Relative poverty across Scottish Local Authorities

Guidance for using these figures

How accurate are these figures?

These figures have been produced from the Scottish Household Survey ( SHS), a large household survey which interviews around 30,000 Scottish families every two years. As with any survey based estimates there is a degree of uncertainty around these estimates because of natural variation within the population. More accurate estimates can be obtained by bigger sample sizes and so the most accurate estimates here are the Scotland level estimates which are based upon the entire SHS sample.

The local authority estimates presented here are based on the SHSLA samples which are naturally smaller than the national sample and so these estimates are less accurate than the national figures. The SHS does not have an equal sample in every local authority and so estimates for LAs with bigger samples, such as Edinburgh and Glasgow are more accurate than those for LAs such as Shetland or Eilean Siar which have smaller samples.

Another source of uncertainty around these estimates is that the method used to link SHS data to the Family Resources Survey involves a random process and this too adds a degree of uncertainty to the estimates. The relatively small sample sizes for some LAs however, are the main source of variation in the data.

What can we say with these figures?

Readers will have noticed that there are error bars on the charts and these are around +/-2 or 3 percentage points for most LAs. These are estimates of the 95% confidence intervals for these figures which have been calculated from estimates of the variability within the SHS data and the degree to which the process used to produce these figures added to that.

The size of these confidence intervals, and the fact that the figures are presented using a four-year rolling average means that interpretations based on small, annual changes should be made with caution. The reasons for this are that:

• What appears as a small increase or reduction of poverty on an annual level may simply be the result of natural variation within the data.
• As we are using a four-year rolling average, for any two consecutive points three quarters of the data used to calculate the two figures will be the same.

These figures are most useful for tracking long-term changes in income and poverty rates at LA level. The most robust comparisons between figures for different years will be between those based on non-overlapping four year intervals. This would ensure that comparisons were made on completely separate samples of households within the local authority. In practise this will not always be possible and past trends, as well as the size of the confidence intervals for a particular LA will help to inform judgements.

Are these figures available below LA level?

The Scottish Household Survey is designed to produce robust LA-level figures every two years and SG analysts currently have no plans to publish SHS figures below LA level.

For some topics and for some areas it may be possible to produce analysis for geographical areas smaller than LAs by, for example, aggregating several year's data. If users require analysis below LA level they should contact the income and poverty statistics team to discuss their requirements. It may be possible to carry out an ad-hoc analysis or for users to obtain the SHS data and produce figures themselves.

Can I get hold of the data?

The Scottish Household Survey data is available on the UK data archive for registered users to download. See the SHS section of the Scottish Government website for further information about obtaining these data.

During the work to produce these figures the Scottish Government income and poverty statistics team have produced a number of additional SHS variables, including an imputed total household income and household relative poverty variable. These could be linked to SHS datasets via the unique household identifier number. The income and poverty statisticians are currently considering the best way to make these additional data available to users. Users who are interested in using these variables should contact the team on the number below.