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DALLAS FEDERAL RESERVE BANK OF OALLAS 1991 March 1991  1  ••  •  CVICW ~conOInlC cononnc eVlew  Forecasting the Louisiana EcolZOJny Economy William C C.. Gruben and Donald W. Hayes  Modeling the Effects ofInjlation of Inflation on the Demandfor Demand for Money Kenneth M. Emery  This publication was digitized and made available by the Federal Reserve Bank of Dallas' Historical Library (  Economic Review  _ .. .........---_....  Federal Reserve Bank ofOal/as Robert D. MeT"" Jr.  HIM\' RoMnblllm  s.- ....... ,...,.., INI  G,rlilli P. O' DriKoli. Jr. ~ t:low.- #t "'-'<II  -..........  W. MkhMlCo.  "'_  SIIplten P. A. Brown ,w,,1MII_~1'Jd  Economil1S Nallonal af1d International John K Hill  Evan F Koenig Robel'1 T Clair Joseph H Haslag Kenneth M Emery  David M Gould Mark A Wynne Kevin J Yeats  RegIOflaI and Ensrgy William C Gnb!n  Robert W Gilmer Mine K Yilcel Keith R. Ptuilips  LOri L Tay10f Fiona 0 Sigalia Editors Rhonda Hams Diana W Palmer Vi/lI,oia M Rogers  The Economic Review II ll,IbIisiled bv ,tie f edefll fIe1.,.... Baonk of o.lIiIS The \'Iew1 e., preued ale !hose of IIle aUltlln lind iXI not rte(e$wwdv reHICI tile pOI!IIttlS of me Feder" Re_ BIr* of OaDn 01 me Fedeli! ResertIII  "'~ s",b$CJ,ptJCIM Me IMIIabie ifw 01 thlrllll PlUS! send ' !quesll lor "ngJ"f(lpy .nd nUl~ SUCISeI~.  back WIllIS. ird d'I¥lQes 10 lilt !'ubi.:; AIIIIfI DIc*t. men!. fWeflllieserve 8irt of o.U•. SIJI>O'I K. o.tIas. Teus 15Z22.121' J651-628S At\Icllls ""Y bt reonmed (J:I1N anltt ... l1li1 !hi IIUt$ IS credcrtd tnd the Aeswt:h ()epIrtmenl IS prOVIded WIth I COPY 01 till pIbIic.I~on COI'IUIIftIn\I the IffIMted ....1eN1 ~ohss  Contents Page 1  Forecasting the Louisiana Economy  William C. Gruben and Don:l ld W. Hayes have constructed a forccasling model that predicts mild overall growth in the louisiana economy in 1991. The model predicts  William C. Gruben and Donald W. Hayes  callnt. the civilian Jabor fo rce, nonllgricultllral employment, hOllsing permits, real personal income, mi n ing, ,md sa les ta x revenue. Only durable and nondurable goods manufactming will decline, according to the forecast. Gruben and Hayes conclude that while I.ouisiana is likely \ 0 experience an economic expansion in 1991. a boom is unlikely.  expansion in seven of nine economic indicators: the rig  Page 17  Modeling the !ffects ofInflation on the Demandfor Money Kenneth M. Emery  Because the Federal Reserve is responsible for controlling the value of money. economic policymakers are very concerned wilh forecasting the public's demand for money. Inflation is one of seveml faclors thai have made forecasti ng the demand for money increasingly difficult over the past fifteen years. In this article, Kenneth M. Emery reviews the ways that inflation may affect the demand for money, and he examines how well tr-.Jditionai money-demand models have captured these effects in the postwar period. Emery finds Ihat money-demand models would have performt:d ocner during 1953-79 had they included Ihe direct effects of inflation However, he also finds some cvidenc(! Ihat the wide use of interest-bearing money and moderate rates of inflation during the 1980s diminished the effects of inflation on the demand for money.  William C. Gruben  Donald W. Hayes  SeniOl' Economist and Policy Advisor Federal Reserve Bank of Dallas  Economic Analyst Federal Reserve Bank of Dallas  Forecasting the Louisiana Economy ur fort.·cbts n~ .n im.· t.·("ono l.nic indica to rs a I)QS II1 VC t.·conOllllC o Ul look for J.ouisia n :1 In 1991. Our fOI"l.:casls p rcdid g rowl h in ~",,\'t.'11 oj Iht.' n in .... indicators fo r I.ouisiana : tht.· rig counl. Iht.' civ ilian lahor fOl"l·..... nonagricultu r.ll t.·lllpl()YrlH:.·nl. hOLlsin~ jx:rmils. rl';11 JX'rsonal iIKOlllL·. mining c mploymL·llt. ;Ind rcal salt.·s lax lv\"t.·nUl· Ernploymt.·nt should (IL-di ne in hOlh dlll~lhk ;lnd nondurahlt.· W)(xls ma nutaCiuring Wt.· <.kriv....d our pn::diclioll., from an ori!!inal tim t'sL'ril.:.' modd. con"'lnlCl L'd "'1x:dlk ally to :.m;.!lyzl.: Iht.' ].(luisian;1 economy u ... in~: 1 pnx:~durc WL' will t.·... plain in thi:- :Inidt! Dt.·... p il .... o ur predit"lt:d t.',,, p:ll1... ion in 1991. Loui"'I;1I1:1 i, unlikdy to Teach ih t.'l1lphl} mt.·!lI peak-. (If 11ll' L':lrly 1980... Firsl \\L' di-"'.:u....., l u.llsian;I·.... , tnK."lur.I1 and bboT for<.·t.· ch; I1~lctL'rislic:-. 111....n " .... (k~rihe our fort.·c.I ...Im~ l1lodd of l..oui,ian:l·s l'conomic indiC,Jlors and cxpbin how W~ \I~ IhL' Illtxk-llo fOR--C lst tbe statL'·... t.·(:ooom": !,x:rfonnancc for 1991 \V~ t;()nc\udt: hy prt.....,.:ntin,g thL' forec, ...( and <.It in,g it!'> implications.  O  .'ll~~i:'st  Characteristics of the Louisiana economy: an Qven'iew J.,llli ...ian:l·s L'("()f)(~niL Stl1lctlll'L' and pcrfonnanc.... arlO alll()n~ Ihe most LUHI .~lI; tI in tIH.: United Statt:s lX:call'L' of thL' extl't:'llldy illlp0l't:lnt role that eneI'. i L'.xtl~ll" li ()n play ... in 11lL' ...I:IIL'· ... L'COnolllY It is no coinL"idt.·nct: Ihal hoth r~;11 oil prict.·... and LoLLi.siana·s ....mploymt.·nl 1'X':lk .... d in 19l-! I :\'01 only does ~nL·rgy I.:xtraclion pl.l}' an imponanl din:t.1 rol~ in (h~ I.ouisiana ~("(momr. h UI il .Ibo strongly affects tb~ ...lnl(·III1\: of Ihl.: stale', 0111t.·1' t.·(:onomic ~-'{,"lors. slldl :I'" m;nlllfa<.1unnA Ent.·rg} -rdated plwn( Illlena arc not thc only UllliMla! :I!'>lx-"t."lS o f Iht: Loui,i:tn:1 L·cono my. E\'~n in hoom IX·ntxi!'>. Ihe I.oui... i:tn:1 blxlr force duunic.llly ... \lI1"l'rs hum higher unelllplorlllt.·n! r.1lt.'S Ih:1I1 tht.·  n;ltion :11 aver.. ~..... I'-I0 rL'0\'l:r, I..oui.,iana's lahor pal1iL"ip:ltion r:1IL'S :H\: Mlm.... whal 10wI.:r rh:11l the n:ltion's AS:I con-"L'(jlICnCL', Louisiana's employl11l'nt r:ltL' (thL' 1~l\ i() of c illploymcnl 10 the civili:tn l1()l1in~tiILilional bl)()f f()rL"~ ) rem:lins chronically Ix:low the nation·s. WL' addl'L'ss Ihe implications of I hi.s p hL'nolllt.·non in:1 !at!.:!' section.  Composition of the Louisi.ana economy BcC.Jll'>t.· o f Louisiana ':- p(.-'Culi:tr L'conom ic ...lruCl urc. it is not unusu;11 for the !'>t:lt,,·s economy 10 Wow \\'h~n mn,1 ol her sl ales' economic... art: dcdinin~ and to shrink \vhen OI:hl..·r stale ... · c("onomil's :lTC ~xIXlnd in~ Among thc OflY SI:I1t:S and thL' Dislril..1 of Collim ili;l. only eight cronomit:... \';uy le~, wit h n:llional Ollctu;Hions (Sht.'rw()(xl-Call 19Xfn. and o nly four aTe I~ ....... divcrsified (Shcrwood-DII 1t)1.)()) The oil :lIld ~a ., t.'xlr.lction industry dominall.:s Loubia n;l·... !.:conomy :-0 p rofoundly that it :It.·COlHll s for :ll1no.'t len ti llleS as large a ... han.: of ,gross Sl alL' p r(xlllt"1 (GSP) as in lilt.' a\'~r.I~t.: state. Energy accOllnl~ tor ;1 ~rcaler ponion of GSI' in Lou isi an:1 than in any olher state except Wyoming (Schmidt 1989) :111(\ for more of l.ouisial):t output than <I ny ot hl.'l' l11ajor L'<"onolllic secl or. A .~ of 19H6, tht: most 1'L'(.'(;:111 yt.·:11' for w h ich d ata exist , oil and ,g:I .~ C.xIr.lClion ac(;()unlcd for one-sixth of L()lIisiana'~ CSt' hUI for onl y one-sixtieth of the n:lt ion ·.s gros... nal ion;11 product (GNP ) 1\·loreo\·cr. 1900 W:lS a particuhlrly WL':l k yea r for tht: L'nl'r,gy indl1slrr: in 19H2 il produced more than 0111.:founh of l oubia na·... GSP  v,c wovId Me 10 InaoI< St_ Brown. l or' Tay10t and Oavrd lor lne. he/fJM commentS  G~  Figure 1  Compos ition of the Louis iana Economy, 1989 (Percent)  (11  SOURCE: U S. Bureau 04 Labor Statistics  Figure 2  Composition of the U.S. Economy, 1989  "'" SOURCE: u .S. Bureau oIlabof Statistics  l  ~)  Energy extraction accounts for a much larger portion o f louisiana's GSP than of employment. Figure 1 :lOd Figure 2 depi<-, employmt:nt shares by industl)' for Louisiana and the UnilL'<.i States in 1989. iI'lining employment. of which 96.9 percent is in oil and gas extraction, occupit:s I(.!ss of the swte's work force than almost :.ny otht:r major sector. Nevertheless, the energy industry still has a ~trong influence 011 employment in Louisi:lOa. Brown and lIiIl ( 1988) show th;1I changes in energy prices affected O\'(ToIIJ L"Inployment in Lou isiana to a grealer degn.'c than in all hut three U.S. states (Wyoming, O klahoma. and Delaware). In lou isiana , a S; increase in tht: price of oil yidds a 1.6-pcrcent increase in th~ swte's nonagricultural employment over tht: long m n (Rosenblu m and others 1990). Moreover, while mining ahsorbs only a small portion of Lallisial13. 's work force , the Slate's industri:11 composilion of employment is far more heavily weighted toward mining than the nation 's is. As Figures I and 2 show, mining accounts for aoout five times as high a share of I.ouisiana 's t:mployment as the nation's. Government also employs a disproJXlrtio nateJy brge st:gment of Louisiana's work force Almost six times as many Lo uisianans work in government :15 in mining, and government's share of t:mploymcnt in Louisiana is aoout one-fourth hi~her than Ihe national average. State and local government accounu, for this disproportionate share. The fedeml government t:mploys a relatively small JXlrtion of workers in Louisiana, but 1000..ll government's employment share is one-fifth higher than th~ national ~l.\'ef'", and slate govcmment"s share is higher by one-half. Despite the relative impon:lOce of government as an employer in Louisian;t, the sector accounts for only 10. 1 pcrct:nt of Louisiana's esp, compared with 11.7 percent nationally. Even though government employs r;l r more Louisianans than mining does, mining accounl~ for :l substantially hlrgcr sh:lre of Louisiana 's GSP. Manur:lcturing also employs more louisiana workers than mining does and aC('OunLS for more esp than government does. Comp:lred with the muion, however. Louisiana's mllOllfacturing sector is relatively small in tenns of jobs and output. Another aspect of the role energy plays in the louisiana economy may be seen from an Federal Rcscrve Bank o f DaIla$  l:'xamination of th~ st:lte'<; m:lnuf:tl:turing .~t.'l'tor. (k·cau.,,>~ the state h:ls :1 \\ ...:I k dUfahk' g<xKI... "'l·cto r. manufacturing's s h:lI'l' of Louisiana·... GSP <U pcrl:ent) is a ftood d ...:11 ... malk-r Ihan it...... han: of the n.. lion·s GNP 09.6 per<.'Cnt). Ho\\'",\·~r. IX·'<:;.Il1se lilt: t:nergy-linkt--d ch ... lllkal :mtl refining indllstric~ :m:: so imponam in Louhi .. n:l. the nondur:lble go()d~ M!Ctor ;Kl'ounts for a We:ltl'T share of L()u i ~ i :m:I's GSP than of the nation's GNP. I Together. the refininj.( and chcmiG.11 industrie... :Kcount for 6 3 percent of Louisiana·... GSP. <..'O1l1paR-xl wilh a 25-perct·nt .~hare n:uionally. ,., Ioreovcr, the value of o utput in theSt: t\"\'o industries aCt'mmt<; for 68.9 peret:nt of th ... value of total LOlli~i:ma nondur:lble goods production. Like mining. tht'se industries are capital intensive. so they :Lecount for :1 lIluch sma ller shan:! of ... tate t:mploymt:nt (27 percent) (han of GSP (6,3 pcret:nt). Finally. hecau.'>I: of ent:rf!Y's imporlant rolt:. g<xxls-producing indu... tries occupy a far brw.:r share of Louisiana's GSP <36.3 pcrct:l,n Ih:m of thl" n:llion's GNP (18 9 pl'rcl'nt) ~ The domin:lnee of mining more than offsets the rd:lli\'dy sm:11I contrihutio ns of l1l:lnllf:.cturing and ClIIl...lruelion. thl" other goods-producing sectors  Thl" !lab nee of the differences between Louisi;ma and U.s. employment rates occurs IX'c'ltI."C a di.'iproportionatdy l:irge number of johle... ~ working·age Loll isianans arc nO! even ~el'king work. which means they are nOt pan of the blx>r forel" Thai is. Louisiana nOI only has a chronically hifth unemployment r,lIe hut also a chronic:.lliy low lallOr panicipation rate. Partly as a rc.">ult or low employment and labor panicipation r:lle."