Local child poverty estimates are difficult – but essential to exposing the stark realities of geographic inequality

A map showing incidence of child poverty in northern England and Wales. Image: End Child Poverty.

Which of the following statements tells you more?

1) Around 4m of Britain’s 14m children live in households classified as in poverty because they have below 60 per cent of median income after housing costs.

2) Among the 2,200 children who live in the Notting Barns area of Kensington, site of Grenfell Tower, nearly a thousand are in families with very low incomes. Just over half a mile away, among the 2,200 children living in three wards around Kensington High Street and Cromwell Road, only 150 are in this situation.

In fact, each statement is useful: the first shows the overall extent of child poverty and the second what it looks like on the ground.

For the past 15 years, I have helped produce maps estimating where child poverty is most concentrated in the UK. These local child poverty figures are not just designed to shock, although they regularly do. They also show local authorities and others in which locations children face the double disadvantage of family poverty and area poverty. These children live in places where a lack of material resources and opportunities can worsen the effects of growing up in a socially and economically disadvantaged household.

Incidence of child poverty in southern England and Wales. Image: End Child Poverty.

The value of these figures is clear: they could help ensure services are targeted where they’re most needed, for example. However, capturing the extent of income poverty in local areas is a highly imperfect process.

To produce our local figures, we use two different data sets in combination to get the best local estimates. In response to our most recent figures, which reflected the clear evidence that child poverty is getting worse, the government has produced figures claiming to show that in fact child poverty is falling. But it has done so using raw data from a single source which is highly unsuitable for tracking changes in child poverty rates over time.      

There are several reasons why local statistics are difficult to produce. National surveys asking people in detail about their incomes are based on samples that are far too small to be able to say anything about incomes at a local level. The best indicators we have of local child poverty come from data held by public authorities on the number of people claiming out-of-work benefits, and the number who claim working tax credits whose reported family income falls below the poverty line.

This so-called “administrative data”, reported regularly by HMRC, certainly gives you a good idea about where the worst-off wards and constituencies are, and some measure of the concentration of low income in these places. However, particularly when tracked over time, they need to be used carefully, in conjunction with other evidence.

One difficulty is that HMRC data assumes that everyone who is out of work is in poverty. In reality, the relationship between being out of work and being in poverty changes over time. The child of a non-working lone parent had around 85 per cent chance of being in poverty 20 years ago, a risk that fell to 58 per cent by 2013, but then rose sharply to 68 per cent by 2015.

Another problem is that HMRC is quite good at assessing family income for tax credit purposes, but not so good at identifying who is in a low-income household (which takes account of a wider range of income than tax credit assessments, including income generated by household members not in the child’s nuclear family). HMRC’s local child poverty statistics only manage to count a third as many people on low working incomes as the full income surveys. This matters a lot – because working poverty has been rising, and out-of-work poverty falling. Two in three children in poverty now have at least one working parent.

An indicator that overcounts out-of-work poverty and undercounts in-work poverty is bound to show current trends – when the latter is falling and the former rising – In a favourable light. This is especially true in London, where in-work poverty, measured after deducting housing costs, is particularly high because of high rents.

And governments, even those like the present one that has underplayed the importance of income poverty, cannot resist highlighting such rose-tinted statistics.

This explains why, after the publication of our latest child poverty map, junior DWP minister and former London deputy mayor Kit Malthouse felt the need to parade data in the House of Commons that seemed to show child poverty in London falling rapidly, and to argue that our data showing the opposite must be mistaken.

But the data he was using, the raw figures produced by HMRC, is flawed in multiple ways. In addition to the limitations I have already pointed to, it has some pretty bizarre aspects – pointed out by HMRC itself in its latest commentary.

One is that the measure of median income to which poverty is being compared by HMRC is actually going down, whereas all the DWP’s income distribution analysis shows median income rising. “Falling” median income creates a falling poverty line, and hence a lower child poverty count. Another feature is that HMRC doesn’t at the moment count out-of-work families on Universal Credit as being in poverty, even though it did so when similar families were on tax credits. This directly brings the child poverty count down.

