Preventing COVID-19 Fatalities: State versus Federal Policies

Renne, Jean‐Paul; Roussellet, Guillaume; Schwenkler, Gustavo

doi:10.2139/ssrn.3720947

Cited by 3 publications

(5 citation statements)

References 25 publications

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“…Combined with empirical literature that documents substantial inter-state spillovers of Covid-19 (Brinkman & Mangum, 2020;Dave et al, 2021;Renne et al, 2020;Rothert et al, 2020), and recent work on policy coordination (Beck & Wagner, 2020;Rothert, 2021), the results in this paper emphasize the important role that the federal government can and should play in battling current and future disease outbreaks.…”

Section: Discussionsupporting

confidence: 59%

“…Rothert (2021) focused on the strategic interaction between states and the free-riding problem, but abstracted from issues related to within state income redistribution, which is an important part of this paper. Policy coordination, an important motivation for this paper, is also a central topic in papers by Renne et al (2020), Crucini and O'Flaherty (2020), or Acharya et al (2020).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The first one is the epidemiological spillover—a susceptible person in one state can catch the virus by coming into a close contact with an infected person from a different state. Numerous empirical studies documented that those spillovers can be substantial (Eckardt et al, 2020; Renne et al, 2020; Rothert et al, 2020). The second factor has to do with the capacity of the healthcare system and the availability of medical equipment.…”

Section: Uncoordinated Response and Inter‐state Redistributionmentioning

confidence: 99%

“…Within the United States, empirical studies suggest that in the early months of the Covid‐19 pandemic as much as 10%–20% new cases arose from interactions between people from different states (Brinkman & Mangum, 2020; Rothert et al, 2020). Model‐based simulations indicate that lax policies in the most lenient states could translate into millions of additional infections in the long‐run (Rothert et al, 2020) and that thousands of lives could have been saved if the states had coordinated their lock‐down policies or had a greater ability to limit inter‐state travel (Giannone et al, 2020; Renne et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimal federal transfers during uncoordinated response to a pandemic

Rothert

2021

J Public Economic Theory

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An outbreak of a deadly disease pushes policymakers to depress economic activity due to externalities associated with individual behavior. Sometimes, these decisions are left to local authorities (e.g., states). This creates another externality, as the outbreak doesn't respect states' boundaries. A strategic Pigouvian subsidy that rewards states which depress their economies more than the average corrects that externality by creating a race‐to‐the‐bottom type of response. In a symmetric equilibrium nobody receives a subsidy, but the allocation is efficient. If states are concerned about unequal burden of the lockdown costs, but cannot easily issue new debt to finance transfer payments, then lock‐downs will be insufficient in some areas and excessive in others. When that's the case, federal stimulus checks can limit the extent of local outbreaks.

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Section: Discussionsupporting

confidence: 59%

Section: Literature Reviewmentioning

confidence: 99%

Section: Uncoordinated Response and Inter‐state Redistributionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal federal transfers during uncoordinated response to a pandemic

Rothert

2021

J Public Economic Theory

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“…Our approach requires much less granular information. Renne et al (2020) estimate a SIRD model using a quasi-likelihood methodology and the extended Kalman filter. Arroyo-Marioli et al (2021), Fernández-Villaverde andJones (2020), Pesaran and Yang (2020), and Lee et al (2021) estimate time-varying contact rates using the restrictions implied by the SIR model.…”

Section: Bayesian Approachmentioning

confidence: 99%

Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs

et al. 2021

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We present a general framework for Bayesian estimation and causality assessment in epidemiological models. The key to our approach is the use of sequential Monte Carlo methods to evaluate the likelihood of a generic epidemiological model. Once we have the likelihood, we specify priors and rely on a Markov chain Monte Carlo to sample from the posterior distribution. We show how to use the posterior simulation outputs as inputs for exercises in causality assessment. We apply our approach to Belgian data for the COVID-19 epidemic during 2020. Our estimated time-varying-parameters SIRD model captures the data dynamics very well, including the three waves of infections. We use the estimated (true) number of new cases and the timevarying effective reproduction number from the epidemiological model as information for structural vector autoregressions and local projections. We document how additional governmentmandated mobility curtailments would have reduced deaths at zero cost or a very small cost in terms of output.

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