Perception versus Reality: Exploring the Relationship between Income Inequality and Crime Rates in the US
Document Type
Event
Faculty Mentor
Michael Cauvel
Abstract
This project analyzes how income inequality affects crime. The theoretical literature tends to agree that there is a positive relationship between income inequality and crime. I am conducting a more in-depth examination of this claim. We are interested in finding whether this relationship is the result of absolute income effects, relative income effects, or a combination of the two. The former would signify a deprivation channel, through which people with lower incomes turn to crime due to a lack of legal channels where they can satisfy their basic needs; it’s an act of necessity caused by real income inequality present in a society. The latter, relative income effects, suggests that crime is the result of perceived unfairness, a data point tougher to grasp and less analyzed in the current published literature. The United States is a particularly interesting case study as it shows a divergence from the standard consensus: crime rates appear to be trending downward as the gap between the richest and poorest grows ever larger. My project builds on this context by critically examining the relationship between these two factors in this country, whose data seemingly goes against the theory. We will test this using regression analysis for U.S.-specific data. To test the impact of relative income effects, data on perceived inequality will be used. To test the impact of absolute income effects, data on income distribution will be used. Data on real income inequality was gathered from an independent research team at SHSU, who compiled a multitude of state-level income inequality measures, of which I am using the top 10% share and the Gini coefficient/index. The perceived inequality data came from an independent researcher named Bill Franko, who constructed the variable using responses to 34 national surveys. My crime data includes a Crime Index, rates of property crimes, and rates of violent crimes, all collected from the FBI website. For most of my control variables, namely median income, LFPR, and poverty, I collected data from FRED.
Perception versus Reality: Exploring the Relationship between Income Inequality and Crime Rates in the US
This project analyzes how income inequality affects crime. The theoretical literature tends to agree that there is a positive relationship between income inequality and crime. I am conducting a more in-depth examination of this claim. We are interested in finding whether this relationship is the result of absolute income effects, relative income effects, or a combination of the two. The former would signify a deprivation channel, through which people with lower incomes turn to crime due to a lack of legal channels where they can satisfy their basic needs; it’s an act of necessity caused by real income inequality present in a society. The latter, relative income effects, suggests that crime is the result of perceived unfairness, a data point tougher to grasp and less analyzed in the current published literature. The United States is a particularly interesting case study as it shows a divergence from the standard consensus: crime rates appear to be trending downward as the gap between the richest and poorest grows ever larger. My project builds on this context by critically examining the relationship between these two factors in this country, whose data seemingly goes against the theory. We will test this using regression analysis for U.S.-specific data. To test the impact of relative income effects, data on perceived inequality will be used. To test the impact of absolute income effects, data on income distribution will be used. Data on real income inequality was gathered from an independent research team at SHSU, who compiled a multitude of state-level income inequality measures, of which I am using the top 10% share and the Gini coefficient/index. The perceived inequality data came from an independent researcher named Bill Franko, who constructed the variable using responses to 34 national surveys. My crime data includes a Crime Index, rates of property crimes, and rates of violent crimes, all collected from the FBI website. For most of my control variables, namely median income, LFPR, and poverty, I collected data from FRED.
