shocks on the medium-term inflationary outlook, due to so-called second round effects acting through the intersect oral linkages and wage setting mechanisms, can be very different according to the nature of the shock itself. Broadly speaking we can distinguish between three situations:
(a) erratic changes with a clearly temporary and reversible impact on prices, such as a sharp increase in the price of fresh vegetables due to bad weather conditions.
(b) Shocks to important production inputs, typically oil, which are likely to induce second round effects. In these circumstances just removing the impact of such shocks can lead to under-estimate an important source of potential future inflationary pressures.
(c) An intermediate case is that in which the price change of a certain item takes place once a year and it is concentrated in a given month, different from year to year. This is often the case for regulated prices. In these circumstances the assessment of inflation is biased in that month, since the monthly change of the overall index which is observed is likely to be quite large but at the same time it would be wrong to interpret it as an erratic change.
The point which is worth stressing here is that forecasting can be performed best on the basis of a broader macro-assessment of all source of inflationary pressures (input prices, labour costs, exchange rate, output gap), captured through a structural macro-model. Hence, the issue is whether the forecasting performance must be assessed only comparing results across various core inflation measures, or enlarging this perspective and comparing also the forecasting per-formance of alternative approaches based on forecasting techniques of headline inflation.
Second, concerning the use of core inflation as a viable target for monetary policy, if the Central Bank is to be held accountable for maintaining inflation within a target, it is better to tar-get a measure which excludes shocks considered out of the Bank’s control, in order to enhance its credibility (Hogan et al., 2001). Equally important are other requirements such as that the preferred measure should not be subject to frequent or strong revisions since that would ques-tion its ability to be used in the current monitoring of inflaques-tion and could create credibility prob-lems, or that core inflation to be “credible” should not exclude too much from headline inflation.
1.3 Is the traditional measure of core inflation out-of-date?
On the basis of the above discussion, it could be argued that the traditional index based on the a priori removal of food and energy products (CPI-XFE) may not that out-of-date as it is often claimed in the recent literature. This could also contribute to explain why most Central banks still refer to it (or to slightly different versions) as their central measure of core inflation.
The traditional measure may represent, in fact, a “fair compromise” between the various desir-able properties, in particular in terms of transparency, communication, accountability, absence of revisions and cross-country comparability (the last requirement is particular important for the euro area). From the point of view of the policy maker a further advantage is claimed by Blinder (1997):
“as a central banker, I always preferred to view the inflation rate with its food and energy compo-nents removed as our basic goal. But not because these compocompo-nents are extremely volatile (…).
The real reason was that the prices of food (…) and energy are, for the most part, beyond the con-trol of the central bank”. On this basis he proposes to exclude from the computation of a core infla-tion measure regulated prices and, eventually, the impact on consumer prices of changes in indirect taxation. The importance of these considerations is also stressed in Hogan et al. (2001).
On the empirical ground, recent evidence based on micro consumer price data for the euro area (Dhyne et al., 2005) confirms that indeed prices of energy and (unprocessed) food products are the most volatile in the CPI basket. The same analysis also suggests that these prices tend to move up and down quite symmetrically; these characteristics would lead to a measure of core inflation based on the a priori removal of these items which is not systematically biased with respect to headline inflation. On a more theoretical ground, this empirical evidence goes hand in hand with the results of recent theoretical models which argue that the higher the degree of nom-inal inertia which affects a given sector of the economy, the higher should be the incentive for the monetary authority to stabilise the corresponding price. More specifically, the overall economic welfare is enhanced if the Central Bank assigns a larger weight to sectors where price developments are more persistent (Benigno, 2004) which, as mentioned above, on the basis of the available empirical analysis turn out to be those producing and selling food and energy goods.5
On the contrary, the main argument to support the view that CPI-XFE index is not an opti-mal measure of core inflation is based on its poor forecasting performance of headline inflation
PROCEEDINGS IFC WORKSHOP – SESSION 6
5 The basic argument is summarised in ECB (2005). In an economy with two sectors (the same applies if two regions are considered, as in Benigno, 2004) of equal size (hence each receives a weight equal to 1/2), one more rigid and
which is outperformed by more sophisticated approaches, confirmed by various empirical analy-ses. This is indeed an important limitation of the CPI-XFE index; however, one may also argue that within a Central Bank, in the context of the a broad assessment of the inflationary outlook to support monetary policy decisions, forecasting is typically carried out on the basis of specific tools (structural macro models) which are better suited to capture the second round effects of shocks to the main determinants of inflation. Hence, the comparison should not be among the forecasting performance of only core inflation measures, but also between the latter and those obtained through these alternative techniques.
