Charting the Relationship Between Wealth and Happiness, by Country
Connect with us


Charting the Relationship Between Wealth and Happiness, by Country



Data visualization showing the relationship between wealth and happiness around the world

Can I share this graphic?
Yes. Visualizations are free to share and post in their original form across the web—even for publishers. Please link back to this page and attribute Visual Capitalist.
When do I need a license?
Licenses are required for some commercial uses, translations, or layout modifications. You can even whitelabel our visualizations. Explore your options.
Interested in this piece?
Click here to license this visualization.

The Relationship Between Wealth and Happiness, by Country

Throughout history, the pursuit of happiness has been a preoccupation of humankind.

Of course, we humans are not just content with measuring our own happiness, but also our happiness in relation to the people around us—and even other people around the world. The annual World Happiness Report, which uses global survey data to report how people evaluate their own lives in more than 150 countries, helps us do just that.

The factors that contribute to happiness are as subjective and specific as the billions of humans they influence, but there are a few that have continued to resonate over time. Family. Love. Purpose. Wealth. The first three examples are tough to measure, but the latter can be analyzed in a data-driven way.

Does money really buy happiness? Let’s find out.

Wealth and Happiness

To crunch the numbers, we looked at data from Credit Suisse, which breaks down the average wealth per adult in various countries around the world.

The table below looks at 146 countries by their happiness score and wealth per adult:

