Download Party Fit Theory: A Candidate-Level Explanation

Party Fit Theory:
A Candidate-Level Explanation for Partisan Polarization in Congress
Danielle Thomsen
214 White Hall
Department of Government
Cornell University
Ithaca, NY 14853
[email protected]
Abstract
Scholars have focused on elite-level and mass-level changes to explain partisan polarization in
Congress. This paper offers a candidate-level explanation for the persistence of polarization and
the rise in asymmetric polarization. I develop a theory of Party Fit that suggests that ideological
extremism in Congress has discouraged moderates in the political pipeline from pursuing a
congressional career. I test Party Fit Theory with a survey of state legislators and with ideology
estimates of state legislators who did and did not run for Congress from 2000 to 2010. I find that
moderate Republican state legislators are less likely to believe they can achieve their electoral
and policy goals, and they are less likely to run for Congress as the party becomes increasingly
conservative. However, these disparities do not emerge on the Democratic side. Party Fit
Theory provides an additional explanation for recent patterns of polarization in Congress.
1 Partisan polarization has received ample attention in the study of American politics, but
scholars have recently suggested that the polarization literature is lacking in one crucial respect.
The term polarization assumes equal movement by the two parties, but what is instead happening
is that “the move from the center has been spearheaded and driven by the Republican Party”
(Hacker and Pierson 2005, 5). Over the past thirty years, the Democratic Party has shifted
modestly to the left while the Republican Party has charged sharply to the right, and the House
Republican caucus is now much more conservative than the House Democratic caucus is liberal.
Partisan polarization in Congress is, in short, an “asymmetric” phenomenon (Carmines 2011;
Hacker and Pierson 2005; Mann and Ornstein 2012; Skocpol and Williamson 2012).
Contemporary patterns of polarization have been driven in part by changes in the
electorate. While the question of voter polarization has been hotly debated (Abramowitz 2010;
Abramowitz and Saunders 2008; Fiorina et al. 2006), most agree that party activists, and
especially Republican activists, have moved increasingly toward the poles (e.g., Fiorina et al.
2006; Hacker and Pierson 2005; Layman et al. 2010; Sinclair 2006; Theriault 2008). What is
puzzling, however, is that members of Congress are even more extreme than both activists and
voters, and there is evidence suggesting that representatives in Congress do not simply reflect the
ideological position of either the median voter or in most cases, the median partisan voter
(Bafumi and Herron 2010; see also Ansolabehere et al. 2001; Bafumi et al. 2010; Clinton 2006;
Hussey and Zaller 2011). Instead we see what Bafumi and Herron (2010) call “leapfrog
representation,” with one extremist in Congress being replaced by another extremist. Such
replacement processes are one of the primary drivers behind the rise in partisan polarization
(Fleisher and Bond 2004; Theriault 2006) and asymmetric polarization (Bonica 2010; Carmines
2 2011; Skocpol and Williamson 2012), yet we do not fully understand why these replacements,
and particularly Republican replacements, are more extreme than their predecessors.
I develop a theory of Party Fit to account for these recent patterns of polarization in
Congress. Party Fit Theory provides a candidate-level explanation for why the Republican Party
has moved to the right while the Democratic Party has adhered closer to the ideological center.
The theory suggests that a party’s ideological reputation sends messages about the type of
candidate that belongs in the party. In the contemporary political context, the increasingly
conservative and homogenous Republican Party and the more moderate and diverse Democratic
Party send distinct messages about the type of candidate that is a good fit for the party. Potential
candidates in the congressional pipeline draw on this reputation to determine whether they can
achieve their electoral and policy goals and to decide whether to run for Congress.
I test Party Fit Theory with both survey data of the perceptions of state legislators
(Maestas et al. 2006; Stone et al. 2004) and with ideology estimates of state legislators who did
and did not run for Congress from 2000 to 2010 (Bonica 2013). I find that moderate Republican
state legislators are less likely to believe they can win the primary and less likely to value a seat
in the House than conservative state legislators. Moreover, I find that moderate Republican state
legislators are less likely to run for Congress as the Republican Party becomes increasingly
conservative, and this relationship is robust to the inclusion of district-level controls. However,
moderate and liberal Democrats in the pipeline do not differ in their perceived chance of victory
or their reported value of a congressional seat, and there is no relationship between Democratic
Party liberalism and running for Congress among moderate and liberal state legislators. By
examining the origins of candidate emergence, Party Fit Theory offers a candidate entry
explanation for why the two parties have followed different ideological trajectories in Congress.
3 The Decline of Moderates in the U.S. Congress
There are two main explanations for the rise in partisan polarization in Congress. One set
of explanations highlights various changes that have occurred in the electorate. First, Southern
constituencies became less homogeneously conservative following the passage of the Voting
Rights Act, which enfranchised many African American voters who supported the Democratic
Party (Aldrich 2011; Rohde 1991). Both parties gradually lost their moderate factions, with
conservative whites in the South abandoning the Democrats and liberals in the Northeast leaving
the Republicans. Second, the electoral bases of the two parties shifted from being diverse to
more uniform (Fleisher and Bond 2004; Stonecash et al. 2003). Despite the dispute over voter
polarization (Abramowitz 2010; Abramowitz and Saunders 2008; Fiorina et al. 2006), most
agree that voters are better sorted along party lines and that they increasingly match their
partisanship with their ideological preferences (Hetherington 2001; Levendusky 2009). Third,
party activists have become increasingly extreme (Fiorina et al. 2006; Layman and Carsey 2002;
Layman et al. 2010; Theriault 2008); because activists participate in primaries, contribute money
to candidates, and spend their time working on campaigns, they have a greater impact on the
electoral process than do ordinary voters.
The other set of explanations for polarization instead highlights changes that have
occurred within Congress. Increased levels of party homogeneity have supplied the leadership
with tools to foster party discipline and advance the party’s agenda (Aldrich 2011; Aldrich and
Rohde 2001; Rohde 1991). Newly empowered party leaders have assumed greater responsibility
in allocating committee assignments, setting the legislative agenda, and structuring debate on the
floor (Cox and McCubbins 2005; Sinclair 2006). Majority party leaders draw extensively on
legislative procedure to exert their will, and the resulting polarization on procedural issues has
4 exacerbated the disparity between the two parties (Sinclair 2006; Theriault 2008). Moreover,
party leaders themselves are more extreme than the median member of the party caucus
(Grofman et al. 2002; Heberlig et al. 2006), and they may move the party’s agenda closer to their
own preferences (Cox and McCubbins 1993; Roberts and Smith 2003).
However, a handful of scholars have recently argued that the polarization literature
ignores a crucial distinction between the Republican and Democratic parties (Carmines 2011;
Hacker and Pierson 2005; Mann and Ornstein 2012; Sinclair 2006; Skocpol and Williamson
2012). They suggest that a large part of the rise in polarization in Congress can be explained by
ideological shifts on the Republican side. A comparison of the parties’ DW-NOMINATE scores
illustrates this point well (Poole and Rosenthal 2007). The scores range from -1 to 1, with higher
values indicating more conservative positions. While the median House Democrat shifted from
-0.31 to -0.37 from 1980 to 2010, the median House Republican shifted from 0.24 to 0.61 during
this time. In addition, the moderate “Blue Dog” Democrats have retained an organized presence
in Congress, whereas the Republicans have all but lost their moderate faction. Between 10 and
20 percent of Republican representatives belonged to the GOP’s right-wing caucus in the 1980s,
but nearly 70% of Republicans in the current Congress are members (Mann and Ornstein 2012).
