May 9, 2023
In this episode of Statistically Speaking we shine the spotlight on local data and look at how good statistics for small areas make for better targeted policy interventions, and more effective use of valuable public resources.
Welcome again to Statistically Speaking, the Office for National Statistics podcast. I'm Miles Fletcher and in this episode we're talking about local data for local people - How good statistics for small areas make for better targeted policy interventions, and more effective use of valuable public resources.
We're going to explore, for example, how new data sources are helping to precisely calibrate economic circumstances and local communities. How we may even be able to calculate the GDP of your street or village. Now many economic forces are of course global. Some of the solutions to issues like competitiveness, productivity and inequality might begin on our doorsteps.
As ever, we have the cream of ONS expertise here on hand, this time in the shape of Emma Hickman, Deputy Director of the ONS sub national stats division, and Libby Richards, Deputy Director for UK wide coherence and head of an important new initiative called ONS Local, which we'll be hearing about in full. Also joining us is Stephen Jones, Director of Core Cities UK. Its aim is to promote the role of our great cities in creating a stronger fairer economy and society.
So Emma, to set the scene for us first
then please explain precisely if you would, the value of
So the needs are multiple, really. I think the most important thing is that we are seeing a huge increase in locally targeted policymaking and that’s at a range of different levels across government. So in central government, we see near the department for levelling up Housing and Communities kind of really wanting to think about how do they target policies that are going to help to level up the country but equally what we're also seeing is an increase in devolution which is giving more power to local areas and local policymakers. And so it's really also important that they have the statistics and the data that they need and the evidence that they need to make really, really good decisions for their local areas. And they can do that in a really powerful way because they also have knowledge of their local areas. And then finally, you know, actually for citizen kind of uses of our data and statistics really one of the inclusive data principles that people are able to see themselves in the data and that they feel that the data and the statistics that we're producing as an office represent them. And so having statistics and data available at really geographies that are very meaningful to people is hugely helpful in making sure that as a country, right across the UK that we are kind of reflective of the experiences of really kind of a wide range of people and you know, local economies and end users and understand kind of how they're experiencing that as well.
I guess one
of the fundamental principles here is that it's it's
knowledge. It's all very well and everybody
thinks they know that local area, but to understand all local
areas, we need comparable statistics and data produced to
Yes, absolutely. And that's, I mean, that's one of the key challenges. I think we'll probably kind of come to talk about a little bit later, but you know, absolutely. And that's really about understanding you know, where are the where are the inequalities within regions, as well as between regions? I think we have a lot of information available about, you know, kind of regions, but actually, we also know that some of the inequalities that people really feel are much greater actually within regions and between them and kind of being able to draw that out of data and statistics in a comparable way I think is really important for helping sort of policymakers and decision makers to understand where best to target resources.
Stephen, from a policy perspective, describe the demand for local data at the moment, what sorts of policy solutions are policy makers coming up with and how are those best informed by really good data?
I think it covers all branches really of policymaking. I think as Emma was saying, the kind of need for really understanding and having a kind of quantitative basis for what's happening in a place is, is actually absolutely crucial for designing policy, whether that's policy about trying to make the economy grow, whether that's policies aimed at trying to reduce disadvantage and challenge facing individuals, whether that's policy about delivering the most effective and efficient public services in the right places at the right times, all of those things, whether that's done in public or private sector need to be built on a good evidence base, good understanding. I think the other thing I would add to the richness of local data can do you can kind of contextualise and understand, you know, a number on its own doesn't mean a huge amount, but if you know that you are 10% higher or 20% lower than your neighbouring place. Or the city of the same size. It's those kinds of contextual dimensions that really help nuance and finesse your policymaking.
And it does come back to that question of trust in data than to make those comparisons in a really reliable and meaningful way. Which I guess is where the ONS, the Office for National Statistics, where we come in. Now Libby tell us about ONS Local. This is an initiative which is all about making sure that that really high quality data is available for the policy makers
ONS Local is our advisory service that is staffed by ONS analysts who are based in every nation of the UK and every region of England. And the idea is that we are here to help local policy makers, regional observatories, and lots and lots of different users of sub national data to really understand the enormous offer from ONS in terms of local data. Having said that, it's also very much about those working relationships as well. Stephen’s talked a lot about context and understanding the nuances and so understanding the situations and challenges that are happening locally is absolutely key to ONS Local helping local areas understand that context better.