CountryMedian Wealth per Adult (US$)Happiness Score
🇫🇮 Finland 73,7757.8
🇩🇰 Denmark 165,6227.6
🇮🇸 Iceland 231,4627.6
🇨🇭 Switzerland 146,7337.5
🇮🇱 Israel 80,3157.4
🇸🇪 Sweden 89,8467.4
🇳🇴 Norway 117,7987.4
🇳🇱 Netherlands 136,1057.4
🇱🇺 Luxembourg 259,8997.4
🇦🇹 Austria 91,8337.2
🇳🇿 New Zealand 171,6247.2
🇦🇺 Australia 238,0727.2
🇩🇪 Germany 65,3747.0
🇺🇸 United States 79,2747.0
🇮🇪 Ireland 99,0287.0
🇨🇦 Canada 125,6887.0
🇨🇿 Czech Republic 23,7946.9
🇬🇧 United Kingdom 131,5226.9
🇧🇪 Belgium 230,5486.8
🇫🇷 France 133,5596.7
🇧🇭 Bahrain 14,5206.6
🇨🇷 Costa Rica 14,6626.6
🇦🇪 United Arab Emirates 21,6136.6
🇸🇮 Slovenia 67,9616.6
🇸🇦 Saudi Arabia 15,4956.5
🇺🇾 Uruguay 22,0886.5
🇷🇴 Romania 23,6756.5
🇽🇰 Kosovo 46,0876.5
🇸🇬 Singapore 86,7176.5
🇹🇼 Taiwan 93,0446.5
🇪🇸 Spain 105,8316.5
🇮🇹 Italy 118,8856.5
🇱🇹 Lithuania 29,6796.4
🇸🇰 Slovakia 45,8536.4
🇶🇦 Qatar 83,6806.4
🇲🇹 Malta 84,3906.4
🇧🇷 Brazil 3,4696.3
🇵🇦 Panama 13,1476.3
🇬🇹 Guatemala 30,5866.3
🇪🇪 Estonia 38,9016.3
🇳🇮 Nicaragua 3,6946.2
🇰🇿 Kazakhstan 12,0296.2
🇷🇸 Serbia 14,9546.2
🇨🇱 Chile 17,7476.2
🇱🇻 Latvia 33,8846.2
🇨🇾 Cyprus 35,3006.2
🇺🇿 Uzbekistan 7,8216.1
🇸🇻 El Salvador 11,3726.1
🇲🇽 Mexico 13,7526.1
🇵🇱 Poland 23,5506.1
🇭🇺 Hungary 24,1266.1
🇲🇺 Mauritius 27,4566.1
🇰🇼 Kuwait 28,6986.1
🇭🇷 Croatia 34,9456.1
🇦🇷 Argentina 2,1576.0
🇭🇳 Honduras 15,3806.0
🇵🇹 Portugal 61,3066.0
🇯🇵 Japan 122,9806.0
🇵🇭 Philippines 3,1555.9
🇯🇲 Jamaica 5,9765.9
🇲🇩 Moldova 7,5775.9
🇹🇭 Thailand 8,0365.9
🇬🇷 Greece 57,5955.9
🇰🇷 South Korea 89,6715.9
🇰🇬 Kyrgyzstan 2,2385.8
🇲🇳 Mongolia 2,5465.8
🇨🇴 Colombia 4,8545.8
🇧🇾 Belarus 12,1685.8
🇧🇦 Bosnia and Herzegovina 15,2835.8
🇲🇾 Malaysia 8,5835.7
🇩🇴 Dominican Republic 22,7015.7
🇵🇾 Paraguay 3,6445.6
🇧🇴 Bolivia 3,8045.6
🇵🇪 Peru 5,4455.6
🇨🇳 China 24,0675.6
🇻🇳 Vietnam 4,5595.5
🇷🇺 Russia 5,4315.5
🇪🇨 Ecuador 5,4445.5
🇹🇲 Turkmenistan 9,0305.5
🇲🇪 Montenegro 30,7395.5
🇳🇵 Nepal 1,4375.4
🇹🇯 Tajikistan 1,8445.4
🇦🇲 Armenia 9,4115.4
🇧🇬 Bulgaria 17,4035.4
🇭🇰 Hong Kong  SAR173,7685.4
🇱🇾 Libya 6,5125.3
🇧🇩 Bangladesh 3,0625.2
🇿🇦 South Africa 4,5235.2
🇮🇩 Indonesia 4,6935.2
🇦🇿 Azerbaijan 5,0225.2
🇨🇮 Côte d'Ivoire6,6215.2
🇦🇱 Albania 15,3635.2
🇲🇰 North Macedonia 51,7885.2
🇬🇲 The Gambia6585.2
🇱🇷 Liberia 1,4645.1
🇱🇦 Laos 1,6105.1
🇩🇿 Algeria 2,3025.1
🇺🇦 Ukraine 2,5295.1
🇲🇦 Morocco 3,8745.1
🇨🇬 Congo 5825.1
🇸🇳 Senegal 1,5705.0
🇬🇪 Georgia 4,2235.0
🇬🇦 Gabon 4,6855.0
🇲🇿 Mozambique 3455.0
🇳🇪 Niger 4925.0
🇨🇲 Cameroon 9415.0
🇬🇭 Ghana 2,1984.9
🇮🇶 Iraq 6,3784.9
🇻🇪 Venezuela 7,3414.9
🇮🇷 Iran 7,6214.9
🇬🇳 Guinea 9384.9
🇹🇷 Turkey 8,0014.7
🇧🇫 Burkina Faso 6224.7
🇰🇲 Comoros 1,4664.6
🇳🇬 Nigeria 1,4744.6
🇰🇭 Cambodia 2,0314.6
🇺🇬 Uganda 6464.6
🇧🇯 Benin 8904.6
🇵🇰 Pakistan 2,1874.5
🇳🇦 Namibia 3,6774.5
🇰🇪 Kenya 3,6834.5
🇹🇳 Tunisia 6,1774.5
🇲🇱 Mali 8694.5
🇲🇲 Myanmar 2,4584.4
🇱🇰 Sri Lanka 8,8024.4
🇨🇩 DR Congo3564.4
🇪🇬 Egypt 6,3294.3
🇹🇩 Chad 3554.3
🇲🇬 Madagascar 6664.3
🇲🇷 Mauritania 1,0374.2
🇾🇪 Yemen 1,2234.2
🇪🇹 Ethiopia 1,5274.2
🇯🇴 Jordan 10,8424.2
🇹🇬 Togo 4684.1
🇮🇳 India 3,1943.8
🇲🇼 Malawi 6063.8
🇿🇲 Zambia 6923.8
🇹🇿 Tanzania 1,4333.7
🇭🇹 Haiti1933.6
🇸🇱 Sierra Leone 3703.6
🇧🇼 Botswana 3,6803.5
🇱🇸 Lesotho 2643.5
🇷🇼 Rwanda 1,2663.3
🇱🇧 Lebanon 18,1593.0
🇸🇸 South Sudan 2,6772.9
🇦🇫 Afghanistan 7342.4

