Policy in 500 Words: Peter Hall’s policy paradigms

Several 500 Word and 1000 Word (a, b, c) posts try to define and measure policy change.

Most studies agree that policymaking systems produce huge amounts of minor change and rare instances of radical change, but not how to explain these patterns. For example:

• Debates on incrementalism questioned if radical change could be managed via non-radical steps.
• Punctuated equilibrium theory describes policy change as a function of disproportionately low or high attention to problems, and akin to the frequency of earthquakes (a huge number of tiny changes, and more major changes than we would see in a ‘normal distribution’).

One of the most famous accounts of major policy change is by Peter Hall. ‘Policy paradigms’ help explain a tendency towards inertia, punctuated rarely by radical change (compare with discussions of path dependence and critical junctures).

A policy paradigm is a dominant and often taken-for-granted worldview (or collection of beliefs) about: policy goals, the nature of a policy problem, and the instruments to address it.

Paradigms can operate for long periods, subject to minimal challenge or defended successfully during events that call current policies into question. Adherence to a paradigm produces two ‘orders’ of change:

• 1^st order: frequent routine bureaucratic changes to instruments while maintaining policy goals.
• 2^nd order: less frequent, non-routine changes (or use of new instruments) while maintaining policy goals.

Radical and rare – 3^rd order – policy change may only follow a crisis in which policymakers cannot solve a policy problem or explain why policy is failing. It prompts a reappraisal and rejection of the dominant paradigm, by a new government with new ways of thinking and/or a government rejecting current experts in favour of new ones. Hall’s example was of rapid paradigm shift in UK economic policy – from ‘Keynesianism’ to ‘Monetarism’ – within very few years.

Hall’s account prompted two different debates:

1. Some describe Hall’s case study as unusual.

Many scholars produced different phrases to describe a more likely pattern of (a) non-radical policy changes contributing to (b) long-term paradigm change and (c) institutional change, perhaps over decades. They include: ‘gradual change with transformative results’ and ‘punctuated evolution’ (see also 1000 Words: Evolution).

2. Some describe Hall’s case study as inaccurate.

This UK paradigm change did not actually happen. Instead, there was:

(a) A sudden and profound policy change that did not represent a paradigm shift (the UK experiment with Monetarism was short-lived).

(b) A series of less radical changes that produced paradigm change over decades: from Keynesianism to ‘neo-Keynesianism’, or from state intervention to neoliberalism (such as to foster economic growth via private rather than public borrowing and spending)

These debates connect strongly to issues in policy analysis, particularly if analysts seek transformative policy change to challenge unequal and unfair outcomes (such as in relation to racism or the climate crisis):

1. Is paradigm change generally only possible over decades?
2. How will we know if this transformation is actually taking place and here to stay (if even the best of us can be fooled by temporary developments)?

See also:

1. Beware the use of the word ‘evolution‘

2. This focus on the endurance of policy instrument change connects to studies of policy success (see Great Policy Successes).

3. Paul Cairney and Chris Weible (2015) ‘Comparing and Contrasting Peter Hall’s Paradigms and Ideas with the Advocacy Coalition Framework’ in (eds) M. Howlett and J. Hogan Policy Paradigms in Theory and Practice (Basingstoke: Palgrave) PDF

Policy Concepts in 1000 Words: Policy Change

Christopher M. Weible & Paul Cairney

Policy change is a central concern of policy research and practice. Some want to explain it. Some want to achieve it.

Explanation begins with the ‘what is policy?’ question, since we cannot observe something without defining it.  However, we soon find that: no single definition can capture all forms of policy change, the absence of policy change is often more important, and important changes can be found in the everyday application of rules and practices related to public policies.  Further, studies often focus on changes in public policies without a focus on societal outcomes or effects.

One pragmatic solution is to define public policies as decisions made by policymakers or policymaking venues such as legislatures, executives, regulatory agencies, courts, national and local governments (and, in some countries, citizen-led policy changes).  Focusing on this type of policy change, two major categories of insights unfold:

1. Patterns of Policy Change: incrementalism, punctuations, and drift

A focus on decisions suggests that most policymaking venues contribute primarily to incremental policy change, or often show little change from year to year but with the occasional punctuation of major policymaking activity.  This pattern reflects a frequent story about governments doing too much or nothing at all. The logic is that policymaking attention is always limited, so a focus on one issue in any policymaking venue requires minimal focus on others.  Then, when attention shifts, we see instances of major policy change as attempts to compensate (or overcompensate) for what was ignored for too long.

An additional focus on institutions highlights factors such as policy drift, to describe slow and small changes to policies, or to aspects of their design, that accumulate eventually and can have huge impacts on outcomes and society.  These drifts often happen outside the public eye or are overlooked as being negative but trivial.  For example, rising economic inequality in the US resulted from the slow accumulation of policies – related to labor unions, tax structures, and corporate governance – as well as globalization and labor-saving technologies.

2. Factors Associated with Policy Change

Many factors help us understand instances of policy change. We can separate them analytically (as below) but, in practice, they occur simultaneously or sequentially, and can reinforce or stifle each other.

Context

Context includes history, biophysical conditions, socio-economic conditions, culture, and basic institutional structures (such as a constitution).  For example, historical and geographic conditions are often viewed as funneling or constraining the type of policy decisions made by a government.

Events 

Policymaking venues are often described as being resistant to change or in a state of equilibrium of competing political forces.  As a result, one common explanation for change is a focusing event or shock.  Events by themselves don’t create policy change. Rather, they present an opportunity for people or coalitions to exploit.   Focusing events might include disasters or crises, tragic incidents, a terrorist attack, disruptive changes in technology, or more routine events such as elections. Events may have tangible qualities, but studies tend to highlight the ways in which people frame events to construct their meaning and implications for policy.

Public Opinion 

The relationship between public opinion and policy change is a difficult one to assess.  Some research shows that the preferences of the general public only matter when they coincide with the preferences of the elite or major interest groups.  Or, it matters only when the topic is salient and the public is paying attention. Little evidence suggests that public opinion matters when few are paying attention.  Others describe public opinion as setting the boundaries within which the government operates.

Learning

Learning is a process of updating understandings of the world in response to signals from the environment.  Learning is a political activity rather than simply a technical exercise in which people learn from teachers. Learning could involve becoming aware of the severity of a policy problem, evaluating outcomes to determine if a government intervention works, and learning to trust an opponent and reach compromise. For example, certain types of rules in a collaborative process can shape the ways in which individuals gain new knowledge and change their views about the scientific evidence informing a problem.

Diffusion of Ideas 

Sometimes governments learn from or transfer policies from other governments. For example, in collections of policymaking venues (such as US state governments or EU member states) it is common for one venue to adopt a policy and prompt this policy to spread across other venues in a process of diffusion.  There are many explanations for diffusion including learning, a response to competition, mimicking, and coercion. In each case, the explanation for policy change comes from an external impetus and an internal context.

Champions and Political Associations

All policy change is driven, to some extent, by individual or group agency.  Key players include public policy champions in the form of policy entrepreneurs or in groups of government and/or non-government entities in the form of coalitions, social movements, epistemic communities, and political parties.  In each case, individuals or organizations mobilize resources, capitalize on opportunities, and apply pressure to formulate and adopt public policies.

 

The presence of these factors does not always lead to policy change, and no single study can capture a full explanation of policy change. Instead, many quantitative studies focus on multiple instances of policy change and are often broad in geographic scope or spans of time, while many case study or qualitative studies focus intensely on a very particular instance of policy change. Both approaches are essential.

See also:

Policy in 500 Words: what is public policy and why does it matter?

Policy in 500 Words: how much does policy change?

Policy Concepts in 1000 Words: Policy change and measurement (podcast download)

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

 

 

Policy Analysis in 750 words: William Dunn (2017) Public Policy Analysis

Please see the Policy Analysis in 750 words series overview before reading the summary. This book is a whopper, with almost 500 pages and 101 (excellent) discussions of methods, so 800 words over budget seems OK to me. If you disagree, just read every second word.  By the time you reach the cat hanging in there baby you are about 300 (150) words away from the end.

