profession has learned so much. No longer do economists conjecture and
speculate. Instead they make quantitative statements as to the consequences
of various shocks and features of reality for business cycle fluctuations. This
paper began a constructive and fruitful research program.
3.1 Business cycle facts
In the 1970s after the development of dynamic economic theory, it was clear
that something other than the system-of-equations approach was needed if
macroeconomics was to be integrated with the rest of economics. I want to
emphasize that macroeconomics then meant business cycle fluctuations.
Growth theory, even though it dealt with the same set of aggregate economic
variables, was part of what was then called microeconomics, as was the study
of tax policies in public finance.
Business cycles are fluctuations in output and employment about trend.
But what is trend? Having been trained as a statistician, I naturally looked to
theory to provide the definition of trend, with the plan to then use the tools
of statistics to estimate or measure it. But theory provided no definition of
trend, so in 1978 Bob Hodrick and I took the then-radical step of using an
operational definition of trend.
1
With an operational definition, the concept
is defined by the procedure used to determine the value of the concept.
376
1
A shortened version of this 1978 Carnegie Mellon working paper, a copy of which I do not have,
is a 1980 Northwestern University working paper. At the time, this paper was largely ignored
because the profession was not using the neoclassical growth model to think about business cycle
fluctuations. But once the then-young people in the profession started using the neoclassical
growth model to think about business cycles, the profession found the statistics reported in this
paper of interest.
Figure 1. Deviations from Trend of U.S. GDP and Hours.
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377
2
See Stigler’s (1978) history of statistics.
Our trend is just a well-defined statistic, where a statistic is a real valued
function. Hodrick and Prescott’s (1980) trend statistic mimics well the
smooth curve that economists fit through the data. The family of trends we
considered is one-dimensional. The one in the family that we used is the first
one we considered. Later we learned that the actuaries use this family of
smoothers, as did John von Neumann when he worked on ballistic problems
for the U.S. government during World War II.
2
A desirable feature of this
definition is that with the selection of smoothing parameters for quarterly
time series, there are no degrees of freedom and the business cycle statistics
are not a matter of judgment. Having everyone looking at the same set of
statistics facilitated the development of business cycle theory by making
studies comparable.
One set of key business cycle facts are that two-thirds of business cycle
fluctuations are accounted for by variations in the labor input, one-third by
variations in total factor productivity, and virtually zero by variations in the
capital service input. The importance of variation in the labor input can be
seen in Figure 1.
This is in sharp contrast to the secular behavior of the labor input and output,
which is shown in Figure 2. Secularly, per capita output has a strong upward
trend, while the per capita labor input shows no trend.
A second business cycle fact is that consumption moves procyclically; that
is, the cyclical component of consumption moves up and down with the
cyclical component of output. A third fact is that in percentage terms, invest-
Figure 2. Indices of Per Capita Real GDP and Hours.
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ment varies 10 times as much as does consumption. Consequently, invest-
ment variation is a disproportionate part of cyclical output variation. This is
shown in Figure 3.
3.2 Inference drawn from these facts
Now why did economists looking at these facts conclude that they ruled out
total factor productivity and other real shocks as being a significant contributor
to business cycle fluctuations? Their reasoning is as follows. Leisure and
consumption are normal goods. The evidence at that time was that the real
wage was acyclical, which implies no cyclical substitution effects and leaves
only the wealth effect. Therefore, in the boom when income is high, the
quantity of leisure should be high, when in fact it is low. This logic is based on
partial equilibrium reasoning, and the conclusion turned out to be wrong.
In the 1970s a number of interesting conjectures arose as to why the
economy fluctuated as it does. Most were related to finding a propagation
mechanism that resulted in Lucas’s monetary surprise shocks having
persistent real effects. With this theory, leisure moves countercyclically in con-
formity with observations. The deviations of output and employment from
trend are not persistent with this theory, but in fact they are persistent. This
initiated a search for some feature of reality that when introduced gives rise
to persistent real effects. To put it another way, economists searched for what
Frisch called a propagation mechanism for the effects of monetary surprises.
Taylor (1980) and Fischer (1977) provided empirical and theoretical evidence
in support of their conjecture that staggered nominal wage contracting might
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Figure 3. Deviations from Trend of U.S. Consumption and Investment.
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