While the results don’t definitively point to wealth contributing to happiness, there is a strong correlation across the board. Broadly speaking, the world’s poorest countries have the lowest happiness scores, and the richest report being the most happy.

Regional and Country-Level Observations

While many of the countries follow an obvious trend (more wealth = more happiness), there are nuances and outliers worth exploring.

  • In Latin America, people self-report more happiness than the trend between wealth and happiness would predict.
  • On the flip side, many nations in the Middle East report slightly less happiness than levels of wealth would predict.
  • Political turmoil, an economic crisis, and the devastating explosion in Beirut have resulted in Lebanon scoring far worse than would be expected. Over the past decade, the country’s score has fallen by nearly two full points.
  • Hong Kong has seen its happiness score sink for years now. Inequality, protests, instability, and now COVID-19 outbreaks have placed the region in an unusual zone on the chart: rich and unhappy.

Examining Inequality and Happiness

We’ve looked at the relationship between wealth and happiness between countries, but what about within countries?

The Gini Coefficient is a tool that allows us to do just that. This measure looks at income distribution across a population, and applies a score to that population. Simply put, a score of 0 would be “perfect equality”, and 1 would be “perfect inequality” (i.e. an individual or group of recipients is receiving the entire income distribution).

Combined with the same happiness scale as before, this is how countries shape up.

Data visualization showing the relationship between inequality and happiness around the world

While there is no ironclad conclusion that can be derived from this dataset, there are big picture observations worth highlighting.

The 15 Countries With Highest Income Inequality

Countries with High inequalityHappiness ScoreGini Score
🇿🇦 South Africa5.20.63
🇳🇦 Namibia4.50.59
🇿🇲 Zambia3.80.57
🇨🇴 Colombia5.80.54
🇲🇿 Mozambique5.00.54
🇧🇼 Botswana3.50.53
🇿🇼 Zimbabwe3.00.50
🇵🇦 Panama6.30.50
🇨🇷 Costa Rica6.60.49
🇧🇷 Brazil6.30.49
🇬🇹 Guatemala6.30.48
🇭🇳 Honduras6.00.48
🇧🇫 Burkina Faso4.70.47
🇪🇨 Ecuador5.50.47
🇨🇲 Cameroon5.00.47

First, countries with lower income inequality tend to also report more happiness. The 15 countries in this dataset with the highest inequality (shown above) have an average happiness score 1.3 lower than the 15 countries with the lowest inequality (shown below).

The 15 Countries With Lowest Income Inequality

Countries with low inequalityHappy ScoreGini Score
🇸🇰 Slovakia6.423.2
🇧🇾 Belarus5.824.4
🇸🇮 Slovenia6.624.4
🇦🇲 Armenia5.425.2
🇨🇿 Czech Republic6.925.3
🇺🇦 Ukraine5.125.6
🇲🇩 Moldova5.926
🇦🇪 United Arab Emirates6.626
🇮🇸 Iceland7.626.1
🇧🇪 Belgium6.827.2
🇩🇰 Denmark7.627.7
🇫🇮 Finland7.827.7
🇳🇴 Norway7.427.7
🇰🇿 Kazakhstan6.227.8
🇭🇷 Croatia6.128.9

Next, interesting regional differences emerge.

Despite high income inequality, many Latin American countries report levels of happiness similar to many much-wealthier European nations.

