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A Factorial Decomposition Of Inflation In Peru, An Alternative Measure Of Core Inflation

Author

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  • Alberto Humala

    ()

  • Gabriel Rodríguez

    () (Departamento de Economía - Pontificia Universidad Católica del Perú)

Abstract

A dynamic factorial decomposition model of inflation is estimated using Peruvian monthly data for 1995:01-2008:07. This model allows identification of changes in three relevant ináation components: idiosyncratic relative prices, aggregate relative prices, and absolute prices. Furthermore, following Reis and Watson (2007), the model allows measuring pure inflation as the common factor in the inflation rate that has a proportionate effect to all prices and that is not correlated with relative price changes at any period of time. This pure inflation estimate relates closely to standard measures of core inflation. Results are robust to different lag structures and various stochastic assumptions on the estimated factors.

Suggested Citation

  • Alberto Humala & Gabriel Rodríguez, 2011. "A Factorial Decomposition Of Inflation In Peru, An Alternative Measure Of Core Inflation," Documentos de Trabajo / Working Papers 2011-315, Departamento de Economía - Pontificia Universidad Católica del Perú.
    • Handle: RePEc:pcp:pucwps:wp00315
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    File URL: http://files.pucp.edu.pe/departamento/economia/DDD315.pdf
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    References listed on IDEAS

    as
    1. Jean Boivin & Marc P. Giannoni & Ilian Mihov, 2009. "Sticky Prices and Monetary Policy: Evidence from Disaggregated US Data," American Economic Review, American Economic Association, vol. 99(1), pages 350-384, March.
    2. Altissimo, Filippo & Mojon, Benoit & Zaffaroni, Paolo, 2009. "Can aggregation explain the persistence of inflation?," Journal of Monetary Economics, Elsevier, vol. 56(2), pages 231-241, March.
    3. Cristadoro, Riccardo & Forni, Mario & Reichlin, Lucrezia & Veronese, Giovanni, 2001. "A Core Inflation Index for the Euro Area," CEPR Discussion Papers 3097, C.E.P.R. Discussion Papers.
    4. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    5. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    6. Marlene Amstad & Simon M. Potter, 2009. "Real time underlying inflation gauges for monetary policymakers," Staff Reports 420, Federal Reserve Bank of New York.
    7. Michal Brzoza-Brzezina & Jacek Kotlowski, 2009. "Estimating pure inflation in the Polish economy," Working Papers 37, Department of Applied Econometrics, Warsaw School of Economics.
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    Cited by:

    1. Wojciech Charemza & Imran Husssain Shah, 2013. "Stability price index, core inflation and output volatility," Applied Economics Letters, Taylor & Francis Journals, vol. 20(8), pages 737-741, May.

    More about this item

    Keywords

    Factoral Decomposition / Pure Inflation / Core Inflation / Price Changes;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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