Α CORE INFLATION MEASURE FOR GREECE


 Ονήσιμος Αντωνόπουλος
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1 ΕΠΙθΕΩΡΗΣΗ ΟΙΚΟΝΟΜΙΚΩΝ ΕΠΙΣΤΗΜΩΝ  Τεύχος 8 (2005), Α CORE INFLATION MEASURE FOR GREECE Abstract Departmentof Flnance and Auditing Technological Educational lnstitution of Epirus The main goal of monetary policymakers is to preserve the price leνel constant and consequently maintain the low rate of inflation. This is the case for Central Bank of Greece (CBG). Neνertheless, monetary authorities are not concern with eνery fluctuation in prices. Rather, they focus οη the underlying trend, the socalled "core inflation". The "core inflation" proνides policy makers with useful information, since it can be a good indicator of current and future trend in inflation, a good measure of inflation for empirical work or a νiable target for monetary policy. Ιη this work, a "core" inflation measure is estimated for Greece using a common trends model. Such a measure embodies longrun economic restrictions strongly supported by the data and bears the interpretation of a longrun forecast, affected only by permanent disturbances to the inflation rate. Περίληψη Ο κύριος στόχος της νομισματικής πολιτικής είναι η διατήρηση των τιμών και επομένως του χαμηλού ρυθμού αύξησης του πληθωρισμού. Αυτή είναι και η πολιτική της Κεντρικής Τράπεζας της Ελλάδας. Παρ' όλα αυτά, οι κυβερνώντες δεν ασχολούνται με όλες της διακυμάνσεις των τιμών. Περισσότερο επικεντρώνουν την προσοχή τους στην υποκείμενη τάση του πληθωρισμού, τον επονομαζόμενο "πυρήνα του πληθωρισμού". Ο "πυρήνας του πληθωρισμού" παρέχει χρήσιμες πληροφορίες στους πολιτικούς, αφού μπορεί να θεωρηθεί ως ένας καλός δείκτης της τρέχουσας και μελλοντικής τάσης του πληθωρισμού, ένα καλό μέτρο του πληθωρισμού για εμπειρική πρακτική δουλειά ή ένας εφικτός στόχος για την νομισματική πολιτική. Στην εργασία αυτή, εκτιμούμε ένα μέτρο του "πυρήνα του πληθωρισμού" για την Ελλάδα, χρησιμοποιώντας ένα μοντέλο κοινής τάσης. Ένα μέτρο τέτοιου είδους εμπεριέχει μακροπρόθεσμου ς οικονομικούς περιορισμούς οι οποίοι υποδεικνύονται από τα εμπειρικά δεδομένα κα ι φέρει την ερμηνεία μιας μακροπρόθεσμής πρόβλεψης, η οποία επηρεάζεται μόνο από μόνιμε ς διαταραχές στον ρυθμό μεταβολή ς του πληθωρισμού. JEL Cla ssificatίo n: C32, CSl, Ε31, Ε52. Keywords: core inflation, comιnon stochastic trends, monetary policy. 79
2 ΓΕΩΡΓΙΑ ΦΟΥΤΣΙΤΖΗ  ΕΠΙθΕΩΡΗΣΗ ΟΙΚΟΝΟΜΙΚΩΝ ΕΠΙΣΤΗΜΩΝ  Τεύχος 8 (2005), Introduction. 80 Ιη the past few decades, inflation targeting has been the main goal of many Central Banks. Among them is the Central bank of Greece that has stressed its policy strategy to achievement and maintenance of low inflation, in order to aggrandize its economic growth and its participation to the European monetary union. Ιη this context, the sharper focus οη price stability has become a widely used framework for design of monetary policy. But monetary authorities are not concerned with every fluctuation in prices. Rather, they focus οη the underlying trend. "Core" inflation corresponds notionally to that general trend in inflation. There are several approaches to measure core inflation (see Wynne (1999) for a thorough overview). Quah and Vahey (1995) proposed a technique for measuring