money is not important for happiness essay

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Does More Money Really Make Us More Happy?

• Elizabeth Dunn
• Chris Courtney

A big paycheck won’t necessarily bring you joy

Although some studies show that wealthier people tend to be happier, prioritizing money over time can actually have the opposite effect.

• But even having just a little bit of extra cash in your savings account ($500), can increase your life satisfaction. So how can you keep more cash on hand?
• Ask yourself: What do I buy that isn’t essential for my survival? Is the expense genuinely contributing to my happiness? If the answer to the second question is no, try taking a break from those expenses.
• Other research shows there are specific ways to spend your money to promote happiness, such as spending on experiences, buying time, and investing in others.
• Spending choices that promote happiness are also dependent on individual personalities, and future research may provide more individualized advice to help you get the most happiness from your money.

Where your work meets your life. See more from Ascend here .

How often have you willingly sacrificed your free time to make more money? You’re not alone. But new research suggests that prioritizing money over time may actually undermine our happiness.

• ED Elizabeth Dunn is a professor of psychology at the University of British Columbia and Chief Science Officer of Happy Money, a financial technology company with a mission to help borrowers become savers. She is also co-author of “ Happy Money: The Science of Happier Spending ” with Dr. Michael Norton. Her TED2019 talk on money and happiness was selected as one of the top 10 talks of the year by TED.
• CC Chris Courtney is the VP of Science at Happy Money. He utilizes his background in cognitive neuroscience, human-computer interaction, and machine learning to drive personalization and engagement in products designed to empower people to take control of their financial lives. His team is focused on creating innovative ways to provide more inclusionary financial services, while building tools to promote financial and psychological well-being and success.

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Can Money Really Buy Happiness?

Money and happiness are related—but not in the way you think..

Updated November 10, 2023 | Reviewed by Chloe Williams

• More money is linked to increased happiness, some research shows.
• People who won the lottery have greater life satisfaction, even years later.
• Wealth is not associated with happiness globally; non-material things are more likely to predict wellbeing.
• Money, in and of itself, cannot buy happiness, but it can provide a means to the things we value in life.

Money is a big part of our lives, our identities, and perhaps our well-being. Sometimes, it can feel like your happiness hinges on how much cash is in your bank account. Have you ever thought to yourself, “If only I could increase my salary by 12 percent, I’d feel better”? How about, “I wish I had an inheritance. How easier life would be!” I don’t blame you — I’ve had the same thoughts many times.

But what does psychological research say about the age-old question: Can money really buy happiness? Let’s take a brutally honest exploration of how money and happiness are (and aren’t) related. (Spoiler alert: I’ve got bad news, good news, and lots of caveats.)

Higher earners are generally happier

Over 10 years ago, a study based on Gallup Poll data on 1,000 people made a big headline in the news. It found that people with higher incomes report being happier... but only up to an annual income of $75,000 (equivalent to about $90,000 today). After this point, a high emotional well-being wasn’t directly correlated to more money. This seemed to show that once a persons’ basic (and some “advanced”) needs are comfortably met, more money isn’t necessary for well-being.

But a new 2021 study of over one million participants found that there’s no such thing as an inflection point where more money doesn’t equal more happiness, at least not up to an annual salary of $500,000. In this study, participants’ well-being was measured in more detail. Instead of being asked to remember how well they felt in the past week, month, or year, they were asked how they felt right now in the moment. And based on this real-time assessment, very high earners were feeling great.

Similarly, a Swedish study on lottery winners found that even after years, people who won the lottery had greater life satisfaction, mental health, and were more prepared to face misfortune like divorce , illness, and being alone than regular folks who didn’t win the lottery. It’s almost as if having a pile of money made those things less difficult to cope with for the winners.

Evaluative vs. experienced well-being

At this point, it's important to suss out what researchers actually mean by "happiness." There are two major types of well-being psychologists measure: evaluative and experienced. Evaluative well-being refers to your answer to, “How do you think your life is going?” It’s what you think about your life. Experienced well-being, however, is your answer to, “What emotions are you feeling from day to day, and in what proportions?” It is your actual experience of positive and negative emotions.

In both of these studies — the one that found the happiness curve to flatten after $75,000 and the one that didn't — the researchers were focusing on experienced well-being. That means there's a disagreement in the research about whether day-to-day experiences of positive emotions really increase with higher and higher incomes, without limit. Which study is more accurate? Well, the 2021 study surveyed many more people, so it has the advantage of being more representative. However, there is a big caveat...

Material wealth is not associated with happiness everywhere in the world

If you’re not a very high earner, you may be feeling a bit irritated right now. How unfair that the rest of us can’t even comfort ourselves with the idea that millionaires must be sad in their giant mansions!

But not so fast.

Yes, in the large million-person study, experienced well-being (aka, happiness) did continually increase with higher income. But this study only included people in the United States. It wouldn't be a stretch to say that our culture is quite materialistic, more so than other countries, and income level plays a huge role in our lifestyle.

Another study of Mayan people in a poor, rural region of Yucatan, Mexico, did not find the level of wealth to be related to happiness, which the participants had high levels of overall. Separately, a Gallup World Poll study of people from many countries and cultures also found that, although higher income was associated with higher life evaluation, it was non-material things that predicted experienced well-being (e.g., learning, autonomy, respect, social support).

Earned wealth generates more happiness than inherited wealth

More good news: For those of us with really big dreams of “making it” and striking it rich through talent and hard work, know that the actual process of reaching your dream will not only bring you cash but also happiness. A study of ultra-rich millionaires (net worth of at least $8,000,000) found that those who earned their wealth through work and effort got more of a happiness boost from their money than those who inherited it. So keep dreaming big and reaching for your entrepreneurial goals … as long as you’re not sacrificing your actual well-being in the pursuit.

There are different types of happiness, and wealth is better for some than others

We’ve been talking about “happiness” as if it’s one big thing. But happiness actually has many different components and flavors. Think about all the positive emotions you’ve felt — can we break them down into more specifics? How about:

• Contentment
• Gratefulness

...and that's just a short list.

It turns out that wealth may be associated with some of these categories of “happiness,” specifically self-focused positive emotions such as pride and contentment, whereas less wealthy people have more other-focused positive emotions like love and compassion.

In fact, in the Swedish lottery winners study, people’s feelings about their social well-being (with friends, family, neighbors, and society) were no different between lottery winners and regular people.

Money is a means to the things we value, not happiness itself

One major difference between lottery winners and non-winners, it turns out, is that lottery winners have more spare time. This is the thing that really makes me envious , and I would hypothesize that this is the main reason why lottery winners are more satisfied with their life.

Consider this simply: If we had the financial security to spend time on things we enjoy and value, instead of feeling pressured to generate income all the time, why wouldn’t we be happier?

This is good news. It’s a reminder that money, in and of itself, cannot literally buy happiness. It can buy time and peace of mind. It can buy security and aesthetic experiences, and the ability to be generous to your family and friends. It makes room for other things that are important in life.

In fact, the researchers in that lottery winner study used statistical approaches to benchmark how much happiness winning $100,000 brings in the short-term (less than one year) and long-term (more than five years) compared to other major life events. For better or worse, getting married and having a baby each give a bigger short-term happiness boost than winning money, but in the long run, all three of these events have the same impact.

What does this mean? We make of our wealth and our life what we will. This is especially true for the vast majority of the world made up of people struggling to meet basic needs and to rise out of insecurity. We’ve learned that being rich can boost your life satisfaction and make it easier to have positive emotions, so it’s certainly worth your effort to set goals, work hard, and move towards financial health.

But getting rich is not the only way to be happy. You can still earn health, compassion, community, love, pride, connectedness, and so much more, even if you don’t have a lot of zeros in your bank account. After all, the original definition of “wealth” referred to a person’s holistic wellness in life, which means we all have the potential to be wealthy... in body, mind, and soul.

Kahneman, D., & Deaton, A.. High income improves evaluation of life but not emotional well-being. . Proceedings of the national academy of sciences. 2010.

Killingsworth, M. A. . Experienced well-being rises with income, even above $75,000 per year .. Proceedings of the National Academy of Sciences. 2021.

Lindqvist, E., Östling, R., & Cesarini, D. . Long-run effects of lottery wealth on psychological well-being. . The Review of Economic Studies. 2020.

Guardiola, J., González‐Gómez, F., García‐Rubio, M. A., & Lendechy‐Grajales, Á.. Does higher income equal higher levels of happiness in every society? The case of the Mayan people. . International Journal of Social Welfare. 2013.

Diener, E., Ng, W., Harter, J., & Arora, R. . Wealth and happiness across the world: material prosperity predicts life evaluation, whereas psychosocial prosperity predicts positive feeling. . Journal of personality and social psychology. 2010.

Donnelly, G. E., Zheng, T., Haisley, E., & Norton, M. I.. The amount and source of millionaires’ wealth (moderately) predict their happiness . . Personality and Social Psychology Bulletin. 2018.

Piff, P. K., & Moskowitz, J. P. . Wealth, poverty, and happiness: Social class is differentially associated with positive emotions.. Emotion. 2018.

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However you spend it, money isn’t the key to happiness

Research Fellow at Stirling Management School, University of Stirling

Disclosure statement

Christopher Boyce receives funding from the Economic and Social Research Council.

University of Stirling provides funding as a member of The Conversation UK.

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How important, if at all, is having more money for our happiness and well-being? Unsurprisingly this question stimulates a lot of opinion and debate. But are people accurate in their predictions about the benefits of having money?

A new study published in the Journal of Positive Psychology highlights that people are often mistaken in how spending our money might benefit our lives. People are prone to forecasting errors – that is, they mistakenly predict future events to be better or worse than they actually turn out to be.

In this latest study the researchers show that people predict that buying material possessions will be a better use of money than spending instead on life experiences. But once the purchases are had, the experience is what’s perceived to have been a better use of money, resulting in higher well-being. More or less, this confirms findings from other studies . And so it seems that a focus on having as opposed to being may limit human potential.

But what does this new study tell us about the importance of money for both happiness and well-being more generally? On the whole money matters much less than people think and has led some to conclude simply that money doesn’t make us happy because we aren’t spending it right .

