 5 Cost of budget in 1983 3 100

$142 5 $100 3 100 5 142

TABLE 7

Cost of 1983 Student Budget in

2007 Prices

	70 Hamburgers at $1.20	$84
	1 pair of jeans at $30	30
	4 movie tickets at $7	28
	Total	$142

So, the SPI in 2007 stands at 142, meaning that students’ cost of living has increased 42 percent over the 24 years.

USING A PRICE INDEX TO “DEFLATE” MONETARY FIGURES

One of the most common uses of price indexes is in the comparison of monetary figures relating to two different points in time. The problem is that if there has been inflation, the dollar is not a good measuring rod because it can buy less now than it did in the past.

Here is a simple example. Suppose the average student spent $100 per month in 1983 but $140 per month in 2007. If there was an outcry that students had become spendthrifts, how would you answer the charge?

The obvious answer is that a dollar in 2007 does not buy what it did in 1983. Specifically, our SPI shows us that it takes $1.42 in 2007 to purchase what $1 would purchase in 1983. To compare the spending habits of students in the two years, we must divide the 2007 spending figure by 1.42. Specifically, real spending per student in 2007 (where “real” is defined by 1983 dollars) is:

Real spending	Nominal spending in 2007
5	3 100
in 2007	Price index of 2007

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Thus:

$140

Real spending in 2007 5 142 3 100 5 $98.59

This calculation shows that, despite appearances to the contrary, the change in nominal spending from $100 to $140 actually represented a small decrease in real spending.

This procedure of dividing by the price index is called deflating, and it serves to translate noncomparable monetary figures into more directly comparable real figures.

Deflating is the process of finding the real value of some monetary magnitude by dividing by some appropriate price index.

A good practical illustration is the real wage, a concept we have discussed in this chapter. As we saw in the boxed insert on page 118, we obtain the real wage by dividing the nominal wage by the price level.

USING A PRICE INDEX TO

MEASURE INFLATION

In addition to deflating nominal magnitudes, price indexes are commonly used to measure inflation, that is, the rate of increase of the price level. The procedure is straightforward. The data on the inside back cover (Column 13) show that the CPI was 49.3 in 1974 and 44.4 in 1973. The ratio of these two numbers, 49.3/44.4, is 1.11, which means that the 1974 price level was 11 percent greater than the 1973 price level. Thus, the inflation rate between 1973 and 1974 was 11 percent. The same procedure holds for any two adjacent years. Most recently, the CPI rose from 201.6 in 2006 to 207.3 in 2007. The ratio of these two numbers is 207.3/201.6 5 1.028, meaning that the inflation rate from 2006 to 2007 was 2.8 percent.

THE GDP DEFLATOR

In macroeconomics, one of the most important of the monetary magnitudes that we have to deflate is the nominal gross domestic product (GDP).

The price index used to deflate nominal GDP is called the GDP deflator. It is a broad measure of economywide inflation that includes the prices of all goods and services in the economy.

Our general principle for deflating a nominal magnitude tells us how to go from nominal GDP to real GDP:

Nominal GDP

Real GDP 5 GDP deflator 3 100

As with the CPI, the 100 simply serves to establish the base of the index as 100, rather than 1.00.

Some economists consider the GDP deflator to be a better measure of overall inflation than the Consumer Price Index. The main reason is that the GDP deflator is based on a broader market basket. As mentioned earlier, the CPI is based on the budget of a typical urban family. By contrast, the GDP deflator is constructed from a market basket that includes every item in the GDP—that is, every final good and service produced by the economy. Thus, in addition to prices of consumer goods, the GDP deflator includes the prices of airplanes, lathes, and other goods purchased by businesses—especially computers, which fall in price every year. It also includes government services. For this reason, the two indexes rarely give the same measure of inflation. Usually the discrepancy is minor. But sometimes it can be noticeable, as in 2000 when the CPI recorded a 3.4 percent inflation rate over 1999 while the GDP deflator recorded an inflation rate of only 2.2 percent.

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| SUMMARY |

1.Inflation is measured by the percentage increase in an index number of prices, which shows how the cost of some basket of goods has changed over a period of time.

2.Because relative prices are always changing, and because different families purchase different items, no price index can represent precisely the experience of every family.

3.The Consumer Price Index (CPI) tries to measure the cost of living for an average urban household by pricing a typical market basket every month.

4.Price indexes such as the CPI can be used to deflate nominal figures to make them more comparable. Deflation amounts to dividing the nominal magnitude by the appropriate price index.

5.The inflation rate between two adjacent years is computed as the percentage change in the price index between the first year and the second year.

6.The GDP deflator is a broader measure of economywide inflation than the CPI because it includes the prices of all goods and services in the economy.

| KEY TERMS |

Price index 127	Consumer Price Index (CPI) 128	GDP deflator 129
Index number problem 127	Deflating 129

| TEST YOURSELF |

1.Below you will find the yearly average values of the Dow Jones Industrial Average, the most popular index of stock market prices, for four different years. The Consumer Price Index for each year (on a base of 1982–1984 5 100) can be found on the inside back cover of this book. Use these numbers to deflate all five stock market values. Do real stock prices always rise every decade?

