Category Archives: 1000 words

Who can you trust during the coronavirus crisis?

By Paul Cairney and Adam Wellstead, based on this paper.

Trust is essential during a crisis. It is necessary for cooperation. Cooperation helps people coordinate action, to reduce the need for imposition. It helps reduce uncertainty in a complex world. It facilitates social order and cohesiveness. In a crisis, almost-instant choices about who to trust or distrust make a difference between life and death.

Put simply, we need to trust: experts to help us understand and address the problem, governments to coordinate policy and make choices about levels of coercion, and each other to cooperate to minimise infection.

Yet, there are three unresolved problems with understanding trust in relation to coronavirus policy.

  1. What does trust really mean?

Trust is one of those words that could mean everything and nothing. We feel like we understand it intuitively, but would also struggle to define it well enough to explain how exactly it works. For example, in social science, there is some agreement on the need to describe individual motivation, social relationships, and some notion of the ‘public good’:

  • the production of trust helps boost the possibility of cooperation, partly by
  • reducing uncertainty (low information about a problem) and ambiguity (low agreement on how to understand it) when making choices, partly by
  • helping you manage the risk of making yourself vulnerable when relying on others, particularly when
  • people demonstrate trustworthiness by developing a reputation for competence, honesty, and/ or reliability, and
  • you combine cognition and emotion to produce a disposition to trust, and
  • social and political rules facilitate this process, from the formal and well-understood rules governing behaviour to the informal rules and norms shaping behaviour.

As such, trust describes your non-trivial belief in the reliability of other people, organisations, or processes. It facilitates the kinds of behaviour that are essential to an effective response to the coronavirus, in which we need to:

  1. Make judgements about the accuracy of information underpinning our choices to change behaviour (such as from scientific agencies).
  2. Assess the credibility of the people with whom we choose to cooperate or take advice (such as more or less trust in each country’s leadership).
  3. Measure the effectiveness of the governments or political systems to which we pledge our loyalty.

Crucially, in most cases, people need to put their trust in actions or outcomes caused by people they do not know, and the explanation for this kind of trust is very different to trusting people you know.

  1. What does trust look like in policymaking?

Think of trust as a mechanism to boost cooperation and coalition formation, help reduce uncertainty, and minimise the ‘transactions costs’ of cooperation (for example, monitoring behaviour, or producing or enforcing contracts). However, uncertainty is remarkably high because the policy process is not easy to understand. We can try to understand the ‘mechanisms’ of trust, to boost cooperation, with reference to these statements about trustees and the trusted:

  1. Individuals need to find ways to make choices about who to trust and distrust.
  2. However, they must act within a complex policymaking environment in which they have minimal knowledge of what will happen and who will make it happen.
  3. To respond effectively, people seek ways to cooperate with others systematically, such as by establishing formal and informal rules.

People seeking to make and influence policy must act despite uncertainty about the probability of success or risk of failure. In a crisis, it happens almost instantly. People generate beliefs about what they want to happen and how their reliance on others can help it happen. This calculation depends on:

  • Another person or organisation’s reputation for being trustworthy, allowing people the ability to increase certainty when they calculate the risk of engagement.
  • The psychology of trust and perceptions of another actor’s motives. To some extent, people gather information and use logic to determine someone’s competence. However, they also use gut feeling or emotion to help them decide to depend on someone else. They may also trust a particular source if the cognitive load is low, such as because (a) the source is familiar (e.g. a well-known politician or a celebrity, or oft-used source), or (b) the information is not challenging to remember or accept.

If so, facilitators of trust include:

  • People share the same characteristics, such as beliefs, norms, or expectations.
  • Some people have reputations for being reliable, predictable, honest, competent, and/ or relatively selfless.
  • Good experiences of previous behaviour, including repeated interactions that foster rewards and help predict future risk (with face to face contact often described as particularly helpful).
  • People may trust people in a position of authority (or the organisation or office), such as an expert or policymaker (although perhaps the threat of rule enforcement is better understood as a substitute for trust, and in practice it is difficult to spot the difference).

High levels of trust are apparent when effective practices – built on reciprocity, emotional bonds, and/ or positive expectations – become the norms or formalised and written down for all to see and agree. High levels of distrust indicate a need to deter the breach of agreements, by introducing expectations combined with sanctions for not behaving as expected.

  1. Who should you trust?

These concepts do not explain fully why people trust particular people more than others, or help us determine who you should trust during a crisis.

