macroeconomics abel ch 08

BUSINESS CYCLES ANDMACROECONOMIC POLICY

P A R T

3

Business Cycles

Since the Industrial Revolution, the economies of the United States and manyother countries have grown tremendously. That growth has transformedeconomies and greatly improved living standards. Yet even in prosperous

countries, economic expansion has been periodically interrupted by episodes ofdeclining production and income and rising unemployment. Sometimes—fortu-nately, not very often—these episodes have been severe and prolonged. Butwhether brief or more extended, declines in economic activity have been followedalmost invariably by a resumption of economic growth.

This repeated sequence of economic expansion giving way to temporarydecline followed by recovery, is known as the business cycle. The business cycle is acentral concern in macroeconomics because business cycle fluctuations—the upsand downs in overall economic activity—are felt throughout the economy. Whenthe economy is growing strongly, prosperity is shared by most of the nation’sindustries and their workers and owners of capital. When the economy weakens,many sectors of the economy experience declining sales and production, and work-ers are laid off or forced to work only part-time. Because the effects of businesscycles are so widespread, and because economic downturns can cause great hard-ship, economists have tried to find the causes of these episodes and to determinewhat, if anything, can be done to counteract them. The two basic questions of(1) what causes business cycles and (2) how policymakers should respond to cycli-cal fluctuations are the main concern of Part 3 of this book.

The answers to these two questions remain highly controversial. Much of thiscontroversy involves the proponents of the classical and Keynesian approaches tomacroeconomics, introduced in Chapter 1. In brief, classical economists view busi-ness cycles as generally representing the economy’s best response to disturbancesin production or spending. Thus classical economists do not see much, if any, needfor government action to counteract these fluctuations. In contrast, Keynesian econ-omists argue that, because wages and prices adjust slowly, disturbances in pro-duction or spending may drive the economy away from its most desirable level ofoutput and employment for long periods of time. According to the Keynesianview, government should intervene to smooth business cycle fluctuations.

We explore the debate between classicals and Keynesians, and the implicationsof that debate for economic analysis and macroeconomic policy, in Chapters 9–11. Inthis chapter we provide essential background for that discussion by presenting thebasic features of the business cycle. We begin with a definition and a brief history ofthe business cycle in the United States. We then turn to a more detailed discussion of

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business cycle characteristics, or “business cycle facts.” We conclude the chapterwith a brief preview of the alternative approaches to the analysis of business cycles.

8.1 What Is a Business Cycle?

Countries have experienced ups and downs in overall economic activity sincethey began to industrialize. Economists have measured and studied these fluc-tuations for more than a century. Marx and Engels referred to “commercialcrises,” an early term for business cycles, in their Communist Manifesto in 1848.In the United States, the National Bureau of Economic Research (NBER), a pri-vate nonprofit organization of economists founded in 1920, pioneered businesscycle research. The NBER developed and continues to update the business cyclechronology, a detailed history of business cycles in the United States and othercountries. The NBER has also sponsored many studies of the business cycle: Onelandmark study was the 1946 book Measuring Business Cycles, by Arthur Burns(who served as Federal Reserve chairman from 1970 until 1978) and WesleyMitchell (a principal founder of the NBER). This work was among the first todocument and analyze the empirical facts about business cycles. It begins withthe following definition:

Business cycles are a type of fluctuation found in the aggregate economic activity ofnations that organize their work mainly in business enterprises. A cycle consists ofexpansions occurring at about the same time in many economic activities, followed bysimilarly general recessions, contractions, and revivals which merge into the expansionphase of the next cycle; this sequence of changes is recurrent but not periodic; in dura-tion business cycles vary from more than one year to ten or twelve years.1

Five points in this definition should be clarified and emphasized.

1. Aggregate economic activity. Business cycles are defined broadly as fluctua-tions of “aggregate economic activity” rather than as fluctuations in a single, spe-cific economic variable such as real GDP. Although real GDP may be the singlevariable that most closely measures aggregate economic activity, Burns andMitchell also thought it important to look at other indicators of activity, such asemployment and financial market variables.

2. Expansions and contractions. Figure 8.1—a diagram of a typical businesscycle—helps explain what Burns and Mitchell meant by expansions and contrac-tions. The dashed line shows the average, or normal, growth path of aggregate eco-nomic activity, and the solid curve shows the rises and falls of actual economicactivity. The period of time during which aggregate economic activity is falling isa contraction or recession. If the recession is particularly severe, it becomes adepression. After reaching the low point of the contraction, the trough (T), aggre-gate economic activity begins to increase. The period of time during which aggre-gate economic activity grows is an expansion or a boom. After reaching the highpoint of the expansion, the peak (P), aggregate economic activity begins to declineagain. The entire sequence of decline followed by recovery, measured from peak topeak or trough to trough, is a business cycle.

8.1 What Is a Business Cycle? 277

1Burns and Mitchell, Measuring Business Cycles, New York: National Bureau of Economic Research,1946, p. 1.

Figure 8.1 suggests that business cycles are purely temporary deviations fromthe economy’s normal growth path. However, part of the output losses and gainsthat occur during a business cycle may become permanent.

Peaks and troughs in the business cycle are known collectively as turningpoints. One goal of business cycle research is to identify when turning pointsoccur. Aggregate economic activity isn’t measured directly by any single variable,so there’s no simple formula that tells economists when a peak or trough hasbeen reached.2 In practice, a small group of economists who form the NBER’sBusiness Cycle Dating Committee determine that date. The committee meets onlywhen its members believe that a turning point may have occurred. By examininga variety of economic data, the committee determines whether a peak or troughhas been reached and, if so, the month it happened. However, the committee’sannouncements usually come well after a peak or trough occurs, so their judg-ments are more useful for historical analysis of business cycles than as a guide tocurrent policymaking.

3. Comovement. Business cycles do not occur in just a few sectors or in just afew economic variables. Instead, expansions or contractions “occur at about thesame time in many economic activities.” Thus, although some industries are moresensitive to the business cycle than others, output and employment in most indus-tries tend to fall in recessions and rise in expansions. Many other economic vari-ables, such as prices, productivity, investment, and government purchases, alsohave regular and predictable patterns of behavior over the course of the business

278 Chapter 8 Business Cycles

Agg

rega

te e

con

omic

act

ivit

y

Time

PT

Normalgrowthpath

Aggregateeconomicactivity

Expansion Expansion

PT

Contraction

FIGURE 8.1

A business cycleThe solid curve graphsthe behavior of aggregateeconomic activity over atypical business cycle.The dashed line showsthe economy’s normalgrowth path. During acontraction aggregateeconomic activity fallsuntil it reaches a trough,T. The trough is followedby an expansion duringwhich economic activityincreases until it reachesa peak, P. A completecycle is measured frompeak to peak or trough to trough.

2A conventional definition used by the media—that a recession has occurred when there are two con-secutive quarters of negative real GDP growth—isn’t widely accepted by economists. The reason thateconomists tend not to like this definition is that real GDP is only one of many possible indicators ofeconomic activity.

cycle. The tendency of many economic variables to move together in a predictableway over the business cycle is called comovement.

4. Recurrent but not periodic. The business cycle isn’t periodic, in that it doesnot occur at regular, predictable intervals and doesn’t last for a fixed or predeter-mined length of time. (Box 8.1, p. 299, discusses the seasonal cycle—or economicfluctuations over the seasons of the year—which, unlike the business cycle, is peri-odic.) Although the business cycle isn’t periodic, it is recurrent; that is, the standardpattern of contraction–trough–expansion–peak recurs again and again in industri-al economies.

5. Persistence. The duration of a complete business cycle can vary greatly,from about a year to more than a decade, and predicting it is extremely difficult.However, once a recession begins, the economy tends to keep contracting for aperiod of time, perhaps for a year or more. Similarly, an expansion, once begun,usually lasts a while. This tendency for declines in economic activity to be followedby further declines, and for growth in economic activity to be followed by moregrowth, is called persistence. Because movements in economic activity have somepersistence, economic forecasters are always on the lookout for turning points,which are likely to indicate a change in the direction of economic activity.

8.2 The American Business Cycle: The Historical Record

An overview of American business cycle history is provided by the NBER’smonthly business cycle chronology,3 as summarized in Table 8.1. It gives the datesof the troughs and peaks of the thirty-two complete business cycles that the U.S.economy has experienced since 1854. Also shown are the number of months thateach contraction and expansion lasted.

The Pre–World War I PeriodThe period between the Civil War (1861–1865) and World War I (1917–1918) wasone of rapid economic growth in the United States. Nevertheless, as Table 8.1shows, recessions were a serious problem during that time. Indeed, the longest con-traction on record is the 65-month-long decline between October 1873 and March1879, a contraction that was worldwide in scope and is referred to by economic his-torians as the Depression of the 1870s. Overall, during the 1854–1914 period theeconomy suffered 338 months of contraction, or nearly as many as the 382 monthsof expansion. In contrast, from the end of World War II in 1945 through January2000, the number of months of expansion (554) outnumbered months of contraction(96) by more than five to one.

The Great Depression and World War IIThe worst economic contraction in the history of the United States was the GreatDepression of the 1930s. After a prosperous decade in the 1920s, aggregate eco-nomic activity reached a peak in August 1929, two months before the stock market

8.2 The American Business Cycle: The Historical Record 279

3For a detailed discussion of the NBER chronologies, see Geoffrey H. Moore and Victor Zarnowitz,“The NBER’s Business Cycle Chronologies,” in Robert J. Gordon, ed., The American Business Cycle:Continuity and Change, Chicago: University of Chicago Press, 1986. The NBER chronology is availableonline at the NBER’s Web site, www.nber.org.

crash in October 1929. Between the 1929 peak and the 1933 trough, real GDP fell bynearly 30%. During the same period the unemployment rate rose from about 3%to nearly 25%, with many of those lucky enough to have jobs only able to workpart-time. To appreciate how severe the Great Depression was, compare it with thetwo worst post–World War II recessions of 1973–1975 and 1981–1982. In contrast tothe 30% real GDP decline and 25% unemployment rate of the Depression, in the1973–1975 recession real GDP fell by 3.4% and the unemployment rate rose fromabout 4% to about 9%; in the 1981–1982 recession real GDP fell by 2.8% and theunemployment rate rose from about 7% to about 11%.

