INFLATION, UNEMPLOYMENT AND MONETARY POLICY IN BRAZIL 1

Transcription

1 INFLATION, UNEMPLOYMENT AND MONETARY POLICY IN BRAZIL Mrcelo S. Porugl Regi C. Mdlozzo Rold O. Hilllbrech 4 Absrc I his ricle we lyse he role of he No-Accelerig Iflio Re of Uemployme NAIRU i iflio rgeig model d lso prese some esimes of he NAIRU usig Brzili D. We prese moery policy model where he NAIRU gp plys key role for iflio rgeig, o becuse moery uhoriies should close he gp every period, bu becuse i helps predic fuure iflio. For he esimio of he NAIRU wo differe models re used. Oe is bsed o rsfer fucio esimio of rdiiol Phillips curve pproch. The secod oe is sigl exrcio mehod where he NAIRU is he uobservble sochsic red of he uemployme d. The NAIRU is esimed usig boh he IBGE d DIEESE d. The resuls show lier Phillips curve for Brzil, d llow good esimes of he NAIRU. The esimios performed usig qurerly d produced ime vryig NAIRU. Our resuls re i lie wih he ccelerio of iflio durig he eighies d he desccelerio of iflio h follow he Rel Pl. Key word: NAIRU, Trsfer Fucio Models, Klm Filer, Iflio Trgeig. JEL Clssificio: C5/E5. Iroducio Afer lmos hree decdes of high iflio res d successive ecoomic pls filures, he "Rel Pl", implemeed i 994, brough dow he iflio re from lmos,5% o jus,48% per yer. A he sme ime, he uemployme re begu o icrese o surprisigly high levels for he Brzili sdrds. A relev quesio i his frmework is he esimio of equilibrium uemployme re. The fc h he risig o uemployme c be origied from decresig iflio is well kow i ecoomics sice Phillips 958 used Eglish d o suppor iverse relio bewee he res of iflio d uemployme. I he prese pper we will use he mos rece cocep of NAIRU No-Accelerig Iflio Re of Uemployme. This cocep ws Pper prepred for he IMF Iflio Trgeig Semir held i Rio de Jeiro, My -5, 999. The uhors would like o hk he reserch ssisship of Gregório Silv Ceo d Príci U. Plermo CNPq/UFRGS. We would lso like o hk Dvid Logworh from he Bk of Cd, d he pricips of XIV Jords Aules de Ecoomí of he Cerl Bk of Uruguy d he XXI Meeig of he Brzili Ecoomeric Sociey for helpful commes. From he Federl Uiversiy of Rio Grde do Sul d ssocie resercher of CNPq. From he Uiversiy of Illiois Urb-Chmpig. Ficil suppor from CAPES is grefully ckowledged. 4 From he Federl Uiversiy of Rio Grde do Sul d ssocie resercher of CNPq.

2 origied from Friedm s 968 url re of uemployme d hs bee esimed for severl couries 5. I his pper we exed he resuls obied i Porugl d Mdlozzo 998 by preseig some ew esimes for he NAIRU for Brzil d developig moery policy model were he NAIRU gp is useful cosruc for iflio rgeig. The esimes re performed seprely for he eighies d for he period of Plo Rel. I he ex secio we will prese hree equio model of iflio rgeig d lyse he effecs of uceriy. I he ex secio he ecoomeric models used o clcule he NAIRU for Brzil re preseed. The resuls for qurerly d esimios re show i he fourh secio. Secio five preses some coclusios d remrks.. O The Use of Shor Ru NAIRU for Iflio Trgeig The model we develop i his secio is used o show how esimes of shor ru NAIRU c be used i iflio rgeig frmework. I resembles he oe employed by Svesso 997b wih oupu gp d sochsic url oupu level, d he resuls we derive re fully cosise wih Esrell d Mishki 999. Moery policy isrume, he ieres re, is ssumed o ffec iflio wih loger lg h he re of uemployme. The model is described by he followig equios u u u ε b ~ u bx bi / η cx ~ x ζ u ξ 4 du where is he iflio re, u is he uemployme re, u is he shor ru NAIRU d x persise ggrege demd shock. is he expeced re of iflio i period codiioed o iformio vilble i. All coefficies re o-egive d c, d. The error erms re i.i.d disurbces, wih zero mes d give vrices. The equilibrium vlue of ll vribles is zero, icludig he rel ieres re i -. For he mome, ssume h ll prmeers re kow wih ceriy. Defie he NAIRU gp s u u. Subrc u from d rewrie he model s 5 ε b b x b i b4u η 6 5 See Gordo 997, Debelle d Lxo 997, Nishizki 997 for NAIRU esimios for Uied Ses,

