peer reviewed article summary
Mark Gius Justice Policy Journal, Spring, 2018
The Effects of Civil and Criminal Forfeitures 1
The Effects of Civil and
Criminal Forfeitures on
Drug-Related Arrests
Mark Gius1
Justice Policy Journal Volume 15, Number 1 (Spring, 2018)
© Center on Juvenile and Criminal Justice 2018 www.cjcj.org/jpj
Abstract
The purpose of the present study is to determine if civil and criminal forfeitures
have statistically-significant and negative effects on drug-related arrests. The
primary focus of this paper will be on the deterrent effects of forfeitures. Using a
random effects model and state-level data for the period 2000-2013, it was found
that there is a negative relationship between the per capita value of seized assets
and the drug-related crime rate. It is important to note, however, that the effect is
very minimal; even if the per capita value of seized assets was doubled, the drug-
related arrest rate would fall by only 0.05336%. Hence, given the constitutional
issues surrounding civil forfeitures and the minimal effects of such forfeitures, it
would be in the public interest to amend the Comprehensive Crime Control Act
(CCCA) of 1984 so that equitable sharing of forfeiture proceeds among federal,
state, and local agencies would no longer be permitted. Amending the CCCA in this
manner would remove the incentives that state and local agencies have to engage
in seizures and forfeitures. Such a revision of the CCCA would only very minimally
affect the drug-related arrest rate but would, at the same time, restore some
degree of due process to forfeiture proceedings.
1 Quinnipiac University
Corresponding Author: Mark Gius, Mark.gius@quinnipiac.edu
2 The Effects of Civil and Criminal Forfeitures
Introduction
In 2007, a waitress, her two young sons, and her boyfriend were travelling through
Tenaha, Texas when they were stopped by local police. They were told that the
reason they were stopped was because they were driving in the passing lane. The
police officer searched their car and found a large amount of cash that the couple
said they were going to use to buy a car. Nothing illegal was found. Nonetheless,
local police detained them and drove them to the local police station. There, the
county’s district attorney told them that they could either be charged with felony
money laundering, in which case the woman would lose custody of her children, or
they could sign over all of their cash to the city of Tenaha and be on their way. They
decided to give up their money. Hence, even though they were never convicted or
even charged with a crime, the waitress and her boyfriend had to forfeit all of their
money that day in Tenaha, Texas. This story originally appeared in the New Yorker
magazine (August 12, 2013) and is an excellent example of civil forfeiture.
In general, there are two types of forfeitures that may be used by authorities:
criminal forfeitures and civil forfeitures. Criminal forfeitures occur when authorities
seize the assets of convicted persons. Civil forfeitures occur when law enforcement
agencies seize the property of persons allegedly involved in criminal activities; the
person involved does not need to have been convicted or even charged with a
crime. For criminal forfeitures, the evidentiary standard is “beyond a reasonable
doubt.” For civil forfeitures, the evidentiary standard is much lower; in some states,
it is only “probable cause.” In addition, once a person’s property has been seized in
a civil forfeiture, it is very difficult to recover. In many jurisdictions, the person must
prove that they did not engage in the alleged criminal activity. Finally, it is important
to note that, in civil forfeitures, the defendant is not the person; the defendant is
the property. Hence, this results in some odd sounding case names, such as “State
of Texas v. $6,037.”
Until the late 20th century, the use of civil forfeitures was very rare and very
limited. They were primarily used in situations involving piracy or border customs.
In 1970, Congress enacted the Forfeiture Act, which allowed federal authorities to
bring civil forfeiture actions against convicted drug dealers. The act was amended
in 1984 (the Comprehensive Crime Control Act), and this new law allowed federal
authorities to seize any property that was used or was intended to be used in drug
trafficking. Although supposedly limited in scope, the Comprehensive Crime Control
Act (CCCA) of 1984 has been used to justify the seizure of almost any property, even
property not related in any way whatsoever to drug trafficking or any type of drug-
related offense. In addition, the CCCA created the Asset Forfeiture Fund which is
where the proceeds from forfeitures are deposited so that they may be used at a
Mark Gius Justice Policy Journal, Spring, 2018
The Effects of Civil and Criminal Forfeitures 3
later date by law enforcement agencies. Finally, this law also allowed for the
equitable sharing of forfeiture proceeds among federal, state, and local agencies.
