The views expressed in this report are solely those of the author. No responsibility for them should be attributed to the Bank of Canada. ISSN 0713-7931 ISBN 0-662-25101-6 Printed in Canada on recycled paperACKNOWLEDGMENTS iii The work on this project has been a co-operative effort. The credit for the development of the extended multivariate filter rightly belongs to Doug Laxton, David Rose and Jean Xie, with considerable input from Bob Tetlow and the programming skills of Hope Pioro. Both Laxton and Xie left the Research Department after the initial development work was completed, at which time I became involved in the project. The implementation and documentation were completed by me.

This paper uses scanner price data collected in retail stores to document that (i) although the average magnitude of price changes is large, a substantial number of price changes are small in absolute value; (ii) the distribution of non-zero price changes has fat tails; and (iii) stores tend to adjust prices of goods in narrow product categories simultaneously. I present an extension of the standard menu-cost model to a multi-product setting in which firms face economies of scope in the technology of adjusting prices that can account for these higher-order moments of the data. The model, because of its ability to replicate this additional set of micro-economic facts, can generate aggregate fluctuations much larger than those in standard menu costs economies.

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This paper looks at unobserved components models and examines the implied weighting patterns for signal extraction. There are three main themes. The first is the implications of correlated disturbances driving the components, especially those cases in which the correlation is perfect. The second is how setting up models with t \Gamma distributed disturbances leads to weighting patterns which are robust to outliers and breaks. The third is a comparison of implied weighting patterns with kernels used in nonparametric trend estimation and equivalent kernels used in spline smoothing. We also examine how weighting patterns are affected by heteroscedasticity and irregular spacing and provide an illustrative example.

and a visiting consultant with the Federal Reserve Bank of Cleveland.

1 The decomposition of real GDP into trend and cycle remains a problem of considerable practical importance, but two widely used methods yield starkly different results. The unobserved component approach, introduced by Harvey (1985) and Clark (1987), implies a very smooth trend with a cycle that is large in amplitude and highly persistent. In contrast, the approach of Beveridge and Nelson (1981) implies that much of the variation in the series is attributable to variation in the trend while the cycle component is small and noisy. This conflict is apparent in Figures 1 and 2 in this paper where the two cycle components are plotted, and has been widely noted; see Watson (1986) Stock and Watson (1988) among others. It should surprise us that the unobserved component (UC) and Beveridge-Nelson (BN) methods produce very different trend-cycle decompositions since both are modelbased. Each implies an ARIMA representation. Neither imposes smoothness in the trend component a priori as does the smoother of Hodrick and Prescott (1997) or as in the polar case of a linear trend that forces all variation, save constant growth, into the cycle. The UC and BN both "let the data speak for itself " in this regard. While it is often stated

1. OECD, Economics Department. The views expressed in this paper are those of the authors and do not necessarily represent those of the OECD or of its Member countries. We thank Phil Hemmings and Paul

The structural rate of unemployment and associated non-accelerating inflation rate of unemployment (the NAIRU) are of major importance to the analysis of macro and structural economic developments, although in practice these concepts are not well defined and there is considerable uncertainty and controversy concerning their measurement and policy use. The present paper reviews a range of conceptual and analytical issues and related empirical studies to examine the usefulness and limitations of such concepts. A reduced-form Phillips curve approach is found the most suitable conceptual framework for representing the NAIRU as currently used by the OECD in its policy analysis and surveillance work. Three distinct classes of NAIRU concept are identified, distinguished by the time-frame in which they are defined, which map directly into the broad requirements for macro and structural policy analysis. In line with a number of recent empirical studies, this general approach is applied across the 21 OECD member countries, using methods which combine the estimation of reduced-form Phillips curve equations for each country using alternative filtering methods which allow the identification of time-varying NAIRU indicators.

This paper conducts counterfactual historical analysis of several monetary policy rules by contrasting actual settings of instrument variables with values that would have been specified by the rules in response to prevailing conditions. Of particular interest is whether major policy mistakes, judged ex post, would have been prevented by candidate rules. The rules studied include those of Taylor and McCallum, previously considered by Alison Stuart, plus several additional combinations of instrument and target variables. The time spans examined are 1962-1998 for the U.S. and U.K., and 1972-1998 for Japan. In addition to various substantive findings, the paper develops several methodological arguments. A surprising result is that rules ’ messages are evidently more dependent upon the specification of their instrument than their target variable.

Dans ce papier, on jauge l'utilit de plusieurs estimations (univaries autant que multivaries) de l'cart de production pour prvoir le taux d'inflation. Une analyse ex post suggre que plusieurs de ces estimations aident prdire l'inflation. Nanmoins, les erreurs de prdictions hors de l'enchantillon qui se sont construites avec les carts de production estims en temps rel indiquent que cette amlioration de prdiction est illusoire. On trouve que l'utilit des carts de production pour prdire l'inflation a t exagre et que les prdictions faites avec l'cart de production sont souvent moins prcises que celles qui ignorent le concept d'un cart de production.