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    2 Chapter 31: Crime

    Furhermore, according o he U.S. Bureau o Jusice, in 2006, [a] he naional level, crime raes remain sabilized a he lowes overall levels experiencedsince 1973.

    Crime is a phenomenon o considerable social concern and grea academicineres or i aecs all o us in one way or anoher. I is obviously relevan ohose who all vicim o crimes and hose who perperae hem. More subly, ialso aecs us as poenial vicims and as axpayers who mus oo he bill orever-burgeoning expendiures on law enorcemen, prisons, and he legal sysem

    broadly deined.In his chaper, we show how economic heory sheds ligh on he deerminan

    o criminal aciviy.5A irs glance, i migh appear obvious ha his approachsimply involves ormulaing and esing hypoheses ha relae economic condiions (such as, he average wage, and boh he unemploymen and povery raes)o he level o criminal aciviy. While here is some ruh o hiseconomiss doexamine he eecs o labor-marke condiions on crimei is only par o hesory.

    Mos signiican, economiss view crime isel as an economic ac. In paricular, building on he seminal work o Becker (1968) and he pioneering works oEhrlich (1973, 1981), and Block and Heineke (1975), economiss model criminal aciviy hrough he concepual lens o raional (yes, raional) choice heoryFor example, Becker (1968) advances he view ha

    [A] useul heory o criminal behavior can dispense wih heories o anomie,psychological inadequacies, or inheriance o special rais and simply exendhe economiss usual analysis o choice.6

    hus he highly educaed whie collar embezzler is deemed o be as raiona

    (i.e., calculaing) as he mugger, he drunk driver, or even he proverbial madax-manwho was las seen chasing Dougal down he sree. he power o heapproach is easy o see. All criminal aciviy is uniied under one umbrella hadiers in degree raher han in kind, and is unied by a sric adherence o he principles o raionaliy (i.e., he maximizaion o uiliy subjec o consrains).

    he economic approach o crime is grounded on he ollowing riumvirae omicroeconomic principles: raionaliy, equilibrium, and eiciency. he irs principle assers ha crime is a raional ac ha responds o incenives, wheher hey

    be provided by he marke (hrough, or example, legiimae earnings opporuniies) or via he criminal jusice sysem (hrough sancions, such as ines, incarceraion, and even orure or capial punishmen).

    According o he second principle, crime is no viewed in isolaion rom ohepars o he economic sysem bu is an inegral par o i. hus povery does nocause crime; insead, povery and crime are joinly deermined as equilibriumoucomes ha depend on deeper economic variables. he imporance o undersanding crime in a general-equilibrium conex ha accouns or all relevanineracions should no be underesimaed. Policy nosrums ha purpor o solv

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    31.1: The Evidence 3

    he crime problem are usually ineecual precisely because hey ignore his crii-cal aspec o economic realiy. he hird principle o economic eiciency permishe (relaively) sraighorward assessmen o he eeciveness o myriad alerna-ive anicrime policies.

    In Secion 31.1, we begin by oulining he key elemens o he sylized evidenceas i perains o he exen o criminal aciviy in he Unied Saes. he secionsha ollow describe he microeconomic approach o crime jus oulined.

    31.1 The EvidenceDaa on criminal aciviy are available rom wo primary sources: he FBIs Uni-orm Crime Reporing Program (UCR) and he Naional Crime VicimizaionSurvey (NCVS). he UCR is compiled by he FBI. I comprises monhly andannual repors gahered naionwide by police, sheris, and sae police on crimesha are commied in heir respecive jurisdicions. he NCVS is colleced annu-ally by he Bureau o Jusice Saisics (BJS).7In shor,

    [D]aa are obained rom a naionally represenaive sample o roughly 45,000households comprising more han 94,000 persons on he requency, characer-isics and consequences o criminal vicimizaion in he Unied Saes.8

    he wo daa ses oen dier markedly in he exen o criminal aciviy hey re-por. he reason is ha no all crimes are repored o he police, and he ones haare repored vary according o he ype o crime:

    [P]olice reporing raes (percen o vicimizaions) varied by ype o crime.

    In 1994, or insance, 32 percen o he rapes/sexual assauls were repored;55 percen o he robberies; 40 percen o assauls; 33 percen o personalhes; 51 percen o he household burglaries; and 78 percen o moor vehiclehes.9

    Dieren caegories o crimes are oen grouped ogeher. hus PropertyCrimes and Robbery reer o robbery, burglary, larceny-he, moor vehiclehe. Violent Crimesreer o criminal homicide, rape, robbery, and aggravaedassaul. An imporan, and apparenly growing, caegory o criminal aciviy, allsunder he rubric owhite collar crime,which, according o he U.S. Deparmeno Jusice, is:10

    [N]onviolen crime or inancial gain commied by means o decepion bypersons whose occupaional saus is enrepreneurial, proessional or semi-proessional and uilizing heir special occupaional skills and opporuniies;also, nonviolen crime or inancial gain uilizing decepion and commied byanyone having special echnical and proessional knowledge o business andgovernmen, irrespecive o he persons occupaion.11

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    4 Chapter 31: Crime

    Criminal Activity: Recent TrendsCriminal aciviy is characerized by several sriking empirical eaures. I is sub

    jec o considerable emporal variaion, i is geographically concenraed, and iexhibis wide dispersion across communiies ha possess osensibly idenicaeconomic characerisics. Less aluen ciies are disproporionaely alicedin

    paricular, hose characerized by chronic povery, a poorly educaed workorceand limied access o employmen opporuniies.

    he Unied Saes winessed a precipious increase in he exen o criminaaciviy ha began in he mid-1970s and ha peaked in he early 1990s. his waimmediaely ollowed by an equally impressive meeoric decline in criminal aciviy ha has coninued unabaed or almos 15 years. Regarding geographic concenraion, Freeman, Grogger and Sonselie (1996) noe ha in 1990 he mediannumber o repored sree robberies in Los Angeles equaled 4 per 1,000 residens

    Ye, 10% o neighborhoods had crime raes our imes greaer han he medianIn a similar vein, Glaeser, Sacerdoe, and Scheinkman (1996) observe, Ridge

    wood village repored 0.008 serious crimes per capia, whereas nearby AlaniCiy repored 0.34.A similar paern can be seen by comparing crime raes in large meropolian

    and rural areas. According o he 2007 U.S. Bureau o he Census (able 300)he rae o violen crime was 510 in large meropolian areas bu only 207 in ruraones.12 he corresponding igures or propery crimes were 3,599 and 1,700respecively.

    A more complee picure o criminal aciviy can be garnered by looking apaerns over a longer ime span. Figure 31.1adepics he homicide rae in he

    Source: Panel (a) U.S. Bureau o Jusice Saisics (BJS). Available a hp://bjs.ojp.usdoj.gov/conen/glance/hmr.cm. Panel (b) FederalBureau o Invesigaion (FBI). Available a www.bi.gov/page2/jan08/ucr_saisics010708.hml. (Boh URLs accessed May 5, 2010.)

    0.2

    0.4

    0.6

    0.8

    1.0

    1.2

    2005

    1900 19 16 1932 1948 1964 1980 19 96 2012

    (a) Homicide Rate (per 10,000 persons)

    2006

    10

    20

    30

    40

    50

    60

    1960 1970 1980 1990 2000 2010

    (b) Property Crime Rate (per 1,000 persons)

    FIGURE 31.1 The Homicide and Property Crime Rates

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    31.1: The Evidence

    Unied Saes over he pas 100 years.13Noice he peaks and roughs in he daa.he rapid decline in he homicide rae ha began in he early 1990s is readilyapparenas is he sligh upick ha began in 2003. Panel (b) depics he U.S.propery crime rae over he period 1960 o 2006. Once again, noice he inexo-rable increase in he level o criminal aciviy unil he lae 1980s, and is seadydecline since hen.

    he Bureau o Jusice Saisics (2006) NCVS provides a useul snapsho ocriminal aciviy in he Unied Saes during 2005:

    In 2005, U.S. residens age 12 or older experienced an esimaed 23 millionviolen and propery vicimizaions, according o he Naional Crime Vicim-izaion Survey (NCVS). hese criminal vicimizaions included an esimaed18 million propery crimes (burglary, moor vehicle he, and he), 5.2 mil-lion violen crimes (rape or sexual assaul, robbery, aggravaed assaul, andsimple assaul), and 227,000 personal hes (pocke picking and purse snach-ing). . . . Beween 1993 . . . and 2005, he violen crime rae decreased 58%,rom 50 o 21 vicimizaions per 1,000 persons age 12 or older. Propery crime

    declined 52%, rom 319 o 154 per 1,000 households.14

    Arican Americans and Hispanics are disproporionaely represened as bohhe perperaors and he vicims o crime. According o he U.S. Bureau o he Cen-sus, Arican Americans represen 47% o all murder vicims,despie he ac hey make up only 12% o he populaion.15

    A he dawn o he new millennium, he Black homicide raewas an appalling 20.5 per 100,000 persons, compared o arae o 3.3 per 100,000 or Whies. he only solace ha can

    be drawn rom hese igures is ha, or Blacks, hey represen

    a signiican improvemen in heir relaive circumsances.Only a decade or so earlier, in 1991, he homicide rae hadbeen wice his number, a 40 per 100,000 persons. hisrendered murder he leading cause o deah among young

    Arican American men.So much or he number o crimes commied, Anderson

    (1999) repors ha (in 1997) he oal dollar value o trans-fers rom vicims o criminals amouned o $603 billion.16able 31.1 breaks down he ransers resuling rom criminalaciviies ino several dieren caegories. Despie he aen-ion ha is placed in he press on crimes such as robbery,

    burglary, and personal he, i is easy o see ha he lionsshare o dollars misappropriaed hrough criminal aciviyresul rom whie collar crimes. hus he various caegorieso raud accouned or some $563 billion annually or 93%o all ransers. Some daa are also available on he average

    value o he losses suered by he vicims o crime. hus in

    TABLE 31.1

    Transfers in Millions of Dollars

    Transfers (1997) $Billions

    Occupational fraud 204

    Unpaid taxes 123

    Health insurance fraud 109

    Financial insurance fraud 53

    Mail fraud 36

    Property/casualty insurance fraud 21

    Telemarketing fraud 17

    Business burglary 13

    Motor vehicle theft 9

    Shoplifting 7

    Household burglary 4.5

    Personal theft 3.9Household larceny 2

    Coupon fraud 0.9

    Robbery 0.8

    Total (approximately) 604

    Source: Anderson (1999), able 6.

