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A New Measure of Monetary Shocks:Derivation and Implications

By CHRISTINA D. ROMER AND DAVID H. ROMER*

This paper develops a measure of U.S. monetary policy shocks for the period1969–1996 that is relatively free of endogenous and anticipatory movements.Quantitative and narrative records are used to infer the Federal Reserve’s inten-tions for the federal funds rate around FOMC meetings. This series is regressed onthe Federal Reserve’s internal forecasts to derive a measure free of systematicresponses to information about future developments. Estimates using the newmeasure indicate that policy has large, relatively rapid, and statistically significanteffects on both output and inflation. The effects are substantially stronger andquicker than those obtained using conventional indicators.(JEL E52, E58, E32,E31)

The accuracy of estimates of the effects ofmonetary policy depends crucially on the valid-ity of the measure of monetary policy that isused. Use of an inappropriate measure may ob-scure a relationship between monetary policyand other economic variables that actually ex-ists, or create the appearance of a relationshipwhere there is no true causal link. For thisreason, this paper derives a new measure ofmonetary policy shocks that is free from somekey deficiencies of previous measures. The newmeasure yields estimates of the impact of mon-etary policy on both real and nominal variablesthat are stronger and faster than those obtainedusing conventional indicators.

Conventional measures of monetary policyhave some obvious flaws. One is the likelihoodof endogenous movements. The money supply,for example, tends to rise in good times becausethe money multiplier rises. Even the federalfunds rate, which has become the standard in-dicator of monetary actions in studies of theeffects of monetary policy, moves a great deal

from day to day for reasons unrelated tomonetary policy. And, in eras when the FederalReserve targeted the funds rate less closely thanit has in the Greenspan era, the funds rate oftenmoved endogenously with changes in economicconditions. Such endogenous movements maylead to biased estimates of the effects of mon-etary policy. For example, the tendency of thefunds rate to rise endogenously with economicactivity may cause researchers to underestimatethe negative impact of increases in interest rateson real economic variables.

Another problem with conventional measuresis that they almost surely contain anticipatorymovements. To avoid the problem of endoge-neity, one might use as the measure of policythe Federal Reserve’s target for some variable,such as the funds rate or nonborrowed reserves.However, movements in such target series aresurely not random. The Federal Reserve investsa huge amount of resources in forecasting thelikely behavior of output and prices. As a result,movements in its target series are often re-sponses to information about future economicdevelopments. For example, the Federal Re-serve typically cuts the target funds rate if itsees signs that a recession is likely. In such asituation, output is unlikely to rise in the wakeof the interest rate cut even if the monetarypolicy action is having a stimulative effect. Ifanticipatory countercyclical actions are com-mon, a regression may again fail to find a

* Department of Economics, University of California,Berkeley, CA 94720, and National Bureau of EconomicResearch (e-mail: [email protected]; [email protected]). We are grateful to Normand Bernardfor providing data and Federal Reserve records, to MarjorieFlavin, Jeffrey Fuhrer, Charles Jones, Janet Yellen, and thereferees for helpful comments and suggestions, and to theNational Science Foundation for financial support.

1055

negative relationship between increases in in-terest rates and output growth even if it is ac-tually present.

To address these difficulties, in this paper wederive a new indicator of monetary policyshocks that avoids the problems in conventionalindicators. We begin by deriving a series onintended funds rate changes around meetings ofthe Federal Open Market Committee (FOMC)for the entire period 1969–1996. To do this wecombine information on the Federal Reserve’sexpected funds rate derived from the WeeklyReport of the Manager of Open Market Opera-tions with detailed readings of the Federal Re-serve’s narrative accounts of each FOMCmeeting. We find that even for periods when theFOMC did not set an explicit funds rate target,the discussion of policy intentions gives a goodindication of desired changes in the funds rate.The resulting series on intended funds ratemovements around FOMC meetings eliminatesmuch of the endogenous relationship betweeninterest rates and economic conditions and cov-ers some crucial episodes missed by existingseries for the funds rate target, such as the Burnsexpansion of the early 1970’s and the Volckerdisinflation of the early 1980’s.

We then use the Federal Reserve’s internalforecasts of inflation and real activity to purgethe intended funds rate of monetary policy ac-tions taken in response to information aboutfuture economic developments. These forecasts,commonly referred to as the “Greenbook” fore-casts, are prepared by the Federal Reserve staffbefore each meeting of the FOMC and play akey role in policy deliberations. We regress thechange in the intended funds rate around fore-cast dates on these forecasts. The residuals fromthis regression show changes in the intendedfunds rate not taken in response to informationabout future economic developments. The re-sulting series for monetary shocks should berelatively free of both endogenous and anticipa-tory actions.

We employ our new measure to analyze theresponses of output and inflation to monetarydevelopments. We estimate straightforward re-gressions of the growth rates of industrial pro-duction and the producer price index forfinished goods on the new measure of monetaryshocks. We also estimate similar regressionsusing the change in the actual funds rate and

other broader measures of monetary policy.Such comparisons can show whether using thenew measure yields different results than thosebased on more conventional measures.

The response of industrial production to ourmeasure of monetary shocks indicates a strongrelationship. Industrial production begins to fallfive months after a contractionary shock andreaches its minimum after roughly two years.The effects are both large and statistically sig-nificant. A one-percentage-point realization ofour series (which is a substantial, but not ex-ceptionally large movement) is associated witha reduction in industrial production of 4.3percent.

The same regression run using the change inthe actual funds rate as the measure of monetarypolicy indicates a considerably weaker correla-tion between monetary developments and realactivity. The estimated impact of this broadermeasure is smaller, slower, and less significantthan the impact of our new indicator. This sug-gests that the endogenous behavior of the fundsrate and the anticipatory component of FederalReserve actions may be substantial, and mayobscure some of the true relationship betweenmonetary policy and the real economy.

Our estimates derived using the new measureof monetary shocks also show a strong, if some-what delayed, negative response of inflation tomonetary contraction. We find that in responseto a one-percentage-point shock, the price levelis virtually unchanged for the first 22 monthsand then falls steadily relative to what it other-wise would have been. After 48 months theprice level is 6 percent lower. The effect ishighly statistically significant.

Using the change in the actual funds rate asthe measure of monetary policy yields verydifferent results. In our baseline specification,the estimated impact of a rise in the funds rateon the price level is positive for all 48 monthsthat we consider. That is, there is a strong “pricepuzzle,” similar to the positive correlation be-tween monetary tightening and the price levelfound in the VAR literature (see, for example,Christopher A. Sims, 1992). Thus, again it ap-pears that endogenous movements in interestrates and anticipatory policy moves are obscur-ing the true effects of monetary policy.

Previous work has found that controlling forcommodity prices eliminates the price puzzle

1056 THE AMERICAN ECONOMIC REVIEW SEPTEMBER 2004

when broader measures of policy are used (see,for example, Sims, 1992; Lawrence J. Chris-tiano et al., 1996; Ben S. Bernanke and IlianMihov, 1998). Nonetheless, commodity pricesmay fail to capture important parts of the Fed-eral Reserve’s information about future devel-opments. To investigate this issue, we examinethe effects of controlling for commodity pricesboth in regressions estimated using our newmeasure of monetary shocks and in ones esti-mated using the broader measures. Controllingfor commodity prices has no consistent effecton the impact of policy estimated using our newmeasure, suggesting that our measure is largelyfree of anticipatory policy actions motivated bysupply shocks. With the broader measures, con-trolling for commodity prices mitigates theprice puzzle. However, the effects of monetarypolicy actions are still much slower and weakerthan when our new measure is used. This sug-gests that using conventional policy measuresbut controlling for commodity prices is notenough to deal with endogeneity and forward-looking Federal Reserve behavior.

Most of the recent literature on the effects ofmonetary policy has used vector autoregres-sions. To facilitate comparisons with this liter-ature, we run VARs using both our newmeasure of monetary shocks and the actual fed-eral funds rate. We find that the VAR resultsusing our new measure show a somewhat stron-ger effect of monetary policy on output and asubstantially stronger and more rapid effect onprices than found in the literature or in ourVARs using the actual funds rate. This againsuggests that endogenous and anticipatorymovements may have led to underestimates ofthe effects of monetary policy.1

I. Derivation of a New Measure of MonetaryPolicy Shocks

The derivation of our new measure of monetarypolicy shocks has two key steps. The first is toderive a series for Federal Reserve intentions forthe federal funds rate around FOMC meetings.The second is to control for Federal Reserveforecasts, and so create a measure of intendedmonetary policy actions not driven by infor-mation about future economic developments.

A. Changes in the Intended Federal FundsRate around FOMC Meetings

Motivation.—The Greenbook forecasts areonly done before FOMC meetings. Therefore,the only policy actions for which we can use theforecasts as a proxy for policy makers’ infor-mation are those around FOMC meetings. Pol-icy actions taken between meetings are oftensubstantial and are usually based on the arrivalof new information. As a result, the Greenbookforecast for the previous meeting would likelybe a poor indicator of the information that led tothe intermeeting action. For this reason, wederive a series for Federal Reserve intentionsaround FOMC meetings. Concretely, we viewthe FOMC decisions for which the Greenbookforecasts are a good summary of the FederalReserve’s information to be those from the fore-cast through the associated FOMC meeting.

The particular variable for which we analyzethe Federal Reserve’s intentions is the nominalfederal funds rate. We focus on intentions forthe funds rate, instead of intentions for reservesor other variables, for several reasons. Mostobviously, for much of the period for which wehave detailed forecast data (1969–1996), theFederal Reserve explicitly targeted the fundsrate. This was the case between 1974 and1 Several recent investigations of the effects of monetary

policy also control for central bank forecasts. Jean Boivin(2001) and Marvin J. Barth III and Valerie A. Ramey (2002)add information from the Federal Reserve’s forecasts tolargely conventional models of monetary policy and itseffects. Per Jansson and Anders Vredin (2001) considerSwedish monetary policy over the period 1992–1998. Theyinclude forecast information in their monetary policy reac-tion function to attempt to isolate policy shocks, and com-pare the central bank’s forecasts with alternatives to attemptto determine the impact of judgmental forecasting on pol-icy. Our paper differs from these studies in two criticalrespects. First, we derive a genuine measure of policyintentions rather than use the actual interest rate. Further-

more, our measure of policy intentions is derived so that thepolicy actions occur at the same time as the forecasts. Thisensures that the forecasts capture policy makers’ anticipa-tions at the time the policy decisions are made. Second, ourfocus is explicitly on the usefulness of the new measure ofmonetary shocks that we derive. By comparing the resultsusing the new measure with those using conventional mea-sures, we can see if using a consistent measure of policyintentions and controlling for anticipatory actions affects theestimates of the impact of monetary policy.

1057VOL. 94 NO. 4 ROMER AND ROMER: A NEW MEASURE OF MONETARY SHOCKS

September 1979 and for the entire period sincethe mid-1980’s. Therefore, the change in theintended funds rate is the single indicator thatbest captures what the Federal Reserve wasaiming to do over this period.

Even in periods when the FOMC was notexplicitly targeting the federal funds rate, it wasconcerned about this key interest rate and dis-cussed the likely implications of policy actionsfor its behavior. Therefore, as a practical matter,the change in the intended funds rate is theeasiest indicator of Federal Reserve intentionsto deduce accurately over a long period of timeand over a variety of monetary regimes.

The final reason for focusing on the intendedfunds rate as the indicator of Federal Reserveintentions is that an interest rate measure ismore likely to be consistent over time than othercandidates. The same Federal Reserve objec-tives for quantity variables such as reserves ormonetary aggregates may reflect very differentintentions even in nearby periods because ofregulatory or definitional changes. This is muchless likely to be true of the funds rate.

Sources.—To identify changes in the in-tended funds rate decided upon around FOMCmeetings, we use two types of sources. One isthe narrative record of FOMC meetings. We useboth the published summaries of FOMC discus-sions contained in the Record of Policy Actionsof the Federal Open Market Committee and themore complete accounts contained in the Min-utes of Federal Open Market Committee and,later, the Transcripts of Federal Open MarketCommittee.2 We also use the FOMC documentMonetary Policy Alternatives, or the “Blue-book,” that is prepared for each FOMC meeting.The Bluebook typically includes a summary ofthe implementation of policy since the previous

meeting and a presentation of some possibledecisions for the FOMC.

Our other type of source is more quantitative.Specifically, we employ a pair of internalmemos from the Federal Reserve showing the“expected federal funds rate.” One covers theperiod from January 1971 to December 1984and the other covers the period from December1983 to September 1992.3 These memos arebased on the Weekly Report of the Manager ofOpen Market Operations. In addition to numer-ical values, the memos contain brief remarksabout the timing of moves and where, within agiven range, the open market desk was aiming.These remarks make it clear that the seriesreflects Federal Reserve intentions rather thanpassive expectations or forecasts. And indeed,the reported expected federal funds rates arevery similar to the target values given in GlennD. Rudebusch (1995) for the periods when theseries overlap (1974–1979 and 1984–1992).The obvious benefit of the internal memos forour purposes is that they also include expectedfunds rate changes in the early 1970’s and theVolcker period.

