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The Role of Anecdotal Information in
Fed Policymaking
Century Club Breakfast
Olin School of Business
Washington University in St. Louis
St. Louis, Missouri
February 13, 2002

T

here was a time when the Federal
Reserve encouraged a public perception of the mystique of policymaking.
That is not the Fed’s view today, but my
reading of press commentary suggests that the
old perception has not disappeared. There is,
however, a difference. Today, rather than referring to the mystique of policy, people are more
likely to refer to policy as “obtuse,” “incomprehensible,” or “deliberately confusing.” Chairman
Greenspan sometimes takes delight in saying
such things as “Senator, if you understand what
I just said I must have made a mistake.”
Although mystique has turned into fodder
for cartoonists, and it is healthy that we smile at
ourselves from time to time, there is a serious
issue involved. Beginning about 35 years ago,
developments in macroeconomic theory began to
make clear that the performance of the economy
depends critically on market expectations about
how economic policymakers will act in the future.
As our understanding of these issues has deepened, it has become clear that one of the key
dimensions of a successful monetary policy is
that the policymakers need to have well-defined
goals and a clear plan as to how they will go about
achieving the goals. Both of these need to be
understood in the markets; otherwise, the economy faces the equivalent of a broken play in football, where some members of a team think one
play is being run and others think another play
is being run.

Despite the jokes about Fed policy, I think
few people today have any doubt about the Fed’s
objectives. Policymakers emphasize and reemphasize the importance of achieving low and stable
inflation and that the Fed will act to the full extent
of its powers, consistent with that objective, to
cushion fluctuations in income and employment.
Financial markets understand that the Fed is prepared to act decisively in times of national emergency and financial market distress, as evidenced
by Fed actions in response to the terrorist attacks
last September 11, to the Russian default and near
collapse of Long Term Capital Management in the
late summer and fall 1998, and the stock market
panic in 1987.
My aim this morning is to illuminate a part
of the policy process that is, I believe, not very
well understood—the use of informal, or anecdotal, information in the policy process. I’ll discuss the nature of this information and how we
use it. I’ll start, though, by outlining the role of
formal data.
Before proceeding, I want to emphasize that
the views I express here are mine and do not
necessarily reflect official positions of the Federal
Reserve System. I thank my colleagues at the
Federal Reserve Bank of St. Louis for their assistance and comments, especially Howard Wall,
Research officer, but I retain full responsibility
for errors.
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MONETARY POLICY AND INFLATION

THE ROLE OF FORMAL DATA
AND ITS PITFALLS
To avoid misunderstanding, I must begin by
emphasizing that the basic picture of the economy
comes from the formal data published by statistical agencies. Among other things, the data include
the national income accounts; labor market statistics on employment, unemployment and related
measures; price and wage statistics; industrial
production and capacity utilization; financial
market statistics on monetary variables, interest
rates, security prices and banking markets; and
international trade and capital flows. We have
available similar data on economies around the
world.
Our basic knowledge of the economy depends
on the formal data. We use these data in our econometric models. Formal data have many advantages. We know the statistical procedures by which
the data are created and have historical records,
well back into the 19th century in many cases,
from which we can study regularities of economic
behavior.
I like to think of informal data as providing
insight into the formal data. The insight runs
across several dimensions, including timeliness
and potential measurement and even conceptual
errors in the formal data.
Consider timeliness. When making monetary
policy decisions, members of the Federal Open
Market Committee (FOMC) need to know as much
as possible about current and future economic
conditions. Unfortunately, the formal data on
which we rely lag current economic conditions.
For example, the Fed has an incomplete picture
of the economy’s two most important indicators,
growth and inflation. The Bureau of Economic
Analysis releases formal estimates of gross domestic product (GDP) with lags of a month or more.
Moreover, the data are subject to frequent and
major revisions. Price indexes also are produced
with a lag and are sensitive to factors that may
be temporary, such as fluctuating energy prices,
and measurement error. Given these problems, it
is easy to see how monetary policymaking has
often been likened to driving a car with a blackedout windshield and fogged-up side windows.
2

