Authors:
Linda Nøstbakken (NHH), Thomas R. Carruthers (IC), Nicolas Roncin
(CEDEM), and other project participants
Project Acronym: COBECOS
Project Full Title: Costs and Benefits of Control Strategies
Project No.: 044153

This report reviews and summarises the literature on regulatory enforcement in fisheries. The report is divided into two main parts; theoretical and empirical work. The theoretical literature
is the focus of section 2, where first some of the main contributions from the general
economic literature of law enforcement are presented, before a review of the literature of law
enforcement applied to the study of fisheries is provided. Section 3 reviews the empirical
work that has been done on enforcement and regulatory compliance in fisheries, and the focus is on empirical investigation of the level of compliance, private costs and benefits of noncompliance, and enforcement costs.
COBECOS ii 22.08.2008

1 Introduction ........................................................................................................................ 1
2 Theoretical knowledge ....................................................................................................... 2
2.1 General Economic Theory of Law Enforcement ....................................................... 2
2.1.1 The Basic Model ................................................................................................ 3
2.1.2 Extending the Basic Model ................................................................................ 6
2.2 Economics of Law Enforcement Applied to Fisheries ............................................... 8
2.2.1 The Basic Model ................................................................................................ 8
2.2.2 Extending the Basic Model ................................................................................ 9
2.3 Concluding remarks ................................................................................................. 14
3 Empirical knowledge ........................................................................................................ 17
3.1 Level of compliance ................................................................................................. 17
3.2 Benefits and costs of non-compliance ...................................................................... 20
3.3 Enforcement effort and costs .................................................................................... 23
3.4 Concluding remarks ................................................................................................. 24
4 Summary .......................................................................................................................... 25
5 References ........................................................................................................................ 26
COBECOS iii 22.08.2008

"If he has a conscience he will suffer for his mistake. That will be punishment-as well as the prison."
Fyodr Dostoevesky
The fishery is a typical example of a common property resource, and thus suffers from the common property problem. Individual fishermen have incentives to harvest more than what is socially optimal, because they do not take into account the stock externality of harvesting. To deal with overfishing and overcapacity, the management authorities have introduced regulations, including gear and effort restrictions, area restrictions, landing taxes, harvest quotas, minimum sizes, by-catch regulations, etc.
Fishery regulations are not, in general, self-enforcing. Neither other fishermen nor the crew of other maritime vessels inform the authorities of infringements they witness. This means that enforcement costs must be incurred. As the cost of enforcement increases with the level of deterrence, it might not be optimal to have full compliance as the objective. This is discussed in greater detail in subsequent sections. The problem of non-compliance with regulations arises because the introduction of rules and regulations in the fishery does not automatically mean that the agents’ incentives to violate regulations are removed, although the fishermen’s incentives certainly can be altered.
Law enforcement and compliance have been studied by researchers representing a wide range of fields, e.g. economists, sociologists, criminologists, and psychologists, and these different groups do not necessarily agree with each other in every respect. The focus of this report is on the economics-based literature. However, in recent years economists have started to draw more upon other fields, such as psychology, sociology, etc.
1
For that reason, other perspectives on law enforcement and compliance are also mentioned in what follows.
This report was written as part of the COBECOS project which is concerned with the development of a cost-benefit analysis of control schemes for management strategies relevant
1 See e.g. Rabin (1998) for an overview of the literature on psychology and economics, and Elster (1989) on sociology and economics.
COBECOS 1 22.08.2008

for the Common Fisheries Policy. The objective of this report is to review and summarise the economic literature on regulatory enforcement in fisheries. This serves two main purposes.
First, it helps avoid duplication of already existing work. Second, it contributes to the project by indicating the gaps in the literature and thereby enabling productive research to be conducted.
The report is divided into two main parts; theoretical and empirical work. The theoretical
literature is the focus of section 2. We present some of the main contributions from the
general economic literature of law enforcement in the first part, and provide a review of the literature applied to the study of fisheries in the second part. With the theory framework in place, we turn to a review of the empirical work that has been done on enforcement and
regulatory compliance in fisheries. This is done in section 3, and the focus is on empirical
investigation of the level of compliance, private costs and benefits of non-compliance, and enforcement costs. The final section concludes and suggests some possibilities for future work.
Our discussion of the theoretical framework is divided into two sections. We start out by discussing the general economic theory of enforcement and crime. Thereafter we continue by providing an overview of some of the work that has been done on this topic within the fisheries economic literature.
The modern literature on the economics of law enforcement was initiated by Becker’s (1968) paper “Crime and Punishment: An Economic Approach.” 2
This approach uses economic theory to analyse how governments should choose enforcement levels (and thereby detection probabilities) and measures of punishment in order to maximise a social welfare function.
Rationality by individual agents is an important assumption in the literature, and committing a
2 Although Becker (1968) may have initiated the modern literature of the economics of law enforcement, scholars had studied similar issues long before Becker’s time. Bentham (1789) argued e.g. that criminal behaviour is economically rational.
COBECOS 2 22.08.2008

harmful act is assumed to be a rational choice for the offender. The economic approach to crime and punishment has been criticised on several levels by, among others, sociologists and criminologists. In particular the notion of rational profit maximising agents and the lack of focus on factors such as social and moral norms have been criticised.
3
However, as we will show later, economists have also introduced normative factors into their models of law enforcement.
In this section we give a brief introduction to the economic theory of law enforcement. We start out by presenting the model of Becker (1968). Most articles in the field published after
Becker (1968) are various extensions to his model. Some of these are briefly presented below.
The focus is on presenting those extensions that seem most relevant for an economic model of law enforcement in fisheries. The economic theory of law and enforcement has grown significantly since Becker (1968), and the literature explores many other issues in addition to those discussed here. For comprehensive reviews of the literature, see Garoupa (1997), and
Polinsky and Shavell (2000, 2006).
In his seminal paper, Becker (1968) asked how much to spend on enforcement and what level of punishment should be used to enforce different kinds of legislation. The objective is to find the levels of enforcement and punishment that minimise the social loss due to crime. The loss is the sum of damages from offences, costs of apprehension and conviction, and cost of carrying out the punishment imposed. Becker assumes that “a person commits an offence if the expected utility to him exceeds the utility he could get by using his time and other resources at other activities,” and his analysis thus falls within the economic theory of rational choice.
In Becker’s model, the utility of offences to the offender is assumed to be a function of the probability of conviction per offence, the punishment per offence, and other influences. The probability of conviction, or rather, the combined probability of an offence being discovered and the offender being apprehended and convicted, is determined by the level of enforcement
3 See Garoupa (2003) for a review of the main criticisms against the economic model of criminal behaviour.
COBECOS 3 22.08.2008

