5. APPROACHES TO ESTIMATING BENEFITS

5.1 Seeking an optimum suite of MCS activities
5.2 Nature of the benefits
5.3 Direct benefits
5.4 Indirect benefits
5.5 Fishing the benefits of illegal
5.6 Deterrence, compliance and benefits

The MCS manager has limited resources in terms of manpower, funds and capital assets. A critical question facing the manager is how to distribute these resources among the various MCS tasks such as information collection, port controls, sea patrols, and legal activities. This requires some means of assessing the benefits of different combinations of MCS activities. Estimating the benefits accruing from the MCS efforts is one of the most difficult questions facing the MCS manager, one which neither developed, nor developing countries have successfully addressed. The following sections offer some guidance on how to approach these issues, specifically:

a) How can the optimum suite of MCS measures be established?
b) how can the benefits of an existing suite of MCS measures be estimated, and
c) how can the effect of proposed MCS changes be measured?

5.1 Seeking an optimum suite of MCS activities

The costs of MCS activities, or sets of complementary or interdependent MCS activities, need to be assessed in relation to the results. The single most important ‘result’ is the biological state of the fish stocks. Where possible there should be a direct and potentially measurable relationship between controls and fishing mortality. This relationship does not exist in many fisheries and results in uncertainty. A ‘decision analysis’ explicitly recognizes uncertainty and can offer a useful step-by-step approach if the MCS objectives are clear.

Figure 4. Decision tree for identifying a suite of effective MCS measures

Within this decision framework several[30] ‘management tools’, or analytical methodologies can be directed at resolving the multi-dimensional problem of assessing control strategies. These include: cost/benefit analysis; cost-effectiveness analysis; critical path analysis; HACCP; LFA and SWOT, some of which are briefly discussed below.

Cost-benefit analysis suffers from difficulty in clearly establishing and valuing the benefits of the MCS activities, even though the costs of MCS can readily be recorded, or calculated. As MCS activities are highly interdependent (e.g., sea controls depend on vessel licensing), the utility of assessing control measures or strategies in isolation is questionable as benefits of control accrue from a suite of measures and cannot readily be allocated to any one control activity, or strategy.

Control assets are not necessarily allocated in the most cost-effective manner in relation to the presumed impact on the fish stocks, which is considered to be the primary object of control. While the principles underlying allocation of enforcement resources may be rational, the actual allocation may often be a response to changing ‘political’ priorities (e.g., resource conflicts), or a public perception of the priority, rather than an empirical assessment of the optimum allocation in relation to the gravity, or extent, of the hazards to the resources. Consequently, attempts to make a cost benefit, or effectiveness analysis, often founder on the question of the allocation priority. However, cost effectiveness analysis may avoid such ineffective use.

Cost effectiveness analysis selects the set of MCS activities which will minimize costs while realizing the policy and operational goals, in other words, finding the least-cost solution to providing a given level of MCS. This approach is particularly useful. It requires the country (fisheries administration) to determine an ‘acceptable level of violations’ consistent with the paramount conservation objective. To determine and monitor this ‘acceptable level of violations’ requires a coherent set of indicators of effectiveness of and compliance. As in most policing work, the absolute effectiveness and benefit of an MCS system is difficult to measure. This is because the total number of violations is unknown. As a result the effectiveness of the MCS activities must be measured in relation to a set of common sense targets set by the fisheries authorities, possibly in association with the industry itself and the national planning agency, or budget office. Given that the quantity of the principal control assets and their operational costs (i.e., numbers of patrol vessels, or fisheries inspectors), are unlikely to vary greatly in the short term, indicators of their operational efficiency are of considerable importance.

