|Unit||Ch. Vol. Index 2016=100, SA|
|Business Confidence||Jun 2019||-10.8||-10.5||Bal. of Op., SA||Monthly|
|Capacity Utilization||2019 Q2||80.7||81.4||%, SA||Quarterly|
|Industrial Production||May 2019||102.7||101.3||Ch. Vol. Index 2016=100, SA||Monthly|
|Change in Inventories||2019 Q1||3,612||4,448||Mil. GBP, SA||Quarterly|
|Real Change in Inventories||2019 Q1||5,711||4,241||Mil. Ch. 2016 GBP, SA||Quarterly|
Industrial production in the U.K. by detailed UKSIC (NACE) categories. Chained volume measures, as indexes and percent changes. Monthly, quarterly and annual.
The non-seasonally adjusted series contain elements relating to the impact of the standard reporting period, moving holidays and trading day activity. When making comparisons it is recommended that users focus on seasonally adjusted estimates as these have the seasonal effects and systematic calendar related components removed.
The Index of Production uses a variety of different data from sources which are produced on either a quarterly or monthly basis.
Most of the series are derived using current price turnover deflated by a suitable price index. This includes the Monthly Business Survey (MBS) data; an ONS short-term survey of various industries in the economy. It is one of the main data sources used in the compilation of the Index of Production.
The index numbers in this statistical bulletin are all seasonally adjusted. This aids interpretation by removing annually recurring fluctuations, for example, due to holidays or other regular seasonal patterns. Unadjusted data are also available.
Seasonal adjustment removes regular variation from a time series. Regular variation includes effects due to month lengths, different activity near particular events such as shopping activity before Christmas, and regular holidays such as the May bank holiday. Some features of the calendar are not regular each year, but are predictable if we have enough data - for example the number of certain days of the week in a month may have an effect, or the impact of the timing of Easter. As Easter changes between March and April we can estimate its effect on time series and allocate it between March and April depending on where Easter falls. Estimates of the effects of day of the week and Easter are used respectively to make trading day and Easter adjustments prior to seasonal adjustments.
Although leap years only happen every four years, they are predictable and regular and their impact can be estimated. Hence, if there is a leap year effect, it is removed as part of regular seasonal adjustment.
It is common for the value of a group of financial transactions to be measured in several time periods. The values measured will include both the change in the volume sold and the effect of the change of prices over that year. Deflation is the process whereby the effect of price change is removed from a set of values.
All series, unless otherwise quoted, are chained volume measures. Deflators adjust the value series to take out the effect of price change to give the volume series.
Figures for the most recent months are provisional and subject to revision in light of (a) late responses to surveys and administrative sources and (b) revisions to seasonal adjustment factors which are re-estimated every month and reviewed annually (changes from the latest review are included in this release).