	Dow Jones
Year	Industrial Average
1970	753
1980	891
1990	2,679
2000	10,735

2.Below you will find nominal GDP and the GDP deflator (based on 2000 5 100) for the years 1987, 1997, and 2007.

a.Compute real GDP for each year.

b.Compute the percentage change in nominal and real GDP from 1987 to 1997, and from 1997 to 2007.

c.Compute the percentage change in the GDP deflator over these two periods.

	GDP Statistics	1987	1997	2007
	Nominal GDP
	(Billions of dollars)	4,740	8,304	13,843
	GDP deflator	73.2	95.4	119.7

3. Fill in the blanks in the following table of GDP statistics:

	2005	2006	2007
Nominal GDP	12,434		13,843
Real GDP	11,003	11,319
GDP deflator		116.6	119.7

4.Use the following data to compute the College Price Index for 2007 using the base 1982 = 100.

		Price	Quantity	Price
		in	per Month	in
	Item	1982	in 1982	2007
	Button-down shirts	$10	1	$25
	Loafers	25	1	55
	Sneakers	10	3	35
	Textbooks	12	12	40
	Jeans	12	3	30
	Restaurant meals	5	11	14

5.Average hourly earnings in the U.S. economy during several past years were as follows:

1970	1980	1990	2000
$3.23	$6.66	$10.01	$13.75

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Use the CPI numbers provided on the inside back cover of this book to calculate the real wage (in 1982–1984 dollars) for each of these years. Which decade had the fastest growth of money wages? Which had the fastest growth of real wages?

6.The example in the appendix showed that the Student Price Index (SPI) rose by 42 percent from 1983 to 2007. You can understand the meaning of this better if you do the following:

a.Use Table 5 to compute the fraction of total spending accounted for by each of the three items in 1983. Call these values the “expenditure weights.”

b.Compute the weighted average of the percentage increases of the three prices shown in Table 6, using the expenditure weights you just computed.

You should get 42 percent as your answer. This shows that inflation, as measured by the SPI, is a weighted average of the percentage price increases of all the items that are included in the index.

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ECONOMIC GROWTH: THEORY AND POLICY

Once one starts to think about . . . [differences in growth rates among countries], it is hard to think about anything else.

ROBERT E. LUCAS, JR., 1995 NOBEL PRIZE WINNER IN ECONOMICS

W hy do some economies grow rapidly while others grow slowly—or not at all? As the opening quotation suggests, there is probably no more important question in all of economics. From 1990 to 2005, according to the World Bank, the American

economy grew at a 3.2 percent annual rate, while China’s grew 10.3 percent per year and Russia’s declined (on average) by 1.2 percent per year. Those are very large differences. What factors account for such disparities?

The discussion in Chapter 6 of the goal of economic growth focused our attention on two crucial but distinct tasks for macroeconomic policy makers, both of which are quite difficult to achieve:

•Growth policy: Ensuring that the economy sustains a high long-run growth rate of potential GDP (although not necessarily the highest possible growth rate)

•Stabilization policy: Keeping actual GDP reasonably close to potential GDP in 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 potential 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 actual 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.

C O N T E N T S

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

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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 parents surely have! And it’s not a myth. Between 1978 and 2007, the component 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 anything, 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. Furthermore, 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 the unusually rapid growth in the cost of attending college applies to services as diverse as visits to the doctor, theatrical performances, and restaurant meals—all of which also have become relatively more expensive over time. Later in this chapter, we shall see precisely what this explanation is.

SOURCE: © Jose Luis Pelaez, Inc./CORBIS

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 economy 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.

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

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C

B

A

L1

Hours of Labor Input

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135

Capital

	Figure 1 resembles Figure 1 of the last chapter (see
	page 108). The lower curve 0K1 is the production func-		YC
	tion when the capital stock is some low number K1. Its
	upward slope indicates, naturally enough, that more	Output	YB
	ogy is held constant in this graph.) The middle curve 0K2
	labor input produces more output. (Remember, technol-
	is the production function corresponding to some larger		YA
	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
	However, the nation’s businesses invest in new plant

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.

Then the economy’s capacity to produce will move up from point a in year 1 to point b in year 2 and point c in year 3. Potential GDP will therefore rise from Ya to Yb to Yc. Because hours of work do not change in this example (by assumption), every bit of this growth comes from rising productivity, which is in turn due to the accumulation of more capital.2 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 available 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. Furthermore, workers with more capital are almost certainly blessed with newer—and, hence, better—capital as well. This advantage, too, makes them more productive. Again, compare 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 improvements 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 commonsense) 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 example, use technologies that are far superior to those employed in Africa.

K3

K2

K1

FIGURE 1

Production Functions Corresponding to Three Different Capital Stocks

2 Because productivity is the ratio Y/L, it is shown on the graph by the slope of the straight line connecting the origin to point a, or point b, or point c. Clearly, that slope is rising over time.

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Labor Quality: Education and Training

Human capital is the amount of skill embodied in the workforce. It is most commonly measured by the amount of 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.

Conceptually, an increase in human capital has the same effect on productivity as an increase in physical capital or an improvement in technology, that is, the same quantity of labor input becomes capable of producing more output. So we can use the ever-adaptable Figure 1 for yet a third purpose—to represent increasing workforce quality as we move up 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 productivity 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 workforce, 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 capital, technology, and workforce quality that matter, rather than their current levels. This distinction 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 percent 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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