Signal Extraction from the Components of the Philippine National Accounts Statistics Using ARIMA Model-Based Methodology
The state-of-the-art in signal extraction gradually evolved from the use of mechanical form of moving average filters to the present sophisticated model-based techniques capable of performing automatic modeling and signal extraction involving hundreds or even thousands of time series in one producti...
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| Format: | text |
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Animo Repository
2011
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| Online Access: | https://animorepository.dlsu.edu.ph/res_aki/47 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1074&context=res_aki |
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| Institution: | De La Salle University |
| Summary: | The state-of-the-art in signal extraction gradually evolved from the use of mechanical form of moving average filters to the present sophisticated model-based techniques capable of performing automatic modeling and signal extraction involving hundreds or even thousands of time series in one production run. The leading edge of technology is being shared by two ARIMA model-based systems – ARIMA X12 of the US Bureau of Census and the twin programs TRAMO-SEATS developed at the Bank of Spain. These specialized expert systems have been adopted by most statistical agencies of advanced OECD countries and the European community. The Philippines on the other hand is still using the ARIMA X11 system modified by the Bank of Canada in its routine seasonal adjustment and time series decomposition tasks. This study is an attempt to implement the ARIMA model-based (AMB) approach of extracting unobserved signals from 194 quarterly national accounts statistics of the Philippines using the TRAMO-SEATS system in a fully automatic modeling mode. The successful result of the application adequately demonstrates the feasibility of adopting a system being used routinely by countries in more advanced economies. |
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