Abstract
Most studies that explore the impact of relative standing on subjective well-being use objective measures of the individual’s relative position, such as the mean income of the reference group or the individual’s ranking in the relevant income distribution. In this paper, using a new household survey from South Africa, we are able to derive subjective measures of relative standing, as information is collected on individuals’ perceptions of where they rank in the income distribution. We find considerable differences between objective and subjective measures of an individual’s relative ranking. Furthermore, our results suggest that an individual’s perceived relative status has a significantly larger effect on subjective well-being than objective measures of relative status based on reported income. We also examine the effects on subjective well-being of how individuals perceive their relative position in the income distribution to have changed since childhood, and what they expect their relative position to be in the future. We find that future upward mobility has a smaller effect than upward mobility compared to one’s past, suggesting that life satisfaction is influenced more by what has been achieved than by anticipated achievements.
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Notes
The corollary of course is that if individuals rank higher than others in the income distribution, their subjective well-being will be greater.
Although we use the term ‘actual’ here to refer to income measures based on reported values in the household survey, we do recognize that these reported values may not represent the ‘true’ values if there is misreporting of income by respondents. We comment further on this issue in Sect. 4.
It is possible that people’s perceptions of where they rank in a particular income distribution are coloured by their attitude towards life in general. For example, individuals who are pessimistic about life, or who tend to consider themselves ‘hard done by’, may be more likely to report being in a lower position in the income distribution than their actual position (and conversely for those who are more optimistic about life). If this is the case, then in a subjective well-being regression, our measure of people’s perceptions of their relative rank would also be capturing in part the effect of attitude towards life, if attitude towards life also influences individual’s reporting on overall life satisfaction. In the absence of panel data, we are unable to control for this unobservable characteristic using fixed effects estimation. However, as we discuss in Sect. 4, our results remain robust to controls for current feelings of happiness, depression and optimism, variables that are likely to be highly correlated with an individual’s general attitude to life.
Since the late 1970s, quality of life surveys have also been conducted in South Africa, where adults have been asked to assess their overall satisfaction with life. In the post-apartheid period, the Human Sciences Research Council has conducted the South African Social Attitudes Survey which also collects information on subjective well-being. These surveys typically sample between 2000 and 3000 adults. See, for example, Møller (1989, 2001) and Pillay et al. (2006).
Møller (2007) analyses national individual-level data on life satisfaction from the General Household Survey of 2002. However this survey only collected information on one individual per household (the person who chose/was chosen to respond to the questions in the household module). Møller (2005) and Hinks and Gruen (2007) also have individual-level measures of subjective well-being, but their studies use regionally specific survey data, so their results cannot be generalized for South Africa. Møller (2005) explores the impact of criminal victimization on quality of life using a 2002 dataset of households in the Nelson Mandela Metropolitan Municipality of the Eastern Cape. Hinks and Gruen (2007) use pooled data from the 1999, 2003 and 2004 Quality of Life Surveys conducted in the Durban Metropolitan region of KwaZulu-Natal to examine the relationship between subjective well-being and a range of personal characteristics.
Some studies have addressed this concern by controlling for individual characteristics of the respondent as well as household characteristics (cf. Bookwalter et al. 2006; Kingdon and Knight 2006, 2007). But this presumes that the problem lies only with whether or not one member can reliably report on the household’s subjective well-being rather than his/her own subjective well-being. It still assumes that the individual subjective well-being of household members can be aggregated into a unified measure of household subjective well-being. Other studies have interpreted the responses on subjective well-being as reflecting the assessment of the respondent’s own individual level of satisfaction (Neff 2007).
The unit of analysis in the quality of life questions in the PSLSD is not consistent. Although respondents are asked to report on the household’s level of satisfaction, they are also asked: “When you compare your situation with that of your parents, do you think that you are richer, about the same, or poorer than they were?”, so that this comparison is at the level of the individual and not the household.
Africans and Whites together make up approximately 90% of the South African population. We do not explore the determinants of subjective well-being among the remaining 10% of the population, comprised predominantly of Indians and Coloureds. This is partly due to sample size concerns, but also because the experiences of Africans and Whites represent the two extremes of a society polarized by apartheid legislation.
A formal dwelling is a house or an apartment which is typically a brick structure; an informal dwelling is a shack typically made of cardboard, plastic or corrugated iron; a rural dwelling is a traditional dwelling (hut) made of traditional materials (mud and thatch).
Children are aged 14 years and younger and pensioners are defined as adults older than 64 years.
In NIDS, information is collected on all sources of labour and non-labour income. Non-labour income is reported as point values. Wages and earnings are also collected as point values except where respondents did not or would not provide this information, in which case, earnings were reported in brackets. To generate a continuous income variable, earnings in brackets were assigned the mid-point of the bracket.
We cannot compare the effects of perceived versus actual ranking in the village or suburb. We are not able to identify directly the village or suburb to which the individual would have referred in answering the question and although household clusters may be a reasonable approximation, the number of households within each cluster in NIDS is too small (approximately 20 households per cluster on average) to generate a reliable distribution of income. More robust measures would be generated using Census data but the most recent Census for South Africa was conducted seven years prior in 2001.
The cut-points in the probit estimations are relatively equally spaced and our findings are robust also to Ordinary Least Squares regressions which treat the dependent variable as a linear measure of subjective well-being.
In contrast to what has generally been found in studies of subjective well-being for developed countries (Shields and Wooden 2003), we find that the presence of children in the household has a positive and significant effect on subjective well-being (similar results were obtained for South Africa in Kingdon and Knight 2006, 2007). As the disaggregated regression results in Table 4 indicate, this is being driven by the effect of children in African households, as the presence of children in White households has a negative although insignificant effect.
The results of these estimations are available from the authors.
We find very similar sized coefficients when the variables representing actual and perceived relative status are included on their own rather than in the same regression as they are here.
In NIDS, individuals are also asked how they anticipated their position to change 5 years hence. We tried including variables for anticipated upward and downward mobility based on this question. However, our results were not significant suggesting that it is difficult to capture meaningful expectations about a more distant future.
It is also possible that the village or suburb is the more relevant reference group for Africans than Whites because Africans are more likely to know their neighbours and be integrated into local community structures. The descriptive statistics in Table 1 provide some evidence of this: Africans are much more likely to report that their neighbours help each other out and they are also more likely to be a member of a social group.
These unexpected results are found to be robust in all the sensitivity tests that we discuss below.
We generally found very little difference in the match between actual and perceived standing in descriptive comparisons using per capita household expenditure and total household income. It is therefore not surprising that our results are robust to using these alternative measures of actual relative standing.
We do not include the variables representing emotions in the earlier specifications due to some concern over the direction of causality in a subjective well-being regression. To give one example, feeling happy in the previous week may have a positive impact on subjective well-being, but one’s feelings of satisfaction with life more generally may also affect happiness in the short-term. Nonetheless, we use these variables here simply to illustrate that once we control for emotional state, the findings with regard to perceived relative standing are robust.
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The authors thank an anonymous reviewer for helpful comments and suggestions, and Economic Research Southern Africa for their support of this project.
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See Table 7.
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Posel, D.R., Casale, D.M. Relative Standing and Subjective Well-Being in South Africa: The Role of Perceptions, Expectations and Income Mobility. Soc Indic Res 104, 195–223 (2011). https://doi.org/10.1007/s11205-010-9740-2
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DOI: https://doi.org/10.1007/s11205-010-9740-2