The Variable Politics of the Policy Process:
Issue Area Differences and Comparative Networks
Matt Grossmann
Assistant Professor of Political Science,
Michigan State University
303 S. Kedzie Hall
East Lansing, MI 48823
(517) 355-7655
matt@mattg.org
Abstract
The politics of policy issue areas differ in multiple ways, including the venues where policies are
enacted, the frequency and type of policy development, the relative importance of different
circumstantial factors in policy change, the composition of participants in policymaking, and the
structure of issue networks. The differences cannot be summarized by typologies because each issue
area differs substantially from the norm on only a few distinct characteristics. To understand these
commonalities and differences, I aggregate information from 231 books and 37 articles that review
the history of American domestic policy in 14 issue areas from 1945-2004. The histories collectively
uncover 790 notable policy enactments and credit 1,306 actors for their role in policy development.
The politics of each issue area stand out in a few important but unrelated aspects.
The Variable Politics of the Policy Process
1
Scholars seek to understand how the political system produces public policy, but the answers
may differ across issue areas.1 Though cognizant of these likely differences, scholars rarely consider
them systematically. Across issue areas, does American national policymaking take place in the same
venues with the same frequency? Is the relative importance of different political circumstances
similar? Are the composition of participants in policymaking and the structure of the networks that
connect them similar? If differences are widespread, can they be easily summarized by a typology?
This paper reviews American federal policymaking in 14 broad domestic issue areas since
World War II: agriculture, civil rights & liberties, criminal justice, education, energy, the
environment, finance & commerce, health, housing & development, labor & immigration,
macroeconomics, science & technology, social welfare, and transportation. Across these issue areas,
neither the causal factors in the policy process nor the composition and structure of issue networks
are universal. Each issue area is distinct from the others on a few characteristics, but typical in most
respects. Separable types of policymaking do not follow from issue area categorizations.
As a result, investigations of policymaking are likely to focus on particular aspects of the
policy process based on issue area case selection decisions, even though they seek generalized
knowledge. The relevant circumstances and actors change with the issue territory, as do the
relationships among actors and the relevant political circumstances. Rather than assuming
universality in the policy process, relying on typologies, or creating unique theories for each issue
area, scholars should be attentive to the few ways that each issue area differs from the others.
1
An online appendix at www.journals.cambridge.org/jop contains a full list of sources used in the
content analysis described in this article as well as relevant codebook instructions. Data to reproduce
all numerical results and network diagrams will be posted at www.mattg.org on publication.
The Variable Politics of the Policy Process
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I address these variations using historical studies of policymaking. First, I compare general
theories of the policy process, policy typologies, and studies of issue networks. Second, I argue that
issue area differences are best conceptualized as issue-specific exceptions to general patterns, rather
than categorical distinctions based on underlying dimensions. Third, I explain the method, which
relies on a content analysis of 231 books and 37 articles that review policy history. Fourth, I review
the record of significant policy enactments in each issue area and the explanations for policy change
found in these sources. Fifth, I analyze the networks associated with each policy area, relying on
information about the actors credited with policy enactments by historians. Sixth, I search for
underlying dimensions of issue area differences as well as clusters of issue types. Finally, I provide
descriptions of the unique features of each issue area to guide future scholarship.
Issue Area Politics and the Policy Process
Many theories of the policy process largely sidestep the question of differences across issue
areas and are meant to apply to many domains. Punctuated-equilibrium (PE) accounts (Baumgartner
and Jones 1993) argue that significant policy change is unlikely without a large increase in
consideration of a problem. The multiple streams (MS) account emphasizes the multiple, largely
independent, streams of problem definition, politics, and policy (Kingdon 2003). The advocacy
coalition framework (ACF) focuses on the ideas and beliefs developed by interest group and
government proponents of policy change (Sabatier and Jenkins-Smith 1993).2 Although these
theories are all applied flexibly to different issues, their applications tend to concentrate in particular
areas. Studies using PE focus more on budgets (Jones and Baumgartner 2012), the MS account
2
The ACF was developed to apply to issue areas that involve scientific disputes and high degrees of
belief conflict. Its application is thus somewhat more restricted than other theories.
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draws more from transportation and health (Zahariadis 2007), and nearly 64% of applications of the
ACF focus on environmental or energy policy (Weible, Sabatier, and McQueen 2009).3
Issue area differences could help reconcile accounts of policymaking from different
theoretical perspectives. For example, PE accounts imply that significant policy change is driven by
episodic agendas; other incremental policy changes are thought to be less important. In contrast,
historical approaches to policy change (Pierson 2004) argue that most significant policymaking is
developmental; it relies on a path dependent process where early decisions constrain later decisions.
Alternatively, some issue areas may be more episodic and others more path dependent.
Some theories of the policy process explicitly analyze issue area differences. They tend to
involve issue categorization schemes that focus on one or two dimensions of variation associated
with clear types. Theodore Lowi (1964) proposes a three-part typology: redistributive, distributive,
and regulatory. The idea is that scholars should expect to find differences in the politics of each issue
area based on the kind of policy under debate and who has something to gain or lose from policy
action. Similarly, James Q. Wilson (1980) argues that policy issues can be divided into types based on
whether the costs and benefits of policy action in the area are concentrated or dispersed: interest
group politics where both are narrow, entrepreneurial politics where only costs are concentrated,
client politics where only benefits are concentrated, and majoritarian politics where both are broad.
These typologies have been difficult for scholars to follow, since most policy areas have
elements of multiple types.4 They have not proved especially fruitful in understanding policy area
3
A content analysis of applications of the ACF (Weible, Sabatier, and McQueen 2009) found few
studies of economic policy, social welfare policy, agriculture, criminal justice, or housing. Although
there is no equivalent content analysis of the other two frameworks, I noticed few applications of
PE to civil rights, science, or transportation and few applications of MS to education or housing.
