Workshop on Well-Being III

MARCH 17, 2008

Following on from the second workshop a month ago, today saw the third in the series of “Workshops on Well-being” take place at the LSE. This time the presentation was given by Andrew Clark of PSE. Below are some (very) impressionistic notes.

Presentation by Andrew Clark on Job Satisfaction: What do we Know and What Next?

  1. Job satisfaction (JS) and individual well-being (LS)
  • well-being/LS function LS = f(Job satisfaction, health satisfaction, leisure etc)
  • data in BHPS (waves 6-15 though 11 missing)
  • health/ income / house / spouse / job / social life / amout leisure / use leisure (scale 1-7)
    • all highly significant
    • social life is top, followed by health, use of leisure, income and job satisfaction is last
    • robust to demographic controls
  • But do individual personality types make any difference (fixed effects)
  1. Panel results
  • all effects go down (there are ‘happy types’) except JS (which doubles) though still the smallest
  • Is this ranking unique to Britain?
  • Is it the same for everyone? (subregressions: old/young, men/women; or do a latent class analysis)
  1. JS is important to firms as well as it will predict worker behaviour
  • Labour turnover
  • Absenteeism
  • Counter-and non-productive work/productivity
  • Worker quitting (but almost impossible to do properly as quitting is self-reported so unreliable)
    • P(quit(t+1)) = f(JS, X(t))
  1. Compare quitting GB and Germany
  • pretty similar, JS is pretty significant
  1. Cognitive biases and context in relation to quitting (SPELL data from BHPS)
  • have panel data so can look at series of JS for an individual
  • refers to Kahnemann and Riedelmeier on evaluation of colonoscopy
    • suggest Peak-End evaluation: evaluations of peak and end point
  • Apply to job quitting (peak-end, min, max, avg, current …)
    • peak-end does best (followed by running max (close), and current)
  • => behaviour would not then seem to max their utility
  1. Try do the same with income but need variations in income (since normally just rises)
  • use truckers as they have exog changes
  • other potential sources: tax changes
  • peak-end divorce
  1. Relative income
  • Traditional: W/LS/JS = W(y,…)
  • Comparisons: LS/JS = W(y/yr, …)
  • yr is comparison/relative income
  • to whom do we compare? (peers, others in HH, spouse, myself in the past, friends, neighbours, work, expectations)
  • Results:
    • +ve effect of income
    • But falling as other’s income rises
    • Overall effect is zero: if everyone’s income rises then no effect
  1. Preference for structure of income
  • same income but in different ways
  • flat slope (A), steeper (+ve) slope (B), and v. +ve slope (C)
  • even though flat slope (using saving to mimic C) would result in being overall better off
    • asked about this (they were told they could this) they still chose C (apparently because of self-control issues – they wouldn’t be able to save)
  1. Does other’s income always affect one negatively
  • Hirschmann’s tunnel effect (happy for something good for you because it means something good is going to happen to me)
  • Danish ECHP (1994-2001): fantastic data (which gave not only individuals but all of their colleage’s info including pay)
  • here one does find a +ve effect of others income on me (check how it varies across firm so not just selection effect at firm level)
  1. Do 2 wrongs make a right?
  • Peak-end utility could be thought of as ‘correct’ as:
    • with adaptation
    • current utility (after something good) understates actual total flow benefits (as one has adapted)
    • PE corrects for this
  1. Instrumental uses of JS
  • ‘Good job’ lit has mainly focused on money
  • But self-employed earn less but are happier (though significat issues about reporting bias)
  • Also why are there different avg. wages in different industries (when they look the same)
    • Compensating differentials vs. rents
  • So let’s use JS to explain different
    • looking at the data: high wage goes with high JS (so suggests this about rents not compensation)
  1. Job Quality: Are things going to the dogs?
  • ISSP (repeated XS in 3 waves 1989 - 2005)
  • Multivariate regressions: JS is improving (went down 1989-1997 but bounced back in 2005)
    • But stressful/dangerous/difficult work has been rising
    • Good job content has been going down.
    • However enough other stuff has been getting better faster (income, opportunities, flexible hours)


  • Paul Dolan:
    • Causality
    • Experienced Utility? Kahnemann would be unhappy
    • Peak-end seems difficult for JS since already a retro-spective evaluation (so peak-end of a peak-end)
  • Gordan:
    • relative ranked position not just compared to the avg
    • care more about those above than those below
    • need to be more specific about form of relativities
  • All: Context, Context, Context
  • RP: Peak-end vs. range-frequency. Take colonoscopy: PE predicts that increasing pain at a single point (early on) would worsen evaluation while range-frequence would predict it would improve evaluation (since you spend more time at a level relatively better than the worst)
  • BHPS: now have a question asking for whether your LS is better/worse than last year
  • Gordan: gratitude is single biggest predictor of happiness
    • individual differences
  • Propensities to adapt
  • Gordon: Andrew Oswald and he also found +ve avg income effects in workplace
  • Judgment vs. Adaptation
  • Paul Dolan: generally we overestimate our +ve attributes but underestimate (their relative) income level