3 where b b ~ 7 b b 4 d b ~ 8 η ~ ξ 9 η E The oe period d he wo period iflio forecss re, respecively η E / i b bx b i b4 u Where E i is he expecio of he iflio re for period, formed i d codiioed o iformio vilble i, icludig he moery policy isrume i. The moery uhoriy coducs moery policy wih he objecive of rechig log ru iflio rge * d reducig i he shor ru NAIRU gp flucuios roud zero. I he log ru, here is o uemployme rge oher h he url re ormlized o zero. The moery policy isrume is he ieres re i, h ffecs uemployme oe period hed d iflio wo periods hed. The moery uhoriy objecive c be summrized by he sdrd qudric ieremporl loss fucio E L τ τ L, u < < τ τ wih he period loss fucio [ ] τ, τ where is he weigh o NAIRU gp sbilizio. I he cse of flexible iflio rgeig s opposed o sric iflio rgeig, where, he moery uhoriy plces posiive weigh o shor ru NAIRU gp sbilizio, h is, >. To solve for he iflio rge rule, cosider firs he soluio for he simpler cse of oe yer corol lg for iflio 6. The vlue fucio c be wrie s V { [ ] E V } mi 4 subjec o 5 ε Where he NAIRU gp c be cosidered he corol. To solve for he firs order codiio, guess h he vlue fucio hs he form Cd, Gre Brii d Jp. 6 See Svesso 997b, ppedix B.

4 4 k k V 6 wih he k coefficies o be deermied. The he firs order codiio becomes E k E V 7 The soluios for he NAIRU gp d he iflio rge rule re, respecively k k 8 k E 9 Noe h hese soluios deped o k, h eeds o be ideified. Use he evelope heorem o 4 d 6 d wih 9 eque he coefficies for - *. The uique posiive soluio h fulfils k is give by 4 k k Now he wo period corol lg for iflio problem c be formuled s [ ] { } / * / / mi / E V V subjec o / / / η ε where is he corol d he opiml ieres re is give by u b b x b b b b b i 4 / Noe h his problem is log o 4 subjec o 5, wih, d ε- η replcig, d ε. This logy leds o k / / 4 where k is give by. From, -/ -. Use his o elimie from bove d ge / / k 5 or / / c 6 oe h c<. Now solve for he isrume rule. From equios d 4, we obi

5 k b k b b b4 i x u 7 b k b k b b or i f f f x f u 8 x u Uder flexible iflio rgeig >, equio 5, he rge rule equio, implies h he wo period expeced iflio should grdully pproch he rge. The reso for his resul is h his sregy reduces shor ru NAIRU gp flucuios. Addiiolly, equio 7, he isrume rule equio, sys h if curre iflio is bove rge, ieres re should be icresed. The opiml ieres re lso depeds o predeermied curre vribles he shor ru NAIRU gp, shocks d he discrepcy of he shor ru NAIRU level from is log ru vlue, for hey help expli fuure iflio. Noe h equios 4 d 6 imply h he ex period expeced shor ru NAIRU gp will o be zero whe fuure iflio devies from rge. The reso for his resul is h he policy objecive is o o drive uemployme owrds he NAIRU, bu o use he NAIRU gp s idicor of he direcio o move he isrume 7. Uder sric iflio rgeig, equio 5 implies h he rge rule is reduced o *, h is, moery uhoriy should djus is isrume for he wo period iflio forecs o rech he rge. Noe h uder sric iflio rgeig k, d herefore he isrume equio 7 will lso deped o he predeermied vribles. Alhough moery uhoriy does o im o sbilise uemployme, kig shor ru NAIRU gp io ccou is sill vluble, sice i helps predic fuure iflio. Cosider ow uceriy bou he coefficies i he model 5-6. Sice he use of shor ru NAIRU esimes for iflio rgeig cocers policy mkers, i is ieresig o sk how uceriy of hese esimes ffecs moery uhoriy recio fucio. Simplify he model igorig shocks, d rewrie i s 9 ε b b i b4u η Uder sric iflio rgeig, Svesso 997 showed h he soluio o he period by period problem give by equios o 4 where i is he corol vrible, is equivle o he dymic soluio of he ieremporl loss fucio. mi [ ] subjec o E 7 This resul is lso sressed by Esrell d Mishki

