The firm-specific human capital theory implies that large firms prefer to hire younger workers
because they invest more in workers than small firms do and because those investments are fixed
costs. In this paper, I use data from the Benefits Supplement to the Current Population Survey
(CPS) to demonstrate that large firms indeed hire younger workers than small firms, especially for
white-collar occupations. I present a simple model of firm cost minimization within an employee
search framework, which is consistent with large firms’ propensity to hire younger workers, and has
additional testable implications regarding large firms’ compensation structures. First, since young
workers are more valuable to large firms than to small firms, large firms ofier higher starting wages
to attract them. This implies flatter starting wage—age profiles among the new hires in large firms.
Second, since large firms invest more in workers, they continue to pay higher wages to retain the
trained employees. This implies steeper wage-tenure profiles in large firms. Both predictions are
borne out by the CPS data. Most strikingly, for the newly hired white-collar workers, not only are
the starting wage-age profiles flatter in large finns, but also the size-wage premium disappears for
workers hired at age 35 or older.
Furthermore, by exploiting cost variations in dimensions other than firm size, such as occupation
and industry, this model has additional testable implications. More specifically, an extension of
the simple model would imply that, for high training occupations, workers displaced at older ages
suffer greater wage losses than younger workers because they have a harder time finding a new good
job that requires high investments. But there should be no systematic difference in wage loss by
age for occupations that require little training. This prediction is supported by the data from the
Displaced Worker Surveys. Finally, limited evidence from the BLS Survey of Employer Provided
Training 1995 and the CPS suggests that industries that train more also appear to hire younger
workers.

Most private health insurance in the US is provided as a benefit of employment. One
explanation for this phenomenon is that employer contributions to health insurance premiums are
not taxed as income to the worker. It is somewhat puzzling, then, that a substantial fraction of
workers contribute to their premiums, since these contributions are frequently made out of after-tax
dollars. In this paper l examine the possibility that firms use employee contributions to distinguish
between workers who do and do not want health insurance, in order to compensate them more
efficiently when recruiting additional workers is costly. This model has clear predictions for the
relationship between worker demand for health insurance and (l) the probability that health
insurance is offered; (2) the probability that an employee contribution is required; (3) the
probability that the firm establishes a Flexible Spending Account that allows the employee
contribution to be made pre-tax; and (4) the employee’s share of the premium when a contribution
is required. l test these predictions using data from the 1993 Robert Wood Johnson Foundation
Survey of Employers. Using worker age as a proxy for health insurance demand, I find results that
are generally consistent with the predictions of the model. However, the fraction of workers who
are female, which should also be related to demand for health insurance, does not exhibit a
consistent relationship with health insurance offering and contribution requirements, so that
overall the evidence on this hypothesis is mixed I conclude that while imperfect worker sorting
on the basis of demand for health insurance does not explain all employee contributions, it may
play a significant role in explaining why firms require contributions.

This paper shows that, in addition to varying with the calendar business cycle, manufacturing firms‘ sales
are significantly higher at the end of the fiscal year, and lower at the beginning, than they are in the
middle. The causes of these fiscal-year effects are investigated, emphasizing the role of salespeople and
their motivation to meet quotas and earn a bonus. In many industries firms have substantially lower
average prices toward the end of fiscal years, but price changes cannot explain all the effect of fiscal years
on revenue seasonality. It is shown that the industry variation in the fiscal year revenue and price effects
are correlated with type of product, distribution method, and the industry average salesperson turnover
rate. The results are consistent with a sales quota model of fiscal seasonality, where all salespeople can
vary their effort throughout the fiscal year but only some salespeople can influence the timing of their
customers’ purchases.