Although no sector escaped the Great Depression, some were particularly hardhit. In the financial sector, stock prices continued to collapse after the crash. Depos-


Expansion Contraction(months from (months from peak

Trough trough to peak) Peak to next trough)

TABLE 8.1

NBER Business Cycle Turning Points and Durations of Post–1854 Business Cycles

Dec. 1854 30 June 1857 18Dec. 1858 22 Oct. 1860 8June 1861 46 (Civil War) Apr. 1865 32Dec. 1867 18 June 1869 18Dec. 1870 34 Oct. 1873 65

Mar. 1879 36 Mar. 1882 38May 1885 22 Mar. 1887 13Apr. 1888 27 July 1890 10May 1891 20 Jan. 1893 17June 1894 18 Dec. 1895 18

June 1897 24 June 1899 18Dec. 1900 21 Sept. 1902 23Aug. 1904 33 May 1907 13June 1908 19 Jan. 1910 24Jan. 1912 12 Jan. 1913 23

Dec. 1914 44 (WWI) Aug. 1918 7Mar. 1919 10 Jan. 1920 18July 1921 22 May 1923 14July 1924 27 Oct. 1926 13Nov. 1927 21 Aug. 1929 43 (Depression)

Mar. 1933 50 May 1937 13 (Depression)June 1938 80 (WWII) Feb. 1945 8Oct. 1945 37 Nov. 1948 11Oct. 1949 45 (Korean War) July 1953 10May 1954 39 Aug. 1957 8

Apr. 1958 24 Apr. 1960 10Feb. 1961 106 (Vietnam War) Dec. 1969 11Nov. 1970 36 Nov. 1973 16Mar. 1975 58 Jan. 1980 6July 1980 12 July 1981 16

Nov. 1982 92 July 1990 8Mar. 1991 120 Mar. 2001 8Nov. 2001

Source: NBER Web site, www.nber.org/cycles.html.

itors withdrew their money from banks, and borrowers, unable to repay their bankloans, were forced to default; as a result, thousands of banks were forced to go outof business or merge with other banks. In agriculture, farmers were bankrupted bylow crop prices, and a prolonged drought in the Midwest turned thousands of farmfamilies into homeless migrants. Investment, both business and residential, fell toextremely low levels, and a “trade war”—in which countries competed in erectingbarriers to imports—virtually halted international trade.

Although most people think of the Great Depression as a single episode, tech-nically it consisted of two business cycles, as Table 8.1 shows. The contractionphase of the first cycle lasted forty-three months, from August 1929 until March1933, and was the most precipitous economic decline in U.S. history. After FranklinRoosevelt took office as President in March 1933 and instituted a set of policiesknown collectively as the New Deal, a strong expansion began and continued forfifty months, from March 1933 to May 1937. By 1937 real GDP was almost back toits 1929 level, although at 14% the unemployment rate remained high. Unemploy-ment remained high in 1937 despite the recovery of real GDP because the numberof people of working age had grown since 1929 and because increases in produc-tivity allowed employment to grow more slowly than output.

The second cycle of the Great Depression began in May 1937 with a contractionphase that lasted more than a year. Despite a new recovery that began in June1938, the unemployment rate was still more than 17% in 1939.

The Great Depression ended dramatically with the advent of World War II.Even before the Japanese attack on Pearl Harbor brought the United States into thewar in December 1941, the economy was gearing up for increased armaments pro-duction. After the shock of Pearl Harbor, the United States prepared for total war.With production supervised by government boards and driven by the insatiabledemands of the military for more guns, planes, and ships, real GDP almost dou-bled between 1939 and 1944. Unemployment dropped sharply, averaging less than2% of the labor force in 1943–1945 and bottoming out at 1.2% in 1944.

Post–World War II U.S. Business CyclesAs World War II was ending in 1945, economists and policymakers were con-cerned that the economy would relapse into depression. As an expression of thisconcern, Congress passed the Employment Act of 1946, which required the gov-ernment to fight recessions and depressions with any measures at its disposal. Butinstead of falling into a new depression as feared, the U.S. economy began togrow strongly.

Only a few relatively brief and mild recessions interrupted the economicexpansion of the early postwar period. None of the five contractions that occurredbetween 1945 and 1970 lasted more than a year, whereas eighteen of the twenty-two previous cyclical contractions in the NBER’s monthly chronology had lasted ayear or more. The largest drop in real GDP between 1945 and 1970 was 3.3% duringthe 1957–1958 recession, and throughout this period unemployment never exceed-ed 8.1% of the work force. Again, there was a correlation between economic expan-sion and war: The 1949–1953 expansion corresponded closely to the Korean War,and the latter part of the strong 1961–1969 expansion occurred during the militarybuildup to fight the Vietnam War.

Because no serious recession occurred between 1945 and 1970, some econo-mists suggested that the business cycle had been “tamed,” or even that it was


“dead.” This view was especially popular during the 106-month expansion of1961–1969, which was widely attributed not only to high rates of military spendingduring the Vietnam War but also to the macroeconomic policies of PresidentsKennedy and Johnson. Some argued that policymakers should stop worryingabout recessions and focus their attention on inflation, which had been graduallyincreasing over the 1960s.

Unfortunately, reports of the business cycle’s death proved premature. Short-ly after the Organization of Petroleum Exporting Countries (OPEC) succeeded inquadrupling oil prices in the fall of 1973, the U.S. economy and the economies ofmany other nations fell into a severe recession. In the 1973–1975 recession U.S. realGDP fell by 3.4% and the unemployment rate reached 9%—not a depression but aserious downturn, nonetheless. Also disturbing was the fact that inflation, whichhad fallen during most previous recessions, shot up to unprecedented double-digit levels. Inflation continued to be a problem for the rest of the 1970s, even as theeconomy recovered from the 1973–1975 recession.

More evidence that the business cycle wasn’t dead came with the sharp1981–1982 recession. This contraction lasted sixteen months, the same length as the1973–1975 decline, and the unemployment rate reached 11%, a postwar high. Manyeconomists claim that the Fed knowingly created this recession to reduce inflation,a claim we discuss in Chapter 11. Inflation did drop dramatically, from about 11%to less than 4% per year. The recovery from this recession was strong, however.

The “Long Boom”The expansion that followed the 1981–1982 recession lasted almost eight years,until July 1990, when the economy again entered a recession. This contraction wasrelatively short (the trough came in March 1991, only eight months after the peak)and shallow (the unemployment rate peaked in mid 1992 at 7.7%—not particular-ly high for a recession). Moreover, after some initial sluggishness, the 1990–1991recession was followed by another sustained expansion. Indeed, in February 2000,after 107 months without a recession, the expansion of the 1990s became the longestin U.S. history, exceeding in length the Vietnam War-era expansion of the 1960s.Taking the expansions of the 1980s and 1990s together, you can see that the U.S.economy experienced a period of more than eighteen years during which onlyone relatively minor recession occurred. Some observers referred to this lengthyperiod of prosperity as the “long boom.” The long boom ended with the businesscycle peak in March 2001, after which the U.S. economy suffered a mild recessionand sluggish growth.


AP P L IC AT ION

Dating the Peak of the 2001 RecessionFor many years, the dates of peaks and troughs of the business cycle have beendetermined by the National Bureau of Economic Research (NBER), a nonprofitorganization that supports a wide variety of applied research in economics. TheNBER has also dated recessions retrospectively back to 1854 (Table 8.1).


As of the beginning of 2001, there had been no “official” recession in the UnitedStates since the one that had begun in July 1990 and ended in March 1991. The ten-year span without a recession was the longest in U.S. history. Indeed, the periodfrom 1982 until 2001, referred to as the “long boom,” was probably the most reces-sion-free in U.S. history, including a total of only eight months of contraction.However, the economy weakened considerably during the latter part of 2000 andin the spring and summer of 2001. A further blow came with the terrorist attacks ofSeptember 11, 2001, which caused significant job losses in New York City and(because people became afraid to travel) in industries such as airlines and hotels.Because of the increased likelihood that a recession had begun, the six economistswho form the Business Cycle Dating Committee—the group within the NBER that“calls” recession dates—convened in November 2001.

Determining whether a recession had begun in 2001, and if so, in which monththe peak occurred, posed an unusually difficult task for the NBER committee. Thecommittee relies heavily on a number of monthly statistical indicators that provideinformation about the state of the economy. Four of the most important indicators are

■ industrial production, which measures the output of factories and mines,■ sales in manufacturing and trade (both wholesale and retail),■ nonfarm employment (the number of jobs), and■ real personal income (excluding transfers such as Social Security payments).

Each of these indicators measures a different aspect of the economy. Because theirmovements tend to coincide with the overall movements in the economy, they arecalled coincident indicators.

Unfortunately, from the perspective of trying to fix a date for the peak, the fourmajor coincident indicators—which normally move more or less together—wereless synchronized than usual in 2000 and 2001. Industrial production (Figure 8.2)and sales in manufacturing and trade had begun to decline significantly as early asJuly 2000. This slump in manufacturing reflected slow sales of information tech-nology (computers, software, communications devices, and so on) following thecollapse of the “dot-com bubble” beginning in March 2000. (The values of manyhigh-tech stocks fell by two-thirds or more during the year.) However, the weak-ness in manufacturing had not been immediately reflected in the economy as awhole, as both employment and real personal income had grown strongly in thefall of 2000. Employment did not start to decline until March 2001 (Figure 8.3), andreal personal income did not appear to decline until October 2001 (though the datawere later revised to show that real personal income in fact began declining inDecember 2000).