To get an idea of the scale of the difficulty of
using formal data, let’s take a look at the timeliness
and uncertainty of estimates of GDP, the most
comprehensive measure of economic conditions.
Just over two weeks ago, the advance GDP estimate
was released, indicating that real GDP had risen
at an annual rate of 0.2 percent in the fourth
quarter of 2001. About two weeks from now we
will see preliminary GDP estimates for the fourth
quarter and a month after that we will see final
estimates.
Since 1978, two-thirds of the revisions
between the advance estimate and the final estimate of real quarterly growth were between –0.6
and 0.9 percentage points. This means that the
likely range of the final estimate of fourth-quarter
real GDP growth—which we won’t see until the
end of this quarter—is between minus 0.4 and
plus 1.1 percent. To compound the problem, the
so-called final estimate isn’t the last estimate.
Every summer, in July or August, the final estimates are revised and every three years we get
major revisions. Since 1978, latest estimates have
differed from final estimates by an average of 1.2
percentage points in either direction. Thus, the
latest estimate for 1980, say, changes over time.
As a consequence, economists like to say that
history is never what it used to be! In principle,
the estimates keep getting better as the statisticians find improved source data, refine estimation methods, and improve underlying concepts.
When one considers the enormous task of
estimating the size of the U.S. economy, these
problems might seem small. But, for making monetary policy decisions, they can make a critical
difference. In fact, the range of uncertainty over
growth rates can imply opposite short-run monetary policy responses. Given the uncertainty, it is
often best for policymakers to sit tight, waiting
for the uncertainty to be resolved by new information and revised data. What this means, obviously, is that sometimes it is clear in hindsight
that policy action should have come sooner, or
even in a different direction.
Of course, official growth and inflation data
are not all that we have to go on. Most financial

The Role of Anecdotal Information in Fed Policymaking

data are very up-to-date, and futures markets
allow us to peer into the future—or at least into
markets’ expectations of the future. In addition,
some real economic data, such as initial unemployment claims, auto and steel production, and
electricity consumption, are available every week.
Because these data are used to construct the official GDP estimates, they can provide partial pictures of current-quarter GDP.
Other data are used as leading or coincident
indicators. Economists and analysts rely on past
patterns of these indicators to provide insight into
the current business cycle phase. Average weekly
hours in manufacturing are a leading indicator
because firms tend to adjust work hours before
increasing or decreasing their workforce. Nonagricultural employment is a coincident indicator because it tends to rise and fall with GDP. In
addition, some data are used to identify turning
points in the economy. For example, many analysts
follow the ratio of inventories to sales because it
has tended to peak at the same time that the economy is in a trough.
While the Fed relies heavily on formal data
and sophisticated statistical methods for analyzing the data, staff and policymakers alike spend
a lot of time collecting and using anecdotal information that we gather from an extensive network
of contacts. This anecdotal information helps us
to see what is going on in the economy almost as
it is happening. Also, because it is collected from
the people who are actually making day-to-day
business decisions, it helps us to understand why
trends in the data are occurring.
For the rest of this talk I am going to discuss
the role that anecdotal information plays in Fed
policymaking. I will outline the ways in which
we gather this information and then describe the
various ways that we use it. I will also discuss
briefly some recent evidence that anecdotal information adds value beyond what we get from other
sources. And finally, I will touch on some of the
dangers and pitfalls of relying too heavily on
anecdotal information.

HOW WE OBTAIN ANECDOTAL
INFORMATION
The Fed gathers its anecdotal information
from a wide range of sources. Directors of the
Federal Reserve Banks and their Branches provide
written economic reports of conditions in their
regions. Reserve Bank presidents and economists
travel around their Districts meeting with business
people and bankers discussing conditions in their
industries. Reserve Banks maintain a network of
industry contacts who are contacted on a regular
basis in advance of FOMC meetings.
We make additional effort to maintain contacts
in bellwether industries, such as freight and transport, whose activity is closely related to total
economic activity. We also pay close attention to
the real estate industry, where the level of activity
might be a good indicator of the confidence that
people have in the future. After all, for most people the purchase of a home is the largest financial
commitment that they will ever make. If they are
willing to continue buying homes when the
economy is slowing, as has been true recently,
they must be reasonably confident about their
personal economic outlook.
In addition, our eyes and ears are always
open, looking for emerging economic trends. A
well-known example of this hands-on approach
is that the president of the Minneapolis Fed has
been known to make regular visits to local shopping malls to count the cars in the parking lots. I
routinely make a number of phone calls to business contacts before FOMC meetings. I seek specialized information highly dependent on current
circumstances. For example, during one of my
trips after September 11, I struck up a conversation with a Southwest flight attendant and learned
that the airline was continuing to hire and train
new flight attendants. That information reinforced
what I knew from press reports, that Southwest
was not cutting flights and had an optimistic
view of the future.
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MONETARY POLICY AND INFLATION

