Institutional Analysis and Development (IAD) Framework

Description

Framework developed by Elinor Ostrom and colleagues at the Workshop in Political Theory and Policy Analysis (Indiana University) for analyzing how institutional rules shape the behavior of actors in situations involving shared resources. The IAD framework centers on the “action arena” — the space where participants interact under a set of rules — and systematically unpacks the rules-in-use (as opposed to rules-on-paper) that govern positions, boundaries, authority, aggregation, information, payoffs, and scope. Ostrom received the 2009 Nobel Prize in Economics partly for demonstrating that commons governance need not follow the “tragedy of the commons” narrative, and the IAD framework was her primary analytical tool.

When to Use

• When analyzing governance of shared or common-pool resources in the space domain: orbital slots, radio frequency spectrum, cislunar space, lunar surface resources.
• When the core question is about institutional design: what rules exist, how they shape behavior, and whether alternative rule configurations could produce better outcomes.
• When multiple actors with different authorities and interests interact within a governance structure (e.g., ITU frequency coordination, UN COPUOS consensus-building).
• When examining why a governance regime succeeds or fails at managing collective action problems.
• Less useful for purely bilateral regulatory analysis; most valuable for multilateral or polycentric governance settings.

How to Apply

1. Define the action arena. Identify the specific decision-making or interaction context: who participates, what actions are available, what outcomes are possible, and what information participants have. For space: the action arena might be the ITU coordination process for satellite orbital slots, or COPUOS negotiations on space resource utilization.
2. Characterize the biophysical/material conditions. Describe the physical or technical characteristics of the resource or domain: subtractability, excludability, spatial extent, temporal dynamics. For space: orbital carrying capacity, debris collision probability curves, spectrum interference characteristics.
3. Map the community attributes. Identify the participants, their heterogeneity, shared norms, trust levels, discount rates, and prior experience with cooperation. For space: spacefaring vs. emerging space nations, commercial vs. governmental actors, legacy operators vs. new entrants.
4. Identify the rules-in-use. Systematically analyze seven types of institutional rules:
   • Position rules: What roles exist? (e.g., launching state, registering state, operator)
   • Boundary rules: Who can participate and how? (e.g., ITU membership requirements)
   • Authority rules: What actions can each position take? (e.g., licensing authority scope)
   • Aggregation rules: How are collective decisions made? (e.g., COPUOS consensus rule)
   • Information rules: What must be disclosed, to whom? (e.g., registration obligations, SSA data sharing)
   • Payoff rules: What rewards/sanctions attach to actions? (e.g., liability regime, insurance requirements)
   • Scope rules: What outcomes are permitted or forbidden? (e.g., non-appropriation principle, debris mitigation guidelines)
5. Analyze patterns of interaction. Given the rules, material conditions, and community attributes, what behavior patterns emerge? Cooperation, free-riding, strategic non-compliance, norm entrepreneurship?
6. Evaluate outcomes. Assess outcomes against criteria: efficiency, equity, sustainability, adaptability, accountability. Compare actual outcomes to what alternative institutional arrangements might produce.
7. Identify institutional gaps or mismatches. Where do rules fail to address the problem? Where are rules-in-use divergent from rules-on-paper? What rule changes could improve outcomes?

Key Dimensions

• Action arena: Participants, positions, actions available, information, potential outcomes, control over outcomes.
• Biophysical conditions: Resource characteristics (subtractability, excludability), technical constraints, physical environment.
• Community attributes: Actor heterogeneity, norms, trust, shared understanding, discount rates.
• Rules-in-use: The seven rule types (position, boundary, authority, aggregation, information, payoff, scope) as actually practiced.
• Patterns of interaction: Cooperation, conflict, free-riding, compliance, negotiation behaviors.
• Evaluative criteria: Efficiency, equity, sustainability, accountability, adaptability of outcomes.

Expected Output

• An action arena diagram or structured description identifying participants, their positions, and available actions.
• A rules-in-use matrix covering all seven rule types, noting both formal rules and de facto practice.
• Analysis of how biophysical conditions and community attributes interact with rules to produce observed behavior patterns.
• Outcome evaluation against at least 3 criteria (efficiency, equity, sustainability).
• Identification of institutional gaps, mismatches, or design flaws with suggested rule modifications.

Limitations

• High analytical overhead: the IAD framework is comprehensive but time-intensive. Overkill for simple bilateral regulatory questions.
• Requires deep knowledge of actual institutional practice, not just formal legal texts — rules-in-use are often hard to observe from outside.
• Better at diagnosing institutional problems than prescribing solutions; design recommendations remain context-dependent.
• Primarily developed for terrestrial commons (fisheries, forests, irrigation); application to space commons requires careful adaptation of concepts like subtractability and excludability.
• Does not inherently address power asymmetries; dominant actors may shape rules regardless of institutional design logic. Complement with power analysis where needed.