Analyzing the relationship between corruption and socio-economic development in Kazakhstan’s regions
Abstract
Relevance. Corruption remains a persistent issue in many countries, including Kazakhstan. By exploring the relationship between the socio-economic characteristics of specific regions and corruption, this research can provide a foundation for informed policy-making and targeted anti-corruption efforts and thus help mitigate its negative impact on regional development.
Research Objective. The research aims to assess the impact of corruption on regional socio-economic development in Kazakhstan through the creation and application of a multifactor corruption index.
Data and Methods. The study uses official statistical data on corruption offenses and regional socio-economic indicators, including industrial production, fixed asset investments, household expenditures, unemployment rates, and foreign trade volumes. A multifactor index methodology was employed, using Pearson correlation coefficients to calculate averaged absolute values of sub-indices for each indicator.
Results. The study found strong correlations between corruption and socio-economic indicators in regions like East Kazakhstan, Abay, Akmola, and Kostanay. The economic structure of these regions plays a key role: East Kazakhstan and Akmola, with dominant mining industries, are more vulnerable to corruption due to public contracts and licensing. Kostanay's agricultural sector, central to its economy, is prone to corruption in land allocation, subsidies, and procurement. The economic importance of these sectors amplifies the impact of corruption on development, strengthening the correlation. Conversely, regions with lower index values show weaker correlations in the analysis, likely due to economic diversity, incomplete data, or less effective governance mechanisms.
Conclusions. The regional specificity of the interrelation between corruption and socio-economic development in Kazakhstan necessitates tailored approaches that consider the unique conditions of each region. These findings can be of interest to policymakers and other stakeholders. The proposed methodology allows for a more precise assessment of both hidden and visible corruption risks, highlighting critical areas for implementing effective anti-corruption measures.
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DOI: https://doi.org/10.15826/recon.2024.10.4.028
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