My own research has also illustrated that we probably don’t spend our money on the things most beneficial for well-being. For example, we have shown that spending on psychological therapy would be an extremely cost-effective way of raising well-being . But, the message from our research is not that we should just spend our money better and that people underestimate the effect of purchasing certain things, as the authors claim in the latest study. Instead, our work highlights just how relatively unimportant money is at raising individual well-being compared to other more important things.

More to life than money

How to spend our money is not the only choice we have – we also have choices as to how we should live our lives and whether in fact we should spend so much time and energy pursuing money in the first place. Thus when we are trying to understand the importance of money for well-being it is one thing to compare types of spending, but really we should be comparing how important money is in relation to other things.

The reality is that how much someone earns contributes very little to their sense of well-being compared with other things such as social relationships, physical and mental health or how a person relates to the world around them. Focusing directly on these factors would probably do much more for our well-being rather than how we chose to spend our money.

We have demonstrated that personality change, for example, contributes substantially more to changes in well-being than income factors . People who, for example, become more open to new experiences or emotionally more stable, are much more likely to experience larger well-being changes than any change to their income.

Being materialistic is well-known to be detrimental to an individual’s well-being. Those that pursue wealth and possessions consistently report lower well-being than those that don’t.

So a better question to address than how we should spend our money is: “Why does more money seem to bring us very little well-being even though we often predict otherwise?”

Money and social standing

One reason is that people don’t care about how much money they have per se, but care more about the social position that their income gives them . But increases in an individual’s income won’t necessarily equate to a growth in social standing. And, while people may think that an income increase will bring greater well-being, this may not factor in that everyone else may experience an income increase at the same time.

It’s also been shown that income losses have a much greater impact on well-being than equivalent income gains . This suggests that any benefit that accrues from an income rise, whether at the individual or national level, may be completely wiped out by much smaller income losses. The importance of income is therefore not in obtaining it, but avoiding losing it. Only once it’s obtained does income become essential to maintain your current level of well-being and this may partly explain why it is believed to be so important for well-being.

The question as to whether more money brings greater happiness comes up time and time again and will no doubt continue to do so. Indeed it is an important question and how we spend our money is of course important – if we have money then of course it makes sense to use it wisely. But it would be a mistake to let the pursuit of money for the sake of happiness distract us away from the things in life that simply matter more.

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Can money buy happiness, three psychological principles to consider before you make your next purchase.

By Sarah Gervais, Associate Professor of Psychology, Social and Cognitive Program and Law-Psychology Program

11 Nov 2015

We’re all familiar with the idea that money can’t buy happiness. Yet, the reality is that we all spend money and for most of us it is a limited resource. How can we spend our hard earned dough in ways that will maximize our happiness? Psychological research offers some useful insights about the connections between money and happiness to consider before you make your next purchase.

• Being Rich Isn’t Necessarily the Path to Happiness. Money is important to happiness. Ask anyone who doesn’t have it. Having a higher income, for example, can give us access to homes in safer neighborhoods, better health care and nutrition, fulfilling work, and more leisure time. However, this only works up to a certain point. Once our income reaches a certain level and our basic needs for food, health care, safety, and shelter are met, the positive effects of money—such as buying your dream home—are often offset by the negative effects—such as working longer hours, or in more stressful jobs, to maintain that income.
• Doing Makes us Happier than Having. Most people assume that “things” will lead to more happiness than “experiences.” Physical objects—such as the latest iPhone, handbag, or car—last longer than say going to a concert, taking a cooking class, or going on vacation. Buying things does make us happy, at least in the short term. In the long-term, however, we habituate to new things and even though they may have made us excited and happy at first, eventually the item becomes the new normal and fades into the background. The happiness that comes from purchasing experiences, however, tends to increase over time. One reason is that we often share experiential purchases with other people. Even when you’ve driven that new car into the ground, you’ll still be telling stories with your family and friends about that time when you went on vacation to Colorado and you’ll even be chuckling about when the car broke down and you had to spend the night in the shady motel
• Consider Spending Money on Others. Most people think that spending money on themselves will make them happier than spending it on other people. Yet, when researchers assess happiness before and after people spend an annual bonus, people report greater happiness when they spend the bonus money on others or donate it to charity than when they spend it on themselves. This occurs regardless of how big the bonus was. One reason for this phenomenon is that giving to others makes us feel good about ourselves

So, before you pull out your wallet or click to order online, think about whether this purchase will really make you happy. If it will jeopardize your basic needs, think twice. If you have some disposable income, considering planning a trip or taking a class to learn a new skill. Finally, in this season of giving, know that if you spend your money on others or donate it to good causes, you may feel better than if you spend it on yourself.

Note: This article presents some basic principles for money and happiness. Individuals differ in their financial situation and psychological well-being. Consult a financial expert or behavioral health professional for guidance about finances and happiness.

Money, Happiness and Satisfaction With Life Essay

Money has always been known as the symbol of wealth, the key to happiness, and the backbone of livelihood. There is also a widespread opinion that money positively affects the growth of happiness. However, with this drastic growth comes a severe decline, and this is because of the human instinct to be acquisitive. The current essay discusses happiness and argues that the veritable happiness and satisfaction with life come not from money but self-actualization and positive thinking.

One of the fundamental explanations of why happiness is not about money lies in flawed human nature. In the book Leviathan , the prominent philosopher Thomas Hobbes (1651) described the state of nature where people live before the government appears and argues that every person wants to possess as many goods as possible. However, the number of goods is finite, and, therefore, people enter into the state of war of all against all in pursuit of wealth (Hobbes, 1651). Thus, it becomes apparent that even though money gives people access to numerous goods, services, pleasures, and opportunities, they are not always a synonym for joy or health.

Some people might argue that richness is a synonym for happiness because it allows one to actualize oneself through helping people in need. For example, in 2000, Bill and Melinda Gates grounded a foundation aimed at fighting inequality, poverty, and diseases all over the world (Bill & Melinda Gates Foundation, n.d.). Nonetheless, this case is rather an exception from the common rule. Novack (2008) mentions statistics provided by the Internal Revenue Service revealing that “rich are evasive when it comes to taxes” (para. 1). Indeed, richness and greed seem to be closely related. As 18th-century Scottish economist Adam Smith (1776) famously said, “it is not from the benevolence of the butcher, the brewer, or the baker that we expect our dinner, but from their regard to their own interest” (p. 30). World War II is an amplified example of how one persons strive for money and power led to 60 million casualties all around the world. Besides, the modern case of the trade war between China and the US, initiated by the Trump administration in 2018, shows what the ruling elites are capable of destroying the lives of citizens of other countries if financial gain is at stake.

Many people believe that money is the key to happiness because money buys us tangible property such as cars, houses, and gadgets. Furthermore, money is used to pay tuition fees, electricity and water bills, purchase food and clothes, and, therefore, they are the primary means of survival. From this, one might fallaciously infer that money buys happiness. Still, one should not forget that money is incapable of purchasing the desire to learn or live. For instance, prominent actor Robin Williams, Linkin Parks singer Chester Bennington, and coal billionaire Dmitry Bosov committed suicide even though they were not poor and enjoyed fame and public acclaim. The reasons for suicide are another topic for discussion. Nonetheless, the previously mentioned examples should be used to remind us that money alone is not a guarantee of happiness, satisfaction with life, and good health. Money and fame could not prevent a person from depression, incurable illnesses, or alcohol and drug addictions. What is more, money could even stimulate the appearance of some of these problems. Thus, wealth is not a guarantee of happiness and satisfaction with life.

Finally, most people would love to get wealthy without the hard work and impossible tasks that come with it. They think that by doing so, they would never need anything from anyone ever again. From one point of view, money undoubtedly brings independence and is exempt from poverty. Even though there are ways how to earn easy money, these ways are not always legal, honest, or morally right. Without a doubt, winning a lottery is not a crime. Nonetheless, some researchers claim that money could bring self-satisfaction only if earned from hard work. The study conducted by Brickman, Coates, and Janoff-Bulman (1978) proves that lottery winners were in a better mental state before becoming wealthy without any effort. Undoubtedly, after the win, test subjects were immensely happy; however, after the lapse of time, their level of happiness equals one of the paralyzed people (Brickman et al., 1978). And this comes from the fact that with drastic growth in wealth comes a severe decline in happiness.

Taking everything into account, it is vitally important not to forget that one could find happiness in life regardless of any life circumstances. Joy and self-actualization are not about the size of income. Instead, it is about doing what one loves, having friends, staying fit and healthy, and loving and being loved. A person could be genuinely happy when looking at the shining sun, talking to parents, or reading a worthy book. The critical takeaway from the present paper is that joy with life could be accomplished by self-satisfaction and optimistically looking forward to the future without overabundance.

Works Cited

Bill & Melinda Gates foundation (n.d.). Web.

Brickman, P., Coates, D., & Janoff-Bulman, R. (1978). Lottery winners and accident victims: Is happiness relative?. Journal of personality and social psychology , 36 (8), 917-927. Web.

Hobbes, T. (1651). Leviathan . St. Pauls Church-yard.

Novack, J. (2008). Rich cheat more on taxes, new study shows. Forbes . Web.

Smith, A. (1776). The Wealth of Nations. (E. Cannan, Ed.). ElecBook Classics.

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IvyPanda. (2022, June 24). Money, Happiness and Satisfaction With Life. https://ivypanda.com/essays/money-happiness-and-satisfaction-with-life/

"Money, Happiness and Satisfaction With Life." IvyPanda , 24 June 2022, ivypanda.com/essays/money-happiness-and-satisfaction-with-life/.

IvyPanda . (2022) 'Money, Happiness and Satisfaction With Life'. 24 June.

IvyPanda . 2022. "Money, Happiness and Satisfaction With Life." June 24, 2022. https://ivypanda.com/essays/money-happiness-and-satisfaction-with-life/.

1. IvyPanda . "Money, Happiness and Satisfaction With Life." June 24, 2022. https://ivypanda.com/essays/money-happiness-and-satisfaction-with-life/.

Bibliography

IvyPanda . "Money, Happiness and Satisfaction With Life." June 24, 2022. https://ivypanda.com/essays/money-happiness-and-satisfaction-with-life/.

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• Sample Essays

Sample essay: does money bring happiness?

by Manjusha Nambiar · Published April 7, 2014 · Updated November 14, 2023

IELTS essay prompt

Some people believe that money brings happiness; others are of the opinion that having too much money is a problem. Discuss both views and give your own opinion.

