Electoral Accountability for State Legislative
Roll-Calls and Ideological Representation
DRAFT
Steven Rogers∗
Department of Politics
Princeton University
July 17, 2013
Abstract
Theories of electoral accountability expect that legislators will receive fewer votes if
they fail to represent their district’s preferences. To determine whether this prediction applies to state legislatures, I conduct two analyses that evaluate the extent to
which voters sanction legislators who cast unpopular roll-call votes or provide poor
ideological representation. Together, these studies offer the most empirically thorough
examination of state legislators’ electoral incentives to represent their districts. Neither
analysis, however, produces compelling evidence of electoral accountability. Across 10
states, I find that voters reward or punish state representatives for 4 of 23 examined rollcalls, and only 9 of 38 states provide evidence that legislators pay an electoral price for
ideologically extreme representation. Weak electoral connections combined with safe
state legislative seats make it difficult to throw “out of step” legislators “out of office.”
Thus, while state legislators wield considerable policy-making power, elections do not
appear to hold most state representatives accountable for their lawmaking.
∗
Ph.D. Candidate in the Department of Politics, Princeton University; [email protected]. I thank
Nolan McCarty, Larry Bartels, Josh Clinton, and Brandice Canes-Wrone for their guidance regarding this
project. For helpful conversations, data assistance, and other support, I am additionally grateful to Michelle
Anderson, Adam Bonica, Michael Davies, Carl Klarner, Peter Koppstein, the Center for Congressional and
Presidential Studies, the National Committee for an Effective Congress, and numerous individuals from
Secretaries’ of States offices or local boards of elections.
1
A central concern of democratic theory is ensuring policymakers represent their constituents, and theories of electoral accountability predict that competition for votes pressures
legislators to adopt policies consistent with their districts’ preferences (e.g. Downs 1957).
The “electoral connection” underlies canonical explanations of representative government
(e.g. Mayhew 1974), but American legislators do not always adopt popular policies. Republicans in state houses have restricted collective bargaining agreements, and Democrats have
tried to redefine the institution of marriage, resulting in voters recalling state legislators and
amending state constitutions across the country.
Legislative parties often pressure their members to pass controversial pieces of legislation, but recognizing the dyadic nature of their representative duties, state legislators
sometimes break the party line. For example when the Maine state legislature legalized
same-sex marriage, Democratic Representative Lajoie voted with his district - where 73% of
voters opposed the legislation - instead of with his party. The bill passed, but Lajoie’s nay
vote put him in the minority in more ways than one. Unlike Lajoie, a majority of Maine state
house members voted against their district’s majority opinion. Electoral connections intend
to prevent this type of unrepresentative behavior, but seemingly counter to the predictions of
theories of electoral accountability, most Maine legislators who voted against their districts
were reelected.
The electoral success of Maine legislators who cast unrepresentative votes highlights
the question of whether state legislative districts hold their representatives accountable for
their individual behavior. Political scientists, however, know little regarding district-level
electoral connections in the states. Studies of American elections overwhelming focus on the
electoral ramifications of congressional representation (e.g. Canes-Wrone et. al 2002; Carson
et. al 2010, Jacobson 1993) despite the considerable amount of lawmaking conducted at the
state level. State legislatures pass 75 times as many laws as Congress, but the most extensive
studies of the electoral implications of individual state legislator’s behavior only examine two
2
elections in less than a third of states (Hogan 2004; 2008).1 This work tells us the most we
know about district-level accountability in state legislatures, but limited data availability
has prevented political scientists from conducting more thorough examinations.
To better evaluate electoral connections in state legislatures, I assemble the largest
cross-state collection of measures of legislators’ and voters’ preferences and behavior at the
state legislative district-level. With these data, I evaluate the electoral consequences legislators face for casting unpopular roll-call votes and the extent to which ideologically extreme
legislators receive lower vote shares over the past decade. Neither analysis, however, provides compelling evidence of accountability in state legislatures. Across ten states, I find
that voters reward or punish legislators for 4 of 23 examined roll-calls, and only 9 of 38 states
produce statistically significant evidence that legislators pay an electoral price for ideologically extreme representation. Weak electoral connections combined with safe state legislative
seats make it difficult to throw “out of step” legislators “out of office.” My findings provide
little support for the assumptions that underlie median voter theories and more importantly
cast doubt on the proposition that elections hold state legislators accountable for how they
represent their districts.
Holding “Out of Step” Legislators Accountable
American legislatures similar to many representative governments frequently face a
principal-agent dilemma. Once in office, little constrains elected officials’ behavior, which
introduces the risk of undesirable policymaking. The ballot box offers a potential solution
to this moral hazard problem. Theories of electoral accountability suggest that competition
for votes can motivate elected officials to represent their constituents (Downs 1957; Ferejohn
1986; see Grofman 2004 for a review), but for elections to be effective means of accountability,
1
Serra and Pinney (2004) examine the relationship between legislator casework and election returns, and
in unpublished work, Birkhead (2013) studies the relationship between legislator extremity and vote-share
in the 2000 election.
3
Figure 1: U.S. and State House Representation
U.S. and state house member ideal plotted points against 2004 presidential vote for Bush. Both
at the federal and state levels, legislators often provide substantially different types of ideological
representation despite coming from constituencies with comparable political preferences. Ideal points
across state legislatures made comparable using NPAT estimates of legislator ideology (Shor and
McCarty 2011).
these theories require a relationship between legislators’ behavior and their probability of
reelection. Through the “electoral connection,” voters can pressure their representatives to
act in their interests.
While an intent of elections is to create incentives for those in government to represent
their constituents, legislators face more than electoral pressures. Party obligations, interest
groups, and personal policy positions also weigh upon legislators’ decision-making (Fenno
1978; Kingdon 1989; Hall and Wayman 1990). These cross-pressures are partly responsible
for the findings that legislators do not always appear to represent the median voter (e.g.
Miller and Stokes 1963; Shaprio et. al 1990; Bafumi and Herron 2010). The top left panel
4
of Figure 1 illustrates an example of ideological incongruence between voters and their representatives in the U.S. House. Using ideal point estimates from 2004, the top left panel
shows conservative members of Congress generally represent districts that supported Bush,
but many ideologically dissimilar members represent constituencies with similar political
opinions. This pattern suggests that at least some federal legislators are “out of step” with
their districts.
When studying the U.S. House, political scientists repeatedly find that “out of step”
legislators face electoral ramifications for their unrepresentative behavior. Voters sanction
their member of Congress for unpopular roll-call votes concerning the budget, congressional
salaries, or health care (Jacobson 1993; Clark 1996; Ansolabehere and Jones 2010; Nyhan
et al. 2012), and there is evidence that ideologically extreme members receive lower vote
shares (Canes-Wrone, Brady, and Cogan 2002; Carson et al. 2010; Ladewig 2010). These
empirical findings support the proposition that district-level electoral connections exist in
the U.S. House and provide evidence that assumptions of median voter theorems apply to
Congress.
Similar to the patterns illustrated by the top left panel of Figure 1, the other panels of
this figure suggest that there are also many state legislators who are “out of step” with their
districts. For nearly every Republican state legislator in Maine, Michigan, and Kentucky,
there is a Democrat from a district with comparable favorability towards Bush.2 Given the
aforementioned empirical findings concerning U.S. House elections, one may expect state
legislators to face electoral consequences for their representative behavior similar to their
congressional counterparts. Key differences in the informational and institutional contexts
surrounding state legislative contests, however, make it relatively more difficult for voters to
hold their state legislator accountable.
2
This could reflect presidential vote being a poor proxy for state-level ideology, but similar patterns occur
in Pennsylvania, whose state party ideology resembles the federal parties (Shor and McCarty 2011).
5
Voters, for example, need to be informed of their representative’s actions in order to effectively hold him or her accountable. Delli Carpini, Keeter, and Kennamer (1994) show that
greater media attention is one way to create informed state legislative electorates, and when
voters pay attention, they appear to learn more about their state legislature. Tennesseans
who reported to “closely follow the news about their state legislature and governor” were
twice as likely to know who their state legislator was and a third more likely to have heard
of state-level legislation regarding voter identification requirements or teaching evolution in
schools (Vanderbilt Poll: May 2012). These types of voters, however, are relatively rare (14%
of sample). Few voters following state political news is partially attributable to down-ballot
elections being overshadowed by federal contests in the media. State legislative elections, for
example, receive less than a fourth of the amount of local news coverage of Congressional
elections (Kaplan, Goldstein, and Hale 2003; 2005; see also Gierzynski and Breaux 1996),
making it relatively difficult for voters to become informed about state legislative affairs
before the election.
While watching the local news may not be sufficient for voters to learn about their state
legislator, they can become informed by other political elites. Parties and their candidates,
for example, can draw attention to incumbents’ unrepresentative legislative behavior and
help voters hold their state representative accountable. Challengers to incumbents, however,
are also scarce in state legislative elections. Rarely do more than 60% of sitting state house
members face a major party opponent (Squire 2000; Rogers 2013), letting the burden of
“sift[ing] through incumbents records” increasingly fall to the individual voter (Arnold 1992:
49). With few major party challengers and little media coverage, it becomes relatively costly
for voters to learn about their state legislator compared to their member of Congress. If one
believes that “the acquisition of any nonfree political information data whatever is irrational”
for most voters (Downs 1957: 239), it is reasonable that most voters know little about their
state legislature (Jewell 1982).
6
Figure 2: Swing Seats in U.S. and State Houses
The above shows the proportion of state legislative seats where George W. Bush’s vote share in the
2004 election was below 45%, above 55%, or between 45% and 55%. Across the country, 10% fewer
state legislative seats fall into this latter category compared to U.S. House districts.
Even if some voters identify and cast ballots against unrepresentative state legislators,
partisan state legislative districts make it difficult to throw an unrepresentative legislator
out of office. Figure 2 presents the proportion of state legislative “swing” districts where
President Bush received between 45 and 55 percent of the vote in the 2004 election. Only
eight states have a higher percentage of swing districts than the U.S. House, and there are
some states, such as Rhode Island, with no legislative districts where Bush received more than
55% of the vote. Partisan districts contribute to state legislators enjoying healthy electoral
margins and often no opposition. Figure 3 illustrates that from 1998 - 2008, approximately
80% of American legislators received at least 60% of the vote, and only 10% received less
than 55% of the vote. A small number of incumbent legislators, therefore, appear to be
electorally vulnerable.
