R. Färe, S. Grosskopf, T. Lundgren, P. Marklund, Wenchao Zhou
{"title":"Productivity: Should We Include Bads?","authors":"R. Färe, S. Grosskopf, T. Lundgren, P. Marklund, Wenchao Zhou","doi":"10.2139/ssrn.2071078","DOIUrl":null,"url":null,"abstract":"This paper studies the interaction between economic and environmental performance. Applying the directional output distance function approach, the purpose is to compare estimates of Luenberger total factor productivity indicators, including and excluding bad outputs. Specifically, based on unique firm level data from Swedish manufacturing covering the period 1990 to 2008, we explore to what extent excluding bad outputs leads to erroneous productivity measurement. The main conclusion is that bad outputs should not only be included in the estimations, but also reduction in bad outputs should be credited. From this point of view the directional output distance function approach and the Luenberger indicator serves as an appropriate basis of productivity measurement.","PeriodicalId":176966,"journal":{"name":"ERN: Externalities; Redistributive Effects; Environmental Taxes & Subsidies (Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Externalities; Redistributive Effects; Environmental Taxes & Subsidies (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2071078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27
Abstract
This paper studies the interaction between economic and environmental performance. Applying the directional output distance function approach, the purpose is to compare estimates of Luenberger total factor productivity indicators, including and excluding bad outputs. Specifically, based on unique firm level data from Swedish manufacturing covering the period 1990 to 2008, we explore to what extent excluding bad outputs leads to erroneous productivity measurement. The main conclusion is that bad outputs should not only be included in the estimations, but also reduction in bad outputs should be credited. From this point of view the directional output distance function approach and the Luenberger indicator serves as an appropriate basis of productivity measurement.