Differences in Wage Distributions Between Canada and the United States: An Application of a Flexible Estimator of Distribution Functions in the Presence of Covariates
提出一种灵活的函数形式估计量，用于估计非负随机变量的累积分布函数，并应用于比较加拿大和美国全职男性工人的工资不平等，发现加拿大工资分布左右尾部更薄，工会作用显著。
We construct a tractable, flexible-functional-form estimator of cumulative distribution functions for non-negative random variables which admits large numbers of covariates. The estimator adopts and extends techniques from the spell-duration literature for estimating hazard functions to distribution functions for wages, earnings, and income. We apply these methods to investigate sources of wage inequality for full-time male workers between Canada and the United States, finding that the Canadian wage density has a thinner left tail because low-educated workers have higher pay and a thinner right tail because of a lower proportion of highly-educated workers. Unions appear to play a large role in these outcomes.