Estimating the immediate impact of monetary policy shocks on the exchange rate and other asset prices in Hungary

Transcription

1 Esimaing he immediae impac of moneary policy shocks on he exchange rae and oher asse prices in Hungary András Rezessy Magyar Nemzei Bank 2005 Absrac The paper applies he mehod of idenificaion hrough heeroskedasiciy as described by Rigobon and Sack (2004) o esimae he immediae impac of Hungarian moneary policy on he forin exchange rae vis-à-vis he euro, on spo and forward governmen bond yields and on he index of he Budapes Sock Exchange. The resuls obained are in line wih he inuiion. There is evidence of a significan negaive impac on he exchange rae in one day i.e. an increase in he policy rae leads o an appreciaion of he domesic currency. The effec increases markedly when he esimaion is carried ou wih a wo-day window suggesing he inefficiency of markes in incorporaing moneary policy decisions in asse prices in a shor period of ime. Moneary policy affecs spo yields posiively, bu he effec gradually dies ou as he horizon ges longer. This can be explained wih he impac on forward yields, as he resuls sugges a posiive impac on shor-erm and a negaive impac on long-erm forwards meaning ha a surprise change in he policy rae leads o a roaion of he forward curve. The negaive impac on long-erm forwards is higher in wo days, enough o make he impac on long-erm spo yields slighly negaive. However, he mehod does no provide inerpreable resuls for he sock exchange index.

2 I. Inroducion Moneary policy exers is influence on he economy hrough several channels, wo major of which are he exchange rae and ineres raes. In undersanding he ransmission mechanism of moneary policy, i is necessary firs o ge a picure how he cenral bank s decisions affec hese raes. Theory does no provide an unambiguous answer how moneary policy affecs he exchange rae. The radiional view mainains ha an increase in he domesic ineres rae makes domesic deb more aracive o foreign invesors and generaes demand for he domesic currency. However, here can be several facors ha migh complicae his relaionship, some of which can even lead o a perverse opposie relaionship. Blanchard (2004) and Sigliz (1999) poin ou ha under cerain circumsances depending among ohers on he level of indebedness and share of foreign financing in a counry a large increase in he domesic ineres rae migh resul in an increase of defaul risk hus reducing he araciveness of domesic deb which can lead o a weakening of he currency. In addiion, Garber and Spencer (1995) describe how he dynamic hedging aciviy in opions markes can lead o a perverse effec of moneary policy on he spo exchange rae. This paper applies he mehod idenificaion hrough heeroskedasiciy as described by Rigobon and Sack (2004) o invesigae how he ineres rae decisions of he Cenral Bank of Hungary affeced he exchange rae of he forin hroughou he firs hree years following he widening of he exchange rae band in he middle of The paper also examines he impac of moneary policy on spo and forward governmen bond yields and on he sock exchange index. The paper is srucured as follows. Secion 2 presens he heoreical consideraions of idenifying he impac of moneary policy and provides a brief descripion of he esimaion mehod applied here. Secion 3 presens he baseline resuls obained wih he heeroskedasiciy-based mehod, compares hose wih he even sudy mehod and checks he robusness of he baseline resuls. Finally, Secion 4 concludes. 2

