The Impact of Cannabis Regulation on Cannabis Consumption in Europe
Paper prepared for the 5th Regulatory Governance Conference, 25 – 27 June 2014, Barcelona
(Working Paper – very first draft – please do not cite without the permission of the authors)
Andreas Raschzok, [email protected]
Christian Adam, [email protected]
Christoph Knill, [email protected]
Abstract
This paper examines whether policies addressed at cannabis possession and consumption can
be shown to actually influence the use of cannabis among the general public. While this
question has already received widespread scholarly attention, we identified several
shortcomings within the literature that motivated the reassessment of this question by
different means. Thus, the paper contributes to existing research by employing an innovative
approach to measure the restrictiveness of rules, sanctions, and enforcement regarding
cannabis possession and consumption that allows us to systematically assess the effect of
different kinds and extents of cannabis policy reform on cannabis prevalence. Furthermore, it
conducts a large scale comparison of the impacts of Cannabis policy in 16 Western European
countries. By conducting regression analysis with fixed country effects, we are able to isolate
correlation between changes in policy and prevalence within countries while controlling for
the potential influence of omitted confounding variables. Adopting this approach, the paper
produces three results. First, the analysis shows that prevalence after reforms has not
increased. Second, liberalizing enforcement strategies can even lead to decreasing prevalence.
Third, this result is, however, strongly influenced by the experiences in the United Kingdom
with such a strategy.
1
1. Introduction
For advocates of drug legalization, the events of 1 January, 2014 in Colorado mark a
milestone: Since then, citizens of the US state are legally allowed to purchase and possess up
to one ounce of marijuana for recreational use. Even more so, Colorado has also – albeit
under strict conditions – permitted the cultivation and sale of cannabis. With this new policy
approach towards cannabis, Colorado has not only become one of the most liberal states
within the USA but it has also adopted one of the most liberal cannabis policies within the
group of Western democracies.1
One of the central questions surrounding cannabis policy reform in Colorado and everywhere
else in the world is the one about likely effects of different policy approaches: will this lead to
a substantial increase in the prevalence of cannabis use and abuse? Existing research tends to
negate this question as most studies fail to identify significant increases in cannabis
prevalence after more liberal policy approaches have been adopted (for a review see Kilmer
2002). This paper tries to contribute to this line of research by adopting an alternative
conceptual and methodological approach to answering this research question.
Since we are unable to randomly assign different policy approaches to different countries as
we would in a controlled experiment, the step from observing correlation to drawing
conclusions about causality becomes inherently more difficult. Existing research is
characterized by two dominant approaches to nevertheless identifying policy impacts. On the
one hand, there are cross-sectional studies that compare cannabis prevalence at one specific
point in time across several different jurisdictions adopting different policy approaches (e.g.,
MacCoun 2001; Pacula et al. 2013; Reinarman et al. 2004; Reuband 1995). It is particularly
difficult to assess causal linkages between cannabis policy and cannabis prevalence in such
cross-sectional research designs. First, based on such designs, we cannot determine whether
the prevalence rate at the specific point in time analyzed is caused by or is itself the cause of
the specific policy regime in place at that time. Second, it is difficult to isolate the influence
of policy on prevalence (let alone different aspects of policy) from the influence of other
jurisdiction-specific confounding factors. Therefore, the validity of results breaks down to a
debate about whether the ‘right’ control variables have been included.
On the other hand, studies therefore focus on time-series data that allow for comparing
prevalence rates before and after specific reforms. Mostly, these time-series data are
1
Although the amended provisions impinge on federal law, authorities in Washington explicitly tolerate the new
drug policy.
2
complemented by cross-section data to avoid focusing on just one reforming jurisdiction and
instead be able to contrast prevalence trends in this jurisdiction with trends in other – nonreforming – jurisdictions (e.g., Donnelly et al. 1995; Lenton 2000; Model 1993) (Harper et al.
2012). This approach is able to better deal with the potential problem of reversed causality,
introduces a “quasi” control group, and is able to systematically control for jurisdictionspecific confounding factors.
While this approach is able to better deal with the methodological challenges inherent to the
analysis of policy impact, we identify two shortcomings in existing research of this kind. First
of all, there is a problem in terms of measuring the independent variable, i.e. policy reform.
