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Well-Being and Inequality

Abstract

Well-being is a favourable state of life. It is something desirable for every human being in the world at all times, or, as Ng (1996, 1) puts it, it is “the main, if not only objective of life”. If a person were allowed to choose between two states of life, he or she would always choose the one which offers a higher degree of well-being. This conceptual definition, albeit fairly simple, opens the field to a rich bundle of research questions. The major questions to ask are what characteristics a state of life should consist of in order to be a favoured one, and how well-being is distributed.

Keywords

  • Life Satisfaction
  • Gross Domestic Product
  • Subjective Approach
  • Objective Approach
  • High Life Satisfaction

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Fig. 20.1
Fig. 20.2
Fig. 20.3
Fig. 20.4
Fig. 20.5
Fig. 20.6
Fig. 20.7
Fig. 20.8
Fig. 20.9
Fig. 20.10

Notes

  1. 1.

    We will use the above terms interchangeably throughout this chapter.

  2. 2.

    Subjective well-being is also sometimes considered as a multidimensional concept in itself. Diener and Suh (1997), for example, state that it consists of three interrelated components: life satisfaction, pleasant effects and unpleasant effects. “Effects” refer to moods and emotions, whereas life satisfaction is rather cognitive (Diener and Suh, 1997, 200). Which dimension of subjective well-being should be part of the conceptualisation of well-being is therefore always questionable.

  3. 3.

    A survey on various measures of subjective well-being can be found in Andrews and Robinson (1991).

  4. 4.

    Further evidence of this sort might be found in Andrews and Robinson (1991); Michalos (1991); Larsen and Fredrickson (1999); Schwarz and Strack (1999) and Veenhoven (1993).

  5. 5.

    The results we are presenting here can only give a very rough overview of the results ascertained by this survey in particular. Readers are therefore asked to additionally refer to the rich literature provided on the website of the European Foundation http://www.eurofound.europa.eu. Additional information can be found in Alber et al. (2004, 2008).

  6. 6.

    This mirrors the incidence of jobless households used in the so-called Laeken indicators (Atkinson et al., 2002).

  7. 7.

    Data for Germany are not shown because of validity problems of the income variable in the German EQLS sample.

  8. 8.

    A biplot can be seen as a graphical device of a principal components analysis (PCA). It shows observations (countries) and variables (dimensions of well-being) in the space of the first two principal components. Biplots allow us to depict variable values, correlations between variables, and Euclidean distances of a multidimensional space at one time. They were originally invented by Gabriel, 1971. An easy-to-read introduction with many interpretation examples is given by Kohler and Luniak, 2005.

  9. 9.

    Countries that do not have a value on one of the indicators shown in Fig. 20.2 cannot be used in the biplot.

  10. 10.

    The question was “All things considered, how satisfied would you say you are with your life these days? Please tell me on a scale of one to ten, where one means very dissatisfied and ten means very satisfied.”

  11. 11.

    The question was “If you were to consider your life in general, how happy or unhappy would you say you are, on the whole.” Respondents could answer on a scale from 1 to 7 with 1 being completely happy and 7 completely unhappy. The scale was reversed for subsequent analyses.

  12. 12.

    The EQLS has been described in some detail in the previous section. The ISSP 2002 is round 15 of a continuing program of cross-national surveys. Between the end of 2001 and February 2004, surveys were carried out in 33 countries, 20 of them being EU members or EU candidates. The target population of the samples are residents of age 18 and older. Sample sizes vary between 1,000 in Latvia and 2,947 in United Kingdom. The ISSP has been made available by the Central Archive for Empirical Social Research at the University of Cologne. The study number (ZA-Nr.) is s3880.

  13. 13.

    The data used for this plot are the Mannheim Eurobarometer Trend File. The data set has been made available by the Central Archive for Empirical Social Research at the University of Cologne. The study number (ZA-Nr.) is s3521. For Fig. 20.5 the data set has been enriched by some additional years by the WZB.

  14. 14.

    Another important line of research is on the direction of causality. It could either be that rich people are more satisfied with their lives, or that happy people are economically more successful. The study of the causal direction requires, at least, longitudinal data, which is not available for Europe as a whole. Studies of well-being before and after sudden and unexpected gains of income suggest that income in fact causes gains in happiness (Smith, 1995; Brickman, et al., 1978; Gardner and Oswald, 2001).

  15. 15.

    There is also a debate about the causal relationship between unemployment and well-being, i.e. do unhappy people become unemployed? Available research suggests that the main causality runs from unemployment to unhappiness, and not vice versa (Dew et al., 1992; Graetz, 1993; Winkelmann and Winkelmann, 1998; Marks, 1999).

  16. 16.

    Self-employed income is typically relatively low in Eastern Europe, unlike in Western Europe.

  17. 17.

    Education was measured as terminal education age in the EQLS.

  18. 18.

    Gender, age, age-squared, income, employment status and marital status were used as control variables.

  19. 19.

    Coefficients of Luxembourg have not been plotted in Fig. 20.6 because of Luxembourg’s outstanding values for GDP per capita.

  20. 20.

    We have not used an indicator for health because it is unclear whether the available indicators can be regarded as “objective”. All models included gender, age, age-squared, employment status, income and education as control variables. for the effect of “contacts with friends and neighbours” we also included marital status as a control variable.

  21. 21.

    Coefficients of Luxembourg have not been plotted in Fig. 20.7 because of Luxembourg’s outstanding values for GDP per capita.

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Acknowledgments

We like to thank our colleagues of the research unit “Inequality and Social Integration” at the WZB, and especially Reinhart Pollak, for invaluable discussions and careful reading.

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Correspondence to Petra Böhnke .

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Böhnke, P., Kohler, U. (2010). Well-Being and Inequality. In: Immerfall, S., Therborn, G. (eds) Handbook of European Societies. Springer, New York, NY. https://doi.org/10.1007/978-0-387-88199-7_20

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