Weekly Money Supply Forecasts:Effects of the October 1979 Change inMonetary Control ProceduresR. W~HAFER

rITE activity of most financial market participants

on Friday afternoons can be predicted with greataccuracy: they anxiously will he awaitimmg the 4:15p.m.EST ammnouucement of the new weekly money stockdata. Despite the fact that the weekly data are con-taminated by a great deal of “noise,” a fact that greatlyreduces the data’s usefulness imm revealing any policytrend, market participants still wager large sums andreputations on correctly anticipating the eltisive week-ly money figure.’

The impact of unanticipated changes in the weeklymoney supply on short-term interest rates has beeninvestigated extensively. In general, the evidenceshows a positive relationship between unanticipatedchanges in money and movements in market rates.2

Although this empirical relationship existed through-

tmSee David A. Pierce, Trend amid Noise imm the ~ionetary Aggre-

gates,’ in Federal Reserve Staff Study New Monetary ControlProcedures, vol. II (February 1981), especially pp. 19—22. Piemeeestim,mates that the noise imm weekly money data is around 83 billiondollars, assuming an aggregate level of $400 hiliion. As he notes,‘to general, these results are further evidence that very little canIme inferred from any hut the most atypical movemiments in weeklydata” (p. 22).

‘See, for example, Jacob Crossmnamm, ‘The ‘Batiommality’ of MoneySupply Expcctatiomms and the Short—Rumm Respommse ofInterest Ratesto Mommctan’ Surprises,” Journal of’ Money, Credit and Banking(Novenmber 1981), pp. 409—24: V. Vance Roley, “The Response ofShort—Termn Immtemost Rates to Weekly Mommey Ammmmoumicements,”Working Paper No. 82-06, Federal Reserve Bank of Kansas City(September 1982); Thomas Urieh, ‘The information Commtcmmt ofWeekly Money Supply Anmmoummcemmments,’’ Jonma! of MonetaryEconomics (July 1982), pp. 73-88; ammd Thonmas J. Uriclm and PaulWachtei, ‘‘Market Response to the Weekly Mommey SupplyAmmmmoummcemermts in time 1970s, “ Journal of Finance (Decemmmber1981), pp. 1063—72. For ammother immterpretatiomm, see Bradford Cor-mmell, ‘Mommev Supply ,Ammnouneemmsemmts ammd Immterest Rates: AnotimerView,’’ Journal of Business )Jamsmsarv 1983), pp. 1—23,

out the 1970s, the relative impact of weekly mnoney“surprises” on short-term interest rates has been great-er since the October 1979 change in monetary controlprocedures. In fact, over 25 percent of the volatility ofthe 3-month Treasury bill rate during the time periodof the money supply announcement can be attributeddirectly to the increased volatility of unanticipatedweekly changes in money since October 1979.~Noreover, unanticipated money supply changes thatlie outside the Federal Reserve’s announced moneygrowth range appear to have a relatively greater effecton interest rates than money surprises falling withinthe announced growth range.4

The evidence clearly indicates that unanticipatedchanges in the money stock have an important effect oninterest rates. Consequently, examining the character-istics of the mommey supply forecasts that give rise tosuch behavior is important. Several studies have ex-amined the weekly money supply forecasts for theperiod prior to October 1979; hnt little has been doneon comparing the forecasts across the announcedchange in monetary control procedures.°The purposeof this article is to analyze the effects of the October

3Rolev, “The Response of Slmort—Tcrnm Immterest Rates,’’

tmibid, See also, Neil C. Berknian, “0mm the Significance of Weekly

Chammges imm Ml,’’ New England Economic Review (May—June1978), pp. 5—22.

5Stmmdios immvestigating the forecasts prior to time October 1979 policyslmift are Crossman. “TIme Rationality’ of Mommey Supply Expecta-lions, ammd Thomas Urieh and Paul \Vaehtel, “The Structure ofExpeetatiomms oftime Weekly Money Supply Anmmouneemnent,’’ (NewYork Ummiversity, F’ehruarv 1982: processed). Role’, “rime Re-spouse of Slmom’t—’fermn lmmterest Rates,” provides sommme evidence 0mmthis issue for time pem’iod Feimrmmarv 1980 to Novemher 1981.

