Crime

Question 1

Becker’s starting point

Answer 1

Criminal behaviour is rational.

(Contrary to approach where the behaviour is deemed to be a result of mental illness/social oppression)

Question 2

Factors to consider in this framework (7)

Answer 2

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

Question 3

Why is the optimal level of crime not 0?

So what is the optimal crime?

Answer 3

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.

Question 4

Why does the type of punishment matter

Answer 4

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)

Question 5

Relationship between enforcement and punishment

Answer 5

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.

Question 6

Decision rule (for the individual) commit crime if:

Answer 6

(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

Question 7

What else must be considered in their decision

Answer 7

Their risk appetite.

Easier to deter risk adverse people through p and s

Question 8

How do we create supply of crime

Answer 8

CP = f(Wc,p,s,W)

Criminal participation function.
Is a function of wage from crime, legitimate wage, probability of caught, and punishment.

Question 9

Demand for crime
2 types of crime, and how they fit into the Becker framework

Answer 9

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.

Question 10

Supply demand diagram pg 7

Answer 10

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…

Question 11

Relationship between unemployment and crime

Answer 11

Positive

Particularly property crime

1% increase unemployement causes increase in crime 1.1%-2.2%

Question 12

What is meant by the ‘porous boundary’ , and what does this imply we need to consider?

Answer 12

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)

Question 13

How can we consider W (legitimate earnings) with inequality?

Answer 13

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?)

Question 14

What did Cantor and Land find?

Answer 14

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

Question 15

Offsetting factors on crime

Answer 15

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.

Question 16

Freeman looked at 2 factors, what did he find?

Answer 16

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.

Question 17

Machin Meghir: what did they consider

Answer 17

Non violent crime (property & vehicle crime) , that is type of crime most likely to be influenced by economic incentives.

Question 18

What did they find?

Answer 18

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.

Question 19

Econometric stat

Answer 19

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!

Question 20

What did they find about increasing the average sentence length

Answer 20

It has a significant negative effect on crime.

Question 21

Why is the link between wages and crime clearer than unemployment and crime?

Answer 21

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.

Question 22

Draca

Answer 22

Study role of illegal wage Wc.

Question 23

How do they do this

Answer 23

Consider burglaries, thefts, robberies, to calculate crime price elasticities.

To see how price changes influence crime trends

Question 24

What were the elasticities for:
Consumer goods

Answer 24

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)

Question 25

What did Freeman find for sanctions and criminal activity

Answer 25

Greater chance of arrest and sentence lead to a lower crime rate.

Question 26

What is an issue with this? What does this imply the need for

Answer 26

Identification. Difficult to find a sufficiently large change in sanctions and control for other factors. Therefore economists seek out natural experiments

Question 27

Draca: what was the natural experiment

Answer 27

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

Question 28

Key finding (stat) Which type of crime was most affected by the increase in police prescence?

Answer 28

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.

Question 29

Evaluation of natural experiments (2)

Answer 29

Hard to find Causation

Question 30

So how can we make sure Draca results are causal (6)

Answer 30

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.

Question 31

What does Han et al look at

Answer 31

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)

Question 32

What are the dependent (2) and independent variables (1)

Answer 32

Dependent: (which are considered one by one) Violent crime rates Property crime rates Independent: Law enforcement variables Socio-economic variables

Question 33

What are law enforcement variables (2)

Answer 33

Crime detection rates (P) Size of prison population (if high suggests punishment S is high)

Question 34

What are socio-economic factors (4)

Answer 34

Unemployment rates Real average weekly earnings Proportion of young (15-24) in population Income inequality (measured by gini)

Question 35

Findings:

Answer 35

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.

Question 36

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:

Answer 36

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 (↓).

Question 37

So what should be done

Answer 37

Consider low wages (25th percentile) like in Machin.

Question 38

Further results

Answer 38

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

Question 39

Han results continued

Answer 39

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.