ecological sciences approaches to ‘complex social-ecological systems’
The result is a framework that resembles CPR studies in key respects. Ostrom’s 2009 article in Science provides a visual emphasis on the interactions between ‘first-level’ concepts including users, their governance system, resourcesystem (such as a protected park) and resourceunits (such as its trees):
It also raises similar questions, such as ‘When will the users of a resource invest time and energy to avert “a tragedy of the commons”’?
It answers them with reference to ‘second level’ concepts describing factors that encourage users to (a) value long term sustainability and (b) self-organize to secure this outcome. This table summarizes many of them:
Note that Ostrom describes their effect as indicative because, ‘As in most complex systems, the variables interact in a nonlinear fashion …Simple blueprint policies do not work’.
As a result, we have a super-complicated framework to help us understand an even more super-complicated world. For some, the SES framework serves to ‘diagnose’ the sustainability of social-ecological systems and explore the prospect of more effective self-organisation to manage resources. However, as with the IAD, effective use of the framework itself requires a fair amount of immersion in the language of analysis.
The IAD provides a language, and way of thinking, about the ways in which different institutions foster collective action. The language is so complicated that I have cheated by summarising key terms in this box (and describing polycentric governance in a different post) to stay within the 1000 words limit:
Governing the Commons
For me, the best way to understand the IAD is through the lens of Governing the Commons (and the research agenda it inspired), which explains how to rethink ‘tragedies of the commons’ and encourage better management of common pool resources (CPRs).
Ostrom rejects the uncritical use of rational choice games to conclude – too quickly – that disastrous collective action problems are inevitable unless we ‘privatize’ commons or secure major government intervention (which is tricky anyway when global problems require international cooperation). The tragedy of the commons presents a too-bleak view of humanity, in which it would be surprising to find cooperation even when the fate of the world is in human hands.
Alternatively, what if there is evidence that people often work collectively and effectively without major coercion? People are social beings who share information, build trust by becoming known as reliable and predictable, and come together to produce, monitor and enforce rules for the group’s benefit. They produce agreements with each other that could be enforced if necessary.
The IAD helps us analyse these cooperative arrangements. Ostrom describes 8 ‘design principles’ of enduring and effective CPR management shared by many real world examples:
CPRs have clear boundaries. Users know what they are managing, and can identify legitimate users.
The rules suit local conditions. Users know what they (a) are expected to contribute to management and (b) receive from CPRs.
The actors affected by the rules help shape them (at low cost).
CPR monitors are users or accountable to users. They monitor (a) the conduct of users and (b) the state of the CPR. The costs of mutual monitoring are low, and their consequences felt quickly.
The penalties for rule-breaking are low if the choice is a one-off and understandable under the circumstances (to avoid alienating the user). The penalties are high if the choice is part of a pattern which makes other users feel like ‘suckers’, or if rule-breaking would be catastrophic.
Conflict resolution is frequent, rapid and low cost.
Users have the right to self-organise without too much outside interference.
Many projects are connected geographically and at different scales – local, regional, national – in ways that do not undermine individual projects.
These design principles help explain why some communities manage CPRs successfully. They allow users to share the same commitment and expect the long-term benefits to be worthwhile.
However, Ostrom stressed that there is no blueprint – no hard and fast rules – to CPR management. There are three particular complications:
Good management requires high trust to encourage norms of reciprocity. Trust is crucial to minimizing the costs of compliance monitoring and enforcement. Trust may develop when participants communicate regularly, share an understanding of their common interests, reciprocate each other’s cooperation, and have proven reliable in the past.
Design principles are important to developing trust and solidarity, but so are ‘evolutionary’changes to behaviour. Actors have often learned about rule efficacy – to encourage cooperation and punish opportunism – through trial-and-error over a long period, beginning with simple, low-cost operational rules producing quick wins.
Rules, rules on rules, more rules, then even more rules
Institutions contain a large, complicated set of rules that serve many different purposes, and need to be understood and analysed in different ways.
Different purposes include:
how many actors are part of an action situation, and the role they play
what they must/ must not do
who is eligible to participate
who can move from one role to another
who controls membership, and how
how many participants are involved in a choice
what will happen if there is no agreement
how to manage and communicate information
the rewards or sanctions
the range of acceptable actions or outcomes from action.
We also need to analyse the relative costs and simplicity of different rules, and the rules about the other rules, including
‘operational’ rules on day-to-day issues (such as specific payoffs/ sanctions for behaviour)
‘collective choice’ rules about how to make those rules
‘constitutional’ rules on who can decide those rules and who can monitor and enforce, and
‘metaconstitutional’ analysis of how to design these constitutions with reference to the wider political and social context.
