In addition to the general caution against using past data for projecting future conditions (and the need for equally spaced time intervals mentioned above), the particulars of time series data require additional attention to some special issues.
Inflation and Constant Dollars
Any time series that deals with dollars (or yen, pounds sterling, wampum, or other forms of currency) must confront the fact that the value of money changes over time. If you are simply making a time series showing the shrinking value of the dollar, that’s fine — it’s what you want to show — but if you want to show something else (say, changes in wages or home prices), then you will need to correct your data to some common base. Usually this is done by starting with a base year (often the start or end of the series, or the “current” year) and adjusting values based on changes to some official inflation statistic (e.g., the consumer price index).1
Growth and Change to the Underlying Population
Over time — especially over long periods — the population of a place can change quite a lot, both in terms of overall numbers and the demographic components. As with inflation, this may be precisely the change that you are interested in observing and predicting (as in the first examples in this chapter), but at times it can introduce a spurious or intervening variable into your analysis.