Book

Alvarez, R. Michael, Nicholas J. Adams-Cohen, Seo-young Silvia Kim, Yimeng Li. 2020. “Securing Elections: How Data-Driven Election Monitoring Can Improve Democracy.” Cambridge University Press.

Selected Peer Reviewed Journal Articles

For a full list of publications, please see my CV.

Selected Working Papers

Fundraising on the Fringe: Do Ideologically Extreme Candidates Solicit Small Donations?

Do ideologically extreme candidates actively pursue small donations? There is a debate in the money in politics literature about whether “small” individual campaign donors are more ideologically extreme than large donors. This paper reverses the question and investigates whether extreme candidates ask for smaller contributions. Using data from U.S. congressional candidates’ fundraising platforms in the 2020 elections, I leverage that campaigns typically present a set of suggested amounts to efficiently solicit money from potential donors. While party, in-state income level, and usage of major fundraising platforms mattered, ideological extremism had no bearing on the amounts candidates asked of their donors. Since solicitation amounts have been long and easily optimized through A/B testing, I interpret this as extreme candidates not finding it profitable to ask for smaller amounts, which is more in alignment with the argument that small donors are not more likely to be ideologically extreme than large ones.

Support and Preference for Grassroots Fundraising (with Yimeng Li.)

Do Americans support small individual donations over other sources of political fundraising? Small online contributions are becoming more prevalent, and political elites and the media often idealize them as leveling the playing field in the American political ecosystem. However, we have little understanding of whether and, if any, how much the public supports small donations as a campaign funding source over others and whether such preferences translate into tangible changes in political behavior. Using a conjoint experiment via a nationally representative survey of U.S. citizens, we test whether candidates with higher dependence on small individual donors are more likely to be chosen. Surprisingly, candidates relying more on small donors attract a higher likelihood of vote choice and candidate ratings, not just within primaries or for Democrats, but across primaries, general elections, and all partisan affiliations. Moreover, the public believes that there should be more small donations in American elections and that, compared to the current baseline, the ideal composition of campaign funding should rely less on PACs and large individual donations and more on small donations and other sources such as candidate self-financing. Such beliefs are unshaken when presented with information about lawmakers with the highest reliance on small donors, who are generally perceived as outsiders or ideologically extreme.

When Do Voter Files Accurately Measure Turnout? How Transitory Voter File Snapshots Impact Research and Representation (with Bernard Fraga.)

Voter files are an essential tool for both election research and campaigns, but relatively little work has established best practices for using these data. We focus on how the timing of voter file snapshots affects the most commonly cited advantage of voter file data: accurate measures of who votes. Outlining the panel structure inherent in voter file data, we demonstrate that opposing patterns of accretion and attrition in the voter registration list result in temporally-dependent bias in estimates of voter turnout for a given election. This bias impacts samples for surveys, experiments, or campaign activities by skewing estimates of the potential and actual voter populations; low-propensity voters are particularly impacted. We provide an approach that allows researchers to measure the impact of this bias on their inferences. We then outline methods that measurably reduce this bias, including combining multiple snapshots to preserve the turnout histories of dropped voters.

Book Reviews