Suppose you had just an hour to teach the basics of
macroeconomics, what relationship would you be sure to include? My answer would
be the Phillips curve. With the Phillips curve you can go a long way to
understanding what monetary policy is all about.
My faith in the Phillips curve comes from simple but highly
plausible ideas. In a boom, demand is strong relative to the economy’s capacity
to produce, so prices and wages tend to rise faster than in an economic
downturn. However workers do not normally suffer from money illusion: in a boom
they want higher real wages to go
with increasing labour supply. Equally firms are interested in profit margins,
so if costs rise, so will prices. As firms do not change prices every day, they
will think about future as well as current costs. That means that inflation
depends on expected inflation as well as some indicator of excess demand, like
unemployment.
Microfoundations confirm this logic, but add a crucial point
that is not immediately obvious. Inflation today will depend on expectations
about inflation in the future, not expectations about current inflation. That
is the major contribution of New Keynesian theory to macroeconomics.
This combination of simple and formal theory would be of little
interest if it was inconsistent with the data. A few do periodically claim just
this: that it is very hard to find a Phillips curve in the data. (For example here is Stephen Williamson talking about
Europe - but see also this from László Andor claiming just the
opposite - and this from Chris Dillow on the UK.) If this was
true, it would mean that monetary policymakers the world over were using the
wrong framework in taking their decisions.
So is it true? The problem is that we do not have good data
series going back very far on inflation expectations. Results from estimating
econometric equations can therefore vary a lot depending how this crucial
variable is treated. What I want to do here is just look at the raw data on
inflation and unemployment for the US, and see whether it is really true that
it is hard to find a Phillips curve.
The first chart plots consumer price inflation (y axis) against
unemployment (x axis), where a line joins one year to the next. We start down
the bottom right in 1961, when inflation was about 1% and unemployment 6.7%.
Over the next few years we get the kind of pattern Phillips originally
observed: unemployment falls and inflation rises.
The problem is that with inflation rising to 5.5% in 1969, it
made sense for agents to raise their expectations about inflation. (In fact
they almost surely started doing this before 1969, which may give the line from
1961 to 1969 its curvature. For given expectations, the line might be quite
flat, a point I will come back to later.) So when unemployment started rising
again, inflation didn’t go back to 1%, because expected inflation had risen.
The pattern we get are called Phillips curve loops: falling unemployment over
time is clearly associated with rising inflation, but this short run pattern is
overlaid on a trend rise in inflation because inflation expectations are rising.
Of course the other thing going on here is that we had two oil price hikes in
1974 and 1979. The chart finishes in 1980.
Most economists agree that things changed in 1980, as Volker
used monetary policy aggressively to get inflation down. The next chart plots
inflation and unemployment from 1980 to 2000.
Inflation came down from 13.5% in 1980 to 3.2% in 1983 partly
because unemployment was high, but also because inflation expectations fell
rapidly. (We do have survey evidence showing this happening.) The remaining
period is dominated by a large fall in unemployment. So why didn’t this fall in
unemployment push inflation back up? In terms of the chart, why isn’t the 2000
point much higher? Again expectations are confusing things. One survey has inflation
expectations at around 5% in 1983, falling towards 3% at the end of 1999. So
inflation was being held back for that reason. A Phillips curve, and its loops,
is still there, but pretty flat.
The final chart goes from 2000 to 2013. Note that the inflation
axis has changed - it now peaks at 4.5% rather than 16%. The interesting point,
which Paul Krugman and others have noted, is that this looks much more like
Phillips’s original observation: a simple negative relationship between
inflation and unemployment. This could happen if expectations had become much more anchored as a result of credible
inflation targeting, and
survey data on expectations do suggest this has happened to some extent. There
are also important changes in commodity prices happening here too.
While the change in inflation scale allows us to see this more
clearly, it hides an important point. Once again the Phillips curve is pretty
flat. We go from 4% to 10% unemployment, but inflation changes by at most 4%.
However from the previous discussion we can see that this is not necessarily a
new phenomenon, once we allow for changing inflation expectations.
Is it this data which makes me believe in the Phillips curve?
To be honest, no. Instead it is the basic theory that I discussed at the
beginning of this post. It may also be because I’m old enough to remember the
1970s when there were still economists around who denied that lower
unemployment would lead to higher inflation, or who thought that the influence
of expectations on inflation was weak, or who thought any relationship could be
negated by direct controls on wages and prices, with disastrous results. But
given how ‘noisy’ macro data normally is, I find the data I have shown here
pretty consistent with my beliefs.
