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The impact of anti-doping legislation in Europe - outlines for the development of model-based hypotheses

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Concrete attempts to prevent doping have always oscillated between the extremes of making athletes' actions an offence prosecutable under the jurisdiction of sports courts and moral appeals serving a purely pedagogical purpose. More recently, one has seen efforts Europe-wide to prevent doping by introducing institutionalized penalties; in Germany, too, for example within the scope of the anti-doping law. This has given rise to an intensive discussion on the rationale and expediency of implicating athletes in criminal jurisdiction. The present article aims firstly to model the supply and the demand side, taking into account actors who make counter-investments in obstructing criminal punishment, based on the recently tightened anti-doping law in Germany. Secondly, based on this model, the authors will attempt to estimate the effects for those countries in Europe with higher or lower penalties, while presupposing the same probability of detection for Europe in general. With the help of this comparison of higher and lower sanctions, it is possible to formulate hypotheses concerning the level of anticipated doping prevalence in these countries.
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Werner Pitsch, Monika Frenger, Eike Emrich
The impact of anti-doping legislation in Europe – outlines
for the development of model-based hypotheses37
1 Introduction
Concrete attempts to prevent doping have always oscillated between the ex-
tremes of making athletes’ actions an offence prosecutable under the jurisdiction
of sports courts – or meanwhile in the case of so-called wire-pullers and the
athletes themselves of ordinary courts – and moral appeals serving a purely
pedagogical purpose. If, as was not only pointed out by Digel (1994), but also
proved from a decision-theory perspective by Bird & Wagner (1997), the prob-
ability of doping results from the system logic of elite sport, then both pedagogi-
cal efforts to put a stop to doping and general crime prevention would logically
be generally unlikely to succeed. More recently, we have seen efforts Europe-
wide to prevent doping by introducing institutionalized penalties; in Germany,
too, for example within the scope of the anti-doping law. This has given rise to
an intensive discussion on the rationale and expediency of implicating athletes
in criminal jurisdiction. In response to protests primarily from the field of organ-
ized sports, the current German anti-doping law does not foresee such involve-
ment. This confronts us squarely with the striking discrepancy between the
widespread notion that penalties for athletes enshrined in law have a deterrent
function and the scepticism towards such a function personally expressed by the
German Olympic Sports Federation president (unpublished, 2006) when he
states, for example, that he does not want to see athletes criminalized.
2 Theoretical background: The normative and empirical
hypothesis of general prevention from the perspective
of methodological individualism
When Bette & Schimank (1995, 285, translated by the authors) state that “as a
result of ongoing commercialization athletes act as selfish utilitarians who, in
light of their brief sporting career, naturally have a vested interest in maximizing
their earnings and are under high pressure to perform in an environment condu-
cive to doping”, they are referring to a form of utilitarianism that was for a long
time generally disapproved of and therefore disregarded in the theoretical dis-
cussion (Höffe, 1975, 8). Growing disillusionment concerning the measurable
success of a concept aimed at prevention, resocialization and therapy, albeit one
that led to a sustained rise in the earnings potential of those active in this field or
of moral entrepreneurs, hand in hand with an economic approach to deviating
37 The authors would like to thank Christian Pierdzioch for his valuable comments.
71
behaviour (Becker, 1974), served to reinforce a utilitarian reasoning behind
penalties. This argument is pursued from two aspects:
a) in a normative sense, namely that the desired deterrent effect on potential
deviators is to be seen as an end to legitimize government prosecution and
b) that government prosecution does actually have a subsequent deterrent ef-
fect (Vanberg, 1982, 7).
In his analysis, Vanberg (1982, 8ff.) points out with reference to Rawls
(1975) the need to differentiate between two legitimization problems when it
comes to justifying punishment:
a) justification of institutionalized punishment and
b) justification of a concrete criminal act.
The first point is concerned with the question of why the state should prose-
cute and how the institution that metes out the punishment is legitimized, while
the second asks why a penalty should be imposed against a particular individual.
The first case relates to the legal certainty that arises from a deterrent effect, as
well as legitimization based not on divine will etc., but on internal consensus-
building within a group; the second case assumes that the individual is actually
guilty in the sense of having violated the law.
Rawls (1975, 98) in this context relates the two levels to two different official
functions, namely that of the legislative body (i.e. parliament), which must give
consideration to the future impact of its decisions, and that of the judge, who
gives a verdict on past actions in a criminal act. A purely arbitrary deterrent, as
is easily conceivable in despotism and also exists in the figure of the dictator in
the Inspection Game in economics, would conflict with the deterrent function. If
punishment could be meted out to everyone irrespective of how they have actu-
ally conducted themselves, there would be no incentive for anyone to refrain
from infringing the law. As Pitsch (2009) and Emrich & Pitsch (2009) have
shown, the questions this gives rise to are certainly relevant in the fight against
doping insofar as fair doping tests do not exist, and investments in the appear-
ance of honesty in sport production may be more rewarding than honesty itself
in the sense of complying with the rules or abstaining from doping.
The fact that an individual mentally accepts a norm does not mean we can as-
sume he or she will automatically act accordingly (Vanberg, 1982, 13). The
economic discussion concerning the collective good problem makes it clear that
the controversial issue is not that rules are sometimes violated, but is to be seen
within the broader context of adherence to a system of rules, observance of
which does not happen per se, but incurs costs.
So where do the advantages of a compliance with norms that aims at estab-
lishing social order lie? First ans foremost it alleviates uncertainty, because insti-
tutionalizing expectations rightly enables us to harbour reliable expectations
about how the social environment behaves, as well as about how people will act
in the future. However, the advantage of these expectations lies in the antici-
pated compliance of the other stakeholders, whereas self-compliance is defi-
nitely a disadvantage because, as Plato taught us, it limits behavioural alterna-
72
tives; in short, rule-breakers only have an advantage to the extent that they can
be relatively sure the other side does not break the rules. In other words, as long
as by complying with the rules others do not bind themselves to the law or sub-
mit to the rules, rule-breakers risk disadvantages by, in turn, binding themselves
to the law. So while people have a manifest interest in stability and guaranteed
compliance with a normative order, they have no direct individual motive to
submit to rules in their own behaviour, unless the stability of the order is guaran-
teed by institutions.
With the increasing size of the group, two factors come into play: first, in our
individual expectations the probability of not being caught and sanctioned in-
creases and second, the probability of our own infringements jeopardizing the
social order and triggering a backslide into anarchy decreases (cf. Vanberg,
1982, 13ff.). In this context, systematic changes in the action situation change
the weighting in the individual decision alternative, which by reason of cost-
benefit calculations makes it appear expedient to choose compliance over devia-
tion. This change in weighting consists in the organization of the state and the
concept of law, which via changed earnings expectations, for example because
of an institutionalized threat of penalties in the case of non-compliance, is in-
tended to free individuals from the above-mentioned large number dilemma,
which Buchanan (1977, 161) formulated as follows: “Each an every person may,
of course, consider that he would be ´better off´, in terms of his own evaluation,
in a different world where the moral law is widely accepted as an overriding
ethical rule. But privately and voluntarily there is simply no means through
which the single individual can choose to make this alternative state of the world
more nearly realizable.”
Independent of sub-group-specific interests that come into play in the formu-
lation of norms, we can therefore establish that the constancy of interindividual
conflicts of interests makes a system of rules necessary in order to guarantee
social order, and also that legal norms which show a general consensus need an
implementation and enforcement apparatus in order to be effective. Voluntary
normative self-commitments, generally subsumed under the term fair play,
while certainly not expendable, by no means replace an enforcement and pun-
ishment apparatus.
2.1 The theory of general prevention as an empirical theory
Compliance and non-compliance each occur taking account of subjectively an-
ticipated benefits and anticipated disadvantages (cf. Beccaria, 1966, 61; Ben-
tham, 2000 [1781], 166). As Vanberg (1982, 18ff.) points out, the more recent
economic theory of criminality postulated by the likes of Becker again ties in
with the earlier conceptions of Beccaria and Bentham and deals with the prob-
lem in terms of the relationship between price and demand. If the price of a
given conduct rises, for example because the risk of punishment brings higher
penalties, demand, or the rate of deviating behaviour, declines accordingly.
73
Threats of punishment in terms of institutionalized rules therefore increase costs
– which, however, presupposes economically rational behaviour (Becker, 1974,
9).