It is less clear why the Republican Party has charged sharply to the right while the
Democratic Party has adhered closer to the center, but like the general polarization literature,
explanations for asymmetric polarization have focused primarily on changes in the Republican
base and on the heightened use of restrictive procedures by Republicans in Congress. However,
neither the polarization literature nor the emerging scholarship on asymmetric polarization can
fully explain the extent to which the parties have polarized. For one, Fiorina et al. (2006)
demonstrate that extremist voters, or at least sorted ones, can elect moderate candidates if these
5 candidates are positioned at the ideological center. Furthermore, gerrymandering and primary
election systems have been largely dismissed as culprits for the increasingly partisan Congress
(Hirano et al. 2010; McCarty et al. 2009; McGhee et al. 2011). There is ample evidence that
representatives in Congress do not simply reflect the ideological position of the median voter or
even the median partisan voter (Bafumi and Herron 2010; see also Ansolabehere et al. 2001;
Bafumi et al. 2010; Clinton 2006; Hussey and Zaller 2011), and Bafumi and Herron (2010) show
that representatives are “leapfrogging” over both voters and partisans. Replacement processes
are one of the primary forces behind the rise in partisan polarization (Fleisher and Bond 2004;
Theriault 2006) and asymmetric polarization (Bonica 2010; Carmines 2011; Skocpol and
Williamson 2012). Fundamental to our understanding of polarization, then, is how the
ideological profile of congressional candidates has changed over time, and scholars must begin
to explore how patterns of candidate emergence have contributed to partisan polarization.
Party Fit Theory: A Candidate-Level Explanation for Polarization
I develop and test a theory of Party Fit to explain why the two parties have followed
different ideological trajectories in Congress. Party Fit Theory begins with the notion that
political parties have ideological reputations. This reputation is about “what the party stands
for–and acts on–in terms of policy” (Aldrich and Freeze 2011, 186). The party’s reputation
gives meaning to its label and distinguishes it from its opponent (Grynaviski 2010; Snyder and
Ting 2002). While a party’s ideological reputation matters in clear ways for the kinds of policies
it pursues, scholars have paid less attention to how this reputation matters for the inclusion and
exclusion of potential candidates in the electoral process. Party Fit Theory argues that a party’s
ideological reputation conveys information about the type of candidate that belongs in the party.
6 Party fit as a concept is the congruence between a politician’s preferences and the
ideological reputation of her party. There are two mechanisms by which party fit affects the type
of candidate who seeks office: self-selection and party recruitment (Aldrich 2011). Potential
candidates will self-select into electoral contests if they believe they are a good fit for the party,
and those who do not will instead abstain. Similarly, party leaders will recruit candidates they
deem electorally viable and gate-keep candidates they do not (Sanbonmatsu 2006). Party Fit
Theory suggests that those who do not conform to the party’s ideological reputation are both less
likely to self-select into electoral contests and less likely to be recruited by party leaders. It is
difficult to distinguish between these two mechanisms, and indeed, they are almost certainly
mutually reinforcing. Due to the continued prominence of the candidate-centered model in
American politics (Jacobson 2004; McGhee and Pearson 2011), this paper focuses on the selfselection mechanism. However, the theory does not preclude an active role for parties, and it is
likely that recruitment also shapes perceptions of party fit. In addition, Party Fit Theory applies
to both incumbent and non-incumbent candidates, but because replacement processes are central
to the rise in polarization (Fleisher and Bond 2004; Theriault 2006), I concentrate here on nonincumbent candidates who are well situated to run for office.
Party Fit Theory suggests that potential candidates in the pipeline use the party’s
ideological reputation to assess their ability to achieve their electoral and policy goals (Fenno
1973; Mayhew 1974). First, potential candidates draw on the party’s reputation to estimate their
likelihood of winning. The party’s reputation is reflective of which types of candidates already
won their races, and potential candidates use this reputation to evaluate their own chance of
winning. Candidates of all ideological stripes pay attention to the party’s reputation, but
depending on their fit with the party, this reputation can be more or less attractive to potential
7 office-seekers. Second, potential candidates rely on the party’s ideological reputation to assess
their future policy impact and their prospective influence in the legislature (Fenno 1973).
Members experience intense pressure to support the party’s agenda, and those who defect can
expect to be punished for their actions and denied party rewards (Sinclair 2006; Theriault 2008).
Party fit influences how potential candidates perceive their potential policy impact and influence
in the legislature, and it ultimately shapes their willingness to self-select into electoral contests.
The perceived ability to achieve these electoral and policy goals has long been shown to
matter for political ambition (Black 1972; Rohde 1979; Schlesinger 1966), and Maestas et al.
(2006) find that state legislators’ perceived chance of winning and their reported value of a
House seat are two of the most important predictors of their attraction to a congressional career.
It is therefore crucial that we have a better understanding of what shapes these predictor
variables. Party Fit Theory suggests that those who conform to the party’s reputation believe
they are more likely to achieve their electoral and policy goals whereas those with preferences
that differ from this reputation believe they are less likely to achieve these goals.1
Because the party’s ideological reputation changes over time and across historical
contexts, the messages about the type of candidate that is a good fit for the party undergo similar
transformations. As I discuss below, I treat initial shifts in the party’s reputation as exogenous.
Over the past forty years, the two parties have become more internally homogeneous as well as
more polarized (e.g., McCarty et al. 2006). Ideological moderates are now a rarity in Congress,
and moderates in the congressional pipeline may believe it is more difficult for them to achieve
1
Snyder and Ting (2002) show that joining a party is less appealing to politicians whose preferences are
distant from the party platform and more appealing to those with preferences that are similar to the platform.
Like them, I also assume that these preferences are exogenous.
8 their electoral and policy goals. They may assume their candidacies are doomed from the start
(see Brady, Han, and Pope 2007), and given the current levels of party cohesion, they may find a
congressional career to be incompatible with their policy goals. In sum, moderates in the
pipeline may conclude that their ability to win the primary, impact the policymaking process, and
obtain an influential position in Congress will be limited because of their ideological preferences.
In light of the recent literature on asymmetric polarization, these patterns are expected to
be more pronounced among Republicans and less pronounced among Democrats in the pipeline.
There is ample evidence showing that the Republican Party has charged to the right over the last
thirty years, while the Democratic Party has moved slightly to the left and has remained more
ideologically dispersed (e.g., Bonica 2013; Hacker and Pierson 2005; Mann and Ornstein 2012;
McCarty et al. 2006). Party Fit Theory predicts that, in the contemporary political context, the
increasingly conservative and homogeneous Republican reputation and the moderate and diverse
Democratic reputation send distinct messages about the type of candidate that belongs in the
party.2 I suggest that moderate Republicans in the congressional pipeline are less likely to
believe they can win and less likely to value a House seat than conservative Republicans. The
Republican reputation suggests that moderates are less likely to win, and even if they win, they
2
There are many ways that potential candidates can learn about the party reputation, such as polls, the media,
and past candidates. Nevertheless, the ideological makeup of the congressional party is the best measure of
party reputation. What is important is that the party reputation provides different information than just
knowing the ideology of the district.
9 will have a limited impact in the House. The Democratic reputation, by contrast, conveys a
message that a wider range of candidates can succeed at the ballot box and in Congress.3
Recent empirical findings are consistent with the notion that incoming Republicans and
Democrats in Congress have a distinct ideological profile. Since 2000, newly elected Democrats
were more moderate than Democrats who were continuing their House careers. Carmines (2011)
notes that this pattern makes “perfect electoral sense,” because many of these new Democrats
came from swing districts where moderates have a greater chance of success. Patterns on the
Republican side, however, have not followed a similar logic. During the same period, newly
elected Republicans were more conservative than continuing House Republicans, even in swing
seats that were previously held by Democrats (Carmines 2011). The cumulative effect has been
to shift the Republican Party increasingly to the right.
Lastly, it is important to be clear about what Party Fit Theory can and cannot explain.