Sample response

Almost all of us are motivated by money. The only reason that most of us spend 8 to 10 hours at the workplace is to earn money. Money probably doesn’t bring happiness, but not having enough money to take care of our basic needs will seriously limit our happiness. No one wants to live in poverty and no one will lend to the poor.

Money helps us lead a comfortable life. It helps us provide the best possible education for our children. It ensures that our near and dear ones have access to medical attention whenever they need it.

Having more money than you need is unlikely to increase your levels of happiness, but not having enough will definitely destroy your peace of mind.

There is a limit to the amount of money that we can spend on ourselves. Still, the richest among us have amassed wealth they or their progeny will never use in their lifetime. Still, they aren’t satisfied. They want more. That is the lure of money. It never makes people content. Those who don’t have it want to have it. Those who have it want to have even more of it. Unfortunately, in our pursuit of riches, we often forget to live. We forget to appreciate the little joys that make our lives worth living.

Having a lot of money is definitely a problem. It even threatens our safety and security and makes us the target of thieves. Look at the richest people. They can’t move around freely like you or I. They are always surrounded by their personal security guards and often live their entire lives in constant fear of getting attacked.

To conclude, money is unlikely to make us happy, but we must still earn enough. However, in our pursuit of riches, we must not lose our souls. True happiness comes from spiritual awakening. Money has hardly anything to do with it.

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Manjusha Nambiar

Hi, I'm Manjusha. This is my blog where I give IELTS preparation tips.

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More Proof That Money Can Buy Happiness (or a Life with Less Stress)

When we wonder whether money can buy happiness, we may consider the luxuries it provides, like expensive dinners and lavish vacations. But cash is key in another important way: It helps people avoid many of the day-to-day hassles that cause stress, new research shows.

Money can provide calm and control, allowing us to buy our way out of unforeseen bumps in the road, whether it’s a small nuisance, like dodging a rainstorm by ordering up an Uber, or a bigger worry, like handling an unexpected hospital bill, says Harvard Business School professor Jon Jachimowicz.

“If we only focus on the happiness that money can bring, I think we are missing something,” says Jachimowicz, an assistant professor of business administration in the Organizational Behavior Unit at HBS. “We also need to think about all of the worries that it can free us from.”

The idea that money can reduce stress in everyday life and make people happier impacts not only the poor, but also more affluent Americans living at the edge of their means in a bumpy economy. Indeed, in 2019, one in every four Americans faced financial scarcity, according to the Board of Governors of the Federal Reserve System. The findings are particularly important now, as inflation eats into the ability of many Americans to afford basic necessities like food and gas, and COVID-19 continues to disrupt the job market.

Buying less stress

The inspiration for researching how money alleviates hardships came from advice that Jachimowicz’s father gave him. After years of living as a struggling graduate student, Jachimowicz received his appointment at HBS and the financial stability that came with it.

“My father said to me, ‘You are going to have to learn how to spend money to fix problems.’” The idea stuck with Jachimowicz, causing him to think differently about even the everyday misfortunes that we all face.

To test the relationship between cash and life satisfaction, Jachimowicz and his colleagues from the University of Southern California, Groningen University, and Columbia Business School conducted a series of experiments, which are outlined in a forthcoming paper in the journal Social Psychological and Personality Science , The Sharp Spikes of Poverty: Financial Scarcity Is Related to Higher Levels of Distress Intensity in Daily Life .

Higher income amounts to lower stress

In one study, 522 participants kept a diary for 30 days, tracking daily events and their emotional responses to them. Participants’ incomes in the previous year ranged from less than $10,000 to $150,000 or more. They found:

• Money reduces intense stress: There was no significant difference in how often the participants experienced distressing events—no matter their income, they recorded a similar number of daily frustrations. But those with higher incomes experienced less negative intensity from those events.
• More money brings greater control : Those with higher incomes felt they had more control over negative events and that control reduced their stress. People with ample incomes felt more agency to deal with whatever hassles may arise.
• Higher incomes lead to higher life satisfaction: People with higher incomes were generally more satisfied with their lives.

“It’s not that rich people don’t have problems,” Jachimowicz says, “but having money allows you to fix problems and resolve them more quickly.”

Why cash matters

In another study, researchers presented about 400 participants with daily dilemmas, like finding time to cook meals, getting around in an area with poor public transportation, or working from home among children in tight spaces. They then asked how participants would solve the problem, either using cash to resolve it, or asking friends and family for assistance. The results showed:

• People lean on family and friends regardless of income: Jachimowicz and his colleagues found that there was no difference in how often people suggested turning to friends and family for help—for example, by asking a friend for a ride or asking a family member to help with childcare or dinner.
• Cash is the answer for people with money: The higher a person’s income, however, the more likely they were to suggest money as a solution to a hassle, for example, by calling an Uber or ordering takeout.

While such results might be expected, Jachimowicz says, people may not consider the extent to which the daily hassles we all face create more stress for cash-strapped individuals—or the way a lack of cash may tax social relationships if people are always asking family and friends for help, rather than using their own money to solve a problem.

“The question is, when problems come your way, to what extent do you feel like you can deal with them, that you can walk through life and know everything is going to be OK,” Jachimowicz says.

Breaking the ‘shame spiral’

In another recent paper , Jachimowicz and colleagues found that people experiencing financial difficulties experience shame, which leads them to avoid dealing with their problems and often makes them worse. Such “shame spirals” stem from a perception that people are to blame for their own lack of money, rather than external environmental and societal factors, the research team says.

“We have normalized this idea that when you are poor, it’s your fault and so you should be ashamed of it,” Jachimowicz says. “At the same time, we’ve structured society in a way that makes it really hard on people who are poor.”

For example, Jachimowicz says, public transportation is often inaccessible and expensive, which affects people who can’t afford cars, and tardy policies at work often penalize people on the lowest end of the pay scale. Changing those deeply-engrained structures—and the way many of us think about financial difficulties—is crucial.

After all, society as a whole may feel the ripple effects of the financial hardships some people face, since financial strain is linked with lower job performance, problems with long-term decision-making, and difficulty with meaningful relationships, the research says. Ultimately, Jachimowicz hopes his work can prompt thinking about systemic change.

“People who are poor should feel like they have some control over their lives, too. Why is that a luxury we only afford to rich people?” Jachimowicz says. “We have to structure organizations and institutions to empower everyone.”

[Image: iStockphoto/mihtiander]

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How does valuing money affect your happiness, two new studies find that tying your self-worth to financial success hampers happiness and well-being—even for the well-off..

It may seem that money is a sure path to prestige and happiness. After all, many of our most well-paid citizens are held up as role models of success, leading seemingly perfect, enviable lives. Still, some people embrace the opposite idea: Money can’t buy you happiness. So, which of these is right?

In recent studies, scientists have found that the connection between wealth and well-being is not clear-cut. While some studies seem to tie wealth to well-being, others show that, after a certain point, a higher income will not bring more happiness or life satisfaction.

Now two new studies shed further light on the relationship between wealth and happiness. Their findings suggest that money doesn’t fulfill basic psychological needs, like belonging and competence. That’s why making more of it will not increase your happiness, even if you value money above other things. In fact, it may do the opposite.

What money can and can’t do for you

In one study , University of Buffalo researcher Lora Park and her colleagues investigated what happens when people tie their self-worth to financial success, scoring high on the “Financial Contingency of Self-Worth” scale, or FCWS. The researchers found that doing so made people engage in more social comparisons, experience more stress and anxiety, and feel less autonomy than those who didn’t tie their self-worth to income, regardless of their actual economic status.

“People in this society are often focused on pursuing money, and they don’t think there is anything bad about that,” says Park. “But in terms of your psychological well-being, there are all kinds of negative consequences.”

It also might affect your problem-solving ability. Park and her colleagues randomly assigned participants to write about their dissatisfaction with either an aspect of their financial situation—like not having enough money to pay rent—or their academic performance, like getting a bad test grade. Afterwards, they reported on what coping strategies they would use in response to the situation.

Research assistants analyzed the essays and found that participants who scored high in FCSW used more emotionally negative words and reported more disengagement strategies—like giving up or avoiding solutions—when writing about a financial stressor versus an academic stressor than people scoring low in FCSW. None of the results were affected by the actual income of the students.

People who are facing a problem should, logically, be focused on figuring out ways to solve it, says Park. “But what we found is that high financial contingency of self-worth somehow blocks that response.”

Why would this be?

Park believes that when people feel their self-concept is threatened in some way, they will become more self-protective so as not to experience low self-esteem. So, if your self-esteem is tied to money, a financial stressor will cause a lot more stress than it would for someone who doesn’t feel that way. Some support for her argument comes from another part of her experiment, where having participants high in FCSW remind themselves of their character strengths—like their intelligence or sense of humor—seemed to negate these avoidance effects.

Affirming Important Values

When your self-image takes a hit, reflect on what matters

“When people take a step back and have a broader perspective on their sense of self, that’s often enough to take them out of the self-esteem rumination/narrow focus they otherwise have,” says Park.

As prior research suggests, it can also be the case that people simply want money to do something that it cannot. “Self-esteem, like happiness, is a byproduct of meeting psychological needs—like meaning or purpose, feeling competent, having close relationships, or having a sense of autonomy—and basing your self-worth on financial success actually detracts from fulfilling those needs,” says Park.

Why community beats money

Park’s findings mirror other recent findings from the University of San Francisco’s Matthew Monnot, who studied financial success and well-being in China.

In his study , Monnot notes that, as China’s economy has grown, its citizens seem to be facing some of the same issues that Americans have faced. A growing number of people equate individual success with making more money and valuing money—an extrinsic reward—over other, more intrinsic rewards, like relationships or community. To see how this trend has affected well-being, he conducted a series of studies involving thousands of participants from several cities in China.

In one experiment, Monnot showed that job satisfaction did not rise in tandem with income. In fact, as with prior studies, wealth beyond a certain point tended to make Chinese workers no more satisfied with their jobs or their incomes, suggesting that money has only so much power to increase our life satisfaction.

“Our findings are pretty aligned with prior research,” says Monnot. “The correlation between income and job satisfaction is really small, to the extent that it predicts about five percent of job satisfaction.”