core inflation based οη an explicit longrun hypothesis. They have defined core inflation as "that component of measure inflation that has ηο mediumto longrun impact οη real output". Α bivariate V AR in output growth and the acceleration of inflation is used to extract core inflation from measuring CPI inflation. This system is assumed as being driven by two independent types of disturbances. The first type ( core inflationary disturbances) has ηο impact οη real output in the long run, whilst the second may have. This allowed them to test whether the noncore shock has permanent effects οη inflation or not. The nonexistence of important long run effects of the noncore shock οη inflation was seen as a crucial element in the successful identification. Blix (1997) expands this approach to a trivariate structural VAR, in order to incorporate a monetary shock as well. He concluded that, in general, there is little difference between core inflation measure resulting from the bivariate V AR and the one resulting from the trivariate V AR. Bagliano et al. (2002) have used a common trend model to estimate the underlying core inflation behavior for the Euro zone. They considered core inflation as the long run forecast of inflation conditional οη the information set including inflation, money, interest rates and output. They find that purely transitory shocks have shortlived effects οη the inflation and the estimated core measure captures the permanent component of inflation fluctuations over a mediumterm horizon consistent with the monetary policy strategy of the European Central Bank. Ιη this work, a multivariate V AR in output growth, interest rates, money balances, inflation and exchange rate is considered. The existence of valid cointegration relations is then explored using data froin the economy of Gre~ce for the period. The common trend approach (Warne 1993) is used to decompose observed inflation into a nonstationary permanent trend component and a stationary transitory element. The permanent "core" inflation component is a foιwardlookίng measure of "core" inflation (Bagliano et al. (2002)). This measure based οη longrun relations among several important macroeconomic
3 GEORGIA FOUTSITZI  REVIEW OF ECONOMIC SCIENCES  Νο 8 (2005), variables such as output, interest rate, money balances, inflation and exchange rate bearing the interpretation of a longrun inflation forecast. The remainder of the paper is organized as follows. In Section 2, a discussion of methodology issues is outlined and the data used in the empirical analysis is presented. In Section 3, the empirical results are reported. Finally, in Section 4, a discussion of the resulting conclusions is presented. 2. Methodology  Data Α Cοιηιηοη Trend Model. Let {χι} denote an ndimensional realvalued vector time series, which is generated by the following unrestricted vector autoregression (VAR) of orderp: A(L) Χι= ρ+ει (2.1) where Α (L) is an nxn matrix polynomial of order p and defined by Ρ A(L) = In  Σ AjLj, Α(Ο) = In, Ljxι = Χιj (the lag operator) and ρ is an j=l unknown vector of constants. The ndimensional vector of the reduced form disturbances {ει} is white noise, with zero mean and positive definite covariance matrix Σ. From the