6 / i ε, η ε u / i /, b, b i, b4 4 /, Now, ssume h here is model uceriy i period, resulig from uceriy bou coefficies, b, b d b 4. Le ν 5,, b, b νb, 6 b, b ν b, 7 b 4, b4 ν b4, 8 Assume h, is kow wih ceriy i. All ν s re i.i.d. sochsic disurbces wih zero me d give vrices. For simpliciy, ssume h ll cross equios covrices re zero. Relisio of disurbces i re kow i 8. The wrie, b ν, α 9, b ν, α 4, b4 4 ν 4, α 4 Agi, he ν s re i.i.d., hve zero me, give vrices σ, σ, σ 4 d zero cross equios covrices. The wrie he cosri i s / α ν, α ν, i / wih /, 4 ν 4, u ε, η ε α 4 4 The wo period iflio forecs ow is / i / α α i / α 4u 44 Now we hve ll he igredies o wrie dow he soluio o he problem give by he loss fucio equio. The relev cosri is give by equio 44, d he firs order codiio leds o σ / i i / 45 α Subsiuig equio 44 io 45, we fid he isrume rule 6

7 α α α α α u 46 i 4 / / α σ α σ α σ Ad from equios 45 d 46 we derive he rge rule s σ α σ / 4 i / u 47 α σ α σ α σ From he isrume rule equio 46, wo implicios re worh o oe. Firs, uceriy wih respec o he policy muliplier coefficie α ffecs he soluio. Brird s 967 lysis pplies, sice he presece of policy muliplier uceriy σ > reduces he coefficies i he recio fucio, mkig he policy mker more coservive, h is, he policy mker will rec o he discrepcies less h i he ceriy equivlece cse. Secod, uceriy wih respec o he shor ru NAIRU does o ffec he moery uhoriy recio fucio. I does, however, ffec he vlue of moery uhoriy loss fucio, sice i icreses he codiiol vrice of 9. The implicios of he rge rule equio 47 re lso srighforwrd. Uceriy bou he shor ru NAIRU coefficie does o ffec he wo period iflio forecs, policy muliplier uceriy moives deviio of iflio forecs from he rge d he wo period iflio forecs pproches oly grdully he rge. This deviio is he sum of frcio of oe period iflio forecs discrepcy from he rge, proporio of shor ru NAIRU gp d proporio of he NAIRU re discrepcy from is log ru vlue ssumed zero. The coclusios derived bove sugges h shor ru NAIRU esimes my be useful cosruc for moery policy frmework bsed o iflio rgeig. Shor ru NAIRU esimes re poeilly impor i his policy pproch becuse he curre NAIRU gp level revels iformio bou fuure iflio d provides policy mkers sigl for he deque coducio of moery policy. α σ. NAIRU Models I his secio we prese he ecoomeric models o be used i he NAIRU esimio. The NAIRU esimios will be performed i wo differe wys. O oe hd, s i Nishizki 997, we will use rdiiol Phillips Curve pproch bsed o rsfer fucio esimio. O he oher hd, s suggesed by Debelle d Lxo 997, we will ry o esime he NAIRU s uobservble sochsic red i he uemployme d series. 8 These ssumpios bou he sochsic srucure imply h here is o room for lerig d experimeio by moery uhoriies. 7

8 . Ecoomeric Models d D Alysis The cocep of Phillips Curve ses h Where: iflio re o period ; U uemployme re o period ; e expecio of iflio re o period ; α cos or level of equio; ε residuls. 48 e α βu ε If he uemployme d iflio res follow sdrd behvior, like he Phillips Curve, he he NAIRU is he re of uemployme whe he iflio re of he period is equl o he expeced iflio re. Therefore, we oly eed hree series o esime he Brzili NAIRU: ifl io, uemployme d expeced iflio res. To cpure he iflio re iol level, we use he Niol Cosumer Prices Idex INPC from IBGE. This price idex mesures he iflio o mi Brzili ciies. For uemployme re we use boh PME Employme Mohly Reserch from IBGE d PED Reserch of Employme d Uemployme from DIEESE/SEADE d. Iflio qurerly d were obied by he geomeric me of mohly d, while for qurerly uemployme res we used he rihmeic me. We hve o obi lso d series for he expeced iflio re. My models re used i ecoomics o ry o model expecios. Oe c use models wih dpive expecios, riol expecios or bouded rioliy. I he period lysed, Brzili ecoomy preseed high iflio res, implyig high cos for forecsig errors. Thus, riol expecios seem o be he more ppelig wy o model he ecoomic ges' expecios. The riol expecios hypohesis ssumes h ges icorpore ll vilble iformio o formule expecios bou vrible so h ges do o mke sysemic errors. Therefore, o obi he expeced iflio re d, we hve esimed severl ARIMA models d choose he oe h geered he bes fi d predicio for he iflio re. 9 See Esrell d Mishki 999. For he hree series we will use oly qurerly d for he period 98 o 998. Sice he DIEESE d series hd differe ciies icluded i differe periods, we re oly usig d for he se of São Pulo. 8

