Spatial Econometric Analysis of Geographic Clustering and Socio-economic Drivers of Crimes Against Children in India

Children are among the most vulnerable members of society, often subjected to various forms of exploitation and violence. Improved spatial hotspot analysis techniques must be used to examine crime hotspots to map out long-term policies to protect children in India. This study examines the spatial distribution and socio-economic determinants of child-targeted crimes across districts in India using 2020–2022 National Crime Records Bureau (NCRB) data. Applying the SaTScan discrete Poisson model, we identified robust, statistically significant spatial hotspots persistently clustered in central Indian states, including Madhya Pradesh and Maharashtra. To investigate the drivers of these hotspots, we calculated population-normalized crime rates and applied a Spatial Lag Model (SLM) to account for spatial dependence. Our findings reveal a powerful spatial spillover effect (ρ = 0.55, p < 0.001), indicating that a district’s child crime rate is heavily influenced by the crime rates of its contiguous neighbors. Once spatial contagion is controlled for, localized socio-economic variables lose much of their predictive power, though literacy rates and domestic violence proxies exhibit marginal associative trends. These findings challenge the assumption that child-targeted crimes are purely products of isolated local deficits, suggesting instead that they are embedded in regional structural vulnerabilities. The study provides actionable intelligence for law enforcement to shift from isolated district-level policing to regional, cross-boundary child protection interventions.