Ben S Bernanke: Inflation expectations and inflation forecasting
Remarks by Mr Ben S Bernanke, Chairman of the Board of Governors of the US Federal
Reserve System, at the Monetary Economics Workshop of the National Bureau of Economic
Research Summer Institute, Cambridge, Massachusetts, 10 July 2007.
The original speech, which contains various links to the documents mentioned, can be found on the US Federal Reserve
System's website.
* * *
I would like to thank Christina Romer and David Romer for giving me the chance to address
participants in the Summer Institute, sponsored by the National Bureau of Economic
Research (NBER). As an academic, I regularly attended the Summer Institute and presented
or commented on research here. I also served for a time as the director of the Monetary
Economics group, the position now shared by David and Christina. The informal nature of the
institute, the large number of talented people in attendance, and the opportunity to hear
about the very latest work in the field - often while in early draft form - made these few
weeks each summer one of the most stimulating times of the year for me. In my current
position, I am keenly aware of the long history of fruitful interaction between economists
inside and outside of central banks, and I am eager to see this interaction continue. This
ongoing intellectual exchange, by improving our understanding of the economy and the
workings of monetary policy, has had and will continue to have sizable benefits.
Today I will offer a few remarks on the relationships among monetary policy, inflation, and
the public's expectations of inflation, focusing - as seems appropriate for this audience - on
some important open questions. I will also give a short overview of the way the Federal
Reserve Board staff forecasts inflation, including some discussion of how the staff
incorporates information about expected inflation into its forecasting process.
As you know, the control of inflation is central to good monetary policy. Price stability, which
is one leg of the Federal Reserve's dual mandate from the Congress, is a good thing in itself,
for reasons that economists understand much better today than they did a few decades ago.
Inflation injects noise into the price system, makes long-term financial planning more
complex, and interacts in perverse ways with imperfectly indexed tax and accounting rules.
In the short-to-medium term, the maintenance of price stability helps avoid the pattern of
stop-go monetary policies that were the source of much instability in output and employment
in the past. More fundamentally, experience suggests that high and persistent inflation
undermines public confidence in the economy and in the management of economic policy
generally, with potentially adverse effects on risk-taking, investment, and other productive
activities that are sensitive to the public's assessments of the prospects for future economic
stability. In the long term, low inflation promotes growth, efficiency, and stability - which, all
else being equal, support maximum sustainable employment, the other leg of the mandate
given to the Federal Reserve by the Congress.
Admittedly, measuring the long-term relationship between growth or productivity and inflation
is difficult. For example, it may be that low inflation has accompanied good economic
performance in part because countries that maintain low inflation tend to pursue other sound
economic policies as well. Still, I think we can agree that, at a minimum, the opposite
proposition - that inflationary policies promote employment growth in the long run - has been
entirely discredited and, indeed, that policies based on this proposition have led to very bad
outcomes whenever they have been applied.
Inflations expectations - conceptual frameworks
Undoubtedly, the state of inflation expectations greatly influences actual inflation and thus
the central bank's ability to achieve price stability. But what do we mean, precisely, by "the
state of inflation expectations"? How should we measure inflation expectations, and how
should we use that information for forecasting and controlling inflation? I certainly do not
have complete answers to those questions, but I believe that they are of great practical
importance. I hope my remarks here will stimulate some of you to work on these issues.
What is the right conceptual framework for thinking about inflation expectations in the current
context? The traditional rational-expectations model of inflation and inflation expectations has
been a useful workhorse for thinking about issues of credibility and institutional design, but,
to my mind, it is less helpful for thinking about economies in which (1) the structure of the
economy is constantly evolving in ways that are imperfectly understood by both the public
and policymakers and (2) the policymakers' objective function is not fully known by private
agents. In particular, together with the assumption that the central bank's objective function is
fixed and known to the public, the traditional rational-expectations approach implies that the
public has firm knowledge of the long-run equilibrium inflation rate; consequently, their
longrun inflation expectations do not vary over time in response to new information.
But in fact, as I will discuss in more detail later, long-run inflation expectations do vary over
time. That is, they are not perfectly anchored in real economies; moreover, the extent to
which they are anchored can change, depending on economic developments and (most
important) the current and past conduct of monetary policy. In this context, I use the term
"anchored" to mean relatively insensitive to incoming data. So, for example, if the public
experiences a spell of inflation higher than their long-run expectation, but their long-run
expectation of inflation changes little as a result, then inflation expectations are well
anchored. If, on the other hand, the public reacts to a short period of higher-than-expected
inflation by marking up their long-run expectation considerably, then expectations are poorly
anchored.
