Economikly

The Economics Of Crime: Tackling Breach Of Law

Introduction

Crime and breach of law is an increasingly debatable issue since the existence of humankind. In today’s world, the term ‘crime’ is not merely used to describe the violation of an individual or a group of individuals through murder, burglary, sexual misconduct, or fraud. The law condemns any form of gross discrimination faced by people belonging to diverse cultures, ages, communities, etc. Crime, broadly interpreted and introduced into the field of Economics by Gary Becker in 1968, includes but is not limited to tax evasion, white-collar crimes, and cyber-bullying/harassment.

With a constant overhaul of how governments and the judicial institution must tackle crime, the probability of a person committing the same is generally believed to depend on the chances of being caught, a factor possibly more important than the severity of punishment. Various models in Economics have tried to examine crime from the view of choices available to a person. The decision to do wrong is often heavily influenced by childhood experiences, lack of cognitive and non-cognitive skill development, and an unequal opportunity in education, employment, and others. The following are mini- studies and standard parameters that are looked at by experts to analyze their effects on crime rates, whether minimal or maximum, and whether the same can help in policy-making.

Do higher sanctions deter crime?

Economic models predict they do due to a rise in the expected costs incurred in criminal activities. However, this theory is difficult to test empirically. For example, in the United States, the ‘three-strikes’ legislation results in prison if one commits certain minor offenses thrice. So, the expected punishment for the same crime for first or second-time offenders is usually different. Economists investigate whether second-time criminals have a lower probability of committing the crime another time than first-time offenders. These subtle differences in probability make examining the causal impact on crime rates due to specific parameters exhausting. Another example of an experiment conducted in mid-2006 was potentially a source of this random variation in expected prison sentences for the same criminal activity. A “Collective Clemency Bill” passed by the then Italian Government in 2006 gave inmates who had committed a crime before May 2nd , 2006, a sentence reduction of up to 36 months. The Italian prisons being overpopulated had created a massive stir in the media, so politicians were expected to take measures. As a result of this Bill, approximately 40% of the prison population was released. However, if these individuals committed a crime within the next five years after freedom from prison, they would have to serve the remaining sentence suspended initially. The remaining sentences could vary between 1-36 months, and so the researchers would be interested in a variation comparison depending only on an inmate’s first entry into prison. This comparison also meant that studying people with the same initial sentences equals people with different residual sentences serving different lengths of time in prison. The estimated effect on recidivism would be interpreted as the combined deterrent effect of an additional month of imprisonment and one month less served. Longer punishments due to higher sanctions imposed by law or governments affect behaviour.

Are people sensitive to the threat of punishment, or instead to social norms and moral appeal?

To understand the mechanisms that lead to compliance with tax laws, economists used TV licenses in Austria as a case study. In 2005, a TV license fee would amount close to EUR 206 or EUR 263 per annum, independent of the number of household members. About 94% of households were recorded to pay this tax since 99% would have a television or a radio. Hence, not evading the payment of this tax would be flagged as a legit “tax fraud.” The researchers, therefore, write to all non-paying households who run the risk of a sudden inspection if they chose not to reply or lie about possessing a television or radio. Fifty thousand addresses of potential tax-evading households were received. The dependent variable of their analysis was the percent of families that would pay 50 days since the commencement of the experiments. While parameters like ‘information sheet’ and ‘response forms’ attached with the letters were kept the same, the ‘cover note’ varied. The text
in the cover note was different across three dimensions. One introduced a legal threat, the second version of social information, and, a moral appeal.

The legal danger warned the citizens of a federal investigation with high costs if there was no response or a refusal to comply with the Austrian Fee Information Service members’ investigation. The social information would put out facts for the households letting them know that compared to them, almost every other home (94%) was fulfilling the civic duty and had registered with
the broadcasting agents to pay taxes. Lastly, the moral appeal would request fairness on behalf of these households as they violate union laws and ‘harm’ honest families that comply with them yet might come under scrutiny. The results from these experiments outlined that sending a letter did have a positive outcome. It efficiently increased the declaration of a TV license in monitored neighbourhoods added the “legal threat,” i.e., warning of a higher sanction triggered a faster and more extensive response rate. However, social information and moral appeal did not seem to matter. The results proved that harsher punishments enforced by the authorities only could deter crime rates. These punishments not only promised a strict federal investigation into tax fraud cases but also an expense of heavy amounts due to fines.