Consequently, numerous objections to the economic theory of criminality
have been raised (cf. Vanberg, 1982, 22ff.), which in the main drew on an all too
rationalistic concept of man. This was, however, significantly expanded in insti-
tutional economics, in which it is assumed that although different levels of in-
formation lead to asymmetrical information, individuals nevertheless act ration-
ally even if only restricted or asymmetrical information is available. Thus rule-
breakers may act on incomplete information; it is also quite possible that they
fail to assess the risk of discovery and conviction, that they wrongly judge the
long-term consequences of their actions, etc. But even if they calculate differ-
ently to conformers, this by no means implies that they do not calculate at all:
“Moreover, the likelihood that an offender will be discovered and convicted and
the nature and extent of punishment differ greatly from person to person and
activity to activity. Yet, in spite of such diversity, some common properties are
shared by practically all legislation […]” (Becker, 1974, 1f.; cf. 11f.).
Moreover, general prevention does not, of course, make rule-breaking disap-
pear; what changes is the frequency with which it occurs. In addition to this, it is
perfectly conceivable for formal punishments in the institution of the law to
overlap with other negative sanctions. State punishment is just one form in addi-
tion to physical, moral and religious punishment (Vanberg, 1982, 28 with refer-
ence to Bentham, 2000 [1781], 27), whereby the economic theory of state pun-
ishment is by no means incompatible with informal negative sanctions.
2.2 General prevention in doping
Assuming economics as a method of analyzing and predicting the behaviour of
the average person, we can make the following conjecture: when it comes to
compliance and non-compliance, people draw on certain resources. This brings
all infringements to light, be they tax evasion, white-collar crimes, traffic viola-
tions, etc. (Becker 1974, 3). The optimum activity structure is determined by the
relative advantageousness of alternative uses of resources. Changes in the ex-
pected benefit from observing the rules are reflected in changed activity pat-
terns, in other words: if the expected benefit to be derived from complying with
the rules declines, resources are diverted from compliance to non-compliance
(ibid., 9). These considerations are in principle based on the subjective expected
utility theory, according to which behavioural effects observed in collectives can
be reconstructed on the basis of the subjective utility of a future event or situa-
tion (benefit, N) and the probability of its occurrence (p) for each element in the
collective. Decisive variables in this context, according to Becker (1974, 11), are
the level and risk of punishment, whereby the risk of punishment acts as a
74
38
higher deterrent than the level of punishment : or in the words of Bentham
(2000 [1781], Chap. XIV, Of the Proportion between Punishments and Of-
fences, 7th rule): “To enable the value of the punishment to outweigh that of the
profit of the offense, it must be increased, in point of magnitude, in proportion
as it falls short in point of certainty”. Using the choice between compliance and
deviation as an example, the corresponding formalization according to Becker
would be:
)()1()(
γ
NpSNpEN
+=
(EN = expected benefit from earnings with the help of deviant behaviour, - (1-p)
= probability of escaping punishment, + benefit in the event of punishment –
N(S) weighted with the likelihood of punishment p).
Taking Becker’s line (1974), this would initially have to be seen as a serious
plea for more restrictive sanctioning, more investigative personnel and improved
methods of prosecution (Becker, 1974, 14ff.)39. Factors influencing the expected
benefit are: (first derivation).
0)()( <=
γ
NSN
p
EN
a)
0
)( <
=
SSN
p
S
EN
b)
Raising the level of punishment and/or the probability of conviction would
thus increase the price of violations and from a simple economic perspective
reduce the number of infringements. A higher level of punishment combined
with a higher likelihood of punishment could therefore also be seen by the dop-
ing market as a plea for much more restrictive sanctioning in the form of legisla-
tion that ideally penalizes both suppliers and consumers, more investigative
personnel and improved methods of prosecution.
2.3 Specific assumptions about the doping ban from the economic perspec-
tive
Compared to other forms of deviating criminal behaviour, doping represents
something of an anomaly. A bank robber, for example, loses any illegally ac-
38 “The widespread generalization that offenders are more deterred by the probability of
conviction than by the punishment when convicted turns out to imply in the expected-utility
approach that offenders are risk preferrers, at least in the relevant region of punishments”
(Becker, 1974, 11)
39 Here, in particular government funds are used in order to introduce repressions intended
to lower incidences of doping and thus “clean up” sport. This is tantamount to subsidizing,
inasmuch as the collective good clean sport is produced with the help of public funds, making
it possible to produce a signal effect with a positive impact on consumers in the sense of clean
sport. This, however, gives rise to the question of whether athletes themselves should not
provide – and finance – proof that they are “clean” (cf. seals of quality in other professions),
given that it is the athletes who use sport (especially clean sport) as a vehicle for promotion
and making money.
75
quired assets on discovery of the loot or through claims for compensation under
civil law, in other words he has to relinquish any illgotten gains or make mate-
rial compensation. Suppliers of doping substances or dopers, by contrast, do not
lose any past earnings generated through doping or through dealing in doping
substances. Voluntary consumption of doping substances rules out compensa-
tion claims against the supplier of those substances – unlike the forced consump-
tion of doping substances in totalitarian regimes, which entitles consumers to
lodge claims against the state. In addition, as a result of enhanced performance,
the undetected doper increases the benefit of the “sport” good for all stake-
holders (Emrich & Pitsch, 2009). With this in mind, when applied to the field of
doping in elite sport, Becker’s formalization requires specification on the one
hand with respect to the ramifications of punishment. On the other hand, it can
be assumed – and should be taken into consideration in the following formaliza-
tions – that the effects of the product of level and probability of punishment
would not represent a linear function (cf. fig. 2) if the punishment were to also
retroactively impact income earned with the help of doping in the form of a
contractual penalty, claims for compensation or the like.
So far, the analysis of decision-making behaviour has been conducted strictly
on the basis of methodological individualism. If, however, we wish to assess the
thus calculated effects within a collective, we must bear in mind that uncon-
nected individual actions can give rise to unexpected non-intended collective
effects. Therefore we must also ask: Is, by analogy with prohibition in the USA,
a state-imposed doping ban with tougher sanctions perhaps the non-intended
motor of the doping market? If for dealers doping, or the sale of doping sub-
stances, were to become an act prohibited by law, they could be expected to
react to such a ruling rationally. They would rationally weigh up the costs and
benefits of the behavioural alternatives of dealing in prohibited substances ver-
sus giving up dealing against each other, whereby the level of sanctions and the
probability of these being imposed here again essentially determine decision-
making behaviour.
When an illegal supplier market is created, we can also expect an increased
level of masking measures. For suppliers it is rational to offer specially designed
masking techniques along with potential doping substances in order to minimize
the likelihood of their customers getting caught and being exposed and subse-
quently punished as suppliers themselves. Government investments in crime
fighting (e.g. by intensifying the government repression system) also influence
the decision of course, as higher government investments also increase the prob-
ability of the risk of punishment. Since it is also in dopers’ interests to lower the
likelihood of detection, it can be assumed that an increase in the level and prob-
ability of sanctions on the supply side leads to rising doping prices and a lower
probability of detection for consumers – and hence also for suppliers.
An increased level of sanctions for dopers as a result of criminal prosecution
can likewise be expected to generate counter-investments, whereby the concrete
level of these counter-investments is in turn influenced by the level and the risk
76
of punishment as well as by the level of income that can be achieved through
doping. The latter is strongly determined by the product of current annual earn-
ings and expected remaining time during which an athletic career can be suc-
cessfully pursued. Those investments a doper makes in order to avoid detection
and punishment are thus a function of the level of punishment S (disadvantages),
the probability of occurrence and the anticipated earnings from doping during
the remaining career (advantages).
3 Problem specification
In terms of the theory of general prevention, it was assumed that higher penalties
– given an unchanged or increased likelihood of discovery – lead to a reduction
in doping abuse. In this context, the probability of detection has generally
proved to be the factor to be given more weight in the product of the two vari-
ables. Even rationally acting players with restricted information react with
counter-investments, with the help of which they influence or believe they can
influence the probability of being discovered.
In the following formalization, we as a generalization assume risk-neutral
suppliers in the market. The behaviour of risk preferers, who at least partly ig-
nore any threat posed by repression and sanctions, can be implicitly derived
from this. In the case of consumers, i.e. doping athletes, on the other hand, it is
necessary to distinguish between risk takers and those averse to taking risks.
The present article aims firstly to model the supply and the demand side, tak-
ing into account actors who make counter-investments in obstructing criminal
punishment, based on the recently tightened anti-doping law in Germany. Sec-
ondly, based on this model, we will attempt to estimate the effects for those
countries in Europe with higher or lower penalties, while presupposing the same
probability of detection for Europe in general. With the help of this comparison
of higher and lower sanctions, it is possible to formulate hypotheses concerning
the level of anticipated doping prevalence in these countries.