(the expenditure on police, courts, etc.). The number of offences is assumed to decrease as both the level of punishment and the probability of prosecution and conviction increases.
The main assumption in Becker’s paper can be expressed as follows:
EU
    f
 
1
   
, (1) where U and EU are utility and expected utility, respectively, the probability of apprehension and conviction is denoted by

, the income if undetected is B , and the income if detected is

B
 f

. The expected utility to an offender is seen to be decreasing in

and f . Crime is risky and the agent will accept the gamble only if the expected utility is high enough.
Let us first assume risk neutral agents. Furthermore, it is assumed that imposing fines does not cost society anything. If we denote the social loss due to crime by L , the optimal fine, given that the probability of conviction is fixed, is: f
0

L

. This is optimal because it leads to an expected fine that equals the harm (
 f
0

L ), and the offence will therefore only be committed if the gain for the offender exceeds the harm of the offence. Let us now assume that the probability of prosecution and conviction can be varied. An increase in the probability of prosecution that is compensated by a reduction in the level of punishment will leave the expected income of an offence unchanged. If the probability of conviction can be varied, the optimal fine is the maximal fine, i.e., to fine an amount approximating the offender’s wealth, as this minimises enforcement costs.
If people are risk averse, an increase in the probability of conviction that is offset by a reduction in fines so as to leave the expected income unchanged, would nevertheless reduce offenders expected utility. Hence, increased probability of conviction has a greater effect than reduced penalties in the case of risk aversion.
Polinsky and Shavell (1979) show that the optimal fine in the case of risk averse agents may be well below the maximal fine. The reason is that a high fine can lead to a reduction in fine revenues that more than offsets the reduced expenditures on enforcement, and thus reduces social welfare.
Becker uses his model, inter alia , to discuss how different types of punishment affect the optimal levels of enforcement and punishment; from fines, which can be imposed on the offender at a social cost close to zero, to imprisonment, torture, etc. that come at a social cost
COBECOS 4 22.08.2008

to society that can be even higher than the cost to the offender. Since fines are socially cheaper than other forms of sanctioning, fines are preferable as a means of deterrence.
Imprisonment should therefore not be used unless the offenders cannot pay the full fine (see also Polinsky and Shavell, 1984, on the optimal use of fines and imprisonment).
Becker’s (1968) study was soon followed by an article by Stigler (1970), also on optimal enforcement and using rational choice theory to explain criminal behaviour. Stigler’s (1970) main contribution is perhaps that of marginal deterrence . Marginal deterrence occurs when a more severe offence is deterred because its punishment exceeds that of a less severe offence.
This is highly relevant under circumstances in which people can choose between committing several harmful acts, e.g. exceeding the quota and illegally catching fish from a stock that is well within safe biological limits or from a collapsed fish stock under recovery. In this context, sanctions not only influence whether individuals commit offences, but also which harmful acts are chosen. All else being equal, it is socially preferable that enforcement policies create marginal deterrence so that the offences that are committed are the less harmful ones. Many others have elaborated on the issue of marginal deterrence since the work of Stigler (1970), see e.g. Shavell (1992), Mookherjee and Png (1994), and Wilde (1992).
Ehrlich (1973) develops a model in which the individual’s decision of whether to commit illegal activities is not an either/or choice. Instead, individuals are allowed to combine illegal and legal activities. Ehrlich models this by assuming that the individual has a given amount of time available ( t
0
), which can be spent on illegal activities ( t ), legal activities ( i t ), and l consumption ( t ), and where c t
0
   t c
. The individual’s utility is a function of the amount of a composite market good that includes returns from both illegal and legal activities, and of time spent on non-market activities ( t ). There is a fixed probability of detection and c punishment if engaging in illegal activities, and the punishment in turn is a function of time spent on illegal activities ( t ). Ehrlich’s (1973) model also includes the supply of offences, i and the model forms the basis for an empirical study of marginal deterrence. Ehrlich’s model and analysis emphasise that the better the opportunities and payoff from legal activities, the more it takes for an individual to engage in illegal activities.
COBECOS 5 22.08.2008

Polinsky and Shavell (1991) study optimal fines when wealth varies among agents . If the highest fine anybody can pay is their wealth, it might not be optimal to raise the fine to the maximal fine in order to lower the enforcement level and thereby reduce costs. Consider the case when the fine already is higher than the wealth of some agents. Increasing the fine would not have a deterrent effect on this group of agents. A reduction in the enforcement level, and consequently the probability of capture and conviction would, on the other hand, have an effect also on the low-wealth agents. Polinsky and Shavell (1991) find that the optimal fine equals the wealth of the individual ( w ) up until the point where w
 f
0

L

. For agents with wealth above this level, the optimal fine is f .
0
Agents can engage in activities that reduce the probability of apprehension and conviction.
Such activities are often referred to as avoidance activities . Among several studies focusing on this is Malik (1990), who analyses optimal enforcement when agents can engage in socially costly activities that reduce the probability of being fined. This can be any activity from investing in technology to increase the likelihood of getting away with a harmful act, to lobbying politicians to relax enforcement in certain areas. Malik assumes that the probability of being captured and fined is a function of the agent’s expenses on avoidance and society’s enforcement expenses. The probability function is decreasing in avoidance and increasing in enforcement. Malik shows that the potential for avoidance makes it expensive to raise the fine, as it increases the level and consequently the social cost of avoidance. Thus, optimal fines might be well below the maximal fine.
Another extension of the basic model is to allow for self-reporting of behaviour by offenders.
An often cited reference on this is Kaplow and Shavell (1994), who define self-reporting as
“the reporting by parties of their own harm-producing actions to an enforcement authority.”
The basic idea is as follows. The expected fine for a risk neutral agent is
 f . Self-reporting is rewarded by a reduced fine. The fine for an agent who self-reports can be set just below the expected fine without self-reporting at
 f
 
