scholarly journals The participatory and partisan impacts of mandatory vote-by-mail

2020 ◽  
Vol 6 (35) ◽  
pp. eabc7685
Author(s):  
Michael Barber ◽  
John B. Holbein
Keyword(s):  
United States ◽  
Voter Turnout ◽  
Political Party ◽  
The United States ◽  
The Other ◽  
County Level ◽  
Policy Makers ◽  
The Past ◽  
Level Data ◽  
Vote By Mail

Recently, mandatory vote-by-mail has received a great deal of attention as a means of administering elections in the United States. However, policy-makers disagree on the merits of this approach. Many of these debates hinge on whether mandatory vote-by-mail advantages one political party over the other. Using a unique pairing of historical county-level data that covers the past three decades and more than 40 million voting records from the two states that have conducted a staggered rollout of mandatory vote-by-mail (Washington and Utah), we use several methods for causal inference to show that mandatory vote-by-mail slightly increases voter turnout but has no effect on election outcomes at various levels of government. Our results find meaning given contemporary debates about the merits of mandatory vote-by-mail. Mandatory vote-by-mail ensures that citizens are given a safe means of casting their ballot while simultaneously not advantaging one political party over the other.

Is Distance to Drop Box an Appropriate Proxy for Drop Box Treatment? A Case Study of Washington State

2021 ◽  
pp. 1532673X2110221
Author(s):  
Loren Collingwood ◽  
Benjamin Gonzalez O’Brien
Keyword(s):  
United States ◽  
Voter Turnout ◽  
The United States ◽  
Washington State ◽  
Individual Level ◽  
Primary 52 ◽  
The One ◽  
Vote By Mail

In the United States, drop box mail-in voting has increased, particularly in the all vote by mail (VBM) states of Washington, Colorado, Utah, and Oregon. To assess if drop boxes improve voter turnout, research proxies box treatment by voters’ residence distance to nearest drop box. However, no research has tested the assumption that voters use drop boxes nearest their residence more so than they do other drop boxes. Using individual-level voter data from a 2020 Washington State election, we show that voters are more likely to use the nearest drop box to their residence relative to other drop boxes. In Washington’s 2020 August primary, 52% of drop box voters in our data used their nearest drop box. Moreover, those who either (1) vote by mail, or (2) used a different drop box from the one closest to their residence live further away from their closest drop box. Implications are discussed.

Abstract P636: Social Determinants of Stroke Hospitalization and Mortality in the United States

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Randhir Sagar Yadav ◽  
Durgesh Chaudhary ◽  
Shima Shahjouei ◽  
Jiang Li ◽  
Vida Abedi ◽  
...  
Keyword(s):  
United States ◽  
Income Inequality ◽  
Social Determinants ◽  
Hemorrhagic Stroke ◽  
The United States ◽  
Care Physician ◽  
County Level ◽  
Medicare Beneficiaries ◽  
Level Data ◽  
Control And Prevention

Introduction: Stroke hospitalization and mortality are influenced by various social determinants. This ecological study aimed to determine the associations between social determinants and stroke hospitalization and outcome at county-level in the United States. Methods: County-level data were recorded from the Centers for Disease Control and Prevention as of January 7, 2020. We considered four outcomes: all-age (1) Ischemic and (2) Hemorrhagic stroke Death rates per 100,000 individuals (ID and HD respectively), and (3) Ischemic and (4) Hemorrhagic stroke Hospitalization rate per 1,000 Medicare beneficiaries (IH and HH respectively). Results: Data of 3,225 counties showed IH (12.5 ± 3.4) and ID (22.2 ± 5.1) were more frequent than HH (2.0 ± 0.4) and HD (9.8 ± 2.1). Income inequality as expressed by Gini Index was found to be 44.6% ± 3.6% and unemployment rate was 4.3% ± 1.5%. Only 29.8% of the counties had at least one hospital with neurological services. The uninsured rate was 11.0% ± 4.7% and people living within half a mile of a park was only 18.7% ± 17.6%. Age-adjusted obesity rate was 32.0% ± 4.5%. In regression models, age-adjusted obesity (OR for IH: 1.11; HH: 1.04) and number of hospitals with neurological services (IH: 1.40; HH: 1.50) showed an association with IH and HH. Age-adjusted obesity (ID: 1.16; HD: 1.11), unemployment (ID: 1.21; HD: 1.18) and income inequality (ID: 1.09; HD: 1.11) showed an association with ID and HD. Park access showed inverse associations with all four outcomes. Additionally, population per primary-care physician was associated with HH while number of pharmacy and uninsured rate were associated with ID. All associations and OR had p ≤0.04. Conclusion: Unemployment and income inequality are significantly associated with increased stroke mortality rates.

Empirical Evidence on the Economic Impacts of Hotel Taxes

2021 ◽  
pp. 089124242110461
Author(s):  
Charles Swenson
Keyword(s):  
United States ◽  
Credit Ratings ◽  
The United States ◽  
The Other ◽  
Tax Rate ◽  
Ex Post ◽  
Level Data ◽  
Data Source ◽  
Dun And Bradstreet ◽  
Occupancy Rates

Tourist taxes are an important source of revenue for many governments. In the United States, all states impose them in the form of hotel/motel occupancy taxes, yet there is little ex post evidence as to whether such taxes affect occupancy rates. This study uses a precise establishment-level data source to examine California's varying rates by city, enabling powerful tests. The author finds that such taxes have negligible impacts on hotel sales and employment. On the other hand, hotels/motels operating in higher tax-rate cities tended to have more financial stress in terms of lower Dun and Bradstreet credit ratings.