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    6 Chapter 31: Crime

    2004 he average loss rom robbery was $1283 (i wa$4153 or bank robberies); $1726 or burglary; $733 olarceny, and $6019 or moor vehicle he.17

    Criminals end o be preponderanly young, maleand undereducaed. able 31.2 describes sel-reporedcriminal paricipaion by age. I is drawn rom he 1980Naional Longiudinal Survey o Youh (NLSY). Noicehe sudden burs o criminal aciviy around he age o 17From he hird column, i is clear only a small percenageo criminals obain mos o heir incomes rom crime

    According o Freeman (1996), his . . . indicaes haor many young men, illegal work may be emporary oransiional work ha supplemens diicul low-wage ooherwise unsaisacory work.18

    he vas majoriy o boh violen and propery crimeare carried ou by men. One sympom o his is he srik

    ing dierence in he relaive numbers o men and women who are currenly incarceraed. According o he U.S. Census Bureau, 1,337,668 men were incarceraedin sae and ederal prisons in 2004. he corresponding igure or emales was leshan one enh o his igure, a only 96,125.

    urning o educaional levels, Lawrence (1995) repors ha (in 1982), In hegeneral populaion, 85% o males 2029 years o age have inished high school; only40% o prisoners have done so. . . . Six percen o prisoners have had no schoolinga all. In ac, several sudiesincluding auchen, Wie, and Griesinger (1994)Lochner (2004); and Lochner and Morei (2004)also indicae ha compleing high school signiicanly reduces criminal procliviies.19hese are he broad

    paerns o crime. Nex, les urn o he issue o law enorcemen.

    Law EnforcementIn 2006, a oal o 836,787 police oicers were employed in he business o lawenorcemen.20heir combined eors resuled in a oal o 10,369,000 arres(excluding arress or raic oenses). Almos 80% o hose arresed were men.2

    In he same year, a oal o 7,211,400 persons were eiher in prison, in jail, on probaion, or on parole.22

    he increase in he number o incarceraed persons (in jail or ederal/saeprison) over he pas 20 years or so is ruly saggering. In 1980 he number was(approximaely) hal a million. oday i is in excess o 2.1 million, which represens a ourold increase over he period. Figure 31.2adepics he numbers opersons under correcional supervision in he Unied Saes. Needless o say, lawenorcemen is no cheap. Panel (b) depics he explosive growh in oal expendiures (consan 2005 dollars) on enorcemen eors (broadly circumscribedover he pas 25 years.

    TABLE 31.2

    Criminal Participation by Age

    Any Income More thanAge from Crime (%) 50%

    15 21.7 4.2

    16 24.4 4.1

    17 29.5 4.5

    18 23.3 2.7

    19 19.6 1.8

    20 19.2 2.2

    21 17.6 2.1

    22 17.1 1.1

    Source: Lochner (2004), able 2.

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    31.1: The Evidence

    Currenly, he Unied Saes spends over $200 billion on policing, correcions,and he judiciary. he coss o enorcemen and running he prison sysem areaking a severe oll on many saes inances. Consider he ollowing accoun givenin heNew York imes(April 1995):

    In 1995 Caliornia spen more on prisons han on higher educaion. Spendingon prisons rose rom 2 percen o he sae budge in 1980 o 9.9% in 1995

    whereas spending on higher educaion shrunk rom 12.6% in 1980 o 9.5 per-cen. he number o inmaes increased rom 23,500 o 126,100 over he periodand 17 new prisons were buil. his was beore he saes hree srikes and

    youre ou law.23

    Expendiures on privae enorcemen eors are also exremely large. For in-sance, Anderson (1999) repors ha, Privae expendiure on guards amouns omore han $18 billion annually. Securiy guard agencies employ 55 percen o he867,000 guards in he U.S.; he remainder are employed in house.24

    Households also incur a variey o coss in heir privae aemps o deer crime.Examples include insalling burglar alarms, living in a saer neighborhood (andpaying a premium on housing), aking a cab insead o walking, and, yes, imespen looking or keys. Perhaps he reader can empahize:

    Based on over 150 observaions o individuals locking and unlocking cars, o-ices, buildings, mail boxes . . . , I esimae ha each adul spends wo minues

    * oal expendiures = policing + correcions + judiciary.Source: U.S. Deparmen o Jusice, hp://bjs.ojp.usdoj.gov/(accessed may 3, 2010).

    1982 1985 1990 1995 2000 2005

    Tot

    alex

    pend

    itures*

    Policing

    Correctional50

    100

    150

    200

    (b) Expenditures on Law Enforcement

    (Billions of Constant 2005 Dollars)

    Total

    Probation

    Prison+jail Parole

    1980 1985 1990 1995 2000 2005

    1

    2

    3

    4

    5

    6

    7

    (a) Number of Persons under Correctional

    Supervision (in Millions)

    FIGURE 31.2 Expenditures on the U.S. Legal System: 19822006

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    8 Chapter 31: Crime

    locking and unlocking doors each day, and jus over wo minues per day look-ing or keys. his represens $89.6 billion worh o ime los due o such crime-prevenion aciviies.25

    31.2 The Economic Approach to Crime: TheoryPain and pleasure are he grea springs o human acion. When a man per-ceives or supposes pain o be he consequence o an ac, he is aced upon insuch a manner as ends, wih a cerain orce, o wihdraw him, as i were, romhe commission o ha ac. I he apparen magniude, or raher value o hapain be greaer han he apparen magniude or value o he pleasure or goodhe expecs o be he consequence o he ac, he will be absoluely prevenedrom perorming i. he mischie which would have ensued rom he ac, iperormed, will also by ha means be prevened.26

    Over he inervening years ha have elapsed since he appearance o Beckers(1968) seminal paper Crime and Punishment, economiss have aken enormousrides oward undersanding he principal deerminans o criminal behavior.

    A Partial Equilibrium ModelIn his secion, we presen a simple model ha capures he main elemens o heconomic approach by ocusing on he individual incenives o engage in crime. Inhe nex secion, we examine he general equilibrium implicaions o he model

    As we shall see, i will be possible, or he irs ime, o capure he inuiive noionha a robus labor marke discourages criminal aciviy and povery omens i.

    A Model of Criminal Behavior. In Model 31.1, we presen he main assumpionwe will use o model criminal aciviy.27

    MOD EL 31.1

    Criminal Behavior

    (a) he economy exends over a single period o ime and is populaed byNhomogeneous, amoral, uiliy-maximizing individuals.

    (b) Each persons uiliy is given by U = U(x), where xis he dollar (equivalen)value o consumpion. Each person is also endowed wih an indivisible uni

    o ime ha is supplied inelasically wihou disuiliy rom eor. Individu-als allocae heir ime eiher o ormal work or o (propery) crime.

    (c) he wage rae rom legiimae aciviy is $w.

    (d) I no apprehended, he (expeced) income rom crime is a n, where nis henumber o crimes commied during he period andais he dollar value oeach crime.

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    31.2: The Economic Approach to Crime: Theory 9

    (e) he auhoriies devoe resources o policing and capuring criminals. heprobabiliy ha a criminal is capured in he commission o a crime is . Inhe even o capure, he criminals uiliy is U(a n s), where s> 0 is hedollar (equivalen) value o any legal sancions imposed on him or her.

    () U(w) > U(a n s).

    In par (a) o Model 31.1, he assumpion o only a single ime period simpliieshe analysis considerably. Obviously, he choices ha people makeespeciallyconcerning wheher o commi crimescan have ar-reaching consequences.hus a senence o 40 years hard labor would be enough o pu a severe din inanyones career prospecs. Neverheless, even wih his imporan resricion,Model 31.1 provides valuable insighs ino he deerminans o criminal behav-ior.28he amoraliy assumpion says ha individuals have no leanings owardoragainscriminal acs per se bu make heir choices solely on he basis o mon-eary oucomes or heir moneary equivalens. As we shall see, we do no need o

    invoke issues o moraliy o explain why some people commi crimes and ohersdo no. hereore hese complicaions can be ignored hrough an applicaion oOccams razor.

    According o par (b), each person supplies his or her labor inelasically andwihou disuiliy rom eor. his neuralizes any labor-supply complicaions.29I is no doub ediying o undersand why some people spend 14 hours per weekplanning and execuing crimes and ohers spend 15 hours (which is possible onlyi here is some laiude in allocaing ime beween work, crime, and leisure); nev-erheless, as economiss, our irs order o business is surely undersanding whypeople commi any crimes a all. he assumpion ha each person possesses asingle indivisible uni o ime also implies ha agens mus specialize eiher inlegiimae ormal employmen or illegiimae criminal aciviies (given you canspli he indivisible). In realiy, however, ew people acually make a living romcrime alone. As Freeman (1999) remarks,

    he border beween illegal and legal work is porous, no sharp. Some personscommi crimes while employeddoubling up heir legal and illegal work.Some persons use heir legal jobs o succeed in crime. . . . Some criminals shi

    beween crime and work over ime, depending on opporuniies.30

    Despie his shorcoming, he indivisibiliy assumpion is a very helpul simpli-icaion. ogeher, pars (c) and (d) o Model 31.1 describe he consequences ohe individuals acions. his is a parial equilibrium seing, so no explanaion isgiven (or required) as o why he wage is w, or why criminals accrue a n romheir aciviies. hey simply do, and has ha.