More on Money & Happiness

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Learn six ways to get more happiness for your money .

To tease out why, Monnot looked at how individual values shape the relationship between money and income satisfaction. He asked participants to pick the five factors they thought were most important for well-being from a list of 25 possible choices—including income—and then measured how satisfied they were with their income as it rose. Though one might expect people valuing income to be happier as they made more money, Monnot found the opposite: People who picked income as an important value were significantly less satisfied, even at higher levels.

“If income is important to you, then income is actually less satisfying as income goes up than if income is not important to you,” he says.

Though this seems paradoxical, Monnot says it makes some sense, when you understand how intrinsic versus extrinsic values affect our happiness.

“Not all goals are equal in terms of producing well-being, productivity, job satisfaction, or life satisfaction,” says Monnot. “If you say income is something really important to you, because income is an extrinsic reward and not part of your intrinsic needs, if you focus on it, it won’t make you happy.”

In other words, look inside of yourself, not your wallet, for happiness.

Monnot was curious to see how living in different cities in China might affect the relationship between valuing income and well-being. After all, if the government is developing policies to increase income in certain areas of the country, it would be good to know the impact this is having on happiness.

Again, he had people pick out five things they valued; but this time he separated people into different groups depending on whether they placed high value on materialistic things, like income and status, and placed low value on relationships and community, or vice versa. When he compared these two groups, people who valued relationships or community versus materialistic things had greater job satisfaction and overall life satisfaction. This was true regardless of their city’s per-capita income.

“The big idea is that higher GDP or people having more money is all great—especially at a societal level. You want your economy to be more productive and to have more resources and money available,” says Monnot. “Well, maybe that’s not necessarily in and of itself something that’s going to produce a happier population.”

Both Monnot and Park hope that their research might lead people to think a bit differently about the supposed benefits of striving for more money. Though neither would deny that we need money to survive, valuing it too highly or tying it to your self-worth is clearly a mistake.

Monnot hopes his research might help individuals—and business leaders and policymakers—to realize that fulfilling psychological needs is more important to happiness than making a lot of money.


“Autonomy, developing a skill set to be good at what you do, being affiliative with others, having a sense of connection to your community—these are all things that we as researchers are fairly convinced are innate, evolved human tendencies that bring happiness,” he says.

“If you can get people to focus on fulfilling those needs, they’ll become happier. The research is strongly in favor of that.”

About the Author

Jill Suttie

Jill Suttie, Psy.D. , is Greater Good ’s former book review editor and now serves as a staff writer and contributing editor for the magazine. She received her doctorate of psychology from the University of San Francisco in 1998 and was a psychologist in private practice before coming to Greater Good .

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Money Is Important But It Is Not Everything It When Comes to Well-Being

Money is important but is it everything? Does money buy happiness? These questions come up frequently but what are the answers? A daily survey in 2010 of 1,000 US residents conducted by the Gallup Organization showed that emotional well-being improved with raising income but this relationship diminished and plateau with further increasing of income beyond a ‘satiation point.’ At the time of the study was reported, the satiation point where no further improvement of emotional well-being with increasing income was around $75,000. Participants’ daily emotional well-being (hedonic well-being or experienced happiness) was measured by answered to questions about emotional experiences the previous day (frequency and intensity of experiences of joy, fascination, anxiety, sadness, anger, stress, worry, affection that make one’s life pleasant or unpleasant) . The study also measured participants’ life satisfaction by having participants answer questions on their thoughts or evaluation about their daily life in a scale from 0 to 10. Interestingly at the same time period, participants’ income ‘satiation point’ where raising income further no longer changed participants’ life satisfaction was higher at around $120,000. This study pointed out that money is important but it is not everything when comes to well-being.

Every individual and family are not created equal. This study indirectly indicates the importance of lifestyle medicine. Happiness is not only limited to hedonia but also eudaimonia. Adhering to lifestyle medicine pillars guides us towards our overall well-being!

By: Rusly Harsono, MD & Maya Shetty, BS

Journal Reference :

• Kahneman, Daniel, and Angus Deaton. “High Income Improves Evaluation of Life but Not Emotional Well-being.”  Proceedings of the National Academy of Sciences of the United States of America , v. 107 ,.38 pp. 16489-16493. doi:  10.1073/pnas.1011492107

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Money and happiness: the income–happiness correlation is higher when income inequality is higher

Shigehiro oishi.

Department of Psychology, University of Chicago, Chicago, IL 60637, USA

Youngjae Cha

Department of Psychology, University of Virginia, Charlottesville, VA 22904-4132, USA

Asuka Komiya

Graduate School of Integrated Arts and Sciences, Hiroshima University, Hiroshima 739-8511, Japan

Hiroshi Ono

School of International Corporate Strategy, Hitotsubashi University Business School, Tokyo 101-8439, Japan

Associated Data

All data (aggregated at the country-level) and the analytic codes are available in the Open Science Framework at https://osf.io/x5gcw .

Has the income–happiness correlation changed over time? If so, what predicts such changes? We tested these questions in diverse economic, political, and cultural contexts. Drawing on nationally representative data, we found that the income–happiness correlation has increased in the USA since 1972, as GDP per capita and income inequality increased (Study 1). Study 2 examined an income–life satisfaction correlation in nationally representative surveys between 1978 and 2011 in Japan. Unlike in the USA, there was no clear increase in the income–life satisfaction correlation over time. We next examined the income–life satisfaction correlations in 16 European countries and found that on average the income–life satisfaction correlation has increased since 1970, and it was particularly high in years of high GDP per capita and high-income inequality (Study 3). Finally, we found that among Latin American countries, the income–life satisfaction correlation has, on average, decreased since 1997, as income inequality has decreased (Study 4). Over the last 5 decades, the income–happiness correlation has increased, not decreased, in the USA and several European countries. The income–happiness correlation tends to get higher when both GDP per capita and income inequality are high, whereas it tends to get lower when GDP per capita and/or income inequality are low. These findings suggest the importance of accounting for income inequality as well as national wealth in understanding the role of money in happiness.

Significance Statement

Past research examined an income–happiness correlation in one cultural context over one time period, limiting our knowledge regarding whether the nature of the income–happiness correlation has changed over a long period of time, and if so, what predicts such changes. We found that the income–happiness correlation has increased in the USA and Europe since the 1970s, as both GDP per capita and income inequality increased. In contrast, the income–life satisfaction correlation has decreased since 1997 among Latin American countries, where income inequality has decreased during that time. The income–happiness correlation tends to get higher when GDP per capita and income inequality are high while getting smaller as GDP per capita and income inequality get smaller.

Introduction

Does money buy happiness? This question has received extensive empirical attention since Richard Easterlin’s seminal work in 1974 (e.g. 1–3 ; see 4–5 for reviews). Easterlin ( 6 ) looked at results from 30 national surveys in 20 countries and concluded that “there is a clear indication that income and happiness are positively associated” (p. 99), and that “in every single survey, those in the highest status group were happier, on the average, than those in the lowest status group” (p. 100). Diener and Oishi ( 7 ) examined the income–happiness correlation in 40 countries and found that the mean income–happiness correlation was 0.13. According to Diener and Biswas-Diener ( 4 ), the income–happiness correlation in a national survey ranged from 0.12 to 0.18 in the USA, 0.06 to 0.15 in West Germany, and 0.17 to 0.27 in the Russian Federation. A recent meta-analysis of 335 studies found that the mean income–happiness correlation was 0.23 ( 8 ).

Inglehart and colleagues ( 9 ) analyzed data from 52 countries and found that the income–happiness correlation was stronger in poorer countries than in richer countries. That is, money seems to buy more happiness in poorer countries than in richer countries. In this light, it is interesting to note that the income–happiness correlation was 0.45 among 83 residents in the slums of Calcutta ( 10 ). The main idea is that among those who are struggling to meet their basic needs, more money means greater access to basic goods (e.g. drinking water, food, shelter). In contrast, it is believed that once the basic needs are met, more money does not necessarily help increase one’s happiness ( 9 , 11 ).

These recent findings suggest that the income–happiness correlation within a country (e.g. the USA, Argentina) might have changed over time. For instance, it is possible that in the USA, the income–happiness correlation was smaller in the 1970s and 1980s when the earlier data were being collected than in the 2010s and the 2020s when more recent data were collected. In contrast, it is possible that in some countries, the income–happiness correlation has become smaller over time, as their national economy grew. These divergent patterns could explain why the earlier cross-country studies (e.g. 9 ) found that the income–happiness correlation was larger among poorer than richer countries, whereas it was larger among richer rather than poorer countries in more recent cross-country studies (e.g. 13 ).

To our knowledge, none of the previous research has examined whether the income–happiness correlation has changed over time. This is a critical oversight because the importance of money changes over time in a given society ( 14 , 15 ). Some countries might be becoming more materialistic, for example, while others might be becoming less materialistic over time ( 16 ).

Past research showed that the satisfaction of important life domains is more strongly associated with overall life satisfaction than the satisfaction of less important life domains ( 17 ). For instance, many people deem family relationships very important, whereas some do not. When the authors computed the correlation between family relationship satisfaction and life satisfaction, it was significantly stronger among those who deemed family relationships important than among those who did not. In the context of the present research, then, the income–happiness correlation should be larger as the importance of money increases, while it should be smaller as the importance of money decreases.

When does the importance of money increase or decrease? Based on Inglehart and colleagues’ findings ( 9 ), the end of materialism hypothesis predicts that the income–happiness correlation should get smaller as a society gets richer. This is because most people in a wealthy society are presumably no longer concerned about money per se, and instead are concerned about non-material issues such as self-expression. Under such a condition, self-expression should become a stronger predictor of happiness than money per se.

In contrast, there is an alternative possibility; as a society gets richer, people’s desires for material goods could also grow ( 18–21 ), and the importance of money could get even larger. For instance, some researchers found that American youths became more materialistic from the 1970s to the 1990s and their materialism remained high since then ( 15 ). In this scenario under the continuous materialism hypothesis, the income–happiness correlation should get larger as the economy grows.

