Unequal Welfare Costs of Staying at Home across Socioeconomic and Demographic Groups
TL;DR: In this paper, the welfare costs of staying at home due to COVID-19 across socioeconomic and demographic groups were investigated using daily census block group level data from the U.S.
Abstract: Using daily census block group level data from the U.S., this paper investigates the welfare costs of staying at home due to COVID-19 across socioeconomic and demographic groups. The investigation is based on an economic model of which implications suggest that the welfare costs of staying at home increase with the stay-at-home probabilities of individuals. The empirical results provide evidence for significant heterogeneity across census block groups regarding the welfare effects of staying at home. This heterogeneity is further used to obtain measures of welfare changes for different socioeconomic and demographic groups at the national level.
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TL;DR: The authors study how the differential timing of local lockdowns due to COVID-19 causally affects households' spending and macroeconomic expectations at the local level using several waves of a customized survey with more than 10,000 respondents.
Abstract: We study how the differential timing of local lockdowns due to COVID-19 causally affects households’ spending and macroeconomic expectations at the local level using several waves of a customized survey with more than 10,000 respondents. About 50% of survey participants report income and wealth losses due to the corona virus, with the average losses being $5,293 and $33,482 respectively. Aggregate consumer spending dropped by 31 log percentage points with the largest drops in travel and clothing. We find that households living in counties that went into lockdown earlier expect the unemployment rate over the next twelve months to be 13 percentage points higher and continue to expect higher unemployment at horizons of three to five years. They also expect lower future inflation, report higher uncertainty, expect lower mortgage rates for up to 10 years, and have moved out of foreign stocks into liquid forms of savings. The imposition of lockdowns can account for much of the decline in employment in recent months as well as declines in consumer spending. While lockdowns have pronounced effects on local economic conditions and households’ expectations, they have little impact on approval ratings of Congress, the Fed, or the Treasury but lead to declines in the approval of the President.
243 citations
TL;DR: A multimodal learning framework that amalgamates statistical regression and machine learning models for predicting local COVID-19 cases in Germany and corroborate that during most of the observational period more dispersed meeting patterns and a lower percentage of people staying put are associated with higher infection rates.
19 citations
TL;DR: The authors examined the relationship between statewide contexts and individuals' COVID-19 vaccine hesitancy by using the Household Pulse Survey, a national and near real-time data timely deployed by the U.S. Census Bureau.
Abstract: This study examines the relationship between statewide contexts and individuals’ COVID-19 vaccine hesitancy by using the Household Pulse Survey, a national and near real-time data timely deployed by the U.S. Census Bureau. Controlling for the individual- and state-level variables in addition to temporal effect, this study finds that racial and ethnic minorities and COVID-19-infected people are more hesitant than their counterparts to receive a vaccine. Individuals who reside in a state where more stringent social distancing measures – particularly mask mandate – are implemented and vaccine rollout conditions are better appear to be less hesitant to receive a COVID-19 vaccine. Vulnerable subpopulation groups such as people of color and COVID-19-infected individuals are more hesitant to vaccine uptake even if regional circumstances are equal. These findings suggest that the continuation and extension of vaccine campaigns at the regional as well as individual levels are all important for expediting COVID-19 vaccination and reducing vaccine hesitancy as the world is in the middle of the third year of the pandemic.
2 citations
TL;DR: In this article , the spatial distribution of HEMO and its transition were not examined, and the effect of household attributes on the duration of out-of-home situations was not analyzed statistically.
Abstract: ABSTRACT Nobody-at-home situations can cause several problems, such as home-delivery failures and burglaries. A recent study demonstrated temporal profiles of households with every member out-of-home (HEMO) situation by using household travel surveys. However, the spatial distribution of HEMO and its transition were not examined, and the effect of household attributes on HEMO was not analyzed statistically. In this study, the spatiotemporal variation in HEMO duration was investigated to address this gap, and the duration was analyzed using two econometric models. The 1984, 1997, and 2012 household travel surveys from Kumamoto, Japan, were used for the spatiotemporal visualization. In addition, the Tobit model and time allocation model were developed to statistically determine the reason for the variation in duration. The average HEMO duration increased by more than 1 h between 1984 and 2012. The downtown area revealed a longer HEMO duration, and the area with a longer duration expanded to rural areas between 1984 and 2012. The estimated econometric models revealed the statistical impacts of household attributes on HEMO duration. The HEMO duration of single-person households with a worker or student was long, and that of households with a working husband and homemaker wife was short. The spatiotemporal distribution of HEMO durations presented in this paper has the potential to be used in future urban studies, including those on the logistics of home-delivery, home-visiting survey design, crime prevention, and energy research.
