Trump Success? Conventional Measures in the Era of an Unconventional President

Jon R. Bond Texas A&M University [email protected]

and

Manny Teodoro Texas A&M University [email protected]

Prepared for Presentation at the 115th Annual Meeting & Exhibition of the American Political Science Association August 29 – September 1, 2019 Washington, DC

Trump Success? Conventional Measures in the Era of an Unconventional President

Abstract

Conventional indicators reported in CQ’s 2017 Presidential Support Study show that President Trump racked up a “Record Success Rate”, winning 100 percent of House votes on which he expressed a position. Although presidency scholars have long recognized that winning roll call votes is not an indication of presidential influence, Trump’s unconventional style and his willful ignorance of Congress and basic details of the policies he “supports” lead us to question whether the results of roll call votes should even be interpreted as presidential success. Including this unconventional president in the study of a still small n of presidents requires innovative indicators that do not rely exclusively on traditional Presidential Support Scores that compare members on a static zero to 100 scale. Taking cues from FiveThirtyEight and from the field of sabermetrics, this paper presents two novel metrics that estimate whether House members’ support for the 11 elected presidents from Eisenhower to Trump is higher or lower than should be expected relative to differing political conditions. One metric, Support Above Expectations (SAE), estimates whether members’ presidential support is higher or lower than should be expected given electoral conditions, partisanship, polarization. This metric builds on 538’s “Trump plus-minus” score. The other metric, Votes Above Replacement (VAR), measures members’ presidential support relative to a “replacement-level” member—i.e., the member who is most likely to be replaced. Similar to sabermetrics Wins Above Replacement (WAR), this metric seeks to estimate how valuable a member is from the president’s perspective. Each of these metrics turns the analysis away from the usual focus on average or representative members to outliers. Identifying outliers is unusual in political science. We hope this unusual approach might provide insights about presidential support in this time of a most unusual president.

Conventional indicators reported in CQ’s annual Presidential Support Study show that President Trump won 100 percent of House votes on which he expressed position in 2017. CQ proclaims this “a record for success” (Bennett 2018, 26). Trump is, indeed, the only president to get everything he wanted from either chamber of Congress in the more than 60-year history of CQ’s vote study. Some might not be surprised that

Trump scored a perfect record in his rookie year. After all, a central theme of Trump’s campaign was his business experience. He pointed to principles in The Art of the Deal (Trump with Schwartz 1987) to convince voters that he would cut the best deals in history. But is it appropriate to credit this score as Trump success?

Presidency scholars have long recognized that winning support on floor votes is not an indication of influence, but understanding the conditions that explain presidential success is important in its own right

(Bond and Fleisher 1990; Edwards 1989). Even so, crediting the outcome of a floor vote as a presidential win assumes that the president contributed to the policy’s development and its movement through Congress.

Trump belies these assumptions: If the president just endorses policies developed by party leaders but remains ignorant of basic details of the policy he “supports”, then calling the results of roll call votes “record high presidential success is akin to giving an ‘A+’ to a student who turned in plagiarized a paper” (Bond 2019a).

Including this unconventional president in the study of a still small n of presidents requires unconventional, or at least innovative, indicators. Fortuitously, the data journalism website FiveThirtyEight began identifying roll call votes on which Trump expressed a position in 2017. Of course, since 538’s basic approach mirrors CQ’s, they produce conventional indicators that do not address the threat to empirical research posed by an erratic position taker (Bond 2019b; Bond and Teodoro 2019). However, analysts at 538, developed an innovative indicator—“Trump plus-minus”—that estimates how much more or less members of

Congress support Trump than should be expected given how well he ran in their district. The plus-minus concept views support from a perspective that is not common in political science. Rather than compare members on a static zero to 100 scale, it compares members’ support relative to the differing political conditions they face. This perspective turns attention to identifying atypical members.

1 2

Can this indicator developed to gauge unusual support for this unusual president be extended to earlier presidents whose styles varied within normal parameters? Rather than include Trump in the usual analysis of presidential support, we extend 538’s unusual indicator to the usual presidents. Who are the members of

Congress who were unusually supportive or unsupportive of Trump, and how do they compare to unusual supporters of previous presidents?

This paper builds on the plus-minus” score in three ways. First, based on findings from political science research, we develop a better-specified model to produce more efficient estimates of expected support.

Second, for greater generalizability, we estimate House members’ plus-minus scores for presidents back to

Eisenhower. Third, we adapt two statistics from sabermetrics—Wins Above Average (WAA) and Wins

Above Replacement (WAR)—that gage the value of a major league baseball player relative to other players.

Expanding on the plus-minus concept, we develop two analogous metrics—Support Above Expectations

(SAE) and Votes Above Replacement (VAR)—that gage House members’ value to the president relative to overall expectations and relative to a hypothetical “replacement” member in each Congress.

The Scientific Study of Presidential Support in Congress

Richard Neustadt (1960, i) taught that to understand presidential leadership, study presidential behavior—what the president “can do, as one man among many, to carry his own choices through that maze of . . . institutions called the government of the United States.” One essential maze the president must navigate in order to succeed is Congress. Students of the presidency (Edwards 1976, 1978, 1980) and Congress (Fleisher and Bond 1977; Bond and Fleisher 1980) began using quantitative methods to analyze presidential support on roll call votes.1

Scientific analysis of this leader-follower relationship requires valid and reliable measures of both the president’s position (yea/nay) and how often members’ votes agree with the president’s preference.

1 A floor vote is but one, and not necessarily the most important, aspect of the multi-faceted concept of presidential success. Yet, it is an essential facet, and one that is available in the public record over many years (Bond and Fleisher 1990, 66-69). 3

Observing how members of Congress vote is highly reliable—casting floor votes is a key part of their job, and their revealed preferences are recorded in the public record. Presidents, in contrast, are not expected to express a position on all roll calls, and when they do, it is not part of the public record. Absent an authoritative source, scholars relied on journalists at Congressional Quarterly to identify votes on which the president expressed a position, and what position the president preferred. A recent paper documents inconsistencies in how CQ identified presidential positions over the vote study’s 60-year history, but these are common challenges in conducting empirical research. Trump’s unconventional behavior poses a fundamental threat to the reliability of conventional measures (Bond 2019a). Analyzing presidential support from a different perspective may provide some insight on addressing this threat.

A Different Perspective on Presidential Support

The traditional Presidential Support Score (PSS) measures how often members vote in agreement with president’s position on roll call votes on a static scale that ranges from zero to 100. Analysis of this indicator seeks to explain why some members support the president more often than do other members. FiveThirtyEight suggests a different way to think about presidential support. Rather than rely exclusively on the traditional support score, the “Trump plus-minus” score estimates whether members supported the president more or less often than should be expected relative to the different political conditions they face. Specifically, 538 estimates expected support by regressing Trump support on his 2016 vote margin in members’ districts. Errors from this regression provide a quantitative estimate of how much more or less members support Trump than should be expected given how well he ran in their constituency.

FiveThirtyEight’s research design is consistent with political science research in some ways. While theory building is not a goal of journalism, analysists at 538 suggest electoral threat as the underlying basis for estimating expected support—“we would expect a member in a district where Trump did well to be more in sync with him than a member in a district where Trump did poorly” (Bycoffe n.d.). Prevailing theory in political science research assumes that reelection is a primary motivation, and members of Congress make 4 rational choices to increase their chances of reelection (Fenno 1973, 1978; Mayhew 1974; Jacobson 1989,

1990; Jacobson and Kernell 1983).

The indicators and methods they use to estimate expected support are also common in political science research. The presidential vote in congressional districts is a standard indicator of voters’ partisan preferences in general (Jacobson and Carson 2016) and popular support for the president in particular

(Edwards 1978; Pritchard 1986). Furthermore, several studies used errors from regression models to estimate whether presidents win more or fewer floor votes, and whether individual members support the president more or less often, than should be expected.2

FiveThirtyEight’s research design is innovative, but incomplete. Political science research suggests three essential refinements to the model. First, party is a primary determinant of congressional behavior. Existing research provides sound theoretical and empirical evidence of how and why party influences roll call voting in

Congress (Aldrich 1995; Kingdon 1981; Weisberg 1978), and consistently finds that party is the strongest determinant of presidential support in Congress (Bond and Fleisher 1990; Edwards 1989). All of the studies that used regression to estimate expected support included party in the model.

Second, while journalists seek accurate information about the current president, political scientists look for general explanations. Generalization requires analyzing multiple years of data for several presidents.

Third, with the addition of more years and presidents, the model needs to account for changes in the nature of the relationships over time. Notably, party polarization among voters and members of Congress has increased sharply over the last several decades. For instance, the correlation between the president’s vote margin in members’ districts and the party that wins the seat increased from an R2 around 0.65 from the

1960s-1980s, to about 0.80 in the 1990s-2000s, and 0.95 in 2012 and 2016 (Jacobson 2017, 29). As a result, party cohesion in Congress also increased. Polarization, however, does not directly raise or lower presidential

2 Studies of unusual success include Bond (n.d.); Bond & Fleisher (1990, chap. 8); Cohen, Bond, & Fleisher (2013a, 2013b); Fleisher, Bond, & Wood (2008) and Teodoro & Bond (2017); studies of unusual support include Fleisher & Bond (1983, 1992). 5 support. Instead, the effects are conditional—i.e., the effects of party and presidential vote are different for same party and opposition party members depending of the level of polarization (Bond and Cohen 2015;

Bond, Fleisher, and Cohen 2015; Bond, Fleisher and Wood 2003; Teodoro and Bond 2017a).

We turn now to the research design we employ in an effort to refine estimates of legislative support.

Research Design The Sample

We expand the analysis of legislative support to presidents since Eisenhower. However, we limit the analysis to House members in the Congress immediately following a presidential election. Reelection is the theoretical basis for using the presidential vote in members’ districts to estimate expected support. The presidential vote is a useful indicator to assess how the president might affect members’ reelection chances, but it is likely to influence calculations only of House members until the midterm.

Because all House members must face voters again in the upcoming midterm, they have an incentive to consider voters’ support for the president in their districts. After the midterm, the president’s electoral margin is less of a consideration—retiring and defeated members have dropped from the analysis, and returning members have demonstrated that they were able to overcome any disadvantage stemming the president’s electoral performance. The connection between the president’s vote margin and reelection in the Senate is more tenuous. Two-thirds of Senators do not face voters again for four or six years. The one-third up for reelection in the midterm are likely to evaluate the president’s recent electoral support in their state as one of multiple forces that may have altered political conditions since their last election.

Since FiveThirtyEight did not identify presidential positions before Trump, we rely on CQ’s vote studies to extend the analysis to presidents to previous. A comparison of 538’s “Trump support” in 2017 to CQ’s

2017 Presidential Support Scores (Bond 2019b) shows that the two indicators are nearly identical (R2=.98; 6 b=1.07). Thus, this paper analyzes House members’ support for the 11 elected presidents in the 17 Congresses following presidential elections since 1952, providing a total n of 14,652 individual support scores.3

Refinements to the Model Estimating Expected Support

The “Trump plus-minus” score indicates how much more or less members support the president than should be expected. FiveThirtyEight estimates expected support with a bivariate regression of members’ support score on Trump’s vote margin in their districts. Residuals from this regression indicate how much more or less each member supports Trump than do other members who represent districts with a similar

Trump vote margin (Bycoffe n.d.). A regression analysis of Trump support in 2017 found a seemingly strong relationship between the president’s vote margin and members’ support—slope of the regression line (b=1.00) indicates a 1-to-1 relationship, and the R2 is a respectable 0.70 (Bond 2019b; Bond and Teodoro 2019). This bivariate relationship is spurious, however, resulting mostly from the large difference in same party and opposition party support. A regression with vote margin interacted with members’ party finds much weaker relationships within party—opposition party (Democrats) support is weakly related to Trump’s electoral support (b=0.17, R2=0.28), but support from the president’s party (Republicans) is unrelated to vote margin

(b=0.06, R2=0.02). Thus, we add party interacted with the president’s vote margin to the model.

Furthermore, increasing party polarization of voters and members of Congress over the last six decades conditions these relationships. When voters were less polarized, more members won districts that favored the other party in presidential elections (Fleisher and Bond 2004), and presidential support scores were less concentrated near the minimum and maximum as these members moderated their presidential support to appeal to voters outside of their party base. Thus, we add polarization and interactions to the model. These refinements incorporate the two most important variables that motivate the behavior of members of

Congress—reelection and party—and accounts for changes in the relationships resulting from polarization.