While the expected funds rate series is auseful input to our identification of Federal Re-serve intentions, it is important to note that wedo not use it in a mechanical fashion. For ex-ample, we do not take the change in the ex-pected rate between the day before the forecastand some arbitrary number of days after thecorresponding FOMC meeting. The reason forthis is that we only want changes in the ex-pected funds rate for which the forecasts are areasonable summary of the available informa-tion. Some funds rate changes even very soonafter FOMC meetings are based on new infor-mation, while other funds rate changes two ormore weeks after an FOMC meeting are explic-itly decided upon at the meeting. For this rea-son, it is crucial to combine the narrative andquantitative evidence.42 The Minutes cover the period through March 1976, and

the Transcripts cover the period beginning in February1981; no detailed accounts are currently available for theintervening period. The Record of Policy Actions of theFederal Open Market Committee is published in the AnnualReport of the Board of Governors of the Federal ReserveSystem. These brief summaries were renamed the Minutes ofFederal Open Market Committee Meetings in 1993. Toprevent confusion between the modern, brief Minutes andthe very detailed Minutes for the pre-1976 period, we callthe brief summaries the Record of Policy Actions in allperiods.

3 We also have an internal e-mail showing the “intendedfederal funds rate” from March 1984 to the present, whichwe use as a check on our analysis after September 1992.Since the Federal Reserve has been targeting the funds rateso closely and explicitly since 1987, this check is of littleimportance.

4 In addition, a mechanical rule based on the expectedfunds rate series would not be practical. There are a number


Method.—To derive the intended series, weneed to identify the level of the federal fundsrate the FOMC intended to prevail at the time ofthe forecast, and the level it intended on thebasis of its decision at its meeting. The Recordof Policy Actions almost always reports the ac-tual level of the funds rate before the meetingand indicates if it was temporarily deviatingfrom what the Federal Reserve was intending.Thus, it is usually straightforward to deduce thelevel the FOMC was intending before the meet-ing. The Record of Policy Actions also typicallyreports any actions taken in the days just beforethe meeting that might have affected the fundsrate, so it is possible to deduce the intendedfunds rate at the time of the forecast.

We check our preliminary estimate againstthe expected funds rate from the internalmemos. If there is a discrepancy or ambiguity,we examine the more detailed accounts of themeetings in the Minutes or Transcripts and thedescriptions of how policy was implemented inthe Bluebooks. If there are discrepancies onthese relatively factual issues, we typically re-solve them in favor of the expected rate, unlessthe narrative sources are very explicit. This isespecially true of changes between the forecastand the meeting, for which the narrative ac-counts are often not particularly quantitative.

We also read the Record of Policy Actions tosee what the FOMC decided to do at the meet-ing. That is, we determine as well as possiblefrom the narrative description what the FOMCintended to happen to the funds rate as a resultof the actions agreed upon at the meeting. Thispostmeeting level for the intended funds rateincorporates any actions taken between the fore-cast and the meeting that are confirmed by theFOMC. In deducing the new intended level wemake no adjustment for timing: changes that arescheduled to be implemented gradually aretreated as immediate changes in intentions.

The Record of Policy Actions is often veryclear about the change in the intended fundsrate. But for some meetings, the FOMC’s inten-tions for the funds rate are more opaque. While

this is especially true in the early Volcker era ofnonborrowed reserve targeting, it also occursperiodically in eras of quite obvious funds ratetargeting. A decision for no change is usuallyvery explicit and the direction of change, ifthere is one, is usually clear. But the magnitudeof the change is often much less explicit.

As with the initial intended rate, we alsoconsider the evidence from the expected fundsrate series. Whenever the Record of Policy Ac-tions and the expected rate do not yield a clearand consistent view of what the FOMC in-tended, we again examine the more detailednarrative sources. In these cases, the Minutesand Transcripts usually provide more explicitinformation than the Record of Policy Actionsabout the FOMC’s intentions. The narrativesources from the subsequent meeting are alsooften very useful: the Record of Policy Actions,Minutes, and Bluebooks almost always containdescriptions of what was decided at the previousmeeting. We assume that when the FOMC saysit made a certain decision at the last meeting, itis not rewriting history.

In the vast majority of cases, either the dif-ferent sources provide a clear picture of whatmonetary policy makers intended, or they leaveroom for only very minor disagreement. In afew cases, however, there is more ambiguity.Sometimes, the narrative sources provide evi-dence about the direction but not the magnitudeof the intended move in the funds rate. In thesecases, we rely mainly on the quantitative evi-dence from the expected funds rate series todeduce the magnitude of the intended action.

Another type of ambiguity concerns asym-metry in the FOMC’s decisions. Periodically,when the FOMC decides not to change ratesimmediately, it makes it clear that any futurerate changes will most likely be in a particulardirection. When such asymmetry is strong andexplicit, we feel it is reasonable to say that theintended funds rate has in fact moved. Thelikely rate change times the probability of achange is surely not zero. As a starting point, wescale strong asymmetry as one-half of the usualrate change in a given era. For example, for themid-1970’s, when quarter-point moves in theintended funds rate were typical, strong asym-metry is recorded as a change of 1/8 of a pointin the intended direction. In the early Burns era,when larger movements were common, strong

of entries for which the expected rate is missing, and formuch of the period a range is given rather than a singlenumber. Also, before 1987 the expected series is dated byweek rather than by the actual day of the change.


asymmetry may get a value of 1/4 point ormore. We then adjust this preliminary estimateof the expected change in the intended fundsrate due to asymmetry using the narrative ac-counts of the meeting. For example, in somecases the narrative accounts make it clear thatthe asymmetry was being included in theRecord of Policy Actions mainly for signalingpurposes and was unlikely to be acted on. Inother cases, the narrative accounts include fairlyclear discussions of the magnitude or likelihoodof a move.

A final case where the evidence is less thanfully clear involves the beginning of the periodof nonborrowed reserve targeting under FederalReserve Chairman Paul Volcker. The FOMCwas sufficiently focused on nonborrowed re-serve targeting that for many meetings theRecord of Policy Actions provides only a vaguedescription of the likely implications of theFOMC’s decisions for the funds rate. Further-more, the Federal Reserve’s series on the ex-pected funds rate is so volatile from week toweek that it is difficult to discern the FOMC’sintentions from this source. Finally, neither theMinutes nor the Transcripts are currently avail-able for late 1979 and 1980. Because of thisambiguity, in our empirical work we check thatour results are robust to omitting the earlyVolcker period.

A meeting-by-meeting description of our ap-plication of these general procedures for deduc-ing Federal Reserve intentions is given in anunpublished Appendix available on the AERWeb site (http://www.aeaweb.org/aer/contents/).Table A1 at the end of the paper shows theresulting series on the FOMC’s intended fundsrate before the forecast and the change in theintended rate associated with each FOMC meet-ing in our sample.

B. Controlling for the Federal Reserve’sForecasts

Motivation.—The second step in the deriva-tion of our measure of monetary policy shocksis to remove from the intended series policyactions taken in response to information theFederal Reserve has about future developments.To do this, we need a measure of the FederalReserve’s information. In this regard, it is im-portant to realize that it is only accurate infor-

mation that matters. If the Federal Reservebases its actions on inaccurate forecasts, policywill not be preemptively countercyclical exceptby chance.

The Federal Reserve’s internal forecasts pro-vide an excellent proxy for the reliable infor-mation about future economic developmentsthat the Federal Reserve possesses and uses.First, the forecasts contain useful information.The Federal Reserve devotes a vast amount ofresources to the forecasts, and as a result pro-duces high-quality forecasts. In a previousstudy, we found that someone having access toa number of well-known private forecasts andthe Greenbook forecasts should put substantialweight on the Greenbook forecast and roughlyzero weight on the private forecasts in pre-dicting future inflation and real GDP growth(Romer and Romer, 2000). That the FederalReserve possesses a useful forecast means thatsuccessful anticipatory movements are a possi-bility, and so controlling for them could beimportant.

The high quality of the Greenbook forecastsmakes it likely that they contain most of theuseful information about future economic de-velopments known by FOMC members. Theforecasts are typically issued just six days be-fore the FOMC meeting, so it is unlikely thatmuch valuable information becomes availablebetween the forecast and the meeting. Indeed, itis the few exceptions that prove this rule: thereare a handful of times when the forecast wasreissued precisely because important new infor-mation became available. We always use thelatest forecast to ensure that we control for asmuch of the Federal Reserve’s information aspossible.

The records of the discussions at FOMCmeetings make it clear that the Greenbook fore-casts play a central role in policy deliberations.Many times, especially early in our sample, thestaff forecasts are accepted without discussion.There are also many times when members quib-ble with the forecasts, but those quibbles aresymmetric. That is, minor disagreements areexpressed, but they are not at all systematic.Much less frequently, the members of theFOMC express disagreement with the staff fore-cast in one particular direction. However, ex-cept in rare instances, these differences aresmall.


This impression that the Greenbook forecastsare a good summary of the FOMC’s informa-tion can be tested to some degree after 1979. Inits semiannual “Monetary Policy Report toCongress,” the Federal Reserve summarizes theforecasts of the individual FOMC members. Wecompare the midpoints of the reported centraltendencies of the members’ forecasts of realGDP growth, inflation, and the unemploymentrate with the staff forecasts.5 For the 35 meet-ings for which we have data, the average abso-lute difference between the midpoint of themembers’ forecasts and the staff forecast is 0.28percentage points for real GDP growth, 0.25percentage points for inflation, and 0.17 per-centage points for the unemployment rate. Itcertainly does not appear that FOMC membershave significant additional information.

The centrality of the Greenbook forecasts inpolicy discussions, combined with the relativeaccuracy of the forecasts, suggests that they docontain the vast majority of the useful informa-tion about future economic developments uponwhich the Federal Reserve bases its policy de-cisions. For this reason, controlling for theGreenbook forecasts should yield a series onFederal Reserve intentions that is largely free ofanticipatory movements.

Specification.—To control for the Greenbookforecasts, we estimate the usual relationship be-tween the Federal Reserve’s intentions for thefunds rate and the forecasts.6 The Greenbookscontain forecasts for a wide variety of variables.The particular forecasts that we use are those forthe growth rate of real GNP/GDP and the GNP/GDP deflator, and for the unemployment rate.

These are three key macroeconomic indicatorsthat the FOMC is likely to consider in settingpolicy.

Both the intended funds rate series that wederive and the forecast data correspond toFOMC meetings. Therefore, at this stage in theanalysis, we use FOMC meetings as our unit ofobservation. In the early part of our sample, theFOMC met at least once a month and some-times twice. Since 1979, the FOMC has typi-cally met eight times a year. The Greenbookforecasts begin in late 1965, but the forecasthorizon was very short (typically just one quar-ter ahead) until 1969. In addition, the forecastsare only released with a substantial lag. As aresult, our analysis is restricted to the period1969–1996.

The specific equation we estimate is:

(1) �ffm � � � �ffbm � �i � �1

2

�i�ymi

� �i � �1

2

�i��ymi � �ym � 1, i� � �i � �1

2

�imi

� �i � �1

2

i�mi � m � 1, i� � �um0 � �m .

�ffm is the change in the intended funds ratearound FOMC meeting m. ffbm is the level ofthe intended funds rate before any changes as-sociated with meeting m. It is included to cap-ture any tendency toward mean reversion inFOMC behavior. , �y, and u refer to the fore-casts of inflation, real output growth, and theunemployment rate. Both the forecasts for thecontemporaneous meeting and the change in theforecast since the previous meeting are includedbecause it is plausible that both the levels andthe changes in the forecasts are important de-terminants of Federal Reserve behavior. The isubscripts refer to the horizon of the forecast:�1 is the previous quarter; 0 is the currentquarter; and 1 and 2 are one and two quartersahead, respectively.7 The forecast for the

5 When available, we take the information about mem-bers’ forecasts, along with the comparable staff forecast,from the staff’s “chart show” given at the FOMC meetingsat which the “Monetary Policy Report to Congress” isdiscussed (typically the February and July meetings). Thechart shows are available on the Board of Governors Website (http://www.federalreserve.gov). The information isavailable starting with the meeting for July 1979. We usethe forecast of real GDP growth and inflation for the fourthquarter of the previous year to the fourth quarter of the currentyear, and the unemployment forecast for the fourth quarter ofthe current year (except for the small number of meetingswhere only forecasts for annual averages are reported).

6 The Greenbook forecasts are contained in the docu-ment Current Economic and Financial Conditions, and areavailable from the Board of Governors upon request.

7 The horizons are relative to the date of the forecastcorresponding to meeting m. That is, if the meeting is in


previous quarter is often actual data rather thana forecast. We include it because lagged condi-tions could obviously play a substantial role inFOMC decisions. Using lagged data from theGreenbook is desirable because it reflects whatthe FOMC believed recent history was at thetime of the meeting, rather than what our currentrevised estimates suggest was the case.

