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COBECOS model simulations. Dutch beam trawl fishery.

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Presentation on theme: "COBECOS model simulations. Dutch beam trawl fishery."— Presentation transcript:

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 Effort Enfor ceme nt costs mEU RPBSB Sole landin gs (kt) Plaice landin gs (kt) NC sole NC plaice Biom ass sole Biom ass plaice Current effort2, % 108%121% Minimum effort f.c.2, % 108%121% Optimal effort1, %67%108%102% No enforcem ent %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 effort Fine ()PBSB Catch sole (kt) Catch plaice NC sole NC plaic e Biom ass sole Biom ass plaic e Current fine 2, % 108%121% Minimum fine for full compliance 1, % 108%121% Range of optimal fines %33%108%112% 1, %33%108%112%

16 Varying the complete penalty: Full compliance and optimal penalty at current effort Penalty % of current penaltyPBSBNC sole NC plaice Biomass sole Biomass plaice Minimum penalty for full compliance100% % 108%121% Optimal penalty90% %50%108%107% 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

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 Decreas e of enforce ment costs per unit Optim al Effort Enfor ceme nt costsPBSB sole (kt) Plaice (kt) NC sole NC plaice Biom ass sole Biom ass plaice 0% 1, %67%108%102% 10% 1, %67%108%102% 20% 1, %67%108%102% 50% 1, %50%108%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 FineEffort Enforc ement costsPBSB NC sole NC plaice P: Minimum fine for full compliance at current effort 8.4 /kg2, % C: Minimum penalty for full compliance100%2, % P: Optimal fine at current effort 8.4 /kg2, % C: Optimal penalty, current effort90%2, %50% P: Optimal effort at that fine level 8.4/kg1, %0% C: Optimal effort, current fine100%1, %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

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28 Increasing social benefits by lowering effort and increasing the fine Enforce ment effort Minimum fine full complian ce ()PBSB Catch sole (kt) Catch plaice (kt)NC sole NC plaice 1,8009, % 1,60026, % 1,40061, %

29 Higher penalties: minimum level of effort for f.c. PenaltyEffortPBSB Landing s sole (kt) Landing s plaice (kt) Biomass sole Biomas s plaice 100%2, %121% 150%1, %121% 200%1, %121%

30 Higher penalties: optimal level of effort Penalt yEffort Enforce ment costsPBSB Landin gs sole (kt) Landin gs plaice (kt) Biomas s sole Bioma ss plaice 100%1, %102% 150%1, %107% 200%1, %102%


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