Rather, first, they help us reflect on the ways in which people have been describing their own thought processes (click here, and scroll to ‘Limiting the use of evidence’), such as trusting an expert source because they: (a) have a particular scientific background, (b) have proven to be honest and reliable in the past, (c) represent a wider scientific profession/ community, (d) are part of a systematic policymaking machinery, (e) can be held to account for their actions, (f) are open about the limits to their knowledge, and/or (g) engage critically with information to challenge simplistic rushes to judgement. Overall, note how much trust relates to our minimal knowledge about their research skills, prompting us to rely on an assessment of their character or status to judge their behaviour. In most cases, this is an informal process in which people may not state (or really know) why they trust or distrust someone so readily.

Then, we can reflect on who we trust, and why, and if we should change how we make such calculations during a crisis like the coronavirus. Examples include:

  • A strong identity with a left or right wing cause might prompt us only to trust people from one political party. This thought process may be efficient during elections and debates, but does it work so well during a crisis necessitating so high levels of cross-party cooperation?
  • People may be inclined to ignore advice because they do not trust their government, but maybe (a) high empathy for their vulnerable neighbours, and (b) low certainty about the impact of their actions, should prompt them to trust in government advice unless they have a tangible reason not to (while low empathy helps explain actions such as hoarding).
  • Government policy is based strongly on the extent to which policymakers trust people to do the right thing. Most debates in liberal democracies relate to the idea that (a) people can be trusted, so give advice and keep action voluntary, or cannot be trusted, so make them do the right thing, and that (b) citizens can trust their government. In other words, it must be a reciprocal relationship (see the Tweets in Step 3).

Finally, governments make policy based on limited knowledge and minimal control of the outcomes, and they often respond with trial-and-error strategies. The latter is fine if attention to policy is low and trust in government sufficiently high. However, in countries like the UK and US, each new choice prompts many people to question not only the competence of leaders but also their motivation. This is a worrying development for which everyone should take some responsibility.

See also:

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

The coronavirus and evidence-informed policy analysis (short version)

The coronavirus and evidence-informed policy analysis (long version)

 

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Policy Concepts in 1000 Words: how do policy theories describe policy change?

The 1000 words and 500 words series already show how important but difficult it is to define and measure policy change. In this post, Leanne Giordono and I dig deeper into the – often confusingly different – ways in which different researchers conceptualise this process. We show why there is such variation and provide a checklist of questions to ask of any description of policy change.

Measuring policy change is more difficult than it looks

The measurement of policy change is important. Most ‘what is policy?’ discussions remind us that there can be a huge difference between policy as a (a)  statement of intent, (b) strategy, (c) collection of tools/ instruments and (d) contributor to policy outcomes.

Policy theories remind us that, while politicians and political parties often promise to sweep into office and produce radical departures from the past, most policy change is minor. There is a major gap between stated intention and actual outcomes, partly because policymakers do not control the policy process for which they are responsible. Instead, they inherit the commitments of their predecessors and make changes at the margins.

The 1000 words and 500 words posts suggest that we address this problem of measurement by identifying the use of a potentially large number of policy instruments or policy tools such as regulation (including legislation) and resources (money and staffing) to accentuate the power at policymaker’s disposal.

Then, they suggest that we tell a story of policy change, focusing on (a) what problem policymakers were trying to solve, and the size of their response in relation to the size of the problem, and (b) the precise nature of specific changes, or how each change contributes to the ‘big picture’.

This recommendation highlights a potentially major problem: as researchers, we can produce very different narratives of policy change from the same pool of evidence, by accentuating some measures and ignoring others, or putting more faith in some data than others.

Three ways to navigate different approaches to imagining and measuring change

Researchers use many different concepts and measures to define and identify policy change. It would be unrealistic – and perhaps unimaginative – to solve this problem with a call for one uniform approach.

Rather, our aim is to help you (a) navigate this diverse field by (b) identifying the issues and concepts that will help you interpret and compare different ways to measure change.

  1. Check if people are ‘showing their work’

Pay close attention to how scholars are defining their terms. For example, be careful with incomplete definitions that rely on a reference to evolutionary change (which can mean so many different things) or incremental change (e.g. does an increment mean small or non-radical)? Or, note that frequent distinctions between minor versus major change seem useful, but we are often trying to capture and explain a confusing mixture of both.

