Happiness and Economics: Can Money Really Make You Happy?

We have often heard the old adage, "money can't buy happiness" but how much of that is really factual in today's society? COVID-19 has not only affected people's health but their finances too. So how strong is the link between income and well-being? In this study, we examine the relationship between happiness and a variety of economic and social factors to answer that very question. Using 25 independent variables to represent economic development, trade and globalization, governance, health spending and state fragility across 106 countries, several regressions were run to see the relation between those variables and the Gallup's World Poll used for the Happiness Index.

Key Findings

Happiness Index

The Happiness Index is compiled every year by the World Gallup Poll, with the respondents across 146 countries being asked to rank their life on a scale of 0 to 10, with 0 being the worst possible life and 10 being the best. When analyzing the top countries on the Happiness Index list each year, it becomes apparent that while many are developed economies, GDP per capita was not a good indicator of happiness.

So what do these countries have in common? It is often assumed that people's happiness is closely tied with their country's GDP per capita, which is also often an indicator of how developed the country is. However, looking at the table above, while they all meet certain development standards, the top 10 happiest countries are not at all aligned with those countries which have the highest GDP per capita. So what could account for this difference if not GDP per capita?

Happiness Index 2019 vs GDP per capita, PPP 2019

Which Indicators Most Closely Predict Happiness Globally?

After performing statistical analysis of 25 indicators across 106 countries between 2008 and 2019, we found that 74.4% of people's happiness worldwide can be attributed to a combination of the top 5 indicators, in the order of importance. While GDP per capita is leading, both economic and social indicators take the lead when it comes to global analysis of happiness.

Top Happiness Indicators Globally 2008-2019

So what do the top countries on the Happiness Index all have in common? Aside from our global analysis which outlines top five indicators, there are a few others which these countries rank highest on.

Money Is Indeed Important

Although money doesn't seem to be the only key factor when it comes to happiness, data suggests that it is indeed very important. Not only is GDP per capita the highest predictor of global happiness over the past 11 years, it is the only indicator that ranks in the top 5 most important factors for the APAC, the Americas and Europe. Youth unemployment, another economic indicator, ranked as the 2nd most important factor influencing people's happiness globally.

What this data suggests is that having a steady source of income is the most important indicator of happiness, for without it, basic human needs such as quality healthcare, safety and security cannot be met. When basic human needs cannot be met, most people don't focus on other areas of life such as education, health and political or social issues. The very basic need is to have employment which provides a steady income. For the majority of countries where people struggle to make ends meet, it is no surprise that GDP per capita is key to their happiness, which in that context is synonymous with survival.

But That's Not All...

However, economic indicators alone cannot fully explain global happiness, otherwise the Happiness Index list would be identical to the list of countries with highest GDP per capita. Of the top five global happiness indicators, two are economic (GDP per capita and youth unemployment) and three are social (social support, health spending and generosity).

Especially for the developed countries where basic needs are met and ensured by governments, such as healthcare and education, decent income and basic security, GDP per capita will likely play less of a key role in determining happiness. Of the four regions analyzed in this study, Europe is the one that dominates the happiness index year after year and happens to be one region with the highest number of developed countries. It is also the only one which stands out as having the highest number of governance indicators of happiness among all regional and global regressions.

Which Indicators Most Closely Predict Happiness Regionally?

While the regression analysis carried out on a global scale was useful in the overall understanding of which factors most closely predict how happy people are, it is also important to study whether on a regional level, those will differ. As the analysis shows, each region differs on which economic and social indicators are most affecting their well-being. In particular, while economic indicators were the most important in predicting happiness in the Americas and in APAC countries, social indicators were leading in Africa. Europe stood out as an exception, as governance indicators were leading in the region.

Asia-Pacific (APAC)

Key factors: Governance and Economic

Model accuracy: 73.8%

While in the Asia-Pacific region, happiness is most closely predicted by control of corruption which is followed by GDP per capita; the indicator strength of each is nearly identical. While GDP per capita is an obvious finding given its prevalence globally, the fact that social support also ranked so highly in Asia may be due to the cultural importance of nuclear families in the region.

