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Executive Power in Crisis

Published online by Cambridge University Press:  15 June 2021

KENNETH LOWANDE*
Affiliation:
University of Michigan
JON C. ROGOWSKI*
Affiliation:
University of Chicago
*
Kenneth Lowande, Assistant Professor, Department of Political Science, University of Michigan, lowande@umich.edu.
Jon C. Rogowski, Associate Professor, Department of Political Science, University of Chicago, jrogowski@uchicago.edu.
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Abstract

Major crises can threaten political regimes by empowering demagogues and promoting authoritarian rule. While existing research argues that national emergencies weaken formal checks on executive authority and increase public appetites for strong leadership, no research evaluates whether crises increase mass support for the president’s institutional authority. We study this question in the context of the coronavirus/COVID-19 pandemic with an experiment embedded in a national survey of more than 8,000 U.S. adults. We find no evidence that the public evaluated policies differently if they were implemented via unilateral power rather than through the legislative process, nor did the severity of the pandemic at either the state, local, or individual levels moderate evaluations of executive power. Instead, individuals’ partisan and ideological views were consistently strong predictors of policy attitudes. Perhaps paradoxically, our results suggest that elite and mass polarization limit the opportunity for crises to promote public acceptance of strengthened executive authority.

Information

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the American Political Science Association
Figure 0

Table 1. COVID-19 Policy Questions

Figure 1

Table 2. Support for COVID-19 Policies

Figure 2

Figure 1. Moderator: County-Level Confirmed Cases of COVID-19Note: Source: https://github.com/CSSEGISandData (accessed April 13, 2020). Plots county-level confirmed cases (log scale) as of the end of day, March 29, 2020.

Figure 3

Figure 2. Moderator: Individual-Level Level of Concern about Personal HealthNote: “How concerned are you about your personal health?” Reports the proportion of respondents who selected each response.

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Figure 3. Presidential Power and Policy SupportNote: Plots the estimated differences in support for each policy between respondents in the unilateral and legislative conditions. Positive values along the x-axis indicate greater support for proposals that are implemented via unilateral power rather than by legislative action. Policy labels found in Table 1. Values simulated from logistic regressions, with level of concern for personal health, treatment condition, income, age, party, race, gender, and education as covariates. The vertical dashed line indicates the null hypothesis of no difference in policy support based on how the policy was implemented. The horizontal lines indicate the 95% confidence intervals associated with the differences in support.

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Figure 4. Support for Policy Interventions Sometimes Associated with Local-Level Case SeverityNote: Plots the predicted probability of support by policy intervention. Values simulated from logistic regressions, with log-transformed county-level cases (as of March 29), treatment condition, income, age, party, race, gender, and education as covariates. For Election, Easter, Vaccine, Prisons, and Tariffs, the association of cases and support is statistically distinguishable from zero by convention.

Figure 6

Figure 5. Support for Policy Interventions Often Associated with Individual-Level Concern for Personal HealthNote: Plots the predicted probability of support by policy intervention. Values simulated from logistic regressions, with level of concern for personal health, treatment condition, income, age, party, race, gender, and education as covariates. For Detain, Election, Congress, Vaccine, Travel, Socialism, and Prisons, support among individuals who report they are “very concerned” is statistically distinguishable by convention from those who are “not at all concerned.”

Figure 7

Table 3. Support for COVID-19 Policies

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Figure 6. Predicted Support Conditioned by Partisan IdentificationNote: Plots the predicted probability of support by policy intervention and party (leaners coded as partisans). Values simulated from logistic regressions, with log-transformed county-level cases (as of March 29), treatment condition, income, age, party, race, and education as covariates. Republicans are statistically distinguishable from Democrats by convention for all but Prisons and Socialism.

Supplementary material: Link

Lowande and Rogowski Dataset

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