Policy in 500 Words: Ecology of Games

The ‘Ecology of Games Framework’ (EG) combines insights from many approaches to analyze ‘institutional complexity’ and ‘complex institutional systems’.

The focus is on actors learning how to secure ‘mutually beneficial outcomes’, cooperating to produce and deliver agreed solutions, and bargaining within a system over which no actor has control. Therefore, it is worth reading the posts on game theory, the IAD, and SES first (especially if, like me, you associated ‘game’ with tig, then Monopoly, then The Wire).

Insights from three key approaches

EG connects Norton’s ‘ecology of games’, the IAD, and insights from complexity theory to reinforce the idea that institutional arrangements are not simple and orderly.

In simple games, we need only analyse the interaction between a small number of actors with reference to one set of self-contained rules providing clear sanctions or payoffs. In real world policymaking, many different games take place at the same time in different venues.

Some policy games may be contained within a geographical area – such as California – but there are no self-contained collective action problems:

• Examples such as ‘biodiversity’, ‘ecology’ or ‘environmental’ policies command a collection of interdependent policies relating to issues like local planning, protected species, water management, air pollution, transport, energy use, and contributors to such policies or policy problems in other areas of government (such as public services).
• Each contributor to policy may come from different institutions associated with many policymaking venues spread across many levels and types of government.

Consequently, many games interact with each other. The same actor might participate in multiple games subject to different rules. Further, each game produces ‘externalities’ for the others; the ‘payoffs’ to each game are connected and complicated.

A focus on ‘complex adaptive systems’ suggests that central governments do not have the resources to control – or understand fully – interaction at this frequency and scale. Rather, policymaking influences are:

• Internal to the game, when actors (a) follow and shape the rules of each institution, and (b) learn through trial and error.
• External to the game, when physical resources change, or central levels of government change the resources of local actors.

Insights from the wider literature

The EG brings in wider insights – from theories in the 500 and 1000 Words series – to analyse this process. Examples include:

• Actors deal with bounded rationality primarily with reference to their ‘social tribal instincts’.
• They form coalitions with their allies to get what they want from different games
• They engage in ‘policy learning’ to update their policy knowledge and enhance their policymaking position.

Consequently, we have come a long way from simple assumptions about human behaviour outlined in our first post in this series.

As with the IAD, the EG emphasis is on (a) finding solutions to complex (largely environmental) policy problems, with reference to (b) initiatives consistent with self-organising systems such as ‘collaborative governance’. Like most posts in this series, it rejects a naïve attachment to a single powerful central government. Policymaking is multi-centric, and solutions to complex problems will emerge in that context.

See also:

Policy Concepts in 1000 Words: the Institutional Analysis and Development Framework (IAD) and Governing the Commons

Policy Concepts in 1000 Words: it’s time for some game theory

Policy in 500 Words: the Social-Ecological Systems Framework

Policy Concepts in 1000 Words: Rational Choice and the IAD (the older post for the 1^st edition)

Policy Concepts in 1000 Words: Multi-centric Policymaking

How to Navigate Complex Policy Designs

How can governments better collaborate to address complex problems?

Yay! I didn't realize that @CairneyPaul has summarized our work on the "ecology of games" in 500 words! Who needs another 7000 word article at this point? All you need is right here! https://t.co/Y5f9O4Gaub pic.twitter.com/CgELtL8CG7

— Mark Lubell (@EnvPolicyCenter) February 20, 2019

 

Policy in 500 Words: the Social-Ecological Systems Framework

Think of the SES framework as the combination of:

• the IAD approach to analyzing ‘the commons’, and
• 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, resource system (such as a protected park) and resource units (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.

See also:

Policy Concepts in 1000 Words: the Institutional Analysis and Development Framework (IAD) and Governing the Commons

Policy in 500 Words: Ecology of Games

Policy Concepts in 1000 Words: it’s time for some game theory

Policy Concepts in 1000 Words: Rational Choice and the IAD (the older post for the 1^st edition)

Policy Concepts in 100 Words: Multi-centric Policymaking

How to Navigate Complex Policy Designs

How can governments better collaborate to address complex problems?

 

Policy Concepts in 1000 Words: the Institutional Analysis and Development Framework (IAD) and Governing the Commons

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:

1. CPRs have clear boundaries. Users know what they are managing, and can identify legitimate users.
2. The rules suit local conditions. Users know what they (a) are expected to contribute to management and (b) receive from CPRs.
3. The actors affected by the rules help shape them (at low cost).
4. 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.
5. 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.
6. Conflict resolution is frequent, rapid and low cost.
7. Users have the right to self-organise without too much outside interference.
8. 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:

1. Trust

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.

2. 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.

 

3. 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.

See also:

Policy Concepts in 1000 Words: it’s time for some game theory

Policy Concepts in 1000 Words: Rational Choice and the IAD (the older post for the 1^st edition)

Policy Concepts in 100 Words: Multi-centric Policymaking

Policy in 500 Words: the Social-Ecological Systems Framework

Policy in 500 Words: Ecology of Games

How to Navigate Complex Policy Designs

How can governments better collaborate to address complex problems?

 

 

Policy Concepts in 1000 Words: game theory and thought experiments

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.

See also:

This post is one of four updates to the post Policy Concepts in 1000 Words: Rational Choice and the IAD 

Policy Concepts in 1000 Words: the Institutional Analysis and Development Framework

Policy in 500 Words: the Social-Ecological Systems Framework

Policy in 500 Words: Ecology of Games

See also:

How to Navigate Complex Policy Designs

How can governments better collaborate to address complex problems?

See also this tweet – and many others paying homage to it – to explain the title of the post:

<THREAD> I’m now hearing this meme that says Obama, Clinton, et al. are doing nothing, just gave up.

Guys. It’s time for some game theory.

— Eric Garland (@ericgarland) December 11, 2016

See also this tweet thread on Hardin:

Something I've been meaning to say about The Tragedy of the Commons. Bear with me for a small thread on why our embrace of Hardin is a stain on environmentalism. tldr: we’ve let a flawed metaphor by a racist ecologist define environmental thinking for a half century. 1/

— mattomildenberger (@mmildenberger) March 4, 2019