3 We code each session of a Congress separately, resulting in observations from 34 years. Analysis of the 93rd Congress (1973-74) is Nixon support. We exclude Ford because he was not elected and he served only four months in 1974. 7

The following OLS regression model estimates expected presidential support:

PSS=B0+B1(Presvt)+B2(Pty)+B3(Plzn)+B4(Presvt*Pty)+B5(Plzn*Pty)+B6(Plzn*Presvt)+ B7(Plzn*Pty*Presvt)

Where:

1. PSS=Presidential Support Score: annual percentage of roll calls on which a House member voted in

agreement with president’s position adjusted for absences (Congressional Quarterly, Inc. 1953-2019)

2. Presvt=President’s vote margin in the district: %vote for the president-%vote for losing candidate;

3. Pty=Member’s party: 1=member of president’s party, 0 otherwise;

4. Plzn=Party polarization: mean distance between the parties— |%Dem yea -%Rep yea| —on all RCs

in the year excluding consensus votes (LT 10% in the minority);

5. Presvt*Pty= interaction of Presvt and Pty;

6. Plzn*Pty=interaction of Plzn and Pty;

7. Plzn*Presvt=interaction of Plzn and Presvt;

8. Plzn*Pty*Presvt=interaction of all three conditional variables.4

Table 1 reports OLS regression results from 1953-2018 with three specifications: The first column is effectively 538’s bivariate model extended to more presidents; the second column is the model with party interactions; the third column is the full model with party and polarization interactions. Presenting the three estimates alongside each other illustrates the importance of including party, polarization, and interactions to estimate expected support. The interaction terms are all significant, indicating conditional relationships—i.e., the effects of the presidential vote on support are different for co-partisans and opposition partisans, and relationships differ depending on the level of polarization in Congress.

4 Polarization is centered on is mean. This transformation gives the intercept term (B0) a meaningful interpretation—predicted support for a member of the opposition party from district with even presidential vote at mean polarization. 8

Table 1 Conditional Effects of President’s Vote Margin, Party and Party Polarization on Presidential Support in the House 1953-2018 Presidential Support Score Presvt Pty*Presvt Pty*Presvt*Plzn Coef. Coef. Coef. President’s vote margin in CD 0.14** 0.28** 0.17** (87.75) (37.12) (24.11)

Party (president’s party=1) 34.17** 35.93** (103.40) (122.13)

Polarization on Roll Call Votes -57.61** (-48.23)

Party*President’s vote -0.12** -0.03* (-10.10) (-2.63)

Party*Polarization 97.72** (51.49)

Polarization*President’s vote 0.32** (7.49)

Party*Polarization*President’s vote -0.29** (-4.40)

Constant 54.34** 40.42** 39.25** (302.56) (206.99) (215.30) N 14,652 14,652 14,652 F(7, 14644) 7699.39** 8373.80** 5526.85** R2 0.34 0.63 0.72 Entries are OLS regression coefficients estimated with Stata 14. (t-test in parentheses) **p<.001, *p<.01

Interaction terms are not directly interpretable, but the marginal effects plots in Figure 1 illustrate some of the effects. The party difference in presidential support is large—support from the president’s co-partisans is around 35 percentage points higher than opposition support (b=34.2 in the model with party only, b=35.9 in the model with polarization). The negative interaction of party and presidential vote indicates that co-partisans are less responsive to the presidential vote (b=-0.12) than are opposition partisans. In the model with polarization, the slope drops to near zero (b=-0.03). This suggests that co-partisans are less responsive to the president’s vote if polarization is high, but at zero (mean) polarization, the slopes are flat for both parties (see 9

Figure 1A). The effects of polarization are quite different depending on party. As polarization increases, support from the president’s party increases and opposition support declines sharply (see Figure 1B).

Figure 1A: Conditional Effects of Party

Figure 1B: Conditional Effects of Party Polarization

Plus-minus Scores from the Refined Model

This refined model establishes a more complete baseline to estimate expected support of House members from 1953-2018. Plus-minus scores differ depending on the verisimilitude of estimated support.

FiveThirtyEight’s plus-minus scores estimate how much more or less members support the president than 10 should be expected given the presidential vote in their districts. With the addition of the party interaction, plus-minus scores estimate how much more or less members support the president than should be expected given the president’s vote in districts won by members of the same party. The plus-minus scores are not the same—the correlation between residuals from the bivariate model and those from the model with party is

R2=0.56. Because the current study analyzes support for 11 elected presidents since 1953, polarization needs to be included to account for changes in relationships over time—the correlation between residuals from the bivariate model and those from the full model with party and polarization is R2=0.42. Thus, we estimate plus- minus scores relative to expected support from the full model with interactions of party and polarization.

Although these refinements account for changes in relationships over time, the standard deviations of residuals varies from year to year. To compare residuals for different presidents, we use studentized residuals

(standardized relative to the standard deviation). Standardization is useful for detecting unusually large outliers. With a 95 percent confidence interval, Studentized residuals exceeding ±2.0 are considered unusual.

Assessing presidential support relative to expectations is a different way to gauge whether support is high or low. Sabermetrics suggests how we might give the plus-minus concept a substantive interpretation.

Sabermetric Estimates of Member Value

Sabermetrics is “the search for objective knowledge about baseball” (James 1982).5 In previous work, we observed a number of parallels between baseball teams’ season records and presidential success rates in Congress. We adapted sabermetric techniques to estimate presidents’ Wins Above Expectations

(WAE)—whether their win/loss records were higher or lower than expected (Teodoro and Bond 2017).

Parallels between baseball players and individual members of Congress, of course, are far more tenuous. Like baseball players, members of Congress play for different teams—the home team

(president’s party) and the away team (opposition party). And just as players contribute wins by scoring

5 The name honors the Society for American Baseball Research (SABR). 11 runs (with hitting and base running) or preventing them (with pitching and defense), members of

Congress cast votes for or against the president.

The parallels unravel quickly after that. Baseball managers get to fill out their team’s roster, but elections determine which politicians are called up to the legislative big league, as well as whether they play for the Democrats or Republicans. The president has limited ability to influence, much less decide, who makes the team or who is replaced.6 Furthermore, baseball players can only score for their own team, but members of Congress can vote for or against the president’s position regardless of their party team.

Finally, members of Congress cast votes not only on policy proposals, but also on organizational issues

(e.g., Speaker and majority leadership elections). On organizational matters, any member of the president’s party is more valuable than is any opposition party member. Even a co-partisan who rarely supports the president’s position votes with their team on the single most important determinant of presidential wins and losses—establishing majority party control (Bond and Fleisher 1990; Edwards

1989).7 Yet, the main advantage of majority control is having co-partisans chairing standing committees and controlling access to floor. Once a bill gets to the floor, votes for the president’s positions are equally valuable regardless of whether they come from the president’s or opposition party.

Although the parallels between baseball players and members of Congress are tenuous, sabermetrics illustrates the analytical benefits of looking beyond metrics that compare teams and players on a fixed scale—e.g., batting average, Runs Batted In, total bases, Earned Run Average. Possibly the most important analytical contribution of sabermetrics is developing metrics that measure whether teams and players perform better or worse than should be expected relative to a baseline that accounts for varying

6 The most famous presidential effort to replace unsupportive co-partisans was Franklin Roosevelt’s campaign to purge conservative Democrats in the 1938 primaries. His efforts failed and conservatives gained seats in Congress. President Trump appears to have been a bit more successful at defeating less than totally supportive Republicans in primaries, but those purges may have contributed to the 40 seat Democratic wave in the 2018 midterm election. 7 In Speaker elections since 1995, there have been a few votes cast for members other than the party nominees, mostly within the same party (Heitshusen 2019). When James Traficant (D-OH) voted for Dennis Hastert (R-IL) for Speaker in 2001, Democrats stripped him of his committee assignments. The House expelled him the following year after his conviction for campaign fraud. 12 conditions. With this empirical ethic in mind, we seek to identify House members who support the president more or less than should be expected.

Sabermetricians have developed an ever-expanding suite of metrics to assess the value of major league baseball players’ performance relative to that of other players. Two of the most useful are Wins

Above Average (WAA) and Wins Above Replacement (WAR). For fans and sports writers debating a player’s standing among the all-time greats and his worthiness of the Hall of Fame, Wins Above Average

(WAA) assessing the value a player adds to a team above that of an average player is most useful

(Darowski 2012). On the other hand, baseball team owners, managers, and fans concerned with roster construction to win games in the immediate future need a metric to assess the relative value of each player compared to available alternatives. Wins Above Replacement (WAR) is the premiere metric for that purpose. We adapt these metrics to estimate House members’ value from the president’s perspective.

Support Above Expectations

Plus-minus scores assess whether members’ presidential support is higher or lower than should be expected relative to varying political conditions over the period from 1953-2018. Similar to WAA, this metric can be thought of as Support Above Expectations (SAE). To be sure, there is no Congress Hall of

Fame to recognize unexpectedly high or low presidential support. Nonetheless, this metric identifies which House members were presidential support outliers over this period, and how they are distributed across each president. In particular, we can see how outliers in support for Trump compare to outliers for earlier presidents. Due to ceiling and floor effects, support from the president’s party will rarely be significantly higher than expected, and opposition party support will rarely be below expectations. Similar to Baseball Hall of Fame enshrinement, we might observe fewer outliers in recent Congresses.

Votes Above Replacement

Building a winning baseball team requires identifying and acquiring skilled athletes. For roster construction in the sabermetric era, the key statistic is WAR, which estimates the value a player brings to his 13 team expressed as wins added relative to a “replacement-level” player (Zimbalist & Baumer 2014). The logic behind WAR is that, when a team must substitute a player on its roster (due to injury, retirement, or release), the available newcomer is unlikely to be a league average player—a player of average ability is probably already in the league. Rather, the best available is likely an unsigned free agent or a player for the team’s minor league affiliate. Replacement-level players are below average, but the best available to a team that must fill a roster slot.

What would a replacement-level member of Congress look like from the president’s perspective? While presidents don’t get to pick the congressional roster, some seats are more likely to flip than are others. Seats most likely to flip in the next election are those where the incumbent won in a district that supported the other party’s presidential candidate. Thus, a replacement-level member from the president’s party (i.e., the co- partisan most likely to be replaced) is one representing a district where the president’s popular vote was weakest. Conversely, a replacement-level member of the opposition party (i.e., the opposition member most likely to be replaced) is one representing a district where the president’s vote was strongest.

To measure members’ legislative value to the president, we calculate Votes Above Replacement (%VAR) for members of each party. For the president’s party, %VARP is the difference between a co-partisan’s presidential support score and the PSS of the replacement-level co-partisan. For the opposition party, %VARO is the difference between an opposition member’s PSS and the PSS of the replacement-level opposition member. Hence, these metrics are calculated from the president’s point of view—i.e., members of each party evaluated in terms of the value that they provide to the president.8

Findings

The analysis of presidential support in Congress traditionally looks for general patterns of behavior in a representative sample of members. The primary analytical focus is on the typical member. Extremely atypical members—outliers—are viewed as threats to an accurate estimate of the underlying relationship. The analysis

8 The method could be easily adapted to evaluate VARP and VARO from the opposition party perspective. 14 of members’ support relative to what should be expected turns the spotlight on atypical members, especially extreme outliers. Who are the members whose presidential support is most unusual relative to expectations?

Outliers in Support Above Expectations (SAE)

The regression model estimates the expected level of support relative to the varying political conditions members face. The residuals from this regression indicate whether members’ presidential support is higher or lower than should be expected given the presidential vote in their districts, party, and the conditioning effects of polarization. We can view the residuals as estimates of Support Above [or below] Expectations (SAE).

Residuals, of course, have no substantive interpretation. The errors contain everything not included in the model, so the unobserved factors that drive them are unknown. They should be random error. Nonetheless, studentized residuals (standardized relative to their standard deviation) provide an objective standard for detecting significantly large outliers—i.e., studentized residuals exceeding ±2.0.l. This standard identifies 511 members who had unusually higher or lower support than should be expected given the political conditions they faced.9 Table A-1 lists the outliers for each presidential administration.

Figure 1 shows the number of members who were significant outliers in support above and below expectations in the Congress following presidential elections. We see wide variation in the number of outliers across the 11 presidents in this study. Eisenhower had the largest number of both over-supporters (73) and under-supporters (51) in his second term. Kennedy, Johnson, and Carter also had a large number of under- supporters, while only Clinton had a large number of over-supporters in his first term.10 The number of outliers for Trump in the 115th Congress is similar to his immediate predecessor—a few more positive outliers

(18) than Obama and Bush, but an average number negative outliers (5).

