1. COBECOS model simulations.
Dutch beam trawl fishery

2. Model Two species: sole and plaice
One enforcement instrument: port inspections
One type of offence: over-quota catches

3. Private benefit function (1)
Penalty structure: Fine plus confiscation of over-quota catch

4. Social benefit function
Social benefits = private benefits excl payments of fines – shadow value fished biomass – enforcement costs

5. Probability function
Probability estimated as number of inspections devided by number of landings
This assumes: probability of detection when inspected is 1

6. Enforcement costs function
Enforcement costs estimated as a linear function of enforcement effort
Costs per inspection: € 965

7. Simulations Effects of varying effort and penalty
Full compliance and optimal level of effort at current penalty
Full compliance and optimal level of penalty at current effort
Effects of alternative penalty structure on optimal effort, compliance and social benefits

8. Simulations (2) Current situation (2006):
Enforcement effort: 2028 port inspections per year (8% of landings controlled)
Penalty: confiscation of over quota catches plus fine €2200
Private benefits of the beam trawl fleet: -10 mEUR
Total revenues of the beam trawl fleet: 160 mEUR
Definitions
Non compliance (NC) = over quota catch as % of quota
Biomass effect = biomass next year as % of biomass in simulation year

9. Full compliance effort and optimal effort at current penalty
Enforcement costs mEUR PB SB
Sole landings (kt)
Plaice landings (kt)
NC sole
NC plaice
Biomass sole
 Biomass plaice
Current effort
2,028
2.0
-10
-130
13.0
22.5 0%
108%
121%
Minimum effort f.c.
2,000
1.9
Optimal effort
1,800
1.7 -7
-128
37.6
67%
102%
No enforcement
0.0 52
-166
21.0
78.8
62%
250%
70%
50%

10. Effects of varying effort on the level of Non- compliance
Minimum effort for full compliance: 2000 insp.

11. Effect of varying enforcement effort on private benefits
Lowering effort from 2000 to 0 increases private benefits from -10 tot 50 mEUR

12. Effect of varying effort on social benefits
Optimal effort: 1800 inspections per year

13. Effect of varying effort on private and social benefits
NPB = SB – PB = payed fines - shadow value – enforcement costs

14. Effects of changing enforcement effort on biomass of plaice and sole
Biomass effect = Biomass as % of biomass in previous year

15. Full compliance fine and optimal fine at current effortPB SB
Catch sole (kt)
Catch plaice
NC sole
NC plaice
Biomass sole
Biomass plaice
Current fine
2,200
-10
-130
13.0
22.5 0%
108%
121%
Minimum fine for full compliance
1,800
Range of optimal fines -9
-129
30.0
33%
112%
1,700

16. Varying the complete penalty: Full compliance and optimal penalty at current effort
Varying the complete penalty: for instance penalty of 90% of current penalty
means that 90% of catches are confiscated and the fine is 90% of current fine
Penalty
% of current penalty PB SB
NC sole
NC plaice
Biomass sole
Biomass plaice
Minimum penalty for full compliance
100%
-10 0%
108%
121%
Optimal penalty
90% -9
50%
107%

17. Effect of varying the penalty on compliance

18. Effect of varying the penalty on private and social benefits

19. Effect of varying the penalty on biomass

20. Impact of more efficient enforcement on optimal effort
Decrease of enforcement costs per unit
Optimal Effort
Enforcement costs PB SB
sole (kt)
Plaice (kt)
NC sole
NC plaice
Biomass sole
 Biomass plaice 0%
1,800
1.7 -7
-128
13.0
37.6
67%
108%
102%
10%
1.6
20%
1.4
-127
50%
1,880
0.9 -9
-119
33.8
107%

21. Impact of an alternative penalty structure
Does a different penalty structure change the optimal level enforcement effort?
And does it change social benefits at the optimal solution?
Current penalty: fine (€2200) + confiscation of over-quota catch
Alternative penalty: fine proportional to over-quota catch

22. Private benefit function (2)
Penalty structure: Fine proportional to over-quota catch

23. Comparing penalty structures
P: proportional fine
C: confiscation + fine
Fine
Effort
Enforcement costs PB SB
NC sole
NC plaice
P: Minimum fine for full compliance at current effort
8.4 €/kg
2,028
2.0
-10
-130.0 0%
C: Minimum penalty for full compliance
100%
P: Optimal fine at current effort
C: Optimal penalty, current effort
90% -9
50%
P: Optimal effort at that fine level
8.4€/kg
1,752
1.7
-128.3 8%
C: Optimal effort, current fine
1,800 -7
-128.0
67%

24. Conclusions /Discussion
Different penalty structures may provide different incentives for fishermen and can lead to different private and social benefits
Partial analysis of: landings inspections are also used for other offences (undersized fish, logbook etc); optimal effort may be different when other offences taken into account

25. Discussion / Questions
Should the shadow value of discards be included in the social benefit function?? If discards are related to landings this would influence the optimizing process.
What does it mean when social benefits are negative? Is society better off without fishing? Have we included all social benefits?

26. The End

28. Increasing social benefits by lowering effort and increasing the fine
Enforcement effort
Minimum fine full compliance (€) PB SB
Catch sole (kt)
Catch plaice (kt)
NC sole
NC plaice
1,800
9,000
-10
-128
13.0
22.5 0%
1,600
26,000
-126
1,400
61,000
-124

29. Higher penalties: minimum level of effort for f.c.
Penalty
Effort PB SB
Landings sole (kt)
Landings plaice (kt)
Biomass sole
 Biomass plaice
100%
2,000
-10
-130
13.0
22.5
108%
121%
150%
1,680 -9
-127
200%
1,480
-125

30. Higher penalties: optimal level of effort
Penalty
Effort
Enforcement costs PB SB
Landings sole (kt)
Landings plaice (kt)
Biomass sole
 Biomass plaice
100%
1,800
1.7 -7
-128
13.0
37.6
108%
102%
150%
1,600
1.6
-10
-125
33.8
107%
200%
1,360
1.3
-124