In a previous post, I ask: if the policy cycle does not exist, what do we do? In this artificial policy cycle world, ‘comprehensively rational’ policymakers combine their values with evidence to define policy problems and their aims, ‘neutral’ bureaucracies produce many possible solutions consistent with those aims, and policymakers select the ‘best’ or most ‘evidence based’ solution, setting in motion a cycle of stages including legitimation, implementation, evaluation, and the choice to maintain or change policy.
In the real world, policymaking is not so simple, and three ‘stages’ seem messed up:
Defining problems. There is too much going on in the world, and too much information about problems. So, policymakers have to ignore most problems and most ways to understand them. They use ‘rational’ and ‘irrational’ short-cuts to help them pay attention to a manageable number of issues and address problems without fully understanding them. Problems get attention based on how they are ‘framed’: actors use evidence to reduce uncertainty, and persuasion to reduce ambiguity (they focus our minds on one way to understand a problem).
Producing solutions. When policymaker attention lurches to a problem, it’s too late to produce a new solution that is technically feasible (will it work as intended?) and politically feasible (is it acceptable to enough people in the ‘community’?). While attention lurches quickly, feasible solutions take time to develop.
Making choices. The willingness and ability of policymakers to select a solution is fleeting, based on their beliefs, perception of the ‘national mood’, and the feedback they receive from interest groups and political parties.
Don’t think of these things as linear ‘stages’. Instead, they are independent ‘streams’ which have to come together during a brief ‘window of opportunity’. All key factors – heightened attention to a problem (problem stream), an available and feasible solution (policy stream), and the motive to select it (politics stream) – must come together at the same time, or the opportunity is lost. If you think of the streams as water, the metaphor suggests that when they come together they are hard to separate. Instead, a ‘window of opportunity’ is like a space launch in which policymakers will abort the mission unless every factor is just right.
So, what do we do in the absence of a policy cycle?
Policy entrepreneurs’ know how to respond. They use persuasion to frame problems, help develop feasible solutions, wait for the right time to present them, and know how to adapt to their environment to exploit ‘windows of opportunity’.
Take home message for students. It is easy to dismiss the policy cycle, and find better explanations, but don’t stop there. Consider how to turn this insight into action. If policymaking is so messy, how should people respond? Studying ‘entrepreneurs’ helps us identify strategies to influence the policy process, but how could elected policymakers justify such a weird-looking process? Finally, look at many case studies to see how scholars describe MSA. It’s a flexible metaphor, but is there a coherent literature with common themes?
‘Policy entrepreneurs’ invest their time wisely for future reward, and possess key skills that help them adapt particularly well to their environments. They are the agents for policy change who possess the knowledge, power, tenacity, and luck to be able to exploit key opportunities. They draw on three strategies:
1. Don’t focus on bombarding policymakers with evidence.
Scientists focus on making more evidence to reduce uncertainty, but put people off with too much information. Entrepreneurs tell a good story, grab the audience’s interest, and the audience demands information.
2. By the time people pay attention to a problem it’s too late to produce a solution.
So, you produce your solution then chase problems.
3. When your environment changes, your strategy changes.
For example, in the US federal level, you’re in the sea, and you’re a surfer waiting for the big wave. In the smaller subnational level, on a low attention and low budget issue, you can be Poseidon moving the ‘streams’. In the US federal level, you need to ‘soften’ up solutions over a long time to generate support. In subnational or other countries, you have more opportunity to import and adapt ready-made solutions.
Paul Cairney and Nikos Zahariadis (2016) ‘Multiple streams analysis: A flexible metaphor presents an opportunity to operationalize agenda setting processes’ in Zahariadis, N. (eds) Handbook of Public Policy Agenda-Setting (Cheltenham: Edward Elgar) PDFsee also
This is a post for my talk at the ‘Politheor: European Policy Network’ event Write For Impact: Training In Op-Ed Writing For Policy Advocacy. There are other speakers with more experience of, and advice on, ‘op-ed’ writing. My aim is to describe key aspects of politics and policymaking to help the audience learn why they should write op-eds in a particular way for particular audiences.