William Dunn (2017) Public Policy Analysis 6^th Ed. (Routledge)

‘Policy analysis is a process of multidisciplinary inquiry aiming at the creation, critical assessment, and communication of policy-relevant knowledge … to solve practical problems … Its practitioners are free to choose among a range of scientific methods, qualitative as well as quantitative, and philosophies of science, so long as these yield reliable knowledge’ (Dunn, 2017: 2-3).

Dunn (2017: 4) describes policy analysis as pragmatic and eclectic. It involves synthesising policy relevant (‘usable’) knowledge, and combining it with experience and ‘practical wisdom’, to help solve problems with analysis that people can trust.

This exercise is ‘descriptive’, to define problems, and ‘normative’, to decide how the world should be and how solutions get us there (as opposed to policy studies/ research seeking primarily to explain what happens).

Dunn contrasts the ‘art and craft’ of policy analysts with other practices, including:

1. The idea of ‘best practice’ characterised by 5-step plans.

• In practice, analysis is influenced by: the cognitive shortcuts that analysts use to gather information; the role they perform in an organisation; the time constraints and incentive structures in organisations and political systems; the expectations and standards of their profession; and, the need to work with teams consisting of many professions/ disciplines (2017: 15-6)
• The cost (in terms of time and resources) of conducting multiple research and analytical methods is high, and highly constrained in political environments (2017: 17-8; compare with Lindblom)

2. The too-narrow idea of evidence-based policymaking

• The naïve attachment to ‘facts speak for themselves’ or ‘knowledge for its own sake’ undermines a researcher’s ability to adapt well to the evidence-demands of policymakers (2017: 68; 4 compare with Why don’t policymakers listen to your evidence?).

To produce ‘policy-relevant knowledge’ requires us to ask five questions before (Qs1-3) and after (Qs4-5) policy intervention (2017: 5-7; 54-6):

1. What is the policy problem to be solved?

• For example, identify its severity, urgency, cause, and our ability to solve it.
• Don’t define the wrong problem, such as by oversimplifying or defining it with insufficient knowledge.
• Key aspects of problems including ‘interdependency’ (each problem is inseparable from a host of others, and all problems may be greater than the sum of their parts), ‘subjectivity’ and ‘artificiality’ (people define problems), ‘instability’ (problems change rather than being solved), and ‘hierarchy’ (which level or type of government is responsible) (2017: 70; 75).
• Problems vary in terms of how many relevant policymakers are involved, how many solutions are on the agenda, the level of value conflict, and the unpredictability of outcomes (high levels suggest ‘wicked’ problems, and low levels ‘tame’) (2017: 75)
• ‘Problem-structuring methods’ are crucial, to: compare ways to define or interpret a problem, and ward against making too many assumptions about its nature and cause; produce models of cause-and-effect; and make a problem seem solve-able, such as by placing boundaries on its coverage. These methods foster creativity, which is useful when issues seem new and ambiguous, or new solutions are in demand (2017: 54; 69; 77; 81-107).
• Problem definition draws on evidence, but is primarily the exercise of power to reduce ambiguity through argumentation, such as when defining poverty as the fault of the poor, the elite, the government, or social structures (2017: 79; see Stone).

2. What effect will each potential policy solution have?

• Many ‘forecasting’ methods can help provide ‘plausible’ predictions about the future effects of current/ alternative policies (Chapter 4 contains a huge number of methods).
• ‘Creativity, insight, and the use of tacit knowledge’ may also be helpful (2017: 55).
• However, even the most-effective expert/ theory-based methods to extrapolate from the past are flawed, and it is important to communicate levels of uncertainty (2017: 118-23; see Spiegelhalter).

3. Which solutions should we choose, and why?

• ‘Prescription’ methods help provide a consistent way to compare each potential solution, in terms of its feasibility and predicted outcome, rather than decide too quickly that one is superior (2017: 55; 190-2; 220-42).
• They help to combine (a) an estimate of each policy alternative’s outcome with (b) a normative assessment.
• Normative assessments are based on values such as ‘equality, efficiency, security, democracy, enlightenment’ and beliefs about the preferable balance between state, communal, and market/ individual solutions (2017: 6; 205 see Weimer & Vining, Meltzer & Schwartz, and Stone on the meaning of these values).
• For example, cost benefit analysis (CBA) is an established – but problematic – economics method based on finding one metric – such as a $ value – to predict and compare outcomes (2017: 209-17; compare Weimer & Vining, Meltzer & Schwartz, and Stone)
• Cost effectiveness analysis uses a $ value for costs, but compared with other units of measurement for benefits (such as outputs per $) (2017: 217-9)
• Although such methods help us combine information and values to compare choices, note the inescapable role of power to decide whose values (and which outcomes, affecting whom) matter (2017: 204)

4. What were the policy outcomes?

• ‘Monitoring’ methods help identify (say): levels of compliance with regulations, if resources and services reach ‘target groups’, if money is spent correctly (such as on clearly defined ‘inputs’ such as public sector wages), and if we can make a causal link between the policy inputs/ activities/ outputs and outcomes (2017: 56; 251-5)
• Monitoring is crucial because it is so difficult to predict policy success, and unintended consequences are almost inevitable (2017: 250).
• However, the data gathered are usually no more than proxy indicators of outcomes. Further, the choice of indicators reflect what is available, ‘particular social values’, and ‘the political biases of analysts’ (2017: 262)
• The idea of ‘evidence based policy’ is linked strongly to the use of experiments and systematic review to identify causality (2017: 273-6; compare with trial-and-error learning in Gigerenzer, complexity theory, and Lindblom).

5. Did the policy solution work as intended? Did it improve policy outcomes?

• Although we frame policy interventions as ‘solutions’, few problems are ‘solved’. Instead, try to measure the outcomes and the contribution of your solution, and note that evaluations of success and ‘improvement’ are contested (2017: 57; 332-41).  
• Policy evaluation is not an objective process in which we can separate facts from values.
• Rather, values and beliefs are part of the criteria we use to gauge success (and even their meaning is contested – 2017: 322-32).
• We can gather facts about the policy process, and the impacts of policy on people, but this information has little meaning until we decide whose experiences matter.

Overall, the idea of ‘ex ante’ (forecasting) policy analysis is a little misleading, since policymaking is continuous, and evaluations of past choices inform current choices.

Policy analysis methods are ‘interdependent’, and ‘knowledge transformations’ describes the impact of knowledge regarding one question on the other four (2017: 7-13; contrast with Meltzer & Schwartz, Thissen & Walker).

Developing arguments and communicating effectively

Dunn (2017: 19-21; 348-54; 392) argues that ‘policy argumentation’ and the ‘communication of policy-relevant knowledge’ are central to policymaking’ (See Chapter 9 and Appendices 1-4 for advice on how to write briefs, memos, and executive summaries and prepare oral testimony).

He identifies seven elements of a ‘policy argument’ (2017: 19-21; 348-54), including:

• The claim itself, such as a description (size, cause) or evaluation (importance, urgency) of a problem, and prescription of a solution
• The things that support it (including reasoning, knowledge, authority)
• Incorporating the things that could undermine it (including any ‘qualifier’, the communication of uncertainty about current knowledge, and counter-arguments).

The key stages of communication (2017: 392-7; 405; 432) include:

1. ‘Analysis’, focusing on ‘technical quality’ (of the information and methods used to gather it), meeting client expectations, challenging the ‘status quo’, albeit while dealing with ‘political and organizational constraints’ and suggesting something that can actually be done.
2. ‘Documentation’, focusing on synthesising information from many sources, organising it into a coherent argument, translating from jargon or a technical language, simplifying, summarising, and producing user-friendly visuals.
3. ‘Utilization’, by making sure that (a) communications are tailored to the audience (its size, existing knowledge of policy and methods, attitude to analysts, and openness to challenge), and (b) the process is ‘interactive’ to help analysts and their audiences learn from each other.

 

 

Policy analysis and policy theory: systems thinking, evidence based policymaking, and policy cycles

Dunn (2017: 31-40) situates this discussion within a brief history of policy analysis, which culminated in new ways to express old ambitions, such as to:

1. Use ‘systems thinking’, to understand the interdependence between many elements in complex policymaking systems (see also socio-technical and socio-ecological systems).