> :.lnd chronically high unemployment rates. LOlli... ian:l r:lnked fony-sixth among the fifty states in personal income pcr capita during 1989.  ConstructJon of the model: an overview The sol~ plI T])().st: of our time-series model is to forcC:l.~t nine Louisiana economic indic:nors as :ICCUr.llely as po~sible In its final form. fhe model indudt·s ninl' foreC:lsling equ:nions, one for each rorCC:I.~t variahle. Thl" model is not designed to te~[ hypotht'se~ :Ihout the stnlcture of louisiana'S economy ;lIld was not constructed in accordance wilh :l ny thl'"'()retieal economic modeP -111c model-huilding approoch we use is a purely process. involVing :l two-stage  Louisiana's labo .. force Louisiana's labor force <:har.Jclen~tiL'" are also unusual. In louisiana. empIO}'111l"nt as a percentage of the cj"ili:m noninSiitulioll:.l fXlpuiation <or Ihe employment mte) h:ls f\.."tnaincd helow the national :IVCr.lgC even when the sta (~·... employment wa ... growing more rapidly th:m the n:llion's Thi... means th:.t a dispropoltionatcly brge numher of workingage Louisi;mans dtllcr lire out uf work but :tt1ivdy seeking it or arc not even part of thc labor force. In 1980 and 1981. for example. total employment in LouLsi:ma grew at more tha n fin~ times the n:.llion:!1 rat~. but l.ollisian:I·S employment r.lle remained lx:low the nation:!1 aver:lgc in both years. Most of the difference.. hetwl.'Cn the Louis;;!n:! :md U.S employment rates Gm Ix: explained hy the statc's unemploYlllent roue, whil'll is usu:llly well al)()\'c the nation:11 :!"erage. Unemployment rates for hlack males. hbck females. white: malt-:-, white femalt'S. and for young persons of b()(h sc:xes are llnifonnlr higher in i..ouisiana th:!n in the nation nlC le&:ll definition of unemployment in\'olvl"S only jobless workers who arc :loivcty St:eking work Eco n Ofld c Rc" icw -  March 199 1  , 18CI1ntCafly. /llerefiNng data Sle8Clual1y b" pelro/eum and coal prOduCts. but ref.rung dotrwIatcS this motu aggregate category > BeSIdes mmmg and fIOfldurab16 goods manufacturing. the  onlymator mdustrycatcgory mat has a /arf}(If-tflan.nat.onal. average shllre 01 GSP m LOUIsiana is transportallon The (ast. mcludlng af}"culrur6. durable goods manufacturmg. who/esal6 trade. relail trade. {mance. services, and government. have shares below the naliona/average , Whlla tha LOUISIana forecastIng 8qVal1QflS were not con· stIVCledlf'laccordaflCCWlthany IhooreDCalCCOflOfflICmodcl. thIS statement sholJla nor be taken 10 mean that we ignored all "'formatlOrl aOOUI LOUISIana If! all aspects 0I/he model. bulldof'f} procedvre We rehed on our MowIedge 01 /tie LOUISlaml economy LmcrI we selected me OVCfall set 01 polenDal fOfecastng vanables. from wh1ch /he candidate vanables were SBfecI8d IlIStlS why we inf;1udfJd 011 pnees 8S a vBnBO/(J We did fIOf. however. fotcc /he oil pnce vortable 10 be 8 candidate I131l8b1e Of 10 appeal'" any frlal Iorccas/lflO cqu8110tl me Sl8tISIICSldecJ$lOll rr.Jles were the baSIS lot all SIJCf'IctIOICes. and they were COfISISlen/ WIth Ihe .o1C>\I$oOn 01 ff'lBOII pnce V3fl8b1c til 5(1V(Ifsi final forecaSlmg  -''''''  ,  system of dt..'(:i.~ion niles.' We llSC tht.:.-.c mk.·s to choose which of ninetlXn national indic:.llor... and nine l.uubiana indic.Ltor:-. to lbC ;L;o. fon.·(:;Jstin~ variahle:. in e;lch of t.he nine final L'tillations. hut we conslmct many prelimin;lry L'(lllation~ before we I'C'Jch the final nine. In the following three .~L....·ti()n.~ . we diM:lL....... detaib of the construction of the mudd. First. we describe the two-stagt;.· pl1X,.·t.....lure u . . L....1 to seleci fOreGlsting \'ariables for each I.: quation 1'ht: modd-building procedure for loui.. . iana n:semhles those presented in pasl anidcs on regional forecastin!i in the Ecol/ omic /{el'iell i. hllt we havt' made a change to accolllL11od:lle the oil-related events of 1990, :u,d we disnlss this change in Ihe sectiO!, laheled 'The u .~e of consensus forecasts in the modd .. In brief. we lise external, (:unsensus-b:l.~ed foreC:lsts of nation:11 indicators instead of Ihe cndoRenous. moddbased forec;lsts that h;Lve been depit-Ied in past anidt..'s The configurJtion of the final model. di.scllSSt..'d in a later .-.cction. refle{.ls in many ways the :.tTl.lcture of the l.ouisi;ma Ix-onomy. E\'en though the model I:' con:.tnl('tcd on time-serit:S principles, energy-related indicators ofll.·n ;Ippt:ar in the equations that forL'Glst tlK' aAArq.pte variable:.. and sc,'cr..11 Dlher c har..Ll·teri... tic:. of tht: model arc con~b(ent with what one might expt:ct from a slructur..11 model.  Tests of variables for the forecasting model The COl1s(rm:tion of tht..' Louisiana (ime-series model involves a two -~t;Lgt: procedure for selecting forecasting variables for each of the nine final equal ions. It, both stages, the Ill(xld-huildl:r constructs a simple foreCaSlil\l.\ regressiol' equ;l -  • I hiS d iSCUSSion of inC modeImg procedure IS very general Ny ITI(ItC derailed descflOiIOflS oIlhlS mode/lOg procedure. S8t! Grubon and Long (19880) and f/oehf1 and Balazsy  ( /985) J  To plCSCfWJ  IlI'1I8-ser~ SllIllOnBflry. 11/11 dalll are placed"  frrsl dlfferCflCCs 01 /ogIIrllhnllc Itxm fills means /hal all vCtflaOles are clfptesscd  as  growrh fares >NhIch are /Jle  same 85 firSI dlffflfflflCes oI1og8l11hms. and nalas absolute /eveI$ ~ WIt COtIS/rUC/ I~ress.on equ<ll/Clns. we are IDglCSSNlg QfOWIh lale oIa V8IIaOJe on lIS own paSI grOWlh f/lles II/IlQI\::Ir on past growrtl rales 01 011>« VCtf.ables  m.  tion. adds a variable to it, and tests to sec if the new variahle ;Idds to forL'Ca"'Ting aCCllr.Lcy .~ The entire proces.... of Illodd constnlltion i.. JUSt a series of variant:.... on this procedure. The stages of Ilux.ld construction rt..'M;~lllhle those taken to dect an individual to puhlic office under thc pany system in the L'nileu State:. . In thi.~ tWo-sl:tgc :....y.. . tcm . the purJXlse of the first stage is 10 :-ell.....·! fOfCl·a:.ting v:lriables that will he c;mdid:Lft..'."; for indu.. . ion in ;11 lea~t one i..."'qualion in the lLltiLllatt: forecLsTing modcl. In continuing thc :1Il;Llogy to :L politic.L1 campaign. this stage Illay be comp;lrcd to :1 party primary. We test every L()ui.~i;m:t variable's ability to forecast itself and il .~ :Ibilil)' 10 foreGI .. t other Louisian;l variables We ,llso Il.,':-.t T1K' ability of each of (he nineteen nation:ll indkators to forecasT lluctu:Hions in the l,()uisian;1 indicators. JU.... I as the viClOr of;1 primary election may not win Ihe gener.L1 election. (hI.,,' Gmdidatl.,,'S :-elcctl.,,'d in this first st;lge may not ultimately find thl'ir way into :lny t'quation in thl.,,' romplcted forL....-:lsting model E\'en so. only vari:Lhles thaI have bt.'Comc Glndidate:-; through the firsl SI:lge of [csts will recd,·c cun.. . ider..ltion for an L,<]lIation in thl' SI..·(:ond :-.tage of m<xlding. Note. however, that :I fort'GI:-.ting \';Iriablc Ih:lt ht.....'Olllcs a Glndidate for one final t.,<]u:ltion ocL'<.1 not be ;t caooid:tte for other:.. To Ix'gin thc fiN! staRt: of model building. we ex;uninl.· tht' ;Ihility of past fluctuations in a variabk to fon:Glst its own fUllLre 1ll0\'ements For each variahle. wc tl·.~t whether an equal ion containing ;. conSI;lnt tcrm-plus one- and twoqU;1I1er bgs of tht..' dcpcndent variable-forecasts more accur.II\:ly Ihan ;1 :-.imple random walk A .... t..'cond .~tep in thi.~ first stage of the model is to add other v;lriahle ....--ont.: ;1( a (imi...'-to the L'qu:Ltion that conTains onc- and tW(K]Lmrter lags of tht.· dept:ndem v;lri;lhle. In this stage, l.,,';lCh of the independent v;lri;lhle."; is te:-.TI.'{1 ;Igainst an equ:ltion that con!:lins only two b!{.... of the dependcnt vari;lble. -n):lt i .... we do not test several vari:tbles at the S:LIlle lime in Ihe same l.'{lu;uion. For t..'x:lmpll·. 10 te:....T Louisiana housing pcmlil'" a:. a predictor of louisiaml's drilling rig count. we add two l:Lg.~ of louisi;lOa housing pennits. We tlll'n tc:....t the il1formlltioll 8(1il1. or increase in fO!'L'(.·a:-.ting accur.KY, [hat the inclusion of thi ... variable Ill.. y h;I\'c over tht' modd Ihat F~dera l  ReK...·~ Hank of Dallas  conta i n.~ only t\VO b~s of the d epcn(it.:nt va riabk.h T:lhk' 1 pn: ...c nts information g:lin st:nistics. and Appendix A <.Jdines tht:: variabk's listro in T;lhk' I. To :Ichic\·c candid;lcY, :l v,lriahl\' must otTer :10 i nfon n ation ~a in \h:11 is significanl al Ill<: 10pt."rn: nl k '\·d . Lo ui:.ian:1 hous in~ pemlils do nol olTl."r an info nn:llio n gain th:1I i ... Significa nt at the IO-pcrn: nt It: \·d fo r the t ouisi:ma rig counl :md a<'."l"o rdingly cannOI become a e.mdid:lte variahle for the fin:11 rig cou nt equation. We also tested the pn.xlun: r p rice index for the refiner cost of crude oil as a prediclor for the Lou bi:ma rig count. This va ri ah le o tTers :1Il infonmllion gai n th:11 is signifi{";'1I11 even at Ihl." I -perccnl Icvd . so il becomes a candid ate the rig (·Olmt equation Once Wt examim! evc l1' variable hy these test... and select Gmdidate variables for each of the nim: l.ol lisi:m:1 forec asting equations. we move to the sC("Ol1d stagc of model h u ilding. This second stage is a n a logou.~ to :t gentral t:lection , in w hich the winners of c:lCh pa ny ·s primal)' election compete as GUldidates. I !ere, \'ie allow C""dch candidate variahle to he considen..>d in a ool1"eOlion:11 ordinary-least...qll ;l n..·~ step\visc regressio n procedure Th b procedure selects varbbles \h:1I expbin the m O....1 in-sa mple \'ariatio n of some i nd iGuor thai \\'(;.' want 10 fo reca ...!. such as the Louisiana rig {·ount . To remain in the final fo rec:.lsl ing equatio n. a ,"ari:l b le must havc a I stati:.l ic thai b significant at lilt: IO-pcrccnt Ic \'cl.- O nce this St.'cond step has IX"t:"n finished for each of the variahles, we han: a model Ill:.t, in p:1SI examinalions for Ohio, T exas. and New r-,·Iexico, h:ls been sho wn 10 fonx;ast w il h rl.":1....anah le accur.:lCy  tions of oil-price shocks more full y Ihan :.tandard timc-serie ... models can . Consequently, we resol\·ed to fo rgo time-series fo rt-alsts of l1alional \·ari ahle~ :lnd to suhstitute natio nal consenslls fo n.:c l sts w henever they we T(" I1c(:d (;.'"(1 in the n ine ... tepwisc l.ouisiana equations.  , The lerm I'IlormaioOfl ga .... relers 10 /he percenlage redt.Jc-  IIOtl If) slandard _ra lhal results /rom the /fIdI.JsIorI of a partICr.sIM varrable III an equatlOtl ConsIder two equaliOllS. eOl.l8to()fl A and eqlIallOtl B. which arc dcslf}flCd 10 fOl8CaSI /flo SBm6 ondependenl variab/8  ror  The use of consensus forecasts in (he model \'(Ie fo llowed the time-ser ies mood-building plUctdure described aoovc to constn lCI forcC:lsting equations for I.."ach of the nine I.o uisi:m:t v;lri;lhles In sim il:ir sll Kli!..'S for New Mexico (Gruhl."n ;lI1d Long 19HHal. Ohio (lloehn and 1:kII:lZ."y 1985 ). and Tn :ls (Gmben and Long 1988b), the model-builders :Iiso l"Ol1stnlCtL-d time-seri!..":> fOr('Clsting equ:ltions for Ihc n:ltion:.1 indiC:IIOrs :Ind u!>Cd fo rcc lSIs from Iho~: t'qualio ns 10 pl't:.'llict the region:11 v:lriahk-s The pre ...enl fon..' Clsting mCKle!. ho wc \"{'r. m U~ 1 :In:ommod;lIc the o il-price ~ h ()<.: k... of the th ird qu:m er of 1990. It !>Cemed compelling to (:hoo.'>C foreclsts that ca n incorp orate the impliGIEco nomic Review - March 199 1  Suppose /flal equatlOll B IS  idenlICallo BqUSIIOll A a}(C9pltllai equa loon B conlallls IWO Jags of one acid,llOfIal varisb le Lei SEE A represenl tile siandard 9"Of of CSllma lC 01 Co ulllIon A and SEE. be the Slandard error of estlmal9 01 equa llon B The gain in 'nlOfma llOll of equa lion  l3  over e q uallon  A is  due 10 the  Inc/uslOll of the vafla/)/o m CqUlll1Ol1 B bul nol in equation A The illformallon {J8m IS the percentag e r:lJfference If! Ihe slandard errOf 0I9SIIfll81ol for BqUSDOfl B compared with /hal of equsliOn A ThaI IS.  and F values  The I'Iforma/JO(l g8WI- vanabic I  CCfTf!