Typically, these approaches provide detailed qualitative descriptions of cannabis policy
(reforms) that are consequently translated into simple binary quantitative measures of the
binary variables. In the context of time-series approaches, this is usually translated into a
binary variable indicating the time before and after the specific reform was introduced. This
approach makes it difficult to assess which aspects of cannabis policy reforms do or do not
affect prevalence. Are all of the aspects of the analyzed policy approaches or reforms equally
important? How does, for example, the “decriminalization” reform in Portugal (Hughes und
Stevens 2010) compare to the “decriminalization” reforms in some US states (Pacula et al.
2005)? Should we expect similar (non-)effects because these were essentially the same
reforms? Making such judgments requires systematic and transparent ways of comparing
different aspects of cannabis policy. Secondly, existing scholarship tends to suffer from a
restricted empirical scope. Specifically, most studies of this kind focus on developments
within countries at the state level, mostly within the United States and Australia. Where
studies try to adopt a time-series cross-section approach with a focus on European countries,
they assess only few countries through qualitative means (e.g., Hughes und Stevens 2010).
This paper addresses both of these shortcomings. It contributes to existing research by
employing an innovative approach to measure the restrictiveness of rules, sanctions, and
enforcement regarding cannabis possession and consumption that allows us to systematically
assess the effect of different kinds and extents of cannabis policy reform on cannabis
prevalence. Furthermore, it conducts a large scale comparison of the impacts of Cannabis
policy in 16 Western European countries. By conducting regression analysis with fixed
country effects, we are able to isolate correlation between changes in policy and prevalence
within countries while controlling for the potential influence of omitted confounding
variables.
3
Adopting this approach, the paper produces three results. First, the analysis shows that
prevalence after reforms has not increased. Second, liberalizing enforcement strategies can
even lead to decreasing prevalence. Third, this result is, however, strongly influenced by the
experiences in the United Kingdom with such a strategy.
2. Theory and Analytical Puzzle: Deterrence – Effective or Counterproductive?
In Western Europe, activities linked with the personal use of cannabis, such as possession or
purchase, are de jure prohibited and punishable in all countries (Adam und Raschzok 2014).
However, the level of sanctions defined by national drug laws differs substantially; it ranges
from administrative sanctions (e.g., in Portugal or Italy) to tough prison sentences (e.g., in
France). Furthermore, countries show differences regarding legal or prosecutorial rules on the
enforcement of prosecution and punishment of offences. In the Netherlands, for example, the
police is urged by prosecutorial guidelines not to take action against drug users; in Germany,
the drug law enables the public prosecutor to refrain from prosecution in the case of
consumption-related offences; in Sweden and Norway, however, such special provisions were
not established; here, public prosecutors normally have to press charges also in case of
consumption-related delicts.
The reduction of illegal drug use through deterrence is one of the main rationales behind the
prohibition and sanctioning of consumption-related activities. Specifically, the threat of
prosecution and sanctioning is expected to minimize the spread of cannabis consumption
throughout society. However, the utility of restrictive approaches has increasingly been
questioned over the last decades.
There are several arguments challenging restrictive policy approaches. First, such policies are
costly to enforce taking up valuable and scarce resources of the police and judicial system that
could be employed otherwise (MacCoun und Reuter 2004). Second, the harsh punishment of
relatively minor cannabis related offences in the form of criminalization and incarceration of
individual consumers can set such offenders on a track of more serious drugs and offences
(MacCoun und Reuter 2004). Finally, restrictive policy approaches represent far-reaching
interferences with individual liberties that modern democracies have to justified.
While these aspects can be read as arguments for more liberal cannabis policies, the main
argument standing in the way of such steps is the fear that this might send a wrong signal to
(potential) consumers regarding the dangers of cannabis consumption (MacCoun und Reuter
2004). Against this background, the main question that existing research on the effects of drug
4
policy has posed is whether restrictive policy approaches towards cannabis are an effective
deterrent preventing a surge in cannabis consumption within society.
Yet, existing research mostly negates this question. Steps towards more liberal cannabis
policies are generally not seen to be associated with more widespread use of cannabis
throughout society (Babor et al. 2009; Hughes und Stevens 2010; Kilmer 2002; Room und
Reuter 2012). As Babor et al. (2009) state, “[t]here is no clear-cut case in which a reduction in
the form or enforcement of the prohibition on use or possession resulted in a substantial
change in consumption of the drug. There are a number of cases where there was no
measurable change in consumption from such a policy change”. Furthermore, research has
also not found significant differences between varyingly severe regulatory regimes. Thus,
Kilmer comes to the conclusion that “jurisdictions with more liberal possession laws do not
necessarily have higher prevalence rates” (Kilmer 2002).