, where
 
0 is small. The deterrent effect is then essentially unchanged, but there might be several advantages of allowing for rewarding self-reporting: (i) reduced enforcement costs, (ii) reduced risk, which is advantageous if agents are risk averse, and (iii) reduced harm if early notice allows harm to be mitigated (e.g. oil spill).
COBECOS 6 22.08.2008

In many cases harmful acts are not committed by an individual person, but by a collective entity or by agents acting on behalf of a collective entity. This calls for analysis of the principal-agent relationship in addition to the analysis outlined above. The literature on corporate crime has focused on the case when the agent (the employee) acts in his own selfinterest and against the interests of his principal (the owners of the firm). In such cases, if a risk neutral principal faces expected fines equal to the harm done, he will have the correct incentives to contract and monitor the agents appropriately (Newman and Wright, 1990).
Another issue that has been analysed is the allocation of a fine between principals and agents
(see e.g. Sykes, 1981, 1984; and Kornhauser, 1982).
Mullin and Snyder (2005)
4
also analyse corporate crime within a principal-agent framework, but their focus is on situations in which the employees do not obtain any direct benefits from corporate crime. The principals may, on the other hand, benefit from such activity. Hence, the structure of the compensation scheme facing the employees may be set up to induce them to commit offences. Mullin and Snyder (2005) use their model to analyse whether indemnification should be prohibited. They find that there are very few circumstances under which it is strictly beneficial to sanction the employee in addition to the firm. Furthermore, they conclude that it is typically inefficient to forbid indemnification.
Polinsky and Shavell (2001) analyse corruption in law enforcement. In particular, they study the use of bribes paid by a violator to an enforcement agent in order to avoid or reduce penalties, and extortion, which occurs when an enforcement agent threatens to frame (or actually frames) an innocent person in order to extort money from him. Corruption dilutes deterrence and is therefore socially undesirable. If corruption is not controlled, bribery will occur whenever someone is apprehended and framing will occur whenever someone is in a position where he can be framed. Polinsky and Shavell (2001) develop a model of corruption where corruption is controlled with sanctions and rewards to enforcers for reporting offenders.
They find that the optimal fines in this situation are maximal both for bribery and framing.
Extortion, on the other hand, should not be sanctioned. Such a policy can only have the two following effects, both socially undesirable. (i) If extortion is not deterred, it would raise the
4 Mullin and Snyder (2005) also give a nice summary of the literature on principal-agent problems and corporate crime.
COBECOS 7 22.08.2008

payment of innocent individuals. (ii) If it is deterred, the enforcement agents would turn from extortion to framing innocent people. The second effect is socially less desirable than the first and thus extortion should not be deterred.
This concludes our presentation of the general literature on the economic theory of law enforcement. In the next section we turn to the economic literature of law enforcement applied to fisheries and related fields.
In this part, we present the economic literature on law enforcement in fisheries. This literature is closely related to the more general literature on non-compliance in natural resource management and environmental policy. The latter is however not reviewed in this report. The interested reader is referred to Cohen (1999) for a review of this literature. The presentation is divided into two main parts. The first part presents how the basic model of fisheries law enforcement is developed, and the second part presents various extensions.
In 1985, Sutinen and Andersen (1985) published a study of fisheries law enforcement, where they applied Becker’s (1968) model to analyse regulatory compliance in fisheries. Their model consists of two parts: (i) supply conditions explaining the behaviour of the firms in terms of harvesting and compliance, and (ii) enforcement costs. Firms are risk neutral and maximise expected profits. Expected profits for a firm harvesting in violation with regulations
( q
 q ) can be written as:
       q
 
1
  
, (2) where

is the probability of detection and conviction, q and x are catch rate
5
and fish stock, respectively,
  
are operating profits, and f
 
is the fine if convicted of a violation, with an upper bound equal to the assets of the firm. It follows that q is determined by the first-
5 Although catch rate is used as an example of what is regulated here, q could also be interpreted as other regulated variables, e.g. gear restrictions.
COBECOS 8 22.08.2008

order condition
   
 q
 
  
 q
. A firm’s catch rate is thus a function of the probability of detection and conviction, stock size, and catch quota. Following Becker (1968),
Sutinen and Andersen (1985) assume that enforcement is costly and that the higher the probability of detection and conviction

, the higher the enforcement costs.
Sutinen and Andersen (1985) use their model to analyse optimal regulatory enforcement in a fishery and compare this to the case of perfect and costless enforcement. They assume the usual criterion of maximising the sum of discounted net social benefits and derive optimal policies, and show, inter alia , that the optimal stock size with costly enforcement is smaller and decreasing in enforcement costs. The situation analysed by Sutinen and Andersen (1985) is that of non-transferable quotas in a single-species fishery, although the model could easily be interpreted to analyse other (similar) cases.
Furlong (1991) develops a theoretical model as a basis for his empirical study of deterrence in fisheries. The model is similar in nature to the supply side of Sutinen and Andersen’s (1985) model, but is based on fishermen having a given amount of time available. Total available time is then allocated between fishing in compliance and in violation with regulations. This approach is similar to the approach taken by Ehrlich (1973). Furthermore, Furlong splits the probability of detection and conviction

