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Core Inflation: Robust Common Trend Model Forecasting

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  • Ajax R. B. Moreira
  • Hélio S. Migon

Abstract

The monetary authorities need a future measure of in°ation trend to keep on tracking the in°ation on target. Many alternatives of the core in°ation measure have appeared in the recent literature pretending to avoid the de¯ciencies of the usual headline in°ation index as a predictor. This price index is de¯ned as some weighted average of the individual price change of a list of goods and services. To use it as the future in°ation 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 e®ects of each component of the price index and a common trend - the core in°ation - will be developed in this paper. The model will be phrased as a dynamic model and a robust sequential ¯lter 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. Di®erent models will be compared using the minimum posterior predictive loss approach and many graphical illustrations will be presented.

Suggested Citation

  • Ajax R. B. Moreira & Hélio S. Migon, 2015. "Core Inflation: Robust Common Trend Model Forecasting," Discussion Papers 0104, Instituto de Pesquisa Econômica Aplicada - IPEA.
    • Handle: RePEc:ipe:ipetds:0104
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    References listed on IDEAS

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    1. Stephen G. Cecchetti & Erica L. Groshen, 2001. "Understanding Inflation: Implications for Monetary Policy," International Economic Association Series, in: Jacques Drèze (ed.), Advances in Macroeconomic Theory, chapter 7, pages 113-135, Palgrave Macmillan.
    2. Quah, Danny & Vahey, Shaun P, 1995. "Measuring Core Inflation?," Economic Journal, Royal Economic Society, vol. 105(432), pages 1130-1144, September.
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