Disaggregating International Regimes: A New Approach to Evaluation and Comparison

7. Aggregate Effectiveness

Aggregate Effectiveness 7 The basic problem or social purpose of an international regime is what motivated states to create it, whether it is avoidance of nuclear conflict, the furtherance of free trade, or the sustainable management of natural resources. Whatever the issue area, the causal chains that might connect the regime and the achievement of that purpose, to whatever degree, are usually long and complex, and therefore difficult to substantiate. The disaggregate approach makes such substantiation more tractable by considering three parts separately before joining them. The partial problems are to build shared and well-based knowledge among regime members on what measures will best achieve the purpose, to create a set of behavioral rules that jointly reflect the knowledge, and finally to ensure that the rules shape the actions of those who can influence the outcome in question. The preceding chapters have examined each of these cognitional, regulatory , and behavioral aspects of the larger problem, which for resource management regimes is to balance utilization and conservation. As this aggregating chapter shows, the Barents Sea fisheries regime has significantly improved that balance and thereby contributed to the present status of Northeast Arctic cod as the world’s biggest cod stock. Near disasters and failures have also occurred in the period under study, however, often because the successes on one aspect of problem solving were undercut or canceled out by poor performance on another. While this chapter brings together the three aspects of problem solving, the approach to assessing regime effectiveness remains disaggregate. Rather than tackling head-on the difficult and highly complex question of how the balance between utilization and conservation would have been in a counterfactual no-regime situation, I first describe and explain the track record of success and failure for actual cases. Thus, the next section specifies what the balancing of utilization and conservation 238 Chapter 7 means in resource management and shows that we can measure the outcome validly for any given year by combining trends in annual catches and the subsequent strength of the spawning stock. On that basis, I derive the aggregate problem-solving scores for the period under study. In the three preceding chapters, I have specified causal models, including factors that are wholly or partly outside ready regime influence, to account for the variation in problem solving. Here I ask instead how well combinations of cognitional, regulatory, and behavioral problem solving can account for the variation we see in the ability to balance present and future use of the resource. On the behavioral aspect, the levels of problem solving can be measured in two ways: whether both regime members adhere to their quotas or only one of them does. Evaluating those models is again done by the fuzzy set qualitative comparative analysis (QCA) technique, which helps identify any combination of causal properties reliably associated with a certain outcome in a dataset. The hallmark of sound counterfactual analysis is that facts and inferences are compatible with those that apply to otherwise similar actual cases, so those reliable success and failure paths can shed light on what the problem solving would have been if the regime had not existed. I showed in chapter 2 that specifying the counterfactual antecedent—the scores on the modeled factors—is much easier than estimating the consequent outcome. Here we enjoy the additional benefit that the preceding chapters have already substantiated the scores, as well as the most plausible counterfactual estimates, for the three modeled drivers: cognitional, regulatory, and behavioral success. Before we evaluate that causal model and consider the results according to the Oslo-Potsdam effectiveness yardstick, we must define the aggregate problem more clearly. The Problem: Balancing Utilization and Conservation Chapters 4 to 6 of this book have offered in-depth but only partial accounts of how the Barents Sea fisheries regime has helped balance present use and future use. Figure 7.1 combines two trends that help aggregate those accounts. The columns show the development in catches of the main stock managed under this regime, including the best estimates of illegal, unregulated, and unreported catches. The solid line plots the weight of the spawning part of the stock—cod aged around six years or more. Stock replenishment depends on the spawning stock, and the management of living resources revolves around how much of the repro- Aggregate Effectiveness 239 ducing part of a stock should be conserved to ensure future use. That is why the...