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Research Using Administrative Data to Support the Work of the Expert Panel on Modernising Child, Youth and Family

3 Calculating risk at a micro-data level

3.1 Calculating risk

In Treasury's earlier analytical work predictive modelling was used to investigate the extent to which various characteristics (observed through ages 0 to 14) were associated with poor outcomes as young adults.

Four outcome measures were selected and defined as follows:

  1. not achieving at least a Level 2 education qualification by age 19
  2. use of mental health or addiction services whilst aged between 18 and 20
  3. receiving a custodial or community sentence before age 21
  4. being on benefit for 2 years or more before age 21.

Logistic regression models were run at each year of age for females and males separately for four outcome measures. Forward selection was used to select the model. This process allowed us to identify the key indicators for each age/gender combination and outcome measure, and calculate a predicted risk score for each outcome for each individual in the population.

In this note the maximum risk score across the (welfare and corrections outcomes) was used to identify the 10 per cent of children with the highest predicted score. This score indicates the combination of risk factors most associated with the projected fiscal costs that we modelled.

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