The following is based on work by Minneapolis Fed visiting scholars
Andrew Atkeson and Lee E. Ohanian, both professors of economics at the
University of California, Los Angeles. Their paper
appears in the Winter 2001 Quarterly Review, published by the
Minneapolis Fed's Research Department.
We've all been there: Stuck in a relationship that's going nowhere.
What was once so special now seems empty and lifeless. The spark
has faded, the magic's gone. And so it isaccording to a new
analysis by Minneapolis Fed visiting scholarswith the Phillips
curve, a line that described the relationship between unemployment
and inflation. Once upon a time ...
Birth of a notion
In 1958, New Zealand economist A.W. Phillips published "The Relation
Between Unemployment and the Rate of Change of Money Wage Rates in the
United Kingdom, 1861-1957." The paper examined nearly a century's
worth of data and found a striking inverse correlation between wage inflation
and unemployment rates, a relationship summarized by the eponymous curve,
showing that in Britain, high rates of unemployment were seen at times
of low wage inflation, and vice versa.
The data were clear and the relationship seemed to make sense:
When unemployment is high, workers tend to be less aggressive in
pushing for higher pay. Conversely, when the job market is tight,
employers have to promise higher wages to draw workers. As Phillips
"When the demand for labour is high and there are very few unemployed,
we should expect employers to bid wage rates up quite rapidly, each
firm and each industry being continually tempted to offer a little above
the prevailing rates to attract the most suitable labour from other
firms and industries."
Higher wages could in turn lead to more inflation, both directly
through their impact on the costs of production and indirectly by
raising incomes, leading consumers to bid up the price of products.
The Phillips curvesupported and elaborated by Paul Samuelson,
Robert Solow and other prominent economistsquickly became
economics gospel and, among other uses, was employed by policymakers
to predict future inflation on the basis of current unemployment.
Challenging the curve
But Milton Friedman, Edmund Phelps, Robert Lucas and other economists
didn't buy it. The simplistic linking of inflation and unemployment, they
argued, didn't make sense on a theoretical level. What matters to both
workers and employers in making decisions about supplying and demanding
labor are real (inflation-adjusted) wages, not nominal wages, said the
Phillips curve critics. If workers expect inflation of a certain level,
they'll implicitly calculate their purchasing power and supply labor accordingly.
The same is true for employers estimating the real costs of hiring more
workers. So while some people might make a few short-term employment changes
on the basis of nominal wage changes, in the long-run the labor market
will adjust to real wage conditions, independent of inflation.
These theorists argued that the predictive ability of a simple
Phillips curve is further limited because people's expectations
about inflation change under different economic conditions, so a
reliable or stable relationship between rates of inflation and unemployment
is unlikely. Significant productivity increases or price declines
in imports, for example, alter perceptions about inflation and unemployment,
making it unwise to assume that relationships that obtained before
will work in the future.
Indeed, the economic conditions of the 1970s brought about stagflationwith
simultaneous high unemployment and high inflationand provided
evidence that the simple Phillips curve wasn't quite as reliable
a guide as once thought.
Improved conventional wisdom
To cope with these theoretical and practical objections but still preserve
what they perceived as a kernel of truth, Phillips curve advocates suggested
a more complex version. The new model posited that an economy tends to
have a natural rate of unemployment at which annual price increases are
steadythat is, inflation is a constant. If unemployment drops below
this natural rate, the rate of inflation will increase. If unemployment
moves above the natural rate, the inflation rate will decline.
According to this new understanding, a high rate of unemployment
(above the natural rate) isn't linked to low inflation, per se,
but to a decrease in the inflation rate (below whatever it is when
unemployment is at its natural rate). That natural unemployment
rate came to be known by the accurate, if ungainly, term nonaccelerating
inflation rate of unemployment (NAIRU), and the new model linking
unemployment rates and changes in inflation rates was called a NAIRU
No one had an exact measure of the nonaccelerating rate, and it
seemed clear that the rate could change if economic conditions varied
(in fact, reducing labor market rigidities could theoretically lower
the NAIRU), but in recent times the NAIRU Phillips relationship
has replaced its predecessor, becoming the new-and-improved conventional
wisdom about unemployment/inflation linkages.