    Alhough n and a are reaed as exogenously given, here is some evidenceconcerning he magniudes o hese imporan variables. Indeed, prisoner surveysshed ligh on he average number o crimes, n, commied per annum. Piehl and

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    10 Chapter 31: Crime

    DiIulio (1995) esimae ha each incarceraed prisoner conducs 12 nondrugrelaed crimes in he year beore his or her capure. Likewise, Marvell and Moody(1994) esimae each prisoner commied abou 17 crimes per year beore capure. Hence i is reasonable o ake n15.

    As or criminal earnings, $a, Freeman (1999) remarks, Average hourly wagerom crime were $19. All hese esimaes exceed he average legal wage o $7.50.3

    Grogger (1998) esimaes ha, on an annual basis, he average criminal earn$1187. Piliavin, Garner, hornon, and Masueda (1986) ocus heir aenionon severe oenders. Using daa colleced beween 1975 and 1979 or he Evaluaion o Naional Suppored Work Demonsraion (a job-creaion program opersons wih severe employmen problems), oenders (1,497 o hem) reporedha heir sree earnings exceeded heir legiimae earnings by 63%. Moreoversome 48% o hose surveyed assered hey had requen opporuniies or commiing crimes.

    The Legal Environment. Par (e) o Model 31.1 describes he legal environmen

    he probabiliy ha a criminal is apprehended during he commission o a crimeis denoed . Obviously, he likelihood o deecion and he probabiliy o convicion depend on he resources devoed o enorcemen eors. For he momenhese acors are simply reaed as given. he uiliy U(a n s) is a cach-all hadescribes he criminals uiliy on capure. Here $sis he dollar-equivalen value olegal sancions arising rom he imposiion o ines and possible incarceraion.3

    Finally, condiion () is included because o is plausibiliy. Wihou his assumpion, criminal behavior would be very srange since a ormal worker would be beer o robbing a bank and running hrough he srees exclaiming, I was me! I

    was me! hoping or his or her arres.

    Optimal BehaviorEach individual in he economy mus decide beween one o wo courses o acion: legiimae work or crime. In deermining he acion ha is bes or him, eachperson looks o his own preerences, he consrains he aces, and selecs he acion ha gives him he greaes expeced uiliy.

    Analysis. In wha ollows, le I = 1 index ormal employmen and le I = 0index crime. he expeced uiliy rom ormal employmen (work), denoed

    EU1, isEU1= U(w), which is he uiliy ha he individual accrues rom earning

    he wage, $w. o deermine he uiliy rom choosing crime, denoed EU0, hindividual is assumed o be ully cognizan o he ac ha he may ge away wihhis ill-goen gains bu also runs he risk o being capured and punished. Usinghe mehods se ou in Appendix D, his expected utilityis hereore,

    EU0= (1 )U(a n) + U(a ns) (31.1

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    31.2: The Economic Approach to Crime: Theory 1

    Wih probabiliy 1 he ges away sco-ree (and enjoys $a no boo); how-ever, wih probabiliy , he games up, hes caugh, punished, and his uiliy is onlyU(a n s), where scapures he severiy o he legal sancions inliced on him.

    IEU0>EU1, hen crime is individually rational. I ollows rom he deiniionsoEU1andEU0ha crime is opimal i,

    (1 )U(a n) + U(a n s) U(w) > 0 (31.2)

    Noice ha U(w) capures he opportunity costo crime. I relecs he legiimaeearnings ha he individual orgoes by pursuing a lie o crime raher han work-ing in he ormal secor. Equaion 31.2 can be used o derive he principal insighso he economic model o crime. For convenience, hey are summarized in MajorResul 31.1.

    MAJOR RESULT 31.1

    Criminal ActivityA given individual is more likelyo op or crime, vis--vis ormal work, he:

    (a) Greaer he earnings rom crime, a n.

    (b) Lower he earnings rom legiimae employmen, w.

    (c) Smaller he probabiliy o deecion, .

    (d) Lower he punishmen, s.

    (e) Lower he degree o he individuals aversion o risk.

    Only poin (e) requires clariicaion. By engaging in crime ha individual is ak-ing a calculaed risk. Wih probabiliy he is apprehended and inds himsel in apickle, and wih probabiliy (1 ) his criminal eors succeed. he greaer anindividuals aversion o risk, he greaer he weigh he places on he bad oucome,U(a n s). In he limiing case o completerisk aversion, he is so averse o riskha he places zero weigh on he avorable one, U(a n). Hence he greaer hedegree o risk aversion, he lower he expeced uiliy o crime vis--vis ormal

    work, U0, which esablishes he claim.

    The Marginal Benefits and Costs of Crime. I is insrucive o rearrange Equa-

    ion 31.2. he oucome is ha i is possible o show ha crime is individuallyopimal only i he ollowing condiion is saisied:

    (1 ) {U(a n) U(w)} > {U(w) U(a n s)} > 0 (31.3)

    According o Par (e) o Model 31.1, we have U(w) > U(a n s). I ollowsha Condiion 31.3 is saisied only i U(a n) > U(w), which, in urn, requires

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    31.3: General Equilibrium 13

    dollar value o he goods hey consume. he risk-neuraliy assumpion meansha hey care abou only heir expeced consumpion levels.

    The Disposition of the Population. Le L denoe he number o people whowork and Cdenoe he number who commi crimes. Because he people in hiseconomy are assumed eiher o work or commi crimes i ollows haN=L + C,

    where i will be recalled haNis he oal populaion.

    General-Equilibrium Features. Les impose Assumpion 31.1, which describeshe economic processes ha deermine boh he wage and he reurns o crime.

    A S S U M PT I ON 31 .1

    General Equilibrium

    (a) he labor marke is compeiive, and he demand or labor is:

    w=D(L)0 (31.4)

    where wis he (real) wage, andD(L)0is a sandard negaively sloped demandcurve (see Figure 31.3a).

    (b) Each crime yields a ixed payo $a.

    (c) he probabiliy a criminal is apprehended is a consan . I apprehended hecriminals uiliy is U(a n s) =a n s.

    According o Assumpion 31.1a, he demand or labor is governed by a san-dard negaively sloped schedule. Les assume, or a momen, ha each crime

    yields a fixedreurn o $a. In pracice, he reurns o crime migh be expeced o

    depend on he average income level in he communiy. he reason is ha, ceterisparibus, an increase in he average income level implies here is more o seal. hispossibiliy is deal wih laer. he legal environmen (characerized by sand ) isalso exogenously given.

    The Expected Cost of Crime. Obviously he proceeds rom each crime,a, do nomaerialize ou o hin air. Raher hey represen ransers rom vicims o crimi-nals. Wih his in mind, le us do some accouning. I here are Ccriminals, eacho whom commis ncrimes, his implies ha a oal o C ncrimes occur duringhe period. In addiion, each crime yields an average booy o $a. his impliesha he oal loss inliced on vicims (gain o criminals) is $a C n. From he

    perspecive o poenial vicims, crime is a random even. Suppose ha everyonein he populaion oNpeoplecriminals and ormal workers alikeeach aceshe same probabiliy o alling vicim o a crime.33Hence each person expecs osuer a crime relaed loss, $z, ha is given by:

    z (anC)/N =anc, where c C/N (31.5)

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    14 Chapter 31: Crime

    Expected Utilities. he expeced uiliies rom legiimae work,EU1, and romcrime,EU0, are given by:

    EU1=w z and EU0=an s z (31.6

    he (possibly negaive) net gain, G, rom commiing crimes (as opposed o or

    mal employmen) is deined by GEU0EU1. In urn, his laer condiion canbe wrien as:

    G an s w (31.7

    I G> 0, hen he individual gains rom crime, which implies ha criminal aciviyis sricly opimal; i G< 0, hen he loses, so ormal employmen is sricly preerred; and i G= 0 he is jus indieren beween ormal employmen and crimeNoice ha, since crime aecs everybody equally, he expeced dollar loss romcriminal vicimizaion, $z, has no eec on he decision o wheher o engage incriminal aciviies a he margin.

    General EquilibriumSo wheres he general equilibrium in all o his? he answer o his quesion is inwo pars. Firs, and mos imporan, noice ha he wage, w, accruing rom ormaemploymen appears in Condiion 31.7. Noice oo ha i depends (negaively)on he number o workers who choose ormal employmen,L. Consequenly, ashown in Figure 31.3a, i he level o employmen is lowhe wage is high. Likewisei he level o employmen is high, hen he wage is low.

    Second, Condiion 31.7 deermines wheher people op or crime or or ormaemploymen (or are indieren beween he wo aciviies). Combining boh heselemens ogeher gives us he general equilibrium ha we are seeking o ind.

    Analysis. o see how he pars o he model i ogeher, suppose ha everyonis ormally employed, implyingL = N. Reading o he demand schedule,D(L)0in Figure 31.3a, shows ha a his high level o employmen he wage is very low(see poin H). Bu hen he ne gain rom criminal aciviy is posiive, G> 0, soeveryone elecs o become a criminal! Obviously, his canno be an equilibrium

    We began wih a siuaion in everyone works bu ended up wih one in which everyone makes precisely he opposie choice and becomes a criminal! Similar buopposie remarks apply o he case in which everyone chooses o be a criminal. Inhis case, he wage is high, so everyone wans o work because G< 0!

    I ollows rom hese remarks ha, in equilibrium, he ne o gain rom crime musbe precisely zero, G= 0. Only hen is i he case ha here is no incenive or anyono change his or her behavior. his oucome is locaed a he inersecion o he wosolid lines in panel (a), implying he equilibrium level o employmen equalsL*0.

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    31.3: General Equilibrium 1

    Figure 31.3b describes how he popula-ion is allocaed beween work and crime.he negaively sloped 45 line, NN, cor-responds o he ideniy N = C + L, whichdescribes he disposiion o he populaion

    beween crime and ormal work. he lineOPQR depics he number o people who

    plan o become criminals condiional onhe given level o employmen L. Everyone

    wans o work or levels o employmen lesshanL*0, and everyone wans o be a criminalor levels o employmen ha exceedL*0, orhe reasons jus given. Individuals are indi-eren beween he wo occupaions only i

    L = L*0. Hence he equilibrium oucome islocaed a poinE, where he lineNNiner-

    secs he line OPQR, since nobody hen hasany incenive o change his or her behavior.

