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FRBSF ECONOMIC LeTTer
2010-23

August 2, 2010

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Stock-Market-Based Measures of Sectoral Shocks and the
Unemployment Rate
Puneet Chehal, Prakash Loungani, and Bharat Trehan
Downturns in the construction and finance sectors played a significant role in the recent recession. A stock-market-based
measure that captures sectoral shocks shows that these disturbances are important for explaining long-duration
unemployment. This is consistent with the intuition that sectoral shocks cause workers to engage in time-consuming
moves across industries in their searches for work. It also suggests that it will take a while before the more than 1.8
million unemployed construction workers and close to a half million unemployed finance and insurance workers find jobs.

Recessions can be precipitated by a variety of shocks. The one that began in 1981, for instance, is
generally attributed to a tightening of monetary policy as the Federal Reserve attempted to squeeze
inflation out of the economy. In the latest recession, developments in the construction and financial
sectors seem to have played a significant role. Economists have debated whether shocks to a particular
sector might affect the economy differently from an aggregate shock, such as a change in fiscal or
monetary policy. This Economic Letter uses a stock-market-based measure to capture sectoral shocks
and discusses the role played by these disturbances in explaining recent high unemployment rates.
Measuring sectoral shocks
Lilien (1982) argued that shocks to individual sectors of the economy would require a reallocation of
labor across sectors. Since finding a job in a different sector of the economy tends to be time
consuming, sectoral shocks push up unemployment. He also showed that a measure of the dispersion of
employment across industries was useful in explaining the unemployment rate. This measure was
subsequently criticized by Abraham and Katz (1986), who pointed out that aggregate shocks could
themselves cause employment in different sectors to grow at different rates. Black (1987) argued that
changes in the relative stock market valuation of different sectors should provide information about the
unemployment rate. Loungani, Rush, and Tave (1990) followed by constructing a measure based on the
dispersion of stock market returns across sectors. They showed that increases in stock market
dispersion were followed by increases in the unemployment rate. Brainard and Cutler (1993) proposed a
related measure. Loungani and Trehan (1997) showed that the dispersion measure was more important

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Federal Reserve Bank San Francisco | Stock-Market-Based Measures of Sectoral Shocks and the Unemployment Rate |

for explaining long-duration unemployment than for explaining short-duration unemployment.
We update this research to cover the latest recession. This approach is of particular interest now because
some recent analyses focusing on employment growth rates and related labor market data found little
evidence of sectoral reallocation (Valletta and Cleary, 2008, for instance). However, the amount of
reallocation observed so far might be an imperfect measure of the sectoral imbalance in the economy.
For example, sectoral reallocation might be held down by a widespread reduction in aggregate demand,
or by uncertainty and credit-market difficulties that limit the ability or willingness of businesses to
expand. Stock prices, being forward looking, can potentially provide a reasonable measure of the
adjustments that may take place in the future once these difficulties have been overcome.
The effect on economywide unemployment
Figure 1 shows how an increase in stock
market dispersion affects the longFigure 1
duration unemployment rate, where longResponse of long-duration unemployment rate to
duration unemployment is defined as a
dispersion
jobless spell in excess of 26 weeks.
Dispersion is measured by an index
defined as the standard deviation of a set
of industry return indexes constructed by
Standard & Poor’s (S&P). The response
(solid line) in Figure 1 is generated from a
statistical model containing the S&P 500
index, real GDP, the federal funds rate,
the relevant unemployment rate, and the
dispersion index. The model is estimated
over the period from the first quarter of
1955 through the first quarter of 2010.
We also show two standard error bands
(dotted lines). Ninety-five percent of the
time the true response lies in the area
between these bands. The figure shows
that the effect on the long-duration rate builds gradually, peaking after more than two years and not
returning to zero for almost five years. Interestingly, the effect of the dispersion index varies with the
duration of unemploy-ment. Dispersion becomes less important as we look at shorter durations. The
opposite is true for the federal funds rate, which is more important at shorter durations and negligible at
longer durations.
Figure 2
illustrates this
point by
providing a
way to
compare the
average effect
of dispersion
shocks and
federal funds
rate shocks on
unemployment
of different

Figure 2
Explaining the unemployment rate

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Federal Reserve Bank San Francisco | Stock-Market-Based Measures of Sectoral Shocks and the Unemployment Rate |

