Sample: Theories of the Policy Process, 4th Ed.


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Table of Contents

Preface to the Fourth Edition

Introduction:  The Scope and Focus of Policy Process Research and Theory, Christopher M. Weible

Part I: Theoretical Approaches to Policy Process Research

1. The Multiple Streams Framework: Foundations, Refinements, and Empirical Applications, Nicole Herweg, Nikolaos Zahariadis, and Reimut Zohlnhöfer

2. Punctuated Equilibrium Theory: Explaining Stability and Change in Public Policymaking, Frank R. Baumgartner, Bryan D. Jones, and Peter B. Mortensen

3. Policy Feedback Theory, Suzanne Mettler and Mallory SoRelle

4. The Advocacy Coalition Framework: An Overview of the Research Program, Hank C. Jenkins-Smith, Daniel Nohrstedt, Christopher M. Weible, and Karin Ingold

5. The Narrative Policy Framework, Elizabeth A. Shanahan, Michael D. Jones, Mark K. McBeth, and Claudio M. Radaelli

6. The IAD Framework and the SES Framework: An Introduction and Assessment of the Ostrom Workshop Frameworks, Edella Schlager and Michael Cox

7. Innovation and Diffusion Models in Policy Research, Frances Stokes Berry and William D. Berry

Part II: Comparisons and Conclusions

8. Comparison of Theories of the Policy Process, Tanya Heikkila and Paul Cairney

9. Struggle and Triumph in Fusing Policy Process and Comparative Research, Jale Tosun and Samuel Workman

10. Moving Forward and Climbing Upward: Advancing Policy Process Research, Christopher M. Weible

About the Contributors



Preface to the Fourth Edition

Policy process research has never reached as many parts of the globe as it does today. The result of this burgeoning network of scholars has been a rapid upsurge of ideas. It has also generated research that implicitly or explicitly exhibits a comparative research approach. The potential benefits of this changing landscape are fantastic. Only through comparative research can we distinguish knowledge that is localized to a particular context or generalized across contexts. Hence, opportunities abound to overcome some of the past obstacles to advance the field to higher plateaus of knowledge. To realize these opportunities, the fourth edition of Theories of the Policy Process reflects this increasing globalization of the field of policy processes.

To underscore the role of these theories in a globalized field, two important changes have been made to this volume. The first is a new chapter on strategies for conducting comparative research authored by Jale Tosun and Samuel Workman. The goal of this new chapter is to offer readers a firm foundation for applying these theories in a global and comparative research environment. The second is that authors of each of the theory-based chapters have been instructed to revise their chapters to describe how their theory fits in this global comparative approach to policy process research. The purpose behind these changes is simple: as the theories of the policy processes become applied in various parts of the world, we must be deliberate in thinking about how our research fits together and how our knowledge could accumulate.

Another change in the fourth edition is a major revision to the introductory chapter that better presents the topic of policy process research and the goals of this volume. To summarize, the goal of this volume is to advance the scholarship of policy process research among a global community of scholars. Obviously, new and experienced scholars can read the original articles or books on these theories and skip this volume. Lost, however, would be the opportunity to compare and contrast the collection of seven of the most established and utilized theories of the policy processes. Theories of the Policy Process remains indispensable in offering readers the chance to discover and learn about them as an anthology.

The opening chapter also updates and clarifies the criteria for continuing to include the theories in this volume. On the basis of these criteria, the chapter on the Social Construction Framework by Anne Schneider, Helen Ingram, and Peter deLeon has been removed from this edition. This decision has nothing to do with the quality of the insights from this theory, which remains invaluable in highlighting the distributions of benefits and burdens of public policies based on the power and constructions of target populations. It also has nothing to do with what some might call this framework’s postpositivism orientation. Instead, in consideration of the criteria outlined in the Introduction, this particular theory is supported by a less vibrant and active research community without much advancement in knowledge beyond the ideas in its original publication (Schneider and Ingram 1993, 1997). Moreover, Policy Feedback Theory in this volume captures a part of the Social Construction Framework, with its focus on how policies shape politics. For those who want to keep the Social Construction Framework in their course readers, the chapter from the third edition is available online, along with other links and resources to supplement the chapters in this volume (

In preparing this volume, I want to express my gratitude to Ada Fung of Westview Press. Without Ada’s support, feedback, and encouragement, the third and fourth editions of Theories of the Policy Process would not exist. I also want to thank the referees who commented on the strengths and weaknesses of each chapter from the third edition, including Stephen Ceccoli (Rhodes College); Casey LaFrance (Western Illinois University); Chandra Commuri (California State University, Bakersfield); Sarah Michaels (University of Nebraska); Xufeng Zhu (Tsinghua University); Saba Siddiki (Syracuse University); ­Stephen Stehr (Washington State University); Claire Dunlop (Exeter University); and others who wished to remain anonymous. Their feedback helped improve many chapters in this volume and definitely motivated the need for a fourth edition. I also want to express my sincerest appreciation to the contributing authors for their efforts in revising their chapters. Their commitment to writing their chapters with the highest standards of quality continues to make this a premier outlet for the most established policy process theories. A special note of gratefulness to Jennifer Armstrong for her excellent comments and feedback on the opening and closing chapters of this volume.

Finally, a great deal of respect must be given to the legacy of Paul Sabatier for leading the efforts in the first two editions of this volume. Following Ted Lowi, Paul used to preach: “Clarity begets clarity, mush begets mush.” The point is simple: if we conduct our research with clear theoretical orientations, our results will more likely be clear, both in their mistakes and in their accuracies. The converse is also true: if we conduct our research with mushy theoretical orientations, we will more likely get mushy results. Given the finite number of research projects any of us might undertake, we must heed this advice and strive to make our thoughts and actions as clear of mush as possible. The best way to do this is together, through thoughtful and constructive feedback. As we continue this journey in advancing our knowledge about policy process on a global frontier, let’s be diligent in reducing the mush and increasing the clarity in our work.


Introduction: The Scope and Focus of Policy Process Research and Theory

Christopher M. Weible

The goal of this volume is to advance the science of policy process among a global community of scholars. In advancing science, theories simultaneously serve as reservoirs of knowledge gained from past research and platforms for guiding new research into the future. The inevitable challenge for anyone learning about or contributing to the policy process is that any one theory inherently focuses on a limited set of concepts and relationships. Therefore, a single theory provides only a partial depiction of the complexity of the policy process. The best strategy to overcome this challenge is to explore and utilize multiple theories of the policy process.1

This volume offers an anthology of seven of the most established theories in the field of policy processes. The latest interpretations of these theories are authored by scholars who are among the most knowledgeable and experienced in working with them, a number of whom are the original creators of the theories. By featuring these theories in a single collection, this volume facilitates efforts to compare and contrast their goals and aims, to identify their relative strengths and weaknesses, to learn about how and when to apply them, and to discover the insights embodied in them.

In this introduction, the term theory is used generically to represent a research tool. These tools specify scope of inquiry, assumptions, and concepts in various relational forms, such as principles, hypotheses, and propositions. Based on what we know and envision, these relational forms specify a limited set of associations among concepts, from the much larger and untamable set. These relational forms also postulate explanations of why and how, under what conditions, by and for whom, and when the concepts might relate (Whetten 1989). Although the meaning of theory varies across the field of policy process research, this generic description is consistent with other uses of the term ­(McCool 1995, 11). It also represents a deliberate mix of frameworks and theories, as described by Ostrom (2005, 27–29).

A Definition of Policy Process Research

The policy processes emerged as a field of study in the 1950s as part of an endeavor to develop a science that integrates research on politics and government around a policy orientation. Among its early leaders, Lasswell (1951) urged scholars to focus their research on policy formulation and execution toward the realization of human dignity.2 Another one of the original exposés on the subject was penned by Shipman, who used the term policy process to denote a needed area of study that integrates politics, policy, and administration. As Shipman (1959, 545) notes, “When the policy-process approach is used, institutions and mechanisms of political organization, legislative action, executive administration, adjudication, and the rest merge into an intricately interconnected process for seeking satisfaction of societal values.” Following the ideas of Lasswell, Shipman, and many others, the phenomenon of policy processes refers to the interactions that occur over time between public policies and surrounding actors, events, contexts, and outcomes.3

At the center of policy processes lies the elusive concept of public policy. Public policy is defined as the deliberate decisions—actions and nonactions—of a government or an equivalent authority toward specific objectives.4 Examples of public policies include, but are not limited to, statutes, laws, regulations, executive decisions, and government programs (Birkland 2016, 8). Other examples of public policies are the commonly understood rules-in-use that structure behavioral situations in policy processes, such as the sustained practices of street-level bureaucrats in delivering public services (Lipsky 1980; Schneider and Ingram 1997; Ostrom 2005).5 Public policies can include both means and goals and can range in form from procedural to substantive and from symbolic to instrumental. Alternatively, a public policy can be understood by identifying the institutions that constitute its design and content. For instance, some institutions prescribe specific authority for a given position, and others require exchanges of information under certain conditions (Ostrom 1980). In studying policy processes, researchers sometimes focus on a single public policy (e.g., a particular welfare law) or on many public policies related to a particular issue (e.g., the many types of public policies affecting the issue of welfare in a locale).

Public policy interactions involve actors—individuals or collectives such as organizations, networks, or coalitions—and their attributes, including their knowledge, values, beliefs, interests, strategies, and resources. Individual actors may be part of the general public who occasionally participate politically in a public policy issue. Alternatively, actors may be affiliated with government or nongovernment organizations that regularly seek to influence public policy on a given issue or control the government venues (e.g., a legislature or an executive administration) wherein policy decisions occur.

The context of a public policy is the setting around which the interactions involving public policy happen. Examples of the contextual categories often studied in policy process research might be socioeconomic conditions, culture, infrastructure, biophysical conditions, and institutions. Sometimes the context lies in the theoretical foreground as the target of public policy, such as economic stimulus programs aimed to stimulate an economy. It can also provide a theoretical background in which actors politically interact to influence public policy. In this regard, context can be relatively stable or susceptible to change over time.

All contexts entail various types of events. Events can be anticipated and unanticipated incidents ranging from elections to scientific discoveries and chronic and acute societal dilemmas and crises. Sometimes actors deliberately create events to affect the policy process, as seen in social movements. Other times, events are unintentional and beyond the control of actors, like an earthquake. Because events can be directly or indirectly related to a given public policy issue, they often provide opportunities for achieving policy objectives. For example, a bureaucracy might release an evaluative report that brings attention to the success or failure of a public policy in addressing an issue. This report, in turn, might shape future legislative agendas. This is but one simple example of the many ways in which the theories in this volume can portray the role of events in shaping policy processes.

The outcomes of policy processes are the short- or long-term consequences or impacts of public policy on a society. These outcomes continue to interact with policy processes over time. Outcomes are essentially changes (or stasis) in the context and actors constituting policy processes. Outcomes are separated as a distinct category because of their importance in assessing the effects on society of the policy processes. Thus, whereas one of the goals of policy process research is the generation of knowledge as embodied in theories, the use of this knowledge must eventually help attain societal values and realize a greater human dignity.

