Gender Differences in Cooperative Environments?

This paper uses data on bill cosponsorship in the U.S. House of Representatives to estimate gender differences in cooperative behaviour. We find that among Democrats there is no significant gender gap in the number of cosponsors recruited, but women-sponsored bills tend to have fewer cosponsors from the opposite party. On the other hand, we find robust evidence that Republican women recruit more cosponsors and attract more bipartisan support on the bills that they sponsor. We interpret these results as evidence that cooperation is mostly driven by a commonality of interest, rather than gender per se.

Cosponsoring and Cashing In: US House Members’ Support for Punitive Immigration Policy and Financial Payoffs from the Private Prison Industry

The private prison industry is a multi-million-dollar industry that has increasingly profited from the detention of undocumented immigrants. As a government contractor, therefore, the industry has a natural interest in government decision making, including legislation that can affect its expansion into immigrant detention. In this article, we examine the relationship between campaign donations made on behalf of the private prison industry and an untested form of position taking—bill cosponsorship—in the US House of Representatives. We hypothesize the private prison industry will reward House members for taking positions that benefit the industry. We also hypothesize the private prison industry will also reward House members who incur greater political risk by taking positions out of sync with the party. To test our hypotheses, we focus on punitive immigration legislation that has the potential to increase the supply of immigrant detainees over the course of eight years. We find support for our second hypothesis, that private prison companies are more likely to reward House Democrats who cosponsor punitive immigration policies even after accounting for possible endogeneity. The findings have important implications regarding the relationship between House members and private interests.

Generative hypergraph clustering: From blockmodels to modularity

Hypergraphs are a natural modeling paradigm for networked systems with multiway interactions. A standard task in network analysis is the identification of closely related or densely interconnected nodes. We propose a probabilistic generative model of clustered hypergraphs with heterogeneous node degrees and edge sizes. Approximate maximum likelihood inference in this model leads to a clustering objective that generalizes the popular modularity objective for graphs. From this, we derive an inference algorithm that generalizes the Louvain graph community detection method, and a faster, specialized variant in which edges are expected to lie fully within clusters. Using synthetic and empirical data, we demonstrate that the specialized method is highly scalable and can detect clusters where graph-based methods fail. We also use our model to find interpretable higher-order structure in school contact networks, U.S. congressional bill cosponsorship and committees, product categories in copurchasing behavior, and hotel locations from web browsing sessions.

A Sum of Its Parts: Party Fit and Party Change in the U.S. House

Previous research has noted the transformation of the American parties since the 1970s, as exhibited in their increased ideological polarization and transformation on social issues like civil rights, abortion, and the environment. We contribute to the literature on party change by theoretically stressing the decentralized and individualistic nature of American parties, while using a measure of party change that is based on legislative behavior beyond roll call voting. Our paper uses social network analysis to analyze the parties from the 93rd to 110th Congresses, utilizing bill cosponsorship to define connections between members. Our analysis illustrates how the core of the party, that is, who are most central in the cosponsorship network, has changed over time. We find evidence that party centrality influenced retirement decisions, thereby reinforcing and contributing to party change.

The Reputations Legislators Build: With Whom Should Representatives Collaborate?

How do legislators build the reputations they use in bids for reelection? Do they use their personal reputations or associate with other legislators? And how do parties, coalitions, and institutions affect these decisions? Research on how electoral systems affect parties in legislatures frequently focuses on the extent to which electoral rules make legislators more or less ideologically convergent with respect to other members of the chamber—copartisan and not. However, finding equilibrium strategies is often possible only under restrictive institutional and spatial assumptions. Instead of viewing ideology spatially, we conceive of ideological reputations as currencies, used to purchase electoral support in transactions we liken to auctions. In our test of the model, we use bill cosponsorship patterns as an indicator of the reputations incumbents use to purchase electoral support. We show that under relatively common institutional conditions, legislators may have strong incentives to cultivate reputations they must share with their toughest electoral competitors.

Estimation and Inference Are Missing Data Problems: Unifying Social Science Statistics via Bayesian Simulation

Bayesian simulation is increasingly exploited in the social sciences for estimation and inference of model parameters. But an especially useful (if often overlooked) feature of Bayesian simulation is that it can be used to estimate any function of model parameters, including “auxiliary” quantities such as goodness-of-fit statistics, predicted values, and residuals. Bayesian simulation treats these quantities as if they were missing data, sampling from their implied posterior densities. Exploiting this principle also lets researchers estimate models via Bayesian simulation where maximum-likelihood estimation would be intractable. Bayesian simulation thus provides a unified solution for quantitative social science. I elaborate these ideas in a variety of contexts: these include generalized linear models for binary responses using data on bill cosponsorship recently reanalyzed in Political Analysis, item—response models for the measurement of respondent's levels of political information in public opinion surveys, the estimation and analysis of legislators' ideal points from roll-call data, and outlier-resistant regression estimates of incumbency advantage in U.S. Congressional elections

Dynamics of Cosponsorship

Electoral-connection theories of legislative politics view bill cosponsorship as low-cost position taking by rational legislators who communicate with target audiences (e.g., constituents) external to the legislature. Legislative signaling games suggest a view of bill cosponsorship in which early cosponsors attempt to communicate to target audiences (e.g., the median voter) within the legislature. Using data from the 103rd U.S. House of Representatives, we show that the timing of legislators' cosponsorship decisions are more supportive of cosponsorship as intralegislative signaling than as extralegislative position taking. First, policy extremists on both sides of the political spectrum are more likely than moderates to be initial endorsers of legislative initiatives. Second, extremist-moderate differences diminish over the course of bill histories.