Policy & Insight Team, 30th January 2025

Each month, the Policy and Insight team reviews datasets which give us an idea of how our local economy is doing. This helps us identify key challenges and respond to them.  The data usually includes:

  • The number of people claiming unemployment benefits, their sex, and ages
  • The number of job vacancies in South Tyneside and the types of jobs
  • The proportion of young people not in education, employment, or training
  • How busy the town centres of South Shields, Hebburn, and Jarrow are
  • The number of people employed
  • The number of people not working and the main reasons for this
  • Information about new job creation, large-scale redundancies, and other business news

We put this information in an overview report which you can find here: South Tyneside Data Observatory – Research, Intelligence and Evaluation – Intelligence

This blog is the first in our ‘Monthly Economic Monitor’ series and provides more details about this data and its implications. This month, we focus on the claimant count and what it tells us about sex differences in workforce participation.

What is the ‘Claimant Count’?

Claimant count data is released every month and tells us how many South Tyneside residents are claiming unemployment benefits.

People claiming this benefit must declare that they are out of work, capable of, available for and actively seeking work. This means that this figure doesn’t include people in receipt of benefits but  without work and not actively seeking it.

Under Universal Credit, a broader span of claimants must look for work. As Universal Credit rolls out, the number of people on the Claimant Count is likely to rise.

Claimant Counts and Rates by Age and Sex

Data from November 2024 shows that 5.3% of South Tyneside residents (16-64) were claiming unemployment benefits (4,765 people 16+).

Looking at the North East region, 4.2% of people were claiming this type of benefit in November 2024. This is the same as the percentage of people claiming across England.

We can also look at this data across different age groups. The highest rate was among those aged 18-24 at 8.6% (870 people) and the lowest rate is among those aged 50+ at 3.8% (1,205 people). Around 2,685 people aged 25-49 were claiming this type of benefit in November, a rate of 6%.

This dataset goes all the way back to 1992 and shows that the male claimant rate has always been higher than the female rate. However, the gap has narrowed over time.

This doesn’t mean that males are less likely to be in work. Actually, the opposite is true. Between 2004 and 2023, the male employment rate between January and December of each year was higher than the female rate.

The difference varied, with the male rate being just 1.8 percentage points higher in 2018 and 11.4 percentage points higher in 2023. However, we know that the male rate was significantly higher than the female rate just 6 times.1 Across all 79 quarterly data points, the female employment rate has been higher just twice. In both cases the difference was less than a percentage point and not significant.

Sex Differences in Employment and Economic Inactivity2

The key reason that the female employment rate is lower than the male rate (despite a lower claimant rate) is because of something called economic inactivity. Economically inactive people are without work and not actively seeking it. This figure is shown as a proportion of the working age population (16-64). It includes people who have retired (before 65), are long term sick, temporarily sick, are looking after their family or home, students or are economically inactive due to ‘other reasons’ such as not needing employment.

Across 79 quarterly data points spanning 20 years, the female economic inactivity rate has been consistently higher than the male rate (and significantly higher 64 times).

One reason for this is the difference in the number of male and female students. Historically, more economically inactive males than females tended to give ‘student’ as their reason for inactivity (though the difference was only significant 18 out of 79 times). While this pattern has reversed since 2022, the difference isn’t significant.

The key driver of higher female inactivity is their higher likelihood of looking after family or the home. The data shows significantly more females have been economically inactive for this reason since at least 2004, except for one data point during the pandemic where the difference was not significant.

South Tyneside is not an outlier. Across England in 2023, 6.1 times more females gave this reason than males, though this has more than halved since 2004. The difference is much starker when looking at the 25-49 age group, when people are most likely to be looking after dependent children. In 2023, there were 10 times more females than males inactive for this reason.

Census 2021 data tells us a similar story of who is more likely to take on unpaid care responsibilities.3 In South Tyneside, 12.5% of the female population said they provided some unpaid care, compared to 8.7% of the male population. This means that that of all people who provided unpaid care (aged 5+), 60.5% were female.

In summary

The claimant count data for South Tyneside shows that despite historically higher male claimant rates, males have consistently shown higher employment rates than females.

The data also highlights a significant gender disparity in economic inactivity, with females more likely to be economically inactive due to caregiving responsibilities. This trend is consistent across England, reflecting broader patterns in unpaid care and employment. The higher rate of female economic inactivity shows the ongoing impact of caregiving roles on their participation in the workforce.

Next time

We’ll discuss new data on employment, economic inactivity, and unemployment, focusing on long-term sickness.

Notes

  1. The difference in the number of times the male rate was ‘higher’ and the number of times it was ‘significantly higher’ relates to how the data was collected. For this dataset (and many others), it isn’t practical to ask everyone in the UK about their employment status. Instead, a sample of people are asked, allowing inferences to be made about the wider population.

To account for normal differences between samples, figures are usually provided with ‘confidence intervals’. Confidence intervals provide the range of values we expect the figure to fall within most of the time, in this instance, 95% of the time.

For example, in 2023, the male employment rate was 70.9% with a 95% confidence interval of 3.5. This means that if the survey was conducted 100 times with different samples, we would expect the male employment rate to be between 67.4% and 74.4% 95 of those times.

When comparing figures with confidence intervals, it’s important to consider whether the ranges overlap. If they do, we can’t say the difference is significant.

  1. The employment and inactivity data mentioned in this blog is from the Annual Population Survey (APS). It is the largest ongoing household survey in the UK, based on interviews with the members of randomly selected households. The survey covers a diverse range of topics, including personal characteristics, labour market status, work characteristics, education and health. Currently, APS estimates are designated experimental statistics and should be interpreted with caution. You can read more about that here: Annual Population Survey – Nomis – Official Census and Labour Market Statistics.
  2. In the Census, a person was defined as a provider of unpaid care if they looked after or gave help or support to anyone because of long-term physical or mental health conditions or illnesses, or problems related to old age. This does not include activities as part of paid employment. No distinction is made about whether care is provided within or outside the household.