A key rule in writing is to ‘know your audience’, but it’s easier said than done if you seek many sympathetic audiences in many parts of a complex policy process. Two simple rules should help make this process somewhat clearer:
Learn how policymakers simplify their world, and
Learn how policy environments influence their attention and choices.
We can use the same broad concepts to help explain both processes, in which many policymakers and influencers interact across many levels and types of government to produce what we call ‘policy’:
Policymaker psychology: tell an evidence-informed story
Policymakers receive too much information, and seek ways to ignore most of it while making decisions. To do so, they use ‘rational’ and ‘irrational’ means: selecting a limited number of regular sources of information, and relying on emotion, gut instinct, habit, and familiarity with information. In other words, your audience combines cognition and emotion to deal with information, and they can ignore information for long periods then quickly shift their attention towards it, even if that information has not really changed.
Consequently, an op-ed focusing solely ‘the facts’ can be relatively ineffective compared to an evidence-informed story, perhaps with a notional setting, plot, hero, and moral. Your aim shifts from providing more and more evidence to reduce uncertainty about a problem, to providing a persuasive reason to reduce ambiguity. Ambiguity relates to the fact that policymakers can understand a policy problem in many different ways – such as tobacco as an economic good, issue of civil liberties, or public health epidemic – but often pay exclusive attention to one.
So, your aim may be to influence the simple ways in which people understand the world, to influence their demand for more information. An emotional appeal can transform a factual case, but only if you know how people engage emotionally with information. Sometimes, the same story can succeed with one audience but fail with another.
Institutions: learn the ‘rules of the game’
Institutions are the rules people use in policymaking, including the formal, written down, and well understood rules setting out who is responsible for certain issues, and the informal, unwritten, and unclear rules informing action. The rules used by policymakers can help define the nature of a policy problem, who is best placed to solve it, who should be consulted routinely, and who can safely be ignored. These rules can endure for long periods and become like habits, particularly if policymakers pay little attention to a problem or why they define it in a particular way.
Networks and coalitions: build coalitions and establish trust
Such informal rules, about how to understand a problem and who to speak with about it, can be reinforced in networks of policymakers and influencers.
‘Policy community’ partly describes a sense that most policymaking is processed out of the public spotlight, often despite minimal high level policymaker interest. Senior policymakers delegate responsibility for policymaking to bureaucrats, who seek information and advice from groups. Groups exchange information for access to, and potential influence within, government, and policymakers have ‘standard operating procedures’ that favour particular sources of evidence and some participants over others
‘Policy community’ also describes a sense that the network seems fairly stable, built on high levels of trust between participants, based on factors such as reliability (the participant was a good source of information, and did not complain too much in public about decisions), a common aim or shared understanding of the problem, or the sense that influencers represent important groups.
So, the same policy case can have a greater impact if told by a well trusted actor in a policy community. Or, that community member may use networks to build key coalitions behind a case, use information from the network to understand which cases will have most impact, or know which audiences to seek.
Ideas: learn the ‘currency’ of policy argument
This use of networks relates partly to learning the language of policy debate in particular ‘venues’, to learn what makes a convincing case. This language partly reflects a well-established ‘world view’ or the ‘core beliefs’ shared by participants. For example, a very specific ‘evidence-based’ language is used frequently in public health, while treasury departments look for some recognition of ‘value for money’ (according to a particular understanding of how you determine VFM). So, knowing your audience is knowing the terms of debate that are often so central to their worldview that they take them for granted and, in contrast, the forms of argument that are more difficult to pursue because they are challenging or unfamiliar to some audiences. Imagine a case that challenges completely someone’s world view, or one which is entirely consistent with it.