The theory takes party reputations as exogenous and it therefore fails to account for why the
parties polarized initially. Scholars have already highlighted the importance of ideological shifts
in both the electorate and within Congress for the emergence of polarization, and these changes
effectively moved the parties apart and clarified the party reputations for voters and potential
candidates alike. The theory does, however, provide an additional mechanism through which
3
Even when the Democratic delegation has moved to the left (in the late 1950s), it was more heterogeneous
than the Republican delegation was when it began shifting in the mid-1980s. This may be one reason why the
Democratic Party did not continue to move left. The standard deviation of the GOP delegation was 0.16 in the
99th and 100th Congresses (1985-88), compared to 0.21 for the Democrats in the 85th and 86th Congresses
(1957-60) (Poole and Rosenthal 2007).
10 polarization in Congress has been reinforced and even exacerbated. Notably, these patterns can
persist irrespective of ideological changes in the electorate.
Data and Method
I use data from the Candidate Emergence Study (Maestas et al. 2006; Stone and Maisel
2003; Stone et al. 2004), a national survey of state legislators. State legislative office is a wellknown springboard to Congress (Jacobson and Kernell 1983), and 51% of those who served in
Congress between 1999 and 2008 had prior state legislative experience (Carnes 2012). It is
therefore ideal to test Party Fit Theory on these individuals.4 The Candidate Emergence Study is
also unique in that it allows for an analysis of the perceptions of state legislators themselves (see
Maestas et al. 2006). Again, Party Fit Theory predicts that moderate Republicans in the
congressional pipeline are less likely to believe they can win the primary and less likely to value
a seat in the U.S. House than conservative Republicans. However, these patterns are expected to
be less pronounced across moderate and liberal Democrats in the congressional pipeline due to
the ideologically moderate and diverse reputation of the Democratic delegation.
I use an OLS regression to examine how party fit shapes state legislators’ perceived
chance of winning the primary and their value of a House seat. The dependent variables capture
potential candidates’ assessment of whether they can achieve their electoral and policy goals.5
4
Because this is a sample of state legislators, Party Fit here is technically congressional party fit. More
broadly, the theory refers to the party to which a candidate would belong upon election; I simply use Party Fit
in this paper to capture the general concept.
5
I follow the coding procedures used in the Maestas et al. (2006) study of political ambition. All descriptive
statistics are also provided in Supplementary Appendix A.
11 The first dependent variable is a direct measurement of state legislators’ perceived chance of
winning the primary.6 State legislators rated their chance of winning the party nomination if they
ran for Congress in the foreseeable future. Following Maestas et al. (2006), the response is
scaled as a “pseudo-probability” that ranges from 0.01 to 0.99 (extremely unlikely to extremely
likely). The second dependent variable concerns the non-electoral goals that Fenno (1973)
highlighted (prospective policy impact and influence in the House), measured as state legislators’
reported value of a seat in the U.S. House. As in Maestas et al. (2006), the value of a House seat
is measured in relative terms; state legislators rated the prestige and effectiveness of a career in
Congress and their career in the state legislature, and the difference between these scores is a
measure of the relative value of a seat in the House. Although this measurement might not
exclusively capture policy impact and influence in the chamber, it is a good proxy for potential
candidates’ expected ability to achieve their non-electoral goals.
The main independent variable of interest is the state legislator’s “fit” with her party’s
ideological reputation, referred to as policy moderate.7 The policy moderate variable was
created from respondents’ positions on four policy issues: school vouchers, environmental
regulations, affirmative action, and states’ control over domestic programs.8 Respondents are
6
I also used perceived “Chance of Winning the Primary and General Election,” but I focus on the primary
because candidates first have to obtain activist support. In addition, I also used “Attraction to a House Career”
as a dependent variable (Maestas et al. 2006), but these variables better capture the electoral and non-electoral
mechanisms that underlie political ambition.
7
This is perhaps more accurately described as “Party Deviant,” but I use “Policy Moderate” here because I am
focusing on the implications of Party Fit Theory for partisan polarization.
8
Although the results are robust to a variety of combinations of policies, these were selected for three main
reasons. First, they are addressed in both the Republican and Democratic national party platforms. Second,
12 coded as moderates if they are “indifferent,” “somewhat oppose,” “oppose,” or “strongly
oppose” the position in their party’s platform on an issue and ideologues if they favor their
party’s position on an issue (1 and 0, respectively). These values were summed across the four
policies; lower (higher) values indicate more (less) conformity with the party. Respondents’
policy positions were used because self-reported ideology proved to be a thorny measure of
political preferences. Nearly 70% of Republicans in the dataset identify as conservative or very
conservative, while only 25% of Democrats identify as liberal or very liberal. Furthermore,
almost 10% of Democrats identify as conservative or very conservative. This is not too
surprising in light of the fact that Americans voice a preference for conservatism in a symbolic
sense (Ellis and Stimson 2012), but it does complicate how we measure political ideology.9
I control for several variables used by Maestas et al. (2006) in their study of political
ambition, as the factors that shape attraction to a House career might also influence state
legislators’ perceived chance of winning the primary and their reported value of a House seat.
State legislators who have been contacted by the party and those who believe they have the
ability to raise money to fund their campaigns are expected to give higher evaluations of their
perceived chance of winning and of their value of a House seat. Respondents who are older as
results from a factor analysis suggest that the four variables load highly on the same dimension. The third and
more practical reason is that these questions had a lower number of missing observations. This is especially
important because of the split-sample design that is needed to test the theory by party. I also generated a factor
score of respondents’ positions across eight issues, and the results are similar with the composite variable.
9
I also ran the models with the respondent’s self-reported ideology (see Appendix A). However, because of
the complications of measuring ideology, I used their responses to policy questions to decide who should count
as a party outlier and who should not.
13 well as female state legislators may have more negative assessments of their chance of winning
and their value of a House seat. Not all of the controls are expected to have the same effect on
both of the dependent variables. State legislators who perceive the district partisanship to be
favorable may rate the value of the seat to be higher but assess their chance of winning to be
lower due to heightened primary competition. Conversely, those who have served more terms in
state legislative office and those in more professionalized state legislatures may report a higher
chance of winning but a lower seat value given the costs of leaving the state legislature (Maestas
et al. 2006). Lastly, because the dependent variables capture distinct goals, the models differ
slightly in terms of which controls are included. Incumbent strength and potential support from
outside groups are expected to influence state legislators’ electoral goals but not their nonelectoral goals. State legislators who face strong incumbents and those with more support from
outside groups are predicted to report lower and higher probabilities of winning, respectively.
Results
The results are presented in Table 1 below. Because the predictions of Party Fit Theory
differ for Republican and Democratic state legislators, only the partisan results will be discussed
here (see Supplementary Appendix B for the full sample). Again, the theory suggests that the
increasingly conservative and homogeneous Republican reputation and the moderate and diverse
Democratic reputation send distinct messages about the type of candidate that belongs in the
party. The Republican results are reviewed first and the Democratic results second. This section
focuses on the main independent variable of interest, the state legislator’s “fit” with her party’s
reputation, and then briefly reports the results on the control variables.
[Insert Table 1 About Here]
14 The key result in Table 1 is that moderate Republicans in the congressional pipeline
believe they are less likely to achieve their electoral and policy goals than those with more
conservative preferences.10 First, moderate Republican state legislators perceive their chance of
winning the primary to be lower, on average, than conservative Republicans.11 Importantly, the
magnitude of this effect ranks highly in comparison to the control variables, which have long
been known to be significant determinants of state legislators’ attraction to a House career. A
standard deviation increase in being ideologically moderate results in a four percentage point
decline in respondents’ expected chance of winning the primary.12 Similarly, a standard
deviation increase in party recruitment and state legislative professionalization leads to a five
percentage point rise in respondents’ perceived chance of winning, and the effect of a standard
deviation increase in the ability to raise money and gain support from outside groups is five
percentage points as well. In addition, a standard deviation increase in age results in a nine
10
The results are the same when self-reported ideology is used. Conservative Republican state legislators are
more likely to believe they can win and more likely to value a House seat (p<0.05). The relationship is
insignificant in both of the Democratic models (see Appendix A).