The lack of attention the media and political elites give to state legislative elections
makes it hard for voters to identify out of step state legislators, and partisan districts increase the difficulty of throwing them out of office. Both of these factors are important for
7
Figure 3: Incumbent Vote Shares in U.S. and State House Elections
The bars of the graph illustrate the proportion of US and state house incumbents that sought reelection who received different levels of vote share. Data cover the 1998 - 2008 elections. Approximately
80% of legislators receive at least 60% of the vote each election.
accountability because if voters do not respond to how they have been represented by their
state legislator enough to threaten an incumbent’s job security, state representatives have
less electoral incentive to represent their constituents. To determine whether this critical
relationship for political accountability emerges in state legislatures, I conduct two analyses
concerning the electoral implications of legislators’ roll-call behavior. I first take advantage
of referendum election results to generate district-level measures of public opinion on 23 bills
enacted by state legislatures. With these measures of public opinion, I examine the electoral
consequences for legislators casting unpopular roll-call votes. Second, I study the electoral
implications of a state legislator’s full roll-call record. For this analysis, I use ideal point estimates of state legislators’ ideology from 1998 - 2008 to evaluate the extent to which voters’
provide electoral incentives for ideological representation in 38 states. Theories of electoral
8
accountability expect that legislators will receive fewer votes if they fail to represent their
district’s preferences, all else equal, and my analyses test the hypotheses that state house
members who cast unpopular roll-call votes or are ideologically extreme relative to their
districts will receive lower vote shares.
Accountability for Unpopular Roll-Call Votes
State legislatures do not always adopt popular policies, and when this is the case, voters
in 21 states can force a “veto-referendum” to have a statewide election determine whether a
bill adopted by the legislature will become law. Political scientists have used referenda and
initiatives to study whether state legislators vote consistently with their districts’ preferences
(e.g. Gerber 1996; Snyder 1996; Lewis and Gerber 2004), but I do not know of any research
that uses referenda to determine the extent to which voters hold legislators accountable for
their unpopular roll-call decisions. Because referenda election returns reflect district opinion
on the exact bills considered by the state legislature, they provide an excellent opportunity
to study the relationship between legislator and voter behavior.
In the last 15 years, 14 states have held veto-referenda. Veto-referenda can repeal
bills considered by the legislature but only occur for adopted legislation, which introduces
potential case selection bias in this study. I aim to include the universe of referenda but
focus on the 10 states that make precinct-level referendum election returns readily available,
which restricts my current analysis to 23 bills.3 Table 1 provides brief descriptions of the
considered bills and reports their levels of support in the state house and electorate. Voters
vetoed 11 of the 23 bills, and in doing so overturned state legislatures’ decisions to legalize
gay marriage, expand health care, and create charter schools.
3
For example, I do not study multiple Oregon veto-referendum since this state only provides county-level
referendum election returns. Excluded states are MA, OR, SD, and UT.
9
Table 1: Referendum Descriptions
SB 267
State
House
Vote
27-11
Statewide
Referendum
Result
53.5-46.5
HB 2518
32-24
36.1-63.9
98,174
SB 1373
51-7
53.5-46.5
98,174
Require medium to large business to provide health care coverage
SB 2
46-32
49.2-50.8
Prop 94
Permits 5500 additional slot machines at certain Native American Casinos
SB 903
61-9
55.6-44.4
2008
Prop 95
Permits 5500 additional slot machines at certain Native American Casinos
SB 174
50-13
55.6-44.4
CA
2008
Prop 96
Permits 3000 additional slot machines at certain Native American Casinos
SB 175
61-9
55.5-44.5
CA
2008
Prop 97
SB 957
52-11
55.5-44.5
ID
2012
Prop 1
S1108
48-22
42.7-57.1
47,432
ID
2012
Prop 2
S1110
44-26
42-58
47,432
ID
2012
Prop 3
S1184
44-26
33.3-66.7
47,432
ME
2005
Question 1
LS 1196
91-58
55-45
$1,554,715
49,458
ME
2008
Question 1
Permits 3000 additional slot machines at certain Native American Casinos
Limits agreements btwn. teachers and school boards and ends
issuing renewable contracts
Establishes teacher pay for performance based on test scores
Increase technology spending in
schools, with ability to offset
costs using teacher salaries
Prevent
discrimination
in
employment, housing, education...based on their sexual
orientation
Soda Tax to pay for Health Care
Program
LD 2247
82-62
35.4-64.6
$4,612,389
55,087
ME
2009
Question 1
Gay Marriage
LD 1020
89-57
47.2-52.8
MI
MI
2006
2012
Prop 3
Prop 1
PA 160
PA 4
65-40
62-48
MI
MT
2002
2012
Prop 1
IR-124
PA 269
SB 423
ND
2012
Measure 4
Authorizes Dove Hunting Season
Authorizes Governor to establish city manager upon state
finding financial emergency
Eliminates Straight Party Ticket
Enact a Medical Marijuana Program
Discontinue University of North
Dakota Fighting Sioux nickname
and logo
OH
2008
Issue 5
WA
2009
Ref. 71
WA
2004
Ref. 55
WA
2007
Ref. 67
State
Year
Referendum
Issue Description
Bill
AK
2000
Measure 6
AZ
1998
Prop 300
AZ
1998
Prop 301
Restrict Land and Shoot Hunting of Wolves
Federal Oversight of Medical
Marijuana
Eligible for Probation with 1st
or 2nd Marijuana Crime
CA
2004
Prop 72
CA
2008
CA
Limit interest rates on short
term loans to 28%
Grants domestic partners all
rights, responsibilities, and obligations granted to married couples
Authorizes creation of Charter
Schools
Allows consumers to collect trip
damages from their insurance
company
10
Spending
Min.
on
Signatures
Referendum Required
19,242
$31,075,168
$172,698,243
$172,698,243
$172,698,243
$172,698,243
354,817
411,345
411,345
411,345
411,345
55,087
31-69
47-53
$10,495,539
$3,003,704
$9,165,638
159,000
161,304
56-47
78-17
40.3-59.7
57.2-42.8
$38,071
151,328
24,337
SB 2370
63-31
67.3-32.7
$19,499
13,452
HB 545
68-27
63.7-36.3
SB 5688
62-35
53.2-47.8
$4,849,167
120,115
ESSHB2295
51-46
41.7-58.3
$9,228,262
96,881
SB 5726
59-38
56.7-43.3
$21,416,231
$19,216,157
241,365
109,864
Veto-referenda range in prominence and attention received. For instance the Michigan
Chamber of Commerce alone spent more money supporting emergency manager reform than
was spent overall on an earlier referendum regarding Michiganders’ hunting rights. With
enough interest group activity and spending, voters become aware of seemingly obscure
issues. Over $100 million spent by California interest groups on referenda regarding slot
machines in Native American casinos contributed to increasing statewide voter awareness of
the issue by 43% in the course of a month (Field Poll: Jan 2008). Interest groups spent at
least $4 million campaigning for or against most of the referenda considered in this analysis.4
Given voters appear to be “educated by the initiative” (Smith and Tolbert 2004), employing
a sample of veto-referenda increases the likelihood of voter awareness of legislators’ positions
compared to employing most other legislation.
Using election returns from these referenda and legislators’ roll-calls, I estimate the extent to which a district’s support for a state legislator’s position correlates with a contested
state house incumbent’s vote share (Klarner et. al 2012) using Ordinary Least Square regressions. To measure district-level opinion of legislators’ positions, I aggregate precinct-level
referendum election returns to the state legislative district-level. For each district, I adjust
this variable - ranging from 0 to 100 - such that higher values indicate greater support for
their state representative’s roll-call vote. Among those who sought reelection and faced a
major party opponent within this study, state house members cast 747 (of 1220) roll-calls
that represented their district’s majority opinion. If voters electorally reward legislators for
taking positions their district favors, β1 in Equation 1 should be positive.
4
These figures reflect the available National Institute for Money in State Politics tabulations of spending
on referendum since 2004.
11
IncumbentV oteShare =β0 + β1 [Supportf orIncumbent0 sRollCall]
+ β2 [IncumbentP artyP residentialV ote]
+ β3 [IncumbentSpendingAdvantage]
+ β4 [IncumbentP reviousV oteShare]
+ β5 [IncumbentP reviouslyContested]
+ β6 [DemocraticDummy] + (1)
OLS regressions include controls common to studies of elections. To account for a
constituency’s partisanship, I control for presidential vote at the legislative district-level
averaged by redistricting cycle.5 Statistical analyses additionally account for incumbents’
fundraising advantages using the difference in logged campaign contributions between the
incumbent and challenger (Bonica 2013; NIMSP). Other controls include an incumbent’s
partisanship, previous vote share, and whether the state representative was contested in the
previous election. Table A-1 in the Appendix provides summary statistics of each of the
variables used in this and subsequent analyses.
To provide legislators greater electoral incentive to represent their constituents, electorates need to punish those in government for making unpopular roll-call decisions, but
statistical analyses provide little evidence that this is the case for most roll-calls considered
here. The fourth column of Table 2 presents central results from separate OLS estimations
for each piece of legislation that faced a veto-referendum. For 19 of 23 bills, there is no statistically significant relationship between voters’ and legislators’ behavior (p ≥ .1). Voters
do not seem to sanction individual legislators for taking unpopular positions on important
legislation regarding payday loans, charter schools, or drug laws.6
5
I collected Gore-Bush vote by pre-2000 legislative district for 45 states and Obama-Romney vote for
MI, MT, and ND. The National Committee for an Effective Congress generously provide 2004 and 2008
presidential vote by post-2000 legislative district for 48 states, and Tausanovitch and Warshaw (2013) supply
Obama-McCain vote for FL and MS. Gore-Bush vote is missing for AR, CO, and MS, and Kerry-Bush vote
is missing for FL and MS due to an inability to collect precinct election returns by state legislative district.
Polidata provide the presidential vote measure for Congressional elections.
6
It should be noted that the only statistically significant results are from elections with the most observations, and null findings may be the result of underpowered tests. The magnitudes of coefficients, furthermore,
12
Table 2: Relationships between District-Level Support of Legislator’s
Roll-Calls and Incumbent Vote Share
State
AK
AZ
AZ
CA
CA
CA
CA
CA
ID
ID
ID
ME
ME
ME
MI
MI
MI
MT
ND
OH
WA
WA
WA
Year of Ref.
2000
1998
1998
2004
2008
2008
2008
2008
2012
2012
2012
2005
2008
2009
2002
2006
2012
2012
2012
2008
2004
2008
2009
Issue Area
Hunting
Medical Marijuana
Marijuana Sentencing
Health Care
Slot Machines
Slot Machines
Slot Machines
Slot Machines
Collective Bargaining
Teacher Pay
Education Spending
Gay Rights
Soda Tax
Gay Marriage
Straight Party Ticket
Dove Hunting
Emergency Managers
Medical Marijuana
Native American Mascot
Payday Loans
Charter Schools
Insurance Claims
Gay Rights
∗∗ p
Coef. District Support of Roll Call
0.167 (0.311)
-0.118 (0.245)
0.076 (0.186)
0.188 (0.138)
0.029 (0.113)
0.085 (0.110)
0.038 (0.113)
0.072 (0.107)
0.333 (0.204)
0.159 (0.143)
-0.003 (0.078)
0.146* (0.081)
0.000 (0.063)
0.101** (0.046)
0.051 (0.208)
0.101** (0.046)
0.087** (0.043)
-0.023 (0.130)
-0.039 (0.022)
-0.112 (0.111)
0.028 (0.048)
0.023 (0.119)
0.103 (0.091)
N
16
26
25
51
40
36
40
36
28
28
28
103
86
104
51
104
84
51
24
47
63
62
62
R-Squared
0.79
0.64
0.67
0.89
0.94
0.93
0.94
0.93
0.83
0.82
0.81
0.44
0.53
0.64
0.86
0.64
0.95
0.69
0.93
0.71
0.91
0.79
0.83
≤ .05; ∗ p ≤ .10 Standard Errors in Parentheses
Relationship between district public opinion for incumbent’s roll-call vote and incumbent vote share.