9 This number counts members who were outliers in both sessions of a Congress only once, but outliers are listed once in each Congress in which they appear. The unit of analysis to estimate plus-minus scores is member-year in Congresses following a presidential election. Summing across years, there are 665 outliers. In a sample 14,652 observations, we would expect to find one in twenty unusual outliers (about 733) by random chance. 10 This pattern raises concern about heteroskedasticity. Keep in mind that this reports only extreme outliers. Plots of all residuals against (1) fitted values, (2) presidential vote, and (3) polarization revealed no relationship (b=0, R2=0) in any test (see Figure A-1). 15

Figure 1: Number of Presidential Support Outliers Above and Below Expectations

*Number of under-supporters are shown as negative numbers to more easily differentiate them from over-supporters

As we speculated, under-supporters are almost exclusively the president’s co-partisans and over- supporters are mostly from the opposition. Because same party support is higher than opposition party support, this pattern in over- and under-support is not surprising. For presidents since Bush-43, with mean same-party support at 88 percent and opposition party support at 25 percent, ceiling effects tend to restrict outliers within party to one direction. In earlier years, the mean difference in partisan support was much less—

73 percent for the president’s party and 44 percent for opposition partisans. The mean gap in support for presidents since Bush-43 (63 percent) was more than twice that for earlier presidents (29 percent). The small number of co-partisan over-supporters and opposition party under-supporters occurred in years when the partisan gap in presidential support was smaller. Carter and Reagan had a number of opposition partisans who joined their co-partisans with presidential support below expectations. Nixon stands out as the president with the fewest over- or under-supporters in either term. 16

Since many members serve in several Congresses, some emerge as extreme outliers multiple times.

Limiting attention to 32 members who were outliers for presidents of different parties, we see the same pattern of support above and below expectations. Presidential support scores of all 16 Democratic outliers and 12 of

15 Republican outliers were below expectations for presidents of their party and above expectations for opposition party presidents (see Table A-2).11

These members with unexpectedly high or low presidential support are atypical in another way: except for Eisenhower, most outliers were outside the ideological mainstream of their party (see Table A-1). These members were moderates (DW-NOMINATE scores between ±0.2) or ideological misfits (Democrats with positive and Republicans with negative DW-NOMINATE scores).12 Finally, we observe one surprising pattern of unusual support for the most unusual president. Donald Trump has repeatedly made derogatory comments about women, African Americans, Hispanics, and other ethnic minorities, yet 13 of the 18 Democrats with unexpectedly high support were women or members of racial/ethnic minorities.

Votes Above Replacement (VAR)

We begin by identifying the replacement-level member of the president’s party and the opposition party for each Congress in our dataset.13 Recall that for the president’s party, the member whose district yielded the lowest vote margin for the president is the replacement-level member. For the opposition party, the member whose district generated the highest vote margin for the president is the replacement-level member. For both the president’s and opposition party, the replacement-level member’s percentage of votes on presidential roll calls defines replacement-level support for that year.

Table 2 shows the replacement-level member identified for each Congress. Some notable results emerge.

First, presidential support from replacement-level members of the president’s party and opposition party are

11 One member, Ogden R. Reid (NY), who switched parties had the same pattern of unusual support. Members who were outliers in both sessions of a Congress are listed only once. The table does not list outliers for different presidents of the same party. 12 This is the definition of moderate commonly used in the literature (Fleisher and Bond 2004; Poole 2016; Shafer 2016). 13 Replacement-level members are the same in both years of a Congress. 17 remarkably close on average, with opposition replacement-level members actually providing three percent greater average support than do replacement-level members of the president’s party. In nine of the 17

Congresses analyzed here, support from the replacement-level opposition member was greater than that of the replacement-level member of the president’s party. Trump’s replacement-level Republican Ileana Ros-

Lehtinen (FL) and replacement-level Democrat Colin Peterson (MN) had the same support score (70 percent) in the 115th Congress. This result is consistent with our earlier finding that opposition members are more responsive to the presidential vote than are co-partisans (see Table 1).

Table 2 Replacement-level Members of the House of Representatives President’s Party Opposition Party %Vote %Vote Cong Pres Member % PSS Member %PSS Margin Margin 115 DJT -20 Ileana Ros-Lehtinen (R-FL) 70 30 Collin Peterson (D-MN) 70 113 BHO-2 -37 Jim Matheson (D-UT) 28 17 Gary Miller (R-CA) 11 111 BHO -36 Gene Taylor (D-MS)*† 47 49 Joseph Cao (R-LA) 69 109 GWB-2 -11 Jim Leach (R-IA)† 46 41 Jim Marshall (D-GA)† 62 107 GWB -25 Jack Quinn (R-NY) 85 44 Ralph Hall (D-TX)*† 78 105 WJC-2 -22 Ralph Hall (D-TX)*† 29 33 Jack Quinn (R-NY) 35 103 WJC -34 Bill Orton (D-UT)† 62 29 Jay Dickey (R-AR)† 40 101 GHWB -33 S. William Green (R-NY) 51 46 Earl Hutto (D-FL)† 63 99 RWR-2 -20 S. William Green (R-NY) 37 54 Richard Stallings (D-ID) 42 97 RWR -17 Newt Gingrich (R-GA) 73 44 Kent Hance (D-TX)* 70 95 JEC -34 K. Gunn McKay (D-UT)† 55 26 S. William Green (R-NY) 75 93 RMN-2 -6 Paul W. Cronin (R-MA)† 49 67 Robert L. F. Sikes (D-FL) 62 91 RMN -30 F. Bradford Morse (R-MA) 68 30 John O. Marsh (D-VA)* 67 89 LBJ -79 John Bell Williams (D-MS) 25 49 Joe Martin Jr. (R-MA)† 64 87 JFK -34 Joe Waggonner (D-LA) 47 16 Laurence Curtis (R-MA) 65 85 DDE-2 -2 John F. Baldwin (R-CA) 81 40 J. Vaughan Gary (D-VA) 45 83 DDE -24 Jacob K. Javits (R-NY) 71 43 Howard Miller (D-KS)† 61 Overall Avg. -28 54 39 57 Republican Avg. -19 63 44 62 Democratic Avg. -40 42 31 51 *Changed parties following replacement-level term. †Eventually lost re-election.

Second, Republican presidents enjoyed far greater average support from replacement-level members of both parties than did Democratic presidents. This result may reflect greater ideological diversity and a larger number of moderates in the Democratic caucus compared to Republicans throughout the period of this study.

Third, four of the 34 replacement-level members switched parties at some point after their replacement- level year in the House; all were Democrats who subsequently became Republicans. Four is a small number, 18 but party switches are rare in American politics. Four of 34 (about 12 percent) is a much larger proportion than the roughly two dozen House members who switched parties during or after their service, out of more than

10,000 House members since the 83rd Congress (1953-1954). Another notable case is John Bell Williams (D-

MS). Although Williams did not formally switch parties, he was a Republican in all but name. He gave

Lyndon Johnson just 4% support in 1965 (25% throughout the 89th Congress), and he endorsed Republican presidential candidates Barry Goldwater in 1964, Gerald Ford in 1976 and Ronald Reagan in 1980.14

Finally, more than a third of replacement-level members eventually lost reelection bids (though not always immediately after their replacement-level years). Although House reelection rates range from 87-97 percent over this period, incumbents who win on the other party’s turf are the most vulnerable to defeat because the opposition targets them. The disproportionate number of rare party-switchers and defeated incumbents lends some face validity to the idea that these members are among the most “replaceable.”

To calculate %VAR, we subtracted the replacement-level member’s presidential support from each member’s presidential support for that year. The result is a %VARP for every member of the president’s party and a %VARO for each opposition member. In substantive terms, %VARP and %VARO estimate the vote share that a member provided the president greater than (or less than) the replacement-level member of his or her party in that year. Table 3 reports average %VARP and %VARO for each Congress. Multiplying %VARP and %VARO by the total number of presidential roll calls yields estimates VARP and VARO for each Congress

(not shown); the sum of these two figures is net VAR for each Congress. Net VAR is in part a measure of overall legislative productivity. As such, it is useful for evaluating an entire Congress or presidency.

Stark partisan differences emerge once again. Democratic presidents enjoy average %VARP more than three times greater than do Republican presidents. Democrats in the White House have also had considerably higher %VARO, indicating less robust opposition from Republicans. Understood as a measure of overall

14 The Democratic caucus stripped Williams and Albert Watson (D-SC) of their seniority for endorsing Goldwater in 1964.Watson resigned and won a special election as a Republican. Williams was reelected to the House in 1966as a Democrat. 19

“roster strength,” these metrics suggest that, on average, Democratic presidents entered the legislative arena with more supportive teams and weaker opposition than did Republican presidents.15 Thus, Republican presidents seem to win more than should be expected (Teodoro and Bond 2017) in spite of weaker teams.

Table 3 %Votes Above Replacement and Net Votes Above Replacement President’s Party Opposition Party Cong Pres Roll Calls Mean %VARP Mean %VARO Net VAR 115 DJT 83 22.1 -46.0 -3,233 113 BHO-2 147 56.8 2.0 17,522 111 BHO 102 41.5 -40.1 3,674 109 GWB-2 82 38.5 -34.1 1,567 107 GWB 74 1.3 -45.7 -6,935 105 WJC-2 139 46.8 -6.3 11,469 103 WJC 162 16.9 4.2 8,067 101 GHWB 189 17.3 -30.7 -9,893 99 RWR-2 163 31.4 -13.3 3,766 97 RWR 130 -2.2 -26.0 -8,758 95 JEC 171 12.5 -32.1 -2,136 93 RMN-2 198 20.0 -17.2 -2,037 91 RMN 83 1.8 -9.0 -1,485 89 LBJ 159 56.1 -18.7 22,126 87 JFK 105 33.9 -21.5 5,387 85 DDE-2 94 -18.8 12.7 -946 83 DDE 58 7.8 -7.7 17 Overall Average 126 22.6 -19.4 2,245 Republican Avg. 11.9 -21.7 -2,793 Democratic Avg. 37.8 -16.1 9,444

Biennial %VAR and Most Valuable Members

So who goes to bat for the president? VAR calculations allow us to identify the sabermetric Most

Valuable Members (MVMs) to the president. Table 4 lists the members with the highest mean %VAR of the president’s (MVMP) and the opposition party (MVMO) by Congresses. We see that %VAR figures for MVMs fluctuate widely from one Congress to the next, owing to the unstable nature of the replacement-level

16 17 support. Notable MVMP winners include past and future Speakers of the House Pelosi and Boehner.

15 th The glaring exception is Eisenhower, whose fellow Republicans generated large negative VARP in the 85 Congress. But note that Eisenhower took moderate to liberal positions. Based on ADA and ACA votes on which Eisenhower expressed a position, his overall liberalism score was 46% overall (Bond and Fleisher 1990. 164), and 67% in the 85th House. Mean Democratic and Republican support were similar (59.3% vs. 62.5%), a difference of only 3.2% compare to an overall mean difference of 39.8%. 16 Recall that the replacement-level member from Congress to Congress is determined relative to different presidential elections. 17 Since Speakers vote at their own discretion, they do not have support scores for the Congress when they are Speaker. In some years, however, the Speaker cast enough votes to have a Support Score. 20

Table 4 Most Valuable Members by %VAR President’s Party Opposition Party Cong Pres Member (MVMP) %VAR Member (MVMO) %VAR 115 DJT 41-way tie 30.0 Peterson (D-MN) 0.0 113 BHO-2 Pelosi (D-CA), Price (D-NC) 68.0 Gibson (R-NY) 23.0 111 BHO Capps (D-CA), Schiff (D-CA), Hoyer (D-MD), 50.5 Cao (R-LA) 0.0 Dicks (D-WA) 109 GWB-2 Oxley (R-OH), Boehner (R-OH) 49.5 Boren (D-OK) 13.0 107 GWB Skeen (R-NM), Oxley (R-OH) 12.0 Lucas (D-KY) 1.5 105 WJC-2 Skaggs (D-CO) 64.5 Morella (D-MD) 37.3 103 WJC Dicks (D-WA) 31.2 Morella (D-MD) 34.8 101 GHWB Michel (R-IL) 34.7 Montgomery (D-MS) 4.4 99 RWR-2 Eckert (NY) 51.6 Daniel (VA) 26.0 97 RWR Badham (CA) 15.1 Stump (AZ) 13.4 95 JEC Boling (MO) 32.7 Whalen (OH) 11.5 93 RMN-2 Rhodes (AZ) 37.1 Waggoner (LA) 13.8 91 RMN Wilson (CA) 25.0 Boggs (LA) 7.8 89 LBJ Dawson (IL) 72.9 Tupper (ME) 25.3 87 JFK Doyle (CA), Miller (CA) 52.8 Tupper (ME) 15.0 85 DDE-2 Dwyer (NJ) 6.8 Dawson (IL) 35.1 83 DDE Halleck (IN) 23.1 Campbell (FL) 16.3

th th th th th MVMP results were tied in the 87 , 107 , 109 , 111 , and 113 Congresses, with as many as four members sharing the honors.18 But perhaps the most striking finding to emerge from Table 4 is the

th unprecedented 41-way tie for MVMP in the 115 Congress: from 2017-2018, 41 Republican members of the House of Representative voted with president Trump’s position on 100% of roll calls. With such extraordinary cohesion among Republicans, the MVMP distinction is meaningless—absurd, even—and is indication of Trumpian exceptionalism (or perhaps Republican exceptionalism in the Trumpian era).