Under this program, federal authorities “adopt” local seizures, and then the
proceeds are equitably shared among federal and local agencies. These
“adoptions” by federal agencies typically occur in states where laws regarding the
disposition of seized assets are somewhat restrictive. In some states, local law
enforcement agencies can only keep a small fraction of the seized assets. By
having federal authorities “adopt” the seizures, local authorities are able to
circumvent these restrictive state laws and keep more of the seized assets for
themselves. Therefore, the CCCA created incentives for both federal and state
agencies to be much more aggressive in their seizure of assets allegedly involved in
criminal activity.
These increased incentives created by the CCCA have led local police
departments to view the proceeds from forfeitures as relatively steady revenue
streams, especially given the volatility of tax revenues available from local
governments. Police departments have direct control over the seizure of
properties, and given the relatively low evidentiary standards that are required for
civil forfeitures, local police departments in many states view forfeiture revenues as
an integral part of their budgets.
The impact of civil forfeitures on police behavior has been extensively examined
(Kelly and Kole, 2016; Holcomb, Kovandzic, and Williams, 2011; Bishopp and
Worrall, 2009; Baicker and Jacobson, 2007; Worrall, 2001; Mast, Benson, and
Rasmussen, 2000). Most of these studies examined the impact of forfeitures on
policing behavior, such as the impact of forfeitures on the rate of drug-related
arrests or the impact of forfeiture laws on local government budgetary decisions. In
Kelly and Kole (2016), Bishopp and Worrall (2009), Baicker and Jacobson (2007), and
Mast, Benson, and Rasmussen (2000), the effects of forfeitures on drug-related
arrests were examined. In these studies, it was assumed that the lure of money
provided by forfeitures resulted in more aggressive policing, thus increasing the
rate of drug-related arrests. Because of lenient civil forfeiture policies, police
focused more of their efforts on forfeiture-related arrests (typically drug-related)
than on other types of arrests (Kelly and Kole, 2016). If this hypothesis is true, then
an increase in forfeitures should result in an increase in drug-related and forfeiture-
related arrests.
Another possibility, however, is that forfeitures may have a deterrent effect on
crime (Kelly and Kole, 2016). An increase in forfeitures should result in a reduction
in assets available to drug dealers and other criminals. This reduction in assets
4 The Effects of Civil and Criminal Forfeitures
means that criminals would have less money with which to purchase adequate
legal defenses and less money to reinvest in their criminal enterprises (Kelly and
Kole, 2016). Thus, we may observe a decrease in drug-related arrests whenever
there is an increase in forfeiture activity. No prior research has examined the
deterrent effects of forfeitures. All pertinent prior studies have tested the
hypothesis that an increase in forfeitures results in an increase in drug-related
arrests (policing behavior), rather than a decrease in drug arrests (deterrent effect).
Hence, the purpose of the present study is to test the validity of the deterrent effect
and to determine if forfeitures have statistically-significant and negative effects on
drug-related arrests. As noted earlier, there has been no research as of yet that has
attempted to determine the statistical significance of the deterrent effect of
forfeitures. A brief review of the relevant literature will be presented in the next
section.
Prior Research
As noted previously, several studies have examined the effects of forfeitures on
police budgeting decisions (Holcomb, Kovandzic, and Williams, 2011; Worrall, 2001).
Given the focus of the present study, these types of studies will not be examined in
this literature review. Instead, only those prior studies that examined the effects of
forfeitures on drug-related arrests will be reviewed.
