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ECOS3997 Interdisciplinary Impact in Economics
创建日期：2024-06-14 18:07:30
所属分类：经济Economics
标签： ECOS3997
Interdisciplinary Impact in Economics

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ECOS3997

Interdisciplinary Impact in Economics
Stream 2: Economics of Crime
Lecture 7: Education, poverty and crime
Dr. Ranae Jabri
University of Sydney
Semester 1, 2024
1 / 49
Course Outline
1. Introduction and economic model of crime
2. Policing
3. Incarceration
4. Education, poverty and crime
5. Spillovers
6. Local criminal justice policy
7. New technologies used in criminal justice policy
2 / 49
Recap of last class:
• The deterrent effect of penalties on crime
• Drago et al. (2009)
• Effects of incarceration on post-release outcomes
• Judge leniency IV research design: Kling (2006); Dobbie et al. (2018)
3 / 49
Outline
3. Incarceration
A. Effects of incarceration on post-release outcomes
4. Education, poverty, and crime
A. Effects of education on crime
B. Heller (2014)
4 / 49
Outline
3. Incarceration
A. Effects of incarceration on post-release outcomes
4. Education, poverty, and crime
A. Effects of education on crime
B. Heller (2014)
5 / 49
How can incarceration affect behaviour post-release?
• Potential mechanisms:
• Effects on criminal capital, employment capital, or social capital
• Scarring/Stigma Effects of Incarceration
• Schools of crime or criminogenic influence
• Recidivism
• We talked about the judge leniency IV research design
• Examples of studies: Kling (2006); Dobbie et al. (2018)
6 / 49
The effect of post-conviction incarceration on recidivism (Loeffler and
Nagin, 2022)
• Most studies find little effect of post-conviction imprisonment on recidivism
• Mixed evidence: “a smaller number of studies do, however, find significant effects,
both positive and negative”
• Studies where recidivism declines: incarceration settings emphasizing rehabilitative
programming
• Studies where recidivism increases: incarceration settings do not emphasize
rehabilitative programming
7 / 49
The effect of pretrial incarceration on recidivism (Loeffler and Nagin,
2022)
• Most studies find a negative effect of pretrial detention on recidivism though some
studies do find a null effect
• Defendants can be detained pretrial in temporary manner (they may or may not be
released pretrial) → disruptive nature
• 500,000 detained pretrial per day in US
• 250,000 detained postconviction per day in US
• Pretrial jail stays are shorter with less certainty and provide less rehabilitative
programming and access to mental health and substance abuse resources
8 / 49
What are the effects of incarceration conditions on post-release
outcomes?
• Incarceration could have effects on ‘criminal capital’ (crime skills)
• Schools of crime: Prisons can have a criminogenic influence – incarceration can affect
the criminal propensity of individuals through social networks
• What influence do peers serving time in the same correctional facility have
on each other’s subsequent criminal behaviour?
• Required reading: Bayer, P., Hjalmarsson, R., and Pozen, D. (2009). Building
criminal capital behind bars: Peer effects in juvenile corrections. The Quarterly Journal
of Economics, 124(1):105–147.
9 / 49
What are the effects of incarceration conditions on post-release
outcomes?
• Incarceration could have effects on ‘criminal capital’ (crime skills)
• Schools of crime: Prisons can have a criminogenic influence – incarceration can affect
the criminal propensity of individuals through social networks
• What influence do peers serving time in the same correctional facility have
on each other’s subsequent criminal behaviour?
• Required reading: Bayer, P., Hjalmarsson, R., and Pozen, D. (2009). Building
criminal capital behind bars: Peer effects in juvenile corrections. The Quarterly Journal
of Economics, 124(1):105–147.
9 / 49
Bayer et al. (2009)
“Danbury wasn’t a prison. It was a crime school. I went in with a bachelor of marijuana
and came out with a doctorate of cocaine.” George Jung describing his introduction to the
cocaine industry in Blow
10 / 49
Bayer et al. (2009)
• Research question: Is the post-release criminal behaviour of a juvenile offender
affected by the characteristics of individuals with whom they are incarcerated?
