miscellaneous factZ

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)

2. 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)

3. 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))

4. Compare quitting GB and Germany

   • pretty similar, JS is pretty significant

5. 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

6. 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

7. 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

8. 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)

9. 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)

10. 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

11. 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)

12. 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)

Discussion

• 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