{"title":"局部指数边界估计","authors":"Carlos Martins-Filho, F. Ziegelmann, H. Torrent","doi":"10.12660/BRE.V33N22013.26508","DOIUrl":null,"url":null,"abstract":"In this paper we propose a local exponential estimator for a multiplicative nonparametric frontiermodel rst introduced by Martins-Filho & Yao (2007). We improve their estimation procedure by adoptinga variant of the local exponential smoothing introduced in Ziegelmann (2002). Our estimator is shown to beconsistent and asymptotically normal under mild regularity conditions. In addition, due to local exponentialsmoothing, potential negativity of conditional variance functions that may hinder the use of Martins-Filhoand Yao's estimator is avoided. A Monte Carlo study is performed to shed light on the nite sample proper-ties of the estimator and to contrast its performance with that of the estimator proposed in Martins-Filho &Yao (2007). We also conduct an empirical exercise in which a production function and associated ecienciesfor branches of nancial institutions in the United States are estimated.","PeriodicalId":332423,"journal":{"name":"Brazilian Review of Econometrics","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Local Exponential Frontier Estimation\",\"authors\":\"Carlos Martins-Filho, F. Ziegelmann, H. Torrent\",\"doi\":\"10.12660/BRE.V33N22013.26508\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we propose a local exponential estimator for a multiplicative nonparametric frontiermodel rst introduced by Martins-Filho & Yao (2007). We improve their estimation procedure by adoptinga variant of the local exponential smoothing introduced in Ziegelmann (2002). Our estimator is shown to beconsistent and asymptotically normal under mild regularity conditions. In addition, due to local exponentialsmoothing, potential negativity of conditional variance functions that may hinder the use of Martins-Filhoand Yao's estimator is avoided. A Monte Carlo study is performed to shed light on the nite sample proper-ties of the estimator and to contrast its performance with that of the estimator proposed in Martins-Filho &Yao (2007). We also conduct an empirical exercise in which a production function and associated ecienciesfor branches of nancial institutions in the United States are estimated.\",\"PeriodicalId\":332423,\"journal\":{\"name\":\"Brazilian Review of Econometrics\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Brazilian Review of Econometrics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12660/BRE.V33N22013.26508\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brazilian Review of Econometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12660/BRE.V33N22013.26508","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we propose a local exponential estimator for a multiplicative nonparametric frontiermodel rst introduced by Martins-Filho & Yao (2007). We improve their estimation procedure by adoptinga variant of the local exponential smoothing introduced in Ziegelmann (2002). Our estimator is shown to beconsistent and asymptotically normal under mild regularity conditions. In addition, due to local exponentialsmoothing, potential negativity of conditional variance functions that may hinder the use of Martins-Filhoand Yao's estimator is avoided. A Monte Carlo study is performed to shed light on the nite sample proper-ties of the estimator and to contrast its performance with that of the estimator proposed in Martins-Filho &Yao (2007). We also conduct an empirical exercise in which a production function and associated ecienciesfor branches of nancial institutions in the United States are estimated.