CAN DRUG ARRESTS PREVENT CRIME?
John Calvin Jones, PhD, JD
Abstract
The American War on Drugs has been sold as a bill of
goods. Included in the promised
benefits of drug prohibition is a lower crime rate. Using data from the two industrial democracies with the greatest
disparity in drug law enforcement, the United States and the Netherlands,
regression analysis finds no evidence to support the claim that drug arrests
lower crime.
Keywords:
drugs, crime, drug policy, war on drugs, drug war, property crime, drug arrests, Netherlands, United States
Biography:
Jones earned his PhD (political science) and JD from the University of Iowa. He currently teaches in the department of Government at South Texas College, Mid-Valley campus in Weslaco, Texas. His research interests are drug policy, addiction theory, civil liberties, media and politics, and HIV-AIDS theory.
Contact information:
Biko97jcj@hotmail.edu
1804 W. Washington Street
Brownsville, TX 78520-6660
BACKGROUND AND CONSIDERATIONS
Defining a Problem
Among the industrial democracies and their approaches to control drugs there are two supposed extremes. On the one hand, we see the United States with a prohibition policy so draconian that individual prison sentences of 100 years or more no longer shock the ear. Taken in its entirely Korf (1995) regards U.S. drug policy as the archetype of drug criminalization. On the other hand, there is the Netherlands with its so-called harm reduction model (Nadelmann et al. 1994). The Dutch state is so permissive as to provide heroin to citizens (Algemeen Dagblad 2002a) and tolerate marijuana “coffee shops” in nearly every city. In July 1998, During the CNN show “TalkBack Live” then American “Drug Czar,”[1] U.S. Air Force General (ret.) Barry McCaffrey claimed that “the Dutch experience … has been an unmitigated disaster.” McCaffrey added, “you must be crazy to make it easier for young people [to use drugs] … and that is essentially what the Dutch have tried to do” (CNN 1998).[2] Less than a week later, while touring the Netherlands, McCaffrey said that, due to its cultural and governmental tolerance toward drugs, the Netherlands suffers a per capita murder rate double that of the U.S. (San Francisco Chronicle 1998).[3]
The claim was erroneous and quickly corrected by Dutch
officials, Interpol, and international reporters, but the corrections were
nearly irrelevant. Nearly irrelevant because American advocates of drug prohibition,
like McCaffrey, do not want to know “the numbers”[4]
and the public has little interest in learning about the iatrogenic effects of
drug prohibition. Apparently neither
the American press nor anyone else is supposed to question Drug War dogma and
its fantastic ideas. This paper,
however, does question the logic and actions pursued in the name of the
American War on Drugs. And as a means
to see understand the effects of drug policy, I compare crime data in the
United States and the Netherlands. In
particular, I test presents arguments and data about the
relationship, if any, between enforcement of drug
laws enforcement and rates of property crime
rates.
Constructing a Research Question and Sample
Criminological research has dismissed and many American
officials have abandoned the claim that drug use induces individuals to commit
crime via some drug-induced psychosis (Grinspoon and Bakalar 1985; USSC
1995). Setting aside arguments about
pharmacological crime, supposedly certain dThe assumed
economic connection linking certain drugs are linked to property
crime as a
function of economics
(Brecher et al. 1972; DEA 1994a; DEA 1994b). We
are told that drug abu, i.e. the“addict” sers cannot earn
enough money legally to pay for their drugs therefore they steal as a means to have money
for drugs (Brownfield 1996b; O’Reilly 2003). The world over, this
reasoning has been
used as a primary justification for
interdiction efforts against drug trafficking (Brownfield 1996b, 126). Among other claims then, Because
ddrug
prohibition ihas been presented to Americans as a policy for reducing crime,
but d reductionoes it?
To test the efficacy of drug prohibition, operationalized
as arrests for drug offenses, I review law enforcement practices and property
crime rates in two American and four Dutch cities. To measure the effect of drug policy, a city-level comparison,
not a national one, is most appropriate.
Generally cRecall from onefor reasons related to theory and comparability, the
evaluation here will only First because I am seeking to measure the effects of
a police activity in the form of a policy, drug (de)criminalization, on overall
crime rates, property rather than violent crime is a better topic of
study. The reasons are multiple
including the idea that deterrence and or the effects of police activity most
readily prevent property crime as violent crimes are more spontaneous (Gillis
1996b, 86).
At the levels of geography and
demography, cross-national studies of public policy provide
suffer
problems of from undue dissimilarityies at the levels of demography and
geography. Because
of the variance at the national and state levels between the U.S. and the
Netherlands, a city-level analysis offers the best point of comparison. Despite differences in the
federal and state/ or provincial contexts systems of for city government
hence, when comparing the United. States. and the Netherlands, cities offer the most
commonality in populations, governing
structures, and social
problems. As Cho (1974) (1974)
writes, “cities are the basic units of government that make or implement public
policy” (113).
More pointedly for the research question presented here,
sFurther, when investigating the effects of policing or
law enforcement, studies show that local police techniques can reduce crime
rates – at the city level (Brown 1978),, but not at state (regional) the or national levels level
(Logan 1975). When
city-wide arrest rates are sufficiently high, greater
than pass
the threshold of 30% (for a particular category of offense), then reis a negative ionbetween arrest and crime
rates
decrease (Brown 1978, 672). Brown’s
premise is strengthened from 1970s crime data of California. In a sample of 67 cities he found that when
arrest probabilities were less than 25% for given FBI index crimes, the
relationship between arrest and crime rate was practically zero (Brown 1978,
673). Hence given the parameters and
object of this study, there is reason to examine the effects of policing at the
city-level, which can control crime via arrests, though State and national
governments cannot.
Despite the theoretical justifications for city-level
comparisons, we must acknowledge that Nagin (1978) (1978)
finds cross-sectional studies of crime suffer because police in
different jurisdictions have different recording practices (97). This means that cross-national data mayight not be comparable. When A reviewing police of local and state
crime records about in the U.nited S.tates and the
Netherlands, however, reveals property -crime reports are to be the most uniform. Tnd hough
official crime statistics are rife with problems troubles of
reliability and validity (Zimring and Hawkins 1973; Russell 2003), a fter comparingson of victim
surveys and police reports, Zimring (1978) concludes
suggests that
there is little reason to doubt the accuracy of police records for crimes against
property (Zimring and
Hawkins 1973). To focus on the relationships between police
activity and property crimes then then seems
the least problematic in a field of investigation open for
a number of to many methodological criticisms.
DRUG WAR IN PRACTICE FROM THEORY
According to a sheriff in San Francisco County, California,
“Drug dealers and users consumed the single most valuable resource in the
criminal justice system: jail
cells. We desperately need the limited
space in our nation’s jails and prisons to house violent offenders, not minor
league dope addicts and dealers” (Kopel 1994).
But under the present
American War on Drugs , replete with itsprovides
incentives for police to make drug arrests, the ease of
makes
convictions
relatively easy (Callahan 1998), and the imposesition of mandatory minimum sentences.
As measured by arrests and convictions, America’s War on dDrugsw
has markedly escalated markedly since
the early 1960s
(Rasmussen and Benson 1994, 4).
In the United States, drug arrests per capita hundred thousand people rose
from 26 in 1960 to 538 in 1989 (Rasmussen and Benson 1994, 46-7). Since 1980 tDrug convictions have become so
prevalent in the 1980s that across the U.S., 44% of the increase in Sthe tate -prison
populations
from 1986 to 1991 was attributable to came from drug convictions
(Kopel 1994). About 220,000 drug
prisoners were held in State prisons in 1995, more than and
that number represented over a 1,000 percent increase increase from over 1980 (Serendipity 1998).
By 1996, (1997) the U.S. prison
population added about some 56,000
persons to a reach a new record, over 1,180,000 inmates in the federal and
state systems combined (McCaffrey 1997).
The population grew with nearly 225,000 convicts sentenced for drug
offenses alone between 1985 and in 1995
(McCaffrey 1997). had
ed By
June 2001, American prison and jail populations swelled to house
nearly two million (Beiser 2001; BJS 2002). Hence America had added about 160,000 people to its prison
population every year between 1996 and 2001.
This
exceeded the record pace of the previous ten years: What may be most remarkable to
consider is that from June 1984 to June 1995, the number of
inmates grew by roughly a then-record of about 90,000
a year (AP
1995). Though some sheriffs and others
in law enforcement, e.g. LEAP, see drug arrests as harmful and wasteful
(McNamara 1999), the public is assured by the likes of Congress members Mica
(R-FL), Souder (R-IN) and McCain (R-AZ) that suchTsignificant
then, as raised here and by Kopel (1994) is, arrests lower crime. Do they?
