Transcript lecture 4 deterrence

Part I
Strategies to Estimate Deterrence
Part II
Optimization of the Criminal
Justice System
Llad Phillips
1
Studying For the Midterm
_
http://econ.ucsb.edu/
Llad Phillips
2
Llad Phillips
3
Llad Phillips
4
Llad Phillips
5
Llad Phillips
6
Llad Phillips
7
Part I
Strategies to Estimate Deterrence
Llad Phillips
8
Questions About Crime
 Why
is it difficult to empirically
demonstrate the control effect of deterrence
on crime?
 What is the empirical evidence that raises
questions about deterrence?
 What is the empirical evidence that supports
deterrence?
Llad Phillips
9
What is the Empirical Evidence
that Supports Deterrence?
 Domestic
violence and police intervention
Experiments
 Traffic
Black Spots
Focused
Llad Phillips
with control groups
enforcement efforts
10
Female Victims of Violent Crime
Llad Phillips
11
Female Victims of Violent Crime
 In
1994
1
homicide for every 23,000 women (12 or
older)
 females
represented 23% of homicide victims in US
 9 out of 10 female victims were murdered by males
1
rape for every 270 women
1 robbery for every 240 women
1 assault for every 29 women
Llad Phillips
12
Victims of Lone Offenders*
Annual Average Numbers
Known
Female
Male
2,715,000
2,019,400
Intimate
1,008,000
143,400
Relative
304,500
122,000
Acquaintance
1,402,500
1,754,000
Stranger
802,300
1,933,100
United States Bureau of Justice Statistics
http://www.ojp.usdoj.gov/bjs/
Llad Phillips
14
Llad Phillips
15
Average Annual Rate of Violent
Victimizations Per 1000 Females
Family Income
Less than $10,000
$10,000 - $14,999
$15,000 - $19,999
$20,000 - $29,999
$30,000 - $49,999
$50,000 or more
Llad Phillips
Total
57
47
42
38
31
25
Intimate
20
13
11
10
5
5
16
Declining Trends in Intimate Violence: Homicide
Llad Phillips
17
United States Bureau of Justice Statistics
Llad Phillips
18
United States Bureau of Justice Statistics
http://www.ojp.usdoj.gov/bjs/
Llad Phillips
19
United States Bureau of Justice Statistics
http://www.ojp.usdoj.gov/bjs/
Llad Phillips
20
United States Bureau of Justice Statistics
http://www.ojp.usdoj.gov/bjs/
Llad Phillips
21
Llad Phillips
22
Domestic Violence in California
http://caag.state.ca.us/
Llad Phillips
23
Domestic Violence Rates in California: 1988-1998
1988: 113.6 per 100.000
1998: 169.9 per 100,000
Llad Phillips
24
Domestic Violence in California
1988: 94% Male Arrests
1998: 83.5% Male Arrests
Llad Phillips
25
Police Intervention with
Experimental Controls
 A 911
the
call from a family member
case is randomly assigned for “treatment”
 A police
patrol responds and visits the
household
police
calm down the family members
based on the treatment randomly assigned, the
police carry out the sanctions
Llad Phillips
26
Why is Treatment Assigned
Randomly?
 To
control for unknown causal factors
assign
known numbers of cases, for example
equal numbers, to each treatment
 with
this procedure, there should be an even
distribution of difficult cases in each treatment group
Llad Phillips
27
911 call
(characteristics of household Participants unknown)
Random Assignment
code blue
code gold
patrol responds
patrol responds
settles the household
verbally warn the husband
Llad Phillips
settles the household
take the husband to jail
for the night
28
Traffic Black Spots
 Blood Alley
Highway
 San
Marcos Pass
Highway
Llad Phillips
126
154
29
Los Angeles Traffic Map
San Marcos Pass Experiment
 Increase
Highway Patrols
 Increase Arrests
Total
accidents decrease
Injury accidents decrease
Accidents involving drinking under the
influence decrease
Llad Phillips
31
Llad Phillips
32
Evidence Against the Death
Penalty Being a Deterrent
 Contiguous
States
Maine:
no death penalty
Vermont: death penalty
New Hampshire: death penalty
 Little
Variation in the Homicide Rate
Source:
Study by Thorsten Sellin in Hugo
Bedau, The Death Penalty in America
Llad Phillips
33
Isaac Ehrlich Study of the Death
Penalty: 1933-1969
 Homicide
Control
Rate Per Capita
Variables
 probability
of arrest
 probability of conviction given charged
 Probability of execution given conviction
Causal
Variables
 labor
force participation rate
 unemployment rate
 percent population aged 14-24 years
 permanent income
 trend
Llad Phillips
35
Ehrlich Results: Elasticities of
Homicide with respect to Controls
Control
Elasticity
Average Value
of Control
0.90
Prob. of Arrest
-1.6
Prob. of Conviction
Given Charged
Prob. of Execution
Given Convicted
-0.5
0.43
-0.04
0.026
Source: Isaac Ehrlich, “The Deterrent Effect of Capital Punishment
Critique of Ehrlich by Death
Penalty Opponents
 Time
period used: 1933-1968
period
of declining probability of execution
 Ehrlich
did not include probability of
imprisonment given conviction as a control
variable
 Causal variables included are unconvincing
as causes of homicide
Llad Phillips
37
U.S.
Llad Phillips
United States Bureau of Justice Statistics
http://www.ojp.usdoj.gov/bjs/
38
U.S.
