Crime Flashcards
Becker’s starting point
Criminal behaviour is rational.
(Contrary to approach where the behaviour is deemed to be a result of mental illness/social oppression)
Factors to consider in this framework (7)
Probability of being convicted
Severity of punishment
Utility gained from crime
Disutility from punishment
Opportunity cost of engaging in criminal activity
Type of punishment (the cost of enforcement)
Cost to society
Why is the optimal level of crime not 0?
So what is the optimal crime?
Not optimal as the cost of fully eliminating crime to 0, is high marginally.
Optimal outcome is where we set MC of last conviction equal to MB of preventing that crime.
Why does the type of punishment matter
Prison might be the most effective deterrent, but doesn’t mean all crimes need sentences.
(I.e for petty theft, damage caused by crime is low, but the cost of putting them in prison is high)
Relationship between enforcement and punishment
There is a trade off between them, since both involve costs
May have a good police force (enforcement) but courts may not be adequate to punish correctly, e.g not keep people who committed serious crimes in prison for long enough or at all, with the crime budget.
Decision rule (for the individual) commit crime if:
(1–p)U(Wc) – pU(S) > U(W)
I.e if expected probability weighted utility from crime exceeds the utility from working legally
U(W) is earnings from wage
U(Wc) earnings from crime
P is probability of being caught
S is punishment if caught
What else must be considered in their decision
Their risk appetite.
Easier to deter risk adverse people through p and s
How do we create supply of crime
CP = f(Wc,p,s,W)
Criminal participation function.
Is a function of wage from crime, legitimate wage, probability of caught, and punishment.
Demand for crime
2 types of crime, and how they fit into the Becker framework
Victimless crimes e.g drugs, prostitution, counterfeit goods.
These can be applied into the framework, with demand sloping demand curve
Victim crimes e.g violent crime
Harder to put into framework, since earnings harder to measure.
Supply demand diagram pg 7
Supply curve is the criminal participation function.
If Wc (earnings from crime) is high, supply of crime is higher, so upward sloping.
Demand downward sloping as when…
Relationship between unemployment and crime
Positive
Particularly property crime
1% increase unemployement causes increase in crime 1.1%-2.2%
What is meant by the ‘porous boundary’ , and what does this imply we need to consider?
People who admit to having committted a crime are more likely to have committed it whilst unemployed, but this is not the full picture.
Criminals also often have legal jobs. So we need to consider the returns to legitimate work (W)
How can we consider W (legitimate earnings) with inequality?
Use Wlow and Whigh.
Consider an increase in inequality caused by a fall in Wlow and an increase in Whigh.
Since the lowest wage is now even lower, the incentive to engage in crime may increase.
Also higher earnings at the top also can increase the incentive to commit crime. (Why tho?)
What did Cantor and Land find?
There are 2 mechanisms that counterbalance each other.
Criminal motivation effect - as lower wages fall, the motivation for crime increases
Criminal opportunity effect - as higher wages increase, opportunity for crime increases
Offsetting factors on crime
Society may now be more willing and able to fund increases in crime prevention (p) and increase sentences (s)
Rich may install better defences against crime or move to gated communities etc.
Freeman looked at 2 factors, what did he find?
Wage level - real incomes of less-skilled young men (crime-prone demographic) fell.
Wage inequality - income inequality rose, as did crime. Not just economic crime, even violent crime, which should be less affected by economic factors.
Machin Meghir: what did they consider
Non violent crime (property & vehicle crime) , that is type of crime most likely to be influenced by economic incentives.
What did they find?
Using 25th percentile wage (less-skilled) , we find areas with lower wage growth at the bottom end of the wage distribution (the 25th percentile) experience faster rising crime rates.
Econometric stat
A region with a 10% higher 25th percentile wage has a lower property crime rate by around 0.7/0.8%.
And overall crime rate is 8%, so it is significant; almost 10% of crime!
What did they find about increasing the average sentence length
It has a significant negative effect on crime.
Why is the link between wages and crime clearer than unemployment and crime?