One of the earliest studies that examined this topic was Mast, Benson, and
Rasmussen (2000). This study used data obtained from the National Institute of
Justice’s Drug Use Forecasting program. This data set covers only 24 cities in the
United States and looks at drug use among arrestees. The data used in this study
were for the years 1987 to 1993. The results of this study suggest that law
enforcement agencies increase drug arrests when the agencies are allowed to keep
the proceeds from forfeitures. Several issues with this study include the use of a
very limited data set (only 24 cities) and the use of data that are over 20 years old.
In Baicker and Jacobson (2007), the authors examined several issues regarding
forfeitures, including the impact of forfeitures on drug-related arrests. This study
obtained data on federal seizures at the judicial district level for the period 1990-
1998. Data for California, Florida, Pennsylvania, Arizona, and New York were
obtained for various years in the 1990s. Arrest data were obtained from the
Uniform Crime Reports. Data are at the county level. Results suggest that when
police are allowed to keep more of the seized assets, drug-related arrests increase.
Bishopp and Worrall (2009) used data obtained from the Law Enforcement
Management and Administrative Statistics (LEMAS) survey for the years 1997 and
Mark Gius Justice Policy Journal, Spring, 2018
The Effects of Civil and Criminal Forfeitures 5
2000. It is important to note that the LEMAS surveys only collect data from law
enforcement agencies with at least 100 officers, thus omitting many smaller law
enforcement agencies. Using an OLS model, results indicate that forfeiture laws
have no statistically-significant effects on drug-related arrests.
Finally, Kelly and Kole (2016) used data from the LEMAS surveys for the years
2000, 2003, and 2007. Using a fixed effects model, their results suggest that
increases in forfeiture activity increase drug-related arrests. However, it is
important to note that the effect is very inelastic: the authors found that a 1%
increase in forfeitures result in only a 0.019% increase in drug-related arrests.
Hence, although forfeitures may influence policing behavior and arrest activity, the
effect is minimal. Kelly and Kole (2016) conclude that the introduction of civil
forfeiture for drug crimes was not one of the primary factors resulting in an
increase in drug-related arrests.
The present study differs significantly from this prior research in several ways.
First, the primary focus of this paper will be on the deterrent effects of forfeitures
and not on the positive effects of forfeitures on drug-related arrests in the 1990s
and 2000s. Second, most prior research in this area used data from the LEMAS
surveys and used data that were not very recent. In addition, LEMAS data is
collected only at the agency level, and LEMAS is conducted only once every 3 or 4
years. The present study will use annual, state-level data for the period 2000-2013,
which is much more recent than any other study on the topic of forfeitures and
crime rates.
Methods
As noted previously, the focus of this study will be on the deterrent effects of
forfeitures. All prior studies have assumed that the introduction of less restrictive
forfeiture laws resulted in an increase in drug-related arrests. The reasoning behind
this hypothesis is that lenient asset forfeiture laws create an incentive for police to
concentrate more of their efforts on drug-related crimes, primarily because they
will be able to keep some or all of the proceeds from the seizures. This increased
desire to aggressively pursue individuals possibly involved in drug-related crimes
should result in more drug-related arrests.
An important extension of this argument, however, is that this increase in drug-
related arrests may eventually increase the costs associated with engaging in drug
crimes. Thus, would-be criminals may be deterred from participating in drug-
related crimes, especially given that not only are police concentrating more of their
6 The Effects of Civil and Criminal Forfeitures
efforts on drug crimes but also because the police may seize all of the alleged
criminal’s property that is associated with the illicit drug trade (Kelly and Kole,
2016). Thus, would-be criminals may shift their focus to other types of crimes, or
they may utilize additional safeguards to lessen the probability that they will be
arrested. Hence, an increase in forfeiture activity may result in a reduction in drug-
related arrests.
In order to test this theory, the following equation will be estimated in the
present study:
Y = α0 + α1 Assets Seized + α2 Control Variables + α3 State Effects (1)
+ α4 Year Effects
In equation (1), Y denotes drug-related arrests, and Assets Seized is the per capita
amount of assets seized by the police in forfeitures. It is expected that the per
capita amount of seized assets will be negatively related to drug-related arrests.