3 II. Idenifying he immediae impac of moneary policy shocks Esimaing he response of asse prices o moneary policy seps is complicaed by he issue of endogeneiy of he variables. The wo variables are simulaneously deermined, i.e. he cenral bank reacs o changes in asse prices while asse prices hemselves are also influenced by moneary policy decisions. Anoher source of endogeneiy is he presence of facors ha affec boh variables e.g. macroeconomic news, changes in he risk premia ec. In he presence of endogeneiy, he sandard ordinary leas squares (OLS) esimaion mehod gives biased esimaes and his necessiaes he use of oher echniques. One way o idenify he response of asse prices o moneary policy commonly used in he lieraure is he even sudy mehod. The main idea here is o use insiuional knowledge o consider only cerain periods when changes in he asse price are dominaed by news abou moneary policy. In pracice, his usually implies running an OLS regression on days of policy decisions of he cenral bank. This mehod was firs used o esimae he impac of moneary policy on money marke yields by Cook and Hahn (1989) in he case of US. An applicaion of he even sudy mehod for Hungarian daa is provided by Pinér and Wenhard (2004) who find a significan impac of moneary policy shocks on forward yields up o a 3-year horizon. Rigobon (2003) and Rigobon and Sack (2004), however, poin ou ha he sric assumpion of he even sudy mehod i.e. ha he only imporan source of innovaions in a carefully seleced subsample of all observaions is news abou moneary policy may no be saisfied even in a shor window of one day and he esimaes obained may be biased. They propose an alernaive idenificaion mehod which makes less sringen assumpions abou he heeroskedasiciy presen in he daa. Their heeroskedasiciybased esimaion mehod can hus lead o consisen esimaes even in cases when he even sudy mehod suffers from a bias. Rigobon and Sack (2004) consider he following wo-equaion sysem o model he simulaneous relaionship of moneary policy and he price of a given asse: i = β s + γz + ε (1) s = α i + z + η, (2) where he firs equaion is a moneary policy reacion funcion and he second one is an asse price equaion. i is he change in he shor-erm ineres rae, s is he change in he price of he given asse and z is a vecor of common shocks. ε is he moneary policy shock while η is a shock o he asse price. The parameer of ineres here is α which measures he reacion of he asse price o changes in he policy variable. I can be shown ha running an OLS regression on (2) will yield an unbiased esimae only if he variance of he moneary policy shock σ ε is infiniely large in he limi relaive o he variance of he asse price shock σ η and o he variance of he common shock σ z. The even sudy mehod assumes ha his holds if one considers only a cerain subse of all 3

4 observaions, e.g. days of moneary policy decisions. Though in many cases his migh be a plausible assumpion, i may no always be he case. On he oher hand, he heeroskedasiciy-based esimaor considers wo subses of observaions: policy daes which can be defined as days of moneary policy decisions and non-policy daes which can be defined as preceding days and assumes ha he variance of he moneary policy shock increases from non-policy daes o policy daes, while here is no sysemaic change in he variances of he oher shocks from one subse o he oher. Thus he mehod does no assume ha only moneary shocks maer on policy daes, bu raher ha he relaive imporance of moneary shocks wih respec o he oher shocks increases beween he wo subses. The even sudy mehod assumes ha he OLS esimae is unbiased if one considers only days of policy decisions. However, in he presence of srong common shocks, for example, his assumpion may no be saisfied. In conras, he heeroskedasiciy-based mehod does no assume unbiasedness on policy days; insead i esimaes α from he change in he bias ha occurs beween he wo subsamples. Assuming he above-menioned srucure of heeroskedasiciy and ha he parameers α and β are sable across he wo subses, Rigobon and Sack (2004) show ha he difference of he covariance marices of s and i calculaed for he wo subsamples ( Ω ) can be wrien as: P NP 1 α Ω = Ω Ω = λ 2, (3) α α where: P NP σ ε σ ε λ =. (4) 2 ( 1 αβ ) Thus, Ω is a funcion of α and a parameer λ, which measures he shif in he moneary policy shock from non-policy daes o policy daes. From his, one can impose hree resricions on he change in he covariance marix o obain α. The esimaion can be implemened in wo differen ways: hrough an insrumenal variables (IV) inerpreaion or wih generalised mehod of momens (GMM). Though he IV approach is easier o implemen, i considers only one of he hree possible resricions. Therefore his esimaion mehod leads o muliple esimaes. The GMM approach, on he oher hand, akes ino accoun all hree resricions a he same ime and provides more efficien esimaes. Anoher useful feaure of his approach is ha i is possible o es he assumpions of he model. Since here are hree resricions and only wo parameers are esimaed (α and λ ), he sysem is overidenified and he sandard es of overidenifying resricions can be applied for his purpose. This paper applies he heeroskedasiciy-based mehod o esimae he immediae response of asse prices o moneary policy shocks. I also compare he resuls wih hose of he even sudy mehod o find ou wheher he laer ones conain any bias. 4