unrestricted reduced form of the V AR model (2.1 ), Α (L) can be reparameterized asa(l)l+a *(L)(lL). If {χι} is cointegrated of order (1,1), CI(l,1), with r cointegration vectors (that is, {χι} is integrated of order one, 1(1) with Ο< r < n linear combinations of the variables in {χι}, which are stationary), then the V AR model can be written as a socalled Vector Error Correction (VEC) model (Engle and Granger, (1987)): Α *(L)Δχι = ρ+αβ'χ11 +ει (2.2) where Δ: p1 p1 =1L,A *(L) = In  Σ A;L; and Α; =  Σ Ajfor ί= 1,2...,pl. i=l j=l The matrices α and β are of dimension n χ r with rank equal to r. The columns of β are called the cointegration vectors. Cointegration implies that the rdimensional process {β'χι} is jointly stationary. The elements of α have natural economic interpretations as adjustment coefficients. If we regard the cointegration vectors as describing a steady state or a long run equilibrium for χ, the term αβ'χι represents the correction of the change in Χι due to last periods long run equilibrium error. 81
4 ΓΕΩΡΓΙΑ ΦΟΥΤΣΙΤΖΗ  ΕΠΙθΕΩΡΗΣΗ ΟΙΚΟΝΟΜΙΚΩΝ ΕΠΙΣΤΗΜΩΝ  Τεύχος 8 (2005), As {Δχι} is assumed to be stationary, it has a Wold vector moving average (VMA) representation of the form Δχι = δ+c(l)ει (2.3) where δ+c(l)p and C(L) = In+ ΣcjLj with Σ j 1Cj1 < οο. j = l j = I Engle and Granger (1987) find that if {χι}ίs cointegrated of order (1,1), then C(l) has rankn  r andβ'c(l) =Ο. That is, a VMA representation of the form (2.3) and cointegration jointly imply the existence of the unrestricted V AR and of the VEC representations ίη (2.1) and (2.2) respectively. From the representation (2.3), C(L) can be parameterized as follows C(L) = C(l)+C*(L)(lL) (2.4) where C(l) has a reduced rank nr under the assumption of cointegration, c (L) = Ι n + Σ c j Lj with Σ j 1 c j 1 < 00 and c ί =  Σ cj for ί > ο. j = 1 j = 1 j =ί +1 Substituting (2.4) into (2.3), recursively substituting for Χι ι,..., χ 1 and letting εs = Ο, for s = Ο, we obtain the following (reduced form common) stochastic trends representation: ι Χι= χ0 +C(l)(ρt+ Σε ; ]+C*(L)ει (2.5) i=l The reduced forms (2.3) and (2.5) can be represented ίη structural form as (2.6) ι Χι= χ0 +Γ(l){ρt+ Σε;}+Γ*(L)φι (2.7) ί =l 00 respectively, where Γ(L )=Γ 0 + Σ Γ;L; and φι is a vector of structural i =l  innovations with mean zero and variance Σv and Γ*(L) is defined analogously to C*(L) in (2.4). The relationship between the reduced form and the structural shocks are given by ει=γοφι where Γ 0 is an invertible matrix. Also, comparison of equations. (2.3) and (2.6) shows that Γ(L)=C(L)Γ 0, (2.8) 82 implying that C; Γ 0 =Γ;, V ί > Ο and C(l)Γ 0 =Γ(l).
5 GEORGIA FOUTSITZI  REVIEW OF ECONOMIC SCIENCES  Νο 8 (2005), Stock and Watson (1988) developed a common trend representation that was shown to be equivalent to a VEC representation. If a vector of n variables has r cointegration relations, the variables are driven by k = nr common trends. These common trends can be considered to be generated by permanent shocks, so that φι can be decomposed into (2.9) where Ψι is a kdimensional vector of permanent shocks and νι is an rdimensional vector of transitory shocks. As developed ίη Κing et al. (1989, 1991), this decomposition ensures that Γ(l)=[rgo] (2.10) where