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Big Data in Asian Central Banks

Author

Listed:
  • Giulio Cornelli
  • Sebastian Doerr
  • Leonardo Gambacorta
  • Bruno Tissot

Abstract

The present paper reviews the use of big data in Asian central banks, leveraging on a survey conducted by the Irving Fischer Committee on Central Bank Statistics (IFC) of the Bank for International Settlements. It reveals four main insights. First, Asian central banks define big data in an encompassing way. Second, they show higher interest in big data, including at the senior policy level. Third, big data already supports a wide range of tasks. Fourth, big data poses new challenges and increases the need for international policy cooperation, especially to make use of payments data and promote innovative technological solutions.

Suggested Citation

  • Giulio Cornelli & Sebastian Doerr & Leonardo Gambacorta & Bruno Tissot, 2022. "Big Data in Asian Central Banks," Asian Economic Policy Review, Japan Center for Economic Research, vol. 17(2), pages 255-269, July.
    • Handle: RePEc:bla:asiapr:v:17:y:2022:i:2:p:255-269
    DOI: 10.1111/aepr.12376
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    References listed on IDEAS

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    1. Nymand-Andersen, Per & Pantelidis, Emmanouil, 2018. "Google econometrics: nowcasting euro area car sales and big data quality requirements," Statistics Paper Series 30, European Central Bank.
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    4. Marlene Amstad & Giulio Cornelli & Leonardo Gambacorta & Dora Xia, 2020. "Investors' risk attitudes in the pandemic and the stock market: new evidence based on internet searches," BIS Bulletins 25, Bank for International Settlements.
    5. Paphatsorn Sawaengsuksant, 2019. "Standardised approach in developing economic indicators using internet searching applications," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
    6. Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2019. "Can media and text analytics provide insights into labour market conditions in China?," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1118-1130.
    7. Giulio Cornelli & Jon Frost & Leonardo Gambacorta & Raghavendra Rau & Robert Wardrop & Tania Ziegler, 2020. "Fintech and big tech credit: a new database," BIS Working Papers 887, Bank for International Settlements.
    8. Gambacorta, Leonardo & Amstad, Marlene & He, Chao & XIA, Fan Dora, 2021. "Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media," CEPR Discussion Papers 15682, Centre for Economic Policy Research.
    9. Bruno Tissot, 2017. "Big data and central banking - Overview," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Big Data, volume 44, Bank for International Settlements.
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    Cited by:

    1. Feng Zhu, 2022. "Comment on “Big Data in Asian Central Banks”," Asian Economic Policy Review, Japan Center for Economic Research, vol. 17(2), pages 272-273, July.
    2. Yiping Huang & Takatoshi Ito & Kazumasa Iwata & Colin McKenzie & Shujiro Urata, 2022. "Digital Finance in Asia: Editors' Overview," Asian Economic Policy Review, Japan Center for Economic Research, vol. 17(2), pages 163-182, July.

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    More about this item

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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