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.
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.
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.
Background: Amid the rapid global spread of the coronavirus disease 2019 (COVID-19), many governments enforced country-wide lockdowns, likely with severe well-being consequences. The actions by governments triggered a debate on whether the costs of a lockdown, economically and in well-being, surpass the benefits perceived from a lower infection rate.Aim: To use the Gross National Happiness index (GNH), derived from Big Data, to investigate the determinants of happiness before and during the first few months of a lockdown in a country as an extreme case, South Africa (a country with low levels of well-being and stringent lockdown regulations). Next, to estimate (1) the probability of being happy during a pandemic year, before and after the implemented lockdown, relative to the mean happiness levels of the previous year, and (2) to utilise simulations to estimate the probability of being happy if there were no lockdown.Setting: This study considers the effect of government-mandated lockdown on happiness in South Africa.Methods: We use Big Data in the forms of Twitter and Google Trends to derive variables and ordinary least squares and ordered probit estimation methods.Results: What contributes to happiness under lockdown, except for COVID-19 cases, are the factors linked to the implemented regulations themselves. If we compare scenarios pre- and post-lockdown, we report a happiness cost of 9%. The simulations indicate that assuming there were no lockdown in 2020, the relative well-being gain is 3%.Conclusion: If policymakers want to increase happiness levels and the probability of achieving the same happiness levels as in 2019, they should consider factors related to the regulations that can increase happiness levels.
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