llad phillips1 part i strategies to estimate deterrence part ii optimization of the criminal justice...

Llad Phillips 1

Part IStrategies to Estimate Deterrence

Part IIOptimization of the Criminal

Justice System



Justice System

Llad Phillips 2

OutlineOutline_ Human Capital & Other NewsHuman Capital & Other News_ Studying for the MidtermStudying for the Midterm_ Deterrence: Deterrence:

_ Evidence proEvidence pro_ Evidence con Evidence con

Llad Phillips 3

Human Capital newsHuman Capital news

Llad Phillips 4

About 60%Of 9th gradersGet a diplomasomewhere

Llad Phillips 5

The highHurdle?Algebra

Llad Phillips 6

Studying For the MidtermStudying For the Midterm

_ http://econ.ucsb.edu/

http://econ.ucsb.edu/

Llad Phillips 7

Llad Phillips 8

Llad Phillips 9

Llad Phillips 10

Llad Phillips 11

Llad Phillips 12

Deterrence: conceptual issuesDeterrence: conceptual issues_ Controlling for causality_ Simultaneity

Llad Phillips 13Source: Report to the Nation on Crime and Justice

Expect

Get

Llad Phillips 14

Crime Generation

Crime Control

OffenseRate PerCapita

ExpectedCost ofPunishment

Schematic of the Criminal Justice System

Causes ?

(detention,deterrence)

Expenditures

Weak Link

Control for Causality

Llad Phillips 15

Crime Generation

Crime Control




Causes ?


Expenditures

Weak Link

RecognizeSimultaneity

Llad Phillips 16

News Over the WeekendNews Over the Weekend_ Deep RecessionDeep Recession

high Unemployment ratehigh Unemployment rate

Keynesian EconomicsKeynesian Economics

drop money from a helicopter?drop money from a helicopter?

Or invest in infrastructure?Or invest in infrastructure?

TransportationTransportation

EnergyEnergy

independenceindependence

greengreen

Llad Phillips 17

Greening the EarthGreening the Earth

_ Greening UCSBGreening UCSB_ Rec-CenRec-Cen

Llad Phillips 18

Human development Index and Electricity Use

Human development Index and Electricity Use

Llad Phillips 19

UN Human Development Index & Electricity Consumption

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 2000 4000 6000 8000 10000 12000 14000 16000 18000

Annual Kwhr Per capita

Ind

ex

Production FunctionProduction Function

Llad Phillips 20

Llad Phillips 21

Llad Phillips 22

Llad Phillips 23

Policy Comment About Economic Development

Policy Comment About Economic Development

_ An Obama Keynesian strategy: invest in infrastructure_ Past investments in infrastructure

_ Canals_ Railroads_ Paved roads_ Airways_ ?

Llad Phillips 24

Cesare Marchetti“Fifty-Year Pulsation In Human Affairs”

Futures 17(3):376-388 (1986)www.cesaremarchetti.org/archive/scan/

MARCHETTI-069.pdf

Cesare Marchetti“Fifty-Year Pulsation In Human Affairs”

Futures 17(3):376-388 (1986)www.cesaremarchetti.org/archive/scan/

MARCHETTI-069.pdf

_ Example: the construction of railroad miles is logistically distributed

Llad Phillips 25

0.0

0.1

0.2

0.3

-10 -5 0 5

RAILMILES

FR

EQ

UE

NC

Y

Mean

constructed

90%10%

1859

1890

1921

Llad Phillips 26

Cesare MarchettiCesare Marchetti

Llad Phillips 27

Llad Phillips 28

Cesare Marchetti: Energy Technology: Coal, Oil, Gas, Nuclear

Cesare Marchetti: Energy Technology: Coal, Oil, Gas, Nuclear

52 years 57 years 56 years

Llad Phillips 29

Cesare MarchettiCesare Marchetti

Llad Phillips 30

Theodore ModisTheodore Modis

Figure 4. The data points represent the percentage deviation of energy consumption in the US from the natural growth-trend indicated by a fitted S-curve. The gray band is an 8% interval around a sine wave with period 56 years. The black dots and black triangles show what happened after the graph was first put together in 1988.[7] Presently we are

entering a “spring” season. WWI occurred in late “summer” whereas WWII in late “winter”.

Llad Phillips 31

0

2

4

6

8

10

12

14

16

1900 1920 1940 1960 1980 2000

HOMICIDECA HOMICIDEUSA

California

USA

Homicide and Non-negligent Manslaaaughter, Rates Per 100,000

Llad Phillips 32

0

5

10

15

20

25

1900 1920 1940 1960 1980 2000

HOMICIDECA MISERY

CA Homicide Rate Per 100,000 & Misery Rate in %

Llad Phillips 33

Causality?Causality?