A further disadvantage of the traditional measure, which should be carefully examined, is the risk that too much expenditure is excluded a priori from the overall basket. For instance, in the case of Canada the portion excluded amounts to around 25 per cent; for Poland this share is even higher (around 30 per cent).
2. Should monetary policy target core inflation or headline inflation?
An important issue in this literature is whether monetary policy should refer to headline infla-tion or to core inflainfla-tion, however it is defined. In dealing with that it might be useful to go back to first principles and remind ourselves why a Central Bank is concerned about inflation. The main reason is that inflation, in the presence of nominal rigidities, induces sub-optimal choices by price and wage setters, which in turn distort relative prices and reduce the welfare of the soci-ety. The sub-optimality of these choices would be reduced, if not eliminated altogether, if price and wage setters were to expect stable prices for the future (i.e. zero or very low and stable infla-tion). Therefore, it is to ensure that current choices (with persistent consequences) of these agents are made under the expectation of zero or low inflation that monetary policy is commit-ted to deliver such a result. Then, it seems natural to argue that monetary policy should take as a reference (a) future inflation (forward-lookingness principle), and (b) a measure of inflation that is comprehensive enough to be relevant for the price and wage setters (comprehensiveness principle). From the point of view of the monetary authority a target set in terms of core infla-tion can be easier to achieve, since it should be less affected by supply shocks beyond the con-trol of monetary policy; however, this could conflict with the need to take as a reference the inflation people refer to in forming their expectation.
Focussing on the euro area, the Eurosystem approach is well in line with the above basic principles: price stability is defined with reference to the future (the medium term) and to the harmonized index of consumer prices (HICP), that more accurately and reliably measures losses in the purchasing power of money with which price and wage setters are mostly concerned, and that therefore is more likely to be the object of their inflation expectations. As a matter of fact, in Europe most wage bargaining is explicitly made taking into account expectations of HICP inflation; the appropriateness of such a choice is further strengthened by the high persistence of wages which characterises labour markets in the euro area.
In this framework, how should the policy maker regard core inflation in particular when its developments are in conflict with headline inflation? While the second principle (comprehen-siveness) would suggest that headline inflation should be heeded, the first (forward-lookingness) suggests that it is important to extract from the dynamics of current variables all the information about future price trends. In this respect, those prices which exhibit higher persistence are likely to contain more information on future inflationary trends, while the most volatile ones should be more heavily discounted. In other terms, this points in the direction of paying attention to measures of core inflation, without dismissing headline inflation.
3. Conclusions
On the basis of the above discussion it is quite clear that core inflation is indeed an elusive con-cept; none of the available indicators can be fully trusted, in the sense that none gives an answer
ROBERTO SABBATINI
the other more flexible, a monetary policy upon the occurrence of an aggregate shock the rigid sector bears a higher cost than the flexible one in the adjustment to that macroeconomic shock, since the stickier prices create more
dis-to all we would like dis-to know from a core inflation measure. We can indeed share the view that
“different measures do well along different dimensions. Each measure can provide some partic-ular insight into how inflation is evolving”.
