IDEAS home Printed from https://ideas.repec.org/a/eee/asieco/v80y2022ics1049007822000343.html
   My bibliography  Save this article

Spread of E-commerce, prices and inflation dynamics: Evidence from online price big data in Korea

Author

Listed:
  • Yim, Sung Taek
  • Son, Jong Chil
  • Lee, Jiwon

Abstract

The so-called Amazon effect is generally defined as such that the increasing competition in the online market and between online and traditional retailers is reducing retail markups and putting downward pressure on prices. This paper investigates the existence of the Amazon effect using online price big data in Korea where e-commerce has been rapidly spreading. For this task, the direct comparison between the online and offline prices were conducted in terms of the levels, trends, inflations, and dynamic correlations for two prices. Online prices for products were collected and classified under the identical classification in the CPI for 14 items in two divisions: food and non-alcoholic beverages and clothing and footwear. Laspeyres formula with identical weights as for the CPIs was applied to compilation of the item- and division-level OPIs (online price indexes) from July 2018 to June 2019. The empirical analyses overall indicated that persistent decreasing trends in the online prices were found when compared to those in the offline prices represented by the CPIs, indicating the existence of the Amazon effect in Korea. More specifically, the OPI covering two divisions decreased by 1.8%, while the CPI increased by 3.6% for the period. In addition, the close dynamic correlations between on-month inflations of two indexes were also found in panel regression and VAR estimations, indicating that a 1% increasing shock to OPI inflation led to an around 0.3% increasing response in the CPI inflation. The dynamic correlations, however, were quite different across the divisions. Those were more pronounced for the division of food and non-alcoholic beverages while they were found little in the division of clothing and footwear.

Suggested Citation

  • Yim, Sung Taek & Son, Jong Chil & Lee, Jiwon, 2022. "Spread of E-commerce, prices and inflation dynamics: Evidence from online price big data in Korea," Journal of Asian Economics, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:asieco:v:80:y:2022:i:c:s1049007822000343
    DOI: 10.1016/j.asieco.2022.101475
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1049007822000343
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.asieco.2022.101475?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alberto Cavallo, 2017. "Are Online and Offline Prices Similar? Evidence from Large Multi-channel Retailers," American Economic Review, American Economic Association, vol. 107(1), pages 283-303, January.
    2. Feenstra, Robert C, 1994. "New Product Varieties and the Measurement of International Prices," American Economic Review, American Economic Association, vol. 84(1), pages 157-177, March.
    3. Yi, Myung Hoon & Choi, Changkyu, 2005. "The effect of the Internet on inflation: Panel data evidence," Journal of Policy Modeling, Elsevier, vol. 27(7), pages 885-889, October.
    4. Mr. Balazs Csonto & Yuxuan Huang & Mr. Camilo E Tovar Mora, 2019. "Is Digitalization Driving Domestic Inflation?," IMF Working Papers 2019/271, International Monetary Fund.
    5. 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.
    6. Austan D. Goolsbee & Peter J. Klenow, 2018. "Internet Rising, Prices Falling: Measuring Inflation in a World of E-Commerce," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 488-492, May.
    7. Austan D. Goolsbee & Peter J. Klenow, 2018. "Internet Rising, Prices Falling: Measuring Inflation in a World of E-Commerce," NBER Working Papers 24649, National Bureau of Economic Research, Inc.
    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. Aitor Goti & Leire Querejeta-Lomas & Aitor Almeida & José Gaviria de la Puerta & Diego López-de-Ipiña, 2023. "Artificial Intelligence in Business-to-Customer Fashion Retail: A Literature Review," Mathematics, MDPI, vol. 11(13), pages 1-32, June.
    2. Bogdan Oancea, 2023. "Automatic Product Classification Using Supervised Machine Learning Algorithms in Price Statistics," Mathematics, MDPI, vol. 11(7), pages 1-32, March.
    3. Yao Li & Yugang He & Renhong Wu, 2023. "Traversing the Macroeconomic Terrain: An Exploration of South Korea’s Economic Responsiveness to Cross-Border E-Commerce Production Technology Alterations in the Global Arena," Sustainability, MDPI, vol. 15(15), pages 1-20, July.

