Brussels the 3rd of December 2008 - COBECOS 1

COMPUTER MODEL

Costs and Benefits of Control StrategiesSIXTH FRAMEWORK PROGRAMME

Policy-Oriented Research

Jenny Nord, Brussels 3rd of December 2008

Brussels the 3rd of December 2008 - COBECOS 2

Outline

1. Description

2. Functionality

3. Simulations using different levels of

• Enforcement effort • Fines• Shadow value of biomass

4. Future work

Brussels the 3rd of December 2008 - COBECOS 3

COBECOS Computer model

Written in the statistical programme R

Based on the theory developed within the COBECOS

Available with manual, tutorial and example data

R and text editors are freely downloadable online

Two versions of the programme:

• Basic version - single exploited stock and single enforcement type.• Extended version - allows for multiple stock and multiple enforcement

types.

Brussels the 3rd of December 2008 - COBECOS 4

Functionality of the programme

Defines:

theoretical relationships between enforcement effort and enforcement costs

and enforcement effort and probability of detecting violations.

Defines functional forms of private and social benefit

Evaluate the private and social benefit at different levels of enforcement effort

Finds the optimal level of enforcement level and evaluates the social benefits at this level

Allows the user to investigate the robustness of the estimated parameters by introducing stochasticity

Brussels the 3rd of December 2008 - COBECOS 5

Simulations

Example fishery: Hake with onboard observers

Is the social benefit from the Hake fishery maximized at the current level onboard inspections?

How will the harvest rate of Hake change if the fines for violation are increased?

Taking costly enforcement into consideration how many onboard inspections should we invest in?

How does a change in the value of leaving the Hake behind to let it grow and spawn influence the social benefit?

Brussels the 3rd of December 2008 - COBECOS 6

Relationship between enforcement effort (e) and costs and enforcement effort (e) and probability of detection Π (e)

Type Enforcmenteffort

Cost

Observer 0.115 1.237

Observer 0.376 1.716

Observer 0.518 1.87

Observer 0.551 1.899

Type Enforcement Effort

Probability

Observer 0.201575 0.517901

Observer 0.3725307 0.811373

Observer 0.448659 0.895643

Observer 0.630469 0.99

Type EP.Model EPpar1 EPpar2 EPpar3 EC.Mod ECpar1 ECpar2 ECpar3 Effort_Min Effort_Max

Observer NA NA NA NA nonlinear NA 0 NA 0 1

Brussels the 3rd of December 2008 - COBECOS 7

Relationship between enforcement effort and C(e) and enforcement effort and Π (e)

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

Enforcement effort

Pro

ba

bili

ty

Observer EP relationship

0.0 0.2 0.4 0.6 0.8 1.00

.00

.51

.01

.52

.0

Enforcement effort

Co

st

Observer EC relationship

Brussels the 3rd of December 2008 - COBECOS 8

Calculating the social benefits

Two options:

1. User defined enforcement effort. The programme displays the associated private and social benefits as well as the harvest rate.

2. Optimisation of social benefit. The program finds the enforcement level that maximizes the social benefit.

Parameter Value

Price 1

Costs 0.5

Biomass 1000

Fine 1

Shadow value 0.2

Enforcement effort 0.1

Brussels the 3rd of December 2008 - COBECOS 9

Calculating social benefits

Brussels the 3rd of December 2008 - COBECOS 10

Optimization of enforcement effort

Brussels the 3rd of December 2008 - COBECOS 11

Increased fine level by 70 % (1-1.7)

Brussels the 3rd of December 2008 - COBECOS 12

Increased shadow value (0.2 – 0.5)

Brussels the 3rd of December 2008 - COBECOS 13

Accuracy of the results

Brussels the 3rd of December 2008 - COBECOS 14

Future development

Tested and used with real data by each case study

Modifications and improvements

Inclusion of multiple enforcement types in the basic model?

Development of a user friendly interface

Brussels the 3rd of December 2008 - COBECOS 15

Thank you for your attention!