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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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A business journal from the Wharton School of the University of Pennsylvania

Does Money Buy Happiness? Here’s What the Research Says

March 28, 2023 • 5 min read.

Reconciling previously contradictory results, researchers from Wharton and Princeton find a steady association between larger incomes and greater happiness for most people but a rise and plateau for an unhappy minority.

• Finance & Accounting

The following article was originally published on Penn Today .

Does money buy happiness? Though it seems like a straightforward question, research had previously returned contradictory findings, leaving uncertainty about its answer.

Foundational work published in 2010 from Princeton University’s  Daniel Kahneman  and Angus Deaton had found that day-to-day happiness rose as annual income increased, but above $75,000 it leveled off and happiness plateaued. In contrast, work published in 2021 from the University of Pennsylvania’s  Matthew Killingsworth  found that happiness rose steadily with income well beyond $75,000, without evidence of a plateau.

To reconcile the differences, Kahneman and Killingsworth paired up in what’s known as an adversarial collaboration, joining forces with Penn Integrates Knowledge  University Professor  Barbara Mellers  as arbiter. In a new  Proceedings of the National Academy of Sciences  paper , the trio shows that, on average, larger incomes are associated with ever-increasing levels of happiness. Zoom in, however, and the relationship becomes more complex, revealing that within that overall trend, an unhappy cohort in each income group shows a sharp rise in happiness up to $100,000 annually and then plateaus.

“In the simplest terms, this suggests that for most people larger incomes are associated with greater happiness,” says Killingsworth, a senior fellow at Wharton and lead paper author. “The exception is people who are financially well-off but unhappy. For instance, if you’re rich and miserable, more money won’t help. For everyone else, more money was associated with higher happiness to somewhat varying degrees.”

Mellers digs into this last notion, noting that emotional well-being and income aren’t connected by a single relationship. “The function differs for people with different levels of emotional well-being,” she says. Specifically, for the least happy group, happiness rises with income until $100,000, then shows no further increase as income grows. For those in the middle range of emotional well-being, happiness increases linearly with income, and for the happiest group the association actually accelerates above $100,000.

Joining Forces to Ask: “Does Money Buy Happiness?”

The researchers began this combined effort recognizing that their previous work had drawn different conclusions. Kahneman’s 2010 study showed a flattening pattern where Killingsworth’s 2021 study did not. As its name suggests, an adversarial collaboration of this type — a notion originated by Kahneman — aims to solve scientific disputes or disagreements by bringing together the differing parties, along with a third-party mediator.

Killingsworth, Kahneman, and Mellers focused on a new hypothesis that both a happy majority and an unhappy minority exist. For the former, they surmised, happiness keeps rising as more money comes in; the latter’s happiness improves as income rises but only up to a certain income threshold, after which it progresses no further.

To test this new hypothesis, they looked for the flattening pattern in data from Killingworth’s study, which he had collected through an app he created called Track Your Happiness. Several times a day, the app pings participants at random moments, asking a variety of questions including how they feel on a scale from “very good” to “very bad.” Taking an average of the person’s happiness and income, Killingsworth draws conclusions about how the two variables are linked.

A breakthrough in the new partnership came early on when the researchers realized that the 2010 data, which had revealed the happiness plateau, had actually been measuring unhappiness in particular rather than happiness in general.

“It’s easiest to understand with an example,” Killingsworth says. Imagine a cognitive test for dementia that most healthy people pass easily. While such a test could detect the presence and severity of cognitive dysfunction, it wouldn’t reveal much about general intelligence since most healthy people would receive the same perfect score.

“In the same way, the 2010 data showing a plateau in happiness had mostly perfect scores, so it tells us about the trend in the unhappy end of the happiness distribution, rather than the trend of happiness in general. Once you recognize that, the two seemingly contradictory findings aren’t necessarily incompatible,” Killingsworth says. “And what we found bore out that possibility in an incredibly beautiful way. When we looked at the happiness trend for unhappy people in the 2021 data, we found exactly the same pattern as was found in 2010; happiness rises relatively steeply with income and then plateaus.”

“The two findings that seemed utterly contradictory actually result from data that are amazingly consistent,” he says.

Does It Matter Whether Money Can Buy Happiness?

Drawing these conclusions would have been challenging had the two research teams not come together, says Mellers, who suggests there’s no better way than adversarial collaborations to resolve scientific conflict.

“This kind of collaboration requires far greater self-discipline and precision in thought than the standard procedure,” she says. “Collaborating with an adversary — or even a non-adversary — is not easy, but both parties are likelier to recognize the limits of their claims.” Indeed, that’s what happened, leading to a better understanding of the relationship between money and happiness.

And these findings have real-world implications, according to Killingsworth. For one, they could inform thinking about tax rates or how to compensate employees. And, of course, they matter to individuals as they navigate career choices or weigh a larger income against other priorities in life, Killingsworth says.

However, he adds that for emotional well-being money isn’t the be all end all. “Money is just one of the many determinants of happiness,” he says. “Money is not the secret to happiness, but it can probably help a bit.”

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• Front Psychol

Money Does Not Always Buy Happiness, but Are Richer People Less Happy in Their Daily Lives? It Depends on How You Analyze Income

Laura kudrna.

1 Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom

Kostadin Kushlev

2 Department of Psychology, Georgetown University, Washington, DC, United States

Associated Data

Publicly available datasets were analyzed in this study. These data can be found at: https://www.atusdata.org (The ATUS extract builder was used to create the ATUS dataset, see Hofferth et al., 2017 ). GSOEP data were requested from https://www.diw.de/en/diw_02.c.222516.en/data.html , see Richter and Schupp, 2015 .

Do people who have more money feel happier during their daily activities? Some prior research has found no relationship between income and daily happiness when treating income as a continuous variable in OLS regressions, although results differ between studies. We re-analyzed existing data from the United States and Germany, treating household income as a categorical variable and using lowess and spline regressions to explore nonlinearities. Our analyses reveal that these methodological decisions change the results and conclusions about the relationship between income and happiness. In American and German diary data from 2010 to 2015, results for the continuous treatment of income showed a null relationship with happiness, whereas the categorization of income showed that some of those with higher incomes reported feeling less happy than some of those with lower incomes. Lowess and spline regressions suggested null results overall, and there was no evidence of a relationship between income and happiness in Experience Sampling Methodology (ESM) data. Not all analytic approaches generate the same results, which may contribute to explaining discrepant results in existing studies about the correlates of happiness. Future research should be explicit about their approaches to measuring and analyzing income when studying its relationship with subjective well-being, ideally testing different approaches, and making conclusions based on the pattern of results across approaches.

Introduction

Does having more money make someone feel happier? The answer to this longstanding question has implications for how individuals live their lives and societies are structured. It is often assumed that more income brings more happiness (with happiness broadly defined herein as hedonic feelings, while recognizing closely related constructs, including satisfaction and eudaimonia; Tiberius, 2006 ; Angner, 2010 ; Dolan and Kudrna, 2016 ; Sunstein, 2021 ). In many aspects of policy, upward income mobility is encouraged, and poverty can result in exclusion, stigmatization, and discrimination by institutions and members of the public. More income provides people with opportunities and, sometimes, capabilities to consume more and thus satisfy more of their preferences, meet their desires and obtain more of what they want and need ( Harsanyi, 1997 ; Sen, 1999 ; Nussbaum, 2008 ). These are all reasons to assume that higher income will bring greater happiness—or, at least, that low income will bring low happiness.