After considering all the evidence, the NBER committee dated a recession peakin March 2001. Based on employment and other indicators, March appeared to bethe month in which the weakness in the industrial sector of the previous autumnwas finally felt more broadly in the economy. And although the recession did notappear to be unusually deep by historical standards, by the end of 2001 it was clearthat economic activity had fallen significantly. For example, between March 2001and November 2001, total nonfarm employment fell by 1.6 million jobs, not muchsmaller in percentage terms than the average of the six previous recessions. (Formore information on how the NBER measures recessions and establishes peak andtrough dates, see the NBER’s Web site at www.nber.org/cycles/recessions.html)


Year2000 2001 2002 2003

105

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6 =

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INDUSTRIALPRODUCTIONINDEX

FIGURE 8.2

Index of industrialproduction, January2000–April 2003This chart shows month-ly values for the index of industrial productionfrom January 2000 toApril 2003. Industrialproduction began fallingin July 2000, decliningwell before NBER’s peakmonth of March 2001,indicated by the thinvertical line.Source: Federal Reserve Bankof St. Louis FRED database,research.stlouisfed.org/fred.

Year2000 2001 2002 2003

130.0

130.5

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132.5

133.0

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s of

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s)

TOTALNONFARMEMPLOYMENT

FIGURE 8.3

Total nonfarmemployment, January2000–April 2003This chart shows month-ly values for total non-farm employment, inmillions of people, fromJanuary 2000 to April2003. Employment began to decline inMarch 2001, the samemonth as the NBER’schoice as the peak of the business cycle. Source: Federal Reserve Bankof St. Louis FRED database,research.stlouisfed.org/fred.

Have American Business Cycles Become Less Severe?Until recently, macroeconomists believed that, over the long sweep of history, busi-ness cycles generally have become less severe. Obviously, no recession in theUnited States since World War II can begin to rival the severity of the Great Depres-sion. Even putting aside the Depression, economists generally believed that busi-ness downturns before 1929 were longer and deeper than those since 1945.According to the NBER business cycle chronology (Table 8.1), for example, theaverage contraction before 1929 lasted nearly twenty-one months and the averageexpansion lasted slightly more than twenty-five months. Since 1945, contractionshave shortened to an average of eleven months, and expansions have lengthenedto an average of fifty months, even excluding the lengthy expansion of the 1990s.Standard measures of economic fluctuations, such as real GDP growth and theunemployment rate, also show considerably less volatility since 1945, relative todata available for the pre–1929 era.

Since World War II a major goal of economic policy has been to reduce the sizeand frequency of recessions. If researchers found—contrary to the generally accept-ed view—that business cycles had not moderated in the postwar period, seriousdoubt would be cast on the ability of economic policymakers to achieve this goal.For this reason, although the question of whether the business cycle has moderat-ed over time may seem to be a matter of interest only to economic historians, thisissue is of great practical importance.

Thus Christina Romer, now at the University of California at Berkeley, sparkeda heated controversy by writing a series of articles denying the claim that the busi-ness cycle has moderated over time.4 Romer’s main point concerned the dubiousquality of the pre–1929 data. Unlike today, in earlier periods the government didn’tcollect comprehensive data on economic variables such as GDP. Instead, econom-ic historians, using whatever fragmentary information they could find, have had toestimate historical measures of these variables.

Romer argued that methods used for estimating historical data typically over-stated the size of earlier cyclical fluctuations. For example, widely accepted esti-mates of pre–1929 GNP5 were based on estimates of just the goods-producingsectors of the economy, which are volatile, while ignoring less-volatile sectors suchas wholesale and retail distribution, transportation, and services. As a result, thevolatility of GNP was overstated. Measured properly, GNP varied substantially lessover time than the official statistics showed. Romer’s arguments sparked addi-tional research, though none proved decisively whether volatility truly declinedafter 1929. Nonetheless, the debate served the useful purpose of forcing a carefulreexamination of the historical data.

New research shows that economic volatility declined in the mid 1980s and hasremained low since then. Because the quality of the data is not an issue for the


4The articles included “Is the Stabilization of the Postwar Economy a Figment of the Data?” AmericanEconomic Review, June 1986, pp. 314–334; “The Prewar Business Cycle Reconsidered: New Estimates of Gross National Product, 1869–1908,” Journal of Political Economy, February 1989, pp. 1–37; and “The Cyclical Behavior of Individual Production Series, 1889–1984,” Quarterly Journal of Economics,February 1991, pp. 1–31.5As discussed in Chapter 2, until 1991 the U.S. national income and product accounts focused onGNP rather than GDP. As a result, studies of business cycle behavior have often focused on GNPrather than GDP.

period following World War II, the decline in volatility in the mid 1980s, relative tothe preceding thirty years, probably reflects a genuine change in economic volatil-ity rather than a change in how economic data are produced.

Other economic variables, including inflation, residential investment, output ofdurable goods, and output of structures, also appear to fluctuate less in the pasttwenty years than they did in the preceding forty years. Research by James Stock ofHarvard University and Mark Watson of Princeton University6 shows that thevolatility, as measured by the standard deviation of a variable, declined by 20 to40% for many of the twenty-one variables they examine, including a decline of 33%for real GDP, 27% for employment, and 50% for inflation.

Somewhat surprisingly, the reduction in volatility seemed to come from asudden, one-time drop rather than a gradual decline. The break seems to have comearound 1984 for many economic variables, though for some variables the breakoccurred much later.

What accounts for this reduction in the volatility of the economy? Stock andWatson investigated a number of possible sources, including the switch from man-ufacturing to services, changes in how business firms use inventories, changes inthe market for housing, fewer major shocks to oil prices, reduced shocks to com-modity prices and food prices, better monetary policy, and just plain good luck.

Some economists theorized that the reduction in GDP volatility may occurbecause the economy now produces fewer manufactured goods and more ser-vices, and because manufacturing industries have more volatile output than serviceindustries. But Stock and Watson showed that the volatility of production of bothservices and manufacturing declined over time, so the change from manufacturingto services cannot explain the decline in volatility.

Another theory that some researchers thought likely to explain the reduction inthe volatility of output is that firms have been better at using inventories to keeptheir output stable. For example, in the face of shocks to their demand, firms maybe able to keep their output stable by allowing their inventories to fluctuate. JamesKahn, Margaret McConnell, and Gabriel Perez-Quiros7 found that much of thereduced volatility of U.S. output can be attributed to a decline in volatility of pro-duction in the sector that produces durable goods. In that sector, output becamemuch less variable over time, but the volatility of sales did not, so invento-ries acted as a better buffer. However, Stock and Watson found that the Kahn–McConnell–Perez-Quiros results were sensitive to the empirical method they used;other methods suggest little role for inventories in reducing output volatility.

Residential investment became much less volatile after the mid-1980s. Someeconomists have suggested that improvements in mortgage markets, which havemade homeownership more easily attainable for everyone, have reduced the sen-sitivity of the housing market to fluctuations in the overall economy. But theimprovements in mortgage markets occurred gradually over time, so it is difficultto see how they could explain the sharp break in volatility that we observe.

Another theory is that a reduced volatility of oil prices since the 1980s has led tosmaller fluctuations in U.S. output. In the 1970s, disruptions to the world oil supplytriggered sharp increases in prices and dramatic swings in U.S. output. To the extentthat oil prices are no longer as variable, we might expect that the volatility of output


6“Has the Business Cycle Changed and Why?” manuscript, August 2002.7“On the Causes of the Increased Stability of the U.S. Economy,” Federal Reserve Bank of New YorkEconomic Policy Review (May 2002), pp. 183–202.

would be reduced. But Stock and Watson found little role for oil prices in reducingthe volatility of output. Instead, smaller fluctuations in food prices and other com-modity prices explain about 15% of the reduced volatility of output, with reducedfluctuations in the economy’s productivity explaining another 15%.

The final source of reduction in volatility that Stock and Watson considered wasimprovements in monetary policy. In the 1960s and 1970s, the inflation rate rose overtime. Monetary policymakers did not react strongly enough to keep inflation undercontrol. But when Paul Volcker became Fed chairman in 1979, he fought inflationaggressively, a policy that was continued by his successor, Alan Greenspan. Thereduction in inflation, and the Fed’s stronger response to threats of future inflation,may have reduced the volatility of output by stabilizing the financial system andeliminating boom-bust cycles from the economy. Stock and Watson found thatabout 20% to 30% of the reduction in GDP volatility is attributable to improvedmonetary policy, though the results are rather sensitive to the model of the econo-my that they use.

Overall, then, Stock and Watson found that better monetary policy is responsi-ble for about 20% to 30% of the reduction in output volatility, with reduced shocksto the economy’s productivity accounting for about 15% and reduced shocks tofood and commodity prices accounting for another 15%. The remainder is attribut-able to some unknown form of good luck in terms of smaller shocks to the economy.

