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More Amazon Effects: Online Competition and Pricing Behaviors


  • Alberto Cavallo


I study how online competition, with its algorithmic pricing technologies and the transparency of the Internet, can change the pricing behavior of large retailers and affect aggregate inflation dynamics. In particular, I show that online competition has raised both the frequency of price changes and the degree of uniform pricing across locations in the U.S. over the past 10 years. These changes make retail prices more sensitive to aggregate ``nationwide" shocks, increasing the pass-through of both gas prices and nominal exchange rate fluctuations.

Suggested Citation

  • Alberto Cavallo, 2018. "More Amazon Effects: Online Competition and Pricing Behaviors," NBER Working Papers 25138, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:25138
    Note: IFM ME

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    References listed on IDEAS

    1. Bernardo Guimaraes & Kevin D. Sheedy, 2011. "Sales and Monetary Policy," American Economic Review, American Economic Association, vol. 101(2), pages 844-876, April.
    2. Yuriy Gorodnichenko & Viacheslav Sheremirov & Oleksandr Talavera, 2018. "Price Setting in Online Markets: Does IT Click?," Journal of the European Economic Association, European Economic Association, vol. 16(6), pages 1764-1811.
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    1. Inflation risks and inflation expectations
      by Steve Cecchetti and Kim Schoenholtz in Money, Banking and Financial Markets on 2019-02-25 13:49:59


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    Cited by:

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    2. Lodge, David & Pérez, Javier J. & Albrizio, Silvia & Everett, Mary & De Bandt, Olivier & Georgiadis, Georgios & Ca' Zorzi, Michele & Lastauskas, Povilas & Carluccio, Juan & Parrága, Susana & Carvalho,, 2021. "The implications of globalisation for the ECB monetary policy strategy," Occasional Paper Series 263, European Central Bank.
    3. Fontaine, François & Martin, Julien & Mejean, Isabelle, 2020. "Price discrimination within and across EMU markets: Evidence from French exporters," Journal of International Economics, Elsevier, vol. 124(C).
    4. Gopalakrishnan, Raja & Guevara, C. Angelo & Ben-Akiva, Moshe, 2020. "Combining multiple imputation and control function methods to deal with missing data and endogeneity in discrete-choice models," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 45-57.
    5. Diego Daruich & Julian Kozlowski, 2018. "Uniform Pricing Within and Across Regions: New Evidence from Argentina," Working Papers 2018-10, Federal Reserve Bank of St. Louis.
    6. Nagengast, Arne J. & Bursian, Dirk & Menz, Jan-Oliver, 2021. "Dynamic pricing and exchange rate pass-through: Evidence from transaction-level data," European Economic Review, Elsevier, vol. 133(C).
    7. Weinand, Sebastian, 2020. "Measuring spatial price differentials: A comparison of stochastic index number methods," Discussion Papers 12/2020, Deutsche Bundesbank.
    8. Bańbura, Marta & Bobeica, Elena, 2020. "Does the Phillips curve help to forecast euro area inflation?," Working Paper Series 2471, European Central Bank.
    9. Rigobon, Roberto, 2020. "What can online prices teach us about exchange rate pass-through?," Journal of International Money and Finance, Elsevier, vol. 106(C).
    10. Glocker, Christian & Piribauer, Philipp, 2021. "Digitalization, retail trade and monetary policy," Journal of International Money and Finance, Elsevier, vol. 112(C).
    11. Claudio Borio, 2019. "Central banking in challenging times," BIS Working Papers 829, Bank for International Settlements.
    12. Hillen, Judith & Fedoseeva, Svetlana, 2021. "E-commerce and the end of price rigidity?," Journal of Business Research, Elsevier, vol. 125(C), pages 63-73.

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    More about this item

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
    • E7 - Macroeconomics and Monetary Economics - - Macro-Based Behavioral Economics

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