{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T14:24:07Z","timestamp":1788445447428,"version":"build-2803163510"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2021,10,18]],"date-time":"2021-10-18T00:00:00Z","timestamp":1634515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,18]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>An empirical likelihood test is proposed for parameters of models defined by conditional moment restrictions, such as models with nonlinear endogenous covariates, with and without heteroscedastic errors and non-separable transformation models. The number of empirical likelihood constraints is given by the size of the parameter, unlike alternative semi-parametric approaches. We show that the empirical likelihood ratio test is asymptotically pivotal, without explicit studentization. A simulation study shows that the observed size is close to the nominal level, unlike alternative empirical likelihood approaches. It also offers a major advantage over two-stage least-squares, because the relationship between endogenous and instrumental variables does not need to be known. An empirical likelihood model specification test is also proposed.<\/jats:p>","DOI":"10.1093\/ectj\/utab032","type":"journal-article","created":{"date-parts":[[2021,10,19]],"date-time":"2021-10-19T05:17:20Z","timestamp":1634620640000},"page":"384-403","source":"Crossref","is-referenced-by-count":3,"title":["Testing conditional moment restriction models using empirical likelihood"],"prefix":"10.1093","volume":"25","author":[{"given":"Yves G","family":"Berger","sequence":"first","affiliation":[{"name":"Economic, Social and Political Sciences, University of Southampton , Southampton, SO17 1BJ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,10,18]]},"reference":[{"issue":"6)","key":"2022100708570705500_bib1","doi-asserted-by":"crossref","first-page":"1795","DOI":"10.1111\/1468-0262.00470","article-title":"Efficient estimation of models with conditional moment restrictions containing unknown 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