Theories of the Policy Process, Second Edition

Paul Sabatier

• Publisher: Routledge
• Year: 2019
• ISBN:
  9781000612370
• Edition: 1
• Topic: Mezzi di comunicazione e arti performative
• Subtopic: Storia e critica del teatro

Theories of the Policy Process provides a forum for the proponents of several of the most promising and widely used theoretical frameworks to present the basic propositions of their frameworks, to assess the empirical evidence that has developed, and to discuss promising directions for future research. The first edition contained analys

PART ONE
Introduction

1
The Need for Better Theories

PAUL A. SABATIER

In the process of public policymaking, problems are conceptualized and brought to government for solution; governmental institutions formulate alternatives and select policy solutions; and those solutions get implemented, evaluated, and revised.

Simplifying a Complex World

For a variety of reasons, the policy process involves an extremely complex set of elements that interact over time:

1. There are normally hundreds of actors from interest groups, governmental agencies, legislatures at different levels of government, researchers, journalists, and judges involved in one or more aspects of the process. Each of these actors (either individual or corporate) has potentially different values/interests, perceptions of the situation, and policy preferences.
2. This process usually involves time spans of a decade or more, as that is the minimum duration of most policy cycles, from emergence of a problem through sufficient experience with implementation to render a reasonably fair evaluation of a program's impact (Kirst and Jung 1982; Sabatier and Jenkins-Smith 1993). A number of studies suggest that periods of twenty to forty years may be required to obtain a reasonable understanding of the impact of a variety of socioeconomic conditions and to accumulate scientific knowledge about a problem (Derthick and Quirk 1985; Baumgartner and Jones 1993; Eisner 1993).
3. In any given policy domain, such as air pollution control or health policy, there are normally dozens of different programs involving multiple levels of government that are operating, or are being proposed for operation, in any given locale, such as the state of California or the city of Los Angeles. Since these programs deal with interrelated subjects and involve many of the same actors, many scholars would argue that the appropriate unit of analysis should be the policy subsystem or domain, rather than a specific governmental program (Hjern and Porter 1981; Ostrom 1983; Sabatier 1986; Rhodes 1988; Jordan 1990).
4. Policy debates among actors in the course of legislative hearings, litigation, and proposed administrative regulations typically involve very technical disputes over the severity of a problem, its causes, and the probable impacts of alternative policy solutions. Understanding the policy process requires attention to the role that such debates play in the overall process.
5. A final complicating factor in the policy process is that most disputes involve deeply held values/interests, large amounts of money, and, at some point, authoritative coercion. Given these stakes, policy disputes seldom resemble polite academic debates. Instead, most actors face enormous temptations to present evidence selectively, to misrepresent the position of their opponents, to coerce and discredit opponents, and generally to distort the situation to their advantage (Riker 1986; Moe 1990a, 1990b; Schlager 1995).

In short, understanding the policy process requires knowledge of the goals and perceptions of hundreds of actors throughout the country involving possibly very technical scientific and legal issues over periods of a decade or more while most of those actors are actively seeking to propagate their specific "spin" on events.

Given the staggering complexity of the policy process, the analyst must find some way of simplifying the situation in order to have any chance of understanding it. One simply cannot look for, and see, everything. Work in the philosophy of science and social psychology has provided persuasive evidence that perceptions are almost always mediated by a set of presuppositions. These perform two critical mediating functions. First, they tell the observer what to look for; that is, what factors are likely to be critically important versus those that can be safely ignored. Second, they define the categories in which phenomena are to be grouped (Kuhn 1970; Lakatos 1971; Brown 1977; Lord, Ross, and Lepper 1979; Hawkesworth 1992; Munro et al, 2002).

To understand the policy process, for example, most institutional rational choice approaches tell the analyst (1) to focus on the leaders of a few critical institutions with formal decisionmaking authority, (2) to assume that these actors are pursuing their material self-interest (e.g., income, power, security), and (3) to group actors into a few institutional categories, for example, legislatures, administrative agencies, and interest groups (Shepsle 1989; Scharpf 1997). In contrast, the advocacy coalition framework tells the analyst to assume (1) that belief systems are more important than institutional affiliation, (2) that actors may be pursuing a wide variety of objectives, which must be measured empirically, and (3) that one must add researchers and journalists to the set of potentially important policy actors (Sabatier and Jenkins-Smith 1993). Thus, analysts from these two different perspectives look at the same situation through quite different lenses and are likely to see quite different things, at least initially.

Strategies for Simplification

Given that we have little choice but to look at the world through a lens consisting of a set of simplifying presuppositions, at least two quite different strategies exist for developing such a lens. On the one hand, the analyst can approach the world in an implicit, ad hoc fashion, using whatever categories and assumptions that have arisen from his or her experience. This is essentially the method of common sense. It may be reasonably accurate for situations important to the analyst's welfare in which she or he has considerable experience. In such situations, the analyst has both the incentive and the experience to eliminate clearly invalid propositions. Beyond that limited scope, the commonsense strategy is likely to be beset by internal inconsistencies, ambiguities, erroneous assumptions, and invalid propositions, precisely because the strategy does not contain any explicit methods of error correction. Since its assumptions and propositions remain implicit and largely unknown, they are unlikely to be subjected to serious scrutiny. The analyst simply assumes they are, by and large, correct—insofar as he or she is even cognizant of their content.