Another important economic factor is the distribution of the national income. If the benefits of economic growth go disproportionately to the wealthy, then the poor feel that the world is unfair and report less happiness over time (e.g. 22 ). The larger the difference in happiness between the rich and the poor, the larger the correlation between income and happiness. In addition, growing income inequality is often driven by the rich getting richer ( 23 ), which in turn, provides more tendencies for ordinary citizens to engage in unfavorable, upward social comparisons ( 24 ). The frequency of upward social comparison is known to be detrimental to one’s happiness ( 25 ). In the current context, then, the economic gap between the rich and the poor should increase people’s tendency to engage in upward social comparison, which should in turn increase the happiness gap between the rich and the poor.

Moreover, income inequality is associated with more perceived competition ( 26 ), zero-sum thinking ( 27 ), and status anxiety ( 28 ). If income inequality has increased over time in a given country, then, the concern for money might have increased also. Indeed, previous research found that an increase in income inequality was associated with an increase in work hours ( 29 ). The increased concern for money, in turn, could translate into a larger income–happiness correlation (hereafter we call it the income inequality hypothesis). Furthermore, income inequality tends to be larger in countries where social welfare spending is low (e.g. Greece) than where social welfare spending is high (e.g. Sweden) because many welfare systems are funded through progressive taxation ( 30 ).

In a cross-sectional study of 29 countries, Ono and Lee ( 31 ) found that the income–happiness correlation was higher in countries where public social expenditure was lower than where it was higher. Ono and Lee’s findings are consistent with the hypothesis that the income–happiness correlation should be higher when income inequality is higher. As stated above, a shortcoming of the previous research is that it has not examined changes in the income–happiness correlation over time.

In sum, the main goals of the present research are to explore historical changes in the income–happiness correlation in diverse cultural, economic, and political contexts: the USA (Study 1), Japan (Study 2), Europe (Study 3), and Latin America (Study 4), and to test whether the historical changes in the income–happiness correlation are associated with GDP per capita and income inequality. The end of materialism hypothesis states that the income–happiness correlation will get smaller with an increase in GDP per capita. In contrast, the continuous materialism hypothesis states that the income–happiness correlation will get larger with an increase in GDP per capita. The income inequality hypothesis provides an alternative explanation for these conflicting hypotheses, instead predicting that the income–happiness correlation will get larger with an increase in income inequality.

Study 1: The USA 1972 to 2018

The General Social Surveys (GSS) have included the 3-point happiness scale since its inception in 1972. We used this item with the self-reported household income from all the survey years. Because the value of the dollar has changed dramatically over time, the income categories in 1972 are not comparable to those in 2018. Furthermore, different years have different income categories (e.g. in 1972, there were 12 income categories; whereas in 1977 there were 20 categories). This inconsistency in response categories across years makes it questionable to use the income variable across different survey years in a single multilevel analysis. Thus, we used the meta-analytic framework, treating each year’s income–happiness correlation as an independent “study” result, as opposed to the multilevel framework in which the income variable has to be treated as equivalent across years. Finally, the original happiness scale was reversed to make the higher score indicate more happiness.

Figure  1 (left, panel A) shows the income–happiness correlation as a function of the survey year in the USA. The income–happiness correlation has steadily increased since the 1970s. Interestingly, however, in the post-Lehman shock surveys from 2010, 2012, and 2014, the correlations decreased. Fisher z -transformed income–happiness correlation coefficient was significantly associated with the survey year ( r [30] = 0.65, P  < 0.001) and the log-transformed GDP per capita ( r [30] = 0.66, P  < 0.001). Overall, the patterns of the results are generally consistent with the continuous materialism hypothesis, as the income–happiness correlation increased over the last 50 years during which GDP per capita has steadily increased.

The log income–happiness correlation by survey year in the USA and in Japan.

Note: The x -axis is the survey year in each country (begins at the first survey year available in each country: 1972 for the USA; 1978 for Japan). The y -axis is the correlation between the log of income and happiness (Fisher z -transformed). The error bar indicates the SE of the log income–happiness correlation. The blue line depicts the total trend (USA: y  = 0.0016x–2.9762, R 2  = 0.4224; Japan: y  = 0.0015x–2.7704; R 2  = 0.0817).

Next, we tested the income inequality hypothesis. To the extent that the rich got richer, while the poor remained poor, the difference between the rich and the poor in the USA widened. The widening of the wealth gap might have translated into the widening of the happiness gap between the rich and the poor. As seen in Fig.  2 , the Gini coefficients were highly positively correlated with the income–happiness correlation ( r [30] = 0.66, P  < 0.001). That is, in the years of greater income inequality, the correlation between income and happiness was stronger. The formal test with the classic meta-analysis function of the JASP program, using the restricted maximum likelihood estimation, showed that the household income inequality (Gini) significantly moderated the income–happiness correlation, b  = 0.767 (SE = 0.149), z  = 5.15, and P  < 0.001. There was a substantial degree of heterogeneity in the income–happiness correlations between 1972 and 2018, Q (1, 31) = 73.20, and P  < 0.001. Once we entered the Gini coefficient as the moderator, there was no longer heterogeneity in the remaining income–happiness correlations, Q (1, 30) = 38.35, P  = 0.141.

The log income–happiness correlation by the Gini coefficient in the USA and in Japan.

Note . The x -axis indicates the Gini coefficient. The y -axis is the correlation between the log of income and happiness (Fisher z -transformed). The error bar indicates the SE of the log income–happiness correlation. The blue line depicts the total trend (USA: y  = 0.5921x + 0.3215, R 2  = 0.4281; Japan: y  = 0.0232x + 0.237; R 2  = 0.010).

Alternative specifications

Because the Gini coefficient is an omnibus index of inequality, it does not specify whether the above findings are driven mostly by the top 10% or the bottom 50%. We used the top 10% share and the bottom 50% share of the national income, respectively, as the moderator. The results were similar to the Gini findings. The income–happiness correlation was larger when the top 10% share of the national income was higher, b  = 0.53 (SE = 0.11), z  = 4.96, and P  < 0.001. With the top 10% share of the national income included in the analysis, there was no longer heterogeneity in the remaining income–happiness correlations, Q (1, 30) = 39.75, P  = 0.110. Conversely, the income–happiness correlation was smaller when the bottom 50% share of the national income was larger, b = −0.86 (SE = 0.18), z = −4.76, and P  < 0.001. With the bottom 50% share of the national income included in the analysis, there was no longer significant heterogeneity, Q (1, 30) = 41.09, P  = 0.085. Thus, using the alternative specifications, the income inequality hypothesis was supported in Study 1. In sum, Study 1 found support for the continuous materialism hypothesis and the income inequality hypothesis and did not find any support for the end of materialism hypothesis.

Study 2: Japanese lifestyle surveys 1978 to 2011

Study 1 found patterns of the income–happiness correlation consistent with the continuous materialism hypothesis and the income inequality hypothesis, and inconsistent with the end of materialism hypothesis. As the economy grew, the income–happiness correlation increased rather than decreased over time. The USA has one of the most extreme forms of the winner-take-all economy and politics ( 32 , 33 ). Thus, the USA could be an exception. Namely, it is possible that in other developed countries, the end of materialism hypothesis could still hold. Japan provides an ideal testing ground, as it is similar to the USA in terms of the GDP per capita, but different in many other dimensions. Most central to this research, the degree of income inequality is substantially smaller in Japan than in the USA (e.g. 34 ), and the Japanese are more aversive toward income inequality than Americans ( 35 ).

In order to test whether the increasing income–happiness correlation is specific to the USA, we next analyzed the Japanese Lifestyle Surveys, the nationally representative surveys conducted by the Japanese government from 1978 to 2011. The same 5-point scale life satisfaction question (“Are you satisfied or dissatisfied with your life in general?”) was included except in 2007, 2010, and 2011.

Figure  1 (right, panel B) shows the income–happiness correlation as a function of the survey year in Japan. Unlike in the USA, the income–life satisfaction correlation has not increased over time between 1978 and 2009 ( r [18] = 0.29, P  = 0.222). The Fischer-transformed income–life satisfaction correlation was not correlated with log-transformed GDP per capita ( r [18] = 0.03, P  = 0.895). Unlike Study 1, the income–life satisfaction correlation in Japan was not correlated with the Gini coefficient ( r [17] = 0.10, P  = 0.675), as well. Similarly, neither the top 10% share of the national income nor the bottom 50% share of the national income were associated with the size of the income–life satisfaction correlation: r (18) = 0.35, P  = 0.131 for the top 10%; r (17) = −0.32, P  = 0.182 for the bottom 50%. In sum, the patterns of the income–happiness correlations in Japan were not consistent with any hypotheses.

Study 3: Eurobarometer surveys 1970 to 2002 and European social surveys 2004 to 2018

The USA and Japan showed different patterns of the income–happiness correlations over time. This could be due to the divergent pattern of economic growth in the USA and Japan: while the USA economy grew more or less linearly between 1972 and 2018 (Study 1), the Japanese economy stagnated between 1991 and 2011 (Study 2). In order to test the generalizability of our initial findings among Americans and Japanese, we examined the income–life satisfaction correlations over time among 16 European countries. We analyzed the Eurobarometer surveys and the European Social Surveys (ESS). The Eurobarometer included the 4-point scale life satisfaction question in most years, whereas the ESS included the 10-point scale life satisfaction question in most years. We chose the countries included both in the Eurobarometer and ESS in the following analyses. (Eurobarometer and ESS contain data from countries have changed their names/boundaries historically [i.e. Great Britain and West-Germany in Eurobarometer; the UK and Germany in ESS]. For consistency, we used “the UK” and “Germany” across the studies.) This resulted in 16 countries with a total income–life satisfaction correlation of 414. Many of the recent Gini coefficients were not available (for instance, the World Bank’s database [ https://data.worldbank.org/indicator ] does not have any Gini coefficients for France before 1978; furthermore, years 1979 to 1988 are missing; in contrast, the World Inequality database [ https://wid.world/ ] has the top 10% share and the bottom 50% share of the national income every year since 1915 for France), whereas the top 10% share and the bottom 50% share were consistently available ( https://wid.world/ ). Thus, in Studies 3 and 4, we used these two indices of income inequality as opposed to the Gini coefficient.

