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Economic Opportunity and Crime. Economics 160. Lecture 5 Professor Votey Crime Generation: Youth and Women. Notes :Votey, Lecture 3, 37. Consider the Circular Flow Process: (again). Depicting ( more elaborately) The Social Costs of Crime. This is the Social Cost Of Crime.

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Economic opportunity and crime

Economic Opportunity and Crime


Economics 160

Economics 160

Lecture 5

Professor Votey

Crime Generation: Youth and Women

Notes:Votey, Lecture 3, 37


Consider the circular flow process again

Consider the Circular Flow Process: (again)

  • Depicting ( more elaborately) The Social Costs of Crime

This is the

Social Cost

Of Crime

Victim Costs +


The circular flow model in symbolic notation

The Circular Flow Model in Symbolic Notation

  • Crime Generation:OF = g( CR, SV, SE) (1)

    • CR=Clearance Ratio

    • SV=Severity of Sentence

    • SE=Soc. & Econ. Conditions

  • Crime Control:(Lect. 3)CR = f( OF, L ) (2)

    • OF=Crime Load on the System

    • L =Law Enforcement Resources

  • Society’s ObjectiveMin. SC = r . OF + w . L (3)

    • where r = loss rate / Offense

    • w = resource price (police wage)

    • We might think of this as a social control model.

    • How does it relate to our notions of individual behavior?

Note the

circularity of the

relationships

Notes p. 37


Recall jeremy bentham s notion of individual utility maximization

Recall Jeremy Bentham’s Notion of Individual Utility Maximization


Recall jeremy bentham s notion of individual utility maximization1

Recall Jeremy Bentham’s Notion of Individual Utility Maximization

  • The Individual will maximize:


Recall jeremy bentham s notion of individual utility maximization2

Recall Jeremy Bentham’s Notion of Individual Utility Maximization

  • The Individual will maximize:E (NB ) = E ( B ) - E ( C ) = $B .P ( B ) - $C . P ( C )


Recall jeremy bentham s notion of individual utility maximization3

Recall Jeremy Bentham’s Notion of Individual Utility Maximization

  • The Individual will maximize:E (NB ) = E ( B ) - E ( C ) = $B .P ( B ) - $C . P ( C )and will commit a crime


Recall jeremy bentham s notion of individual utility maximization4

Recall Jeremy Bentham’s Notion of Individual Utility Maximization

  • The Individual will maximize:E (NB ) = E ( B ) - E ( C ) = $B .P ( B ) - $C . P ( C )and will commit a crime if E ( NB ) > 0


Recall jeremy bentham s notion of individual utility maximization5

Recall Jeremy Bentham’s Notion of Individual Utility Maximization

  • The Individual will maximize:E (NB ) = E ( B ) - E ( C ) = $B .P ( B ) - $C . P ( C )and will commit a crime if E ( NB ) > 0

  • Consider a potential criminal with two options:


Recall jeremy bentham s notion of individual utility maximization6

Recall Jeremy Bentham’s Notion of Individual Utility Maximization

  • The Individual will maximize:E (NB ) = E ( B ) - E ( C ) = $B .P ( B ) - $C . P ( C )and will commit a crime if E ( NB ) > 0

  • Consider a potential criminal with two options:A Crime:E(NB(Crime))= $Take . P(Not Jail))-$Jail . P(Jail)where P(Not Jail) = 1 - P(Jail)


Recall jeremy bentham s notion of individual utility maximization7

Recall Jeremy Bentham’s Notion of Individual Utility Maximization

  • The Individual will maximize:E (NB ) = E ( B ) - E ( C ) = $B .P ( B ) - $C . P ( C )and will commit a crime if E ( NB ) > 0

  • Consider a potential criminal with two options:A Crime:E(NB(Crime))= $Take . P(Not Jail))-$Jail . P(Jail)where Not Jail = 1 - P(Jail)An Honest Job:E(NB(Job)) = $wage . P(E)-$U . P(U)where E=Employed, U=Unempl, and P(E) = 1- P(U)


Recall jeremy bentham s notion of individual utility maximization8

Recall Jeremy Bentham’s Notion of Individual Utility Maximization

  • The Individual will maximize: E (NB ) = E ( B ) - E ( C ) = $B .P ( B ) - $C . P ( C ) and will commit a crime if E ( NB ) > 0