26

FEDERAL RESERVE BANK OF ST. LOUIS APRIL 1983

1979 clmammge in monetary commtroi 0mm time weekly money time change in motmetarv commtrol procedures affectedsupply forecasts. Under the assumption of rational ex-pectations, a change fromn one recognized monetarycontrol procedum-e to another should have mmo effect 0mmthe forecast characteristics.6 In other words, a changefrom one monetary control procedure to anothershould not affect the unbiased and efficiencyaspects ofthe forecasts. IE however, the new procedure is not“well-defined” — that is, the rules of the gamne arechanging constantly — then weekly money supplyforecasts may appear biased and inefficient.’

5%]IAT DO.ES “RATIONALITY” 15IPLY?

The theory of rational expectations is based on thepremise that market participants construct forecasts ofthe futtire in a manner that fully reflects the relevantinformation available to them. Because wealth-maxi-mizing individuals will not make forecasts that arecontinually wrong in the same direction, the rationalexpectations approach suggests that forecasts of eco-nomic phenomena should be unbiased. Moreover, ifthe forecast errors could uot have been reduced byusing other available information, then forecastershave efficiently utilized the relevant data at their dis-posal

the unbiased and efficiency characteristics of time week-ly money supply forecasts? If time fbrccasts from timepost-October 1979 period are not dilferent thaim thosefromn before, we timeim would conchmde timat tile fore-casters have adapted to the new policy regime. If theydiffer, however, the evidence would not reject thehypothesis that they have been unable to ascertain thepolic~maker’sbehavioral rule.8

Three sample periods are used in time followinganal-ysis. The full period is from the week ending January11, 1978, totheweekeudingJune 16,1982. Giventhechange in operating procedures in late 1979, the rele-vant subperiods are from the week ending January 11,1978, to the week ending October 3, 1979, and fromthe week ending October 10, 1979, to the week endingJune 16, 1982.°With these sample periods, the un-biased and efficiency characteristics of the weeklymoney snppiy forecasts across the change in monetarycontrol procedures can be investigated.

Weekly Mon.eq Supply Data

The nmoney data series used in this article are theactual and expected, initially announced week-to-

The issue investigated here is whether the weeklyforecasts of the Ml money stock change have beenaffected noticeably by the October 1979 change inmonetary control procedures. More specifically, thequestion asked is: assuming rational expectations, has

(trhe concept of rational expectations is based on the belief that

ee0000mic agents are utility maximizers. hums, mnarket participammtsform expectations that fully reflect all available immfonmuation, Moreformally, rational expectations imnply that individuals’ subjectiveprobability distribution of possible outcomes is identical to theobjective probability- distm’ibmitiomms that actually occur. Commse—(lmiemitlY, the ommiy way policymakers can afl~etbehavior is to “fool”the people in an immeonsistent manner. This eommcept is developedmore fully’ imm John F, Muth, “Ratiommal Expectatiomms amid the Theoryof Price Movements,’ Econometrica (Jmily 1961), pp. 315—35;Robert E. Lucas, Jr. “Expectations and time Neutrality of Money.”journal of Ecotmosnic Theory (April 1972), pp. 103—24; Robert J.Barmo, “Rational Expectations and the Role of Monetary Policy,Journal of Monetary Economics (January 1976), pp. 1—32; amidThomnas J. Sargemit amid Neil Wallace, “Rational Expectatiomms, timeOptimmmal Monetary lnstrsssnent, and time Optimmmal Mommcy SupplyRule,” Jomimnal of Political Economy (April 1975), pp. 241—51.

Tlmplieit in tlmis is time presumption that mnam’ket participammts will

expend resomim’ces to decipher time miew pohey procedures ammd adapttheir forecast formation process accordingly. This does miot sceniunreasommable given time sopimistication of financial msmarkct ammalystsin gauging actual F’ccleral Reserve beimavior. For a diseussiomm (inthe transition from omie policy to another amid time nnplieatiomms forrational expectations, see Bemmjamnin Xl - Friedman, “Optimimal Ex—peetations and time Extreme Imiformatioim Assumptions of ‘RationalExpectations Macronmodels, “ Journal of Monetary Economics(January 1979), pp. 23—41.

