Political Parties and Representation of the Poor
in the American States
Elizabeth Rigby
Gerald C. Wright
George Washington University
Indiana University
Motivated by recent work suggesting that low-income citizens are virtually ignored in the American policymaking process,
this article asks whether a similar bias shapes the policy positions adopted by political parties much earlier in the policymaking
process. While the normative hope is that parties serve as linkage institutions enhancing representation of those with fewer
resources to organize, the resource-dependent campaign environment in which parties operate provides incentives to appeal
to citizens with the greatest resources. Using newly developed measures of state party positions, we examine whether lowincome preferences get incorporated in parties’ campaign appeals at this early stage in the policymaking process—finding
little evidence that they do. This differential responsiveness was most pronounced for Democratic parties in states with
greater income inequality; it was least evident for Republicans’ social policy platforms. We discuss the implications of these
findings for representation in this era of growing economic inequality.
A
central tenet of democratic representation is responsiveness to all citizens as political equals. Yet,
the ability of any political system to achieve this
normative goal may be undermined if its citizens hold
vastly different wealth and associated resources such as
information, time, money, and civic skills (Schlozman,
Verba, and Brady 2012; Verba, Schlozman, and Brady
2006; Winters and Page 2009). For this reason, rising rates
of income inequality in the United States have prompted
concern about the ability of our political system to provide political equality as economic resources have become
more concentrated in fewer hands (Jacobs and Skocpol
2005; McCarty, Poole, and Rosenthal 2006).
This worry—that some citizens’ power and resources
may overwhelm others’ right to equality of political
voice—is not a new concern. It was more than 50 years
ago that Schattschneider wrote his often-cited critique
that “the flaw in the pluralist heaven is that the heavenly
chorus sings with a strong upper-class accent” (1960,
34). In recent years, we have seen renewed attention
from political scientists to the interplay of economic and
political inequality (Jacobs and Soss 2010). These empirical investigations have illustrated uneven responsiveness
of policy makers to citizens from different income groups
(Bartels 2008; Druckman and Jacobs 2011; Gilens 2005,
2012; Hacker and Pierson 2010a; Jacobs and Page 2005;
Rigby and Wright 2011). Together, these studies suggest
that American democracy is falling far short of its ideal of
political equality due to legislators’ heightened attention
to more affluent constituents and political elites at the
expense of the poor.
We suspect this differential responsiveness begins
very early in the policymaking process—at the point
in which political parties aggregate diverse constituent
preferences and advance a policy platform on which to
run for election. Across distinct electoral contests, Democratic and Republican party affiliations serve to group
individual candidates around coherent political alternatives from which voters may choose. At the same time,
parties provide voters ongoing monitoring and discipline
Elizabeth Rigby is Assistant Professor of Public Policy and Public Administration, The Trachtenberg School, George Washington University,
MPA Building 601C, 805 21st St. NW, Washington, DC 20052 ([email protected]). Gerald C. Wright is Professor of Political Science, 1100
E. Seventh Street, Indiana University, Bloomington, IN 47405 ([email protected]).
The authors are grateful to the Russell Sage Foundation and the National Science Foundation for their financial support as well as to Project
Vote Smart for providing us with data from their NPAT survey of candidates. Earlier versions of this article received critical feedback and
helpful guidance from Michael Berkman, Ernesto Calvo, and Eric Plutzer and from many anonymous reviewers, as well as participants at the
2007 APSA Conference, 2008 State Politics and Policy Conference, and the Summer 2010 Russell Sage Foundation Working Group on the
Politics of Inequality. The authors are responsible for any errors or for the interpretations presented. The data used in this study are stored
on the AJPS Data Archive on Dataverse, available at http://dvn.iq.harvard.edu/dvn/dv/ajps/faces/study/StudyPage.xhtml?studyId=85907&
versionNumber=1.
American Journal of Political Science, Vol. 57, No. 3, July 2013, Pp. 552–565
C 2013,
552
Midwest Political Science Association
DOI: 10.1111/ajps.12007
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POLITICAL PARTIES AND REPRESENTATION OF THE POOR
mechanisms to ensure that politicians pursue the party’s
agenda once elected (Aldrich 1995; APSA 1950; Bawn
et al. 2012; Piven 2006; Schattschneider 1942; Snyder
and Ting 2002). If the preferences of the poor—or
other citizens with limited political resources—are not
incorporated within the campaign agenda of either
political party, those preferences are likely to remain off
the agenda throughout the policymaking process. In this
way, exclusion of any group’s interests at this early stage of
the policymaking process sets a limit on the level of policy
responsiveness possible in subsequent stages. Further,
persistent exclusion of any group’s interests is likely to
demobilize and further marginalize that group over time
(Lukes 2005; Schattschneider 1960; Solt 2008) and further
reduce the likelihood of its preferences ever being considered on the political agenda (Bachrach and Baratz 1970).
This article examines the responsiveness of state political parties to the preferences of low-income, middleincome, and high-income citizens during this early stage
of the policymaking process. We begin by applying resource theory to political parties—highlighting the incentives in our current political environment for both
parties to make policy appeal to citizens with the greatest
resources. Yet, due to the distinct ideologies of Democratic and Republican parties, we expect each to respond
to these resource-driven incentives with distinct appeals
as Democratic parties capitalize on the relative liberalism
of the wealthy on social issues and Republican parties
benefit from the relative conservatism of the wealthy on
economic issues. Finally, we expect these incentives to be
most pronounced in states with higher levels of income
inequality—where the distribution of resources among
citizens is, by definition, most unequal. We test these
expectations using new measures of the economic and
social policy positions adopted by state parties, as well
as economic and social policy preferences held by low-,
middle-, and high-income constituents in each state. We
find both parties to be most responsive to the preferences
of more affluent constituents—with this skewed responsiveness most pronounced on economic issues and among
Democratic parties in states with high levels of income
inequality.
reciprocity between voters and state elites on which the
democratic idea rests” (2006, 4). In fact, the normative
hope is that strong parties serve to equalize responsiveness
across citizens and act as one of the primary avenues for
representation of those with fewer resources to organize
on their own (APSA 1950).