Some research challenges the assumption that earning more should lead to greater happiness. First, because people expect that more money should make them happier, people may feel less happy when their high expectations are not met ( Graham and Pettinato, 2002 ; Nickerson et al., 2003 ) and they may adapt more quickly to more income than they expect ( Aknin et al., 2009 ; Di Tella et al., 2010 ). Second, since the 1980s in many developed countries, the well-educated have had less leisure time than those who are not ( Aguiar and Hurst, 2007 ) and people living in high-earning and well-educated households report feeling more time stress and dissatisfaction with their leisure time ( Hamermesh and Lee, 2007 ; Nikolaev, 2018 ). The quantity of leisure time is not linearly related to happiness, with both too much and too little having a negative association ( Sharif et al., 2021 ). Evidence also shows that people with higher incomes spend more time alone ( Bianchi and Vohs, 2016 ). The lower quality and quantity of leisure and social time of people with higher incomes may, in turn, negatively impact their happiness, especially given there are strong links between social capital or “relational goods” and well-being ( Helliwell and Putnam, 2004 ; Becchetti et al., 2008 ).

At the same time, some—but not all—evidence suggests that working class individuals tend to be more generous and empathetic than more affluent individuals ( Kraus et al., 2010 ; Piff et al., 2010 ; Balakrishnan et al., 2017 ; Macchia and Whillans, 2022 ), and such kindness toward others has been associated with higher well-being ( Dunn et al., 2008 ; Aknin et al., 2012 ). Relatedly, psychological research suggests that people with lower socioeconomic status have a more interdependent sense of self ( Snibbe and Markus, 2005 ; Stephens et al., 2007 ). It is, therefore, possible that people high in income have lower well-being because they experience less of the internal “warm glow” ( Andreoni, 1990 ) benefit that comes along with valuing social relationships and group membership. In theory, therefore, there are reasons to suppose that high income has both benefits and costs for well-being, and empirical evidence can inform the debate about when and whether these different perspectives are supported.

Empirical Evidence on Income and Happiness

The standard finding in existing literature is that higher income predicts greater happiness, but with a declining marginal utility ( Dolan et al., 2008 ; Layard et al., 2008 ): that is, higher income is most closely associated with happiness among those with the least income and is least closely associated with happiness for those with the most income. Recently, this finding has been qualified by studies showing that the relationship between income and happiness depends on how happiness is conceptualized and measured: as an overall evaluation of one’s life or as daily emotional states ( Kahneman and Deaton, 2010 ; Killingsworth, 2021 ). In this vein, authors Kushlev et al. (2015) found no relationship between income and daily happiness in the American Time Use Survey (ATUS), which has recently been found for other happiness measures, too ( Casinillo et al., 2020 , 2021 ) The finding from Kushlev et al. (2015) was replicated in the German Socioeconomic Panel Survey (GSEOP) by Hudson et al. (2016) , and in another analysis of the ATUS by Stone et al. (2018) .

Some research has focused specifically on the effect of high income on happiness. Kahneman and Deaton (2010) conducted regression analyses using a Gallup sample of United States residents, finding that annual income beyond ~$75K was not associated with any higher daily emotional well-being. Income beyond ~$75K, however, predicted better life evaluations. Using a self-selecting sample of experiential data in the United States, Killingsworth (2021) conducted piecewise regressions and found no evidence of satiation or turning points. Jebb et al. (2018) fit regression spline models to global Gallup data, showing that the satiation point in daily experiences found by Kahneman and Deaton (2010) was also apparent in other countries. Unlike Kahneman and Deaton (2010) , however, Jebb et al. (2018) also found evidence of satiation in people’s life evaluations, and even some evidence for “turning points”—whereby richer people evaluated their lives as worse than some of those with lower incomes. A satiation point in life evaluations was also found in European countries at around €28K annually ( Muresan et al., 2020 ).

This pattern of findings could partly depend on the choice of analytic strategy. In analyses of the same dataset as Jebb et al. (2018) but using lowess regression, researchers found no evidence of satiation or turning points in the relationship between income and people’s life evaluations ( Sacks et al., 2012 ; Stevenson and Wolfers, 2012 ). These conflicting results suggest that the effect of analytic strategy on results deserves a closer examination.

The Research Gap

While there has been much research on income and happiness, including according to how happiness is defined and measured, we are not away of any studies that have compared the relationship between income and happiness according to how income is defined and measured. We propose that the relationship between income and happiness may depend not only on how happiness is measured, but also on how income is measured and analyzed. To improve our knowledge of the relationship between income and happiness, this paper, we focus on nonlinearities in the relationship between income and happiness and re-analyze the ATUS data used by Kushlev et al. (2015) and Stone et al. (2018) , as well as the GSOEP data used by Hudson et al. (2016) . Specifically, while Kushlev et al. (2015) analyzed income as a continuous variable in the ATUS, we treat income the way it was measured: as a categorical variable. We compare these results to GSOEP data where we re-code the original continuous measure of income into categorical quantiles. To further explore nonlinearities in the relationship between income and happiness, we also conduct local linear “lowess” and spline regression analyses.

We chose to re-analyze these data to address the question of differences in the relationship between income and happiness according to the measurement and analysis of income because the ATUS and GSOEP provide nationally representative data on people’s feelings as experienced during specific “episodes” of the day after asking them to reconstruct what they did during the entire day. Thus, compared to data from Gallup, which measures affect “yesterday,” measurements in the ATUS are more grounded in specific experiences, and therefore, less subject to recall bias ( Kahneman et al., 2004 ). And unlike Gallup, which uses more crude, dichotomous (“yes-no”) response scales, ATUS measures happiness along a standard seven-point Likert-type scale. In the GSOEP, we were also able to analyze data from the Experience Sampling Methodology (ESM), which asks people how they are feeling during specific episodes during the day and, as such, is even more grounded in specific experiences.

Measuring and Analyzing Income

The original ATUS income variable—family income—contains 16 uneven categories (see Table 1 ). For example, Category 11 has a range of ~$10K, whereas Category 14 has a range of ~$25K. The increasingly larger categories are designed to reflect declining marginal utility as an innate quality of income. Based on this, Kushlev et al. (2015) analyzed income as a continuous variable using the original uneven categories. Continuous scales, however, assume equal intervals between scale points—a strong assumption to make for the relatively arbitrary rate of change in the category ranges. Is increasing one’s income from $20,000 to $25,000 really equidistant to increasing it from $35,000 to $40,000 ( Table 1 )? And can we really assume, for example, that adding $5,000 of additional income to $35,000 is the same as adding $10,000 of additional income to $40,000? Recognizing this issue, income researchers have adopted alternative strategies. For example, Stone et al. (2018) took the midpoints of each category of income, and then log-transformed it. Thus, they transformed the categorical measure of income into a continuous measure. This approach produced results for happiness consistent with the findings of Kushlev et al. (2015) .