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differences, but new typologies have nonetheless proliferated (Smith 2002). The continued interest
in typologies highlights the need to understand variation across issue areas in the venues where
policymaking takes place and the factors responsible for policy change. I investigate this variation,
focusing on several categories of explanations for policy referenced in both issue area histories and
the general literature on public policy: media coverage, public opinion, interest groups, international
factors, state and local factors, research, events, and path dependence.5
If differences across issue areas produce distinct politics, scholars should also observe
different kinds of networks emerging in different areas. In the classic formulation of “issue
networks,” Hugh Heclo (1978) argues that experts form relationships based on reputations for issuespecific knowledge. Other scholars analyze these relationships, finding a “hollow core” with no
central player arbitrating conflict in many issue domains (Heinz et al. 1993).
Yet comparative analysis of issue networks is rare. In addition, some scholars argue that not
all policy communities are large and broad enough to merit the label of issue networks (Marsh and
Rhodes 2004). Others argue that policymaking in some areas may instead resemble iron triangles
involving a set of client interest groups, an executive agency, and relevant congressional committees
4
Applying Lowi’s typology might categorize criminal justice and energy as regulatory, transportation
and health as distributive, and social welfare and housing as redistributive. Apply Wilson’s typology
might categorize energy as interest group politics, housing and labor as client politics, environment
and criminal justice as entrepreneurial politics, and macroeconomics as majoritarian politics.
5
This article considers the factors external to government institutions that are the focus of policy
process theory, rather than negotiations within the three branches. These external factors are cited as
causes of policy change, however, rather than contextual factors driving other determinants.
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(Berry 1989).6 To investigate variation across networks, I examine the composition of actors
involved in each issue area and the configuration of their relationships.
Issue Area Differences as Exceptions to General Patterns
Extant research has not uncovered typologies that successfully explain how either the
politics of policymaking or the character of networks differ across issue areas. Kevin Smith (2002,
381) advocates a move from typologies to taxonomies, classifying items “on the basis of empirically
observable and measurable characteristics.” This paper generally takes this approach, addressing two
fundamental problems of policy typologies. First, typologies assume that differences in the politics
of issue areas can be distilled into only a few important dimensions. Second, they assume that most
issue areas will fall in a clear zone along these dimensions, enabling scholars to place them in boxes.
Both assumptions may be false. Issue areas may have broadly similar policy processes and each issue
area may stand out in only a few important aspects. This perspective should apply to both the
institutions and circumstances that make policy change possible (the focus of the policy process
literature) and the actors responsible for policy change and their relationships (the focus of the issue
networks literature). Whether scholars are looking at where and how often policy change occurs, the
role of circumstantial factors in driving policy development, or the people and organizations that
jointly bring it about, they should not expect issue area differences to conform to any typology.7
6
Issue areas like agriculture, energy, housing, labor, science, and transportation have these three
institutions and are sometimes considered candidates for networks that resemble iron triangles.
7
Interactions between context and political factors also help produce policy change, but historians
do not discuss interactions with enough consistency to enable incorporation into content analysis.
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Issue area differences manifest themselves in both obvious and subtle ways. It should be no
surprise that criminal justice policy change happens more often in the courts compared to other
areas; after all, a large proportion of court proceedings confront related issues. Learning that energy
policy is less likely to be affected by public opinion than other areas, in contrast, may elicit more
surprise. These differences are unlikely to be reducible to a few categories. Categorizing criminal
justice as a court-centered issue area, for example, would miss all of the ways that it is similar to
other issue areas while highlighting only one of its features. Similarly, categorizing energy policy as
immune from public opinion would also put too much emphasis on a single aspect of its politics.
Issue network differences are also unlikely to allow categorization into separable types. In
particular, the composition of networks (such as the partisan or institutional affiliations of its
members) may vary independently of their structure. I find that a large issue network bridging two
branches of government determines macroeconomic policy, for example, but this may not
correspond to a category that any other issue network fits well within. Issue area differences are thus
unlikely to correspond to the characteristics that make typologies useful. Scholars should instead
specify the differences between issue areas, even if they only amount to a series of exceptions to the
typical policy process and the common features of issue networks.
Compiling Policy Area Histories
Specifying the differences across issue areas requires comparative studies of many different
policy processes. To make that possible, I rely on secondary sources of policy history. Policy
specialists often review extensive case evidence on the political process, attempting to explain how,
when, and why public policy changes. These authors, who I call policy historians, identify important
policy enactments in all branches of government and produce in-depth narrative accounts of policy
development. David Mayhew (2005, 245-252) used policy histories to produce his list of landmark
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laws; he found them more conscious of the effects of public policy and less swept up by hype from
political leaders than contemporary scholarly or journalistic judgments.
The analysis here relies on 268 books and articles that review policy history since 1945. I
compile published accounts of federal policy change in 14 issue areas, each corresponding to a
category from the Policy Agendas Project (PAP).8 I exclude the foreign policy areas of defense,
8
The agriculture category, category 4 in the PAP, covers issues related to farm subsidies and the
food supply. The civil rights & liberties policy area, category 2, includes issues related to
discrimination, voting rights, speech, and privacy. The criminal justice area, category 12, includes
policies related to crime, drugs, weapons, courts, and prisons. Education policy, category 6, includes
all levels and types of education. The energy issue area, category 7, includes all types of energy
production. The environment issue area, category 8, includes air and water pollution, waste
management, and conservation. The finance & commerce area, category 15, includes banking,
business regulation, and consumer protection. Health policy, category 3, includes issues related to
health insurance, the medical industry, and health benefits. Housing & community development,
category 14, includes housing programs, the mortgage market, and aid directed toward cities. Labor
& immigration, category 5, covers employment law and wages as well as immigrant and refugee
issues. The macroeconomics area, category 1, includes all types of tax changes and budget reforms.
