Choice and Happiness in South Africa
Andrea Szabó
Gergely Ujhelyi
Department of Economics
Department of Economics
University of Houston
University of Houston
aszabo2@uh.edu
gujhelyi@uh.edu
December 8, 2015
Abstract
Do people choose what makes them feel happy or do they pursue other goals instead?
Benjamin, He¤etz, Kimball, and Rees-Jones (2012) present a methodology to study
this question and provide results for US samples. We replicate their methodology in a
sample taken from low-income South African townships. We …nd that in this sample
people almost always choose what makes them feel happy. In addition, respondents
perceive little con‡ict between own happiness and other relevant determinants of choice
such as sense of purpose and family happiness.
1
Introduction
There are well-documented cases where people’s choices do not appear to maximize their
happiness. For example, those who choose to work longer hours are less happy than others
(Di Tella and MacCulloch, 2008), and having children does not seem to make people happier
(Hansen, 2012; Stanca, 2012). Benjamin, He¤etz, Kimball, and Rees-Jones (2012), BHKR
from now on, examine this question directly and report that in hypothetical choice situations
between 5 and 38 percent of respondents say that they would choose the option that would
make them less happy. At least some of the time, for at least some measures, people’s choices
appear to have goals other than increased happiness.1
Direct evidence on the extent to which happiness guides choices is scarce and no study
that we know of has been conducted outside of the richest countries.2 This is an important gap because understanding what contributes to happiness is particularly important for
public policy (Layard, 2006; Loewenstein and Ubel, 2008). For example, policy experiments
advocated in developing countries are often based on the notion that self-control problems,
lack of information, or other constraints prevent people from making “optimal”choices. At
the same time, we seem to know little about the objectives that people seek when making
these choices. Is the pursuit of happiness equally important among the poor and the rich?
We use the methodology proposed by BHKR to study people’s choices and happiness in
a low income population in a group of South African townships near Pretoria. We confront
survey respondents with hypothetical choice scenarios, for example, would they choose to
travel to an important social event (a friend’s wedding), or would they rather save the time
and money and stay at home? Would they choose a job with a higher salary where they
would make less than others at the …rm, or one with a lower salary where they would make
more than others? Then, we ask them which choice would make them happier or help them
ful…ll some of their other goals in life, such as their family’s happiness, good health, or a
sense of purpose.3
1
BHKR show that there are di¤erences between measures, e.g., between those capturing people’s life
satisfaction, happiness with life as a whole, or their current feelings of happiness (see also Diener et al., 2010
and Deaton et al., 2010). As described below, our main measure asks about feelings of happiness immediately
after making a choice. BHKR found this type of measure to be the least predictive of choice.
2
While the literature on the economics of happiness has traditionally focused on OECD countries, the
number of studies conducted in developing countries has grown in recent years. Examples include Ravallion
and Lokshin (2002), Kingdon and Knight (2007), Appleton and Song (2008), Deaton et al. (2010), Fontaine
and Yamada (2014), and Stillman et al. (2015). Our work di¤ers from these studies by focusing on the
relationship between choice and happiness rather than on the determinants of happiness.
3
In the psychology literature, studies using similar methods include Tversky and Gri¢ n (1991) and Hsee
et al. (2003). In economics, see also Benjamin et al. (2014). One may object to this methodology, e.g., on
the grounds that respondents may have di¢ culty predicting how they would feel in a choice situation. In
this paper, we simply accept the methodology at face value and study whether it yields di¤erent results in
2
We have three main results. First, we …nd that respondents mostly choose the option that
makes them feel happier. Across all scenarios, choice and happiness coincide in 87 percent of
the cases, with little variance between scenarios. It is noteworthy that our questions explicitly
ask about a¤ect (feelings of happiness) rather than judgement (life satisfaction). The former
is typically viewed as a weaker predictor of choices, which makes the concordance between
choice and happiness in our sample particularly salient. As we emphasize below, while
our procedures are similar, our sample di¤ers from BHKR’s in many dimensions (income,
education, language, etc.) and one must therefore be cautious in drawing comparisons.
Subject to these caveats, in this South African sample happiness seems to predict choices
more than it did in the US.
Second, like BHKR we identify certain goals, notably achieving a sense of purpose and
family happiness, which are strong determinants of choices apart from happiness. Interestingly, in previous surveys respondents in the US and elsewhere rated these same goals as
being highly important (Ry¤, 1989; Diener and Oishi, 2004). The principal goals driving
choices in our low-income South African sample are similar to those identi…ed as important
elsewhere in the world.
Our third result resolves the tension between the …rst two set of …ndings, that happiness is
important and that, at the same time, other goals are also important. In general, respondents
in our study perceive little con‡ict between happiness and other goals. People in our sample
tend to view choices that make them happy as also contributing to their other goals in life.
This di¤ers somewhat from the US results and suggests that, in our context, it is possible for
people to simultaneously achieve happiness and other goals. We also show that individual
characteristics, such as marital status or the number of children in the household, a¤ect the
extent to which these various objectives can be reconciled.
In the rest of the paper, Section 2 describes our research design, Section 3 presents the
results, and Section 4 compares our results to BHKR’s. Section 5 discusses robustness and
Section 6 concludes.
2
2.1
Research design
Study environment
We conducted our surveys in a group of townships about an hour’s drive north of Pretoria
(Mabopane, Ga-Rankuwa, and Winterveldt). The setting is typical of peri-urban areas in
many African countries, featuring a combination of informal shacks, (single-family) governour context.
3
ment housing, and some larger single-family homes. Most of the infrastructure is relatively
well-developed (all households have running water, there is a large number of paved roads).
The average household size in our sample is slightly above 4, with one member employed.
Average monthly household income reported in our survey is around 6000 Rand ( 600
USD), and two-thirds of the respondents completed high school. These …gures are close to
those reported by the South African statistical agency for the average Black household in
the country.4 While there are clearly many dimensions in which our setting di¤ers from
BHKR’s (see Section 4) we believe comparing results from the two studies can provide at
least suggestive comparisons between samples from a developed and a developing country.
2.2
Survey design
The starting point for our design was BHKR’s “Cornell study,”because this is the only one
allowing for an analysis of which life goals besides happiness a¤ect choices. We presented
respondents with 8 hypothetical choice scenarios, 7 of which were directly adapted from
BHKR, adjusting for the South African context.5 For example, in one scenario we asked
participants to imagine choosing between a job that pays R6000 (about $600) a month and
allows 7.5 hours of sleep each day and one that pays R10,000 (about $1000) but only allows 6
hours of sleep. The same question appears in BHKR with income …gures of $80,000 per year
for 7.5 hours of sleep or $140,000 per year for 6 hours of sleep. For scenarios involving money,
we chose the monetary …gures to be comparable round …gures to those in BHKR, adjusting
for income di¤erences. In the above scenario, the R6000 …gure is slightly higher than the
average household income reported by our respondents, and it is 60% of the alternative
choice being o¤ered. In some cases, adjustments were necessary for the social and economic
context. For example, we replaced traveling home for Thanksgiving by plane with traveling
to a friend’s wedding by bus. Like BHKR, we also included a scenario where choice and
happiness was predictable in order to test the validity of the methodology. This involved a
choice between an apple or an orange, where BHKR predicted and found very few reversals
and a particularly large e¤ect of happiness on choice (as it turns out, in South Africa this
scenario is a useful test on the methodology for reasons very di¤erent from the US, see Section
3.1). Finally, we included an 8th scenario involving a choice between luxury consumption
(buying a nicer meal than usual) and paying down debt, because we thought this was a
particularly realistic choice situation in our setting. The full list of choice scenarios is given
4
Average monthly income: R 5,803, household size: 3.98, unemployment rate: 40%. Source: Statistics
South Africa (http://beta2.statssa.gov.za/)
5
We took 6 scenarios (BHKR’s 1, 3, 5, 6, 8, and 10) from the Cornell study. These include the only
scenario asked in the CNSS study and two of the scenarios in the Denver study. We added a 7th scenario
(BHKR’s 13) that only appeared in the Denver study.
4
in the Appendix.
After each scenario, we asked the respondents which option they think they would choose.
We also asked them how each option would make them feel in terms of a variety of possible
goals including their own subjective well-being (SWB), their family’s happiness, their health,
their social life, etc. Speci…cally, we asked “Between these two options, in the few minutes
immediately after making the choice, which option do you think would make you feel better in
terms of... your own happiness / your family’s happiness / etc.”Note that in this formulation
our measure of SWB explicitly asks about instantaneous feelings of happiness. We are not
measuring more evaluative notions like life satisfaction.
