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117 Monthly Lab. Rev. 17 (1994)
Seasonality: Economic Data and Model Estimation

handle is hein.journals/month117 and id is 1287 raw text is: Seasonality: economic data
and model estimation
Seasonality is a pattern that more or less repeats itself
each year, although this pattern may drift or change
in amplitude over time; the study of seasonality
also is linked to the study of business cycles

hat is seasonality? This is a surpris-
ingly difficult question, for which there
is no simple answer. At the most basic
level, there is the intuition that seasonality is an
approximately cyclical pattern in a time series
that more or less repeats itself each year. Com-
plicating matters is the possibility that the pattern
will drift or change in amplitude from year to year.
The consensus among economists is that three
basic exogenous factors give rise to seasonality
in economic data. I The first factor is the weather:
temperature, hours of daylight, and the likelihood
of severe storms. All change somewhat predict-
ably with the calendar and affect the costs of
doing many types of business. Second, predict-
able and regular calendar events, such as Christ-
mas, the Federal tax payment deadline on April
15, and the Independence Day holiday, affect
production and consumption decisions. Third,
social conventions have an impact on the timing
of certain activities. For example, families with
school-aged children time their vacations with
the school calendar.
Businesses and consumers smooth over or
heighten these exogenous factors as they plan
their activities. For instance, a firm might time a
shutdown for retooling to accommodate the va-
cation plans of employees. In response, the firm's
suppliers and customers also might shut down at
that time, causing what amounts to a seasonal
slump in the industry.
In addition, changes in production techniques
or preferences can accentuate or diminish sea-
sonal patterns. For example, improvements in
transportation between the Northeast and Cali-

fornia might dampen seasonal patterns in pro-
duce prices in the Northeast.
Why bother with seasonality?
Historically, the study of seasonality has been
tied to the study of business cycles. The busi-
ness cycle is a pattern of boom and bust that is
apparent in economic data over long periods,
particularly in measures of output. A typical busi-
ness cycle lasts about 48 months, although a cycle
may extend for as little as 2 years or as long as 8
years. Predicting business cycles, or even deter-
mining where we are in a particular cycle, is
important to business and government. As a re-
sult, many analysts use current data to make in-
ferences about changes in the overall economy.
The aim is to identify changes in the trend of
economic activity from movements in certain
indicators, such as data on prices or interest rates,
or some other index of economic activity that is
reported very frequently.
In this context, a seasonal pattern can compli-
cate inferences about the business cycle. For ex-
ample, industrial production drops significantly
in the first quarter of the year, whether the
economy is in an expansion or a recession. Ana-
lysts must judge whether a first-quarter dip is
caused by seasonal factors that will disappear
next quarter or whether the decline is a signal of
a change in the business cycle from boom to bust.
Decisions such as whether to hire additional
workers and whether to invest in new plant and
equipment will depend on a correct reading of
the causes of economic changes.
Monthly Labor Review  December 1994  17

Ted Jaditz
Ted Jaditz is an economist
in the Office of Prices and
Living Conditions, Bureau
of Labor Statistics.

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