-  spend 10 one IJfIOlher ,., /he following fomt I~I  {(n - I<.  I . q~  1<.-I .. qF/I!I.  whereq IS /he numIJer 01 iJdd9d varl8bles."  B ccmpared  WJlhA. n IS IhenumlJer 01 0bSefva11Of'lS. and I<. IS /henumber  01 vanables 1'1 B Thus. Iho rnonomum valve 01 I  /hal a /JoWs a new varl8b1e in B 10 bollflCluded .... a forecastlflg equallOl1  CCfTCSportds 10 Ihe value  01 F IhallS srgmf>eanl at /he a ,  level T  The slepWise procedur9 we use coolalns a declSIOI1 rule thaI reiCCls somo candidale vanables Ihal origInally ar9 mcluded 1M the IOffJCaSlmg oloualoon The rule worl<s as follOws Suppose some V/lflsbi8 x, ad ds enoug h IOfecaslmg pawer 10 warra nl including II In some noarly final predICllYO equa twn I/ I/le subSCqU6nt mcluslOIl of other predICtively powerful vllflabJes (say  x, Ihrough ~J pushes  the t StallSIIC for /Ile cocffoclem of x , below thea IS level of srgrnl>eance. lhen  x,  IS deletlJd  'rom  the equsliOn. and  Tho only CxCCpllOt'110 thiS re}eCIKXI rute was IMIIWO own I8gs were used any lme tlI6y resr.slled '" a kMer mean squarc CffOf /tlan ono'y 8 firSl own lag Of ono'y a ~ 1"  ~" remaln  sCC(l(H1 OWl' lag. rflgiJId!ess  011 slatlS/1C II not even  one  own lag was selecled for anyequallOl1. WtI did not force any ." Even mcscdcc&Ofl rules aremr:xerestnclJv8 than those oIHoehnSlldBalarsy(r985J, who used two own lags ." a. cases Wc. Hoehn SlId BaIaLsy (1985). and Grueen and Loog (1988a. 1988b) apply some speoaI, less rCSlrro;lNe rule for /he IfIC/usIotI 01 own lags oeclluse we have S/roog {XI(}(  behBfs aOOuf Ih6If fQfscastmg pq.Nef  ,  Table 1  Information Gain Statistics LARIG  LACIVlF  LANAG  1.6616  8.1853 8.7443  LAHQUSE  LAPV  LAMINE  LADUR  13.2320 5.8189 31 3110 2.9310  0 193 3.3464 2.1234 .6472 4.8635  3.4795 1.7916 12232 3.6038 4778 2.1176  lANDUR lASALES  Regi onal Variable s LARIG LACIVLF lANONAG LAHOUSE LAINCOME LAMINE LADUR LANDUR LASALES  2.9453 2.4097 .7046 .2491 9.1935 9.1429 .3589 2.1244  2_1099 3.1255 3.4313  2.4938 3.5250 5.6310 7,4125 1.8068 2.0287 2.0386  6.8539 .7993 6.0856 6.6385 .8966 6.5702  .4619 .4049 4.4981 4.0652 3.2327  16.8368 15.3678 8.0740 .8573  3.8229 116948 4.3610 .7502 .2402 .6730 2.7242 88399 54624 3.0811 7.6331 6.4417 4.1853 .3555 5.6633 1.7168 .4215 1.4401 .4678  .5674 2.8264 15385 3.1039 .3479 2.4537 8.5124 7.6676 .1739 3.9612 .4410 .6688 8.5021 .3106 2.3191 1 1345 1,4018 11 .8296 2.8637  6.2078 4.3366 24.1981 14.9124 16.5106 8.8614 3.6471 5.4135 2.9158 18.3035 16.1936 141299 12.4646 ' .7843 10.2659 11.7320 2.7969 9.5220 1.9768  1.6480 4.4937 5.1955 1.0702 2.5825 .2901 8.4950 6.3242 6.2224 .2257 2.0539 1.9240 1.5568 7.4026 .8842 .0152 .4339 5.5698 ,3123  8.2093 1415 5.3289  4.5442 4.5699 5.9017 5.5021 5.7348 .7240 13.6964  5.8868 7.3784  1.1639  7.2933 .0570 4.1261 3.2825 1.0379 2.1945 2.9407 7.5858 1.4237 2.7128 .4620 .0158 2.7897 24073 2.9304 2.0627 .9981 1.9797 5.5017  14.5606 4.5463 5.1457 23.2370 1.5532 18.5228 2.1330 .3708 1.4553 16.3177 8.5981 4.2702 15.9263 9105 2.7067 4.2651 5.7575 13.6274 8.0893  6.8791 .1556 6.9515 .1089 6.4556 6.2576 11 .2339 5.5768  National Variables REALGNP .4009 GNPDEFLATOR 3.8777 CPIMSA 4.3095 USNONAG .6921 MASOND 5.6227 INDUSPROD 1.9254OILPRICE 22,8751 PPIFGA 12.0540  M1  23858  UNEMPLOY 2.4354 TBILL 1.4855 PRIME 44341 CIVEMPL 2.1458 INCOME 2.1790 EXPORT .3146 IMPORTS 12.4990 PERSCONSUM 1.3079 NONRES 5.1068 RES 1.4211 LevelNalue'  .10 .05 .01  F 2.39 3.15 4.98  1.9242 10.3982 9 .3603 .7220 95561 1.4076 19.0901 16.5807 3.5865 1.53545.7978 69030 1.0223 .9839 1.77541.7000  .9961 6.3207 .9743  2.2023 1.6620 1.6550 1,9856 1,2756 .9875 .3567 .8217 4.7597 .7063 .9413 1.8661 .6763 .54-57 .6943 .6606 .1108 5.9358 2.0008  1.8271 2.7846 4.9800  • For a mathemallcat derlnl\lon or the relationship beIWeen /values and Fvalues. see footnote 6 NOTE: AppendIx A dehnes the VlInab~ used In tns table .  •  F~-dt:-r:. 1  Rl"SC.· ,....• Hank of r>aUas  R;nher Ihan huilding :1 mouo.:! to forcc:!.'>t oil prices, Wt' indutk<l quant'rly :lverages of futures m:lrket prkt's for each uf Ihe qU:Hters to IX! forecast" For the rest of the forecasts of n:ltion:d indicaIors. we lI,'i(."(lthe const.'n,~us fOI"{_-'(:<lsts from the Scptemlx:r 1990 issue of Bille Chip ECOllomic flidicato/~ :md thl: quarterly sLlpplt'rnent that also :tppea~u in thl: S:HTIe month. T heSl..' mile Cbip conSt;'nsus foreclsis arc b:lst.'<l on :m ;l\·erage of the fon_"Clsts of tiff)' finns that participate in the Blue Chip p:lIlel. so thl:Y incOfJXmHI: much infonnation that h:ts IX'"l·n captul\.'d by m:my fo~caslcrs.q Consensus forecasts are oftt'll relatively accurate I n:1 sludy of seven macro<:'conomk' vi.lriables that :tppear in the mile Chip consensus forecasts. McNIXs (1987) finds that about only one-fourth of the individual fOf1.:.'clsters were consistently lllOTe accurate th:ln tIll' BIlle ChiP consen,~llS fOrt:CISt Anothl:r group, about onethird of all foreGls! panel memhers, Wl're consisten Tly less :tu:ur:.He Ihan the consenSllS. The n.:maining panel members, :t link: less than half the total. wert' slightly inferior to the consensus. For any particular variable. the BIlle ChiP consensus W;IS more accur:l1e than mast indi\·idual forecastc.:rs. even thou~h every forecaster was more :In:uratc.: than the consensus for at leas! one \'ari;lble. Non!.: of the forecasters oUlperfonned the consensus for all sevc.:n variables.  Configuration of the final model Wt' fol1owt:d the limc-series lmxleling procedure dcscrihed above to construct forecasting equ:llions for t;'ach of the nine Louisi;lna variables. WI: used quarterly <lat:t for the period 1970:1~1990:2 10 forecast rTloVem<:'nts in indicators for 1991. Appendix t\ define.~ the variahles, and Appendix B contains the n:l1ional consensus forecasts that were used in the Louisiana forecasling equations . Appendix C de.'i(."fibes the cquations. Recill th,l{ hecause thi.~ is a time-series model. its equations arc purcly predictive; th!.:y uo not represent :llIempts to explain the Louisiana t'conomy hut onl}' 10 forecast It Ne\'erthdcss, il is i!1leresting to note how often the purely statistical v:lriab[c.;: selecl ion rules r<:'sult in c<..juations suggestive of the actual structure of the Louisiana econo m y. For example. the import:Hlce of energy t:xtr:.K"tion to Louisiana F.cooomic  Revkw~M3rch  1991  i.~ ,~uggested by the regularity with which energyrdated varia hIes appear in forecasting equ:lt io ns. Oil prices appear directly not only in the equations for the louisiana rig count and mining emp loyment hut also in the equation for nonagricultural employment. More(wer, beCluSC i.ouisiana nonagricultural employmem is forecast by oil prices. and such employment fOf{'CaSL'i Louisi:ma personal income. oil prices may be seen as indirectly foret·:lsting Louisiana personal income The ri~ count is a predictive variable in the Louisiana hOUSing permit equation. Considering the state·s relatively low labor force partidpation ralC', it is also interesting to note thitt cbanges in rC<l 1 person:ll income forecast c nt!), into the Louisiana civi lian labor force. While changes in the labor force mily suggest inmigration in response to rising real income, it may :tlso suggest :1 discouraged worker phenomenon. The years 1980 and 198 1 not only saw Louisiana's highest r:.Ues of growth in re:ll personal income during the 1980s but also the decade's highest employment r:.llcs. Becausc few states' et·onomies vary less consistently with national nuctllations than  II should be noled Ihal we used the prOOVC6r price rndex for the refme,·s cost of crude 011 or, Ihe coos/ructlOll of lhe forecasl'ng model but relied on forecasls 01 the price 01 I,ghl. sweel crvde as mpu/s to lhe I()(~st Movements m these 011 priccs are highly cQffelaled We based our dec,· SJQ(1/Q use two different prICes of crudeoo the avaifabililyol e/ongcr time scncs for the reliners cost 01 crvde end the ava,lablllty of 8 de facto consensus lorecast, VI8 futures prices, for light. sweet crude Wecons/luc/ed a regression equalion /0 lelale movements of one to the olher and estimated a forecasl growll! rate IOf reliner's cost of clude. based on the term structure 01 futuros prices IOf IIghl, sweet crude When following the model·buildmg procedUfe for our Louls,ane forecasllng equation. we restricted the set of nalional vanables from whICh candidates could be selected Only varoables thaI were /otecas/ m Blue ChIp EconomIC indi-  cators.  lIS quarterly Sl.Ipplemenl. or by means of futlJles  market prICes. were a/lowed /0 be conSidered lor cand,· dacy Ollhe nmet8fJfl nalJQfl3/ val/abies m Ihls set. Ween IQlJlld thelf way infO  IfIC  linal /otecasting equations Tile  nallOf"lal indicators that appear In lhe fmal forecasting equations are. tnemselves, forecast 00 tile bas,s of tile above sources  7  1.0ll l .... i.IIl,I .... ('.... IlL·f\\()<)(I-CIII  11Jx,,'{). I IlL'  n.:gu bri l ~  w i l h \1 11Il1l Illlll ..o i l 1l;lI io n :d \ ;I r i.lh].,· .... fin d IhL'i r  w:.y  inlo IhL' llillL' for\,.·c .....1lI1g ...·qu,nion .... i ........ Inl.. ing  Table  :1 1),. Ihll'CII:l l illlh in .... i\ (If lIlt· Ilin..: Ilm..'''·: . .... t I:.ri .. . Ih l l •....  F. II'  t!L·di n..: . . il) l ong Il'1111 i llllTe.....1 th L· AA \ h Ol1 d 1:ItL') prL'din i l wl .....;!.... e ..  L·\:1I 11pk.  1:l tL·.... (herL·. in 1,c )lI l ..... :l n .1 11ll' p n nw  2  1991 Forecasts of Growth Rates of Nine louisiana Economic IndIcators  C h .mgL· .... '11 1l:,lulI1,. 1 111I(·r\,.·.... 1 r: II L· .... lor(·L';t ....1 1.0lII .. i -  hc'u. . i n .!.!:  .:I1\,.· prL'd ill inl re: .....L· .... l1l11K' l,oui .... I.IIl;[  LARIG LACtVlF LANONAG LAHOUSE LAINCOME LAMtNE LADUR lANDUR lASAlES  rig COUll t On Ih...· othl'r h .llul . real G\P 1)t,,'(oIllL·..... 1 /ol'l·la .... l tn g 1.l ri.lht". in only 1110 t.'{jIl, lI nm ..... thlhl'  of LOllI .... I.IIl.1 dlll~lhk· good . . \:l1lp[OI1l11.:'1lI .lIld IllL' 1.01l1 .... i.m.1 ('II Ik lll 1.11)<11" fo rct.'. \ l llfl·(lll·r. :-.IK"nI I)()(I·C, II ·.... fi l)d l ll).: .... 11;1ll' in:.ln1tllll· 1I11pl ic ilUlIh for lilt' Illie I h ,1I n .ltlon :ti 1·;ll"i;ll1l..-.... pby i n ... HilL'  o f Ille  Forecast rales (Percem)  lnd;cat()(  IXTlll il ... I\hik ,k·din ..: .... In  l orl'c .....l i n ,!.: L·qualion ....  I S JX'T'<()Il:d i n colIIL'. for e '"" ;l mp t..-. fO!\.·l ·a.... 1 i l1 o \ ·:1:.\·:, in Lou i:.i:lll:t ['ll:t':'ool1aJ iIKllIll\.·  9 .• .9  10 16.0 2.1  2.  - 2.1  -5 3.9  D e d i Ill ' . . i n  EIl'l)' onL' u t l llL' nilK I'OI'L·C;.I..... l ill).: L·qll:ltlon ....  NOTE: Appendix A defines the variables used in this table.  l'(Hl ..  1:1I1h :11 le:I ....1 OIl\' nOll-oil 11:lIlo n:.1 1 :U1,lhk  Forecasting the Louisiana economy T.lhk .! prl· ....L·ll h 11K' Ilil)(lvl'-. 11J) 1 l u n.·cl"'h ot' ninl' l'COll01llll IIld ICllOI'" t'or LOlli:'l.lI1.1 To  qll\'llt " 'nL'I):1 ( ·r: I .... I1(: .... led l.oui .... i; t!1 :1 L'rl1p ln~ !l1t..'Il!  lInd l ....... I;lnd Illl' lI11plicliioll'" o j I ll",...",. jOI"L'l·;I .... ". 11 I..  10 ,,~·:tI..L·r .1\l·T~'gC L'''P: II1,' ' lon tlLlIltlll' n ali o n ....  \·I1\'r).:~ 11I)()tn ~l·;l r ....  of II)HO :lnd II)X I. 11t\ · .... ull . . \·  lI"l'f lill u n lll ... i d L'" P:l... 1 I1 l1(1 l1:11 1011 .... ill 11lL' ....U I L' "  I, If (11\' 11),0.\( h ( F i ).:u I"e :~) Dv.. p I( l' ....1 Illll' .l : 1'I III l it i 11  l ·\·OIlIJ!l!il'ind l(;l h l)".. I.iI.. L· ih L'l'0I101Il il' ....lrtl"·l lI rL' .  I ll\' I. II ~· I I}HO..... l .o u i .... i.lIl;l Ii.h n eIL'!, ;I).:ai ll !'L';ld 1l'd  1.l lll l "I:ll l.I ·" "l'l,'n l l'lll!1(l! " ic pI:r!(lnn;l n u,: de\ 1;1 1..: ..  11](' \'l1lplo~ tnt.'111 Jl\'ak il IlI h l \'d in I <)HI  II Ilk·" f)"olll 11K' 1I.lI lon ....  