“Coef. District Support of Roll-Call” is the OLS coefficient and standard error for β1 of Equation
1. Positive coefficients indicate voters reward or punish legislators for their roll-call position, which
appears to be the case for 4 of 23 bills examined. See Tables A-2 to A-7 for full estimates.
Findings from Table 2 do reveal some evidence of district-level electoral connections
in the Maine and Michigan state legislatures. Returning to the example of gay marriage
in Maine from the beginning of this paper, statistical analyses suggest that a state house
incumbent’s reelection vote share would increase by 1% with a 10% increase in district-level
support for their roll-call position. Providing further evidence of a relationship between legislator and voter behavior, a 10% increase in support for a legislator’s roll-call concerning
GLBT discrimination in 2006 results in approximately a 1.5% increase in vote share for the
incumbent. These statistical results suggest that Representative Lajoie electorally benefitted from his vote on gay marriage but most of his colleagues lost votes. The strength of
are larger for positions legislators took on issues recently prominent in state legislatures, such as health care,
gay rights, and collective bargaining.
13
electoral connections, however, varies by issue. Maine voters appear to hold their legislators
accountable for their positions on gay rights but not for enacting an unpopular soda tax to
pay for health care programs.
Michigan voters also at times seem to hold their legislators accountable. In 2012, a
veto-referendum overturned a party-line vote by the Republican legislature that enabled the
governor to appoint emergency managers in financially-struggling local governments. Some
legislators paid a price for toeing the party line. Using estimates from Table 2, a 10% decrease
in support for a Michigan state house member’s roll call resulted in approximately a 0.9%
loss in incumbent vote share. Analyses additionally suggest that Michiganders punished
their legislators for their position taking on dove hunting but fail to provide evidence that
they held their representatives accountable for changes to electoral laws, such as eliminating
the straight party ticket.
Findings from Maine and Michigan provide some evidence that electoral connections
exist in these states, but the relationships between legislator and voter behavior likely are
not strong enough to affect most legislators’ job security. As shown by Figure 3, voters
reelect most state legislators with considerable electoral margins, reducing the meaningful
electoral impact of an unpopular roll-call. For example if every Maine state house member
voted with the majority of their district on gay marriage, statistical analyses predict that
only two additional incumbents would have held onto their seats, and likewise even if every
incumbent voted against their district, only two additional incumbents would have lost.
Similarly if every Michigan state house member either voted with or against their district
on emergency manager reform, statistical analyses predict that only one seat outcome would
change. The potential vote share losses attributable to a state representative’s roll-call on
these pieces of legislation, therefore, do not appear to threaten most incumbents’ reelection.
14
Accountability for Ideological Representation
The above findings suggest that few legislators would lose votes for unpopular rollcalls and fewer would lose their jobs for providing poor representation. Considering a single
roll-call, however, may be too narrow a test of Downsian predictions. State legislators take
hundreds of positions each legislative session. For example the 124th Maine legislature both
legalized gay marriage and cut education spending, and Michigan representatives created
emergency managers and tried to establish stricter voter ID laws from 2011 to 2012. Each
position taken by state legislators on these issues reflects their ideological representation
of their constituents, and spatial theories of electoral competition fundamentally expect
legislators to receive lower vote shares if they fail to represent their district on a broad
ideological dimension, all else equal.
To study whether voters hold their state representatives accountable for their overall legislative record, I investigate the electoral implications for how state representatives
ideologically represent their district. For this analysis, I compile district-level measures of
legislative behavior, constituent ideology, and election outcomes from the 38 states that exclusively had single-member districts in the 1998 - 2008 elections. The dependent variable
is a contested state house member’s two-party vote share, and the primary independent
variable of interest is a measure of a legislator’s ideological representation.
To test the claim that “ideological moderation should increase an incumbent’s vote
share” (Canes-Wrone et. al 2002: 129), prior work on Congress often measures legislators’
ideological extremity by taking “the absolute value of [DW-NOMINATE] scores so that high
values...indicate that a member has an “extreme” voting record” (Carson et. al 2010: 606).7
Using this absolute value approach, however, presumes an ideal point of zero to be moderate
7
Carson et. al argue “voters place greater weight on partisanship than ideology when evaluating behavior
in Congress” (Carson et. al 2010: 601-2) and argue that a legislators’ party loyalty matters more for
their reelection prospects than ideology. Similar to the ideological extremity findings in the main text, a
replication of Carson’s analysis at the state legislative level provides little evidence of relationships between
state legislators’ party loyalty scores and their vote shares in most states (See Table A-16.)
15
across all districts and potentially overlooks ideologically similar legislators representing
dissimilar districts.
Figure 4: Measuring Ideological Extremity
Assuming Jefferson and Lincoln represent districts with similar preferences, measures of ideological
extremity do not necessarily correspond to legislators’ ideological distance from their district.
Figure 4 illustrates an example of how a candidate classified as “extreme” using this
absolute value measurement may be more representative than a “non-extreme” one. In this
example, Jefferson and Lincoln respectively have ideal points of -50 and 60 and are competing
for votes in a district whose ideal point is 25. When measuring extremity by taking the
absolute value of an ideal point, Lincoln is considered more extreme than Jefferson with
a score of 60 compared to 50. However, the ideological distance between Lincoln’s ideal
point and the district (35) is less than the comparable distance for Jefferson (75). Lincoln’s
ideology, therefore, is more congruent with the district’s preferences, but in regards to how
Lincoln’s ideological representation will influence his electoral fate, empirical findings from
some congressional research suggest that the “extreme” Lincoln will receive fewer votes
than Jefferson. Spatial theories of elections, meanwhile, predict the ideologically congruent
Lincoln will receive more votes than Jefferson.
For my analysis, I aim to more closely follow the framework of spatial theories and
measure a legislator’s ideological representation or extremity relative to their district. My
available measures of legislators’ and voters’ ideology - ideal points and district-level pres16
idential vote - however are on different scales and not directly comparable. I, therefore,
impute district ideal points under a general assumption that Democrat and Republican legislators on average represent their districts. Variation between a legislator’s and her district’s
ideal points serve as evidence of ideologically extreme representation.
LegislatorIdealP oint =φ0 + φ1 [RepublicanP resV ote]
+ φ2 [RepublicanP artyDummy] + (2)
EstimatedDistrictIdealP oint = |φ0 + φ1 [RepublicanP resV ote]| + λ|φ2 |
(3)
To create district ideal points and measure legislative extremity, I first estimate an ideal
point for each state legislator (Clinton, Jackman, and Rivers 2004; Shor and McCarty 2011).8
Second, I regress legislators’ ideal points on their district presidential vote and party dummy
using Equation 2 for each legislative session. The party dummy accounts for intradistrict
divergence or Democrat and Republican legislators providing different representation to the
same district, captured by φ2 (McCarty, Poole, and Rosenthal 2009). Third, I predict
a district ideal point using estimates from Equation 2 in Equation 3 where the final term
assumes that Republicans and Democrats equally misrepresent the same district by setting λ
equal to 0.5.9 With this district ideal point projected into the ideal point space of legislators,
I measure extremity by taking the absolute value of the difference between a legislator’s ideal
point and their district’s ideal point. For each session, I divide this measure by its standard
deviation to create comparability across time within legislatures. In the main text, I focus
discussion on findings using this distance measure but provide comparable estimates using
the absolute value and other extremity measures in the Appendix (Tables A-14 & A-15).
8
I use a single ideal point in order to facilitate cross-state comparisons. Substantive results do not change
when using session specific ideal points or adjusting session-level ideal points following the approach used by
Groseclose, Levitt, and Snyder (1999).
9
When excluding this party dummy and doing a residual regression, I find evidence of district-level
electoral connections in fewer - but different - states.
17
Outside of this difference in measuring extremity, I aim to follow the econometric setup of
Canes-Wrone et al by estimating Equation 4 for each state.10
IncumbentV oteShare =γ0 + γ1 [ExtremityM easure]
+ γ2 [IncumbentP artyP residentialV ote]
+ γ3 [IncumbentSpendingAdvantage]
+ γ4 [F reshmanDummy] + γ5 [DemocraticDummy]
+ γ6 [P residentialApproval] + (4)
I contrast the strength of state legislative electoral connections to those in Congress by
conducting a comparable study of U.S. House elections for the same 1998 - 2008 time period
(McCarty, Poole, and Rosenthal 2008). Both the state legislative and congressional analyses
control for district level presidential vote and campaign contributions using the variables
described in the individual roll-call analyses.11 I additionally control for presidential approval
as measured by the last national Gallup poll before the November election. This variable
ranges from 0 to 100, and I adjust values to reflect incumbents’ affiliation with the president’s
party. Freshman is a dummy variable indicating if the incumbent just completed his first
term, and the Democratic party variable denotes whether the state house member seeking
reelection was a Democrat.
Since legislators from different states do not vote on the same bills, state-level ideal
points are not directly comparable across states, thereby preventing comparisons of γ1 across
legislatures. To provide comparable meaning to estimates, I calculate the differences in average predicted vote shares associated with a common shift in legislator ideology. Specifically,
I difference a legislator’s predicted vote share holding all variables at their true values and
10
My study of state legislative elections further differs from the Congressional analysis in two respects.
Given the relative infrequency that state legislative incumbents face major party challengers, the below
findings pool elections from 1998 - 2008 to increase statistical power. Second, I do not control for challenger
quality given the lack of availability of this measure at the state legislative-level. Main results from Congressional analyses do not change when excluding this control. Canes-Wrone et. al do not control for previous
incumbent vote share, but findings are not sensitive to including this control.
11
Due to a lack of contribution data, I omit elections from Oklahoma and Delaware in 1998.
18
a legislator’s predicted vote share after making her ideal point a standard deviation more
extreme or distant from their district. To make standard deviation changes comparable
across states, I utilize the NPAT Common Space (described in greater detail below) and calculate a NPAT standard deviation within the ideal point space of each legislature (Shor and
McCarty 2011). This counterfactual ideological adjustment is approximately equivalent to
the median member of the U.S. House in 2008 always voting with the Democratic majority
leader, Steny Hoyer, or roughly a 1 unit change on the Y-Axis on the top left panel of Figure
1 and approximately a .7 unit change on other panels.