  • Consider a potential criminal with two options:A Crime:E(NB(Crime))= $Take . P(Not Jail))-$Jail . P(Jail) where Not Jail = 1 - P(Jail)An Honest Job:E(NB(Job)) = $wage . P(E)-$U . P(U) where E=Employed, U=Unempl, and P(E) = 1- P(U)

  • A Rational Individual will pick the Best Option


Note that using bentham s analysis suggests a two pronged set of policy alternatives

Note that Using Bentham’s Analysis suggests a two pronged set of policy alternatives

Raise the Cost of Jail (length of sentence) and / or

Increase P(Arrest), P(Conviction|Arrest),

P(Jail|Conviction)

thru Crime Control

Social Choice

thru Crime Generation

Lower P(Being Unemployed)

and / or

Raise Wages


Two views or maybe three

Two Views – or maybe three

  • The Rational Man Approach to Crime Control¹(Bentham’s Logic )

  • Most Modern Criminologists 2(Rejecting Bentham)

  • The Liberal Rational Man3(Bentham’s Logic Extended)

    ¹ Deterrence Works – Use the threat of Punishment

    ² Deterrence Doesn’t Work –(Rely on the Imprisonment Model)

    ³ Deterrence Works, but so do Economic Opportunities (In Today’s World this might have been Bentham’s View)


Some personal questions in regard to career choice

Some Personal Questions in Regard to Career Choice


Some personal questions in regard to career choice1

Some Personal Questions in Regard to Career Choice

  • Not for the record


Economic opportunity and crime

The Charles Schultz Perspective


At this point we are back to positive economics

At this point, we are – Back to Positive Economics

  • A little bit like detective work

    • A detective’s job is to solve a crimeso that the prosecutor can deal with the criminal

  • Our task was to explain criminal behavior

    • So that Public Policy could be modified|to reduce the likelihood of crime

  • The same sort of stimulus was facing Steven Levitt when he wrote his book


Consider crimes committed by youth we note that

Consider Crimes Committed by Youth:We Note That:

  • Crime involvement greatest among youth


Economic opportunity and crime

FBI,

Uniform Crime Reports

Cities of the U.S.,

By Type of Offense,

By Age


Consider crimes committed by youth we note that1

Consider Crimes Committed by Youth:We Note That:

  • Crime involvement greatest among youth

  • Historically Crime has been predominantly a malephenomenon


Relatively few offenders are female

Relatively few offenders are female

%Females

in group

All arrests (adults

and juveniles) 17%

Index crime arrests 21

Violent crime arrests 11

Property crime arrests 24

Larceny 31

Non larceny 8

Report to the Nation, 2nd Edit., p. 46

(Incarceration Data from 1984)


Consider crimes committed by youth we note that2

Consider Crimes Committed by Youth:We Note That:

  • Crime involvement greatest among youth

  • Historically Crime has been predominantly a malephenomenon

    (I will talk further about women’s increasing involvement in crime.)


Consider crimes committed by youth we note that3

Consider Crimes Committed by Youth:We Note That:

  • Crime involvement greatest among youth

  • Historically Crime has been predominantly a malephenomenon

  • Crime is more prevalent in the cities


Who are the victims of violent crime

Who are the victims of violent crime?

Rates per 1,000 persons

age 12 and older____

Residence (1984) RobberyAssaultRape

Central City 11 31 1

Suburban 5 24 1

Rural 3 19 1

Report to the Nation, 2nd Edit., p. 27


Consider crimes committed by youth we note that4

Consider Crimes Committed by Youth:We Note That:

  • Crime involvement greatest among youth

  • Historically Crime has been predominantly a malephenomenon.

  • Crime is more prevalent in the cities

  • Non-whites are more than proportionately involved


Economic opportunity and crime

Notes p.40


Consider crimes committed by youth we note that5

Consider Crimes Committed by Youth:We Note That:

  • Crime involvement greatest among youth

  • Historically Crime has been predominantly a malephenomenon.

  • Crime is more prevalent in the cities

  • Non-whites are more than proportionately involved

  • In our earliest analysis of youth participation in crime,we believed that a primary cause was lack of economic opportunities


Consider the picture of economic opportunities for youth

Consider the picture of economic opportunities for youth

  • Youth unemployment rates are high relative to those of older workers.Unempl. Rate = Persons actively seeking workLabor Force


Economic opportunity and crime

Notes p. 41


Consider the picture of economic opportunities for youth1

Consider the picture of economic opportunities for youth

  • Youth unemployment rates are high relative to those of older workers.Unempl. Rate = Persons actively seeking workLabor Force

  • What has been the effect of higher unemploymentrates for youth ?