Science & technology, category 17, includes policies related to space, media regulation, the computer
industry, and research. Social welfare, category 13, includes anti-poverty programs, social services,
and assistance to the elderly and the disabled. The transportation area, category 10, includes policies
related to highways, airports, railroads, and boating.
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8
trade, and foreign affairs, but cover nearly the entire spectrum of domestic policy areas.9 For each
issue area, I search multiple book catalogs and article databases using keywords from the topic lists
and subcategories available at policyagendas.org. To find additional sources, I use bibliographies and
literature reviews. Rather than sample, I construct a population of sources based on several
exclusion criteria. To focus on broad historical reviews of the policy process, I exclude sources that
do not identify the most important enactments, those that focus on advocating policies or explaining
the content of current policy, and those that cover fewer than ten years of policymaking. I also
exclude sources that analyze the politics of the policy process from a single theoretical orientation
without a broad narrative review of policy history.10 The full list of sources, categorized by issue area,
is available in the supporting materials on the journal’s website.
With the help of research assistants, I read each text and identified significant policy
enactments. I include policy enactments when any author indicated that the change was important
and attempted to explain how or why it occurred. The relevant portions of the codebook and
instructions are available in the supporting materials. For each enactment, I code whether it was an
9
The PAP divides policymaking into 19 categories. Three categories cover foreign policy and two
categories do not have an associated separable policy history literature (government operations and
public lands). Foreign policy may be subject to different dynamics than those studied here and is
typically reviewed in international relations scholarship, rather than policy history.
10
At least 80 policy studies using the ACF (Weible, Sabatier, & McQueen 2009) and at least 35
policy studies undertaken to study PE (listed at policyagendas.org) are excluded. This guards against
a search for confirming evidence, where scholars emphasize factors that are central to theory. Policy
historians also share biases, but their collective judgment serves as a useful comparison to
theoretically driven research. For a comparison of the advantages of each, see Grossmann (2012).
The Variable Politics of the Policy Process
9
act of Congress, the President, an administrative agency or department, or a court. I also categorize
it by issue area based on the PAP issue area codebook.11
I code all policy histories for the factors that each author judged significant in each policy
enactment. To capture their explanations, I have coders ask themselves 61 questions about each
author’s explanation of each enactment from a codebook. Based on these questions, I record
dichotomous indicators of whether each author’s explanation included each factor for every
significant change in policy that they analyze. The supporting materials include the relevant factors
included in the content analysis classified into the categories used here. Coders of the same volume
reach agreement on more than 95% of all codes.12 In the results below, I aggregate explanations
across all authors, considering a factor relevant when any source considered it part of the
explanation for an enactment.13
Most authors rely on their own qualitative research strategies to identify significant actors
and circumstances. For example, the books that I use quote first-hand interviews, media reports,
reviews by government agencies, and secondary sources. I rely on the judgments of experts in each
11
For the list of policy enactments, an assistant reassessed codes for policymaking venue and issue
area and, where available, compared our codes to those in the PAP database. The Krippendorff’s
Alpha reliability score was .903 for the venue analysis and .848 for the issue area analysis.
12
Percent agreement is the only acceptable inter-coder reliability measure for many different coders
analyzing a single case; other measures are undefined due to lack of variation across cases.
13
I use this minimal standard because many policy histories did not include substantial explanatory
material on some of the policy enactments that they viewed as significant. Some authors consistently
list more explanatory factors than others. Further analysis revealed that author differences do not
substantially change the relative frequency of the explanatory factors associated with each issue area.
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policy area, who have already searched the most relevant available evidence, rather than impose one
standard of evidence across all cases and independently conduct my own analysis that is less
sensitive to the context of each policy debate. Collectively, however, policy historians likely still have
biases that are reflected in their focus.14 These biases, if similar across scholars, also inevitably color
the aggregate content analysis. The policy histories therefore offer a useful comparison to current
theoretically focused research on the policy process, but not a definitive test of their claims.
I also record every individual and organization that was credited by policy historians with
bringing about policy change. For each policy enactment mentioned by each author, I catalogue all
mentions of credited actors (proponents of policy change that were seen as partially responsible for
the enactment). I then combine explanations for the same policy enactments, aggregating the actors
that were associated with policy enactments across all authors.15 The typical explanation credits the
few actors most responsible for each policy change. Coders of the same volume reach agreement on
more than 95% of actors mentioned as responsible for each enactment. I also count the number of
14
Grossmann (2012) reviews these likely biases. Historians may be less likely to notice policymaking
in administrative agencies and lower courts compared to laws passed by Congress. No measure of
differences in author research method, scholarly discipline, or time period explain the differences
across issue areas reported here, but unexplained variation in author judgments remains. There is
variation in the emphasis authors put on each factor that they mention, but not enough similarity in
the language they use to incorporate it in the analysis. I also assume equality across policy changes of
very different scope by using frequencies from the population of all significant policy enactments.
15
I use this standard because some policy histories did not include any actors associated with some
policy enactments that they viewed as significant. Further analysis using different standards (such as
majority rule across authors) revealed similar results.
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11
members of Congress, interest groups, and government organizations credited with policy
enactments in each issue area and categorize the actors ideologically, based on whether they were
Democrats (or liberal organizations) or Republicans (or conservative organizations).16
I use affiliation networks to understand the structure of relationships in each issue area.
These networks include all of the actors that were partially credited with a policy enactment in each
issue area, with undirected ties based on actors that were jointly credited with the same policy
enactments.17 This does not necessarily indicate that the actors actively worked together, but that
they were both on the winning side of a significant policy enactment and that a policy historian
thought they each deserved some credit. The affiliation network ties are valued as integer counts of
the number of shared policy enactments between every pair of actors.18
To assess the extent to which differences across issue areas can be easily summarized, I use
nonmetric multidimensional scaling and k-means cluster analysis (see Everitt et al. 2011). First, I
construct a dissimilarities matrix between all pairs of issue areas based on their differences on the
number of enactments in each venue, the percentage of enactments associated with each causal
16
Actors that could not be easily categorized were put in separate unidentified categories.