(cf. equation (2)) into the probability of detection, and several conditional probabilities; prosecution given detection, conviction given prosecution, and punishment given conviction. The main focus of Furlong’s study is however not on developing a theoretical model of regulatory enforcement in fisheries, but on estimating the supply of violations based on data on individual units (fishermen).
As long as enforcement is not perfect, there are illegal gains as well as legal gains from the fishery. Milliman (1986) discusses how this should be dealt with; should the fishery manager only maximise expected legal benefits, or should illegal benefits also be taken into account.
Milliman also analyse the implications when the agents operating in the fishery can engage in costly avoidance activities . This is also dealt with in the studies by e.g. Anderson and Lee
(1986) and Charles et al.
(1999), which are presented below. In Milliman’s model, there are two groups of fishermen; those fishing legally and those fishing illegally. Both groups
COBECOS 9 22.08.2008

maximise profits, and both are assumed to obtain the same price of landings. The cost side, on the other hand, differs between the two groups, as the cost function of the illegal group includes an avoidance cost function and the expected fine. The probability of detection is assumed to depend on the number of illegal vessels, level of avoidance activities, and on the enforcement level. The cost of enforcement depends on the level of enforcement.
Milliman (1986) assumes open access in the illegal part of the fishery, and studies optimal regulation based on maximisation of total gains versus legal gains. He finds that optimal policies deviate significantly depending on what is being maximised. Furthermore, if legal gains are maximised, the cost of increased avoidance activity in the illegal market is ignored.
If maximising total gains, regulatory instruments that reduces the number of illegal agents without increasing the cost of avoidance are preferred.
6
Anderson and Lee (1986) develop a model of an effort regulated fishery where fishing in excess of the maximum effort limit is fined if detected. Their model is similar to Milliman’s
(1986) model, as the profit function of a fishing vessel includes the expected fine if detected as well as the cost of avoidance activities, in addition to operating costs and revenues.
Anderson and Lee’s (1986) avoidance cost function is zero when the level of enforcement is zero, it increases with enforcement initially, before decreasing and approaching zero as enforcement level increases. The optimal policy based on maximisation of total gains from the fishery is derived, and the authors also discuss how to best choose between various management instruments. In correspondence with the results of Milliman (1986), Anderson and Lee (1986) find that the social cost of avoidance is important in setting up optimal management programs.
Charles et al.
(1999) focus on the effectiveness of input and output controls when enforcement is not perfect. Their model is similar to those presented above; fishers maximise expected profits net of expected punishment, and their variable cost functions include avoidance costs. The authors argue that general conclusions regarding the relative merits of input and output controls cannot be drawn, as the optimality conditions of the agents differ structurally depending on the regulatory control used, as do the units of measurement under the two control regimes. Furthermore, they find that the impact of enforcement on illegal
6 See also e.g. Malik (1990) on the implications of costly avoidance activities.
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fishing depends strongly on the cost and effectiveness of the avoidance activity. If avoidance is very cheap and/or very efficient, the fishermen’s response to increased enforcement is increased avoidance activity. If not, increased enforcement is first met by increased avoidance activity, up until a point where it is more efficient for the fisherman to decrease illegal fishing than to increase avoidance.
Drawing on the economic literature on environmental policies, Jensen and Vestergaard (2002) treat illegal landings as a moral hazard problem and propose an individual tax scheme as a solution to the non-compliance problem. There is asymmetric information on the harvest level of individual fishermen, in the sense that this is only known with certainty by the fisherman himself. Stock levels are on the other hand assumed to be observable and used as a basis for setting a variable, individual tax. Each fisherman’s tax in any given period is a function of the fisherman’s marginal net social cost from exceeding the optimal catch level, and the fisherman’s perceived biological response to his catch. The tax scheme thus requires detailed information on inter alia the individual fishermen’s cost and benefit functions.
Hansen et al . (2006) build on the work of Jensen and Vestergaard (2002), and propose a similar tax scheme based upon estimated aggregate catch instead of total biomass. In this model, each fisherman reports his planned catch quantity ex-ante . The individual tax, to be paid by each fisherman after the termination of the fishing season, depends on these selfreported catch quantities. The authors argue that there exists a unique Nash equilibrium in which individual fishermen’s self-reported catch quantities are truthful, and they show that their proposed tax scheme results in optimal or almost optimal individual catches. In contrast to Jensen and Vestergaard (2002), this tax scheme does not require data on the cost structure of individual fishing firms, nor is perfectly observable stock size necessary.
Compliance problems arise in fisheries regulated with individual transferable quotas (ITQs)
(Copes 1986). This makes illegal fishing under ITQs a particularly relevant area of study.
Several studies deal with issues of illegal fishing in ITQ fisheries, which is what we turn to now.
Chavez and Salgado (2005) develop a model of compliance in an ITQ fishery. Their model follows along the lines of the studies presented above, but with the individual quota being chosen by a risk-averse fisherman who is permitted to trade in a quota market. The
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optimisation problem of the individual agent is then to chose the level of quota holdings and harvest (effort) to maximise expected gains (cf. equation (2)):
      
0
  
    q

, (3) where p is the price of fish, h
 
is total harvest as a function of effort e , and biomass x , c
 
is operating costs, w is the market price of quota, q and q
0
are quota holdings and initial quota, respectively, and
 f
 
as before gives expected punishment (if q h
 
).
Chavez and Salgado (2005) show that the optimal level of effort depends on the price of fish, the quota price, and the biomass of the stock. Defining the violation as v h
  q , they argue that also the violation is a function of those three variables, in addition to the enforcement level (

). They study how non-compliance affects the quota price, and how the quota price and the level of violations are affected by the size of the total quota (total allowable catch, TAC) and biomass level. Chavez and Salgado (2005) find that the presence of non-compliance decreases the equilibrium quota price in an ITQ system.
This issue is further elaborated upon by Hatcher (2005), who shows that the effect of noncompliance on the quota price depends on inter alia the way violations are defined. Chavez and Salgado (2005) focused on the case when the violation was defined in absolute terms.
Hatcher (2005) pointed out that the results may change if violation instead is expressed in relative terms. Hatcher used a static model in his analysis of the effect of various specifications of the penalty function on quota price etc. in an ITQ fishery. Among other things, he shows that if the penalty is a function of the relative violation (total harvest as a fraction of quota) rather than the absolute violation, quota prices in an ITQ system with noncompliance can be higher than in an ITQ system with perfect compliance.
Thus far, we have presented papers that are loyal to the main ideas proposed by Becker
(1968). Fishermen have been assumed to be driven purely by self-interest, and the compliance decision is typically based on maximisation of expected profits or gains (instrumental rationality). In the following we turn to studies that to a certain degree relax the assumption of pure instrumental rationality of agents. In addition to the traditional instrumental drivers of compliance, additional normative drivers of compliance are proposed in this literature. This means that one acknowledges that the utility function of the agents may depend also on other
COBECOS 12 22.08.2008