• Empirical challenge: People do not randomly match with their peers
• Research design using facility and facility-by-prior offense fixed effects
• Findings: Evidence that peer effects exist juvenile correctional facilities
11 / 49
Bayer et al. (2009)
• Research question: Is the post-release criminal behaviour of a juvenile offender
affected by the characteristics of individuals with whom they are incarcerated?
• Empirical challenge: People do not randomly match with their peers
• Research design using facility and facility-by-prior offense fixed effects
• Findings: Evidence that peer effects exist juvenile correctional facilities
11 / 49
Bayer et al. (2009)
• Research question: Is the post-release criminal behaviour of a juvenile offender
affected by the characteristics of individuals with whom they are incarcerated?
• Empirical challenge: People do not randomly match with their peers
• Research design using facility and facility-by-prior offense fixed effects
• Findings: Evidence that peer effects exist juvenile correctional facilities
11 / 49
Bayer et al. (2009)
• Research question: Is the post-release criminal behaviour of a juvenile offender
affected by the characteristics of individuals with whom they are incarcerated?
• Empirical challenge: People do not randomly match with their peers
• Research design using facility and facility-by-prior offense fixed effects
• Findings: Evidence that peer effects exist juvenile correctional facilities
11 / 49
Motivation
• No formal institutions for criminal sector of the economy
• Social and peer networks could play an extensive role in the proliferation of criminal
activity
• These networks could develop through peer effects while offenders are incarcerated
• Potential cost of incarceration: peer effects in incarceration could increase the
proliferation of criminal networks
12 / 49
Context
• 169 juvenile correctional facilities in Florida, US
• Peer group changes over time as individual cycles out and peers cycle in and out
• Individual’s exposure to peers depends on individuals sentence overlap with peers
• Peer effects may depend on your own criminal experience and the criminal experience
of peers
• Need to allow for crime-specific peer effects that can vary with own criminal history
experience
13 / 49
Data
• Sample: 8000 inmates over 2 year period in Florida
• Individual-level data on demographic and criminal history, facility assignments
• Individual-level outcomes: arrest and adjudication outcomes for 1 year after release
• Peer data on demographic and criminal history
14 / 49
Research Design
• Empirical challenge: Juveniles are not randomly assigned to facilities
• Facility and facility-by-prior-offense fixed effects → using the within-facility over time
variation that juveniles overlap in the SAME facility
• Research design accounts for nonrandom assignment of juveniles to facilities “as long
as the date at which a given individual is assigned to a facility within the two-year
sample period is random with respect to the peers in the facility at the time”
15 / 49
Research Design
• Empirical challenge: Juveniles are not randomly assigned to facilities
• Facility and facility-by-prior-offense fixed effects → using the within-facility over time
variation that juveniles overlap in the SAME facility
• Research design accounts for nonrandom assignment of juveniles to facilities “as long
as the date at which a given individual is assigned to a facility within the two-year
sample period is random with respect to the peers in the facility at the time”
15 / 49
Empirical Strategy
Rhijt =β0(Offensehijt ∗ Peer offensehijt)
β1(No Offensehijt ∗ Peer offensehijt)
+ Pijtα+Xijtγ + λj +Offensehijt ∗ µj + ηt + εhijt
• Rhijt: Indicator variable for whether individual i in facility j released in period t
recidivates with offense type h
• Peer offensehijt: individual’s exposure to peers with a history of offense type h
• Offensehijt: Indicator variable for whether individual i has a history of offense type h
• No Offensehijt: Indicator variable for whether individual i has no history of offense
type h
16 / 49
Empirical Strategy
Rhijt =β0(Offensehijt ∗ Peer offensehijt)+
β1(No Offensehijt ∗ Peer offensehijt)
+ Pijtα+Xijtγ + λj +Offensehijt ∗ µj + ηt + εhijt
• Pijt: vector of peer characteristics
• Xijt: vector of individual demographic and criminal history
• λj : facility fixed effects
• Offensehijt ∗ µj : facility-by-prior-offense fixed effects
17 / 49
Empirical Strategy
• Crime-specific peer effects allowed to vary with an individual’s own criminal
experience
• β0: crime-specific peer effect for those with a history of having committed the relevant
offense
• β1: crime-specific peer effect for those without a history of having committed the
relevant offense
• Table 2: evidence that juveniles specialize
18 / 49
19 / 49
Tests of the central identifying assumption
• Is the date at which a given individual is assigned to “a facility within the two-year
sample period is random with respect to the peers in the facility at that time”?
