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| Does being happy help you earn more? | Does being happy help you earn more? |
| (about 2 hours later) | |
| Does being happy make you more likely to earn more? The answer is yes, according to one economist. | Does being happy make you more likely to earn more? The answer is yes, according to one economist. |
| Professor Satya Paul, an economist at the University of Western Sydney, has analysed the effect of happiness on income inequality. | Professor Satya Paul, an economist at the University of Western Sydney, has analysed the effect of happiness on income inequality. |
| Using data from the Household, Income and Labour Dynamics in Australia survey (HILDA), Paul's results suggest that "an individual who is completely satisfied with life earns $1766.7 more than the one who is completely unsatisfied with life". | Using data from the Household, Income and Labour Dynamics in Australia survey (HILDA), Paul's results suggest that "an individual who is completely satisfied with life earns $1766.7 more than the one who is completely unsatisfied with life". |
| The HILDA survey asked 9,300 people to answer questions about their economic situation and their wellbeing. Run from 2001 to 2005, respondents were required to rank their "happiness" (or life satisfaction) from zero to ten, where zero was least satisfied with their life, and ten was most satisfied. | The HILDA survey asked 9,300 people to answer questions about their economic situation and their wellbeing. Run from 2001 to 2005, respondents were required to rank their "happiness" (or life satisfaction) from zero to ten, where zero was least satisfied with their life, and ten was most satisfied. |
| Using mathematical modelling, Paul showed that for every one point increase in the happiness scale, the net effect on the individual's annual income was an increase of $176.76. | Using mathematical modelling, Paul showed that for every one point increase in the happiness scale, the net effect on the individual's annual income was an increase of $176.76. |
| Extrapolated to percentages, he suggests that for every 1% increase in happiness there's a 0.056% increase in income. | Extrapolated to percentages, he suggests that for every 1% increase in happiness there's a 0.056% increase in income. |
| Interestingly, there's also a negative effect of happiness on income – the number of hours worked. A one point rise in happiness results in a loss of $27.41 because of fewer hours worked – that is, people who are more satisfied with life are willing to trade work for leisure. | Interestingly, there's also a negative effect of happiness on income – the number of hours worked. A one point rise in happiness results in a loss of $27.41 because of fewer hours worked – that is, people who are more satisfied with life are willing to trade work for leisure. |
| Paul suggests the increase in income resulting from higher happiness is a result of happier people being more efficient in earning activities. Or, to put it more simply, happier people are better workers. | Paul suggests the increase in income resulting from higher happiness is a result of happier people being more efficient in earning activities. Or, to put it more simply, happier people are better workers. |
| The effect of happiness on income is also proportionally greater for people in lower income brackets. In 2005, happiness explained 26.33% of the variation in income for people in the lowest one-fifth income bracket, whereas it only explained 2.69% of the variation in income for the richest fifth. Paul says this is because changes in smaller incomes result in larger percentage changes overall compared to a change of the same proportion with a higher base salary. | The effect of happiness on income is also proportionally greater for people in lower income brackets. In 2005, happiness explained 26.33% of the variation in income for people in the lowest one-fifth income bracket, whereas it only explained 2.69% of the variation in income for the richest fifth. Paul says this is because changes in smaller incomes result in larger percentage changes overall compared to a change of the same proportion with a higher base salary. |
| He also analysed the contribution of poor health, gender and a number of other variables to income. Being female had the largest negative effect on income, with -17.35% in 2005. Poor health also had a small negative effect. | He also analysed the contribution of poor health, gender and a number of other variables to income. Being female had the largest negative effect on income, with -17.35% in 2005. Poor health also had a small negative effect. |
Click here for the graph on mobile | Click here for the graph on mobile |
| Paul will be presenting the results of this study at the HILDA conference in October, at the University of Melbourne. | Paul will be presenting the results of this study at the HILDA conference in October, at the University of Melbourne. |
| And, as an aside, one of the articles cited in the study was too good not to mention: | And, as an aside, one of the articles cited in the study was too good not to mention: |
| Oswald et al [2008] designed a randomised trial at the University of Warwick to see how emotions affect human productivity. They ran the experiment twice, both times working with 182 subjects. The first time they induced happiness in a group of people by showing them 10 minutes of comedy clips. Another group saw no clips. Then, both groups took a short math test. They were told they would be paid based on how many questions they answered correctly. The group that had watched the clips answered 10% more questions correctly than the group that hadn't. | Oswald et al [2008] designed a randomised trial at the University of Warwick to see how emotions affect human productivity. They ran the experiment twice, both times working with 182 subjects. The first time they induced happiness in a group of people by showing them 10 minutes of comedy clips. Another group saw no clips. Then, both groups took a short math test. They were told they would be paid based on how many questions they answered correctly. The group that had watched the clips answered 10% more questions correctly than the group that hadn't. |
| So next time you're preparing for an exam or difficult round of number-crunching, maybe try loading up a few cat videos first. | So next time you're preparing for an exam or difficult round of number-crunching, maybe try loading up a few cat videos first. |
| Edit: A few people are asking how the study distinguishes the direction of the relationship - that is, how he has determined that varying happiness results in an increase in income, rather than the increase in income resulting in making people happier. The study uses a regression analysis to determine the degree of variation each variable explains, in this case happiness determining a change in income. To correct for the issue of endogeneity whereby both factors might be cross-correlated, he has corrected the analysis using lagged variables from the time series: | |
| Another related issue that is equally crucial and requires mention at the very outset relates to the possibility of bidirectional causality between happiness and income which can lead to simultaneous/ endogeneity bias in the coefficient of happiness variable in income generating function. One effective way to resolve this problem is to use an instrument which is correlated with happiness variable but is uncorrelated with the error term. In a recent attempt to examine the effect of happiness on consumption, saving and risk taking behaviour with panel data for Germany and the Netherlands, Guven (2007) overcomes the problem of endogeneity in each regression equation by instrumenting individual happiness with regional sunshine. However, while working with time series data, the lagged value of the variable serves as a natural instrument in the model (Greene, 2003, pp. 78-79). | Another related issue that is equally crucial and requires mention at the very outset relates to the possibility of bidirectional causality between happiness and income which can lead to simultaneous/ endogeneity bias in the coefficient of happiness variable in income generating function. One effective way to resolve this problem is to use an instrument which is correlated with happiness variable but is uncorrelated with the error term. In a recent attempt to examine the effect of happiness on consumption, saving and risk taking behaviour with panel data for Germany and the Netherlands, Guven (2007) overcomes the problem of endogeneity in each regression equation by instrumenting individual happiness with regional sunshine. However, while working with time series data, the lagged value of the variable serves as a natural instrument in the model (Greene, 2003, pp. 78-79). |
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