factors than profit maximisation. This as a response to some of the criticisms raised against the traditional instrumental rationality approach to compliance and law enforcement. See
Hønneland (1999) for a presentation of some of the literature.
7
Kuperan and Sutinen (1998) point out that the compliance level in most fisheries is fairly high, although neither the fines are very high nor is the probability of conviction very low.
8
They argue that if the behaviour of fishermen is determined only by rational optimisation of expected gains, the compliance level in many fisheries should have been much lower. Their paper is mainly empirical, and using data on Malaysian fisheries, they find support for including additional factors than those representing pure instrumental rationality when accounting for non-compliance.
9
Sutinen and Kuperan (1999) develop what they refer to as an “enriched theoretical model” of non-compliance by drawing on psychology and sociology. The compliance decision in their model depends on potential illegal gain, expected punishment, the agent’s moral development and standards of personal morality, legitimacy of regulations and social environmental influences. The utility function of the individual depends not only on economic gains, but also on personal morality and social reputation. Personal morality is assumed to be affected by legitimacy of the regulations, as perceived by the agent, and a factor representing the agent’s moral development, in addition to the time spent fishing in violation with regulations. They argue that a compliance model that accounts for behavioural influences in addition to pure profit maximisation may explain why fishermen are seen to comply with regulations although the expected economic gains of illegal fishing outweighs legal gains (cf. Kuperan and
Sutinen, 1998).
Sethi and Somanathan (1996) develop an evolutionary game theoretical model of a common property resource. In addition to modelling the dynamics of the resource stock, they model the
7 In their discussion of non-compliance and fisheries policy formulation, Hatcher and Pascoe (2006) present models of individual’s behaviour that incorporate social and moral norms.
8 See also the environmental enforcement literature on the Harrington paradox (e.g. Harrington, 1988; Heyes and
Rickman, 1999), i.e., the observation that (i) the probability of conviction if violating environmental regulations is low, (ii) the expected penalty facing a violator is small compared to the gains from violation, and (iii) despite this, firms are compliant most of the time.
9
Empirical results from this and other studies are presented in section 3.
COBECOS 13 22.08.2008

evolution of the game between the users of the common resource. Referring to studies showing how social norms have important influence on behaviour, their model of evolutionary dynamics is set up in such a way that cooperation today is more likely followed by cooperation tomorrow while non-cooperation today is more likely to be followed by noncooperation tomorrow. In their model ’good’ behaviour is more likely to appear although such behaviour would not have been chosen in a model where individuals strictly maximise own profits without caring about social norms, etc.
Xepapadeas (2005) also takes on an evolutionary approach to regulatory compliance, and analyses the outcome of regulation in terms of compliance and resource stock level by means of a dynamic model. He defines two harvesting strategies, one cooperative and one noncooperative, and divides the population of fishermen into two segments, one for each strategy.
In addition to modelling stock dynamics, he uses replicator dynamics to describe compliance with harvest rules; each segment’s share, cooperative and non-cooperative, is assumed to increase if individual profits increase relative to average group profits and vice versa . The analysis shows that under certain conditions, a limit cycle, implying oscillating compliance and stock levels, could be the result. Full compliance is a possible outcome of the analysis given that the fine and/or the probability of getting detected are high enough.
Some of the studies presented above have dealt with enforcement costs along with other issues of non-compliance. There are few, if any, studies that focus exclusively on the theoretical aspects of the cost of enforcement activities . However, several chapters of Schrank et al . (2003), “The Cost of Fisheries Management,” are devoted to theoretical investigation of fisheries management costs. Arnason et al . (2003) discuss who should cover the cost of fisheries management. Arnason (2003) shows how optimal harvesting schemes may differ depending on whether management costs are ignored in the model. Finally, Andersen and
Sutinen (2003) analyse fisheries management and how it is financed from the perspective of public choice theory. The cost of enforcement of fisheries regulations is only part of the total cost of fisheries management, but several of the considerations still apply.
In section 2.1, a review of the basic theory underlying the economics of crime was presented
together with some topics believed to be of relevance for the analysis of regulatory
COBECOS 14 22.08.2008

