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Modelling the Early life-course (MELC)
The aim of the project is to construct a computer-based simulation model as a decision-support tool for policy-making in the early life course. This entails building a model with micro-level data derived from existing longitudinal studies to quantify, for policy purposes, the underlying drivers and determinants of progress in the early life course.
Type of content:
Assets
Type of asset:
Use case
Big data potential
Yes
Phase in the policy cycle:
Policy Design and Analysis
Open license availability
No
Ease of use
High
Tags:
BI
Data analytics
IT
IT processes
Serves:
| SWOT Analysis for Modelling the Early life-course (MELC) |
||
|---|---|---|
| Helpful | Harmful | |
Internal |
Strengths• Ability to test scenarios that are relevant to policy makers via a user-friendly interface. • Dynamic discrete-time micro-simulation model • Focusses on three main outcomes: health service use, early literacy, and conduct problems. • Acts as a decision-support tool for policy makers • Relies on data from the real world to create an artificial one that mimics the original but upon which virtual experiments can be carried out • Does not model population growth and demographic change. Instead, it models the same group (cohort) of individuals from birth to age 13 and assesses the type of factors that could be modified to improve child outcomes. |
Weaknesses• Is a discrete-time dynamic MSM with status updates every year, so it not designed to handle events in continuous time. • Covers a limited lifespan (from birth to age 13) for a limited range of factors. • Simulates a closed cohort rather than a current and growing population: does not model population growth and demographic change. Instead, it models the same group (cohort) of individuals from birth to age 13 and assesses the type of factors that could be modified to improve child outcomes. |
External |
Opportunities• Understand the factors upon which policies can be devised to improve the lives of children and young people • Construct a computer-based simulation model as a decision-support tool for policy-making in the early life course • Understanding the factors upon which policies can be devised to improve the lives of children and young people • Improving early literacy |
Threats• Is a discrete-time dynamic MSM with status updates every year, so it not designed to handle events in continuous time • Covers a limited lifespan (from birth to age 13) for a limited range of factors. • Simulates a closed cohort rather than a current and growing population: does not model population growth and demographic change. Instead, it models the same group (cohort) of individuals from birth to age 13 and assesses the type of factors that could be modified to improve child outcomes. |