1 citations
References
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Uppsala University1, Karolinska Institutet2, University of Glasgow3, University College London4, University of Oxford5, King's College London6, University of Exeter7, Black Dog Institute8, University of California, Irvine9, University of Cambridge10, Swansea University11, Guy's and St Thomas' NHS Foundation Trust12, UCL Institute of Child Health13, St George's, University of London14, Emory University15, University of Bristol16, Academy of Medical Sciences, United Kingdom17
TL;DR: There is an urgent need for research to address how mental health consequences for vulnerable groups can be mitigated under pandemic conditions, and on the impact of repeated media consumption and health messaging around COVID-19.
3,909 citations
TL;DR: Having relatives or acquaintances infected with COVID-19 was a risk factor for increasing the anxiety of college students and economic effects, and effects on daily life, as well as delays in academic activities, were positively associated with anxiety symptoms.
Abstract: A COVID-19 epidemic has been spreading in China and other parts of the world since December 2019. The epidemic has brought not only the risk of death from infection but also unbearable psychological pressure. We sampled college students from Changzhi medical college by using cluster sampling. They responded to a questionnaire packet that included the 7-item Generalized Anxiety Disorder Scale (GAD-7) and those inquiring the participants' basic information. We received 7,143 responses. Results indicated that 0.9% of the respondents were experiencing severe anxiety, 2.7% moderate anxiety, and 21.3% mild anxiety. Moreover, living in urban areas (OR = 0.810, 95% CI = 0.709 - 0.925), family income stability (OR = 0.726, 95% CI = 0.645 - 0.817) and living with parents (OR = 0.752, 95% CI = 0.596 - 0.950) were protective factors against anxiety. Moreover, having relatives or acquaintances infected with COVID-19 was a risk factor for increasing the anxiety of college students (OR = 3.007, 95% CI = 2.377 - 3.804). Results of correlation analysis indicated that economic effects, and effects on daily life, as well as delays in academic activities, were positively associated with anxiety symptoms (P < .001). However, social support was negatively correlated with the level of anxiety (P < .001). It is suggested that the mental health of college students should be monitored during epidemics.
3,460 citations
TL;DR: The feasibility of working at home for all occupations is classified and it is found that 37% of jobs in the United States can be performed entirely at home, with significant variation across cities and industries.
742 citations
TL;DR: In this paper, the authors developed a quantitative model of internal city structure that features agglomeration and dispersion forces and an arbitrary number of heterogeneous city blocks, which can account both qualitatively and quantitatively for the observed changes in city structure.
Abstract: This paper develops a quantitative model of internal city structure that features agglomeration and dispersion forces and an arbitrary number of heterogeneous city blocks. The model remains tractable and amenable to empirical analysis because of stochastic shocks to commuting decisions, which yield a gravity equation for commuting flows. To structurally estimate agglomeration and dispersion forces, we use data on thousands of city blocks in Berlin for 1936, 1986, and 2006 and exogenous variation from the city's division and reunification. We estimate substantial and highly localized production and residential externalities. We show that the model with the estimated agglomeration parameters can account both qualitatively and quantitatively for the observed changes in city structure. We show how our quantitative framework can be used to undertake counterfactuals for changes in the organization of economic activity within cities in response, for example, to changes in the transport network.
318 citations
TL;DR: In this paper, the differential timing of local lockdowns due to COVID-19 causally affects households' spending and macroeconomic expectations at the local level at the macroeconomic level.
Abstract: We study how the differential timing of local lockdowns due to COVID-19 causally affects households’ spending and macroeconomic expectations at the local level
279 citations