Consider the picture of economic opportunities for youth2

Consider the picture of economic opportunities for youth

  • Youth unemployment rates are high relative to those of older workers.Unempl. Rate = Persons actively seeking workLabor Force

  • What has been the effect of higher unemploymentrates for youth ?1. A decline in their Labor Force Participation RatesAge Specific =No. Empl. or Seeking Work (Age) LFPR Population (Age)


Economic opportunity and crime

Recall that, in my previous lecture

I showed that a factor in the growth

crime was a decline in police effectiveness

starting in the mid-fifties.

Here we see another factor that may be

important, This is labor market data (BLS)

The decline in the Labor Force

Participation Rate

This is something Philip Cook

Didn’t Understand

Notes p. 42


An important elaboration here

An Important Elaboration Here

  • Prof. Phillips showed video of Phil Cook, Duke Univ, saying unemployment didn’t have much to do with crime patterns.

  • There was something he didn’t understand.He wasn’t alone in not understanding the link between jobs and crime.


Consider the picture of economic opportunities for youth3

Consider the picture of economic opportunities for youth

  • Youth unemployment rates are high relative to those of older workers.Unempl. Rate = Persons actively seeking workLabor Force

  • What has been the effect of higher unemploymentrates for youth ?1. A decline in their Labor Force Participation RatesAge Specific =No. Empl. or Seeking Work (Age) LFPR Population (Age)2. Youth invest in schooling to get a better job, stay out of the labor force temporarily.


Economic opportunity and crime

Notes p. 43


More recent data on the labor market and schooling

More Recent Data on the Labor Market and Schooling

Measure Population Year___________________

________Males, 18-19 1968 1979 1982 1984 1988 1998_2000UR % White 7.9 19.0 10.4

Non-white 12.3 29.6 25.0

LFPR% White 65.7 74.5 69.0

Non-white 63.3 57.8 43.8

School Combined 60.4 47.8

Enrollments

______,all ages

UR Combined 3.6 5.8 11.0 7.5 7.04.4 4.0

LFPR “ 59.6 63.367.1 67.2Source: Employment and Training Report of the President, various issues; 2000 data, www.bls.gov


Economic opportunity and crime

Testing the Hypothesis that Crime Rates for youth

are related to economic opportunities

The Population

of 18-19

year olds

This figure in Notes, p.38

AS

IP

Persons

committing

crimes

EMPL

NLF

UNEM

These relationships

can be stated in

terms of probabilities


Economic opportunity and crime

AS

IP

EMPL

NLF

UNEM


Economic opportunity and crime

Our Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- as a probability statement: Notes, p.38

We start by simply describing the relationships illustrated

in the Venn Diagram of Fig. 3.6 as a probability statement:


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- as a probability statement: Notes, p.32

  • We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

AS

IP

EMPL

NLF

UNEM


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

AS

IP

EMPL

NLF

UNEM


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

AS

IP

EMPL

NLF

UNEM


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

AS

IP

EMPL

NLF

UNEM


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

AS

IP

EMPL

NLF

UNEM


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function oflack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

P(Commit Crime and NLF) + P(other)

AS

IP

EMPL

NLF

UNEM


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function oflack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

P(Commit Crime and NLF) + P(other)

AS

IP

EMPL

NLF

UNEM


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function oflack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

P(Commit Crime and NLF) + P(other)

AS

IP

EMPL

NLF

UNEM


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function oflack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

P(Commit Crime and NLF) + P(other)

in terms of the components:


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function oflack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

P(Commit Crime and NLF) + P(other)

in terms of the components:

(OF/ Pop)[Age,Sex,Race] = (CrimeRate EMP)Prob(EMP)[Age,Sex,Race] +


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

P(Commit Crime and NLF) + P(other)

in terms of the components:

(OF/ Pop)[Age,Sex,Race] = (CrimeRate EMP)Prob(EMP)[Age,Sex,Race] +

(Crime Rate UNEM)Prob(UNEM)[Age,Sex,Race] +


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function oflack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

