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The Variable Politics of the Policy Process: Issue Area Differences and Comparative Networks

Matt GrossmannAssistant Professor of Political Science,

Michigan State University303 S. Kedzie Hall

East Lansing, MI 48823(517) [email protected]

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.

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.


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.

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 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

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.

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


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.

PE to civil rights, science, or transportation and few applications of MS to

education or housing.


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 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.

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.


In the classic formulation of “issue networks,” Hugh Heclo (1978) argues

that experts form relationships based on reputations for issue-specific

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 (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

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.


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

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

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.


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 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, trade, and

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


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

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.

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.


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 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

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).

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.


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

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.


agencies, and secondary sources. I rely on the judgments of experts in each

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

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


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 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

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.

16 Actors that could not be easily categorized were put in separate

unidentified categories.


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 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.

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.


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 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.


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. 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


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.


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.



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 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).


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

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).


other actors.20 Table 3 also reports two versions of the E-I (external-

internal) 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

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)

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).


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 Although the model is depicted in two dimensions, the results suggest

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


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.

created an alternative dissimilarity matrix based on 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.


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.

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 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.


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 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 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.


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.

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.


Table 1: Reported Circumstances Associated with Policy Enactments in Issue Area Histories

Media Coverage

Public Opinion

Interest Groups

International

State or Local Research

Agriculture 18.42% 21.05% 63.16% 13.16% 0% 47.37%Civil Rights & Liberties 21.31% 31.15% 67.21% 11.48% 24.59% 22.95%Criminal Justice 25% 30.77% 30.77% 0% 9.62% 42.31%Education 12.12% 27.27% 48.48% 12.12% 18.18% 42.42%Energy 18.18% 13.64% 36.36% 13.64% 18.18% 31.82%Environment 29.9% 25.77% 69.07% 12.37% 19.59% 54.64%Finance & Commerce 10.34% 6.9% 36.21% 3.45% 5.17% 22.41%Health 10.53% 11.58% 36.84% 7.37% 9.47% 38.95%Housing & Development 16.67% 13.89% 58.33% 0% 19.44% 44.44%Labor & Immigration 16.07% 30.36% 55.36% 10.71% 12.5% 37.5%Macroeconomics 22.92% 41.67% 54.17% 14.58% 8.33% 41.67%Science & Technology 7.89% 7.89% 36.84% 23.68% 2.63% 28.95%Social Welfare 22.22% 22.22% 38.89% 0% 13.89% 36.11%Transportation 22.22% 17.78% 57.78% 0% 6.67% 31.11%

The table reports the percentage of enactments that involved each factor, according to policy historians.


Table 2: Issue Area Governing Network Composition

Most Central (Degree)

Dominant Type

Congress Members

Interest Groups

Government Orgs.

# Links # Links # Links

Agriculture Ag. Dept, Farm Bureau Congress 17 9.9 8 9.9 6 6

Civil Rights & Liberties

NAACP, JFK, MLK Jr.

Int. Groups 63 20.4 52 4.9 16 23.1

Criminal Justice ACLU, Bar Assoc.Int. Groups 20 6.7 16 8.4 11 7.2

Education Edith Green, NEA Congress 54 19.5 27 16.1 15 16.1Energy Ford, Ted

Kennedy Congress 20 5.3 12 4.1 9 2.4

Environment Ed Muskie, J. Blatnik Mixed 36 13.1 34 7.2 33 13.1

Finance & Commerce Eisenhower, LBJ Congress 19 3.4 3 3 7 3.1

Health Truman, Mary Lasker Congress 46 9.7 31 9.9 26 8.7

Housing & Development

U.S. Conf. of Mayors Mixed 39 9.7 29 14.6 22 9.5

Labor & Immigration

AFL-CIO, Labor Dept. Mixed 76 14.8 63 17.4 24 16.5

Macroeconomics Wilbur Mills, Treasury Congress 42 11.6 12 15.2 16 20.4

Science & Technology FCC, Nixon Mixed 12 2.8 12 2.8 13 4.7

Social Welfare Wilbur Mills, Social Sec Congress 45 11.4 24 12.7 18 16.7

Transportation Ford, Ted Gov. Orgs. 24 16.1 29 18.6 30 20.8


KennedyThe table reports characteristics of the actors credited with policy enactments in each issue area.


