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Evaluation of Wavelet-based Core Inflation Measures: Evidence from Peru

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  • Erick Lahura

    () (Departamento de Economía - Pontificia Universidad Católica del Perú, Banco Central de la Reserva del Perú)

  • Marco Vega

    () (Departamento de Economía - Pontificia Universidad Católica del Perú, Banco Central de la Reserva del Perú)

Abstract

Under inflation targeting and other related monetary policy regimes, the identication of non-transitory inflation and forecasts about future inflation constitute key ingredients for monetary policy decisions. In practice, central banks perform these tasks using so-called "core inflation measures". In this paper we construct alternative core inflation measures using wavelet functions and multiresolution analysis (MRA), and then evaluate their relevance for monetary policy. The construction of wavelet-based core inflation measures (WIMs) is relatively new in the literature and their assessment has not been addressed formally, this paper being the first attempt to perform both tasks for the case of Peru. Another main contribution of this paper is that it proposes two alternative criteria for evaluating core inflation measures: (i) a VAR-based long-run criterion, and (ii) forecast-based criteria. Evidence from Peru shows that WIMs are superior in terms of long-run performance, and that they could improve short-term (up-to-6-months) inflation forecasts.

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Bibliographic Info

Paper provided by Departamento de Economía - Pontificia Universidad Católica del Perú in its series Documentos de Trabajo with number 2011-320.

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Length: pages
Date of creation: 2011
Date of revision:
Publication status: published
Handle: RePEc:pcp:pucwps:wp00320

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Postal: Av. Universitaria 1801, San Miguel, Lima, Perú
Phone: (511) 626-2000 ext. 4950, 4951
Fax: (511) 626-2874
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Web page: http://www.pucp.edu.pe/departamento/economia/
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Keywords: Core inflation; wavelets; forecast; structural VAR;

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  1. Olivier Jean Blanchard & Danny Quah, 1990. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," NBER Working Papers 2737, National Bureau of Economic Research, Inc.
  2. Danny Quah & Shaun Vahey, 1995. "Measuring Core Inflation," Bank of England working papers 31, Bank of England.
  3. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Working Papers 02-3, Bank of Canada.
  4. kevin dowd & john cotter, 2011. "U.S. Core Inflation: A Wavelet Analysis," Papers 1103.5659, arXiv.org.
  5. David Baqaee, 2009. "Using wavelets to measure core inflation: the case in New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2009/05, Reserve Bank of New Zealand.
  6. Armas, Adrián & Vallejos , Lucy & Vega, Marco, 2011. "Indicadores tendenciales de inflación y su relevancia como variables indicativas de política monetaria," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 20, pages 27-56.
  7. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  8. Pesaran, M.H. & Timmermann, A., 1990. "A Simple Non-Parametric Test Of Predictive Performance," Papers 29, California Los Angeles - Applied Econometrics.
  9. Ribba, Antonio, 2003. "Permanent-transitory decompositions and traditional measures of core inflation," Economics Letters, Elsevier, vol. 81(1), pages 109-116, October.
  10. Timothy Cogley, 1998. "A simple adaptive measure of core inflation," Working Papers in Applied Economic Theory and Econometrics 98-06, Federal Reserve Bank of San Francisco.
  11. Lahura Serrano, Erick W., 2004. "La relación dinero-producto, brecha del producto e inflación subyacente: algunas aplicaciones de las funciones Wavelets," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 11.
  12. Smith, Julie K, 2004. "Weighted Median Inflation: Is This Core Inflation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(2), pages 253-63, April.
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