To imagine the policy process as interactions involving public policy over time underscores the permanence of politics and continuity of policy processes where “there is no beginning or end” (Lindblom 1968, 4). Indeed, any given output of the policy process in one study can serve as an input of the policy process in another. The choice of any given output and input in policy process research is not absolute but rather a reflection of the priorities of the researcher, the practicalities of available data, and the foci of a given theory.

These ongoing interactions are also best understood by the various interpretations of the “process” in policy process research. A process refers to the continuous points in time (e.g., usually in terms of actors’ decisions and actions, events, and outcomes) that constitute policy processes. One of the most common depictions of this process is the policy cycle. The policy cycle simplifies the policy process by delineating the stages of decision making through which policy proposals must traverse for their manifestation. These stages typically include agenda setting, policy formulation and adoption, policy implementation, evaluation, and termination.

Many have criticized the policy cycle for its overly simplistic and inaccurate portrayal of the policy process (e.g., Sabatier and Jenkins-Smith 1993). But criticisms aside, it remains a useful heuristic archetype. The policy cycle becomes a hindrance when scholars believe the key interactions in the policy process are strictly the policy cycle, force theories into its stages, and ignore important questions that lie outside its scope. Indeed, the problem with the policy cycle is less its simplistic and inaccurate depiction of policy processes and more its overuse by scholars as the sole lens through which to view and organize the field.

The theories in this volume offer additional portrayals of the interactions in policy processes. These interactions might be enduring periods of political conflict and concord observed in the behavior of coalition members or serendipitous circumstances leading to windows of opportunity in changing agendas and policies. In addition, patterns and speed of policy adoption across different units of government, the continuous tinkering with rules by people self-­governing a collective action situation, and the various feedback effects on the general public of adopted public policies represent other interactions. Indeed, the theories in this volume depict interactions that vary in what is emphasized or deemphasized. These interactions can reflect the linearity of the policy cycle stages, yet can also portray a policy process that is far more complicated and messy.

The Criteria for Including Theories

This volume features the most established theories of the policy process. Their continued inclusion in the fourth edition of this volume was based on several criteria:

(1) A focus on developing scientific theory of policy processes. Each of the approaches in this volume represents efforts toward developing a scientific theory that focuses on a set of interrelated concepts involving actors, events, contexts, and outcomes that surround public policies over time. As scientific theories, the approaches in this volume specify sets of assumptions and conditions under which they apply and posit interactions that come in various relational forms (hypotheses, propositions, principals, or other). Underlying these relationships are causal drivers—usually anchored at the individual level—that explain why a relationship could exist. No matter the name, these relational forms serve to enable falsification and learning, to communicate explicitly the relationships under investigation, and to summarize what we know about a given phenomenon. When the concepts are defined abstractly, the relational forms promote comparative applications of the theories to tease apart local versus generalizable understandings and explanations.

(2) The presence of an active research community. Science is a “social enterprise” (King, Keohane, and Verba 1994, 8). All theories in this volume must be supported by a community of scholars advancing the science. Such a community might be motivated by a common set of research questions or objectives, a shared vocabulary of concepts, a balanced research effort that interplays theoretical expositions and empirical applications, and common epistemological and ontological assumptions. The composition of these research programs varies, but most involve active and experienced leadership, a regular influx of graduate students, and an expanding base of interested and experienced scholars applying a theory. These scholars often participate on the same research projects and organize and participate on panels at general conferences. In some cases, these communities organize and participate in small workshops or seminars focused on developing their theory.

(3) A comparative research approach. To gain knowledge about the policy process, a theory’s research community must apply the theory in a comparative approach.6 Sometimes this is done implicitly, as when one theory is applied in a single country. In this situation, a follow-up study could aggregate the results in a meta-analysis from a number of similarly executed applications of the theory across many countries. Other times this is done explicitly. For example, some research teams might apply a given theory to answer the same question across countries in a single research design; here, the underlying goal of the research might be to ascertain effects of the contextual setting on the results. The comparative approach need not be restricted to country comparisons but may involve comparisons of a variety of different actors, contexts, events, outcomes, or times. The challenge in comparative research agendas is creating and using a shared research platform to foster generalizable knowledge across policy processes while, at the same time, offering enough flexibility to portray a given policy process in a valid way.

(4) An effort toward making research as public as possible. The quality of policy process research is only as good as the transparency of its procedures for collecting and analyzing data. Sabatier (1999, 5) made famous the phrase “be clear enough to be proven wrong.” The point is that obscure procedures produce results immune to criticism. There will always be some ambiguous steps in a research project, and pure replication is usually impractical or impossible. However, given human fallibility, there is no better way to learn from our mistakes than to be as clear as we can in all aspects of our science.

(5) Continual growth in knowledge about policy processes. Theories offer a number of important academic and practical contributions, from teaching to conducting community-based research. Of all these contributions, probably the most important is advancing the reservoir of localized and generalized knowledge. Given that some of the theories in this volume have been around for decades, we must eventually ask: What new insights have each of these theories produced since its creation? Our understanding of the policy process is, and always will be, incomplete. Yet, if our theories stagnate, then so does progress in reaching higher plateaus of knowledge.

The extent to which the theories in this volume meet the above criteria varies and, in some situations, is debatable. Of these criteria, the most important is an engaged group of scholars advancing the science under a given approach. Indeed, one of the main lessons from decades of developing theory is that it takes teams of scholars working together over extended periods of time to create shared methods and analytical techniques, to conduct their research comparatively, and to aggregate those results into lessons learned. No theory is perfect, and assessing the accumulation of knowledge for a given theory is exceedingly difficult. Thus, the best short-term indicator of future progress is the presence of a large group of scholars working together to advance a theory toward the enrichment of knowledge.

Theories Included in This Volume

This volume offers seven different theories of policy process research that meet, to various extents and ways, the criteria outlined above for their inclusion in the discussion.

The first chapter, coauthored by Nicole Herweg, Nikolaos Zahariadis, and Reimut Zohlnhöfer (2017), covers the Multiple Streams Framework. The Multiple Streams Framework depicts a process that emphasizes timing in the merging of problem, political, and policy streams in the creation of windows of opportunity for both agenda setting and decision making. Among the strengths of the Multiple Streams Framework are its accessibility, vibrant research community, and constant evolution.

Chapter 2, by Frank R. Baumgartner, Bryan D. Jones, and Peter B. Mortensen (2017), is on the Punctuated Equilibrium Theory. Under this ­theory, scarce attention drives incremental and punctuated patterns of policy change over time. Of all the theories in this volume, the Punctuated Equilibrium Theory offers perhaps the best current example of a coordinated policy community leveraging a comparative approach.

The third chapter on the Policy Feedback Theory, coauthored by Suzanne Mettler and Mallory SoRelle (2017), takes a different perspective. Drawing on the notion that policies shape politics, the Policy Feedback Theory seeks to understanding what happens after a policy is adopted, with an emphasis on resource and interpretive effects on mass publics. Policy Feedback Theory represents another vibrant research community that continues to develop this theory.

The Advocacy Coalition Framework is the fourth theory, coauthored by Hank C. Jenkins-Smith, Daniel Nohrstedt, Christopher M. Weible, and Karin Ingold (2017). The Advocacy Coalition Framework deals with ongoing patterns of conflict and concord as reflections of different beliefs, situations fostering belief change and learning, and rationales for major and minor policy change. The literature under the Advocacy Coalition Framework features a strong comparative agenda with applications spanning the globe.

Elizabeth A. Shanahan, Michael D. Jones, Mark K. McBeth, and Claudio M. Radaelli (2017) coauthored Chapter 5 on the Narrative Policy Framework. This relatively new theory focuses on the politics of storytelling and the impacts on public policy. The Narrative Policy Framework is quickly evolving, with an increasing number of applications, a common methodological approach that spurs applications across contexts, and constant refinement to its concepts and posited interactions.

The sixth chapter, coauthored by Edella Schlager and Michael Cox (2017), summarizes the Institutional Analysis and Development framework and its offspring, the Social-Ecological Systems framework. Both frameworks are extremely versatile, with an exceptionally large number of applications in a variety of contexts. Based, in part, on the idea of self-governance and the constant tinkering with institutional rules, these frameworks continue to flourish in describing and explaining a variety of collective action situations.

Chapter 7, the last theoretical chapter, directs scholars to approach policy change by looking at the reasons, speed, and patterns of adoption or rejection of policy proposals across government units, as found in Berry and Berry’s (2017) summary of innovation and diffusion models. This chapter provides the latest summary of this long-standing research area in the study of policy processes.

Strategies for Using This Volume

The chapters are organized in a way that facilitates reading the volume from beginning to end, though some instructors and readers will prefer a different order of the theories.7 Part I encompasses the theory chapters, beginning with the Multiple Streams Framework and Punctuated Equilibrium Theory, given their traditional emphases on agenda setting and policy change. Policy Feedback Theory comes next, with its focus on the impacts of policy design on society. Encompassing a range of phenomena, the next three chapters include the Advocacy Coalition Framework, Narrative Policy Framework, and the Institutional Analysis and Development framework. The last of the theory-based chapters is on innovation and diffusion models, with its emphasis on the adoption and rejection of policy output across space and time.

Part II of this volume includes three summary chapters. The first (Chapter 8), by Tanya Heikkila and Paul Cairney (2017), provides a comparison and critique of the theories in this anthology. Given the importance of the comparative approach in advancing policy process theory, in Chapter 9 Jale Tosun and Samuel Workman (2017) provide tips and strategies for using the theories to conduct comparative research. The final chapter, by Christopher M. Weible (2017), offers an overview of the status of the field and general strategies for moving forward and climbing upward.

Each of the theory chapters should be considered a thorough yet brief summary of a theory. To develop a deeper understanding of any of these theories, readers are encouraged to read the chapter in this volume along with some combination of the foundational pieces of a given theory, previous theoretical depictions of the theory, and empirical applications. For example, advanced graduate students exploring the Multiple Streams Framework could read Cohen, March, and Olsen’s (1972) “A Garbage Can Model of Organizational Choice,” Kingdon’s (1984) Agendas, Alternatives, and Public Policies, Chapter 1 by Herweg and colleagues in this volume, and one or two empirical applications. For intermediate graduate or undergraduate students, the theoretical chapters in this volume could be combined with one or two empirical applications.

Theories of the Policy Process is not intended to provide comprehensive coverage of policy process research. Readers are encouraged to supplement this volume with articles or books that cover other topics or theories. Among those deserving attention are the policy cycle (deLeon 1999), policy success and failure (McConnell, 2010), policy styles (Richardson 1982), power (Bachrach and Baratz 1963; Lukes 1974), policy instruments and design (Howlett 2011), policy entrepreneurs (Mintrom and Norman 2009), social capital (Putnam, Leonardi, and Nanetti 1994), implementation (Pressman and Wildavsky 1973; Moulton and Sandfort, 2016), causal stories (Stone 1989), the postpositivist literature (Fischer and Forester 1993; Fischer 2003), and the social construction framework (Schneider and Ingram, 1993; Schneider, Ingram, and deLeon, 2014). Additionally, there has been another burst of innovation in the formation of new and emerging theories of the policy process. In 2013, Policy Studies Journal published a collection of these new theories, including the Ecology of Games (Lubell 2013), the Policy Regime Perspective (May and Jochim 2013), the Institutional Collective Action Framework (Feiock 2013), and the Collective Learning Framework (Heikkila and Gerlak 2013).

