Assessing the differences in the levels and dynamics of economic development of Kazakhstani regions


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This study aims to analyze the level of differences based on effectiveness, statistical dependence, and mutual influence of economic indicators for ranking the regions of Kazakhstan. In the paper, a systematic algorithm of actions is used, ensuring the interconnectedness, the sequence of work, and the validity of the methods used. Several model specifications were formulated to identify interregional differences in economic development indicators: the operating data environment analysis model (DEA) and the random effects regression model (RE). The information database of the Bureau of National Statistics of the Republic of Kazakhstan for 2010–2020 was used. The construction of the RE model was carried out in the SPSS program. A regression model with fixed and random effects in panel data was employed to determine the impact of the selected indicators on gross regional product produced (GRP). Based on the results, the influence of the physical volume of industrial products on GRP per capita in the regions of Kazakhstan for 11 years was revealed in both models with a high significance of coefficients. The study results can be used by public administration bodies that carry out effective strategic management by smoothing interregional differences. Moreover, they can determine the prospects for studying other parameters based on efficiency, statistical dependence, and mutual influence of economic indicators for ranking regions.

This study has been funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (grant “Priorities and mechanisms of inclusive regional development of Kazakhstan in the context of overcoming the economic recession” AP09259004).

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    • Figure 1. Comparison of the dynamics of Kazakhstan’s performance indicator from 2010 to 2020
    • Table 1. Description of the selected factors
    • Table 2. Performance evaluation result and benchmarkable regions for 2010 and 2020
    • Table 3. Regression model of Kazakhstani regions for 2010–2020
    • Conceptualization
      Anel Kireyeva, Nailya Nurlanova, Nurgul Saparbek
    • Data curation
      Anel Kireyeva
    • Formal Analysis
      Anel Kireyeva
    • Software
      Anel Kireyeva, Akan Nurbatsin, Farida Alzhanova
    • Writing – original draft
      Anel Kireyeva, Akan Nurbatsin
    • Writing – review & editing
      Anel Kireyeva, Akan Nurbatsin
    • Funding acquisition
      Nailya Nurlanova, Nurgul Saparbek
    • Investigation
      Nailya Nurlanova, Farida Alzhanova
    • Resources
      Nailya Nurlanova, Farida Alzhanova
    • Visualization
      Nailya Nurlanova, Nurgul Saparbek
    • Supervision
      Akan Nurbatsin
    • Methodology
      Nurgul Saparbek, Farida Alzhanova