Indeed, political parties play a key role in structuring the broader political conflict across a range of distinct
district-level contests. Serving as issue aggregators, parties
link ideologically similar candidates under a clear party
label in a way that transmits important political content to
incompletely informed voters (Aldrich and Griffin 2010;
Snyder and Ting 2002). This information signal is effective
because party membership imposes costs on candidates,
with parties acting as gatekeepers screening out candidates with policy positions that deviate too far from its
“brand name” (Cohen et al. 2008; Gibson et al. 1983;
Masket 2009; Snyder and Ting 2002). It is in the interest
of parties to undertake this recruitment, screening, and
monitoring function because their value depends on the
relative cohesiveness of candidates running under that
label (Aldrich and Griffin 2010; Grynaviski 2011). And
most candidates comply with this party-structured environment because cohesive and clear party labels also help
solve many of the information and coordination problems they face in trying to win elections and build stable
careers in elected office (Aldrich 1995).
Of course, for the party label to be of value to voters and candidates alike, it is necessary for party labels
to signal the actions that party members will undertake
if elected to office. Central to this accountability mechanism are policy positions, which help clarify, reinforce,
and refine each party’s reputation (Cox and McCubbins
1993, 2005). But even without these electoral incentives,
parties—defined broadly as elected officials, party activists, and loyal interest groups—are typically coalitions
of policy high-demanders motivated to identify, elect, direct, and maintain in office those who will pursue their
key policy priorities (Bawn et al. 2012; Cohen et al. 2008;
Hussey and Zaller 2011). It is not surprising, therefore,
that parties operate as governing teams—leading to the
bundling of issues, a reduced conflict, and a more structured and polarized political environment (Aldrich and
Battista 2002; Wright and Schaffner 2002).
Representation via Political Parties
We zero in on political parties due to their centrality in
the health of democratic systems (Schattschneider 1960)
and particularly their ability to include or exclude disadvantaged citizens from the political process (Key 1949).
Piven acknowledged this role by describing parties as the
“agencies that actualize—or fail to actualize—the ideal of
Unequal Resources and Parties’
Responsiveness
A consistent finding from the political behavior literature
is the importance of resources in structuring individuals’ political lives. Wealthier individuals are more likely
554
ELIZABETH RIGBY AND GERALD C. WRIGHT
choosing whom to contact and mobilize (Campbell 2007;
Huckfeldt and Sprague 1992), we can assume they
use rational prospecting (Hacker and Pierson 2010a)
and segmented policy appeals (Druckman and Jacobs
2011) in deciding whose policy priorities to emphasize.
In this way, differential responsiveness can stem from
strategic political parties operating in an increasingly
resource-dependent environment, which incentivizes
greater attention to wealthier constituents. This leads to
our first hypothesis:
to also hold other salient advantages in terms of information, time, and civic skills that lead to higher rates of
registration, voting, and especially other forms of political
participation (Brady, Verba, and Schlozman 1995; Verba,
Schlozman, and Brady 2006; Winters and Page 2009). This
includes direct lobbying and campaign contributions but
can also occur indirectly because the wealthy are more
likely to control large organizations that lobby on their
behalf (Winters and Page 2009).
This reality has always played into the strategic calculations of political parties, which must assemble the
resources needed to run a successful campaign. Yet, in recent years, the resource demands on parties have reached
new heights. Today, American elections are the most expensive in the world with increasing reliance on media
and high-cost advertising (Powell and Wilcox 2010). Further, the nature of campaigning has shifted away from
mobilization via traditional organizational bases, such as
unions and cross-class membership organizations that in
the past had mobilized a broad swath of voters (Hacker
and Pierson 2010a; Skocpol 1999). Instead, as argued by
Hacker and Pierson (2010a), the organizational routines
of American politics have been monetized, with more of a
campaign’s time, attention, and budget devoted to efforts
to secure financial donations.
Of course, donors to political campaigns are disproportionately affluent (Powell and Wilcox 2010); in fact,
among all forms of political participation, contributing is
the one that most amplifies the voice of wealthy interests
and fuels participatory bias (Powell 2012; Schlozman et al.
2012). This fact, paired with growing resource demands,
has led parties to focus their efforts on the wealthy who are
in a position to make donations and are most disposed to
vote (Huckfeldt and Sprague 1992; Schier 2000). Indeed,
Campbell (2007) documented a sharp increase in parties’ efforts to mobilize high-income voters over the last
few decades, which has resulted in a world in which both
parties depend on the wealthy to finance their campaigns.
Of course, we do not expect Democratic and Republican parties to occupy the exact same policy space as a
result of prioritizing the preferences of their wealthiest
constituents. Both parties—and their supporters—retain
long-standing ideological commitments, with the more
conservative Republicans favoring the interests of the
rich, including free-market policies, and New Deal–style
Democrats being more concerned with the situation of
the poor and more amenable to redistributive and regulatory policies to serve their interests (Ladd and Hadley
1975; Stonecash 2000). Thus, the current political environment, with its high resource demands, provides an
advantage to Republicans who naturally have a wealthier constituency (Campbell 2007). We expect Democratic
parties to address this structural disadvantage by balancing broad appeals to their traditional constituency and
long-standing policy priorities with more targeted appeals to wealthier constituents on particular issues. At the
same time, Republican parties are likely to make crossincome appeals to court the median voter in order to
broaden their constituency beyond those in the (small)
upper-income group.
Incentives for Differential Responsiveness. This
increased reliance on support from wealthy citizens provides greater incentive for parties to assess and understand
the priorities of their wealthy donors. In addition, today’s
party activists are no longer motivated by prospects of
patronage, but instead prioritize candidates who share
deeply held values and specific policy preferences (Cohen
et al. 2008). Not surprisingly, appeals to these ideologically
motivated donors can constrain policy makers via campaign promises on which they will be held accountable in
future cycles of fundraising and electoral contests (Powell
2012). Just as political parties are strategic—taking
into consideration their political environment—when
Issue-Specific Appeals. As Hacker and Pierson explained, “The art for policy makers is not to respond
to the median voter; it is to minimize the trade-offs when
the desires of powerful groups and the desires of voters
collide” (2010b, 173). We expect parties, in making these
strategic calculations, to capitalize on opportunities provided to them by the cross-cutting opinion structure in
which higher-income Americans tend to be more conservative than the poor on economic issues, but more liberal on social and moral issues (Ansolabehere, Rodden,
and Snyder 2006; Gilens 2009; Rigby and Wright 2011).