As mentioned earlier, readers should avoid forcing the theories into a stage of the policy cycle—the result would be an incomplete, and quite possibly an inaccurate, portrayal of them. Although some theories may fit into one or more of the stages, most incorporate the entire policy cycle in one way or another or depict the policy process in an entirely different way.8 The best strategy is to interpret how the different theories provide insight into policy process rather than to impose an artificial categorization on them.

Readers should also adopt a broad definition of public policy, as previously described, that includes both formal elements of public policy, such as laws and regulations, and public policies as rules-in-use that govern, for example, traditional venues of government, from city councils to legislatures, as well as various associations charged with the provision and production of public goods and services. This strategy is most useful for relating the Institutional Analysis and Development framework to the other theories covered in this volume. The point is that the interactions involving public policies encompass not just the formal structures of government as written down and adopted by officials and other authorities but also the actual rules-in-use that structure the day-to-day behaviors of actors engaged in policy process situations. Any definition of public policy must include both because so much of government activities is informed by what is written down and by the informal rules of a given situation. Arguably, such a broad definition of public policy may inhibit comparison if we do not take into account the type of public policy under study.

The goal of this volume is to provide in a single outlet the latest versions of the major theories of the policy process, to compare and contrast these theories, to offer strategies for strengthening the international community engaged in comparative policy process research, and to help propel policy process research to higher levels of excellence. Whether this book serves as an introduction to the field or as a sturdy reference guide, the hope is that readers will test and develop policy process theories to provide for a better understanding and explanation of policy processes.


  1. The complexity of the policy process emerges from interactions among a large number of diverse people seeking political influence, periodic as well as unexpected events, a complicated mix of policies that span levels of government, and contextual settings characterized by a range of conditions from geographical to socioeconomic. In studying such complexity, people are innately restrained by cognitive presuppositions that cause them to recognize some aspects of the process and ignore others. Using one or more theories is one strategy to help mitigate the effects of such presuppositions by highlighting the most important items for study and specifying relationships between them. By requiring conscientious rigor in choosing what to study in analyzing the policy process, theories increase the likelihood that errors will be recognized and, thus, they facilitate lesson learning over time. Such benefits are magnified when theories are applied with transparent data collection and analysis methods, especially when compared to research based on unspecified and implicit observations. Ideally, scholars become versed in the use of more than one theory, which is one of the best ways to guard against both theory tenacity and confirmation bias. Theory tenacity is the tendency to maintain commitment to a theoretical argument even in response to disconfirming evidence. Confirmation bias is the tendency to seek out evidence that confirms a theoretical argument. See Loehle (1987) for discussion of both theory tenacity and confirmation bias.
  2. For Lasswell (1951), the policy process was a key intellectual pillar of the “policy science.” The field of policy analysis and evaluation encapsulates the other key pillar.
  3. This definition matches that found in Weible and Carter (2016).
  4. The definition of public policy offered in the text seeks to capture common elements found across the literature, most notably in Weible and Carter (2016, 3), Birkland (2016, 8), McCool (1995, 8–9), Parson (1995, 2–16), Cairney (2012, 23–26), Howlett (2011, 15–17), Heclo (1972, 84–88), and Ranney (1968, 6–7).
  5. Rules-in-use refers to the definitions and logic of the Institutional Analysis and Design Framework (Ostrom 2005, 2010). Ostrom (2010, 647) defines the rules-in-use as rules that “specify common understandings of those involved related to who must, must not, or may take which actions affecting others subject to sanctions.” The point is that the content of public policy as formally written may or may not reflect the in-use rules structuring the regular practices and behaviors of government officials or the equivalent. The inclusion of in-use rules as part of the definition of public policies is somewhat atypical compared to most definitions, but it is consistent with a few others (Schneider and Ingram 1997, 2) and necessary in understanding and explaining policy processes, especially when considering the roles of street-level bureaucrats (Lipsky 1980).
  6. See the excellent book by Dodds (2013) for some of the inspiration of the ideas underlying this criterion.
  7. Of course, some instructors and readers might want to adopt a “machete order” by rearranging the sequence in which the chapters are read. Some instructors, for example, start with the introduction and concluding chapters and then read the theory chapters in a different order than presented.
  8. For example, the Advocacy Coalition Framework and Institutional Analysis and Development Framework could be applied to any of the stages of the policy cycle. Consider policy change: (1) analysts could use the Advocacy Coalition Framework to discover how policy change is the result of conflict between adversarial coalitions conditioned by events, learning, and negotiations; (2) analysts could use the Institutional Analysis and Development Framework to understand an instance of policy change as institutional adaptation among actors continuously tinkering with the rules governing a particular situation. Consider implementation: (1) analysts could use the Advocacy Coalition Framework to study implementation and find a continuation of coalition conflict and the absence of learning in rulemaking in yet another political game; (2) analysts could use the Institutional Analysis and Development Framework to study implementation as the behaviors associated with the patterns of enforcement and monitoring of rules governing a particular resource.


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Berry, Frances Stokes, and William D. Berry. 2017. “Innovation and Diffusion Models in Policy Research.” In Theories of the Policy Process, 4th ed., edited by Christopher M. Weible and Paul A. Sabatier, 253–297. Boulder, CO: Westview Press.

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Lubell, Mark. 2013. “Governing Institutional Complexity: The Ecology of Games Framework.” Policy Studies Journal 41 (3): 537–559.

Lukes, Steven. 1974. Power: A Radical View. London: Macmillan.

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Chapter 4

Chapter 4

The Advocacy Coalition Framework: An Overview of the Research Program

Hank C. Jenkins-Smith, Daniel Nohrstedt, Christopher M. Weible, and Karin Ingold

The study of policy processes brings focus to many questions of both theoretical and practical significance. Some questions concern policy change and stasis over time: What factors explain the likelihood of occurrence of major and minor policy change? To what extent is policy change affecting government agencies and procedures and, through them, broader public opinion? Another set of questions involves learning by actors: To what extent are actors learning from their experiences, from the experiences of others, or from scientific and technical information? What factors facilitate learning among allies and among opponents? Yet another set of questions centers on the behavior of actors who directly or indirectly attempt to influence policy processes by advocating for change or maintenance of the status quo: Under what conditions do actors form and maintain coalitions to achieve their policy objectives in a coordinated fashion? What are the characteristics of the network structures of these coalitions? To what extent, and in what ways, do opposing coalition actors interact?

To answer these questions is to provide insight into some of the fundamental themes of governance and politics that ultimately affect the composition, dynamics, and course of society. The purpose of this chapter is to provide an overview of one framework that can help answer these questions: the Advocacy Coalition Framework (ACF).1 The chapter begins with a summary of the intellectual foundations of the ACF. It then provides an overview of the framework and its theoretical foci, including assessments of the hypotheses based on extensive empirical applications. The chapter ends by suggesting an ongoing agenda to continue the advancement of the ACF research program.


Intellectual Foundations of the ACF

The ACF was created in the early 1980s by Paul Sabatier and Hank Jenkins-­Smith. Chief inspirations were drawn from past shortcomings in policy process research, including a need to develop an alternative policy process theory to overcome the limitations of the stages heuristic; a need to provide theoretical insight into the role of scientific and technical information in policy debates; a need to shed light on ideological disagreement and policy conflicts; and a need to provide a comprehensive approach to understanding politics and policy change over time that went beyond traditional emphases in political science on government institutions (e.g., executive, legislative, and judiciary) and a few forms of political behavior (e.g., voting and lobbying) (see the discussion in Sabatier 1991). Establishing the framework took several years of effort that included conference papers written by Sabatier and Jenkins-Smith, ongoing data collection through interviews and surveys, and the creation of code forms for measuring belief systems and coalition stability over time.2

The foundations of the ACF were also influenced by debates in the philosophy of sciences that were still prominent in the 1970s and 1980s. Partly in response to Thomas Kuhn’s (1962) notion of scientific revolutions and paradigm shifts, Imré Lakatos developed his conception of the evolution of scientific research “programmes” in an effort to rescue the conception of cumulative, falsifiable science and the growth of knowledge (Lakatos 1970). A key contribution from Lakatos was the notion that scientific theories can be described as consisting of a “hard core” of unchanging and largely axiomatic propositions surrounded by a “protective belt” of auxiliary hypotheses that can be adjusted (or rejected) in response to potentially falsifiable evidence. This concept is a recognizable ancestor of the structure of belief systems in the ACF, which are characterized as hierarchically structured with a deep core of ontological and normative beliefs that are extraordinarily difficult to change, and “secondary aspects” of more specific propositions about how to effectively translate core beliefs into policy.3

A second important contribution was drawn from Lakatos’s related proposition that—given that Popper’s ([1935] 2002) ideal of falsifiable theories had proven implausible—theoretical progress was most readily evident in “progressive problem-shift.” As noted by Kuhn (1962), counterevidence need not displace a theory; empirical anomalies can persist for hundreds of years while a theory hangs on because (1) ad hoc defense of a theory was too effective to displace a vital theory and (2) a ready replacement theory was not available. Lakatos argued that ad hoc defense of a theory fails if it is persistently regressive—­meaning ad hoc “adjustments” of theories to accommodate counterevidence do not add new theoretical content that can be (and eventually is) empirically verified. Lakatos also argued that healthy theories experience progressive problem-­shift, wherein theoretical adjustments (i.e., new concepts and hypotheses added to the theory) not only address counterevidence but also add new empirical content that extends the explanatory reach of the theory. Hence, defense (or expansion) of a theory needs to be progressive to be scientifically legitimate. For Sabatier and Jenkins-Smith, this conception of scientific progress characterized the spirit of the theoretical growth of the ACF. The basic framework of the ACF (e.g., the assumptions and general subsystem dynamics) characterized the hard core while new propositions and theoretical logic (e.g., the addition of the concepts of coalition opportunity structures and endogenous pathways to policy change) occupy the auxiliary belt. Thus, revisions to the auxiliary belt were acceptable as long as they added new substantive theoretical content to the ACF. Indeed, the many additions to, and revisions of, key ACF hypotheses are reflections of this view of theory change and the growth of knowledge. Naturally, the assessment of whether these cumulative changes are truly progressive remains an open and important question.

The earliest journal publications of the ACF began with Sabatier (1986), where the ACF was described as a synthesis of top-down and bottom-up approaches to implementation, and continued with Sabatier and Pelkey (1987), where the ACF was described as an approach to understand regulatory policymaking.4 The first overview of the ACF by Sabatier (1987) was published in Knowledge, and a nearly identical publication by Sabatier (1988) led to the symposium on the ACF in Policy Sciences.5 Jenkins-Smith’s work on policy analysis within a process characterized by advocacy coalitions was published soon after (Jenkins-Smith, 1990). Applications of the framework slowly accumulated, with a coedited volume by Sabatier and Jenkins-Smith published in 1993.