Career VAR and Candidates for a Congressional Hall of Fame (if there were one)19

A perennial question among sports fans in debates over who were the all-time greats is how to think about peak value versus career value. How should we evaluate a player who performs spectacularly over a few short seasons (e.g., Sandy Koufax), relative to a player who is good-to-great over a long career (e.g., Frank

Robinson)?20 In political terms, a member may be a presidential support outlier in a particular Congress, but

18 Five of the six ties have occurred since 2001, consistent with the growing polarization in Congress. 19 An institution that we absolutely do not advocate. 20 From 1963-1966 pitcher Koufax averaged an extraordinary WAR of 9.1—he reached 10.7 in 1963—but the lefty Dodgers’ 12- year career total was just 53.1. Robinson’s single-season best WAR was 8.7, but the rangy outfielder accumulated 107 WAR over his remarkable 21-year career. Both are Hall-of-Famers. 21 may leave office after just one or two terms—perhaps because of his/her support for the president. Another member might provide unexceptional support relative to the replacement members in any single Congress, but do so consistently over many Congresses.

Single-Congress %VAR offers a snapshot of Congress members’ relative value to the president at a particular point in time. Yet, most members serve multiple terms and so accumulate legislative records across multiple Congresses. Cumulative VAR over a congressional career offers some clues to who might belong in an imaginary House of Representatives Hall of Fame. To arrive at career value, we total each member’s cumulative VARP and subtract his or her VARO. This approach rewards members for consistently supporting presidents of their party and opposing opposition presidents over a long career. Table 5 lists the members with the top ten highest career VAR from the 17 Congresses analyzed here.

Not surprisingly, the top ten is composed of very long-serving members, none of whom appears on the

MVM list in Table 4. These members show remarkably high career value, but not necessarily peak value.

Somewhat more surprisingly, all ten are Democrats. Indeed, Democrats hold career VAR positions 1-24, with the highest ranking Republican coming in at #25 (Robert Michel, R-IL).21 Detroit’s John Conyers is the Babe

Ruth of presidential support in the House—the runaway G.O.A.T. by our sabermetric reckoning. Over his 26 terms in Congress, the Michigan representative contributed 261.4 VAR in support of Democratic presidents and 214.6 VAR in opposition to Republican presidents. We also observe that all ten members are men. The highest-ranking woman by career VAR is Marcy Kaptur (Ohio’s 9th District) checks in at #19 all-time.22 This result is not surprising in light of the perineal under-representation of women in Congress during this period.

21 Michel’s career totals are VARP=143.1, VARO=-136.0, VAR=179.1. 22 Kaptur’s career totals are VARP=107.5, VARO=-178.2, VAR=285.7. 22

Table 5 Top Ten All-time Career VAR House Members Rank Member Term Career VARP Career VARO Total VAR 1 John Conyers (D-MI) 1965-2017 261.4 -214.6 476.0 2 George Miller (D-CA) 1975-2015 188.6 -220.2 408.8 3 Pete Stark (D-CA) 1973-2013 179.2 -213.0 392.2 4 William D. Ford (D-MI) 1965-1995 180.2 -179.1 359.3 5 Louis Stokes (D-OH) 1969-1999 153.0 -195.0 347.9 6 Barney Frank (D-MA) 1981-2013 138.2 -204.7 342.9 7 Lee H. Hamilton (D-IN) 1965-1999 247.9 -91.1 339.0 8 Edward R. Roybal (D-CA) 1963-1993 147.9 -183.2 331.1 9 John Dingell (D-MI) 1955-2015 312.5 -17.8 330.3 10 Jim Scheuer (D-NY) 1965-1973, 1983-1993 155.8 -168.6 324.4

Discussion

The 45th president of the United States has forced reassessment of some conventional political science theories of presidential politics. Records from the 115th Congress provide an opportunity to examine the ways that members of Congress related and responded to Trump. Was Trump really exceptionally successful in the legislative arena, as CQ suggests? Addressing this question also provides a point of departure for development and refinement of metrics to assess individual members’ presidential support.

To those ends, we crafted two new metrics—SAE and VAR—that measure members’ support for presidential positions relative to expectations rather than on a static zero to 100 scale. SAE is a refinement of 538’s regression-based score that estimates House members’ expected support given the president’s electoral margin, partisanship, and polarization, and then identifies members whose support was unusually above or below expectations. This approach implicitly compares presidential support relative to the average member of the same party. By contrast, sabermetric-style %VAR measures each member’s presidential support relative to a “replacement-level” member—i.e., the member who is most likely to be replaced. This approach gauges support on scale that perhaps more accurately reflects the real political circumstances that presidents and congressional leaders face when forging legislative coalitions. Each of these metrics turns attention from average or representative members to the outliers, and offers a promising avenue for further analysis of individual members. 23

Calculating SAE and %VAR for representatives from 17 Congresses yields patterns that reveal insights about the presidency generally and President Trump specifically. SAE results suggest that, after accounting for electoral dynamics, partisanship, and, polarization, Trump’s legislative success is not markedly different from most of his predecessors. That is, measured by SAE, Trump has enjoyed roughly the same level of support that conventional political science models would predict given the broader political context. Furthermore, the unusual outliers in support for Trump and past presidents (except for

Eisenhower) are disproportionally moderates and ideological misfits in their party.

Sabermetric %VAR sheds a somewhat different light on the 115th Congress. President Trump enjoyed unusually strong support from replacement-level Republicans, and a startling 41-way tie for sabermetric

MVMP. Where SAE indicates that Trump’s record is broadly consistent with his predecessors, patterns of

%VAR reveal a president who receives exceptional loyalty from a hard core of co-partisans.

Do these extensions address the existential threat to empirical research of an unorthodox president?

Unlikely. But borrowing President Trump’s modal dodge to any controversy, crisis, or self-inflicted wound: “We’ll see what happens” (Cillizza 2019). 24

References

Aldrich, John H. 1995. Why Parties: The Origin and Transformation of Political Parties in America. Chicago: University of Chicago Press. Bennett, John T. 2018. “CQ Vote Studies: Presidential Support - Trump Divided, Conquered.” CQ Weekly (February 12, 2018). http://library.cqpress.com/cqweekly/weeklyreport115-000005263239. Bond, Jon R. 2019a. “Validity and Reliability of Identifying Presidential Positions on Roll Call Votes in the Age of Trump.” Presidential Studies Quarterly 49 (March): First published: 27 December 2018 https://doi.org/10.1111/psq.12508. Bond, Jon R. 2019b. “Presidential Support in Congress in the Trump Era.” Presented at the annual meeting of the Southern Political Science Association, Austin, TX, January 17-19. Bond, Jon R. n.d. “Which Presidents Are Uncommonly Successful in Congress? A Trump Update.” Presidential Studies Quarterly 49 (December 2019): forthcoming. Bond, Jon R., and Jeffrey E. Cohen. 2015. “Polarized Public Opinion and Presidential Success in Congress.” Presented at the annual meeting of the American Political Science Association, San Francisco, CA, September 3-6. Bond, Jon R. and Richard Fleisher. 1990. The President in the Legislative Arena. Chicago: University of Chicago Press. Bond, Jon R. and Richard Fleisher. 2000. Polarized Politics: Congress and the President in a Partisan Era. Washington, DC: CQ Press. Bond, Jon R., and Richard Fleisher. 1980. “The Limits of Presidential Popularity as a Source of Influence in the U.S. House.” Legislative Studies Quarterly, 5 (February): 69-78. Bond, Jon R., Richard Fleisher, and Jeffrey E. Cohen. 2015. “Presidential-Congressional Relations in an Era of Polarized Parties and a 60-Vote Senate.” In American Gridlock: Causes, Characteristics, and Consequences of Polarization, eds. James A. Thurber and Antoine Yoshinaka, eds. New York: Cambridge University Press, 133-151. Bond, Jon R., Richard Fleisher, and B. Dan Wood. 2003. “The Marginal and Time Varying Effect of Public Approval on Presidential Success in Congress.” Journal of Politics 65 (February): 92-110. Bond, Jon R. and Manny Teodoro. 2019. “Going to Bat for the White House: A Sabermetric Analysis of Congressional Support for the President.” Presented at the annual meeting of the Midwest Political Science Association, Chicago, IL, April 4-7. Bycoffe, Aaron. N.d. “Introducing the Trump Score.” FiveThirtyEight. https://fivethirtyeight.com/features/introducing-the- trump-score/. Cillizza, Chris. 2919. “'We'll see what happens': An investigation into Donald Trump's favorite phrase.” THE PO!NT, CNN politics. May 13, 2019. https://www.cnn.com/2019/05/13/politics/donald-trump-iran-mueller-taxes/index.html Cohen, Jeffrey, Jon R. Bond, and Richard Fleisher. 2013a. “Placing Presidential-Congressional Relations in Context: A Comparison of Barack Obama and His Predecessors.” Polity 45 (January): 105-126. Cohen, Jeffrey, Jon R. Bond, and Richard Fleisher. 2013b. “The Implications of the 2012 Presidential Election for Presidential-Congressional Relations: Change or More of the Same?” In The 2012 Presidential Election: Forecasts, Outcomes, and Consequences, eds. Amnon Cavari, Richard J. Powell, and Kenneth R. Mayer. New York: Routledge, 151-172. Congressional Quarterly, Inc. Annually 1953-2019. “Presidential Support.” Congressional Quarterly Almanac. Washington, DC: Congressional Quarterly, Inc. Darowski, Adam. 2012. “Wins Above Average: Taking the “Replacement” out of WAR.” SBNATION: Beyond the Boxscore. https://www.beyondtheboxscore.com/2012/4/24/2971859/wins-above-average-taking-the-replacement-out- of-war Edwards, George C. III. 1976. “Presidential Influence in the House: Presidential Prestige as a Source of Presidential Power.” American Political Science Review 70 (March): 101-113. Edwards, George C. III. 1978. “Presidential Electoral Performance as a Source of Presidential Power.” American Journal of Political Science 22 (February): 152-168. Edwards, George C. III. 1980. Presidential Influence in Congress. San Francisco: W.H. Freeman. 25

Edwards, George C. III. 1989. At the Margins: Presidential Leadership of Congress. New Haven: Yale University Press. Edwards, George C. III. 2003. On Deaf Ears: The Limits of the Bully Pulpit. New Haven: Yale University Press. Fenno, Richard F. Jr. 1973. Congressmen in Committees. Boston: Little, Brown. Fenno, Richard F. Jr. 1978. Home Style: House Members and Their Districts. Boston: Little, Brown. Fleisher, Richard, and Jon R. Bond. 1977. “Presidential-Congressional Relations: The Effects of Party, Presidential Popularity, and Ideological Conflict on Presidential Support in the House.” Presented at the annual meeting of the Midwest Political Science Association, Chicago, IL April 21-23. Fleisher, Richard, and Jon R. Bond. 1983. “Assessing Presidential Support in the House: Lessons from Reagan and Carter.” Journal of Politics 45 (August): 745-58. Fleisher, Richard, and Jon R. Bond. 1992. “Assessing Presidential Support in the House II: Lessons from George Bush.” American Journal of Political Science 37 (May): 525-41. Fleisher, Richard, and Jon R. Bond. 2004. “The Shrinking Middle in the US Congress.” British Journal of Political Science 34 (July): 429-451. Fleisher, Richard, Jon R. Bond, and B. Dan Wood. 2008. “Which Presidents are Uncommonly Successful in Congress?” In Presidential Leadership: The Vortex of Power, eds. Bert A. Rockman and Richard W. Waterman. New York: Oxford University Press, pp. 191-214. Heitshusen, Valerie. 2019. “Speakers of the House: Elections, 1913-2019.” Congressional Research Service, RL30857. https://crsreports.congress.gov Jacobson, Gary C. 1989. “Strategic Politicians and the Dynamics of U.S. House Elections, 1946-86.” American Political Science Review 83 (September), pp. 773-793. Jacobson, Gary C. 1990. The Electoral Origins of Divided Government. Boulder, CO: Westview Press. Jacobson, Gary C. 2017. “The Triumph of Polarized Partisanship in 2016: Donald Trump's Improbable Victory.” Political Science Quarterly 132 (spring): 9-41. Jacobson, Gary C., and Jamie L. Carson. 2016. The Politics of Congressional Elections, 9th ed. Lanham, MD: Rowman & Littlefield. Jacobson, Gary C., and Samuel Kernell. 1983. Strategy and Choice in Congressional Elections. 2d. ed. New Haven, CT: Yale University Press. Kingdon, John W. 1981. Congressmen’s Voting Decisions. 2nd Ed.. New York: Harper & Row. Lindbergh, Ben and Sam Miller. 2016. The Only Rule is It Has to Work: Our Wild Experiment in Building a New Kind of Baseball Team. New York: Henry Holt & Co. Mayhew, David R. 1974. Congress: The Electoral Connection. New Haven, CT: Yale University Press. Neustadt, Richard E. 1960. Presidential Power. New York: Wiley. Poole, Keith. T. 2016. “The Polarization of the Congressional Parties.” Voteview.com: Political Polarization Page, http://voteview.com/political_polarization_2015.htm. Updated 30 January 2016. (Accessed August 9, 2019). Pritchard, Anita. 1986. “An Evaluation of CQ Presidential Support Scores: The Relationship between Presidential Election Results and Congressional Voting Decisions.” American Journal of Political Science 30 (May): 480-495. Shafer, Byron E. 2016. The American Political Pattern: Stability and Change, 1932-2016. Lawrence: University of Kansas Press. Teodoro, Manuel P. and Jon R. Bond. 2017. “Presidents, Baseball, and Wins Above Expectations: What Can Sabermetrics Tell Us about Presidential Success? Or why Lyndon Johnson is like Joe Torre and Ronald Reagan is like Bobby Cox,” PS: Political Science and Politics 50(2): 339-346. Trump, Donald J. with Tony Schwartz. 1987. Trump: The Art of the Deal. New York: Random House. Weisberg, Herbert F. 1978. “Evaluating Theories of Congressional Roll-Call Voting.” American Journal of Political Science 22 (August): 554-577. Zimbalist, Andrew & Baumer, Benjamin. 2014. The Sabermetric Revolution. Philadelphia: University of Pennsylvania Press.

