Quantifying Vote Trading Through Network Reciprocity

39 Pages Posted: 16 Jun 2021

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

Date Written: June 14, 2021

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.

Keywords: Vote trading, roll-call voting, networks, reciprocity, US Congress

JEL Classification: D72, D85

Suggested Citation

Guerrero, Omar A and Matter, Ulrich, Quantifying Vote Trading Through Network Reciprocity (June 14, 2021). Available at SSRN: https://ssrn.com/abstract=3866572 or http://dx.doi.org/10.2139/ssrn.3866572

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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