We only include forecasts up to two quartersahead for two reasons. The more prosaic one isthat the Greenbooks for the late 1960’s andearly 1970’s rarely forecasted more than twoquarters out. As a result, we lose many obser-vations if we try to incorporate longer-termforecasts. The more fundamental reason has todo with policy assumptions. All forecasters, in-cluding the Federal Reserve staff, must incor-porate assumptions about future policy intotheir forecasts. The Greenbook forecast is al-most always predicated on the assumption of nochange in monetary policy in the very short run,where the very short run means at least until theFOMC meeting after the one for which theforecast is being made. This characteristic,along with the usual assumption of some lag inthe effects of monetary policy, makes it unlikelythat forecasts zero, one, and two quarters aheadare contaminated by assumptions or inside in-formation about the course of monetary policy.As a result, these near-term forecasts provideinformation about what the Federal Reserve ex-pected to happen to the economy in the absenceof changes in monetary policy. At the sametime, both output growth and inflation are seri-ally correlated enough that forecasts one andtwo quarters ahead provide a good indication ofthe likely forecasted path of the economy overlonger horizons.

Because the Okun’s Law relationship be-tween output growth and unemployment is sostrong, we do not include all horizons of theforecasts of both variables. We focus primar-ily on forecasts of output growth because ithas greater prominence in the Greenbooks,

suggesting a more central role in FOMC de-cision-making. We do, however, include thecontemporaneous unemployment forecast sothat we control for the current level of theeconomy as well as forecasted changes.

It is important to note that the goal of thisregression is not to estimate the Federal Re-serve’s reaction function as well as possible.What we are trying to do is to purge the in-tended funds rate series of movements taken inresponse to useful information about future eco-nomic developments. Once we have accom-plished this, it is desirable to leave in as much ofthe remaining variation as possible. It is thisvariation that will allow us to identify the effectof monetary shocks on output and inflation. Forthis reason, in our baseline regression we do notdo some of the obvious procedures, such assplitting the sample, that one would do if thegoal was to match Federal Reserve behavior asclosely as possible. Changes in the tastes or oper-ating procedures of the Federal Reserve are argu-ably a key source of changes in the intended fundsrate that are not correlated with information aboutfuture economic conditions, and so should not beremoved from the shock series.

Results.—The results of estimating equation(1) are reported in Table 1. The coefficientestimates show that the FOMC tends to behavecountercyclically. The sum of the coefficientson the real growth forecasts is 0.04 with at-statistic of 2.5, and the sum of the coefficientson the changes in the real growth forecasts sincethe previous meeting is 0.24 (t � 4.0). Anincrease from one meeting to the next in fore-casted real growth at all horizons of one per-centage point leads to a rise in the intendedfunds rate of 29 basis points. Although all theestimated coefficients on the growth variablesare positive, the strongest estimated effect is forthe change in the forecast of real growth for thecurrent quarter. The estimated coefficient on�ym0 � �ym � 1,0 is 0.15 (t � 5.1). The signifi-cant negative coefficient on the forecast of theunemployment rate for the current quarter alsoconfirms the countercyclical tendency in FOMCbehavior.

The regression suggests that the Federal Re-serve also resists forecasted inflation. The sumof the coefficients on the inflation forecasts is

early July 1980 and the forecast is in late June 1980, thecontemporaneous forecast is for the second quarter of 1980.In computing the forecast innovations, the forecast horizonsfor meetings m and m � 1 are adjusted so that the forecastsrefer to the same quarter.


0.04 (t � 2.3). The sum of the coefficients onthe changes in the inflation forecasts is 0.03, butis estimated quite imprecisely (t � 0.3). Thus,an increase from one meeting to the next inforecasted inflation at all horizons of one per-centage point is associated with a rise in theintended funds rate of seven basis points. Allbut two of the coefficients on the inflation vari-ables are positive. The largest are for the levelof forecasted inflation two quarters ahead andthe change in forecasted inflation for the previ-ous quarter.

The magnitudes of these estimated responsesare small, particularly for inflation. But we areconsidering the change in the intended funds

rate only over the brief interval from the fore-cast to the associated FOMC meeting. There-fore, our results merely show that the FederalReserve’s initial responses to output and infla-tion are modest. Furthermore, the estimated co-efficient on the initial level of the intendedfunds rate is close to zero (�0.021, with at-statistic of 1.8). Thus, to a first approximationit is the change in the intended rate that dependson economic conditions, as in the rule consid-ered by Andrew Levin et al. (1999). Our esti-mates therefore imply that in response to, forexample, an increase in the level of inflation, theFOMC would not just raise the funds rate im-mediately, but would continue to increase it atsubsequent meetings. In addition, our results donot address the question of how the FOMCbehaves between meetings. For both these rea-sons, our estimates are not informative abouthow the Federal Reserve adjusts the level of thefunds rate to output and inflation over longerhorizons.

The R2 of the regression is 0.28. This sug-gests that a substantial fraction of Federal Re-serve actions over the last three decades havebeen taken in response to their forecasts offuture growth and inflation. Thus, it is cer-tainly possible that not controlling for theseresponsive actions could bias estimates of theeffects of policy. At the same time, that the R2

is quite far below one indicates that manyFederal Reserve actions were taken for rea-sons unrelated to anticipations of outputgrowth and inflation.

C. New Measure of Monetary Shocks

We construct our new measure of monetaryshocks by taking the residuals of equation (1).The resulting series shows changes in the in-tended federal funds rate around FOMC meet-ings not made in response to forecasts ofinflation and real growth.

Because the data used in equation (1) corre-spond to FOMC meetings, the residuals alsocorrespond to FOMC meetings. Before theshocks series can be used in further analysis, itmust be converted to a monthly series. To dothis, we assign each shock to the month inwhich the corresponding FOMC meeting oc-curred. If there are two meetings in a month, wesum the shocks. If there are no meetings in a

TABLE 1—DETERMINANTS OF THE CHANGE IN THE

INTENDED FEDERAL FUNDS RATE

CoefficientStandard

error

Constant 0.171 0.141Initial level of intended funds rate �0.021 0.012Forecasted output growth,

Quarters ahead:

�1 0.007 0.0100 0.003 0.0191 0.010 0.0322 0.022 0.032

Change in forecasted outputgrowth since previousmeeting,

Quarters ahead:

�1 0.050 0.0300 0.152 0.0301 0.021 0.0462 0.021 0.051

Forecasted inflation,Quarters ahead:

�1 0.021 0.0240 �0.044 0.0291 0.010 0.0442 0.052 0.047

Change in forecasted inflationsince previous meeting,

Quarters ahead:

�1 0.057 0.0450 0.003 0.0481 0.031 0.0742 �0.062 0.081

Forecasted unemployment rate(current quarter)

�0.048 0.021

Notes: R2 � 0.28; D.W. � 1.84; s.e.e. � 0.39; N � 263.The sample is FOMC meetings over the period 1969:3–1996:12.


month, we record the shock as zero for thatmonth.8 Table 2 reports our monthly shock se-ries. The top panel of Figure 1 presents a graphof the series, where the monthly values havebeen summed into quarterly observations to im-prove readability.

Sources of the Shocks in the New Series.—Estimates of monetary policy “shocks” derivedfrom a regression procedure do not reflect sim-ple random departures by the Federal Reservefrom its normal behavior.9 Rather, they reflect

all influences on policy not captured by what-ever specification is being used. In our case,because we control for the Federal Reserve’sforecasts of the paths of output and inflation,most of those residual influences are appropriatefor estimating the impact of monetary policy onthe economy.

One important source of our estimatedshocks is the evolution of the Federal Reserve’soperating procedures. In several parts of oursample, the Federal Reserve placed consider-able emphasis on some quantity measure inimplementing policy. Concern about the quan-tity measure often caused the Federal Reserve toset interest rates differently than it otherwisewould have given its expectations concerningoutput and inflation. This is almost surely animportant source of the volatility of our shockseries in the period of nonborrowed reservetargeting in 1979–1982 and, to a lesser extent,in the period of partial money targeting in theearly 1970’s.

8 Recording these observations as zeroes is appropriate.Our shock series shows changes in Federal Reserve inten-tions for the federal funds rate decided at FOMC meetingsthat are not systematic responses to forecasts. If there is nomeeting, there is no change in Federal Reserve intentionsaround an FOMC meeting that is not a response to forecasts.There is, therefore, a shock of zero by our measure, not amissing observation.

9 This point is made persuasively by Rudebusch (2002).

TABLE 2—NEW MEASURE OF MONETARY POLICY SHOCKS

(Percentage points)

Jan. Feb. March April May June July Aug. Sept. Oct. Nov. Dec.

1969 0.0 0.0 �0.245 0.405 0.204 �0.020 0.181 0.309 0.029 0.088 �0.005 0.0651970 �0.160 �0.360 �0.140 �0.145 0.300 �0.180 �0.243 �0.483 �0.272 �0.009 �0.346 �0.2291971 �0.682 �0.025 �0.065 0.461 0.003 0.343 �0.117 0.0 0.0 �0.322 �0.342 �0.9201972 �0.234 �0.086 0.252 �0.104 �0.115 �0.050 0.0 0.0 0.0 0.0 0.036 �0.0271973 0.279 0.225 0.064 �0.063 0.317 0.409 0.115 0.318 �0.571 �0.848 �0.095 �0.1651974 �0.206 0.201 0.733 0.387 0.392 0.280 �0.091 �0.022 �0.430 �0.284 0.336 �0.2291975 �0.354 0.243 �0.499 �0.637 0.136 0.170 0.070 �0.136 �0.114 �0.200 �0.281 0.2801976 �0.091 �0.469 �0.239 0.139 �0.298 �0.038 �0.139 �0.044 0.019 �0.041 0.030 �0.1311977 �0.097 �0.085 �0.228 �0.049 �0.051 �0.146 �0.240 0.030 0.073 �0.026 �0.048 �0.1221978 �0.205 0.106 0.042 �0.069 �0.216 0.243 �0.142 �0.064 �0.156 0.133 0.168 �0.0421979 0.0 �0.152 0.133 �0.064 0.105 0.0 0.761 0.322 �0.224 0.0 0.045 0.01980 �0.011 0.197 1.422 �3.221 �0.764 0.0 0.403 �0.198 0.771 1.218 1.871 �0.6341981 0.0 �0.783 0.307 0.0 1.515 0.0 �0.611 �0.041 0.0 �0.574 �0.356 0.1001982 0.0 1.021 �0.435 0.0 �0.056 0.0 �0.196 �0.211 0.0 �0.242 0.125 0.6511983 0.0 0.185 0.145 0.0 �0.019 0.0 �0.008 �0.234 0.0 0.282 �0.172 0.2171984 0.257 0.0 �0.101 0.0 0.173 0.0 0.327 �0.061 0.0 0.035 �0.546 �0.1441985 0.0 �0.158 0.201 0.0 �0.104 0.0 0.060 0.186 0.0 0.104 0.021 �0.0691986 0.0 �0.110 0.0 0.207 0.076 0.0 �0.168 �0.234 0.001 0.0 0.021 �0.0821987 0.0 0.176 0.191 0.0 0.238 0.0 �0.041 �0.021 �0.147 0.0 �0.085 �0.1801988 0.0 �0.224 0.018 0.0 0.188 0.308 0.0 �0.182 �0.067 0.0 �0.009 0.4461989 0.0 0.297 0.061 0.0 0.153 0.0 0.075 �0.139 0.0 �0.087 0.108 �0.0671990 0.0 0.313 �0.094 0.0 0.044 0.0 �0.066 0.150 0.0 �0.119 �0.018 �0.1591991 0.0 �0.251 0.227 0.0 0.262 0.0 �0.077 0.140 0.0 �0.035 �0.121 0.1131992 0.0 �0.004 �0.126 0.0 0.148 0.0 �0.088 �0.003 0.0 �0.175 �0.029 �0.2371993 0.0 0.094 �0.063 0.0 0.335 0.0 0.009 0.044 0.159 0.0 �0.087 �0.1631994 0.0 0.224 0.313 0.0 0.287 0.0 0.070 0.417 0.041 0.0 0.549 �0.2481995 0.0 0.501 0.241 0.0 0.209 0.0 �0.006 �0.091 0.025 0.0 0.052 �0.1711996 0.073 0.0 0.056 0.0 �0.027 0.0 �0.040 �0.065 �0.042 0.0 0.048 �0.029


Policy makers’ beliefs about the workings ofthe economy are another source of shocks. Forexample, in the early 1970’s the prevailingframework at the Federal Reserve held that in-flation was extremely unresponsive to economicslack (Romer and Romer, 2002). One wouldexpect this belief to lead the Federal Reserve toset lower interest rates than it otherwise wouldhave. And indeed, our shock series is generallynegative in 1971 and 1972.

A third source of shocks are the Federal Re-serve’s tastes and goals. A Federal Reserve thathas a particular distaste for inflation, for exam-ple, is likely to set higher interest rates than ittypically would. Our series shows obvious up-

ward spikes in 1969, 1973–1974, and 1979–1982. These are three periods that we identifiedin previous work as times when the FederalReserve decided that the current level of infla-tion was too high and that it was willing toendure output losses to reduce it (Romer andRomer, 1989).10

10 These policy shifts involved more than mere changesin tastes, and to a large extent reflected changes in theFederal Reserve’s understanding of the economy. Thusthere is not a sharp distinction between shocks coming fromthe Federal Reserve’s beliefs and ones stemming from itstastes.