11
The results on the Moderate variable are the same when “Chance of Winning the Primary and General” is
the dependent variable (p<0.05 for Republicans; insignificant for Democrats). Also, for Republicans, the
relationship between Moderate and the two dependent variables is equally strong when the control variables
are omitted from the models; for Democrats, this relationship is insignificant when the controls are omitted.
12
To facilitate comparison, all non-dummy predictor variables were standardized to have a mean of zero and a
standard deviation of one.
15 percentage point decrease in state legislators’ perceived chance of winning, and shifting from an
unfavorable to a favorable partisan balance results in a decline of eight percentage points.13
Second, policy moderate is also a significant predictor of Republican state legislators’
perceived value of a congressional seat, with moderate Republican state legislators assessing the
relative value of a House seat to be lower than conservative Republicans. A standard deviation
increase in being ideologically moderate results in nearly a half-point decline in state legislators’
reported value of a congressional seat, or approximately 2.2% of the total range of the scale.
Among Democratic state legislators, the results suggest that moderates and liberals are
statistically indistinguishable in terms of their perceived chance of winning the primary and their
reported value of House seat. The coefficient for policy moderate is negative in both models, but
it fails to reach conventional levels of statistical significance. These findings lend support to the
argument that Democratic state legislators who express either moderate or liberal positions do
not differ in their perceptions of whether they can achieve their electoral and policy goals. The
results on the control variables are similar to those in the Republican models.14 Those who were
contacted by the political party and those in more professionalized state legislatures believe they
are more likely to win the primary. Also, Democratic state legislators rate their chance of victory
13
I am not able to test whether moderates self-select out of running or are gate-kept out by party leaders, but
the relationship between candidate ideology and party recruitment is not statistically significant for state
legislators in either party. This gives credibility to the candidate-centered emphasis, but I am cautious to
dismiss gate-keeping as a possibility. In terms of the model, this would lead me to underestimate the effect of
ideology as candidate ideology might have an influence on party recruitment but not vice versa, as the
ideology of most legislators does not change significantly over time (Poole and Rosenthal 2007).
14
When the sample is not split along party lines, nearly all of the control variables conform to the expectations
in the Data and Method section (see Supplementary Appendix B).
16 to be lower when the incumbent is strong, and respondents who are older as well as those who
deem their districts to be ideologically favorable again say they are less likely to win the
primary. Lastly, Democratic women, state legislators who are older, and those who have served
for longer periods in the state legislature assess the value of a House seat to be lower (p<0.10).
In sum, traditional factors such as party recruitment, past political experience, and the
ability to garner support from voters, donors, and outside groups matter in clear ways for
whether state legislators believe they can achieve their electoral and policy goals. However,
scholars have overlooked how state legislators’ ideological congruence—or lack thereof—with
their party’s policy positions may also influence candidate emergence. The findings suggest
that, at least on the Republican side, state legislators in the congressional pipeline who do not
conform to the party platform believe they are less likely to achieve their electoral and policy
goals. However, moderate and liberal Democrats in the congressional pipeline are statistically
indistinguishable in terms of their expected likelihood of winning the primary and their reported
value of a seat in the House. Party Fit Theory suggests that the Democratic Party, despite
moving slightly to the left over the past thirty years, is nevertheless inclusive of legislators who
express a wide range of policy positions.
The Implications of Party Fit Theory for Candidate Emergence
The results presented above suggest that the ideology of state legislators shapes their
perceived ability to achieve their goals, but it would also be useful to analyze the ideological
makeup of state legislators who actually run for Congress. Moreover, because the implications
of the theory vary by context, it would be ideal to explore how the makeup of congressional
candidates has changed over time. A new dataset created by Bonica (2013) allows us to examine
17 both of these issues. Specifically, the data enable a more direct test of how shifts in the parties’
ideological positions have affected potential candidates’ decision to seek congressional office.
The dataset includes ideology estimates for state legislators who ran for Congress and state
legislators who did not from 2000 to 2010.15 This is perhaps a better test of Party Fit Theory
post-polarization, as partisan polarization in Congress had already begun to crystallize by this
point.16 The parties’ mean DW-NOMINATE scores after the 1998 elections were 0.49 for
Republicans and -0.38 for Democrats. Nevertheless, the party reputations, and particularly the
Republican reputation, have changed significantly over the past decade, and we can use this
variation to test the over-time implications of Party Fit Theory.
15
The goal was to restrict the sample to “quality candidates” who do and do not run for Congress (Jacobson
and Kernell 1983). Thus, the sample includes state legislative incumbents who make their first run for
Congress and state legislative incumbents who run for the state legislature again but could have run for
Congress. The sample excludes first-time state legislative candidates who are not yet quality candidates, those
who have previously run for the state legislature and lost, as well as state legislators who seek higher state
legislative office. The sample also excludes state legislators who have previously run for Congress, as the aim
is to compare the decision to run for Congress across similarly situated state legislators.
16
Bonica’s state legislator estimates are available from 1990 to 2010, but I restrict the sample from 2000 to
2010. Because the number of state legislative candidates who filed with the FEC was significantly lower prior
to 2000, the percentage of state legislators in the sample who ran for office was unreasonably inflated. For
example, the percentage of state legislators in the sample who ran for Congress from 1990 to 1998 is 6.8%,
compared to the 2.3% of those who ran for Congress from 2000 to 2010. In their study of political ambition,
Maestas et al. (2006) note that about 1% of their sample of state legislators ran for Congress; thus, 2.3% seems
to be a closer approximation to the number of state legislators who run for Congress than 6.8%.
18 Yet, it is possible that the pool of congressional candidates with state legislative
experience varies by party. If successful Republican candidates are less likely to have previous
state legislative experience or if Republican candidates are more likely to be political amateurs,
an analysis of state legislators may be less relevant for patterns of polarization in Congress.
However, there is little evidence of such partisan differences either among the pool of successful
candidates or the full pool of congressional candidates. First, the same proportion of Democrats
and Republicans in Congress––successful candidates––has previous state legislative experience
(50.9% of Democrats and 51.5% of Republicans) (Carnes 2012). Moreover, in the full pool of
successful and unsuccessful non-incumbent candidates who ran for Congress from 2000 to 2010,
17% of Republicans and 15% of Democrats had state legislative backgrounds. Both of these
suggest that state legislators are an appropriate sample from which to assess the broader
implications of Party Fit Theory for changes in congressional polarization.
I use a logistic regression to estimate the relationship between congressional party
ideology and a state legislator’s decision to run for Congress.17 The dependent variable is coded
1 if the state legislator runs for Congress in a given year and 0 if she runs for the state legislature
again. The main independent variable of interest is party fit, which is an interaction between the
17
The Republican model has 13,239 observations. Of the pool of Republican state legislators who were well
situated for Congress in a given election year from 2000 to 2010, 367 (2.8%) ran for Congress and 12,872 did
not. The Democratic model has 15,133 observations; in this pool, 263 (1.7%) ran for Congress and 14,870 did
not. I also ran a rare event logistic regression, and the results are virtually identical. In addition, I ran both
models with state fixed effects; the results on the party fit variable remain the same, though I do not include
state fixed effects here because doing so leads to a sizeable decrease in the number of observations.
19 state legislator’s ideology and the mean ideology of her party in Congress.18 I use Bonica’s
(2013) estimates to measure state legislator ideology and Poole and Rosenthal’s (2007) DWNOMINATE scores to measure the mean ideology of the party in Congress. The interaction
term enables a more direct test of Party Fit Theory.19 Again, I hypothesize that moderate state
legislators are less likely to run for Congress as the party reputation becomes increasingly
ideologically extreme. In light of the recent literature on asymmetric polarization, I expect these
patterns to be more (less) pronounced among Republican (Democratic) state legislators.20
The model includes controls for a variety of electoral, institutional, and partisan factors.
