This post is part of the special series Vehicle Sales 1976-2010.
Every month Calculated Risk posts the graph of monthly light-vehicle sales. The sales are usually presented as the seasonally adjusted annual rate (SAAR) reported by the BEA. The reason for the adjustment is a strong seasonality in sales which make it difficult to see underlying trends in the short-term. These numbers are suitable for comparison from month to month or even year-over-year, but I found them unsuitable for looking at longer-term trends. To remedy this, I decided to find some different ways of looking at the data to try to get a better look at long term trends in light vehicle sales and hopefully gain some insight as to plausible future outcomes.
To begin, let's consider some of the factors that affect light-vehicle sales:
Vehicle-ownership is harder to define. The Federal Highway Administration publishes a series of statistics every two years that includes the number of registered vehicles and the number of licensed drivers. The series is slightly out of date right now, but I believe it should be updated in 2011. The series is limited in various ways; for example, numbers are rounded to the millions and vehicles registered are not broken down into separate categories by use (a motorcycle, a garbage truck, a school bus and my mom's Matrix are all counted as a motor vehicle). Additionally, a vehicle does not necessarily belong to a licensed owner, or even an individual, and not every licensed individual drives. Despite this, I believe that the numbers will be useful in identifying long-term trends, even if they lack precision.
It is hard to determine the current lifespan of an automobile. We can find an approximation by looking at the mean age of automobiles, which gives us an idea of the lifespan of past models, but this isn't very reliable. New models may have longer or shorter life than past models, and things like wage levels affect the potential lifespan of vehicles--if labor is expensive, fixing and maintaining older automobiles becomes less economically attractive. Additionally, economic conditions affect how often people look for new cars.
I will hopefully have time in the future to extract more precise figures from archived reports, but the task is time-consuming and I am skeptical about it's added value (e.g. buses and motorcycles only accounted for 0.41% of the total fleet in 2008). Many the series were split-up recently and many of the numbers are only available from PDF reports from which the data must be re-entered into a spreadsheet to be usable.