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Income Targeting and the Evolution of a Fishery
John Lynham and David Siegel
F-cubed meeting, Jan. 24th, 2007
What is Income Targeting?
• Camerer et al., 1997
• Chou, 2000
• Fehr and Goette, 2005
• Farber, 2005
• Koszegi and Rabin, 2002
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
The Evolution of a Fishery
• Jackson et al., 2001
• Watson and Pauly, 2001
• Pauly et al., 2002
• Worm et al., 2006
“Boom” and “Bust” trend
“Boom” and “Bust” trend
“Boom” and “Bust” trend
Economic Agents and the Evolution of a Fishery
Northern California Red Urchin Fishery
Northern California Red Urchin Fishery(1) (2) (3)
Dependent Variable: Hours Worked Pounds Harvested Hours Worked
Independent Variable: Price Price Biomass
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Northern California Red Urchin Fishery
(1) (2) (3)
Dependent Variable:
Hours Harvest Hours
Independent Variable:
Price Price Biomass
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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
Model Details
• Biomass:
• Entry and Exit
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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.
Model Details
• Income-Maximizer [zero marginal cost]:
• Income-Targeter
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Model Details
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Steady State• 3 equations, 3 unknowns• Revenues=Costs
• Growth=Harvest
• Expected Total Hours:
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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
Model Simulation
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?
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
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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