The second column of Table 3 presents central results from estimations of Equation 4
for each legislature. These estimates are the OLS coefficient for the extremity variable - as
measured by legislators’ distance from their district - for Congress (US) and each state house.
Increases in incumbents’ ideological extremity produce statistically significant decreases in
vote shares in 9 of 38 states (p ≤ .1). Using these estimates, Figure 5 displays the difference
in average predicted incumbent vote share when a state’s legislator’s roll-call behavior undergoes a common ideological shift away from their district. A standard deviation change
in a legislator’s ideal point results in over a 4% predicted vote share loss for incumbents in
Oklahoma, Wisconsin, Missouri, and Utah, over twice the comparable punishment endured
by U.S. House members (1.9%). Despite the accountability findings regarding individual
roll-calls from Maine and Michigan, neither states’ elections produce strong evidence for the
hypothesis that ideologically extreme legislators receive lower vote shares.
Predicted losses in vote share support the proposition that district-level electoral connections appear to exist in some states. The magnitudes of these relationships suggest that if
some legislators become more ideologically distant from their district they could be voted out
of office. When converting predicted vote share losses from Figure 5 into seat losses, at least
an additional 7% of Wisconsin and Oklahoma incumbents who sought reelection in the past
decade are predicted to lose their seats. Seat losses in Wisconsin are partially attributable to
19
Table 3: Relationships between Incumbent’s Ideological Extremity & Vote
Share
State
US
AL
AK
AR
CA
CT
CO
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
MA
ME
MI
MN
MO
MS
MT
NC
NM
NY
OH
OK
OR
PA
RI
SC
TN
TX
UT
VA
WI
WY
∗∗ p
Distance from District
-0.220* (0.125)
-0.230 (0.957)
-1.126 (1.260)
0.113 (1.061)
-0.131 (0.165)
0.244 (0.266)
-0.148 (0.311)
0.280 (0.375)
-0.322 (0.226)
-0.339 (0.332)
-0.866** (0.417)
-0.042 (0.152)
-1.121** (0.319)
-0.442 (0.291)
0.045 (0.260)
0.268 (0.343)
0.281 (0.554)
0.038 (0.312)
-0.171 (0.271)
-0.242 (0.163)
-0.110 (0.211)
-0.616** (0.20)
-0.809 (0.935)
0.301 (0.296)
0.397 (0.317)
0.585 (0.520)
-0.145 (0.268)
-0.097 (0.294)
-1.520** (0.473)
-0.509** (0.190)
-0.414 (0.264)
-1.653** (0.496)
-0.403 (0.615)
0.087 (0.633)
-0.714** (0.276)
-0.997** (0.432)
0.377 (0.528)
-0.966** (0.203)
0.040 (0.773)
R-Squared
0.64
0.57
0.49
0.54
0.84
0.60
0.81
0.82
0.68
0.50
0.26
0.51
0.70
0.79
0.59
0.46
0.29
0.46
0.26
0.83
0.56
0.56
0.60
0.28
0.56
0.62
0.81
0.72
0.52
0.78
0.63
0.69
0.46
0.49
0.56
0.63
0.44
0.59
0.47
N
1931
72
83
35
239
466
132
97
152
275
188
293
429
298
285
290
160
178
397
398
621
373
46
266
136
117
534
299
147
153
538
166
138
167
262
185
131
262
80
≤ .05; ∗ p ≤ .10 Standard Errors in Parentheses
Second column presents the estimates and standard errors for γ1 of Equation 4 using the sample
of contested state house incumbents who sought reelection from 1998 - 2008. Negative estimates
provide evidence for the hypothesis that ideological extreme legislators receive lower-vote shares, all
else equal. Full Estimates available in Tables A-8 to A-12.
20
Figure 5: Predicted Changes in State House Incumbent Vote Share
Points represent average predicted vote-share loss associated with a common change in an all incumbents’ ideal points for state house elections from 1998 - 2008. The point labeled US represents
the comparable estimate for the U.S. House. Black and grey bars are 95% and 90% bootstrapped
confidence intervals. Only 7 states produce statistically significant evidence of vote-share loss for a
standard deviation change in all legislators’ ideal points.
this state having the fifth most swing seats - those where Bush received between 45 - 55% of
the vote in 2004 - in the country (Figure 2). Analyses similarly predict seat losses in Oregon
where there is a relatively weaker relationship between ideological extremity and vote share
but over a third of districts are swing districts. Only in these three states along with Idaho
and Congress does a standard deviation change in a legislator’s ideal point away from their
constituency result in statistically significant predicted seat losses (p ≤.1). Safe seats, therefore, appear to insulate ideologically extreme legislators from losing their jobs, even in the
Utah or Missouri state legislatures where comparably strong electoral connections exist.12
Despite few legislators being voted out of office for how they represent their districts,
Figure 5 illustrates that the strengths of electoral connections vary across states. Ideological
12
Kerry received 45 - 55% of vote share in only 16% of districts in these states.
21
extremity has larger electoral consequences for legislators in Wisconsin than Wyoming, and
institutional features may be responsible for this variation. Legislators are more likely to
be reelected from professionalized legislatures such as the Wisconsin Assembly (King 1991;
Berry, Berkman, and Schneiderman 2000) despite voters being more disapproving of these
types of legislatures (Squire 1993; Kelleher and Wolak 2007 but see also Richardson, Konisky,
and Milyo 2011). Recent work additionally demonstrates that increases in district population
negatively associate with favorable opinions about state government (Bowen 2013). These
institutional features may relate to voters’ opinions and behavior concerning their state legislature, but it is unclear if they contribute to holding ideologically unrepresentative legislators
accountable.
To further investigate the electoral impact of ideological extremity across the country
and better determine why the differences in Figure 5 exist, I pool observations from the
38 state legislatures. In these analyses, I examine whether extreme state representatives
from more professionalized legislatures or larger districts are more likely to receive lowervote shares. I additionally revisit Hogan’s (2008) finding that increased incumbent spending
advantages decrease the likelihood a legislator receives fewer votes for unresponsive legislative
behavior. To estimate these conditional effects, I interact my measure of ideological extremity
with variables that capture state legislative professionalism, district size, and individual
candidates’ fundraising. To capture professionalism, I use Squire’s index that accounts for
differences across states in legislators’ pay, staff, and length of legislative session (Squire
2007), and I measure constituency size using the logged value of district population reported
by the National Conference of State Legislatures. OLS coefficients on these interaction terms
reflect how states’ legislative institutions influence the strength of district-level electoral
connections.
For comparable measures of ideology, I again calculate legislators’ ideological distance
from their districts using the method described above but replace legislators’ state-level
22
roll-call ideal points with NPAT ideal points (Shor and McCarty 2011). Shor and McCarty
estimate ideal points using survey responses of state legislators who responded to Project
Vote Smart’s National Political Awareness Test (NPAT), producing a common space of
state legislator ideology across states. For each state, legislators’ survey ideal points are
then regressed on their corresponding roll-call ideal point and a dummy variable for party.
Coefficients from this regression and all state legislators’ roll-call ideal points then predict
state legislators’ NPAT ideal point, which is assumed to be on a common scale across states.
It should be noted that NPAT measures of ideology are less polarized - and therefore likely
less extreme - and estimated with more error than the roll-call, state ideal points used in
the analyses presented in Table 3 (Ansolabehere, Snyder, and Stewart 2001), but they are
currently the best cross-state measure of legislator ideology (Berry et al. 2012).
To disentangle the influence of incumbent and challenger fundraising similar to Hogan’s
(2008) analysis, I take advantage of increased statistical power and replace the incumbent
spending advantage variable with separate logged measures of the amount raised by these
candidates. Likewise for presidential approval, I include the unadjusted presidential approval
rating from the last national Gallup poll before the election and this measure interacted with
a dummy variable denoting if a legislator was a member of the President’s party. Coefficients
on these variables reflect the relationship between presidential popularity and the respective
vote shares for state legislators not affiliated and affiliated with the president’s party. For
this cross-state study, OLS regressions include state and year fixed effects and other control
variables are similar to those described in the prior analyses.
When pooling states, statistical analyses from Table 4 suggest that unrepresentative
legislators receive lower vote shares, but the electoral consequences of legislators providing
poor ideological representation are relatively small.13 Estimates from the first column of
13
Which incumbents are included in the sample may be biased by challenger decision-making. Drawing on
the findings from research on challenger entry (Rogers 2013), I replicate the analysis conducted in Table 4
using a Heckman selection model. For this analysis, I assume that chamber competition influences challenger
23
Table 4: Cross-State Regression using NPAT Measures of Ideological Extremity
Variable
Ideological Extremity
Extremity
-0.155*
(0.048)
Extremity X Professionalism
Extremity X District Size
Incumbent Contrib. X Extremity
Challenger Contrib. X Extremity
Inc. Party Presidential Vote
Logged Incumbent Contributions
Logged Challenger Contributions
Incumbent Previous Vote Share
Incumbent Previously Contested Dummy
Q4 Presidential Approval
Presidential Approval X Pres Party
Professionalism
Logged District Size
Democratic Party Dummy
Member of Pres Party
Freshman Incumbent
Midterm Election Dummy
Constant
R-Squared
N
∗p
0.288*
(0.006)
-0.09
(0.087)
-1.403*
(0.032)
0.245*
(0.008)
6.816*
(0.327)
-0.032*
(0.01)
0.139*
(0.011)
-1.597
(2.778)
5.382*
(1.6)
1.33*
(0.164)
-7.79*
(0.615)
0.675*
(0.152)
-0.542*
(0.261)
-12.609
(14.687)
0.67
8851
Extremity w/ Controls
-0.496
(0.754)
-0.668
(0.498)
0.053
(0.087)
-0.017
(0.037)
0.013
(0.013)
0.288*
(0.006)
0.003
(0.219)
-1.477*
(0.078)
0.245*
(0.008)
6.802*
(0.328)
-0.031*
(0.01)
0.139*
(0.011)
2.812
(4.248)
4.68*
(1.782)
1.338*
(0.164)
-7.809*
(0.616)
0.673*
(0.152)
-0.582*
(0.264)
-6.944
(16.083)
0.67
8851
≤ .05; Standard Errors in Parentheses
Relationship between state representative’s ideological extremity and vote share for contested incumbents who sought reelection from 1998 - 2008. Ideal points made comparable across states using
NPAT surveys (Shor and McCarty 2011). Statistical analyses suggest more extreme legislators receive lower-vote shares, but the strength of this relationship is relatively weak and not conditioned
by professionalism, district size, or campaign finance as described in the main text.
24
this table suggest that going from the minimum to maximum observed values of the ideological extremity variable results in only a 2.4% change in vote share. This predicted loss attributable to a voter having the least representative state legislator in the country instead
of the most - is equivalent to the estimated impact of a 9% change in district partisanship
and would not change the outcome of over 97% of 2008 state legislative elections where the
incumbent sought reelection.