‘trhe dilemma facing market participants is known as the ‘Lucasproblem Essentially, even though individsals act rationally inmaking their forecasts -..— that is, use all of time information thoughtto he relevant — failure to account for a procedural shift will lead toincorrect forecasts. Timns, forecasting guidelines used under oneprocedure mmmay not apply under another, For the specific problemtested here, it nmay be the case that the annonmmced policy differsFrom that actually followed. Ifpolicy actions are mmot characterizedeasily, that is, if policy is smnpredictable, then forecasts may bebiased amid inefficient simply because agents Imave mmot deternminedthe strmmctmmre of the model. For a discussion of this concept, seeRobert F. I~uc4s. Jr., ‘‘Ecomiometrie Policy Evaluation: A Cri-tique, imm Karl Brunner and Allamm H. Meit-xer, eds., TIme PhillipsCurve and Labor Markets, Time Carnegie-Rochester CommforemmccSeries omm Pmihhc Policy (voi, 1, 1976), pp. i9—46.

Bradford Cornell recently’ has argued that apparemmt irratiommalbehavior on time part of mnarket participants evidenced by biasedammd immefficient forecasts, mnay yen well be doe to time change froni apredictable policy regime to one that comitinoes to lie ummpredict—able. As he states, “On October 6 [1979], mnarket pam’ticipammtssuddenly rliscovered that cvemm time roles of tIme gammic were smmbjectto change. As a result, they begamm studying weekly mnommcy snpplvfigures not ommiy- with the goal of dcterminimmg “hat time currentpolicy was, bmit also witim tIme goal of determnimming how tIme rules ofthe gamne might ime chammged. “ In this semmsc, niarket participammtsface a perpctnal “Lucas problemu. ‘ See Cornell, ‘Momiev SupplyAnnonncemcmmts and immtcrest Rates: Amsotimcr View,” p. 21.

‘Note that time post-October 1979 period imicludes the period ofcredit controls, essentially time sceomid qmmarter of 1980. This periodis imseluded becammsc aim examnimmation of tIme erm-or pattern from week-ly- money lorecasts immdicated no differemmee bctweemm this period amidany- other, Moreover, mmiarket participants comitimined to forecastweekly muoney chammges tbrommgbormt tIme coimtrol period.

27

FEDERAL RESERVE BANK OF ST. LOUIS APRIL1983

week changes in the narrowly defined money stock(Ml). Figures for the actual changes in Ml are takenfrom the Federal Reserve’s 1-1.6 weekly statistical re-lease, Because the sample covers a period of changingdefinitions, the following guideline is used: FromJanuary 11, 1978, to January 31, 1980, the weeklymoney supply changes are based on the oid definitionofMl, From February 8, 1980, toNovember 20, 1981,the money stock is defined as the actual M1B mneasnre,not the M1B figure that was adjusted for NOW accountmovemiments. Finally, frommm Novemmmher27, 1981, to June16, 1982, the data are based on the then-current defini-tion of Ml.

The data used as a mmmeasure ofthe market’s forecastswere obtained from Money Market Services, Inc.’0

Since 1977 this firm has conducted a weekly telephonesurvey of50 to 60 government securities dealers to gettheir expectations of the impending change in rnommey.Prior to early 1980, the poH was conducted twice aweek, on Tuesdays and Thursdays. Since then, howev-er, only the Thursday survey has been conducted con-sistently, because of the shift in the Federal Reserve’sannouncement of the weekly money supply figuresfrom Thursday to Friday afternoon. For our purposes,therefore, we empioy the mean ofthe Thursday stirveyresponses. mm

Are •%iveekly I.4oneq Fareeasts- 1.-Abler-ed?

Forecasts of weekly changes in time money stock areunbiased predictors of the actual change if the actualand forecasted values differ only by some randomterm. Mathematically, this requiremmmeut can be statedas

(1) ~ = ~~1AM~ + e~

where AM~is the actual change in the money stock,~ 1SM~”is the expectation held in period t-1 for thechange in the money stock in period t, and Em 15 arandom error term with zero mean and variance o’~.