Legal provisions with respect to doping violations differ considerably from
one European country to another. In a formalization of amendments to the law,
Pitsch und Emrich (2009) already developed a model outlining the impacts of
changes in legislation. This was based on an economic evaluation of a planned
tightening of the law in Germany that could possibly influence the decisions of
suppliers and consumers of doping substances.
4 Formalization of the basic model
The formalization presented in the following is based on an economic efficiency
evaluation of the amendments to the legal situation in Germany in respect of the
tightening of sanctions (Pitsch & Emrich, 2009). The model is outlined in a
partly abridged and revised form.
77
4.1 Supply side
First of all it shall be assumed suppliers react rationally, in other words that they
make counter-investments (
I
) that lower the probability ( ) of being caught
and punished.
p
40 The level of the counter-investment is, in addition to the prob-
ability of punishment ( ), influenced by the level of punishment, government
investment in direct obstruction and imposition of criminal punishment (in the
following
p
R
= repression) and by the level of income from the sale or use of
doping substances .
Nv
In this, we assume a supplier who, if sanctioned, is not able to generate an in-
come, whose opportunity costs in the case of sanctioning are the result of the
product of the level of the sanction in years and his or her average income per
year and who thus suffers no additional income losses from the possible but not
compulsory – and to date only in absolutely exceptional cases (contractual pen-
alties in professional cycling) subsequently imposed – confiscation of realized
profits by the prosecuting authorities. In this respect, this argumentation targets
both the small-scale businessman in the illegal doping market and well-
organized illegal suppliers that generate a higher turnover. This allows small-
scale black market dealers to be caught as well as larger-scale doping labs (e.g.
“Balco”) or developers of designer steroids. It does not, on the other hand, detect
pharmaceutical companies that develop and manufacture products suitable for
doping for other purposes.
In the following, functions such as the subjectively anticipated benefit EN as
a result of the interaction of investments I in obstructing punishment, the level of
sanctions ( ), the level of repression (
S
R
) and the probability of detection (p) are
considered. In this, the effects of the independent variables on the anticipated
benefit are considered as follows:
In order to establish whether it is feasibly possible to reduce the
number of suppliers of doping substances or dopers, we analyze the
conditions under which their anticipated benefit becomes negative.
In order to see how exogenous parameters (e.g. the level of sanc-
tions) interacting with endogenous parameters (e.g. the level of
counter-investments) influence the anticipated benefit, it is neces-
sary to consider the derivation of the function to one variable re-
spectively. For example, the derivation of I to the variable S de-
scribes the increase of the function I at a point S. If this is always
40 Kistner (2010, 34) reported in the German daily Süddeutsche Zeitung that a court ruling
has upheld the right of doping expert Werner Franke to claim that racing cyclist Jan Ulrich
paid 35,000 euros in one year for the procurement of illegal substances. According to the
public prosecutor’s office, between the years of 2003 and 2006, Ulrich visited the physician
Fuentes 24 times in Madrid (sometimes for as little as 2 hours) and in the years 2004 and
2006 paid Fuentes a total of 80,000 euros. This on the one hand illustrates the costs of doping
and on the other hand, it also demonstrates the illegal and illegitimate investment activity by
small-scale businessman Ulrich in his performance potential.
78
positive with a growing parameter (strictly monotonically increas-
ing), this means the value of I then increases. Conversely, if the
derivation is consistently negative, the value of the function de-
creases with a growing parameter. Zero means the function is
constant.
Assumption 1: Investments (
I
; which also include information costs, costs of
trust and search costs), that a doping supplier makes in order to avoid being
detected and punished are thus a function of the impending losses (level of pun-
ishment and level of investments in prosecution ).
S
R
(1)
()
RSII ,=
Whereby:
0
),( >
SRSI 0
),( >
R
RSI
and
(2)
shall apply, i.e. (based on the above explanation): the higher the level of the
sanction and the higher the investments of the collective actors (prosecuting
authorities) in the detection of suppliers, the higher the level of the counter-
investments. Counter-investments in this context may be the development and
sale of unknown doping substances or those still in the process of development
(such as S 107 that was presumably used in China), or the sale of doping sub-
stances together with masking agents. Other conceivable counter-investments
could include bribe monies and the employment of paid “stooges” as vendors.41
The function of the counter-investments on the supply side is perforce also to
lower the risk of the athlete’s detection, since as an initial suspicion a detected
case of doping would entail the risk of the supplier’s own illegal behaviour be-
ing exposed. Any athlete already convicted as a dopers represents as a customer
a higher risk for the supplier, which is likely to be reflected in higher prices or
possibly in a refusal to supply the product. Supplier and consumer have only
partially conflicting interests, inasmuch as suppliers are out to maximize their
material benefit; at the same time, however, they can also be seen as having
identical interests, since both parties have a vested interest in non-detection, in
other words a specific form of antagonistic symbiosis (Emrich & Pitsch, 2009).
Assumption 2: The probability of detection is a function of the repressions
and the counter-investments defined in (1):
(3) with
()
),(, RSIRpp =0)),(,(1 RSIRp
Whereby:
0
)),(,( <
IRSIRp
(4)
41 As recent assumptions in the Armstrong case suggest, it cannot be ruled out that substantial donations to
the UCI have at least created a certain goodwill (Kistner writing in the Süddeutsche Zeitung of Saturday, 7
August). Even the head of the special doping commission in Austria, Andreas Holzer, noted in the Wiener
Kurier newspaper that the international doping trade is well organized, the risk in the doping trade is, by contrast,
lower than in the doping market, while profits are higher (Kistner, 2010, p. 25).
79
shall apply, i.e. investments on the part of the suppliers in non-detection of
the sale and of the doped athletes definitely lead to a lower probability of being
detected themselves. For this reason, the effect of repression on the probability
of detection can only be obtained via the derivation of (3):
RRSI
IRSIRp
R
p
=
),()),(,(
(5)
For the investments, it was assumed that with a growing R they steadily rise
(2), so that the sign in front of the second factor is always positive. The sign in
front of the first factor, however, depends on the ratio of the effects of the re-
strictions and the counter-investments on the probability of detection
p
. If the
effect of improved detection methods exceeds that of investments in the avoid-
ance of punishment, the overall probability of detection increases despite
counter-investments, and all the suppliers can do is minimize the risk. If on the
other hand the effect of the counter-investments exceeds the effect of improved
detection methods, an increase in
R
leads to a lowering of the probability of
detection. Government control via increased repression is therefore only possi-
ble if we assume that in their effect on the probability of detection the improved
detection methods (e.g. efforts by the Federal Criminal Police Office) cannot be
fully compensated by counter-investments. The case of repression measures that
can be overcompensated by counter-investments ( 0<
R
p) turns out to be trivial
in this context, because increasing government investments in the detection of
doping offences would always result in rising incomes for suppliers accompa-
nied by a lower probability of detection for dopers.
0>
R
p
In the case of potentially effective control ( ), the first derivation of (3)
to S produces:
0
),()),(,( <
=
SRSI
IRSIRp
S
p
(6)
Irrespective of the extent of the perceived level of repressions, the probability
of detection (4)
p decreases with increasing investment I. If we further assume
that the probability of detection is greater than 0, and that at the same time with
an increasing level of sanctions individual investments in avoiding detection – in
the form of buying expensive, innovative and as yet undetectable products or
known products with mimetics – increase, then the probability of detection for
athletes and suppliers decreases the higher sanctions are (6).
For consideration of the expected benefit, the following assumptions must be
made:
A benefit definitely accrues from the sale of doping substances – we are as-
suming an actual increase in sales prices and not just a certain rise in reservation
prices – and is positive:
80
(7)
0>Nv
The benefit (opportunity costs) from the sanction is negative and decreases
the higher the sanction is:
0
)( <
SSN
(8) and
0)( <SN
In the case of the counter-investments, it follows for the expected benefit of
the supplier, who always compensates the negative benefit through counter-
investments by means of an actual price mark-up (not just an increase in the
reservation price), that:42
(9) NvSNRSIRpRSEN
+
=
)()),(,(),(
If we proceed from the plausible assumption that the expected benefit for
suppliers was so far positive (why else would they – give or take the occasional
blackmail case – still be on the market), then an increase in the probability of
detection is definitely effective if the future expected benefit becomes negative
as a result. In this case, there would certainly be a drastic reduction in the num-
ber of suppliers. The effectiveness of the increased repression thus primarily
depends on the expected probability of detection.
The solution of the inequation produces:
0
<
EN
)(
)),(,( SN
Nv
RSIRp >
(10)
A closer look at this inequation shows that a simultaneous increase in sanc-
tions and in the probability of detection can only be an unreliable means of
squeezing the doping market dry and thus of eliminating doping, since for both
sides of the inequation the respective term becomes smaller with increasing
sanction levels (cf. (6))
The first derivation to R produces:
0)(
),()),(,(),( <
=
SN
RRSI
IRSIRp
RRSEN
(11)
since given the assumption of reliably effective detection methods (cf. reflec-
tions relating to (5)) and the negative benefit of sanctions, increasing repressions
thus certainly lower the expected benefit for suppliers.