Table 5.1: Possible indicators of MCS efficiency

Offences/violations	Patrols
Number of offences detected at sea	Hours/days patrolled; Ratio air/sea hours
Number of offences detected on land	No. boardings; No. per patrol hour/day
Industrial offences	No. sightings; No. per patrol hour/day
Artisanal offences	No. catch/net inspections (sea)
Major offences number and %	Hours per boarding
Cost efficiency	Data efficiency
Cost per 1 000 t or US$ million of fish landed	No. of logbooks checked*
Cost per log sheet checked	% of aerial position sightings checked with logbooks
Cost per boarding Cost per sighting	Landings physically checked against declarations Export declarations linked with dealer purchases
Cost per shore inspection Cost per VMS poll
Administrative efficiency	Casework efficiency
Violation ® report (% with 48 hours)	% of violations reported resulting in cautions/warnings
Report ® prosecution (% within 60 days)	% of violations reported resulting in prosecutions
Report ® sanction (% within 30 days)	Success rate of prosecutions

Hazard analysis critical control point (HACCP). Valuable lessons may be drawn from the HACCP approach Canada[31] is applying integrated fisheries management. The HACCP approach, which is already well known in relation to fish sanitary controls, simply acts as a framework to systematize the planning and organization of control activities. The main steps in the use of HACCP are:

• identify of hazards;
• identify critical control points (CCPs) - locations, procedures and operational steps;
• establish limits to the critical parameters at CCPs;
• establish means of measuring and monitoring parameters at CCPs;
• identify corrective actions if limits are exceeded;
• document all procedures and record results; and
• periodically verify control measures.

The main threats and hazards to the fish resources are usually well known, e.g., violations which have the greatest impact on fish stocks. The critical control points are also known, but for various reasons may not be effectively used (e.g., lack of port inspectors, no factory gate checks, lack of authority to check dealer accounts). Many of the limits to the critical parameters are not codified, (e.g., there may be no standardized conversion factors for fish products such as ‘fillet as percent live weight for particular species’, shrimp ‘tails to whole weight’ for different size classes, or stowage factors ‘kg per m³’). The tolerance allowed when comparing log sheets to landings may be excessive. Penalties may not harmonize or be sufficiently specified in relation to the gravity of violations. Due to an absence of updated inspector manuals, different provinces, inspectors, or magistrates may interpret regulations differently. The annual reports required by the fisheries administration rarely make an assessment of the impact of fisheries control.

Logical framework approach (LFA). LFA is an objective orientated approach[32] used to design complex projects and often used to structure stakeholder dialogue to reach agreed solutions. The LFA is normally developed through a team of stakeholders progressively working through several steps: participation analysis, problem analysis, objective analysis, alternative analysis, determination of project elements, and external factors. The LFA produces three main outputs two of which are provided[33] here by way of a generic example: the problem and objective trees, upon which is based the logical framework matrix.

Integrated fishery management plans. The USA offers an example of a distinctly different approach to fishery management which includes the MCS component as an integral part of the fishery management plan[34]. The plan is approved through comprehensive legislation, which includes the budgetary provisions for its implementation, and evaluation. The essential point is that the costs of MCS are considered and budgeted prior to implementing management measures. The plan is a negotiated compromise settlement of stakeholder positions (including the fishermen) and ‘losers’ may receive financial compensation (e.g., for fleet reduction) to ensure their support for the plan. Decision rules may be included with linkages to biological or economic reference points.

Value for money. Finance ministries are becoming more concerned that government services provide ‘value for money’. Joint civil/military audits (e.g., for more cost-effective patrol), establishment of a ‘value for money’ committee, and realignment of budget sub-heads to reflect operational realities may contribute to improvement of the financial management and administration.

Targeting. A range of US and Canadian studies resulted in broadly similar recommendations on improvement of control effectiveness, including:

• targeting[35] chronic violators[36];
• concentrating enforcement measures on areas characterized by non-compliance;
• extending application of management measures to the post harvesting sectors;
• substantially increasing the severity of penalties[37];
• ensuring input from enforcement authorities early in deliberations of new fishery management plans and regulations; and
• devoting resources to strengthen the use of non-coercive factors of compliance, such as social pressures, self-interest, inducement and obligation (fishermen sensibilisation/education).

