We study the impacts of a major reform to vocational secondary education that aimed to move beyond the trade-off between providing occupational skills and closing off academic opportunities. Norway’s Reform 94 integrated more general education into the vocational track, offered vocational students a pathway to college, and increased access to apprenticeships. We identify reform impacts through a difference-in-discontinuity research design applied to linked population registries. The reform substantially increased initial vocational enrollment, but with divergent consequences by gender. Overall, the reform succeeded at improving social mobility, particularly for disadvantaged men, but it somewhat exacerbated the gender gap in adult earnings.

Using Norwegian population panel data with nearly career-long earnings histories, we provide a detailed picture of the causal relationship between schooling and earnings over the life cycle. To address selection bias, we apply three commonly used identification strategies. We find that additional schooling gives higher lifetime earnings and a steeper age-earnings profile, in line with predictions from human capital theory. Our preferred estimates imply an internal rate of return of around 11%, suggesting that it was highly profitable to acquire additional schooling. Our analysis reveals that Mincer regressions dramatically understate the returns to schooling because key assumptions are violated.

Many studies use matched employer-employee data to estimate a statistical model of earnings determination with worker and firm fixed effects. Estimates based on this model have produced influential yet controversial conclusions. The objective of this paper is to assess the sensitivity of these conclusions to the biases that arise because of limited mobility of workers across firms. We use employer-employee data from the United States and several European countries while taking advantage of both fixed effects and random effects methods for bias correction. We find that limited mobility bias is severe and that bias correction is important.