The reason for this is because criminals would regard the increase in forfeiture
activity as an increase in the costs of engaging in criminal activity. Hence,
individuals will engage in less drug-related criminal activity, or they will take more
safeguards in order to reduce the probability that they will be arrested.
A panel data model was used to estimate Equation (1). This model is superior to
both cross-sectional and time series models for two reasons. First, panel data
models control for potentially important but unobservable state-level and year-
specific effects that may be correlated with other determinants. If a panel data
model is not used when appropriate, state-level and year-specific effects may be
omitted, and omitted variable bias may result. Second, panel data, which combines
time-series and cross-sectional data, greatly increases the degrees of freedom;
hence, one can examine state-level data even though there may be limited annual
data available.
There are two ways in which a panel data model may be estimated. If one
assumes that parameters estimates are independent of state-level effects, then
fixed effects should be used. A fixed effects model is a classical regression model
with state and year dummies. If one assumes, however, that parameter estimates
vary across states, then a random effects model should be used. A random effects
model allows for parameter estimate variation among states by utilizing a
generalized regression model where the variance is dependent upon a state-level
disturbance term. In order to determine which model is more appropriate for a
given model, a Hausman Test is used. For the present study, results of the
Hausman Test suggest that random effects would be the more appropriate model.
Mark Gius Justice Policy Journal, Spring, 2018
The Effects of Civil and Criminal Forfeitures 7
Hence, equation (1) is estimated using a random effects model that controls for
both state-level and year-specific effects.
In addition, all observations are weighted using state-level population, standard
errors are corrected using a clustering method (clustering is done at the state-level),
and a log-linear functional form is used. The reason for weighting all observations
by population is to correct for potential heteroscedasticity. Clustering standard
errors is necessary in order to account for potentially nonrandom variations within
certain groups. Finally, a log-linear function is used because it corrects for
nonlinearities in the data. Nonlinearities are sometimes due to a dependent
variable with a very large standard deviation.
Control variables that are used in the estimation of equation (1) include the
following: percentage of state population that is African-American, real per capita
income, percentage of population that has a bachelor’s degree, unemployment
rate, dummy variables denoting region of country (Northeast, South, and West),
percentage of population ages 18-24, population density, per capita alcohol
consumption, per capita prison population, percentage of population living in large
cities, and police department employees per capita. All of these variables were used
in prior studies that examined the determinants of criminal activity (Kelly and Kole,
2016; Bishopp and Worrall, 2009; Mast, Benson, and Rasmussen, 2000).
Data and Results
All data used in this study are at the state-level and are for the period 2000-2013.
This is one of the largest and most recent data sets ever used to test the impact of
forfeitures on drug-related arrests. Although prior studies in this area examined
local police agencies or counties, the state is the more appropriate geographic level
of analysis. The primary reason for this is because laws governing forfeitures are
state laws. Thus, the rules by which police agencies can seize properties are the
same for all agencies in a given state. Most prior research on this topic used LEMAS
survey data, which is at the law enforcement agency level and which exclude police
agencies with fewer than 100 officers. Hence, LEMAS data exclude a substantial
number of police agencies, including the police department of Tenaha, Texas, which
was discussed in the introduction of this paper. Using state-level data should result
in a more inclusive and exhaustive data set.
