Coalitions in Fisheries

1. Coalitions in Fisheries

2. Why game theory? • Whenever there is more than one interest group (country, fishermen etc.) strategic behaviour / competition may prevent optimal harvest control • International fisheries have very limited possibilities to prevent strategic behaviour / free-riding

3. Alternative game models • Non-cooperative games • only individual benefits matter • Cooperative games • sharing of benefits • Coalitional games • how coalitions form

4. Cooperative games • Assume Sweden, Norway and Finland can form coalitions when harvesting fish stocks • Possible coalitions {SWE}, {FIN}, {NOR}, {SWE, NOR}, {SWE, FIN}, {NOR, FIN}, {SWE, NOR, FIN}

5. Cooperative Solutions • How should they share cooperative benefits? • The solutions search an allocation of cooperative benefits given e.g. individual & group rationality

6. NOR SWE FIN {NOR, FIN} SWE {NOR, SWE, FIN} Coalitional games: Searching for equilibrium cooperation structures Non-Cooperation Partial Cooperation Full Cooperation

7. How to make cooperation more attractive? • Threat (trigger) strategies • Side payments • Safe Minimum Bioeconomic Levels of fish stocks (Reference points) • Give fishermen more responsibility in harvest control

8. Motivation • Recent papers Ruseski (JEEM 1998) and Quinn & Ruseski (NRM 2001) using the Schaefer-Gordon game model do not allow for coalition formation • The problem of new entrants in Regional Fisheries Management Organisations (RFMOs) ” Stateshaving a real interest in the fisheriesconcerned may become members of suchorganization or participants in such arrangement.” --> new entrants make cooperation more difficult

9. The model • Gordon-Schaefer production with logistic growth, stock in steady state • Countries choose their coalition in the first stage and fishing effort in the second stage • Symmetric versus asymmetric countries with respect to unit costs of effort • Stability of full cooperation when every country prefers cooperation to free riding

10. Logistic growth Production Steady state

11. Symmetric countries max Non-Cooperation Partial Cooperation  Cooperation stable if n < 3

12. € ph ce e

13. Asymmetric countries Assume Non-Cooperation Partial Cooperation  Cooperation may be stable for any n

14. Effect of fishing costs on stability of full cooperation: three asymmetric countries Stability condition Costs of countries k and j affect stability via free rider profits

15. Figure 1: Effect of ck on total free-rider profits

16. Figure 2: Effect of cj on total free-rider profits

17. Example: New entrants and stability • Introduce one new entrant into a fishery with three original members that are symmetric • Initially no cooperation, but new entrant may create incentives for cooperation • Every country may be economically and biologically better off

18. Figure 4: Effect of the new entrant on stability of full cooperation

19. Conclusions • Cost structure of the fishery important in determining the stability of cooperation • Limited number of new entrants to RFMOs may improve stability of cooperation if the new entrants have low enough costs (but not too low) The sustainable number of new entrants :

20. MANAGEMENT OF REGIONAL FISHERIES ORGANISATIONS: AN APPLICATION OF THE SHAPLEY VALUE

21. The Shapley value • Lloyd Shapley 1953 • Possible orders of coalition formation are equally likely • Countries have already agreed to cooperate • Interpretations: • Average outcome of the negotiations • Marginal contributions of countries to each coalition • Sum of dividends that each coalition pays to its members

22. Objective function of the players

23. Assumptions of the model • The countries outside coalitions play non-cooperatively against the ones inside the coalition • C-game perspective: The coalitions that the countries can form with one another define their contributions in the cooperative agreement and consequently their bargaining strengths • C-function normalised so that the values of the coalitions are between 0 and 1

24. Characteristic function v*(i) = 0

25. Extending the c-game: Restricted Coalitions and n players • Simple restriction leads to changes in bargaining strengths of fishing nations • Setting restricted coalition’s value equal to zero • Ability to calculate Shapley imputations to a large number of players

26. Restricted coalition formation • Only same type of countries want to join together, feasible subcoalitions are {C1,C2} and {D1,D2}, ie we have 4 players • In the case where the DWFNs have high unit costs of fishing they can improve their negotiation position by refusing to form a coalition with the coastal states • - > 0

27. Cooperationstructure C1 C2 D1 D2

28. Case I: DWFNs gain individually from coalition restrictions • Costs of the DWFNs are higher than for the coastal states • However, when the value of the coastal state coalition is larger than 3/5 then the core is empty for the restricted case • When the cost difference between DWFNs is large (when the more efficient DWFN has a stronger incentive to join the coastal state coalition) then the result does not apply

29. Case II: DWFNs gain together from coalition restrictions • We compare the sum of restricted and unrestricted Shapley values of the DWFNs • cC1 < cD1 £ cC2 < cD2 • If cC2 = cD2 then DWFNs are indifferent between coalition restriction and unrestriction