Responses were on a 6-point scale for choices (1 = De…nitely choose option 1, 2 =
Probably choose option 1, ..., 6 = De…nitely choose option 2) and on a 7-point scale for
happiness and other goals (1 = Option 1 would de…nitely feel better, ..., 4 = No di¤erence,
..., 7 = Option 2 would de…nitely feel better). Importantly, as in BHKR’s Cornell study,
the scale for happiness and other life goals includes a “No di¤erence” option. To facilitate
at least suggestive comparisons to the CNSS and Denver studies, we also included another
version of the happiness question: “If you were limited to these two options, which do you
think would make you feel happier?”This was a stand-alone question (without the other life
goals), did not specify “in the few minutes immediately after making the choice,” and the
response scale did not allow for an indi¤erence option (it used the same 6-point scale as the
choice question).
In some of the analysis below, we collapse the choice question to a binary variable indicating which option the respondent would be more likely to choose. Similarly, we sometimes
collapse the SWB question using a binary variable to represent which option would more
likely make the individual happier (excluding responses indicating indi¤erence). Each respondent was randomly given one of four di¤erent versions of the questionnaire. The questions
asked were always the same, but the versions di¤ered in the order in which speci…c questions
or scenarios were presented. In the robustness analysis of section 5 below we compare the
di¤erent versions to check for questionnaire e¤ects.
As part of the survey, we also collected various socio-economic characteristics of the
respondents, including age, education, marital status, household size, and income, among
others. We present more details on these variables in Section 3.3 below.
2.3
Sampling and implementation
We randomly sampled 1000 households from the full list of residential addresses in the
townships of Mabopane, Ga-Rankuwa, and Winterveldt. The original sampling was done for
5
a project on residential water consumption (Szabó and Ujhelyi, 2015), and we included our
choice scenarios at the end of the last survey for that project. All households were surveyed in
February 2013. Our surveyors visited each address and interviewed an adult member of the
household.6 Surveys were conducted face to face at the respondent’s home. Our surveyors
received special training for this project; they are local residents employed by a survey and
market research company with extensive experience working in the area. Questionnaires
were available in both English and the local language (Setswana). 34 households could not
be located or refused to participate, resulting in a sample size of 966. Histograms of our
raw data on the answers to the choice, SWB and other life goal questions appear in the
Appendix.
3
3.1
Results
Choice-SWB reversals
Table 1 shows the distribution of answers to the choice and SWB questions using binary
measures. Each column corresponds to a di¤erent scenario. The …rst four cells in each
column are restricted to respondents who did not view the two options as providing the
same level of SWB and the fraction of respondents stating indi¤erence is shown in the …fth
row of the table. For example, the …rst cell in the …rst column reveals that 15 percent of
non-indi¤erent respondents would choose a job with more sleep and less pay and say that
this option would make them happier. Similarly, the second cell shows that 72 percent would
choose the job with less sleep and more pay and would feel happier with this option. Of
particular interest are the 3rd and 4th rows: these show the fraction of respondents exhibiting
a “choice-SWB reversal.”In the third cell of the …rst column, 7 percent of respondents would
choose more sleep but think that the job with more income would make them happier, and
5 percent exhibit a reversal in the opposite direction.
In our sample, people mostly choose the option that makes them happier. Across all
scenarios, choice and happiness coincide in 87 percent of the cases. The fraction of choicehappiness concordance for individual scenarios falls in a tight range: between 84 and 90
percent. These numbers are remarkably large, especially since we explicitly ask about a¤ect
(feelings of happiness), which BHKR found to be less predictive of choice than more evaluative notions of happiness (e.g., life satisfaction). In this South African sample, choices are
highly correlated with instantaneous feelings of happiness.
6
More impersonal survey methods, such as phone surveys or self-administered questionnaires would not
have been practical in our context.
6
7
10.98
4.75
1.35
0.0000
947
5.47
1.14
0.1455
950
34.21
72.21
7.26
Money
versus
Time
%
50.05
Sleep
versus
Income
%
15.05
1.14
0.0000
947
4.22
9.29
75.29
Friends
versus
Income
%
11.19
3.21
0.0901
934
5.68
7.82
45.12
Friends/Family
versus
Money
%
41.37
1.24
0.0001
948
4.96
10.13
57.28
Fun
versus
Debt
%
27.64
2.08
1.0000
939
4.9
4.79
23.43
Money
versus
Time, v. 2
%
66.88
0.93
0.0057
953
3.78
6.82
20.36
Abs. Inc.
versus
rel. inc.
%
69.05
4.25
0.0000
921
3.37
11.62
37.13
Apple
versus
Orange
%
47.88
Notes: For each scenario, the …rst four rows present the distribution of responses among those who did not indicate indi¤erence for
the SWB question. The fraction of indi¤erent SWB responses is indicated in the …fth row. The Liddell test tests the hypothesis
that the average choice response is equal to the average SWB response for paired data. The text of each scenario appears in the
Appendix.
Higher SWB: Option 1
Chosen: Option 1
Higher SWB: Option 2
Chosen: Option 2
Higher SWB: Option 2
Chosen: Option 1
Higher SWB: Option 1
Chosen: Option 2
Indi¤erence for SWB
p-value of Liddell Exact Test
N
Choice scenario
Table 1: Choice and SWB responses across scenarios
One scenario that requires some discussion is the “test” scenario involving a choice between two free snacks, an apple or an orange. BHKR included this question because response
patterns are predictable (in the US context, one would expect few reversals), thus providing
a check on the methodology. In the South African case we …nd that this scenario yields
one of the largest fraction of reversals (15 percent). It turns out that, in this context, these
patterns also provide support for the methodology. As we became aware after the conclusion
of our survey, there exists in South Africa a powerful urban legend about somebody handing
out free oranges infected with HIV. This conspiracy theory, going back to the 1990s, was
documented to be part of the local culture as recently as 2011 (Sivela, 2012). Such beliefs
mean that this choice scenario should involve trade-o¤s between own happiness (a taste for
a fruit) and other goals, health in particular, especially for those who like oranges. Indeed,
we …nd that while our respondents were evenly split between assigning higher SWB to apples or oranges, this scenario yielded the largest di¤erence in reversals. 24 percent of those
preferring oranges based on SWB said that they would choose an apple, while only 7 percent
of those preferring apples would choose an orange. Below, we also …nd direct evidence that
concerns about health and romantic life were strong determinants of choice in this scenario.
In the South African context, these patterns make perfect sense and are exactly what one
would expect in the presence of beliefs about HIV infected oranges.7
3.2
Determinants of choice
What other factors besides own happiness explain choices, and how strong is own happiness
as a determinant of choice relative to these? Table 2 presents regressions of choice on own
happiness and other factors. For OLS regressions, all variables are demeaned at the scenario
level to control for di¤erences across scenarios. In column 1, we see that 49 percent of the
variation in choice is explained by own happiness alone. This con…rms the strong association
between choice and happiness documented in the previous section. The next column excludes
own happiness but includes the other 11 goals. This results in an R2 similar to the …rst
column: excluding own happiness, other factors are also important determinants of choices.
The largest coe¢ cients are on family happiness and sense of purpose: these goals are highly
correlated with choices in our sample.
The …nding that choices closely re‡ect family happiness and sense of purpose echoes the
7
Another noteworthy feature of Table 1 is that respondents always prefer more money, both in terms of
choice and SWB. For example, in the …rst column, 78% would choose more income and less sleep and 79%
predict that more income would yield higher SWB. We observe a similar pattern in the remaining scenarios:
respondents prefer to save money rather than time, earn more rather than live among friends, save money
rather than go to a wedding, get money now rather than later, and have a higher absolute income rather
than a higher relative income. This is of course what one would expect given the low incomes in the sample.
8
results from a series of interviews reported by Clark (2003) who collected what people in
two South African townships thought to be important aspects of a “good life.” The top
four aspects mentioned were having a job, housing, an education, and adequate income.
In our context these are likely to increase one’s sense of purpose (interpreted as “knowing
what to do”). The …fth most important aspect mentioned was a good family (respondents
explained that this was valued because of the support it provided in times of need). It is
also noteworthy that these same aspects are also typically rated as being highly important
in surveys in other countries (e.g., Ry¤, 1989; Diener and Oishi, 2004). We …nd that the
goals rated as important in the US and elsewhere are also highly correlated with choices in
our low-income South African sample.
The third column of Table 2 includes all 12 goals. This results in little change in explanatory power but large drops in individual coe¢ cients compared to the …rst two columns.
This pattern indicates the presence of multicollinearity: it suggests that respondents tend
to view choices that are more conducive to one goal (e.g., own happiness) as useful for the
attainment of other goals as well. We con…rm this directly in Table 3 where we regress the
score on own happiness on the other 11 goals. Across all scenarios, these goals explain 86
percent of the variation in which option makes a person happier. For the individual scenarios, this R2 is always above 80 percent. In our sample, respondents appear to perceive little
con‡ict between SWB and other goals in life.
