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dc.contributor.authorCavallo, Alberto F.
dc.date.accessioned2018-03-06T15:35:08Z
dc.date.available2018-03-06T15:35:08Z
dc.date.issued2016-11
dc.date.submitted2016-06
dc.identifier.issn0034-6535
dc.identifier.issn1530-9142
dc.identifier.urihttp://hdl.handle.net/1721.1/114028
dc.description.abstractI use daily prices collected from online retailers in five countries to study the impact of measurement bias on three common price stickiness statistics. Relative to previous results, I find that online prices have longer durations, with fewer price changes close to 0, and hazard functions that initially increase over time. I show that time-averaging and imputed prices in scanner and CPI data can fully explain the differences with the literature. I then report summary statistics for the duration and size of price changes using scraped data collected from 181 retailers in 31 countries.en_US
dc.publisherMIT Pressen_US
dc.relation.isversionofhttp://dx.doi.org/10.1162/REST_A_00652en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceMassachusetts Institute of Technology Pressen_US
dc.titleScraped Data and Sticky Pricesen_US
dc.typeArticleen_US
dc.identifier.citationCavallo, Alberto. “Scraped Data and Sticky Prices.” The Review of Economics and Statistics, November 2016. © 2016 MIT Pressen_US
dc.contributor.departmentSloan School of Managementen_US
dc.contributor.mitauthorCavallo, Alberto F.
dc.relation.journalReview of Economics and Statisticsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2018-03-02T14:53:45Z
dspace.orderedauthorsCavallo, Albertoen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-9701-3507
mit.licensePUBLISHER_POLICYen_US


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