    Comparative Statics. he general equi-librium ramework can be used o examinehe eecs o an assormen o policies andchanges in he economic environmen. Con-sider, or example, he eec o an adversemacroeconomic shock ha reduces he de-mand or labor in he ormal secor (e.g., he

    recen near caasrophe ha occurred duringhe 2008 inancial meldown). As shown inFigure 31.3a, he shock induces a lewardshi in he labor-demand schedule, whichmoves rom D(L)0 o D(L)1 along he un-changedreurn-o-crime schedule,a n s.Noice ha workers are now indieren be-ween crime and ormal work a poin F,

    where here are a oal oL*1ormal workers.Reading down o panel (b) reveals ha

    he opimal-behavior schedule shis romOPQRo OPQR. In urn, his change causes he equilibrium o shi rom poin

    E o E. I is readily seen ha he equilibrium number o criminals increasesrom C*0 o C*1. Noice ha, despie he reducion in he demand or labor, heequilibrium wage remains unchanged a w*0; i mus, or each worker has he op-ion o becoming a criminal, which provides an invarian expeced income o$(a n s).

    N

    D(L)1

    D(L)0

    E

    Q R

    H

    $w

    45

    Optimal behavior

    (given L)

    Disposition of

    the population

    Return to Crime

    an s

    P

    F

    L

    C

    N

    w*0

    C*0

    C*1

    L*0L*1

    LNL*0L*1

    O

    O

    F

    E

    Q

    P

    (a) Returns to Formal Employment and to Crime

    (b) Optimal Behavior

    Criminals

    Formal Workers

    FIGURE 31.3 The Equilibrium Levels of Crimeand Employment

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    16 Chapter 31: Crime

    Endogenous Returns to CrimeUp o his poin, he reurns o each crime, $a, have, in he ineress o simpliciy

    been reaed as exogenously given. In pracice, however, a, migh be expeced odepend on several dieren acors. Consider Assumpion 31.2.

    A S S U MP T I ON 31 . 2

    Endogenous Returns to Crime

    Assume haa= a(C, w), where ais decreasingin Cand increasingin w.

    Assumpion 31.2 says ha he reurns o each crime,a, depend negaively onhe number o criminals C and posiively on he wage. Inuiively, or very lowlevels o criminal aciviy, he ew acive criminals in he populaion can searchou so high-reurn arges wih ease, bu as heir numbers increase i becomeincreasingly diicul o do so. Moreover, as he crime rae increases, individual

    migh respond by becoming more vigilan and devoing greaer eors oward ensuring heir own securiy: Doors remain unlocked in much o rural America buhis would hardly be pruden in many poor urban neighborhoods.34An increase inaverage earnings, w, implies ha he ypical individual has more possessions haare available or criminals o seal, which explains why aincreases wih he wage

    Analysis. he expeced netreurns o crime are once again given by,

    G EU0EU1=an s w, (31.8

    where a= a(C, w) and w=D(L). Previously, awas exogenously given bu now

    i depends on C and w. his simple bu plausible exension makes or a worldo dierence. he reason is ha he directeec o an increase in he number ocriminals, C, is o lower a. Neverheless, here is an indirectgeneral-equilibriumeec ha works hrough w. More speciically, as Crises henLalls, which raise

    boh he wage, w, anda. Hence, depending on he size o hese wo eecs, he(expeced) uiliy rom crime, an s, may increaseor decreaseas he number ocriminals, C, rises.

    Figure 31.4adepics he reurns-o-crime schedule an s, denoed QQ. Ipossesses boh increasing and decreasing segmens, or he reasons jus describedFigure 31.4bdepics he schedule OR, which deermines he number o individuals who plan o become criminals given he number o ormal workers, L. Noice ha he OR locus inersecs he negaively sloped 45 line a several (hree)poins: G, B, Uhe good, he bad, and he ugly. his oucome is reerred o aa siuaion o multiple equilibria, because all hree poins represen poenial equilibrium oucomes.

    he ugly equilibrium, depiced a U, is characerized by a high level o criminaaciviy and a low level o ormal employmen. he good equilibrium, G, has lil

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    31.3: General Equilibrium 1

    crime and a high level o employmen. (CaseBis inermediae.) he acual oucome haperains depends on he belies held by hepopulaion a large. For insance, poin Uisa pessimisic equilibrium: everyone expecshe crime rae o be very high and employ-men o be low. Given he high wages earned

    by he ew individuals who do work, every-one expecs ha crime is also lucraive andheir belies are ulilled. Similar, bu oppo-sie, remarks apply o he opimisic equilib-rium shown a poin G.

    Recent Developmentshe economic approach o crime is a very

    acive area o curren research. Below, wobroad classes o developmens are oulined.

    Dynamic Models. he hallmark o dynamicmodels o criminal behavior is ha individu-als recognize ha heir curren acions haveuure ramiicaions or heir well-being.Imrohorolu, Merlo, and Ruper (2000)consruc a model in which individualsspecialize in eiher legiimae or criminal ac-

    iviies. Greaer numbers o police increaseapprehension raes, bu resul in a greaer axburden o inance hem. he level o policeexpendiures is deermined by he oucomeo he poliical process ha depends on ma-

    joriy voing. Using U.S. daa he auhorsind ha a echnologically induced reduc-ion in income inequaliy lowers he crime rae. Neverheless, (depending on hedeails) policies ha reduce inequaliy hrough axes and ransers may increaseor decrease he crime rae.

    Imrohorolu, Merlo, and Ruper (2004) sudy propery crime in he UniedSaes in a very rich general-equilibrium seing. Individuals dier in heir pro-duciviies and hey are orward-looking, recognizing heir curren acions haveuure consequences. he auhors calibrae heir model o he 1980 U.S. daa. (Inessence, his means ha some o he parameers are seleced so ha he model re-produces he major eaures o he U.S. experience in 1980.) hey hen use 1996daa o evaluae he eecs o various changes ha occurred in he U.S. economy

    D(L)0

    $w

    45

    L

    C

    Q

    O

    O

    (a) Returns to Formal Employment and to Crime

    (b) Optimal Behavior

    Criminals

    L

    Formal Workers

    N

    N

    Optimal

    behavior

    (given L)

    Disposition

    of the

    population

    Q

    U

    B

    B

    G

    R

    G

    U

    Return to Crime

    an s

    FIGURE 31.4 Multiple Equilibria

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    18 Chapter 31: Crime

    over he period. he model is rich enough o accoun or he decline in he (propery) crime rae over he period. he mos imporan acors ha explain he decline (in order o imporance) are (1) greaer policing, (2) he sronger economyand (3) he aging populaion.35Mos ineresing, he auhors ind ha he increasin income inequaliy ha occurred over he period would, absen eecs 13, havled o a subsanial increase in he number o propery crimes.

    In Huang, Laing, and Wang (2004) we consruc a model eauring search aciviy and crime. Some individuals elec o become criminals (and search or vicims), while ohers become ormal workers and search or jobs. Formal workerscan accumulae human capial, which increases heir produciviy once employed

    We show ha criminal aciviy (he) essenially acs as a ax on he accumulaiono human capial. Aer all, here is lile poin acquiring a cosly educaion i, asome uure poin in he no oo disan uure, here is a high chance ha onepossessions (i.e., he ruis o ones labor) will be solen. Because o hese consideraions, he model exhibis muliple equilibria o he sor jus considered, wihhigh crime, low levels o educaional aainmen, long spells o unemploymen

    and povery (low incomes) correlaed across hem.Burde, Lagos, and Wrigh (2003) also consider an environmen characer

    ized by labor-marke search and by he random ineracion beween criminals andormal workers. In heir model, an equilibrium wage disribuion arises in whichsome irms use high wage paymens o reduce cosly labor urnover. Workers employed a high-wage irms do no commi (propery) crimes because hey havoo much o lose i hey are apprehended, incarceraed, and lose heir jobs as aresul. I is, however, opimal or workers employed a low-wage irms o commi crimes, since hey have lile o lose.36heir paper oers ineresing insighino he relaionship beween he disribuion o wages and he level o crimina

    aciviy.

    Interaction Models. Glaeser, Sacerdoe, and Sheinkman (1996) develop a ramework, in which each agen mus choose beween criminal and legiimae behaviorhe choices o some agens are, however, parly driven by peer group eecs, in

    which hey imiae he behavior o heir neares neighbor. hey show a disribuion o equilibria may emerge, which oers valuable insighs ino he high emporal and spaial variance o crime raes ha are observed in he Unied Saes.

    31.4 Crime and Punishment: Deterrencehe exen o enorcemen o laws depends upon he amoun o resourcesdevoed o he ask. Wih enough policemen almos every speeding auomo-

    bile could be ideniied. . . . We could make cerain ha crime does no payby paying enough o apprehend mos criminals. Such a level o enorcemenwould o course be enormously expensive, and only in crimes o enormous

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    31.4: Crime and Punishment: Deterrence 1

    imporance will such expendiures be approached. he sociey will normallygive o he enorcemen agencies a budge which dicaes a much lower levelo enorcemen.

    Stigler(1970)37

    One o he major beneis o he economic approach is ha i orces us o clearly

    ariculae he coss and beneis o criminal aciviy and he resources used in isprevenion. Hence i is relaively easy o assess he relaive eicacy o alernaiveanicrime programs (such as he value o spending an addiional ax dollar onpolicing as opposed o prisons). In his secion, we examine he eeciveness osome o hese policy opions.

    DeterrenceIn he year 1531, when Henry VIII was King, an ac was passed or boiling pris-oners o deah. he ac deails he case o one Richard Roose, or Coke, a cook

    in he diocese o he Bishop o Rocheser, who had, by puing poison in heood o several persons, occasioned he deah o wo, and he serious illness oohers. He was ound guily o reason, and senenced o be boiled o deah.