HOW WE USE ANECDOTAL
INFORMATION
The vast amount of anecdotal information
collected throughout the Federal Reserve System
is used for a variety of purposes. Most systematically, it is used to produce the “Summary of
Commentary on Current Economic Conditions”—
commonly known as the Beige Book—which is
published two weeks before every FOMC meeting.
To produce the Beige Book, each Federal Reserve
Bank gathers information about its District through
a network of contacts. The 12 District reports are
collected together by an assembling Bank, whose
staff prepares the national summary of economic
conditions. The Beige Book, by the way, is available on the web site maintained by the Board of
Governors.
The anecdotal information collected makes
its way into FOMC meetings, where Fed governors and Reserve Bank presidents present their
views on the economic outlook. In addition to
their use in assessing the state of the economy,
the anecdotes might be used to illustrate a point,
thus adding impact to the comments. For example,
a Bank president could say that “the market for
construction material in my District continues to
be tight and prices are rising.” Or, he could say
the same thing and add, “The situation is so tight
that we have had reports of truckloads of drywall
being hijacked.” The addition of the anecdote
(which happens to be an actual one from another
District) adds more to the report than could several charts or tables.
Anecdotal information also can be used to
confirm or to help understand ongoing trends
that arise from the formal data. For example, during the late 1990s, the unemployment rate fell
well below what many people thought was the
level where inflation would start to take off. If
we had relied only on the formal data, the Fed
might have overlooked what firms and workers
were doing to drive down the unemployment
rate and how they were responding to tight labor
markets. For example, we learned from our contacts in businesses that companies were willing
to leave positions unfilled rather than bid aggres4

sively for labor. My interpretation of this information was that firms were convinced that inflation
would remain low and that they dared not let
wage costs increase, because they were unlikely
to be able to recover those costs in higher prices.
For a specific example, the owner of a manufacturing firm in Louisville told us how he was
able to expand employment and production even
though most of his traditional workforce—primeaged men—were already employed. This challenge
led him to rethink his production process to make
it a better match for the workers that were available to him. The result was that, whenever possible, his production methods were changed to
reduce the requirement for physical strength.
We heard many similar stories about how
firms were providing basic skills, making their
work schedules more flexible, providing transportation for their workers, and so forth, to cope
with the rapidly changing nature of their workforce. Without this first-hand knowledge of firms’
ability to respond to competitive challenges and
new environments, the Fed might not have known
that unemployment could keep falling, at least
for a time, without inflation being ignited.
Our network of contacts is also useful to
identify emerging trends. For example, well in
advance of it actually occurring, we had a good
idea that firms’ health insurance premiums would
increase at double-digit rates in 2001. We knew
this increase was coming before it appeared in
official data because our contacts told us in mid2000 about the health insurance contracts they
were signing for 2001.
Another good example of anecdotal information came from one of our Branch directors who
noted in the summer of 2000 that loan demand
at his bank was falling and that other firms in his
area were beginning to experience problems. This
information was important because, at the time,
the economy was growing rapidly and nearly all
forecasts indicated that rapid growth would continue. Nevertheless, reports of this sort continued
to surface throughout the rest of 2000 and into
2001, helping the Fed to get ahead of the recession
by starting to lower its federal funds rate target

The Role of Anecdotal Information in Fed Policymaking

early last year, even though official GDP data
available at the time suggested that the economy
was still going strong.
While most of the anecdotal information collected by the Fed is used to supplement other
information at our disposal, for some one-time
events, the anecdotal reports become the primary
source of information. In these instances, standard
data are not reliable guides because history has
not recorded a pattern for how the economy is
likely to respond. An example of such an event
was the series of terrorist attacks on September 11,
which had immediate and dramatic economic
consequences, although we had no history to use
to predict what these consequences might be.
Nonetheless, we were able to use our network of
contacts to get a good idea of the sectors that were
affected the most, weeks before any formal data
were available.
We found out very quickly that the Fed’s
injection of liquidity into the banking system had
been successful, in that few banks reported having liquidity problems despite the near-complete
shutdown of financial markets. We also found
that retail sales came to a halt in the two to three
days after the attacks but surged back to nearnormal levels by the weekend, that manufacturers
in the District were anticipating that they would
be reducing their output by an average of 10 percent, and that auto sales for the period might be
down by as much as 50 percent. Within a few
weeks, our contacts told us that auto sales in
October were in fact strong, in response to the
zero-interest financing incentive offered by auto
manufacturers. All of this information was vital
in the weeks immediately following the attacks,
when the Fed had to react very quickly while
navigating the uncharted waters of September
and October. Indeed, based on anecdotal reports
and experience, but without any substantial
amount of formal data applying to the period
after September 11, the FOMC cut the intended
federal funds rate on September 17 and again on
October 2.

