We examine whether representatives are more likely to serve long-term campaign donors instead of constituents during times of low media attention to politics. Based on 425 roll calls between 2005 and 2014 in the US House of Representatives, we show that representatives are more likely to vote with special interests and against constituency interests when the two are in conflict. Importantly, the latter effect is significantly larger when there is less attention on politics due to exogenous newsworthy events. The opportunistic behavior seems not to be mediated by short-term scheduling of sensitive votes right after distracting events.
We examine the ownership structure and reach of thousands of news websites in the U.S., Canada, and Europe. By combining data on domain registrants, firm ownership, and domain-level web traffic, we draw detailed ownership networks behind news domains. We find that more than half of these websites have one ultimate owner. Otherwise, they tend to have highly diversified ownership structures, making it non-transparent as to who is ultimately responsible for the content. Moreover, the market concentration for online news is moderate to high and varies substantially across countries. Financial industry firms ultimately own substantial shares in the online news market.
Search engines play a central role in routing political information to citizens. The algorithmic personalization of search results by large search engines like Google implies that different users may be offered systematically different information. However, measuring the causal effect of user characteristics and behavior on search results in a politically relevant context is challenging. We set up a population of 150 synthetic internet users ("bots") who are randomly located across 25 US cities and are active for several months during the 2020 US Elections and their aftermath. These users differ in their browsing preferences and political ideology, and they build up realistic browsing and search histories. We run daily experiments in which all users enter the same election-related queries. Search results to these queries differ substantially across users. Google prioritizes previously visited websites and local news sites. Yet, it does not generally prioritize websites featuring the user's ideology.
This paper examines the role of local TV market structure in US congressional politics, exploiting variation in the overlaps of political markets and TV markets. Local TV stations are hypothesized to report relatively more per US House representative in less populous markets (where the number of House districts covered is smaller), leading to better informed voters and more accountable representatives. We find that smaller markets are indeed associated with (i) higher coverage of representatives, and (ii) a higher level of voters' knowledge about their representatives. However, (iii) representatives of smaller and more congruent markets are only more likely to decide aligned with their constituents' policy preferences in highly competitive districts. This evidence suggests that local political news coverage on TV serves as a complement rather than a substitute in holding members of the US Congress accountable.
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.
We study the link between precisely timed campaign finance donations and the exertion of influence on legislative decisions. We propose that the incentives around the pass margin of votes can be exploited to infer whether moneyed interests buy contested votes. Our theoretical reasoning suggests that vote-buying induces a discontinuity both in the vote outcome distribution and in donation flows at the pass margin. The theoretical predictions are tested based on two decades of roll-call voting in the U.S. House. Several pieces of evidence substantiate the main finding, suggesting that moneyed interests exert effective control over the passage of contested bills.
Search Engines, Online News, and Political Polarization (with Roland Hodler)
Lobbying in Disguise (with Stefano Carattini and Matthias Roesti)
TheOpenAIR: Integrate ‘OpenAI’ Large Language Models into Your ‘R’ Workflows. R package version 0.1.0. https://openair-lib.org/
tidyair: Tidy Data With Large Language Models. R package version 0.1.0. https://umatter.github.io/tidyair
placeR: A wrapper for the Google Places API. R package version 0.1.0. https://github.com/umatter/placeR
mediacloudR: An R Package to Interact with the Media Cloud API. R package version 0.1. https://github.com/umatter/mediacloudR (first release: 2021)
pvsR: An R Package to Interact with the Project Vote Smart API for Scientific Research. R package version 0.3. http://CRAN.R-project.org/package=pvsR (first release: 2013-05-29)
RWebData: A High-Level Interface to the Programmable Web. R package version 0.1. https://github.com/umatter/RWebData (first release: 2016-03-01)
netensembleR: Analysis and Sampling of Directed Networks in R. R package version 0.1. https://github.com/umatter/netensembleR (first release: 2016-07-18)