1. Alternative measures to evaluate core inflation Banco Central do Brasil seminar on core inflation and price indices harmonization

2. Conceptions of core inflation Persistent element of inflation, excluding transient supply shocks. Generalized element of inflation excluding relative price shocks. Empirical issue: is generalized inflation persistent?

3. Alternative approaches Variety of approaches discussed in Roger (1998) and Wynne (1999). Empirical focus has been primarily on estimating the generalized component of CPI inflation. Time-series versus cross-sectional approaches to generalized inflation.

4. The stochastic approach Price movements in each period viewed as core inflation plus relative price shocks. If relative price shocks distributed normally, sample mean inflation is unbiased, lowest volatility estimate of generalized, core inflation. But distribution rarely normal – typically high kurtosis and right-skewed.

5. High kurtosis, right skewness

6. Implications of high kurtosis Mean inflation rate an inefficient (volatile) estimator of generalized inflation. 3 main approaches to trying to get a better estimator: Exclusion-based measures (e.g. CPI ex volatiles); Volatility-adjusted measures (neo-Edgeworthian); Robust measures (e.g. trimmed means).

7. Skewness/asymmetry Right-skewness indicates asymmetry: extreme price rises larger than extreme price declines. Can lead to undesirable downward bias to core measures if symmetry assumed. Alternative sources of positive skewness: Arithmetic versus log-normal price change; Infrequent price adjustment.

8. Log-normal price changes If price changes are log-normal, percentage changes will show chronic right-skewness. Skewness independent of inflation rate.

9. Infrequent price adjustment Reasons for infrequent price adjustment: Seasonal supply; Infrequent measurement of prices; Infrequent adjustment of administered prices; Stickiness in private sector prices. Theory has focused on 4 th factor, but evidence mainly for 1 st – 3 rd factors. Important consequence: asymmetry and bias no longer independent of level of inflation.

10. Dealing with asymmetry Log-normality: Fix the CPI. Increase use of geometric averaging in CPI construction. Infrequent price adjustment: Seasonal adjustment of CPI components. For residual asymmetry, use of asymmetric trimming.

11. Evaluation of measures For public accountability purposes: All 3 types of measures available on timely basis. All 3 transparent & verifiable. Minimal bias vs. CPI feasible. Exclusion-based easier to explain than others. For internal policy formulation purposes: Volatility & forecasting properties very important - Marques et al (2000) criteria, not Bryan & Cecchetti. Performance in structural models & forecasting.

12. Which measures are best? Evidence from Asia-Pacific suggests: Exclusion-based measures always show poor performance. Volatility-adjusted measures smooth, but exclude signal as well as noise. Trimmed means – only work well if over 20%. Efficiency gains over CPI about as expected from Roger (2000): 30 to 50 percent reduction in volatility of changes in quarterly inflation.

13. Observations Construction of core measures: Inter-temporal aggregation should be linked to policy decision-making; Cross-sectional aggregation should be linked to external accountability needs; Consider use of seasonally-adjusted data; Interpolation between discrete points may be useful in trimmed means.

14. Observations Use of core measures: Variety of measures for public accountability; Best technical measure for policy formulation. Generalized, transient shocks: VAT type shocks – relatively easy to remove; Exchange rate shocks – how and whether to remove – a policy issue, not just a technical one.