    Andrews(1991)

    As we saw in Secion 31.2, crime is individually opimal i:

    (1 )U(a n)+ U(a n s) U(w) > 0 (31.9)

    where i will be recalled ha is he probabiliy o arres (and convicion), andU(a n s) is he criminals uiliy in his even. here are a variey o inerprea-ions o he sancion s. I could represen a moneary ine or he dollar cos he

    individual places on his incarceraion (or even orure). For simpliciy assume heindividual is risk neural, so U(x) = x. he individuals decision hen boils downo (no pun inended) choose crime if:

    a n w s > 0 (31.10)

    I is quie easy o see, rom his expression, how he economics o deerrencework. Holding consan he gross rewards rom crime, a n w, he individual isless likely o commi crimes he greaer is eiher he likelihood o his apprehen-sion (given he penaly s) or he greaer he penaly $s(given he apprehensionlikelihood, ).

    his simple ramework has an immediae bu sarling implicaion or heopimal design o policies inended o comba crime. In paricular, noice hahe deerrence eec is consan provided ha he combined produc sis con-san. I ollows ha i is reduced bu s is increased in proporion, hen hedeerren eec, s, remains unchanged. Ye, sociey bears he coss associaed

    wih deecion (), and he elon, by and large, bears he coss o his punishmen.

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    20 Chapter 31: Crime

    Consequenly, sociey should seek o implemen any given level o deerrence s, by minimizing or, equivalenly, by maximizing s. I ollows ha he moscos-eecive way or sociey o preven crimesvarying rom murder o evenhe lae reurn o library booksis o execue oenders wih a suiably chosenprobabiliy. (Boiling hem o deah would be even more eecive.) Alhoughhis is a predicion o he model, i is obviously a variance wih he acs. Noeven Singapore execues people or crimes such as liering or spraying car

    wih pain.38

    Why the Punishment (Usually) Fits the Crime. Almos no sociey givemurderers a slap on he wris and execues hose who reurn heir library

    books lae. In general, he punishmen usually is he crime. In a now classipaper, Sigler (1970) advanced wo main reasons or why his is so and o

    why here is a balance beween enorcemen expendiures and he severiy opunishmens.

    Firs, expendiures on policing and law enorcemen reduce he likelihood o

    convicing and punishing he innocen. For example, i would be mos unorunae were we o execue Norbur or he lae reurn o his library books, only ohen discover ha he had in ac reurned hem on ime and here had been clerical error. his concern alone is suicien o miigae he harshness o manylegal sancions.

    he second reason concerns he proper pricing o criminal punishmens. Foexample, suppose I can be execued or a minor crime, such as illegally parkingmy car. I ollows ha i I commi his crime, hen I migh as well also commi amore serious one, such as armed robbery. However, his logic ails i, insead, I aca $20 ine or he ormer crime and 15 years in sae prison or he laer.39

    An Interesting Externality. Sah (1991) and Freeman, Grogger, and Sonseli(1996) ideniy an ineresing exernaliy ha arises whenever a given level oresources are used o invesigae and prosecue crimes. o see wha is aoo, le ureurn o he ne gain rom crime G, which previously was shown o equal:

    G a n s w (31.11

    where i will be recalled ha is he probabiliy o inerdicion. Sah (1991) andFreeman, Grogger, and Sonselie (1996) argue ha i is plausible o assume ha

    his deecion probabiliy is given by: = (P, C) (31.12

    where Pdenoes oal policing expendiures, and, once again, C represens hnumber o criminals. As sociey increases he level o policing (say, by increasing he number o police parols) each criminal aces a greaer likelihood o arres, so increases wihP. However, or any given level o policing,P, an increas

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    31.4: Crime and Punishment: Deterrence 2

    in Creduces he likelihood ha any given criminal will be apprehended. (hinko police resources being sreched o he breaking poin during a crime wave.)hereore, i is plausible o suppose ha declinesas C rises.

    his laer eec is ermed an externality: my decision o become a criminallowers he chances ha, as a criminal, youwill be arresed. I is ineresing be-cause i means ha as he number o criminals, C, increases, hen he expeced nereurns o crime, G, also increase a he margin, since here is a lower probabiliy odeecion. his leads o he possibiliy o muliple equilibria (o he sor describedearlier), which, in urn, can help o explain why, during some periods, here is acrime wave and during ohers he crime rae is relaively low.

    PrisonsPrisons are an inegral par o he U.S. jusice sysem: We don jus ine murder-ers, we lock hem up! here are our main reasons why we do his. DiIulio (1996)eleganly summarizes hese reasons as ollows:

    Imprisonmen oers a leas our ypes o social beneis. he irs is reri-buion: imprisoning Peer punishes him and expresses socieys desire o dojusice. Second is deerrence: imprisoning Peer may deer eiher him or Paulor boh rom commiing crimes in he uure. hird is rehabiliaion: while

    behind bars, Peer may paricipae in drug reamen or oher programs hareduce he chances ha he will reurn o crime when ree. Fourh is incapacia-ion: rom his cell, Peer can commi crimes agains anyone save oher prison-ers, sa or visiors.40

    O hese, only incapaciaion is unique o he prison sysem. Sociey can bohdeer crimes and exrac reribuion via he use o eiher ines or corporal punish-

    men, and i can rehabiliae by educaing he conviced. Regarding incapacia-ion, DiIulio (1996) coninues,

    As columnis Ben Waenberg so vividly pu i, everyone grasps, A hug inprison can shoo your siser. Few criminologiss (and no average ciizens)doub ha i we empied he prisons onigh we would have more crimeomorrow.41

    In ac, he argumens or incapaciaion appear o be so compelling ha i is di-icul o imagine ha here is any room or debae on he issue. here is. heclaim ha incarceraion reduces crime because i removes criminals rom civil

    sociey, so denying hem he means o doing urher harm, is based on a partial-equilibriumview o he world. Neverheless, as Freeman sresses, i is imporan oaccoun or he poenial replacemen o hose who are incarceraed by he enryo new criminals. Freeman (1996) remarks,

    From he mid-1970s o he mid-1990s, he Unied Saes roughly ripled henumber o men in prison or jail. . . . Incapaciaion o so many criminals should

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    22 Chapter 31: Crime

    have grealy reduced he crime rae: i he wors oenders are in prison, heycan mug, rob or oherwise commi oenses agains he ciizenry. Bu no suchdrasic reducion in crime occurred. . . . Non-insiuionalized men evidenlyreplaced incarceraed criminals in commiing crimes.42

    Replacement Effects. he general-equilibrium model, presened in Secion 31.3oers valuable insighs ino he workings o he replacemen eec. he only

    modiicaion required o he ramework is ha i mus be exended o coverwo ime periods: he minimum number required o sudy he eecs o h

    capure and incarceraion o one cohor ocriminals and heir subsequen replacemen

    by anoher.Once again, assume ha he disposi

    ion o he populaion, N, beween ormaworkers,L, and criminals, C, is N= C + Lo make he argumens as crisp as possible

    les assume (Figure 31.5b) ha he labordemand curve, D(L)0, is perecly elasi(i.e., horizonal), which implies he wage iconsan and equals $w0.

    Suppose ha he value o each crime, a=a(C), depends (negaively) on he numbeo criminals, C, because i becomes mordiicul o locae so arges as C rises.4

    Condiional on a given number o criminalsC, he expeced earnings rom crime ar

    $(a(C) n s). In urn, given CN Lhis can be wrien as $(a(N L) n s)Noice ha he reurn depends posiively on

    L(as shown by he lineBBin Figure 31.5b)Inuiively, a greaer number o ormal workers auomaically means here are ewer criminals, which raises he value rom each crime$a(C). Finally (and mos imporan), sincea(C) a(N L), noice ha i bohNand

    L happen o change by he same amoun

    hen he reurns o crime,a

    (C

    ) n

    s

    remain unchanged.he signiicance o his laer ac is ha

    i Npeople are incarceraed in one periodhen he reurns-o-crime schedule,BB, shiftleftward by N in he nex. (Why? I hepopulaion, N, declines by N and i h

    D(L)0

    Optimal behavior

    (given L)

    Return to

    crime

    Formal

    work

    Disposition of

    the population

    Arrests

    C*0

    L

    L

    N0

    w0

    N0

    N1

    N1

    L*0

    L*0

    L*1

    L*1

    $w

    O

    FF

    R

    E E

    B

    B

    B

    B

    (b) Returns to Formal Employment and to Crime

    (a) Optimal Behavior

    Formal Workers

    C

    C*0

    O

    Crimin

    als

    an

    s

    FIGURE 31.5 Replacement Effects

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    31.4: Crime and Punishment: Deterrence 2

    number o ormal workers, L, declines by N, hen he reurns o crime remainunchanged or he reasons jus given.)

    We are now ready o analyze he properies o he model. In he irs period, heequilibrium is locaed a poinsEand Fin he igure. here are a oal o C*0crimi-nals,L*0(N0 C*0) legiimae workers, and nobody has an incenive o change

    his behavior.Based on he arres and convicion probabiliy, , a oal o C*0criminals arearresed in he irs period. Suppose ha hey all remain behind bars in he secondperiod, which removes hem rom civil sociey. he resul is ha he populaiondeclines by C*0 (rom N0 o N1). As shown in Figure 31.5b, his displaces hereurns-o-crime schedule,BB, leward (by he amoun C*0) oBB(or he rea-sons jus described).

    Because he average criminal commis ncrimes, he parial-equilibrium com-monsense eec o incarceraing he C*0apprehended criminals is ha he overalllevel o criminal aciviy will decrease by n C*0. Neverheless, he olly o lookinga only parial-equilibrium eecs is quie apparen. In he second period, many

    o he incarceraed are replaced by hose who were legiimae workers in he irsperiod. he ligh green lines depic he general-equilibrium eecs. In panel (a),heN0N0schedule shis inward, by he amoun C*0, oN1N1(relecing he in-carceraion o hose arresed in he irs period).