Misery Index Offense Rate

Mystery Force

Llad Phillips 34

-0.004

-0.002

0.000

0.002

0.004

0.00

0.01

0.02

0.03

0.04

55 60 65 70 75 80 85 90 95 00 05

Residual Actual Fitted

Regress CAINDXPC = a + b*MISERY + e(t)where e(t) = 0.96*e(t-1) + u(t)

Llad Phillips 35

Crime Generation

Crime Control




Causes ?


Expenditures

Weak Link

Control for Causality

Llad Phillips 36

0

2000

4000

6000

8000

10000

60 70 80 90 00 10 20 30 40

CAPRISONERS

California Prisoners: 1851-1945

Llad Phillips 37

-1000

0

1000

2000

3000

4000

5000

6000

60 70 80 90 00 10 20 30 40

DETREND

detrend = caprisoners - 19.656 - 48.569*time

1851 1945

1900

1930

Llad Phillips 38

-0.004

-0.002

0.000

0.002

0.004

0.006

0.00

0.01

0.02

0.03

0.04

55 60 65 70 75 80 85 90 95 00 05

Residual Actual Fitted

Regression of CAINDXPC on MISERY and CAPRPC

Llad Phillips 39

Llad Phillips 40



Llad Phillips 41

Questions About CrimeQuestions About Crime

Why is it difficult to empirically Why is it difficult to empirically demonstrate the control effect of deterrence demonstrate the control effect of deterrence on crime?on crime?

What is the empirical evidence that raises What is the empirical evidence that raises questions about deterrence?questions about deterrence?

What is the empirical evidence that supports What is the empirical evidence that supports deterrence?deterrence?

Llad Phillips 42

Evidence Against the Death Penalty Being a DeterrentEvidence Against the Death Penalty Being a Deterrent Contiguous StatesContiguous States

Maine: no death penaltyMaine: no death penalty Vermont: death penaltyVermont: death penalty New Hampshire: death penaltyNew Hampshire: death penalty

Little Variation in the Homicide RateLittle Variation in the Homicide Rate Source: Study by Thorsten Sellin in Hugo Source: Study by Thorsten Sellin in Hugo

Bedau, Bedau, The Death Penalty in AmericaThe Death Penalty in America

Llad Phillips 44

Isaac Ehrlich Study of the Death Penalty: 1933-1969Isaac Ehrlich Study of the Death Penalty: 1933-1969 Homicide Rate Per CapitaHomicide Rate Per Capita

Control VariablesControl Variables probability of arrestprobability of arrest probability of conviction given charged probability of conviction given charged Probability of execution given convictionProbability of execution given conviction

Causal VariablesCausal Variables labor force participation ratelabor force participation rate unemployment rateunemployment rate percent population aged 14-24 yearspercent population aged 14-24 years permanent incomepermanent income trendtrend

Ehrlich Results: Elasticities of Homicide with respect to ControlsEhrlich Results: Elasticities of Homicide with respect to Controls

Control Elasticity Average Valueof Control

Prob. of Arrest -1.6 0.90

Prob. of ConvictionGiven Charged

-0.5 0.43

Prob. of ExecutionGiven Convicted

-0.04 0.026

Source: Isaac Ehrlich, “The Deterrent Effect of Capital Punishment

Llad Phillips 46

Critique of Ehrlich by Death Penalty OpponentsCritique of Ehrlich by Death Penalty Opponents Time period used: 1933-1968Time period used: 1933-1968

period of declining probability of executionperiod of declining probability of execution Ehrlich did not include probability of Ehrlich did not include probability of

imprisonment given conviction as a control imprisonment given conviction as a control variablevariable

Causal variables included are unconvincing Causal variables included are unconvincing as causes of homicideas causes of homicide

Llad Phillips 47

U.S.

United States Bureau of Justice Statisticshttp://www.ojp.usdoj.gov/bjs/

Llad Phillips 48

U.S.


