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Happiness and Sociability in a Nonrecursive Model: The US and Taiwan Compared

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A Life Devoted to Quality of Life

Part of the book series: Social Indicators Research Series ((SINS,volume 60))

Abstract

Researchers have conventionally surveyed an individual’s personal relationships and their effect on subjective well-being, but the hypothesis that happiness accelerates interpersonal relations has received insufficient attention. An individual’s sociability and happiness are expected to show a reciprocal relationship. This study offers a contribution to studies of well-being by empirically evaluating this mutual influence with a cross-sectional nonrecursive modeling. The data are drawn from recent large scale surveys provided by the General Social Survey in the US and the Taiwan Social Change Survey in Taiwan. The results from the structural equation modeling suggest that in the US, sociability indeed leads to increased happiness. It is more often that happiness leads to sociability in both cultures.

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Notes

  1. 1.

    There are also notable research efforts that explore social capital and life satisfaction at an aggregate level. Bjornskov (2003, 2006) documented that social capital is a multifaceted phenomenon at the country level, suchthat social norms, social trust and associational activities can constitute distinct features of society, with trust being closely correlated with avowed satisfaction with life across more than 40 countries. However, recent studies using a larger size of country samples show that aggregated generalized trust has a decreased influence (Ram 2010). Recker (2013) provides interesting findings on the association between bridging (i.e., between group) social capital and assessment of quality life, both measured at the community level on the basis of small Iowa communities in the US. Since this study is concerned with micro-level association, I will only alert the readers to the relevant literatures.

  2. 2.

    Not all respondents in each survey were solicited to provide information on social activities and subjective well-being variables. In average, each survey provides about 500 subjects for pooling. As time lags were short and the differences between surveys were small, there is no need to apply specific techniques such as multilevel modeling for estimation.

  3. 3.

    Other possibilities were experimented with but did not improve our estimation. For instance, a model with health serving as an instrument for sociability failed to converge, perhaps because it has a lower correlation with three original sociability variables (no higher than .10 for a social evening with relatives or neighbors for the pooled data (2002–2012); its correlation coefficient with a social evening with friends is slightly higher (.14).

  4. 4.

    The models also meet the requirement of identification by satisfying both order and rank conditions. Discussion of these technical issues is beyond the scope of this paper. See Kline (2004) and Paxton et al. (2011).

  5. 5.

    The response categories for both happiness and life satisfaction differ slightly as the survey of 2005 used a four-point scale, while the 2010 survey used a five-point scale. The outcome appeared much the same, as only a small group of respondents (less than 3 %) placed themselves at the mid-point (see Appendix Table A.16.2).

  6. 6.

    The health variable is a measure of the extent to which any discomforts or injuries affected the respondent’s daily activities in the past 2 weeks. It is somewhat restrictive. I substituted another measure of ‘perceived level of health’ and obtained similar findings.

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Correspondence to Ming-Chang Tsai .

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Appendix

Appendix

Table A.16.1 Summary statistics for the US samples
Table A.16.2 Summary statistics for the Taiwan samples

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Tsai, MC. (2016). Happiness and Sociability in a Nonrecursive Model: The US and Taiwan Compared. In: Maggino, F. (eds) A Life Devoted to Quality of Life. Social Indicators Research Series, vol 60. Springer, Cham. https://doi.org/10.1007/978-3-319-20568-7_16

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