IDEAS home Printed from https://ideas.repec.org/p/ecb/ecbops/2023320.html
   My bibliography  Save this paper

E-commerce and price setting: evidence from Europe

Author

Listed:
  • Strasser, Georg
  • Wieland, Elisabeth
  • Macias, Paweł
  • Błażejowska, Aneta
  • Szafranek, Karol
  • Wittekopf, David
  • Franke, Jörn
  • Henkel, Lukas
  • Osbat, Chiara

Abstract

E-commerce has become more prevalent throughout Europe in the last decade. The coronavirus (COVID-19) pandemic accelerated this trend, particularly in the retail sector. This paper focuses on the implications of increasing business-to-consumer e-commerce for prices and inflation in the euro area. It highlights three key results. First, whether online prices and inflation are higher or lower than their offline counterparts depends on the distribution model, the sector and the country. Moreover, properly selected online prices track official inflation indices even in real time. Second, the effect of e-commerce on inflation appears to be transient and differs between countries. However, as the penetration of some markets is still low, these transitory effects will likely persist at the euro area level for several years. Third, online prices change more frequently than offline prices. This might lead to greater price flexibility overall as online trade gains market share in a growing number of sectors. JEL Classification: D4, E31, L11

Suggested Citation

  • Strasser, Georg & Wieland, Elisabeth & Macias, Paweł & Błażejowska, Aneta & Szafranek, Karol & Wittekopf, David & Franke, Jörn & Henkel, Lukas & Osbat, Chiara, 2023. "E-commerce and price setting: evidence from Europe," Occasional Paper Series 320, European Central Bank.
  • Handle: RePEc:ecb:ecbops:2023320
    Note: 1137785
    as

    Download full text from publisher

    File URL: https://www.ecb.europa.eu//pub/pdf/scpops/ecb.op320~58d9c47950.en.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Adam, Klaus & Gautier, Erwan & Santoro, Sergio & Weber, Henning, 2022. "The case for a positive euro area inflation target: Evidence from france, germany and italy," Journal of Monetary Economics, Elsevier, vol. 132(C), pages 140-153.
    2. Itai Ater & Oren Rigbi, 2023. "Price Transparency, Media, and Informative Advertising," American Economic Journal: Microeconomics, American Economic Association, vol. 15(1), pages 1-29, February.
    3. Cavallo, Alberto, 2013. "Online and official price indexes: Measuring Argentina's inflation," Journal of Monetary Economics, Elsevier, vol. 60(2), pages 152-165.
    4. Marco Bonomo & Carlos Carvalho & Oleksiy Kryvtsov & Sigal Ribon & Rodolfo Rigato, 2020. "Multi-Product Pricing: Theory and Evidence from Large Retailers in Israel," Staff Working Papers 20-12, Bank of Canada.
    5. Diego Aparicio & Zachary Metzman & Roberto Rigobon, 2021. "The Pricing Strategies of Online Grocery Retailers," NBER Working Papers 28639, National Bureau of Economic Research, Inc.
    6. Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
    7. Aparicio, Diego & Bertolotto, Manuel I., 2020. "Forecasting inflation with online prices," International Journal of Forecasting, Elsevier, vol. 36(2), pages 232-247.
    8. Alberto Cavallo, 2018. "More Amazon Effects: Online Competition and Pricing Behaviors," NBER Working Papers 25138, National Bureau of Economic Research, Inc.
    9. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:ecb:ecbdps:202323 is not listed on IDEAS

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dedola, Luca & Ehrmann, Michael & Hoffmann, Peter & Lamo, Ana & Paz-Pardo, Gonzalo & Slacalek, Jiri & Strasser, Georg, 2023. "Digitalisation and the economy," Working Paper Series 2809, European Central Bank.
    2. repec:ecb:ecbdps:202323 is not listed on IDEAS
    3. Macias, Paweł & Stelmasiak, Damian & Szafranek, Karol, 2023. "Nowcasting food inflation with a massive amount of online prices," International Journal of Forecasting, Elsevier, vol. 39(2), pages 809-826.
    4. Aparicio, Diego & Bertolotto, Manuel I., 2020. "Forecasting inflation with online prices," International Journal of Forecasting, Elsevier, vol. 36(2), pages 232-247.
    5. Diego Aparicio & Alberto Cavallo, 2021. "Targeted Price Controls on Supermarket Products," The Review of Economics and Statistics, MIT Press, vol. 103(1), pages 60-71, March.
    6. Barış Soybilgen & M. Ege Yazgan & Hüseyin Kaya, 2023. "Nowcasting Turkish Food Inflation Using Daily Online Prices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 171-190, September.
    7. Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What's Up with the Phillips Curve?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(1 (Spring), pages 301-373.
    8. Sullivan, Tom, 2022. "Price dispersion in the rideshare industry : a study of the Mexico City market," Warwick-Monash Economics Student Papers 40, Warwick Monash Economics Student Papers.
    9. Patrick Bajari & Zhihao Cen & Victor Chernozhukov & Manoj Manukonda & Jin Wang & Ramon Huerta & Junbo Li & Ling Leng & George Monokroussos & Suhas Vijaykunar & Shan Wan, 2023. "Hedonic prices and quality adjusted price indices powered by AI," CeMMAP working papers 08/23, Institute for Fiscal Studies.
    10. Cavallo, Alberto & Kryvtsov, Oleksiy, 2023. "What can stockouts tell us about inflation? Evidence from online micro data," Journal of International Economics, Elsevier, vol. 146(C).
    11. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    12. Barkan, Oren & Benchimol, Jonathan & Caspi, Itamar & Cohen, Eliya & Hammer, Allon & Koenigstein, Noam, 2023. "Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1145-1162.
    13. Diego Daruich & Julian Kozlowski, 2023. "Macroeconomic Implications of Uniform Pricing," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 64-108, July.
    14. Philip ME Garboden, 2019. "Sources and Types of Big Data for Macroeconomic Forecasting," Working Papers 2019-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    15. W. Erwin Diewert & Kevin J. Fox, 2020. "Measuring Real Consumption and CPI Bias under Lockdown Conditions," NBER Working Papers 27144, National Bureau of Economic Research, Inc.
    16. Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2023. "Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany," Discussion Papers 34/2023, Deutsche Bundesbank.
    17. Resce, Giuliano & Maynard, Diana, 2018. "What matters most to people around the world? Retrieving Better Life Index priorities on Twitter," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 61-75.
    18. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially Biased Statistics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(1 (Spring), pages 59-108.
    19. Hillen, Judith & Fedoseeva, Svetlana, 2021. "E-commerce and the end of price rigidity?," Journal of Business Research, Elsevier, vol. 125(C), pages 63-73.

    More about this item

    Keywords

    consumer prices; e-commerce; inflation; microdata; price rigidity;
    All these keywords.

    JEL classification:

    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ecb:ecbops:2023320. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Official Publications (email available below). General contact details of provider: https://edirc.repec.org/data/emieude.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.