These differences have been found to be even more pronounced among those who make financial contributions
H1: Both political parties will endorse policy preferences
more closely aligned with their higher-income constituents; preferences of low-income citizens will be
underrepresented.
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POLITICAL PARTIES AND REPRESENTATION OF THE POOR
to campaigns—a group disproportionately liberal on social issues and conservative on economic issues (Schlozman et al. 2012). This cross-cutting pattern of public
opinion opens up opportunities for both parties to appeal to both the median voter and the wealthy by altering
their strategies across economic and social policy issues.
Recent evidence suggests that this strategy may be effective; Schlozman et al. (2012) found that Democratic
contributors hold similar economic policy positions as
other Democrats on economic policy issues—but stand
out for their more liberal stance on social issues. Exhibiting the opposite pattern, Republican contributors hold
social policy views similar to other Republicans but are
distinguished by their more conservative stances on economic issues.
Given these patterns of public opinion, Democratic
parties have greater incentives to move away from the
preferences of the poor and toward the preferences of the
rich on social policy issues, such as gun control, abortion, or gay rights, in which the wealthy are more liberal
than low-income Americans. On these social issues, we
expect Democrats to seek support (and donations) from
higher-income voters by being responsive to this group’s
more liberal social policy preferences, a pattern consistent
with voting in recent presidential elections (Bartels 2008;
Gelman et al. 2008). In contrast, Republicans are already
well positioned to compete in the resource-dependent
campaign environment we face today (Campbell 2007),
but they may still wish to capitalize on the relative conservatism of lower-income voters on social policy issues
in order to secure broader support than their wealthy
constituency alone. This leads to our second hypothesis:
H2: Democratic and Republican parties will make distinct social policy appeals based on the opportunities
provided by the cross-cutting opinion structure—
with Democratic parties aligning most closely with
the wealthy and Republican parties with the middleincome group.
Responsiveness and Income Inequality. If parties respond to resource gaps among their constituents when
making policy appeals, we expect to see the most pronounced bias in responsiveness when and where economic resources are most unequal. Relative power theory
highlights the importance of the distribution of resources
in structuring political power, since money can be used
to influence others and therefore can be translated into
greater political power among wealthy vis-à-vis poorer
citizens (Goodin and Dryzek 1980; Solt 2008). As argued
by Schattschneider (1960), income inequality provides
greater opportunity for a smaller set of richer constituents
to set the agenda and define the scope of conflict, while
encouraging less political participation and engagement
among everyone else.
Indeed, a large gap in income and related life circumstances works against a sense of common fate and
concern (Hero 1998), resulting in a society divided into
“haves” and “have nots,” with little social or political capital bridging Americans (Alesina and Glaeser 2004). When
income inequality is high, people are more segregated by
income (Soss and Jacobs 2009), and societal well-being
suffers along many dimensions (Wilkinson and Picket
2010). These divisions extend into the political domain as
well—with inequality linked to greater party polarization
(McCarty, Poole, and Rosenthal 2006), more ideological distance between partisan identifiers (Garand 2010),
greater geographic segregation of rich voters from poor
nonvoters (Jacobs and Soss 2010), and greater policy conservatism among the public (Kelly and Enns 2010).
From the perspective of resource-dependent parties,
income inequality produces electorates that are not only
smaller but also wealthier—with the resources to fund
campaigns concentrated in fewer hands (Winters and
Page 2010). This narrowing of the electorate occurs in
two ways. First, income inequality raises the stakes for the
wealthy to participate in politics given growing evidence
that policy choices play a key role in structuring the
current and future distribution of wealth (Hacker and
Pierson 2010a; Kelly 2009), including the benefits that
accrue to the advantaged in more unequal economies
(Albrech and Albrech 2007). At the same time, income
inequality serves to depress political interest, discussion,
and participation among all but the most affluent
citizens (Solt 2008, 2010) and exacerbates inequalities
in participation (Soss and Jacobs 2009). Solt concludes
that the “declining political engagement of nonaffluent
citizens with rising inequality suggests that issues on
which a consensus exists among richer individuals, such
as redistribution, become increasingly unlikely to even
be debated within the political process regardless of
whether poorer citizens would care to raise them” (2008,
57). This leads to our third hypothesis:
H3: Where and when income inequality is higher, parties
will exhibit greater differential responsiveness toward
their income-third constituents.
Data and Measurement
To test these hypotheses, we capitalize on the variation
in party positioning and income-based political characteristics across the states. We combine new data on
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ELIZABETH RIGBY AND GERALD C. WRIGHT
state parties’ ideological positioning with estimates of
income-group opinion for 47 states, excluding Nebraska
because of its nonpartisan legislature and both Alaska and
Hawaii due to their exclusion from the survey data used
to estimate mass opinion and behavior.
Estimating State-Level Opinion across
Income Groups
To estimate opinion across income groups, we use the
National Annenberg Election Survey (see Romer et al.
2006); its large sample of the 2000 presidential electorate
consists of 58,373 respondents, including a substantial
number from each of the 48 continental states. A drawback to the Annenberg survey data is that respondents
were interviewed via a set of rolling, cross-sectional surveys in which different sets of questions were asked of each
cross-section. To generate measures of policy preferences
across these surveys, we pooled the cross-sectional surveys for 2000 into one dataset and identified 13 common
policy items in the survey—each asking for respondents’
preferences across a range of policy areas (for items, see
online Appendix A).
Three of these 13 items were asked on all the surveys,
while the other 10 were asked in approximately half of the
surveys. As a result, we used respondents’ answers on the
questions they were asked to estimate their responses to
other policy items. We imputed these missing data using
multiple chained equations (see Royston 2005), which
maximized similarities in responses across items. As a
result, these data are best suited to capturing a latent construct (e.g., social policy liberalism) rather than precise
views on a particular issue (i.e., the death penalty or abortion). In fact, simulations designed to assess the accuracy
of these imputations (described in online Appendix B)
indicate that the scales created using imputed values correlate very highly with measures based on full information
(r = .97 for economic issues and .96 for social issues).
