A year of pandemic: Levels, changes and validity of well-being data from Twitter. Evidence from ten countries.

We use daily happiness scores (Gross National Happiness (GNH)) to illustrate how happiness changed throughout 2020 in ten countries across Europe and the Southern hemisphere. More frequently and regularly available than survey data, the GNH reveals how happiness sharply declined at the onset of the pandemic and lockdown, quickly recovered, and then trended downward throughout much of the year in Europe. GNH is derived by applying sentiment and emotion analysis-based on Natural Language Processing using machine learning algorithms-to Twitter posts (tweets). Using a similar approach, we generate another 11 variables: eight emotions and three new context-specific variables, in particular: trust in national institutions, sadness in relation to loneliness, and fear concerning the economy. Given the novelty of the dataset, we use multiple methods to assess validity. We also assess the correlates of GNH. The results indicate that GNH is negatively correlated with new COVID-19 cases, containment policies, and disgust and positively correlated with staying at home, surprise, and generalised trust. Altogether the analyses indicate tools based on Big Data, such as the GNH, offer relevant data that often fill information gaps and can valuably supplement traditional tools. In this case, the GNH results suggest that both the severity of the pandemic and containment policies negatively correlated with happiness.

Positive attitudes towards COVID-19 vaccines: A cross-country analysis.

COVID-19 severely impacted world health and, as a consequence of the measures implemented to stop the spread of the virus, also irreversibly damaged the world economy. Research shows that receiving the COVID-19 vaccine is the most successful measure to combat the virus and could also address its indirect consequences. However, vaccine hesitancy is growing worldwide and the WHO names this hesitancy as one of the top ten threats to global health. This study investigates the trend in positive attitudes towards vaccines across ten countries since a positive attitude is important. Furthermore, we investigate those variables related to having a positive attitude, as these factors could potentially increase the uptake of vaccines. We derive our text corpus from vaccine-related tweets, harvested in real-time from Twitter. Using Natural Language Processing (NLP), we derive the sentiment and emotions contained in the tweets to construct daily time-series data. We analyse a panel dataset spanning both the Northern and Southern hemispheres from 1 February 2021 to 31 July 2021. To determine the relationship between several variables and the positive sentiment (attitude) towards vaccines, we run various models, including POLS, Panel Fixed Effects and Instrumental Variables estimations. Our results show that more information about vaccines' safety and the expected side effects are needed to increase positive attitudes towards vaccines. Additionally, government procurement and the vaccine rollout should improve. Accessibility to the vaccine should be a priority, and a collective effort should be made to increase positive messaging about the vaccine, especially on social media. The results of this study contribute to the understanding of the emotional challenges associated with vaccine uptake and inform policymakers, health workers, and stakeholders who communicate to the public during infectious disease outbreaks. Additionally, the global fight against COVID-19 might be lost if the attitude towards vaccines is not improved.

The impact of exogenous shocks on national wellbeing. New Zealanders' reaction to COVID-19.

In this paper, we explore the response of an aggregate measure of subjective wellbeing to the arrival and passage of the COVID-19 pandemic in a small, geographically separate economy in the South Pacific. Studies of national wellbeing and emotional responses to infection rates during a pandemic have been rare thus far. While several disciplines offer theoretical priors in the case of individuals, far less attention has been paid to the wellbeing and emotional response at a national level. Our paper contributes to the literature by applying a time-series approach to the relationship between wellbeing, emotions and the passage of a pandemic. As such we contribute to a wider literature on macro responses to exogenous shocks. Our analysis involves the use of a wellbeing index and emotional time-series derived from Big Data in the form of tweets originating within New Zealand. The index captures the daily evaluative mood of the country several weeks before the first domestic case of COVID-19 was recorded until several weeks of no new COVID-19 cases. We find distinct reactions to the pandemic: a initial fall in national wellbeing generated by a decrease in the emotions 'joy', 'anticipation' and 'trust'. Following a rapid and severe lockdown designed to limit domestic transmission of the virus national wellbeing recovered relatively quickly. Gaining insight into the wellbeing (happiness) reponse to pandemics at the national level is important because the average level of happiness within countries is known to be associated with a range of economic, social, health and political outcomes.

The evolution of happiness pre and peri-COVID-19: A Markov Switching Dynamic Regression Model.