8.3 Business Cycle Facts

Although no two business cycles are identical, all (or most) cycles have features incommon. This point has been made strongly by a leading business cycle theorist,Nobel laureate Robert E. Lucas, Jr., of the University of Chicago:

Though there is absolutely no theoretical reason to anticipate it, one is led by the factsto conclude that, with respect to the qualitative behavior of comovements among series[that is, economic variables], business cycles are all alike. To theoretically inclined econo-mists, this conclusion should be attractive and challenging, for it suggests the possibil-ity of a unified explanation of business cycles, grounded in the general laws governingmarket economies, rather than in political or institutional characteristics specific to par-ticular countries or periods.8

Lucas’s statement that business cycles are all alike (or more accurately, thatthey have many features in common) is based on examinations of comovementsamong economic variables over the business cycle. In this section, we study thesecomovements, which we call business cycle facts, for the post–World War II periodin the United States. Knowing these business cycle facts is useful for interpretingeconomic data and evaluating the state of the economy. In addition, they provideguidance and discipline for developing economic theories of the business cycle.When we discuss alternative theories of the business cycle in Chapters 10 and 11,we evaluate the theories principally by determining how well they account forbusiness cycle facts. To be successful, a theory of the business cycle must explainthe cyclical behavior of not just a few variables, such as output and employment,but of a wide range of key economic variables.

8.3 Business Cycle Facts 287

8Robert E. Lucas, Jr., “Understanding Business Cycles,” in K. Brunner and A. H. Meltzer, eds.,Carnegie-Rochester Conference Series on Public Policy, vol. 5, Autumn 1977, p. 10.

The Cyclical Behavior of Economic Variables: Direction and TimingTwo characteristics of the cyclical behavior of macroeconomic variables are impor-tant to our discussion of the business cycle facts. The first is the direction in whicha macroeconomic variable moves, relative to the direction of aggregate economicactivity. An economic variable that moves in the same direction as aggregate eco-nomic activity (up in expansions, down in contractions) is procyclical. A variablethat moves in the opposite direction to aggregate economic activity (up in con-tractions, down in expansions) is countercyclical. Variables that do not display aclear pattern over the business cycle are acyclical.

The second characteristic is the timing of the variable’s turning points (peaks andtroughs) relative to the turning points of the business cycle. An economic variable isa leading variable if it tends to move in advance of aggregate economic activity. Inother words, the peaks and troughs in a leading variable occur before the corre-sponding peaks and troughs in the business cycle. A coincident variable is onewhose peaks and troughs occur at about the same time as the corresponding businesscycle peaks and troughs. Finally, a lagging variable is one whose peaks and troughstend to occur later than the corresponding peaks and troughs in the business cycle.

The fact that some economic variables consistently lead the business cycle sug-gests that they might be used to forecast the future course of the economy. Someanalysts have used downturns in the stock market to predict recessions, but suchan indicator is not infallible. As Paul Samuelson noted: “Wall Street indexes pre-dicted nine out of the last five recessions.”9 The idea that recessions can be forecastalso underlies the index of leading indicators, discussed in the box, “In Touch withthe Macroeconomy: Leading Indicators.”

In some cases the cyclical timing of a variable is obvious from a graph of itsbehavior over the course of several business cycles; in other cases elaborate statisti-cal techniques are needed to determine timing. Conveniently, The Conference Boardhas analyzed the timing of dozens of economic variables. This information is pub-lished monthly in Business Cycle Indicators, along with the most recent data for thesevariables. For the most part, in this chapter we rely on The Conference Board’stiming classifications.

Let’s now examine the cyclical behavior of some key macroeconomic variables.We showed the historical behavior of several of these variables in Figs. 1.1–1.4.Those figures covered a long time period and were based on annual data. We can geta better view of short-run cyclical behavior by looking at quarterly or monthly data.The direction and timing of the variables considered are presented in Summarytable 10 on page 290.

ProductionBecause the level of production is a basic indicator of aggregate economic activity,peaks and troughs in production tend to occur at about the same time as peaks andtroughs in aggregate economic activity. Thus production is a coincident and pro-cyclical variable. Figure 8.4, on page 291, shows the behavior of the industrial pro-duction index in the United States since 1947. This index is a broad measure ofproduction in manufacturing, mining, and utilities. The vertical lines P and T in


9Newsweek column, September 19, 1966, as quoted in John Bartlett, Bartlett’s Familiar Quotations,Boston: Little Brown, 2002.


IN TOUCH WITH THE MACROECONOMY

Leading Indicators

Many different economic variables are considered tolead the business cycle, but because none give an exactindication of when a turning point may arrive, econo-mists have spent considerable effort trying to deter-mine if a combination of those variables can helpindicate when a peak or trough may occur.

The first such index was originally developed in1938 at the National Bureau of Economic Research(NBER) by Wesley Mitchell and Arthur Burns,* whoseimportant early work on business cycles was men-tioned earlier in this chapter. The NBER’s work wasmade official by the U.S. Department of Commerce,which first published the “composite index of leadingindicators” in its publication Business Conditions Digestin November 1968. In 1995, the Commerce Departmentpassed the composite index back to the private sector,and it is now produced by The Conference Board.

Although the composite index of leading indica-tors was designed to predict the onset of recessions andexpansions, its history is spotty. When the index declinesfor two or three consecutive months, it warns that arecession is likely. However, its forecasting acumen inreal time has not been very good because of the follow-ing problems:

1. Data on the components of the index are oftenrevised when more complete data become avail-able. Revisions change the value of the index andmay even reverse a signal of a future recession.

2. The index is prone to giving false signals, predict-ing recessions that did not materialize.

3. The index does not provide any information on whena recession might arrive or how severe it might be.

4. Changes in the structure of the economy over timemay cause some variables to become better predic-tors of the economy and others to become worse.For this reason, the index must be revised periodi-cally, as the list of component indicators is changed.

Research by Francis Diebold and Glenn Rudebuschshowed that the revisions were substantial.** Theagency calculating the index (the Commerce Depart-ment or The Conference Board) often demonstrates the

value of the index with a plot of the index over time,showing how it turns down just before every recession.But Diebold and Rudebusch showed that such a plot isillusory because the index plotted was not the one usedat the time of each recession, but rather a revised indexmade many years after the fact. In real time, they con-cluded, the use of the index does not improve forecastsof industrial production.

For example, suppose you were examining thechanges over time in the composite index of leadingindicators, and used the rule of thumb that a decline inthe index for three months in a row meant that a reces-sion was likely in the next six months to one year. Youwould have noticed in December 1969 that the indexhad declined two months in a row; by January 1970 youwould have seen the third monthly decline. In fact, theNBER declared that a recession had begun in December1969, so the index did not give you any advance warn-ing. Even worse, if you had been following the index in1973 to 1974, you would have thought all was well untilSeptember 1974, when the index declined for the secondmonth in a row, or October 1974, when the third month-ly decline occurred. But the NBER declared that a reces-sion had actually begun in November 1973, so the indexwas nearly a year late in calling the recession.

After missing a recession’s onset so badly, the cre-ators of the index naturally want to improve it. So, theymay revise the index with different variables, give thevariables different weights, or manipulate the statistics sothat, if the new revised index had been available, it wouldhave indicated that a recession were coming. For exam-ple, the revised index published in April 1979 wouldhave given eight months of lead time before the recessionthat began in December 1969 and six months of lead timebefore the recession that began in November 1973. But ofcourse, that index was not available to forecasters when itwould have been useful—before the recessions began.

Because of the problems of the official compositeindex of leading indicators, James Stock and MarkWatson*** set out to create some new indexes that wouldimprove the value of such indexes in forecasting. They

*Statistical Indicators of Cyclical Revivals (New York: National Bureau of Economic Research, 1938). **“Forecasting Output with the Composite Leading Index: A Real-Time Analysis.” Journal of the American Statistical Association(September 1991), pp. 603–610.***“New Indexes of Coincident and Leading Economic Indicators,” in Olivier J. Blanchard and Stanley Fischer, eds., NBERMacroeconomics Annual, 1989 (Cambridge, MA: MIT Press, 1989), pp. 351–394.

(Continued)


created several experimental leading indexes, with thehope that such indexes would prove better at helpingeconomists forecast turning points in the business cycle.However, it appears that the two most recent recessionshave been sufficiently different from earlier recessionsthat the experimental leading indexes did not suggestan appreciable probability of recession in either 1990 or2001. In early 1990, the experimental recession index ofStock and Watson showed that the probability that arecession would occur in the next six months neverexceeded 10%. Also, in late 2000 and early 2001, the

index did not rise above 10%. So, although the Stock andWatson approach appeared promising in prospect, itdid not deliver any improvement in forecasting therecessions.

The inability of leading indicators to forecast reces-sions may simply mean that recessions are often unusu-al events, caused by large, unpredictable shocks such asdisruptions in the world oil supply. If so, then the pur-suit of the perfect index of leading indicators mayprove to be frustrating.

SUMMARY 10The Cyclical Behavior of Key Macroeconomic Variables (The Business Cycle Facts)

ProductionIndustrial production Procyclical Coincident

Durable goods industries are more volatile than nondurable goods and services

ExpenditureConsumption Procyclical CoincidentBusiness fixed investment Procyclical CoincidentResidential investment Procyclical LeadingInventory investment Procyclical LeadingGovernment purchases Procyclical —a

Investment is more volatile than consumption

Labor Market VariablesEmployment Procyclical CoincidentUnemployment Countercyclical Unclassifiedb

Average labor productivity Procyclical Leadinga

Real wage Procyclical —a

Money Supply and InflationMoney supply Procyclical LeadingInflation Procyclical Lagging

Financial VariablesStock prices Procyclical LeadingNominal interest rates Procyclical LaggingReal interest rates Acyclical —a

aTiming is not designated by The Conference Board.bDesignated as “unclassified” by The Conference Board.Source: Business Cycle Indicators, April 2003. Industrial production: series 47 (industrial production); consumption:series 57 (manufacturing and trade sales, constant dollars); business fixed investment: series 86 (gross privatenonresidential fixed investment); residential investment: series 29 (new private housing units started); inventoryinvestment: series 30 (change in business inventories, constant dollars); employment: series 41 (employees onnonagricultural payrolls); unemployment: series 43 (civilian unemployment rate); money supply: series 106(money supply M2, constant dollars); inflation: series 120 (CPI for services, change over six-month span); stockprices: series 19 (index of stock prices, 500 common stocks); nominal interest rates: series 119 (Federal fundsrate), series 114 (discount rate on new 91-day Treasury bills), series 109 (average prime rate charged by banks).

