Working Papers
Do Housing Supply Skeptics Learn? Evidence from Economics and Advocacy Treatments.
Abstract: Recent research finds that most people want lower housing prices but, contrary to expert consensus, do not believe that more supply would lower prices. This study tests the effects of four informational interventions on Americans’ beliefs about housing markets and associated policy preferences and political actions (writing to state lawmakers). Several of the interventions significantly and positively affected economic understanding and support for land-use liberaliza- tion, with standardized effect sizes of 0.15 − 0.3. The most impactful treatment—an educational video from an advocacy group—had effects 2-3 times larger than typical economics-information or political-messaging treatments. Learning about housing markets increased support for development among homeowners as much as renters, contrary to the “homevoter hypothesis.” The treatments did not significantly affect the probability of writing to lawmakers, but an off-plan analysis suggests that the advocacy video increased the number of messages asking for more market-rate housing.
Single Family Schoolyards: Residential Zoning and School Segregation.
Abstract: Though the Supreme Court’s 1955 decision in Brown v. Board of Education outlawed explicit segregation of public schools, segregation has remained stubbornly persistent in the intervening decades. What explains continuous racial segregation in the absence of explicit policy? One possible driver is America’s built environment–designed with similar segregationist impulses but not subject to corrective legal action. Zoning and land use policy may inhibit residential mobility which in turns leads to segregated schools. I investigate this drawing on data from over 150 million residential parcels provided by Zillow. I find that school districts whose boundaries include a higher proportion of single-family parcels have a higher proportion of White students and more racial concentration than districts whose boundaries include more mixed types of housing. However, I do not find that districts with more single-family parcels have more racially segregated student populations compared to the larger metro area. These findings help illuminate how land use policy influences educational segregation and contributes to literature on how policies that regulate the built environment affect racial sorting.
Buying the Ballot: Political Actors and Official Ballot Initiative Language with Mitch Downey, Economics, Stockholm IIES.
Abstract: At the time of their inception in the Progressive Era, ballot initiatives were intended as a way for citizens to wrest control of the policy making process away from politicians corrupted by special interests. However, this measure of popular sovereignty may not be as immune to meddling these same special interests as either the founders of direct democracy or the literature suggests. Many voters learn about initiatives only from the titles and summaries appearing on ballots, which are themselves written by elected politicians. We study that special interest groups influence the wording of these official ballot initiative summaries, showing that summaries are more likely to use supporters’ preferred language as supporters contributed more to the summary writer. This relationship holds true even when the summary writer is running for a different office and does not exist in summaries written by an independent, apolitical non-profit group. We then show that donors are more likely to give to Attorney General candidates when relevant initiatives appear on the ballot. This result is not reflected in broader state-level political activity and exists only in states where the Attorney General writes the summary. Our results show the risks of tasking elected officials with fundamentally bureaucratic tasks and indicate that this process designed to reduce the power of special interests over the legislative process may have actually given them another avenue of control.
The Supply and Demand of Fact v. Opinion in Presidential Tweets. with Thad Kousser, UCSD Political Science.
Abstract: Do presidential candidates, and now President Trump, use social media to lay out the factual basis for their positions, or do they primarily communicate their values and opinions? We investigate this question by using human categorizations of over 8,000 tweets to train machine learning algorithms to code all of the tweets sent by all 23 candidates during and since the 2016 presidential election campaign. We argue that politicians should supply more opinions than facts, in order to match voter demand for opinion over fact and increase audience engagement with their tweets. In a descriptive analysis, we chart the flow of factual claims – many of which happen to be false, according to prominent fact-checking websites – versus opinion over the course of the campaign and across candidates. Donald Trump leaned heavily toward opinion during the campaign, but so did Hillary Clinton and many of the of the most successful candidates. Turning to the demand for tweets, we analyze the rate at which a candidate’s tweet is liked or retweeted, relative to her number of followers. We find that, for nearly every candidate, tweets that espouse an opinion generate significantly more engagement than factual claims. Negative opinions are especially engaging. These findings persist in multivariate models that hold constant the tone, subject matter, and ideology of the tweet, providing strong evidence that voters are more responsive to opinion than fact on social media.
All the President’s Tweets: Studying the Big Data of Twitter Political Communication with a Small Data Approach. with Thad Kousser, UCSD Political Science.
Abstract: This paper describes and demonstrates an approach to studying political communication on Twitter that combines the flexibility and subtlety of human coding on small datasets with the scalability of big data methods. We apply this method to study the 152,134 tweets sent by candidates and their SuperPACs during the 2016 American presidential election. We begin by outlining the importance of studying this increasingly prominent form of political communication, laying out both the opportunities and obstacles to analyzing the massive volume of social media political texts. We then explain our supervised learning method to classify the ideology and sentiment of tweets, what policy spheres they address, whether they make factual statements or espouse opinions, and other characteristics. To demonstrate what this approach to studying political communication can tell us about a campaign, we then focus on our measure of ideology. We map the candidates on a spatial spectrum based on their social media rhetoric, explore Donald Trump’s unique brand of populism by looking at where he placed himself on different issues, and asked whether he and Hillary Clinton followed the Downsian impulse to moderate their message from the primary to the general election.