Abstract
While scholars posit an electoral link between congressional approval and majority party electoral fortunes, it is unclear whether citizens are grounding their assessments of approval on policy or valence grounds, such as retrospective economic evaluations. Whereas it is commonly understood that there is an ideological component to constituents’ job approval of their individual members of Congress, in addition to a strong partisan effect, the ideological basis of institutional approval has not been established. Using cross-sectional and panel survey data, which allow for scaling citizens and the congressional parties in the same ideological space, I demonstrate that, distinct from the partisan basis of congressional approval, citizens’ ideological distance from the majority party has a separate and distinct effect. These results suggest that the link between congressional approval and majority party fortunes is rooted in the collective ideological representation provided by the legislative majority in an increasingly responsible U.S. Congress.
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Notes
CNN: Graham on passing tax reform: ’I think we’ll get there’
The post-conference committee vote to pass the bill was 224–201 in the U.S. House and 51–48 in the U.S. Senate. With the exception of 12 Republican defections in the House, the Republican tax bill passed on a straight party-line vote. Given the temporary nature of the individual and pass-through tax cuts, the Congressional Budget Office ruled that the post-conference Republican tax bill could pass under the budget reconciliation process, which only requires a simple majority in the Senate rather than the 60 vote threshold provided by the legislative filibuster (CBO 2017).
This is articulated in Senate Minority Leader Chuck Schumer’s (D-NY) remarks on the verge of passage in his official press release.
The Herald Sun (12/28/2017): Mitch McConnell says Congress can sell American people on tax reform
As a robustness check, I also evaluate the model using perceptual-based ideological scaling and survey cross-sectional data from 1980 to 2016 provided by the American National Election Study. The findings of the model, which can be found in the supporting information of this manuscript, hold in this context.
To that end, this is congruent with the argument popularized by Fenno (1978), that MCs have a strong incentive to “bash” Congress as a collective institution. With incumbents choosing to“run for Congress by running against it,” they are able to skirt collective accountability and focus on individual accountability, the notion of being evaluated as individuals rather than as members of a collective partisan team. In theory, this maximizes their chances of being re-elected by skirting responsibility for unpopular congressional policies.
Indeed, one of the consistent findings in the comparative literature is that macroeconomic outcomes are associated with partisan control of governments, with liberal governments passing more redistributive policies than conservative governments (Franzese 2002).
I should note that Jones (2013) shows that congressional approval may rise in the event of a significant majority party victory. In the context of the passage of the Affordable Care Act in the 111th Congress, Jones (2013) finds that passing healthcare reform raised approval amongst supporters of the bill (i.e., Democrats) and lowered it amongst opponents of the bill (i.e., Republicans). However, no evidence is found that these changes in approval brought about by healthcare reform stem from comprehensive ideological “outlooks.” (Jones 2013).
Indeed, with MCs being more extreme than even the partisan median voter in their district (Bafumi and Herron 2010), they may consider and act on policies that are even more extreme than the preferences of their co-partisans. As such, majority co-partisans may approve of Congress even though the majority may be passing legislation that is more ideologically extreme than their preferences.
Griffin (2011) finds in his review of aggregate congressional approval that the nadir of occurred in 2008. According to data from Gallup, the nadir of 9%, reached in November of 2013.
It is important to note that Jones and McDermott (2002) do not explicitly apply a spatial model to their analysis. They define ideological proximity as the absolute difference between respondent raw self-perceived ideological placement and their perception of the location of the majority party rather than proximity between the respondent and the two parties.
To that point, split control Congresses are a very rare phenomena. Since the 1914 midterm elections, the first election cycle in which the electorate elected both MCs and Senators, split Congresses only occurred from: 1931–1932/1981–1986 (Democratic House/Republican Senate) and 2001–2002/2011–2014 (Republican House/Democratic Senate). This makes for a total of 14 out of 102 years that featured a split control Congress.
This is usually done on the standard 7 point scale from 1 (very liberal) to 7 (very conservative).
Thus, the ideal point of respondents (\(x_{i}\)) can be articulated in the following form: \(x_{i} = \frac{z_{i (self)} - \alpha _{i}}{\beta _{i}}\) , where \(z_{i(self)}\) is raw self-placement on the ideological scale, \(\alpha _{i}\) is the shift distortion parameter, and \(\beta _{i}\) is the weight distortion parameter. Note that positive values of \(\alpha _{i}\) indicates over-placement of themselves and the stimuli on the scale while positive values of \(\beta _{i}\) (the weight parameter) indicates correct placement of the stimuli (i.e., placement of liberal stimuli to the left of the conservative stimuli) (Hare et al. 2015). Respondent ideal points (\(x_{i}\)) are recovered from citizen left-right placements of themselves and national stimuli consistently present over the survey cross-sectional years (i.e., placements of the Democratic party, the Republican party, and President Obama).