In fact, if we look at evidence from the United Kingdom (UK), we might even conclude that a
more liberal policy approach can even lead to decreasing cannabis prevalence among the
general public. In 2003, the UK effectively changed the rules guiding enforcement of its
cannabis regime by giving police officers the opportunity to abstain from using police
cautions for first-time offenders caught in the possession of cannabis (for personal use,
without aggravating circumstances). Such a caution involved formal prosecution in
(magistrate or crown) court and remained in the criminal record of the offender. Instead,
police officers were now able to hand out a cannabis warning directly on the street. While this
warning is recorded, it does not involve formal prosecution and does not enter the criminal
record of individuals (Smith und Dodd 2009). Furthermore, cannabis was downgraded in the
UK from a grade B to a grade C drug which would effectively lower the highest applicable
sentences for punishable offences in 2004. While cannabis was again upgraded to the group
of grade B drugs in 2009 (Turnbull 2009; Warburton et al. 2005), the system of cannabis
warnings representing a permissive enforcement approach towards individual consumer being
caught possessing cannabis for the first time remained in place. Interestingly, these policy
changes in the UK have not only left cannabis prevalence unaffected, they coincided with a
decrease in (self-reported) cannabis prevalence among the general public (see figure 1).
Whether this relationship is due to a reduced “allure of the forbidden” in response to the more
permissive approach or causally affected this policy change at all remains unclear. In any
case, however, the UK experience does confront existing research with an analytical puzzle.
5
4
1 month prevalence ages 15 - 64
5
6
7
Figure 1: Decreasing prevalence in the UK
1995
2000
2005
2010
year
Note: the vertical line identifies the year in which the UK switched to the more permissive enforcement
approach including cannabis warnings. Prevalence data were obtained from the European Monitoring Centre for
Drugs and Drug Addiction (EMCDDA).
Against the background of this analytical puzzle as well as in response to the conceptual and
methodological shortcomings of existing research outlined above, this paper revisits the
question about the impact of cannabis policy on cannabis consumption.
3. Measuring and Comparing Cannabis Policy Approaches
This paper attempts to contribute to the existing scholarship by applying an unusually detailed
and systematic measurement concept for different forms and extents of cannabis policy
reforms. Specifically, our concept for measuring and comparing the (changing) level of
restrictiveness of cannabis policy regimes consists of three dimensions. The concept
distinguishes between (a) the statutory rules governing cannabis use and possession, (b) the
statutory sanctions imposed in the case of illegal cannabis possession (for personal use), and
(c) the statutory or prosecutorial provisions on the enforcement of prosecution and
punishment of possession offences.
6
Rules dimension: The rules dimension measures the extent to which a drug law restricts the
use and possession of cannabis. The measurement scheme consists of three levels: (1) the
general policy paradigm, (2) personal requirements, and (3) procedural rules. With regard to
the first level, the scheme differentiates between three policy paradigms: (a) prohibition, (b)
partial prohibition, and (c) permission. States that have adopted a prohibitive paradigm
completely prohibit cannabis consumption and possession. Under the partially prohibitive
paradigm, possession is completely forbidden, whereas consumption is allowed or restricted
to a certain degree (through personal requirements). Countries that maintain a permissive
paradigm restrict consumption and possession only to a limited extent (through personal
requirements and/or procedural rules) or not at all. The assumption that guides the ordering of
the three paradigms is that the prohibition of cannabis consumption and possession is
regarded as more restrictive than a ban on possession alone. Likewise, regulatory regimes that
completely prohibit possession (but not consumption) are considered more restrictive than
regimes that tolerate possession and consumption or restrict both activities only to a limited
extent.
With regard to personal requirements, the measurement scheme distinguishes between the
existence and absence of situational or locational requirements that the consumer must satisfy
in order to consume or possess cannabis legally. For example, the current Spanish drug law
forbids the consumption and possession of drugs (for personal use) in public, but does not ban
either activity when it takes place in private. In terms of procedural rules, the scheme
distinguishes between the existence and absence of restrictions on the quantity of cannabis
that an individual can legally possess. Alternatively, restrictions on the intention of cannabis
possession are taken into account. For example, in Spain, the possession of drugs intended for
personal use was not illegal or punishable throughout the 1980s. Since procedural rules are
logically irrelevant with regard to consumption and only play a role when cannabis possession
is not completely prohibited, the third level of the measurement scheme is not applicable in
cases of the prohibitive or partially prohibitive paradigm.