One issue with forfeiture data, however, is that few states report the value of
seized assets. Some states report only a few years of data, while other states do not
report any data at all. Unfortunately, there are also issues with federal forfeiture
8 The Effects of Civil and Criminal Forfeitures
data. Civil forfeiture and criminal forfeiture data are combined in the federal
surveys. A civil forfeiture, which is the primary focus of this paper, is an action
brought against property. The property is the defendant, and no criminal charges
against the owner of the property are necessary in order for a civil forfeiture to
proceed. A criminal forfeiture is an action brought as part of the criminal
prosecution of a defendant. It is an action against a person (the defendant in a
criminal proceeding) and requires that the government indict the property used or
derived from the crime. It would be ideal if the value of assets seized in a civil
forfeiture were separate from the value of assets seized in a criminal forfeiture, but,
unfortunately, the federal forfeiture data combine the values of assets seized for
both types of forfeitures. Hence, it is not possible to examine only the value of
assets seized in a civil forfeiture. In addition, there are two sources of data for
seized assets: the U.S. Department of Justice (DOJ) and the U.S. Department of the
Treasury (DOT). Unfortunately, Department of Justice data is calendar year while
Department of Treasury data is fiscal year; hence, they cannot be aggregated.
Given the lack of reliable data on civil forfeiture seizures, only the individual
state’s share of DOJ seizures will be used in the present study. It is important to
note that this data include only the state’s share of equitable sharing of forfeiture
proceeds. Although the data used in this study exclude state and local agency
forfeiture proceeds that were not obtained through the DOJ equitable sharing
program as well as state-level equitable sharing proceeds obtained through the
DOT, the data used in the present study are the best indicator of forfeiture activity
in a given state.
Data on state-level equitable sharing forfeiture proceeds were obtained from
Carpenter, Knepper, Erickson, and McDonald (2015). This report presents data for
those states that report state forfeiture activity and for DOJ and DOT equitable
sharing forfeitures. The federal data lumps together both civil and criminal
forfeitures. As noted previously, for purposes of this study, only the state’s share of
DOJ equitable sharing proceeds will be used as a proxy for the overall level of
forfeiture activity in a given state.
State-level drug-related arrest data were obtained from various issues of Crime
in the United States. All other data are at the state level and were obtained from
various reports published by the U.S. Census Bureau. Dollar-denominated values
were deflated using the Consumer Price Index-Urban, base year 1982-1984.
Descriptive statistics are presented on Table 1, and bivariate correlations are
presented on Tables 2-5.
Regarding some of more interesting statistics on asset forfeitures and crime
rates, the average per capita value of seized assets, in real dollars, was $0.58, and
Mark Gius Justice Policy Journal, Spring, 2018
The Effects of Civil and Criminal Forfeitures 9
the average rate of drug-related arrests (per 100,000 persons) was 410. The per
capita value of seized assets ranged from a low of $0 (Idaho in 2004) to a high of
$10.39 (West Virginia in 2007). The West Virginia data appears to be an outlier as
the next highest per capita value of seized assets was $1.61 (Florida in 2001). The
vast majority of per capita values of seized assets were less than $1 per person.
Table 1. Descriptive Statistics
Variable Mean Standard Deviation
Real per capita value of seized assets $0.58 $3.61
Percentage African-American 0.102 0.0945
Real per capita income $17,472 $2,694
Percentage with bachelor’s degree 0.267 0.049
Unemployment rate 0.059 0.021
Percentage ages 18-24 0.099 0.0093
Population density 192 257
Per capita alcohol consumption 2.36 0.48
Per capita prison population 431 177
Percentage in large cities 0.139 0.155
Police employees per capita 308 113
Rate of drug-related arrests 410 245
N = 690
Table 2: Bivariate Correlations for Seized Assets, Percentage of African-
Americans, and Per Capita Income
Real per
capita value of
seized assets
Percentage
African-
American
Real per capita
income
Real per capita value of seized
assets
1 0.0618 -0.0233
Percentage African-American 0.0618 1 -0.0816
Real per capita income -0.0233 -0.0816 1
Percentage with bachelor’s
degree
0.0034 -0.150 0.753
10 The Effects of Civil and Criminal Forfeitures
Unemployment rate 0.03282 0.198 -0.0029
Percentage ages 18-24 -0.0218 -0.0494 -0.251
Population density -0.0146 0.193 0.601
Per capita alcohol consumption 0.01809 -0.221 0.324
Per capita prison population 0.00901 0.510 -0.163
Percentage in large cities -0.02837 0.0113 0.0468
Police employees per capita 0.00754 0.211 0.181
Rate of drug-related arrests 0.02931 0.1611 0.134
Regarding correlations between the variables, the strongest correlations are
between percentage African-American and per capita prison population (0.51), real
per capita income and percentage with bachelor’s degree (0.753), real per capita
income and population density (0.601), per capita prison population and police
employees per capita (0.49241), and per capita prison population and rate of drug-
related arrests (0.41791). These correlations suggest that there is substantial
correlation between measures of economic success and between measures of
criminal activity in a given state. Interestingly, there is weak correlation between the
value of seized assets and drug-related arrests. Hence, it appears that civil and
criminal forfeitures may have minimal impact on drug-related crime. However, a
correlation analysis may be inadequate in capturing the relationship between these
two variables, especially in the context of panel data and because of the significant
variability in seized asset data.