9 . Trsfer Fucio Model Whe oe vrible ppers o suffer ifluece from is ps vlues d lso from curre d/or ps vlues of oher exogeous vribles, he bes modellig sregy is o use rsfer fucio. Equio 49 specifies he rsfer fucio model. where y edogeous vrible ime ; z exogeous vrible ime ; ε residuls α cos; AL, BL d CL lgs polyomils. y α A L y C L z B L ε 49 I order o be ble o use his model, we hve o ssume h ll he series re siory d h z i exogeous for y. If we fid o-siory series, he he pproprie mehodology would ivolve coiegrio lysis. O he oher hd, if z is o exogeous oe would hve o use VAR model o esime he NAIRU. I our cse he exogeous vrible c be he uemployme re or some o-lier fucio of i, d supply shock such s wom s shre i he work force. I our esimes we lwys use he uemployme re i lier fshio.. Uobservble Compoes Model Srucurl Models The lierure o uobservble compoes models UCM hs grow quie sigificly i he ls few yers, due mily o he iroducio of he Klm filer o ecoomerics. The Klm filer hs helped mke hese models operiol, givig esy wy o esime he ime vryig uobservble compoes. Such models hve bee developed i boh clssicl d byesi sisics frmeworks. The mi differece bewee hese wo pproches is he esimio of he vrices or hyperprmeers. I he byesi models he observiol d evoluio vrices re obied by vrice lerig d discou fcors. I he clssicl models, o he oher hd, he hyperprmeers re esimed by mximum likelihood. 4 I his pper we re goig o follow he clssicl pproch. 5. For deils o rsfer fucios models see Eders 995. No-lier fucios hve presumbly beer resuls whe he icrese o iflio is more h proporiol o he decrese o uemployme. We esed for o lieriy bu i led o worse esimes. 4 See Mihold d Sigpurwll 98 d Wes d Hrriso 989 for discussio o he byesi pproch. 5 For deiled preseio d discussio o his model see Hrvey 987 d

10 I his frmework ime series is modelled by decomposiio io is bsic formig elemes. Th is, i is decomposed by red µ, cycle ψ, sesol γ d irregulr ε compoes. 6. u ε ψ γ µ 5 The complee model lso should specify he behviour of ech oe of he idividul compoes. A complee reme of uobserved compoe models is beyod he scope of his ricle. Therefore, we will oly briefly discuss he cse of he "bsic srucurl ime series model". I he bsic srucurl ime series model oly hree compoes re used sice he cycle compoe is omied. 7 The red, which will give us esime of he NAIRU, is modelled s rdom wlk wih ime vryig drif while he drif iself is rdom wlk. The sesol compoe c be modelled by combiio of sie d cosie wves or by he iroducio of sesol dummies. The full model wih sesol dummies c be wrie s u ε γ µ µ µ β η 5 β β ζ - S j j ω γ γ where ω ζ η ε d,, re ll ormlly disribued errors wih vrices d,, ω ζ η ε σ σ σ σ. To simplify mers le us suppose h we re delig wih qurerly d, so h s 4. Therefore, equios 5 c be cs i he se-spce form s y α ε ω ζ η γ γ γ β µ γ γ γ β µ α Oce he models hve bee cs i he se spce form, esimio of he uobservble compoes c be performed by he Klm Filer d he esimios of he vrices d,, ω ζ η ε σ σ σ σ by mximum likelihood. 6 The esimio of NAIRU usig srucurl models ws ispired o Debelle d Lxo 997 bu Porugl d Grci 996 lso use he sme process h used i his pper. I Corseuil, Gozg d Issler 996, he srucurl model is gi used o defie he NAIRU o severl meropoli regi os from PME of IBGE. 7 The red plus cycle model is discussed i Porugl 99.

11 Grph Sesol Compoe of Qurerly Uemployme Re from IBGE,6,4,, -, -,4 -,6 -, I his specificio we hve compoe o represe he level of he series µ d oher o represe he red iself or slope coefficie β. Therefore, series wih o slope will hve β, while i he cse of cos slope we hve β β σ. This llows us o exrc he NAIRU from he red of he uemployme series 8. For ll series lysed we foud h he slope compoe is equl o zero, herefore, he red of he series hs oly he level compoe. Someimes oe c be cofused believig h he series hs o red becuse i hs oly he level compoe. Bu, s show by Hrvey 989, he cocep of red sill exiss eve whe he slope is zero. For ll series lysed i his pper he sesol compoe hs fixed prmeers, sice he esimed vrice of he residuls ω is o sigificly differe from zero σ. Hece, here re o chges i he sesol per of uemployme durig he esimio period. This fc c be beer see o Grph, h shows he behviour of he sesol compoe of uemployme from he IBGE qurerly 9. ζ ω 8 There is ohig h imposes h he red of he series mus be is equilibrium vlue. I order o susi h he behviour of he uemployme re is goig o he NAIRU, we eed oher resricios. I he Phillips Curve heory, his ide is bsed o he fc h he NAIRU will hppe whe he iflio expecios re sisfied. If he ecoomic ges ry o 'mch' he ex period iflio re, i is o cohere o believe h hey will lwys overesime or uderesime he cul uemployme re he miskes will follow o-predicble per. Therefore, he NAIRU c be he red of he uemployme re series. 9 The sesol compoe of he DIEESE series show similr resuls.

