Published: 2013-09-06

Exploring the Phillips Curve

I'm taking a course on data visualization this semester and our first project was pretty simple: find some data on the Bureau of Labor Statistics web site and visualize it using some kinda of scatter plot to support a hypothesis. We also have to make use of a best-fit line. Of course there are a number of principles to think about, but that's not important.

Having a background in economics, BLS data was in my wheelhouse, so to speak. I pondered a suitable hypothesis and settled on demonstrating the presence of the Phillips Curve in actual BLS data. The Phillips Curve is essentially a theory that says that the unemployment and inflation rates are negatively correlated. In other words, if you push unemployment down through some sort of policy, inflation will rise.

Of course, like so many economic theories, there is debate as to whether the Phillips Curve actually exists or not. But I'm not trying to get this published or anything, so whatever.

Several (non-academic) articles I found online dealt with the Phillips Curve in an overly simplistic manner. The procedure appeared to be: plot the data since 1948, draw a line through it, judge the theory based on the slope of the line. The problem with this is that, without going into too much detail, the curve can move around, up, down, left, right. This happens (at least in theory) in response to changes in variables other unemployment and inflation.

This means that over a sufficiently wide range of time the data will end up looking like a cloud of points, with no particular pattern at all.

It occurred to me that breaking the data into smaller ranges, during each of which other variables could be expected to stay relatively constant, would be a helpful start. As it turns out, this yields some nifty results, seen below.

Phillips Curve Data

The plot above highlights the data points approximately by decade. Note, for instance, the dark blue cluster in the upper right, they appear to form a curve that is convex to the origin, just as they theory says they should.

As interesting as this plot is, there is a ton of information here. In order to make better sense of it, I decided to create a small, interactive, web app with R and Shiny. The app lets you subset the data by year and cluster into different size groups. You can also adjust the time lag (the assumed time between the change in unemployment and the subsequent change in inflation, or vice versa).

Take a look and feel free to play around with it and decide whether you think the Phillips Curve really exists!

Exploring the Phillips Curve