Joint Estimation and Bandwidth Selection in Partially Parametric Models
提出一种同时估计参数向量和带宽向量的单步方法，用于包含已知非线性参数部分和未知非参数部分的模型，并应用于部分常替代弹性生产函数估计，发现线性化参数会导致经济上不可行的估计结果。
ABSTRACT We propose a single‐step approach to estimating a model with both a known nonlinear parametric component and an unknown nonparametric component. We study the large sample behavior of a simultaneous optimization routine that estimates both the parameter vector of the parametric component and the bandwidth vector used to smooth the unknown function. In our application, we estimate a partially constant elasticity of substitution production function and uncover results that are relevant for policy‐driven conclusions stemming from macroeconomic theory. An attempt to make the parametric component linear in parameters leads to parameter estimates that are economically infeasible, showing the need for our approach in practice.