Table 3: Bivariate Correlations for Percentage with Bachelor’s Degree, the
Unemployment Rate, and Percentage Ages 18-24
Percentage with
bachelor’s degree
Unemployment
rate
Percentage
ages 18-24
Percentage with bachelor’s degree 1 -0.00815 -0.08412
Unemployment rate -0.00815 1 -0.11997
Percentage ages 18-24 -0.08412 -0.11997 1
Population density 0.48734 0.10623 -0.2356
Per capita alcohol consumption 0.24921 -0.03833 -0.1662
Per capita prison population -0.32289 0.12033 -0.00605
Percentage in large cities 0.00626 0.2045 -0.11333
Mark Gius Justice Policy Journal, Spring, 2018
The Effects of Civil and Criminal Forfeitures 11
Police employees per capita 0.03393 -0.02764 -0.04592
Rate of drug-related arrests 0.00968 0.0401 -0.15158
Table 4: Bivariate Correlations for Population Density, Per Capita Alcohol
Consumption, and Per Capita Prison Population
Population
density
Per capita
alcohol
consumption
Per capita prison
population
Population density 1 0.00511 -0.10085
Per capita alcohol consumption 0.00511 1 0.01449
Per capita prison population -0.10085 0.01449 1
Percentage in large cities -0.10027 -0.01916 0.17288
Police employees per capita 0.13948 0.06884 0.49241
Rate of drug-related arrests 0.07248 0.04657 0.41791
As noted previously, in order to determine if civil and criminal forfeitures
deterred drug-related crimes, a random effects model that controls for both state-
level and year-specific random effects was used. All observations were weighted
using state-level population, standard errors were corrected using a clustering
method (clustering is done at the state-level), and a log-linear functional form was
used. Results are presented on Table 6. These results suggest that there is a
negative relationship between the per capita value of seized assets and the drug-
related crime rate. These results provide evidence of the deterrent effect of
forfeitures. The greater the value of seized assets, the lower is the drug-related
crime rate. It is important to note, however, that the effect is very minimal.
According to these results, for every $1 increase in the value of per capita seized
assets, the drug-related arrest rate falls by 0.092%. Given that the average value of
per capita seized assets for all states and for the entire period examined is $0.58,
the effect of forfeitures on drug arrests is negative, but very minimal.
12 The Effects of Civil and Criminal Forfeitures
Table 5: Bivariate Correlations for Percentage in Large Cities, Police Per
Capita, and Drug-Related Arrest Rate
Percentage in
large cities
Police employees
per capita
Rate of drug-
related arrests
Percentage in large cities 1 0.13134 0.19475
Police employees per capita 0.13134 1 0.67416
Rate of drug-related arrests 0.19475 0.67416 1
Regarding the control variables, states with greater percentages of college-
educated individuals, higher per capita incomes, higher unemployment rates, more
18-24 year olds, greater per capita alcohol consumption, and larger per capita
prison populations have higher rates of drug-related arrests. These results are
consistent with the results of prior studies in this area (Kelly and Kole, 2016; Mast,
Benson, and Rasmussen, 2000). In terms of magnitude, the variables that have the
greatest effects on drug-related arrests are the percentage of the population ages
18-24 and the unemployment rate. Hence, states with more unemployed young
adults have higher rates of drug-related arrests.