Does an increase in police resources reduce crime?

The Street Crime Initiative (SCI) was introduced in 2002-03 by the Crime Department of England and Wales to reduce robbery. Only some police forces received financial support, so large counties were divided into two parts: SCI and non-SCI. Since numbers initially showed that regions witH additional resources were those with higher pre-policy robbery rates, economists used a difference-in-difference approach to compare robbery rates over a while. They found that SCI and non-SCI areas have similar trends in robbery and other street crimes before the policy intervention of deploying additional police monitoring. After the policy implementation, robbery rates fell in SCI areas more strongly. In contrast, rates in non-SCI regions continued to rise. Further enforcement of police reduced robberies by more than 25%. Thus, if perhaps a quick and efficient measure is to be looked at to reduce significant and minor street crimes, investment into better and large-scale personnel has proven to give hopeful endings.

Can supervising workers reduce losses?

With a global estimated annual loss of USD 3.5 trillion due to occupation fraud cases, experts look at constant monitoring as a means to reduce them. A 2016 experiment considered three dimensions, one of which would be particularly monitored to see if there would be negative spillovers to others. The subjects were from the University of Magdeburg. The job was to identify the provenance of Euro coins collected in different Eurozone countries. Each student received four boxes of coins, for which they were asked to fill out identification forms. Within each set, the composition of packages varied to the value and number of coins. They were asked to indicate the exact time they would return the coins that the research team would note. The three dimensions of productivity that were measured here were quality (how many mistakes do participants make), tardiness (punctuality in returning coins), and theft (stealing coins). The control group received no monitoring while two treatment groups received supervision with mild incentives and harsh incentives. The results were as follows.

  • Treatment 1 does not lead to lesser mistakes compared to the controlled but treatment 2 does. It seemed that strict incentives rather than monitoring had a direct effect on quality.
  • Theft is constant across all.
  • Both treatment groups affect tardiness since workers wanted to retaliate for being monitored by not being punctual. Overall, experts concluded that monitoring does pay off to reduce losses if it is associated with harsh incentives, if monitoring costs are low, and lastly, if the dimensions that cannot be supervised either entail high moral costs or the relative gains in productivity in that dimension more than compensate for the losses in other parameters due to no monitoring.

Conclusion

Researchers are constantly analyzing various models to develop a definitive way to gain more insight into crime models and how economics can tackle it. They look at criminal behavior as they look at any other to carry out a cost- benefit study. However, when doing this, they tend to compare the possible net gains of committing a crime with net revenues of other activities. For some people with low human capital, committing a crime might be more attractive than those with high human capital (skills, education build-up). Those who enter the labor market in a recession might face fewer outside opportunities that are more profitable compared to others. Education has a huge role to play here. With the completion of an entire school term, young people who can fulfill this have less time to commit a crime. Therefore, lack of privilege often triggers a career in wrongdoing out of the inherent need to sustain life and maintain a minimum standard of living.

References

Machin, S. and O. Marie (2011) Crime and Police Resources: The Street Crime Initiative. Journal of the European Economic Association 9, 678-701. Available from: https://personal.lse.ac.uk/machin/drafts/ms.pdf

Becker, G. (1968) Crime and Punishment: An Economic Approach. Journal of Political Economy 76, 169-217. Available from: https://www.nber.org/system/files/chapters/c3625/c3625.pdf

Belot, M. and M. Schroeder (2016) The Spillover Effects of Monitoring: A Field Experiment. Management Science 62, 37-45. Available from: https://econpapers.repec.org/article/inmormnsc/v_3a62_3ay_3a2016_3ai_3a1_3ap_3a37-45.htm

Drago, F., R Galbiati and P. Vertova (2009) The Deterrent Effects of Prison: Evidence from a Natural Experiment. Journal of Political Economy 117, 257-280 Available from: http://ftp.iza.org/dp2912.pdf

Fellner, G., R. Sausgruber and C. Traxler (2013) Testing Enforcement Strategies in the Field: Threat, Moral Appeal and Social Information. Journal of the European Economic Association 11, 634-660. Available from: https://scholar.google.dk/citations?user=L6y2dKIAAAAJ&hl=da

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