Nonparametric Identification in Structural Economic Models

Structural economic models allow one to analyze counterfactuals when economic systems change and to evaluate the well-being of economic agents. A key element in such analysis is the ability to identify the primitive functions and distributions of the economic models that are employed to describe the economic phenomena under study. Recent developments have provided ways to achieve identification of these primitive functions and distributions without imposing parametric restrictions. In this article, I consider a small set of stylized models and provide insight into some of the approaches that have been taken to develop nonparametric identification results in those models.