Essays on the economics of crime and policing

Matsa, Ariana (2019). Essays on the economics of crime and policing. University of Birmingham. Ph.D.

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Abstract

In this thesis we contribute to the debate on how economic incentives affect crime. As shown by theoretical models, deteriorating labour market opportunities can shift an individual’s incentives to engage in legitimate or illegitimate acts. In the first chapter, using a panel data analysis, we empirically test the relationship between U.S. business cycles and burglary rates. We find that increasing benefits is more effective at reducing countercyclical crime than providing unemployment support for an extended period. The second chapter utilises a novel measure of income inequality and two measures to capture the incentives of the unemployed and low-income earners in a dynamic panel-data model to evaluate their effect on different types of crime in England and Wales. The findings strongly support the pervasive relationship between economic indicators and property crime, both in short- and long-run. Finally, the third chapter builds a predictive solvability model by examining how the presence and absence of factors, during the preliminary phase of the investigation, determine case solvability of fraud and cybercrime. The predictive capabilities of the model are assessed on an external validation sample and the findings show a high degree of accuracy.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
Supervisor(s):
Supervisor(s)EmailORCID
Bandyopadhyay, SiddharthaUNSPECIFIEDUNSPECIFIED
Banerjee, AnindyaUNSPECIFIEDUNSPECIFIED
Licence: All rights reserved
College/Faculty: Colleges (2008 onwards) > College of Social Sciences
School or Department: Birmingham Business School, Department of Economics
Funders: Other
Other Funders: Birmingham Business School - University of Birmingham
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HV Social pathology. Social and public welfare
URI: http://etheses.bham.ac.uk/id/eprint/9962

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