Abstract
How well can roll calls detect the causal impact of majority party agenda setting in Congress? Estimating the counterfactual required to assess the effects of majority party agenda setting is complicated by time-varying differences in the political environment and the fact that measures commonly used to control for compositional changes may themselves depend on the extent of agenda control being exercised. Using techniques popularized by recent work focused on causal inference, I characterize whether agenda changes occuring during changes in majority party control in the US House of Representatives are consistent with predictions from models of majority party agenda control. Comparing how the same members in consecutive Congresses are affected by changes in party control and using fixed effects to account for time-varying differences between consecutive Congresses helps isolate the changes in the agenda attributable to agenda setting. The analyses highlight the challenge in consistently estimating the effects of agenda control and suggest that although recent transitions produce patterns consistent with the predictions of agenda setting theories, the average effect over the post-Reconstruction period is harder to interpret as being produced by agenda control.
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Notes
It also is possible to estimate the elasticity between variables without relying on exogenous variation. Structural modeling, for example, while relatively rare in political science (but see, for example, Canen et al. 2019), adopts strong assumptions about theory, functional form and available measures to define a likelihood that directly estimates the elasticity.
To be clear, the record of observed roll calls does not necessarily reflect the record of congressional accomplishment (e.g., Schickler et al. 2010; Clinton and Lapinski 2011; Koger and Lebo 2017; Lee 2018)—especially in earlier periods. Focusing on agenda control in terms of observed votes necessarily combines two processes—the choice of which issues to consider and the choice of which issues to resolve by recorded roll call votes (see, for example, Lynch and Madonna 2012). That the characterizations and divisions revealed by roll call voting may differ from members’ policy preferences arguably highlights the question—can parties control the set of issues being voted upon to craft a party brand even if the brand is only a partial representation of actual preferences?
As Cox and McCubbins (2007, p. 42) argue, “No dimension j on which the status quo is preferred to the floor median by a majority of the majority party is ever scheduled for floor consideration”. In other words, we should observe floor activity only on those proposals that a majority of the majority party prefer to the status quo on a given issue dimension, j. That is, the probability of observing a roll call if a majority of the majority party prefers the status quo to proposal j is zero, and if a majority of the majority prefer proposal j to the status quo the probability not only presumably is greater than zero, but also presumably increasing in the level of majority party support.
If b is the location of the outcome associated with voting yea in the policy space and q is the location associated with voting nay, \(\kappa _{j}=(b+q)/2\).
The analysis assumes, of course, that the brand of a party is defined by the voting behavior of a majority of the party. If a party brand is able to be defined by the positions taken by party extremists, then such votes may be valuable for branding the opposition party. While it certainly is possible—if not plausible given the willingness of both parties to use the positions of extreme members to characterize one another—I follow existing interpretations and assume that party brands are defined by the voting behavior of a majority of party members.
In the analysis that follows, I use ideal points to summarize the propensity for members to vote together, on average, on the observed agenda regardless of their motivations. Because the probability that two members vote together on an issue is a function of the proximity of their estimated ideal points, a one-dimensional representation of ideal points summarizes the average likelihood that members will vote together, on the observed roll call votes. A unidimensional ideal point consequently is precisely the right measure for analyzing the ability of a party to create an agenda that fosters purposeful coalitions and splits.
The idea conceptually is similar to a design used by Nokken and Poole (2004) to evaluate whether members change their voting behavior over time.
Because unanimous and near-unanimous votes provide no and very little information for identifying the unknown parameters, respectively, such votes are omitted from the estimation of ideal points and midpoints. While they are uninformative for distinguishing between members’ ideal points—and therefore for quantifying the extent to which agenda control is used to unite or expose the parties—they arguably are relevant for characterizing the amount of political conflict that occurs—a Congress with 100 unanimous votes and 10 party-line votes arguably differs qualitatively from a Congress with 0 unanimous votes and 10 party-line votes. Ignoring such votes is unproblematic for studying agenda control because unanimous votes are not obviously related to the desire and ability of the majority party to establish a party brand, but that consideration is important for scholars studying the level of polarization or partisan contestation.
Although it is possible to derive the expected direction of the parameters in the presence of agenda control it difficult to know what the precise point estimate should be in light of the complications caused by the potential for theoretically valid votes to occur within the interval during periods when majority control changes.
While the effects for Republicans appear to be largervthan for Democrats (perhaps because of the Conservative Coalition), investigating the potential reasons for this difference is difficult given the available data.
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Prepared for the Conference on Causal Inference and American Political Development, University of Southern California, January 12–14, 2019. I thank conference participants—and especially Chris Tausanovitch, Jeff Jenkins, Nolan McCarty and Charles Stewart—for helpful feedback and reactions.
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Clinton, J.D. The effect of majority party agenda setting on roll calls. Public Choice 185, 459–483 (2020). https://doi.org/10.1007/s11127-019-00706-3
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DOI: https://doi.org/10.1007/s11127-019-00706-3