17
The networks are not made up of all of the participants in policy communities. Instead, they
include people credited with policy enactments in each issue area. All of the issue areas analyzed here
therefore have some network of actors jointly credited with influencing policy. Because not all ties in
the networks convey political collaboration, however, the results are not directly comparable to past
research that analyzes networks of working relationships or coalitions.
18
If an individual and an organization of which they were a part were both credited, they are treated
as separate actors in the network. These instances accounted for a small minority of all connections.
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factor, and the characteristics of each issue network. I then place the issue areas in dimensional
space and clusters. The goal is to see whether typologies can account for issue area differences.
Policy Enactments Across Issue Areas
Policy is enacted in every branch of government and issue area, though hardly with equal
frequency. Figure 1 depicts the number of significant policy enactments in each issue area in each
venue since 1945, separating laws passed by Congress from executive orders by the president,
administrative agency rules, and court decisions. Unsurprisingly, Congress dominates policymaking
in most issue areas. Nevertheless, a few issue areas stand out for the extent to which policy
enactments occur in other branches of government. In civil rights, criminal justice, and finance &
commerce, policymaking occurs disproportionately in the judiciary. Enactments in the energy and
science & technology domains are more likely to come from administrative agencies.
[Insert Figure 1 Here]
Policymaking in each issue area also differs dramatically in its frequency: health and the
environment are associated with more policy enactments. This is partially a consequence of their
consistent prominence on the government agenda. The correlation between the total policy
enactments in each issue area and the number of congressional hearings over the entire period is .49.
Transportation, however, is regularly on the agenda without producing many policy enactments.
Issue areas also differ substantially in the extent to which their policymaking is path
dependent or episodic. Figure 2 compares the percentage of policy enactments where policy
historians referred to factors related to path dependence with the percentage of enactments where
they pointed to particular events driving policy change. This does not indicate that the historians
used any language related to the theoretical concepts of path dependence or focusing events; most
did not. Instead, explanations involving path dependence included any statement that the enactment
The Variable Politics of the Policy Process
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was an extension of an earlier policy, that an earlier choice made the enactment more likely, or that
an earlier choice eliminated a potential alternative policy. Explanations involving events pointed to
the effects of war, economic downturn, a government financial problem, a focusing event such as a
school shooting, or a case highlighting problems in a previous policy.
[Insert Figure 2 Here]
The results show that policy enactments in agriculture, energy, housing, and labor are most
likely to be path dependent. Enactments in energy and macroeconomics are most likely to be
associated with events, especially nuclear disasters and economic downturns. These two potential
sets of explanatory factors do not directly trade-off with one another. Some policy changes were not
associated with either category of factors. Others were associated with both past policy choices and
focusing events, such as reauthorization of an environmental statute in response to a natural disaster.
Nevertheless, more episodic policy areas were associated with more congressional hearings. The
number of hearings in each issue area is correlated at .46 with the difference between the percentage
of enactments that were episodic and path dependent. Analyzing the policy agenda may thus track
episodic issue areas while missing significant enactments in areas with more path dependence.
Reported Circumstances Responsible for Policy Enactments
Policy histories also point to somewhat different types of circumstances in explaining policy
change in each area. Table 1 reports the percentage of policy enactments in each issue area
associated with six categories of causal factors. These categories are not mutually exclusive or
exhaustive. They were the external circumstances mentioned by policy historians most often and are
common components of theories of the policy process. Explanations involving media coverage
point to general attention or specific articles. In the public opinion category, I include references to
public views, issues raised in an election campaign or by constituents, or a public protest.
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Explanations involving interest groups include advocacy by non-governmental organizations,
business interests, professional associations, or unions. Those involving international factors include
references to foreign examples and international pressure or agreements. Explanations involving
state or local factors include references to state or local actions that preceded federal action or
reports from state or local officials. For explanations involving research, I include references to data
or research findings, think tank or academic involvement, or research reports.
[Insert Table 1 Here]
Media coverage was most commonly associated with policymaking in macroeconomics, the
environment, social welfare and transportation. Reports of pollution, poverty, and dilapidated
infrastructure all play roles in policy development. Public opinion was a commonly reported cause of
enactments in macroeconomics, civil rights, and labor and significantly less common in energy,
finance, and science. Public concern over economic conditions, for instance, was regularly credited
with macroeconomic policy change. Interest group influence was quite common in most issue areas,
but was significantly more common in agriculture, transportation, the environment, and civil rights.
Historians regularly credit lobbying by industry groups in agriculture and transportation as well as
advocacy by public interest groups for civil rights and environmental protection. Science &
technology policy registered the highest rate of international influence, with the Soviet launch of
Sputnik serving as the most prominent example. State or local influence on policy enactments was
most common in the areas of housing and civil rights but was significantly less common in science
and agriculture. According to policy historians, factors related to research were commonly associated
with policy change in most issue areas, with the exception of civil rights. Policy historians regularly
cite new data as well as summary reports from government agencies as factors in policy change.
The Diversity of Issue Networks
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Policy histories also credit particular individuals and organizations with bringing about policy
change in each area. The networks that I analyze enable a visualization of the relationships among
these actors. Figure 3 depicts a sample of four issue networks. Nodes are actors credited with
enactments; links connect actors credited with the same enactments. Black nodes are Democrats or
liberal organizations; white nodes represent Republicans or conservative organizations; others are
grey. Actors in the legislative branch are represented as circles; actors in the executive branch are
squares; diamonds represent those in the judicial branch and triangles are non-governmental actors.
[Insert Figure 3 Here]
There is remarkable variation in the composition and structure of networks across issue
areas, though none resembles a hollow core. None of the issue areas have a clearly bifurcated
network polarized by ideology, though there are differences in degree. There is also substantial
cross-branch interaction in most, but not all, issue areas. Table 2 reports several characteristics of the
composition of each issue area’s network. Members of Congress dominate half of the networks and
interest groups dominate two of the networks; others have a mix of central players. Organizations
like executive agencies are central in the transportation network.
