1. Income Targeting and the Evolution of a Fishery John Lynham and David Siegel F-cubed meeting, Jan. 24 th, 2007

2. What is Income Targeting? Camerer et al., 1997 Chou, 2000 Fehr and Goette, 2005 Farber, 2005 Koszegi and Rabin, 2002

3. Income Targeting in Fisheries Anthropological and anecdotal evidence suggests that commercial fishermen exhibit income-targeting behavior: “Their concern is going out, obtaining a certain amount of fish in a reasonable amount of time, and returning to port.” (Orbach, 1977, p. 197) The Fisherman and the Industrialist story

4. The Evolution of a Fishery Jackson et al., 2001 Watson and Pauly, 2001 Pauly et al., 2002 Worm et al., 2006

5. “Boom” and “Bust” trend

8. Economic Agents and the Evolution of a Fishery

9. Northern California Red Urchin Fishery

10. (1)(2)(3) Dependent Variable:Hours WorkedPounds HarvestedHours Worked Independent Variable:Price Biomass 88-*** 89+***+ 90--***+ 91-*-***+*** 92-*-***+** 93-*** 94+***-***- 95+-***- 96--***- 97--*** 98+***-**- 99--***-

11. Northern California Red Urchin Fishery (1)(2)(3) Dependent Variable: HoursHarvestHours Independent Variable: Price Biomass 88-*** 89+***+ 90--***+ 91-*-***+*** 92-*-***+** 93-*** 94+***-***- 95+-***- 96--***- 97--*** 98+***-**- 99--***-

12. A Model of Fishery Evolution The model allows for two types of economic agents: income maximizers and income targeters Daily fish abundance is an i.i.d. uniformly distributed random variable (within a season) Each day within a season the agents in the fishery choose how many hours to work At the end of each season, the agents decide to either enter or exit the fishery The rest of the model is identical to standard fisheries economics models

13. Model Details Biomass: Entry and Exit

14. Model Details How many hours do fishermen decide to work? In general, income-maximizers will work all day long Income-targeters decide how long to work based on observed abundance. If it’s a good day (high abundance) they work until they hit their daily target. If it’s a bad day (low abundance) they try to get as close to their daily target as possible.

15. Model Details Income-Maximizer [zero marginal cost]: Income-Targeter

16. Model Details

17. Steady State 3 equations, 3 unknowns Revenues=Costs Growth=Harvest Expected Total Hours:.

18. Model Simulation Parameters Years=20 Days=300 Carrying Capacity=1000 Intrinsic Growth Rate=5% Targeters' catchability= 3.6312e-007 Maximizers' catchability: 4.8000e-007 10 work hours in a day Price=1 Speed of entry of Targeters=20 Speed of entry of Maximizers=40 Alternative Profit Opportunity for Targeters=0.08 Alternative Profit Opportunity for Maximizers=0.5 Biomass Target=50 Marginal cost of Harvest=0 Predicted Steady State Values: Total Number of Fishermen=100 Biomass=800

19. Model Simulation

20. Next Step: Policy Experiment Once the model reaches steady-state, we prevent further entry and rebuild the stock How does this improve the livelihoods of the incumbent fishermen? Is it sufficient incentive to motivate support for government regulation of their fishery?

21. Policy Experiment – An Extreme Example Suppose that costs are zero and the daily distribution of biomass takes the following form: This implies that the incumbent fishermen can not be made better off by closing entry to the fishery and rebuilding biomass

22. Summary First empirical evidence of Income-Targeting behavior in a fishery Income-Targeting behavior tends to be most prevalent during the “Bust” period of the fishery We present a simple extension of a standard fisheries economics model that matches the evolution of economic types observed The model and subsequent policy experiment provides one possible explanation for why incumbent fishermen rarely support fisheries management proposals