ABSTRACT
Walmart is a major player in the US retail sector and was one of the grocery corporations that bucked the trend of declining retail sales at the start of the COVID-19 pandemic in 2020. Particularly in the initial stages of the pandemic, governance priorities focussed on restricting the movement of people and closing non-essential retailers and service providers to slow the spread of the virus and keep people safe. This paper investigates the impact of non-pharmaceutical interventions, in the form of lockdown stringency measures, on consumer purchasing behaviours for essential goods over the onset of the pandemic. Focussing on both instore and online sales outcomes for Walmart in the US, we examine changes between pre-pandemic trends in two different sales outcomes, sales transactions and total spend, and trends in 2020. We then employ a series of multi-level regression models to estimate the impact that imposed stringency measures had on these sales outcomes, at both national and state level. Results indicate that nationally consumers were making fewer, larger physical shopping trips and huge increases in online sales was seen ubiquitously across the country. Novel and expansive insights from such a wide-spread retailer, such as Walmart, can help retailers, stakeholders and policy makers understand changing consumption trends to inform business strategies and resilience planning for the future. Furthermore, this study highlighted the value of examining spatial trends in sales outcomes and hopes to influence greater consideration of this in future research.
ABSTRACT
The present study examined the impact of meteorological variations and preventive policy measures on the spread and mortality of COVID-19 in ten European countries. The results from negative binomial regression indicated that the average period of high death count is characterised with low average temperature and confirmed that respiratory infections are enhanced during cold and low humidity conditions. The role of suggested and implemented preventive measures by the respective governments showed the effectiveness of all the measures taken to reduce the probability of mortality. Nonetheless, the effect of educational institutes' closure remained significantly higher than other preventive measures. The study suggested less exposure to low temperature and smart lockdowns to avoid deaths during the predicted waves of COVID-19.
ABSTRACT
To address the economic losses caused by the COVID-19 pandemic, countries have implemented, together with policies aimed at stopping the spread of the virus, a mixture of fiscal and monetary measures. This work investigates the effect of containment policies and economic support measures on economic growth in the short run, investigating a time window of six quarters in a cross country perspective. Our results confirm the existence of a negative effect of stringency measures on GDP; we also detect a positive effect from economic support measures. Moreover, looking at the interaction between these two kinds of interventions, our findings suggest that up to a relatively low level of stringency policies, economic support measures are able to positively counterbalance the negative impact of containment and closure policies. When the level of closures became more severe, however, the economic support measures that countries adopt are not able to completely recoup, in the short run, the economic losses due to stringency policies. Results suggest that in order to have a positive net effect, policymakers should take into account the level of stringency measures implemented before investing in economic support.
Subject(s)
COVID-19 , Daucus carota , Health Policy , Humans , Pandemics/prevention & control , Program EvaluationABSTRACT
Corruption is considered in the literature as an activity with several externalities and spillover effects. Adding to the recent research on the corruption-COVID-19 nexus, we study the impact of corruption on coronavirus cases. High perceived levels of corruption have been proven to lead to lower institutional trust, and hence possibly to lower levels of citizen compliance with non-pharmaceutical interventions (NPIs), such as lockdowns, imposed by the authorities during the first wave of the pandemic to reduce the spread of coronavirus. Applying quantitative analysis with the use of hybrid models, we find that in countries with higher levels of perceived corruption, across alternative corruption measures, more COVID-19 cases are observed, ceteris paribus. This suggests that corruption has a detrimental effect on the spread of COVID-19, and that countries experiencing higher levels of corruption should pay extra attention when implementing NPIs.
Subject(s)
COVID-19 , Communicable Disease Control , Humans , Pandemics/prevention & control , SARS-CoV-2ABSTRACT
This paper examines the effects of stringency measures (provided by the Oxford Coronavirus Government Response Tracker) and total time spent away from home (provided by the Google COVID-19 Community Mobility Reports) on the COVID-19 outcomes (measured by total COVID-19 cases and total deaths related to the COVID-19) in the United States. The paper focuses on the daily data from March 11, 2020 to August 13, 2021. The ordinary least squares and the machine learning estimators show that stringency measures are negatively related to the COVID-19 outcomes. A higher time spent away from home is positively associated with the COVID-19 outcomes. The paper also discusses the potential economic implications for the United States.
Subject(s)
COVID-19 , Government , Humans , SARS-CoV-2 , Social Mobility , United StatesABSTRACT
Background: The COVID-19 pandemic is having major adverse consequences for the mental health of individuals worldwide. Alongside the direct impact of the virus on individuals, government responses to tackling its spread, such as quarantine, lockdown, and physical distancing measures, have been found to have a profound impact on mental health. This is manifested in an increased prevalence of anxiety, depression, and sleep disturbances. As older adults are more vulnerable and severely affected by the pandemic, they may be at increased psychological risk when seeking to protect themselves from COVID-19. Methods: Our study aims to quantify the association between the stringency of measures and increased feelings of sadness/depression in a sample of 31,819 Europeans and Israelis aged 65 and above. We hypothesize that more stringent measures make it more likely that individuals will report increased feelings of sadness or depression. Conclusions: We found that more stringent measures across countries in Europe and Israel affect the mental health of older individuals. The prevalence of increased feelings of sadness/depression was higher in Southern European countries, where the measures were more stringent. We therefore recommend paying particular attention to the possible effects of pandemic control measures on the mental health of older people.
Subject(s)
COVID-19 , Pandemics , Aged , Anxiety , Communicable Disease Control , Depression/epidemiology , Europe/epidemiology , Government , Humans , Israel/epidemiology , Quarantine , SARS-CoV-2ABSTRACT
BACKGROUND: In response to COVID-19, the Swedish government imposed few travel and mobility restrictions. This contrasted with its Scandinavian neighbours which implemented stringent restrictions. The influence these different approaches had on mobility, and thus on COVID-19 mortality was investigated. METHODS: Datasets indicating restriction severity and community mobility were examined; Google's 'Community Movement Reports' (CMR) show activity at key location categories; the Oxford COVID-19 Government Response Tracker collates legislative restrictions into a 'Stringency Index' (SI). RESULTS: CMR mobility categories were negatively correlated with COVID-19 mortality. The strongest correlations were obtained by negatively time lagging mortality data, suggesting restrictions had a delayed influence. During the 'first wave' a model using SI (AIC 632.87) proved favorable to one using contemporaneous CMR data and SI (AIC 1193.84), or lagged CMR data and SI (AIC 642.35). Validation using 'second wave' data confirmed this; the model using SI solely again being optimal (RMSE: 0.2486 vs. 0.522 and 104.62). Cross-country differences were apparent in all models; Swedish data, independent of SI and CMR, proved significant throughout. There was a significant association for Sweden and the death number across models. CONCLUSION: SI may provide a broader, more accurate, representation of changes in movement in response to COVID-19 restrictions.