Repealing the Universal Credit two-child limit

How removing the limit of some benefits to two children would affect the UK in 2023.

See the full, customisable impacts on PolicyEngine here.

Introduced in 2017, the two-child limit in Universal Credit restricted parents from receiving financial support for more than two children (with children born before 2017 exempt). Using the PolicyEngine microsimulation model, we estimate that repealing it would cost £1.8 billion in 2023, rising to £2.8 billion in 2025 as non-exempt age cohorts replace exempt children. The repeal would also lower absolute child poverty before housing costs by 310,000 this year.

While the Cameron-led Conservative government introduced the two-child limit, last month, Labour Party leader Sir Keir Starmer confirmed that a Labour government would keep the policy due to the cost of repealing it.

In this analysis, we examine how the policy currently affects households, and use PolicyEngine to estimate the distributional and poverty impacts of both full and partial repeals proposed by the Child Poverty Action Group and the Fabian Society. We also attempt to reproduce claims made using other microsimulation models. The open-source code powering the custom analyses in this report can be found here.

See how repealing the two-child limit would affect your household here.

Households claiming Universal Credit, or the legacy Child Tax Credit, currently do not receive additional benefits for their third or subsequent children. With benefit levels recently uprated as of April 2023, the two-child limit reduces benefits by up to £2,935 per child (lowered with increased parental earnings as the family reduces their Universal Credit entitlement). The cap applies regardless of whether a household is in or out of work, but its impact changes with earnings due to the normal Universal Credit taper.

Figure 1 shows the impact of removing the two-child limit under a range of employment incomes for a single parent family. The gains are highest (and equal) for families under around £30,000 in employment income, after which point the taper rate begins to reclaim the extra benefit value. For a single parent with 5 children, this value will not be reduced to zero before more than £60,000 in earnings.

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Figure 1: the impact of removing the UC child limit on net income for a single parent by number of children and employment income. Note: this does not incorporate housing costs, which would extend the phase-out region to the right.

The most straightforward way to repeal the cap is to remove it entirely, at a cost of £1.8bn in 2023. ¹ This net cost rises over time due to age cohort transitions: with each year, the minimum age required to be exempt under the 2017 transitional protection rule increases.²

Under a full abolition, we estimate that the number of children in absolute poverty before housing costs would fall by 255,000 in 2023 (relative, after housing costs child poverty would fall by 162,000). The overall absolute, before housing costs poverty rate for all individuals would fall by 0.7 percentage points, bringing just under 450,000 people out of absolute poverty.

Table 1 shows a range of other estimates made by the Child Poverty Action Group using the UKMOD microsimulation model, and PolicyEngine's replications for comparison. The appendix contains more details about the reasons PolicyEngine's microsimulation modelling differs from other estimates.

Table 1: comparisons between CPAG's UKMOD-based modelling results and PolicyEngine's replications for 2023.

The Fabian Society's 2021 report "Going with the grain" proposes instead repealing the two-child limit for families with a parent who meets one of the following conditions:

• Having employment or self-employment income

• Receiving disability benefits

• Having a child aged two or under

We estimate this partial abolition would cost £1.3 billion in 2023, saving £500m compared to the full repeal. The Fabian Society modelling, based on the IPPR tax-transfer model, projected that the number of households hit by the two-child limit would fall by 94% from 790,000 to 75,000. This projection assumes a full roll-out of the policy as it would be in 2035, where the transitional protection rule does not occur.

PolicyEngine estimates in 2023 that 333,000 households are affected by the two-child limit (close to estimates by the House of Commons Library in April 2021 that 317,500 families were affected), and that this would fall by 302,000 to 31,000 (a reduction of 93%, close to the Fabian Society estimate).

PolicyEngine's modelling largely aligns with the findings from other microsimulation models but finds around 30% lower net costs and poverty impacts than CPAG.

Funding proposals also feature in the discussion around the two-child limit. Tom Clark, fellow at the Joseph Rowntree Foundation, pointed to a 1p increase in the higher rate of income tax as a possible option. Given our higher net cost estimate for the two-child limit repeal, we estimate this would leave £470m deficit (distributional impacts shown in Figure 2).

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Figure 2: the distributional impacts of funding the two-child limit repeal with a 1p higher rate increase.

PolicyEngine's microsimulation modelling is completely open-source. See the full analysis for the repeal on PolicyEngine here. If you have feedback or questions on the results in this report, please do get in touch.

When first estimating the impacts of this reform, we used our Family Resources Survey-based microdata and reached impacts of lower magnitude. However, administrative statistics suggested that the true impacts may in fact be larger, so we extended our data enhancement process to repair the specific biases remaining present in the FRS under the guidance of the administrative statistics.

Microsimulation models based on survey microdata often reach estimates differing from administrative data, due to sampling or measurement bias in the data collection process. PolicyEngine applies a calibration process to adjust for this as much as possible by both imputing missing income data and reweighting households to repair consistency with administrative totals.

To illustrate, take the following example (based on completely hypothetical characteristics).

By adjusting survey weights, we can shift the distributions of survey variables to reconcile them with more trusted administrative data. This requires collecting as many administrative statistics as possible, and calibrating as closely as possible to them all, together. In the example above, it was possible to match exactly, but this often isn't possible in practice because we are operating on a survey, and not a census.

A key learning point in this report was the government's administrative statistics on households affected by the two-child limit. Using benefit administrative databases, the Department for Work and Pensions estimated that in April 2023 around 1.5 million children lived in households meeting two conditions:

• The household claims Universal Credit or the Child Tax Credit.

• The household does not receive a child element for at least one child.

Our initial model estimate was lower than this (around £1.3m children), largely due to biases in the Family Resources Survey not fully countered by our data enhancement process (although we included child counts and Universal Credit caseloads in our calibration function, we did not include this specific intersection).

To correct this underestimate, we recalibrated the survey microdata, applying an extra penalty to the algorithm for deviating from:

• The number of households affected by the UC and CTC two-child limits, respectively.

• The number of children living in UC- and CTC-claiming households with 3, 4, and 5-plus children, respectively.

Figure 3 shows how this process operates for the first of these parameters. Note that PolicyEngine still carries out this process for the other 2,000+ statistics we target, ensuring that the model weights do not over-calibrate towards this new set of statistical targets.

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Figure 3: An example of PolicyEngine's calibration process, in which survey weights are adjusted to shift the FRS projection of UC-claiming, child limit-affected households towards the administrative estimate.

PolicyEngine now reproduces this 1.5m statistic. However, what we subsequently found suggests that the 1.5m figure is an underestimate of the true number of children affected by the reform. Because the administrative data does not include households brought into eligibility by reforms, it cannot include households who are not currently eligible for Universal Credit but would be under an abolition of the two-child limit.³ These households are represented by points on the diagonal slope in Figure 1.

We estimate 200,000 children fall into this category, bringing the number of children living in households affected by the two-child limit to 1.7 million.

nikhil woodruff
PolicyEngine's Co-founder and CTO

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