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Your House, Your Car, Your Education: The Socioeconomic Situation of the Neighborhood and its Impact on Life Satisfaction in Germany

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Abstract

This study deals with the impact of socioeconomic conditions and social integration into a local neighborhood on individual life satisfaction in Germany. While the majority of ecological studies to date are based on very broad neighborhood concepts, using large research units for defining neighborhood the present study contains micro-geographic information on a representative sample of private households in Germany, including features of their respective residential environments. The data was derived from the German Socio-Economic Panel (SOEP) study and enriched with data from the Micromarketing-Systeme and Consult GmbH (microm) for the years 2000–2006. Our analyses reveal neighborhood effects on various facets of life satisfaction. Controlling for several covariates at the household and individual level, life satisfaction increases when a person lives in a neighborhood with a higher socioeconomic status. In addition, the individual gap between a person’s economic status and the status of the neighborhood also affects individual well-being. However, when comparing with other neighborhood aspects, the strongest effects on individual life satisfaction have social networks.

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Notes

  1. Clark et al. (2008b)suggest that social comparison or relative income modeled within a utility function could overcome the Easterlin Paradox on the one hand and the typically found positive relationship between income and happiness at the micro level.

  2. Nonnenmacher (2007), using data on three German cities (Hamburg, Kiel and Munich), finds that mean neighborhood disorder only increases the fear of crime if this effect is tested for small neighborhoods of less than six to eight square kilometers.

  3. The data is available to all researchers, but can only analyzed within the DIW Berlin due to data security regulations.

  4. The average number of households in SOEP located at the same street section is 1.4, and within one building is 1.02.

  5. The original version of the question (apart from a translation into English) can be found in the “Appendix” in Fig. 2.

  6. As microm provides data for commercial purposes the data documentation is not on a scientific level, i.e., we can not reproduce in detail the variables provided by microm. However, we have—as far as possible—done extensive data checks (e.g., correlation of purchasing power and household income, or number of foreigners in a neighborhood and nationality) and only plausible associations observed.

  7. We apply the modified OECD scale, assigning 1 to the first person in the household and 0.5 to every other person aged older than 14 and 0.3 to all children under the age of 15.

  8. We assume that personality is relatively stable (at least what is measured by these concepts) and therefore assign the 2005 personality variables as time-invariant variables to all persons available in 2004.

  9. Conversely, studies about the wellbeing of elderly people have indicated that older adults who show a tendency towards internal locus of control have lower life satisfaction than those with an external locus of control (Rogers 1999). It may be that older individuals who are externally focused easily develop trust in others, e.g., in their health care provider, and that this ability helps them to better cope with age-specific restrictions.

  10. Measured by the nine quantiles of the net equivalence household income of the previous year, see previous section.

  11. The satisfaction means by neighborhood status and household income quantiles can be found in the “Appendix” in Table 4.

  12. We have to bear in mind that changes in life satisfaction also depend on other aspects not considered in this study, for example marital transitions, divorces, loss of partner, or loss of job (Lucas et al. 2003; Clark et al. 2008a).

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Authors and Affiliations

  1. Institute for Social Work and Social Education (ISS), Zeilweg 42, 60439, Frankfurt am Main, Germany

    Joerg Dittmann

  2. German Institute for Economic Research (DIW), SOEP, Mohrenstraße 58, 10117, Berlin, Germany

    Jan Goebel

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  1. Joerg Dittmann
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  2. Jan Goebel
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Correspondence to Jan Goebel.

Appendix

Appendix

See Table 4 and Fig. 2.

Table 4 Mean of satisfaction by neighborhood status and income quantile
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Fig. 2
figure 2

Measuring life satisfaction, SOEP 1984–2007

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Dittmann, J., Goebel, J. Your House, Your Car, Your Education: The Socioeconomic Situation of the Neighborhood and its Impact on Life Satisfaction in Germany. Soc Indic Res 96, 497–513 (2010). https://doi.org/10.1007/s11205-009-9489-7

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