Michael Dueker

English

Research Papers in Economics

June 2003
MonetaryTrends
Views expressed do not necessarily reflect official positions of the Federal Reserve System.
Why Predict Past
FOMC Actions?
T
he daily effective federal funds rate contains
noise—that is, departures from the target level
established by the Federal Open Market Commitee
(FOMC) that reflect idiosyncratic conditions in the inter-
bank loan market. Averaging the daily data across a month
or quarter is one way to cancel most of this noise, and,
for this reason, the monthly or quarterly average of the
daily federal funds rate has become a widely used measure
of monetary policy. The first chart on page 10 of this
publication, for example, plots a quarterly average as the
actual federal funds rate in a Taylor rule description of
monetary policy. The monthly average is also the bench-
mark for payoffs in the federal funds futures market.
One often-neglected consequence of monthly averaging,
however, is that any change in the target federal funds
rate will affect the monthly average for two months. For
example, if the FOMC raised the target by 50 basis points
precisely halfway through this month, then the monthly
average for this month will rise by 25 basis points relative
to last month, and next month’s average will
also exceed this month’s average by 25 basis
points, all else equal. Similarly, if the FOMC
raised the target by 50 basis points three-
quarters of the way through this month,
then the expected monthly average for the
next month would rise by 37.5 basis points.  
To gauge how strongly target changes in
one month affect the change in the monthly
average funds rate from that month to the
next, I estimated two regressions of the
change in the monthly average on its own
lagged value. In one regression, I also
included information about how the size
and timing of any target change in the
previous month would affect this month’s
average. The sample period covered
January 1984 through March 2003. The
accompanying chart plots the squared fore-
cast errors from both regressions and shows
how the information on target changes improves the pre-
cision of the forecasts. It is striking that when the infor-
mation on last month’s target change is included, the
adjusted R-squared measure of fit more than doubles,
from 21 percent to 44 percent.
Furthermore, the lagged change in the monthly average
becomes statistically insignificant, once the information
regarding the previous month’s target change is included
in the regression. In fact, the coefficient on the target
change variable is slightly greater than (though not signifi-
cantly different from) 1.0. A coefficient greater than 1
would imply that a target change in one month tends to
precede an additional target change in the same direction
the next month. Such a prediction would be consistent with
the view that the FOMC has active and passive periods
and target changes tend to be in the same direction during
each active period. The bottom line is that any forecasting
model of the monthly average of the federal funds rate
that does not take into account known, past FOMC target
changes unnecessarily handicaps itself in forecast compar-
isons with the federal funds futures market, where profit-
motivated traders follow FOMC policy actions closely.
—Michael Dueker
Available on the web at research.stlouisfed.org
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Squared Forecast Errors for Monthly Average of
Federal Funds Rate
(12-Month Moving Average)
Using previous month’s FOMC target change(s)
Ignoring last month’s FOMC target change(s)

Why predict past FOMC actions?

http://research.stlouisfed.org/publications/mt/20030601/cover.pdf

Why predict past FOMC actions?

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Research Papers in Economics