Financial depth-economic growth nexus: Implications for the Ukrainian banking sector

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The relevance of this study is warranted by changes in the modern understanding of the interrelation between economic growth and financial depth. While earlier studies consider it to be universally positive, newer ones tend to challenge both nature and direction of such a relationship. This paper aims to investigate the nature of the financial depth-economic growth nexus in Ukraine during 2008–2019 based on data provided by the State Statistics Committee of Ukraine and the National Bank of Ukraine, using the standard OLS regression. The resulting model with an adjusted R squared of 0,96 confirms a strong (within a 90% confidence interval) linear relationship between real GDP per capita, denominated in local currency, which was used as a proxy for economic growth, and financial depth, which was assessed using three indicators: the share of bank loans to non-financial institutions in real GDP, the share of non-bank loans to non-financial institutions in real GDP, and the share of stock market capitalization in real GDP. Both bank and non-bank loans to real GDP ratios have a negative impact on economic growth (UAH 2,154 and UAH 78,154 decline per 1% growth, respectively), while market capitalization provides a positive influence (UAH 1,641,130 growth per 1% growth). This implies that, despite concentrating the majority of the resources available to the Ukrainian financial sector, the banking sector does not contribute to its economic growth. This can be alleviated by imposing additional restrictions on the amount of government securities allowed in a bank’s capital structure.

Acknowledgments
The paper was funded as a part of the “Relationship between financial depth and economic growth in Ukraine” research project (No. 0121U110766), conducted at the State Institution “Institute for Economics and Forecasting of the NAS of Ukraine”.

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    • Table 1. List of dependent variables
    • Table 2. Descriptive statistics
    • Table 3. Correlation matrix for variables
    • Table 4. Regression outputs
    • Conceptualization
      Pavlo Kerimov
    • Data curation
      Pavlo Kerimov
    • Formal Analysis
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    • Investigation
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    • Methodology
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    • Project administration
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    • Resources
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    • Software
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    • Validation
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    • Visualization
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    • Writing – original draft
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    • Writing – review & editing
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