The ACF has since become one of the most utilized frameworks of the policy process. The ACF has been the topic of five special issues in peer-reviewed journals, including Policy Sciences (Sabatier 1988), PS: Political Science & Politics (Sabatier 1991), Policy Studies Journal (Weible et al. 2011), Administration & Society (Scott 2012), and Journal of Comparative Policy Analysis (Henry et al. 2014). Weible, Sabatier, and McQueen (2009) and Pierce et al. (2017) conducted comprehensive reviews of over 240 English-language ACF applications from 1987 through 2014 that span the globe.6 Additionally, Sotirov and Memmler (2012) reviewed ACF applications in the context of environmental and natural resource issues. Country-specific reviews have been conducted for applications of the ACF in South Korea (Jang et al. 2016) and Sweden (Nohrstedt and Olofsson, 2016b). Jang et al. (2016) found 62 ACF applications in Korean, suggesting the ACF is frequently applied in other languages. One edited volume compares and contrasts advocacy coalitions and policy change on the topic of unconventional oil and gas development across seven countries in North America and Western Europe (Weible et al. 2016). In aggregate, these reviews confirm the portability of the ACF to different policy issues and governing systems, but they also expose areas where the ACF’s concepts and assumptions appear to be less applicable and problematic. We return to these issues below when discussing a research agenda for the future.

The ACF offers a general foundation for single case studies and for comparative analyses of policy processes across a wide range of policy issues and governing systems. Although a single chapter cannot adequately summarize the development of the ACF over time, present all the intricacies of the framework, list all the hypotheses offered by various analysts, or synthesize the findings from various applications of the framework, we offer here a synthesis of the most recent developments in the ACF and encourage interested readers to explore past theoretical and empirical publications as cited herein.


The Framework and Theoretical Emphases

Borrowing from Easton (1965), Laudan (1977, 70–120), Lakatos (1970), and Ostrom (2005, 27–29), the ACF is best thought of as a framework supporting multiple, overlapping theoretical foci.7 The purpose of a framework is to provide a shared research platform that enables analysts to work together in describing, explaining, and, sometimes, predicting phenomena within and across different contexts. The components of a framework include a statement of the assumptions, description of the scope or type of questions the framework is intended to help answer, and the establishment of concept categories and their general relations. Most importantly, a framework provides a common vocabulary to help analysts communicate across disciplines, from different substantive policy areas, and from different parts of the world. Akin to Lakatos’s hard core foundation of a research program, a framework should be fairly stable in its basic premises over time. Additionally, frameworks are not directly testable but provide guidance toward specific areas of descriptive and explanatory inquiry. This is an important reminder, given the misperception among some students and researchers that a comprehensive “test” of the ACF requires empirical assessments of all its components and relationships among them.

Rather, a framework supports multiple theories, which are narrower in scope and emphasize a smaller set of questions, variables, and relationships. Theories provide more precise conceptual and operational definitions of concepts and interrelate concepts in the form of testable and falsifiable hypotheses or propositions. The theories within the framework are where students and researchers should attempt to test and develop descriptions and explanations. Theories are, hence, akin to Lakatos’s protective belt that can (and should) be subject to experimentation, adjustment, and modifications over time. Although hypotheses should ideally offer refutable expectations among concepts, a pragmatic reason for using hypotheses is to highlight the most important relationships that describe what, why, and how those concepts relate and when and where those relationships are expected to be evident (Whetten 1987).


A Summary of the ACF as a “Framework”

A framework is best described by its assumptions, scope (type of questions), and basic categories of concepts and general relations for answering research questions. This section provides an overview of the framework of the ACF.


The policy subsystem is the primary unit of analysis for understanding policy processes. Policy subsystems are defined by a policy topic, territorial scope, and the actors directly or indirectly influencing policy subsystem affairs. Policy subsystems have several defining properties that help in interpretation and application (Sabatier 1998; Nohrstedt and Weible 2010). First, subsystems contain a large set of components that interact in nontrivial ways to produce outputs and outcomes for a given policy topic. These components range from physical and institutional characteristics to actor attributes, including belief systems and political resources. One of the purposes of a framework and its theories is to specify some of the most important subsystem components to study in attempting to help solve puzzles concerning the policy process. Second, policy subsystems demarcate the integrated and nonintegrated actors on a given policy topic. Policy subsystems do not involve all people interested and affected by the policy decisions. Indeed, given limited time and attention, most people do not engage in any subsystem and, for those who do, the number of policy subsystems where they are active is finite and usually small in number. Third, policy subsystems are semi-independent but overlap with other subsystems and are nested within yet other subsystems. For example, an energy policy subsystem in Colorado overlaps with a food policy subsystem in the same state and nests within a national energy policy subsystem in the United States.8 Fourth, policy subsystems often provide some authority or potential for authority. Such authority may exist in the enforcement and monitoring of policy, the legislative or legal processes, or the potential for new policies that may alter the status quo. Fifth, policy subsystems undergo periods of stasis, incremental change, and major change.

The set of relevant subsystem actors include any person regularly attempting to influence subsystem affairs. Borrowing from Heclo (1978), the depiction of subsystem actors expands beyond traditional interpretations of the policy process that tends to focus narrowly on legislative committees, government agencies, and interest groups. Subsystems are affected by any actor directly or indirectly influencing subsystem affairs and may include officials from any level of government, representatives from the private sector, members from nonprofit organizations, members of the news media, academic scientists and researchers, private consultants, lobbyists, think tanks, and even members of the courts (Hjern and Porter 1981). The extent and consistency of involvement and influence of these actors, of course, varies.

Individuals are boundedly rational, with limited ability to process stimuli, motivated by belief systems, and prone to experience the “devil shift.” The ACF conception of individuals is based on a modified version of methodological individualism, that is, change in the world is primarily driven by people and not by organizations (Sabatier 1987, 685). In the terms coalition beliefs, coalition behavior, and coalition learning, coalition is used metaphorically in reference to the individuals comprising the coalition. Indeed, coalitions do not learn, but rather the actors within coalitions learn. Furthermore, the modified version of methodological individualism in the ACF does not suggest that people’s behavior is independent of context. Indeed, the theory within the ACF would expect that people’s behavior is shaped by various contextual factors, particularly, the nature of relevant institutions, the intensity of conflict, and the perceived severity of threats posed by opponents.

The ACF’s assumption that individuals are boundedly rational means that people are motivated instrumentally by goals but are often unclear how to achieve those goals, and they are limited in their cognitive abilities to process stimuli such as information and experience (Simon 1957, 1985). Additionally, given limited cognitive abilities, individuals simplify the world through their belief systems and are, therefore, prone to biased assimilation of stimuli (Munro and Ditto 1997; Munro et al. 2002).

The ACF assumes that policy actors have a three-tiered belief system structure. Deep core beliefs are fundamental normative values and ontological axioms. Deep core beliefs are not policy specific and, thus, can be applicable to multiple policy subsystems. One way to conceptualize and measure deep core beliefs is by incorporating insights from cultural theory (Douglas and Wildavsky 1982; Ripberger et al. 2014; Jenkins-Smith et al. 2014; Trousset et al. 2015). Cultural theory offers four distinct orientations—hierarchs, egalitarians, individualists, and fatalists. Each of these orientations is buttressed by a set of “myths”—about human nature, society, and natural systems—that can serve both to justify the orientation and its values and to imply appropriate forms of social organization (Douglas and Wildavsky 1982; Thompson, Ellis, and Wildavsky 1990). Whereas cultural theory has demonstrated its utility as one way of conceptualizing and measuring deep core beliefs especially for comparative analyses, other ways certainly exist and could be developed.

In contrast to deep core beliefs, policy core beliefs are bound by scope and topic to the policy subsystem and thus have territorial and topical components. Policy core beliefs can be normative and empirical. Normatively, policy core beliefs may reflect basic orientation and value priorities for the policy subsystem and may identify whose welfare in the policy subsystem is of greatest concern. Empirically, policy core beliefs include overall assessments of the seriousness of the problem, basic causes of the problem, and preferred solutions for addressing the problem (called policy core policy preferences). Secondary beliefs deal with a subset of the policy subsystem or the specific instrumental means for achieving the desired outcomes outlined in the policy core beliefs.9 Finally, the ACF borrows one of the key findings from prospect theory that people remember losses more readily than gains (Quattrone and Tversky 1988). Remembering losses and the tendency to filter and assimilate stimuli through belief systems result in the “devil shift,” where actors exaggerate the power and maliciousness of their opponents (Sabatier, Hunter, and McLaughlin 1987). The expected result is a noncollaborative attitude, growing mistrust, the protraction of conflict, and the obstruction of effective policy solutions (Fischer et al. 2016).

Subsystems are simplified by aggregating actors into one or more coalitions. Depicting policy subsystems as consisting of any actor attempting to directly or indirectly influence subsystems affairs presents a dilemma for analysts: there might be hundreds of actors somehow involved in a policy subsystem. Also, analysts encounter subsystems at different levels of maturity; mature subsystems comprise relatively established and clearly differentiated coalitions, whereas nascent or emergent subsystems are characterized by ambivalence and unclear political positions. Simplifying assumptions must be made to describe and analyze.10 Analysts could organize subsystems by organizational affiliation, which provides important insight into the resources and strategies of actors in the policy subsystem, but the organizational level of analysis comes at the cost of realizing that the number of organizations involved in the policy subsystem is not many fewer than the number of actors.

A more effective approach is to organize actors into one or more advocacy coalitions on the basis of shared beliefs and coordination strategies. By grouping and analyzing actors by coalitions, the analysts can simplify the hundreds of actors and their organizational affiliations into groupings that may be stable over time (Sabatier and Brasher 1993) and that are instrumental for understanding policy actors’ strategies for influence and policy change (Nohrstedt 2010). Aggregating actors into coalitions can follow the rule of first identifying actors sharing similar belief systems, and subsequently searching for a non­trivial degree of coordination among those actors (Henry 2011). It then also raises original questions such as the degree of cross-coalition interactions, intracoalition cohesiveness, and factors contributing to coalition defection (Jenkins-­Smith, St. Clair, and Woods 1991).

Policies and programs incorporate implicit theories reflecting the translated beliefs of one or more coalitions. Public policy can be conceptualized and defined in multiple ways (Birkland 2010, 8). Whereas some definitions can be simply stated and communicated, such as defining public policy as any inaction and action by government, other definitions are more nuanced and insightful. Lasswell and Kaplan (1950, 71), for example, describe policy as “a projected program of goal values and practices.” Notable from this definition, and from similar ones, is the insight that public policy consists of translations of the belief systems of the designers. In this regard, public policies represent the political maneuvering and negotiations not just among coalitions but also of causal theories (Pressman and Wildavsky 1973, xv; Mazmanian and Sabatier 1983, 5). Causal theory, when used to describe the implicit or explicit content of public policy, refers to the sequence of steps, a linking of anticipated events, or desired procedures that describe the reasoning for achieving outputs and outcomes of a public policy. Analysts applying the ACF should, therefore, interpret policies not just as the actions or inactions of government but also as the translations of belief systems as manifested in goals, rules, incentives, sanctions, subsidies, taxes, and other instruments regulating any given issue (Jenkins-Smith et al. 2014, 486). This interpretation of policy provides insight into why coalition actors advocate so intently over time and how they interpret public policies as bolstering or as being antithetical to their belief systems.

