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Exploring Multidimensional Well-Being in Switzerland: Comparing Three Synthesizing Approaches

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Abstract

Well-being is increasingly conceptualized and measured from a multidimensional perspective in order to provide policy makers and the general public with the necessary tools for monitoring social change. Synthetic measures of multidimensional concepts such as well-being are, therefore, needed. This paper provides a systematic comparison of three methodological approaches applicable in a top-down perspective to construct a synthetic multidimensional measure of well-being using the same theoretical framework and the same data. The three methodologies used are the confirmatory factor analysis, the Alkire and Foster counting approach and the posetic approach. The first two methodologies belong to the family of composite indicators, the most common way to synthetize multidimensional information. The third was developed in order to deal with the construction of composite indicators’ two major issues, namely weighting and aggregating. The main contribution of this paper is methodological; it aims at discussing the advantages and drawbacks of the three methodologies, and at identifying their similarities and specificities.

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Fig. 1
Fig. 2

Source: Swiss Household Panel 2013

Fig. 3

Source: Swiss Household Panel 2013

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Notes

  1. We have not explicitly mentioned the other steps between item selection and weighting recommended by the OECD (2008), namely, imputation of missing data, multivariate analyses, and normalization, for the following reasons: Firstly, although the imputation of missing data is a major issue when creating indicators, it concerns all methods used here equally. Secondly, we conducted multivariate analyses as these are a central step in exploring the data; these analyses, however, are not shown here since we are following a top-down approach, where no item selection is made. Thirdly, the normalization step refers in particular to quantitative data, notably for rescaling data into a single metric or handling non-normal distribution and outliers—issues that do not concern ordinal data.

  2. The subdimensions of the other four core areas are: cultural diversity: (1) ethnic and migration-related aspects of diversity, (2) linguistic diversity, (3) religious diversity, (4) diversity in cultural consumption, cultural practices, leisure and sports activities; social integration: (1) integration and disintegration in the sphere of the couple and family life, (2) social contacts outside the family and the household (including intra- and intergenerational contacts), (3) health and healthcare, (4) social security and social policies, (5) social integration through volunteering, (6) deviant behavior (e.g., crime); political shaping: (1) political opinions, political concerns and political trust, (2) political activities, political participation and political mobilization, (3) relationships between political elites and the population, (4) relationships between national government and the population; environment: (1) Use of, and burden on, environmental resources, (2) perception of environmental problems, (3) environmental (ecological) behavior, (4) environmental policies.

  3. Achievement can be considered as the possession of goods, accessibility to goods and services, and life satisfaction.

  4. Objects are therefore called partially ordered.

  5. Similar lines are used with the Alkire and Foster cutoff method.

  6. Achievement poset, which includes all profiles.

  7. This study has been realized using the data collected by the Swiss Household Panel (SHP), which is based at the Swiss Centre of Expertise in the Social Sciences FORS. The project is financed by the Swiss National Science Foundation.

  8. The individual survey was administrated to SHPIII’s participants only from 2014 onwards.

  9. As the purpose of synthetic measures is to monitor well-being over time, we only used the indicators and data available in all SHP waves for operationalizing the theoretical framework.

  10. We chose one indicator per dimension as they were highly correlated. This follows the principle of parsimony suggested by the OECD (2008). Since the different indicators by dimension are expected to operationalize the same construct, they are somewhat interchangeable. We selected two models out of the 72 possible models corresponding to our theoretical framework with one indicator per dimension.

  11. The variables in the first model correspond to the third AF model, and the second model is one of the 71 other possible models.

  12. Descriptive statistics of the 12 variables included in the analyses can be found in Appendix 4.

  13. Expect the correlation with the variable “arrears of payment” to be at 0.38.

  14. Since correlations between intensity, severity, and depth ranged between 0.90 and 0.98 within the models, we decided to present only intensity. Between models with different weights, the three measures also correlated highly. This was mostly due to the fact that weights only impact the deprived people who represent only a small percentage.

  15. The result was controlled for age, in order to ensure that the difference is not due to old people in senior positions and young people in junior positions.