P(Commit Crime and NLF) + P(other)

in terms of the components:

(OF/ Pop)[Age,Sex,Race] = (CrimeRate EMP)Prob(EMP)[Age,Sex,Race] +

(Crime Rate UNEM)Prob(UNEM)[Age,Sex,Race] +

(CrimeRate NLF)Prob(NLF)[Age,Sex,Race] + P(Other)


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function oflack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

P(Commit Crime and NLF) + P(other)

in terms of the components:

(OF/ Pop)[Age,Sex,Race] = (CrimeRate EMP)Prob(EMP)[Age,Sex,Race] +

(Crime Rate UNEM)Prob(UNEM)[Age,Sex,Race] +

(CrimeRate NLF)Prob(NLF)[Age,Sex,Race] + P(Other)

Or, in terms of the estimation relationship in the text:


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

P(Commit Crime and NLF) + P(other)

in terms of the components:

(OF/ Pop)[Age,Sex,Race] = (CrimeRate EMP)Prob(EMP)[Age,Sex,Race]

rE x (1 - m) +

(Crime Rate UNEM)Prob(UNEM)[Age,Sex,Race] +

rUx m +

(CrimeRate NLF)Prob(NLF)[Age,Sex,Race] + P(Other)

rN x (1 - r) +e


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- as a probability statement:

We start by simply describing the relationships illustrated in the Venn Diagram of Fig. 3.6 as a probability statement:

P(Commit Crime) = P(Commit Crime and EMPL) +

P(Commit Crime and UNEM) +

P(Commit Crime and NLF) + P(other)

in terms of the components:

(OF/ Pop)[Age,Sex,Race] = (CrimeRate EMP)Prob(EMP)[Age,Sex,Race] +

Key for symbolsrE x (1 - m) +

in Text: (Crime Rate UNEM)Prob(UNEM)[Age,Sex,Race] +

m = Unempl. RaterUx m +

r= LFPR (CrimeRate NLF)Prob(NLF)[Age,Sex,Race] + P(Other)

e = error termrN x (1 - r) +e


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white

Results: for whites: rU > rE > rN


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white

Results: for whites: rU > rE > rN

Crime rate for those employed greater than crime rate for.....


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white

Results: for whites: rU > rE > rN

for non-whites rN > rU > rE


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white

Results: for whites: rU > rE > rN

for non-whites rN > rU > rE

Model Explains

(R2)

(In Regression

Analysis)


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white

Results: for whites: rU > rE > rN

for non-whites rN > rU > rE

Model Explains 87% of variation of Larceny OF rate

(R2)

(In Regression

Analysis)


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white

Results: for whites: rU > rE > rN

for non-whites rN > rU > rE

Model Explains 87% of variation of Larceny OF rate

(R2) 82 Burglary

(In Regression

Analysis)


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white

Results: for whites: rU > rE > rN

for non-whites rN > rU > rE

Model Explains 87% of variation of Larceny OF rate

(R2) 82 Burglary

(In Regression55 Robbery

Analysis)


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white

Results: for whites: rU > rE > rN

for non-whites rN > rU > rE

Model Explains 87% of variation of Larceny OF rate

(R2) 82 Burglary

(In Regression55 Robbery

Analysis)79 Auto Theft


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white

Results: for whites: rU > rE > rN

for non-whites rN > rU > rE

Model Explains 87% of variation of Larceny OF rate

(R2) 82 Burglary

(In Regression55 Robbery

Analysis)79 Auto Theft

Why the difference between whites and non-whites ?


Economic opportunity and crime

The Hypothesis: Crimes by youth are a function of lack of legitimate economic opportunities- empirical results:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19; separated: white, non-white

Results: for whites: rU > rE > rN

for non-whites rN > rU > rE

Model Explains 87% of variation of Larceny OF rate

(R2) 82 Burglary

(In Regression55 Robbery

Analysis)79 Auto Theft

Why the difference between whites and non-whites ?

We hypothesized that a greater proportion of the whites who were NLF were

enrolled in school, whereas a greater proportion of non-whites were

discouraged workers.