• Note the huge difference between (a) policy analysis discussions of ‘systems thinking’ built on the hope that if we can understand them we can direct them, and (b) policy theory discussions that emphasise ‘emergence’ in the absence of central control (and presence of multi-centric policymaking).
• Also note that Dunn (2017: 73) describes policy problems – rather than policymaking – as complex systems. I’ll write another post (short, I promise) on the many different (and confusing) ways to use the language of complexity.

2. Promote ‘evidence based policy’, as the new way to describe an old desire for ‘technocratic’ policymaking that accentuates scientific evidence and downplays politics and values (see also 2017: 60-4).

In that context, see Dunn’s (47-52) discussion of comprehensive versus bounded rationality:

• Note the idea of ‘erotetic rationality’ in which people deal with their lack of knowledge of a complex world by giving up on the idea of certainty (accepting their ‘ignorance’), in favour of a continuous process of ‘questioning and answering’.
• This approach is a pragmatic response to the lack of order and predictability of policymaking systems, which limits the effectiveness of a rigid attachment to ‘rational’ 5 step policy analyses (compare with Meltzer & Schwartz).

Dunn (2017: 41-7) also provides an unusually useful discussion of the policy cycle. Rather than seeing it as a mythical series of orderly stages, Dunn highlights:

1. Lasswell’s original discussion of policymaking functions (or functional requirements of policy analysis, not actual stages to observe), including: ‘intelligence’ (gathering knowledge), ‘promotion’ (persuasion and argumentation while defining problems), ‘prescription’, ‘invocation’ and ‘application’ (to use authority to make sure that policy is made and carried out), and ‘appraisal’ (2017: 42-3).
2. The constant interaction between all notional ‘stages’ rather than a linear process: attention to a policy problem fluctuates, actors propose and adopt solutions continuously, actors are making policy (and feeding back on its success) as they implement, evaluation (of policy success) is not a single-shot document, and previous policies set the agenda for new policy (2017: 44-5).

In that context, it is no surprise that the impact of a single policy analyst is usually minimal (2017: 57). Sorry to break it to you. Hang in there, baby.

 

Can A Government Really Take Control Of Public Policy?

This post first appeared on the MIHE blog to help sell my book.

During elections, many future leaders give the impression that they will take control of public policy. They promise major policy change and give little indication that anything might stand in their way.

This image has been a major feature of Donald Trump’s rhetoric on his US Presidency. It has also been a feature of campaigns for the UK withdrawal from the European Union (‘Brexit’) to allow its leaders to take back control of policy and policymaking. According to this narrative, Brexit would allow (a) the UK government to make profound changes to immigration and spending, and (b) Parliament and the public to hold the UK government directly to account, in contrast to a distant EU policy process less subject to direct British scrutiny.

Such promises are built on the false image of a single ‘centre’ of government, in which a small number of elected policymakers take responsibility for policy outcomes. This way of thinking is rejected continuously in the modern literature. Instead, policymaking is ‘multi-centric’: responsibility for policy outcomes is spread across many levels and types of government (‘centres’), and shared with organisations outside of government, to the extent that it is not possible to simply know who is in charge and to blame. This arrangement helps explain why leaders promise major policy change but most outcomes represent a minor departure from the status quo.

Some studies of politics relate this arrangement to the choice to share power across many centres. In the US, a written constitution ensures power sharing across different branches (executive, legislative, judicial) and between federal and state or local jurisdictions. In the UK, central government has long shared power with EU, devolved, and local policymaking organisations.

However, policy theories show that most aspects of multi-centric governance are necessary. The public policy literature provides many ways to describe such policy processes, but two are particularly useful.

The first approach is to explain the diffusion of power with reference to an enduring logic of policymaking, as follows:

• The size and scope of the state is so large that it is always in danger of becoming unmanageable. Policymakers manage complexity by breaking the state’s component parts into policy sectors and sub-sectors, with power spread across many parts of government.
• Elected policymakers can only pay attention to a tiny proportion of issues for which they are responsible. They pay attention to a small number and ignore the rest. They delegate policymaking responsibility to other actors such as bureaucrats, often at low levels of government.
• At this level of government and specialisation, bureaucrats rely on specialist organisations for information and advice. Those organisations trade that information/advice and other resources for access to, and influence within, the government.
• 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.

This description suggests that senior elected politicians are less important than people think, their impact on policy is questionable, and elections may not provide major changes in policy. Most decisions are taken in their name but without their intervention.

A second, more general, approach is to show that elected politicians deal with such limitations by combining cognition and emotion to make choices quickly. Although such action allows them to be decisive, they occur within a policymaking environment over which governments have limited control. Government bureaucracies only have the coordinative capacity to direct policy outcomes in a small number of high priority areas. In most other cases, policymaking is spread across many venues, each with their own rules, networks, ways of seeing the world, and ways of responding to socio-economic factors and events.

In that context, we should always be sceptical when election candidates and referendum campaigners (or, in many cases, leaders of authoritarian governments) make such promises about political leadership and government control.

A more sophisticated knowledge of policy processes allows us to identify the limits to the actions of elected policymakers, and develop a healthier sense of pragmatism about the likely impact of government policy. The question of our age is not: how can governments take back control? Rather, it is: how can we hold policymakers to account in a complex system over which they have limited knowledge and even less control?

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.

2. 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’.

3. 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.

2. 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’).

3. 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).

4. 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.

 

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).

 

Policy in 500 Words: The advocacy coalition framework

Here is the ACF story.

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:

Policy actors use their beliefs to understand, and seek influence in, this world. Beliefs about how to interpret the cause of and solution to policy problems, and the role of government in solving them, act as a glue to bind actors together within coalitions.

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.

1. 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.
2. ‘Shocks’ affect the positions of coalitions within subsystems. Shocks are the combination of events and coalition responses. External shocks are prompted by events including the election of a new government with different ideas, or the effect of socioeconomic change. Internal shocks are prompted by policy failure. Both may prompt major change as members of one coalition question their beliefs in the light of new evidence. Or, another coalition may adapt more readily to its new policy environment and exploit events to gain competitive advantage.

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.

See also:

The 500 and 1000 Words series

Why Advocacy Coalitions Matter and How to Think about Them

Three lessons from a comparison of fracking policy in the UK and Switzerland

Bonus material

Scottish Independence and the Devil Shift

Image source: Weible, Heikkila, Ingold, and Fischer (2016: 6)

For a slightly longer review. https://t.co/C7M6u6RIFg

— Adam Wellstead (@amwellstead) February 11, 2019

 

 

 

Evidence-informed policymaking: context is everything

I thank James Georgalakis for inviting me to speak at the inaugural event of IDS’ new Evidence into Policy and Practice Series, and the audience for giving extra meaning to my story about the politics of ‘evidence-based based policymaking’. The talk (using powerpoint) and Q&A is here:

 

James invited me to respond to some of the challenges raised to my talk – in his summary of the event – so here it is.

I’m working on a ‘show, don’t tell’ approach, leaving some of the story open to interpretation. As a result, much of the meaning of this story – and, in particular, the focus on limiting participation – depends on the audience.

For example, consider the impact of the same story on audiences primarily focused on (a) scientific evidence and policy, or (b) participation and power.

Normally, when I talk about evidence and policy, my audience is mostly people with scientific or public health backgrounds asking why do policymakers ignore scientific evidence? I am usually invited to ruffle feathers, mostly by challenging a – remarkably prevalent – narrative that goes like this:

• We know what the best evidence is, since we have produced it with the best research methods (the ‘hierarchy of evidence’ argument).
• We have evidence on the nature of the problem and the most effective solutions (the ‘what works’ argument).
• Policymakers seems to be ignoring our evidence or failing to act proportionately (the ‘evidence-policy barriers’ argument).
• Or, they cherry-pick evidence to suit their agenda (the ‘policy based evidence’ argument).

In that context, I suggest that there are many claims to policy-relevant knowledge, policymakers have to ignore most information before making choices, and they are not in control of the policy process for which they are ostensibly in charge.

Limiting participation as a strategic aim

Then, I say to my audience that – if they are truly committed to maximising the use of scientific evidence in policy – they will need to consider how far they will go to get what they want. I use the metaphor of an ethical ladder in which each rung offers more influence in exchange for dirtier hands: tell stories and wait for opportunities, or demonise your opponents, limit participation, and humour politicians when they cherry-pick to reinforce emotional choices.