Γg is an n χ k matrix and Ο is an n χ r matrix of zeros, representing longrun effects of permanent shocks and transitory shocks, respectively. Using the relations (2.9) and (2.10), Eq. (2.7) can be written as ι χ1 = χ0 +rλρt+ ΣΨι}+Γ*(L)φι (2.11) ί=ι ι The permanent part ίη the above equation, ΣΨι, may be expressed as ί=ι a kvector random walk with drift μ and innovation Ψι : τι= μ+τι_ 1 +Ψι = τ0 +μt+ Σ~ i=l (2.12) Using Eq. (2.11) ίη Eq. (2.11), the common trends representation for Χι is obtained. (2.13) As shown ίη detail by Stock and Watson (1988), Κίηg et al. (1991) and Warne (1993), the identification of separate permanent shocks requires a sufficient number of restrictions οη the longrun impact matrix Γg ίη Equation (2.13). Part of these restrictions is provided by the cointegrating relations and the consistent estimate of matrix C(l); additional ones are suggested by economic theory. Finally, having estimated Γg, the behavior of the variables ίη Χι due to the permanent disturbances only, interpreted as the longrun forecast of Χι, may be computed as χ0 + Γg τι. 2.2 The Data. The empirical analysis has been carried out using quarterly data for the period 1975 to 2000 for Greece. The vector of endogenous variables ίs given as 83
6 ΓΕΩΡΓΙΑ ΦΟΥΤΣΙΤΖΗ  ΕΠΙθΕΩΡΗΣΗ ΟΙΚΟΝΟΜΙΚΩΝ ΕΠΙΣΤΗΜΩΝ  Τεύχος 8 (2005), χι = (mι  Ρυ Υι, Πι, r 1, Sι, eι) ι, where mι  Ρι is the money balance ίη quarter t, Υι is the output ίη quarter t, Πι is the annualized inflation rate (πι Ξ 4 (p 1  Ρι~)) ίη quarter t, r 1 and sι are interest rates ίη quarter t and eι is the exchange rate ίη quarter t. We used (log of) real GDP as a measure of the output (y), (log of) CPI (1995=100) as a measure of price level (p), (log of) broad money Μ3 as a measure of money (m ), 12month time deposit rate and saving deposit rate as measures of the interest rates rι, sι, respectively and (log of) the nominal effective exchange rate index for exchange rate eι. Data was kindly provided by Prof. L. Zarangas. 3. The empirical results. Table 1 presents the ADF and ΡΡ tests for all variables ίη levels and first differences. The test statistics show that all variables are integrated of order one, 1(1), whereas the first differences are integrated of order zero, 1(0). Table 1. Unit Root Tests ADFTest ΡΡ Test Ω::i!. ν a!ues<3j Decision Vaήablc SctιφOJ Statistic ft!!!!_(2) Sctιφ Statistic ft!!!!. 1% 5% mp c, c, I(l) Δ(mp} c * c * Ι(Ο) Υ c, t, c, t, (1) Δy c, * c, * (0) π c, c, I(l) Δπ c, ο * c, ο * Ι(Ο) r c, t, ο c, t, ο I(l) Δ r c,o * c, ο * Ι(Ο) $ c, t, ο c, t, ο I(l) Δs c, ο * c, ο * Ι(Ο) e c, t, ο c, t, ο I(l) Δe c, ο c, ο * Ι(Ο) indicates significance at one percent level (1) c: constant, the integers indicate the lags of differenced dependent vaήables included ίπ the regression (ADF test) and the truncation lag (ΡΡ test). (2) MacΚinnon (1996) onesided pvalues (3) Critical values from MacΚinnon (1991) 84 Next we performed test procedures for the determination of the lag length (see Table 2). The Akaike information criterion suggests that p=5 and the Schwartz suggests p=3. Checking the other misspecification tests for p=3,p=4 andp=5 showed that all of them got much worse compared to p=4. Therefore, we choose four lags in the V AR model.