Economic opportunity and crime

Testing the hypothesis that black-white differenceswere due to differences in school enrollment rates:

The Data: U. S. cities, 1952-1967

Focus: Males, 18-19 ( not separated by race or ethnicity)

Results are for two offenses: burglary, robbery

Results:rDNLF > rSNLF

rDU > rDNLF > r DE

rSE ~rSU ~rSNLF

where E = enrolled in school

D = dropped out of school

Clearly, for this age group during these years, those enrolled had lower imputed offense rates than those dropped out of school, and the relative criminality of dropouts were similar to the ordering for whites, once the factor of school enrollment is eliminated. There was little difference in criminality among labor market classifications for those enrolled.


A verbal quiz regarding the choice model

A verbal quiz regarding the choice model:

  • Suppose someone could convince you that he had a job for you that


A verbal quiz regarding the choice model1

A verbal quiz regarding the choice model:

  • Suppose someone could convince you that he had a job for you that1. was illegal, requiring


A verbal quiz regarding the choice model2

A verbal quiz regarding the choice model:

  • Suppose someone could convince you that he had a job for you that1. was illegal, requiring2. that you steal once a month


A verbal quiz regarding the choice model3

A verbal quiz regarding the choice model:

  • Suppose someone could convince you that he had a job for you that1. was illegal, requiring2. that you steal once a month3. that the probability of being caught in any year was 1%


A verbal quiz regarding the choice model4

A verbal quiz regarding the choice model:

  • Suppose someone could convince you that he had a job for you that1. was illegal, requiring2. that you steal once a month3. that the probability of being caught in any year was 1%4. that you could earn $200,000 per year for this work


A verbal quiz regarding the choice model5

A verbal quiz regarding the choice model:

  • Suppose someone could convince you that he had a job foryou that1. was illegal, requiring2. that you steal once a month3. that the probability of being caught in any year was 1%4. that you could earn $200,000 per year for this work

  • Probability never caught in ten years:


A verbal quiz regarding the choice model6

A verbal quiz regarding the choice model:

  • Suppose someone could convince you that he had a job for you that1. was illegal, requiring2. that you steal once a month3. that the probability of being caught in any year was 1%4. that you could earn $200,000 per year for this work

  • Probability never caught in ten years:P(Never Caught10YEARS)= (1-.01)1x (1-.01)2 - - - -(1-.01)10

    = (.99)10 =.9044


A verbal quiz regarding the choice model7

A verbal quiz regarding the choice model:

  • Suppose someone could convince you that he had a job for you that1. was illegal, requiring2. that you steal once a month3. that the probability of being caught in any year was 1%4. that you could earn $200,000 per year for this work

  • Probability never caught in ten years:P(Never Caught10YEARS)= (1-.01)1x (1-.01)2 - - - -(1-.01)10

    = (.99)10 =.9044

    Expected Income(10 Years)= 10 x $100,000 x .9044

    = $1,808,800


What if you are caught

What if you are caught ?

  • The penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)


How many of you would take the job

How many of you would take the job ?


How many of you would take the job1

How many of you would take the job ?

  • Knowing that the penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)

  • Why, yes?


How many of you would take the job2

How many of you would take the job ?

  • The penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)

  • Why, yes?Easy Money.


How many of you would take the job3

How many of you would take the job ?

  • The penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)

  • Why, yes? Easy Money.

  • Why, no?


How many of you would take the job4

How many of you would take the job ?

  • The penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)

  • Why, yes? Easy Money.

  • Why, no?The “What would my mother (girl friend,boy friend) think? question


How many of you would take the job5

How many of you would take the job ?

  • The penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)

  • Why, yes? Easy Money.

  • Why, no? The “What would my mother (girl friend,boy friend) think? question

  • Moral Compliance with the Law


How many of you would take the job6

How many of you would take the job ?

  • The penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)

  • Why, yes? Easy Money.

  • Why, no? The“What would my mother (girl friend,boy friend) think? question

  • Moral Compliance with the Law1. Raised in a religion


How many of you would take the job7

How many of you would take the job ?

  • The penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)

  • Why, yes? Easy Money.

  • Why, no? The “What would my mother (girl friend,boy friend) think? question

  • Moral Compliance with the Law1. Raised in a religion2. Still have a religion


How many of you would take the job8

How many of you would take the job ?

  • The penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)

  • Why, yes? Easy Money.

  • Why, no? The “What would my mother (girl friend,boy friend) think? question

  • Moral Compliance with the Law1. Raised in a religion2. Still have a religion3. Frequency of church attendance


How many of you would take the job9

How many of you would take the job ?

