A Structural Analysis of Crime and Economic Incentives of Youth

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Authors
Chan, Yun-Shan
Issue Date
1-May-12
Type
Dissertation
Language
en_US
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Abstract
In this thesis, a dynamic model is estimated to analyze the effect of economic incentives on crime involvement and recidivism of young people. The model assumes that the utility of individuals depends on their earnings from legal work and illegal activities. Every period, young agents face an expected wage. They may get extra income from criminal activities but lose some when punishment occurs. There are two types of punishment: arrest and incarceration. Criminals have to pay a fine if arrested but need to serve sentences from months to years with no earnings if incarcerated. The model is estimated through the SMM using data from the NLSY97, a nationally representative survey of 8984 individuals with employment records, criminal information, illegal income, and detailed arrest and sentence records, as well as other socio-demographic information. Although there are many other factors contribution to youth crime, this study shows that economic incentives explain well the behavior of individuals. Since the negative impact of punishment increases as the wage level goes up, people with lower wage levels from the legitimate labor market are more likely to commit a crime. People without criminal records have the highest persistent wage rate, while the wages of ex-offenders highly depends on the wage shock, which is explained by a large wage gap before and after jail. In general, people have lower propensity to commit a crime if their expected income from illegal activities is low. However, compared with ex-offenders, people without any record are more likely to commit a crime as their expected illegal income increases. If the expected illegal income becomes high enough, they will always commit a crime. Since the probability of being punished is higher to ex-offenders once they recidivate, they are less likely to be involved in criminal activities if the expected wage is over a certain level. The ability of the model to incorporate the wide variety of sentence terms and types of punishment allows me to evaluate the effect of different policies on the crime participation and recidivism of youth. An increase in the probability of incarceration, an increase in the probability of long sentences or a decrease in the probability of being released can decrease the overall crime involvement but increases the jail population. An increase in the probability arrest, such as increase in the police force, may decrease the crime involvement of people without criminal records but increases the overall crime involvement, which is due to a highly increase in the crime participation and population of people with arrest or jail records. An increase in the fine rate slightly decreases the overall crime involvement and the population with criminal records.
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85 pg.
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The Graduate School, Stony Brook University: Stony Brook, NY.
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