分析和预测俄罗斯的犯罪,作为社会领域有效公共管理的工具

L. Parshintseva
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摘要

这项研究的目的是查明俄罗斯犯罪发展的主要趋势和模式,以便制定有效的公共行政措施,改善犯罪情况。本研究的对象是俄罗斯联邦按犯罪类别划分的犯罪。这项研究的主题是描述俄罗斯犯罪状况和动态的统计数据。本研究采用了相对值法、指数分析法、时间序列分析法和预测法等统计方法,特别是自适应法、相关和方差分析法以及可视化数据分析方法。通过这项研究,对过去10年来按犯罪类别划分的犯罪分布的状态、结构和结构变化进行了评估,揭示了区域因素对犯罪率变化的影响,并评估了按犯罪类别划分的犯罪水平与失业、人均酒精饮料零售额等社会经济因素、移民增长系数、基尼系数、人口收入的分化系数。在研究各犯罪类别登记犯罪数量时间序列水平行为的基础上,采用自适应方法对指标进行建模和预测,直至2023年底。
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Analysis and forecasting of crime in Russia as a tool of effective public administration in the social sphere
The purpose of the study is to identify the main trends and patterns of crime development in Russia in order to develop effective public administration measures aimed at improving the criminogenic situation. The object of the study is crime in the Russian Federation by categories of crimes. The subject of the study is statistical data characterizing the state and dynamics of crime in Russia. The study was conducted using statistical methods such as the method of relative values, index analysis, time series analysis and forecasting methods, in particular, adaptive methods, correlation and variance analysis methods, as well as methods of visual data analysis.    As a result of the study, an assessment of the state, structure and structural shifts in the distribution of crimes by crime categories over the past 10 years has been made, the influence of a regional factor on the variation in crime rates has been revealed, and the correlation between crime levels by crime categories and socio-economic factors such as unemployment, retail sale of alcoholic beverages per capita has been assessed, the coefficient of migration growth, the Gini coefficient, the coefficient of differentiation by income of the population. Based on the study of the behavior of time series levels of the number of registered crimes by crime categories, modeling and forecasting of indicators using adaptive methods until the end of 2023 were performed.
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