![]() The Bank conducts annual reviews (split into three separate phases each year) of the settings used for seasonal adjustment of published series, and publishes the results via a Statistical article. Some series may be reviewed more frequently. When the seasonal adjustment of a particular series is being reviewed, the Bank considers various diagnostic tests to assess the quality of potential seasonal adjustment to ensure that the final seasonal adjustment is of as high a quality as possible. The method chosen is whichever is shown to give a better seasonal adjustment of the total aggregate. Aggregation considerations: Aggregate time series can be adjusted directly or indirectly, as a sum of their components.Footnotes are placed on series that do not show sufficient seasonality to indicate that they have been considered for seasonal adjustment, but are currently not seaso Detection of seasonality: Before seasonally adjusting, various diagnostics are examined to decide whether the series requires seasonal adjustment.Length: X-13ARIMA-SEATS requires a minimum of three years of data to seasonally adjust though a longer span of data is preferred to obtain reliable results.Frequency: Where possible, the seasonally adjusted quarterly series are derived from the corresponding seasonally adjusted monthly series, but in some cases the monthly equivalent is not available or is only available over a very short time span, in which case the quarterly series is seasonally adjusted directly.And the treatment for seasonally adjusting a levels series differs slightly to that for seasonally adjusting a pure flows series Type: Flows series that are derived from levels (stocks) series are not seasonally adjusted directly, but are instead derived from the seasonally adjusted levels series as described below.The following considerations are taken into account when adjusting a series: The Bank seasonally adjusts approximately 400 published series, the majority being of monthly periodicity. The Bank uses the X-12-ARIMA functionality within this package. ![]() The Bank of England seasonally adjusts its data using X-13ARIMA-SEATS. The seasonally adjusted flows for credit card lending to individuals (blue line below), removes both the regular seasonal movements and any calendar effects. For those series where identifiable seasonality is detected, a seasonally adjusted version is also published. These can be explained by more spending in December and lower spending in January.ĭata users are often interested in series which have been adjusted to remove seasonal effects, since these may give a better indication of the underlying movements. The non seasonally adjusted flows for credit card lending to individuals (red line below) show a seasonal peak in December followed by a seasonal trough in January. Calendar effects include effects caused by the number of working days or calendar days in the month, or the dates of particular occasions, such as Easter, within the year – the influence of such effects on a particular month can vary from year to year, but they can be quantified and adjusted.Īn example of a seasonal series is the flow of credit card lending to individuals, where credit card lending tends to increase in December as consumers spend more in the run-up to Christmas. Regular seasonal fluctuations are those movements which, on the basis of the past movements of the time series in question, can under normal circumstances be expected to recur with similar intensity in the same season each year. News and publications Open News and publications sub menu.Option-implied probability density functions Gross Domestic Product Real-Time Database The PRA’s statutory powers and enforcement Money Markets Committee and UK Money Markets Code Greening our Corporate Bond Purchase Scheme (CBPS) Operational resilience of the financial sector Financial market infrastructure supervision
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