The Bottom Line

People have been seeking understanding on happiness for millennia now, and it’s unlikely that slicing and dicing datasets will crack the code. Still though, much like the pursuit of happiness, the pursuit of understanding is human nature.

And, in more concrete terms, the more policymakers and the public understand the link between wealth and happiness, the more likely we can shape societies that give us a better chance at living a happy life.

Where does this data come from?

Source: Credit Suisse Global Wealth Databook 2021, World Happiness Report 2022, World Bank

Data notes: This visualization includes countries that had available data for both happiness and wealth per adult. Credit Suisse notes that due to incomplete data, the following countries are estimates of average wealth per adult: North Macedonia, Kosovo, Guatemala, Dominican Republic, Honduras, Uzbekistan, Côte d’Ivoire, and South Sudan. Happiness data for countries is from the 2022 report, with the exception of: Qatar, DRC, Haiti, and South Sudan, which pull from the 2019 report. For Gini Coefficient calculations, only countries with data from 2014 onward were included. As a result, major economies such as India and Japan are excluded from that visualization.

Chart note: The wealth axis was plotted logarithmically to better show the trend visually. This approach is often used when a small number of results skew the visualization, making it harder to glean insight from. In this case, there are large extremes between the richest and poorest countries around the world.

Subscribe to Visual Capitalist
Click for Comments


Mapped: The 3 Billion People Who Can’t Afford a Healthy Diet

More than three billion people across the globe are unable to afford a healthy diet. See which countries are most affected.



The 3 Billion People Who Can’t Afford a Healthy Diet

While they aren’t often the focus of news media, hunger and undernourishment are problems plaguing millions of people every day.

According to the UN Food and Agriculture Organization (FAO), more than 3 billion people could not afford a healthy diet in 2020, an additional 112 million more people than in 2019. The increase was partly because of rising food prices, with the average cost of a healthy diet rising by 3.3% from 2019 levels.

As of August 2022, the FAO food price index was up 40.6% from average 2020 levels. Unless income levels increased by a similar magnitude, the healthy diet crisis is likely to have worsened, especially in low-income countries experiencing rampant food inflation.

Using data from the FAO, the above infographic maps the share of people unable to afford a healthy diet in 138 different countries as of 2020 (latest available data).

The Cost and Affordability of a Healthy Diet

According to the FAO, a healthy diet is one that meets daily energy needs as well as requirements within the food and dietary guidelines created by the country.

The (un)affordability is measured by comparing the cost of a healthy diet to income levels in the country. If the cost exceeds 52% of an average household’s income, the diet is deemed unaffordable.

Here’s a look at the share of populations unable to afford a healthy diet, and the cost of such a diet around the world:

