John Calvin Jones, PhD, JD




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.  



drugs, crime, drug policy, war on drugs, drug war, property crime, drug arrests, Netherlands, United States




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:




            1804 W. Washington Street

Brownsville, TX 78520-6660 




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.



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]



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]



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.


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.


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.