Scientific and technical information is important for understanding subsystem affairs. In the previous assumption, belief systems were described as the mechanism for simplifying and interpreting the world. Belief systems are not, however, simply abstract representations of values and priorities but also encapsulate policy actors’ perceived causal patterns and relationships that shape the empirical world. A major source of this causal representation in a given context is scientific and technical information that can point to specific causal relations, problem attributes, and, sometimes, policy alternatives. To better understand policy processes is thus to understand how scientific and technical explanations are integrated into (or deflected from) belief systems, used in political debates and negotiations, and integrated with other forms of knowledge, especially local knowledge.11

Researchers should adopt a long-term time perspective (e.g., ten years or more) to understand policy processes and change. Policy processes are ongoing without beginning or end (Lindblom 1968, 4) and, thus, strategic behavior and learning of coalition actors, the reasoning and patterns of policy change, and assessments of the success or failure of public policy should be understood from a long-term perspective. The point has been misinterpreted to mean that a perspective of ten years or more is required to interpret policy processes through the ACF. This is too literal of an interpretation and often prevents interested analysts from applying the ACF even if the framework could help answer their research question. Some questions, for example, require intensive methods of data collection that preclude longitudinal data, such as an understanding of coalition structure using quantitative network analysis approaches (Henry 2011). Other datasets permit long-term perspectives, such as the multidecade perspectives taken by Albright (2011), Andersson (1999), and others to understand patterns of policy change. We also know that coalitions, though existing for decades, often take short-term perspectives as opportunities and constraints alter their immediate strategies (Jenkins-Smith, St. Clair, and Woods 1991). The general meaning behind this assumption is the recognition that understanding public policy requires focusing on temporal processes that characterize public policy over time.



A framework’s scope provides the set of general questions about the policy process that it helps the analyst answer. The traditional scope of the ACF includes questions involving coalitions, learning, and policy change. As suggested by the assumptions above, the framework is most useful for understanding these topics in high-conflict situations at the subsystem level of analysis. However, the framework has been applied in other settings, such as at the organizational level in collaborative settings (Leach and Sabatier 2005; Leach et al. 2013), a form of application to which we return when discussing future research agendas.

General Conceptual Categories and Relations

Flow diagrams are useful for identifying general categories of concepts and how they relate. Figure 4.1 presents a flow diagram depicting the policy process within the ACF.12 The policy subsystem is represented by the rectangle on the right illustrating a case with two competing coalitions representing their actors’ beliefs and resources. The two coalitions use various strategies to influence decisions by government authorities that affect institutional rules, policy outputs, and, eventually, policy outcomes. These decisions then feed back into the policy subsystem but also can affect external subsystem affairs.

One category of variables that condition subsystem affairs includes relatively stable parameters, which are the basic social, cultural, economic, physical, and institutional structures that embed a policy subsystem (Hofferbert 1974; Heclo 1974). Some concepts within relatively stable parameters are best conceptualized as external to subsystem affairs, such as the basic constitutional structure of the political system, whereas others can be internal to the subsystem, such as physical conditions of the subsystem. A second category of variables consists of dynamic external events, which includes relevant features external to the subsystem and prone to change. Examples include socioeconomic conditions, the state of subsystem-relevant technology, public opinion, the composition of governing coalitions (Burnham 1970), and spillover effects from other policy subsystems. The listings under relatively stable parameters and dynamic external events in Figure 4.1 are illustrative examples and are not exhaustive; clearly, other concepts can be placed in each category, such as crises and disasters under dynamic external events (Nohrstedt 2011; Jenkins-Smith, St. Clair, and Woods 1991). In between relatively stable parameters and a policy subsystem is an intermediary category of concepts concerning the nature of the long-term coalition opportunity structures that establish the degree of consensus needed for major policy change, the openness of the political system, and overlapping societal cleavages.

Essentially, long-term coalition opportunity structures are some of the important by-products of the relatively stable parameters on policy subsystems. Between external events and policy subsystems are the short-term constraints and resources of subsystem actors; this means that changes outside the subsystem provide short-term opportunities for coalitions to exploit.


Theoretical Emphases

Theoretical Focus on Policy Change

One of the central objectives of the ACF is to contribute to the understanding of policy change and stability, and this has been the subject of considerable empirical investigation. Thanks to these contributions, we now have more detailed knowledge about the nature and causes of policy change within and across policy subsystems than we had just a few decades ago. What has provoked this focus is the recurrent observation that, although many public policies and programs remain stable over long periods of time, others are subject to periods of dramatic and nonincremental change (Sabatier 1988; Baumgartner and Jones 1993).13 For example, indicators of such policy change may include revisions in policy core components of governmental programs, termination of programs, or launching of new programs.

Similarly to other theoretical perspectives on policy change (Baybrook and Lindblom 1963; Hall 1993; Rose 1993), the ACF focuses on the directionality of policy evolution and makes a clear distinction between minor and major policy change (Capano 2009, 2012; Howlett and Cashore 2009; Nisbet 1972). The level of change in a governmental program is defined according to the extent to which alterations deviate from previous policy. The ACF assumes that public policies and programs are translations of policy-oriented beliefs and can be conceptualized and measured hierarchically, like belief systems. Change in the core aspects, defined as “major policy change,” indicates significant shifts in the direction or goals of the subsystem, whereas change in secondary aspects (e.g., change in means for achieving the goals) is evidence for “minor policy change” (Sabatier and Jenkins-Smith 1999, 147–148). Advocacy coalitions often disagree on proposals related to these components, and policy debates therefore often revolve around diverging preferences regarding initiatives to either change or preserve governmental programs (Sabatier and Weible 2007, 195).

Since the belief system categories differ according to their susceptibility to change, minor policy change should be not as difficult to achieve as major policy change (Sabatier 1988). For example, minor changes in administrative rules, budgetary allocations, statutory interpretation, and revision are relatively frequent and do not necessitate as much evidence, agreement among subsystem actors, or redistribution of resources. By contrast, because normative (policy core) beliefs are rigidly held and screen out dissonant information, major policy change is unlikely as long as the advocacy coalition that instituted the program remains in power.

The ACF offers four conceptual pathways to policy change. The first is attributed to some external source (e.g., as might be found in the categories of dynamic external events or even relatively stable parameters from Figure 4.1). External shocks, or perturbations, include events outside the control of subsystem participants (in terms of their ability to influence underlying causes and triggers) and involve change in socioeconomic conditions, regime change, outputs from other subsystems, and extreme events such as some crises and disasters. These events increase the likelihood of major policy change but require one or several enabling factors (causal mechanisms), including heightened public and political attention, agenda change, and most importantly redistribution of coalition resources and opening and closing of policy venues (Sabatier and Weible 2007, 198–199). A key factor in this regard is mobilization by minority coalitions to exploit the event, for instance, by pursuing public narratives to attract attention to favored courses of action and by appealing to new actors (Sabatier and Jenkins-Smith 1999, 148; see also McBeth et al. 2007; Nohrstedt 2008). Because of the importance of these intervening steps, it has been hypothesized that significant perturbations external to the subsystem are one of the necessary, but not sufficient, paths for changing the policy core attributes of a governmental program (Sabatier 1988).

Major policy change may also result from a second pathway based on internal events that (1) occur inside the territorial boundaries and/or the topical area of the policy subsystem and (2) are more likely affected by subsystem actors (Sabatier and Weible 2007, 204–205). Various types of internal events, including crises, policy fiascoes, scandals, and failures, are likely to influence beliefs and heighten attention to certain governmental programs (Birkland 2006; Bovens and ’t Hart 1996). Advocacy coalitions can be expected to engage in framing contests over such events and debate the severity of problems, their underlying causes, attribution of responsibility, and policy implications (Boin, ’t Hart, and McConnell 2009; Nohrstedt and Weible 2010). Internal events can be expected to confirm the policy core beliefs of minority coalitions and increase doubts about the core beliefs of the dominant coalition and bring into question the effectiveness of their policies. Whether or not internal shocks result in major policy change depends on the same mechanisms that mediate the effect from external shocks.

A third source of minor policy change is policy-oriented learning, but this is likely to happen incrementally over longer periods of time. Following Caplan, Morrison, and Stanbaugh (1975) and Weiss (1977), Sabatier (1988) expects that policy analysis seldom influences specific governmental decisions but often serves an “enlightenment function” by gradually altering the concepts and assumptions of subsystem participants. In addition, learning can also facilitate major policy change, but this is more likely when learning takes place in conjunction with an external or internal shock (Nohrstedt 2005).

A fourth pathway to policy change is through negotiated agreement among previously warring coalitions and may result in substantial change in governmental programs. Negotiated agreements may emerge in a variety of ways but are facilitated by collaborative institutions conducive to negotiation. Specifically, Sabatier and Weible (2007, 205–206) identify nine prescriptions fostering negotiation: a “hurting stalemate,” broad representation, leadership, consensus decision rules, funding, commitment by actors, importance of empirical issues, trust, and lack of alternative venues. The most important condition instigating negotiations is a “hurting stalemate,” which occurs when warring coalitions perceive the status quo as unacceptable and do not have access to alternative venues for achieving their objectives (Weible and Nohrstedt 2012, 132).

A recent review of ACF case studies shows that among 161 empirical applications from 2007 to 2014, learning is the most frequently cited source of policy change (identified in 29 percent of the applications reviewed), followed by external sources and events (28 percent), negotiated agreements (14 percent), and internal events (6 percent) (Pierce et al. 2017).

In summary, the original version of the ACF offered two hypotheses of policy change, focusing on external perturbations and power shifts. However, Weible and Nohrstedt (2012, 133) merge the four pathways to policy change into a single hypothesis:

Policy Change Hypothesis 1. Significant perturbations external to the subsystem, a significant perturbation internal to the subsystem, policy-oriented learning, negotiated agreement, or some combination thereof is a necessary, but not sufficient, source of change in the policy core attributes of a governmental program.

There has been strong support for the first policy change hypothesis. Many find support for at least one of the pathways (Barke 1993; Bischoff 2001; Green and Houlihan 2004; Tewari 2001; Kübler 2001; Dudley and Richardson 1999). One challenge in testing this hypothesis is the occurrence of one of the pathways without a change in policy (Weible, Sabatier, and McQueen 2009; Sotirov and Memmler 2012). Another challenge is explaining minor policy changes after an external shock (Burnett and Davis 2002; Davis and Davis 1988). Critical in testing the first hypothesis about policy change is to understand how a coali­tion can capitalize on (or exploit) the opportunity, which ultimately involves attempts to either preserve the status quo or seek policy change. This has led some analysts to focus heavily on coalition resources and strategies following various external events and developments (Smith 2000; Ameringer 2002; Albright 2011; Ingold 2011; Nohrstedt 2005, 2008).

The second hypothesis relates coalition influence in the subsystem, major policy change, and nested policy subsystems:

Policy Change Hypothesis 2. The policy core attributes of a government program in a specific jurisdiction will not be significantly revised as long as the subsystem advocacy coalition that instated the program remains in power within that jurisdiction—except when the change is imposed by a hierarchically superior jurisdiction.

There is strong to partial support for Policy Change Hypothesis 2 (Sotirov and Memmler 2012). Studies that confirm the logic of the second policy change hypothesis include Ellison (1998), Olson, Olson, and Gawronski (1999), Elliot and Schlaepfer (2001), and Kübler (2001). However, this second policy change hypothesis has been tested but a few times.

