Alternative measures to evaluate core inflation

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 4th factor, but evidence mainly for 1st – 3rd 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 publicaccountability; • 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.