The big ONS surveys of course have long carried, many of them are typically think about the Labour Force Survey over a very long period of time, carried a great wealth and local data that obviously gets lost in the national headlines that these data releases generate. But is it a question of getting better value out of what the ONS is already creating or actually about sourcing new data from different sources?
It's a bit of both, very much, in being able to take people through what we already have when understanding their questions, particularly when multiple local areas are asking the same question that's really maximising what ONS already do. However, Emma's side of the house in particular, less so in the regionally and nationally distributed ONS Local is really about developing those new statistics getting into how do we get down to hyper localised sort of 400 to 1200 household building block data that then allow people to build those areas that means something to them. Emma, I don't know if you want to chip in?
Yeah, very happy to. There's two strands I think to that Miles. I think there's one which is about, you know, how do we make the most of survey data and kind of new administrative data sources together to enable that level of granularity? And then the second part is actually when we talk about administrative data probably, that might not really mean things to lots of people. That's data that is collected for a different purpose, but collected on a on a very, very routine basis. And there are actually a fair number of new sources of that kind of data that we're able to get into the ONS.
That's interesting. Can you give us an example of that?
So, I say relatively new. I mean, I think ONS have had this data for quite some time now. But in order to get the level of granularity that we need on Gross Value Added statistics, for example, which is a measure of productivity, we use HMRC’s VAT data for businesses and then we can link that to kind of our survey data and think about how can we then apportion estimates down to the level of geography that we need, knowing that the survey is the place where we've been able to ask the question that we really want to know the answer to and then we can use the other data to model sort of some of the other granularity that we need. The other thing is we've been really successful and using card payments data throughout the pandemic to inform the government's response. And we've recently successfully acquired a really exciting new data source from Visa, it's aggregated, so there's absolutely no way of identifying people in the data, but they've aggregated it at a really granular level of geography for us. So again, it would be in the region of probably hundreds of households, but actually that's granular enough for us to get some really, really good insights into kind of how you know, consumer spending is kind of playing out in the local economy. And there are all sorts of applications for that, that we're really excited to be to be able to start taking forwards now that we've got that data in the office.
So just with those three very important data sources, suddenly we're creating right down to that very micro level, as you say, 400 to 1200 households really quite a full picture of local economic activity.
And the really exciting thing about that is that people can then build their own geographies as well from that. So you know, traditionally in statistics, we tend to produce data at the level of an authoritative boundary like a local authority, but actually you might really want to know about, I don't know, West Midlands Metro, for example, they extended the line a few years ago, you might really want to know about local economic activity around that and actually, that's not going to be captured in the sort of administrative boundaries and so having the data at that level of granularity really allows people to build a geography that sort of area of interest or importance to them in some way.
Creating a GDP of your street or village.
the project for now,
but it comes across with some pretty
significant challenges. It comes back to
this problem of comparability doesn't it, and particularly if
looking across the
UK contexts there. We've got different government
structures, we've got some devolved areas,
got areas and
got big metropolitan
authorities as well. How difficult is it to be able to standardise
and to make uniform the data right across that rather complex
Incredibly so. To the point where we don't necessarily aim for uniformity. It's very much about how do we make sure that we're able to tell stories that are coherent and consider that UK wide angle when thinking about the nations but also thinking about how do you enable that comparability that's very tricky. And the more and more devolution happens, the more and more difficult that actually can become, particularly when you're looking, for example, at health data where it is a devolved policy area across the four nations. But actually, if you live on the border, let's say between Wales and England, actually, you may well be getting your health care on the opposite side of the border from which you live and therefore you've got to be able to have an opportunity to consider that.
There's the issue then of course of samples as well. And the more local you go, of course the less representative your sample is going to be.
