5.1 Impact of the review on each QES series

There were 40 quarterly series reviewed. The revisions encompass the full span of the series up to Quarter 4 2025 results and are shown in Tables 3a and 3b. The values reflect the absolute difference between the data adjusted using the new seasonal adjustment models and the data adjusted using the previous seasonal adjustment models, expressed as a proportion, such that:

Revision = |yT – yt|/yt where yT = value from the current review and yt = value from the previous review.

As seen in Tables 3a and 3b the values are small with the largest revision being 0.009.

The data changes arising from the revised seasonal adjusted models are reflected predominantly in shifting the level of the series, but the patterns are generally preserved.

5.2 Impact of the review on total NI employee jobs estimates

The employee jobs estimates for each industry section A-S are individually seasonally adjusted and added to give the total number of seasonally adjusted employee jobs for NI. This figure should not be compared with the combined total of the seasonally adjusted Public & Private series, as these are also individually seasonally adjusted and will not give the same total.

The impact of the seasonal adjustment review on the total numbers of employee jobs is minimal (average absolue quarterly difference of 0.04%), meaning that the seasonal adjustment is quite stable, as can be seen in Table 4 below.

Figure 1: Comparison between the 2026 and 2026 seasonal adjustment models at NI total jobs level, March 2005 to December 2025

7.1 Carrying out the seasonal adjustment review

The seasonal adjustment of each series was reviewed by ONS using X-13ARIMA-SEATS. Each review included:

• assessment of whether the series is seasonal

• choosing the appropriate decomposition type, that is additive or multiplicative

• calculating prior adjustments to be made to the series before seasonal adjustment. For example: temporary prior adjustments for outliers and level shifts; and permanent prior adjustments for trading days, Easter effects and seasonal breaks

• selecting the ARIMA forecasting model

• deciding the lengths of the seasonal and Henderson trend moving averages

• reviewing X-13ARIMA-SEATS diagnostics, both quantitative and visual

• plotting original and seasonally adjusted series

• For series common with the previous review, the old parameters were re-assessed and changed where appropriate.

The first stage of a review is a “default” run where all the models choices (decomposition, ARIMA model, outliers, seasonal and trend moving averages) are made automatically by X-13ARIMASEATS. The outcome from the default run is then refined with the over-riding aim being to fit the simplest appropriate adjustment. The end result is then compared with the choices made in the previous review. A decision to alter previous recommendations or to introduce complications must be supported by evidence and reasonable argument. User-defined files for prior adjustments (rmx and ppp files) from the previous review were tested for significance and updated where necessary, e.g. if transformation type for the series has changed.

This robust approach is taken to avoid uninformative revisions caused by minor changes to seasonal adjustment settings – changes that could easily revert back in the next review.

7.2 Seasonal adjustment models

The recommended seasonal adjustment is shown in Table 5.

[Note 1] TMA (Trend Moving Average) = Length of Henderson Filter
[Note 2] SMA (Seasonal Moving Average) = Order of seasonal moving average

An additive outlier (AO) is a data point which falls out of the general pattern of the trend and seasonal component. Although an outlier may be caused by a random effect, i.e. an extreme irregular point, it may have an identifiable cause such as a strike, bad weather or a pandemic.

A level shift (LS) is an abrupt but sustained change in the underlying level of the time series. The annual seasonal pattern is not changed by a level shift. A temporary change (TC) allows for an abrupt increase or decrease in the level of the series, with an exponentially rapid return to its previous level.

Accessibility contact

Please contact Dissemination Branch for assistance with accessibility requirements or alternative formats. Contact details are:

Email: info@nisra.gov.uk

Telephone: +44 (0)300 200 7836

Dissemination Branch
NISRA
Colby House
Stranmillis Court
BELFAST
BT9 5RR