26

Appendix

Table A-1: Outliers with Support Above or Below Expectations Donald Trump 115th Congress (2017-18) Member PSS %SAE SAE_stdz DW-1 Raúl Labrador (R-ID) 58 -27.53 -2.03 0.7 ran for Governor Thomas Massie (R-KY) 43 -42.10 -3.10 0.7 reelected Justin Amash (R-MI) 37 -44.36 -3.27 0.6 Reelected; switched parties 2019 Walter B. Jones Jr. (R-NC)* 34 -53.22 -3.92 0.2 Reelected; libertarian Mark Sanford (R-SC) 53 -28.64 -2.11 0.7 defeated in primary

Tom O'Halleran (D-AZ) 70 37.34 2.75 -0.2 reelected Kyrsten Sinema (D-AZ)* 61 37.73 2.78 -0.1 ran for Senate Ami Bera (D-CA) 67 36.81 2.71 -0.2 reelected Jim Costa (D-CA) 59 30.86 2.27 -0.2 reelected Salud Carbajal (D-CA) 59 30.65 2.26 -0.3 reelected Lou Correa (D-CA) 57 32.35 2.38 -0.3 reelected Al Lawson (D-FL) 57 29.68 2.19 -0.3 reelected Stephanie Murphy (D-FL) 73 41.99 3.09 -0.2 reelected Sanford Bishop (D-GA) 62 32.01 2.36 -0.3 reelected Brad Schneider (D-IL) 66 39.50 2.91 -0.2 reelected Collin Peterson (D-MN)* 70 35.40 2.61 -0.1 reelected Jacky Rosen (D-NV) 63 30.34 2.23 -0.2 ran for Senate Ann McLane Kuster (D-NH) 66 34.17 2.52 -0.3 reelected Josh Gottheimer (D-NJ) 77 44.34 3.27 -0.1 reelected Kathleen Rice (D-NY) 59 28.60 2.11 -0.3 reelected won special election Oct- 2017 to fill vacancy; ran and reelected Conor Lamb (D-PA) 67 30.65 2.26 -0.1 in new 14th CD in general election in 2018 Jim Cooper (D-TN) 57 28.24 2.08 -0.2 reelected Henry Cuellar (D-TX)* 68 45.17 3.33 -0.2 reelected; primary target 2020 *PSS and SAE is the mean from both sessions of Congress; DW-1 in bold/ital. indicates member is a moderate ( between ±2.49; or ideological misfit)

Barack Obama 113th Congress (2013-14) Member PSS %SAE SAE_stdz DW-1 Ron Barber (D-AZ)* 55 -30.09 -2.22 -0.1 Kyrsten Sinema (D-AZ)* 55 -30.63 -2.26 -0.1 Patrick Murphy (D-FL) 50 -35.34 -2.60 -0.2 Joe Garcia (D-FL) 57 -27.88 -2.05 -0.2 John Barrow (D-GA)* 29 -54.11 -3.99 -0.1 Gary Peters (D-MI)* 65 -29.08 -2.14 -0.2 Collin Peterson (D-MN) 17 -67.44 -4.97 -0.1 Sean Patrick Maloney (D-NY) 56 -28.44 -2.09 -0.2 Bill Owens (D-NY) 56 -30.83 -2.27 -0.2 Daniel Maffei (D-NY) 61 -27.32 -2.01 -0.2 Mike McIntyre (D-NC) 28 -53.05 -3.91 -0.1 Mike McIntyre (D-NC) 22 -61.10 -4.51 -0.1 Pete Gallego (D-TX)* 53 -31.94 -2.35 -0.2 Henry Cuellar (D-TX) 45 -44.21 -3.26 -0.2 Jim Matheson (D-UT)* 28 -51.41 -3.79 -0.1 Nick Rahall (D-WV) 30 -51.16 -3.77 -0.3

Zero significant over-supporters Barack Obama 111th Congress (2009-10) Bobby Bright (D-AL) 51 -30.56 -2.25 0.1 Gene Taylor (D-MS)* 47 -32.50 -2.40 0.0

27

Michael Castle (R-DE) 62 31.41 2.31 0.2 Joseph Cao (R-LA)* 69 31.12 2.30 0.1 Vern Ehlers (R-MI) 55 28.54 2.10 0.3 Candice Miller (R-MI) 56 30.02 2.21 0.3 Frank LoBiondo (R-NJ) 68 39.39 2.90 0.2 Chris Smith (R-NJ) 65 39.73 2.93 0.2 Peter King (R-NY) 54 28.73 2.12 0.3 Walter Jones (R-NC) 51 32.43 2.39 0.2 Mike Turner (R-OH) 61 35.50 2.61 0.3 Steve LaTourette (R-OH) 63 36.54 2.69 0.2 Tim Murphy (R-PA)* 59 36.30 2.67 0.3

George W. Bush 109th Congress (2005-06) Member PSS %SAE SAE_stdz DW-1 Timothy V. Johnson (R-IL)* 54 -30.30 -2.23 0.3 Jim Leach (R-IA) 46 -33.62 -2.48 0.1 Wayne Gilchrest (R-MD) 57 -27.52 -2.03 0.2 Walter B. Jones (R-NC) 53 -32.96 -2.43 0.2 Ron Paul (R-TX)* 37 -49.15 -3.62 0.9 Ran for President 1988 as Libertarian; returned to House as R 1996-2018

Bud Cramer (D-AL)* 69 33.89 2.50 -0.1 Artur Davis (D-AL) 53 27.91 2.05 -0.3 Switched parties 2012 D>R; returned to D 2018 Allen Boyd (D-FL) 62 29.06 2.14 -0.2 Sanford Bishop (D-GA) 63 31.76 2.34 -0.3 John Barrow (D-GA) 65 33.55 2.47 -0.1 Charlie Melancon (D-LA) 72 37.16 2.74 -0.2 Mike McIntyre (D-NC) 63 29.22 2.15 -0.1 Dan Boren (D-OK)* 75 40.54 2.99 -0.1 Lincoln Davis (D-TN)* 68 33.26 2.45 -0.2 Bart Gordon (D-TN) 63 27.52 2.03 -0.2 John S. Tanner (D-TN) 66 33.49 2.47 -0.2 Harold Ford, Jr. (D-TN) 55 32.24 2.37 -0.4 Henry Cuellar (D-TX) 85 52.06 3.83 -0.2 Jim Matheson (D-UT) 67 28.34 2.09 -0.1 George W. Bush 107th Congress (2001-02) Ron Paul (R-TX)* 50 -32.77 -2.41 0.9

Robert E. Cramer (D-AL) 67 29.31 2.16 -0.1 William Lipinski (D-IL) 61 28.48 2.10 -0.2 Ken Lucas (D-KY)* 80 40.35 2.97 -0.1 Christopher John (D-LA) 69 31.11 2.29 -0.1 Voted for Hastert (R-IL) for Speaker, stripped of his committee James Traficant (D-OH) 81 49.75 3.66 -0.1 assignments. Expelled in 2002 after conviction for campaign fraud. Ralph Hall (D-TX)* 78 34.98 2.58 0.1 Switched parties 2004 D>R

Bill Clinton 105th Congress (1997-98) DW- Member PSS %SAE SAE_stdz 1 William Lipinski (D-IL)* 46 -33.89 -2.50 -0.2 Christopher John (D-LA) 50 -29.88 -2.20 -0.1 James A. Barcia (D-MI) 45 -34.79 -2.56 -0.2 Gene Taylor (D-MS)* 33 -41.13 -3.03 0.0 Ike Skelton (D-MO) 47 -28.87 -2.13 -0.2 Pat Danner (D-MO)* 44 -33.85 -2.49 -0.2 Mike McIntyre (D-NC) 45 -31.36 -2.31 -0.1 Marcy Kaptur (D-OH) 49 -31.46 -2.32 -0.4 James Traficant (D-OH)* 42 -40.88 -3.01 -0.1 Ralph Hall (D-TX)* 29 -45.60 -3.36 0.1 Switched parties 2004 D>R 28

Virgil Goode (D-VA)* 28 -48.93 -3.60 0.1 Switched parties 2000 D>I; 2002 I>R

Connie Morella (R-MD)* 72 32.09 2.36 0.0 Bill Clinton 103rd Congress (1993-94) Gary A. Condit (D-CA) 50 -29.76 -2.19 -0.1 W.J. Billy Tauzin (D-LA) 48 -31.70 -2.33 0.0 Switched parties 1995 D>R Gene Taylor (D-MS) 48 -27.40 -2.02 0.0

Michael Huffington (R-CA) 68 32.41 2.39 0.3 Stephen Horn (R-CA)* 67 29.78 2.19 0.2 Gary A. Franks (R-CT) 72 39.00 2.87 0.3 Nancy L. Johnson (R-CT)* 68 32.68 2.41 0.1 Michael N. Castle (R-DE) 71 34.62 2.55 0.2 Tillie K. Fowler (R-FL) 63 33.60 2.47 0.3 Ileana Ros-Lehtinen (R-FL)* 59 30.37 2.24 0.2 Lincoln Diaz-Balart (R-FL)* 61 33.04 2.43 0.2 E. Clay Shaw, Jr. (R-FL) 63 27.12 2.00 0.3 Fred Grandy (R-IA) 61 28.06 2.07 0.3 Jan Meyers (R-KS) 70 35.83 2.64 0.2 Wayne T. Gilchrest (R-MD) 64 31.19 2.30 0.2 Constance Morella (R-MD)* 75 36.83 2.71 0.0 Peter I. Blute (R-MA) 68 30.05 2.21 0.2 Peter G. Torkildsen (R-MA) 73 35.49 2.61 0.2 Jim Saxton (R-NJ) 63 28.57 2.10 0.2 Marge Roukema (R-NJ) 67 36.01 2.65 0.2 Dean Gallo (R-NJ)* 65 35.26 2.60 0.2 Rick A. Lazio (R-NY) 72 37.78 2.78 0.2 Susan Molinari (R-NY) 60 27.56 2.03 0.3 Hamilton Fish, Jr. (R-NY) 62 28.85 2.12 0.1 Benjamin Gilman (R-NY)* 70 35.53 2.62 0.0 Sherwood Boehlert (R-NY)* 73 39.58 2.91 0.1 James T. Walsh (R-NY) 70 34.82 2.56 0.2 Amo Houghton (R-NY) 72 38.84 2.86 0.2 Alex McMillan (R-NC) 61 31.24 2.30 0.3 Paul Gillmor (R-OH) 64 31.19 2.30 0.3 Curt Weldon (R-PA) 66 32.34 2.38 0.2 James C. Greenwood (R-PA) 69 34.51 2.54 0.2 Joseph M. McDade (R-PA)* 69 35.35 2.60 0.1 Ronald Machtley (R-RI)* 72 32.97 2.43 0.1 Herbert H. Bateman (R-VA) 60 29.35 2.16 0.2