12 4. NAIRU Esimes for Brzil 4. Esimios wih Trsfer Fucio Models The iiil sep o esimig he rsfer fucio model ws specifyig he proper fucio d esig he series for sioriy d exogeeiy. All series re siory, which llows us o model hem usig he rsfer fucio pproch. Thus, he objecive fucio o be esimed 5 follows he sme specificio of he equio 49. α A Bsed o equio 5 he NAIRU c be clculed s Eve whe usig qurerly d, he e e L[ ] C L U B L ε 5 NAIRU α B Lε C L e series exhibis srucurl chges for some specific periods, mily he begiig of price sbilisio pls. The firs wo qurers of 99 d he secod qurer of 994 were he mos ffeced. O he firs qurer of 99, he iflio re ws more h fory perceul pois greer h he expeced iflio. I he followig qurer, we c observe excly he iverse, wih he expeced iflio beig greer h he cul iflio by he sme proporio. To llow for hese srucurl chges we isered wo dummy vribles i equio 5 d esed for heir sigificce. O he secod qurer of 994, period h he Rel Pl ws beig implemeed, we hd gi problems wih he expecios. I his cse, he expeced iflio ws hiry perceul pois bove he cul iflio. We, herefore, icluded he hird dummy vrible o he model d esed is sigificce. Afer he iclusio of he dummy vribles we hve equio 5 o be esimed. where α A L[ e 5 e e ] C L U γd ϕd D D,D d D dummy vribles for he periods of expecios reversio e esimed residuls. The sioriy d exogeeiy ess d he esimio of he rsfer fucio model were performed usig he sofwre S 6.. The ess resuls re o he ppedix I. The sioeriy of iflio re hve bee quesioed be some uhors sice he freque srucurl breks my geere bised his resul see Perro, Ci d Grci 995. Eve if he iflio re series is I, i does o ffec our resuls becuse we re modellig he differece bewee he cul d expeced iflio. Therefore i is s if we were kig he firs differece iflio re. The Augmeed Dickey-Fuller ADF ess show h here is o ui roos %. Sice uemployme d is bouded bewee % d % he ui roo ess hve o be mde up from rsformio o he origil d. Followig Corseiul, Gozg d Issler 996 we used logi fucio [log U/-U] before pplyig he ADF es. Followig he procedure described o Eders 995, we rejec he ull hypohesis of ui roos for boh uemployme series. The iclusio of dummy vribles i equio 5 my be impor oly whe fidig he esimed prmeers, bu o whe clculig he NAIRU. To clcule NAIRU i he periods where he dummies were prese, we mde rihmeic me bewee he previous d ex NAIRU.

13 The residuls i equio 5 do o ecessrily hve o be whie oise. Therefore, he iclusio of relev lgged residuls c improve our esimio by icresig he explory power. The, we cosruc residul polyomil BL s i equio 54 e B L ε 54 The degree of BL is give by he residuls uocorrelio fucios ACF d pril uocorrelio fucios PACF. The polyomil BL my follow pure uoregressive model AR or combiio of uoregressive d movig verge process ARMA. I our esimios, he mos coveie model ws AR for ll cses. Afer defiig he form d degree of BL, we iclude equio 54 o equio 5 d we ge he fil equio o be esimed. Oe should oe h i is he iclusio of 54 h will geere ime vryig NAIRU. If we fid h e is whie oise, he NAIRU will be fixed. 4.. NAIRU for IBGE d The esimio of equio 5 usig qurerly uemployme d from IBGE resuled i o whie oise residuls. The fil esimed equios ws equio e e e U D 55.5 D 8.77 D.85 ε Number of obs. 6 F7, R-Squred.779 Adj. R-Squred.75 Afer some lgebric mipulio, seig iflio re equl o expeced iflio re for ech period d isolig he uemployme vrible 5, we foud he vlue of flexible NAIRU expressed by he equio 56 NAIRU U * D 55.5 D 8.77 D.85 ε - / Grph shows he vlues for he uemployme re of IBGE for ech qurer d he vlues foud for NAIRU. By defiiio, whe he uemployme re equls he NAIRU, here is o pressio for eiher ccelerio or desccelerio of he iflio re. Whe he uemployme is bove bellow he NAIRU here re movemes o desccelere ccelere he iflio re. Noice h i he periods whe he iflio re ws very high, mig he ed of 8's d beggig of 9's, he NAIRU ws lmos every period bove he uemployme re. The iclusio of lgged residul o equio 6 c cuse loss i cosisecy whe usig ordiry les squres esimio. Thus, we used Isrumel Vribles esimio. To see discussio o he coveiece of usig les squres or isrumel vribles esimio, see Hrvey 99 pg d pg Eders, Sdler d Prise 99, for exmple, esime rsfer fucio model by les squres. 4 The vlues i prehesis re he sdrd deviios for ech esimed prmeer. 5 For he uemployme series ll ime lgs re ke o be he sme.

