Happiness lost: Was the decision to implement lockdown the correct one?
| Autor: | Talita Greyling, Tamanna Adhikari, Stephanié Rossouw |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
south africa
Gross National Happiness Index (economics) HF5001-6182 Coronavirus disease 2019 (COVID-19) media_common.quotation_subject Big data Ordered probit big data regulations 0502 economics and business Management. Industrial management Economics happiness Business HB71-74 media_common 050208 finance business.industry 05 social sciences HD28-70 General Business Management and Accounting Economics as a science covid-19 Ordinary least squares Happiness Demographic economics Estimation methods business General Economics Econometrics and Finance 050203 business & management |
| Zdroj: | South African Journal of Economic and Management Sciences, Vol 24, Iss 1, Pp e1-e11 (2021) |
| ISSN: | 2222-3436 1015-8812 |
| DOI: | 10.4102/sajems.v24i1.3795 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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