Socioeconomic factors and events: influence how policymakers see the outside world
Some worldviews can be shattered by external events or crises, but this is a rare occurrence. It may be possible to generate a sense of crisis with reference to socioeconomic changes or events, but people will interpret these developments through the ‘lens’ of their own beliefs. In some cases, events seem impossible to ignore but we may not agree on their implications for action. In others, an external event only matters if policymakers pay attention to them. Indeed, we began this discussion with the insight that policymakers have to ignore almost all such information available to them.
Know your audience revisited: practical lessons from policy theories
To take into account all of these factors, while trying to make a very short and persuasive case, may seem impossible. Instead, we might pick up some basic rules of thumb from particular theories or approaches. We can discuss a few examples from ongoing work on ‘practical lessons from policy theories’.
Storytelling for policy impact
If you are telling a story with a setting, plot, hero, and moral, it may be more effective to focus on a hero than villain. More importantly, imagine two contrasting audiences: one is moved by your personal and story told to highlight some structural barriers to the wellbeing of key populations; another is unmoved, judges that person harshly, and thinks they would have done better in their shoes (perhaps they prefer to build policy on stereotypes of target populations). ‘Knowing your audience’ may involve some trial-and-error to determine which stories work under which circumstances.
Appealing to coalitions
Or, you may decide that it is impossible to write anything to appeal to all relevant audiences. Instead, you might tailor it to one, to reinforce its beliefs and encourage people to act. The ‘advocacy coalition framework’ describes such activities as routine: people go into politics to translate their beliefs into policy, they interpret the world through those beliefs, and they romanticise their own cause while demonising their opponents. If so, would a bland op-ed have much effect on any audience?
Don’t focus on bombarding policymakers with evidence. Scientists focus on making more evidence to reduce uncertainty, but put people off with too much information. Entrepreneurs tell a good story, grab the audience’s interest, and the audience demands information.
By the time people pay attention to a problem it’s too late to produce a solution. So, you produce your solution then chase problems.
When your environment changes, your strategy changes. For example, in the US federal level, you’re in the sea, and you’re a surfer waiting for the big wave. In the smaller subnational level, on a low attention and low budget issue, you can be Poseidon moving the ‘streams’. In the US federal level, you need to ‘soften’ up solutions over a long time to generate support. In subnational or other countries, you have more opportunity to import and adapt ready-made solutions.
On the day, we can use such concepts to help us think through the factors that you might think about while writing op-eds, even though it is very unlikely that you would mention them in your written work.
Policy influence is impossible to find if you don’t know where to look. Policies theories can help you look in the right places, but they take time to understand.
It’s not realistic to expect people with their own day jobs – such as scientists producing policy-relevant knowledge in other fields – to take the time to use the insights it takes my colleagues a full-time career to appreciate.
So, we need a way to explain those insights in a way that people can pick up and use when they engage in the policy process for the first time. That’s why Chris Weible and I asked a group of policy theory experts to describe the ‘state of the art’ in their field and the practical lessons that they offer.
None of these abstract theories provide a ‘blueprint’ for action (they were designed primarily to examine the policy process scientifically). Instead, they offer one simple insight: you’ll save a lot of energy if you engage with the policy process that exists, not the one you want to see.
Then, they describe variations on the same themes, including:
There are profound limits to the power of individual policymakers: they can only process so much information, have to ignore almost all issues, and therefore tend to share policymaking with many other actors.
You can increase your chances of success if you work with that insight: identify the right policymakers, the ‘venues’ in which they operate, and the ‘rules of the game’ in each venue; build networks and form coalitions to engage in those venues; shape agendas by framing problems and telling good stories, design politically feasible solutions, and learn how to exploit ‘windows of opportunity’ for their selection.