Table 1: Summary of the ordinal measure of rules
Paradigm
Locational
requirements
Procedural requirements
7
Ordinal
score
Prohibition
n.a.
n.a.
3
Yes
Yes
[e.g.
only
private]
in
[maximum
defined]
amount
No
[no amount defined]
Partial prohibition
2.75
2.50
Yes
[maximum
defined]
No
amount
No
[no amount defined]
2.25
2
Yes
Yes
[e.g.
only
private]
in
[maximum
defined]
amount
No
[no amount defined]
Permission
1.75
1.5
Yes
[maximum
defined]
No
amount
No
[no amount defined]
1.25
1
Sanctioning dimension: The sanctioning dimension measures the sanctions for illegal
possession of a small amount of cannabis for personal use. The sanctioning dimension
consists of 16 categories of possible sanctions that are ordered according to their severity. The
scale ranges from ‘no sanction’ (1) to life sentence in jail (16). Non-custodial sanctions such
as administrative sanctions (2) and fines (3) are considered weaker than custodial sanctions.
These start with category (4). Specifically, categories 4 to 6 indicate sanctions where low (4),
medium (5), or high (6) prison sentences can still be substituted by fines. Categories 7 to 9
capture sanctions where low (7), medium (8), or high (9) prison sentences can either be
substituted or complemented by fines. Categories 10 to 15 indicate systems in which
offenders face mandatory prison sentences of low duration without (10) and with (11)
additional fines, of medium duration without (12) and with (13), and of high duration without
8
(14) and with (15) additional fines. Generally, a jail sentence of six months or less is
considered ‘low’, a sentence between six months and two years is ‘medium’, and a sentence
longer than two years is ‘high’. The scale ends with a life sentence in jail as most extreme
form of sanction (16).
Table 2: Summary of the ordinal measure of sanctions
Sanction
Ordinal score
Life/Death
15
Prison, mandatory, high, fine
14
Prison, mandatory, high, no fine
13
Prison, mandatory, medium, fine
12
Prison, mandatory, medium, no fine
11
Prison, mandatory, low, fine
10
Prison, mandatory, low, no fine
9
Prison, substitutable (and/or), high
8
Prison, substitutable (and/or), medium
7
Prison, substitutable (and/or), low
6
Prison, substitutable (or), high
5
Prison, substitutable (or), medium
4
Prison, substitutable (or), low
3
Fine
2
Administrative sanctions
1
No sanctions
0
Enforcement dimension: The enforcement dimension measures the degree of enforcement of
the sanctions. To assess this degree, we check for the existence of special drug law or
prosecutorial provisions which specify how to implement the sanctions defined in the drug
law. In general, the enforcement dimension is only relevant if cannabis possession is
classified as a (a) criminal and (b) punishable offence in the drug law. If cannabis possession
is defined and punished as an administrative offence, we assume that such lenient penalties
are normally enforced. If the law states that cannabis possession is an offence that is
9
prohibited, but not punishable, we logically do not have to check for the enforcement of nonexistent sanctions.
However, if cannabis possession is a criminal and punishable offence, we distinguish between
three levels of enforcement: (1) Obligatory prosecution and punishment, (2) potential
refraining from prosecution and / or punishment, and (3) obligatory refraining from
prosecution and punishment. With regard to the level (1), the drug law does not include
special provisions concerning the refraining from punishment; prosecution and sanctioning
are the rule. According to level (2), the drug law provides the opportunity for the public
prosecutor or the court to refrain from prosecution or punishment. Regarding level (3),
prosecutorial guidelines or the drug law determine that the enforcement authorities have to
refrain from prosecution and punishment.
Table 3: Summary of the ordinal measure of enforcement
Enforcement
Ordinal score
Obligatory prosecution and punishment
Potential refraining from prosecution and /or
1
0.5
punishment
Obligatory refraining from prosecution and
0
punshment
4. Methodological Approach
There are several inherent methodological challenges to analyzing the effects of cannabis
policy. First, epidemiological studies in this field tend to rely on survey data that capture selfreported cannabis use (Hughes und Stevens 2012; Pacula et al. 2005; Reinarman et al. 2004;
Reuband 1995). Obtaining such data on the prevalence of cannabis use is cumbersome and
expensive. Consequently, data availability on the dependent variable is limited (see for
example the limited availability of complete time series evident in figure 3).
