For release on delivery
10:00 p.m. EDT (7:00 p.m. PDT)
March 31, 2023
The Unstable Phillips Curve
Remarks by
Christopher J. Waller
Member
Board of Governors of the Federal Reserve System
at
Macroeconomics and Monetary Policy, a conference sponsored by
the Federal Reserve Bank of San Francisco
San Francisco, California
March 31, 2023
Thank you, Sylvain, and thank you to the Federal Reserve Bank of San Francisco
for inviting me to speak tonight. After listening to many dinner speakers through the
years, I am well aware that after the entrees are served, no one wants to hear someone
blabber for 45 minutes. So, I will try to keep this short to leave enough time for a robust
discussion afterward, which I hope my remarks will generate.
My topic tonight is "The Unstable Phillips Curve."1 This is not intended to be a
deep academic analysis but rather to present some thoughts for discussion. I know that I
am walking into the Phillips curve lion's den, given the number of researchers in the Bay
Area who work on Phillips curve estimation. But in my current job, I am used to people
disagreeing with me.
The Phillips curve, a relationship between price or wage inflation and some
measure of economic slack, has been the foundation of monetary policy for decades. A
common way to estimate it is to look at output price inflation and the unemployment rate.
One theory, or story, is that as aggregate demand increases, labor demand will increase as
well. As a result, prices of goods and services will rise and firms will hire more workers,
as long as there is some stickiness in nominal wages. Consequently, this story implies
that the unemployment rate will fall. So, there is a negative relationship between price
inflation and unemployment.
Another story, based on the New Keynesian model, is that monopolistically
competitive firms set prices for some period of time. Firms may have "sticky prices"
because of menu costs. That is, firms face costs to adjust their prices and so choose to
reset their prices only when the benefits outweigh the costs. Because firms are not
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identical, only a share of firms adjust their prices each period. So, when aggregate
demand increases, firms with set prices agree to supply the goods demanded at their
current prices. Firms that find it worthwhile to adjust their prices will increase their
prices. As a result, inflation will arise from the firms that adjusted their prices.
Meanwhile, higher employment will come from the sticky price firms, and, implicitly,
higher employment goes along with lower unemployment. Once again, we obtain a
negative relationship between output price inflation and unemployment. The slope of
this relationship hinges on the fraction of firms adjusting their prices in response to the
aggregate demand shock. Put another way, the frequency of price changes determines
the slope of the Phillips curve.
In both these stories, expectations of future inflation play a critical role. In the
sticky nominal wage story, workers will seek to maintain their real wages by setting their
wage demands based on what they think future inflation will be. In the New Keynesian
model, firms set their output prices based on what they think aggregate price inflation
will be in the future, and how often and at what pace they expect to change prices.
Regardless of whether you think nominal wages are sticky or output prices are sticky,
inflation expectations play a critical role in how unemployment responds to changes in
the inflation rate.
This explanation is all about the short run. In either model, in the long run,
nominal rigidities, or stickiness, disappear and expectations of inflation converge to trend
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inflation. As a result, in most models of nominal rigidities the long-run Phillips curve is
vertical.2
What do economic data tell us about this relationship? We all know that if you
simply plot inflation against the unemployment rate over the past 50 years, you get a
blob. There does not appear to be any statistically significant correlation between the two
series. In the 1980s and 1990s, so-called freshwater macroeconomists, who tended to
work at universities in the middle of the country, argued the data showed that stories
about nominal wage or price stickiness were simply wrong and we should quit talking
about Phillips curves of any type. Diehard believers in the Phillips curve, the saltwater
economists working on the East and West coasts, argued that the data blob was the result
of unstable inflation expectations. If inflation expectations were not stable, then the
Phillips curve would shift around in such a way that you could not observe the true
relationship in the data.
What would cause inflation expectations to be unstable? Kydland and Prescott
(1977) provided an explanation, later popularized by Barro and Gordon (1983), that
blamed the central bank. If the central bank's promises to keep inflation low were not
credible, then private agents' inflation expectations would be different than what the
central bank promised, which in turn would cause the Phillips curve to shift around. As a
result, the idea that the central bank had to make credible promises to keep inflation low
became a bedrock principle of central banking that holds to this day.
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Inflation targeting provided a framework for making promises of low inflation
credible, and since the late 1990s it has proved to be very successful in practice. With a
central bank strongly committed to inflation targeting, promises to keep inflation at 2
percent are credible in large part because the central bank is observed taking action to
keep it near 2 percent, regardless of what is happening to the unemployment rate. When
these promises are credible, the Phillips curve should be relatively flat.