OIL'!' I ll ... ' p :I .... ' declll\· hOIl\·\\·r. Ill,,· I.oll l .... i·  '" Ihl' lOl1nJ.:Ur:ll iol) of Iht..· 1ll1)(ld "'1I~t.''''''. I.t )lI i .... i;I11,( .... l'(fI!1( l illy ).:11)\\ ..... ;K I: l'Ier:lI l· .... . ... 11)11 .....  \' lllplo} Illl'nt 1\:l;Ii n .... :.hou l fhe Il lIIl· ... ,I .... 1.l rg,,' . 1  :md l'OIll r:IU", II lIlt I ll\' priel' o f t..· ner).:~  ....I u n..'  111 1<):-;( •.  .In.1 \·\"j)o tll } lu .. Ch.lIlgL·d  . \ lth(lll~ 1i lIlltllll).:  of l.oU! .... I.uu l ·lll ploylll\ ·111 . t-. th.1l 0 1 ti ll'  II Ill'l) \'Ill'rg~ p rin: .... ld l pn:dpil ou t h L' 11111);1\'1  11;111011. lIlil1il1~ ' ", .. h :lrL·  11la dL· I,I)llhl.ll1;1 I lllL' ()fllnl} .... ix "'1,lI l', ,,11I ):'L'  I h \· ....I ;IIL·. !:d l m).: lrom "i .H pel'"ell l III ]1),'>1 I I I :~6  h: ... d ..:d  i!ll.: d 1l1.u'I..L·d l~  !1)  11(lIll ill. 11 (;:-' 1' ..I,·di llL'd I" I.lllli 'I;I I).II'll:).::I11 .1  rl1.Hl·111 i n 11)1'1) Co m·~· I~ dy . joh .... III f t..·I :1 1I a mi  rL'('(l1 L' T'y d uring I I) K"' . :111 hough :t n nll:d :II·L' I: I).< L· ....  ....I T \ i( l' 1'l'I:1(l·d illdl..... lril·.~ 11 ;1\ l ' 1l1 ; 1I1 l'l ll ~ 111,'f L':! ~ l'd  le lr 1I 111.... 1 (l j' llll' .... 1: 11..:· .... ,lg.l.!rq':;l I\· ind icl l())" .... )"L"  I l ll'ir ~ 11. lrl· " (II (1 I l'l";l J l l' I'l p lll ~ lllL' n l '1'111' l· l ll·r).< ~  1ll:l Il lL'd h ..: loll 1\)1';(1 1L·1t.'1, . :Illd Ilil' .... tIlL· h:I" .... i lln·  indu"lr~ Ivlll,u n .... \ L'r~ i mpOt1:lTlIII . I.I IUi .... l.lIl. l . I lUI  ).,:1'(11\11 1111111,: :.111\\J~ 111:111 Illl' n;UI(1Il L'IL' )") ~ ·l·.lr I n  inll'\·.I ..(· .... in 1111 p r iel '" nIl IOIl).:L·r 1llt..';l ll .1 .... t1llllll 10  JI) h·<).).<ro ........ 1l01ll 1ll,IIIXT-.e,n ,t1I1l(,(II)lL· rO ....l· "' ,(I  1I1l' J.olII .. i.I1l.1 L'COllom\':'" II1\'\ IInu' d id  fk.· ...."·111  1).lI lon.111I hlll (lnl~  5  I Ix·rn·nt III 1 ~)[ 1t "1.1I),1  \ hllllUgll 1.IIIII .. j;l ll;I " l'nl pl l)~l l ll'nl gr,,·\\  "lllbl.IIlIL I IJ~ b ....I ..:r Ih:lIl tilL' n;lliol1" dll r in).< 111\·  'l'h\' 1')<)1 f OI'l'C"'h indll(k· (0 h ig h l·\p.I O.... I{)1l III 1 ;m.l h lt.' .... reL llcd III I h ...· 01 1 .lIld g.l .... \·\tr.I( lllltlllldu .. t0 hul .... 10\\ ).:rll\\ lh .•tt k""'1 h~ n'U1< ' I1.1 1 .... t.ll1d.ll1.1..... in thL· .. 1, 1(L··." .1).:).:I"\ ·).<.l l l· Li l liit' fllf,\· ind ll,ltl)t... Ik.11 1'\"1',,111:11 I !H, U))L' ).:\'(11\1 11 I .... IlItld "' I~lll' \\ 'h ik- l lll'rl' i:. ;l good \1\':\1 III 1;l ri; lI ion  in AI<tsJ<a New Mt1I 'c() ()j..1<111011~' 1{",M .mtl WYOUJ/1l9 afO also _9,(,,,,00"(:'''9 51,>les filo)  •  olhef he sl•• rcs  tl1\'  prnl ll'1l 'd 1lI01 "'l11l'n h in nl h e!' I.lllIi .... i:ln:1  \'U ' 1lI111111 IIltliL;l tOr... ( 1)91 i:-. gl' n er: l lt~ II 'I\:I';I"'! .1 .... .1 IlI).... 1(ill· ~l·.lr lor thL' ..;tatt..· \ \·I\·l'Il w k:. ..... dl· ... pll .... r t'tkr,1llk SC,' r'\'': U.:m k " flh l b s  Figure 3  Figure 5  Nonagricultural Employment  Louisiana Housing Permits  InOex, JIIfIuary 1980.100  '" '"  .....  n,  -  '"  "" ''''  '" '"  .  SOU RCE US Bureau 01Labor  ... ..."" ...  $+a1lS1>es  SOU RCE OF PRIMARY OAT" : U S Bureau 01 the Census  Figure 4  Lou isiana Nonagricultural Employment  "  """,,, f\.- ............  ,."'"  "" SOURCE OF PRI MARY DATA, U S Bureau 01 Labor Sla~StlCS  imTL·a.......·d oil prit"o.:... Illl· mudd dol..''' not pn:dit"t:1 hool11 for Loui .. iana  Thl: I ·pl..'rc~ nl raiL' of L·XP:ln.~10n prL'(licIL·d for 1.001l~i:tna n()t1a~rinlhtlr:d \\";Igl..' :lnd ..alar), l'mploymcnt h mort.' than I hree time.. as f;lSI :1;'0 \\"h:1I W:I~ :Khl:llly p()~ll'd in 1l)H() (0 ..3 pcKl'nO, Fi~lIrc 'l til·piet.. I);'~t Illlctlialion" ill Loubian:I's nOlla).trlcliliur.:t1 W;l!-ll' :uld ,alar)" I..'mploynlL'nl.  10gL'l hL'r \\ illl Iht.: lorL'Cl..t v:l llIl'S 'I1H: figure .. ho\\ .~ thaI. while Illl' forccl .., gl'Owlh r:lle I~ low hy nalional .~I,lnd:tr<.h. it i .. compar:lIivt'lr high hl' rL'i.:t:nl LOIII:.i:m:1 ..t:u1d.lrd.. .\'L·\ enhdc::.... the 1991 fort:G' . . 1 of 1.0 u i . . I;ln:l L·mployment ..till doc:. not n.·ach Ihl' It:\·c:! . . of thL· .,:arty 1980s. Likc\\i . . e.tlu..' mild O.9'pL· rcen ll~lI l' of expan.. ion fo rt.:e l'l for I.oubi:ma ·... bhor force i... a good de:11 fa:.lcr 111:111 Ihl..' dt.:dl1ll' it realizL'(1 in 19H9 (OA pt,·rcL·nl) Till' 199 1 fort:"<.·;I.""t.~ abo :.lIAAc:.t f:I,'t.:r I: lhor market indicalor /-:ro\\,lll than whal :Ippr.::trs 10 ha\'L' O<XUI'fL·d III 1990. \\o!"L·on:r. the lll(xkl foreGl .. . \...."itnJllg~·r gro\\th III rL':11 pn:.on:ti income (2 I \ )Cf(:~nt) I h:m for L'ithL'r nonagriclIillII':ti ,,:mploymL·nl or the lahor fore..·. The 1990 ;nl'l"t.:;I~t.::' in o il rricL·s hl..'lp to forcca ... t a 9o.percent illl'1"e;t."i~ in drilling activity :I nd a 26·rx·I"CL·nt incrr.::tsL' in mining employment in l.o11i~iat1:t for 1991 ov(.."r 1990 ['ositivL' 1-::lin." :Ire ;, ).,0 fore<.<ht fo r rL':11 .. .:til'S 1;(.1( eol!cctiot1 .... which \\ill irKrl..'a"L· ';.9 pt.·1"("..'nt in 1991. Thl..' highL· . . t r:.ttL· of (,."xp:msiol1 (If any \'ariabic fOI" I..oUl"ibna in 1991 is housing \x'llnit... \\ hieh :lrL' prr.:di{:ll·d 10 intTe:lM! 16 pert.:enl I\:. Figure 5 .. ho\\:.. L·n.'11 with this r.tte of \.'xp:ll1sion. p<:rJmls n:m:lin f:lr hL'IO\\ their kVl'b of mo... t of t h~ 19HQ-.. '111t: pn.·uil1ed expan .. ion:. in i.oui,i:ln:("i pt:r:-.onal JOC·OI1K·. lahor fo".-e. nOnf;ln1l employrnt.:Tlt .  •  urill mg at·[i\"i[y. Ilou ... ing periniI:-.. ;lnd re[ail S:IIe:[ax colll..·(·[ion ... do nol im ply ('mplnymenl gro\\ t il in Ihe :.1;111.:':- manufa('luring "'I.:clor Durable good... empl(lym(,.'nt f:ll1:-. Il)' 1.1 percenl. whih: nlllldur.lble good ... ('rnployment ... Iip:- h y 0.5 pern:n(. Despit(· I lie continued impon ance o f energyre!all.-'(I C\'t'n", 10 lI)l' I.oui.... iana l·('·onOIll}'. thc :-t'l Ilf flll"l.-'(.':I:-ling t'(jll:tl i()n:- incllt(k ... fifteen n:llion:ll fOI"l.·c.l"ling \·ari;lhll.·:- nut of t he n il1l'lcen origina lly con:-kk'red in thl' fir-I :-t:tge of Illodd bllilding Appl..'ndix U (it'pit"l:-. Iht' foreGI:-!.... of till'....c \ ':IIi:tblc::md oITt'l":'> :t pil'lllI"I.· of ... Iow on:'l~ llll·xpa n i n [Illal (IUl pul :l nd empl(IY!1lell!. For 1991. l)(lIh re:ll G~ P and I is n()n:twindHIl~lll'mplo}"lnt'nl i ncre:tse hy I Iw rn'n t It is intt'rt':-ling to nOll' Ih:Ll. (lespi\(;.· Louisi:tna 's typical (kvi:tliolh from U.S p:lltcrns of t·x[u llsion. Ihl.: fOfcGlst for I r.s no nagril'u itur.t l wagl' :tnd sal:IIY l' l11ploYllll'nt Wmvl h for 1991 is i(kntict110 Ihat for l.o11i ... ian:l II :-llOUld hl' noll.:d thai Ihl' fOn.:GI:-1 ItlT i.<llli:-.iana·... ntmagrinlilural !.:l1lpl(lY111en[ growl h in 19l}1 i... ha:-'l'd. in pan . on foreGI....1:-. of SOIllI: dedin(':' in oi l pli('I..·:- in Ihe -.c<:oml half of th:lI ye;lr I.<)ui:-i;lna·s lal xlr market indic.llor:- wew more r.lpidly in 19HH. w hen IIIl" :.Iate was l akmg o il' aflt'r con......nLlivl... :tnnuallkdme:. oycr the period 198s-B7, Ihan Ihe J-tTO\\·th our model pn.'dicl:-' for 1991 BUI a ... i<lt' frum 19HH. thc fOrCGI'it for 199 1 impJi!.:., Ihal loui ... i:ln:(s (,'!l1ploymcnl :tnd lalx)r forcc will g row b:-.[er I ha n a[ ;tny lime Mncc Ihe early 19HOs. I.oui:.i:m:l will nOI boum in 1991. hut the ye:lf will hI..' better Ih:m almo:-I :my rear :-.inn: Ihe IXlom yeaTS of :1 d!.:Glde aJ.:o  10  Conclusion l.olli:-.i:ln:(:-. Cl'onomy dillep. :-lllht:tnti:tlly from lil:1I of Illo:-t ... tatc .... hOlh in ...Iflll ·turl..· :tnd dYlla111il·:-. Stfllctur.llly. tilt' I.()ui:-.i:ln:l l'(,(lIll)IllY i:Ullll:-U:l l in llle cxtent 10 whid! till' l..'nl·l'/-:y industry dOl11inatl..·:- it Ix,·all-.c of Ihe profound t-rfl~CI of cncrgy price 1l10\'c melll:- on till' :-.t:l\t·, l,oui:-.i:tn:t·:-. c("(lIlornit" Illl('lu:lljon:- differ frolll lhl' n;ujon·:-. not only in rn:lgnilude bu[ :1 1-..:) :-,ollleliml'''' in dirl,('llon Alt hou/-:h \\C u ...n l :-.i:tli,ticilly h;l:-l'(l d •..'cisioll fuk:- 10 \,:o n:-t fll<:1 a fOfl·c l.... ting model. cncrgy·rt"!ated \ ': In:lhlc.... appcarl 'd in equ;lIlOlb not only for thc 1..ouhian'l rig ('OUllt and mining cmployment hut al:.o for th \;.' ... t:llt·· ... nonawil"llltllr:ll Clllpl(lY1111:111 l\'1<lrC(l\'l'f, t'nt'rgy prlt.·!.:s indirt'Ctly I(lf!.:ca:-I [.()[li.o;ial1a ]1""rsl)n:ll in("(lIlK' :lnd houo; ing permils Ik:-pitc 11K' pecliliaritit's of [hc l.ouisbn:1 ,,·("(momy. SI..·\'cr:.11 \·ariahlc:-. rdlcl'li\'l' of national tlul·l\lalion... found their way into tlK' fOfl..·c:.lsting l'(lu:lIion:-.. 1\":ltion:l1 e\'I:Il1'" dearly h:IVl' f( ll"l.·l:l:-'Iin).: pO\\l'r on Ihc [.<lui ... iana t:<;onomy. l'\'('n thollgh tiK'ir I)()\\'('r rnay Ill.: le:..... lh:!n for 1I10:-.t olhl..·r ... t;ttl·... Our model fOR'(."";l:.b ).:I1>wlli in 11)9 1 for !'>I..·\·l:n ( If the nine 1.<)ui... i;lIl:\ CC()I)(lmit.· \':Iri:lhk':-,. '111e Ill( xld prl..'dit.·ts mOlll-r.lle 10 high l.'xp:lI1:-.ion for \';tri:lhle:-. rd:llt'd to 111(' oi l :tnd g;ls l.'xtr.ll"t ion indll"'l!), in the St:ltC. hut gro\\·,h III LOll i,'ii:l na ':- :ll-Q-trl·/-::ltl· lahor fOfl'(' indiGlitl["') \\"illl)!,;: relalively ... Io\\". l{c;d personal in('ollll..· will :-bow IllO< incr!.::l:-<:'" Tilt' upturn in oil pri('es d uring 1990 doe:. not ... ignal a 1)(IOm for I.Ollbi:II1:1 in 199 1. hilt t'xp;l!l ... ion will he more r:l pid Ihan for mO....1 rece nt Yl.'ars  Appendix A Definitions of Variables in Forecasting Model Equations (Quarterly data; monetary values expressed in 1982 dollars)  CPIMSA :::: U.S. consumer price index for all urban consumers.  State variables  AAABOND :E Moody's Triple-Acorporate bond interest rate. INDUSPROD ::: U.S. index of industrial production. OILPRICE = U.S. producer price index for crude petroleum. PPI FGA ::II U.S. producer price index for finished goods. M1 = M1. UNEMPl OY:: U.S. civilian unemployment rate. TBllL == 3-month Treasury-bill interest rate. PRIME ::: Prime interest rate. CIVEMPl = U.S. civilian employment . INCOME", U.S. disposable personal income. EXPORTS = U.S. expo<1S of goods and seMces.  USNONAG • U.S. nonagricultural employment.  lARIG ::: Hughes rotary rig count for Louisiana. LACIVLF::: Louisiana civilian labor force from the U.S. Bureau of Labor Statistics household series . LANONAG ::: Louisiana nonagricultural employment . LAHOUSE ::: louisiana housing permits. LA INCOME ::: louisiana personal income. LAMINE ::: Louisiana mining employment. LADUR ::: Louisiana durable goods manufacturing employment. l ANDUR :::: lou isiana nondurable goods manufacturing employment. LASAlES :::: louisiana sales tax revenue.  National variables REALGNP:::: U.S. gross national product. GNPDEFLATOR "," Implicit GNP price deflator.  f.":"ll.,lIIic Rev ie w _ ,\l arch 1\)9 1  fMPORTS = U.S. irrjlOrts of goods and seMces. PERSCONSUM:::: U.S. personal consumption expenditures. NONRES :: U.S. nonresidential fixed investment. RES = U.S. residential investment.  "  Appendix B  1991 Forecasts of Growth Rates of National Variables  Forecast rates (Percent)  Variable  1.0  REALGNP GNPDEFLA TOR CPIMSA USNONAG AAA80ND INDUSPROD OILPRICE PPIFGA UNEMPLOY T81LL PRIME INCOME EXPORTS NONRES RES NOTE Appendox A (iel,nes the vilflables used  Il  4.3 4.7 1.0  -.3 1.2  13.8 4.0 .5 -.5 -.5 1.3  2.7 .4  -.7 ~  Appendox B  ft-deral Rescryc Bank ofOaUa...  