5.2 Nature of the benefits

Three types of benefits of MCS can be identified: direct, indirect and ‘illegal’. The direct benefits are characterized by transfers, or payments made to the public sector through fines, licence fees, royalties and other charges. The indirect benefits of effective are characterized by the avoidance, or reduction of negative impacts characterized by:

• unauthorized foreign fishing and illegal trans-shipments;
• depletion of spawning and juvenile stocks and depletion of the fishable biomass;
• tax and levy avoidance and creation of opportunities for transfer pricing;
• increase in conflicts on the fishing grounds,
• undermining the rule of law and compromising aspects of coastal zone management and marine environmental protection;
• reduced profitability of fisheries, reduced economic rent and fleet efficiency, and less than optimal use of scarce national resources;
• declining levels of production reducing employment both at sea and on shore;
• additional direct costs of catching and handling illegal fish, and subversion of traceability and HACCP controls;
• costs of additional management and control measures resulting from stock decline; and
• reduction in legitimacy of management measures perceived to be based on inaccurate information.

The delinquent, or violating fisherman is likely to have an ‘illegal’ short-term benefit from breaking the fisheries laws (otherwise he is unlikely to violate). These gains are also measurable.

5.3 Direct benefits

In the Falklands approximately US$45 million was raised through the sale of fishing licences, while the total costs of fishery management was in the order of US$10 million in 2000. However, without the substantial expenditure on fishery protection, it is questionable whether the revenue would have been as high.

Table 5.2: Revenues associated with MCS activities during late 1990s in West Africa

	Gambia	Guinea	G. Bissau	Mauritania	Senegal
Value of landings 1996 (US$ million)	19	19	38	140	212
Licence revenues 1996 (US$1 000)	285				690
Fines paid/owed (in US$100)/Year: 1997	247		1 539	1 551	467
1996	6	460	1 525	1 963	810
1995	971		150	1 652	676
1994	180			686
Licence revenue as % of value of landings ‘96	1.5%				0.3%
Fines as % of value of landings 1996	0.03%	2.5%	4.0%	1.4%	0.4%

Source: Kelleher, K. 1997

5.4 Indirect benefits

The primary operational objective of the MCS system is to enforce and support the management regime. The primary benefits of control accrue through improvement in the state of the resource, which is dependent on both natural and fishing mortality. Different control measures influence the fishing mortality in different ways, e.g., a violation concerning undersized fish will have a different biological effect from an over-quota violation concerning adult fish. In this manner, the management objectives and the nature of the control targets and regime determine the (biological) benefits derived from MCS activities. In principle these effects can be examined through simulations using a stock assessment model for the fishery and applying the compliance rates for each type of violation. However, uncertainty in biological models and the assumptions required regarding compliance levels makes calculation of marginal benefits of control extremely problematic, even for a simple regime. Estimating the aggregate benefits of control for a set of management measures impacting on several different fisheries represents an even greater challenge. In practical terms, fisheries scientists often assume 100 percent compliance, or make subjective assumptions regarding compliance.

This problem simply illustrates the need for management measure to be 100 percent enforceable[40] in order that their effects can be measured, and reinforces the need to simplify regulations, and to promote cost-effective, aggregate, or concentrated controls such as closed areas, VMS, and fish dealer and auction checks.

Effective MCS provides accurate catch and effort information essential for stock assessment[41]. Misreporting of catches initiates a ‘vicious circle’ of hidden costs from a reduction in the accuracy of stock assessment and thereby undermines the biological basis for management measures and their adequacy. According to ICES[42] it is not possible to retrospectively estimate misreporting accurately.

5.5 Fishing the benefits of illegal

Most of the research on the benefits accruing to fishermen from illegal fishing has been carried out in OECD countries. Annual potential losses from a projected sustained withdrawal of US Coast Guard patrols in the Bering Sea and resulting from increased incursions by foreign vessels targeting pollack have been estimated[43] at between US$6.7 million and US$40 million. Further losses from rising international tension and conflicts on the fishing grounds could also be expected. Estimates[44] of the value of illegal catches in the US Northeast ground fish fishery ranged from one-two percent of the value of landings in one area to 11-25 percent in another, indicating wide variations by State and fishing ground. A study of five OECD countries indicated that the value of the benefits from illegal fishing was up to eight times greater than the cost of MCS and that between six percent and 22 percent of fishing activities were non-compliant.