Llad Phillips 49

What is the Empirical Evidence that Supports Deterrence?What is the Empirical Evidence that Supports Deterrence? Domestic violence and police interventionDomestic violence and police intervention

Experiments with control groupsExperiments with control groups Traffic Black SpotsTraffic Black Spots

Focused enforcement effortsFocused enforcement efforts

Llad Phillips 50

Traffic Black SpotsTraffic Black Spots

Blood AlleyBlood Alley Highway 126Highway 126

San Marcos PassSan Marcos Pass Highway 154Highway 154

Llad Phillips 51

San Marcos Pass ExperimentSan Marcos Pass Experiment

Increase Highway PatrolsIncrease Highway Patrols Increase ArrestsIncrease Arrests

Total accidents decreaseTotal accidents decrease Injury accidents decreaseInjury accidents decrease Accidents involving drinking under the Accidents involving drinking under the

influence decreaseinfluence decrease

Llad Phillips 52

Los Angeles Traffic Map

Llad Phillips 54

Domestic Violence & Police Intervention

Domestic Violence & Police Intervention

Llad Phillips 55

1993-20051993-2005

Llad Phillips 56

Female Victims of Violent Crime, 1973-2003

Llad Phillips 57

Homicides of Intimates, 1976-2005Homicides of Intimates, 1976-2005

Llad Phillips 58

Female Victims of Violent CrimeFemale Victims of Violent Crime

In 1994In 1994 1 homicide for every 23,000 women (12 or older)1 homicide for every 23,000 women (12 or older)

females represented 23% of homicide victims in USfemales represented 23% of homicide victims in US 9 out of 10 female victims were murdered by males9 out of 10 female victims were murdered by males

1 rape for every 270 women1 rape for every 270 women 1 robbery for every 240 women1 robbery for every 240 women 1 assault for every 29 women 1 assault for every 29 women

Victims of Lone Offenders*Annual Average NumbersVictims of Lone Offenders*Annual Average Numbers

Female Male

Known 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

* Excludes Homicide

Llad Phillips 60


Llad Phillips 61

Llad Phillips 62

Average Annual Rate of Violent Victimizations Per 1000 FemalesAverage Annual Rate of Violent Victimizations Per 1000 FemalesFamily Income Total IntimateLess than $10,000 57 20$10,000 - $14,999 47 13$15,000 - $19,999 42 11$20,000 - $29,999 38 10$30,000 - $49,999 31 5$50,000 or more 25 5

Llad Phillips 63

Llad Phillips 64

Declining Trends in Intimate Violence: Homicide

Llad Phillips 65

Nonfatal Violent victimization RatesNonfatal Violent victimization Rates

Llad Phillips 66


Llad Phillips 67


Llad Phillips 68


Llad Phillips 69

Llad Phillips 70

Nonfatal intimate Victimization Rates By AgeNonfatal intimate Victimization Rates By Age

Llad Phillips 71

Llad Phillips 72

Female victimization rates by relationshipFemale victimization rates by relationship

Llad Phillips 73

Llad Phillips 74

Llad Phillips 75

Llad Phillips 76

Intimate homicides by weapon typeIntimate homicides by weapon type

Llad Phillips 77

Domestic Violence in California

http://caag.state.ca.us/

Llad Phillips 78

Llad Phillips 79

Domestic Violence Rates in California: 1988-19981988: 113.6 per 100.0001998: 169.9 per 100,000

Llad Phillips 80

Domestic Violence in California1988: 94% Male Arrests1998: 83.5% Male Arrests

Llad Phillips 81

Police Intervention with Experimental ControlsPolice Intervention with Experimental Controls A 911 call from a family memberA 911 call from a family member

the case is randomly assigned for “treatment”the case is randomly assigned for “treatment” A police patrol responds and visits the A police patrol responds and visits the

householdhousehold police calm down the family memberspolice calm down the family members based on the treatment randomly assigned, the based on the treatment randomly assigned, the

police carry out the sanctionspolice carry out the sanctions

Llad Phillips 82

Why is Treatment Assigned Randomly?Why is Treatment Assigned Randomly? To control for unknown causal factorsTo control for unknown causal factors

assign known numbers of cases, for example assign known numbers of cases, for example equal numbers, to each treatmentequal numbers, to each treatment

with this procedure, there should be an even with this procedure, there should be an even distribution of distribution of difficultdifficult cases in each treatment cases in each treatment groupgroup

Llad Phillips 83

911 call(characteristics of household Participants unknown)

Random Assignment

code blue code gold

patrol responds patrol responds

settles the household settles the household

verbally warn the husband take the husband to jail for the night

Llad Phillips 84


Justice System


Justice System

Llad Phillips 85

Questions About Statistical Studies of DeterrenceQuestions About Statistical Studies of Deterrence_ Do we know enough about the factors that cause Do we know enough about the factors that cause

crime?crime?_ Can we find variables that will control for variation in Can we find variables that will control for variation in

crime generation?crime generation?