scholarly journals The evolution of infant mortality inequality in the United States, 1960–2016

2020 ◽  
Vol 6 (29) ◽  
pp. eaba5908
Author(s):  
Nick Turner ◽  
Kaveh Danesh ◽  
Kelsey Moran
Keyword(s):  
United States ◽  
Infant Mortality ◽  
The United States ◽  
Mortality Rates ◽  
County Level ◽  
Level Data ◽  
Antipoverty Programs ◽  
The Relationship ◽  
Over Time ◽  
Mortality Inequality

What is the relationship between infant mortality and poverty in the United States and how has it changed over time? We address this question by analyzing county-level data between 1960 and 2016. Our estimates suggest that level differences in mortality rates between the poorest and least poor counties decreased meaningfully between 1960 and 2000. Nearly three-quarters of the decrease occurred between 1960 and 1980, coincident with the introduction of antipoverty programs and improvements in medical care for infants. We estimate that declining inequality accounts for 18% of the national reduction in infant mortality between 1960 and 2000. However, we also find that level differences between the poorest and least poor counties remained constant between 2000 and 2016, suggesting an important role for policies that improve the health of infants in poor areas.

scholarly journals Mask adherence and rate of COVID-19 across the United States

2021 ◽  
Author(s):  
Charlie B. Fischer ◽  
Nedghie Adrien ◽  
Jeremiah J. Silguero ◽  
Julianne J. Hopper ◽  
Abir I. Chowdhury ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
General Public ◽  
State Level ◽  
The United States ◽  
Policy Makers ◽  
Level Data ◽  
High Adherence ◽  
Key Factor ◽  
Public Health Officials

AbstractMask wearing has been advocated by public health officials as a way to reduce the spread of COVID-19. In the United States, policies on mask wearing have varied from state to state over the course of the pandemic. Even as more and more government leaders encourage or even mandate mask wearing, many citizens still resist the notion. Our research examines mask wearing policy and adherence in association with COVID-19 case rates. We used state-level data on mask wearing policy for the general public and on proportion of residents who stated they always wear masks in public. For all 50 states and the District of Columbia (DC), these data were abstracted by month for April ⍰ September 2020 to measure their impact on COVID-19 rates in the subsequent month (May ⍰ October 2020). Monthly COVID-19 case rates (number of cases per capita over two weeks) >200 per 100,000 residents were considered high. Fourteen of the 15 states with no mask wearing policy for the general public through September reported a high COVID-19 rate. Of the 8 states with at least 75% mask adherence, none reported a high COVID-19 rate. States with the lowest levels of mask adherence were most likely to have high COVID-19 rates in the subsequent month, independent of mask policy or demographic factors. Mean COVID-19 rates for states with at least 75% mask adherence in the preceding month was 109.26 per 100,000 compared to 249.99 per 100,000 for those with less adherence. Our analysis suggests high adherence to mask wearing could be a key factor in reducing the spread of COVID-19. This association between high mask adherence and reduced COVID-19 rates should influence policy makers and public health officials to focus on ways to improve mask adherence across the population in order to mitigate the spread of COVID-19.

scholarly journals Explaining COVID-19 Outbreaks with Reactive SEIRD Models

2021 ◽  
Author(s):  
Kunal Menda ◽  
Lucas Laird ◽  
Mykel J. Kochenderfer ◽  
Rajmonda S. Caceres
Keyword(s):  
Neural Network ◽  
United States ◽  
Infection Rate ◽  
Expectation Maximization ◽  
The United States ◽  
County Level ◽  
Training Set ◽  
Single Model ◽  
Partial Observability ◽  
Level Data

AbstractCOVID-19 epidemics have varied dramatically in nature across the United States, where some counties have clear peaks in infections, and others have had a multitude of unpredictable and non-distinct peaks. In this work, we seek to explain the diversity in epidemic progressions by considering an extension to the compartmental SEIRD model. The model we propose uses a neural network to predict the infection rate as a function of time and of the prevalence of the disease. We provide a methodology for fitting this model to available county-level data describing aggregate cases and deaths. Our method uses Expectation-Maximization in order to overcome the challenge of partial observability—that the system’s state is only partially reflected in available data. We fit a single model to data from multiple counties in the United States exhibiting different behavior. By simulating the model, we show that it is capable of exhibiting both single peak and multi-peak behavior, reproducing behavior observed in counties both in and out of the training set. We also numerically compare the error of simulations from our model with a standard SEIRD model, showing that the proposed extensions are necessary to be able to explain the spread of COVID-19.

When Did the Campaign End? An Examination of the Timing of Vote Returns in the 2008 General Election in Washington State

2012 ◽  
Vol 45 (04) ◽  
pp. 711-715 ◽  
Author(s):  
Kevin A. Pirch
Keyword(s):  
United States ◽  
Voter Turnout ◽  
The United States ◽  
Washington State ◽  
General Election ◽  
The Past ◽  
Using Data

AbstractDuring the past decade the United States has seen an increase in alternative forms to Election Day voting, including voting by mail. Voting by mail has spurred a number of studies concerning the effects it has on voter turnout and other aspects of voting. However, one important facet of voting by mail has not been examined—when people decide to send in their vote. Because ballots are mailed out weeks before the election, voting by mail creates, in effect, a rolling Election Day. This could have profound effects for campaigns as candidates must determine when to use campaign resources and campaign to an electorate who might have already voted. Using data from the 2008 general election in Washington State, this study examines when voters turned in their ballots and determines if age, partisanship, or other factors play a role in the timing of turning in a ballot.

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