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Acknowledgments

The authors wish to thank Nicole Egli Anthonioz and Stéphanie Baggio for their valuable comments and their support, Gaël Curty and Rachel Matthey for the English proofreading, and the financial support of Faculty of Arts and Humanities of University of Neuchâtel for the English revision.

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Authors and Affiliations

  1. Center for the Understanding of Social Processes, University of Neuchâtel, A. L. Breguet 1, 2000, Neuchâtel, Switzerland

    Katia Iglesias

  2. Department of Sociology, University of Neuchâtel, Fbg de l’Hôpital 27, 2000, Neuchâtel, Switzerland

    Christian Suter

  3. Department of Sociology, Center for the Understanding of Social Processes, University of Neuchâtel, A. L. Breguet 1, 2000, Neuchâtel, Switzerland

    Tugce Beycan

  4. Institute for Social and Economic Change (ISEC), Nagarabhavi P.O., Bangalore, 560072, India

    B. P. Vani

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  1. Katia Iglesias
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Correspondence to Katia Iglesias.

Appendices

Appendix 1: Properties Satisfied by the Multidimensional Deprivation Measure (Mα)

Property

Explanation

Measures satisfying property

Decomposability

x and y be two data matrices (x, y) be the matrix obtained by merging the two; and w is the weight. Then M(x,y;z) = w*M(x;z) + (1 − w)*M(y;z) i.e., overall deprivation measure is weighted average of subgroup deprivation measure

Mα and H

Replication invariance

If x is obtained from y by a replication then M(x;z) = M(y;z)

Mα and H

Symmetry

let x be obtained from y by a permutation i.e., reshuffling vector of achievement across people then M(x;z) = M(y;z)

Mα and H

Poverty focus

If x is obtained from y by a simple increment among the non-poor, then M(x;z) = M(y;z)

Mα and H

Deprivation focus

If x is obtained from y by a simple increment among non-deprived then M(x;z) = M(y;z)

Mα and H

Weak monotanicity

Ix x is obtained from y by a simple increment then M(x;z) ≤ M(y;z)

Mα and H

Monotonicity

x is obtained from y by a deprived increment among the poor and satisfying weak monotonicity axiom then M(x;z) < M(y;z)

Mα for α > 0

Dimensional monotonicity

x is obtained from y by a dimensional increment among the poor then M(x;z) < M(y;z)

Mα

Normalisation

M achieves minimum value of zero and maximum value of 1

Mα and H

Weak transfer

if x is obtained from y by an averaging of achievements among the poor, then M(x;z) ≤ M(y,z)

Mα for α ≥ 1

Weak rearrangement

If x is obtained from y by association decreasing rearrangement among the poor then M(x;z) ≤ M(y;z)

Mα and H

  1. For details see Alkire and Foster (2009)

Appendix 2: Variables Operationalizing the Theoretical Framework

  • Dimension 1: Conciliation professional/private life composed by:

    • Interference work/private activities: How strongly does your work interfere with your private activities and family obligations, more than you would want this to be, if 0 means “not at all” and 10 “very strongly”?

    • Exhausted after work: How strongly are you exhausted after work to do things you would like to do, if 0 means “not at all” and 10 means “very strongly”?

    • Difficult to disconnect from work: How difficult do you find it to disconnect from work when the work day is over, if 0 means “not difficult at all” and 10 means “extremely difficult”?

  • Dimension 2: Financial situation of Household (HH) composed by:

    • Satisfaction with financial situation: Overall how satisfied are you with the financial situation of your household, if 0 means “not at all satisfied” and 10 “completely satisfied”?

    • Assessment of income and expenses: If you consider the total of your household’s income and expenses, would you say that currently your household can save money, your household spends what it earns, your household eats into its assets and savings, or your household gets into debts?

    • Arrears of payments: Last 12 months: Since (month, year) have you experienced problems which resulted in arrears in payments of your household bills?

    • Financial situation manageable: How do you manage on your household’s current income, 0 means “with great difficulty” and 10 “very easily”?

