IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i2p242-d723949.html
   My bibliography  Save this article

Transmission Channels between Financial Deepening and Economic Growth: Econometric Analysis Comprising Monetary Factors

Author

Listed:
  • Marina Abramova

    (Banking and Financial Markets Department, Research Center for Monetary Relations, Financial University under the Government of the Russian Federation, 125993 Moscow, Russia)

  • Dmitri Artemenko

    (The Higher School of Business, Southern Federal University, 344000 Rostov-on-Don, Russia)

  • Konstantin Krinichansky

    (Banking and Financial Markets Department, Research Center for Monetary Relations, Financial University under the Government of the Russian Federation, 125993 Moscow, Russia)

Abstract

Contemporary literature continues to foster discussion whether financial development is important for economic growth. In the clash of theoretical arguments, the prevailing idea is that finance exerts a direct positive influence on GDP growth. However, the presence of theoretical counterarguments and contradictory results of empirical studies suggest that scientists, in search of an answer about the direction and power of the net effect, should develop methods of empirical analysis, and the very mystery of the relationship between finance and growth will finally be solved exclusively empirically. In this paper, the authors contribute to the development of the ‘finance-growth’ literature by answering some existing questions concerning the transmission channels from finance to growth, relying on more recent data compared to already conducted studies. We use panel data covering the period 1995 to 2019 for 168 countries. In addition, the paper touches on the problem of studying the exogenous conditions of such channels, considering the assumption that among these conditions there may be those that hinder the impact of financial deepening on economic growth. Our focus is on monetary conditions, and in the empirical part of the study, we touch upon the problem of the influence of price stability on the operation of these transmission channels. The methods of the conducted study are based on the dynamic panel data analysis techniques (System GMM). The novelty of this paper lies in the development of the modern theory of the financial sector transmission mechanism in the economic growth context. The main result of the study is that productivity channel is the most reliable transmission channel of financial deepening to economic growth. Furthermore, the effectiveness of this channel remains virtually unaffected by inflation. The channel of capital accumulation should be considered less reliable (in terms of statistical reliability of estimates obtained), but it has turned out to be a more economically significant transmission channel. This channel is sensitive to the inflation factor in certain categories of countries. Finally, as follows from the estimates gained, the non-linearity of the “finance-growth” relationship can be explained by the non-linearity of the variable responsible for the capital accumulation channel.

Suggested Citation

  • Marina Abramova & Dmitri Artemenko & Konstantin Krinichansky, 2022. "Transmission Channels between Financial Deepening and Economic Growth: Econometric Analysis Comprising Monetary Factors," Mathematics, MDPI, vol. 10(2), pages 1-27, January.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:2:p:242-:d:723949
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/2/242/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/10/2/242/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Hao, Yunping & Zhang, Bing, 2024. "The impact of digital financial usage on resident’s income inequality in China: An empirical analysis based on CHFS data," Journal of Asian Economics, Elsevier, vol. 91(C).
    2. Xu Zhang & Pingping Chen & Genjian Yu & Shaohao Wang, 2023. "Deep Reinforcement Learning Heterogeneous Channels for Poisson Multiple Access," Mathematics, MDPI, vol. 11(4), pages 1-13, February.

    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:gam:jmathe:v:10:y:2022:i:2:p:242-:d:723949. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.