MODELLING THE IMPACT OF NATURAL RESOURCE ABUNDANCE ON THE SPREAD OF CORRUPTION IN THE COUNTRY
DOI:
https://doi.org/10.37332/2309-1533.2022.2-3.3Keywords:
corruption, natural resources, cluster analysis, canonical analysis, resource curse.Abstract
Bozhenko V.V., Нerasymenko V.V. MODELLING THE IMPACT OF NATURAL RESOURCE ABUNDANCE ON THE SPREAD OF CORRUPTION IN THE COUNTRY
Purpose. The aim of the article is estimating the degree of impact of natural resources on the corruption on the global scale.
Methodology of research. The methodological basis of the study is a systematic combination of the methods of comparative, cluster (k-means method) and canonical correlation analyses. To characterize the level of corruption in the country, three indicators were used (the level of corruption control, regulatory quality and the rule of law), calculated by World Bank specialists within the Worldwide Governance Indicators (WGI) project. The country's provision of natural resources is considered in terms of renewable (volume of wind electricity production, volume of solar electricity production, volume of geothermal energy production) and non-renewable (volume of oil production, volume of gas production). The research object is 44 countries of the world for renewable natural resources and 28 non-renewable countries.
Findings. According to the results of the cluster analysis using the k-means method, three homogeneous groups of countries were distinguished depending on the level of their provision of renewable and non-renewable natural resources. The cluster with the highest level of supply of natural resources includes the USA and China (renewable sources) and the USA and Russia (non-renewable sources). Ukraine belongs to the cluster with a low level of extraction of renewable and non-renewable natural resources. The hypothesis that the level of corruption depends on the supply of natural resources is correct, as indicated by the following indicators: the canonical coefficient of determination is more than 0.9; χ2 is Bartler's test and its p-value is less than 0.05. The closest relationship between the two sets of variables exists in countries that are moderately endowed with natural resources.
Originality. A scientific-methodical approach for assessing the degree of impact of natural resource on the level of corruption through a systematic combination of cluster and canonical analysis was developed.
Practical value. The obtained results can be used by state authorities and local self-government bodies to combat corruption in the natural resources management system and increase the country's investment attractiveness.
Key words: corruption, natural resources, cluster analysis, canonical analysis, resource curse.
References
Erum, N. and Hussain, S. (2019), “Corruption, natural resources and economic growth: Evidence from OIC countries”, available at: https://econpapers.repec.org/article/eeejrpoli/ v_3a63_3ay_3a2019_3ai_3ac_3a18.htm (access date May 19, 2022).
Kordbacheh, H. and Sadati, S. (2021), “Corruption and banking soundness: Does natural resource dependency matter?”, available at: https://www.emerald.com/insight/content/doi/10.1108/JFC-01-2021-0004/full/html?skipTracking=true (access date May 18, 2022).
Kolstad, I., Søreide, T. and Williams, A. (2008), “Corruption in Natural Resource Management – An Introduction”, available at: https://www.u4.no/publications/corruption-in-natural-resource-management-an-introduction (access date May 18, 2022).
Kolstad, I. and Wiig, A. (2011), “Natural resources, corruption and trust: A complex relationship”, available at: https://www.u4.no/publications/natural-resources-corruption-and-trust-a-complex-relationship.pdf (access date May 19, 2022).
Bhattacharyya, S. and Hodler, R. (2010), “Natural Resources, Democracy and Corruption”, available at: https://econpapers.repec.org/article/eeeeecrev/v_3a54_3ay_3a2010_3ai_3a4_3ap_3a608-621.htm (access date May 19, 2022).
Khvesyk, M.A. (Ed.) (2021), Pryrodno-resursnyi potentsial Ukrainy: zabezpechennia dobrobutu ta ekolohichnoi bezpeky naselennia [Natural resource potential of Ukraine: ensuring the well-being and ecological safety of the population], monograph, DU IEPSR NAN Ukrainy, Kyiv, Ukraine, 148 p.
“Analysts named the TOP-10 corruption risks during the sale of wood by state forestry farms”, available at: https://statewatch.org.ua/publications/analityky-nazvaly-top-10-koruptsiynykh-ryzykiv-pid-chas-realizatsii-derevyny-derzhavnymy-lishospamy/ (access date May 06, 2022).
“What corruption schemes create conditions for the shadow circulation of land? an analytical review of NACP”, available at: https://nazk.gov.ua/uk/novyny/yaki-koruptsijni-shemy-stvoryuyut-umovy-dlya-tinovogo-obigu-zemli-analitychnyj-oglyad-nazk/ (access date May 05, 2022).
“100 corruption schemes in the regions of Ukraine”, available at: https://www.rpk.org.ua/wp-content/uploads/2020/12/as-100-schemes-2-1.pdf (access date May 06, 2022).
The Worldwide Governance Indicators (WGI) project, available at: http://info.worldbank.org/governance/wgi/ (access date May 10, 2022).
Statistical Review of World Energy, available at: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html (access date May 10, 2022).
Klymchuk, V.O. (2006), “Cluster analysis: use in psychological research”, Praktychna psykholohiia ta sotsialna robota, no. 4, pp. 30-36.
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