To generate the opinion scales used in these analyses,
we factor analyzed two subsets of items. The first was a set
of seven items related to economic policy issues (e.g., tax
policy, health care, and social welfare programs). Then, we
factor analyzed six items tapping social policy issues (e.g.,
abortion, death penalty, gay rights, and school prayer).
Information on these items and their factor loadings are
presented in online Appendix A. Most critical to this
analysis, both factor models explained the vast majority
(>97%) of the variance among items, with eigenvalues
well above 1 (and eigenvalues for both of the second factors below .50). Both scales are coded so that higher values
indicate more liberal policy positions.
To estimate the policy preferences of different income groups across states, we needed to collapse the
nine-category income variable used by the Annenberg
survey into fewer categories. We classified respondents
based on their relative income within the state, dividing each state electorate into thirds. Adopting a method
used by Bhatti and Erikson (2011), when an income category spanned one of the percentile thresholds (the 33rd
or 66th percentile), we assigned those respondents the
mean opinion score for that income response category in
that state. We then assigned that group’s mean opinion
score proportionally to the low, middle, or high third. For
example, in Missouri there were 319 respondents who reported income between $50,000 and $75,000. This group
spanned the 66 percentile cut-off between the middle and
upper third—ranging from the 59.4 to 78.4 percentile of
Missouri’s income distribution. Therefore, we assigned
34.7% of this group’s respondents (and mean opinion
score) to Missouri’s middle-income third and 65.3% to
the state’s high-income third.
Equally sized groups within each state were an important component of our modeling strategy because we
wanted to test a proportional notion of equality of representation in which each income group is influential in
proportion to its size, rather than resources. This measurement strategy also allowed us to take a simple average
of the policy preferences of each third in each state rather
than requiring the use of weights to adjust for varying
sizes of each group in each state. However, we acknowledge that there are other ways to divide state electorates
by income. Online Appendix C provides a comparison of
our measures with those generated using two alternative
methods: scaled scores (as employed by Bartels 2008) and
predicted values (as used by Gilens 2005, 2012). As shown
in the appendix, these approaches generate estimates of
states’ low-, middle-, and income-third opinion that are
highly correlated (r > .95 across each method) with those
generated from the pooled-thirds approach we employ.
These aggregated preference measures (N = 47
states) are presented in Figure 1, which displays the distribution of preferences of low-, middle-, and income-third
constituents across the states. Consistent with previous
work, we find different distributions of preferences for
the economic (top panel) and social (bottom panel) policy preferences even though both measures are standardized on the same scale (M = 0, sd = 1) at the individual
level. In particular, we see a larger income gap in economic policy preferences—with the low-income group
most liberal (M = .16, sd = .12) on these issues, followed by the middle-income group (M = −.03, sd = .11),
and then the relatively more conservative higher-income
group (M = −.18, sd = .12). For social issues, we find
557
POLITICAL PARTIES AND REPRESENTATION OF THE POOR
FIGURE 1 Public Policy Preferences, by Income
Group
(a)
Economic Issues
Low
Income
Middle
Income
High
Income
-.4
(b)
-.2
0
.2
Economic Policy Liberalism
.4
-.2
0
.2
Social Policy Liberalism
.4
Social Issues
Low
Income
Middle
Income
High
Income
-.4
Note: N = 47 states. Policy preferences estimated from 2000 National Annenberg Election Survey, aggregated to the state level.
the opposite pattern, with the income-third group being
more liberal (M = .03, sd = .22), followed by the middleincome (M = −.03, sd = .20), and then the more socially
conservative low-income group (M = −.08, sd = .17).
Further, the gap between income groups is smaller for social issues than for economic issues; however, the variation
across states is larger for social issues than economic issues
(consistent with other research; see Ansolabehere, Rodden, and Snyder 2006; Gilens 2009; Rigby & Wright 2011).
Estimating State Party Ideology
We define state party ideology as the ideology that
emerges from the collective issue stances of the states’
Democratic and Republican candidates. This approach
captures the policy positions candidates present to the
electorate during the campaigns, which likely carry more
force than the seldom-read official platforms. Further, by
using electoral positions—rather than legislative votes—
we capture party positions on the same scale across states
and chambers, while avoiding state differences in patterns
of party control, agenda control, and legislative procedures that could distort ideology measured through rollcall votes across 94 chambers.
We pooled data gathered by Project Vote Smart, a
nonpartisan voter education service that administers the
National Political Awareness Test (NPATs) to candidates
for federal and state office. We used responses from 18,467
surveys completed by Democratic or Republican candidates for the state legislature, Congress, or governor. By
pooling across years, we achieved adequate state samples,
which average 373 (sd = 182) and range from 115 in
Louisiana to 968 in New Hampshire. Project Vote Smart
adapts its surveys for each election cycle, office, and state.
Therefore, we needed to extract the overlapping questions across the 255 distinct surveys fielded from 1996
to 2005. We identified 87 items asked to at least half of
the party candidates during this time. Missing items were
imputed using a process parallel to that used for the public opinion data described above (multiple imputations
by chained equations; see online Appendix B for more
information on imputation strategy). As with the public
opinion measures, a set of simulations found this imputation approach to yield measures that are highly correlated
with scales developed from full information (r = .99 for
both issue scales).
To generate measures of candidates’ economic and
social policy preferences, we followed the same procedure
as undertaken for the public opinion data and factor
analyzed subsets of items capturing economic policy
issues (25 items related to redistributive tax and spending
policies and the social safety net) and social policy issues
(20 items related to abortion, gun control, civil rights,
and school prayer). The specific items are listed in online
Appendix A, along with information on the raw (versus
imputed) number of cases and factor loadings. Beginning
with the economic policy items, we factor analyzed the
25 items and extracted the first factor, which explained
78% of the variance (eigenvalue = 7.03). Predicted values
were generated for each candidate-year and rescaled
so that higher values indicated greater liberalism on
economic policy issues. Candidates varied from −3.42
to 1.92 on this scale; not surprisingly, Democrats had
higher scores (M = .65, sd = .61) than did Republicans
(M = −.66, sd = .81). We then factor analyzed the 20
social policy items and extracted the first factor, which
explained 65% of the variance (eigenvalue = 4.53), and
coded the scores so that higher values indicated more
liberal positions on social policy issues. The individual
scores varied from −2.01 to 1.89, with Democratic
candidates more liberal (M = .55, sd = .77) than Republicans (M = −.57, sd = .74). From these individual-level
558
ELIZABETH RIGBY AND GERALD C. WRIGHT
Their response rate of 32% (sd = 7%, ranging from 20% in
Virginia to 47% in South Dakota) is about average for an elite
survey such as this but nevertheless has the potential to introduce selection bias. To attempt to account for any selection effects,
we generated individual-level poststratification weights that adjust
the state-specific estimates for observed patterns of nonresponse.