It’s ‘show don’t tell’ but I hope that the take-home point for most of the audience is that they shouldn’t focus so much on one aim – maximising the use of scientific evidence – to the detriment of other important aims, such as wider participation in politics beyond a reliance on a small number of experts. I say ‘keep your eyes on the prize’ but invite the audience to reflect on which prizes they should seek, and the trade-offs between them.

Limited participation – and ‘windows of opportunity’ – as an empirical finding

I did suggest that most policymaking happens away from the sphere of ‘exciting’ and ‘unruly’ politics. Put simply, people have to ignore almost every issue almost all of the time. Each time they focus their attention on one major issue, they must – by necessity – ignore almost all of the others.

For me, the political science story is largely about the pervasiveness of policy communities and policymaking out of the public spotlight.

The logic is as follows. Elected policymakers can only pay attention to a tiny proportion of their responsibilities. They delegate the rest to bureaucrats at lower levels of government. Bureaucrats lack specialist knowledge, and rely on other actors for information and advice. Those actors trade information for access. In many cases, they develop effective relationships based on trust and a shared understanding of the policy problem.

Trust often comes from a sense that everyone has proven to be reliable. For example, they follow norms or the ‘rules of the game’. One classic rule is to contain disputes within the policy community when actors don’t get what they want: if you complain in public, you draw external attention and internal disapproval; if not, you are more likely to get what you want next time.

For me, this is key context in which to describe common strategic concerns:

• Should you wait for a ‘window of opportunity’ for policy change? Maybe. Or, maybe it will never come because policymaking is largely insulated from view and very few issues reach the top of the policy agenda.
• Should you juggle insider and outsider strategies? Yes, some groups seem to do it well and it is possible for governments and groups to be in a major standoff in one field but close contact in another. However, each group must consider why they would do so, and the trade-offs between each strategy. For example, groups excluded from one venue may engage (perhaps successfully) in ‘venue shopping’ to get attention from another. Or, they become discredited within many venues if seen as too zealous and unwilling to compromise. Insider/outsider may seem like a false dichotomy to experienced and well-resourced groups, who engage continuously, and are able to experiment with many approaches and use trial-and-error learning. It is a more pressing choice for actors who may have only one chance to get it right and do not know what to expect.

Where is the power analysis in all of this?

I rarely use the word power directly, partly because – like ‘politics’ or ‘democracy’ – it is an ambiguous term with many interpretations (see Box 3.1). People often use it without agreeing its meaning and, if it means everything, maybe it means nothing.

However, you can find many aspects of power within our discussion. For example, insider and outsider strategies relate closely to Schattschneider’s classic discussion in which powerful groups try to ‘privatise’ issues and less powerful groups try to ‘socialise’ them. Agenda setting is about using resources to make sure issues do, or do not, reach the top of the policy agenda, and most do not.

These aspects of power sometimes play out in public, when:

• Actors engage in politics to turn their beliefs into policy. They form coalitions with actors who share their beliefs, and often romanticise their own cause and demonise their opponents.
• Actors mobilise their resources to encourage policymakers to prioritise some forms of knowledge or evidence over others (such as by valuing scientific evidence over experiential knowledge).
• They compete to identify the issues most worthy of our attention, telling stories to frame or define policy problems in ways that generate demand for their evidence.

However, they are no less important when they play out routinely:

• Governments have standard operating procedures – or institutions – to prioritise some forms of evidence and some issues routinely.
• Many policy networks operate routinely with few active members.
• Certain ideas, or ways of understanding the world and the nature of policy problems within it, becomes so dominant that they are unspoken and taken for granted as deeply held beliefs. Still, they constrain or facilitate the success of new ‘evidence based’ policy solutions.

In other words, the word ‘power’ is often hidden because the most profound forms of power often seem to be hidden.

In the context of our discussion, power comes from the ability to define some evidence as essential and other evidence as low quality or irrelevant, and therefore define some people as essential or irrelevant. It comes from defining some issues as exciting and worthy of our attention, or humdrum, specialist and only relevant to experts. It is about the subtle, unseen, and sometimes thoughtless ways in which we exercise power to harness people’s existing beliefs and dominate their attention as much as the transparent ways in which we mobilise resources to publicise issues. Therefore, to ‘maximise the use of evidence’ sounds like an innocuous collective endeavour, but it is a highly political and often hidden use of power.

See also:

I discussed these issues at a storytelling workshop organised by the OSF:

See also:

Policy in 500 Words: Power and Knowledge

The politics of evidence-based policymaking

Palgrave Communications: The politics of evidence-based policymaking

Using evidence to influence policy: Oxfam’s experience

The UK government’s imaginative use of evidence to make policy

 

Teaching evidence based policy to fly: how to deal with the politics of policy learning and transfer

This post provides (a generous amount of) background for my ANZSOG talk Teaching evidence based policy to fly: transferring sound policies across the world.

The event’s description sums up key conclusions in the literature on policy learning and policy transfer:

1. technology and ‘entrepreneurs’ help ideas spread internationally, and domestic policymakers can use them to be more informed about global policy innovation, but
2. there can be major unintended consequences to importing ideas, such as the adoption of policy solutions with poorly-evidenced success, or a broader sense of failed transportation caused by factors such as a poor fit between the aims of the exporter/importer.

In this post, I connect these conclusions to broader themes in policy studies, which suggest that:

3. policy learning and policy transfer are political processes, not ‘rational’ or technical searches for information
4. the use of evidence to spread policy innovation requires two interconnected choices: what counts as good evidence, and what role central governments should play.
5. the following ’11 question guide’ to evidence based policy transfer serves more as a way to reflect than a blueprint for action.

As usual, I suggest that we focus less on how we think we’d like to do it, and more on how people actually do it.

Policy transfer describes the use of evidence about policy in one political system to help develop policy in another. Taken at face value, it sounds like a great idea: why would a government try to reinvent the wheel when another government has shown how to do it?

Therefore, wouldn’t it be nice if I turned up to the lecture, equipped with a ‘blueprint’ for ‘evidence based’ policy transfer, and declared how to do it in a series of realistic and straightforward steps? Unfortunately, there are three main obstacles:

1. ‘Evidence based’ is a highly misleading description of the use of information in policy.
2. To transfer a policy blueprint completely, in this manner, would require all places and contexts to be the same, and for the policy process to be technocratic and apolitical.
3. There are general academic guides on how to learn lessons from others systematically – such as Richard Rose’s ‘practical guide’  – but most academic work on learning and transfer does not suggest that policymakers follow this kind of advice.

Instead, policy learning is a political process – involving the exercise of power to determine what and how to learn – and it is difficult to separate policy transfer from the wider use of evidence and ideas in policy processes.

Let’s take each of these points in turn, before reflecting on their implications for any X-step guide:

3 reasons why ‘evidence based’ does not describe policymaking

In a series of ANZSOG talks on ‘evidence based policymaking’ (EBPM), I describe three main factors, all of which are broadly relevant to transfer:

1. There are many forms of policy-relevant evidence and few policymakers adhere to a strict ‘hierarchy’ of knowledge.

Therefore, it is unclear how one government can, or should, generate evidence of another government’s policy success.

2. Policymakers must find ways to ignore most evidence – such as by combining ‘rational’ and ‘irrational’ cognitive shortcuts – to be able to act quickly.

The generation of policy transfer lessons is a highly political process in which actors adapt to this need to prioritise information while competing with each other. They exercise power to: prioritise some information and downplay the rest, define the nature of the policy problem, and evaluate the success of another government’s solutions. There is a strong possibility that policymakers will import policy solutions without knowing if, and why, they were successful.

3. They do not control the policy process in which they engage.

We should not treat ‘policy transfer’ as separate from the policy process in which policymakers and influencers engage. Rather, the evidence of international experience competes with many other sources of ideas and evidence within a complex policymaking system.

The literature on ‘policy learning’ tells a similar story

Studies of the use of evaluation evidence (perhaps to answer the question: was this policy successful?) have long described policymakers using the research process for many different purposes, from short term problem-solving and long-term enlightenment, to putting off decisions or using evidence cynically to support an existing policy.