The original categories of income in the ATUS family income measure with number of individuals in each income category in the ATUS 2010, 2012, and 2013 well-being modules.

Complete cases only for all variables analyzed.

Both the increasing ranges of the income scale itself and its log-transformations reflect an assumed declining marginal utility of income: They treat a given amount of income increase at the higher end of the income distribution as having less utility than the same amount at the lower end of the distribution. But by subsuming income’s declining utility in its very measurement (or transformation thereof), it becomes difficult to interpret a null relationship with happiness. In other words, we might not be seeing a declining marginal utility of income reflected on happiness because the income variable itself reflects its declining utility.

Even when the income variable itself does not reflect its declining utility, a null relationship between income and daily experiences of happiness has been observed. Hudson et al. (2016) used GSOEP, which contains a measure of income that is continuous in its original form. Whether analyzing this income measure in its raw original form or in transformed log and quadratic forms, a null relationship with happiness was observed. This approach, however, does not consider whether there might be nonlinear/log/quadratic turning or satiation points at higher levels of income—an issue also applicable to previous analyses of ATUS ( Kushlev et al., 2015 ; Stone et al., 2018 ). This is important because there are theoretically both benefits and costs to achieving higher levels of income that could occur at various levels of income; however, this possibility has not yet been fully explored in ATUS or GSOEP data.

In sum, past research using ATUS has treated categorically measured income as a continuous variable, either assuming equidistance between scale points or attempting to create equidistance through statistical transformations. By doing so, however, researchers may have statistically accounted for the very utility of income for happiness that they are trying to test. In both ATUS and GSOEP, the question of whether there might be satiation and/or turning points at higher levels of income has not been fully considered. The present research explores whether treating income as a categorical variable in both ATUS and GSOEP would replicate past findings or reveal novel insights, focusing on possible nonlinearities in the relationship between income and happiness.

Materials and Methods

We used data from ATUS well-being modules in 2010, 2012, and 2013. To facilitate future replications of this research, the ATUS extract builder was used to create the dataset ( Hofferth et al., 2017 ). 1 The ATUS is a repeated cross-sectional survey and is nationally representative of United States household residents aged 15 years and older. Its sampling frame is the Current Population Survey (CPS), which was conducted 2–5 months prior to the ATUS. Some items in the ATUS come from the CPS, including the household income item that we analyze.

Data from the GSOEP come from the Innovation Sample (IS), which is a subsample of the larger main GSOEP ( Richter and Schupp, 2015 ). The main GSOEP and the IS are designed to be nationally representative. The IS contains information on household residents aged 17 years of age and older. We used two modules from these data: the 2012–2015 DRM module, which is a longitudinal survey, and the 2014–2015 ESM module.

Outcome Measures

In ATUS, participants were called on the phone and asked how they spent their time yesterday: what activities they were doing, for how long, who they spent time with and where they were located. This information was used to create their time use diary. A random selection of three activities were taken from these diaries and participants were asked how they felt during them. The feelings items were tired, sad, stressed, pain, and happy. Participants were also asked how meaningful what they were doing felt.

In GSOEP, participants were interviewed face to face for the DRM questions and through smartphones for the ESM questions. In the DRM, as in the ATUS, they were asked how they spent their time yesterday and, for a random selection of three activities, they were asked further details about how they felt. In the ESM, participants were randomly notified on mobile phones at seven random points during the day for around 1 week. As in the DRM, they were asked how they were spending their time at the point of notification, as well as how they felt. Participants in both ESM and DRM samples were asked about whether they were feeling happy, as well as other emotions such as sadness, stress, and boredom.

The focus of this research is on the happiness items from both the ATUS and GSOEP to highlight differences according to the treatment of the independent measure of income rather than differences according to the dependent outcome of emotional well-being.

Data were analyzed in STATA 15 and jamovi. The Supplementary Material S1 file contains the STATA command file for the main commands written to analyze the data. In both ATUS and GSOEP, OLS regressions were conducted with happiness as the outcome measure and income as the explanatory measure. Following Kushlev et al. (2015) and Hudson et al. (2016) , the average happiness across all activities each day was taken to create an individual-level measure. Because the GSOEP DRM sample contained multiple observations across years, the SEs were clustered at the individual level for models using this dataset.

The treatment of income differed according to the dataset because income was collected differently in each dataset. In the ATUS, income was first analyzed in continuous, log, and quadratic forms in OLS regressions, as in other research ( Kushlev et al., 2015 ; Hudson et al., 2016 ). Next, it was analyzed as a categorical variable with 16 categories, preserving the identical format that it was originally collected in from the CPS questionnaire.

In GSOEP, the income variable in the dataset is provided in continuous form because participants reported their monthly income as an integer. To compare to the ATUS results, 16 quantiles of income were created and analyzed in GSOEP DRMs (see Table 2 - note that there were insufficient observations to conduct these analyses with GSOEP ESMs). This income variable was also analyzed in continuous, log, and quadratic forms.

The range and number of person-year observations of the GSOEP Income 4 variable divided into 16 quantiles.

Omnibus F -tests and effect sizes ( n 2 ) are also reported to compare the categorical, continuous, log, and quadratic approaches.

We conducted lowess and spline regressions to further investigate possible nonlinearities in the relationship between income and happiness. For the lowess regressions, the smoothing parameter was set at of 0.08. For the regression splines, we fitted knots at four quartiles and five quantiles of income. We also used the results of OLS regressions treating income as a categorical variable, as well as the results of the lowess regression treating income as continuous, to fit knots at pre-specified values of income (where these analyses suggested there could be turning and/or satiation points).

Complete case analyses were conducted with 33,976 individuals in ATUS, 6,766 individuals in German DRMs, and 249 individuals in German ESMs. There was item-missing data in some samples (ATUS, 1.7% missing; GSOEP DRMs, 8.2% missing; GSOEP ESMs data, and 6.0% missing). We make analytical and not population inferences and therefore do not use survey weights ( Pfeffermann, 1996 ).

Results are presented without and with controls for demographic and diary characteristics. Following Kushlev et al. (2015) , Hudson et al. (2016) , and Stone et al. (2018) , these controls were age, gender, marital status, ethnic background, 2 health, 3 employment status, children, 4 and whether the day was a weekend. We also control for the year of the survey in ATUS DRM data to address the issue that our results are not due to new data but rather how we treat the income variable.

The list of variables we use in analyses are in Table 3 .

List of variables used in analyses in ATUS and GSOEP.

In both ATUS and GSOEP, daily happiness was analyzed using a 0–6 scale (in GSOEP scale points 1–7 were recoded to 0–6 to match ATUS). The ATUS mean happiness was 4.38 (SD = 1.33). The GSOEP DRM mean happiness was 2.91 (SD = 1.46), and the GSOEP ESM mean happiness was 2.65 (SD = 1.03).