compliance in fisheries. Although important parts of the general literature on the economics of law enforcement have been adopted and used to study similar issues in the fishing industry
(cf. section 2.2), there appears to be some further areas of the general theory of the economics
of enforcement that could be applied to fisheries.
Amongst the areas not yet explored in the fisheries economics literature is corporate crime and the application of principal-agent theory to analyse the relationship between the owners of possibly non-compliant fishing firms and the employees. This seems highly relevant in many fisheries, especially those in which large, vessels with many employees operate, since in fact, most of the regulatory violations must be carried out by the employees. Who should be punished and how severe should the punishment be? And how are the incentives within the firm to avoid, or perhaps induce, non-compliance?
One issue likely to arise in ITQ systems with absentee ownership (i.e., quotas are not held by active fishermen but rented out by quota owners) is who should be punished, and how incentives to cheat may differ between quota owners and those who rent quota. The stewardship effect only works for the quota owners. Those who rent quota have strong incentives to cheat. The quota owners have few opportunities to monitor them?
Furthermore, the existence of corruption in fisheries has been discussed by several authors, but to our knowledge, little work has been done when it comes to including corruption and bribery into formal models of compliance in fisheries. Self reporting in fisheries, in the sense that fishing firms can report their own illegal actions after committing violations, represents another possibility for future research that may prove fruitful.
There are of course many other possible extensions that could be explored in order to better understand the mechanisms behind regulatory compliance in fisheries and how best to enforce regulations. In addition to looking to the general economics theory of law enforcement, one should also take into account the peculiarities of the fishing industry and the management of fisheries compared to e.g. traditional manufacturing industries. Furthermore, literature from other fields like sociology and psychology may offer useful theoretical approaches that can be drawn on.
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Finally, although the literature above is of a theoretical and stylised nature, several implications for policy and practice can be drawn. First and foremost, when considering any management measure aimed at reducing compliance problems, it is crucial to understand the underlying incentives driving the fishermen/fishing firms. Targeting one way used by fishermen to violate regulations will only lead the fishermen to look for new ways, as long as their incentives to violate regulations are still there. However, the more risky (in terms of higher probability of being apprehended) or the more costly for the fishermen to violate the regulation (both in terms of monetary costs, fines, and normative sources of utility loss), the less likely is violation. Many examples can be used to illustrate this. An important problem of illegal fishing is due to the fact that when an illegal fish is landed, it cannot be distinguished from a legally landed fish on the market. Management measures that aim at strengthening the traceability of fish from vessel to market and across boarders help to alleviate this problem.
Furthermore, such measures are likely to increase the cost of dealing with illegal fish, and thereby reducing the incentives to do so. Another, and yet more obvious example, is to punish non-compliance harder, which reduces fishing firms’ incentives to choose non-compliant behaviour.
Looking at the more specific extensions of the basic model and implications for practical management measures, consider the problem of illegal fishing under ITQs. If every fishing firm comply with its quota, an ITQ system should lead to efficiency in the fishery. That includes fishing firms adjusting to and operating at the production and capacity levels each firm finds optimal relative to their quota and other factors. However, if fishing firms have the option to illegally catch more than their quota, this may not hold. This brings us to another important implication for policy makers. If firms do fish illegally so that actual catch levels exceed quotas, firms are likely to also have excess capacity compared to what would have been optimal under perfect compliance. This emphasises the importance of focusing on capacity, per se, but it also suggests to better track capacity development at the vessel or firm level. By obtaining more detailed data on investment in physical capital, analysis of such data could yield important knowledge also with respect to non-compliance and incentives to fish illegally.
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Our discussion of empirical knowledge takes place within the framework of the available enforcement theory. For this theory, the (1) level of compliance, (2) the expected benefits and
costs of non-compliance and (3) the costs of enforcement play a crucial role (cf. section 2).
So, it is in these terms that we primarily discuss the current state of empirical knowledge.
In most fisheries there is limited knowledge and certainly very little published work quantifying the level of compliance in relation to management measures. Most investigations on compliance are commissioned by management organisations and published in the grey literature ( e.g.
Nautilus Consultants, 1998; OECD, 2003; MRAG et al ., 2004). Thus far, the work of MRAG et al . (2004) is unique in obtaining quantitative information about compliance at different levels of enforcement. The investigation of descriptive models suggested that under certain circumstances, a logistic function best approximated the observed data and was considered theoretically possible. The report also provided some evidence that relatively high rates of compliance (>80%) can be achieved at relatively low levels of enforcement (<50 inspections per 1000 t catch). More simple qualitative/descriptive studies are available. For example, in their survey-based investigation of Scottish fisheries, Clapton et al., (2006) found that both fishermen and sellers considered the rates of compliance to have improved due to tighter regulations and stronger penalties.
To identify unreported fishing, several approaches have been taken. These include accounting for sightings, estimation based on trade and market information (Willock, 2004), monitoring landings, comparing the results of stock assessments, estimation based on anecdotal information (Pitcher et al ., 2002), and estimates based on fisheries protection vessel cruise data (Agnew and Kirkwood, 2005). Using trade information to estimate unreported catches of fish rather than the more traditional methods, FAO estimates of unreported fishing were found to be underestimated by as much as 30% in some years (Willock, 2004). There are however also problems with the use of trade data, e.g. the difficulty of attributing catches to areas and years.
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The European Commission draws up a compliance scoreboard (European Commission, 2006) based on working papers on control in Member States which are in turn based on annual submissions from Member States as well as observations by the Commission. However these are generally concerned with compliance in reporting rather than compliance with management measures. For instance, the 2005 scoreboard notes that only two nations submitted effort declarations on time compared to three the previous year. According to the scoreboard there was a marginal reduction in overruns of quota with a 1.8% overrun reported for 2004. More useful indicators such as the extent to which the reported landings match real landings are not estimated.
This creates severe difficulties for those who need to know how many fish are removed from the fishery each year in order to assess stock levels and determine appropriate management responses.
According to a 2005 study group (ICES, 2005); illegal, unreported and unregulated fishing
(IUU) represents the single largest potential source of unrecorded fishing mortality for stock assessment. The Arctic Fisheries Working group (AFWG) report that for North East Arctic cod, since 2002, between 90,000 - 115,000t of catch per annum has gone unreported because of trans-shipment. For Baltic cod, the Baltic Fisheries Assessment Working Group estimate that the true catch is between 35 - 45% greater than is currently reported. Based on observations from vessel detection systems (using satellite imagery), ICES North-Western
Working Group (NWWG) report that redfish catches may be underestimated by 25%. Other stock assessment working groups are aware of potential biases in catch data due to IUU fishing that are seriously compromising their stock assessments, but presently have no way of quantifying this inaccuracy.
10
Other estimates of non-compliance include, at the international level, the Antarctic area (39% of total CCAMLR
11
catches in 2000/01 on average in the area, but with stocks having been reduced by as much as 90% in some parts of the area due to IUU fishing), Willock (2004),
10 See e.g. the Working Group on the Assessment of Mackerel, Horse Mackerel, Sardine and Anchovy
(WGMHSA), the Working Group for North Sea, Skagerrak and Kattegat (WKNSSK) and the Working Group for Assessment of Deep-sea Fisheries Resources (WGDEEP).
11 Commission for the Conservation of Antarctic Marine Living Resources.
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and the ICCAT 12 (25,000 tonnes or around 18% of all fishing activity for tuna over the
2001/2002 season). In the Northwest Atlantic Fisheries Organisation (NAFO) area, it was estimated that 10,000 tonnes of groundfish were illegally caught in 2001, including plaice, cod and redfish. In addition, Greenland halibut quotas were also estimated to have been exceeded by 3,100 tonnes, and some parties were referred to fail submitting observer reports in 2000 and 2001 (OECD, 2003).
A recent study identified that the worldwide scale of IUU fishing may be in the order of USD
4 - 9bn per annum, with at least USD 1bn from sub-Saharan Africa countries alone and over
USD 1bn from unregulated high seas fishing (MRAG, 2005).
The single most important drivers for IUU fishing are economic factors (Agnew & Barnes,
2004) and poor enforcement of international and national regulations which are often exacerbated by the management systems that are chosen (HSTF, 2006). Some of the relationships between compliance and enforcement are known in their functional form, if not in their quantitative form. There is usually a non-linear relationship between enforcement effort and the level of compliance, with 100% compliance being notoriously difficult and prohibitively expensive to achieve (MRAG et al ., 2004). This leads, naturally, to there being enforcement optima, but the precise level of the optimum will depend on many exogenous factors such as the general satisfaction of fishermen with the management system, the general level of compliance with laws in the country in question and alternative rural employment.
For instance, compliance in European fisheries seems to be worse when fishermen do not believe the science underpinning management decisions, and particularly when TACs are dropping faster than fishermen think is warranted (see e.g. Kuperan and Sutinen, 1998). In developing countries, there also seems to be a direct relationship between the level of governance of a country and the level of compliance in its fisheries (MRAG, 2005).
For locally important fisheries, such as the scallops fisheries in the Bay of Saint-Brieuc which is governed by input restrictions, estimates of non-compliance vary between 30% and 60%
(Guyader and Fifas, 2006). In nearly all these cases, estimates of non-compliance are based on some judgement rather than statistical analysis.
12 International Commission for the Conservation of Atlantic Tuna.
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For the British Columbia salmon and groundfish fisheries, Ainsworth et al . (2005) estimate the quantity of discards, illegal catch and unreported catch over time. The estimates are based on influences in the history of the fishery assigning influence factors to regulatory, technological, and political changes on IUU fishing, and on independent estimates of misreporting. The IUU estimates vary greatly depending on fleet and targeted species. IUU catches for salmon and groundfish increased from the 1950s and throughout the 1980s, and by
1990, the amount was close to 18% of recorded landings. By 2000, IUU estimates had dropped to about 6.6% of landings.
Eggert and Ellegård (2003) seek to reveal the extent of unreported catches in Swedish fisheries by conducting a mail survey among commercial fishermen. According to the respondents, 90% of all Swedish catches are reported. Hatcher and Gordon (2005) give an assessment of the extent of non-compliance with fishing quotas in a UK fishery based on a survey of the fishermen. 20% of the respondents claimed not to have landed any fish illegally, around 50% admitted to having exceeded their quota by up to 10%, and 27% by 20% or more.
Comparing compliance among case-studies is not straightforward since they may contain varying proportions of offence type of different severity; it may be difficult to objectively compare two fisheries at similar levels of compliance if one consists of quota overruns, the other restricted area violations.
A 1998 study of compliance in Denmark, Germany, Netherlands and Scotland (Nautilus,
1998) summarized and characterized prosecutions for infringements but did not attempt to identify the hidden non-detected level of non compliance. Such levels were, however, identified in a later study undertaken directly to support the establishment of the European
Control Agency (MRAG et al ., 2004).
The benefits and costs of non-compliance can be analysed at two different levels; on the one hand, private benefits and costs to those harvesting in violation with regulations, and, on the other hand, social benefits and costs of non-compliance. Knowledge of private benefits and costs is necessary to be able to analyse the behaviour of individual fishermen or fishing firms.
However, to be able to determine the extent of non-compliance as a problem for society, we
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must also know the corresponding benefits and costs to society. E.g. although a fish is harvested and sold illegally and unreported, it may still give the fisherman, the consumer, and others positive benefits and it can therefore not be regarded simply as a loss.
13
According to the theory, the private expected costs and benefits of non-compliance are the primary determinants of non-compliance. The benefits of non-compliance are the net operating incomes, often in the form of increased catch and sometimes reduced costs, generated by violating management measures and the costs are primarily the expected penalties for doing so. The theoretical literature also proposes other drivers of compliance behaviour that go beyond the assumption of instrumental rationality (e.g. moral and social norms). Violating regulations may then be said to come at a cost to the violator, although not a pecuniary cost. The possible effect of norms and similar non-pecuniary factors has been explored empirically in several studies, as we shall see below.
In many fisheries, bio-economic models have been developed that allow the assessment of the private benefits of increased catch (or reduced costs) as well as the group or social economic impacts of that in the long run as stocks adjust. The European Commission’s Scientific,
Technical and Economic Committee for Fisheries sub-group for economic affairs described and analysed those bioeconomic models currently used within the EU (Anon., 2006).
It appears to be widely accepted that penalties are a deterrent to infringement. For instance the
Nautilus study indicates that the Dutch fishers thought that “sanctions are quite prohibitive and are designed to eliminate economic gain. Two examples are mentioned. When a fisherman is caught fishing with inlets, the fine is DFL 20,000 (€9,800) approximately half the value of his weekly catch. Infringement of the private group rules, such as putting a box of fish aside, will cost the fisherman DFL 5,000 (€2,450). Le Gallic (2004) argues that penalties in the form of trade measures can be used to reduce illegal fishing.
Little seems to be known about the cost of illegal fishing. Among the few studies of this kind are Sumaila et al . (2004) that examine the cost of being apprehended fishing illegally in three case studies (Namibia, Patagonian toothfish, Northwest Australia). The factors they consider are benefits from IUU fishing, the probability of detection, the expected penalty, the cost of
13 Cf. Milliman (1986) on how to deal with legal vs. illegal landings from a management perspective.
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avoidance activities, and moral and social drivers. Their conclusion is that the expected cost is, in most cases, negligible. Sumaila et al . (2004) also look at the spatial distribution of IUU fishing in the world. Based on various, heterogeneous information sources, they try to identify the relative expected costs and revenues from illegal fishing. They find that apart from in a few cases (4 out of 16), economic incentives are strong drivers of IUU fishing.
OECD (2005) presents data to document the level of fines for offences by foreign flagged vessels in various countries. The maximum penalty for offences committed by foreign flagged vessels, as reported by the OECD members, range from USD 3,600 (Turkey) or USD 5,056
(Netherlands), to USD 84,745 (Japan), and USD 535,514 (Canada). These fines are in many countries the result of court decisions.
Sutinen et al . (1990) estimate that in the groundfish fishery of the north-eastern United States the earnings from mesh size and closed area violations were USD 15,000 per trip, which adds up to USD 225,000 for the year 1987 for flagrant violators. Penalties for those sanctioned typically ranged from USD 3,000 to 15,000. Kuperan and Sutinen (1998) claim that similar patterns of large potential illegal gains to expected sanctions are the case in most fisheries, and argue that this calls for investigating other drivers of compliance in addition to instrumental drivers.
Several studies investigate different types of compliance drivers, both normative (moral obligations, legitimacy, fairness, etc.) and instrumental (economic incentives and expected penalties), and try to assess their relative influence. Sutinen and Kuperan (1999) find that instrumental drivers are important in any compliance regime, also in cases where normative drivers like moral obligation and social influence are found to be important. Hatcher et al.
(2000) and Hatcher and Gordon (2005) assess a wide range of different factors both instrumental and normative in their analysis of quota compliance in a UK fishery. They find some evidence on the influence of normative drivers (moral and social), but also they find that economic incentives predominate in the results. From a survey of three Danish fisheries,
Nielsen and Mathiesen (2003) found strong indications that economic gains are the driving force behind non-compliance behaviour in Danish fisheries. Nonetheless, the empirical study also confirms that moral and social norms, etc. influence compliance behaviour. In their study of compliance in Swedish fisheries, Eggert and Ellegård (2003) argue that deterrence may
COBECOS 22 22.08.2008