Learn from ‘multiple streams’ analysis
My paper on the ‘multiple streams approach’ shows what happens in the absence of two things you might want to see: ‘rational’ and ‘evidence based’ policymaking which takes place in a policy cycle with linear stages. If you act according to that hope, you’ll likely say the wrong thing to the wrong people at the wrong time. It would be better to adapt to the following implications of an agenda setting process in which framing is more important than evidence, and solutions chase problems (table 1).
Learn the meaning of timing and windows of opportunity
Most people would associate ‘timing’ with the idiom ‘be in the right place at the right time’. In agenda setting it means two more important things:
Learning the right time to exploit emotional thinking in policymakers to help generate attention to a policy problem, not waiting for their attention to shift naturally.
Producing policy solutions first, then waiting for the right time to attach them to problems. If a policy cycle existed, policymakers would identify a problem then spark of a series of stages, to select a solution, implement, and evaluate it. In the real world, policymaker attention often shifts before a feasible solution can be developed.
Learn from ‘policy entrepreneurs’
So, successful ‘policy entrepreneurs’ ‘lie in wait in and around government with their solutions at hand, waiting for problems to float by to which they can attach their solutions, waiting for a development in the political stream they can use to their advantage’ (Kingdon 1984: 165–6). Entrepreneurs are the elected policymakers or unelected influencers with the knowledge, power, tenacity and luck to be able to exploit ‘windows of opportunity’ when: attention rises to a problem, a feasible solution is available, and policymakers have the motive to select it.
Policy entrepreneurs seem to have particular skills or strategies, to frame issues well, build networks, and lead coalitions. However, Kingdon described them as ‘surfers waiting for the big wave’, which suggests that their environment is more important than their action. He was describing a large US political system in which different actors tended to be involved in different ‘streams’ or parts of policymaking (such as a President raising problems, and a bureaucracy coordinating solutions), no one was powerful enough to bring them together, and it took a lot of time for policy solutions to ‘soften’ or change enough to become acceptable to many actors in the system.
In modern studies, we can see some key differences: policymaking at a smaller scale seems to allow ‘entrepreneurs’ more opportunities to propose solutions and generate attention to problems; and, it seems possible to short-circuit the need to ‘soften’ policies by finding sympathetic audiences in different ‘venues’ or importing solutions that have a reputation for working elsewhere. Yet, most of MSA’s abstract insights remain ‘universal’, inviting us to adopt a counterintuitive strategy of producing solutions then chasing problems, and focus on framing and persuasion to reduce ambiguity and generate demand for evidence, rather than producing more and more evidence to reduce uncertainty in the hope that scientific evidence will win the day or speak for itself.
We often use the metaphor of ‘tools’ to describe the ways in which people use public policy analysis. For some, the suggestion is that – like a hammer and chisel – anyone could pick them up and use them. Yet, let’s think about that metaphor some more:
Anyone can use a hammer and chisel, but many people lop of their fingers or break things while doing so.
You use a hammer and chisel for a particular purpose, such as to create a sculpture. We can all whack a bit of stone with a blunt object, but it takes skill to turn it into something worth your attention.
Many tools require training before you should use them: power tools, lasers, MRIs, the screws to insert frames into broken bones, and so on.
My argument is this: you wouldn’t trust a political scientist to make you a piece of art, fix your window, do your laser eyesight correction, or scan your brain, because it is generally not a good idea to pick up and use these tools without training. So, have a quick think about who you would trust with policy tools if they just picked them out of the shed and used them for the first time.
What sort of training do you need to use policy analysis tools effectively?
Let me give you three examples, bearing in mind that the tools metaphor will get annoying soon:
It offers a simple way to turn evidence into policy: you use evidence to identify a problem, provide a range of feasible evidence-based solutions, choose the best solution, then legitimise, implement, and evaluate the solution. However, you soon find that the cycle is the equivalent of, say, a manual carpet sweeper. The technology has moved on, and we now have a much improved understanding of the policy process. In empirical policy analysis, the cycle remains as a way to begin our discussion before identifying more useful concepts and theories.