The magnitude of our results can be considered in the context of effect sizes from other research on demographic characteristics and daily happiness ( Kahneman et al., 2004 ; Stone et al., 2010 ; Luhmann et al., 2012 ; Hudson et al., 2019 ). For example, the effect size for the relationship between age and daily experiences of happiness was 0.16 in Stone et al. (2010) . Our effect sizes range from 0.06 to 0.37. Throughout, we focus on coefficients, their 95% CIs, and visualizations of these coefficients and CIs, rather than on their statistical significance ( Lakens, 2021 ). The purpose of this is to highlight how analytic treatments of income affect the magnitude and precision of the relationship between income and happiness.

When treating the 16-category family income variable as continuous in OLS regressions, there was no substantive relationship between income and happiness as in other prior research ( Kushlev et al., 2015 ; Hudson et al., 2016 ; Stone et al., 2018 ). Out of the linear, squared, and log coefficients without and with controls, the largest and most precise coefficients were with controls; for linear income it was ( b  = −0.006, 95% CI = −0.01, −0.002), squared income ( b  = −0.0001, 95% CI = 0.0003, 0.00006), and log income ( b  = −0.03, 95% CI = −0.05, 0.001). The omnibus F -test (without controls) for linear income was F  = 0.28, n 2  = 0.000008 (95% CI = 0.00, 0.0002), for income squared was F  = 1.60, n 2  = 0.00005 (95% CI = 0.00, 0.0003), and for log income was F  = 0.23, n 2  = 0.000006 (95% CI = 0.00,0.0002).

The categorization of income focused attention on those with incomes of $35–40K, who appeared substantively happier than some of those with higher incomes (and lower incomes; see Figure 1 ). For example, with controls, those with incomes of $35–40K appeared happier relative to those with incomes of $150K+ ( b  = 0.16, 95% CI: 0.08, 0.24) and $100–150K ( b  = 0.14, 95% CI: 0.07, 0.221). The omnibus test for categorical income was F  = 1.61, n 2  = 0.007 (95% CI = 0.00, 0.0009).

Predicted values of average individual happiness in the American Time Use Survey (ATUS) at the 16 values of the family income variable without and with controls. Covariates at means. 95% CI.

Results from regression splines and a lowess regression suggested null results overall (see Figure 2 ). Further details of the analyses are in Supplementary Material S2 .

Line graph of predicted values from lowess regressions explaining variance in happiness from income treated as a continuous variable in ATUS.

When treating the continuous household income variable as continuous (in €10,000s) in OLS regressions, there was no substantive relationship between income and happiness as in other prior research ( Kushlev et al., 2015 ; Hudson et al., 2016 ; Stone et al., 2018 ). The association with the largest magnitude and most precision was for log income with controls ( b  = −0.08, 95% CI = −0.18, 0.01). 5

As in ATUS, treating the variable as categorical suggested some relationships between income and happiness. These results drew attention to those third quantile (~€14–18K), who seemed happier than those both higher and lower in income (see Figure 3 ). For example, with controls, they were happier than those in quantiles 13 (€42.6–48K, b  = 0.46, 95% CI = 0.25, 0.67), seven (~€24–27K, b  = 0.34, 95% CI = 0.13, 0.56), and one (€2.40–11,520K, b  = 0.28, 95% CI = 0.05, 0.51). The omnibus test for categorical income was F  = 4.00, n 2  = 0.009 (95% CI = 0.003, 0.01), whereas the omnibus test for linear income was F  = 0.09, n 2  = 0.00001 (95% CI = 0.00, 0.0007). The omnibus for log income was F  = 1.42, n 2  = 0.0002 (95% CI = 0.00, 0.0001) and for income squared it was F  = 0.96, n 2  = 0.0001 (95% CI = 0.00, 0.001).

Predicted values of average person-year happiness from GSOEP DRMs at 16 quantiles of income (Income 4) without and with controls. Covariates at means. 95% CI.

The lowess and spline regressions suggested null results overall, as the coefficients were small in magnitude (see Figure 4 ). Further details of the analyses are in Supplementary Material S3 .

Line graph of predicted values from lowess regressions explaining variance in happiness from income treated as a continuous variable in GSOEP DRMs at 16 quantiles of income.

There was no evidence to suggest any substantive association between income and happiness in ESM data for linear income, income squared, log income, in the lowess regressions, or regression splines. A visualization of the lowess results are in Figure 5 and further details of the analyses are in Supplementary Material S4 .

Results of local linear “lowess” regression from GSOEP Experience Sampling Methodology (ESM) data with happiness as the outcome and continuous annual income as the explanatory variable.

The omnibus F -test for linear income was F  = 0.53, n 2  = 0.002 (95%CI = −0.00, 0.03), and for log income it was F  = 0.12, n 2  = 0.0005, 95%CI = 0.00, 0.02. For income squared it was F  = 0.63, n 2  = 0.003, 95%CI = 0.00 0.03.

Is income creating a signal in these data on daily experiences of happiness, or is it all simply noise? The present results suggest that whether income can be concluded as being associated with daily experiences of happiness may depend on how income is analyzed. When income in ATUS is analyzed in its original, categorical form, there is some evidence that some people with higher incomes feel somewhat less happy than some of those with lower incomes. When the continuous income variable in GSOEP is split into categories, a similar pattern is observed. This is not inconsistent with the findings of Kushlev et al. (2015) , Hudson et al. (2016) , and Stone et al. (2018) , who found no relationship between income and daily feelings of happiness in the same data when income was analyzed as a continuous variable. It simply illustrates that a relationship between income and happiness could be interpreted when treating income categorically rather than continuously.

There are at least three possible interpretations to our overall results. One interpretation tends toward conservative. We conducted multiple comparisons of many transformations of income, which might inspire some to question whether we should have accounted for this in some way by adjusting for multiple comparisons. Although we found some evidence of differences in happiness according to income, such an adjustment might lead to an overall null conclusion when characterizing the relationship between income on happiness. A second interpretation is more generous. Within this perspective, one might emphasize the fact that because our income measures were correlated, no correction for multiple comparisons was required. It could then be argued that because we found some evidence for the relationship between income on happiness, there is good evidence that the overall effect is not null. A more moderate perspective, and the one adopted in this paper, is that because the overall pattern of our results showed mixed null and nonnull results, we can make an overall conclusion of some differences in happiness according to income. We also noticed that equivalizing income in the German data strengthened the relationship of income and happiness, further supporting the conclusion of some differences—and that the analytic treatment of income matters.

Based on the moderate perspective, we conclude that there is very little evidence of any relationship between income and daily experiences of happiness—and any relationship that does exist would suggest higher income could be associated with less happiness. The results do not support the results of Sacks et al. (2012) or Killingsworth (2021) , where a greater income was associated with greater happiness, and there were no satiation or turning points (see also Stevenson and Wolfers, 2012 ). These results are more aligned with Kahneman and Deaton (2010) , who found a satiation point in the relationship between income daily experiences of happiness, researchers finding no association between income and happiness ( Kushlev et al., 2015 ; Jebb et al., 2018 ; Casinillo et al., 2020 , 2021 ), who found that higher income can be associated with worse evaluations of life. We suggest the analytic strategy for income could contribute to explaining discrepant results in existing literature, and researchers should be clear about the approaches they have tested, although we acknowledge that sampling differences could play a role, too.