9
Table 2: Regressions of choice on SWB and other goals
OLS
Own happniess
0.569***
(0.007)
Family happiness
Health
Life’s level of romance
Social life
Control over your life
Life’s level of spirituality
Life’s level of fun
Social status
Life’s nonboringness
Physical comfort
Sense of purpose
Observations
(pseudo) R2
7451
0.4867
0.250***
(0.024)
0.090***
(0.024)
-0.013
(0.023)
0.032
(0.023)
0.036*
(0.021)
-0.042**
(0.020)
0.031
(0.020)
0.029
(0.023)
-0.066***
(0.022)
0.023
(0.025)
0.260***
(0.022)
7451
0.4899
0.312***
(0.024)
0.136***
(0.025)
0.028
(0.024)
-0.028
(0.022)
-0.005
(0.022)
0.011
(0.021)
-0.059***
(0.019)
0.040**
(0.019)
0.010
(0.023)
-0.048**
(0.022)
0.020
(0.024)
0.197***
(0.022)
7451
0.5104
Ordered Probit
0.247***
(0.019)
0.111***
(0.020)
0.018
(0.020)
-0.018
(0.019)
-0.009
(0.019)
0.002
(0.019)
-0.071***
(0.018)
0.025
(0.018)
0.011
(0.020)
-0.081***
(0.020)
0.003
(0.021)
0.191***
(0.019)
7451
0.2392
Probit
0.195***
(0.021)
0.173***
(0.023)
0.014
(0.024)
0.017
(0.024)
-0.041*
(0.024)
0.041*
(0.023)
-0.102***
(0.024)
0.090***
(0.022)
-0.002
(0.026)
-0.009
(0.026)
0.029
(0.027)
0.107***
(0.022)
7451
0.4907
Notes: The dependent variable is choice on a 6-point scale for OLS and Ordered Probit, and on a
binary scale for Probit. All independent variables are on a 7-point scale. Variables are demeaned at
the scenario level for the OLS regressions. Ordered Probit and Probit regressions include scenario
…xed e¤ects. Robust standard errors in parentheses. ***, **, * denote signi…cance at the 1, 5, and
10 percent, respectively.
10
11
All
scenarios
pooled
0.368***
(0.025)
0.200***
(0.022)
0.050**
(0.024)
0.122***
(0.023)
0.078***
(0.020)
0.052***
(0.018)
-0.026
(0.016)
0.062***
(0.021)
-0.059***
(0.018)
0.009
(0.022)
0.201***
(0.021)
7473
0.860
Sleep
versus
Income
0.399***
(0.063)
0.162***
(0.051)
0.084
(0.057)
0.049
(0.053)
0.086*
(0.051)
0.001
(0.042)
-0.030
(0.037)
0.000
(0.044)
-0.035
(0.043)
0.068
(0.047)
0.259***
(0.048)
937
0.855
Money
versus
Time
0.332***
(0.060)
0.210***
(0.054)
0.127*
(0.065)
0.121**
(0.053)
0.170***
(0.052)
0.038
(0.045)
-0.100**
(0.043)
0.070
(0.058)
-0.085**
(0.041)
-0.029
(0.059)
0.204***
(0.054)
939
0.896
Friends
versus
Income
0.191***
(0.064)
0.296***
(0.063)
0.038
(0.062)
0.013
(0.052)
0.159***
(0.051)
0.031
(0.044)
0.015
(0.048)
0.046
(0.057)
-0.080*
(0.047)
0.024
(0.055)
0.295***
(0.060)
934
0.821
Friends/Family
versus
Money
0.466***
(0.060)
0.222***
(0.052)
0.048
(0.060)
0.036
(0.053)
0.064
(0.045)
0.067*
(0.037)
-0.065**
(0.029)
0.118***
(0.045)
-0.034
(0.045)
0.023
(0.052)
0.139***
(0.047)
933
0.896
Fun
versus
Debt
0.362***
(0.071)
0.314***
(0.064)
0.104
(0.074)
0.134**
(0.064)
-0.007
(0.054)
0.057
(0.042)
-0.032
(0.040)
-0.009
(0.055)
-0.048
(0.047)
0.026
(0.068)
0.135**
(0.053)
931
0.875
Money
versus
Time, v. 2
0.380***
(0.066)
0.213***
(0.059)
0.068
(0.051)
0.046
(0.049)
0.018
(0.049)
-0.027
(0.039)
0.032
(0.042)
0.095*
(0.050)
0.006
(0.043)
-0.005
(0.056)
0.234***
(0.048)
932
0.877
Abs. Inc.
versus
Rel. inc.
0.412***
(0.075)
0.231***
(0.063)
-0.045
(0.061)
0.344***
(0.080)
-0.034
(0.049)
-0.052
(0.051)
-0.001
(0.045)
0.082
(0.066)
0.004
(0.046)
-0.028
(0.057)
0.141***
(0.047)
931
0.897
Apple
versus
Orange
0.340***
(0.071)
0.115**
(0.056)
-0.040
(0.071)
0.195***
(0.071)
0.080
(0.072)
0.292***
(0.073)
0.040
(0.074)
0.039
(0.071)
-0.112
(0.070)
0.022
(0.088)
0.099
(0.073)
936
0.801
Notes: Happiness regressed on other goals. All variables are on a 7-point scale and demeaned at the scenario level. Robust standard errors in
parentheses. ***, **, * denote signi…cance at the 1, 5, and 10 percent, respectively.
Observations
R2
Sense of purpose
Physical comfort
Life’s nonboringness
Social status
Life’s level of fun
Life’s level of spirituality
Control over your life
Social life
Life’s level of romance
Health
Family happiness
Choice scenario
Table 3: The correlation between happiness and other life goals
3.3
3.3.1
Heterogeneity
Heterogeneity between scenarios
To explore the heterogeneity of our …ndings across scenarios further, Table 4 presents regressions similar to those in Table 2 separately by scenario (the …rst column reproduces column
3 from Table 2 for comparison). For each scenario, choice is …rst regressed on SWB and
then we add the other life goals. The table presents the latter regressions, and indicates the
change in R2 as the 11 life goals are added.
We note that the incremental R2 is highest for decisions that are most realistic in the
context of the study (being asked to contribute time vs. money at a child’s school, spending
a small unexpected bonus on having fun vs. ful…lling a debt obligation, choosing between an
apple and an orange). These scenarios, which are the closest to decisions respondents may
face in everyday life, are most a¤ected by additional life goals besides happiness. Interestingly, this is exactly what BHKR …nd in the US, where decisions deemed most relevant for
respondents also resulted in the highest incremental R2 :
Recall that the decision making process in the apple vs. orange scenario is partially
predictable due to the urban legend about oranges infected with HIV. Indeed, we see that
health considerations are particularly important determinants of choice in this scenario, as
is respondents’concern about their romantic life.
12
13
All
scenarios
pooled
0.312***
(0.024)
0.136***
(0.025)
0.028
(0.024)
-0.028
(0.022)
-0.005
(0.022)
0.011
(0.021)
-0.059***
(0.019)
0.040**
(0.019)
0.010
(0.023)
-0.048**
(0.022)
0.020
(0.024)
0.197***
(0.022)
7451
0.510
0.034
Sleep
versus
Income
0.308***
(0.066)
0.113
(0.070)
-0.012
(0.054)
0.021
(0.057)
0.068
(0.062)
0.004
(0.056)
-0.039
(0.050)
-0.068
(0.047)
0.022
(0.058)
0.007
(0.060)
0.018
(0.060)
0.092*
(0.055)
935
0.408
0.001
Money
versus
Time
0.287***
(0.069)
0.029
(0.063)
-0.032
(0.070)
-0.019
(0.063)
0.014
(0.061)
-0.090
(0.061)
-0.069
(0.052)
0.158***
(0.059)
0.011
(0.065)
-0.174***
(0.059)
-0.015
(0.075)
0.443***
(0.067)
937
0.486
0.056
Friends
versus
Income
0.300***
(0.072)
0.113*
(0.066)
0.066
(0.060)
-0.101
(0.062)
0.019
(0.051)
-0.063
(0.056)
-0.012
(0.050)
0.086*
(0.051)
-0.050
(0.066)
-0.114*
(0.059)
0.029
(0.064)
0.229***
(0.063)
929
0.365
0.036
Friends/Family
versus
Money
0.278***
(0.068)
0.193***
(0.073)
-0.002
(0.076)
0.075
(0.065)
-0.026
(0.065)
0.097*
(0.057)
-0.153***
(0.054)
0.018
(0.042)
0.086
(0.062)
-0.120*
(0.069)
0.068
(0.065)
0.146**
(0.066)
932
0.581
0.039
Fun
versus
Debt
0.348***
(0.066)
0.221***
(0.073)
-0.082
(0.066)
-0.100
(0.067)
0.013
(0.065)
0.072
(0.058)
-0.096*
(0.056)
-0.037
(0.059)
0.091
(0.060)
-0.034
(0.064)
0.009
(0.067)
0.209***
(0.061)
926
0.530
0.050
Money
versus
Time, v. 2
0.304***
(0.066)
0.268***
(0.065)
-0.067
(0.057)
-0.019
(0.053)
0.034
(0.046)
0.058
(0.048)
-0.094**
(0.043)
0.055
(0.046)
-0.048
(0.053)
-0.019
(0.051)
0.015
(0.053)
0.211***
(0.052)
929
0.633
0.037
Abs. Inc.
versus
Rel. inc.
0.352***
(0.072)
0.136*
(0.081)
0.007
(0.071)
-0.008
(0.061)
-0.037
(0.062)
-0.009
(0.057)
-0.071
(0.054)
0.098*
(0.054)
0.085
(0.061)
-0.101*
(0.058)
0.015
(0.066)
0.184***
(0.060)
930
0.603
0.042
Apple
versus
Orange
0.298***
(0.058)
0.047
(0.067)
0.171***
(0.058)
-0.169**
(0.067)
-0.038
(0.073)
-0.057
(0.064)
0.081
(0.072)
0.112
(0.076)
-0.108
(0.079)
0.156**
(0.074)
0.056
(0.079)
0.092
(0.064)
933
0.513
0.069
Notes: OLS regressions. The dependent variable is choice on a 6-point scale and all independent variables are on a 7-point scale. Variables are
demeaned at the scenario level. Incremental R2 is the change in the R2 of the regression as the 11 goals other than own happiness are added. Robust
standard errors in parentheses. ***, **, * denote signi…cance at the 1, 5, and 10 percent, respectively
Observations
R2
Incremental R2
Sense of purpose
Physical comfort
Life’s nonboringness
Social status
Life’s level of fun
Life’s level of spirituality
Control over your life
Social life
Life’s level of romance
Health
Family happiness
Own happniess
Choice scenario
Table 4: Regressions of choice on happiness and other goals, by scenario
3.3.2
Heterogeneity between individuals
Which respondents are more likely to exhibit choice-SWB reversals and which ones tend
to choose what makes them happy? In Table 5 we look at this question by regressing the
incidence of reversals on various individual characteristics of the respondents. These were
collected as part of the survey, and include the respondent’s gender, age, marital status,
household size (adults and children), highest level of education, and household income. For
the latter, we have 143 missing values. To maximize the number of observations and limit
measurement error, we use observed income and ownership of various household appliances
to predict household income (in logs), and use these predicted values for the entire sample.8
In the …rst column of Table 5, our dependent variable is the number of scenarios in which
the respondent exhibited a reversal. In the remaining columns, the dependent variable is 1 if
the respondent exhibited a reversal in the given scenario, and 0 otherwise. In all regressions,
respondents who indicated indi¤erence in the SWB question are coded as missing. The
regressions in Table 5 are estimated with OLS. For the individual scenarios, Table 12 in the
Appendix presents similar results from Probit regressions.
The regressions in this table tend to paint a consistent picture: the same types of respondents are likely to exhibit reversals in all scenarios. We …nd that choice-SWB reversals
are signi…cantly less likely among men, older respondents, widowers, and those with fewer
children. Given our earlier results, these patterns make perfect sense. As we saw in Section
3.2, one’s family’s happiness was one of the strongest correlates of choice apart from SWB.
Thus, we would expect respondents for whom family is more important to exhibit more reversals, and respondents for whom family carries less weight to more often base their choices
on own happiness. This is exactly what we …nd: older men, widowers, and those with fewer
children are likely to attach less importance to family, and they are particularly likely to
choose what makes them personally happy.
8
Predicted income is based on the regression ln(Y + 1) = X + " where Y is reported income in Rand,
and X includes ownership of the following: hot running water, TV, DVD player, car, cellphone, refrigerator.
14
15
-0.238**
(0.116)
-0.014**
(0.006)
0.119
(0.448)
-0.391**
(0.163)
0.045
(0.144)
0.028
(0.044)
0.103**
(0.044)
0.325
(0.203)
-0.158
(0.205)
-0.222
(0.607)
0.088
(0.189)
818
Male
Sleep
versus
Income
-0.054**
(0.022)
-0.001
(0.001)
-0.032
(0.061)
-0.103***
(0.030)
0.017
(0.028)
-0.005
(0.009)
0.002
(0.007)
0.028
(0.048)
-0.038
(0.049)
-0.158
(0.118)
0.058
(0.037)
939
Money
versus
Time
-0.049**
(0.024)
-0.001
(0.001)
-0.031
(0.070)
-0.075*
(0.043)
-0.012
(0.029)
-0.001
(0.010)
0.012
(0.009)
0.100*
(0.051)
-0.015
(0.051)
-0.071
(0.126)
0.017
(0.040)
937
Friends
versus
Income
-0.081***
(0.022)
-0.002*
(0.001)
-0.062
(0.062)
-0.120***
(0.034)
-0.032
(0.028)
0.007
(0.009)
-0.004
(0.008)
0.103**
(0.043)
-0.012
(0.044)
0.058
(0.118)
-0.012
(0.037)
936
Friends/Family
versus
Money
-0.036
(0.023)
-0.002*
(0.001)
-0.013
(0.061)
-0.002
(0.043)
0.015
(0.027)
0.012
(0.010)
0.015*
(0.009)
0.046
(0.049)
-0.010
(0.050)
-0.059
(0.124)
0.029
(0.039)
924
Fun
versus
Debt
-0.020
(0.024)
-0.004***
(0.001)
-0.034
(0.059)
-0.117***
(0.033)
-0.018
(0.029)
0.010
(0.010)
0.031***
(0.010)
-0.012
(0.056)
-0.095*
(0.056)
-0.106
(0.154)
0.041
(0.047)
937
Money
versus
Time, v. 2
-0.002
(0.020)
-0.003***
(0.001)
0.021
(0.055)
0.022
(0.036)
-0.003
(0.024)
-0.006
(0.007)
0.014**
(0.006)
0.033
(0.027)
0.006
(0.029)
-0.244*
(0.130)
0.083**
(0.040)
928
Abs. Inc.
versus
Rel. inc.
-0.010
(0.020)
-0.003**
(0.001)
-0.028
(0.048)
-0.061**
(0.030)
-0.000
(0.025)
-0.002
(0.007)
0.016**
(0.007)
0.026
(0.040)
-0.036
(0.041)
0.065
(0.084)
-0.016
(0.027)
942
Apple
versus
Orange
0.007
(0.024)
-0.003***
(0.001)
0.075
(0.076)
-0.056
(0.040)
0.009
(0.029)
-0.010
(0.009)
0.022***
(0.009)
0.060
(0.050)
-0.004
(0.052)
-0.279*
(0.150)
0.076*
(0.045)
911
Notes: OLS regressions. In the …rst column, the dependent variable is a respondent’s total number of choice-SWB reversals; in the other columns it is
an indicator equal to 1 if the respondent exhibited a reversal in the given scenario. ‘Primary school’is 1 if the respondent’s highest level of completed
education is primary school; ‘High school’is 1 if it is high school or above. Income is measured in logs and predicted based on ownership of household
appliances as described in the text. All regressions include a constant. Robust standard errors in parentheses. ***,**,* denote signi…cance at the 1,
5, and 10 percent, respectively.
Observations
Income squared
Income
High school
Primary school
Number of children
Number of adults in the HH
Single
Widowed
Divorced
Age
Total
reversal
Choice scenario
Table 5: Reversals and respondent characteristics
4
Comparison with BHKR
How do our …ndings compare to BHKR’s? Before turning to this issue, we must discuss two
basic questions: what to compare, and how to interpret the comparisons.
4.1
What to compare?
BHKR analyze 29 survey versions across 3 samples, using two di¤erent survey methods.
Reproducing this rich design was not possible in our context. An immediate implication is
that not every result in BHKR will have a meaningful counterpart in our study. Because we
believe that studying other correlates of choices besides happiness is important, the starting
point for our design was the only study that allowed for this, BHKR’s Cornell study. As
described in Section 2, most choice scenarios, the wording of our main happiness question,
and the response scale were all based on this study.
It is plausible that these design choices could matter for the results. First, recall that the
SWB question included the option for respondents to indicate that they were indi¤erent (and
indi¤erent respondents were excluded when computing the fraction of SWB-choice reversals
/ concordances). This can potentially a¤ect the results through framing e¤ects, or because
indi¤erent respondents are forced to indicate either a reversal or a concordance when the
indi¤erence option is not present. Our results below show that, within our sample, we get
fewer reversals when the indi¤erence option is not included.
Second, in the Cornell study the SWB question asked exclusively about “happiness:”
happiness with life as a whole and immediately felt own happiness. Apart from these two
questions, the Denver study also contained a question on “life satisfaction.” In the Cornell
study, there was no signi…cant di¤erence in the explanatory power of the two happiness
measures for choices. By contrast in the Denver study life satisfaction had a signi…cantly
higher explanatory power for choice than immediately felt own happiness, while happiness
with life as a whole did not result in statistically signi…cant di¤erences compared to either of
the other two measures. The CNSS study only asked about happiness with life as a whole.
Whether or not these di¤erences in design caused the Cornell results to be di¤erent
from BHKR’s other two studies cannot be formally established. Because BHKR observe
considerably more reversals in the Cornell sample than in the other two samples (BHKR,
p2093-4), this suggests that design features could be important. We conclude that the safest
comparison of our …ndings described above is with the Cornell results.
It is of course always possible to …nd dimensions in which our study is closer to one of
the other BHKR samples (see below). To allow some comparison of our results to the other
two studies our surveys also included a version of the SWB question that did not allow for
16
indi¤erence, was asked as a stand-alone question without other life goals, and did not refer
to immediately felt happiness (asked about “happiness” rather than “happiness in the few
minutes immediately after making the choice”). We use these results (shown in Table 11
below) when comparing our …ndings to BHKR’s Denver or CNSS study.
4.2
How to interpret the comparisons?
BHKR’s study and ours obviously di¤er in the country where the study is located, but there
are many other di¤erences. These include observable sample characteristics like income, education, and age (especially relative to the Cornell sample). They are also likely to include
various unobservable characteristics stemming from random sampling vs. convenience sampling (in the case of the Denver and Cornell studies). For example, it could be that subjects
who are willing to …ll out a self-administered questionnaire are more or less likely to exhibit
reversals than those who don’t. There is a di¤erence in language and culture, perhaps including how people think of “happiness.”9 There are also several di¤erences in design: we
use a subset of the BHKR scenarios adapted to the local context, and face-to-face interviews
instead of self-administered or telephone questionnaires. The latter is relevant if respondents
are more likely to admit to choice-SWB reversals in impersonal, self-administered surveys
than face-to-face to an interviewer.10
In theory, any of these di¤erences could impact the …ndings, and we cannot formally
test whether they do. In fact, BHKR themselves …nd substantial di¤erences between their
various studies. Thus, one should not attribute the di¤erences in results to any one particular
factor.
Finally, we should mention that there are legitimate questions one may raise regarding
external validity. For example, …nding that our respondents exhibit more SWB-choice reversals in the scenarios in our survey does not rule out the existence of scenarios which we
did not consider that could yield fewer reversals in our sample than in BHKR.
9
While we have no direct evidence of this, our …eldworkers and translators assured us that the word
“happiness” (lethabo) is interpreted similarly in English and Setswana. We are aware of one paper in
psychology studying whether various measures of well-being make sense in Setswana and whether they yield
comparable scales to their English counterpart. That paper concludes that they do (Wissing et al., 2010).
10
This possibility is mitigated by the signi…cant experience of our surveyors. Our …eldworkers are members
of the local community who regularly conduct surveys on topics much more sensitive than ours in this
population, including projects on health or sexual behavior. They are trained to overcome issues of trust
and respondent bias in these delicate situations.
17
0
.2
Density
.4
.6
Figure 1: Number of reversals across respondents
0
2
4
Number of reversals
6
8
Notes: The graph shows the histogram of the number of scenarios for which a respondent exhibited a
choice-SWB reversal.
4.3
Comparing the …ndings
Subject to the caveats above, we now discuss how our results compare to those found in
BHKR’s US samples.
4.3.1
Cornell study
Choice-SWB reversals. The comparison of reversals with BHKR’s Cornell study is summarized in Table 6. In BHKR, the fraction of responses where choice and happiness coincided
was 77 percent, with a range of 62-84 percent across scenarios.11 This is signi…cantly smaller
than the 87 percent, with a range of 84-90, reported in our Table 1. People in our sample
appear to choose what makes them happy more than they do in the Cornell study.12 This
conclusion is con…rmed by looking at the distribution of reversals. In the Cornell study, 82
percent of the subjects had a reversal in at least one scenario (see BHKR’s Web Appendix,
p43). The corresponding fraction in our sample is 38 percent (Figure 1 shows the histogram
of the number of reversals across individuals in our sample).
One obvious di¤erence with the Cornell sample is that our respondents are older on
average. In the Appendix, we calculate Table 1 for respondents under the age of 30, and …nd
very similar results to those shown here, with an average concordance of 86% and a range
of 83-89% across scenarios (third column of Table 6).
11
BHKR, Table 2, excluding the Apple vs. Orange scenario that was designed to generate no reversals.
Including that scenario yields an average of concordance of 78%.
12
This conclusion is una¤ected by excluding the scenario with the largest fraction of reversals from the
Cornell study, or by excluding/including the Apple vs. Orange test scenario in both studies.
18
Table 6: Comparison with BHKR’s Cornell study
BHKR: Cornell
SWB question
In the few minutes immediately after making the choice, which
option do you think
would make you feel
better in terms of your
own happiness? Taking all things together,
which option do you
think would make your
life as a whole better in
terms of your own happiness?
yes
9
333-409
South Africa (Table 1)
South Africa, under
30 only (Table 10)
Between these two options, in the few minutes
immediately after making the choice, which option do you think would make you feel better
in terms of your own happiness?
Indi¤erence allowed
yes
yes
Number of scenarios
7
7
Number of observa921-953
109-114
tions
Frequency of reversals
16-38
10-16
11-17
(%)
Average frequency of
23
13
14
reversals (%)
21
Average frequency of
reversals without Interest vs. Career (%)
Average frequency of
22
13
15
reversals including Apple vs. Orange (%)
Notes: BHKR’s Cornell study summarized based on Table 2 in BHKR (2012). Number of observations
and Frequency of reversals are per scenario. Interest vs. Career is the scenario in BHKR yielding the
largest fraction of reversals.
19
Determinants of choice. Turning to the various determinants of choices (Table 2), our
…ndings show some di¤erences compared to those observed for the US (BHKR, Table 3).
First, the R2 of the univariate regression of choice on happiness is smaller in the BHKR
study (38% vs. 49%). This con…rms the stronger association between happiness and choice
documented in the previous section. Second, and more importantly, in BHKR the explanatory power of SWB for choice changed little when other factors were included in the regression. This indicates that the correlation between the various life goals is smaller in their
sample. This can be con…rmed directly by regressing own happiness on other goals in the
BHKR data: for all scenarios pooled, this yields an R2 of 0.27, compared to 0.86 in the …rst
column of our Table 3. Among our respondents happiness and other life goals seem to be
more closely aligned than in BHKR’s sample.
In everyday life, people’s choices are more likely to maximize their subjective well-being
when other goals are not in con‡ict with it. Therefore, to the extent that our …ndings
generalize to a su¢ ciently large set of actual choices faced in everyday life, we expect people
in South Africa to exhibit higher levels of happiness than in the US. We can test for this
directly using the BHKR data and our study. In both surveys respondents were asked,
separately from the choice scenarios, to rate their actual level of happiness, as well as how
they felt in terms of their other goals.13 Table 7 presents the average ratings in the South
African and US samples on a 1-10 scale (1=bad, 10=good). As can be seen, in spite of
their very di¤erent circumstances, people in South Africa report signi…cantly higher levels of
subjective well-being (“Own happiness”). This makes sense if, compared to the US, trade-o¤s
between the various life goals in this population are less of a constraint to the maximization
of subjective well-being.
Heterogeneity. As already mentioned above, both in BHKR and our study SWB seems
to be a stronger determinant of choices in scenarios that are closest to decisions respondents
are likely to actually face. In terms of heterogeneity across individuals, BHKR do not …nd
individual characteristics to be important determinants of reversals, with the exception that
black respondents in the Cornell sample are signi…cantly more likely to exhibit reversals.
By contrast, in Table 5 we found several characteristics that were associated with reversals.
However, these …ndings are not easily comparable because (i) our sample has no variation
in respondents’race (everyone is black), and (ii) BHKR’s regressions do not include some of
the characteristics which we found to be signi…cant (marital status and number of children).
13
“Thinking about how you felt today, how would you rate ... your own happiness / your family’s happiness
/ etc.”
20
Table 7: How respondents currently feel about their various life goals in South Africa vs.
the US
Own happniess
Family happiness
Health
Life’s level of romance
Social life
Control over your life
Life’s level of spirituality
Life’s level of fun
Social status
Life’s nonboringness
Physical comfort
Sense of purpose
South Africa
N
Mean
961 8.414
(0.062)
961 7.946
(0.068)
961 7.580
(0.072)
961 7.006
(0.079)
961 7.061
(0.070)
961 7.532
(0.068)
961 7.615
(0.068)
961 7.010
(0.072)
961 7.066
(0.075)
962 7.058
(0.078)
962 7.707
(0.071)
961 8.301
(0.066)
Cornell
N
Mean
415 7.636
(0.073)
415 7.455
(0.082)
414 7.860
(0.083)
415 6.101
(0.124)
414 7.292
(0.087)
414 7.254
(0.088)
413 6.015
(0.118)
413 7.249
(0.087)
414 7.072
(0.085)
414 7.147
(0.091)
413 7.659
(0.077)
415 7.520
(0.090)
Di¤erence
p-value
0.0000
0.0000
0.0220
0.0000
0.0572
0.0198
0.0000
0.0534
0.9624
0.5019
0.6882
0.0000
Notes: Each goal was rated on a 10 point scale. The …rst two columns
refer to our South African data, the following two to the comparable
US survey in BHKR (Cornell sample).
