Scraped Data and Sticky Prices

• 成果类型: Article
• 署名作者: Cavallo, Alberto
• 署名单位: Massachusetts Institute of Technology (MIT); National Bureau of Economic Research
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/REST_a_00652
• 发表日期: 2018-03
• 页码: 105-119
• 关键词: multiproduct firms; menu cost; online; facts; inflation; internet; models

摘要

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.