Interestingly, political stability—the perception of the likelihood that a government will be overthrown by unconstitutional means—has a slightly negative effect on people's happiness according to the data. This could be explained by the fact that the index measures perceptions of stability, and such both perception of stability as well as perception of happiness are by nature subjective. Another reason could be that strong family ties and social support could have such a positive effect on people's happiness, that it would overshadow the negative effects a lack of political stability could have.

The Curious Case of Singapore's Happiness

Although control of corruption and GDP per capita are the two most important indicators in the Asia-Pacific region, indicators Singapore ranks highly on, this surprisingly doesn't translate into a high ranking on the Happiness Index, where Singapore is 37th.

This suggests that there could be other indicators, aside from control of corruption and GDP, which also play a large role in people's happiness. When it comes to indicators such as uneven economic development, health spending and political rights, Singapore ranks rather poorly in comparison to other developed nations which take the lead on the Happiness Index.

North and South America

Key factors: Economic

Model accuracy: 71.6%

The top indicators of happiness in the Americas are GDP per capita, life expectancy, uneven economic development, corruption and female labor force participation rate, factors which are primarily economic. Social and governance factors don't play a major role in people's lives in this region as they do in Europe or the APAC. One possible explanation could be the sheer number of developing economies in the region, since economic indicators heavily influence happiness in the region.

The United States Stands Out From the Region

What is interesting about the US is how highly it scored on GDP per capita (#10 in the world) compared to the region's average for 2019, yet how little difference that made on the Happiness Index. This may again indicate that GDP per capita alone is not a good determinant of happiness.

Other crucial indicators where happiest countries rank highly on, and the US does not, are uneven economic development, where it ranks similarly to Bulgaria and Kazakhstan, and control of corruption. Similar to Singapore which ranks even higher on its GDP per capita but low on uneven economic development, the US likely does not have an even distribution of wealth which implies that a large portion of the population may be struggling financially.

Another contributing factor could be the general lack of security people feel towards a government that does not provide adequate safety nets when it comes to healthcare and unemployment benefits. While the US ranks highly on civil liberties and political rights, as do many of the happiest countries in the world, its economic inequalities which undoubtedly translate into social inequalities have an impact on people's happiness.

Europe

Key factors: Governance and Economic

Model accuracy: 79.4%

The top five factors affecting people's happiness in Europe are very different from both global and regional regressions performed. Between 2008 and 2019, the top factors most closely affecting people's happiness in Europe were rule of law, GDP per capita and social support.

That Rule of Law index played such an important role could be due to the fact that most of Western and Central Europe, while having a capitalist system, have somewhat socialist policies in place such as workers' protections, generous unemployment benefits, public healthcare and tax systems that largely minimize income inequality. This suggests that Europeans put more value on social safety nets than individual wealth, which may also be due to the fact that wealth in the economy is distributed more evenly than it is in the US or in Singapore.

It is also important to point out that for several years, European countries have consistently made up 80% to 90% of the top 10 counties on the Happiness Index. This also makes the relatively low importance of GDP per capita compared with the rest of the world that much more intriguing.

One economic indicator used in the data that can provide some explanation here is the uneven economic development index. As the table below illustrates, most of the top 10 countries on the Happiness Index are also the top 10 countries with the lowest Uneven Economic Development score. This suggests that in particular for the happiest countries in Europe, economic equality plays an important role.

Happiness Index vs Uneven Economic Development 2019

Africa

Key factors: Social and Economic

Model accuracy: 32.1%

Due to limited data availability, our analysis of happiness indicators in Africa is not as accurate as it is for other regions. The following ten indicators only account for 32.1% of people's happiness:

The top indicators of happiness in Africa according to our analysis are population density and the economic decline index, which indicate the importance living standards and the economy play in the region. Economic Decline Index measures per capita income, inflation, debt, productivity, poverty levels and business failures. Population density is also an important factor, which has a negative effect on people's well-being. Possible explanation for this inverse correlation could be that often high population density leads to lower quality of life, fewer resource availability and higher pollution.