FIGURE 1. MEASURES OF MONETARY POLICY


http://www.atypon-link.com/action/showImage?doi=10.1257/0002828042002651&iName=master.img-000.png&w=299&h=360

A fourth source is politics. For example, ithas been argued that Arthur Burns pursued un-usually expansionary policy at the beginning ofthe Carter administration because he believed itwould increase his chances of being nominatedfor another term (William Grieder, 1987). Thismay be a reason for the string of negative valuesof our shock series in 1977.

A fifth source of our estimated shocks is thepursuit of other objectives. For example, attimes the Federal Reserve has been concernedabout the exchange rate above and beyond anyimplications exchange rate movements mighthave for future inflation and output growth. Thisappears to have been the case in late 1984 andearly 1985, when the FOMC repeatedly citedthe strength of the dollar as one reason foreasing policy (see, for example, Board of Gov-ernors, Annual Report, 1984, pp. 139–40, and1985, pp. 87–8). Our shock series shows sub-stantial negative values during this period.

Finally, our estimated shocks also stem fromfactors reasonably thought of as leading to ran-dom variation in policy. Though such factorsare, almost by definition, difficult to pinpoint,they include such elements as the personalities,moods, and idiosyncratic views about the stateof the economy that the participants bring to themeeting, the persuasiveness of their rhetoric,and so on.

There is one potential source of our estimatedshocks that it is not appropriate to use to esti-mate the effects of monetary policy on outputand inflation. To the extent that policy makersemploy useful information about the paths ofoutput and inflation beyond what is in theGreenbooks, some of what we classify asshocks will be responses to information aboutfuture movements in output and inflation. Thatis, our series could still include anticipatoryactions, and so could lead to biased estimates ofthe effects of monetary policy. However, be-cause we remove the component of monetarypolicy actions that represent responses to theGreenbook forecasts, our estimates are verylikely to be an improvement over previous es-timates. More fundamentally, it is likely thatany residual bias is small. Our shock seriescontains a large amount of variation that isappropriate for identifying the effects of mone-tary policy. And as discussed above, there is noevidence that monetary policy makers use a

substantial amount of additional information insetting policy.

It is also important to point out that ourapproach excludes some types of policy movesthat could be used to estimate the effects ofmonetary policy. One is moves made in re-sponse to incorrect information. For example,policy makers must base their decisions in parton preliminary data, which often contain signif-icant errors. Policy moves resulting from sucherrors are not responses to correct informationabout current and prospective economic devel-opments, and so are appropriate for estimatingthe effects of policy. But because we removepolicy makers’ normal responses to their beliefsabout economic conditions in constructing ourmeasure, we do not include such moves. Asecond type of potentially useful policy movethat we exclude is intermeeting moves not madein response to information about the paths ofoutput and inflation: because we do not have arecord of the information that intermeetingmoves are based on, we exclude all suchmoves. As long as what remains in our shockseries is not correlated with other factors af-fecting the path of the economy, however, theexclusion of potentially useful moves will notbias our estimates, but merely make them lessprecise.

Robustness of the New Series.—The new se-ries is derived by regressing the intended fundsrate on the Federal Reserve’s internal forecastsand taking the residuals. There are obviouslymany possible ways of specifying the key re-gression. One permutation that we consider is toinclude a quadratic trend in the regression totake into account possible long-run changes ininflation and the level of the intended funds rate.Another is to include the lagged, contempora-neous, and one- and two-quarter-ahead fore-casts and forecast innovations for the change inthe index of industrial production. Includingindustrial production could be useful because itis a cyclically sensitive series and one that theFederal Reserve is likely to forecast particularlywell (since it constructs the index). A thirdpermutation adds the full complement of unem-ployment forecasts to the basic specification.Finally, a fourth permutation estimates the re-gression separately for the pre- and post-1983periods; this allows us to assess the importance


to our results of the changes in Federal Reservebehavior starting in the Volcker era.

The various permutations have some effecton the individual coefficient estimates. How-ever, the sums of the coefficients on the differ-ent forecasts and forecast innovations arequalitatively very similar. More importantly,the shock series derived as the residuals of thealternative regressions are all extremely similarto the basic series. The correlation between thepermutations and the basic series is over 0.97 ineach case. Given that the series being compareddo not have a noticeable trend, this degree ofcorrelation is indicative of genuinely similarmovements. Thus, our new shock series is ro-bust to a wide array of sensible variations in thespecification of the underlying regression.

That splitting the sample has little impact onthe estimated reaction function, and thereforeon the shock series derived as the residuals,parallels the findings in Athanasios Orphanides(2003). Orphanides finds that the Federal Re-serve’s behavior is remarkably stable over timewhen one uses the views of potential outputprevailing at the time in measuring the deviationof output from trend. In our case, it is possiblethat the Federal Reserve has responded to itsforecasts in much the same way over our entiresample period, but that the forecasts have be-come more realistic over time. Consistent withthis, Romer and Romer (2002) show that theestimates of the natural rate implicit in theGreenbook forecasts were substantially moreoptimistic in the late 1960’s and the early andlate 1970’s than they have been in the Volckerand Greenspan eras. It is important to note,however, that if the early forecasts contain someincorrect information, this should only lead usto misclassify some policy moves as responsesto information rather than as policy shocks. Itshould not lead us to classify something as ashock that is not, and therefore should not leadto biased estimates of the effects of policy whenour new measure is used.

Broader Measures of Policy.—The main mo-tive for developing the new measure of mone-tary policy shocks is that broader measures ofpolicy may include endogenous movements andpolicy changes the FOMC makes in response toinformation it has about future economic devel-opments. To see if correcting for these potential

problems genuinely matters, in the analysis thatfollows we compare the results using our newseries with those using broader measures ofpolicy. Because the new measure is based oninterest rates, it is desirable to compare it withother interest rate measures. The key broadermeasure that we consider is the change in theactual federal funds rate.11 This is clearly themost commonly used indicator of monetary pol-icy (see, for example, Bernanke and Alan S.Blinder, 1992; Sims, 1992; Christiano et al.,1996).

The change in the actual funds rate is given inthe lower panel of Figure 1.12 As one wouldexpect given the derivation of our new series,the broad movements in the new series and thechange in the funds rate are usually similar. Theearly Volcker era, for example, is a period ofextreme volatility in both series. Likewise, 1969and 1973–1974 are periods of contraction inboth series, while 1971 and 1975 are periods ofexpansion in both series. The contemporaneouscorrelation between our new measure of mone-tary shocks and the change in the actual fundsrate over the entire sample period is 0.43.

However, the behavior of the two series issometimes quite different. For example, ourshock series shows a string of negative values inthe early Carter era (1977 and 1978), while thechange in the actual funds rate shows a string ofpositive values. This difference shows the im-portance of controlling for the forecasts: whilethe Federal Reserve was raising interest rates inthis period, it was raising the funds rate by lessthan it normally would have given its forecastsof rapid growth and high inflation. Therefore,what shows up as a contraction in the actualfunds rate is a period of substantial expansion inour new series. Controlling for forecasts alsoexplains why some contractions are larger out-liers in our new series than in the actual fundsrate. For example, the new series shows twoquarters of relatively extreme tightening in

11 The federal funds rate data are from the Board ofGovernors Web site. We use the change in the monthlyaverage of the funds rate to minimize the effects of extremeday-to-day variation.

12 Again, to improve readability we present the quarterlysums of the monthly changes. Note that the scale is differentin the two panels of Figure 1. The new monetary shocksseries shows smaller movements than the actual funds rate.


early 1974, while the actual funds rate fallsslightly in the first quarter of 1974 and risesmoderately in the second. The movements inthe actual funds rate in both quarters were un-usual given the fact that the Federal Reservewas forecasting severe economic decline, andso show up as relatively extreme contractions inthe new measure.

As the derivation of the new measure makesclear, our series differs from the change in theactual funds rate in two ways: we consider onlyintended movements in the funds rate aroundFOMC meetings, and we exclude movementsthat are the FOMC’s normal response to antic-ipated economic developments. We will there-fore also consider two intermediate broaderseries in our comparisons. The first is thechange in the intended funds rate around FOMCmeetings. This shows the effects of focusing onintended movements without controlling for in-formation about prospective economic develop-ments, and so addresses endogeneity but notanticipatory policy actions. Thus, this compari-son will show the bias that might result fromusing a series on the change in the funds ratetarget in empirical analysis.

The second intermediate series is the residu-als from a regression of the change in the actualfunds rate on the Greenbook forecasts [that is,the residuals from equation (1) with the changein the funds rate as the dependent variable].13

As described above, because many of the move-ments in the funds rate occur between meetings,the Greenbook forecasts are a highly imperfectcontrol for the information underlying the over-all change in the funds rate from one meeting tothe next. Nevertheless, this series shows the

effects of controlling for some of the informa-tion the Federal Reserve possesses about pro-spective developments, and thus partiallyremoves anticipatory movements. Because itdoes not restrict attention to intended move-ments, the series does not address short-runendogeneity. The results based on this serieswill show the effects of simply including theGreenbook forecasts as control variables in em-pirical studies of the effects of monetary policy.

II. Implications of the New Measure

The next step in our analysis is to use the newmeasure of monetary policy shocks to estimatethe effects of policy. We first examine the im-pact of policy on output and on prices in simple,single-equation regressions. We then examinethe impact of policy in a single-equation frame-work with an explicit control for supply shocks,and in a vector autoregression framework.

A. Output

Methodology.—We want to determine howoutput behaves in the wake of monetary shocks.The obvious way to do this is simply to regressoutput growth on a constant, its own laggedvalues, and lagged values of the new policymeasure. The lagged values of the shock seriesare included to capture the direct impact ofshocks on output growth, and the lagged valuesof output growth are included to control for thenormal dynamics of output.

A natural variation on our approach is tocontrol for other variables that may affect out-put. Since we control for the Federal Reserve’sinformation about future output growth in con-structing the measure of policy changes, there isno reason to expect the measure to be correlatedwith other variables that influence output. Ourbasic specification therefore does not includeany controls. We show below that controllingfor a measure of supply shocks has little impacton the results. Similarly, an obvious alternativeto our one-equation approach is to run a vectorautoregression with output growth and the pol-icy measure (and perhaps other variables). Weshow below that using our new policy measurein a VAR yields results similar to those in ourbasic specification.

Because our measure of monetary policy is

13 This regression requires the change in the funds rateusing meetings rather than months as the unit of observa-tion. Conceptually what one wants is the change in the fundsrate from just before the forecast for one FOMC meeting tojust before the forecast for the next meeting. To minimizethe effects of day-to-day fluctuations in the funds rate, andbecause the forecasts are typically issued on Wednesdays,we use the average for the week ending on the Wednesdayof the week that includes the date of the forecast. Theweekly averages are from the Board of Governors Web site.We then estimate equation (1) using this series in place ofthe change in the intended funds rate around the meeting(and using the average funds rate for the week of theforecast in place of the intended rate before the forecast).We then take the residuals and convert them to a monthlyseries in the same way we do for our shock series.


monthly, we use industrial production as ouroutput series.14 To avoid the complications in-troduced by the government’s seasonal adjust-ment algorithm, we use data that have not beenseasonally adjusted and include monthly dum-mies in the regression.15 In our baseline regres-sion, we include 24 lags of output growth and36 lags of the monetary policy measure. Wemake the conventional assumption that mone-tary policy does not affect output within themonth; thus we do not include the contempora-neous value of the shock series.16

Our baseline regression is therefore:

(2) �yt � a0 � �k � 1

11

ak Dkt � �i � 1

24

bi�yt � i

� �j � 1

36

cjSt � j � et ,

where y is the log of industrial production, S isour new measure of monetary policy shocks,and the Dk’s are monthly dummies. Our sampleperiod is 1970:1–1996:12, with the values of Stbefore 1969:3 set to zero. The end date is thelast month for which our policy measure isavailable. The start date is chosen so that areasonable number of lagged values of the pol-icy measure are available at the beginning of thesample.

We summarize the results by examining theresponse of the level of log output to a one-timerealization of our monetary policy variable(S) of one percentage point. The estimated re-sponse of log output after one month is justc1, the coefficient on the first lag of S; the

estimated response of log output after twomonths is c1 � (c2 � b1c1); and so on. Ascan be seen in Table 2, the realization we con-sider is a substantial shock, roughly the size ofthat in March 1974. However, it is only aboutone-third the size of the largest shock in oursample.

Results.—The estimates of equation (2) aregiven in Table 3. The coefficients on the firsttwo lags of our shock variable are positive, andthe first is significantly larger than zero. Thecoefficients then turn sharply negative: all buttwo of the estimated coefficients on lags 3through 27 are negative, although most of themare not individually significant. Starting withlag 28, the coefficients are all positive, thoughagain few are significant.

