Happiness and money – Oskar Wolthoorn

14-11-2019: This is a living document. I believe in rapid innovation and working online. I like interaction, so if you want to contact me about any of my work, don’t hesitate and contact me here. I’m especially interested in doing research concerning the topic of happiness, giving lectures about what makes people (un)happy and interesting conversations over a coffee! Contact me 🙂

Main conclusions:

Research found that 50% of the variance in current happiness is heritable (Lykken & Tellegen, 1996). So happiness is highly dependent on someone’s genetics. This was found in twin studies with 5945 individuals contributing, measured at around 20 years of age and around 30 years of age. Education accounted for around ~3% of wellbeing, income 2%, marriage yes/no 1%, genetics ~40-60%.
Research shows that when people are poorer, other negative life events’ effects are worse (Kahneman & Deaton, 2010). For example, people who have an income of <$1000/mo, report much more headache the previous day (38%) in comparison to people earning >$3000/mo. Thus, there is a positive relationship between earning more and being healthier.
Meta-analytical research shows that there is only a weak relationship between pay level and overall job satisfaction (ρ̂=.15). The relationship is stronger between the pay level and pay satisfaction (ρ̂=.24). 61 studies with 18.460 participants were included (Judge, Piccolo, Podsakoff, Shaw & Rich, 2010).
Having more money is associated with experiencing greater happiness up until $75.000 household income per year (Kahneman & Deaton, 2010). After $75.000 people aren’t happier.
Having more spare time in life is associated with greater happiness and life satisfaction even after controlling for income (Kasser & Sheldon, 2009).
People who value life over money report experiencing greater happiness, independent from how much time and money someone has available (Hershfield, Mogilner & Barnea, 2016).
When individuals are asked what would most improve the quality of their lives, the most common response is a higher income (Campbell, 1981).
Research found that spending money on others provides more happiness than spending money on oneself (Dunn, Aknin & Norton, 2008). This was very strong experimental, longitudinal and correlational research.
Having more money doesn’t contribute as much to happiness as many more important factors in your life do. Health, friends, relationships are all far more impactful (source needed).

Kahneman & Deaton, 2010

Judge, Piccolo, Podsakoff, Shaw & Rich, 2010

This meta-analysis summarised 61 studies in research on pay level and job satisfaction. There was a weak positive relationship. This suggests that pay level doesn’t contribute a lot to job satisfaction, but other factors do. Furthermore, they found that employees earning salaries in the top half (>$64.000) report similar job satisfaction as employees in the bottom half (<$64.000) of the data range. One example of a sample of lawyers earning on average $148.000 per year were less satisfied (68%) with their job in comparison to child care workers earning $23.500 a year (79%).

This figure shows that the average job satisfaction doesn’t differ very much between studies. Thus, the found relationship between pay level and job satisfaction is independent of studies, making it a stable relationship. This figure does suggest a negative relationship between pay level and job satisfaction, but that is not the case as only averages per study were shown and thus this suggestion is false.

Myers, 2000. Between 1965 and 2000, more individuals entering colleges in the U.S. found being well off financially more important (~72%) in comparison to developing a meaningful philosophy in life (~45%). Being well off financially was ~44% in 1965 versus ~82% for developing a meaningful philosophy of life. However, it should be noted that in 1965 only 5.92 million people enrolled in colleges versus 15.31 in 2000 (Statistica.com). It could be that the majority of the students entering colleges in 1965 were already financially well off in comparison to students entering in 2000.

Steel, P., Taras, V., Uggerslev, K., & Bosco, F. (2018)

Having low power distance in your culture is highly related to higher aspects of wellbeing. Furthermore, it was also related to lower GDP per capita and reduced governance effectiveness. Yet, a critical note here is that countries placed on the top left corner are generally more developed countries in comparison to the lower right.

Notably, achievement motivation, which predicted higher salaries, also predicted reduced SWB. At the individual level, this provides unique direct support for Easterlin’s (2001) observation, that “subjective wellbeing varies directly with income and inversely with material aspiration” (p. 481).

