{"created":"2021-03-01T07:02:32.361194+00:00","id":42625,"links":{},"metadata":{"_buckets":{"deposit":"4346f92d-9d52-40a5-ba59-c46d6cfad26a"},"_deposit":{"id":"42625","owners":[],"pid":{"revision_id":0,"type":"depid","value":"42625"},"status":"published"},"_oai":{"id":"oai:repository.dl.itc.u-tokyo.ac.jp:00042625","sets":["62:7433:7434","9:7435:7436"]},"item_8_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2014-02","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"CIRJE-F-918","bibliographic_titles":[{"bibliographic_title":"Discussion paper series. CIRJE-F"}]}]},"item_8_description_13":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_8_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"The paper develops empirical Bayes and benchmarked empirical Bayes estimators of positive small area means under multiplicative models. A simple example will be estimation of per capita income for small areas. It is now well-understood that small area estimation needs explicit, or at least implicit use of models. One potential difficulty with model-based estimators is that the overall estimator for a larger geographical area based on (weighted) sum of the model-based estimators is not necessarily identical to the corresponding direct estimator, such as the overall sample mean. One way to fix such a problem is the so-called benchmarking approach which modifies the model-based estimators to match the aggregate direct estimator. Benchmarked hierarchical and empirical Bayes estimators have proved to be particularly useful in this regard. However, while estimating positive small area parameters, the conventional squared error or weighted squared loss subject to the usual benchmark constraint does not necessarily produce positive estimators. Hence, it is necessary to seek other meaningful losses to alleviate this problem. In this paper, we consider the transformed Fay-Herriot model as a multiplicative model for estimating positive small area means, and suggest a weighted Kullback-Leibler divergence as a loss function. We have found out that the resulting Bayes estimator is the posterior mean and that the corresponding benchmarked Bayes and empirical Bayes estimators retain the positivity constraint. The prediction errors of the suggested empirical Bayes estimators are investigated asymptotically, and their second-order unbiased estimators are provided. In addition, bootstrapped estimators of these prediction errors are also provided. The performance of the suggested procedures is investigated through simulation as well as with an empirical study.","subitem_description_type":"Abstract"}]},"item_8_description_6":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"本文フィルはリンク先を参照のこと","subitem_description_type":"Other"}]},"item_8_publisher_20":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"日本経済国際共同センター"}]},"item_8_relation_25":{"attribute_name":"関係URI","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://www.cirje.e.u-tokyo.ac.jp/research/dp/2014/2014cf918ab.html","subitem_relation_type_select":"URI"}}]},"item_8_source_id_10":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11450569","subitem_source_identifier_type":"NCID"}]},"item_8_text_21":{"attribute_name":"出版者別名","attribute_value_mlt":[{"subitem_text_value":"Center for International Research on the Japanese Economy"}]},"item_8_text_4":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Department of Statistics, University of Florida"},{"subitem_text_value":"Faculty of Economics, University of Tokyo"},{"subitem_text_value":"Graduate School of Economics, University of Tokyo"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ghosh, Malay"}],"nameIdentifiers":[{"nameIdentifier":"98024","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Kubokawa, Tatsuya"}],"nameIdentifiers":[{"nameIdentifier":"98025","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Kawakubo, Yuki"}],"nameIdentifiers":[{"nameIdentifier":"98026","nameIdentifierScheme":"WEKO"}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Asymptotic approximation","subitem_subject_scheme":"Other"},{"subitem_subject":"constrained Bayes","subitem_subject_scheme":"Other"},{"subitem_subject":"Fay-Herriot model","subitem_subject_scheme":"Other"},{"subitem_subject":"parametric bootstrap","subitem_subject_scheme":"Other"},{"subitem_subject":"second-order approximation","subitem_subject_scheme":"Other"},{"subitem_subject":"second-order unbiased","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"technical report","resourceuri":"http://purl.org/coar/resource_type/c_18gh"}]},"item_title":"Benchmarked Empirical Bayes Methods in Multiplicative Area-level Models with Risk Evaluation","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Benchmarked Empirical Bayes Methods in Multiplicative Area-level Models with Risk Evaluation"}]},"item_type_id":"8","owner":"1","path":["7436","7434"],"pubdate":{"attribute_name":"公開日","attribute_value":"2014-05-01"},"publish_date":"2014-05-01","publish_status":"0","recid":"42625","relation_version_is_last":true,"title":["Benchmarked Empirical Bayes Methods in Multiplicative Area-level Models with Risk Evaluation"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-19T04:17:46.941234+00:00"}