  • Dimension 3: Employment situation composed by:

    • Job security: Would you say that your job is very secure, quite secure, a bit insecure or very insecure?

    • Risk of unemployment: Next 12 months: personally unemployed in the next 12 months, if 0 means “no risk at all” and 10 “a real risk”?

    • Satisfaction with work conditions: On a scale from 0 “not at all satisfied” to 10 “completely satisfied” can you indicate your degree of satisfaction with work conditions?

  • Dimension 4: Educational and occupational position composed by:

    • Educat: Highest level of education achieved: (1) incomplete compulsory school, (2) compulsory school, elementary vocational training, (3) domestic science course, 1 year school of commerce, (4) general training school, (5) apprenticeship (CFC, EFZ), (6) full-time vocational school, (7) bachelor/maturity, (8) vocational high school with master certificate, federal certificate, (9) technical or vocational school, (10) vocational high school ETS, HTL etc., and (11) university, academic high school, HEP, PH, HES, FH.

    • CSP: Swiss socio-professional category of main job: (1) top management, (2) liberal professions, (3) other self-employed, (4) academic professions and senior management, (5) intermediate professions, (6) qualified non-manual professions, (7) qualified manual professions, and (8) unqualified non-manual and manual workers

Appendix 3: Construction of Indicators for the Construct Validity

As a measure of standard of living, we used the Proportional Deprivation Index (PDI) of Halleröd (1995). It is based on a list of goods and services (having a color TV, a car, a washing machine, a dishwasher and a computer, being able to eat at a restaurant at least once a month, to take a week’s holiday away from home, being able to save money in a private pension fund, and being able to invite friends to one’s home at least once a month). Each item is weighted by the percentage of people considering the item as absolutely necessary for a decent living in Switzerland. The PDI corresponds to the sum of the weighted items multiplied by one if the household cannot afford the item. Then, the PDI was standardized, and three groups were defined: no restriction (PDI = 0), low restriction (PDI > 0 but lower than 15, corresponding to the mean score of the deprived people) and high restriction (PDI equal or >15).

As a measure of health, we used a question the following question: “Please tell me to what extent, generally, your health is an impediment in your everyday activities (in your housework, your work or leisure activities), 0 means “not at all” and 10 “a great deal”. No health as impediment corresponds to 0, low impediment corresponds to values between 1 and 4, and great impediment values between 5 and 10.

And finally as a measure of social support, we aggregated (mean) 8 questions: practical and emotional support of 4 kind of social supports (friends, neighbors, partner (if in couple) and colleagues). 0 means «not at all» to 10 «completely». We defined three groups of social support: low social support (values lower than 5, medium social support (values between 5 à 7.5) and strong social support (values >7.5).

Appendix 4: Descriptive Statistics

Variables

Median [25 %; 75 %] or  %

Deprived* (%)

Interference work/private activities

4 [2; 6]

29.1

Exhausted after work

5 [3; 6]

35.3

Difficult to disconnect from work

3 [2; 5]

20.4

Job security

Quite secure [very secure; quite secure]

9.3

Risk of unemployment

1 [0; 3]

17.3

Satisfaction with work conditions

8 [7; 9]

8.9

Satisfaction with financial situation

8 [7; 9]

14.5

Assessment of income and expenses

Save money [save money; spends what it earns]

5.7

Arrears of payments (yes)

9.2 %

9.2

Financial situation manageable

8 [7; 9]

16.5

Educational level

Bachelor/maturity [apprenticeship (CFC, EFZ); vocational high school ETS, HTL]

11.4

Occupational status

intermediate professions [academic professions and senior management; qualified non-manual professions]

8.0

  1. * Unidimensionally deprived based on the first threshold of AF and POSET approaches
  2. Source: Swiss Household Panel 2013

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Iglesias, K., Suter, C., Beycan, T. et al. Exploring Multidimensional Well-Being in Switzerland: Comparing Three Synthesizing Approaches. Soc Indic Res 134, 847–875 (2017). https://doi.org/10.1007/s11205-016-1452-9

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