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Experiments in the Lobbying Activity of Fishers with Heterogeneous Preferences Matthew Freeman Louisiana State University/LA Sea Grant Chris Anderson University of Rhode Island
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Why lobbying activity? In ’09 NMFS report, 16% of 251 stocks with a “known” overfishing status are subject to overfishing, and 23% of 199 stocks with a “known” overfished status are overfished. To further improve the status of fish stocks, existing regulations need to be evaluated and improved. However, fishery management can be impacted by regulatory capture.
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Research Question Motivating Question – Does lobbying activity influence plans of fishery (and other CPR) regulation, and if so, to what extent? Use experimental economics & game theory Test market mechanisms in controlled environment Guide creation of policy & expose flaws in management design
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Experimental Design The experiment is modeled upon a common pool fishery harvested by 10 firms, which are heterogeneous in externality cost. 8 subjects comprise group A, which faces a higher externality cost (1.45), than the 2 subjects comprising group B, which faces a lower externality cost (1.4).
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Experimental Parameters
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Treatment Descriptions 1 st treatment (15 rounds): – each subject chooses a level of resource extraction. – his profit is a function of both his individual choice & the summed choices of the other subjects’.
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Treatment Descriptions 2 nd treatment (6 rounds, 6 distinct caps): – proposed cap (limits level of resource extraction). – each subject may lobby to increase or to decrease the proposed cap, or take no action. Lobbying expenditures deducted from profit at end of round. – final cap based on the proposed cap & the summation of lobbying to increase & decrease the cap. – each subject may then choose a level of extraction (bound by final cap).
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Question 1 Do individuals allocate effort in the unregulated CPR consistent with the Nash Equilibrium predictions? – Censored Tobit model Dependent variable: effort levels 3 independent variables: round, dummy variable for low-cost group (Group B), interactive term for effect of round from low-cost group – Group A converges quickly on NE; Group B doesn’t converge quickly but still shows upward trend
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Unregulated Effort Levels
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Censored Tobit Model Indicates Group B has higher initial effort level Indicates Group B retains higher effort level
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Question 2 Do individuals lobby to change a proposed regulation on effort in a manner consistent with their group type and the Nash Equilibrium predictions of non-cooperative behavior? – Use t-test to see if observed levels are equal to non-cooperative & cooperative model predictions – Group B performs more consistently with N-C model than does Group A. Free-riding is prevalent within Group A.
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Lobbying Expenditures
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Bounds for Profitable Cooperative & Non-cooperative Lobbying Cooperative Non-cooperative ABAB Upper bound7.469.8912.2112.72 Lower bound6.094.171.271.32 Social optimum6.787.026.787.02
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t-test of Observed Lobbying Expenditures Deviation Total from both groups > Group A’s coop model prediction Total from both groups falls between Group A’s coop & N-C model predictions
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Lobbying Expenditures
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Question 3 Do individuals allocate effort in a regulated CPR, post-lobbying, consistent with the Nash Equilibrium predictions? – Use t-tests of the observed effort levels, with the Nash equilibrium predictions as a benchmark – At final caps 2-5, can’t reject that observed effort levels are equal to predicted levels – At finals cap > 5, some deviation occurs
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Regulated Effort Levels Due to lobbying efforts toward the preferred regulation, fewer final caps occurred at levels higher than thirteen.
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Comments on Regulated Levels While perhaps not meaningful per individual, small deviations could be economically meaningful when considering the cumulative effort for a large industry. Future research -hold several rounds after a final regulation is imposed to see if an upward trend in effort level occurs (as w/unregulated treatment).
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Concluding Remarks Homogeneity within groups denotes similar interests & might encourage cooperative actions (Poteete and Ostrom, 2004). Our experiments show that, due to the relation between group size & cost of lobbying, one group may have no incentive to lobby, if the optimal interests are close to one another. – This concept adds another dimension to the role of group size, beyond the effect it has on determining the impact of one individual’s lobbying contributions (Poteete and Ostrom, 2004; Olson, 1965).
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Concluding Remarks These experimental results support an idea of strong collective action against regulation that is below the optimal level and of weaker collective action against regulation that is above the optimal level. Despite being unable to reach the predicted levels of cooperative lobbying, the individuals in our experiments did show some restraint in resource appropriation after the final cap was imposed.
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Questions? We gratefully acknowledge the support for this research provided by a NOAA/Sea Grant Joint Fellowship in Marine Resource Economics and by RI Sea Grant.
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