Thursday, January 28, 2016

Back to the 60's Phillips Curve ?

I have been postponing posting this post. Now it is a bit late as it is, I think, strictly inferior to Nick Bunker's post "Context may be everything when it comes to the Phillips curve" which you should probably just read. Both are mainly comments on Olivier Blanchard's Peterson Institute for International Economics policy brief (pdf) "The US Phillips Curve: Back to the 60s? " which itself is largely based on Blanchard Cerutti and Summers (2015) (which he cites).

Blanchard analyzed US unemployment and inflation with a model including time varying parameters and concluded two things. First it appears that inflation expectations are anchored. What this really means is that recent inflation has a small effect on current inflation (Blanchard and Blanchard et al don't attempt to directly measure expectations). Second, the slope of the Phillips curve has declined with large changes in unemployment followed by small changes in inflation. Blanchard stressed that the computer is convinced that the slope declined in the early 90s and that this is not a new great-recession pattern.

I will present some very simple graphs assuming expectations are completely anchored. That is, I will do what old Keynesians are often (incorrectly) accused of doing and ignore fluctuations in expected inflation entirely. The point, as noted by Bunker following Ekaterina V. Peneva and Jeremy B. Rudd, is that the change from the 60s to around now is a reduction of the pass through of labor costs to price inflation. Like Blanchard and BCS, they use a sophisticated time varying parameter model, but the point is simple -- in recent decades wage and price inflation have not moved together.

I think it is worth a blog post to check whether the relationship between unemployment and the increase of nominal labor costs (roughly wage inflation) has changed too. My impression is that it hasn't. I look at two series from FRED

HCOMPBS Business Sector: Compensation Per Hour, Index 2009=100, Quarterly, Seasonally Adjusted

and UNRATE "Civilian Unemployment Rate (UNRATE), Percent, Quarterly, Seasonally Adjusted" with 1950s econometrics, that is scatter plots. awinf is the % rate of increase of HCOMBS over 4 quarters (so the points on the scatter are not independent observations. I pool data from before 1973q1 and after 1985q1, that is back in the good old days and after the Volcker deflation. A 0 next to the dot means data from after 1985q1 and a 1 means data from before 1973q1.

The scatter is scattered. The old and new clouds of points overlap. I think there seems to be a reasonably stable and not shifting long run downward sloping Phillips curve. the main difference between the sub periods is that unemployment has often been very high post 1985.

Here is another scatter using only data from after 1953 so 1953-1972 and then 1985-2015.

For what it's worth, STATA isn't convinced that there has been a statistically significant change since 1973 even though it calculated standard errors ignoring the overlap of the intervals over which labor cost inflation was measured.

Now I look at annual GDP deflator iflation and labor cost inflation (always with overlapping intervals). The scatters look completely different pre 1973 and post 1985

before 1973, the two inflation rates were extremely highly correlated.

After 1985 the (still statistically signficant) correlation was much reduced

It sure seems to me that the change from one period of anchored expectations to another has a lot to do with price setting and not so much to do with wage setting. Given the gigantic changes in the US labor market (roughly the death of trade unions) this is very puzzling.

2 comments:

  1. My maintained hypothesis (though I'm a lot less than 100% committed to it) is that the only thing that changed is that central banks stopped doing as much random stuff and started (at first implicitly) targeting price inflation.

    For example, if you wanted to design an experiment to see if price inflation and wage inflation were correlated, you would ask the central bank to do a lot of big random stuff. With perfect inflation targeting, so that price inflation never changed at all, you would only observe the other things that affected wage inflation.

    For example, if you take your pre 73 scatterplot, and delete all the observations where price inflation was either above 4% or below 0% (which is roughly the range in your post 85 scatterplot), the correlation would look a lot lower.

    And that is setting aside the fact that expected inflation would have much lower correlation with actual inflation post 85 than pre 73. Because post 85 changes in actual inflation would be mostly temporary, while pre 73 changes in actual inflation would be expected to persist, because they did persist.

    If you wanted to measure the correlation between a person's height and weight, restricting your sample to people between 5' 0" and 5' 2" would give you a much lower correlation than a random sample.

    ReplyDelete
  2. I like this. I think the US-changes at the labour market are only relevant for the independent variable, wage-rise. here we must focus on fixprice conduct. There are two facts to considr:
    The PC poured into offices around 1985, and internet came around 2000. It matters for calculation costs and communication costs.
    Along with the increase of the number of brands, the increase of frequency in price changes must have made consumer minds gear in market model.

    You can think of:
    Before 1973 costprice revisions and price revisions were timed by dominant wage changes, which were always there.
    After 1985 material input price changes could also provoke a price change and some wage changes were too small.

    I wish you success with the puzzle.

    ReplyDelete