• “Balance check”: test that within-facility variation in peer characteristics is orthogonal
to individual-level observables
• We saw a similar kind of check last week in Drago et al. (2009)
• Check that estimated peer effects do not differ after accounting for trends in criminal
activity
• Check that estimated peer effects can’t be explained by peers who already committed
crimes together being assigned together
20 / 49
21 / 49
Discussion
• Peer effects have a reinforcing nature: peers can increase crime-specific knowledge
• What implications do these findings have for how to group juveniles in correction
facilities?
• What implications do these findings have for policies that incarcerate more juveniles?
• Finding: “Exposure to peers with a history of committing a particular crime increases
the probability that an individual who has already committed the same type of crime
recidivates with that crime”
• Crime reduction can have dynamics effects through reducing criminal histories of
potential peers who can have crime-specific peer effects
22 / 49
Discussion
• Peer effects have a reinforcing nature: peers can increase crime-specific knowledge
• What implications do these findings have for how to group juveniles in correction
facilities?
• What implications do these findings have for policies that incarcerate more juveniles?
• Finding: “Exposure to peers with a history of committing a particular crime increases
the probability that an individual who has already committed the same type of crime
recidivates with that crime”
• Crime reduction can have dynamics effects through reducing criminal histories of
potential peers who can have crime-specific peer effects
22 / 49
Outline
3. Incarceration
A. Effects of incarceration on post-release outcomes
4. Education, poverty, and crime
A. Effects of education on crime
B. Heller (2014)
23 / 49
Outline
3. Incarceration
A. Effects of incarceration on post-release outcomes
4. Education, poverty, and crime
A. Effects of education on crime
B. Heller (2014)
24 / 49
How does more schooling affect the decision to commit crime?
The individual chooses to commit a crime if and only if:
Expected utility of crime > Expected utility of abstention
pU(Y − f) + (1− p)U(Y ) > Unc
• Potential offenders have more education and better labor market prospects
• Higher Unc → crime is expected to decline
25 / 49
How does more schooling affect the decision to commit crime?
The individual chooses to commit a crime if and only if:
Expected utility of crime > Expected utility of abstention
pU(Y − f) + (1− p)U(Y ) > Unc
• Potential offenders have more education and better labor market prospects
• Higher Unc → crime is expected to decline
25 / 49
How could education affect crime?
• Income effects?
• Time availability?
• Time preferences?
• Education → patience → value future earnings more
• Risk preferences?
• Education → risk aversion → give more weight to potential sanction
• Deterrence vs. incapacitation?
26 / 49
How could education affect crime?
• Income effects?
• Time availability?
• Time preferences?
• Education → patience → value future earnings more
• Risk preferences?
• Education → risk aversion → give more weight to potential sanction
• Deterrence vs. incapacitation?
26 / 49
How could education affect crime?
• Income effects?
• Time availability?
• Time preferences?
• Education → patience → value future earnings more
• Risk preferences?
• Education → risk aversion → give more weight to potential sanction
• Deterrence vs. incapacitation?
26 / 49
How could education affect crime?
• Income effects?
• Time availability?
• Time preferences?
• Education → patience → value future earnings more
• Risk preferences?
• Education → risk aversion → give more weight to potential sanction
• Deterrence vs. incapacitation?
26 / 49
How could education affect crime?
• Income effects?
• Time availability?
• Time preferences?
• Education → patience → value future earnings more
• Risk preferences?
• Education → risk aversion → give more weight to potential sanction
• Deterrence vs. incapacitation?
26 / 49
How could education affect crime?
• Income effects?
• Time availability?
• Time preferences?
• Education → patience → value future earnings more
• Risk preferences?
• Education → risk aversion → give more weight to potential sanction
• Deterrence vs. incapacitation?
26 / 49
How can we estimate the effect of increased schooling on crime?
• Endogeneity issue: unobserved characteristics that determine schooling decisions
could be correlated with the unobserved determinants of criminal behavior
• Example: people with high return from crime drop out from school and commit crime
→ education decreases crime?