To account for district-level electoral factors, I control for the ideology of the congressional
18
While the theory also posits a role for the ideological heterogeneity of the party delegation, the standard
deviation of the DW-NOMINATE scores of either party do not vary sufficiently during the time frame here to
include them in the model.
19
Party Fit was measured in several different ways: 1) an interaction of the state legislator’s ideology (Bonica)
and Bonica’s measure of the mean ideology of the party in Congress; 2) the difference between the state
legislator’s ideology (Bonica) and Bonica’s measure of the mean ideology of the party in Congress; 3) an
interaction of the state legislator’s ideology (Bonica) and the mean ideology of the party leadership in
Congress (DW-NOMINATE); and 4) the difference between the state legislator’s ideology (Bonica) and
Bonica’s measure of the mean ideology of the party leadership in Congress. The results are largely the same
across models (see Appendix B).
20
The distributions of state legislator ideology also lend support to this notion. The mean ideology of
Republican state legislators is more extreme than that of Democratic state legislators (-0.67 and -0.49,
respectively, with higher values indicating moderate positions [unstandardized]), and the standard deviation for
Republicans is smaller than that for Democrats (0.38 and 0.54 [unstandardized]). However, Party Fit here is
congressional party fit, so these patterns would not have to emerge for the argument to hold (particularly if
state parties have reputations that differ from the national party).
20 district that the state legislator either ran in or would have run in (Tausanovitch and Warshaw
2013) and whether there was an incumbent running for re-election in the state legislator’s
congressional district.21 I calculated the average amount of money individuals raised as state
legislators from Bonica’s data, as this likely corresponds to their ability to fund a congressional
campaign, and I also control for the number of times individuals sought state legislative office as
well as the gender of the state legislator. Lastly, state legislative professionalization is measured
with the Squire (2007) index, and I include measures of partisan control of the state legislature
(Klarner 2013) and whether the state legislature has term limits.
The results are presented in Table 2. The Republican model is discussed first and the
Democratic model second. In terms of the controls, Republican state legislators that are nested
in liberal congressional districts or in districts with incumbents seeking re-election are less likely
to run for Congress.22 Also, Republicans serving in professionalized state legislatures and in
state legislatures with term limits are more likely to run, as well as those in state legislatures with
higher levels of Democratic control. Those who raised more money as state legislators and who
have more experience running as state legislative candidates are more likely to run for Congress.
[Insert Table 2 About Here]
Of most importance is the negative coefficient on the interaction term, as Party Fit
Theory suggests that candidate emergence depends in part on the individual’s fit with the
21
I used Census data to assign state legislative districts (SLD) to their corresponding congressional district
(CD). For SLDs that fall into more than one CD, I used the CD in which their SLD comprised a larger portion
of the CD population. The incumbency data were generously provided by Gary Jacobson.
22
To ease interpretation of the interaction term, all non-dummy predictor variables were again standardized to
have a mean of zero and a standard deviation of one.
21 ideological reputation of her congressional party. As predicted, moderate Republican state
legislators are less likely to run for Congress as the GOP congressional delegation becomes
increasingly conservative. To better convey the conditional relationship between Republican
Party conservatism and state legislator ideology, Figure 1 illustrates the marginal effect of GOP
conservatism across different values of state legislator ideology. Republican Party conservatism
has a positive effect on running for Congress for Republican state legislators at the conservative
end of the ideological spectrum (near -2 on the x-axis), but a negative effect for those at the
moderate end (near +2 on the x-axis). Yet, this relationship is not statistically significant across
all state legislators, and the confidence intervals overlap zero when the legislator’s score is
between -2 and -0.7. In addition, the confidence intervals are much wider at the conservative
end of the distribution, which suggests that we can be more confident in who is less likely to run
(moderate Republicans) than who is more likely to run (conservative Republicans).
[Insert Figure 1 About Here]
We can also use the ideology scores of existing and former members of Congress to
calculate the predicted probability of running for Congress for a state legislator who shares that
ideology score. Figure 2 shows the probability of running for congressional office when a state
legislator resembles ideological moderates like Olympia Snowe (R-ME) and Steven LaTourette
(R-OH) or conservatives like Michele Bachmann (R-MN) and Paul Ryan (R-WI).23 The
probability that a moderate state legislator resembling Olympia Snowe will run for Congress
decreases from 0.6% when the Republican Party is moderate (the party mean is near -1.5) to
0.1% when the GOP delegation is conservative (the party mean is near +1.5). Similarly, the
23
The standardized ideology scores of Bachmann, Ryan, LaTourette, and Snowe are -1.71, -1.46, 0.23, and
1.12, respectively (from conservative to moderate).
22 probability that a moderate like Steven LaTourette runs for Congress decreases from 1.2% to
0.4%. It is important to note that the probability that Snowe and LaTourette run for Congress
when the GOP mean is moderate is statistically different from the probability of running when
the GOP mean is conservative (i.e., the confidence intervals at -1.5 and +1.5 do not overlap).
[Insert Figure 2 About Here]
However, when a state legislator resembles conservatives like Michele Bachmann or Paul
Ryan, the probability of running for Congress increases from 4.3% and 3.6%, respectively, when
the GOP is moderate to 5.6% and 4.1%, respectively, when the GOP is conservative. Yet, the
confidence intervals are wider for state legislators at the conservative end of the spectrum, so
although the point estimate for Bachmann and Ryan is higher when the GOP is conservative, we
cannot conclude that the probability that a state legislator who resembles Bachmann and Ryan
runs for Congress is different across Republican Party means.24 Again, these results suggest that
we are more confident in who is less likely to run than we are in who is more likely to run.
We can also see from Figure 2 that the disparity in the probability of running between
state legislators changes when the GOP is moderate (the party mean is near -1.5) and when it is
conservative (the party mean is near +1.5). For example, the difference in the probability of
running for Congress between Ryan and LaTourette is 2.4 percentage points when the GOP is
moderate, but it increases to 3.7 percentage points when the GOP is conservative. Similarly, the
difference between Snowe to Bachmann is 3.7 percentage points when the Republican delegation
is moderate, but it widens to 5.5 percentage points when the party is conservative. To be sure,
24
If we use a member of Congress who is more conservative, such as Ron Paul (R-TX), the probability is
statistically different across party means (i.e., more likely to run when the GOP mean is conservative).
Because Paul is an outlier, I used Bachmann and Ryan here.
23 conservative Republican state legislators are more likely than moderate Republicans to run for
Congress even when the Republican Party mean is comparatively moderate within the time
frame here, but it is important to remember that the GOP was, by historical standards, already
being pushed in a conservative direction by the late 1990s and early 2000s. Moreover, what is
crucial is that the disparity in the probability of running for Congress has widened between
moderate and conservative state legislators as the GOP has become increasingly conservative.
For Democratic state legislators, the situation looks quite different, although the results
on the control variables mirror those in the Republican model. Democratic state legislators that
are nested in liberal congressional districts are more likely to run for Congress, and those in
districts with incumbents running for re-election are less likely to do so. Democrats serving in
professionalized state legislatures and in state legislatures with term limits are more likely to run
for Congress, and those in state legislatures with higher levels of Democratic control are less
likely to launch a congressional bid. Democratic women are less likely to run than their male
counterparts, and Democrats who raised more money as state legislators and those with more
experience running as state legislative candidates are more likely to seek congressional office.
Importantly, the coefficient on the interaction term is not statistically significant. This
finding conforms to the predictions of Party Fit Theory as well as the literature on asymmetric
polarization. Specifically, Carmines (2011) demonstrates that the ideological distribution of
newly elected Democrats is wider than that of newly elected Republicans (see also Bonica 2010).
Because the Democratic Party has adhered closer to the center and retained more ideological
diversity, the theory predicts that moderate Democrats in the pipeline are no less likely to run for
Congress as the party becomes more liberal. Figure 3 shows the marginal effect of Democratic
Party liberalism across different values of legislator ideology. The relationship between
24 Democratic Party liberalism and running for Congress is similar for moderate and liberal state
legislators alike. We are less confident in the precision of this estimate when state legislators are
liberal, but the estimated relationship is zero across almost all values of legislator ideology.
