People engage in politics to turn their beliefs into policy. They form advocacy coalitions with people who share their beliefs, and compete with other coalitions. The action takes place within a subsystem devoted to a policy issue, and a wider policymaking process that provides constraints and opportunities to coalitions.
The policy process contains multiple actors and levels of government. It displays a mixture of intensely politicized disputes and routine activity. There is much uncertainty about the nature and severity of policy problems. The full effects of policy may be unclear for over a decade. The ACF sums it up in the following diagram:
If the policy issue is technical and humdrum, there may be room for routine cooperation. If the issue is highly charged, then people romanticise their own cause and demonise their opponents.
The outcome is often long-term policymaking stability and policy continuity because the ‘core’ beliefs of coalitions are unlikely to shift and one coalition may dominate the subsystem for long periods.
There are two main sources of change.
Coalitions engage in policy learning to remain competitive and adapt to new information about policy. This process often produces minor change because coalitions learn on their own terms. They learn how to retain their coalition’s strategic advantage and use the information they deem most relevant.
‘Shocks’ affect the positions of coalitions within subsystems. Shocks are the combination of external events – such as the election of a new government with different ideas, or the effect of socio-economic change – and the reaction by coalitions. Events may prompt major change as members of a dominant coalition question their beliefs in the light of new evidence (internal shock). Or, another coalition may adapt more readily to its new policy environment and exploit events to gain competitive advantage (external shock).
The ACF began as the study of US policymaking, focusing largely on environmental issues. It has changed markedly to reflect the widening of ACF scholarship to new policy areas, political systems, and methods.
For example, the flow diagram’s reference to the political system’s long term coalition opportunity structures is largely the response to insights from comparative international studies:
A focus on the ‘degree of consensus needed for major policy change’ reflects applications in Europe that highlighted the important of proportional electoral systems
A focus on the ‘openness of the political system’ partly reflects applications to countries without free and fair elections, and/ or systems that do not allow people to come together easily as coalitions to promote policy change.
As such, like all theories in this series, the ACF discusses elements that it would treat as (a) universally applicable, such as the use of beliefs to address bounded rationality, and (b) context-specific, such as the motive and opportunity of specific people to organize collectively to translate their beliefs into policy.
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).
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:
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.
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.
Most policy theories in this series begin with reference to bounded rationality. Policymakers and influencers can only process a tiny proportion of all policy relevant information. They must find ways to limit their attention, to make choices under political and time pressures. They combine cognition and emotion, or rational and irrational shortcuts. Actors also exercise power to frame issues, to focus the attention of their audience to specific information and ways to interpret issues.
Narrative can be an effective means to that end, but the stories that we tell people compete with the stories they tell to themselves. The same story can motivate some audiences, if it chimes with their beliefs or pulls their heartstrings, but backfire in others, if it grates with their view of the world.
In that context, the Narrative Policy Framework (NPF) identifies the narrative strategies of actors seeking to exploit other actors’ cognitive biases. A narrative contains four elements:
Characters. It contains at least one actor, such as a hero or villain.
Plot. Common story arcs include: heroes going on a journey or facing and overcoming adversity, often relating to villains causing trouble and victims suffering tragedy.
Moral. A story’s take-home point describes the cause of, and solution to, the policy problem.
Empirical NPF studies suggest that narrators are effective when they:
use an audience’s fundamental beliefs to influence their more malleable beliefs
tie their story to a hero rather than villain
help the audience imagine a concrete, not abstract, problem, and
connect individual stories to a well understood ‘grand narrative’.
They also compete with others, using stories to: ‘socialise’ or ‘privatise’ issues, romanticize their own coalition’s aim while demonizing others, or encourage governments to distribute benefits to heroic target populations and punishments to villains.
However, narrator success also depends on the audience and context. Particular narratives may only be influential during a window of opportunity in which the audience is receptive to the story, or when the story fits with the audience’s beliefs (think of the same message to left and right wing populations). Indeed, NPF studies suggest that the stories with the biggest short-term impact were on the audiences predisposed to accept them.
It may not seem important that stories have most impact when telling people what they already think, but it could make the difference between thought and action, such as when people turn out to vote or prioritise one problem at the expense of the rest. We may struggle to persuade people to change their minds, but we can encourage them to act by focusing their attention to one belief over another.
Follow up reading
As described, the NPF does not seem too controversial: people tell stories to themselves and each other, and persuasive stories really matter to policymaking. However, note the wider debate about the implications of the NPF’s ‘positivist’ approach in a field often characterised as ‘post-positivist’. This debate – for example in Critical Policy Studies – is a great way into some profound academic differences about (a) the nature of the world, (b) how we can gather knowledge of it, and (c) the methods we should use.
Classic studies suggest that the most profound and worrying kinds of power are the hardest to observe. We often witness highly visible political battles and can use pluralist methods to identify who has material resources, how they use them, and who wins. However, key forms of power ensure that many such battles do not take place. Actors often use their resources to reinforce social attitudes and policymakers’ beliefs, to establish which issues are policy problems worthy of attention and which populations deserve government support or punishment. Key battles may not arise because not enough people think they are worthy of debate. Attention and support for debate may rise, only to be crowded out of a political agenda in which policymakers can only debate a small number of issues.
Studies of power relate these processes to the manipulation of ideas or shared beliefs under conditions of bounded rationality (see for example the NPF). Manipulation might describe some people getting other people to do things they would not otherwise do. They exploit the beliefs of people who do not know enough about the world, or themselves, to know how to identify and pursue their best interests. Or, they encourage social norms – in which we describe some behaviour as acceptable and some as deviant – which are enforced by the state (for example, via criminal justice and mental health policy), but also social groups and individuals who govern their own behaviour with reference to what they feel is expected of them (and the consequences of not living up to expectations).
Such beliefs, norms, and rules are profoundly important because they often remain unspoken and taken for granted. Indeed, some studies equate them with the social structures that appear to close off some action. If so, we may not need to identify manipulation to find unequal power relationships: strong and enduring social practices help some people win at the expense of others, by luck or design.
In practice, these more-or-less-observable forms of power co-exist and often reinforce each other:
Example 1. The control of elected office is highly skewed towards men. Male incumbency, combined with social norms about who should engage in politics and public life, signal to women that their efforts may be relatively unrewarded and routinely punished – for example, in electoral campaigns in which women face verbal and physical misogyny – and the oversupply of men in powerful positions tends to limit debates on feminist issues.
Example 2. ‘Epistemic violence’ describes the act of dismissing an individual, social group, or population by undermining the value of their knowledge or claim to knowledge. Specific discussions include: (a) the colonial West’s subjugation of colonized populations, diminishing the voice of the subaltern; (b) privileging scientific knowledge and dismissing knowledge claims via personal or shared experience; and (c) erasing the voices of women of colour from the history of women’s activism and intellectual history.
It is in this context that we can understand ‘critical’ research designed to ‘produce social change that will empower, enlighten, and emancipate’ (p51). Powerlessness can relate to the visible lack of economic material resources and factors such as the lack of opportunity to mobilise and be heard.
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.