    As shown in panel (b), his, in urn, causes he reurns o crime locus o shileward romBBo BB. In he second period, he new equilibrium perains apoinsEand F. Noice ha, in his simple model, here is complee replacemen

    because he number o criminals remains unchanged! his example is obviouslyexreme, and in realiy, we migh expec only parial replacemen o occur. Evenso, is main message should be enough o give policy makers pause or hough.

    In 2007, he Unied Saes spen over $60 billion on he prison sysem. Nev-erheless, he oal cos o he prison sysem is much greaer han his numbersuggess. he reason is ha sociey loses he value o each prisoners conribuiono GNP rom his poenial employmen. (Anderson (1999) esimaes hese coss

    were abou $35 billion in 1997.) In addiion, he use it or lose itprinciple has par-icular relevance or members o he prison populaion. he possibiliy o sewingmail bags nowihsanding, prisoners have (or reasons ha are all oo ranspar-en) ew opporuniies or inding gainul employmen. As a resul, hey mighlose much o heir human-capial socks over lenghy periods o incarceraion.

    his loss in human capial is unorunae on a leas wo couns. Firs, sociey

    obviously loses some (producive) human capial. Second, he loss in human cap-ial encourages recidivism a he margin. Recall ha one o he primary insighso Beckers model o crime is ha one o he major deerrens o criminal aciv-iy is he legiimae earnings, $w, ha an individual orgoes by choosing a lie ocrime. A lenghy prison senence, however, weakens his deerrence eec becausei reduces he individuals human capial sock and hereore his legiimae earn-ings on release.

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    24 Chapter 31: Crime

    31.5 The Economic Model of Crime: The Evidencehe hallmark o he economic model o crime, irs proposed in Becker (1968)is ha criminal aciviy responds o incenives. More speciically, according o he

    basic model presened in Secion 31.1 he crime rae is prediced o decline wih

    l An improvemen in ormal employmen opporuniies.l A deerioraion o criminal opporuniies.

    l An increase in eors ha are direced a legal deerrence, such as an increase inhe likelihood o deecion, , or in he severiy o punishmens, $s.

    A huge number o empirical sudies have esed he main predicions o Beckers model o criminal aciviy, and, on balance, he ramework has received srongempirical suppor. In his secion, we discuss some o he major empirical indingo his lieraure, beginning wih hose ha have ocused on changes in he opporuniies ha are available o workers in he ormal labor marke.

    Labor Market OpportunitiesEarlier, in Secion 31.1, we presened evidence ha showed ha he Unied Sae

    winessed, on he one hand, a sriking increase in criminal aciviy ha exendedover a 20-year period (beginning in he early 1970s) and, on he oher hand, anequally impressive meeoric decline in crime during he 1990s. For example, aeconrolling or couny level demographic changes in race, age, and sex raiosGould, Weinberg, and Musard (2002, p. 47) repor he number o properycrimes increased by abou 29% beween 1979 and 1993 and decreased by 7.6%

    beween 1991 and 1997.

    he changes in criminal aciviy, however, apparenly mirrored wo signiicandevelopmens ha occurred in he Unied Saes labor marke: he sharp declinein he earnings o young unskilled men, which began in he early 1970s, and hesubsanial decrease in he aggregae rae o unemploymen, which began in he1990s. More speciically, rom he mid-1970s o he early 1990s he earnings o(unskilled) young men decreased by 20%30% and beween 1992 and 1998 heaggregae unemploymen rae plummeed rom 7.5% o 4.5%.44he close paralledevelopmens o hese evens immediaely raises he quesion o wheher heyare relaed in some way. O course, such a connecion migh be expeced o holdon a priori grounds because he decision o wheher o engage in criminal aciviyis a ime allocaion problem. In ac, as we have seen, changes in he opporuniieavailable o workers in he ormal labor marke are prediced o have a direc andinelucable impac on he crime rae, by aecing he opportunity costo crimina

    behavior.In perhaps he mos comprehensive sudy o dae, Gould, Weinberg, and

    Musard (2002) analyze he eecs on he crime rae o he changes ha occurred over he las wo decades in he (legal and illici) opporuniies available

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    31.5: The Economic Model of Crime: The Evidence 2

    o young men.45According o one se o esimaes, hey ind a 1% increase in heweekly wage o non-college-educaed men reduces propery crimes by 0.54%; a1% decrease in unemploymen reduces hem by 2.2%; and inally a 1% decrease insaewide per capia income reduces propery crimes by 0.48%. (Broadly similaresimaes are obained or an assormen o oher criminal aciviies.)

    Despie he ac ha he eec o a 1% change in unemploymen on crime isalmos 5 imes greaer han he eec o a 1% change in he wage, he auhorsargue ha, beween 1979 and 1993, he increase in criminal aciviy was largelydriven by he decline in he real earnings o young men. Quie simply, despie hepowerul connecion beween crime and unemploymen, he unemploymen raedid no change enough, over he period o ineres, o have much o an impac.(In ac, he unemploymen rae in 1979 was virually he same as i was in 1997,despie he ac ha propery crimes were 21% higher.) Gould, Weinberg, andMusard (2002) deermine ha he 23.3% reducion in he real wages o unskilledmen, beween 1979 and 1993, explains much o he increase in criminal aciviy:

    he non-college-educaed wage explains 43% o he 29% increase in adjusedpropery crime during his ime period, and 53% o he 47.2% increase inadjused violen crime. he unemploymen rae o non-college-educaed menexplains 24% o he oal increase in propery crime and 8% o he increasein violen crime. Clearly, he long-erm rend in wages was he dominan acoron crime during his ime period.46

    hey coninue by observing ha he decline in he unemploymen rae did ex-plain much o he reducion in criminal aciviy ha occurred aer 1993.

    he declining crime rends in he 19931997 period are beer explained byhe unemploymen rae. he adjused propery and violen crime raes ell

    by 7.6% and 12.3%, respecively. . . . he 3.1% increase in he wages o non-college-educaed men predic a decrease o 1.7% in propery crime and 3.3%in violen crime. he comparable predicions or he 3.1% decline in he un-employmen rae are decreases o 7.5% or propery crime and 4.0% or violencrime.47

    he auhors include sae per capia incomes o conrol or he relaive prosperiyo he area, which has a heoreically ambiguous eec on crime. On he one hand,as average incomes increase, here is more or criminals o seal. On he oher, in-dividuals migh use par o heir exra wealh o beer proec hemselves againscrime. Beween 1979 and 1994 per capia incomes increased by abou 7.7%. Ac-cording o he auhors esimaes his is prediced o raise propery crimes byabou 4% (i.e., 0.54 imes 7.7%). Hence beween 1979 and 1994, he increase inper capia incomes explains abou 14% o he increase in propery crimes ha oc-curred during his period.48

    Freeman (1996), Freeman and Rodgers (1999), Grogger (1998), and Raphaeland Winer-Ebmer (2001) examine he eecs o labor-marke condiions on

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    26 Chapter 31: Crime

    crime. Consisen wih he indings o Gould, Weinberg, and Musard (2002)Raphael and Winer-Ebmer (2001) ind ha a 1% increase in unemploymenleads o a 1.6%2.4% increase in propery crimes. Freeman and Rodgers (1999esimae ha unemploymen and crime are posiively relaed, and ha each 1%increase in unemploymen raises he crime rae by abou 1.5%. Grogger (1998esimaes he crime-wage elasiciy lies beween 0.95 and 1.2.

    Black men earn subsanially less han Whie men (see Chaper 12). Moreovera subsanive body o evidence indicaes ha Black men are more likely o commicrimes han Whie men. Grogger (1998) invesigaes wheher his racial wage gapcan explain he observed racial dierences in criminal behavior and inds ha hegap does indeed go some way oward hem:

    Blacks ypically earn less han whies, and his wage gap explains abou one-ourh o he racial dierence in criminal paricipaion raes.49

    Groggers analysis is also useul or helping us undersand he age disribuiono crime. Recall rom Secion 31.1 ha criminal behavior declines rapidly wihage.50 Ye, earnings also increase wih experience because o he human capiaha is accumulaed hrough on-he-job learning. I ollows ha par or all o hereducion in criminal aciviy over he lie cycle migh hen jus represen he acha legiimae earningswhich capure he opporuniy cos o crimeincreas

    wih age.51

    DeterrenceIn addiion o he overall improvemen in labor-marke opporuniies, he las25 years also winessed an aggressive increase in policing eors. he signiicanc

    o his observaion is ha according o he economic model o crime, criminabehavior is driven by boh he value o crime relaive o legiimae labor-markeaciviy and by deerrence measures (i.e., policing eors and he penalies inliced on hose who are capured).52

    Policing.One o he mos surprising empirical resuls in his lieraure is he repeaedailure o uncover evidence ha an increase in he number o police reduceshe crime rae. O he 22 sudies surveyed by Samuel Cameron (1988) haaemp o esimae a direc relaionship beween police and crime using varia-ion across ciies, 18 ind eiher no relaionship or a posiive (i.e. incorrecly

    signed) relaionship beween he wo. Levitt(1997)53

    he greaes obsacle o obaining valid esimaes o he eec o deerrencemeasures on crime arises because o simulaneiy problems. Crime and lawenorcemen eors are joinly deermined, so crime-ridden ciies have larger police deparmens. As Levi (1997) succincly pus i,

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    31.5: The Economic Model of Crime: The Evidence 2

    Deroi has wice as many police oicers per capia as Omaha, and a violencrime rae ha is our imes as high, bu i would be a misake o aribue hedierences in crime raes o he police.54

    In an ingenious sudy, Levi (1997) gahers daa ha poenially allow himo overcome his simulaneiy problem. Speciically, he explois (exogenous)

    changes in police expendiures ha occur around he ime o mayoral elecionsin he Unied Saes. In elecion years here is a 2% increase in policing and innonelecion years here is no increase in policing a all. He inds ha addiionalpolicing has a subsanial deerren eec on boh violen and propery crimes.

