The Fed, Presidential Elections, and Coincidence – Part 6
Over the past few days I’ve had a few posts looking at whether the Fed acts to improperly influence elections. Last night, that included this post looking at real M2 per capita and changes in real GDP per capita. So far, a pattern has been developing in these posts… factors the Fed has some control over (real M2 per capita, the Fed Funds rate) seem to always loosen up when an incumbent is running for office if that incumbent is from the same party as the Fed. These same factors tend to tighten up when an incumbent is running for office if that incumbent is from a different party from the Fed. Additionally, the pattern observed does not seem to be in reaction to changes in the economy, at least as measured by real GDP per capita. In fact, movements in real GDP per capita around these elections seem to reflect changes in the real M2 per capita (or fed funds rate).
Today’s post is not where I intended to go next. (I’m hoping to have a look at the ten year rate next. I expect it to behave a bit differently – the Fed has less control over that, after all so the pattern I’m expecting is different.) But in response to reader dilbert dogbert’s question, the table below shows the real M1 per capita in the various months through the year. As with the other graphs, I have color coded the fastest growing and slowing growing months in each category, and as before, there is a solid column of orange (least favorable to growth) and a solid column of green (most favorable to growth), and the columns are precisely where they are in the other series.
The interesting thing for me is that M1 tends to be negative throughout the sample, except in years in which a “friendly” incumbent is running for re-election. Society has been using less cash per person, once you adjust for inflation, since 1959 (when the sample begins). The use of other instruments – credit cards, for instance, seems to be making cash less important… except right before a friendly incumbent is running for re-election.
One more interesting thing… columns 1 and 2 might be negative, just like column 3. But notice the difference in magnitude of the numbers. This is not something that is attributable to randomness. And as we’ve already seen before, its not attributable to the Fed reacting to the economy either. So what else is there? At some point, we move beyond the realm of coincidence.
Monthly M1 and M2
Quarterly population data which I then linearized into monthly
Quarterly real GDP per capita
As always, let me know if you want my spreadsheet.