[Insert Table 2 Here]
Table 3 reports common characteristics of the structure of each issue area’s network.19 Size
is the number of actors. Density is the average number of ties between all pairs of actors. In this
case, the interpretation is the average number of policy enactments for which each pair of actors in
the network shared credit. Paul Hallacher (2005) uses equivalent notions of size and interaction to
19
Although there are fit statistics proposed for some of these measures (beyond the fitness measure
for the core-periphery model), they generally require simulated data and are not usefully compared
to familiar statistics (Wasserman and Faust 1994).
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16
compare subgovernments and issue networks, suggesting that issue networks have high values for
each. The core-periphery model in Table 3 compares each network to an ideal type in which a
central group of actors is closely tied to one another and surrounded by a periphery of less
connected actors. The fitness statistic reports the extent to which the network fits this ideal type; the
core density statistic reports the density within the group of actors identified as the core of the
network (a categorical distinction). High values here would indicate that a network is far removed
from the “hollow core” that characterized some previous networks (see Heinz et al. 1993).
[Insert Table 3 Here]
Degree Centralization measures the extent to which all ties in the network are to a single
actor. The Clustering Coefficient measures the extent to which actors that are tied to one another
are also tied to the same other actors.20 Table 3 also reports two versions of the E-I (externalinternal) index to track cross-branch and cross-party ties. The index measures the extent to which
ties are disproportionately across groups (positive) or within groups (negative). The groups for the
first index are actors in Congress and those in the executive branch; for the second, the groups are
Republicans or conservative organizations and Democrats or liberal organizations.21
20
Higher clustering coefficients indicate that, if actors share ties to other actors, they are more likely
to be tied. To determine whether actors divide into clustered neighborhoods throughout the
network, it is useful to compare the clustering coefficient to the overall density in each network.
21
The indexes are calculated as (number of ties between actors in the two different groups - number
of ties between actors in the same group)/(sum of both of these types of ties). These indexes may be
measures of the extent of conflict (negative) or cooperation (positive) across groups; more conflict is
usually seen as an indicator of issue networks rather than subgovernments (Hallacher 2005).
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17
Issue networks differ in their structure across issue areas. Some networks are large and dense
like transportation, whereas others are small and dense like agriculture. The health network is large
but sparse but science is small and sparse. The issue networks that most resemble the core-periphery
structure are civil rights and the environment. The most centralized networks are housing (around
the U.S. Conference of Mayors) and labor (around the AFL-CIO). Clustering is most evident in the
environment and least evident in energy. The networks most polarized by partisanship are the
environment, science, and civil rights. The networks with most ties between the legislative and
executive branch are housing, finance, and macroeconomics; civil rights and science had the least
cross-branch oriented networks.
Dimensions of Issue Area Politics
To evaluate the number of underlying dimensions of issue area politics and to see where
issue areas sit relative to one another on these dimensions, I use nonmetric multidimensional scaling.
This provides two kinds of output: information about how well a model with each number of
dimensions fits the data and a scale score for each case on each dimension. A typology that
successfully made sense of the differences in politics across issue areas would require differences to
be summarized by a small number of dimensions where the cases clearly separated into clusters.
Figure 4 depicts a multidimensional analysis of issue area dissimilarities, using the
characteristics of policy change reported in Figures 1 and 2, the reported circumstances associated
with policy change from Table 1, and the characteristics of issue networks from Tables 2 and 3.22
22
It uses a dissimilarity matrix of the Euclidian distances between pairs of issue areas for all variables
in the three tables and two figures. I also created an alternative dissimilarity matrix based on
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18
Although the model is depicted in two dimensions, the results suggest no clean break in the number
of dimensions. The measure of Stress_1, a fit statistic where lower numbers indicate a better fit, is
.075 for a one-dimension solution, .037 for a two-dimension solution, .016 for a three-dimension
solution, and .003 for a four-dimension solution.
[Insert Figure 4]
I also use k-means cluster analysis to divide the issue areas into clusters based on the same
dissimilarities. The Calinski-Harabasz and Duda-Hart procedures (see Everitt et al. 2011) for
determining the appropriate number of clusters were inconclusive, with the former producing
improved fit statistics with 3 and 13 clusters and the latter producing improved fit statistics with 4
and 5 clusters. A two-cluster solution divides agriculture, crime, energy, finance, and science into one
cluster (the issue areas on the right side of Figure 4). One interpretation is that these issue areas are
associated with less popular mobilization whereas the others involve broader economic and social
policy agendas. An alternative three-cluster solution separates crime into its own cluster from this
group. A four-cluster solution has a separate cluster for agriculture and for civil rights and labor.
Beyond this number, the algorithm begins separating each issue area into a unique cluster.
Rather than clean categories, distinctions among issue areas are best seen as continuous
differences. The results suggest that there is no easy way to summarize the differences across the
political processes surrounding each issue area and their associated issue networks. A two-by-two
typology, for example, would have an especially poor fit with the data. We cannot be sure that two
dimensions best account for issue area differences, that the issue areas divide cleanly along those
dimensions, or that four clusters would be the most appropriate division.
standardized versions of all of these variables. A low-dimensional solution based on the standardized
measures does not fit the data as well and fails to produce differentiated clusters.
The Variable Politics of the Policy Process
19
I also analyze several reformulations of the data to ensure that the results were not a product
of methodological decisions. First, I divide the data across time into subsets of 15-year periods and
searched for an underlying structure. Second, I categorize the issue areas into a larger number of
subtopics, each covering a smaller territory. Third, I analyze only the policy enactments considered
significant by most authors in each area and limit the explanatory factors considered to only those
with consensus across authors. Fourth, I construct distinct sets of dissimilarities based on network
characteristics and based on the factors reportedly driving policy change. Issue area differences did
not produce clear clustering on a few underlying dimensions in any of these analyses.