George H.W. Bush 101st Congress (1989-90) Name PSS SAE SAE-stdz DW-1 Christopher Shays (R-CT)* 35 -40.81 -3.00 0.1 John G. Rowland (R-CT) 42 -34.32 -2.53 0.2 Patricia Saiki (R-HI) 43 -29.68 -2.19 0.1 Jim Jontz (D-IN) 14 -31.30 -2.30 -0.4 James A. Leach (R-IA) 39 -33.61 -2.47 0.1 Olympia J. Snowe (R-ME) 48 -27.17 -2.00 0.1 Constance Morella (R-MD)* 34 -38.54 -2.84 0.0 Silvio O. Conte (R-MA) 31 -40.95 -3.02 0.0 Robert W. Davis (R-MI) 46 -29.23 -2.15 0.1 Chris Smith (R-NJ) 43 -32.49 -2.39 0.2 Marge Roukema (R-NJ) 50 -28.91 -2.13 0.2 Matthew J. Rinaldo (R-NJ) 48 -28.85 -2.12 0.0 Robert J. Mrazek (D-NY) 16 -27.24 -2.01 -0.3 S. William Green (R-NY) 41 -28.19 -2.08 0.0 29

Hamilton Fish, Jr. (R-NY) 45 -32.37 -2.38 0.1 Benjamin Gilman (R-NY)* 39 -36.90 -2.72 0.0 Sherwood Boehlert (R-NY) 40 -35.57 -2.62 0.1 James T. Walsh (R-NY) 45 -30.18 -2.22 0.2 Frank Horton (R-NY) 33 -42.19 -3.11 0.0 Ronald K. Machtley (R-RI) 38 -34.15 -2.51 0.1 Claudine Schneider (R-RI)* 34 -38.22 -2.81 0.0 John Wiley Bryant (D-TX) 13 -27.13 -2.00 -0.4 Peter Smith (R-VT) 37 -37.66 -2.77 0.1

Doug Barnard, Jr. (D-GA) 74 27.14 2.00 0.0 Thomas “Jerry” Huckaby (D-LA) 77 31.11 2.29 0.0 G.V. Montgomery (D-MS) 78 31.19 2.30 0.0 Mike Parker (D-MS) 76 31.37 2.31 0.0 Switched parties 1995 D>R Charles W. Stenholm (D-TX) 72 27.34 2.01 0.0

Ronald Reagan 99th Congress (1985-86) SAE- Name PSS SAE DW-1 stdz Don Young (R-AK) 53 -28.12 -2.07 0.3 Sam Gejdenson (D-CT) 13 -31.42 -2.31 -0.4 Stewart B. McKinney (R-CT)* 33 -45.48 -3.35 0.0 Nancy L. Johnson (R-CT) 50 -29.00 -2.13 0.1 Cecil Heftel (D-HI) 9 -33.95 -2.50 -0.3 Marty Russo (D-IL) 19 -27.16 -2.00 -0.2 Lane Evans (D-IL) 13 -29.23 -2.15 -0.5 James A. Leach (R-IA)* 41 -34.31 -2.53 0.1 T. Cooper Evans (R-IA) 43 -33.29 -2.45 0.2 John R. McKernan Jr. (R-ME)* 47 -30.04 -2.21 0.1 Olympia J. Snowe (R-ME)* 46 -31.69 -2.33 0.1 Barbara A. Mikulski (D-MD) 12 -29.00 -2.13 -0.4 Silvio O. Conte (R-MA)* 32 -42.60 -3.14 0.0 Joseph D. Early (D-MA) 14 -29.09 -2.14 -0.3 Edward J. Markey (D-MA) 12 -29.03 -2.14 -0.5 Howard Wolpe (D-MI) 16 -28.92 -2.13 -0.4 Paul B. Henry (R-MI) 43 -36.06 -2.65 0.3 Dale E. Kildee (D-MI) 13 -29.33 -2.16 -0.4 Robert William Davis (R-MI)* 49 -28.43 -2.09 0.1 David E. Bonior (D-MI) 17 -29.33 -2.16 -0.5 Dennis M. Hertel (D-MI) 14 -30.77 -2.27 -0.3 William L. Clay (D-MO) 9 -27.54 -2.03 -0.5 John Patrick Williams (D-MT) 13 -31.08 -2.29 -0.3 Chris Smith (R-NJ)* 46 -31.68 -2.33 0.2 Marge Roukema (R-NJ) 49 -31.71 -2.33 0.2 Matthew J. Rinaldo (R-NJ) 41 -36.82 -2.71 0.0 Thomas J. Downey (D-NY) 18 -27.97 -2.06 -0.4 Robert J. Mrazek (D-NY) 18 -27.45 -2.02 -0.3 S. William Green (R-NY)* 37 -34.52 -2.54 0.0 Hamilton Fish Jr. (R-NY)* 46 -34.10 -2.51 0.1 Benjamin A. Gilman (R-NY)* 45 -33.30 -2.45 0.0 Sherwood Boehlert (R-NY)* 44 -34.77 -2.56 0.1 Frank Horton (R-NY)* 30 -47.83 -3.52 0.0 Stan Lundine (D-NY) 19 -27.66 -2.04 -0.3 Tony P. Hall (D-OH) 14 -28.60 -2.11 -0.3 Jim Traficant (D-OH) 10 -28.60 -2.10 -0.1 James H. Weaver (D-OR) 9 -33.10 -2.44 -0.3 Peter H. Kostmayer (D-PA) 17 -28.16 -2.07 -0.3 Lawrence Coughlin (R-PA)* 50 -27.48 -2.02 0.2 30

Doug Walgren (D-PA) 14 -29.78 -2.19 -0.2 Tom Ridge (R-PA)* 46 -29.61 -2.18 0.2 William F. Clinger (R-PA) 51 -27.98 -2.06 0.2 Claudine Schneider (R-RI)* 34 -41.62 -3.06 0.0 James M. Jeffords (R-VT)* 38 -38.94 -2.87 0.0 Switched parties 2001 flipped Senate to Dems

Dan Daniel (D-VA) 73 28.08 2.07 -0.2 Bill Nelson (D-FL) 74 27.13 2.00 0.2 Ronald Reagan 97th Congress (1981-82) John L. Burton (D-CA) 18 -28.96 -2.13 -0.4 Ronald V. Dellums (D-CA) 17 -27.72 -2.04 -0.6 Lawrence Joseph DeNardis (R- 41 -29.99 -2.21 0.0 CT) Stewart B. McKinney (R-CT) 43 -28.09 -2.07 0.0 Margaret M. Heckler (R-MA) 38 -31.74 -2.34 0.0 Harold C. Hollenbeck (R-NJ) 42 -30.44 -2.24 0.0 Robert W. Edgar (D-PA) 23 -27.16 -2.00 -0.3 Allen Edward Ertel (D-PA) 23 -28.09 -2.07 -0.2 Claudine Schneider (R-RI) 40 -27.33 -2.01 0.0 James M. Jeffords (R-VT) 43 -27.28 -2.01 0.0 Switched parties 2001 flipped Senate to Dems

Richard Shelby (D-AL) 78 30.73 2.26 0.0 Bob Stump (D-AZ)* 83 30.37 2.01 0.3 Switched parties 1982 D>R Andy Ireland (D-FL)* 80 29.15 2.30 0.0 Switched parties 1984 D>R Larry McDonald (D-GA)* 82 33.81 2.37 0.9 Doug Barnard Jr. (D-GA) 79 32.60 2.40 0.0 Gillespie V. Montgomery (D- 78 29.14 2.23 0.0 MS)* Phil Gramm (D-TX)* 82 32.18 2.05 0.2 Switched parties 1983 D>R Dan Daniel (D-VA)* 79 29.06 2.16 0.2

Jimmy Carter 95th Congress (1977-78) Name PSS SAE SAE-stdz DW-1 Bill Nichols (D-AL) 35 -34.16 -2.52 0.0 Bob Stump (D-AZ)* 28 -37.58 -2.77 0.3 Switched parties 1982 D>R Eldon D. Rudd (R-AZ) 18 -31.30 -2.30 0.4 William V. Chappell Jr. (D-FL) 32 -35.22 -2.59 -0.1 Richard Kelly (R-FL) 23 -28.01 -2.06 0.5 Dawson Mathis (D-GA) 41 -31.11 -2.29 0.0 Jack T. Brinkley (D-GA) 44 -27.62 -2.03 -0.1 Jack Flynt (D-GA)* 35 -37.81 -2.78 0.0 Lawrence P. McDonald (D-GA)* 20 -51.98 -3.83 0.9 Steve Symms (R-ID) 15 -33.76 -2.49 0.7 George V. Hansen (R-ID) 16 -32.56 -2.40 0.6 Philip M. Crane (R-IL) 13 -34.39 -2.53 0.7 Joe Waggonner (D-LA)* 30 -36.48 -2.69 0.0 Jerry Huckaby (D-LA) 35 -31.60 -2.33 0.0 John B. Breaux (D-LA) 32 -38.09 -2.80 -0.1 Robert Bauman (R-MD) 20 -30.89 -2.27 0.5 Marjorie Holt (R-MD) 21 -29.84 -2.20 0.4 David R. Bowen (D-MS) 38 -29.21 -2.15 -0.1 Gillespie V. Montgomery (D-MS)* 35 -32.67 -2.41 0.0 Richard Ichord Jr. (D-MO)* 36 -31.05 -2.29 0.0 Harold L. Runnels (D-NM)* 32 -35.29 -2.60 0.1 John M. Ashbrook (R-OH) 18 -32.39 -2.38 0.6 Ted Risenhoover (D-OK) 31 -36.53 -2.69 -0.2 Wes Watkins (D-OK)* 39 -33.12 -2.44 -0.1 31

Glenn English (D-OK)* 34 -32.34 -2.38 0.0 Sam B. Hall (D-TX)* 32 -38.37 -2.82 0.1 James M. Collins (R-TX) 19 -27.28 -2.01 0.7 H. Ray Roberts (D-TX)* 37 -31.61 -2.33 -0.1 William R. Poage (D-TX)* 33 -36.76 -2.71 -0.1 Kika de la Garza, II (D-TX)* 41 -31.17 -2.30 -0.3 Richard C. White (D-TX) 39 -27.65 -2.04 -0.1 Omar T. Burleson (D-TX)* 29 -41.07 -3.02 0.0 Robert Gammage (D-TX)* 39 -28.62 -2.11 0.0 Abraham Kazen (D-TX)* 41 -29.80 -2.19 -0.2 Dale Milford (D-TX)* 29 -38.75 -2.85 0.0 David E. Satterfield III (D-VA) 28 -39.47 -2.91 0.3 Robert Daniel (R-VA) 23 -29.96 -2.21 0.3 Dan Daniel (D-VA)* 28 -40.04 -2.95 0.2

Pete McCloskey (R-CA) 78 27.46 2.02 0.0 Switched parties R>D 2007 after leaving Congress Stewart Brett McKinney (R-CT) 80 33.87 2.49 0.0 Millicent Fenwick (R-NJ) 79 29.24 2.15 0.1 Charles W. Whalen Jr. (R-OH)* 86 36.43 2.68 -0.1

Richard M. Nixon 93rd Congress (1973-74) Name PSS SAE SAE-stdz DW-1 John L. Burton (D-CA) 14 -40.33 -2.97 -0.4 Gilbert Gude (R-MD) 42 -27.21 -2.00 0.0 Margaret Heckler (R-MA) 40 -27.39 -2.02 0.0 James J. Howard (D-NJ) 22 -31.95 -2.35 -0.4 Ogden R. Reid (D-NY)* 25 -29.71 -2.19 -0.4 Switched parties R>D 1972 Joseph M. McDade (R-PA) 43 -28.57 -2.10 0.1 John H. Dent (D-PA) 23 -29.03 -2.14 -0.4

Zero significant over-supporters Richard M. Nixon 91st Congress (1969-70) John G. Schmitz (R-CA) 39 -30.98 -2.28 0.9 Phil Crane (R-IL) 38 -30.39 -2.24 0.7 Harold R. Gross (R-IA) 36 -31.56 -2.32 1.0

Bob Wilson (R-CA) 98 29.37 2.16 0.3 John B. Anderson (R-IL) 95 27.17 2.00 0.2 Ran for Pres as Independent in 1980 Henry P. Smith III (R-NY) 92 27.40 2.02 0.2 Buz Lukens (R-OH) 95 27.85 2.05 0.5

Lyndon Johnson 89th Congress (1965-66) Name PSS SAE SAE-stdz DW-1 George W. Andrews (D-AL) 36 -29.62 -2.18 0.0 Ezekiel C. Gathings (D-AR) 46 -29.15 -2.15 0.0 James A. Haley (D-FL)* 32 -38.08 -2.80 0.1 G. Elliott Hagan (D-GA) 39 -29.69 -2.19 -0.1 Maston E. O'Neal (D-GA)* 36 -30.19 -2.22 0.0 F. Edward Hébert (D-LA) 40 -31.26 -2.30 -0.1 Otto Passman (D-LA)* 34 -28.95 -2.13 -0.1 Speedy O. Long (D-LA) 39 -29.18 -2.15 0.0 Thomas Abernethy (D-MS)* 29 -33.59 -2.48 0.1 Jamie L. Whitten (D-MS)* 31 -31.00 -2.29 -0.2 John Bell Williams (D-MS)* 25 -36.73 -2.71 0.1 William M. Colmer (D-MS) 29 -33.98 -2.51 0.1 Paul C. Jones (D-MO) 38 -37.04 -2.73 -0.1 Walter S. Baring (D-NV)* 37 -37.51 -2.76 -0.1 32