The US data is available at
http://dx.doi.org/10.1257/aer.102.5.2083. Standard errors in parentheses. The
last column is the p-value for the equality-of-means t-test.
21
4.3.2
Denver and CNSS studies
As discussed above, BHKR’s Denver and CNSS studies have fewer elements in common with
our design. One potentially important di¤erence is that the happiness question in these
samples did not allow respondents to indicate indi¤erence. Thus, in these studies indi¤erent
respondents were forced to indicate either a choice-SWB reversal or a concordance (or say
that they don’t know or leave the question blank). To obtain at least suggestive comparisons,
we also included a happiness question without the indi¤erence option in our survey. As in the
Denver and CNSS studies, this was included as a stand-alone question not grouped together
with the other 11 life goals. Responses were on a 6-point scale which we transform to a
binary scale as above.14
Our …ndings for this question are in Table 11 in the Appendix. Compared to the results
in Table 1 where indi¤erence was allowed, we now …nd more concordance in every scenario.
The average concordance is 93 percent with a range of 90-94 percent across scenarios. This
mirrors BHKR’s …ndings, who see more concordance in the Denver and CNSS studies than
in the Cornell sample where indi¤erence was allowed. Our …ndings suggest that removing
the indi¤erence option in the happiness question may force some respondents to indicate
concordance.
The comparison with the Denver and CNSS studies is summarized in Tables 8 and 9.
Comparing the Denver and CNSS results to our no-indi¤erence results, we again …nd more
concordance in the South African sample. Combining all treatments in the Denver study,
the average choice-SWB concordance was 85 percent (calculated from BHKR, Table 2).15
The CNSS study included a single scenario (Sleep vs. Income), with a concordance of 92
percent. In our sample, the concordance for this scenario was 95 percent - a small, but
statistically signi…cant di¤erence. Qualitatively, these results show a similar pattern to the
Cornell study: respondents in our survey appear to choose what makes them happy more
often than they did in BHKR.
5
Robustness
Following BHKR, we checked the robustness of our …ndings to three types of questionnaire
e¤ects (cf. BHKR, Section IV). Detailed tables for this section are in the Appendix. First, as
in BHKR’s Denver study, we wanted to check whether respondent fatigue may have resulted
14
This is the same scale that was used in the Denver study. In the CNSS study, the scale was binary.
Recall that the Denver study includes a life satisfaction question which BHKR found to yield
signi…cantly more concordance than the felt happiness question.
Excluding the life satisfaction
question yields 83% concordance in the Denver sample (calculated from BHKR’s data posted at
http://dx.doi.org/10.1257/aer.102.5.2083).
15
22
Table 8: Comparison with BHKR’s Denver study
SWB question
BHKR: Denver
South Africa (Table 11)
Which do you think would make
you more satis…ed with life, all
things considered? Taking all
things together, which do you
think would give you a happier
life as a whole? During a typical
week, which do you think would
make you feel happier?
No
6
420-425
10-19
15
Which do you think would
make you feel happier?
Indi¤erence allowed
No
Number of scenarios
7
Number of observations
961-965
Frequency of reversals (%)
5-9
Average frequency of re7
versals (%)
7
Average frequency of reversals including Apple vs.
Orange (%)
17
Average frequency of reversals excluding life satisfaction question (%)
Notes: BHKR’s Denver study summarized based on Table 2 in BHKR (2012). Number
of observations and Frequency of reversals are per scenario. The last row reports average
reversals in the Denver study excluding respondents who were asked the …rst version of the
SWB question.
Table 9: Comparison with BHKR’s CNSS study
BHKR: CNSS
SWB question
South Africa (Table 11, column 1)
Which do you think would give
you a happier life as a whole?
No
1 (Sleep vs. income)
972
8
Which do you think would make you
feel happier?
Indi¤erence allowed
No
Number of scenarios
1 (Sleep vs. income)
Number of observations
961
Frequency of reversals (%)
5
p-value for equal reversals
0.01
Notes: BHKR’s CNSS study summarized based on Table 2 in BHKR (2012). The last row reports
a t-test for the hypothesis that the frequency of reversals in the two studies is the same.
23
in scenario-order e¤ects. To this end, we reversed the order of the scenarios and checked
whether choices were a¤ected. We …nd that average choices in the reversed questionnaires
are not statistically di¤erent for 7 out of the 8 scenarios, whether we measure choice on a
binary scale or on the 6 point scale. We can also compare respondents’choices for scenarios
that were asked in the …rst half of the survey vs. for scenarios asked later. We …nd a small
tendency for respondents to favor option 2 more for scenarios asked later: 50% vs. 53%
(p = 0:06). We …nd a similar tendency for SWB (55% vs. 57%) but this di¤erence is not
statistically signi…cant (p = 0:21). Overall these order e¤ects are even smaller than those
found in BHKR, perhaps re‡ecting the fact that respondent fatigue was less prevalent in our
surveyor-administered surveys. Like in BHKR, order e¤ects did not a¤ect the frequency of
choice-SWB reversals: we …nd reversals in 8% of cases regardless of scenario order (p = 0:91).
Second, in one version of the questionnaire we reversed the presentation of the various
life goals, so that the own happiness question came last. This is to make sure that life goals
introduced earlier were not mechanically more correlated with choices. Regressing choice on
happiness and the 11 other life goals for these observations yields similar results to those
seen above. Own happiness is highly correlated with choice when entered on its own, but
its coe¢ cient drops dramatically without a large change in the R2 of the regression when
the other variables are entered as well. This again indicates a strong correlation between
the respondents’ various life goals in this sample. Like BHKR, we do see a change in the
magnitude of some of the individual coe¢ cients depending on the order in which life goals
were listed. However, this does not tend to a¤ect which life goals are statistically signi…cant
in explaining choices.
Finally, in one version of the questionnaire, we asked the stand-alone SWB question
before the choice question. Thus, we prompted respondents to think about happiness before
thinking about choice. We wanted to know if this could a¤ect how respondents would choose
and whether they would exhibit a choice-SWB reversals. We did not …nd this to be the case.
In most cases, the fraction of respondents choosing one option over the other did not change
by more than one or two percentage points when the SWB question was asked …rst. We
only …nd a statistically signi…cant di¤erence in 1 out of 8 scenarios.16 Similarly, there was
no signi…cant di¤erence in the average number of reversals exhibited by a respondent.17
16
For the Fun vs. Debt scenario the 5 percentage point di¤erence in the fraction of responses is only
marginally insigni…cant, with a p-value of 0.15.
17
BHKR perform this robustness check in their Cornell study where the SWB response scale includes the
indi¤erence option. Since our stand-alone SWB question did not include indi¤erence, the two robustness
checks are not directly comparable. In general, neither BHKR nor we …nd evidence that asking about SWB
before or after asking about choice has large e¤ects on the results.
24
6
Discussion
We investigated happiness and other determinants of choices in a developing country. We
presented respondents in South African townships with hypothetical choice scenarios and
asked about their choices as well as which option they would prefer along a variety of dimensions. We found that people mostly choose what makes them feel happy. In addition,
respondents perceive little con‡ict between happiness and other important determinants of
choice such as sense of purpose and family happiness. The …ndings show some di¤erences
relative to those found by BHKR in US samples, suggesting that there might be relevant
di¤erences between developed and developing countries. More broadly, our results highlight
a potentially important dimension of heterogeneity: not only can people have di¤erent goals
when making choices, they can also di¤er in the degree to which these various goals are in
con‡ict with each-other.
A possible interpretation of our …ndings is suggested by the literature on hedonic adaptation (Frederick and Loewenstein, 1999; Loewenstein and Ubel, 2008). It is well documented
that people’s hedonic experiences adapt to changing life circumstances, such as increased
income or disability. Some of this adaptation is passive, embodied in the basis of comparison (as when the sick experience life’s “little pleasures”more intensively than the healthy).
However, adaptation can also be active, embodied in the choices that people make. For
example, time-use studies show that one’s circumstances a¤ect day-to-day activities and the
resulting ‡ow of happy experiences (Krueger et al., 2009; Knabe et al., 2009).18 Development
economists have also noted that such adaptation may be important:
“These three men all lived in small houses without water or sanitation. They
struggled to …nd work, and to give their children a good education. But they all
had a television, a parabolic antenna, a DVD player, and a cell phone. Generally,
it is clear that things that make life less boring are a priority for the poor.”
(Banerjee and Du‡o, 2011, p36).
The pronounced happiness-seeking behavior we observe in the South African sample may
re‡ect adaptation to life among the poor. The lack of ample resources to improve one’s life
may be compensated, to some extent, by attaching a higher weight to happiness in decision
making.
18
Similarly, Maslow’s (1943) concept of a hierarchy of needs would suggest that the goals people seek adapt
to their circumstances, with higher level goals (e.g., self-ful…lment) becoming more desirable as lower level
goals (e.g., physical safety) are attained.
25
Social status
Nonboringness
Comfort
Purpose
.3
.1
.2
.3
.1
.2
.3
.1
.2
.3
.1
.2
.3
.4
.1 .2 .3
.4
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
.3
5
.2
4
.1
3
0
2
.4
1
0 .1 .2 .3
7
.3
6
.2
5
.1
4
0
3
.3
2
.2
1
.1
7
0
6
.3
5
.2
4
.1
3
0
2
0 .05 .1 .15 .2 .25
1
0 .05 .1 .15 .2 .25
26
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
0 .05 .1 .15 .2
3
0 .05 .1 .15 .2 .25
2
0 .05 .1 .15 .2
1
0 .05 .1 .15 .2
0
.1
.2
.3
6
0 .05 .1 .15 .2
5
0 .05 .1 .15 .2
4
0 .05 .1 .15 .2
3
0 .05 .1 .15 .2
2
0 .05 .1 .15 .2
1
0 .05 .1 .15 .2
0 .1 .2 .3 .4 .5
.2
.3
0
.1
.2
.3
0 .1 .2 .3 .4 .5
0 .1 .2 .3 .4 .5
.1 .2 .3 .4
.1
Fun
versus
Debt
0 .05 .1 .15 .2 .25
0 .1 .2 .3 .4
5
0 .1 .2 .3 .4
4
0 .1 .2 .3 .4
3
0 .1 .2 .3 .4
2
.1 .2 .3 .4
1
0
7
.3
6
.2
5
.1
4
0
3
.3
2
.2
1
.1
7
0
6
.3
5
.2
4
.1
3
0
2
.3
1
.2
6
.1
5
0
4
.3
3
.2
2
.1
1
0
0 .1 .2 .3 .4 .5
0
0
Friends
versus
Money
0 .1 .2 .3 .4
.4
1
.1 .2 .3
7
0
6
.4
5
0 .1 .2 .3
4
.3
3
.2
2
.1
1
0
7
.3
6
.2
5
.1
4
0
3
.3
2
.2
1
.1
7
0
6
0 .05 .1 .15 .2 .25
5
0 .05 .1 .15 .2 .25
4
.3
3
.2
2
.1
1
0
6
0 .05 .1 .15 .2 .25
5
.3
4
.2
3
.1
2
0
1
.1 .2 .3 .4
.1 .2 .3 .4
.3
Friends
versus
Income
0
0
6
0 .05 .1 .15 .2 .25
5
0 .05 .1 .15 .2
4
.3
3
.2
.3
2
.1
.2
1
0
.1
.2
Time
.1 .2 .3 .4
0
.1
0 .1 .2 .3 .4 .5
0
0 .1 .2 .3 .4 .5
Money
versus
0
0 .05 .1 .15 .2 .25
3
0 .05 .1 .15 .2 .25
2
0 .05 .1 .15 .2
1
0 .05 .1 .15 .2
6
0 .05 .1 .15 .2
5
0 .05 .1 .15 .2
4
0 .05 .1 .15 .2 .25
3
0 .05 .1 .15 .2
.3
2
0 .05 .1 .15 .2
.2
1
0 .05 .1 .15 .2
.1
0 .1 .2 .3 .4 .5
0
0 .1 .2 .3 .4 .5
Sleep
versus
Income
0 .05 .1 .15 .2 .25
.4
2
.1 .2 .3
1
0
7
.4
6
.2 .3
5
0 .1
4
.3
3
.2
2
.1
1
0
7
.3 .4
6
0 .1 .2
5
.3
4
.2
3
.1
2
0
1
.3 .4
7
.1 .2
6
0
5
.3
4
.2
3
.1
2
0
0 .05 .1 .15 .2 .25
0
1
.4
0 .05 .1 .15 .2 .25
0 .1 .2 .3
6
.2 .3
0 .05 .1 .15 .2 .25
0
5
0 .1
0 .05 .1 .15 .2 .25
0
4
0 .05 .1 .15 .2 .25
0 .05 .1 .15 .2
0
3
.3 .4
0 .05 .1 .15 .2
0
2
0 .1 .2
0 .05 .1 .15 .2
0 .05 .1 .15 .2 .25
1
0 .1 .2 .3 .4
0 .05 .1 .15 .2
.2
Fun
.1
Spirituality
0 .05 .1 .15 .2 .25
0
Control
0 .05 .1 .15 .2 .25
Social life
0 .05 .1 .15 .2
.3
Romance
.2
Health
.1
Family
happiness
0 .05 .1 .15 .2 .25
0
Own
happiness
.1 .2 .3 .4
Choice
0
7
Appendix
Figure 2: Histograms of choice, SWB and other life goals, by scenario
Money
versus
Time, v2
Abs. Inc.
versus
Rel. Inc.
1
2
3
4
5
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
Apple
versus
Orange
6
1
2
3
4
5
6
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
27
10.53
5.26
0
0.2379
114
5.31
0
0.6072
113
32.46
69.91
7.96
Money
versus
Time
%
61.75
Sleep
versus
Income
%
16.81
0
0.5811
114
4.39
7.02
74.56
Friends
versus
Income
%
14.04
1.75
1.0000
112
6.25
7.14
28.57
Friends/Family
versus
Money
%
58.04
0.88
0.3593
113
6.19
10.62
45.13
Fun
versus
Duty
%
38.05
3.51
1.0000
109
5.50
6.42
33.03
Money
versus
Time, v. 2
%
55.05
0.88
0.3323
113
5.31
9.73
12.39
Abs. Inc.
versus
rel. inc.
%
72.57
2.63
0.0015
111
2.70
16.22
33.33
Apple
versus
Orange
%
47.75
Notes: For each scenario, the …rst four rows present the distribution of responses among those who did not indicate indi¤erence for
the SWB question. The fraction of indi¤erent SWB responses is indicated in the …fth row. The Liddell test tests the hypothesis
that the average choice response is equal to the average SWB response for paired data. The text of each scenario appears in the
Appendix.
Higher SWB: Option 1
Chosen: Option 1
Higher SWB: Option 2
Chosen: Option 2
Higher SWB: Option 2
Chosen: Option 1
Higher SWB: Option 1
Chosen: Option 2
Indi¤erence for SWB
p-value of Liddell Exact Test
N
Choice scenario
Table 10: Choice and SWB responses across scenarios among respondents under the age of 30
28
Money
versus
Time
%
56.22
35.37
4.88
3.53
0.1821
964
Sleep
versus
Income
%
18.42
76.69
4.16
0.73
0.0000
961
0.0000
960
0.94
3.96
78.02
Friends
versus
Income
%
17.08
0.0001
965
2.38
6.01
48.6
Friends/Family
versus
Money
%
43.01
0.0000
961
1.87
6.87
60.25
Fun
versus
Debt
%
31.01
0.0000
961
0.94
4.68
27.16
Money
versus
Time, v. 2
%
67.22
0.0000
963
1.04
4.47
22.95
Abs. Inc.
versus
rel. inc.
%
71.55
0.0000
962
2.39
7.59
37.73
Apple
versus
Orange
%
52.29
Notes: The table presents the distribution of choice and SWB responses on a binary scale using the stand-alone SWB question.
Responses were on a 6-point scale with no allowance for indi¤erence. The Liddell test tests the hypothesis that the average choice
response is equal to the average SWB response for paired data. The text of each scenario appears in the Appendix.
Higher SWB: Option 1
Chosen: Option 1
Higher SWB: Option 2
Chosen: Option 2
Higher SWB: Option 2
Chosen: Option 1
Higher SWB: Option 1
Chosen: Option 2
p-value of Liddell Exact Test
N
Choice scenario
Table 11: Choice and SWB responses across scenarios, stand-alone SWB question
29
Sleep
versus
Income
-0.278**
(0.114)
-0.004
(0.005)
-0.151
(0.338)
-0.721**
(0.327)
0.088
(0.131)
-0.017
(0.050)
0.010
(0.037)
0.132
(0.271)
-0.205
(0.278)
-0.811
(0.601)
0.300
(0.187)
939
Money
versus
Time
-0.216**
(0.107)
-0.005
(0.005)
-0.104
(0.321)
-0.354
(0.236)
-0.040
(0.123)
-0.005
(0.046)
0.053
(0.036)
0.433
(0.264)
-0.040
(0.271)
-0.279
(0.554)
0.064
(0.175)
937
Friends
versus
Income
-0.425***
(0.116)
-0.010*
(0.005)
-0.279
(0.346)
-0.835**
(0.341)
-0.157
(0.132)
0.044
(0.048)
-0.016
(0.038)
0.587*
(0.312)
0.040
(0.326)
0.481
(0.707)
-0.110
(0.215)
936
Friends/Family
versus
Money
-0.177
(0.109)
-0.009*
(0.005)
-0.087
(0.330)
-0.035
(0.219)
0.044
(0.126)
0.054
(0.046)
0.062*
(0.036)
0.220
(0.264)
-0.030
(0.274)
-0.177
(0.623)
0.105
(0.192)
924
Fun
versus
Debt
-0.102
(0.108)
-0.018***
(0.005)
-0.191
(0.335)
-0.920***
(0.334)
-0.105
(0.126)
0.045
(0.046)
0.127***
(0.036)
-0.069
(0.264)
-0.454*
(0.272)
-0.449
(0.694)
0.185
(0.211)
937
Money
versus
Time, v. 2
-0.030
(0.119)
-0.021***
(0.006)
0.125
(0.325)
0.153
(0.241)
-0.028
(0.148)
-0.049
(0.049)
0.087**
(0.037)
0.338
(0.299)
0.178
(0.309)
-1.514**
(0.698)
0.515**
(0.214)
928
Abs. Inc.
versus
Rel. inc.
-0.067
(0.116)
-0.015**
(0.006)
-0.204
(0.365)
-0.580*
(0.326)
-0.008
(0.138)
-0.015
(0.047)
0.091**
(0.038)
0.200
(0.308)
-0.144
(0.316)
0.577
(0.624)
-0.145
(0.192)
942
Apple
versus
Orange
0.019
(0.107)
-0.013***
(0.005)
0.313
(0.281)
-0.349
(0.279)
0.034
(0.124)
-0.047
(0.045)
0.101***
(0.036)
0.338
(0.295)
0.067
(0.307)
-1.149*
(0.595)
0.312*
(0.185)
911
Notes: The dependent variable is an indicator equal to 1 if the respondent exhibited a reversal in the given scenario. ‘Primary school’is 1 if the
respondent’s highest level of completed education is primary school; ‘High school’is 1 if it is high school or above. Income is measured in logs
and predicted based on ownership of household appliances as described in the text. All regressions include a constant. Robust standard errors
in parentheses. ***,**,* denote signi…cance at the 1, 5, and 10 percent, respectively.
Observations
Income squared
Income
High school
Primary school
Number of children
Number of adults in the HH
Single
Widowed
Divorced
Age
Male
Choice scenario
Table 12: Reversals and respondent characteristics, probit regressions
Table 13: Robustness: Choices with reordered scenarios
Scenario
Sleep vs. Income
Money vs. Time
Friends vs. Income
Friends/Family vs. Money
Fun vs. Debt
Money vs. Time, v.2
Abs. Inc. vs. Rel. Inc.
Apple vs. Orange
Average choice
(binary)
All Scenarios
reordered
1.77
1.77
1.39
1.46
1.79
1.77
1.51
1.49
1.62
1.62
1.28
1.25
1.24
1.21
1.40
1.37
Di¤erence
p-value
0.95
0.03
0.49
0.50
0.92
0.31
0.33
0.44
Average choice
(6-point)
All Scenarios
reordered
4.73
4.84
3.20
3.46
4.81
4.79
3.63
3.59
4.04
4.04
2.46
2.33
2.43
2.28
3.14
3.07
Di¤erence
p-value
0.39
0.06
0.86
0.80
1.00
0.32
0.26
0.64
Notes: For each scenario, the table displays the average responses to the choice questions for
all observations as well as for observations where the order of the scenarios was reversed. The
p-value is for the equality-of-means t-test.
30
Table 14: Robustness: Regressions of choice on SWB and other goals, with goals reordered
Own happniess
(1)
0.501***
(0.015)
Family happiness
Health
Life’s level of romance
Social life
Control over your life
Life’s level of spirituality
Life’s level of fun
Social status
Life’s nonboringness
Physical comfort
Sense of purpose
Observations
R2
1886
0.3987
(2)
0.177***
(0.046)
0.078*
(0.046)
0.037
(0.046)
0.026
(0.045)
-0.013
(0.040)
-0.055
(0.039)
0.027
(0.043)
0.095**
(0.045)
-0.190***
(0.041)
0.006
(0.054)
0.359***
(0.045)
1886
0.4547
(3)
0.165***
(0.053)
0.107**
(0.054)
0.040
(0.046)
0.019
(0.047)
0.011
(0.045)
-0.027
(0.040)
-0.054
(0.038)
0.023
(0.042)
0.080*
(0.047)
-0.190***
(0.041)
0.020
(0.054)
0.341***
(0.045)
1886
0.4594
Notes: OLS regressions for observations where the presentation of the various
life goals was reversed for each scenario. The dependent variable is choice on
a 6-point scale, all independent variables are on a 7-point scale. Variables are
demeaned at the scenario level. Robust standard errors in parentheses. ***,
**, * denote signi…cance at the 1, 5, and 10 percent, respectively.
31
Table 15: Robustness: Choices with reordered choice and SWB questions
Scenario
Sleep vs. Income
Money vs. Time
Friends vs. Income
Friends/Family vs. Money
Fun vs. Debt
Money vs. Time, v.2
Abs. Inc. vs. Rel. Inc.
Apple vs. Orange
Average choice
(binary)
SWB
All
before
choice
1.77
1.80
1.39
1.39
1.79
1.85
1.51
1.49
1.62
1.67
1.28
1.29
1.24
1.24
1.40
1.42
Di¤erence
p-value
0.37
0.95
0.05
0.54
0.15
0.90
0.98
0.53
Average choice
(6-point)
SWB
All
before
choice
4.73
4.63
3.20
3.13
4.81
4.89
3.63
3.40
4.04
4.12
2.46
2.41
2.43
2.29
3.14
3.10
Di¤erence
p-value
0.40
0.63
0.52
0.11
0.58
0.71
0.29
0.77
Notes: For each scenario, the table displays the average responses to the choice questions for all
observations as well as for observations where the stand-alone SWB question was asked …rst. The
p-value is for the equality-of-means t-test.
32
7.1
Choice scenarios in the survey
Scenario 1: Sleep vs. Income
Suppose that you have to decide between two new jobs. The jobs are exactly the same
in almost every way, but have di¤erent work hours and pay di¤erent amounts.
Option 1: A job paying R 6,000 per month. The hours for this job are reasonable, and
you would be able to get about 7.5 hours of sleep on the average work night.
Option 2: A job paying R 10,000 per month. However, this job requires you to go to
work at unusual hours, and you would only be able to sleep around 6 hours on the average
work night.
Scenario 2: Money vs. Time
Imagine that the school your child goes to (suppose you have one), implements a “student
activity fee”of R 60 per week to help pay for maintenance of facilities and cleaning. However,
the school allows you to not pay the fee if instead you put in 2 hours of work a week at the
school helping with minor repairs or cleaning. You face two options:
Option 1: Spend 2 hours each week with school service.
Option 2: Pay R 60 each week.
Scenario 3: Friends vs. Income
Imagine that you have been reassigned at your job, and will be moved to a new location.
There are two o¢ ces where you could request to work. One o¢ ce is in the town where many
of your friends happen to be live, and pays 4800. The other o¢ ce is in a town where you
don’t know anyone, and pays R 6600. Your job will be exactly the same at either o¢ ce. You
must decide between the following two options:
Option 1: Make R 4800 and move to the town where your friends are.
Option 2: Make R 6600 and move to a town where you don’t know anyone.
Scenario 4: Friends/Family vs. Money
Imagine that one of your closest friends moved to a di¤erent city three years ago. You
recently received an invitation to his/her wedding where many of your mutual friends will
attend. You face two options. Would you choose to go to the wedding if you had to buy a
R 700 round-trip bus ticket and travel 8 hours each way to get there?
Option 1: Go the wedding, which requires a R 700 round trip bus ticket.
Option 2: Miss the wedding, but save the money.
Scenario 5: Fun vs. Debt
Suppose this month you received an extra R 150 in your paycheck.
33
Option 1: I would use the money to treat myself and my family to a nicer meal than
usual.
Option 2: I would save the money and pay o¤ my utility bill balance or other debt.
Scenario 6: Money vs. Time, version 2
Suppose your employer wants to give you a bonus.
Option 1: R 300 now.
Option 2: R 350 in three months.
Scenario 7: Absolute Income vs. Relative Income
Say you are considering a new job, and have o¤ers from two companies. Even though
all aspects of the two jobs are identical, employees’ salaries are di¤erent across the two
companies. Everyone in each company knows the other employees’ salaries. You must
choose one of the two companies, which means you must decide between the following two
options:
Option 1: Your monthly income is R 15,000, while on average others at your level earn
R 17,500.
Option 2: Your monthly income is R 14,000 while on average others at your level earn R
11,500.
Scenario 8: Apple vs. Orange
Suppose you are checking out a new supermarket that just opened near where you live.
As you walk by the fresh fruit display, you are o¤ered your choice of a free snack:
Option 1: A freshly sliced apple.
Option 2: A freshly sliced orange.
The following pictures illustrate the presentation of the scenarios in the survey.
34
35
36
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