Like in Studies 1 and 2, we first computed an income–life satisfaction correlation for each year for each country (e.g. r  = 0.13 in 1976, r  = 0.11 in 1977, r  = 0.14 in 1978 etc. in France; r  = 0.17 in 1976, r  = 0.20 in 1977, r  = 0.18 in 1978 etc. in Belgium). We then computed a correlation between income–life satisfaction correlations (Fisher z -transformed) and the survey year, GDP per capita (log-transformed), the top 10%, and the bottom 50% share in each of the 16 countries, respectively. Table  1 shows these correlations. Figure  3 shows the income–happiness correlation as a function of the survey year across countries in Europe.

The log income–happiness correlation by survey year by Country in Europe (1970 to 2018).

Note . Inc-LS Cor. Indicates the correlations between log income and life satisfaction (Fisher z -transformed). The error bar indicates the SE of the correlation coefficient.

The correlations between the log income–happiness correlations and the survey year (yearly trend), GDPpc (LN), and two-income inequality indices (top10% share of the national income and bottom 50% share of the national income).

Note . * P  < 0.05. ** P  < 0.01. The correlation coefficients between the within-country log income–happiness correlations (Fisher z -transformed) and the survey year, GDP per capita (Log-transformed), top 10% share of the national income, and bottom 50% share of the national income of the year.

The first column of Table  1 shows the correlation between the income–life satisfaction correlation and the year of the survey. A positive correlation (e.g. r  = 0.78 in Germany, 0.74 in France) indicates that the income–life satisfaction correlation increased over time in that country, whereas, a negative correlation (e.g. r = −0.28 in Norway) indicates that the income–life satisfaction correlation decreased over time in that country. Like in the USA, the income–life satisfaction correlation has substantially increased between 1970 and 2018 in France, Germany, Finland, Portugal, the UK, and the Netherlands ( r s ranged from 0.42 to 0.78). In contrast, the income–life satisfaction correlation has decreased in Norway. We meta-analyzed the correlations between the within-country income–life satisfaction correlation (Fisher z -transformed) and the year of the survey, with the random-effects model, using the meta package in R. The meta-analytic mean correlation of yearly trends was 0.44 (95% CI: 0.29; 0.57; t  = 5.80, P  < 0.001) among 16 European countries. That is, on average, the income–happiness correlation increased over time among 16 European countries.

The second column of Table  1 shows the correlation between the income–life satisfaction correlation and GDP per capita (log-transformed). A positive correlation (e.g. r  = 0.72 in Germany, r  = 0.67 in Portugal) indicates that the income–life satisfaction correlation was larger when GDP per capita was higher, whereas a negative correlation (e.g. r = −0.36 in Norway) indicates that the income–life satisfaction correlation was smaller when GDP per capita was lower. Our results showed that the size of an income–life satisfaction correlation was highly positively correlated with GDP per capita (log-transformed) in Portugal, France, Germany, the Netherlands, and the UK ( r s ranged from 0.38 to 0.72). The meta-analytic mean correlation of the income–life satisfaction correlation with GDP per capita was 0.35 (95% CI: 0.20; 0.49; t  = 4.81, P  < 0.001) among 16 European countries. These findings are consistent with the continuous materialism hypothesis, and inconsistent with the end of materialism hypothesis.

Next, we examined whether the income–life satisfaction correlations were larger in the year of larger income inequality. The third column of Table  1 shows the correlation between the income–life satisfaction correlation and the top 10% share of the national income. A positive correlation (e.g. r  = 0.79 in Germany) indicates that the income–life satisfaction correlation got larger, as the top 10% share grew, whereas a negative correlation (e.g. r = −0.71 in Sweden) indicates that the income–life satisfaction correlation got smaller, as the top 10% share grew. Like in the USA, the income–life satisfaction correlations were substantially higher in the year of a higher share of the national income being held by the richest 10% of the population in Germany, Portugal, Austria, Greece, and the UK. In contrast, it was smaller in the year with a higher top 10% share in Sweden. Overall, the meta-analytic mean correlation of the income–life satisfaction correlation with the top 10% share was 0.22 (95% CI: −0.03 0.44; t  = 1.85, P  = 0.083). That is, across 16 European countries, on average, the income–life satisfaction correlation tended to be larger in the year of the higher concentration of the national wealth in the richest 10% of the population.

The last column of Table  1 indicates the correlation between the income–life satisfaction correlation and the bottom 50% share of the national income. A negative correlation (e.g. r = −0.79 in Germany) in this column means that the income–life satisfaction correlation was smaller in the year of the larger bottom 50% share of the national income. Like in the USA, the income inequality hypothesis was supported in Germany, Finland, the Netherlands, Portugal, and Austria. In contrast, it was not supported in Belgium, the UK, Ireland, Spain, and Norway. Overall, the meta-analytic mean correlation of the income–life satisfaction correlation with the bottom 50% share was −0.26 (95% CI: −0.45; −0.05; t = −2.65, P  = 0.018). Thus, on average, the income–life satisfaction correlations were larger when the bottom 50% share was smaller, consistent with the income inequality hypothesis.

In sum, the meta-analyses showed that the income–life satisfaction correlations between 1970 and 2018 among 16 European countries on average were similar to those in the USA. Like in the USA, the income–life satisfaction correlations increased over time. The income–life satisfaction correlation was higher in the year of higher GDP per capita. It was marginally higher in the year of higher top10% share, whereas significantly lower in the year of higher bottom 50% share of the national income. The European data on average provided support for the continuous materialism hypothesis and the income inequality hypothesis, and no support for the end of materialism hypothesis.

Study 4: Latinobarometro 1997 to 2018

Studies 1 to 3 showed that the income–life satisfaction correlation (a) increased over time in the USA and European countries on average, (b) coincided with an increase in GDP per capita, and (c) an increase in income inequality in the USA and European countries on average. We explored whether the patterns of the income-happiness/life satisfaction correlations found in the USA and European countries are generalizable among Latin American countries. In the USA and several European countries, income inequality has increased as the economy grew over the last 40 years. Latin America is an interesting case in that, unlike in the WEIRD (Western Educated Industrialized Rich Democratic) countries, income inequality has decreased over the last 40 years as the economy grew ( 36 , 37 ). We tested the trends of the income–life satisfaction correlation over time among 18 Latin American countries over the last 2 decades.

We analyzed the Latinobarometro data from 1997 to 2018. Life satisfaction was assessed with the 4-point scale (1 = not very satisfied to 4 = very satisfied). Income was not directly assessed. However, respondents’ assessment of their income was assessed every year using the 4-point scale (“Does your salary and the total of your family’s salary allow you to satisfactorily cover your needs?” 1 = Does not cover, there are great difficulties to 4 = covers them well, I can save”). We used these two items to calculate the correlation between income and life satisfaction each year for each country.

Like in Studies 1 to 3, the income–life satisfaction correlation was computed for each year for each country, separately. First, whereas the income–life satisfaction correlations have grown larger over time in the USA and several European countries, on average, the income–life satisfaction correlation has become smaller among Latin American countries (see Fig.  4 ), as indicated by many negative correlations in the first column of Table  1 : the meta-analytic r = −0.15 (95% CI: −0.28; −0.02; t = −2.43, P  = 0.027).

The log income–happiness correlation by survey year by country in Latin America (1997 to 2018).

Furthermore, the second column of Table  1 shows that, unlike the USA and several European countries, the income–life satisfaction correlation was not associated with GDP per capita among 18 Latin American countries: meta-analytic r = −0.04 (95% CI: −0.18; 0.10, t = −0.63, P  = 0.53). Finally, the patterns of the income–life satisfaction correlation with income inequality indices (the 3rd and 4th columns of Table  1 ) were similar to those found in the USA and Europe. The income–life satisfaction correlation was smaller when the bottom 50% share was larger: meta-analytic r = −0.16 (95% CI: −0.31; 0.003; t = −2.07, P  = 0.054), although the correlation with the top 10% share of income was not statistically significant (meta-analytic r  = 0.09 [95% CI: −0.05; 0.23; t  = 1.38, P  = 0.186]). Thus, Latin American data were mostly consistent with the income inequality hypothesis.

The multilevel meta-analyses of studies 1 to 4

We next meta-analyzed the income-happiness/life satisfaction correlations from the USA, Japan, 16 European countries, and 18 Latin American countries simultaneously to get an overall estimate of the effect size across 36 countries. There were 768 income-happiness/life satisfaction correlations from 36 countries. We meta-analyzed them with the multilevel model, using the metafor package in R (Level 1 = within-country; Level 2 = between-country). The base model in which the income–happiness correlation was predicted by year only showed that the intercept was 0.173 ( SE  = 0.009), t (766) = 19.85, P  < 0.001. On average, the z -transformed income–happiness correlation was 0.173 in the first year of the survey across 36 countries, which were slightly higher than Diener and Oishi’s ( 7 ) earlier review ( r  = 0.13, which did not include Latin America) and lower than the most recent meta-analysis: r  = 0.23 ( 8 ). The slope for the year was 0.001 ( SE  = 0.0014), t  = 7.50, P  < 0.001, meaning that one year corresponded to an increase of 0.001 in the income–happiness correlation on average. The results from 3 different sets of meta-analyses are shown in Table  2 . Model 1 included year, three dummies (dummy 1 = Japan; dummy 2 = Europe, 3 = Latin America), and interaction terms (region dummies with the yearly trend). The results from Model 1 showed that (a) the income–happiness correlations in the USA were on average higher than Japan, Europe, and Latin America, (b) that there was no difference between Japan and the USA, nor a difference between Europe and the USA in the yearly trend, but (c) that the yearly trend of Latin American countries was significantly different from that of the USA.

Multilevel meta-analyses of studies 1 to 4.

Note . Bold-faced lines indicate statistically significant findings. Asterisks indicate interaction terms. The z-transformed log income–happiness correlation was predicted by yearly trend (the first year of the survey coded as 0), Japan (Japan = 1; the rest = 0), Euro (Euro = 1; the rest = 0), Latin America (Latin American = 1; the rest = 0), and three interaction terms in Model 1. The z -transformed log income–happiness correlation was predicted by Japan (Japan = 1; the rest = 0), Euro (Euro = 1; the rest = 0), Latin America (Latin American = 1; the rest = 0), GDP per capita (log-transformed, then z -scored within each country), top 10% (z-scored within each country), and the interaction term in Model 2. The z -transformed log income–happiness correlation was predicted by Japan (Japan = 1; the rest = 0), Euro (Euro = 1; the rest = 0), Latin America (Latin American = 1; the rest = 0), GDP per capita (log-transformed, then z -scored within each country), bottom 50% ( z -scored within each country), and the interaction term in Model 3. CILL = Confidence Interval Lower Limit. CIUL = Confidence Interval Upper Limit. Q denotes Q statistics, the indicator of heterogeneity of effect sizes.