Exceptional Time Periods: 2017-2019

While the analysis above provides a good general overview, a year-to-year data comparison gives another interesting insight. Between 2017 and 2019, the top five factors most closely affecting happiness were not economic at all, but rather had to do with state fragility, social support and human rights. This is an interesting observation as it is very different from top indicators in the period between 2008 and 2019.

Top Happiness Indicators Globally 2017-18 vs 2018-19

The fact that the top two indicators for both 2017-2018 and 2018-2019 were related to state fragility, rule of law and presence of a support system in people's lives may be reflective of the time period in question. From Brexit and increased political polarization in Europe, isolationism in the US, migrant crises and US-China trade war, this period was dominated by political instability. It may be logical to conclude that, as the world goes through different phases of regional conflicts, new variables will have a larger impact on people's lives, and by extension their happiness.

So What Does This Mean

What the global and regional analyses can tell us is that happiness is relative and depends largely on the country and region you come from. However, what the study does indicate is that while money, measured by GDP per capita, is an important determinant of people's happiness, it is not the only factor that affects people's well-being. It is rather a combination of economic, social and governance factors.

Another important outcome of the study is that for certain regions the coefficient of determination was high enough that it could be used to not only analyse the top indicators of happiness in the past, but to also predict that those factors will be key determinants of happiness in the future as well. We can therefore reasonably predict that GDP per capita, youth unemployment, social support, health spending and generosity not only accounted for 74.4% of global happiness between 2008 and 2019, but will be among the top indicators of happiness globally in the next few years.

Similarly, on a regional basis, we can assume that rule of law, GDP per capita, political rights, health spending and youth unemployment, having accounted for 79.4% of people's happiness in Europe, will continue to play a key role in the coming years. In the Americas, GDP per capita and life expectancy will continue to remain key indicators of happiness. In the APAC region, control of corruption, GDP per capita and social support will play the most important role in determining happiness.

Another key finding of this study is that key happiness indicators are very much a reflection of the given time period and a given region. While between 2008 and 2019, happiness was primarily determined by GDP per capita, between 2017 and 2019, the key indicator was actually the fragile state index. Lastly, a crucial factor to be considered when analyzing the Happiness Index, is the fact that people who live in more developed countries with higher average income have a different baseline expectation of happiness than those who live in poorer countries.

Methodology

We collected data for 25 independent variables using the World Bank, the Heritage Foundation, Fund for Peace and several other sources. The dependent variable in the study is the Happiness Index, which comes from the Gallup World Poll. Data was collected and analyzed for 106 countries between 2008 and 2019 and regression analysis was conducted on the entire dataset as well as its various subsets.

In order to determine the factors that influence happiness the most on a global as well as regional levels, we have used a multivariate regression. The first step was to reduce the set of 25 potential variables to a subset of only five variables that provide the highest explanatory value, measured by the overall coefficient of determination (R-squared). In other words, we used an algorithm that for a global and regional analyses returns those five explanatory variables that maximize R-squared.

Once we determined those variables, as a second step we ranked them in order of importance by using standardized, coded coefficients. More specifically, we standardized each coefficient by deducting the mean and dividing the result by the standard deviation of the underlying variable. While this method renders the coefficient unitless, and therefore makes it harder to interpret those on an individual basis, it enabled us to rank them in order of impact on happiness, since this methodology takes mean and variation of each underlying variable into account. Ultimately, this standardization makes a comparison of absolute values of each coefficient possible.

Data Limitations

Possible shortcomings of the regression analysis include data and variable limitations. With over 193 countries in the world, crucial data was missing for nearly half, making the analysis more challenging. Regarding the independent variable which is the Happiness Index from the Gallup World Poll, it was only available for 146 countries. Of those 146 countries, the 25 independent variables data was only available for 106 countries. As a result, regression analysis was only done for those 106 countries.

Data Quality

Of the 25 independent variables, 3 variables (happiness index, social support and generosity) were fully reliant on survey data from Gallup's World Poll, which is subjective in nature. In addition, data was collected from different sources, which can vary in their quality. Data sources include the World Bank, the Heritage Foundation, Fund for Peace, the Freedom House, Food and Agriculture Organization, The Swiss Institute of Technology in Zurich and The World Happiness Report.

List of Independent Variables Used in the Study