7 GEORGIA FOUTSITZI  REVIEW OF ECONOMIC SCIENCES  Νο 8 (2005), Table 2. Information Criteria. Lags AIC sc * * Α graphical analysis οη the residuals based οη the unrestricted V AR( 4) model suggests the inclusion of the following set of deterministic variables: i) D 89.; 1, ί = 1,2,3, which are centered seasonal dummies for the period 1989:12000:4, ii) the dummy variable DΊ which is equal to 0.5 for the periods 1982:3, 1982:4, 1983:3, 1983:4, to 1 for the period 1983:1, to 1 the periods 1983:2, 1984:1 and to Ο otherwise and iii) the dummies 1, ίftef;, D = { ί=12 ι,t ο otherwίse ' ' ' 1, ίfte.l;, D;,ι = 1, ίft El;, ί = 3,4,5,6 { Ο, otherwίse, where / 1 = { 1985: 4}, / 2 = { 1997: 4}, / 3 = {1978: 2,1979: 3 }, /4 = {1980: 1}, /5={1985:1}, /6={1997:1,1998: 2}, 1 3 = {1979: 2,1979: 4}, 1 4 = {1980: 2}, 1 5 = {1985: 2}, 1 6 = {1998: 3}. Since formal Johansen's (1995) test for the cointegration rank cannot be used, due to the presences of the dummy variables, we rely οη visual inspection and proceed under the assumption that there exist three cointegration vectors. Misspecification analysis ( not reported here) for V AR( 4) model with deterministic variables, centered seasonal dummies and r = 3 cointegration vectors with respect to multivariate serial correlation and multiva~iate autoregressive conditional heteroscedasticity support the dynamic specification of the system.( 1 ) Moreover, recursive estimation shows coefficient robustness over time. Therefore, the analysis proceeds with VAR(4) and r = 3. Having determined the number of cointegration vectors, it is necessary to consider whether these are unique and consequently whether they tell us (1) Calculations were performed using software packages Eviews 3.0 and the Structural VAR package of Warne, Α., which is available in 85
8 ΓΕΩΡΓΙΑ ΦΟΥΤΣΙΤΖΗ  ΕΠΙθΕΩΡΗΣΗ ΟΙΚΟΝΟΜΙΚΩΝ ΕΠΙΣΤΗΜΩΝ  Τεύχος 8 (2005), anything about the structural economic relationships underlying the longrun model. Therefore, it is necessary to impose restrictions motivated by economic arguments and test whether the columns of matrix β are identified. We assume a relation between money balances mι  Ρι, output Υι and exchange rate e 1, interpreted as a longrun money demand function, a generalized Fisher parity relation linking interest rate rι, inflation Πι and exchange rate eι and a term structure equation between the two interest rates sι, rι and the exchange rate eι. The LRtest of three overidentifying restriction on the coefficients of β yields a χ2 (3) statistic of 0,2238 with pvalue 0,9737, strongly supporting the chosen identification scheme. If additional zero restrictions are imposed on the loading parameters in α, we obtain a χ2 (6) statistic of 0,8554 with pvalue 0,99. The restricted loading factors and cointegration parameters estimates are reported ίn Table 3 below. Table 3. Coίntegration parameter estίmates Loadi ιι g Coeffic ieιιt s (α) Restιicted QρLl\!Jϊ&tί_llJQg Y~grm:. (β') 171p p Υ π r s e (Ο~ (Oc2040) ;_(0}8_04) Υ ο ο ο i 1 π ο ο Jl1c0Q:ι7), (Q 0309) ι (0.0576)_ 1 r (Ο 0084) 1 (Ο 0550) (Ο 1 ω6) 0.7:U}J ο Ο 0350 s   ο Ο r ojtn (0.0080) L (0 ~5 24) j_(o Q277) _ 1 ο ο ! e i LRtest of 6 alpha and beta restrictίons= (pvalue: 0.99) The estimated loading parameters show that positive deviations from the equilibrium relation between mp, y and e cause an upward pressure οη inflation π and an error correction reaction of rea..l money balances mp. Furthermore, positive deviations from the equilibrium relation between r, e and π cause a strong upward pressure οη real money balances mp and an error coπecting reaction of inflation π. Finally, positive deviations from the equilibήum relation between s, r and e cause a negative reaction of real money balances mp, an equilibrium response of interest rates r, s and an error correction reaction of exchange rate e. 86 Ιη the common trends framework the existence of three cointegrating relationships