Absolutely. And that gets particularly tricky. Even at a nation level where we're thinking about Scotland, Wales or Northern Ireland, for example, the opinions and lifestyle survey, actually, it's quite difficult to find out what that looks like for Northern Ireland. And ideally, we'd want to be able to get more granular than the nation level, but sample sizes make that really tricky to still be representative. And so either we'd need to expand the survey to get that level of granularity or we have to actually say the best we can do is this.
Yes, because there is only one holy universal survey of course and that is the census and that only happens once every 10 years. I recall when we were running the big COVID infection survey at the height of the pandemic, even a massive data gathering operation like that. We could still only end up getting it down to sub regional level which is what units are for half a million people. So it does show doesn't it how important it is to make the most of that admin data which can be extremely comprehensive sometimes
I, you know, completely agree with you there Miles on administrative data and how important it is to be able to kind of think about innovative ways to combine that data with our survey data to get a more granular level of information. I talked a bit earlier about kind of estimates of gross value added and I can say that's just that's a measure of productivity and it feeds into the largest component of GDP and in local areas. What we were able to do there as I mentioned kind of earlier, we took HMRC’s VAT tax data which is collected for all businesses that pay VAT, we were able to link that to a data set that ONS hold called the interdepartmental business register and the information that's held on that is all of the information about business structure, so has a VAT reference in there so we can link it to HMRC data. But the most important information on there for us was actually that where the local units are, so for example, Tescos will have a headquarters somewhere but you probably have a Tesco Express quite close to where you live. And that's one of the local units so tells us where the local units are and their postcodes and it also tells us how many employees work in those local units. And so we can make an assumption like productivity for all employees in the organisation is the same, and then we can look at actually what the productivity for that firm is top level and then divide that by the number of employees to kind of say, well, actually, if all employees are equally productive, this local unit has a productivity sort of measure of this much, and then we can aggregate that back up again to the sort of area so you know, really kind of key to be able to understand those methods, but there are some other challenges as well, but I can probably come back to those.
That's fascinating stuff. I mean, you could point to a certain, perhaps a certain enterprise, a certain employer, that is considered to be, you know, fundamental to a local economy. But this way, you can actually really press precisely quantify what that importance is.
And I think that's one of the challenges because actually as a as an office, we don't want to be disclosing the productivity of any single firm or any single business because that is personal information. So one of the things that we've had to do in very local areas where there are what we call dominant businesses or dominant organisations who have like most of the productivity for that area, is we've actually, you know, I'm gonna be honest, we've we've sort of masked it a bit. And so we've kind of averaged a few local areas together so that you still have a building block level of data, you still have a building block so you can build a bigger area, but you don't actually have any businesses that are considered dominant within the statistics that we produce. That's taken quite a complex algorithm to be able to achieve that. I won't go into too many details just to say that it is a consideration and the challenge that we've had to really innovate to be able to be able to publish that information.
It's important to stress Isn't it that all the usual principles of non-identification and confidentiality apply in this work as much as they do anywhere else across the ONS.
Give me a couple of examples of some specific bits of work that you've been doing then. There's been an analysis of towns and out of town locations particularly and how local employment growth is happening outside of town and city centres.
My team kind of over the last sort of couple of years have been doing a whole series of analysis of towns in particular, like I say, that's a geography that people can really relate to, you know, lots of people kind of live in a town or a city. And that's something that's a bit more understandable than maybe a local authority and is a bit closer to them than the region for example. Our recent analysis on towns and out of town locations when we looked at employment growth, I think has some quite important findings actually for transport planning. For example, what we found is that actually employment growth is not happening the most in town centres, it's happening more and faster within two kilometres of the edges of a town of the town boundaries. And so what we think it might be happening is that kind of employment growth is actually happening in industrial parks are situated on that cusp between town and kind of rural areas. And when you're thinking about, you know, how people might travel to work, for example, I think it's really, really important to have those insights so that we're not just planning transport routes, for example, that go into town centres
And what other insights have we been generating?
recent piece was a new piece of analysis on the nighttime
So I think
lots of people will think about the nighttime
being predominantly about
bars and restaurants
and obviously, you know, they will have a really, really
those sort of industries during the pandemic. But in
fact, what we find is that actually
economy in rural
are surprisingly busy and
because we also have
economy that is
around health and health care. Nurses, for example, kind of
working night shifts and that sort of thing. And then the other
kind of aspect to it is sort of warehousing and transport as well.