The first derivation of (9) to S produces:
42 Whether the attainable price goes up is contingent on market conditions. What will cer-
tainly increase are the reservation prices (minimum sales price). Since empirical findings
currently do not indicate any significant drop in demand – the use of doping substances in
amateur and leisure-time sports even appears to increase impartial demand – we not only
expect reservation prices to increase, but in fact sales prices too.
81
SSN
RSIRpSN
SRSI
I
RSIRp
SRSEN
+
=
)(
)),(,()(
),()),(,(),(
(12)
A closer look at this derivation does not allow a definitive conclusion to be
drawn concerning how the expected benefit varies depending on the level of
sanctions, without additional assumptions being made or conditions met.
If we proceed on the assumption that sanctions are effective, the expected
benefits should decrease with increasing sanction levels, i.e. 0
),( !
<
SRSEN ; it
should then follow that:
)(
)( SN
S
SNS
p
p
>43
(13)
Since the probability of detection p must (by definition) always lie between 0
and 1 (i.e. between “never occurs” and “always occurs”), at least one of the
following conditions must be met: either the change in the benefit of sanctions
as a result of the sanction (denominator of the fraction) must be significantly
greater than the variability of the probability of detection as a result of the sanc-
tion (numerator of the fraction). This condition is symbolically represented in
figure 1. The expected benefit of the supplier decreases as a result of this condi-
tion only in those areas where the derivation of p to S (solid line) runs below the
derivation of N to S (dotted line). This is only the case for low values of S, in
other words low sanctions, since with higher values the effect of the counter-
investments on the probability of detection overcompensates the decreasing
benefit in the event of discovery. The second condition under which the inequa-
tion is satisfied is that the costs incurred through sanctions must be significantly
lower than 1. The equation is also satisfied if both occur simultaneously. Alto-
gether it becomes clear that the form of the functions of
p
and depending on
the level of sanctions is decisive for satisfying the condition and there are only a
few constellations for satisfying the inequation.
N
By way of illustration, we compare two types of supplier: Type A supplier
earns only a marginal income from the sale of doping substances, is thus a typi-
cal chance vendor. Type B supplier earns a high income from the sale of either
very expensive or very innovative and/or high quantities of doping substances.
If, based on our formalization, both behave rationally, the number of existing
suppliers will certainly decrease, because at least for type A suppliers the ex-
43 This inequation can also be resolved with reference to elasticities in economics as follows:
SNSIIp
N
S
S
N
I
S
S
I
p
I
I
p
NS
N
S
I
pI
p
,,,
11
εεε
>
>
>
82
pected costs arising from the sanctions and the impossibility of factoring the
costs of counter-investments into the price of their small quantities of doping
substances sold (i.e. passing these on to consumers) would be too high, forcing
them to withdraw from the market. Type B suppliers, on the other hand, would
remain in the market, since their possibility to make higher counter-investments
still provides them with a considerable benefit.
Fig. 1: Graphic representation of the necessary condition for p (see (13))
As an interim conclusion we can therefore note that tightening the penalties for
suppliers, i.e. raising the price for violating the norms, leads to concentration
effects in the number of suppliers.
4.2 Demand side
Athletes consume doping substances (on the extent cf. Pitsch, Klein & Em-
rich, 2005, 2007; Pitsch, Maats & Emrich, 2009). This consumption is modelled
in the following as demand, and the athlete thus considered as a consuming
household. Other aspects, such as demand by the public for peak athletic per-
formances or demand by the media for actual or asserted past doping violations,
are not taken into consideration.
By analogy with the supply side, we attempt to model the athlete as a rational
actor who makes active counter-investments, believing in their effectiveness and
thus having restricted information about the actual impact of counter-measures.
The above assumptions (1) and (2), which describe the dependency of the level
of investment on the level of sanctions and repression, are adopted for the de-
mand side in the same way as for the supply side, however with the difference
that for the athletes the probability of detection is determined above all by the
doping tests carried out by the associations. This means that a possible increase
in repression has only a minimal influence on the probability of detection and
sanctioning. is a function of R and S and the probability of detection is only
I
83
indirectly dependent on the level of repression via the effect of on
R
I
. It there-
fore follows that:
(14) with
(
),( RSIpp =
)
0)(1 >> Ip
and
0
)( <
IIp
(15)
i.e. the individual investments in avoiding prosecution definitely lead subjec-
tively to a lower probability of punishment. The first derivation to and
S
R
produces:
0
),()),(( <
=
SRSI
IRSIp
S
p
(16)
and
0
),()),(( <
=
R
RSI
I
RSIp
R
p
(17)
With increasing sanction levels, measured in terms of the duration in years of
the (future effective) doping-related bans, and increasing repressions on suppli-
ers, which in turn push up prices (cf. (20) below), investments in efforts to es-
cape punishment on the part of athletes also increase (cf. (2)). Depending on the
investments, the probability of detection for athletes decreases (15) and thus
tougher sanctions for consumers, in the same way as tighter repression measures
for suppliers, lead to lower probabilities of detection on the demand side.
Apart from this effect on the probability of detection, the investment in pun-
ishment avoidance also has a direct benefit-lowering effect since it incurs costs
and therefore reduces income (investments = costs). Since this benefit equals the
negative benefit of the investment, in the following we simplify matters by con-
sidering the investment directly as a negative benefit in the expected benefit.
The benefit for athletes from the sanction can be formulated in relation to the
benefit from the doped practice of sport. If refers to the number of years of a
doping-related ban (currently a maximum of 4) and refers to the (uncertain)
average annual income of a doped athlete (due to injuries, fluctuations in per-
formance, etc.) it follows for that
SNd
)(SN
(18)
NdSSN =)(
Where counter-investments are made, it therefore follows for the expected
benefit of an athlete that:
(19) ),()),((1()()),((),( RSINdSRSIpNdSRSIpRSEN
+
=
When considering the expected benefit, additional assumptions are made with
respect to the functions
I
and . Since the counter-investments made by con-
sumers consist on the one hand in repression-induced price increases on the
supply side and on the other hand in self-determinable components, the function
p
84
can be replaced by the sum of
),( RSI cSI
+
)( . The constant c is determined by
the repression on the suppliers and impacts on the maximum investments of the
consumers in the form of higher prices (= costs).
Assumption 1: As S increases, I increases in a straight line up to the maxi-
mum
(
cNd
x
1
)
, whereby describes the earnings from sport reduced by
the constant and
cNd
x
1
c defines the fraction of this available income that the doper
is willing to additionally invest in escaping detection over and above the costs
already incurred by doping.
We assume that a consumer will not be prepared to make counter-investments
at a level that exceeds his or her expected benefit, and consequently that the
maximum fraction (
x
1) of his or her income is limited by x
<
1.
<
=
otherwisecNd
x
cNd
x
ISm
I
:)(
1
)(
1
:
(20)
If we start by taking the current sanctioning practice (four-year maximum ban
()) and the current counter-investments of an athlete ( ) as a baseline, then it
follows for I with a given
0
S0
I
that:
R
S
S
I
I
S
I
m==
0
0
0
0
(21)
Based on the definition of I, a distinction can be made between two types.
First, depending on the level of sanctions, (individually) increasing counter-
investments are made until the “personal pain threshold” )(
1cNd
x
with respect
to Nd is reached. From this point on, irrespective of whether the level of sanc-
tions increases, investments are only made up to the threshold amount and it is
accepted that beyond this level, the probability of detection cannot be further
influenced by investments. An actor who invests a high amount within a short
time (m very high), will reach his or her limit (ceteris paribus) faster than an
actor who only reacts to a lesser extent to increases in sanctions . We
look initially at the first case, in which increasing counter-investments are made,
and then at those actors whose rate of increase with respect to counter-
investments is low, since this is the more relevant of the two cases. Given this,
as a result of incorporation into
)0( m
(19), it therefore follows for the expected benefit
that:
85
(22) )()(2)( cSmNdScSmpSNdSEN
+
+
+
=
This first prompts us to ask under what conditions a doped athlete who makes
counter-investments anticipates a negative expected benefit. Based on this, the
“doping” strategy would not be an alternative that a rationally acting player
would choose. We therefore consider the inequation :
0
<
EN
(23) 0)()(2
<
+
++
cSmNdScSmpSNd
A distinction can be made here between quick-response actors (those who
make high investments even in the case of low increases in S) and wait-and-see
actors (with low m). The second group is the more interesting to observe in this
context, since in the first group the maximum level of investments is quickly
reached and thus the second case of (19) applies. Considering the borderline
case produces the following conditions for a negative expected benefit:
0m
>
>
<
<
5.0
))(21(
5.0
))(21(
pfor
cpNd c
S
pfor
cpNd c
S
(24)
If , the expected benefit, regardless of the benefit derived
from doping and the costs incurred through counter-investments on
the part of suppliers, is, whatever the level of sanctions ( ), al-
ways negative. Hence it ought to be possible for the prosecuting au-
thority to increase the probability of detection to over 50% or gener-
ate belief in a correspondingly high probability of detection in order
to persuade consumers to abandon their “doping” strategy.