VALUE ADDED
I have already mentioned some of the ways
that anecdotal information adds value to Fed
policymaking, but my comments themselves are
only anecdotal. Recently, though, economists
within the Federal Reserve System have tried to
use more technical methods to evaluate the Beige
Book as an indicator of present and future economic activity. The first such study was done at
the Minneapolis Fed and found that the Beige
Book has been an accurate predictor of real growth
in the current quarter. They also found, however,
that the Beige Book did not improve upon private
sector forecasts of real growth. The study concluded that the Beige Book’s value is not in forecasting economic activity, but in reflecting the
economy. In other words, the Beige Book was
found to add value by providing insight and
context not found in formal forecasting models,
while not improving on the performance of these
models.
More recently, research from the Dallas Fed
has found stronger empirical support for the Beige
Book as a predictive tool. This study found that
the national summary of the Beige Book has significant predictive content for current and future
quarterly growth. Further, it found that the Beige
Book has predictive content beyond what is provided by private forecasts. Of particular interest
is that, according to this study, the Beige Book
appears to have been better than alternative
methods at identifying turning points in the
economy.
Another potential source of added value is
from the Beige Book’s 12 regional summaries.
The decentralized nature of the Beige Book means
that the Fed has an instrument for detecting
regional differences in the business cycle. Business
cycle fluctuations are now thought to be more
heterogeneous across regions and sectors than
they used to be. Hence, one hears references to a
“rolling recession” that affects different regions
with greatest severity at different times. State and
regional data, however, are much less complete
than national data. For example, gross state product data are produced with a two-year lag. In this
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MONETARY POLICY AND INFLATION

void, the Beige Book can help pinpoint focal
points of such a rolling downturn or a rolling
recovery. In fact, the Dallas Fed study suggests
that, taken as a whole, the regional sections of
the Beige Book add predictive power beyond
what the national summary provides. Further,
some of the regional sections—including that
produced by the St. Louis Fed—have been useful on their own in predicting GDP growth one
quarter ahead.

DANGERS AND PITFALLS
There are a number of dangers and pitfalls
inherent with anecdotal information, so a great
deal of care should be taken in using it. For one
thing, despite the effort that the Fed puts into it,
the number of contacts is small from a statistical
standpoint, and they are not selected randomly.
They tend to be in businesses that are familiar to
a director of a Fed Bank, who have voluntarily
agreed to serve as a contact, or whose manager or
owner has been asked to serve on a Fed Bank’s
advisory board. Because of this selection process,
numerous biases can arise. For example, perhaps
the type of person who would serve as a contact
or be a member of an advisory board would also
tend to be more successful than the average businessperson. If so, then the information that the
Fed receives would tend to underrepresent firms
that are more likely to be experiencing difficulties.
Also, the responses might reflect the biases
of the contacts rather than be accurate representations of conditions. This bias would not arise
through any conscious misrepresentation, but
perhaps through the tendency for successful
business people to be more optimistic than the
average person. An example of this occurred during a recent lunch at our Bank when we hosted a
group of residential housing developers. The first
time I went around the table asking them for their
outlook on future conditions in their industry,
nearly every one of them was quite upbeat. This
near unanimity was surprising because this was
not long after September 11 and most of them
also felt that the overall economy was not in the
6

best of shape. I then asked them if their answers
were really what they thought would happen or
if they instead reflected what they hoped would
happen. Several of them then admitted that their
outlook was probably more hope than expectations, and adjusted their answers accordingly.
The biases of the economist collecting and
analyzing the anecdotal information may also
mean that it is not representative of general economic conditions. For example, the economist
might tend to pay more attention to anecdotes
that fit his or her previously held beliefs. As a
consequence, the overall impression that is conveyed from the anecdotes in, for example, the
Beige Book, might tend to reflect the economist’s
personal views. It might also be that the odd or
quirky anecdotes are the ones that have the most
influence because they are the most interesting,
even though they might not be representative of
general trends.

SUMMARY AND CONCLUSIONS
Because anecdotal information is inherently
unscientific, the Fed will continue to rely most
heavily on formal methods when making monetary policy decisions. Use of formal statistics is
an important discipline. Nonetheless, because
these methods provide a far from perfect picture
of the economy, the Fed should continue to use
anecdotal information to help fill the gaps. Anecdotal information improves upon our understanding of where the economy is and where it might
be going, most notably by providing information
ahead of formal data. The process of gathering
the information puts us in direct contact with
people actually making day-to-day economic
decisions. The information forces us to question
the formal data and provides a view of the economy that formal methods simply miss.
This constant process of testing the formal
data against the anecdotal reports, and vice versa,
strengthens our understanding of both types of
information. I know that I did not understand the
scale and importance of the effort when I came to
the Fed about four years ago, and I suspect that

The Role of Anecdotal Information in Fed Policymaking

few observers outside the Fed appreciate the role
of anecdotal information in the monetary policy
process. That is why I thought this topic deserves
some attention, and I hope I’ve been successful
in explaining to you how the process works.

7