Appendi x C Features of the Forecasting Model Equations State variables DEPENDENT VARIABLE : LARIG  Variable Constant LAMINE LADUR PRIME OI LPRICE R2 = .4 180 ,  ,  R = .3857,  Lag  Coefficient  Standard error  t statistic  0  -.0129 - .7086 2.2273 -.0199 .6390  .0094 .4185 .5615 .0080 .1161  - 1.375 -1.692 3.967 -2 .474 5.502  SSR = .4695,  SEE = ,0808,  DW = 2.031  DEPENDENT VARIABLE : LACIVLF  Variable Constant LACIVLF LAINCOME REALGNP GNPDEFLA TOR PRIME EXPORTS R2=.3813 ,  Fi2  Lag  Coefficient  Standard error  t statistic  0 1 2 1 2 2 2  - .0062 -,2452 ,2049 ,1722 .7593 -,0024 -.0529  .0029 .0999 .0916 .0963 .1729 .0008 .0312  -2, 156 -2,455 2.236 1.789 4,391 - 2,914 - 1,697  = .3283, SSR = .0048, SEE = ,0083, DW = 1.966  DEPENDENT VARIABLE: LANONAG  Variable Constant LANONAG LANONAG LAC IVLF LADUR LASALES LASALES OILPRICE EXPORTS NON RES RES R2 = .6608,  Lag  Coefficient  Standard error  t statistic  0 1 2 2  ,0034 ,2888 .1121 ,1693 .2141 -.0390 .0322 .0214 -.0601 - .0908 .0329  .00 11 .1135 .1004 .0786 .0527 .0156 .0141 .0083 .0251 .0358 ,0128  3.041 2.545 1, 11 7 2,153 4,064 - 2,499 2.279 2,578 -2 ,399 - 2,535 2,583  1 2  -, R = ,6094 ,  1 2 2 SSR = .0028,  SEE = .0065,  DW = 1.968 (Continued on the next page)  13  Features of the Forecasting Model Equations-Continued  DEPENDENT VARIABLE: LAHOUSE Variable  Lag  Coefficient  Constant  0 1 2  -.0157 -.3074 .1009 .3905 3.8016 3.9341 - .1348  LAHOUSE LAHOUSE LARIG LACIVLF LANDUR AAABOND UNEMPLOY INDUSPROD PPIFGA R2 ", .5376,  1 2 2  -, R :  .4755, SSR "" , .6242,  2 .8222  3.4075 -3 .5255 SEE: .1557,  Standard error  t statistic -.484 - 3.247 1.158 2.093 2.033 2.117  .0324 .0947 .0871 .1865 , .8704  1.8587 .0391 .6115 1.8770 1.6764  -3.444 4.615  1.815 - 2.103  DW: 1.99  DEPENDENT VARIABLE : LAINCOME Variable  Lag  Coefficient  Constant  0 1  .0017 - .2213  LAINCOME LANONAG LADUR CPIMSA AAABOND INCOME NONRES RES R2 ", .5746 ,  .6689 .1697  ,  1 2 1 2  .3318 - .0086 -.2'50  .0855 -.0956  R : .5246, SSR: .0041 , SEE : .0078,  Standard error  t statistic .713  .0023 .1021 .1361 .0647 .1283 .0022 .0890 .0442 .0427  -2.168 4.9'6  2.623 2.586 - 3.950 -2.416 1.937 - 2.242  DW : 1.889  DEPENDENT VARIABLE : LAM INE Variable  Lag  Coefficient  Constant  0 1 2 1 1  -.0'47  LAMINE LAMINE GNPDEFLATOR LADUR TBILL OILPRICE R2 ", .7612 .  ,.  ,  .3887 - .1163 .9695 .5025 - .0039 .1207  R : .7407 , SSR: .0197, SEE: .0168,  Standard error  .0053 .1258 .1005 .3533 .1183 .0019 .0262  t statistic -2.779 3.090 -1.158 2.744  4.247 -1 .980 4.607  DW.2.095 (Continued on the next page)  .'...Ito ..... l .h'.!oo ....... .. Ib ll k of Dallas  Features of the Forecasti ng Model Equation s-Continued  DEPENDENT VARIABLE : LADUR  Variable  Lag  Coefficient  Standard error  t statistic  Constant  0 1 1 1  -.0014 .7816 -.0651 .3548  .0019 .0729 .0299 .1536  - .740 10.727 -2.179 2.310  LADUR LASALES REALGNP  ,  R2 = .6788.  R = .6656,  SSR = .013,  SEE = .0133,  DW = 1.899  DEPENDENT VARIABLE : LANDUR  Standard Variable  Lag  Coefficient  error  t statistic  Constant  0 1 1 2 1 2  - .0005 .2060 .0095 .0032 .2226 - .1286  .0012 .0574 .0056 .0011 .0638 .0507  -.456 3.587 1.689 2.931 3.489 -2.536  LADUR LAHOUSE TBILL INDUS PROD NONRES  R2::: .4508,  -A, ::: .4121 ,  SSR = .006 , SEE = .0092,  DW = 2.146  DEPENDENT VARIABLE: LASALES  Variable  Lag  Coefficient  Standard error  t statistic  Constant  0 1 1 2 1  .0315 1.0839 -4.6418 .6855 .3028  .0083 .3018 1.3394 .2781 .1017  3.815 3.591 -3.466 2.465 2.977  LADUR USNONAG NON RES RES  R2::: .2585,  ,  R = .2173 ,  SSR = .1621,  SEE = .0475 ,  DW = 1.92  NOTE : Append'x A de/lnes the variables used tn Appendix C SEE .. Stal'ldard error of estImate SSA .. Sum 01 squared fesiduals OW .. Durbin-Watson stati sti c.  IO ... " .. "" k Rt'vicw -  \bn:h  I ~~ I  "  References Brar, j agjit, P. Pete ChonR. and Ralph W. Lang~ 0989a), "UsinR Lahor ~b rket Dala in Tr.u:k ing a State Economy," Delta Busilless Review I , FallJ\Vimer. 17-25.  - - - . William C G ruben , and Thomas O. Fomby (1984). "Timc-s<;rics ForcC'.!sting Models of the Texas Economy: A Compa.rison,FL'<ieral Reserve Bank of D:llbs EcOllomic Reviell', :\l ay. 11- 23.  ~GS P  Analy. sis: Louisiana Economy lluough a New Lookjng Glas.'i,~ Delta BIiSilless Review 1, FalV Winter, 31-41.  - - , - - . ;md - - (1989b).  Brown, Stephen P.A., a nd John K. Ifill (988). "Lower Oil Pric~s a nd S I :It~ Em ployment ," C0 l1temfJ0 rtlry Policy Issues VI, july,  60--68.  Gruben, WiIli:Ull c., :md Willi:lln T. l ong (l981:1a), ~Thc New Mexico Economy: Outlook for 1989: Fcderal lkscrvt: B;lnk of Dallas t.COIlO lIIlc Review, November, 21-36. - - -, and - -- 0988b). "Fort."C:lSting the TcxlIs Economy: Applic;ttions and Evaluation of a Systematic Multiv:lriate Time-Series Model,- F(.-der.!1 Reserve B:mk of Dallas Eco llo mic Rc!view, january, 11 - 28.  Hoehn , j ames G . and James J Bala:rsy, Jr. (1985), "The Ohio Economy: Using Time-Series Characteristics in FOTl.'CJsting, - Federal Reserve Bank of Clc\'dand Working Paper No. 8508 (Cleveland, December).  t6  l\kNcL'S, Stephen K. (1987). "Consensus Forecasts: Tymnny of the ~'Ia ;ori t y?" Federal Reserye Bank of Boston New England Eco llomic Rel/iew. November/ Decemher. 15-2 1.  Rosenblum, l!:trvey, Stephen Bro wn , Evan Koenig, Keith Phillips, and Mine YikcJ (1990), "Oil Prices ;lI1d the Econom ic O utlook," l:cd cr:ll lks(:rvc Uank of Dallas 17Je SOllthwest Economy, November. Schmidt, Ro nald II (1989), "N:lIural Rc:.:SOllrccs and Regio nal Growth," Federal Reserve Ban k o f San Francisco Ecol1omic Review, FlIll , 3- 19.  Sherwood'<:lll , C:lrolyn (1990), vAsscssing Regio nal Economk Stahil ity: A Portfolio Approach," Feder.!1 Reserve Bank of San Fmncisco Economic Reviell', Wime r. 17- 26. - -- ( 1988). "Explo ring the Rebt ionsbi ps Between National and Regional Economic Fluctuations, " Feder.!1 Reserve B:mk of San EcO ll om ic Review, Summer, 15-25.  Ft.-deral Reserve Bank of Dallas  Kenneth M. Emery Economist Federal Reserve Bank of Datlas  Modeling the Effects of Inflation on the Demand for Money I.·Clll ... l· ,hI.' r . :dcral Ik..l,:rw..... mo~t import:lnl 1'l·~po n ... ih i1it )' I... ('onll'olli ng thl.· \ ~t1 UI.· o f Illonq'. pol iq'l1lakcl"! arlO "CI)' conl.·l.·rnt:d wilh forl.·cl ... ting t he public's dcmand for money. Durinj.: thL· pa~t fiftccn }'L·:lr... however. mtxlding 11lL' tkl11:tlld for money ha ... 1)L'cumc \'cry prohk'll1atic 1'('1':1 numhcr of rl.·a .~(l!lS I'riltlar}, among tiles..: l'e:ISOlh is ,hI.' d)'ct'i intl:i tio n Ii:1.'> Ii:Kl. tx)t h din.'l·tl} and indiret'ilr. on thl' dL'Ill:tnd for money Tlt t .. :llliclc focu:...:.... 011 thL' qUL·..IIOIl of how intlation .. I!ould IX::.I he ir1l'Orr)(U:II..:d into t:mpiric:t! modd .. of the dl.'m:lnd 1'01' mOIlL·Y. To model the dfL"l'b of intblion, 1'I,;'!'>Carclll'J"o h:I\l,: traditionally :t.'NIIllI."(1 [Iial including a nominal interbl r.lte on .. holl-II.:nn bond.. would hc :'UrriI.K:nl .\Ion: ft'1.'I.,tlIl~, Il(I\\I.·\l'r . :-.t:)IllI.' (I.·x·an:ht:r- ( l bIXi. Hendry. :md :'Iarr 11}HH. and ilelll.'! and !\k:hr.l 19$9) ha\'l' Ix:gull 10 diTL't:ll} indudl.· Ihl.· inl1:lIion r.ue- in addilioll to the nomin:tl inll.·ll.,...1 r.IIL' -in their l.·mplrR,:tlmodd:-. \X/hill;' IheN,; :-.llIdiL.... :iuppiy i1l1por1:tnl l.·rnpiril':11 finding~. Ihq' providl;' "1..'1')' linle IhL'ofelil':rl Ju ...llfienion for indudltlj.: th~ inf1:rtion r.HL· ."l·P:Ir.11c1r in m(xlcl~ 0 1 11]oney demand In 1111... :1I1idc. I re, 'iL·\\ t hL· Ir.ldllion;rl 0pp0r1Unit~ {'O.~I :If).,:ument for mdudill~ ~hot1-t~rm intL'I'L'SI r:III.'." in lIlone},-dL'm:rnd IlHxlcis :!nd lhcn prt.:.x·11I li1eorL'licl1 r.llion:lks for : II.~() dilt'a~1' induding thc inllalion l':r1l.· T hi:i d i;>.(.'\I....~i()n is l'ollO\\'L'{1 by :rn L'xamin:ll ioll of how Ihe CllrL'I').,:":I1(.:!.: of intcrt..... t1X::lrinJ.( Illorll'), Illay h:I\'e ~11tl.'r'(:d Iht:: dfL-'Cls of intl:ilion 011 lilt.· d!.:lIIan<i for I\IOllq'. In thl' b.~t p:111 of Ill..: all ide. I ex:ulIinL' \\'hL'IIlL'T inf1:ltion indl..'(xl i.~. or 11:1 .. I)(:t·n. ;1 ... i~nificlill ,kIL'rrllin:tnt of tht: deIHand for Illoney  B  The importance of inflation in explaining money demand  liL's L'conomists h:I\'L' had in mexlelinj.: Ih~ demand for mone}, durin~ Ihe pa:-.t t\\'O dccadc:i, During thl.· 1970.~. high mtbtiorl r.lIc~ lr.m~l:rtcd inlo high nominal iOlL·fL·... I r. lles :Ind. ('onsequl;'nll y. a hig h opp0r1unily Co.,1 of holding moncy. Whl.'n (.:O1llhi ned \\'il h kg:!1 impt:tiim..:nts 10 thL' payment of inle re~t on monL')'. this high opporlunity l'O.~1 induced finand:11 innm'a tions thaI :I1IO\\'L,d firrll.~ I() m:rn:lg<.' 1l(JIlintl.·rL·s'-I)I.'~lring rnonq' m()1'1.' d()~dy I In p:lrt l)(:cau:-.e 01 tbe~L' innov:Hio lb. ~Iandard moncy-tlL'ma nd models I X'g~tn to ()\'l'Tpnxlicl Ihe amount o f mone}' b:ll:tncl.·s Ille public desiTl.'d to hold In till.' I~s, hO\\,t·\·t:r. IIK'se lIIodding I;:rror- Wl·(I.· (I.·'"crscd wben tr.lditional model:i hl;:~:m 10 umIL'rpredicl thL' :lInounl of money ha];tn('L·... Ihe p"hli(' desired [0 hold . .tll 1'I!/oCJ~),. thl.' mtlo of Wos.... n:lIional pnxllll't (GNP) to the ,\II money "'Io(:k, hegan to f:tlt. tlil!'" turning from the upward lrend it had displayed throllgh011\ the po~lw:l r pl.'rioG (Fi}{urt.' I ). Two h}]X11IlL':-.e:-. l.·tI\crgcd to L'xpl:tin Ihis more rl;'('L'nt phL·llolllcnon. The fir:-I hyp()the:ii.~ maintained Ihal Ihe Inm)\':ttions thaI IX'j.::m in the 1970.... :md ('onlinlll.·d \\ illl Ihe inlroduct ion of nc~()tiabie ()rdl'r~ (II' withdr.twa] (NOW) :1l'c()lInt:i (i nd uded in ,\ ] I J. ;t IOIl~ wilh t he simllltam:()us phascout of inl efl's/·r;t lr.: {'dling rq.:lIl:uioIlS, !t:d to ;tn inCfe;lSL: in thl.' (IL'rn:lrld for 1\'11 money h:tbnccs  I WIsh ro thank VI MIChael ColI. Evan F /{oerng and Joseph N Ha slaglothelpiuleotrmenlS A/letrOts. however. 8re my  ~"  _arO'l$ IIIC/uded f!e'N COfpcxate caslr managerCC/lfllQIJCS such 8S repurchase agreements oerte.-  rhese ment  ..tormall()'l systems and f!l!.t/II ms/lumen/s SUCIl as lock ~es  1nl1.I\iorl h.l:-. hL·I.·n an illl1x,rt:ull lactor nllltril)lliing Ix)th dirL'('liy :llld indifL'clly to ditTinll-  coo/rol dlSlXltsemefl/ and payable thtough drafts  SeeHcslet ( 1ge1lOt POIret, $Impson and Mavsk.opi(l 919) lot a d,scUSSJ(ln aI /heS(! and O/het .nnovaIO'lS  17  Figure 1 Levels of M1 Velocity  ", •  ,  (Cox and Rosenblum 1989). The second hypothesis stated that falli ng inflation rates in the ea rly 1980s increased the demand fo r money, leading to a fa ll in MI velocity (Gavin and Dewald 1989, Rasche 1989). Both hypotheses assign infla tion a major C'dusal role in money-demand behavior during the past two decades.  Modeling the opportunity cost of holding money In the empirical literature on the demand for money, a short-term nominal interest idte, R, has commonly served as a proxy for the opportunity cost of holding money. : Because money has not traditio nally ea rned inte rcst. the real return o n money has been cast as the negative of the inOa-  , Recent e)(cspllOO$ mclvde Gokifeld and Sichel (981). 8aba. Hendry. and SIIJ" (1988). and Het~eI and Mehra (1989) &lverat studieS have 10000 that inflal/Ofl. In adell/I()f)  to a nommal interest rate. IS a sign/lteant determinant of fi"OQ"Iey demand durlflg pe:r1Ods 01 hypennf/a/1On These sIuCIeSIflCVdeCagan( 1958). FltJt!ktJI(I971). andHartJerger (1963) • The IdenbtyA •  I .. 1\  rs known as /he Frshef eqvatlOfl  Ex  ante. infl8tlOl1lS rep/a(;ed IJy exp«ted inIIatlOfl BehaVlOfally. /tte Idea IS thai /efIder$ will set the Iendong rare. R WIth /he fft/JlIZallOfll1llJllflfltJllOfI erodes /he f)<JfCfla5Jf)fJ power 01 money /flal is I~ Therel()(e. II lICluallllflatlOt'r equals expected inf/arJOfl. the ~ eams a raal rate 01 return r  .8  tion rate. The real return on honds, on the other hand. equals the nominal return on bonds minus inflation (r - R - It). The refore. the opportunity cost of holding money is R-equal to r + n-thc difference betwcen the real return on bonds and the rea l return on mo ney.J Infl ation is clearly onc comJXlnent of the opportunity COSt of holding money. Inflation diminishes the purchasing JXlwcr of money. Therefore. when inflation in<.