This paper shows how record-value theory, a branch of statistics that deals with the timing and magnitude of extreme values in sequences of random variables, can be used to nonparametrically identify the offer distribution of wages workers face.Using NLSY wage data, I show that the data supports the hypothesis that the wage offer distribution is Pareto but rejects that it is lognormal.In addition, I show that my approach can be used to construct a bound on the return to job-specific human capital.Using the same NLSY data, I find that job-specific human capital plays only a minor role in the wage growth of the workers in my sample.Instead, wage growth among the young workers in my sample appears to be driven primarily by the accumulation of general human capital as well as on-the-job search.

In many professional service firms, new associates work long hours while competing in up-or-out promotion contests. Our model explains why. We argue that the productivity of skilled partners in professional service firms (e.g., law, consulting, investment banking, and public accounting) is quite large relative to the productivity of their peers who are competent and experienced but not well suited to the partner role. Therefore, these firms adopt personnel policies that facilitate the identification of new partners. In our model, both heavy workloads and up-or-out rules serve this purpose.

Galí (2014) showed that a monetary policy rule that raises rates when bubbles exceed some steady-state benchmark can paradoxically lead to larger deviations from steady state. Nevertheless, this comment shows that a central bank can always dampen a bubble by setting a higher-than-expected rate, although it may have to raise the rate aggressively. This is a different point from the Miao, Shen, and Wang (2019) comment on Galí (2014). They showed that when the central bank targets a different steady state than Galí considered, raising rates when bubbles exceed this alternative benchmark leads to smaller deviations from steady state.