Scraped Data and Sticky Prices

A-Tier
Journal: Review of Economics and Statistics
Year: 2018
Volume: 100
Issue: 1
Pages: 105-119

Score contribution per author:

4.036 = (α=2.02 / 1 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:tpr:restat:v:100:y:2018:i:1:p:105-119
Journal Field
General
Author Count
1
Added to Database
2026-01-25