Thoughts on Drugs and Crime
In studying the etiology of crime, the term
“drug-related” is often unhelpful and misleading. The concept fails to distinguish between crimes caused by the
pharmacology of drugs and crimes related to participation in the drug trade
(NYCLA 1996). The latter
second
set is better understood as “drug-prohibition” related
crime (NYCLA 1996).
According to Ostrowski (1989), supporters of drug
prohibition frequently use the argue that “drugs
cause crime.” argument.
Their motto logic is: Stop drug use, and and
crime will be reduced significantly. Part of the argument declares:
“The use of drugs, especially cocaine, crack, PCP and methamphetamine, is often associated with violent criminal behavior. There is no denying the fact that drug use changes behavior and exacerbates criminal activity” (DEA 1994b).
The argument is not unique to America. Even Dutch officials believe that addicts commit a disproportionate number of property offences solely to get money to buy drugs (VWS 1995a).
It turns out, however, Yet the evidence
linking drug use and crime is weak at best.
There is no simple connection between recreational drug use and criminal
activity (Chaiken and Chaiken 1990).
Consistently Such is perhaps most true because ostudies
find that deviant or illegal behaviors are correlate positively
correlated with one another (Brownfield
1996b, 125). The correlation
means it is As well there are difficult to
find a causal links. Anglin and Speckart (1988) note that most
individual-level studies that find positive correlations betweenconnecting drug use with
and criminality, i.e. where any positive correlation was found,
suffered from selection bias.: Namely, such studies they merelycounted numbers of and
were also affirmed userroutinely
. These studies never examine ignore the vast
majority of illicit -drug users who
are outside of and or never go to prison (Brownfield 1996b, 130).
Most drug users commit neither index
or violent nor property crime (Kim et al.
1990). Users who engage in
crime routinely, their typical offenses are drug dealing and prostitution (Leuw
1994; Korf 1994). And while most
criminals use illicit substances, they started drug use their
drug career after startlaunching criminal careers (Osgood et al.
1988; Kim et al. 1990; Inciardi and McBride 1991; Brownfield 1996b).
Another problem with tThese
observations were confirmed by From sheories linking drug use and
property crime are activity wrong-headed
assumptions about the inevitability of escalating use patterns and or the idea
that heavy drug use or addiction leads to social dysfunction, being able to compelling the addict to steal to
support a habit (Brownfield 1996b, 129; O’Reilly 2003). EDespite a lack of mpirical
research to does not show most drug users consume ever
more drugs in escalating patterns (Maddux and Desmond 1979; Peele 1985).[5] In fact ,principle drug
use patterns are variable and reversiblelogic and (Ball et al. 1981; Biernacki
1986). Even if we believed
that drug use “caused” property crime, the
intervening variable must be drug prohibition: the black market tariff raises prices astronomically. Without prohibition, the link between drug use,
per se, and property crime collapses (Staley
1992).[6] for one tTo accept the
addict-crime hypothesis under a condition of drug prohibition is to acknowledge
what the New York City Lawyers Association (1996) rightly frames as
“drug-prohibition” related crime.
Another familiar assertion It is often argued that
illicit drugs cause crime through biochemical effects on the user’s brain. Early in the twentieth century, Ssuch claims
justified served as restrictions on
marijuana and cocaine in the early part of the 20th
century (Bonnie and Whitebread 1970; Ostrowski 1989) as Initially eofficials claimed that marijuana
caused insanity, promiscuity, and prompted used heinous
acts of violence (Anslinger 1937; Rock 1977).
Despite federal research, some from as far back as 1951 (Isbell 1951),
that demonstrated edmarijuana did not provokes neither violence, hyper-sexuality nor crime (Bonnie
and Whitebread 1974, 213; Earleywine 2002) myths persisted
and persist. As recently as In a September 2002 editorial printed in the Detroit News, current the dDrug cCzar,, John Walters,,
claimed claimed that “it is not true that marijuana
makes you mellow... it increases tendencies towards stealing, isolation,
fighting, and violence.”
Walters’ charges are amazing considering the findings of
reports commissioned by Presidents Johnson and Nixon. Taking the studies reports on at face value, Goode (1984) (1984) ofinferred that “the notion that marijuana causes
crime is no longer taken seriously by even the most ardent [anti-] marijuana
propagandists” (124).
Though people might feel comfortable dismissing claims
linking marijuana and violence, many still Generally it
is assumeed that harddrug[7]
users are highly criminal. Dutch law
enforcementrs commonly considers
that regard
drug use ias the underlying
motivation for property crime (NIAD 1995).
Looking at hard
drug users, Hhowever, among in
Amsterdam a majority (63%) of Dutch addicts can afford their drugs use through legal sources of income, usually such :work,
or government aid, or prostitution. Only a minority, ,15%,, earneded
a living from drug sales , and only 22% ever committed a property crime
to earn money to buy drugs (NIAD 1995).
Nurco et al. (1988) and others (1988) found report that cocaine and heroin users
typically engaged in more crime when their
frequency and intensity of use increaseds (418). But their study treats However
within the categories of crime, Nurco et al. (1988) included drug
trafficking as criminal and drug-trade
crimes accounted for over 50% half of all the offenses Nurco et al. (1998) reported in their sample
(Nurco et al. 416). And As well, tFor all subjects, activities of prostitution
and gambling constituted another 30% of their
criminality in their sample (416). We
must be skeptical of claims linking drug use and property crime if, as Nurco et
al. (1988) concede, Nurco et al. (1988) note, property crime is one of the least
likely recourse
of drug ways that drug user who
wants money.
In sum, When reva matter of the
most apparent observations about the main relationship
between drugs and crime are is that criminal
careers precede drug use (Inciardi and McBride 1991; Fromberg 1994). Perhaps what is more
significant is Beyond that, the common correlates of crime and drug use
suggest that other factors promote their concurrence (Brownfield 1996b, 134). And perhaps most importantly, the drug most
often associated with crime in the United States is alcohol (Roth 1994; Parker
et al. 1998).
Crime as a Sign of Social Control
When we put aside questions of drugs as pathological, what we should recognize
is that social -control
mechanisms help create
crime and construct the criminal (Nixon Commission 1972; Kääriäinen 1996). “Social control is the
organized way society responds to criminal, deviant, threatening, immoral and
undesirable people and behavior” (Cohen 1985, 1). So Without noting the politics that
underlie legal definitions of crime, (1985) introduces the idea that the
state simply classifies certain some behaviors as criminal, no matter how consensual, e.g. (sexual, commercial, or
recreational) , as criminalthey might be.
To put it succinctly, iStates
allow for some define types of crimes that enable them to execute
perform
“legitimate” functions like arrest and imprisonment that
because
these reinforce modes of controlling social conditions control and notions of who and what is
deviant (Foucault 1977; Black 1984; Tannenbaum 1994). Though Lowman (1992) (1992) argues
that crime statistics are not merely artifacts of police activity, he warns “it
would be misleading to interpret [crime statistics] as not being influenced by
police practices” (235). Police recognize the enormity of the realities of both violent and property
crime leave police to admit they can do little to prevent crimes of passion or calculated theft, let alone crimes of
passion, so one means to Hence as the means
treduce counter public criticism in general, is for t rates to crack down on successes
in the area of and problems with drugs. sLaw enforcementment repeats familiar mantras,
of “where are turning the corner”
(Levine 1999) and stress what they can do “with more resources....” (Levine 1999). Along with the rhetoric comes – ingdrug -related activity.
EBeyond a simplistic political/power
perspective, From we see conomic incentives members
within the criminal -justice system
help to explain greathow the state fights crime (Cohen 1985). Under the present
regime dDrug crime and its
creation, which it is relatively cheapinexpensive to create as
and is
the institutional
fuel is most favored by police,
prosecutors, and prison officials (Dyer 2000).
Clear
(1996) points out that eClear (1996) reports that
each urban drug arrest , often through
,represents means rateehome ,is a
sizable boon
to a prison “prison community as
incarceration costs range .”anywhere from Each prisoner represents $25,000-$60,000
annually (Mergenhagen 1996)for the community where the
prison is located value facility (Clear
1996). From a policy
standpoint, we are still left to wonder, This brief
overview provides cause to accept theoretical and ideological what
is the effect of a drug prohibition on property crime?
