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Trading Up the Happiness Ladder

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Abstract

How globalization affects subjective happiness is highly disputed. Several studies use an index that amalgamates globalization’s different dimensions into a single variable. Unlike previous studies and in order to better illuminate its facets, we adopt a disaggregated perspective on trade (policy) data. Distinguishing actual trade flows and the option value of trade, we find the former to slightly depress happiness, the latter to significantly promote happiness. Segmentation of WVS-data shows that the positive connotation is concentrated in low-income countries still in the process of climbing the income ladder, thus backing the notion of a shift in values.

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Notes

  1. While there is a wide set of definitions as to what makes for “quality of life” (see Land et al. 2012), variants of the more objective approach have been, inter alia, proposed by Dasgupta and Weale (1992) and are documented in the annual reports of the United Nations Development Programme (see the 2011 report for instance)— though especially with an eye on how people fare in developing countries.

  2. Differences in the evaluation of globalization may also be due to the economists and the affected individuals using different metrics when rating outcomes. Caplan (2002, 2008) provides ample, though mostly non-trade related, evidence on differences and their importance when it comes to politically selling and implementing policy measures, as does Kemp (2007) with a particular focus on trade.

  3. Although the choice of variables and their weight in the second group surely has a subjective component.

  4. However, despite their fundamental differences, objective measures are sometimes used to cross check the validity of subjective data. One example are suicide studies (see, for instance, Daly and Wilson 2009). Oswald and Wu (2010, 2011) also find the two being related in that they establish a negative correlation, suggesting that income partly compensates for displeasures. This is different though from Kahneman’s objective happiness, which actually constitutes a third approach that uses inter alia neuroscience in order to somehow “objectify” subjective data.

  5. See Sect. 3 for details on the data.

  6. For a detailed discussion of these matters see, for instance, Diener et al. (2012).

  7. See, inter alia, Bradburn (1969), Diener (1994), Diener et al. (1999), or, for a short survey, Bruni and Porta (2005). Helliwell and Barrington-Leigh (2010) provide a systematization and also discuss the validity of results in the light of differences across individuals, communities, provinces (with special reference to Canada), and countries. On matters of definition see also Veenhoven (2012), who, though taking a slightly different tack, distinguishes as well between a cognitive and an affective part. Contributions in Land et al. (2012) illuminate the various dimensions and indicators known to bear a relationship with the quality of life, including various subjective measures.

  8. Much of the economics literature is not precise in this respect. Sometimes, these terms are even used interchangeably (see McGillivray and Clarke 2006: 3, or quite explicitly, Easterlin 2005a: 29).

  9. Generally speaking, surveys of public opinion have their own difficulties. For a discussion with particular reference to surveys on trade opinion see Hiscox (2006).

  10. Some studies, as for example Baker (2005) or Broda and Weinstein (2006), lean towards the subjective component in that they try to explore the role of tastes and variety or availability of goods on welfare and attitudes towards trade. Yet, tastes may vary too much across countries to deliver meaningful results as to the reasons for dissent.

  11. Scheve and Slaughter also provide a comprehensive survey of the previous empirical literature on the political economy of trade, mostly with a focus on a single country and in search for Stolper-Samuelson effects versus specific factors as explanans.

  12. For a similar approach (using the 1995 and the 2003 ISSP data set respectively) see O’Rourke and Sinnott (2001) and, with a focus on intra-industry trade liberalization, Beaulieu et al. (2011). Drawing on cross-country survey data as supplied by the 1995 ISSP, O’Rourke (2006), as well, finds evidence in support of the income hypothesis in that higher skill level is related to less protectionist attitudes (as measured on a scale from 1 to 5). Margalit (2011) also sees a strong link between voting behavior and labor market implications of globalization. Sirgy et al. (2007) consider quite generally speaking labor market implications in particular to affect various dimensions of well-being (economic, consumer, social, health, all associated with the “quality of life”). Based thereupon, they conclude that (temporary) trade restrictions might be a suitable means to dampen the negative effects on the labor market side and thus on well-being. However, they discuss the impacts trade might have on the economy and the individual in purely qualitative terms. Our quantitative analysis in Sect. 3, by contrast, suggests that trade restrictions may well contribute to a worsening of (subjective) well-being.

  13. Based on their findings they conclude that “Unfortunately, the explanatory value of these models has been quite limited to date, and even simple demographics often explain more about trade preferences than variables linked to either model.” (p. 429)

  14. Kleinberg and Fordham (2010) illuminate the nexus in the other direction. They explore how trade and its impacts shapes attitudes towards foreign policy in general. Notably, following Milner and Tingley (2011), the embedded-liberalism hypothesis according to which per-capita spending on welfare influences trade opinion does not stand up to the facts.

  15. The evidence on macro-variables affecting trade opinion also eclipses shifts in reference groups as possible determinants of individual happiness when evaluating one’s own happiness in the process of globalization, as, for instance, suggested by Becchetti et al. (2010) and Van Praag (2011).

  16. On the paradox controversy see Di Tella et al. (2003), Gul and Pesendorfer (2007), Stevenson and Wolfers (2008), Sacks et al. (2010), or the surveys by Frey and Stutzer (2002), or Clark et al. (2008). On the relationship between income and the various components of subjective well-being (and thus in disaggregated perspective as compared to Easterlin) see Diener et al. (2010). Accordingly, the link differs when seen across components.

