{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T15:40:49Z","timestamp":1790264449617,"version":"4.1.0"},"reference-count":32,"publisher":"The Econometric Society","issue":"2","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["QE"],"abstract":"<jats:p>Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modeling 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 modeling 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\u2010stage 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\u2010stage 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.<\/jats:p>","DOI":"10.3982\/qe1239","type":"journal-article","created":{"date-parts":[[2020,5,5]],"date-time":"2020-05-05T07:43:26Z","timestamp":1588664606000},"page":"503-533","source":"Crossref","is-referenced-by-count":20,"title":["Semiparametric estimation of structural functions in nonseparable triangular models"],"prefix":"10.3982","volume":"11","author":[{"given":"Victor","family":"Chernozhukov","sequence":"first","affiliation":[{"name":"Department of Economics, MIT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iv\u00e1n","family":"Fern\u00e1ndez-Val","sequence":"additional","affiliation":[{"name":"Department of Economics, Boston University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Whitney","family":"Newey","sequence":"additional","affiliation":[{"name":"Department of Economics, MIT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sami","family":"Stouli","sequence":"additional","affiliation":[{"name":"Department of Economics, University of Bristol"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francis","family":"Vella","sequence":"additional","affiliation":[{"name":"Department of Economics, Georgetown University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2359","published-online":{"date-parts":[[2020]]},"reference":[{"issue":"6","key":"quan200050-bib-0001","doi-asserted-by":"crossref","first-page":"1613","DOI":"10.1111\/j.1468-0262.2007.00808.x","volume":"75","author":"Blundell","year":"2007","journal-title":"Econometrica"},{"key":"quan200050-bib-0002","unstructured":"Blundell, R., W. 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