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Scraped Data and Sticky Prices

Author

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  • Alberto Cavallo

    (MIT and NBER)

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.

Suggested Citation

  • Alberto Cavallo, 2018. "Scraped Data and Sticky Prices," The Review of Economics and Statistics, MIT Press, vol. 100(1), pages 105-119, March.
    • Handle: RePEc:tpr:restat:v:100:y:2018:i:1:p:105-119
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    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/REST_a_00652
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    JEL classification:

    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General

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