Abstract
The study aims to explore the feasibility of adopting for inflation forecasting a sophisticated expert system normally used in routine outlier detection and deseasonalization of time series. Known as TRAMO/SEATS expert system, this twin program is a fully automatic procedure that extracts the trend-cycle, seasonal, irregular and certain transitory components of high frequency time series via the so-called ARIMA-model-based method. The results of the study reveal the feasibility of the use of the technique for routine inflation forecasting. The automatic model building capability of TRAMO/SEATS is exploited to arrive at an ex-ante model that has the ability to generate optimal forecasts. The results show the ability of the final model to forecast inflation with remarkable accuracy.
Recommended Citation
Rufino, Cesar C.
(2010)
"Forecasting Philippine Monthly Inflation Using TRAMO/SEATS,"
DLSU Business & Economics Review: Vol. 20:
No.
1, Article 3.
DOI: https://doi.org/10.59588/2243-786X.1332
Available at:
https://animorepository.dlsu.edu.ph/ber/vol20/iss1/3
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