Variable Direction Timing

Figs. 8.4–8.10 indicate the dates of business cycle peaks and troughs, as determinedby the NBER (see Table 8.1). The turning points in industrial production correspondclosely to the turning points of the cycle.

Although almost all types of production rise in expansions and fall in reces-sions, the cyclical sensitivity of production in some sectors of the economy is greaterthan in others. Industries that produce relatively durable, or long-lasting, goods—houses, consumer durables (refrigerators, cars, washing machines), or capital goods(drill presses, computers, factories)—respond strongly to the business cycle, pro-ducing at high rates during expansions and at much lower rates during recessions.In contrast, industries that produce relatively nondurable or short-lived goods(foods, paper products) or services (education, insurance) are less sensitive to thebusiness cycle.

ExpenditureFor components of expenditure, as for types of production, durability is the key todetermining sensitivity to the business cycle. Figure 8.5 shows the cyclical behav-ior of consumption of nondurable goods, consumption of services, consumptionexpenditures on durable goods, and investment. Investment is made up primarilyof spending on durable goods and is strongly procyclical. In contrast, consumptionof nondurable goods and consumption of services are both much smoother.Consumption expenditures on durable goods are more strongly procyclical thanconsumption expenditures on nondurable goods or consumption of services, butnot as procyclical as investment expenditures. With respect to timing, consumption


TP TP TP TP TP TP TPTP TPTP

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FIGURE 8.4

Cyclical behavior ofthe index of industrialproductionThe index of industrialproduction, a broad mea-sure of production inmanufacturing, mining,and utilities, is procycli-cal and coincident. Thepeaks and troughs of thebusiness cycle are shownby the vertical lines Pand T. The shaded areasrepresent recessions.Source: Federal Reserve Bankof St. Louis FRED database atresearch.stlouisfed.org/fred.


P T P T P T PT P T PT PT

CONSUMPTIONOF SERVICES

CONSUMPTION OFNONDURABLEGOODS

INVESTMENT

EXPENDITURE ONDURABLE GOODS

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FIGURE 8.5

Cyclical behavior ofconsumption andinvestmentBoth consumption andinvestment are procycli-cal. However, investmentis more sensitive thanconsumption to the busi-ness cycle, reflecting thefact that durable goodsare a larger part ofinvestment spendingthan they are of con-sumption spending.Similarly, expenditureson consumer durablesare more sensitive to the business cycle than is consumption of non-durable goods or services.Source: Federal Reserve Bankof St. Louis FRED database atresearch.stlouisfed.org/fred.

10Summary table 10 shows that residential investment leads the cycle.

and investment are generally coincident with the business cycle, although indi-vidual components of fixed investment vary in their cyclical timing.10

One component of spending that seems to follow its own rules is inventoryinvestment, or changes in business inventories (not shown), which often displayslarge fluctuations that aren’t associated with business cycle peaks and troughs. Ingeneral, however, inventory investment is procyclical and leading. Even thoughgoods kept in inventory need not be durable, inventory investment is also veryvolatile. Although, on average, inventory investment is a small part (about 1%) oftotal spending, sharp declines in inventory investment represented a large part ofthe total decline in spending in some recessions, most notably those of 1973–1975,1981–1982, and 2001.

Government purchases of goods and services generally are procyclical. Rapidmilitary buildups, as during World War II, the Korean War, and the Vietnam War,are usually associated with economic expansions.

Employment and UnemploymentBusiness cycles are strongly felt in the labor market. In a recession, employment growsslowly or falls, many workers are laid off, and jobs become more difficult to find.

Figure 8.6 shows the number of civilians employed in the United States since1959. Employment clearly is procyclical, as more people have jobs in booms than inrecessions, and also is coincident with the cycle.

Figure 8.7 shows the civilian unemployment rate, which is the fraction of thecivilian labor force (the number of people who are available for work and want towork) that is unemployed. The civilian unemployment rate is strongly countercycli-cal, rising sharply in contractions but falling more slowly in expansions. AlthoughThe Conference Board has studied the timing of unemployment, Summary table 10shows that the timing of this variable is designated as “unclassified,” owing to theabsence of a clear pattern in the data. Figures 8.6 and 8.7 illustrate a worrisomechange in the patterns of recent recessions: namely, in both the 1990–1991 and 2001recessions, employment growth has stagnated and unemployment has tended torise for some time even after the recession’s trough was reached. This pattern has ledthe recovery period of both of these recent recessions to be referred to as “joblessrecoveries.” An encouraging observation is that the jobless aspect of the 1990–1991recession eventually did come to an end; indeed, by the end of the 1990s, the unem-ployment rate had reached its lowest level since the 1960s.

Average Labor Productivity and the Real WageTwo other significant labor market variables are average labor productivity and thereal wage. As discussed in Chapter 1, average labor productivity is output per


Civ

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CIVILIANEMPLOYMENT

TP TP TPTP TP TP TP

FIGURE 8.6

Cyclical behavior ofcivilian employmentCivilian employment isprocyclical and coinci-dent with the businesscycle.Source: Federal Reserve Bankof St. Louis FRED database atresearch.stlouisfed.org/fred.

unit of labor input. Figure 8.8 shows average labor productivity measured as totalreal output in the U.S. economy (excluding farms) divided by the total number ofhours worked to produce that output. Average labor productivity tends to be pro-cyclical: In booms workers produce more output during each hour of work thanthey do in recessions.11 Although The Conference Board doesn’t designate thetiming of this variable, studies show that average labor productivity tends to leadthe business cycle.12

Recall from Chapter 3 that the real wage is the compensation received byworkers per unit of time (such as an hour or a week) measured in real, or pur-chasing-power, terms. The real wage, as shown in Fig. 8.8, is an especially impor-tant variable in the study of business cycles because it is one of the maindeterminants of the amount of labor supplied by workers and demanded by firms.Most of the evidence points to the conclusion that real wages are mildly procycli-cal, but there is some controversy on this point.13


Year1960 1965 1970 1975 1980 1985 1990 1995 2000

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FIGURE 8.7

Cyclical behavior ofthe unemployment rateThe unemployment rateis countercyclical andvery sensitive to thebusiness cycle. Its timingpattern relative to thecycle is unclassified,meaning that it has nodefinite tendency to lead,be coincident, or lag.Source: Federal Reserve Bankof St. Louis FRED database atresearch.stlouisfed.org/fred.

11The Application in Chapter 3, “The Production Function of the U.S. Economy and U.S. ProductivityGrowth,” p. 64, made the point that total factor productivity A also tends to be procyclical.12See Robert J. Gordon, “The ‘End of Expansion’ Phenomenon in Short-Run Productivity Behavior,”Brookings Papers on Economic Activity, 1979:2, pp. 447–461.13See, for example, Mark Mitchell, Myles Wallace, and John Warner, “Real Wages Over the BusinessCycle: Some Further Evidence,” Southern Economic Journal, April 1985, pp. 1162–1173; and MichaelKeane, Robert Moffitt, and David Runkle, “Real Wages Over the Business Cycle: Estimating the Impactof Heterogeneity with Micro Data,” Journal of Political Economy, December 1988, pp. 1232–1266.Stronger procyclicality for the real wage is claimed by Gary Solon, Robert Barsky, and Jonathan Parker,“Measuring the Cyclicality of Real Wages: How Important Is Composition Bias?” Quarterly Journal ofEconomics, February 1994, pp. 1–25.


FIGURE 8.8

Cyclical behavior of average laborproductivity and the real wageAverage labor produc-tivity, measured as realoutput per employeehour in the nonfarmbusiness sector, is pro-cyclical and leading. Theeconomywide averagereal wage is mildly pro-cyclical, and its growthhas slowed sharply since 1973.Source: Federal Reserve Bankof St. Louis FRED database atresearch.stlouisfed.org/fred.

Year1960 1965 1970 1975 1980 1985 1990 1995 2000

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TP TP TP TP TP TPTP

Money Growth and InflationAnother variable whose cyclical behavior is somewhat controversial is the moneysupply. Figure 8.9 shows the behavior since 1959 of the growth in the M2 measureof the money supply.14 Note that (nominal) money growth fluctuates a great dealand doesn’t always display an obvious cyclical pattern. However, as Fig. 8.9 shows,money growth often falls sharply at or just before the onset of a recession. More-over, many statistical and historical studies—including a classic work by MiltonFriedman and Anna J. Schwartz15 that used data back to 1867—demonstrate thatmoney growth is procyclical and leads the cycle.

The cyclical behavior of inflation, also shown in Fig. 8.9, presents a somewhatclearer picture. Inflation is procyclical but with some lag. Inflation typically buildsduring an economic expansion, peaks slightly after the business cycle peak, andthen falls until some time after the business cycle trough is reached. Atypically,inflation did not increase during the long boom of the 1990s.

Financial VariablesFinancial variables are another class of economic variables that are sensitive tothe cycle. For example, stock prices are generally procyclical (stock prices rise

14See Table 7.1 for a definition of M2. To reduce the effect of high month-to-month volatility in moneygrowth, Fig. 8.9 presents a six-month moving average of money growth rates; that is, the reportedgrowth rate in each month is actually the average of the growth rate in the current month and in theprevious five months.15A Monetary History of the United States, 1867–1960, Princeton, N.J.: Princeton University Press forNBER, 1963. We discuss this study further in Chapter 10.


in good economic times) and leading (stock prices usually fall in advance of arecession).