Based on observed factors (office seeking, district safety, incumbency, election year), selection bias in these data appears to be
quite modest. In fact, the state-specific R2 s explaining participation in the NPATs averaged only .08 (sd = .05). Therefore, it is not
surprising that correcting for possible selection bias at the individual level had little effect on the aggregated scores for the state
parties, which correlate highly (r = .96 and .98) with the simple
state-party means.
1
2
We theorize in this article about parties and their strategic policy
appeals; however, we acknowledge that legislator behavior may also
affect constituency preferences—leaving open the possibility of endogeneity within our cross-sectional measures. Yet, while there may
be legislative leadership of some constituents’ opinions, we cannot
come up with a plausible story for how that would undermine our
findings across this broad swath of policy issues and candidates,
particularly since it seems unlikely that high-income voters are
more easily persuaded than middle- and low-income voters.
1
Democratic Parties
.5
0
Republican Parties
-.5
-1
-.2
-.1
0
.1
.2
Average State Opinion: Economic Issues
Democratic Parties
.5
1
(b) Social Issues
0
Our approach to assessing policy responsiveness is in
the correlation tradition established by Miller and Stokes
(1963) and adapted in many studies of representation
since. We measure how well the relative liberalismconservatism of the public, or income groups within
the public, covary with the economic and social issue
stances of the state Democratic and Republican parties.
While this approach has known limitations (Achen 1977;
Erikson, Wright, and McIver 1993), it is also the case that
given reasonable variance in public preferences, congruence is a necessary condition for policy responsiveness.
That is, at a minimum if the parties are responsive to citizen preferences, then more liberal state electorates should
also have more liberal parties. Thus, while it is arguably
preferable to measure the parties’ stances and the public’s preference on the same metric, a great deal can still
be learned by assessing patterns of relative congruence.
Most importantly, we are able to detect whether parties’
positions vary systematically with the preferences of each
income group. If parties are especially sensitive to the
preferences of a particular income group, then we would
expect cross-state differences in party positions to most
closely track cross-state differences in that group’s policy
preferences.2
(a) Economic Issues
Republican Parties
-.5
Empirical Strategy and Results
FIGURE 2 Party Platforms, by Average Public
Opinion in the State
-1
scores, we estimated each state party’s liberalism by
taking the mean response of candidates for each party
in the state. However, we also generated weighted scores
that adjusted individual-level responses for patterns of
nonresponse in the Project Vote Smart data.1
-.4
-.2
0
.2
.4
Average State Opinion: Social Issues
Note: N = 47 states. Average policy liberalism score for candidates
from Democratic and Republican parties, estimated from Project
Vote Smart data.
Average Responsiveness
Before moving into testing our hypotheses, we examine
the positioning of state parties in terms of the average
opinion in each state (the mean of all state respondents).
These basic relationships are presented in Figure 2. The
top scatterplot shows the relationship between parties’
economic policy liberalism and the average public opinion on economic issues. There is little relationship between the two parties on these issues (r = .24), which
is primarily due to the absence of a relationship between
Democratic party liberalism and public opinion (r = .04).
In contrast, Republican parties are more liberal on economic issues when they represent a public more liberal on
economic issues (r = .40). The bottom panel presents the
559
POLITICAL PARTIES AND REPRESENTATION OF THE POOR
TABLE 1 Parties’ Responsiveness to Policy Preferences of Each Income Group
Democratic Parties
(1)
Economic Issues
Low Income
(2)
R-squared
Social Issues
Low Income
0.64∗
(0.04)
0.033
0.60∗
(0.03)
0.002
0.44
(0.28)
0.53∗
(0.21)
0.69∗
(0.05)
0.121
−0.52+
(0.29)
−0.09
(0.39)
0.80∗
(0.28)
0.83∗
(0.07)
0.246
1.40∗
(0.13)
0.37∗
(0.03)
0.726
−0.32
(0.36)
0.51
(0.35)
1.19∗
(0.29)
0.37∗
(0.04)
0.740
1.42∗
(0.16)
High Income
R-squared
(1)
1.52∗
(0.22)
Middle Income
Constant
(4)
0.07
(0.24)
High Income
Constant
(3)
−0.27
(0.22)
Middle Income
0.53∗
(0.04)
0.510
0.45∗
(0.03)
0.632
Republican Parties
(2)
(3)
(4)
0.82∗
(0.27)
−0.51∗
(0.06)
0.173
−0.11
(0.39)
0.50
(0.52)
0.55
(0.37)
−0.53∗
(0.09)
0.195
0.84∗
(0.15)
−0.62∗
(0.03)
0.409
−0.42
(0.40)
1.09∗
(0.38)
0.24
(0.32)
−0.60∗
(0.05)
0.504
0.80∗
(0.29)
−0.74∗
(0.06)
0.053
−0.64∗
(0.03)
0.149
0.97∗
(0.21)
1.00∗
(0.15)
−0.51∗
(0.04)
0.324
−0.56∗
(0.03)
0.489
Note: N = 47, excludes AK, HI, NE. Coefficients from OLS regression models in which measures of party policy positions are regressed on
the mean opinion of each group. Models 1–3 examine alignment: the bivariate relationship between each group’s opinion and the party
position (regardless of preferences of other two groups. Model 4 tests for influence: the partial association after controlling for the opinion
of the other two groups. Standard errors are presented in parentheses beneath each coefficient. ∗ = p < .05, + = p < .10.
same relationships for our measures of social policy liberalism. Here we see a positive relationship between public
preferences and both Democratic (r = .83) and Republican (.67) parties’ social policy liberalism. The two parties
are correlated at .60 as well.
