{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T21:16:09Z","timestamp":1788642969984,"version":"build-2803163510"},"reference-count":40,"publisher":"Cambridge University Press (CUP)","issue":"6","license":[{"start":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T00:00:00Z","timestamp":1682294400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Econom. Theory"],"published-print":{"date-parts":[[2024,12]]},"abstract":"<jats:p>We propose various semiparametric estimators for nonlinear selection models, where slope and intercept can be separately identified. When the selection equation satisfies a monotonic index restriction, we suggest a local polynomial estimator, using only observations for which the marginal cumulative distribution function of the instrument index is close to one. Data-driven procedures such as cross-validation may be used to select the bandwidth for this estimator. We then consider the case in which the monotonic index restriction does not hold and\/or the set of observations with a propensity score close to one is thin so that convergence occurs at a rate that is arbitrarily close to the cubic rate. We explore the finite sample behavior in a Monte Carlo study and illustrate the use of our estimator using a model for count data with multiplicative unobserved heterogeneity.<\/jats:p>","DOI":"10.1017\/s0266466623000105","type":"journal-article","created":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T10:48:21Z","timestamp":1682333301000},"page":"1311-1363","source":"Crossref","is-referenced-by-count":1,"title":["INTERCEPT ESTIMATION IN NONLINEAR SELECTION MODELS"],"prefix":"10.1017","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6760-1412","authenticated-orcid":false,"given":"Wiji","family":"Arulampalam","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valentina","family":"Corradi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Gutknecht","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2023,4,24]]},"reference":[{"key":"S0266466623000105_r20","doi-asserted-by":"publisher","DOI":"10.2307\/1912352"},{"key":"S0266466623000105_r29","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9892.1996.tb00294.x"},{"key":"S0266466623000105_r5","doi-asserted-by":"publisher","DOI":"10.1090\/S0025-5718-1976-0421040-7"},{"key":"S0266466623000105_r2","doi-asserted-by":"publisher","DOI":"10.1111\/1467-937X.00055"},{"key":"S0266466623000105_r26","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466600005636"},{"key":"S0266466623000105_r27","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/S0304-4076(03)00157-X","article-title":"Nonparametric estimation of regression functions with both categorical and continuous data","volume":"119","author":"Li","year":"2004","journal-title":"Journal of Econometrics"},{"key":"S0266466623000105_r30","doi-asserted-by":"publisher","DOI":"10.1016\/j.red.2006.06.001"},{"key":"S0266466623000105_r17","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2014.06.003"},{"key":"S0266466623000105_r33","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176325632"},{"key":"S0266466623000105_r23","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2014.09.011"},{"key":"S0266466623000105_r36","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466602181035"},{"key":"S0266466623000105_r10","doi-asserted-by":"publisher","DOI":"10.1111\/j.1368-423X.2006.00187.x"},{"key":"S0266466623000105_r15","unstructured":"Goh, C. 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