Table 5.3: Estimate of the value of illegal fishing activities in the SRFC area in mid-1990s

Calculation	Value	Reference
Estimated total recorded catches in SRFC area	1 273 000 tons	CECAF
11% of all sightings are illegal fishing operations	11%	AFR/010
91% of all illegal fishing operations are serious infractions	91%	AFR/010
Assuming illegal catches are unrecorded	100%	assumption
Estimated quantity of illegal catches	127 000 tons/year
Estimated average value per ton of fish (1994)*	US$1 300
Possible value of illegal catches	166 million US$/year

* Average value of Senegal trawl fish in 1994 (most illegal fishing is trawling).

5.6 Deterrence, compliance and benefits

There is a close relationship between deterrence, compliance and the perceived benefits from illegal fishing. A number of studies in OECD countries have examined these relationships. The approaches and results are of interest to those designing MCS systems in developing countries.

Estimates of compliance require an estimate of the total number of violations. None of the approaches used to estimate the absolute, or total level of violations is entirely satisfactory. The analysis of recorded violations in relation to control efforts is routinely used to provide an indicator[45] of the level of violations, though such information is a measure of the outputs of enforcement, rather than the level of violations. Surveys of fishermen have been used with mixed success[46] and form the basis for most studies to date. However, such surveys cannot be conducted on a regular basis, and as the subject matter is of a highly sensitive nature, results may be largely dependent on the design of the survey and skills of the interviewer(s).

Consequently, estimates of compliance require certain assumptions. Extrapolation of a compliance estimate from one type of offence to another, and from one fishery to another requires additional assumptions. Measurement[47] of the effects of controls on compliance requires both a known change in the level of enforcement efforts and a corresponding knowledge of the resulting compliance.

Models of compliance. A series of reports[48], focused largely on the Northeast region and Eastern Canada, developed models[49] of delinquent fisheries behaviour and the economics of fisheries enforcement. The models identified three main factors influencing compliance and deterrence:

• the level of the expected penalty and probability of incurring the penalty;
• the moral attitude of the fisherman, in particular his perception of the legitimacy of the regulation;
• social influence, particularly[50] through other fishermen.

Fishermen may not consider certain fisheries regulations to be legitimate[51]. Consequently, the fisherman does not consider he is doing a moral wrong when violating such regulations and the balance of peer opinion may support this moral position of the fisherman.

The level of penalties is often inadequate[52] as a deterrent and can be regarded simply as a ‘cost of doing business’. Given that the probability of detection of offences at sea cannot easily be reduced in a cost effective manner, effective deterrence may require substantial increase in the severity[53] of penalties. If both the probability of detection and subsequently paying a penalty is so low that it is not a deterrent, either the penalties must be increased, and/or the regulations changed to make them more enforceable. The following table are based on actual OECD country studies of compliance and deterrence and illustrate these points.

Table 5.4: Summary deterrence indicators from sea patrols in an OECD country

Indicator	Value*
% of vessels boarded each year	31
No. of vessels boarded per patrol vessel day	2.2 - 3.6
Correlation coefficient patrol vessel days and boardings (r2)	0.65 - 0.81
Monthly boarding rate range (boardings/no. vessels)	0.05 - 0.65
Peak boarding period/peak fishing period	Oct-Nov/May-June
Probability of a violator being boarded	0.23 - 0.39
Probability of a violation being detected, assuming boarding detects 50% of violations	0.12 - 0.22
Probability that a case (arrest/prosecution) will be dismissed	0.14 - 0.20
Probability that a fine/penalty will accrue in a case	0.42
Probability of monetary penalty given a violation detected	0.04 - 0.08
Average value of fine/penalty (excluding legal costs to fisherman) in 1995	US$4 934, median US$1 348

* Probabilities expressed as decimals

Sampled vessels
Average number of fishing days/yr	257
Perceived average boardings/vessel/year (from interviews)	4
Probability of being boarded/day (from interview/MCS records)	1.56%
All vessels
Total fishing vessel targets/day (av. of samples from high level radar)*...(a)	195
Boardings per patrol day (1999)...........................................(b)	0.98
Probability of being boarded/day (all vessels) (b/a)..........................(A)	0.5%
Probability of detection of violation per boarding (from MCS records)	15%
Probability of detention (arrest) at sea............................................(B)	3%
Probability of penalty if detained (ratio prosecutions/penalties).............(C)	66%
Probability of paying a penalty in a given fishing day.............(A*B*C)	0.01%

*Actual example from an OECD country