14 This mes h iflio re could be icresig lso becuse he uemployme ws o i he equilibrium re. O he secod yer of he Rel Pl, he opposie begu o hppe, h is he NAIRU ws lower h he cul uemployme re. This mes h, i his period, he high uemployme could hve helped o reduce he iflio res. Grph Uemployme d NAIRU Qurerly D from IBGE 9, 8, 7, 6, 5, 4,,, Uemployme IBGE NAIRU The resuls show o grph re quie iuiive. To cofirm his iuiio we formule simple es. We w o es h whe he NAIRU ws lower h he cul uemployme re, he iflio re ws ccelerig d whe he NAIRU ws greer h he uemployme re, he iflio ws desccelerig. Therefore, we esime by les squres regressio of he NAIRU gp he differece bewee uemployme d NAIRU for ech period o he iflio re. The resuls re show o equio 57 U NAIRU By direc observio of equio 57, he egive d sigific coefficie i he iflio re idices he cosisecy of our esimio. The ccelerio of iflio re is reled s expeced wih he icrese o he NAIRU gp. 4.. NAIRU for DIEESE d Followig he sme procedure used before, we lso foud o-whie oise residuls for he esimio of equio 5 for he DIEESE qurerly uemployme d. Therefore, fer icludig he residuls of he isrumel vrible esimio of equio 5 d re-esimig by ordiry les squres we fid he equio 55' 4

15 - e U 8. D 46. D 7.9 D.57 ε - 55' Number of obs 54 F 5, R-Squred.7844 Adj. R-Squred.76 Give he coefficies i equio 55 oe c fid gi ime vryig NAIRU by equio 56. NAIRU U * D 46. D 7.9 D.57 ε - / ' Grph shows he behviour of he esimed NAIRU d he DIEESE cul uemployme re. A simple ispecio of Grph shows h he esimed NAIRU follows expeced per, h is for periods of high iflio he NAIRU is bove he uemployme re d vice-vers. For he period fer he Rel Pl, specificlly he secod hlf of 995, he NAIRU becomes bigger h he uemployme d his gp ppers o be persise. Grph Uemployme d NAIRU Qurerly D from DIEESE 4,,, 8, 6, 4, Uemployme DIEESE NAIRU Usig gi more geerl es we regressed he NAIRU gp o he iflio re d he resuls re preseed i equio 57' U NAIRU.6. 57'.5. Oce more, he respose of icresig he NAIRU gp is decrese o he ccelerio of he iflio re. The equio 57' llows us o cofirm h he esimed NAIRU is relly cosise wih he predicios oe could mke bsed o Phillips Curve pproch. 6 6 I is o our objecive here o discuss he differe mehodologies used by IBGE d DIEESE o mesure he ope uemployme re i Brzil. Bu i is ieresig o oice h he respose of iflio o he NAIRU gp is differe i ech cse, s show by he differe coefficies o equios d. This resul my be due o he fc h for IBGE we re usig he ol uemployme re, where s for DIEESE we re usig d for São 5

16 4. Esimios wih Uobservble Compoes Model Srucurl Model The srucurl model preseed i equio 5 is used o esime he red i qurerly uemployme d from boh IBGE d DIEESE. We hve oly sochsic red d sesol compoe i h model. I his cse, he NAIRU is he red compoe µ for he series. The esimed vrice of he sesol residul ω is o sigificly differe from zero, idicig h he sesol per of uemployme re hd bee cos for ll series. Grphs 4 d 5 show he evoluio of NAIRU d he uemployme re for he qurerly IBGE d DIEESE d 7. A simple ispecio o grphs 4 d 5 shows h he esimed NAIRUs re compleely differe from he oes esimed wih he rsfer fucio pproch. The mi feure o be oiced here is h he esimed NAIRUs follow very closely he cul uemployme re, s oe would expec from sochsic red. We perform here he sme es s before, regressig he NAIRU gp o he iflio re, bu i his cse he esimed coefficie ws o sigificly differe from zero. This mes h he NAIRU gp did o hve y ifluece o iflio which is o i ccordce wih he Phillips Curve predicios. Grph 4 Uemployme d NAIRU Srucurl Model Qurerly D from IBGE 9, 8, 7, 6, 5, 4,,, Uemployme IBGE NAIRU Pulo oly. O he oher hd, sice São Pulo is resposible for more he oe hird of Brzili GDP d, herefore, my be ke o be represeive of wh hppes i he coury s whole, he differece i he iflio respose could be cused by he differe mehodologies used o mesure uemployme. I his cse, i is crucil for y discussio relig iflio d uemployme o ry o evlue which is he bes wy o mesure he ope uemployme re. 7 All esimed NAIRUs re preseed i he ppedix II. 6

