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The Efficiency of Direct Public Involvement in Environmental Policymaking: An Experimental Test. Christopher Bruce. Jeremy Clark. Motivation. How should land use conflicts on public lands be settled? - often multiple users, - conflicting over multiple dimensions
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The Efficiency of Direct Public Involvement in Environmental Policymaking: An Experimental Test Christopher Bruce Jeremy Clark
Motivation • How should land use conflicts on public lands be settled? - often multiple users, - conflicting over multiple dimensions of land use policy. - e.g. preservation vs. ranching vs. recreation • One approach: a government agency subjects competing land use policies to cost benefit analysis. Use non-market valuation techniques where necessary
Motivation, Cont’d • However, governments often lack information on the true benefits competing parties would receive from various allocation arrangements. (Posturing) • They can implement policies that they hope will maximise social welfare, but more efficient ones might exist if competing users’ utility functions were known.
Motivation (Cont’d) • An alternative: the government can propose a backstop policy for public land use. It can then invite all interested parties to negotiate over all dimensions of land use “in the shadow” of the fallback policy. • The government pre-commits itself to implement any alternative policy that the parties can agree to. • In contrast to government decision making with public consultation, this mechanism is called “public policy making.”
Examples – North America • U.S. Negotiated Rule Making Act – used by the Environmental Protection Agency • British Columbia’s Land and Resource Management Plans (1997) • Saskatchewan’s Wildlife Diversification Taskforce • Minnesota Wetlands Conservation Plan
There has been little systematic economic analysis of public policymaking. Will it yield allocation plans that are Pareto efficient? Equitable? Socially Optimal? • Is there a framework within which the efficiency of various bargaining rules can be compared? Or the effects of differing backstop policies on the likelihood of efficient outcomes?
We model public policy making using axiomatic models of bargaining outcomes from a cooperative game, using the representation of the Edgeworth Box. • We then design an experiment to test whether public policy bargaining outcomes will satisfy • 1) Pareto superiority, • 2) Pareto efficiency, and • 3) the Nash bargaining solution.
Empirically testing the success of axiomatic models of bargaining is difficult, because often the parties themselves and those observing them do not know the true benefits they receive from any given allocation. • Lab bargaining experiments enable a researcher to induce material payoff functions for participants in a way that makes axiomatic bargaining theories testable. The researcher can then “bridge the gap” between providing full information (as theories assume), and partial information (as in in reality).
Our Experimental Design I • We try to simulate the problem faced by the environmentalist and developer illustrated in the Edgeworth Box. • In each session of the experiment, 10 subjects are seated separately in a room. • Each has his/her coefficient of relative risk aversion measured using the method of Holt and Laury (2002).
Experimental Design II • Half of subjects are assigned one payoff function over two abstract goods, X and Y. The other half of participants are assigned a different payoff function over X and Y. • Participants of both types are each given an initial endowment of units of X and Y. • Between a person of each type, there is a total of 20 units of X, and 20 units of Y.
Experimental Design III • After being given as much time as they want to study the instructions and payoff tables, the 5 subjects of one type are then seated across tables from the 5 subjects of the other type. • Each pair of opposing types is then given a 2 minute round of unstructured and unrestricted communication. Their communication is recorded on micro-cassette. • If a pair can agree to a different allocation than G within the 2 minutes, this will become their allocation for that round. Cash envelopes are then filled for each individual (based on G or the new agreed-upon allocation).
Experimental Design IV • There are 5 such bargaining rounds, each with a different person of the opposing type. • Only one of the five rounds is selected at random to count for each individual. A separate draw is held for each subject when being paid to make the offer of side payments non-credible.
Experimental Design V • We run four different treatments: Treatment I: The Nash bargain is also the unique socially optimal allocation. (G set well.) Full information. N = 40 Treatment II: The Nash bargain is one of many socially optimal allocations along the contract curve. (Doesn’t matter where G is set.) Full information. N = 40
Experimental Design VI Treatment III: The Nash bargain diverges from the unique socially optimal allocation, which is located outside the bargaining lens. (G set poorly.) Full information. N = 40 Treatment IV: same as Treatment III, but with private payoff information that individuals can choose to share or not. N = 40 or 48. In all cases, the Nash Bargain was also the allocation that equalised final incomes. This can be expected to raise the apparent level of support for the Nash Bargain across all four treatments.
Experimental Design VII • Parameters of the two types of payoff function were manipulated to create the changes across Treatments I- III. .
Experimental Design VIII • Held constant across treatments were: 1. the size of the Edgeworth Box, • the endowment allocation • the size of the bargaining lens • the Nash bargain allocation • payoffs at the NB equal at $18.10 • the sum of endowment values at $20
Experimental Design IX • We also tried to maximise the joint payoff dominance of the Nash bargain over the Endowment, ($36.20 vs. $20), and for Treatment III/IV of the Social Optimum over the Nash bargain ($47.37 vs. $36.20) • There is an unfortunate confound that individual endowment values are near equal ($10) in Treatments I and II, but favour the Developer in Treatments III and IV ($13.15 vs. $6.15).
Results I – Outcomes Averaged Across 5 Bargaining Rounds TI TII TIII TIV TIVAug On or in Lens 100 97.0 98.0 99.0 99.2 Tech Efficient 100 99.0 99.0 96.0 94.2 Agreement % 92.0 88.0 90.0 82.0 83.3 -Excluding R1 97.5 92.5 95.0 92.5 93.8
Results I Cont’d TI TII TIII TIV TIVAug Pareto efficient 86.071.0 73.027.0 24.2 -Excluding R1 97.577.5 78.8 31.3 28.1 Nash Bargain 81.070.0 69.022.0 18.3 -Excluding R1 92.577.5 75.027.5 22.9 Summary: efficiency predictions met in T1, not met in T2, T3, T4 absolutely, but only T4 differed sig. from T1. What was the distance and cost of the deviations?
Results II • Physically, individuals converge over the five rounds to the contract curve and NB in particular in Treatments II and III. • But they converge to two cells symmetrically adjacent to the NB point on the contract curve in Treatment IV. The deviation sacrifices some efficiency to preserve earnings advantage for developer. • Private information made the developers less willing to surrender their initial relative advantage over the environmentalists.
Results III: Average Earnings Per Person R1 R2 R3 R4 R5 AVE N I 15.4718.08 18.09 17.68 18.1017.48 40 II 15.5417.24 17.57 17.49 17.29 17.02 40 III 15.5117.17 17.07 18.00 17.88 17.12 40 IV 12.56 15.50 16.88 17.57 18.0516.11 40 IVA 12.6715.68 17.00 17.50 17.9416.21 48
Conclusions I • Even with small stakes and limited time, we find encouraging evidence that parties can reach bargaining outcomes that satisfy technical efficiency and Pareto superiority. • With full information, subjects reached Pareto efficient outcomes after only 1 bargaining round, or else allocations that generated total earnings indistinguishably close to such outcomes. True even when the bargaining lens excluded the socially optimal outcome. • But with partial information and a lens that excluded social optimality, most subjects failed to reach Pareto efficient outcomes, or allocations that yielded indistinguishable earnings.