Differential Responsiveness
We test for two distinct notions of responsiveness as commonly operationalized in the literature, which we call
alignment and influence. Representation as alignment
asks, how well do the state parties’ stances on economic
and social issues covary with the preferences of each income group? To answer this question, we look at the simple bivariate relationships between each income group’s
preferences and state party positions. This is the measurement strategy used by Soroka and Wlezien (2008)
and others, who tend to find less evidence of differential
responsiveness across income groups—concluding that
the overlap in preferences among the rich and poor provides a “natural limit” on the level of political inequality
that can occur. In contrast, conceptualizing representation as influence raises the bar, asking: whose preferences
are responded to on issues in which lower-, middle-, and
high-income constituents disagree? We test for influence
with the partial association between each income group’s
opinion and each party’s position, controlling for the
preferences of the other two income groups in the state. It
is this second notion of responsiveness employed by Bartels (2008) and most others who have identified unequal
responsiveness to various groups.
Rather than choosing between these two modeling
approaches, we compare the results from models using
each operationalization. This allows us to capture a potential midlevel of responsiveness in which a group’s preferences are included in party positions (alignment) even
if their preferences are ignored when these preferences
diverge from those of the other income groups in the
state (influence). Teasing apart these distinct notions of
responsiveness is particularly important for contextualizing differential responsiveness within our current public
opinion landscape, in which the preference gap between
the rich and poor varies in size across specific policy
560
FIGURE 3 Parties’ Responsiveness to
Preferences of Different Income
Groups
(a) Economic Issues
Republicans: Alignment
Democrats: Influence
Republicans: Influence
-1
0
1
2
-1
0
1
2
Democrats: Alignment
.
Low
Middle
High
.
.
slope
Low
Middle
High
.
95% CI
(b) Social Issues
Republicans: Alignment
Democrats: Influence
Republicans: Influence
0
1
2
-1
0
1
2
Democrats: Alignment
-1
issues, as well as across and within states (Gelman et al.
2008; Gilens 2009; Rigby and Wright 2011; Soroka and
Wlezien 2008). Rather than attributing parties’ responsiveness to overlapping preferences as evidence of equality
in responsiveness (as did Soroka and Wlezien 2008) or excluding this alignment from an assessment of differential
responsiveness (as did Bartels 2008), we wish to explore
and identify these alternative forms of responsiveness to
the rich versus the poor.
We tested our hypotheses in cross-sectional OLS
models that regressed the policy liberalism of each party
(separately) on the preferences of each income-third in
the state. We adopt a reduced-form model since our aim
is not to maximize the explained variance in party positions but rather to assess the fit between the preferences
of different income groups and how the parties align.
Including a range of state-level economic, demographic,
and political variables to these models would add to our
ability to explain party positions but would seriously limit
our ability to assess the relative alignment and influence
of income groups.
Table 1 presents the results of these OLS models for
both economic policy positions (top) and social policy
positions (bottom). Beginning with Democratic parties,
we find little alignment between party positions and the
opinion of either low-income or middle-income citizens
in the state. Instead, the economic platforms of Democratic parties are only aligned with the preferences of those
in the top income third in the state (b = .53, se = .21).
Not surprisingly, this result persists in Model 4 (b = .80,
se = .28), which tests for the independent influence of
each group’s preferences on the issues in which income
groups disagree.
In contrast, Republican parties’ economic positions
exhibit almost parallel associations for both the middleincome (b = .80, se = .29) and income-third (b = .82,
se = .27) groups—but again, no bivariate association for
the low-income group. These alignment models provide
some insight into why we find no independent influence
in Model 4, where we test for the independent influence of
each group’s opinion over and above the other two groups.
Since the economic campaign appeals made by Republican parties vary with both the opinion of the middle- and
upper-income groups, neither of these two coefficients is
significant in Model 4. However, the joint significance of
these two coefficients is significant (F = 3.79, p < .05), as
are individual coefficients for middle- and income-third
opinion (but never low income) in models that omit either middle- or income-third opinion.
We see a different pattern for social policy issues.
Both parties exhibit alignment with the preferences of
all three income groups when considered alone (coeffi-
ELIZABETH RIGBY AND GERALD C. WRIGHT
.
Low
Middle
High
slope
.
.
Low
Middle
High
.
95% CI
Note: N = 47 states. Predicted first differences for a one-unit
change in each group’s opinion. Alignment estimates reflect the
bivariate relationship between the group’s opinion and party
position. Influence estimates reflect the partial association after
controlling for the opinion of the other two groups.
cients ranging from .84 to 1.52). However, in Model 4,
which tests for the independent influence of each income group, we see clear evidence of differential responsiveness in which one income group exhibits greater influence. As expected, when the income groups disagree
on social issues, Democratic parties are most responsive to the distinct preferences of the high-income group
(b = 1.19, se = .29), while Republican parties are most
aligned with the distinct preferences of the middleincome group (b = 1.09, se = .38).