17 This resul my led o wo differe coclusios. O he oe hd, oe c sy h his resul llows us o coclude h he uemployme red foud by srucurl model does o represe vlid proxy for NAIRU. Regrdless h he cocep of NAIRU d srucurl uemployme re very close 8, we could o ideify i our ess he red compoe of he series s he represeive vlue for he uemployme re h does o ccelere he iflio for Brzil. Therefore, oly he resuls for rsfer fucio esimio c be cosidered vlid o represe he relioship bewee uemployme d iflio i Brzil. O he oher hd, if oe believes i he busiess cycle heory, oe c be very hppy wih he resuls of he srucurl model, sice i llows us o coclude h oupu is lwys close o is poeil level. Grph 5 Uemployme d NAIRU Srucurl Model Qurerly D from DIEESE,,,, 9, 8, 7, 6, 5, 4, Uemployme DIEESE NAIRU Fil Remrks d Coclusio Give he ifliory ps of Brzili ecoomy d he vrious filures i price sbilisio pls h were impled before he Rel Pl, covex Phillips Curve ppers o be more iuiive h he lier oe. The covexiy would llow us o sy h here exis bigger price o be pid o uemployme for iflio reducio h he beefis h oe c ge by icresig employme whe he iflio ws ccelerig. However, we could o derive his relio from our empiricl resuls. O he oher hd, he esimio of lier rde-off bewee iflio d uemployme hs sisic sigificce d ppers o be deque o he 8 See Schs d Lrri 99, chp. XVI. 7

18 Brzili d. I ll of our esimios he uemployme re is bove he NAIRU for he period fer he Rel Pl. This resul is cosise wih he reducio of iflio h hs hppe sice July 994. We eed lso o ry o expli he differece, which ppers o ccelere, bewee he employed populio d he uemployed oe. If he percege of uemployed grows up proporiolly o he decrese o he iflio re s much s would decrese wih he elevio o price levels, he he coclusio c be direcly reled o he credibiliy of he ecoomic policies. We lso could ry o udersd his fcor by lysig he expecio of he ecoomic ges o he oher pois of he sbilisio progrm. I coury like Brzil, which suffered filure of severl ecoomics pls i he ps wo decdes, i is resoble h he ecoomic ges do o hve gre mou of cofidece o he implemeio of oher ecoomic reform. The reversio of expecios does o come oly wih he sbiliy of prices. The icrese i uemployme is well reled o he chges o he equilibrium poi of uemployme re. This c be jusified by he wrog coducio of he ps ecoomic policy. The loger he sbilisio o prices kes o occur, more pelisio will occur o he lbour force by uemployme. Bu his does o me h he uemployme mus be forever his high. Policies of chgig he equilibrium re of uemployme c be pplied brigig good resuls wihou implyig o he reur of ifliory process. The lower res of NAIRU h we foud durig he Rel Pl c be used o jusify his kid of policy. If we cosider he ler resuls, he he mi problem o he Brzili lbour mrke ppers o be he srucure of he employme/uemployme. The quliy of jobs d he skills of he lbour force c be quesioed. The imporce of more flexible lbour regulios o reducig he equilibrium re of uemployme is highlighed ogeher wih he iceive o ives o hum cpil. We hik h hese prmeers should be deeply lysed o lower he uemployme wihou ccelerig he iflio. Filly, he moery policy model we developed suggess h NAIRU esimes c ply impor role i moery policy frmework for iflio rgeig. Two resuls from his lysis sress he imporce of NAIRU esimes. Firs, uceriy bou hese esimes does o pper o hve impc o he moery uhoriy recio fucio. Secod, NAIRU esimes re impor o becuse hey ell moery uhoriies rge for uemployme, bu becuse he curre NAIRU gp helps predic fuure iflio d herefore provides useful sigl for he pproprie coducio of moery policy. 8