5 III. Resuls III. 1. Daa The paper analyses he impac of moneary policy on he exchange rae of he forin vis-àvis he euro, on spo governmen bond yields wih mauriies of 1, 5 and 10 years, on forward yields wih he same mauriies and on he index of he Budapes Sock Exchange (BUX). The spo yields are he benchmark yields published daily by he Governmen Deb Managemen Agency Ld., while he forward yields are esimaes made by he MNB using he yield-curve esimaion mehod developed by Svensson (1994). The daa are represened as firs differences of daily observaions, wih he exchange rae and he sock index reaed as logarihmic differences. Thus, wha is measured here is he impac of moneary policy in one day 1. Policy daes include days of rae-seing meeings of he Moneary Council of he Cenral Bank of Hungary, while non-policy daes are he preceding working days. Because of he variaions in he iming of he variables, he daa series are correced in a way ha he observaions for policy daes conain he informaion from he cenral bank s decisions. The sample covers he period Augus, 2001 November, 2004 and conains 160 observaions. The sample includes he regular meeings of he Moneary Council, which ook place every second week unil July, 2004 and once every monh since hen, and also includes four irregular meeings. As i is usual in he lieraure, moneary policy shocks are inerpreed as unanicipaed moves of he cenral bank, which ake financial markes as a surprise. 2 This is capured by he change in he hree-monh yield, as i is assumed o change only as much as he cenral bank s move represens a surprise o he marke. Approximaing he surprise elemen of policy rae changes wih hree-monh yields also has he advanage ha hey are less likely o be influenced by he uncerainy regarding he iming of he cenral bank s acion. I is worh noing ha wih his approach, keeping he cenral bank s policy rae unchanged can also represen a surprise o he marke which would hen be refleced in a change in he shor-erm yield. 1 The secion examining he robusness of he resuls presens esimaions wih a wo-day window. One could perform he esimaion for longer windows measuring he effec of moneary policy on a longer horizon. However, here is a radeoff here as in a longer esimaion window i is less likely ha he imporance of policy shocks changes sufficienly for he model s assumpions o be saisfied. The ime-frame of he measured effec is no exacly one day, because differen variables are recorded a differen hours of he day and he iming of he publicaion of he cenral bank s ineres rae decision varies in he sample. For insance, he exchange rae and he benchmark yields are colleced around afer he publicaion of he cenral bank s decision in a large par of he sample, while forward yields are colleced he following morning excep in he case of irregular meeings of he Moneary Council. 2 See Vonnák (2005) for a discussion on he imporance of focussing on he surprise elemen of he cenral bank s acions in analysing he ransmission mechanism of moneary policy. 5

6 Since he esimaion mehod is based on he change in he variance/covariance srucure of he daa from one subsample o he oher, i is worh analysing his srucure. As can be seen in Table 1, he variance of he policy rae is more han wice as high on policy daes as on non-policy daes, which is in line wih he assumpion ha he imporance of moneary policy shocks is higher on policy daes. Table 1: Variances of he variables and heir covariances wih he policy rae Variances Covariances wih policy rae (*10-3 ) Non-policy Policy Non-policy Policy Policy rae n.a. n.a. HUF/EUR Y BM Y BM Y BM Y FW Y FW Y FW BUX The covariance srucure of he exchange rae shows a posiive co-movemen wih he policy rae on non-policy daes suggesing ha a rise in he shor-erm ineres rae is associaed wih a depreciaion of he forin whereas he relaionship is slighly negaive on policy daes 3. The posiive relaionship on non-policy daes can be he resul of common shocks such as changes in he risk premia or macroeconomic news, which are likely o affec he exchange rae and he shor-erm ineres rae in he same direcion. On policy daes, however, when he imporance of moneary shocks increases subsanially while oher shocks are sill presen, he co-movemen becomes slighly negaive, which may imply ha moneary policy affecs he exchange rae negaively. From his covariance srucure, one would expec a negaive coefficien for he esimae of α in he case of he exchange rae. This change in he covariances is also visible on he scaer plos of he wo variables for he wo subsamples. The posiive relaionship is clearly visible on non-policy daes, while here is a much less discernible direcion on policy daes. Each observaion ploed on he graphs can be inerpreed as an inersecion of he asse price curve and he moneary policy reacion funcion curve. These inersecs are moving because shocks are coninuously hiing boh curves. If i is almos exclusively he moneary policy curve ha is being hi by moneary shocks while he asse price curve is sable and here are no common shocks ha is he assumpions of he even sudy mehod are fulfilled he inersecs will be close o he asse price curve. However, he apparenly srong role of common shocks in he case of he exchange rae suggess ha his may no hold on policy daes and he slope coefficien α esimaed wih OLS for his subsample will be biased. 3 A rise in he value of he exchange rae variable represens a depreciaion of he forin agains he euro. 6

