A Network-Based Measure of Cosponsorship Influence on Bill Passing in the United States House of Representatives

TL;DR

This paper introduces a network-based influence measure derived from cosponsorship dynamics to predict bill passage in the US House, showing it outperforms standard centrality metrics in explaining legislative success.

Contribution

The paper proposes a novel influence metric based on cosponsorship networks that better predicts bill outcomes than traditional centrality measures.

Findings

Influence network properties correlate with bill passage.

The proposed influence measure outperforms standard centrality metrics.

Cosponsorship influence significantly explains legislative success.

Abstract

Each year, the United States Congress considers thousands of legislative proposals to select bills to present to the US President to sign into law. Naturally, the decision processes of members of Congress are subject to peer influence. In this paper, we examine the effect on bill passage of accrued influence between US Congress members in the US House of Representatives. We explore how the influence of a bill's cosponsors affects the bill's outcome (specifically, whether or not it passes in the House). We define a notion of influence by analyzing the structure of a network that we construct using cosponsorship dynamics. We award `influence' between a pair of Congress members when they cosponsor a bill that achieves some amount of legislative success. We find that properties of the bill cosponsorship network can be a useful signal to examine influence in Congress; they help explain why some bills pass and others fail. We compare our measure of influence to off-the-shelf centrality measures and conclude that our influence measure is more indicative of bill passage.