Like any cross-national study, comparisons of Nevertheless wAmerican and Dutch criminal
justice systems have differences systems in
questionshould be able to .
Further though much police work is unrecorded (Russell 2003) and reliant
on informal social controls if not non-events (e.g. episodes of non-crime), political/power drug arrests in each nation are
similar if not identical metrics. Using
this one tangible record of police work then, that I
can construct a cross-sectional time-series analysis model of property crime
that controls for its common correlates: ,age-s, poverty, and race and , etc.
as well asevaluate the efficacy of drug arrests.
UNDERSTANDING PROPERTY CRIME: Police Practices and Other Correlates
As noted above I understand that
pProperty
crime is a function of multiple various social
phenomena that including:e policeing, various population demographics, and economic
variables. Sherman (1996) and others
observe that politicians, publics, and police often hold that “the more police
we have, the less crime there will be.”
But whether police can prevent crime depends on their objectives, job tasks, and performance (Sherman 1996).
Instead of confirming such the conventional commonsense wisdom, social scientists findfind that
police make only minimal modest contributions
to reduce crime in comparison to far like the familyies and labor markets
(Sherman 1996). In fact, Hence Sherman (1992) (1992)
insists that research on the etiology of crime has not settled the
debate about the effects of policing in reducing on rates of crime
(160).
Nagin (1978) (1978) found some support for the idea that increasing the
number of police per capita, at the city-level, and increasing police
expenditures have a negative relationship with decreases crime
(108-110). But this is Nagin’s findings probably best fit under limited
scenarios. not always true. A review of 36 thirty-six quantitative
studiesof them found detected little
evidence that “more police reduces crime” (Marvell and Moody 1996).
The findings of Marvell and
Moody (1996) probably show that institutional culture, more that political
objectives and directives, controls resource application. PFirst and foremost olice
often iesve by which they pursue given objectivesdefine their ends and means
(Gillis 1996b, 77). AAs one Dutch criminologist notes, ds one Dutch
criminologist observes, “it is long well-known that police, on the
street, create their own crime solving strategies” (Horn 1988, 375).[8] And iOnce goals are
setn
light of their own culture, policement
takes “rational” reasonable steps,
in line with standard operating procedures, to achieve their goals most most efficiently (Simon and Burns 1997; Levine
1999).
The
rational moves Police prefer take
various forms ingto the make of arrests for crimescrimes with high conviction rates and strong
public affirmation,
e.g. drug bustsor certain (Simon and Burns 1997). At the same time, wWhatever their plan or course of action though, there are
opportunity costsas . For instance, decisions
to establish sobriety checkpoints designed
might reduce drunk-driving accidents, but such efforts tax law
enforcement enough
to reduce the likelihood of arrests for other crimes (Sherman 1990; Benson and
Rasmussen 1991). As
Sherman (1992) insists, above all else
By the early 1990s, Dutch police recognized that opportunity
costs limiteded their effectiveness in
reducing crime. Such
a was based on observations by government officials After national
and local authorities placed relatively gave more
attention on to organized crime, namely
the trafficking of women,
drugs, and weapons, Dutch officials understood assert
that given their limited resources, the direct effect of such a plan was that
arrest and clearance rates for property crimes could not climb above 10% (VWS
1995b, 423).
Each year between 1981 and 1989, Sas
tate-wide
conviction and incarceration rates for drug offenses in Florida increased,; and each year, state-wide
there was a correlative 20-34% decrease
in the probabilityies of arrest for
property crimes and
violent crimes (Rasmussen and Benson 1994, 96-98).[9] And dDespite the added
drug arrests, no particular there was no evidence that crime
rates diminisheded. From tIn
fact, increases in when the relative number of drug arrests, relative to arrests for property
crime, correlates with an arrests increases,increase in rates of property crime rates also rise (Benson and Rasmussen 1991,
106).
Appreciating that Given
the theory and data noting the effects of drug arrests as pose opportunity costs in
the for
controlling
of property crime, we can understand these relationships
symbolically as follows:
Drug Arrests ® Property Crime Arrests ¯ (Benson and Rasmussen 1991; Gillis 1996b)[10]
Property Crime Arrests ® Property Crime ¯ (Tittle and Rowe1974)
\ Drug Arrests ® Property Crime
On the basis of this Hence
the model, will seek it makes sense to
test thise proposition,
that drug arrests increase property crime,. in an effort to verify
Sfoundationauthors cholars who research
the subject generally agree find that
certaincertain statistics correlate strongly or significantly with property crime. That is, various
schools of thought are resigned to filter through the same data and induce
mechanisms of the etiology of crime.
Given such constraints, I too am left to examine those variables
commonly understood as most logically related to the phenomenon of property
crime.
General observations from
academics in fields from economics or sociology, attempts at forming
econometric models of crime note relationships between crime: (a1) gender, (i.e., the number of males in a population (Korf
1995)); (b2) age-cohorts, because (teens and young adults are most likely to
commit street crimes
(Korf 1995)); (c3) ethnicity, (i.e., the numbers of non-WWhites (or
non-Northern Europeans in the developed nations));
(d4) aggregate educational levels; and levels
of nd(e5) income and (6)
(un)employment
(Hirschi 1969; Chiricos 1987). While nNo model is definitive, but research a sampling of the literature shows that modeling
the etiology of crime should account for include these
variables in some respect.
It is well-known that there is a The correlation
between age and crime is clear (Clinard 1968). PWhen talking about roperty
crime careers, like other deviant acts of
deviance including drug use, there is a
natural ingdeviant thenstart
in the teen years (Mackenzie 1996) and usually end by the late 20s. So we find that
jWithout making overt declarations about the roles of age and gender in crime
As Hirschi (1969) argued that, for youth, unemployment ties significantly
associated with their to involvement with in crime (Brownfield 1996a, 107). A study of crime in Amsterdam (Korf 1995)
shows that drug use matters little, but to might we
attribute then Among other factors, ethnicity, homogeneityunemployment, rates and household income may account for up
to 80% of urban crime.
Property crime decreases correlates with
increases in ethnicity homogeneity,[11]
education levels, and employment rates.
Education and employment are even more important as applied to
minorities (Kalmijn and Kraaykamp 2000).
Using American data, Sjoquist (1976) found that “non-WWhite”
population correlates
positively and was significantly and positively correlated to with crime. The eExplanations for the data are fairly straightforward. The first ties to One is racism
(Banerjee et al. 2000).[12] Turk (1982) notes that vagaries in the law
and discretionary enforcement allow the state to target
and criminalize certain specific sets classes of people (Gillis 1996b, 83). The second reason is
subtler. Another is skill. In Western nations, higher paying jobs
in the service and information sectors demand literacy and educational
attainment beyond high school (Rifkin 1995).
When certain groups, like rRecent immigrants or long-standing ethnic
minorities, who lack language skills and formal education, they are at a competitive disadvantage in the labor markets (Arts and Nabha 2001).
In the Netherlands, there are four significant ethnic
minorities: Moroccans, Turks,
Surinamese, and Antillians. A Randstad[13]
study reportfound that 70% of all juvenile crime
suspects were from these four ethnic groups though they made up only 40% of
their cohort (VWS 1995b, 422).[14] Above all others, Moroccan
teens were most over-represented.[15] By 1996, the Dutch Ministry of Domestic
Affairs, the Binnenlandse Zaken, their and confirmeded
widely-held suspicions that minorities in
general, especially Moroccans especially, weare disproportionately active in crime
(Banerjee et al. 2000).[16]
Age, ethnicity, and educational attainment are perhaps the
three most significant factors tied to correlates of employment
and, in turn, income. Hence as Because age, ethnicity, and education are
endogenous to employment and household income (conversely
poverty), they must be addressed accounted
for if, – as Gottfredson
and Hirschi (1990) claim ,– the root
causes of crime are unemployment and poverty.[17]
MODELING PROPERTY -CRIME RATES AND DATA ANALYSIS
Street
crime in the form of zakenrollen, roverij, and straatroof (pick -pocketing,
robbery, and muggings) cannot be explained simply well simply by
quantitative evaluations of “criminal opportunities” and poverty rates (De Haan
1993).
