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Pro-environmental Norms, Green Lifestyles, and Subjective Well-Being: Panel Evidence from the UK

Abstract

Previous literature has found a significantly positive relationship between green lifestyles and subjective well-being. These well-being gains could either come from individuals’ conformity with a general social greenness norm or from adhering to a group-specific norm that enhances individuals’ sense of identity. We aim to provide a better understanding about those two channels. We construct measures of the regional prevalence and diversity of green self-image as indicators of the strength of a hypothetical green social norm. Using panel data from the UK, we find the positive relationship between individuals’ green self-image and life satisfaction to be unrelated to the prevalence of greenness attitudes, whereas the more polarized green/non-green attitudes are, the more well-being is gained from being green and the less well-being is lost from being non-green. This evidence is consistent with the idea that the relationship between a green lifestyle and subjective well-being relies (in addition to conformity with an internalized moral norm) on group identity more than on conformity with a society-wide green norm.

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Notes

  1. 1.

    As a matter of convenience, we use the term “diversity” in a wider sense, denoting a lack of unanimity of the relevant self-perceptions (green vs. non-green). Diversity in this wider sense comprises both fractionalization and polarization, though polarization is to be distinguished from diversity in the narrow sense (Esteban and Ray 1994).

  2. 2.

    A broad definition would hold that norms are shared beliefs, which act as vague guides to behavior in actual situations (Schwartz 1977). Norms can be differentiated along several dimensions. We can distinguish between descriptive and injunctive norms, where descriptive norms inform about “what most people do (what is)” and injunctive norms relate to “what most people approve/disapprove of doing (what ought to be)” (Cialdini et al. 1990; Kallgren et al. 2000; Cialdini and Goldstein 2004). “What most people do”, for instance taking a shower rather than a bath, has no value significance per se. Yet, by noting the environmental implications, one or the other alternative may become an injunctive norm irrespective of its empirical prevalence.

  3. 3.

    Prevalence, fractionalization and polarization of greenness may correlate with environmental quality (through the strictness of environmental policy), prevalence positively and fractionalization and polarization negatively so (Welsch and Kühling 2018). It can be expected, however, that this latter concern applies more to the national than to the regional level, as environmental policy is typically a matter of national rather than regional legislation.

  4. 4.

    Technically, the coefficient measures the LS-GSI relationship when the prevalence, fractionalization and polarization, respectively, take the value of zero. If zero is outside the empirically observed range (which is usually the case), the coefficient estimate may be negative. The LS-GSI relationship evaluated at the minimum of prevalence, fractionalization and polarization may nevertheless be positive (see Sect. 4.1).

  5. 5.

    While the variable would strictly speaking necessitate the estimation of an ordered response model, consensus has emerged in the literature that it can be usefully treated as cardinal and that the gains from using a fixed effects OLS approach, i.e. being able to control for individual-specific factors such as personality traits or response styles, outweigh the drawbacks from assuming life satisfaction to be cardinal (Ferrer-i-Carbonell and Frijters 2004).

  6. 6.

    To check the robustness of our results with regard to index construction, we also use a mean behavior index (PEBmean), where we divide the sum of intensities by the sum of applicable behaviors (mean PEBmean 1.94, sd 0.63). Both indices are strongly correlated (\(r=.92^{***}\)) and results do not change much with index choice, so that we focus on the sum index in the following.

  7. 7.

    Cross-national analyses may benefit from controlling for environmental quality.

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Correspondence to Martin Binder.

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We appreciate the comments of two anonymous referees. We would further like to thank Leonhard Lades, Jorge Marco Renau, as well as seminar participants at the Cournot Seminar (BETA), University of Strasbourg, the EPA Workshop on Behavioral Science, Subjective Well-being, and the Environment (UCD Geary Institute for Public Policy), University College Dublin, and the ESEE, EAERE conferences for helpful comments. The UKHLS panel data set used in this publication were made available to us by the University of Essex, Institute for Social and Economic Research and NatCen Social Research, Understanding Society. Neither the original collectors of the data nor the Archive bears any responsibility for the analyses or interpretations presented here. Remaining errors are ours alone.

Appendix

Appendix

Measures of diversity have been axiomatically characterized by Esteban and Ray (1994) and Montalvo and Reynal-Querol (2005, (2008). Both our measure of fractionalization and the measure of polarization can be derived via the following formalization,

$$\begin{aligned} P(k,\alpha )=k\sum _{i=1}^{N}\sum _{j=1}^{N}\pi _i^{1+\alpha } \pi _j | y_i-y_j | \end{aligned}$$
(2)

where \(\pi _{i,j}\) are the proportions of individuals belonging to groups i, j summed over N different groups (incomes, attitudes, organizations) and multiplied by a distance function \(\delta _{i,j}= |y_i-y_j |\) between groups i, j. In the following, we assuming that the Euclidean distance between groups i and j has a defined meaning (otherwise, redefining the distance function to a binary relation of being the same group or not yields a different type of measures not discussed here). The polarization parameter \(\alpha\) defines whether Eq. (2) gives rise to measures of fractionalization (\(\alpha = 0\)) or polarization (\(\alpha = 1\)). The scale parameter k rescales the function values but has no deeper meaning. For \(\alpha = 0\), we arrive at Rao’s (1982) entropy measure

$$\begin{aligned} Rao's\ Q=\sum _{i=1}^{N}\sum _{j=1}^{N}\pi _i \pi _j | y_i-y_j | \end{aligned}$$
(3)

which is identical to the well-known Gini index apart from a different normalization applied to the latter (dividing Eq. (3) by 2 times the mean distance of y transforms Rao’s entropy into the Gini coefficient). Intuitively, Rao’s entropy (Eq. 3) measures the probability of two different individuals belonging to different groups, weighted by the (normalized) distance between groups. The measure is equal to zero when all individuals belong to one group, i.e. no diversity. It increases in value with more groups and bigger distances (it may not be maximal at the largest number of possible groups due to the distance weighting, and hence has been called an index of “weak diversity”, Ricotta 2005). When setting \(\alpha = 1\), we arrive at Esteban and Ray’s (1994) measure of polarization, where the size of the groups plays a role in addition to the number of groups and their distance from each other:

$$\begin{aligned} ER=\sum _{i=1}^{N}\sum _{j=1}^{N}\pi _i^2 \pi _j | y_i-y_j | \end{aligned}$$
(4)

Intuitively, we can see the correspondence to Rao’s measure by noting the additional multiplicative factor of \(\pi _i\) in Eq.  (4) as compared to Eq. (3), which means that we are looking at the probability of two individuals belonging to different groups, weighted by distance and by group size. A polarization measure increases thus also in terms of group size and more polarized setups have, for instance, two big groups opposing each other alongside some smaller groups (if \(N > 2\), otherwise Eq. (4) collapses into Eq. (3), see Montalvo and Reynal-Querol 2008, p. 1840).

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Binder, M., Blankenberg, AK. & Welsch, H. Pro-environmental Norms, Green Lifestyles, and Subjective Well-Being: Panel Evidence from the UK. Soc Indic Res 152, 1029–1060 (2020). https://doi.org/10.1007/s11205-020-02426-4

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Keywords

  • Subjective well-being
  • Norms
  • Green behavior
  • Green self-image
  • Diversity
  • Fractionalization
  • Polarization

JEL Classification

  • I31
  • Q51
  • Q58
  • Z13