Overall, the results were broadly consistent between countries because there was no substantive relationship between income and happiness when income was treated continuously but there appeared to be relationships when treating income categorically. Despite a similar overall pattern in the income results, there were other difference between countries. German residents rated their happiness as lower than United States residents (a difference of ~1.5 scale points out of seven). This could be because of different interpretations of the word “happiness” in Germany and the United States. The word for happiness in German used in the survey— glück —can mean something more akin to lucky or optimistic—which is different from the meaning of word “happy” in the United States. Despite this linguistic difference, those with higher incomes were still less happy than some of those with lower incomes in both samples.

Limitations

One limitation to our results is the representativeness of the income distribution. Household surveys like those that we used do not tend to capture the “tails” of the income distribution very well: People in institutions and without addresses are excluded from these sample populations, which omits populations such as those living in nursing homes and prisons, as well as the homeless. Moreover, people do not always self-report their income accurately due to issues such as social desirability bias ( Angel et al., 2019 ). Existing studies that have focused on those with very low incomes do tend to find that low income is associated with low happiness ( Diener and Biswas-Diener, 2002 ; Clark et al., 2016 ; Adesanya et al., 2017 ). In ATUS, the highest household income value available was $150K, whereas in GSOEP it was €360K. Thus, it is not always clear whether the very affluent, such as millionaires, are represented in these samples ( Smeets et al., 2020 ). Overall, our results cannot be taken as representative of people who are very poor or rich and should not be interpreted as such.

Another limitation is that the present results cannot be interpreted casually because there has been no manipulation of income in these data nor exploration of mechanisms and there was no longitudinal data in ATUS. As discussed by Kushlev et al. (2015) , there are issues such as reverse causality. Here, however, some of our results potentially suggest an alternative reverse causality pathway, whereby less happy people may select into earning more income. Because the counterfactual is not apparent—we do not know how happy people with high incomes would be without their higher income—it could also be that those with high incomes would be even less happy than they currently are if they had not attained their current level of income. In other words, people with high incomes may have started out as less happy in the first place and be even less happy if they did not have high incomes.

A further limitation is the time period of the data, especially that they were collected prior to the COVID-19 pandemic. This could be an issue because it is possible that the relationship between income and daily experiences of happiness has changed, such as due to the exacerbation of health inequalities and restrictions on freedom of movement due to nationwide lockdowns. Our study does not provide any information on the longer-term and health and well-being consequences of both COVID-19 itself and the policy response to COVID-19 ( Aknin et al., 2022 ). As one example, access to green space, which has health and well-being benefits, is lower among those with low income, and this mechanism between income and happiness may have become more salient during COVID-19 ( Geary et al., 2021 ). Overall, it is important to consider the regional, political, and socioeconomic contexts in which income is attained to understand its relationship with well-being, including levels of income in reference groups such as neighbors, friends, and colleagues ( Luttmer, 2005 ; De Neve and Sachs, 2020 ). It would be important to replicate the results in this research with more recent data to address the limitation that the data we used are not recent, considering our broader point that the measurement and analysis of income should be considered as carefully as the measurement and analysis of happiness.

Future Directions

This research points to several directions for future research. One direction relates to data and measures: Nonlinearities in the relationship between income and happiness could be examined using time use data from other countries, considered between countries and/or within countries over time ( Deaton et al., 2008 ; De Neve et al., 2018 ), and investigated for measures of emotional states other than happiness ( Piff and Moskowitz, 2018 ). In general, our results suggest that researchers should pay attention to how income is measured and analyzed when considering how it is related to happiness, which complements findings from other research that the way happiness is measured and analyzed is important ( Kahneman and Deaton, 2010 ; Jebb et al., 2018 ).

Future research could also explore mechanisms that may explain our findings. In addition to those mentioned in the Introduction—expectations ( Graham and Pettinato, 2002 ; Nickerson et al., 2003 ), time use ( Aguiar and Hurst, 2007 ; Hamermesh and Lee, 2007 ; Bianchi and Vohs, 2016 ; Nikolaev, 2018 ; Sharif et al., 2021 ); generosity ( Dunn et al., 2008 ; Kraus et al., 2010 ; Piff et al., 2010 ; Aknin et al., 2012 ; Balakrishnan et al., 2017 ; Macchia and Whillans, 2022 ), and sense of self ( Snibbe and Markus, 2005 ; Stephens et al., 2007 )—another is the identity-related effect of transitioning between socioeconomic groups. Though one might expect upward mobility to be associated with greater happiness, research suggests that some working class people do not wish to become upwardly mobile because it could lead to a loss of identity and change in community ( Akerlof, 1997 ; Friedman, 2014 ). Indeed, upward intergenerational mobility is associated with worse life evaluations in the United Kingdom—though not in Switzerland ( Hadjar and Samuel, 2015 ), although recent findings show substantial negative effects of downward mobility, too ( Dolan and Lordan, 2021 ). Over time, therefore, the degree of mobility in a population could influence the relationship between income and happiness in both positive and negative directions.

Additionally, social comparisons could drive the effects of higher income on happiness. Higher income might not benefit happiness if one’s reference group—that is, the people to whom we compare or have knowledge of in some form ( Hyman, 1942 ; Shibutani, 1955 ; Runciman, 1966 )—changes with higher socioeconomic status. As income increases, people might compare themselves to others who are also doing similarly or better to them, and then not feel or think that they are doing any better by comparison—or even feel worse ( Cheung and Lucas, 2016 ). This is one of the explanations for the well-known “Easterlin Paradox” ( Easterlin, 1974 ), which suggests that as national income rises people do not become happier because they compare their achievements to others. The paradox is debated ( Sacks et al., 2012 ). Additionally, some research shows that it is possible to view others’ greater success as one’s own future opportunity and for upward social comparisons to then positively impact upon well-being ( Senik, 2004 ; Davis and Wu, 2014 ; Ifcher et al., 2018 ). As with the role of mobility in the relationship between income and happiness, it is unclear whether the role of social comparisons would create a positive or negative impact over time and future research could explore this.

Final Remarks

Overall, our results provide some evidence that individual attainment in terms of income may not equate to the attainment of individual happiness—and could even be associated with less daily happiness, depending upon how income is measured and analyzed. These results suggest that how income is associated with happiness depends on how income is measured and analyzed. They provide some support to the idea that financial achievement can have both costs and benefits, potentially informing normative discussions about the optimal distribution of income in society.

Data Availability Statement

Ethics statement.

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the participants’ legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.

Author Contributions

LK and KK contributed to conception and design of the study. LK organized the data, performed the statistical analysis in STATA, and wrote the first draft of the manuscript. KK performed additional statistical analysis in jamovi and wrote sections of the manuscript. All authors contributed to the article and approved the submitted version.