  17. Although obviously using the life satisfaction data of the WVS when examining the impact of globalization, they sometimes refer to life satisfaction (for instance p. 124), sometimes to the broader concept of well-being (for instance, pp. 125, 131).

  18. The “KOF-index” is developed and maintained by the KOF Swiss Economic Institute at the Swiss Federal Institute of Technology Zurich (with“KOF” being the acronym for “Konjunkturforschungsinstitut”). See Dreher et al. (2008) for details on the index and with the respective data available for download at http://globalization.kof.ethz.ch/ (last accessed June 8, 2012).

  19. Unlike those studies that concentrate on macro-indicators, Tsai (2007) and Tsai et al. (2011) adopt a complete micro perspective in that they try to track individual sociological impacts of globalization and their role for work satisfaction, life achievements and subjective happiness within the Asian populations with a particular focus on illuminating the quality of life.

  20. The negative effect prevails despite controlling for income effects which may at least partially outweigh any negative impact of increased variability. The interaction of trade with the personal income position is significantly positive at the 1 percent level though, suggesting that negative concerns about trade are mainly clustered around the low-income earners. A similar pattern emerges with respect to skill-level. Both results thus indicate that in happiness studies as well, there is some indication of Stolper-Samuelson at work. Xin and Smyth (2010), in examining how openness influences life satisfaction as ranked from 1 (“very unsatisfied”) to 5 (“very satisfied”) in 30 Chinese cities and a survey especially carried out for these purposes, see a negative relationship. However, export and import flows are not only difficult to trail but are less meaningful in a within-country nexus.

  21. See Beghin (2008) for a survey. According to recent estimates by Kee et al. (2009) non-tariff barriers add approx. 87 percent to the restrictiveness imposed by tariffs and in about half of their set of 78 countries their restrictiveness exceeds the one caused by tariffs. The Fraser Institute (http://www.fraserinstitute.org/programs-initiatives/economic-freedom.aspx;as of June 16, 2012) also publishes data on trade freedom as part of their economic-freedom index, however, by tracking a more narrow set of policy instruments.

  22. Veenhoven (2000), for instance, focuses on happiness defined as life satisfaction and distinguishes between political, economic and private freedom. Accordingly, life satisfaction is positively correlated with economic freedom in poor countries. The other dimensions of freedom, however, show no positive relation. In rich countries, the opposite seems to hold. However, he draws on data from the Fraser Institute that uses a narrow definition of international restrictiveness. Inglehart et al. (2008), by contrast, consider a composite measure of subjective well-being (a weighted average of life satisfaction and subjective happiness as reported by the WVS) as well as each component separately. They find that “sense of free choice” affects all of the indicators positively, but in cross-section perspective not significantly. Free choice seems to be largely mediated by other variables such as GDP per capita, level of democracy, tolerance of outgroups. When tracking changes in subjective well-being, though, effects turn significant with changes in the “sense of free choice” becoming an important factor in explaining changes in subjective well-being. Verme (2009), however, finds that freedom of choice even overshadows many other commonly conjectured variables in influencing life satisfaction, in particular, when considered jointly with control of one’s own life. Gropper et al. (2011), by using Fraser-data on economic freedom, also find a positive impact on life satisfaction (supplemented by indicators of objective well-being as for instance health). However, they employ a quite narrow set of controls so that it is not clear what the freedom variable actually picks up.

  23. As suggested by Davidson et al. (2012), Frijters and Geishecker (2008) as well as Geishecker (2010), perceived job insecurity and the fear of job loss might well be exacerbated with trade.

  24. For a discussion on the many ways in which globalization may interact with systems of social values see Whalley (2008).

  25. The original data sets are freely available at (1) the website of the WVS (http://www.worldvaluessurvey.org), (2) the PWT website (http://pwt.econ.upenn.edu/index.html), (3) the website of the Heritage Foundation (http://www.heritage.org/index/), as well as (4) the statistics section of the OECD webpage (http://www.oecd.org).

  26. How we treat these differently scaled variables in the estimation is described in greater detail in Sect. 3.1.

  27. We use GDP per capita in current prices converted at PPP in US Dollar. Unemployment information is available for 36 countries: the 34 OECD member countries plus Indonesia and Brasil.

  28. See also Helliwell (2003) on the general importance of the linkage between the individual and the societal level and, with particular reference to globalization (though retaining largely a Canadian focus), Helliwell (2002).

  29. The World Bank country classification, which draws on the World Bank Atlas method (http://data.worldbank.com/about/country-classifications), provides a suggestion for distinguishing countries with different income levels in empirical analyses: 1,005 US-$ GDP per capita or less for low-income economies, 1,006 US-$–12,275 US-$ for middle-income economies, and 12,276 US-$ and more for high-income economies. In this contribution, we are not able to apply this three-type classification. Including the information of the countries’ unemployment rate constrains our data to OECD countries (that are middle or high-income economies) only. The happiness literature, see for example Layard (2003), suggest a threshold level of 15,000 US-$ GDP per capita. Therefore, in line with the literature, we apply a two-type classification distinguishing economies at the income level of 15,000 US-$.

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  1. Department of Economics, Helmut Schmidt University—University FAF Hamburg, Holstenhofweg 85, 22043, Hamburg, Germany

    Barbara Dluhosch & Daniel Horgos

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Dluhosch, B., Horgos, D. Trading Up the Happiness Ladder. Soc Indic Res 113, 973–990 (2013). https://doi.org/10.1007/s11205-012-0122-9

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