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Basic Needs and Wealth as Independent Determinants of Happiness: An Illustration from Thailand

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Abstract

Thailand has been a global economic success story, transforming from one of the poorest countries in Southeast Asia in the 1960s, to a modern and dynamic nation, and all within the lifetime of the current generation. However, growth has been accompanied by marked increases in economic inequality both at the regional and individual levels. In this context studying how relatively poor people appraise their situation (‘subjective wellbeing’) and how this relates to traditional ‘objective’ measures of wellbeing such as wealth and basic needs is particularly relevant. This paper investigates the relationship between basic needs as defined by the Theory of Human needs (THN, Doyal and Gough 1991), material wealth and happiness. Specifically, we intend to answer the following research question: Are wealth and basic needs indicators always interchangeable when analyzing happiness determinants in low income settings? The paper focuses on seven communities in the South and North-east of Thailand with contrasting levels of access to markets and services. It challenges the common assumption that at low economic levels, wealth or income matter for people’s happiness because they increase satisfaction of basic needs, arguing instead that wealth might contribute to happiness for personal or symbolic reasons, which are not related to the use of goods as basic needs satisfiers. Thus, it suggests that indicators of wealth and basic needs should not be used interchangeably when studying happiness determinants in low income settings.

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Notes

  1. See Clark (2002: 81–92) for a discussion of several alternative conceptions of the good.

  2. Refer to Frey and Stutzer (2002), Hirata (2001) and Guillen-Royo (2007) for a survey of the literature on income and SWB.

  3. Refer to http://www.welldev.org.uk/research/methods-toobox/ranq-toolbox.htm.

  4. A discussion about the validity of the scales used in happiness studies can be found in Cummins (2003).

  5. An alternative asset index was computed using factor analysis and principal component analysis. Similar results were obtained when these asset indexes were used as determinants of happiness.

  6. Food shortages are especially common in Ban Dong where nearly 60% of the households reported experiencing food shortages during the year before the interview, possibly due to its relative remoteness and the poor quality of the agricultural land.

  7. A one-way ANOVA (F = 19.876 and p < 0.001) shows that there exist differences within the sites and a post-hoc test (Scheffe) shows that Ban Dong (p < 0.001) and Ban Chai Khao (p < 0.05) are respectively the poorest and the richest sites although the latter is not significantly richer than Ban Tha and Ban Tung Nam.

  8. A one-way ANOVA indicates that communities differ in relation to basic needs deprivation levels (F = 13.392 and p < 0.001) and that households in Nai Muang and Ban Chai Khao are significantly better off than people in Ban Thung Nam, Ban Laow and Ban Dong.

  9. Some caution is required when carrying out an empirical analysis of subjective wellbeing using regression analysis due to the small percentage of variation in SWB measures explained by socio-economic-demographic variables (Graham 2005) and the issue of causation (Diener and Biswas-Diener 2002). Acknowledging the relevance of the previous debates, we follow the tradition of happiness economics considering that socio-economic variables affect utility which is here approximated by happiness.

  10. In addition to the ordered probit model, a probit model of the selected regression was also estimated. The results were quite similar using both models.

  11. Table 7 in the Appendix contains the description and descriptive statistics of selected variables for the full sample of 745 households.

  12. Age is significant at the 0.05 level and type of job at the 0.10.

  13. Many happiness studies find that the relationship between age and happiness has a U shape implying that there is a turning point at which happiness starts to increase with age (Frey and Stutzer 2002: 54). Although this was also the case in the previous study by Guillen and Velazco (Ibid.) focussing on the rural communities, it was not found when the urban population was added to the sample.

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Acknowledgments

The data analysed in this paper was collected by the UK Economic and Social Research Council research group on Wellbeing in Developing Countries (WeD, www.well-dev.org.uk) as part of its exploration of the social and cultural construction of wellbeing in Thailand. The authors would like to thank our collaborators in Prince of Songkhla and Khon Kaen Universities. The support of the Economic and Social Research Council is gratefully acknowledged.

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Correspondence to Jackeline Velazco.

Appendix

Appendix

See Tables 6 and 7.

Table 6 Socio-demographic characteristics: Households in Thailand
Table 7 Descriptives of the variables included in the regression analysis

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Guillen-Royo, M., Velazco, J. & Camfield, L. Basic Needs and Wealth as Independent Determinants of Happiness: An Illustration from Thailand. Soc Indic Res 110, 517–536 (2013). https://doi.org/10.1007/s11205-011-9941-3

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