{"title":"Measuring Fishing Capacity Using Quantile Data Envelopment Analysis","authors":"J. Walden, J. Atwood","doi":"10.1086/724932","DOIUrl":null,"url":null,"abstract":"Data envelopment analysis (DEA) is an extensively used method to estimate capacity and technical and economic efficiency of fishing vessels. However, DEA is often criticized because of the influence that outliers, or noisy data, can have on the DEA estimates. Recently, quantile data envelopment analysis (QDEA) was introduced to identify and address issues caused by influential data outliers. QDEA endogenously identifies potential outliers and eliminates them from a given observation’s DEA reference set. In this study, we utilize QDEA to estimate fishing fleet capacity for vessels operating in the northwest Atlantic Ocean during 2019. We present methods for implementing the QDEA model that we think are practical and can be adapted for fishing fleets worldwide. Results show lower capacity estimates using the QDEA model than what the standard capacity model would yield. Our results are quite encouraging in terms of utilizing the QDEA model in future work.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":"38 1","pages":"229 - 247"},"PeriodicalIF":4.6000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1086/724932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Data envelopment analysis (DEA) is an extensively used method to estimate capacity and technical and economic efficiency of fishing vessels. However, DEA is often criticized because of the influence that outliers, or noisy data, can have on the DEA estimates. Recently, quantile data envelopment analysis (QDEA) was introduced to identify and address issues caused by influential data outliers. QDEA endogenously identifies potential outliers and eliminates them from a given observation’s DEA reference set. In this study, we utilize QDEA to estimate fishing fleet capacity for vessels operating in the northwest Atlantic Ocean during 2019. We present methods for implementing the QDEA model that we think are practical and can be adapted for fishing fleets worldwide. Results show lower capacity estimates using the QDEA model than what the standard capacity model would yield. Our results are quite encouraging in terms of utilizing the QDEA model in future work.