Abstract
The use of filters for the seasonal adjustment of data generated by the UK new car market is considered. UK new car registrations display very strong seasonality brought about by the system of identifiers in the UK registration plate, which has mutated in response to an increase in the frequency with which the identifier changes, while it also displays low frequency volatility that reflects UK macroeconomic conditions. Given the periodogram of the data, it is argued that an effective seasonal adjustment can be performed using a Butterworth lowpass filter. The results of this are compared with those based on adjustment using X-12 ARIMA and model-based methods.
Original language | English |
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Article number | 4 |
Pages (from-to) | 4-14 |
Number of pages | 10 |
Journal | Computational Statistics & Data Analysis |
Volume | 58 |
Issue number | 1 |
Early online date | 11 Sept 2011 |
DOIs | |
Publication status | Published - Mar 2013 |
Keywords
- Seasonal adjustment; Signal extraction; Frequency response; Butterworth lowpass filter