19 Sioriy Tess: APPENDIX I We used he Augmeed Dic key-fuller ADF Tes. The ull hypohesis of exisece of ui roos ws rejeced for ll series, s c be see o he Box A. BOX A ADF Tble Vlue % - e qurerly series Qurerly Uemployme Series of IBGE Qurerly Uemployme Series of DIEESE b Exogeeiy Tess: To es for exogeeiy of he vrible - e i relio o he uemployme vribles, we used Grger Cusliy Tes. The ull hypohesis of o-cusliy c be esed by ddig he vrible - e o he uemployme regressio. The resuls re: Grger-Cusliy es for ddig - e o qurerly Uemployme Series of IBGE: -.6 P>.5 Grger-Cusliy es for ddig - e o qurerly Uemployme Series of DIEESE:. P>.9 9

20 APPENDIX II Tble II. - Qurerly D d NAIRU Period Uemployme NAIRU NAIRU Uemployme NAIRU NAIRU IBGE Trsfer Fucio Srucurl Model DIEESE Trsfer Fucio Srucurl Model

21 Period Uemployme NAIRU NAIRU Uemployme NAIRU NAIRU IBGE Trsfer Fucio Srucurl Model DIEESE Trsfer Fucio Srucurl Model

22 Refereces CORSEUIL, C. H., GONZAGA, G. & ISSLER, J. V. 996, Desemprego Regiol o Brsil: um Abordgem Empiric, Ais do XVIII Ecoro Brsileiro de Ecoomeri, Vol. I. BRAINARD, W. 967 Uceriy d he Effeciveess of Policy, Americ Ecoomic Review, DEBELLE, G. d LAXTON, D. 997, Is he Phillips Curve Relly Curve? Some Evidece for Cd, he Uied Kigdom d he Uied Ses IMF Sff Ppers, Vol. 44, Jue. ENDERS, W.995, Applied Ecoomeric Time Series, Joh Wiley & Sos, Ic, New York ENDERS, W., SANDLER, T. d PARISE, G. F.99, A Ecoomeric Alysis of he Impc of Terrorism o Tourism, Kyklos, Vol. 45. ESTRELLA, A. d MISHKIN, F. 999 Rehikig he role of Niru i Moery Policy: Implicios of model formulio d uceriy, i Tylor, J. ed, Moery Policy Rules, he Uiversiy Chicgo Pres, Chicgo. FRIEDMAN, M.968, The Role of Moery Policy, Americ Ecoomic Review, Vol. 58, Mrch. GORDON, R. J.997, The Time-Vriyig NAIRU d is Implicios for Ecoomic Policy, Jourl of Ecoomic Perspecives, Vol., Wier. HARVEY, A. C. 987, "Applicios of he Klm Filer i Ecoomerics", i T. F. Bewley ed, Advces i Ecoomerics - Fifh World Cogress, vol. I, Cmbridge Uiversiy Press, Cmbridge. 989, Forecsig Srucurl Time Series Models d he Klm Filer Cmbridge Uiversiy Press, Cmbridge , The Ecoomeric Alysis of Time Series, secod ediio, Philip All, Lodo. MEINHOLD, R. J. d SINGPURWALLA, N. D. 98, "Udersdig he Klm Filer", The Americ Sisici, Vol. 7. NISHIZAKI, F., 997, The NAIRU i Jp: Mesureme d is implicios, OCDE, Pris. PERRON, P.; CATI, R. C. d GARCIA, M. G. P., 995, Ui roos i he presece of brup govermel ierveios wih pplicio o Brzili d, Texo pr Discussão,. 49, Deprme of Ecoomics, PUC-Rio. PHILLIPS, A. W.,958, The Relio Bewee Uemployme d he Re of Chge of Moey Wges Res i he Uied Kigdom , Ecoomeric, Vol. 5. PORTUGAL, M. d GARCIA, L.996, Nos sobre o Desemprego Esruurl o Brsil, i L. Crleil d R. Vlle orgs., Reesruurção Produiv e Mercdo de Trblho o Brsil, Huciec, São Pulo, p PORTUGAL, M. S. d MADALOZZO, R. C. 998, Um Modelo de NAIRU pr o Brsil, Ais do XXVI Ecoro Brsileiro de Ecoomi, vol.. SVENSSON, L. 997 Iflio forecs rgeig: Implemeig d moiorig iflio rges, NBER workig pper # 5797 SVENSSON, L. 997b Iflio rgeig: some exesios, NBER workig pper # 596. WEST, M. d HARRISON, J. 989, Byesi Forecsig d Dymic Models, Spriger Verlg, New York.

23 SACHS d LARRAIN 99, Mcroecoomics for Globl Ecoomy, Hrveser Wheshef, New York.