LK was supported by a London School of Economics PhD scholarship during early work and later by the National Institute for Health Research (NIHR) Applied Research Collaboration (ARC) West Midlands. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

LK thanks Professor Paul Dolan and Dr Georgios Kavetsos for their support early on in conducting this research, as well as Professor Richard Lilford for insights about multiple comparisons.

1 https://www.atusdata.org

2 In the ATUS this was Hispanic and Black, in GSOEP this was German origin.

3 In the ATUS this was whether the respondent had any physical or cognitive difficulty (yes/no), in GSOEP this was self-rated general health (bad, poor, satisfactory, good, and very good).

4 In the ATUS this was presence of children <18 years in the household, in GSOEP this was number of children.

5 This association was stronger and more precise when equivalizing income (dividing by the square root of household size), b  = −0.16, 95%CI = −0.06, −0.27, underscoring the importance of transparency in the treatment of income.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2022.883137/full#supplementary-material

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Greater Good Science Center • Magazine • In Action • In Education

How Does Valuing Money Affect Your Happiness?

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.”

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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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Does More Money Make You Happier? Why so much Debate?

• Published: 15 July 2011
• Volume 6 , pages 219–239, ( 2011 )

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Easterlin’s famous paradox questioned standard economic assumptions about a fundamental relationship in economics: that between happiness and income. In recent years there has been renewed debate about the paradox. In this essay, I highlight some of the methodological issues and challenges underlying that debate. I focus on the sensitivity of the results to the method selected, the choice of micro or macro data, and the way that happiness questions are defined and framed, all of which result in divergent conclusions. I also note the mediating role of the pace and nature of economic growth, institutional frameworks, and inequality. What is most notable is the remarkable consistency in the determinants of individual happiness – including income – within countries of diverse income levels and, at the same time, how happiness is affected by cross-country differences that are related to average per-capita income levels, such as political freedom and public goods. Income clearly plays a role in determining both individual and country level happiness. Still, assessing its role relative to other more difficult to measure factors as countries develop in new ways and at different rates will remain a challenge for the foreseeable future.

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The Relationship Between Income Inequality and Economic Growth: Are Transmission Channels Effective?

The global distribution of gains from globalization.

Is happiness U-shaped everywhere? Age and subjective well-being in 145 countries

See Easterlin ( 1974 and 2003 ); Blanchflower and Oswald ( 2004 ); Frey and Stutzer ( 2002a ); and Graham and Pettinato ( 2002b ).

This finding holds for people who are, on average, happier, but not necessarily for those that are the happiest in every sample. See (Diener and Biswas-Diener 2008 ); and Graham et al. ( 2004 ).

Deaton gets a positive and significant coefficient on a squared specification of the income variable. Stevenson and Wolfers split their sample into those countries above and below $15,000 per capita (in year 2000 U.S. dollars), they get a slightly steeper slope for the rich countries than for the poor ones.

Blanchflower and Oswald find a correlation coefficient of .50 for the two questions in Europe and the United States; Graham and Pettinato find one of .55 for Latin America, where the questions were used inter-changeably in various years of the Latinobarometro poll. See Blanchflower and Oswald ( 2004 ); and Graham and Pettinato ( 2002a , b ).

This question is limited, at least in econometric terms, as 96% answer yes to the yes-no question.

For detail on the exact question phrasing and distribution of responses, see Graham ( 2010 ), Chapter 3.

In each country, Gallup includes a categorical question on total monthly household income, with respondents given choices within brackets expressed in local currency. The number of brackets is different in each country, and in Latin America it ranges from four brackets to 20. We relied on an adjustment to the Gallup income variable in which each household was assigned a normalized random value within the bracket that they self-reported. Income was transformed to U.S. PPP dollars and then divided by household size, resulting in a monthly per capita household income variable which is normally distributed across the sample. See Gasparini et al. ( 2009 ). While the most common adaptation for scale is to divide total household income by the square root of the number of people in the household. The Gasparini et al. adaptation divided income by the number of household members. As a check, we adjusted the same income variable by the square root of household size and got essentially the same results.

In theory, these two should be identical. In practice, with substantial misreporting at the top and with a very fat left tail (with far fewer few observations on the right/top) the log of the average may place higher relative weight on the households at the bottom of the distribution and smooth out the effects of the outliers on the right.

We used both the simple, un-weighted scale of asset ownership, and then a principle-components-analysis (PCA) based index in which the assets that are more unequally distributed across households are weighted more. Our results are essentially identical using alternative methods; the results on wealth reported in the tables are those based on the PCA approach. For more detail on the particular assets in the index and its construction, see Graham et al. ( 2010b ).

We use the following model: average happiness (as measured by each separate question) in country i   = f (average log of per capita income or wealth in country i +characteristics of the average individual in country i ).

The model is: individual happiness = f (household log income or wealth +personal controls +country dummies). We ran the model sequentially, first looking at just happiness and income or wealth, then adding the country dummies, and finally adding the personal controls.

See the appendix to Stevenson and Wolfers ( 2008 ).

I thank both Justin Wolfers and Charles Kenny for thoughtful conversations on this point.

For more detail, see Graham and Pettinato ( 2002b ).

See Graham and Felton ( 2006 ); Luttmer ( 2005 ); Luttmer’s work is based on U.S. PUMA’s, geographic units which are established in census data, which proxy for neighborhoods; and Kingdon and Knight ( 2007 ).

In related research, Graham et al. ( 2011 ) show that better reference group health is positive for health satisfaction, controlling for individual levels of health. Signaling effects seem to dominate over comparison effects, most likely because there are positive externalities related to being surrounded by healthier people.

For additional details see Alesina et al. ( 2004 ). Benabou and Ok ( 1998 ); and Graham and Young ( 2003 ).

Because there is not a good income variable in the Latinobarometro, the authors use an index of assets to proxy for wealth/income. See Graham and Felton ( 2006 ).

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The author is Senior Fellow and Charles Robinson Chair at the Brookings Institution and College Park Professor at the University of Maryland. This essay draws heavily on a paper she co-authored with Soumya Chattopadhyay and Mario Picon for an October 2008 Princeton Conference on International Differences in Well-Being. The authors would like to thank Peyton Young, Andrew Felton, and Charles Kenny, as well as the participants and reviewers from the Princeton conference for very helpful comments. Also see Graham et al. ( 2010a ).

This manuscript is adapted from Happiness around the World: The Paradox of Happy Peasants and Miserable Millionaires (authored by Carol Graham and published by Oxford University Press in 2009). Available direct from Oxford University Press at: http://www.oup.com/uk/catalogue/?ci=9780199549054

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Graham, C. Does More Money Make You Happier? Why so much Debate?. Applied Research Quality Life 6 , 219–239 (2011). https://doi.org/10.1007/s11482-011-9152-8

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Can money buy happiness? Scientists say it can.

It’s a question that philosophers, economists and social scientists have grappled with for decades: Can money buy happiness?

For most people in the United States, the answer is, seemingly, yes.

