Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/189776
Authors: 
Chernozhukov, Victor
Fernández-Val, Iván
Newey, Whitney
Stouli, Sami
Vella, Francis
Year of Publication: 
2017
Series/Report no.: 
cemmap working paper CWP48/17
Abstract: 
This paper introduces two classes of semiparametric triangular systems with nonadditively separable unobserved heterogeneity. They are based on distribution and quantile regression modeling of the reduced-form conditional distributions of the endogenous variables. We show that these models are flexible and identify the average, distribution and quantile structural functions using 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. We illustrate the implementation and applicability of our methods with numerical simulations and an empirical application to demand analysis.
Subjects: 
Structural functions
nonseparable models
control function
quantile and distribution regression
semiparametric estimation
uniform inference
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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