Summary
Childhood outcomes across a range of domains are correlated with the socio-economic characteristics of the child’s neighbours. Yet, work on the topic is dominated by observational designs that do not consider the confounding effect of genetics. Although experimental designs exist, these are extremely expensive and usually rely on a restricted range of people from lower socio-economic backgrounds. Consequently, the overarching aim of the PAN project is to estimate the plausible effect of neighbourhoods, absent genetic confounding and restricted socio-economic range, by examining neighbourhood effects on adoptees.
Danish registry data provides a unique opportunity to pursue this aim due to its combination of adoptees placed pseudo-randomly with non-relatives across the full socio-economic spectrum, and the availability of annual personality assessments as well as classic outcomes data throughout the childhood years. The use of registry personality data allows me to explore neighbourhood effects on pertinent child characteristics from a young age, as there are domains for which the classical outcome data primarily apply at later ages even if dispositions towards particular outcomes are detectable earlier—e.g., behavioural disinhibition as a precursor to crime. The integration of adoptees and childhood personality is, therefore, a distinctively powerful and practical approach to clarify where (in the socio-economic distribution) and when (in children’s development) effects of neighbourhoods are most potent. Given the potential importance of neighbourhoods in intergenerational inequality, answers to these questions may inform effective government policies.
By completing the project under the supervision of Associate Professor Steven Ludeke at University of Southern Denmark, I will gain valuable training as well as experience on registry data, adoptees, and ‘big data’, which will make me more competitive in my pursuit of a career in academia or as a data scientist.
Danish registry data provides a unique opportunity to pursue this aim due to its combination of adoptees placed pseudo-randomly with non-relatives across the full socio-economic spectrum, and the availability of annual personality assessments as well as classic outcomes data throughout the childhood years. The use of registry personality data allows me to explore neighbourhood effects on pertinent child characteristics from a young age, as there are domains for which the classical outcome data primarily apply at later ages even if dispositions towards particular outcomes are detectable earlier—e.g., behavioural disinhibition as a precursor to crime. The integration of adoptees and childhood personality is, therefore, a distinctively powerful and practical approach to clarify where (in the socio-economic distribution) and when (in children’s development) effects of neighbourhoods are most potent. Given the potential importance of neighbourhoods in intergenerational inequality, answers to these questions may inform effective government policies.
By completing the project under the supervision of Associate Professor Steven Ludeke at University of Southern Denmark, I will gain valuable training as well as experience on registry data, adoptees, and ‘big data’, which will make me more competitive in my pursuit of a career in academia or as a data scientist.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101109141 |
| Start date: | 01-09-2024 |
| End date: | 31-08-2026 |
| Total budget - Public funding: | - 214 934,00 Euro |
Cordis data
Original description
Childhood outcomes across a range of domains are correlated with the socio-economic characteristics of the child’s neighbours. Yet, work on the topic is dominated by observational designs that do not consider the confounding effect of genetics. Although experimental designs exist, these are extremely expensive and usually rely on a restricted range of people from lower socio-economic backgrounds. Consequently, the overarching aim of the PAN project is to estimate the plausible effect of neighbourhoods, absent genetic confounding and restricted socio-economic range, by examining neighbourhood effects on adoptees.Danish registry data provides a unique opportunity to pursue this aim due to its combination of adoptees placed pseudo-randomly with non-relatives across the full socio-economic spectrum, and the availability of annual personality assessments as well as classic outcomes data throughout the childhood years. The use of registry personality data allows me to explore neighbourhood effects on pertinent child characteristics from a young age, as there are domains for which the classical outcome data primarily apply at later ages even if dispositions towards particular outcomes are detectable earlier—e.g., behavioural disinhibition as a precursor to crime. The integration of adoptees and childhood personality is, therefore, a distinctively powerful and practical approach to clarify where (in the socio-economic distribution) and when (in children’s development) effects of neighbourhoods are most potent. Given the potential importance of neighbourhoods in intergenerational inequality, answers to these questions may inform effective government policies.
By completing the project under the supervision of Associate Professor Steven Ludeke at University of Southern Denmark, I will gain valuable training as well as experience on registry data, adoptees, and ‘big data’, which will make me more competitive in my pursuit of a career in academia or as a data scientist.
Status
SIGNEDCall topic
HORIZON-MSCA-2022-PF-01-01Update Date
31-07-2023
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