One of the next steps in studying policy change will be to focus on developing best practices for documenting and explaining policy while accounting for context. Too many studies of policy change apply different methods of data collection and analysis, with the result that comparison across cases is difficult. In addition, studies adopt slightly different definitions of policy, which complicates the task of comparing drivers of policy change across governing systems.

Advocacy Coalitions

Advocacy coalitions are defined by actors who share policy core beliefs and who coordinate their actions in a nontrivial manner to influence a policy subsystem. In studying coalitions, analysts typically focus on a range of topics, from the structure and stability of coalition actor belief systems to the formation and maintenance of coalitions over time. The traditional hypotheses about advocacy coalition include the following:

Coalition Hypothesis 1. On major controversies within a policy subsystem when policy core beliefs are in dispute, the lineup of allies and opponents tends to be rather stable over periods of a decade or so.

Coalition Hypothesis 2. Actors within an advocacy coalition will show substantial consensus on issues pertaining to the policy core, although less so on secondary aspects.

Coalition Hypothesis 3. Actors (or coalitions) will give up secondary aspects of their belief systems before acknowledging weaknesses in the policy core.

Coalition Hypothesis 4. Within a coalition, administrative agencies will usually advocate more moderate positions than their interest group allies.

Coalition Hypothesis 5. Actors within purposive groups are more constrained in their expression of beliefs and policy positions than actors from material groups.

From these hypotheses, evidence to date largely confirms Coalition Hypothesis 1 about the stability of coalitions over time (see Pierce et al. 2017 review paper). To assess the stability of coalitions, most of these studies use coded legislative statements (Jenkins-Smith, St. Clair, and Woods 1991; Jenkins-Smith and St. Clair 1993; Sabatier and Brasher 1993; Zafonte and Sabatier 2004; Pierce 2011; Nohrstedt 2010), with a few studies using survey and interviews (Weible, Sabatier, and McQueen 2009; Ingold 2011) and discourse analysis (Leifeld 2013). Important in these studies is the documentation that although coalitions are generally stable over time defection is not uncommon and membership often changes. Analysts have documented a range of reasons for defection or change in coalition composition, such as extreme coalition actors defecting to prevent the adoption of “balanced” policies (Munro 1993, 126); major internal or external events that switch allegiances, especially elections (Jenkins-Smith, St. Clair, and Woods 1991; Zafonte and Sabatier 2004; Pierce 2011); and strategic decisions by coalition actors to achieve short-term political objectives (Nohrstedt 2005; Larsen, Vrangbaek, and Traulsen 2006). To further develop Coalition Hypothesis 1, the next steps must develop and test a range of theoretical rationales for the stability or instability of coalitions.

The testing of Coalition Hypotheses 2 and 3 has resulted in only a few confirmations (Weyant 1988; Elliot and Schlaepfer 2001; Kim 2003) but many falsifications and, at best, findings of partial support (Barke 1993; Jenkins-Smith and St. Clair 1993; Sabatier and Brasher 1993; Olson, Olson, and Gawronski 1999; Sobeck 2003; Larsen, Vrangbaek, and Traulsen 2006; Ingold 2011; Zafonte and Sabatier 2004). There are at least two interpretations for the mixed support for Coalition Hypotheses 2 and 3. The first interpretation involves variation in conceptualizations and measurement of belief systems in establishing coalitions. If this interpretation is correct, there needs to be a concerted effort to clarify the theoretical distinction between policy core and secondary aspects as well as methodological guidelines for measurement. Olson, Olson, and Gawronski (1999), for example, found it difficult to isolate policy core beliefs from secondary aspects. The second interpretation points to a faulty or imprecise model of the belief system and overall logic of Coalition Hypotheses 2 and 3. To put it simply, even if analysts could adequately measure and distinguish policy core and secondary aspects, perhaps Coalition Hypotheses 2 and 3 are wrong. Although we are not in a position in this chapter to reject both hypotheses, we underscore the mixed support for them and draw attention to a need for better approaches in conceptualizing and measuring belief systems in the ACF.

The fourth and fifth hypotheses are rarely tested in the ACF. Evidence supporting the Coalition Hypothesis 4 remains mixed, with some evidence offering confirmation (Jenkins-Smith, St. Clair, and Woods 1991; Jenkins-Smith and St. Clair 1993) and others providing only partial to no support (Sabatier and Brasher 1993). The most important confirmation for Coalition Hypothesis 5 remains Jenkins-Smith, St. Clair, and Woods (1991) and Jenkins-Smith and St. Clair (1993). The implication from this assessment is clear enough: there is a need for renewed testing and development of Coalition Hypotheses 4 and 5.

Although it is not a traditional hypothesis, a large number of studies have tested the expectation that coalitions form on the basis of shared beliefs, known as the Belief Homophily Hypothesis. Studies confirming this hypothesis can be found in a number of publications, including Weible (2005), Matti and Sandström (2011), Henry (2011), Ingold (2011), and Leifeld (2013). Whereas the results tend to confirm the Belief Homophily Hypothesis, the findings raise two new implications for studying coalitions under the ACF. The first implication is the presence of other factors, outside of beliefs, that affect coalition formation and stability. These other factors include, but are not limited to, perceived influence or resources of others (Weible 2005; Matti and Sandström 2011), interests (Nohrstedt 2010), and trust (Henry, Lubell, and McCoy 2011). The second implication is that coalitions are shaped more by sharing opponents than by sharing beliefs (Henry, Lubell, and McCoy 2011). Research on the Belief Homophily Hypothesis supports the argument that beliefs remain a major factor in forming and maintaining coalitions, but other factors clearly have an effect, and the precise role of beliefs in shaping coalitions needs theoretical refinement.

The traditional hypotheses about coalitions highlight some of the theoretical logic about coalitions and many of the most important concepts. However, the theoretical argument about coalitions is broader than is articulated in the listed hypotheses and sometimes includes additional concepts and their interrelations, some of which are summarized below in four categories.

  • Dominant and minority coalitions. Although some subsystems exhibit advocacy coalitions steeped in conflict marked by long periods of ongoing one-upmanship, other subsystems exhibit a “dominant” coalition that largely controls (most likely through resource superiority) subsystem politics and policy, and either a “minority” coalition vying for influence or the absence of any coordinated opposition. Even though a number of studies have documented the stability of dominant advocacy coalitions in steering a policy subsystem, the attributes of various coali­tions remain underdeveloped, particularly the comparison of beliefs, resources, strategies, and activities.
  • Overcoming threats to collective action. One of the critical theoretical arguments that has yet to be sufficiently developed involves how coalitions overcome threats to collective action (Schlager 1995). Actors form coali­tions and overcome threats to collective action on the basis of three rationales (Zafonte and Sabatier 1998; Sabatier and Weible 2007, 197). First, similar beliefs among allies reduce the transaction costs for coordination. Second, actors are involved in policy subsystems at different levels of intensity and, thus, some engage in weak forms of coordination (sharing information) and others in strong forms of coordination (jointly developing and executing shared plans). Third, actors often experience the devil shift and, therefore, exaggerate the costs of inaction and the need for action (Sabatier, Hunter, and McLaughlin 1987).
  • Principal and auxiliary coalition actors. Network analysis techniques have shown that some coalition actors are more central to a coalition than others and that sometimes actors rarely interact with their allies. To account for this variation in coalition membership, a distinction is made between actors who are principal and those who are auxiliary to a coalition (Larsen, Vrangbaek, and Traulsen 2006; Silva 2007; Zafonte and Sabatier 2004; Weible 2008). Principal actors are expected to be more central and consistent coalition members, whereas auxiliary actors are expected to be on the periphery, involved intermittently or sometimes only for a short period of time, and therefore not as regularly engaged in coalition-related activities.
  • Resources, strategies, and activities. Coalitions are marked not only by shared beliefs and coordination patterns but also by their resources. These resources include formal legal authority to make policy decisions, public opinion, information, mobilizable supporters, financial resources, and skillful leadership (Sabatier and Weible 2007; Weible 2007; Nohr­stedt 2011; Ingold 2011; Albright 2011; Elgin and Weible 2013). Resources are an important contribution that provide the theoretical leverage for understanding the capacity of a coalition to make strategic decisions and engage in various activities to influence policy subsystems.

Overall, the support for the study of coalitions is strong for Coalition Hypoth­esis 1 and for the Belief Homophily Hypothesis, mixed for Coalition Hypotheses 2 and 3 that involve the hierarchical belief systems in the ACF, and mostly untested for Coalition Hypotheses 4 and 5. Several underdeveloped areas within this theoretical emphasis involve the role of coalition resources, strategies, and activities; the role and type of coalition members; the testing of the argument involving the collective action rationale for the formation of coalitions; and the continued development of dominant and minority coalitions.


Policy-Oriented Learning

Policy-oriented learning is one prominent pathway within the ACF for the explanation of policy change and plays a central role in belief change and reinforcement of members of advocacy coalitions. If it has always been of central focus within the ACF, it is possibly still the most intractable concept to study (Bennett and Howlett 1992; Levy 1994). Policy-oriented learning is defined as “enduring alternations of thought or behavioral intentions that result from experience and which are concerned with the attainment or revision of the precepts of the belief system of individuals or of collectives” (Sabatier and Jenkins-Smith 1993, 42). Learning is associated with changes in beliefs systems of coalition members that include not only the understanding of a problem and associated solutions but also the use of political strategies for achieving objectives (see May 1992). Some of the important questions in the study of learning include: What belief system components change or remain the same through learning? What contexts foster learning by coalition members? How does learning diffuse among allies and possibly among opponents? What is the role, if any, of policy brokers in facilitating learning among opponents?

The theory underlying learning in the ACF emphasizes four categories of explanatory factors.

  • Attributes of forums. Forums are the venues where coalitions interact, debate, and possibly negotiate. Jenkins-Smith (1982, 1990, 99–103) makes the theoretical argument about how the attributes of a forum, essentially the forum’s institutional arrangement, affect the extent that learning occurs among allies and opponents. A couple of the most important attributes defining a forum are the degree of openness in participating (open vs. closed forums) and the extent that participating actors share a common analytical training and norms of conduct.
  • Level of conflict between coalitions. Level of conflict relates to the extent that actors perceive a threat to their policy core beliefs from their opponents’ objectives or actions. Jenkins-Smith (1990, 95–97) and Weible (2008) essentially argue for an inverted quadratic relationship between level of conflict and learning between members of opposing coalitions, which has been called “cross-coalition learning.” At low levels of conflict, there is little cross-coalition learning because coalition actors attend to other subsystem affairs. At high levels of conflict, there is also little cross-coalition learning because coalition actors defend their positions and reject information that disputes their belief systems. At intermediate levels of conflict, opposing coalitions are threatened just enough to attend to the issue and remain receptive enough to new information to increase the likelihood for cross-coalition learning.
  • Attributes of the stimuli. Attributes of the stimuli relates to the type of ­information and experience coalition actors are exposed to. Jenkins-­Smith (1990, 97–99) argues that analytically intractable phenomena involve uncertainty, low-quality data, and, hence, variation in interpretation and high levels of disagreement. The more intractable an issue, the lower the level of cross-coalition learning expected.
  • Attributes of actors. Attributes of the individual actors include their belief system, resources, strategies, and network contacts. Given the importance of belief systems in filtering and interpreting information, for example, the expectation is that coalition actors with extreme beliefs are less likely to learn from opponents than are coalition actors with more moderate beliefs. Additionally, some actors can serve as policy brokers who primarily seek to mitigate the level of conflict and help opponents reach agreements (Sabatier and Jenkins-Smith 1993, 27). There are no predetermined criteria defining who can or cannot be a broker within a subsystem; indeed, a broker could be affiliated with any organization type, from academia to government to the private or nonprofit sector. One important role for brokers is facilitating learning among opponents (Ingold and Varone 2012).