To test for the absence of bias, equation 1 is rewrit-ten and estimated as

(2) ~ = a0 + Pm _1~M~’+ g~

where a0 and Pm are the parameters to be estimated. maIn this form, the weekly money forecasts are tmnbiasedpredictors of actual money supply changes if the jointhypothesis that &ç~= 0 and 13m = 1 cannot be rejected.Moreover, the estimated residuals frommm this regression(~~)should not exhibit serial correlation if the forecastsare unbiased predictions of the actual change inmoney.

Table 1 presents the regression results from estimat-ing equation 2 using the expected and actual moneystock changes. The full-period results suggest that theforecasts of weekly changes in the money stock areunbiased predictors of the actual chamiges. The calcu-iated F-statistic does not exceed the criticai value of3,04 at the 5 percent significance level. Consequently,the null joint hypothesis that &o = 0 and Pm = 1 is notrejected. Moreover, the residuals ofthe equation showno indication of first-order serial correlation, as evi-denced by the Dnrbin-Watson statistic. Thus, theweekly money supply forecasts appear to be unbiasedacross the ftmil sample,

To see if the forecasts are unbiased before and afterthe October 1979 change in monetary control proce-dures, equatiomm 2 was re-estimated for the two periodsJanuary11, 1978, to October 3, 1979, and October 10,1979, to June 16, 1982, These regression results alsoare reported in table 1. i3

The estimates from the pre-October 1979 periodagain indicate that the forecasts are unbiased. Thecalcuiated F-statistic is not statistically significant, andthe Durbin-Watson statistic again indicates no first-order seriai correlation amommg the residuals. In con-trast, the post-October 1979 regression results permitus to reject the hypothesis that the forecasts are un-biased predictors of the actuai changes. Although theestimated constant term is statistically insignificant,the hypothesis that the estimated slope term (Pm) doesnot differ from unity is rejected easiiy (t = 2,33),Conseqtientiy, the joint hypothesis underlying this

501t has been argued that survey data are not good measures of themarket’s expectations ofsomue macroeconomic vam-iahle. This argu-ument is Foonded on the belief that most sun-ey m-espondents arenot actual mnarket partieipammts. 1mm other words, their responses tothe survey are not based on some proflt-maxinuzing behavior timathas generated the forecast, The weekly mnoney forecasts used hereare taken from dealers actively partieipatimig in the financial mar-ket, thns reducing the force of this criticisos, See Edward J, Kammeand Burton C. Malkiel, “Autoregressive and NonaotoregressiveElements in Cross-Sectiomm Forecasts of Inflation,” Economet rica(January 1976), pp. 1—16.

ilFor an analysis ofthe Tuesday amid Tlmursday forecasts, see Cross-

nsami, “Time ‘Rationality’ of Money Smmppl~ Expectations” Thisanalysis covers only the period 1977 to 1979.

‘tm

This type of test is used widely imm studies of expectations data. Forstudies examnimming money stock forecasts, see, for example, Cross-muan, “The ‘Rationality’ of Money Supply Expectations;” Uricisand Waehtell, “The Structure of Expectations;” and Roley, “TimeResponse oF Short-Termn Interest Rates-”

ma~1-h~Sdiehotomizatiomm of the sample is supported statistically by

Chow-test results: the calculated F-value is F(2,228) 3.93,which exceeds the critical 5 percent level,

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FEDERAL RESERVE BANK OF ST. LOUIS APRIL 1983

-~ / - - -, A -~- - -- \~1///’’ m~-

ab~Test Results for BiasEquation Estimated W — aG + J3i .4Mf ~

Estimate~coefIictents1 SummarystabstS~

Patio - p 8! OW P

1/ 1/78~~6/16/82 0044 ,207 022 si 185(030) (tO~43)