We should therefore reject the temptation to (a) equate ‘policy learning’ with a simplistic process that we might associate with teachers transmitting facts to children, or (b) assume that adults simply change their beliefs when faced with new evidence. Rather, Dunlop and Radaelli describe policy learning as a political process in the following ways:

1.It is collective and rule-bound

Individuals combine cognition and emotion to process information, in organisations with rules that influence their motive and ability to learn, and in wider systems, in which many actors cooperate and compete to establish the rules of evidence gathering and analysis, or policymaking environments that constrain or facilitate their action.

2.’Evidence based’ is one of several types of policy learning

• Epistemic. Primarily by scientific experts transmitting knowledge to policymakers.
• Reflection. Open dialogue to incorporate diverse forms of knowledge and encourage cooperation.
• Bargaining. Actors learn how to cooperate and compete effectively.
• Hierarchy. Actors with authority learn how to impose their aims; others learn the limits to their discretion.

3.The process can be ‘dysfunctional’: driven by groupthink, limited analysis, and learning how to dominate policymaking, not improve policy.

Their analysis can produce relevant take-home points such as:

• Experts will be ineffective if they assume that policy learning is epistemic. The assumption will leave them ill-prepared to deal with bargaining.
• There is more than one legitimate way to learn, such as via deliberative processes that incorporate more perspectives and forms of knowledge.

What does the literature on transfer tell us?

‘Policy transfer’ can describe a spectrum of activity:

• driven voluntarily, by a desire to learn from the story of another government’s policy’s success. In such cases, importers use shortcuts to learning, such as by restricting their search to systems with which they have something in common (such as geography or ideology), learning via intermediaries such as ‘entrepreneurs’, or limiting their searches for evidence of success.
• driven by various forms of pressure, including encouragement by central (or supranational) governments, international norms or agreements, ‘spillover’ effects causing one system to respond to innovation by another, or demands by businesses to minimise the cost of doing business.

In that context, some of the literature focuses on warning against unsuccessful policy transfer caused by factors such as:

• Failing to generate or use enough evidence on what made the initial policy successful
• Failing to adapt that policy to local circumstances
• Failing to back policy change with sufficient resources

However, other studies highlight some major qualifications:

• If the process is about using ideas about one system to inform another, our attention may shift from ‘transfer’ to ‘translation’ or ‘transformation’, and the idea of ‘successful transfer’ makes less sense
• Transfer success is not the same as implementation success, which depends on a wider range of factors
• Nor is it the same as ‘policy success’, which can be assessed by a mix of questions to reflect political reality: did it make the government more re-electable, was the process of change relatively manageable, and did it produce intended outcomes?

The use of evidence to spread policy innovation requires a combination of profound political and governance choices

When encouraging policy diffusion within a political system, choices about: (a) what counts as ‘good’ evidence of policy success have a major connection to (b) what counts as good governance.

For example, consider these ideal-types or models in table 1:

In one scenario, we begin by relying primarily on RCT evidence (multiple international trials) and import a relatively fixed model, to ensure ‘fidelity’ to a proven intervention and allow us to measure its effect in a new context. This choice of good evidence limits the ability of subnational policymakers to adapt policy to local contexts.

In another scenario, we begin by relying primary on governance principles, such as to respect local discretion as well as incorporate practitioner and user experience as important knowledge claims. The choice of governance model relates closely to a less narrow sense of what counts as good evidence, but also a more limited ability to evaluate policy success scientifically.

In other words, the political choice to privilege some forms of evidence is difficult to separate from another political choice to privilege the role of one form of government.

Telling a policy transfer story: 11 questions to encourage successful evidence based policy transfer  

In that context, these steps to evidence-informed policy transfer serve more to encourage reflection than provide a blueprint for action. I accept that 11 is less catchy than 10.

1. What problem did policymakers say they were trying to solve, and why?
2. What solution(s) did they produce?
3. Why?

Points 1-3 represent the classic and necessary questions from policy studies: (1) ‘what is policy?’ (2)  ‘how much did policy change?’ and (3) why? Until we have a good answer, we do not know how to draw comparable lessons. Learning from another government’s policy choices is no substitute for learning from more meaningful policy change.

4. Was the project introduced in a country or region which is sufficiently comparable? Comparability can relate to the size and type of country, the nature of the problem, the aims of the borrowing/ lending government and their measures of success.

5. Was it introduced nationwide, or in a region which is sufficiently representative of the national experience (it is not an outlier)?

6. How do we account for the role of scale, and the different cultures and expectations in each policy field?

Points 4-6 inform initial background discussions of case study reports. We need to focus on comparability when describing the context in which the original policy developed. It is not enough to state that two political systems are different. We need to identify the relevance and implications of the differences, from another government’s definition of the problem to the logistics of their task.

7. Has the project been evaluated independently, subject to peer review and/ or using measures deemed acceptable to the government?

8. Has the evaluation been of a sufficient period in proportion to the expected outcomes?

9. Are we confident that this project has been evaluated the most favourably – i.e. that our search for relevant lessons has been systematic, based on recognisable criteria (rather than reputations)?

10. Are we identifying ‘Good practice’ based on positive experience, ‘Promising approaches’ based on positive but unsystematic findings, ‘Research–based’ or based on ‘sound theory informed by a growing body of empirical research’, or ‘Evidence–based’, when ‘the programme or practice has been rigorously evaluated and has consistently been shown to work’?

Points 7-10 raise issues about the relationships between (a) what evidence we should use to evaluate success or potential, and (b) how long we should wait to declare success.

11. What will be the relationship between evidence and governance?

Should we identify the same basic model and transfer it uniformly, tell a qualitative story about the model and invite people to adapt it, or focus pragmatically on an eclectic range of evidential sources and focus on the training of the actors who will implement policy?

In conclusion

Information technology has allowed us to gather a huge amount of policy-relevant information across the globe. However, it has not solved the limitations we face in defining policy problems clearly, gathering evidence on policy solutions systematically, and generating international lessons that we can use to inform domestic policy processes.

This rise in available evidence is not a substitute for policy analysis and political choice. These choices range from how to adjudicate between competing policy preference, to how to define good evidence and good government. A lack of attention to these wider questions helps explain why – at least from some perspectives – policy transfer seems to fail.

Paul Cairney Auckland Policy Transfer 12.10.18

 

 

How to write theory-driven policy analysis

Writing theory driven policy analysis 10.11.17

(or right click to download this lecture which accompanies my MPP)

Here is a guide to writing theory-driven policy analysis. Your aim is to identify a policy problem and solution, know your audience, and account for the complexity of policymaking.

At first, it may seem like daunting task to put together policy analysis and policy theory. On its own, policy analysis seems difficult but relatively straightforward: use evidence to identify and measure a policy problem, compare the merits of one or more solution, and make a recommendation on the steps to take us from policy to action.

However, policy process research tells us that people will engage emotionally with that evidence, and that policymakers operate in a complex system of which they have very limited knowledge and control.

So, how can we produce a policy analysis paper to which people will pay attention, and respond positively and effectively, under such circumstances? I focus on developing the critical analysis that will help you produce effective and feasible analysis. To do so, I show how policy analysis forms part of a collection of exercises to foster analysis informed by theory and reflection.

Aims of this document:

1. Describe the context. There are two fields of study – theory and analysis – which do not always speak to each other. Theory can inform analysis, but it is not always clear how. I show the payoff to theory-driven policy analysis and the difference between it and regular analysis. Note the two key factors that policy analysis should address: your audience will engage emotionally with your analysis, and the feasibility of your solutions depends on the complexity of the policy environment.
2. Describe how the coursework helps you combine policy theory and policy analysis. Policy analysis is one of four tasks. There is a reflection, to let you ‘show your work’; how your knowledge of policy theory guides your description of a problem and feasible solutions. The essay allows you to expand on theory, to describe how and why policy changes (and therefore what a realistic policy analysis would look like). The blogs encourage new communication skills. In one, you explore how you would expect a policy maker or influencer to sell the recommendations in your policy analysis. In another, you explain complex concepts to a non-academic audience.

Background notes.

I have written this document as if part of a book to be called Teaching Public Policy and co-authored with Dr Emily St Denny.