Nominal interest rates are procyclical and lagging. The nominal interest rateshown in Fig. 8.10 is the rate on three-month Treasury bills. However, other interestrates, such as the prime rate (charged by banks to their best customers) and the Fed-eral funds rate (the interest rate on overnight loans made from one bank to anoth-er) also are procyclical and lagging. Note that nominal interest rates have the samegeneral cyclical pattern as inflation; in Chapter 7 we discussed why nominal inter-est rates tend to move up and down with the inflation rate.

The real interest rate doesn’t have an obvious cyclical pattern. For instance, thereal interest rate actually was negative during the 1973–1975 recession but wasvery high during the 1981–1982 recession. (Annual values of the real interest rateare shown in Fig. 2.2.) The acyclicality of the real interest rate doesn’t necessarilymean its movements are unimportant over the business cycle. Instead, the lack of astable cyclical pattern may reflect the facts that individual business cycles havedifferent causes and that these different sources of cycles have different effects onthe real interest rate.

International Aspects of the Business CycleSo far we have concentrated on business cycles in the United States. However,business cycles are by no means unique to the United States, having been regular-ly observed in all industrialized market economies. In most cases the cyclical

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FIGURE 8.9

Cyclical behavior of nominal moneygrowth and inflationNominal money growth,here measured as the six-month moving averageof monthly growth ratesin M2 (expressed inannual rates), is volatile.However, the figureshows that moneygrowth often falls at orjust before a cyclical peak.Statistical and historicalstudies suggest that, gen-erally, money growth isprocyclical and leading.Inflation, here measuredas the six-month movingaverage of monthlygrowth rates of the CPI(expressed in annualrates), is procyclical andlags the business cycle.Source: Federal Reserve Bankof St. Louis FRED database atresearch.stlouisfed.org/fred.

behavior of key economic variables in these other economies is similar to thatdescribed for the United States.

The business cycle is an international phenomenon in another sense: Fre-quently, the major industrial economies undergo recessions and expansions atabout the same time, suggesting that they share a common cycle. Figure 8.11 illus-trates this common cycle by showing the index of industrial production since 1961for each of six major industrial countries. Note in particular the effects of world-wide recessions in about 1975, 1982, 1991, and 2001. Figure 8.11 also shows thateach economy experiences many small fluctuations not shared by the others.

8.4 Business Cycle Analysis: A Preview

The business cycle facts presented in this chapter would be useful even if we tookthem no further. For example, being familiar with the typical cyclical patterns ofkey macroeconomic variables may help forecasters project the course of the econ-omy, as we showed when discussing leading indicators. Knowing the facts aboutcycles also is important for businesspeople making investment and hiring deci-sions and for financial investors trying to choose portfolios that provide thedesired combinations of risk and return. However, macroeconomists are inter-ested not only in what happens during business cycles but also in why it happens.This desire to understand cycles isn’t just idle intellectual curiosity. For example,as we demonstrate in Chapters 9–11, the advice that macroeconomists give to

8.4 Business Cycle Analysis: A Preview 297

TP TP PT PT PT PT PT PTP T P T

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FIGURE 8.10

Cyclical behavior of the nominal interest rateThe nominal interestrate, measured here asthe interest rate on three-month Treasury bills, isprocyclical and lagging.Source: Federal Reserve Bankof St. Louis FRED database atresearch.stlouisfed.org/fred.

policymakers about how to respond to a recession depends on what they think iscausing the recession. Thus, with the business cycle facts as background, in the restof Part 3 we describe the primary alternative explanations of business cycle fluc-tuations, as well as policy recommendations based on these explanations.

In general, theories of the business cycle have two main components. The firstis a description of the types of factors that have major effects on the economy—wars, new inventions, harvest failures, and changes in government policy areexamples. Economists often refer to these (typically unpredictable) forces hittingthe economy as shocks. The other component of a business cycle theory is a model ofhow the economy responds to the various shocks. Think of the economy as a carmoving down a poorly maintained highway: The shocks can be thought of as thepotholes and bumps in the road; the model describes how the components ofthe car (its tires and shock absorbers) act to smooth out or amplify the effects of theshocks on the passengers.

The two principal business cycle theories that we discuss in this book are theclassical and the Keynesian theories. Fortunately, to present and discuss these two the-ories we don’t have to develop two completely different models. Instead, both canbe considered within a general framework called the aggregate demand–aggregatesupply, or AD–AS, model. To introduce some of the key differences between the clas-sical and Keynesian approaches to business cycle analysis, in the rest of this chapterwe preview the AD–AS model and how it is used to analyze business cycles.


FIGURE 8.11

Industrial productionindexes in six majorcountriesThe worldwide effect ofbusiness cycles is reflect-ed in the similarity of thebehavior of industrialproduction in each of the six countries shown.But individual countriesalso have fluctuationsnot shared with other countries. Note: The scales for the indus-trial production indexes differby country; for example, thefigure does not imply that theUnited Kingdom’s total indus-trial production is higher thanthat of Japan.

Source: International FinancialStatistics, May 2003, fromInternational Monetary Fund(with scales adjusted for clarity).

JAPAN

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FRANCEGERMANY

UNITED STATES

Year

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Note: Scales differ by country

2000

UNITED KINGDOM

Aggregate Demand and Aggregate Supply: A Brief IntroductionWe develop and apply the AD–AS model, and a key building block of the AD–ASmodel, the IS–LM model, in Chapters 9–11. Here, we simply introduce and brieflyexplain the basic components of the AD–AS model. The AD–AS model has threecomponents, as illustrated in Fig. 8.12: (1) the aggregate demand curve, (2) the short-run aggregate supply curve, and (3) the long-run aggregate supply curve. Eachcurve represents a relationship between the aggregate price level, P, measured onthe vertical axis in Fig. 8.12, and output, Y, measured along the horizontal axis.


BOX 8 .1

The Seasonal Cycle and the Business Cycle

Did you know that the United States has a large eco-nomic boom, followed by a deep recession, every year?The boom always occurs in the fourth quarter of the year(October through December). During this quarter outputis 5% higher than in the third quarter (July–September)and about 8% higher than in the following first quarter(January–March). Fortunately, the first-quarter recessionis always a short one, with output rising by almost 4% inthe second quarter (April–June). This regular seasonalpattern, known as the seasonal cycle, actually accountsfor more than 85% of the total fluctuation in the growthrate of real output!

Why don’t large seasonal fluctuations appear inFigs. 8.4–8.11? Normally, macroeconomic data are sea-sonally adjusted, meaning that regularly recurring sea-sonal fluctuations are removed from the data. Seasonaladjustment allows users of economic data to ignore sea-sonal changes and focus on business cycle fluctuationsand longer-term movements in the data. However,Robert Barsky of the University of Michigan and JeffreyMiron of Boston University* argue that the practice ofseasonally adjusting macroeconomic data may throwaway information that could help economists betterunderstand the business cycle. Using data that hadn’tbeen seasonally adjusted, Barsky and Miron determinedthat the comovements of variables over the seasonalcycle are similar to their comovements over the businesscycle. Specifically, they obtained the following results:

1. Of the types of expenditure, expenditures on dur-able goods vary most over the seasonal cycle andexpenditures on services vary least.

2. Government spending is seasonally procyclical.

3. Employment is seasonally procyclical, and theunemployment rate is seasonally countercyclical.

4. Average labor productivity is seasonally procycli-cal, and the real wage hardly varies over the sea-sonal cycle.

5. The nominal money stock is seasonally procyclical.

Each observation appears to be true for both thebusiness cycle and the seasonal cycle (although, as dis-cussed, there is some controversy about the cyclicalbehavior of the real wage). However, the seasonal fluc-tuations of inventory investment, the price level, andthe nominal interest rate are much smaller than theirfluctuations over the business cycle.

The seasonal cycle illustrates three potential sourcesof aggregate economic fluctuations: (1) changes in con-sumer demand, as at Christmastime; (2) changes in pro-ductivity, as when construction workers become lessproductive because of winter weather in the first quar-ter; and (3) changes in labor supply, as when people takesummer vacations in the third quarter. Each of thesethree sources of fluctuation may also contribute to thebusiness cycle.

As we discuss in Chapter 10, classical economistsbelieve that business cycles generally represent theeconomy’s best response to changes in the economicenvironment, a response that macroeconomic policyneed not try to eliminate. Although it doesn’t necessar-ily confirm this view, the seasonal cycle shows that largeeconomic fluctuations may be desirable responses tovarious factors (Christmas, the weather) and do notneed to be offset by government policy.

*“The Seasonal and the Business Cycle,” Journal of Political Economy, June 1989, pp. 503–534.

The aggregate demand (AD) curve shows for any price level, P, the total quantityof goods and services, Y, demanded by households, firms, and governments. The ADcurve slopes downward in Fig. 8.12, implying that, when the general price level ishigher, people demand fewer goods and services. We give the precise explanationfor this downward slope in Chapter 9. The intuitive explanation for the downwardslope of the AD curve—that when prices are higher people can afford to buy fewergoods—is not correct. The problem with the intuitive explanation is that, althoughan increase in the general price level does reflect an increase in the prices of mostgoods, it also implies an increase in the incomes of the people who produce and sellthose goods. Thus to say that a higher price level reduces the quantities of goods andservices that people can afford to buy is not correct, because their incomes, as wellas prices, have gone up.