Second, independent variables of interest, i.e. public policy, cannot be assigned in a controlled
way like in an experimental setting. Instead we rely on natural experiments in the form of
policy-makers changing the policy status quo. Since such experiments are rather rare, we not
10
only suffer from limited data on the dependent variable but also have to deal with limited and
non-random variation on the independent variables.
These two challenges have contradictory implications. The second challenge of limited nonrandom variation on the independent variables calls two things. To begin with, it requires
controlling for country-specific confounding variables. In addition, it calls for exploiting the
analytical leverage of large-scale comparison of developments in as many countries as
possible. Yet, the first challenge, i.e. the costliness of obtaining comparable epidemiological
data on a regular basis for many countries, makes exactly this endeavor difficult.
In consequence, many studies tend to answer these contradictory challenges by focusing on
just one jurisdiction before and after a reform. Thereby, studies obtain the required variance
on the independent variable to assess the impact of reform. At the same time, however, they
restrict this variance to just one country. In consequence, they are unable to control for
influences like general processes of modernization and value change that would affect all
countries in a similar way and might lead to a more relaxed attitude towards “soft drugs” like
cannabis.
Why should this be relevant? Assume we identify a slight increase of cannabis prevalence in a
country for the years after liberalizing cannabis policy. Without controlling for the trend in
prevalence in countries within the same cultural hemisphere, any analysis will suggest that the
increase in prevalence is the result of the specific policy change. If, however, these results are
analyzed in the light of data suggesting that prevalence has slightly increased within the
observed time period in a series of countries that have not changed their policy approaches,
our conclusions are likely to be different. Only if the increase in prevalence of the reforming
countries is substantially larger than the increase in prevalence in the inactive countries, will
the analysis suggest a correlation between the liberal reform and the increased prevalence. In
fact, only when including inactive countries we have a chance to assess whether the increase
in prevalence in the reforming country might even be substantially smaller than the increase
in prevalence in countries with persistent policy approaches. Such a result would suggest that
liberal cannabis reforms can even decrease cannabis prevalence. Against this background, our
analysis includes 16 Western European countries that have shown varying degrees of activity
regarding cannabis policy reform.
Yet, since independent variables are not assigned at random to different countries, we need to
make sure to control for omitted and potentially confounded variables making certain
countries not only more prone to reform but also make them rank higher on prevalence rates.
11
Applying fixed effects regression analysis allows us to focus on effects of policy changes
within countries before and after reforms while at the same time increasing the variation on
the independent variable. This increase in variation on the independent variable is simply the
result of including more countries than usual in the analysis. This enables us to compare the
effects of more natural policy experiments and to control for experiences in countries that
have not carried out such policy experiments. Furthermore, by assuming fixed effects for
different countries, we effectively control for the impact of omitted variables responsible for
the time constant unobserved cross-country differences in prevalence rates (Woolridge 2010).
5. Data
In terms of data, our paper draws on original data collected as part of the MORAPOL
research project headed by Christoph Knill (LMU Munich) and funded by the European
Research Council (ERC). MORAPOL analyses the regulatory development in nine so-called
morality policies – among others drug, gambling, abortion, and prostitution policy – for 26
OECD countries and over a period of fifty years (1960 – 2010). Data on the development of
drug regulation were gathered by systematically examining relevant national laws and other
legal documents, as well as central executive or judicial documents.
The dependent variable analyzed in this paper is cannabis consumption. We examine the
effects of drug regulation on two kinds of prevalence rates among the general public (ages 1564): one year prevalence, and one month prevalence of cannabis use. We draw on data
generated by national general population surveys and compiled by the European Monitoring
Centre for Drugs and Drug Addiction (EMCDDA). With regard to Switzerland, we use data
provided by the Suchtmonitoring Schweiz (2014). Since this data source only includes one
month prevalence, Switzerland drops out of analyses of policy impact on one year prevalence.
Geographically, we focus on Western European countries. Specifically, we analyze 16
Western European countries; these are the EU-15 countries without Luxembourg and
supplemented by Norway and Switzerland. The case selection is determined by the data on
national drug regulation provided by MORAPOL. The period of analysis comprises the
period from 1990 to 2010. We restrict the analysis to 1990 since the EMCDDA does not
provide prevalence rates prior to that year. Furthermore, due to data restrictions on the
independent variable (MORAPOL’s data range from 1960 to 2010), our analysis does not
include the years after 2010.