Figure 2 shows the implied response of logoutput to a realization of the policy measureof one percentage point, together with one-standard-error bands.17 The estimated cumula-tive impact is slightly positive for the first fourmonths, and then declines roughly linearlythrough month 22. The estimated effect is es-sentially flat at �4.3 percent in months 22through 27. This means that a one-percentage-point rise in the Federal Reserve’s intentions forthe funds rate, not taken in response to infor-mation about future economic developments,reduces industrial production by over 4 percent.The impact then weakens gradually, reaching�1.7 percent at month 48. The estimated impactin the middle months is highly significant: thet-statistic for the estimated effect in each ofmonths 17 through 27 exceeds 2.5. The two-standard-error confidence interval for the im-pact in month 22 is (�7.0%, �1.4%). Theeffect at longer horizons, on the other hand,is not precisely estimated. The two-standard-error confidence interval in month 48 is

14 The industrial production data are from the Board ofGovernors Web site. We use series B50001 in its non-seasonally-adjusted form.

15 We have also run all of the regressions in the paperusing seasonally adjusted data and excluding the monthlydummies. None of the results are sensitive to this change.

16 The same logic that implies that one does not need toinclude controls implies that it is not necessary to includethe lagged values of output growth. This specification hasthe added advantage that if monetary policy affects outputcontemporaneously, the estimated effects of policy on out-put growth in later months will not be biased. We find thatexcluding the lags of the dependent variable has little effecton any of our estimates, but that it reduces the standarderrors substantially.

17 The standard errors are computed by Monte Carlomethods. Specifically, we repeatedly draw coefficients froma multivariate normal distribution with mean and variance-covariance matrix given by the point estimates andvariance-covariance matrix of the regression coefficients.For each draw, we compute the implied response of outputto a realization of S of one percentage point. The standarderror for the response at month h is then the standarddeviation across the different draws of the estimated re-sponses at month h. The standard errors used in constructingthe figures are based on 500 draws.


(�6.4%, �3.0%). Thus it encompasses both noeffect and the estimated maximum impact.18

Since it is not plausible that contractionarypolicy raises output, the finding of a significantpositive coefficient on the first lag of the shock

18 These results are similar in their essentials to those inour earlier work on the real effects of monetary policy(Romer and Romer, 1989, 1994). In the earlier papers weidentified only a very specific type of shock: Federal Re-serve decisions to contract aggregate demand in order toreduce inflation from its current level. We found that themaximum impact of such a decision on industrial produc-tion was a reduction of 12 percent after 32 months. Like ournew measure, this anti-inflation shock variable is designedto isolate changes in monetary policy not taken in responseto anticipated developments. It is, however, not calibrated asthe new measure is, and does not include expansionary

shocks. The obvious reason that the earlier studies found alarger effect is that the average shock is much larger: in theseven episodes we identify, the actual monthly funds raterose an average of 3.6 percentage points (measured as thedifference between the low in the six months before theshock to the high in the six months after the shock). Thefinding that the lags with which policy affects output arelonger for these shocks than for our new measure couldstem from the fact that important interest rate movementsoften occurred after the decisions to follow tighter policythat we identify.

TABLE 3—THE IMPACT OF MONETARY POLICY SHOCKS ON INDUSTRIAL PRODUCTION

Monetary policy shock Change in industrial production

Lag Coefficient Standard error Lag Coefficient Standard error

1 0.0038 0.0018 1 0.063 0.0642 0.0026 0.0018 2 �0.013 0.0633 �0.0038 0.0018 3 0.107 0.0634 �0.0012 0.0018 4 0.048 0.0635 �0.0039 0.0018 5 0.028 0.0636 �0.0001 0.0018 6 �0.005 0.0637 �0.0008 0.0019 7 0.018 0.0638 �0.0029 0.0019 8 0.008 0.0639 �0.0021 0.0019 9 0.040 0.062

10 �0.0047 0.0018 10 �0.043 0.06111 �0.0025 0.0019 11 0.071 0.05912 �0.0035 0.0019 12 0.287 0.06013 �0.0021 0.0019 13 0.023 0.06114 �0.0007 0.0018 14 �0.196 0.06015 �0.0003 0.0019 15 �0.151 0.06116 0.0019 0.0018 16 �0.128 0.06217 �0.0009 0.0018 17 0.078 0.06318 �0.0024 0.0018 18 0.085 0.06319 �0.0023 0.0019 19 0.056 0.06320 �0.0007 0.0019 20 0.081 0.06321 �0.0011 0.0019 21 �0.060 0.06322 �0.0032 0.0018 22 �0.017 0.06323 0.0015 0.0019 23 �0.068 0.06324 �0.0000 0.0019 24 0.086 0.06325 �0.0001 0.001926 �0.0000 0.001927 �0.0007 0.001928 0.0038 0.001929 0.0013 0.001930 0.0035 0.001931 0.0018 0.001932 0.0009 0.001833 0.0014 0.001834 0.0047 0.001835 0.0011 0.001836 0.0024 0.0018

Notes: R2 � 0.86; D.W. � 2.01; s.e.e. � 0.009; N � 324. The sample period is 1970:1–1996:12.Coefficients and standard errors for the constant term and monthly dummies are not reported.


variable is troubling. Closer inspection of thedata reveals that this result is due to the April1980 observation. Our shock measure for April1980 is �3.2 percentage points, and industrialproduction fell 2.5 percent (seasonally adjusted)from April to May. Setting the April shock tozero lowers the coefficient on the first lag from0.0038 to 0.0023, and the t-statistic from 2.1 to1.1. Examination of the Record of Policy Ac-tions for the April 1980 meeting yields no evi-dence that the FOMC’s decision to easeaggressively was based on information aboutunfavorable economic prospects beyond the in-formation contained in the Greenbook forecast.Indeed, if anything the members’ outlook mayhave been less pessimistic than the forecast.Thus, there is no reason to think that our shockseries is mismeasured. The most likely possibil-ity is therefore that the positive coefficient onthe first lag of our shock variable reflectssampling error due to the single extremeobservation.

Robustness.—We investigate the robustnessof these results along four dimensions. First,because our estimated policy changes are larg-est and least certain during the early part of theperiod of nonborrowed reserve targeting underPaul Volcker, we reestimate equation (2) treat-ing the policy measure as missing from October1979 through May 1981. Omitting these obser-vations weakens the results only slightly. Theestimated peak effect is now �3.4 percentrather than �4.3 percent, and the estimatedeffect after 48 months is �0.2 percent ratherthan �1.7 percent. The omission of the infor-mation from the early Volcker era raises the

standard errors of the estimated effects only byabout 10 percent.

Second, we examine the effects of including48 rather than 36 lags of the policy measure.This change has virtually no impact on the pointestimates or standard errors through month 36.Thereafter the inclusion of the additional lagsincreases the extent of mean reversion. With theadditional lags, the estimated impact at month48 is �0.8 percent rather than �1.7 percent.

Third, we investigate the robustness of ourfindings to alternative specifications of the re-gression used to derive the shock series. Usingany of the alternative shock series described inSection I, subsection C, leads to very similarestimates of the effect of monetary shocks onoutput. For example, using the residuals from theregression of the intended funds rate on FederalReserve forecasts estimated separately before andafter 1983 leads to an estimated peak effect ofmonetary policy on output of �3.9 percent.

Fourth, we examine the effects of controllingfor a measure of supply shocks. We describe thisexperiment in Section II, subsection C, below.

Broader Measures of Policy.—It is importantto compare the results using our measure withthose using broader measures. A finding that theestimated effects of policy on output are similarusing both our new measure and broader mea-sures would suggest that the broader measuresare not severely contaminated by endogenousand anticipatory movements, and thus wouldallow researchers to use those measures withmore confidence. A finding that the estimatedeffects are very different, on the other hand,would suggest that using a narrower measuresuch as ours is important.

To investigate this issue, we reestimate equa-tion (2) using the change in the actual funds ratein place of our shock series. The top panel ofFigure 3 displays the estimated response of out-put to a one-percentage-point rise in the fundsrate. The effects of policy using the change inthe actual funds rate are both substantiallyslower and considerably smaller than with ourmeasure. The estimated effect becomes nega-tive beginning in month 6, only a month laterthan it does with our measure. However, theeffect is close to zero through month 10, and isless than a third as large as with our measurethrough month 17. The effect reaches �2.4

FIGURE 2. THE EFFECT OF MONETARY POLICY ON OUTPUT



percent in month 30 and is roughly flat thereaf-ter. With our measure, in contrast, the estimatedeffect peaks at �4.3 percent in months 22–27.At all horizons, there is considerable overlapbetween the two-standard-error confidence in-tervals using the actual funds rate and using ournew series. Nonetheless, the contrast betweenthe point estimates using the two measures sug-gests that endogenous and anticipatory move-ments in interest rates have a quantitativelyimportant impact on the estimated speed andsize of the effect of policy on output.19

We also estimate equation (2) using thechange in the intended funds rate and thechange in the actual funds rate controlling forthe forecasts. The results are shown in the bot-tom panel of Figure 3. The results using bothintermediate broader series are similar to thoseobtained using the change in the actual fundsrate. That the results using both intermediateseries are quite different from those using thenew measure, and similar to those using theactual funds rate, suggests that dealing withboth endogeneity and anticipatory movementsis important to estimating the effects of policy.Indeed, the fact that neither correction alone hasa large impact, while the two together clearlydo, suggests that there are important interactioneffects between the two corrections.

B. Prices

Methodology and Basic Results.—Our newseries can also be used to estimate the impact ofmonetary policy on inflation and the price level.While there are few broad monthly output mea-sures, there are a number of reliable monthlyprice indexes to choose from. In our baselineregressions we use the PPI for finished goods,which is a standard measure covering a widerange of goods.20 We discuss the results usingother common measures below.

19 As Figure 1 makes clear, the actual funds rate issubstantially more volatile than our new measure. If the twoseries are highly correlated, this difference in volatilitycould account for some of the difference in the estimatedeffects of policy when we consider the same one-percent-age-point innovation in each series. To investigate thisissue, we first regress the change in the actual funds rate on24 own lags and the contemporaneous value and 36 lags ofour new shock measure, and compute the implied responseof the actual funds rate to a one-percentage-point realization

of our new measure. We find that the funds rate rises morethan one-for-one with our measure for the first few monthsfollowing a shock, but quickly falls to zero (and thenbelow). We then compute what the coefficients from equa-tion (2) (estimated using the actual funds rate) imply abouthow industrial production responds to this path of the fundsrate. That is, we calculate the response of output, not to aone-percentage-point rise in the funds rate, but to the usualresponse of the funds rate to a one-percentage-point real-ization of our new measure. We find that only about half ofthe gap between the maximum effect estimated using ourmeasure and the maximum effect estimated using the fundsrate goes away when we make this change. At shorterhorizons, an even smaller portion of the gap is eliminated.Furthermore, because the estimated effects of the actualfunds rate on output are close to zero for ten months,changing the path of the funds rate considered has no effecton the speed of the output response. Therefore, our findingthat output responds more quickly using our new measurethan using the actual funds rate is robust to considering thealternative path for the funds rate.

20 The PPI data are not seasonally adjusted. Theyare from the Bureau of Labor Statistics Web site(http://wwwbls.gov), series WPUSOP3000.

FIGURE 3. THE EFFECT OF BROADER MEASURES OF

MONETARY POLICY ON OUTPUT


http://www.atypon-link.com/action/showImage?doi=10.1257/0002828042002651&iName=master.img-002.jpg&w=191&h=279

Our approach parallels the one we use toexamine the impact of policy on output. Theone change is that because there appear to belonger lags in the impact of policy on prices, ourbasic specification includes 48 rather than 36lags of the policy measure. Thus our baselineregression is

(3) �pt � a0 � �k � 1

11

ak Dkt � �i � 1

24

bi�pt � i

� �j � 1

48

cjSt � j � et ,

where p is the log of the PPI for finished goods.The estimates are reported in Table 4.

Figure 4 shows the estimated cumulativeimpact on the PPI for finished goods of arealization of our policy measure of one per-centage point, together with one-standard-error confidence bands. The estimated impactis virtually zero for the first 22 months afterthe shock. The price level rises for the firsteight months, but the maximum impact is just0.3 percent and is not close to statisticallysignificant. Two years after the contractionarypolicy shock, prices begin to fall substan-tially. The estimated impact is �1.9 percentafter 30 months and �5.9 percent after 48months. The effect becomes progressivelymore statistically significant. The t-statisticreaches 2 (in absolute value) in month 29, 4 inmonth 37, and 5 in month 43. The two-standard-error confidence interval for the effect after 48months is (�8.0%, �3.7%).21

The finding that inflation slows only after a

substantial delay raises the possibility that ourpolicy measure still contains some anticipa-tory actions, so that the true effect of policy isfaster and larger than our estimates imply.However, two considerations suggest that thisis unlikely. First, the possibility that theFOMC has important information about infla-tion beyond what is in its forecasts seemsmost plausible for very short horizons. If theFOMC were setting policy on the basis ofadditional information about the very nearterm, one would expect to see a clear positiveestimated impact of policy on inflation atshort horizons followed by a negative impact.But instead, we find no clear effect for twoyears. Second, as described below, when weadd commodity prices—which is the seriesmost often thought to provide additional in-formation about future inflation—to the infla-tion regression, the estimated effects of policyon prices are no faster or stronger than before.Indeed, if anything they are weaker. Thus, themost likely possibility is that there are genu-inely long delays in the impact of monetarypolicy on inflation.

