Identification of determinants of corruption in government: a mar-spline approach

Abstract

Purpose.Development of a scientific and methodological approach to the identification of the most impactful determinants on corruption using multivariate adaptive regression splines. Methodology. Methodological tools of the research methods are comparison, grouping, bibliometric analysis, and multivariate adaptive regression splines in the form of piecewise linear functions. Findings. Systematization of the literary sources and approaches for factors influencing corruption indicates that most empirical studies are based on using panel data. Panel data allows you to insert general patterns, but does not consider the patterns of the national economy. For the study on corruption in Ukraine, 15 influencing factors were selected, characterizing the institutional, economic and social environment. Based on the constructed MAR Spline models, three regression equations were obtained that describe the linear dependence of the level of corruption in governance on the selected factors. The paper found that the relevant factors influencing corruption in Ukraine are: tax burden, general government final consumption expenditure, average monthly wage in Governance and rule of law. Originality.The proposed approach makes it possible to determine the dynamics of the degree of factor influence on the level of corruption in the country. The paper defines the threshold values of statistically significant indicators at which the maximum degree of correlation with the corruption perception index is achieved. Practical value.The regularities between the level of corruption and economic, institutional and social factors revealed by the research results can be used in the development of tools to fight corruption in Ukraine. The formation of an effective anti-corruption system will strengthen financial stability in the country and increase the level of public trust in society.