If police practices can reduce crime rates, it should be easiest to measure the effects of the policeing on property- crime rates,
that category of crime most controllable through patrols, stings, and
crackdowns, should
be easy to measure (Kleiman 1988; Sherman and Rogan 1995). Given theory and past findings (Tittle and
Rowe 1974), t
o test demonstrate the
plausibility of a causal connection between drug arrests and property crime, analyses we should control for demographic variables
like age, income, ethnicity, population, as well as police resources (Benson and
Rasmussen 1991; Brownfield 1996b, 127; Cho 1974). Hence Hence, given I hold that the
number of property crimes (PCR) committed annually, in a city, on a yearly basis can be expressed as the
function a function in the following manner:
PCR = f(Pol,
PCA, DA, Pop, Y, NWP, NWY, Inc and Un),
Police
(where Pol) represents
is a
measure of
the number of police officers in a city for a given year;
Property
Crime Arrests (PCA) presents is the number of
arrests for property crimes arrests such as robbery,
breaking and entering, and larceny within a the city for a particular that year, measured
in absolute number for offenses like robbery, breaking and entering, and
larceny;
Drug
Arrests (DA) is the absolute number of arrests for drug
crime arrests in a given in the calendar
year;
Population (Pop) is the city’s total population for a given year;
Youth
(Y) is the areacity’s total youth and or young adult populationnumber of youths and
young adults, ranging in ages from 15-24, measured in
absolute number the same year;
Non-White
Population (NWP) represents a is the city’s
non-WWhite population (as defined as
non-Western European, e.g. Black, Latino, Indonesian, etc.), as measured in absolute numbers of people for a given year;
Non-White
Youth (NWY) is for the city’s population of youths and young adults of the population, againabsolute non-WWhites
demographics between the ages of 15- and 24;
Inc
represents is the city’s per -capita income within the city in real dollars that year (with 1996 as = the benchmark); and
Un
is the city’s rate
of unemployment
for the year;.
Data: availability and explanation
Using The data from
government documents and library records come from six different
jurisdictions: ,Dutch cities of Amsterdam (n=6), Rotterdam
(n=3), Utrecht (n=6), and Haarlem (n=6); and American cities of the
Netherlands, and Raleigh, North Carolina (n=20),, and San Francisco, California (n=8), I.
With figures covering years anywhere from 1975 to 1995, the
cross-section, pooled-time series model has an N of 49.[18]
Due to rRecording
problems, that is due to the
unavailability of data and or limitations
ofn cross-national comparisons, I was not able to keep me from incorporateing all the desired variables desired. First pPolice budgets, available , though obtained for the American data pointcities,, were
are not
accessible for each Dutch city in the sampley. Secondly iSecond
city governments in the Netherlands, gemeenteraden, (city governments) are
responsible for reporting arrest rates and property crime arrest rates., In my data set, various but several offices
and reports fail to present
such collect
these data annually. WhileT
American jurisdictions regularly report such figures, due in part to federal
assistancesuch , the Dutch lapse
prevents the in this instance I cannot use
of a
“property crime
arrest”
variable to make cross-national evaluations directly.
A Tthird limitation arises because information on
youth and young -adult
populations was is not
readily
available in accessible for each jurisdiction. Lastly though sSome unemployment
data wasere available at the regional and
national levels, but
not for the cities of again, such was not
published San Francisco and Raleigh for for
the particular years neededat issue. Ultimately Therefore, the
base model (M1) employeds five
independent variables to explain property crime rates as a function:. Hence I offer the following model, Cr = f(Pol,
Pop, NWP, DA, PCI),. Awhich I ps
a linear equation, the form becomes:
Y = a + b1X1 + b2X2 + b3X3 + b4X4 + b5X5 + e
where where Y represents is the number of property crimes for a city
in a given year,. t X1 is the actual
number of employed police officers/personnel (Pol) employed in a by the city (Pol);. X2
is the city’s total population (Pop),. X3 is that city’s non-WWhite (non-European) population (NWP),. X4
is the number of drug arrests in a given that year (DA),. aAnd X5 is per capita income for a particular the city in 1996 U.S. dollars (PCI).
From Table 1 (below) we see the results of regressing the
independent variables on the dependent variable.
M1, with only the five independent and unmodified variables, per year calculations
were as followsdemonstrates an excellent goodness of fit with its
high adjusted R2 value (.961) and relatively low standard error of
estimate, less than one-fifth of a standard deviation (Berry and Feldman 1985,
16).
One explanation of for the high adj.
R2 mayight be
multicollinearity among in the independent
variables. The presence of multicollinearity,
where one or more independent variable strongly predicts another, raises the wtend to R2 ,yet
lowers the t-ratios (Lewis-Beck 1980).
High multicollinearity challengess
the notion inference that the specified independent
variables have any influence on affect the
dependent variable (Lewis-Beck 1980).
Table 2 (below) presents correlations between the variables of M1. Among the independent variables, the range
runs from .329 to .908.
TThough there is a high
correlation between city population and ,the
number of police personnel, the nearly 90% correlation between drug arrests and
a ,city’s non-White population (nwp) might be of note
to policymakerswith ,. TStill the fact
that M1 provides three statistically significant variables, the number of
police personnel, the city’s total and non-White populations, arguesuggests that multicollinearity is not an insuperable
problem in M1.
How shall we In evaluatinge the coefficients reported in M1?, we see that as the
variables of While
figures for police and the overall population are statistically significant and
report a positive sign, as expected, More importantly
for this study, acontrary to conventional wisdom, however, drug
arrests are correlate positively correlated with property crime, though not
at the .05 level. TLastly
the coefficient generated for on the
non-White population, presents a puzzle. in that it Its correlation with crime is statistically
significant but both
negative. and statistically
significant.Part of the explanation may lie in The negative sign
might result from the
grossness of the variable, as it includes the entire minority
population in a city, not just as opposed
to just young males, young adults, or
youth – cohorts more – those most likely to commit property crimes. Further cities like San Francisco, Amsterdam
and Rotterdam enjoy a certain level of affluence and a relatively high cost of
living that might reduce their teenage population relative to cities of
comparable size.[19]
However there is a A major
limitation to M1, as noted is apparent in
the pooled Durbin-Watson d
statistic. The value of .591 is far
below the acceptable lower bound[20]
and signals that M1 violates a basic regression assumption, “no
auto-correlation in residual terms of successive observation” (Pindyck and
Rubinfeld 1995). Correlating the M1
residual terms of successive observations demonstrates a high level of
auto-correlation at .564, well far in excess of an acceptable .1 (Lewis-Beck
1980).
I am not surprised by tThe presence of
auto-correlation in
the residuals for a time-series model is not surprising (Berry 1993, 67). This is because the excluded variables often
increase or change incrementally over time (Berry 1993, 67). Further when using cross-sectional data,
common in econometric analyses of crime, the likelihood of serial correlation
is high because there is often wide variation in the excluded excluded variables across the sampling units
(Nagin 1978, 129).[21]
Several There are
various statistical techniques one may
employ to can correct for residual
auto-correlation. One method is to
divide the independent variables by the “offending”
variable”
and create a weighted least squares model (Berry and Feldman 1985).[22] In this instance though, I
elected to correct for the high degree of auto-correlation the
Prais-Winsten (P-W) modification is employed.[23] TheThe P-W modification brings
certain to First, the modification tends to lower the R2
and adjusted R2 measures. In this sense, but narrows the
range about the slope coefficients, thus raisesing the confidence
about with which I can claim the accuracy of each slope estimates.
Table 1 (above) notes the
results from regressing the P-W modified data in M3, M4 and M5. As asWe see then, as noted above, anticipated, relative
to M1 and M2, the three have lower adjusted R2 figures. But in explaining over 91% of variance in
annual property crime reports for the cities in the sample, the models are
robust (Berry and Feldman 1985).
Further we have greater confidence about the accuracy of the statistical
significance of the slope coefficients of the independent variablesof .
As with M1, the variables of
overall population and non-White population are statistically significant > 95% beyond the .001 level. For M3 in particular, the variable of per
capita income reports a p value of .06.
We would
also expect Logically there should be a negative
relationship between income and crimeincome and
property crime and M3 shows this. here we see and, as
expected, relationship .The What is more remarkable
finding though, is that,, among these data, the relationship between
according to M3, property
crimes increase with drug
arrests and property crime is positive. While the p value of .138 (for a one-tailed
test), falls just short of a more comfortable level of statistical
significance, we should read the data to say that one cannot reject the null hypothesis about the relationship between
drug arrests and property crime. That
is, M3 provides evidence that Our starting point for
any scientific or statistical inquiry is to assume the null hypothesis, that
there is no relationship between to phenomena.