Walter B. Jones (D-NC) 40 -36.60 -2.69 -0.1 Lawrence H. Fountain (D-NC)* 44 -31.77 -2.34 0.0 David N. Henderson (D-NC) 42 -32.29 -2.38 -0.1 Ralph J. Scott (D-NC) 41 -31.30 -2.30 0.0 Alton A. Lennon (D-NC)* 36 -39.80 -2.93 0.0 Basil L. Whitener (D-NC) 46 -27.25 -2.01 0.0 Robert T. Ashmore (D-SC)* 39 -31.23 -2.30 0.1 John Dowdy (D-TX)* 40 -36.42 -2.68 0.1 Omar T. Burleson (D-TX)* 48 -28.85 -2.12 0.0 O. Clark Fisher (D-TX)* 43 -32.89 -2.42 0.0 Joe R. Pool (D-TX) 48 -28.54 -2.10 0.0 David Satterfield III (D-VA)* 38 -32.66 -2.41 0.3 Watkins M. Abbitt (D-VA)* 37 -34.87 -2.57 0.1 William M. Tuck (D-VA)* 33 -38.09 -2.80 0.2 John O. Marsh (D-VA)* 41 -31.34 -2.31 0.1 Howard W. Smith (D-VA) 40 -33.24 -2.45 0.0

Stanley R. Tupper (R-ME)* 89 40.36 2.97 0.0 Seymour Halpern (R-NY)* 82 36.09 2.66 -0.1 John Lindsay (R-NY) 94 44.18 3.25 0.0 Ogden R. Reid (R-NY)* 82 34.99 2.58 -0.1 Switched parties R>D 1972 Frank Horton (R-NY) 77 27.82 2.05 0.0 Richard Schweiker (R-PA) 73 28.43 2.09 0.0 Robert J. Corbett (R-PA) 73 27.62 2.03 0.1

John F. Kennedy 87th Congress (1961-62) Name PSS SAE SAE-stdz DW-1 Dale Alford (D-AR) 28 -46.85 -3.45 0.0 Catherine Dorris Norrell (D-AR) 47 -29.26 -2.15 -0.1 James A. Haley (D-FL)* 36 -34.05 -2.51 0.1 Tic Forrester (D-GA) 43 -34.18 -2.52 0.0 John J. Flynt (D-GA) 43 -36.60 -2.69 0.0 James C. Davis (D-GA) 22 -51.59 -3.80 0.1 Iris Blitch (D-GA) 38 -40.07 -2.95 -0.1 Switched parties D>R 1964; segregationist Noah M. Mason (R-IL) 10 -30.42 -2.24 0.6 Joe Waggonner (D-LA) 33 -34.77 -2.56 0.0 Thomas G. Abernethy (D-MS)* 41 -35.92 -2.64 0.1 Jamie L. Whitten (D-MS)* 33 -44.07 -3.24 -0.2 John B. Williams (D-MS)* 30 -40.75 -3.00 0.1 W. Arthur Winstead (D-MS)* 31 -46.57 -3.43 0.0 William M. Colmer (D-MS)* 34 -42.29 -3.11 0.1 John H. Ray (R-NY) 12 -28.55 -2.10 0.4 L. Mendel Rivers (D-SC) 43 -27.70 -2.04 -0.1 John J. Riley (D-SC) 41 -28.16 -2.07 0.0 W.J. Bryan Dorn (D-SC)* 32 -44.38 -3.27 0.0 Robert T. Ashmore (D-SC) 31 -42.96 -3.16 0.1 John L. McMillan (D-SC)* 41 -33.19 -2.44 -0.1 Bruce R. Alger (R-TX)* 10 -29.44 -2.17 0.6 Olin E. Teague (D-TX) 47 -29.15 -2.15 -0.1 John V. Dowdy (D-TX)* 33 -41.54 -3.06 0.1 Omar Burleson (D-TX)* 41 -31.42 -2.31 0.0 O. Clark Fisher (D-TX)* 38 -33.88 -2.49 0.0 Robert R. Casey (D-TX)* 40 -30.35 -2.23 -0.1 Watkins M. Abbitt (D-VA)* 46 -29.42 -2.17 0.1 William M. Tuck (D-VA) 39 -33.50 -2.47 0.2 Howard W. Smith (D-VA) 39 -33.17 -2.44 0.0

William S. Mailliard (R-CA) 76 32.21 2.37 0.1 33

Dalip Singh Saund (D-CA) 100 29.13 2.14 -0.5 Stanley R. Tupper (R-ME) 80 38.46 2.83 0.0 Charles Mathias (R-MD) 74 31.41 2.31 0.0 William H. Bates (R-MA) 76 32.57 2.40 0.2 Al Quie (R-MN) 70 29.19 2.15 0.2 Walter Judd (R-MN) 78 36.39 2.68 0.1 Phillip Hart Weaver (R-NE) 68 29.36 2.16 0.2 Chester Earl Merrow (R-NH)* 78 35.94 2.65 0.1 William T. Cahill (R-NJ) 73 29.33 2.16 0.1 Florence P. Dwyer (R-NJ) 73 29.84 2.20 0.1 Frank C. Osmers (R-NJ) 71 29.50 2.17 0.2 George M. Wallhauser (R-NJ) 73 29.16 2.15 0.1 Seymour Halpern (R-NY)* 77 33.28 2.45 -0.1 John V. Lindsay (R-NY) 73 30.34 2.23 0.0 Paul A. Fino (R-NY)* 74 30.15 2.22 0.0 Edwin B. Dooley (R-NY) 70 29.11 2.14 0.2 Jessica M. Weis (R-NY) 70 28.35 2.09 0.2 Ed Edmondson (D-OK) 98 27.51 2.03 -0.3 John C. Kunkel (R-PA) 67 28.61 2.11 0.2 Robert T. Stafford (R-VT) 68 27.18 2.00 0.1 Ken Hechler (D-WV) 98 27.13 2.00 -0.3

Dwight D. Eisenhower 85th Congress (1957-58) Name PSS SAE SAE-stdz DW-1 William S. Mailliard (R-CA) 43 -29.47 -2.17 0.1 H. Allen Smith (R-CA) 38 -37.72 -2.78 0.4 Edgar W. Hiestand (R-CA)* 41 -31.32 -2.31 0.5 Glenard P. Lipscomb (R-CA) 45 -27.70 -2.04 0.4 James B. Utt (R-CA)* 42 -31.80 -2.34 0.5 Hamer H. Budge (R-ID)* 44 -29.26 -2.15 0.5 Emmet F. Byrne (R-IL) 40 -33.73 -2.48 0.3 William E. McVey (R-IL) 43 -31.35 -2.31 0.4 Harold R. Collier (R-IL) 40 -35.74 -2.63 0.4 Timothy P. Sheehan (R-IL) 43 -31.77 -2.34 0.3 Marguerite S. Church (R-IL) 43 -33.61 -2.48 0.3 Russell W. Keeney (R-IL) 27 -50.50 -3.72 0.4 Noah M. Mason (R-IL)* 33 -41.92 -3.09 0.6 Robert H. Michel (R-IL) 45 -30.12 -2.22 0.4 Sid Simpson (R-IL) 44 -27.89 -2.05 0.3 E. Ross Adair (R-IN)* 43 -31.13 -2.29 0.3 John V. Beamer (R-IN) 36 -36.96 -2.72 0.3 Earl Wilson (R-IN) 43 -29.49 -2.17 0.4 Charles B. Brownson (R-IN) 40 -33.59 -2.47 0.3 Harold R. Gross (R-IA)* 35 -37.67 -2.77 1.0 Ben F. Jensen (R-IA) 35 -38.40 -2.83 0.4 Errett P. Scrivner (R-KS) 44 -27.55 -2.03 0.5 Wint Smith (R-KS)* 34 -40.81 -3.01 0.6 Eugene Siler (R-KY) 34 -42.37 -3.12 0.3 Donald W. Nicholson (R-MA)* 40 -34.63 -2.55 0.4 August E. Johansen (R-MI)* 37 -37.49 -2.76 0.6 Clare E. Hoffman (R-MI)* 39 -36.31 -2.67 0.7 Joseph P. O'Hara (R-MN) 39 -35.07 -2.58 0.4 H. Carl Andersen (R-MN) 43 -28.27 -2.08 0.3 Arthur L. Miller (R-NE) 47 -28.17 -2.07 0.4 Albert H. Bosch (R-NY) 41 -34.19 -2.52 0.4 Ralph W. Gwinn (R-NY)* 40 -35.42 -2.61 0.5 J. Ernest Wharton (R-NY)* 49 -28.19 -2.08 0.4 Dean P. Taylor (R-NY) 47 -31.04 -2.29 0.2 Bernard W. Kearney (R-NY) 32 -44.85 -3.30 0.2 Clarence E. Kilburn (R-NY) 49 -27.79 -2.05 0.3 William R. Williams (R-NY) 48 -27.18 -2.00 0.4 34

John Taber (R-NY) 45 -31.45 -2.32 0.6 Daniel A. Reed (R-NY)* 45 -30.25 -2.23 0.5 Graham A. Barden (D-NC) 8 -34.73 -2.56 0.0 Otto Krueger (R-ND) 32 -41.21 -3.03 0.4 Gordon H. Scherer (R-OH) 39 -35.95 -2.65 0.5 Cliff Clevenger (R-OH) 41 -32.89 -2.42 0.6 John E. Henderson (R-OH)* 46 -28.06 -2.07 0.4 Frank T. Bow (R-OH)* 46 -27.32 -2.01 0.4 William E. Minshall (R-OH) 45 -30.36 -2.24 0.3 Page Belcher (R-OK) 47 -27.18 -2.00 0.3 Bruce R. Alger (R-TX)* 34 -39.59 -2.92 0.6 Will E. Neal (R-WV) 45 -27.60 -2.03 0.3 Lawrence H. Smith (R-WI) 40 -33.85 -2.49 0.5 William K. Van Pelt (R-WI) 41 -33.43 -2.46 0.4 Melvin R. Laird (R-WI) 42 -31.47 -2.32 0.4

Robert E. Jones (D-AL) 68 28.47 2.10 -0.4 Stewart Lee Udall (D-AZ) 89 38.85 2.86 -0.4 John E. Moss (D-CA) 77 29.13 2.14 -0.6 John F. Shelley (D-CA) 76 29.63 2.18 -0.5 George P. Miller (D-CA) 76 28.06 2.07 -0.4 Bernice F. Sisk (D-CA) 75 28.35 2.09 -0.4 Harlan Hagen (D-CA) 80 31.24 2.30 -0.3 Cecil R. King (D-CA) 78 29.23 2.15 -0.5 Chet Holifield (D-CA) 80 34.51 2.54 -0.5 Clyde Doyle (D-CA)* 78 31.64 2.33 -0.4 James Roosevelt (D-CA) 74 28.96 2.13 -0.6 Byron G. Rogers (D-CO) 81 31.27 2.30 -0.3 William L. Dawson (D-IL)* 80 36.33 2.68 -0.5 Barratt O'Hara (D-IL) 76 27.40 2.02 -0.5 John C. Kluczynski (D-IL) 77 28.36 2.09 -0.4 Thomas Joseph O'Brien (D-IL) 78 30.78 2.27 -0.4 Roland V. Libonati (D-IL) 80 35.62 2.62 -0.5 Thomas S. Gordon (D-IL)* 80 33.17 2.44 -0.5 Sidney R. Yates (D-IL) 79 29.91 2.20 -0.5 Charles A. Boyle (D-IL) 80 31.23 2.30 -0.3 Peter F. Mack (D-IL) 80 30.02 2.21 -0.3 Melvin Price (D-IL)* 80 34.29 2.52 -0.4 Ray J. Madden (D-IN) 77 28.46 2.10 -0.4 Edward Garmatz (D-MD) 80 31.54 2.32 -0.3 Samuel Friedel (D-MD) 81 31.99 2.36 -0.4 Edward Boland (D-MA) 80 29.76 2.19 -0.3 John W. McCormack (D-MA)* 78 33.21 2.45 -0.3 Future Speaker 87th-91st Cong Thaddeus M. Machrowicz (D-MI)* 76 35.73 2.63 -0.5 Charles C. Diggs (D-MI)* 78 34.90 2.57 -0.5 John Dingell (D-MI)* 71 27.64 2.03 -0.4 John Lesinski (D-MI) 74 27.75 2.04 -0.4 Eugene McCarthy (D-MN) 77 29.77 2.19 -0.4 Frank M. Karsten (D-MO)* 77 31.96 2.35 -0.5 Leonor Sullivan (D-MO)* 76 32.61 2.40 -0.4 Richard Bolling (D-MO) 76 28.30 2.08 -0.5 Charles Harrison Brown (D-MO) 78 27.56 2.03 -0.4 A.S.J. Carnahan (D-MO) 79 32.89 2.42 -0.4 Lee Metcalf (D-MT) 79 29.19 2.15 -0.5 Frank Thompson (D-NJ) 85 36.09 2.66 -0.5 Peter W. Rodino (D-NJ) 84 32.80 2.42 -0.4 Hugh J. Addonizio (D-NJ) 84 33.22 2.45 -0.4 Alfred D. Sieminski (D-NJ) 79 28.47 2.10 -0.4 Joseph Montoya (D-NM) 82 31.58 2.33 -0.3 Lester Holtzman (D-NY) 85 36.41 2.68 -0.5 35

