Wednesday, June 14, 2006

The NAIRU is 4.3%

One problem with using the NAIRU as a guide to policy is that most analyses do not include a useful theory of how and why the NAIRU shifts over time. By now, everyone acknowledges that it does shift. Otherwise the late 1970s and the late 1990s (as experienced by the US) could not have happened in the same country. Unfortunately, the usual way of dealing with these shifts is to treat them as a purely empirical phenomenon. The problem with that approach is that we don’t find out about the shifts until long after they happen.

Here I will make the bold claim to have a useful theory of NAIRU shifts. It’s not a new theory, really, but it has, in my opinion, gotten a lot less attention than it deserves (and as a result, the whole NAIRU concept has gotten more abuse than it deserves). The idea is that inflationary pressure from the labor market is determined by the relationship between the number of unemployed workers and the number of available jobs. In general, the more jobs there are available, the more inflationary a given level of unemployment will be. If only a few firms want to hire, for example, then most firms will not have occasion to raise wages even if the unemployment rate gets quite low.

The specific relationship between unemployment, job vacancies, and inflation can be estimated empirically by including a job vacancy variable in a standard Phillips curve specification. The Phillips curve results can be combined with information about the Beveridge curve – the inverse relationship between unemployment and job vacancies over the business cycle – to provide an estimate of what unemployment rate is consistent with stable inflation, and voila: the NAIRU!

It so happens I’ve done just that. The whole procedure isn’t very fancy, but I think it provides a sensible first cut. My Phillips curve has no control variables. (It does have a third-order polynomial distributed lag on past inflation and a constraint that the coefficients sum to one – the latter necessary to identify the NAIRU.) The proxy for job vacancies is based on a combination of the Conference Board Help Wanted Index and the Monster Employment Index. (I won’t go into the details of how I combine them, but the Conference Board index usually dominates, because newspapers still have the lion’s share of the want ad market.) I use a purely visual process to ascertain the normal slope of the Beveridge curve, because I don’t have time right now for the fancy econometrics needed to estimate a shifting relationship between two noisy variables. (I assume that all shifts in the Beveridge curve are parallel shifts.) I use monthly data going back to 1953.

As expected, both unemployment and job vacancies are highly significant in the Phillips curve. I took a line through the data point for March 2006 to represent the current position of the Beveridge curve. Conclusion: See the title of this post.

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Anonymous Anonymous said...

So what do you think has changed to make the NAIRU lower than it was ?


Wed Jun 14, 05:58:00 PM EDT  
Blogger knzn said...

Regional dispersion of employment growth seems to be a major factor. See this paper from the San Francisco Fed.

The story I would tell – although I don’t have any specific evidence – is about oil. In the 70s and 80s, oil was a more important input in the oil-consuming regions than it is now, and the oil-producing regions were less diversified than they are now. So when the price of oil changed, you would get large shifts in employment. In the 70s there was a lot of labor demand, but it was disproportionately in the Southwest, so the national unemployment rate was still high. In 1986, there was a recession in the Southwest, causing significant unemployment, but the rest of the nation was booming.

Wed Jun 14, 10:03:00 PM EDT  
Anonymous Anonymous said...

And how wide is the 95% confidence interval around your point estimate?

Thu Jun 15, 08:47:00 AM EDT  
Blogger knzn said...

The NAIRU estimate depends on several coefficient estimates (including one that’s purely visual), so calculating an overall confidence interval would involve more difficulty than I currently have time for. The coefficient to which the NAIRU is most sensitive is the constant term in the Phillips curve. The 95% confidence interval for this coefficient implies a range of 2.4% to 6.2% for the NAIRU, admittedly rather wide.

It occurs to me, though, that this Phillips curve probably shouldn’t even include a constant term. Since the assumed inflation process depends on the relationship between unemployment and vacancies, it wouldn’t make sense for the inflation rate to drift systematically when both values are zero. Also, the constant term has a T-statistic less than 1, so removing it raises the adjusted R-squared of the regression.

When I fit without a constant term, I get a NAIRU of 4.0% with fairly narrow confidence intervals. It is most sensitive to the coefficient on the vacancy variable, and the confidence interval implies a range from 3.2% to 4.5%. If I allow all 3 coefficients (unemployment in the Phillips curve, vacancies in the Phillips curve, and the slope of the Beveridge curve, around which I placed a visually guesstimated confidence interval) to vary in their individual confidence intervals, the range for the NAIRU is 2.5% to 5.2%.

Thu Jun 15, 01:09:00 PM EDT  
Blogger spencer said...

It is something of an identity, but the ratio of productivity to real gdp growth has shifted.

From 1960 to 1974 productivity growth was 70% of real gdp growth.

In the low productivity era this fell to only 55% and since 1994 the ratio has risen to 82%s.

Although it is not exact this implies that we have had a shift in the employment growth a given gdp growth generates.

Thu Jun 15, 04:18:00 PM EDT  
Anonymous Anonymous said...

Your idea makes sense, but I think it's a mistake to assume that the entire burden of explanation has to fall on the labor market. There is an even simpler interpretation of NAIRU, one which can accommodate a more flexible analysis. A variety of factors, such as the extent of domestic competition, exchange rates and expectation, impart an inflationary impetus to the economy. Unemployed workers, directly and as a proxy for other excess factor supplies, impart a counter impetus. NAIRU registers the rate of unemployment at which these two exactly offset each other.

I'm all for improvements in specification and measurement. For instance, the unemployment rate, by itself or in conjunction with vacancies, may be an imperfect proxy for labor market slack. (Employment growth, if we could select the right denominator, might be better.) But it strikes me as a serious mistake to rule out all the "group 1" factors (xrate etc.) by assumption.

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