I 1/78=10/3/fl tSa2 1080 03 89 80£6) (664)

j0h10/79-6fl682 018 1373 a 70(09 (860

Absolute value ofStatistics anpear uaparermtltesesrp ibsadjusted toefifetent otdetevmmnatlon (MN ceptasents the Ourtsnwatsqmu testatatmelt The

repoiled F-staflstme us used to<test theSt hypothesistat ( 1)3Therelevant 5 percent cultlcat Sues-are January I 1978 toJune 6 962 04 January1978,leOctohers 97~ tO~andOSt0ber0 9~$b tSfl 0-

mm(4) ~

5AM

1= ~ 13~z~M~

1+ P’at,

i=l

where ltmt and p~are random error terms. In thisformat, weak-form efficiency requires that Pt = j3~forall i; i = 1, 2

To determine if survey respondents efficiently uti-lized time information contained in past weekly mmmoneysupply changes, equation 4 is subtracted from equation3, yielding the estimated equation

n(5) iXM~— m_mt~M~= h0 + ~ h~/SM~ + ~

where the dependent variable ~ — t - ~ repre-sents the forecasters’ errors in predicting weeklymoney changes, and the independent variables,

are the actual changes in money.’6 The equa-tion permnits a constant term (b0) to be estimated in-stead ofstmbsmiming it into the error structure, which isrepresented by the term ~ (= ~

1t~— ~). The null

hypothesis to be tested is that the estimated b~( = p —

mafia form ofthe efficiency test was proposed in James E, Pesando,

“A Note ou the Rationality of the Livingston Price ExpeetatiomisData,’ Journal of Political Economy (August 1975), pp. 849—58,

‘°The lagged values of data used in the efficiency test are thecourse, additional information will he acquired only if the one-week revised numbers, not the initially reported weekly

marginal benefits are at least as large as time marginal costs of figures. Since time revised figures contain umore iuformnation thanacquisition. A useful discussion of this poimmt is provided in Armen the originaliy released data — the data contained in the revisionA,Alchiau, “Information Costs, Pricing, and Resource Unem- itself — using original data would deprive forecasters of someployment,” in Edmummd S. Phelps, and others, Microeconornic inforumatiou, It should he noted, however, that the conclusionsFoundation.s of Employment and Inflation Tlmeory (Xv. xv. Norton reached were not affected when originally reported data was used& Compammy, Inc., 1970), pp. 27—52. to generate lagged changes iu the momiey stock.

test also is rejected; the calculated F-statistic of 3.70exceeds the 5 percent critical value of 3.07, Thus, theevidence suggests that forecasts of weekly moneysupply changes have been biased since the October1979 change in implementing monetary policy,

Are SLeekly Money Foreearls Fffi.eient?

The efficiency condition requires that forecasts fullyreflect all pertinent and readily available informa-tion. “ Since the information available to individualsincludes the past history ofthe series being forecast, itis possible to test the hypothesis that the forecasts are“weakly” efficient; that is, at least the information con-tained in the history of weekly money supply changesis used efficiently. This concept of efficiency requiresthat the process actually generating observed changesin weekly money and the process generating the fore-casts of these chammges are the same. The simplestprocess to assume is an autoregressive one, whereobserved and expected changes are generated solelyby the past history of the series itself. Mathematically,this concept of efficiency can he stated as

n(3) AM~= I I3~AM~ + t

tn

i= 1

i=1

29

FEDERAL RESERVE BANK OF ST. LOUIS APRIL 1983

are imot statistically difkremmt from zero for all i (i =

1, 2,.,., n) as a group. Moreover, the estinmated errorstructure slmould not eximibit serial correlation. ~

Table 2 presents time results ofestinmating equation 5for the period January tI, 1978, to June 16. 1982, Fourlags were chosen to capture time informational commtemmtof past chammges imm weekly mnonev, The regression re-sults immchcate that past changes in the nmoimev suppl~’dommot explaiim any’ sigmmificant portiomm of time forecast error.The calculated F—statistic (0.81) is far below acceptablecritical values. Time Durbin—V~atsommstatistic also indi-cates timat serial correlation is not present among theresiduals. Thus. for the full period, we cammmmot rejecttime hypothesis that forecasters efficiently used the in-formation contained in past chammges iii the money stockin forming their predictions.

