Institutional economic/SES framework

By Maja Schlüter

How does the perspective approach causation? 

Elinor Ostrom developed the SES framework as an extension of her Institutional Analysis and Development (IAD) framework (Figure 1). The core unit of analysis of the IAD is the action situation, which is a social interaction context in which actors in positions interact to produce outcomes, such as a rule to manage a resource. The action situation is modelled on the game theoretic model of a game but acknowledges that real world games are more complex than what can be analysed using analytical tools of game theory. The IAD and institutional analysis as carried out by the Ostrom school focuses on analysing institutions, understood as the rules and patterns of behaviour in a society that shape human interaction, in common pool resource (CPR) contexts and understanding the conditions under which communities can self-organize to design successful institutions. Several key institutional arrangements in common pool resource management include monitoring and sanctioning and conflict resolution mechanisms.

The SES framework extends the IAD by suggesting specific external variables that across many cases have proven to be relevant for explaining successful self-organization (i.e. the development of rules for resource management by the community itself) in local communities. It expands on the “external variables” that influence action situations in the IAD by suggesting variables for the first level tiers resource system and resource unit (biophysical conditions) and users (attributes of community). The variables are organized in a multi-tier system, where each variable at one tier can be specified more at a lower tier. 

Figure 1: The IAD (left) and the model of the action situation (Ostrom 1990).

Causation in the SES framework is mainly addressed through the use of cooperation or CPR theories that propose causal relationships between variables and outcomes. The foundation of causal analysis is thus first and foremost the existence of a CPR theory proposing how certain factors are causally related to outcomes, e.g. how the number of resource users ( a variable of the users) affects the ability of a community to self-organize. In this example theory predicts that the larger the number of users the more difficult it is to achieve the necessary collective action. A central assumption/insight from Ostrom’s work is that groups of resource users can under some conditions develop the rules necessary to maintain collective action and sustainable resource use. 

Ostrom highlights the need to move beyond panaceas and acknowledge that “diagnosing the problems and potentialities of linked SESs requires serious study of complex, multivariable, nonlinear, cross-scale, and changing systems”. Ostrom and Ostrom scholars advocate a diagnostic approach to overcome the challenges of establishing causal relationships in specific contexts and beyond. A diagnostic approach starts with asking which of the attributes of a particular SES are likely to have a major impact on particular patterns of interactions and outcomes. The answer to each question further unpacks the complexity of a system, asking more specific questions and allowing an analyst to explore patterns of interactions that produce outcomes (Cox 2011).

What methods are mainly used?

One of the purposes of the SES framework is to guide data collection in case studies, both in terms of alerting users to the many different factors that may affect successful collective action and to enhance comparability between cases by providing a shared vocabulary. Data are either collected empirically in a specific case or extracted from the literature through content analysis of case studies. The data can be analysed qualitatively (e.g. by evaluating each relevant variable and assessing how it may have contributed to the observed outcome, or by comparing values across a few cases (e.g. Basurto et al. 2013), combining qualitative and quantitative measures of indicators (e.g. Leslie et al. 2015), or through meta-analysis (e.g. Gutiérrez et al. 2011). 

Some scholars have combined theory testing with methods such as within case comparison and process tracing as a method for causal inference to establish which CPR variables can help understand cooperation (e.g. Villamajor-Tomas et al. 2014).  


Basurto, X., Gelcich, S., Ostrom, E., 2013. The social–ecological system framework as a knowledge classificatory system for benthic small-scale fisheries. Global Environmental Change 23, 1366–1380.

Cox, M., 2011. Advancing the diagnostic analysis of environmental problems. International Journal of the Commons 5.

Leslie, H.M., Basurto, X., Nenadovic, M., Sievanen, L., Cavanaugh, K.C., Cota-Nieto, J.J., Erisman, B.E., Finkbeiner, E., Hinojosa-Arango, G., Moreno-Báez, M., others, 2015. Operationalizing the social-ecological systems framework to assess sustainability. Proceedings of the National Academy of Sciences 112, 5979–5984.

Gutiérrez, N.L., Hilborn, R., Defeo, O., 2011. Leadership, social capital and incentives promote successful fisheries. Nature 470, 386–389.

Villamayor-Tomas, S., Fleischman, F. D., Perez Ibarra, I., Thiel, A., & van Laerhoven, F. (2014). From Sandoz to Salmon: Conceptualizing resource and institutional dynamics in the Rhine watershed through the SES framework. International Journal of the Commons, 8(2), 361–395. DOI: