730 vII. APPLICATIONS  AND  IMPLICATIONS
change, and that individuals are stuck with 
a biologically determined level of happiness 
that is only weakly linked to the circum -
stances they experience in life. In the follow -
ing sections, we review evidence from these 
four different lines of research. Although we 
believe that personality plays an important 
role in SWB, a careful examination of the 
existing evidence suggests that life circum -
stances also matter, and that there is room 
for change.
Associations with  External Life  Circumstances
People’s behavior is often guided by their 
beliefs about the types of things that will 
make them happy (Gilbert, 2006). People 
may choose a high-  paying job, an expen -
sive house, or a short commute over other 
alternatives, because they believe that these 
life circumstances will improve or maintain 
their happiness. Thus, one goal for psycho -
logical research is to identify the factors 
that actually do correlate with happiness. 
Through such research, people’s intuitions 
can be tested, and practical guidance can be 
offered. However, one most common con -
clusion from such inquiries is that very few 
objective life circumstances exhibit strong 
associations with SWB (see, e.g., Diener et 
al., 1999).
Perhaps the most surprising finding in 
this line of research concerns the link be -
tween income and happiness. Many stud -
ies have been conducted, and a number of 
consistent findings have emerged (Diener & 
Biswas-  Diener, 2002). Most important for 
the current discussion, research shows that 
at an individual level, correlations tend to 
be positive but small. For instance, Lucas 
and Dyrenforth (2006) reviewed evidence 
from two meta-  analyses (Haring, Stock, & 
Okun, 1984; Pinquart & Sörensen, 2000), 
a narrative review of cross-  national results 
(Diener & Biswas-  Diener, 2002), and many 
waves of an annual nationally representa -
tive survey (General Social Survey; Davis, 
Smith, & Marsden, 2003). This review 
showed that the correlation between income 
and happiness tends to fall between .17 and 
.21. The typical interpretation of these data 
is that people overestimate the importance 
of money, and that once people have their 
basic needs met, income does not matter (see Lucas & Schimmack, 2009, for a discus -
sion).
Although we do not dispute the size of the 
correlations that have been found in previ -
ous research, we caution that such correla -
tions need to be interpreted carefully. For 
instance, a .20 correlation would mean that 
each additional standard deviation of income 
would only “buy” one-fifth of a standard 
deviation in happiness. However, income 
standard deviations are quite small relative 
to the range of the distribution. Thus, when 
people’s intuitions suggest that money will 
make them happier, they may by concerned 
with moving closer to the endpoint of the 
distribution rather than just moving up one 
or two standard deviations. Even with a 
relatively weak .20 correlation, the intuition 
that money matters could still be correct (see 
Lucas & Schimmack, 2009, for a more com -
plete discussion and illustration).
Additional interpretational concerns 
about the importance of external circum -
stances arise when inappropriate measures 
of the predictor variables are used. This 
problem can be illustrated by examining the 
association between health and well-being. 
Correlations with health tend to be small to 
moderate in size. Okun, Stock, Haring, and 
Witter (1984) conducted a meta-  analysis 
of over 200 effect sizes and found correla -
tions around .30. Similarly, Brief, Butcher, 
George, and Link (1993) found that subjec -
tive reports of health tended to correlate be -
tween .30 to .40 with life satisfaction. Ef -
fects of this size might suggest that health 
plays a reasonably important role in SWB. 
However, both groups of researchers have 
suggested that when more objective mea -
sures of health are obtained, the correlation 
drops close to zero. For instance, Okun and 
George (1984) found that physician ratings 
of health were not correlated with well-
being, and Brief et al. (1993) found that 
the number of doctor visits only correlated 
about .10 with life satisfaction.
Although some have suggested that this 
type of discrepancy provides evidence that 
self- reports of health are not valid (e.g., Die -
ner et al., 1999; Kahneman & Riis, 2005), 
there are some indications that the opposite 
might be true. Self-  reports may in fact be 
more valid than other objective measures. 
For instance, self-  reports of health predict 