An increasing fraction of jobs in the U.S. labor market explicitly pay workers for their performance using bonus pay, commissions, or piece-rate contracts. Using data from the Panel Study of Income Dynamics, we show that compensation in performance-pay jobs is more closely tied to both observed and unobserved productive characteristics of workers than compensation in non-performance-pay jobs. We also find that the return to these productive characteristics increased faster over time in performance-pay than in non-performance-pay jobs. We show that this finding is consistent with the view that underlying changes in returns to skill due, for instance, to technological change induce more firms to offer performance-pay contracts and result in more wage inequality among workers who are paid for performance. Thus, performance pay provides a channel through which underlying changes in returns to skill get translated into higher wage inequality. We conclude that this channel accounts for 21% of the growth in the variance of male wages between the late 1970s and the early 1990s and for most of the increase in wage inequality above the eightieth percentile over the same period.

We propose a new regression method to evaluate the impact of changes in the distribution of the explanatory variables on quantiles of the unconditional (marginal) distribution of an outcome variable. The proposed method consists of running a regression of the (recentered) influence function (RIF) of the unconditional quantile on the explanatory variables. The influence function, a widely used tool in robust estimation, is easily computed for quantiles, as well as for other distributional statistics. Our approach, thus, can be readily generalized to other distributional statistics.