Influence of state policy components on the rate of violence and crime against human life and health

  • Received September 16, 2022;
    Accepted November 28, 2022;
    Published December 15, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/ppm.20(4).2022.34
  • Article Info
    Volume 20 2022, Issue #4, pp. 451-464
  • TO CITE АНОТАЦІЯ
  • Cited by
    1 articles
  • 334 Views
  • 59 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

The share of crimes against human life and health on average is up to 10% worldwide, and losses are estimated from 0.3 to 3% of GDP. This study examines the dependence of the rate of violence and crime against human life and health on the state policy elements in the example of transitioning and developing countries. The crime index, the share of people reporting crime, the rate of violence or vandalism in the area, and the number of intentional homicide offenses in the largest cities were used as parameters characterizing the rate of violence and crime against human life and health. All parameters were divided into institutional, social, and economic. The dependence between the indicators was studied using fixed-effects and random-effects models; a grouping of countries according to the nature of this dependence employed the iterative separation method of k-means and tree clustering. Based on the results, it is justified that institutional and economic (highest GDP and real minimum wages) components significantly influence the level of violence and crime against human life and health. For example, the average value of the crime index for the fourth cluster is 29.98 compared to 54.09 for the first cluster. At the same time, strengthening responsibility for committed crimes has a more negligible impact on the crime level than increasing the material well-being of the population and supporting its vulnerable segments.

view full abstract hide full abstract
    • Figure 1. Tree of the hierarchical structure of the distribution of drivers of combating crimes against human life and health
    • Figure 2. Classification tree according to the scenarios of combating crimes against human life and health
    • Table 1. Variance analysis for four clusters
    • Table 2. Dispersion analysis for four clusters
    • Table 3. Criteria for clustering the countries according to the factors of crimes against human life and health prevention
    • Table 4. Classification tree structure according to the scenarios of combating crimes against human life and health
    • Table 5. Descriptive statistics for the first cluster from 2011 to 2020
    • Table 6. Descriptive statistics for the second cluster from 2011 to 2020
    • Table 7. Descriptive statistics for the third cluster from 2011 to 2020
    • Table 8. Descriptive statistics for the fourth cluster from 2011 to 2020
    • Conceptualization
      Zamina Aliyeva
    • Data curation
      Zamina Aliyeva
    • Formal Analysis
      Zamina Aliyeva
    • Funding acquisition
      Zamina Aliyeva
    • Investigation
      Zamina Aliyeva
    • Methodology
      Zamina Aliyeva
    • Project administration
      Zamina Aliyeva
    • Resources
      Zamina Aliyeva
    • Software
      Zamina Aliyeva
    • Supervision
      Zamina Aliyeva
    • Validation
      Zamina Aliyeva
    • Visualization
      Zamina Aliyeva
    • Writing – original draft
      Zamina Aliyeva
    • Writing – review & editing
      Zamina Aliyeva