Quantifying Vote Trading Through Network Reciprocity

Omar A. Guerrero, Ulrich Matter
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Abstract

Building on the concept of reciprocity in directed weighted networks, we propose a framework to study legislative vote trading. We first discuss the conditions to quantify vote trading empirically. We then illustrate how a simple empirical framework--complementary to existing approaches--can facilitate the discovery and measurement of vote trading in roll-call data. The application of the suggested procedure preserves the micro-structure of trades between individual legislators, shedding light on, so far, unstudied aspects of vote trading. Validation is provided via Monte Carlo simulation of the legislative process (with and without vote trading). Applications to two major studies in the field provide richer, yet consistent evidence on vote trading in US politics.
通过网络互惠量化投票交易
基于有向加权网络中的互惠概念,我们提出了一个研究立法投票交易的框架。我们首先讨论了实证量化投票交易的条件。然后,我们说明了一个简单的经验框架——与现有方法互补——如何有助于发现和衡量唱名数据中的投票交易。所建议程序的适用保留了个别立法者之间交易的微观结构,揭示了迄今为止尚未研究的投票交易方面。通过蒙特卡罗模拟立法过程(有和没有投票交易)提供验证。应用于该领域的两项主要研究为美国政治中的投票交易提供了更丰富、更一致的证据。
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