A Simple Buyback Auction for Fisheries Management. Ted Groves, UCSD John Ledyard, Caltech

Transcription

1 A Simple Buyback Auction for Fisheries Management Ted Groves, UCSD John Ledyard, Caltech

2 Background (Assume: Bjorndal and Munro) Many, if not most, national and international fisheries are subject to overfishing. Open access: Too many boats chasing too few fish. Olympic TAC: Too many boats chasing the right number of fish? It is natural to try to restrict the number of vessels. Resistance from fishers requires incentives. Government financed buyback programs often come at a high cost in the form of government subsidies. If fishery aggregate profit is capacity inelastic, subsidies can exceed the full gain in social surplus realized from eliminating the excess capacity. The aggregate gains from contraction can be large and worth pursuing. The problem is how to split the pie into individual gains that are large for all. July IIFET

3 A standard model of the fishery with asymmetric information July IIFET

4 Buyback Policies A buyback policy determines which boats remain in the fishery and the compensation/payments. A buyback policy determines the steady state stock and the profits of all the fishers, both in and out. July IIFET

5 General Theory A buyback policy is satisfactory if it is Self-financing: No subsidies or taxes to fishery. Efficient: Least cost vessels remain in the fishery. Voluntary: All fishers are better off after the policy. There exist buy-back policies that are S, E, and V under Bayesian equilibrium behavior. Arrow, D Aspremont/Gerard-Varet, Cremer/McLean There are practical issues with these policies. Rely heavily on common knowledge of both information and rationality. Require complicated transfer payment schemes. Require complex communication, equivalent to full profit function. Is there something simpler that is also satisfactory? July IIFET

6 A Simple Buyback Auction Second price auction A desired capacity level, K*, is chosen. Boats each submit a per-unit capacity bid. Bids are accepted from high to low and until K* is reached. (Partial acceptance = full acceptance) The per capacity price, P*, is the highest rejected bid. Winners pay P* times their capacity. With rebate The total of all payments, P*K*, is then redistributed to ALL bidders in proportion to capacity Winners pay to remain in the fishery; losers are paid to leave the fishery. July IIFET

7 This presentation Explores whether this simple buy-back auction can be the basis for a satisfactory buy-back policy Considers three possibilities for follow-up policies Buy-back auction Buy-back auction followed by an individual quota (IQ) Buy-back auction followed by tradable IQs (ITQ). Assumes No policy changes after these Sufficient monitoring and enforcement Fixed capacities and no new entrants Initially we were optimistic that the simple buyback auction was the key to successful buyback programs. But, the rest of this presentation is a cautionary tale. July IIFET

8 Buyback Auction Basics The fisher choose a bid, given the others bids, to maximize: If no externalities, common knowledge of information and rationality, identical priors, and symmetric equilibrium, bid functions are increasing in π/(rk). This gives E,S,V For ease in understanding the impact of each policy, we assume a competitive auction. Each bid affects the price P only if it is the first rejected In a competitive auction each i ignores their impact on P. If no externalities and competitive auction, then It is dominant strategy to bid π/(rk). The buyback auction will be E,S,V w/o common knowledge, identical priors, and symmetric equilibrium. July IIFET

9 Buyback Auction Only July IIFET

10 Pure Buyback Auction Sufficient conditions to get efficiency in a competitive auction Competitive fishery All fishers act as if G is independent of θ and b. Common rational expectations on G Each fisher s believe G is the same G*. G* is the actual distribution that occurs given these beliefs. Single crossing property for profits. The ranking of π/k does not change with s. These are highly unlikely in practice. July IIFET

11 BB followed by Individual Quota To get full efficiency we need tradable quota. With quota based on historical catch, the auction again has externalities. July IIFET

12 BB followed by Individual Tradable Quota TAC known before auction. Trading allowed. After auction, winners are awarded quota, historically based. July IIFET

13 BB followed by Individual Tradable Quota July IIFET

14 BB + ITQ* Allocate quota to all before the auction. Trading allowed. Losers cannot fish, but can sell their initial endowment. All fishers will (potentially) get the money from selling their initial endowment whether they win or lose in the auction. July IIFET

15 BB + ITQ* July IIFET

16 Some open questions Is the competitive auction assumption reasonable? What if there is uncertainty about stocks? With ITQ*, can BB still play a role in price discovery? See C. Anderson and J. Sutinen initial lease only periods help price discovery We address these with experiments. July IIFET

17 Experiment: Parameters 20 subjects, 4 win Values randomly drawn Private values: v in [50,550] then V in [v-50,v+50]. Signal = V, Value = V This is all common knowledge. We ran 5 sealed bid, 10 clock, 5 sealed bid July IIFET

18 competitive auction assumption looks good. Bidding Behaviors Overbid Truthful Underbid Sealed-Bid 1 Clock 1 Clock 2 Sealed-Bid 2 July IIFET

19 Efficiency Results Efficiency = (subject payoffs random)/(max possible random) Efficiencies From left to right: Sealed bid Clock Clock Sealed bid Private Both (ε=150) Both (ε=50) -0.2 Sealed-Bid 1 Clock 1 Clock 2 Sealed-Bid 2 July IIFET

20 What if stocks are uncertain? Same auctions, different values randomly drawn Case 1: tight information Value = V + c, Signals are V and C v in [50, 550], V in [v-50,v+50], (same as before) c in [750,2550], C in [c-50,c+50] Case 2: loose information Value = V + c, Signals are V and C v in [50, 550], V in [v-50,v+50], (same as before) c in [750,2550], C in [c-150,c+150] This is all common knowledge July IIFET

21 Efficiency Results Efficiency = (subject payoffs random)/(max possible random) 1 Efficiencies Private Both (ε=150) Both (ε=50) -0.2 Sealed-Bid 1 Clock 1 Clock 2 Sealed-Bid 2 July IIFET

22 Summary There are ESV buyback policies generally too complicated in practice. With independent values and no externalities, it is definitely possible to design self-financing, efficient, voluntary buyback auctions. Both sealed bid and clock designs perform about the same. Neither BB, nor BB+IQ, nor BB+ITQ satisfy both independent values and no externalities without more assumptions on beliefs and fundamentals. A buyback followed by ITQ is E, V, S If quota awarded before the auction, if competitive auction, and if rational quota price expectations. But the auction is then unnecessary for E, S, and V. Large uncertainty about stocks lowers the efficiency of the buyback auction under any follow-up. Need better design - more information to bidders # left bidding in clock auction, etc. Make public all information about the stocks expected after contraction. Yet to do BB as an aid in quota price discovery BB + ITQ* vs. ITQ only vs. initial lease only ITQ. July IIFET

23 Questions? July IIFET