  1. Look out for different questions

Multiple typologies of change often arise because different theories ask and answer different questions:

  • The Advocacy Coalition Framework distinguishes between minor and major change, associating the former with routine ‘policy-oriented learning’, and the latter with changes in core policy beliefs, often caused by a ‘shock’ associated with policy failure or external events.
  • Innovation and Diffusion models examine the adoption and non-adoption of a specific policy solution over a specific period of time in multiple jurisdictions as a result of learning, imitation, competition or coercion.
  • Classic studies of public expenditure generated four categories to ask if the ‘budgetary process of the United States government is equivalent to a set of temporally stable linear decision rules’. They describe policy change as minor and predictable and explain outliers as deviations from the norm.
  • Punctuated Equilibrium Theory identifies a combination of (a) huge numbers of small policy change and (b) small numbers of huge change as the norm, in budgetary and other policy changes.
  • Hall distinguishes between (a) routine adjustments to policy instruments, (b) changes in instruments to achieve existing goals, and (c) complete shifts in goals. He compares long periods in which (1) some ideas dominate and institutions do not change, with (2) ‘third order’ change in which a profound sense of failure contributes to a radical shift of beliefs and rules.
  • More recent scholarship identifies a range of concepts – including layering, drift, conversion, and displacement – to explain more gradual causes of profound changes to institutions.

These approaches identify a range of possible sources of measures:

  1. a combination of policy instruments that add up to overall change
  2. the same single change in many places
  3. change in relation to one measure, such as budgets
  4. a change in ideas, policy instruments and/ or rules.

As such, the potential for confusion is high when we include all such measures under the single banner of ‘policy change’.

  1. Look out for different measures

Spot the different ways in which scholars try to ‘operationalize’ and measure policy change, quantitatively and/ or qualitatively, with reference to four main categories.

  1. Size can be measured with reference to:
  • A comparison of old and new policy positions.
  • A change observed in a sample or whole population (using, for example, standard deviations from the mean).
  • An ‘ideal’ state, such as an industry or ‘best practice’ standard.
  1. Speed describes the amount of change that occurs over a specific interval of time, such as:
  • How long it takes for policy to change after a specific event or under specific conditions.
  • The duration of time between commencement and completion (often described as ‘sudden’ or ‘gradual’).
  • How this speed compares with comparable policy changes in other jurisdictions (often described with reference to ‘leaders’ and ‘laggards’).
  1. Direction describes the course of the path from one policy state to another. It is often described in comparison to:
  • An initial position in one jurisdiction (such as an expansion or contraction).
  • Policy or policy change in other jurisdictions (such as via ‘benchmarking’ or ‘league tables’)
  • An ‘ideal’ state (such as with reference to left or right wing aims).
  1. Substance relates to policy change in relations to:
  • Relatively tangible instruments such as legislation, regulation, or public expenditure.
  • More abstract concepts such as in relation to beliefs or goals.

Take home points for students

Be thoughtful when drawing comparisons between applications, drawn from many theoretical traditions, and addressing different research questions.  You can seek clarity by posing three questions:

  1. How clearly has the author defined the concept of policy change?
  2. How are the chosen theories and research questions likely to influence the author’s operationalization of policy change?
  3. How does the author operationalize policy change with respect to size, speed, direction, and/or substance?

However, you should also note that the choice of definition and theory may affect the meaning of measures such as size, speed, direction, and/or substance.

 

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A general theory of public policy

This is a placeholder for future work and discussion. It tails off at the end.

People sometimes talk about a ‘general theory’ of public policy to put in our minds a comparison with the physical sciences. Usually, the punchline is that there are ‘no general theories of public policy that are not bounded by space or time’ (p21). There may be some reference to the accumulation of knowledge or wisdom in policy studies, but based rarely on the understanding that policy studies contain the equivalent of general laws (I can only think of one possible exception).

This outcome is not too surprising in the social sciences, in which context really matters and we would expect a lot of variation in policy, policymaking, and outcomes.

On the other hand, we still need a way to communicate our findings, relate them to other studies, compare them, and wonder what it all adds up to. Few people go as far as expressing the sense that every study is unique (to the point of non-comparability) and that every description of policymaking does not compare to another.

In other words, we may be looking for a happy medium, to reject the idea of general laws but encourage – when appropriate or necessary – enough of a sense of common outlook and experience to help us communicate with each other (without descending too quickly into heated debate on our cross-purposes). Or, we can at least tell a story of policy studies and invite others to learn from, or challenge, its insights.

In my case, there are two examples in which it is necessary to project some sense of a common and initially-not-too-complicated story:

  1. When describing policy theory insights to students, on the assumption that it may be their gateway to more reading.

It is possible to choose how many words to devote to each topic, including 500 Words, 1000 Words, a 9000 word Understanding Public Policy chapter, more in the source material, and even more if students start to ‘snowball’.

