Quantifying Vote Trading Through Network Reciprocity

Autor: Ulrich Matter, Omar A. Guerrero
Rok vydání: 2021
Předmět:
Zdroj: SSRN Electronic Journal.
ISSN: 1556-5068
DOI: 10.2139/ssrn.3866572
Popis: 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.
Databáze: OpenAIRE