Abstract
Among the surprising results of research on the relation between a person’s material circumstances and his or her subjective well-being was the finding that this relationship appears to be rather weak (throughout this paper the terms ‘(general) life satisfaction’, ‘(subjective) satisfaction’, ‘happiness’ and ‘subjective well-being’ will be used interchangeably. The same applies to the terms ‘material circumstances’, ‘material conditions’, ‘material situation’ and ‘material well-being’). However, more recently authors began to ask the question, whether this might at least in part be explained by the insufficiencies of income as an indicator for the material situation. Building on this idea, they have shown that the inclusion of alternative measures for the respondents’ material situation—such as wealth measures in particular—reveals that the relationship between a person’s material well-being and his or her subjective well-being might just be somewhat stronger than researchers thought before. The paper will follow this lead but will go beyond current research by first, systematically reviewing the various approaches available for measuring the material situation and second, by proposing the use of a so-called deprivation index, an alternative measure of material well-being, which is frequently used in the context of poverty research (compare e.g. Townsend in Poverty in the United Kingdom, Penguin Books, Harmondsworth, 1979; Halleröd in J Eur Soc Policy 5:111–129, 1995; Nolan and Whelan in J Eur Soc Policy 6:225–240, 1996). It will be argued, that such a deprivation based measure will perform better than indicators like income or wealth when analyzing the relationship between material conditions and subjective well-being. This hypothesis will be tested using three different German datasets. Based on this data it will be shown that in all cases deprivation measures perform better in explaining differences in subjective well-being than the alternatives. However, both types of measures seem to capture slightly different aspects of the material situation, a result which has also been found in the poverty literature cited above. Thus using a combination of both seems to be the best alternative.
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Notes
This appears to be a problem since it is just the fraction of happiness which is not influenced by personality but by external factors, which is of interest here. This is not to say that personal characteristics are unimportant for a person’s happiness. Quite to the contrary, they should be considered a central influence-factor (for an overview compare e.g. Diener and Lucas 1999). However, using well-being as an output indicator in analyses on social policies or as proxy for preferences in economic analyses would be inadequate, should it entirely be determined by personality.
Due to the lacking information on general life satisfaction in the data used by Clark et al. they can show this only for the relation between income satisfaction and actual income.
This means that there is not only a different intercept for each stage of the satisfaction-variable, while effects of independent variables are assumed to be the same at all stages—as is the case in standard ordered probit or logit models—but coefficients for the independent variables might vary, too. In contrast to a multinomial model, which would also allow calculating different coefficients for the independent variables at different stages of the dependent variable, the generalized ordered probit model will consider the ordering information of the dependent variable when calculating the estimates.
It should be noted that the term deprivation in this context does not refer to a subjective concept as it e.g. does in relative deprivation (Stouffer 1949). Since it was designed as a poverty measure it explicitly aims at identifying those who actually are poor and not those who feel that way (in comparison to some reference group) but probably are not (compare e.g. Halleröd 1995: 115). Instead, the term deprivation refers to living in material circumstances which are lower than a commonly shared and/or socially agreed upon standard, i.e. a person is considered to be deprived if he or she does lack a certain amount of items, which are regarded to be part of this standard. Usually the items that actually make up the standard are identified by either asking the survey-respondents, which among the items presented to them should be considered a necessity or by identifying those items, which are held by a majority.
For a more detailed description compare the paragraph on measures for the material situation below.
Howell and his collaborators examine the relationship between subjective well-being and material living conditions for an indigenous ethnic minority in Malaysia. Since many respondents in this population group have no or only irregular income, collecting adequate income information was not possible. Instead, they presented heads of households with a list of 13 consumer items, asking which items their households possessed. However, instead of generating a deprivation index based on these items, they were used as proxies for monetary wealth by substituting market prices for used goods for each item possessed and combining the resulting sum with information on savings into a single wealth indicator.
Measures of expenditure and consumption are related but they are not the same. The main difference is that measures of expenditure only focus on actual spending, while consumption measures will also account for the consumption of durables (like owned housing or cars). They do so by adding an appropriate amount for their usage/consumption to actual spending (while not fully considering such one-time investments in case they should fall in the reporting period). Moreover, certain kinds of expenditures like e.g. cash payments to family members are not considered (for a more detailed description compare for example Meyer and Sullivan 2003, pp. 1188 et seq.). In addition, consumption might also include goods which are not bought, e.g. benefits in kind (Headey 2008), foodstuffs from subsistence farming or other home-made products (although the latter should not be too common in developed countries).
This period is often 1 or 2 weeks. It might, however, be considerably longer. In the German income and expenditure survey (EVS) for example, respondents have to keep a book of household accounts for 3 months in total and at least part of them has to keep a detailed list of all expenditure on food, drinks and tobacco for 1 month.
