Scraped Data and Sticky Prices

Author(s)
Cavallo, Alberto F.
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Abstract
I 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.
Date issued
2016-11
URI
http://hdl.handle.net/1721.1/114028
Department
Sloan School of Management
Journal
Review of Economics and Statistics
Publisher
MIT Press
Citation
Cavallo, Alberto. “Scraped Data and Sticky Prices.” The Review of Economics and Statistics, November 2016. © 2016 MIT Press
Version: Final published version
ISSN
0034-6535
1530-9142
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