Findings from Table 4, furthermore, suggest state legislative elections are largely determined by factors outside of state representatives’ own control. Consistent with findings that
national politics loom large in state-level elections (Chubb 1988; Carsey and Wright 1998;
Rogers 2012), a standard deviation decrease in presidential approval has a larger electoral
impact than a 3 standard deviations change in the ideological distance measure for members of the president’s party. The sensitivity of the relationship between incumbent vote
share and presidential approval is greater for the president’s state legislative copartisans,
but even for non-president’s party state legislators, the predicted impact of a 10% decrease
in presidential approval on vote share exceeds that of a standard deviation decrease for the
ideological extremity measure. These findings imply that state legislators fearing electoral
retribution need to worry more about the president’s performance than their own.
The relationship between how state legislators represent their districts and how they
perform in elections, furthermore, does not appear to be sensitive to cross-state institutional
contexts. Statistical analysis in the second column of Table 4 fail to provide evidence that
state legislators who represent larger districts or serve in more professionalized legislatures
are more likely face electoral ramifications for unrepresentative behavior. Similar to prior
work (Hogan 2008), I find that increased challenger fundraising decreases incumbent vote
while incumbent fundraising has little effect. For example, a challenger raising $20,000
entry but has no direct relationship with incumbent vote share. Results from this analysis (Table A-13) are
similar to findings from the main text.
25
instead of $10,000 for their campaign equates to approximately a 1% decrease in incumbent
vote share, but unlike Hogan, I do not find that increased challenger fundraising is more
electorally advantageous when running against an ideologically unrepresentative incumbent,
as implied by the near zero coefficient on ”Challenger Contrib. X Extremity.” It should be
noted that Hogan’s and my measure of representation differ considerably, and I could not
replicate Hogan’s finding using the 1998 election with my measure.14
Conclusion
Findings from this study of district-level accountability suggest that most state legislators have relatively weak electoral incentives to represent their districts. State representatives
rarely seem to receive lower vote shares for casting unpopular roll-call votes, and most state
legislative elections from the past decade produce little support for the proposition that
elections hold legislators accountable for providing poor ideological representation. Weak
electoral connections combined with partisan legislative districts make it difficult for voters
to throw unrepresentative incumbents out of office. Most state legislators, therefore, do not
appear to face meaningful electoral consequences for their own legislative behavior.
Being unable to remove unrepresentative legislators from power not only has implications for representation in state legislatures but also for Congress itself. State-level electoral
competition can weed out undesirable politicians and create a farm team of tested “quality”
candidates for political parties (Jacobson and Kernell 1983). State legislative teams have
14
My measure of extremity more closely follows Hogan’s (2004) measure of policy responsiveness. In this
study from 2004, he does not consider whether there is the relationship between vote share and extremity
is conditional on challenger spending. In Hogan’s later 2008 work, his partisan policy position measure,
emphasizes whether legislators voted with their party to capture “extreme partisan voting records” (Hogan
2008: 863). Two legislators with the same interest group score who represent identical districts receive oppositely signed “party policy positions” if these legislators belong to different political parties. A limitation of
this approach is that it automatically classifies conservative Democrats and liberal Republicans as extremely
representative regardless of their districts. For example, consider Representatives Jackson (D) and Bush (R)
who have ideal points of 75 and 60 but both represent a district with an ideal point of 50. Following Hogan’s
example in footnote 13, Bush’s “party policy position” would be +10 and Jackson’s would be -25. Bush is
considered more extreme, despite being more ideologically representative of his district.
26
potential all-stars including Illinois state senator Barack Obama and busts, such as Nevada
assemblywoman Sharon Angle. State legislative elections, however, never cut Angle - the
twice selected worst Assembly member by the Las Vegas Review-Journal - off the Republican
farm team, better enabling her to spoil Republicans’ chances to oust Harry Reid from the
U.S. Senate in 2010 (Vogel 2010). Political scientists, therefore, may want to more carefully
consider whether previously holding elected office necessarily defines a quality candidate.
The above findings provide little support for median voter theories’ assumption that
electoral competition creates incentives for representation, but it is important to recognize
the empirical and theoretical limitations of my analyses. My empirical investigations of
district-level accountability in state legislatures are the most thorough to date in terms of
elections considered, but the veto-referenda I study only shed light on electoral connections
in a subset of states for a limited set of issues. Additionally while my measure of ideological
extremity more closely follows the framework of spatial theories compared those that assume
an ideal point equal to zero is “perfectly moderate” (Ladewig 2010: 503), it still does not
accurately put voters and legislators on a common ideological space (Achen 1978).
Of greater theoretical consequence, my analyses give little consideration to the challenger. Ferejohn assumes that “the challengers play no active role” (Ferejohn 1986: 8), but
Downs and other theorists presume that voters respond to both “government activities” and
“the strategies of opposition parties” (Downs 1957: 138).15 Who incumbents face may systematically vary due to strategic parties or legislative leaders (Sanbonmatsu 2006), which
potentially has implications for voters’ choices in the spatial model.
15
Ansolabehere, Snyder, and Stewart (2001) provide empirical evidence for this assumption in congressional
elections. Fearon (1999) additionally presents the argument that elections are the solution to an adverse
selection instead of a moral hazard problem. The analysis here focuses on retrospection and sanctioning
more so than selection, but the two interpretations of elections are not “mutually exclusive.” Unless voters
are purely prospective (e.g. comparing only campaign platforms), “successful selecting of good types implies
sanctioning bad types” (Fearon 1999: 57).
27
The 2010 New Hampshire state house elections underscores this point. At the time of
the candidate filing deadline, President Obama’s approval rating in New Hampshire was the
lowest of his presidency (Granite Poll 2010), and the Republican state party chair claimed
future Speaker Bill O’Brien recruited challengers “not only to fill seats, but to find people
who were ideological - you know the right kind of Republican. He wanted the strongest antiObama types” (Glass 2012).16 New Hampshire voters’ ideological choices in state legislative
elections, therefore, were not random, and if voters reelect an incumbent who is a better
option than choosing a less ideologically representative alternative, my findings would be
more consistent with the predictions of spatial theories.
Despite the limitations of this analysis, my research designs are comparable to those
employed by congressional studies, are the most powerful to date, and still fail to provide
compelling evidence that elections hold state representatives accountable for their legislative
behavior. Without a meaningful threat of electoral accountability, legislators can submit
to party pressures or follow self interest with little fear of losing their job. State legislators
may still “run scared,” act in their constituents’ interests, and produce representative policies
(Erikson, Wright, and McIver 1994). There, however, appears to be not much electoral reason
for them to do so, as elections do relatively little to hold state representatives accountable.
16
I thank Eric Lawrence for pointing me to this quote.
28
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32
Appendix
Table A-1: Summary Statistics of Variables
Variable
Support for Incumbent’s Roll Call (Referendum Measure)
Incumbent Vote Share
Incumbent Previous Vote Share
Contested Incumbent
Freshman Dummy
Democratic Member Dummy
Presidential Approval (Adjusted)
Ideological Extremity - State Level
Ideological Extremity - National (NPAT) Level
Incumbent Contribution Advantage
Logged Incumbent Contributions
Logged Challenger Contributions
Incumbent Party Presidential Vote
State Legislative Professionalism
Logged District Size
33
Min.
23.88
15.68
36.66
0.00
0.00
0.00
12.00
0.61
0.71
-6.18
4.48
0.00
11.92
0.05
8.25
Max
90.90
100.00
100.00
1.00
1.00
1.00
88.00
14.54
16.35
13.61
16.07
15.02
98.14
0.63
12.09
Median
55.54
77.48
72.95
1.00
0.00
1.00
53.00
4.67
5.19
1.25
10.66
9.10
59.93
0.17
9.84
Mean
53.09
79.76
77.89
0.53
0.24
0.53
50.40
5.04
5.58
1.95
10.65
8.71
60.19
0.20
9.88
SD
12.17
19.09
19.17
0.50
0.43
0.50
13.45
2.07
2.23
2.28
1.30
2.28
13.68
0.12
0.74
Full Estimates of Individual Roll-Call Analysis
Table A-2: Full Referendum Estimates: Part 1
Variable
Support for Legislator’s Position
Inc. Party Presidential Vote
Incumbent Previous Vote Share
Incumbents Contributions Advantage
Democratic Party Dummy
Incumbent Previously Contested Dummy
Constant
R-Squared
N
∗p
AK-2000-Measure-6
0.167
(0.311)
0.733*
(0.311)
0.76
(0.45)
0.014
(0.008)
0.172
(0.121)
0.303
(0.189)
-0.713
(0.371)
0.791
16
CA-2004-Prop-72
0.188
(0.138)
0.607*
(0.104)
0.051
(0.119)
0.004
(0.003)
-0.025
(0.018)
0.04
(0.043)
0.101
(0.057)
0.891
51
CA-2008-Prop-94
0.029
(0.113)
0.134
(0.118)
0.638*
(0.127)
0.003
(0.003)
0.089*
(0.014)
0.209*
(0.053)
-0.132
(0.089)
0.937
40
CA-2008-Prop-95
0.085
(0.11)
0.153
(0.125)
0.633*
(0.136)
0.003
(0.003)
0.092*
(0.015)
0.212*
(0.054)
-0.177
(0.102)
0.934
36
≤ .05; Standard Errors in Parentheses
Contested Incumbent Reelection Vote Share as a function of District Support for Incumbent’s RollCall Position and control variables. Column heading denotes referendum. See Table 2 for corresponding bills.
34
Table A-3: Full Referendum Estimates: Part 2
Variable
Support for Legislator’s Position
Inc. Party Presidential Vote
Incumbent Previous Vote Share
Incumbents Contributions Advantage
Democratic Party Dummy
Incumbent Previously Contested Dummy
Constant
R-Squared
N
∗p
CA-2008-Prop-96
0.038
(0.113)
0.136
(0.117)
0.636*
(0.127)
0.003
(0.003)
0.089*
(0.014)
0.208*
(0.053)
-0.135
(0.088)
0.937
40
CA-2008-Prop-97
0.072
(0.107)
0.159
(0.128)
0.629*
(0.137)
0.003
(0.003)
0.091*
(0.015)
0.205*
(0.056)
-0.163
(0.095)
0.934
36
ID-2012-Prop-1
0.333
(0.204)
0.625*
(0.122)
0.019
(0.223)
0.005
(0.004)
-0.053
(0.062)
-0.005
(0.087)
0.058
(0.206)
0.833
28
ID-2012-Prop-2
0.159
(0.143)
0.674*
(0.12)
0.073
(0.227)
0.004
(0.004)
0.005
(0.042)
0
(0.089)
0.056
(0.215)
0.823
28
≤ .05; Standard Errors in Parentheses
Contested Incumbent Reelection Vote Share as a function of District Support for Incumbent’s RollCall Position and control variables. Column heading denotes referendum. See Table 2 for corresponding bills.