Two prominent researchers, Daniel Kahneman and Matthew Killingsworth, came to this conclusion in a joint study published this month in the Proceedings of the National Academy of Sciences, overturning the dominant thinking that people are generally happier as they earn more, with their joy leveling out when their income hits $75,000.

This threshold was initially posited by Kahneman, a Nobel Prize-winning economist and psychologist, in a 2010 study that concluded that “emotional well-being [also] rises with log income, but there is no further progress beyond an annual income of $75,000.”

But in 2021, Killingsworth, a happiness researcher and senior fellow at the University of Pennsylvania’s Wharton School, found that happiness does not plateau after $75,000, and that “experienced well-being” can continue to rise with income well beyond $200,000.

Kahneman and Killingsworth said their latest study was an “adversarial collaboration” where they pitted their theories against each other with the help of an arbiter. The latest research adjusted for inflation, they said.

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In their study, Kahneman and Killingsworth surveyed 33,391 adults aged between 18 and 65 who live in the United States, are employed and report a household income of least $10,000 a year. The authors said they lacked substantial data for those earning over $500,000.

To measure their happiness, participants were asked to report on their feelings at random intervals in the day via a smartphone app developed by Killingsworth called Track Your Happiness . Killingsworth said in an email that the data came from “repeatedly pinging people at randomly-timed moments during daily life, and asking about their happiness at that moment in real-time.” Specifically, they were asked “How do you feel right now?” on a scale ranging from “very bad” to “very good,” he said.

The study reached two big conclusions: First, that “happiness continues to rise with income even in the high range of incomes” for the majority of people, showing that for many of us, on average having more money can make us increasingly happier.

But the study also found that there was an “unhappy minority,” about 20 percent of participants, “whose unhappiness diminishes with rising income up to a threshold, then shows no further progress.”

These people tend to experience negative “miseries” that typically cannot be alleviated by earning more money; the report cites examples such as heartbreak, bereavement or clinical depression. For them, their “suffering” may diminish as their income rises to about $100,000 but “very little beyond that,” the study said.

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“In the simplest terms, this suggests that for most people larger incomes are associated with greater happiness,” Killingsworth said in a statement about the study.

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“The exception is people who are financially well-off but unhappy. For instance, if you’re rich and miserable, more money won’t help. For everyone else, more money was associated with higher happiness to somewhat varying degrees.”

The study acknowledges that happiness or emotional well-being is a changing daily scale for many people and that “happy people are not all equally happy” but argues that there are “degrees of happiness” and often a “ceiling” for happiness.

The study also found that money can affect happiness differently, depending on income. Among lower earners, “unhappy people gain more from increased income than happier people do,” it said. “In other words, the bottom of the happiness distribution rises much faster than the top in that range of incomes.”

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In his statement, Killingsowrth made clear that money isn’t everything — “just one of the many determinants of happiness.” He added: “Money is not the secret to happiness, but it can probably help a bit.”

The study also made its way to social media Wednesday, with one Twitter user joking : “Anyone who says money doesn’t buy happiness just doesn’t know where to go for shopping.”

Another teased : “Money won’t make you happy, but it’s nicer to cry in a Ferrari.”

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Research: Can Money Buy Happiness?

In his quarterly column, Francis J. Flynn looks at research that examines how to spend your way to a more satisfying life.

September 25, 2013

A boy looks at a toy train he received during an annual gift-giving event on Christmas Eve 2011. | Reuters/Jose Luis Gonzalez

What inspires people to act selflessly, help others, and make personal sacrifices? Each quarter, this column features one piece of scholarly research that provides insight on what motivates people to engage in what psychologists call “prosocial behavior” — things like making charitable contributions, buying gifts, volunteering one‘s time, and so forth. In short, it looks at the work of some of our finest researchers on what spurs people to do something on behalf of someone else.

In this column I explore the idea that many of the ways we spend money are prosocial acts — and prosocial expenditures may, in fact, make us happier than personal expenditures. Authors Elizabeth Dunn and Michael Norton discuss evidence for this in their new book, Happy Money: The Science of Smarter Spending . These behavioral scientists show that you can get more out of your money by following several principles — like spending money on others rather than yourself. Moreover, they demonstrate that these principles can be used not only by individuals, but also by companies seeking to create happier employees and more satisfying products.

According to Dunn and Norton, recent research on happiness suggests that the most satisfying way of using money is to invest in others. This can take a seemingly limitless variety of forms, from donating to a charity that helps strangers in a faraway country to buying lunch for a friend.

Witness Bill Gates and Warren Buffet, two of the wealthiest people in the world. On a March day in 2010, they sat in a diner in Carter Lake, Iowa, and hatched a scheme. They would ask America‘s billionaires to pledge the majority of their wealth to charity. Buffet decided to donate 99 percent of his, saying, “I couldn‘t be happier with that decision.”

And what about the rest of us? Dunn and Norton show how we all might learn from that example, regardless of the size of our bank accounts. Research demonstrating that people derive more satisfaction spending money on others than they do spending it on themselves spans poor and rich countries alike, as well as income levels. The authors show how this phenomenon extends over an extraordinary range of circumstances, from a Canadian college student purchasing a scarf for her mother to a Ugandan woman buying lifesaving malaria medication for a friend. Indeed, the benefits of giving emerge among children before the age of two.

Investing in others can make individuals feel healthier and wealthier, even if it means making yourself a little poorer to reap these benefits. One study shows that giving as little as $1 away can cause you to feel more flush.

Quote Investing in others can make you feel healthier and wealthier, even if it means making yourself a little poorer.

Dunn and Norton further discuss how businesses such as PepsiCo and Google and nonprofits such as DonorsChoose.org are harnessing these benefits by encouraging donors, customers, and employees to invest in others. When Pepsi punted advertising at the 2010 Superbowl and diverted funds to supporting grants that would allow people to “refresh” their communities, for example, more public votes were cast for projects than had been cast in the 2008 election. Pepsi got buzz, and the company‘s in-house competition also offering a seed grant boosted employee morale.

Could this altruistic happiness principle be applied to one of our most disputed spheres — paying taxes? As it turns out, countries with more equal distributions of income also tend to be happier. And people in countries with more progressive taxation (such as Sweden and Japan) are more content than those in countries where taxes are less progressive (such as Italy and Singapore). One study indicated that people would be happier about paying taxes if they had more choice as to where their money went. Dunn and Norton thus suggest that if taxes were made to feel more like charitable contributions, people might be less resentful having to pay them.

The researchers persuasively suggest that the proclivity to derive joy from investing in others may well be just a fundamental component of human nature. Thus the typical ratio we all tend to fall into of spending on self versus others — ten to one — may need a shift. Giving generously to charities, friends, and coworkers — and even your country — may well be a productive means of increasing well-being and improving our lives.

Research selected by Francis Flynn, Paul E. Holden Professor of Organizational Behavior at Stanford Graduate School of Business.

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This is the relationship between money and happiness

Does money make you happy? Image:  REUTERS/Mohamed Abd El Ghany

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Can money buy you happiness?

It’s a longstanding question that has many different answers, depending on who you ask.

