Uncovering Vote Trading through Networks and Computation

47 Pages Posted: 5 Nov 2016 Last revised: 10 Aug 2018

See all articles by Omar A Guerrero

Omar A Guerrero

The Alan Turing Institute

Ulrich Matter

University of St. Gallen - Swiss Institute for International Economics and Applied Economic Research

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Date Written: November 4, 2016

Abstract

We develop a new methodological framework for the empirical study of legislative vote trading. Building on the concept of reciprocity in directed weighted networks, our method facilitates the measurement of vote trading on a large scale, while estimating the micro-structure of trades between individual legislators. In principle, it can be applied to a broad variety of voting data and refined for various specific contexts. It allows, for example, to study how vote trading in a specific legislative assembly varies over time. We validate our method with a computational model in which we control the level of vote trading. Finally, we demonstrate our framework in an analysis of four decades of roll call voting in the U.S. Congress.

Keywords: vote trading, logrolling, networks, agent-computing, cooperation, computational social science

Suggested Citation

Guerrero, Omar A and Matter, Ulrich, Uncovering Vote Trading through Networks and Computation (November 4, 2016). Available at SSRN: https://ssrn.com/abstract=2864421 or http://dx.doi.org/10.2139/ssrn.2864421

Omar A Guerrero (Contact Author)

The Alan Turing Institute ( email )

96 Euston Road
London, NW1 2DB
United Kingdom

Ulrich Matter

University of St. Gallen - Swiss Institute for International Economics and Applied Economic Research ( email )

Bodanstrasse 8
St. Gallen, 9000
Switzerland

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