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Subjective Well-Being in The European Union During the 90s

  • Bernhard Christoph
  • Heinz-Herbert Noll
Part of the Social Indicators Research Series book series (SINS, volume 18)

Abstract

Welfare is not only a matter of favourable objective conditions — as for example comfortable housing, a healthy environment, good working conditions, educational opportunities and access to public services — but also includes subjective feelings of well-being and appreciation of life: “The quality of life must be in the eye of the beholder” as Angus Campbell (1972) put it once. More recently, Robert E. Lane has emphasised the role of subjective experience as a constitutive element of life quality. “Quality of life is properly defined by the relation between two subjective or personbased elements and a set of objective circumstances. The subjective elements of a high quality of life comprise (1) a sense of wellbeing and (2) personal development, learning growth. [...] The objective element is conceived as quality of conditions representing opportunities for exploitation by the person living a life” (Lane, 1996: p. 259). Thus there is a consensus among the majority of quality of life researchers to base welfare measurement on both objective and subjective indicators, given the fact “that similar living conditions are evaluated quite differently, that people in bad conditions frequently are satisfied and privileged “persons may be very dissatisfied” (Zapf, 1984: p. 20, authors’ translation).

Keywords

Life Satisfaction Leisure Time Life Domain Income Quintile Social Indicator Research 
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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Notes

  1. 1.
    In 1996 the Eurobarometer 44.2_bis study, fielded in February, has been used. In 1999 the only data set available including general life satisfaction was fielded in October/November. Results covering these years should thus be interpreted cautiously, since seasonal effects might occur. In addition it should be mentioned that the 44.2_bis study is different from the rest of the surveys used, to the extent that it has a much larger sample size (overall it includes 65,178 respondents while the respective number for the other surveys is between 13,121 and 19,477). Detailed information on Eurobarometer surveys is available at the Central Archive for Empirical Social Research (ZA) in Cologne (http://www.gesis.org/en/data_service/eurobarometer/index.htm.)
  2. 2.
    Please note that the time between these two surveys is 18 months rather than a year, since the 1999 data were collected in October/November, while most of the other data (including those for 1998) have been collected in spring (compare the data description above for details). Thus assuming a continuous process, 1999 spring time data might have shown a somewhat lower incline.Google Scholar
  3. 3.
    On attempts to explain European differences in life satisfaction see for example Inglehart and Rabier (1986), Inglehart (1989), Veenhoven (1994), Noll (1997), Inglehart and Klingemann (2000).Google Scholar
  4. 4.
    In our analyses of Eurobarometer data we used the harmonised household income quartiles included in the datasets. We preferred this to the alternative, which would have been to calculate quintiles from a grouped income variable. Since this variable covered only 10 income groups we did not consider this an appropriate procedure. Please note that the Eurobarometer household income figures are not need adjusted.Google Scholar
  5. 5.
    Please note that during the weighting procedure the number of cases for the East German subsample is weighted down in order to put the number of cases in the right proportion to that of its West German counterpart (which is roughly 1:4). This might have an influence on the results of statistical significance testing. If unweighted analysis of the data is performed the t-test for this age difference in East Germany renders significant results.Google Scholar
  6. 6.
    Please note that the questions discussed here were not covered by the Nordic surveys used to supplement ECHP data in other parts of this volume. Therefore it was not possible to cover Sweden and Norway in the ECHP-based analyses in this chapter, since there are no data available for these countries in the ECHP waves 1 to 3.Google Scholar
  7. 7.
    For detailed results on life satisfaction and satisfaction with various life domains in West-and East-Germany based on the German Welfare Surveys see Habich et al. (1999) and the respective articles in Datenreport 1999 and Datenreport 2002: on general life satisfaction see Bulmahn (2000, 2002), an overview of satisfaction with life domains is given in Habich and Noll (2000) and in Christoph (2002), for differences concerning the labour market see Noll (2000), information on satisfaction with housing conditions can be found in Berger-Schmitt (2000a, b) and on satisfaction with amount of leisure time see Schöb (2000). A good documentation of differences regarding income-related measures is included in Hanesch et al. (2000).Google Scholar
  8. 8.
    Speaking of disposable income we refer to a need adjusted net household income. Household income is computed by summing incomes from all sources (such as e.g. work, social transfers etc.) and of all persons in the household. Need adjustments are made using the OECD modified scale, weighting the first adult in the household by 1, further persons aged 14 or older by 0.5 and children under 14 years of age by 0.3. All income quintiles have been calculated relative to the respective countries’ income distributions.Google Scholar
  9. 9.
    Data Source for GDP-figures: European Commission (2000b: p. 215).Google Scholar
  10. 10.
    The index for housing amenities has values from 0 to 5. One is added for each of the following features that is present in the dwelling: a separate kitchen; a bath or a shower; an indoor flushing toilet; hot running water; a place to sit outside. The item ‘heating or electric storage heaters’ was not included in the index since its importance varies greatly between northern and southern member countries. The index for problems with the accommodation has values from 0 to 7. It was coded in a manner that high values indicate a positive situation. Therefore one is added for each of the following problems that is not present: shortage of space; noise from neighbours or from outside; not enough light; lack of adequate heating facilities; leaky roof; damp walls, floors etc.; rot in window frames or floors.Google Scholar
  11. 11.
    Another question whether there is pollution by traffic or industry was also tested. Since it did not show a significant influence on housing satisfaction, the variable was not included in the model.Google Scholar
  12. 12.
    Results shown are the country coefficients of four OLS-Regression models. Countries were coded as dummy variables. If a set of dummy variables is used in regression analysis, it is necessary to drop one of them from the model so that it can be used as a reference category. We decided to use France, because the French values were in both cases closest to the European average (compare Figure 5). The first model includes no control variables. In the other models the groups of control variables discussed above are consecutively added to the model (thus that the fourth model includes all control variable discussed).Google Scholar
  13. 13.
    Parts of this paragraph have been published previously in German (Christoph, 2001).Google Scholar
  14. 14.
    The index for consumer-goods available to household members has values from 0 to 7. One is added for each of the following goods owned by the household: a car; a colour TV; a video recorder; a microwave oven; a dishwasher; a telephone; a second home. The index for the standard of living has values from 0 to 6. One is added to the index for each of the following items the household can afford: keep the home adequately warm; a week’s annual holiday away from home; replace wornout furniture; buy new, rather than second-hand clothes; eat fish, meat or chicken every second day; have friends or family for drink/dinner once a month. The index for financial problems has values from 0 to 4. One is added if during the preceding year the household was unable to pay any of the following: rent for the accommodation; mortgage payments; utility bills; installments or other loan repayments.Google Scholar

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Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Bernhard Christoph
    • 1
  • Heinz-Herbert Noll
    • 1
  1. 1.Centre for Survey Research and Methodology (ZUMA)MannheimGermany

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