    A 1% increase in police expendiures reduces violen crimes by 1.1% and properycrimes by 0.3%.

    Juvenile Crime. Levi (1998) examines he major deerminans o juvenilecriminal aciviy. Beween 1979 and 1993, he Unied Saes saw he juvenilecrime rae grow wice as as as he adul crime rae. he divergence in murder

    raes is paricularly sriking. hus,Juvenile murder arress rose 177 percen, whereas he murder arres rae oraduls acually ell 7 percen.55

    Levi presens evidence indicaing ha 60% o he juvenile crime wave is a-ribuable o relaive change in sancions.56 Mos imporan, congruen wihhe economic model o crime, juveniles are as responsive o legal sancions asaduls. he sronges evidence or his is he observaion ha here is a sharpreducion in crime a he age o majoriy (a which poin adul penalies comeino eec). his inding suggess deerrenceas opposed o incarceraion

    plays an imporan role. For violen crimes, saes wih lenien juvenile sysemswiness a 3.8% reducion in he crime rae, a he age o majoriy, bu hose saesha are ough on juveniles see heir crime raes increase by 23% a he age omajoriy.57

    Carrots and Sticks. Because o daa limiaions, relaively ew sudies havejoinly examined he eecs o criminal sancions and labor-marke condiions onhe level o criminal aciviy. Corman and Mocan (2002) is an ineresing excep-ion. he auhors examine he eec o economic condiions (carros) and sanc-ions (sicks) on murder, assaul, robbery, burglary, and moor vehicle he in

    New York Ciy, using monhly ime-series daa ha span he period 19741999.Carrotsare capured by he unemploymen rae and he real value o he mini-mum wage. hey proxy he severiy o he sticksby he number o elony arress,he size o he police orce, and number o New York Ciy residens in prison or

    jail. he paper also ess he validiy o he broken windows hypohesis, usingmisdemeanor arress as a measure o policing. heir evidence provides somesuppor or he hypohesis in he case o robbery and moor vehicle he. While

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    28 Chapter 31: Crime

    boh economic and deerrence variables are imporan in explaining he declinin crime, heir evidence indicaes ha he impac o deerrence measures is morepronounced han economic variables.

    Private Enforcement Efforts. here are imporan exernal eecs associaedwih privae enorcemen eors. I I lock he doors o my house, insall an expensive burglar alarm sysem, buy a gun, and so on hen, ceteris paribus, i becomes relaively cheaper or criminals o vicimize my neighbors. hereoreprivae enorcemen eors may displace crime oward soer arges and so havlile eec on he overall level o criminal aciviy. Criics, however, argue hahe exen o hese subsiuion eecs is limied, and ha privae crime prevenion aciviies is socially beneicial because i lowers he overall reurns o crimeand he number o crimes commied.

    In an ineresing sudy, Ayres and Levi (1998) examine he eecs oncrime (car hes) o he LoJack auomobile recovery sysem.58A noable eaure o LoJack is ha he vehicle has no visible indicaion ha he sysem is

    insalled in he car. I ollows ha, in areas in which he sysem operaes, carhieves canno simply arge heir eors a auomobiles ha are no ied

    wih he device. hey always run he risk o sealing a LoJack-equipped carhis eaure o he sysem eliminaes he negaive exernaliy associaed wihindividual enorcemen eors jus described, and i leaves only he posiiveexernaliy ha arises because auomobile he becomes less lucraive a hemargin. he auhors ind ha in ciies ha implemen he sysem, here is asigniican reducion in auo hes. In ac, on average, 1 car he is prevenedor every 3 auomobiles ied wih LoJack. (he auhors ind no evidenceha would-be car hieves swich oward he commission o dieren crimes.)

    From an eiciency sandpoin, i is likely ha oo ew people will purchashe LoJack sysem because hose who do purchase and insall i ail o capurhe ull beneis o heir acions, which resul rom he overall reducion in henumber o car hes.

    A debae is currenly raging concerning wheher greaer gun ownershipraises or lowers he crime rae. he argumen is simple enough. On he one handI migh buy a gun o proec boh mysel and my amily. On he oher, I migh hensubsequenly use he gun I bough (perhaps wih hese iniial legiimae goals inmind) o shoo Norbur (or one o an assormen o possible reasons). he ormer o hese eecs migh be expeced o reduce he average number o crime

    because i increases he (expeced) coss he ypical criminal bears in he commission o a crime. he laer eec, obviously, raises he crime rae. he eeco gun ownership raes on crime hereore depend on he relaive magniudes ohese wo orces.

    Duggan (2001) careully examines his relaionship empirically. Much ohe earlier research in he area suered rom a pleniul lack o reliable daa on

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    31.5: The Economic Model of Crime: The Evidence 2

    gun ownership raes. he auhor explois a unique daa se o accuraely esi-mae annual raes o gun ownership a boh he sae and he couny levels overa 2-decade span o ime. His main indings are ha changes in gun ownershipare signiicanly posiively relaed o changes in he overall murder rae and hahis relaionship is driven almos enirely by he impac o gun ownership on gun-relaed homicides. Almos one hird o he dierenial decline in gun-relaed ho-micides relaive o non-gun-relaed homicides, since 1993, is explained by recenreducions in he racion o households owning a gun. (his inding conrass

    wih Lo and Musard (1997), who ind a subsanial deerren eec o con-cealed handgun laws.)

    The Deterrent Effects of Arrests and Prisons. More people are arresed andincarceraed when he crime rae is high han when i is low. his simple ac olie leads o classic case o simulaneiy bias in esimaing he rue deerren eeco prisons. he reason is ha he raw evidence spuriously poins o he possibiliyha high incarceraion raes lead o more crimes being commied.

    Levi (1996) employs an ineresing approach o overcome his simulane-iy problem. Speciically, he uses daa generaed by he passage o legislaiondealing wih prison overcrowding o capure he eecs o exogenous changesin he number o incarceraed prisoners. he idea is based on he acs ha heovercrowding legislaion is driven by he size o he prison populaion (and nohe crime rae per se), and ha i leads o he early release o an exogenousnum-

    ber o criminals. His resuls are sriking: he beneicial crime-reducing eecs oincapaciaion are wo o hree imes greaer han hose ound in previous sud-ies. In ac, a one person reducion in he prison populaion is associaed wihhe commission o an addiional 15 crimes per year. (Mos ineresing, his num-

    ber is close o he number o crimes ha are commied by he median criminalrepored on page 4.)I is naural o ocus on he loss o reedom as he primary cosand hence

    source o deerrenceha an individual bears because o his arres and his subse-quen incarceraion. Ye, he consequences o incarceraion can exer a prooundnegaive eec on an individuals subsequen career developmen. he aemp oexplain o poenial employers ha he 30-year gap in your rsum resuled roma riple murder you commied in your youh may no go over ha well.59In hissense, he deerren eec o arres and subsequen convicion mus include heoal cos o all legal sancions, including ines, he value o los reedom, and he

    value o any reducion in expeced uure labor-marke earnings.60In an ineres-ing sudy, Grogger (1995) esimaes he employmen consequences o arres andincarceraion. o do so he merged longiudinal daa on arress rom he Caliorniacorrecion sysem wih unemploymen insurance records. he raw daa indicaeha workers who wen o prison had earnings ha were some 20% lower hanoher comparable workers.

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    Problems 3

    SUMMARY

    l Criminal aciviy is subjec o considerableemporal and spaial variaion. he 1980s wi-nessed a sriking increase in criminal aciviy

    and he 1990s an equally impressive meeoricdecrease.

    l he esimaed coss o criminal aciviy in heUnied Saes are huge. According o somemeasures hey exceed $1.5 rillion annually.

    l According o Beckers model o crime, individu-als raionally decide wheher o commi crimeson he basis o he ne perceived beneis.

    l In a general equilibriumseing, he reurns oboh crime and o ormal employmen dependon he number o paricipans in each aciviy.

    Muliple equilibria may emerge. Some equilibria have low levels o crime and high levelo employmen. Ohers have precisely h

    opposie characerisics.l here are poenially signiican replacemen

    eecs ha mus be accouned or in esablishing he eeciveness o incarceraing oenders

    l Empirically assessing he eeciveness o alernaive policies designed o lower crime icomplicaed because o simulaneiy issuesFor example, he level o policing is generallyhighes in neighborhoods where crime is mosprevalen.

    PROBLEMS

    P1.Describe he major rends in criminal aciviy inhe Unied Saes over he las 40 years.

    P2.Is i reasonable o model criminal behavior usinga raional choice approach?

    P3.he crime rae exhibis huge emporal and spaialvariaions. Why is his observaion a problem orheories ha sress ha crime is largely he produc obad genes?

    P4.Explain he role played by risk aversion in deer-mining wheher an individual chooses o commicrimes.

    P5.Larry, Curly, and Mo have allen on hard imesand are conemplaing esablishing heir own prin-ing business. Indeed, hey esimae ha i hey can

    ge away wih prining $10 bills, hen hey will eachpocke $10K. Neverheless, here is a 5050 chancehey will be caugh red-handed, sen o jail, andreceive only a meager $1 o consumpion during heirincarceraion. Larry is risk neural and his uiliy is

    u(c) = c. Boh Curly and Mo are risk averse, deriv-ing uiliy u(c) =

    -cand u(c) = log10(c) respecively.Despie he ac ha he earnings rom legiimaework are only w= $200, one o hem chooses hisopion raher han he criminal enerprise. Which

    one and why?

    P6.Why are relaively so many criminals youngmen?

    P7.Suppose he likelihood o alling vicim o crimediers beween criminals hemselves and ormalworkers. Indeed, suppose ha only ormal workersare vicims. How does his change he general equi-librium analysis?

    P8.Using a igure similar o Figure 31.3, show wha

    happens o he crime rae i (a) here is an increasedprobabiliy o arres, , and (b) here is an increasein he dollar value o each crime $a. Wha does hislas resul sugges abou he eecs o an increase ininequaliy on he crime rae?