    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. 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.
    2. Mr. Balazs Csonto & Yuxuan Huang & Mr. Camilo E Tovar Mora, 2019. "Is Digitalization Driving Domestic Inflation?," IMF Working Papers 2019/271, International Monetary Fund.
    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. Anderton, Robert & Jarvis, Valerie & Labhard, Vincent & Morgan, Julian & Petroulakis, Filippos & Vivian, Lara, 2020. "Virtually everywhere? Digitalisation and the euro area and EU economies," Occasional Paper Series 244, European Central Bank.
    5. Ha,Jongrim & Ivanova,Anna & Ohnsorge,Franziska Lieselotte & Unsal Portillo Ocando,Derya Filiz, 2019. "Inflation : Concepts, Evolution, and Correlates," Policy Research Working Paper Series 8738, The World Bank.
    6. Yoon J. Jo & Misaki Matsumura & David E. Weinstein, 2019. "The Impact of E-Commerce on Relative Prices and Consumer Welfare," NBER Working Papers 26506, National Bureau of Economic Research, Inc.
    7. Diewert, Erwin & FOX, Kevin J. Fox & SCHREYER, Paul, 2017. "The Digital Economy, New Products and Consumer Welfare," Microeconomics.ca working papers erwin_diewert-2017-12, Vancouver School of Economics, revised 14 Dec 2017.
    8. Vivian Chu & Tatjana Dahlhaus & Christopher Hajzler, 2023. "Digitalization: Prices of Goods and Services," Discussion Papers 2023-27, Bank of Canada.
    9. Baslandze, Salomé & Argente, David & Hanley, Douglas & Moreira, Sara, 2020. "Patents to Products: Product Innovation and Firm Dynamics," CEPR Discussion Papers 14692, C.E.P.R. Discussion Papers.
    10. 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.
    11. Aitor Lacuesta & Pau Roldan & Darío Serrano-Puente, 2020. "Effects of e-commerce on prices and business competition," Economic Bulletin, Banco de España, issue 4/2020.
    12. Cong Peng, 2019. "Does e-commerce reduce traffic congestion? Evidence from Alibaba Single Day shopping event," CEP Discussion Papers dp1646, Centre for Economic Performance, LSE.
    13. Goldin, Ian & Koutroumpis, Pantelis & Lafond, François & Winkler, Julian, 2020. "Why is productivity slowing down?," MPRA Paper 99172, University Library of Munich, Germany.
    14. Doris Ritzberger-Grünwald & Fabio Rumler, 2019. "Challenges for measuring inflation in a digital world from a monetary policy perspective," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/19, pages 42-53.
    15. Paul Dolfen & Liran Einav & Peter J. Klenow & Benjamin Klopack & Jonathan D. Levin & Larry Levin & Wayne Best, 2023. "Assessing the Gains from E-Commerce," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(1), pages 342-370, January.
    16. Jouchi Nakajima & Masato Takahashi & Tomoyuki Yagi, "undated". "An Assessment of Online Consumption Trends in Japan during the COVID-19 Pandemic," Bank of Japan Working Paper Series 22-E-11, Bank of Japan.
    17. Peng, Cong, 2019. "Does e-commerce reduce traffic congestion? Evidence from Alibaba Single Day shopping event," LSE Research Online Documents on Economics 103411, London School of Economics and Political Science, LSE Library.
    18. Chung, Jamie, 2023. "The spillover effect of E-commerce on local retail real estate markets," Regional Science and Urban Economics, Elsevier, vol. 101(C).
    19. György Matolcsy & Márton Nagy & Dániel Palotai & Barnabás Virág, 2020. "Inflation in the Digital Age: Inflation Measurement and Bias in the 21st Century," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 19(1), pages 5-36.
    20. 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.

    More about this item

    Keywords

    E-commerce; Online prices; Big data; CPI;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    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:eee:asieco:v:80:y:2022:i:c:s1049007822000343. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/asieco .

    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.