5.0>p
0>S
If , the expected benefit can only become negative if the costs
incurred by the supplier are very low in relation to the benefit de-
rived from doping. In this case, the level of sanctions would have to
be very low in order to generate a negative expected benefit.
5.0<p
Assumption 2: As
I
increases, decreases. The form of the function can
be approximated to a hyperbolical function in the 1st quadrant and thus takes
into account that, relatively, increased investments per employed resource pro-
duce decreasing effects. A scaling factor is needed to meet the conditions that
a probability between 0 and 1 is given. Conversely, given the magnitudes of
p p
k
I
, a
comparatively low investment (for example € 10) would lead to an enormous
decrease in p (in the example would then be 0.1).
p
kcSmwith
cSm k
cSmI k
cSmp >+
+
=
+
=+)(
)(
(25)
86
2
)( cSm
mk
S
p
+
=
(26)
For the further analysis, it would appear relevant in this context to examine
the conditions under which the level of sanctions can be drawn on to control
(generally: lower) the expected benefit of the consumer. After incorporation of
(25) into (22) and derivation to S we obtain:
m
cSm ck
NdmNd
cSm mk
SNdcSmpNd
S
EN
+
=
+
++=
)
)(
2
1(
)(
2)(2 22
(27)
In order to bring about a decline in the expected benefit as a result of in-
creased sanctions, 0<
S
EN shall apply. It therefore follows for the lowering of
EN that:
)2,(
)24(2:0
)(
2
1
0)
)(
2
1(
2
2
kkc
applieskcfromandkcmfor
cSm ck
Nd
m
m
cSm ck
Nd
><
+
+<
<
+
(28)
However, against the background of (25), the condition in (28) means that
)1,
2
1
(
p must apply. The results of studies conducted by Pitsch et al. (2005,
2007, 2009) reveal, however, that significantly lower probabilities of detection
can be expected, so that on the basis of empirical findings it can be assumed that
in the case of actors who take a wait-and-see attitude to changes in sanctions a
decrease in the expected benefit is all but impossible. It also becomes apparent
in this connection that in the sense of adverse selection those who have little
regard for social standing and therefore do not overinvest at the threat of doping
controls are the ones who remain in the market.
In the second case differentiated in (20), athletes invest all means they are
prepared to invest in avoiding detection of their doping activities. This is the
case, for example, with those consumers who react very defensively to the threat
(m is very high) and for whom the maximum counter-investment limit is
reached even where sanctions are low. However, by contrast with a negative
expected benefit, these actors stay in the market, because despite non-increasing
counter-investments they have a positive expected benefit. In this case it follows
for the expected benefit by incorporating the second solution of into (19) that:
I
ccNd
x
NdSccNd
x
pSNdSEN ++= )(
1
))(
1
(2)(
(29)
87
As in the first case, we consider first of all the conditions under which the ex-
pected benefit becomes negative (and thus a decision to engage in doping would
be meaningless). We therefore consider :
0
<
EN
>
+
+
>
<
+
+
<
<++
5.0
))(
1
(21(
)(
1
5.0
))(
1
(21(
)(
1
0)(
1
))(
1
(2
pfor
ccNd
x
pNd
ccNd
x
S
pfor
ccNd
x
pNd
ccNd
x
S
ccNd
x
NdSccNd
x
pSNd
(30)
Based on the observations made in the first case, it is sufficient for this condi-
tion to consider the first inequation ( 5.0
<
p). The expected benefit of an actor
would in this case ( ) become negative precisely in cases where is very
small. Let us assume the probability of detection is 10%. If an actor invests 20%
of his or her benefit from doping (own investment and the investment that arises
through the supplier), then
S
5.0<p
4
1
<S would have to be true in order for the expected
benefit of this actor to be negative. Thus he or she would have made bad in-
vestments precisely in those cases where the first condition in (30) is met. In all
other cases, in other words where is higher, this actor invests his or her entire
benefit, even if the threat is minimal. These comparatively high investments are
made very quickly and are in turn compensated by the benefit in the event of
non-detection. This describes homo sociologicus, who in order to prevent the
loss of social standing will keep his or her investments at a consistently high
level irrespective of the level of the threat. We thus have the interesting case that
homo sociologicus, as the type who has to a high degree internalized values and
norms and tends to demonstrate norm-compliant behaviour, is interestingly also
to be found among dopers, although even here he will protect himself against
discovery by means of high and quick investments with the highest possible
feeling of subjective security even if the threats of detection are low, because he
wishes to avoid the costs of detection at almost any price. It is conceivable that
the logic of the sports system, in which everyone would be better off by not
doping, in which, however, a doping rival forces an athlete to engage in doping
if they are to have any hope of realizing their competitive and, consequently,
earnings opportunities, coerces athletes to dope if they do not want to lose their
position in the sports system. In turning to doping, these security-seeking ath-
letes are probably in many cases the “victims” of these structural constraints.
S
We again turn our attention to the conditions under which the level of sanc-
tions can be drawn on to control (generally: lower) the expected benefit of the
consumer, and consider in this context the derivation of to :
EN S
88
)))(
1
(1())(
1
(2 ccNd
x
pNdNdccNd
x
pNd
S
EN +=++=
(31)
In order to bring about a lowering of the expected benefit through sanctions,
0<
S
EN must also apply here. For the second case from (19), this therefore pro-
duces the condition:
2
1
))(
1
(0)))(
1
(1( >+<+ccNd
x
pccNd
x
pNd
(32)
In the event that an actor invests everything he or she is prepared to invest,
the only possibility to lower the expected benefit of this actor via changes in the
level of sanctions is if the probability of detection is greater than 50%. How-
ever, the observations relating to (27) have already shown that it is currently not
possible to achieve such a value for the probability of detection. Control via
sanctions thus appears to be unrealistic.
p
5 Interim conclusion
A government-imposed doping ban that poses a threat to suppliers of doping
substances automatically serves to privilege illegal suppliers, since the supplier
power of those highly profitable illegal suppliers who remain in the market in-
creases. The tougher the doping ban, the higher the sanctions and the greater the
risk of punishment, the stronger the anticipated concentration effect in the mar-
ket for highly-profitable suppliers could be expected to be, whereby we must
anticipate a supranational, at the very least Europe-wide, concentration process
in the market. As a non-intended effect, tighter penalties and higher probabilities
of being punished would increase the earnings of those doping suppliers who
remain undeterred and apply a risk bonus, provided that simultaneously imposed
measures do not reduce the number of consumers in the same way.
The probability of punishment is the result of the efforts of the state and sup-
pliers of doping substances who attempt to thwart successful detection efforts.
The more illegal doping suppliers are deterred by tighter penalties, the more the
police and the special anti-doping prosecutor’s office become involuntary aiders
and abetters to the doping suppliers by encouraging concentration effects and
higher prices, thus generally contributing to higher profits.
This gives rise to the second non-intended effect, namely that the expected
benefit of dopers increases, with the extent to which the threat of punishment or
an increase in the level of punishment prompts punishment-avoiding invest-
ments on the part of suppliers. The higher exogenously-determined penalties are
and the greater the probability of them being imposed, the more likely suppliers
will be to do everything they can to avoid punishment, thus also reducing the
risk of punishment for buyers. This relates not only to distribution channels (risk
of discovery) and to efforts to conceal the substances being used by the doper
89
(development and utilization of masking agents), but also to the bribing of labo-
ratory staff, donations for laboratories, etc., although as veiled bribery the latter
would even be tax-deductible for high-income professional athletes. The result-
ing higher prices consequently rule out lower-income buyers as consumers. This
could trigger a similar concentration effect on the demand side, which we do not
model here.
Added to this is the justified assumption that rational dopers initiate activities
of their own in an attempt to lower the probability of being punished. For the
demand side it has been shown that neither a negative expected benefit, corre-
sponding to a solution to the “doping” problem, nor a lowering of the expected
benefit of athletes through higher sanctions, is plausible.
