Longitudinal Child Data: What Can be Gained by Linking Administrative Data and Cohort Data?

Longitudinal Child Data: What Can be Gained by Linking Administrative Data and Cohort Data?

Longitudinal Child Data: What Can be Gained by Linking Administrative Data and Cohort Data?

Longitudinal Child Data: What Can be Gained by Linking Administrative Data and Cohort Data?s

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Référence bibliographique [20656]

International Journal of Population Data Science, vol. 3, no 21, p. 1-11.

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1. Objectifs


Intentions :
«The purpose of the current paper is to describe the methods of linking administrative tax information with child-focused survey data […]. [The] objective of the current study is to explore the association between child behaviour outcomes (from the cohort file) and later tax outcomes as an example of how this particular linked dataset can produce unique findings.» (p. 2)

2. Méthode


Échantillon/Matériau :
L’étude relie des données sur la taxation qui ont été recueillies par Statistique Canada, avec celles de deux études longitudinales réalisées au Québec, soit l’Étude longitudinale et expérimentale de Montréal et l’Étude longitudinale des enfants de maternelle au Québec. «Using probabilistic linkage methods, Statistics Canada was able to link 84% of valid cases in the original cohort file to valid tax records.» (p. 4)

Type de traitement des données :
Analyse statistique

3. Résumé


Results show how parents’ or families’ socioeconomic status can impact the living condition of their child even once he reached adulthood. More precisely, this article demonstrates «the correlations between two different early child behaviours (anxiety and opposition) and individual earnings and household income. […] Anxiety and opposition showed similar patterns of negative correlation to individual earnings over time, but different patterns of correlation to household income: the correlation of household income with anxiety in young adulthood was lower (closer to zero) than opposition, but as individuals aged became more similar […]. One possible reason for the different patterns observed between individual earnings and household income is the possibility of belonging to a multiple earner household (through marriage or living with parents). […] This linkage opens an array of analyses that were previously impossible, which can provide long-term insight into the relationship of early childhood circumstances to adult outcomes.» (p. 4-5)