  • The penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)

  • Why, yes? Easy Money.

  • Why, no? The “What would my mother (girl friend,boy friend) think? question

  • Moral Compliance with the Law1. Raised in a religion2. Still have a religion3. Frequency of church attendance

  • Crime Generation:


How many of you would take the job10

How many of you would take the job ?

  • The penalty if caught: 1st Offense:Max: 2 years, State PrisonMin: Suspended Sentence + Probation, 5 years (most likely somewhere in between)

  • Why, yes? Easy Money.

  • Why, no? The“What would my mother (girl friend,boy friend) think? question

  • Moral Compliance with the Law1. Raised in a religion2. Still have a religion3. Frequency of church attendance

  • Crime Generation:OF = g( CR, SV, SE, MC )


Public realization of women s increasing involvement with crime

Public Realization of Women’s Increasing Involvement with Crime

Wall Street

Journal,Thur.

Jan.25,1990


Public realization of women s increasing involvement with crime1

Public Realization of Women’s Increasing Involvement with Crime

Wall Street

Journal,Thur.

Jan.25,1990


Economic opportunity and crime

Between 1979 and 1988, the number of women ar-rested for violent crimes went up 41.5% versus 23.1% for men. The trend is even starker among teen-agers.


Women s increasing participation in crime

Notes, p. 47

Women’s Increasing Participation in Crime

Embezzlement

Robbery

Burglary

Homicide

Crime Rates for Women


Economic opportunity and crime

The Work/Leisure Trade-off for Women

See Notes, p 49

Preferences

$

Income

Available Market Income

8Hr. Std. Work Day

A

B

Income

Shortfall

D

C

b

a

12 hrs.

8hrs.work

Leisure

Work

24 Hours

Time Endowment

Desired Work Hours

at Market Wage


We can add another complication to a job seeker s objectives

We can add another complication to a job seeker’s objectives

The conventional labor market standardizing

on 8 hour jobs creates a situation we call

underemployment

for the individual we have depicted here.

Underemployment may contribute to an individual’s willingness to consider crime as a source of income


Economic opportunity and crime

The Work/Leisure Trade-off

adding a new constraint: Committed Leisure

See Notes, p 49

$

Income

Available Market Income

Binding Constraint

8 hr. Job

Desired Work Day

C

A

24 Hours

Committed Leisure

Time Endowment

Notes pp.49-51


Economic opportunity and crime

Here, the conventional labor market createsa state ofoveremployment

for the individual we have depicted

in our analysis

As Family responsibilites for

single parent women increase,

the constraints narrow further.


The changing labor market status of women

The Changing Labor Market Status of Women


Economic opportunity and crime

The Work/Leisure Trade-off

a more constraining: Committed Leisure

See Notes, p 50

$

Income

Available Market Income

Binding Constraint

8 hr. Job

Desired Work Day

C

A

24 Hours

Committed Leisure

Time Endowment


Economic opportunity and crime

The Work/Leisure Trade-off for Women:

a more constraining Committed Leisure

$

Income

Available Market Income

Binding Constraint

8 hr. Job

Desired Work Day

A

24 Hours

Committed Leisure

Time Endowment

Notes, p.50


Economic opportunity and crime

The appeal of the crime solution

becomes even greater.


Economic opportunity and crime

The Work/Leisure Trade-off for Women:

a more constraining Committed Leisure

$

Income

Available Market Income

Binding Constraint

8 hr. Job

Desired Work Day

A

b

a

24 Hours

Committed Leisure

Time Endowment

Crime may permit optimal hours of work

and a higher monetary return


Economic opportunity and crime

And this could be true

in both cases of

underemployment

and overemployment.


