1. 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

2. 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…

3. 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)

4. Presentation outline Core measures properties Core measures for Brazil Current measures New measures Evaluation Variability Bias Capacity to indicate future inflation

5. 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

6. Core measures in Brazil IPCA 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)

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

8. Kurtosis – IPCA items

9. Skewness – IPCA items

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

11. Core measures in Brazil IPCA 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 60 th percentile of the weighted distribution 24% cutoff: 14.4% in the bottom tail 9.6% in the upper tail

12. IPCA vs. smoothed trimmed mean vs. asymmetric trimmed mean

13. Monthly figures

14. Core measures in Brazil IPCA index Weighted median Value of the 50 th 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

15. IPCA vs. weighted median vs. double weighted

16. Core measures in Brazil Core based on common factors Based on Cristadoro, 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

17. Core measures in Brazil Core based on common factors Inflation modeled as: Core measure:

18. Core measures in Brazil Core based on common factors Panel of 106 series Prices Economic activity Money, credit, and financial variables Fiscal sector External sector International economy

19. IPCA vs. common-factor-based core measure

20. Bias and variability

22. Forecasting

23. Cogley’s equation

25. 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