Using the tools metaphor, you need regular training to know about the state of the art of the technology we use.
It too offers a simple way into the subject. Further, it remains a well-respected and much-used tool for analysis. Let’s say it is like the X-ray. It has been used for decades and it remains a key tool in medicine (and security). You need some training to operate it and, crucially, your training would not stop at ‘here is how we used it in the 1980s’.
In other words, many people pick up Kingdon’s classic book and apply its simple insights without much reference to 3 decades of conceptual advance (much contemporary MSA was developed by other people) and hundreds of other empirical applications.
Using the tools metaphor, you need regular training to keep up to date with the ways in which people use the technology.
This is a fairly common exercise: people pick and choose concepts, adapt them to produce their models, and apply different concepts in different ways. If you are optimistic, you will think of something like a Dremel which has the same starting point/ base unit and dozens of compatible attachments. If, like me, you are not so optimistic, you imagine a frying pan radio or an X-ray machine glued onto the side of an MRI. It can be fruitful to combine the insights of concepts and theories, but not without thinking about the trade-offs and the compatibility between concepts (which prompts some scholars to identify one kind of tool to replace another).
Using the tools metaphor, you need regular training to know how compatible each tool is with the other, and if one is used to replace another.
This last point is crucial if you want to go beyond using a tool for a one-off project, to compare your insights and lessons with other people. Many people will want to know how you fared when you used the same tools/ approach/ language as them, and you can learn from each other’s experiences. Indeed, the aim of theory is to produce comparable and, if possible, generalisable insights, Relatively few people will want to learn from someone who glues an X-ray to an MRI, and it will be difficult to generalise from the experience.
The upshot is that you can indeed pick up some policy analysis tools and use them to improve your understanding of the world. Indeed, I encourage you to do so in this series of posts which outlines the concepts you are most likely to see stocked in Home Depot.
However, I also suggest that you use them as the first step of your project (or engage the help of more qualified people), since most of these concepts come with a training manual that can take years to read.
Think of policy theory as an antidote to our fixation on elections, as a focus on what happens in between. We often point out that elections can produce a change in the governing party without prompting major changes in policy and policymaking, partly because most policy is processed at a level of government that receives very little attention from elected policymakers. Elections matter but, in policy studies, they do not represent the centre of the universe.
Imagine a simple definition: ‘the sum total of government action, from signals of intent to the final outcomes’. Then consider these questions. Does policy include what policymakers say they will do (e.g. in manifestos) as well as what they actually do? Does it include the policy outcome if it does not match the original aim? What is ‘the government’ and does it include elected and unelected policymakers? Does public policy include what policymakers decide to not do? Is it still ‘public policy’ when neither the public nor elected policymakers have the ability to pay attention to what goes on in their name?
Usually we know that something has changed because the government has passed legislation, but policy is so much more: spending, economic penalties or incentives (taxes and subsidies), social security payments and sanctions, formal and informal regulations, public education, organisations and staffing, and so on. So, we need to sum up this mix of policies, asking: is there an overall and coherent aim, or a jumble of policy instruments? Can we agree on the motives of policymakers when making these policies? Does policy impact seem different when viewed from the ‘top’ or the ‘bottom’? Does our conclusion change when we change statistical measures?
We know that policy evaluation is political because left/right wing political parties and commentators argue as much about a government’s success as its choices. Yet, it cannot be solved by scientists identifying objective or technical measures of success, because there is political choice in the measures we use and much debate about the best measures. Measurement also involves (frequently) a highly imperfect proxy, such as by using waiting times to measure the effectiveness of a health service. We should also note the importance of perspective: should we measure success in terms of the aims of elected policymakers, the organisations carrying out policy, or the people who are most affected? What if many policymakers were involved, or their aims were not clear? What if their aim was to remain popular, or have an easy time in the legislature, not to improve people’s lives? What if it improved the lives of some, but hurt others?