These findings are brought together in Figure 3,
which presents the predicted first difference for a oneunit change in each group’s opinion. It illustrates how,
for economic policy issues (top panel), party positions
are aligned with the preferences of their more advantaged
561
POLITICAL PARTIES AND REPRESENTATION OF THE POOR
TABLE 2 Differential Responsiveness, by State Income Inequality
Economic Issues
Democratic Parties
Low Income
Middle Income
High Income
Income Inequality
Democratic Parties
Republican Parties
(2)
(1)
(2)
(1)
(2)
(1)
(2)
−0.53+
(0.29)
−0.01
(0.44)
0.77∗
(0.29)
−0.43
(1.02)
8.20
(6.30)
4.98
(7.40)
−10.04+
(5.66)
7.05∗
(3.14)
−17.87
(12.95)
−10.00
(14.97)
21.81+
(11.44)
−2.62+
(1.54)
0.362
−0.10
(0.39)
0.33
(0.58)
0.62
(0.39)
0.88
(1.37)
−7.57
(9.08)
3.43
(10.66)
−0.36
(8.15)
−1.89
(4.53)
15.38
(18.65)
−6.42
(21.56)
2.05
(16.48)
0.38
(2.21)
0.219
−0.54
(0.40)
0.65+
(0.36)
1.18∗
(0.28)
−1.45
(1.12)
3.70
(6.58)
12.67∗
(4.94)
−18.44∗
(5.96)
−3.94∗
(1.92)
−8.42
(13.47)
−24.83∗
(9.97)
39.68∗
(12.12)
2.32∗
(0.93)
0.821
−0.29
(0.45)
1.00∗
(0.41)
0.24
(0.32)
0.86
(1.26)
−0.21
(8.33)
−0.35
(6.26)
−3.96
(7.55)
1.11
(2.43)
0.39
(17.06)
2.30
(12.62)
8.23
(15.35)
−1.11
(1.18)
0.555
Mid X Ineqality
High X Inequality
R-squared
Republican Parties
(1)
Low X Inequality
Constant
Social Issues
1.03∗
(0.50)
0.249
−0.96
(0.67)
0.203
1.07+
(0.55)
0.749
−1.02
(0.62)
0.510
Note: N = 47, excludes AK, HI, NE. Coefficients from OLS regression models in which measures of party policy positions are regressed on
the mean opinion of each group. Model 1 adds the measure of income inequality (market gini) to the basic models presented in Table 1;
Model 2 includes three interaction terms to test for a conditional effect of preferences across states with different levels of income inequality.
Standard errors are presented in parentheses beneath each coefficient. ∗ = p < .05, + = p < .10.
constituents—with Democrats exhibiting differential responsiveness skewed toward the wealthy and Republicans
aligned jointly with the preferences held by the middleand high-income thirds. In contrast, for social issues, both
parties align with the preferences all three income groups;
this is largely a function of the greater agreement on social issues among those in the same state (see Figure 1).
Yet, even for social issues, we see that when the social
policy preferences of income groups diverge, it is only the
more advantaged constituents who exert independent influence (high-income group for Democrats and middleincome group for Republicans). In terms of the poor, their
preferences align only on social issues—and only when
they overlap with the preferences of the middle- or highincome groups to whom parties are more likely to attend.
As shown in online Appendix C, we reestimated these
models using different methods of dividing respondents
into income thirds within the state. We found quite consistent results for all patterns of alignment, as well as
the influence of the middle-income group on Republicans’ social policy liberalism and the high-income group
on Democratic economic policy liberalism. What differed
was only the relative influence of the middle- versus high-
income group for Republican economic positions (jointly
significant in two of the three models) and for Democratic
social policy liberalism (skew toward the rich in two of
the three models). Under no specification did the lowerincome third exert influence on either party.
Role of Income Inequality
We now turn to examining our third hypothesis: that income inequality would serve to further skew responsiveness toward the wealthy in states with more concentrated
wealth. We ask whether responsiveness to the wealthy is
greater in states with more unequal income distributions.
We use a cross-sectional measure of income inequality
based on market-income, pretax, and transfer family income drawn from the 1997–2005 March Current Population Surveys conducted by the U.S. Census Bureau. This
takes the form of a gini coefficient (M = .50, sd = .03)
capturing how far the state’s income distribution deviates
from equality.
Table 2 presents the estimated models, which add the
measure of income inequality along with three interaction
562
FIGURE 4 Democratic Party Responsiveness, by
State Income Inequality
(a) Economic Issues
High Income Inequality: Economic Issues
.
.
-1
0
1
2
Low Income Inequality: Economic Issues
Low
Middle
High
Middle
High
.
High Income Inequality: Social Issues
0
1
2
Low Income Inequality: Social Issues
Low
Middle High
slope
Before concluding, we undertook a set of sensitivity analyses to address two common rationales for differential
responsiveness at this early electoral stage of the policymaking process. First, it may be that our focus on both
winning and losing candidates exacerbated differential
responsiveness since winners may be more aligned with
constituent opinion than those who lose their election.
Second, parties may simply be paying more attention to
voters, rather than nonvoters in their state; and since we
know that voters are not a random subset of the population but tend to be wealthier and better educated (Leighley
and Nagler 2007; Rosenstone and Hansen 1993), greater
attention to voters may explain responsiveness to highincome constituents.
To conduct these sensitivity tests, we restricted the
data used to (a) only those candidates who won their
election and (b) only those respondents to the Annenberg
survey who reported voting “always” or “often.” We then
created parallel measures of Democratic and Republican
Party positions, as well as the average policy liberalism
for those in the bottom, middle, and top third of income
among voters in the state. Online Appendix D presents
the results of these models, which are consistent with the
Low
95% CI
(b) Social Issues
.
Sensitivity Analyses: Electoral Results and
Political Participation
.
slope
-1
terms (income inequality X each group’s opinion). For
both economic and social policy issues, the responsiveness of Democratic parties did vary by the level of income
inequality in the states, with greater income inequality
associated with even more of a skew in responsiveness toward the upper-income third. But, the responsiveness of
Republican parties did not vary by income inequality for
economic issues or for social issues. These findings were
robust to the alternative measures of income groups (see
Appendix C). To illustrate the role of income inequality in
moderating the responsiveness of Democratic parties, we
used the models in Table 2 to estimate Democratic party
liberalism on both economic and social policy issues in a
state with low (one standard deviation below the mean)
versus high (one standard deviation above) income inequality. These predicted values are presented in Figure 4.
The pattern indicates there may well be a basis for concerns that heightened economic inequality exacerbates
representational inequalities among the state Democratic
parties. Importantly, in states with more equal distributions of income, we find no evidence of differential
responsiveness across income groups. However, in states
with higher levels of income inequality, Democratic party
positions were even more highly skewed toward the rich.
ELIZABETH RIGBY AND GERALD C. WRIGHT
.
.
Low
Middle High
.