Although variations in the extent to which inflation expectations are anchored are not easily
handled in a traditional rational-expectations framework, they seem to fit quite naturally into
the burgeoning literature on learning in macroeconomics. The premise of this literature is that
people do not have full information about the economy or about the objectives of the central
bank, but they instead must make statistical inferences about the unknown parameters
governing the evolution of the economy. In a learning context, the concept of anchored
expectations is easily formalized in a variety of ways; in general, if the public is modeled as
being confident in its current estimate of the long-run inflation rate, so that new information
has relatively little effect on that estimate, then the essential idea of well-anchored
expectations has been captured.
Allowing for learning has important implications for how we think about the economy and
policy. For example, some work has shown that the process of learning can affect the
dynamics and even the potential stability of the economy (see, of many possible examples,
Bullard and Mitra, 2002). Considerations of how the public learns about the economy affect
the form of optimal monetary policy (Gaspar, Smets, and Vestin, 2006). Notably, in a world
with rational expectations and in which private agents are assumed already to understand all
aspects of the economic environment, talking about the effects of central bank
communication would not be sensible, whereas models with learning accommodate the
analysis of communication-related issues quite well (Orphanides and Williams, 2005;
Bernanke, 2004). Macroeconomic models with learning also give content to the idea of an
economy moving gradually from one regime to another, particularly if the central bank as well
as the public is assumed to be updating its beliefs. For example, if the central bank and the
public learn from experience that high inflation imposes greater costs and fewer benefits than
previously thought, then the equilibrium will adjust toward one with lower inflation and lower
inflation expectations. This line of explanation of how economies move between monetary
regimes, which has been explored by Sargent and others, strikes me as quite plausible as a
historical description (Sargent, 1999). In sum, many of the most interesting issues in
contemporary monetary theory require an analytical framework that involves learning by
private agents and possibly the central bank as well.
Implications of anchored inflation expectations
Why do we care about the variability of inflation expectations? As my colleague Rick Mishkin
recently discussed, the extent to which inflation expectations are anchored has first-order
implications for the performance of inflation and of the economy more generally (Mishkin,
2007). Mishkin illustrated this point by considering the implications of the fact that inflation
expectations have become much better anchored over the past thirty years for the estimated
coefficients of the conventional Phillips curve, which I define here to encompass
specifications that use lagged values of inflation to proxy for expectations or other sources of
inflation inertia. As he noted, many studies of the conventional Phillips curve find that the
sensitivity of inflation to activity indicators is lower today than in the past (that is, the Phillips
curve appears to have become flatter);1 and that the long-run effect on inflation of "supply
shocks," such as changes in the price of oil, also appears to be lower than in the past
(Hooker, 2002). These findings are of much more than academic interest. To the extent that
the Phillips curve may have flattened, inflation will now tend to be more stable than in the
past in the face of variations in aggregate demand. (Of course, this can be a good thing or a
bad thing, depending on whether inflation expectations are anchored in the vicinity of price
stability.) Likewise, a lower sensitivity of long-run inflation to supply shocks would imply that
such shocks are much less likely to generate economic instability today than they would
have been several decades ago. Notably, the sharp increases in energy prices over the past
few years have not led either to persistent inflation or to a recession, in contrast (for
example) to the U.S. experience of the 1970s.
Various factors might account for these changes in the Phillips curve, but, as Mishkin pointed
out, better-anchored inflation expectations - themselves, of course, the product of monetary
policies that brought inflation down and have kept it relatively stable - certainly play some
role. If people set prices and wages with reference to the rate of inflation they expect in the
long run and if inflation expectations respond less than previously to variations in economic
activity, then inflation itself will become relatively more insensitive to the level of activity - that
is, the conventional Phillips curve will be flatter.
Similar logic explains the finding that inflation is less responsive than it used to be to changes
in oil prices and other supply shocks. Certainly, increases in energy prices affect overall
inflation in the short run because energy products such as gasoline are part of the
consumer's basket and because energy costs loom large in the production of some goods
and services. However, a one-off change in energy prices can translate into persistent
inflation only if it leads to higher expected inflation and a consequent "wage-price spiral."
With inflation expectations well anchored, a one-time increase in energy prices should not
lead to a permanent increase in inflation but only to a change in relative prices. A related
implication is that, if inflation expectations are well anchored, changes in energy (and food)
prices should have relatively little influence on "core" inflation, that is, inflation excluding the
prices of food and energy.