30. Case III: DWFNs are worse off with coalition restrictions • cC1 < cD1 £ cD2 < cC2 • Note that in principle roles can be changed to have same results for coastal state • In cases 2 and 3, for country D2 coalition restrictions may be individually beneficial • Coalition restriction means here that all countries will negotiate with one another but if a coalition is restricted then the negotiations are not successful

31. Increasing number of players • Provide Shapley values for n player game • Two most efficient players act as veto players, their presence is necessary for a coalition to have a positive bargaining strength • limitation: it may not be possible to have a large number of countries in the Regional Fisheries Management Organisation

32. Parallel fisheries agreements

33. Parallel fisheries agreements • Typically modelling n countries exploiting one common fish stock x • How many countries cooperate, compare to non-cooperative and full cooperative outcomes • However, there are almost always more species • There can therefore be two parallel fisheries agreeements, one for x and one for y

34. Class I: One stock, many agreements • Think of 4 countries exploiting x • Two agreements: Countries 1,2 sign a bilateral agreement and also countries 3,4 sign an agreement • Stability • Allocation

35. Example I • Stage 1: Coalition formation • Stage 2: max ph – cE • Two parallel agreements exist if it is not optimal to break the bilateral agreements (1,2) and (3,4) • For example country 3 compares the payoff v(1,2) v(3,4) to v(1,2,3) v(4) and v(1,2) v(3) v(4) • Payoff to individual country also depends on allocation (sharing of cooperative benefits)

36. Class II: Multiple stocks • issue linkage, interconnected games • Multi-species fisheries • The set of countries exploiting each stock may be same or different • Consider three countries exploiting two stocks: Countries 1,2 sign a bilateral agreement on x but for y all countries sign an agreement • x and y fisheries may be biologically and economically dependent

37. Example II • Consider a three-player case where full cooperation is stable in x fishery. This means that the gains of full cooperation exceeds the sum of gains from free-riding: • C =17 & F = 14  total benefits 17 • Assume further that full cooperation is not stable for y fishery: • C = 17 F = 18  total benefits 13 • In this case joint management of the stocks would be beneficial since it would make full cooperation stable in both fisheries • C = 34 & F = 32  total benefits 34 (compared to 30)

38. Case III: One stock, countries may be part of several agreements • Countries may e.g. sign bilateral agreements on various issues concerning same stock • Example: Countries 1,2 agree on technology, countries 2,3 on biology, countries 1,3 on enforcement, all countries on research • Implications for Regional Fisheries Management Organisations: What should we agree on? Who should agree?  Optimal structures of RFMOs, e.g. how many RFMOs should there be?

39. Discussion • Realism in the game-theoretic models, e.g. national and international level negotiations • Effect of species interactions • Case III needs a new more complicated model

40. A Coalition Game of the Baltic Sea Cod Fishery Lone Grønbæk Kronbak Department of Environmental and Business Economics University of Southern Denmark Marko LindroosDepartment of Economics and Management University of Helsinki

41. Literature • Kaitala & Munro (1993): Need for coalition modelling in high seas fisheries management • Kaitala & Munro (1995): First analysis on coalitions and high seas fisheries • Followed by Kaitala & Lindroos (1998), Arnason et al. (2000), Duarte et al. (2000), Gallastegui et al. (2002), Kennedy (2003), Pham Do et al. (2003), Pintassilgo (2003)

42. Motivation • Previous empirical studies applying c-games: - Lindroos & Kaitala (2000) - Arnason, Magnusson & Agnarsson (2000) - Costa Duarte, Brasão & Pintassilgo (2000) - Brasão, Costa Duarte & Cunha-e-Sá (2000) determine sharing rules, but these sharing rules does not satisfy all players. • Kronbak & Lindroos (2003) shows cooperation in the Baltic Sea cod fishery should be encouraged.

43. Our Goal Determine a stable sharing rule for the cooperative Baltic Sea cod fishery

44. The Baltic Sea • Remote Area with no international waters • Cod most valuable fishery in the Baltic Sea • All Parties exploiting cod are members on IBSFC • IBSFC sets TACs for cod • TAC measures are often exceeded

45. Bio-Economic Model • Discrete time • Single species • Age-structured model (6 cohorts) • Beverton-Holt stock-recruitment relationship (ICES 2000) • Simulation length: 50 years (1997-2046)

46. Bio-Economic Model (cont’d) • 3 players/groups of countries • Players commit to fishing mortality only in the beginning of the game • Players move simultaneously • Cost function squared in harvest and inverse in stock; players differ in cost parameter c1>c2>c3 • Prices are assumed identical and constant

47. Optimal Strategy and Benefits

48. Shapley Value The potential to change the worth of the coalition by joining or leaving it The expected marginal contribution Nucleolus Minimize the dissatisfaction of the coalition Finding the lexicographic centre of the core Sharing Rules

49. Sharing RulesPercentage of cooperative benefits received

50. Satisfactory nucleolus • A cooperative sharing imputation which is stable to free rider values