In a recent New York Times article, published on 5 August, Alissa J. Rubin briefly mentioned a relationship between poverty, crime and drug trafficking in Roubaix, a town in the northeast of France. According to the article, half of Roubaix’s households live below the poverty line, and many of its neighborhoods suffer from crime and drug trafficking.
Arizona State University published a study in 2005 entitled “The Dynamics of Poverty and Crime.” Its authors, Haiyun Zhao, Zhilan Feng and Carlos Castillo-Chavez, created a mathematical and statistical model based on a correlation between poverty and crime in metropolitan areas. They postulated that the poverty-stricken population in these areas is more willing to commit a property crime if committing the crime benefits their lifestyle more than not committing it. They further observed that the rates of detention and incarceration associated with diminishing the effects of crime are high and continuing to rise.
They further posited that two factors can affect a change in the level of crime: decrease in poverty and increase in the severity of the punishment. Since they agreed that both conditions cannot occur in a pragmatic world, the results of their study concluded that a combination of the two would be the best alternative.
Their method of mathematical and statistical calculations broke up the population into five separate sectors: “the non-impoverished class N, the poverty class P, the criminal class C, the jailed class J and the recovered class (from jail or from impoverished class) R.”
In their resulting system of equations, the researchers accounted for several transitions each sectors can expect to encounter, including the rate of conversion from the poverty class to the recovered class due to government interventions and the “transmission” rate at which a person in poverty can resort to a life of crime after coming in contact with a criminal. Moreover, the recovered class, having been incarcerated and encountered criminals there, can also revert back to criminality.
The total cost model calculated two costs associated with the crime activity: the total cost in the absence of any intervention parameters and the total cost when someone interferes.
The resulting calculations showed that eliminating all crime is not feasible. However, it is possible to find an acceptable level of intervention to optimize the cost of crime fighting. Their study recommended a balanced approach to controlling crime and keeping the cost at “less than the total cost of crime under the status quo.”