Relationship between banking infrastructure, innovation and economic growth in Kazakhstan


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Today, the development of financial technologies and their application in the banking sector have changed the processes of economic growth in general and commercial banks in particular, giving them an innovative orientation. The aim of this study is to investigate the relationship between the banking infrastructure, innovation, and economic growth in Kazakhstan based on panel data. The study relies on information extracted from annual publications issued by the National Bank of Kazakhstan, the World Bank Database, and the Bureau of the National Statistics of Kazakhstan from 2004 to 2022, and also uses a regression model. Within this framework, variables used in the study, the number of ATMs, the number of bank branches, and the share of innovative products, are explanatory variables, and the gross domestic product per capita is the dependent variable. The study showed that both business innovations and the prevalence of ATMs have a significant and noticeable impact on the economic landscape of Kazakhstan, as evidenced by the impressive value of the R-square of 0.890. Moreover, the regression model demonstrates reliable stability and reliability, which is confirmed by the p-value of 0.001. In light of these findings, it is important to contribute valuable insights and evidence-based recommendations to enhance Kazakhstan’s economic growth strategy by leveraging the synergistic potential of its banking infrastructure and innovation ecosystem.

The study was funded by the Committee Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan “Investigating the impact of macroeconomic, political, and digital processes on financial sustainability of Kazakhstan” No. AP19674948.

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    • Figure 1. Stages of the study
    • Figure 2. GDP per capita in Kazakhstan for 2004–2022, in KZT
    • Figure 3. Growth rate results of GDP per capita, automated teller machines, and the share of innovative products and bank branches in Kazakhstan, in %
    • Table 1. Variables presented in the study
    • Table 2. Descriptive statistics
    • Table 3. Pearson correlation
    • Table 4. Model validity indicators
    • Table 5. Model coefficients – GDPper
    • Data curation
      Kuralay Nurgaliyeva, Nazym Zaitenova, Anna Kredina
    • Investigation
      Kuralay Nurgaliyeva, Olga Koshkina, Anna Kredina
    • Resources
      Kuralay Nurgaliyeva, Nazym Zaitenova
    • Writing – review & editing
      Kuralay Nurgaliyeva, Nazym Zaitenova, Anel Kireyeva, Anna Kredina
    • Formal Analysis
      Olga Koshkina
    • Funding acquisition
      Olga Koshkina, Nazym Zaitenova, Anna Kredina
    • Software
      Olga Koshkina, Anel Kireyeva, Anna Kredina
    • Visualization
      Olga Koshkina
    • Writing – original draft
      Olga Koshkina, Anel Kireyeva, Anna Kredina
    • Conceptualization
      Anel Kireyeva
    • Project administration
      Anel Kireyeva
    • Supervision
      Anel Kireyeva
    • Methodology
      Anna Kredina