Although inflation expectations seem much better anchored today than they were a few
decades ago, they appear to remain imperfectly anchored. A number of studies confirm that
observation. For example, Gürkaynak, Sack, and Swanson (2005) found that long-run
inflation expectations, as measured by the difference in yields between nominal and
inflationindexed bonds, move in response to news about the economy, rather than remaining
unaffected. Levin, Natalucci, and Piger (2004) have shown that some survey measures of
inflation expectations in the United States respond to recent changes in the actual rate of
inflation, which would not be the case if expectations were perfectly anchored. Models of the
term structure of interest rates better fit the data under the assumption that both inflation
expectations and beliefs about the central bank's reaction function are evolving (Kozicki and
Tinsley, 2001; Rudebusch and Wu, 2003; Cogley, 2005).
An indirect but elegant way to make the point that inflation expectations remain imperfectly
anchored comes from a statistical analysis of inflation by Stock and Watson (2007). Stock
and Watson model inflation as having two components, which may be interpreted as the
trend and the cycle. Changes in the trend component are highly persistent whereas shocks
to the cyclical component are temporary.2 The key finding of this research is that the
variability of the trend component of inflation (and thus the share of the overall variability of
inflation that it can explain) appears to have fallen significantly after about 1983. That is,
unexpected changes in inflation are today much more likely to be transitory than they were
before the early 1980s. Because it seems quite unlikely that changes in inflation could persist
indefinitely unless long-run expectations of inflation also changed, I interpret the
StockWatson finding as consistent with the view that inflation expectations have become much
more anchored since the early 1980s. At the same time, that the variability of the trend
component of inflation, though modest, remains positive, implies that long-run expectations
of inflation are not perfectly anchored today.
The policy implications of the much-improved but still imperfect anchoring of inflation
expectations are not at all straightforward. To evaluate these implications, we must
understand better the historical variation in inflation expectations, the effect of this variation
on actual inflation and economic activity, and the relationship between policy actions and the
formation of inflation expectations. With the hope of promoting progress on these broad
topics, I pose three questions to researchers, the answer to any of which would be quite
useful for practical policymaking.
First, how should the central bank best monitor the public's inflation expectations?
Theoretical treatments tend to neglect the fact that in practice many measures of inflation
expectations exist, including the forecasts of professional economists, results from surveys of
consumers, information extracted from financial markets such as the market for
inflationindexed debt, and limited information on firms' pricing plans. In a very interesting paper,
Mankiw, Reis, and Wolfers (2003) compared the available measures, emphasizing in
particular that median measures of inflation expectations often obscure substantial
crosssectional dispersion of expectations.3 On which measure or combination of measures should
central bankers focus to assess inflation developments and the degree to which expectations
are anchored? Do we need new measures of expectations or new surveys? Information on
the price expectations of businesses - who are, after all, the price setters in the first instance
- as well as information on nominal wage expectations is particularly scarce.
Second, how do changes in various measures of inflation expectations feed through to actual
pricing behavior? Promising recent research has looked at price changes at very
disaggregated levels for insight into the pricing decision (Bils and Klenow, 2004; Nakamura
and Steinsson, 2007). But this research has not yet linked pricing decisions at the
microeconomic level to inflation expectations; undertaking that next step would no doubt be
difficult but also very valuable.
Third, what factors affect the level of inflation expectations and the degree to which they are
anchored? Answering this question essentially involves estimating the learning rule followed
by the public or various components of the public, although one could consider alternative
frameworks like Carroll's (2003) epidemiological model of the propagation of information
among private agents. A fuller understanding of the public's learning rules would improve the
central bank's capacity to assess its own credibility, to evaluate the implications of its policy
decisions and communications strategy, and perhaps to forecast inflation. Realistically
calibrated models with learning would also inform our thinking about policy and the economy.
Inflation forecasting at the Federal Reserve
I would like to shift gears at this point to tell you a bit about how the Federal Reserve Board
staff goes about forecasting inflation. Obviously, this activity provides critical inputs into the
making of monetary policy, and as I will discuss, the staff's long-term track record in
forecasting inflation is quite good by any reasonable benchmark. I hope that my brief
description will stimulate your interest in the complex and challenging problems of real-time
macroeconomic forecasting. But, as you will see, the discussion of practical inflation
forecasting will bring us back to one theme of my remarks - that our ability to forecast
inflation and predict how inflation will respond to policy actions depends very much on our
capacity to measure and to understand what determines the public's expectations of inflation.