-reases, the demand for Illoney falls. O n the basis of this simple analysis, one might think that empirical models using a shorttem) nomi nal interest rate to capture the opportunity costs of holding money due to infla tion would be adequate. However, there are reasons to suspect that models that incorporate only a short-tenn nominal interest rate may fail to capture the full cffects of inflation on the demand for money. The inflalion rate as a direct, significant determinant of the demand for money Alternatives to holding money_ One way inflation may din::ctly cnter empirical models of money demand concerns precisely the issue of money substitutes and opJXlnunity cost. By including only a short-tern) inte rest rdte in money-demand models, the implicit assumption is that the only alternative to holding money is to hold short-teml honds. Several economists (Caga n 1956, Friedman 1956, Frenkel 1977) have JXlintcd out that during pt.·riods of vel)' higb inflation rates, asseL'i other than short-tenn bond,; may scrvc as substitutes for money. Considcr individua ls' behavior toward real goods and services during periods of high inflation. As inflmion rises and becomes particularly t:.Lxing. may acceler::l1e their purchases of real goods :.L nd services rather than hold money, o r they may choose to store their wealth in physical assets, such as land or gold. The idea is that these physical asSClS are immune to the devaluing effects o f inflation, whereas noninterestbearing money i.s not. Even during periods o f moderate inflat ion. such as thc 1960s and 1970s, assets other than s hon-tcnn bonds may have served 3S substitutes for money holdings. If asselS other than short-term bonds serve as substitutes for money, the implicatio n for empirical models o f  Federat Reserve Bank of Dallas  nlonl:Y d~m:tnd is that t h~ nominal r;.l(I:S of H:turn on tll\..'.'>C ()dl~r as.~ets should he indu<k'd in thl' modd. along with [h~ nominal return on shorttl'nn honlb.' And, ;I.~ Fril'{lman ( 19'>6) pointl'd out. if L"~r1ain goods chac yidd chei r return in kind scrve as Mlhsticut~s for mont:y holdings, th!.:n th~ nomin;ll r~[Urn on cheSL' physiGd g(xKb-in chis (';.lSC tIll' innation r.Ltl'should Ix: induded as ;1 det ~rminant of money dl.:'lll:lnd ,..elxlr.lIdy from the nominal interl'st r.lIL' on IXlOds. AmJtILL'r illustr.lti(m ((m('erns l(lO~ -l ~n n l)(lOd.. SUPI)( )......... that I)()tll ...hoI1- :md I()n~-tenn I)(mds ;lrc sllh~titlltes for money holdings ;Lnd that inflation incrcasl·s. If a given llloney-{km:md l1l(xiel ~x­ du(ks the mte of return on lonK-term bonds. the m( x ld may tt il to det~L"t the substitution of money inlo lo ng-tl:l111 honds (';I\lsl:d hy the higher infl:ltion er(x ling the value of money. In this case, the r.lte of rctum on shon-tenn l)()n(is will fail to Clpture tIll: full opronunity ('ost of holdinK money. and int1:tlion may have :m independent effL'{'t .. Many L"(·onomi:-.b would :LrAlle th:lt even if phr:--.i(:l l or othcr as.~ets an: l-ouh '>titutes for moncy. va riation.~ in nomin;ll int~rest," o n shon-term IXlIlds brgd)' reflL·t:t vari;lIions in inflalion ;md long-tl'rm IXlOd r.lh::S so that induding proxiL'S for the:-.c tcrm:--. would hL' fL"(lun d ant \Vhik it is [me th;lI inflation and nomin:l l interest r.lIes l el1(J IO 1ll()\'~ t0t-:e(h~r CFigll1't: 2). the ('{)rrebtion is Ell' from pcrfL'Cl. Thcr(;.{ore. \lsing IhL' only nominal r.lIe of return on shon-term honds to measuf(;.· lht' opronllnity ('()....( of holding money dl11.: to inflation may not hc sufficient Money-demand adjustment behavior, Another explan:ltion for why inflalion llla y din.:ctly t'ntL'r empi rical1llodels of money (!L'l11a nd concerns the L"ostlint'ss of :H.ljllsting cash hal:mcl's, A class of thcoretical m(xlds known as (111'('11/01'), modf.>!" of 1II01l~J' demaud suggests thaI. in tht: shon run. individuals 1ll;IY not fully L'Ol'sid~r the effeL"fs o f inflation In lliL'Se models, ad justing clsh balanL"cs involvc" L"cn;lin fixC(1 co . . t . . SUL"h :lS [r,mspolt:.!tion costs. information (.:osts, and tr.lns:lction ('o... ts: cons..'qllcntly. individlmb estah lish uppcr and lower (;Irget l)(llll1ds for thdr nominal h:l bnct's and adju:-.t thl'ir :K'11I;t1 holdings only when thL' bounds arc viol:IIL"<.1. '111e,'>(;: IX)lmds can lx.' thought of as lX'int-: M:t in the short 11m, ,'i() th:lt Economlc Review _ March 199 1  Figure 2  Three-Month Treasury Bill Rate and Growth in the Consumer Price Index Treasury bill (p&rcent)  r "  " "  "  individuals arc dema nding nominal bahmces and passively allowing inn;ttion to erodc the value of their hal:mL"~s in the shon run, In the longer run, however, individll:t b adjust their targel ho unds 10 rt'fle(.·1 tht: co.~t of innation and (){her del enninants of the dem;l nd for mon~ y 1lle impoltant point IO nolC here is that if Ihe inventory-type hehavior is prescnt, then individuab' demand for money in the shon run is  • ThIs result can be seen by using me approach K1 whICh moneylS allowed 10 en/ef a repteS6f1tativc IndiVIdual's utility funcllOl1 (see POflerba 6nd Rorcmoerg r987) If the onty arguments of /he indlvldual's ullllly func/1OI1 6,e money and consumptlOfl. rIlen //le mtI'glnel lale of subsr./ulion be!Ween money and consumptlOfl WIll equal rile nomInal rate of return on a benchm6rk asset rhet serves as a store 01 value and does noI6flter th6 ur.llly funcrl(J(l In //l,s case. the demand for money is a /(In(;tion 01 consumptlOf'l and the flCll7l<nal r6tcof return on the benctmarlr asset However." there IS an alternatIve svt>slllure fat moocy besides con, SumpllOl1 th8tlS also en ergument oflhe /IldivIduaJ's utili/y tvocllOl1, /hen ~ dtlmand funcbonS have as thetr 8Igu· f1ICf1lS IIOl only con5umpllOl1 6fld the rate 01 rerum on the  /.>enCIVJJarlr asset. bul alS() /lie rare 01 relum on the a/lema/We subsllMe for money ~  dlscvsseo on fOOlOOIe 4. lonQ-tent1 bonds would now be the benchmark 115ser and shotI-lerms bonds would dlfflCt/y enter the uldsty fUflCbOn  In rCfnl$ 01 the ul/ll/y frtJfl'tC'Nt7k  DeC9L1S6 they PflJVIdo 1IqtNd"y servrces  '9  Figure 3  Transactions Balances BiIboos 01 dOIlaNi  ·.......""'"'"•  ~ MIIMC DIpoIil Ac:c:cura ~ ~ Mo.aIIII F.....  • OIW' 0 * * - DI!XIIb  .. NOTE: Transactions balances are M2less savings and small iln18 dEtPQs,rs.  not purdy :1 dt..'I11:II,d for re:l1 bal:mo,..s " And, :IS tht.' Appendix :-ho \\"s, if individu:lis bil 10 :HTOUIli fm tht.., fulleO't..'("( o f inl1mion on Iht.' dt.,tn:lI1d for lIlurK'}' in tht.., :-.l1on 11111 (that is, if do not exhihit pllrel)' :1 ( klll:md for re:l1 1110nt.'Y h:d:lI1ce., l, lllt.'n the infl alion r:lI e \\ill be:l ...ep:rratt.' :md :-.r~n i fk:.tnl detenn in:rlll in empiri c:d m()(kt... o f the dt.'mand for mo ney.  The impaci of inflation in a deregulaled financial environmenl The IWills bro ught a prolifl:r.llion of rnoneylike ass\.:ls sllch :l.~ NOW accounts that, unlike  Another  'cason IndlVld ua!s may be concerned wIth f)()(TII'  nal. 'ather than ,eal money balances IS /hal ban/< fee schedvles /lfe based on f)()(TIIna! accOUtlt balances  The 8PfXCIP',aIO fICIffllI!al talC 01 rcrvrn  on tn(ltI(.'y '5 USIJ8IIy  COflSfflJClcd as a we<ghted meaSLWe oIlheddfefem nomtnal re/ums pard on the IfIdIvrdual COfT¥)(JIlf1il/S 01 me monetary Bggfeg;lle UIldef consldera/1OtI  rhos ass..mes /hal changes If! III/iatlOfl do flO! af/ocl the rcal rateS 01 rtHUm en varIOUS assets dlfferenlly fhal IS. a  '·percent cllaf"98lf1/he 1fI/ia/1OtI rate fCSvl/s III a r ,percenr c/laflfJ6lf1l11 f/OtTIII1a/ ralllS 01 relUm  zo  t."lr rrl'nq and demand (kposib. t';l rn a nominal 1:ltt.· o f rt:tu m and ...till pro\'ide t '~l n,.rcti()n :-.crvices Fi~ lII"t..' j pre:-.cllls [he compo... ition o f till.: ;\12 aRi!lq.:ate, \\ h id l d t':lrly :.ho\\"... thai the intt..'rt..·:-tIX':l ring (·ompont..' nt o f ,\12 h:l:-. hl'l"olUe \'t.'I)' :-uhslalllial . \'\ 'hal dOt.'... the int« )(lul"tlon and proliter.ltion 0 1 Ihe:-t.· a...:-t.'t:-. Imply for in natlon ':- dl"t.'"(.'t on the demand for monl;'Y! To ;rnS\\l'r this qUl;'stion, mos[ t.'l"OnOI11l ... t!> I,.,\"c,.' 1ll(){lifit.-d tht: rdl.'\";rnl nominal i ntt.'re... t r.lIt.' II1dlldl;'d in the l.'lllprri(:al Ill()(kl :-on (hal it b now tho.: diffc renct.' I)o.!t\\ cen Ihe aprropri;lle nomi n:d rl;'turn on mo nt: y :rnd Iht' nOlllin;r! n:lllrn Oil :. shor1 -1I.:I"I)) ho ndo Thi." difference rqm..'sents I hI.' oppo rtllnity cost of holding mOlley if holdi ng a short -It..·lm bond is Ihe aitl;'rnativc to holdill~ money W hat if ;lssctS other lh:rl) shol1 -t..:rm bonds :1I"t.' serving as sllhstilutes to holding Ill()ney~ T o thl." l."xtent th:lI (:h:..nges in inllatio n art.' rdlet.kd in thl." nominal relllnl!> o n both mont..'}' and ass,,:ls tlr:.t :-t.· ....·e a .~ :-ouh... tillrt e.~ for mo ney. <:hang..:s in i nll:rtio n sho uld nOI afft..'Ct thc n:I:lli\'t.· rt.·:.1 rt..·turns lX'tween monev and its ...uh..slitult.·:-o [nlbtion. tht.'fd'on:. sho uld not afft..-'CI tht.· dCI11:.rnd for lllo nt.'Y regardle ......... o f whether o r nOl the nl()(k-l indutle:-. tht.., ".rtt..'S o f return of all :rppropriat..: mo ney substi tutes ~ 111C impliGuions ()f fin:.Jn ciai dl:rt..·gul:nion for the in\'c nlol)'-t)'Pc behavior o f l11ont..'}' ckmand :1ft..' also illlponalll !\gain, in completely derq.(lIlalt..'d finandal markets. the nominal returns on both 11101lt.·y and honds fully n.:nel"t :.. l"han~t..· in the intbtion r.lIe , and the ch:mgl;.' ([OI;.'S not alter R·btin:' rl;.';rl rt.:IUfIls between monl;.'y and honds Basically. i"n:lIion d ocs not "ffl,;'ct ;rdjustment hdl;rvior hec<luse innation d(X's not altl;.'r TI..'l:rtivt..' re:rl returns hl..'twl;.'l..'n mon..:y and bonds So. t:rrg..:! hounds arl." set in Ihe invcl1tolY lllodcl.~ ;IS usual. but ch:lI1ges in inflation no longcr requirt..· an :ldjuStIHl'nt in either nominal bal:rnct..'S or Ihl,;' target hounds bcc:..u:.e tht.., "III,;' of rl."turn pai<.l on the llomiTl;l1 h:.l;mce!> will comllt:matl,;' for the changl." in infbtion (:I:' delllon .~tr.I1t.-d in Ihl;' Appendixl, 1I0wl;'vcr, to Ihe extent th:.11 inflation en)(le:-. the v;llut.' o f the Cllnr.?llC), component of Illont')'. the in flmion r:rtt..' rn;.y still be:t ~i~nifiGlnt ne~;lIi ... e dt.'lennin;mt o f the dl'rn:.rnd fo r money. In sUl1ullary. sho n -tenn nornin:..1 intcrt'sl r.rtl..'S on hond s m ar fail 10 fully capture thl;' t'fft..-'CL'i Foo.,nal R"""n'e BaRk of Dallas  of inlbtiun on till.' d . ... I11;md lor 11101l ...:}' :l11d may tllu.... 1,.·( llll1il,.·t \\itll til ..... \ iI,.'\\ ()f tr.ldili(lIlallIHI11I.'Ylkl11,md . . . tlldi ...·.... TIll' r...·;t-.(ub fOI Ihi." l':1ilul'l.' indud ...• 1111..' ol11i.... sion 01 r.tlo..· . . of n:turn on a,·;,,:I .. (oth...·r IIl:tn .... hOI1 -1...'rm hO!l(t....) Ihat 1Il:1} ....1...1'\..1... as Mlh~tlt\ll ...•.... lilr mlml'Y 1Hlltlin).::. alld thl'  pl"l..·. . I..·1\Cl·  of Ilxl.."{1 \,."IN .... in .ldlll . . lillJ-t cl ....h habnn· ..... Om.: \\ (lu ld Ilunk. :t pno!'l. I h:1l thl' in;lhdit~· 01 a nomi n;11 r:1\ .... of n:lurn Ol) .... !loll-lI,.·nH huntt.... 10 Gtplllr...· l ull} th ...· df...·I,.·h of inlblioll i .... mo.. . t likdy to h.t\l·II(.·I,.·wTI.."{1 dll1'in).: 11K' 19..0 ..... \\Ill'n high inl1;1lion 1~1I ...·:- 111ad...· :h:-...·l..... n1iK'r Ih:Hl bonds likdy :-ul).. . tit1.I1 ...·.... lllr t1llll1l'Y In Ihl.' 1):I:.t d l'cld ..... 1H)\\ ",·\·",·r. Ih ...· l·m ...·q.\...·I1l'1.' of inll'l'l....... I-lx·:lr;n,l.( nlOl1..:} :111(1111"" r...·l;! li\l·ll)\\ Inll:tlilltl. \\llidllll:ld ...· 111:lny  k'... :. a!lr;Kli\l' nUlI""'Y Mlil.. .lillll..:...... Sll,l.(,I.(..:sl th:11 Ih",· ...·11;.:1.."[:- of intl:tlion on IlHlIlo.,.·} d""I11:lI1d  :I:-:-l'I ....  lIlay h:t\l' Ill't'um ...· !L· . . s Importanl during th ...· 19XOs th:tn for Ilw 1........ 1 01 th ...· P0:-I\\:lr p ...·riod Th ...· an;tly . . . I..... tlll·r..:ftll ...... lu1'l1 .... tll:lll ...·m]1;l'i ...·al l';';;llllill:I' !Ion of 1111 .... 1......... \11.'  Some cmpi.rical results In t hl .... :'l.'t·lion . I ...·":l1l1inl· \\ hl·lh...