Nonparametric Identification in Structural Economic Models

2013/05/17 by Rosa L. Matzkin · 74 citations
Economics, Econometrics and Finance · Business, Management and Accounting · Mathematics · #Economic theories and models #Consumer Market Behavior and Pricing #Complex Systems and Time Series Analysis #Stylized fact #Identification (biology) #Nonparametric statistics #Economic model #Counterfactual conditional #Econometrics #Set (abstract data type) #Parametric statistics #Parametric model #Key (lock) #Computer science #Economics #Mathematical economics #Mathematics #Counterfactual thinking #Macroeconomics #Statistics

paper · doi:10.1146/annurev-economics-082912-110231

published in Annual Review of Economics 5(1), 457-486 (Annual Reviews)

openalex publication_date 2013/05/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/15

Abstract

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.

Citations

• Identification in Parametric Models
• Instrumental Variable Estimation of Nonparametric Models
• The Jacobian matrix and global univalence of mappings
• Nonparametric methods for inference in the presence of instrumental variables
• Maximum score estimation of the stochastic utility model of choice
• The Statistical Implications of a System of Simultaneous Equations
• A Note on the Pure Theory of Consumer's Behaviour
• Nonparametric Instrumental Regression

Cited by

• Parameter identification problem [wikipedia]

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