Table 6: Random Effects Regression Results
Variable Coefficient Test Statistic
Real per capita value of seized assets -0.0092 -2.81***
Percentage African-American -0.12 -0.17
Real per capita income 0.00011 7.97***
Percentage with bachelor’s degree 2.602 3.56***
Unemployment rate 5.21 4.80***
Percentage ages 18-24 10.17 6.16***
Population density -0.0002 -0.83
Per capita alcohol consumption 0.44 5.78***
(Continued) Variable Coefficient Test Statistic
Per capita prison population 0.00097 3.82***
Percentage in large cities 1.237 5.12***
Police employees per capita 0.00032 1.46
Region of residence – northeast -0.068 -0.40
Mark Gius Justice Policy Journal, Spring, 2018
The Effects of Civil and Criminal Forfeitures 13
Region of residence – south 0.547 3.71***
Region of residence - west 0.0746 0.57
Note: p-value<=1% ***; 1%<p-value <5% **; 5%<= p-value <= 10% *
Dependent variable = log of rate of drug-related arrests
Conclusions
According to the Fifth Amendment of the U.S. Constitution, “No person… (shall) be
deprived of life, liberty, or property without due process of law.” Unfortunately,
ordinary citizens are deprived of their property every day without any form of due
process. Law enforcement agencies may seize property in civil forfeitures with
minimal due process and very low evidentiary standards. Ostensibly enacted in
order to help wage the war on drugs, civil forfeiture has morphed into a ready
source of income for local and state law enforcement agencies.
Although it would be reasonable to assume that civil forfeitures were created in
order to discourage individuals from engaging in criminal activity, no prior research
has attempted to ascertain if there is a negative relationship between the value of
assets seized and crime rates. Most prior research has attempted to determine if
forfeiture activity resulted in an increase in drug-related arrests, primarily due to
the fact that most forfeitures deal with the seizure of property associated with
drug-related crimes (Kelly and Kole, 2016; Bishopp and Worrall, 2009; Baicker and
Jacobson, 2007; Mast, Benson, and Rasmussen, 2000). These studies assumed the
police would engage in more arrests and hence more forfeitures in order to obtain
needed funds for their departments.
The present study took a different approach and attempted to determine if
there was a deterrent effect associated with forfeitures. In other words, did an
increase in forfeiture activity result in an increase in the costs associated with being
involved in drug-related activity and thus result in a decline in drug-related crime?
In order to test this hypothesis, the present study estimated a model of drug-
related arrests using a random effects model and state-level data for the period
2000-2013. Results of this study suggest that, although forfeiture activity had a
significant and negative effect on drug-related arrests, the effect was very minimal.
Even if the value of per capita seized assets were doubled, drug-related arrests
would fall by only 0.05336%.
The benefits of seizing assets (reduction in drug-related arrests) must be
balanced against the costs of seizing assets (lack of due process in depriving
someone of their property). According to the results of this study, the benefits of
14 The Effects of Civil and Criminal Forfeitures
forfeitures are very minimal, while the constitutional costs in the form of the lack of
due process may be quite substantial. Hence, given the constitutional issues
surrounding civil forfeitures and the minimal effects on arrest rates of such
forfeitures, it would be in the public interest to amend the Comprehensive Crime
Control Act (CCCA) of 1984 so that the equitable sharing of forfeiture proceeds
among federal, state, and local agencies would no longer be permitted. Amending
the CCCA in this manner would remove the incentives that state and local agencies
have to engage in seizures and forfeitures. Such a revision of the CCCA would only
very minimally affect the drug-related arrest rate but would, at the same time,
restore some degree of due process to forfeiture proceedings.