Victor L. Anfuso (D-NY) 75 28.38 2.09 -0.5 Emanuel Celler (D-NY) 74 30.83 2.27 -0.5 Abraham J. Multer (D-NY) 77 32.07 2.36 -0.6 Adam Clayton Powell (D-NY)* 80 36.85 2.71 -0.8 Alfred E. Santangelo (D-NY) 78 29.42 2.17 -0.6 Leonard Farbstein (D-NY) 81 33.99 2.50 -0.6 Ludwig Teller (D-NY) 83 36.74 2.71 -0.6 Herbert Zelenko (D-NY)* 76 30.95 2.28 -0.5 James C. Healey (D-NY)* 75 32.68 2.41 -0.5 Isidore Dollinger (D-NY)* 75 33.07 2.44 -0.6 Leo W. O'Brien (D-NY) 80 30.23 2.23 -0.3 Thomas L. Ashley (D-OH) 79 30.04 2.21 -0.4 Charles A. Vanik (D-OH) 83 36.51 2.69 -0.4 Carl Albert (D-OK)* 73 28.26 2.08 -0.4 Future Speaker 92nd-94th Cong William A. Barrett (D-PA) 82 36.25 2.67 -0.5 Kathryn E. Granahan (D-PA) 84 38.68 2.85 -0.5 James A. Byrne (D-PA) 80 33.80 2.49 -0.4 Earl Chudoff (D-PA) 69 27.58 2.03 -0.6 Robert N.C. Nix (D-PA) 89 45.05 3.32 -0.6 William J. Green (D-PA)* 79 32.61 2.40 -0.5 George M. Rhodes (D-PA) 84 34.11 2.51 -0.4 Francis E. Walter (D-PA) 82 31.88 2.35 -0.2 Augustine B. Kelley (D-PA) 80 34.07 2.51 -0.4 Thomas E. Morgan (D-PA) 76 28.85 2.12 -0.4 Herman P. Eberharter (D-PA) 80 34.99 2.58 -0.4 Elmer J. Holland (D-PA)* 78 31.36 2.31 -0.5 John E. Fogarty (D-RI) 80 31.29 2.30 -0.3 Clement J. Zablocki (D-WI) 78 28.91 2.13 -0.4 Henry S. Reuss (D-WI) 77 28.63 2.11 -0.5 Dwight D. Eisenhower 83rd Congress (1953-54) Noah M. Mason (R-IL) 29 -46.72 -3.44 0.6 Harold R. Gross (R-IA) 26 -49.88 -3.67 1.0 Wint Smith (R-KS) 48 -30.63 -2.26 0.6 Clare E. Hoffman (R-MI) 35 -42.37 -3.12 0.7 Alvin E. O'Konski (R-WI) 32 -41.95 -3.09 0.1

Frank W. Boykin (D-AL) 69 28.04 2.06 -0.1 Carl Elliott (D-AL) 69 29.64 2.18 -0.4 Brooks Hays (D-AR) 71 27.25 2.01 -0.3 Cecil R. King (D-CA) 82 37.92 2.79 -0.5 Clyde Doyle (D-CA) 73 30.21 2.22 -0.4 Samuel W. Yorty (D-CA) 72 30.79 2.27 -0.3 Byron G. Rogers (D-CO) 75 29.19 2.15 -0.3 Courtney W. Campbell (D-FL) 81 33.27 2.45 -0.1 Carl Vinson (D-GA) 67 29.48 2.17 -0.2 F. Edward Hébert (D-LA) 71 27.11 2.00 -0.1 Tip O'Neill (D-MA) 69 28.45 2.09 -0.4 Future Speaker 95th – 99th Cong Alfred D. Sieminski (D-NJ) 70 27.49 2.02 -0.4 Antonio M. Fernández (D-NM) 76 30.70 2.26 -0.2 Louis B. Heller (D-NY) 71 30.60 2.25 -0.5 Robert T. Secrest (D-OH) 76 29.24 2.15 -0.1 Francis E. Walter (D-PA) 76 31.00 2.28 -0.2 L. Mendel Rivers (D-SC) 75 27.15 2.00 -0.1 Jere Cooper (D-TN) 68 28.22 2.08 -0.2 Sam Rayburn (D-TX) 74 32.41 2.39 -0.4 Speaker 82nd Cong; minority leader 83rd J. Vaughan Gary (D-VA) 76 29.41 2.17 -0.1

36

Table A-2: Outliers Who Served Under Presidents of Different Parties Cong Pres Name PSS SAE SAE-stdz DW-1 95 JEC + Stewart B. McKinney (R-CT) 80 33.87 2.49 0.0 97 RWR - Stewart B. McKinney (R-CT) 43 -28.09 -2.07 0.0 99 RWR-2 - Stewart B. McKinney (R-CT)* 33 -45.48 -3.35 0.0

99 RWR-2 - Nancy L. Johnson (R-CT) 50 -29.00 -2.13 0.1 103 WJC + Nancy L. Johnson (R-CT)* 68 32.68 2.41 0.1

89 LBJ + Frank Horton (R-NY) 77 27.82 2.05 0.0 99 RWR-2 - Frank Horton (R-NY)* 30 -47.83 -3.52 0.0 101 GHWB - Frank Horton (R-NY) 33 -42.19 -3.11 0.0

99 RWR-2 - Sherwood Boehlert (R-NY)* 44 -34.77 -2.56 0.1 101 GHWB - Sherwood Boehlert (R-NY) 40 -35.57 -2.62 0.1 103 WJC + Sherwood Boehlert (R-NY)* 73 39.58 2.91 0.1

99 RWR-2 - Hamilton Fish Jr. (R-NY)* 46 -34.10 -2.51 0.1 101 GHWB - Hamilton Fish, Jr. (R-NY) 45 -32.37 -2.38 0.1 103 WJC + Hamilton Fish, Jr. (R-NY) 62 28.85 2.12 0.1

99 RWR-2 - Benjamin A. Gilman (R-NY)* 45 -33.30 -2.45 0.0 101 GHWB - Benjamin A. Gilman (R-NY)* 39 -36.90 -2.72 0.0 103 WJC + Benjamin A. Gilman (R-NY)* 70 35.53 2.62 0.0

99 RWR-2 - Marge Roukema (R-NJ) 49 -31.71 -2.33 0.2 101 GHWB - Marge Roukema (R-NJ) 50 -28.91 -2.13 0.2 103 WJC + Marge Roukema (R-NJ) 67 36.01 2.65 0.2

99 RWR-2 - Chris Smith (R-NJ)* 46 -31.68 -2.33 0.2 101 GHWB - Chris Smith (R-NJ) 43 -32.49 -2.39 0.2 111 BHO + Chris Smith (R-NJ) 65 39.73 2.93 0.2

93 RMN-2 - Joseph M. McDade (R-PA) 43 -28.57 -2.10 0.1 103 WJC + Joseph M. McDade (R-PA)* 69 35.35 2.60 0.1

83 DDE - Noah M. Mason (R-IL) 29 -46.72 -3.44 0.6 85 DDE-2 - Noah M. Mason (R-IL)* 33 -41.92 -3.09 0.6 87 JFK - Noah M. Mason (R-IL) 10 -30.42 -2.24 0.6

91 RMN - Philip M. Crane (R-IL) 38 -30.39 -2.24 0.7 95 JEC - Philip M. Crane (R-IL) 13 -34.39 -2.53 0.7

101 GHWB - Constance A. Morella (R-MD)* 34 -38.54 -2.84 0.0 103 WJC + Constance A. Morella (R-MD)* 75 36.83 2.71 0.0

109 GWB-2 - Walter B. Jones (R-NC) 53 -32.96 -2.43 0.2 111 BHO + Walter B. Jones (R-NC) 51 32.43 2.39 0.2 115 DJT - Walter B. Jones (R-NC)* 34 -53.22 -3.92 0.2

85 DDE-2 - Bruce R. Alger (R-TX)* 34 -39.59 -2.92 0.6 87 JFK - Bruce R. Alger (R-TX)* 10 -29.44 -2.17 0.6

85 DDE-2 - William S. Mailliard (R-CA) 43 -29.47 -2.17 0.1 87 JFK + William S. Mailliard (R-CA) 76 32.21 2.37 0.1

89 LBJ + Ogden R. Reid (R-NY)* 82 34.99 2.58 -0.1 93 RMN-2 - Ogden R. Reid (D-NY) 25 -29.71 -2.19 -0.4

95 JEC - Larry McDonald (D-GA)* 20 -51.98 -3.83 0.9 97 RWR + Larry McDonald (D-GA)* 82 33.81 2.37 0.9

109 GWB-2 + John Barrow (D-GA) 65 33.55 2.47 -0.1 113 BHO-2 - John Barrow (D-GA)* 29 -54.11 -3.99 -0.1

83 DDE + F. Edward Hébert (D-LA) 71 27.11 2.00 -0.1 89 LBJ - F. Edward Hébert (D-LA) 40 -31.26 -2.30 -0.1

105 WJC-2 - Christopher John (D-LA) 50 -29.88 -2.20 -0.1 107 GWB + Christopher John (D-LA) 69 31.11 2.29 -0.1

37

95 JEC - Gillespie V. Montgomery (D-MS)* 35 -32.67 -2.41 0.0 97 RWR + Gillespie V. Montgomery (D-MS)* 78 29.14 2.23 0.0 101 GHWB + Gillespie V. Montgomery (D-MS) 78 31.19 2.30 0.0

105 WJC-2 - Mike McIntyre (D-NC) 45 -31.36 -2.31 -0.1 109 GWB-2 + Mike McIntyre (D-NC) 63 29.22 2.15 -0.1 113 BHO-2 - Mike McIntyre (D-NC) 25 -57.07 -4.21 -0.1

83 DDE + L. Mendel Rivers (D-SC) 75 27.15 2.00 -0.1 87 JFK - L. Mendel Rivers (D-SC) 43 -27.70 -2.04 -0.1

105 WJC-2 - Ralph Hall (D-TX)* 29 -45.60 -3.36 0.1 107 GWB + Ralph Hall (D-TX)* 78 34.98 2.58 0.1

109 GWB-2 + Henry Cuellar (D-TX) 85 52.06 3.83 -0.2 113 BHO-2 - Henry Cuellar (D-TX) 45 -44.21 -3.26 -0.2 115 DJT + Henry Cuellar (D-TX)* 68 45.17 3.33 -0.2

95 JEC - Dan Daniel (D-VA)* 28 -40.04 -2.95 0.2 97 RWR + Dan Daniel (D-VA)* 79 29.06 2.16 0.2 99 RWR-2 + Dan Daniel (D-VA) 73 28.08 2.07 0.2

99 RWR-2 - James Traficant (D-OH) 10 -28.60 -2.10 -0.1 105 WJC-2 - James Traficant (D-OH)* 42 -40.88 -3.01 -0.1 107 GWB + James Traficant (D-OH) 81 49.75 3.66 -0.1

105 WJC-2 - William Lipinski (D-IL)* 46 -33.89 -2.50 -0.2 107 GWB + William Lipinski (D-IL) 61 28.48 2.10 -0.2

113 BHO-2 - Collin Peterson (D-MN) 17 -67.44 -4.97 -0.1 115 DJT + Collin Peterson (D-MN)* 70 35.40 2.61 -0.1

95 JEC - Bob Stump (D-AZ)* 28 -37.58 -2.77 0.3 97 RWR + Bob Stump (D-AZ)* 83 30.37 2.01 0.3

113 BHO-2 - Kyrsten Sinema (D-AZ)* 55 -30.63 -2.26 -0.1 115 DJT + Kyrsten Sinema (D-AZ)* 61 37.73 2.78 -0.1

109 GWB-2 + Jim Matheson (D-UT) 67 28.34 2.09 -0.1 113 BHO-2 - Jim Matheson (D-UT)* 28 -51.41 -3.79 -0.1 *PSS and SAE is mean from both sessions of Congress; DW-1 in bold/ital. indicates member is a moderate ( between ±2.49; or ideological misfit)

38

Figure A-1: Residual Plots to Check for Heteroskedasticity