And while American officials and or mainstream arguments about drug
prohibition and crime presumes a negative relationship, M2 shows us that we
cannot rule out the null hypothesis.contravenes a major justification for the Drug War in
America. Namely M3 says that drug arrests do not lower crime.[24]
CONSIDERATIONS OF THE DATA
Limitations within the Sample and Data
Availability
With any statistical analysis, we
must be critical of the data. Crime
studies in generally, and cross-national crime studies in
particular are rife with statistical problems. First The
sample used here was data here, as ,not randomly selected, as which violates the regression analysis assumptiones (Sayrs 1989; Pindyck and Rubinfeld
1995). At the
same time Moreover I selected Dutch municipalities with
relatively high crime rates and drug use within the Netherlands (VWS 1995b;
Abraham et al. 1998)is concentrated . As the object
of comparison then, I present Dutch cities with the highest crime rates and
drug use rates – ifact can be seen as in this respect – as contrasted with American
cities in the sample are not known as
places of for disproportionately high per capita crime rates. So although the small set of cities might limit the credibility of
the statistical evaluations herethen with this small
sample, broader the statistical
findings should only be strengthened by use of data sample
would only be strengthened by adding from other Dutch cities (with lower crime rates) and more
prominent American cities.[25] Above all, a larger data set would replicate
the findings here because police in every American city make relatively large
numbers of drug arrests while Dutch cities make few – and sometimes no – drug
arrests.
Beyond certain crime data,
generally one would like to include yYouth unemployment figures are helpful in a regression models that measurethe crime (Hirschi 1969; Banerjee et al. 2000). Unfortunately I could not obtain comparable data on youth
unemployment data across for the American and Dutch cities studied
here. The problems are varied and
systemic. Individual city governments Dutch at the city level in the Netherlands keep
records ofn youth unemployment. But such numbers include we
must keep in mind however, that the youth unemployment is entin youth
as young as 16, and the Netherlands.for the DutchFirst,
i, schooling is only mandatory
only through
age 15. Further,
iIn
the United States, unemployment figures are generated according to local
rules, and maintainbut aggregated to the SState
level, according to local administrative rules. American youth,
who livinge at home, will
are not
counted as unemployeddue to their status. Further But ly,young
people in the United States do seldom not apply for,
much lesst alone qualify, for SState unemployment aid in
connection with their unemployed status. In these instances, Consequently official
American labor statistics do not count most unemployed American youths.
Such an omission significance
here for the regression model is that the might bias or skew the slope
coefficients reported in Table 1. I might be skewed or biased due to the limits of the dataf
youth unemployment is higher than recorded, the coefficients for the included included variables might be inflated (Berry and
Feldman 1985, 21), as capturing twhat which otherwise
could be attributed to youth unemployment.
Still ,there is reason to believe
that that minority and youth unemployment
lead to higher rates of drug dealing and prostitution not property crime (Hagan 1993; Gillis 1996a; Staley 1992). mMany people
involved in the drug trade, in American cities, are minority youth for despite
the associated risks, drug dealing represents one of the few avenues to them
(NYCLA 1996).
Purposeful
Omissions
From a methodological
standpoint, there are acceptable parameters to justify the exclusion of certain
variables in a regression model. King
et al. (1993) provide two instances in which one can justify excluding certain
variables. The first is when an
excluded independent variable has no effect on the dependent variable
(176). Second the excluded variable
does not correlate with the included variables (176).
The
simple models presented here leave out three oft considered factors of
crime: property crime arrests (Brown
1978), incarceration (Gillis 1996b; DiIulio and Piehl 1991), and individual
measures of drug use Godshaw et al. 1987; percent
percent percent Ostrowski 1989).[26] The omissions were intentioned as informed
by general statistical theory, criminological studies, and level-of-analysis
problems.
Blumstein In this context punishment comes in the form of arrest and
confinement. et al. (1978)
(1978) concedes
that no one can estimate ertaintythe
degree to which deterrence,, qua through arrest and incarceration,, reduces crime (136). In fact, rational -choice models
looking at arrest and prison as that test deterrents
to crime receive little support (Gillis 1996b, 97).
Brown (1978) (1978) argues
that general arrest rates and crime -specific arrest
rates for crimes
on the FBI Index crimes mayight have an affect
in reducinge crime rates
(679-680). Specifically However instead of supporting Brown contends that
a the threshold or tipping point of affect of arrest rates > 30% crime-specific arrest rate decreases on crime only in cities with fewer than 10,000
people (679). The
point is significant because aAll six of the cities in
my study compared here have over
more
than 100,000 residents and in fact are part of larger metropolitan areas
with anywhere from 250,000 to over 1,000,000 people, hence and
are relatively I omit crime-specific arrest rates. In addition, general arrests rates cannot be
compared between American and Dutch cities for in the American case, a large
number of arrests are made for non-criminal acts, namely parole and probation
violations (Jones 1996). Further these
administrative arrests are neither disaggregated in reports nor presented as
city-level data (Jones 1996).
As for incarceration data, tTheoretical and
methodological considerations
arguments advise against
incorporating these incarceration data
in my the regression
equation models tested here. As a rule, incarceration is a function and consequence of arrest, but Ccuriously lystudies
find no consistent examining the association relationship between
incarceration and arrest have not found any consistent relationship between the two(Zimring
and Hawkins 1995). Such The lack absence of a relationship
satisfies the position of one of conditions
offered by King et al. et al. (1993) as to justify to excludeing incarceration
data causes. The syllogism is as follows:
There is no statistically significant relationship between incarceration and arrests (Zimring and Hawkins 1995; Jacobs and Helms 1996).[27]
Arrests correlate significantly with property crime (Tittle and Rowe 1974; Rasmussen and Benson 1994).
Therefore, incarceration does not produce a measurable affect on property crime.
Putting aside the syllogism, what does research say about
incarceration and crime? Authors like
DiIulio and Piehl (1991) argued that
increasing incarceration rates and lengths of sentences decrease crime. Spelman (1994) found the effect of incarceration to be
limited., who Spelman reanalyzed the original RAND
data and methods used by Zedlewski (1987) and DiIulio and Piehl (1991), indicates to show that current incarceration rates
avert perhaps no little more than
8% of crimes in
the United States.[28] Subsequent estimates by Zimring and Hawkins
(1995)nd and Dyer (2000) simply refuted claims of DiIulio and Piehl (1991).
Generally wWhen
incarceration rose increased in
various American States and cities, – crime
did not neither decrease nor decreased no more than crime numbers in comparable
places with fewer prison commitments. For example, a In a review of imprisonment from 1997-1999, Macallair et
al. (2000) found that those California Scounties
that which most vigorously pursued imprisonment
and long sentences for offenders did did not
experiencee the greaterst declines in
drug use or crime. One explanation
could be, as DiIulio (1996) admits, drug arrests are inefficient at reducing
crime.
As noted in here previous
chapters, wWithin regimes of social control, rates of arrest
and incarceration depend less on the particular “crime” in itself than greatly on the social distance(s) between state actors and “criminals” more than crime itself (Zimring and Hawkins
1973, 333). Official discretion plays a
large part in determining who goes to prison (Simon and Burns 1997). In the United States, where annually there
are more marijuana possession arrests that those for the FBI Index crimes
combined, context we must remember that
prosecutors use the a “laundry list” approach of charges to secure guilty pleas from
defendants (Livingston 2001). Hence that is, the size of the prison population first and foremost reflects social heterogeneity
first and foremost,
not crime (Black 1984; Jones 2001).
Therefore any statistical relationship between prison commitments and
property crime rates might be spurious, wrongly capturing or
unmeasured or unstated institutional aims and larger social questions dynamics of class and race.
From a sheer methodological
perspective, there are a number of problems with iIncarceration
data also pose
methodological problems.[29] The problems include
questions of relate to levels of analysis, recording disparities, and
cultural differences between the use and in practices of
incarceration – in
this case between the
United States versus and the
Netherlands.
Incarceration is often measured at the State or national
level. These numbers do not necessarily
correspond or correlation with to criminal
activity in any given city. Further we have no way of This also makes it
difficult to knowing if
incarcerating a number offenders from “City A” a particular city will reduce crime
there. Moreover tIf
for no other reason, he arrest and removal of one set of criminals
can produce a vacuum or demand for more, offenders and motivateing would-be criminals to relocate there (Sherman
1990). Moreover
t
JWe
must also consider anotherurisdictional question
in regards to differences between jails and
prisons affect the
comparability of incarceration records.