7 Figure 1: Scaer plo of he exchange rae and he policy rae on non-policy daes HUFEUR BMK3M Figure 2: Scaer plo of he exchange rae and he policy rae on policy daes HUFEUR BMK3M On he oher hand, given ha here is a subsanial increase in moneary policy shocks beween he wo subsamples, he cloud of he inersecions of he wo curves will be roaed owards he moneary policy curve from non-policy daes o policy daes. As menioned earlier, he heeroskedasiciy-based mehod esimaes α from he change in he size of he bias, which in his conex appears as he roaion of he cloud of realisaions. Thus, he covariance srucure of he exchange rae suggess ha he heeroskedasiciy-based mehod may provide a beer esimae of α han he even sudy mehod in he case of he exchange rae and also ha he difference beween he wo may be subsanial. The covariances of he benchmark yields wih he policy rae show a posiive co-movemen on non-policy daes which increases on policy daes. This may sugges some role of cerain 7

8 common shocks which push he wo variables in he same direcion even on non-policy daes. I also suggess ha, conrary o he case of he exchange rae, moneary policy migh affec he 1-year benchmark yield posiively. The covariances of he benchmark yields a longer horizons show a similar srucure. Based on his covariance srucure, one would expec a much smaller difference beween he wo esimaion mehods for he benchmark yields. Figure 3: Scaer plo of he 1-year benchmark rae and he policy rae on non-policy daes BMK1Y BMK3M Figure 4: Scaer plo of he 1-year benchmark rae and he policy rae on policy daes BMK1Y BMK3M Regarding he forward yields, one can find a srucure similar o ha of he benchmark yields a he shor horizon, while he covariance srucure of he 5 and 10 year forward yields are more similar o ha of he exchange rae. The BUX index shows a negaive comovemen for boh subsamples which increases subsanially for he policy daes. 8

9 III. 2. Resuls of he heeroskedasiciy-based mehod The paper applies boh ways of implemenaion of he heeroskedasiciy-based esimaion mehod: he IV and he GMM approach. The insrumen for he IV esimaion is based on he policy rae 4. The IV esimaion can be carried ou wih a sandard single-equaion wosage leas squares (TSLS) mehod. In his case, he asse price variable is regressed on he policy rae separaely for each variable using he relevan insrumen. Alernaively, he esimaion can be carried ou in a sysem including all he individual asse price equaions using hree-sage leas squares (3SLS). The laer one is usually preferred as i is more efficien. However, he coefficiens obained wih he wo IV mehods are almos idenical and he improvemen in efficiency is marginal, herefore only he 3SLS resuls are repored here. Since he efficiency gain from esimaing in sysem is neglecable as compared o single equaions in he case of he IV mehod, he GMM mehod is carried ou only in single equaions. As can be seen in Table 2, he coefficiens are significan wih boh mehods excep in he case of he BUX index. The coefficiens obained wih IV and GMM are close for all variables excep for he sock exchange index. This is imporan because he wo esimaions should yield asympoically equal resuls provided ha he assumpions of he model are saisfied. The overidenifying resricions are in line wih he fac ha only he BUX shows srongly differen coefficiens wih IV and GMM. The significan es saisic for he BUX index implies ha he model s assumpions are no saisfied in his case, while he overidenifying resricions canno be rejeced for any of he oher variables. Table 2: The resuls of he insrumenal variables and generalised mehod of momens esimaions IV GMM Coefficien Sd. Error Coefficien Sd. Error Overid. resr. hufeur -0.60* * bmk1y 0.66* * bmk5y 0.21* * bmk10y 0.10* * fw1y 0.48* * fw5y -0.24* * fw10y -0.50* * bux * * * significan a 5% level 4 More precisely, he insrumen equals he policy rae wih a posiive sign on policy daes and wih a negaive sign on non-policy daes. The IV esimaion can also be carried ou wih an insrumen obained wih a similar ransformaion of he asse price variables. The coefficiens hus obained are no significanly differen from he ones repored here (excep for he en-year forward yields), hough hey show much higher sandard errors. 9