An alternative strategy is that of science. Its fundamental ontological assumption is that a smaller set of critical relationships underlies the bewildering complexity of phenomena. For example, a century ago Darwin provided a relatively simple explanation—summarized under the processes of natural selection—for the thousands of species he encountered on his voyages. The critical characteristics of science are that (1) its methods of data acquisition and analysis should be presented in a sufficiently public manner that they can be replicated by others; (2) its concepts and propositions should be clearly defined and logically consistent and should give rise to empirically falsifiable hypotheses; (3) those propositions should be as general as possible and should explicitly address relevant uncertainties; and (4) both the methods and concepts should be selfconsciously-subjected to criticism and evaluation by experts in that field (Nagel 1961; Lave and March 1975; King, Keohane, and Verba 1994). The overriding strategy can be summarized in the injunction: Be clear enough to be proven wrong. Unlike "common sense," science is designed to be self-consciously error seeking, and thus self-correcting.

A critical component of that strategy—derived from principles 2-4 above—is that scientists should develop clear and logically interrelated sets of propositions, some of them empirically falsifiable, to explain fairly general sets of phenomena. Such coherent sets of propositions have traditionally been termed theories.

Elinor Ostrom has developed some very useful distinctions among three different sets of propositions (see Chapter 2 of this volume). (1) In her view, a "conceptual framework" identifies a set of variables and the relationships among them that presumably account for a set of phenomena. The framework can provide anything from a modest set of variables to something as extensive as a paradigm. It need not identify directions among relationships, although more developed frameworks will certainly specify some hypotheses. (2) A "theory" provides a denser and more logically coherent set of relationships. It applies values to some of the variables and usually specifies how relationships may vary depending upon the values of critical variables. Numerous theories may be consistent with the same conceptual framework. (3) A "model" is a representation of a specific situation. It is usually much narrower in scope, and more precise in its assumptions, than the underlying theory. Ideally, it is mathematical. Thus, frameworks, theories, and models can be conceptualized as operating along a continuum involving increasing logical interconnectedness and specificity but decreasing scope.

One final point: Scientists should be aware of, and capable of applying, several different theoretical perspectives—not just a single one (Stinchcomb 1968; Loehle 1987). First, knowledge of several different perspectives forces the analyst to clarify differences in assumptions across frameworks, rather than implicitly assuming a given set. Second, multiple perspectives encourage the development of competing hypotheses that should ideally lead to "strong inference" (Platt 1964), or at least to the accumulation of evidence in favor of one perspective over another. Third, knowledge and application of multiple perspectives should gradually clarify the conditions under which one perspective is more useful than another. Finally, multiple perspectives encourage a comparative approach: Rather than asking if theory X produces statistically significant results, one asks whether theory X explains more than theory Y.

Consistent with this multiple-lens strategy, the original edition of this volume discussed seven conceptual frameworks. A few of them—notably, institutional rational choice—have given rise to one or more theories, and virtually all have spawned a variety of models seeking to explain specific situations.

Theoretical Frameworks of the Policy Process

The Stages Heuristic

Until the mid-1980s, the most influential framework for understanding the policy process—particularly among American scholars—was the "stages heuristic," or what Nakamura (1987) termed the "textbook approach." As developed by Lasswell (1956), Jones (1970), Anderson (1975), and Brewer and deLeon (1983), it divided the policy process into a series of stages—usually agenda setting, policy formulation and legitimation, implementation, and evaluation—and discussed some of the factors affecting the process within each stage. The stages heuristic served a useful purpose in the 1970s and early 1980s by dividing the very complex policy process into discrete stages and by stimulating some excellent research within specific stages—particularly agenda setting (Cobb, Ross, and Ross 1976; Kingdon 1984; Nelson 1984) and policy implementation (Pressman and Wildavsky 1973; Hjern and Hull 1982; Mazmanian and Sabatier 1983).

Beginning in the late 1980s, however, the stages heuristic was subjected to some devastating criticisms (Nakamura 1987; Sabatier 1991; Sabatier and Jenkins-Smith 1993):

1. It is not really a causal theory since it never identifies a set of causal drivers that govern the policy process within and across stages. Instead, work within each stage has tended to develop on its own, almost totally without reference to research in other stages. In addition, without causal drivers there can be no coherent set of hypotheses within and across stages.
2. The proposed sequence of stages is often descriptively inaccurate. For example, evaluations of existing programs affect agenda setting, and policy formulation/legitimation occurs as bureaucrats attempt to implement vague legislation (Nakamura 1987).
3. The stages heuristic has a very legalistic, top-down bias in which the focus is typically on the passage and implementation of a major piece of legislation. This focus neglects the interaction of the implementation and evaluation of numerous pieces of legislation—none of them preeminent—within a given policy domain (Hjern and Hull 1982; Sabatier 1986).
4. The assumption that there is a sing...