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Retrospective voting studies typically examine policies where the public has common interests. By contrast, climate policy has broad public support but concentrated opposition in communities where costs are imposed. This spatial distribution of weak supporters and strong local opponents mirrors opposition to other policies with diffuse public benefits and concentrated local costs. I use a natural experiment to investigate whether citizens living in proximity to wind energy projects retrospectively punished an incumbent government because of its climate policy. Using both fixed effects and instrumental variable estimators, I identify electoral losses for the incumbent party ranging from 4 to 10%, with the effect persisting 3 km from wind turbines. There is also evidence that voters are informed, only punishing the government responsible for the policy. I conclude that the spatial distribution of citizens' policy preferences can affect democratic accountability through 'spatially distorted signalling', which can exacerbate political barriers to addressing climate change.

How does the context in which a person lives affect his or her political behavior? I exploit an event in which demographic context was exogenously changed, leading to a significant change in voters' behavior and demonstrating that voters react strongly to changes in an outgroup population. Between 2000 and 2004, the reconstruction of public housing in Chicago caused the displacement of over 25,000 African Americans, many of whom had previously lived in close proximity to white voters. After the removal of their African American neighbors, the white voters' turnout dropped by over 10 percentage points. Consistent with psychological theories of racial threat, their change in behavior was a function of the size and proximity of the outgroup population. Proximity was also related to increased voting for conservative candidates. These findings strongly suggest that racial threat occurs because of attitude change rather than selection.

Retrospective voting models assume that offering more information to voters about their incumbents’ performance strengthens electoral accountability. However, it is unclear whether incumbent corruption information translates into higher political participation and increased support for challengers. We provide experimental evidence that such information not only decreases incumbent party support in local elections in Mexico, but also decreases voter turnout and support for the challenger party, as well as erodes partisan attachments. While information clearly is necessary to improve accountability, corruption information is not sufficient because voters may respond to it by withdrawing from the political process. We conclude with a discussion of the implications of our findings for studies of voting behavior.

In this article, we examine the effect of \"choice fatigue\" on decision making. We exploit a natural experiment in which voters face the same contest at different ballot positions due to differences in the number of local issues on their ballot. Facing more decisions before a given contest significantly increases the tendency to abstain or rely on decision shortcuts, such as voting for the status quo or the first-listed candidate. We estimate that, without choice fatigue, abstentions would decrease by 8%, and 6% of the propositions in our data set would have passed rather than failed.

This article reexamines the argument that targeted programs increase pro-incumbent voting by persuading beneficiaries to cast ballots against their first partisan choice. The evidence comes from the randomized component of Progresa, the pioneering Mexican conditional cash transfer (CCT) program. Experimental data show that early enrollment in the program led to substantive increases in voter turnout and in the incumbent's vote share in the 2000 presidential election. The experiment also reveals that opposition parties' vote shares were unaffected by the program. Thus, the electoral bonus generated by CCTs may be best explained by a mobilizing rather than persuasive mechanism. These findings are difficult to reconcile with the notion that the electoral effects of CCTs are a result of prospective concerns triggered by threats of program discontinuation or endogenous program enrollment. Instead, the evidence in this article suggests that CCTs' mobilizing effects are compatible with programmatic politics.

In both political behavior research and voting rights litigation, turnout and vote choice for different racial groups are often inferred using aggregate election results and racial composition. Over the past several decades, many statistical methods have been proposed to address this ecological inference problem. We propose an alternative method to reduce aggregation bias by predicting individual-level ethnicity from voter registration records. Building on the existing methodological literature, we use Bayes's rule to combine the Census Bureau's Surname List with various information from geocoded voter registration records. We evaluate the performance of the proposed methodology using approximately nine million voter registration records from Florida, where self-reported ethnicity is available. We find that it is possible to reduce the false positive rate among Black and Latino voters to 6% and 3%, respectively, while maintaining the true positive rate above 80%. Moreover, we use our predictions to estimate turnout by race and find that our estimates yields substantially less amounts of bias and root mean squared error than standard ecological inference estimates. We provide open-source software to implement the proposed methodology.

In a large-scale controlled trial in collaboration with the reelection campaign of an Italian incumbent mayor, we administered (randomized) messages about the candidate's valence or ideology. Informational treatments affected both actual votes in the precincts and individual vote declarations. Campaigning on valence brought more votes to the incumbent, but both messages affected voters' beliefs. Cross-learning occurred, as voters who received information about the incumbent also updated their beliefs on the opponent. With a novel protocol of beliefs elicitation and structural estimation, we assess the weights voters place upon politicians' valence and ideology, and simulate counterfactual campaigns.

Modern campaigns develop databases of detailed information about citizens to inform electoral strategy and to guide tactical efforts. Despite sensational reports about the value of individual consumer data, the most valuable information campaigns acquire comes from the behaviors and direct responses provided by citizens themselves. Campaign data analysts develop models using this information to produce individual-level predictions about citizens' likelihoods of performing certain political behaviors, of supporting candidates and issues, and of changing their support conditional on being targeted with specific campaign interventions. The use of these predictive scores has increased dramatically since 2004, and their use could yield sizable gains to campaigns that harness them. At the same time, their widespread use effectively creates a coordination game with incomplete information between allied organizations. As such, organizations would benefit from partitioning the electorate to not duplicate efforts, but legal and political constraints preclude that possibility.

Do distributive benefits increase voter participation? This article argues that the government delivery of distributive aid increases the incumbent party's turnout but decreases opposition-party turnout. The theoretical intuition here is that an incumbent who delivers distributive benefits to the opposing party's voters partially mitigates these voters' ideological opposition to the incumbent, hence weakening their motivation to turn out and oust the incumbent. Analysis of individual-level data on FEMA hurricane disaster aid awards in Florida, linked with voter-turnout records from the 2002 (pre-hurricane) and 2004 (post-hurricane) elections, corroborates these predictions. Furthermore, the timing of the FEMA aid delivery determines its effect: aid delivered during the week just before the November 2004 election had especially large effects on voters, increasing the probability of Republican (incumbent party) turnout by 5.1% and decreasing Democratic (opposition party) turnout by 3.1%. But aid delivered immediately after the election had no effect on Election Day turnout.

Does media bias affect voting? We analyze the entry of Fox News in cable markets and its impact on voting. Between October 1996 and November 2000, the conservative Fox News Channel was introduced in the cable programming of 20 percent of U. S. towns. Fox News availability in 2000 appears to be largely idiosyncratic, conditional on a set of controls. Using a data set of voting data for 9,256 towns, we investigate if Republicans gained vote share in towns where Fox News entered the cable market by the year 2000. We find a significant effect of the introduction of Fox News on the vote share in Presidential elections between 1996 and 2000. Republicans gained 0.4 to 0.7 percentage points in the towns that broadcast Fox News. Fox News also affected voter turnout and the Republican vote share in the Senate. Our estimates imply that Fox News convinced 3 to 28 percent of its viewers to vote Republican, depending on the audience measure. The Fox News effect could be a temporary learning effect for rational voters, or a permanent effect for nonrational voters subject to persuasion.