9 GEORGIA FOUTSITZI  REVIEW OF ECONOMIC SCIENCES  Νο 8 (2005), among the six variables implies the presence of three distinct sources of shocks having permanent effects on at least some of the variables in χ. As previously mentioned, such (restricted) cointegrating vectors are used to identify the elements of Γg in Equation (2.13) together with additional restήctions grounded οη economic theory. In order to achieve identification of the common trends model, the following assumptions are made on the nature of the three permanent shocks in the system: a domestίc real shock (ψ,), a domestic nominal disturbance (Ψn ) and a foreign shock (Ψι) are considered. The perrnanent part Equation (2.12) of the common trends representation is then the following trivariate random walk: ( ω ~ ~:) + (;) + (::) (3.1) ι ι μι ι ι 1 Ψι ι where μ is a vector of constant drift terms. As additional restrictions it is assumed that (long run monetary neutrality) ί) the output y is not affected in the long run by the domestic nominal shock Ψn and foreign shock Ψι and ίί) the inflation rate π is not affected in the long run by the foreign shock Ψι Letting γίf denote the generic element of Γg, the first assurnption above irnply γ 22 = γ 23 = Ο and the second one that γ 33 = Ο. In addition, the cointegration relations imply that γlj = Ο.84γ2Γ Ο.22 γ6 j, γ 3 j = Ο. 73 γ 4 j + Ο.04 γ6 j, Ysj = Ο,93γ 4 j γ6j,j=l, 2,3. The estimated matrix Γg of the comrnon trend model (2.13) is presented in Table 4. The estirnated coefficients show that a positive dornestic norninal trend shock Ψn raises the inflation π ίη the long run. It also raises both interest rates r and s. The dornestic real shock ψ,, which is the only determinant of the longrun behavior of output y, plays only a marginal role in explaining the longrun features the inflation and of the two interest rates, that are dorninated by nominal disturbances Ψn. This conclusion is supported also by the results of the forecast error variance decomposition reported in Table 4, showing that in the long run, more than 99% of the inflation variability is due to the nominal disturbances. The measure of 'core' inflation, derived from the common trends mo dl e, h d ιs t en compute as π Λ c Λ Λ Λ Λ Λ Λ 1 = π 0 + γ31 τ,, 1 + γ32 τn, ι + γ33 τμ. 87
10 ΓΕΩΡΓΙΑ ΦΟΥΤΣΙΤΖΗ  ΕΠΙΟΕΩΡΗΣΗ ΟΙΚΟΝΟΜΙΚΩΝ ΕΠΙΣΤΗΜΩΝ Τεύχος 8 (2005), Table 4. Common trends model Variable nιp Υ π r 5 e Long nm effects ( Γ g) ψ, Ψn ,1 ( ) (O.OOJ4 13) (Ο 0057JJ) ο Ψι ( ) Long nm ( οο) foiecast eπor vaiiance explained by Ψ, Ψn Ψι ( ) 1 ( ) ( ) ο ο ο ( ) (Ο ) Ο ! ( ])! ( ) ( ) (0.J1 4473) 1 ( ) 1 (U UUY) /UJ σ: Ο : ο ϊ U.Ul54UU (Ο ) i (Ο ) (Ο J) (Ο J44698) (Ο. J44606) (Ο )  σ Γ :.ο.οο 27ο!Γ ~ ο~οσs21.ϊ ο (Ο ) ( ), ( ) ( ) i ( ) ( ) ο Note: Asymptotic standard errors ίη parentheses In Figure 1, a comparative plot of the estimated core inflation and the observed consumer price inflation is presented. Both are calculated οη an annual basis, using a simple moving average process for the four quarters of each fiscal year. Visual inspection of Fig.1 shows that core and actual inflation series have pretty much the same shape; however, there is an important "transformation": the actual inflation series follows the estimated core inflation series. Figure 1. Obserνed consumer prίce ίnflatίon rate and estίmated core ίnflatίon rate ( annual ra_tes) Actual InflatioConi inflatio
