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Fisheries Enforcement: Basic Theory

Fisheries Enforcement: Basic Theory. Ragnar Arnason. Paper presented at COBECOS Kick-off meeting. Salerno February, 22-3, 2007. Introduction. Fisheries management needs enforcement Without it there is no fisheries management Enforcement is expensive Enforcement is complicated

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Fisheries Enforcement: Basic Theory

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  1. Fisheries Enforcement:Basic Theory Ragnar Arnason Paper presented at COBECOS Kick-off meeting Salerno February, 22-3, 2007

  2. Introduction • Fisheries management needs enforcement • Without it there is no fisheries management • Enforcement is expensive • Enforcement is complicated • Optimal fisheries policy needs to take enforcement into account • Enforcement theory is fundamentally the theory of crime (Becker 1968)

  3. Model Social benefits of fishing: B(q,x)-·q Private benefits of fishing: B(q,x) Shadow value of biomass Enforcement sector: Enforcement effort: e Cost of enforcement: C(e) Penalty: f Announced target: q* Exogenous

  4. (e) 1 e Model (cont.) Probability of penalty function (if violate): (e)

  5. (q;e,f,q*) (e)f q* q Model (cont.) Private costs of violations: (q;e,f,q*)=(e)f(q-q*), if qq* (q;e,f,q*) = 0 , ifq<q*

  6. Model (cont.) Private benefits under enforcement B(q,x)-(e)f(q-q*), q q* B(q,x), otherwise Social benefits with costly enforcement: B(q,x)-q-C(e)

  7. Necessary condition: Bq(q,x)-(e)f=0  Enforcement response function: q=Q(e,f,x) Private behaviour Maximization problem: Max B(q,x)-(e)f(q-q*)

  8. q Free access q q* [higher f] [lower f] e Enforcement response function

  9. B(q,x)-q-C(e). subject to:q=Q(e,f,x), e0, f fixed. Necessary conditions , if q=Q(e,f,x)>q* Q(e*,f,x)=q*, otherwise Optimal enforcement Social optimality problem

  10. $ e° e* e Social optimality: Illustration

  11. The discontinuity problem • Analytically merely cumbersome • Practically troublesome • Stop getting responses to enforcement alterations • To avoid the problem • Set q* low enough (lower than the real target) • Aim for the appropriate level of noncompliance • A well chosen q* is not supposed to be reached ( Non-compliance is a good sign!)

  12. Some observations • Costless enforcement  traditional case (Bq=) • Costly enforcement  • The real target harvest has to be modified (....upwards, Bq<) • Optimal enforcement becomes crucial • The control variable is enforcement  not “harvest”! • The announced target harvest is for show only • Non-compliance is the desired outcome • Ignoring enforcement costs can be very costly • Wrong target “harvest” • Inefficient enforcement

  13. Private fishing benefits: Cost of enforcement: Probability of penalty: An example Shadow value of biomass:  (assumed known) (can calculate on the basis of biomeconomic model)

  14. Enforcement response function: q, harvest f=0.5p f=p f=2p e, enforcement Example (cont.)

  15. Example (cont.) Socially optimal harvest: q, harvest q* (no enforcement cost) f, penalty

  16. To apply theory:Empirical requirements • The private benefit function of fishing, B(q,x) • The shadow value of biomass,  • The enforcement cost function, C(e) • The penalty function,(e) • The penalty structure, f Note: Items 1 & 2 come out of a bio-economic model of the fishery. Items 3, 4 and 5 are special enforcement data

  17. To apply theory (cont) • In real empirical cases, the functions will normally be more complicated • Include more variables (if only for statistical purposes) • Vary across fisheries and management systems • However, they must contain the basic elements of the theory

  18. Extensions • Different enforcement targets (controls) • How does that affect theory • A vector of controls • Disaggregation (fishing units, gear, areas) • Alternative fishing opportunities • Optimal mix of enforcement tools • Vector of tools • Cost of each • Efficiency of each • Optimal mix (calculation of gains) • The structure (not only severity) of penalties

  19. END

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