The authors

Talita Greyling: School of Economics, University of Johannesburg, South Africa, and GLO; email: talitag@uj.ac.za
Stephanié Rossouw: Faculty of Business, Economics and Law, Auckland University of Technology, Auckland, New Zealand,and GLO; email: stephanie.rossouw@aut.ac.nz

The analysis

Traditionally, economists measured the well-being of people or a nation by using objective economic indicators such as gross domestic product (GDP). We know that these indicators do not measure well-being per se, but merely specific conditions, which is believed to lead to a good life. What we should be measuring is whether people’s lives are getting better? In general, when people are happy and satisfied with their life, it signals that they have a higher level of well-being.

Gross National Happiness (GNH) refers to the level of happiness for a group of citizens or nations and the best-known surveys that captures cross country data are the Gallup World Poll Survey data and World Value Survey data. In these surveys we find measures of subjective-wellbeing, thus evaluative happiness, which if averaged across a country gives the mean subjective well-being of a specific country. Although these measures of subjective well-being are very useful and informative there are significant time-lags between real-time events and the reporting of this evaluative happiness levels. What is needed is a real-time measure of happiness.

Using social media and the voluntary information sharing structure of Twitter, Greyling and Rossouw (in collaboration with AFSTEREO) have been determining the happiness in real-time (mood) of citizens in Australia, New Zealand and South Africa since April 2019 (http://gnh.today/), and lately also been analyzing the specific emotions of Tweets, distinguishing between eight emotions, anger, anticipation, disgust, fear, joy, sadness and surprise.

They analyze extracted Tweets using sophisticated software to determine the sentiment and the emotions of the Tweets. Sentiment analysis is used to label a ‘live’ stream of tweets of these countries as having either a positive, neutral or negative sentiment after which a sentiment balance algorithm is applied to derive a happiness score. The scale of the happiness scores is between 0 (not happy) and 10 (very happy), with 5 being neutral, thus neither happy nor unhappy. In this manner, they have been tracking the ‘mood’ of these nations and analyzed the impact of various economic (industrial actions), political (national elections), social (death of Kobe Bryant and COVID-19, xenophobia, music concerts) and sport events on happiness levels, as early as one hour after it happened. See Figures 1-3 for a peek into what the happiness index can ascertain.

As can be seen from Figure 1, on 25 January when Australia confirmed its first COVID-19 case, there was very little reaction. Happiness even increased somewhat after the announcement, though the higher levels of happiness were related top sport events. The dip in the happiness on 27 March was due to the death of the American basketball player, Kobe Bryant’. On 17 March when Prime Minister Scott Morrison banned gatherings larger than 100 people, we for the first time saw a significant decrease in the happiness levels. The Australians are not on complete lockdown, but it seems that their happiness levels continue to stay below pre-Corona times. We will be tracking these changes in the coming weeks, to see if the happiness levels return to pre-Corona levels as time goes by.

Coincidentally, until the outbreak of COVID-19, the lowest happiness level in New Zealand was on 27 January (6.43), also signalling New Zealander’s empathy with Kobe Bryant’s death. As can be seen from the Figure 2, on 28 February when New Zealand confirmed its first COVID-19 case, there was very little reaction. On 4 March, New Zealand experienced the ‘Toilet paper apocalypse’, but it wasn’t until 13 March that the lowest level of happiness (6.37) was recorded. People were devastated by all the concert and festival cancellations, because of COVID-19. The first day of complete lockdown was on 26 March. We will be monitoring whether New Zealanders adjust to their new normal over the coming weeks.

As can be seen from Figure 3, on 6 March when South Africa confirmed its first COVID-19 case, the happiness level was above the average for the period preceding the outbreak, as well as the total average. It wasn’t until 16 March when reality set in for most South Africans after President Cyril Ramaphosa declared a national state of disaster, that we saw a decrease in happiness levels. When the announcement came on 23 March, that a complete lockdown of South Africa will commence on 27 March, the index fell to its lowest level yet (5.35). We will be monitoring whether South Africans adjust to their new normal over the coming weeks.

Technical Support by AFSTEREO

Reference
Greyling T. & Rossouw S. 2020. Gross National Happiness Project. Afstereo (IT partner). University of Johannesburg (funding agency). Pretoria, South Africa.  www.gnh.today.

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GLO Discussion Papers are research and policy papers of the GLO Network which are widely circulated to encourage discussion. Provided in cooperation with EconStor, a service of the ZBW – Leibniz Information Centre for Economics, GLO Discussion Papers are among others listed in RePEc (see IDEAS, EconPapers). Complete list of all GLO DPs downloadable for free.

GLO Discussion Paper of the Month: March

GLO Discussion Paper No. 494, 2020

Impacts of Social and Economic Factors on the Transmission of Coronavirus Disease 2019 (COVID-19) in China
by Qiu, Yun & Chen, Xi & Shi, Wei
PDF of the GLO Discussion Paper

Related interview: #Coronavirus and now? GLO – Interview with Top #Health Economist Xi Chen of Yale University
Other related GLO activities.