·1' 11ldmling Ihl..· 1Il11u;on ...·. in additIon to :t j)ol1llllal inllT...·:.1 r.lll'. add:. l':-..plan:llory po\\ .... r to mOIl ...·~-d ...·1l1:tnd IUIKId,..... TIK' l'llljllrtt;11 \\01'1.: nm ... i ...h of ...·...lim;lling mOlll'y-dl'Ill,lnd r...·grl·,.... io!l. . . of tilt: fonn  \\ I1l·t....' Cb:l ...·011 . . 1:1111. III I .~ lilt: I'v:11 mon.... y .~IOl'k. is 1'L':tl (,,\,1'. f( i . . lilt: IIl1'l'l"IllOlllh Trl..':I:-ury hill r:1l",'. IOf i.. . Ill ...· O\\1l I~tll' (If t'l'llInl 011 IllOIlL'y. Jt is Illl' inll.llillil 1"1,,,' (lll'sl dilli.·t'",·nCt· III' 111<': l()~ (II IhL' priel,.· k·\ l·ll. and IJ I . . an t'rror Il'fIll Th..: dala :11-",' quant·dr. ;Ind tilt: 0\\ 11 r:111..· of I'l'llIrn on 11l()11L'~· i:. ITlllll tilt: Ik,;lld I,f (;11\ l·I·I\I,I':. (If III",' F.... tkr:~1 Ik........ rh· !'>\:.ll·1ll Allo\II ...·r <.1:11:1 af.... fTlltll Ciliha:.",·. \ltlll\,,'\ ·tkluand Illt Kk·l . . l':-I illl:II ..."{1 \\ lth  y  <tU:trll' r1~ d,II.1 Iml-.\ iIKorpor:II ...· thl' app;lr...·lll  b)ZI.!I..'d n· . . potl ....l' III' th ...· d ...· lill" mOll..:} to ... h;I!l~"""" III tlw lll-ll·l·lllin.ltlh "f th ...· d ...·Ill;tnd for Ill()nl..·~ In tlK" P;1-.1. 1110:.1 mOll ...·) -til'm:md mlxkb I:con o miC Rt" 'icw- ,\ I arc h 199 1  :Kcompli.. . h\",d Illi:. hy 1I .~ing r..:gr ....:.slotl... of Iltl..· litrln dl·."lTlbl"{1 hy L'quation A" in Ilil' Appendi;.;. in \\ hicll onlr tlK" (!L-p\:mk'nt \·;tr;:lhk 1..·!l1l·fS ;tS :t bAAl'd \.';.;p1:tn;lIory \·ar;:II1I..:. Ikn'nll)" hO\\·e\·(·r. 11ll' rl.';l·t;\'I.· n;lIlIn.: of Ihi.... "'"{Iu:llion. in Il.'rms of Ihe bAAI..'<.l re . . . I>0n........•. . :Illo\\(·d. h:t~ come umkr ('filid~Ill :' In r..::.porl~l·. mOT": g..:n":~~11 modds..~uch :I~ ""qu:lI;on J. 11;1\''': h...'I.'Ollll· pn..·\·;tk'nI h ....'(~llISI..· th ..:y all .. l\\ :t mot'...• 11I..-;.;ihk rc . . . IXltlSl' pallt;'m 10 :Iri .......· from dl:mg...·:. in Ih .... d..:t .... nnin:ltlh of mon ...·)' d ...·ll1;lnd ,.,  til\.'  Ikenl .. . ",· Ill..: .lbm·1.' :1I1:tly:.b .~lIAA""'~t..... Ihal of i nll:tt ion Illay h ..:nlllie ks ... ;mIX)rtanl  drl.."{·\.~  a:- mon..:} bl..·u)I11I.'.... mlWl' int":I'\"'.~I-lx·arillg. 1ll0n ...'Yd ...·mand 1l10{kl.~ :11'<..' ..::-lim:III.."{1 ti)!' I Ill' :lggrL'g:tll.'. . . il.I IA. 1\'11. ;Ind 1\12 T:thk I (ks(Tilll's Ill .......",· :lggl''':' g:ttl'S As Ihl' ;lggt'I.:).::Il ...·s Ix,com .... hI'O;Kkr. m()ving from 1\1 lA 10 1\12. a blgl.'r proportion of I hI.' aggr .... gall' i.. . int..:l'l·... t·h....aring Addilionally. lilt· :,:ullpk pl'l'i(xl umkr ...·on .... kkralion. ll)'ij-W), is tli\'Kkd inlo 1\\0 :.uilpnilxls. Tlli .... ....I .... p i... donI.' for 1\\0 "l'a"'JIl~ I'ir~t. di;lgIlO:.lil· :.1;lIbtit.·s. sucll :IS 11.::.1 .... for . . t:thilily of tltl.' 1.."{lll:llion .... · (,·I ICIl"il·i .... nt:.. uldic;lIl' Ih:1I :I ~lIlglo: t1l1Kkl for th..: ...·ntir.... s:tnlpk perilKI is nol :Ippfopnatl.: for 1\1 IA . MI. or il.12 " Scnllld. hl't.~tll:''''· Illl' r.lngl.' of inll·rl':-.I-Ix:aring :t:':-l'b h":gall to I..·"p:tnd gre:tlly in 19HO. IWII inll..·1'l· ....lin}.t <]u...•...lion .... :lrl' \\'1ll'IIlL'f Ih..: dkt.·I:. of inll;tlilJ!l diff...·r :I('R)~:' IllIJllt'l:tl)' :lJ.Q.:TI..·g:ttl·'" :tnd \\ 1I1..·,ItI..·r thl'}" d ill".... r :to'O.....:. lil11": ]'x:rilxt:.. Til .... rl·grl.' ....Mlln:- :tl'l' :.rl(.:dlkd In hoth log-I..:\·..:! :lnd fil,:,Ol-dilr...·I'l·IK..: r(Jrlll lx·ctu . . ..: Ill' spuriml:' l'orr..... I:Ilion.... Ihal m;IY ;lrisl..· \\ 11":11 \ ':Iri:thks :Ir..: slrongly  . For onstance Ihe cqmlllon reQuires thai real money oal. /lnces adJUst /0 cllangcs  In  caell 01 tile money· demand  (l()1()fmmllnlS ....111 rIle same gcomcmc lag  Til,S /rcndClOOS nollfTlPfy tMr models of the IOfm of CQual/fXl 1 overcome 0I118f orOO/Cms such  as Idcrm/;ca r!()(l IssueS.  IIlIle/enl III eS/1fTI1l11fl!) moncy-dcmand equal!()(lS See  Roley (1965) lor a C1tSCUSSIOfl 01 some oIlhesc ptoblems ACkUlOIlIJ1/y IfItemalellwoacheslocquatOOfl 1 exlS/. such  as error COf/CC/1QIl models ac/vocalcd I:1y Henaty (1919) TheSe IfICIuOO Chow ICSlS antJ 8f0Wl'l. Or.Kbtn and £\I3fl S CUSUMSO leSI s181,SJICS  lor  paramel()f SJilb<h1y TeslS lot  senaicorrt!lallQll. heleroscedaSJlCl1y and ARCH reSIduals WIJPO(IOO /fle lmal  model SPOClllCiltlOflS  "  Table 1  Components and Definttions of Money Bank reserves Currency' M1A  Travelers checks 01 nonbank issuers  Ml  Demand deposits2 Other checkable deposits  (CX:;Ds)~  M2  Money market deposit accounts (MMDAs) Money market mutual fund (MMMF) balances' Savings and small-<lenomination time deposits' Overnight repurchase agreemenls and overnight Eurodollars'  , Currerocy 0UISida the Treasuty , Fedlfal AHeM! Ba.nks, and the vaulls of depository IfIStrtutions.  • Oemand deposrts at aI corrvneIdal batiks othef than those due!(l depository insbtul.ons. the U.S. government, and fOfelOn banks and otfioaIln$litu!ions less cash itt<'nS N'1 the process ot coIectIon and Federal F\eserIte lbat. > Consist 01 n&gobable order ot Wlthdtawal (NOW) and aUIOma\1e lI'anster servlc:e (ATS) accounts at depository inslltutoons, credit U!'IIOI'1 share dra" accounts, and demand depoSits at Ihrifl lnstilutions.  • Time deposits, including retail 'epl.ln::hase agr~nts tRPs).  N'1  amounts less Itlan 5100,000.  • 0vern0Qht (and c:ontinulIIg conlr8Ct) repurchase agreements ISsued by a. oomtTl8fcial banks and overnight  Eur~ IuufId 10  U .S. rvsderIts by foreign bfanchvs of U.S. banks WOfIdwida.  NOTE: M2 excludes individual retirement accounts (IRAs) and Keogh balances held at deposOOry nstitubons and money market funds and aI balances held by money mal1tet funds (e~cepl insbtullOfl'OI'I/y 1utIds), U.S and foreign c:ommet'cral bilrIq, and the U.S. and foreign gove«menlS.  "  tn.:nded I! The diagnostic:; indicatt:d that suitahle MIA and M I m(xI~1:; wuld be specified by hre:Lking the s:.11llple period:u 1979:.3 for both Ihe k'\'d and first -d i ff~rence :.rx-cifications Ii For M2. par..uneter stahility t"ould not he obtained withOlJl dr()ppin~ the 19,3-,H pcri(KI Once those years wen.: dropJX."'<I. howen:r. the test statistics indi<:~Ih..--d weil-beh:l\"Cd Illodeb for the 1959: 1- 1979:.3 :lnd the 1979:4- 19H9:4 period:. I' One Ia:;t issue I:; the :Lppropriate lag icn!-,oth to lL.~e for the right-h:md-.;;ide va riables in C<.juation L After some l;:xperirnent;lIion. [ followed Goklfdd and Siebel (19H7) and lietzel and Mdml ( 1989) hy u~ing fo ur lags o f each v:lri:lble. 11 A:; Goldfekl and Sichel (1987) point OUL equation I C:1n be u:;ed to di:'lingu ish lx-'\ween ShOl1- and long·run ellens of inll:llion on money tk-rn:lnd. Testing d! - 0 for any j::iven i amounts to testing the hypothesis th:lt realllloney balances adjust without :1 I:Ig to ch'lnges in infl ation, or in other words, tll:!t the!\: an.: no shon-run effe«s of inflation on the dell\and for money. I" A second hypothesis is that infl'ltion m:.y have a short-nm. but not a long-nm, efft."t.l on n.:al halano..""S . In teon" of I;.'qu.ltion I. this hypothesis is  It.'nt with the hypothe:.i .~ that inflation effects are import:lnt for money dem:lOd and even more imporlant fo r those m o n~tary aggreg-.ltes th:ll have sm;lll interest-bc:Lring componenlS. The analysiS :llxwc :LIso :.uggested that the (:"mergence of intcresl-1X::Lring money should diminish the effect o f infl:Llion on the demand for  OZ  Thls finding occurs when the '8Dres$(Xs are not slatoona/)' OIfferenclf/(J the vsnalJles usually e/lffIII'lat6S any nonsla-  llOfIllfiry III tll6 dala In /116 analysis herc. estllllal!Ofl and dIagnostic tcsrs are done lor oeth rile level lind first .. d,l/erCflCo Spccmcaroons ThIS IS done as a lest 01 rObust.. ness of t/lolcsulrslor lt1ee/lllCtsol,nflallOfllfimoney·demand myresslOlls IJ DlagnosllC SlatlstlCs wcrcr;cneralcdwhcri 1/10 whole sample  was IJsed in the eSllmation and lor varIOUs subsampleS Th6se slallSIICS tndicated that a well-t)chaved model could  be spcciflCd /or Ih8 1.953. 1 1979 3 period and lor the 1979.4 1989 4 perJOCi ArlemtJlmfJ 10 lengthen the sample periods /or Clthcr rrodeI resutlOO If! pal8I1I81er Ins/abillry. as IIldlCSrcd by the CUSUMSO tests AddillOf)al/y. /or all tile IIggregare!l. thetJotnoQcnelryofrne demand for tnOne)' with respf1CllO the pnce level. cmbcddcd In the level spect(/C81lCn$. was tcsted BOd IICceplcd  .. With M2. hOwever. Itle SlatistlCS onchcated /lnll a stable rrodeI could t:le SDecilled beyond the 1979 3 bleak U$JIlQ etth8t the IlIs/-{;ilffercr1C8 Of Jellfl/ spccificatoon Ht;mever.  Tahles 2 :md 3 present the Muns of the distrihuted \:L~ cocm("ielll.~ ;lnd the I statistics for Ihe test that the Slun of the d;s ~qu;ll zero, llsing Ihe log-level :md fiN-diffl;"rl;"nce specificnions 1Both the first-differt.' lKt: ;lnd log· level specifica tions yield the s'l1nl;.' (ondusions. First , the inflation rate cntcrs with a neg:lIivl' sWtistically significant sign for MIA :Ind MI during the 1953-79 period. l~ The coefficient on tht: intlation term Is more negntivc than tlwt on thl! interest-rate term and has a larger I st;tlistic In tenns of explanatory power. for both MIA and M I, including the inflation r.L1C improvcs the explan:nory power of the first-dilTcrence model hy 35 to 40 perc~nt. ''/ For M2. innation imposes no statistically signifi .. canl direct shon - or I()n~ .. rlln effects on the dem;md for mone)'. '111C intcrest .. rate effects, ho,,"c\'er, are important. The resullS indiC'.ltc that the inflation rate should he dif't."Ctly includl;.-d in MIA and M1 monc}'-dcm:ltld models for the 1953--79 period. Thl.!rcforc, the resullS are consisEcon o mic Rcvlt.-w- M an:h 199 1  parameter stlllJi/!ly could not be oolalfl8d for !he efJt!re 1959-89 period CholeiltO 8S/lI1I8tC a different ~  me  afrer 1979 3 was made on the baSIS aI the c/1ange in oporatmg ploclldures by /116 Federal Reserve at //la /lime and because stablliry could not be oblSmed unll/ 1982. the end of the period lor the parhculllr operallng ptoccdures " lags lon9er than lour were sta/lstlcally insl{Jnificanr and did  not add explanatory power 10 thc rQf}resslons Of  For th61lfst-dd'erence speclflca/lOIl. tile hypothesis IS /hal the first difference of tnlllllion does not a/leel !he first d,/lerence  01 '681 balances  " If thel statlst,c is greater Itlan 2. then the sumo( coeffic/8llts 1$ dccmcd 10 b4! slatlstlcally SlgrullCant Ihis les/IS for the less restrlCll" hypo/tlcsls tna/lnflatoon does have Iong-rvn effllCts on Ih6 dem8na fOf mot'Iey  .. Very lew cNfcrences 8fJ(J881 In the fes..Dts between MI and MIA 101 the 19S3-79f)11nOd becaus801tlC1 checkable dePOSits IS a very smaR component through 1979 Of  11lB adJUSled Ws Ifl(;rCIISC 10 0 59 and 0 56 from 0 43 and 040 /or MIA and MI. respectMJiy  "  Table 2  First-Difference Specification of Money-Demand Regression MIA  ra ro.  lb,  rd,  1953:1- 1979:3  1979:4-19894  .928 .093 - .0057 -. 021  1.05 -. 130 - ,001 - .075  (7.86) (1.53) (2.85) (3.50)  R'  (5.00) (0.63) (0.14) (2.00) .7.  .59  Ml  1953:1- 1979:3  ra,  .902 .095 -.004 - .022  lb, I. c,  rd,  (7.27) (1 .53) (1.61) (3.67)  R'  1979:4- 1989:4 .518 .360 -.013 - .003  (2.41) (1.30) (1.94)  (0,10) .70  .56  M2  1959:1-1979:3  ra, ro.  .02\)  1.23 - .058 - 034  lb.  rd,  (0. 10) (2.03) (2.42) (0.69)  Fi '  1979:4-1989:4 .389  (1.30)  .450  (1.40) (0 .78) (2.00)  - .007 - .035  18  56  NOTE: t stallSIICS we in parentheses  1l10l1l'V T hi:-. I~ till' l·:I.~C lX'C llI:-'C. t() thl' L'x tl:nt that  1)llil11 o.: ..l illl:\I,,:"I>ftllo.: lnlbl;()lll·lkl·t.... rail in till'  thl> p:1I1il"ubr lllunl·t;lry : 1~).:rq~: ltl· i,.. intL'i"l""I-  lir~l-di lrL'rl:l1lL' ~pLTilk' lt ion hu t il1nl"; I~L' III till" II J,I.!- k\ d ~pl"l'lnl': !I;<)I1 h)f 1ho.: ,\ 11 . \ ~IX·l·ilk:l1i()l1.  hL'; lrin~ . l" h;lngL'~ 111  ;ntl;niul1 \\ ilJ III >t ;lffL-cl tht:  op pnrtl1ni[~ lO:-.1 oj' ho\tllll).: 111()IW~  1l1lkL'lL II1\.'  