10 The heeroskedasiciy-based mehod shows a negaive coefficien for he exchange rae. I implies ha a 50 basis-poin surprise rae hike resuls in an immediae percen appreciaion of he forin. Thus, he resuls show no evidence of he presence of a perverse effec of moneary policy on he exchange rae, he direcion of he impac is in line wih he classic inuiion. Considering benchmark yields, he resuls indicae ha moneary policy has a posiive impac on spo governmen bond yields. A 50 basis-poin surprise increase of he cenral bank s policy rae leads o a basis-poin rise in he 1-year benchmark yield and his effec reduces o around 10 and 5 basis poins for he 5 and 10-year yields respecively. This is in line wih he inuiion and implies ha moneary policy can affec shor-erm yields wih a posiive sign bu has a much more limied impac on long-erm yields. The effec of moneary policy almos dies ou a he en-year horizon. The srucure of he impac of moneary policy on forward yields helps explain his phenomenon. The esimaed impac of moneary policy on he 1-year forward yield is close o ha on he 1-year benchmark yield; i is only slighly below he laer one. On he oher hand, an unexpeced 50 basis-poin rae-hike resuls in a 12 basis-poin fall in he 5-year, and a basis-poin fall in he 10-year forward yield. In oher words, moneary policy affecs he shor end of he forward yield curve posiively and has a negaive impac on he longer end of he curve, which increases wih mauriy. Thus, he resuls sugges ha an unanicipaed change in he policy rae leads o a roaion of he forward curve. According o he expecaion hypohesis of he erm srucure, spo yields can be inerpreed as averages of he forward yields calculaed unil he relevan mauriies. Therefore he fac ha moneary policy affecs he shor and on he long end of he forward curve in he opposie direcions can explain why he impac of moneary policy dies ou gradually on spo yields as he mauriy increases. I is ineresing o invesigae wha can be he reasons behind he negaive impac on forward yields. As hese yields can be inerpreed as he marke s expecaions for he fuure shor-erm ineres raes, he resuls indicae ha a surprise cenral bank rae-hike leads o an increase in he shor-erm horizon and a decrease in he long-erm horizon of he expeced pah of ineres raes. A possible explanaion of his can be ha a surprise increase in he policy rae may signal a reinforced commimen of he cenral bank o is mandae of achieving and mainaining price sabiliy on he long-run wih he help of higher ineres raes emporarily in he shor-run. As menioned earlier, he highly significan overidenifying es saisic for he BUX implies ha he model s assumpions are no saisfied in his case and herefore hese resuls are no inerpreable. The reasons for his can be ha he parameers α, β or he shocks o he BUX index or he common shocks show insabiliy beween he wo subsamples. III. 3. Comparison of he even sudy and he heeroskedasiciy-based mehods 10

11 Rigobon and Sack (2004) also consruc a hypohesis es wih which i is possible o es wheher he resuls obained wih he even sudy mehod are biased. Table 3 compares he resuls of he GMM and even sudy mehods and presens he biasedness ess 5. Table 3: Comparison of he even sudy and he heeroskedasiciy-based mehods Even sudy GMM Biasedness es Coefficien Sd. Error Coefficien Sd. Error hufeur * * bmk1y 0.78* * * bmk5y 0.35* * * bmk10y 0.19* * * fw1y 0.53* * fw5y -0.19* * fw10y -0.30* * bux * * A quick comparison of he coefficien esimaes reveals ha he wo mehods give similar resuls for spo and forward yields. The even sudy approach produces significan coefficiens for hese variables jus as he GMM, and he differences beween he coefficiens are usually a he second decimal. On he oher hand, he even sudy mehod fails o give a significan coefficien for he exchange rae, as he parameer obained is srongly below he GMM esimae in absolue value. This difference in he size of bias for he exchange rae and for ineres raes can be explained wih he differen covariance srucures as oulined in secion III.1. The GMM-based resul shows ha he unbiased coefficien is srongly negaive for he exchange rae. However, here was indicaion of a srong presence of common shocks which presumably push he policy rae and he exchange rae in he same direcion hereby reducing he negaive impac of moneary policy even on policy daes. As he even sudy mehod ignores his issue, he resul obained wih his approach is biased upwards and hus i ges close o zero. The biasedness es provides srong evidence ha he even sudy approach gives a biased resul in he case of he exchange rae. In he case of he benchmark yields, he ess indicae ha he even sudy resuls are biased, hough hey are quaniaively closer o he GMM coefficiens han in he case of he exchange rae. The even sudy esimaes exceed he GMM values for all he benchmark variables which can again be he resul of common shocks ignored by he former mehod. Finally, forward yields represen he only asse class, where he biasedness ess canno rejec he hypohesis ha he even sudy mehod provides unbiased esimaes. For longerm forward yields as heir coefficiens are negaive similarly o ha of he exchange rae he even sudy resuls are smaller in absolue value han he GMM resuls, bu he size of he bias is small herefore he coefficiens remain significan. I is worh noing ha in his case, he even sudy approach is more efficien han he heeroskedasiciy-based mehod. 5 The biasedness ess comparing he even sudy and he IV esimaes mainly lead o he same conclusions and herefore hey are no repored. 11