Most American cities have jails, but they are part of a the jurisdiction of county government and are
often used solely for pre-trial or and transfer
purposes. In the Netherlands, the prisons are part of an integrated national
system. Though disparate nature of how the two nations keep incarceration records
might thus help us learn about aggregate
prison commitments, the the lack of dissimilarities
demand omission from ity in thethe cannot assist the econometric models here.
Further eEven if it were
possible to collect comparable prison data, there are cultural
differences would that might mislead usdeductions based on . First tThe U.nited S.tates and the
Netherlands have
different hold widely varied views and institutional
norms and in re incarceration practices.[30] trends and practices Evidence
of Among these differences includes the
prevalence of in America of drug arrests, along with stunningly high rates of conviction
and disproportionately high incarceration rates.
According to Bureau of Justice Statistics data on
convictions and prison sentences, in those The 1994
about analysis revealed45% of all felony
convictions lead to incarceration, but the rate was . However it was 71%
for drug convictions.[31] As one common
example of For the fiscal
year year 2001, the Oklahoma
Criminal Justice Resource Center (OCJRC)
reported, that fully one-third (33.4%) of all new state inmates were drug offenders, usually
convicted for methamphetamine (DRCNet 2002b).
Violent criminals, on the other hand, accounted for only 13.7% of new
inmates (DRCNet 2002b).[32]
Aside from the Ttypes of crimes pursued and punished aside, the the difference
in of scale of in incarceration
between the Netherlands and the United States isis enormous. As of 1997, the Netherlands had only about 4,000 jail and prison
spaces for a nation of approximately 16,000,000 people. ,bed peFrom
the mid- 1990s to 2001, the prothe U.S.
prison population portion of people imprisoned in the United States grew
from one out of
every 250 individuals (about onelittle over million inmates), or one for every
250 people, to one prisoner out of
every 140 people prisoners or roughly one
prisoner for every 140 people (BJS 2002). In pIn per capita terms
terms, the American incarceration rate is at
least more
than 25 times the Dutch rate.
A Llastly problematic
complication in connections betweenng rates of crime rates and
incarceration become apparent given stems from the implied relationship between
implied
for imprisonment and crime, when so
many Americans are imprisoned for drugs crime(Jones
1996, 11).[33] AGlyone might
consider that rrest and imprisonmentcommitments reflects a small, but measurable amount
of the true crime rate. But as the rates of consensual
behaviors, activity like drug use and drug
trafficking rates are unknown
unknown to within the criminal justice system (Hagan
et al. 1996, xiv; Jones 1996). Officials know that And while drug offenders constituted 21% of S1997 tate prison inmates
in 1997, and
60% of 1996 federal prison
inmates in 1996 (The Sentencing Project 1999a), y,et no one knows knows
how many drug crimes were committedoccurred in those or other
years.[34] Without knowing the baseline, officials cannot predict or
explain therefore cannot help us predict how
many other non-drug crimes, if any, are being
preempted by
drug imprisonments are otherwise created or
eliminated. It is
hardly any wonder that increases in drug-crime incarceration have not
been shown
to correlate
with decreases in property crimes.
Nevertheless defenders of There might be
anthe
Drug War hold that raised the high probability
of conviction arrest and incarceration numbers for drug arrest in America offenses should get means that “bad
eggs” are pulled off the street, which in
turn should ,decrease property crime. To test that idea I allowed a one-year by which there would be lag between drug arrests
and crime for the American cities, as presented in M5 of Table 1 (above) effectpossibly of one ,after which the community would see
a reductionAgain tingproblems
replacement effects, the aging-out effect, of resulting in ,the question
remains, by which -0s year-1Regression analysis on this question, both pre and
post P-W modifications, reported nearly identical findings. setbut for drug arrests from the previous
year, constructthir,.
As
compared to the findings above, tThe goodness of fit, the direction of
the coefficients,
and the statistical
significance of the independent variables for M5 is are nearly
identical to the non-lagged data setmodels that do not use a lag. Hence “giving” time for incarceration to reduce crime does not make a
difference. This observation reinforces earlier
reasons for omitting incarcerationDue to research
findings on the effects of incarceration on crime then, in addition to problems
with cross-national comparisons, as well as statistical theory (King, et al.
1993), my model does not include prison commitments as an
independent variable. Importantly
omission of that variable does not affect the slope coefficient that is the
focus of this study, the effect of drug arrests on property crime.
.DISCUSSION AND CONCLUSION
Drug Arrests Probably Increase Crime
As reported here, tThere is a positive data
here show that at best drug arrests have no effect on property crime and at
worst increase the incidence of such acts, in , perhaps
even a one -to -one relationship. Why would it be that Why property crime increases
with drug arrestssuch occur?
Perhaps it is a function of externalitiesand or
the consequences , laws or actions. Cohen (1985) (1985) draws upon Weberian and Marxistan ideas of
structural constraint to explain “unintended,” yet easily foreseen, effects ofrom patterns of social control (56). That is given a
particular set ofake laws, e.g.
that prohibit drugs prohibition, as
filtered throughpply them disproportionately in a politiesy divided along fissures of by class and
race, as well as systems of bureaucracy, certainnd certain
patterns in the application of law should are
expected (Sherman and Rogan 1995). Police crackdowns moves make force criminals
to become smarter, raise the price of
drugs – increasing incentives to deal, and inducee
more property crime (Kleiman 1985; Nadelmann 1991).
In a 1997 speech beforebefore the New York Bar Association, William
F. Buckley Jr. made the following commentobserved:
Serious crime is 480 percent higher than in 1965. The correlation is not absolute, but it is
suggestive: crime is reduced by the
number of available enforcers of law and order, namely policemen. The heralded new crime legislation, passed
last year and acclaimed by President Clinton, provides for 100,000 extra
policemen, even if only for a limited amount of time. But 400,000 policemen would be freed to pursue criminals engaged
in activity other than the sale and distribution of drugs if such sale and
distribution, at a price at which there was no profit, were to be done by, say,
a federal drugstoreBuckley .
Over
1.6 million people are arrested for drug crimes annually (FBI 2001), and around four
hundred thousand of them are imprisoned.
As Bucklely (1997), DiIulio (1996) (1997)
and others suggest, American drug policy raises crime rates are higher than need be because of drug policy. When police seek out
target
drug offenders,
property criminals face
have fewer impediments if not are left free to roam the streets (Levine
1999).
In rRecalling a sting
operation in New York City in the early 1990s, former DEA agent, Michael Levine
(1999), (1999) notes
that:
“It took a squad of 10 men the rest of the night to process the prisoner, run down some leads, write reports, store evidence, seize and inventory his car, question and release for lack of evidence two people who had accompanied [the offender] and store him in a cell ... By the following morning we had expended approximately 220 total man-hours on the case and much of the administrative work including case reports were still to be done. The [dealer] was free on bail before we could get home to sleep.”
Noting the tremendous number of With over 700,000
arrests yearly drug arrests, especially those
just for marijuana alone, over 700,000 (FBI 2001), it is evident clear that more police time could be
redirected toward dealing with more serious
crimes
(McVay 1991, 156). Because breaches of
the law always outstrip police capacity, police discretion is inevitable
(Reiner 1994, 723). DYet discretionary
practices have seriousignificant
implications for crime control and crime creation (Zimring and Hawkins 1992).[35] Theoretically cCriminals can recognize there are lowerat the opportunity costs for non-drug crimes decline when because police attention
to concentrate
on drug offenses (-relatedleaves with edKopel 1994).
Pnegligent or limited olicing
drug activity probably ay be a function of“over-taxes”
the system. In a system that is over-taxworked, increasing drug arrests may
have no effect on leaves other crime rates unaffected (Nagin
1978). As well lFrom
the other side, the locals can adapt to police the
increased police presence, i.e. the crackdowns., with Over time people learning how to engage
in crime despite added police the presence of more police (Barnett
1988; Simon and Burns 1997).