L'ltlp lr ictll'l"~lI h ~ IllllicltL' tl1:l 1 till' dlrcll  dkcb of  11l1l;ilion. :L~ 11ll':I"lIrl'd h~ till: l()l:ffil'il' nh on tilL' inll;l l!on ! enll~. 'I!'L' no lon).:l:1' .... t:Ll i .... t; ctlly ,..;).:nifi CUll for :\ 11 in  till' l 'rlJ-l-.'<) rx.:rind Th.: long run  lh l' in!bli()11 uldl'ICll'nh ;lI'L' Illl\\ ()11 1 ~ l1l:trgin:tll~ ,ignificln1. .dl!tOllgli 11ll' point l' .. til11:lll·'" l1;1n: imrl':I,.. ed Tltl' inlll1ion l·( ...·f!llll·nh for Ih\: ,\ 12 ~lX·t' i nG l1 ion .... ,II'\' no\\' I1I;Ir!-(in;dl~ .. ignitk:tlli.  \\!tik'lho.: 1)()ll1ll'~tlllt:lIL'~ arlO \lrtU:l II ~, tIK' ~:Ull\" III tern", of ~horl run l.ffL·l"l'. \)ll'ur~ IX'\\\l'l'l)  :t  OIlL' 10 onL' n)rI't'I:l1ioll  till' IHL"l'llll' 01 dl!'''·''! long-run  :uld ..hon-nm ..:fln!' In ot lwr \\ord,. \d1\."n lh~fl'  Less  ~,""II>O" ,1'1  Sl3tlOil,d .. "<)II'  039""'" 0  24  ",f/alOOf!  (X;c;ur  mar  bg 1110' U':JSCfI ~  1arrJC'f  The ~.l"'lnrc 01 wlflJl1(JI) dechncs 10  49 1//>1' fhlr'~ ~',1lI  \\ L'rl" no long rUIl l·fI ..:Ch. !IWfL' ,Iho \\ l'rL' no .... hoI1-run dl...·ch Tf))..!L'IIll'f, tllL' .......· fl·,I1I! ... ;t1l;;" ('flrhi~! 0.:1l1 ..\ illt till' h\ pOlho.::-., .... Ih,l1 IIln:ujOll h:1.'  I ""'\(>I\\L" a  k" ill1l)('.';ll1llk"IL'nlun.ll11  ".."tI.,,..,.. t R.,,,,,,..'"  ( )f  \11 \\i th  tSa nk of Da Uas  Table 3  Log-Level SpecHlcatlon of Money-Demand Regression MIA 1953:1-1979:3  Ea, H , E c, Ed,  1.046  (61 .53) (5.07) (2.59) (5.39)  .039 -.002 -.014  ii '  1979:4-1989:4 1.146 (10.05)  - .135 .003 - .059  (2.11 ) (0.81 ) (1.90)  .98  .99  Ml  Ea, H , Ec, Ed,  1953:1-1979:3  1979:4-1989:4  1.020 .032 -.002 -.011  .680 .246 - .013 - .036  (60.10) (4.05) (1.62) (4.15)  R'  .99  (5.62) (2.05) (2.20) (1.56) .99  M2 1959:1-1979:3  Ea, H Ec, Ed,  (19.27) (1.45) (2.87) (0.71)  906  1." -.066 -.015  ii '  .98  1979:4-1989:4 .934 - .012 - .007 -.018  (9.83) (0.11 ) (0.73) (2.22) .99  NOTE: I $lallS\o(::$ ale In parenlheses  th ...' ...·m ...·rg...·nn· ill inl ...·r...·,.,1 Il.... aflng 111(lI ..... ~  \X'11~  inl1;!lion h:l.' IWnJTll ...· :1 III0r..., ,ignifinl1l (kllTllli11;11)[llf  [\12 r ...·lll;lln':1 1)U/1-1o...' .  IH'\\ ...·'",")"  .\ddiliun;lll~ . th ...· gl'Ill"!~1i r .... ,.,ulh of Ih .... i"irstditl...'r...·nt ...· !llod .... b ;l rl' 10.. .,." th.!!l 'ati,Etclorv Although tlw ...·"pLIl1;Hor~ pI ," .... r. :1' m ...·a:-.lITnl hy 1<-"-.. illl"r"".I'"", from Ih ...· ...·arlil·r :-':lIllplo...-. \ .... ~ ,.....,' of 11ll" ...·"pbn;lI(lr~ \.lri,lhlo...-, olh ...·r Ih;1Il bgg...·d rl';l1 h:lblll"l" :11..... 'I:UI,licll ly ,iglllficll11 TIll" UllU 111'101) I dr:I" frol11 Illl" l 'mplrictl :1I)'I I ~ .. i' IlIl·n. I' Ih,11 lor til<..' 1I)'l.~ -I) dlll'lll~ tndudillg  p.:riod.  till" inll:ilioll r:1I ..., in empirical 11)(1(10...·1:-. III !lMIIll"} tlo...·lll:tnd ,Ilk" ,uh:-.I,lmi:lll·"pbn:lI ()r~ I)()\' ...·rlor \ .\11A Forthl · ItF9-.,",'<) IXTIIM..I. thl' l" idl·Ill'...• I' mi" ...,<1 :I' tCI \\ hl'[hn  inll:tlion h;l .~ b ...·("olm: k:-.s import:lnt for mon ... y d ...·mand and \\ hl:lhl:r inll:i(ion 1~11 .... t ...·nll.' ., hould ho...· dir...·clly indlllk'd in lllont.:y·d",'Ill:lnd model ....  Conc lus io ns Thi' :trud ...• :Iddr...·.,:-..... d (It.... i:-..~\I ...• of how inlbwm ,hOlI\d hl'., ( ht.: in(:()rpllr:l1l'd into mont.:}"lit-manti IIII)(k·h AIIIIII\I).:h r...·ct.:l1l ly ~(II1l ...· ...·{"()IlI ... mhl;'o h.IH· dirn·t l} inn)rpor.ul:d tllo...' intblioo r.l1l: into IIWlr mOlk'h of Illont') lK:mand . 11)(I,t ,tudi...·... ,1"11111...• 111.11 ,I 'holl-I ...·nn Ilolllmal i tlll·n..·,( r.llt.: i, 'uffiu.... lll 10 captur.... [h ...· dkch o f inthlion In Ihis :ll1idl". 'I\.·,il·"t.:d till" Ir:ldllilm:l t argum....n t fllr indudin)-: ()nl~ :1 ,hol1-ll'rl11 iOll'H.·,1 r:11l' and  "  Empirical Implications of Alternative Money Substitutes The analysis in the main text indicates that if assets other than short-term bonds serve as substitutes lor money, then their rates of return should be included in moneydemand specifications . If these rates of return are excluded, then inflation may be a significant determinant of money demand , in addition to a nominal rate of return on short-term bonds. The analysis suggests , then , that moneydemand models should incorporate rates of return on all assets that may be serving as money substitutes. Including such rales of return would then render the inflation terms insignificant. To examine this hypothesis, equation 1 in the main text is modified to include contemporaneous and lagged values of long-term Aaa corporate bond rates under the assumption that long-term bonds or capi-  pft..' ... t.:ntl'{I I\\" rc; ....on ... mllu.on m,.y ;.I-.()  dIH'('/~)'  enter llltKh:J ... ,,( thl' tk'lII,md f"r ll1()n~y TIll' ........  rc:."'()Il.s .... t.'t11 fnUl. t\\(1 (:Io:,:lor ...-Illt.., (,'():-llinl.'''':- (If (:ontinl.ou ... lr ;Idiu~t i ng moncy habncc.s and Iht.' exblL'rKl' (.1' :.lIl·I'I1;I\.\ '-' "'lIh:-l iUUl· ... for 1l1011L' Y I al.'>!) a rg ul..'d Ill:.!. lhco!'l·tictllr. lilt' ;ntrodu('lior1 of inll're ... l-hl..'al'l ng .nOl'ey .ll:.}' h: ~''''l·n Ih(' ne('d 10 indud(' Ihe ;nl1.lI .o., r: IlL' dir'l:'L'lly ;nlo moneyck'lll;md nHxlvl ... Enlpirk:.i l'\'ilkon n : indic .tL'cl tha t ... t:l!j~lic:dl \' s;!-lniti C:ln l .• ll').,::lt;\(' i()1\).,:-l'l. n dll'ct.~ ()f inlbli(lll on Ihl' cic!ll:m d for r1101K'~ o(:t llrred <illrin)..:l9') j---r) ;md th:!! Ihe"'l' cO ...·u ... Wen: ,'01 fully captlll'l.'d hy simply a ... !torl lu m imel'\,''''1 r:lIl·. Till' l'e"'ll lh fill' Iht: 19}{(j.., \\'L'I'L' 1l1iXL'd :1'" 10 \\,hl..·l lIer (krq..:ubt iol1 ha.s led to in[1I1I011 l><-"il11-( k ...., of .111 L'xplan;t lory  factor in tltL' (IL'mantl for monq I h;l\l' omdudL'd . IIK'n. Ih;1I dunng t ill'  rxN\\ ar p'-'ri()(1 unlil Illl' ~'I rl y 1900:-. \\ Itl..·n .110rll·) did not l';1fIl inll·l'l· ... I. intbw)!l had an impO!l;u\l . (hrL'{·t dTI..·(:l on tIll' dem.lnd for lllonL'Y-;Ul l..·ffl..'CI dl'oWWI [ro lll .1 ... inllul'rlcl' Ihrou).,:h .sho n -It·nli ;ntL'rc...ll'all..·... By L',('\udmg Ih l • din:('1 dh'lh o(  '6  tal are serving as substitutes for money , If inflation is significant because these rates of return were previously omitted from the moneydemand specifications, we would expect to find that , once they are included , inflation would be statistically insignificant. In fact. when the Aaa corporate bond rates are included in equation 1, inflation remains significant in every specification (for both samples and in the log-level and first-difference specifications) . Furthermore. the coefficients onthe other included variables, including inflation, are unchanged. In addition, the Aaa corporate bond rates are insignificant for atl the specifications . These results suggest that inflation enters as a significant determinant of money demand for reasons other than the omission of rates of return on long-term bonds.  mlb'''111  f"l.l1 ll le 19-'). ('X-t)llotlll ...I... · lr:.lditl0n;l[ lllotley-tlL·m.Uld 1ll()(ld . . d.d nol pI:donn .h w{'11 a ... 11ll')' ('ollid h:I\": . \hhough "'Ollll' Ilworl·lIc;.11 cl11lll\..' d..:Ill;lnd It,r 1ll11I1l'\  p<. I"'I\\<lr lX'nexl  until  iu ... t if'ic.tI;lln for includi ng lilt, r.lll· o f i l)l1alion  m( mLT-dl'Ill:lIld IlJ(Kk-t...  !1l  Ilw \\ iciL''oprL'ad II ........ o( ir\ll'rl'sl -hearitlg mOlll'} :1Ilt! Ih L, pre"'l'1lI1y .lJ(Kk-l~ltl· 1~ 1\ ...· of inlbllo)) ... u1-(ge ... t tiLl! tl lI'L'ct  dYt'l'h 0 1 inl1;1l1on Illay Lint m t)l\:  p:t ... t dl:.'C. ci<-,  .'\.·.II;1ill ....  h:I\'L'  IX:O'Illt..' k'~", i lllpo r-  Appendix Adjustment Costs and InflaUon In Money-Demand Models ThiS Appendix shows how inflation may enter empirical models of money demand if the short-run demand for money does not completely enforce zero erosion of money due to inflation. The analysis largely borrows from Goldfeld and Sichel (1987) and Hwang (1985) . A divergence between short- and long-run demands lor money typically is motivated by cost-minimizing behavior, where the costs of disequilibrium are balanced against adjustment costs. The adjustment formulation is usually of the form  equation A.2 into an equation suitable for estimation requires a specification for m; or M;. Before doing this, however, it is worthwhile to elaborate on the analysis of Hwang (1985), who shows that specifying partial adjustment in completely nominal or real terms is nol necessary. Hwang specifies a quadratic cost function of the form (A.3)  C - a ,[ln  M; - In M,J2  + ~[(In M, - In M,...,)  +o(ln P, -In P/-1 )]2. (A.l )  Inm, -Inmr-, ""A(ln m;-lnm/-1)'  where m, is the actual stock of real money balances and m; is the long-run desired stock. Equation A.1 is known as the real partialadjustment model (RPAM) because itenforces zero erosion 01 money balances due to inflation . The nominal partial-adjustment model (NPAM), which enforces complete erosion of money balances due to inflation , is given by (A.2)  In M, - In M""j : A(ln M; - In M/-1)'  where M,'" m' Pf M;: m~ P,and P,istheprice level . The difference between equation A. 1 and equation A.2 can be seen by rewriting equation A.l as Illn M, : A(ln m; -In m/-1) + Illn  Ma rc h 19') I  °  In M, -In M,.., '" A(ln M; - In M,.., ) + "((In PI- In P/-1 )' where A 3 0.,1(0. , + ~) , and y : Oa/(a\ +~) '" 0(1 - '). Given astandardspecificationfor  m;, say  ~.  Hence, the RPAM implies that an instantaneous adjustment to changes in the price level does occur. Converting equation A.1 or  F.cono mic Nc vic w -  The first and second terms of equation A.3 correspond to the disequilibrium and adjustment costs, respectively. For 0",0, minimizing equation A.3 yields the NPAM, while for 0:1 , minimizing equatKln A.3 yields the RPAM. Values of 0 between and 1 yield hybrid models. In general, minimizing equation A.3 with respect to M, yields  where y\ is a transactions variable, R, is a nominal interest rate, and 1t. is the rate of in(Continued on the next page)  n  Adjustment Costs and Inflation In Money-Demand Models-Continued flation . Combining equation A.3 and equation A.4 implies an estimating equation of the form (A.S)  In m, = ).90 + A6,ln Y, + ).621n R,  + (1 - A)ln m"" + pin (P,tP,) , where p= H1 -A) + A63 + S(l -A)] . Two points need to be made from this analysis. First. as long as Sdoes not equal 0, then inflation [In(p,1 P,.)) will enter as a significant variable even if inflation is not a determinant of The sec~ and point is that estimation of equation A.S will provide estimates of A and p, but these esti~ mates are consistent with an infinite set of underlying valuesof 63 and S. This result means that there is a problem in identifying the source of the inflation effects. One cannot say whether inflation enters the model because of adjust~ ment behavior or because inflation is a determinant of the real desired long-run level of real balances. Th> emergeroe of interest-bearing mooey has important implications for inventory~type  m;.  money-demand models and the real and nominal partial-adjustment mechanisms that under1ie these models. The idea under1ying inventory-type money-demand models is that in the short run individuals monitor their nominal balances and will allow inflation to erode the real value of their money holdings. In the long run, however, individuals take into account the devaluing effects of inflation on their money holdings. With the emergence of interestbearing money, inflation no longer erodes the value of money. As long as the nominal rate of return on money fully reflects the effects of inflation, an increase in the inflation rate will not increase the opportunity cost of holding money. Therefore, in terms of inventory moneydemand models , an increase in inflation does not entail individuals adjusting target bounds or long-run desired money balances. 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