State policy of preventing crimes against a person: Which best practices should be used by Azerbaijan?
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Author(s)Zamina AliyevaLink to ORCID Index: https://orcid.org/0000-0003-2693-0057
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DOIhttp://dx.doi.org/10.21511/ppm.21(4).2023.57
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Article InfoVolume 21 2023, Issue #4, pp. 771-789
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State policy of prevention, detection, termination, disclosure, and investigation of crimes against a person in Azerbaijan should be based on other countries’ best practices and experience. The choice of countries to be followed by Azerbaijan should be very well-founded, given that the dynamics of crimes against a person depend significantly on many social and economic determinants: income inequality, the dominance of the rule of law in the country, the level of literacy and financial literacy of citizens, or racial diversity.
50 countries are clustered according to the similarity of trends regarding the dependence of crimes against persons on these socio-economic determinants. Clustering is based on data of 2021 from the World Bank, World Population Review, UNODC, and WGI (the selection of countries is due to the availability of comparable statistical information, the choice of year – to the availability of the most up-to-date data). Clustering was carried out using two methods (DBSCAN and K-Means) to ensure the adequacy of the calculations. Clustering is performed for 3 combinations: 1) by the entire set of crimes and their determinants; 2) by the specific type of crime and all types of determinants; 3) by the entire set of crimes and a specific socio-economic determinant. Albania, Jordan, Mongolia, Romania, and Serbia were most often in the same cluster with Azerbaijan. Therefore, the best experience and best practices of these countries can be used by the state regulatory bodies of Azerbaijan in developing state policy on preventing crimes against the person.
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JEL Classification (Paper profile tab)K14, K42, H70, B55
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References44
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Tables5
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Figures3
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- Figure 1. Scree plot
- Figure 2. Clusters built on the entire set of crimes and their determinants by the K-Means method
- Figure 3. Results of clustering by the entire set of crimes and their socio-economic determinants using the DBSCAN method
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- Table 1. Variables of the number of crimes against the person and the levels of their socio-economic determinants for different countries as of 2021
- Table 2. Normalized input data on the number of crimes against the person and the levels of their socio-economic determinants for different countries
- Table 3. Descriptive analysis
- Table 4. The results of clustering by specific type of crime and all types of their socio-economic determinants (K-Means and DBSCAN methods)
- Table 5. Results of clustering by all types of crime and a specific socio-economic determinant (by K-Means and DBSCAN methods)
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