2001年-ECB欧洲央行_Measures_of_underlying_inflation_in_the_euro_area_11页_157kb

Summary of Measures of Underlying Inflation in the Euro Area

Core Content

The European Central Bank (ECB) defines price stability as a year-on-year increase in the Harmonised Index of Consumer Prices (HICP) for the euro area of below 2%, to be maintained over the medium term. The HICP is used to quantify this objective because it is a homogeneous statistic that closely represents the price of the basket of goods and services consumed by private households. However, the HICP is subject to short-term fluctuations caused by sector-specific or idiosyncratic price changes, which may obscure underlying inflation trends. To address this, various measures of underlying inflation have been developed to isolate persistent and generalised price trends.

Main Approaches to Measuring Underlying Inflation

There are two broad approaches to measuring underlying inflation:

1. Time Series Approach: Focuses on identifying the persistent component of inflation by filtering out temporary fluctuations.
2. Cross-Section Approach: Seeks to distinguish between common price changes and relative price changes by examining the distribution of individual price changes.

Time Series Approach

• Smoothing Techniques: Use moving averages to estimate the trend component of inflation. These are simple but may be slow to reflect new trends.
• Dynamic Factor Index (DFI): Assumes that both idiosyncratic and common price components follow mean-reverting models. It accounts for persistence in price changes and is used to estimate underlying inflation.
• Vector Autoregressions (VARs): Based on economic theory, they identify the part of headline inflation that has no long-term effect on real variables, suggesting that underlying inflation reflects the trend component.

Cross-Section Approach

• Exclusion-Based Measures: Remove specific volatile components from the HICP. Common exclusions include energy products and unprocessed food.
• Variability-Adjusted Measures: Assign weights to price changes based on historical volatility. The Edgeworth index is an example, where prices are weighted by the inverse of their variance.
• Trimmed Means: Exclude the top and bottom percentage of price changes in the distribution. This approach is more flexible than exclusion-based measures but may still be influenced by statistical rather than economic criteria.

Key Information

• Exclusion-Based Measures are the most commonly used. They exclude items like energy and unprocessed food, which have historically shown high volatility.
• Variability-Adjusted Measures, such as the Edgeworth index, reduce the impact of volatile items by adjusting their weights. However, they may not always align with the HICP weights.
• Trimmed Means are a statistical method that excludes the most extreme price changes. They are more dynamic than exclusion-based measures but can sometimes exclude items that are not representative of general inflation trends.
• The ECB monitors these measures regularly and uses them for policy analysis and reporting, such as in the Monthly Bulletin.

Limitations and Ambiguities

• The concept of underlying inflation is not universally agreed upon, and different methodologies lack a consistent theoretical foundation.
• Many measures rely on statistical techniques rather than economic theory, leading to potential inconsistencies in their interpretation.
• None of the measures can be considered reliable as a primary indicator for policy decisions due to their varying effectiveness and potential for misinterpretation.

Conclusion

While measures of underlying inflation can help identify long-term price trends and the sources of shocks affecting headline inflation, they are not without limitations. The ECB continues to monitor and use these measures as part of its analysis, but they are not used as key policy indicators. The choice of method depends on the purpose and the time horizon considered, and no single measure is universally accepted or preferred.