6 Different European premises
The German anti-doping law is a so-called omnibus act that determines which
provisions from various laws should be amended. Its most important corner-
stones are punishability of possession, tighter penalties, which have been in-
cluded in the German Drug Law, as well as a mandatory labelling requirement
for doping substances (cf. details in Pitsch & Emrich, 2009). Punishability of
possession stipulates that possession of “non-small amounts” of prohibited sub-
stances is punishable. This foresees imprisonment and fines for organized and
commercial trafficking. Doped athletes are still only subject to the jurisdiction of
the respective sports association, provided they do not exceed the limits defined
as “non-small amounts”.44
As mentioned initially, legislation governing doping offences varies within
Europe from country to country. Differences are to be found relating to conse-
quences under criminal law with respect to which offences are prosecutable and
also with respect to the legal consequences, manifested in the level of punish-
44 The position put forward for discussion by Bavarian Minister of Justice, Dr. Beate Merk,
in the journal Sport und Recht (2010, pp. 104f.; cf. König, 2010, pp. 106f. and Kudlich, 2010,
pp. 108f.; cf. also Momsen, 2009) in respect of the pros and cons from the legal point of view
does not really change anything from the economy of law perspective. The qualificatory
formulations in § 5 Sporting Fraud, Sections 1 and 2, according to which the use of doping
substances as well as the use of methods to enhance oxygen transport are not punishable “if
the doping substance, the metabolite or the marker stems from the intended administration of
a pharmaceutical prescribed to treat a specific medical condition” (ibid., p. 105) or (in Section
2), “if in accordance with medical knowledge application of the method was necessary to treat
a specific case of illness” (ibid., p. 105) mean that, despite a higher level of sanctions, the
probability of sanctions is fundamentally not influenced. In this respect, tightening the level
of penalties for consumers is equally ineffective because of the potentially vast impediments
to the likelihood of penalties being imposed created by the above provisions. Moreover, reali-
zation is likely to raise interesting problems of balancing legal interests, if, for example, in-
voking human rights and the right of inviolability of the individual, athletes take legal action
against judicially imposed penalties on the grounds that they are entitled to effective treat-
ment, and physicians have ultimately monopolized therapeutic privilege as well as the right to
err (cf. Kudlich, 2010, p. 109).
90
ment. We consider the following nine European countries: Belgium, Denmark,
Germany, France, Italy, Austria, Sweden, Switzerland and Spain. Table 1 illus-
trates legal consequences under criminal law, subdivided according to offence
and the consequences imposed by prosecuting authorities.
In addition to these offences, some countries cite the doping regulations of the
sports associations or name offences that largely correspond to WADC stipula-
tions (e.g. in Austria, France, Switzerland or Spain). In France, in addition to
criminal prosecution for propagating and trafficking doping substances, athletes
face the possibility of a 4-year or lifelong ban. Therefore in France possession is
an offence that carries unspecified consequences. Spain, too, names other of-
fences. Illegal conduct of coaches, referees, sporting officials or club physicians
is a punishable act in the same way as selling or distributing prohibited sub-
stances at venues dedicated to the practice of sport.
In some of the countries listed, the organization of controls and subsequent
sanctioning proceedings are also partly in the hands of different bodies. In Italy,
for example, doping controls are carried out by a “commission for the supervi-
sion and control of doping and for health safeguards attached to the Ministry of
Health”, while sanctioning procedures fall under the responsibility of state juris-
diction. In countries like Spain, controls and sanctioning are in the first instance
carried out by the sports associations (state institutions only become implicated
after a certain period) and are only dealt with by state authorities at the appeal
stage.
It should also not be forgotten that the powers of the authority for prosecuting
a (doping) offence present an open question. In Germany, provisions under
German law apply provided the offence was committed within Germany (§3
StGB – German Criminal Code). Pursuant to §5 StGB, German criminal law
may still apply in the case of some offences perpetrated outside Germany, al-
though these may also fall under the law of the country where the offence was
committed. From the consumer/athlete perspective, it must be borne in mind that
self-doping is a punishable act only in Italy, and therefore athletes are for the
most part ruled out as perpetrators. Other national legislations concentrate first
and foremost on possession, trafficking, etc.
91
Tab. 2: Legal consequences under criminal law (offences and their legal con-
sequences) differentiated according to the various European countries45
Austria
1 July 2007: Anti-Doping-Bundesgesetz 2007,
8 August 2008: Änderung des Anti-Doping-Bundesgesetzes 2007, Arzneimittel- und Rezept-
pflichtgesetz
Offence: § 22a: Putting into circulation, use by third parties, possession (with corresponding
intention); also applies to gene doping and methods to increase oxygen transfer, § 2a Pre-
scription Drug Act: Prohibition to prescribe illegal substances
Legal consequences: Up to six months’ imprisonment or fine
Belgium
27 March 2001: Décret relatif à la promotion de la santé dans la pratique du sport, à
l’interdiction du dopage et à sa prévention en Communauté française (Amended: 26 July
2007 and 12 August 2009)
Offence: Art. 9 II: Punishability of all participatory actions
Legal consequences: Six months to five years imprisonment, fine (Art. 13)
Denmark
1 July 1999: Act no. 232 of 21 April 1999, Act on Prohibition of Certain Doping Substances
1 January 2005: Act no. 1438 of 22 December 2004, Act on Promotion of Doping-free Sport
1 January 2007: Executive Order no. 1681 of 12 December 2006, Executive Order on Pro-
motion of Doping-free Sport
Offence: Production, import and export, dispensing, sale, possession (Art. 3.1)
Legal consequences: Up to two years’ imprisonment, fine (Art. 4.1)
Germany
21 September 2007: Entwurf eines Gesetzes zur Verbesserung der Bekämpfung des Dopings
im Sport, Bundesrat document BR-Drs. 223/07
Offence: § 6a in conjunction with § 95 subsection 3 of the German Drug Law (AMG):
commercial or organized activity; Possession of non-small amounts
Legal consequences: Up to 10 years’ imprisonment
France
Code du Sport (Partie Législative, extraits; Livre II: Acteurs du Sport, Titre III – Santé des
Sportifs et Lutte contre le Dopage) – Version dated 4 July 2008; Loi no 2008-650 du 3 juillet
2008 relative à la lutte contre le trafic de produits dopants
Offence: Trafficking, administering, use by third parties, production, import and export (Art.
2)
Legal consequences: Up to seven years’ imprisonment, fine of up to EUR 150,000 (Art. 7);
Occupational ban for physicians
45 The authors thank Ms Katja Senkel for providing the information listed in the table.
92
Italy
2 January 2001: Legge n. 376 del 14 dicembre 2000, Disciplina della tutela sanitaria delle
attività sportive e della lotta contro il doping
Offence:
Art. 9 para 1 and 2:Ingestion/use; provision, administering;
Art. 9 para 7: Illegal trafficking;
Drug-legislation regulations: Art. 7: Regulations governing production, import, sale of drugs
containing doping substances; warning on packs and package inserts
Legal consequences:
Art. 9 para 1 and 2: 3 months’ – 3 years’ imprisonment, 5 to 100 million Lire fine,
Art. 9 para 7: 2-6 years’ imprisonment, 10-150 million Lire fine
Sweden
19 December 1991: Act prohibiting certain doping substances (1991:1969)
Offence: Import, dispensing, production, mediation, sale, possession and consumption (Sec-
tion 2)
Legal consequences: Up to two years’ imprisonment (Section 3)
Switzerland
1 January 2002: Ergänzung des Bundesgesetzes über die Förderung von Turnen und Sport
(FTSG), Abschnitt: Vb (Maßnahmen gegen Doping)
Offence: Production, introduction, mediation, distribution, prescription, dispensing or use by
third parties, (Art. 11d, f FTSG), where applicable § 19a BetMG (Narcotics Act)
Legal consequences: Imprisonment or fine
Spain
22 February 2007: Ley Orgánica 7/2006, de 21 de noviembre, de protección de la salud y de
lucha contra el dopaje en el deporte
Offence: Incorporation of Art. 361 into Spanish Criminal Code (Offences against public
health): prescription, offering and provision of illegal drugs to athletes taking part in offi-
cially organized competitions in Spain (not: possession or consumption by athletes)
Legal consequences: 6 months’ to 2 years’ imprisonment
Table 2 illustrates examples of offences from the field of sport and the respec-
tive levels of penalties, albeit limited to penalties imposed by sports associa-
tions. Nevertheless, it clearly shows that related to the severity of the offence the
level of penalties on the one hand differs considerably, and on the other is usu-
ally significantly below the maximum penalties defined by WADA.46
46 Cáceres and Catuogno (2010, p. 27) cite the example of swimmer Rafael Munoz to show
the scope of fluctuation of the sports associations in dealing with missed doping tests. Despite
missing three doping tests in succession, the swimmer was not banned because a psychologi-
cal assessment attested he was suffering from a “severe crisis”.