For that audience, I have two aims: (1) to persuade policy scholars-as-teachers to adopt this kind of coursework in their curriculum; and, (2) to show students how to complete it effectively.

If you prefer shorter advice, see Writing a policy paper and blog post and Writing an essay on politics, policymaking, and policy change.

If you are interested in more background reading, see: The New Policy Sciences (by Paul Cairney and Chris Weible) which describes the need to combine policy theory-driven research with policy analysis; and, Practical Lessons from Policy Theories which describes eight attempts by scholars to translate policy theory into lessons that can be used for policy analysis.

The theories make more sense if you have read the corresponding 1000 Words posts (based on Cairney, 2012). Some of the forthcoming text will look familiar if you read my blog because I am consolidating several individual posts into an overall discussion.

I’m not quite there yet (the chapter is a first draft, a bit scrappy at times, and longer than a chapter should be), so all comments welcome (in the comments bit).

Writing theory driven policy analysis 10.11.17

Writing an essay on politics, policymaking, and policy change

I tend to set this simple-looking question for coursework in policy modules: what is policy, how much has it changed, and why? Students get to choose the policy issue, timeframe (and sometimes the political system), and relevant explanatory concepts.

On the face of it, it looks super-simple: A+ for everyone!

Give it a few more seconds, and you can see the difficulties:

1. We spent a lot of time agreeing that it seems almost impossible to define policy (explained in 1000 Words and 500 Words)
2. There are a gazillion possible measures of policy change (1000 Words and 500 Words)
3. There is an almost unmanageable number of models, concepts, and theories to use to explain policy dynamics (I describe about 25 in 1000 Words each)

I try to encourage some creativity when solving this problem, but also advise students to keep their discussion as simple and jargon-free as possible (often by stretching an analogy with diving, in which a well-executed simple essay can score higher than a belly-flopped hard essay).

Choosing a format: the initial advice

1. Choose a policy area (such as health) or issue (such as alcohol policy).
2. Describe the nature of policy, and the extent of policy change, in a particular time period (such as in the post-war era, since UK devolution, or since a change in government).
3. Select one or more policy concept or theory to help structure your discussion and help explain how and why policy has changed.

For example, a question might be: What is tobacco policy in the UK, how much has it changed since the 1980s, and why? I use this example because I try to answer that – UK and global – question myself, even though my 2007 article on the UK is too theory-packed to be a good model for an undergraduate essay.

Choosing a format: the cautionary advice

You may be surprised about how difficult it is to answer a simple question like ‘what is policy?’ and I will give you considerable credit for considering how to define and measure it, by identifying, for example, the use of legislation/ regulation, funding, staff, and ‘nodality’ and/ or by considering the difference between, say, policy as a statement of intent or a long term outcome. In turn, a good description and explanation of policy change is difficult. If you are feeling ambitious, you can go further, to compare, say, two issues (such as tobacco and alcohol) or places (such UK Government policy and the policy of another country), but sometimes a simple and narrow discussion can be as, or more, effective. Similarly, you can use many theories or concepts to aid explanation, but often one theory will do. Note that (a) your description of your research question, and your essay structure, is more important than (b) your decision on what topic to focus or concepts to use.

Choosing a topic: the ‘joined up’ advice

The wider aim is to encourage students to think about the relationship between different perspectives on policy theory and analysis. For example, in a blog and policy analysis paper they try to generate attention to a policy problem and advocate a solution. Then, they draw on policy theories and concepts to reflect on their papers, highlighting (say): the need to identify the most important audience; the importance of framing issues with a mixture of evidence and emotional appeals; and, the need to present ‘feasible’ solutions.

The reflection can provide a useful segue to the essay, since we’re already identifying important policy problems, advocating change, reflecting on how best to encourage it – such as by presenting modest objectives – and then, in the essay, trying to explain (say) why governments have not taken that advice in the past. Their interest in the policy issue can prompt interest in researching the issue further; their knowledge of the issue and the policy process can help them develop politically-aware policy analysis. All going well, it produces a virtuous circle.

Some examples from my pet subject

Let me outline how I would begin to answer the three questions with reference to UK tobacco policy. I’m offering a brief summary of each section rather than presenting a full essay with more detail (partly to hold on to that idea of creativity – I don’t want students to use this description as a blueprint).

What is modern UK tobacco policy?

Tobacco policy in the UK is now one of the most restrictive in the world. The UK government has introduced a large number of policy instruments to encourage a major reduction of smoking in the population. They include: legislation to ban smoking in public places; legislation to limit tobacco advertising, promotion, and sponsorship; high taxes on tobacco products; unequivocal health education; regulations on tobacco ingredients; significant spending on customs and enforcement measures; and, plain packaging measures.

[Note that I selected only a few key measures to define policy. A fuller analysis might expand on why I chose them and why they are so important].

How much has policy changed since the 1980s?

Policy has changed radically since the post-war period, and most policy change began from the 1980s, but it was not until the 2000s onwards that the UK cemented its place as one of the most restrictive countries. The shift from the 1980s relates strongly to the replacement of voluntary agreements and limited measures with limited enforcement with legislative measures and stronger enforcement. The legislation to ban tobacco advertising, passed in 2002, replaced limited bans combined with voluntary agreements to (for example) keep billboards a certain distance from schools. The legislation to ban smoking in public places, passed in 2006 (2005 in Scotland), replaced voluntary measures which allowed smoking in most pubs and restaurants. Plain packaging measures, combined with large and graphic health warnings, replace branded packets which once had no warnings. Health education warnings have gone from stating the facts and inviting smokers to decide, and the promotion of harm reduction (smoke ‘low tar’), to an unequivocal message on the harms of smoking and passive smoking.

[Note that I describe these changes in broad terms. Other articles might ‘zoom’ in on specific instruments to show how exactly they changed]

Why has it changed?

This is the section of the essay in which we have to make a judgement about the type of explanation: should you choose one or many concepts; if many, do you focus on their competing or complementary insights; should you provide an extensive discussion of your chosen theory?

I normally recommend a very small number of concepts or simple discussion, largely because there is only so much you can say in an essay of 2-3000 words.

For example, a simple ‘hook’ is to ask if the main driver was the scientific evidence: did policy change as the evidence on smoking (and then passive smoking) related harm became more apparent? Is it a good case of ‘evidence based policymaking’? The answer may then note that policy change seemed to be 20-30 years behind the evidence [although I’d have to explain that statement in more depth] and set out the conditions in which this driver would have an effect.

In short, one might identify the need for a ‘policy environment’, shaped by policymakers, and conducive to a strong policy response based on the evidence of harm and a political choice to restrict tobacco use. It would relate to decisions by policymakers to: frame tobacco as a public health epidemic requiring a major government response (rather than primarily as an economic good or issue of civil liberties); place health departments or organisations at the heart of policy development; form networks with medical and public health groups at the expense of tobacco companies; and respond to greater public support for control, reduced smoking prevalence, and the diminishing economic value of tobacco.

This discussion can proceed conceptually, in a relatively straightforward way, or with the further aid of policy theories which ask further questions and help structure the answers.

For example, one might draw on punctuated equilibrium theory to help describe and explain shifts of public/media/ policymaker attention to tobacco, from low and positive in the 1950s to high and negative from the 1980s.

Or, one might draw on the ACF to explain how pro-tobacco coalitions helped slow down policy change by interpreting new scientific evidence though the ‘lens’ of well-established beliefs or approaches (examples from the 1950s include filter tips, low tar brands, and ventilation as alternatives to greater restrictions on smoking).

One might even draw on multiple streams analysis to identify a ‘window of opportunity for change (as I did when examining the adoption of bans on smoking in public places).

Any of these approaches will do, as long as you describe and justify your choice well. One cannot explain everything, so it may be better to try to explain one thing well.

Policy in 500 Words: how much does policy change?

You should get the impression from 1000 words that most policy changes are small or not radically different from the past: Lindblom identifies incrementalism; punctuated equilibrium  highlights a huge number of small changes and small number of huge changes; the ACF compares routine learning by a dominant coalition to a ‘shock’ which prompts new subsystem and policy dynamics; and multiple streams identifies the conditions (rarely met) for major change.