The Board staff employs a variety of formal models, both structural and purely statistical, in
its forecasting efforts. However, the forecasts of inflation (and of other key macroeconomic
variables) that are provided to the Federal Open Market Committee are developed through
an eclectic process that combines model-based projections, anecdotal and other
"extramodel" information, and professional judgment. In short, for all the advances that have been
made in modeling and statistical analysis, practical forecasting continues to involve art as
well as science.
The forecasting procedures used depend importantly on the forecast horizon. For near-term
inflation forecasting - say, for the current quarter and the next - the staff relies most heavily
on a disaggregated, bottom-up approach that focuses on estimating and forecasting price
behavior for the various categories of goods and services that make up the aggregate price
index in question. For example, we know from historical experience that the prices of some
types of goods and services tend to be quite volatile, including not only (as is well known) the
prices of energy and some types of food but also some "core" prices such as airfares,
apparel prices, and hotel rates. The monthly autocorrelations of price changes in these
categories tend to be low or even negative. In contrast, changes in inflation rates in some
services categories, such as shelter costs, tend to be more persistent. In assessing what
price changes in a particular category imply for future price changes in that category, the
staff uses not only various forms of time-series analysis but also specialized knowledge
about how the various indexes are constructed - for example, whether certain categories are
sampled every month in all localities and how seasonal adjustments are performed. In
making very near-term price forecasts, the staff also uses diverse information from a variety
of sources, such as surveys of prices of gasoline and other important items, news reports
about price-change announcements, and anecdotal information from our business contacts.
Conceptually, one might think of this effort to distinguish transitory from persistent price
changes as a more nuanced way of estimating the underlying inflation trend, analogous to
the trend measures provided by more mechanical indicators such as trimmed-mean or
weighted-median inflation rates.
An accurate forecast of very near-term inflation is important not only for its own sake but also
because it provides a better "jumping-off point" for the longer-term forecast. Because inflation
continues to exhibit some inertia, improved near-term forecasts translate into more-accurate
longer-term projections as well.
For forecasting horizons beyond a quarter or two, detailed analyses of individual price
components become less useful, and thus the staff's emphasis shifts to inflation's
fundamental determinants. Food and energy inflation are forecasted separately from the
core, using information from futures prices and other sources. However, forecasts of core
inflation must take into account the extent to which food and energy costs are passed
through to other prices.
To project core inflation at longer-term horizons, the staff consults a range of econometric
models. Most of the models used are based on versions of the new Keynesian Phillips curve,
which links inflation to inflation expectations, the extent of economic slack, and indicators of
supply shocks. Despite the common conceptual framework, the model specifications
employed differ considerably in their details, including how lagged inflation enters the
equation, how resource utilization is measured, and whether a survey-based measure of
inflation expectations is included. In principle, formal econometric tests could determine how
much weight should be put on the forecast of each model, but in practice the data do not
permit sharp inferences; moreover, estimated forecasting equations may not reflect
information about special factors affecting the outlook. Because of these considerations, as I
have already noted, the staff's inflation forecasts inevitably reflect a substantial degree of
expert judgment and the use of information not captured by the models.
Another reason for the reliance on judgment in the forecasting process is the practical
requirement that the forecast for inflation be consistent with the staff's overall view of the
economy, including the forecasts for key economic variables such as wages, interest rates,
and consumption spending. Achieving this consistency requires a thoughtful understanding
of why sectoral forecasts may be at odds and how best to reconcile those differences. Again,
in principle, consistency of sectoral forecasts could be ensured by estimating the inflation
equation as part of a general equilibrium system. Indeed, considerable progress has been
made in recent years, at the Board and elsewhere, in developing dynamic stochastic general
equilibrium (DSGE) models detailed enough for policy application. These models have
become increasingly useful for policy analysis and for the simulation of alternative scenarios.
They are likely to play a more significant role in the forecasting process over time as well,
though, like other formal methods, they are unlikely to displace expert judgment.
A potential drawback of the simple Phillips curve model for analyzing and forecasting inflation
is that it does not explicitly incorporate the possible influence of labor costs on the inflation
process. The Board's large macroeconomic simulation model, known as FRB/US, projects
inflation through a system approach that captures the interaction of wage and price
determination. Interestingly, however, the system approach does not seem to forecast price
inflation as well as single-equation Phillips curve models do. This weaker performance
appears to reflect, at least in part, the shortcomings of the available data on labor
compensation. The two principal quarterly indicators of aggregate hourly compensation are
the employment cost index (ECI) and nonfarm compensation per hour (CPH). Both are
imperfect measures of the labor costs relevant to pricing decisions. For example, the ECI's
fixed employment and occupation weights may not reflect changes in the labor market, and
the ECI excludes stock options and similar forms of payment. CPH is volatile, perhaps in part
because it measures stock options at exercise rather than when granted, and it is subject to
substantial revisions. Moreover, these two hourly compensation measures often give
contradictory signals. Despite these problems, labor market developments certainly influence
how the staff and policymakers view the inflation process and inflation risks, illustrating yet
another point in the forecasting process at which judgment must play an important role. In
particular, in evaluating labor-market conditions and trends in labor costs, the staff takes note
of a wide range of data, anecdotes, and other qualitative information as well as the official
data on compensation.
