IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v62y2024ipas154461232400151x.html
   My bibliography  Save this article

Does non-bank fintech development hurt the effect of targeted monetary policy tools? Micro evidence from China

Author

Listed:
  • Wang, Xi
  • Tang, Yanfei

Abstract

Since the financial crisis, central banks have implemented unconventional monetary policies, while fintech has developed rapidly and reshaped the credit market. Using firm data from China, this paper empirically tests whether the development of non-bank fintech influences the effect of targeted monetary policy tools. We find that targeted reserve requirement ratio (RRR) cuts in China expand the borrowing amounts of targeted micro and small enterprises (MSEs), but have no effect on their borrowing costs. Moreover, non-bank fintech increases the effect of targeted RRR cuts on MSEs' borrowing amounts, while it does not change the policy effect on borrowing costs.

Suggested Citation

  • Wang, Xi & Tang, Yanfei, 2024. "Does non-bank fintech development hurt the effect of targeted monetary policy tools? Micro evidence from China," Finance Research Letters, Elsevier, vol. 62(PA).
    • Handle: RePEc:eee:finlet:v:62:y:2024:i:pa:s154461232400151x
    DOI: 10.1016/j.frl.2024.105121
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S154461232400151X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2024.105121?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. Wei, Xiaoyun & Li, Jie & Han, Liyan, 2020. "Optimal targeted reduction in reserve requirement ratio in China," Economic Modelling, Elsevier, vol. 85(C), pages 1-15.
    2. Andreas Fuster & Matthew Plosser & Philipp Schnabl & James Vickery, 2019. "The Role of Technology in Mortgage Lending," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1854-1899.
    3. Niu, Geng & Jin, XiaoShu & Wang, Qi & Zhou, Yang, 2022. "Broadband infrastructure and digital financial inclusion in rural China," China Economic Review, Elsevier, vol. 76(C).
    4. Bernanke, Ben S. & Gertler, Mark & Gilchrist, Simon, 1999. "The financial accelerator in a quantitative business cycle framework," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 21, pages 1341-1393, Elsevier.
    5. Cheng, Maoyong & Qu, Yang, 2020. "Does bank FinTech reduce credit risk? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).
    6. Jean Boivin & Marc P. Giannoni, 2006. "Has Monetary Policy Become More Effective?," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 445-462, August.
    7. Liu, Yang & Luan, Lin & Wu, Weilong & Zhang, Zhiqiang & Hsu, Yen, 2021. "Can digital financial inclusion promote China's economic growth?," International Review of Financial Analysis, Elsevier, vol. 78(C).
    8. John Sedunov, 2017. "Does Bank Technology Affect Small Business Lending Decisions?," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 40(1), pages 5-32, March.
    Full references (including those not matched with items 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. Wu, Fei & Hu, Yan & Shen, Me, 2024. "The color of FinTech: FinTech and corporate green transformation in China," International Review of Financial Analysis, Elsevier, vol. 94(C).
    2. Fan, Chenguang & Bae, Seongho & Liu, Yu, 2024. "Can FinTech transform corporate liquidity? Evidence from China," Innovation and Green Development, Elsevier, vol. 3(2).
    3. Marco Airaudo & Salvatore Nisticò & Luis‐Felipe Zanna, 2015. "Learning, Monetary Policy, and Asset Prices," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(7), pages 1273-1307, October.
    4. Lu, Yao & Li, Lu & Zhan, Huanqi & Zhan, Minghua, 2024. "Fintech, information heterogeneity, and the regional distribution effects of corporate financing constraints," Economic Modelling, Elsevier, vol. 137(C).
    5. repec:zbw:bofrdp:2010_011 is not listed on IDEAS
    6. Wang, Weilong & Xiao, Deheng & Wang, Jianlong & Wu, Haitao, 2024. "The cost of pollution in the digital era: Impediments of air pollution on enterprise digital transformation," Energy Economics, Elsevier, vol. 134(C).
    7. Castelnuovo, Efrem & Nisticò, Salvatore, 2010. "Stock market conditions and monetary policy in a DSGE model for the U.S," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1700-1731, September.
    8. Eickmeier, Sandra & Hofmann, Boris, 2013. "Monetary Policy, Housing Booms, And Financial (Im)Balances," Macroeconomic Dynamics, Cambridge University Press, vol. 17(4), pages 830-860, June.
    9. Norhana Endut & James Morley & Pao-Lin Tien, 2018. "The changing transmission mechanism of US monetary policy," Empirical Economics, Springer, vol. 54(3), pages 959-987, May.
    10. Tan, Changchun & Mo, Lingyu & Wu, Xiaomeng & Zhou, Peng, 2024. "Fintech development and corporate credit risk: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 92(C).
    11. Grunspan, T., 2005. "The Fed and the Question of Financial Stability: An Empirical Investigation," Working papers 134, Banque de France.
    12. Jiang, Kangqi & Chen, Zhongfei & Rughoo, Aarti & Zhou, Mengling, 2022. "Internet finance and corporate investment: Evidence from China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    13. Guo, Pin & Zhang, Cheng, 2023. "The impact of bank FinTech on liquidity creation: Evidence from China," Research in International Business and Finance, Elsevier, vol. 64(C).
    14. Frank Smets & Raf Wouters, 2005. "Comparing shocks and frictions in US and euro area business cycles: a Bayesian DSGE Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 161-183.
    15. Zanetti, Francesco, 2011. "Labor market institutions and aggregate fluctuations in a search and matching model," European Economic Review, Elsevier, vol. 55(5), pages 644-658, June.
    16. Goodness C. Aye & Mehmet Balcilar & Rangan Gupta, 2020. "The Effectiveness Of Monetary Policy In South Africa Under Inflation Targeting: Evidence from a Time-Varying Factor-Augmented Vector Autoregressive Model," Journal of Developing Areas, Tennessee State University, College of Business, vol. 54(4), pages 55-73, October-D.
    17. Zhang, Dongyang, 2024. "The pathway to curb greenwashing in sustainable growth: The role of artificial intelligence," Energy Economics, Elsevier, vol. 133(C).
    18. Castelnuovo, Efrem & Nisticò, Salvatore, 2010. "Stock market conditions and monetary policy in a DSGE model for the U.S," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1700-1731, September.
    19. Sun, Guanglin & Li, Ting & Ai, Yongfang & Li, Qinghai, 2023. "Digital finance and corporate financial fraud," International Review of Financial Analysis, Elsevier, vol. 87(C).
    20. Li, Bin & Guo, Fei & Xu, Lei & Meng, Siqi, 2024. "Fintech business and corporate social responsibility practices," Emerging Markets Review, Elsevier, vol. 59(C).
    21. Jakub Mateju, 2013. "Explaining the Strength and the Efficiency of Monetary Policy Transmission: A Panel of Impulse Responses from a Time-Varying Parameter Model," Working Papers IES 2013/18, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2013.

    More about this item

    Keywords

    Targeted reserve requirement ratio cuts; Micro and small enterprises; Enterprises’ borrowing; Fintech;
    All these keywords.

    JEL classification:

    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    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:finlet:v:62:y:2024:i:pa:s154461232400151x. 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/frl .

    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.