affect industrial fleets more, whereas social influences may be more important for smaller fleets.
Although some data on infringements and enforcement effort are available, nobody appears to have used this information to calculate either what the overall degree of compliance is or what the expected cost of a certain degree of infringement is, averaged over the whole fishery.
In recent years there have been a number of studies trying to assess fisheries management and fisheries enforcement costs. The most prominent of these studies are in Nautilus Consultants
(1998), Arnason et al.
(2000), Schrank et al.
(2003), OECD (2003), and MRAG et al . (2004).
These studies are predominantly on a national basis (rather than fishery basis). For the most part, they are limited to accounting for the management and enforcement costs over a period of few years and provide limited or no data on enforcement effort (Nautilus Consultants
(1998) is a bit of an exception in this respect). These studies have found that the cost of managing fisheries is typically a significant fraction of the gross revenues of the fisheries
(between 3 - 25%; Arnason et al ., 2002) of which enforcement is often the most costly component (28 - 76%; Arnason et al ., 2002; OECD, 2003). In their study of the
Newfoundland, Icelandic and Norwegian fisheries, Arnason et al . (2000) found the total cost of enforcement to be USD 26, 13 and 57 million, respectively.
With the exception of Korea and Norway (that were much higher), 1999 enforcement in the
OECD countries represented between 28 and 44% of the total management costs. In this year the US and the EU spent €136 and €212 million on enforcement, respectively. Within the
EU, the fisheries management costs were estimated to be about 10% of the value of the landings in 1999. EU enforcement costs are likely to have risen to approximately €273 million in 2002 (MRAG et al ., 2004), in which year, Italy had by far the largest expenditure
(€84 million in comparison to €36 million and €23 million for the UK and Spain that were the next highest spenders on enforcement). In contrast to case studies of Arnason et al . (2000), the OECD report (2003) found that the relative cost of enforcement can vary widely between countries. In the example of Norway and Korea, enforcement spending relative to other management expenditures was roughly double that of the other nations (67% of management costs for Norwegian fisheries and 76% for Korean fisheries).
COBECOS 23 22.08.2008

