Uncovering Vote Trading Through Networks and Computation

48 Pages Posted: 5 Oct 2017

See all articles by Omar A Guerrero

Omar A Guerrero

Alan Turing Institute - Alan Turing Institute; University College London - Department of Economics

Ulrich Matter

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

Date Written: September 2017

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.

Suggested Citation

Guerrero, Omar A and Matter, Ulrich, Uncovering Vote Trading Through Networks and Computation (September 2017). Saïd Business School WP 2017-16. Available at SSRN: https://ssrn.com/abstract=3047871 or http://dx.doi.org/10.2139/ssrn.3047871

Omar A Guerrero (Contact Author)

Alan Turing Institute - Alan Turing Institute ( email )

96 Euston Road
London, NW1 2DB
United Kingdom

University College London - Department of Economics ( email )

Drayton House, 30 Gordon Street
30 Gordon Street
London, WC1H 0AX
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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