Increasinged surveillance
generates a
similar result over the long-term does not reduce
their criminal activities (MacKenzie 1996; Kleiman 1988). In I1987 according to police
in Tulsa, Oklahoma, reported that added increasing foot- patrols around in and around public housing apartments as early as 1987 allowed the increased arrests
of street drug dealers. In response, ,
literally hanging outsidethe apartmentslocal dealers began to forcibly removed tenants, taking forcibly
and -over apartments, and made deals that police could not see (Robison 1994) (Robison 1994). That is, police presence moved the drug
market from an open bazaar to a more clandestine operation. In the worse case then, p
Similarly in the mid-1980s, two towns in Massachusetts sought to close
black market trade in heroin and cocaine (Sherman 1990, 18-20). WIn the smaller locale, where
treatment was available and utilized, local rates of drug use rates
and property crime decreased as did local crime. The anticipated effects of In addition,
there was ndisplacement did not spur crime ment of crimein
adjoining municipalities (Sherman 1990). But Win the larger city, where the target area was sufficiently large and there
was no treatment, however, property crime
increased substantially in response to more with drug arrests
(Kleiman 1988; Sherman 1990, 19-20). Such could have resulted as a significant
number of drug arrests,, where the market was
sufficiently in a large market, onmotivated
dealers to pass on added risks/ and costs to
local consumers (Kleiman 1988). And lIn turn, local users, with fewer as captives without the option suppliers, , had toturned to property crime to pay added to pay enforcement tariffs. (Kleiman 1988).
On the whole, no matter how many arrests are made for drug crime use or dealing, there is no
little
evidence that drug crime decreases (Jones 1996). And if police are If the effort ultimately inefficient when applying resources to
fight drugs is
ineffective, then allocating resources toward prohibition is inefficient, and the
inefficiency spreads a yplace in to other areas of
law enforcement.[36] Between 1982 and 1987, the
State of Florida saw an increase in violent crime and property
crime in Florida
increased despite more arrests and longer sentences for drug and
property crime arrests (Benson and
Rasmussen 1991, 107). At the same time,
iDuring that time, in Florida, as across the United
States, despite growing numbers of drug arrests and imposition of longerprison
sentencesn Florida, as in the rest of the country, the
price of cocaine dropped anywhere
from 50%- to 75%.
Given their inverse relationship, iSo there is
little reason t strains credulity to attribute any rise in
crime in Florida to drug prices (Kleiman 1988; Benson and Rasmussen 1991). A more plausible explanation for the rising crime rate then is that property crime in Florida rose
as an function of law enforcement opportunity costs of concentrating law enforcement on drug
related offenses, arrests, prosecution and incarceration.
Foucault (1977) insists argued that States
encourage and modern governments promote certain some categories of crime ,
as part of a complex ofto maintain the ruling order by authorizing legitimating employ
of policeing and the imprisonment.[37] Drug prohibition creates what are That is, some inherently political crimes
(Salvesberg 1994; Jacobs and Helms 1996), those made via is
social design, such is the case with drug
prohibition. Given On the other side, pockets of poverty and
underdevelopment in the U.S. mean that the black market drug trade trade acts functions as an employment agency (Hagan et
al. 1996, 13). What then are the implications esismean for crimerates ?
Repression of the drug trade should
increases generate more crime in a number of ways. To inhibit When one
economic opportunity, drug sales, is to promote othersinhibited,
would-be dealers either turn to other activities, like they re-double their
make s in an ever. When
police spend relativemore time on drug
trafficking, property criminals should have
greater chances to succeed (Phillips and Votey 1981). And as we have seen, bBecause repression policing drugs often increases profit margins, incentives increase for
drug traffickers have greater incentive to
control their
markets. That means more violence among traffickers against police and
eventually more violence by policeDue to the
problematic nature of illicit drug markets, namely the need for dealers to
resort to violence to settle contracts and their constant threat of police
violence, traffickers typically carry firearms (USSC 1995; Nelson
and Ostrow 1998; Donald 2002). And for
those who are arrested and convicted, Thus crimes against persons too should rise
as dealers compete with both rivals and police.they are
stigmatized, and may lose employment opportunities (NTFC 1994; Bushway 1996;
Jones 2000). “It is difficult to
over-estimate the harm caused by forcing drug users into a life of crime. Once this threshold is crossed, there is
often no return” (Barnett 1988, 85; Germuska 1989).[38]
If policy makers truly desire to reduce property crime, then
police should target property criminals, and young ones at that. According to A
disproportionate number of property crimes of crimes are
committed by 15-18 year-old males (Mauer 1994). Careers in burglary and robbery, for example, have
a peak at
age of commission of 18 (FBI
1993). Instead we see that drug offense convictions
overcrowd America’s lead to jails and prisons overcrowding.
Prison roles in the United States America's
jails and prisons expanded by 587 people each
a week
in 2001 (BJS 2002),
even .
Incredibly this growth occurred though more than 600,000
convicts completed their sentenceswalked out of prison that year (DRCNet 2002a). To alleviate the stress, courts order
the release of convicts who do not have mandatory sentences (Welch 1994; Simon
and Burns 1997). By the illogical
mandates of
American law, early release orders are released
are often
handed to violent offenders (Kopel 1994).[39] Are we surprised then that rates of
recidivism of run around 60% or
more for released prisonersin many respects represents
shows a national commitment to policies that are both (The Sentencing Project 1999b)? Wif hen
drug arrests
mean the release
of when younger and more violent
convicts are released without sufficient supervision or job opportunitiesthe community s, communities suffering
more violence and property
and violent crime.
Conclusions
Decades of Drug War mean
that America has abandoned one of Sir Robert Peel’s fundamental principles,: “to
recognize always that the test of police efficiency is the absence of crime and
disorder, and not the visible evidence of police action in dealing with them”
(Pruder 1998). By Peel’s criterion, drug
prohibition through criminal law and policing has failed utterly,. with nNo evidence of this is more damning than seeing law enforcement repeatedly
inviting the media to view “trophy busts”exemplified by
of marijuana -grow operations and imported or record seizures of cocaine or and heroin seizures (Pruder 1998). Such these seizures xamples, however,only proves testify to the failure
of drug criminal drug policiesization (Pruder 1998).
Pruder, a Canadian police officer states
that case well, as he measures the logic of prohibition against the illogic of
its claims and counter-productive actions.
This chapter laid out three areas of consideration for scrutiny, drug
use, trafficking and crime. Academics,
police, political leaders, and others have long-known that prohibition cannot
meet its aims, and such is especially true in the area of crime reduction.
Police can control address crime
better than they do at present.
Increasing police visibility and significantly
increasing arrest probabilities for property crime are the best
methods. Under the present policy of prohibition, What is most significant about the 30% number is that, in
large cities, the probability of arrest for property crime per recorded act of street crime never
approaches 30%,, but
instead it hovers around ten percent10%. Hence wWithout a massive
shift in man--power away from policing drug
crime and toward
combating property crime, arrests
cannot increase police efficiency, there can be little or no benefits to decrease property crime
significantly reduction through arrest per se.
As Benson and Rasmussen (1991) (1991) find,
the probability of property -crime arrests grows with an increase in police resources so olong as police do not devote added resources to
the relative drug arrests rate (111).
Additionally The Ooverall the price
of drug prohibition is includes spreading of disease, increasing crime, costly incarceration,
growing black- markets activity, escalating violent
drug marketsce in the drug trade, unnecessary violence with and by police, and wasted law -enforcement costresources that
could instead be used to stop predatory crime (Moynihan 1993, 356; Kleiman
1992). My hope is that through
inquiries and empirical investigations such as presented here, evidence rather
than myth, racism, and the profit motives, will guide decision about drug
policy to be far more efficacious in reducing crime.
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[1] The title “Drug Czar” is the popular name given the Executive Director of the Office of National Drug Control Policy (ONDCP). The director functions as the President’s mouthpiece on federal drug policy.
[2] If the government of the Netherlands has tried to make it easy for young people to use drugs, they have failed in comparison to the United States, England, Switzerland, Sweden, Norway, and Australia to name a few, where teen drug use rates are higher.
[3] We might assume he implied Dutch tolerance of marijuana, hashish, cocaine, XTC, and heroin. Other drugs like GBH, Ketamine, PCP, and methamphetamine are practically unknown in the Netherlands (Abraham et al. 1998), yet more prevalent in the United States (McCaffrey 1999). Further, the Dutch murder rate is about 1.8/100,000, the United States rate is 7.4/100,000 (Panhuis 1998).
[4] During the same CNN broadcast, when Mike Gray corrected McCaffrey about American versus Dutch murder rates, McCaffrey insisted that the numbers were not his, and that he did not want to “debate the figures.”
[5] The Shafer Commission (1972) announced that cocaine is not physically addictive and causes no withdrawal symptoms.
[6] A typical heroin habit of 40 mg/day would cost only 25 cents (in 1986 dollars). Hence if drug users did commit crimes to support their habits, lower prices would drop crime dramatically (Staley 1992, 110). Accepting federal data on the street price and purity of heroin, in 1986, given the black market tariff, 40 mg cost about $50. By 1998, adjusting for inflation and purity, the equivalent amount cost only 1/6th of that.