It is also possible, if you have a clearly defined audience, to introduce some level of uncertainty about these descriptions and their limitations.

For example, I try to describe ‘the policy process’ in 500 words and 1000 words, but in the context of a wider discussion of images of the policy process.

Circle image policy process 24.10.18

It is also possible to provide more context, such as in this kind of introductory box, coupled with 12 things to know about studying public policy

Introduction box

(from Chapter 1)

You can also get into the idea that my story is one of many, particularly after students have invested in many versions of that story by the end of an introductory book

conclusion box

(from Chapter 13)

  1. When describing these insights to people – from other disciplines or professions – who do not have the time, inclination, or frame of reference to put in that kind of work.

In this case, one presentation or article may be the limit. People may want to know the answer to a question – e.g. Why don’t policymakers listen to your evidence?rather than hear all about the explanation for the answer.

You do your best, and then – if there is time – you talk about what you missed out.

For example, in this talk, the first question was: why didn’t you mention the role of power?

 

A general theory or a general understanding? Two key issues

That was a long-winded introduction to a more philosophical point about what we might want from general theories. My impression is that you might be seeking one of these two possibilities:

  1. To use theories and concepts to describe material reality. In producing a general theory, we seek a general understanding of the ways in which the real world works. If so, we may focus primarily on how well these concepts describe the world, and the extent to which we can produce methods to produce systematic and consistent findings. The lack of a general theory denotes too much complexity and context.
  2. To use theories and concepts to represent a useful story. In producing a general understanding, we focus on the ways in which people generate and communicate their understanding. If so, we may focus more on how people come together to produce and share meaning through concepts. The lack of a general theory could reflect the lack of agreement on how to study policymaking. Or, the presence of a general understanding could represent the exercise of power, to set the agenda and limit scholarly attention to a small number of theories.

I describe this distinction in the following audio clip, produced halfway through a run with the dogs, while jetlagged. The large gap in the middle happens when I am trying to see if the voice to text is working well enough for me to copy/paste it here (no).

Key examples of the exercise of power include:

  1. The act of dismissing an individual, social group, or population by undermining the value of their knowledge or claim to knowledge (discussed in power and knowledge and Chapter 3).
  2. Ongoing discussions about how we deal with (a) a relatively new focus (among the most-established policy theories) on policy studies in countries in the Global South, given that (b) the dominant interpretations of policymaking come from experiences in the Global North.

box 13.4 part 1box 13.4 part 2

So, if you read these posts or Chapter 13 you will find a story of a general understanding of policy followed, almost immediately, by a list of reasons for why you should engage with it critically and perhaps not accept it. I’m setting your agenda but also reminding you that I’m doing it.

That’s it really. To be continued.

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Understanding Public Policy 2nd edition

All going well, it will be out in November 2019. We are now at the proofing stage.

I have included below the summaries of the chapters (and each chapter should also have its own entry (or multiple entries) in the 1000 Words and 500 Words series).

2nd ed cover

titlechapter 1chapter 2chapter 3chapter 4.JPG

chapter 5

chapter 6chapter 7.JPG

chapter 8

chapter 9

chapter 10

chapter 11

chapter 12

chapter 13

 

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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:

IAD box 2.2.19

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.

  1. 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.

 

  1. 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 1st 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?

 

 

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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).

Table 7.1 prisoners

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:

See also this tweet thread on Hardin:

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Policy Concept in 1000 Words: Multi-centric Policymaking

Many theories in this 1000 words series describe multiple policymaking venues. They encourage us to give up on the idea of an all-knowing, all-powerful national central government. Instead, there are many venues in which to make authoritative choices, each contributing to what we call policy.

The word ‘multi-centric’ (coined by Professor Tanya Heikkila, with me and Dr Matt Wood) does not suggest that every venue is of equal importance or power. Rather, it prompts us not to miss something important by focusing too narrowly on one single (alleged) centre of authority.

To some extent, multi-centric policymaking results from choice. Many federal political systems have constitutions that divide power between executive, legislative, and judicial branches, or give some protection to subnational governments. Many others have become ‘quasi-federal’ more organically, by sharing responsibilities with supranational and subnational governments. In such cases, there is explicit choice to distribute power and share responsibility for making policy (albeit with some competition to assert power or shuffle-off responsibility).