United States Bureau of Justice Statistics
http://www.ojp.usdoj.gov/bjs/
Llad Phillips
39
Long Swings in the Homicide Rate in the US: 1900-1980
Source: Report to the Nation on Crime and Justice
Long Swings in
The Homicide Rate
United States Bureau of Justice Statistics
http://www.ojp.usdoj.gov/bjs/
Llad Phillips
41
California Homicide Rate Per 100,000: 1952-2003
16
14
12
Rate
10
8
6
4
2
0
1950
1960
1970
1980
1990
2000
2010
Year
Llad Phillips
42
Part II
Optimization of the Criminal
Justice System
Llad Phillips
43
Questions About Statistical
Studies of Deterrence
_
Do we know enough about the factors that
cause crime?
_
_
Can we find variables that will control for
variation in crime generation?
We have better measures for the factors that
control crime than for the factors that cause
crime.
_
Unknown variation in crime generation may
mask the effects of crime control.
Llad Phillips
44
Schematic of the Criminal Justice System
Causes ?
Weak Link
Offense
Rate Per
Capita
Crime Generation
Expenditures
Expected
Cost of
Punishment
(detention,
deterrence)
Crime Control
Llad Phillips
45
Crime Generation
1. variation of offense rate per capita with expected cost
of punishment
2. Shift in the relationship with a change in causal factors
Offense
rate per
capita
crime generation function
Expected cost(severity) of punishment
Crime Generation
1. variation of offense rate per capita with expected cost
of punishment
2. Shift in the relationship with a change in causal factors
Offense
rate per
capita
crime generation function
High causal conditions
Low causal conditions
Expected cost(severity) of punishment
Production Function for the Criminal Justice System (CJS)
1. Variation in expected costs of punishment with
criminal justice system expenditure per capita
Expected
costs of
punishment
production function
Criminal Justice System expenditures per capita
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
offense rate per capita
Crime Generation
expected cost of punishment
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
per capita
expenditures
on CJS
offense rate per capita
Production
Function
Crime Generation
expected cost of punishment
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
square
per capita
expenditures
on CJS
Production
Function
450
offense rate per capita
Crime Generation
expected cost of punishment
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
1
square
per capita
expenditures
on CJS
Production
Function
1
450
offense rate per capita
Crime Generation
expected cost of punishment
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
1
square
per capita
expenditures
on CJS
Production
Function
1
450
offense rate per capita
Crime Generation
expected cost of punishment
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
1
square
per capita
expenditures
on CJS
Production
Function
1
450
offense rate per capita
Crime Generation
expected cost of punishment
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
1
square
per capita
expenditures
on CJS
Production
Function
1
450
offense rate per capita
Crime Generation
expected cost of punishment
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
1
square
2
per capita
expenditures
on CJS
Production
Function
1
2 450
offense rate per capita
Crime Generation
expected cost of punishment
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
1
square
2
per capita
expenditures
on CJS
Production
Function
3
1
2 450
offense rate per capita
Crime Generation
expected cost of punishment
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
1
2
3
offense rate per capita
Source: Report to the Nation on Crime and Justice
Four-Way Diagram: Crime Generation & Crime Control
per capita expenditures on CJS
1
square
2
per capita
expenditures
on CJS
Production
Function
3
1
2 450
offense rate per capita
Crime Generation
expected cost of punishment
Causal
factors
control
Source: Report to the Nation on Crime and Justice
Expenditures
per Capita
Crime Control Technology
South Dakota
North Dakota
$100
$0
0
2500 Index crimes
per 100,000 people
Offenses Per Capita
Optimization of the Criminal
Justice System (CJS)
 Minimize
damages to victims plus the costs
of control, subject to the crime control
technology
damages
to victims per capita = loss rate per
offense * offense rate per capita
Costs of control = per capita expenditures on
CJS
Total cost = damages + expenditures
Llad Phillips
63
Expenditures
per Capita
Total cost = expenditures per capita
Crime Control Technology
$200
South Dakota
North Dakota
$100
$0
0
2500 Index crimes
per 100,000 people
Offenses Per Capita
Expenditures
per Capita
Total cost = expenditures per capita
Crime Control Technology
$200
South Dakota
North Dakota
$100
Total cost = damages
to victims
$0
0
2500 Index crimes
per 100,000 people
Offenses Per Capita
5000 Index offenses per 100,000 people = 0.05 per capita
Expenditures
per Capita
Total cost = expenditures per capita
Crime Control Technology
$200
South Dakota
North Dakota
$100
Total cost = damages
to victims
$0
0
0.025
0.050 Offenses Per Capita
Index crimes
per capita
Total cost = $200 per capita = damages to victims = loss rate*0.05
so loss rate = $4,000 per Index Crime in South Dakota
Llad Phillips
66
Cost to Victims in US, 1993
Offense
Robbery
Loss Rate Reported
Offenses
$13,000
659,757
Damages,
Billions $
$8.6
Auto
Theft
Burglary
$4,000
1,561,047
$6.2
$1,500
2,834,808
$4.3
Larceny
$370
7,820,909
$2.4
Total
Source: National Institute of Justice,
$21.5
Victim Costs and Consequences(1996)
Llad Phillips
Source: Phillips: Lecture One
17
Expenditures per capita
Total cost = expenditures per capita
High
Family of Total Cost Curves
$100
Low
2500 Index crimes
per 100,000 people
Llad Phillips
Total cost = damages
to victims
Offenses Per Capita
68
Expenditures
per Capita
Total cost = expenditures per capita
Crime Control Technology
$100
South Dakota
North Dakota
Total cost = damages
to victims
2500 Index crimes
per 100,000 people
Llad Phillips
Offenses Per Capita
69
Application of the Economic
Paradigm
 Specify
the feasible options
the
states of the world: Crime control
technology
 Value
the options
loss
rate per offense
 Optimize
Pick
the lowest cost point on the crime control
technology
Llad Phillips
70
Female Victims of Violent Crime
Llad Phillips
72