•	country

•	income

•	gender

•	age

•	type of work. 


Indiana University

Of all of the factors used to measure the overall happiness index, the income is measured and compared across 5 different categories to help visualize and interpret the data.  

How the Income Factor is measured across 5 categories.  

World Happiness Report 2021

5 Categories 

The global economic impacts of the crisis have been so far highly unequal, with disproportionate effects in developing countries. 

Workers in lower-middle-income countries have experienced a 43 percent larger reduction in working hours and labour income than in high-income countries. Informal sector workers make up a considerable portion of the labour force in developing countries.

Estimates from the ILO suggest that 1.6 billion informal sector workers have seen their hours decrease since the onset of the pandemic. 

In low-income countries, the resulting drop in earnings is estimated to be 86 percent. 

Many governments in low-income countries have also been financially incapable of providing workers with sufficient economic relief.


Differences in impact between countries 

Young people are facing multiple social and economic shocks resulting from the COVID-19 crisis. The International Labour Organization (ILO) found that roughly 178 million young people – 1 in 4 of the global working population between the ages of 15 and 24 – worked in the hardest-hit sectors when the pandemic began. 

Young women, in particular, make up more than half of youth employment in food and accommodation. More than 75 percent of young workers are also informally employed. In low-income countries, this percentage climbs to above 90 percent.

The resulting increases in youth unemployment and inactivity have been severe. Between February and July 2020, employment among adults declined by 5.1 percent, while employment among young adults fell by 17.4 percent, more than three times as much.



Differences in impact on Age

Women have benn particularly vulnerable to the labour market consequences of the pandemic. 
Globally, four in ten employed women work in sectors that were hard-hit COVID-19, including travel, retail, food, accommodation, and services. 

In low-and middle-income countries, women are also much more likely to be employed in domestic work, a sector in which three out of four workers were at risk of losing their job in June 2020. 

At the same time, women are also overrepresented in certain essential sectors, including health and social work, exposing them to greater physical and mental health risks. 

In many high-income countries, more than 80 percent of the health workforce is made up of women. 

Childcare responsibilities arising as a result of school closures can also play a role in the reduction of working mothers’ labour supply.

Single parents are particularly at risk, of whom almost four out of five around the world are women.

Gendered impacts of COVID-19 

Differences in the extent to which workers can shift to a home office have become extremely salient during the pandemic. The ability to work from home has been an important predictor of job loss. These impacts have also varied considerably by sector. Accommodation and food service employees have been particularly hard hit.  Workers employed under less secure work arrangements have also been more likely to lose their job or suffer earnings losses during the crisis.

Differences in impact on type of work

Vulnerable workers were also at greater risk of experiencing low subjective well-being before the pandemic took root. Low-income and low-skill workers are typically less satisfied with their jobs while also more dependent on them.

White-collar workers include managers, senior administrators, higher technical workers, professionals, and clerical workers. Blue-collar workers include those performing skilled or unskilled manual labour. Both groups’ happiness levels also began to decline dramatically in February and March, before the first national lockdown was implemented. Beginning in April, happiness levels began to steadily rebound for both groups, although white-collar workers recovered significantly faster than blue-collar workers after the first wave. 


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