However, for the most part, this series helps explain the necessity of multi-centric policymaking with reference to two concepts:

  1. Bounded rationality. Policymakers are only able to pay attention to – and therefore understand and seek to control – a tiny proportion of their responsibilities.
  2. Complex policymaking environments. Policymakers operate in an environment over which they have limited understanding and even less control. It contains many policymakers and influencers spread across many venues, each with their own institutions, networks, ideas (and ways to frame policy), and responses to socio-economic context and events.

Both factors combine to provide major limits to single central government control. Elected policymakers deal with bounded rationality by prioritising some issues and, necessarily, delegating responsibility for the rest. Delegation may be inside or outside of central government.

1000 Words theories describing multi-centric government directly

Multi-level governance describes the sharing of power vertically, between many levels of government, and horizontally, between many governmental, quasi-non-governmental and non-governmental organisations. Many studies focus on the diffusion of power within specific areas like the European Union – highlighting choice – but the term ‘governance’ has a wider connection to the necessity of MLG.

For example, part of MLG’s origin story is previous work to help explain the pervasiveness of policy networks:

  • Policymakers at the ‘top’ ask bureaucrats to research and process policy on their behalf
  • Civil servants seek information and advice from actors outside of government
  • They often form enduring relationships built on factors such as trust.
  • Such policymaking takes place away from a notional centre – or at least a small core executive – and with limited central attention.

Polycentricity describes (a) ‘many decision centers’ with their own separate authority, (b) ‘operating under an overarching set of rules’, but with (c) a sense of ‘spontaneous order’ in which no single centre controls the rules or outcomes. Polycentric governance describes ‘policymaking centres with overlapping authority; they often work together to make decisions, but may also engage in competition or conflict’.

This work on polycentric governance comes primarily from the Institutional Analysis and Development (IAD) framework that helps compare the effectiveness of institutions designed to foster collective action. For example, Ostrom identifies the conditions under which non-governmental institutions can help manage ‘common pool resources’ effectively, while IAD-inspired studies of municipal governance examine how many ‘centres’ can cooperate as or more effectively than a single central government.

Complexity theory has a less clear origin story, but we can identify key elements of complex systems:

  • They are greater than the sum of their parts
  • They amplify or dampen policymaking activity, so the same action can have a maximal or no impact
  • Small initial choices can produce major long term momentum
  • There are regularities of behaviour despite the ever-present potential for instability
  • They exhibit ‘emergence’. Local outcomes seem to defy central direction.

Systems contain many actors interacting with many other actors. They follow and reproduce rules, which help explain long periods of regular behaviour. Or, many actors and rules collide when they interact, producing the potential for many bursts of instability. In each case, the system is too large and unpredictable to be subject to central control.

1000 Words theories describing multi-centric government indirectly

Many other theories in this series describe multi-centric policymaking – or aspects of it – without using this term directly. Examples include:

Punctuated equilibrium theory suggests that (a) policymakers at the ‘centre’ of government could pay attention to, and influence, most issues, but (b) they can only focus on a small number and must ignore the rest. Very few issues reach the ‘macropolitical’ agenda. Multiple policymaking organisations process the rest out of the public spotlight.

Multiple streams analysis turns the notion of a policy cycle on its head, and emphasises serendipity over control. Policy does not change until three things come together at the right ‘window of opportunity’: attention to a problem rises, a feasible solution exists, and policymakers have the motive and opportunity to act. Modern MSA studies show that such windows exist at multiple levels of government.

The advocacy coalition framework describes the interaction between many policymakers and influencers. Coalitions contain actors from many levels and types of government, cooperating and competing within subsystems (see networks). They are surrounded by a wider context – over which no single actor has direct control – that provides the impetus for ‘shocks’ to each coalition.

In such accounts, the emphasis is on high levels of complexity, the potential for instability, and the lack of central control over policymaking and policy outcomes. The policy process is not well described with reference to a small group of policymakers at the heart of government.

The implications for strategy and accountability

Making Policy in a Complex World explores the implications of multi-centric policymaking for wider issues including:

  1. Accountability. How do we hold elected policymakers to account if we no longer accept that there is a single government to elect and scrutinise? See MLG for one such discussion.
  2. Strategy. How can people act effectively in a policy process that seems too complex to understand fully? See this page on ‘evidence based policymaking’

Further Reading:

Key policy theories and concepts in 1000 words

Policy in 500 words

5 images of the policy process

[right click for the audio]

Making Policy in a Complex World (preview PDF ) also provides a short explainer of key terms as follows:

multicentric box 1

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