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Multi-horizon inflation forecasts using disaggregated data

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  • Capistrán, Carlos
  • Constandse, Christian
  • Ramos-Francia, Manuel

Abstract

In this paper we use multi-horizon evaluation techniques to produce monthly inflation forecasts for up to twelve months ahead. The forecasts are based on individual seasonal time series models that consider both, deterministic and stochastic seasonality, and on disaggregated Consumer Price Index (CPI) data. After selecting the best forecasting model for each index, we compare the individual forecasts to forecasts produced using two methods that aggregate hierarchical time series, the bottom-up method and an optimal combination approach. Applying these techniques to 16 indices of the Mexican CPI, we find that the best forecasts for headline inflation are able to compete with those taken from surveys of experts.

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Bibliographic Info

Article provided by Elsevier in its journal Economic Modelling.

Volume (Year): 27 (2010)
Issue (Month): 3 (May)
Pages: 666-677

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Handle: RePEc:eee:ecmode:v:27:y:2010:i:3:p:666-677

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Web page: http://www.elsevier.com/locate/inca/30411

Related research

Keywords: Aggregated forecasts Bottom-up forecasting Forecast combination Hierarchical time series Inflation targeting Seasonal unit roots;

References

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  1. 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.
  2. Etienne Gagnon, 2007. "Price setting during low and high inflation: evidence from Mexico," International Finance Discussion Papers 896, Board of Governors of the Federal Reserve System (U.S.).
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  4. Daniel Chiquiar & Antonio Noriega & Manuel Ramos-Francia, 2010. "A time-series approach to test a change in inflation persistence: the Mexican experience," Applied Economics, Taylor & Francis Journals, vol. 42(24), pages 3067-3075.
  5. Capistran, Carlos, 2006. "On comparing multi-horizon forecasts," Economics Letters, Elsevier, vol. 93(2), pages 176-181, November.
  6. Duarte, Claudia & Rua, Antonio, 2007. "Forecasting inflation through a bottom-up approach: How bottom is bottom?," Economic Modelling, Elsevier, vol. 24(6), pages 941-953, November.
  7. Ghysels, Eric & Osborn, Denise R. & Rodrigues, Paulo M.M., 2006. "Forecasting Seasonal Time Series," Handbook of Economic Forecasting, Elsevier.
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  9. Hyndman, Rob J. & Ahmed, Roman A. & Athanasopoulos, George & Shang, Han Lin, 2011. "Optimal combination forecasts for hierarchical time series," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2579-2589, September.
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  12. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, 02.
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  16. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
  17. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
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  20. Philip Hans Franses, 2007. "Constant vs. Changing Seasonality," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 6, pages 24-25, Spring.
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Citations

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Cited by:
  1. Carlos Medel, 2012. "How Informative are In–Sample Information Criteria to Forecasting? The Case of Chilean GDP," Working Papers Central Bank of Chile 657, Central Bank of Chile.
  2. Rob J Hyndman & Alan Lee & Earo Wang, 2014. "Fast computation of reconciled forecasts for hierarchical and grouped time series," Monash Econometrics and Business Statistics Working Papers 17/14, Monash University, Department of Econometrics and Business Statistics.
  3. Robinson Durán & Evelyn Garrido & Carolina Godoy & Juan de Dios Tena, 2012. "Predicción de la inflación en México con modelos desagregados por componente," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 27(1), pages 133-167.
  4. Pablo Pincheira & Carlos A. Medel, 2012. "Forecasting Inflation with a Simple and Accurate Benchmark: a Cross-Country Analysis," Working Papers Central Bank of Chile 677, Central Bank of Chile.

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