The AD curve relates the amount of output demanded to the price level, if wehold other economic factors constant. However, for a specific price level, anychange in the economy that increases the aggregate quantity of goods and servicesdemanded will shift the AD curve to the right (and any change that decreases thequantity of goods and services demanded will shift the AD curve to the left). Forexample, a sharp rise in the stock market, by making consumers wealthier, wouldlikely increase households’ demand for goods and services, shifting the AD curveto the right. Similarly, the development of more efficient capital goods wouldincrease firms’ demand for new capital goods, again shifting the AD curve to theright. Government policies also can affect the AD curve. For example, a decline ingovernment spending on military hardware reduces the aggregate quantity ofgoods and services demanded and shifts the AD curve to the left.


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P

Output, Y

LRAS

SRAS

AD

Y

E

FIGURE 8.12

The aggregatedemand–aggregatesupply modelThe aggregate demand(AD) curve slopes down-ward, reflecting the factthat the aggregate quan-tity of goods and servicesdemanded, Y, falls whenthe price level, P, rises.The short-run aggregatesupply (SRAS) curve ishorizontal, reflecting theassumption that, in theshort run, prices arefixed and firms simplyproduce whatever quan-tity is demanded. In thelong run, firms producetheir normal levels ofoutput, so the long-runaggregate supply (LRAS)curve is vertical at thefull-employment level ofoutput, Y. The economy’sshort-run equilibrium isat the point where theAD and SRAS curvesintersect, and its long-run equilibrium is wherethe AD and LRAS curvesintersect. In this example,the economy is in bothshort-run and long-runequilibrium at point E.

An aggregate supply curve indicates the amount of output producers are will-ing to supply at any particular price level. Two aggregate supply curves are shownin Fig. 8.12—one that holds in the short run and one that holds in the long run. Theshort-run aggregate supply (SRAS) curve, shown in Fig. 8.12, is a horizontal line. Thehorizontal SRAS curve captures the ideas that in the short run the price level isfixed and that firms are willing to supply any amount of output at that price. If theshort run is a very short period of time, such as a day, this assumption is realistic.For instance, an ice cream store posts the price of ice cream in the morning and sellsas much ice cream as is demanded at that price (up to its capacity to produce icecream). During a single day, the owner typically won’t raise the price of ice creamif the quantity demanded is unusually high; nor does the owner lower the price ofice cream if the quantity demanded is unusually low. The tendency of a producerto set a price for some time and then supply whatever is demanded at that price isrepresented by a horizontal SRAS curve.

However, suppose that the quantity of ice cream demanded remains highday after day, to the point that the owner is straining to produce enough icecream to meet demand. In this case, the owner may raise her price to reduce thequantity of ice cream demanded to a more manageable level. The owner willkeep raising the price of ice cream as long as the quantity demanded exceedsnormal production capacity. In the long run, the price of ice cream will be what-ever it has to be to equate the quantity demanded to the owner’s normal level ofoutput. Similarly, in the long run, all other firms in the economy will adjust theirprices as necessary so as to be able to produce their normal level of output. Asdiscussed in Chapter 3, the normal level of production for the economy as awhole is called the full-employment level of output, denoted Y. In the long run,then, when prices fully adjust, the aggregate quantity of output supplied willsimply equal the full-employment level of output, Y. Thus the long-run aggregatesupply (LRAS) curve is vertical, as shown in Fig. 8.12, at the point that output sup-plied, Y, equals Y.

Figure 8.12 represents an economy that is simultaneously in short-run andlong-run equilibrium. The short-run equilibrium is represented by the intersectionof the AD and SRAS curves, shown as point E. The long-run equilibrium is repre-sented by the intersection of the AD and LRAS curves, also shown as point E.However, when some change occurs in the economy, the short-run equilibrium candiffer from the long-run equilibrium.

Aggregate Demand Shocks. Recall that a theory of business cycles has toinclude a description of the shocks hitting the economy. The AD–AS frameworkidentifies shocks by their initial effects—on aggregate demand or aggregate supply.An aggregate demand shock is a change in the economy that shifts the AD curve. Forexample, a negative aggregate demand shock would occur if consumers becamemore pessimistic about the future and thus reduced their current consumptionspending, shifting the AD curve to the left.

To analyze the effect of an aggregate demand shock, let’s suppose that theeconomy initially is in both short-run and long-run equilibrium at point E in Fig. 8.13. We assume that, because consumers become more pessimistic, the aggre-gate demand curve shifts down and to the left from AD1 to AD2. In this case, thenew short-run equilibrium (the intersection of AD2 and SRAS) is at point F, whereoutput has fallen to Y2 and the price level remains unchanged at P1. Thus the


decline in household consumption demand causes a recession, with output fallingbelow its normal level. However, the economy will not stay at point F forever,because firms won’t be content to keep producing below their normal capacity.Eventually firms will respond to lower demand by adjusting their prices—in thiscase downward—until the economy reaches its new long-run equilibrium at pointH, the intersection of AD2 and LRAS. At point H, output is at its original level, Y,but the price level has fallen to P2.

Our analysis shows that an adverse aggregate demand shock, which shifts theAD curve down, will cause output to fall in the short run but not in the long run.How long does it take for the economy to reach the long run? This question is cru-cial to economic analysis and is one to which classical economists and Keynesianeconomists have very different answers. Their answers help explain why classicalsand Keynesians have different views about the appropriate role of governmentpolicy in fighting recessions.

The classical answer is that prices adjust quite rapidly to imbalances in quan-tities supplied and demanded so that the economy gets to its long-run equilibriumquickly—in a few months or less. Thus a recession caused by a downward shift ofthe AD curve is likely to end rather quickly, as the price level falls and the econo-my reaches the original level of output, Y. In the strictest versions of the classicalmodel, the economy is assumed to reach its long-run equilibrium essentially imme-diately, implying that the short-run aggregate supply curve is irrelevant and thatthe economy always operates on the long-run aggregate supply (LRAS) curve.Because the adjustment takes place quickly, classical economists argue that little isgained by the government actively trying to fight recessions. Note that this con-clusion is consistent with the “invisible hand” argument described in Chapter 1,


FIGURE 8.13

An adverse aggregatedemand shockAn adverse aggregatedemand shock reducesthe aggregate quantity of goods and servicesdemanded at a givenprice level; an example isthat consumers becomemore pessimistic andthus reduce their spend-ing. This shock is repre-sented by a shift to theleft of the aggregatedemand curve from AD1

to AD2. In the short run,the economy moves topoint F. At this short-runequilibrium, output hasfallen to Y2 and the pricelevel is unchanged. Even-tually, price adjustmentcauses the economy tomove to the new long-run equilibrium at pointH, where output returnsto its full-employmentlevel, Y, and the pricelevel falls to P2. In thestrict classical view, theeconomy moves almostimmediately to point H,so the adverse aggregatedemand shock essentiallyhas no effect on output inboth the short run andthe long run. Keynesiansargue that the adjustmentprocess takes longer, sothat the adverse aggre-gate demand shock maylead to a sustaineddecline in output.

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Output, Y

LRAS

SRAS

AD1AD2

P1

P2

YY2

E

H

F

Consumersbecomemore thrifty

according to which the free market and unconstrained price adjustments are suffi-cient to achieve good economic results.

In contrast to the classical view, Keynesian economists argue that prices (andwages, which are the price of labor) do not necessarily adjust quickly in response toshocks. Hence the return of the economy to its long-run equilibrium may be slow,taking perhaps years rather than months. In other words, although Keynesiansagree with classicals that the economy’s level of output will eventually return fromits recessionary level (represented by Y2 in Fig. 8.13) to its full-employment level, Y,they believe that this process may be slow. Because they lack confidence in the self-correcting powers of the economy, Keynesians tend to see an important role for thegovernment in fighting recessions. For example, Keynes himself originally arguedthat government could fight recessions by increasing spending. In terms of Fig. 8.13,an increase in government spending could in principle shift the AD curve up and tothe right, from AD2 back to AD1, restoring the economy to full employment.

Aggregate Supply Shocks. Because classical economists believe that aggregatedemand shocks don’t cause sustained fluctuations in output, they generally viewaggregate supply shocks as the major force behind changes in output and employ-ment. An aggregate supply shock is a change in the economy that causes the long-runaggregate supply (LRAS) curve to shift. The position of the LRAS curve dependsonly on the full-employment level of output, Y, so aggregate supply shocks can alsobe thought of as factors—such as changes in productivity or labor supply, forexample—that lead to changes in Y.

Figure 8.14 illustrates the effects of an adverse supply shock—that is, a shockthat reduces the full-employment level of output (an example would be a severe


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Output, Y

LRAS2 LRAS1

E

F

AD

Y1Y2

P1

P2

Adversesupplyshock

FIGURE 8.14

An adverse aggregatesupply shockAn adverse aggregatesupply shock, such as adrought, reduces the full-employment level ofoutput from Y1 to Y2.Equivalently, the shockshifts the long-run aggre-gate supply curve to theleft, from LRAS1 toLRAS2. As a result of theadverse supply shock,the long-run equilibriummoves from point E topoint F. In the new long-run equilibrium, outputhas fallen from Y1 to Y2

and the price level hasincreased from P1 to P2.

drought that greatly reduces crop yields). Suppose that the economy is initially inlong-run equilibrium at point E in Fig. 8.14, where the initial long-run aggregatesupply curve, LRAS1, intersects the aggregate demand curve, AD. Now imaginethat the adverse supply shock hits, reducing full-employment output from Y1 to Y2and causing the long-run aggregate supply curve to shift to the left from LRAS1 toLRAS2. The new long-run equilibrium occurs at point F, where the level of outputis lower than at point E. According to the classical view, the economy moves quick-ly from point E to point F and then remains at point F. The drop in output as theeconomy moves from point E to point F is a recession. Note that the new price level,P2, is higher than the initial price level, P1, so adverse supply shocks cause prices torise during recessions. We return to this implication for the price level and discussits relation to the business cycle facts in Chapter 10.

