1 COBECOS – Lone Grønbæk Kronbak Cost and Benefits of Control Strategies (COBECOS) - the case of Norway lobster trawl fishery in Kattegat and Skagerrak (work in Progress) Lone Grønbæk Kronbak University of Southern Denmark Frank Jensen Institute of Food and Resource Economics

2 COBECOS – Lone Grønbæk Kronbak COBECOS - project WP 5 The objective: to estimate the basic relationships in the theoretical enforcement model for use in the computer model (the COBECOS-software). Estimation of: -Enforcement-probability function -Enforcement-cost function -Benefit functions (private and social)

3 COBECOS – Lone Grønbæk Kronbak COBECOS - project WP The objective: Implementation of the empirical description of the case study in the computer model. Simulations to answer questions about the enforcement and the benefits in the industry Simulation of: -One species (Norway lobster) One type of enforcement (dock-side inspections) -Two species (Norway lobster and cod) Two types of enforcement (dock-side and bordings)

4 COBECOS – Lone Grønbæk Kronbak Norway lobster trawl fishery in Kattegat and Skagerrak nMixed trawl fishery Most important species: Norway lobster Atlantic cod Common sole European plaice. Norway lobster and Atlantic cod have a catch value more than two thirds of the total value of landings. The Danish Directorate of Fisheries risk-ranked these species to require a full enforcement effort.

5 COBECOS – Lone Grønbæk Kronbak Enforcement effort nEnforcement effort challenges n Find a measure between 0 and 1 (required as input to the COBECOS software) n Cross-sectional data (all landings 2005 & 2006) n Normalised effort is a ratio of landings inspected

6 COBECOS – Lone Grønbæk Kronbak Probability of apprehension nA probability tree n Control/No Control n Violation/No Violation n Sanction/No Sanction No Control Control No Violation Violation No Sanction Sanction * No Violation No Control Control Violation

7 COBECOS – Lone Grønbæk Kronbak Actual Enforcement The enforcement fraction or normalised enforcement in the Danish fishing industry The enforcement effort in the Kattegat and Skagerrak is slightly higher (2006) 0.04.

8 COBECOS – Lone Grønbæk Kronbak

9 Benefit functions The private and the social benefit functions differ by; Expected fines Enforcement costs Shadow values of biomass. The shadow value of biomass illustrates society’s value of the stock.

Application of COBECOS software Version 1: (limited to) n1 species; Norway lobster n1 type of enforcement; dock-side inspections Applied functional forms: 10 COBECOS – Lone Grønbæk Kronbak

Applied Parameter values Name of VariableValue TAC (the legal limit of harvest/MLS)8000 kg/vessel Price6.80 EUR/kg Range over which solutions are sought10000 kg Fine (Paid pr. unit of harvest if TAC is exceeded)1 EUR/kg Shadow value of biomass (ShadowVB)1 EUR/kg 11 COBECOS – Lone Grønbæk Kronbak

Cost of enforcement 3 different models for enforcement costs are applied: TC=s*x (Model A) TC=s√x (Model B) TC=sx 2 (Model C) 12 COBECOS – Lone Grønbæk Kronbak LowMediumHigh Model A Model B Model C

Estimations; EP and EC 13 COBECOS – Lone Grønbæk Kronbak

Results of simulation S-parameter squared model Middle=5000 (baseline) Private benefit Euro Social benefit Euro Harvest 8000 Kg Optimized control frequency COBECOS – Lone Grønbæk Kronbak

Results of simulation Changing the TAC 15 COBECOS – Lone Grønbæk Kronbak

Results of simulation Changing the fine 16 COBECOS – Lone Grønbæk Kronbak

Results of simulation Changing the Shadow Value of Biomass 17 COBECOS – Lone Grønbæk Kronbak

Application of COBECOS software Version 2: (very much work in progress) n2 species; Norway lobster & Cod n2 types of enforcement; dock-side & bording inspections Applied functional forms: (as previously) 18 COBECOS – Lone Grønbæk Kronbak

Simulations (input) 19 COBECOS – Lone Grønbæk Kronbak

Simulations (output) 20 COBECOS – Lone Grønbæk Kronbak

Simulation (output) 21 COBECOS – Lone Grønbæk Kronbak

Simulation (output) NameValue Private benefit Euro Social benefit Euro Nephrops harvest Kg (TAC = 5500) Cod harvest Kg (TAC=2000) Optimised effort levels: Dock-side0.314 Optimised effort levels: Bordings COBECOS – Lone Grønbæk Kronbak – Preliminary Results

23 COBECOS – Lone Grønbæk Kronbak General Challenges nThe enforcement effort is targeted (Non-random). nOnly information about apprehended violators. nExtrapolation is necessary to define the enforcement probability function. nApplication of actual, and not perceived, probabilities.

24 COBECOS – Lone Grønbæk Kronbak Case Specific Challenges nDefining what enforcement effort is and rescale it btw 0 and 1 for the COBECOS software. nCross sectional enforcement data (no time series). nExtremely limited enforcement cost information.

Lessons to be learned (- so far) nNothing gets better than the data underlying it! nConfirms the theory: n Higher fine reduces the need for enforcement. n A more binding regulation increases the enforcement need. n The shadow value of biomass only affects the benefits to society 25 COBECOS – Lone Grønbæk Kronbak

Lessons to be learned (- so far) nIn the single species model (version 1): n The enforcement effort is triggered by the size of the regulation relatively to the social optimum of the benefit profile. n The type of enforcement cost function have little influence on the optimal enforcement effort. 26 COBECOS – Lone Grønbæk Kronbak

To be continued… The work with version 1: nSimulations according to WP8 The work with version 2: nSensitivity analysis for n enforcement-cost functions n enforcement probability functions nSimulations according to WP8 27 COBECOS – Lone Grønbæk Kronbak