12
6. Empirical Analysis
Different countries have shown varying levels of activity regarding policy reforms addressing
cannabis consumption and possession. Figure 2 illustrates reform activities within our sample
of 16 Western European countries between 1990 and 2010. The figure provides a very rough
measure of reform activity, as it does not take into account how far reaching reforms were.
Any change regarding the rules on cannabis possession and/or consumption, the level of
sanctions that formally apply in case of violation of these rules, and the enforcement of this
policy regime is counted equally as one instance of reform. Nevertheless, we see that
countries like Austria, Germany or Greece have maintained stable cannabis policy regimes
and enforcement schemes since 1990.
In contrast, we do observe reform activity in countries like Italy, Spain, Belgium, France or
Portugal. Specifically, Italy has adjusted the rules applying to cannabis consumption and
possession twice within the observation period and adjusted the level of sanctions once. In
1990, consumption was formally prohibited and administrative sanctions for the illegal
possession of drugs (for personal use) – which had not been punishable prior to the reform –
were introduced. This ban on drug consumption was abolished just three years later, however.
Belgium and Portugal are the only two countries within our sample that have adopted changes
on all three dimensions of cannabis policy captured by our analysis: rules, sanctions, and
enforcement. Portugal made drug consumption an illicit activity in 1993, but decreased the
sanctioning level for illegal drug possession. In 2000, Portugal replaced custodial sanctions
for drug possession by administrative sanctions. Belgium eliminated its custodial sanctions
for drug possession in 2003 and established a system of low monetary penalties (“police
fines”). In both countries, the reforms on the sanctioning level in 2000 and 2003 respectively
involved changes on the enforcement dimension: Prior to both reforms, illegal possession
resulted in criminal proceedings which – however – could be stopped by the public
prosecutor. The new sanctioning regimes no longer foresee criminal proceedings.
Enforcement of the more lenient penalties is now, however, obligatory.
Figure 2: Changes in national policy addressing cannabis consumption and possession 1990 –
2010.
13
Austria
Germany
Greece
Ireland
Italy
Netherlands
Norway
rules
Spain
sanctions
Sweden
enforcement
Switzerland
Belgium
Denmark
Finland
France
Portugal
United Kingdom
0
1
2
3
number of reforms
4
While this measure is rather crude – ignoring the extent and direction of policy change – it
allows us to carry out a preliminary assessment of the impact of reform activities on the
prevalence of cannabis consumption. Some of these reforms are carried out in the hope to
reduce prevalence rates. Other changes are adopted in the hope to leave prevalence
unaffected. The main idea behind a more liberal enforcement approach in the UK was, for
example, to liberate scarce policy resources for other tasks while hoping for cannabis
prevalence not to be negatively affected. In consequence, no matter the direction and extent of
the policy changes carried out, it is plausible to assume that policy-makers always hoped for
prevalence rates at least to remain stable; i.e. not to increase.
Table 4 presents results of a linear regression with fixed country effects. It provides estimates
for the effect of changes of (a) rules, (b) sanctions, and (c) enforcement regarding cannabis
policy while controlling for cross-country differences in the level of prevalence and
controlling for the development of prevalence in the absence of reform. Independent variables
are coded as binary variables taking the value of zero for all years before a specific policy
change (including the year of the reform) and the value of one for all subsequent years.
14
Because the one year prevalence data suggest a slight linear increase over time (see
appendix), we include a linear time trend as additional control variable. Avoiding to do so
would enhance the risk of producing “spurious” regression results simply resulting from the
regression of one trending variable (before and after policy change) on another trending
variable (one year prevalence). Nevertheless, the results (although not explicitly reported) are
robust even when leaving this time trend aside.
Table 4: Assessing the relationship between reform action and cannabis prevalence
After a change of ...
rules
sanctions
enforcement
time trend
constant
(1)
with UK
one year
0.408
(1.072)
-1.969***
(0.700)
0.127***
(0.0422)
0.773
(1.653)
(2)
no UK
one year
0.461
(1.078)
-0.0499
(1.037)
0.121***
(0.0443)
-0.204
(1.734)
(3)
with UK
one month
1.346
(1.309)
0.327
(0.695)
-1.324***
(0.408)
3.199***
(0.453)
(4)
no UK
one month
0.456
(1.648)
0.327
(0.726)
-0.433
(1.015)
2.786***
(0.602)
observations
84
70
81
67
R-squared
0.168
0.183
0.149
0.010
No. of countries
15
14
16
15
Note: Unstandardized coefficients. Estimates result from fixed effects linear regression.
Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.