There's often kind of an overnight element to that, too.
And again, having that understanding of like how that kind of plays
out in different parts
of the country is
kind of a really, really
did it just for London, interestingly, and then we've done this kind of new analysis
looking at the whole country, which was really
Other things produced quite recently as well are an expansion of
job quality indicators of work across the UK, which is important
because if you just look at kind of employment numbers, you're not
really getting a sense of, you know, you get a sense of who's
employed and who's unemployed in terms of characteristics of
people, but what you don't get is like how good is the job quality
for those people and actually, job quality is probably quite
important for a lot of individuals and in terms of how
they feel about kind
of going into work and how productive they are? And all of
That also forms the understanding doesn't it of why some people have opted out of employment in recent years.
Absolutely. And it also can tell us about things like how many people are working part time who want to be working full time for example. Or vice versa, you know, so there's kind of like a measure of underemployment in there. It tells us a little bit about what percentage of people are working on zero hours contracts versus permanent contracts, all those kinds of things, I think are quite, you know, sort of quite important.
Some other developments well worth pulling out as well. I think we've been able to produce very interesting picture of comparative housing affordability down to quite local level.
Yes, I think our main housing affordability release goes down to local authority level, but we have produced actually a range of housing affordability statistics, the local authority, one that we published recently probably been the most comprehensive, we're also doing a lot of work on the housing data that's collected through the census as well to understand dwellings and their characteristics as well. You know, how many dwellings are occupied and versus non occupied and how that varies by different parts of the country as well. Housing affordability in particular tells us about how people's earnings relate to what they spend on housing, and obviously that has huge impact on again, kind of, you know, people's disposable income at the end of the day. So I think it's certainly an important one.
So lots of fresh insights that are coming from the ONS and local statistics, but it's important to point out that a lot of this you could be doing for yourself if you're so inclined, and we've brought forward a tool called and it's much more exciting than the name implies, actually. It's called the Sub National Indicator Explorer tool. Libby, can you explain how that operates? And some of the really interesting insights that you can generate with it.
So the Sub National Indicators Explorer is something that we know and have known for a while that users desperately want. So often, if you are trying to understand a particular place, you have to go to lots of different sources to actually find information about one area. So for example, if you want health you have to go to one place. If you want to find out about education, you have to go to another and find your area and then collate that yourself. What the sub national indicators Explorer allows you to do is bring together all of those relevant indicators into one place so you can find your local authority and compare it with say up to three others across more than 40 different metrics ranging from gross median pay, right the way through to healthy life expectancy, and so you have this incredibly useful tool where you go, I want to know everything about place x and you get it all in one place. Our intention is to develop that a little bit further and eventually head into some of the developments that have come out recently around the census where you can build your own maps, build your own areas and flexibly bring different data things together. Alongside that we've also been thinking about how else we might be able to compare other areas and the team have recently done an analysis that clusters local areas together under metrics similar to and including some of the same from the sub national indicators tool and so that explores places that are statistically similar using things like regional growth metrics, and we can see what different parts of the country could potentially learn more from each other. They might be facing similar challenges and therefore getting beyond their local area to kind of join up with other areas across the country and this also gives some really weird potentially interesting insights.
Yes, which shows that despite the north south divide, about which we continue to hear a great deal some places in North and South have a great deal in common with each other.
Indeed, and actually places for example, in the south may be very different. So Portsmouth down on the south coast can look a lot more like places in the Northeast than possibly other areas on the south coast. Portsmouth is in a cluster of higher connectivity but lower health and well being whereas neighbouring Havant is in a much higher health and wellbeing and moderate educational performance cluster and you can see this all over the place. So for example, Newcastle upon Tyne is actually very similar to the New Forest and Havant and in fact, so is York and Great Yarmouth. And so they're actually disperate across the country, but mostly situated in particular areas. However, if Havant or the New Forest is facing a particular problem, maybe going and having a chat with York might actually be quite helpful depending on the problem.
