Working with Time Series Data

Lags, Leads, Differences, and Summations

When working with time series data, you sometimes need to refer to the values of a series in previous or future periods. For example, the usual interest in the consumer price index series shown in previous examples is how fast the index is changing, rather than the actual level of the index. To compute a percent change, you need both the current and the previous values of the series. When you model a time series, you might want to use the previous values of other series as explanatory variables.

This section discusses how to use the DATA step to perform operations over time: lags, differences, leads, summations over time, and percent changes.

The EXPAND procedure can also be used to perform many of these operations; see ChapterĀ 15: The EXPAND Procedure, for more information. See also the section Transforming Time Series.