Today’s chart approaches this fundamental question from a data-driven perspective, and it provides one potential solution: money does buy some happiness, but only to a limited extent.

Money and happiness

First, a thinking exercise.

Let’s say you have two hypothetical people: one of them is named Beff Jezos and he’s a billionaire, and the other is named Jill Smith and she has a more average net worth. Who do you think would be happiest if their wealth was instantly doubled?

Beff might be happy that he’s got more in the bank, but materially his life is unlikely to change much – after all, he’s a billionaire. On the flipside, Jill also has more in the bank and is likely able to use those additional resources to provide better opportunities for her family, get out of debt, or improve her work-life balance.

These resources translate to real changes for Jill, potentially increasing her level of satisfaction with life.

Just like these hypotheticals, the data tells a similar story when we look at countries.

The data-driven approach

Today’s chart looks at the relationship between GDP per capita (PPP) and the self-reported levels of happiness of each country. Sources for data are the World Bank and the World Happiness Report 2017 .

According to the numbers, the relationship between money and happiness is strong early on for countries. Then later, when material elements of Maslow’s hierarchy are met, the relationship gets harder to predict.

In general, this means that as a country’s wealth increases from $10k to $20k per person, it will likely slide up the happiness scale as well. For a double from $30k to $60k, the relationship still holds – but it tends to have far more variance. This variance is where things get interesting.

Outlier regions

Some of the most obvious outliers can be found in Latin America and the Middle East:

In Latin America, people self-report that they are more satisfied than the trend between money and happiness would predict.

Costa Rica stands out in particular here, with a GDP per capita of $15,400 and a 7.14 rating on the Cantril Ladder (which is a measure of happiness). Whether it’s the country’s rugged coastlines or the local culture that does the trick, Costa Rica has higher happiness ratings than the U.S., Belgium, or Germany – all countries with far higher levels of wealth.

In the Middle East, the situation is mostly reversed. Countries like Saudi Arabia, Qatar, Iran, Iraq, Yemen, Turkey, and the U.A.E. are all on the other side of the trend line.

Outlier countries

Within regions, there is even plenty of variance.

We just mentioned the Middle East as a place where the wealth-happiness continuum doesn’t seem to hold up as well as it does in other places in the world.

Interestingly, in Qatar, which is actually the wealthiest country in the world on a per capita basis ($127k), things are even more out of whack. Qatar only scores a 6.37 on the Cantril Ladder, making it a big exception even within the context of the already-outlying Middle East.

Have you read?

5 things everyone needs to know about happiness, is part-time working the key to happiness, it’s official: money really does buy you happiness (but only if you spend it in the right way).

Nearby Saudi Arabia, U.A.E., and Oman are all poorer than Qatar per capita, yet they are happier places. Oman rates a 6.85 on the satisfaction scale, with less than one-third the wealth per capita of Qatar.

There are other outlier jurisdictions on the list as well: Thailand, Uzbekistan, and Pakistan are all significantly happier than the trend line (or their regional location) would project. Meanwhile, places like Hong Kong, Ireland, Singapore, and Luxembourg are less happy than wealth would predict.

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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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Why Money Doesn't Buy Happiness

According to kahneman and deaton, money doesn't buy happiness. why not.

Posted August 25, 2022 | Reviewed by Michelle Quirk

• It's often said that money doesn't buy happiness, and, in a 2010 study, Kahneman and Deaton show that it doesn't.
• Nevertheless, most people apparently think that it does.
• Kahneman and Deaton found that "emotional well-being" is associated with social interaction rather than with higher income.

The old saw “money can’t buy happiness ” is often used, mostly by people who don’t have much, as a challenge to the importance of wealth in human society. But is it true? Does more money really not make people happier?

In a 2010 study, Nobel laureate Daniel Kahneman and Angus Deaton set out to answer this question. They explored two aspects of what’s known as “subjective well-being.” Importantly, they made a distinction between emotional well-being and life evaluation. Emotional well-being is defined as “…the emotional quality of an individual’s everyday experience—the frequency and intensity of experiences of joy, fascination, anxiety , sadness, anger , affection that make one’s life pleasant or unpleasant." Life evaluation “refers to a person’s thoughts about his or her life.” Here is what they found:

In the present study, we confirm the contribution of higher income to improving individuals’ life evaluation, even among those who are already well off. However, we also find that the effects of income on the emotional dimension of well-being satiate fully at an annual income of ∼$75,000… (Kahneman and Deaton, 2010, p. 16490).

In other words, getting more money makes us think our lives are better, but doesn’t make us feel any better.

To be sure, not having enough money negatively affects our emotional well-being. But once we have enough (about $75,000 in 2010), having more doesn’t positively affect it. So, while we think our lives would be better if we got a raise or hit the lottery jackpot, we’d be no happier than we were before the windfall. Now that’s interesting. Money really doesn’t buy happiness.

But why not? We think that Kahneman and Deaton’s distinction between life evaluation and emotional well-being might provide an answer.

Evolution of Emotional Well-Being

The emotions of well-being the authors identify—joy, fascination, anxiety, sadness, anger, affection—evolved over hundreds of thousands of years in hunter–gatherer bands. There was no money in these bands, of course, and, as we’ve noted in previous blogs, it was more important to use possessions as gifts than hold on to them. Well-being was having enough to eat and interacting with the other members of the band—hunting, gathering, quarreling, fighting, telling stories, dancing, healing.

However, since the agricultural revolution, human history has been in large part the story of acquisition—more land, money, possessions, power. Today, acquisition messages are all around us: Buy more and better things, get a higher-paying job. These messages address post-agricultural thinking but ignore ancient emotional needs.

Thinking about how your life is going or will go is another creation of our old friend and nemesis the neocortex. Given the obvious advantages of wealth and power after the agricultural revolution, the cortex turned them into ideas, things to aspire to, goals . Moving up was good, whether it made you happy or not.

As more and more opportunities to move up were created by the industrial revolution and the market economy, more and more people could rise. It was great to have enough—enough money, enough to eat, and a place to live. And it felt good to rise and have more status.

A Moving Goal

Unfortunately, there was an unintended consequence: The goal kept moving. There was always a better position, a better salary, higher status. Thinking about well-being became associated with making more money. When Donald Trump was asked about what money meant to him, he said “Money was never a big motivation for me, except as a way to keep score.” He didn’t mention happiness.

So, here we humans are, stuck again between ancient emotions and an environment that pushes us to achieve and acquire. As Kahneman and Deaton note in their study, when asked the question, “What made you happy yesterday,” most people emphasized time with family and friends, taking care of a relative, working on a project with others, etc. When asked what they thought would make them happier, most said, “Having more money.”

Kahneman, D. and Deaton, A. 2010. “High Income Improves Evaluation of Life, But Not Emotional Well-Being.” PNAS. September 21, 2010, vol. 107, no. 38, pp. 16489-16493.

J. Gary Bernhard, Ed.D. has been involved in educational leadership for more than 40 years. Kalman Glantz, Ph.D. has spent nearly 30 years as a psychotherapist in private practice in Boston.

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