Scraped data and sticky prices

This paper introduces Scraped Data as a new source of micro-price information for the study of sticky prices. Scraped data are collected from online retailers and have a unique advantage in sampling frequency, product details, and country availability. Using daily prices of 80 thousand products in four countries, between 2007 and 2010, I present three new empirical results. First, the distribution of the size of price changes is bimodal, with few changes close to zero percent. Second, hazard functions are hump-shaped, with the probability of a price change increasing for the first 40 to 90 days. Third, there is daily synchronization in the timing of price changes among closely competing brands. These findings are consistent with adjustment costs and strategic interactions in price-setting decisions