Table 3: Issue Area Governing Network Structural Characteristics

Core-Periphery E-I Index

Size Density

Fitness

Core Densi

ty

DegreeCentraliza

tion

Clustering

Coefficient

Congress-Admin.

Bipartisan

Agriculture 49 0.17 0.7 0.88 9.50% 1.02 -0.11 -0.14Civil Rights & Liberties 210 0.1 0.69 1.07 7.21% 1 -0.34 -0.28Criminal Justice 83 0.08 0.52 1 10.52% 1.02 -0.5 -0.17Education 170 0.1 0.47 0.62 9.83% 0.97 -0.14 -0.23Energy 65 0.07 0.59 1 5.96% 0.91 -0.18 -0.28Environment 144 0.09 0.68 4.39 7.74% 1.2 -0.21 -0.42Finance & Commerce 54 0.06 0.48 1.05 4.34% 0.99 -0.03 -0.03Health 141 0.07 0.49 1.17 6.60% 1.01 -0.28 -0.01Housing & Development 119 0.1 0.48 0.87 15.50% 1 -0.07 -0.23Labor & Immigration 211 0.1 0.49 0.84 14.18% 1.14 -0.06 -0.19Macroeconomics 118 0.12 0.67 1.07 9.94% 1.06 -0.02 -0.01Science & Technology 70 0.06 0.29 2 4.38% 0.98 -0.38 -0.29Social Welfare 136 0.1 0.56 1.04 8.06% 1.07 -0.13 -0.24Transportation 127 0.19 0.76 1.29 13.48% 1.12 -0.13 -0.15

The table reports structural characteristics of the affiliation networks associated with policy enactments in each issue area.


Table 4: The Relative Features of Each Issue Area’s Politics

Type of Policymaking

Relevant Circumstances

Network Composition Network Structure

AgricultureRegular, path dependent enactments

High interest group influence

Small, mostly congressional network

Dense core-periphery network

Civil Rights & Liberties

Multi-branch, frequent, and path dependent

High state/local influence but low research influence

Large network with many interest groups

Core-periphery structure but low centralization

Criminal Justice

Disproportionately judicial enactments

High research influence but no international influence

Small network with central interest groups

Executive-congressional divide

EducationPath dependent enactments by Congress

No dominant influential factors

Large network dominated by members of Congress

Core with satellite clusters

EnergyDisproportionately administrative, event-driven

Low public opinion and high state/local influence

Small network, concentrated in Congress

Low centralization

EnvironmentMany enactments with congressional dominance

High media, state/local, and research influence

Disproportionately Democratic network

Dense core with high clustering

Finance & Commerce

Split policymaking between Congress and courts

Low research influence

Small, congressional and presidential network

Sparse decentralized network

Health Many enactments in Congress

No dominant influential factors

Large network, dominated by members of Congress

Sparse ties

Housing & Developmen

Path dependent enactments in

High state/local, low public opinion

Large diverse network

Centralized network with partisan divide


t Congress influenceLabor & Immigration

Multi-branch enactments

High public opinion and group influence

Large, diverse network, centralized on AFL-CIO

Sparse network, with high clustering

Macroeconomics

Event-driven, legislative enactments

High public opinion and research influence

Congress-dominated network

Dense network with high inter-branch/bipartisan ties

Science & Technology

Disproportionately administrative enactments

Low public opinion but high international influence

Diverse, with many government organizations

Sparse, disconnected network with no core

Social Welfare

Infrequent, path dependent enactments

High media but no international influence

Congress-dominated network

Large divided network

Transportation

Regular congressional enactments

High interest group, no international influence

Large diverse network, with government organizations

Dense core-periphery 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.


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.


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.


Figure 3: A Sample of Issue Networks

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.

Education

Social Welfare

Transportation

Labor


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.

· web viewlearning that energy policy is less likely to be affected by public opinion than...

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