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Scraped Data and Sticky Prices

Alberto Cavallo

MIT and NBER

The Review of Economics and Statistics 2018 open access

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.

DOI
10.1162/rest_a_00652
Volume
100 (1)
Pages
105-119
Language
en
Export
BibTeX
Sources
openalex crossref