We mmext test the efficiency hypothesis for the pre-ammd post-October 1979 periods; timese emnpirical resultsalso are found in table 2. 1mm both instances, we againcannot reject the hypothesis that past informationabout weekly money changes was used efficiently.Neither F-statistic is significammt at the 5 percent level,Based on these results, therefore, the weak-form effi-ciency hypothesis is not rejected by the data, regard-less of the sample used.

m7Sec, Donald J. Mullineaux, “Omi Testing for Rationality: AnotherLookat the Livingston Price Expectatiomms Data, “Journal ofPout-icalEconomny (April 1978), pp 329—36for a discnssiomm ofthis test,

Tests of Stronger-Form Efficiency

The above evidence suggests that forecasts ofweeklymoney stock changes are weakly efficient. Efficiency,however, also may be considered in a broader sense.This broader efficiency criterion requires that forecastsincorporate all of the relev~mtand available informa-tion. Thus, similar to the previous hypothesis, efficien-cy in the broad sense reqmmires that the forecast errorsbe orthogonal, or systematically unrelated to all rele-vant available information sets.

To test this concept of efficiency, we estimate theequation

(6) AM1

— t--m AM~= c0

+ I c~I1

.~+ w~i=O

where l~_~refers to lagged values (i = 0, 1,..., n) ofinformation that are not incorporated in past moneystock changes, and w1 is another randonm error term.The analysis is intended to determine whether thesurvey respondent’s weekly errors in forecastingmoney supply changes can be explained by some set(s)of information that are readily available. If the esti-

Table 2Test Results for Weak-Form Efficiency

4Equation Estimated: ..XM~— ~ = b0 + ~ b1XM~.1÷th1

i=1Estmrraled r:oeftm( mem’ls b.irnia’y stal’sI’cs

Per,od h a, ‘~‘ DW [U~

11

t78.61

682 c139 00~2 0067 0057 0005 oci 1921087; ~Oh

9J ‘1 ‘

4~C 481 mO OY~

78--tO 379 0259 0026 0077 0 02: 001? 001 1 95 0.28ml

24J (025) 1082m iO ?3J 020:’

‘01079 61682 0398 0071 0068 0112 0007 002 193 082ml ?7j 10901 10901 C 48j ID ~Om

‘Soc noles accon’pammvmm”q table 1~See notes acc-orrpanymno abme 1 rho ‘oporled F sta~msmcu csed :0 lesT The nut nypot”mes’s That b123Am 0.

Joe re:evanl 5 perceit er lmcal r-vaILos aT Janua’y ~1 1978 to Jimre 16, 1982 241. Jarmlmanj 11‘978 10 October 3 1979 -. 245 dud Oclober 10 1979 m Jure ‘6 1982 - 244

msTests usimig this stronger form of efficiency are pm’esented in Cross-

man, “The ‘Rationality’ of Money Supply Expectations,” and,Imsing interest rate expectations data, in Benjamin M, Friedman.“Survey Evidemmee on time ‘Rationality’ of Interest Rate Expecta-tions, “Journal of Pmionetary Economnic.s (October 1980), pp. 453—65, where the phrase “information orthogonality” was coined.

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FEDERAL RESERVE BANK OF ST. LOUIS APRIL 1983

Table 3Test Resutts for Stronger-Form Efficiency

nEquation Estimated: .SM1 — ~.. -~.XM~= c0 + ~. c1 ‘t.i + w1

i=O

consumer ard mndustrmaloans 365’ 1 74 2.94

Demano depos’ls al maraeweercmy ‘eportmng barns 425 0.51 357’

F’oat 060 055 061

Adjustea base 329’ 055 365

- Smgnitmcant at the S percenl leve ot contmdence, The re evant crmlmcal F-values are January 11. 1978. to June 16, 1982 —- 2.26. January 11.1978. to October 3, 1979 - -. 2 32, and Octooer 10. 1979 Ia June 16, 1982 ‘- 2 28.

mated cm coefficients are not significantly different fromzero as a group, then we cannot reject the stronger-form hypothesis of efficiency. If contrary evidence isfound, then the results would suggest that forecasterscould have reduced their prediction errors by usingthe information sets investigated here.