The local data that we produce corrects for these quirks in the HMRC data by calibrating the results with the Households Below Average Income (HBAI) survey results. It uses the national differences between the HBAI and HMRC results, for in-work and out-of-work poverty respectively, as the basis for an adjustment to each of the local results. While this can only be seen as an estimate of what the correct figures actually are at the local level, it is a far more meaningful estimate than using the flawed HMRC figures without adjustment.

The two graphs below show why. In recent years, HMRC figures on their own have shown steady falls in poverty rates, particularly in London – which are not borne out by the HBAI data that measures income more accurately. Our data  produces results much more in line with the HBAI data, which show that child poverty is now increasing (except in London before housing costs, where the rate is steady).

Percentage point change in UK child poverty rate using different indicators:  Her Majesty’s Revenue and Customs (HMRC); Households Below Average Income measure, Before Housing Costs/After Housing Costs (HBAI BHC/AHC); End Child Poverty (ECP).

Percentage point change in London child poverty rate using different indicators (three-year averages; labels show the middle year).

The Institute for Fiscal Studies forecasts that child poverty will continue to rise at an alarming rate, more than wiping out the considerable falls that took place in the 2000s. This will have very real impacts at the local level, which we will continue to estimate.

A government that simultaneously publishes these figures but boasts about its progress on another measure purporting to show the opposite has its head stuck very firmly in the sand.

Donald Hirsch is director of the Centre for Research in Social Policy at Loughborough University.


Urgently needed: Timely, more detailed standardized data on US evictions

Graffiti asking for rent forgiveness is seen on a wall on La Brea Ave amid the Covid-19 pandemic in Los Angeles, California. (Valerie Macon/AFP via Getty Images)

Last week the Eviction Lab, a team of eviction and housing policy researchers at Princeton University, released a new dashboard that provides timely, city-level US eviction data for use in monitoring eviction spikes and other trends as Covid restrictions ease. 

In 2018, Eviction Lab released the first national database of evictions in the US. The nationwide data are granular, going down to the level of a few city blocks in some places, but lagged by several years, so their use is more geared toward understanding the scope of the problem across the US, rather than making timely decisions to help city residents now. 

Eviction Lab’s new Eviction Tracking System, however, provides weekly updates on evictions by city and compares them to baseline data from past years. The researchers hope that the timeliness of this new data will allow for quicker action in the event that the US begins to see a wave of evictions once Covid eviction moratoriums are phased out.

But, due to a lack of standardization in eviction filings across the US, the Eviction Tracking System is currently available for only 11 cities, leaving many more places facing a high risk of eviction spikes out of the loop.

Each city included in the Eviction Tracking System shows rolling weekly and monthly eviction filing counts. A percent change is calculated by comparing current eviction filings to baseline eviction filings for a quick look at whether a city might be experiencing an uptick.

Timely US eviction data for a handful of cities is now available from the Eviction Lab. (Courtesy Eviction Lab)

The tracking system also provides a more detailed report on each city’s Covid eviction moratorium efforts and more granular geographic and demographic information on the city’s evictions.

Click to the above image to see a city-level eviction map, in this case for Pittsburgh. (Courtesy Eviction Lab)

As part of their Covid Resource, the Eviction Lab together with Columbia Law School professor Emily Benfer also compiled a scorecard for each US state that ranks Covid-related tenant protection measures. A total of 15 of the 50 US states plus Washington DC received a score of zero because those states provided little if any protections.

CityMetric talked with Peter Hepburn, an assistant professor at Rutgers who just finished a two-year postdoc at the Eviction Lab, and Jeff Reichman, principal at the data science research firm January Advisors, about the struggles involved in collecting and analysing eviction data across the US.

Perhaps the most notable hurdle both researchers addressed is that there’s no standardized reporting of evictions across jurisdictions. Most evictions are reported to county-level governments, however what “reporting” means differs among and even within each county. 