As Ramey (2016) mentions, the third step is simply a linear transformation which adjusts the subnational stimuli estimates to the overall space by assuming that estimates of party locations at the district and state-level are comparable to those estimated using the national-level sample. Moreover, this method accounts for the heterogeneity in perceptions of the two parties over subnational units.
To adjust for the potential time-varying dynamics, I use the national-level party stimuli to perform a linear transformation on the individual MC and Senator stimuli estimates to place all estimates in the same space over time. This transformation is minimal, given the lack of variation in the placements of the national Democratic and Republican parties from 2008 to 2016.
Moreover, it is important to note, that another contribution of Jessee’s (2016) model is the ability to jointly-scale citizens and legislators using a small amount of roll-call items and limitations in survey sample size. These points are significant given the flexibility of the model to jointly scale the CCES panel and their legislators and the large amount of measurement error which may present itself in using a small number of roll-call survey questions to jointly scale citizens and elites.
I estimate Aldrich–McKelvey ideal points using Poole et al.’s (2016) basicspace R package and, for the roll-call based ideal point estimation, I use Jackman’s (2017) pscl R package.
Citizen perceptual Aldrich–McKelvey ideal points & roll-call based ideal points are correlated at \(\rho = 0.62\).
The logistic regression model omits certain constituent and interaction terms for presentation purposes. The omitted constituent terms are: binary variables for partisan independents and periods of split-control of Congress (2011–2014). This allows for a base line comparison consistent with the presented hypotheses. As such, the partisanship omitted category are Republican voters, and the Congress-type omitted category indicates a year in which there is a Republican-controlled Congress (2015–2016).The model is specified with relevant survey weights. As such, the omitted interaction terms are: \((Indy \times DemCongress)\), \((Indy \times SplitCongress)\),\((Dem \times SplitCongress)\), & \((Proximity \times SplitCongress)\).
Throughout the entire pooled data series, Congress sports a weighted approve-disapprove rating of 21–79%. Reflecting the general unpopularity of Congress, the individual year weighted approval-disapproval rating is as follows: 21–79% (2008), 30–70% (2009), 24–76% (2010), 24–76% (2011), 18–82% (2012), 13–87% (2013), 18–82% (2014), 23–77% (2015), & 24–76% (2016).
The arrangement of split-control of Congress, as witnessed from 2011 to 2014, is a Democratic Senate and a Republican House. Democrats controlled the House & Senate from 2008 to 2010 and the Republicans controlled both congressional chambers from 2015 onward.
Full model results can be found in the Tables 3 and 4 of the appendix. I specify the pooled models with Eicker–Huber–White clustered standard errors by year-district. Full coding of the control variables can be found in the appendix. All model marginal effects are post-estimated using Leeper’s (2017) margins package in R.
The pre-election interviews are typically conducted in October and the post-election interviews are typically conducted in November. For more details on the panel survey see Schaffner and Ansolabehere (2015).
The panel dataset also reflects the general trend of congressional unpopularity found in the cross-sectional survey data with the following weighted approval-disapproval job ratings for each survey panel wave: 20–80% (2010), 14–86% (2012), and 11–89% (2014).
Ideally, one would want the three distinct Congress-types (Democratic, Republican, split) to be covered by the panel survey. Given the limitation in years here, the only comparison that can be evaluated is the comparison between a Democratic Congress and a split Congress.
The resulting congressional ideal points are correlated with first-dimension DW-Nominate at 0.93 for the House and 0.95 for the Senate. Citizen ideal points are correlated with raw 7 point self-placements at 0.76. These strong correlations provide face validity of the joint-scaling estimating procedure on the panel dataset.
Congressional approval in 2010 is correlated at 0.09 and 0.07 with approval in 2012 and 2014. There is no control for lagged partisanship given that partisanship is stable across the survey panel. Indeed, 2010 partisanship is correlated at 0.94 and 0.93 with partisan preferences in 2012 and 2014, respectively. Results of the panel models are articulated in Tables 3 and 4 of the appendix.
In this panel wave analysis, weaker retrospective economic evaluations lowers congressional approval by 7% in 2010, 15% in 2012, while being an significant predictor in 2014. This compliments the preceding pooled analysis by finding that ideological proximity is a more consistent predictor of congressional approval than valence economic evaluations.
To that end, the correlation between partisan affinity and estimated ideological ideal points presented are \(\rho =0.62\) for the Aldrich–McKelvey perceptual-based ideological measure and \(\rho = 0.66\) for the roll-call based joint scaling measure.
Montagnes, B. Pablo, Zachary Peskowitz, and Joshua McCrain. 2019. “Bounding Partisan Approval Rates under Endogenous Partisanship: Why High Presidential Partisan Approval May Not Be What It Seems.” Journal of Politics 81(1):321–326.
