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Published Work

November 2021

Energy Inequality and Clientelism in the Wake of Disasters: From Colorblind to Affirmative Power Restoration

Do social vulnerabilities and ruling party support shape government responsiveness in times of disasters? The 2017 hurricane María territory-wide power outage, the second longest in world history, is a tragic natural experiment that provides a unique opportunity to examine the determinants of government responsiveness during disaster recovery processes. We use data on power restoration crew deployments (N = 18,614 deployments), a novel measure of government responsiveness, and a new social vulnerability index to assess the determinants of government responsiveness in the wake of disasters. We find that communities with ties to the ruling party elicit greater government responsiveness while socially vulnerable communities are less likely to be prioritized during the disaster relief efforts, controlling for disaster damage as well as logistical, economic, and essential service recovery priorities. Existing power restoration policies place larger burdens on marginalized communities, motivating the need for including power restoration to vulnerable communities among restoration priorities.

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Co-authors: Fernando Tormos-Aponte; Gustavo García-López

June 2021

Local Politics as a Context for Polarizing Cues

There is adequate research demonstrating that source cues (such as prominent politicians or interest groups) can move public support for some policies, however, most of the research on source cues in the United States tests the impact of national leaders or parties as cues. We argue that hypotheses about source cues should be tested in other settings, such as local politics. Local settings offer a test where source cues may not be so closely tied to partisan identity. We hypothesize that in contexts where the source is well-known, and the policy is relatively obscure, source cues can polarize public opinion substantially. However, on highly salient policies the impact of source cues may be much weaker. We report the results of three survey experiments testing the polarizing impact of a mayor as a source cue on city voters. We find strong source cue effects in each test. The often racially divisive nature and machine-versus-reform type polarization of urban politics provides a fertile context for testing the polarizing impact of source cues.

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Co-author: David C. Kimball

April 2020

Curb-Sided: How Technology Disrupts the American Transportation Planning
Process

The disruptive arrival of Uber, Lyft, and other transportation network companies (TNCs) into American cities ignited arguments on how policy-makers should regulate such entities. Policy debates started among policymakers, companies, and existing industries and interests. In attempts to persuade policy, actors adopted a variety of language and used different levels of government to achieve policy goals. In almost all cases, TNCs were able to gain favorable policy through image framing and venue shopping –the key components to Punctuated Equilibrium Theory (PET). This analysis looks at the policy process of three American cities: Chicago, IL, St. Louis, MO, and Austin, TX. Transportation network companies framed the issue favorably to their policy demands, winning over the public, drivers, and policymakers in most cases. However, when the political climate was harsher for TNCs, they sought sympathy from policy makers in different regulator institutions. Conversely, taxi interests were unable to use the same tactics to achieve their demands. I argue that this is due to TNC’s ability to appeal to framing suitable for target audiences, mainly free-market, business-friendly, and tech-savvy language. This language appealed to mayors, city council members, and state lawmakers, making TNCs able to “shop” from one level of government to another to achieve lax regulation and company oversight.

Publications: Publications

Upcoming Publications

Coming Soon! (In R&R)

Clientelism and Corruption in the Wake of Disasters

Puerto Rico’s uninterrupted history of crisis provides an opportune context for the study of corruption in times of crisis and disasters. This article conceptualizes the phenomenon of pork-barrel spending and disaster resource allocations as forms of corruption. We expand the traditional focus of pork-barrel spending on legislative appropriations to include other forms of pork, such as disaster aid. We conceptualize pork-barrel spending and clientelism as enablers of other forms of corruption that are larger in scale, relative to the allocation of pork. We argue that pork barrel spending may contribute to the concentration of power, thereby enabling the continuity of the systems in which corruption takes place. Yet, their electoral impact in disaster contexts like Puerto Rico remain under examined. We use the case of disaster mitigation resource allocation during the hurricane María recovery as an illustrative case of pork-barrel spending. This article provides evidence that suggests the plausibility of the relationship between disaster aid allocations and electoral outcomes. Drawing from data on energy restoration crew deployments and the 2020 election results, we use univariate linear regressions to assess the extent to which energy restoration impacts electoral outcomes. We find that delayed disaster response has statistically significant correlation with the decrease in support for both major parties on the national level, while support for local candidates does not have this relationship.  …This research points to the need to adopt transparency measures that enable assessments of disparities in disaster resource allocation as well as policies that mandate more equitable distribution of disaster recovery resources.

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Co-Authors: Fernando Tormos-Aponte, Wendy Prudencio, Brevin Franklin

Coming Soon!

Can government responsiveness to climate disasters be measured? The case of electricity restoration after hurricane María in Puerto Rico

This paper conceptualizes government responsiveness to climate disasters, and what could be measured as such. First, we provide a theoretical basis for government responsiveness, describing its conceptualization in the scholarly literature. Second, we use this synthesis to construct a spatial measure of government responsiveness to power restoration in Puerto Rico following hurricane María -- one of the deadliest climate disasters in modern U.S. history. Through the use of a mixed-methods and multi-scalar design, we develop an index integrating a big dataset on electricity crew visits at the address level (n = 18,614 deployments) with National Aeronautics and Space Administration’s (NASA) calibrated, corrected, and validated nighttime light satellite data product, Black Marble.

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Co-authors: Sameer H. Shah, Fernando Tormos-Aponte

Coming Soon!

Without Power but not Powerless: Electoral Consequences of Disaster Response

Marginalized communities are more likely to experience power outages, energy poverty, and stand in the frontlines of climate change-related extreme weather events. In times of disasters, governments must make expeditious decisions on how to distribute disaster relief resources. The urgency with which these decisions are made and the shock that disasters deliver to impacted communities inhibit the extent to which disaster decision-making is transparent and subject to mechanisms of democratic accountability. The opacity of disaster recovery decision-making processes enables their clientelistic allocation and the neglect of marginalized communities. This project examines the extent to which marginalized communities punish incumbents for their disaster resource allocations. Scholars debate whether disaster resources are enough to finance clientelism or whether grand corruption schemes are needed to support the electoral continuity of elites who neglect marginalized communities. Using power restoration crew deployments as a novel measure of government responsiveness, we study  the archipelago-wide power outage in Puerto Rico after hurricane María in 2017 to examine how government responsiveness affected the 2020 Puerto Rico elections. Building  on earlier research documenting the partisan bias of disaster crew deployments in favor of communities that supported the ruling Partido Nuevo Progresista (PNP) and the neglect of marginalized communities,  we find that the time that communities waited for power restoration is associated with electoral support for the ruling PNP party.  While the ruling PNP had a decline in support from 2016 to 2020, the decline in support was smaller in areas that were prioritized during the energy restoration process. This finding provides empirical support for the notion that disaster resource allocations have political consequences for those in power.

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Co-authors: Fernando Tormos-Aponte, Brevin Franklin, Sameer H. Shah

Publications: Publications
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