11 GEORGIA FOUTSITZI  REVIEW OF ECONOMIC SCIENCES  Νο 8 (2005), lndeed, during the period both series have three local minima and three local maxima, accordingly shifted for the actual inflation series. Furthermore, Fig. 1 indicates three major turning points ίη actual inflation ίη 1979, 1990 and The first turning point is ίη 1979, where the conservative government was facing growing disapproval from the people and massive strikes enhanced the instability of the economy. The situation turned even worse ίη 1980 due to the second oil crisis. The elections ίη 1981 were won by the socialist party (PASOK), which, after its reelection ίη 1985 applied strict measures (very small salary increases, severe cuts ίη public expenses, etc.), managing to bring the inflation rate down. The turning point ίη year 1990 may be attributed to the political uncertainty ίη Greece, stemming from the three consecutive national elections ίη less than 10 months. Α stable government (though based οη a onevote critical majority ίη parliament) was formed after the third election. The conservative government applied tough measures οη the economy, resulting ίη fierce reaction from several population groups; however, these measures made the stabilization of the inflation rate possible and the result was shown ίη As may be seen, core inflation displays peaks one time period before actual inflation, effectively acting as a "predictor" for changes ίη actual inflation, which is the case for a forwardlooking measure. From 1991 (1992 for actual inflation) οη, the two series decline as a consequence of the strict monetary policy followed during this period. But, of particular interest is the change ίη the behavior of core inflation series at This behavior may be attributed to the property of the forwardlooking common trends measure to signal an increase ίη the actual inflation due to the introduction of the Euro. Notice that the introduction of the Euro ίη several European countries was implemented before 2001, for purposes of accounting, interbanking transactions, etc., although the actual monetary unit was used ίη Naturally, a core inflation rate estimate coming from a common trend model depends οη the parameters and restrictions assumed for the system, which may be proven inaccurate. However, the core inflation data obtained from the smallscale macroeconomic model used ίη this paper, using relationships and interactions between real money balances, inflation, interest rates and exchange rate, seems a useful benchmark to evaluate the properties of other measures of core inflation currently used ίη the monetary policy debate. Acknowledgment: The author wishes to thank Assoc. Prof. Leonidas Zarangas (Dept. Finance & Auditing, ΤΕΙ of Epirus, Preveza, Greece) for introducing her ίη the subject and providing her with data and numerous helpful comments. 89
12 ΓΕΩΡΓΙΑ ΦΟΥΤΣΙΤΖΗ ΕΠΙθΕΩΡΗΣΗ ΟΙΚΟΝΟΜΙΚΩΝ ΕΠΙΣΤΗΜΩΝ Τεύχος 8 (2005), References Bagliano, F. Golinelli, R and Morana, G. (2002), "Core Inflation in Euro", Applied Economics Letters, 9, pp Blix, Μ. (1997) "Underlying Inflation  Α Common Trends Approach", Sveriges Riksbank, Working paper Νο. 23 Engle, R. and Granger, C.W.J. (1987), "Cointegration and Error Correction: Estimation, Representation and Testing", Econometrica, 55, pp Gali, J., Gertler, Μ. and LopezSalido, J. D. (2001) "European inflation dynamics", European Economic Review, 45, pp Johansen, S. (1988) "Statistical analysis of cointegration vectors", Ioumal of Economic Dynamics and Control, 12, pp Johansen, S. (1995) Likelihoodbased inference ίn cointegrating vector autoregressive models, O:xford University Press. Κing R.J., Plosser, C., Stock, J.H, and Watson, M.W. (1991), "Stochastic Trends and economic fluctuations",american Economic Review, 81, pp Quah, D. and Vahey, S. Ρ. Joumal, 105, pp (1995) "Measuring core inflation", The Economic Stock, J.H. and M.W. Watson (1988) "Testing the common trend", Ioumal of American Statistical Association, 83, pp Warne, Α. (1993) 'Ά Common Trends Model: Identification, Estimation and Inference", Seminar Paper Νο. 555, IIES, Stockholm University Wynne, Μ. Α. (1999) "Core inflation: a review of some conceptual issues", European Central Bank, Working Paper Series, no
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