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In this paper the long-run trend in CPI inflation (core inflation) for the US over the 1960-2000 period is estimated using a common trends model. In this framework, core inflation is interpreted and constructed as the long-run forecast of inflation conditional on the information contained in nominal money growth, output fluctuations and movements in the oil price. Unlike other commonly used measures of core inflation, the common-trends core inflation rate exploits the long-run link between inflation and monetary growth, a strong feature of the data.
Large price changes in industries affected by the COVID-19 pandemic have caused erratic fluctuations in the U.S. headline inflation rate. This paper compares alternative approaches to filtering out the transitory effects of these industry price changes and measuring the underlying or core level of inflation over 2020-2021. The Federal Reserve’s preferred measure of core, the inflation rate excluding food and energy prices (XFE), has performed poorly: over most of 2020-21, it is almost as volatile as headline inflation. Measures of core that exclude a fixed set of additional industries, such as the Atlanta Fed’s sticky-price inflation rate, have been less volatile, but the least volatile have been measures that filter out large price changes in any industry, such as the Cleveland Fed’s median inflation rate and the Dallas Fed’s trimmed mean inflation rate. These core measures have followed smooth paths, drifting down when the economy was weak in 2020 and then rising as the economy has rebounded. Overall, we find that the case for the Federal Reserve to move away from the traditional XFE measure of core has strengthened during 2020-21.
The monetary authorities need a future measure of inflation trend to keep on tracking the inflation on target. Many alternatives of the core inflation measure have appeared in the recent literature pretending to avoid the deficiencies of the usual headline inflation index as a predictor. This price index is defined as some weighted average of the individual price change of a list of goods and services. To use it as the future inflation indicator is criticized in the literature, as far as the products are heterogeneous in respect to the variability and some of the involved prices have relevant seasonal movements. A multivariate model including simultaneously the seasonal effects of each component of the price index and a common trend - the core inflation - will be developed in this paper. The model will be phrased as a dynamic model and a robust sequential filter will be introduced. The posterior and predictive distributions of the quantities of interest will be evaluated via stochastic simulation techniques, MCMC - Monte Carlo Markov Chain. Different models will be compared using the minimum posterior predictive loss approach and many graphical illustrations will be presented.
N this paper the long-run trend in CPI inflation (core inflation) for Italy is estimated over the 1962-1997 period. The estimates obtained with the Quah and Vahey (1995) bivariate structural VAR methodology and with a multivariate common trends model are compared. The results show the potential advantages for monetary policy of using a more informative common trends model to estimate the core inflation process.
Inflation is regarded by the many as a menace that damages business and can only make life worse for households. Keeping it low depends critically on ensuring that firms and workers expect it to be low. So expectations of inflation are a key influence on national economic welfare. This collection pulls together a galaxy of world experts (including Roy Batchelor, Richard Curtin and Staffan Linden) on inflation expectations to debate different aspects of the issues involved. The main focus of the volume is on likely inflation developments. A number of factors have led practitioners and academic observers of monetary policy to place increasing emphasis recently on inflation expectations. One is the spread of inflation targeting, invented in New Zealand over 15 years ago, but now encompassing many important economies including Brazil, Canada, Israel and Great Britain. Even more significantly, the European Central Bank, the Bank of Japan and the United States Federal Bank are the leading members of another group of monetary institutions all considering or implementing moves in the same direction. A second is the large reduction in actual inflation that has been observed in most countries over the past decade or so. These considerations underscore the critical – and largely underrecognized - importance of inflation expectations. They emphasize the importance of the issues, and the great need for a volume that offers a clear, systematic treatment of them. This book, under the steely editorship of Peter Sinclair, should prove very important for policy makers and monetary economists alike.
This paper provides an overview of statistical measurement issues relating to alternative measures of core inflation, and the criteria for choosing among them. The approaches to measurement considered include exclusion-based methods, imputation methods, limited influence estimators, reweighting, and economic modeling. Criteria for judging which approach to use include credibility, control, deviations from a smoothed reference series, volatility, predictive ability, causality and cointegration tests, and correlation with money supply. Country practice can differ in how the approaches are implemented and how their appropriateness is assessed. There is little consistency in the results of country studies to readily suggest guidelines on accepted methods.
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The ability of central banks to differentiate between permanent & transitory price movements is critical for the conduct of monetary policy. The importance of gauging the persistence of price changes has led to the development of measures of underlying, or ¿core,¿ inflation that are designed to remove transitory price changes from aggregate inflation data. This article examines several proposed measures of core inflation -- the ex food & energy series, an ex energy series, a weighted median series, & an exponentially smoothed series -- to identify a ¿best¿ measure. Evaluates the measures¿ performance according to criteria such as ease of design, & accuracy in tracking trend inflation. Charts & tables.