It is, ofcourse, impossible toaccount for every imag-inable information set that each forecaster could haveused. Consequently, we analyze several sets of in-formation that are available on a timely basis and arepotentially useful in estimating future money stockdevelopments. The informmmation sets used are consum-er and industrial loans, demand deposits at largeweek-ly reporting banks, float and the adjusted monetarybase as defined by the Federal Reserve Bank of St.Louis. In all cases, the data used are taken from origi-n-al Federal Reserve statistical releases that were avail-able to forecasters prior to the weekly money stockannouncements. ~‘ Although we realize that the series

moAn data am-c imi terms oflevel ctmammges from the previous week. Data

sources are the Federal Reserve H4. 1 and H4,2 statistical re-leases, and the Federal Reserve Bank of St. Louis,

This procedure ma” imupart somiie measnm’ement error since omilythe initially released data are used, Civen the short time horizomiused and the observation that the weekly data m’evisions arc mmotsevere, the approach used seemns sufficient. It also slmouid benoted that, since February 1980, data on cormsunmer amid indimstrialioamis and demand deposits at weekly reporting hammks have beenreleased comacurrently with the money supply numbers, Thus,these two series offer no prior informatiomm durirmg the post-

chosen do not exhaust the set of possible informationsources, they are sufficiently broad to test the hypoth-esis at hand.

Table 3 reports the calculated F-statistics fromestimating equation 6 using the different informatiormsets. In each test, the information set contains contemmm-poraneous and four lagged terms. The outcome for thefull period suggests that forecasters efficiently utilizedthe infornmation contained in the float information set:the reported F-statistic isnot large enough to reject thenull hypothesis. The results for the other informationsets — consumer and industrial loans, demand de-posits at large weeklyreporting banks and the adjustedbase — reject the efficiency hypothesis. For these, theF-statistics exceed the 5 percent critical value (2.26),implying that forecast errors could have been lessenedif the information contained in these data had beenused.

Equation 6 was re-estimated for the pre- and post-October 1979 periods; these results also are found intable 3. The full-period results are dominated by timepost-October 1979 period. Prior to the shift in controlprocedures, forecasters’ predictions of weekly m’noneysupply changes appear to have efficiently incorporatedthe information sets tested here: all the F-statistics areless than the 5 percemmt critical vahme (2.32). In contrast,

February 1980 pcm-iod. Tlmey do, however. provide niore imifbrmna—tion that fom-ecasters may’ use in gemmerating their expected mmioneynmmmiibers,

31

- — R~” ,~- .4 \/ ~_//4’~//’4.- ~ 4 / __\_/_//\////\/_/ - — /4

the post-October 1979 results reveal that, except forfloat, the forecasters could have immmproved upon theirability to predict changes in the money stock by incor-porating the information contained in the series onloans, demand deposits and the adjusted base. Thus,over the recent period, the forecasts do not meet thebroader efficiency criterion tested here.

CONe! USION

Previous examinations of survey data on weeklymoney supply forecasts have focused primarily on theeffects of unanticipated money changes on market in-terest rates. Although several studies have examinedthe forecasts’ rationality, there has been no systematicinvestigation into the effect of the change in monetarycontrol procedures on the unbiased and efficiencycharacteristics of the forecasts.

The evidence presented here indicates that thechange in control procedures has had a significanteffect on the characteristics of weekly money supplyforecasts. Prior to October 1979, the forecasts of thechange in the weekly money stock were unbiased andefficient. In contrast, weekly money forecasts sinceOctober 1979 have been biased and inefficient.

The results of this investigation lend support to therecently suggested hypothesis that, since October1979, “market participants [have] concluded that therules under which monetary policy is conducted couldno longer be considered constant.”2°If this indeed istrue, then the combined evidence from this study andthose dealing with the interest rate effects of unantici-pated money supply changes suggests that a morepredictable control procedure would contribute to amore stable financial market.

20Cormmell, “Money Supply Announcements,” p. 22,

32