[Insert Figure 3 About Here]
We can again use the ideology scores of Democratic members of Congress to calculate
the predicted probability of running for Congress for a state legislator who shares that ideology
score. Figure 4 shows the probability of running when a Democratic state legislator resembles
moderates like Marcy Kaptur (D-OH) and Jim Matheson (D-UT) or liberals like Nancy Pelosi
(D-CA) and Mike Capuano (D-MA).25 The probability that a moderate state legislator like
Kaptur or Matheson runs for Congress increases from 0.3% and 0.6%, respectively, when the
Democratic Party is moderate (the party mean is near -1.5) to 0.7% and 1.0%, respectively, when
the party delegation is liberal (the party mean is near +1.5). The probability that a liberal like
Capuano or Pelosi runs for Congress increases from 1.0% to 1.5% and 1.3% to 1.7%,
respectively, when the party mean shifts from moderate to liberal. To be sure, the probability
that a moderate state legislator runs for Congress is lower than the probability that a liberal state
legislator runs, but it is crucial to note, first, that both are trending in the same direction, and
second, that the disparity between moderate and liberal Democrats is very small. It appears that
ideological shifts in the Democratic Party appeal to both moderates and liberals in the pipeline.
[Insert Figure 4 About Here]
In sum, the findings suggest that the probability that moderate Republican state legislators
run for Congress decreases as the Republican delegation becomes increasingly conservative, and
25
The standardized ideology scores of Pelosi, Capuano, Matheson, and Kaptur are -0.90, -0.73, -0.23, and
0.25, respectively (from liberal to moderate).
25 importantly, this result is robust to the inclusion of electoral and institutional controls. By
comparison, the probability that Democratic state legislators run for office does not differ as the
Democratic Party becomes more liberal, perhaps because the Democratic delegation has adhered
closer to the center and has remained more ideologically diverse. Taken together, the findings
conform to the expectations of Party Fit Theory, which suggests that the ideological reputations
of the Republican and Democratic parties have important implications for the types of candidates
who are willing to run for congressional office.
Conclusion
Observers of American politics have pointed to two main explanations—changes in the
electorate and changes in Congress—to account for recent patterns of partisan polarization in
Congress. However, these explanations fail to fully explain the extent to which the parties have
polarized. Research suggests that representatives do not simply reflect the ideological position
of either the median voter or in most cases, the median partisan voter, and members of Congress
are instead “leapfrogging” over both voters and activists (Bafumi and Herron 2010). It is
therefore puzzling that candidate entry has gone largely unstudied as a cause for the persistence
of polarization and the rise in asymmetric polarization.
This paper has sought to build on the literature by offering a candidate entry explanation
for these recent patterns of polarization. Party Fit Theory suggests that the party’s reputation
sends messages about the type of candidate that belongs in the party. As the party reputation
becomes more extreme, moderates in the congressional pipeline are less likely to believe they
can achieve their electoral and policy goals and they are ultimately less likely to run for
Congress. The first analysis tested Party Fit Theory by examining perceptions of state
26 legislators, and the second analysis tested the theory by exploring ideological differences in the
types of state legislators who run for Congress. Importantly, the latter allowed for an over-time
assessment of how the probability of running is moderated by the state legislator’s ideology and
the ideology of the congressional party delegation. The results suggest that moderate Republican
state legislators are less likely to believe they can win and less likely to value a House seat than
their conservative counterparts. Also, moderate Republican state legislators are less likely to run
for Congress as the GOP becomes increasingly conservative, which offers direct support for
Party Fit Theory. Given that replacement processes are a primary driver behind heightened
levels of polarization, this finding has implications for the reinforcement of polarization and the
rise in asymmetric polarization in Congress. The abstention of moderate Republicans from the
candidate pool—and the selection of conservative Republicans into the candidate pool—suggests
that the brand of conservatism that currently characterizes the Republican Party is here to stay.
A final note is that the quality of political representation is compromised when only a
narrow ideological subset of individuals is willing to engage in electoral contests. Moreover, if
political candidates increasingly come from the poles, the ideological gulf that pervades
contemporary American politics will continue to persist. Scholars of legislative representation
and partisan polarization must turn their attention to questions of candidate emergence to
understand why some individuals seek elective office and others do not. The democratic ideal
deeply depends on, and indeed takes for granted, the existence of a vibrant and diverse pool of
candidates from which voters can choose. If the only candidates who are willing to run for office
are as extreme as the rascals in office, this has serious consequences for the representation of
those in the ideological middle—which includes the majority of the American people.
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31 Table 1: The Determinants of State Legislators’ Perceived Ability to Achieve their
Electoral and Policy Goals, By Party
Republican State Legislators
Democratic State Legislators
Chance of
Winning Primary
Policy Moderate
-0.037**
(Higher=Moderate)
(0.017)
Favorable District
-0.077**
Partisanship
(0.036)
Ability to Raise
0.050**
Money
(0.020)
Contacted by
0.053***
Political Party
(0.017)
Terms in State
-0.014
Legislative Office
(0.018)
Serves in Professional
0.053***
State Legislature
(0.018)
Incumbent Strength
-0.006
(0.018)
Support from
0.054***
Outside Groups
(0.019)
Female
0.045
(0.050)
Age
-0.091***
(0.018)
Constant
0.538***
(0.028)
Number of
Observations
258
2
R
0.32
Value of a
House Seat
-0.417**
(0.181)
-0.319
(0.374)
0.115
(0.184)
-0.005
(0.183)
-0.209
(0.191)
-0.284
(0.191)
__
Value of a
House Seat
-0.005
(0.195)
0.496
(0.384)
-0.149
(0.191)
-0.128
(0.190)
-0.347*
(0.202)
-0.194
(0.190)
__
-0.732
(0.520)
0.158
(0.192)
0.441
(0.285)
Chance of
Winning Primary
-0.012
(0.017)
-0.065**
(0.033)
0.022
(0.017)
0.055***
(0.017)
-0.010
(0.017)
0.045***
(0.016)
-0.052***
(0.016)
0.001
(0.017)
-0.055
(0.038)
-0.105***
(0.017)
0.564***
(.028)
281
0.05
292
0.28
297
0.04
__
__
-0.761*
(0.453)
0.333*
(0.199)
-1.023***
(0.321)
Source: Candidate Emergence Study (Stone and Maisel 2003; Stone et al. 2004; Maestas et al. 2006).
Note: Entries are OLS regression coefficients with standard errors in parentheses.
***=p<0.01, **=p<0.05, *=p<0.10.
32 Table 2: The Determinants of Running for Congress, By Party (2000-2010)
Republican
Democratic
State Legislators
State Legislators
Ideology of State Legislator
-1.04***
-0.97***
(Higher=Moderate)
(0.09)
(0.10)
Ideology of Party in Congress
-0.28***
0.19**
(Higher=Extreme)
(0.08)
(0.08)
Party Fit
-0.22***
0.11
(Ideology of Legislator x
(0.07)
(0.07)
Ideology of Party)
Liberal Congressional
-0.46***
0.45***
District
(0.06)
(0.10)
Incumbent Running in
-2.28***
-2.22***
Congressional District
(0.12)
(0.14)
Log of Mean Receipts
0.23***
0.23***
Raised as State Legislator
(0.07)
(0.09)
Number of Times Run for
0.32***
0.14*
State Legislature
(0.07)
(0.08)
Woman
-0.20
-0.51***
(0.16)
(0.15)
In Professionalized
0.29***
0.34***
State Legislature
(0.06)
(0.08)
In State Legislature with
0.62***
0.79***
Term Limits
(0.13)
(0.15)
Democratic Control of
0.28***
-0.18**
State Legislature
(0.06)
(0.08)
Constant
-2.45***
-2.86***
(0.11)
(0.14)
Number of Observations
13,239
15,133
Log-Likelihood
-1348.29
-1081.23
Note: Entries are logistic regression coefficients with robust standard errors clustered by individual in parentheses.