Indeed, during the 1990s and on into the new century, as unemployment
rates have dropped and stayed low, both economists and policymakers have
shown their implicit faithand fearthat inflation will soon
return. They warn of "overheating" the economy-conjuring images
of a boiler set to explode, unleashing the scalding wrath of inflation.
The stock market, too, seems to believe in NAIRU (or believes that the
Fed does), regularly greeting news of rising wages or dropping unemployment
with plunges in stock prices, as analysts fear the Fed will pull in the
economy's reins by raising interest rates to stem "inevitable"
A closer look
This abiding faith in a stable link between unemployment and inflation
is the subject of close empirical scrutiny in Andrew Atkeson and Lee Ohanian's
paper in the Winter 2001 edition of the Quarterly Review. In "Are
Phillips Curves Useful for Forecasting Inflation?" the Minneapolis
Fed visiting scholars point out that many academics and government officials
still hold close to some version of an inflation/unemployment relationship,
and that Phillips curve analysis continues to carry substantial weight
in Federal Open Market Committee (FOMC) inflation forecasts. Their task
was to evaluate whether data support the use of such a tool. Is some version
of the Phillips relationship still magic?
Atkeson and Ohanian first look at the classic Phillips curve relationship,
seeing if the data fit the original Phillips theory. They analyze
U.S. data on inflation and unemployment in two different time periods,
from 1959 to 1969 and then from 1970 to 1999. In the earlier time
span, the 1960s, they find that, indeed, there is a clear negative
relationship between the unemployment rate at a given point in time
and inflation over the next four quarters: a classic Phillips curve
similar to that seen in the British data for the preceding century.
But their scatter plot of unemployment and subsequent inflation data
for the next 30 years shows virtually no correlation (see Chart 1). Apparently,
whatever relationship existed in the 1960s had disappeared. "Moreover,"
note the authors, "any inflation forecast for post-1970s data based
on the 1960s [data] clearly would be inaccurate." The classic Phillips
curve is dead. Q.E.D. R.I.P.
Chart 1 The Breakdown in an Early Phillips Curve
Quarterly Unemployment as a Percentage of the U.S. Labor Force
vs. Changes in the Implicit Price Deflator for U.S. GDP Over the
Next Four Quarters, 1st Quarter 1959-1st Quarter 1999
Long live the curve
Well, that was too easy. After all, Friedman, et al., had already undercut
the theoretical basis of the simple Phillips curve. And stagflation sent
it to an early empirical grave. But what about the more sophisticated
version? Atkeson and Ohanian take a similar graphical look at a NAIRU
Phillips curve, plotting the unemployment rate against changes
in the subsequent inflation rateessentially asking whether a high
unemployment rate can predict not low inflation, but a decrease in inflation.
Here again they look at the data for two different time periods, from
1960 to 1983, and then from 1984 to 1999.
In the early time span, they find, there is a negative relationship
between unemployment and subsequent changes in inflation. Specifically,
the data indicate that when unemployment is about 6 percent, the
inflation rate will neither rise nor fallthe NAIRUbut
if unemployment drops to 5 percent, inflation is forecast to rise
0.6 of a percentage point over the following year. (Note that this
isn't saying prices will rise 0.6 percent, but that the inflation
rate itself4 percent, 7 percent, whatever it might bewill
increase by 0.6 of a percentage point.)
But over the following 15-year time spanour recent historythe
data show very little relationship. In a graphical description,
the line that best fits the data points has flattened out, meaning
that large changes in unemployment in this later time period forecast
very little change in inflation. So, while an unemployment rate
of 4 percent in the early time span would have led to a prediction
of a 1 point increase in inflation, a similar unemployment rate
in more recent years would forecast just a one-quarter point increase
(see Chart 2).
Chart 2 A Shift in the Textbook NAIRU Phillips Curve
Quarterly Unemployment as a Percentage of the U.S. Labor
Force vs. Difference Between Change in the Implicit Price Deflator
for U.S. GDP Over the Next Four Quarters and Its Change Over the
Previous Four Quarters,
1st Quarter 1960-1st Quarter 1999
Things have changed, evidently, to make the measurable relationship
between these variables so different in one time period compared
with the other. Atkeson and Ohanian indicate that lower volatility
in the business cycle, monetary policy and inflation since the 1980s
might have altered the economic environment sufficiently to weaken
the unemployment/inflation change link and diminish the predictive
power of the NAIRU Phillips curve.