This general conclusion supports the Eurosystem approach to the analysis of the inflationary outlook, based on the regular analysis of a number of indicators of inflationary pressures, none of which, however, is sufficient by itself to completely understand inflation developments. Instead, the best assessment is that based on a broad cross-checking of all indicators with a view to identify the nature of the shocks impacting inflation and their likely persistence. This analysis must necessarily be carried out also by relying on structural macro-models better suited to envisage future trends.
Having in mind all this, the traditional measure of core inflation based on excluding a priori the most volatile items from the overall index (CPI-XFE or slightly different version of it) is appealing in the sense that it may represent a fair compromise between various needs. In partic-ular, due to its simplicity, it can be a relatively easy and transparent way to communicate to the public about the inflationary outlook. Furthermore, it presents the same general trend as head-line inflation but it is much less volatile, and it is never revised, at least not too often. Besides all that, it is also likely that the monetary authority has some capacity to realize a (operational) target defined in terms of an index excluding food and energy products (better if regulated prices are excluded as well), whose price movements are dominated by supply shocks which are beyond the influence of monetary policy. A further important advantage of this measure (in par-ticular for euro area countries) is that it can be easily computed for all countries. All in all, in terms of communication, transparency and accountability this traditional indicator presents important advantages over more sophisticated approaches. On the theoretical ground, recent the-oretical contributions taking on board welfare considerations seem to support a measure which assigns zero weight to the most volatile components.
In terms of forecasting future trends of headline inflation, its relatively poor performance compared to more sophisticated measures should not receive too much emphasis since typically within a Central Bank the process of forecasting inflation is based on different tools (structural macro models, etc.).
All this does not imply that more sophisticated measures cannot be used by the monetary authority in the context of an approach based on cross-checking various pieces of information.
However, their high degree of sophistication might be hardly understood by the public opinion and by price setters: hence, their use could be restricted to internal purposes, in the context of a broad assessment of inflationary pressures.
References
Aoki, K. (2001), “Optimal monetary responses to relative price changes”, Journal of Monetary Economics, Vol. 48.
Aucremanne, L. (2000), “The use of robust estimator as measures of core inflation”, National Bank of Belgium, Working paper No. 2, March.
Bagliano, F.C., Golinelli, R. and Morana, C. (2001), “Core inflation in the euro area”, Dipartimento di Scienze Economiche e Finanziarie, Torino.
Bakhshi, and Yates, A. (1999), “To trim or not to trim? An application of a trimmed mean estimator to the United Kingdom”, Bank of England, Working paper series, No. 97.
Benigno, P. (2004), “Optimal monetary policy in a currency area”, Journal of international Economics, No. 63, pp. 293–320.
Blinder, A. (1997), “Commentary to the paper by S.G. Cecchetti: ‘Measuring short-run inflation for cen-tral bankers’ ”, Federal Reserve Bank of St. Louis Review, pp. 157–160.
Blix, M. (1995), “Underlying inflation: a common trend approach”, Sveriges Riksbank Arbetsapport, No. 23.
Bryan, M.F., and Cecchetti, S. (1993), “The consumer price index as a measure of inflation”, NBER Working paper, N. 4505.
Bryan, M.F., and Cecchetti, S. (1994), “Measuring core inflation”, in N.G. Mankiw (ed.), Monetary pol-icy, NBER, University of Chicago Press. NBER Working paper, N. 4505.
Bryan, M.F., Cecchetti, S.G. and Wiggins, R.L. (1997), “Efficient inflation estimator”, NBER Working paper, n. 6183.
Chatelain, J.B., Odonnat, I. and V.P. Sicsic (1996), “Construction sur longue periode d’un indicateur d’inflation sous-jacente”, Banque de France, manuscript.
Czyzewski, A.B. (2006), “Core inflation measures at the National Bank of Poland”, IFC Workshop on CPI measurement, Basel 20–21 April.
