PARAMETRIC CONDITIONAL MEAN INFERENCE WITH FUNCTIONAL DATA APPLIED TO LIFETIME INCOME CURVES
提出一种针对函数型协变量的参数条件均值模型估计框架，证明了估计量的相合性和渐近正态性，并研究了Wald、拉格朗日乘子和拟似然比检验，应用于不同人口群体的终生收入路径比较。
Abstract We propose a framework for estimation of the conditional mean function in a parametric model with function space covariates. The approach employs a functional mean squared error objective criterion. Under regularity conditions, consistency and asymptotic normality are established. The analysis extends to situations where the asymptotic properties are influenced by estimation errors arising from the presence of nuisance parameters. Wald, Lagrange multiplier, and quasi‐likelihood ratio statistics are studied. An empirical application conducts lifetime income path comparisons across different demographic groups according to years of work experience.