Some readers may interpret the findings as evidence that there are large differences among
the scholars studying these issue areas, rather than the issue areas themselves, but the evidence does
not point in this direction. First, authors covering policy enactments outside of their area of focus
(such as health policy historians explaining the political process behind general tax laws) reached
most of the same conclusions about who was involved and what circumstances were relevant as
specialist historians. Second, there were few consistent differences in the types of actors credited and
few differences in relevant circumstantial factors reported based on whether the authors used
interviews, quantitative data, or archival research, whether the authors came from political science,
policy, sociology, economics, history, or other departments, or how long after the events took place
the sources were written. There were idiosyncratic differences across authors, but they did not
produce the differences across issue areas.
Making Sense of Issue Area Similarities and Differences
There are some seemingly universal features of the policy process, but there are also
important differences in each issue area’s politics. The 14 domestic policy areas analyzed here differ
in their frequency of policymaking, their common venues, the circumstantial factors enabling policy
The Variable Politics of the Policy Process
20
change, the actors responsible for enactments, and the structure of networks. On each dimension of
issue area differences, most issue areas fall in the middle rather than at the extremes.
Policy typologies are unlikely to isolate the different features of policymaking in each issue
area. Indeed, the available policy area typologies are not predictive of the differences analyzed here.
Theoretical distinctions made by Lowi (1964) and Wilson (1980) are not helpful in distinguishing
among the types of politics present in each issue area. Distinctions between iron triangles, issue
networks, and policy communities are equally unhelpful. This is a sign that the theories that produce
typologies should be subjected to more scrutiny. The project of creating minimalist models of the
policy process based on ideal types may not be helpful. The iron triangle ideal type, for example,
mixes three independently varying dimensions of network structure: a strong core, cross-institutional
links, and bipartisan links.
Instead of assuming that issues will fall clearly into boxes, scholars should acknowledge that
issue area differences are widespread but not very amenable to categorization. Table 4 lists
descriptions of the features of each issue area that stand out when compared to the others, including
the type of policymaking, the circumstances associated with policy enactments, and the composition
and structure of the governing network. All policy areas stand out in some ways in comparison to
the others. This comparative analysis should enable authors of case studies to check whether their
findings are likely to apply only to a few issue areas or generalize to the policy process as a whole.
[Insert Table 4 Here]
There are also important similarities in policymaking that are reportedly common across
issue areas, even though I rely on 14 distinct literatures on a broad spectrum of domestic policy.
First, Congress is the most frequent maker of significant policy in nearly all issue areas and it is
responsible for the bulk of policymaking in most areas. Second, all policy areas have some policy
enactments where path dependent explanations are apt and others where event-related explanations
The Variable Politics of the Policy Process
21
are apt. Third, interest groups and research reportedly play a common role in policymaking in most
issue areas whereas public opinion and media coverage play less frequent roles. Fourth, all issue
areas are associated with networks of actors credited with policy change, including members of
Congress, executive branch agencies, and interest groups. These similarities are generally consistent
with the textbook treatments of federal policymaking that focus on institutions.
The issue area differences, however, have important implications for the generalizability of
research findings. Issue area case selection decisions make large differences in likely findings. For
example, Kingdon’s (2003) study of the policy process is based on case studies of health and
transportation. If he had instead chosen to study education and labor, he might have shown more
influence for public opinion and international factors. Likewise, because a great deal of scholarship
using the ACF focuses on environmental policy (Weible, Sabatier, and McQueen 2009), scholars
may be more likely to find influence by interest groups and research.
The results may also show where each of the policy process frameworks could be
productively applied. The research and coalition focus of the ACF, for example, might be useful in
studies of agriculture and housing. The focus on episodic determinants of policy change in PE
studies has been useful in studies of nuclear energy and budgets (Jones and Baumgartner 2012). This
comparative research shows that energy and macroeconomic policies more broadly are the most
likely to be associated with episodic causes of policy change. Theories of path dependent
policymaking, in contrast, may be most appropriate in agriculture, education, and housing.
The findings also have implications for normative discussions of the policy process. Scholars
who sought to divide policymaking into categories (e.g. Wilson 1980, Lowi 1964) associated their
typologies with judgments about the relationship between the policy process and democratic values.
If issue area politics cannot be easily predicted based on whether policies tend to benefit majorities
or minorities, general claims about where policymaking is likely to be more or less democratic may
The Variable Politics of the Policy Process
22
not hold up to scrutiny. Similarly, politics in every issue area may be labeled “interest group politics”
to some degree, even though groups are not the only important actors in any area.
Claims about iron triangles and issue networks were also meant to raise concerns that
policymaking did not live up to America’s founding principles. Iron triangles supposedly involved
domination of policymaking by political insiders. Heclo (1978) also viewed issue networks with
concern, arguing that they came with a “democratic deficit” because they empowered technocratic
elites. Disproportionate involvement by administrators and scientists, however, is only one source of
difficulty in matching our expectations of wide participation with the reality of the policy process.
Disinterested citizens representative of the nation as a whole do not make up any issue networks.
Instead, each issue area is associated with distinct distributions of political elites.
Despite differences across issue areas, there is potential ground for general theories of the
policy process and associated critiques of the relationship between democracy in theory and practice.
Across the issue areas analyzed here, all issue areas involved multiple institutions, interest groups,
and diverse policymakers. They incorporated several circumstantial factors and responded to both
past policy development and current events. There are many factors in the policy process but some
are much more frequently influential than others. Issue area differences are decipherable and should
be emphasized, but the similarities in the relative importance of each component of policymaking
across issue areas are just as important. The American national government has both a general policy
process and some unique variants for each issue area.
The Variable Politics of the Policy Process
23
References
Baumgartner, Frank R. and Bryan D. Jones. 1993. Agendas and Instability in American Politics. Chicago:
University of Chicago Press.