Robustness.—These results do not depend onthe large swings in our policy measure in theearly Volcker period. Treating the measure asmissing from October 1979 through May 1981has virtually no impact on the point estimates.The standard errors increase by about 20 per-cent, but the effects remain overwhelminglysignificant.

Using the shock series derived from thealternative specifications of the regression ofthe intended funds rate on Federal Reserveforecasts also has little impact on the results.For example, a one-percentage-point innova-tion in the shock series derived using separateregressions on Federal Reserve forecasts be-fore and after 1983 has a cumulative impacton the price level of �6.6 percent after 48months. At the same time, using these alter-native shock series typically increases thestandard errors, though never by enough torender the estimated impact insignificantlydifferent from zero.

Our results are also robust to the measure ofprices. We reestimate equation (3) using boththe CPI excluding shelter and the chain-type price index for personal consumption

21 Our shock series accounts for a moderate amount ofthe nonseasonal variation in both output growth andinflation. Consider, for example, equations (2) and (3)estimated with seasonally adjusted data and without theseasonal dummies. For the output equation, (2), exclud-ing the shock variables lowers the R2 of the regressionfrom 0.414 to 0.281. For the price equation, (3), it lowersthe R2 from 0.483 to 0.340. Our shock series reflects onlya subset of independent shifts in monetary policy, andobviously much of the month-to-month variation in bothoutput growth and inflation stems from idiosyncraticsources. Thus, the explanatory power of the shock seriesis substantial.


TABLE 4—THE IMPACT OF MONETARY POLICY SHOCKS ON PRICES

Monetary policy shock Change in producer prices

Lag Coefficient Standard error Lag Coefficient Standard error

1 0.0006 0.0009 1 0.192 0.0652 0.0001 0.0009 2 0.002 0.0653 �0.0005 0.0009 3 �0.038 0.0654 0.0010 0.0009 4 �0.098 0.0655 0.0014 0.0009 5 0.009 0.0666 �0.0006 0.0009 6 0.107 0.0657 0.0001 0.0009 7 �0.056 0.0658 0.0005 0.0009 8 0.050 0.0659 �0.0013 0.0009 9 0.074 0.065

10 0.0009 0.0009 10 �0.049 0.06511 �0.0016 0.0009 11 0.087 0.06512 �0.0003 0.0009 12 0.127 0.06513 0.0001 0.0009 13 �0.071 0.06514 �0.0002 0.0009 14 �0.020 0.06415 0.0010 0.0009 15 �0.019 0.06416 �0.0004 0.0009 16 �0.018 0.06317 0.0003 0.0009 17 0.056 0.06318 �0.0012 0.0009 18 0.029 0.06319 0.0005 0.0009 19 0.009 0.06220 �0.0020 0.0009 20 0.093 0.06321 0.0002 0.0009 21 0.004 0.06322 �0.0001 0.0009 22 �0.004 0.06323 �0.0013 0.0009 23 �0.057 0.06224 �0.0019 0.0009 24 0.045 0.06125 �0.0024 0.000926 �0.0025 0.001027 �0.0017 0.001028 �0.0002 0.001029 �0.0022 0.001030 �0.0033 0.001031 �0.0031 0.001032 �0.0006 0.001033 �0.0013 0.001034 �0.0010 0.001035 �0.0015 0.001036 �0.0033 0.001037 �0.0019 0.001038 �0.0016 0.001039 0.0001 0.001040 �0.0017 0.001041 �0.0007 0.001042 �0.0029 0.001043 �0.0013 0.001044 �0.0003 0.000945 �0.0014 0.000946 0.0001 0.000947 �0.0015 0.000948 �0.0008 0.0009

Notes: R2 � 0.57; D.W. � 2.00; s.e.e. � 0.005; N � 324. The sample period is 1970:1–1996:12. Coefficients and standard errors for the constant term and monthly dummies are notreported.


expenditures from the National Income andProduct Accounts.22 The estimated responses ofthese series to a realization of our policy mea-sure of one percentage point are given in Figure5. Using either alternative, the price effects of amonetary shock remain large and overwhelm-ingly significant. There are two interesting dif-ferences from our baseline results. First, theeffects are somewhat smaller: with either alter-native, the impact after 48 months is �3.6 per-cent (t � 4.3 for the CPI excluding shelter and5.0 for the PCE price index), as opposed to�5.9 percent (t � 5.5) when the PPI for finishedgoods is used. Second, when we use the PCEprice index (but not the CPI excluding shelter),the estimates suggest that the price level turnslower immediately after a shock. The estimatedshort-run price effects are quite small, however;for example, the estimated effect after 18months is �0.3 percent (t � 0.8).

Broader Measures of Policy.—We againcompare the results using our new policy mea-sure with those obtained using the change in theactual federal funds rate. Since the results aresimilar for all three price measures, in this andall subsequent analysis we only report the re-sults using the PPI for finished goods. The toppanel of Figure 6 shows the estimated cumu-

lated response of the price level to a one-percentage-point rise in the actual funds rate.The estimates imply that the price level rises byabout 1 percent over the first two years after acontractionary move and is then essentially con-stant. Thus, the point estimates are radicallydifferent from those using our new measure.Moreover, in contrast to the results for output,for prices the two-standard-error confidence in-tervals using the actual funds rate and using ournew measure are far apart. At 48 months, forexample, the confidence interval is (�1.4%,�3.3%) using the actual funds rate and(�8.0%, �3.7%) using the new measure.

This finding that prices typically rise ratherthan fall after Federal Reserve tightenings whenpolicy is measured using the funds rate is rep-resentative of the “price puzzle” found by manyprevious studies. The fact that there is a strongprice puzzle when the actual funds rate is used,but not when our new measure is used, stronglysuggests that the funds rate is contaminated byendogenous and anticipatory movements. As aresult, it yields inaccurate estimates of the ef-fects of policy, at least in the simple specifica-tions we consider. The next two subsectionsaddress the question of whether the funds ratecan nevertheless yield accurate estimates inmore complicated specifications.23

The bottom panel of the figure shows the

22 The CPI data are from the Bureau of Labor StatisticsWeb site, series CUUR0000SA0L2. The PCE data are fromthe Bureau of Economic Analysis Web site (http://www.bea.gov), series P1PCEG B. Because the PCE price index isonly available in seasonally adjusted form, in the regressionusing this series we omit the seasonal dummies.

23 Because the estimated price effects using the actualfunds rate and using our new measure are of opposite signs,considering the alternative path of the funds rate discussedin footnote 19 does not eliminate the fundamental differencebetween the two sets of estimates.

FIGURE 5. THE EFFECT OF MONETARY POLICY USING

ALTERNATIVE MEASURES OF THE PRICE LEVELFIGURE 4. THE EFFECT OF MONETARY POLICY ON THE

PRICE LEVEL




effects of using our two intermediate broadermeasures: the change in the intended ratearound FOMC meetings, and the residuals froma regression of the change in the actual fundsrate on the Greenbook forecasts. When we usethe change in the intended funds rate aroundFOMC meetings but do not control for the fore-casts, the results are similar to those using thechange in the actual funds rate. When we con-trol for the forecasts but do not restrict ourattention to intended changes in the funds rate,the results show a very slow and weak effect ofpolicy on prices: the price level does not turndown until 25 months after a shock, and after 48months it is only 1.9 percent lower (t � 2.8).These estimated effects are roughly midwaybetween those using the change in the actualfunds rate and those using our shock series.

That the results for both intermediate broadermeasures are quite different from those usingour new measure suggests again that consider-ing only intended interest rate changes and con-

trolling for the Federal Reserve’s forecasts areboth critical to estimating the effects of policy.At the same time, the fact that using the fundsrate controlling for the forecasts moves the re-sults noticeably closer to those using our newmeasure suggests that, at least for prices, antic-ipatory movements are the more importantsource of bias when the actual funds rate is usedas the measure of policy.

C. Supply Shocks

Motivation.—We have attempted to removeanticipatory movements from our measure ofmonetary policy shocks by controlling for theFederal Reserve’s internal forecasts. However,it is obviously possible that some such move-ments are still present in our measure. Remain-ing anticipatory policy moves could be theresult of the Federal Reserve having additionalinformation about either supply shocks or de-mand shocks that is not included in theforecasts.

The literature on the effects of monetary pol-icy has tended to emphasize the consequencesof uncaptured responses to supply shocks. Ifsome of the changes that an econometricianinterprets as policy shocks are in fact responsesto supply shocks that will lower output in thefuture, this would lead to overestimates of thestrength of the negative relationship betweencontractionary policy shocks and output. Like-wise, because a supply shock will raise inflationin the future, uncaptured responses to supplyshocks would lead to underestimates of the neg-ative effect of contractionary policy on pricesand, in extreme cases, to a finding of a posi-tive correlation between prices and monetarycontraction.

This literature has suggested that an index ofworld commodity prices is a particularly timelyindicator of supply shocks. Adding world com-modity prices to our regressions therefore pro-vides a test of whether our new measure stillincludes some policy moves taken in responseto supply shocks. If adding this measure ofsupply shocks makes the estimated impact ofpolicy on output weaker (that is, less negative)and its estimated impact on prices stronger(more negative), this would indicate that ournew measure is positively correlated withsupply shocks. This would suggest that our

FIGURE 6. THE EFFECT OF BROADER MEASURES OF

MONETARY POLICY ON THE PRICE LEVEL



measure is still somewhat contaminated by an-ticipatory movements. But if controlling for abroad measure of supply shocks has no impor-tant effect on the estimates, this would stronglysuggest that our measure largely reflects inde-pendent changes in policy.

Including Commodity Prices in Our BasicSpecification.—To investigate the effects ofcontrolling for commodity prices, we add thecontemporaneous value and 12 lags of the per-centage change in world commodity prices toour basic output and price regressions.24 Theresults are shown in the top panels of Figures 7and 8. They give no hint that unmeasured re-sponses to supply shocks are affecting our re-sults. The idea that the Federal Reserve has

important additional information about supplyshocks is most plausible for short horizons. Yetthe estimated short-run effects of policy are virtu-ally unaffected by controlling for commodityprices. For output, there is no discernible changein the impact of policy for the first five months.For prices, this is true for the first 20 months.

Controlling for commodity prices doeschange the estimated impacts moderately there-after. For output, the estimated impacts areslightly smaller than before. The estimated cu-mulative effect is �1.8 percent rather than �2.1percent after 12 months, and �3.2 percentrather than �4.3 percent after 24. These differ-ences, though small and delayed, are in thedirection one would expect if a portion of whatwe identify as policy shocks are actually re-sponses to supply shocks.

For prices, however, the estimated impact ofpolicy in fact falls moderately when we controlfor commodity prices. It is �0.2 percent ratherthan �0.5 percent after 24 months, and �4.4

24 The series that we use is the index of world commod-ity prices from International Financial Statistics (seriesCMPRI02).

FIGURE 7. THE EFFECT OF MONETARY POLICY ON OUTPUT

WITH AND WITHOUT COMMODITY PRICESFIGURE 8. THE EFFECT OF MONETARY POLICY ON THE

PRICE LEVEL WITH AND WITHOUT COMMODITY PRICES




percent rather than �5.9 percent after 48. Thisis the opposite of what one would expect if ourmeasure were contaminated by responses tosupply shocks. In short, the impact of control-ling for commodity prices is small and does notfit the pattern one would expect if our newmeasure still included important responses tosupply shocks.

Including Commodity Prices in the Regres-sion Using a Broader Measure of Policy.—Asdescribed above, the previous literature has sug-gested that an index of commodity prices cap-tures the most important information to whichthe Federal Reserve responds. It therefore ar-gues that including this measure of supplyshocks in regressions estimating the effects ofmonetary policy using broad policy indicators isenough to deal with the problem of anticipatorymovements. And, indeed, previous work hasfound that including world commodity priceslargely eliminates the price puzzle.

But, the fact that the estimates have the antici-pated sign does not mean they are free of bias.There are clearly other possible sources of uncap-tured anticipatory policy movements. Most obvi-ously, the Federal Reserve surely responds toanticipated inflation caused by demand shocks aswell as by supply shocks. In addition, there couldbe indicators of supply shocks other than com-modity prices that the Federal Reserve respondsto. As a result, the estimates of the effects ofmonetary policy derived using broad measures ofpolicy controlling for world commodity pricesmay still yield inaccurate results.