95% CI
Note: N = 47 Democratic parties. Predicted first differences for
a one-unit change in each group’s opinion, controlling for the
preferences of the other two groups (influence models). Compare
estimates under conditions of low (−1 sd) versus high (+1 sd)
income inequality. Confidence intervals for these point estimates
generated with CLARIFY. Slopes and intervals greater than two
are top-coded at two for ease of presentation. Parallel estimates
are not presented for Republican parties since their responsiveness
did not vary by income inequality.
earlier results, leading us to conclude that neither patterns
of electoral success nor income bias in voting explains the
differential responsiveness we identify. Yet, we note
two consistent patterns in terms of the magnitude
of coefficients across models, which suggest potential
mechanisms. First, we found larger coefficients when
considering only candidates who won their election,
indicating even greater skew in responsiveness among
successful candidates. Second, when we considered parties’ responsiveness to the opinion of the lowest, middle,
and highest third of voters, we found smaller coefficients,
suggesting that a portion of the differential responsiveness
we identified stems from parties overlooking low-income
constituents who are unlikely to vote. These findings are
only suggestive, but do highlight areas for future study.
POLITICAL PARTIES AND REPRESENTATION OF THE POOR
Conclusion
Motivated by recent research that has found skewed responsiveness among the policy outcomes of our political
process, this article asked whether a similar bias shapes
the policy positions taken by political parties much earlier in the policymaking process. Since parties serve to
aggregate diverse interests and function as mechanisms
linking public opinion and policy outputs, any incomebased bias in this process would raise both empirical and
normative concerns, as well as identify a likely source of
political inequality in the later, and more consequential,
policy formation stage.
In assessing the equality of this process, we distinguished between two forms of responsiveness: alignment
and influence, with alignment simply capturing whether
parties align with the preferences of each income group
(considered alone) and influence requiring a higher bar
in which parties respond to the preferences of one income group even when their preferences diverge from
those of the other two groups. However, on economic
policy issues, this distinction was unnecessary since neither party even aligned with the preferences of their lowincome constituents. More responsiveness to the poor
was identified on social policy issues—with both parties
aligned with their social policy preferences. Yet, once we
accounted for the social policy preferences of those in the
top two-thirds of the income distribution, we found no
independent influence of the social policy preferences of
the poor. As a result, the representation of low-income
citizens only occurs when their preferences happen to
concur with the preferences of their economic betters.
When their preferences diverge, those preferences seem
to be left off of the active agenda—even this early in the
policymaking process.
We are limited here in our ability to explain why or
how the preferences of the poor are overlooked. This is
clearly an important question for future work. In particular, we hope to tease apart the degree to which party elites
are aware of the preferences of the poor—intentionally
overlooking them in favor of wealthier constituents—or
whether these patterns can be explained by less stable attitude formation and fewer efforts to communicate those
preferences among the poor. Indeed, we found slightly
lower reliabilities among the poor in the individual-level
data we used to estimate each group’s policy preferences.
Yet, it is not clear whether this reflects measurement errors, which may be cancelled out via the aggregation
process, or a true difference in preference stability that
could shape the process of representation.3 The lack of
3
A similar question was taken up by Gilens (2012), who used a
multiple-measure technique to estimate the reliability of opinions
563
responsiveness to the poor does not necessarily mean
that both parties cater to the narrow self-interests of the
rich. Indeed, when we examine differences between the
state parties, it is clear that the Democrats are a good deal
more liberal and many of their policies favor redistribution and regulations that would improve the material
circumstances of those with lower incomes. So while the
Democratic parties in the states do tend to stand for economic policies benefiting the “have nots,” the extent of
that stance tends to be sharply circumscribed by preferences among more affluent citizens.
Does this make any difference? Normatively, it is less
than satisfying to find that the least fortunate in society
have no independent voice in the formulation of party
platforms. Materially, while there is overlap across the
states in the preferences of income groups, it is also clear
(see Figure 1) that the poor (and even the middle-income
group) prefer more liberal economic policies than do
those in the upper-income third. Therefore, we suspect
that if the preferences of each income group were accorded equal weight, both parties’ stances on economic
issues would shift to the left. And accordingly, although
to a smaller degree, Democratic parties’ stances on social
issues would shift rightward.
Our findings also shed light on our general understanding of political representation. These patterns are
consistent with our notion of resource constraints on parties. With Republicans enjoying a wealthier constituency
base, they have more leeway to make broader campaign appeals aligned with the preferences of the middleincome group, which includes the median voter. As expected, this appeal to the middle is evident for Republican
parties on social issues, while Republican economic positions are skewed toward the middle- and high-income
groups. In contrast, the resource demands of today’s campaigns do more to constrain Democratic parties, whose
natural constituencies are less affluent; thus, Democrats
must find a way to appeal to the policy priorities of potential donors. Indeed, we find that Democratic parties
are most aligned with the preferences of the top third
of the income distribution on both economic and social
held by respondents at different groups. He found quite similar reliabilities (.77 for 10th percentile, .80 for 50th percentile, and .77 for
90th percentile) at the individual level; further, he expressed similar
uncertainty regarding whether these reliabilities were even applicable once these data were aggregated (Gilens 2012, 88). Further,
we believe that differences in reliabilities among income groups
reflect true differences in the opinion structure of these groups—as
opposed to measurement error resulting from measures that work
better for one group or the other. Thus, even if we knew the relative reliability of our aggregated measures, an errors-in-variables
approach is not appropriate here as it would be if we were comparing different measures in which some were more reliably measured
than others.
564
ELIZABETH RIGBY AND GERALD C. WRIGHT
issues. This responsiveness to the affluent is most pronounced in states with greater income inequality where,
by definition, economic resources (including those that
can be used to finance campaigns) are most concentrated
in the fewest hands—serving to exacerbate any income
bias in representation at this early, formative stage of the
policymaking process.
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Supporting Information
Additional Supporting Information may be found in the
online version of this article at the publisher’s web site:
Appendix A: Information on Survey Items used in
Policy Liberalism Scales
Appendix B: Additional Information on Missing
Data Imputation
Figure B1: Proportion of Cases Imputed, Public
Opinion Liberalism
Figure B2: Proportion of Cases Imputed, Parties’
Liberalism
Figure B3: Public Opinion Liberalism Scores, Imputed versus Known Values
Figure B4: Policymakers’ Liberalism Scores, Imputed
versus Known Values
Appendix C: Sensitivity Analyses: Alternatives for
Dividing Income Groups
Appendix D: Sensitivity Analyses: Restricted Samples
(Winners and Voters)