Estimators for IPCA core inflation Francisco Marcos R. Figueiredo Roberta Blass Staub June 7 th, 2001 Research Department Central Bank of Brazil

Research Department – Central Bank of Brazil 1 - Motivation  Relevant inflation for Central Bank  Core inflation as a common indicator within Mercosur

Research Department – Central Bank of Brazil 2 – Core inflation measures used by Central Banks

Research Department – Central Bank of Brazil 3 – Core inflation in Brazil  FGV - trimmed mean with smoothed components (IPC-BR)  IPEA - common trend of prices and smoothed trimmed mean  Pichetti & Toledo - dynamic factor index and asymmetric trimmed mean  Central Bank - trimmed mean with smoothed components

Research Department – Central Bank of Brazil 4 – Desired characteristics of a core measure  Timely computable  Forward looking nature  Good performance in description of the evolution of the inflation in the past  Easy understanding  Definitive  Theoretical base

Research Department – Central Bank of Brazil 5 – Statistical features of core inflation  Less volatile than the headline inflation  Long run stable relation with inflation  Inflation attractor (time precedence)

Research Department – Central Bank of Brazil 6 - Core inflation estimates  Exclusion method  Symmetric trimmed mean with smoothed series  Asymmetric trimmed mean

Research Department – Central Bank of Brazil 7 - Exclusion method  IPCA less food at home and administered prices  Excluded items amount 46% of IPCA basket

Research Department – Central Bank of Brazil 8 – Exclusion method Chart 1 - IPCA and exclusion core, Jan/96 through Apr/2001

Research Department – Central Bank of Brazil 9 – Symmetric Trimmed mean %% %%(1-2  )%

Research Department – Central Bank of Brazil % Trimmed mean

Research Department – Central Bank of Brazil 11 – 20% Trimmed mean Chart 2 - IPCA and 20% trimmed-mean core, Jan/96 through Apr/2001

Research Department – Central Bank of Brazil 12 - Bryan & Cecchetti core  Bryan and Cecchetti (2001) Asymmetric trimmed mean centered at 60 th percentile 24-month moving average  Optimal trims 14.4% - lower tail 9.6% - upper tail

Research Department – Central Bank of Brazil 13- Bryan & Cecchetti core Chart 3 - IPCA e Bryan & Cecchetti core, Jan/96 through Apr/2001

Research Department – Central Bank of Brazil 14 - Statistics of core inflation measures

Research Department – Central Bank of Brazil 15 - Granger causality tests  Exclusion core does not cause IPCA is caused by IPCA  Trimmed 20 core causes IPCA ( 2 lags) is not caused by IPCA  Bryan & Cecchetti core causes IPCA is not caused by IPCA

Research Department – Central Bank of Brazil 16 - Impulse response from a bivariate VAR Response of IPCA to IPCA IPCA and Trim 20 - Response to One S.D. Innovations ± 2 S.E.

Research Department – Central Bank of Brazil 17 - Concluding remarks  A essential tool to track the inflation trend path  Use a set of core inflation indicators

Research Department – Central Bank of Brazil 18 - Further research  Use bootstrapping procedures to check the optimal trims in symmetric and asymmetric trimmed means  Combine different core inflation estimates