The dependent variable is coded 1 if the incumbent state legislator ran for Congress and 0 if the incumbent state
legislator instead ran for the state legislature. ***=p<0.01, **=p<0.05, *=p<0.10.
33 Figure 1: The Marginal Effect of Republican Party Conservatism on Running for
Congress, Across Different Values of Republican State Legislator Ideology (2000-2010)
Note: The marginal effect plots are constructed using estimates from Table 2.
State legislator ideology was standardized to have a mean of zero and a standard deviation of one.
Figure 2: Predicted Probability of Running for Congress for Republican State Legislators
with Ideological Profiles that Resemble Members of Congress, Across Different Levels of
Republican Party Conservatism (2000-2010)
Note: Congressional party ideology was standardized to have a mean of zero and a standard deviation of one. The
Republican Party mean has become more conservative over time; thus, -1.5 on the x-axis corresponds to the party
mean in the 106th Congress (1999-2000), and +1.5 on the x-axis corresponds to the party mean in the 111th Congress
(2009-2010).
34 Figure 3: The Marginal Effect of Democratic Party Liberalism on Running for Congress,
Across Different Values of Democratic State Legislator Ideology (2000-2010)
Note: The marginal effect plots are constructed using estimates from Table 2.
State legislator ideology was standardized to have a mean of zero and a standard deviation of one.
Figure 4: Predicted Probability of Running for Congress for Democratic State Legislators
with Ideological Profiles that Resemble Members of Congress, Across Different Levels of
Democratic Party Liberalism (2000-2010)
Note: Congressional party ideology was standardized to have a mean of zero and a standard deviation of one. The
Democratic Party mean has not become increasingly liberal over time; for example, -1.5 on the x-axis corresponds
to the party mean in the 111th Congress (2009-2010), and +1.5 on the x-axis corresponds to the party mean in the
109th Congress (2005-2006).
35 Appendix A: Alternative Specification of State Legislator Ideology (Table 1) The Determinants of State Legislators’ Perceived Ability to Achieve their Electoral and
Policy Goals, By Party (With Self-Reported Ideology)
Republican State Legislators
Democratic State Legislators
Reported Ideology
(Higher=Extreme)
Favorable District
Partisanship
Ability to Raise
Money
Contacted by
Political Party
Terms in State
Legislative Office
Serves in Professional
Legislature
Incumbent Strength
Support from
Outside Groups
Woman
Age
Constant
Number of
Observations
R2
Chance of
Winning Primary
0.037**
(0.017)
-0.066*
(0.035)
0.050***
(0.019)
0.057***
(0.017)
-0.013
(0.018)
0.051***
(0.017)
-0.008
(0.018)
0.056***
(0.019)
0.023
(0.049)
-0.102***
(0.018)
0.537***
(0.027)
Value of a
House Career
0.360**
(0.179)
-0.509
(0.368)
-0.005
(0.179)
-0.002
(0.180)
-0.131
(0.187)
-0.266
(0.184)
__
Value of a
House Career
-0.151
(0.190)
0.548
(0.361)
-0.232
(0.182)
-0.166
(0.179)
-0.272
(0.191)
-0.222
(0.180)
__
-0.653
(0.508)
0.078
(0.188)
0.546*
(0.280)
Chance of
Winning Primary
0.003
(0.017)
-0.070**
(0.032)
0.032*
(0.017)
0.063***
(0.016)
-0.009
(0.017)
0.042***
(0.016)
-0.052***
(0.016)
-0.003
(0.016)
-0.025
(0.037)
-0.105***
(0.016)
0.561***
(0.027)
266
0.32
289
0.05
319
0.28
326
0.05
__
__
-0.495
(0.426)
0.340*
(0.186)
-1.150***
(0.305)
Source: Candidate Emergence Study (Stone and Maisel 2003; Stone et al. 2004; Maestas et al. 2006).
Note: Entries are OLS regression coefficients with standard errors in parentheses.
***=p<0.01, **=p<0.05, *=p<0.10.
36 Appendix B: Alternative Specifications of Party Fit (Table 2)
The Determinants of Running for Congress, By Party (2000-2010)
(Bonica’s Measures of Congressional Party Mean)
Republicans Democrats Republicans
Ideology of State Legislator
(Bonica) (Higher=Moderate)
Mean Ideology of Party in Congress
(Bonica) (Higher=Extreme)
Party Fit I
Ideology of State Legislator x
Mean Ideology of Party in Congress
(Both are Bonica Measures)
Party Fit II
Distance Between State Legislator
and Mean Ideology of Party
(Both are Bonica Measures)
(Higher=More Distance)
Liberal Congressional District
Incumbent Running in
Congressional District
Log of Mean Receipts Raised as
State Legislator
Number of Times Sought State
Legislative Office
Woman
Serves in Professionalized State
Legislature
Serves in State Legislature with
Term Limits
Democratic Control of
State Legislature
Constant
Number of Observations
Log-Likelihood
Democrats
-1.03***
(0.09)
-0.75***
(0.22)
-0.65***
(0.22)
-0.99***
(0.11)
-0.31**
(0.14)
-0.20
(0.15)
___
___
___
___
___
___
___
___
-0.21***
(0.07)
-0.11
(0.08)
-0.46***
(0.06)
-2.28***
(0.12)
0.22***
(0.07)
0.32***
(0.07)
-0.19
(0.16)
0.29***
(0.06)
0.63***
(0.13)
0.28***
(0.06)
-2.45***
(0.11)
13,239
-1346.88
-0.45***
(0.10)
-2.21***
(0.14)
0.24***
(0.09)
0.18**
(0.08)
-0.51***
(0.15)
0.33***
(0.08)
0.80***
(0.15)
-0.19**
(0.08)
-2.87***
(0.14)
15,133
-1081.02
-0.25***
(0.07)
-2.24***
(0.11)
0.06
(0.07)
0.14**
(0.06)
-0.18
(0.15)
0.24***
(0.06)
0.56***
(0.12)
0.11*
(0.06)
-2.15***
(0.10)
13,239
-1457.03
0.17**
(0.08)
-2.19***
(0.14)
0.02
(0.09)
0.04
(0.07)
-0.17
(0.14)
0.41***
(0.09)
0.91***
(0.14)
-0.07
(0.06)
-2.69***
(0.13)
15,133
-1153.33
Source: All ideological estimates are from Bonica (2013).
Note: Entries are logistic regression coefficients with robust standard errors clustered by individual in parentheses.
The dependent variable is coded 1 if the incumbent state legislator ran for Congress and 0 if the incumbent state
legislator instead ran for the state legislature. ***=p<0.01, **=p<0.05, *=p<0.10.