Putting NAIRU to the test
To an econometrician, this begs a question: Is the underlying relationship
"stable" enough, can we depend upon it, to serve as an accurate
predictor of inflation in the current economic environment? The graphs
indicate that the relationship is not as strong as once it was, but is
it strong enough to be useful?
The litmus test that Atkeson and Ohanian use is straightforward. A given
forecasting model will be considered useful if it can do a better job
of forecasting inflation than simply predicting that next year's inflation
rate will be the same as last year's. If a complex model can't outdo this
simple "rear-view mirror," then it's not worth the computer
They apply the test to three different variations of the NAIRU
Phillips curve over the 1984-1999 period, seeing statistically if
any of them do a better job of predicting inflation than simply
projecting forward last year's inflation. They look at: (1) a textbook
NAIRU Phillips curve that says that changes in inflation are proportional
to the previous year's unemployment rate, (2) a more sophisticated
NAIRU Phillips curve that incorporates lagged values of unemployment
and inflation rates as well as present values and (3) a still more
complex NAIRU Phillips curve that tries to forecast changes in inflation
using a broad economic index incorporating 85 indicators of economic
activity. (They also try out several different inflation measuresthe
consumer price index (CPI), the "core" CPI, which excludes food
and energy, and a price deflator for personal consumption expendituresto
see if the Phillips curve variations are better at forecasting one
or another measure of inflation.)
The authors find that the simple rearview mirror does basically
just as well or better than the three NAIRU Phillips curve variations.
In fact, the rearview model is 88 percent more accurate than the
textbook NAIRU curve, at least 4 percent better than the activity
index model and essentially just as good as the unemployment rate
version. In other words, the models aren't at all useful for forecasting
inflation. A policymaker trying to guess at next year's inflation
rate could come up with an equally good estimate simply by looking
at last year's inflation rate. Why hire an economist?
Atkeson and Ohanian then take the bull by the horns, examining inflation
forecasts produced by staff of the Federal Reserve System's Board of Governors.
While acknowledging that complex econometric models are only one of a
number of inputs used by Fed staff in constructing the inflation forecasts
that appear in their Greenbook reports prepared for FOMC meetings, Atkeson
and Ohanian emphasize that the models are again based on a NAIRU Phillips
curve relationship. So they subject the Greenbook forecasts to the same
test: Does the Fed model do a better job at predicting inflation than
the simple rearview mirror?
Because the Greenbooks are not made public for several years, the
researchers can analyze Greenbook forecasts only from 1984 to 1996,
not the full period used in the previous tests, but again they find
that the Fed model does no better (and no worse) than their litmus
test. Comparing inflation rate predictions to actual inflation rates
for both forecasting models reveals that the complicated NAIRU Phillips
curve econometrics used by the Fed's Board of Governors has no real
inflation-predicting edge over a naive glance at the past year's
inflation rate. The ratio of prediction errors for the Fed and naive
models is 1.01basically, they do equally well.
The bottom line
So what should economists and policymakers conclude from this? One clear
implication is that existing Phillips curve-based forecasting models simply
don't work in the current economic environment. "For the last 15
years," say the authors, "economists have not produced a version
of the Phillips curve that makes more accurate inflation forecast than
those from a naive model."
Does that imply that more effort should go into building a better model,
a more sophisticated, insightful forecasting tool that can hone in on
the proper variables that will illustrate the underlying though elusive
unemployment/inflation link? Atkeson and Ohanian say no. Enough is enough.
Theorists and applied economists have looked high and low for a stable
relationship between the two, but whatever link once existedin Phillips'
British data or America's 1960s economy, for exampleno longer obtains,
and further efforts are likely to be fruitless. "The search for yet
another Phillips curve-based forecasting model," they conclude, "should
The Phillips curve magic that once seemed to give policymakers a clear
signpost is now gone. Time to move on.