Partial identification in non-separable triangular models

(2020)

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Abstract
We define an identification region and an estimator for the regression function $g(X, \varepsilon)$ of non-separable triangular models in the case where data is supposed to follow a general missing data pattern. We use fundamental concepts of partial identification, the generation of the unobservable random term $\varepsilon$ from within the model and assumptions on the instrumental variable to do so. General results are given and an empirical example is presented.