Imagine this simple advice to policymakers: identify your aims, identify policies to achieve those aims, select a policy measure, ensure that the selection is ‘legitimised’ by the population or its legislature, identify the necessary resources, implement, and then evaluate the policy. If only life were so simple. Instead, think of policymaking as a collection of thousands of policy cycles, which interact with each other to produce much less predictable outcomes. Then note that it is often impossible in practice to know when one stage begins and another ends. Finally, imagine that the order of stages is completely messed up, such as when we have a solution long before a problem arises.
A classic reference point is the ‘ideal-type’ of comprehensive (or synoptic) rationality which helps elected policymakers translate their values into policy in a straightforward manner. They have a clear, coherent and rank-ordered set of policy preferences which neutral organizations carry out on their behalf. We can separate policymaker values from organizational facts. There are clear-cut and ordered stages to the process and analysis of the policymaking context is comprehensive. This allows policymakers to maximize the benefits of policy to society in much the same way that an individual maximizes her own utility. In the real world, we identify ‘bounded rationality’, challenge all of the assumptions of comprehensive rationality, and wonder what happens next. The classic debate focused on the links between bounded rationality and incrementalism. Our current focus is on ‘rational’ and ‘irrational’ responses to the need to make decisions quickly without comprehensive information: limiting their options, and restricting information searches to sources they trust, to make their task manageable; but also making quick decisions by relying on instinct, gut, emotion, beliefs, ideology, and habits.
Most policy theories use the word ‘actor’ simply to describe the ability of people and organisations to deliberate and act to make choices. Many talk about the large number of actors involved in policymaking, at each level and across many levels of policymaking. Some discuss a shift, in many countries since the early post-war period, from centralized and exclusive policymaking, towards a fragmented multi-level system involving a much larger number of actors
In political science, ‘institution’ refers to the rules, ‘norms’, and other practices that influence policymaking behaviour. Some rules are visible or widely understood, such as constitutions. Others are less visible, such as the ‘rules of the game’ in politics, or organisational ‘cultures’. So, for example, ‘majoritarian’ and ‘consensus’ democracies could have very different formal rules but operate in very similar ways in practice. These rules develop in different ways in many parts of government, prompting us to consider what happens when many different actors develop different expectations of politics and policymaking. For example, it might help explain a gap between policies made in one organisation and implemented by another. It might cause government policy to be contradictory, when many different organisations produce their own policies without coordinating with others. Or, governments may contribute to a convoluted statute book by adding to laws and regulations without thinking how they all fit together.
Put simply, ‘policy network’ describes the relationships between policymakers, in formal positions of power, and the actors who seek to influence them. It can also describe a notional venue – a ‘subsystem’ – in which this interaction takes place. Although the network concept is crucial to most policy theories, it can be described using very different concepts,and with reference to different political systems. For example, in the UK, we might describe networks as a consequence of bounded rationality: elected policymakers delegate responsibility to civil servants who, in turn, rely on specialist organisations for information and advice. Those organisations trade information for access to government. This process often becomes routine: civil servants begin to trust and rely on certain organisations and they form meaningful relationships. If so, most public policy is conducted primarily through small and specialist ‘policy communities’ that process issues at a level of government not particularly visible to the public, and with minimal senior policymaker involvement. Network theories tend to consider the key implications, including a tendency for governments to contain ‘silos’ and struggle to ‘join up’ government when policy is made in so many different places
Policy theory is about the relationship between power and ideas (or shared beliefs). These terms are difficult to disentangle, even analytically, because people often exercise power by influencing the beliefs of others. Classic power debates inform current discussions of ‘agenda setting’ and ‘framing’. Debates began with the idea that we could identify the powerful by examining ‘key political choices’: the powerful would win and benefit from the outcomes at the expense of other actors. The debate developed into discussions of major barriers to the ‘key choices’ stage: actors may exercise power to persuade/ reinforce the popular belief that the government should not get involved, or to keep an issue off a government agenda by drawing attention to other issues. This ability to persuade depends on the resources of actors, but also the beliefs of the actors they seek to influence.