Employed people can commit crime too. If W is low, they may be encouraged to supplement income through crime.
Thus wages are a better indicator.
Draca
Study role of illegal wage Wc.
How do they do this
Consider burglaries, thefts, robberies, to calculate crime price elasticities.
To see how price changes influence crime trends
What were the elasticities for:
Consumer goods
Consumer goods: 0.35 (inelastic; crime for that good is unresponsive to change in price)
Commodities: >1, elastic; crime for that good is responsive to price (REWARD)
What did Freeman find for sanctions and criminal activity
Greater chance of arrest and sentence lead to a lower crime rate.
What is an issue with this? What does this imply the need for
Identification. Difficult to find a sufficiently large change in sanctions and control for other factors.
Therefore economists seek out natural experiments
Draca: what was the natural experiment
Following the 7/7 bombings, police activity increased by 30% to prevent further terrorist attacks.
However they used this to identify the types of crime which are most likely deterred by additional police prescence
Key finding (stat)
Which type of crime was most affected by the increase in police prescence?
A 10% in policing reduces crime by 3.2%
Larger effects for susceptible crimes e.g theft pickpocketing rather than non-susceptible e.g burglary.
Evaluation of natural experiments (2)
Hard to find
Causation
So how can we make sure Draca results are causal (6)
Scale of police deployment was so large (30%)
Deployment was unpredictable - anticipation not possible e.g could not know to increase crime a lot before the increase in policing.
Timing of reduction in crime fits
Types of crime were carefully chosen
Police prescence remained constant in non-affected neighbouring boroughs and there was no increase in crime in these boroughs.
When police prescence return to pre-attack level, crime rate increased.
What does Han et al look at
A dynamic model of crime - study property and violent crime, allowing for inertia/persistance in crime rates.
(Since crime rates may be slow to react - policy lags)
What are the dependent (2) and independent variables (1)
Dependent: (which are considered one by one)
Violent crime rates
Property crime rates
Independent:
Law enforcement variables
Socio-economic variables
What are law enforcement variables (2)
Crime detection rates (P)
Size of prison population (if high suggests punishment S is high)
What are socio-economic factors (4)
Unemployment rates
Real average weekly earnings
Proportion of young (15-24) in population
Income inequality (measured by gini)
Findings:
Crime rates exhibit a high degree of persistence, recidivism (crime yesterday can be linked to crime today due to the lag, people can reoffend)
Crime detection rate is strongly negatively correlated with property crime. An increase in detection rate leads to a 0.11% fall in burglary, 0.2% fall in theft, 0.14% fall in fraud.
Increase in prison population leads to a fall in burglary, but not theft or fraud.
Higher detection rate also reduces violent crime
Higher prison population can reduce robbery and sexual offences, but unexpectedly a higher rate of violence.
Higher unemployment = lower rates of burglary and fraud, but no effect on theft. (You would expect a higher unemployment to increase burglary!! Iterates again how unemployment is not a good independent variable to use)
Real earnings and property crime are positively related.
Real earnings and property crime are positively related: is this counter intuitive
Recall that a decline in real earnings can exert two
opposing effects on the level of crime:
The incentive effect due to the lower opportunity
cost of crime; motivation effect (↑).
But there are now likely to be fewer valuable items
available to steal; opportunity effect (↓).
So what should be done
Consider low wages (25th percentile) like in Machin.
Further results
For violent crimes, unemployment only has a
statistically significant effect on robbery. Higher
unemployment leads to lower rates of robbery.
The effect of real earnings is positive for violence
against the person and sexual offences but there is
no statistically significant effect for robbery.
These results are similar to those reported for property crime
Han results continued
The ‘proportion of young people’ is found to have no
statistically significant effect for most of the categories
of crime considered, although burglary and robbery
are exceptions.
The Gini coefficient has a positive and significant effect
on burglary and theft & handling (as expected).
The sign of the estimated coefficient on the Gini
coefficient varies for the violent crimes considered:
positive for robbery and negative for violence against
the person and sexual offences.
