Suchergebnisse

ObjectivesThe experiences and conditions that children are exposed to in utero and early infancy impact their health in adulthood. Understanding the channels through which these effects emerge is important, because this may help us to anticipate which children are at highest risk of adverse effects, and provide early interventions to help. In this paper, we test a new channel linking perinatal experiences to later-life health: immunity.
MethodWe use administrative birth records, linked with hospital admissions episodes and primary care consultations for children in the Northern Territory of Australia. This data forms part of the Child and Youth Development Partnership data linkage project. We analyse the impact of a shock to household income in Aboriginal communities, resulting from a change in government transfer policy. We estimate the impact of exposure to this shock in utero or in the first 3 months of life, relative to exposure later in childhood, to isolate the impact of an income shock during this key developmental period.
ResultsWe find that children who were exposed to the shock in utero or in their first three months of life were at higher risk of severe infection requiring hospital admission. They spend, on average, 4.5 more days in hospital from birth to their 6th birthday (a 45 percent increase). Most of this impact is concentrated in admissions for infection. Only a small share of the effect can be explained by the immediate impact of the policy on birthweight.
ConclusionOur findings are consistent with the explanation that an income shock worsens nutrition, and that worse nutrition during key developmental stages can permanently weaken children's immune systems. This finding speaks to the importance of attention to key phases in childhood development, when designing policies that affect households' financial resources. Furthermore, we find birthweight is a poor predictor of childhood hospital admission. However, use of longitudinal administrative data helps us to identify alternative markers of new-born health that are better predictors.

Australia's 'income management' policy requires benefit recipients to spend at least half of their government transfers on essentials (e.g. food, housing). We estimate income management's impact on birth outcomes by exploiting its staggered rollout. By changing parents' consumption patterns, the policy aims to improve child outcomes. We find no evidence of this. Instead, our estimates suggest it reduced average birthweight by 95 grams and increased the probability of low birthweight by 3 percentage points. We explore the mechanisms that may explain this finding. Our study demonstrates how policies that are not carefully implemented and tested can unintentionally escalate existing inequalities.

We present the opportunities and limitations of administrative benefits data held by local authorities for data linkage projects. Whilst the richness of this data has been exploited by practitioners for administration, its potential remains little explored by researchers. We discuss data quality, sample selection and legal gateways for data sharing.
Drawing on our experience working with over 40 local authorities, we present the structure of three datasets: the Council Tax Reduction Scheme, the Single Housing Benefits Extract and the Universal Credit Data Share. We show what variables are usually included, under which legal gateways this data can be shared and how the cohorts represented within the data compare with the low-income population. We discuss how these datasets can be linked at the household level with a number of other data held by local authorities such as social rent and Council Tax arrears, Housing Benefit overpayments and Discretionary Housing Payments (DHPs).
Administrative benefits data provides a comprehensive snapshot of a household's financial situation. Local authorities can proactively use and share this data with external data processors to fulfil their statutory duties if a legal gateway allows. By identifying households at risk of cash shortfalls before they reach a crisis point, councils can target support when administering local welfare schemes and preventing homelessness. By assessing eligibility for benefits, they can run data-driven uptake campaigns. This data captures a proportion of the population on national and local benefits within a local authority at several points in time. Attrition is of concern since households may leave datasets over time. Some will see their income rise and no longer qualify for benefits. Others will move out of the constituency.
Local authorities routinely process longitudinal data on households receiving means-tested benefits by administering housing benefits, council tax support, and discretionary support funds. This data provides a unique real-time insight into the socioeconomic situation of low-income households. Yet, we show that its promising potential for policy research remains largely untapped.