Abstract
This article has two goals. First, using district-level panel data we identify key determinants of violent crime, nonviolent crime, and crime against women in India, 1990-2007. Second, using district-level variation in regard to Maoist-driven social conflict, we examine how social conflict affects crime and its determinants. In addition to conventional determinants of crime (e.g., law enforcement and economic variables), we examine how variation in sex ratios affects crime. We also study whether the gender of the chief political decisionmaker in each state affects crime. We find that improvements in arrest rates decreases the incidence of all types of crimes. Socioeconomic variables have relatively little explanatory power. We also find evidence that unbalanced sex ratios, particularly in rural areas, increase crime. The presence of a female Chief Minister diminishes violent crime and, especially, crimes against women. Finally, we find that in districts affected by the Maoist insurgency, all types of crime are lower and we offer explanations for why that may be the case.
Highlights
This article examines patterns of interpersonal crime in India for the period 1990-2007
Note that in conflict states the police force is crime categories except for the case of crimes against women supplemented by paramilitary forces, but our measure of law in which higher arrest rates in Red Corridor districts are enforcement in conflict states does not account for these statistically associated with increased violence against women
Our analysis of interpersonal crime and social conflict in India shows that deterrence in the form of arrest rates matters in lowering crime and that socioeconomic variables do not systematically influence crime
Summary
Arrest marginal (interaction) effect of arrests on crime in Red rates are higher in conflict states but police force per capita is Corridor (RC) districts is not statistically significant across the lower. In the very first line, the between social conflict and nonconflict areas may be reported coefficients suggest that crime rates across all crime picking up reverse causality, lagged values for police force categories are lower in Red Corridor districts than in other give similar results. This suggests that our main findings are not driven by states of a particular economic size, rich or poor
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