GLO Fellows Yun Qiu & Xi Chen & Wei Shi

• Yun Qiu & Wei Shi are Professors at the Institute for Economic and Social Research (IESR), Jinan University, China
• Xi Chen is a Professor at Yale University & President of the China Health Policy and Management Society

Author Abstract: This paper examines the role of various socioeconomic factors in mediating the local and cross-city transmissions of the novel coronavirus 2019 (COVID-19) in China. We implement a machine learning approach to select instrumental variables that strongly predict virus transmission among the rich exogenous weather characteristics. Our 2SLS estimates show that the stringent quarantine, massive lockdown and other public health measures imposed in late January significantly reduced the transmission rate of COVID-19. By early February, the virus spread had been contained. While many socioeconomic factors mediate the virus spread, a robust government response since late January played a determinant role in the containment of the virus. We also demonstrate that the actual population flow from the outbreak source poses a higher risk to the destination than other factors such as geographic proximity and similarity in economic conditions. The results have rich implications for ongoing global efforts in containment of COVID-19.

GLO Discussion Papers of March 2020

506 The Dynamic Electoral Returns of a Large Anti-Poverty Program – Download PDF
by Zimmermann, Laura

505 Do Public Program Benefits Crowd Out Private Transfers in Developing Countries? A Critical Review of Recent Evidence – Download PDF
by Nikolov, Plamen & Bonci, Matthew

504 Why Guarantee Employment? Evidence from a Large Indian Public-Works Program – Download PDF
by Zimmermann, Laura

503 Wage Setting and Unemployment: Evidence from Online Job Vacancy Data – Download PDF
by Faryna, Oleksandr & Pham, Tho & Talavera, Oleksandr & Tsapin, Andriy

502 Sentiment, emotions and stock market predictability in developed and emerging markets – Download PDF
by Steyn, Dimitri H. W. & Greyling, Talita & Rossouw, Stephanie & Mwamba, John M.

501 Who’s declining the “free lunch”? New evidence from the uptake of public child dental benefits – Download PDF
by Nguyen, Ha Trong & Le, Huong Thu & Connelly, Luke B.

500 Paradise Postponed: Future Tense and Religiosity – Download PDF
by Mavisakalyan, Astghik & Tarverdi, Yashar & Weber, Clas

499 Game of Prejudice – Experiments at the Extensive and Intensive Margin – Download PDF
by Dasgupta, Utteeyo & Mani, Subha & Vecci, Joe & Želinský, Tomáš

498 Welfare Magnets and Internal Migration in China – Download PDF
by Jin, Zhangfeng

497 Gender Bias and Intergenerational Educational Mobility: Theory and Evidence from China and India – Download PDF
by Emran, M. Shahe & Jiang, Hanchen & Shilpi, Forhad

496 What Do Employers’ Associations Do? – Download PDF
by Martins, Pedro S.

495 Does vocational education pay off in China? Instrumental-variable quantile-regression evidence – Download PDF
by Dai, Li & Martins, Pedro S.

494 Impacts of Social and Economic Factors on the Transmission of Coronavirus Disease 2019 (COVID-19) in China – Download PDF
by  Qiu, Yun & Chen, Xi & Shi, Wie

493 Flexible Work Arrangements and Precautionary Behavior: Theory and Experimental Evidence – Download PDF
by  Orland, Andreas & Rostam-Afschar, Davud

492 Life Satisfaction, Subjective Wealth, and Adaptation to Vulnerability in the Russian Federation during 2002-2017 – Download PDF
by  Dang, Hai-Anh H. & Abanokova, Kseniya & Lokshin, Michael M.

491 Unobserved Worker Quality and Inter-Industry Wage Differentials – Download PDF
by  Ge, Suqin & Macieira, João

490 Climate Shocks and Teenage Fertility – Download PDF
by  Dessy, Sylvain & Marchetta, Francesca & Pongou, Roland & Tiberti, Luca

489 Intergenerational Occupational Mobility in Latin American Economies: An Empirical Approach – Download PDF
by  Doruk, Ömer Tuğsal & Pastore, Francesco & Yavuz, Hasan Bilgehan

488 Employee Training and Firm Performance: Quasi-experimental evidence from the European Social Fund – Download PDF
by Martins, Pedro S.

487 France and Germany Exceed Italy, South Korea and Japan in Temperature-Adjusted Corona Proliferation: A Quick and Dirty Sunday Morning Analysis – Download PDF
by Puhani, Patrick A.

486 Business visits, technology transfer and productivity growth – Download PDF
by  Piva, Mariacristina & Tani, Massimiliano & Vivarelli, Marco

485 A Broken Social Elevator? Employment Outcomes of First- and Second-generation Immigrants in Belgium – Download PDF
by  Piton, Céline & Rycx, François

484 What Does Someone’s Gender Identity Signal to Employers? – Download PDF
by  Van Borm, Hannah & Dhoop, Marlot & Van Acker, Allien & Baert, Stijn

483 The Future of Work in Developing Economies: What can we learn from the South? – Download PDF
by  Egana del Sol, Pablo

482 Performance Feedback and Peer Effects – Download PDF
by  Villeval, Marie Claire

481 Ethnicity differentials in academic achievements: The role of time investments – Download PDF
by  Nguyen, Ha Trong & Connelly, Luke B. & Le, Huong Thu & Mitrou, Francis & Taylor, Catherine L. & Zubrick, Stephen R.

480 Conversionary Protestants do not cause democracy – Download PDF
by Nikolova, Elena & Polansky, Jakub

GLO DP Managing Editor: Magdalena Ulceluse, University of Groningen. DP@glabor.org

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