We derive a tractable nonlinear earnings function which we estimate separately for each individual in the NLSY79 data. These estimates yield five important parameters for each individual: three ability measures (two representing the ability to learn and one the ability to earn), a rate of skill...

We derive a tractable nonlinear earnings function which we estimate separately for each individual in the NLSY79 data. These estimates yield five important parameters for each individual: three ability measures (two representing the ability to learn and one the ability to earn), a rate of skill...

This paper proposes a new strategy to identify causal effects. Instead of finding a conventional instrumental variable correlated with the treatment but not with the confounding effects, we propose an approach which employs an instrument correlated with the confounders, but which itself is not...

We derive a non-standard unit root serial correlation formulation for intertemporal adjustments in the labor force participation rate. This leads to a tractable three-error component model, which in contrast to other models embeds heterogeneity into the error structure. Unlike in the typical iid...

This paper proposes a new strategy to identify causal effects. Instead of finding a conventional instrumental variable correlated with the treatment but not with the confounding effects, we propose an approach which employs an instrument correlated with the confounders, but which itself is not...

This paper examines how human capital based approaches explain the distribution of earnings. It assesses traditional, quasi-experimental, and new micro-based structural models, the latter of which gets at population heterogeneity by estimating individual-specific earnings function parameters....

In 1958 Jacob Mincer pioneered an important approach to understand how earnings are distributed across the population. In the years since Mincer's seminal work, he as well as his students and colleagues extended the original human capital model, reaching important conclusions about a whole array...