• 1. E.g. “A New Gauge to See What’s Beyond Happiness”, York Times, 16 May 2011.
  • 2. The definition used is taken largely from Diener et al. (2006).
  • 3. By “decision utility” Kahneman refers to the sort of evaluation used by individuals to make choices between different options. He distinguishes this from “experienced utility” which is the sum of felicific experience for an individual over time. The former approaches what economists mean by utility in standard microeconomic models, while the latter is closer to Jeremy Bentham’s original notion of utility in the context of utilitarianism (Bentham, 1789).
  • 4. For example, the Gallup World Poll contains a range of questions on affect during the previous day, which have been extensively tested. The UK Office of National Statistics has collected similar measures of affect in its Integrated Household Survey programme.
  • 5. One concern sometimes raised about subjective measures is that they are unlikely to change as fast over time as more traditional indicators. In fact, this is not strictly true (see Box 1.2), However, even for those circumstances where measures of subjective well-being do not change as much as, say, resource-based measures, this should be regarded as information rather than as a problem with the measure.
  • 6. There are two primary reasons why subjective well-being might be considered to differ substantially from overall well-being. First, subjective well-being is affected by a number of factors, such as personality and culture, which might be considered a source of bias in terms of measuring actual well-being. Second, most theories of well-being are not strictly utilitarian in nature and recognise standards that are important to well-being regardless of their association with a person’s subjective state. For example, Sen (1979) defines well-being in terms of achieved “capabilities” to do certain things, explicitly rejecting a subjective (utilitarian) alternative.
  • 7. Consideration of initial sample variance in each measure is important here: if the sample has uniformly high levels of health satisfaction, but variable levels of housing satisfaction, housing satisfaction may look more important in a regression analysis, simply because it has more variation to associate with variation in the outcome measure.
  • 8. Cronbach’s coefficient alpha is considered to be the most stable and accurate index of internal consistency reliability (Kline, 2000; Nunnally and Bernstein, 1994). Provided all item standard deviations are equal, alpha is mathematically equivalent to the mean of all split-half reliabilities (i.e. dividing test items into two halves and correlating those halves with one another); it is slightly lower than the mean where item standard deviations vary (Cortina, 1993). Alpha is calculated by multiplying the mean average inter-item co-variance by the number of items in a test (which estimates the true score variance) and dividing this figure by the sum of all the elements in the variance-covariance matrix, which equals the observed test variance (Nunnally and Bernstein, 1994).
  • 9. Not all of this “noise” is strictly error, however. The sensitivity of affect measures to the day of the week, for example, validates these measures to the extent that individuals participate in more pleasurable activities, such as time spent with friends and family, on weekends (Heliwell and Wang, 2011; Stone, 2011).
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