CountryPercent of population unable to afford a healthy dietCost of Healthy Diet (USD per Person per Day)
Burundi 🇧🇮97.2%$2.9
Madagascar 🇲🇬97.0%$3.2
Liberia 🇱🇷96.8%$3.9
Malawi 🇲🇼96.6%$3.1
Nigeria 🇳🇬95.9%$4.1
Central African Republic 🇨🇫95.1%$3.6
Guinea 🇬🇳94.9%$4.1
Angola 🇦🇴94.3%$4.5
Congo 🇨🇬92.4%$3.4
Sudan 🇸🇩91.8%$4.3
Mozambique 🇲🇿91.5%$3.2
Democratic Republic of Congo 🇨🇩90.0%$2.1
Sierra Leone 🇸🇱89.2%$2.9
Niger 🇳🇪88.8%$2.9
Zambia 🇿🇲88.0%$3.3
Tanzania 🇹🇿87.6%$2.7
Guinea-Bissau 🇬🇼87.2%$3.5
Ethiopia 🇪🇹86.8%$3.4
Rwanda 🇷🇼86.3%$2.7
Haiti 🇭🇹85.9%$4.5
Sao Tome and Principe 🇸🇹84.7%$3.6
Nepal 🇳🇵84.0%$4.4
Lesotho 🇱🇸83.5%$4.3
Pakistan 🇵🇰83.5%$3.7
Chad 🇹🇩83.4%$2.8
Benin 🇧🇯82.9%$3.7
Uganda 🇺🇬82.2%$2.7
Kenya 🇰🇪81.1%$3.0
Burkina Faso 🇧🇫80.1%$3.3
Laos 🇱🇦79.8%$4.1
Mali 🇲🇱74.3%$3.1
Bangladesh 🇧🇩73.5%$3.1
Egypt 🇪🇬72.9%$3.4
Eswatini 🇸🇿71.8%$3.4
India 🇮🇳70.5%$3.0
Indonesia 🇮🇩69.1%$4.5
Philippines 🇵🇭68.6%$4.1
Jamaica 🇯🇲66.2%$6.7
South Africa 🇿🇦65.2%$4.3
Myanmar 🇲🇲65.1%$4.2
Gambia 🇬🇲64.0%$3.1
Djibouti 🇩🇯63.9%$3.1
Botswana 🇧🇼61.4%$3.7
Ghana 🇬🇭61.2%$4.0
Cameroon 🇨🇲60.7%$2.8
Mauritania 🇲🇷60.7%$3.7
Fiji 🇫🇯60.4%$3.9
Suriname 🇸🇷58.8%$5.7
Namibia 🇳🇦56.8%$3.5
Bhutan 🇧🇹53.0%$5.0
Mongolia 🇲🇳51.4%$5.1
Honduras 🇭🇳51.3%$3.5
Iraq 🇮🇶49.6%$3.5
Kyrgyzstan 🇰🇬49.6%$3.2
Sri Lanka 🇱🇰49.0%$3.9
Senegal 🇸🇳46.0%$2.3
Guyana 🇬🇾43.0%$4.9
Armenia 🇦🇲42.9%$3.2
Tajikistan 🇹🇯42.1%$3.5
Cabo Verde 🇨🇻38.1%$3.6
Belize 🇧🇿36.4%$2.1
Gabon 🇬🇦36.3%$3.6
Nicaragua 🇳🇮35.7%$3.3
Algeria 🇩🇿30.2%$3.8
Vietnam 🇻🇳30.0%$4.1
Colombia 🇨🇴26.5%$3.1
Mexico 🇲🇽26.3%$3.3
Bolivia 🇧🇴24.7%$3.8
Palestine 🇵🇸23.1%$3.4
Ecuador 🇪🇨21.4%$2.9
Saint Lucia 🇱🇨20.6%$3.6
Peru 🇵🇪20.5%$3.3
Iran 🇮🇷20.3%$3.6
Tunisia 🇹🇳20.3%$3.6
Albania 🇦🇱20.1%$4.2
Brazil 🇧🇷19.0%$3.1
Dominican Republic 🇩🇴18.3%$3.9
Panama 🇵🇦18.2%$4.5
North Macedonia 🇲🇰18.0%$3.4
Paraguay 🇵🇾17.8%$3.5
Montenegro 🇲🇪17.5%$3.5
Thailand 🇹🇭17.0%$4.3
Costa Rica 🇨🇷16.8%$4.1
Morocco 🇲🇦16.7%$2.8
Serbia 🇷🇸16.3%$4.2
Jordan 🇯🇴14.9%$3.6
Mauritius 🇲🇺13.5%$3.6
China 🇨🇳12.0%$3.0
Trinidad and Tobago 🇹🇹11.6%$4.2
Romania 🇷🇴8.8%$3.2
Bulgaria 🇧🇬8.5%$4.1
Seychelles 🇸🇨6.8%$3.8
Moldova 🇲🇩6.7%$2.8
Chile 🇨🇱3.8%$3.4
Croatia 🇭🇷3.8%$4.3
Bosnia and Herzegovina 🇧🇦3.7%$4.0
Uruguay 🇺🇾3.6%$3.4
Russia 🇷🇺3.5%$3.4
Greece 🇬🇷3.2%$3.1
Italy 🇮🇹2.9%$3.1
Japan 🇯🇵2.5%$5.8
Hungary 🇭🇺2.0%$3.5
Spain 🇪🇸2.0%$2.8
Malaysia 🇲🇾1.9%$3.5
Latvia 🇱🇻1.8%$3.2
South Korea 🇰🇷1.7%$5.2
United States 🇺🇸1.5%$3.4
Maldives 🇲🇻1.4%$3.9
Estonia 🇪🇪1.3%$3.3
Kazakhstan 🇰🇿1.2%$2.7
Lithuania 🇱🇹1.2%$3.1
Slovakia 🇸🇰1.2%$3.2
Israel 🇮🇱1.0%$2.5
Poland 🇵🇱1.0%$3.2
Austria 🇦🇹0.8%$3.0
Australia 🇦🇺0.7%$2.6
Canada 🇨🇦0.7%$3.0
Malta 🇲🇹0.7%$3.8
Sweden 🇸🇪0.6%$3.3
Portugal 🇵🇹0.5%$2.7
United Kingdom 🇬🇧0.5%$1.9
Denmark 🇩🇰0.4%$2.5
Norway 🇳🇴0.4%$3.5
Cyprus 🇨🇾0.3%$3.0
Belarus 🇧🇾0.2%$3.3
Belgium 🇧🇪0.2%$3.1
Germany 🇩🇪0.2%$3.0
Netherlands 🇳🇱0.2%$3.0
Finland 🇫🇮0.1%$2.7
France 🇫🇷0.1%$3.2
Ireland 🇮🇪0.1%$2.2
Luxembourg 🇱🇺0.1%$2.7
Slovenia 🇸🇮0.1%$3.1
Azerbaijan 🇦🇿0.0%$2.5
Iceland 🇮🇸0.0%$2.4
Switzerland 🇨🇭0.0%$2.7
United Arab Emirates 🇦🇪0.0%$3.1
World 🌎42.0%$3.5

