Council tax is inherently ‘unsexy’. It doesn’t hit the headlines all too often, let alone national news. In the media it’s an oft-neglected, much-maligned thing. In fact, you’re probably already thinking of closing this blog. Why on Earth would I read about council tax? I’d rather read the manual for my oven, or watch paint dry, or… I’ll stop you there. Council tax may not seem interesting, and for some of you it may not be, but it is, in fact, vital for the delivery of local services.
Now more than ever, council tax is essential to local government budgets. The National Audit Office estimates that almost 40% of local authority revenue funding is from council tax. The climate of local government finance is turbulent. Growing service demand, falling central government grants, and the scarring legacy of COVID, all paint a challenging picture for local authorities.
There are, however, two sides to the council tax coin. Balancing budgets is not only a challenge for local authorities. Council tax debts and related enforcement are growing for households across the country. Nationally, an estimated 3 million people have been taken to court over council tax debt over the past year *. This raises an important question: what can we do as a county council to better target support to residents that are most in need?
Well, the first step in answering this question is identifying who and where households who may be struggling are. In order to support our partner organisations, we also wanted to quantify the financial impact of reduced council tax revenue on local authorities across Essex.
Despite the magnitude of the issue, there is a lack of data on council tax collection rates (or at least accessible at a county council level). Internal data is limited: often it’s high-level, complex, and difficult to draw substantive insight from. This meant answering our research questions quickly became a more difficult task than anticipated. Taking a conventional approach, and a healthy dose of assumption, we created a model that simulated that the cost-of-living crisis would have the same fiscal impact as the coronavirus pandemic. This model was simple. We applied district-level 2019-20 collection rates to LSOA-level 2023-24 taxbase. However, it was a blanket approach, and didn’t capture the uneven nature of deprivation. With a far from robust model, and limited access to data, what could we achieve?
After trawling the internet, running through reams of data, and countless discussions, it seemed all hope for a solution was lost. Then Eureka! I found myself seeking inspiration from my fellow ECC Analysts via our Insight Library, the go-to resource for all ECC analysis both past and present. Within minutes, I had found a model I liked that took inspiration from the work of the UCL Jill Dando Institute, to build a model identifying and indexing vulnerability.
The concept of a vulnerability index seemed highly suitable for this project: holistic, dynamic, and ideal for mapping. It simply takes factors which make an area vulnerable to a particular issue, and calculates a score based upon these. In the case of the council tax vulnerability index, these factors include demographics- for instance, people over the age of 65 who are living alone- as well as financial indicators- such as the proportion of people on low discretionary incomes.
The vulnerability index highlighted LSOAs** (lower-level super output areas) with extreme vulnerability to the cost-of-living crisis. Although the index is specific to council tax, arguably the factors which make someone vulnerable to council-tax non-payment also make one vulnerable to the likes of food and fuel poverty.
A question that has arisen many times when presenting this work is ‘so what?’. What sort of interventions could the index lead to? How can districts act on this information, as budgets are increasingly limited, and resources increasingly strained? Even at its most basic level, the index provides us with a way of better understanding our taxbase. This means that we can better support our residents. From tailoring interventions that off our residents advice and support, through to fine-tuning budgets, we hope that the index will provide a valuable insight tool to teams across the county.
This project has also taught us something important: learn from your team. There’s a whole wealth of knowledge, skill, and experience in the Data and Analytics team to draw upon. Resources such as Insight Libraries and Open Data platforms that enable collaboration are vital for service improvement. As is engagement, for instance having a chat with a colleague whose expertise differ from yours. Collaboration leads to innovation.
So, dear reader, have you changed your mind on council tax? I hope so!
If you want to hear more about our work. You can find our vulnerability maps and further interpretation over on Open Data.
** An LSOA, or lower level super output area, is a geographically bounded area- similar to a ward. It has a population of 1,000 to 3,000 people, which equates to around 400 to 1,200 households. Most public sector data is organised at LSOA level, which makes it simpler for us compare small-area level statistics.