Forecasting Philippine monthly inflation using TRAMO/SEATS
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-...
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oai:animorepository.dlsu.edu.ph:faculty_research-20342024-05-03T05:11:51Z Forecasting Philippine monthly inflation using TRAMO/SEATS Rufino, Cesar C. 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. © 2010 De La Salle University, Manila, Philippines. 2010-01-01T08:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/1035 info:doi/10.3860/ber.v20i1.1665 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2034/type/native/viewcontent/ber.v20i1.1665 Faculty Research Work Animo Repository |
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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. © 2010 De La Salle University, Manila, Philippines. |
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Rufino, Cesar C. |
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Rufino, Cesar C. Forecasting Philippine monthly inflation using TRAMO/SEATS |
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Rufino, Cesar C. |
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Rufino, Cesar C. |
title |
Forecasting Philippine monthly inflation using TRAMO/SEATS |
title_short |
Forecasting Philippine monthly inflation using TRAMO/SEATS |
title_full |
Forecasting Philippine monthly inflation using TRAMO/SEATS |
title_fullStr |
Forecasting Philippine monthly inflation using TRAMO/SEATS |
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Forecasting Philippine monthly inflation using TRAMO/SEATS |
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forecasting philippine monthly inflation using tramo/seats |
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2010 |
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https://animorepository.dlsu.edu.ph/faculty_research/1035 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2034/type/native/viewcontent/ber.v20i1.1665 |
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