What have we seen in the recent data? Let's consider a Phillips curve based on
the price index for personal consumption expenditures, which is the Federal Open Market
Committee's (FOMC) preferred measure. As shown in figure 1, the Phillips curve was
very flat for the 20-plus years before the pandemic, consistent with the story that the
Federal Reserve was credible at keeping inflation low.3
Then in the spring of 2021, after more than a decade of hibernation, inflation
came roaring back to life. As the economy recovered from the pandemic shutdowns,
inflation increased each month of the year and was running at more than double the Fed's
2 percent target throughout the latter half of 2021. Meanwhile, unemployment fell quite
rapidly in 2021, from 6.3 percent at the start of the year to 3.9 percent in December,
which was surprising given the long, slow recoveries after recent recessions. Based on
the flatness of the Phillips curve in recent decades, some commentators argued that
unemployment would have to rise dramatically to bring inflation back down to 2 percent.
Others argued that, based on analysis of the Beveridge curve, inflation could be brought
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down without a significant rise in unemployment, although this conjecture was not
without controversy.4
But considering the data for 2021, as shown in figure 2, the Phillips curve
suddenly looked relatively steep. That is, the labor market became extremely tight as the
U.S. economy emerged from pandemic lockdowns. Figure 3 shows that since January
2022, the Phillips curve is essentially vertical: The unemployment rate has hovered
around 3.6 percent, and inflation has varied from 7 percent (in June) to 5.3 percent (in
December).
The recent experience raises the question: What happened to the Phillips curve
that it is acting so differently now than in the pre-pandemic period? Freshwater
macroeconomists would once again argue that this difference shows the Phillips curve is
a statistical anomaly and should not be used as a foundational element guiding monetary
policy. Having grown up in the profession surrounded by freshwater macroeconomists, I
am very sympathetic to this argument.
But setting that view aside for now, let's consider the two other possible stories
I've mentioned to explain the data. The first story relies on inflation expectations
becoming unanchored and causing the short-run Phillips curve to shift around. This
theory is illustrated in figure 4. There is a vertical long-run Phillips curve anchored at
U*, which is the rate of unemployment that occurs in the absence of price stickiness, and
realized inflation is equal to inflation expectations. And there is a downward sloping
short-run Phillips curve that shows a tradeoff between inflation and unemployment due to
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some nominal price or wage stickiness in the economy. The short-run Phillips curve
assumes a given level of inflation expectations. If inflation expectations increase, the
short-run Phillips curve shifts up. So, if inflation expectations have increased in recent
history, we would move from a lower to a higher Phillips curve, as shown by the vertical
shift up in the dots. These shifting dots generate what, on the surface, looks like an
essentially vertical Phillips curve, thereby matching the 2022 data.
The second possible explanation follows from the New Keynesian Phillips curve
where there is a sudden increase in the frequency of price changes.5 In that model, the
slope of the Phillips curve is determined by the frequency of price changes-the more
often prices change, the steeper is the Phillips curve. This dynamic is illustrated in figure
5. An increase in the frequency of price changes steepens the short-run Phillips curve
even if inflation expectations are well anchored at 2 percent. If in recent years the
frequency of price changes has increased, we would move from a flatter to a steeper
short-run Phillips curve. On the surface, moving from the blue to red dot, it again looks
like an essentially vertical Phillips curve, but just as in the first story, the data are
showing us points on different Phillips curves.
What does this suggest about the relationship between inflation and labor market
slack and the implications for monetary policy? The answer depends on data about
inflation expectations and the frequency of output price changes. Let's look at each of
these factors.
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Figure 6 reproduces two charts on inflation expectations from the Federal
Reserve's March 2023 Monetary Policy Report.6 The charts show that the behavior of
inflation expectations depends on the data one uses to measure those expectations.7 The
left panel reports survey-based measures, while the right panel captures market-based
inflation expectations over a variety of time horizons.
On the left, we see that shorter-run inflation expectations followed observed
inflation up and down in recent years, with a notable increase in 2021 before reversing
course in 2022 and into early 2023. But inflation expectations over a longer horizon
remained within the range of values seen in the years before the pandemic and appear
broadly consistent with the FOMC's longer-run 2 percent inflation objective. Similarly,
in the right panel, market-based measures of longer-term inflation compensation are also
broadly in line with readings seen in the years before the pandemic. So, overall,
measures of longer-term inflation expectations have remained contained, while shorter-
term expectations had moved up in 2021 and have partially reversed their earlier
increases. These data suggest that changes in inflation can be associated with an
unanchoring of inflation expectations if we believe price-setting behavior is influenced
by changes in shorter-term inflation expectations.