Yet, I just gave you the impression that we don’t know how to define policy. If we can’t define it well, how can we measure it well enough to come to this conclusion so consistently?

Why is the measurement of policy change important?

We miss a lot if we equate policy with statements rather than outputs/ outcomes. We also miss a lot if we equate policy change with the most visible outputs such as legislation. I list 16 different policy instruments, although they tend to be grouped into smaller categories: focusing on regulation (including legislation) and resources (money and staffing) to accentuate the power at policymaker’s disposal; or regulatory/ distributive/ redistributive to suggest that some policy measures are more difficult to ‘sell’ than others.

We also give a limited picture if we equate change with outputs rather than outcomes, since a key insight from policy studies is that there is generally a gap between policymaker expectations and the actual result.

What are the key issues in measurement?

So, as in defining policy change, we need to make choices about what counts as policy in this instance to measure how much it has changed. For example, I have (a) written on one output as a key exemplar of policy change –  legislation to ban smoking in public places for Scotland, England/ Wales, the UK, and (almost) EU – to show that a government is signalling major changes to come, but also (b) situated that policy instrument within a much broader discussion – of many tobacco policies in the UK and across the globe – to examine the extent to which it is already consistent with a well-established direction of travel.

To make such choices we need to consider:

• Breadth (to give the ‘big picture’) versus depth (to note important details forensically)
• How much we expect policy to change, given the size of the problem (a big feature in public health studies, which criticise government inaction)
• How radical policy change looks from the ‘top’ (at the point of central government choice) or the ‘bottom’ (longer-term delivery of policy by other bodies)
• What policies mean (what problem were policymakers trying to solve?)
• How consistent ‘policy’ seems when made of often-contradictory instruments

How do we solve the problem?

The problem is that we can produce very different accounts of policy change from the same pool of evidence, by accentuating some measures and ignoring others, or putting more faith in some data more than others (e.g. during interviews).

Sometimes, my preferred solution is to compare more than one narrative of policy change. Another is simply to ‘show your work’.

Take home message for students: ‘show your work’ means explaining your logical process and step-by-step choices. Don’t just write that it is difficult to define policy and measure change. Instead, explain how you assess policy change in one important way, why you chose this way, and shine a light on the payoffs to your approach. Read up on how other scholars do it, to learn good practice and how to make your results comparable to theirs. Indeed, part of the benefit of using an established theory, to guide our analysis, is that we can engage in research systematically as a group.

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PS Here is the way in which I describe these issues to MPP students writing theory-driven coursework on policy and policy change (using the case study of UK tobacco policy as a guide):

 

‘Evidence-based Policymaking’ and the Study of Public Policy

This post accompanies a 40 minute lecture (download) which considers ‘evidence-based policymaking’ (EBPM) through the lens of policy theory. The theory is important, to give us a language with which to understand EBPM as part of a wider discussion of the policy process, while the lens of EBPM allows us to think through the ‘real world’ application of concepts and theories.

To that end, I’ll make three key points:

1. Definitions and clarity are important. ‘Evidence-based policymaking’, ‘evidence-based policy’ and related phrases such as ‘policy based evidence’ are used incredibly loosely in public debates. A focus on basic questions in policy studies – what is policy, and how can we measure policy change? – helps us clarify the issues, reject superficial debates on ‘evidence-based policy versus policy-based evidence’, and in some cases identify the very different assumptions people make about how policymaking works and should work.
2. Realistic models are important. Discussing EBPM helps us identify the major flaws in simple models of policymaking such as the ‘policy cycle’. I’ll discuss the insights we gain by considering how policy scholars describe the implications of policymaker ‘bounded rationality’ and policymaking complexity.
3. Realistic strategies are important. There is a lot of academic discussion of the need to overcome ‘barriers’ between evidence and policy. It is often atheoretical, producing naïve recommendations about improving the supply of evidence and training policymakers to understand it. I identify two more useful (but potentially controversial) strategies: be manipulative and learn where the ‘action’ is.

Definitions and clarity are important, so what is ‘evidence-based policymaking’?

What is Policy? It is incredibly difficult to say what policy is and measure how much it has changed. I use the working definition, ‘the sum total of government action, from signals of intent to the final outcomes’ to raise important qualifications: (a) it is problematic to conflate what people say they will do and what they actually do; (b) a policy outcome can be very different from the intention; (c) policy is made routinely through cooperation between elected and unelected policymakers and actors with no formal role in the process; (d) policymaking is also about the power not to do something. It is also important to identify the many components or policy instruments that make up policies, including: the level of spending; the use of economic incentives/ penalties; regulations and laws; the use of voluntary agreements and codes of conduct; the provision of public services; education campaigns; funding for scientific studies or advocacy; organisational change; and, the levels of resources/ methods dedicated to policy implementation (2012a: 26).

In that context, we are trying to capture a process in which actors make and deliver ‘policy’ continuously, not identify a set-piece event which provides a single opportunity to use a piece of scientific evidence to prompt a policymaker response.

Who are the policymakers? The intuitive definition is ‘people who make policy’, but there are two important distinctions: (1) between elected and unelected participants, since people such as civil servants also make important decisions; (2) between people and organisations, with the latter used as a shorthand to refer to a group of people making decisions collectively. There are blurry dividing lines between the people who make and influence policy. Terms such as ‘policy community’ suggest that policy decisions are made by a collection of people with formal responsibility and informal influence. Consequently, we need to make clear what we mean by ‘policymakers’ when we identify how they use evidence.

What is evidence? We can define evidence as an argument backed by information. Scientific evidence describes information produced in a particular way. Some describe ‘scientific’ broadly, to refer to information gathered systematically using recognised methods, while others refer to a specific hierarchy of scientific methods, with randomized control trials (RCTs) and the systematic review of RCTs at the top. This is a crucial point:

policymakers will seek many kinds of information that many scientists would not consider to be ‘the evidence’.

This discussion helps identify two key points of potential confusion when people discuss EBPM:

1. When you describe ‘evidence-based policy’ and EBPM you need to clarify what the policy is and who is making it. This is not just about some elected politicians making announcements.
2. When you describe ‘evidence’ you need to clarify what counts as evidence and what an ‘evidence-based’ policy response would look like. This point is at the heart of often fruitless discussions about ‘policy based evidence’, which seems to describe almost a dozen alleged mistakes by policymakers (relating to ignoring evidence, using the wrong kinds, and/ or producing a disproportionate response).

Realistic models are important, so what is wrong with the policy cycle?

One traditional way to understand policymaking in the ‘real world’ is to compare it to an ideal-type: what happens when the conditions of the ideal-type are not met? We do this in particular with the ‘policy cycle and ‘comprehensive rationality’.

So, consider this modified ideal-type of EBPM:

• There is a core group of policymakers at the ‘centre’, making policy from the ‘top down’, breaking down their task into clearly defined and well-ordered stages;
• Scientists are in a privileged position to help those policymakers make good decisions by getting them as close as possible to the ideal of ‘comprehensive rationality’ in which they have the best information available to inform all options and consequences.

So far, so good (although you might stop to consider who is best placed to provide evidence, and who – or which methods of evidence gathering – should be privileged or excluded), but what happens when we move away from the ideal-type? Here are two insights from a forthcoming paper (Cairney Oliver Wellstead 26.1.16).

Lessons from policy theory: 1. Identify multi-level policymaking environments

First, policymaking takes place in less ordered and predictable policy environment, exhibiting:

• a wide range of actors (individuals and organisations) influencing policy at many levels of government
• a proliferation of rules and norms followed by different levels or types of government
• close relationships (‘networks’) between policymakers and powerful actors
• a tendency for certain beliefs or ‘paradigms’ to dominate discussion
• shifting policy conditions and events that can prompt policymaker attention to lurch at short notice.