37 Appendix B: Alternative Specifications of Party Fit (Table 2)
The Determinants of Running for Congress, By Party (2000-2010)
(Ideological Fit of State Legislator In Relation to Party Leadership in Congress)
Republicans Democrats Republicans Democrats
Ideology of State Legislator (Bonica)
(Higher=Moderate)
Mean Ideology of Party Leadership in
Congress (Bonica) (Higher=Extreme)
Party Fit III
Ideology of State Legislator (Bonica)
x Mean Ideology of Party Leadership
(DW-NOMINATE)
Party Fit IV
Distance Between State Legislator and
Mean Ideology of Party Leadership
(Both are Bonica Measures)
(Higher=More Distance)
Liberal Congressional
District
Incumbent Running in
Congressional District
Log of Mean Receipts Raised as State
Legislator
Number of Times Sought State
Legislative Office
Woman
Serves in Professionalized State
Legislature
Serves in State Legislature with Term
Limits
Democratic Control of
State Legislature
Constant
Number of Observations
Log-Likelihood
-1.01***
(0.08)
-0.23**
(0.09)
-0.20**
(0.08)
-1.00***
(0.11)
0.23***
(0.08)
0.13*
(0.08)
___
___
___
___
___
___
___
___
-0.15**
(0.07)
-0.19**
(0.08)
-0.46***
(0.06)
-2.28***
(0.12)
0.22***
(0.07)
0.29***
(0.07)
-0.19
(0.16)
0.29***
(0.06)
0.62***
(0.13)
0.27***
(0.06)
-2.43***
(0.11)
13,239
-1351.59
0.44***
(0.10)
-2.19***
(0.14)
0.24***
(0.09)
0.18**
(0.08)
-0.51***
(0.15)
0.33***
(0.08)
0.81***
(0.15)
-0.20***
(0.08)
-2.91***
(0.14)
15,133
-1079.63
-0.23***
(0.07)
-2.25***
(0.11)
0.06
(0.07)
0.13**
(0.06)
-0.18
(0.15)
0.24***
(0.06)
0.57***
(0.12)
0.10*
(0.06)
-2.14***
(0.10)
13,239
-1459.58
0.20**
(0.08)
-2.19***
(0.14)
0.02
(0.09)
0.04
(0.07)
-0.18
(0.14)
0.40***
(0.09)
0.91***
(0.14)
-0.07
(0.06)
-2.70***
(0.13)
15,133
-1151.16
Source: State legislator estimates from Bonica (2013). DW-NOMINATE scores from Poole and Rosenthal (2007).
Note: Entries are logistic regression coefficients with robust standard errors clustered by individual in parentheses.
The dependent variable is coded 1 if the incumbent state legislator ran for Congress and 0 if the incumbent state
legislator instead ran for the state legislature. ***=p<0.01, **=p<0.05, *=p<0.10.
38 Supplementary Appendix A: Summary Statistics (Republican State Legislators)
Mean
Median
SD
Range
Table 1
DV: Chance of Winning
DV: Value of House Seat
Policy Moderate
District Partisanship
Raise Money
Contacted by Party
Terms in State Legislature
Professional Legislature
Incumbent Strength
Support from Groups
Female
Age
0.50
0.16
0.74
0.59
5.09
0.21
2.41
2.69
5.81
5.19
0.13
3.91
0.50
0
1
1
5
0
2
3
6
5
0
4
0.31
3.03
0.83
0.49
1.29
0.61
1.04
1.38
1.14
1.29
0.34
1.32
[0.01, 0.99]
[-10, 9]
[0, 4]
[0, 1]
[1, 7]
[0, 4]
[1, 4]
[1, 5]
[1, 7]
[1, 7]
[0, 1]
[1, 6]
Table 2
DV: Run for Congress
State Legislator Ideology
Party Ideology
Party Fit Interaction
Liberal Congressional District
Incumbent Running in District
Receipts Raised as State Legislator
Times Run for State Legislature
Woman
In Professionalized State Legislature
In State Legislature with Term Limits
Democratic Control of State Legislature
0.03
-0.67
0.56
-0.38
0.11
0.88
10.83
3.63
0.17
0.19
0.25
0.42
0
-0.73
0.56
-0.40
0.15
1
10.82
3
0
0.17
0
0.38
0.16
0.38
0.04
0.22
0.20
0.32
1.22
1.57
0.37
0.11
0.43
0.41
[0, 1]
[-1.94, 1.75]
[0.48, 0.62]
[-1.12, 1.09]
[-0.85, 0.49]
[0, 1]
[6.45, 15.04]
[2, 10]
[0, 1]
[0.03, 0.63]
[0, 1]
[0, 1]
Note: In all of the models, all non-dummy predictor variables were standardized to have a mean of zero
and a standard deviation of one.
39 Supplementary Appendix A: Summary Statistics (Democratic State Legislators)
Mean
Median
SD
Range
Table 1
DV: Chance of Winning
DV: Value of House Seat
Policy Moderate
District Partisanship
Raise Money
Contacted by Party
Terms in State Legislature
Professional Legislature
Incumbent Strength
Support from Groups
Female
Age
0.51
-0.91
1.38
0.64
4.91
0.31
2.55
2.65
5.63
5.18
0.27
3.70
0.50
-1
1
1
5
0
3
2
6
5
0
4
0.31
3.18
1.18
0.48
1.36
0.73
1.16
1.33
1.32
1.35
0.45
1.21
[0.01, 0.99]
[-12, 9]
[0, 4]
[0, 1]
[1, 7]
[0, 4]
[1, 4]
[1, 5]
[1, 7]
[1, 7]
[0, 1]
[1, 6]
Table 2
DV: Run for Congress
State Legislator Ideology
Party Ideology
Party Fit Interaction
Liberal Congressional District
Incumbent Running in District
Receipts Raised as State Legislator
Times Run for State Legislature
Woman
In Professionalized State Legislature
In State Legislature with Term Limits
Democratic Control of State Legislature
0.02
-0.49
0.38
-0.19
-0.09
0.90
10.83
3.76
0.28
0.21
0.20
0.62
0
-0.57
0.38
-0.22
-0.09
1
10.81
3
0
0.19
0
0.75
0.13
0.54
0.01
0.21
0.29
0.29
1.18
1.66
0.45
0.12
0.40
0.40
[0, 1]
[-1.99, 1.29]
[0.36, 0.40]
[-0.76, 0.49]
[-1.09, 0.49]
[0, 1]
[5.59, 15.45]
[2, 11]
[0, 1]
[0.03, 0.63]
[0, 1]
[0, 1]
Note: In all of the models, all non-dummy predictor variables were standardized to have a mean of zero
and a standard deviation of one.
40 Supplementary Appendix B: Full Sample of State Legislators (Table 1)
The Determinants of State Legislators’ Perceived Ability to Achieve their Electoral and
Policy Goals, Full Sample (With Policy Positions and Self-Reported Ideology)
All State Legislators
All State Legislators
Policy Moderate
(Higher=Moderate)
Reported Ideology
(Higher=Extreme)
Favorable District
Partisanship
Ability to Raise
Money
Contacted by
Political Party
Terms in State
Legislative Office
Serves in Professional
Legislature
Incumbent Strength
Support from
Outside Groups
Woman
Age
Constant
Number of
Observations
R2
Chance of
Winning Primary
-0.019
(0.012)
__ Value of a
House Career
-0.317**
(0.131)
__
Chance of
Winning Primary
Value of a
House Career
0.291**
(0.127)
0.032
(0.258)
-0.042
(0.127)
-0.085
(0.128)
-0.268**
(0.134)
-0.227*
(0.129)
__
-1.011***
(0.326)
0.300**
(0.137)
-0.221
(0.213)
0.013
(0.011)
-0.062***
(0.024)
0.045***
(0.012)
0.059***
(0.012)
-0.011
(0.012)
0.045***
(0.012)
-0.034***
(0.012)
0.022*
(0.012)
-0.015
(0.028)
-0.105***
(0.012)
0.547***
(0.019)
-0.068***
(0.024)
0.039***
(0.013)
0.053***
(0.012)
-0.011
(0.012)
0.049***
(0.012)
-0.032***
(0.012)
0.025**
(0.013)
-0.026
(0.029)
-0.101***
(0.012)
0.550***
(0.020)
0.060
(0.268)
0.032
(0.132)
-0.084
(0.132)
-0.346**
(0.139)
-0.225*
(0.135)
__
-0.921***
(0.307)
0.280**
(0.132)
-0.241
(0.206)
550
0.27
578
0.05
585
0.27
615
0.05
__
__
Source: Candidate Emergence Study (Stone and Maisel 2003; Stone et al. 2004; Maestas et al. 2006).
Note: Entries are OLS regression coefficients with standard errors in parentheses.
***=p<0.01, **=p<0.05, *=p<0.10.
41