{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T15:08:39Z","timestamp":1649171319330},"reference-count":19,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2017,2,1]],"date-time":"2017-02-01T00:00:00Z","timestamp":1485907200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":["www.cambridge.org"],"crossmark-restriction":true},"short-container-title":["Econom. Theory"],"published-print":{"date-parts":[[2018,2]]},"abstract":"<jats:p>Using a simplified approach developed by Severini and Tripathi (2001), we calculate the semiparametric efficiency bound for the finite-dimensional parameters of censored linear regression models with heteroskedastic errors. Under an additional identification at infinity type assumption, we propose an efficient estimator based on a novel result from Lewbel and Linton (2002). An extension to censored partially linear single-index models is also presented.<\/jats:p>","DOI":"10.1017\/s0266466617000044","type":"journal-article","created":{"date-parts":[[2017,2,1]],"date-time":"2017-02-01T09:39:05Z","timestamp":1485941945000},"page":"228-245","update-policy":"http:\/\/dx.doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":0,"title":["SEMIPARAMETRIC EFFICIENCY FOR CENSORED LINEAR REGRESSION MODELS WITH HETEROSKEDASTIC ERRORS"],"prefix":"10.1017","volume":"34","author":[{"given":"Tao","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2017,2,1]]},"reference":[{"key":"S0266466617000044_ref6","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1017\/S0266466609090732","article-title":"Efficiency bounds for semiparametric estimation of inverse 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