Context’ describes the policy conditions that policymakers take into account when identifying problems, such as a country’s geography, demographic profile, economy, and social attitudes. This wider context is in addition to the ‘institutional’ context, when governments inherit the laws and organisations of their predecessors. Important ‘game changing’ events can be routine, such as when elections produce new governments with new ideas, or unanticipated, such as when crises or major technological changes prompt policymakers to reconsider existing policies. In each case, we should consider the extent to which policymaking is in the control of policymakers. In some cases, the role of context seems irresistible – think for example of a ‘demographic timebomb’ – but governments show that they can ignore such issues for long periods of time or, at least, decide how and why they are important. This question of policymaker control is also explored in discussions of ‘complexity theory’, which highlights the unpredictability of policymaking, limited central government control, and a tendency for policy outcomes to ‘emerge’ from activity at local levels.
For example, policymakers often recognise that they make decisions within an unpredictable and messy, not ‘linear’, process. Many might even accept the implications of complexity theory, which suggests that they should seek new ways to act when they recognise their limitations: use trial and error; keep changing policies to suit new conditions; devolve and share power with the local actors able to respond to local areas; and so on. Yet, such pragmatic advice goes against the idea of Westminster-style democratic accountability, in which ministers remain accountable to Parliament and the public because you know who is in charge and, therefore, who to blame. Or, for example, we might use policy theory to inform current discussions of evidence-based policymaking, saying to scientists that they will only be influential if they go beyond the evidence to make manipulative emotional appeals.
John Kingdon published his Agendas, Alternatives, and Public Policies in 1984. What has happened since then? Put simply, it is now a classic text, and it took off in a way that Kingdon did not expect. Put less simply, it contributed to the intellectual development of policy theory and inspired a huge number of studies under the banner of ‘multiple streams analysis’ (or the ‘multiple streams approach’, MSA).
In our PSJ article, Michael Jones and I sum up this theoretical and empirical contribution and give some advice about how to produce effective MSA analysis.
Kingdon identifies many elements of the policy process that we describe as ‘universal’ because they are abstract enough to apply to any case study.
Ambiguity and competition for attention.
There are many ways to understand and frame any policy problem, but the policy agenda can often be dominated by one ‘frame’.
There are many problems to solve, but few reach the top of the policy agenda.
There are many possible solutions to problems, but very few gain attention and even fewer gain support.
Decision-making processes are neither ‘comprehensively rational’ nor ‘linear’.
New information is difficult to gather and subject to manipulation.
Actors have limited resources such as time and cognitive ability. This limitation forces people to make choices before they have considered all possibilities and made sure that their preferences are clear.
The policy process does not follow a policy cycle with ordered stages, in which (i) a policymaker identifies a problem, (ii) a bureaucracy produces many possible solutions, and (iii) the policymaker selects the best solution according to her aims and values.
These ‘universal’ insights underpin MSA’s specific contribution, in which Kingdon draws on the ‘garbage can model’ to suggest that we think of these three ‘stages’ (metaphorically) as independent streams which must come together at the same time, during a ‘window of opportunity’ before any major policy change will take place:
Problem stream – attention lurches to a policy problem.
Policy stream – a solution to that problem is available.
Politics stream – policymakers have the motive and opportunity to turn it into policy.
MSA’s intellectual contribution: 2. New theories and perspectives.
