Assessment of the relationship between inequality, income and economic growth in the regions of Kazakhstan

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This paper aims to analyze various indicators to explain the impact of inequality and income on economic growth at the regional level of Kazakhstan. The data collected from the Bureau of National Statistics from 1995 to 2020 examined the impact of country, interregional, and market inequality indices and real income/wage on the GRP of different regions. Applying the methods such as analysis of unique statistical data covering 16 regions of Kazakhstan and log-linear multivariate regression analysis, which was carried out using the STATA software package, evidence was provided on the influence of interregional, country inequality, and income on economic growth. The analysis showed the differential impact of inequality and income. It was found at the first stage that the gap between interregional inequality and country inequality is insignificant. It was identified at the second stage that in models with real incomes, an increase in income has a negative impact on the development of the economy of Kazakhstan. All the models obtained are consistent and have (although not very high) significant explanatory power and confirm the relationship between inequality and economic growth. The findings can help policymakers, regionalists, economists, and governmental bodies understand the importance of income inequality and which areas can contribute to the formation of effective regional policy.

Acknowledgments
The study was carried out within the framework of program targeted IRN OR11465433 funding by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan “Development of the concept and mechanisms of balanced territorial development of the economy and society of Kazakhstan”.

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    • Figure 1. Dynamics of interregional (G1) and country`s inequality (G2), in %
    • Table 1. Description of variables
    • Table 2. Indicators of average nominal income per capita of Kazakhstan`s population
    • Table 3. Regression analysis results for regions with income data (lag 1) (all models are consistent)
    • Table 4. Regression analysis results for regions with wage data (lag 1) (all models are consistent)
    • Conceptualization
      Karina Turkebayeva, Makpal Bekturganova, Orazaly Sabden, Galiya Dauliyeva
    • Funding acquisition
      Karina Turkebayeva
    • Investigation
      Karina Turkebayeva, Gaukhar Kenzhegulova
    • Methodology
      Karina Turkebayeva, Makpal Bekturganova
    • Resources
      Karina Turkebayeva
    • Visualization
      Karina Turkebayeva, Makpal Bekturganova, Galiya Dauliyeva
    • Writing – original draft
      Karina Turkebayeva, Makpal Bekturganova
    • Writing – review & editing
      Karina Turkebayeva, Galiya Dauliyeva
    • Data curation
      Orazaly Sabden
    • Project administration
      Orazaly Sabden
    • Supervision
      Orazaly Sabden
    • Software
      Gaukhar Kenzhegulova
    • Validation
      Gaukhar Kenzhegulova