Let's now look at the data on the frequency of output price changes in 2021 and
2022. Preliminary work by Montag and Villar Vallenas (2023) uses U.S. Consumer Price
Index micro-data to examine about 90,000 individual prices each month and determines
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if there was a change and, if so, was the change an increase or decrease. Figure 7
summarizes their findings. The monthly price change frequency (the black line)
increased from about 10 percent of the sample in 2019 to around 20 percent by the end of
2021 and held around that level in 2022. The increase in price change frequency is
primarily driven by firms upwardly adjusting their prices (the red dashed line) during this
period. Furthermore, anecdotal evidence I have received from market contacts is
consistent with the view that firms were quicker to change prices over 2021-22 than they
were in the previous decade. So, hard and soft data suggest that the frequency of price
changes is contributing to what looks like a steep Phillips curve in recent years.
Other than providing for a fun academic discussion, what does this analysis mean
for monetary policy makers? If unanchored inflation expectations were driving what
looks like a shifting Phillips curve, this would be extremely problematic for central
bankers because it could require dramatic actions by the FOMC to lower inflation
expectations to shift the Phillips curve back down. In current circumstances, one would
need to believe it is shorter-term expectations that matter for price setters. If this belief is
true, I take some comfort in the fact that short-term inflation expectations have moved
down reasonably fast over the past year. However, I am not sure how much weight to put
on this story.
The higher-frequency-of-price-changes story is a more encouraging guide for
central bankers. A steep Phillips curve means inflation can be brought down quickly
with relatively little pain in terms of higher unemployment. Recent data are consistent
with this story.
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To conclude, it may not surprise you all that I like story number two a lot better.
But we will need more data to conclude which story is right-which is what a data-
dependent central bank does to implement appropriate monetary policy. With that, I will
stop talking, and I look forward to a robust discussion with lots of good arguments telling
me I am wrong.
References
Robert J. Barro, David B. Gordon. A Positive Theory of Monetary Policy in a
Natural Rate Model, Journal of Political Economy, Vol. 91, No. 4 (Aug. 1983), pp. 589-
610.
Aleksander, Berentsen, Guido Menzio and Randall Wright (2011). Inflation and
Unemployment in the Long Run, American Economic Review, Vol. 101, No. 1, (Feb.
2011), pp. 371-98.
Olivier Blanchard, Alex Domash and Lawrence H. Summers. Bad News for the
Fed from the Beveridge Space, Peterson Institute for International Economics, Policy
Briefs, 22-7, July 2022.
Andrew Figura and Christopher Waller. What Does the Beveridge Curve Tell Us
About the Likelihood of a Soft Landing? FEDS Notes, July 29, 2022.
Milton Friedman. Nobel Lecture: Inflation and Unemployment, Journal of
Political Economy, Vol. 85, No. 3 (June 1977), pp. 451-472.
Yuriy Gorodnichenko. Why Did We Miscast Inflation? Panel discussion, US
Monetary Policy Forum, (Feb. 2023)
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Robert Hall. A Major Shock Makes Prices More Flexible and May Result in a
Burst of Inflation or Deflation, NBER Working Paper No. 31025, March 2023.
Finn Kydland and Edward Prescott. Rules Rather than Discretion: The
Inconsistency of Optimal Plans, Journal of Political Economy, Vol. 85, No. 3 (June
1977), pp. 473-492
Hugh Montag and Daniel Villar Vallenas. Price-Setting in the Covid Era.
https://www.aeaweb.org/conference/2023/program/powerpoint/ZkzNkh7Q
The Unstable Phillips Curve
Christopher J. Waller
Member
Board of Governors of the Federal Reserve System
Remarks at
Macroeconomics and Monetary Policy
A conference sponsored by
the Federal Reserve Bank of San Francisco
March 31, 2023
The views expressed here are my own and do not reflect those of the Board of Governors or the Federal Open Market
Committee.
Figure 1
Figure 2
Figure 3
Figure 4 - Unanchored Inflation Expectations
(%)
Rate
ππe=4%
Inflation
ππe=3%
ππe=2%
Figure 5 - Frequency of Price Changes
ππe=2%
(%)
ππe=2%
Rate
Inflation
2%
iiiiiiiiiiiiiiiiiiii ppiiiippii ppccciicciicc
iiiiiiiiiiiiiiii ppiiiippii ppccciicciicc
Figure 6 - Inflation Expectations
Source: Board of Governors of the Federal Reserve System, Monetary Policy Report, March 3, 2023.
https://www.federalreserve.gov/monetarypolicy/files/20230303_mprfullreport.pdf
Figure 7 - Frequency of Price Changes
0.25 10
9
0.20 8
7
0.15 6
5
Percent
Fraction
0.10 4
3
0.05 2
1
0.00 0
Price Increases Price Decreases Price Changes CPI inflation
Note. CPI is consumer price index.
Source: Montag and Villar Vallenas (2023)