12 III. 4. Robusness There are several aspecs from which he robusness of hese resuls can be checked. The sabiliy of he coefficiens in ime is assessed by performing he esimaions on a smaller ime-frame: from Augus, 2001 unil December The reason why his subperiod is especially ineresing is ha i excludes he year 2003, in which Hungarian financial markes experienced several episodes of exreme urbulence. The resuls for he spo and forward yields obained for his period are very similar o he baseline esimaion, however here is a slighly posiive bu insignifican coefficien for he exchange rae. This could imply ha only he large changes in he policy rae which were associaed wih he urbulen episodes of 2003 have had a significan impac on he exchange rae. However, cauion is necessary when inerpreing hese resuls as he mehods applied are asympoic esimaions and herefore require large samples. The fac ha he sample is much smaller may explain some of he differences as compared o he baseline esimaion. Table 4: Resuls for he period Augus, December, SLS GMM Coefficien Sd. Error Coefficien Sd. Error Overid. resr. hufeur * bmk1y 0.94* * * bmk5y 0.34* * bmk10y 0.17* * fw1y 0.77* * * fw5y * fw10y To invesigae he imporance of large moves in he policy rae, he esimaion is also implemened on he enire sample wih he exclusion of hese observaions 6. The coefficiens for he benchmark and forward yields are similar o he baseline esimaion, however he assumpions of he model are no saisfied in many cases. The reason for his is ha he exclusion of he larges moneary policy seps renders he rise in he variance of policy shocks insufficien o reach idenificaion which is evidenced by he insignifican λ coefficiens 7. On he oher hand, he model s assumpions are saisfied for he exchange rae and boh heeroskedasiciy-based mehods give a negaive coefficien larger han he baseline resuls. While he coefficien obained wih 3SLS is insignifican, he GMM resul is weakly significan providing weak evidence ha small moneary policy seps can also have an impac on he exchange rae, which in fac may be greaer han he impac of large seps. 6 The excluded observaions are days on which he cenral bank changed he base rae by a leas 100 basispoins. 7 In conras, he λ coefficiens in he baseline esimaion are significan for all he variables (excep for he BUX index) in line wih he inuiion. 12

13 Table 5: Resuls for he enire sample excluding large changes in he policy rae 3SLS GMM Coefficien Sd. Error Coefficien Sd. Error Overid. resr. hufeur bmk1y * bmk5y * bmk10y fw1y fw5y * fw10y * Finally, I also check wheher he resuls change when he esimaion is carried ou wih a wo-day daa window. The resuls for shor-run yields boh spo and forward are no subsanially differen, hough hey are slighly lower. However, he negaive impac of moneary policy on long-erm forward yields is considerably higher in wo days han in one day which is enough o make he impac even on spo long-erm yields slighly negaive. Table 6: Resuls obained wih a wo-day daa window 3SLS GMM Coefficien Sd. Error Coefficien Sd. Error Overid. resr. hufeur -2.51* * bmk1y 0.53* * bmk5y bmk10y -0.22* * fw1y 0.41* * fw5y -0.47* * * fw10y -0.71* * There is also a marked difference for he exchange rae, as he coefficiens obained for wo days are around four imes higher. This large difference can be inerpreed as a failure of he model o provide sable coefficiens. Anoher and perhaps more realisic explanaion can be he inefficiency of financial markes as i akes ime for marke paricipans o fully adjus o moneary policy shocks. 8 The very low overidenifying es saisics for he exchange rae and shor-erm yields also suppor he validiy of hese esimaions. 8 I is imporan o noe, however, ha he daa for he exchange rae and benchmark yields are colleced some minues afer he publicaion of he cenral bank s decision in a large par of he sample. Thus, wha he resuls show is ha markes fail o incorporae fully he innovaion from he cenral bank s decision in he exchange rae in such a shor ime-frame. 13

