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Using Seasonal Models to Forecast Short-Run Inflation in Mexico

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  • Carlos Capistrán
  • Christian Constandse
  • Manuel Ramos Francia

Abstract

Since the adoption of inflation targeting, the seasonal appears to be the component that explains the major part of inflation's total variation in Mexico. In this context, we study the performance of seasonal time series models to forecast short-run inflation. Using multi-horizon evaluation techniques, we examine the real-time forecasting performance of four well-known seasonal models using data on 16 indices of the Mexican Consumer Price Index (CPI), including headline and core inflation. These models consider both, deterministic and stochastic seasonality. After selecting the best forecasting model for each index, we apply and compare two methods that aggregate hierarchical time series, the bottom-up method and an optimal combination approach. The best forecasts are able to compete with those taken from surveys of experts.

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File URL: http://www.banxico.org.mx/publicaciones-y-discursos/publicaciones/documentos-de-investigacion/banxico/%7BC394E560-3F85-FE01-0EF0-7560FA06AB9A%7D.pdf
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Bibliographic Info

Paper provided by Banco de México in its series Working Papers with number 2009-05.

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Date of creation: Jul 2009
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Handle: RePEc:bdm:wpaper:2009-05

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Web page: http://www.banxico.org.mx
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Related research

Keywords: Aggregated forecasts; bottom-up forecasting; forecast combination; hierarchical time series; inflation targeting; multi-horizon evaluation; seasonal unit roots.;

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Cited by:
  1. José Julián Sidaoui & Carlos Capistrán & Daniel Chiquiar & Manuel Ramos Francia, 2009. "A Note on the Predictive Content of PPI over CPI Inflation: The Case of Mexico," Working Papers 2009-14, Banco de México.
  2. Raúl Ibarra-Ramírez, 2010. "Forecasting Inflation in Mexico Using Factor Models: Do Disaggregated CPI Data Improve Forecast Accuracy?," Working Papers 2010-01, Banco de México.

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