93
Tab. 3: Athletes prosecuted for doping with the respective ban for the years
2008 and 2009 (source: http://www.sportgericht.de)
Na-
tion Sport Court Offence Penalty Comment
Name
Cases of doping in 2009
Arbi,
Roberto ITA Athletics IAAF n.s. lifelong Repeat of-
fender
Cabreira,
João
Port. Cycling
Federation
POR Cycling Protease 24 mths n.s.
Doping sample
refused
Draguhn,
Sebastian 12 mths n.s.
GER Hockey NADA
Malt. Football
Association
Grech,
Ryan n.s. 12 mths n.s.
MAL Football
Violation of
anti-doping
regulations
Mannini,
Daniele ITA Football CAS Delayed test 12 mths
Martinaus,
Gilbert
Malt. Football
Association
MAL Football n.s. 12 mths n.s.
Mattocks,
Claude
Malt. Football
Association
MAL Football n.s. 12 mths n.s.
Cases of doping in 2008
8 mths/
SFR 3,500
Horse treated
with prohibited
ointment (Cap-
saicin)
CAS doubles
ban*
Ahlmann,
Christian GER Riding FEI (*16 mths/
SFR
7,000)
Alifirenko,
Sergej RUS Shooting ISSF Dexamethasone 24 mths n.s.
Alves,
Bernardo BRA Riding FEI Capsaicin 3 mths 14-week ban
Bastianelli,
Marta
Ital. Cycling
Federation
ITA Cycling Fenfluramine 24 mths n.s.
Bayer, Nico GER Athletics DLV Amphetamine 24 mths Suspended
Beltran,
Manuel ESP Cycling AFLD EPO 24 mths
Suspended,
imprisonment
and ban pend-
ing
Blonska,
Ludmilla UKR Athletics Ukrainian Athlet-
ics Federation Steroid lifelong
Repeat of-
fender
Benzoylecgon-
ine 24 mths Suspended
Bond, Chris USA Basketball DBB
Ban reduced
from 24 to 12
months on the
grounds of
illness
Chepkemei,
Susan KEN Athletics IAAF Salbutamol 12 mths
Downhill
skiing
Deflorian,
Mirko CONI Cocaine 18 mths n.s.
ITA
94
Na-
tion Sport Court Offence Penalty Comment
Name
Weight
lifting
Indian Weight
Lifters’ Federation
Refusal of B
sample
Devi, Kavita IND Anabolic steroid 24 mths
Dunkley,
Julien JAM Athletics IAAF Boldenone 24 mths n.s.
Ekpukhon,
Christy NIG Athletics IAAF Metenolone 24 mths n.s.
Fofonov,
Dimitri KAZ Cycling FFC Heptaminol 3 mths n.s.
Marihuana
cigarette,
admission
Fränkel,
Purrel NED Football KNVB Cannabis 1 mth
NADA belat-
edly informed
Anti-allergenic
(asthma drug)
Funck,
Annette 2 mths
GER Athletics DLV
Gaag,
Dimitrij KAZ Triathlon ITU EPO 24 mths n.s.
Galliker,
Martin CH Bobsledding Swiss Olympic Testosterone 24 mths Withdrawal
Ghezielle,
Bouchra FRA Athletics French Athletics
Federation EPO 42 mths
Appeal against
ban
Horse treated with
prohibited medi-
cation (Capsaicin)
Hansen,
Tony Andre
4 mths /€
2,000
NOR Riding FEI n.s.
Herzog,
Tommy CH Bobsledding Swiss Olympic Testosterone 24 mths n.s.
Accused of
bribery, reduced
from 24 to 18
months on the
grounds of
admission
Hütthaler,
Lisa AUT Triathlon NADA Austria EPO 18 mths
Kohl, Bern-
hard
Erythropoetin
(Cera)
AUT Cycling NADA Austria 24 mths n.s.
Konopka,
Mikulas
Slovak Athletics
Federation
SVK Athletics Methandienone lifelong Repeat offender
2 missed
samples
Kreutzer,
Daniel GER Ice hockey NADA n.s. 3 mths
Kunpeng,
Ouyang CHN Swimming
Chinese Swimming
Association Clenbuterol lifelong n.s.
Initially exon-
erated by Braz.
association,
CAS confirms
ban
Lucas,
Ricardo BRA Football CAS n.s. 24 mths
Mazzoleni,
Eddy ITA Cycling Ital. Cycling Fed-
eration n.s. 24 mths
“Oil for Drugs”
affair, refused
to testify
Mourhit,
Hassan
Belgian Athletics
Federation
BEL Athletics Anastrazol 24 mths n.s.
95
Na-
tion Sport Court Offence Penalty Comment
Name
Accused of
manipulating
doping samples
Naimowa,
Tesdschan
Bulgarian Athletics
Federation
BUL Athletics 24 mths Ban accepted
O'Neill,
Nathan AUS Cycling CAS Phentermine 15 mths n.s.
Banned from
2008 Paralym-
pics
Osmanowa,
Ludmila
Weight
lifting
UKR IPC Anabolic steroid 24 mths
Palacios,
Noraldo ESP Athletics Columbia Athletics
Association n.s. 6 mths
Banned from
the Olympic
Games
7 Modelling of differences and derivation of hypotheses
With respect to the level of sanctions, considerable differences exist between
various European countries. Based on the model presented above, we consider
in the following different manifestations of the sanction level , to which –
depending on the respective situation – the individual European countries can be
assigned.
S
s
S denotes a sanction level on the supply side that shall be considered as a
standard value. h
S then describes a level of penalty that lies above and a level
below the standard. For the supply side, it shall therefore be established that:
n
S
(33)
nsh SSS >>
From this relation (33) and the assumption (2), it can be derived that a higher
sanction also leads to a higher investment and it therefore follows that:
(34)
),(),(),( RSIRSIRSI nsh >>
i.e. in countries with a higher level of penalties, investments made by a sup-
plier and/or a consumer in escaping punishment are higher than they are in
countries where the level of penalties corresponds to the standard. Conversely,
actors from countries with a comparatively low level of sanctions invest less in
avoiding punishment.
With respect to the impact of different levels of sanctions on the probability
of detection – given the same level of repression – it can be concluded from the
above reflections relating to (6) that where sanctions are higher, as in Germany
or France, the probability of detection is lower than in countries with lower
sanctions, i.e.
(35)
),()(),( ,RSpRSpRSp nsh <
<
Thus on the supply side, it follows specifically from the reflections relating to
the benefit (8) and its impact on the expected benefit of suppliers that initially an
96
increased level of sanctions will reduce the benefit of trafficking doping sub-
stances:
(36)
)()()( nsh SNSNSN <<
Reflections concerning the variability of the expected benefit as a result of the
level of sanctions show that without additional conditions for the functions
and no statements can be made. It is revealed that the expected benefit de-
creases with rising sanction levels provided that the respective condition
p
N(13) is
met. In condition (13) it was shown that via increasing sanction levels it is only
possible to influence the expected benefit of suppliers with a low income (de-
scribed above as type A). Concerning the difference between European coun-
tries this means that in countries where the level of sanctions is higher we ought
to find a higher market concentration of a few, high-earning suppliers.
On the demand side, in addition to sanctions relating to the individual Euro-
pean countries it is possible to establish to what extent sanctions exist beyond
those stipulated by WADC. It has been found that with the exception of Ger-
many, Switzerland and Spain, consumers (i.e. athletes) can be criminally prose-
cuted for possession, consumption or importing and exporting illegal substances.
In order to classify the occurrences of higher sanctions in cases of doping, we
denote a sanction at WADC level (currently in WADC: 4-year ban for dopers)
in the following with . If additional sanctions for athletes exist in a given
country, this is represented as . Thus we additionally obtain:
W
S
+W
S
(37) , which affects and , therefore:
WW SS >
+)(SI ))(( SIp
(38) and
)()( WW SISI >
+
(39) ))(())(( WW SIpSIp
<
+
shall apply.
Considerations of the expected benefit on the demand side included giving
consideration to different investment strategies. On the one hand there are con-
sumers who react very quickly to tougher sanctions and therefore even in the
case of comparatively low sanctions invest everything they are prepared to in
investments. On the other hand there are those who take a wait-and-see attitude
to increased sanctions and make proportionately low counter-investments
. With respect to the relevant conditions, it became apparent that on the
one hand the expected benefit and on the other hand the derivation of the ex-
pected benefit (i.e. the possibility of control via S) is not possible under real
conditions in any of the observed cases (cf.