A focus on this bigger picture shifts our attention from the use of scientific evidence by an elite group of elected policymakers at the ‘top’ to its use by a wide range of influential actors in a multi-level policy process. It shows scientists and practitioners that they are competing with many actors to present evidence in a particular way to secure a policymaker audience. Support for particular solutions varies according to which organisation takes the lead and how it understands the problem. Some networks are close-knit and difficult to access because bureaucracies have operating procedures that favour particular sources of evidence and some participants over others, and there is a language – indicating what ways of thinking are in good ‘currency’ (such as ‘value for money’) – that takes time to learn. Well-established beliefs provide the context for policymaking: new evidence on the effectiveness of a policy solution has to be accompanied by a shift of attention and successful persuasion. In some cases, social or economic ‘crises’ can prompt lurches of attention from one issue to another, and some forms of evidence can be used to encourage that shift. In this context, too many practitioner studies analyse, for example, a singular point of central government decision rather than the longer term process. Overcoming barriers to influence in that small part of the process will not provide an overall solution.

Lessons from policy theory: 2. Policymakers use two ‘shortcuts’ to make decisions

How do policymakers deal with their ‘bounded rationality’? They employ two kinds of shortcut: ‘rational’, by pursuing clear goals and prioritizing certain kinds and sources of information, and ‘irrational’, by drawing on emotions, gut feelings, deeply held beliefs, habits, and the familiar to make decisions quickly. Consequently, the focus of policy theories is on the links between evidence, persuasion, and framing (in the wider context of a tendency for certain beliefs to dominate discussion).

Framing refers to the ways in which we understand, portray, and categorise issues. Problems are multi-faceted, but bounded rationality limits the attention of policymakers, and actors compete to highlight one image at the expense of others. The outcome of this process determines who is involved (for example, portraying an issue as technical limits involvement to experts), who is responsible for policy, how much attention they pay, and what kind of solution they favour. For example, tobacco control is more likely when policymakers view it primarily as a public health epidemic rather than an economic good, while ‘fracking’ policy depends on its primary image as a new oil boom or environmental disaster (I discuss both examples in depth here).

Scientific evidence plays a part in this process, but we should not exaggerate the ability of scientists to win the day with reference to evidence. Rather, policy theories signal the strategies that practitioners may have to adopt to increase demand for their evidence:

• to combine facts with emotional appeals, to prompt lurches of policymaker attention from one policy image to another (punctuated equilibrium theory)
• to tell simple stories which are easy to understand, help manipulate people’s biases, apportion praise and blame, and highlight the moral and political value of solutions (narrative policy framework)
• to interpret new evidence through the lens of the pre-existing beliefs of actors within coalitions, some of which dominate policy networks (advocacy coalition framework)
• to produce a policy solution that is feasible and exploit a time when policymakers have the opportunity to adopt it (multiple streams analysis).

Further, the impact of a framing strategy may not be immediate, even if it appears to be successful. Scientific evidence may prompt a lurch of attention to a policy problem, prompting a shift of views in one venue or the new involvement of actors from other venues. However, for example, it can take years to produce support for an ‘evidence-based’ policy solution, built on its technical and political feasibility (will it work as intended, and do policymakers have the motive and opportunity to select it?).

This discussion helps identify two key points of potential confusion when people discuss the policy cycle and comprehensive rationality:

1. These concepts are there to help us understand what doesn’t happen. What are the real world implications of the limits to these models?
2. They do not help you give good advice to people trying to influence the policy process. A focus on going through policymaking ‘stages’ and improving ‘rationality’ is always relevant when you give advice to policymakers. However unrealistic these models are, you would still want to gather the maximum information and go through a process of stages. This is very different from (a) giving advice on how to influence the process, or (b) evaluating the pros and cons of a political system with reference to ideal-types.

Realistic strategies are important, so how far should you go to overcome ‘barriers’ between evidence and policy?

You can’t take the politics out of EBPM. Even the selection of ‘the evidence’ is political (should evidence be scientific, and what counts as scientific evidence?).

Further, providers of scientific evidence face major dilemmas when they seek to maximise the ‘impact’ of their research. Armed with this knowledge of the policy process, how should you seek to engage and influence decisions made within it?

If you are interested in this final discussion, please see the short video here and the follow up blog post: Political science improves our understanding of evidence-based policymaking, but does it produce better advice?

See also:

This post is one of many on EBPM. The full list is here: https://paulcairney.wordpress.com/ebpm/

To bridge the divide between evidence and policy: reduce ambiguity as much as uncertainty

 

Policy change, convergence and divergence since Scottish devolution #POLU9SP

Policy change is already difficult to measure and explain, but in Scottish politics there is an added dimension. It is common to gauge policy change according to the extent to which Scottish Government policy diverges from UK Government policy. This comparison can only take us so far, so I will begin with a discussion of divergence then take us back to Scottish policy change in its own right.

What might cause convergence and divergence?

Here is a list of possible causes, which we can discuss at more depth in the lecture (and can you think of others?):

Reasons for policy divergence (or difference):

• Different social attitudes
• Different parties in government
• Ministers trying to make a difference
• The larger role of public sector professionals in Scotland
• Different policy conditions
• A different policy process or style

Reasons for convergence (or similarity):

• Public expenditure and borrowing limits
• Overlaps between reserved and devolved policies
• A ‘single market’ in the UK and the need to avoid unintended consequences
• The same party of government
• A similar role for key professions
• Incrementalism, inertia, wicked problems and other reasons to limit policy change
• Similar problems and ways of thinking (and learning)

Policy divergence: ‘Scottish solutions to Scottish problems’

We sometimes describe policy divergence in Scotland as ‘evolution, not revolution’ (although evolution is not the opposite of revolution). In other words, devolution did not produce a radical departure from the past, in the way that we might associate with former Soviet countries. Rather, there is a mix of high profile ‘flagship’ policies mixed with a lot of fairly innocuous updating of the statute book. The big ones from 1999-2007 include:

• ‘free’ personal care for older people
• the reduction of higher education tuition fees
• the abolition of the healthcare internal market
• mental health legislative reforms
• the introduction of the single transferable vote in local elections
• the ‘smoking ban’ (does this example count?)

Then the big SNP government polices included:

• the abolition of higher education tuition fees (and prescription charges)
• the minimum unit price on alcohol
• the reform of criminal justice sentencing
• the pursuit of renewable energy projects and rejection of new nuclear energy stations
• the pursuit of new ways to fund capital projects (e.g. schools and hospitals)

So, we have three images of the much-talked-about-before-devolution phrase ‘Scottish solutions to Scottish problems’

The first relates to the idea that Westminster had insufficient time for Scottish legislation, and so devolution would present a new opportunity for policy innovation and new ideas. Yet, perhaps after a honeymoon period, public policy did not appear to change dramatically or mark dramatic policy divergence from the past or the rest of the UK.

The second relates to devolution as a way to avoid policy innovation: to step off the train associated with the constant top-down reform agenda of the UK government. This second image is often a better guide, and we can link it to (a) the idea that devolution in 1979 represented a missed opportunity to cushion the blow of Thatcherism, and (b) current debates on the extent to which devolution can actually protect Scotland from the worst excesses of UK policy (I am paraphrasing the arguments of other people here).

The third relates more to policymaking than policy: ‘Scottish solutions to Scottish problems’ may relate to how Scottish institutions process policy than the actual policy outputs and outcomes (the ‘Scottish policy style’ or ‘Scottish approach’). As we have discussed in several lectures, this is not necessarily a small difference (particularly if you focus on Greer/ Jarman’s account of the differences in the use of ‘policy tools’).

Don’t forget existing differences

We miss a lot if we just focus on divergence, because much Scottish policy reinforces or maintains existing policy differences, such as when the Scottish Government reformed its curriculum and addressed teacher-local authority relations. Can you think of other examples?

Don’t forget policy change

We miss a lot of policy change if we only focus on divergence from UK government policy. For example, maybe the governments innovate and emulate each other (they don’t though – see box 9.2).

Or, they do very similar things or don’t quite manage to do different things:

• Housing stock transfer and (until recently) the ‘right to buy’
• Policies to address so called ‘anti-social behaviour’
• Attempts by the Scottish and UK Governments (often in vain) to address ‘wicked problems’ such as social inclusion/ exclusion and socio-economic inequalities
• Public health reforms such as tobacco control
• Agricultural and fisheries policies (although can you identify key differences?)
• Land taxation
• Policies in development, such as an expansion of pre-school care and the very long gestation of local income tax

In the next lecture, we can also go into more depth on the idea of policy change, to identify a difference between (for example) policy divergence as a set of policy choices and their actual effect.