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Evaluating Alternative Core Inflation Measures for Argentina

Author

Listed:
  • Laura D´Amato

    (Central Bank of Argentina)

  • PLidia Sanz

    (Central Bank of Argentina)

  • Juan Sotes Paladino

    (Central Bank of Argentina)

Abstract

Monetary policymaking requires an adequate appraisal of price dynamics and reliable forecasts for short and medium term inflation. Since the relevant inflation for monetary policy purpose may not be adequately measured by conventional consumer price indexes, there is a need for core inflation measures that adequately reflect joint and persistent movements in prices. With this aim, eight different measures of core inflation are constructed, based on i) re-weighting of CPI components in a new aggregate index according to the relative significance of each item as a signal of inflation, ii) excluding the most volatile CPI components, or directly those related to food and energy, considered to be less affected by monetary policy, iii) calculating a robust estimator of the first order moment for the cross sectional distribution of CPI inflation that excludes extreme values. These indicators are evaluated on the basis of their ability to predict consumer price inflation. The results indicate that the measure constructed according to criterion i) of signal extraction provides the core inflation indicator with the best relative performance.

Suggested Citation

  • Laura D´Amato & PLidia Sanz & Juan Sotes Paladino, 2005. "Evaluating Alternative Core Inflation Measures for Argentina," BCRA Working Paper Series 200501, Central Bank of Argentina, Economic Research Department.
  • Handle: RePEc:bcr:wpaper:200501
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    More about this item

    Keywords

    Argentina; consumer price index; core inflation measures; inflation;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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