)0( m
(24), (28), (30) and (32)). Conse-
quently a higher level of sanctions can only produce a negative expected benefit
under very restricted conditions and control via is not possible under any
circumstances. S
97
Nevertheless, a change in the level of sanctions results in changes in counter-
investments (which are known to increase with higher sanctions), causing a
lowering of the probability of detection. Thus consumers in countries with
higher sanctions would have to invest more (presumably by consuming more
masking agents), therefore lowering the probability of detection. However,
based on the observations made, there is no change in the prevalence in these
countries.
8 Conclusion
For the supply side it has been shown that the higher exogenously-determined
penalties are and the greater the probability of them being imposed, the more
likely suppliers will be to do everything they can to avoid punishment, thus also
reducing the risk of punishment for buyers. This relates not only to distribution
channels (risk of discovery) and to efforts to conceal the substances being used
by the doper (development and utilization of masking agents), but also to the
bribing of laboratory staff, donations for laboratories, etc., although as veiled
bribery the latter would even be tax-deductible for high-income professional
athletes. The resulting higher prices consequently rule out lower-income buyers
as consumers. In general, we may expect to see a concentration process in the
market towards a few, high-earning suppliers.
For the demand side it has been shown that neither a negative expected bene-
fit, corresponding to a solution to the “doping” problem, nor a lowering of the
expected benefit of athletes through higher sanctions, is plausible.
For the European comparison it has been shown that different threats of sanc-
tions also tend to produce different investment strategies on the part of consum-
ers. Thus on the one hand we can anticipate consumers who react very quickly
to tougher sanctions and in the case of comparatively low sanctions are willing
to invest everything they are prepared to in counter-investments. On the other
hand there are those who take a wait-and-see attitude to increased sanctions and
make proportionately low counter-investments.
The formalization revealed that the conditions for “producing” a negative ex-
pected benefit as a precondition for the effectiveness of sanctions were not met
under anything approximating real conditions in any of the observed cases. Con-
trol via , i.e. the level of sanctions, on the demand side proved ineffective in
the sense of a reduced benefit. However, increasing sanctions produce counter-
investments and thus lower the probability of dopers being detected. Conse-
quently, consumers in countries with higher sanctions are likely to invest more
(presumably by consuming more masking agents) in order to lower the probabil-
ity of detection, which in turn simply means that in Europe, despite different
sanction levels, a stable market equilibrium is established among those consum-
ers still in the market. However, based on the observations made, there is no
change in the prevalence of doping in these countries. It has to be concluded that
S
98
doping prevalence evades the controlling arm of criminal law and that in light of
the existing probabilities of detection and punishment the dilemma of doping
cannot be solved via criminal law.
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Otto Loewi, Nobelpreisträger für Medizin, hielt in hohem Alter einen Vortrag als Ehrenpräsident des Internationalen Physiologenkongresses. Befragt nach seinem Erfolgsgeheimnis erläutert er sein Rezept: Der Tag beginnt mit einer Dosis Speed (Weckamin), um ganz wach zu werden, und […] einer großen Dosis Vitamin C, zusätzlich etwa ein Aluminiumhydroxid, sofern der Magen wegen Überlastung drücken sollte, und ein schleimlösendes Mittel, um die Bronchien freizukriegen. Dazu eine Tablette mit Verdauungsenzym zur Anregung des Darmes. Das genügt, um nach dem Frühstück das Labor zu besuchen. Die Lektüre der Post und der eingetroffenen Publikationen mag verstimmen. Bevor sich depressive Gedanken einstellen, eine genügende Dosis Morphium oder Heroin, zusätzlich ein Anabolikum, das den Appetit für das Mittagessen erfreulich anregt. Der Espresso begleitet die Unterhaltung mit Besuchern. Danach benötigt der Professor meist ein Glas Rotwein, das der Schläfrigkeit für die Siesta zum Durchbruch verhilft. Beim Erwachen um halb fünf allerdings ist am besten eine Dosis Kokain – gegen Abend kein Speed! –, damit die nun folgende geistige Arbeit bald in Gang kommt. […] (Parin 1997, S. 144) « Bei dieser Antwort, die möglicherweise auch ironisch gemeint war, handelt es sich um einen Fall des kontrollierten Einsatzes von rezeptpflichtigen Medikamenten und verbotenen Drogen mit spezifischen Wirkungen. Auch Doping ist eine solche Form des gewöhnlich heimlichen bzw. hinter den Kulissen vorgenommenen Einsatzes von Medikamenten oder Methoden, die jedoch ausschließlich im Feld des Sports auftritt.
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Biomedical doping tests specifically, as well as doping test practises as a whole, have severe shortcomings which are based upon the fact that test procedures are in principle imperfect. With the help of Bayesian logic, it can be shown that the interpretation of doping test results is far from trivial with reference to individual athletes and single doping tests, but that these tests can reveal results which can be fairly dependable when it comes to estimating the prevalence of doping. Even if multiple tests are conducted and the samples are analyzed repeatedly for substance abuse, the need for positive A- and B-sample analysis is a strong argument in assuming that positive-tested athletes are guilty. However, this does not save an anti-doping policy which relies on increasing numbers of doping tests all over the world from the problem of false positive tests, which becomes the more severe the better anti-doping works in terms of lowering doping prevalence through deterrence. The considerations based on test theory and Bayesian logic lead to important ethical questioning of anti-doping policies.
Chapter
IntroductionBasic AnalysisOptimality ConditionsShifts in the Behavioral RelationsFinesSummary and Concluding Remarks
Article
The use of drugs in high-performance sports (doping) is a common pool resource (CPR) dilemma: regardless of the number of other athletes who dope, the athlete with strong tastes for victory will find doping optimal; yet if all athletes dope, they all bear negative health consequences, although each one's odds of victory are not greatly changed. The current regulatory approach relies entirely on centralized bureaucratic methods and is ineffective. The authors use insights developed in the common property resource literature and the theory of social norms to analyze the failure of these methods. The programs they propose—the drug diary and a collegial enforcement system—are superior to the current system in that they encourage the development of athletic norms against unfair drug use. In the end, such norms are the only hope for controlling doping, which is becoming increasingly difficult to observe. Empirical evidence shows that such norms against unobservable sports violations can be very powerful. Norms of conduct in golf, for example, successfully enforce that sport's many rules regulating unobservable aspects of play.
Chapter
Der zentralen Überlegung Durkheims folgend, dass abweichendes Verhalten eine normale Erscheinung ist und dass lediglich Abweichungen über und unter ein bestimmtes „normales“ Maß anomisch und damit im soziologischen Sinn auffällig sind, wurde in Fortführung bereits 2005 publizierter Studien zur Verbreitung des Phänomens Doping im Kollektiv der deutschen Athleten 2008 erneut eine umfangreiche Studie mittels der Randomized Response Technique, eine Form indirekter Befragung, durchgeführt. Frühere Kritik an der Verläss¬lichkeit von Onlinebefragungen wurde aufgegriffen und das Antwortverhalten im Fall einer standardisierten schriftlichen und postalischen mit demjenigen ei¬ner Online- Befragung verglichen.
Article
Die Frage der konkreten Häufigkeiten von Dopingpraktiken im Spitzensport ist bisher ungeklärt. Mit Hilfe der randomized response technique wurde eine inter-netgestützte Befragung durchgeführt. Sie ergab für die Frage „haben Sie nicht erlaubte Dopingmittel oder -methoden zum Zweck der Leistungssteigerung ein-gesetzt?“ in den Ergebnissen eine untere Grenze des Intervalls von 25,8 % und eine obere von 48,1 %. Für die laufende Saison betragen die entsprechenden Werte 20,4 % und 38,7 %. Für die gesamte sportliche Laufbahn bis zum Zeit-punkt der Befragung ist von einem Anteil von 51,9 % ehrlicher Nicht-Doper und für die aktuelle Saison von einem Anteil von 61,3 % ehrlicher Nicht-Doper aus-zugehen.
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Mit Hilfe der ökonomischen Effizienzbeurteilung rechtlicher Rahmenbedingun¬gen der Dopingbekämpfung wird die aktuell geforderte Nachjustierung des Anti-Doping-Gesetzes hinsichtlich der erwartbaren Wirkungen abgeschätzt. Die Beurteilung beruht dabei auf einem eigens entwickelten ökonomischen Modell eines rationalen Anbieters und Konsumenten von Dopingmitteln, mit dessen Hilfedie Wirkung verschärfter Repressionen und erhöhter Wahrscheinlichkeiten des Eintritts der Strafe abgeschätzt werden können.