In Texas, evictions go through the Justice of the Peace Courts. In Virginia they’re processed by General District Courts. Judges in Milwaukee are sealing more eviction case documents that come through their courtroom. In Austin, Pittsburgh and Richmond, eviction addresses aren’t available online but ZIP codes are. In Denver you have to pay about $7 to access a single eviction filing. In Alabama*, it’s $10 per eviction filing. 

Once the filings are acquired, the next barrier is normalizing them. While some jurisdictions share reporting systems, many have different fields and formats. Some are digital, but many are images of text or handwritten documents that require optical character recognition programs and natural language processors in order to translate them into data. That, or the filings would have to be processed by hand. 

“There's not enough interns in the world to do that work,” says Hepburn.

Aggregating data from all of these sources and normalizing them requires knowledge of the nuances in each jurisdiction. “It would be nice if, for every region, we were looking for the exact same things,” says Reichman. “Instead, depending on the vendor that they use, and depending on how the data is made available, it's a puzzle for each one.”

In December of 2019, US Senators Michael Bennet of Colorado and Rob Portman of Ohio introduced a bill that would set up state and local grants aimed at reducing low-income evictions. Included in the bill is a measure to enhance data collection. Hepburn is hopeful that the bill could one day mean an easier job for those trying to analyse eviction data.

That said, Hepburn and Reichman caution against the public release of granular eviction data. 

“In a lot of cases, what this gets used for is for tenant screening services,” says Hepburn. “There are companies that go and collect these data and make them available to landlords to try to check and see if their potential tenants have been previously evicted, or even just filed against for eviction, without any sort of judgement.”

According to research by Eviction Lab principal Matthew Desmond and Tracey Shollenberger, who is now vice president of science at Harvard’s Center for Policing Equity, residents who have been evicted or even just filed against for eviction often have a much harder time finding equal-quality housing in the future. That coupled with evidence that evictions affect minority populations at disproportionate rates can lead to widening racial and economic gaps in neighborhoods.

While opening up raw data on evictions to the public would not be the best option, making timely, granular data available to researchers and government officials can improve the system’s ability to respond to potential eviction crises.

Data on current and historical evictions can help city officials spot trends in who is getting evicted and who is doing the evicting. It can help inform new housing policy and reform old housing policies that may put more vulnerable citizens at undue risk.

Hepburn says that the Eviction Lab is currently working, in part with the ACLU, on research that shows the extent to which Black renters are disproportionately affected by the eviction crisis.

More broadly, says Hepburn, better data can help provide some oversight for a system which is largely unregulated.

“It's the Wild West, right? There's no right to representation. Defendants have no right to counsel. They're on their own here,” says Hepburn. “I mean, this is people losing their homes, and they're being processed in bulk very quickly by the system that has very little oversight, and that we know very little about.”

A 2018 report by the Philadelphia Mayor’s Taskforce on Eviction Prevention and Response found that of Philadelphia’s 22,500 eviction cases in 2016, tenants had legal representation in only 9% of them.

Included in Hepburn’s eviction data wishlist is an additional ask, something that is rarely included in any of the filings that the Eviction Lab and January Advisors have been poring over for years. He wants to know the relationship between money owed and monthly rent.

“At the individual level, if you were found to owe $1,500, was that on an apartment that's $1,500 a month? Or was it an apartment that's $500 a month? Because that makes a big difference in the story you're telling about the nature of the crisis, right? If you're letting somebody get three months behind that's different than evicting them immediately once they fall behind,” Hepburn says.

Now that the Eviction Tracking System has been out for a week, Hepburn says one of the next steps is to start reaching out to state and local governments to see if they can garner interest in the project. While he’s not ready to name any names just yet, he says that they’re already involved in talks with some interested parties.

*Correction: This story initially misidentified a jurisdiction that charges $10 to access an eviction filing. It is the state of Alabama, not the city of Atlanta. Also, at the time of publication, Peter Hepburn was an assistant professor at Rutgers, not an associate professor.

Alexandra Kanik is a data reporter at CityMetric.