• Research design: exogenous or quasi-exogenous variation in schooling
27 / 49
Lochner and Moretti (2004)
• Research question: What is the effect of education on crime?
• Natural experiment: in half of U.S. states, legal to drop out of school at age 16, but in
1960-80 some states increased their minimum age to 17 or 18.
• Findings: Birth cohorts that were forced to stay in school longer had lower arrest and
incarcerations rates as adults than their predecessors.
• 1 extra year of high school reduced arrest rates by 11%
28 / 49
Machin et al. (2011)
• Research question: What is the effect of education on crime?
• Natural experiment: Compulsory School Leaving Age reform affected 15 year old
youth in England and Wales in the early 1970s
• Findings: Birth cohorts that were affected by the laws had a large drop in property
crime; results are not clear for violent crime.
29 / 49
30 / 49
31 / 49
32 / 49
Outline
3. Incarceration
A. Effects of incarceration on post-release outcomes
4. Education, poverty, and crime
A. Effects of education on crime
B. Heller (2014)
33 / 49
Heller (2014)
• Research question: What is the effect of summer jobs on crime for disadvantaged
youth?
• Randomized controlled trial among 1634 disadvantaged youth in Chicago
• Findings: Summer jobs reduce violence by 63% over 16 months
34 / 49
What is the motivation for this paper?
• Violent crime public health crisis: 150 people killed through acts of violence every day
in the US
• Youth twice more likely than adults to be victims/perpetrators of violence
• Disadvantaged minority youth: violent crime arrests rates for Black youth is 5 times
as high as for white youth
35 / 49
What is the motivation for this paper?
• Violent crime public health crisis: 150 people killed through acts of violence every day
in the US
• Youth twice more likely than adults to be victims/perpetrators of violence
• Disadvantaged minority youth: violent crime arrests rates for Black youth is 5 times
as high as for white youth
35 / 49
Large-scale RCT
• Treatment group: One Summer Plus (OSP) public summer jobs program in Chicago
• Treatment group 1:8 weeks of part time summer mininum wage employment (25
hours)
• Non-profit and government sectors; job mentors
• Treatment group 2: Social-emotional learning (SEL) on CBT principles to help
manage thoughts and emotions, and affect behaviour, to help with job (15 hours + 10
hours of SEL)
• Control group: Excluded from the program
• Aim to prevent crime rather than manage after crime onset
36 / 49
Data
• Sample: 1634 8-12th grade from 13 high-violence CPD schools
• Admin data tracking program participation
• Student-level Chicago Public Schools data on academic outcomes
• Neighborhood-level data from American Community Survey
37 / 49
How can summer jobs affect crime?
• Income effects?
• Incapacitation effects?
38 / 49
How can summer jobs affect crime?
• Income effects?
• Incapacitation effects?
38 / 49
Mean preprogram characteristics for treatment and control groups
39 / 49
Balance check?
Where have we seen this kind of balance check before?
• We saw this kind of balance check in Drago et al. (2009)
• Why does the author do a balance check here?