Happiness levels often fluctuate from one day to the next, and an exogenous shock such as a pandemic can likely disrupt pre-existing happiness dynamics. This paper fits a Marko Switching Dynamic Regression Model (MSDR) to better understand the dynamic patterns of happiness levels before and during a pandemic. The estimated parameters from the MSDR model include each state's mean and duration, volatility and transition probabilities. Once these parameters have been estimated, we use the one-step method to predict the unobserved states' evolution over time. This gives us unique insights into the evolution of happiness. Furthermore, as maximising happiness is a policy priority, we determine the factors that can contribute to the probability of increasing happiness levels. We empirically test these models using New Zealand's daily happiness data for May 2019 -November 2020. The results show that New Zealand seems to have two regimes, an unhappy and happy regime. In 2019 the happy regime dominated; thus, the probability of being unhappy in the next time period (day) occurred less frequently, whereas the opposite is true for 2020. The higher frequency of time periods with a probability of being unhappy in 2020 mostly correspond to pandemic events. Lastly, we find the factors positively and significantly related to the probability of being happy after lockdown to be jobseeker support payments and international travel. On the other hand, lack of mobility is significantly and negatively related to the probability of being happy.

The impact of exogenous shocks on national wellbeing. New Zealanders’ reaction to COVID-19

In this paper, we explore the response of an aggregate measure of subjective wellbeing to the arrival and passage of the COVID-19 pandemic in a small, geographically separate economy in the South Pacific. Studies of national wellbeing and emotional responses to infection rates during a pandemic have been rare thus far. While several disciplines offer theoretical priors in the case of individuals, far less attention has been paid to the wellbeing and emotional response at a national level. Our paper contributes to the literature by applying a time-series approach to the relationship between wellbeing, emotions and the passage of a pandemic. As such we contribute to a wider literature on macro responses to exogenous shocks. Our analysis involves the use of a wellbeing index and emotional time-series derived from Big Data in the form of tweets originating within New Zealand. The index captures the daily evaluative mood of the country several weeks before the first domestic case of COVID-19 was recorded until several weeks of no new COVID-19 cases. We find distinct reactions to the pandemic: a initial fall in national wellbeing generated by a decrease in the emotions ‘joy’, ‘anticipation’ and ‘trust’. Following a rapid and severe lockdown designed to limit domestic transmission of the virus national wellbeing recovered relatively quickly. Gaining insight into the wellbeing (happiness) reponse to pandemics at the national level is important because the average level of happiness within countries is known to be associated with a range of economic, social, health and political outcomes.

A Tale of Three Countries: What is the Relationship Between COVID-19, Lockdown and Happiness?

The COVID-19 pandemic led many governments to implement lockdown regulations to curb the spread of the virus. Though lockdowns do minimise the physical damage caused by the virus, there may also be substantial damage to population well-being. Using a pooled data set, we analyse the relationship between a mandatory lockdown and happiness in three diverse countries: South Africa, New Zealand and Australia. These countries differ amongst others in terms of lockdown regulations and duration. The primary aim is to determine, whether a lockdown is negatively associated with happiness, notwithstanding the characteristics of a country or the strictness of the lockdown regulations. Second, we compare the effect size of the lockdown on happiness between these countries. We use Difference-in-Difference estimations to determine the association between lockdown and happiness and a Least Squares Dummy Variable estimation to study the heterogeneity in the effect size of the lockdown by country. Our results show that a lockdown is associated with a decline in happiness, regardless of the characteristics of the country or the type and duration of its lockdown regulations. Furthermore, the effect size differs between countries in the sense that the more stringent the stay-at-home regulations are, the greater it seems to be.

The good, the bad and the ugly of lockdowns during Covid-19.

Amidst the rapid global spread of Covid-19, many governments enforced country-wide lockdowns, with likely severe well-being consequences. In this regard, South Africa is an extreme case suffering from low levels of well-being, but at the same time enforcing very strict lockdown regulations. In this study, we analyse the causal effect of a lockdown and consequently, the determinants of happiness during the aforementioned. A difference-in-difference approach is used to make causal inferences on the lockdown effect on happiness, and an OLS estimation investigates the determinants of happiness after lockdown. The results show that the lockdown had a significant and negative impact on happiness. In analysing the determinants of happiness after lockdown, we found that stay-at-home orders have positively impacted happiness during this period. On the other hand, other lockdown regulations such as a ban on alcohol sales, a fear of becoming unemployed and a greater reliance on social media have negative effects, culminating in a net loss in happiness. Interestingly, Covid-19, proxied by new deaths per day, had an inverted U-shape relationship with happiness. Seemingly people were, at the onset of Covid-19 positive and optimistic about the low fatality rates and the high recovery rates. However, as the pandemic progressed, they became more concerned, and this relationship changed and became negative, with peoples' happiness decreasing as the number of new deaths increased.