NONPARAMETRIC IDENTIFICATION OF POSITIVE EIGENFUNCTIONS
NONPARAMETRIC IDENTIFICATION OF POSITIVE EIGENFUNCTIONS
复制标题
正特征函数的非参数辨识
作者：
T. Christensen
通过研究适当选择的线性算子的正本征函数，可以揭示某些经济模型的重要特征。例子包括动态资产定价模型中的长期风险收益关系和外部习惯形成模型中的边际效用成分。本文给出了非参数模型正特征函数的识别条件。如果该算子满足两个温和的正性条件和一个幂紧性条件，则可以实现识别。在进一步的非简并条件下，得到了存在性和可识别性。一般的结果被应用到获得新的外部习惯形成模型的识别条件和定价算子的正特征函数的动态资产定价模型。
Important features of certain economic models may be revealed by studying positive eigenfunctions of appropriately chosen linear operators. Examples include long-run risk–return relationships in dynamic asset pricing models and components of marginal utility in external habit formation models. This paper provides identification conditions for positive eigenfunctions in nonparametric models. Identification is achieved if the operator satisfies two mild positivity conditions and a power compactness condition. Both existence and identification are achieved under a further nondegeneracy condition. The general results are applied to obtain new identification conditions for external habit formation models and for positive eigenfunctions of pricing operators in dynamic asset pricing models.