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Argyle, Causes and Correlates of Happiness

  • Age
  • Education
  • Social Status
  • Income
  • Marriage
  • Ethnicity
  • Employment
  • Leisure
  • Religion
  • Life Events

Synopsis by major factor:

  • Age
  • The older are slightly happier, notably in postive affect. Some evidence that women become less happy with age. In assessing causality, we might need to acknowledge a cohort effect (older people are those who survive, hence not nec. representative of a sampling of all age groups). Older people are less satisfied than others with their future prospects.
  • Old people could have lower expectations, and hence their greater self-reported happiness might not be comparable to a younger person's self-reported happiness.
  • Puzzle: objective conditions are worse for old people (health, depression and loneliness!), yet they are more satisfied. (Neural degeneration has got to be on the table as a hypothesis.)
  • Education
  • The educated are slightly happier. Effect weak in US. Data suggest the education effect is greater in poorer countries. Control for income and job status effects and there is still a slight effect from education. [From personal achievement?] But income and job status account for most of the education effect.
  • Social Status
  • About twice the effect of education or age, but half of the effect is from job status. Greater effect for stratified societies. [Comment on being a professor in Italy, for example.]
  • Income
  • Average correlation of .17 across studies. See chart on p. 356 -- curvilinear, with slight upward tail at highest incomes. (intriguing)
  • Steep relation of income from poverty to material sufficiency.
  • Diener found a stronger correlation when using multiple income measures (such and GNP, purcasing power indexes, etc.)
  • Famous Myers and Diener 1996 study: "In the United States, average personal income has risen from $4,000 in 1970 to $16,000 in 1990 (in 1990 dollars), but there has been no change in average happiness or satisfaction." Some evidence that happiness is sensitive to economic downturns (Belgium), some evidence of variation in strength of effect across culture.
  • Lottery winner studies may not be a good way to test income effects since you get lots of disruptions with winning the lottery.
  • Cluster effect with income: Income comes with host of other goods: p. 358.
  • Michalo's "goal achievement gap model" p. 358: "whereby happiness is said to be due to the gap between aspirations and achievements and this gap is due to comparisons with both "average folks" and one's own past life (see figure 18.3).
Other Resources:
  • Kahneman and Deaton, "High income improves evaluation of life but not emotional well-being"
  • Graham, et. al, "The Easterlin Paradox and Other Paradoxes: Why both sides of the Debate May be Correct"
  • Marriage
  • Average effect from meta-analysis of .14. Stronger effects for young. Does more for women than men, though stronger effect on male health.
  • Causal model: Married people have higher social well being indicators (mental and physical health). These indicators are independent factors for happiness. Marriage is a source of emotional and material support. Married people just take better care of themselves. Men might benefit from emotional support more since women provide that to male spouses more than males? (differently?)
  • Effects of marriage has a life-stage dimension to them. (figure 18.4) Having children has a small effect.
  • Reverse causation is a consideration, but hard to support since 90% of people get married.
  • Good example in this section of distinguishing between correlational data and causal discussion.
  • Ethnicity
  • Widely confirmed studies show that average happiness for US African Americans is lower than for US whites.
  • Mostly accounted for by income, education, and job status.
  • Interestingly, African American children enjoy higher self-esteem than white kids.
  • Employment
  • Studies of unemployed and retired help isolate effects.
  • Unemployed sig less happy: "The unemployed in nearly all countries are much less happy than those at work. Inglehart (1990) found that 61 percent of the unemployed were satisfied, compared with 78 percent of manual workers."
  • Causal model: income and self-esteem account for most of effect.
  • Leisure
  • Relatively strong correlation: .2 in meta-studies.
  • Leisure effects observed in lots of contexts (social relations from work, adolescent leisure habits, even a short walk. Sport and exercise include both social effects and release of endorphins.
  • Flow is a factor. Comparisons of high engagement and high apathy (tv) leisure activities.
  • TV watching as a leisure activity. Soap opera watchers!
  • Volunteer and charity work were found to generate high levels of joy, exceeded only by dancing!
  • Religion
  • The strength of religion on happiness is positive, sensitive to church attendance, strength of commitment, related to meaningfulness and sense of purpose (an independent variable). Overall modest effect, but stronger for those more involved in their church. note demographic factors.
  • Reverse causation: Are happier people more likely to be religious?
  • Causal model: Religion works through social support, increasing esteem and meaningfulness.
  • Kirpatrick 1992 study: self-reported relationship with God has similar effects as other relationships.
  • Life events and activities (especially on affect)
  • "' A study in five Eu European countries found that the main causes of joy were said to be relationships with friends, the basic pleasures of food, drink, and sex, and success experiences (Scherer etal. 1986)."..."Frequency of sexual intercourse also correlates with happiness, as does satisfaction with sex life, being in love, and frequency of interaction with spouse, but having liberal sexual attitudes has a negative relationship." "...alcohol, in modest doses, has the greatest effects on positive mood."