Table A-4: Full Referendum Estimates: Part 3
Variable
Support for Legislator’s Position
Inc. Party Presidential Vote
Incumbent Previous Vote Share
Incumbents Contributions Advantage
Democratic Party Dummy
Incumbent Previously Contested Dummy
Constant
R-Squared
N
∗p
ID-2012-Prop-3
-0.003
(0.078)
0.691*
(0.124)
0.073
(0.243)
0.005
(0.005)
0.038
(0.032)
0.001
(0.093)
0.119
(0.242)
0.812
28
ME-2005-Question-1
0.146
(0.081)
0.174
(0.123)
0.449*
(0.108)
0.026
(0.015)
0.011
(0.019)
0.148*
(0.066)
0.002
(0.12)
0.438
103
ME-2008-Question-1
0
(0.063)
0.297*
(0.09)
0.438*
(0.088)
0.005
(0.006)
0.019
(0.025)
0.156*
(0.053)
0.02
(0.096)
0.531
86
ME-2009-Question-1
0.101*
(0.046)
0.409*
(0.082)
0.411*
(0.082)
0.002
(0.005)
-0.126*
(0.019)
0.115*
(0.037)
0.029
(0.085)
0.636
104
≤ .05; Standard Errors in Parentheses
Contested Incumbent Reelection Vote Share as a function of District Support for Incumbent’s RollCall Position and control variables. Column heading denotes referendum. See Table 2 for corresponding bills.
35
Table A-5: Full Referendum Estimates: Part 4
Variable
Support for Legislator’s Position
Inc. Party Presidential Vote
Incumbent Previous Vote Share
Incumbents Contributions Advantage
Democratic Party Dummy
Incumbent Previously Contested Dummy
Constant
R-Squared
N
∗p
MI-2002-Prop-1
0.051
(0.208)
0.462*
(0.109)
0.26*
(0.109)
0.018*
(0.005)
-0.024
(0.038)
0.111*
(0.05)
0.061
(0.108)
0.856
51
MI-2004-Prop-3
0.086
(0.231)
0.469*
(0.125)
0.236*
(0.118)
0.005*
(0.002)
-0.042
(0.042)
0.11*
(0.055)
0.087
(0.117)
0.83
51
MI-2012-Prop-1
0.087*
(0.043)
0.644*
(0.07)
0.06
(0.054)
0.01*
(0.002)
0.036*
(0.012)
-0.03
(0.028)
0.154*
(0.037)
0.946
84
MT-2012-IR-124
-0.023
(0.13)
0.255*
(0.091)
0.679*
(0.111)
0.012*
(0.006)
0.048*
(0.021)
0.239*
(0.047)
-0.209
(0.121)
0.69
51
≤ .05; Standard Errors in Parentheses
Contested Incumbent Reelection Vote Share as a function of District Support for Incumbent’s RollCall Position and control variables. Column heading denotes referendum. See Table 2 for corresponding bills.
Table A-6: Full Referendum Estimates: Part 5
Variable
Support for Legislator’s Position
Inc. Party Presidential Vote
Incumbent Previous Vote Share
Incumbents Contributions Advantage
Democratic Party Dummy
Incumbent Previously Contested Dummy
Constant
R-Squared
N
∗p
OH-2008-Issue-5
-0.112
(0.111)
0.264
(0.136)
0.431*
(0.191)
0.024*
(0.007)
0.047
(0.031)
0.139*
(0.065)
0.068
(0.157)
0.71
47
WA-2004-Measure-55
0.028
(0.048)
0.516*
(0.055)
0.413*
(0.071)
0.011*
(0.003)
0.005
(0.01)
0.135*
(0.027)
-0.104
(0.06)
0.912
63
WA-2008-Measure-67
0.023
(0.119)
0.553*
(0.112)
0.178
(0.102)
0.013*
(0.004)
-0.032*
(0.014)
0.061
(0.039)
0.116
(0.079)
0.787
62
WA-2009-Ref-71
0.103
(0.091)
0.47*
(0.147)
0.335*
(0.119)
0.026*
(0.004)
-0.106*
(0.017)
0.109*
(0.043)
-0.025
(0.075)
0.83
62
≤ .05; Standard Errors in Parentheses
Contested Incumbent Reelection Vote Share as a function of District Support for Incumbent’s RollCall Position and control variables. Column heading denotes referendum. See Table 2 for corresponding bills.
36
Table A-7: Full Referendum Estimates: Part 6
Variable
Support for Legislator’s Position
Inc. Party Presidential Vote
Incumbent Previous Vote Share
Incumbents Contributions Advantage
Democratic Party Dummy
Four Candidates in Current Race
Three Candidates in Previous Race
Four Candidates in Previous Race
Constant
R-Squared
N
∗p
AZ-1998-Prop-300
-0.118
(0.245)
0.41
(0.248)
0.183
(0.122)
0.015
(0.008)
-0.02
(0.03)
-0.031
(0.017)
0.028
(0.017)
0.027
(0.021)
0.076
(0.129)
0.644
26
AZ-1998-Prop-301
0.076
(0.186)
0.258
(0.193)
0.126
(0.111)
0.011
(0.008)
-0.006
(0.023)
-0.041*
(0.018)
0.021
(0.018)
0.024
(0.021)
0.107
(0.131)
0.669
25
ND-2012-Measure-4
-0.039
(0.022)
0.258*
(0.038)
0.743*
(0.108)
-0.003
(0.004)
0.033*
(0.012)
-0.053*
(0.009)
0.084*
(0.016)
-0.076
(0.052)
0.93
24
≤ .05; Standard Errors in Parentheses
Contested Incumbent Reelection Vote Share as a function of District Support for Incumbent’s RollCall Position and control variables. Column heading denotes referendum. See Table 2 for corresponding bills.
37
Full Estimates of Ideological Representation Analysis
Table A-8: Full Ideological Extremity Estimates: Part 1
Variable
Ideological Extremity
Presidential Approval
Inc. Party Presidential Vote
Incumbents Contributions Advantage
Freshman Incumbent
Democratic Party Dummy
Constant
R-Squared
N
∗p
AL
-0.23
(0.957)
-0.042
(0.055)
0.25*
(0.057)
2.589*
(0.37)
-0.646
(1.608)
6.155*
(2.724)
44.944*
(6.729)
0.575
72
AK
-1.126
(1.26)
0.192*
(0.085)
0.5*
(0.095)
3.252*
(0.527)
-1.379
(1.46)
7.884*
(2.893)
19.607*
(8.327)
0.489
83
AR
0.113
(1.061)
-0.066
(0.097)
0.581*
(0.141)
3.032*
(0.996)
3.528
(2.607)
12.663*
(4.138)
21.514*
(10.621)
0.541
35
CA
-0.131
(0.165)
0.149*
(0.023)
0.681*
(0.031)
0.445*
(0.095)
-0.238
(0.471)
-3.584*
(0.678)
16.767*
(2.045)
0.84
239
CT
0.244
(0.266)
0.087*
(0.028)
0.5*
(0.036)
1.729*
(0.162)
-0.473
(0.847)
-3.165*
(0.962)
28.811*
(2.641)
0.598
466
CO
-0.148
(0.311)
0.14*
(0.026)
0.66*
(0.037)
1.313*
(0.226)
-0.337
(0.642)
-2.448*
(0.741)
15.259*
(3.08)
0.81
132
DE
0.28
(0.375)
0.257*
(0.046)
0.51*
(0.047)
1.222*
(0.344)
-0.513
(1.358)
-0.459
(1.614)
21.865*
(3.612)
0.825
97
FL
-0.322
(0.226)
0.11*
(0.034)
0.399*
(0.046)
2.772*
(0.282)
-0.37
(0.745)
-1.131
(1.083)
29.627*
(2.739)
0.679
152
≤ .05; Standard Errors in Parentheses
OLS regressions where Dependent Variable is Contested Incumbent Two-Party Vote-Share. Independent variable is estimated ideological distance between legislator and his district.
38
Table A-9: Full Ideological Extremity Estimates: Part 2
Variable
Ideological Extremity
Presidential Approval
Inc. Party Presidential Vote
Incumbents Contributions Advantage
Freshman Incumbent
Democratic Party Dummy
Constant
R-Squared
N
∗p
GA
-0.339
(0.332)
0.186*
(0.039)
0.323*
(0.028)
2.36*
(0.26)
-3.238*
(1.028)
-0.052
(1.064)
34.583*
(2.915)
0.503
275
HI
-0.866*
(0.417)
0.147*
(0.067)
0.553*
(0.134)
0.635*
(0.243)
-1.137
(1.706)
-5.622
(3.456)
34.077*
(7.942)
0.263
188
IA
-0.042
(0.152)
0.04
(0.028)
0.464*
(0.049)
2.08*
(0.182)
-0.826
(0.665)
-0.121
(0.787)
30.33*
(3.151)
0.512
293
ID
-1.121*
(0.319)
-0.146*
(0.027)
0.698*
(0.036)
1.194*
(0.265)
-3.508*
(0.747)
13.918*
(1.363)
27.203*
(3.133)
0.698
429
IL
-0.442
(0.291)
0.097*
(0.027)
0.469*
(0.026)
1.836*
(0.142)
-0.552
(0.803)
0.493
(0.849)
30.624*
(2.037)
0.79
298
IN
0.045
(0.26)
0.184*
(0.031)
0.414*
(0.035)
1.429*
(0.157)
-2.247*
(0.931)
0.409
(0.906)
25.917*
(3.387)
0.591
285
KS
0.268
(0.343)
-0.037
(0.034)
0.299*
(0.039)
2.726*
(0.21)
-0.833
(0.816)
7.176*
(1.195)
38.261*
(3.419)
0.455
290
KY
0.281
(0.554)
0.185*
(0.06)
0.195*
(0.065)
2.088*
(0.333)
-1.584
(1.336)
1.459
(1.92)
36.494*
(4.763)
0.294
160
≤ .05; Standard Errors in Parentheses
OLS regressions where Dependent Variable is Contested Incumbent Two-Party Vote-Share. Independent variable is estimated ideological distance between legislator and his district.