_ We have better measures for the factors that We have better measures for the factors that control crime than for the factors that cause crime.control crime than for the factors that cause crime._ Unknown variation in crime generation may mask the Unknown variation in crime generation may mask the

effects of crime control.effects of crime control.

Llad Phillips 86

Crime Generation

Crime Control




Causes ?


Expenditures

Weak Link

per capita expenditures on CJS

offense rate per capita

Four-Way Diagram: Crime Generation & Crime Control

1

2

3

Source: Report to the Nation on Crime and Justice


control

Causalfactors

Expenditures per Capita

Offenses Per Capita

Crime Control Technology

South Dakota North Dakota

2500 Index crimesper 100,000 people

$100

$00

Llad Phillips 91

Optimization of the Criminal Justice System (CJS)Optimization of the Criminal Justice System (CJS) Minimize damages to victims plus the costs Minimize damages to victims plus the costs

of control, subject to the crime control of control, subject to the crime control technologytechnology damages to victims per capita = loss rate per damages to victims per capita = loss rate per

offense * offense rate per capitaoffense * offense rate per capita Costs of control = per capita expenditures on CJSCosts of control = per capita expenditures on CJS Total cost = damages + expendituresTotal cost = damages + expenditures


Offenses Per Capita




$100

Total cost = expenditures per capita

$200

$00


Offenses Per Capita




$100


Total cost = damages to victims

$200

$00

5000 Index offenses per 100,000 people = 0.05 per capita

Llad Phillips 94


Offenses Per Capita



0.025 Index crimesper capita

$100



0.050

Total cost = $200 per capita = damages to victims = loss rate*0.05so loss rate = $4,000 per Index Crime in South Dakota

$200

$00

Llad Phillips 17

Cost to Victims in US, 1993Offense Loss Rate Reported

OffensesDamages,Billions $

Robbery $13,000 659,757 $8.6

AutoTheft

$4,000 1,561,047 $6.2

Burglary $1,500 2,834,808 $4.3

Larceny $370 7,820,909 $2.4

Total $21.5

Source: National Institute of Justice, Victim Costs and Consequences (1996)

Source: Phillips: Lecture One

Llad Phillips 96

Expenditures per capita

Offenses Per Capita


$100



Family of Total Cost CurvesHigh

Low

Llad Phillips 97


Offenses Per Capita




$100



Llad Phillips 98

Application of the Economic ParadigmApplication of the Economic Paradigm Specify the feasible optionsSpecify the feasible options

the states of the world: Crime control the states of the world: Crime control technologytechnology

Value the optionsValue the options loss rate per offenseloss rate per offense

OptimizeOptimize Pick the lowest cost point on the crime control Pick the lowest cost point on the crime control

technologytechnology

That’s all folks!

Crime Generation1. variation of offense rate per capita with expected cost of punishment2. Shift in the relationship with a change in causal factors

Offenserate percapita

Expected cost(severity) of punishment

crime generation function

Crime Generation1. variation of offense rate per capita with expected cost of punishment2. Shift in the relationship with a change in causal factors

Offenserate percapita

Expected cost(severity) of punishment

crime generation function

High causal conditions

Low causal conditions

Production Function for the Criminal Justice System (CJS)1. Variation in expected costs of punishment with criminal justice system expenditure per capita

Expected costs ofpunishment

Criminal Justice System expenditures per capita

production function



expected cost of punishment

Crime Generation





Crime Generation



ProductionFunction




Crime Generation



ProductionFunction

square

450




Crime Generation



ProductionFunction

square

4501

1




Crime Generation



ProductionFunction

square

4501

1

2

2




Crime Generation



ProductionFunction

square

4501

1

2

2

3

Llad Phillips 113

Female Victims of Violent CrimeFemale Victims of Violent Crime

Llad Phillips 114

Llad Phillips 115

Llad Phillips 116

Long Swings in the Homicide Rate in the US: 1900-1980


Llad Phillips 118


Long Swings inThe Homicide Rate

Llad Phillips 119

California Homicide Rate Per 100,000: 1952-2003

0

2

4

6

8

10

12

14

16

1950 1960 1970 1980 1990 2000 2010

Year

Rat

e

llad phillips1 part i strategies to estimate deterrence part ii optimization of the criminal justice...

Documents

llad phillips27 slide

llad phillips22 slide

llad phillips20 slide

llad phillips32 slide

llad phillips21 slide

llad phillips11 slide

llad phillips31 slide

llad phillips7 slide