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Subjective Well-Being and Heterogeneous Contexts: A Cross-National Study Using Semi-Nonparametric Frontier Methods

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Abstract

This paper aims to contribute to the literature on subjective well-being by exploring the extent to which certain economic, social and institutional variables may affect the levels of well-being declared by individuals from different countries. To do this, we adopt a novel methodological approach based on frontier techniques in order to identify whether the maximum possible levels of well-being are achieved given the available resources. Specifically, the technique used to conduct the analysis is the stochastic nonparametric envelopment of data model, which combines the advantages of parametric methods and the flexibility of the nonparametric approach. This methodology has been adapted to deal with contextual variables by reformulating the original mathematical syntax of convex nonparametric least squares. Our empirical analysis is based on longitudinal information gathered from the World Values Survey for a set of 82 countries. Our results suggest that the most efficient countries in terms of well-being include mainly developing Latin American nations together with some European countries. Moreover, we find that several social indicators, such as the quality of government, the unemployment rate or different inequality indices, have a significant effect on the estimated efficiency measures.

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Notes

  1. The literature on well-being is based on individuals’ self-reported data about life satisfaction, happiness or subjective well-being. Although there are significant differences between these constructs, we will use the words happiness, satisfaction and (subjective) well-being indistinctly throughout the paper (see, for example, Ferrer-i-Carbonell 2005). In any case, the focus of our study is on life satisfaction.

  2. See Fried et al. (2008) for an overview of these methods.

  3. The work of Mizobuchi (2017b), who applies corrected convex nonparametric least squares to construct composite well-being indicators incorporating sustainability concerns, can also be classed in this group.

  4. Unlike other methods like DEA or FDH, this approach does not use data about all the units within the sample to build the frontier, but focusing on only some selected units with similar characteristics to the unit under evaluation.

  5. Kuosmanen and Johnson (2010) show that this problem is equivalent to the standard (output-oriented, variable returns to scale) DEA model when a sign constraint on residuals is incorporated to the formulation (\(\varepsilon_{i}^{CNLS - } \le 0 \forall i\)) and considering the problem subject to shape constraints (monotonicity and convexity).

  6. Kuosmanen et al. (2015) propose the use of the point estimator developed by Jondrow et al. (1982), but it is well-known that it is not a consistent estimator of \(u_{i}\) (Andor and Hesse 2014).

  7. The dataset also provides information about the level of happiness. However, we ruled out the use of this indicator because it is more likely to be influenced by emotions or feelings, whereas life satisfaction is a more cognitive construct (Nettle 2005; Kapteyn et al. 2015).

  8. The first-, second-, third-, fourth-, fifth- and sixth-wave data were collected from 1981 to 1984, from 1990 to 1994, from 1995 to 1998, from 1999 to 2004, from 2005 to 2009 and from 2010 to 2014, respectively.

  9. The WVS dataset also provides information about incomes, health status and educational level. However, these measures are based on the relative position of individuals with respect to people from the same country, and are thus considered as not providing an appropriate measure for a cross-country study.

  10. This variable has also been used in Abdallah et al. (2008) and Helliwell and Huang (2008).

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Acknowledgements

The authors would like to express their gratitude to the Spanish Ministry for Economy and Competitiveness for supporting this research through Grant ECO2017-83,759-P. Cristina Polo and Jose M. Cordero would also like to acknowledge the support and funds provided by the Extremadura Government (Grants GR18106 and IB16171).

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Authors and Affiliations

  1. Department of Economics, Universidad de Extremadura, 06006, Badajoz, Spain

    Jose Manuel Cordero & Cristina Polo

  2. Department of Economics, Universidad Autónoma de Madrid, 528049, Madrid, Spain

    Javier Salinas-Jiménez

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  1. Jose Manuel Cordero
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Appendix

Appendix

See Table 6 and Figs. 2, 3.

Table 6 Countries included in the empirical study by continent
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Cordero, J.M., Polo, C. & Salinas-Jiménez, J. Subjective Well-Being and Heterogeneous Contexts: A Cross-National Study Using Semi-Nonparametric Frontier Methods. J Happiness Stud 22, 867–886 (2021). https://doi.org/10.1007/s10902-020-00255-3

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