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Forecasting Brazilian Inflation Using a Large Data Set

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  • Francisco Marcos Rodrigues Figueiredo

Abstract

The objective of this paper is to verify if exploiting the large data set available to the Central Bank of Brazil, makes it possible to obtain forecast models that are serious competitors to models typically used by the monetary authorities for forecasting inflation. Some empirical issues such as the optimal number of variables to extract the factors are also addressed. I find that the best performance of the data rich models is usually for 6-step ahead forecasts. Furthermore, the factor model with targeted predictors presents the best results among other data-rich approaches, whereas PLS forecasts show a relative poor performance.

Suggested Citation

  • Francisco Marcos Rodrigues Figueiredo, 2010. "Forecasting Brazilian Inflation Using a Large Data Set," Working Papers Series 228, Central Bank of Brazil, Research Department.
  • Handle: RePEc:bcb:wpaper:228
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    File URL: http://www.bcb.gov.br/pec/wps/ingl/wps228.pdf
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    References listed on IDEAS

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    1. Ard H.J. den Reijer, 2005. "Forecasting Dutch GDP using Large Scale Factor Models," DNB Working Papers 028, Netherlands Central Bank, Research Department.
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    Cited by:

    1. Tabak, Benjamin M. & Takami, Marcelo & Rocha, Jadson M.C. & Cajueiro, Daniel O. & Souza, Sergio R.S., 2014. "Directed clustering coefficient as a measure of systemic risk in complex banking networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 211-216.
    2. Öğünç, Fethi & Akdoğan, Kurmaş & Başer, Selen & Chadwick, Meltem Gülenay & Ertuğ, Dilara & Hülagü, Timur & Kösem, Sevim & Özmen, Mustafa Utku & Tekatlı, Necati, 2013. "Short-term inflation forecasting models for Turkey and a forecast combination analysis," Economic Modelling, Elsevier, vol. 33(C), pages 312-325.
    3. Eliana González, 2011. "Forecasting With Many Predictors. An Empirical Comparison," BORRADORES DE ECONOMIA 007996, BANCO DE LA REPÚBLICA.

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