Exploring quality adjustment in PPI cloud computing.
The article discusses the challenges in accurately measuring price changes in cloud computing services due to rapid technological advancements. It mentions the use of time dummy hedonic models is proposed as a solution, using publicly available data and statistical learning techniques to select vari...
| Publicado en: | Monthly Labor Review pp. 1 - 26 |
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| Formato: | Artículo |
| Publicado: |
US Department of Labor
Feb2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=162197878&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 162197878 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00981818 MLR jtl: Monthly Labor Review issn: 00981818 maglogo: N pubinfo: dt: Feb2023 pid: 1929 pub: US Department of Labor artinfo: ui: 162197878 10.21916/mlr.2023.4 ppf: 1 ppct: 25 formats: fmt: @attributes: type: P size: 1.7MB tig: atl: Exploring quality adjustment in PPI cloud computing. aug: ab: The article discusses the challenges in accurately measuring price changes in cloud computing services due to rapid technological advancements. It mentions the use of time dummy hedonic models is proposed as a solution, using publicly available data and statistical learning techniques to select variables, and shows results which exhibits that microprocessor characteristics can be used to estimate quality-adjusted price change. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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