Essentially the analysis makes three suggestions. First of all, the analysis does not provide
evidence supporting the fear that cannabis reforms have increased cannabis prevalence among
the general public (ages 15-64) in a statistically significant way. While there is a statistically
significant (linear) increase in prevalence over time (“time trend”), there is no evidence for
this increase to be any stronger in countries that have reformed their cannabis policy approach
in any way (see the insignificant interaction term in table 5). Secondly, models (1) and (3)
even seem to suggest a negative relationship between enforcement reforms and prevalence.
Specifically, after enforcement reforms were adopted, prevalence rates appear significantly
lower than before enforcement reforms. This result holds for both, the one year as well as for
the one month cannabis prevalence. Thirdly, however, this result is largely driven by the
15
developments experienced by the UK. Excluding this influential case – which does not only
enter the analysis with an unusual development of the dependent variable (a substantial
reduction of prevalence) but also with a relatively high number of observations due to the
greater data availability on the dependent variable – makes these results disappear.
Table 5: Assessing the interaction between policy reform and the linear time trend
Reform X time
After any reform
Time trend
constant
Observations
R-squared
Number of c_id
(1)
(2)
one year
one year
with UK
no UK
-0.254
-0.177
(0.210)
(0.440)
8.704
6.938
(8.560)
(17.53)
0.345*
0.291
(0.206)
(0.439)
-6.849
-6.462
(8.318)
(17.43)
80
67
0.130
0.129
15
14
Note: Coefficients are unstandardized. Estimates result from linear regression with fixed country effects.
Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.
Yet, the impact of policy reform on prevalence might not simply depend on whether a policy
reform was carried out or not. Instead, the impact should depend on the content of policy
reform. Consequently, we now focus on how and to what extent rules, sanctions, or
enforcement have changed and whether this can be shown to have any substantial effect on
cannabis prevalence.
Figure 3 illustrates the empirical developments regarding rules, sanctions and enforcement of
cannabis policy addressing individual consumers according to our measurement approach
16
presented above. Furthermore, the figure combines these developments with the available
information of cannabis prevalence among the general population as provided by the
EMCDDA.
The figure highlights at least four things. First of all, rules have remained rather stable with
our sample throughout the observation period. Part of the reason for this is that these countries
have limited their ability to change these rules by committing to the UN Drug Conventions
(Bewley-Taylor 2003; Boister 2001). Secondly, the figure indicates some more reform
activity with respect to the sanctions applying to violations of rules on consumption and
possession. Specifically, several countries have reduced the level of sanctions for these
offences, such as Portugal through its well-known “decriminalization” reform. For UK, no
change in sanctions is coded despite the reclassification of Cannabis from Class B to Class C
drug in 2004 and the reversal back to Class B drug in 2009. This is because these changes
only affected the maximal level of sanctions when Cannabis possession was treated as
indictment offence. We coded the maximal severity of sanctions when Cannabis possession
went on trial as summary offence. In this case, the reclassification had no effect on sanctions.
Thirdly, the figure highlights that enforcement reforms should generally be interpreted in the
light of existing rules and sanctions. We see for example that while Belgium has liberalized
its rules and sanctions in 2003, we record that this more permissive regime is now enforced
more restrictively. In case of violations of the newly established cannabis regime,
enforcement of (lenient and non-criminal) sanctions is now obligatory. Prior to this reform,
the public prosecutor had the possibility to refrain from punishment. The same holds true for
Portugal. Finally, the figure indicates that enforcement reforms do not indicate a uniform
trend. While enforcement has become more restrictive in Denmark, for example, others have
become more permissive. The more permissive enforcement of legally defined rules and
sanctions in the UK, for example, reflect the introduction of cannabis warnings mentioned
above.
Figure 3: Illustrating country specific patterns of cannabis policy and cannabis prevalence
17
Belgium
Switzerland
Germany
Denmark
Spain
Finland
France
UK
Greece
Irland
Italy
Netherlands
Norway
Portugal
Sweden
0
5 10 15
0
prevalence in %
0
5 10 15
h ig h
lo w
h ig h
lo w
0
lo w
5 10 15
h ig h
restrictiveness of IVs
lo w
5 10 15
h ig h
Austria
1990
2000
2010 1990
2000
2010 1990
2000
2010 1990
2000
2010
year
rules
sanctions
one year prevalence
one month prevalence
enforcement
Graphs by countries
Note: For illustrative purposes in this graph only, we subjected the values for rules and enforcement to a linear
transformation (rules x 5; enforcement x 15) in order to have all variables range from 0 to 15 allowing us to
better identify value changes on this common scale.