Let’s take one example of Kingdon’s influence: on the early development of punctuated equilibrium theory (PET). In their own ways, MSA and PET are both ‘evolutionary’ theories, although they identify different kinds of evolutionary metaphors or processes, and present somewhat different implications:
Kingdon uses the evolutionary metaphor partly to help explain slow and gradual policy development despite lurches of attention and the importance of windows of opportunity. Note the importance of the idea of ‘feasibility’ and ‘softening’, as potential policy solutions emerge from the ‘policy primeval soup’. Kingdon is describing the slow progress of an idea towards acceptability within the policy community, which challenges the notion that policies will change whenever attention lurches to a new problem. On the contrary, a feasible solution must exist, and these solutions take a lot of time to become both technically and politically feasible, before policymakers develop the motive and opportunity to adopt them.
Baumgartner and Jones identify the conditions under which Kingdon’s picture of slow progress, producing ‘partial mutations’ should be replaced by their identification of fast, disruptive, ‘pure mutation’. For example, major ‘policy punctuations’ may occur when issues break out of one policymaking ‘venue’. In such cases, more radical change may be acceptable to the policymakers – in other venues – that are less committed to existing policies and, therefore, less likely to select a policy solution only when it has been ‘softened’.
MSA’s empirical contribution: 1. How useful is the metaphor?
Michael and I identify a blessing and a curse, related to two aspects of Kingdon’s original work:
The barriers to entry are low. If you are looking for an easy way into policy theory, you can read some of Kingdon’s book and feel you have gained some insight.
The metaphor is flexible. You don’t have to learn a huge codebook or set of rules before you dive into empirical analysis.
The blessing is that both factors allow a lot of material to be produced in diverse and perhaps innovative ways. The curse is that it is difficult to see the accumulated results from all that effort. If the MSA is there to help explain one case, and one case only, then all is well. If we want more – to compare a lot of cases in a meaningful way – we have a problem.
MSA’s empirical contribution: 2. How have other scholars used the metaphor?
Michael Jones and his colleagues identified a huge number of MSA studies: over 300 applications, in over 40 countries, in 10 years. However, they also identify a high proportion of theoretical superficiality: scholars mention Kingdon, but do not go into much detail on the meaning of key MSA concepts, or explain how they used those concepts in a meaningful way to explain policy or policymaking.
Michael and I zoomed in to focus on the ‘state of the art’, to see how the best studies used MSA. We found some interesting work, particularly in studies which extended Kingdon’s original focus on the US federal government (in the 1980s) to subnational and supranational studies, and used MSA to explain developments in many other countries. The best work identified how the MSA related to wider policy theory discussions and/or how we might adapt MSA to deal with new cases. However, we also found a lot of applications which made cursory reference to theory or the MSA literature, or studies which used MSA largely as a way to identify their own models.
It all adds up to a lot of activity but it is difficult to know how to sum up its value. The flexibility of the MSA has allowed people to take it in all sorts of directions, but also to use it in a way that is difficult to relate to Kingdon’s original study or important new developments (put forward by scholars such as Zahariadis).
Where do we go from here? Some simple rules for you to consider.
So, we propose three simple rules to help maintain MSA flexibility but allow us to accumulate empirical insights or encourage conceptual development: demonstrate proficiency with MSA; speak to MSA; and, speak to broader policy research.
In other words, a lot has been written about MSA and policy theory since 1984. The world has changed, and so too have the ways in which we describe it. So, put simply, it would be weird if people continued to produce scholarly research based simply on one book written in the 80s and little else (you might be surprised about how much of this approach we found, and how few people explained MSA concepts before presenting their empirical analysis).
We don’t call for a set of rigid rules to allow systematic comparison (although I really like the suggestion by a colleague, presented with tongue firmly in cheek, that we have become the ‘multiple streams Taliban’). Instead, at the very least, we encourage people not to submit Kingdon-inspired articles for review until they have read and digested a lot of the MSA literature. That way, we’ll be able to go beyond the sense that we are all using the same conceptual descriptions without knowing if we mean the same thing or if my results can be compared usefully with yours.
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.
Policymaking in Scotland #POLU9SP
A series of lectures on policymaking, written up as blog posts with further reading.