TY - JOUR
T1 - The Nexus between Crime Rates, Poverty, and Income Inequality
T2 - A Case Study of Indonesia
AU - Sugiharti, Lilik
AU - Purwono, Rudi
AU - Esquivias, Miguel Angel
AU - Rohmawati, Hilda
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/2
Y1 - 2023/2
N2 - This study examines whether income inequality and poverty are determinants of crime rates across 34 provinces in Indonesia. Three indicators of income inequality and four poverty measures are tested to examine whether the dimension and degree of unequal welfare distribution are linked to crime occurrences. We use panel data from 2010 to 2019 with the Generalized Method of Moments (GMM) approach. The findings indicate that higher income levels and wider income inequality are associated with higher crime rates. Our first indicator of income inequality, non-food expenditure, has a larger impact on crime rates than our second and third indicators, i.e., the gap in food expenditure and the Gini ratio. Poverty is also positively associated with crime. The wider the poverty gap (a measure of poverty) and the severity index, the higher the deprivation levels among the poor, which lead to more crime. The significant and positive effect of poverty on crime rates, and the positive nexus between crime, income, and inequality suggest that Indonesia will face a higher crime risk as the country becomes increasingly more affluent. In such a scenario, policymakers can leverage education and investment (domestic and foreign) to minimize the crime rate. The government could also strengthen crime prevention programs, crime settlement systems, and policing in Indonesia, and raise the budget for social assistance.
AB - This study examines whether income inequality and poverty are determinants of crime rates across 34 provinces in Indonesia. Three indicators of income inequality and four poverty measures are tested to examine whether the dimension and degree of unequal welfare distribution are linked to crime occurrences. We use panel data from 2010 to 2019 with the Generalized Method of Moments (GMM) approach. The findings indicate that higher income levels and wider income inequality are associated with higher crime rates. Our first indicator of income inequality, non-food expenditure, has a larger impact on crime rates than our second and third indicators, i.e., the gap in food expenditure and the Gini ratio. Poverty is also positively associated with crime. The wider the poverty gap (a measure of poverty) and the severity index, the higher the deprivation levels among the poor, which lead to more crime. The significant and positive effect of poverty on crime rates, and the positive nexus between crime, income, and inequality suggest that Indonesia will face a higher crime risk as the country becomes increasingly more affluent. In such a scenario, policymakers can leverage education and investment (domestic and foreign) to minimize the crime rate. The government could also strengthen crime prevention programs, crime settlement systems, and policing in Indonesia, and raise the budget for social assistance.
KW - crime rates
KW - income inequality
KW - population density
KW - poverty
KW - quality of education
KW - well-being
UR - http://www.scopus.com/inward/record.url?scp=85148635272&partnerID=8YFLogxK
U2 - 10.3390/economies11020062
DO - 10.3390/economies11020062
M3 - Article
AN - SCOPUS:85148635272
SN - 2227-7099
VL - 11
JO - Economies
JF - Economies
IS - 2
M1 - 62
ER -