NONPARAMETRIC IDENTIFICATION OF POSITIVE EIGENFUNCTIONS
研究了非参数模型中正特征函数的识别条件，通过算子的正性和幂紧性条件实现识别，并应用于外部习惯形成模型和动态资产定价模型。
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.