Overall, the Board staff's inflation forecasting has been remarkably good, at least compared
with the available alternatives (Romer and Romer, 2000; Sims, 2002). To cite a recent study,
Faust and Wright (2007) show that real-time staff forecasts of inflation reliably outperform
statistical benchmarks at all horizons and that this advantage is not solely the result of the
staff's expertise at estimating near-term inflation rates.
To link this discussion of forecasting to the first portion of my remarks, I turn to the treatment
of inflation expectations in staff forecasts. As I noted earlier, while inflation expectations
doubtless are crucial determinants of observed inflation, measuring expectations and
inferring just how they affect inflation are difficult tasks. A popular shortcut is to include
lagged inflation terms in the Phillips curve equation; besides being a convenient means of
capturing the inertial component in inflation, the estimated coefficients on lagged inflation
almost certainly reflect to some degree the formation of inflation expectations and their
influence on the inflation process. However, using lagged inflation as a proxy for inflation
expectations has drawbacks, notably its susceptibility to the Lucas critique.4 The staff
consequently analyzes a number of survey measures of inflation expectations. One question
in choosing among measures of expectations is whether to focus on measures of short-term
inflation expectations (say, twelve months ahead) or of longer-term expectations (five to ten
years ahead). Generally, measures of longer-term inflation expectations, such as the
five-toten-year expected inflation measures from the Michigan/Reuters survey of households and
from the Survey of Professional Forecasters, seem to be better gauges of the expectations
that influence wage- and price-setting behavior.
The staff also looks at measures derived from comparing yields on nominal and
inflationindexed Treasury securities (the breakeven inflation rate). Measures of inflation
compensation derived from the market for inflation-indexed securities are influenced by
changes in inflation risk premiums and liquidity premiums, and analyses are constrained by
the fact that these markets have been operating in the United States for only a relatively
short period. Nevertheless, unlike survey measures, breakeven inflation rates are determined
in a market in which investors back their views with real money. Moreover, breakeven
measures of inflation expectations provide information on the expectations of a different
group of agents - financial-market participants - which can be compared with the views of
economists and consumers as represented by surveys.
Measurement is only one aspect of understanding inflation expectations. We also need a
better understanding of how inflation expectations affect actual inflation and of the factors
that determine inflation expectations. I will say a few words about the latter issue in the
context of the practical problems of forecasting and policy analysis faced by the staff of the
Federal Reserve Board.
Model-based simulations of the inflation process are useful tools for both forecasting and
policy analysis. In conducting such simulations, the analyst must specify how inflation
expectations are formed - in particular, how they react to actual changes in the economy and
in policy. In most simulations of the FRB/US model, the public is assumed to update its
inflation projections based on the historical relationship between inflation and other key
economic variables. Essentially, this approach assumes that the public updates its inflation
expectations in a sensible way based on economic developments but does not assume that
the public has full knowledge of the underlying model of the economy, consistent with the
structure of learning models (Brayton and others, 1997).
Recent staff work at the Board has analyzed the implications of expanding the set of
variables allowed to influence the public's long-term inflation expectations to include, among
others, the federal funds rate.5 If the public's long-term inflation expectations are influenced
directly by Fed actions, as this specification suggests, a number of interesting implications
follow. One is that the output costs of disinflation may be lower than those suggested by
reduced-form-type Phillips curves. Intuitively, if the Fed attempts to disinflate by raising the
federal funds rate, the disinflationary effect will be felt not only through the usual output gap
channel but also through a direct restraint on long-term inflation expectations. This
interpretation is consistent with some analyses of the Volcker disinflation; although the costs
of that disinflation were high, they were perhaps less than economists would have predicted
in advance, given conventional estimates of the sacrifice ratio (Erceg and Levin, 2003).
To be sure, this and similar analyses remain speculative. A good deal more must be done
before such work proves a reliable basis for policy choices. Nevertheless, I hope this
example illustrates for you the theme of my remarks, that a deeper understanding of the
determinants and effects of the public's expectations of inflation could have significant
practical payoffs.
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