ESTABLISHING CRIMINOLOGICAL LAWS OF CRIMINALITY IN UKRAINE USING CORRELATION AND REGRESSION ANALYSIS

Objective: To explain, predict and counteract bribery in Russia and Ukraine. Methods: Analysis of time series of criminological data, including revealing trends and obtaining trend equations, calculating the central tendency and dispersion measures, calculating and analyzing the coefficient of bribery variations, calculating the specific weight of bribery in the criminality structure, the least square method, the double regression analysis, calculating the approximation coefficients, building functions graphs, observation, comparative-legal method, formal-logical methods, historical method, using the probability laws of distribution. Results: 1) The criminal legislations of Russia and Ukraine are compared by the appropriate corpus delicti, their comparability is determined; 2) bribery trends in Russia and Ukraine are revealed and interpreted in Soviet and post-Soviet periods: а) in the Soviet period bribery in RSFSR and UkrSSR had similar indicators and dynamics of development; б) in post-Soviet period opposite trends are marked in bribery dynamics in Russia and Ukraine; 3) it is shown that bribery distribution by the Ukraine regions is close to normal one (Gauss distribution); 4) it is proved that both in Russia and Ukraine bribery has low specific weight in the criminality structure (does not exceed 0.5 % in Russia and 1 % in Ukraine). Scientific novelty: Obtaining trend equations of bribery in Russia and Ukraine, comparing bribery trends in Ukraine regions, revealing the forms of bribery distributions in Ukraine regions, researching the variations and central trend of time series of bribery coefficients in the compared countries, analysis of bribery coefficients, bribery variations and specific weight of bribery in Russia and Ukraine. Practical value: The obtained scientific results would be useful in analytical-staff work of Interior bodies, law-making activity of various state bodies aimed at corruption counteraction.

criminology, criminality, criminality laws, intended killing, bribery, quintile coefficient of differentiation of the total gain of the population, quintile coefficient of funds, personal disposable income per capita, correlation analysis, regression analysis

1. Ольков С.Г. Аналитическая юриспруденция (методология юриспруденции): учебник. Ч. I. – М.: Юрлитинформ, 2013. – С. 349–584.

2. Ольков С.Г. Структурная модель преступности России девяностых годов ХХ столетия // Научный вестник Тюменского юридического института МВД России: сборник научных трудов. – Тюмень: ТЮИ МВД России, 2002. – С. 61–64.

3. Ольков С.Г. О пользе и вреде неравенства (криминологическое исследование) // Государство и право. – 2004. – № 8. – С. 73–78.

4. Скифский И.С. Насильственная преступность в современной России: объяснение и прогнозирование. – Тюмень: Вектор Бук, 2007. – 276 с.

5. Скифский И.С. Прогнозирование преступности: опыт статистического моделирования: учеб. пособие / под ред. д-ра юрид. наук, проф. В.В. Лунеева. – Тюмень: ТюмГНГУ, 2009.

6. Юзиханова Э.Г. Преступность, обусловленная политико-экономическими факторами (региональный криминологический анализ на примере Тюменской области): дис. … канд. юрид. наук. – Тюмень, 2002.

7. URL: http://www.ukrstat.gov.ua/