That seems an excellent moment to bring in Stephen Jones as director of Core Cities. Stephen, the local picture, of course, is much more complex than that old cliche about the north south divide. But what work are you doing with the ONS and with others, to produce a really informed picture which policymakers can then act on to deal with these issues of localised deprivation, economic disadvantage and so forth.
Firstly, we're doing a piece of work as Core Cities with the Royal Society of Arts called Urban Futures Commission, looking at the kind of like what's the long term potential and trajectory of our biggest cities in the UK and within that, you know, this is the sort of position of why do UK cities relatively underperform compared to the international peers in the developed world is quite a well established problem that's decades old. What some of the new data available is allowing us to kind of really get a better handle on is, why is that the case what is happening to for example, a fairly recent new release of fixed capital formation, so investment data, at a local authority level split by the different asset classes that the ONS have produced is really helpful to bring an understanding and a kind of richness to basically what both public and private investment we can see that our big cities outside of London have a relatively lower levels of public and private investment, particularly then if you strip out real estate investment. So investment in capital and business intangibles, those things are particularly low. So not all of our core cities, the total investment in Greater Manchester most recently was about 9000 pounds per head, central London, it's 55,000 pounds per head. If you go down to Newcastle I think it's down to 3000 pounds per head. You know, that's a dramatic difference in levels of public and private investment.
Does having much more reliable local data, perhaps hold with it the promise that the policy interventions that result from it can be therefore much more effective?
So completely. You know, one of the things that I'm quite excited about in terms of using the local GVA data that Emma was talking about as a new release is there's been a whole host of different policy interventions over the last 10, 20, 30 years trying to kind of create economic activity within zones areas and whatever was saying about the ability to build your own geographies, I think is really has real potential in it. So whether it's the enterprise zones of the Heseltine era or the enterprise zones of the George Osborne era, whether it's free ports policy more recently, whether it's transport led regeneration schemes around new road junctions or new rail stations, whether it's the role of universities, science parks, investment in innovation zones, the government recently announced in the budget just a few weeks ago, the question of investment zones, all of these policies, they are some of the national ones – there's many more when you think locally are attempting to try and create concentrated economic activity within certain locations. One of the main criticisms in a policy sense is that that activity will just get displaced from elsewhere. If the business that is currently located three miles up the road will move to within the zonal boundary to gain sort of benefits and advantages that are being offered there. Well, we'll kind of be able to tell whether that's true or not, by actually looking to see whether the areas nearby have sort of reducing GVA compared to the areas that are growing and I think being able to properly evaluate policy interventions over the last 30 years to really then decide, well, is it worth pursuing policies like the investment zone announcement of recent weeks or actually should we be trying other approaches? I think that that kind of insight is going to be incredibly valuable.
Indeed, and perhaps also with data at a much lower level and much more micro local level as well, perhaps much smaller, more precisely targeted interventions might be what's called for.