Using this data to reassess the research question of whether or not cannabis policy affects
cannabis prevalence, we again find that the answer to this question critically relies on how we
deal with the UK experience. If we include the UK in the analysis, more restrictive
enforcement is shown to be associated with increasing prevalence while more lenient
enforcement is suggested to decrease prevalence (see models 1 and 2). Interestingly, this
effect of enforcement reform seems to be independent of the regime that is to be enforced.
Otherwise, we would expect to see the effect of enforcement reforms to vary with the level of
restrictiveness of the policy regime. In other words, we would expect to see an significant
interaction term in model 3. This is not the case, however.
This result would not support existing research challenging the validity of the argument that
restrictive policy has a deterrent effect. Even more so, these results would suggest that more
lenient enforcement could even lead to lower prevalence rates. In this sense, the results could
18
be interpreted as support for arguments accusing restrictive policy regimes of creating an
“allure of the forbidden”.
Yet, the analysis also clearly indicates that – again – these results are strongly influenced by
the UK experience where a more permissive approach to enforcement coincided with a
reduction of prevalence. When we exclude the UK from the analysis, we find no evidence for
such a correlation between changes in enforcement and the one month prevalence (see models
4 – 6). This result also holds for one year prevalence (although this result is not explicitly
reported).
Table 6: Assessing the relationship between the direction and extent of policy reform and
cannabis prevalence
In sum, three findings can be highlighted. First of all, the analysis shows that prevalence after
reforms has not increased. This result provides further support to existing findings
challenging the validity of the “deterrence-argument”. We find no relationship between a
liberalization of cannabis policy in any form and an increase in cannabis prevalence among
19
the general public. The second finding that we would like to highlight is that while we do find
some evidence for a liberalization of enforcement strategies can lead to decreasing
prevalence, this result is strongly influenced by the UK experience.
7. Conclusion
This paper set out to investigate the question of whether policies addressed at cannabis
possession and consumption can be shown to actually influence the use of cannabis among
the general public. While this question has already received widespread scholarly attention,
we identified several shortcomings within this literature that motivated the reassessment of
this question by different means. Specifically, we used the analytical leverage of regression
methods for panel data in order to control for the developments regarding cannabis prevalence
in countries that have not changed their policy regimes and to control for country-specific
differences causing different levels of prevalence. Furthermore, we presented a sophisticated
measurement of cannabis policy approaches by providing detained ordinal measures for three
different dimensions of cannabis policy: rules, sanctions, and enforcement.
Essentially the analysis gives further support to existing findings challenging the deterrent
effect of restrictive policy regimes. We do not find evidence for policy reforms of any kind to
lead to an increase or a quicker increase in the prevalence of cannabis consumption. Instead,
we find that a liberalization of enforcement is – independently from the rules and sanctions
that are to be enforced – associated with decreasing prevalence of cannabis consumption.
However, this result is strongly influenced by developments in the UK where the introduction
of a more permissive enforcement strategy – i.e. the replacement of cautions involving formal
prosecution and potential custodial sanctions with warnings that do not lead to criminal
records – coincided with a decrease in cannabis prevalence among the general public.
Whether the causal link between the two developments is the fact that the more permissive
enforcement guidelines were accompanied by a substantial rise in Cannabis seizures between
2004 and 2008 (Weissenborn und Nutt 2012) remains an open question that cannot be
answered by this paper. Yet, this paper can in fact show that which conclusions we draw
about the impacts of Cannabis policy reform depends crucially on how we treat the UK
experience. Should we include the UK in or exclude it from the analysis? This decisions
should be based on whether we understand what caused the decline in the UK and believe that
the reforms carried out in the UK will have similar effects elsewhere. In other words, this
decision depends on our judgment about exactly how British the other countries are. Yet, in
20
order to make that decision, more extensive in-depth research on the UK experience is
required in order to isolate the mechanisms underlying the statistical relationship between
more permissive enforcement and decreasing cannabis prevalence.
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Appendix
% of population (age 15-64)
5
10
15
Analyzing trend in cannabis prevalence 1990 – 2010 in Western European countries.
one year
one month
prediction one year
0
prediction one month
1990
1995
2000
year
2005
2010
Note: lines reflect predicted values predicted on the basis of models (1) and (2) presented in the
table below. Data on prevalence is obtained from the EMCDDA.
23