Berry, Jeffrey. M. 1989. The Interest Group Society, 5th ed. New York: HarperCollins Publishers.
Everitt, Brian S., Sabine Landau, Morven Leese, and Daniel Stahl. 2011. Cluster Analysis, 5th ed.
Hoboken, NJ: Wiley.
Grossmann, Matt. 2012. “Interest Group Influence on US Policy Change: An Assessment Based on
Policy History.” Interest Groups & Advocacy 1 (2): 1-22.
Hallacher, Paul M. 2005. Why Polity Issue Networks Matter: The Advanced Technology Program and the
Manufacturing Extension Partnership. Lanham, MD: Rowman & Littlefield Publishers.
Heclo, Hugh. 1978. “Issue Networks and the Executive Establishment.” In The New American
Political System, ed. Anthony King. Washington: American Enterprise Institute.
Heinz, John P., Edward O. Laumann, Robert L. Nelson, and Robert H. Salisbury. 1993. The Hollow
Core: Private Interests in National Policy Making. Cambridge: Harvard University Press.
Jones, Bryan D. and Frank R. Baumgartner. 2012. “From There to Here: Punctuated Equilibrium to
the General Punctuation Thesis to a Theory of Government Information Processing.” Policy
Studies Journal 40 (1): 1-19.
Lowi, Theodore. 1964. “American Business, Public Policy, Case-Studies, and Political Theory.”
World Politics 16 (4): 677-715.
Kingdon, John W. 2003. Agendas, Alternatives and Public Policies, 2nd Ed. New York: Addison-Wesley.
Marsh, David and R. A. W. Rhodes. 2004. “Policy Communities and Issue Networks: Beyond
Typology,” In Social Networks: Critical Concepts in Sociology, ed. John Scott. London: Routledge.
Mayhew, David R. 2005. Divided We Govern: Party Control, Lawmaking, and Investigations, 1946-2002.
New Haven: Yale University Press.
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Pierson, Paul. 2004. Politics in Time: History, Institutions, and Social Analysis. Princeton: Princeton
University Press.
Sabatier, Paul A. and Hank C. Jenkins-Smith. 1993. Policy Change and Learning: An Advocacy Coalition
Approach. Boulder, CO: Westview Press.
Smith, Kevin B. 2002. “Typologies, Taxonomies, and the Benefits of Policy Classification.” Policy
Studies Journal 30 (3): 379-395.
Wasserman, Stanley and Katherine Faust. 1994. Social Network Analysis: Methods and Applications.
Cambridge: Cambridge University Press.
Weible, Christopher M., Paul Sabatier, and Kelly McQueen. 2009. “Themes and Variations: Taking
Stock of the Advocacy Coalition Framework.” Policy Studies Journal 37(1): 121-40.
Wilson, James Q. 1980. “The Politics of Regulation.” In The Politics of Regulation, ed. James Q.
Wilson. New York: Basic Books, 357-94.
Zahariadis, Nikolaos. 2007. “The Multiple Streams Framework: Structure, Limitations, Prospects.”
In Theories of the Policy Process, ed. Paul Sabatier. Boulder, CO: Westview Press.
The Variable Politics of the Policy Process
25
Table 1: Reported Circumstances Associated with Policy Enactments in Issue Area Histories
Media
Public
Interest
International
Coverage
Opinion
Groups
Agriculture
18.42%
21.05%
63.16%
13.16%
Civil Rights & Liberties
21.31%
31.15%
67.21%
11.48%
Criminal Justice
25%
30.77%
30.77%
0%
Education
12.12%
27.27%
48.48%
12.12%
Energy
18.18%
13.64%
36.36%
13.64%
Environment
29.9%
25.77%
69.07%
12.37%
Finance & Commerce
10.34%
6.9%
36.21%
3.45%
Health
10.53%
11.58%
36.84%
7.37%
Housing & Development
16.67%
13.89%
58.33%
0%
Labor & Immigration
16.07%
30.36%
55.36%
10.71%
Macroeconomics
22.92%
41.67%
54.17%
14.58%
Science & Technology
7.89%
7.89%
36.84%
23.68%
Social Welfare
22.22%
22.22%
38.89%
0%
Transportation
22.22%
17.78%
57.78%
0%
The table reports the percentage of enactments that involved each factor, according to policy historians.
State or
Local
0%
24.59%
9.62%
18.18%
18.18%
19.59%
5.17%
9.47%
19.44%
12.5%
8.33%
2.63%
13.89%
6.67%
Research
47.37%
22.95%
42.31%
42.42%
31.82%
54.64%
22.41%
38.95%
44.44%
37.5%
41.67%
28.95%
36.11%
31.11%
The Variable Politics of the Policy Process
26
Table 2: Issue Area Governing Network Composition
Congress Members
#
Links
Agriculture
17
9.9
Ag. Dept, Farm Bureau Congress
Civil Rights & Liberties
63
20.4
NAACP, JFK, MLK Jr. Int. Groups
Criminal Justice
20
6.7
ACLU, Bar Assoc.
Int. Groups
Education
54
19.5
Edith Green, NEA
Congress
Energy
20
5.3
Ford, Ted Kennedy
Congress
Environment
36
13.1
Ed Muskie, J. Blatnik
Mixed
Finance & Commerce
19
3.4
Eisenhower, LBJ
Congress
Health
46
9.7
Truman, Mary Lasker
Congress
Housing & Development U.S. Conf. of Mayors
39
9.7
Mixed
Labor & Immigration
76
14.8
AFL-CIO, Labor Dept. Mixed
Macroeconomics
42
11.6
Wilbur Mills, Treasury Congress
Science & Technology
12
2.8
FCC, Nixon
Mixed
Social Welfare
45
11.4
Wilbur Mills, Social Sec Congress
Transportation
24
16.1
Ford, Ted Kennedy
Gov. Orgs.
The table reports characteristics of the actors credited with policy enactments in each issue area.