PROCEEDINGS IFC WORKSHOP – SESSION 6
Cristadoro, R., Forni, Reichlin, L. and Veronese, G. (2005), “A measure of core inflation for the euro area”, Journal of Money, Credit and Banking, Vol. 37.
Dow, J.P. (1994), “Measuring inflation using multiple price indexes”, manuscript, Department of Economics, University of California.
Dyhne, E., Alvarez, L., Le Bihan, H., Veronese, G., Dias, D., Hoffman, J., Jonker, N., Lünnemann, P., Rumler, F., and J. Vilmunen (2005), “Price setting in the euro area: some stylised facts from individual consumer price date”, ECB Working paper.
European Central Bank (2001), “Measures of underlying inflation in the euro area”, Monthly Bulletin, July.
European Central Bank (2005), “Recent economic literature on the implications of inflation differentials for monetary policy in a currency area”, Monthly Bulletin, May.
Faust, J. and Leeper, E.M. (1997), “When do long run identifying restrictions give reliable results”, Journal of Business and Economic Statistics, 15.
Folkertsma, C.K. and Hubrich, K.S.E.M. (2000), “Performance of core inflation measures”, De Nederlandische Bank, Research memorandum WO&E, No. 639.
Johnson, M. (1999), “Core inflation: a measure of inflation for policy purposes”, in Bank for International Settlements, “Measures of underlying inflation and their role in the conduct of monetary policy – Proceedings of the workshop of central bank model builders”, 18–19 February, Basel.
Hogan, S., Johnson, M. and Laflèche, T. (2001), “Core inflation”, Technical report No. 89, Bank of Canada.
Kearns, J. (1998), “The distribution and measurement of inflation”, Reserve Bank of Australia Research Discussion Paper, No. 10.
Le Bihan, H, and Sedillot, F. (2000), “Do core inflation measures help forecast inflation? Out of sample evidence from French data”, Economic Letters, Vol. 69.
Marques, C.R., Neves, P.D. and L.M. Sarmento (2000), “Evaluating core inflation indicators”, April.
Meyler, A. (1999), “A statistical measure of core inflation”, Central Bank of Ireland Technical Paper Series, No. 2.
Quah, D.T. and S.P. Vahey (1995), “Measuring core-inflation”, Bank of England, Working paper series n. 31.
Roger, S. (1998), “Core inflation: concepts, uses and measurement”, Reserve Bank of New Zealand, Discussion paper series, n. 9, luglio.
Siviero, S. and Veronese, G. (2006), “A Policy-Sensible Core-Inflation Measure for the Euro Area”, mimeo.
Stock, J.H. and M.W. Watson (1991), “A probability model of the coincident economic indicators”, in K. Lahiri and G.H. Moore (eds.), “Leeding economic indicators: new approaches and forecasting records”, Cambridge, Cambridge University Press.
Vega, J.L. and Wynne, M.A. (2001), “An evaluation of some measures of core inflation for the euro area”, ECB Working paper No. 53.
Wynne, M. (1998), “Background paper on the measurement of core inflation”, European Monetary Institute, mimeo, March.
Appendix: Seasonality versus core inflation
A practical issue which can be analysed in evaluating alternative versions of a core inflation measure based on the a priori exclusion of specific items from the overall basket concerns the treatment of seasonality.
Seasonal movements may be regarded as a “particular” source of noise, in the sense that they affect monthly development of the index but its pattern is quite regular over the years. As known, turning points cannot be readily identified either by changes over the previous period calculated on the raw data (which are affected by seasonal factors) or by changes over the corresponding period of the previous year (which reveal turning points long after they have occurred, since they are affected by developments over the whole year). Hence, an issue is if the core measure should be seasonally adjusted, with figures presented in terms of month-on-month changes, or not. In the first case, turning points would be detected more promptly but at the price of lower trans-parency and revisions in the figures. Besides that, various methodological aspects are involved in the seasonal adjustment process; these concern: (i) the method to use; (ii) the best time span