Exactly and I think that again, picking up some of what Emma was saying earlier, some of this data is a tool for local authorities. This has huge potential sort of exactly where are the jobs located? Are they in the town centre? Are they in the business park on the edge of town? What time of day is that activity happening? Is it shift patterns versus is it concentrated in the sort of 945 when we know these things, whether you're sitting there working out your local plan and working out where you're going to zone, your new employment land where you're working out whether you're going to offer any business rate incentives in a business improvement district when you're sitting there working out and what time of day do you need to have your trading standards officers available, these kinds of planning decisions day to day when you're trying to think about what your refuse collection plans and patterns are those things that local authorities are doing on just managing public services bringing together those different aspects having that sort of insight to know what's happening, when and what's most effective, we'll just make our policies more efficient. And in a world where public finances are constrained, particularly so for local authorities and have been for a while or be able to use the funding that is available more efficiently and the delivery of those services I think is hugely beneficial. The other thing that I'm interested in I think, is an area where we as Core Cities can can work with the ONS and others going forward is how do we make more advantage and take more advantage of the data, administrative data that is held locally? So if you think of an average local authority, they have huge amounts of data about that area. Whether that's through kind of council tax dates on collections, arrears, council tax discounts, whether that's through business rate data, whether that's through library card membership, planning applications, the list goes on. Obviously, for the same reasons, as we've talked about the need for protecting individuals and protecting data confidentiality, some of that data, you know, we'll need to be careful about how do we use but at the moment, it's largely sitting there on databases being under explored. If we can get to a world where we can start matching some of that data with some of the data sources that the ONS are making available, and then matching it with data sources such as Emma was talking about that the private sector can bring to the table like Visa and others. I think it's in bringing those sort of insights together. You can actually really, really develop the rich pictures. I can see Libby you would like to come in, so I might just pause there.
Yeah. I was just gonna say Stephen there mentioned about utilising locally held local data alongside national level local data, sort of your ONS data, your government department data, and actually that is one of the things that we're really hoping that ONS Local can help with by having people locally with very good relationships with those individuals in local government, local authorities, regional observatories, actually, if we can pull together their administrative data with what we have at the national level and help with some of that analytical insight because also aware, as Stephen said, local governments are constrained and resources actually, if ONS can help in that analytical insight, then even better that we can help along the way.
So Emma, an exciting vision of the future there and the possibility to be really improving local and regional policy interventions. What's coming next?
The really big exciting development that I just wanted to mention is the kind of opportunity for collaboration and I think ONS as an organisation are on the cusp of opening up the Integrated Data Service more widely, and actually, we've been working really, really closely with that team over the last couple of years or so to understand what a good data asset would look like for subnational. And to kind of start to make sure that we can do some of the data engineering to make that micro data. So when I talk about micro data, I'm talking like response level information from surveys kind of available in a secure and safe way and also in a way that's easily linkable, so that you can easily pick up something about health and something about quality jobs and link them together in that service and do the analysis that you were talking about. That's one of the most exciting developments. I think that's on the horizon in terms of how we'll be able to collaborate and kind of use and share data more widely, keeping in mind that privacy aspect. So you know, the idea is that all of that data is anonymized before it goes into the service and then things will be in kind of really strictly controlled through it. But there is that opportunity for those wider collaborations. I don't know Libby, whether you wanted to come in a little bit on some of the other kind of future developments as well.
Yes, so over
the last 9 to
10 months we have co-designed the ONS Local service going out
across the country, doing round tables, getting people
the room, putting forward our vision of what ONS Local might look
like but very much saying “tell us why we’re wrong, what doesn’t
work for you, tell us what we’re missing”. So really building that service
with our users, and now we’re really beginning to fly now that
we have people across the country. Other bits of
new work also on the
horizon include new data looking at the effect of place on
geographic mobility across towns and cities, so we can follow those
trends as people move around the country and can help us build
pictures of places, track educational outcomes and workforce trends
by area, at a level that we’ve not been able to
do in the past. We’ve also talked a lot today about
the Gross Value Added (GVA) data, and that obviously focuses on
businesses. The next innovation for those
sorts of granular statistics is more looking at the
households aspect, and therefore allowing
more targeted policymaking for those bespoke
areas, and understand those hyper-local
affects that are so important at
particularly when considering all those devolution
Some insight there on the work underway here to ensure people across the UK see themselves in our data. Many thanks to our guests today Emma Hickman, Deputy Director of ons sub national stats division, Libby Richards, Deputy Director for ONS Local and UK wide coherence, and Stephen Jones, Director of Core Cities UK.
I'm Miles Fletcher and thank you to you for listening. If you've got a question or comment about these ONS podcasts, you can find us on Twitter @ONSfocus. You can also subscribe to new episodes of the podcast on Spotify, Apple podcasts and all other major platforms.
Many thanks to our producer for this episode at the ONS Alisha Arthur. Until next time, goodbye.