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Version of this paper presented at the 2018 Midwest Political Science Association Annual Meeting in Chicago, IL (April 5–8, 2018) and the 2018 UC Davis Institute for Social Sciences & Humanities Initiative Workshop in Berkeley, CA (April 13–14, 2018). I thank Walt Stone, Erik Engstrom, Chris Hare, Roi Zur, Soren Jordan, Leanne Powner, and participants of the Graduate Association of Political Science Students Research Workshop for comprehensive & helpful comments. Replication files can be found on the Political Behavior Replication Dataverse here: https://doi.org/10.7910/DVN/VQCGNW.
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Appendix
Appendix
Control Variable Coding Scheme for the CCES Cross-Sectional & Panel Models
Political Sophistication
The political sophistication measure is coded as a summated rating scale encompassing the following political participation and political knowledge items: attendance at political meetings, participation in putting up a political yard sign, participation in donating money to political candidates & causes, self-reported interested in political affairs, and correct recall of the following political stimuli: U.S. House majority party, U.S. Senate majority party, Governor, U.S. Representative, both U.S. Senators, and the majority party in both chambers of the state legislature. All of these variables, available for each year of the CCES cross-sectional surveys, are coded dichotomously, 1 for correct office recall/self-reported political participation and 0 for incorrect office recall/self-reported lack of political participation. This required recoding the interest into political affairs as a 1 if the respondent indicated following political affairs “most of the time” or “some of the time” or a 0 if the respondent indicated following political affairs “hardly at all” or “only now and then.” The survey panel models incorporate each of these indicators with the exception of the political indicator measuring interest in following political affairs. Instead, the survey panel variable incorporates a binary indicator if the respondent has worked on a political campaign during the election cycle, coded 1 if the respondent participated in this form of political activity and 0 if not. The panel wave also includes two voting validated measures if the respondent voted in the primary or general election during the electoral cycle, coded 1 if the respondent voted in the corresponding election or 0 if not. The resulting composite measure has a Cronbach’s alpha reliability coefficient of 0.82 for the CCES cross-sectional data and the 0.81, 0.74, & 0.76 for the 2012, 2014, & 2016 CCES panel data waves. The political sophistication variable is measured on a summated rating scale from 0 (low) to 1 (high) .
Congressional Delegation Approval
This variable is a summated rating scale, from 0 to 1, capturing the degree to which a citizen approves of the job performance of their congressional delegation (i.e., their member of Congress, their Senior U.S. Senator, and their Junior U.S. Senator). Each approval variable used in this summated scale of congressional delegation approval is dichotomous, coded 1 if a citizen approves of their legislator and 0 if the citizen disapproves. A score of 1 would indicate that a citizen approves of the job their entire delegation or, in other words, approves of the individual job performance of their U.S. Representative and both U.S. Senators.
Presidential Approval
This is an ordinal variable captures the degree to which a citizen approves of the job performance of President Barack Obama. This variable is coded on a scale of 1 (strongly disapprove) to 4 (strongly approve) for the CCES pooled model and on a dichotomous scale of 0 (disapprove) to 1 (approve) for the CCES panel models. The latter is due to the chronic lack of variation in non-extreme evaluations of presidential job approval (i.e., somewhat disapprove, somewhat approve) in the CCES panel sample. This coding decision does not change the substantive results presented. Given the incredibly polarized and endogenous nature of presidential approval to partisanship (Montagnes et al.)Footnote 33, the Democratic and Republican partisan panel models do not include the presidential approval covariate. Reflecting this salient point and pronounced lack of variation, President Obama’s approval rating ranges from 2-3% among Republican identifiers in the panel survey. This is hardly surprising, given that the CCES panel sample tends to include more politically sophisticated and active respondents than the full CCES Schaffner & Ansolabehere (2015).
Retrospective Economic Evaluations
This ordinal variable captures a citizen’s retrospective evaluation of the national economy. This variable is coded on a scale from − 2 (gotten much worse) to 2 (gotten much better).
Quality of Dyadic Representation
This variable captures the ideological divergence between a citizen’s ideological ideal point and their member of Congress. This variable is specified by taking the absolute difference between the ideological location of a member of Congress and a given respondent (i.e., constituent). Greater values indicate a greater ideological divergence between legislator and constituent. This measure is specified using Aldrich–McKelvey perceptual-based ideal points and roll-call based policy ideal points (Tables 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10).
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Algara, C. Congressional Approval and Responsible Party Government: The Role of Partisanship and Ideology in Citizen Assessments of the Contemporary U.S. Congress. Polit Behav 45, 33–73 (2023). https://doi.org/10.1007/s11109-021-09678-x
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DOI: https://doi.org/10.1007/s11109-021-09678-x