These four attributes can be found in the following five hypotheses on policy-­oriented learning within the ACF:

Learning Hypothesis 1. Policy-oriented learning across belief systems is most likely when there is an intermediate level of informed conflict between the two coalitions. This requires that: (1) each has the technical resources to engage in such a debate, and (2) the conflict is between secondary aspects of one belief system and core elements of the other or, alternatively, between important secondary aspects of the two belief systems.

Learning Hypothesis 2. Policy-oriented learning across belief systems is most likely when there exists a forum that is: (1) prestigious enough to force professionals from different coalitions to participate and (2) dominated by professional norms.

Learning Hypothesis 3. Problems for which accepted quantitative data and theory exist are more conducive to policy-oriented learning across belief systems than those in which data and theory are generally qualitative, quite subjective, or altogether lacking.

Learning Hypothesis 4. Problems involving natural systems are more conducive to policy-oriented learning across belief systems than those involving purely social or political systems because in the former many of the critical variables are not themselves active strategists and because controlled experimentation is more feasible.

Learning Hypothesis 5. Even when the accumulation of technical information does not change the views of the opposing coalition, it can have important impacts on policy—at least in the short run—by altering the views of policy brokers.

Studies of policy-oriented learning have not always supported these hypotheses. A good number of studies have documented learning at both secondary (expected) and policy core (not expected) levels of the belief system (Sabatier and Brasher 1993; Eberg 1997; Elliot and Schlaepfer 2001; Larsen, Vrangbaek, and Traulsen 2006). These results echo the mixed support for Coalition Hypotheses 2 and 3. That is, the hierarchical belief system of the ACF—­especially the distinction between policy core and secondary aspects—is not finding strong support in many of the hypothesis tests.

In support of Learning Hypothesis 3, Sotirov and Memmler (2012) find in their review of the literature that a handful of studies show that learning was limited when data were lacking or were of qualitative or subjective nature (e.g., Weyant 1988; Elliot and Schlaepfer 2001; Nedergaard 2008), but the findings also show the same for situations for learning using quantitative data (Elliot and Schlaepfer 2001; Kim 2003).

Studies have found that learning is more likely to occur with tractable issues, with intermediate levels of conflict, and with the availability of scientific and technical information (Larsen, Vrangbaek, and Traulsen 2006; Meijerink 2005; Elliott and Schlaepfer 2001). Providing indirect support for learning within the ACF, Leach et al. (2013) find forum structure, attributes of the individual learner, and level of scientific certainty affected belief change and knowledge acquisition. This is an area in need of renewed theoretical and empirical attention.

One promising direction of research involves development of the policy broker concept (Ingold and Varone, 2012). This work finds support for Learning Hypothesis 5 and identifies some systematic evidence that certain actor types are more likely to play the broker role than others. These actors are not acting in an altruistic way: to engage in a brokerage role, they need a certain level of self-interest and an awareness of the potential benefits from policy compromise or the potential losses from the status quo.

Across many of the applications of learning, the most pressing concern is the inconsistency in conceptualization and measurement of the concept. And similarly to the change hypotheses, what also needs to be addressed in this theoretical emphasis is a set of best practices for studying learning within and across advocacy coalitions. There must also be a fresh look at the factors that shape learning, including levels of conflict, attributes of the actor, the role of policy brokers, nature of stimuli, and characteristics of the forum.

A Future Research Agenda

The future trajectory of the ACF depends on the innovative and creative efforts of numerous analysts from around the world. Nonetheless, we offer a research agenda for analysts to consider in moving the framework forward.

Reconsider the ACF’s belief system. Empirical applications of the ACF suggest that the belief system model needs to be further specified. There are many ways forward, including clarifying the distinction between policy core and secondary beliefs, combining the policy core beliefs and secondary beliefs into a single category under deep core beliefs, and drawing inspiration from other theories, such as the value-belief-norm theory (Stern 2000; Henry and Dietz 2012), cultural theory (Douglas and Wildavsky 1982; Jenkins-Smith et al. 2014), and Narrative Policy Framework (Shanahan, Jones, and McBeth 2011).

Advance the theory and measures of learning. Despite its centrality to the framework, conceptual development of policy-oriented learning—including causes, kinds of learning, and implications—is among the least mature components of the ACF. Analysts are encouraged to undertake reexamination of this concept within the framework as well as the theoretical implications. Research in this domain should emphasize clear conceptualization and measurement of various products of learning and the processes by which it is encouraged and inhibited (Heikkila and Gerlak 2013).

Refine the theory of coalition structures and coordination. The study of coalitions remains a staple of the framework, and significant advances in understanding coalitions have occurred over the past decade, particularly with network analysis techniques (Henry 2011). This effort should continue with special attention to the assumed hierarchy of belief homophily and coordination patterns among coalition members (Calanni et al. 2015; Ingold and Fischer 2014). It also needs to focus on the sources of stability of coalitions, with attention to the likelihood and reasons for defection by coalition members.

Develop a hierarchy for coalition resources. The ACF assumes that access to and exploitation of various political resources are important for advocacy coalitions as they seek to influence public policy. Following Sewell (2005) and Sabatier and Weible (2007, 201–204), we encourage efforts to identify a typology of political resources that includes formal legal authority to make policy decisions, public opinion, information, mobilizable troops, financial resources, and skillful leadership. Although coalition resources were long neglected in empirical research (Sabatier and Weible 2007, 201), recent studies have investigated how coalitions mobilize and exploit resources in the policy process (Albright 2011; Ingold 2011). These studies confirm that redistribution of political resources is an important step in explaining policy change. Meanwhile, as suggested by Nohrstedt (2011, 480), some resources are more important than others for coalitions to achieve influence, which is ultimately given by governing system attributes such as constitutional rules. For example, having coalition actors in positions of legal authority is a major resource because legislators are veto players whose agreement is needed for policy change (Tsebelis 1995; see also Sabatier and Pelkey 1987). Legal authority is also one defining element of a dominant coalition, which has more of its allies in positions of formal authority than do minority coalitions (Sabatier and Weible 2007, 203). Resources could therefore be hierarchically arranged with regard to their perceived usefulness and effectiveness to coalitions, which in turn raises challenges and questions for future research (Weible et al. 2011, 356–357). For example, under what conditions are some resources more important than others for coalitions to gain influence? Which strategies do coalitions utilize to select which resources to exploit? What is the relative importance of specific kinds of resources in different political systems? How does redistribution of resources influence policy change and learning? A related challenge is to advance approaches to operationalize resources by, for example, network analysis (Ingold 2011) and qualitative research (Mintrom and Vergari 1996; Nohrstedt 2011).

Study venues and forums within policy subsystems. The focus of the ACF on policy subsystems has important impacts on conducting research. However, some notable applications of the ACF have focused on organizational-level analysis, especially in the area of collaborative partnerships (Leach and Sabatier 2005; Leach et al. 2013). For example, Leach and Sabatier (2005) applied the ACF in the study of watershed partnerships. These partnerships, however, do not encapsulate the entire policy subsystem but rather involve a single venue within the subsystem. As a result, the study of the partnership represents a selected sample of subsystem actors choosing to participate in the partnership. Such organizational-level applications of the ACF are encouraged because we gain a deeper understanding of how coalition actors learn from each other and negotiate agreements. Additionally, because coalitions seek to affect government decisions through venues, the choice of one venue over another remains an important topic of study.

Use the ACF for comparative public policy research. Most comparative work on the ACF has been based on implicit comparison across political-­institutional systems. Few empirical studies based on the ACF systematically compare policy subsystems, coalition behavior, and policy processes across political systems (Gupta 2012). One is an ACF study applied in seven countries (Canada, France, Germany, Sweden, Switzerland, the United Kingdom, and the United States) that compares the policies and regulations related to oil and gas development using hydraulic fracturing (Weible et al. 2016). Using different methods of data collection and analyses, the same research questions about advocacy coalitions and the propensity for policy change were asked and answered. The comparison confirmed the importance of subsystem properties for explaining differences observed across the seven countries (Ingold et al. 2016). Not only do basic institutional and constitutional arrangements of the political system decisively affect coalition formation and the propensity for policy change but also subsystem attributes (such as jurisdictional level, maturity, or autonomy) and issue characteristics (such as salience and potential threat to certain values within the belief system) do as well. We encourage future work in this direction, developing systematic comparisons of policy subsystems across countries to disentangle the factors accounting for advocacy coalitions, policy-oriented learning, and policy change.

The expansion of applications to new countries is a trend that can inspire future comparison across systems. Comparative work obviously brings additional costs in terms of data acquisition and analysis but also important gains in terms of new insights regarding the role of political institutions and cultures in shaping the formation, maintenance, and behavior of advocacy coalitions in the policy process. Here is a gap waiting to be filled. Fruitful avenues for future comparative work involve vicarious policy-oriented learning (how coalitions learn from the experience of others) and policy transfer (how policies diffuse from one political system to another) (Bandura 1962; Dolowitz and Marsh 1996). Following the emphasis on coalition opportunity structures (Kübler 2001; Sabatier 1998; Sabatier and Weible 2007), there is also a need to investigate how specific institutional attributes such as veto players, the required level of consensus, and system openness shape coalition interaction and policy change (Fischer 2015; Gupta 2013). Empirical research in these areas would yield important insights about the policy process and expose questions and areas for future research, including the role and importance of advocacy coalitions as a type of political organization actors exploit to coordinate strategies and gain influence. Although comparative analysis is a long-term challenge and will probably generate limited generalizability in the short term given the complexity of the policy process (Schmitt 2012), the ACF offers concepts and assumptions that should stimulate and facilitate comparative analysis.

Focus on types of actors, including auxiliary and principal coalition actors, policy brokers, and policy entrepreneurs. Exceptional actors often play critical roles in policy subsystems. Some of these actors could be principal coalition actors but possibly auxiliary coalition actors. Other categories are policy brokers (Ingold and Varone 2012) and policy entrepreneurs (Mintrom 2009; Mintrom and Vergari 1996). From its earliest renditions, the ACF has suggested that brokers can play important roles in policy-oriented learning (Sabatier and Jenkins-Smith 1993), and empirical applications have provided some evidence on brokers’ impact on policy outputs (Ingold and Varone 2012; Ingold 2011). But further research is needed to theoretically and empirically refine the role of brokers in policy subsystems in general (Christopoulos and Ingold 2015) and in the design of learning mechanisms in particular. Policy entrepreneurs might also be critical players in maintaining coalitions and causal drivers of policy change, but few have analyzed this type of exceptional actor in ACF studies.