Model 2 tested whether the income–happiness correlations were larger in the years of higher levels of GDP per capita and the top 10% of share simultaneously (Model 2). Controlling for the regional differences in the mean income–happiness correlation and top 10% share, one standard deviation increase in GDP per capita (e.g. 1 SD of log GDP was 0.22 for the USA) corresponded to a 0.009 increase in the income–happiness correlation, t  = 3.79, P  < 0.001. Thus, across 36 countries, on average, the income–happiness correlation was larger when GDP per capita was higher, supporting the continuous materialism hypothesis as opposed to the end of materialism hypothesis. In addition, this analysis showed that one standard deviation increase in the top 10% share of the national income was, on average, associated with a 0.009 increase in the income–happiness correlation, t  = 4.33, P  < 0.001, supporting the income inequality hypothesis (for the time trends in GDP and the top 10% share across countries, see Figures S1 to S8, Supplementary Material 2 ).

Model 3 tested whether the income–happiness correlation was larger in the years of a smaller share of the bottom 50% across the 36 countries. The results from Model 3 showed that controlling for the regional differences and the bottom 50% share, the income–happiness correlation was larger in the year of higher GDP per capita, again supporting the continuous materialism hypothesis. One standard deviation increase in GDP per capita was associated with a 0.008 increase in the income–happiness correlation. Consistent with the income inequality hypothesis, the income–happiness correlation was smaller in the year of a larger bottom 50% share of the national income (i.e. less income inequality) than in the year of a smaller bottom 50% share of the national income (i.e. more income inequality). One standard deviation increase in the bottom 50% share of the national income was associated with a 0.010 decrease in the income–happiness correlation. Finally, there was a significant interaction between GDP per capita and the bottom 50% share, such that the income–happiness correlations were larger in the year of higher GDP per capita and the smaller bottom 50% share (i.e. more income inequality).

General discussion

We started our investigation to explore historical changes in the income–happiness correlation in diverse samples. In the USA the income–happiness correlation has increased substantially since 1972 (Fig.  1 ). In contrast, the income–life satisfaction correlation did not increase from 1978 to 2011 in Japan (Study 2). Study 3 analyzed the Eurobarometer and European Social Surveys from 1970 to 2019. The meta-analysis largely replicated the findings from the USA On average, the income–life satisfaction correlation among the 16 European countries increased over time. Finally, we examined the patterns of the income–life satisfaction correlation among Latin Americans from 1997 to 2018. Unlike in the USA, Japan, and Europe, the income–life satisfaction correlation decreased over time in Latin America.

Overall, the historical patterns of the income–happiness correlation observed in the USA and several European countries, most notably Germany, the UK, the Netherlands, and Portugal, were consistent with the continuous materialism hypothesis and the income inequality hypothesis. In contrast, the patterns observed in Latin America were only consistent with the income inequality hypothesis.

In support of the continuous materialism hypothesis, the income–happiness correlation became larger as GDP per capita increased in the USA, France, Germany, UK, the Netherlands, and Portugal. In these countries, when the national economy was stronger, money appeared to be more important to people’s happiness than when the national economy was weaker. These findings are consistent with Robert Frank’s (1999) idea of luxury fever at a time of the economic boom. Even when survival per se is no longer an issue, money still matters to many people. Money can buy them a better car, a smartphone, and a bigger house. As people’s financial situations improve, the material possessions deemed necessary increase, as well ( 38–40 ). As desires increase, money continues to matter even more, making the income–happiness correlation stronger, not weaker.

Furthermore, in the USA and European countries on average, when income inequality was larger, money appeared to be more important than when income inequality was smaller. These findings are consistent with the previous findings on the psychology of inequality: namely, inequality appears to amplify people’s tendencies to perceive more competition in society ( 26 ), believe in the zero-sum nature of society ( 27 ), and engage in unfavorable upward social comparison ( 24 ), in particular among the poor. Likewise, fairness and general trust might be eroded particularly among the poor at a time of high levels of income inequality ( 22 ). This could, in turn, increase the happiness gap between the rich and the poor, inflating the income–happiness correlation. In addition, Laurin et al. ( 38 ) findings on fairness and self-regulation suggest that the poor might be more likely to give up trying to achieve long-term goals at a time of vast inequality than small inequality. This in turn could decrease the happiness of the poor, resulting in a larger happiness gap between the rich and the poor. In the future, it is important to directly measure changes in desires and the importance of money, as well as these psychological mechanisms in the context of changes in the income–happiness correlation.

Whereas the continuous materialism hypothesis and the inequality hypothesis were equally associated with historical changes in the income happiness correlations in the USA and Europe, the income inequality hypothesis was the only hypothesis that received empirical support in Latin America. Since 1997 (the first year of our data in Latin America), income inequality has declined in most Latin American countries. For instance, in Argentina, the bottom 50% share of the national income increased from 10.6% in 2000 to 17.8% in 2018. In contrast, during the same period, the bottom 50% share went down from 15.1% to 13.5% in the USA. Thus, in many Latin American countries, the decreased levels of income inequality might have reduced perceived competition, zero-sum thinking, and unfavorable upward social comparison, reducing the happiness gap between the rich and the poor. Again, these psychological mechanisms should be explicitly tested in the context of Latin America.

Although we analyzed most of the nationally representative data available today, the years covered by these surveys were still limited. For instance, Study 2 included only 20 surveys, limiting the statistical power to detect only large effect sizes. Second, it is interesting that among European countries, several countries such as the Netherlands, Germany, UK, and Portugal were similar to the USA (a strong positive correlation between GDPpc and income inequality); The yearly trend in Norway was quite different from other European countries. It is important to identify a moderator to explain these cross-national variations in the future. It is also important to examine alternative explanations to the continuous materialism (e.g. inflation, unemployment rate) and income inequality hypotheses (e.g. social welfare spending).

Finally, although it is unlikely that a change in the income–happiness correlation causally affects a change in income inequality or GDPpc, our design does not allow for causal inference. As more data become available, a more stringent time series analysis (e.g. Granger’s causality test) should be conducted to discern a causal relation better.

We found that the income–happiness correlation has increased in the USA and several European countries (e.g. Germany, the Netherlands, Portugal) since 1972 as GDP per capita and income inequality increased. In contrast, in Latin American countries on average, the income–happiness correlation has decreased since 1997. In Japan and several other countries (e.g. Denmark, Panama), the income–happiness correlation has not significantly changed. These divergent historical trends of the income–happiness correlation were associated with economic conditions. The income–happiness correlation tends to get larger as GDP per capita increases, providing support for the continuous materialism hypothesis. Independently, the income–happiness correlation tends to get larger as top 10% share of the national income increases and bottom 50% share of income decreases, providing support for the income inequality hypothesis. These findings suggest that on average, money becomes more central to one’s happiness under high GDP per capita and high income inequality. That is, in developed countries such as the USA, Germany, and the Netherlands, materialism is persistent. In understanding the role of money in happiness, researchers need to account for not just national wealth but also how national wealth is distributed across social class, as both national wealth and inequality appear to be associated with materialism.

Materials and methods

All data, the analytic codes, and supplementary materials are available in the Open Science Framework at https://osf.io/x5gcw . For the descriptive statistics and correlations between variables, see Supplementary Material 1 .

Study 1 method

General social surveys.

Participants were 64,814 Americans (28,614 men, 36,200 women) age 18 and over. Out of 64,814 respondents, 52,033 were white, 9,187 were black (3,594 were “Other”). The mean age was 46.10 (SD = 17.54). The mean number of respondents who answered the happiness item per survey year was 1,692.91 (SD = 481.13), ranging from 1,173 to 2,627.

The 3-point scale happiness item (“Taken all together, how would you say things are these days—would you say that you are very happy, pretty happy, or not too happy?”) was included in every survey. The responses were reverse scored such that 1 = not too happy, 2 = pretty happy, and 3 = very happy.

GDP per capita was taken from https://wid.world/ . Gini coefficient was taken from Table H-4 in https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-income-households.html .

Study 2 method

Participants were 80,857 Japanese (37,212 men; 40,254 women) age 15 to 88. The mean age was 44.54 (SD = 15.57). The mean number of respondents for the life satisfaction question used per year was 2,846.61 (SD = 1,548.23), ranging from 1,692 to 7,405.

The 5-point scale life satisfaction item (1 = dissatisfied, 2 = rather dissatisfied, 3 = neither satisfied nor dissatisfied, 4 = rather satisfied; 5 = satisfied) was included in 1978, 1981, 1984, 1985, 1987, 1988, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1999, 2001, 2002, 2005, 2006, 2008, and 2009.

Income was measured differently in different surveys. In 1978, 1981, 1984, 1987, 1988, 1990, it was measured by a 21-point scale (1 = less than 750,000 yen; 2 = 750,000 to 1.25 mil yen; 3 = 1.25 to 1.75 mil yen. . .21 = over 10.25 mil yen). In 1985, it was measured by a 27-point scale (1 = None, 2 = less than 500,000 yen; 3 = 500,000 to 1 mil yen; 4 = 1 to 1.5 mil yen. . .27 = over 20 mil yen). In 1991, it was measured by a 23-point scale (1 = less than 1.25 mil yen; 2 = 1.25 to 1.75 mil yen; 3 = 1.75 to 2.25 mil yen, 4 = 2.25 to 2.75 mil yen. . .23 = over 30mil yen). In 1992, 1996, 1999, 2002, 2005, 2008, and 2011, it was measured by an 8-point scale (1 = less than 2mil yen; 2 = 2 to 4 mil yen; 3 = 4 to 6 mil yen; 4 = 6 to 8 mil yen; 5 = 8 to 10 mil yen; 6 = 10 to 12 mil yen; 7 = 12 to 14 mil yen, 8 = over 14 mil yen). In 1993, it was measured by a 12-point scale (1 = less than 750,000 yen; 2 = 750,000 to 2.25 mil yen; 3 = 2.25 to 3.75 mil yen. . .12 = over 15.75 mil yen). In 1994, it was measured by a 13-point scale (1 = less than 500,000 yen; 2 = 500,000 to 1 mil yen; 3 = 1 to 1.5 mil yen; 4 = 1.5 to 2 mil yen. . .13 = over 10 mil yen). In 1995, it was measured by a 9-point scale (1 = less than 1 mil yen; 2 = 1 to 2 mil yen; 3 = 2 to 4 mil yen; 4 = 4 to 6 mil yen. . .9 = over 14 mil yen). In 2001, it was measured by a 10-point scale (1 = less than 20mil yen; 2 = 2 to 4 mil yen; 3 = 4 to 6 mil yen; 4 = 6 to 8 mil yen. . .10 = over 20 mil yen). In 2006 and 2007, it was measured by a 10-point scale (1 = less than 1mil yen; 2 = 1 to 3 mil yen; 3 = 3 to 5 mil yen; 4 = 5 to 7 mil yen. . .10 = over 20 mil yen). In 2009 and 2010, it was measured by a 5-point scale (1 = less than 1 mil yen; 2 = 1 to 3 mil yen; 3 = 3 to 5 mil yen; 4 = 5 to 10 mil yen; 5 = over 10 mil yen). The income variables were converted to yen, then log-transformed, as in Study 1.