The world is too complex to break down into simple pieces
By now, you may be thinking that the IAD – and analysis of resource management – is complicated. This is true, partly because each case study – of the physical conditions and social practices regarding resource management – is different in some way. We can use the IAD to compare experiences, but accept that a profoundly successful scheme in one context may fail miserably in another.
Simplicity versus complexity: the world is complex, but should our analysis follow suit?
Indeed, this is why we need to think about rational choice games and the IAD simultaneously, to understand the analytical trade-offs.
Game theory laboratory experiments – built on simple rules and relatively small numbers of parameters – produce parsimonious analysis and results that we can understand relatively easily.
We may reject simple games as unrealistic, but what if we take this criticism to its extreme?
IAD in-depth field studies embrace complexity to try to understand the key dimensions of each study’s context. When we put them all together, there are too many concepts, variables, global applications, and variations-by-context, to contain in a simple theory.
The IAD addresses this trade off by offering a language to help organize research, encouraging people to learn it then use it to apply many different theories to explain different parts of the whole picture.
In other words, it is OK to reject simple models as unrealistic, but to embrace real-world complexity may require a rather complicated language.
Rational choice theory provides a way of thinking about collective action problems. There is great potential for choices made by individuals to have an adverse societal effect when there is an absence of trust, obligation, or other incentives to cooperate. People may have collective aims that require cooperation, but individual incentives to defect. While the action of one individual makes little difference, the sum total of individual actions may be catastrophic.
Simple ‘games’ provide a way to think about these issues logically, by limiting analysis to very specific situations under rather unrealistic conditions, before we consider possible solutions under more realistic conditions. For example, in simple games we assume that individuals pursue the best means to fulfil their preferences: they are able to act ‘optimally’ by processing all relevant information to rank-order their preferences consistently.
Go with it just now, and then we can consider what to do next.
The ‘prisoner’s dilemma’
Two people are caught red-handed and arrested for a minor crime, placed in separate rooms and invited to confess to a major crime (they both did it and the police know it but can’t prove it). The payoffs are:
If Paul confesses and Linda doesn’t, then Paul walks free and Linda receives a 10 year jail sentence (or vice versa)
If both confess they receive a much higher sentence (8 years) than if neither confesses (1 year).
Also assume that they take no benefit from the shorter sentence of the other person (a non-cooperative game).
It demonstrates a collective action problem: although the best outcome for the group requires that neither confess (both would go to jail for a total of 2 years), the actual outcome is that both confess (16 years). The latter represents the ‘Nash equilibrium’ since neither would be better off by changing their strategy unilaterally. Think of it from an individual’s perspective:
Imagine Paul will confess. Linda knows that if she stays silent, she gets suckered into 10 years. If she confesses, she gets 8.
Imagine Paul will stay silent. Linda knows that if she stays silent, she gets 1 year. If she confesses, she suckers Paul into 10.
The effect of Paul and Linda acting as individuals is that they are worse off collectively. Both ‘defect’ (confess) when they should ‘cooperate’ (stay silent).
The ‘logic of collective action’
Olson argues that, as the membership of an interest group rises, so does:
(a) the belief among individuals that their contribution to the group would make little difference and
(b) their ability to ‘free ride’.
I may applaud the actions of a group, but can – and will try to – enjoy the outcomes without leaving my sofa, paying them, or worrying that they will fail without me or punish me for not getting involved.
The ‘tragedy of the commons’
The scenario is that a group of farmers share a piece of land that can only support so many cattle before deteriorating and becoming useless. Although each farmer recognizes the collective benefit to an overall maximum number of cattle, each calculates that the marginal benefit she takes from one extra cow for herself exceeds the extra cost of over grazing to the group. Individuals place more value on the resources they extract for themselves now than the additional rewards they could all extract in the future.
The tragedy is that if all farmers act on the same calculation then they will destroy the common resource. The group is too large to track individual behaviour, individuals place more value on current over future consumption, and there is low mutual trust, with minimal motive and opportunity to produce and enforce binding agreements
This ‘tragedy’ sums up current anxieties about one of the defining problems of our time: global ‘common pool resources’ are scarce and the world’s population and consumption levels are rising; there is no magic solution; and, collective action is necessary but not guaranteed. We may value sustainable water, air, energy, forests, crops, and fishing stocks, but find it difficult to imagine how our small contribution to consumption will make much difference. As a group we fear climate change and seek to change our ways but, as individuals, contribute to the problem.
