A new approach for quality-adjusting PPI microprocessors.
The Producer Price Index (PPI) for microprocessors has declined more slowly since 2010 than it did previously. This shift in microprocessors inflation occurred at the same time that a major manufacturer changed its pricing behavior. With these changes, we must explore a different approach to the mat...
| Publicado en: | Monthly Labor Review pp. 1 - 33 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
US Department of Labor
Dec2018
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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=134100510&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 134100510 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: Dec2018 pid: 1929 pub: US Department of Labor artinfo: ui: 134100510 10.21916/mlr.2018.29 ppf: 1 ppct: 32 formats: fmt: @attributes: type: P size: 4.7MB tig: atl: A new approach for quality-adjusting PPI microprocessors. aug: au: Sawyer, Steven D. So, Alvin affil: Economist in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics Economist of the U.S. Bureau of Labor Statistics su: Wholesale price indexes Microprocessors Product quality Quality of service Statistical learning sug: subj: Wholesale price indexes Microprocessors Product quality Quality of service Statistical learning ab: The Producer Price Index (PPI) for microprocessors has declined more slowly since 2010 than it did previously. This shift in microprocessors inflation occurred at the same time that a major manufacturer changed its pricing behavior. With these changes, we must explore a different approach to the matched-model methodology that has been used for microprocessors. Hedonic quality adjustment can account for changes in the quality (characteristics) of products that cannot be captured with the use of a matched model. We look at the implementation of a time dummy hedonic model in a recent article and evaluate its suitability to PPI microprocessors. We then develop our own time dummy hedonic model for microprocessors. The choice of characteristics to include in a model is crucial, because the characteristics help determine the inflation rate the model estimates. We turn to statistical learning techniques to select characteristics for our model. We use our model to construct counterfactual PPI indexes for 2009-17 to determine what the effect of using our model would have been. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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