GDP per capita was taken from https://wid.world/ . Gini coefficient was taken from https://data.worldbank.org/indicator .

Study 3 method

Study 3 combined annual datasets from Eurobarometer Surveys 1973 to 2002 and biennial datasets from European Social Surveys 2004 to 2018. Participants from Eurobarometer Surveys were 659,140 Europeans ( M age  = 43.16, SD age  = 17.92, 51.7% women). Participants from European Social Surveys were 422,985 Europeans ( M age  = 48.29, SD age  = 18.63, 53.8% women). The mean number of respondents who answered the life satisfaction item per survey year was 28,885.73 ( SD  = 14,422.27), ranging from 8,767 to 54,151.

As for the life satisfaction item, every survey year of Eurobarometer Surveys included the 4-point scale life satisfaction item (“On the whole, are you very satisfied, fairly satisfied, not very satisfied, or not at all satisfied with the life you lead?”), except for 1974 and 1996. Every survey year of European Social Surveys included the life satisfaction item (“How satisfied with life as a whole”), with different answer scales such as 10-points (0 = extremely dissatisfied; 10 = extremely satisfied). As for the household income item, both Eurobarometer Surveys and European Social Surveys used different categories and scales across countries and years. There are the variables named “income” in Eurobarometer Surveys and “hinctnt” and “hinctnta” in European Social Surveys, which used different categories and scales in each of the 16 countries. Compared to the other survey years that used money values, the 2008 to 2018 surveys used income deciles in each nation. All the income variables were converted to the local currency and log-transformed, as in Studies 1 and 2.

GDP per capita, the top 10% share of the national income, the bottom 50% share of the national income were taken from https://wid.world/ .

Study 4 method

Data across 18 Latin American countries were derived from Latinobarometro 1997 to 2018 ( https://www.latinobarometro.org/ ). The total number of participants who answered life satisfaction and income item were 431,148 ( M age  = 40.05, SD age  = 16.47, 51.5% women). Ethnicity/race data are available only in 2007 to 2018 (0.66% Asian, 5.45% Black, 9.33% Indigenous, 46.83% Mestizo, 5.95% Mulato, 29.86% White, 1.94% Other race). The mean number of respondents who answered the life satisfaction item per survey year was 20,873 ( SD  = 1560.91), ranging from 17,601 to 22,615.

Life satisfaction was measured with the 4-point scale (“Generally speaking, would you say you are satisfied with your life? Would you say you are. . .? 1 = not very satisfied to 4 = very satisfied).

Income was assessed using the 4-point scale (“Does your salary and the total of your family’s salary allow you to satisfactorily cover your needs? 1 = Doesn’t cover, there are great difficulties to 4 = covers them well, I can save”).

Skewness and kurtosis were within the acceptable range (skewness < 2.00; kurtosis < 7.00, according to 39) as follows: 1997 (0.17; −0.56), 1998 (0.12; −0.65), 2000 (0.09; −0.58), 2001 (0.11; −0.73), 2002 (0.01; −0.72), 2003 (−0.02; −0.8), 2004 (−0.01; −0.82), 2005 (−0.03; −0.78), 2006 (0.11; −0.58), 2007 (0.11; −0.58), 2008 (0.05; −0.57), 2009 (0.06; −0.61), 2010 (0.09; −0.56), 2011 (0.19; −0.42), 2013 (0.23; −0.49), 2015 (0.17; −0.52), 2016 (0.12; −0.61), 2017 (0.16; −0.65), 2018 (0.12; −0.73). Thus, we report correlations based on the raw subjective income data.

The GDP per capita, the top 10% share, and the bottom 50% share of the national income data came from https://wid.world/ .

Supplementary Material

Pgac224_supplemental_file, acknowledgements.

We would like to thank the following individuals for invaluable comments: Jana Berkessel, Margaux Wienk, Ana Di Giovanni, and Megan Goldring. We would like to thank Marina Albuquerque, Radhika Kothari, Charlotte Phillips, Arsen Seitov, Shreya Iyer, and Ricky Patterson for editing this paper.

Competing Interest: The authors declare no competing interests.

Contributor Information

Shigehiro Oishi, Department of Psychology, University of Chicago, Chicago, IL 60637, USA.

Youngjae Cha, Department of Psychology, University of Virginia, Charlottesville, VA 22904-4132, USA.

Asuka Komiya, Graduate School of Integrated Arts and Sciences, Hiroshima University, Hiroshima 739-8511, Japan.

Hiroshi Ono, School of International Corporate Strategy, Hitotsubashi University Business School, Tokyo 101-8439, Japan.

Ethics Approval Statement

All data analyzed were secondary data. Data analyses were approved by the University of Virginia IRB (Title: Good Life Study; Protocol Number: 3950).

Authors' Contributions

S.O came up with the research questions, and Y.C., A.K., and H.O. obtained the datasets. Y.C. conducted preliminary analyses, and S.O. and Y.C. conducted analyses reported here. S.O. wrote a draft, Y.C., A.K., and H.C. revised it.

Data Availability

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The essence of happiness.

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Money can buy materialistic things, but it cannot buy happiness. Happiness comes from love, peace, and satisfaction, which are not for sale. Even the richest person can be unhappy if he lacks love and peace.

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250 Words Essay on Happiness Is More Important Than Money

The illusion of wealth.

Money, often dubbed the key to happiness, is a deeply ingrained part of our societal consciousness. However, it is not the ultimate solution to our quest for contentment. The illusion of wealth as a synonym for happiness is a misconception that fails to consider the complexity of human emotions.

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500 Words Essay on Happiness Is More Important Than Money

Introduction: the value of happiness.

Happiness, an emotional state that is often sought after, is a complex and multifaceted concept. Unlike money, a tangible and quantifiable commodity, happiness is subjective and varies from person to person. Despite the material comforts that money can provide, it is the contention of this essay that happiness holds greater importance.

Happiness and Subjective Well-being

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Research in the field of economics and psychology illustrates the concept of diminishing marginal utility of wealth. This means that beyond a certain income level necessary for meeting basic needs and financial security, additional wealth contributes very little to overall happiness. A study by Kahneman and Deaton (2010) found that emotional well-being rises with income up to about $75,000 per year, but there is no further progress beyond that. This suggests that the pursuit of wealth beyond a certain point does not contribute to increased happiness.

Money vs. Experiential Wealth

While money can buy material possessions, it cannot buy experiences, relationships, or time – factors that significantly contribute to happiness. The value of shared experiences, personal growth, and meaningful relationships far outweighs the temporary satisfaction derived from material possessions. Moreover, the pursuit of money often comes at the expense of time, which could otherwise be spent on enriching experiences and relationships.

The Role of Happiness in Health and Longevity

Happiness has been linked to numerous health benefits, including a stronger immune system, reduced risk of chronic diseases, and increased longevity. In contrast, the pursuit of wealth can often lead to stress and work-related health issues. These findings suggest that prioritizing happiness over wealth can lead to a healthier, longer life.

Conclusion: The Superiority of Happiness

In conclusion, while money is a necessary tool for survival and comfort, it is not a definitive path to happiness. The importance of happiness lies in its ability to enrich our lives beyond material wealth, contributing to better health, meaningful relationships, and a sense of purpose. As such, it is essential to strike a balance between the pursuit of wealth and the pursuit of happiness, with the latter taking precedence. After all, happiness is not just an end in itself, but also a means to a fulfilling and meaningful life.

That’s it! I hope the essay helped you.

If you’re looking for more, here are essays on other interesting topics:

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Ielts exam preparation for a higher band score., ielts essay: money is an important source of happiness.

IELTS Essay Topic:

Some people like to save money because they consider it is an important source of happiness. Others believe that money should be spent as it is the way to fulfill our dreams.

Discuss both the views and give your opinion.

Give reasons for your answer and include any relevant examples from your own knowledge or experience.

Sample Answer: Money is an important factor to achieve happiness. Different people use money in different ways. There has been a considerable debate on the issue whether we should save money or spend all on our needs.

On one hand, it is believed that money should be spent on things and on our needs, because it is a major source of getting happiness in life, if we do not have money, we cannot survive in this modern world anymore. So, it is rightly said that life is like an ice-cream, so we should enjoy it before it melts. In other words, we should take benefits from each and every moment of the life. For instance, with the help of money people can easily uplift their status in the society, because every individual wants to develop his or her living standard, which in turn helps them to raise their personality in the world.

On the other hand, it is considered that, people should save money in order to secure their future. Mostly people save money for their children, because the savings will help them in their further life for their better education and basic needs, which are necessary and play a significant role in one’s life. Money is a valuable thing, because nowadays without money, it is very difficult to stand in the society. So that is why people should save money for the rainy days, because everyone goes through the ups and downs in life and who knows when we need some extra savings.

In conclusion, both aspects have their own values and that is why we should spend money within a limit- for important and basic needs, because if we spend all the money we earn, there will be no money for the better future.

[Written by – Arman Josan]

2 thoughts on “ IELTS Essay: Money is an important source of happiness ”

This short essay deeply inspired me showing me how to deal with money.

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