Abstract

We extend life cycle models of human capital investments by incorporating matching theory to examine the sorting pattern of heterogeneous scientists into different career trajectories. We link differences in physical capital investments and complementarities between basic and applied scientists across industry and academic settings to individual differences in scientist ability and preferences to predict an equilibrium matching of scientists to careers and to their earnings evolution. Our empirical analysis, using the National Science Foundation's Scientists and Engineers Statistical Data System database, is consistent with theoretical predictions of (i) sorting by ability into basic versus applied science among academic scientists, but not among industry scientists; and (ii) sorting by higher taste for nonmonetary returns into academia over industry. The evolution of an earnings profile is consistent with these sorting patterns: the earnings trajectories of basic and applied scientists are distinct from each other in academia but are similar in industry. This paper was accepted by Lee Fleming, entrepreneurship and innovation.

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