Overall, these scenarios suggest that individuals have weak incentives to cooperate even if it is in their interests and they agree to do so. This problem famously prompted Hardin (to recommend ‘mutual coercion, mutually agreed upon’ to ensure collective action.
What happens when there are many connected games?
In real life, it is almost impossible to find such self-contained and one-off games.In many repeated – or connected – games, the players know that thereare wider or longer-term consequences to defection.
In ‘nested games’, the behaviour of individuals often seems weird in one game until we recognise their involvement in a series. It may pay off to act ‘irrationally’ in the short term to support a longer-term strategy, or to lose in one to win in another.
In an ‘ecology of games’, many overlapping games take place at roughly the same time, and players to learn how to play one game while keeping an eye on many others, while some key players encourage a wider set of rules under which all games operate.
Evolutionary game theory explores how behaviour changes over multiple games to reflect factors such as (a) feedback and learning from trial and error, and (b) norms and norm enforcement.
For example, player 2 may pursue a ‘tit-for-tat’ strategy. She cooperates at first, then mimics the other player’s previous choice: defecting, to punish the other player’s defection, or cooperating if the other player cooperated. Knowledge of this strategy could provide player 1 with the incentive to cooperate. Further, norms develop when players enforce and expect sanctions for non-cooperation, foster socialisation to discourage norm violation, and some norms become laws.
In other words, this focus on the rules of repeated games gives us more hope than the tragedy of the commons. Indeed, it underpin Ostrom’s famous analysis of the conditions under which people can govern the commons more effectively.
Should we try to get people to change their behaviour, perhaps ‘for their own good’ or to act in the ‘collective’ rather than their own narrow self-interest?
If so, how? Should we rely on the state to address ‘collective action problems’?
If so, should we use incentives, coercion, and/ or ‘nudges’ to change behaviour?
In other words, we ask if it is appropriate to change public behaviour and, if so, what means are most effective.
A classic approach is to make some simplifying assumptions – for example, about people’s ability to process information and rank their preferences when making choices – to help us imagine how they might act in particular situations.
For example, people might ‘free ride’ if they can benefit from a good or service without paying for it. This insight underpins the argument that the state must intervene to solve ‘market failure’, such as in the provision of ‘public goods’ (which are ‘non-excludable’, i.e. no-one can be excluded from enjoying their benefits, and ‘non-rival’, i.e. their use by one person does not diminish their value to another).
Or, people might contribute to Hardin’s ‘tragedy of the commons’: the potentially catastrophic, cumulative effect of individual choices regarding scarce ‘common pool resources’ such as fertile land, unpolluted water, clean air, and fishing stocks. It is in our collective interest to act collectively to manage such resources, but individual interest to take a little bit more. So, if we all act individually, not collectively, the scarce resource is ruined.
Hardin’s solution to this problem is ‘mutual coercion, mutually agreed upon’, such as state intervention. He recommends taxation as a good example of a coercive device. However, state intervention is not a panacea and it produces major unintended consequences. So, this recommendation prompts two key discussions that are central to contemporary studies of public policy:
The Institutional Analysis and Development Framework (IAD) is a key development
Elinor Ostrom’s Nobel prize-winning work challenges the idea that state intervention is necessarily the best solution to collective action problems. It demonstrates the potential for non-market solutions based on a combination of trust and less coercive means to minimize the costs of monitoring and enforcing collective agreements. This approach involves individuals seeking agreements with each other that could be enshrined in a set of meaningful rules (institution). The rules may be enforced by a private authority, and the ‘commons’ would remain common and actors would observe each other’s behaviour and report rule-breaking to the third party that everyone pays for and agrees to respect.
Should we nudge instead of coerce?
Behavioural economics takes insights from psychology to identify the cognitive biases that influence human choice. It has become associated with the idea of ‘nudge’, in which we influence people’s behaviour by exploiting their biases (such as by having them opt-out-of rather than opt-into services, or making it easier to process the information required to make choices).
Take home message for students: don’t just reject rational choice because you read that it uses wackily unrealistic assumptions. Instead, focus on the practical benefits of different ways of thinking. In this case, what issues do these simple models raise? Then note the links between classic and modern studies. Behavioural economics draws insights from psychology to get a better understanding of ‘rational choice’ but you can see the same broad aim to understand how people might act and if we should try to change such action. The IAD also informs the study of state and market failure: can we say with any certainty what governing set-up is best?
These posts introduce you to key concepts in the study of public policy. They are all designed to turn a complex policymaking world into something simple enough to understand. Some of them focus on small parts of the system. Others present ambitious ways to explain the system as a whole. The wide range of concepts should give you a sense of a variety of studies out there, but my aim is to show you that these studies have common themes.