To address this issue, we add commodityprices to our regressions that use the change inthe actual funds rate. As before, we include thecontemporaneous value and 12 lags of thechange in commodity prices. The results of thisexercise are presented in the bottom panels ofFigures 7 and 8. The estimates of the impact ofmonetary policy move in the direction onewould expect: both the estimated declines inindustrial production and the estimated rises inproducer prices in response to contractionarymonetary policy become slightly weaker whencommodity prices are controlled for. This sup-ports the standard view that changes in thefunds rate include a component that representsresponses to supply shocks rather than indepen-dent changes in policy.

Crucially, however, the estimated effects ofpolicy when commodity prices are included inthe regressions continue to be very differentwhen the actual funds rate is used as the mea-sure of policy than when our new measure isused. For output, the estimated impact of pol-icy for the first two years remains about twoto three times weaker when the actual funds rateis used than when our measure is used. Forprices, for our particular specification and sam-ple, controlling for commodity prices does noteven eliminate the price puzzle from the resultsthat use the actual funds rate: the estimatedimpact of policy on prices remains positive(though it is no longer ever significantly differ-ent from zero). With our measure, in contrast,the estimated effects of policy are negative,large, and statistically significant either with orwithout controlling for commodity prices. Wetake this as strong evidence that controlling forcommodity prices is not enough to solve thedifficulties with the funds rate as a measure ofpolicy.25

D. Vector Autoregressions

Motivation.—Vector autoregressions areoften used to estimate the effects of policy.It is therefore useful to embed our new mea-sure of monetary policy shocks in a VARso that we can compare our results more di-rectly with those from earlier studies. VARsalso have the advantage of controlling for thepast behavior of all the variables in thesystem.

The interpretation of the impulse responsefunctions from a VAR is complicated, how-ever.26 An impulse response function for outputor prices to a monetary policy innovation re-flects both the effect of the initial innovationand the effect of the predictable subsequentmoves in the policy measure. In the case where

25 The results of our various robustness checks in theregressions controlling for commodity prices are verysimilar to the results of our baseline specifications. Forthis reason, we do not detail the results of the individualrobustness checks. We also do the experiment of addingworld commodity prices to the regressions using theintermediate broader measures of policy. The results forthese regressions are similar to those using the actualfunds rate.

26 This point is discussed by John H. Cochrane (1998).


only unanticipated changes affect output orprices, the impulse response function simplyshows the impact of the innovation. But antic-ipated movements in interest rates almost surelyaffect output and prices. For example, the re-sponse of output to a surprise change in ourmeasure would surely be different if a surprisechange were typically followed quickly by ad-ditional shifts in policy in the same directionthan if it were typically followed by large off-setting policy moves. Similarly, no reasonablemodel implies that prices do not respond toforecastable policy changes. Thus, what theVAR impulse response functions capture are thecombined effects of the initial innovation andthe later policy moves that are forecastablebased on the innovation.

VARs Using Our New Measure of MonetaryPolicy Shocks.—The specific VAR we consideris a variant of the one examined by Christiano etal. (1996). Our basic VAR has three variables:the log of industrial production, the log of thePPI for finished goods, and a measure of mon-etary policy. Following Christiano et al., wealso consider a VAR that adds commodityprices. Throughout, we use Christiano et al.’srecursive identification strategy: monetary pol-icy is assumed to respond to, but not to affect,the other variables contemporaneously. Chris-tiano et al.’s VAR includes only a year of lags.Thus, monetary policy is not allowed to haveany direct impact on the economy at horizonsbeyond a year. Since this assumption is verystrong and highly questionable, we do not im-pose it. Instead, we include three years of lags inour baseline specification.

Our key difference from Christiano et al. isour measure of monetary policy. Our basicspecification employs our new measure of pol-icy shocks, whereas Christiano et al. use theactual funds rate. Since standard VARs enterthe federal funds rate in levels, we cumulate ourshock to produce a comparable series.

Figure 9 shows the response of the cumulatedshock, output, and the price level to a one-percentage-point innovation in the shock, to-gether with the one-standard-error bands. Thetop panel shows that the cumulated shock fallsto about half its initial level after about a yearand is then fairly flat. Thus the experimentconsidered here involves a less persistent

change than the permanent, one-time shockconsidered above.

The other two panels of the figure show thatthe responses of output and prices are broadlysimilar to those we found in the simple re-gressions reported above. Output rises by asmall amount for the first two months, thenfalls sharply through month 23, and thenreturns toward its initial level. The maxi-mum t-statistic is over 3. For output, themain difference from our earlier findings isthat the estimated effect is smaller. For ex-ample, the peak effect is 2.9 percent here, asopposed to 4.3 percent in the single-equationregression. Presumably this reflects the factthat in the experiment considered here, a sub-stantial part of the interest rate movement isundone quickly. Also, output returns essen-tially all the way to its initial level here, as

FIGURE 9. THE EFFECT OF MONETARY POLICY IN A VARUSING THE NEW MEASURE OF MONETARY POLICY SHOCKS



opposed to two-thirds of the way in the earlierresults.

The response of prices implied by the VAR issmall, irregular, and insignificant for eightmonths, and then negative. The monetary policyinnovation lowers the price level by 0.5 percentafter 18 months, 2.4 percent after 30, and 5.0percent after 48. The t-statistic reaches 2 inmonth 20, 3 in month 24, and 4 in month 26.This response is somewhat faster than we foundin our simple regression, where the price levelwas essentially unaffected until almost twoyears had passed.27

The effects of adding commodity prices tothe system are similar to those of adding them tothe baseline regressions. There are no majorchanges in the patterns or magnitudes of theresponses of output and the price level to aninnovation in the policy measure. The estimatedoutput effects become somewhat smaller, peak-ing at �1.9 percent after 22 months (t � 2.7);and the estimated price effects also fall some-what, reaching �3.8 percent after 48 months(t � 4.5).

VARs Using a Broader Measure of MonetaryPolicy.—We also estimate the VAR using theactual funds rate as the indicator of monetarypolicy. The estimated impact of policy on out-put is much slower and smaller than with ourmeasure. And the price puzzle reemergesstrongly: the price level does not fall below itsinitial level until about two years after theshock. This supports our earlier conclusion thatthe actual funds rate is contaminated by endo-geneity and responses to anticipated economicdevelopments.

As in other VARs, adding commodity pricesto the system using the actual funds rate largely

eliminates the price puzzle. There is now neverany noticeable rise in the price level followingan interest rate innovation; the peak effect is�0.1 percent after seven months. Crucially,however, the fall is dramatically weaker thanwith our new measure. For example, the effectof a monetary shock on the price level after 48months is �0.5 percent using the actual fundsrate, as opposed to �3.8 percent using our newmeasure. Similarly, the output effects remainmuch smaller than with our measure. The max-imum effect of a shock on industrial productionis �0.9 percent using the actual funds rate, and�1.9 percent using our measure. This suggestsonce again that including commodity prices isonly a partial solution to the problem offorward-looking policy-making.

The VARs estimated using our new mea-sure suggest larger but not faster output ef-fects of monetary policy than found inprevious VAR studies. Sims (1992), Chris-tiano et al. (1996), and Bernanke and Mihov(1998), using VARs with broad policy mea-sures and controlling for commodity prices,all find that output begins falling three to sixmonths after a shock. This is similar to whatwe find using our new measure. Sims esti-mates a maximum impact of a one-percent-age-point innovation in the funds rate onindustrial production of about 1.5 percent,and Bernanke and Mihov and Christiano et al.find a maximum effect on real GDP ofslightly less than 1 percent. In contrast, theVARs using our new measure suggest a max-imum impact on industrial production of 2 to3 percent. Thus, our results suggest that mon-etary policy has a larger impact on outputthan traditionally believed.

For prices, VARs estimated using our newmeasure suggest effects that are both muchlarger and much faster than previous estimates.Sims, Christiano et al., and Bernanke andMihov find that when commodity prices arecontrolled for, a one-percentage-point innova-tion in the funds rate has little effect on pricesfor about a year and a half, and then causes adecline of 1 to 2 percent over the next fewyears. But the VARs with our new measuresuggest a much stronger response: the priceeffect is consistently negative after six monthswhen commodity prices are controlled for andafter nine months when they are not, and the

27 Restricting the number of lags, as Christiano et al.do, has mixed effects. When we reestimate our VAR withonly one year of lags, the estimated response of output toa policy shock tracks the response with three years of lagsclosely for a year, but then diverges. The response peaksat �1.5 percent after 12 months. Reducing the number oflags has a smaller effect on the estimated response ofprices, though again the estimated impact is smaller whenfewer lags are included. These findings suggest that thetrue response of output and prices to monetary policy isquite drawn out, and that forcing the direct effects to bezero after a year leads to underestimates of the effects ofpolicy.


price level is roughly 4 to 5 percent lower afterfour years.28

III. Conclusion

Determining how monetary policy affects theeconomy is critically important both for distin-guishing between competing theories of fluctu-ations and for conducting policy. Unfortunatelyfor economists interested in estimating the ef-fects of policy, monetary policy is not con-ducted as a randomized experiment. There is nounique instrument of policy, such as the federalfunds rate, that the Federal Reserve always fo-cuses on. As a result, any candidate measure ofpolicy sometimes moves in response to outsideeconomic developments rather than to decisionsby the Federal Reserve. More importantly, indeciding how to move its instruments, the Fed-eral Reserve considers a tremendous amount ofinformation about likely future movements inmacroeconomic variables. As a result, measuresof policy are likely to include many anticipatorymovements. Because of these problems withconventional policy measures, estimating theeffects of policy is extremely difficult.

To derive more accurate estimates of the ef-fects of policy, this paper proposes and imple-ments a new method for isolating monetarypolicy shocks. Our approach considers onlychanges in the federal funds rate that are theresult of deliberate decisions by the FederalReserve made at meetings for which there is aforecast prepared by the staff. We then removethe portions of these moves in the intended

funds rate that represent the Federal Reserve’susual response to the forecasts. The resultingseries should be largely free of interest ratemovements that are either endogenous re-sponses to economic developments or attemptsby policy makers to counteract likely futuredevelopments. The movements in output andinflation in the wake of our new measure ofmonetary shocks should therefore reflect theimpact of monetary policy, and not otherfactors.

Estimates of the effects of policy using thenew shock series indicate that monetary policyhas large and statistically significant effects onreal output. In our baseline specification, ashock of one percentage point starts to reduceindustrial production after five months, with amaximum fall of 4.3 percent after two years.The peak effect is highly statistically significant.For prices, we find that the one-percentage-pointshock has little effect for almost two years, butthen lowers the inflation rate by 2 to 3 percent-age points. As a result, the price level is about6 percent lower after four years. This estimate isoverwhelmingly significant. The results for bothoutput and prices are quite robust to variationsin sample periods, control variables, specifica-tion, and the particular regression used to formour shock measure. The results are also robustto the measure of prices used. The most impor-tant uncertainty concerns the lag in the impactof policy on prices: in some specifications, theprice level begins falling within six months afterthe policy shock, while in others it is unchangedfor as much as 22 months.

Qualitatively, our findings are very consistentwith textbook views of the effects of monetarypolicy. Contractionary monetary policy reducesboth output and inflation. Both effects occurwith a lag, with output moving before inflation.Quantitatively, the results suggest that the lagsin the output effects are fairly short, while thelags in the inflation effects are harder to deter-mine. More importantly, the results indicate thatthe impacts of monetary policy on both outputand inflation are large.

28 Our finding of larger price effects than earlier studiesappears to be due partly to our focus on the PPI for finishedgoods. However, when we use the alternative price series,the effect after four years is slightly under 3 percent, whichis still substantially larger than previous work has found. Asbefore, the results of our robustness exercises in the VARsare similar to the results of the robustness exercises in theunivariate regressions. We also estimate the VARs using theintermediate broader measures of policy. The results arequalitatively similar to those when the VAR is estimatedusing the actual funds rate.


TABLE A1—CHANGES IN INTENDED FEDERAL FUNDS RATE AT FOMC MEETINGS

Meetingdate

Initialintended

rate(percent)

Change inintended

rate(percent)

Meetingdate

Initialintended

rate(percent)

Change inintended

rate(percent)

Meetingdate

Initialintended

rate(percent)

Change inintended

rate(percent)

1/14/69 6.4375 0.0000 6/19/73 8.5000 0.5000 3/21/78 6.7500 0.00002/4/69 6.4375 0.0000 7/17/73 9.7500 0.2500 4/18/78 6.7500 0.25003/4/69 6.7500 �0.1250 8/21/73 10.5000 0.2500 5/16/78 7.3125 0.18754/1/69 6.7500 0.5000 9/18/73 10.7500 �0.3750 6/20/78 7.5000 0.2500

4/29/69 7.6875 0.2500 10/16/73 10.5000 �0.7500 7/18/78 7.7500 0.12505/27/69 8.5000 0.1250 11/20/73 10.1250 0.0000 8/15/78 7.8750 0.12506/24/69 9.0000 0.0000 12/18/73 10.2500 �0.6250 9/19/78 8.3750 0.12507/15/69 9.0000 0.1250 1/22/74 9.7500 �0.3750 10/17/78 8.7500 0.25008/12/69 9.5000 0.2500 2/20/74 9.0000 �0.1250 11/21/78 9.6875 0.18759/9/69 9.0000 0.0000 3/19/74 9.1875 0.6875 12/19/78 9.8750 0.1875

10/7/69 9.1250 0.0000 4/16/74 9.8750 0.6250 2/6/79 10.0625 0.000010/28/69 9.1250 0.0000 5/21/74 11.0000 0.3750 3/20/79 10.0625 0.000011/25/69 9.1250 0.0000 6/18/74 11.6250 0.2500 4/17/79 10.0625 0.000012/16/69 9.0000 0.0000 7/16/74 12.7500 �0.5000 5/22/79 10.2500 0.00001/15/70 9.0000 �0.2500 8/20/74 12.2500 �0.3750 7/11/79 10.2500 0.00002/10/70 9.1250 �0.5000 9/10/74 11.7500 �0.6250 8/14/79 10.6250 0.37503/10/70 8.3125 �0.1875 10/15/74 10.4375 �0.8125 9/18/79 11.3750 0.1250

4/7/70 7.7500 0.0000 11/19/74 9.5000 �0.2500 10/6/79 11.5000 3.00005/5/70 8.2500 0.1250 12/17/74 8.8750 �0.6250 11/20/79 13.5000 0.0000

5/26/70 8.0000 0.0000 1/21/75 7.2500 �0.5625 1/9/80 13.5000 0.00006/23/70 7.8750 �0.2500 2/19/75 6.2500 �0.5000 2/5/80 13.5000 0.50007/21/70 7.3125 �0.2500 3/18/75 5.7500 �0.5000 3/18/80 16.5000 1.75008/18/70 6.7500 �0.5000 4/15/75 5.5000 �0.1250 4/22/80 18.3750 �3.87509/15/70 6.3750 �0.1875 5/20/75 5.1250 0.0000 5/20/80 10.8750 �1.3750

10/20/70 6.2500 �0.1250 6/17/75 5.2500 0.3750 7/9/80 9.3750 0.000011/17/70 5.7500 �0.6250 7/15/75 6.0000 0.1250 8/12/80 9.6250 0.250012/15/70 5.1250 �0.3750 8/19/75 6.1875 0.0000 9/16/80 10.2500 1.0000

1/12/71 4.5000 �0.5000 9/16/75 6.1250 0.2500 10/21/80 12.1250 1.50002/9/71 3.7500 �0.1250 10/21/75 5.7500 �0.2500 11/18/80 14.5000 1.75003/9/71 3.5000 0.1250 11/18/75 5.2500 �0.2500 12/19/80 18.7500 �0.75004/6/71 3.7500 0.3750 12/16/75 5.2500 0.0000 2/3/81 17.5000 �0.5000

5/11/71 4.2500 0.2500 1/20/76 4.7500 0.0000 3/31/81 15.0000 0.87506/8/71 4.7500 0.3750 2/18/76 4.7500 0.0000 5/18/81 18.5000 1.5000

6/29/71 5.1250 0.2500 3/16/76 4.7500 0.0000 7/7/81 18.5000 �1.00007/27/71 5.5000 0.1250 4/20/76 4.7500 0.1250 8/18/81 18.0000 �0.50008/24/71 5.6250 0.0000 5/18/76 5.1250 0.2500 10/6/81 15.5000 �1.00009/21/71 5.5000 �0.2500 6/22/76 5.5000 0.0000 11/17/81 13.5000 �1.0000

10/19/71 5.1875 �0.1250 7/20/76 5.2500 0.0000 12/22/81 12.1250 �0.250011/16/71 4.7500 �0.3750 8/17/76 5.2500 0.0000 2/2/82 14.0000 0.500012/14/71 4.3750 �0.6250 9/21/76 5.2500 0.0000 3/30/82 14.7500 �0.5000

1/11/72 3.6250 �0.3125 10/19/76 5.0000 �0.1250 5/18/82 14.0000 �0.75002/15/72 3.2500 0.0000 11/16/76 5.0000 �0.2500 7/1/82 14.0000 �0.50003/21/72 3.9375 0.3125 12/21/76 4.6875 �0.0625 8/24/82 10.2500 �0.75004/18/72 4.2500 0.1250 1/18/77 4.6250 0.0625 10/5/82 10.2500 �0.75005/23/72 4.2500 0.3125 2/15/77 4.6875 0.0000 11/16/82 9.5000 �0.50006/20/72 4.4375 0.1250 3/15/77 4.6875 0.0000 12/21/82 8.5000 0.00007/18/72 4.6250 0.0000 4/19/77 4.6875 0.1250 2/9/83 8.5000 0.00008/15/72 4.7500 0.1250 5/17/77 5.2500 0.1250 3/29/83 8.5000 0.12509/19/72 5.0000 0.1875 6/21/77 5.3750 0.0000 5/24/83 8.6250 0.2500

10/17/72 5.0625 0.1250 7/19/77 5.3750 0.0000 7/13/83 9.0625 0.312511/21/72 5.0625 0.1250 8/16/77 5.8750 0.1250 8/23/83 9.5625 �0.062512/19/72 5.3750 0.2500 9/20/77 6.1250 0.1250 10/4/83 9.3750 0.00001/16/73 5.7500 0.5000 10/18/77 6.5000 0.0000 11/15/83 9.3750 0.00002/13/73 6.3750 0.3125 11/15/77 6.5000 0.0000 12/20/83 9.5000 0.12503/20/73 7.0000 0.1250 12/20/77 6.5000 0.0000 1/31/84 9.3750 0.00004/17/73 7.0000 0.1875 1/17/78 6.7500 0.0000 3/27/84 10.1250 0.37505/15/73 7.5000 0.5000 2/28/78 6.7500 0.0000 5/22/84 10.5000 0.0000


REFERENCES

Barth, Marvin J., III and Ramey, Valerie A. “TheCost Channel of Monetary Transmission,” inBen S. Bernanke and Kenneth Rogoff, eds.,NBER macroeconomics annual 2001. Cam-bridge, MA: MIT Press, 2002, pp. 199–240.

Bernanke, Ben S. and Blinder, Alan S. “The Fed-eral Funds Rate and the Channels of Mone-tary Transmission.” American EconomicReview, September 1992, 82(4), pp. 901–21.

Bernanke, Ben S. and Mihov, Ilian. “MeasuringMonetary Policy.” Quarterly Journal of Eco-nomics, August 1998, 113(3), pp. 869–902.

Board of Governors of the Federal Reserve Sys-tem. Annual report, various years.

. Current economic and financial con-ditions, various issues.

. Minutes of Federal Open Market Com-mittee, various years.

. Monetary policy alternatives, variousissues.

. Transcripts of Federal Open MarketCommittee, various years.

Boivin, Jean. “The Fed’s Conduct of MonetaryPolicy: Has It Changed and Does It Matter?”Unpublished manuscript, Columbia Univer-sity, October 2001.

TABLE A1—Continued.

Meetingdate

Initialintended

rate(percent)

Change inintended

rate(percent)

Meetingdate

Initialintended

rate(percent)

Change inintended

rate(percent)

Meetingdate

Initialintended

rate(percent)

Change inintended

rate(percent)

7/17/84 11.0000 0.3750 9/20/88 8.1250 0.0000 12/22/92 3.0000 0.00008/21/84 11.5625 �0.0625 11/1/88 8.2500 0.0000 2/3/93 3.0000 0.000010/2/84 11.2500 �0.3750 12/14/88 8.4375 0.5625 3/23/93 3.0000 0.000011/7/84 10.0000 �0.7500 2/8/89 9.0000 0.1875 5/18/93 3.0000 0.1250

12/18/84 8.7500 �0.6250 3/28/89 9.7500 0.1250 7/7/93 3.0000 0.00002/13/85 8.5000 0.0000 5/16/89 9.8125 0.0000 8/17/93 3.0000 0.00003/26/85 8.5000 0.0000 7/6/89 9.5625 �0.2500 9/21/93 3.0000 0.00005/21/85 8.1250 �0.3750 8/22/89 9.0625 0.0000 11/16/93 3.0000 0.00007/10/85 7.6250 0.0000 10/3/89 9.0000 0.0000 12/21/93 3.0000 0.00008/20/85 7.8125 0.0000 11/14/89 8.5000 0.0000 2/4/94 3.0000 0.250010/1/85 7.8750 0.0000 12/19/89 8.5000 �0.2500 3/22/94 3.2500 0.250011/5/85 8.0000 �0.0625 2/7/90 8.2500 0.0000 5/17/94 3.7500 0.5000

12/17/85 7.9375 �0.1875 3/27/90 8.2500 0.0000 7/6/94 4.2500 0.00002/12/86 7.8125 0.0000 5/15/90 8.2500 0.0000 8/16/94 4.2500 0.50004/1/86 7.3750 0.0000 7/3/90 8.2500 �0.2500 9/27/94 4.7500 0.1250

5/20/86 6.8750 0.0000 8/21/90 8.0000 0.0000 11/15/94 4.7500 0.75007/9/86 6.8750 �0.5000 10/2/90 8.0000 �0.2500 12/20/94 5.5000 0.0000

8/19/86 6.3125 �0.3750 11/13/90 7.7500 �0.2500 2/1/95 5.5000 0.50009/23/86 5.8750 0.0000 12/18/90 7.2500 �0.2500 3/28/95 6.0000 0.000011/5/86 5.8750 0.0000 2/6/91 6.7500 �0.5000 5/23/95 6.0000 0.0000

12/16/86 6.0000 0.0000 3/26/91 6.0000 0.0000 7/6/95 6.0000 �0.25002/12/87 6.0000 0.0000 5/14/91 5.7500 0.0000 8/22/95 5.7500 0.00003/31/87 6.0625 0.1875 7/3/91 5.7500 0.0000 9/26/95 5.7500 0.00005/19/87 6.5000 0.2500 8/20/91 5.5000 0.0000 11/15/95 5.7500 0.00007/7/87 6.7500 0.0000 10/1/91 5.2500 0.0000 12/19/95 5.7500 �0.2500

8/18/87 6.6250 0.0000 11/5/91 5.2500 �0.5000 1/31/96 5.5000 �0.25009/22/87 7.2500 0.0000 12/17/91 4.5000 �0.2500 3/26/96 5.2500 0.000011/3/87 7.1250 �0.3125 2/5/92 4.0000 0.0000 5/21/96 5.2500 0.0000

12/16/87 6.8125 0.0000 3/31/92 4.0000 0.0000 7/3/96 5.2500 0.00002/10/88 6.6250 �0.1250 5/19/92 3.7500 0.0000 8/20/96 5.2500 0.00003/29/88 6.5000 0.2500 7/1/92 3.7500 �0.1250 9/24/96 5.2500 0.00005/17/88 7.0000 0.2500 8/18/92 3.2500 �0.1250 11/13/96 5.2500 0.00006/30/88 7.3750 0.2500 10/6/92 3.0000 �0.2500 12/17/96 5.2500 0.00008/16/88 8.1250 0.0000 11/17/92 3.0000 0.0000


Christiano, Lawrence J.; Eichenbaum, Martinand Evans, Charles. “The Effects of MonetaryPolicy Shocks: Evidence from the Flow ofFunds.” Review of Economics and Statistics,February 1996, 78(1), pp. 16–34.

Cochrane, John H. “What Do the VARs Mean?Measuring the Output Effects of MonetaryPolicy.” Journal of Monetary Economics,April 1998, 41(2), pp. 277–300.

Grieder, William. Secrets of the temple: How theFederal Reserve runs the country. New York:Simon & Schuster, 1987.

Jansson, Per and Vredin, Anders. “Forecast-Based Monetary Policy in Sweden 1992–1998: A View from Within.” SverigesRiksbank Working Paper No. 120, Febru-ary 2001.

Levin, Andrew; Wieland, Volker and Williams,John C. “Robustness of Simple Policy Rulesunder Model Uncertainty,” in John B. Taylor,ed., Monetary policy rules. Chicago: Univer-sity of Chicago Press (for NBER), 1999, pp.263–99.

Orphanides, Athanasios. “The Quest for Prosper-ity without Inflation.” Journal of MonetaryEconomics, April 2003, 50(3), pp. 633–63.

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Spirit of Friedman and Schwartz,” in OlivierJ. Blanchard and Stanley Fischer, eds., NBERmacroeconomics annual 1989. Cambridge,MA: MIT Press, 1989, pp. 121–70.

. “Monetary Policy Matters.” Journal ofMonetary Economics, August 1994, 34(1),pp. 75–88.

. “Federal Reserve Information and theBehavior of Interest Rates.” American Eco-nomic Review, June 2000, 90(3), pp. 429–57.

. “The Evolution of Economic Under-standing and Postwar Stabilization Policy,”in Rethinking stabilization policy. KansasCity, MO: Federal Reserve Bank of KansasCity, 2002, pp. 11–78.

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. “Term Structure Evidence on Mone-tary Policy Inertia and Interest Rate Smooth-ing.” Journal of Monetary Economics,September 2002, 49(6), pp. 1161–87.

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