Scraped Data and Sticky Prices
利用五个国家在线零售商的日度价格数据，研究测量偏差对三种常见价格粘性统计量的影响，发现在线价格持续时间更长、价格变化更少接近零，且风险函数初期递增。
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.