Table A-10: Full Ideological Extremity Estimates: Part 3
Variable
Ideological Extremity
Presidential Approval
Inc. Party Presidential Vote
Incumbents Contributions Advantage
Freshman Incumbent
Democratic Party Dummy
Constant
R-Squared
N
∗p
MA
0.038
(0.312)
-0.067
(0.088)
0.491*
(0.066)
1.373*
(0.278)
0.632
(1.34)
-1.328
(2.297)
41.161*
(5.218)
0.461
178
ME
-0.171
(0.271)
0.139*
(0.058)
0.364*
(0.05)
1.424*
(0.231)
-0.869
(0.722)
-3.034*
(1.511)
35.274*
(3.629)
0.264
397
MI
-0.242
(0.163)
0.119*
(0.023)
0.665*
(0.023)
0.769*
(0.099)
0.276
(0.475)
0.405
(0.644)
19.914*
(1.89)
0.828
398
MN
-0.11
(0.211)
0.061*
(0.023)
0.485*
(0.027)
1.779*
(0.196)
-1.972*
(0.547)
0.477
(0.639)
30.274*
(2.217)
0.557
621
MO
-0.616*
(0.2)
0.059*
(0.029)
0.471*
(0.036)
1.667*
(0.149)
-0.155
(0.591)
2.091*
(0.831)
33.213*
(2.842)
0.557
373
MS
-0.809
(0.935)
0.035
(0.085)
0.217*
(0.064)
4.186*
(0.657)
1.068
(2.079)
7.186*
(3.127)
41.871*
(6.048)
0.602
46
MT
0.301
(0.296)
0.001
(0.035)
0.228*
(0.041)
1.908*
(0.266)
0.936
(0.803)
2.35*
(1.097)
43.25*
(3.419)
0.284
266
NC
0.397
(0.317)
0.067
(0.055)
0.388*
(0.048)
1.204*
(0.204)
-1.566
(0.979)
4.354*
(1.751)
28.365*
(3.941)
0.558
136
≤ .05; Standard Errors in Parentheses
OLS regressions where Dependent Variable is Contested Incumbent Two-Party Vote-Share. Independent variable is estimated ideological distance between legislator and his district.
39
Table A-11: Full Ideological Extremity Estimates: Part 4
Variable
Ideological Extremity
NM
0.585
(0.52)
0.132*
(0.056)
0.504*
(0.055)
1.256*
(0.285)
-2.246
(1.244)
0.851
(1.18)
21.043*
(4.889)
0.62
117
Presidential Approval
Inc. Party Presidential Vote
Incumbents Contributions Advantage
Freshman Incumbent
Democratic Party Dummy
Constant
R-Squared
N
∗p
NY
-0.145
(0.268)
0.095*
(0.023)
0.583*
(0.02)
1.047*
(0.097)
-1.065
(0.699)
-1.71*
(0.801)
27.607*
(1.67)
0.807
534
OH
-0.097
(0.294)
0.145*
(0.026)
0.506*
(0.031)
1.098*
(0.137)
-0.135
(0.609)
3.461*
(0.697)
23.645*
(2.457)
0.724
299
OK
-1.52*
(0.473)
0.038
(0.056)
0.295*
(0.054)
2.855*
(0.304)
-1.646
(1.251)
6.236*
(1.763)
46.187*
(5.026)
0.517
147
OR
-0.509*
(0.19)
0.126*
(0.032)
0.579*
(0.04)
1.191*
(0.142)
-1.344
(0.701)
-2.858*
(0.886)
23.665*
(2.961)
0.776
153
PA
-0.414
(0.264)
0.065*
(0.023)
0.432*
(0.021)
1.649*
(0.116)
-1.625*
(0.792)
-0.019
(0.64)
37.264*
(1.928)
0.633
538
RI
-1.653*
(0.496)
0.063
(0.052)
0.732*
(0.061)
1.364*
(0.248)
-2.921
(1.542)
-10.275*
(2.01)
29.741*
(4.036)
0.69
166
SC
-0.403
(0.615)
0.002
(0.055)
0.48*
(0.069)
1.405*
(0.346)
0.025
(1.534)
8.151*
(1.688)
29.409*
(5.1)
0.464
138
≤ .05; Standard Errors in Parentheses
OLS regressions where Dependent Variable is Contested Incumbent Two-Party Vote-Share. Independent variable is estimated ideological distance between legislator and his district.
Table A-12: Full Ideological Extremity Estimates: Part 5
Variable
Ideological Extremity
Presidential Approval
Inc. Party Presidential Vote
Incumbents Contributions Advantage
Freshman Incumbent
Democratic Party Dummy
Constant
R-Squared
N
∗p
TN
0.087
(0.633)
-0.018
(0.042)
0.279*
(0.051)
1.84*
(0.256)
-0.855
(1.375)
3.097*
(1.575)
41.908*
(4.524)
0.487
167
TX
-0.714*
(0.276)
0.096*
(0.028)
0.474*
(0.032)
0.485*
(0.123)
-0.827
(0.819)
4.309*
(0.943)
30.09*
(2.72)
0.556
262
UT
-0.997*
(0.432)
0.128*
(0.042)
0.487*
(0.038)
1.603*
(0.224)
0.736
(0.899)
6.898*
(1.267)
24.191*
(3.848)
0.63
185
VA
0.377
(0.528)
0.063*
(0.025)
0.354*
(0.052)
2.059*
(0.384)
0.638
(1.167)
1.252
(1.035)
33.256*
(4.146)
0.441
131
WI
-0.966*
(0.203)
0.142*
(0.029)
0.561*
(0.045)
1.602*
(0.187)
-1.533*
(0.754)
-0.854
(0.833)
31.467*
(3.361)
0.587
262
WY
0.04
(0.773)
0.078
(0.076)
0.375*
(0.079)
2.785*
(0.603)
1.441
(1.617)
8.535*
(3.008)
28.998*
(6.347)
0.473
80
≤ .05; Standard Errors in Parentheses
OLS regressions where Dependent Variable is Contested Incumbent Two-Party Vote-Share. Independent variable is estimated ideological distance between legislator and his district.
40
Table A-13: Cross-State Regression using NPAT Measures of Ideological Extremity
Variable
Ideological Extremity
Extremity
-0.155*
(0.048)
Extremity X Professionalism
Extremity X District Size
Incumbent Contrib. X Extremity
Challenger Contrib. X Extremity
Inc. Party Presidential Vote
Logged Incumbent Contributions
Logged Challenger Contributions
Incumbent Previous Vote Share
Incumbent Previously Contested Dummy
Q4 Presidential Approval
Presidential Approval X Pres Party
Professionalism
Logged District Size
Democratic Party Dummy
Member of Pres Party
Freshman Incumbent
Midterm Election Dummy
Constant
Log-Likelihood
Uncensored Observations
∗
0.288*
(0.006)
-0.090
(0.087)
-1.403*
(0.032)
0.245*
(0.008)
6.816*
(0.327)
-0.020
(0.025)
0.139*
(0.011)
-1.597
(2.778)
1.671*
(0.437)
1.33*
(0.164)
-7.79*
(0.613)
0.675*
(0.151)
2.866*
(0.777)
20.53
(4.24)
-27837.05
8851
Extremity w/ Controls
-0.496
(0.751)
-0.668
(0.496)
0.053
(0.087)
-0.017
(0.037)
0.013
(0.013)
0.288*
(0.006)
0.003
(0.219)
-1.477*
(0.078)
0.245*
(0.008)
6.802*
(0.328)
-0.018
(0.01)
0.139*
(0.011)
2.812
(4.248)
1.26*
(0.659)
1.338*
(0.164)
-7.809*
(0.616)
0.673*
(0.152)
2.95*
(0.778)
23.52
(5.91)
-27835.36
8851
p ≤ .05 Standard Errors in Parentheses, Dependent Variable: Contested Incumbent Vote Share
Results from a Heckman selection model where the selection equation follows the model
from Rogers (2013) of this dissertation controlling for Quarter 2 Presidential Approval interacted with whether an incumbent was a member of the president’s party. There are a total
of 17460 observations with 8609 censored and 8851 uncensored.
41
Alternative Measurement of Extremity
As described in the main text, prior work on Congressional elections at times measures
a legislator’s ideological extremity using the absolute value of a legislator’s ideal point. For
replication purposes Table A-14 presents comparable estimates of γ1 from Equation 4 using
this absolute value measure.
Table A-14: Relationships between Absolute Value of Incumbent’s Ideal Point
and Vote Share
State
US
AL
AK
AR
CA
CT
CO
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
MA
ME
MI
MN
MO
MS
MT
NC
NM
NY
OH
OK
OR
PA
RI
SC
TN
TX
UT
VA
WI
WY
∗∗ p
Abs. Value of Ideal Point
-3.702** (0.481)
-3.714 (2.873)
-8.484** (3.407)
-3.738 (2.392)
-3.381** (0.922)
0.070 (1.177)
-0.822 (0.925)
4.949** (1.966)
-3.062** (1.495)
0.784 (1.055)
3.902 (3.353)
0.160 (1.472)
-4.928** (0.589)
-0.445 (0.825)
-1.938 (1.836)
-0.550 (0.978)
-0.528 (1.074)
3.385* (1.801)
-3.503** (0.983)
-6.914** (0.961)
-3.926** (0.916)
-1.926* (1.108)
-5.70** (2.679)
1.183 (1.212)
-0.912 (1.262)
-3.548** (1.322)
2.063** (0.705)
-4.895** (0.824)
4.620** (1.821)
-2.165** (1.009)
-2.398** (0.828)
-3.802** (1.242)
-0.492 (1.753)
3.468** (1.534)
-3.20** (0.850)
-3.774** (1.156)
-2.181 (1.603)
-2.357 (1.905)
-2.270 (1.529)
R-Squared
0.64
0.58
0.53
0.56
0.85
0.60
0.81
0.82
0.69
0.50
0.25
0.52
0.73
0.79
0.59
0.45
0.29
0.49
0.29
0.85
0.57
0.55
0.63
0.28
0.55
0.64
0.78
0.75
0.50
0.77
0.64
0.69
0.49
0.50
0.56
0.64
0.45
0.55
0.51
N
1931
72
83
35
239
466
132
97
152
275
188
293
429
298
285
290
160
178
397
398
621
373
46
266
136
117
534
299
147
153
538
166
138
167
262
185
131
262
80
≤ .05; ∗ p ≤ .10 Standard Errors in Parentheses
Dependent Variable: Contested Incumbent Vote Share.
42
An ideal point of zero does not imply a legislator is “perfectly moderate” (Ladewig 2010:
503). For example, Joe Democrat with an ideal point of -0.1 would be and be classified as
“extreme” as a Jane Democrat with an ideal point of 0.1, even though Joe is more liberal than
Jane. To investigate the extent to which liberal Democrats and conservative Republicans
receive lower vote shares, Table A-15 presents estimates of γ1 from Equation 4 when extremity
is a legislator’s unadjusted ideal point. Estimates are from separate OLS regressions on data
subset by an incumbent’s political party. For the the Democratic subset, positive coefficients
indicate more liberal Democrats receive lower vote shares, and for the Republican subset,
negative coefficients indicate conservative Republicans receive lower vote shares.
