Bending the Heckman Curve: Competing Declines in Learning Capacity and Skill Relevance Over the Life Course

The Heckman curve has powerfully influenced social policy by providing mathematical support for the concentration of human-capital investments early in the life course. The canonical model behind this curve derives a single relationship for aggregate human capital and does not address how return trajectories vary across skill types. We extend the canonical mathematical framework to derive skill-specific return trajectories, incorporating two key parameters governing declines in (a) human capacity to learn and (b) skill relevance over the life course. Our microfoundation model implies that the shape of return trajectories depends on the relative magnitudes of these two declines, indicating a trade-off: although early investments may be more efficient due to declining human learning capacity, they risk misalignment with future labor market needs. Depending on the targeted skill, investments in adult workers might more effectively align with evolving skill content. We illustrate this result with numerical simulations using empirically plausible parameter ranges and selected skill profiles. Our work suggests that optimal investment timing may be skill-dependent, and identifies empirical questions that can better inform human-capital policy in a time of rapid technological change and lengthening lifespans.

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