The incentive effects of current welfare rules depend on a full employment economy

The Incentive Effects of Current Welfare Rules depend on a full employment economy


The incentive effects of current welfare rules depend on a full employment economy1

The Incentive Effects of Current Welfare Rules depend on a full employment economy

  • The Demand for Jobs


The incentive effects of current welfare rules depend on a full employment economy2

The Incentive Effects of Current Welfare Rulesdepend on a full employment economy

  • The Demand for Jobs1. Numbers


The incentive effects of current welfare rules depend on a full employment economy3

The Incentive Effects of Current Welfare Rules depend on a full employment economy

  • The Demand for Jobs1. Numbers2. Characteristics


The incentive effects of current welfare rules depend on a full employment economy4

The Incentive Effects of Current Welfare Rules depend on a full employment economy

  • The Demand for Jobs1. Numbers2. CharacteristicsUnderemployment Case:


The incentive effects of current welfare rules depend on a full employment economy5

The Incentive Effects of Current Welfare Rules depend on a full employment economy

  • The Demand for Jobs1. Numbers

    2. CharacteristicsUnderemployment Case:Longer Hours (Overtime work)


The incentive effects of current welfare rules depend on a full employment economy6

The Incentive Effects of Current Welfare Rules depend on a full employment economy

  • The Demand for Jobs1. Numbers2. CharacteristicsUnderemployment Case:Longer Hours (Overtime work)Part time jobs


The incentive effects of current welfare rules

The Incentive Effects of Current Welfare Rules:

  • The Demand for Jobs1. Numbers2. CharacteristicsUnderemployment Case:Longer Hours (Overtime work)Part time jobsOveremployment Case


The incentive effects of current welfare rules1

The Incentive Effects of Current Welfare Rules:

  • The Demand for Jobs1. Numbers2. CharacteristicsUnderemployment Case:Longer Hours (Overtime work)Part time jobsOveremployment CasePart time Jobs


The incentive effects of current welfare rules2

The Incentive Effects of Current Welfare Rules:

  • The Demand for Jobs1. Numbers2. CharacteristicsUnderemployment Case:Longer Hours (Overtime work)Part time jobsOveremployment CasePart time JobsFlextimeWorking out of one’s home


The incentive effects of current welfare rules3

The Incentive Effects of Current Welfare Rules:

  • The Demand for Jobs1. Numbers2. CharacteristicsUnderemployment Case:Longer Hours (Overtime work)Part time jobsOveremployment CasePart time JobsFlextimeWorking out of one’s home

  • The Alternatives


The incentive effects of current welfare rules depend on a full employment economy7

The Incentive Effects of Current Welfare Rules depend on a full employment economy

  • The Demand for Jobs1. Numbers2. CharacteristicsUnderemployment Case:Longer Hours (Overtime work)Part time jobsOveremployment CasePart time JobsFlextimeWorking out of one’s home

  • The Alternatives1. Job Creation


The incentive effects of current welfare rules depend on a full employment economy8

The Incentive Effects of Current Welfare Rules depend on a full employment economy

  • The Demand for Jobs1. Numbers2. CharacteristicsUnderemployment Case:Longer Hours (Overtime work)Part time jobsOveremployment CasePart time JobsFlextimeWorking out of one’s home

  • The Alternatives1. Job CreationEconomic Growth


Effects of recent change in welfare rules depend on the state of the economy

Effects of Recent Change in Welfare Rules Depend on the State of the Economy

  • The Demand for Jobs1. Numbers2. CharacteristicsUnderemployment Case:Longer Hours (Overtime work)Part time jobsOveremployment CasePart time JobsFlextimeWorking out of one’s home

  • The Alternatives1. Job CreationEconomic GrowthIncentives


Economic opportunity and crime

US Civilian Labor Force - Thousands

US Labor Force Participation Rate

All Employees, Thousands

Unemployment Levels

What is happening with U S Labor

Not in the Labor Force, Thousands


The economy was doing well but compared to what

The economy was doing well,but compared to what?

Employment Levels 1991 to 2001

2002-2006


The incentive effects of current welfare rules depend on a full employment economy9

The Incentive Effects of Current Welfare Rules depend on a full employment economy

  • The Demand for Jobs1. Numbers2. CharacteristicsUnderemployment Case:Longer Hours (Overtime work)Part time jobsOveremployment CasePart time JobsFlextimeWorking out of one’s home

  • The Alternatives1. Job CreationEconomic GrowthIncentives2. Crime ??


Professor phillips

Next Time

Professor Phillips

Deterrence and the

Death Penalty

Notes, Phillips 3, p51


Points to remember

Points to remember

  • Who are the most crime prone elements of society? Why?

  • How do they fit into a model of crime generation and control? Can we explain the why?

  • Why do we think blacks responded to crime in a different pattern from whites?

  • What has been happening with respect to women and crime? Again, why?

  • Why didn’t crime go up when the country changed the welfare rules?


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