Focus on nascent and mature policy subsystems. Most studies of the ACF focus on mature policy subsystems. In mature policy subsystems, policy actors have typically fortified their belief systems about the risks and benefits associated with an issue, they interact in stable advocacy coalitions, and conflicts among opponents have endured over time both within and across decision making venues. Sometimes, mature policy subsystems absorb new issues as they emerge on the political agenda, whereas on other occasions new issues provoke the formation of a new policy subsystem (Nohrstedt and Olofsson 2016a). Unfortunately, few scholars have studied nascent policy subsystems (Ingold, Fischer, and Cairney 2016; Stritch 2015; Beverwijk, Goedegebuure, and Huisman 2008). As a result, theoretical insights about nascent subsystems remain underdeveloped. Speculatively, nascent policy subsystems are likely to feature policy actors with ambiguous perceptions of the risk and benefits of a policy issue, unclear preferences for known policy solutions, and unstable alliances among allies and opponents. Studies on nascent subsystems could yield insights about the initial conditions of policy subsystem characteristics, the process of coalition formation, the establishment of interactions within and across coalitions, and the role of coalitions in agenda setting. A focus on nascent policy subsystems will allow scholars to adopt a prospective approach (e.g., how does the variation in initial conditions in nascent policy subsystems give rise to differences in conditions in mature policy subsystems?), help identify the reasons for nascent subsystem formation (e.g., in response to a crisis, a policy change, or other), and assist in investigating the propensity for future policy change (Weible et al. 2016).

Expand our understanding of science and policy analysis in the policy process. The ACF was originally created to help inform the role of scientists and science in the policy process. Several recent publications address this area. Much of this work began with Jenkins-Smith’s (1990) theoretical and empirical efforts in studying the role of policy analysis in the policy process. Since then the effort has shifted mostly to the roles of scientists and technicians and scientific and technical information in the policy process (Jenkins-Smith and Weimer 1985; Weible 2008; Silva and Jenkins-Smith 2007; Silva, Jenkins-Smith, and Barke 2007; Weible, Sabatier, and Pattison 2010; Montpetit 2011; Lundin and Öberg 2014). This research strongly suggests that the use of science and policy analysis is driven by the level of conflict in the policy subsystem (Jenkins-Smith 1990; Weible 2008). The next step is to test these expectations under different conditions and develop a coherent theoretical explanation for the findings.

Establish common methods of data collection and analyses for applying the framework, identify trade-offs in using different methods, and promote contextually based theoretical innovations. The ACF is a tool for comparative analyses of policy processes. To foster comparative work, there is a need to develop common methods of collecting and analyzing data given common research questions. Clearly, some methods of data collection and analysis are more suitable in some contexts than in others (e.g., online surveys vs. interviews). Similarly, other methods of data collection and analysis are feasible when directly comparing policy subsystems over time (e.g., newspaper content analysis). The best strategy is not to promote one method of data collection and analysis over another but rather to utilize the best methods given the research questions, contexts, and resources of the researchers. To support such an effort, researchers must recognize the trade-offs of different approaches and, ideally, combine more than one to capture their respective strengths and compensate for their weaknesses.

Explore the need for theoretical refinement emanating from application in nontraditional settings. Underlying the need for comparative methods is a simultaneous need for contextually based theoretical development. The majority of empirical applications of the ACF involves cases of mature policy subsystems marked by high conflict in heavily democratized political systems (Weible et al. 2016; Pierce et al. 2017). Application of the ACF to nascent subsystems, to policy subsystems marked by low or moderate levels of conflict, or to policy subsystems within different types of political systems is less frequent and might require theoretical innovations and adjustments. Prior comparative work on the ACF outside the United States and Western Europe reports strengths as well as weaknesses; studies confirm the applicability of the ACF’s concepts and assumptions, and they identify limitations related to descriptive and explanatory validity (Henry et al. 2014). Although some of these limitations (as discussed above in this chapter) apply more broadly, scholars should also identify limitations that are related to the attributes of policy processes in (for example) hybrid or authoritarian regimes. Ascertaining how the ACF might be adapted to address this expanded array of contexts (without altering the framework’s axiomatic propositions) and how the ACF fares compared to alternative frameworks are important questions for the future.14



Our intent in this chapter is to provide an overview of the ACF research program. The framework has attracted worldwide attention and scholarship over several decades, and we readily acknowledge that in this short chapter we have not been able to adequately incorporate all of the important theoretical and empirical contributions. To supplement this chapter, we highly recommend the excellent theoretical and methodological insights that can be found in Fischer (2015) on the role of institutions on coalition formation, in Sotirov and Memmler (2012) on the ACF in environmental and natural resource contexts, and in Leifeld (2013) on discourse coalitions. In addition, some of the best emerging work can be found in recent PhD dissertations (Gupta 2013; Valman 2014; Donadelli 2016). The continuing growth of ACF scholarship gives us some confidence that—over thirty years after its initial articulation—the framework is still undergoing progressive problem-shift.

We conclude this chapter with a challenge. Although the ACF has spawned a fruitful research program on coalitions, learning, and policy change, we must raise the question: What ends will ACF research serve? Clearly, analysts applying the ACF must continue to use the best science available to improve and develop the framework and to seek answers to some of the most pressing puzzles about policy processes. But some analysts must also work toward developing the framework as a tool for informing and, possibly, improving actual policy processes. To what extent can the framework be used as a policy analysis tool for informing decisions (Nohrstedt 2013; Weible, 2007)? Can the logic of the framework help people strategically influence the policy process (Weible et al. 2012)? And can we eventually draw lessons from the framework to inform what may enhance (or undercut) the capacities of a policy process for the betterment of society? We do not have answers to these questions, but we encourage new and experienced analysts to take them on.



  1. We must disclose our liability to Paul Sabatier, who permanently influenced how we think as serious social scientists. After years of exposure to Paul, Hank’s sense of humor is permanently warped, Daniel remains addicted to clarifying mush, Chris will never overcome his impulsive inclination to code everything (this footnote is already coded), and Karin suffers from chronic periods of transfixion in the absence of theoretical guidance. Given that we cannot escape from the influence of Paul’s way of thinking, we have learned to embrace his impact on our lives by drinking a beer or stinger in his name, a habit we trust others will soon adopt. Furthermore, whereas all errors and omissions will forever be wrought by those sinister forces in the world muddying the lucidity of our thoughts and communications, we remain steadfast in achieving greater clarity in our theories and methods and in believing that this effort will eventually beget clarity in our understandings and explanations.
  2. Sabatier submitted the initial theoretical manuscript of the ACF, as the lead article in a special issue on the ACF, to Policy Sciences. The manuscript was eventually rejected with a scathing blind review in 1984.
    This paper has little to recommend it. The conceptual framework is a conceptual mishmash that makes no obvious contributions to our ability to do policy analysis, to design institutions to use policy analysis, or to understand policy processes. The author never explains the potential value of a conceptual framework such as he attempts to develop. The unit of analysis is incoherent. The hypotheses offered are banal and/or nonoperational. There are no data, only allusions, adductions, and sketchy examples. The organization is loose and wandering. There is little to disagree with in this paper; refutation would require more operational concepts, a tighter logic and/or data. . . . The problems with this paper are legion.
    Other attempts to publish a theoretical overview of the ACF by Sabatier continued with rejections received from the Journal of Policy Analysis and Management (JPAM) in 1985 and the American Journal of Political Science (AJPS) in 1985.
  3. The ACF adds a third layer, the policy core, which includes beliefs that are general to, and highly salient for, the concrete policy subsystem.
  4. Interested readers will also find one of the first publications of the ACF in Jenkins-­Smith’s dissertation (1985).
  5. A symposium on the ACF was also accepted in Knowledge: Creation, Diffusion, and Utilization with a projected publication in 1987 (Sabatier 1987). Early in 1987, however, Sabatier and Jenkins-Smith withdrew the symposium from Knowledge and submitted it to Policy Sciences, wherein it was published in 1988.
  6. Pierce et al. (2016) tabulated the number of applications from 2007 through 2014 by the following topical areas: environmental or energy issues (n = 70), public health (n = 15), education (n = 14), science and technology (n = 12), social welfare (n = 12), foreign and defense (n = 8), economic and finance (n = 7), urban planning and transportation (n = 5), and other (n = 18). Pierce et al. (2016) also found most applications in North America and Western Europe but an increasing number that span the world.
  7. In the ACF literature, there have been differences in the interpretation of the terms framework and theory (see, for example, Sabatier and Jenkins-Smith 1999, 154–155). Despite the different interpretations and uses in the past, we find the clearer and more explicit articulation of the framework-theory distinction is needed because the components of the ACF have become increasingly complex, requiring some attention to the internal organization of the concepts and logic, and because modifications of the ACF over time have clouded the essential and nonessential components of the framework, making it difficult for any reader—and even these authors—to keep track of what has changed and what has remained the same. With the distinction between frameworks and theories, our goal is to convey the more stable components of the ACF at the “framework” level from the theoretical components, which are subject to development through systematic empirical testing and imaginative thinking (Weible and Nohrstedt 2012; Weible et al. 2011).
  8. With respect to subsystems being nested and overlapping in the ACF, this property is important to recognize because many theories and perspectives in the field of policy process maintain traditional depictions of policy subsystems as subgovernments with a requirement that a legislative subcommittee dealing primarily with the subsystem topic must be present for a subsystem to exist. This is most evident in the Policy Regime Perspective (May and Jochim 2013) and some applications of Punctuated Equilibrium Theory (Worsham and Stores 2012). The point is not to argue that one definition is better than the other but rather to recognize the subtle differences in the use of the term and to use those subtle differences as leverage in conducting research.
  9. A comprehensive listing of the different components of the belief system of the ACF, circa 1999, can be found in Sabatier and Jenkins-Smith (1999, 133).
  10. This dilemma in the 1980s was particularly pertinent given that traditional public administration scholarship often focused on a single government agency and the top-down implementation literature focused on a single program. When the unit of analysis was broadened to a policy subsystem characterized by high levels of conflict, the concept of advocacy coalitions emerged as a useful device for simplifying policy actors. In current ACF studies, analysts often focus their attention on organizations rather than on individuals. This is done for a range of reasons, including to maintain confidentiality of the identity of the research subject and because organizations supply the resources and are often the unit that individuals represent in policy subsystem politics (Fischer 2015; Ingold 2011; Knoke et al. 1996).
  11. The point of this assumption is not that scientific and technical information is better than other forms of knowledge but rather that scientific and technical information is critically important in understanding policy debates. Indeed, other forms of knowledge can be just as important.
  12. Careful observers of the ACF have noted that brokers are no longer listed in the current Figure 4.1, as was also the case in Jenkins-Smith et al. (2014). The reason is not to discount the importance of the concept but to recognize that not all policy subsystems have policy brokers and that other types of exceptional actors might also be present, such as policy entrepreneurs.
  13. A public program is the means by which a public service is delivered given a policy directive. In this respect, a public program is concrete in its application, may operate under one or more policies, and may vary across locations.
  14. People interested in applying the ACF are welcome to contact the authors for some of the previously used survey, interview, and coding instruments.



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