The Social Genome Model (SGM) projects how changes in childhood and adolescence may affect adulthood outcomes. The SGM can help policymakers and practitioners identify and assess which policy interventions might most effectively and efficiently break patterns of intergenerational disadvantage. This brief assesses whether the SGM’s findings pertaining to the association between cognitive and noncognitive predictors and adult earnings are comparable with results found in the broader academic literature.

Why This Matters

Assessing the comparability of the SGM with the research literature and findings using other data sources provides assurances that conclusions derived from the model provide useful guidance to policymakers and practitioners seeking to improve children’s long-term outcomes.

Key Takeaways

• SGM estimates for cognitive predictors of earnings align with estimates from the literature. The SGM produces results that are broadly similar to existing estimates of the relationship between cognitive outcomes (e.g., test scores) in childhood and adult earnings.
• SGM estimates for noncognitive predictors weakly align with estimates from the literature. Evidence from one study with noncognitive inputs that directly aligned with the SGM, and from alternative analyses we conducted, suggest that the SGM is directionally similar but understates the relationship between noncognitive skills and adult earnings outcomes.
• SGM estimates can be considered a floor for the impacts of an intervention. As a correlational model, researchers might be concerned that the SGM overestimates the impact of a given intervention. Our analysis suggests the opposite; SGM estimates serve as a floor, or minimum value, for the potential effects of an intervention.
• The scarcity of recent, high-quality, longitudinal datasets that link childhood to adulthood underscores the value of the SGM. Most of the literature we identified that links childhood or adolescent predictors to adult earnings relies on samples of people born before 1975, showing that studies following representative groups of individuals from childhood into adulthood remain rare. The SGM can fill that gap, providing an estimate of the potential impact of interventions on several adult outcomes, including earnings, degree attainment, and mental and physical health.

How We Did It

We compared SGM outputs with similar outputs in the literature, identifying literature using a systematic review process. To ensure comprehensive coverage of both domains, we conducted separate literature searches on Google Scholar and in academic databases such as ERIC, JSTOR, EBSCOhost, and Wiley Online Library for cognitive and noncognitive predictors of adult earnings.