43
Table A-15: Relationships between Incumbent’s Ideal Point and Vote Share
State
US
AL
AK
AR
CA
CT
CO
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
MA
ME
MI
MN
MO
MS
MT
NC
NM
NY
OH
OK
OR
PA
RI
SC
TN
TX
UT
VA
WI
WY
Democrat Subset
2.725** (0.675)
5.202 (3.347)
-0.882 (3.666)
4.162* (2.426)
3.246** (1.094)
-1.179 (1.494)
2.019 (1.815)
-6.013** (2.968)
1.165 (1.433)
-0.865 (1.773)
-5.447** (2.501)
-0.643 (3.368)
1.514 (3.244)
-0.167 (0.648)
4.043 (2.683)
2.646 (1.672)
2.262* (1.276)
-5.388** (1.869)
2.442 (1.528)
8.631** (1.553)
6.641** (1.445)
3.219 (2.043)
1.776 (2.496)
0.952 (1.758)
1.822 (2.092)
1.629 (2.688)
-1.704** (0.572)
5.10** (1.945)
-5.971** (2.927)
-1.032 (1.655)
3.094** (1.383)
0.799 (1.128)
0.640 (1.604)
4.175 (2.723)
2.688** (1.187)
3.294* (1.946)
2.356 (2.930)
7.275** (3.549)
-3.014** (1.486)
∗∗ p
R-Squared
0.69
0.55
0.64
0.57
0.84
0.61
0.82
0.88
0.78
0.52
0.20
0.48
0.35
0.78
0.62
0.44
0.24
0.50
0.19
0.86
0.65
0.61
0.63
0.32
0.47
0.58
0.81
0.70
0.55
0.82
0.69
0.71
0.64
0.64
0.59
0.51
0.35
0.52
0.54
N
955
51
31
25
141
324
66
32
43
146
138
129
41
150
168
102
102
169
197
188
327
139
33
116
81
67
369
111
82
53
271
136
62
109
124
72
56
93
25
Republican Subset
-5.139** (0.676)
1.044 (5.459)
-19.441** (5.434)
-0.268 (3.319)
-3.642* (1.883)
0.211 (2.266)
-0.271 (0.951)
1.981 (2.549)
1.078 (1.827)
0.806 (1.103)
-7.480 (8.499)
0.009 (1.373)
-4.905** (0.504)
0.003 (1.274)
1.814 (2.496)
-0.155 (1.108)
1.567 (1.603)
-4.708 (3.425)
-4.004** (1.235)
-5.080** (1.180)
-1.944* (1.159)
-2.255* (1.273)
-11.411* (6.126)
1.265 (1.482)
0.002 (1.458)
-4.330** (1.286)
-5.901** (1.302)
-3.869** (0.80)
6.216** (1.977)
-3.918** (1.342)
-1.099 (0.976)
-0.812 (2.010)
4.454 (3.119)
5.008** (2.266)
-1.959 (1.331)
-20* (1.132)
-1.606 (1.693)
1.656 (2.245)
-5.884** (1.916)
R-Squared
0.49
0.67
0.55
0.77
0.71
0.29
0.84
0.57
0.64
0.51
0.26
0.56
0.76
0.61
0.61
0.48
0.51
0.58
0.35
0.67
0.25
0.54
0.65
0.29
0.62
0.78
0.39
0.65
0.57
0.74
0.47
0.14
0.42
0.34
0.53
0.76
0.59
0.56
0.58
≤ .05; ∗ p ≤ .10 Standard Errors in Parentheses
Dependent Variable: Contested Incumbent Vote Share.
44
N
989
23
53
13
98
142
66
66
111
135
50
166
388
149
117
192
59
45
201
212
295
236
15
150
55
50
171
191
65
100
275
37
81
58
140
116
75
169
57
Electoral Accountability for Party Loyalty
Some contend that “voters place greater weight on partisanship than ideology when
evaluating behavior in Congress” (Carson et. al 2010: 601-2). Carson and his coauthors
argue identifying legislators who break party ranks is likely easier for voters than pinpointing
their representative’s ideology. For example, Maine voters may recognize that Representative
Lajoie did not succumb to the party whip and reward him for his loyalty to district over
party. The extent to which a legislator votes with his party, furthermore, could approximate
their extremity and whether she represented her district, permitting an indirect application
of Downsian expectations.
P artyLoyalty =π0 + π1 [|AbsoluteV alueof IdealP oint|]
+ π2 [IncumbentP artyP residentialV ote]
+ π3 [IncumbentSpendingAdvantage] + π4 [F reshmanDummy]
+ π5 [P resident0 sP artyDummy] + π6 [P residentialApproval]
+ π7 [IncumbentP reviousV oteShare]
+ π8 [IncumbentP reviouslyContested] + π9 [P reviousP artyLoyalty] + (5)
ˆ
P artyLoyalty =α0 + α1 [P artyLoyalty]
+ α2 [IncumbentP artyP residentialV ote]
+ α3 [IncumbentSpendingAdvantage] + α4 [F reshmanDummy]
+ α5 [P resident0 sP artyDummy] + α6 [P residentialApproval]
+ α7 [IncumbentP reviousV oteShare]
+ α8 [IncumbentP reviouslyContested] + 45
(6)
To replicate Carson’s analysis at the state legislative level, I evaluate the extent to which
voters punish party loyal state legislators. I again examine state house elections from 1998
- 2008. Similar to ideological representation analysis, the dependent variable is a contested
incumbent’s vote-share. The independent variable of interest is an incumbent’s party loyalty.
Carson et. al argue that “party loyalty is not exogenous to legislators’ reelection prospects”
and use a two-stage least squares panel data estimator where ideological extremity - the
absolute value of a legislator’s ideal point - instruments for party loyalty. To account for this
potential endogeneity, I calculate session specific estimates of party loyalty and extremity
for each state house member to use in a first state estimation of equation 5. Similar to
Carson, I then conduct a second state estimation using equation 6. Control variables follow
the measurement described in the main text.
The first column of Table A-16 presents the OLS coefficient on the party loyalty measure
from state-level estimations of Equation 6. Similar to Carson et. al’s results, estimates
suggest more party loyal members of the US house receive lower vote shares. A 15% increase
in party loyalty results in approximately a 3.2% decrease in incumbent vote share. The same,
however, is not the case in most state legislatures. There is only a negative relationship
between party loyalty and incumbent vote share in 4 of 38 states. Statistical analyses again
provide evidence of district-level electoral connections in Michigan, but despite the findings
the Maine voters appear to hold their state representative accountable for individual rollcalls, neither the ideological extremity nor party loyalty analysis provides similar evidence
of district level accountability. Results are relatively similar when controlling for legislators
ideological distance from their district (third column of Table A-16).
Figure A-1 presents differences across states by plotted the predicted average change
in incumbent vote-share if all legislators voted with the majority of their party 15% more
of the time. These estimates suggest only legislators in Missouri, Michigan, and Texas will
receive less votes on average for this increase in party loyalty, and it appears that legislators
46
Figure A-1: Predicted Changes in State House Incumbent Vote Share for
Increased Party Loyalty
Points
represent average predicted vote-share loss associated with a 15% increase in an all incumbents’
party loyalty scores for state house elections from 1998 - 2008. The point labeled US represents
the comparable estimate for the US House. Black and grey bars are 95% and 90% bootstrapped
confidence intervals.
in Alaska and North Carolina would actually receive larger electoral margins if they vote
more often with the majority of their party.
47
Table A-16: Relationships between Incumbent’s Party Loyalty and Vote Share
State
US
AL
AK
AR
CA
CT
CO
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
MA
ME
MI
MN
MO
MS
MT
NC
NM
NY
OH
OK
OR
PA
RI
SC
TN
TX
UT
VA
WI
WY
Loyalty
-0.219** (0.041)
0.009 (0.016)
0.323** (0.138)
-0.115 (1.328)
-0.087 (0.077)
-0.012 (0.108)
-0.210 (0.248)
0.144 (0.121)
-0.146 (0.304)
0.035 (0.446)
0.257* (0.153)
-0.023 (0.126)
-0.157 (0.166)
0.223 (0.214)
0.017 (0.066)
-0.023 (0.119)
-0.275 (0.374)
0.157 (0.201)
-0.090 (0.077)
-0.263** (0.102)
-0.128 (0.101)
-0.353** (0.102)
-0.468 (0.478)
0.091 (0.115)
0.379** (0.113)
-0.052 (0.155)
-0.028 (0.113)
-0.159** (0.059)
-0.158 (0.130)
-0.004 (0.137)
-0.093 (0.10)
-0.047 (0.090)
-0.171 (0.112)
0.017 (0.112)
-0.907** (0.135)
0.021 (0.10)
-0.269 (0.243)
0.036 (0.051)
-0.40 (0.429)
∗∗ p
Loyalty - Control for Extremity
-0.195** (0.040)
0.010 (0.019)
0.301** (0.130)
-0.129 (1.405)
-0.093 (0.078)
-0.015 (0.109)
-0.224 (0.260)
0.157 (0.136)
-0.142 (0.306)
-0.038 (0.466)
0.211 (0.169)
0.073 (0.138)
-0.217 (0.198)
0.221 (0.214)
0.122* (0.072)
-0.017 (0.119)
-0.355 (0.390)
0.287 (0.216)
-0.094 (0.078)
-0.262** (0.102)
-0.153 (0.104)
-0.366** (0.102)
-0.583 (0.493)
0.070 (0.126)
0.390** (0.113)
-0.055 (0.156)
-0.035 (0.113)
-0.189** (0.060)
-0.281** (0.134)
0.014 (0.153)
-0.113 (0.103)
-0.121 (0.089)
-0.197* (0.114)
0.025 (0.113)
-0.704** (0.138)
-0.009 (0.105)
-0.291 (0.244)
0.039 (0.050)
-0.425 (0.430)
Extremity
-0.067 (0.115)
0.20 (2.745)
-3.230** (1.214)
-0.613 (1.580)
-0.130 (0.206)
-0.169 (0.282)
-0.092 (0.467)
0.102 (0.458)
-0.210 (0.318)
-0.225 (0.410)
-0.327 (0.496)
-0.30 (0.187)
-0.320 (0.574)
-0.228 (0.369)
0.398 (0.292)
0.290 (0.466)
-0.546 (0.741)
-0.051 (0.354)
-0.129 (0.434)
-0.036 (0.204)
0.115 (0.209)
-0.316 (0.30)
-1.262 (1.295)
-0.290 (0.382)
0.428 (0.408)
0.604 (0.650)
0.147 (0.293)
-0.492 (0.334)
-1.637** (0.585)
0.090 (0.324)
0.071 (0.307)
-1.347** (0.543)
0.368 (0.819)
0.475 (0.806)
-0.703** (0.273)
-0.508 (0.525)
0.599 (0.60)
-0.759** (0.226)
-0.986 (0.987)
≤ .05; ∗ p ≤ .10 Standard Errors in Parentheses
Incumbent Vote Share as a function of Instrumented Party Loyalty
48
N
1663
25
51
16
118
309
76
78
76
166
116
180
108
209
206
173
108
148
180
149
464
186
32
119
98
72
364
204
111
82
401
124
110
139
218
133
91
191
42