14 IV. Conclusion The paper esimaes he immediae impac of Hungarian moneary policy on he forin exchange rae vis-à-vis he euro, on spo and forward governmen bond yields and on he index of he Budapes Sock Exchange. The endogeneiy problem which sems from he simulaneous relaionship of moneary policy and asse prices and from he presence of common shocks is reaed wih he mehod of idenificaion hrough heeroskedasiciy as described by Rigobon and Sack (2004). Being a small and open economy, he exchange rae plays an imporan role in he moneary ransmission mechanism in Hungary and as a resul he cenral bank needs o know how is decisions affec he exchange rae. Theory does no give an unambiguous answer abou he direcion of his effec. While he radiional view suppors a negaive impac of moneary policy, several auhors emphasise he possibiliy of a perverse opposie effec. The resuls obained wih he heeroskedasiciy-based mehod suppor he validiy of he radiional view for Hungary for he period There is evidence of a significan negaive impac on he exchange rae in one day suggesing ha a 50 basispoin surprise increase in he policy rae causes 0.3 percen appreciaion. This negaive effec increases by around four imes when he esimaion is carried ou wih a wo-day window suggesing he inefficiency of markes in incorporaing moneary policy decisions in asse prices in a shor period of ime. The resuls provide evidence ha moneary policy affecs spo yields posiively, bu his effec gradually dies ou as he horizon ges longer. This can be explained wih he impac on forward yields, as he resuls sugges a posiive impac on shor-erm and a negaive impac on long-erm forwards implying ha a surprise change in he policy rae leads o a roaion of he forward curve. The negaive impac on long-erm forwards is higher in wo days, enough o make he impac on long-erm spo yields slighly negaive. However, he mehod does no provide inerpreable resuls for he sock exchange index. The paper also shows ha he even sudy mehod ofen used in he lieraure o esimae he impac of moneary policy does no provide a valid resul in he case of he exchange rae. This can be explained wih he srong posiive correlaion possibly he resul of common shocks visible on non-policy daes. Ignoring ha his can influence he comovemen of he variables also on policy daes, he even sudy mehod overesimaes he effec and gives a coefficien close o zero. The biasedness of he even sudy mehod is less of a problem for spo yields, and here is no evidence ha his mehod would be biased in he case of he forward yields. To assess he sabiliy of he resuls, he esimaion is also carried ou in a shorer period running unil he end of 2002 excluding he year 2003 which saw many periods of exreme urbulence ofen associaed wih large changes in he policy rae. The coefficiens for he yields are similar o he baseline resuls, while he coefficien for he exchange rae is no significan and posiive. However, he shorness of he sample is a problem here as he asympoic mehod used requires large samples. The imporance of he large moneary policy seps is invesigaed in an alernaive esimaion on he enire sample excluding he large changes in he policy rae. This provides weak evidence ha small moneary policy seps can also influence he exchange rae negaively. 14

15 References Blanchard, O. (2004), Fiscal Dominance and Inflaion Targeing: Lessons from Brazil, NBER Working Paper, No Cook, T. and Hahn, T. (1989), The Effec of Changes in he Federal Funds Rae Targe on Marke Ineres Raes in he 1970s, Journal of Moneary Economics, Volume 24, Pages Garber, P. M. and Spencer, M. G. (1995), Foreign Exchange Hedging and he Ineres Rae Defence, IMF Saff Papers, Volume 42, No. 3, Pages Hamilon, J. D. (1994), Time Series Analysis, Princeon Universiy Press, Princeon. Pinér, K. and Wenhard, T. (2004), A jegybanki kamadönések előrejelezheősége és haása a hozamokra (The Predicabiliy of he Cenral Bank s Ineres Rae Decisions and heir Impac on Yields), MNB Working Paper, No. 2004/31, (available only in Hungarian). Rigobon, R. (2003), Idenificaion hrough Heeroskedasiciy, Review of Economics and Saisics, Volume 85, No. 4., Pages Rigobon, R. and Sack, B. (2004), The Impac of Moneary Policy on Asse Prices, Journal of Moneary Economics, Volume 51, Issue 8, Pages Svensson, L. E. O. (1994), Esimaing and inerpreing forward ineres raes: Sweden , IMF Working Paper, No. 114, Sepember. Sigliz, J. E. (1999), Ineres Raes, Risk, and Imperfec Markes: Puzzles and Policies, Oxford Review of Economic Policy, Volume 15, Issue 2, Pages Vonnák, B. (2005), Esimaing he Effec of Hungarian Moneary Policy wihin a Srucural VAR Framework, MNB Working Paper, No. 2005/1. 15