May the New Year bring YOU Happiness!
A data based approach using World Happiness Reports from 2015 until 2019.
Introduction
Once a year comes a survey about the global happiness, the World Happiness Report. It ranks 156 countries by how their citizens
perceive themselves to be, thanks to a referenced value called ‘Happiness Score’.
This index is being defined as a ‘Life Ladder’, with steps numbered from 0 at the bottom to 10 at the top. The top of the ladder
represents the best possible life for you. It is simply calculated by averaging the answers to a single number.
In addition, the authors have found a number of key factors that could likely explain the variance in happiness:
- the Gross Domestic Product (GDP) — the value of all the goods and services a country produced on a yearly basis.
- the Social Support — an average of all answers ‘yes’ / ‘no’ to this question:
“If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not?” - the Healthy Life Expectancy — calculated by the WHO based on over 100 different health factors.
- the Freedom to make Life Choices — an average of all answers ‘yes’ / ‘no’ to this question:
“Are you satisfied or dissatisfied with your freedom to choose what you do with your life?” - the Generosity — an average of all answers ‘yes’ / ‘no’ to this question:
“Have you donated money to a charity in the past month?” - the Perceptions of Corruption — an average of all answers ‘yes’ / ‘no’ to these questions:
“Is corruption widespread throughout the government or not?”
“Is corruption widespread within businesses or not?”
I was interested in collecting the data from Kaggle available from 2015 until 2019 to answer the following questions:
- from the different key factors , which ones are the most correlated to the ‘Happiness Index’ ?
- How are distributed the key factors per region in the World?
- What are the happiest countries? Is there any change in the top 10 ranking between 2015 and 2019?
Part 1. The Key Factors and the ‘Happiness Index’
As defined above the key factors, I was interested in finding correlations between the key factors and the ‘Happiness Score’.
From the matrix above, I could guess that the happy countries are also the wealthy countries because ‘GDP’ and ‘Happiness Score’ are highly positively correlated. Money buys happiness up to a certain degree, as it enables development, growth, convenience that could well lead to a higher level of happiness.
The same logic goes with the ‘GDP’ and ‘Health Life Expectancy’. The richer the country is, the more developed in healthcare system it is, which means consequently people live longer and healthier.
The lack of Social support seems to affect the ‘Happiness Index’ up to a certain level.
‘Trust’ and ‘Freedom’ are connected. It seems that the more people are free, the more they trust the government as it gives them more rights to express themselves.
On the contrary, it is interesting to notice that ‘Generosity’ is poorly correlated to the ‘Happiness Score’. I would like to highlight here you are paradoxically happier when you focus on sharing your own happiness. In that way, the definition of generosity should be much broader than the basic question stated above. People don’t necessarily have to donate money to charity in order to be generous. Giving money or helping a random stranger on the street are already signs of generosity. Another explanation to the less correlated value could be that the human being is becoming more and more selfish, thinking more about satisfying its own needs without supporting the others.
Part 2. The Distribution of the Key Factors all around the World
After the correlation analyzis, the next step consisted in visualizing the distribution of the Key Factors all around the world:
From the chart above, I could draw some conclusions:
- ‘Western Europe’ and ‘Australia / New Zealand’ are the happiest regions in the world. They are well ranked (if not top 1 and 2) in all criteria.
- They are the most ‘Free’, which confirms the famous statement the ‘Western Free World’. Additionnaly, the ‘Trust in Government’ is very high in the ‘Western World’. It is astonished to see that most of the countries of the world do not trust their politics. Indeed, outside the top 3 regions, the average score is below 0.1 in average (0 for ‘No’, 1 for ‘Yes’)! I deduce then here that this is not only a French thing to complain about politics but also a kind of general disapointment feeling of the politics from the world.
- It is interesting to notice ‘Southeastern Asia’ is the most ‘generous’ region whereas it is ranked 8/10 in ‘Economy’. It could be related to the fact according to their religions (for instance Buddhism or Islam), people should give a part of their income to their gods or poor people whatever the income they earn.
- The ‘Life Expectancy’ in ‘North America’ (the richest region) is lower than ‘Western Countries’ or ‘Australia / New Zealand’. It could be explained by the fact in the US the social care is private and costly. This is not accessible to everyone compared to Europe for instance. ‘Eastern Asia’ is reputed to care about the quality of their food. Besides, some countries are not completely industrialized compared to the ‘Western World’ (less polluted then).
- Unfortunately, Sub-Saharan Africa shows problems in all domains, especially ‘GDP’. Increasing its value will definitively help to improve all other domains.
Part 3. The Happiest Countries
To finish with, I was interesting in checking what the happiest countries are, and if there was any change in the top 10 ranking from 2015 to 2019.
From Part 2, I would expect that most of the top countries are from ‘Western Europe’.
Indeed, it was not surprising to see that eight of them were from this region.
The top 9 countries, which stayed in the top 10, are: Switzerland, Iceland, Denmark, Norway, Canada, Finland, Netherlands, Sweden and New Zealand.
I added to the plot the ‘Average Country’ in order to see how high in the ranking are these countries.
Finland shows above the best growth from the whole top 9 ranking, going from rank 6 in 2015 to rank 1 in 2018 (keeping its position since).
I decided then to plot the Stacked Scores in all the features, along with the rank of the country (over 156).
From the main Key Factors which are highly correlated to the ‘Happiness Score’, these countries are in the top 20. Despite an indisputable economic power, they do not belong to the most ‘generous’ countries. It confirms one more time the fact our society is heading towards a more self-centered development.
Conclusion
That concludes this brief introduction to the World Happiness Reports analyzis.
Together, we have learned:
- the Definition of the main Key Factors and how much they impact the ‘Happiness Score’.
‘Economy’, ‘Health Life Expectancy’ and ‘Social support’ play a major role in guessing the ‘Happiness Index’. You might then think that a Regression Linear Model would be enough to predict the ‘Happiness Score’ for the coming years. Unfortunately, it has been proved in social studies that there’s always a big factor of uncertainty regarding Happiness and unlike other genres of science, the results simply can never be 100% explained. That’s because our daily feeling of happiness is dependent on an endless list of (unexpected) factors, most of which are emotional and/or unmeasurable. For instance, the whole situation around COVID-19 is a capital factor in faking results for the year 2020.
- The Distribution of the Key Factors all around the world.
Without any surprise, the “Western Industrialized World” is dominating all domains. We got the confirmation of the gravity of the situation of Sub-Saharan Africa, showing unfortunately problems in all domains.
- The Happiest Countries
Most of them are from ‘Western Europe’ and they consolidate their positions in all domains for already many years.
Last but not least, it could have been interesting too, in predicting the next countries with the highest potential to see their economy or social support improving. But with the COVID-19 situation, the world economy has been damaged and therefore Learning Algorithms might not work here as many other factors play a role…
Let’s then close with wise words as Dalai Lama said:
“A happy mind is a healthy mind, and a healthy mind is good for the body.”
Stay healthy and happy!
To see more about this analysis, see the link to my Github available here.