In 52 countries, more than half of the population cannot afford a healthy diet. The majority of these are in Africa, with the rest located across Asia, Oceania, and the Americas.

By contrast, in four countries—Azerbaijan, Iceland, Switzerland, and the UAE—everyone is able to afford a healthy diet. The picture is similar for most European and developed high-income countries, where more than 95% of the population can afford a healthy diet.

When the percentages are translated into numbers, Asia contains the most number of people unable to afford a healthy diet at 1.89 billion, of which 973 million people are in India alone. Another 1 billion people are in Africa, with around 151 million people in the Americas and Oceania.

While hunger is a worldwide concern, it is particularly acute in African countries, which cover all of the top 20 spots in the above table.

Africa’s Deepening Food Crisis

In many countries across sub-Saharan Africa, more than 90% of the population cannot afford a healthy diet.

Sub-Saharan Africa is particularly susceptible to extreme climate events and the resulting volatility in food prices. Roughly one-third of the world’s droughts occur in the region, and some sub-Saharan countries are also heavily reliant on imports for food.

Russia’s invasion of Ukraine has deepened the crisis, with many African countries importing over 50% of their wheat from the two countries in conflict. The rising food prices from this supply chain disruption have resulted in double-digit food inflation in many African nations, which means that more people are likely to be unable to afford healthy diets.

The Horn of Africa region at the Eastern tip of Africa is particularly in turmoil. All the countries in the region are reliant on wheat from Russia and Ukraine, with Eritrea (100%) and Somalia (>90%) high up in the import dependency chart. Additionally, the region is facing its worst drought in 40 years alongside ongoing political conflicts. As a result, 22 million people are at risk of starvation.

Population Growth and Food Insecurity

In November of 2022, the global population is projected to surpass 8 billion people, and many of the fastest growing countries are also food-insecure.

By 2050, the global population is likely to increase by 35%, and to meet the growing demand for food, crop production will need to double. Given that agriculture is one of the biggest contributors to greenhouse gas emissions, this increase in crop production will also need to be environmentally sustainable.

