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Core Inflation in Brazil. André Minella Tomiê Sugahara Research Department - Banco Central do Brasil VIII Annual Seminar August 2006 Work in Progress – Comments are Welcome. Motivation. Core inflation measures are used in most countries, but… Are core inflation measures really useful?

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Core Inflation in Brazil

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Core Inflation in Brazil

André Minella

Tomiê Sugahara

Research Department - Banco Central do Brasil

VIII Annual Seminar

August 2006

Work in Progress – Comments are Welcome


Motivation

  • Core inflation measures are used in most countries,

    but…

  • Are core inflation measures really useful?

  • Do they convey information about “underlying” or future inflation?

  • How do core measures compare to each other?

  • Can new measures, such as those based on common factors, be useful?

    Let’s take a look at what Brazil’s experience says…


Literature

  • Brazil

    • Figueiredo (2001), Bryan and Cecchetti (2001)

    • Pichetti and Toledo (2000), Fiorencio and Moreira (2002), Moreira and Migon (2004), Araújo and Fiorencio (2005)

    • Gonçalves, Schechtman and Barros (2000)

  • Other countries

    • Hogan, Jonhson and Laflèche (2001), Armour (2006)

    • D’Amato, Sanz and Paladino (2006)

    • Cristadoro, Forni, Reichlin and Veronese (2005)

    • Bryan and Cecchetti (1994), Bryan, Cecchetti, and Wiggins II (1997)

    • Roger (1997, 1998)


Presentation outline

  • Core measures properties

  • Core measures for Brazil

    • Current measures

    • New measures

  • Evaluation

    • Variability

    • Bias

    • Capacity to indicate future inflation


Core measures desirable properties

  • Practical issues

    • Timely computable

    • Definite figures (not revisable)

    • Easily understood by the public

  • Substantial issues

    • Reflects “underlying” inflation

    • Forward-looking nature


Core measures in BrazilIPCA index

  • By exclusion

    • Food at home and administered prices are excluded (around 50% of the index)

  • Trimmed mean (non-smoothed)

    • 20% of each tail of weighted distribution is excluded

    • Distribution: Monthly change of IPCA items (47 items up to 1999:7; 52 items 1999:8-2006:6)


IPCA vs. core by exclusion vs. trimmed mean (non smoothed)


Kurtosis – IPCA items


Skewness – IPCA items


IPCA vs. (non-smoothed) trimmed mean using different cutoffs: 20%, 15% and 10%


Core measures in BrazilIPCA index

  • Smoothed trimmed mean

    • For 8 items, y-o-y change instead of m-o-m

  • Asymmetric trimmed mean

    • Bryan and Cecchetti (2001)

    • Centered on the 60th percentile of the weighted distribution

    • 24% cutoff:

      • 14.4% in the bottom tail

      • 9.6% in the upper tail


IPCA vs. smoothed trimmed mean vs. asymmetric trimmed mean


Monthly figures


Core measures in BrazilIPCA index

  • Weighted median

    • Value of the 50th percentile of the weighted distribution

  • Double weighted

    • All items are considered, but they are reweighted according to their volatility: the greater the volatility, the lower the weight


IPCA vs. weighted median vs. double weighted


Core measures in BrazilCore based on common factors

  • Based onCristadoro, Forni, Reichlin and Veronese (2005), index for the Euro Area

  • Use information of a large panel of time series

  • Inflation driven by common factors

  • Core measure: projection of the medium- and long-run component of monthly inflation on the common factors


Core measures in BrazilCore based on common factors

Inflation modeled as:

Core measure:


Core measures in BrazilCore based on common factors

Panel of 106 series

  • Prices

  • Economic activity

  • Money, credit, and financial variables

  • Fiscal sector

  • External sector

  • International economy


IPCA vs. common-factor-based core measure


Bias and variability


Bias and variability


Forecasting


Cogley’s equation


Cogley’s equation


Conclusions (up to this point)

  • Core measures:

    • are less volatile than headline inflation

    • contain information on future inflation

    • but some of them are biased downwards

  • Although results are mixed, Figueiredo’s (2001) result as to the relatively good performance of smoothed trimmed-mean core measure is held

  • Core based on common factors may be promising, but too early to tell - additional research is warranted


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