Semiparametric estimation of structural functions in nonseparable triangular models

Victor Chernozhukov, Ivan Fernandez-Val, Whitney Newey, Sami Stouli, Francis Vella

Research output: Contribution to journalArticle (Academic Journal)peer-review

8 Citations (Scopus)
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Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modelling of complex structural relationships. However, they are not commonly used in practice due to the need for exogenous variables with large support for identification, the curse of dimensionality in estimation, and the lack of inferential tools. This paper introduces two classes of semiparametric nonseparable triangular models that address these limitations. They are based on distribution and quantile regression modelling of the reduced form conditional distributions of the endogenous variables. We show that average, distribution and quantile structural functions are identified in these systems through a control function approach that does not require a large support condition. We propose a computationally attractive three-stage procedure to estimate the structural functions where the first two stages consist of quantile or distribution regressions. We provide asymptotic theory and uniform inference methods for each stage. In particular, we derive functional central limit theorems and bootstrap functional central limit theorems for the distribution regression estimators of the structural functions. These results establish the validity of the bootstrap for three-stage estimators of structural functions, and lead to simple inference algorithms. We illustrate the implementation and applicability of all our methods with numerical simulations and an empirical application to demand analysis.
Original languageEnglish
Pages (from-to)503-533
Number of pages31
JournalQuantitative Economics
Issue number2
Publication statusPublished - 4 May 2020

Structured keywords

  • ECON Econometrics
  • ECON CEPS Data


  • Structural functions
  • nonseparable models
  • control function
  • quantile and distribution regression
  • semiparametric estimation
  • uniform inference

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