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    32 Chapter 31: Crime

    P9.Examine he case in which he probabiliy oarres, , depends negaively on he number o crimi-nals C(or any given level o policing). Show hamuliple equilibria may arise.

    P10.Wha are he major rade-os ha sociey acesin choosing he appropriae amoun o spend on

    law-enorcemen eors vs. he severiy o he sanc-ions i mees ou on hose who are conviced ocrimes?

    P11.Wha are he main beneis and drawbacks oincarceraing hose conviced o commiing crimes?

    NOTES

    1. DiIulio (1996), p. 3.

    2. Te saisics perain o U.S. residens aged 12or older. See www.ojp.usdoj.gov/bjs/pub/pd/cv06.pd (accessed May 5, 2010).

    3. Freeman (1996) esimaes ha he oal cos o

    crime is abou 4% o GDP. 4. See www.ojp.usdoj.gov/bjs/pub/pd/cv05.pd

    (accessed May 5, 2010).

    5. Tere are some excellen and accessible surveysavailable o hose who are ineresed in pursuinghe economics o crime in greaer deph. Free-man (1999) sands ou or is clariy.

    6. Becker (1968), p. 170.

    7. Te Bureau o Jusice Saisics was ounded in1979. I is par o he U.S. Deparmen o Jusice.

    8. Source: www.ojp.usdoj.gov/Plan/ex/bjs.x(accessed May 5, 2010).

    9. U.S. Census Bureau, Statistical Abstract of UnitedStates(2003), p. 196. Te Statistical Abstract ofthe United States(various saes) is available awww.census.gov.compedia/saab (accessedOcober 20, 2010).

    10. Te erm white collar crimewas firs coined in1939 by he sociologis Edwin Suherland.

    11. Quoed by Srader (2002, p. 2).

    12. Unless saed oherwise, hese numbers reer ohe rae o crime per 100,000 persons. For rea-sons ha are all oo obvious, murderevidenlya violen crimeis no included in he NCVS.

    13. In 1980 here were 23,040 murders in he UniedSaes. See U.S. Bureau o he Census, (2000),

    able 312. By 2005 his number had allen o16,692. Abou 76% o murder vicims are maleand 90% are aduls. Firearms are used in 7 in 10homicides. Daa are available a www.i.gov/ucr/05cius/daa/able_01.hml (accessed May 52010).

    14. See BJS bullein (2006), www.ojp.usdoj.gov/bjs/pub/pd/cv05.pd (accessed May 5, 2010).

    15. See U.S. Bureau o he Census, (2000),able 310.

    16. Tere is some debae abou wheher ransersshould be couned as a social cos o crime.Tus i I break ino your aparmen and abscondwih your collecion o Dolly Paron CDs, hensociey gains i I value hem more han you;oherwise, i loses. Tis perspecive, alhough

    superficially plausible, ignores he value o heime I spend planning and execuing he crime;see Becker (1968). I also ignores an imporanex ane cos. Perhaps your Dolly Paron collec-ion is only a shadow o wha i oherwise wouldhave been in he absence o is prospecive hef.

    17. Source: Statistical Abstract of the United States(2007), able 306.

    18. Freeman (1996), p. 35.

    19. Indeed, according o Lochner (2004), wo

    hirds o he 1.35 million men incarceraed in1993 had no compleed high school.

    20. Source: htp://fp2.census.gov/govs/apes/06slus .x (accessed May 5, 2010).

    21. See htp://www.census.gov/compendia/saab/ables/08s0318.pd.

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    22. Source, able 350, U.S. Census Bureau Statisti-cal Abstract of the United States(2007). Almos2.3 million persons were incarceraed eiherin jail or sae/ederal prison. Over 4.2 millionpeople were on probaion, and almos 800,000were on parole.

    23. Quoed by Freeman (1996), pp. 3738.

    24. Anderson (1999), p. 621.

    25. Anderson (1999), p. 623624.

    26. Benham (1830), Bk. 1, Ch. 3.

    27. Te model is an amalgam o ohers ha are seenin he lieraure. In paricular, see Becker (1968),Ehrlich (1973), Block and Heineke (1975), andFreeman (1999). I is easy o exend he modelpresened here o oher crimes, such as raud and

    violen crimes.28. Some o he mos exciing work currenly being

    underaken is unquesionably ha perainingo he dynamics o criminal aciviy. One o hemos eloquen call o arms in his area was madein Merlo (2001).

    29. Tese issues are deal wih horoughly in Blockand Heineke (1975).

    30. Freeman (1999), p. 3543.

    31. Freeman (1999), p. 3551.

    32. Tis ormulaion is quie general. For example, is= a n c0hen he apprehended criminalsuiliy is simply U(c0). Tis corresponds o hesiuaion in which (say) he sae confiscaeshe criminals ill-goten gains and provides some(possibly minimal) level o consumpion $c0.

    33. Te model can be exended o he case in which,or example, criminals ace a lower (or greaer)likelihood o alling vicim o crime han legii-mae workers. See, or example, Murphy, Shleier,and Vishny (1993).

    34. DiIulio (1996) describes hese privae anicrimeacions as target hardening.

    35. Criminal aciviy is overwhelmingly concen-raed among young innerciy men. As a conse-quence, a reducion in he racion o young menin he populaion is prediced, ceteris paribus, o

    lower he crime rae. Indeed, he auhors reporha in 1980 almos 21% o he populaion wasaged beween 15 and 25. By 1996 his racionhad allen o only 15.1%.

    36. Tis ormulaion is an adapaion o he em-ployee crime models o Becker and Sigler(1974) and Dickens, Kaz, Lang, and Summers(1989), in which firms pay efficiency wages odeer maleasan behavior.

    37. Sigler (1970), p. 527.

    38. Singapore does imprison and cane hem hough.In 1994 he Singaporean High Cour dismissedAmerican suden Michael Peer Fays appealagains a senence o 4 monhs in jail, and sixsrokes o he cane or vandalizing wo cars.

    39. Friedman (1999) offers a hird reason: corrupion

    among law enorcemen agencies. Under a sysemo fines, some agency benefis rom he fine. I heranser is large enough, hen i is in he agencysineres o seek a convicion regardless o acualguil. Moreover, law enorcemen agencies have anincenive o hreaen o prosecue he innocen,unless hey receive a suiable paymen.

    40. DiIulio (1996), p. 18.

    41. Ibid.

    42. Freeman (1996), p. 25.

    43. Since he wage is consan, i is sae o ignore iseffecs on a.

    44. See Bound and Johnson (1992) and Kaz andMurphy (1992).

    45. wo early sudies ha documen a posiive effec ounemploymen on crime include Canor and Land(1985) and Freeman (1983). ser and Agell(2007) documen ha as much as 15%20% o hreducion in burglaries and auo hefs winessedin Sweden during he 1990s is atribuable o he

    decline in unemploymen ha occurred over heperiod. (For people under he age o 25hosemos likely o commi crimesunemploymendecreased rom 21.2% o 8.7% during ha ime.)Nilsson (2004) demonsraes ha income inequaliy levels are an imporan conribuory acordeermining he Swedish crime rae.

    Notes 3

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    34 Chapter 31: Crime

    46. Gould, Weinberg, and Musard (2002), p. 50.

    47. Ibid.

    48. Ehrlich (1973) was one o he firs o recognizehe imporance o per capia incomes as a pos-sible deerminan o criminal aciviy.

    49. Grogger (1998), p. 787.50. Grogger presens evidence indicaing ha

    criminal paricipaion raes decrease rom 37.5%among 17- o 18-year-olds o 18.9% among 22- o23-year-olds.

    51. Some auhors have argued ha he effec o ageon crime is essenially inexplicable. Tus Hirschiand Gotredson (1983) have argued ha he ageeffec is direc and invarian, and simply can-no be accouned or by any . . . combinaion o

    variables . . . currenly available o criminology.Quoed in Grogger (1998, p. 786). Regardinghis possibiliy, Grogger concludes, [W]ageslargely explain he endency or crime o decreasewih age, a phenomenon widely observed bycriminologiss. . . . Wages represen he opporu-niy cos o crime and are well-known o rise wihage (p. 787).

    52. A seminal sudy in his area is Ehrlich (1975),who atemped o measure he deerren effeco capial punishmen. Wite (1980) and

    auchen, Wite, and Griesinger (1994) uncoverevidence poining o a subsanial deerrenceeffec.

    53. Levit (1997), p. 270.

    54. Levit (1997), p. 270271.

    55. Levit (1998), p. 1156.

    56. For aduls, incarceraions per violen crimeincreased rom 0.34 o 0.54 (a 60% increasebeween 1978 and 1993). Te juvenile crime raeell rom 0.36 o 0.29a decline o 20%seeLevit (1998, p. 1155).

    57. Here he key is o look a he relaive gap be-ween juvenile and adul punishmens. Tus,consider a sae ha is lenien on he ormer andharsh on he laer. In his case, an individual acea siff increase in penalies a he age o majoriy,which is prediced o reduce he crime rae (ahis poin). In conras, a sae ha is ough onjuveniles and aduls experiences no such relaivechange in penalies.

    58. LoJack involves he use o a small radio ransmi-er ha is hidden somewhere in he car. I i isrepored solen, he auhoriies can hen rackhe car, deermining is precise locaion.

    59. Te loss in earnings could arise or any one oa variey o reasons, including sigma effecsor rom he loss o skills ha resul rom anexended period o incarceraion.

    60. Waldogel (1994) presens evidence indicaingha here is a large negaive effec o arress onuure earnings.

    61. Grogger (1995), p. 61.

    62. In an ineresing sudy, Glaeser and Sacerdoe(1999) urnish evidence ha also indicaes heimporance o demographic acors or under-sanding changes in he incidence o crime. Teyshow ha he preponderance o crime observedin large meropolian urban areas is explained byhe large number o single-paren households.

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