Even though systematic comparisons between different weighting approaches have shown, that applying either of these or none at all will only generate minor differences between the resulting indices (Lipsmeier 1999), weighting an index still seems reasonable for conceptual reasons.
Even though in our example it is somewhat unlikely that a threshold of three items will identify exactly ten percent of the population to be poor, the actual percentage value should be close.
For the current paper, the fact that defining a poverty line based on deprivation measures is a somewhat difficult task seems to be of minor importance, since it merely focuses on the relationship between well-being and measures for the material situation but does not explicitly focus on the relation between well-being and poverty.
This is why poverty researchers often argue to combine direct and indirect measures to identify the “truly poor”, as e.g. Halleröd (1995) calls the group of persons that is deprived according to both measures.
The fact that a deprivation indicator is particularly apt to identify people at the lower end of the material distribution but does not so good a job in distinguishing differences among the better-off has been made e.g. by Andress et al. (2001).
The most notable official data being the EVS described above.
As mentioned above, Headey et al. (2005, 2008) have also examined the influence of consumption indicators using the British household panel survey (BHPS) and the Hungarian Tarki Panel. At least in the case of general well-being, results were mixed, showing a strong influence for the Hungarian data but no significant effects for the BHPS. To what extend these results might be due to the somewhat reduced set of consumption questions one is restricted to in a multi-topic household survey, i.e. whether more detailed data would show a stronger effect, might be an interesting question for further research. In any case, since to the knowledge of the author even a reduced set of consumption data is unavailable in any German dataset covering subjective well-being as well as deprivation items, an empirical comparison for consumption and deprivation indicators and their influence on subjective well-being is not possible using German data.
For more details on this problem compare the theoretical discussion of deprivation indices above and/or the description of index construction below.
The primary goal of PASS is to provide information on recipients of the reformed unemployment assistance scheme in Germany, the so-called Arbeitslosengeld II (Unemployment Benefit II). In order to achieve this goal, the study comprises two different samples, a sample consisting only of households, receiving this benefit at the date the sample was drawn and a sample of the general population, which might also include benefit recipients, but only to the degree usually found in the population. As of January 2009 this was 10.1% of all applicable persons, i.e. those between 0 and 65 years of age (STBA 2009: 12. This value equates to 8.1% of the entire population. Note, however, that calculating such a percentage for the entire population might be somewhat problematic, since this figure does not represent all recipients of means tested benefits. This is so since people of age 65 and older would have to apply for a different type of benefit, if they are in need. This benefit will result in quite comparable financial circumstances of the needy person, but is governed by a different part of the German Social Code, namely social assistance legislation/SGB XII). For details on the sampling design compare Rudolph and Trappmann (2007). When calculating models that should provide representative information on the entire population, appropriate weighting factors are available, which allow to adequately combine the two subsamples.
This results in an overall response-rate of 30.5%. Response rate within households varied between 84.3 and 85.6% resulting in person-level response rates of 30.0% for the recipient sample, 22.4% for the population sample and 25.9% for the combined samples (for wave 1 figures compare Christoph et al. 2008). Overall re-response rates for wave two were 62.4% on the household and 53.1% on the person level (compare Büngeler et al. 2009). The welfare survey, which is a cross-sectional survey, had a response rate of 56.1%. Due to the complex sample structure and up to now more than 25 panel waves, it is not possible to present detailed figures for the GSOEP here. Original response rates on the household level are between 60.6% in sample A (1984) and 40.2% in sample H (2006; compare Haisken-DeNew and Frick 2005; von Rosenbladt et al. 2007). For an overview of attrition between panel waves in the GSOEP compare Kroh and Spiess (2008).
The consumer price index information standardized to 2005 values in StaBA (2009) was re-standardized to 1998 values. Prices in the year 2007, which was used as the reference year for price adjustment, were equal to 114.3% of 1998 prices.
The actual values logged were savings or debts plus one, in order to be able to calculate a logged value for respondents with debts or savings of zero.
For the highest category, indicating ‘50 000 Euro or more’, a value of 75,000 Euro was imputed.
For a detailed list of items available in each survey compare Table 7 in the appendix.
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The author likes to thank Heinz-Herbert Noll, Gerhard Krug, Torsten Lietzmann and the anonymous reviewer for helpful comments.
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Christoph, B. The Relation Between Life Satisfaction and the Material Situation: A Re-Evaluation Using Alternative Measures. Soc Indic Res 98, 475–499 (2010). https://doi.org/10.1007/s11205-009-9552-4
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DOI: https://doi.org/10.1007/s11205-009-9552-4