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MOEC0021 STA 106 ENGG 1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A 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COMP2013 IB9X60 INVP001 EMATM0051 COMP220 BLAW1002 E20 TCP8001 ECON61001 EART40005 ECONM1022 MATH 365 MATH 367 ELEC6218 COMP 5812M EDUC 5061M ELEC ENG 1101 equation MATH6174 ST334 C4 EC9570 A33648 EBUS603 ECON47815 stata WFMS0001 PEM102 INF6060 ionically ELECTRICAL MATH 375 MMW 12 MKTG860 ECON60401 ALY6010 SOST20131 Introduction COM3524 MME2 GGR305 JNB 538 EECS101 COMM5030 IEOR E4601 2B CSC336 EN2315 LAW 432 CSC263 MATH2001 OLET1143 CSCB63 SIT772 COMM1170 STAT 441 MS930 INFT3050 GLBH0030 Stat 120B MAST10007 MGEC61 Machine GGR 252H1S ECON7030 Financial Marketing MGMT30019 ECON5120 SDSC 8009 CSC165H1S DSCI 551 3081W ACM41000 ECA 5304 MATH 1064 ECSE444 DATA 604 COMP7105 MIE1615 ECON4004 ENV200H1S EC481 MKT 306 EC1B1 MATH08051 ALY6140 CS260C CSE30 MSIN0226 CS4103 CSC3064 AM16 COMP11212 CSE4101 PSTAT 174 Math 380W CNT 5106C STAT 310 FIN2028 CS5014 STAT 425 COMP 4102A ELEC2140 MANF9544 QRM 9 QRM 8 ECON 457 COMPSCI 4091 MATH 523 DNSC-4211 PEAS 6000 MSIN0180 COMP2119 A2A HT 2022 IB93F0 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ACCOUNTING BUSS1040 CHEM 181 MAT136H1 GY 6183 COMP3170 AGRI90089 PHYSICS 1002 ECON10003 IEOR E4004 ACS61012 MATH 40550 MKTG2113 TELE4653 ENSC1004 ECE 232E MK726 MTRX2700 SHEET 3 CSCA08 COMP30027 Math 2XX3 statistic MMAN3200 BISM7213 ECMM109 ECON 2022 FNCE 20005 GR5067 CSCB09 ME 3017 CS 5100 PHYS 2903 COMS 4771 COMP222 COMP 1046 CSC148H1 ISYS2038 FINS2615 OT5206 COMP2048 A6 MECH5770M MA826/20 CMPT 726 STA457 INFS6071 INFS588 integral ECON 216 IRDR 0017 MA323 PA 15213 PSYC2001 ENV222 Statistics ACCT5930 ACCT12 LAND2121 ME 5405 COMM1180 TELE3113 A7 ECE 568 ACCT2019 INFS1200 ENGG1340 CS 1400 ASST3 FINM7409 SWEN30006 INFO2222 FIN20150 SOSS1000 CSSE7231 FINS5513 COMS3200 CECN 702 ECON4060H MN3515 HW2 PSYA02H3 ECON 2112 COMP90051 CS 1652 MA30059 AF1605 MKTG7501 ECO-6003B COM4521 CTM ECON3350 COMP 3804 ELEC9762 BISM 7255 ST22 MATH20014 MNE3122 COMP343 MATH5165 ELE7029 ENGR30002 SEEM3500 ECON7350 RISK5002 FINM7405 COMP90059 MOS 3320B STAT 431 BISM7221 MATH3014 MTH783P EBA 35302 ACS133 BUS2206 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FN1024 MATH0094 MANG 6554 ECOS3003 ELEC6252 C2511C PHY328 EC1060 ECON32202 COMP4002-E1 MATH3063 EFIMM0124 QBUS2310 ECON4411 FUNDAMENTALS ACCT20001 18YX RPM COMP 2711 QBUS6600 BUSS5221 ST3189 FIT1047 MAT344 EGB375 MATH60013 MATH96011 COMP3557 MAST20029 ECM159 EAE1011 ENSCEN 105 SECTION A STA 141C SOSE 2022 PAM006 COMP0048 M40007 ISOM2500 CMPE 142 A06472 MCC150 ACST 8083 GEOG6087 ECON920 FINM7008 ENVENG 4110 COMPSCI 361 ENGRCEE 21 PHYS 1112 ACF2100 ECMM108 COMPS267F MAT00050M MAST30025 CSIT970 MSCI 224 INT202 PUBL0054 MSDM5004 BMAN 21020 BMAN21020 MGMT1002 MATH11150 LAWS7023 ACTL30002 CIVL3340 MATH1002 ECON 8069 COMPSCI 351 IBUS7302 STAT4528 CHEM1101 STAT3925 BUSN 7008 Comp 3120 ECOS2040 SWEN90010 ENGN6528 ECM158 ECON20022 COMP6452 Calculation CITS1401 S1889112 BUS 351 ACTL30008 FIT2091 ECON6002 IBUS6020 PHI 001 ECON30290 MATH7501 ECON10004 MFIN7017 ISYS90043 LAWS7012 ECON30025 COMP30023 COMM1190 ECOM20001 GSBS6009 STAT 337 EMET8002 ECOM90001 ECOM30001 FINC 2012 BUSINESS ENGCV512 ECO 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