durations.
Technically, it
shows how
much of the
Measured at 20-quarter horizon.
variance of the
error in
predicting
unemployment 20 quarters ahead is due to either of these shocks. The results are intuitively appealing.
The first panel shows that dispersion shocks have almost no effect on short-duration unemployment but
become more important as duration increases. This is what one would expect of shocks that cause
people to move across sectors looking for jobs. The second panel shows that federal funds rate shocks
matter more for the shorter durations and have almost no effect on long-duration unemployment.
It is also instructive to look at the
importance of the dispersion index in the
Figure 3
latest recession. Figure 3 provides an
Explaining long-duration unemployment
estimate of how much of the recent rise in
long-duration unemployment can be
explained by the dispersion index. We
show the long-duration unemployment
rate and two forecasts. The line labeled
base forecast shows the forecast that
would have been made at the beginning of
2005 using the model estimated earlier.
Basically, the model predicts a relatively
flat unemployment rate with long-duration
unemployment converging to its sample
mean of 1%. The dashed line shows what
would have been predicted had the shocks
to the dispersion index been known over
this period. Knowledge of these shocks did
not help much until early 2008. But, by
the first quarter of 2010, these shocks explain about half the difference between the actual longduration unemployment rate of about 4.1% and its long term forecast of 1%. A similar exercise for
short-duration unemployment reveals that knowledge of the dispersion index shocks does not explain
much of the difference between the base forecast and the actual unemployment rate.
Evidence from a specific sector
The aggregate analysis carried out so far
does not directly link stock market returns
in a specific sector to employment
outcomes in that sector. It is instructive to

Figure 4
Excess returns in the homebuilding sector

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Federal Reserve Bank San Francisco | Stock-Market-Based Measures of Sectoral Shocks and the Unemployment Rate |

look at some evidence regarding the
construction sector. Figure 4 shows excess
returns in the Standard & Poor’s home
building sector since 2000, that is, returns
in the homebuilding sector measured
relative to the market average. Note that
excess returns turn negative around mid2005 and stay negative until the end of
2007, when the recession begins.
Figure 5 presents unemployment data on
the construction sector. (This is a more
comprehensive sector than homebuilding,
but the closest we can come to it in the
unemployment data). The sectoral
unemployment rate averaged about 20%
over the 12 months ending in June 2010,
which is more than twice the aggregate
rate. This large difference more than two
years after the recession started suggests
that the effects on the unemployment rate
are likely to be persistent because many
workers laid off from this sector have not
found jobs elsewhere. We also show the
12-month average of median weeks
unemployed, which is rising towards 20
weeks. Note that duration does not begin
to increase until 2007, more than a year
after returns first turn negative.

Figure 5
Unemployment in construction industry
(12-month moving average)

Conclusion
The analysis presented here is not meant
to argue that sectoral shocks are the main
reason behind the high unemployment
rate today. Yet the evidence from
industries that were hard hit in the latest recession suggests that sectoral considerations are likely to
play a significant role in the evolution of the unemployment rate over the next few years. An average of
about 1.8 million construction workers was unemployed over the first six months of this year. It appears
that many of these workers will have to move across sectors, as it is extremely unlikely that
construction, especially homebuilding, will return to levels seen before the crisis. Similarly, it is hard to
believe that employment in the finance and insurance sector will return anytime soon to levels seen
before the recession began, although this is a smaller sector with an average of less than a half million
unemployed in the first six months of the year. How quickly these workers find jobs in other sectors will
depend on how fast businesses in other sectors expand hiring. Unfortunately, so far employers seem
unwilling or unable to hire at the rates that are required to make an appreciable difference to the
unemployed in these sectors.
Puneet Chehal is a research associate at the Federal Reserve Bank of San Francisco.
Prakash Loungani is an advisor in the Research Department at the International Monetary Fund.
Bharat Trehan is a research advisor at the Federal Reserve Bank of San Francisco.

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Federal Reserve Bank San Francisco | Stock-Market-Based Measures of Sectoral Shocks and the Unemployment Rate |

References
Abraham, Katharine, and Lawrence Katz. 1986. “Cyclical Unemployment: Sectoral Shifts or Aggregate
Disturbances?” Journal of Political Economy 94(3, part 1), pp. 507–522.
Black, Fischer. 1987. Business Cycles and Equilibrium. New York: Basil Blackwell, Inc.
Brainard, S. Lael, and David Cutler. 1993. “Sectoral Shifts and Cyclical Unemployment Reconsidered.”
Quarterly Journal of Economics 108(1), pp. 219–243.
Lilien, David. 1982. “Sectoral Shifts and Cyclical Employment.” Journal of Political Economy 90(4), pp.
777–793.
Loungani, Prakash, Mark Rush, and William Tave. 1990. “Stock Market Dispersion and Unemployment.”
Journal of Monetary Economics 25(3), pp. 367–388.
Loungani, Prakash and Bharat Trehan. 1997. “Explaining Unemployment: Sectoral vs. Aggregate
Shocks.” FRBSF Economic Review 97-1, pp. 3–15.
Valletta, Rob, and Aisling Cleary. 2008. “Sectoral Reallocation and Unemployment.” FRBSF Economic
Letter 2008-32 (October 17).
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Opinions expressed in FRBSF Economic Letter
do not necessarily reflect the views of the
management of the Federal Reserve Bank of
San Francisco or of the Board of Governors of
the Federal Reserve System. This publication is
edited by Sam Zuckerman and Anita Todd.
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