How we mapped working-age poverty risk by parliamentary constituency

We have mapped the risks of working-age poverty across Great Britain, looking at out-of-work benefits, in-work tax credits, low pay and skill levels to provide a constituency-level snapshot of where high levels of working-age poverty are most likely to exist.

In a new-style blog focussing on our data methodology, JRF’s head of analysis Helen Barnard explains how we went about it.

Why are we mapping poverty risk?

Poverty exists in all parts of the country and requires solutions which reach every area. This analysis focuses on working-age households. It uses published data to show which parliamentary constituencies have high levels of people claiming out-of-work benefits or in-work tax credits. Benefit and tax credit receipt are not perfect measures of poverty, but they provide a good indicator of people with a high risk of experiencing poverty, since most of them are only available to people on low incomes.  

What do the maps show?

As well as the Risk Index, which combines information about the risk of out-of-work and in-work poverty, there are maps showing these separately. Alongside the Working-Age Poverty Risk Index, there are maps focusing on two of the underlying drivers of poverty: low skills and low earnings.

What data did we use?

The analysis uses indicators drawn from JRF’s Inclusive Growth Monitor. The Working Age Poverty Risk Index combines data on the receipt of out-of-work and in-work benefits to generate a poverty risk score for each parliamentary constituency in Great Britain. High risk scores mean a constituency has high levels of in- and/or out-of-work benefit receipt – two factors strongly associated with poverty. Low scores mean a constituency has lower levels on these indicators.

Poverty Risk by Parliamentary Constituency

‘Working Age Poverty Risk Index’ scores for constituencies across Great Britain.

How are constituencies ranked?

For each indicator that makes up the risk index, a constituency is given a score between 0 and 10, where 0 is the constituency with the lowest rate and 10 is the constituency with the highest rate. (Further details of the methodology for generating the scores, and the indicators themselves, are available as part of the inclusive growth monitor.) The scores are then combined, with a weighting applied to reflect the fact that a greater proportion of working-age adults in poverty live in working families than workless families. (The out-of-work benefit score is weighted to make up 34% of the final risk score with the in work tax credit score making up 66%. These values represent the ratio of out-of-work to in-work poverty amongst working age adults in HBAI 2014/15.)

The final risk score for a constituency will be between 0 and 10, where 0 would be a constituency with both the lowest rate of in-work benefit receipt and the lowest rate of tax credit receipt and 10 would be a constituency with the highest rates on both indicators. In practice, because there is variation in where constituencies rank across the two indicators, the highest score is 8.5 (Bradford West) and the lowest score is 0.1 (Wimbledon).

Is any other data involved?

A range of additional indicators, also based on the inclusive growth monitor, have also been published alongside the risk index to provide further information. We have made an adjustment to the in-work tax credit indicator to take account of multiple benefit unit households. This involves multiplying the number of working households in the calculation by 1.2 (the ratio of working benefit units to working households in FRS2014/15). 

The data sources for all of the indicators are summarised below and draw on the most up-to-date information available:

  • In-work tax credit propensity: 2014. The proportion of working families in receipt of tax credits are an estimate, based on dividing the number of working benefit units receiving tax credits by the total number of working benefit units. Tax credit receipt taken from HMRC data. Number of working benefit units based on working and workless households via NOMIS, with an adjustment applied to account for multi-benefit unit households, based on the ratio of working benefit units to working households in FRS 2014/15 (1.2 : 1).
  • Proportion of population without NVQ level2 qualification:  Annual Population Survey. Three year averages (2014-16). Data via Nomis, Great Britain.
  • 20th percentile full time gross weekly earnings: Annual Survey of Hours and Earnings 2016. Data via Nomis, Great Britain.
  • Ratio of lower quartile full-time annual earnings to house prices. 2016. Earnings data from Annual Survey of Hours and Earnings via Nomis. House price data from ONS. Where annual earnings were not available annualised, gross weakly earnings were used. England and Wales.
  • Proportion of working-age population in receipt of out-of-work benefits: August 2016. Work and Pensions Longitudinal study, available via Nomis, Great Britain.

See the results here: Working-Age Poverty Risk Index 2017 

Let us know in the comments area whether you found this blog useful and whether you'd like to hear more about our data methodologies.