As the impacts of climate change intensify and food demand increases, reducing food waste, building climate-resilient agricultural infrastructure, and improving agricultural productivity will all play a key role in reducing the levels of food insecurity sustainably.

world at 8 billion report

Get our new “The World at 8 Billion” report and webinar by becoming a VC+ member


Continue Reading

Personal Finance

How Do Americans Spend Their Money, By Generation?

This interactive graphic shows a breakdown of how average Americans spend their money, and how expenses vary across generations.



Annual Expenditure in the U.S. by Generation

How Americans Spend Their Money, By Generation

In 2021, the average American spent just over $60,000 a year. But where does all their money go? Unsurprisingly, spending habits vary wildly depending on age.

This graphic by Preethi Lodha uses data from the U.S. Bureau of Labor Statistics to show how average Americans spend their money, and how annual expenses vary across generations.

A Generational Breakdown of Overall Spending

Overall in 2021, Gen X (anyone born from 1965 to 1980) spent the most money of any U.S. generation, with an average annual expenditure of $83,357.

GenerationBirth Year RangeAverage Annual Expenditure (2021)
Silent1945 or earlier$44,683
Boomers1946 to 1964$62,203
Generation X1965 to 1980$83,357
Millennials1981 to 1996$69,061
Generation Z1997 or later$41,636

Gen X has been nicknamed the “sandwich generation” because many members of this age group are financially supporting both their aging parents as well as children of their own.

The second biggest spenders are Millennials with an average annual expenditure of $69,061. Just like Gen X, this generation’s top three spending categories are housing, healthcare, and personal insurance.

On the opposite end of the spectrum, members of Generation Z are the lowest spenders with an average of $41,636. per year. Their spending habits are expected to ramp up, especially considering that in 2022 the oldest Gen Zers are just 25 and still early in their careers.

Similarities Across Generations

While spending habits vary depending on the age group, there are some categories that remain fairly consistent across the board.

One of the most consistent spending categories is housing—it’s by the far the biggest expense for all age groups, accounting for more than 30% of total annual spending for every generation.

GenerationAverage Spend on Housing (2021)% of Total Spend
Silent (1945 or earlier)$16,65637.3%
Boomers (1946 to 1964)$21,27334.2%
Generation X (1965 to 1980)$26,38531.7%
Millennials (1981 to 1996)$24,05234.8%
Generation Z (1997 or later)$15,44937.1%

Another spending category that’s surprisingly consistent across every generation is entertainment. All generations spent more than 4% of their total expenditures on entertainment, but none dedicated more than 5.6%.

GenerationAverage Spend on Entertainment (2021)% of Total Spend
Silent (1945 or earlier)$2,0274.5%
Boomers (1946 to 1964)$3,4765.6%
Generation X (1965 to 1980)$4,6945.6%
Millennials (1981 to 1996)$3,4575.0%
Generation Z (1997 or later)$1,6934.1%

Gen Zers spent the least on entertainment, which could boil down to the types of entertainment this generation typically enjoys. For instance, a study found that 51% of respondents aged 13-19 watch videos on Instagram on a weekly basis, while only 15% watch cable TV.

Differences Across Generations

One category that varies the most between generations and relative needs is spending on healthcare.

As the table below shows, the Silent Generation spent an average of $7,053 on healthcare, or 15.8% of their total average spend. Comparatively, Gen Z only spent $1,354 on average, or 3.3% of their total average spend.

GenerationAverage Spend on Healthcare (2021)% of Total Spend
Silent (1945 or earlier)$7,05315.8%
Boomers (1946 to 1964)$6,59410.6%
Generation X (1965 to 1980)$5,5506.7%
Millennials (1981 to 1996)$4,0265.8%
Generation Z (1997 or later)$1,3543.3%

However, while the younger generations typically spend less on healthcare, they’re also less likely to be insured—so those who do get sick could be left with a hefty bill.

Continue Reading