{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,5]],"date-time":"2025-10-05T04:19:07Z","timestamp":1759637947674},"reference-count":19,"publisher":"Cambridge University Press (CUP)","issue":"5","license":[{"start":{"date-parts":[[2016,9,19]],"date-time":"2016-09-19T00:00:00Z","timestamp":1474243200000},"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":[[2017,10]]},"abstract":"<jats:p>This paper proposes an empirical likelihood-based estimation method for semiparametric conditional moment restriction models, which contain finite dimensional unknown parameters and unknown functions. We extend the results of Donald, Imbens, and Newey (2003, <jats:italic>Journal of Econometrics<\/jats:italic> 117, 55\u201393) by allowing unknown functions to be included in the conditional moment restrictions. We approximate unknown functions by a sieve method and estimate the finite dimensional parameters and unknown functions jointly. We establish consistency and derive the convergence rate of the estimator. We also show that the estimator of the finite dimensional parameters is <jats:inline-formula><jats:alternatives><jats:graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" orientation=\"portrait\" mime-subtype=\"gif\" mimetype=\"image\" position=\"float\" xlink:type=\"simple\" xlink:href=\"S0266466616000360_inline1\" \/><jats:tex-math>$\\sqrt n$<\/jats:tex-math><\/jats:alternatives><\/jats:inline-formula>-consistent, asymptotically normally distributed, and asymptotically efficient.<\/jats:p>","DOI":"10.1017\/s0266466616000360","type":"journal-article","created":{"date-parts":[[2016,9,19]],"date-time":"2016-09-19T01:35:45Z","timestamp":1474248945000},"page":"1242-1258","update-policy":"http:\/\/dx.doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":2,"title":["A NOTE ON GENERALIZED EMPIRICAL LIKELIHOOD ESTIMATION OF SEMIPARAMETRIC CONDITIONAL MOMENT RESTRICTION MODELS"],"prefix":"10.1017","volume":"33","author":[{"given":"Naoya","family":"Sueishi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2016,9,19]]},"reference":[{"key":"S0266466616000360_ref18","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1016\/j.jeconom.2006.05.004","article-title":"Efficient information theoretic inference for conditional moment restrictions","volume":"138","author":"Smith","year":"2006","journal-title":"Journal of Econometrics"},{"key":"S0266466616000360_ref1","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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