It is important to note, however, that all forfeiture research is subject to criticism
given the lack of accurate and reliable data on forfeiture activity. There are two
primary problems with forfeiture data. First, depending on the type of assets seized
or particular police investigation involved, the value of seized assets can vary
dramatically from year to year for a given state. For example, in Idaho, in 2002, the
value of seized assets was $0; in 2004, it was $1,526,064; in 2008 it was only
$190,800. These dramatic swings in forfeitures make it difficult to establish any type
of statistical relationship between forfeiture activity and drug-related arrests,
especially given that drug crime rates are not as volatile as forfeitures.
Second, one of the primary reasons why equitable sharing is so enticing for
states is because they can request federal authorities to “adopt” assets as a way to
circumvent restrictive state laws regarding the disposition of seized assets. Hence,
it stands to reason that police agencies in states that have fewer such restrictions
may opt to not participate as frequently in the equitable sharing program as police
agencies in those states that have very restrictive forfeiture laws. Thus, the DOJ
data may be more indicative of the restrictiveness of state forfeiture laws rather
than representative of the relationship between drug crimes and forfeiture activity.
Finally, as noted previously, most states do not report the value of seized assets
and the agency-level data available through LEMAS is incomplete because smaller
agencies are excluded. Although not ideal, the DOJ equitable sharing data is the
best state-level data on forfeiture activity that is currently available.
For states that do report forfeiture data, it is usually incomplete and is limited in
terms of years of availability. Regarding federal seizure data, seizures from both
civil and criminal forfeitures are lumped together, and data for the various federal
agencies engaged in forfeitures do not conform to a standard calendar. Finally,
while agency-level data on forfeitures are available from the LEMAS survey, this
data exclude smaller police agencies, which are usually the agencies involved in
some of the more egregious abuses of civil forfeitures. Hence, in order to more
Mark Gius Justice Policy Journal, Spring, 2018
The Effects of Civil and Criminal Forfeitures 15
properly estimate the effects of civil forfeitures on criminal activity, the collection of
data on both civil and criminal forfeitures must be improved upon and expanded at
both the state and federal levels.
References
Baicker, Katherine and Mireille Jacobson (2007) “Finders keepers: forfeiture laws,
policing Incentives, and local budgets.” Journal of Public Economics, 91, 2113-
2136.
Bishopp, Stephen and John Worrall (2009) “Do state asset forfeiture laws explain
the upward trend in drug arrests?” Journal of Crime and Justice, 32, 2, 117-138.
Carpenter, Dick, Lisa Knepper, Angela Erickson, and Jennifer McDonald (2015)
“Policing for profit: the abuse of civil asset forfeiture.” Arlington, VA: Institute for
Justice.
Holcomb, Jefferson, Tomislav Kovandzic, and Marian Williams (2011) “Civil asset
Forfeiture, equitable sharing, and policing for profit in the United States.” Journal
of Criminal Justice, 39, 273-285.
Kelly, Brian and Maureen Kole (2016) “The effects of asset forfeiture on policing: A
panel approach.” Economic Inquiry, 54, 1, 558-575.
Mast, Brent, Bruce Benson, and David Rasmussen (2000) “Entrepreneurial police
and Drug enforcement policy.” Public Choice, 104, 3, 285-308.
Stillman, Sarah (2013) “Taken.” The New Yorker.
Worrall, John (2001) “Addicted to the drug war: the role of civil asset forfeiture as a
Budgetary necessity in contemporary law enforcement,” Journal of Criminal
Justice, 29, 171-187.
About the Author
Mark Gius, Ph.D. is a Professor of Economics at Quinnipiac University, Hamden,
Connecticut. Dr. Gius has published extensively on the topics of gun control and
crime. His most recent research has examined the impact of stand-your-ground
laws on crime and the impact of gun control laws on school shootings. E-mail:
Mark.gius@quinnipiac.edu