The observed variability in the national enforcement costs may be explained by geographical factors ( e.g.
length of coastline, size of EEZ, number of landing sites), resource characteristics
(vulnerable biomass, number of fished species, stock status, level of certainties in the stock assessment), the relative size of the fishing sector, the structure of the fleet ( e.g.
number of vessels, size distribution of vessels, proximity to shore of fishing operations, number of foreign nations / vessels), the type of management instrument applied ( e.g.
time and/or area closure, effort or catch quotas, ITQs) (OECD, 2003, provides further details). The forces driving enforcement costs are not always apparent. Korea for example, has among the highest national enforcement spending for a relatively short coastline and small EEZ (OECD, 2003).
A key finding of the previous studies is that enforcement costs alone can seriously affect the net profitability of fishing. In the case of the Newfoundland fishery it was suggested that the attainable fisheries rents may not even exceed the relatively high management costs (Arnason et al ., 2000).
An objective comparison of enforcement effort among nations may prove difficult. The annual submissions from member states of the European Union under article 35 of the Control
Regulation summarise enforcement effort in terms of number of inspectors, number of flight hours, and number of inspections at sea. However, whilst the Commission has made some efforts to harmonise the reports, the different institutional frameworks in the different States mean that it is not always possible to make direct comparisons. For instance the Spanish authorities report that Guardia Civil del Mar has 19 light patrol vessels of which 2 exclusively for fisheries monitoring, which raises questions over the fraction of time that the remaining vessels spend undertaking fisheries monitoring.
This concludes our review of the current empirical knowledge of compliance and regulatory enforcement in fisheries. The fact that illegal fishing is illegal complicates the collection of exact data from those operating in the fisheries. As we have seen, many different approaches have been taken to extend the empirical knowledge in this area. Despite this, there is nevertheless a need for considerable work to fill the gaps. Quantitative investigations of
COBECOS 24 22.08.2008

greater detail are required in order to better understand the relationship between enforcement activities and compliance.
The purpose of the report was to provide a good basis for further work, both theoretical and empirical, on the costs and benefits of regulatory enforcement in fisheries. Initially, the basic economic model of law enforcement was presented, along with some relevant theoretical extensions. In light of this, we reviewed the theoretical work that has been done on fisheries law enforcement, and identified some possibilities for future research.
We nevertheless believe that it is on the empirical side that further work is most pressingly needed. The paucity of quantitative work on compliance is surprising given the potentially large consequences for management and stock assessment. It is clear that in order to understand the relationship between enforcement and compliance and identify factors that modify such a relationship, quantitative investigations of greater detail are required. Research of this kind could provide invaluable information about the relative cost-efficacy of different enforcement methods at different levels of compliance. The results of such research may provide a basis for bio-economic modelling of fisheries that may be used to investigate optimal enforcement solutions. Equally, information about compliance is likely to improve the reliability of fisheries stock assessments and subsequent management advice.
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