Although classical economists first emphasized supply shocks, Keynesian econ-omists also recognize the importance of supply shocks in accounting for businesscycle fluctuations in output. Keynesians agree that an adverse supply shock willreduce output and increase the price level in the long run. In Chapter 11, we discussthe Keynesian view of the process by which the economy moves from the short runto the long run in response to a supply shock.


CHAPTER SUMMARY

1. A business cycle consists of a period of decliningaggregate economic activity (a contraction or reces-sion) followed by a period of rising economic activity(an expansion or a boom). The low point of the con-traction is called the trough, and the high point of theexpansion is called the peak. Business cycles havebeen observed in market economies since the begin-ning of industrialization.

2. The tendency of many economic variables to movetogether in regular and predictable ways over thecourse of the cycle is called comovement. We refer tothe typical cyclical patterns of key macroeconomicvariables as the “business cycle facts.”

3. The fluctuations in aggregate economic activity thatconstitute business cycles are recurrent, having beenobserved again and again in industrialized marketeconomies. However, they aren’t periodic, in that theydon’t occur at regular or predictable intervals. Busi-ness cycle fluctuations also are persistent, whichmeans that once a recession or expansion begins, itusually lasts for a while.

4. Many economists believe that the U.S. economybefore 1929 had longer recessions and more cyclicalvolatility than the post–World War II economy. How-ever, data problems prevent precise measurements ofhow much more cyclical the pre–1929 economy was.The Great Depression that began in 1929 and didn’t

end until the onset of World War II was the mostsevere cyclical decline in U.S. history. Moderation ofthe business cycle after World War II led to prematurepronouncements that the cycle was “dead.” However,the U.S. economy suffered severe recessions in1973–1975 and 1981–1982. Between 1982 and the endof the millennium the economy enjoyed a “longboom,” with only one minor recession in 1990–1991.

5. The direction of a variable relative to the businesscycle can be procyclical, countercyclical, or acyclical.A procyclical variable moves in the same direction asaggregate economic activity, rising in booms andfalling in recessions. A countercyclical variable movesin the opposite direction to aggregate economic activ-ity, falling in booms and rising in recessions. Anacyclical variable has no clear cyclical pattern.

6. The timing of a variable relative to the business cyclemay be coincident, leading, or lagging. A coincidentvariable’s peaks and troughs occur at about the sametime as peaks and troughs in aggregate economicactivity. Peaks and troughs in a leading variable comebefore, and peaks and troughs in a lagging variablecome after, the corresponding peaks and troughs inaggregate economic activity.

7. The cyclical direction and timing of major macroeco-nomic variables—the business cycle facts—aredescribed in Summary table 10. In brief, production,

consumption, and investment are procyclical andcoincident. Investment is much more volatile over thebusiness cycle than consumption is. Employment isprocyclical, but the unemployment rate is counter-cyclical. Average labor productivity and the real wageare procyclical, although according to most studiesthe real wage is only mildly so. Money and stockprices are procyclical and lead the cycle. Inflation andnominal interest rates are procyclical and lagging. Thereal interest rate is acyclical.

8. A theory of business cycles consists of (1) a descrip-tion of shocks that affect the economy and (2) amodel, such as the aggregate demand–aggregatesupply (AD–AS) model, that describes how the econ-omy responds to these shocks. In the AD–AS model,shocks to the aggregate demand (AD) curve causeoutput to change in the short run, but output returnsto its full-employment level, Y, in the long run. Shocks

to the aggregate supply curve can affect output bothin the long run and the short run.

9. Classical economists argue that the economy reachesits long-run equilibrium quickly, because prices adjustrapidly. This view implies that aggregate demandshocks have only very short-lived effects on real vari-ables such as output; instead, classical economistsemphasize aggregate supply shocks as the source ofbusiness cycles. Classicals also see little role for gov-ernment policies to fight recessions. Keynesian econ-omists, in contrast, believe that it takes a long timefor the economy to reach long-run equilibrium. Theyconclude, therefore, that aggregate demand shockscan affect output for substantial periods of time. Fur-thermore, they believe that government policies maybe useful in speeding the economy’s return to fullemployment.

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KEY TERMS

acyclical, p. 288boom, p. 277business cycle, p. 277business cycle chronology, p. 277coincident variable, p. 288comovement, p. 279contraction, p. 277

countercyclical, p. 288depression, p. 277expansion, p. 277index of leading indicators, p. 288lagging variable, p. 288leading variable, p. 288

peak, p. 277persistence, p. 279procyclical, p. 288recession, p. 277trough, p. 277turning points, p. 278

REVIEW QUESTIONS

1. Draw a diagram showing the phases and turningpoints of a business cycle. Using the diagram, illustratethe concepts of recurrence and persistence.

2. What is comovement? How is comovement related tothe business cycle facts presented in this chapter?

3. What is the evidence for the view that the U.S. businesscycle has become less severe over time? Why is thequestion of whether the cycle has moderated over timean important one?

4. What terms are used to describe the way a variablemoves when economic activity is rising or falling?What terms are used to describe the timing of cyclicalchanges in economic variables?

5. If you knew that the economy was falling into a reces-sion, what would you expect to happen to production

during the next few quarters? To investment? To aver-age labor productivity? To the real wage? To the unem-ployment rate?

6. How is the fact that some economic variables areknown to lead the cycle used in macroeconomic fore-casting?

7. What are the two components of a theory of businesscycles?

8. How do Keynesians and classicals differ in their beliefsabout how long it takes the economy to reach long-runequilibrium? What implications do these differences inbeliefs have for Keynesian and classical views aboutthe usefulness of antirecessionary policies? About thetypes of shocks that cause most recessions?

QUIZ

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16For further discussion of these issues, see Christina D. Romer, “Remeasuring Business Cycles,” Journal of Economic History,September 1994, pp. 573 – 609; and Randall E. Parker and Philip Rothman, “Further Evidence on the Stabilization of PostwarEconomic Fluctuations,” Journal of Macroeconomics, Spring 1996, pp. 289–298. Romer was the first to emphasize the potentialimportance of the change in business cycle dating methodology.

WORKING WITH MACROECONOMIC DATA

For data to use in these exercises, go to the Federal Reserve Bankof St. Louis FRED database at research.stlouisfed.org/fred.

1. An economic variable is persistent if declines in the vari-able tend to be followed by more declines, and increasesby more increases. This question asks you to study thepersistence of the civilian unemployment rate.

Using data since 1961, identify all quarters in whichthe unemployment rate (in the last month of the quar-ter) changed by at least 0.2 percentage points from theprevious quarter (either up or down). How many ofthese changes by 0.2 percentage points or more werefollowed in the subsequent quarter by (1) anotherchange in the same direction, (2) a change in the oppo-site direction, or (3) no change? Based on your count,would you say that the unemployment rate is a persis-tent variable?

2. Graph the NBER experimental leading index and coin-cident index (found at www.nber.org/data), using month-ly data since 1959. Based on the graphs, estimate datesof business cycle peaks and troughs. How close areyour estimates to the NBER turning-point dates listedin Table 8.1?

3. How does each of the following variables respond tothe business cycle? Develop graphs to show yourresults and give economic explanations.

a. Index of help-wanted advertising in newspapersb. Real importsc. Federal government receiptsd. Housing startse. Capacity utilization rate, manufacturingf. Average weekly hours, manufacturing

ANALYTICAL PROBLEMS

1. Figure 8.1 shows that business cycle peaks and troughsare identified with peaks and troughs in the level ofaggregate economic activity, which is consistent withcurrent NBER methodology. However, for businesscycles before 1927, the NBER identified business cyclepeaks and troughs with peaks and troughs in detrendedaggregate economic activity (aggregate economic activ-ity minus the “normal growth path” shown in Fig. 8.1).Show that this alternative methodology implies thatpeaks occur earlier and that troughs occur later thanyou would find when using the current methodology.Compared to the current methodology, does the alter-native methodology increase or decrease the computedlength of contractions and expansions? How might thischange in measurement account for the differences inthe average measured lengths of expansions and con-tractions since World War II compared to the periodbefore World War I?16

2. Consumer expenditures on durable goods such as carsand furniture, as well as purchases of new houses, fallmuch more than expenditures on nondurable goodsand services during most recessions. Why do you thinkthat is?

3. Output, total hours worked, and average labor pro-ductivity all are procyclical.

a. Which variable, output or total hours worked, increas-es by a larger percentage in expansions and falls by alarger percentage in recessions? (Hint: Average laborproductivity = output ÷ total hours worked, so thatthe percentage change in average labor productivityequals the percentage change in output minus the per-centage change in total hours worked.)

b. How is the procyclical behavior of average laborproductivity related to Okun’s Law, discussed inChapter 3?

4. During the period 1973–1975, the United States experi-enced a deep recession with a simultaneous sharp risein the price level. Would you conclude that the reces-sion was the result of a supply shock or a demandshock? Illustrate, using AD–AS analysis.

5. It is sometimes argued that economic growth that is“too rapid” will be associated with inflation. UseAD–AS analysis to show how this statement might betrue. When this claim is made, what type of shock isimplicitly assumed to be hitting the economy?

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4. It has been argued that the stock market predicts reces-sions. Using quarterly data since 1961, plot the realvalue of the stock market index (the S&P 500 index inthe last month of the quarter divided by the GDP defla-tor). [Note that data on the S&P 500 index may befound at finance.yahoo.com.] Draw in the business cyclepeaks and troughs. Do you find the stock market to bea good economic forecaster?

5. Graph the levels of real GDP for the United States,Canada, and Germany (data can be found at www.oecd.org under Statistics and then under NationalAccounts). Are U.S. and Canadian business cyclesclosely related? U.S. and German business cycles?

Chapter Summary 307

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analysis of business

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whenthe economy