Nonparametric estimation of marginal effects in regression-spline random effects models
研究了B样条回归方法对随机效应模型进行非参数建模，重点估计边际效应及其渐近性质，并通过蒙特卡洛模拟和1970-1986年美国48州面板数据验证方法，分析公共基础设施对私人生产的影响。
We consider a B-spline regression approach toward nonparametric modeling of a random effects (error component) model. We focus our attention on the estimation of marginal effects (derivatives) and their asymptotic properties. Theoretical underpinnings are provided, finite-sample performance is evaluated via Monte–Carlo simulation, and an application that examines the contribution of different types of public infrastructure on private production is investigated using panel data comprising the 48 contiguous states in the United States over the period 1970–1986.