For individuals, cultural values are among the most important trait predictors of salary we have yet uncovered. Essentially, values related to working hard, working well with others, and delaying gratification are all linked to financial success. For example, each standard deviation increase in future orientation is associated with an extra $9,000 in salary. However, when we switch our focus to SWB, we find that results can change.

Subjective well-being, hapiness, life, and job satisfaction across the world between 1970-1990, 1990s and 2000s.

Hershfield, Mogilner & Barnea, 2016

Qualitative research from Mturk results (N=800).

Own research into money and happiness

Using amazon Mtuk to gather responses from “rich” and “poor” countries. Good research which used Mturk to gather participants: People Who Choose Time Over Money Are Happier, Hershfield, Mogilner & Barnea (2016). Use their methods to do it well.

Method: measure life satisfaction and stuff first before moving into measuring money and hapiness. Also, measure job satisfaction to find out what relationship between job satisfaction and life satisfaction is (seems to be gap in research).

Pay participants at least .5 or something for ~5 mins of work so that everyone does enter. Take demographics, money earned, a subjective wellbeing questionnaire. Maybe other factors that have been proven to be valid before could be interesting to take into account as well.

Check whether the data is normally distributed. Check whether the sample is representative of the normal population. Take at least ~400,- participants per country, or do a power analysis to make sure that my results will be representative of the population.

Possible countries could be, Netherlands (rich), Nepal (poor).

Investigate whether the countries significantly differ in money earned or subjective wellbeing. Change them into Z-values. Investigate how strong this relationship is between the two factors.

Do a factor analysis to find out which aspects are most important. Thus, catch in percentages which factors attribute to happiness. I think ANOVA is needed for this, double-check this. R^2 is the % that attributes.

Discuss the results. Before doing this research, double-check with someone from the UvA whether this design is any good (Michelle? Brigitte? Anyone else?).

Kleiner onderzoek in wat mensen nu willen weten over geld en geluk.

Online marketing-onderzoek over wat mensen vooral googlen over geld en geluk. Hoeveel animo is er eigenlijk voor dit onderwerp? Wie zoekt eigenlijk erop? Is er een relevant subonderwerp dat ik niet moet vergeten?

De vraag of geld gelukkig maakt lijkt veel mensen bezig te houden.

Interactive part of presentation

I could let participants live calculate their subjective well-being and some other factor like health satisfaction or family satisfaction (which are much stronger predictors of subjective well-being).

And if enough people respond, I could maybe calculate the real-time relationship between their salary (brackets) and subjective well-being. Furthermore, I could prove that health is a more important indicator of subjective well-being. Thus first ask for subjective well-being. Then salary, then send them a summary of their subjective well-being and have an interactive session in which I can calculate the relationship between the values. Maybe I can integrate such a widget in the slides to show a real-time calculation. I guess there must be widgets that extract the data from Google. Real-time process it to a graphical showing and then have that graph in the picture. Maybe via Mentimeter or something. Maybe search here for other tools: https://www.eventbrite.co.uk/blog/audience-interaction-tools-ds00/

And if this doesn’t work I could just show some more data from other responses, and some results from all the data I’ve gathered so far (including some Mturk data).

Other research which is bad:

Chitchai, Senasu & Sakworawich, 2018.

Main conclusion: Having a “love for money” is negatively related to happiness, job satisfaction and income satisfaction (Chitchai, Senasu & Sakworawich, 2018).

This research compared the socio-economic status (SES) with happiness. They found no direct relationship between SES and happiness. There was an indirect positive effect between SES and happiness via job, family and income satisfaction. Furthermore, love of money (LOM) was investigated. Love of money is the extent to which people value having money in life. It has four dimensions which measures to what extent people see money as successful, motivating, important and whether they want to be rich. Love for money (LOM) was negatively related to happiness, job satisfaction, and income satisfaction. LOM also had a weakening effect on the positive relationship between job satisfaction and happiness. This suggests that having high LOM is negative for overall happiness.

They gathered 433 participants in Thailand from people in poor circumstances, very rich circumstances and religious groups. The fact that a big part of the data consists of religious individuals could distort the results. This is because many religions state money is not important for happiness, and want their followers to live by these principles. It could be having this belief is in line with low LOM. As it is a big part of the respondents, it could be that this influenced the outcome.