[7] The Dutch call substances with “unacceptable social risks” harddrugs, inter alia heroin, cocaine, LSD, XTC, and methamphetamines. Conversely they call marijuana and hashish, softdrugs (Trimbos Instituut 1996).
[8] In the original Nederlands, the quote is: ,,Het is langer bekend dat de politiemensen op straat het opsporingsbelied self concrete gestalte geeft.”
[9] As well, drunk-driving arrests decreased 22% (Rasmussen and Benson 1994, 96-98).
[10] Though he did not control for drug arrests, Lynch (1988) found that only the number of police (at year t0), and the police budget appropriation (at year t-1) statistically significant as predictors of the property crime arrest rate (338).
[11]
Growing numbers of immigrants led to a can dissipateion in the social coreherence. As subsequently social
distances increase, dwhereby more stic,ingethe crime increases as the social norm against could more easily violateing others declines. Since the 1970s, informal social networks, zuilen,,
once so central to Dutch society, have minimal smaller effects
in controlling behavior. Analysts As well, the lessening effect of the pillars is lamented see that the weakening of
social pillars,
ontzuiling, accompanies rising crime
rates and street-violence (Bovenkerk 2000).
[12]
Sociologist Frank Bovenkerk found consistent race-based employment
discrimination in the Netherlands from 1978 and 1997
(Banerjee et al. 2000). As
much as a third of the unemployment among non-native Dutch could
be seems
attributedable to ethnic
discrimination (Banerjee et al. 2000).
[13] This is the collective name for a central region (Midden-Nederland) of the Netherlands that includes Alphen aan den Rijn, Amersfoort, Delft, Den Haag, Gouda, Leiden, and Utrecht.
[14] The practice can be traced to cultural mores and a national policy that calls for assimilation and integration of immigrants. In everyday life, Dutch police distinguish foreigners or allochtonen, but to what extent police target immigrants is unknown.
[15] When walking through Amsterdam and Rotterdam, I was often approached by drug dealers, usually Moroccan, who spoke English or Spanish. Moroccan youth are over-represented in street-level dealing due to their recent arrival to the Netherlands (Bovenkerk 2000).
[16] More recent data slow that immigrants from the former Yugoslavia are disproportionately engaged in crime (Algemeen Dagblad 2002b).
[17]
There is nothing inherent in Black American culture conducive to crime (Sampson
1987, 348). Crime rates among Blacks
and Whites are linked structurally to unemployment (348). We should not assume, however, that
the relationship between employment and crime runs one way. Economic prosperity, e.g. Western Europe in
the 1970s, can accompany crime increases So as Van Dijk
(1990) found, growing out of the Western Europe saw (Van Dijk 1990).
[18] In one model, M5, I test for the presence of a one-year lag in the relationship between drug arrests and property crime for the American cities in the sample. This reduced the sample whereby N = 47.
[19] To determine if the non-White population figures, much less the drug arrest practices in general, were capturing another factor, namely some national effect, I controlled for differences in the two nations through a dummy variable in M2. As one can see, for this sample, there was no national effect.
[20] Given 48 degrees of freedom, with five independent variables, the upper and lower bounds for D-W d are approximately 1.33 to 1.77 (Savin and White 1977).
[21] Locations with actual crime rates higher that those predicted by OLS models in one year are likely to remain higher in the next year as well (Nagin 1978, 129).
[22] The offending variable is that without homoskedastic residuals.
[23]
The P-W technique is similar to the Cochrane-Orcutt AR1 method, but has the
advantage of keeping the first data -point.
[24] In fact, an F test comparing M3 with M4, the model sans the drug arrest variable or the “short regression,” shows that there is no need to include drug arrests in an econometric model that attempts to explain annual rates of property crime for cities.
[25] Other cities, like New Orleans, San Diego, Miami, and Washington, DC, have higher crime rates than the American cities used in the data set here (Raleigh and San Francisco). As well, on average American cities have higher crime rates than Dutch.
[26] I omit any measure of city-specific drug-use rates. As with prison data (discussed below), there is a levels-of-analysis problem because most American drug use data is not for cities. More significantly there is little reason to think American drug data is accurate (Harrison 1997). Self-report surveys suffer for many reasons, including the fact that users cannot identify their drugs (Jones 2002).
[27] Jacobs and Helms (1996) find that crime rates only predict prison admissions if the “square of the variable” is tested (348). Squaring the number of reported crimes simply and wrongly captures drug arrests – that which is not reported in crime rate figures. Further, in footnote 15 they explain that when they include drug incarceration, crime rates are not statistically significant predictors of incarceration.
[28] The modest effect of incarceration on crime may tell us something about rehabilitation. Meta-analysis on recidivism by Gendreau, Little and Goggin (1996) found that self-esteem, depression, and anxiety are relatively weak predictors of recidivism (MacKenzie 1996) though these concerns are the most common targets of offender-treatment programs.
[29] Due to recording problems, I do not use “clearance rates” as an independent variable. In the Netherlands, a case is “cleared” only when a defendant is convicted (Fromberg 1998). In the United States, cases are cleared when they are adjudicated or when local police decide to end investigations.
[30]
The Netherlands adheres strictly to the “one-man, one-cell” principle. When jails and prisons are full, convicts
are released to be called to serve their time once space becomes available –
sometimes months after conviction. Due to limited
space, a lack of space or and institutional
etpreferences against incarceration, the vast majority only about 20% of Dutch convicts never
go to prison, only about 20% do., and Around 90% percent of all sentences are for less than one
year. Easily More than a one-third are one month or less (VWS 1995c,
435). Since epresent
starting in the 1980s, the Dutch began to employ community -service as “alternative sentences” for
convicts (De Cock and Verheijen 1989, 11).
NCommunity service orders now and almost early as many
people are are assigned community service
as sent to jail annually on a yearly basis (VWS
1995c, 436).
[31] In America, the ratio of incarceration to probation for drug crime is 70% to 30%, but 60-40 for non-drug crime.
[32] Another problem is the length of sentence for drug offenders versus violent criminals. The Massachusetts Department of Corrections indicates that 84% of its inmates serving mandatory minimum sentences for drug offenses crimes are first-time offenders (Boston Globe 1998). These inmates are serving an average term of five years, one year more than that for the average violent offender (Boston Globe 1998).
[33] American jails teem with non-violent, first-time, drug offenders, unlikely to cause any other social or private harm (MacKenzie 1996). These non-violent offenders fueled the American’s prison boom of the 1990s (Greene and Schiraldi 2001).
[34] For Rusche and Kirchheimer (1933) penal forms correspond to objectives of crime control, but penal methods are determined by wider social forces. The argument holds that “punishment is not a consequence of crime” (Garland 1990, 91; Rusche and Kirchheimer 1933, 6). Instead convictions and prison commitments are best understood as products of economic inequality, political oppression, corrupt judicial processes, etc.
[35] Jacobs et al. (1984) found a positive relationship between income inequality and police size (Liska et al. 1985, 135). Hence they theorize that “crime control,” via the size of the police force, is a product of social inequities rather than crime rates. If Jacobs and colleagues are correct, law enforcement against particular acts like seatbelt laws, domestic abuse, etc. are probably the result of social inequity too, not crime rates per se.
[36] For example, through his dissent in Lawrence and Gardner v. Texas, 123 SCt 2472 (2003), Clarence Thomas wrote that enforcing sodomy prohibition is an inefficient use of resources. “Punishing someone for… noncommercial consensual conduct… does not appear to be a worthy way to expend valuable law enforcement resources.”
[37] Foucault (1977) wrote about the “threat of prison” that works most effectively against people unlikely to see its walls from the inside. Simultaneously the prison provides jobs for people on the economic margins, who frequently comprise the most obedient and patriotic citizens.
[38] Due to recent civil judgments, employers may be held liable for violent, yet non-work related, criminal acts of employees (Jones 2000a). Because non-violent drug offenders can be considered “dangerous” in the civil courts, potential employers must think twice before hiring them. Given a choice, most employers would choose rather not to hire a parolee or ex-convict (Jones 2000a).
[39] The testable argument is that such practices provide criminals with information about the opportunity costs for non-drug crime. When the criminal-justice system attends to drug-crime and simultaneously reduces the probability and length of penalties for non-drug crime, rational criminals can be expected to choose property crime over drug crime.