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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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