Most Central
(Degree)
Dominant
Type
Interest Groups
#
Links
8
9.9
52
4.9
16
8.4
27
16.1
12
4.1
34
7.2
3
3
31
9.9
29
14.6
63
17.4
12
15.2
12
2.8
24
12.7
29
18.6
Government Orgs.
#
Links
6
6
16
23.1
11
7.2
15
16.1
9
2.4
33
13.1
7
3.1
26
8.7
22
9.5
24
16.5
16
20.4
13
4.7
18
16.7
30
20.8
The Variable Politics of the Policy Process
27
Table 3: Issue Area Governing Network Structural Characteristics
Core-Periphery
Core
Degree
Clustering
Size Density Fitness
Density Centralization Coefficient
Agriculture
49
0.17
0.7
0.88
9.50%
1.02
Civil Rights & Liberties
210
0.1
0.69
1.07
7.21%
1
Criminal Justice
83
0.08
0.52
1
10.52%
1.02
Education
170
0.1
0.47
0.62
9.83%
0.97
Energy
65
0.07
0.59
1
5.96%
0.91
Environment
144
0.09
0.68
4.39
7.74%
1.2
Finance & Commerce
54
0.06
0.48
1.05
4.34%
0.99
Health
141
0.07
0.49
1.17
6.60%
1.01
Housing & Development
119
0.1
0.48
0.87
15.50%
1
Labor & Immigration
211
0.1
0.49
0.84
14.18%
1.14
Macroeconomics
118
0.12
0.67
1.07
9.94%
1.06
Science & Technology
70
0.06
0.29
2
4.38%
0.98
Social Welfare
136
0.1
0.56
1.04
8.06%
1.07
Transportation
127
0.19
0.76
1.29
13.48%
1.12
The table reports structural characteristics of the affiliation networks associated with policy enactments in each issue area.
E-I Index
CongressBipartisan
Admin.
-0.11
-0.14
-0.34
-0.28
-0.5
-0.17
-0.14
-0.23
-0.18
-0.28
-0.21
-0.42
-0.03
-0.03
-0.28
-0.01
-0.07
-0.23
-0.06
-0.19
-0.02
-0.01
-0.38
-0.29
-0.13
-0.24
-0.13
-0.15
The Variable Politics of the Policy Process
28
Table 4: The Relative Features of Each Issue Area’s Politics
Agriculture
Civil Rights &
Liberties
Criminal Justice
Education
Energy
Environment
Finance &
Commerce
Type of Policymaking
Regular, path dependent
enactments
Multi-branch, frequent, and
path dependent
Disproportionately judicial
enactments
Path dependent enactments
by Congress
Disproportionately
administrative, event-driven
Many enactments with
congressional dominance
Split policymaking between
Congress and courts
Many enactments in
Congress
Path dependent enactments
in Congress
Relevant Circumstances
High interest group
influence
High state/local influence
but low research influence
High research influence but
no international influence
No dominant influential
factors
Low public opinion and
high state/local influence
High media, state/local,
and research influence
Low research influence
Network Composition
Small, mostly congressional
network
Large network with many
interest groups
Small network with central
interest groups
Large network dominated
by members of Congress
Small network,
concentrated in Congress
Disproportionately
Democratic network
Small, congressional and
presidential network
Large network, dominated
by members of Congress
Network Structure
Dense core-periphery
network
Core-periphery structure
but low centralization
Executive-congressional
divide
Core with satellite clusters
Low centralization
Dense core with high
clustering
Sparse decentralized
network
No dominant influential
Sparse ties
factors
Housing &
High state/local, low public
Centralized network with
Large diverse network
Development
opinion influence
partisan divide
Labor &
High public opinion and
Large, diverse network,
Sparse network, with high
Multi-branch enactments
Immigration
group influence
centralized on AFL-CIO
clustering
Event-driven, legislative
High public opinion and
Congress-dominated
Dense network with high
Macroeconomics
enactments
research influence
network
inter-branch/bipartisan ties
Science &
Disproportionately
Low public opinion but
Diverse, with many
Sparse, disconnected
Technology
administrative enactments high international influence government organizations network with no core
Infrequent, path dependent High media but no
Congress-dominated
Social Welfare
Large divided network
enactments
international influence
network
Regular congressional
High interest group, no
Large diverse network, with Dense core-periphery
Transportation
enactments
international influence
government organizations network; high clustering
The table reports descriptions of where each issue area stands out among the others, based on the analysis of policy area histories conducted here.
Health
The Variable Politics of the Policy Process
Figure 1: Policy Enactments by Venue and Policy Area
The figure depicts the number of policy enactments in each branch of government from 1945-2004, based on policy histories of each issue area.
29
The Variable Politics of the Policy Process
Figure 2: Developmental and Episodic Reported Causes of Enactments by Policy Area
The figure depicts the percentage of policy enactments in each issue area that were reportedly affected by path dependence (including earlier policy choices that
made the enactment more likely or eliminated alternatives) and focusing events (including wars and economic downturns). The reports are based on policy
histories in each issue area covering significant policy enactments from 1945-2004.
30
The Variable Politics of the Policy Process
31
Figure 3: A Sample of Issue Networks
Education
Social Welfare
Labor
Transportation
Nodes are actors credited with policy enactments in each area. Links connect actors credited with the same policy enactments. Democrats are black; Republicans are
white; others are grey. Shape represents branch of government; circles are legislative; squares are executive; diamonds are judicial; triangles are non-governmental.
The Variable Politics of the Policy Process
Figure 4: Nonmetric Multidimensional Scaling of Dissimilarities Among Issue Areas
The figure is a two-dimensional plot of nonmetric multidimensional scaling results of dissimilarities based on the reported factors in
policy change since 1945 and the characteristics of their issue networks. The dissimilarities are based on the characteristics of issue
areas reported in Figures 1-2 and Tables 1-3.
32